Role of Chemolithoautotrophic Microorganisms Involved in Nitrogen and Sulfur Cycling in Coastal Marine Sediments

Role of chemolithoautotrophic microorganisms involved in nitrogen and sulfur cycling in coastal marine sediments

Yvonne Antonia Lipsewers THIS RESEARCH WAS FINANCIALLY SUPPORTED BY DARWIN CENTER FOR BIOGEOSCIENCES NIOZ – ROYAL NETHERLANDS INSTITUTE FOR SEA RESEARCH

ISBN: 978-90-6266-492-4 Cover photos: S. Rampen, L. Villanueva, M. van der Meer Printed by Ipskamp Printing, The Netherlands Role of chemolithoautotrophic microorganisms involved in nitrogen and sulfur cycling in coastal marine sediments

De rol van chemolithoautotrofe micro-organismen die deelnemen in de stikstof- en zwavelcyclus in mariene kustsedimenten (met een samenvatting in het Nederlands)

Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof.dr. G.J. van der Zwaan, ingevolge het besluit van het college voor promoties in het openbaar te verdedigen op dinsdag 5 december 2017 des ochtends te 10.30 uur

door Yvonne Antonia Lipsewers geboren op 18 juli 1977 te Salzkotten, Duitsland Promotor: Prof. dr. ir. J.S. Sinninghe Damsté Copromotor: Dr. L. Villanueva „Hinterher ist man immer schlauer…“

Für meine Familie

Table of contents

Chapter 1 – Introduction ...... 1

Chapter 2 – Seasonality and depth distribution of the abundance and activity of ammonia oxidizing microorganisms in marine coastal sediments (North Sea)...... 23

Chapter 3 – Lack of 13C-label incorporation suggests low turnover rates of thaumarchaeal intact polar tetraether lipids in sediments from the Iceland Shelf ...... 53

Chapter 4 – Abundance and diversity of denitrifying and anammox bacteria in seasonally hypoxic and sulfidic sediments of the saline Lake Grevelingen...... 79

Chapter 5 – Impact of seasonal hypoxia on activity and community structure of chemolithoautotrophic bacteria in a coastal sediment ...... 107

Chapter 6 – Potential recycling of thaumarchaeotal lipids by DPANN archaea in seasonally hypoxic surface marine sediments...... 147

Chapter 7 – Synthesis ...... 167

Summary...... 187

Samenvatting...... 191

References...... 195

Acknowledgements ...... 223

1. Introduction

Marine sediments are dynamic habitats shaped by interactions of biotic and abiotic processes including the redox reactions performed by microorganisms to gain energy for growth (Schrenk et al., 2010). The biogeochemical cycling of carbon-, nitrogen- and sulfur compounds in marine sediments is tightly coupled in space and time. Due to electron donor and acceptor availability, an overlap of the activity of metabolically diverse microorganisms involved in carbon-, nitrogen- and sulfur cycling occurs. Aerobic mineralization processes of organic matter reaching the sediment surface are mainly mediated by the metabolism of phototrophic and chemoorganoheterotrophic microorganisms.

These processes result in the consumption of oxygen (O2) within the first few millimeters/centimeters of marine sediments. Underneath the O2 penetration depth, anaerobic mineralization processes occur due to the vertical distribution of electron acceptors in the sediment: O2 → ni- − 3+ 2− trate (NO3 ) → manganese (IV) oxide (MnO2) → ferric iron (Fe ) → sulfate (SO4 ) → carbon − dioxide/bicarbonate (CO2/HCO3 ) reflecting the gradual decrease of the redox potential. Most microorganisms involved in anaerobic mineralization processes grow chemoorganoheterotrophically, such as most denitrifying bacteria, manganese- or iron reducing bacteria, most sulfate reducing bacteria, fermenting bacteria, methane oxidizing bacteria and archaea. As a result, re- + − − duced inorganic compounds, such as ammonium (NH4 ), nitrite (NO2 ), NO3 , ferrous iron 2+ 0 (Fe ) and reduced sulfur species, such as sulfide (H2S), elemental sulfur (S ), iron sulfide (FeS), 2− 2− thiosulfate (S2O3 ) and sulfite (SO3 ), accumulate in the sediment (Jørgensen, 2006; Herbert, 1999), which can subsequently be reoxidized by chemolithoautotrophic microorganisms. Chemolithoautotrophic microorganisms (bacteria and archaea) gain energy for growth using chemical compounds as energy source (chemo-) in contrast to phototrophic organisms using light. Chemolithoautotrophs are able to use reduced inorganic compounds (litho-) as electron − donor and inorganic carbon, CO2 and/or HCO3 , as their only carbon source (-autotroph). The electron donors used by chemolithoautotrophic microorganisms comprise reduced nitrogen 2+ and sulfur compounds, as well as Fe , H2 and carbon monoxide (CO). Other microorganisms are able to assimilate organic carbon, while using inorganic electron donors, which is termed chemolithoheterotrophy, whereas those able to use inorganic or organic compounds as carbon source while utilizing inorganic electron donors are called mixotrophs. Many microorganisms use organic electron donors and fix organic carbon in a process known as chemoorganoheter- otrophy. Most chemolithoautotrophs are facultative chemolithoautotrophs, i.e. are able to grow chemolithoautotrophically as well as using a different metabolism. As chemolithoautotrophs are not able to synthesize adenosine triphosphate (ATP) from nicotinamide adenine dinucleotide (NADH) oxidation, most obligate chemolitoautotrophs couple the oxidation of their electron donors to the reduction of quinone or cytochromes supplying reducing equivalents for carbon fixation and biosynthesis through reverse electron transport (Kim and Gadd, 2008). Many per- − 2− form aerobic respiration using O2, while anaerobic chemolithoautotrophs use NO3 , SO4 , CO2 or metal oxides as electron acceptors (Jørgensen, 2006). Chemolithoautotrophic microorganisms are metabolically versatile and able to use a broad variety of electron donors for inorganic oxidation in coastal marine sediments (Table 1). Aer- obic and anaerobic ammonia oxidizing bacteria, sulfide oxidizing and sulfate reducing bacteria are believed to be the main contributors to chemolithoautotrophic carbon fixation in coastal 1 Chapter 1 ) ), ), Nitrosomonas Nitrosopumilus Thiomargarita ) Desulfovibrio spp. spp.) Thiobacillus denitrificans ), Thiobacillus, BeggiatoaThiobacillus, ) Nitrobacter)(Thiobacillus, ) large sulfur oxidizing bacteria ( Beggiatoalarge sulfur oxidizing ) anammox bacteria ( Scalindua anammox some sulfate reducing bacteria ( denitrifying sulfur bacteria ( nitrate reducing sulfur bacteria ( ammonia oxidizing bacteria (AOB) ( bacteria (AOB) ammonia oxidizing ( (AOA) archaea ammonia oxidizing acetogenic bacteria bacteria ( Hydrogenobacter oxidizing hydrogen thermophilus nitrifying bacteria methanogenic archaea Chemolithoautotrophic microorganisms (e.g.) colorless sulfur bacteria ( ) , Shewanella iron bacteria ( Ferrobacillus anaerobic ammonia oxidation hydrogen oxidation coupled to oxidation hydrogen sulfate reduction sulfide oxidation coupled to sulfide nitrate reduction to ammonia (DNRA) ammonia oxidation acetogenesis hydrogen oxidation hydrogen nitrite oxidation methanogenesis Process sulfur oxidation iron and manganese oxidation + 4 ) 0 , S O 2 2− S + NH O 3 2 2 ) 2− 2− O 4 2 2− +H 3 + , S O 2 O 2− O + H 2 3 O 2 + 2 , S 0 + 2H − O → SO − 2 2 3 + 2H COOH + 2H 2 + 2H + 2H 3 → 4H + 2− 3+ +H 4 4 + O 2 → NO → N → NO 2 2 − → CH 2 +H + 2H 2 − O → SO 3 2– → 4Fe 2 2 4 2 → CH / 2 → 2H ) 3 2 Versatility of Versatility reactions/processes performed reoxidation microorganisms chemolithoautotrophic by in coastal marine sediments (modified 2+ + ½ O + O + NO + − + + 2 4 4 +O + SO + 2CO 2+ 2+ 2 2 2 S + 2O S + NO + CO 2 2 2 4Fe H H 4H Electron donating reaction NH (other possible donors: SO (other possible donors: S (or Mn 2H NO 4H NH H Table 1: Table from Jørgensen, 2006). 2 Introduction marine sediments. In addition, many archaea are chemolithoautotrophs and representatives of the phylum Thaumarchaeota (formerly known as ‘marine group I Crenarchaeota’) have been determined to oxidize ammonia to gain energy for inorganic carbon fixation (Wuchter et al., 2003 and 2006; Könneke 2005, Brochier-Armanet et al., 2008) suggesting the contribution of archaea to the reoxidation of reduced inorganic compounds and inorganic carbon fixation in coastal marine sediments. Chemolithoautotrophy in coastal sediments is generally considered to be insignificant in terms of biogeochemistry, due to the low growth yields of these microorganisms and the competition with photo- and heterotrophic processes, which are the main source of labile organic matter in coastal sediments (Jørgensen and Nelson, 2004). However, although chemolithoautotrophic microorganisms might play a minor role in terms of growth, they are able to reoxidize important amounts of reduced inorganic substrates (Cypionka, 2006). The dependency of chemolithoautotrophic microorganisms on the availability of reduced inorganic compounds produced by chemoorganoheterotrophic microorganisms suggests a tight coupling between different microbial metabolic pathways in marine sediments. Unfortunately, direct measurements of chemolithoautotrophic activity are rare. Two rate measurements of dark CO2 fixation in shallow sub- tidal sediments of the Baltic Sea suggest that up to 20% of the inorganic carbon produced by mineralization appears to be reoxidized by chemoautotrophic microorganisms (Enoksson and Samuelsson, 1987; Thomsen and Kristensen, 1997). Only recently, chemolithoautotrophic sulfur oxidizing Gammaproteobacteria have been shown to contribute substantially to CO2 fixation by combined fluorescence in situ hybridization and microautoradiography (MAR FISH) analysis in the oxygen-, nitrate- and sulfide transition zone (0−3 cm) of intertidal sandy sediments (Lenk et al., 2011). Inorganic carbon fixation in coastal and ocean margin sediments, characterized by high organic carbon loadings, has been estimated to account for about 48% of the total oceanic chemoautotrophic carbon fixation rate (Middelburg, 2011). Considering the combination of high respiration rates and dominantly anoxic conditions, coastal and ocean margin sediments are presumably a hot spot for chemolithoautotrophy. The activity of chemolithoautotrophic microorganisms in coastal sediments has global implications for the cycling of carbon and the availability of nitrogen and sulfur compounds in marine environments. However, the diversity of chemolithoautotrophic microorganisms involved in nitrogen and sulfur cycling of coastal marine sediments, as well as the temporal and spatial distribution of their abundance and activity, is still poorly understood, especially in subsurface sediment layers. In the upper marine sediments, dark CO2 fixation is believed to be predominantly driven by oxidation of reduced nitrogen and sulfur compounds. 1.1. Chemolithoautotrophic contribution to nitrogen cycling in marine coastal sediments + − Inorganic nitrogen concentrations (NH4 , NO3 ) in marine sediments are determined by the sedimentation and decomposition rate of organic matter, as well as by diffusive transport rates and bioturbation. The cycling of nitrogen in coastal marine sediments consists of a series redox reaction performed by phototrophic, heterotrophic and autotrophic microorganisms and underlies complex regulatory mechanisms, comprising physicochemical and biological factors (Herbert, 1999; Joye and Anderson, 2006). The complexity of the cycle is revealed in Fig. 1.

Nitrogen fixation, e.g. the conversion of molecular nitrogen (N2) to bioavailable organic ni- 3 Chapter 1 Figure 1: Nitrogen cycling in coastal marine sediments (simplified and modified from Herbert,Joye 1999; and Anderson, 2006). Dashed lines indicate or surface advective, exchange between diffusive, compartments; solid lines represent microbial mediated Bold processes. process indicates - chemolitho autotrophic contribution. 4 Introduction

trogen compounds (Norg, e.g. proteins), is the initial step of the nitrogen cycling in marine sediments. During the mineralization of organic nitrogenous matter ammonification, the release of + + NH4 occurs. The NH4 released by ammonification is available for primary production and for + ammonia oxidation in the O2 transition zone of the sediment (Herbert, 1999). The fate of NH4 regenerated in sediments may either be the adsorption to particles, the flux from the sediment to the overlying water, the consumption by biological processes within the sediment or at the − − sediment–water interface, the oxidation to NO2 and then NO3 by nitrifying microorganisms, or the transformation to molecular nitrogen (N2) via the denitrification and anammox process (Joye and Anderson, 2006). 1.1.1. Nitrification − Nitrification is a two-step process, first ammonium is oxidized to NO2 by chemolithoautotrophic ammonium oxidizing bacteria (AOB) and archaea (AOA), which is then further oxidized − to NO3 by nitrite oxidizing bacteria (NOB) (Kim and Gadd, 2008). Aerobic ammonium oxidation is a two-step process, in which ammonium is oxidized to hydroxylamine catalyzed by the enzyme ammonia monooxygenase (AMO). In bacteria, hydroxylamine is further oxidized − to NO2 by the enzyme hydroxylamine oxidoreductase (HAO), whereas in archaea, the oxida- − tion of hydroxylamine to NO2 may be catalyzed via nitroxyl oxidoreductase (NxOR) (Schlep- er and Nichol, 2010). In coastal marine sediments, AOB belong to the Gammaproteobacteria (Nitrosococcus oceanus) and to Betaproteobacteria (Nitrosomonas spp. and Nitrosospira spp.), based on the phylogenetic analysis of 16S rRNA genes (Herbert, 1999). Ammonia oxidizing archaea (AOA) belong to the distinct phylum of Thaumarchaeota (Brochier-Amanet et al., 2008). Most AOBs are obligate chemolithoautotrophs, whereas Thaumarchaeota can grow chemolithoautotrophically (e.g. “Candidatus Nitrosopumilus” maritimus; Könneke et al., 2005) and possibly mixotrophically (e.g. “Nitrososphaera viennensis”; Tourna et al., 2011), besides heterotrophic growth cannot be ruled out (Pester, 2011). The communities of AOB and AOA seem to be favored by different physicochemical parameters, such as salinity, ammonia and O2 concentrations (Mosier and Francis, 2008; Santoro et al., 2008), with AOA preferring lower salinities and lower ammonia + concentrations. The oxidation of NH4 plays an important role in generating nitrogen oxides − − (NO2 and NO3 ) for microorganisms utilizing these to gain energy for carbon fixation, such as anammox and denitrifying bacteria. 1.1.2. Anammox Bacteria of the phylum Planctomycetes have been discovered to perform anaerobic ammonia + − oxidation (anammox) reaction, which consist on conversion of NH4 and NO2 into N2 while growing chemolithoautotrophically (Strous et al., 1999, Kuypers et al., 2003). In addition to − 3+ − NO2 , anammox bacteria are also able to use Fe , manganese oxides and NO3 as electron acceptors in their metabolism (Strous et al., 2006). All five described anammox genera belong to the order Brocadiales and are related to the order Planctomycetales (Jetten et al., 2009), but at present only “Candidatus Scalindua” has been detected in marine sediments and O2 minimum zones (OMZs) (Daalsgard et al., 2005; Woebken et al., 2008; Lam et al., 2009). The contribution of the anammox process to the total nitrogen removal in marine sediments has been estimated to be between 0–80% (Dalsgaard, 2005).

5 Chapter 1

1.1.3. Denitrification

After the consumption of dissolved O2 in the sediment pore water, organic matter decomposition continues via denitrification, anammox or dissimilatory nitrate reduction to ammonium (DNRA) (Zumft, 1997; Seitzinger, 2006). Whereas DNRA results in bioavailable ammonia, denitrification leads to the release of gaseous end products such as nitric oxide (NO), nitrous oxide

(N2O), and dinitrogen gas (N2) to the atmosphere. Dissimilatory denitrification, the microbial − − oxidation of organic matter with NO3 or NO2 as terminal electron acceptor, is considered to be the sequence of nitrate respiration, nitrite respiration combined with NO reduction, and N2O respiration: NO3 → NO2 → NO → N2O → N2. The denitrification process is performed by facultative chemoorganoheterotrophic bacteria, some archaea and foraminifera (Zumft, 1997; Risgaard-Petersen et al., 2006), and occurs as well in chemolithoautotrophic organisms performing the oxidation of an inorganic compound such as H2S coupled to nitrogen oxide reduction. Recently, sulfide-dependent denitrification, performed by autotrophic members of Alpha-, Beta- Gamma-, and Epsilonproteobacteria (especially Thiobacillus denitrificans and Sulfurimonas denitrificans), has been suggested to play a major role in the denitrification process in the oxygen- and sulfide- transition zone of coastal marine sediments (Shao, 2010). − The processes of nitrification and denitrification in sediments are the major source of NO3 − for denitrification in some estuaries and shelf regions. In systems with low NO3 concentrations (<10 μM) in the oxygenated bottom water, coupled nitrification/denitrification accounts for − 90% of the NO3 that is required for denitrification (Risgaard-Petersen, 2003). However, coupled nitrification/denitrification is a mechanism that can be responsible for substantial nitrogen removal from the sediment, which is in turn not available for primary producers. Nitrogen removal by denitrification, including anammox, might control the rate of eutrophication in coastal marine systems that receive large amounts of anthropogenic nitrogen (Herbert, 1999). 1.2. Chemolithoautotrophic sulfur cycling in coastal marine sediments Below the oxygen penetration depth (OPD) and after the depletion of electron acceptors, such − − as oxygen, NO3 /NO2 , and metal oxides, sulfate reduction to H2S becomes the prevalent microbial redox process in marine sediments (Jørgensen, 2006). Sulfate reduction, the reduction 0 of elemental sulfur (S ) and sulfur disproportionation can result in H2S production and upward diffusion. Most H2S is reoxidized by chemical and microbial mediated sulfur oxidation or buried as iron sulfide and pyrite (FeS, FeS2). 1.2.1. Sulfate reducing microorganisms 2– Sulfate reducing microorganisms have a key role in the sulfur cycle, they use SO4 as a terminal electron acceptor in the degradation of organic matter, which results in the production of H2S (Muyzer and Stams, 2008), which subsequently can be oxidized aerobically and anaerobically by sulfur oxidizing bacteria (e.g. Thiobacillus or Beggiatoa spp.). During dissimilatory sulfate reduc- 2− tion, SO4 is activated by the enzyme ATP sulfurylase, catalyzing the formation of adenosine 2− 2− phosphosulfate (APS) from SO4 and phosphate (ATP). The SO4 in APS is directly reduced 2− to SO3 by the cytoplasmic enzyme adenosine-5’ phosphosulfate (APS) reductase, which is then further reduced to H2S by the enzyme sulfite reductase. Sulfate reducing microorganisms are metabolically and genetically divers, some grow chemoorganoheterotrophically by using acetate, propionate, butyrate or lactate as electron acceptor, whereas many chemolithoautotrophic repre-

6 Introduction

2− sentatives use hydrogen as electron donor and SO4 as electron acceptor while utilizing CO2 as carbon source (e.g. Desulfovibrio spp.). Sulfate reducing bacteria belong to the class of Deltapro- teobacteria, as well as to the phyla of the Firmicutes and Nitrospirae. Within the archaea, sulfate reducing representatives belong to the genus Archaeglobus within the phylum of Euryarchaetoa, and to the phylum of Crenarchaeota (Muyzer and Stams, 2008). The activity of sulfate reducing microorganisms is especially important in organic-rich sediments underlying highly productive waters of continental shelves and slopes (Jørgensen, 1982a, b; Jørgensen and Kasten, 2006). It has been estimated that sulfate reduction can account for more than 50% of the organic carbon mineralization in marine sediments (Jørgensen, 1982a, b). 1.2.2. Sulfur oxidizing microorganisms in marine sediments 2− 2− Sulfur oxidation, i.e. the oxidation of reduced sulfur compounds, such as H2S, SO3 , S2O3 , 0 2− S , to SO4 can be performed by taxonomical divers chemolithoautotrophic bacteria and some − archaea, using mainly O2 and NO3 as electron acceptor, which ultimately links the carbon-, nitrogen- and sulfur cycling in marine sediments. Sulfide oxidation starts with the conversion of

H2S (sulfur, thiosulfate) to sulfite. Some sulfur oxidizing chemolithoautotrophs use the enzyme sulfite oxidase, which transfers electrons directly to cytochrome c generating ATP during electron transport and proton motive force formation. Others use the enzyme adenosine-5’ phosphosulfate (APS) reductase, which is an essential enzyme of sulfate reducing bacteria, which 2− results in SO4 production in sulfur oxidizers (Meyer and Kuever, 2007b). Chemolithoautotrophic bacteria belonging to the class of Betaproteobacteria (Thiobacillus), Gammaproteobacteria (Thiomicrosprira), and to the Epsilonproteobacteria (Acrobacter, Sulfuri- monas, Sulfurovum), have been shown to contribute to chemolithoautotrophic sulfide oxidation in coastal marine sediments (Jørgensen and Nelson, 2004; Campbell et al., 2006; Lenk et al., 2011). Chemolithoautotrophic sulfur oxidizing bacteria are taxonomically broad, while chemolithoautotrophic sulfur oxidizing archaea seem to be restricted to Sulfolobales (Crenarchaeota) using metal oxides, Thermoplasmatales (Euryarchaeota) using elemental sulfur, and only two genera − seem to be able to oxidize H2S, i.e. Acidianus sulfidivorans and Ferroglobus placidus, using NO3 and Fe3+ as electron acceptors (Hafenbradl et al., 1996; Plumb et al., 2007). Additionally, large sulfur bacteria, Gammaproteobacteria of the order Thiotrichales (Beggiatoa, Thioploca, Thiomargarita), contribute substantially to sulfide oxidation in coastal marine sediments. − Under low O2 conditions, Beggiatoaceae are able to store NO3 in an internal vacuole at the 0 sediment surface, before gliding into anoxic and sulfidic layers, where they oxidize H2S to S with − 0 the stored NO3 . Here, S is stored in globules and transported back to the surface to complete the oxidation to sulfate. Most members of the marine Beggiatoaceae family are chemolithoautotrophs, some species are able to use an organic carbon source for mixotrophic or chemooar- ganoheterotrophic growth (Mußmann et al., 2003; Jørgensen and Nelson, 2004).

1.3. Autotrophic CO2 fixation pathways of microorganisms

Up to date six different CO2 fixation pathways used by taxonomically diverse bacteria and archaea have been discovered (Fig. 2). In the Calvin-Benson-Bassham (CBB) cycle, CO2 reacts with ribulose 1,5-bisphosphate to gain two 3-phosphoglycerate, from which the sugar is formed. Apart from eukaryotes such as plants and algae, the CBB cycle is utilized by cyanobacteria, many aerobic or facultative aerobic Proteobacteria belonging to the Alpha-, Beta-, and Gamma- classes 7 Chapter 1

(including AOB), Sulfobacillus spp., iron and sulfur oxidizing Firmicutes, some mycobacteria, and bacteria of the phylum Chloroflexi Oscillochloris( ) (Berg et al., 2010). The CBB cycle prevails under oxic conditions, whereas the more energy efficient and less O2 sensitive reductive tricarboxylic acid (rTCA) cycle is restricted to microaerobic and anaerobic conditions (Berg et al., 2010). The rTCA cycle reverses the reactions of the oxidative citric acid (Krebs-) cycle and operates in sulfate reducing Delta- and sulfur oxidizing Epsilonproteobacteria, green sulfur bacteria and in microaerophilic bacteria of the phylum Aquificae (Hügler et al., 2005; Campbell et al., 2006). The strictly anaerobic reductive acetyl-coenzyme A (acetyl-CoA) pathway is a noncyclic pathway, in which one CO2 molecule is reduced to CO and one to a methyl group, from which acetyl-CoA is synthesized subsequently. The acetyl-CoA pathway functions in acetogenic and methanogenic bacteria, as well as in anammox bacteria (Planctomycetes), sulfate reducing Del- taproteobacteria (Desulfobacterium sp.), and in Euryarchaeota (Archaeglobales). The 3-hydroxypropionate bicycle is currently restricted to members of the Chloroflexacae family. The 3-hydroxypropionate/4-hydroxybutyrate cycle occurs in aerobic Crenarchaeota (Sulfolobales) and marine Thaumarchaeota (AOA), whereas the dicarboxylate/4-hydroxybutyrate cycle functions in anaerobic Crenarchaeota of the orders Thermoproteales and Desulfurococcales. The prevalence of

CO2 fixation pathways utilized by chemolithoautotrophic microorganisms in seasonally hypoxic coastal marine sediments is poorly known at present (Berg et al., 2010, and 2011).

Thaumarchaeota

Figure 2: Phylogenetic classification of autotrophic bacteria and archaea; green: Calvin-Benson-Bassham cycle, red: reductive tricarboxylic acid cycle, blue: reductive acetyl-CoA cycle, orange: 3-hydroxypropionate bicycle, purple: 3-hydroxypropionate-/ 4-hydroxybutyrate cycle, brown: dicarboxylate/4-hydroxybutyrate cycle (Figure modified from Hügler and Sievert, 2011). 8 Introduction

1.4. Physicochemical parameters affecting microbial chemolithoautotrophy in coastal marine sediments Various abiotic and biotic factors control the abundance and activity of chemolithoautotrophic microorganisms involved in carbon-, nitrogen-, and sulfur cycling in marine sediments. Gener- ally, O2 is one of the most important ecological factors influencing chemolithoautotrophy, especially in the oxygen transition zones of coastal marine sediments, where O2 is depleted within the first millimeters. The 2O concentration shapes the distribution of different autotrophic carbon fixation pathways, as well as the availability of suitable electron donors and acceptors, metals and coenzymes (Berg, 2011). Whereas nitrification is predominantly an obligate aerobic process, denitrification is a facultative anaerobic process, most denitrifiers prefer to respire2 O instead of − NO3 when O2 concentrations exceed 20 mM (Tiedje, 1982). Anammox bacteria are obligate anaerobes and despite their O2 tolerance, the activity seems to be limited to anoxic conditions (Dalsgaard et al., 2005; Risgaard-Petersen et al., 2004, and 2005). Coastal regions, especially estuaries and coastal areas with limited water exchange, often obtain large amounts of anthropogenic nitrogen leading to eutrophication, (Howarth and Marino, 2006). Hypoxia is one of the common features of eutrophication and the phenomenon of seasonal hypoxia has expanded over the last decades in coastal regions. Seasonal hypoxia causes − a decrease in the availability of electron acceptors, i.e. O2 and NO3 in the bottom water (Rosen- berg and Diaz, 2008), suggesting consequences for chemolithoautotrophic microorganisms involved in carbon-, nitrogen-, and sulfur cycling in marine coastal sediments and thus for the biogeochemistry in marine sediments (Middleburg and Levin, 2009).

Extensive sulfate reduction leads to the accumulation of free H2S in anoxic sediments, which is diffusing upwards (Jørgensen and Nelson, 2004). Sulfide has been shown to inhibit ammonia oxidation (Joye and Hollibaugh, 1995), as well as enzymes catalyzing the last steps of denitrification (Sørensen, 1980; Porubsky et al., 2009). The effect of H2S on anammox is relatively unclear, but there is certain evidence, that the activity of anammox bacteria is inhibited in sulfidic waters of oxygen minimum zones (Daalsgaard 2003; Jensen et al., 2008), suggesting that the abundance and activity of anammox bacteria might as well be inhibited by rising H2S concentrations in coastal marine sediments.

However, it is well known that high concentrations of free H2S are toxic for benthic animals, such as bioturbating organisms (Vaquer-Sunyer and Duarte, 2008). The key role of bioturbation in nutrient cycling is well established (Meysman et al., 2006) and has been suggested to extend the area of O2 availability in deeper sediment layers, supporting aerobic microbial processes, such as nitrification, which in turn might fuel anammox and denitrification (Meyer et al., 2005). Recently, bioturbation has been shown to induce changes in the sedimentary microbial community composition, resulting in distinct communities within the burrow (Laverock et al., 2010). 1.5. Methods to study microbial chemolithoautotrophy The majority of microorganisms that occur in natural environments cannot be cultured or isolated using traditional cultivation techniques, which limits our knowledge of environmental microbial diversity (Rappé et al., 2003). In the last decades, a wide range of cultivation independent approaches have been developed to understand the abundance, diversity and metabolic activity of microbial communities in the environment using a wide range of organic and inorganic

9 Chapter 1 biomarker molecules, such as DNA/RNA and lipids, as well as the incorporation of labeled substrates into biomarker molecules. 1.5.1. Abundance and diversity of chemolithoautotrophic microorganisms using DNA-based methods The analyses of DNA sequences of microorganisms has expanded our knowledge of the taxonomic and functional diversity of marine microbes to a large extent. Molecular methods revealed a diverse community of microorganisms with diverse metabolic capabilities, new species and novel pathways of organic matter cycling (Delong, 1992; Fuhrman et al., 1992). Advances in molecular microbiology allow for DNA sequence analysis and comparison to sequences that are already available in sequence databases. The development of quantitative PCR (qPCR) for the real time quantification of selected DNA sequences (genes) can be used to estimate the abundance of specific groups of microorganisms. In general, two kinds of genes are normally targeted, the 16S rRNA gene and functional genes. The 16S ribosomal RNA is part of the 30S small subunit of a prokaryotic ribosome, and the 16S rRNA gene sequence has been used to reconstruct the microbial phylogeny (Woese and Fox, 1977). The 16S rRNA gene sequence is especially useful because as it is present in all Domains of life, i.e. Bacteria, Archaea and Eukarya. Variable regions of the 16S rRNA gene are diagnostic for specific groups of organisms, whereas highly conserved regions can be used to assess the diversity of the microbial community. Sequencing of the highly conserved and species specific 16S rRNA gene has been extensively used to characterize the microbial community in marine surface and subsurface sediments (Madsen, 2008). Nevertheless, the rapid development of new generation sequencing methods allows for high throughput sequencing, and 16S rRNA gene amplicon sequencing has been shown to be a powerful tool to study the diversity of the microbial community as well as the relative abundance of specific groups in a high resolution in the marine environment (Gilbert and Dupont, 2011; Klindworth et al., 2013; Cruaud et al., 2014). As the 16S rRNA gene gives only limited and indirect information about the metabolism, i.e. the contribution to CO2 fixation and reoxidation pathways, functional gene analysis, i.e. genes encoding for key-enzymes involved in different CO2 fixation and reoxidation pathways, is a powerful tool to study the diversity and abundance of chemolithoautotrophic microorganisms. Gene sequences, i.e. the cbbL gene coding for ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) and the aclB gene coding for the ATP-citrate lyase, functioning in the CBB and rTCA cycle respectively, have been used to assess the diversity of chemolithoautotrophic microorganisms in intertidal mudflat sediments as well as in hydrothermal vent sediments and in sediments with an oxygen-sulfide chemocline (Nigro and King, 2007; Campbell et al., 2003, and 2006). However, the temporal and spatial distribution of the diversity and the abundance of chemolithoautotrophic microorganisms using the CBB or rTCA cycle have rarely been studied in coastal marine sediments. Some important key-enzymes and their corresponding functional genes for inorganic carbon assimilation and reoxidation pathways are summarized in Table 2. The key-enzyme of aerobic ammonia oxidation is a membrane-bound putative ammonia monooxygenase (AMO), catalyzing the oxidation of ammonium to hydroxylamine in Bacteria (Rotthauwe et al., 1997) and Archaea (Venter et al., 2004; Könneke et al., 2005; Yakimov et al., 2009). The metabolic gene amoA, encoding AMO, has been used to analyze the diversity and abundance of AOA and AOB in estuarine sediments (Beman and Francis, 2006; Mosier and

10 Introduction References Lam et al., 2009 Bracker et al., 1998 Bracker Hornek et al. (2006) Harhangi et al., 2012 Campbell et al., 2003 Yakimov et al. (2011) Yakimov Nigro and King, 2007 Rotthauwe et al. (1997); Rotthauwe Meyer & Kuever, 2007c Meyer & Kuever, nirS nirS aclB cbbL aprA hzsA gene amoA amoA Functional (AMO) reductase Key enzyme reductase (NIR) reductase (NIR) oxygenase (RuBisCO) oxygenase ATP-citrate lyase (ACL) ATP-citrate monooxygenase (AMO) monooxygenase hydrazine synthase (HZS) hydrazine β-proteobacterial ammonia cytochrome cd 1-containing nitrite cytochrome cytochrome cd1-containing nitrite cytochrome archaeal ammonia monooxygenase ammonia monooxygenase archaeal adenosine-5’ phosphosulfate (APS) ribulose1,5-bisphosphate carboxylase/ fixation and reoxidation pathways. Primer sequences are reported in the given references. references. Primer sequences are reported in the given pathways. fixation and reoxidation 2 Denitrification Pathway Ammonia oxidation Arnon–Buchanan cycle reductive pentose phosphate cycle reductive Calvin-Benson-Bassham (CBB) cycle/ reductive tricarboxylic acid (rTCA) cycle/ tricarboxylic reductive Denitrification coupled to sulfur oxidation sulfur to coupled Denitrification Anaerobic ammonia oxidation (anammox) Anaerobic ammonia oxidation

Important functional genes of CO

2 2 fixation CO reoxidation Table 2: Table 11 Chapter 1

Francis, 2008; Abell et al., 2010) and in sandy coastal sediments (Santoro et al., 2008). Howev- er, the spatial and temporal distribution of the diversity and abundance of microbial ammonia oxidizers, as well as of anammox bacteria, denitrifiers, sulfate reducers and sulfur oxidizers, in seasonally hypoxic sediments, is still unknown. The hzsA and nirS gene of anammox bacteria, encoding for the hydrazine synthase (HZO) and cytochrome cd1-containing nitrite reductase (NIR), have been proposed as suitable biomarker to detect anammox bacteria diversity and abundance in the marine environment (Kartal et al., 2011; Harhanghi et al., 2012; Lam et al., 2009) as well as in marine sediments (Li et al., 2011). The cytochrome cd1-containing nitrite reductase, coded by the nirS gene, operates as well in the dissimilatory denitrification process, cata- − lyzing the reduction of NO2 to NO, the first gaseous product in the sequence of denitrification (Zumft, 1997; Braker, 1998). The nirS gene has been used to study the diversity and to estimate the abundance of denitrifying microorganisms in estuarine sediments (Smith at al., 2007; Mosi- er and Francis, 2010). The diversity of sulfate reducing and sulfur oxidizing microorganisms have been studied using the aprA gene encoding the disssimilatory adenosine-5’ phosphosulfate (APS) reductase, which is a key enzyme in sulfate reduction and sulfur oxidation processes. The 2− APS reductase catalyzes the conversion of APS to AMP and SO3 in sulfate reducing microorganisms, and operates in the reverse direction in sulfur oxidizing microorganisms. The highly conserved aprA gene has been shown to be a suitable biomarker to profile the community structure of sulfate reducing and sulfur oxidizing microorganisms in marine and estuarine sediments (Meyer and Kuever, 2007c, Muyzer and Stams, 2008). 1.5.2. Archaeal and bacterial membrane lipids as taxonomic markers Membrane lipids are considered as taxonomic markers that can be used to estimate the abundance, distribution, and physiological status of certain microbial groups (White, 2007). In addition, these lipids can be preserved in sediments upon cell depth and thus being used as biomarkers of the presence of certain organisms both in present and past ecosystems. On the contrary, other biomolecules like DNA have a more rapid turnover and they cannot be used for this purpose. In recent years, intact polar lipids (IPLs) are increasingly applied for tracing ‘living’ bacteria and archaea in the environment (Lipp et al., 2008; Rossel et al., 2008; Lipp and Hinrichs, 2009). IPLs with polar head groups are present in living cells but upon cell lysis the polar head groups are lost, releasing the core lipids (CLs) that may be preserved in the fossil record. Since IPLs degrade relatively quickly after cell death (Harvey et al., 1986), it is possible to associate the presence of IPLs in the environment with the occurrence of their living producers (Zink et al., 2003; Biddle et al., 2006; Huguet et al., 2010; Schubotz et al., 2009). Specifically, IPLs with phospho- head groups have been shown to degrade rapidly after cell death, while IPLs with glycosidic polar head groups might be preserved in the sediment record (White et al., 1979; Harvey et al., 1986; Bauersachs et al., 2010; Lengger et al., 2012). Membrane lipids from bacteria and eukaryotes are composed of fatty acid chains that are linked to the glycerol moiety through ester bonds and organized in a bilayer structure. On the other hand, archaeal membrane lipids are characterized by ether bonds, isoprene-based alkyl moieties, and an opposite stereochemistry of the glycerol phosphate backbone, i.e. sn-glycerol-1-phosphate (G1P). Archaeal membrane lipids are typically a variation of two main structures, sn-2,3-diphytanylglycerol diether (archaeol) with phytanyl (C20) chains in a bilayer structure, and sn-2,3-dibiphytanyl diglycerol tetraether (glycerol dibiphytanyl glycerol tetraether, GDGT), in which the two glycerol moieties are connected by two C40 isoprenoid chains, allowing the 12 Introduction

Table 3: Membrane lipid composition of the main groups of archaea involved in chemolithoautotrophy and sulfur metabolism in marine sediments (modified from Villanueva et al., 2014). Species specific GDGT occurrence and distributions of pure cultures are described in detail in Schouten et al. (2013) and references therein.

Phylum Order Metabolism Membrane lipid ammonia oxidizer GDGT-0 to 4, Cenarchaeales autotroph crenarchaeol Thaumarchaeota ammonia oxidizer GDGT-0 to 4, Nitrosopumilales (AOA) autotroph/mixotroph crenarchaeol ammonia oxidizer GDGT-0 to 4, Nitrosospherales autotroph crenarchaeol Desulfurococcales sulfur dependent GDGT-0 to 4, GDGT-0 to 4, Sulfolobales sulfur dependent Crenarchaeota GDGT-5 to 8 GDGT-0 to 4, Thermoproteales sulfur dependent GDGT-5 to 8 GDGT-0 to 4, Thermoplasmatales sulfur dependent GDGT-5 to 8 archaeol, Thermococcales sulfur dependent Euryarchaeota GDGT-0 Archaeglobales sulfur dependent GDGT-0 methane oxidation ANME-cluster GDGT-0 to 4 chemoorganoautotroph formation of monolayer membranes (Koga and Morii, 2007). GDGTs have been found to be ubiquitous in the marine water column and sediments (Schouten et al., 2000). Isoprenoid GDG- containing 0–8 cyclopentane moieties (Fig. 3) are commonly found in different archaeal groups, such as Thaumarchaeota (Wuchter et al., 2006), extremophiles (Huber et al., 1998; Lattuati et al., 1998; Ellen et al., 2009), methanogens (Koga et al., 1998; Gattinger et al., 2002; Zhang et al., 2011), and anaerobic methane-oxidizing archaea, ANME (Pancost et al., 2001). However, the isoprenoid GDGT crenarchaeol (Sinninghe Damsté et al., 2002a), containing four cyclopentane moieties and a cyclohexane moiety, is considered to be characteristic of Thaumarchaeota (Schouten et al., 2000; Sinninghe Damsté et al., 2002a; Zhang et al., 2006; Pester et al., 2011; Pitcher et al., 2011a). The culture-based GDGT compositions of the main archaeal groups, which are potentially involved in chemolithoautotrophy and sulfur metabolism in marine sediments, are summarized in Table 3. The distribution of thaumarchaeotal GDGTs in the marine environment has been shown to be affected by temperature, i.e. with increasing temperature there is an increase in the relative abundance of cyclopentane-containing GDGTs (Schouten et al., 2002; Wuchter et al., 2004, and 2005). Based on this relationship, the TEX86 paleotemperature proxy was developed and calibrated using sea surface temperature and it has been widely applied for more than a decade

13 Chapter 1

Figure 3: Structures of isoprenoid GDGTs (0–8) and crenarchaeol (mod. from Schouten et al., 2013).

(Schouten et al., 2002). However, evidences increasingly demonstrate that temperature is not the only variable affecting the GDGT distribution (Schouten et al., 2013, Pearson et al., 2013).

For example, TEX86 responds to temperature in a different way in enrichments (Schouten et al., 2007a) and cultures (Pitcher et al., 2011a) than in suspended particulate matter (SPM) or when fossilized in surface sediments (Kim et al., 2010). It is also known that TEX86 does not reflect surface temperatures but rather subsurface temperatures (Huguet et al., 2007; Lopes dos Santos et al., 2010; Kim et al., 2010), and that archaeal production in the deeper water column may also contribute to the signal of GDGTs in sediments (Pearson et al., 2001; Shah et al., 2008). In addition, the TEX86 signal may also be affected by input from other archaea, which could potentially synthesize GDGTs used in TEX86. For example, it has been suggested that in situ produced lipids of benthic and methanogenic archaea might contribute to the GDGT pool in marine sediments, which might be relevant for the reliability of the TEX86 proxy (Weijers et al., 2006a; Blaga et al., 2009; Sinninghe Damsté et al., 2012a). In addition, some studies have suggested that benthic archaea might be able to recycle core lipid GDGTs in marine sediments (Takano et al., 2010; Liu et al., 2011). Recent advances in high performance liquid chromatography (HPLC)- mass spectrometry (MS) methods have allowed the analysis of core GDGTs as well as IPL GDGTs. IPL GDGTs have been analyzed by separating them from the core lipids using silica gel chromatography and hexane/EtOAc mixtures as eluent (Oba et al., 2006; Pitcher et al., 2009) followed by acid hydrolysis and high pressure liquid chromatography coupled via an atmospheric pressure chemical ionization interface to a mass spectrometer (HPLC−APCI−MS) (Hopmans et al., 2000; Sturt et al., 2004; Schouten et al., 2007a). With this method, IPL derived core GDGTs can be quantified using internal standards, but it does not allow to specify the kind of head group that was attached to the GDGT. In contrast, the development of HPLC combined with electrospray chemical ionization mass spectrometry (HPLC−ESI−MS), allows to analyze GDGT IPLs, with 14 Introduction

Figure 4: Main head groups of crenarchaeol detected in cultures of “Ca. Nitrosopumilus maritimus”, “Ca. Nitrososphaera gargensis” and “Ca. Nitrosoarchaeum limnia”, as well as in marine sediments. the polar head group still attached to the core (Rütters et al., 2002; Zink et al., 2003; Sturt et al., 2004). Core and intact polar GDGTs have been analyzed by HPLC-ESI-MS2 in selected reaction monitoring (SRM) (Schouten et al., 2008a), in AOA sediment enrichment cultures, including “Candidatus Nitrosoarchaeum limnia” (Pitcher et al., 2011a), as well as in marine sediments (Lengger et al., 2012). Polar headgroups of creanarchaeol have been seen to be mainly comprised by monohexose (MH), dihexose (DH), phosphohexose (PH) and hexose-phosphohexose (HPH) (Fig. 4) (Pitcher et al., 2011a). Results suggest that HPH-crenarchaeol is the most suitable lipid biomarker to trace living Thaumarchaeota of marine group I.1a due to the labile nature of the phosphate bond (Harvey et al., 1986; Schouten, et al., 2010) in comparison with glycosidic crenarchaeol-IPL-GDGTs. Additionally, it has been shown that the HPH-crenarchaeol concentration corresponds well to DNA-based thaumarchaeal abundance (Pitcher, 2011a and b; Schouten et al., 2012a; Lengger et al., 2012). Bacterial membrane lipids are composed by fatty acids linked by ester bonds to the glycerol-3-phosphate backbone. The phospholipid-linked fatty acids (PLFAs) have been extensively used to characterize bacteria and eukaryotic microorganisms in different environmental settings including estuarine sediments (Guckert et al., 1985). PLFAs have complex structures with different carbon lengths, unsaturations, methylations and isomers (Vestal and White, 1989) and in some cases, PLFA signatures are specific enough to pinpoint shifts in the bacterial and eukaryotic community composition (Boschker and Middleburg, 2002) (Table 4), but it does not offer a high taxonomic resolution compared to DNA/RNA-based methods. PLFA concentrations can be analyzed by gas chromatography (GC)-flame ionization detection (FID) and MS according to a method previously described (Boschker et al., 1998). Other membrane lipids, present in microbial cells can be used as biomarkers of the presence of their producer. For the case of chemolithoautotrophic microorganisms of importance in marine sediment, the specific lipids contained in anammox bacteria are a clear example. Anammox bacteria contain a membrane bound compartment in the cytoplasm, the anammoxosome, in

15 Chapter 1

Table 4: PLFA signatures of the main groups of chemoautotrophic bacteria in marine sediments. The relative contributions of the main fatty acids to the total PLFA composition and complete PLFA signatures are described in the listed references (mod. from Vasquez-Cardenas, 2016). For details on the nomenclature of PLFAs see supplementary information.

Metabolism PLFA signature Reference 16:1ω7c Ammonium oxidizers Blumer et al., 1969 16:0 16:1ω7c Lipski et al., 2001 Nitrite oxidizers 16:0 Blumer et al.,1969 18:1ω7c 14:0 15:0 i15:0 Taylor and Parks, 1983 Sulfate reducers 16:1ω7c Edlund et al., 1985 (Deltaproteobacteria) 16:0 Suzuki et al., 2007 i17:1ω7c Pagani et al., 2011 17:1ω6c 18:1ω7c 14:0 16:1ω7c Mat forming sulfur oxidizers Zhang et al., 2005 16:1ω7t (Gammaproteobacteria) Li et al., 2007 16:0 18:1ω7c 14:0 Inagaki et al., 2003 Sulfur oxidizers 16:1ω7c Takai et al., 2006 (Epsilonproteobacteria) 16:0 Donachie et al., 2005 18:1ω7c 16:1ω7c 16:0 Iron and Sulfur oxidizers Knief et al., 2003 cy17:0 cy19:0 which the anammox reaction takes place (van Niftrik et al., 2008). The anammoxosome consists of ladderane lipids with three or five linearly arranged cyclobutane rings (Sinninghe Damsté et al., 2002b). Ladderane lipids can be either ester- or ether bound to glycerol and major polar headgroups are phosphatidylcholine (PC), phosphoetanolamine (PE) and phosphoglycerol (PG) (Boumann et al., 2006; Rattray et al., 2008). Whereas ladderane core lipids have been shown to be suitable biomarkers for anammox bacteria abundance in the fossil sediment record, the

C20-[3]-monoether ladderane lipid attached to a PC head group has been shown to be a suitable 16 Introduction

Figure 5: Chemical structures of ladderane core lipids and the intact PC-monoether ladderane lipid. biomarker for living anammox bacteria in continental shelf sediments (Jaeschke et al., 2010). Ladderane core lipids can be analyzed as fatty acid methyl esters (FAMEs) by HPLC-APCI-MS2 in selective reaction monitoring (SRM) mode as previously described (Hopmans et al., 2006) and modified to include short chain fatty acids (Rush et al., 2012). The PC-monoether ladderane lipid can be analyzed by HPLC-MS2 (Jaeschke et al., 2009), and quantified using an external PC-monoether ladderane standard. Main structures of ladderane core lipids and the intact PC-monoether ladderane lipid are summarized in Fig. 5. 1.5.3. Determining the activity of chemolithoautotrophic microorganisms The determination of active (chemolithoautotrophic) microorganisms in marine sediments has been a challenge and has been addressed using different methods by targeting the metabolic process or the activity of specific groups or specific microorganisms.

In sediments, microsensor profiling, i.e. concentration measurement of respiratory gases O2 and H2S has been used to identify active microbial processes, such as photosynthesis, respiration and sulfur oxidation (Nielsen et al., 1990; Schramm et al., 1996). The activity of microbes participating in nitrogen cycling processes, such as nitrification, denitrification and anammox, 15 14 − − have been estimated by isotope tracer experiments with N- and N-labeled NO3 , NO2 and + NH4 by the discrimination of isotope pairing in marine sediments (Nielsen, 1992; Rysgaard et al., 1993). Microsensor profiling, as well as isotope tracer experiments, are adequate methods to measure overall process rates, but do not provide any taxonomic information about metabolically active microorganisms. In contrast, the expression of functional genes, i.e. the quantification of mRNA by reverse transcription (Holmes et al., 2004) and subsequent qPCR, has been proposed to be a good marker to determine the activity of specific microorganisms in the marine environment. The positive gene expression of functional genes may serve as evidence for active in situ processes and provide insight into the diversity of active microorganisms (Nogales et al., 2002; Wellington 17 Chapter 1 et al., 2003). For the case of chemolithoautotrophic microorganisms, the transcript abundance of the archaeal amoA gene has been quantified to estimate the activity of Thaumarchaeota in oceanic waters, showing that marine Thaumarchaeota are actively involved in ammonia oxidation in the water column of the Pacific Ocean, as well as in the Peruvian OMZ and in the Mediterranean Sea (Lam et al., 2009; Church et al., 2010; Yakimov et al., 2011). Additionally, gene expression of the bacterial and archaeal amoA gene has been analyzed in soil, as well as in estuarine sediments as a measure of the transcriptional activity, indicating the protein production potential (Nicol et al., 2008; Abell et al., 2011). In estuarine sediments, the expression of bacterial amoA genes was reduced at low dissolved O2 (DO) concentrations, whereas the archaeal amoA gene expression was not affected, suggesting that AOB and AOA show different responses to changes in sediment DO, which may be a significant factor in niche partitioning of different ammonia oxidizer groups. The gene expression of other functional genes has also been determined as an indicator for the potential activity of specific groups. For example, the nirS transcript abundance of denitrifying bacteria has been quantified in estuarine sediments (Nogales et al., 2002; Smith et al., 2007; Bulow et al., 2008), showing the decrease of potentially active denitrifying bacteria from the head to the mouth of the estuary. The nirS transcript abundance of anammox bacteria has been used to estimate the potential activity of anammox bacteria, showing the contribution of anammox bacteria to nitrogen removal the Peruvian oxygen minimum zone (Lam et al., 2009). Stable carbon isotopes have been also used to track the activity of microorganisms in marine sediments. In contrast to radioactive isotopes (14C), stable carbon isotopes (12C, 13C) do not decay in nature and are less harmful. In nature, stable carbon and nitrogen isotopes occur in different abundances. Whereas the isotope with the low mass (e.g. 12C) is highly abundant (98%), the isotope with the higher mass (e.g. 13C) represents less than 2% (Fry, 2006). The difference in the abundance gives the possibility to track the cycling of elements by the metabolic incorporation of 13C into specific molecules. The labeled substrate is added to an environmental sample (e.g. intact sediment core) and biomarkers are purified and analyzed following the consumption of the substrate. Stable isotope probing (SIP) has been applied to track the incorporation of 13C substrates into membrane lipids, such as archaeal GDGTs (Wuchter et al., 2003), IPL derived GDGTs (Pitcher et al., 2011b) and bacterial PLFAs (Boschker et al., 2002). The 13C incorporation into the biphytanes of GDGTs and into PLFAs can be measured by chromatography combustion isotope ratio mass spectrometry (GC-c-IRMS) (Boschker et al., 1998; Wuchter et al., 2003; Pitcher et al., 2011b). GDGT SIP, i.e. the incorporation of 13C labeled bicarbonate into the biphytanyl chains of crenarchaeol revealed the capability of Thaumarchaeota to grow autotrophically (Wuchter et al., 2003), which was later confirmed by the isolation and physiological characterization of Candidatus Nitrosopumilus maritimus (Könneke et al., 2005). SIP has been used to label membrane lipids, as well as to track the incorporation of 13C into nucleic acids, such as DNA (DNA-SIP) and RNA (RNA-SIP) (Radajewski et al., 2000, and 2003). PLFA-SIP is the most sensitive method, whereas the DNA-SIP is the less sensitive approach. In contrast to RNA and PLFA, the replication of DNA depends on cell division in presence of the labeled substrate, which makes it difficult to accomplish sufficient incorporation for separation of labeled DNA (Neufeld et al., 2006). A method that does not imply extraction of labeled compounds, but rather visualizes active microbial cells that have been targeted with a sequence specific labeled probe under the micro- 18 Introduction scope, is fluorescence in situ hybridization (FISH). The combination of FISH with catalyzed reporter deposition (CARD-FISH) has been used to estimate the abundance of active microorganisms in the marine environment, targeting DNA and RNA molecules as well as rare molecules, such as mRNA and genes, with signal amplification using horseradish peroxidase (HRP) (Llobet-Brossa et al., 2002; Pernthaler et. al., 2002; Ishii et al., 2004). For example, the abundance of Crenarchaeota has been estimated by CARD-FISH in water samples of the Atlantic Ocean (Wuchter et al., 2006). CARD-FISH has been also combined with other approaches to determine metabolic activity in chemolithoautotrophic microorganisms. For example, catalyzed reporter deposition (CARD)-FISH combined with microautoradiography (MAR) demonstrated that novel groups of Gammaproteobacteria attached to sediment particles have been shown to 14 incorporate C-labeled CO2 by MAR-FISH concluding that these groups performed a chemolithoautotrophic metabolism based on sulfur oxidation, and also suggesting that they play a more important role for H2S removal and primary production in marine sediments than previously thought (Lenk et al., 2011). Another novel technique, providing information about elemental, isotopic and molecular characteristics of single cells is nano-scale secondary ion mass spectrometry (NanoSIMS). NanoSIMS can be combined with SIP as well as with CARD-FISH methods. A combination of CARD-FISH and NanoSIMS has been used to track the fate of carbon and nitrogen in microbial aggregates (Behrens et al., 2008). However, the NanoSIMS method is cost-intense and time consuming regarding the sample preparation and fine tuning of the instrument. 1.6. Scope of this thesis The research described in this thesis is focused on the spatial and temporal distribution of chemolithoautotrophic microorganisms in coastal marine sediments. These microbes have not been studied extensively and there is a growing need to determine their role in the sedimentary carbon-, nitrogen-, and sulfur cycle, as well as to identify microbial key-players that are involved, especially in the oxygen transition zone of seasonally hypoxic sediments. To this end, the diversity, abundance and activity of chemolithoautotrophic microorganisms, such as AOA, AOB, anammox and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing microorganisms have been determined. Additionally, the diversity and activity of chemolithoautotrophic microorganisms involved in the CBB and rTCA cycle as well as the metabolism of Thaumarchaeota and the abundance of Archaea have been addressed. In the following studies, we focused on coastal marine sediments, exposed to summer hypoxia, i.e. (1) the seasonal hypoxic basin of the Oystergrounds in the central North Sea, (2) different sediment types (sand, clay, and mud) of the Iceland Shelf, and (3) seasonally hypoxic and sulfidic sediments of saline Lake Grevelingen (The Netherlands). The work presented here is divided in the following chapters: Chapter 2 shows the seasonal and depth distribution of the abundance and potential activity of archaeal and bacterial ammonia oxidizers (AOA and AOB) and anammox bacteria in coastal marine sediments of the southern North Sea. Specific intact polar lipids as well as the gene abundance and expression of the 16S rRNA gene, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) of anammox bacteria were quantified in contrasting seasons (i.e. February, March and August). AOA, AOB and anammox bacteria were detected and transcriptionally active down to 12 cm sediment depth in all seasons. 19 Chapter 1

AOA seem to play a more dominant role in aerobic ammonia oxidation compared to AOB, as their abundance was higher in all seasons. Anammox bacteria were abundant and active even in bioturbated and oxygenated sediment layers, especially in August, suggesting that their growth and activity are favored by higher temperatures and lower O2 concentrations during summer stratification. The metabolic activity of the studied microbial groups is spatially coupled leading to the assumption that the rapid consumption of O2 allows the coexistence of aerobic and aerobic ammonia oxidizers in the sediments of the Oyster Grounds in the southern North Sea. In Chapter 3, we aimed to determine the metabolism of sedimentary Thaumarchaeota and bacteria by studying the incorporation of 13C-label from bicarbonate, pyruvate, glucose and amino acids into the thaumarchaeal IPL-GDGTs and bacterial/eukaryotal PLFAs during 4−6 days of incubation in intact marine sediment cores from three different sites on the Iceland shelf. The abundance of thaumarchaeal IPL-GDGTs, in particular HPH-crenarchaeol, were detected at all stations and the concentrations remained constant or decreased slightly during incubation, suggesting that living Thaumarchaeota were present in sediments at all stations. In organic-rich sediments a large uptake of 13C label from organic substrates in bacterial/eukaryotic IPL-derived fatty acids was found, implying that heterotrophic bacteria and potentially non-photosynthetic eukaryotes incorporated label into their biomass, whereas the incorporation of labeled bicarbonate into the PLFAs of chemolithoautotrophic bacteria and archaea seem to be of minor relevance or under the detection limit of the method. In sandy sediments, some enrichment of 13C (1−4%) in thaumarchaeotal IPL-GDGTs was detected after the incubation with bicarbonate and pyruvate, but overall no substantial incorporation of 13C into the biphytanyl chains of HPH-crenarchaeol has been detected. We conclude that the low incorporation rates detected suggest a slow growth of sedimentary Thaumarchaeota in contrast to other sedimentary organisms and/ or a slow turn-over of thaumarchaeotal IPL-GDGTs in contrast to bacterial/eukaryotic PLFAs. In Chapter 4 the abundance and diversity and potential activity of denitrifying and anammox bacteria, as well as of H2S dependent denitrifying bacteria in seasonally hypoxic and sulfidic sediments of saline Lake Grevelingen (The Netherlands) were studied. The depth distribution of 16S rRNA and nirS genes of denitrifying and anammox bacteria, as well as the aprA gene of sulfur oxidizing and sulfate reducing bacteria, were estimated down to 5 cm sediment depth at three different locations before (March) and during (August) summer hypoxia. The abundance of denitrifying bacteria was relatively stable, whereas anammox bacteria were more abundant and active during summer hypoxia in sediments with lower H2S concentrations, suggesting a possible inhibition of anammox bacteria by sulfide. Heterotrophic and autotrophic denitrifiers as well as anammox bacteria and SRB/SOB spatially coexist, but nirS-type denitrifiers outnumbered anammox bacteria leading to the conclusion that anammox does not contribute significantly to nitrogen removal in Lake Grevelingen sediments. The transcriptional activity of denitrifying and anammox bacteria as well as of sulfur oxidizing, including sulfide-dependent denitrifiers, and sulfate reducing bacteria was potentially inhibited by the accumulation of H2S during summer hypoxia. Both denitrifiers and anammox bacteria could be inhibited by the competition for − − NO3 and NO2 with cable and Beggiatoa-like bacteria before summer hypoxia. Results suggest that H2S detoxification mediated by sulfur oxidizers including sulfide-dependent denitrifiers is not sufficient to sustain the activity of denitrifying and anammox bacteria in Lake Grevelingen sediments. In Chapter 5 the impact of seasonal hypoxia on the activity and the community structure of 20 Introduction chemolithoautotrophic bacteria was studied in seasonally hypoxic and sulfidic sediments of saline Lake Grevelingen (The Netherlands) before (March) and during summer hypoxia (August). Combined 16S rRNA gene amplicon sequencing and PLFA analysis revealed a major temporal shift in the community structure. Aerobic sulfur oxidizing Gamma- and Epsilonproteobacteria predominated the chemolithoautotrophic community in spring, whereas Deltaproteobacteria were prevalent during summer hypoxia. Chemolithoautotrophic rates, determined by PLFA-SIP, were three times higher in spring than during summer hypoxia, especially in surface sediments. The abundance of cbbL (RuBisCO) and aclB (ATP-citrate lyase) genes revealed a predominance of microorganisms using the CBB cycle compared to the rTCA cycle independent of the season and location. Gene abundances of both, the cbbL and aclB genes decreased significantly between the seasons, suggesting that the abundance of chemolithoautotrophic bacteria using the CBB or – the rTCA cycle is inhibited by the limited availability of electron acceptors, such as O2 and NO3 , regulated by summer hypoxia. In Chapter 6 the archaeal abundance and community composition was studied in seasonally hypoxic and sulfidic surface sediments of Lake Grevelingen (The Netherlands). We combined archaeal 16S rRNA gene amplicon sequencing and the analysis of archaeal GDGT IPLs to determine the biological sources of these archaeal lipids under changing O2 and H2S conditions, before (March) and during summer hypoxia (August). In spring, the archaeal community was predominated by aerobic Thaumarchaeota, whereas during summer hypoxia, anaerobic members of the DPANN superphylum prevailed. The abundance of IPL-GDGTs decreased one order of magnitude between March and August, and polar head groups changed from phospho- to glycosidic head groups, suggesting that Thaumarchaeota might be in a stationary growth phase and/or a slow degradation of these GDGTs in the sediment. The switch from a Thaumarchaeota to a DPANN-dominated community during summer hypoxia together with a change in the lipid composition suggest that DPANN archaea may use fossil lipids found in the surface sediment to build up their membranes as they are unable to do so themselves, suggesting that DPANN archaea could be considered as important lipid recyclers in sediment systems and should be taken into account in organic geochemistry interpretations.

2. Seasonality and depth distribution of the abundance and activity of ammonia oxidizing microorganisms in marine coastal sediments (North Sea)

Yvonne A. Lipsewers, Nicole J. Bale, Ellen C. Hopmans, Stefan Schouten, Jaap S. Sinninghe Damsté, and Laura Villanueva

Microbial processes such as nitrification and anaerobic ammonium oxidation (anammox) are important for nitrogen cycling in marine sediments. Seasonal variations of archaeal and bacterial ammonia oxidizers (AOA and AOB) and anammox bacteria, as well as the environmental factors affecting these groups, are not well studied. We have examined the seasonal and depth distribution of the abundance and potential activity of these microbial groups in coastal marine sediments of the southern North Sea. This was achieved by quantifying specific intact polar lipids (IPLs) as well as the abundance and gene expression of their 16S rRNA gene, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) gene of anammox bacteria. AOA, AOB and anammox bacteria were detected and transcriptionally active down to 12 cm sediment depth. In all seasons, the abundance of AOA was higher compared to the AOB abundance suggesting that AOA play a more dominant role in aerobic ammonia oxidation in these sediments. Anammox bacteria were abundant and active even in oxygenated and bioturbated parts of the sediment. The abundance of AOA and AOB was relatively stable with depth and over the seasonal cycle, while anammox bacteria abundance and transcriptional activity were highest in August. North Sea sediments thus seem to provide a common, stable, ecological niche for AOA, AOB and anammox bacteria.

Frontiers in Microbiology 5, 472, 2014

23 Chapter 2

2.1. Introduction Nitrogen is an essential component for living organisms and thus plays a critical role in controlling primary production (Gruber & Galloway 2008). Microbial aerobic and anaerobic nitrogen cycling processes such as nitrification, denitrification and anaerobic ammonium oxidation are tightly coupled in marine sediments where 50% of marine nitrogen removal occurs (Zhang et al., 2013, and references therein). The discovery of ammonia-oxidizing archaea (AOA) (Kön- neke et al., 2005; Wuchter et al., 2006) belonging to the phylum Thaumarchaeota (Brochier-Ar- manet et al., 2008), and bacteria of the Planctomycetes phylum performing the anaerobic ammonia oxidation (anammox) reaction (Strous et al., 1999; Kuypers et al., 2003), has changed our perspective on the marine nitrogen cycle and the involved microbial key-players over the last decade. Ammonia oxidation is the first and rate-limiting step of nitrification in which ammonia is oxidized to nitrite by AOA and ammonia oxidizing bacteria (AOB) (see Prosser and Nicol, 2008 for a review). The anammox process involves the combination of ammonium with nitrite to form dinitrogen gas which is then released from the system (Kuenen et al., 2008). Several studies focusing on ammonia oxidation in marine sediments have suggested that AOA have a more prominent role in marine nitrification than AOB based on the higher abundance of AOA amoA gene copies (Beman & Francis, 2006; Mosier & Francis, 2008; Santoro et al., 2008; Abell et al., 2010). Proposed environmental controls shaping the distribution and activity of AOA in marine and estuarine surface sediments include the presence of sulfide, salinity, dissolved oxygen (DO) concentration, the availability of phosphorous, temperature and primary production (Bernhard et al., 2010; Dang et al., 2010; Erguder et al., 2009; Mosier & Francis, 2008; Sahan & Muyzer, 2008; Sakami et al., 2012; Bale et al., 2013). Beman et al. (2012) studied the seasonal distribution of AOA and AOB amoA gene abundance in Catalina Harbor down to 10 cm sediment depth and showed higher abundances of AOA and AOB amoA genes during 15 + summer compared to winter months as well as coinciding higher NH4 oxidation rates. For anammox bacteria, studies have shown that temperature, organic carbon content, nitrite concentration, water depth, sediment characteristics and bioturbation play a role in their distribution, abundance and activity in marine and estuarine sediments (Dale et al., 2009; Dalsgaard & Thamdrup, 2002b; Engström et al., 2005; Meyer et al., 2005; Dang et al., 2010; Jaeschke et al., 2009; Li et al., 2010; Zhang et al., 2013; Laverock et al., 2013; Neubacher et al., 2011, 2013). However, most of the studies have focused on the spatial distribution of anammox bacteria abundance and activity only in surface sediments (Dalsgaard & Thamdrup, 2002a; Engström et al., 2005; Thamdrup & Dalsgaard, 2002; Nicholls & Trimmer, 2009; Bale et al., 2014). Limited studies have been focused on the abundance of anammox bacteria with sediment depth or the impact of seasonality on this group (Jaechke et al., 2009; Zhang et al., 2013). Anammox bacteria abundance and activity has been previously detected using anammox specific ladderane biomarker lipids in combination with 15N-labeling experiments in continental shelf and slope sediments of the Irish and Celtic Sea down to eight centimeters depth with spatial differences (Jaeschke et al., 2009). Recently, anammox bacteria abundance was shown to be higher during summer compared to the winter months in surface sediments of three hyper-nutrified estuarine tidal flats of Laizhou Bay (Bohai Sea, China) through the quantification of anammox bacteria 16S rRNA gene (Zhang et al., 2013). A study by Laverock et al. (2013) indicated that the temporal variation in the abundance of N-cycling functional genes is directly influenced by bioturbation activity varying between different bacterial and archaeal N-cycling genes. The relative 24 Introduction/Material and Methods abundance of AOB amoA genes is significantly affected by bioturbation whereas the relative abundance of AOA amoA seems to be controlled by other factors (Laverock et al., 2013). Inter- estingly, bioturbation and mixing can extend the area of nitrate reduction in sediments leading to the production of nitrite which would fuel the anammox process (Meyer et al., 2005). The aim of our study was to determine differences in abundance and activity of ammonia oxidizers with sediment depth (down to 12 cm depth) in marine sediments from the southern North Sea, a continental shelf sea. To address this issue, we quantified the abundance of 16S rRNA gene of ammonia oxidizer groups (AOA, AOB, and anammox bacteria), metabolic genes (amoA of AOA and AOB, and hzsA gene of anammox bacteria), and the intact polar membrane lipids specific for anammox bacteria (i.e. ladderane lipids, Sinninghe Damsté et al., 2002b), and Thaumarchaeota (i.e. crenarchaeol; Sinninghe Damsté et al., 2002a). The potential transcriptional activity of the target genes was analyzed to elucidate the potential activity of the target organisms in the sediment. Our results suggest that both aerobic and anaerobic ammonia oxidizers coexist in the same niche and are actively involved in the nitrogen cycle in oxygenated and bioturbated sediments in the North Sea. 2.2. Material and Methods 2.2.1. Study site and sampling The Oyster Grounds, an almost circular depression with a maximum depth of 50 m located in the southern North Sea (Weston et al., 2008), is a temporary deposition center for sediment (Raaphorst et al., 1998), which plays an important role in the carbon and nitrogen cycle in the region (Weston et al., 2008). The sedimentation of organic matter in this region leads to organic rich and muddy sediment, which supports high levels of benthic fauna (Van Raaphorst, 1992; Duineveld, 1991). Sediment cores were collected at a station (4˚33.01’ E, 54˚13.00’ N) in the Oyster Grounds during three cruises on board of the R/V Pelagia in February, May and August 2011. Sediment was collected with 10 cm diameter multicores. Bottom water of the overlaying water was collected using a syringe and filtered (through a 0.45 µm 25 mm Acrodisc HT Tuffryn Membrane syringe filter) for nutrient analysis. The cores were sliced into 1 cm slices using a hydraulic slicer or a manual slicer. Samples were collected for lipid and DNA/RNA analysis and kept at –80ºC (DNA/RNA) and –40ºC (lipids) until processing. Bottom water temperature, water depth and salinity were measured using a SBE911+ conduc- tivity-temperature depth (CTD) system (Seabird Electronics, Inc., WA). The oxygen concentration in the water column was measured using a dissolved oxygen (DO) sensor SBE 43 (Seabird Electronics, Inc., WA) integrated in the CTD system. 2.2.2. Physicochemical parameters Pore water was extracted from 2.5 mm sediment slices from 0 to 2 cm depth, and from 1 cm sediment slices from 2–12 cm depth by centrifugation (approx. 4000 g, 5 min, through a 0.45 µm 25 mm Acrodisc HT Tuffryn Membrane syringe filter), and the obtained concentrations of the first 2 cm were averaged for the first and second centimeter of the sediment to estimate pore water nutrient concentrations in a 1 cm resolution. Pore water samples were stored in pre-rinsed + – – 3– pony vials and NH4 , NO3 , NO2 and PO4 concentrations were analyzed as described by Bale et al. (2013). The total organic carbon (TOC) and total organic nitrogen (TON) content 25 Chapter 2 per gram of freeze dried sediment were determined after acidification of freeze dried sediment (0.5−1 g) with 2N HCl. Residues were analyzed by using a Thermo Finnigan Delta plus isotope ratio monitoring mass spectrometer (irmMS) connected to a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan). 2.2.3. Intact polar lipid extraction and analysis IPLs were extracted following Bale et al. (2013). Hexose-phosphohexose (HPH) crenarchaeol, a specific biomarker lipid for AOA (Schouten et al., 2008b), was analyzed using high performance liquid chromatography mass spectrometry (HPLC/MS) as described by Pitcher et al. (2011a). Due to the lack of a standard the results are reported here as response unit per gram of sedi- –1 ment (r.u. g ). The anammox bacteria specific intact ladderane phospholipid, C20-[3]-monoether ladderane, attached to a phosphatidylcholine (PC) headgroup (PC-monoether ladderane) was analyzed by HPLC/MS following Jaeschke et al. (2009) and quantified using an external standard consisting of isolated PC-monoether ladderane. 2.2.4. DNA/RNA extraction DNA and RNA from sediment cores were extracted by using the DNA and RNA PowerSoil® Total Isolation Kit, respectively (Mo Bio Laboratories, Inc., Carlsbad, CA). Nucleic acid concentrations were quantified spectrophotometrically (Nanodrop, Thermo Scientific, Wilming- ton, DE) and checked by agarose gel electrophoresis for integrity. Extracts were kept frozen at –80°C. The RNA extracts were treated with RNase-free DNase (DNA-free™, Ambion Inc., Austin, TX). RNA quality and concentration were estimated by the Experion RNA StdSens Analysis Kit (Bio-Rad Laboratories, Hercules, CA). DNA contamination was checked by PCR using RNA as a template. 2.2.5. Reverse transcription (RT)-PCR Reverse transcription (RT) was performed with the Enhanced Avian First Strand synthesis kit (Sigma-Aldrich Co., St Louis, MO) using random nonamers as described previously (Holmes et al., 2004). Two negative controls lacking reverse transcriptase or RNA were included. PCR reactions were performed as described above to confirm the transcription to complementary DNA (cDNA) and the negative controls using the RT reaction as a template. 2.2.6. Quantitative PCR analysis Quanititative (qPCR) analyses were performed on a Biorad CFX96TM Real-Time System/ C1000 Thermal cycler equipped with CFX ManagerTM Software. Gene copy numbers of the Thaumarchaeota group 1.1a were estimated by using the 16S rRNA gene primers MCGI-391F/ MCGI-554R (Coolen et al., 2007). The AOA amoA gene was amplified using the primer combination AmoA-ModF/AmoA-ModR (Yakimov et al., 2011). Abundance of AOB 16S rRNA gene was estimated using primers CTO189F/CTO654R as described by Kowalchuk et al. (1997). Gene copy numbers of the AOB amoA gene were estimated using the primer set AOB-amoAF/ AOB-amoAR new (Rotthauwe et al., 1997; Hornek et al., 2006). Abundance of the anammox bacteria 16S rRNA gene was estimated using primers Brod541F/Amx820R as described by Li et al. (2010). Additionally, the anammox bacteria hzsA gene was quantified using the primer combination hzsA_1597F/hzsA_1857R as described by Harhangi et al. (2012) (See Table S1 for details). All qPCR reactions were performed in triplicate with standard curves from 100 to 107 molecules per microliter. Standard curves were generated as described before (Pitcher et al., 26 Material and Methods

2011b). Gene copies were determined in triplicates on diluted DNA extracts (1:10) and on complementary DNA (cDNA) extracts. The reaction mixture (25 μL) contained 1 U of PicoMaxx high fidelity DNA polymerase (Stratagene, Agilent Technologies, Santa Clara, CA) 2.5 μL of 10x PicoMaxx PCR buffer, 2.5 μL 2.5 mM of each dNTP, 0.5 μL BSA (20 mg mL–1), 0.02 pmol μL–1 of primers, 10,000 times diluted SYBR Green® (Life Technologies, Carlsbad, CA) (optimized concentration), 0.5 μL 50 mM of MgCl2 and ultra-pure sterile water. All reactions were performed in iCycler iQTM 96-well plates with optical tape (Bio-Rad, Hercules, CA). Specificity of the reaction was tested with a gradient melting temperature assay. The cycling conditions for the qPCR reaction were the following: 95°C, 4 min; 40–45 × [95°C, 30 s; melting temperature (Tm), 40 s; 72°C, 30 s]; final extension 80°C, 25 s. Specificity for qPCR reaction was tested on agarose gel electrophoresis and with a melting curve analysis (50°C–95°C; with a read every 0.5°C held for 1 s between each read) in order to identify unspecific PCR products such as primer dimers or fragments with unexpected fragment lengths. Melting temperature, PCR efficiencies (E) and correlation coefficients for standard curves are listed in Table S2. 2.2.7. PCR amplification and cloning Amplifications of the anammox bacteria 16S rRNA gene, AOA and AOB amoA genes were performed with the primer pairs specified above (Table S1). PCR reaction mixture was the following (final concentration): Q-solution (PCR additive, Qiagen, Valencia, CA) 1 ×; PCR buffer –1 –1 1 ×; BSA (200 µg mL ); dNTPs (20 µM); primers (0.2 pmol µL ); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA). PCR conditions for these amplifications were the following: 95°C, 5 min; 35 × [95°C, 1 min; Tm, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen, Valencia, CA), cloned in the TOPO-TA cloning® kit (Life Technologies, Carlsbad, CA), and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. Recombinant plasmidic DNA was sequenced using M13R (5’-CAG GAA ACA GCT ATG AC-3’) primer by Macrogen Inc. (Am- sterdam, The Netherlands). 2.2.8. Phylogenetic analysis Sequences were analyzed for the presence of chimeras using the Bellerophon tool at the Green- Genes website (http://greengenes.lbl.gov/). Sequences were aligned with Mega5 software (Ta- mura et al., 2011) by using the alignment method ClustalW. Partial sequences of the archaeal amoA gene generated in this study were added to the amoA gene reference tree provided in Pester et al. (2012) using the ARB Parsimony tool (Ludwig et al., 2004). Phylogenetic trees of AOB amoA and the anammox bacterial 16S rRNA genes were computed with the Neigh- bour-Joining method (Saitou and Nei, 1987) in the Mega5 software. The evolutionary distances were estimated using the Jukes-Cantor method (Jukes and Cantor, 1969) with a bootstrap test of 1,000 replicates. Sequences were deposited in NCBI with the following accession numbers: KJ807530–KJ807556 for partial sequences of the archaeal amoA gene, KJ807557–KJ807597 for partial bacterial amoA gene sequences and KJ807598–KJ807609 for partial anammox bacterial 16S rRNA gene sequences. 2.2.9. Statistical analysis Spearman’s rank order correlation coefficient (rs) analysis was performed using the SigmaPlotTM (12.0) Exact Graphs and Data Analysis (Systat Inc., San Jose, CA). Additional multivariate anal-

27 Chapter 2 ysis did not show additional correlations of environmental data with gene and expression data therefore results were not included in this study. 2.3. Results 2.3.1. Physicochemical conditions Oxygen concentrations of the water column corresponding to the sampling time and location of sediment core sampling are shown in Fig. S1. In February, oxygen concentrations decreased throughout the water column from 301.3 to 299 µM (300 µM on average). In May, the oxygen concentration was slightly lower compared to February (282 µM on average) and decreased between 17.8–22.8 m water depth from about 287 to 278 µM. Lowest oxygen concentrations were detected in August compared to February and May (230 µM on average) and decreased between 17.8–24.8 m water depth from 242 to 217.25 µM. Physicochemical parameters of the bottom water during the cruises of February (winter), May (spring) and August (summer) are shown in Table S3. Bottom water temperatures ranged from 5 to 15.4˚C. Salinity values were stable throughout the year ranging from 34.3–34.7 practical sa- + linity units (psu). Ammonia (NH4 ) concentrations in the bottom water ranged between 1.6 and – 3 µM with a maximum concentration in February. Bottom water nitrite (NO2 ) concentrations – varied from 0.6 µM in February to 0.1 µM in May and August. Highest nitrate (NO3 ) concentrations were detected in February (1 µM) and lowest in August (0.5 µM). + Pore water concentrations of NH4 ranged between 3–53 µM in all three seasons (Fig. 1). The depth trend of ammonia concentrations in the pore water was similar in all seasons with lower concentrations in the upper 4 cm of the sediment (3–34 µM) compared to increasing concen- + trations of the underlying layers (20–53 µM) down to 12 cm sediment depth. Highest NH4 concentrations were detected in August (40–53 µM) compared to February and May. Nitrite – (NO2 ) concentrations ranged between 0.1–1.2 µM in all seasons (Fig. 1). Depth profiles of pore water nitrite concentrations showed different seasonal trends. In February, nitrite concentrations were relatively low (0.3 µM) in the first 3 cm of the sediment and increased with depth (0.6 µM) whereas in May and August, nitrite concentrations were higher between 1–2 cm sediment depth (0.8 µM) compared to the underlying sediment layers (0.4 and 0.2 µM, respectively). Pore water – nitrate (NO3 ) concentrations strongly varied with sediment depth and season (Fig. 1). In Feb- ruary and May, nitrate concentrations were highly variable with depth and reached maximum values between 3−4 cm (38 µM) and 4−5 cm of the sediment (24 µM), while the concentration strongly decreased in the underlying layers. In August, lower nitrate concentrations were detected compared to the other seasons with slightly elevated values in the first 2 cm of the sediment (7.3 µM) and lower concentrations in the underlying layers (1.3 µM). Phosphate concentrations ranged between 1.4–5.2 µM in all seasons (Fig. 1). Pore water phosphate concentrations were stable in the first 4 cm of the sediment (1.7 µM, averaged) in all three seasons. In February and May, phosphate concentrations increased slightly (3.4 µM, averaged) in the underlying sediment layers whereas the depth profile remained stable in August. TOC and TON percentages of the sediment were relatively stable in all seasons (between 0.15–0.38% and 0.02–0.08% respectively), with highest values in May between 1–2 cm and 4–5 cm sediment depth (Table S4). 2.3.2. Abundance, distribution, activity and diversity of AOA and AOB The abundance of AOA in the sediments was determined by quantification of the 16S rRNA 28 Material and Methods/Results

+ – – 3+ Figure 1: Sediment pore water nutrients: A) NH4 ; B) NO2 ; C) NO3 and D) PO4 [µM] with sediment depth [cm] below sea floor [bsf]. and amoA gene copies, as well as by quantification of HPH-crenarchaeol (Figs. 2A–C Table S5). The seasonal variations in depth profiles of AOA 16S rRNA and amoA gene abundance were generally similar (Figs. 2A, B). Both AOA gene abundances were higher between 0−5 cm (6 × 106 and 1.4 × 107 gene copies g–1, respectively) compared to 5−12 cm of the sediment (5 × 106 and 8.2 × 106 gene copies g–1, respectively). Gene copy numbers of the AOA amoA gene were higher in August in comparison to the values observed in February and May (1.4-fold and 2.7- fold higher, respectively) for the 0–5 cm interval. HPH-crenarchaeol concentration was variable over the first 5 cm of the sediment (between 3 × 106–17 × 106 r.u. g–1), but stable values (around 5.9 × 106 r.u. g–1) were detected in the layers underneath. No clear seasonal differences were detected (Fig. 2C). The abundance of AOB was determined by quantifying the AOB 16S rRNA and amoA gene (Figs. 2D, E). Values were relatively stable with depth with seasonal variations between 0–4 cm of the sediment. Abundance of the AOB 16S rRNA gene showed values similar to the AOA 16S rRNA gene abundance in February and August (on average 5.1 × 106 and 5.8 × 106 gene copies g–1, respectively), while in May AOB 16S rRNA gene copy numbers were lower on average compared to the AOA 16S rRNA gene copy number (4.0 × 106 gene copies g–1, 1.4-fold lower). The AOB amoA gene abundance followed the same seasonal trends as that of the AOB 16S rRNA gene, AOA 16S rRNA and amoA gene abundances, with higher values in August, but absolute values were one order of magnitude lower than AOA amoA gene copy numbers (2.3 × 105–5.2 × 106 gene copies g–1). AOB amoA gene abundance was highest in the 0−5 cm depth interval except in May when values between 2−5 cm and in the 5−12 cm depth interval were lower than in the surface sediment. 29 Chapter 2

Figure 2: Abundance of A) AOA 16S rRNA gene [copy number g–1]; B) AOA amoA gene [copy number g–1]; C) Hexose phosphohexose (HPH)-crenarchaeol [response units g–1], and D) AOB 16S rRNA gene [copy number g–1]; E) AOB amoA gene [copy number g–1] with sediment depth [cm] below sea floor [bsf].

The RNA:DNA ratios of the AOA and AOB 16S rRNA and amoA genes were calculated as an indicator of the potential transcriptional activity of the targeted microbial group (Figs. 3A– F).In all three seasons, AOA 16S rRNA gene RNA:DNA ratio showed relatively stable values down core ranging between 0.9–5.0 and 1.2–3.4 in May and August but reached slightly higher values (2.2–8.2) in February (Fig. 3A). AOB 16S rRNA gene RNA:DNA ratio was between 0.1–2.1 with a minimum of 0.1 between 4−5 cm of the sediment in February and 0.1–3.7 with a minimum between 2−3 cm sediment depth in May. The AOB 16S rRNA gene RNA:DNA ratio was slightly higher (1.2–4.1) in August (Fig. 3C). Values were relatively stable with depth in August whereas in February and May values were more variable. Compared to the RNA:DNA ratio of the AOA 16S rRNA gene, the AOB 16S rRNA gene RNA:DNA ratio was lower (5-fold in February, 1.5-fold in May and 1.3-fold lower in August) in all seasons (Figs. 3A, C). AOA amoA gene transcripts (Fig. 3B) were only detected in February in the first 3 cm and in August throughout the core, and were under the detection limit in May. AOB amoA gene RNA:DNA ratio (Fig. 3D) varied between 4 × 10–5–2 × 10–2 in all seasons with a slight decrease with depth and highest values in August. The diversity of AOA and AOB was evaluated in two selected depth intervals (0–1 and 9–10 cm sediment depth) of the sediment core recovered in August by targeting the AOA amoA gene and the AOB amoA gene, respectively (Figs. S2, S3). Amplified AOAamoA gene sequences were closely related to AOA amoA gene sequences previously isolated from marine and estuarine environments and did not cluster according to depth (Figs. S2A, B). Sequences were mainly affiliated to the Nitrosopumilus subclusters 12 and 16, also known as the stable marine cluster, or to 30 Results

Figure 3: Transcriptional activity given as RNA:DNA ratio of A) AOA 16S rRNA gene; B) AOA amoA gene; C) AOB 16S rRNA gene, D) AOB amoA; E) Anammox 16S rRNA gene, and F) Anammox bacteria hzsA gene with sediment depth [cm] below sea floor [bsf]. the Nitrosopumilus subcluster 4.1, known as the estuarine cluster, according to the phylogenetic classification proposed by Pester et al. (2012). The AOBamoA gene sequences were affiliated to AOB amoA gene sequences previously isolated from estuarine sediments. Sequences were closely related to the AOB amoA gene sequences of Nitrospira sp. (accession number X90821) and Nitrosolobus multiformis (accession number AF042171). No clustering of AOB amoA sequences according to depth was observed (Fig. S3). 2.3.3. Abundance, distribution, activity and diversity of anammox bacteria The abundance and distribution of anammox bacteria were estimated by quantification of anammox bacteria 16S rRNA and hzsA gene copy number, as well as by quantification of the PC-monoether ladderane (Figs. 4A–C). Depth profiles of anammox bacteria 16S rRNA and hzsA gene abundances followed similar trends. Gene copy numbers of the hzsA gene were one order of magnitude lower (between 3.5 × 105 and 2 × 106 copies g–1) than anammox bacteria 16S rRNA gene copy numbers in all three seasons (Figs. 4 A, B). Values were higher in August compared to those in February and May, especially for the anammox bacteria 16S rRNA gene (3.7-fold higher). The RNA:DNA ratio for the anammox bacteria 16S rRNA gene varied between 1.6–34.6 (Fig. 3E) with higher values in August compared to February and May (on average 4-fold higher). The hzsA gene RNA:DNA ratio (Fig. 3F) depth profiles showed relatively stable values (between 0.008–0.125) throughout the core without significant seasonal differences. The PC-monoether ladderane concentration (Fig. 4C) was variable over the first 5 cm of the sediment (between 0.25–1.25 ng g–1), while in the underlying sediment layers values decreased slightly to more stable

31 Chapter 2

Figure 4: Abundance of A) Anammox bacteria 16S rRNA gene [copy number g–1]; B) Anammox bacteria hzsA gene [copy number g–1], and C) PC-monoether ladderane [ng g–1] with sediment depth [cm] below sea floor [bsf]. values (approximately 0.36 ng g–1) down to 12 cm sediment depth. There was no clear seasonal difference observed. The diversity of anammox bacteria was evaluated in two selected depths (0–1 and 9–10 cm) of the sediment core in August by targeting the 16S rRNA gene of anammox bacteria. The sequences were closely related to “Candidatus Scalindua marina” (accession number EF602038) and “Candidatus Scalindua brodae” (accession number AY254883) and to sequences previously detected in waters of marine oxygen minimum zones (Woebken et al., 2008). Anammox bacterial 16S rRNA gene sequences from different depths were closely related to each other (Fig. S4). 2.4. Discussion 2.4.1. Aerobic ammonia oxidizers In this study, we defined two niches in the Oyster Grounds sediment based on the differences in physicochemical parameters and in the abundance of the target organisms, i.e. the upper 4 cm of the sediment, and the underlying sediment. Ammonia concentration in the pore water of the upper part of the sediment (0–4 cm) was consistently lower than in deeper sediment layers (4–12 cm) (Fig. 1), suggesting ammonia diffusion from below formed by mineralization of organic matter by ammonification or dissimilatory nitrate reduction to ammonium (DNRA). In addition, the abundance of AOA and AOB (as well as anammox bacteria, see below) was higher and more affected by seasonality in the upper part than deeper in the sediment, which apparently is a more stable compartment. The higher variability observed in the upper part of the sediment is in agreement with the seasonal mixing of the bottom water layers and sediment deposition 32 Results/Discussion dynamics in this area (Greenwood et al., 2010). Oxygen availability is expected to play an important role in the dynamics of ammonia oxidizing microorganisms in marine sediments. In the summer months, water stratification leads to a decrease in the dissolved oxygen concentration in the bottom water in the Oyster Grounds area (Greenwood et al., 2010) (see Fig. S1). Indeed, bottom water hypoxia has been shown to cause a decrease in oxygen penetration depth and oxygen consumption in Oyster Grounds sediments by induced short-term hypoxia in intact sediment cores (Neubacher et al., 2011). Lohse et al. (1996) reported an oxygen penetration depth (OPD) of 1.7 cm in February and 0.5 cm in August in sediment at a station close to the Oyster Grounds using oxygen microelectrodes, suggesting permanently anoxic conditions from a depth of approximately >2 cm throughout the year. How- ever, the OPD into the sediment must be interpreted with caution because the Oyster Grounds sediment is known to be an area of intense bioturbation by macro- and meiobenthos even in periods of low oxygen concentration in the bottom water (De Wilde et al., 1984; Duineveld et al., 1991), thus the import of oxygen by macrofaunal burrows into the deeper sediment could be relevant (Kristensen, 2000; Meysman et al., 2006). A study by Laverock et al. (2010) has also shown that bioturbation can induce changes in the microbial community composition, resulting in distinct communities within the burrow. However, in our study we did not observe changes in the diversity of amoA gene sequences of AOA or AOB, which might indicate that the changing physicochemical conditions in this system do not select for specific ammonia oxidizing microorganisms. The depth and seasonal variability for AOB was more pronounced than for AOA in the first 4 cm of the sediment, which is consistent with the fact that the relative abundance of AOB is more significantly affected by bioturbation than AOA according to previous studies (Laverock et al., 2013). AOA and AOB 16S rRNA and amoA genes and AOA-IPLs and were detected up to 12 cm depth in Oyster Grounds sediments. The detection of aerobic ammonia oxidizing microorganisms in marine sediment at depths where the oxygen concentration is expected to be undetectable seems counterintuitive with their aerobic metabolism. However, the intense bioturbation reported in the Oyster Grounds sediments, as mentioned above, might provide enough oxygen to support the activity of these microbial groups. In fact, Beman et al. (2012) detected AOB and 15 + AOA amoA genes up to 10 cm sediment depth as well as readily detectable NH4 oxidation – rates up to 9 cm sediment depth with maxima overlapping with a peak in pore water NO3 + – NO2 concentrations between 3–7 cm sediment depth in bioturbated sediments of Catalina Island (CA, USA) . Thus, our results, and those of Beman et al. (2012), suggest that aerobic ammonia oxidizers are indeed living and actively involved in the marine sedimentary nitrogen cycle deeper (i.e. up to at least ca. 10 cm) in coastal marine sediments. The detection of a potential transcriptional activity of the AOA 16S rRNA gene up to 12 cm depth supports that AOA are indeed active deeper in the marine sediment. The potential AOA 16S rRNA gene transcriptional activity was higher during winter, whereas the abundance was slightly higher during summer months. Previous studies showed higher AOA abundance during winter months in the in the North Sea water column (Wuchter et al., 2006; Herfort et al., 2007; Pitcher et al., 2011c) attributed to the higher availability of ammonia and the lack of competition for ammonia with phytoplankton. However, none of these studies targeted the transcriptional activity of AOA. Recently, Bale et al. (2013) observed that the abundance of the benthic Thaumarchaeota (given by HPH crenarchaeol) in the surface sediment (0–1 cm) at the 33 Chapter 2

Oyster Grounds was on average highest in the summer (August) and lowest in the winter (No- vember), which they attributed to the deposition of algal-bloom-derived organic matter taking place in late spring and summer resulting in the formation of ammonia. However, it should also be noted that Bale et al. (2013) did find that transcriptional activity of the AOA 16S rRNA gene was higher during winter in the surface sediment. The disparity in seasonality between the results of these two studies highlights the difference between the seasonal ammonia dynamics at the surface sediment/water interface (Bale et al., 2013) and with depth in the sediment (this study). To complement the determination of potential transcriptional activity of AOA based on 16S rRNA gene, we also determined the AOA amoA gene RNA:DNA ratio, which was possible for samples from August throughout the core but only in the upper 3 cm depth in February because the quantity of transcripts in the other seasons and depths was under the detection limit of the qPCR assay. The relationship of amoA gene expression and in situ ammonia oxidation is still unclear (Lam et al., 2007; Nicol et al., 2008; Abell et al., 2011; Vissers et al., 2013). However, recent studies have observed a good correlation between nitrification rates and abundance of AOA amoA gene and transcripts in coastal waters (Urakawa et al., 2014; Smith et al., 2014). Therefore, the detection of AOA amoA transcripts in our setting suggests that AOA were active in the summer throughout the sediment in comparison with the winter in which AOA would be only active in the upper part of the sediment (upper 2 cm). AOB 16S rRNA gene abundance was in the same order of magnitude than AOA 16S rRNA gene abundance, however, AOB amoA gene abundance was one order of magnitude lower than AOA amoA gene abundance, which can be explained by biases introduced by the primers or by differences in copy number of 16S rRNA and amoA genes per cell. In fact, it is assumed that 3.3 ± 1.6 copies of 16S rRNA can exist per cell in AOB (Větrovský et al., 2013), whereas marine Crenarchaeota seem to contain only one copy per genome (Klappenbach et al., 2001; Laverock et al., 2013). For the amoA gene it is assumed that AOB genomes contain 2 to 3 copies (Arp et al., 2007) while AOA genomes contain only one copy. In addition, the transcriptional activity of the AOB 16S rRNA gene was lower compared to the one of AOA 16S rRNA gene in all seasons. On the other hand, the abundance of AOB amoA gene transcripts was higher than for AOA and was detected up to 12 cm depth in all seasons which would suggest a higher AOB activity vs AOA. However, a recent study by Urakawa et al. (2014) in water of the Puget Sound Estuary did not observe a correlation between nitrification rates and AOBamoA transcripts. In addition, previous studies have detected the presence of AOB amoA transcripts in non-active starved cells (Bollmann et al., 2005; Geets et al., 2006; Ward et al., 2011) indicating that the AOB amoA transcriptional activity is not a good indicator of AOB nitrification activity due to a longer half-life of AOB amoA transcripts than that expected for AOA amoA transcripts. Taking together the AOA and AOB amoA gene quantification results, AOA have a more important role in the nitrification process in Oyster Grounds sediments than AOB. In addition, all available evidence points to the presence of some oxygen deeper in the sediments of the Oyster Grounds in all seasons probably due to the intense bioturbation in the area, which favors the activity of both AOB and AOA. In the case of AOA, and due to their higher affinity for oxygen (Martens-Habbena et al., 2009), the niche occupancy of AOA could be potentially larger than for AOB.

34 Discussion

Previous studies observed a positive correlation between AOA abundance and low phosphate concentrations and suggested that phosphate plays a role in determining the niches of Thau- marchaeota (Dang et al., 2013; Erguder et al., 2009). In our study, AOA amoA gene transcript copy number and RNA:DNA ratio was negatively correlated with phosphate (rs= –0.745 and –0.739 respectively; both P ≤ 0.005) suggesting a lower expression of the AOA amoA gene with an increase in pore water phosphate concentrations. These results support the assumption that some ecotypes of AOA dominate over AOB in environments with low phosphate availability. Previously, homologues of the pst gene, encoding for the Pst phosphate ABC transporter, which is usually activated in phosphate deficient environments, was found in marine metagenomes of thaumarchaeotal origin (Rusch et al., 2007; Dang et al., 2013) emphasizing the importance of phosphate availability in marine environments. No correlations were found between AOB abundance or transcriptional activity with pore water nitrogen species, but a negative correlation with the sediment depth (rs= –0.646; P ≤ 0.005) was observed indicating that sediment depth is a factor determining the AOB abundance and activity in Oyster Grounds sediments which might be explained by the decreasing oxygen availability with depth. 2.4.2. Anaerobic ammonia oxidizers Anammox bacteria 16S rRNA and hzsA gene abundance was detected throughout the analyzed sediment with more pronounced depth and seasonal differences than those observed for AOA and AOB. This was not reflected in the abundance of PC-monoether ladderane lipid. It is possible that the PC-monoether ladderane is partly derived from fossil material and thus reflects a long-term presence of anammox bacteria averaged throughout the entire year rather than an actively living anammox population. This possibility has been already suggested by Bransdsma et al. (2011) and Bale et al. (2014) who found dissimilarities between the PC-monoether ladderane concentration and gene copy numbers in surface sediments of the Gullmar Fjord and the Southern North Sea, respectively. We also observed an up to 10-fold difference in the quantification of anammox bacteria 16S rRNA and hzsA gene abundance (Figs. 4A, B). This discordance between the anammox bacteria gene markers has been previously observed in environmental samples (Harhangi et al., 2012), and it could be due to primer biases as previously suggested (Bale et al., 2014). Both the anammox 16S rRNA and the hzsA gene revealed a higher abundance in August compared to February and May. This may indicate that anammox bacteria are more active and abundant at higher temperatures (15˚C), which is the anammox bacteria temperature optimum in temperate shelf sediments (Dalsgaard and Thamdrup, 2005). Additionally, the oxygen penetration depth is expected to decrease during water stratification between May and October, which would also favor anammox bacterial growth and activity (Dalsgaard and Thamdrup, 2002). Previous studies by Neubacher et al. (2013) observed an increase in anammox activity up to 82% compared to control treatments in mesocosms under sustained hypoxic conditions, which corresponds well with our findings of high anammox activity during summer stratification associated with lower oxygen concentrations in the bottom water (Fig. S1). The presence of anammox markers in the upper layers of the sediment (0–4 cm) is remarkable as the metabolism of anammox bacteria is expected to be incompatible with the presence of oxygen. However, some studies have reported that anammox bacteria can cope with low oxygen concentrations (Kalvelage et al., 2011; Yan et al., 2012), and that anammox bacteria can

35 Chapter 2 be present and active at high oxygen levels by being dormant or using anaerobic niches (Kuypers et al., 2005; Woebken et al., 2007). It is also possible that a high activity of AOA and AOB and heterotrophic bacteria inhabiting these marine sediments would rapidly consume the oxygen available and allow the activity of anammox bacteria even in presence of oxygen. Some studies have also concluded that the potential for anammox bacteria activity is indeed not affected by bioturbation or physical mixing (Rooks et al., 2012). On the contrary, bioturbation and mixing can extend the area of nitrate reduction and thus the availability of nitrite, which fuels the anammox process (Meyer et al., 2005). Our results thus suggest that anammox bacteria can tolerate the presence of oxygen and co-exist with aerobic ammonia oxidizers and potentially have an important role in the nitrogen cycle in marine sediments. In fact, the potential transcriptional activity of anammox bacteria 16S rRNA and hzsA gene was observed throughout the sediment in all seasons. The transcriptional activity of anammox bacteria 16S rRNA gene was higher in the summer as observed for the anammox bacteria abundance. A recent study by Bale et al. (2014) observed a good correlation between the rate of anammox and anammox bacteria 16S rRNA gene transcript abundance in North Sea sediments, which suggests that the transcriptional activity of anammox bacteria 16S rRNA gene is a good proxy of anammox bacteria activity, and confirm a higher anammox activity in the summer for the sediments analyzed in our study. Nevertheless, quantification results of anammox bacteria 16S rRNA gene transcripts have to be interpret with caution because there is evidence that the ribosome content does not decrease during the period of starvation (Schmid et al., 2005; Li et al., 2011). However, the increase of anammox bacteria 16S rRNA gene transcriptional activity during summer was not observed for the hzsA gene, which remained stable across sediment depth and also for the different seasons, and gene abundances were generally an order of magnitude lower. The low and constitutive transcriptional activity of the hzsA gene indicates that the hzsA gene transcript abundance does not reflect variations of anammox bacteria activity in environmental sediment samples, thus the hzsA gene transcript abundance does not seem to be an adequate biomarker for the estimation of the activity of anammox bacteria. Further experiments, especially with pure cultures and under controlled physiological conditions, should be performed to clarify the regulation of the expression of the hzsA gene. No evidence of a niche separation of aerobic and anaerobic ammonia oxidizers was observed in the oxygen transition zone of the marine sediments. Surprisingly, aerobic and anaerobic ammonia oxidizers are present and active throughout the year in oxygenated sediment layers as well as in anoxic layers. These results seem to be counterintuitive with regards to the individual oxygen requirements of the targeted microbial groups. We hypothesize that the presence and activity of aerobic ammonia oxidizers (AOA, AOB) is supported by the oxygen supply in deeper anoxic layers due to bioturbation. Likewise, the presence and activity of anammox bacteria in these sediments is then possible by the rapid consumption of oxygen by aerobic ammonia oxidizers and/or other groups, as well as the availability of nitrite provided either by ammonia oxidizers or by an active nitrate reduction present in bioturbated sediments (Meyer et al., 2005). 2.5. Conclusion Our study has unraveled the coexistence and metabolic activity of AOA, AOB, and anammox bacteria in bioturbated marine sediments of the North Sea, leading to the conclusion that the metabolism of these microbial groups is spatially coupled based on the rapid consumption of

36 Discussion/Cocnlusion oxygen that allows the coexistence of aerobic and anaerobic ammonia oxidizers. AOA outnumbered AOB throughout the year which may be caused by the higher oxygen affinity of AOA compared to AOB. Anammox bacterial abundance and activity were higher during summer, indicating that their growth and activity are favored by higher temperatures and lower oxygen available in the sediments due to summer stratifying conditions in the water column. During the summer, anammox bacteria are probably not in competition with AOA and AOB for ammonia as the concentrations were relatively high in the sediment pore water most likely as a result of ammonification processes and the activity of denitrifiers and DNRA. Further studies are required to get a complete picture of the nature of these interactions in the oxygen transition zone of coastal marine sediments.

Acknowledgements We thank the captain and crew of the R/V Pelagia for logistic support and E. Panoto, J. van Bleijswijk, H. Witte, and A. Mets for technical support. We thank J. van Oijen and S. Ossebaar for nutrient sample collection and analysis. We thank T. Richter for providing and discussing the CTD data. This work was supported by a grant to J. S. Sinninghe Damsté from the Dutch Orga- nization for Scientific Research (NWO) (NICYCLE; 839.08.331) and a grant to Y.A. Lipsewers (grant number 3062) of the Darwin Center for Biogeosciences.

37 Chapter 2

Figure S1: Oxygen profiles [µM] of the water column in February, May and August.

38 Supplementary Material

84 Nitrosopumilus subcluster 9 uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine 16 Nitrosopumilus subcluster 1 uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured archaeon, Nitrosopumilus cluster, coral Nitrosopumilus maritimus SCM1, Nitrosopumilus cluster, marine uncultured archaeon, Nitrosopumilus cluster, marine uncultured ammonia−oxidizing, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, estuary Marine metagenome ctg_1101668569825, Nitrosopumilus cluster uncultured crenarchaeote, Nitrosopumilus cluster, freshwater uncultured crenarchaeote, Nitrosopumilus cluster uncultured archaeon, Nitrosopumilus cluster, freshwater uncultured crenarchaeote, Nitrosopumilus cluster, freshwater uncultured archaeon, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, sponge uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine 1cm 1 uncultured crenarchaeote, Nitrosopumilus cluster, estuary 5 Nitrosopumilus subcluster 10 uncultured archaeon, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured archaeon, Nitrosopumilus cluster, coral uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment uncultured archaeon, Nitrosopumilus cluster, marine uncultured crenarchaeote, Nitrosopumilus cluster uncultured crenarchaeote, Nitrosopumilus cluster 4 Nitrosopumilus subcluster 11 uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, estuary uncultured crenarchaeote, Nitrosopumilus cluster, wastewater uncultured crenarchaeote, Nitrosopumilus cluster uncultured crenarchaeote, Nitrosopumilus cluster, marine 25 Nitrosopumilus subcluster 12, Oyster Grounds sediment, 8 seq 1cm, 12 seq 10 cm 1cm 3 1cm 4 uncultured archaeon, Nitrosopumilus cluster, marine uncultured archaeon, Nitrosopumilus cluster, coral uncultured ammonia−oxidizing, Nitrosopumilus cluster, aquarium biofilter uncultured crenarchaeote, Nitrosopumilus cluster, estuary 4 Nitrosopumilus subcluster 13 uncultured crenarchaeote, Nitrosopumilus cluster, estuary 7 Nitrosopumilus subcluster 14

26 Nitrosopumilus subcluster 2

8 Nitrosopumilus subcluster 15 13 Nitrosopumilus subcluster 3 uncultured crenarchaeote, Nitrosopumilus cluster, sponge uncultured crenarchaeote, Nitrosopumilus cluster, sponge uncultured crenarchaeote, Nitrosopumilus cluster, sponge 7 Nitrosopumilus subcluster 16, Oyster Grounds sediment, 1 seq 1 cm 23 Nitrosopumilus subcluster 4, Oyster Grounds sediment 3 seq 1 cm

21 Nitrosopumilus subcluster 5 uncultured crenarchaeote, Nitrosopumilus cluster, sponge 14 Nitrosopumilus subcluster 6

36 Nitrosopumilus subcluster 7 uncultured crenarchaeote, Nitrosopumilus cluster, sponge uncultured crenarchaeote, Nitrosopumilus cluster, marine uncultured ammonia−oxidizing, Nitrosopumilus cluster, aquarium biofilter uncultured crenarchaeote, Nitrosopumilus cluster, wastewater uncultured crenarchaeote, Nitrosopumilus cluster, wastewater 28 Nitrosopumilus subcluster 8

39 Nitrosotalea cluster 2 Nitrosocaldus cluster

315 Nitrososphaera cluster

0.10 14 Nitrososphaera sister cluster 8 bacterial amoA

Figure S2A: Phylogenetic tree of AOA amoA gene sequences retrieved in this study and closest relatives (Bold: sequences retrieved at 1cm sediment depth and sequences retrieved at 10 cm sediment depth; Au- gust 2011 and clusters containing sequences retrieved in this study, find details in Fig. S2B); the scale bar indicates 10% sequence divergence. 39 Chapter 2

Nitrosopumilus subcluster 12

10cm 10 1cm 6 1cm 12 10cm 3 1cm 7 10cm 6 1cm 2 10cm 13 uncultured crenarchaeote, Nitrosopumilus subcluster 12, marine 10cm 2 1cm 9 10cm 14 10cm 12 1cm 15 10cm 15 1cm 14 10cm 7 10cm 9 10cm 1 10cm 11 1cm 8 uncultured crenarchaeote, Nitrosopumilus subcluster 12, marine uncultured archaeon, Nitrosopumilus subcluster 12, marine uncultured archaeon, Nitrosopumilus subcluster 12, marine

Nitrosopumilus subcluster 16 uncultured crenarchaeote, Nitrosopumilus subcluster 16, marine uncultured crenarchaeote, Nitrosopumilus subcluster 16, marine uncultured ammonia−oxidizing, Nitrosopumilus subcluster 16, aquarium biofilter uncultured archaeon, Nitrosopumilus subcluster 16, marine uncultured crenarchaeote, Nitrosopumilus subcluster 16, marine 10cm 5

Nitrosopumilus subcluster 4 1cm 13 1cm 5 1cm 10 10cm 8 uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marine uncultured ammonia−oxidizing, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marine uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marine uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marine uncultured ammonia−oxidizing, Nitrosopumilus subcluster 4.1, estuary uncultured ammonia−oxidizing, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marine uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1 uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, wastewater uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary uncultured crenarchaeote, Nitrosopumilus subcluster 4, estuary 0.10

Figure S2B: Phylogenetic tree of AOA amoA gene sequences retrieved in this study and closest relatives (Bold: sequences retrieved at 1cm sediment depth and sequences retrieved at 10 cm sediment depth; Au- gust 2011) the scale bar indicates 10% sequence divergence. 40 Supplementary Material

59 10cm 10cm 10cm 10cm 10cm 66 10cm 10cm 10cm 94 1cm 65 10cm 10cm 10cm 1cm 55 KC736030.1 Uncultured Nitrosomonadaceae bacterium clone (Yangtze estuary sediments) HM364248.1 Uncultured bacterium clone (estuary sediments Elkhorn Slough CA) 56 HM364256.1 Uncultured bacterium clone (estuary sediments Elkhorn Slough CA) AY736864.1 Uncultured ammonia-oxidizing bacterium clone (Monterrey Bay CA) 10cm 96 57 HQ247909.1 Uncultured ammonia oxidising bacterium clone (estuarine sediment) 77 1cm 10cm 1cm 62 10cm 10cm 93 JQ010925.1 Uncultured beta proteobacterium clone (sediment China East Sea) 91 EU244548.1 Uncultured bacterium clone (sediments Jiaozhou Bay China) 86 AB373459.1 Uncultured ammonia-oxidizing bacterium clone (aquarium biofilter) AB373510.1 Uncultured ammonia-oxidizing bacterium clone (aquarium biofilter) KC735937.1 Uncultured Nitrosomonadaceae bacterium clone (Yangtze estuary sediments) 79 1cm 68 JQ638783.1 Uncultured beta proteobacterium clone (estuarine sediment) 1cm 1cm 79 84 78 10cm 10cm AY785983.1 Uncultured beta proteobacterium clone (Guaymas Basin hydrothermal plumes particle attached) 1cm 100 76 1cm 1cm 55 1cm 1cm 89 10cm 95 1cm 60 10cm 100 1cm 1cm 98 10cm 50 JQ345981.1 Uncultured bacterium clone (sediment of Chongming eastern tidal flat) 95 JX465211.1 Uncultured ammonia-oxidizing bacterium clone (Laizhou Bay sediment) 1cm 50 51 1cm 57 10cm 100 10cm 65 10cm 10cm X90821.1 Nitrosospira sp. 100 AF042171.1 Nitrosolobus multiformis AJ388578.1 uncultured proteobacterium clone (water column freshwater lake Medemblik) 97 AF272406.1 Nitrosomonas oligotropha AF272398.1 Nitrosomonas halophila 100 U51630.1 Nitrosomonas eutropha 99 L08050.1 Nitrosomonas europaea

0.05

Figure S3: Phylogenetic tree of AOB amoA gene sequences retrieved in this study; the scale bar indicates 5% sequence divergence.

41 Chapter 2 (Candidatus Scalindua brodae) Candidatus Scalindua (uncultured Planctomycetales bacterium) Candidatus Scalindua (uncultured anaerobic ammonium-oxidizing bacterium) (Candidatus Scalindua marina) Candidatus Scalindua (uncultured planctomycete) Candidatus Scalindua (uncultured Planctomycetales bacterium) Candidatus Scalindua (uncultured bacterium) Candidatus Scalindua (uncultured Planctomycetales bacterium) 1.1 Candidatus Scalindua (uncultured planctomycete) EU478659.1 EU039843.1 Candidatus Scalindua HQ163732.1 EU478640.1 GQ35071 EU491842.1 EU478626.1 80 Candidatus Scalindua Y254883.1 A

1cm EF602038.1 1cm 50 1cm 50 1cm 74 10cm 10cm 1cm 10cm 10cm 0.002 10cm 1cm 1cm 68 Figure tree of S4: Phylogenetic in this study; the scale bar indicates 0.2% sequence divergence. bacteria 16S rRNA gene sequences retrieved anammox 42 Supplementary Material (2006) (2007) (2010) Li et al. al. (2012) al. (2011) Rotthauwe Rotthauwe × [95˚C 30 s, × [95˚C 30 s, Kowalchuk Kowalchuk Yakimov et Yakimov et al. (1997) Harhangi et Reference et al. (1997), Coolen et al.

Hornek et al. 260 279 163 465 491 626 Amplicon size [bp*] size m T qPCR qPCR 61.6˚C 59.5˚C PCR 55˚C PCR 58˚C PCR 58˚C qPCR 51˚C qPCR 59˚C qPCR 61˚C qPCR 60˚C † † ) 40 s, 72˚C 1 min]; 72˚C 5 min; qPCR conditions: 95˚C 4 min; 40 72˚C 1 min]; 5 min; qPCR conditions: 95˚C 4 ) 40 s, m Primer pair The primer contains an equimolar mixture of forward the reported primers. forward † hzsA_1597F (5’-WTYGGKTATCARTATGTA-3’) MCGI-554R (5’-TGACCACTTGAGGTGCTG-3’) AmoA-ModR (5’-GCCATCCATCTGTAWGTC-3’) AOB-amoAF (5’-GGGGTTTCTACTGGTGGT-3’) AOB-amoAF Brod541F (5’-GAGCACGTAGGTGGGTTTGT-3’) AmoA-ModF (5’-GGTCTGGYTWAGACGATG-3’) Amx820R (5’-AAAACCCCTCTACTTAGTGCCC-3’) hzsA_1857R (5’-AAABGGYGAATCATARTGGC-3’) CTO654R (5’-CTAGCYTTGTAGTTTCAAACGC-3’) MCGI-391F (5’-AAGGTTARTCCGAGTGRTTTC-3’) CTO189F_A (5’-GGAGRAAAGCAGGGGATCG-3’) CTO189F_C (5’-GGAGGAAAGTAGGGGATCG-3’) AOB-amoAR new (5’-CCCCTCBGSAAAVCCTTCTTC-3’) new AOB-amoAR × [95˚C 1 min, melting temperature (T gene

base pairs (bp); * gene gene

gene Target hzsA 16S rRNA AOB amoA AOB AOA amoA gene Anammox bacteria Anammox Anammox bacteria Anammox AOA 16S rRNA AOA AOB 16S rRNA gene AOB Primer pairs described in the text, polymerase chain reaction (PCR) conditions and amplicon size used in this study. Primer pairs described in the text, polymerase chain

qPCR qPCR qPCR PCR/ PCR/ PCR/ 40 s, 72˚C 30 s]; 80˚C 25 s; 40 s, Assay cloning cloning cloning m qPCR + qPCR + qPCR + Table S1: Table PCR conditions: 95˚C 5 min; 40 T 43 Chapter 2 2 R 0.993 0.994 0.998 0.998 0.996 0.997 0.993 0.989 0.995 0.994 0.999 0.999 91.0 85.4 84.0 86.6 80.4 80.1 98.9 96.4 97.8 97.2 94.3 106.8 E [%] [˚C] m 61.6 61.6 60.0 60.0 51.0 59.0 51.0 59.0 59.5 59.5 61.0 61.0 T August 2 R 0.993 0.994 0.998 0.998 0.997 0.996 0.997 0.995 0.984 0.988 0.998 0.988 ). 2 91.0 85.4 84.0 86.6 80.2 93.7 81.1 96.4 99.7 98.8 93.5 107.6 E [%] [˚C] 61.6 61.6 60.0 60.0 51.0 59.0 51.0 59.0 59.5 59.5 61.0 61.0 m T May 2 R 0.993 0.994 0.998 0.998 0.998 0.999 0.997 0.998 0.983 0.998 1.000 0.998 ) 40 s, 72˚C 30 s]; 80˚C 25 s ) 40 s, 91.0 85.4 84.0 86.6 80.0 98.4 82.0 99.0 99.9 96.1 m 100.7 100.0 E [%] [˚C] 61.6 61.6 60.0 60.0 51.0 59.0 51.0 59.0 59.5 59.5 61.0 61.0 m February T

DNA DNA DNA DNA DNA DNA target cDNA cDNA cDNA cDNA cDNA cDNA molecule × [95˚C 30 s, melting temperature (T × [95˚C 30 s,

A gene

Quantitative polymerase chain reaction (qPCR) efficiencies (E) and correlation polymerase chain coefficients (R Quantitative

(AOB-amoAF/AOB-amoAR new) (AOB-amoAF/AOB-amoAR AOB amo A gene AOB (CTO189F/CTO654R) AOB 16S rRNA gene AOB (hzsA_1597F/hzsA_1857R) (Brod541F/Amx820R) bacteria hzs Anammox Anammox bacteria 16S rRNA gene Anammox (AmoA_modF/AmoA_modR) AOA amo A gene (MCGI-391F/MCGI-554R) AOA 16S rRNA gene AOA qPCR assay Table S2: Table qPCR conditions: 95˚C 4 min; 40 44 Supplementary Material [m] 43.0 44.0 45.0 water depth water 34.4 34.3 34.7 [psu] Salinity 5.0 8.6 15.4 [˚C] Temperature

1.0 0.7 0.5 [µM] Phosphate

6.8 2.0 0.5 [µM] Nitrate

0.6 0.1 0.1 [µM] Nitrite

3.0 1.9 1.6 [µM] Ammonium Physical (CTD) and chemical (nutrient) properties (nutrient) of (CTD) and chemical Physical (BW). the bottom water

BW BW BW [cm] Feb-11 Aug-11 May-11 Parameter/ Sediment dbsf Table S3: Table 45 Chapter 2

Table S4: Total organic carbon (TOC) and total organic nitrogen (TON).

Parameter/ TOC TON Sediment dbsf [cm] [%] [%] Feb-11 0.5 0.22 0.02 1.5 0.22 bdl* 2.5 0.21 0.04 3.5 0.22 0.04 4.5 0.26 0.03 6.5 0.20 0.02 8.5 0.28 0.03 11.5 0.37 0.08 May-11 0.5 0.20 0.02 1.5 0.30 0.05 2.5 0.25 0.04 3.5 0.27 0.03 4.5 0.38 0.08 6.5 0.25 0.05 8.5 0.15 0.03 11.5 0.21 0.02 Aug-11 0.5 0.26 0.03 1.5 0.27 0.05 2.5 0.23 0.02 3.5 0.20 0.02 4.5 0.31 0.06 6.5 0.25 0.03 8.5 0.28 0.03 11.5 0.22 0.04

*bdl: below detection limit

46 Supplementary Material ] -1 gene

amoA 0.694*** AOA AOA (DNA) [copies g (DNA)

0.846*** (RNA:DNA ratio) (RNA:DNA AOA 16S rRNA gene 16S rRNA AOA

[%] TON 0.657*** + 4

-values ≤ 0.005. P -values PO [µM] 0.801*** - 3

NO [µM] 0.734*** + 4

[µM] NH 0.822*** -values ≤ P -values 0.05 were reported. The degree of significancewas indicatedby using a single asterisk for ] ] -1 -1 ] -values ≤ 0.01 and three asterisks for P -values ] -1 -1 ] ] ≤ -0.6 with s -1 -1 ] r -1 ] ] ] ] -1 -1 -1 -1 ] ] -1 -1

≥ 0.6 and ] s -1 r gene (cDNA) [copies g gene (DNA) [copies g gene (RNA:DNA ratio) (DNA) gene [copies g (cDNA) gene [copies g Spearman rank order correlation of all parameters observed in this study. [µM] 16S rRNA gene (DNA) [copies g

[µM] [µM] - + + 3 4 4 AOA amoA gene (RNA:DNA ratio) IPLs total [area g Crenarchaeol AOA 16S rRNA gene (cDNA) [copies g AOA Anammox hzsA Anammox PC Monoether ladderane [ng g Anammox bacteria 16S rRNA gene (cDNA) [copies g Anammox TOC [%] Anammox bacteria 16S rRNA gene (DNA) [copies g Anammox AOA amoA gene (DNA) [copies g NO HPH-crenarchaeol [area g HPH-crenarchaeol AOB amoA gene (RNA:DNA ratio) AOB Parameter AOA amoA gene (cDNA) [copies g Anammox bacteria hzsA Anammox Anammox bacteria 16S rRNA gene (RNA:DNA ratio) Anammox bacteria hzsA Anammox AOB amoA AOB AOB 16S rRNA gene (cDNA) [copies g AOB PO NH Sediment depth [cm] AOA AOB amoA AOB Table S5a: Table Correlation coefficients -values ≤ 0.05 and ≥ 0.01, two asterisks for ≤ 0.05 and ≥ 0.01, two P -values 47 Chapter 2 ] -1

0.629*** 0.797*** -0.743*** (cDNA) [copies g (cDNA) Anammox 16S rRNA gene 16S rRNA Anammox ] -1

0.725*** -0.647*** (DNA) [copies g (DNA) Anammox 16S rRNA gene 16S rRNA Anammox gene

amoA 0.994*** 0.717*** -0.739*** AOA AOA (RNA:DNA ratio) (RNA:DNA ] -1 gene

amoA -0.745*** AOA AOA (cDNA) [copies g (cDNA) ] ] -1 -1 ] ] -1 -1 ] ] -1 -1 ] -1 ] ] ] ] -1 -1 -1 -1 ] ] -1 -1

] -1 gene (cDNA) [copies g gene (DNA) [copies g gene (RNA:DNA ratio) (DNA) gene [copies g (cDNA) gene [copies g Spearman rank order correlation of all parameters observed in this study. [µM] 16S rRNA gene (DNA) [copies g

[µM] [µM] - + + 3 4 4 AOA amoA gene (RNA:DNA ratio) IPLs total [area g Crenarchaeol AOA 16S rRNA gene (cDNA) [copies g AOA Anammox hzsA Anammox PC Monoether ladderane [ng g Anammox bacteria 16S rRNA gene (cDNA) [copies g Anammox TOC [%] bacteria 16S rRNA gene (DNA) [copies g Anammox Sediment depth [cm] NH AOA amoA gene (DNA) [copies g NO HPH-crenarchaeol [area g HPH-crenarchaeol AOB amoA gene (RNA:DNA ratio) AOB Parameter AOA amoA gene (cDNA) [copies g Anammox bacteria hzsA Anammox Anammox bacteria hzsA Anammox Anammox bacteria 16S rRNA gene (RNA:DNA ratio) Anammox AOB amoA AOB AOB 16S rRNA gene (cDNA) [copies g AOB PO AOA AOB amoA AOB Table S5b: Table 48 Supplementary Material ] -1 [ng g -0.662*** PC-ME ladderane

hzsA 0.797*** 0.760*** -0.751*** Anammox Anammox (RNA:DNA ratio) (RNA:DNA ] -1

hzsA 0.713*** Anammox Anammox (cDNA) [copies g (cDNA) ] -1

hzsA 0.662*** 0.848*** 0.729*** Anammox Anammox (DNA) [copies g (DNA) 0.708*** 0.748*** (RNA:DNA ratio) (RNA:DNA Anammox 16S rRNA Anammox ] ] -1 -1 ] ] -1 -1 ] ] -1 -1 ] -1 ] ] ] ] -1 -1 -1 -1 ] ] -1 -1

] -1 gene (DNA) [copies g gene (cDNA) [copies g gene (RNA:DNA ratio) Spearman rank order correlation of all parameters observed in this study.

(DNA) gene [copies g [µM] 16S rRNA gene (DNA) [copies g

[µM] [µM] - + + 3 4 4 AOA 16S rRNA gene (cDNA) [copies g AOA Anammox hzsA Anammox PC Monoether ladderane [ng g Sediment depth [cm] AOA amoA gene (DNA) [copies g NO Parameter NH AOA amoA gene (cDNA) [copies g AOA amoA gene (RNA:DNA ratio) IPLs total [area g Crenarchaeol [area g HPH-crenarchaeol TOC [%] bacteria 16S rRNA gene (DNA) [copies g Anammox bacteria 16S rRNA gene (cDNA) [copies g Anammox bacteria 16S rRNA gene (RNA:DNA ratio) Anammox bacteria hzsA Anammox amoA gene (RNA:DNA ratio) AOB Anammox bacteria hzsA Anammox AOB amoA AOB AOB 16S rRNA gene (cDNA) [copies g AOB PO AOA AOB amoA (cDNA) gene [copies g AOB Table S5c: Table 49 Chapter 2 Supplementary Material

amoA

-0.646*** AOB (RNA:DNA ratio) (RNA:DNA ] -1

amoA 0.887*** AOB (cDNA) [copies g (cDNA) 0.620*** AOB 16S rRNA (RNA:DNA ratio) (RNA:DNA ] -1 0.656*** 0.702*** AOB 16S rRNA AOB 16S rRNA (cDNA) [copies g (cDNA) ] -1 0.617*** AOB 16S rRNA AOB 16S rRNA (DNA) [copies g (DNA) ] ] -1 -1 ] ] -1 -1 ] ] -1 -1 ] -1 ] ] ] ] -1 -1 -1 -1 ] ] -1

-1 ] -1 A gene (cDNA) [copies g A gene (DNA) [copies g gene (RNA:DNA ratio) Spearman rank order correlation of all parameters observed in this study. [µM] 16S rRNA gene (DNA) [copies g

[µM] [µM] - + + 3 4 4 AOA amoA gene (RNA:DNA ratio) IPLs total [area g Crenarchaeol AOA 16S rRNA gene (cDNA) [copies g AOA Anammox bacteria 16S rRNA gene (cDNA) [copies g Anammox Sediment depth [cm] TOC [%] bacteria 16S rRNA gene (DNA) [copies g Anammox AOA amoA gene (DNA) [copies g NO HPH-crenarchaeol [area g HPH-crenarchaeol Parameter NH hzsA Anammox amoA (DNA) gene [copies g AOB amoA (cDNA) gene [copies g AOB amoA gene (RNA:DNA ratio) AOB PC Monoether ladderane [ng g AOA amoA gene (cDNA) [copies g Anammox bacteria hzs Anammox Anammox bacteria 16S rRNA gene (RNA:DNA ratio) Anammox bacteria hzs Anammox AOB 16S rRNA gene (cDNA) [copies g AOB PO AOA Table S5d: Table 50

3. Lack of 13C-label incorporation suggests low turnover rates of thaumarchaeal intact polar tetraether lipids in sediments from the Iceland Shelf

Sabine K. Lengger, Yvonne A. Lipsewers, Henk de Haas, Jaap S. Sinninghe Damsté and Stefan Schouten

Thaumarchaeota are amongst the most abundant microorganisms in aquatic environments, however, their metabolism in marine sediments is still debated. Labeling studies in marine sediments have previously been undertaken, but focused on complex organic carbon substrates which Thaumarchaeota have not yet been shown to take up. In this study, we investigated the activity of Thaumarchaeota in sediments by supplying different 13C-labeled substrates which have previously been shown to be incorporated into archaeal cells in water incubations and/or enrichment cultures. We determined the incorporation of 13C-label from bicarbonate, pyruvate, glucose and amino acids into thaumarchaeal intact polar lipid-glycerol dibiphytanyl glycerol tetraethers (IPL-GDGTs) during 4–6 day incubations of marine sediment cores from three sites on the Iceland Shelf. Thaumarchaeal intact polar lipids, in particular crenarchaeol, were detected at all stations and concentrations remained constant or decreased slightly upon incubation. No 13C incorporation in any IPL-GDGT was observed at stations 2 (clay-rich sediment) and 3 (organic-rich sediment). In bacterial/eukaryotic IPL-derived fatty acids at station 3, contrastingly, a large uptake of 13C label (up to + 80‰) was found. 13C was also respired during the experiment as shown by a substantial increase in the 13C content of the dissolved inorganic carbon. In IPL- GDGTs recovered from the sandy sediments at station 1, however, some enrichment in δ13C (1–4‰) was detected after incubation with bicarbonate and pyruvate. The low incorporation rates suggest a low activity of Thaumarchaeota in marine sediments and/or a low turnover rate of thaumarchaeal IPL-GDGTs due to their low degradation rates. Cell numbers and activity of sedimentary Thaumarchaeota based on IPL-GDGT measurements may thus have previously been overestimated.

Biogeosciences, 11, 201–216, 2014

53 Chapter 3

3.1. Introduction Thaumarchaeota are ubiquitous microorganisms (Hatzenpichler, 2012 and references cited therein) which have recently been discovered to form a separate phylum, the Thaumarchaeota (Brochier-Armanet et al., 2008; Spang et al., 2010). They were initially discovered as the Marine Group I Crenarchaeota in the coastal and open ocean (DeLong, 1992; Fuhrman et al. 1992; Karner et al., 2001) where they are abundantly present in the epipelagic zone (e.g. Francis et al., 2005; Beman et al., 2008) but also in deep water (Fuhrman and Davis, 1997; Herndl et al., 2005; Agogué et al., 2008) where they can be as abundant as the total bacterial population. Thaumar- chaeota have also been detected in marine sediments (Hershberger et al., 1996; Francis et al., 2005). Before enrichment cultures became available, the metabolism of Thaumarchaeota was unclear. Hoefs et al. (1997) suggested, based on the 13C-enrichment of thaumarchaeal lipids in comparison to algal biomarkers, the possibility of autotrophic assimilation of dissolved inorganic carbon (DIC) using a different pathway than via Rubisco, or, alternatively, the heterotrophic uptake of small organic molecules. Indeed, 13C-labeling studies with bicarbonate showed the incorporation of 13C-labelled DIC into thaumarchaeal membrane lipids and thus their autotrophic metabolism (Wuchter et al., 2003). Unambiguous proof for the growth of Thaumarchaeota on inorganic carbon came with the first enrichment culture of Nitrosopumilus maritimus, which was growing chemolithoautotrophically on bicarbonate, and gaining energy by the oxidation of ammonia to nitrite (Könneke et al., 2005). It was suggested that 3-hydroxypropionate/4-hydroxybutyrate pathway was used by these microorganisms (Berg et al., 2007), which was supported by genetic analyses of C. symbiosum (Hallam et al., 2006) and N. maritimus (Walker et al., 2010). However, in these two species, also genes involved in heterotrophic metabolisms were detected, which implies their potential for mixotrophy. Furthermore, the uptake of pyruvate into cell material in cultures of a Thaumarchaeote enriched from soil, Nitrososphaera viennensis, was demonstrated (Tourna et al., 2011). Indeed, there is some environmental evidence for a mixotrophic metabolism of Thaumar- chaeota. Ouverney and Fuhrman (2000) as well as Herndl et al. (2005) showed, via MICRO- CARD-FISH using 3H-labeled amino acids, that thaumarchaeal cells present in sea water take up amino acids. There is also circumstantial evidence for mixotrophy of Thaumarchaeota, such as the radiocarbon values of archaeal lipids in the deep ocean (Ingalls et al., 2006), thaumarchaeal activity (as quantified by uptake of substrate measured by MAR-FISH) being correlated to the presence of urea (Alonso-Sáez et al., 2012), and the possession of genes for urea transporters (Baker et al., 2012). Mußmann et al. (2011) found thaumarchaeal cell numbers in waste reactors that were too high to be supported by the rates of ammonia oxidation, and a lack of incorporation of 13C-labelled DIC into thaumarchaeal lipids during growth, also suggesting heterotro- phy of Thaumarchaeota. Circumstantial evidence, based on the correlation of organic carbon concentration with archaeal biomarker lipids, suggests that Archaea in deep subsurface marine sediments (<1 m) use organic carbon (Biddle et al., 2006; Lipp et al., 2008; Lipp and Hinrichs, 2009), however, this empirical correlation could also be due to preservation factors affecting biomarkers and total organic carbon in a similar way (Hedges et al., 1999; Schouten et al., 2010). These studies thus illustrate the potential for diversity of thaumarchaeal metabolisms. Cell membranes of Thaumarchaeota consist of glycerol dibiphytanyl glycerol tetraether lipids (GDGT) in the form of intact polar lipids (IPL; Schouten et al., 2008; Pitcher et al., 2011a; 54 Introduction/Material and Methods

Sinninghe Damsté et al., 2012; Fig. 1a). They possess GDGTs which are also present in other Archaea (Koga and Nakano, 2008), such as GDGT-0, -1, -2 and -3 (Fig. 1b), but also a specific lipid named crenarchaeol, which up to now has only been found in (enrichment) cultures of Thaumarchaeota (Sinninghe Damsté et al., 2002; de la Torre et al., 2008; Schouten et al., 2008; Pitcher et al., 2011b; Sinninghe Damsté et al., 2012). Stable isotope probing (SIP) experiments targeting the biphytanyl chains contained in crenarchaeol (Fig. 1c), have been undertaken in order to determine the uptake of different substrates. This revealed the incorporation of 13C from bicarbonate into crenarchaeol (Wuchter et al., 2003). Pitcher et al. (2011c) showed that this uptake was dependent on ammonia oxidation in North Sea water, as addition of inhibitors for ammonia oxidation, nitrapyrine (N-serve) or chlorate, resulted in a decreased incorporation of 13C-labelled DIC. Other SIP experiments carried out with organic substrates were less successful: Lin et al. (2012) achieved only a 2‰ enrichment in one of the biphytanyl chains of crenarchaeol, but 2‰ depletion in the other biphytanyl chain when adding 13C -labeled phytodetrital organic carbon to sediment slurries. Takano et al. (2010) and Nomaki et al. (2011) also carried out benthic in situ-labeling experiments and did not find incorporation of 13C in the biphytanyl chains in an incubation experiment with 13C-labeled glucose in sediment from Sagami Bay, Ja- pan, after 405 days, although they noted an initial apparent increase in δ13C of one biphytane by ~10‰. This was in spite of an increase in molecular thaumarchaeal biomarkers within 9 days. Remarkably, however, they did report labeling of the glycerol moieties of the GDGT molecules after 405 days. Thus, not much evidence for substantial incorporation of carbon from organic substrates into thaumarchaeal lipids is observed in SIP experiments performed with sediments. It is possible that the types of substrate used in these studies were not suitable, i.e. not readily taken up by the Thaumarchaeota, and that other organic compounds would result in higher incorporation. Interestingly, none of the previously conducted labeling studies in sediments used 13C-labelled DIC. Bicarbonate had previously unambiguously been shown to be incorporated by pelagic Thaumarchaeota (Wuchter et al., 2003; Pitcher et al. 2011c) and by Thaumarchaeota enriched from sediments (Park et al., 2010) and soils (Jung et al., 2011; Kim et al., 2012). To shed further light on the metabolism of sedimentary Thaumarchaeota, we performed labeling experiments using 13C-labeled substrates, i.e. bicarbonate, pyruvate, amino acids and glucose in sediment cores from the Iceland shelf and determined the degree of 13C incorporation into the most abundant GDGT-lipids, i.e. crenarchaeol which is specific for Thaumarchaeota and GDGT-0, which can also be produced by other Archaea. All these compounds have previously been shown to be taken up by Thaumarchaeota either in the environment (Ouverney and Fuhrman, 2000; Wuchter et al. 2003; Herndl et al., 2005; Takano et al., 2010; Pitcher et al. 2011c) or enrichment cultures (Park et al., 2010; Jung et al., 2011; Tourna et al., 2011; Kim et al., 2012) and were thus deemed the most suitable substrates and most likely to result in uptake by sedimentary Thaumarchaeota. The results are discussed with respect to the uptake of substrates as well as the turnover rates of thaumarchaeal GDGTs. 3.2. Material and Methods 3.2.1. Sampling stations Sediment cores were sampled at three stations, located on the Iceland Shelf, during the ‘Long Chain Diols’ cruise on the R/V Pelagia in July 2011 (Fig. 2). Station 1 (63°21’N 16°38’W), south of Iceland, was at 240 m water depth and consisted of dark, sandy sediment. 55 Chapter 3

a c HO O HO O O O O O O HO OH Crenarchaeol O OH O HO O O O O O O O OH OH GDGT-0 HI, ∆ b HO LiAlH , ∆ O 4 HO O O HO OH acyclic biphytane O O HO O O OH HO O bicyclic biphytane HO OH O Monohexose-crenarchaeol HO O HO OH O

O O tricyclic biphytane O OH HO O HO O Dihexose-crenarchaeol O HO OH

O O OH O O O O P O OH OHO OH Hexose, phosphohexose-crenarchaeol

Figure 1: Structures of crenarchaeol and GDGT-0 (a), IPL-crenarchaeol species (b) and biphytanyl chains released from crenarchaeol and GDGT-0 by chemical degradation (c).

Station 2 (66°18’N 13°58’W) is located north-east of Iceland, at 261 m water depth, and the sediment was sandy-clayish. Sediment at Station 3 (67°13’N 19°07’W), north of Iceland, at 503 m water depth, and further offshore than the other two stations, consisted of dark, soft, black mud. From each station, multicores were retrieved in polycarbonate core tubes. Ten cores from each station were retrieved in tubes of 10 cm diameter with drilled holes downwards, spaced 1 cm apart, and used for incubation. Cores sampled with tubes of 5 cm diameter were used for oxygen microprofiling, pore-water extraction, and four cores from each station were sliced and stored for density and total organic carbon (TOC) analysis. 3.2.2. Core characterization For each station, control cores were sliced into 1 cm thick layers from 0–10 cm core depth. The water content of each sediment was determined by weighing prior to and after freeze-drying. To- tal organic carbon was determined from freeze-dried sediments following overnight acidification with 2N HCl, subsequent washes with bidistilled H2O and water removal by freeze-drying. The decalcified sediments were measured on a Flash EA 1112 Series (Thermo Scientific, Waltham, MA) analyzer coupled via a Conflo II interface to a Finnigan Deltaplus mass spectrometer. Stan- dard deviations from three measurements ranged from 0.0 to 0.6% TOC. Two cores (5 cm diameter) from each cast were used for oxygen microprofiling with an OX- 100 Unisense oxygen microelectrode (Unisense, Aarhus, DK; Revsbech, 1989). A two-point

56 Material and Methods

Jan Mayen

30 °

° 10 20 ° 3000 Greenland 2000

1000

Station 3 Denmark Strait 100 500 Station 2

100 IcelandIceland 2000

Station 1 Faroes

1000

60 ° Iceland Basin 2000

3000

Figure 2: Map of the sampling stations (1, 2 and 3) on the Iceland shelf. calibration was carried out with bottom water from the same station bubbled with air at 4°C for at least 5 min (100% saturation) and a solution of 0.1 M sodium ascorbate in 0.1 N NaOH in Milli-Q Water (0% saturation) and the electric current measured in pA was converted to mg L–1

O2. The sensor was moved with a micromanipulator one mm at a time. Pore water was extracted on board from slices of several cores by centrifugation. Five mL 13 from each depth was preserved air-free with added HgCl2 for analysis of the δ C of the dissolved inorganic carbon (DIC) at 4°C, and 3 mL were preserved at –20°C for analysis of phosphate, ammonia, nitrite and nitrate. Dissolved inorganic phosphate, ammonia, nitrite and nitrate were measured on a Traacs 800 Autoanalyzer (Seal Analytical, Fareham, UK). Ortho-phosphate was measured using potassium antimonyltartrate as a catalyst and ascorbic acid as a reducing reagent which resulted in formation of a blue (880 nm) molybdenum phosphate-complex at pH 0.9–1.1 (Murphy and Riley, 1962). Ammonia was measured via formation of the indo-phenol blue-complex (630 nm) with phenol and sodium hypochlorite at pH 10.5 in citrate (Helder and de Vries, 1979). Dissolved inorganic nitrite concentrations were measured after diazotation of nitrite with sulphanilamide and N-(1-naphtyl)-ethylene diammonium dichloride to form a reddish-purple dye measured at 540 nm. Nitrate was first reduced in a copperized Cd-coil using imidazole as a buffer, measured as nitrite and concentrations were calculated by subtraction of nitrite (Grasshoff et al., 1983). δ13C of DIC was measured in pore water from all stations, and bottom water samples from the experiments, on a Thermo GasBench II coupled to a Thermo Delta Plus and is reported in 57 Chapter 3

Filter 0.2 mm

Stopper Air in (pipette)

Yellow tape Airpump

Distance 1 cm Lower part of splitable core (upper part removed)

Drilled holes 2.5 mm filled with silicon

90°

Stopper

Water bath for optimum temperature (4°C)

Figure 3: Scheme of the incubation set-up of the cores. the delta notation against the Vienna Pee-Dee Belemnite (V-PDB) standard. To this end, 0.5 mL of each sample was injected into gastight exetainers, containing 0.1 mL of 80% H3PO4, that had been flushed for 15 min each with He. Performance was monitored by analysis of an in-house 13 laboratory standard of Na2CO3 with a δ C of –0.57‰ after every 12 measurements and an in- 13 house laboratory standard of CaCO3, with a δ C value of –24.2‰ at the start and the end of every series. Measured values of these standards were usually not deviating by more than 0.5‰ from the calibrated (on NBS-19) values. 3.2.3. Incubation conditions Ten cores from each station were used for incubations (Table 2). For this, splitable polycarbonate core tubes with 10 cm diameter were prepared by drilling two rows of 1 mm holes spaced at distances of 1 cm. The two rows were 90° contorted; holes were filled with silicon and covered with plastic non-permeable tape (see setup in Fig. 3). The cores were, after recovery from the multicorer, transferred as quickly as possible to a temperature-controlled room kept at 4°C, and the bottom water was sampled with a sterile pipette for determination of pH, δ13C of DIC and nutrients as described above. Four whole cores at each station were incubated with 13C-labelled substrates, i.e. bicarbonate, pyruvate, amino acids and glucose, and one whole core (‘background’) was injected with MilliQ water only. Four more cores were incubated with solutions containing one of the substrates and a nitrification inhibitor, and one (‘background + inhibitor’) with MilliQ water and the nitrification inhibitor. The incubation solutions were injected into

58 Material and Methods the seven injection ports from the surface downwards, i.e. the first 8 cm were supplied with the labeled substrate. Injection solutions contained 99% 13C-labelled substrates as supplied by Cam- bridge Isotope Laboratories (Andover, MA, USA). The substrates were dissolved in MilliQ-H2O –1 – –1 in concentrations of 3.7 mg mL for NaHCO3 (Bic), 1.01 mg mL for Glucose (Glu), 0.89 mg mL–1 for a mix of 16 algal amino acids (AA; 97–99% labeled; CLM 1548) and 1.24 mg mL–1 of sodium pyruvate (Pyr). 200 μL were delivered to each slice by injection through the two 90° contorted injection ports, which corresponded to a total addition of 1.6 g 13C m–3 sediment for the bicarbonate, and 1.2 g 13C m–3 for the organic compounds. The nitrification inhibitor was Nitrapyrine (N-Serve, Pestanal) at 11.5 μg mL–1, which is known to inhibit archaeal ammonia oxidation (Park et al., 2010; Pitcher et al., 2011c). As Nitrapyrine cannot be dissolved in pure water, 5% of EtOH was added and the solutions were kept at 30°C to prevent precipitation of the Nitrapyrine. Nitrapyrine-free incubation solutions were kept at the same conditions. After injection, the cores were stored in the dark at 4°C in a water bath - boxes with core holders filled with water for 62 h (38 h for Station 3), after which the bottom water was sampled for 13C-DIC and N- and P-nutrients as described above and re-injected with a fresh solution of the substrates in water, with or without nitrapyrine added. During the incubation time, the cores were covered lightly with a rubber stopper, so that the escape of air was possible, and aerated through a sterile plastic pipette, with air pumped by an aquarium pump and filtered through a 0.2 mm filter for sterilization purposes. After 144 h (96 h for Station 3), bottom water samples for 13C-DIC (dissolved inorganic carbon) and N- and P-nutrients were taken again, and oxygen microprofiles were measured as described above on all cores (except for Station 2, where cores were too short and thus surfaces too low in the core tubes, to allow measurements in more than three cores). Subsequently, the upper 10 cm of the sediment were sliced in 1 cm resolution and each slice mixed thoroughly, split in half and both parts were frozen at –80°C immediately. The incubations at station 3 were shorter due to time constraints. 3.2.4. Lipid extraction, separation and measurements The freeze-dried sediments of 0–1 cm, 1–2 cm and 7–8 cm depth intervals of the incubation and background cores were ground and extracted by a modified Bligh-Dyer extraction method (Pitcher et al., 2009). Briefly, they were extracted ultrasonically three times in a mixture of methanol/dichloromethane (DCM)/phosphate buffer (2:1:0.8, v:v:v), centrifuged and the solvent phases were combined. The solvent ratio was then adjusted to 1:1:0.9, v:v:v, which caused the DCM to separate. Liquid extraction was repeated two more times, the DCM fractions were combined, the solvent was evaporated and bigger particles were removed over cotton wool. An aliquot of the extracts was stored for high performance liquid chromatography /electron spray ionization tandem mass spectrometry (HPLC/ESI-MS2) analysis, and another aliquot was separated into core lipid (CL)- and intact polar lipid (IPL)-GDGTs by silica column separation with hexane/ethyl acetate (1:2, v:v) for the CL-fraction and MeOH to elute the IPL-fraction. 0.1 mg

C46 internal standard (Huguet et al., 2006) were added to the CL-fractions. The IPL-fraction was split in three aliquots: 5% were used to determine the carry-over of CL-GDGTs into the IPL-fraction and measured directly via HPLC/APCI-MS, 60% were kept for ether cleavage in order to determine the 13C incorporation into the biphytanes (see below), and 35% were subjected to acid hydrolysis under reflux for 2 h with 5% HCl in MeOH, followed by addition of water and extraction (3 ×) of the aqueous phase at an adjusted pH of 4–5 with DCM. This yielded the

IPL-derived GDGTs which were measured via HPLC/APCI-MS. The C46 internal standard was 59 Chapter 3 used to quantify the IPL-derived GDGTs and the carry over, but was added after the aliquot for 13C analysis was taken in order to prevent any possible interference of alkyl chains released from the internal standard molecule. 3.2.5. δ13C analysis of biphytanes Aliquots (60%) of the IPL-fractions were subjected to chemical treatment in order to cleave GDGTs, releasing the biphytanyl chains (Fig. 1c) according to Schouten et al. (1998). For this, the IPL fraction was refluxed in 57% HI for 1 h to break the ether bonds and produce alkyliodides and subsequently extracted three times with hexane. The hexane phase was washed with

5% NaS2O7 and twice with water. The alkyliodides were purified over Al2O3 with hexane/DCM

(9:1, v:v), hydrogenated with H2/PtO2 in hexane for 1 h (Kaneko et al., 2011) and eluted over

Na2O3 with DCM. As the H2/PtO2 hydrogenation-procedure has never been tested for stable carbon isotope analysis, we used four CL-fractions of extracts from Station 1 and Station 2, split them in half and hydrogenated one half with the conventional LiAlH4 reduction method described by Schouten et al. (1998), the other half with the method described here and by Kaneko et al. (2011). The conventional method consisted of LiAlH4 in 1,4-dioxane for 1 h under reflux, then the remaining LiAlH4 was reacted with ethyl acetate, bidistilled H2O was added and the biphytanes were extracted with DCM from the dioxane/H2O mixture. Additional purification was 13 achieved by elution over an Al2O3 column using hexane. The results showed that the δ C values of the biphytanes were not significantly different when H2/PtO2 treatment and LiAlH4 hydrogenation were compared (Table 1). However, when yields were compared, it was obvious that hydrogenation with H2/PtO2 gave better results. This is probably due to the fact that the H2/

PtO2 treatment requires fewer workup procedures after hydrogenation (only one drying step) than the LiAlH4 treatment, which requires two column separations in addition to a drying step. 3.2.6. δ13C of phospholipid-derived fatty acids In order to demonstrate that the incubation experiments did result in label uptake by the sedimentary microbial community, we determined the uptake of 13C-label by bacteria and eukaryotes by isotopic analysis of polar lipid-derived fatty acids (PLFA). For this, one third of the extract of the 0–1 cm sediment slice from Station 3, from the cores incubated with bicarbonate, glucose, amino acids and the background core (all without nitrapyrine), were used and analyzed for PLFA according to Guckert et al. (1985). Briefly, the aliquots were separated over a silica column with DCM, acetone and methanol, respectively, with the methanol-fraction containing the PLFA. PLFA fractions were saponified in methanolic KOH (2N) and, after adjusting to pH 5, the re- 13 sulting fatty acids were extracted with DCM and methylated with BF3-MeOH (with a δ C of –25.4 ± 0.2 ‰V-PDB) before measurements by gas chromatography – isotope ratio mass spectrometry (GC-irMS). The δ13C values for the fatty acids were corrected for the added carbon. 3.2.7. HPLC-APCI-MS and HPLC-ESI-MS2 The CL-fractions, hydrolyzed IPL- fractions and the IPL-fractions themselves (to determine the carry-over of CL into the IPL fraction) were analyzed by HPLC-APCI-MS as described previously (Schouten et al., 2007). HPLC-ESI-MS2 in selected reaction monitoring (SRM) mode, as described by Pitcher et al. (2011b), was used to analyze selected IPL-GDGTs. IPL-GDGTs monitored were monohexose (MH)-crenarchaeol, dihexose (DH)-crenarchaeol and hexose, phosphohexose (HPH)-crenarchaeol. Performance was monitored using a lipid extract of sed-

60 Material and Methods

13 Table 1: δ C values of the acyclic, bicyclic, and tricyclic biphytanes obtained via H2/PtO2 and LiAlH4 reduction of alkyliodides formed via HI ether cleavage.

δ13C (‰) acyclic bicyclic tricyclic

Sample H2/PtO2 LiAlH4 H2/PtO2 LiAlH4 H2/PtO2 LiAlH4 Station 1 –20.3 ± 0.4 –20.2 ± 0.0 –19.7 ± 0.7 –20.0 ± 0.6 –19.5 ± 1.1 –21.2 ± 0.8 0–1 cm Station 1 –19.9 ± 0.6 –22.0 ± 0.2 –18.4 ± 0.2 –20.2 ± 1.6 –19.0 ± 0.2 –19.8 ± 0.6 1-–2 cm Station 2 –22.7 ± 0.7 –22.0 ± 0.4 –24.2 ± 1.0 –22.4 ± 0.3 –22.6 ± 1.6 –22.0 ± 0.4 0–1 cm Station 2 –24.0 ± 1.0 –25.6 ± 0.2 –22.3 ± 1.4 –25.6 ± 0.8 –22.6 ± 0.2 –25.0 ± 0.6 1–2 cm

Total amount / μg acyclic bicyclic tricyclic

Sample H2/PtO2 LiAlH4 H2/PtO2 LiAlH4 H2/PtO2 LiAlH4 Station 1 0.79 0.28 0.27 0.16 0.31 0.18 0–1 cm Station 1 0.42 0.16 0.14 0.07 0.15 0.08 1–2 cm Station 2 0.45 0.34 0.17 0.16 0.23 0.23 0–1 cm Station 2 1–2 cm 0.13 0.05 0.04 0.0 0.06 0.0 iment known to contain the monitored GDGTs that was injected every 8 runs. Response areas per mL sediment (mL sed) are reported, as absolute quantification was not possible due to a lack of standards. The values reported are the averages of duplicate injections and their standard deviations. 3.2.8. GC-MS and GC-irMS GC-MS was used to identify the biphytanes and phospholipid-derived fatty acid methyl esters (FAME) using a TRACE GC with a DSQ-MS. The gas chromatograph was equipped with a fused silica capillary column (25 m, 0.32 mm internal diameter) coated with CP Sil-5 (film thickness 0.12 mm). The carrier gas was helium. The compound specific isotope composition of the biphytanes and fatty acids was measured with an Agilent 6800 GC, using the same GC column conditions, coupled to a ThermoFisher Delta V isotope ratio monitoring mass spectrometer. The isotopic values were calculated by integrating the mass 44, 45 and 46 ion currents of the 13 peaks and that of CO2-spikes produced by admitting CO2 with a known C-content into the mass spectrometer at regular intervals. The performance of the instrument was monitored by 61 Chapter 3

– 13 Table 2: The bottom water NO3 concentrations and δ DIC changes over the incubation time (Δt–t0), as well as oxygen penetration depths measured after the incubations. In brackets, the average values of oxygen penetration depth for the cores before incubation. BG: background, Bic: bicarbonate, Pyr: pyruvate, +Inh: nitrification inhibitor nitrapyrine added.

– 13 O Pen NO Δδ DIC 2 3 t–t0 depth Station Incubation [mM] [‰] [mm] t=0h t=62 h t=144h t=62 h t=144h t=144h (before: 17) BG 17.9 19.1 4.1 0.6 2.8 11 Bic 15.9 16.2 8.2 66.5 156.2 16 Pyr 18.1 19.2 5.9 109.1 457.0 16 1 BG+Inh 15.5 16.3 13.9 –0.5 2.6 20 Bic+Inh 11.5 12.0 3.8 135.3 275.5 20 Pyr+Inh 25.4 25.6 14.3 72.7 671.1 16 (before: 13) BG 12.14 11.37 0.09 –0.5 2.9 9 Bic 5.55 4.05 0.07 336.5 606.0 6 Pyr 13.77 12.48 0.12 366.6 1570.7 6 2 BG+Inh 10.72 10.45 0.19 0.1 3.5 5 Bic+Inh 7.22 6.79 0.09 255.4 570.1 6 Pyr+Inh 5.01 3.17 0.06 511.3 1136.4 16 (before: 16) BG 13.84 0.00 0.13 1.5 –2.3 n.d. Bic 13.83 12.60 0.08 558.2 814.3 n.d. Pyr 6.45 4.23 0.12 1108.9 1496.3 n.d. Glu 14.14 12.03 0.11 90.4 194.2 n.d. AA 15.34 13.55 0.15 82.7 201.9 n.d. 3 BG+Inh 16.06 13.39 0.11 0.3 4.9 8 Bic+Inh 15.23 14.05 0.18 244.8 520.3 n.d. Pyr+Inh 8.92 6.68 0.10 682.7 1644.5 8 Glu+Inh 5.86 4.77 0.03 110.8 301.2 10 AA+Inh 14.36 13.41 0.09 62.2 368.2 n.d. n.d. - could not be determined.

62 Material and Methods

3- -1 - -1 13 a PO4 [µmol . L ] NO 2 [µmol . L ] δ C - DIC [‰] 0481216 0.00.2 0.40.6 -4 -3 -2 -1 012 -2

Sediment depth [cm] 8

024681012 020406080 010203040 + -1 - -1 O2 [mg/L] NH4 [µmol . L ] NO 3 [µmol . L ]

3- -1 - -1 13 b PO4 [µmol . L ] NO2 [µmol . L ] δ C - DIC [‰] 024681012 0.00.2 0.40.6 -4 -3 -2 -1 012 -2

6 Sediment depth [cm] 8

0246810 12 020406080 0481216 + -1 - -1 O2 [mg/L] NH 4 [µmol . L ] NO 3 [µmol . L ]

c 3- -1 - -1 13 PO4 [µmol . L ] NO2 [µmol . L ] δ C - DIC [‰] 0246810 0.00.2 0.40.6 -4 -3 -2 -1 012 -2

Sediment depth [cm] 8

0246810 12 01020304050 0246810121416 + -1 - -1 O2 [mg/L] NH 4 [µmol . L ] NO 3 [µmol . L ]

Figure 4: Oxygen microprofiles and pore water results vs. depth at station 1 (a), 2 (b) and 3 (c). 63 Chapter 3

daily injections of a standard mixture of a C20 and a C24 perdeuterated n-alkane. Two replicate analyses (one in the case of the fatty acids) were carried out and the results were averaged in order to obtain the average and standard deviations. The stable carbon isotope compositions are reported in the delta notation against the V-PDB standard. Some values of the biphytanes could not be determined due to low concentrations, mainly in the background cores at station 2. For calculations of incorporation, the background values from station 1 were used. 3.3. Results 3.3.1. Sediment characteristics The sediments at stations 1–3 consisted of sand, sandy clay, and dark and soft mud, respectively. Oxygen penetration depth was on average 17 mm at station 1, while oxygen penetrated slightly less deep at station 2 (13 mm on average) and station 3 (15.5 mm on average; Fig. 4). At station 1, organic carbon contents were low with 0.6 % at 0–1 cm depth and 0.3% at 1–2 cm and 6–7 cm depth. Organic carbon contents were higher at station 2 and amounted to 1.4–1.7% and were highest at station 3 (2.0–2.5%). The pH of the bottom water hardly differed between stations and was typically marine, i.e. 8.2 at station 1, 8.0 at station 2, and 7.9 at station 3. Pore water concentrations of nutrients, as shown in Fig. 4, showed similar trends with depth at the three stations. Inorganic phosphate concentrations were 1 μM in the bottom water and generally increased with depth up to 7–14 μM. Ammonia concentrations increased as well with sediment depth, from 0.19 to 1.3 μM in bottom water to 44–70 μM at depth. Nitrite concentrations were an order of magnitude higher in the pore water (0.32–0.62 μM) than in the bottom water (0.055 μM), and increased with sediment depth. Nitrate concentrations were high in the bottom water, 14 μM, and generally decreased quickly with depth in the sediment to values between 0.6 and 3 μM. The δ13C of the DIC showed also similar profiles at the three stations. It decreased from 1‰ in the bottom water to –3‰ in the pore water. At station 2, δ 13C of the DIC could only be measured in the bottom water and the four uppermost pore water samples, but, in these samples, showed the same decrease with depth as observed at Station 1, from –1.3 ‰ to –2.9 ‰. 3.3.2. GDGT-abundance GDGT-concentrations averaged over all cores from the incubations (10 per station) are shown with standard deviation in order to give an impression of the range of concentrations found (Fig. 5). GDGT-0 and crenarchaeol were present as a core lipid in concentrations of 0.4 to 0.8 μg mL sed–1, and 0.08 to 0.12 μg mL sed–1 for the minor isoprenoid GDGTs (i-GDGTs; GDGT- 1, -2 and -3). Concentrations were similar at all stations and did not show substantial changes with sediment depth. IPL-derived GDGTs were present in lower concentrations and amounted to 0.09 to 0.3 (GDGT-0), 0.07 to 0.18 (crenarchaeol) μg mL sed–1. Concentrations were generally lower at station 1 compared to stations 2 and 3. Direct analysis of individual IPL-crenarchaeol showed that the head groups mainly consisted of monohexose (MH)- and hexose, phosphohexose (HPH)- headgroups, with only a small contribution of dihexose (DH)- head groups (Fig. 5c). The proportion of HPH- to the total peak area of IPL-crenarchaeol was ca. 80–90% in the surface sediments (0–1 and 1–2 cm) of all stations. At station 1 and 2, this decreased to 10–25% in the deepest sediment slice analyzed, 6–7 cm. At station 3, HPH-crenarchaeol dominated at all sediment depths (Fig. 4).

64 Material and Methods/Results BP tricyclic tricyclic – 19.8 ± 0.8 – 17.7 ± 1.9 – 19.2 ± 0.6 – 19.4 ± 0.3 – 19.2 ± 0.2 – 20.7 ± 0.1 C ofcorresponding the C [‰] BP 13 13 bicyclic bicyclic Station 3 δ – 20.2 ± 1.2 – 18.3 ± 1.4 – 20.1 ± 0.4 – 19.7 ± 0.6 – 19.9 ± 0.4 – 21.4 ± 0.4 BP acyclic acyclic – 20.4 ± 0.2 – 19.6 ± 1.2 – 20.6 ± 0.4 – 19.3 ± 0.6 – 19.4 ± 0.1 – 22.4 ± 0.0 * * * * C of with water, just incubated that were the biphytanes BP 13 n.d. n.d. n.d. n.d. tricyclic tricyclic – 20.3 ± 0.9 – 20.0 ± 0.4 C: BG values were subtracted from the subtracted were C: BG values 13 * * * * Δ C [‰] BP 13 n.d. n.d. n.d. n.d. Station 2 δ bicyclic bicyclic – 21.4 ± 1.4 – 21.0 ± 0.4 * * * * BP n.d. n.d. n.d. n.d. acyclic acyclic – 22.9 ± 0.9 – 22.0 ± 0.0 * BP n.d. tricyclic tricyclic – 21.3 ± 0 – 22.2 ± 0 – 20.2 ± 0.0 – 21.5 ± 2.3 – 19.9 ± 0.3 C of δ (i.e. measured in the sediment (BP) the biphytanes * 13 C [‰] BP n.d. 13 Station 1 δ bicyclic bicyclic

– 20.7 ± 0.1 – 22.4 ± 1.9 – 21.2 ± 0.4 – 20.0 ± 0.6 – 20.5 ± 1.1 * BP n.d. acyclic acyclic – 22.0 ± 0 – 22.4 ± 0 – 21.4 ± 0.5 – 21.4 ± 0.2 – 22.0 ± 0.1 0 – 1 1 – 2 6 – 7 1 – 2 6 – 7 0 – 1 (cm) – + Sediment n.d. – could not be determined. but under the same conditions). These values were used for determinationused were Theseconditions). same under the but values of the Background (BG) values of δ 3: Background values (BG) Table * value measured value from the cores 6). incubated Numbers with indicate label the (Fig. depth interval the sample coming was from, + : nitrification inhibitor at station 2 could not be determined concentrations. due to low nitrapyrine added for incubation, - : no inhibitor added. Values 65 Chapter 3

Station 1 Station 2 Station 3 a 1.2

1.0

-1 0.8

0.6

0.4 [ µ g (mL sed) ]

CL-GDGT concentration 0.2

0.0 0-1 cm 1-2 cm 6-7 cm 0-1 cm 1-2 cm 6-7 cm 0-1 cm 1-2 cm 6-7 cm b 0.4

0.3 -1

0.2

[ µ g (mL sed) ] 0.1 IPL-GDGT concentratio n

0.0 0-1 cm 1-2 cm 6-7 cm 0-1 cm 1-2 cm 6-7 cm 0-1 cm 1-2 cm 6-7 cm

GDGT-0 Crenarchaeol c 100

60 [% ] 40 IPL-crenarchaeol 20

0 0-1 cm 1-2 cm 6-7 cm 0-1 cm 1-2 cm 6-7 cm 0-1 cm 1-2 cm 6-7 cm

Depth interval HPH-crenarchaeol DH-crenarchaeol MH-crenarchaeol

Figure 5: GDGT-0 and crenarchaeol concentrations (averages), for CL-GDGTs (a) and IPL-derived GDGTs (b) at all three stations and core depths. Proportions of head groups of IPL-crenarchaeol at all three stations (c). 66 Results

3.3.3. Incubation experiments Incubations experiments were started directly after core recovery and initial sampling by injection of solutions, which contained 13C-bicarbonate, pyruvate, glucose , amino acids or just water (incubated for comparison and further called the “background core”) over the first 7 cm of the cores. The cores were incubated at in situ temperatures (4°C) for 6 days (4 days for station 3) and subsequently sliced and stored for analysis of 13C-enrichment in lipids. Oxygen penetration depths were measured and bottom water was sampled at the start of the experiment, after 48 hours (36 for Station 3) and at the end of the incubations. At all stations, nutrient concentrations of the bottom water did not change over the 6 days (5 days for station 3) of incubation, except for nitrate, which generally showed a decrease (Table 2). The bottom water pH remained mostly constant, except at station 1, where it changed during the incubation from 8.2 to 8.0 in all incubations, similar to the other sediment cores and perhaps indicating that the initial value of 8.2 might have been due to an error in the measurement. The δ13C of the DIC in the bottom water substantially increased in the cores where 13C-labeled compounds and bicarbonate was added, but not in the background cores (Table 2). In cores from station 2, oxygen penetration depths decreased to 6–9 mm in all incubation experiments except for the core incubated with pyruvate and inhibitor, as well as in cores from station 3, where a decrease in oxygen penetration depth to 8–10 mm was observed (Table 2). In all cores from the three stations, no major differences in IPL-crenarchaeol concentrations upon incubation could be detected (Figs. S1–S3). The δ13C-values of the biphytanes released from the IPL-GDGTs of the background cores were ranging from –17 to –24‰ at all stations (Table 3), which is within the natural variation observed for biphytanes sourced by Thaumarchaeota in marine sediments (Hoefs et al., 1997; Könneke et al., 2012; Schouten et al., 2013). No substantial 13C enrichment of biphytanes was observed in nearly all of the incubation experiments (Fig. 6). The only exception was the tricyclic biphytane in some of the incubations at station 1 (with 13C-labelled substrates bicarbonate, bicarbonate and inhibitor, and pyruvate and inhibitor at nearly all depths) and one incubation (with pyruvate and inhibitor at 6–7 cm depth) at station 2 with enrichments ranging from 2 to 4‰. However, due to the large standard deviations in the δ13C values of the background cores, only the enrichment of 2–5 ‰ in the 1–2 cm slices of station 1 is statistically significant at a 95% confidence level (t(2)= 6.6–9.0, P=0.05). To determine whether the added 13C-labelled substrate was incorporated into sedimentary microbial biomass at all, phospholipid-derived fatty Table 4: δ13C values of fatty acids measured in the 0-1 cm slice in cores from station 3, incubated without inhibitor, for 5 days.

δ13C [‰] Fatty acid BG Bic Glu AA

C16:0 –25.5 ± 0.2 –25.3 ± 0.6 20.6 ± 0.5 30.0 ± 3.9

* C18:0 –24.6 –24.5 ± 0.2 66.2 ± 0.4 63.1 ± 2.1

* Single measurement 67 Chapter 3

(a) Station 1 5 Bicyclic biphytane Tricyclic biphytane ] Acyclic biphytane

inc-BG 0 13 ∆ δ C [‰

-5 0-1* 1-2 6-7 0-11-2 6-70-1 1-26-7 0-1 1-2 6-7 Depth [cm] Bicarbonate Bicarbonate + Inh Pyruvate Pyruvate + Inh (b) Station 2 5 ]

inc-BG 0 13 ∆ δ C [‰

-5 0-1 1-2 6-7 0-11-2 6-70-1 1-26-7 0-1 1-2 6-7 Depth [cm] Bicarbonate Bicarbonate + Inh Pyruvate Pyruvate + Inh (c) Station 3 5 ]

0 inc-BG 13 ∆ δ C [‰

-5

0-1 1-2 6-7 0-11-2 6-70-1 1-26-7 0-1 1-2 6-7 Depth [cm] Bicarbonate Bicarbonate + Inh Pyruvate Pyruvate + Inh (d) Station 3 5 ]

0 inc-BG 13 ∆ δ C [‰

-5

0-1 1-2 6-7 0-11-2 6-70-1 1-26-7* 0-1 1-2* 6-7 Depth [cm] Glucose Glucose + Inh AA AA + Inh

Experiment 13 13 Figure 6: Difference inδ C-values (Δδ Cinc-bg) of the acyclic, bicyclic and tricyclic biphytanes in ‰ in the cores incubated with labeled substrate versus the 13C-values in the background cores (incubated with and without inhibitor) at station 1 (a), station 2 (b) and station 3 (c) from the cores incubated with bicarbonate and pyruvate, with and without inhibitor, and the cores incubated with glucose and amino acids with and without inhibitor, at station 3 (d). 68 Results/Discussion acids, stemming from bacteria or eukaryotes, were analyzed from the surface sediments of the bicarbonate, amino acids and glucose incubation experiments. δ13C values of the most common 13 fatty acids, C16:0 and C18:0 were enriched in C by up to 80‰ in the amino acid and glucose incubation experiments compared to the background (Table 4). The cores incubated with 13C-labeled bicarbonate that were analyzed showed no 13C-enriched fatty acids. 3.4. Discussion 3.4.1. Biomarkers indicative for live sedimentary Thaumarchaeota The only biomarker lipids up to now which are probably indicative for live Thaumarchaeota are crenarchaeol IPLs (Pitcher et al., 2011b). Of these, the ones with a glycosidic head group likely contain a substantial fossil component, while the hexose, phosphohexose (HPH)-crenarchaeol is more labile and its concentration corresponds well to DNA-based thaumarchaeal abundance (Pitcher 2011a and 2011b; Schouten et al., 2012; Lengger et al., 2012a). The presence and dominance of HPH-crenarchaeol in the sediments strongly suggests that live Thaumarchaeota were present in sediments at all the stations (Fig. 5). This was expected for the surface sediment, as oxygen and ammonium were present (Martens-Habbena et al., 2009; Erguder et al., 2009; Hat- zenpichler, 2012). The ammonium concentration profiles, with concentrations decreasing upwards, agree with aerobic ammonia oxidation proceeding in the oxygenated parts, using the ammonium diffusing from below. However, HPH-crenarchaeol was present down to 7 cm depth, below the oxygen penetration depth, which could indicate that either live Thaumarchaeota were present at depth, using a metabolic process different from aerobic ammonia oxidation, or that this HPH-crenarchaeol is not stemming from live Thaumarchaeota at depth and was partly preserved. In any case, it is not yet known what exactly the preferred environment for Thau- marchaeota is, as they have been found to be active in low and high ammonia and low and high oxygen environments (Martens-Habbena et al., 2009; Erguder et al., 2009; Hatzenpichler, 2012). 3.4.2. Activity indicators and label uptake during incubation Several parameters can be monitored during the incubation experiments to cast a light on sedimentary microbial activities stimulated by the addition of substrates. During incubation, a decrease of oxygen penetration depths would indicate an increased aerobic metabolism at the surface, utilizing oxygen and preventing it from penetrating deeper, which was expected in the slices where organic carbon was added. However, at station 1, this was not observed and oxygen penetration depths only decreased in the background core (Table 2). This could be due to the aeration carried out by bubbling air into the bottom water of the core, and oxygen penetrating deeper into the sandy sediment. However, the cores from station 2 showed a decrease of oxygen penetration depth after incubation, except for the core incubated with pyruvate and inhibitor. Also the cores from station 3, i.e. those where oxygen penetration depth could be measured, showed a decrease, indicating that the oxygen was consumed upon incubation, independent of the type of substrate added to the cores. Ammonia and nitrite concentrations in the bottom water showed no changes during the incubations. No significant differences can be seen if the cores incubated with and without nitrification inhibitor are compared, indicating that either the communities are not affected by it, or potentially that the inhibitor was not as effective in a sedimentary environment as in water incubations (e.g. due to adherence to particles). Nitrate concentrations were, at station 2 and station 3, below detection limit after 6 and 5 days, respec-

69 Chapter 3 tively, suggesting consumption of nitrate (Table 2). This may indicate a strong contribution of denitrification to organic carbon processing in these sediments in the sections below oxygen penetration depth. The increase in δ13C of the DIC in the bottom water of all cores compared to the background cores (Table 2) clearly showed that the organic substrates added were respired. Previous labeling experiments with similar substrates have been successful in detecting uptake 13 of C-label into bacterial PLFA (e.g. Guilini et al., 2010), resulting in a highly labeled C16:0, among other PLFAs. Indeed, the strong labeling of the bacterial PLFA C16:0 at station 3 indicated that the organic substrates were readily taken up by bacteria, and potentially non-photosynthetic eukaryotes (PLFA C16:0, C18:0), and incorporated into their biomass. Intriguingly, no incorporation was observed upon labeling with bicarbonate, which is in contrast to other studies with oligotrophic sediment cores who used similar concentrations (e.g. Guilini et al., 2010). The amount of PLFA generated by chemoautotrophs present might have been too low to allow unambiguous detection of the incorporation in this case. The most abundant archaeal lipids were crenarchaeol, a lipid specific for Thaumarchaeota (Sinninghe Damsté et al., 2002; de la Torre et al., 2008; Schouten et al., 2008; Pitcher et al., 2011b; Sinninghe Damsté et al., 2012), and GDGT-0, a lipid produced by Thaumarchaeota as well as some other Archaea (cf. Koga and Nakano, 2008). Their concentrations did not substantially change upon incubation, suggesting that Thaumarchaeota abundances did not change (Fig. 5 showing an average of all incubated cores, with standard deviations). However, this could also indicate that the majority of IPLs in these sediments were fossil (cf. Schouten et al., 2010; Logemann et al., 2011; Lengger et al., 2012a) and not part of living Thaumarchaeota, and thus not affected at all by the incubation. This could include HPH-GDGTs as well, though it is also possible that the bias during analysis, i.e. loss during silica column chromatography (cf. Lengger et al., 2012b), resulted in an underrepresentation of HPH- derived GDGTs. The biphytanes analyzed included a-, bi- and tricyclic biphytane, which are mainly derived from the two most abundant GDGTs: GDGT-0 (acyclic; general archaea), and crenarchaeol (bi- and tricyclic; Thaumarchaeota). Importantly, in nearly all of the incubation experiments, the δ13C values of all measured biphytanes, including those derived from crenarchaeol, changed by less than 2‰ and sometimes even decreased in 13C-content compared to the background values (Fig. 6). In some of the experiments, mainly at station 1, a slight enrichment in the tricyclic biphytane, derived from crenarchaeol, of up to 4 ± 2‰ was observed though this difference is not statistically significant for individual experiments. Furthermore, the bicyclic biphytane, also predominantly derived from crenarchaeol, shows, in general, lower 13C-enrichments than the tricyclic biphytane and also no statistically significant enrichments for individual experiments. Thus, there is no evidence for substantial uptake of 13C-label in archaeal GDGTs, contrary to what is observed for the PLFA. This apparent lack of uptake could be due to three reasons. Firstly, it is possible that the Thau- marchaeota were active, but the substrates were not taken up. As the metabolism of the different Thaumarchaeota could be diverse, this is possible, but, in case of the bicarbonate incubations, unlikely, as in sea water incubations as well as enrichment cultures – including those of sedimentary Thaumarchaeota – 13C from bicarbonate has been shown to be readily incorporated into biphytanes (Wuchter et al., 2003; Park et al., 2010; Pitcher et al., 2011c). Secondly, it is possible that most of the IPLs measured (i.e. MH- and DH-GDGTs, assuming the chromatographic discrimination against the HPH-GDGTs) are fossil, and thus only a small amount of these IPLs 70 Discussion are part of live and active sedimentary Thaumarchaeota. Finally, it is also possible that a higher proportion of the IPLs are part of sedimentary Thaumarchaeota, but that their metabolism and growth rates are so slow (as opposed to Thaumarchaeota in sea water and enrichment cultures), that no incorporation could be detected over the time scales investigated. Thus, our incubation times of 96–144 h may have been too short. However, longer incubation times inevitably result in spreading of the label over the whole sedimentary food web as e.g. discussed by Radajewski et al. (2003) for stable isotope probing of nucleic acids. This is why this study, and nearly all other incubation studies (e.g. Boschker et al. 1998, Guilini et al. 2010, cf. Middelburg 2013 and references cited therein), including those for sediments (e.g. Middelburg et al. 2000, Moodley et al. 2002), use only a short time interval (mostly just a few days) to avoid this label scrambling. Indeed, our results show that the uptake in bacteria is occurring within a few days suggesting that, if active, microbes rapidly take up label. 3.4.3. Estimating growth rates of Thaumarchaeota and turnover rates of IPL-GDGTs To investigate whether growth rates as well as degradation rates of IPL-GDGTs were responsible for the apparent lack of substantial 13C-labeling, we used data from our experiments to estimate minimal growth rates and the turnover time of IPL-GDGTs. The greatest label incorporation was found at station 1 in the sandy sediment, indicating that Thaumarchaeota may have been active there. If all IPL-GDGT biphytanes are stemming from living cells, and an enrichment of 2‰ of biphytanes is assumed, this can be converted to growth rates by using a formula used for growth of phytoplankton based on the isotope dilution theory of Laws (1984;

Eq. (1)), with µ representing the growth rate, tinc the incubation time, P* the atom%-excess of the product, in our case the biphytane, and A* the atom%-excess of the substrate added (cf. alkenone lipids for eustigmatophyte algae; Popp et al., 2006):

(1) Unfortunately, as natural concentrations of the added substrates were not determined, A* could not be calculated for the incubation experiments with pyruvate, glucose and amino acids. In the bicarbonate experiments, we calculated A* based on the amount of added 99%-labeled DIC and natural δ13C and concentration of DIC (Table 2). For P* we used the highest enrichment observed at 6–7 depth with no inhibitor, i.e. 4‰. This gives an estimate of the maximum µ as 6.3 × 10–4 d–1, corresponding to a generation time of 3 yr. Clearly, for the other bicarbonate experiments which resulted in even less label incorporation, generation times will be much higher (e.g. for a 2 ‰ enrichment, 9 yr). Interestingly, growth rates as low as estimated here have been predicted by Valentine (2007), who stated that the archaeal domain, other than bacteria and eukaryotes, has adapted to low energy conditions and is thus characterized by the exceptional ability to live in low energy environments. They are thus not fast in adapting to settings with higher concentrations of available carbon and redox substrates. However, this has not been observed for pelagic Thaumarchaeota as SIP experiments showed a substantial enrichment in 13C in IPL-GDGTs (Wuchter et al., 2003; Pitcher et al., 2011c) in incubation experiments of 168 and 24 h duration, respectively. Indeed, the generation times calculated from enriched North Sea water labeling experiments conducted by Wuchter et al. (2003; A*=5%; P*=0.46% – 400 ‰ enrichment) and Pitcher et al. (2011c; A*=9%; P*=0.07% – 44‰ enrichment) were at least an order of magnitude lower than observed here – 50 and 88 d, respectively. Also sedimentary 71 Chapter 3

Thaumarchaeota have been shown to incorporate 13C from bicarbonate in enrichment cultures (Park et al., 2010). The growth rates reported here might be an underestimation if a large proportion of archaeal cells is fossil; and the use of lipid turnover times might be more suitable, as discussed below. Slow growth could potentially be due to the experiments not being carried out in situ on the sea floor. However, incubations were carried out in whole, intact sediment cores, in the dark, immediately after recovery, and at in situ temperatures in order to minimize the deviations from in situ conditions, although, admittedly, the pressure was at atmospheric conditions. Therefore, this is unlikely to explain the low growth rates. The calculations above assume exponential growth of sedimentary Thaumarchaeota and an immediate translation of this signal into the lipid pool. If, on the other hand, steady state conditions are assumed, i.e. cell numbers and lipid concentrations are not increasing but remain constant, the turnover time for the sedimentary lipid pool tto can be calculated according to Lin et al. (2012) : A* ⋅t t = inc to P* (2) Using Eq. (2), the turnover time of IPL-crenarchaeol in sediments would thus be at least ~4 yrs based on the 4‰ enrichment of the tricyclic biphytane in the bicarbonate incubation experiment. Since labeling was not detected in the other sediments, this turnover time estimate is likely to be a minimal estimate. This large turnover time is not an unusual postulate for thaumarchaeal lipids in sediments, as also Lin et al. (2012) found very low 13C incorporation rates of labeled glucose into sugar moieties of glycosidic GDGTs over >400 d in slurry incubations of subsurface sediments and used these to estimate turnover times of diglycosyl-lipids of 1,700–20,500 years. Similarly, recently published degradation experiments by Xie et al. (2013) using 14C-labeled IPL-diether lipids found very high turnover times and estimated half-lives of up to 310 kyr under energy-deprived subsurface conditions. This is in strong contrast to GDGTs in the water column: Using the SIP data of Wuchter et al. (2003) and Pitcher et al. (2011c) from incubations of North Sea water, we obtained tto of 76 and 128 d, respectively, for the thaumarchaeal GDGTs. Our results are similar to those obtained by in situ-incubations carried out by Takano et al. (2010) and Nomaki et al. (2011), i.e. they did not observe significant incorporation after 405 days into the biphytanyl chains either (even though one single data point after 9 days does show a 10‰ enrichment), though they did observe incorporation into the glycerol moiety. A possibility, as suggested earlier, is that biphytanyl chains are not or hardly produced by sedimentary Thau- marchaeota, but recycled, and the sugar headgroups and/or the glycerol are only newly generated and 13C-labeled. In this case, isotope ratios of whole ether lipids instead of the biphytanes would enable detection of the label, but this involves laborious clean-up of the isolated ether lipids (Takano et al., 2010). However, as also the incorporation into the sugar headgroups of GDGTs, as reported by Lin et al. (2012), is similarly low, it suggests that there is indeed a lack of, or only a very slow 13C-uptake into IPL-GDGTs. It seems that stable carbon isotope probing using biphytanes is most likely not the method of choice for thaumarchaeal activity measurements in sediments, where conditions are favorable for preservation of fossil GDGTs, thus creating a large background signal. In the water column, however, where growth of Thaumarchaeota is faster and lipids are likely degraded on shorter time scales, due to the abundant presence of oxygen and lack of mineral matrix protection (Keil 72 Discussion/Conclusion et al., 1994; Hedges and Keil, 1995), stable isotope incubations are useful for determining activities of Thaumarchaeota. In sediments that contain a high proportion of fossil IPL-GDGTs which are not part of live Archaea, the incorporation of 13C into the lipids of the few active Thaumarchaeota is probably not enough to change the δ13C of the IPL-GDGTs to a significant degree over the commonly used time scales of SIP experiments. 3.5. Conclusion Incubations of sediment cores from the Iceland Shelf were used in order to determine the metabolism of sedimentary Thaumarchaeota. Thaumarchaeal IPLs were present in sediment cores recovered from the Iceland Shelf and the presence of labile IPL-biomarkers for Thaumarchae- ota, such as HPH-crenarchaeol, suggested the presence of living Thaumarchaeota. However, incubations with 13C-labeled substrates bicarbonate, pyruvate, glucose and amino acids did not result in any substantial incorporation of the 13C into the biphytanyl chains of these lipids. Turn- over times and generation times of thaumarchaeal lipids were estimated to be at least several years, suggesting slow growth of sedimentary Thaumarchaeota in contrast to other sedimentary organisms, and/or a slow degradation of IPL-GDGTs, in contrast to bacterial or eukaryotic PLFAs.

Acknowledgements We thank Dr. Y. Takano and one anonymous reviewer for their useful comments which greatly improved the manuscript. The authors would like to thank the Master and crew of the R/V Pelagia and the participants of the Long Chain Diols Cruise 64PE341, in particular M. Baas, S. Rampen, M. Besseling, L. Handley and W. Lenthe, as well as the NIOZ technical department (Y. Witte, J. Schilling). We would also like to thank L. Moodley, H.T.S. Boschker, L. Pozzato, J. Mid- delburg, G. Duineveld and M. Lavaleye for helpful advice in planning the experiments and K. Koho / Utrecht University and L. Stal and N. Bale for providing equipment. We are grateful for analytical assistance to J. van Ooijen, S. Crayford, A. Mets, M. Verweij and J. Ossebaar. S.K.L. was funded by a studentship from the Darwin Center for Biogeosciences to S. S. This is a publication nr. DW-2013-1007 of the Darwin Center for Biogeosciences.

73 Chapter 3

BG Bic Pyr BG + Inh Bic + Inh Pyr + Inh 0-1 cm

107 -1 e 106

105 IPL abundanc [SRM area . mL ]

104 MH DH HPH MH DH HPHMMH DH HPHMHDHHPH HDHHPH MH DH HPH 1-2 cm

107 -1 e

106

IPL abundanc 10 [SRM area . mL ]

104 MH DH HPH MH DH HPHMMH DH HPHMHDHHPH HDHHPH MH DH HPH 6-7 cm

107 -1 e 106

105 IPL abundanc [SRM area . mL ]

104 MH DH HPH MH DH HPHMMH DH HPHMHDHHPH HDHHPH MH DH HPH

Monohexose-crenarchaeol Dihexose-crenarchaeol Hexose, phosphohexose-crenarchaeol

Figure S1: IPL-crenarchaeol profiles of the incubated cores (station 1) - background (BG), bicarbonate (Bic) and pyruvate (Pyr) without (left plot) and with nitrification inhibitor (right plot). Top graphs shows the values in SRM area . mL–1 from 0–1 cm depth, graphs in the middle the profiles from 1–2 cm depth and at the bottom the profiles from 6–7 cm depth

74 Supplementary Material

BG Bic Pyr BG + Inh Bic + Inh Pyr + Inh 0-1 cm

105 -1 e

104 IPL abundanc [SRM area . mL ]

103 MH DH HPH MH DH HPHMMH DH HPHMHDHHPH HDHHPH MH DH HPH 1-2 cm -1 e 105

104 IPL abundanc [SRM area . mL ]

103 MH DH HPH MH DH HPHMMH DH HPHMHDHHPH HDHHPH MH DH HPH 6-7 cm

5 -1

e 10

104 IPL abundanc [SRM area . mL ]

103 MH DH HPH MH DH HPHMMH DH HPHMHDHHPH HDHHPH MH DH HPH

Monohexose-crenarchaeol Dihexose-crenarchaeol Hexose, phosphohexose-crenarchaeol

Figure S2: IPL-crenarchaeol profiles of the incubated cores (station 2) - background (BG), bicarbonate (Bic) and pyruvate (Pyr) without (left plot) and with nitrification inhibitor (right plot). Top graphs shows the values in SRM area. mL–1 from 0–1 cm depth, graphs in the middle the profiles from 1–2 cm depth and at the bottom the profiles from 6–7 cm depth.

75 Chapter 3 Supplementary Material H H H HP HP HP DH DH DH MH MH AA+Inh MH H H H HP HP HP DH DH DH from 0–1 cm depth,cm from 0–1 graphs in MH MH MH Glu+Inh –1 H H H HP HP HP DH DH DH MH MH MH Pyr + Inh PH PH PH HH HH HH HD HD HD Bic + Inh PH PH PH HH HH HH HD HD HD Hexose, phosphohexose-crenarchaeol BG + Inh H H H HP HP HP DH DH DH AA MH MH MH H H H HP HP HP DH DH DH Glu MH MH MH Dihexose-crenarchaeol HM HM HM HP HP HP DH DH DH Pyr MH MH MH HM HM HM HP HP HP DH DH DH Bic MH MH MH H H H HP HP HP DH DH DH BG Monohexose-crenarchaeol MH MH MH 8 7 6 5 4 8 7 6 5 4 8 7 6 5 4

10 10 10 10 10

] mL . area [SRM ] mL . area [SRM ] mL . area [SRM

-1 -1 -1

e abundanc IPL e abundanc IPL e 0-1 cm abundanc IPL 1-2 cm 6-7 cm the middle profiles from 1–2 cm depth and at the bottom profiles from 6–7 cm depth. Figure S3: IPL-crenarchaeol profiles of the incubated cores (station 3) - background (BG), bicarbonate (Bic), pyruvate (Pyr), glucose (Glu) and amino acids (AA) without (left plot) and with Topnitrification inhibitorgraphs (rightvalues shows the plot). in SRM area. mL 76

4. Abundance and diversity of denitrifying and anammox bacteria in seasonally hypoxic and sulfidic sediments of the saline Lake Grevelingen

Yvonne A. Lipsewers, Ellen C. Hopmans, Filip J.R. Meysman, Jaap S. Sinninghe Damsté, and Laura Villanueva

Denitrifying and anammox bacteria are involved in the nitrogen cycling in marine sediments but the environmental factors that regulate the relative importance of these processes are not well constrained. Here, we evaluated the abundance, diversity and potential activity of denitrifying, anammox, and sulfide-dependent denitrifying bacteria in the sediments of the seasonally hypoxic saline Lake Grevelingen, known to harbor an active microbial community involved in sulfur oxidation pathways. Depth distributions of 16S rRNA gene, nirS gene of denitrifying and anammox bacteria, aprA gene of sulfur-oxidizing and sulfate-reducing bacteria, and ladderane lipids of anammox bacteria were studied in sediments impacted by seasonally hypoxic bottom waters. Samples were collected down to 5 cm depth (1 cm resolution) at three different locations before (March) and during summer hypoxia (August). The abundance of denitrifying bacteria did not vary despite of differences in oxygen and sulfide availability in the sediments, whereas anammox bacteria were more abundant in the summer hypoxia but in those sediments with lower sulfide concentrations. The potential activity of denitrifying and anammox bacteria as well as of sulfur-oxidizing, including sulfide-dependent denitrifiers and sulfate-reducing bacteria, was potentially inhibited by the competition for nitrate and nitrite with cable and/or Beggiatoa-like bacteria in March and by the accumulation of sulfide in the summer hypoxia. The simultaneous presence and activity of organoheterotrophic denitrifying bacteria, sulfide-dependent denitrifiers and anammox bacteria suggests a tight network of bacteria coupling carbon-, nitrogen- and sulfur cycling in Lake Grevelingen sediments.

Frontiers in Microbiology 7, 1661, 2016

79 Chapter 4

4.1. Introduction Nitrogen availability is a major factor controlling primary production in temperate coastal marine environments with high anthropogenic nitrogen input (Herbert, 1999). Denitrification is a key process in the nitrogen cycle of coastal sediments releasing gaseous end products, nitric oxide (NO), nitrous oxide (N2O) and dinitrogen gas (N2) to the atmosphere. This nitrogen removal can result in a decrease of nitrogen availability for primary producers and thereby controlling the rate of eutrophication in coastal marine systems (Seitzinger 1988; Herbert 1999). Multiple microbial mediated pathways result in the removal of nitrogen in anoxic sediments (see Devol, 2015 for a detailed review). Here we focus on (1) denitrification, the stepwise conversion of nitrate/nitrite to dinitrogen gas which is mainly performed by facultative organoheterotrophic anaerobic bacteria and some archaea (Zumft, 1997); (2) anaerobic ammonium oxidation (anammox), the oxidation of ammonium with nitrite to dinitrogen gas carried out by anammox bacteria (Kuypers et al., 2003); and (3) sulfide-dependent denitrification, the oxidation of sulfide with nitrate performed by autotrophic members of α-, β-, γ- and ε-proteobacteria, which could contribute to denitrification and to the removal of sulfide in the oxygen transition zone of coastal marine sediments (Shao et al., 2010). Numerous environmental factors, such as the availability of nitrogen speciation and concentration, temperature, oxygen concentrations, organic matter quality and quantity, bioturbation and other sediment characteristics have been suggested to affect the distribution and abundance of denitrifying and anammox bacteria (Thamdrup and Dalsgaard 2002; Meyer et al., 2005; Jen- sen et al., 2008; Dang et al., 2010; Laverock et al., 2013; Prokopenko et al., 2013; Babbin et al., 2014; Zhang et al., 2014). In this study, we assessed the effects of hypoxia and elevated sulfide concentration on the abundance and activity of denitrifiers and anammox bacteria in marine sediments as these factors have been previously suggested as potential limiting factors in denitrification processes (Brunet and Garcia-Gil, 1996; Burgin and Hamilton, 2007; Aelion and Wart- tinger, 2010; Neubacher et al., 2011; 2013; Bowles et al., 2012). Seasonal hypoxia is an increasing – phenomenon that occurs in coastal areas causing a decrease in the electron acceptors (O2, NO3 ) in the bottom waters (Diaz & Rosenberg 2008). Besides, sulfide inhibition can decrease denitrification rates as the enzyme catalyzing the reduction of nitrous oxide to N2 is sensitive to sulfide (e.g. Porubsky et al., 2009). In addition, several studies have provided putative evidence indicating that sulfide inhibits the anammox reaction. For example, Dalsgaard et al. (2003) reported a decrease in anammox activity in the sulfidic waters of the anoxic basin of Golfo Dulce (Costa Rica). Also Jensen et al. (2008) showed that sulfide had a direct inhibiting effect on the activity of anammox bacteria in the Black Sea. In this study, we evaluated the impact of environmental factors, such as oxygen and free sulfide concentrations in the diversity, abundance, activity, and spatial distribution of bacteria involved in N2 removal pathways in sediments of Lake Grevelingen (The Netherlands), a seasonally hypoxic saline reservoir. Here, we determined the diversity, abundance and potential activity of denitrifying bacteria, anammox bacteria and sulfur-oxidizing bacteria (SOB), including sulfide-dependent denitrifiers, and sulfate-reducing (SRB), in three different stations within the lake both in March (before hypoxia) and August (i.e. during hypoxia). In order to determine changes in the diversity, abundance and activity of denitrifiers, we targeted the nirS gene, encoding for the cytochrome cd1 nitrite reductase, catalyzing nitrite reduction to nitric oxide (NO) (Braker et al., 1998; Smith et al., 2007; Huang et al., 2011). Here, we focused on the cytochrome 80 Introduction/Material and Methods cd1-containing nitrite reductase (nirS gene), as it has been found to be more widespread in the bacterial communities compared to the copper-containing nitrite reductase (nirK) in various sediments (Braker 1998; Priemé et al. 2002; Liu et al. 2003; Throbäck et al. 2004; Tiquia et al. 2006; Oakley et al. 2007; Dang et al. 2009; Huang et al. 2011). For anammox bacteria, the nirS gene was also quantified as it has been recently suggested to be a functional biomarker anammox bacteria (Li et al., 2011). Both, denitrifying and anammox bacteria harbor one copy of the nirS gene, indicating that the nirS gene might be a suitable marker to compare the abundance and distribution of nirS-type denitrifiers and anammox bacteria in coastal sediments. The potential activity of denitrifying and anammox bacteria was also determined by estimating the gene expression of those metabolic genes as in previous studies (Smith et al., 2007; Lam et al., 2009; Bale et al., 2014; Bowen et al., 2014; Zhang et al., 2014; Chapter 2). Besides functional genes, the abundance of anammox bacteria was also determined by the quantification of ladderane lipids, which are specific lipid biomarkers for this microbial group (Sinninghe Damsté et al., 2002; Jaeschke et al., 2009; Russ et al., 2013). Finally, the diversity and abundance of sulfur-oxidizing and sulfate-reducing bacteria in marine sediments was estimated by targeting the aprA gene encoding the adenosine-5’-phosphosulfate (APS) reductase (Lenk et al., 2011; Blazejak and Schippers, 2011; Dyksma et al., 2016). The APS reductase is operating in in SOB, oxidizing sulfite to APS, as well as in SRB, operating in reverse direction, converting APS to adenosine monophosphate (AMP) 2– and sulfite (SO3 ) (Meyer and Kuever, 2007b). Our starting hypothesis is that the abundance and potential activity of organoheterotrophic denitrifiers and anammox bacteria would decrease upon increase of the sulfide concentration found in the sediments during the summer hypoxia. Moreover, recent studies point out that sulfide-dependent denitrifiers play a relevant role in the sulfide transition zone of intertidal -sedi ments (Dyksma et al., 2016). Therefore, we hypothesize that their abundance and activity would be higher in hypoxic and sulfidic conditions, thus contributing more to the general 2N removal in comparison to organoheterotrophic denitrifying and anammox bacteria and eventually being involved in sulfide detoxification which could promote anammox activity. 4.2. Material and Methods 4.2.1. Study site and sampling Lake Grevelingen is a former estuary within the Scheld- Rhine- Meuse delta, and was formed by the construction of the Grevelingendam on the landside in 1964 and the Brouwersdam on the seaward side in 1971. The lake (surface area: 108 km2, mean water depth 5.3 m) mainly consists of shallow water areas with the exception of the former tidal gullies, that have a water depth of up to 48 m (Keldermann 1984; Nienhuis and De Bree, 1984). After its closure, the lake transformed into a freshwater body, but in 1979, the connection with the North Sea was partially re-established, and since then, Lake Grevelingen has a high and relatively constant salinity (29−32). Within Lake Grevelingen, the Den Osse basin forms a deeper basin within the main gully, and experiences a regular seasonal stratification leading to oxygen depletion in the bottom water (summer hypoxia) (Wetstejn, 2011). Due to sediment focusing, the Den Osse basin (maximum water depth 34 m) also experiences a rapid accumulation of fine-grained, organic rich sediments (sediment accumulation rate ~2 cm yr–1; Donders, 2012). Sediment cores were collected along a depth gradient in Den Osse basin during two cruises March and August 2012 on board of the RV Luctor. Sampling took place at three different sta- 81 Chapter 4 tions: S1 was located in the deepest point of the basin at 34 m water depth (51.747°N, 3.890°E), S2 at 23 m (51.749°N, 3.897°E) and S3 at 17 m (51.747°N, 3.898°E). Sediment was collected with single core gravity corer (UWITEC) using transparent PVC core liners (6 cm inner diameter, 60 cm length). Four sediment cores were collected at each station in March and in August. The cores were sliced with a 1 cm resolution until 5 cm depth, and sediment samples were collected for lipid and DNA/RNA analysis and kept at –80ºC until further processing. In each sampling campaign, a water column depth profile of temperature, salinity and oxygen (O2) concentration was recorded at S1 using an YSI 6600 CTD instrument (for details see Hagens et al., 2015). Oxygen concentrations recorded by the CTD instrument were calibrated based on dis- crete water samples using an automated Winkler titration procedure (Knap et al., 1996). Bottom + – – water concentrations of ammonium (NH4 ), nitrite (NO2 ) and nitrate (NO3 ) were measured colometrically on a SEAL QuAAtro segmented flow nutrient analyzer. Monitoring data at Lake Grevelingen (Wetstejn, 2011) shows that the water column is laterally homogenous over the Den Osse basin scale, which allows estimation of the bottom water parameters at S2 and S3 from corresponding depths in the measured CTD profiles at station S1. 4.2.2. Sediment geochemistry

High-resolution depth profiles of 2O and sulfide (H2S) were measured in intact sediment cores to determine the oxygen penetration depth (OPD) and the sulfide appearance depth (SAD), using commercial micro-electrodes (Unisense A.S., Denmark) operated with a motorized micromanipulator (for details on the procedure see Malkin 2014). The oxygen penetration depth (OPD) is operationally defined as the depth below which [O2] < 1 µM, while the sulfide appearance depth

(SAD) is operationally defined as the depth below which [H2S] > 1 µM (Seitaj et al., 2015). Sediment cores were sectioned in increments of 0.5 cm from the sediment-water interface to 5 cm depth, and pore water was extracted by centrifugation, and analyzed following the procedure of (Sulu-Gambari et al., 2016). After filtration through 0.22 µm cellulose filters (Chromafil

Xtra), pore water samples were analyzed for total free sulfide (∑H2S) via spectrophotometry + (Cline, 1969; standard deviation ± 0.4 µM), whereas ammonium (NH4 ) was determined by a SEAL QuAAtro segmented flow analyzer (Aminot et al., 2009) after a 25 times dilution with a low nutrient seawater matrix solution (standard deviation ± 3.5%). The free sulfide and ammonium concentration depth profiles of the sediment pore water were averaged to provide a 1 cm resolution down to 5 cm sediment depth to enable a direct comparison with results of the DNA/RNA and lipid analysis. The total organic carbon (TOC) content of the sediment was determined on sediment samples that were freeze-dried, ground to a fine powder and analyzed by an a Thermo Finnigan Delta plus isotope ratio monitoring mass spectrometer (irmMS) connected to a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan). Before the analysis, samples were first acidified with 2N hydrogen chloride (HCl) to remove the inorganic carbon (Nieuwenhuize et al., 1994). Concentrations of TOC are expressed as mass % of dry sediment. 4.2.3. DNA/RNA extraction DNA and RNA from sediments (previously centrifuged to remove excess of water thus values are given as grams of wet weight; S1, S2 and S3; 0–5 cm sediment depth; 1 cm resolution) were extracted by using the DNA and RNA PowerSoil® Total Isolation Kit, respectively (Mo Bio Laboratories, Inc., Carlsbad, CA). Nucleic acid concentrations were quantified spectrophoto- 82 Material and Methods metrically (Nanodrop, Thermo Scientific, Wilmington, DE) and checked by agarose gel electrophoresis for integrity. Extracts were kept frozen at –80°C. The RNA extracts were treated with RNase-free DNase (DNA-free™, Ambion Inc., Austin, TX), and RNA quality and concentration were estimated by the Experion RNA StdSens Analysis Kit (Bio-Rad Laboratories, Hercules, CA). DNA contamination was checked by PCR using RNA as a template. Reverse transcription was performed as specified in Chapter 2. 4.2.4. PCR amplification and cloning Amplifications of thenirS gene of denitrifying bacteria (S1, S2, S3, March and August, 0–1 cm), and anammox bacteria 16S rRNA gene (S2, March, 1–2 cm), specific nirS genes of Scalindua sp. (S3, August, 0–1 cm) and the aprA gene (S2, August, 0–1 cm) were performed with the primer pairs specified in Table S1. The PCR reaction mixture consisted of (final concentration): Q-solution (PCR additive, Qiagen, Valencia, CA) 1 ×; PCR buffer 1 ×; BSA (200 µg mL–1); dNTPs –1 (20 µM); primers (0.2 pmol µL ); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA). PCR conditions for these amplifications were: 95°C, 5 min; 35 × [95°C, 1 min; Tm, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen, Valencia, CA) and cloned in the TOPO-TA cloning® kit (Life Technologies, Carlsbad, CA) and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. In addition, in order to test the specificity of the quantitative PCR reaction we repeated the reactions of anammox bacteria 16S rRNA gene (Broc541F - Amx820R) with DNA extract of S2, March, 0–1 cm, nirS gene of heterotrophic denitrifying bacteria (nirS1F - nirS3R) with cDNA of S2, March, 0–1 cm, and aprA gene (Apr1F- Apr5R) with cDNA of S2, August, 0–1 cm, which were then treated to add 3’-A-overhangs and then cloned with the TOPO-TA cloning® kit as indicated above. Recombinant plasmid DNA was sequenced using the M13R primer by Macrogen Inc. (Amsterdam, The Netherlands). 4.2.5. Phylogenetic analysis Sequences were analyzed for the presence of chimeras using the Bellerophon tool at the Green- Genes website (http://greengenes.lbl.gov/). Sequences were aligned with MEGA6 software (Tamura, 2013) by using the alignment method ClustalW. The phylogenetic trees of the nirS and aprA genes were computed with the Neighbour-Joining method (Saitou and Nei, 1987) using the Poisson model with a bootstrap test of 1,000 replicates. The phylogenetic affiliation of the partial anammox bacteria 16S rRNA gene sequences was compared to release 123 of the SILVA NR SSU Ref database (http://www. arb-silva.de/; Quast et al., 2013) using the ARB software package (Ludwig et al., 2004). Sequences were added to the reference tree supplied by the SILVA database using the ARB Parsimony tool. Sequences were deposited in NCBI with the following accession numbers: KP886533–KP886678 for nirS gene sequences of denitrifiers, KP886679– KP8866700 for 16S rRNA gene sequences of anammox bacteria, KP886701–KP886721 for nirS gene sequences of anammox bacteria and KP886722–KP886804 for aprA gene sequences of SOB and SRB. 4.2.6. Quantitative PCR (qPCR) analysis qPCR analyses were performed on a Biorad CFX96TM Real-Time System/C1000 Thermal cycler equipped with the CFX ManagerTM software for sediment DNA/RNA extracts (S1, S2 and S3; 0–5 cm sediment depth; 1 cm resolution). Detailed information about the primers used in this

83 Chapter 4 study are summarized in Table S1. The abundance of denitrifying bacteria specificnirS gene was quantified using the primer set nirS1F/nirS3R as described by Braker et al. (1998). The abundance of anammox bacteria 16S rRNA gene was estimated using primers Brod541F/Amx820R as described by Li et al. (2010). Additionally, a fragment of the Scalindua sp. specific nirS gene, which codes for the cytochrome cd1-containing nitrite reductase, was quantified using the primer combination Scnir372F/Scnir845R as described by Lam et al. (2009). The abundance of SOB and SRB including sulfide dependent denitrifiers was estimated by targeting the dissimilatory adenosine-5’-phosphosulfate (APS) reductase (aprA gene) involved in the APS reduction of sulfur-oxidizing bacteria and in the sulfite oxidation of sulfate-reducing bacteria by using the primer combination Apr-1-FW/Apr-5-RW as described by Meyer and Kuever (2007a) (see Table S1 for details). Gene abundances are expressed as copies g–1 sediment of wet weight. All qPCR amplifications were performed in triplicate with standard curves ranging from 100 to 107 molecules per microliter. Standard curves and qPCR amplifications were performed as previously described in Chapter 2. Coefficients of determination R( 2) for standard curves ≥ 0.998 and qPCR efficiencies (E) ≥ 80% were accepted. 4.2.7. Anammox bacteria ladderane lipid analysis Intact polar lipids (IPLs) were extracted with the Bligh and Dyer extraction method (Bligh 1959; mod. by Pitcher et al., 2011) as described in detail by Bale et al. (2014). Intact ladderane phospholipids specific for anammox bacteria, the 20C -[3]-monoether ladderane attached to a phosphatidylcholine (PC) headgroup (PC-monoether ladderane) was analyzed by HPLC-MS/MS following Jaeschke et al. (2009) and quantified using an external standard consisting of isolated PC-monoether ladderane. Sediment samples between 0–5 cm depth (1 cm resolution) were analyzed and PC-monoether ladderane lipid concentrations were expressed per nanogram of dry weight sediment (ng g–1). In order to determine the fatty acid composition of the ladderane lipids, aliquots of the Bligh and Dyer extracts (BDE) obtained from the 0–1 and 4–5 cm sediment layers were saponified by reflux with aqueous KOH (in 96% MeOH) for 1 h. Fatty acids were obtained by acidifying the saponified samples to a pH of 3 with 1N HCl in MeOH and extracted using dichloromethane (DCM). The fatty acids were converted to their corresponding fatty acid methyl esters (FAMEs) by methylation with diazomethane (CH2N2) as described by Rush et al. (2012a). Polyunsaturated fatty acids (PUFAs) were removed by eluting the sample over a silver nitrate (AgNO3) (5 %) impregnated silica column with DCM and air-dried at room temperature. The fatty acid fractions were dissolved in acetone, filtered through a 0.45 μm polytetrafluoroeth- ylene (PTFE) filters (4 mm diameter), and analyzed by high performance liquid chromatography coupled to positive ion atmospheric pressure chemical ionization tandem mass spectrometry (HPLC/APCI-MS/MS) in selective reaction monitoring (SRM) mode following Hopmans et al. (2006) including the recent modifications described by Rush et al. (2012b). Ladderane lipids were quantified using external calibration curves of three standards of isolated methylated ladderane fatty acids (C20-[3]-ladderane fatty acid, and C20-[5]-ladderane fatty acid) (Hopmans et al., 2006; Rush et al., 2011). 4.3. Results Sediment samples were collected along a depth gradient in Den Osse basin (Lake Grevelingen) during two cruises March (before summer hypoxia) and August (during summer hypoxia) 2012. Sampling took place at three different stations: S1 was located in the deepest point of the basin 84 Material and Methods/Results at 34 m water depth, S2 at 23 m and S3 at 17 m. 4.3.1. Environmental conditions The temperature of the bottom water at station S1 (Fig. S1) showed a regular seasonal cycle with lowest values in late winter (1.5 °C in February) and highest values in late summer (16.9 °C in September). During the spring campaign (March 2012), the water column was only partially stratified and showed a limited surface-to-bottom temperature gradient. In contrast, during the summer campaign (August 2012), the water column was thermally stratified. The yearly pattern of the bottom water oxygenation at station S1 was inversely correlated the temperature, with greatest oxygenation levels in winter and fall, and lowest concentrations in summer (Fig. S1). In March 2012, the bottom water oxygenation was similar for all three stations, whereas in August 2012, the bottom water at S1 and S2 were anoxic (< 1 µM), while the bottom water at S3 still had + 88 µM of O2 (36% air saturation). Bottom water ammonium (NH4 ) concentrations in station S1 – ranged from 3 µM in March to 11.5 µM in August; nitrite (NO2 ) concentrations were relatively constant (0.7–1 µM) in March and August. Nitrate concentrations ranged from 28 µM in March to <2 µM in August in station S1 (Fig. S1) whereas in stations S2 and S3 values varied between 28 µM in March to ~10 µM in August. The OPD in the sediment was seasonally variable and increased from S1 to S3, i.e. in S1 in March OPD was 1.5 mm and in August the sediment was completely anoxic. In S2, OPD was between 1.7–2.5 mm in March and in August ca. 0.5 mm (hypoxic) and in S3, the OPD was between 1.5–2.2 mm in March and ca. 1.0 mm (hypoxic) in August. (Table 1). The sulfide appearance depth (SAD) varied between March and August in all stations. The SAD moved towards the sediment surface between March and August in all stations. In March, the SAD in stations S1 and S2 was at 18.4 and 21.3 mm respectively, whereas in S3, the SAD was detected at 41.8 mm sediment depth. However, in August, SAD in stations S1 and S2 was at 0.4 and 0.6 mm, respectively. In station S3, the sulfide was detected at 4.2 mm sediment depth (Table 1). At station S2, white mats of Beggiatoa sp.-like microorganisms covered the sediment surface in March. Small polychaetes were observed in the sediment at station S3 in March, suggesting some bioturbation.

Sulfide (∑H2S) concentrations in the sediment pore water were low in March in all three stations, i.e. ranging from 0 to 0.007 mM, whereas in comparison, all three stations showed high sulfide concentrations in August, i.e. 0.15 to 1.6 mM (Table 1) (see Seitaj, 2015 for detailed geochemical profiles of station S1). Ammonium concentrations were low in March, i.e. ranging from 0.24 + to 0.63 mM on average, in comparison with August when NH4 concentrations reached higher values, i.e. 0.7 to 1.2 mM on average (Table 1). The TOC content of the sediments varied slightly between stations and seasons, ranging between 1.8 and 4.4% (Table S2). 4.3.2. Diversity, abundance and potential activity of nirS-type denitrifiers In our study, we focused on heterotrophic and autotrophic bacteria that are able to perform the dissimilatory reduction of nitrite to nitric oxide. This reaction forms an intermediate step in the complete denitrification of nitrate to N2 and is catalyzed by the cytochrome cd1-containing nitrite reductase encoded by the nirS gene (Braker et al., 2000). The diversity of nirS-type denitrifiers was evaluated for the surface sediment layer (0–1 cm) at the three stations in March and August by phylogenetic analysis targeting the nirS gene (Figs. 1 A, B). In general, the nirS sequences obtained (147 sequences in total) were closely related to nirS sequences of uncultured organisms found in coastal marine environments with a high input of organic matter such as 85 Chapter 4 - 4.2 0.6 0.4 August SAD [mm] 41.8 21.3 18.4 March 0 2.2 2.5 August OPD [mm] 1.5 1.7 1.5 March 694 537 550 836 736 749 746 656 1228 1138 1768 1027 1567 1322 1071 August [μM] + 4 NH 73 671 592 154 979 165 455 526 236 833 333 408 636 410 279 March 93 177 211 802 146 109 810 1190 1238 2063 1157 1008 1962 1639 1503 ) concentrations (1 cm resolution), oxygen penetration depth (OPD) and sulfide appear – August [μM] - HS 0 0 0 2 0 0 0 0 0 0 0 0 0 27 33 March ) and sulfide (HS + 4 1–2 4–5 0–1 1–2 3–4 2–3 4–5 0–1 2–3 3–4 3–4 4–5 2–3 1–2 0–1 [cm] Sediment depth 3 2 1 Station Data are averaged to reach a 1 cm resolution; data provided by Fatimah Sulu-Gambari (2016; unpublished data), **data provided by Dorina Seitaj, by Sulu-Gambari (2016; unpublished data), **data provided Fatimah by a 1 cm resolution; data provided to reach Data are averaged * Sediment porewater ammonia (NH porewater Sediment 1: Table 2015; unpublished data). ance depth (SAD) determined micro-sensor profiling. by 86 Results estuarine sediments and eutrophic bay sediments (Braker et al., 2000, Zhang et al., 2014). The phylogenetic analysis of protein sequences of the nirS gene revealed two distinct clusters (Fig. 1A; cluster 1 and 2), where most (ca. 95%) of the sequences clustered in cluster 1 (ca. 95%). Within cluster 1, approximately 90% of the nirS gene sequences were grouped into subcluster 1.1 and 10% into subcluster 1.2 (Figs. 1 A, B; Fig. S2). Within subcluster 1.1 sequences were affiliated to nirS sequences of members of α-, β- and γ-proteobacteria able to perform autotrophic denitrification coupled to sulfide oxidationThiobacillus ( denitrificans) and heterotrophic denitrification Azospirillum( brasilense, Marinobacter hydrocarbonoclasticus, Kangiella aquamirina, Halomonas sp.). Sequences grouped in subcluster 1.2 were affiliated to the nirS gene sequences of divers α- proteobacteria able to perform autotrophic denitrification coupled to sulfide or iron oxidation (Paracoccus denitrificans, Sideroxidans lithotrophicus), as well as heterotrophic denitrification (e.g. Aromatoleum aromaticum, Azocarus toluclasticus, Acidovorax delafieldii). Sequences grouped into cluster 2 were affiliated to nirS gene sequences of uncultured bacteria detected in coastal marine and estuarine sediments (Braker et al., 2000; Zhang et al., 2014). In order to determine the specificity of the qPCR assay, sequences of nirS cDNA (complementary DNA of nirS mRNA) generated during the qPCR reaction were cloned and sequenced (28 sequences in total) and also added to the protein-coding nirS sequences phylogenetic tree showing that those sequences were grouped in the clusters described before (Figs. 1 A, B). The abundance and distribution of nirS-type denitrifiers was estimated through quantification of the nirS gene copy number in the upper 5 cm (1 cm resolution) of the sediments at the three sampling sites in March and August (Fig. 2). The nirS gene abundance was relatively stable with depth with slightly higher values in station S1 (6.4 × 107 copies g–1 on average) compared to stations S2 and S3 (5.7 × 107 and 5.2 × 107 copies g–1 on average, respectively). Overall, nirS gene abundance was slightly higher in March compared to August in S2 and S3, and this difference was especially evident in station S1. To estimate the potential transcriptional activity of nirS-type denitrifiers, nirS transcripts (mRNA copy numbers) were quantified (data reported in Table S3) and the RNA:DNA ratio was calculated. In station S1, transcripts were only detectable in March in the upper 2 cm of the sediment, 5.6 × 103 copies g–1on average, whereas in August, nirS gene transcripts could only be detected within the 2–3 cm depth layer (102 copies g–1). In station S2, nirS gene transcripts were only detectable in March in the upper 3 cm and numbers varied between 1.9 × 102–1.5 × 103 copies g–1 with the highest value within the 1–2 cm zone. In station S3, the nirS gene transcripts could be detected in March in the upper cm of the sediment (1.5 × 102 copies g–1) and in August for 1–2 cm and for 3–4 cm sediment (1.1 × 102 and 1.8 × 103 copies g–1, respectively ) (Table S3). The ratio of nirS gene and transcript copies (RNA:DNA ratio) was ≤ 0.00013 in all stations in March and August. 4.3.3. Diversity, abundance and potential transcriptional activity of anammox bacteria Most of the anammox bacterial nirS gene sequences obtained in this study (20 sequences out of 21) were part of one cluster (cluster 1, Fig. 3) closely related to nirS sequences of “Candidatus Scalindua profunda” (Van de Vossenberg et al., 2013), and of uncultured bacteria obtained from continental margin sediment of the Arabian Sea (Sokoll et al., 2012) and surface sediments of the South China Sea (Li et al., 2013).

Chapter 4 subcluster 1 1 subcluster (YP005430950) 1 x Station 2, (26) (4) (9) 1) ; cDNA 1) ; cDNA (AJ248421) ; cDNA (20) August + 1 August March, cDNA August A -Proteobacterium ɣ ; ; cDNA -Proteobacterium (AF361789) α -Proteobacterium (WP018076713) β ; August August August + 10 x Station 2, March, cDNA -Proteobacterium (WP018624170) ɣ Azospirillum brasilense ; 4 x Station 1 March 5 19 x Station 2 March 7 16 x Station 3 March 15 August; 0-1 cm Lake Grevelingen sediment (30) Thiobacillus denitriﬁcans August; 0-1 cm Lake Grevelingen sediment (5) August; 0-1 cm Lake Grevelingen sediment (26) August; 0-1 cm Lake Grevelingen sediment (14) Marinobacter hydrocarbonoclasticus August; 0-1 cm Lake Grevelingen sediment (6) August; 0-1 cm Lake Grevelingen sediment (9) August; 0-1 cm Lake Grevelingen sediment (1 August; 0-1 cm Lake Grevelingen sediment (7) uncultured bacterium clone; estuarine sediment, China (EU23587 4) uncultured bacterium clone; estuarine sediment, China (EU23578 3) uncultured bacterium clone; estuarine sediment, China (EU2360 93) uncultured bacterium clone; estuarine sediment, China (EU23596 7) uncultured bacterium; coastal marine sediment, W uncultured bacterium clone; estuarine sediment, China (EU23580 2) uncultured bacterium clone; estuarine sediment, China (EU2359 19) Kangiella aquimarina ; uncultured bacterium clone; estuarine sediment, China (EU23588 0) Station 1, March; 0-1 cm Lake Grevelingen sediment (1) uncultured bacterium clone; estuarine sediment, China (EU23587 3) uncultured bacterium; Baltic Sea sediment (CAJ87437) uncultured bacterium clone; estuarine sediment, China (EU23581 3) uncultured bacterium clone; estuarine sediment, China (EU23580 9) Station 2, March; 0-1 cm Lake Grevelingen sediment Station 3, uncultured bacterium; Baltic Sea sediment (CAJ87431) uncultured bacterium; Baltic Sea sediment (CAJ87433) uncultured bacterium clone; estuarine sediment, China (EU23579 7) Station 2, March; 0-1 cm Lake Grevelingen sediment uncultured bacterium clone; estuarine sediment, China (EU23599 3) uncultured bacterium clone; estuarine sediment, China (EU23574 9) uncultured bacterium clone; estuarine sediment, China (EU2358 28) Station 3, March; 0-1 cm Lake Grevelingen sediment (18) 56 uncultured bacterium clone; estuarine sediment, China (EU23584 1) uncultured bacterium; cyanobacterial aggregate, Baltic Sea (CA D29810) uncultured bacterium clone; estuarine sediment, China (EU23589 7) uncultured bacterium; clone; estuarine sediment, China (EU2358 57) Station 2, March; 0-1 cm Lake Grevelingen sediment (1 uncultured bacterium clone; estuarine sediment, China (EU23607 2) 90 Station 2, March; 0-1 cm Lake Grevelingen sediment Station 1, 48 sequences 0-1 cm Lake Grevelingen sediment: 8 x Station 1 March 3 4 x Station 2 March 7 6 x Station 3 March 10 Station 3, Station 3, Station 1, Station 2, Station 2, March; 0-1 cm Lake Grevelingen sediment (6) Station 3, March; 0-1 cm Lake Grevelingen sediment (5) Station 1, March; 0-1 cm Lake Grevelingen sediment (21) Station 3, Station 1, March; 0-1 cm Lake Grevelingen sediment (10) Station 2, March; 0-1 cm Lake Grevelingen sediment (10) Station 1, March; 0-1 cm Lake Grevelingen sediment (12) 93 Station 1, March; 0-1 cm Lake Grevelingen sediment (14) Station 3, 59 56 Station 1, March; 0-1 cm Lake Grevelingen sediment (5) Station 1, March; 0-1 cm Lake Grevelingen sediment (3) 86 64 62 77 sequences 0-1 cm Lake Grevelingen sed. 0.1 63 Station 2, March; 0-1 cm Lake Grevelingen sediments

cluster 1 cluster cluster 2 cluster subcluster 2 subcluster (28) (28) (27) 18) 1) ; cDNA ; cDNA ; cDNA 1386514) 10091 1748767) (WP015669866) 1236329) (AJ248420) 1241999) (WP01 A (WP024843009) (AJ248438) A -Proteobacterium α -Proteobacterium (WP01 -Proteobacterium (WP0095421 α 10) -Proteobacterium (WP013963004) α -Proteobacterium -Proteobacterium (WP007089813) -Proteobacterium (WP021 α -Proteobacterium (WP019646524) -Proteobacterium (WP021248854) α α August α α α -Proteobacterium (WP013029265) ; ; -Proteobacterium (WP01 ; ; β (AEI95094) β ; ; -Proteobacterium (WP006938174) -Proteobacterium (WP01 (AAB17878) V97354) α -Proteobacterium (WP020593499) α -Proteobacterium(WP018988937) α β -Proteobacterium (WP005793436) August; 0-1 cm Lake Grevelingen sediment (16) (AA August; 0-1 cm Lake Grevelingen sediment (13) β August; 0-1 cm Lake Grevelingen sediment (12) genenirS ofsequences S1, from stations recovered DNA sequences (147 study in this retrieved bacteria denitrifying sp. SO-1 (WP008620648) -Proteobacterium (WP003279945) sp. Sw2 (WP008027070) ɣ (details see part B) -Proteobacterium β ; sp. MR-S7 (WP020228065) sp. BIS7 (WP0194491 uncultured bacterium clone; estuarine sediment, China (EU23596 8) Station 2, Station 1, Station 3, March; 0-1 cm Lake Grevelingen sediment (29) sp. HGDK1 (ACV88081)

August; 0-1 cm Lake Grevelingen sediment (13) Roseobacter litoralis ; Roseobacter litoralis Station 2, March; 0-1 cm Lake Grevelingen sediment Station 1, Station 2, March; 0-1 cm Lake Grevelingen sediment Station 1, March; 0-1 cm Lake Grevelingen sediment (27) Station 3, March; 0-1 cm Lake Grevelingen sediment (30)

Station 1, March; 0-1 cm Lake Grevelingen sediment (27)

uncultured bacterium; marine sediment, W Station 2, March; 0-1 cm Lake Grevelingen sediment

Novispirillum itersonii 63 Rhodobacter Thalassobacter arenae 100 Caenispirillum salinarum ; uncultured bacterium; marine sediment, W Paracoccus denitriﬁcans 99 Ruegeria pomeroyi Ruegeria pomeroyi ; Bradyrhizobium oligotrophicum; Magnetospirillum Paracoccus denitriﬁcans Paracoccus pantotrophus ; Labrenzia aggregata ; Kiloniella laminariae ; Acidovorax Thalassospira xiamenensis Magnetospirillum magneticum ; Station 3, March; 0-1 cm Lake Grevelingen sediment (12) Cupriavidus 100

Aromatoleum aromaticum 2 x Station 3 March, 1 uncultured bacterium clone; estuarine sediment, China (EU23582 7) 5 x Station 1 March, 2 March + (cDNA), Halomonas 100 Station 1, March; 0-1 cm Lake Grevelingen sediment (18) 12 sequences 0-1 cm Lake Grevelingen sediment: 94 Station 1, Azoarcus toluclasticus ;

uncultured bacterium clone; estuarine sediment, China (EU23596 4) uncultured bacterium clone; estuarine sediment, China (EU23595 6)

Sideroxydans lithotrophicus

86 Station 3, March; 0-1 cm Lake Grevelingen sediment (16) Acidovorax delaﬁeldii ; 98

100 71 subcluster 1 Pseudomonas stutzeri ; Thauera terpenica 65 73 100 76 85 100 77 75 100 64 0.1 A) Phylogenetic tree ofFiguretree Phylogenetic 1: partial amplification0–1 (PCR)S2 andcm and sediment by cloningS3 depth, andbetween 28 cDNAand sequences obtainedAugust in fromMarch station S2 between 0–1 cm sediment depth in by March amplificationrecovered (qPCR) and cloning) and closest (bold: relatives our sequences and closest known the scale bar indicates 10 % sequence divergence. relatives); 88 Results

Figure 2: Depth profiles of anammox bacteria 16S rRNA gene abundance [copies g–1] (circle); anammox bacteria nirS gene abundance [copies g–1] (triangle), denitrifying bacteria nirS gene abundance [copies g–1] (square); SOB and SRB aprA gene abundance [copies g–1] (diamond); A) Station 1; B) Station 2; C) Station 3; black symbol: March; white symbol: August.

The diversity of the 16S rRNA gene sequences of anammox bacteria (Fig. S3) obtained from surface sediments (0–1 cm) revealed that most of the sequences (21 sequences derived from PCR plus cloning, and 23 gene sequences obtained from the qPCR assay and further cloning to check the specificity of the qPCR assay) were closely related to Candidatus“ Scalindua” brodae and “Candidatus Scalindua marina” obtained from surface sediments of the Gullmar Fjord (Brandsma et al., 2011), and to sequences detected in OMZ waters of the Arabian Sea, Peru and Namibia (Woebken et al., 2008) and Peruvian coastal margin (Henn, unpublished). Two 16S rRNA sequences were more distantly related to the other sequences, and were closely related to the 16S rRNA sequence of “Candidatus Scalindua wagneri” obtained from a bioreactor (Woeb- ken et al., 2008) (Fig. S3).

We also quantified the C20-[3]-ladderane monoether-PC (for 0–5 cm sediment depth) and ladderane core lipids (for 0–1 and 4–5 cm sediment depth) (Table S4 and S5) as markers for the presence of anammox bacteria. Abundance of PC-monoether ladderane ranged between 0.9–20.4 ng g–1 with highest values in station S1 in March (between 3.4–20.4 and 2.4–7 ng g–1, respectively). PC-monoether ladderane values were relatively constant with depth in August in all stations (between 0.9–7 ng g–1; Table S4). On the other hand, PC-monoether ladderane abundance was always higher in March in the upper 2 cm of the sediment and decreased four-fold between 2 and 5 cm in all stations (on average from 10.7 to 2.5 ng g–1). The summed concentration of the ladderane fatty acids was on average lowest in station S1 (13 ng g–1), with slightly 89 Chapter 4

uncultured bacterium, Peruvian OMZ seawater (ACR07885) uncultured Candidatus Scalindua sp., Black Sea water(AFO85870) Station 3, August; Lake Grevelingen 0-1 cm sediment depth (15) uncultured bacterium, Peruvian OMZ seawater (ACR07884) 58 Candidatus Kuenenia stuttgartiensis (CT573071) Anaerolinea thermophila (WP013561145) uncultured bacterium, Peruvian OMZ seawater (ACR07901) uncultured Candidatus Scalindua sp., Paciﬁc marine water column, USA (AGM49043) 2 sequences subseaﬂoor sediment, South China Sea (ACV84553; ACV84614) 0.25 2 sequences Black Sea water column OMZ (AFO85813; AFO85819) 65 uncultured bacterium, Peruvian OMZ seawater (ACR07879) uncultured bacterium, Peruvian OMZ seawater (ACR07891) uncultured bacterium,Peruvian OMZ seawater(ACR07882) uncultured bacterium, Peruvian OMZ seawater (ACR07881) uncultured bacterium, Peruvian OMZ seawater (ACR07877) uncultured bacterium, Peruvian OMZ seawater (ACR07883) uncultured bacterium, Peruvian OMZ seawater (ACR07890) uncultured bacterium, Peruvian OMZ seawater (ACR07889) Uncultured bacterium, Peruvian OMZ seawater (ACR07875) uncultured CandidatusScalindua sp. Black Sea water (AFO85831) uncultured CandidatusScalindua sp. Black Sea water (AFO85849) Candidatus Scalindua profunda (scal02098) uncultured bacterium, sediment, South China Sea (ACV84622) uncultured Candidatus Scalindua sp. Black Sea water (AFO85782) uncultured bacterium, surface sediment, South China Sea (AEJ85669) cluster 1 50 uncultured bacterium, sediment, Arabian Sea (AFZ84060) Station 3, August; Lake Grevelingen 0-1 cm sediment depth (20) 73 Station 3, August; Lake Grevelingen 0-1 cm sediment depth (5) 54 Station 3, August; Lake Grevelingen 0-1 cm sediment depth (7) Station 3, August; Lake Grevelingen 0-1 cm sediment depth (4) Station 3, August; Lake Grevelingen 0-1 cm sediment depth (18) 15 x Station 3, August; Lake Grevelingen 0-1 cm sediment depth

Figure 3: Phylogenetic tree of partial nirS gene sequences of anammox bacteria retrieved in this study and closest relatives (S3; 0–1 cm Lake Grevelingen sediment; bold: sequences retrieved in March and sequences of known relatives); the scale bar indicates 25% sequence divergence. higher average values in S2 (27 ng g–1), and the highest average values in S3 (41 ng g–1) (Table S5). The summed ladderane fatty acid concentrations were comparable to the abundance of anammox bacteria determined by the 16S rRNA gene quantification in the first centimeter of the sediment obtained in different stations and seasons, whereas the PC-monoether ladderane revealed a different trend compared to the 16S rRNA gene abundance, i.e., was more abundant in March compared to August (Table S4). The abundance of anammox bacteria was determined by the quantification of the 16S rRNA gene copy number of anammox bacteria as well as of the nirS gene copy number of members of the genus “Candidatus Scalindua” (Figure 2) (Strous et al., 2006; Li et al., 2011). Copy numbers of the anammox bacteria 16S rRNA gene ranged between 9.5 × 105 and 8.1 × 107 copies g–1 with highest values in S3 (between 2 × 106 and 8.1 × 107 copies g–1). The abundance of the anammox bacterial 16S rRNA gene was slightly higher in August compared to March in all stations. The “Candidatus Scalindua” nirS gene abundance followed the same depth trend but values were 2 – 3 orders of magnitude lower (between 1.1 × 104 and 9.9 × 104 copies g–1) compared to the anammox bacteria 16S rRNA gene copy numbers. The anammox bacterial 16S rRNA transcript, used as a proxy for the potential transcriptional activity, varied between 1.3 × 103 – 5.1 × 106 copies g–1 of sediment (Table S3). The anammox 16S rRNA transcript copy number varied slightly and reached highest values in S2 and S3 in August between 2–4 cm sediment depth (2.7 × 106 copies g–1 on average). The ratio between 16S rRNA gene and transcript (RNA:DNA ratio) was ≤ 0.32 in all stations in March and August. 90 Results

Anammox bacteria nirS transcript copies were below detection level of the qPCR assay. 4.3.4. Diversity, abundance and potential transcriptional activity of bacteria involved in sulfur cycling Here, we focused on bacteria involved in sulfur cycling, performing dissimilatory sulfur oxidation or sulfate reduction. The dissimilatory APS reductase encoded by the aprA gene is operating 2– in SRB, converting APS to adenosine monophosphate (AMP) and sulfite (SO3 ), as well as in SOB, operating in reverse direction, oxidizing sulfite to APS (Meyer and Kuever, 2007b). The diversity of the microorganisms harboring the aprA gene was evaluated in the first centimeter of the sediment core at S2 in August as the observation of Beggiatoa mats on top indicated the occurrence of sulfide oxidation at this station. The protein sequences (86 sequences PCR + cloning) coded by the aprA gene grouped in two clusters (Fig. 4; cluster I (66%) and II (34%)). Within cluster I, sequences clustered in three distinct subclusters. Sequences of the aprA gene included in subcluster 1.1 (36%) were affiliated to heterotrophic SRB of the δ-proteobacteria class (e.g. Desulfosarcina sp., Desulfofaba gelida, Desulfobulbus propionicus) and to aprA gene sequences of uncultured bacteria found in environments such as in Black Sea sediments and associated with benthic organisms (Blazejak and Schippers, 2011; Ruehland et al., 2008). In subcluster 1.2 (21%), sequences were closely affiliated to β- and γ-proteobacteria involved in autotrophic sulfur-dependent denitrification Thiobacillus( denitrificans and Sulfuricella denitrificans) or in phototrophic sulfur oxidation (Lamprocystis purpurea) and to the aprA gene sequence of an uncultured bacterium associated with the sea urchin Asterechinus elegans (Quast et al., 2009). Sequences clustering in subcluster 1.3 (9%) were affiliated withaprA gene sequences of bacteria of the phylum Firmicutes (i.e. Desulfotomaculum sp.) known to perform heterotrophic sulfate reduction, and to sequences of uncultured bacteria obtained in various sediments such as hydrothermal seep sediments, Peru margin sediments and salt lake sediments (Blazejak and Schippers, 2011; Meyer and Kuever, 2007c; Kleindienst et al., 2012). Cluster II contained sequences (34%) closely related to obligately chemolithoautotrophic members of the β-proteobacteria class (Thiobacillus thioparus) able to perform nitrate reduction to nitrite with thiocyanate, and to aprA gene sequences of uncultured bacteria retrieved in salt lake sediments or associated with benthic organisms (Becker et al., 2009). In addition, to assess the specificity of the aprA gene qPCR assay, aprA gene transcripts (cDNA of aprA mRNA) generated during the qPCR assay (21 sequences in total) were cloned, sequenced and added to the aprA phylogenetic tree, where they were classified in the clusters previously described (Fig. 4). The abundance and the potential activity of SOB including sulfide-dependent denitrifiers and SRB were determined by the quantification of the aprA gene and its gene transcripts (Fig. 2, Table S3). The copy number of the aprA gene was relatively constant with varying sediment depth and season. Gene copy numbers of the aprA gene were of the same order of magnitude as observed for the denitrifiers nirS (on average 3.1 × 108 copies g–1) and reached highest values in S2 in March and August (on average 3.3 × 108 copies g–1). At station S1, the aprA gene transcript (Table S3) was detectable at 2–3 cm sediment depth in March (5.4 × 102 copies g–1 on average), whereas in August the nirS transcript was detectable at 0–1 cm (3.8 × 103 copies g–1) and 2–4 cm (1.8 × 104 copies g–1 on average) sediment depth. In S2 and S3, aprA gene transcripts were detectable at 1–4 cm sediment depth in March and August (on average 4.7 × 103 copies g–1 in March and 4.4 × 103 copies g–1 in August). The ratio between aprA gene and transcript (RNA:DNA ratio) was ≤ 0.000088 in all stations in March and August. 91 Chapter 4

23 sequences Station 2, August; 0-1 cm Lake Grevelingen sediment (including 3 x cDNA) closely related to sequences of uncultured bacteria and δ-Proteobacteria Desulfatibacillum alkenivorans, Desulfofaba gelida and Desulfobacter curvatus Station 2, August; 0-1 cm Lake Grevelingen sediment (45) Olavius algarvensis endosymbiont; marine sediment (CAJ81243) cluster 1 83 Station 2, August; 0-1 cm Lake Grevelingen sediment (44) Station 2, August; 0-1 cm Lake Grevelingen sediment (79) 54 Station 2, August; 0-1 cm Lake Grevelingen sediment (57) 90 Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (18) 89 uncultured bacterium; mud vulcano (AFV48087) Station 2, August; 0-1 cm Lake Grevelingen sediment (56) 63 Station 2, August; 0-1 cm Lake Grevelingen sediment (63) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (9) 93 Station 2, August; 0-1 cm Lake Grevelingen sediment (39) 99 subcluster 1 51 Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (19) Station 2, August; 0-1 cm Lake Grevelingen sediment (59) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (1) Station 2, August; 0-1 cm Lake Grevelingen sediment (65) 84 uncultured δ-Proteobacterium; surface of crab (ABY89711) 53 98 95 Desulfobulbus propionicus; δ-Proteobacterium (YP004194237) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (23) uncultured Desulfofustis sp.; δ-Proteobacterium (WP023406400) 69 uncultured bacterium; marine sponge (AFK76428) 90 Station 2, August; 0-1 cm Lake Grevelingen sediment (1) 51 Station 2, August; 0-1 cm Lake Grevelingen sediment (33) 23 sequences Station 2, August; 0-1 cm Lake Grevelingen sediment 83 (including 5 x cDNA) closely related to sequences of uncultured bacteria and β-ProteobacteriaThiobacillus denitriﬁcans and Sulfuricella denitriﬁcans and ɣ-Proteobacterium Lamprocystis purpurea

99 Station 2, August; 0-1 cm Lake Grevelingen sediment (74) subcluster 2 uncultured bacterium; marine sediment Gulf of Mexico (CCB84484) 91 Station 2, August; 0-1 cm Lake Grevelingen sediment (37) 99 Station 2, August; 0-1 cm Lake Grevelingen sediment (67) 98 uncultured bacterium; Black Sea sediment (CCC58324) Desulfotomaculum alcoholivorax; Firmicutes (WP027366015) 52 Station 2, August; 0-1 cm Lake Grevelingen sediment (13) 82 Station 2, August; 0-1 cm Lake Grevelingen sediment (52) Station 2, August; 0-1 cm Lake Grevelingen sediment (50) Station 2, August; 0-1 cm Lake Grevelingen sediment (69) uncultured bacterium; Peru margin sediment (CCC58328) Desulfotomaculum thermocisternum; Firmicutes (WP027356136) Station 2, August; 0-1 cm Lake Grevelingen sediment (14) subcluster 3 Station 2, August; 0-1 cm Lake Grevelingen sediment (64) 99 uncultured bacterium; salt lake sediment (ACM47772) 57 δ-Proteobacterium NaphS2 (WP006420559) Archaeoglobus sulfaticallidus; Archaeoglobi (YP007908062) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (13)

99 41 sequences Station 2, August; 0-1 cm Lake Grevelingen sediment 97 (including 12 x cDNA) closely related to sequences of uncultured bacteria 0.05 and the ɣ-Proteobacterium Thiobacillus thioparus (WP018507768) cluster 2

Figure 4: Phylogenetic tree of partial aprA gene sequences of sulfur-oxidizing and sulfate-reducing bacteria (SOB and SRB) retrieved in this study (86 DNA sequences recovered by amplification (PCR) and 21 cDNA sequences recovered by amplification (qPCR) and cloning from sediments (0–1 cm) of station S2 in August) and closest relatives (bold: our sequences and closest known relatives); the scale bar indicates 5% sequence divergence. 92 Discussion

4.4. Discussion The phylogenetic analysis of the nirS gene sequences amplified from Lake Grevelingen sediments revealed a substantial diversity of autotrophic and heterotrophic denitrifiers (Fig. 1). Most of the sequences obtained in this study were affiliated to α-, β- and γ-proteobacteria able to perform denitrification coupled to the oxidation of reduced sulfur compounds. Sequences of the nirS gene (~30%) and the aprA gene (21%) (Fig. 4) were closely related to sequences of Thiobacillus denitrificans, able to couple the oxidation of inorganic sulfur species such as sulfide with denitrification (Shao et al., 2010). Sulfide-dependent denitrifiers couple nitrogen and sulfur cycling and their presence point to an important denitrification potential in these sediments. In order to determine differences in abundance, and therefore of denitrification potential, between sediments and with depth, in our study we quantified the abundance of the nirS gene. The nirS gene abundance was relatively constant with increasing sediment depth, suggesting a stable community of heterotrophic and autotrophic denitrifying bacteria in Lake Grevelingen sediments. NirS gene abundance (in the order of 107 copies g–1) was slightly higher in March in all three stations, but the difference was especially notable in station S1, most likely explained by the lower free sulfide concentrations in March compared to August (Table 1). Lower sulfide concentrations in March could favor the proliferation of heterotrophic denitrifiers not coupled with sulfide oxidation as sulfide has been seen to impair denitrification by inhibition of NO and

N2O reductases (Sørensen et al., 1980). In addition, the nirS gene abundance (Fig. 2) determined in Lake Grevelingen sediments (between 107–108 copies g–1) was one to three orders of magnitude higher compared to the values previously detected in other marine sediments such as in sediments of open estuaries with permanently oxygenated bottom water (104–107 copies g–1 on average) (Smith et al., 2007; Zhang et al., 2013). The nirS gene abundance has previously been shown to correlate positively with potential denitrification rates (Mosier and Francis, 2010), and therefore, we can conclude that the sediments of the marine Lake Grevelingen harbor a stable community of heterotrophic and autotrophic denitrifiers, which can be actively involved in the denitrification process independent of season and sediment depth. Besides quantifying the nirS gene as an indicator of the denitrification potential of these sediments, we also estimated the presence of nirS gene transcripts as a measure of potential activity (Table S3). Unfortunately, there is a lack of in situ studies correlating nirS gene expression with denitrification rates, and some studies have even shown a lack of direct relationship betweennirS gene expression and modeled rates of denitrification in marine surface sediments (Bowen et al., 2014). On the other hand, other studies have observed a correlation between a decrease of nirS gene transcripts and reduction of denitrification rates together with declining concentrations of nitrate in estuarine sediment (Dong et al., 2000, 2002; Smith et al., 2007), which would justify the use of nirS gene transcripts as a proxy for potential denitrification performed by nirS-type denitrifiers. In this study, the copy number of denitrifiernirS transcripts was two to three orders of magnitude lower compared to values previously reported for estuarine sediments (Smith et al., 2007), suggesting a low denitrification rate in surface sediments of all stations in March and in deeper sediment layers in August. Gene expression of the nirS gene was detected in surface sediments in March (all stations) and in deeper sediment layers in August (stations S1 and S3), which is most likely explained by the availability of nitrate/nitrite in the water-sediment interface (bottom water).

93 Chapter 4

Apart from nirS-containing denitrifiers, also anammox bacteria were detected in Lake Grev- elingen sediments by applying both DNA and lipid-based biomarkers. The phylogenetic analysis of the anammox 16S rRNA gene amplified from the sediments pointed to an anammox community dominated by “Candidatus Scalindua” (Fig. S3). In order to estimate the abundance of anammox bacteria in the sediments and their potential role in the nitrogen cycle in this system, we estimated the abundance of the “Candidatus Scalindua” nirS gene. In contrast to nirS-type denitrifiers, anammox bacteria showed a clear seasonal contrast in their nirS gene abundance with higher copy numbers in August (summer hypoxia) compared to March (Fig. 2). However, this seasonal trend was not reflected in the abundance of the anammox bacteria lipid biomarker PC-monoether ladderane lipid (Table S4). Previous studies have suggested that this biomarker lipid could be partly preserved in the sediment due to a relatively low turnover rate (Brandsma et al., 2011; Bale et al., 2014; Chapter 2). On the other hand, the concentration of ladderane lipid fatty acids (Table S5) correlated with the anammox bacteria abundance given by 16S rRNA gene quantification, i.e. with the lowest values in station S1 and highest values in station S3. This suggests that the abundance of ladderane lipid fatty acids could be interpreted as a proxy for anammox bacteria abundance together with specific gene quantification. It is also worth notic- ing that a difference of three to four orders of magnitude was detected between abundances of anammox 16S rRNA gene and the “Candidatus Scalindua” nirS gene (Fig. 2). This discordance between anammox 16S rRNA genes and functional genes has been previously observed and is possibly linked to primer biases attributed to the anammox bacteria 16S rRNA gene primers that would amplify 16S rRNA gene fragments of bacteria other than anammox bacteria (Li et al., 2010; Harhangi et al., 2012; Bale et al., 2014; Chapter 2). However, in our study we have ruled out the possibility of the anammox bacteria 16S rRNA gene primers amplifying bacteria other than anammox by cloning and sequencing of the product generated during the qPCR reaction as shown in Fig. S3. Therefore, further studies should address the causes of this discordance. Factors other than hypoxia and sulfide concentration could have also contributed to the differences in abundance and activity of anammox bacteria. For example, both the anammox bacteria 16S rRNA and nirS gene abundances were higher in August in comparison to March (Fig. 2). This may indicate that anammox bacteria are more abundant at higher temperatures (15°C), which is the anammox bacteria temperature optimum in temperate shelf sediments (Dalsgaard et al., 2005). This seasonality of anammox bacteria abundance has been reported before in sandy and as well in muddy, organic rich sediments of the North Sea (Bale et al., 2014; Chapter 2). Ad- ditionally, oxygen penetration depth in the sediments decreased and the sediment even became entirely anoxic during summer stratification (Table 1), which would also favor the anaerobic metabolism of anammox bacteria (Dalsgaard and Thamdrup, 2002). Anammox bacterial abundance was highest in station S3, which could also be related to elevated bioturbation activity that was observed in this station, as bioturbation and mixing extends the area of nitrate reduction, which might fuel the anammox process (Meyer et al., 2005; Laverock et al., 2013). Another factor determining anammox and denitrification pathways in sediments is the organic carbon content. Anammox and denitrification have been suggested to be more important nitrogen removal pathways in sediments of low carbon input compared to sulfide-dependent denitrification which seem to be more important in sulfidic sediments with high carbon input (Burgin and Hamilton, 2007). The TOC content in Lake Grevelingen sediments is high, i.e. in the order of 2.5–4.5% (Malkin et al., 2014), which is hence consistent with the low activity of anammox bacteria. More-

94 Discussion over in station S1, fresh organic-rich sediment rapidly accumulates (> 2 cm yr–1; Malkin et al., 2014), which might inhibit the activity of anammox bacteria and denitrifying bacteria. Overall, the nirS gene abundance of denitrifiers was three to four orders of magnitude higher compared to the anammox bacteria ‘Scalindua’ nirS gene values, suggesting that nirS-type denitrifiers have a more prominent role in the overall denitrification activity in Lake Grevelingen sediments in comparison with anammox bacteria (Fig. 2). This is also supported by the anammox bacteria nirS gene transcript abundance, which remained below detection limit. On the other hand, anammox bacteria 16S rRNA gene transcripts were detected throughout the sediment (Table S3). A recent study by Bale et al. (2014) observed a good correlation between the 16S rRNA gene abundance, 16S rRNA gene transcript abundance and anammox rates in North Sea sediments, which suggests that the transcriptional activity of anammox bacteria 16S rRNA gene is a suitable proxy of anammox bacteria activity. However, the anammox bacteria 16S rRNA gene RNA:DNA ratio was low (0.01–1) compared to the values previously reported in sediments of the southern North Sea (1.6–34.6) (Chapter 2), further supporting a low anammox activity in the Lake Grevelingen sediments. Although denitrification was more relevant than anammox process as suggested by the gene abundance and potential activity (Fig. 2, Table S3), the measured denitrification rates (between 36–96 µM m–2 d–1; D. Seitaj, personal communication) in Lake Grevelingen are low in comparison with other marine sediments. For example, denitrification rates were reported to vary between 30–270 µM m–2 d–1 in marine Arctic sediments (Rysgaard et al., 2004), while denitrification −2 −1 rates of 270±30 µmol N2 m d were measured in sediments of the Lower St. Lawrence Estu- ary (Crowe et al., 2012). The lower denitrification and anammox potential in Lake Grevelingen sediments could be explained by the effect of high concentrations of sulfide (potentially inhibiting both heterotrophic denitrification and anammox). In our study, the abundance ofnirS -type denitrifiers did not vary substantially for the different stations however the highest anammox bacterial abundance was observed in station S3 where lowest sulfide concentration was reported (Fig. 2, Table 1). Besides, these sediments harbor an important population of sulfide-dependent denitrifiers (as indicated by aprA gene values comparable to those found in sediments of the Black Sea; Blazejak and Schippers, 2011), which could alleviate the inhibitory effect of sulfide on other microbial groups such as anammox bacteria. For example, a study by Russ et al. (2014) observed the coexistence and interaction of sulfide-dependent denitrifying and anammox bacteria in a co-culture in which anammox bacteria remained active. Also a study by Wenk et al (2013) provided evidence for the coexistence of anammox bacteria and sulfide-dependent denitrifiers in the stratified water column of Lake Lugano, and reported that the addition of sulfide in incubation studies enhanced both processes. They speculated that anammox bacteria in this system would rely on nitrite released as intermediate during sulfide-dependent denitrification and that they would overcome inhibiting or toxic effects of sulfide by creating a sulfide-free microenvi- ronments in aggregates as previously proposed by Wenk et al (2013). However, in the case of Lake Grevelingen sediments the potential detoxification of sulfide and a source of nitrite by sulfide-dependent denitrifiers did not translate in significant anammox potential. Another explanation for the low denitrification potential of these sediments can be found in the interactions of anammox and heterotrophic denitrifiers with sulfur oxidizers also involved in the nitrogen

95 Chapter 4 cycle. For example in Lake Grevelingen, cable bacteria have been detected in stations S1 and S3 in March, whereas station S2 was dominated by Beggiatoaceae down to ~3 cm, but both groups were hardly detectable in subsurface sediments (0.5 cm downwards) during summer hypoxia (Seitaj et al., 2015; Seitaj, unpublished data). In fact, the analysis of aprA gene of SOB/SRB in our study showed that up to 36% of the aprA gene sequences were closely related to the aprA sequences of Desulfobulbus propionicus (Fig. 4), which has been identified as closest known relative of cable bacteria (Pfeffer et al., 2012). Cable bacteria perform a novel ‘electrogenic’ form of sulfur oxidation, in which the oxidation of the electron donor and the reduction of the electron acceptor are separated over centimeter-scale distances, and the necessary redox coupling is ensured by long-distance electron transport (Nielsen et al., 2010; Pfeffer et al., 2012). Cable bacteria use oxygen as terminal electron acceptor (Nielsen et al., 2010; Meysman et al., 2015) and recent studies also indicate that nitrate (Marzocchi et al., 2014) and nitrite (Risgaard-Petersen et al., 2014) can be utilized, suggesting that cable bacteria can also play a role in bioavailable nitrogen removal. In addition, marine Beggiatoa spp. couple the oxidation of sulfide to nitrate reduction resulting in N2 + and/or NH4 (Mußmann et al., 2003). Previous studies have observed that both denitrification and anammox in anoxic sediments can be supported by intracellular nitrate transport performed by sulfide-oxidizing bacteria likeThioploca and Beggiatoa (Prokopenko et al., 2013; Muβmann et al., 2007; Jørgensen et al., 2010) down to deeper sediment layers and possibly supplying anammox bacteria with nitrite and/or ammonia produced by DNRA (Teske and Nelson, 2006, Prokopen- ko et al., 2011).The nrfA gene, encoding a nitrite reductase catalyzing the conversion of nitrite to ammonia (Smith et al., 2007), could not be detected in our sediment samples (data not shown) by using general nrfA primers (Mohan et al., 2004), however we cannot rule out completely the presence of microorganisms performing DNRA as the primers used could be not the most ap- propriate ones for this system. Therefore, the presence of sulfide-dependent denitrifiers (such as Thiobacillus denitrificans), cable bacteria and Beggiatoa-like bacteria present in Lake Grevelingen sediments could potentially support denitrification and anammox processes in March. However, the nitrate and nitrite concentrations in the bottom water in March were reported to be relatively low (28 and 0.7 μM on average, respectively, Fig. S1), which is expected to induce a strong competition for nitrate, nitrite and sulfide with Beggiatoaceae, cable bacteria and other nitrate-reducing bacteria (e.g. Thiobacillus thioparus), explaining the limited denitrification potential observed in the Lake Grevelingen sediments. 4.5. Conclusion Our study has unraveled the coexistence and potential activity of heterotrophic and autotrophic denitrifiers, anammox bacteria as well as SOB/SRB in seasonally hypoxic and sulfidic sediments of Lake Grevelingen. Our starting hypothesis was that the abundance and activity of denitrifiers and anammox bacteria would decrease upon increase of the sulfide concentration found in the sediments during the summer hypoxia. However, nirS-type heterotrophic denitrifiers were a stable community regardless of changes in oxygen and sulfide concentrations in different seasons and with a similar abundance to that detected in other sediments not exposed to high sulfide concentrations. Besides, nirS-type denitrifiers outnumbered anammox bacteria leading to the conclusion that anammox does not contribute significantly to the N2 removal process in Lake Grevelingen sediments. Apart from that, the anammox bacteria population seemed to be affected by the phys-

96 Discussion/Conclusion icochemical changes between seasons. For example, their abundance and activity was higher in lower sulfide concentrations and low carbon input, also supporting a possible inhibition of anammox bacteria by sulfide. The sulfide-dependent denitrifiers in Lake Grevelingen sediments have proven to be abundant and expected to contribute significantly to the N2-removal in these sediments. Their activity of sulfide oxidation is intuitively expected to reduce the concentration of sulfide, which is in turn toxic for organoheterotrophic denitrifiers and anammox bacteria. However, in this system the detoxification mediated by sulfide-dependent denitrifiers is either not sufficient or other factors are contributing to the low denitrification potential observed in the sediments of Lake Grevelingen. Recent studies have also reported the presence of cable bacteria and sulfide-oxidizers of the Beggiatoaceae family in the Lake Grevelingen sediments. Both denitrifiers and anammox bacteria activity could be inhibited by the competition with cable bacteria and Beggiatoaceae for electron donors and acceptors (such as sulfide, nitrate and nitrite) before summer hypoxia (March). During summer hypoxia (August), sulfide inhibition and low nitrate and nitrite concentrations seem to limit the activity of heterotrophic and autotrophic (sulfide-dependent) denitrifiers and anammox bacteria. Further studies also involving denitrification rate determinations will be required to further assess the effects of hypoxia and high sulfide concentrations in the sediments of Lake Grevelingen.

Acknowledgements We thank the captain and crew of the R/V Luctor (Peter Coomans and Marcel Kristalijn) for support during sampling. We thank Eric Boschker for support and discussions during the sampling campaigns, and Diana Vasquez, Dorina Seitaj, Fatimah Sulu-Gambari and Anton Tramper for assistance with the collection and analysis of water column and pore water data. We thank Pieter van Rijswijk, Silvia Hidalgo Martinez, Marcel van der Meer and Sandra Heinzelmann for assistance during sediment sampling. Analytical support was provided by Anchelique Mets, De- nise Dorhout, Irene Rijpstra and Elda Panoto. We thank Prof. Stefan Schouten for constructive comments on the manuscript. This work was supported by grants from the Darwin Center for Biogeosciences (grant numbers 3062 and 142.16.3092) and ERC Grant 306933 to FM. This Re- search was supported by the SIAM Gravitation Grant 024.002.002 from the Dutch Ministry of Education, Culture, and Science (OCW).

97 Chapter 4

Figure S1: Bottom water temperature [°C] (red square) and concentrations of oxygen [μM] (blue square), ammonium [μM] (dark green triangle), nitrite [μM] (pink triangle) and nitrate [μM] (light green triangle).

Figure S2: A) Relative percentage of nirS sequences of denitrifying bacteria in cluster 1 and 2 and B) in subcluster 1.1 and 1.2 according to the three stations in March and August. 98 Supplementary Material

8 x Station 2, March, 1-2 cm Lake Grevelingen sediment (cloning) 17 x Station 2, March, 0-1cm Lake Grevelingen sediment (qPCR) Candidatus Scalindua brodae, anaerobic ammonium oxidizer enrichment reactor (EU142948) Candidatus Scalindua brodae (JRYO01000256) Candidatus Scalindua brodae, Black Sea (AY257181) uncultured bacterium, seafloor lavas from the East Pacific Rise (EU491842) uncultured planctomycete, Barrow Canyon sediment, Alaskan margin (DQ869385) uncultured bacterium, sediment from the Kings Bay, Svalbard, Arctic (EU050867) uncultured planctomycete, Saanich Inlet, 200 m depth (HQ163732) uncultured planctomycete, seawater (DQ534740) uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478646) uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478653) uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478687) uncultured planctomycete, seawater (DQ534739) uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478684) uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478669) uncultured planctomycete, seawater (DQ534742) uncultured Planctomycetales bacteria, Peruvian OMZ; Station 4; 35 m uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU47869) uncultured Planctomycetales bacterium, Black Sea, 100 m (EU478626) uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478632) uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478631) uncultured planctomycete, Saanich Inlet, 120 m depth (GQ349291) uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478645) uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478634) uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478633) uncultured planctomycete, Saanich Inlet, 120 m depth (GQ349285) uncultured planctomycete, Saanich Inlet, 120 m depth (GQ349247) uncultured planctomycete, Barrow Canyon sediment, Alaskan margin (DQ869384) uncultured bacteria Arabian Sea; Xisha Trough (South China Sea); OMZ of Chile; hypersaline grondwater uncultured Planctomycetales bacterium, low temperature hydrothermal oxides (South West Indian Ridge) (JN860309) Candidatus Scalindua Candidatus Scalindua marina, surface sediment under a water column of 118 m (EF602039) Candidatus Scalindua marina, surface sediment under a water column of 118 m (EF602038) uncultured planctomycete, sea water from Gullmarsfjorden (DQ386151) Candidatus Scalindua sp. anaerobic ammonium oxidizer enrichment reactor (EU142947) uncultured Planctomycetales bacterium (AB573102) 11 x Station 2, March, 1-2 cm Lake Grevelingen sediment (cloning) 6 x Station 2, March, 0-1 cm Lake Grevelingen sediment (qPCR) uncultured Candidatus Scalindua sp., estuarine sediment, 0−1 cm depth (FM992882) uncultured bacterium, Yellow Sea continental shelf sediment (GQ143789) uncultured bacterium, Manantial del Toro hypersaline groundwater (JF747652) Station 2, March, 1-2 cm Lake Grevelingen sediment (1) Station 2, March, 1-2 cm Lake Grevelingen sediment (8) Candidatus Scalindua wagneri, rotating biological contactor (AY25488) uncultured Candidatus Scalindua sp., estuarine sediment, 0−1 cm depth (FM992881) uncultured planctomycete, intertidal sand bank (AB300486) uncultured Candidatus Scalindua sp., laboratory−scale bioreactor (AB822932) uncultured Candidatus Scalindua sp., enrichment culture from marine sediment (AB811947) anaerobic ammonium−oxidizing planctomycete JMK−2, anammox bioreactor (AB281489) uncultured planctomycete, marine sediment ca. 50 m (EU373086) uncultured bacterium, Manantial del Toro hypersaline groundwater (JF747633) uncultured bacteria Xisha Trough (South China Sea); Manantial del Toro hypersaline grondwater uncultured bacterium, subseafloor sediment of the South China Sea (EU386010) uncultured bacterium, deep−sea sediments from different depths (AB015552) uncultured bacterium, ocean sediment, 5306 m water depth (FJ746210) uncultured bacterium, Manantial del Toro hypersaline groundwater (JF747691) 0.1

Figure S3: Phylogenetic tree of anammox bacteria partial 16S rRNA gene sequences retrieved in this study (21 DNA sequences recovered by amplification (PCR) and cloning and 21 DNA sequences recovered by amplification (qPCR) and cloning from sediments (0–1 cm) of station S2 in March) and closest relatives (bold: our sequences and closest known relatives); the scale bar indicates 10% sequence divergence. 99 Chapter 4 Ref. 2009 2007 2010 Kuever, Kuever, Li et al., al., 1998 Meyer & Braker et Braker Lam et al., 474 222 359 279 size [b] size Amplicon qPCR/ qPCR/ qPCR/ PCR 60 PCR 57 PCR 56 Tm [°C] Tm qPCR 59/ PCR 58 Primer pair Apr5R (5’-GCGCCAACYGGRCCRTA-3’) nirS1F (5’-CCTAYTGGCCGCCRCART-3’) nirS3R (5’-GCCGCCGTCRTGVAGGAA-3’) Apr1F (5’TGGCAGATCATGATYMAYGG-3’) Scnir845R (5’-TCAAGCCAGACCCATTTGCT-3’) Scnir372F (5’-TGTAGCCAGCATTGTAGCGT-3’) Brod541F (5’-GAGCACGTAGGTGGGTTTGT-3’) Amx820R (5’-AAAACCCCTCTACTTAGTGCCC-3’) gene sp. nirS gene sp. Target nirS gene 16S rRNA gene Sulfide oxidizing Sulfide bacteria aprA Anammox bacteria Anammox Denitrifying bacteria Scalindua Primer pairs described in the text, PCR conditions and amplicon size used this study. PCR/ PCR/ PCR/ Assay cloning cloning cloning cloning qPCR+ qPCR + qPCR + qPCR + Table S1: Table 72°C 30 s]; 40 s, Tm 72°C 1 min]; 5 min. qPCR conditions: 95°C 4 min; 40× [95°C 30 s, 40 s, PCR conditions: 95°C 5 min; 40× [95°C 1 min, Tm 80°C 25 s. 100 Supplementary Material

Table S2: Total organic carbon (TOC) after acidification of freeze dried sediment.

Sediment depth TOC [%] Station [cm] March August 0–1 2.86 1.81 1–2 3.67 2.47 1 2–3 3.83 3.52 3–4 3.98 3.11 4–5 4.28 3.66 0–1 3.11 2.38 1–2 3.62 3.29 2 2–3 3.77 3.24 3–4 3.49 3.5 4–5 3.85 3.52 0–1 2.87 3.04 1–2 4.02 3.9 3 2–3 3.89 3.56 3–4 4.01 4.39 4–5 3.63 3.73

101 Chapter 4 3 4 4 2 3 2 4 2 3 ] n.d. n.d. n.d. n.d. n.d. n.d. -1 August 3.8 × 10 1.1 × 10 2.5 × 10 7.4 × 10 3.4 × 10 5.9 × 10 1.8 × 10 4.3 × 10 3.7 × 10 gene

aprA 2 3 4 3 3 2 3 SOB and SRB cDNA [copy g [copy cDNA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. March 5.4 × 10 7.0 × 10 1.4 × 10 1.6 × 10 3.5 × 10 5.0 × 10 1.4 × 10 5 3 5 5 5 5 6 6 5 4 5 6 6 5 4 ] -1 August 8.1 × 10 1.3 × 10 2.8 × 10 6.9 × 10 2.3 × 10 3.0 × 10 1.1 × 10 1.7 × 10 1.3 × 10 5.5 × 10 2.9 × 10 5.1 × 10 3.1 × 10 1.3 × 10 3.7 × 10 5 5 5 4 4 4 5 5 5 4 6 6 5 5 4 16S rRNA gene 16S rRNA cDNA [copy g [copy cDNA anammox bacteria anammox March 6.5 × 10 2.5 × 10 1.9 × 10 4.8 × 10 4.1 × 10 8.5 × 10 1.9 × 10 1.8 × 10 8.5 × 10 6.0 × 10 9.6 × 10 4.9 × 10 1.0 × 10 3.1 × 10 2.2 × 10 2 2 3 ] n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. -1 August 1.8 × 10 1.0 × 10 1.1 × 10 gene

nirS 2 4 2 3 2 2 cDNA [copy g [copy cDNA denitrifying bacteria n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. March 1.9 × 10 1.5 × 10 1.1 × 10 6.7 × 10 1.5 × 10 1.8 × 10 nd: non detectable, i.e. values were under the detection limit of were values i.e. nd: non detectable, 72°C 30 s]; 80°C 25 s. the 40 s, Tm × [95°C 30 s,

0–1 0–1 1–2 3–4 4–5 2–3 3–4 4–5 2–3 3–4 4–5 2–3 1–2 1–2 0–1 Sediment depth [cm] Transcript (cDNA; mRNA copy) abundance detected in sediments ofTranscript and August. all stations in March

2 3 1 Station qPCR approach. qPCR conditions: 95°C 4 min; 40 Table S3: Table 102 Supplementary Material

Table S4: Results of anammox bacteria PC-monoether ladderane lipid analysis at all stations in March and August (0−5 cm sediment depth).

PC-monoether ladderane lipid [ng g−1] Station Sediment depth [cm] March August 0–1 20.4 2.4 1–2 13.3 3.4 1 2–3 6.1 2.8 3–4 3.4 7 4–5 5 7 0–1 10.8 6.2 1–2 4.7 1.9 2 2–3 2 1.9 3–4 1 1.4 4–5 1 1.4 0–1 8.6 2.4 1–2 6.1 1.2 3 2–3 1.6 1.2 3–4 1.1 0.9 4–5 1.4 1.4

103 Chapter 4 -[5] 18 7.8 16.8 15.8 13.1 25.4 22.7 38.7 19.8 19.5 27.4 10.6 sum 106.5 -[3]–C 20 C -[5] 5.5 5.0 3.9 2.8 7.8 4.4 8.4 4.1 4.0 9.7 3.0 18 39.3 C ] -1 -[3] 4.0 2.0 5.1 1.4 6.9 4.4 4.4 4.0 8.9 1.6 18 19.3 32.1 C -[5] 3.8 5.4 1.5 1.8 4.7 9.1 5.7 8.2 7.9 4.1 3.2 20 16.3 C long chain FAMEs [ng g long chain FAMEs -[3] 3.6 3.5 2.5 1.8 6.1 4.8 5.3 3.1 3.6 4.7 2.8 20 18.9 C 0.5 4.5 0.5 4.5 0.5 4.5 0.5 4.5 0.5 4.5 0.5 4.5 depth March March March March March March August August August August August August month Results ofResults analysis of bacteria FAME anammox (0−1 and 4−5 cm sediment depth). and August all stations in March

Station Station 1 Station 2 Station 3 Table S5: Table 104

5. Impact of seasonal hypoxia on activity and community structure of chemolithoautotrophic bacteria in a coastal sediment

Yvonne A. Lipsewers, Diana Vasquez-Cardenas (equal contributors), Dorina Seitaj, Regina Schauer, Silvia Hidalgo Martinez, Jaap S. Sinninghe Damsté, Filip J.R. Meysman, Laura Villanueva, and Henricus T.S. Boschker

Seasonal hypoxia in coastal systems drastically changes the availability of electron acceptors in bottom water, which alters the sedimentary reoxidation of reduced compounds. However, the effect of seasonal hypoxia on the chemolithoautotrophic community that catalyze these reoxidation reactions, is rarely studied. Here we examine the changes in activity and structure of the sedimentary chemolithoautotrophic bacterial community of a seasonally hypoxic saline basin under oxic (spring) and hypoxic (summer) conditions. Combined 16S rRNA gene amplicon sequencing and analysis of phospholipid derived fatty acids indicated a major temporal shift in community structure. Aerobic sulfur-oxidizing Gammaproteobacteria (Thiotrichales) and Epsi- lonproteobacteria (Campylobacterales) were prevalent during spring, whereas Deltaproteobac- teria (Desulfobacterales) related to sulfate reducing bacteria prevailed during summer hypoxia. Chemolithoautotrophy rates in the surface sediment were three times higher in spring compared to summer. The depth distribution of chemolithoautotrophy was linked to the distinct sulfur oxidation mechanisms identified through microsensor profiling, i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae. The metabolic diversity of the sulfur-oxidizing bacterial community suggests a complex niche partitioning within the sediment probably driven by the availability of reduced 0 2− − sulfur compounds (H2S, S , S2O3 ) and electron acceptors (O2, NO3 ) regulated by seasonal hypoxia. Chemolithoautotrophic microbes in the seafloor are dependent on electron acceptors like oxygen and nitrate that diffuse from the overlying water. Seasonal hypoxia however drastically changes the availability of these electron acceptors in the bottom water, and hence, one expects a strong impact of seasonal hypoxia on sedimentary chemolithoautotrophy. A multidisciplinary in- vestigation of the sediments in a seasonally hypoxic coastal basin confirms this hypothesis. Our data show that bacterial community structure and the chemolithoautotrophic activity varied with the seasonal depletion of oxygen. Unexpectedly, the dark carbon fixation was also dependent on the dominant microbial pathway of sulfur oxidation occurring in the sediment (i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae). These results suggest that a complex niche partitioning within the sulfur-oxidizing bacterial community additionally affects the chemolithoautotrophic community of seasonally hypoxic sediments.

Applied and Environmental Microbiology 83, e03517-16, 2017

107 Chapter 5

5.1. Introduction The reoxidation of reduced intermediates formed during anaerobic mineralization of organic matter is a key process in the biogeochemistry of coastal sediments (Soetaert et al., 1996, Jør- gensen and Nelson, 2004). Many of the microorganisms involved in the reoxidation of reduced compounds are chemolithoautotrophs, which fix inorganic carbon using the chemical energy derived from reoxidation reactions (dark CO2 fixation). In coastal sediments, sulfate reduction forms the main respiration pathway, accounting for 50% to 90% of the organic matter mineralization (Soetaert et al., 1996). The reoxidation of the pool of reduced sulfur compounds produced during anaerobic mineralization (dissolved free sulfide, thiosulfate, elemental sulfur, iron monosulfides and pyrite) hence forms the most important pathway sustaining chemolithoautotrophy in coastal sediments (Jørgensen and Nelson, 2004, Howarth, 1984). Various lineages from the Alpha-, Gamma-, Delta- and Epsilonproteobacteria, including recently identified groups, such as particle-associated Gammaproteobacteria and large sulfur bacteria, couple dark CO2 fixation to the oxidation of reduced sulfur compounds in oxygen deficient marine waters and sediments, in coastal marine sediments and in lake sediments (Brüchert et al., 2003; Lavik et al., 2009; Sorokin et al., 2011; Grote et al., 2012; Jessen et al., 2016; Ye et al., 2016). Both chemolithoautotrophic sulfur-oxidizing Gammaproteobacteria and sulfur dis- proportionating Deltaproteobacteria have been identified to play a major role in the sulfur and carbon cycling in diverse intertidal sediments (Lenk et al., 2010; Boschker et al., 2014; Dyksma et al., 2016). Hence, chemolithoautotrophic sulfur-oxidizing communities vary between sediment environments, but it is presently not clear as to which environmental factors are actually determining the chemolithoautotrophic community composition at a given site. Seasonal hypoxia is a natural phenomenon that occurs in coastal areas around the world (Diaz and Rosenberg, 2008) and provides an opportunity to study the environmental factors controlling sedimentary chemolithoautotrophy. Hypoxia occurs when bottom waters become de- –1 pleted of oxygen (< 63 µmol O2 L ), and has a large impact on the biogeochemical cycling and ecological functioning of the underlying sediments (Diaz and Rosenberg, 2008). The reduced – availability or even absence of suitable soluble electron acceptors (O2, NO3 ) in the bottom water during part of the year should in principle result in a reduction or complete inhibition of sedimentary sulfur reoxidation, and hence, limit chemolithoautotrophy. At present, the prevalence and temporal variations of chemolithoautotrophy have not been investigated in coastal sediments of seasonal hypoxic basins. – Likely, the availability of soluble electron acceptors (O2, NO3 ) in the bottom water is not the only determining factor of chemolithoautotrophy. A recent study conducted in a seasonally hypoxic saline basin (Lake Grevelingen, The Netherlands) indicated that the intrinsic structure and composition of the sulfur oxidizing microbial community also determined the biogeochemistry of the sediment (Seitaj et al., 2015). In this study, three distinct microbial sulfur oxidation mechanisms were observed throughout a seasonal cycle: (1) electrogenic sulfur oxidation by heterotrophic cable bacteria (Desulfobulbaceae); (2) canonical aerobic oxidation of free sulfide at the oxygen-sulfide interface and, (3) sulfide oxidation coupled to nitrate reduction by filamentous members of the Beggiatoaceae family that store nitrate intracellularly. The consequences of these three mechanisms on the chemolithoautotrophic community have however not been studied. The first sulfur oxidizing mechanism has been shown to affect the chemolithoautotrophic community in sediments only under laboratory conditions (Vasquez-Cardenas et al., 108 Introduction/Material and Methods

2015) while the third mechanisms may directly involve chemolithoautotrophic Beggiatoaceae as some species are known to grow autotrophically (Nelson and Jannasch, 1983). Accordingly, we hypothesize that the presence of these sulfur oxidation regimes as well as the depletion of – O2 and NO3 will result in a strong seasonality in both the chemolithoautotrophic activity and community structure under natural conditions. To examine the above-mentioned hypothesis, we conducted a multidisciplinary study with intact sediments of Lake Grevelingen, involving both geochemistry and microbiology. Field sampling was conducted during spring (oxygenated bottom waters) and summer (oxygen depleted bottom waters). The dominant sulfur oxidation mechanism was geochemically characterized by sediment microsensor profiling (O2, H2S, pH) whereas the abundance of cable bacteria and Beggiatoaceae was performed with fluorescence in situ hybridization (FISH). General bacterial diversity was assessed by 16S rRNA gene amplicon sequencing and the analysis of phospholipid derived fatty acids (PLFA). PLFA analysis combined with 13C stable isotope probing (PLFA-SIP) provided the activity and community composition of chemolithoautotrophs in the sediment.

This approach was complemented by the analysis of genes involved in dark CO2 fixation, i.e., characterizing diversity and the abundance of the genes cbbL and aclB that code for key enzymes in Calvin-Benson Bassham (CBB) and reductive tricarboxylic acid (rTCA) carbon fixation pathways. This multidisciplinary research showed strong temporal and spatial shifts of the chemolithoautotrophic composition and activity in relation to the seasonal hypoxia and the main sulfur oxidation mechanisms present in the sediments of the marine Lake Grevelingen. 5.2. Material and methods 5.2.1. Study site and sediment sampling Lake Grevelingen is a former estuary located within the Rhine-Meuse-Scheldt delta area of the Netherlands, which became a closed saline reservoir (salinity ~30) by dam construction at both the land side and sea side in the early 1970s. Due to an absence of tides and strong currents, Lake Grevelingen experiences a seasonal stratification of the water column, which in turn, leads to a gradual depletion of the oxygen in the bottom waters (Hagens et al., 2015). Bottom water oxygen at the deepest stations typically starts to decline in April, reaches hypoxic conditions by end of May (O2 < 63 µM), further decreasing to anoxia in August (O2 <0.1 µM), while the re-oxygenation of the bottom water takes place in September (Seitaj et al., 2015). To study the effects of the bottom water oxygenation on the benthic chemolithoautotrophic community we performed a field sampling campaign on March 13th, 2012 (before the start of the th annual O2 depletion) and August 20 , 2012 (at the height of the annual O2 depletion). Detailed water column, pore water and solid sediment chemistry of Lake Grevelingen over the year 2012 have been previously reported (Seitaj et al., 2015; Hagens et al., 2015; Sulu-Gambari et al., 2016). Sediments were recovered at three stations along a depth gradient within the Den Osse basin, one of the deeper basins in Marine Lake Grevelingen: Station 1 (S1) was located in the deepest point (34 m) of the basin (51.747°N, 3.890°E), Station 2 (S2) at 23 m depth (51.749°N, 3.897°E) and Station 3 (S3) at 17 m depth (51.747°N, 3.898°E). Intact sediment cores were retrieved with a single core gravity corer (UWITEC) using PVC core liners (6 cm inner diameter, 60 cm length). All cores were inspected upon retrieval and only cores with a visually undisturbed surface were used for further analysis.

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Thirteen sediment cores for microbial analysis were collected per station and per time point: two cores for phospholipid-derived fatty acid analysis combined with stable isotope probing (PLFA-SIP), two cores for nucleic acid analysis, four cores for 13C-bicarbonate labeling, three cores for microelectrode profiling, one core for quantification of cable bacteria (see supplement), and one core for quantification of Beggiatoaceae (see supplement). Sediment cores for PLFA extractions were sliced manually on board the ship (5 sediment layers; sectioning at 0.5, 1, 2, 4, and 6 cm depth). Sediment slices were collected in Petri dishes, and replicate depths were pooled and thoroughly mixed. Homogenized sediments were immediately transferred to centrifuge tubes (50 mL) and placed in dry ice until further analysis. Surface sediments in August consisted of a highly porous “fluffy” layer that was first left to settle after core retrieval. After- wards, the top 1 cm thick layer was recovered through suction (rather than slicing). Sediment for nucleic acid analysis was collected by slicing manually at a resolution of 1 cm up to 5 cm depth. Sediment samples were frozen in dry ice, transported to the laboratory within a few hour and placed at −80°C until further analysis. 5.2.2. Microsensor profiling Oxygen depth profiles were recorded with commercial microelectrodes (Unisense, Denmark; tip size: 50 µm) at 25−50 µm resolution. For H2S and pH (tip size: 50 and 200 µm), depth profiles were recorded at 200 µm resolution in the oxic zone, and at 400 or 600 µm depth resolution below. Calibrations for O2, pH and H2S were performed as previously described (Seitaj et al., 2015;

Malkin et al., 2014). ΣH2S was calculated from H2S based on pH measured at the same depth using the R package AquaEnv (Hofmann et al., 2010). The oxygen penetration depth (OPD) is operationally defined as the depth below which [O2] < 1 µM, while the sulfide appearance depth

(SAD) is operationally defined as the depth below which [H2S] > 1 µM. The diffusive oxygen uptake (DOU) was calculated from the oxygen depth profiles as previously described in detail (Vasquez-Cardenas et al., 2015). 5.2.3. DNA extraction and 16S rRNA gene amplicon sequencing DNA from 0 cm to 5 cm sediment depth (in 1 cm resolution) was extracted using the DNA PowerSoil® Total Isolation Kit (Mo Bio Laboratories, Inc., Carlsbad, CA). Nucleic acid concentrations were quantified spectrophotometrically (Nanodrop, Thermo Scientific, Wilmington, DE) and checked by agarose gel electrophoresis for integrity. DNA extracts were kept frozen at –80°C. Sequencing of 16S rRNA gene amplicons was performed on the first cm of the sediment (0–1 cm depth) in all stations in March and August as described before (Moore et al., 2015). Further details are provided in the SI. The 16S rRNA gene amplicon reads (raw data) have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject number PRJNA293286. The phylogenetic affiliation of the 16S rRNA gene sequences was compared to release 119 of the SILVA NR SSU Ref database (http://www. arb-silva.de/; Quast et al., 2013) using the ARB software package (Ludwig et al., 2004). Sequences were added to a reference tree generated from the Silva database using the ARB Parsimony tool. 5.2.4. Sediment incubations and PLFA-SIP analysis Sediment cores were labeled with 13C-bicarbonate to determine the chemolithoautotrophic activity and associated bacterial community by tracing the incorporation of 13C into bacterial PLFA. 110 Material and Methods

To this end, four intact cores were sub-cored with smaller core liners (4.5 cm inner diameter; 20 cm height). In situ bottom water was kept over the sediment and no gas headspace was present. Cores were kept inside a closed cooling box during transport to the laboratory. Stock solutions of 80 mM of 13C-bicarbonate (99% 13C; Cambridge Isotope Laboratories, Andover, Ma, USA) were prepared as previously described (Boschker et al., 2014). 13C-bicarbonate was added to the sediment from 3 cm above the surface to 8 cm deep in the sediment cores in aliquots of 100 μL through vertically aligned side ports (0.5 cm apart) with the line injection method (Jørgensen, 1978). March sediments were incubated at 17±1°C in the dark for 24 h and 13 continuously aerated with C-saturated air to maintain 100% saturated O2 conditions as those found in situ, but avoiding the stripping of labeled CO2 from the overlying water (Vasquez-Carde- nas et al., 2015). In August, sediments were incubated at 17±1°C in the dark for 40 h to ensure sufficient labeling as a lower activity was expected under low oxygen concentrations. In August, oxygen concentrations in the overlying water were maintained near in situ O2 levels measured in the bottom water (S1: 0−4% saturation, S2: 20−26%, S3: 35−80%). A detailed description of aeriation procedures can be found in the SI. At the end of the incubation period, sediment cores were sliced in five depth intervals (as described for PLFA sediment cores sliced on board) thus obtaining two replicate slices per sediment depth and per station. Sediment layers were collected in centrifuge tubes (50 mL) and wet volume and weight were noted. Pore water was obtained by centrifugation (4500 rpm for 5 min) for dissolved inorganic carbon (DIC) analysis, and sediments were lyophilized for PLFA analysis. Biomarker extractions were performed on freeze dried sediment as described before (Guckert et al., 1985) and 13C-incorporation into PLFA was analyzed as previously reported (Boschker et al., 2014). Nomenclature of PLFA can be found in the SI. Detailed description of the PLFA calculations can be found in the literature (Vasquez-Cardenas et al., 2015; Boschker and Middelburg, –2 –1 2002). Total dark CO2 fixation rates (mmol C m d ) are the depth-integrated rates obtained from the 0−6 cm sediment interval. 5.2.5. Quantitative PCR To determine the abundance of chemolithoautotrophs we quantified the genes coding for two enzymes involved in dark CO2 fixation pathways: the large subunit of the RubisCO enzyme (ribulose 1,5-bisphosphate carboxylase/oxygenase) cbbL gene, and the ATP citrate lyase aclB gene. Abundance of the RubisCO cbbL gene was estimated by using primers K2f/V2r, specific for the forms IA and IC of the RuBisCO form I large subunit gene cbbL which is present in obligately and facultatively lithotrophic bacteria (Nanba et al., 2004; Nigro and King, 2007). The abundance of ATP citrate lyase aclB gene was quantified by using the primer set aclB_F/aclB_R, which is based on the primers 892F/1204R (Campbell et al., 2003), specific for the ATP citrate lyase β gene of chemoautotrophic bacteria using the rTCA pathway, with several nucleotide differences introduced after aligning n=100 sequences of aclB gene fragments affiliated to Epsi- lonproteobacteria (See Table S1 for details). The quantification of cbbL and aclB genes via quantitative PCR (qPCR) was performed in 1 cm resolution for the sediment interval between 0–5 cm depth in all stations in both March and August. qPCR analyses were performed on a Biorad CFX96TM Real-Time System/C1000 Thermal cycler equipped with CFX ManagerTM Software. All qPCR reactions were performed in triplicate with standard curves from 100 to 107 molecules per microliter. Standard curves and

111 Chapter 5 qPCR reactions were performed as previously described (Chapter 2). Melting temperatures (Tm) are listed in Table S1, qPCR efficiencies E( ) for aclB gene and cbbL gene amplifications were 70 and 82%, respectively. Correlation coefficients for standard curves were ≥ 0.994 for aclB gene and ≥ 0.988 for cbbL gene amplification. 5.2.6. PCR amplification and cloning Amplifications of the RubisCO cbbL gene and the ATP citrate lyase aclB gene were performed with the primer pairs specified in Table S1. The PCR reaction mixture was the following (final concentration): Q-solution (PCR additive, Qiagen, Valencia, CA) 1 ×; PCR buffer 1 ×; BSA –1 –1 (200 µg mL ); dNTPs (20 µM); primers (0.2 pmol µL ); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA). PCR conditions for these amplifications were the following: 95°C, 5 min; 35 × [95°C, 1 min; Tm, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen, Valencia, CA) and cloned in the TOPO-TA cloning® kit (Life Technologies, Carlsbad, CA) and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. Recombinant plasmid DNA was sequenced using M13R primer by BASECLEAR (Leiden, The Netherlands). Sequences were aligned with MEGA5 software (Tamura et al., 2011) by using the alignment method ClustalW. The phylogenetic trees of the cbbL and aclB genes were computed with the Neighbour-Joining method (Saitou and Nei, 1987). The evolutionary distances were estimated using the Jukes-Cantor method (Jukes and Cantor, 1969) for DNA sequences and with the Poisson correction method for protein sequences (Zuckerkandl and Pauling, 1965) with a bootstrap test of 1,000 replicates. Sequences were deposited in NCBI with the following accession numbers: KT328918–KT328956 for cbbL gene sequences and KT328957–KT329097 for aclB gene sequences. Further details on experimental procedures and methods are found in the Sup- plementary Information. 5.3. Results 5.3.1. Geochemical characterization The seasonal variation of the bottom water oxygen concentration in Lake Grevelingen strongly influenced the porewater concentrations of O2 and H2S. In March, bottom waters were fully oxygenated at all stations (299–307 μM), oxygen penetrated 1.8–2.6 mm deep in the sediment, and no free sulfide was recorded in the first few centimeters (Table 1). The width of the suboxic zone, operationally defined as the sediment layer located between the oxygen penetration depth (OPD) and the sulfide appearance depth (SAD), varied between 16–39 mm across the three stations in March 2012. In contrast, in August, oxygen was strongly depleted in the bottom waters at S1 (< 0.1 μM) and S2 (11 μM), and no O2 could be confidently detected by microsensor profiling in the surface sediment at these two stations. At station S3, the bottom water O2 remained higher (88 μM), and oxygen penetrated down to 1.1 mm. In August, free sulfide was present near the sediment-water interface at all three stations, and the accumulation of sulfide in the pore water increased with water depth (Fig. 1a). Depth pH profiles showed much larger variation between stations in March compared to August (Fig. 1a). The pH profiles in S1 and S3 in March were similarly characterized by highest values in the oxic zone and low pH values (pH < 6.5) in the suboxic zone. The pH depth profile in S2 showed an inverse pH profile with a pH minimum in the oxic layer and a subsurface maximum below. The pH profiles at S1 and S3 112 Material and Methods/Results in August 2012 showed a gradual decline of pH with depth, while the pH profile at S2 in August was more or less constant with depth. 5.3.2. Bacterial diversity by 16S rRNA gene amplicon sequencing The general diversity of bacteria was assessed by 16S rRNA gene amplicon sequencing analysis, which was applied to the surface sediments (0−1 cm) of all stations in both March and August. Approximately 50% of the reads were assigned to three main clades: Gamma, Delta-, and Epsilonproteobacteria (Fig. 2). The remaining reads were distributed amongst the orders Bacteroidetes (14%), Planctomycetes (6%), Alphaproteobacteria (3%), other orders (20%), the candidate phylum WS3 (2%) and unassigned (5%) (given as the average of the three stations and both seasons). Reads classified within the Gammaproteobacteria were more abundant in March during oxygenated bottom water conditions than in August (Fig. 2). The majority of these reads were assigned to the orders Alteromonadales, Chromatiales and Thiotrichales. The first order includes chemoheterotrophic bacteria that are either strict aerobes or facultative anaerobes (Bowman and McMeekin, 2005). Phylogenetic comparison revealed that the reads assigned to the Chromatiales group were closely related to the Granulosicoccaceae, Ectothiorhodospiraceae, and Chroma- tiaceae families (Fig. S1). Reads falling in the Thiotrichales group were closely related to sulfur-oxidizing bacteria from the Thiotrichaceae family with 30% of the sequences related to the genera “Candidatus Isobeggiatoa”, “Ca. Parabeggiatoa” and Thiomargarita (Fig. S2). It has been recently proposed that the genera Beggiatoa, Thiomargarita and Thioploca should be reclassified into the originally published monophyletic family of Beggiatoaceae (Salman et al., 2011, 2013), and so here, these genera will be further referred to as Beggiatoaceae. Most of the reads assigned to the Beggiatoaceae came from station S2 in spring, whereas the percentage of reads assigned to sulfur oxidizers from the order Thiotrichales decreased in August when oxygen concentrations in the bottom water were low. Within the Deltaproteobacteria, reads were assigned to the orders Desulfarculales and Desul- fobacterales (Fig. S3). Reads within the order of Desulfobacterales were mainly assigned to the families Desulfobacteraceae (between 10−20%) and Desulfobulbaceae (~5%) (Fig. 2). Addition- al phylogenetic comparison revealed that within the Desulfobulbaceae, 60% of reads, obtained from the three stations in both seasons, clustered within the genus Desulfobulbus, of which 30% were related to the electrogenic sulfur-oxidizing cable bacteria (Fig. S4). Overall, the relative abundance of reads assigned to the Desulfobulbaceae family was similar between the two seasons in S2 and S3, whereas in S1 the percentage of reads was approximately 4.5-fold higher in March compared to August (Fig. 2). In contrast, the relative abundance of reads assigned to the Desulfarculales and Desulfobacteraceae increased in August during hypoxia (Fig. 2), and phylogenetic comparison revealed typical sulfate reducer genera Desulfococcus, Desulfosarcina, and Desulfobacterium, indicative of anaerobic metabolism (Figs. S5a–c). All Epsilonproteobacteria reads were assigned to the order Campylobacterales, such as the Campylobacteraceae and Helicobacteraceae families. Phylogenetic comparison showed that the reads were closely related to the genera Sulfurovum, Sulfurimonas, Sulfurospirillum, Arcobacter (Figs. S6a–d), all capable of sulfur oxidation with oxygen or nitrate (Campbell et al., 2006). The percentage of reads assigned to the Epsilonproteobacteria in August was lower than those in March, with highest numbers present in S2 in March (~6%), (Fig. 2).

113 Chapter 5 ] -2 cm 3 3.24 0.02 0.11 0.05 0.004 0.001 Beggiatoa Beggiatoa biovolume [mm ] -2 cm 3 ND ND 2.55 0.11 2.08 0.003 Cable Cable biovolume [mm

-2 ] -1 d 0.8±0.3 1.1±0.5 3.1±0.5 0.2±0.1 1.9±0.1 1.4±0.3 autotrophy [mmol C m Chemolitho- pH sulfur e-SOx e-SOx Sulfate storing Nitrate- oxidation canonical Beggiatoa S appearance depth; e-SOx: electrogenic sulfur oxidation; oxidation; sulfur electrogenic e-SOx: depth; appearance S reduction/ 2 signature*** 3 16 19 39 0.6 0.9 [mm] zone** Suboxic Suboxic SAD 0.6±0 [mm] 4.2±2.7 0.9±1.1 17.5±0.7 21.3±2.5 41.8±8.6 μ M. **The 63 of below thickness 1 μ M and hypoxic concentration below suboxic the 2 penetration depth; SAD: ∑H SAD: depth; penetration 2 0 0 OPD [mm] 1.1±0.1 2.4±0.4 1.8±0.04 2.6±0.65

2 . Cable - cable bacteria. ] -1 d 0 0 -2 DOU m 13.9±2.1 18.2±1.7 15.8±3.1 17.1±5.7 uptake; OPD: O OPD: uptake; [mmol O 2 – 3 1.7 10.6 28.2 11.6 27.9 27.7 NO [μM] (oxic) (oxic) (oxic) DOU: dissolved O DOU: dissolved (anoxic) (hypoxic) (hypoxic) 2 0 O 88 12 Bottom water * conc. Bottom water 299 301 307 5 5 5 19 17 17 °C Geochemical characterization, chemoautotrophy rates, and quantification of rates, chemoautotrophy characterization, Geochemical cable bacteria and Beggiatoaceae in the three stations Lake 3 1 1 2 2 3 A M Station Month/ Table 1: Table and summer (August). for spring (March) Grevelingen ND: not determined. *Bottom water is classified as anoxic with O with anoxic as classified is water determined.*Bottom not ND: zone is defined as theaverage SAD minus theaverage OPD. ***pH signature chemistrySeitaj et al. (2015) porewater as described by serves to indicate the sulfuroxidizing mechanism that dominates the M - March, A - August, A - August, M - March, 114 Results Geochemical fingerprint, (b) chemoautotrophy depth profiles, (c) biovolume (c) biovolume depth fingerprint,Figure profiles, chemoautotrophy 1: Geochemical (b) of filamentous and cable bacteria (blue) Beggiatoaceae (black) in sediment of S1: in scale for Beggiatoaceae in all three stations (note change and August). and August March for March Grevelingen between Lake station 1 (34 m), S2: 2 (23 S3: 3 (17 m). 115 Chapter 5

5.3.3. Bacterial community structure by phospholipid derived fatty acid analysis The relative concentrations of phospholipid derived fatty acid (PLFA) were determined to a depth of 6 cm and were analyzed by principal component analysis (PCA) to determine differences in bacterial community structure (Fig. 3). A total of 22 individual PLFA, each contributing more than 0.1% to the total PLFA biomass, were included in this analysis. Samples with low total PLFA biomass (less than one standard deviation below the mean of all samples) were excluded. The PCA analysis indicated that 73% of the variation within the dataset was explained by the first two principal components (PC). While PC1 correlated with sediment depth (particularly for the March samples), PC2 clearly exposed differences in the bacterial community structure between seasons (Fig. 3a). Surface sediments (0–1 cm) were characterized by high relative concentrations of C16 and C18 monounsaturated PLFA. In contrast, ai15:0, i17:1ω7c, and 10Me16:0 were more abundant in deeper sediments (Fig. S7a). The surface sediment showed an increased contribution of iso, anteiso and branched PLFAs in August relative to March, and this was more similar to the deeper sediments from March (Fig. 3a). Nonetheless, August sediments also showed a higher abundance of 16:0, 14:0, and 18:1ω9c compared to the deeper sediment layers in March (Fig. S7a). 5.3.4. Chemolithoautotrophic activity and community by 13C-phospholipid fatty acids analysis Incorporation of 13C-labeled dissolved inorganic carbon was found in bacterial PLFAs after 24 13 to 40 hours of incubation (Fig. S7b). Depth integrated dark CO2 fixation rates based on C-incorporation (Table 1) showed a significant difference between seasons and stations (p = 0.0005). In March, chemolithoautotrophy increased with water depth, while in August, the opposite trend was observed. The dark CO2 fixation rate in March for S1 was the highest across all seasons and stations, but dropped by one order of magnitude in August. In contrast, at the intermediate station (S2), the dark CO2 fixation rate was only two times higher in March compared to August, while in the shallowest station (S3) the depth integrated rates were not significantly different between seasons (p = 0.56). The depth distribution of the chemolithoautotrophic activity also differed between seasons (p = 0.02; Fig. 1b). In August, the chemolithoautotrophic activity was restricted to the upper cm of the sediment at all stations while in March, chemolithoautotrophic activity was measured deep into the sediment (up to 4 cm). In stations S1 and S3 during March, the activity depth profile showed high activities down to 4 cm, whereas at S2 chemolithoautotrophy only extended down to 2 cm with highest activity in the top 1 cm. This distinction between the depth distributions of chemolithoautotrophy at S2 versus S1/S3 in March correlated with the distinct pH profiles observed for S2 versus S1/S3 (Fig. 1c). The PLFA 13C-fingerprints were analyzed by PCA to identify differences in chemolithoautotrophic community. Only PLFA that contributed more than 0.1% to the total 13C-incorporation and sediment layers that showed chemolithoautotrophy rates higher than 0.01 μmol C cm–3 d–1 were taken into account in this analysis. Because chemolithoautotrophy rates were low in Au- gust, the PCA analysis mainly analyzed the chemolithoautotrophic communities in March (Fig. 3b). Within the dataset, 64% of the variation was explained by two principal components. PC1 revealed a clear differentiation between station S2, and stations S1 and S3 (Fig. 3b) in agreement with the distinct pH profiles described for March (Fig. 1a). S2 sediment horizons showed a 116 Results

Figure 2: Percentages of total bacterial 16S rRNA gene reads in stations S1 (yellow), S2 (blue) and S3 (red) in March (filled) and August (hatched). Classified bacterial phyla, classes and orders > 3% of the total bacteria reads (in March or August) are reported (exception: family Thiotrichaceae < 3%), *including cable bacteria, **including Beggiatoaceae. 117 Chapter 5

Figure 3: Principal component analysis (PCA) of relative PLFA concentrations (a) and of 13C-incorporation into PLFA (b) in sediments from the three stations in March (no border) and August (black border). The percentage of variability explained by the first two principal components (PC) is indicated on each axis. Red: station S1, Yellow: S2, Blue S3. Symbols indicate sediment depth as seen in plot. higher contribution of monounsaturated C16 and C18 fatty acids, whereas sediments from S1 and 13 S3 revealed an increased C-incorporation into fatty acids with iso and anteiso C15 and saturated

C14 PLFA (Fig. S7c), together these results indicate distinct chemolithoautotrophic microbial assemblages between S2 and S1/S3. On the contrary, the three sediment samples from August (that had sufficient 13C-incorporation for the analysis) did not cluster in the PCA analysis and exhibited divergent PLFA profiles, thus the chemolithoautotrophic bacterial community for Au- gust could not be characterized further based on PLFA analysis. 5.3.5. Chemolithoautotrophic carbon fixation pathways

Various CO2 fixation pathways are used by autotrophic bacteria (for detailed reviews see Berg, 2011, Hügler and Sievert, 2011). The CBB pathway is utilized by cyanobacteria and many aerobic or facultative aerobic proteobacteria of the alpha, beta and gamma subgroups whereas the rTCA pathway operates in anaerobic or microaerobic members of phyla such as Chlorobi, Aquificae, proteobacteria of the Delta- and Epsilon- subgroups and Nitrospirae (Berg, 2011). The spatial and temporal distribution of bacteria possessing these two autotrophic carbon fixation pathways was studied by quantifying the abundance of cbbL gene (CBB pathway) (Nigro and King, 2007) and aclB gene (rTCA pathway) (Campbell et l., 2006, modified in this study) by quantitative PCR down to 5 cm sediment depth (Fig. 4).The diversity of cbbL and aclB gene sequences obtained from the surface sediments (0–1 cm) was analyzed (Figs. 5a, b). Significant differences were found in the abundance of cbbL and aclB genes (p = 5.7 × 10–7) and between season (p = 0.002), but not between stations (Fig. 4). The abundance of the cbbL gene copies was at least 2-fold higher than that of the aclB gene in March and August in all stations (p = 5×10–5). In March, the depth profiles ofcbbL gene showed a similar trend in stations 118 Results

Figure 4: Abundance [copy g−1] of two carbon fixation pathway genes with sediment depth [cm] for S1 (left), S2 (middle) and S3 (right) (a) RuBisCO cbbL gene (b) ATP citrate lyase aclB gene (black: March, white: August). The error bars represent the standard deviations of qPCR replicates.

S1 and S3 with a decreasing gene abundance from the surface towards deeper layers, but depth integrated abundance of the cbbL gene was more than two-fold higher in S1 than in S3 (Fig. 4a). The depth distribution of the cbbL gene in the deepest station (S1) differed between seasons (p = 0.004), with lower gene copy abundances in the top 4 cm in August (Fig. 4a). In contrast, in the shallow station (S3), which experiences less seasonal fluctuations in bottom water 2O , the cbbL gene copy number did not differ significantly between seasons (p = 0.4), except for a sharp decrease in the top cm of the sediment. In station S2, abundance and depth distribution of cbbL gene copies was similar between the two seasons (p = 0.3). All detected cbbL gene sequences clustered with uncultured Gammaproteobacteria clones (Fig. 5a), assigned to the orders Chro- matiales and Thiotrichales (both cbbL1 and cbbL2 clusters) reported in intertidal sediment from Lowes Cove, Maine (Nigro and King, 2007). The abundance of the aclB gene significantly differed between months (p = 0.0004) and stations (p = 0.04). Similar depth profiles of theaclB gene were detected in stations S1 and S3, with subsurface maxima in deeper sediments (at 3–4 cm and 2–3 cm deep for S1 and S3 respectively, Fig. 4b). Station S2 showed the highest aclB gene abundance in March, which remained constant with sediment depth (p = 0.86). In August, aclB gene abundance decreased substantially in S2 (p < 0.001). All stations showed a uniform distribution of the aclB gene abundance with depth in August. Bacterial aclB gene sequences in surface sediments (0−1 cm) of all stations were predominantly related to aclB sequences of Epsilonproteobacteria (Fig. 5b). Within the Epsi- lonproteobacteria, sequences clustered in six different subclusters and were mainly affiliated to bacteria in the order of Campylobacterales, i.e., to the genera Sulfuricurvum, Sulfurimonas, Thiovu- 119 Chapter 5

Station 1 August (seq19); 0-1 cm Lake Grevelingen sediment Station 3 August (seq19); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCS147; intertidal marine surface sediment (DQ683601) Station 2 August (seq4); 0-1 cm Lake Grevelingen sediment Station 3 August (seq18); 0-1 cm Lake Grevelingen sediment Station 3 August (seq16); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCB16; intertidal marine sediment, burrow (DQ683650) 57 uncultured proteobacterium clone LCS69; intertidal marine surface sediment, (DQ683590) 68 60 uncultured proteobacterium clone LCS120; intertidal marine surface sediment, (DQ683598) 57 Station 1 March (seq4); 0-1 cm Lake Grevelingen sediment Station 2 March (seq27); 0-1 cm Lake Grevelingen sediment 73 Station 2 March (seq20); 0-1 cm Lake Grevelingen sediment Station 2 March (seq22); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCS15; intertidal marine surface sediment, (DQ683585) 51 uncultured proteobacterium clone LCSS223; intertidal marine subsurface sediment, (DQ683644) Station 3 August (seq13); 0-1 cm Lake Grevelingen sediment 97 Station 2 March (seq15); 0-1 cm Lake Grevelingen sediment 53 uncultured proteobacterium clone LCSS; intertidal marine subsurface sediment, (DQ683627) 93 uncultured proteobacterium clone LCSS21; intertidal marine subsurface sediment, (DQ683641) Station 3 August (seq20); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCB173; intertidal marine sediment, burrow (DQ683661) 68 Station 1 August (seq16); 0-1 cm Lake Grevelingen sediment Station 2 March (seq23); 0-1 cm Lake Grevelingen sediment 53 Station 3 March (seq23); 0-1 cm Lake Grevelingen sediment Station 2 August (seq24); 0-1 cm Lake Grevelingen sediment Station 3 August (seq17); 0-1 cm Lake Grevelingen sediment Station 1 March (seq26); 0-1 cm Lake Grevelingen sediment 79 uncultured proteobacterium clone LCSS9 (intertidal marine subsurface sediment (DQ683619) 75 Station 2 March (seq18); 0-1 cm Lake Grevelingen sediment 65 83 Station 1 August (seq17); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCS155 (intertidal marine surface sediment (DQ683603) Station 3 August (seq14); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCS42 (intertidal marine surface sediment (DQ683588) Station 3 August (seq15); 0-1 cm Lake Grevelingen sediment 94 Station 3 March (seq19); 0-1 cm Lake Grevelingen sediment 67 Station 2 March (seq21); 0-1 cm Lake Grevelingen sediment Station 2 March (seq26); 0-1 cm Lake Grevelingen sediment 70 Station 2 March (seq17); 0-1 cm Lake Grevelingen sediment Station 2 March (seq19); 0-1 cm Lake Grevelingen sediment 54 Thioalkalivibrio denitriﬁcans strain ALJD (AY914807) Thioalkalivibrio halophilus strain Hl17 (EF199949) 62 -Proteobacteria, Chromatiales 98 Thioalkalivibrio sp. K90mix (CP001905) 53 Thioalkalivibrio thiocyanoxidans strain Arh2 (AY914804) Thioalkalivibrio versutus strain Al2 (AY914800) Thioploca ingrica (AP014633) Beggiatoa sp. PS (ABBZ01000395) 80 Thiomicrospira halophila strain HL 5 cbbL-1 gene (DQ390451)  50 Thiomicrospira sp. Lilliput-1 (AM404076) -Proteobacteria, Thiotrichales 96 Thiomicrospira crunogena XCL-2 (CP000109) 99 Thiomicrospira crunogena cbbL-1 gene (DQ272534) 83 Thiomicrospira kuenenii cbbL-1 gene (DQ272531) cbbL 1 95 Hydrogenovibrio marinus cbbL-1 gene (D43621) 68 Hydrogenovibrio marinus (AB122069) Station 2 March (seq25); 0-1 cm Lake Grevelingen sediment Station 3 March (seq24); 0-1 cm Lake Grevelingen sediment Station 2 March (seq16); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCSS153; intertidal marine subsurface sediment (DQ683632) 60 Station 1 August (seq18); 0-1 cm Lake Grevelingen sediment 56 Station 1 March (seq28); 0-1 cm Lake Grevelingen sediment 86 Station 2 August (seq24); 0-1 cm Lake Grevelingen sediment 66 Station 2 March (seq24); 0-1 cm Lake Grevelingen sediment Station 1 August (seq15); 0-1 cm Lake Grevelingen sediment uncultured proteobacterium clone LCS90 (intertidal marine surface sediment (DQ683592) 86 Station 3 March (seq21); 0-1 cm Lake Grevelingen sediment 88 Station 3 March (seq25); 0-1 cm Lake Grevelingen sediment Station 1 March (seq27); 0-1 cm Lake Grevelingen sediment 96 Station 2 March (seq18); 0-1 cm Lake Grevelingen sediment Thiomicrospira halophila strain HL 5 cbbL-2 gene (DQ390452) Thioalkalivibrio paradoxus strain Arh1 (AY914806) Thiomicrospira crunogena XCL-2 (CP000109) 77 Thiomicrospira crunogena cbbL-2 gene (DQ272533)

Thiomicrospira kuenenii cbbL-2 gene (DQ272532) Thiotrichales 94 Thiomicrospira sp. Lilliput-1 (AM404077) Hydrogenovibrio marinus cbbL-2 gene (AB122070) Hydrogenovibrio marinus cbbL-2 gene (D43622) 95 Thiomicrospira pelophila (DQ272530) Thiomicrospira sp. V2501 cbbL-2 gene (AB634593) cbbL 2 99 Thioalkalimicrobium aerophilum Al3 (CP007030) Thioalkalimicrobium cyclicum ALM1 (CP002776) 70 59 Thioalkalimicrobium sibiricum (DQ272529) 95 Thioalkalimicrobium aerophilum (DQ272527) Thioalkalimicrobium cyclicum (DQ272528)

0.02 -Proteobacteria, 

Figure 5a: Phylogenetic tree (amino acid-based) of cbbL gene sequences retrieved in this study and closest relatives. The scale bar indicates 2% sequence divergence. 120 Results

10x Station 1 March 8x Station 1 August 16x Station 2 March 7x Station 2 August 9x Station 3 March 8x Station 3 August cluster 1 Station 2 March (seq14); 0-1 cm Lake Grevelingen sediment Station 2 March (seq26); 0-1 cm Lake Grevelingen sediment Station 2 March (seq3); 0-1 cm Lake Grevelingen sediment 67uncultured bacterium; epibiota hydrothermal vent shrimp (CBJ18443) Station 2 March (seq21); 0-1 cm Lake Grevelingen sediment Station 2 March (seq4); 0-1 cm Lake Grevelingen sediment Station 3 March (seq10); 0-1 cm Lake Grevelingen sediment Station 1 March (seq7); 0-1 cm Lake Grevelingen sediment Station 2 August (seq11); 0-1 cm Lake Grevelingen sediment uncultured bacterium; epibiota hydrothermal vent shrimp (CBJ18444) cluster 2 Station 2 March (seq9); 0-1 cm Lake Grevelingen sediment uncultured bacterium; hydrothermal vent (CBH30829) 65 uncultured bacterium; epibiota hydrothermal vent shrimp (CBJ19314) 57 uncultured bacterium;epibiota hydrothermal vent shrimp (CBJ19314) Sulfuricurvum kujiense (YP004059532) Station 2 August (seq9); 0-1 cm Lake Grevelingen sediment Sulfurimonas denitriﬁcans (WP011372203) Thiovulum sp. ES (WP008352685) Station 1 March (seq9); 0-1 cm Lake Grevelingen sediment 94 Station 1 August (seq3); 0-1 cm Lake Grevelingen sediment Station 1 March (seq13); 0-1 cm Lake Grevelingen sediment 55 uncultured bacterium; hydrothermal vent (CBH30846) Candidatus Arcobacter sulﬁdicus (AAQ76339) uncultured bacterium; hydrothermal vent (CBH30845) Station 1 March (seq3); 0-1 cm Lake Grevelingen sediment Station 2 March (seq25); 0-1 cm Lake Grevelingen sediment 58 Station 1 August (seq11); 0-1 cm Lake Grevelingen sediment uncultured bacterium; deep sea hydrothermal vent (CBH30818) uncultured episymbiont of Alvinella pompejana (AAQ76330) Station 2 March (seq28); 0-1 cm Lake Grevelingen sediment Station 2 August (seq17); 0-1 cm Lake Grevelingen sediment cluster 3 Station 3 August (seq3); 0-1 cm Lake Grevelingen sediment Station 2 August (seq8); 0-1 cm Lake Grevelingen sediment Station 1 August (seq5); 0-1 cm Lake Grevelingen sediment Station 1 March (seq5); 0-1 cm Lake Grevelingen sediment Station 1 March (seq12); 0-1 cm Lake Grevelingen sediment Station 1 August (seq10); 0-1 cm Lake Grevelingen sediment Station 3 August (seq14); 0-1 cm Lake Grevelingen sediment Station 3 August (seq6); 0-1 cm Lake Grevelingen sediment Station 1 March (seq21); 0-1 cm Lake Grevelingen sediment Station 1 March (seq24); 0-1 cm Lake Grevelingen sediment Station 3 March (seq3); 0-1 cm Lake Grevelingen sediment Station 3 March (seq13); 0-1 cm Lake Grevelingen sediment 62 Station 1 March (seq7); 0-1 cm Lake Grevelingen sediment

73 Station 3 March (seq16); 0-1 cm Lake Grevelingen sediment cluster 4 Station 3 March (seq15); 0-1 cm Lake Grevelingen sediment Station 1 March (seq4); 0-1 cm Lake Grevelingen sediment Station 1 March (seq25); 0-1 cm Lake Grevelingen sediment Station 3 March (seq8); 0-1 cm Lake Grevelingen sediment Sulfurimonas gotlandica (WP008336361) Station 2 August (seq2); 0-1 cm Lake Grevelingen sediment 57 Station 1 August (seq18); 0-1 cm Lake Grevelingen sediment cluster 5 52 Station 1 August (seq15); 0-1 cm Lake Grevelingen sediment 86 Station 2 August (seq6); 0-1 cm Lake Grevelingen sediment Station 3 August1 (seq11); 0-1 cm Lake Grevelingen sediment Station 1 August (seq22); 0-1 cm Lake Grevelingen sediment Sulfurimonas autotrophica (WP013327378) Station 3 August (seq7); 0-1 cm Lake Grevelingen sediment uncultured bacterium; deep sea hydrothermal vent (AAS01105) 65

Sulfurovum sp. AR (WP008245184) Epsilonproteobacteria Station 3 March (seq7); 0-1 cm Lake Grevelingen sediment Station 2 March (seq15); 0-1 cm Lake Grevelingen sediment 67 Station 2 August (seq16); 0-1 cm Lake Grevelingen sediment 80 Station 2 March (seq27); 0-1 cm Lake Grevelingen sediment 52 Station 3 March (seq9); 0-1 cm Lake Grevelingen sediment Station 2 March (seq1); 0-1 cm Lake Grevelingen sediment Station 2 March (seq8); 0-1 cm Lake Grevelingen sediment Station 1 August (seq16); 0-1 cm Lake Grevelingen sediment Station 2 August (seq3); 0-1 cm Lake Grevelingen sediment 71 Station 1 March (seq2); 0-1 cm Lake Grevelingen sediment Station 1 March (seq29); 0-1 cm Lake Grevelingen sediment

Station 2 March (seq22); 0-1 cm Lake Grevelingen sediment cluster 6 Station 3 March (seq4); 0-1 cm Lake Grevelingen sediment Station 1 March (seq20); 0-1 cm Lake Grevelingen sediment Station 1 March (seq17); 0-1 cm Lake Grevelingen sediment Station 3 March (seq12); 0-1 cm Lake Grevelingen sediment 50 Station 1 March (seq15); 0-1 cm Lake Grevelingen sediment Station 2 March (seq2); 0-1 cm Lake Grevelingen sediment Station 1 March (seq14); 0-1 cm Lake Grevelingen sediment Station 1 March (seq19); 0-1 cm Lake Grevelingen sediment Station 3 March (seq16); 0-1 cm Lake Grevelingen sediment 50 Station 3 August (seq15); 0-1 cm Lake Grevelingen sediment uncultured episymbiont of Alvinella pompejana (AAQ76323) uncultured episymbiont of Alvinella pompejana (AAQ76331) uncultured episymbiont of Alvinella pompejana (AAQ76305) 97 88 Nautilia profundicola (WP012663645) Caminibacter mediatlanticus (WP007475383) uncultured episymbiont of Alvinella pompejana (AAQ76296) 80 uncultured episymbiont of Alvinella pompejana (AAQ76291) Station 1 March (seq8); 0-1 cm Lake Grevelingen sediment 82 Station 2 March (seq5); 0-1 cm Lake Grevelingen sediment Nitratifractor salsuginis (WP013553540) 51 Station 3 March (seq22); 0-1 cm Lake Grevelingen sediment Desulfurobacterium sp. TC5-1 (WP022847029) 99 51 uncultured Sulfurihydrogenibium sp. (ABW04211) 98 Persephonella marina (WP012676068) 89 Desulfurobacterium thermolithotrophum (WP013638724) Phylum Aquiﬁcea 63 Desulfurobacterium crinifex (ABI50077) 52 Thermovibrio ammoniﬁcans (WP013537775) Thermovibrio ruber (ABI50082) 66 100 Station 2 August (seq23); 0-1 cm Lake Grevelingen sediment Station 2 August (seq24); 0-1 cm Lake Grevelingen sediment 98 Station 2 August (seq22); 0-1 cm Lake Grevelingen sediment Station 2 August (seq25); 0-1 cm Lake Grevelingen sediment 64 Station 1 August (seq13); 0-1 cm Lake Grevelingen sediment 66 Station 1 August (seq14); 0-1 cm Lake Grevelingen sediment 65 Station 1 August (seq9); 0-1 cm Lake Grevelingen sediment 100 Station 1 August (seq20); 0-1 cm Lake Grevelingen sediment 60 Station 1 August (seq21); 0-1 cm Lake Grevelingen sediment Station 1 August (seq8); 0-1 cm Lake Grevelingen sediment 99 54 100 Thermoplasmatales archaeon (WP008441970) Station 3 August (seq8); 0-1 cm Lake Grevelingen sediment 100 79 Methanosaeta harundinacea (WP014587073) Station 3 March (seq20); 0-1 cm Lake Grevelingen sediment 59 94 Station 2 August (seq21); 0-1 cm Lake Grevelingen sediment 89 Station 2 August (seq18); 0-1 cm Lake Grevelingen sediment 84 Station 2 August (seq20); 0-1 cm Lake Grevelingen sediment Phylum Euryarchaeota

0.05 Figure 5b: Phylogenetic tree (amino acid-based) of aclB gene sequences retrieved in this study and closest relatives. The scale bar indicates 5% sequence divergence. 121 Chapter 5 lum, Arcobacter, and macrofaunal endosymbionts. As observed for the cbbL gene, no clustering of sequences was observed according to station or season (Fig. 5b). 5.3.6. Quantification of cable bacteria and filamentous Beggiatoaceae We performed a detailed microscopy-based quantification of the biovolume of sulfur oxidizing cable bacteria and filamentous Beggiatoaceae because both groups have been reported to govern the sediment geochemistry and sulfur cycling in sediments of Lake Grevelingen (Seitaj et al., 2015), and thus are likely to influence the chemolithoautotrophic community. Biovolume data of both filamentous bacteria for S1 have been reported before (Seitaj et al., 2015) whereas data for S2 and S3 are novel results from the 2012 campaign. In March, high biovolumes of cable bacteria were detected in S1 and S3 (Table 1) with filaments present throughout the suboxic zone until a maximum depth of 4 cm (Fig. 1c). At the same time, cable bacteria were absent in S2 (Fig. 1c). In August, cable bacteria were only detected between 1 and 2 cm deep at the deepest station (S1), albeit at abundances that were close to the detection limit of the technique. Beggiatoaceae were found in all three stations in March, although the biovolume at S2 was one order of magnitude higher than in the other two stations (Table 1). In station S2, Beggiatoaceae were uniformly distributed up to the sulfide appearance depth (Fig. 1c). In August, Beggiatoaceae were no longer detectable in stations S1 and S3 (Table 1), while at S2, filaments were no longer found in deeper sediment, but formed a thick mat at the sediment-water interface (Fig. 1c). 5.4. Discussion 5.4.1. Temporal shifts of chemolithoautotrophy and the associated bacterial assemblages Together, our geochemical and microbiological characterization of the sediments of Lake Grev- – elingen indicates that the availability of electron acceptors (O2, NO3 ) constitutes the main environmental factor controlling the activity of the chemolithoautotrophic bacterial community. In the deeper basins of Lake Grevelingen (below water depth of 15 m), the electron acceptor availability changes on a seasonal basis due to the establishment of summer hypoxia (Seitaj et al., 2015; Sulu-Gambari et al., 2016). In March, when high oxygen levels are found in the bottom waters, the chemolithoautotrophy rates were substantially higher than in August when oxygen in the bottom water was depleted to low levels (Fig. 1b; Table 1). Moreover in August, the chemolithoautotrophy rates showed a clear decrease with water depth (from S3 to S1) in line with the decrease of the bottom water oxygen concentration over depth. The 16S rRNA gene amplicon sequencing analysis in our study reveals that the response of the chemolithoautotrophic bacterial community in the surface sediments of Lake Grevelingen is associated with the seasonal changes in bottom water oxygen (Fig. 2). Generally, Lake Grevelin- gen surface sediments harbor a distinct microbial community compared to other surface sediments such as coastal marine (North Sea), estuarine and Black Sea sediments (Jessen et al., 2016; Ye et al., 2016; Dyksma et al., 2016) studied by 16S rRNA gene amplicon sequencing analysis. In March, with oxic bottom waters, the microbial community in the top centimeter of the sediment at all three stations was characterized by high abundances of Epsilon- and Gammapro- teobacteria, which are known chemolithoautotrophic sulfur-oxidizers (e.g. capable of oxidizing sulfide, thiosulfate, elemental sulfur and polythionates) using oxygen or nitrate as electron acceptor (Campbell et al., 2006; Sorokin et al., 2001; Takai et al., 2006; Labrenz et al., 2013). In 122 Results/Discussion

– August, the lack of electron acceptors (O2, NO3 ) in the bottom water was accompanied by a decrease in the relative abundance of these Gammaproteobacteria and Epsilonproteobacteria. At the same time, the numbers of reads related to the Desulfobacteraceae family increased in the top centimeter of the sediment, and a shift in the microbial community structure towards sulfate reducing bacteria related to the genera Desulfococcus and Desulfosarcina was evident. In coastal sediments, these genera are characteristic in deeper sediment layers experiencing anaerobic mineralization (Llobet-Brossa et al., 2002; Miyatake, 2011; Muyzer and Stams, 2008), and thus, they are not unexpected in surface sediments during strongly hypoxic (S2) and anoxic (S1) conditions encountered in August. Shifts in PLFA patterns are in agreement with the temporal difference in the bacterial community (Fig. 3a), with more PLFAs found in Gammaproteobacteria and Epsilonproteobacteria in March (i.e., 16:1ω7c and 18:1 ω7c; Vestal and White, 1989) as opposed to more PLFAs found in sulfate reducing bacteria in the Deltaproteobacteria in August (i.e., ai15:0, i17:1ω7c, 10Me16:0; Boschker and Middelburg, 2002; Taylor and Parkes, 1983, Edlund et al., 1985). However, sediments below the OPD in March have PLFA patterns that are more similar to those of surface sediments in August, in agreement with the observation that anaerobic metabolism such as sulfate reduction prevail in deeper anoxic sediments also in March. 5.4.2. Spring: Activity and diversity of chemolithoautotrophic bacteria – Although the availability of soluble electron acceptors (O2, NO3 ) in the bottom water is important, our data show that it cannot be the only structuring factor of the chemolithoautotrophic communities. In March 2012, all the three stations examined experienced similar bottom water – O2 and NO3 concentrations (Table 1), but still substantial differences were observed in the composition of the chemolithoautotrophic communities as determined by PLFA-SIP (Fig. 3b), as well as in the depth distribution of the chemolithoautotrophy rates in the sediment (Fig. 1b). We attribute these differences to the presence of specific sulfur oxidation mechanisms that are active in the sediments of Lake Grevelingen (Seitaj et al., 2015). In March 2012, based on FISH counts and microsensor profiles two separate sulfur oxidation regimes were active at the sites investigated: sites S1 and S3 were impacted by electrogenic sulfur oxidation by cable bacteria, while site S2 was dominated by sulfur oxidation via nitrate-storing, filamentous Beggiatoaceae. Each of these two regimes is characterized by a specific sulfur-oxidizing microbial community and a particular depth distribution of the chemolithoautotrophy. We now discuss these two regimes separately in more detail. Electrogenic sulfur oxidation In March, stations S1 and S3 (Fig. 1a) showed the geochemical fingerprint of electrogenic sulfur oxidation (e-SOx) consisting of a centimeter-wide suboxic zone that is characterized by acidic pore waters (pH < 7) (Nielsen et al., 2010; Meysman et al., 2015). Electrogenic sulfur oxidation is attributed to the metabolic activity of cable bacteria (Pfeffer et al., 2012), which are long filamentous bacteria related to the sulfate reducing genus Desulfobulbus that extend centimeters deep into the sediment (Schauer et al., 2014). The observed depth-distribution of cable bacteria at S1 and S3 (Fig. 1c) was congruent with the geochemical fingerprint of e-SOx. Cable bacteria couple the oxidation of sulfide in deeper layers to the reduction of oxygen near the sediment-water interface, by channeling electron along their longitudinal axis (long-distance electron transport). Note that stations S1 and S3 also contained some Beggiatoaceae. However, they 123 Chapter 5 attained low biovolumes and were only found at certain depths, suggesting that they did not play a significant role in sulfur oxidation. When e-SOx was present in the sediment (sites S1 and S3 in March), the chemolithoautotrophic activity penetrated deeply into the sediment and was evenly distributed throughout the suboxic zone (Fig. 1b). These field observations confirm previous laboratory incubations in which cable bacteria were induced under oxic conditions in homogenized sediments, and a highly similar depth pattern of deep chemolithoautotrophy was noted (Vasquez-Cardenas et al., 2015). This deep dark CO2 fixation is unexpected in two ways. Firstly, cable bacteria are likely not responsible for the deep CO2 fixation although they do perform sulfur oxidation, as cable bacteria from Lake Grevelingen have been shown to incorporate organic carbon rather than inorganic carbon (Vasquez-Cardenas et al., 2015). Secondly, chemolithoautotrophy is generally dependent on reoxidation reactions, but there is no transport of oxygen or nitrate to centimeters depth in these cohesive sediments, and so the question is: how can chemolithoautotrophic reoxidation occur in the absence of suitable electron acceptors? To reconcile these observations, it was proposed that in incubated electro-active sediments from Lake Grevelingen, heterotrophic cable bacteria can form a sulfur-oxidizing consortium with chemolithoautotrophic Gamma- and Epsilonproteobacteria throughout the suboxic zone

Figure 6: Schematic representation of the main sulfur oxidation mechanisms by chemoautotrophic bacteria under oxic conditions in spring (left) and hypoxic conditions in summer (right) in marine Lake Grevelingen (single-celled and filamentous sulfur-oxidizing bacteria are shown as follows, Epsilonproteo- bacteria (yellow), Gammaproteobacteria (green), Deltaproteobacteria (red), grey arrows represent possible reoxidation processes by chemoautotrophic bacteria and the color of the reaction indicates the bacterial group involved, blue arrow: trajectory of filamentous Beggiatoaceae (thick green lines) from the surface to the sulfide horizon and back up to the surface, black arrow: long-distance electron transport by cable bacteria (red broken lines). 124 Discussion

(Vasquez-Cardenas et al., 2015). The results obtained in our study provide various lines of evidence that support the existence of such a consortium in intact sediment cores. The PLFA-SIP patterns in S1 and S3 (Fig. 3b) showed major 13C-incorporation in PLFA which are present in sulfur-oxidizing Gamma- and Epsilonproteobacteria (Takai et al., 2006; Inagaki et al., 2003; Donachie et al., 2005; Zhang et al., 2005), and this occurred throughout the top 5 cm of the sediment corresponding to the zone of e-SOx activity. In addition, the depth profiles of genes involved in dark CO2 fixation (Fig. 4) revealed chemolithoautotrophic Gammaproteobacteria using the CBB cycle as well as Epsilonproteobacteria using the rTCA cycle, which confirms the potential dark CO2 fixation by both bacterial groups deep in the sediment. The higher abundance of cbbL genes in S1 compared to S3 indicates a greater chemolithoautotrophic potential of Gammaproteobacteria, which may explain the two-fold higher total chemolithoautotrophy rate encountered in S1. Moreover, the peak in aclB gene abundance found in deeper sediment suggests that Epsilonproteobacteria could play an important role in sulfur oxidation in the deeper suboxic zone in both stations. Clearly, a consortium could sustain the high rates of chemolithoautotrophy throughout the suboxic zone. It has been speculated that chemolithoautotrophs use – the cable bacteria as an electron sink in the absence of an electron acceptor like O2 or NO3 in centimeter deep sediments (Vasquez-Cardenas et al., 2015). However the question still remains as to how the Gamma- and Epsilonproteobacteria are metabolically linked to the cable bacteria (Fig. 6). In March, stations S1 and S3 also showed a higher contribution of fatty acids occurring in the sulfate reducing Deltaproteobacteria (Boschker et al., 2014; Taylor and Parkes, 1983; Webster et al., 2006) compared to the PLFA-SIP profiles in station S2 (Fig. 3b). Deltaproteobacteria such as Desulfobacterium autotrophicum and Desulfocapsa sp., as identified by 16S rRNA gene sequencing, 0 are known to grow as chemolithoautotrophs by performing H2 oxidation or S -disproportionation (Finster et al., 1998, Böttcher et al., 2005; Fig. 6), and are important contributors to the chemolithoautotrophic activity in coastal sediments (Boschker et al., 2014; Thomsen and Kris- tensen, 1997). However, a further identification of the chemolithoautotrophic Deltaproteobac- teria through the functional genes related to carbon fixation pathways was not performed in this study. Although it is known that autotrophic Deltaproteobacteria mainly use the reverse TCA cycle or the reductive acetyl-CoA pathway (Hügler and Sievert, 2011), further development of the functional gene approach, by designing specific primers is necessary to determine and clarify the diversity of Deltaproteobacteria involved in the chemolithoautotrophic activity. Overall, we hypothesize that such a diverse assemblage of chemolithoautotrophic bacteria in the presence of cable bacteria is indicative of a complex niche partitioning between these sulfur-oxidizers (Gamma-, Epsilon-, and Deltaproteobacteria). In sulfidic marine sediments found in tidal and deep sea habitats, complex S0 niche partitioning have been proposed where uncultured sulfur-oxidizing Gammaproteobacteria mainly thrive on free sulfide, the epsilonproteobacterial Sulfurimonas/Sulfurovum group oxidizes elemental sulfur, and members of the deltaproteobacterial Desulfobulbaceae family may perform S0-disproportionation (Pjevac et al., 2014). Nitrate-storing filamentous Beggiatoaceae Nitrate-storing filamentous Beggiatoaceae glide through the sediment transporting their electron – acceptor (intracellular vacuoles filled with high concentrations of NO3 ) into deeper sediment 125 Chapter 5 and electron donor (intracellular granules of elemental sulfur) up to the surface, and in doing so, they oxidize free sulfide to sulfate in a two-step process that creates a wide suboxic zone (Seitaj et al., 2015; Mußmann et al., 2003; Sayama et al., 2005; Fig. 6). In March, the microsensor depth profiles at S2 (Fig. 1a) revealed a cm-thick suboxic zone with a subsurface pH minimum at the OPD followed by a pH maximum at SAD, which is the characteristic geochemical fingerprint of sulfur oxidation by nitrate-storing Beggiatoaceae (Seitaj et al., 2015; Sayama et al., 2005). At the same time, microscopy revealed high biovolumes of Beggiatoaceae that were uniformly distributed throughout the suboxic zone (Fig. 1c), and more than half the filaments found were thicker than 15 μm indicating potential nitrate storage. Together these results corroborate the indica- tions of the dominant sulfur-oxidation mechanism suggested by the geochemical fingerprint. The chemolithoautotrophy depth profile at S2 in March (Fig. 1b) recorded higher activities in the top 1 cm and chemolithoautotrophic activity penetrated down only to 2 cm (at the sulfide appearance depth). The similar depth distribution of Beggiatoaceae and chemolithoautotrophic activity suggests that dark CO2 fixation was primarily carried out by the nitrate-storing Beggia- toaceae. Beggiatoaceae can indeed grow as obligate or facultative chemolithoautotrophs de- pending on the strain (Hagen and Nelson DC, 1996). The PLFA-SIP analysis further supported chemolithoautotrophy by Beggiatoaceae as the PLFA patterns obtained at S2 resembled those of Beggiatoa mats encountered in sediments associated with gas hydrates (Zhang et al., 2005).

However, the CO2 fixation by Beggiatoaceae could be complemented by the activity of other chemolithoautotrophs. Beggiatoaceae have previously been reported to co-occur with chemolithoautotrophic nitrate-reducing and sulfur-oxidizing Epsilonproteobacteria (Sulfurovum and Sul- furimonas) in the deep sea Guyamas basin (Bowles et al., 2012). Interestingly, station S2 in March showed the highest abundance of aclB gene copies of all stations and seasons (Fig. 4b), and in addition, had the highest relative percentage of 16S rRNA gene read sequences assigned to the

Epsilonproteobacteria (Fig. 2). Therefore, the dark CO2 fixation at station S2 is likely caused by both the motile, vacuolated Beggiatoaceae as well as the sulfur-oxidizing Epsilonproteobacteria. Yet, as was the case of the cable bacteria above, the metabolic link between Beggiatoaceae and the Epsilonproteobacteria remains currently unknown. However, it seems possible that internal- – ly stored NO3 is released into the sediment once Beggiatoa filaments lyse, allowing sulfur-oxida- – tion with NO3 by Epsilonproteobacteria. 5.4.3. Summer: Activity and diversity of chemolithoautotrophic bacteria

In August, when the O2 levels in the bottom water decreased substantially, a third geochemical regime was observed at all stations, which was different from the regimes associated with cable bacteria or nitrate-storing Beggiatoaceae. The microsensor profiling revealed an upward diffusive transport of free sulfide to the top millimeters of the sediment, which was produced in deeper sediment horizons through sulfate reduction (Fig. 1a). The uniform decrease in pH with depth is consistent with sediments dominated by sulfate reduction (Meysman et al., 2015). As noted above, the chemolithoautotrophy rates strongly decreased compared to March and were restricted to the very top of the sediment. Chemolithoautotrophic activity showed a close relation with the bottom water oxygen concentration. The number of gene copies of the two carbon fixation pathways investigated (CBB and rTCA) also decreased under hypoxic conditions (Fig. 4), suggesting a strong dependence of subsurface chemolithoautotrophy on the availability of oxygen in bottom waters.

126 Discussion/Conclusion

The highest chemolithoautotrophy rate was recorded at the shallower station (S3), which was the only station in August where O2 was found to diffusive into the sediment (Table 1), thus supporting aerobic sulfur oxidation at a shallow oxic-sulfidic interface in the sediment (Meysman et al., 2015). Several studies have shown that chemolithoautotrophy ceases in the absence of oxygen in the overlying water column (Vasquez-Cardenas et al., 2015; Miyatake, 2011; Thomsen and Kristensen, 1997). Such full anoxia occurred in the deepest station (S1), but still limited chemolithoautotrophic activity was recorded in the top layer of the sediment. A possible explanation is that some residual aerobic sulfur oxidizing bacteria were supported by the very low oxygen levels. Alternatively, cable bacteria activity at S1 in spring leads to a buildup of iron (hydr) oxides (FeOOH) in the top of the sediments, which prevents sulfide diffusion to the bottom 0 water during summer anoxia (3H2S + 2FeOOH → 2FeS + S + 4H2O) (Seitaj et al., 2015). The elemental sulfur formed in this reaction may support chemolithoautotrophic sulfur dispropor- tionating bacteria (Finster et al., 1998). At station S2, Beggiatoaceae were found forming a mat at the sediment surface in S2 (Fig. 1b) and chemolithoautotrophy rates were limited to this mat (Fig. 6). Beggiatoaceae can survive hypoxic periods by using stored nitrate as electron acceptor (Schulz and Jørgensen, 2001), which is thought to be a competitive advantage that leads to their proliferation in autumn in S1 (Seitaj et al., 2015). Such survival strategies may be used to produce energy for maintenance rather than growth under hypoxic conditions which would in combination with the low oxygen concentrations explain the low chemolithoautotrophy to biovolume ratio observed in S2 in August compared to March. 5.5. Conclusion Coastal sediments harbor a great potential for chemolithoautotrophic activity given the high anaerobic mineralization, which produce a large pool of reduced sulfur in these organic rich sediments. In this study, two environmental factors were identified to regulate the chemolithoautotrophic activity in coastal sediments: seasonal hypoxia and the dominant sulfur oxidation mechanism. In sediments where oxygen, the main electron acceptor for chemolithoautotrophs, is depleted because of seasonal hypoxia, chemolithoautotrophy was strongly inhibited. In addition, it is clear that the different sulfur oxidation mechanism (e.g. canonical sulfur oxidation, electrogenic sulfur oxidation, or sulfur oxidation mediated by vacuolated Beggiatoaceae) observed in the sediment also determine the magnitude and depth distribution of the dark CO2 fixation, as well as the chemolithoautotrophic bacterial community structure. The seasonal variations in electron acceptors and potentially reduced sulfur species suggest complex niche partitioning in the sediment by the sulfur-oxidizing bacterial community. An in depth study on the availability of different sulfur species in the sediment could shed light on the sulfur preferences by the different bacterial groups. Likewise, the potential mechanism used to metabolically link filamentous sulfur-oxidizers and chemolithoautotrophic bacteria remains presently unresolved and requires further study. These tight metabolic relationships may ultimately regulate the cycling of sulfur, carbon and even nitrogen in coastal sediments, including (but not limited to) sediments affected by seasonal hypoxia.

Acknowledgments We thankfully acknowledge the crew of the R/V Luctor (Peter Coomans and Marcel Kristalijn) and Pieter van Rijswijk for their help in the field during sediment collection, Marcel van der 127 Chapter 5

Meer and Sandra Heinzelmann for support onboard and assistance with incubations, Peter van Breugel and Marco Houtekamer for their assistance with stable isotope analysis, Elda Panoto for technical support and Alexandra Vasquez Cardenas for designing Figure 6. This work was financially supported by several grants from Darwin Centre for Biogeosciences to HTSB (grant no: 3061), LV (grant no: 3062) and FJRM (grant no: 3092), FJRM received funding from the Euro- pean Research Council under the European Union’s Seventh Framework Program (FP7/2007– 2013) via ERC grant agreement n°[306933], and RS received support from Danish Council for Independent Research-Natural Sciences.

128 Supplementary Material

Supplementary information Experimental procedures Aeration of 13C- incubations To maintain the low oxygen levels found in August at S2 and S3, 30 ml of in situ overlying water was removed and cores were closed with rubber stoppers. Headspace was then flushed with N2 through a needle inserted between the core liner and the rubber stopper without disturbing the water surface. After several minutes, N2 flushing was stopped and 10 and 35% of the headspace was replaced with air using a syringe for S2 and S3, respectively. No air was added to S1 cores. All cores were gently mixed (0.2 rpm) on a shacking plate to homogenize oxygen concentration in headspace with those in overlying water. At the end of the experiment oxygen saturation in overlying water were verified with oxygen optodes (PreSens Fibox 3 LCD) obtaining anoxic conditions for S1 (0−4% air saturation), hypoxic for S2 (20−26%) and S3 (35−80%). PLFA nomenclature The shorthand nomenclature used for phospholipid derived fatty acids is as follows. The number before the colon indicates the number of carbon atoms, while the number after represents the number of double carbon bonds in the fatty acids chain. The position of the initial double bond is then indicated by the last number after the number of carbons from the methyl end (ω). The double bond geometry is designated by cis (c) or trans (t). Methyl branching is described as being in the second carbon iso (i), third carbon anteiso (a) or a number followed by Me is used to indicate the position relative to the carboxyl end (e.g. 10Me16:0). Further details can be found in the literature (Vestal and White, 1989). PCR 16S rRNA gene amplicon library preparation and analysis PCR reactions were performed with the universal (Bacteria and Archaea) primers S-D-Arch- 0519-a-S-15 (5’-CAG CMG CCG CGG TAA-3’) and S-D-Bact-0785-a-A-21 (5’-GAC TAC HVG GGT ATC TAA TCC-3’) (Klindworth et al., 2013) adapted for pyrosequencing by the addition of sequencing adapters and multiplex identifier (MID) sequences. To minimize bias three independent PCR reactions were performed containing: 16.3 µL H2O, 6 µL HF Phusion buffer, 2.4 µL dNTP (25 mM), 1.5 µL forward and reverse primer (10 µM; each containing an unique MID tail), 0.5 µL Phusion Taq and 2 µL DNA (6 ng/µL). The PCR conditions were following: 98ºC, 30 s; 25 × [98ºC, 10 s; 53 ºC, 20 s; 72ºC, 30 s]; 72 ºC, 7 min and 4ºC, 5 min. The PCR products were loaded on a 1% agarose gel and stained with SYBR® Safe (Life technologies, Netherlands). Bands were excised with a sterile scalpel and purified with Qiaquick Gel Extraction Kit (QIAGEN, Valencia, CA) following the manufacturer’s instructions. PCR purified products were quantified with Quant-iTTM PicoGreen® dsDNA Assay Kit (Life Tech- nologies, Netherlands). Equimolar concentrations of the barcoded PCR products were pooled and sequenced on GS FLX Titanium platform (454 Life Sciences) by Macrogen Inc. Korea. Samples were analyzed using the QIIME pipeline (Caporaso et al., 2010). Raw sequences were demultiplexed and then quality-filtered with a minimum quality score of 25, length between 250−350, and allowing maximum two errors in the barcode sequence. Sequences were then clustered into operational taxonomic units (OTUs, 97% similarity) with UCLUST (Edgar, 2010). Reads were aligned to the Greengenes Core reference alignment (DeSantis et al., 2006) using 129 Chapter 5 the PyNAST algorithm (Caporaso et al., 2010). Taxonomy was assigned based on the Green- genes taxonomy and a Greengenes reference database (version 12_10) (McDonald et al., 2012; Werner et al., 2012). Representative OTU sequences assigned to the specific taxonomic groups were extracted through classify.seqs and get.lineage in Mothur (Schloss et al., 2009) by using the greengenes reference and taxonomy files. In order to determine a more accurate taxonomic classification of the bacterial groups with high percentage of reads and known to contain members with chemolithoautotrophic metabolism, sequence reads of the order Chromatiales and Thiotrichales (Fig. S1, S2), reads of the order Desulfarculales (Fig. S3), the family of Desulfobulbaceae (Fig. S4a) and the genus Desulfubulbus (Fig. S4b), reads of the family Desulfobacteraceae (Fig. S5a–c), and additionally reads of the order Campylobacterales (Fig. S6a–d) were extracted from the dataset and added to a phylogenetic tree as described in the supplementary experimental procedures. Quantification of cable bacteria and Beggiatoaceae Microscopic identification of cable bacteria was achieved by fluorescence in situ hybridization (FISH), using a Desulfobulbaceae-specific oligonucleotide probe (DSB706; 5′-ACC CGT ATT CCT CCC GAT-3′), according to (Schauer et al., 2014). Cable bacteria biovolume per unit of sediment volume (mm3 cm−3) was calculated based on measured filament length and diameter. The areal biovolume of cable bacteria (mm3 cm−2) was obtained by depth integration over all sediment layers analyzed. The minimum limits of quantification via FISH for single cells were 1.5 × 106 cells cm−3, taken as the FISH count with the negative control probe NON338; a minimum of 1000 DAPI (4,6-diamidino-2-phenylindole) stained cells was evaluated for this count. The FISH detection limit for cable bacteria was lower than for single cells, and was calculated to be 10 cm filament cm−3 (corresponding to <1 filament in 0.1 mL of sediment). Filamentous Beggiatoaceae were identified via inverted light microscopy (Olympus IM) within 24 h of sediment retrieval. Intact sediment cores were sectioned at 5 mm intervals over the top 4 cm from which subsamples (20−30 mg) were used to count living Beggiatoaceae (Seitaj et al., 2015). The biovolume was determined by measuring length and width of all filaments found in the subsample, following the counting procedure described in (Jørgensen et al., 2010). Statistical analysis All statistical analyses were performed using the CRAN: stats package in the open source software R. A two-way ANOVA (aov) was used to test the effect of station, season, and sediment depth on bacterial biomass, chemolithoautotrophic activity, and gene abundances. PLFA concentrations and 13C-incorporation values were expressed as a fraction of the total bacterial biomass and 13C-incorporation (respectively) per sediment sample. These relative PLFA values were first log-transformed (log (x+1)) and subsequently analyzed with Principal Component Analysis (PCA: prcomp) to distinguish different bacterial and chemolithoautotrophic communities in the sediment.

130 Supplementary Material Campbell Nigro and et al., 2003 Reference King, 2007 312 492-495 size [b] size s, 72°C 40 s, Tm [95°C 30 s, Amplicon

PCR 62 PCR 53 qPCR 57 qPCR 54 Tm [°C] Tm Primer pair K2f (5’-ACCAYCAAGCCSAAGCTSGG-3’) V2r (5’-GCCTTCSAGCTTGCCSACCRC-3’) aclB R (5’-ATARTTKGGBCCACCKCKTC-3’) aclB F (5’-TGGACHATGGTDGCHGGKGGT-3’) s, 72°C 1 min]; 5 min. qPCR conditions: 95°C 4 min; 40 40 s, [95°C 1 min, Tm

gene Target aclB genecbbL Primer pairs described in the text, PCR conditions and amplicon size used this study. Assay cloning cloning qPCR + PCR/ qPCR + PCR/ Table S1: Table PCR conditions: 95°C 5 min; 40 s. 30 s]; 80°C 25 s. 131 Chapter 5

JX138882, uncultured bacterium, marine sediments JF809744, uncultured bacterium, Medea hypersaline basin, Mediterranean Sea EU373841, uncultured gamma proteobacterium, canyon and slope sediment DQ498828, Thiocapsa imhoffii ARB_38DFA738, denovo886 GI3.1_648 JX521203, uncultured bacterium, terrestrial sulfidic spring JX138600, uncultured bacterium, marine sediments EU491667, uncultured bacterium, seafloor lavas from the East Pacific Rise AJ223235, Lamprocystis purpurea KC471275, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough AJ006063, Lamprocystis roseopersicina DQ289918, uncultured gamma proteobacterium, South Atlantic Bight Permeable Shelf Sediment Y12366, Lamprocystis purpurea ARB_7A35AA84, denovo1280 GI1.1_178 Ab478670, uncultured Chromatiaceae bacterium, submerged biofilm mats wetland HE817849, uncultured bacterium, tissue of sponge Vaceletia crypta DQ676347, uncultured gamma proteobacterium, suboxic freshwater−pond bacterioplankton ARB_D868D57F, denovo435 GI3.1_117 ARBC01000182, Lamprocystis purpurea DSM 4197 GU119047, uncultured bacterium FJ205275, uncultured gamma proteobacterium, active hydrothermal field sediments, depth:1922m AJ006057, phototrophic bacterium JQ347472, uncultured bacterium, Da Ya Bay DQ676296, uncultured gamma proteobacterium, suboxic freshwater−pond bacterioplankton ARB_C8883AA2, denovo18 GII3.1_3781 FN396696, uncultured marine bacterium, Arctic marine surface sediment ARB_120B20A, denovo2400 GII3.1_10467 ARB_DB9D716A, denovo836 GI3.1_1527 ARB_B82136A6, denovo1971 GII2.1_2927 Am882544, uncultured gamma proteobacterium, sediment from oil polluted water Lamprocystis ARB_639358B4, denovo3330 GII3.1_10833 ARB_3ED72159, denovo2717 GI2.1_4916 ARB_B3D72EEA, denovo473 GI2.1_3560 JQ062714, uncultured bacterium, sponge tissue ARB_4D38CEFC, denovo3368 GII2.1_10913 ARB_57D58DCA, denovo51 GI2.1_107 ARB_2E607D92, denovo759 GII1.1_1362 ARB_83FE435B, denovo2355 GI3.1_549 AJ831752, uncultured bacterium, chemocline FJ937838, uncultured gamma proteobacterium, coastal waters of Lingshui Bay of Hainan Island in the South China Sea JX521262, uncultured bacterium, terrestrial sulfidic spring FJ937834, uncultured bacterium, coastal waters of Lingshui Bay of Hainan Island in the South China Sea AJ224430, Isochromatium buderi JF344578, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_66261C8C, denovo2664 GII3.1_1805 16 uncultured EF208706, uncultured bacterium, sandy carbonate sediment EU652575, uncultured bacterium, Yellow Sea sediment ARB_A2F14DB, denovo674 GII3.1_6959 KF741570, uncultured bacterium, Talbert salt marsh sediment Jn479885, uncultured organism, Guerrero Negro Hypersaline Mat JF727679, uncultured gamma proteobacterium, petroleum−contaminated saline−alkali soils Jn461133, uncultured organism, Guerrero Negro Hypersaline Mat JQ347371, uncultured bacterium, Da Ya Bay ARB_528E7DEA, denovo59 GI1.1_4285 ARB_C634BA31, denovo1128 GI3.1_3820 ARB_9441BCE4, denovo1555 GII2.1_57 Jn450999, uncultured organism, Guerrero Negro Hypersaline Mat GU118309, uncultured bacterium Jn458696, uncultured organism, Guerrero Negro Hypersaline Mat JX280354, uncultured bacterium, marine sponge Jn459399, uncultured organism, Guerrero Negro Hypersaline Mat DQ513032, uncultured bacterium, ridge flank crustal fluid DQ330804, uncultured proteobacterium, hypersaline microbial mat: Guerrero Negro FJ535071, uncultured gamma proteobacterium, cave wall biofilm Jn469059, uncultured organism, Guerrero Negro Hypersaline Mat AF317768, unidentified bacterium wb1_P19 Am882535, uncultured gamma proteobacterium, sediment from oil polluted water EF125399, uncultured bacterium, naked tidal flat sediment near mangrove Chromatiales_Chromatiaceae ARB_37CE9830, denovo1458 GI1.1_565 Am882566, uncultured gamma proteobacterium, sediment from oil polluted water FJ905747, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga Arc DQ330805, uncultured proteobacterium, hypersaline microbial mat: Guerrero Negro FJ205285, uncultured gamma proteobacterium, active hydrothermal field sediments, depth:1922m HQ877095, Lamprobacter modestohalophilus JF272102, uncultured bacterium, biofilms X93472, Halochromatium glycolicum Halochromatium GU061300, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 20 m depth ARB_78A3E9B6, denovo818 GI1.1_1073 X98597, Halochromatium salexigens JF344260, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beach Am283535, Halochromatium roseum

HQ191094, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea Chromatiales_Chromatiaceae_Nitrosococcus KF799054, uncultured bacterium, gut ARB_8F2AAD3A, denovo1907 GI3.1_2023 ARB_C9137E14, denovo4029 GII3.1_8926 JQ579854, uncultured gamma proteobacterium, sediments from Figueiras Beach KF513141, uncultured Thiohalocapsa sp., pink berry consortia from Sippewissett salt marsh Thiohalocapsa JF344662, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach AVFP01004244, microbial mat metagenome, pink berry consortia of the Sippewissett salt marsh GQ246358, uncultured bacterium, North Yellow Sea sediments DQ867047, uncultured bacterium, natural gas field Am491592, Thiohalocapsa marina M96398, Nitrosococcus oceani JQ738932, uncultured bacterium, Lonar sediment surface rocks AY690336, Nitrosococcus oceani AF508987, Nitrosococcus oceani 0.05 AF363287, Nitrosococcus oceani CP000127, Nitrosococcus oceani ATCC 19707 CP000127, Nitrosococcus oceani ATCC 19707 AF508994, Nitrosococcus oceani CP002086, Nitrosococcus watsonii C−113 CP002086, Nitrosococcus watsonii C−113 CP001798, Nitrosococcus halophilus Nc 4 AJ298727, Nitrosococcus oceani CP001798, Nitrosococcus halophilus Nc 4 AJ298748, Nitrosococcus halophilus JX240761, uncultured proteobacterium, coastal soil HF558562, uncultured bacterium, tailing material AM882518, uncultured gamma proteobacterium, sediment from oil polluted water from petrochemical treatment plant AF170421, sulfur−oxidizing bacterium OBII5 AJ810552, uncultured gamma proteobacterium, superficial sediments uncultured ARB_334A7441, denovo4022 GII3.1_923 AB681900, Granulosicoccus antarcticus ARB_BB6DFFA9, denovo421 GI1.1_601 EF495228, Granulosicoccus antarcticus, seawater ARB_516EEF6C, denovo342 GII3.1_5432 KC160719, Granulosicoccus sp. SS10.26, Antarctic sea sediment DQ351800, uncultured gamma proteobacterium, marine sediments FJ535355, Granulosicoccus coccoides, leaves of sea grass in Troitza Bay, Gulf of Peter the Great, Sea of Japan HQ191097, uncultured sediment bacterium, Dangast muddy intertidal sediment; German Wadden Sea GU451354, uncultured bacterium, macroalgal surface GQ246364, uncultured bacterium, North Yellow Sea sediments JF344155, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beach AF223297, uncultured gamma proteobacterium B2M28 ARB_EFBD0A28, denovo1856 GI2.1_972 ARB_AB5216C3, denovo3247 GII2.1_612 AF223299, uncultured gamma proteobacterium B2M60 JX559163, uncultured bacterium, antarctic aerosol JQ586305, uncultured bacterium, arctic marine sediment FJ905714, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga Arc HQ191062, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea GQ119472, uncultured proteobacterium HQ191090, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea ARB_E6BF6C65, denovo119 GI1.1_2739 KF624106, uncultured bacterium, anoxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea Hq153883, uncultured bacterium, shallow hydrothermal vent 189.1 m AY193138, uncultured proteobacterium, marine sediment EU246808, uncultured gamma proteobacterium, Calcinus obscurus abdominal flora DQ394966, uncultured gamma proteobacterium, harbor sediment ARB_5B178E07, denovo1043 GI1.1_895 ARB_57253D3A, denovo1419 GI1.1_2310 JF344255, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beach ARB_1DF4361C, denovo2934 GII2.1_7000 EU050785, uncultured gamma proteobacterium, sediment from the Kings Bay, Svalbard, Arctic FJ545494, uncultured bacterium, North Yellow Sea sediment GU234740, uncultured marine bacterium, Antarctic sea water collected from 5m GU061176, uncultured gamma proteobacterium, Yellow Sea intertidal beach surface seawater ARB_62B26A19, denovo3300 GII3.1_6302 EU491687, uncultured bacterium, seafloor lavas from the East Pacific Rise AB099937, uncultured bacterium, inactive deep−sea hydrothermal vent chimneys EU491530, uncultured bacterium, seafloor lavas from the East Pacific Rise DQ269113, uncultured gamma proteobacterium, surface of marine macro−alga HQ191065, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea GQ274231, uncultured gamma proteobacterium, heat exchange system using biocides to inhibit biofilm formation FJ712412, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea ARB_BB7219C4, denovo505 GII2.1_2624 AM889168, uncultured gamma proteobacterium, Sediments ARB_97A6CE1, denovo309 GI2.1_1401 FM211768, uncultured gamma proteobacterium, sediment of Bizerte lagoon EU491486, uncultured bacterium, seafloor lavas from Hawai’i South Point X4 HQ191095, uncultured sediment bacterium, Dangast muddy intertidal sediment; German Wadden Sea JN606989, uncultured bacterium, white microbial mat from lava tube wall KF799091, uncultured bacterium, gut EU491392, uncultured bacterium, seafloor lavas from Hawai’i South Point X3 HQ190975, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea JX226828, uncultured bacterium, nodule collected from station WS0904 in the Clarion−Clipperton Fracture Zone HQ190997, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea EU287407, uncultured bacterium, arctic surface sediment HF922366, uncultured bacterium, high pressure reactor KC861163, uncultured bacterium HF922334, uncultured bacterium, high pressure reactor EU652530, uncultured bacterium, Yellow Sea sediment KF624415, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea ARB_6609E7D9, denovo1802 GI1.1_2332 EU491232, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2 JF266091, uncultured bacterium, white microbial mat lava tube wall Gu369920, uncultured epsilon proteobacterium, white microbial film shallow hydrothermal vent HQ397072, uncultured gamma proteobacterium, haloalkaline soil ARB_97962E3E, denovo2892 GI3.1_431 JF344181, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beach DQ351779, uncultured gamma proteobacterium, marine sediments AB476263, uncultured bacterium, ventral setae of Shinkaia crosnieri GU061213, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 5 m depth ARB_BBCD0639, denovo969 GI1.1_2370 JF344014, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from rodas beach Hq153957, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal vent DQ351744, uncultured gamma proteobacterium, marine sediments EF092205, uncultured gamma proteobacterium ARB_9A36BE2D, denovo2926 GII3.1_4245 FR744557, uncultured bacterium, nitrate−amended injection water from the Halfdan oil field Gu302450, uncultured bacterium, marine sediments (900 m water depth, Gulf of Mexico EU491601, uncultured bacterium, seafloor lavas from the East Pacific Rise EU491337, uncultured bacterium, seafloor lavas from Hawai’i South Point X3 HQ379738, gamma proteobacterium S−1(2010) KC470886, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough JX391088, uncultured bacterium, marine sediment FJ416116, uncultured bacterium, sediment from station NEC5 in the Northern Bering Sea JF344304, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach Chromatiales_Granulosicoccaceae_Granulosicoccus FN396751, uncultured marine bacterium, Arctic marine surface sediment ARB_9C00EB59, denovo1294 GII1.1_8935 DQ351776, uncultured gamma proteobacterium, marine sediments ARB_9C00EB59, denovo2723 GI1.1_3081 JQ580264, uncultured gamma proteobacterium, sediments from Rodas Beach polluted with crude oil JF344362, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach FJ264585, uncultured bacterium, methane seep sediment JF344419, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach FJ358865, uncultured gamma proteobacterium, marine reef sandy sediment JF344330, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_B77AF6B7, denovo2435 GI1.1_1585 JF344428, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach JX504392, uncultured bacterium, oolitic sand FM242303, uncultured gamma proteobacterium, sediment JF344659, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach AM176842, uncultured bacterium, mangrove sediment JX193397, uncultured bacterium, intertidal surface sediment HQ916536, uncultured bacterium, Lei−Gong−Huo mud volcano JF344391, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach AB278144, uncultured bacterium, obtained from Mariana Trough DQ395021, uncultured gamma proteobacterium, harbor sediment HF558592, uncultured bacterium, tailing material ARB_781E2AD4, denovo2106 GI2.1_4886 ARB_C0B550B5, denovo551 GII1.1_195 ARB_C0B550B5, denovo1651 GI1.1_51 0.05 HQ203959, uncultured bacterium, seawater FM211764, uncultured gamma proteobacterium, sediment of Bizerte lagoon DQ351781, uncultured gamma proteobacterium, marine sediments ARB_AD855E3B, denovo1086 GII3.1_4940 ARB_42D76043, denovo2199 GI2.1_788 ARB_6192704D, denovo1940 GI2.1_2314 AB530205, uncultured bacterium, marine sediment GQ500735, uncultured bacterium, Charon’s Cascade, sandy clastic sediments Hm598244, uncultured bacterium, surface sediment Xisha Trough, China Sea ARB_754734E8, denovo507 GI2.1_2211 EF999373, uncultured bacterium, Pearl River Estuary sediments at 22cm depth DQ395015, uncultured gamma proteobacterium, harbor sediment AM889166, uncultured gamma proteobacterium, Sediments DQ395051, uncultured gamma proteobacterium, harbor sediment JN977193, uncultured bacterium, Jiaozhao Bay sediment JF344480, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach DQ394926, uncultured gamma proteobacterium, harbor sediment FJ545485, uncultured bacterium, North Yellow Sea sediment GQ246283, uncultured bacterium, North Yellow Sea sediments AB530211, uncultured bacterium, marine sediment GU230357, uncultured gamma proteobacterium, coastal sediment JF344616, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach AM889165, uncultured gamma proteobacterium, Sediments JN977291, uncultured bacterium, Jiaozhao Bay sediment AM889164, uncultured gamma proteobacterium, Sediments DQ394995, uncultured gamma proteobacterium, harbor sediment DQ395062, uncultured gamma proteobacterium, harbor sediment KF463825, uncultured gamma proteobacterium, Marine coastal sediment ARB_800DD24B, denovo2123 GI1.1_1928 GQ246321, uncultured bacterium, North Yellow Sea sediments GU230358, uncultured gamma proteobacterium, coastal sediment GU061255, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 5 m depth GU061303, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 20 m depth JN038904, uncultured gamma proteobacterium, Chongxi wetland soil Chromatiales_Ectothiorhodospiraceae FJ786140, uncultured bacterium, prawn farm sediment ARB_BA77D3F2, denovo1553 GII2.1_8765 ARB_E4ED143B, denovo942 GII2.1_8839 ARB_136300C8, denovo2859 GI1.1_837 ARB_E7A49636, denovo132 GII2.1_1684 ARB_5E12BDAE, denovo3289 GII3.1_10675 ARB_47DF8362, denovo147 GI2.1_4282 ARB_429AAAE0, denovo1745 GI2.1_3679 Am882524, uncultured gamma proteobacterium, sediment from oil polluted water FJ416094, uncultured bacterium, sediment from station NEC5 in the Northern Bering Sea ARB_2EDF208B, denovo2396 GII3.1_9109 ARB_87D422D8, denovo2963 GII3.1_3051 ARB_BB3E52D1, denovo907 GI2.1_2633 ARB_65268B1C, denovo1635 GII2.1_5704 AB722093, uncultured bacterium, subseafloor massive sulfide deposit Fn553610, uncultured sediment bacterium, Logatchev hydrothermal vent depth = 3224 m ARB_82B8D5B4, denovo910 GI2.1_3635 Fn553597, uncultured sediment bacterium, Logatchev hydrothermal vent 3224 m EU491112, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2 FJ497654, uncultured gamma proteobacterium, Vailulu’u Seamount AB722101, uncultured bacterium, subseafloor massive sulfide deposit ARB_F3CD46EB, denovo3941 GII2.1_7119 AB294934, uncultured gamma proteobacterium, microbial mat at a shallow submarine hot spring Fr670375, uncultured gamma proteobacterium, microbial mat from Eiffel Tower edifice in Lucky Strike EU652533, uncultured bacterium, Yellow Sea sediment JN977309, uncultured bacterium, Jiaozhao Bay sediment ARB_6DE0F30B, denovo2739 GI3.1_126 EU330397, uncultured gamma proteobacterium, mangrove forest mud ARB_910196BD, denovo1551 GI3.1_1932 Hq153920, uncultured bacterium, white microbial film shallow hydrothermal vent EU491810, uncultured bacterium, seafloor lavas from the East Pacific Rise DQ431906, uncultured gamma proteobacterium, Gulf of Mexico sediment HQ191077, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea GU061216, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 5 m depth ARB_8B4C06BD, denovo3718 GII1.1_5285 ARB_8B4C06BD, denovo1901 GI1.1_3043 HQ588368, uncultured bacterium, Amsterdam mud volcano sediment GQ246407, uncultured bacterium, North Yellow Sea sediments FJ497635, uncultured bacterium, Vailulu’u Seamount Fj712561, uncultured bacterium, Kazan Mud Volcano Kc682690, uncultured bacterium, hydrothermal sulfide chimney, Lau Basin EU491101, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2 Fj640811, uncultured bacterium, hydrothermal vent chimney Juan de Fuca Ridge 2267m GQ903353, uncultured bacterium, ODP Hole 896A basalt crust formation fluid EF999348, uncultured bacterium, Pearl River Estuary sediments at 6cm depth HQ003527, uncultured gamma proteobacterium, Carrizo shallow lake 0.05

Figure S1: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Gammaproteobacteria, order: Chromatiales (black bold: sequences retrieved in this study and closest relatives). 132 Supplementary Material

AM176844, uncultured bacterium, mangrove sediment HQ203915, uncultured bacterium, seawater FJ497639, uncultured gamma proteobacterium, Vailulu’u Seamount ARB_3553A2D9, denovo1695 GII2.1_1026 Fr670408, uncultured gamma proteobacterium, microbial mat from Eiffel Tower Lucky Strike vent area Ef687244, uncultured bacterium, iron−oxidizing mat, Chefren mud volcano KC682859, uncultured bacterium, surface of a basalt collected from Kilo Moana vent field, Lau Basin AB476269, uncultured bacterium, ventral setae of Shinkaia crosnieri Hq153952, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal vent FJ787300, uncultured bacterium, gas hydrate sediments of the Kazan Mud Volcano, East Mediterranean Sea KF624162, uncultured bacterium, oxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea HQ191073, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea ARB_9F2BCD1A, denovo2124 GI1.1_1929 AB015250, uncultured gamma proteobacterium, deepest cold−seep area of the Japan Trench ARB_27D9B048, denovo3381 GII3.1_4329 Fn553471, uncultured sediment bacterium, Logatchev hydrothermal vent field,oceanic sediment AB476207, uncultured bacterium, ventral setae of Shinkaia crosnieri AB476206, uncultured bacterium, ventral setae of Shinkaia crosnieri AB530202, uncultured bacterium, marine sediment HQ191082, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea AM882552, uncultured gamma proteobacterium, sediment from oil polluted water from petrochemical treatment plant KF624159, uncultured bacterium, oxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea ARB_17F65DD9, denovo2929 GII1.1_4344 ARB_17F65DD9, denovo1483 GI1.1_747 KF624231, uncultured bacterium, suboxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea JQ287244, uncultured bacterium, East Pacific Rise JQ287289, uncultured bacterium, East Pacific Rise ARB_585E8CC4, denovo2756 GI3.1_2429 FJ905708, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga Arc KF624156, uncultured bacterium, oxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea ARB_83A518EC, denovo2486 GI1.1_92 ARB_83A518EC, denovo1329 GII3.1_629 FJ205286, uncultured gamma proteobacterium, active hydrothermal field sediments, depth:1922m Ef687482, uncultured bacterium, sediment underneath an iron−oxidizing mat, Chefren mud volcano ARB_8F6B21AE, denovo413 GI1.1_285 AM882574, uncultured gamma proteobacterium, sediment from oil polluted water from petrochemical treatment plant FJ712538, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea Fn397820, uncultured gamma proteobacterium, GeoB 9072−1 anoxic sub−surface mud volcano AJ535246, uncultured gamma proteobacterium, marine sediment above hydrate ridge AM745138, uncultured gamma proteobacterium, marine sediments Fn553607, uncultured sediment bacterium, Logatchev hydrothermal vent sediment at 3224 m AF154089, uncultured hydrocarbon seep bacterium BPC036 FJ712588, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea ARB_71C0FE2D, denovo2398 GII3.1_2072 ARB_DFAE6D84, denovo669 GI2.1_13 FJ264668, uncultured bacterium, methane seep sediment JN977166, uncultured bacterium, Jiaozhao Bay sediment EU652548, uncultured bacterium, Yellow Sea sediment uncultured ARB_1103BE8F, denovo1699 GI2.1_3700 ARB_2C6B48A0, denovo576 GI1.1_851 ARB_40FFFC75, denovo472 GI1.1_1416 Hq153917, uncultured bacterium, white microbial film shallow hydrothermal vent Hq153955, uncultured bacterium, white filamentous microbial mat shallow hydrothermal vent ARB_97098AEA, denovo2230 GI2.1_1696 HQ191071, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea EF644802, uncultured bacterium, MAR Logatchev hydrothermal vent system, 3000m water depth, sulfide sample Jf344197, uncultured gamma proteobacterium, petroleum spot over marine sediments ARB_6C6887C4, denovo1420 GI1.1_961 KF268708, uncultured bacterium, marine sediment Jf344186, uncultured gamma proteobacterium, petroleum spot over marine sediments AB271125, Oligobrachia mashikoi endosymbiont G AB271122, Oligobrachia mashikoi endosymbiont D

AB271124, Oligobrachia mashikoi endosymbiont F Thiotrichales_Thiotrichaceae AB271120, Oligobrachia mashikoi endosymbiont B AB252051, Oligobrachia mashikoi endosymbiont A EU491817, uncultured bacterium, seafloor lavas from the East Pacific Rise JF344283, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach JQ580274, uncultured gamma proteobacterium, sediments from Rodas Beach polluted with crude oil Fn397817, uncultured gamma proteobacterium, GeoB 9072−1 anoxic sub−surface mud volcano DQ925898, uncultured bacterium, hydrothermal vent chimneys of Guaymas Basin AB476202, uncultured bacterium, ventral setae of Shinkaia crosnieri Fn397818, uncultured gamma proteobacterium, GeoB 9072−1 anoxic sub−surface mud volcano FJ497576, uncultured gamma proteobacterium, Vailulu’u Seamount FJ497611, uncultured gamma proteobacterium, Vailulu’u Seamount FJ497565, uncultured gamma proteobacterium, Vailulu’u Seamount FJ497622, uncultured gamma proteobacterium, Vailulu’u Seamount ARB_F1FB6017, denovo1531 GI2.1_1865 ARB_BF291963, denovo1853 GII2.1_888 KF624239, uncultured bacterium, suboxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea ARB_2B841FB1, denovo642 GI3.1_474 FJ712548, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea FJ264584, uncultured bacterium, methane seep sediment JF344299, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach FJ905702, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga Arc ARB_D102CB76, denovo2637 GI1.1_1578 ARB_8C35E7C7, denovo309 GII3.1_11763 EU491119, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2 Fn553445, uncultured sediment bacterium, Logatchev hydrothermal vent field,oceanic sediment JQ579946, uncultured gamma proteobacterium, sediments from Figueiras Beach JX559252, uncultured bacterium, antarctic aerosol ARB_D18874D7, denovo1457 GI2.1_998 ARB_D18874D7, denovo3229 GII2.1_12387 JX570601, endosymbiont of Ridgeia piscesae KC682827, uncultured bacterium, surface of a basalt collected from Kilo Moana vent field, Lau Basin Fr670405, uncultured gamma proteobacterium, microbial mat from Eiffel Tower Lucky Strike JQ200201, uncultured bacterium, seawater; next to dolphin Y AB495251, Cocleimonas flava, marine mollusk Jn662081, uncultured gamma proteobacterium, particulate detritus Eu107481, uncultured Leucothrix sp., Okinawa Trough at depth of 1309 meters Cocleimonas AB476220, uncultured bacterium, ventral setae of Shinkaia crosnieri 0.05 EU555124, uncultured bacterium, Dudley hydrothermal vent

AF532775, Candidatus Isobeggiatoa divolgata, marine sediment AF532769, Candidatus Isobeggiatoa divolgata, Wadden Sea sediment ARB_D11B76E1, denovo3026 GII2.1_578 ARB_D11B76E1, denovo976 GI2.1_627 AB108786, Candidatus Isobeggiatoa divolgata, marine sediment ARB_D764416C, denovo1446 GI2.1_519 Candidatus Isobeggiatoa FJ875195, uncultured Beggiatoa sp., marine sediment underlying a salmon farm FN561862, Candidatus Isobeggiatoa divolgata, marine sediment AF532771, uncultured Beggiatoa sp., marine sediment ARB_6BD95FAD, denovo1168 GI2.1_4524 ARB_9D6DFEEE, denovo3057 GII2.1_5949 AF532773, Candidatus Parabeggiatoa communis, marine sediment AF532772, Candidatus Parabeggiatoa communis, marine sediment ARB_C4375616, denovo1726 GI1.1_3844 Candidatus Parabeggiatoa JN793555, uncultured Beggiatoa sp., hydrothermal seep at Guaymas Basin FJ875199, uncultured Beggiatoa sp., marine sediment underlying a salmon farm FR847872, Candidatus Halobeggiatoa sp. HMW−W562, white microbial mat _Thiotrichaceae Fr847873, Candidatus Halobeggiatoa sp. HMW−W572, white microbial mat FR847870, Candidatus Halobeggiatoa sp. HMW−W520, white microbial mat FR847871, Candidatus Halobeggiatoa sp. HMW−S2528, white microbial mat ARB_9D825299, denovo578 GI1.1_2396 FN811663, Thiomargarita namibiensis, sediment surface Fr690927, Candidatus Thiomargarita nelsonii, sediment

FR690929, Candidatus Thiomargarita nelsonii, sediment Thiotrichales FR690966, Candidatus Thiomargarita nelsonii, sediment FR690953, Candidatus Thiomargarita nelsonii, sediment Thiomargarita ARB_4BFED579, denovo1545 GII2.1_7825 FR690945, Candidatus Thiomargarita nelsonii, sediment FR690946, Candidatus Thiomargarita nelsonii, sediment FR690961, Candidatus Thiomargarita nelsonii, sediment ARB_330D7B34, denovo283 GII2.1_1879 ARB_330D7B34, denovo347 GI2.1_475 FR690894, Thiomargarita namibiensis, sediment FR827866, Thiomargarita namibiensis, intertidal mud ﬂat

JN793554, uncultured Beggiatoa sp., hydrothermal seep at Guaymas Basin Thiomargarita 0.05 ARB_9FCD4774, denovo879 GI3.1_3565 Figure S2: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Gammaproteobacte- ria, order: Thiotrichales, family: Thiotrichaceae (black bold: sequences retrieved in this study and closest relatives). 133 Chapter 5

EU592480, uncultured bacterium, hypersaline sediment ARB_7060483C, denovo2020 GI3.1_5100 GQ500708, uncultured bacterium, Charon’s Cascade, sandy clastic sediments Fq658834, uncultured soil bacterium, PAH−contaminated soil DQ137968, uncultured bacterium, wetland ARB_10DE197D, denovo40 GI2.1_3162 FJ516989, uncultured Desulfobacteraceae bacterium, upper sediment GU208294, uncultured prokaryote, Dongping Lake sediment HM243855, uncultured bacterium, middle sediment from Honghu Lake HQ003578, uncultured delta proteobacterium, Carrizo shallow lake KF268888, uncultured bacterium, marine sediment ARB_7004B897, denovo93 GII2.1_1855 ARB_7004B897, denovo1972 GI3.1_386 AB530221, uncultured bacterium, marine sediment AB694469, uncultured bacterium, Deep−sea sediment at a depth 7111m. Jn511815, uncultured organism, Guerrero Negro Hypersaline Mat Jn537626, uncultured organism, Guerrero Negro Hypersaline Mat GQ246439, uncultured bacterium, North Yellow Sea sediments ARB_6181BE0B, denovo348 GI1.1_2389 FJ716464, uncultured bacterium, Frasassi cave system, anoxic lake water ARB_8D6EA0F6, denovo3241 GII3.1_2770 JQ925081, uncultured bacterium, cold seep sediment from oxygen mimimum zone in Pakistan Margin JQ580439, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil JN207182, uncultured delta proteobacterium, Namako−ike surface sediment (0−1 cm) JQ036264, uncultured bacterium, Eel River Basin sediment 2688 Gu302479, uncultured bacterium, marine sediments Mississippi Canyon HQ691991, uncultured delta proteobacterium, stratified lagoon AF029045, benzene mineralizing consortium clone SB−21 DQ394937, uncultured Desulfobacterium sp., harbor sediment GQ246425, uncultured bacterium, North Yellow Sea sediments EF125430, uncultured bacterium, mangrove soil DQ811822, uncultured delta proteobacterium, mangrove soil ARB_5BA65306, denovo2937 GI3.1_931 ARB_7BD0700F, denovo1902 GII1.1_5946 FN396676, uncultured marine bacterium, Arctic marine surface sediment ARB_666D9846, denovo1315 GI2.1_3389 ARB_D6FD159, denovo3965 GII2.1_38 FJ485073, uncultured delta proteobacterium, biomat in El Zacaton at 114m depth Gu127072, uncultured delta proteobacterium, sediment; anoxic zone DQ831550, uncultured delta proteobacterium, marine sediment ARB_D788D99F, denovo2296 GII3.1_7171 ARB_3535E826, denovo1384 GI2.1_3008 HQ178897, uncultured bacterium, sediment treated with Mr. Frosty slow freeze method Gu302445, uncultured bacterium, marine sediments Mississippi Canyon Jf344708, uncultured delta proteobacterium, hydrocarbon polluted marine sediments GU362957, uncultured bacterium, marine sediment from the South China Sea ARB_AB57ED2D, denovo1051 GII3.1_1604 JQ816986, uncultured bacterium, subseafloor sediment at the Good Weather Ridge DQ811813, uncultured delta proteobacterium, mangrove soil ARB_8F5D807B, denovo60 GII3.1_7337 KC470953, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough Jn518898, uncultured organism, Guerrero Negro Hypersaline Mat DQ811811, uncultured delta proteobacterium, mangrove soil EU385682, uncultured bacterium, subseafloor sediment of the South China Sea FJ628273, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 50 AJ241002, uncultured delta proteobacterium Sva0516 Jf344210, uncultured delta proteobacterium, petroleum spot over marine sediments ARB_E20D5C9D, denovo188 GI1.1_278 FJ437826, uncultured bacterium, Green Lake chemocline at 20.5 m water depth AY216442, uncultured bacterium, temperate estuarine mud JQ580448, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_4EA6FD94, denovo1367 GII1.1_529 AJ430774, delta proteobacterium EbS7, sediment ARB_A61B58E9, denovo3408 GII2.1_14147 FJ437866, uncultured bacterium, Green Lake at 25 m water depth ARB_A26C8AD9, denovo3152 GII2.1_5152 HQ003580, uncultured delta proteobacterium, Carrizo shallow lake HQ691995, uncultured delta proteobacterium, stratified lagoon

JQ580482, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil uncultured ARB_39E47D34, denovo2286 GI1.1_833 Hm598151, uncultured bacterium, 1400 m depth surface sediment Xisha Trough, China Sea ARB_F317CBC0, denovo1489 GII3.1_3131 ARB_B01D0B7D, denovo988 GI3.1_3020 JF495321, uncultured bacterium, sediment from anoxic fjord AF154102, uncultured hydrocarbon seep bacterium GCA017 JQ580472, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_5B4D5DA9, denovo2879 GI1.1_2108 AY542227, uncultured delta proteobacterium, Gulf of Mexico seaﬂoor sediments JQ580206, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_56A14516, denovo843 GII2.1_2149 ARB_56A14516, denovo558 GI2.1_1507 Jn534265, uncultured organism, Guerrero Negro Hypersaline Mat Jf344192, uncultured delta proteobacterium, petroleum spot over marine sediments ARB_85297555, denovo2583 GI2.1_230 Jn515097, uncultured organism, Guerrero Negro Hypersaline Mat FJ484510, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 53m depth ARB_EA0946DA, denovo2630 GII2.1_2303 JQ817357, uncultured bacterium, subseaﬂoor sediment at the Formosa Ridge

JQ925098, uncultured bacterium, cold seep sediment from oxygen mimimum zone in Pakistan Margin Desulfarculales_Desulfarculaceae ARB_170270B2, denovo244 GII1.1_367 HQ588498, uncultured bacterium, Amsterdam mud volcano sediment JN977161, uncultured bacterium, Jiaozhao Bay sediment HM231166, uncultured bacterium, coconut husk retting soil EU592498, uncultured bacterium, hypersaline sediment HQ174924, uncultured bacterium, Cherokee Road Extension Blue Hole JQ816148, uncultured bacterium, subseafloor sediment at the Deep Basin AM745154, uncultured delta proteobacterium, marine sediments JQ580310, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_68DB4272, denovo228 GII2.1_2567 Jn518931, uncultured organism, Guerrero Negro Hypersaline Mat FJ437756, uncultured bacterium, Green Lake chemocline at 20.5 m water depth AB630766, uncultured bacterium, aquatic moss pillars FJ716322, uncultured bacterium, Sawmill Sink water column, at 10.3 m water depth ARB_9AE7AD4E, denovo2234 GI1.1_2318 ARB_364C0C47, denovo3678 GII1.1_6861 ARB_5D22E99, denovo730 GI1.1_3588 AJ237601, Desulfobacterium anilini DQ394914, uncultured Desulfobacterium sp., harbor sediment AF121886, bacterium 2BP−6 Ab763347, Desulfobacterium sp. DS, a river sediment contaminated chlorinated volatile organic compounds GQ354966, uncultured delta proteobacterium, spring FJ517129, uncultured Desulfobacteraceae bacterium, water FJ516988, uncultured Desulfobacteraceae bacterium, upper sediment HM066266, uncultured bacterium, Texas state well #DX 68−23−616A JQ245553, uncultured bacterium, mud volcano EU245563, uncultured organism, hypersaline microbial mat Jn497298, uncultured organism, Guerrero Negro Hypersaline Mat ARB_1537C093, denovo32 GII3.1_1946 Jn529954, uncultured organism, Guerrero Negro Hypersaline Mat ARB_9B500F68, denovo614 GII3.1_2698 FR682646, uncultured delta proteobacterium, hydrothermal sediments FJ485020, uncultured delta proteobacterium, biomat in El Zacaton at 114m depth FJ485340, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 273m depth Jn532040, uncultured organism, Guerrero Negro Hypersaline Mat ARB_E828CF31, denovo3306 GII3.1_6873 FM164951, uncultured Desulfobacterium sp., hot spring AF026998, unidentified delta proteobacterium OPB16 EF205578, uncultured delta proteobacterium, geothermal spring mat FR682638, uncultured delta proteobacterium, hydrothermal sediments DQ415831, uncultured bacterium, Frasassi sulfidic cave stream biofilm JN397733, uncultured bacterium, river bank ARB_9F80C0F0, denovo460 GII2.1_6145 Desulfarculus AJ576343, uncultured bacterium, hindgut homogenate of Pachnoda ephippiata larva ARB_2EB6DECF, denovo3036 GII2.1_284 ARB_2EB6DECF, denovo38 GI2.1_214 ARB_986F247C, denovo2054 GII3.1_553 EU487879, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed ARB_783FDF21, denovo1576 GII3.1_1060 uncultured FM242399, uncultured delta proteobacterium, sediment ARB_FA468FAA, denovo730 GII3.1_1182 KF697533, uncultured bacterium, activated sludge from inclined plate membrane bioreactor 0.05 ARB_740BDBE3, denovo1219 GI1.1_1259

Figure S3: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Deltaproteobacteria, order: Desulfarculales (black bold: sequences retrieved in this study and closest relatives). 134 Supplementary Material

133 sequences (seq), uncultured bacteria, including 8 seq obtained by Pfeffer et al., 2012, and Lake Grevelingen surface sediments, August, station 3 (3 seq), Lake Grevelingen surface sediments, August, station 1 (1 seq)

85 seq, uncultured bacteria related to Desulforhopalus sp., Lake Grevelingen surface sediments, March and August, station 1 (2 seq), Lake Grevelingen surface sediments, March and August, station 2 (2 seq) Lake Grevelingen surface sediments, August, station 3 (4 seq) 9 seq, uncultured bacteria, including Lake Grevelingen surface sediments, August, station 3 (2 seq)

12 seq, uncultured bacteria, including Lake Grevelingen surface sediments, August, station 3 (2 seq) Am176855, uncultured bacterium, mangrove sediment 131 seq, uncultured Desulfopila sp., including Lake Grevelingen surface sediments, March, station 1 (1 seq), Lake Grevelingen surface sediments, August, station 2 (1 seq), Lake Grevelingen surface sediments, August, station 3 (2 seq) 30 seq, uncultured bacteria related to Desulfotalea sp., including Lake Grevelingen surface sediments, March, station 1 (1 seq), Lake Grevelingen surface sediments, August, station 3 (1 seq), 43 seq, uncultured bacteria (SEEP−SRB4), including Lake Grevelingen surface sediments, March and August, station 2 (2 seq),

2 seq, uncultured bacteria, sediments from Gulf of Mexico and Peru Margin 59 seq, uncultured bacteria, including Lake Grevelingen surface sediments, March, station 1 (1 seq) and 3 (2 seq), Lake Grevelingen surface sediments, August, station 2 (5 seq)

35 seq, uncultured bacteria related to Desulfofustis sp.

2 seq, uncultured bacteria

273 seq, uncultured bacteria related to Desulfocapsa sp. including Lake Grevelingen surface sediments, March, station 1 (1 seq) and 2 (2 seq), Lake Grevelingen surface sediments, August, station 2 (2 seq) and 3 (1 seq),

2 seq, uncultured bacteria, microbial mat and muddy salt marsh sediment

70 seq, uncultured bacteria related to Desulfocapsa sp., including Lake Grevelingen surface sediments, March, station 1 (1 seq) and 2 (1 seq), Lake Grevelingen surface sediments, August, station 1 (1 seq)

14 seq, uncultured bacteria, including Lake Grevelingen surface sediments, August, station 2 (1 seq)

16 seq, uncultured bacteria, subsurface aquifer sediment and volcanic soil Jx223964, uncultured bacterium, subsurface aquifer sediment

30 seq, uncultured bacteria, including 1 seq obtained by Pfeffer et al., 2012, Desulfobacterales_Desulfobulbaceae Lake Grevelingen surface sediments, August, station 2 (1 seq) and station 3 (4 seq)

5 seq, uncultured bacteria, including Lake Grevelingen surface sediments, March and August, station 1 (2 seq)

2 seq, uncultured bacteria, subsurface aquifer sediments 6 seq, uncultured bacteria, including Lake Grevelingen surface sediments, March, station 1 (1 seq) and station 2 (1 seq), and August, station 2 (1 seq)

478 seq, uncultured bacteria related to Desulfobulbus sp. (see Desulfobulbus tree; following ﬁgure)

44 seq, uncultured bacteria related to Desulfurivibrio sp.

42 seq, uncultured bacteria, including 2 seq obtained by Malkin et al., 2014, 1 seq by Pfeffer et al., 2012, Lake Grevelingen surface sediments, March, station 1 (2 seq) and station 3 (2 seq), and August, station 2 (2 seq) and station 3 (2 seq) 7 seq, uncultured bacteria, including 5 seq obtained by Pfeffer et al., 2012

2 seq, uncultured bacterium, marine sediment (1 seq) and Lake Grevelingen surface sediments, August, station 3 (1 seq) 0.10

Figure S4a: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Deltaproteobacteria, order: Desulfobacterales, family: Desulfobulbaceae (black bold: sequences retrieved in this study and closest relatives). 135 Chapter 5

group 1: 18 sequences uncultured bacteria

group 2: 7 sequences uncultured bacteria

group 3: 3 sequences uncultured bacteria

group 4: 24 sequences uncultured bacteria

Dq676284, uncultured delta proteobacterium, suboxic freshwater−pond sediment Cp002364, Desulfobulbus propionicus DSM 2032, freshwater mud Ay548789, Desulfobulbus propionicus Cp002364, Desulfobulbus propionicus DSM 2032, freshwater mud Ay160859, uncultured bacterium, Cubitermes orthognathus Ab189697, uncultured bacterium, Termes comis Af482433, uncultured bacterium, granular sludge X95180, Desulfobulbus elongatus Dq831531, uncultured Desulfobulbus sp., brackish sediment Jq815615, uncultured Desulfobulbus sp., Tinto River sediment (extreme acid environment) KF020725, Desulfomicrobium sp. enrichment culture clone LDC−, soil Gq133652, uncultured bacterium, ASBR reactor treating swine waste Eu104773, uncultured delta proteobacterium, anaerobic biofilm reactor Gq138460, uncultured bacterium, ASBR reactor treating swine waste Gq138956, uncultured bacterium, ASBR reactor treating swine waste KC260892, uncultured bacterium, bottlenose dolphin mouth Eu488160, uncultured bacterium, siliciclastic sediment from Thalassia sea grass bed Hm069062, uncultured bacterium, sediment of Rupa Lake Ab546247, Desulfobulbus rhabdoformis, sludge sample of crude−oil storage tank U12253, Desulfobulbus rhabdoformis Ef442993, Desulfobulbus sp. DSM 2033 Jn688053, Desulfobulbus sp. S4, microbial consortium enriched from mangrove soil HM750216, Desulfobulbus alkaliphilus AJ866934, Desulfobulbus mediterraneus, tidal flat sediment EU142055, uncultured bacterium, methane seep sediment AF354663, Desulfobulbus mediterraneus AUCW01000075, Desulfobulbus mediterraneus DSM 13871 Eu528183, uncultured bacterium, sediment AF099055, psychrophilic sulfate−reducing bacterium LSv55 AM404380, uncultured delta proteobacterium, marine sediment Fj716980, uncultured bacterium, marine sediment from Cullercoats, Northumberland, United Kingdom Am882629, uncultured delta proteobacterium, sediment from oil polluted water from petrochemical treatment plant Ab110550, Desulfobulbus japonicus, harbor sediment in Japan AB110549, Desulfobulbus japonicus, harbor sediment in Japan U85473, Desulfobulbus sp. BG25 JQ209390, uncultured bacterium, bottlenose dolphin mouth JQ211736, uncultured bacterium, bottlenose dolphin mouth JQ215032, uncultured bacterium, bottlenose dolphin mouth Gq134058, uncultured bacterium, ASBR reactor treating swine waste AB243815, uncultured bacterium, Niigata oil well FJ792164, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field Fr853023, uncultured bacterium, active hydrothermal chimney, Juan de Fuca Ridge Aj969450, uncultured delta proteobacterium, rock fragments, Rainbow, deep sea hydrothermal vent field Fr852968, uncultured bacterium, active hydrothermal chimney, Dudley, Juan de Fuca Ridge Fr853007, uncultured bacterium, active hydrothermal chimney, Dudley, Juan de Fuca Ridge Ay672535, uncultured bacterium, hydrothermal vent, East Pacific Rise, Pacific Ocean Ay672502, uncultured bacterium, hydrothermal vent, East Pacific Rise, Pacific Ocean AM404330, uncultured delta proteobacterium, marine sediment AF420336, uncultured proteobacterium Ay592579, uncultured bacterium, Napoli mud volcano, Eastern Mediterranean, sediment layer 0−8 cm GU584659, uncultured bacterium, marine hydrocarbon seep sediment JQ287080, uncultured bacterium, East Pacific Rise Fj5746, uncultured bacterium, iron oxide sediments, Tonga Arc EU555141, uncultured bacterium, Dudley hydrothermal vent Lake Grevelingen surface sediments, March, station 3 AM268767, uncultured prokaryote, hot fluid vent, site Irina II group 5: 6 sequences uncultured bacteria Jn874112, uncultured bacterium, TrapR1, East Pacific Rise AY327886, uncultured delta proteobacterium, surface of vent snail foot Jn873947, uncultured bacterium, TrapR1, East Pacific Rise Fr852967, uncultured bacterium, active hydrothermal chimney, Dudley, Juan de Fuca Ridge group 6: 41 seq, mainly uncultured bacteria and 2 seq obtained by Pfeffer et al., 2012 (JX091042.2; JX091026.1)

Ay531563, uncultured bacterium, Indian Ocean hydrothermal vent AY531586, uncultured bacterium, Indian Ocean hydrothermal vent Kc682614, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin Lake Grevelingen surface sediments, August, station 3 Lake Grevelingen surface sediments, August, station 3 Lake Grevelingen surface sediments, August, station 3 JX224538, uncultured bacterium, subsurface aquifer sediment JX225752, uncultured bacterium, subsurface aquifer sediment JX225113, uncultured bacterium, subsurface aquifer sediment Lake Grevelingen surface sediments, March, station 3 Lake Grevelingen surface sediments, August, station 2 Lake Grevelingen surface sediments, March, station 1 KF624269, uncultured bacterium, anoxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea Lake Grevelingen surface sediments, March, station 1 HM992531, uncultured Desulfobacteraceae bacterium, oil sands tailings settling basin AB525452, uncultured bacterium, deep−sea methane seep sediment off Joetsu, Japan Sea Fn554116, uncultured sediment bacterium, Logatchev hydrothermal vent field,Anya’s Garden

Jn662305, uncultured delta proteobacterium, particulate detritus, c tubeworm Ridgeia piscesae Desulfobulbus Lake Grevelingen surface sediments, March, station 2 Lake Grevelingen surface sediments, August, station 3 HQ588389, uncultured bacterium, Amsterdam mud volcano sediment Hq153922, uncultured bacterium, white microbial film on pebble substrate in the aphotic zone of a shallow hydrothermal vent group 7: 5 sequences uncultured bacteria, carbonate chimney in Lost City hydrothermal vent Hq153967, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal vent KC682422, uncultured bacterium, substrate mineral chips JF738104, uncultured bacterium, Lau Basin hydrothermal sulfide chimney FR852988, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca Ridge group 8: 40 seq; including 17 seq obtained by Schauer et al., 2014; 11 seq by Pfeffer et al. 2012; 7 seq by Malkin et al., 2014; 4 seq uncultured bacteria obtained from marine sediment JF268391, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae, station 309; SO191_3_309 Gu302481, uncultured bacterium, marine sediments (0−24 m sediment depth) from Mississippi Canyon 118, Gulf of Mexico GU208270, uncultured prokaryote, Dongping Lake sediment FQ658831, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs group 9 : 59 sequences, including Lake Grevelingen surface sediments, i.e. 3 seq station 1, March; 1 seq station 1, August; 1 seq station 2, March; 2 seq station 2, August; 2 seq station 3, March; 3 seq station 3, August FJ264588, uncultured bacterium, methane seep sediment FJ712577, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea FJ264787, uncultured bacterium, methane seep sediment GU180162, uncultured bacterium, sediment and soil slurry HQ153843, uncultured bacterium, white microbial film on pebble substrate in the aphotic zone of a shallow hydrothermal vent, Volcano 1, South Tonga Arc at a depth of 189.1 m group 10: 9 seq, uncultured bacteria, marine sediment FJ358873, uncultured delta proteobacterium, marine reef sandy sediment FR744613, uncultured bacterium, production water from the Halfdan oil field Aj535237, uncultured delta proteobacterium, marine sediment above hydrate ridge Lake Grevelingen surface sediments, August, station 2 JN256008, uncultured delta proteobacterium, surface of pereopod of new species of Yeti crab from mound 12 JN662199, uncultured delta proteobacterium, particulate detritus collected from grabs of the vestimentiferan tubeworm Ridgeia piscesae in low−flow environment AY355303, uncultured bacterium, epibiontic

group 11: 113 seq, including Lake Grevelingen surface sediments, i.e. 7 seq station 1, March; 6 seq station 2, March; 8 seq station 2, August; 1 seq station 3, March; 11 seq station 3, August

FJ813526, uncultured bacterium, marine sediment Lake Grevelingen surface sediments, August, station 2 KF596661, uncultured bacterium, soil FM179887, uncultured delta proteobacterium, marine sediments AY771956, uncultured delta proteobacterium, marine surface sediment HQ588373, uncultured bacterium, Amsterdam mud volcano sediment Lake Grevelingen surface sediments, March, station 1 Lake Grevelingen surface sediments, August, station 2 JN977397, uncultured bacterium, Jiaozhao Bay sediment DQ831546, uncultured delta proteobacterium, marine sediment DQ831536, uncultured delta proteobacterium, freshwater sediment Lake Grevelingen surface sediments, August, station 3 Lake Grevelingen surface sediments, March, station 2 Lake Grevelingen surface sediments, August, station 2 Lake Grevelingen surface sediments, March, station 1 HQ857627, uncultured delta proteobacterium, hydrocarbon contaminated saline alkaline soils JN860370, uncultured Desulfobulbus sp., low temperature hydrothermal oxides at the South West Indian Ridge AB722257, uncultured bacterium, freshwater iron−rich microbial mat AB754135, uncultured bacterium, lake water HM141864, uncultured bacterium, in situ samplers incubated in the Mahomet aquifer JX434192, uncultured bacterium, gold mine borehole JX434246, uncultured bacterium, gold mine borehole AB188785, uncultured Desulfobulbus sp., cold seep sediment JF344301, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach Lake Grevelingen surface sediments, August, station 3 Lake Grevelingen surface sediments, August, station 1 GQ246446, uncultured bacterium, North Yellow Sea sediments Lake Grevelingen surface sediments, March, station 2 JN977170, uncultured bacterium, Jiaozhao Bay sediment JN977290, uncultured bacterium, Jiaozhao Bay sediment Lake Grevelingen surface sediments, August, station 2 KC682706, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau Basin JQ287075, uncultured bacterium, East Pacific Rise KC682691, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau Basin KC470997, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough Lake Grevelingen surface sediments, August, station 3 Lake Grevelingen surface sediments, March, station 3 Lake Grevelingen surface sediments, August, station 3 AM882608, uncultured delta proteobacterium, sediment from oil polluted water from petrochemical treatment plant Lake Grevelingen surface sediments, March, station 3 Lake Grevelingen surface sediments, March, station 1 Lake Grevelingen surface sediments, August, station 3 DQ833475, uncultured bacterium, sediment of Guanting Reservoir AB722237, uncultured bacterium, freshwater iron−rich microbial mat AB754082, uncultured bacterium, lake water 0.1 AB240495, uncultured bacterium, PCR−derived sequence from root−tip (0 to 40 mm) of Phragmites at Sosei River in Sappro, Japan group 12: 9 seq, uncultured bacteria, marine sediment, hydrothermal vents

Figure S4b: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Deltaproteobacteria, order: Desulfobacterales, family: Desulfubulbaceae, genus: Desulfubulbus (black bold: sequences retrieved in this study and closest relatives). 136 Supplementary Material

Jn493110, uncultured organism, Guerrero Negro Hypersaline Mat Jn509712, uncultured organism, Guerrero Negro Hypersaline Mat FJ813564, uncultured bacterium, marine sediment Jn533073, uncultured organism, Guerrero Negro Hypersaline Mat Jq580317, uncultured delta proteobacterium, sediments from Rodas Beach crude oil Jf344658, uncultured delta proteobacterium, hydrocarbon polluted marine sediments Kc471241, uncultured bacterium, marine sediment Okinawa Trough ARB_AB025D00, denovo2174 GII3.1_2112 ARB_7212B3B6, denovo1556 GII2.1_787 FJ517135, uncultured Desulfobacteraceae bacterium, water AY771938, uncultured delta proteobacterium, marine surface sediment Jf344433, uncultured delta proteobacterium, hydrocarbon polluted marine sediments Jf344655, uncultured delta proteobacterium, hydrocarbon polluted marine sediments DQ811834, uncultured delta proteobacterium, mangrove soil Am882597, uncultured delta proteobacterium, sediment from oil polluted water DQ811835, uncultured delta proteobacterium, mangrove soil Gu302441, uncultured bacterium, marine sediments Mississippi Canyon FJ873366, uncultured bacterium, sediments from the Okhotsk Sea Jf344367, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_2B982B23, denovo78 GII3.1_1891 Jf344621, uncultured delta proteobacterium, hydrocarbon polluted marine sediments EU488132, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed Fn396669, uncultured marine bacterium, Arctic marine surface sediment EU385712, uncultured bacterium, subseafloor sediment of the South China Sea KF741562, uncultured bacterium, Talbert salt marsh sediment Ab177130, uncultured bacterium, ethane hydrate bearing subseafloor sediment at the Peru margin Jf344336, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_8376DD2A, denovo2689 GII2.1_12013 AB250573, uncultured bacterium, microbial mat FN820322, uncultured bacterium, marine sediment, mud volcano GQ259292, uncultured bacterium, deep sediment JN977360, uncultured bacterium, Jiaozhao Bay sediment ARB_9B5D30FB, denovo2586 GII3.1_7180 GQ357013, uncultured bacterium, methane seep sediment Jq580293, uncultured delta proteobacterium, sediments Rodas Beach with crude oil ARB_609A165E, denovo1706 GII3.1_4850 DQ394998, uncultured delta proteobacterium, harbor sediment ARB_276A6BD5, denovo3922 GII3.1_9884 JQ586318, uncultured bacterium, arctic marine sediment EU181465, uncultured bacterium, marine sediments FN600637, Olavius sp. associated proteobacterium Delta 1 GU982811, uncultured bacterium, marine sediment from the Western Pacific Ocean Jf344583, uncultured delta proteobacterium, hydrocarbon polluted marine sediments JX138851, uncultured delta proteobacterium, marine sediments ARB_E4F47108, denovo2691 GI3.1_2447 ARB_A42CEBFC, denovo210 GI2.1_484 DQ831553, uncultured Desulfosarcina sp., marine sediment JQ817421, uncultured bacterium, subseafloor sediment at the Formosa Ridge ARB_3BDC7AF5, denovo1926 GI3.1_5119 JF495316, uncultured bacterium, sediment from anoxic fjord JQ579984, uncultured delta proteobacterium, sediments from Figueiras Beach ARB_CA3EC558, denovo365 GII2.1_11472 FJ264667, uncultured bacterium, methane seep sediment GU553724, uncultured bacterium, subseafloor sediment at the Yung−An Ridge ARB_E6ACD753, denovo1584 GII3.1_4528 ARB_D98560D6, denovo3652 GII2.1_1870 AY222311, uncultured delta proteobacterium, host hindgut caecum JN469616, uncultured organism, Guerrero Negro Hypersaline Mat Am882638, uncultured delta proteobacterium, sediment from oil polluted water Jn495515, uncultured organism, Guerrero Negro Hypersaline Mat AXXK01000236, delta proteobacterium PSCGC 5451 Fj416106, uncultured bacterium, sediment fNorthern Bering Sea ARB_AFCDBB4E, denovo2464 GI1.1_733 ARB_F2527D65, denovo2119 GII3.1_5230 EU925915, uncultured bacterium, sediment from station DBS1, northern Bering Sea EU287209, uncultured bacterium, arctic surface sediment ARB_527A343A, denovo125 GII3.1_1095 ARB_ACA31ABA, denovo1320 GI1.1_4519 ARB_CFF4FC25, denovo2734 GII3.1_1621 AY771936, uncultured delta proteobacterium, marine surface sediment ARB_5666EC06, denovo2457 GII3.1_1313 ARB_FC6CBA6, denovo2741 GI1.1_105 ARB_35A5F4CB, denovo3527 GII3.1_3458 ARB_7F8C1CB7, denovo3949 GII2.1_7114 ARB_60341410, denovo2446 GII2.1_510 ARB_47DE09C, denovo2094 GII3.1_9138 ARB_7E58A22C, denovo1560 GI2.1_4724 DQ811820, uncultured delta proteobacterium, mangrove soil Jf344664, uncultured delta proteobacterium, hydrocarbon polluted marine sediments FN396758, uncultured marine bacterium, Arctic marine surface sediment DQ395018, uncultured delta proteobacterium, harbor sediment KF624243, uncultured bacterium, suboxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea AASZ01000534, metagenome, gutless worms collected in the Mediterranean Sea ARB_DECA4E83, denovo514 GI1.1_1612 AJ620511, Olavius crassitunicatus delta−proteobacterial endo, marine sediment ARB_21531FCD, denovo1023 GI1.1_2208 Jq580141, uncultured delta proteobacterium, sediments from Rodas Beach crude oil HM245653, uncultured bacterium, pockmark sediments FJ786116, uncultured bacterium, prawn farm sediment DQ811797, uncultured delta proteobacterium, mangrove soil ARB_64DE2518, denovo1514 GI1.1_1793 ARB_5498C7B, denovo1552 GI2.1_1268 JQ586291, uncultured bacterium, arctic marine sediment ARB_F96C7440, denovo3157 GII2.1_2571 ARB_2308CAA0, denovo1932 GI1.1_3278 JF344653, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_92BF177B, denovo3292 GII3.1_5475 FJ716454, uncultured bacterium, Frasassi cave system, anoxic lake water ARB_8199C09B, denovo1844 GII3.1_1277 JF344629, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach Jf344447, uncultured delta proteobacterium, hydrocarbon polluted marine sediments EU266854, uncultured delta proteobacterium, tar−oil contaminated aquifer sediments ARB_21640F45, denovo2946 GII2.1_7360 AM882620, uncultured delta proteobacterium, sediment from oil polluted water from petrochemical treatment plant ARB_B959CA3E, denovo1101 GI3.1_326 ARB_89F1B619, denovo3034 GII3.1_5660 AXXL01000032, delta proteobacterium PSCGC 5342 Jn533825, uncultured organism, Guerrero Negro Hypersaline Mat KC470928, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough ARB_C183B8DF, denovo1811 GII3.1_3650 Jf344436, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_F53E48CB, denovo1126 GI3.1_3827 ARB_2375B3D7, denovo2041 GII2.1_1621 ARB_F53E48CB, denovo2039 GII1.1_3417 ARB_2375B3D7, denovo2116 GI1.1_1921 KF741416, uncultured bacterium, Talbert salt marsh sediment FM242225, uncultured delta proteobacterium, sediment ARB_BC7F083C, denovo345 GI2.1_712 ARB_DCA38B18, denovo2024 GII2.1_3527 KC358194, uncultured bacterium, large−discharge carbonate springs AM040123, uncultured delta proteobacterium, sandy sediments HQ691983, uncultured delta proteobacterium, stratified lagoon ARB_BAC5426A, denovo3444 GII2.1_5360 AM404371, uncultured delta proteobacterium, marine sediment Jn495286, uncultured organism, Guerrero Negro Hypersaline Mat JQ580124, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil Jf344372, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_FBF16789, denovo2108 GII3.1_2264 ARB_70856E3C, denovo2194 GI2.1_783 ARB_FBF16789, denovo2361 GI2.1_1158 Jf344690, uncultured delta proteobacterium, hydrocarbon polluted marine sediments EU048693, uncultured bacterium, marine sediment, South Slope, South China Sea FN396636, uncultured marine bacterium, Arctic marine surface sediment ARB_49159E95, denovo2425 GII3.1_9745 Jf344696, uncultured delta proteobacterium, hydrocarbon polluted marine sediments GQ261770, uncultured delta proteobacterium, deep sea sediment associated with whale falls ARB_8ADD6B04, denovo2164 GII3.1_4296 ARB_44DC591A, denovo2386 GI2.1_2938 SEEP−SRB1 ARB_35BFAC0E, denovo1701 GI2.1_3256 ARB_857E05F1, denovo1899 GII2.1_12697 GQ472418, uncultured bacterium, lake sediment EU652612, uncultured bacterium, Yellow Sea sediment FJ516927, uncultured Desulfobacteraceae bacterium, upper sediment GQ348508, uncultured delta proteobacterium, Saanich Inlet, 200 m depth FJ716475, uncultured bacterium, Frasassi cave system, anoxic lake water EU386062, uncultured bacterium, subseafloor sediment of the South China Sea GU208253, uncultured prokaryote, Dongping Lake sediment Jf344630, uncultured delta proteobacterium, hydrocarbon polluted marine sediments GU208215, uncultured prokaryote, Dongping Lake sediment FJ517136, uncultured Desulfobacteraceae bacterium, water Fj485545, uncultured delta proteobacterium, wall biomat sample in El Zacaton ARB_AF14643E, denovo783 GII1.1_4238 AJ620510, Olavius crassitunicatus delta−proteobacterial endo, marine sediment ARB_88ACEA80, denovo2073 GI3.1_2120 JQ712425, uncultured delta proteobacterium, hydrothermal vent fluids ARB_24074B89, denovo2258 GII3.1_4875 ARB_2FDA25E1, denovo2589 GII3.1_649 EU488487, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed ARB_923AE546, denovo3737 GII2.1_1274 DQ811826, uncultured delta proteobacterium, mangrove soil ARB_5F670FDF, denovo3450 GII2.1_2063 Jn506728, uncultured organism, Guerrero Negro Hypersaline Mat Fm165241, uncultured bacterium, tubeworm Lamellibrachia sp. from cold seeps JN512076, uncultured organism, Guerrero Negro Hypersaline Mat ARB_B59ABBF4, denovo2404 GII2.1_6581 Jn535830, uncultured organism, Guerrero Negro Hypersaline Mat ARB_BBF73459, denovo2912 GI1.1_3098 ARB_C0585716, denovo1150 GII2.1_2398 ARB_4DE6ABCD, denovo560 GII3.1_3361 ARB_6DECB96F, denovo1068 GII2.1_4639 EF125388, uncultured bacterium, naked tidal flat sediment near mangrove FJ746161, uncultured bacterium, ocean sediment, 5306 m water depth, during Cruise Knox02rr JF428822, uncultured delta proteobacterium, zero water exchange shrimp pond sediment AB858610, uncultured bacterium, subseafloor massive sulfide deposit GQ246372, uncultured bacterium, North Yellow Sea sediments ARB_11D292FD, denovo839 GII1.1_186 Jf344682, uncultured delta proteobacterium, hydrocarbon polluted marine sediments Jn449287, uncultured organism, Guerrero Negro Hypersaline Mat ARB_8BA374D8, denovo1060 GII2.1_1391 Jn461602, uncultured organism, Guerrero Negro Hypersaline Mat ARB_8BA374D8, denovo1625 GI1.1_2788 ARB_BC1B7B7C, denovo2903 GII1.1_4184 EF999398, uncultured bacterium, Pearl River Estuary sediments at 50cm depth ARB_DE50BAE, denovo2728 GII2.1_7574 ARB_17225923, denovo35 GI1.1_4513 ARB_E97A75AA, denovo3575 GII3.1_6200 JX221943, uncultured bacterium, subsurface aquifer sediment JN672650, uncultured bacterium, surface layer sediment of the East China sea JX225840, uncultured bacterium, subsurface aquifer sediment ARB_8D6E9E8D, denovo264 GII2.1_2368 ARB_7896FCD9, denovo3335 GII3.1_131 EU246034, uncultured organism, hypersaline microbial mat HQ697836, uncultured bacterium, hydrocarbon contaminated saline−alkali soil Desulfonatronobacter AJ620501, Olavius ilvae Delta 3 endosymbiont, marine sediment JX240710, uncultured delta proteobacterium, coastal soil JQ580056, uncultured delta proteobacterium, sediments from Figueiras Beach GU289732, Desulfonatronobacter acidivorans, soda lake ARB_3CB8B01, denovo822 GII2.1_5065 Jf268373, uncultured bacterium, Hikurangi margin AM493254, Olavius algarvensis associated proteobacterium Del, marine sediment AJ704684, uncultured delta proteobacterium, marine sediment ARB_3A6149F0, denovo438 GI1.1_1942 ARB_242A7D9D, denovo1494 GII1.1_2254 AB188777, uncultured delta proteobacterium, cold seep sediment ARB_F85668AB, denovo305 GII3.1_161 ARB_53E34389, denovo597 GI2.1_641 ARB_222F3CA4, denovo584 GII3.1_2561 ARB_BEC97052, denovo2382 GI2.1_1911 ARB_3E5AFB8D, denovo1509 GII3.1_3622 ARB_5769CAF9, denovo1696 GII2.1_8379 ARB_3367F4DF, denovo977 GII3.1_2082 Fr853018, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge ARB_242A7D9D, denovo2742 GI1.1_1973 Fn553934, uncultured sediment bacterium, Logatchev hydrothermal vent field ARB_5F9B7D1E, denovo1873 GII3.1_5804 FJ535333, uncultured bacterium, sediment ARB_46062F0A, denovo791 GI3.1_1456 ARB_7EEB8DA1, denovo1999 GI2.1_157 ARB_8C59A6BA, denovo1742 GII3.1_2529 ARB_BD08D4DA, denovo2785 GII2.1_4055 GU291339, uncultured bacterium, acid mine drainage contaminated salt marsh sediments ARB_7171ABDD, denovo2495 GI3.1_1328 FJ497421, uncultured delta proteobacterium, Vailulu’u Seamount AM889193, uncultured delta proteobacterium, Sediments ARB_F6791D49, denovo1990 GII3.1_998 Jn860325, uncultured Desulfobacteraceae bacterium, low temperature hydrothermal oxides South West Indian Ridge DQ394951, uncultured delta proteobacterium, harbor sediment AJ535249, uncultured delta proteobacterium, marine sediment above hydrate ridge Hq405625, bacterium enrichment culture clone AOM−SR−B8, enrichment anaerobic oxidation of methane ARB_F2B93C6B, denovo3181 GII3.1_3701 AM176871, uncultured bacterium, mangrove sediment ARB_742457D2, denovo3235 GII3.1_3463 GQ259270, uncultured bacterium, deep sediment Gu302438, uncultured bacterium, marine sediments Mississippi Canyon AJ704683, uncultured delta proteobacterium, marine sediment ARB_EC6D159F, denovo3009 GII2.1_4940 ARB_579A7566, denovo2160 GI2.1_3055 ARB_86E2CFD9, denovo1535 GI2.1_196 ARB_42D72CEA, denovo486 GI2.1_275 HQ588558, uncultured bacterium, Amsterdam mud volcano sediment Fn554099, uncultured sediment bacterium, Logatchev hydrothermal vent FN820295, uncultured bacterium, marine sediment, mud volcano HQ691980, uncultured delta proteobacterium, stratified lagoon Fn421323, uncultured delta proteobacterium, marine sediments ARB_B5B2E1EF, denovo1135 GI2.1_2083 ARB_EC6B3962, denovo1757 GII3.1_527 ARB_42D72CEA, denovo1053 GII1.1_751 ARB_1132C70D, denovo666 GII3.1_2969 HM141895, uncultured bacterium, in situ samplers incubated in the Mahomet aquifer JF344558, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_3B3150E, denovo2691 GII3.1_3664 FJ712476, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea HQ174942, uncultured bacterium, Cherokee Road Extension Blue Hole JQ036271, uncultured bacterium, Hydrate Ridge carbonate 2518 ARB_70290A1B, denovo94 GI2.1_1300 JF344483, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_4B1EF6D, denovo1731 GI2.1_342 HQ588578, uncultured bacterium, Amsterdam mud volcano sediment ARB_DBAFDA21, denovo2860 GII2.1_5120 ARB_47DF84C1, denovo133 GI2.1_1635 ARB_A6EACD9, denovo1419 GII3.1_8756 ARB_47DF84C1, denovo1667 GII3.1_7440 ARB_128F1521, denovo1842 GII2.1_12592 JF344359, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach FM242223, uncultured delta proteobacterium, sediment HQ003583, uncultured Desulfobacteraceae bacterium, Carrizo shallow lake Am882554, uncultured gamma proteobacterium, sediment from oil polluted water JQ816993, uncultured bacterium, subseafloor sediment at the Good Weather Ridge ARB_E2F92A82, denovo2276 GI1.1_1174 FJ716406, uncultured bacterium, Frasassi cave system, anoxic lake water Am882618, uncultured delta proteobacterium, sediment from oil polluted water EU385687, uncultured bacterium, subseafloor sediment of the South China Sea ARB_61BA32E3, denovo2873 GI3.1_134 Jn474717, uncultured organism, Guerrero Negro Hypersaline Mat ARB_39A85234, denovo716 GII3.1_1509 ARB_FCD1073C, denovo1850 GII3.1_2677 ARB_E2B4FFB0, denovo287 GII2.1_10006 DQ154853, uncultured bacterium, hypersaline microbial mat Am882636, uncultured delta proteobacterium, sediment from oil polluted water HM141837, uncultured bacterium, in situ samplers incubated in the Mahomet aquifer ARB_768D549B, denovo2723 GII3.1_9116 JQ580445, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_ED8C662E, denovo3475 GII2.1_540 ARB_C2FCF446, denovo1290 GII2.1_8359 ARB_F56DA353, denovo3774 GII2.1_8690 ARB_DFC45A49, denovo1961 GI3.1_4202 ARB_942E6C15, denovo717 GII3.1_5336 AJ937690, uncultured bacterium, mud from a terrestrial volcano DQ394899, uncultured delta proteobacterium, harbor sediment Hq622295, bacterium enrichment culture clone Oil_45, polluted estuarine sediment Palestine ARB_1C79E7C1, denovo123 GII3.1_4596 Cp000859, Desulfococcus oleovorans Hxd3

ARB_97748389, denovo525 GI2.1_2980 uncultured FJ712452, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea ARB_87BD5B07, denovo2143 GII3.1_1826 ARB_DE12A1A0, denovo106 GII3.1_8455 EU542429, uncultured bacterium, sediment and soil slurry ARB_8A60CE22, denovo2792 GI2.1_115 HQ190518, uncultured bacterium, Zhongyuan oil ﬁeld ARB_9DAF10FF, denovo1830 GI2.1_2003 Am882592, uncultured delta proteobacterium, sediment from oil polluted water Jn427089, uncultured organism, Guerrero Negro Hypersaline Mat Jn539400, uncultured organism, Guerrero Negro Hypersaline Mat Jn513553, uncultured organism, Guerrero Negro Hypersaline Mat ARB_40933119, denovo1876 GI1.1_500 ARB_EE004B84, denovo1007 GII1.1_6352 ARB_40933119, denovo411 GII1.1_601 ARB_B4C116D9, denovo2961 GII1.1_74 AB530178, uncultured bacterium, marine sediment Ay592356, uncultured bacterium, Amsterdam mud volcano, Eastern Mediterranean Am882593, uncultured delta proteobacterium, sediment from oil polluted water DQ395063, uncultured delta proteobacterium, harbor sediment AY851292, Algorimarina butyrica ARB_565A6172, denovo168 GI1.1_583 ARB_C3823A0C, denovo2233 GII3.1_11024 ARB_715AC8A9, denovo1506 GII3.1_5149 ARB_62175954, denovo1151 GII1.1_5521 ARB_A58971EA, denovo1416 GI3.1_1406 ARB_62175954, denovo639 GI1.1_635 ARB_E30E2486, denovo2288 GII3.1_7373 Jf344183, uncultured delta proteobacterium, petroleum spot over marine sediments from AJ241022, uncultured delta proteobacterium Sva0405 DQ394892, uncultured delta proteobacterium, harbor sediment KF741487, uncultured bacterium, Talbert salt marsh sediment AF286034, saltmarsh clone LCP−80 AM176857, uncultured bacterium, mangrove sediment ARB_231AEC8D, denovo1538 GII1.1_7681 ARB_2DE56776, denovo1282 GII3.1_6573 ARB_26FE5501, denovo1968 GII3.1_510

EU488125, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed Desulfococcus JF344657, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_2CB6E1DA, denovo2662 GII2.1_13512 ARB_DC9284AB, denovo3677 GII3.1_10827 ARB_8D032F64, denovo159 GII1.1_1709 ARB_E5FB189, denovo22 GI2.1_3017 ARB_890E687C, denovo491 GII3.1_7669 ARB_9BF6A65E, denovo1751 GI2.1_3671 ARB_809B64D8, denovo303 GII2.1_13944 ARB_7CA9BAA1, denovo1264 GII2.1_466 ARB_9B8D811B, denovo3373 GII1.1_2350 ARB_F5D39F51, denovo89 GII3.1_2169 FJ264783, uncultured bacterium, methane seep sediment DQ831539, uncultured delta proteobacterium, marine sediment AM745163, uncultured delta proteobacterium, marine sediments JF344689, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach EU290703, uncultured bacterium, sediment 4−6cm depth JF344569, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach AB530218, uncultured bacterium, marine sediment EU592471, uncultured bacterium, hypersaline sediment JQ580328, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil JF344202, uncultured delta proteobacterium, petroleum spot over marine sediments from figueiras beach FJ712547, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea ARB_A55FD4F6, denovo374 GI2.1_643 JQ580337, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil JF344676, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach Ay592214, uncultured bacterium, Kazan mud volcano, Eastern Mediterranean GU553709, uncultured bacterium, subseafloor sediment at the Yung−An Ridge JQ816985, uncultured bacterium, subseafloor sediment at the Good Weather Ridge JQ580267, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_ED592767, denovo91 GII2.1_7106 JQ580366, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil Ay592199, uncultured bacterium, Kazan mud volcano, Eastern Mediterranean ARB_180B36CB, denovo816 GI3.1_1982 Hq405618, bacterium enrichment culture clone AOM−SR−B34, enrichment anaerobic oxidation of methane FJ813588, uncultured bacterium, marine sediment FN820352, uncultured bacterium, marine sediment, mud volcano FN820349, uncultured bacterium, marine sediment, mud volcano uncultured FN820318, uncultured bacterium, marine sediment, mud volcano AF354163, uncultured delta proteobacterium, marine methane seep AJ535248, uncultured delta proteobacterium, marine sediment above hydrate ridge JQ580408, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil Fn553961, uncultured sediment bacterium, Logatchev hydrothermal vent field Fm165265, uncultured bacterium, chitineous tube of the vestimentiferan tubeworm Lamellibrachia sp. JQ580515, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil HQ711383, uncultured delta proteobacterium, marine sediment JQ925093, uncultured bacterium, cold seep sediment from oxygen mimimum zone in Pakistan Margin ARB_AC5CC84B, denovo3507 GII3.1_47 ARB_D2CDF56A, denovo3569 GII3.1_1966 JF428850, uncultured bacterium, zero water exchange shrimp pond sediment

Desulfosarcina

Figure S5a: Bacterial 16S rRNA gene amplicon sequences assigned to in the class of Deltaproteobac- teria, order: Desulfobacterales, family: Desulfobacteraceae (black bold: sequences retrieved in this study and closest relatives). 137 Chapter 5

GU584771, uncultured bacterium, marine hydrocarbon seep sediment FM242377, uncultured delta proteobacterium, sediment ARB_7BB7CC2B, denovo1528 GI2.1_1861 AY222313, uncultured delta proteobacterium, host hindgut caecum ARB_D1E9F9BC, denovo1688 GII2.1_1597 DQ004679, uncultured bacterium, marine hydrocarbon seep sediment ARB_A0038697, denovo3562 GII3.1_6063 ARB_7FED19F4, denovo57 GII1.1_2044 ARB_18096835, denovo477 GII3.1_5967 Jn662198, uncultured delta proteobacterium, tubeworm Ridgeia piscesae in low−ﬂow environment ARB_20167A57, denovo1173 GI1.1_1953 Jn442364, uncultured organism, Guerrero Negro Hypersaline Mat ARB_6E8E107, denovo1703 GII1.1_5238 ARB_D6DE1887, denovo2591 GII2.1_5313 ARB_D0A2A25A, denovo3037 GII3.1_8560 Jn451747, uncultured organism, Guerrero Negro Hypersaline Mat He648188, uncultured delta proteobacterium, mercury contaminated sediments Jn456653, uncultured organism, Guerrero Negro Hypersaline Mat ARB_DC50913D, denovo2564 GI2.1_308 ARB_67DDF75D, denovo1296 GII1.1_1741 AY177788, uncultured Desulfosarcina sp., Antarctic sediment Jn438994, uncultured organism, Guerrero Negro Hypersaline Mat ARB_1A22C78C, denovo2306 GII3.1_8988 JN511301, uncultured organism, Guerrero Negro Hypersaline Mat KF741381, uncultured bacterium, Talbert salt marsh sediment Jn522159, uncultured organism, Guerrero Negro Hypersaline Mat AM745205, uncultured delta proteobacterium, marine sediments Jn451253, uncultured organism, Guerrero Negro Hypersaline Mat AJ237603, Desulfosarcina cetonica Jn453804, uncultured organism, Guerrero Negro Hypersaline Mat HE797782, uncultured bacterium, anoxic brackish photosynthetic bioﬁlms JN450823, uncultured organism, Guerrero Negro Hypersaline Mat M34407, Desulfosarcina variabilis JN534382, uncultured organism, Guerrero Negro Hypersaline Mat M26632, Desulfosarcina variabilis Jn501880, uncultured organism, Guerrero Negro Hypersaline Mat FJ516893, uncultured Desulfobacteraceae bacterium, upper sediment ARB_1CA67942, denovo3200 GII1.1_9293 Y17286, Desulfosarcina ovata Desulfosarcina Jn451179, uncultured organism, Guerrero Negro Hypersaline Mat AB587702, delta proteobacterium 28bB2T ARB_3AE4005F, denovo2475 GII3.1_4668 Jn532272, uncultured organism, Guerrero Negro Hypersaline Mat ARB_FF2383AD, denovo2345 GII3.1_2479 FM242231, uncultured delta proteobacterium, sediment ARB_54481FDD, denovo2635 GII2.1_3097 ARB_F37E9CA4, denovo1201 GII3.1_9072 Jn459735, uncultured organism, Guerrero Negro Hypersaline Mat ARB_713AB900, denovo1352 GII2.1_5864 Jn454132, uncultured organism, Guerrero Negro Hypersaline Mat FN396663, uncultured marine bacterium, Arctic marine surface sediment Jn510800, uncultured organism, Guerrero Negro Hypersaline Mat ARB_CB5BEF9B, denovo2020 GII2.1_2856 Fj712416, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains JQ214259, uncultured bacterium, bottlenose dolphin mouth ARB_4C2031DA, denovo1511 GI3.1_613 ARB_2B785AAB, denovo3244 GII3.1_1828 Jn522209, uncultured organism, Guerrero Negro Hypersaline Mat

EU290724, uncultured bacterium, sediment 4−6cm depth JN452209, uncultured organism, Guerrero Negro Hypersaline Mat Desulfonema JQ215139, uncultured bacterium, bottlenose dolphin mouth ARB_2EB5FAA4, denovo2738 GII3.1_6817 ARB_8D28BB07, denovo302 GI2.1_5299 Jn458684, uncultured organism, Guerrero Negro Hypersaline Mat Am882600, uncultured delta proteobacterium, sediment from oil polluted water Jn459841, uncultured organism, Guerrero Negro Hypersaline Mat ARB_48683D96, denovo1131 GI2.1_2394 JN450773, uncultured organism, Guerrero Negro Hypersaline Mat ARB_48683D96, denovo432 GII2.1_7718 Jn442849, uncultured organism, Guerrero Negro Hypersaline Mat Jf344673, uncultured delta proteobacterium, hydrocarbon polluted marine sediments Jn450721, uncultured organism, Guerrero Negro Hypersaline Mat ARB_DCF3EA7D, denovo3912 GII3.1_6692 JN460649, uncultured organism, Guerrero Negro Hypersaline Mat ARB_902EB904, denovo2089 GI1.1_200 U45991, Desulfonema ishimotonii ARB_9896FE39, denovo774 GII2.1_5886 U45992, Desulfonema ishimotonii Jf344442, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_A7DF0EB4, denovo3805 GII3.1_11577 DQ630712, uncultured delta proteobacterium, salt marsh JQ036269, uncultured bacterium, Eel River Basin sediment 2688 ARB_E400D27A, denovo2526 GI2.1_3217 ARB_1DFD6BEC, denovo952 GII1.1_2275 KF925363, Candidatus Magnetananas sp. Rongcheng City JN038818, uncultured delta proteobacterium, Chongxi wetland soil Hq857738, Candidatus Magnetananas tsingtaoensis JX521572, uncultured bacterium, terrestrial sulfidic spring ARB_8B4B91B, denovo1795 GII1.1_3318 Jn440228, uncultured organism, Guerrero Negro Hypersaline Mat ARB_AB672D1F, denovo4081 GII1.1_4099 ARB_D6FCA9F0, denovo1736 GII3.1_2524 ARB_A41502C5, denovo1324 GI1.1_3580 ARB_85BA90CD, denovo2250 GI1.1_2008 Jn438841, uncultured organism, Guerrero Negro Hypersaline Mat ARB_85BA90CD, denovo400 GII2.1_7007 ARB_B521EEA2, denovo1656 GII2.1_1288 U45990, Desulfonema limicola ARB_E0A88F1, denovo2036 GI3.1_1767 ARB_782235F9, denovo3920 GII2.1_7847 ARB_E0DCFAF3, denovo1979 GI2.1_798 JQ215065, uncultured bacterium, bottlenose dolphin mouth ARB_DBAEF3D1, denovo2878 GII2.1_13288 ARB_14DE0EB5, denovo764 GII3.1_1091 Jn484364, uncultured organism, Guerrero Negro Hypersaline Mat FJ814756, uncultured Desulfobacterales bacterium, Carmel Canyon JN463006, uncultured organism, Guerrero Negro Hypersaline Mat ARB_EB7F7EB9, denovo37 GII1.1_11048 Jn482322, uncultured organism, Guerrero Negro Hypersaline Mat U45989, Desulfonema magnum Ef077226, uncultured delta proteobacterium, Gulf of Mexico, gas seep sedimen ARB_138F9ACC, denovo158 GII2.1_13064 HQ588478, uncultured bacterium, Amsterdam mud volcano sediment ARB_860FB93E, denovo844 GII3.1_3379 FR823373, uncultured delta proteobacterium, associated sediment Jn485046, uncultured organism, Guerrero Negro Hypersaline Mat FR823363, uncultured delta proteobacterium, gas seep sediment ARB_CD61D4ED, denovo1166 GII1.1_241 AXAM01000010, Desulfosarcina sp. BuS5 ARB_CD61D4ED, denovo2718 GI1.1_256 HG513093, uncultured delta proteobacterium, marine sediments ARB_82AEB832, denovo3766 GII3.1_7784 ARB_5888730, denovo1188 GII3.1_10608 Jn432947, uncultured organism, Guerrero Negro Hypersaline Mat ARB_F0E82616, denovo420 GII2.1_2648 Jn436445, uncultured organism, Guerrero Negro Hypersaline Mat FR823364, uncultured delta proteobacterium, gas seep sediment ARB_86F3D39D, denovo1322 GII3.1_5031 EU570889, uncultured bacterium, Nitinat Lake at a depth of 50 m Am882643, uncultured delta proteobacterium, sediment from oil polluted water ARB_3CE6694D, denovo1374 GI2.1_1017 Jn470593, uncultured organism, Guerrero Negro Hypersaline Mat ARB_92706565, denovo2432 GII2.1_422 ARB_3847EEB8, denovo1986 GI1.1_4326 ARB_B99B5F84, denovo2534 GII2.1_1677 ARB_385A98C2, denovo944 GII2.1_698 Jn520563, uncultured organism, Guerrero Negro Hypersaline Mat JX224716, uncultured bacterium, subsurface aquifer sediment Jn528692, uncultured organism, Guerrero Negro Hypersaline Mat JX224719, uncultured bacterium, subsurface aquifer sediment ARB_4101ED26, denovo1240 GI3.1_2030 ARB_F6EFB277, denovo1388 GII3.1_8824 ARB_E852A741, denovo3862 GII2.1_3081 ARB_1B95CE8A, denovo1016 GII3.1_5381 AB630474, uncultured bacterium, aquatic moss pillars AM882627, uncultured delta proteobacterium, sediment from oil polluted water Fj712404, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains ARB_7BDF5E2E, denovo3523 GII3.1_3456 KF268892, uncultured bacterium, marine sediment ARB_C4BDFDE5, denovo667 GI3.1_271 AJ620497, Olavius algarvensis Delta 4 endosymbiont, marine sediment ARB_9709B744, denovo2912 GII3.1_10066 Fj712498, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, ARB_B470EE51, denovo659 GII3.1_2742 Jn387434, uncultured microorganism, Zodletone spring sediment ARB_61518FF, denovo3305 GII3.1_9312 ARB_28682B51, denovo2197 GI2.1_784 ARB_4E1BBC63, denovo1224 GI2.1_837 Am882623, uncultured delta proteobacterium, sediment from oil polluted water JX223505, uncultured bacterium, subsurface aquifer sediment ARB_76C9EFC4, denovo149 GII1.1_819 AB237683, uncultured bacterium, deep subsurface groundwater from sedimentary rock milieu ARB_76C9EFC4, denovo2253 GI2.1_1760 JX222865, uncultured bacterium, subsurface aquifer sediment ARB_8FFDF050, denovo208 GII3.1_7256 JX225750, uncultured bacterium, subsurface aquifer sediment ARB_19CA1269, denovo3467 GII3.1_7023 ARB_8DA8F9E5, denovo433 GI2.1_3360 JF344320, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach AB355075, uncultured bacterium, sediment, Manzallah Lake ARB_87AB5B4E, denovo1028 GII3.1_1044 Ef999366, uncultured bacterium, Pearl River Estuary sediments ARB_C029BEB9, denovo2068 GII3.1_3423 DQ415752, uncultured bacterium, Frasassi sulfidic cave stream biofilm JF344560, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach ARB_7E558345, denovo924 GII3.1_3115 ARB_85F032BD, denovo3750 GII2.1_1454 ARB_BC245D35, denovo1031 GII3.1_2710 ARB_DF16678C, denovo386 GII3.1_11802 Fq659033, uncultured soil bacterium, PAH−contaminated soil FR823365, uncultured delta proteobacterium, gas seep sediment ARB_EA44E0C5, denovo1195 GI1.1_2747 FR823374, uncultured delta proteobacterium, associated sediment ARB_77B1D6BD, denovo1947 GII2.1_1107 JQ580521, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_F9FC6349, denovo1840 GII3.1_9728 FM242228, uncultured delta proteobacterium, sediment ARB_369D1854, denovo601 GI1.1_2578 JN387432, uncultured microorganism, Zodletone spring source sediment FJ516891, uncultured Desulfobacteraceae bacterium, upper sediment EU290686, uncultured bacterium, sediment 10−12cm depth ARB_D0E35DBE, denovo1637 GII2.1_5707 FJ802207, denitrifying bacterium enrichment culture clone NO, Ebro River Delta sediment AB525467, uncultured bacterium, deep−sea methane seep sediment off Joetsu, Japan Sea ARB_C7FB7BD3, denovo4038 GII2.1_5507 JN454071, uncultured organism, Guerrero Negro Hypersaline Mat FJ802214, denitrifying bacterium enrichment culture clone NO, Ebro River Delta sediment ARB_7CB39937, denovo3870 GII2.1_5347 AB630477, uncultured bacterium, aquatic moss pillars Jn486306, uncultured organism, Guerrero Negro Hypersaline Mat KC662297, uncultured bacterium, shrimp sediment Jn443588, uncultured organism, Guerrero Negro Hypersaline Mat EU266914, uncultured Desulfobacteraceae bacterium, tar−oil contaminated aquifer sediments Cu925954, uncultured bacterium, mesophilic anaerobic digester wastewater sludge DQ146482, Desulfatirhabdium butyrativorans ARB_A049BE09, denovo1909 GII3.1_1493 AUCU01000039, Desulfatirhabdium butyrativorans DSM 18734 ARB_E0A335A9, denovo2058 GI2.1_966 ARB_34FBA2FC, denovo2748 GII3.1_5675 AF154058, Eubostrichus dianae epibacterium 2_25 ARB_1216BFC8, denovo523 GII3.1_10002 DQ415749, uncultured bacterium, Frasassi sulfidic cave stream biofilm ARB_FC4CC3BF, denovo1568 GII3.1_8534 EU246060, uncultured organism, hypersaline microbial mat ARB_C45E6319, denovo1783 GII3.1_3436 ARB_8F55C3F4, denovo2751 GII2.1_6026 Jf344627, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach DQ415820, uncultured bacterium, Frasassi sulfidic cave stream biofilm ARB_D6AA1912, denovo1579 GI2.1_4294 DQ133938, uncultured bacterium, limestone−corroding stream biofilm ARB_B02A7801, denovo3004 GII3.1_6642 DQ415847, uncultured bacterium, Frasassi sulfidic cave stream biofilm FJ485367, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 273m depth Jn537551, uncultured organism, Guerrero Negro Hypersaline Mat ARB_D7DF1E65, denovo183 GII3.1_662 Jn512532, uncultured organism, Guerrero Negro Hypersaline Mat

ARB_3B67EA53, denovo1846 GI1.1_44 Desulfatirhabdium ARB_42A2A09C, denovo2685 GII2.1_2390 FJ502253, uncultured bacterium, Lake Cadagno chemocline; 12.5m AM086154, uncultured bacterium, lake profundal sediment KF741543, uncultured bacterium, Talbert salt marsh sediment DQ133936, uncultured bacterium, limestone−corroding stream biofilm JF268407, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae, station 309; SO191_3_309 DQ133911, uncultured bacterium, limestone−corroding stream biofilm ARB_118B74EC, denovo680 GII2.1_440 DQ133934, uncultured bacterium, limestone−corroding stream biofilm HQ174906, uncultured bacterium, Cherokee Road Extension Blue Hole Jn522187, uncultured organism, Guerrero Negro Hypersaline Mat Jf344612, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_988C1618, denovo3179 GII3.1_3268 JX504502, uncultured bacterium, oolitic sand AF099065, Desulfofrigus fragile AB530220, uncultured bacterium, marine sediment ARB_29F48A4E, denovo655 GI3.1_4246 KF596671, uncultured bacterium, soil HE600063, uncultured Desulfofrigus sp., marine sediment ARB_19855F1B, denovo18 GI2.1_3831 ARB_A5B339C9, denovo2168 GII2.1_7178 AM086163, uncultured bacterium, lake profundal sediment AF099064, Desulfofrigus oceanense Jn446846, uncultured organism, Guerrero Negro Hypersaline Mat AB015240, uncultured delta proteobacterium, deepest cold−seep area of the Japan Trench Jn455820, uncultured organism, Guerrero Negro Hypersaline Mat EU052250, uncultured delta proteobacterium, anode from microbial fuel cell fed with marine plankton Gu302437, uncultured bacterium, marine sediments Mississippi Canyon EU052237, uncultured delta proteobacterium, anode from microbial fuel cell fed with marine plankton ARB_566A0BD4, denovo661 GII3.1_2960 AB530175, uncultured bacterium, marine sediment ARB_D9F5669B, denovo10 GI2.1_3947 ARB_1EFDF7DA, denovo1912 GI1.1_3304 ARB_7581FAA0, denovo3528 GII1.1_2970 ARB_F38F9C78, denovo438 GII3.1_9848 ARB_4D3AC268, denovo1169 GI2.1_1067 ARB_B3F8690C, denovo3171 GII2.1_2892 FM242402, uncultured delta proteobacterium, sediment ARB_C3BF8B7, denovo3566 GII2.1_13654 Am882622, uncultured delta proteobacterium, sediment from oil polluted water Jf344495, uncultured delta proteobacterium, hydrocarbon polluted marine sediments FM242376, uncultured delta proteobacterium, sediment ARB_972BEFDB, denovo2749 GI1.1_3156 Am882604, uncultured delta proteobacterium, sediment from oil polluted water ARB_972BEFDB, denovo831 GII1.1_1216 AJ237607, Desulfobacterium indolicum ARB_EDD81177, denovo4017 GII2.1_4348 FJ813595, uncultured bacterium, marine sediment ARB_824ACC52, denovo1977 GII3.1_7096 ARB_3A7EB538, denovo512 GII3.1_4964 Desulfobacterium ARB_CEB514CF, denovo327 GII3.1_2683 HQ178881, uncultured bacterium, sediment treated with Mr. Frosty slow freeze method ARB_5499095F, denovo3967 GII2.1_121 FQ659849, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs ARB_EA25DAB2, denovo301 GI1.1_5383 EU385675, uncultured bacterium, subseafloor sediment of the South China Sea KC471130, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough AY851291, Algidimarina propionica KC471154, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough GQ356960, uncultured bacterium, methane seep sediment ARB_230591CA, denovo2332 GII1.1_5560 ARB_69CF1588, denovo3217 GII2.1_765 KC471196, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough ARB_4D5BC411, denovo2235 GII1.1_8125 ARB_E3CF55F2, denovo3886 GII3.1_9557 EF125422, uncultured bacterium, mangrove soil ARB_875F4162, denovo3943 GII3.1_12311 JN038987, uncultured delta proteobacterium, Chongxi wetland soil KC471054, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough DQ811793, uncultured delta proteobacterium, mangrove soil HQ703812, uncultured bacterium, Lianyungang marine sediment DQ811836, uncultured delta proteobacterium, mangrove soil ARB_5366F7CC, denovo2113 GII3.1_12485 AY216453, uncultured bacterium, temperate estuarine mud KC471037, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough ARB_E9C88F6B, denovo45 GII2.1_6638 KC471011, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough Desulfofaba_1 ARB_B6B3A7A9, denovo3493 GII1.1_310 KC471046, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough JX222415, uncultured bacterium, subsurface aquifer sediment AF321820, Desulfofaba hansenii ARB_A67B6D71, denovo2403 GII3.1_10460 JX222073, uncultured bacterium, subsurface aquifer sediment ARB_6E5ADDED, denovo3435 GII2.1_1449 ARB_42DA9ED8, denovo1976 GI1.1_1431 ARB_6E5ADDED, denovo408 GI3.1_2254 ARB_FAF7585E, denovo2155 GII3.1_6836 EU290687, uncultured bacterium, sediment 10−12cm depth ARB_700BB89E, denovo2433 GI2.1_1599 ARB_BF175B5A, denovo2686 GII1.1_64 ARB_B43CC987, denovo87 GII2.1_481 Jn521333, uncultured organism, Guerrero Negro Hypersaline Mat Ay592706, uncultured bacterium, Napoli mud volcano, Eastern Mediterranean, ARB_4BCB9692, denovo2286 GII1.1_1807 ARB_6CB546A4, denovo3222 GII3.1_3868 Desulfofaba_2 ARB_1C9EAE25, denovo1438 GII3.1_1 AY268891, Desulfofaba fastidiosa AM745219, uncultured delta proteobacterium, marine sediments EU487968, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed ARB_B8B5FD8, denovo1541 GII2.1_6936 JX222769, uncultured bacterium, subsurface aquifer sediment ARB_EC4D5ED7, denovo1034 GII3.1_1420 DQ415842, uncultured bacterium, Frasassi sulfidic cave stream biofilm ARB_5FE96A7F, denovo1725 GII3.1_11421 ARB_7A94311A, denovo1579 GII3.1_3316 AB121109, uncultured delta proteobacterium, cold seep sediment ARB_102BDE9A, denovo1602 GI2.1_1649 ARB_8270E60B, denovo4084 GII2.1_2351 HE613444, Desulfatiferula sp. BE2801, estuary sediment ARB_EA29AB53, denovo1053 GI2.1_3353 FR667781, uncultured bacterium, iron snow from acidic coal mining−associated Lake 77 JX222455, uncultured bacterium, subsurface aquifer sediment Jf344222, uncultured delta proteobacterium, petroleum spot over marine sediments EF999346, uncultured bacterium, Pearl River Estuary sediments at 6cm depth DQ826724, Desulfatiferula olefinivorans Jn530486, uncultured organism, Guerrero Negro Hypersaline Mat ARB_E11A1166, denovo399 GI2.1_871 Desulfatiferula ARB_E9534EC3, denovo248 GI2.1_3488 JX222822, uncultured bacterium, subsurface aquifer sediment Am882642, uncultured delta proteobacterium, sediment from oil polluted water JX223240, uncultured bacterium, subsurface aquifer sediment ARB_2869D04F, denovo1318 GII3.1_720 ARB_2CD45AD4, denovo2141 GI2.1_1838 JQ245689, uncultured bacterium, mud volcano JX222458, uncultured bacterium, subsurface aquifer sediment DQ811807, uncultured delta proteobacterium, mangrove soil JX223512, uncultured bacterium, subsurface aquifer sediment JQ516448, uncultured Desulfobacteraceae bacterium, healthy tissue JX457247, uncultured bacterium, gut ARB_350E391, denovo2371 GI2.1_3686 Desulfatitalea GQ866071, uncultured bacterium, gut JQ739023, uncultured bacterium, Lonar sediment surface rocks ARB_3A4D20D7, denovo2746 GII3.1_2705 AF177428, delta proteobacterium S2551 AB614135, Desulfatitalea tepidiphila, tidal flat sediment JQ245513, uncultured bacterium, mud volcano

Figure S5b: Bacterial 16S rRNA gene amplicon sequences assigned to in the class of Deltaproteobac- teria, order: Desulfobacterales, family: Desulfobacteraceae (black bold: sequences retrieved in this study and closest relatives). 138 Supplementary Material

Jn452561, uncultured organism, Guerrero Negro Hypersaline Mat ARB_5E38B580, denovo3953 GII1.1_1602 JX391346, uncultured bacterium, marine sediment Kf623992, uncultured bacterium, Janssand tidal flat, Wadden Sea KF799406, uncultured bacterium, gut KF268874, uncultured bacterium, marine sediment JX391709, uncultured bacterium, marine sediment JX391368, uncultured bacterium, marine sediment FJ949149, uncultured Desulfobacteraceae bacterium, calcareous sandy sediment JX391090, uncultured bacterium, marine sediment ARB_9E2E722F, denovo2789 GII1.1_7427 JX391589, uncultured bacterium, marine sediment Fj716993, uncultured bacterium, marine sediment from Cullercoats, Northumberland ARB_9D945629, denovo867 GII1.1_234 U51844, delta proteobacterium WN ARB_B6C76362, denovo522 GII3.1_7062 ARB_8AA8018, denovo3096 GII2.1_5852 JQ212736, uncultured bacterium, bottlenose dolphin mouth Fj717001, uncultured bacterium, marine sediment from Cullercoats, Northumberland AF099054, Desulfobacter sp. ASv25 GQ261762, uncultured delta proteobacterium, deep sea sediment associated with whale falls GQ356938, uncultured bacterium, methane seep sediment GQ356949, uncultured bacterium, methane seep sediment FR733673, Desulfobacter hydrogenophilus DQ057079, Desulfobacter psychrotolerans FJ717003, uncultured bacterium, marine sediment from Cullercoats, Northumberland Fj716965, uncultured bacterium, marine sediment from Cullercoats, Northumberland JF343993, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from rodas beach Fj716962, uncultured bacterium, marine sediment from Cullercoats, Northumberland U85469, Desulfobacter sp. BG8 KF268856, uncultured bacterium, marine sediment ARB_DD288351, denovo2652 GI2.1_4358 JX225079, uncultured bacterium, subsurface aquifer sediment ARB_7BB6FB78, denovo2419 GI3.1_4466 ARB_A58E3C3B, denovo3178 GII3.1_10337 JX120461, uncultured bacterium, subsurface aquifer sediment JX120460, uncultured bacterium, subsurface aquifer sediment JX125449, uncultured bacterium, subsurface aquifer sediment JX120466, uncultured bacterium, subsurface aquifer sediment AF418180, Desulfobacter postgatei M26633, Desulfobacter postgatei AGJR02000005, Desulfobacter postgatei 2ac9, anaerobic sediment of brackish water ditch near Jadebusen Eu864440, uncultured bacterium, Xiao River EU864484, uncultured bacterium, Xiao River receiving treated oxytetracycline production wastewater JX120459, uncultured bacterium, subsurface aquifer sediment JX225700, uncultured bacterium, subsurface aquifer sediment Jx271977, uncultured bacterium, activated sludge in lab−scale reactor EU234252, uncultured bacterium, downstream of Wang Yang River, receiving penicillin G production wastewater AGJR02000008, Desulfobacter postgatei 2ac9, anaerobic sediment of brackish water ditch near Jadebusen FJ716310, uncultured bacterium, Sawmill Sink water column, at 10.3 m water depth KF933845, Desulfobacula sp. TS−7 ARB_68E1E8F6, denovo1052 GII3.1_1606 AY222309, uncultured delta proteobacterium, host hindgut caecum ARB_55128A66, denovo3319 GII2.1_11393 EF442984, sulfate−reducing bacterium JHA1 AY177795, uncultured Desulfobacula sp., Antarctic sediment FR823371, uncultured delta proteobacterium, gas seep sediment JF514280, uncultured bacterium, sea ARB_691E454A, denovo157 GI2.1_919 ARB_BCB1D27F, denovo1223 GII3.1_11648 EU290701, uncultured bacterium, sediment 0−2cm depth AY177800, uncultured Desulfobacula sp., Antarctic sediment KF268860, uncultured bacterium, marine sediment JQ753193, uncultured bacterium, Antarctic sea ice GU197423, uncultured bacterium, intertidal sediment, depth 0−15 cm Ay922192, uncultured delta proteobacterium, grey whale bone, Pacific Ocean, Santa Cruz Basin FR823375, uncultured delta proteobacterium, associated sediment FR823376, uncultured delta proteobacterium, associated sediment JF344268, uncultured delta proteobacterium, petroleum spot over marine sediments from figueiras beach KC471161, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough KC471246, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough KC471078, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough ARB_9E645E6E, denovo210 GII3.1_1506 ARB_AD101018, denovo343 GII2.1_4906 ARB_9900558E, denovo1638 GII2.1_10513 ARB_ADF00A92, denovo796 GII3.1_7275 KC471244, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough KC471084, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough ARB_4A9FE3FF, denovo1772 GII2.1_879 ARB_2423619F, denovo2566 GI2.1_305 ARB_18F285C2, denovo2618 GII2.1_3476 ARB_E1D7A46E, denovo1731 GII1.1_2949 KC492863, uncultured Desulfobacula sp., Baltic Sea redoxcline, 119 m depth AY177803, uncultured Desulfobacula sp., Antarctic sediment AJ937698, uncultured bacterium, mud from a terrestrial volcano ARB_A9ED3C90, denovo127 GII3.1_1097 ARB_C5D21D56, denovo1906 GII3.1_607 ARB_752C5DFE, denovo3090 GII3.1_10845 ARB_56BD7EAD, denovo3258 GII2.1_9782 Fj628185, uncultured bacterium, brackish water from anoxic fjord ARB_C5116C1C, denovo1634 GII2.1_4094 ARB_A9D2324B, denovo1307 GI1.1_2919 ARB_7BB990DB, denovo1697 GII3.1_8393 FJ628265, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 22 GU145490, uncultured bacterium, Black Sea, potential density 15.81 KC545723, uncultured Desulfobacula sp., oxycline region of a coastal marine water column KC545728, uncultured Desulfobacula sp., oxycline region of a coastal marine water column AM774314, delta proteobacterium JS_SRB50Hy, tidal flat sediment AJ237606, Desulfobacula phenolica GQ261767, uncultured delta proteobacterium, deep sea sediment associated with whale falls GQ348356, uncultured delta proteobacterium, Saanich Inlet, 200 m depth GU197424, uncultured bacterium, intertidal sediment, depth 0−15 cm DQ831540, uncultured Desulfobacula sp., marine sediment ARB_CB393774, denovo2285 GII1.1_285 ARB_831C7D25, denovo1192 GII1.1_11241 ARB_F227D1D4, denovo344 GII3.1_2379

ARB_FE2B548D, denovo2584 GI2.1_237 Desulfobacula ARB_F4D910C0, denovo2876 GII2.1_5307 Kc000940, unidentified marine bacterioplankton, surface seawater samples from South China Sea ARB_8741E9EF, denovo551 GI1.1_5282 ARB_6AAFAFB, denovo1020 GII1.1_1771 ARB_E6C2968D, denovo1222 GI1.1_1092 HQ405662, bacterium enrichment culture clone AOM−SR−B24, enrichment mediating the anaerobic oxidation of methane ARB_8921930, denovo1642 GI3.1_5066 EU570896, uncultured bacterium, Nitinat Lake at a depth of 13 m ARB_FE450D44, denovo2673 GII2.1_270 Dq925890, uncultured bacterium, hydrothermal vent Guaymas Basin AB189365, uncultured Desulfobacterium sp., cold seep sediment AJ704693, uncultured delta proteobacterium, marine sediment AJ704685, uncultured delta proteobacterium, marine sediment ARB_7FCB72A1, denovo1108 GI1.1_3343 ARB_844A3AFA, denovo994 GII3.1_5707 JF268367, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae, station 309; SO191_3_309 KF624105, uncultured bacterium, anoxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea JF344167, uncultured delta proteobacterium, petroleum spot over marine sediments from figueiras beach FN820309, uncultured bacterium, marine sediment, mud volcano JQ580395, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_F3E53A99, denovo2676 GII3.1_2047 AY197397, uncultured bacterium, Guaymas Basin hydrothermal vent sediments ARB_B802BE9, denovo1369 GII3.1_343 FJ497571, uncultured delta proteobacterium, Vailulu’u Seamount ARB_4BCB0690, denovo2794 GII1.1_6932 JX225725, uncultured bacterium, subsurface aquifer sediment JX224838, uncultured bacterium, subsurface aquifer sediment ARB_38687E91, denovo1775 GII3.1_357 JX224531, uncultured bacterium, subsurface aquifer sediment KF059938, uncultured Desulfobacula sp., oil well water JX224964, uncultured bacterium, subsurface aquifer sediment ARB_90F03020, denovo418 GI3.1_3548 ARB_903AB4BE, denovo400 GI1.1_2096 ARB_E811D690, denovo2159 GII3.1_4428 ARB_6E68406, denovo3323 GII3.1_11303 ARB_2658D044, denovo736 GI2.1_1998 Ef687285, uncultured bacterium, sediment underneath a sulfide−oxidizing mat, Chefren mud volcano ARB_5E2AC7C5, denovo2114 GII1.1_9836 ARB_B40486E4, denovo3407 GII1.1_957 ARB_BDBAEB51, denovo2557 GII2.1_2691 ARB_7F4AC00D, denovo2965 GII2.1_4835 ARB_5AFBF727, denovo3032 GII3.1_1347 ARB_99C327D9, denovo3509 GII2.1_3753 ARB_F6FC891D, denovo2989 GII3.1_6268 HQ405610, bacterium enrichment culture clone AOM−SR−B20, enrichment mediating the anaerobic oxidation of methane Ef687314, uncultured bacterium, sediment underneath a sulfide−oxidizing mat, Chefren mud volcano, Nile Deep Sea Fan FR823370, uncultured delta proteobacterium, gas seep sediment AM883182, uncultured bacterium, host trophosome tissue AY177799, uncultured Desulfobacteraceae bacterium, Antarctic sediment Jn455195, uncultured organism, Guerrero Negro Hypersaline Mat EU570886, uncultured bacterium, Nitinat Lake at a depth of 50 m ARB_1852A786, denovo4080 GII1.1_371 ARB_E77D75, denovo2622 GII3.1_3718 ARB_138286CE, denovo2476 GI2.1_431 ARB_138286CE, denovo3966 GII3.1_12408 ARB_12774C80, denovo2714 GII2.1_11932 AY197376, uncultured proteobacterium, Guaymas Basin hydrothermal vent sediments DQ925877, uncultured bacterium, hydrothermal vent chimneys of Guaymas Basin ARB_6BE57BCD, denovo466 GI2.1_3816 ARB_51E6D082, denovo2560 GII1.1_904 ARB_4D98103A, denovo590 GI1.1_2711 ARB_F2CADC85, denovo1645 GII2.1_320 ARB_8DA9F1F2, denovo2813 GI3.1_4146 AY197389, uncultured proteobacterium, Guaymas Basin hydrothermal vent sediments CP001087, Desulfobacterium autotrophicum HRM2 AF099056, Desulfobacterium sp. LSv25 GQ261805, uncultured delta proteobacterium, deep sea sediment associated with whale falls ARB_85D093E0, denovo3220 GII1.1_3563 U85474, Desulfobacterium sp. BG33 U85471, Desulfobacterium sp. BG18

FR733668, Desulfococcus niacini Desulfobacterium_2 EF442983, Desulfobacterium zeppelinii AF418178, Desulfobacterium vacuolatum ARB_DCBB76E5, denovo3877 GII1.1_2385 ARB_3CD31A93, denovo1687 GI3.1_2927 ARB_42406D1, denovo1081 GI3.1_4342 ARB_F4D45108, denovo1094 GII1.1_537 ARB_F23C63C1, denovo2424 GII2.1_6963 JN252194, Candidatus Desulfamplus magnetomortis BW−1 Candidatus Desulfamplus EU047537, uncultured sulfate−reducing bacterium, benzene−degrading, sulfate−reducing enrichment culture ARB_D6D2D42B, denovo157 GII3.1_9438 ARB_45B9A382, denovo999 GII3.1_1990 AB530188, uncultured bacterium, marine sediment ARB_B33F233E, denovo1250 GII3.1_11390 ARB_3811BEBC, denovo272 GI2.1_266 ARB_B99FC159, denovo735 GII2.1_4119 ARB_217ED137, denovo1265 GII3.1_6977 ARB_6F53D9A2, denovo941 GII2.1_6606 ARB_6CFF573D, denovo1362 GII1.1_9507 ARB_6CFF573D, denovo289 GI2.1_1883 ARB_C7AE2C97, denovo2652 GII3.1_3409 ARB_7D646BD3, denovo593 GI2.1_647 ARB_4AFD410D, denovo1138 GI2.1_2087 ARB_12CB3B73, denovo3860 GII3.1_10456 GQ348489, uncultured delta proteobacterium, Saanich Inlet, 200 m depth ARB_1BD1B139, denovo185 GII1.1_842 ARB_AE84C44F, denovo827 GII2.1_8140 EU885094, uncultured bacterium, GI tract JQ216349, uncultured bacterium, bottlenose dolphin mouth ARB_843ECF4E, denovo2893 GII3.1_8486 JX391413, uncultured bacterium, marine sediment ARB_BE36ACE0, denovo3825 GII3.1_3441 ARB_DFC8E39B, denovo3243 GII2.1_7317 KF268778, uncultured bacterium, marine sediment ARB_9BF7C65, denovo232 GI3.1_3136 GQ259286, uncultured bacterium, deep sediment ARB_F7DCEB29, denovo227 GII2.1_2296 ARB_14204A90, denovo1504 GII2.1_6800 ARB_13808028, denovo2840 GI3.1_827 GU127076, uncultured bacterium, sediment; anoxic zone; tucurui hydroeletric power plant reservoir ARB_51EF3CEE, denovo718 GII3.1_4007 HM243869, uncultured bacterium, middle sediment from Honghu Lake FJ485347, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 273m depth JQ580417, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil ARB_6F8CC735, denovo624 GII2.1_730 KF548223, uncultured bacterium, aerobic tank of a full−scale produced water treatment plant ARB_57B3B254, denovo617 GI1.1_920 AB530187, uncultured bacterium, marine sediment ARB_BFBB7707, denovo738 GII3.1_701 Figure S5c: Bacterial 16S rRNA gene amplicon sequences assigned to in the class of Deltaproteobac- teria, order: Desulfobacterales, family: Desulfobacteraceae (black bold: sequences retrieved in this study and closest relatives). 139 Chapter 5

Ay280427, uncultured epsilon proteobacterium, hydrothermal vent sulfide chimney, Juan de Fuca Ridge Jn662023, uncultured epsilon proteobacterium, ubeworm Ridgeia piscesae AB278151, uncultured bacterium, obtained from Mariana Trough AY531599, uncultured bacterium, Indian Ocean hydrothermal vent JQ712438, uncultured epsilon proteobacterium, hydrothermal vent fluids Jn662026, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae AJ441211, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions AJ576002, uncultured epsilon proteobacterium, deep sea hydrothermal vent Jn874168, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise Jn873951, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise AY672507, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean AY672537, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean EU555121, uncultured bacterium, Dudley hydrothermal vent AF449232, uncultured epsilon proteobacterium, Riftia pachyptila’s tube JQ611095, uncultured bacterium, biofilm near white vent off Kueishan Island JQ611085, uncultured bacterium, biofilm near white vent off Kueishan Island Ay280407, uncultured epsilon proteobacterium, hydrothermal vent sulfide chimney, Juan de Fuca Ridge ARB_64F4AD65, denovo915 GI2.1_384 ARB_305B8363, denovo513 GII1.1_682 Jn662076, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae ARB_EA631019, denovo1504 GI2.1_3731 AY672526, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean AY672530, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean AY672521, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean AY672520, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean AJ441209, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions Gu369886, uncultured epsilon proteobacterium, shallow hydrothermal vent region 32 uncultured AF449253, uncultured epsilon proteobacterium, Riftia pachyptila’s tube 37 uncultured AJ431222, proteobacterium BHI80−16 AF420345, uncultured proteobacterium Jn874159, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise JQ712462, uncultured epsilon proteobacterium, hydrothermal vent fluids Jn662191, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae AP009179, Sulfurovum sp. NBC37−1 AP009179, Sulfurovum sp. NBC37−1 AP009179, Sulfurovum sp. NBC37−1 JQ611086, uncultured bacterium, biofilm near white vent off Kueishan Island JQ611159, uncultured bacterium, core sediment at 0−3 cm depth in yellow vent off Kueishan Island AJ431221, proteobacterium BHI60−14 AB091292, Sulfurovum lithotrophicum, deep−sea hydrothermal vent environments Jn873995, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise FR853000, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca Ridge JQ712487, uncultured epsilon proteobacterium, hydrothermal vent fluids Jn662247, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae uncultured (9 sequences) AY531576, uncultured bacterium, Indian Ocean hydrothermal vent AF449235, uncultured epsilon proteobacterium, Riftia pachyptila’s tube Jn874207, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise Jn874109, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise Jn874231, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise AY672533, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean JQ611145, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611112, uncultured bacterium, biofilm near yellow vent off Kueishan Island Hq153866, uncultured bacterium, white microbial film shallow hydrothermal vent Jn662036, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae Jn662064, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae FJ535344, uncultured bacterium, sediment FJ535271, uncultured bacterium, iron mat Jn662133, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae AF449231, uncultured epsilon proteobacterium, Riftia pachyptila’s tube JQ611132, uncultured bacterium, core sediment at 0−5 cm depth in white vent off Kueishan Island JQ611123, uncultured bacterium, core sediment at 21−24 cm depth in white vent off Kueishan Island JQ712402, uncultured epsilon proteobacterium, hydrothermal vent fluids

AB842288, uncultured bacterium, gut of S.crosnieri _Sulfurovum

182 uncultured

JF747909, uncultured bacterium, Frasassi cave system sulfidic spring JF747989, uncultured bacterium, Frasassi cave system sulfidic spring GQ355039, uncultured bacterium, spring EF444740, uncultured bacterium, Thermopiles hot springs Dq295592, uncultured epsilon proteobacterium, microbial mat from sulfidic spring Dq295601, uncultured epsilon proteobacterium, microbial mat from sulfidic spring Dq295602, uncultured epsilon proteobacterium, microbial mat from sulfidic spring AF121887, bacterium 2BP−7 GQ227834, uncultured bacterium, ground swab in mangrove forest GQ355011, uncultured epsilon proteobacterium, spring Jn662280, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae EF061978, uncultured epsilon proteobacterium, mangrove sediment GU583971, uncultured bacterium, mangrove soil GU583970, uncultured bacterium, mangrove soil JX403047, uncultured bacterium, bitumen GU180159, uncultured bacterium, sediment and soil slurry GU180158, uncultured bacterium, sediment and soil slurry EU488101, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed KC009865, uncultured Campylobacteraceae bacterium, shallow fluidized muds off the French Guiana coast KF465256, uncultured Sulfurovum sp., Alang−Sosiya ship breaking yard ARB_5E9258CC, denovo3386 GII3.1_7847 ARB_482679F6, denovo1298 GII1.1_1746 KC763867, uncultured bacterium, oil−contaminated soil GU120550, uncultured epsilon proteobacterium, inside erupting mud volcano, temperature = 27.7 C GU056082, uncultured bacterium, soil sample above gas and oil field DQ394915, uncultured epsilon proteobacterium, harbor sediment JQ989773, uncultured bacterium, subseafloor sediment at the KP−9 EF061977, uncultured epsilon proteobacterium, mangrove sediment JQ989775, uncultured bacterium, subseafloor sediment at the KP−9 KF758699, uncultured Sulfurovum sp., ocean water KF758616, uncultured Sulfurovum sp., ocean water KF758740, uncultured Sulfurovum sp., ocean water JQ989774, uncultured bacterium, subseafloor sediment at the KP−9 KF758756, uncultured Sulfurovum sp., ocean water KF758605, uncultured Sulfurovum sp., ocean water JQ989767, uncultured bacterium, subseafloor sediment at the KP−9 KF758583, uncultured Sulfurovum sp., ocean water JQ989770, uncultured bacterium, subseafloor sediment at the KP−9 AF420360, uncultured proteobacterium JX403027, uncultured bacterium, underground water

EF467546, uncultured bacterium, Frasassi sulﬁdic cave stream bioﬁlm Campylobacterales_Helicobacteraceae Jn662200, uncultured epsilon proteobacterium, Ridgeia piscesae tubeworm AF420343, uncultured proteobacterium

120 uncultured

8 uncultured JQ036280, uncultured bacterium, Hydrate Ridge sediment 2518 11 uncultured JQ611092, uncultured bacterium, biofilm near white vent off Kueishan Island AJ441206, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions EU570833, uncultured bacterium, Nitinat Lake at a depth of 37.5 m Kc545718, uncultured Desulfopila sp., oxycline region GQ354918, uncultured Desulfobacterales bacterium, spring GQ354989, uncultured delta proteobacterium, spring Jn662041, uncultured proteobacterium, tubeworm Ridgeia piscesae Jn662234, uncultured delta proteobacterium, tubeworm Ridgeia piscesae ARB_870C0E9A, denovo896 GII2.1_6517 ARB_D61337BA, denovo3327 GII3.1_2152 GU120555, uncultured epsilon proteobacterium, inside erupting mud volcano AB530185, uncultured bacterium, marine sediment KF758719, uncultured Salimesophilobacter sp., ocean water KF758696, uncultured Sulfurovum sp., ocean water DQ394916, uncultured bacterium, harbor sediment GQ354985, uncultured epsilon proteobacterium, spring Fn554089, uncultured sediment bacterium, Logatchev hydrothermal vent field FJ615414, uncultured bacterium, high rate anaerobic methane−oxidizing submerged membrane bioreactor HM445989, uncultured bacterium, wastewater EU234154, uncultured bacterium, effluent of the WWTP for treating penicillin G production wastewater AJ431220, proteobacterium Dex80−27 FJ535262, uncultured bacterium, iron mat GU220732, uncultured bacterium, low temperature hydrothermal precipitates of East Lau Spreading Center FR852993, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca Ridge FR853069, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca Ridge KF624533, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea AB842287, uncultured bacterium, gut of S.crosnieri KF545018, uncultured Sulfurovum sp., deep−sea sediment Jn662077, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environment Ay280435, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca Ridge Jn662174, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environment Jn874024, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise Jn874212, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise Jn662066, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environment Jn662253, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environment Jn662149, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environment JQ712481, uncultured epsilon proteobacterium, hydrothermal vent fluids Jn662098, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environment JQ712460, uncultured epsilon proteobacterium, hydrothermal vent fluids JQ712484, uncultured epsilon proteobacterium, hydrothermal vent fluids JQ712444, uncultured epsilon proteobacterium, hydrothermal vent fluids AJ431224, proteobacterium Dex80−90 JN874140, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N JN873965, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N JN874006, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N AY672518, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean JN873957, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N JN874072, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N JN874274, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’N JN873975, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N AQWF01000016, Sulfurovum sp. SCGC AAA036−F05 JN873991, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N AY672522, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean JN873979, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N AY672531, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean 25 uncultured AB842280, uncultured bacterium, gut of S.crosnieri Ay280389, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca Ridge JX521118, uncultured bacterium, terrestrial sulfidic spring JQ611148, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611152, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611146, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611125, uncultured bacterium, core sediment at 21−24 cm depth in white vent off Kueishan Island JQ611156, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611139, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611117, uncultured bacterium, core sediment at 21−24 cm depth in white vent off Kueishan Island JQ611179, uncultured bacterium, porewater fluid near yellow vent off Kueishan Island JQ611147, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611151, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island JQ611137, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island AY672540, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean Figure S6a: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobac- teria, order: Campylobacterales, family: Helicobacteraceae, genus: Sulfurovum (black bold: sequences retrieved in this study and closest relatives). 140 Supplementary Material

16 uncultured JX570598, endosymbiont of Ridgeia piscesae JQ712409, uncultured epsilon proteobacterium, hydrothermal vent fluids AF449239, uncultured epsilon proteobacterium, Riftia pachyptila’s tube ARB_A468E98B, denovo1651 GII3.1_10383 JQ199082, uncultured bacterium, seawater; next to dolphin U GQ357014, uncultured bacterium, methane seep sediment JX016315, uncultured bacterium, marine bulk water HM057704, uncultured bacterium, ocean water from the Yellow Sea HQ203962, uncultured bacterium, seawater ARB_BDD1DF7F, denovo1949 GI1.1_1153 FR666865, uncultured bacterium, microbial mat FR666868, uncultured bacterium, microbial mat FR666860, uncultured bacterium, microbial mat FR666861, uncultured bacterium, microbial mat FR666863, uncultured bacterium, microbial mat FR666862, uncultured bacterium, microbial mat JQ712383, uncultured epsilon proteobacterium, hydrothermal vent fluids ARB_7969B766, denovo561 GI2.1_1182 FR666864, uncultured bacterium, microbial mat Gq261829, uncultured epsilon proteobacterium, deep sea sediment whale falls FR666869, uncultured bacterium, microbial mat Gu061298, uncultured epsilon proteobacterium, Yellow Sea intertidal beach FR683719, uncultured marine bacterium, marine biome, fjord, coastal water He576783, uncultured epsilon proteobacterium, biorector inoculated microbial mat KF799694, uncultured bacterium, gut KF799695, uncultured bacterium, gut KF799571, uncultured bacterium, gut ARB_B31CB100, denovo3137 GII1.1_1105 AY548997, uncultured bacterium, marine environment Fn429802, uncultured epsilon proteobacterium, marine sediments (1.1 mbsf) Jf268371, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae JQ712406, uncultured epsilon proteobacterium, hydrothermal vent fluids AB189374, uncultured epsilon proteobacterium, cold seep sediment JQ712417, uncultured epsilon proteobacterium, hydrothermal vent fluids JQ712419, uncultured epsilon proteobacterium, hydrothermal vent fluids JQ712382, uncultured epsilon proteobacterium, hydrothermal vent fluids 6 uncultured JX521734, uncultured bacterium, terrestrial sulfidic spring 4 uncultured uncultured JX521782, uncultured bacterium, terrestrial sulfidic spring Ay922188, uncultured epsilon proteobacterium, grey whale bone 22 uncultured

9 uncultured Gu061286, uncultured epsilon proteobacterium, Yellow Sea intertidal beach ARB_F642CBD4, denovo370 GI2.1_670 Gu061291, uncultured epsilon proteobacterium, Yellow Sea intertidal beach seawater EU050947, uncultured bacterium, sediment from the Kings Bay, Svalbard, Arctic KF799046, uncultured bacterium, gut Eu573099, bacterium enrichment culture clone EB24.3, North Sea, Ekofisk oil field JQ862033, uncultured epsilon proteobacterium JX391668, uncultured bacterium, marine sediment JX391694, uncultured bacterium, marine sediment EF999357, uncultured bacterium, Pearl River Estuary sediments at 6cm depth JN018454, uncultured bacterium, Gulf of Mexico stable isotope probing incubations Jn233497, uncultured marine bacterium, ocean water Cape Lookout, NC from 505m depth KC682345, uncultured bacterium, substrate mineral chips KC682364, uncultured bacterium, substrate mineral chips AB015529, uncultured epsilon proteobacterium, deep−sea sediments from different depths Jn233480, uncultured marine bacterium, ocean water continental slope off Cape Lookout ARB_87561165, denovo588 GI3.1_1443 AJ810558, uncultured epsilon proteobacterium, superficial sediments 4 uncultured Dq357825, epsilon proteobacterium Oy−M7, adult oyster mantle EF645952, uncultured bacterium, Namibian upwelling system EF028937, uncultured bacterium, Zostera marina roots GU584643, uncultured bacterium, marine hydrocarbon seep sediment Fj717168, uncultured bacterium, marine sediment from Cullercoats, Northumberland Fj717163, uncultured bacterium, marine sediment from Cullercoats, Northumberland JQ586324, uncultured bacterium, arctic marine sediment ARB_21BC0A68, denovo2795 GI2.1_5638 EU142059, uncultured bacterium, methane seep sediment EU236320, uncultured bacterium, 13 m depth in the Pacific Ocean 50 uncultured

6 uncultured L42994, Arcobacter sp. Solar Lake, cyanobacterial mat from hypersaline lake EF031096, uncultured bacterium, endorheic hypersaline atalasohaline lake EF031092, uncultured bacterium, endorheic hypersaline atalasohaline lake EU512920, Arcobacter marinus, seawater associated with starfish JX403054, uncultured bacterium, bitumen FN356234, uncultured bacterium, oil production water Eu573100, bacterium enrichment culture clone EB27.1, North Sea, Ekofisk oil field FR675876, Arcobacter molluscorum FR675875, Arcobacter molluscorum FR675874, Arcobacter molluscorum CECT 7696 AB893930, uncultured bacterium, digestive tract JN596130, bacterium A1(2011) JN596128, bacterium A2(2011b) ARB_18DB62B1, denovo487 GI2.1_2840 ARB_3F2E08E3, denovo592 GII2.1_8864 EU669904, Arcobacter mytili, mussels HG792246, uncultured bacterium, intestinal contents of Chinese Mitten Crab AF513455, Arcobacter halophilus KF268902, uncultured bacterium, marine sediment FJ202783, uncultured bacterium, Montastraea faveolata kept in aquarium for 23 days 7 uncultured KC527432, uncultured bacterium, White Plague Disease infected coral 25 uncultured

4 uncultured

AJ271655, Arcobacter sp. A3b2 _Arcobacter EU142043, uncultured bacterium, methane seep sediment AJ271654, Arcobacter sp. D1a1 9 uncultured FR683715, uncultured marine bacterium, marine biome, fjord, coastal water AJ810559, uncultured epsilon proteobacterium, superﬁcial sediments ARB_DD34D980, denovo2326 GII2.1_3882 Fj717102, uncultured bacterium, marine sediment from Cullercoats, Northumberland Fj717122, uncultured bacterium, marine sediment from Cullercoats, Northumberland HQ203797, uncultured bacterium, seawater EU052239, uncultured epsilon proteobacterium, anode from microbial fuel cell fed with marine plankton GU584648, uncultured bacterium, marine hydrocarbon seep sediment 15 uncultured

26 uncultured AB530236, uncultured bacterium, marine sediment FR666867, uncultured bacterium, microbial mat Jf344171, uncultured epsilon proteobacterium, petroleum spot over marine sediments EU245155, uncultured organism, hypersaline microbial mat EF123613, uncultured epsilon proteobacterium, black band diseased (BBD) coral tissues JX570599, endosymbiont of Ridgeia piscesae DQ218324, uncultured Arcobacter sp., microbial mat 15 uncultured Campylobacterales_Campylobacteraceae FJ628351, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 28 FR666871, uncultured bacterium, microbial mat ARB_2017809, denovo3313 GII3.1_10544 HM057719, uncultured bacterium, ocean water from the Yellow Sea CP001999, Arcobacter nitrofigilis DSM 7299, roots L14627, Arcobacter nitrofigilis CP001999, Arcobacter nitrofigilis DSM 7299, roots CP001999, Arcobacter nitrofigilis DSM 7299, roots CP001999, Arcobacter nitrofigilis DSM 7299, roots Eu106661, Arcobacter nitrofigilis JX403044, uncultured bacterium, bitumen JF904743, uncultured Arcobacter sp., mangrove soil EF648116, uncultured Arcobacter sp., aerobic activated sludge HQ203800, uncultured bacterium, seawater JN118552, Arcobacter sp. sw028, a−surface water of South Pacific HM057804, uncultured epsilon proteobacterium, ocean water from the Yellow Sea HM057749, uncultured epsilon proteobacterium, ocean water from the Yellow Sea HM057779, uncultured epsilon proteobacterium, ocean water from the Yellow Sea HQ203831, uncultured bacterium, seawater JQ712049, uncultured bacterium, surface seawater offshore Qingdao JQ712030, uncultured bacterium, surface seawater offshore Qingdao JQ712046, uncultured bacterium, surface seawater offshore Qingdao HM057765, uncultured epsilon proteobacterium, ocean water from the Yellow Sea JQ712055, uncultured bacterium, surface seawater offshore Qingdao AM084114, Arcobacter sp. R−28314 JQ845784, uncultured Arcobacter sp., wash water from wash basin 2 of a spinach−processing plant HE565359, Arcobacter venerupis, Sea ARB_AD7A5D23, denovo709 GI1.1_4652 JQ845782, uncultured Arcobacter sp., wash water from wash basin 2 of a spinach−processing plant DQ234254, uncultured Arcobacter sp., mangrove HM057679, uncultured epsilon proteobacterium, ocean water from the Yellow Sea FJ946551, uncultured epsilon proteobacterium, arctic meltwater JX403059, uncultured bacterium, bitumen HQ860689, uncultured bacterium, stream water FJ612319, uncultured bacterium, lake water 44 uncultured JQ845771, uncultured Arcobacter sp., wash water from wash basin 2 of a spinach−processing plant group DQ234101, uncultured Arcobacter sp., mangrove FN428747, uncultured bacterium, Mahananda river water FR691497, uncultured bacterium, Mahananda river sediment HQ860691, uncultured bacterium, stream water 21 uncultured

26 mainly uncultured including Arcobacter butzleri JX912503, Arcobacter butzleri AM084124, Arcobacter sp. R−28214 JQ086899, uncultured Arcobacter sp., push core sediment sample from the vadose zone of a hydrocarbon contaminated aquifer JF497852, uncultured bacterium, activated sludge JN397809, uncultured bacterium, river bank Z93999, uncultured bacterium 44 uncultured JF915357, Arcobacter cryaerophilus HQ860539, uncultured bacterium, stream water KF703990, Arcobacter sp. 69948, American crow feces EU560811, uncultured bacterium, intestinal ﬂora AF324539, uncultured epsilon proteobacterium BioIuz K34 AB355029, uncultured bacterium, surface water, Manzallah Lake CU925313, uncultured bacterium, mesophilic anaerobic digester which treats municipal wastewater sludge CU926906, uncultured bacterium, mesophilic anaerobic digester which treats municipal wastewater sludge CU924753, uncultured bacterium, mesophilic anaerobic digester which treats municipal wastewater sludge

62 uncultured

JQ213140, uncultured bacterium, bottlenose dolphin mouth FJ959725, uncultured bacterium, blowhole 20 uncultured 19 uncultured 4 uncultured JQ611225, uncultured bacterium, venting fluid in yellow vent off Kueishan Island KC527475, uncultured bacterium, White Plague Disease infected coral AY035822, Candidatus Arcobacter sulfidicus 9 uncultured AF144693, oilfield bacterium ’FWKO B’ 7 uncultured JQ712410, uncultured epsilon proteobacterium, hydrothermal vent fluids JQ712384, uncultured epsilon proteobacterium, hydrothermal vent fluids AY542568, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment ARB_34C3AB2A, denovo2381 GI2.1_228 AF458287, uncultured epsilon proteobacterium, Mono Lake, California Figure S6b: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobacteria, order: Campylobacterales family: Campylobacteraceae, genus: Acrobacter (black bold: sequences retrieved in this study and closest relatives). 141 Chapter 5

AFRZ01000001, Sulfurimonas gotlandica GD1, sulfidic area of central Baltic Sea Fj717113, uncultured bacterium, marine sediment from Cullercoats, Northumberland Fj717120, uncultured bacterium, marine sediment from Cullercoats, Northumberland JQ712116, uncultured bacterium, oil−contaminated seawater KF268813, uncultured bacterium, marine sediment KF268857, uncultured bacterium, marine sediment Ay922189, uncultured epsilon proteobacterium, grey whale bone, Pacific Ocean, Santa Cruz Basin GQ261771, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls 3 uncultured JQ287474, uncultured bacterium, East Pacific Rise JQ287473, uncultured bacterium, East Pacific Rise 9 uncultured JQ287433, uncultured bacterium, East Pacific Rise KC492834, uncultured Sulfurimonas sp., Baltic Sea redoxcline, 119 m depth 3 uncultured ARB_CC0227FD, denovo2021 GI2.1_1757 JX521790, uncultured bacterium, terrestrial sulfidic spring FJ497608, uncultured epsilon proteobacterium, Vailulu’u Seamount HQ729106, uncultured epsilon proteobacterium, bacterial mat FJ497591, uncultured bacterium, Vailulu’u Seamount JX521773, uncultured bacterium, terrestrial sulfidic spring Fj717063, uncultured bacterium, marine sediment from Cullercoats, Northumberland JX521779, uncultured bacterium, terrestrial sulfidic spring 8 uncultured HQ729098, uncultured epsilon proteobacterium, bacterial mat JX521774, uncultured bacterium, terrestrial sulfidic spring Fj717036, uncultured bacterium, marine sediment from Cullercoats, Northumberland HQ729096, uncultured epsilon proteobacterium, bacterial mat Fj717079, uncultured bacterium, marine sediment from Cullercoats, Northumberland Gu120613, uncultured epsilon proteobacterium, active mining area Fj717049, uncultured bacterium, marine sediment from Cullercoats, Northumberland ARB_FD05D18F, denovo2886 GI1.1_2548 Fj717093, uncultured bacterium, marine sediment from Cullercoats, Northumberland AM982624, uncultured bacterium, pig saw dust spent bedding Fj717084, uncultured bacterium, marine sediment from Cullercoats, Northumberland Fj037619, uncultured bacterium, biofilms of iron−ixodizing bacteria FJ717065, uncultured bacterium, marine sediment from Cullercoats, Northumberland JN637800, uncultured marine microorganism, middle port Fj717096, uncultured bacterium, marine sediment from Cullercoats, Northumberland Jn662232, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae Fj717067, uncultured bacterium, marine sediment from Cullercoats, Northumberland ARB_E5EE2E71, denovo1628 GI2.1_503 11 uncultured JN637811, uncultured marine microorganism, middle port GU583978, uncultured bacterium, mangrove soil DQ228650, uncultured bacterium, sulfide−microbial incubator HM057666, uncultured bacterium, ocean water from the Yellow Sea GQ261797, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls EF444735, uncultured bacterium, Thermopiles hot springs 4 uncultured JX403049, uncultured bacterium, bitumen JX403058, uncultured bacterium, bitumen AB176067, uncultured bacterium, PCR−derived sequence from vent area water FJ535290, uncultured bacterium, iron mat AB176111, uncultured bacterium, PCR−derived sequence from vent area water FJ535325, uncultured bacterium, sediment AB176109, uncultured bacterium, PCR−derived sequence from vent area water AB189712, Alviniconcha sp. gill symbiont AY704397, uncultured bacterium, oceanic crust DQ228648, uncultured bacterium, sulfide−microbial incubator ARB_4672D8F7, denovo1916 GI2.1_90 Ay251059, uncultured proteobacterium, deep−sea hydrothermal vent biofilm from the Edmond vent field EU487967, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed DQ925870, uncultured bacterium, hydrothermal vent chimneys of Guaymas Basin FJ624448, uncultured bacterium, Lau Basin hydrothermal vent sediment AB252048, Sulfurimonas paralvinellae, Paralvinella sp. polychaetes’ nest GQ848475, uncultured bacterium, deep sea hydrothermal vent sediment Jn873966, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise GQ848408, uncultured bacterium, deep sea hydrothermal vent sediment Jn874012, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise GU198381, bacterium enrichment culture clone 16S−9, marine sediment Jn874124, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise JX120496, uncultured bacterium, subsurface aquifer sediment Jn874136, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise ARB_40E96DC5, denovo1140 GI2.1_3851 Jn874166, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise AB176113, uncultured bacterium, PCR−derived sequence from vent area water Ay280406, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca Ridge GQ349272, uncultured epsilon proteobacterium, Saanich Inlet, 120 m depth AY672505, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean Fj717167, uncultured bacterium, marine sediment from Cullercoats, Northumberland Jn662183, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environment JQ287448, uncultured bacterium, East Pacific Rise JQ712432, uncultured epsilon proteobacterium, hydrothermal vent fluids Jn873929, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise JQ712447, uncultured epsilon proteobacterium, hydrothermal vent fluids Ab193899, uncultured bacterium, obtained from Mariana Trough hydrothermal vent water AY225611, uncultured epsilon proteobacterium, organic−rich substrate exposed to a Mid−Atlantic Ridge vent Jn874362, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise Jn873940, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise 23 uncultured AB015257, unidentified epsilon proteobacterium, deepest cold−seep area of the Japan Trench ARB_EC842CDC, denovo3733 GII1.1_1431 EF036297, uncultured bacterium, Zostera marina roots Jn874097, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise AJ515712, uncultured epsilon proteobacterium ARB_C5F1B8A5, denovo885 GI3.1_315 AJ515713, uncultured epsilon proteobacterium AY211683, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment JQ712418, uncultured epsilon proteobacterium, hydrothermal vent fluids JQ712411, uncultured epsilon proteobacterium, hydrothermal vent fluids Jn662192, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae 5 uncultured AY216438, uncultured bacterium, temperate estuarine mud KF465274, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard FJ497252, uncultured epsilon proteobacterium, Vailulu’u Seamount EU574677, uncultured bacterium, hydrothermal vent mat; Champagne Vent on N.W. Eifuku JN637808, uncultured marine microorganism, middle port AY211663, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment JN637788, uncultured marine microorganism, middle port GQ357037, uncultured bacterium, methane seep sediment FJ497618, uncultured gamma proteobacterium, Vailulu’u Seamount GQ357021, uncultured bacterium, methane seep sediment HQ203919, uncultured bacterium, seawater AB013263, uncultured epsilon proteobacterium, Nankai Trough sediments at a depth of 3,843m FJ497584, uncultured delta proteobacterium, Vailulu’u Seamount ARB_3F56C503, denovo1533 GI2.1_190 FJ535288, uncultured bacterium, iron mat AY225612, uncultured epsilon proteobacterium, organic−rich substrate exposed to a Mid−Atlantic Ridge vent Hq153998, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal vent 25 mainly uncultured including Sulfurimonas autotrophica AB188787, uncultured Helicobacter sp., cold seep sediment FN553987, uncultured sediment bacterium, Logatchev hydrothermal vent field,site F, watercolumn depth = 3000 m FJ535336, uncultured bacterium, sediment Fn554146, uncultured sediment bacterium, Logatchev hydrothermal vent field,Anya’s Garden FJ535346, uncultured bacterium, sediment Jn874121, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise DQ394918, uncultured epsilon proteobacterium, harbor sediment JQ712373, uncultured epsilon proteobacterium, hydrothermal vent fluids ARB_251565CE, denovo454 GII2.1_1533 FJ535303, uncultured bacterium, iron mat JX391546, uncultured bacterium, marine sediment JN874138, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N Ab697024, uncultured bacterium, Bacterial mat Jn874070, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise Jq723654, uncultured Campylobacterales bacterium, biofilm KC682592, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin _Sulfurimonas AF068806, uncultured bacterium VC2.1 Bac32 JQ712437, uncultured epsilon proteobacterium, hydrothermal vent fluids EF644801, uncultured bacterium, MAR Logatchev hydrothermal vent system, 3000m water depth, sulfide sample KF464524, uncultured bacterium, Alang−Sosiya ship breaking yard AF367490, uncultured epsilon proteobacterium KF624354, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea AF367496, uncultured epsilon proteobacterium GQ848454, uncultured bacterium, deep sea hydrothermal vent sediment AY225613, uncultured epsilon proteobacterium, pumice fragments exposed to a Mid−Atlantic Ridge vent GQ848449, uncultured bacterium, deep sea hydrothermal vent sediment EU574671, uncultured bacterium, hydrothermal vent mat; Champagne Vent on N.W. Eifuku JN874382, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’N EU574674, uncultured bacterium, hydrothermal vent mat; Champagne Vent on N.W. Eifuku JN874185, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’N JN874190, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’N 21 uncultured JN873941, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N EU491825, uncultured bacterium, seafloor lavas from the East Pacific Rise JX391632, uncultured bacterium, marine sediment EU491791, uncultured bacterium, seafloor lavas from the East Pacific Rise KF624431, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea EU491826, uncultured bacterium, seafloor lavas from the East Pacific Rise Fr853059, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge DQ070790, uncultured epsilon proteobacterium, basalt glass from 9N latitude East Pacific Rise Jq072913, uncultured prokaryote, active sulfide structures Juan de Fuca Ridge EU491816, uncultured bacterium, seafloor lavas from the East Pacific Rise Fr852963, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge EU491792, uncultured bacterium, seafloor lavas from the East Pacific Rise Fr853045, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge GQ848457, uncultured bacterium, deep sea hydrothermal vent sediment ARB_E46846F5, denovo2532 GII1.1_85 JN873959, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N Fr852998, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge JQ287099, uncultured bacterium, East Pacific Rise ARB_D69AC317, denovo4058 GII1.1_2141 JQ586308, uncultured bacterium, arctic marine sediment Fr852969, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge ARB_8340C096, denovo2767 GII2.1_5839 FJ497579, uncultured bacterium, Vailulu’u Seamount KF624353, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea DQ145977, bacterium ML2−86 KF624411, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea JX391568, uncultured bacterium, marine sediment KF624438, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea GQ261791, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls KF624409, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea EF999352, uncultured bacterium, Pearl River Estuary sediments at 6cm depth Fj717137, uncultured bacterium, marine sediment from Cullercoats, Northumberland AY218555, uncultured bacterium Fj717173, uncultured bacterium, marine sediment from Cullercoats, Northumberland EF219007, uncultured bacterium, Ridge Flank Abyssal Hill hydrothermal site on the east Pacific rise EF219001, uncultured bacterium, Ridge Flank Abyssal Hill hydrothermal site on the east Pacific rise 18 uncultured JQ287049, uncultured bacterium, East Pacific Rise Fj717179, uncultured bacterium, marine sediment from Cullercoats, Northumberland JQ036261, uncultured bacterium, Eel River Basin sediment 2688 Fj717157, uncultured bacterium, marine sediment from Cullercoats, Northumberland EF687416, uncultured bacterium, sulfide−oxidizing mat, Chefren mud volcano, Nile Deep Sea Fan, Eastern Mediterranean

FJ615170, uncultured epsilon proteobacterium, Saanich Inlet, depth of 10m in anoxic marine fjord Campylobacteraceae AJ441199, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions ARB_1401C19A, denovo2596 GI1.1_1762 EU652648, uncultured bacterium, Yellow Sea sediment EU652653, uncultured bacterium, Yellow Sea sediment EU662310, uncultured bacterium, microbial mat FJ535347, uncultured bacterium, sediment AJ441200, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions KF465277, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard DQ676325, uncultured epsilon proteobacterium, suboxic freshwater−pond sediment KF465242, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard KF464419, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard KF464511, uncultured bacterium, Alang−Sosiya ship breaking yard JQ611140, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island GU369904, uncultured epsilon proteobacterium, white filamentous microbial mat in the photic region of a shallow hydrothermal vent AF355050, uncultured epsilon proteobacterium KF465252, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard AY225615, uncultured epsilon proteobacterium, iron−rich substrate exposed to a Mid−Atlantic Ridge vent EF379628, uncultured bacterium, sea water from Victoria Harbor (Hong Kong) area EF441903, uncultured epsilon proteobacterium, endolithic community in the acidic Rio Tinto basin ARB_3223D2E0, denovo508 GI3.1_1312 DQ071281, uncultured epsilon proteobacterium, deep−sea hydrothermal vent KF624336, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea DQ071286, uncultured epsilon proteobacterium, deep−sea hydrothermal vent GQ261804, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls DQ228651, uncultured bacterium, sulfide−microbial incubator AY922185, uncultured epsilon proteobacterium, grey whale bone, Pacific Ocean, Santa Cruz Basin (N33.30 W119.22) depth 1674 meters KC682636, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin KF624343, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea JQ611149, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island ARB_C6318A, denovo1788 GI1.1_3689 DQ395005, uncultured epsilon proteobacterium, harbor sediment 49 mainly uncultured including Sulfurimonas denitrificans EU652651, uncultured bacterium, Yellow Sea sediment ARB_5EA6F342, denovo917 GI2.1_381 AY532543, uncultured bacterium, uranium−contaminated aquifer ARB_53282A96, denovo2773 GII2.1_8103 FJ628245, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 50 ARB_1615A492, denovo2370 GI2.1_3681 FJ628235, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 37.5 EU652650, uncultured bacterium, Yellow Sea sediment KC682581, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin GQ349003, uncultured epsilon proteobacterium, Saanich Inlet, 100 m depth ARB_314DFE6B, denovo3359 GII3.1_4254 GQ261792, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls AY672532, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean FJ497261, uncultured bacterium, Vailulu’u Seamount JQ611150, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island KF545003, uncultured Sulfurimonas sp., deep−sea sediment AJ441204, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions JN977221, uncultured bacterium, Jiaozhao Bay sediment AJ575997, uncultured epsilon proteobacterium, deep sea hydrothermal vent AB530237, uncultured bacterium, marine sediment FJ628204, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 37.5 KF624267, uncultured bacterium, anoxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea Ay251063, uncultured proteobacterium, deep−sea hydrothermal vent biofilm from the Edmond vent field KF624342, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea JQ586311, uncultured bacterium, arctic marine sediment KF624358, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea ARB_FBD03AE6, denovo1223 GI2.1_522 JQ196547, uncultured bacterium, seawater; next to dolphin E FJ628251, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 50 ARB_77205F9F, denovo889 GI2.1_254 KF624356, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea JQ586310, uncultured bacterium, arctic marine sediment ARB_7A60E850, denovo2375 GI2.1_220 FJ205271, uncultured epsilon proteobacterium, active hydrothermal field sediments, depth:1922m ARB_97CD83C8, denovo1803 GII3.1_2388 EU652667, uncultured bacterium, Yellow Sea sediment FJ535253, uncultured bacterium, iron mat EU266014, uncultured bacterium, Nitinat Lake at a depth of 26 m AJ575998, uncultured epsilon proteobacterium, deep sea hydrothermal vent KF801506, uncultured epsilon proteobacterium ARB_DFCFDB0A, denovo1215 GI1.1_2525 mainly uncultured related to Sulfuricurvum AJ441201, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions Jn662179, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environment DQ890422, uncultured bacterium, empty intestine 256 AJ441198, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions HM154512, uncultured bacterium, Yellowstone Lake hydrothermal vent biofilm HM154504, uncultured bacterium, Yellowstone Lake hydrothermal vent biofilm GU291331, uncultured bacterium, acid mine drainage contaminated salt marsh sediments 7 uncultured Kc682699, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney JQ287031, uncultured bacterium, East Pacific Rise GU291328, uncultured bacterium, acid mine drainage contaminated salt marsh sediments GU291330, uncultured bacterium, acid mine drainage contaminated salt marsh sediments JX403024, uncultured bacterium, underground water Kf624439, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat

Figure S6c: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobac- teria, order: Campylobacterales family: Campylobacteraceae, genus: Sulfurimonas (black bold: sequences retrieved in this study and closest relatives). 142 X82931, Sulfurospirillum multivorans JQ713915, uncultured Sulfurospirillum sp., sediments from shallow hydrothermal vents CP007201, Sulfurospirillum multivorans DSM 12446 CP007201, Sulfurospirillum multivorans DSM 12446 JX403043, uncultured bacterium, surface water JX521007, uncultured bacterium, terrestrial sulfidic spring Eu864435, uncultured bacterium, Xiao River wastewater Jq087039, uncultured Sulfurospirillum sp.,sedimenthydrocarbon contaminated aquifer AY570615, uncultured bacterium, low−temperature biodegraded Canadian oil reservoir JX521473, uncultured bacterium, terrestrial sulfidic spring JX521469, uncultured bacterium, terrestrial sulfidic spring JN685481, uncultured bacterium, production water sample from oil well JF304793, uncultured Sulfurospirillum sp., mining wastewater Fq659417, uncultured soil bacterium, PAH−contaminated soil; retention systems HM481314, uncultured bacterium, TCE−contaminated field site FJ612331, uncultured bacterium, lake water CU922216, uncultured bacterium, mesophilic anaerobic digester Dq295746, uncultured epsilon proteobacterium, microbial mat in sulfidic spring Dq295743, uncultured epsilon proteobacterium, microbial mat in sulfidic spring AB355036, uncultured bacterium, surface water, Manzallah Lake JF747911, uncultured bacterium, Frasassi cave system sulfidic spring AB355034, uncultured bacterium, surface water, Manzallah Lake AB186804, uncultured bacterium, uncultured clone from polychlorinated dioxin dechlorinating microcosm AY756596, uncultured bacterium, Siwhaho sediment Jx271945, uncultured bacterium, activated sludge in lab−scale reactor JX521449, uncultured bacterium, terrestrial sulfidic spring Fq660045, uncultured soil bacterium, PAH−contaminated soil Fq659173, uncultured soil bacterium, PAH−contaminated soil Af144694, Campylobacter sp. DSM 806 Fq659063, uncultured soil bacterium, PAH−contaminated soil L14632, Campylobacter sp. Jx462539, uncultured Campylobacter sp., methanogenic bioelectrochemical reactor AY780560, uncultured Sulfurospirillum sp., chlorinated ethene−degrading culture FJ612315, uncultured bacterium, lake water AY189928, Sulfurospirillum sp. JPD−1 FQ659988, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs FQ659274, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs HM481322, uncultured bacterium, TCE−contaminated field site JF789596, uncultured Sulfurospirillum sp., Athabasca oil sands formation water FJ612310, uncultured bacterium, lake water DQ234114, uncultured Sulfurospirillum sp., mangrove FJ612314, uncultured bacterium, lake water FJ612328, uncultured bacterium, lake water FJ612333, uncultured bacterium, lake water FJ612317, uncultured bacterium, lake water KF933844, Sulfurospirillum sp. b10 KF933843, Sulfurospirillum sp. b1 DQ234236, uncultured Sulfurospirillum sp., mangrove AY756183, arsenate−reducing bacterium NP4, groundwater JX521339, uncultured bacterium, terrestrial sulfidic spring FQ659969, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs AB368775, Sulfurospirillum deleyianum AB286550, uncultured bacterium, activated sludge AB246781, Sulfurospirillum cavolei, underground crude−oil storage cavity Jx000050, uncultured bacterium, anaerobic wastewater reactor Jx271924, uncultured bacterium, activated sludge in lab−scale reactor with dissolved oxygen above 2.5 mg/l AJ488086, uncultured bacterium Kc179071, uncultured bacterium, activated sludge taken from a microaerobic bioreactor KF836224, uncultured bacterium, springs and wells fed by a deep, fractured rock aquifer in the Mojave Desert AF038843, Sulfurospirillum barnesii U41564, Sulfurospirillum barnesii CP003333, Sulfurospirillum barnesii SES−3, selenate−contaminated freshwater marsh sediment Cp003333, Sulfurospirillum barnesii SES−3, selenate−contaminated freshwater marsh sediment AJ535704, Sulfurospirillum sp. EK7, river sediment Y13671, Sulfurospirillum deleyianum CP001816, Sulfurospirillum deleyianum DSM 6946 CP001816, Sulfurospirillum deleyianum DSM 6946 CP001816, Sulfurospirillum deleyianum DSM 6946 AJ249226, bacterium DCE10 GU120580, uncultured epsilon proteobacterium, active mining area of Pitch Lake EU662599, uncultured bacterium, floating microbial mat from sulfidic water JX399885, Sulfuricurvum sp. L12, enrichment culture of coal−tar from a natural coal−tar source Am157656, epsilon proteobacterium AN−BI3A, hypersaline brine and seawater in the Mediterranean. HM468037, uncultured bacterium, solid waste with green color in tanning process before Cr recovery FN356324, uncultured bacterium, oil production water FN356312, uncultured bacterium, oil production water DQ228139, Sulfurospirillum sp. C6, bioreactor inoculated with oil field produced water AY570614, uncultured bacterium, low−temperature biodegraded Canadian oil reservoir AY570602, uncultured bacterium, low−temperature biodegraded Canadian oil reservoir GQ863490, Sulfurospirillum alkalitolerans AY570598, uncultured bacterium, low−temperature biodegraded Canadian oil reservoir AY570558, uncultured bacterium, low−temperature biodegraded Canadian oil reservoir Jx898111, uncultured bacterium, series of continously fed aerated tank reactors system Gq133407, uncultured bacterium, ASBR reactor treating swine waste GQ415373, uncultured bacterium, Daqing oilfield production water AB546014, uncultured bacterium, #AR39 oil wellhead JQ088439, uncultured bacterium, crude oil reservoir JQ214236, uncultured bacterium, bottlenose dolphin mouth JQ214253, uncultured bacterium, bottlenose dolphin mouth JQ215461, uncultured bacterium, bottlenose dolphin mouth AB546035, uncultured bacterium, #AR39 oil wellhead AB546080, uncultured bacterium, #SR123 oil wellhead AB192073, uncultured epsilon proteobacterium, Microcerotermes sp. 2 AB192072, uncultured epsilon proteobacterium, Microcerotermes sp. 1 AJ576349, uncultured bacterium, hindgut homogenate of Pachnoda ephippiata larva AB231076, uncultured epsilon proteobacterium, Neotermes koshunensis JN619494, uncultured bacterium, insect gut Sulfurospirillum JN620073, uncultured bacterium, insect gut AB234540, uncultured epsilon proteobacterium, Macrotermes gilvus FJ792313, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792353, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792370, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ791985, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792434, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792359, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field ACQI01000338, hydrothermal vent metagenome, Lost City hydrothermal chimney biofilm FJ792218, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792357, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792283, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field FJ792210, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field KC682802, uncultured bacterium, surface of a basalt collected from Kilo Moana vent field, Lau Basin JN637820, uncultured marine microorganism, middle port ARB_E5A35806, denovo3111 GII1.1_6079 JX391284, uncultured bacterium, marine sediment JX391327, uncultured bacterium, marine sediment U85965, Sulfurospirillum sp. SM−5 AF367491, uncultured epsilon proteobacterium Fn773278, bacterium endosymbiont of Osedax mucofloris, Osedax mucofloris extacted from whale bone AY548994, uncultured bacterium, marine environment FN658698, epsilon proteobacterium ectosymbiont of Rimicaris FJ717081, uncultured bacterium, marine sediment from Cullercoats, Northumberland FJ497338, uncultured bacterium, Vailulu’u Seamount FJ814746, uncultured Campylobacterales bacterium, Carmel Canyon ARB_E2983623, denovo180 GII3.1_8793 FJ497463, uncultured epsilon proteobacterium, Vailulu’u Seamount FJ535312, uncultured bacterium, iron mat AY211681, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment Y11561, Sulfurospirillum arcachonense GU220754, uncultured bacterium, low temperature hydrothermal precipitates of East Lau Spreading Center ARB_9981C26F, denovo2147 GII3.1_1394 AF357198, Sulfurospirillum sp. Am−N AF357199, Sulfurospirillum sp. 18.1 HM128339, uncultured bacterium, Xiaochaidan Lake AF513952, uncultured Sulfurospirillum sp., Hawaiian lake water AB550501, uncultured Sulfurospirillum sp. FJ497442, uncultured epsilon proteobacterium, Vailulu’u Seamount JQ287455, uncultured bacterium, East Pacific Rise JQ286985, uncultured bacterium, East Pacific Rise JQ287296, uncultured bacterium, East Pacific Rise JQ287108, uncultured bacterium, East Pacific Rise KC682703, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau Basin JQ611155, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island KC682704, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau Basin FJ497620, uncultured bacterium, Vailulu’u Seamount Ay280408, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca Ridge KC357921, uncultured bacterium, large−discharge carbonate springs Jn662188, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environment Ef462744, uncultured bacterium, dorsal surface of the deep sea hydrothermal vent polychaete worm Alvinella pompejana 6 Thiofractor 0.10 Figure S6d: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobacte- ria, order: Campylobacterales family: Campylobacteraceae, genus: Sulfurospirillum (black bold: sequences retrieved in this study and closest relatives). 143 Chapter 5 Supplementary Material

Figure S7: Characteristic PLFA profiles of (a) the average relative concentration of PLFAs for March (0–0.5 cm and 2–4 cm) and August (0–1 cm), (b) the average Δδ 13C values and (c) relative 13C incorporation of PLFAs for S2 and S1/S3 March (0–1 cm). 144

6. Potential recycling of thaumarchaeotal lipids by DPANN archaea in seasonally hypoxic surface marine sediments

Yvonne A. Lipsewers, Ellen C. Hopmans, Jaap S. Sinninghe Damsté, and Laura Villanueva

Thaumarchaeota are known to synthesize specific glycerol dibiphytanyl glycerol tetraethers (GDGTs), the distribution of which is affected by temperature which forms the base of the paleotemperature proxy TEX86. Lipids present in the marine surface sediments are believed to be mostly derived from pelagic Thaumarchaeota; however, some studies have evaluated the possibility that benthic archaea also contribute to the lipid fossil record. Here, we compared the archaeal abundance and composition by DNA-based methods and the archaeal intact polar lipid (IPL) diversity in surface sediments of a seasonally hypoxic marine lake to determine the potential biological sources of the archaeal IPLs detected in surface sediments under changing environmental conditions. The archaeal community changed from March (oxic conditions) to August (euxinic) from a Thaumarchaeota-dominated (up to 82%) to an archaeal community dominated by the DPANN superphylum (up to 95%). This marked change coincided with a one order of magnitude decrease in the total IPL-GDGT abundance. In addition, the polar head groups of the IPL-GDGTs changed from predominantly containing phospho- to glyco- polar head groups. This may indicate a transition to Thaumarchaeota growing in stationary phase or selective preservation of the GDGT pool. However, considering the apparent inability of the DPANN archaea to synthesize their own membrane lipids, we hypothesize that an alternative explanation might be that DPANN archaea use the lipids previously synthesized by the Thau- marchaeota to form their own cell membranes, which would indicate an active recycling of fossil IPLs in the marine surface sediment.

Submitted to Organic Geochemistry

147 Chapter 6

6.1. Introduction Archaea occur ubiquitously, are abundant in aquatic and terrestrial habitats, and play an important role in global biogeochemical cycles (Jarrell et al., 2011). Marine sediments have been shown to harbor a diverse archaeal community, of which ammonia-oxidizing Thaumarchaeota (marine group I.1a) are the most studied (Pester et al., 2011). Recent genomic studies have revealed the presence of other benthic archaeal groups, such as Miscellaneous Crenarchaeota Group (MCG), Marine Benthic Group-B and D, and archaea of the DPANN superphylum, in marine sediments, which are predicted to be involved in degradation of polymers and proteins under anoxic conditions (Castelle et al., 2015; Lloyd et al., 2013, Meng et al., 2014). Archaeal lipids occur widespread in marine sediments and are commonly used as biomarkers of Archaea both in present-day systems and in past depositional environments. However, their biological sources are not well constrained, especially in the light of the expanding archaeal diversity. Archaeal lipids in marine surface sediments are thought to be derived mainly from pelagic Thaumarchaeota, which due to grazing and packing in fecal pellets are efficiently transported to the sediment where they get preserved in the sedimentary record (Huguet et al., 2006b). Thaumarchaeota are known to synthesize isoprenoid glycerol dibiphytanyl glycerol tetraether (GDGT) containing 0–4 cyclopentane moieties (GDGT-0 to GDGT-4) as well as the GDGT crenarchaeol (Sinninghe Damsté et al., 2002), containing four cyclopentane moieties and a cyclohexane moiety, which is considered to be characteristic of this phylum (Pearson et al., 2004; Zhang et al., 2006; Pester et al., 2011; Pitcher et al., 2011a; Sinninghe Damsté et al., 2012). The distribution of thaumarchaeotal GDGTs in the marine environment has been shown to be affected by temperature, i.e. with increasing temperature there is an increase in the relative abundance of cyclopentane-containing GDGTs (Schouten et al., 2002; Wuchter et al., 2004, 2005).

Based on this relationship, the TEX86 paleotemperature proxy was developed and calibrated on sea surface temperature (e.g. Schouten et al., 2002; Kim et al., 2010) and it has been widely applied for more than a decade (Schouten et al., 2013). Although it is generally thought that GDGTs in marine sediments derive from surface-derived thaumarchaeotal biomass (e.g. Wakeham et al., 2003), some studies have addressed the possibility of a potential contribution of lipids from benthic archaea to the fossil record, which would be relevant for the reliability of TEX86 (Shah et al., 2008; Biddle et al., 2006; Lipp et al., 2008; Lipp and Hinrichs, 2009). Archaeal intact polar lipids (IPLs), where the core lipid (CL) GDGTs are attached to polar head groups from the building blocks of membranes of living cells with phospho head groups have been shown to degrade rapidly upon death of the source organism (White et al., 1979; Harvey et al., 1986), while IPLs with glyco polar head groups may be preserved over (much) longer timescales (Lipp et al., 2008; Lipp and Hinrichs, 2009; Bauersachs et al., 2010). IPLs of Archaea have been detected in surface marine sediments and used as biomarkers of the presence of living in situ benthic Archaea (Biddle et al., 2006; Lipp et al., 2008; Lipp and Hin- richs, 2009; Lengger et al., 2012). Evidence has been presented that the IPL-GDGTs produced in situ in the surface sediments are rapidly recycled upon burial (Lengger et al., 2012). Some studies have suggested that benthic marine archaea recycle fossil CL-GDGTs when producing IPL-GDGTs de novo to decrease energy requirements (Liu et al., 2011; Takano et al., 2010). With the exception of Thaumarchaeota, the membrane lipid composition of other phyla of benthic archaea present in marine sediments has not been yet characterized and, therefore, their potential impact on the archaeal lipid pool preserved in the sedimentary record remains un- 148 Introduction/Material and Methods known. In surface sediments where oxygen is still available, Thaumarchaeota are expected to be dominant due to their oxygenic metabolism as nitrifiers (Könneke et al., 2005, Wuchter et al., 2006). However in subsurface sediments, where oxygen is no longer present, archaeal groups such as MBG-D, MCG, Thermoplasmatales and methanogens have been reported to be pre- dominant (Lloyd et al., 2013; Kubo et al., 2012), and may contribute to the total archaeal lipid pool in marine sediments. Recent studies have also observed a high presence of archaea of the superphylum DPANN both in surface and subsurface coastal marine sediments (Choi et al., 2016), as well as in freshwater systems (Ortiz-Alvarez et al., 2016; Ma et al., 2016). However, their contribution to the sedimentary archaeal lipid pool is expected to be negligible as their small genomes (Castelle et al., 2015) lack the genes of the membrane lipid biosynthetic pathway, suggesting that they rely on host cells or cell debris for the synthesis of their lipids (Waters et al., 2003; Jahn et al., 2004). Here, we determined the archaeal abundance and composition using DNA-based methods in surface sediments of a seasonally hypoxic marine lake with different oxygen and sulfide bottom water concentrations and compared this with the composition of the archaeal IPLs. We aim to identify the potential biological sources of the archaeal IPL lipids detected in surface sediments under changing environmental conditions which could impact the biology of the producer but also the preservation potential of the archaeal lipids. 6.2. Material and Methods 6.2.1. Study site, sediment sampling and physicochemical analyses Lake Grevelingen is a former estuary located within the Rhine-Meuse-Scheldt delta area of the Netherlands. The delta became a closed saline reservoir (salinity ~30) by dam construction at both the land side and sea side in the early 1970s. As a result of the absence of tides and strong currents, Lake Grevelingen experiences a seasonal stratification of the water column, which in turn, leads to a depletion of oxygen in the bottom waters (Hagens et al., 2015). Bottom water oxygen concentration at the deepest stations starts to decline in April, reaches hypoxic conditions by end of May (O2 < 63 µM), and further decreases to reach the state of anoxia in August

(O2 < 0.1 µM), while re-oxygenation of the bottom water takes place in September (Seitaj et al., 2015). Two sampling campaigns were performed on March 13th, 2012 (before the start of the annual

O2 depletion) and on August 20th, 2012 (at the peak of the annual O2 depletion). Detailed water column, pore water and solid sediment chemistry of Lake Grevelingen over the year 2012 have been previously reported (Seitaj et al., 2015; Sulu-Gambari et al., 2016, Hagens et al., 2015). In- tact sediment cores were recovered at three stations along a depth gradient within the Den Osse basin, one of the deeper basins in Marine Lake Grevelingen: Station 1 (S1) was located in the deepest point (34 m) of the basin (51.747°N, 3.890°E), Station 2 (S2) at 23 m depth (51.749°N, 3.897°E) and Station 3 (S3) at 17 m depth (51.747°N, 3.898°E) (Fig. S1). Sediment cores were retrieved with a single core gravity corer (UWITEC) using PVC core liners (6 cm inner diameter, 60 cm length). Further details of sediment sampling have been previously described in detail (Chapter 4). Four sediment cores were sliced with a 1 cm resolution (for the purposes of this study we only focused on the top centimeter) for lipid and DNA/RNA analysis and kept at –80ºC until further processing.

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The total organic carbon (TOC) content of the sediment was determined on sub-samples that were freeze-dried, ground to a fine powder and analyzed by an a Thermo Finnigan Delta plus isotope ratio monitoring mass spectrometer (irmMS) connected to a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan). Before the analysis, samples were first acidified with 2N hydrogen chloride (HCl) to remove the inorganic carbon (Nieuwenhuize et al., 1994). Con- centrations of TOC are expressed as mass % of dry sediment. Oxygen, sulfide, bottom water and pore water ammonium, nitrite and nitrate were determined as previously described (Malkin et al., 2014; Seitaj et al., 2015) and reported in Chapter 5. 6.2.2. DNA/RNA extraction Sediment was centrifuged and the excess of water was removed by pipetting before proceeding with the extraction of nucleic acids from the sediment. DNA/RNA of surface (0–1 cm) sediments was extracted with the RNA PowerSoil® Total Isolation Kit plus the DNA elution acces- sory (Mo Bio Laboratories, Carlsbad, CA). Concentration of DNA was quantified by Nanodrop (Thermo Scientific, Waltham, MA) and Fluorometric with Quant-iTTM PicoGreen® dsDNA Assay Kit (Life technologies, Netherlands). 6.2.3. 16S rRNA gene amplicon sequencing and sequencing analyses PCR reactions were performed with the universal, Bacteria and Archaea, primers S-D-Arch- 0159-a-S-15 and S-D-Bact-785-a-A-21 (Klindworth et al., 2013) as previously described in Moore et al. (2015). The archaeal 16S rRNA gene amplicon sequences were analyzed by QIIME v1.9 (Caporaso et al., 2010). Raw sequences were demultiplexed and then quality-filtered with a minimum quality score of 25, length between 250–350, and allowing maximum two errors in the barcode sequence. Taxonomy was assigned based on blast and the SILVA database version 123 (Altschul et al., 1990; Quast et al., 2013). The 16S rRNA gene amplicon reads (raw data) have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject no. PRJNA293286. 6.2.4. PCR amplification, cloning and archaeal 16S rRNA gene quantification Amplification of the archaeal amoA gene was performed as described by Yakimov et al. (2011). PCR reaction mixture was the following (final concentration): Q-solution 1 × (PCR additive, –1 –1 Qiagen); PCR buffer 1 ×; BSA (200 µg ml ); dNTPs (20 µM); primers (0.2 pmol µl ); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA, USA). PCR conditions for these amplifications were the following: 95°C, 5 min; 35 × 95°C, 1 min; 55°C, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen) and cloned in the TOPO-TA cloning® kit from Invitrogen (Carlsbad, CA, USA) and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. Recombinant clones plasmid DNAs were purified by Qiagen Miniprep kit and screening by sequencing (n ≥ 30) using M13R primer by BaseClear (Leiden, The Netherlands). Obtained archaeal amoA protein sequences were aligned with already annotated amoA sequences by using the Muscle application (Edgar, 2004). Phylogenetic trees were constructed with the Neighbor-Joining method (Saitou and Nei, 1987) and evolutionary distances computed using the Poisson correction method with a bootstrap test of 1,000 replicates. Quantification of archaeal 16S rRNA gene copies was performed by quantitative PCR (qPCR) by using the primers Parch519F and ARC915R as previously described (Pitcher et al., 2011b).

150 Material and Methods/Results

6.2.5. Lipid extraction and analysis Total lipids were extracted from surface (upper 0–1 cm) sediments after freeze-drying using a modified Bligh and Dyer method (Bligh and Dyer, 1959) following an experimental protocol previously described by Lengger et al. (2014). The extracts were then dissolved by adding solvent

(hexane:isopropanol:H2O 718:271:10 [v/v/v/v]) and filtered through a 0.45 µm, 4 mm-diameter True Regenerated Cellulose syringe filter (Grace Davison, Columbia, MD, USA). IPLs were analyzed with Ultra High Pressure Liquid Chromatography- High Resolution Mass spectrometry (UHPLC-HR MS). An Ultimate 3000 RS UHPLC, equipped with thermostated auto-injector and column oven, coupled to a Q Exactive Orbitrap MS with Ion Max source with heated electrospray ionization (HESI) probe (Thermo Fisher Scientific, Waltham, MA), was used. Separation was achieved on a YMC-Triart Diol-HILIC column (250 x 2.0 mm, 1.9 µm particles, pore size 12 nm; YMC Co., Ltd, Kyoto, Japan) maintained at 30°C. The following elution program was used with a flow rate of 0.2 mL min–1: 100% A for 5 min, followed by a linear gradient to 66% A: 34% B in 20 min, maintained for 15 min, followed by a linear gradient to 40% A: 60% B in 15 min, followed by a linear gradient to 30% A: 70% B in 10 min, where A

= hexane/2-propanol/formic acid/14.8 M NH3aq (79:20:0.12:0.04 [v/v/v/v]) and B = 2-propanol/water/formic acid/ 14.8 M NH3aq (88:10:0.12:0.04 [v/v/v/v]). Total run time was 70 min with a re-equilibration period of 20 min in between runs. HESI settings were as follows: sheath gas (N2) pressure 35 (arbitrary units), auxiliary gas (N2) pressure 10 (arbitrary units), auxiliary gas (N2) T 50 ˚C, sweep gas (N2) pressure 10 (arbitrary units), spray voltage 4.0 kV (positive ion ESI), capillary temperature 275 °C, S-Lens 70 V. IPLs were analyzed with a mass range of m/z 375 to 2000 (resolution 70,000), followed by data-dependent MS2 (resolution 17,500), in which the ten most abundant masses in the mass spectrum (with the exclusion of isotope peaks) were fragmented successively (stepped normalized collision energy 15, 22.5, 30; isolation window 1.0 m/z). An inclusion list was used with a mass tolerance of 3 ppm to target specific compounds (supplementary File S1). The Q Exactive Orbitrap MS was calibrated within a mass accuracy range of 1 ppm using the Thermo Scientific Pierce LTQ Velos ESI Positive Ion Calibration Solution (containing a mixture of caffeine, MRFA, Ultramark 1621, and N-butylamine in an acetonitrile-methanol-acetic solution). IPLs were quantified by integrating the summed mass chromatograms (within 3 ppm mass accuracy) of the dominant adduct formed (in case of MH-, DH- and HPH-IPLs the ammoniated adduct) and the first isotopomer and reported as peak area response per gram of dry sediment extracted, due to the lack of quantitative standards (for details see Pitcher et al., 2011b). The total lipid extracts from the surface sediments were further analyzed by acid hydrolysis to determine the composition and relative abundance of IPL-derived CL (resulting from the acid hydrolysis of IPLs) and CL-GDGTs using the method described by Lengger et al. (2012) and analyzed by via high-performance liquid chromatography-atmospheric pressure chemical ionization/mass spectrometry (HPLC-APCI/MS) (Schouten et al., 2007) using an internal C46 GTGT standard as described previously (Huguet al. 2006a). 6.3. Results 6.3.1. Physicochemical conditions The seasonal variation of the bottom water oxygen concentration in Lake Grevelingen strongly

151 Chapter 6

influenced the bottom and pore water concentrations of O2 and sulfide (Table 1). In March, bottom waters were fully oxygenated in all stations (299–307 μM), oxygen penetrated 1.8–2.6 mm deep in the sediment, and no free sulfide was recorded in the first few centimeters (Hagens et al., 2015). The width of the suboxic zone, operationally defined as the sediment layer located between the oxygen penetration depth (OPD) and the sulfide appearance (SAD), varied between 16–39 mm across the three stations in March 2012. In contrast, in August, oxygen was strongly depleted in the bottom waters at S1 (<0.1 μM) and S2 (11 μM), and no O2 was detected by microsensor profiling in the surface sediment at these two stations. At station S3, the bottom water concentration of O2 remained higher (88 μM), and oxygen still penetrated into the surface sediment down to 1.1 mm. In August, free sulfide was present near the sediment-water interface at all three stations, and the concentration of sulfide in the pore water increased with water depth. + Bottom water ammonium (NH4 ) concentrations in station S1 ranged from 3 µM in March to – 11.5 µM in August; nitrite (NO2 ) concentrations were relatively constant (0.7–1 µM) in March and August. Nitrate concentrations ranged from 28 µM in March to <2 µM in August in station S1, whereas in stations S2 and S3 values varied between 28 µM in March to ~10 µM in August (Table 1; for detailed bottom water biogeochemistry see Seitaj et al., 2015; Sulu-Gambari et al., 2016; Hagens et al., 2015; Chapter 4).The TOC content of the sediments varied slightly between stations and seasons, ranging between 1.8 and 4.4% as described previously (Table 1; Chapter 4). 6.3.2. Archaeal lipid diversity and distribution The archaeal IPL GDGT concentration (quantified as IPL-derived CLs) was almost an order of magnitude higher in March in all stations in comparison with the values in August, although this drop was less for station 3, where slightly lower concentrations of GDGT-0 and crenarchaeol were detected in March in comparison with the other stations (Table 2). In March, total IPL- GDGTs were mostly distributed between IPL-GDGT-0 (approximately 5 μg g–1 dry weight of sediment) and IPL-crenarchaeol (average 2.6 μg g–1). In August, the total IPL-GDGT abundance was lower in comparison with March (approximately an order of magnitude less), while the distribution did not change (Table 2). CL-GDGT abundance was also higher in March (26 to 79 μg g–1 dry weight of sediment) than in August (5 to 15 μg g–1 dry weight of sediment) (Table 2). CL-GDGT abundances were also higher than those of IPL-GDGTs at all stations and seasons (Table 2). In station 1 it was on average three times higher both in March and in August. On the other hand in station 2, CL-GDGTs were in average 8 times higher than IPL-GDGTs in March, and 30 times higher in August, with CL-crenarchaeol as the most abundant CL-GDGT in August (8 μg g–1 dry weight of sediment; Table 2), 40 times more of that detected for IPL-crenarchaeol (0.2 μg g–1; Table 2). In station 3, CL-GDGTs were on average 4 times higher in concentration than IPL-GDGTs (Table 2). The IPL composition was assessed by UHPLC-HRMS analysis and various GDGT-IPLs and archaeol-IPLS were specifically targeted by using an inclusion list as part of the analytical rou- tine (see supplementary File S1). Within the various IPL types detected, the distribution of observed cores was comparable to the distribution obtained after analysis of the IPL-derived CLs. IPLs with GDGT-0 and crenarchaeol as CL are the most abundant IPLs, with the highest concentrations in March (approximately 1010 response units g–1), while IPLs with GDGT-1 and -2 as CLs were two orders of magnitude less abundant (Table 3). In August, total IPL-GDGT concentrations decreased by two orders of magnitude as compared with the concentrations in

152 Results S appearance 2 19 88 2.5 0.1 211 537 10.6 3.04 March 4.2±2.7 1.1±0.1 (hypoxic) Station 3 5 0 73 2.8 0.7 307 27.7 2.87 (oxic) 2.4±0.4 August 41.8±8.6 penetration depth; SAD: ∑H 2 0 17 12 4.3 0.7 550 11.6 2.38 1157 0.6±0 March (hypoxic) Station 2 5 0 3.0 0.7 165 301 27.9 3.11 (oxic) August 21.3±2.5 2.6±0.65 0 0 17 1.7 1.0 656 810 11.5 1.81 March 0.9±1.1 (anoxic) Station 1 concentration below 1 μM and hypoxic below 63 μM; OPD: O below μM and hypoxic 1 concentration below 2 5 0 3.2 0.7 279 299 28.2 2.86 (oxic) August 17.5±0.7 1.8±0.04 [μM] [μM] [μM] [μM] [μM] + − − + [μM] 2 3 4 − 2 O TOC [%] HS SAD [mm] NH NO NO OPD [mm] NH4 Physicochemical parameters of Physicochemical in spring (March) Grevelingen and surface sediment (0–1 cm) in the three stations Lake the bottom water Bottom water Temperature [°C] Temperature Surface sediment Table 1: Table Data included in Seitaj et al., 2015; Sulu-Gambari 2016; Hagens et al., 2015; Chapter 4 and 5. and in summer (August). with O is classified as anoxic Bottom water depth. 153 Chapter 6 7.1 3.0 3.7 (53) August 0.2 (3.5) 0.1 (1.5) 0.1 (4.6) 0.1 (2.3) 2.9 (40.8) 0.05 (0.7) 1.7 (54.6) 0.03 (0.9) 1.1 (37.2) 0.01 (0.4) 0.04 (0.6) Station 3 5.1 26.0 0.3 (5) March 0.05 (1) 0.9 (3.5) 0.4 (1.5) 0.2 (0.7) 0.1 (0.2) 0.1 (2.7) 3.0 (58.6) 1.7 (32.5) 0.02 (0.3) 11.8 (45.3) 12.7 (48.8) of dry in the surface sediment (0–1 weight) -1 0.5 14.8 August 0.5 (3.5) 0.2 (1.4) 0.1 (0.7) 5.8 (39.3) 8.1 (54.8) 0.04 (0.3) 0.2 (45.5) 0.02 (4.9) 0.01 (2.6) 0.01 (1.1) 0.2 (44.8) 0.01 (1.1) Station 2 9.7 78.8 March 2.9 (3.7) 1.3 (1.6) 0.6 (0.8) 0.3 (0.4) 0.4 (4.4) 0.2 (2.2) 0.1 (0.8) 36.2 (46) 5.9 (60.5) 3.1 (31.6) 0.04 (0.4) 37.5 (47.6) 1.6 4.9 2.1 (43) August 0.2 (3.6) 0.1 (1.6) 0.1 (5.5) 0.1 (3.7) 0.04 (0.7) 2.5 (50.5) 0.03 (0.5) 0.8 (48.2) 0.02 (1.3) 0.6 (40.8) 0.01 (0.5) Cren = Crenarchaeol, Cren’ = crenarchaeol regioisomer . = crenarchaeol Cren’ Cren = Crenarchaeol, b Station 1 9.0 29.2 March 1.1 (3.7) 0.5 (1.6) 0.2 (0.8) 0.1 (0.4) 0.4 (4.6) 0.2 (2.2) 0.1 (0.9) 12.9 (44) 5.1 (56.9) 3.1 (34.8) 0.04 (0.5) 14.5 (49.5) b b Cren Cren’ Total Total Cren Cren’ GDGTs GDGT-1 GDGT-2 GDGT-3 GDGT-0 GDGT-0 GDGT-1 GDGT-2 GDGT-3 CL-GDGTs IPL-derived IPL-derived Values between parentheses correspond to the fractional (relative) abundance of abundance parentheses correspond between to the fractional (relative) Values GDGT as the concentration of individual each the by GDGT divided the individual cm) of and in summer (August). in spring (March) Grevelingen the three stations in Lake Abundance and distributiona of IPL-derived (released by acid hydrolysis) and CL GDGTs (µg g 2: Abundance and distributiona of and CL GDGTs acid hydrolysis) (released by Table IPL-derived a sum of the concentration of in that fraction. all GDGTs 154 Results

7 9 9 9

7 7 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. 7×10 August 2.6×10 1.5×10 1.8×10 3.4×10 4.9×10 Station 3

7 8 6 7 7 8 8 7 7 9

10 10 8 7 7 n.d. n.d. 1×10 5×10 1×10 March 9.5×10 6.7×10 1.4×10 1.2×10 6.2×10 5.2×10 1.1×10 6.6×10 8.2×10 1.3×10 2.2×10 1.4×10

7 8 7 8 9 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. August 4.4×10 5.7×10 6.1×10 1.6×10 8.5×10

Station 2

8 7 8 6 8 8 8 7 7 8 8 9 10 10 n.d. n.d. n.d. March 7.3×10 8.9×10 2.1×10 3.4×10 2.7×10 1.5×10 3.1×10 8.5×10 2.1×10 2.7×10 3.1×10 1.2×10 1.9×10 3.0×10

7 8 7 8 8 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. August 1.3×10 5.3×10 2.4×10 8.7×10 3.3×10

Station 1

7 7 7 8 8 8 7 8 8

10 10 10 8 6 n.d. n.d. n.d. 2×10 8×10 March 9.4×10 6.3×10 3.8×10 4.6×10 1.9×10 1.4×10 1.5×10 7.8×10 9.4×10 1.1×10 1.7×10 3.0×10 – 1 Total ru g Total GDGT IPL Archaeol-DH GDGT-0-DH GDGT-1-DH GDGT-2-DH GDGT-3-DH GDGT-4-DH GDGT-0-MH GDGT-1-MH GDGT-0-DH’ GDGT-1-DH’ GDGT-3-DH’ GDGT-4-DH’ GDGT-0-HPH GDGT-1-HPH Absolute abundance as response units per gram of dry of weight GDGT IPLs in surface sediments (0–1cm). detected archaeal

Crenarchaeol-MH Crenarchaeol-HPH ’isomers of specific GDGTs; n.d.: not detected. MH: monohexose, DH: Dihexose, HPH, hexose phosphohexose. phosphohexose. ’isomers of HPH, hexose DH: Dihexose, n.d.: not detected. MH: monohexose, specific GDGTs; Table 3: Table 155 Chapter 6 8 8 7 8 9 9 8 9 9 9 10 10 2.9 n.d 10.1 August 2.0 ×10 9.0 ×10 1.0 ×10 6.0 ×10 1.7 ×10 2.0 ×10 1.2 ×10 3.7 ×10 1.2 ×10 2.3 ×10 2.1×10 1.2 ×10 8 8 8 7 8 9 9 10 10 Station 3 1.4 n.d n.d n.d n.d 31.1 March 4.1 ×10 2.3 ×10 1.2 ×10 5.8 ×10 8.2 ×10 6.4 ×10 1.5 ×10 3.1×10 2.2 ×10 8 7 8 8 8 9 9 9 9 8 7 10 10 9.8 15.3 August 1.4 ×10 9.0 ×10 6.0 ×10 2.4 ×10 7.8 ×10 3.0 ×10 1.4 ×10 2.1 ×10 2.9 ×10 6.0 ×10 7.8 ×10 2.8×10 1.9 ×10 7 8 8 8 8 8 9 9 8 9 Station 2 3.0 n.d n.d n.d 88.5 March 6.5×10 5.5 ×10 1.7 ×10 1.1 ×10 3.1 ×10 2.2 ×10 6.1 ×10 9.4 ×10 1.7 ×10 2.0 ×10 8 8 8 9 9 6.5 7.5 n.d n.d n.d n.d n.d n.d n.d n.d August 4.4×10 1.1 ×10 1.1 ×10 1.1 ×10 4.2 ×10 7 9 9 7 9 Station 1 1.3 n.d n.d n.d n.d n.d n.d n.d n.d 38.2 March 7.1×10 1.1 ×10 9.9 ×10 4.9 ×10 5.8 ×10 – 1 of sediment) detected in the surface sediment (0–1cm) of and in March the three stations in –1 of the percentages of multiplying sediment) calculated by 16S rRNA gene the total archaeal reads by –1 Nitrosopumilus ] –1 DPANN, Woesearchaeota DHVEG-6 Woesearchaeota DPANN, organism Thermoplasmatales, AMOS1A-4113-D04 Thermoplasmatales, CCA47 Thermoplasmatales, MBG-D & DHVEG-1 Arc6 Thermoplasmatales, VC2.1 Sum of reads Thermoplasmatales C3 Group, Miscellaneous Crenarchaeota Thaumarchaeota, Marine Group I, Miscellaneous Euryarchaeotic Group (MEG) MBG-B Others abundance [cell g archaeal Total GDGT mg g and IPL-derived CL-GDGTs Total Calculated femtograms of GDGT per cell Thermoplasmata, 20a-9 n.d = not detected. MBG-D, Marine Benthic Group D; MBG-B, Marine Benthic Group B. Marine Benthic Group B. Marine Benthic Group D; MBG-B, n.d = not detected. MBG-D, August, assuming one 16S rRNA gene copy number per genome. assuming one 16S rRNA gene copy number August, archaeal 16S rRNA gene g archaeal abundance (copy number Archaeal classes abundances (cells g 4: Archaeal Table 156 Results ofdetected sediment] –1 =0.991. 2 Percentages of Percentages g rRNA generRNA gene 16S 16S number abundance [copy archaeal reads [%] and (B) archaeal total (A)

in the surface sediment (0–1cm) of(0–1cm) sediment surface in the groupsOnly archaeal percentages with and in August. are reported. >3% in March stations three the conditions, qPCR efficiency = 90%; R Figure1: 157 Chapter 6

March. In March both IPLs with GDGT-0 and crenarchaeol cores were mostly found with hexose phosphohexose (HPH) as IPL type, while in August the IPL type MH increased at the expense of HPH (Table 3). 6.3.3. Archaeal 16S rRNA gene diversity and abundance Archaeal diversity was estimated by 16S rRNA gene amplicon sequencing using universal primers. The archaeal community was dominated by Thaumarchaeota marine group I (MGI) in March both in station 1 and 3 with 72–82% of the total archaeal reads (Fig. 1A, Table S1). In station 2 these archaea were slightly less dominant but still comprised almost half of the total archaeal reads. Other archaeal groups were also present in the surface sediment in March in addition to MGI such as members of the DPANN Woesearchaeota (DHVE-6) (16–31%), Thermoplasmatales (3–14%), and MCG (1.4–2.5%). In August, the percentage of reads attributed to the DPANN Woesearchaeota increased notably from 16 to 95% in station 1, from 31 to 66% in station 2, and from 21 to 57% in station 3 at the expense of the reads assigned to the Thaumarchaeota MGI (Fig. 1A, Table S1). In addition, a slight increase of percentage of reads was observed from March to August for archaea affiliated to the MCG and Thermoplasmatales groups. Total archaeal abundance estimated by qPCR with general archaea 16S rRNA gene primers was comparable between March and August in all stations with slightly lower values in station 1 (average 6 × 109 gene copies g–1) and 1–2 × 1010 gene copies g–1 for station 2 and 3 (Fig. 1B). The diversity of Thaumarchaeota was further analyzed by amplification, cloning and sequencing of the amoA gene in the surface sediments of the three stations. All amoA sequences were closely related to sequences previously detected in marine surface sediments. Although certain variability was detected between the sequences recovered in different stations and seasons, no clear clustering was observed (Figs. S2A, B). 6.4. Discussion The seasonal changes in the oxygen and sulfide concentration in the bottom water of the marine Lake Grevelingen trigger an important switch in the archaeal community composition in the surface sediment. The archaeal community changed considerably from a Thaumarchaeota MGI-dominated community in March, when oxygen was still present and sulfide was not (Table 1) to an archaeal community dominated by archaea of the DPANN superphylum. Besides, the seasonal change did not induce a diversity change within the Thaumarchaeota as indicated by the amoA gene phylogeny (Figs. S2A, B). By multiplying the percentage of 16S rRNA gene reads of the Thaumarchaeota and the DPANN Woesearchaeota by the total archaea 16S rRNA gene copies per gram of sediments, we can estimate the abundances of these groups (assuming one 16S rRNA gene copy number per genome) (Table 4). For Thaumarchaeota, the abundance decreased dramatically in station 1 (from 6 × 109 cells g–1 to undetected) and in station 3 (2 × 1010 to 1.2 × 109 cells g–1), while in station 2 the abundance remained fairly constant (Table 4). On the other hand, members of the DPANN Woesearchaeota were the major component of the archaeal population in August in all stations with absolute numbers increasing in all stations (1 × 109 to 4.2 × 109 cells g–1 of sediment in station 1; 2 × 109 to 2 × 1010 cells g–1 in station 2, 6.4 × 109 to 1.2 × 1010 cells g–1 in station 3; Table 4). This change in the archaeal community is entirely compatible with the metabolism of both Thaumarchaeota and the DPANN archaea, which is aerobic (Könneke

158 Results/Discussion et al., 2005) and anaerobic (Castelle et al., 2015), respectively. Also, nitrification conducted by Thaumarchaeota has been shown to be inhibited by sulfide (Berg et al., 2015), which additionally explains the decrease in the MGI population upon increase of the sulfide concentration in the summer. In the same way, the abundance of the other archaeal benthic groups, which increased in the surface sediments in August, such as the Thermoplasmatales and the MCG, are predicted to have an anaerobic metabolism based on their genome. The environmental control of the change in the archaeal community diversity is also supported by the fact that this change is less evident in the surface sediment of station 3, where oxygen was still present and the sulfide concentration in summer was substantially lower than at stations 1 and 2 (Table 1). Although the seasonality changes in the physicochemical conditions in the bottom and pore water induced a large change in the archaeal community diversity, the total archaeal abundance remained fairly constant between seasons and in the different stations (Fig. 1B). The archaeal community analysis was conducted by primer-based 16S rRNA gene amplicon sequencing. Therefore, we cannot completely rule out a possible primer bias (Sipos et al., 2010; Schloss et al., 2011), although the underrepresentation of DPANN sequences in the databases would imply that if any those primer biases would negatively detect DPANN in our samples, which in that case would induce to a underestimation of this group. The large change in the archaeal community composition in the surface sediments upon the decrease of oxygen concentration in the summer coincided with an order of magnitude decrease of the total IPL-GDGTs detected. The IPL-GDGT profiles in March were compatible with a Thaumarchaeota-dominated population, due to the relatively high abundance of crenarchaeol, the specific CL of Thaumarchaeota (Sinninghe Damsté et al., 2002). In addition, the IPL type of crenarchaeol (and all other main GDGTs) switched from mostly HPH to MH from March to August (Table 3). The predominance of HPH IPL-crenarchaeol has been previously interpreted as an indication of the presence of an active Thaumarchaeotal population synthesizing membrane lipids in situ (Lengger et al., 2012, 2014), due to the labile nature of HPH IPLs (Harvey et al., 1986; Schouten et al., 2010). On the other hand, glycolipid-type IPLs (here mostly MH) have been considered as fossil signal (Lengger et al., 2012, 2014) or, alternatively, as the preferred IPL type in conditions where the Thaumarchaeota are in a stationary phase of growth (Elling et al., 2014). This latter explanation is not likely in the case where the surface sediment became fully sulfidic. Recent studies suggest that members of the DPANN have a reduced genome with limited metabolic capabilities (Rinke et al., 2013; Castelle et al., 2015), suggesting that these archaea may have a symbiotic or parasitic lifestyle. In addition, they also lack most if not all the genes coding for the enzymes of the archaeal lipid biosynthetic pathway (Jahn et al., 2004; Villanueva et al., 2017). They are, therefore, not expected to contribute to the total IPL-GDGT pool by actively synthesizing lipids but may recycle the membrane lipid of other archaea. The decline of the total archaeal IPL-GDGTs in August coinciding with the switch to a DPANN-dominant population with similar or even higher cell abundances to that reported in March would therefore imply that the DPANN Woesearchaeota make use of the preserved (‘fossil’) pool of IPL-GDGTs to make their membranes. A question with respect to this membrane lipid acquisition mechanism is whether the pool of ‘fossil’ IPL-GDGTs is able to fulfill the membrane requirements of the large archaeal DPANN population detected in the surface sediments sampled in August in view of the much reduced concentration of IPL-GDGTs, which is an order of magnitude lower. This

159 Chapter 6 can only work when the DPANN archaea have a much smaller cell size than the Thaumarchae- ota that thrive in spring. The size of the DPANN Woesearchaeota present in Lake Grevelingen surface sediment is unknown. The only characterized archaeon from the DPANN superphylum is Nanoarchaeum equitans, which is considered to be a symbiont of the archaeon Ignicoccus sp. by growing on its surface. The lipids of N. equitans have been shown to be derived from Ignicoccus sp. (Jahn et al., 2004), but the uptake mechanisms remain unknown. N. equitans is 5 times smaller than its host, the archaeon Ignicoccus sp.. Assuming a similar size difference between the DPANN Woesearchaeota found in the Lake Grevelingen surface sediments and its potential host, sufficient IPLs would be available to sustain the DPANN population detected in the sediments in August. Alternatively, the DPANN archaea could recycle the CL-GDGTs present in the sediment as previously suggested (Liu et al., 2011; Takano et al., 2010), which is presumed to involve hydrolysis and reformation of the ether bond to the glycerol backbone as suggested by the 13C-glucose labeling studies of Takano et al. (2010). However, since the members of the DPANN generally lack the genes coding for the enzymes involved in producing the ether bonds to the glycerol backbone (Villanueva et al., 2017), this is unlikely. Alternatively, they could also use the CL- GDGTs and add the polar head groups de novo. Waters et al. (2003) observed the presence of genes for lipid modification, such as glycosylation, in the genome ofN. equitans. We performed a search for the gene encoding cytidine diphosphate (CDP)-archaeol synthase (CarS, E.C. 2.7.7.67) that catalyzes the activation of 2,3-bis-O-geranylgeranylglyceryl diphosphate (DGGGP) by cytidine triphosphate (CTP) to form the intermediate for polar head group attachment (i.e. CDP-archaeol), and we found homologs in most of the DPANN Micrarchaeota genomes and in some of the DPANN Parvarchaeota and Diapherotrites (perfomed by find function in JGI Integrated Microbial Genomes, IMG with genomes available in July 2017). However, the genes coding for the enzymes that catalyze the subsequent replacement of cytidine monophosphate of the cytidine diphosphate (CDP)-archaeol of CDP-diacylglycerol with a polar head group in DPANN genomes were not detected, in contrast to N. equitans (Waters et al., 2003). This may indicate that the members of the DPANN either do not have the capacity of adding the polar head groups to the CL-GDGT or that the polar head groups of their IPLs are different and added by enzymes different to those already characterized. 6.5. Conclusion We observed a dramatic change in the archaeal community composition and lipid abundance in surface sediments of a seasonally hypoxic marine lake which corresponded to a switch from a Thaumarchaeota-dominated to a DPANN-dominated archaeal community, while the total IPLs detected were significantly reduced. Considering the reduced genome of the members of the superphylum DPANN and their apparent inability to synthesize their own membrane lipids, we hypothesize that they use the CLs previously synthesized by the Thaumarchaeota to form their membrane.

Acknowledgements We acknowledge the crew of the R/V Luctor and Pieter van Rijswijk for their help in the field during sediment collection, Marcel van der Meer and Sandra Heinzelmann for support onboard 160 Discussion/Conclusion/Supplementary Material and assistance with incubations, Elda Panoto for technical support, and Eric Boschker and Filip Meysman for helpful discussions. This work was financially supported by the Darwin Centre for Biogeosciences to LV (grant no: 3062). LV and JSSD receive funding from the Soehngen Institute for Anaerobic Microbiology (SIAM) through a Gravitation Grant (024.002.002) from the Dutch Ministry of Education, Culture and Science (OCW).

Figure S1: Scheme of the sampling locations in Lake Grevelingen 161 Chapter 6 4.6 4.2 5.6 5.6 0.9 7.9 2.8 0.9 n.d. 10.6 56.9 17.1 August Station 3 4.7 2.6 0.2 0.4 0.7 1.3 n.d. n.d. n.d. n.d. 20.6 72.1 March 0.2 3.2 5.1 7.4 4.9 1.1 2.7 0.8 0.2 2.7 66.5 10.1 August Station 2 3.4 2.5 1.7 9.3 2.5 0.8 n.d. n.d. n.d. 31.4 14.4 48.3 March 2.6 2.6 2.6 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. 94.9 August Station 1 0.7 1.4 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. 16.0 81.9 March Nitrosopumilus organism Others MBG-B Thaumarchaeota, Marine Group I, DPANN, Woesearchaeota DHVEG-6 Woesearchaeota DPANN, Miscellaneous Crenarchaeota Group, C3 Group, Miscellaneous Crenarchaeota Sum of reads Thermoplasmatales Miscellaneous Euryarchaeotic Group (MEG) Thermoplasmatales, VC2.1 Arc6 Thermoplasmatales, VC2.1 Thermoplasmatales, MBG-D & DHVEG-1 Thermoplasmatales, CCA47 Thermoplasmatales, AMOS1A-4113-D04 Thermoplasmata, 20a-9 Percentages of Percentages S1: rRNA gene 16S of(0–1cm) sediment Table surface the in detected [%] reads archaeal total and in August. in March stations three the groupsOnly archaeal with percentages >3% are reported. Marine Benthic Group B. Marine Benthic Group D; MBG-B, n.d = not detected. MBG-D, 162 Supplementary Material

Lake Grevelingen sediment; 0-1 cm depth; 2 seq March: 1 x S2, 1 x S3; 6 seq August: 2 x S1, 2 x S2, 2 x S3 Lake Grevelingen sediment; 0-1 cm depth; March S2 uncultured crenarchaeote, Elkhorn Slough sediment (DQ148892) Lake Grevelingen sediment; 0-1 cm depth; August S1 Lake Grevelingen sediment; 0-1 cm depth; August S2 Lake Grevelingen sediment; 0-1 cm depth; March S2 Lake Grevelingen sediment; 0-1 cm depth; August S3 Lake Grevelingen sediment; 0-1 cm depth; 5 seq March: 2 x S1, 2 x S2, 1 x S3 Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; August S2 Lake Grevelingen sediment; 0-1 cm depth; 4 seq March: 1 x S1, 3 x S2; 5 seq August: 1 x S1, 2 x S2, 2 x S3 Lake Grevelingen sediment; 0-1 cm depth; 2 seq March: 1 x S1, 1 x S3; 2 seq August: 1 x S1, 1 x S3 Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; August S2 uncultured crenarchaeote clone, Elkhorn Slough sediment (DQ148771) uncultured archaeon clone, aquarium bioﬁlter (AB373356) Lake Grevelingen sediment; 0-1 cm depth; March S1 Lake Grevelingen sediment; 0-1 cm depth; March S3 uncultured archaeon, marine aquaculture (AM295172) uncultured crenarchaeote clone, marine sediment (FJ656584) Nitrosopumilus maritimus (SCM1) (CP000866) Lake Grevelingen sediment; 0-1 cm depth; 4 seq March: 2 x S1, 2 x S3 Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; March S1 Lake Grevelingen sediment; 0-1 cm depth; August S3 Lake Grevelingen sediment; 0-1 cm depth; August S1 Lake Grevelingen sediment; 0-1 cm depth; 4 seq March: 1 x S1, 2 x S2, 1 x S3; 4 seq August: 1 x S2, 3 x S3 Lake Grevelingen sediment; 0-1 cm depth; March; S1 Lake Grevelingen sediment; 0-1 cm depth; March; S1 Lake Grevelingen sediment; 0-1 cm depth; August S1 uncultured archaeon clone, deep sea sediments (AB289355) uncultured crenarchaeote clone, Black Sea water 100 m (EF414231) Lake Grevelingen sediment; 0-1 cm depth; August S3 Lake Grevelingen sediment; 0-1 cm depth; March: 1 x S1; 6 seq August: 3 x S1, 2 x S2, 1 x S3 Lake Grevelingen sediment; 0-1 cm depth; 20 seq March: 5 x S1, 8 x S2, 7 x S3; 24 seq August: 5 x S1, 12 x S2, 7 x S3 Lake Grevelingen sediment; 0-1 cm depth; March; S2 Lake Grevelingen sediment; 0-1 cm depth; March; S1 53 Lake Grevelingen sediment; 0-1 cm depth; August S1 Lake Grevelingen sediment; 0-1 cm depth; March S2 Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; 3 seq March: 1 x S1, 1 x 2, 1 x S3; 3 seq August: 2 x S1, 1 x S3 Lake Grevelingen sediment; 0-1 cm depth; August S2 Lake Grevelingen sediment; 0-1 cm depth; August S3 73 uncultured archaeon clone, deep sea sediments (AB289348) uncultured thaumarchaeota clone, Arabian Sea surface sediment (KJ509763) uncultured archaeon clone (deep sea water column) (AB289377) Lake Grevelingen sediment; 0-1 cm depth; August S3 Lake Grevelingen sediment; 0-1 cm depth; 3 seq March: 1 x S1, 1 x S2, 1 x S3; 3 seq August: 2 x S1, 1 x S3 Lake Grevelingen sediment; 0-1 cm depth; 8 seq March: 2 x S1, 2 x S2, 4 x S3; 8 seq August: 2 x S1, 4 x S2, 2 x S3 Lake Grevelingen sediment; 0-1 cm depth; March S2 uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148664) Lake Grevelingen sediment; 0-1 cm depth; 2 seq August S3 Lake Grevelingen sediment; 0-1 cm depth; 3 seq March: 1 x S1, 1 x S2, 1 x S3 uncultured crenarchaeote clone, wastewater (HM589775) 96 uncultured crenarchaeote clone, wastewater (HM191510) 53 uncultured archaeon clone, freshwater aquaria (JN183601)

0.02

Figure S2A: Phylogenetic tree of amoA protein sequences recovered from the surface sediment (0–1 cm) of Stations 1, 2 and 3 in Lake Grevelingen during March and August (black bold: sequences retrieved in this study and closest relatives) constructed with the Neighbor-Joining method (Saitou and Nei, 1987). Scale bar indicates 2% sequence dissimilarity. The evolutionary distances were computed using the Poisson correction method with a bootstrap test of 1,000 replicates (values higher than 50% are shown on the branches).

163 Chapter 6 Supplementary Material

uncultured crenarchaeote clone, Gulf of California (EU340510) uncultured crenarchaeote clone, Black Sea water 70 m (DQ148740) uncultured archaeon clone, Peruvian OMZ (FJ799200) uncultured crenarchaeote clone, South China Sea 100m (EU885994) uncultured crenarchaeote clone, North Pacific subtropical gyre 130 m (EF106932) uncultured crenarchaeote clone, tropical marine estuarine sediment (FJ601621) uncultured crenarchaeote clone, Elkhorn Slough sediments (DQ148805) uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148759) uncultured crenarchaeote clone, intertidal sandy flat (EU099940) uncultured ammonia-oxidizing archaeon clone, salt marsh sediment (EU925267) Candidatus Nitrosoarchaeum limnia (SFB1) (CM001158) 86 uncultured crenarchaeote clone (Monterey Bay 30 m) (DQ148820) uncultured crenarchaeote clone, Changjiang Estuary sediment (EU025183) uncultured Thaumarchaeota clone, Arabian Sea 170 m (KF512326) 54 uncultured archaeon clone, Peruvian OMZ (FJ799198) 76 uncultured crenarchaeote clone, Pacific Ocean 150 m (GU364066) Lake Grevelingen sediment; 0-1 cm depth; March S1 Lake Grevelingen sediment; 0-1 cm depth; August S2 87 uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148670.1) 57 Lake Grevelingen sediment; 0-1 cm depth; March S1 Lake Grevelingen sediment; 0-1 cm depth; March S2 51 uncultured crenarchaeote clone, Elkhorn Slough South Marsh (FJ227870) uncultured archaeon clone, aquarium biofilter (AB373264) Cenarchaeum symbiosum (A) (DQ397569) uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148654) 81 Candidatus Nitrosoarchaeum koreensis (My1) (HQ331117) uncultured crenarchaeote clon, Gulf of California (DQ148574) uncultured crenarchaeote clone, Elkhorn Slough sediment (DQ148796) uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148671) uncultured archaeon clone, hydrothermal vents (AB451499) 83 uncultured crenarchaeote clone, Gulf of California (EU340541) 99 uncultured crenarchaeote clone, North pacific subtropical gyre 4000 m (EF106928) 55 uncultured crenarchaeote clone, Black Sea 70 m (DQ148697) uncultured archaeon, sponge tissue (DQ333425) 69 uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148764) uncultured crenarchaeote, ETNP OMZ 200 m (DQ148750) uncultured crenarchaeote clone, North East Atlantic 2502 m (EU810223) uncultured crenarchaeote clone, North East Atlantic 2502 m (EU810225) 63 uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148769) 53 uncultured archaeon, sponge tissue (DQ333419) 54 uncultured thaumarchaeota clone, Arabian Sea 1050 m (KF512379) uncultured crenarchaeote clone, Gulf of California (EU340549) uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148746) uncultured crenarchaeote clone, Gulf of Mexico (GQ250723) uncultured crenarchaeote clone, Juan de Fuca Ridge 2267 m (EU864296) uncultured crenarchaeote clone, North Pacific subtropical gyre 700 m (EF106899) uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148762) uncultured archaeon clone, Lake water (FN773449) uncultured archaeon clone, Lake water (FN773418) 51 uncultured archaeon clone, Lake water (FN773404) 94 uncultured crenarchaeote clone, rhizosphere (EU667867) 67 100 Candidatus Nitrosotalea devanaterra (JN227489) 78 uncultured crenarchaeote clone, forest soil (EF530119) Candidatus Nitrosocaldus yellowstonii (EU239961) Candidatus Nitrososphaera vienensis (FR773159) 99 0.02 97 Candidatus Nitrososphaera gargensis (EU281321) 99 uncultured crenarchaeote clone, vapour cave (DQ672686)

Figure S2B: Phylogenetic tree of amoA protein sequences recovered from the surface sediment (0–1 cm) of Stations 1, 2 and 3 in Lake Grevelingen during March and August (black bold: sequences retrieved in this study and closest relatives) constructed with the Neighbor-Joining method (Saitou and Nei, 1987). Scale bar indicates 2% sequence dissimilarity. The evolutionary distances were computed using the Poisson correction method with a bootstrap test of 1,000 replicates (values higher than 50% are shown on the branches).

164

7. Synthesis

167 Chapter 7

In general, my results support that the oxygen concentration of the bottom water and the OPD into the sediment is one of the major factors shaping the temporal and spatial distribution of the diversity, abundance and activity of chemolithoautotrophic microorganisms, due to different oxygen requirements of their respective metabolism. Next to the availability of electron donors and acceptors, I have concluded that other factors such as bioturbation (Kristensen, 2000; Meyer et al., 2005; Beman et al., 2012) and the interactions between different microbial groups are important factors allowing for the activity of aerobic and anaerobic microorganisms together in the same niche. The abundance and activity of Thaumarchaeota and anammox bacteria was detected in Oyster Grounds sediments (Fig. 1) independent of the season and decreasing oxygen concentrations in the bottom water, whereas in Lake Grevelingen sediments, the abundance and activity of Thaumarchaeota was restricted to March, when the bottom water was still oxygenated (Fig. 2). These results suggest that the presence of bioturbation, oxygen- ating deeper layers in Oyster Grounds sediments, favors the presence and activity of aerobic ammonia oxidizing microorganisms, which could in turn fuel the activity of anammox bacteria by consuming oxygen and providing nitrite (Meyer et al., 2005; Laverock et al., 2013), compared to Lake Grevelingen sediments, where bioturbation was absent and sulfide accumulates in the sediment pore water during summer hypoxia. In comparison to Oyster Grounds sediments, temporal and spatial differences of the community structure, as well as of the abundance and activity of studied microorganisms were more pronounced in Lake Grevelingen sediments (Fig. 2), most likely due to the full development of hypoxia and rising sulfide concentrations as it has been shown recently for Black Sea sediments (Jessen et al., 2017). High sulfide concentrations are not only toxic for benthic bioturbating animals as sulfide has also been shown to inhibit ammonia oxidation (Joye and Hollibaugh, 1995; Berg et al., 2015) and the last steps of denitrification (Sørensen, 1980; Porubsky et al., 2009). My results showed that decreasing oxygen and rising sulfide concentrations induce drastic changes in the archaeal and bacterial community structure, and limit the abundance and/or the activity as well of specific groups involved in the sedimentary nitrogen and sulfur cycle, i.e. Thaumarchae- ota (AOA), AOB, anammox (Chapters 2, 3, 4) and denitrifying bacteria, sulfate and sulfur oxidizing bacteria including sulfide-dependent denitrifiers in Lake Grevelingen sediments (Chapters 4 and 6), as well as of chemolithoautotrophic bacteria (Chapter 5). Additionally, the potential activity of anammox bacteria was relatively low in Lake Grevelingen sediments compared to Oyster Grounds sediments, suggesting that this group is strongly affected by increasing sulfide concentrations. The activity of other groups, i.e. denitrifying bacteria, sulfate reducing and sulfur oxidizing bacteria including sulfide-dependent denitrifiers, was relatively low in seasonally hypoxic Lake Grevelingen sediments independent of the season, suggesting that the activity of these groups is as well affected by decreasing oxygen and rising sulfide concentrations between spring and summer. Both anammox and denitrification pathways have been suggested to be more important in sediments with low sulfide concentrations, but also with low carbon input (Burgin and Ham- ilton, 2007). The TOC content in Lake Grevelingen sediments is high (2.5−4.5%) and fresh organic rich sediment rapidly accumulates (> 2 cm y−1), which might additionally inhibit the activity of anammox and denitrifying bacteria. The TOC content in Oyster Grounds sediments was low (0.15−0.38%), which might explain the higher activity of anammox activity compared to Lake Grevelingen sediments. However, sediment incubation experiments (using labeled ni-

168 Synthesis trite) have previously shown that the ratio of anammox to denitrification depends on the carbon to nitrogen (C/N) ratio, i.e. the activity of anammox bacteria increased with higher nitrogen relative to carbon content (lower C/N) ratio of the source substrate (Babbin et al., 2014). How- ever, in my studies, I have observed a difference in the potential activity of anammox bacteria with higher expression levels in Oyster Ground compared to Lake Grevelingen sediments. The C/N ratio is relatively high in sediments of the Oyster Ground (7−8) and Lake Grevelingen (9.2 ± 0.2; Rao et al., 2016), indicating that this does potentially not explain the differences in the potential activity of anammox bacteria in the sediments studied here. Generally, the activity of chemolithoautotrophic bacteria in Lake Grevelingen sediments was restricted to March under oxygenated bottom water concentrations, indicating that chemolithoautotrophic bacteria in general are affected by bottom water hypoxia/anoxia, the lack of bioturbation and rising sulfide concentrations (Chapter 5). Additionally, the abundance and metabolic capacities of the chemolithoautotrophic aerobic ammonia oxidizing archaea (AOA), i.e. Thaumarchaeota, were also evaluated in other marine sediment systems, i.e. in sandy to muddy sediments of the Iceland shelf. Thaumarchaeota were detected at all stations but their metabolic activity was low based on lack of incorporation of 13C-labeled substrate in archaeal GDGT lipids. The low activity of Thaumarchaeota is in agreement with the low oxygen penetration into the sediment, supporting that the absence of oxygen is limiting the activity of Thaumarchaeota. Ammonia and nitrite concentrations showed no changes during incubations, indicating that other factors than the availability of ammonia might inhibit the activity of Thaumarchaeota. 7.2. Diversity of chemolithoautotrophic microorganisms in coastal sediments The general diversity of the microbial community was studied in Lake Grevelingen surface sediments by applying 16S rRNA amplicon sequencing analysis (Chapters 5, 6), before and during summer hypoxia. In general, these sediments harbor a distinct bacterial community comparable to other surface sediments, such as coastal marine (North Sea), estuarine and Black Sea sediments (Jessen, et al., 2016; Ye et al., 2016; Dyksma et al., 2016). Approximately, 50% of the bacterial reads were assigned to the clades of Gammaproteobacteria, Deltaproteobacteria and Ep- silonbacteria, whereas the remaining reads were distributed among the orders of Bacteroidetes (14%), Planctomycetes (6%), Alphaproteobacteria (2%) and other orders (22%). The majority of reads assigned to the Gammaproteobacteria were closely related to the orders Alteromo- modales, Chromatiales and Thiotrichales, whereas most of the reads of Epsilonproteobacteria were assigned to the order of Campylobacterales. Within the Deltaproteobacteria, most reads were assigned to the orders of Desulfarculales and Desulfobacterales. In March, under oxygenated bottom water conditions, the surface sediment was characterized by high relative abundances (percentage of 16S rRNA gene reads) of Gammaproteobacteria and Epsilonproteobacteria, which are known chemolithoautotrophic sulfur oxidizers, e.g. capable of oxidizing sulfide, thiosulfate, elemental sulfur and polythionates, using oxygen and nitrate as electron acceptor. In August, the lack of electron acceptors in the bottom water, i.e. oxygen and nitrate, coincided with a decrease in the relative abundance of Gammaproteobac- teria and Epsilonproteobacteria. At the same time, the number of reads assigned to the order of Desulfobacterales increased in the top centimeter of the sediment and a shift in the bacterial 169 Chapter 7 community toward chemoorganoheterotrophic sulfate-reducing bacteria related to the genera Desulfococcus and Desulfosarcina was evident. In coastal sediments, these genera are characteristic in deeper sediment layers experiencing anaerobic mineralization (Llobet-Brossa et al., 2002; Mi- yatake, 2011; Muyzer and Stams, 2008). The DNA-based 16S rRNA gene amplicon sequencing was complemented with the analysis of bacterial phospholipid derived fatty acids (PLFA) analysis in Lake Grevelingen sediments down to 6 cm sediment depth in all seasons and stations.

In March, surface sediments were characterized by relative high concentrations of C16 and C18 monosaturated PLFAs found in Gammaproteobacteria and Epsilonproteobacteria (Vestal and White 1989), whereas in deeper sediment layers, ai15:0, i17:1ω7c, and Me16:0, indicating that sulfate-reducing Deltaproteobacteria were more abundant (Boschker et al., 2002; Taylor and Parks, 1983; Edlund et al., 1985). In August, surface sediment showed an increased contribution of iso, anteiso, and branched PLFAs, more similar to the deeper sediments from March, but showed higher abundances of 16:0, 14:0, and 18:1ω9c compared to March. These shifts in the PLFA patterns are in agreement with the temporal difference in the bacterial community shown by 16S rRNA gene amplicon sequencing. However, the results of the PLFA analysis have to be interpreted with caution because there is now evidence that the method used here (Guckert et al., 1985), i.e. the separation of phospholipids from glycolipids and neutral lipids using silica column chromatography, does not result in a fraction only containing phospholipids but also other lipid classes (Heinzelmann et al., 2014). Thus, commonly reported PLFA composition might be not derived purely from phospholipids but from of other lipid classes. Additionally, the archaeal diversity was estimated by 16S rRNA gene amplicon sequencing in surface sediments of Lake Grevelingen (Chapter 6). The archaeal community was dominated by chemolithoautotrophic Thaumarchaeota marine group I (MGI) in March (50−82%), when oxygen was still present and sulfide was absent, next to the presence of other archaeal groups, such as members of the DPANN Woesearchaeota, Thermoplasmatales and members of the Miscellaneous Crenarchaeotic group (MCG). In August, the percentage of reads, attributed to the DPANN Woesearchaeota increased notably (57−95%) at the expense of reads assigned to the Thaumarchaeota. This change in the archaeal community is compatible with the aerobic metabolism of Thaumarchaeota (Könneke et al., 2005) and the anaerobic metabolism of DPANN archaea (Castelle et al., 2015). Thaumarchaeota have been shown to be inhibited by sulfide (Berg et al., 2015), potentially explaining the decrease in the MGI population upon the increase of sulfide concentrations in the summer. In summary, results of the community analysis revealed a diverse microbial community in Lake Grevelingen surface sediments consisting of chemolithoautotrophic and chemoorgano-heterotrophic microorganisms, responding to changes in the availability of reduced nitrogen and sulfur compounds and electron acceptors (oxygen and nitrogen) induced by hypoxia. Nevertheless, the bacterial and archaeal community analysis was performed by 16S rRNA gene amplicon sequencing, therefore I cannot completely exclude a possible primer bias (Sipos et al., 2010; Schloss et al., 2011). Additionally, the diversity analysis of the 16S rRNA gene does not give information about absolute abundances, the metabolism and more importantly, about the activity of sedimentary microorganisms and their role in biogeochemical cycling of carbon, nitrogen and sulfur.

To further estimate the diversity of microorganisms fixing CO2 via the Calvin-Benson-Bassh- am (CBB) and the reductive tricarboxylic acid (rTCA) pathways, surface sediments of Lake Grevelingen sediments (Chapter 5) were investigated by cloning and sequencing the cbbL and 170 Synthesis aclB gene, encoding for the key enzymes ribulose 1,5-bisphosphate carboxylase/oxygenase (Ru- bisCO) and ATP citrate lyase, respectively. All detected cbbL sequences clustered with uncultered gammaproteobacterial clones, assigned to the orders Chromatiales and Thiotrichales, reported in intertidal sediment from Lowes Cove, ME (Nigro and King, 2007). The aclB gene sequences in surface sediments were predominantly related to aclB sequences of Epsilonproteobacteria of the order Campylobacterales, macrofaunal symbionts and to sequences of Euryarchaeota. No clustering of cbbL and aclB gene sequences according to one of the stations or one of the seasons was observed. Results revealed a stable community of bacteria using the CBB cycle, as well as bacteria and archaea using the rTCA pathway in Lake Grevelingen surface sediments. Until today, there is no PCR-based approach available to identify microorganisms using other

CO2 fixation pathways, such as the reductive acetyl-CoA, or Wood-Ljungdahl (WL) pathway utilized by Firmicutes, Planctomycetes, Deltaproteobacteria, Spirochaeta and Euryarchaeota, or the 3-hydroxypropionate/4-hydroxybutyrate (3-HP/4-HB) cycle and the dicarboxylate/4- hydroxybutyrate (DC/4-HB) cycle operating in Crenarchaeota (Hügler and Sievert, 2011), mainly due to the diversity of key genes of these pathways which impairs the development of a PCR- based detection method. Thus, an underestimation of the diversity of chemolithoautotrophic microorganisms in the coastal marine sediments under study in this thesis is possible. Another goal of this thesis was to further estimate the diversity of chemolithoautotrophic microorganisms involved in the sedimentary nitrogen and sulfur cycle by using group specific 16S rRNA genes and functional genes involved in reoxidation pathways. This approach was applied in sediments of the Oyster Grounds (North Sea) and Lake Grevelingen surface sediments. In Oyster Grounds surface (0–1 cm) and deeper (9–10 cm) sediments, the diversity of ammonia oxidizing archaea (Thaumarchaeota, AOA) and ammonia oxidizing bacteria (AOB), was determined by targeting the functional amoA gene of AOA and AOB. Results showed that amoA gene sequences of AOA amplified from Oyster Grounds surface sediments fell into distinct subclusters of Nitrosopumilus sp., whereas most of the archaeal amoA sequences obtained from Lake Grevelingen sediments were closely related to Nitrosopumilus maritimus (SCM1) and in minor proportion to “Candidatus Nitrosoarchaeum limnia” found in low-salinity habitats (Mosier et al., 2012), showing a different community composition of AOA in Lake Grevelingen surface sediments, which is most likely explained by the lower salinity (~30 psu) compared to Oyster Grounds sediments (~34.5 psu). AOB amoA gene sequences retrieved from Oyster Grounds sediments were closely related to Nitrospira sp. and Nitrosolobus multiformis. Another important chemolithoautotrophic microbial group present in anoxic sediment and involved in the nitrogen cycle is anammox bacteria. One issue much in debate is the relevance of anammox bacteria vs. heterotrophic denitrifiers in the N2 removal process in the environment. In this thesis I tackled this issue by determining the diversity and role of anammox bacteria, heterotrophic denitrifiers and other microbial groups involved in nitrogen removal (e.g. sulfur oxidizers coupled to nitrate reduction) in Lake Grevelingen sediments (Chapter 4). The diversity of the anammox 16S rRNA gene, whereas the nirS gene of denitrifying and anammox bacteria, as well as the aprA gene of sulfur oxidizing and sulfate reducing bacteria, were determined in Lake Grevelingen surface sediments (chapter 4). The diversity of nirS-type denitrifiers in surface sediments (0−1 cm) revealed a temporally stable community of denitrifying bacteria involved in autotrophic denitrification coupled to sulfide or iron oxidation (e.g. Thiobacillus denitrificans, Sid- eroxidans lithotrophicus), and of diverse heterotrophic denitrifiers. Most of the anammox bacterial 171 Chapter 7 nirS gene sequences obtained from Lake Grevelingen surface sediments were closely related to “Candidatus Scalindua profunda”, whereas anammox bacterial 16S rRNA gene sequences were closely related to “Candidatus Scalindua marina” and “Candidatus Scalindua brodae” as found in Oyster Grounds sediments (0–1 cm and 9–10 cm sediment depth). The analysis of the aprA gene also revealed a diverse sulfur oxidizing community; including affiliations to autotrophic sulfur-dependent denitrifying Beta- and Gammaproteobacteria Thio( - bacillus denitrificans and Sulfuricella denitrificans), chemolithoautotrophic sulfur-dependent nitrate reducing Betaproteobacteria (Thiobacillus thioparus), heterotrophic sulfate reducing Deltaproteo- bacteria (e.g. Desulfosarcina sp., Desulfobulbus propionicus) or phototrophic sulfur oxidizing bacteria (Lamprocystis purpurea). In addition, the diversity of genes involved in carbon fixation and reoxidation pathways were also estimated showing no clustering of sequences according to the depth, station or season. These results were interpreted as an indication of the presence of a stable population of ammonia oxidizing archaea and bacteria, anammox (Chapter 2) and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing bacteria including sulfide-dependent denitrifiers (Chapter 4) in coastal sediments experiencing decreasing bottom water oxygen concentrations due to summer stratification. In general, the microbial community in Lake Grevelingen surface sediments consisted of phototrophic, heterotrophic and autotrophic microorganisms involved in carbon-, nitrogen and sulfur cycling. Thaumarchaeota have been detected in Oyster Ground sediments and Lake Grev- elingen sediments, where they seem to play an important role in the reoxidation of reduced inorganic compounds in order to sustain biogeochemical cycling of carbon and nitrogen compounds especially under oxygenated bottom water conditions and/or in bioturbated sediments (Fig. 1). The diversity of anammox bacteria in Oyster Grounds sediment is comparable to the anammox bacterial diversity in Lake Grevelingen sediments by the 16S rRNA gene diversity, indicating that the diversity of anammox bacteria is less affected by seasonal hypoxia and rising sulfide concentrations compared to the archaeal population as shown in chapter 2 and 4. 7.3. Abundance and distribution of chemolithoautotrophic microorganisms in coastal sediments Microbial processes such as nitrification, denitrification and anammox are important forni- trogen and carbon cycling, and are tightly coupled in marine sediments (Zhang et al., 2013). The abundance and seasonal variations of archaeal and bacterial ammonia oxidizers, anammox and denitrifying, and sulfide dependent denitrifiers, as well as environmental factors affecting these groups, are not well studied in coastal marine sediments. In this thesis, the seasonal and depth distribution of the abundance of these groups was estimated in marine sediments of the Oyster Grounds (North Sea), in sediments of the Iceland shelf, as well as in Lake Grevelingen sediments to get insights of the importance of these groups and their impact in the carbon and nitrogen cycles in selected marine sediments. In Oyster Grounds sediments (Chapter 2) this was achieved by quantifying specific intact polar lipids attributed to ammonia oxidizing Thaumarchaeota (AOA) (i.e. hexose phosphohexose (HPH) crenarchaeol) and anammox bacteria (i.e. phosphatidylcholine (PC)-monoether ladderane), as well as the abundance of the 16S rRNA genes, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) of anammox bacteria, in February, May, and in August during decreasing bottom water oxygen concentrations. One of 172 Synthesis the highlights of the study in the Oyster Grounds sediments is the detection of aerobic ammonia oxidizing microorganisms at depths where the oxygen concentration was expected to be undetectable, which is counterintuitive with their aerobic metabolism. This was attributed to the intense bioturbation reported in these sediments which could provide enough oxygen to support the presence and activity of these microbial groups. This is further supported by other studies like the one of Beman et al. (2012), where AOA and AOB amoA genes were detected up to 10 cm sediment depth in bioturbated sediments of Catalina Island (CA, USA). My results, and those of Beman et al. (2012), suggest that aerobic ammonia oxidizers are indeed living and actively involved in the marine sedimentary nitrogen cycle in deeper layers of coastal marine sediments than previously thought, which is relevant as it extends the area of active dark carbon fixation and nitrification in marine sediments. Another conclusion of the study performed in the Oyster Grounds sediments is that seasonal variation in the abundance of Thaumarchaeota (AOA) within the sediment given by quantification of 16S rRNA and amoA gene were not reflected in the specific Thaumarchaeota lipid biomarker HPH-crenarchaeol quantification, which was stable with depth in the first 12 cm. HPH-crenarchaeol has been shown to be more labile compared to crenarchaeol with a glycosidic head group, and its concentration corresponds well to the DNA-based abundance of Thaumar- chaeota (Pitcher et al., 2011a; Schouten et al., 2012; Lengger et al., 2012a). These results might suggest a possible preservation of this biomarker within the sediment vertical profile which would invalidate the use of it as indicator of abundance of living Thaumarchaeota in deep sediments. The presence and potential activity of Thaumarchaeota were also assessed in Iceland shelf sediment incubations with 13C-labeled substrates (chapter 3). This study also included a direct analysis of IPL-crenarchaeol as specific lipid of Thaumarchaeota. The IPL-crenarchaeol with (HPH)- head group was between 80−90% in surface sediments of all stations and it decreased up to 10−25% in the deepest sediment layer. However, the presence of HPH-crenarchaeol in anoxic parts of the sediment, as seen in the Oyster Grounds sediments (Chapter 2), can again be due to preservation of this compound and cannot be then taken as a biomarker of a living Thaumarchaeota population. In order to rule out a possible preservation effect of lipid biomarkers in deep sediments, the analysis or archaeal lipids was later restricted to surface sediments in Lake Grevelingen in order to determine the abundance and distribution of chemolithoautotrophic ammonia oxidizing Thaumarchaeota as well as other archaeal groups present. The methodological improvement of this study with respect to the one included in Chapter 2 and chapter 3 is that a new method was applied for the detection of the polar head groups of different IPL-GDGTs and was not only restricted to the specific GDGT crenarchaeol of Thaumarchaeota. With this, it was possible to extend the analysis of IPL-GDGT to the entire archaeal population present in the sediments. The detection of HPH-GDGTs in March in Lake Grevelingen sediment, coinciding with a higher presence of Thaumarchaeota detected by 16S rRNA gene amplicon sequence, indicated that the Thaumarchaeota population was actively living in those sediments. On the other hand, the switch to an archaea DPANN-dominated population in August with a similar IPL-GDGT profile, and the fact that DPANN archaea are not genetically capable of synthesizing their own lipids, suggest that this archaea group might be recycling the IPL-GDGTs already present in the sediment. This factor complicates the interpretations of the lipid sources in sedimentary settings 173 Chapter 7 Figureof 1: The as of and activity abundance as well (dark blue), (green)and AOB ofin bioturbated sediments bacteria (yellow) AOA anammox the arrow Grounds (Northabundance potential Oyster indicates depth).bioturbation. Red sediment cm (0–4 Sea) arrowblue Big by supply oxygen indicates and activity of other microbial groups. Please note that the dashed lines do not reflect the actual depth profiles represent the ofprofile biomarkers distribution(find (taken togetherin chapter the abundance and2), but potential activity); (thin dashed line) lower abundance (thicker and dashed activity, lines) higher abundance and activity. 174 Synthesis Representation Representation of the profile distribution (taken together the abundance and potential activity) (dashed lines) andchemolithoautotrophic

C PLFA-SIP) (triangle) in Lake Grevelingen sediments during oxygenated bottom water conditions (left) and during hypoxia (right) (0–5 cm (0–5 (right) and during hypoxia conditions (left) water bottom during oxygenated sediments Grevelingen in Lake (triangle) C PLFA-SIP) 13 activity ( activity Figure2: sediment depth)(green)bacteria, sediment and autotrophic denitrifying heterotrophic Thaumarchaeota,(pink) (dark blue) [color code: 6). and 5 (Chapter 4, sulfate reducing and sulfur microorganismsoxidizing including (purple)sulfide-dependent cable denitrifiers, bacteria, (red) Beggiatoaceae, (light ox - blue) sulfur and reducing sulfate blue) (light Woesearchaeota, idizing Gammaproteobacteria, (dark green) Epsilonproteobacteria, (orange)DPANN oxidizing sulfur Only activity. potential (grey abundant and low characters) active, abundant and potentially disproportioningsulfur characters) (black Deltaproteobacteria]. reduced species and electron acceptors are shown. 175 Chapter 7 and highlight the need of combining different methodological approaches (i.e. lipid biomarkers, gene-based detection, activity measurements) to determine the chemolithoautotrophic potential and biological sources. Also, this study highlights the dramatic change in the archaea population in Lake Grevelingen surface sediments upon summer hypoxia and increase of sulfide concentration in the pore water. This can be explained by a toxic effect of sulfide on the Thaumarchaeota population, together with decrease in oxygen available for their aerobic metabolism. In fact, a similar toxic effect of sulfide has been observed in Thaumarchaeota enrichment cultures from Baltic Sea water (Berg et al., 2015). In this thesis, I have also determined the abundance and distribution of anammox bacteria in different marine sediment systems both by using specific lipid biomarkers and quantification of specific 16S rRNA and metabolic genes. For example, anammox bacteria 16S rRNA and the hydrazine synthase (hzsA) gene abundance were detected throughout the Oyster Grounds sediment with more pronounced depth and seasonal differences than those observed for AOA and AOB. Both, anammox bacteria 16S rRNA and hzsA gene abundances were higher in August compared to February and May, which was not reflected in the abundance of the anammox specific lipid biomarker PC-monoether ladderane. This can be explained by partial preservation of this biomarker lipid in the sediment due to a relatively low turnover rate (Brandsma et al., 2011; Bale et al., 2014). I also observed a ten-fold difference between abundances of the anammox 16S rRNA gene and the hzsA gene. This difference between the 16S rRNA gene and functional genes of anammox bacteria has been previously observed and is possibly explained by primer biases of the 16S rRNA gene primers, suggesting the amplification of 16S rRNA gene fragments of bacteria other than anammox bacteria (Harhangi et al., 2012; Bale et al., 2014). The presence of anammox bacteria biomarkers in the upper layers of Oyster Grounds sediments (0−4 cm) is still remarkable as the metabolism of anammox bacteria is expected to be incompatible with the presence of oxygen. Some studies have reported that anammox bacteria can be present at high oxygen levels, by being dormant or using anaerobic niches (Kuypers et al., 2005; Woebken et al., 2007). It is also possible that the metabolic activity of AOA/AOB and heterotrophic bacteria support the presence of anammox bacteria by oxygen consumption allowing the presence of anammox bacteria even in the oxygenated sediments. My results suggest that anammox bacteria can tolerate the presence of oxygen (Kalvelage et al., 2011; Yan et al., 2012) and co-exist with aerobic ammonia oxidizers and potentially have an important role in the nitrogen cycle in marine sediments. Similarly, anammox bacteria detected in Lake Grevelingen sediments showed a clear seasonal contrast in their nitrite reductase (nirS) gene abundance with higher copy numbers in August during summer hypoxia compared to March, similar to the 16S rRNA and hzsA gene abundance of anammox bacteria detected in Oyster Ground sediments (Chapter 2). The seasonal trend was as well not reflected in the abundance of the anammox bacteria lipid biomarker PC-monoether ladderane lipid, as it has been reported for Oyster Grounds sediments (Brandsma et al., 2011; Bale et al., 2014). In contrast, the concentration of ladderane lipid fatty acids correlated with the abundance of anammox bacteria determined by the 16S rRNA gene abundance, suggesting that the abundance of ladderane lipid fatty acids could be interpreted as a proxy for the abundance of anammox bacteria, together with specific gene quantification. A difference of three to four orders of magnitude between abundances of the anammox 16S rRNA gene and the “Candidatus Scalindua” specific nirS gene was detected. This discordance between the 16S rRNA gene and 176 Synthesis functional genes of anammox bacteria has been previously observed and has been discussed above in detail, thus the possibility of amplifying other bacteria has been ruled out by cloning and sequencing of the product generated during the quantitative PCR reaction for Lake Grev- elingen sediments. Overall, the nirS gene abundance of denitrifiers was three to four orders higher compared to the anammox nirS gene abundance, suggesting that nirS-type denitrifiers have a more prominent role in the nitrogen removal in Lake Grevelingen sediments compared to anammox bacteria. The abundance of denitrifying bacteria did not vary substantially despite of differences in the oxygen and sulfide availability, whereas anammox bacteria were more abundant in the summer hypoxia, but in those sediments with lower sulfide concentrations, indicating that the abundance of anammox bacteria is impaired by high sulfide concentrations as previously suggested by others (Dalsgaard et al., 2003; Jensen et al., 2008). Anammox abundance was also highest in Oyster Grounds sediments (0.5 cm) in August under low bottom water oxygen conditions and decreasing oxygen penetration. These results are most likely explained by of the fact that anammox bacteria are favored by hypoxic conditions (i.e. Neubacher et al., 2013). Besides, the optimum temperature of anammox bacteria of 15°C has been reported in temperate shelf sediments (Dalsgaard et al., 2005) which is close to the summer temperature in Oyster Grounds and Lake Grevelingen sediments (~17°C). Additionally, bioturbation has been shown to extend the area of aerobic processes such as nitrate reduction and thus the availability of reduced compounds such as nitrite, which would fuel the anammox process (Meyer et al., 2005). In Lake Grevelingen sediments, anammox abundance was highest in bioturbated compared to non bioturbated sediments (S3), indicating that bioturbation might additionally favor the abundance of anammox bacteria. Bioturbation has also been reported in Oyster Grounds (Duineveld et al., 1991), which together with the reported high activity of AOA, AOB and/or other aerobic heterotrophs re- moving the available oxygen, could contribute to the proliferation of anammox bacteria. In order to determine the abundance of other microorganisms involved in nitrogen removal in Lake Grevelingen sediments (Chapter 4), I also quantified the nitrite reductase nirS( ) gene of chemoorganoheterotrophic denitrifying bacteria and archaea, performing the stepwise conversion of nitrate/nitrite to dinitrogen gas (Zumft, 1997), as well as the aprA gene of sulfate reducing and sulfur oxidizing bacteria including autotrophic sulfide-dependent denitrifying members of the Alpha-, Beta-, Gamma-, and Epsilonproteobacteria (Shao et al., 2010).The nirS gene abundance has previously been show to correlate positively with potential denitrification rates (Mosier and Francis, 2010). Here, the nirS gene abundance of denitrifying bacteria was relatively constant with sediment depth, suggesting a stable community of heterotrophic and autotrophic denitrifying bacteria actively involved in the denitrification process in Lake Grevelingen sediments. However, assumptions have to be made with caution, because foraminiferal denitrification might be as important as heterotrophic denitrification in marine sediments, as well as metal-dependent denitrification (Devol, 2015). Besides, and some denitrifying microorganisms use the copper-containing nitrite reductase encoded by the nirK gene which could have led to the underestimation of the diversity and abundance of total denitrifiers by exclusively targeting the nirS gene. However, nirS denitrifiers are more likely to have a complete denitrification pathway (including nor and nos genes), suggesting that nirS-containing denitrifiers may be more likely to reduce nitrite to N2 (Graf et al. 2014). In addition, the nirS gene has been shown to be more abundant and more diverse than nirK in estuarine sediments, although this pattern sometimes 177 Chapter 7 shifts in different estuarine regions (Nogales et al. 2002; Abell et al. 2010; Mosier and Francis 2010; Beman, 2014; Smith et al. 2015b; Lee and Francis, 2017). In general, the nirS gene abundance was slightly higher in March in all three stations in Lake Grevelingen sediments (Chapter 4), but the difference was more pronounced in station 1, which can be most likely explained by lower sulfide concentrations in March compared to August. The lower sulfide concentrations in March could favor the proliferation of heterotrophic denitrifiers, as sulfide has been shown to impair denitrification by inhibition of NO and N2O reductases (Sørensen et al., 1980). The abundance of chemolithoautotrophic microorganisms utilizing the CBB and rTCA pathways for carbon fixation was also estimated in Lake Grevelingen sediments (Chapter 5) by quantifying the cbbL and aclB gene, encoding for the key-enzymes ribulose 1,5 bisphosphate carboxylase/oxygenase (CBB) and ATP citrate lyase (rTCA). Significant differences were determined in the abundance of cbbL and aclB genes between the seasons but not between the stations, suggesting a stable community of community of autotrophic microorganisms using the CBB and rTCA pathway. The abundance of the cbbL gene was at least 2-fold higher than aclB gene abundance independent of the season or station, indicating a more prominent role of microorganisms using the CBB cycle compared to those using the rTCA pathway. The results indicated a more important role of autotrophic aerobic or facultative aerobic Gammaproteobacteria of the orders Chromatiales and Thiotrichales compared to Epsilonproteobacteria of the order Cam- pylobacterales and Euryarchaeota in Lake Grevelingen sediments. However, these assumptions have to be made with caution, as the primers used to amplify aclB genes are mainly based on sequences of Epsilonproteobacteria (Campbell et al., 2006), suggesting that potentially there is an underestimation of the abundance of microorganisms using the rTCA pathway in these sediments, as well as the abundance of microorganisms using other carbon fixation pathways than the CBB or rTCA pathway (Hügler and Sievert, 2011; Berg et al., 2010, 2011). Taking all the considerations mentioned above, the determination of the abundance of microorganisms based on DNA sequences and lipid biomarker molecules in marine coastal and estuarine sediments has to be interpreted with caution. DNA-based methods employed in this thesis depend on PCR amplification with primers, designed based on the sequences available in the databases, potentially causing an underestimation of the diversity as well as of the abundance of target organisms. As the abundance of functional and 16S rRNA genes was estimated by qPCR and 16S rRNA gene amplicon sequencing, I cannot completely rule out primer induced PCR biases (Schloss et al., 2011; Sipos et al., 2010). Additionally, DNA and lipid biomarkers can be partly preserved in anoxic sediments, which possibly leads to an overestimation of the abundance of the studied microorganisms (Torti et al., 2015; Lengger et al., 2012; Rush et al., 2012). 7.4. Activity of chemolithoautotrophic microorganisms in coastal sediments In my thesis, I have estimated activity by determining incorporation of 13C-labeled substrates in membrane lipids as well as the gene expression of 16S rRNA and functional genes as proxy of transcriptional activity. The abundance and gene expression of functional genes has been frequently interpreted as an indication of the process rate in which the protein-coding gene is involved (Nogales et al., 2002; Smith et al., 2007; Abell et al., 2010, 2011; Bowen et al., 2014). However, this is not always the case and it is in general dependent on the regulation of the specific gene under study. As an example, the transcript levels of the coding gene for the dissimilatory sulfite reductase dsrA( ), catalyzing the final step in sulfate reduction, has been seen to positively 178 Synthesis correlate with sulfate reduction rate (SRR) when growing under limited electron acceptor (sulfate) while no correlation between SRR and dsrA gene expression was observed when grown under electron donor limitation (Villanueva et al., 2008). Similarly, a recent study by Carini et al. (2017) observed that ammonia limitation in the thaumarchaeon “Candidatus Nitrosopelagicus brevis” induced a decrease in the expression of the ammonia oxidation core proteins, which could be interpreted as a confirmation that lower ammonia oxidation activity is correlated to lower amoA gene expression levels. However, this study also concluded that the genes involved in ammonia oxidation constitute a large part of the total transcript pool irrespective of growth and environmental conditions, which makes it difficult to connect changes in gene expression to differences in the metabolic process. Examples like this illustrate the need of studying, in pure cultures and under controlled conditions, the regulation of the expression of metabolic genes and its potential correlation to the process rates before making definite conclusions based on environmental samples. In this thesis, several metabolic genes involved in key re-oxidation pathways were analyzed for their gene expression patterns in environmental samples. For some of these genes, previous information on the regulation of their gene expression was available (e.g. AOA amoA gene; Abell et al., 2011), which allowed us to interpret the results more confidently. For some other genes, e.g. anammox bacterial hzsA gene (Harhangi et al., 2011), the determination of their gene expression and comparison with their gene abundance and process rate in environmental samples in this thesis (Chapters 2, 4), has allowed to get a better understanding of the environmental conditions that can affect the activity of the metabolic process. To estimate the activity of aerobic and anaerobic ammonia oxidizers and anammox bacteria in coastal sediments, the gene expression of their 16S rRNA gene, the amoA gene of AOA and AOB, and the expression of the anammox bacterial hzsA gene, were analyzed here by quantifying the transcript abundance by reverse transcription and subsequent qPCR, in sediments of the Oyster Grounds (North Sea) (Chapter 2) and in Lake Grevelingen (chapter 4). The detection of the transcriptional activity of the AOA 16S rRNA gene up to 12 cm depth in Oyster Grounds sediment supports that AOA are indeed active in subsurface sediments. The potential transcriptional activity, by the 16S rRNA gene RNA:DNA ratio, was higher during winter, whereas the abundance was slightly higher during the summer months. The AOA amoA gene RNA:DNA ratio has been detected in August throughout the core but only in the upper 3 cm in February, because the quantity of transcripts in other seasons and depths was under the detection limit of the qPCR assay. However, the relationship of amoA gene expression and in situ ammonia oxidation is still unclear (Lam et al., 2007; Nicol et al., 2008; Abell et al., 2011; Vissers et al., 2013). Recent studies have observed a good correlation between nitrification rates and the abundance of amoA genes and transcripts in coastal waters (Smith et al., 2014; Urakawa et al., 2014), indicating that the detection of AOA amoA transcripts suggest AOA were active in Oyster Grounds sediments in the summer throughout the sediment in comparison with the winter in which AOA would be only active in the upper part of the sediment (upper 2 cm). The abundance of AOB amoA transcripts was higher than for AOA, and was detected up to 12 cm sediment depth in all seasons, which would suggest a higher AOB activity compared to AOA. However, a study by Urakawa et al. (2014) in estuarine waters did not observe a correlation between nitrification rates and AOB amoA transcripts. Additionally, previous studies have detected the presence of AOB amoA transcripts in non-active starved cells (Bollmann et al., 2005; 179 Chapter 7

Geets et al., 2006; Sayaveda-Soto and Arp, 2011) indicating that the AOB amoA transcriptional activity is not a good indicator of AOB nitrification activity due to a longer half-life of AOB amoA transcripts than expected for AOA amoA transcripts. The metabolic capacities of sedimentary Thaumarchaeota are still under debate. To shed further light on this important chemolithoautotrophic metabolism in marine sediments, we also performed labeling experiments using 13C-labeled substrates, such as bicarbonate, pyruvate, amino acids and glucose in sediment cores of the Iceland Shelf (Chapter 3) and determined the degree of 13C-incorporation into the most abundant GDGT lipids, i.e. crenarchaeol and GDGT-0. These compounds have been suggested to be taken up by Thaumarchaeota in the environment (Ouverney and Fuhrman, 2000; Wuchter et al., 2003; Herndl et al., 2005; Takano et al., 2010; Pitcher et al., 2011c), or in enrichment cultures (Park et al., 2010; Jung et al., 2011; Tourna et al., 2011; Kim et al., 2012), and are possibly the most suitable substrates resulting in uptake by sedimentary Archaea. However, the incubation with labeled 13C substrates did not result in any substantial incorporation of the 13C into the biphytanyl chains of these lipids. No incorporation of 13C in IPL-GDGT was detected in clay rich and organic rich sediments, whereas some enrichment in δ13C (1−4‰) of IPL-GDGTs recovered from sandy sediment was detected after incubation with bicarbonate and pyruvate. This apparent lack of uptake could be due to several reasons. It is possible that the Thaumarchaeota were active, but the substrates were not taken up. Secondly, it is possible that most of the IPLs measured are fossil, and thus only a small amount of these IPLs are part of living and active sedimentary Thaumarchaeota, as also discussed above. Another possibility is that the metabolism and growth rates are so slow that no incorporation could be detected over the timescales investigated. Thus, the incubation period of 96−144 h, may have been too short. These results suggested that sedimentary Thaumarchaeota grow slowly in contrast to other sedimentary organisms, and/or a slow turn-over of IPL-GDGTs compared to bacterial/eukaryotic PLFAs. Interestingly, enrichment culture experiments with a thaumarchaeal strain closely related (99%) to Nitrosopumilus maritimus (SCM1), discovered that α-keto acids, such as pyruvate and oxaloacetate, were not directly incorporated into AOA cells, but functioned as chemical scavengers that detoxified intracellularly produced H2O2 during ammonia oxidation (Kim et al., 2016), indicating that previous findings of pyruvate incorporation could have been misinterpreted as evidence for mixotrophic growth of AOA. In order to determine the potential activity of anammox bacteria in Oyster Grounds and Lake Grevelingen sediments, the potential transcriptional activity of the 16S rRNA gene, as well as of the functional genes hzsA and nirS encoding for the key-enzymes of the anammox reaction, hydrazine synthase and nitrite reductase (Chapter 2 and 4, respectively). A previous study by Bale et al. (2014) observed a good correlation between anammox rate activity and anammox bacterial 16S rRNA transcript abundance in North Sea sediments, suggesting that the transcriptional activity of anammox bacteria 16S rRNA gene is a good proxy for anammox bacteria activity. In Oyster Grounds sediments, the transcriptional activity of anammox bacteria 16S rRNA and hzsA gene was detected throughout the sediment in all seasons, and the 16S rRNA RNA:DNA ratio was higher during summer as observed for the anammox bacteria abundance. In Lake Grevelingen sediments the anammox 16S rRNA gene transcript abundance was detected throughout the sediment. However, the anammox bacteria 16S rRNA RNA:DNA ratio was low (0.01−1) compared to the values reported in sediments of the Oyster Grounds (1.6−34.5), further supporting a low anammox activity in Lake Grevelingen sediments.

180 Synthesis

Nevertheless, quantification results of anammox bacteria 16S rRNA gene have to be interpreted with caution because there is evidence that the ribosome content does not decrease during the period of starvation (Schmid et al., 2005; Li and Gu, 2011). Besides, the increase of anammox bacteria 16S rRNA gene transcriptional activity during summer in Oyster Grounds sediments was not observed for the hzsA gene, which remained stable with sediment depth and also for the different seasons. The low and constitutive transcriptional activity of the hzsA gene indicates that the hzsA gene transcript abundance does not reflect variations of anammox bacteria activity in environmental sediment samples, thus the hzsA transcript abundance does not seem to be an adequate biomarker for the estimation of the activity of anammox bacteria. Fur- ther experiments, preferably with pure cultures and under controlled physiological conditions, should be performed to clarify the regulation of the hzsA gene expression. Environmental conditions favoring the abundance and activity of anammox bacteria have been discussed above in detail. Bioturbation activity could explain the differences in the activity of anammox bacteria in sediments of the Oyster Grounds compared to the Lake Grevelingen sediments, where only in station S3 bioturbators have been recognized in March, coinciding with the highest anammox abundance compared to the other stations. Additionally, the activity of anammox bacteria might be inhibited by high carbon and sulfide concentrations, as discussed above, probably explaining the higher activity of anammox bacteria in Oyster Grounds (low TOC), compared to Lake Grevelingen sediments (high TOC). To further estimate the potential activity of microbial groups involved in denitrification other than anammox bacteria, i.e. denitrifying bacteria, sulfate reducing/sulfur oxidizing bacteria including sulfide-dependent denitrifying microorganisms, in seasonal hypoxic and sulfidic sediments of Lake Grevelingen (Chapter 4), I also analyzed the potential transcriptional activity of these groups. This was achieved by quantifying the nirS transcript abundance of denitrifying bacteria, as well as the aprA transcript abundance of sulfate reducing and sulfur oxidizing microorganisms. Unfortunately, there is a lack of studies correlating the nirS gene expression of denitrifying bacteria with denitrification rates, and some studies have shown a lack of direct relationship between nirS gene expression and modeled rates of denitrification in marine surface sediments (Bowen et al., 2014), whereas other studies have observed a correlation between a decrease of nirS transcript abundance and the reduction of denitrification rates coinciding with declining concentrations of nitrate in estuarine sediments (Dong et al., 2000, 2002; Smith et al., 2007). These studies would justify the use of nirS gene transcript abundance as a proxy for denitrification performed bynirS -type denitrifiers. In my study, thenirS transcript abundance of nirS-type denitrifiers was two or three orders lower compared to values previously reported for estuarine sediments, suggesting a low denitrification rate in surface sediments of all stations in March and in deeper sediment layers in August. Gene expression of the nirS gene was detected in surface sediments in March (all stations) and in deeper layers in August (stations S1 and S3), which is most likely explained by the availability of nitrate/nitrite in the bottom water. The potential transcriptional activity of sulfate reducing and sulfur oxidizing including chemolithoautotrophic sulfide-dependent denitrifiers, determined by the aprA gene RNA:DNA ratio was relatively low (≤ 0.00088), which also indicated a low denitrification potential of these groups. Although denitrification was more relevant than the anammox process as suggested by the gene abundance and potential transcriptional activity, and measured denitrification rates (between 36 and 96 μM m−2 d−1; Seitaj, D. personal communication) in Lake Grevelingen sediments 181 Chapter 7 which were low compared to other marine sediments. Denitrification rates vary between 30 and 270 μM m−2 d−1 in marine arctic sediments (Rysgaard et al., 2004), whereas in estuarine sediments of the lower St. Lawrence estuary, denitrification rates of 270 ± 30 μM m−2 d−1 were measured (Crowe et al., 2012). The lower denitrification and anammox potential in Lake Grev- elingen sediments could be explained by the effect of high concentrations of sulfide, potentially inhibiting both heterotrophic denitrification and anammox. Another explanation of the low denitrification and anammox potential of Lake Grevelingen sediments can be found in the interactions of anammox and heterotrophic denitrifiers with sulfur-oxidizers also involved in the nitrogen cycle. Large filamentous sulfur oxidizing bacteria have been detected in Lake Grevelin- gen sediments, i.e. cable bacteria and Beggiatoaceae including the genera Beggiatoa, Thiomargarita and Thioploca (Salman et al., 2011, 2013). Cable bacteria perform electrogenic sulfur oxidation (e-SOx), in which the oxidation of the electron donor and the reduction of the electron acceptor are separated over cm-scale distances and the redox coupling is ensured by long distance electron transport (Nielsen et al., 2010; Pfeffer et al., 2012). Cable bacteria can play a role in bioavailable nitrogen removal, as they have been shown to use oxygen but might as well use nitrite and nitrate (Meysman et al., 2015; Marzocchi et al., 2014; Risgaard-Petersen et al., 2014).

Additionally, Beggiatoaceae couple the oxidation of sulfide to nitrate reduction resulting in N2 + and/or NH4 (Mußmann et al., 2003). Previous studies have observed that in anoxic sediments both denitrification and anammox can be supported by intracellular nitrate transport, performed by sulfide-oxidizingThioploca and Beggiatoa (Mußmann et al., 2007; Jorgensen, 2010; Prokopenko et al., 2013) down to deeper sediment layers and possibly supplying anammox and denitrifying bacteria with nitrite and/or ammonia produced by DNRA (Teske and Nelson, 2006; Proko- penko et al., 2011). Cable bacteria have been detected in S1 and S3 in March, whereas station S2 was dominated by Beggiatoaceae down to ~3 cm, but both groups were hardly detected in subsurface sediments (0.5 cm downwards) during summer hypoxia. The presence of sulfide-dependent denitrifiers, as shown by theaprA gene abundance and diversity, as well as the presence of cable bacteria and Beggiatoa-like bacteria could potentially support the denitrification and anammox processes in March. However, the nitrate and nitrite concentrations in the bottom water in March were reported to be relatively low (28 and 0.7 μM on average, respectively). This limitation could induce a strong competition for nitrate, nitrite and sulfide with Beggiatoaceae, cable bacteria and other nitrate-reducing bacteria, which may explain the limited denitrification potential observed in March. During summer hypoxia (August), sulfide inhibition and low nitrate and nitrite concentrations seem to limit the activity of heterotrophic and autotrophic denitrifiers and anammox bacteria. Further studies, involving denitrification rate measurements will be required to further assess the effects of hypoxia and high sulfide concentrations in the sediments of Lake Grevelingen. The chemolithoautotrophic activity of the bacterial community has also been determined by PLFA analysis combined with 13C-stable isotope probing in Grevelingen sediments (Chapter 5). In March, under oxygenated bottom water conditions, the chemolithoautotrophic rates were substantially higher than those in August, when oxygen in the bottom water was depleted to low levels. Moreover, in August, the chemolithoautotrophic rates showed a clear decrease in with water depth (S3 to S1), which is in line with the bottom water oxygen concentration over water depth. At the same time, the 16S rRNA gene amplicon sequencing revealed that the response of the chemolithoautotrophic bacterial community in surface sediments is associated

182 Synthesis with the seasonal changes in the bottom water oxygen concentrations. As described above, in March the microbial community in surface sediments of all stations was characterized by high relative abundances of chemolithoautotrophic sulfur oxidizing Gammaproteobacteria and Ep- silonproteobacteria using oxygen or nitrate as electron acceptor. In August, the lack of oxygen and nitrate in the bottom water was accompanied by a decrease in the relative abundances of Gamma- proteobacteria and Epsilonproteobacteria, and an increase of the relative abundance of heterotrophic sulfate-reducing Deltaproteobacteria using sulfate as electron acceptor. These results support the chemolithoautotrophic rates measured in March and August, indicating that the lack of electron acceptors such as oxygen and nitrate induced by hypoxia limiting the activity of chemolithoautotrophic bacteria in August. Recently, a study by Jessen et al. (2017) addressed the effects of hypoxia on the microbial community composition in Black Sea sediments, and showed that variations in oxygen supply to the seafloor influenced the composition of the bacterial community in surface sediments. Similar to my results, they reported an increase of Del- taproteobacteria under variable to anoxic conditions, whereas Gammaproteobacteria reached highest abundances under variable hypoxic conditions while decreasing toward stable oxic and anoxic conditions (Jessen et al., 2017). Together, these results show the important impact of bottom water hypoxia on the microbial community composition and especially on chemolithoautotrophs in sediments. 7.5. Outlook In the last five years, new and improved methods have been developed and their cost reduced, which would now make them compatible with studies with a massive amount of samples. In the last two chapters of this thesis, I have already applied both 16S rRNA gene amplicon sequencing and lipid analysis with high resolution accurate mass/mass spectrometry that showed a quantitative and qualitative increase in the amount of data and the estimation of the diversity of not only chemolithoautotrophic microorganisms. The studies included in this thesis regarding the gene expression and abundance of key metabolic genes of chemolithoautotrophs under different environmental and physiological conditions have shed further light on the role of this group in the carbon and nitrogen cycle in coastal sediments. In this thesis, the diversity of chemolithoautotrophic microorganisms was mostly determined with gene-targeted approaches, either by amplifying and sequencing specific 16S rRNA gene or functional genes involved in the carbon fixation of re-oxidation pathways. In this synthesis, I have listed the disadvantages of this approach mainly due to the biases introduced by the primer design, lack of sequences in databases, and inherent PCR amplification biases. Currently, these limitations could have been overcome by metagenomic and metatranscriptomic approaches, which are now much more affordable, the data analysis is more feasible, and most importantly they are not PCR-biased. With this approaches, I could have determined both diversity and the gene expression of chemolithoautotrophic key genes. However, the connection between gene expression and the activity of the actual process is still problematic. This information can only be validated by laboratory experiments in which the regulation of the gene of interest is thoroughly studied under different physiological and environmental conditions. Another recommendation is the combination of activity proxy measurements included in this thesis with direct rate measurements when possible to directly assess if the gene expression can be correlated to the activity measurement. Apart from using metatranscriptomics, the activity

183 Chapter 7 of specific microorganisms could now also detected by using more sensitive approaches than the lipid-SIP approaches used in this thesis. For example, nano-scale secondary ion mass spectrometry (NanoSIMS) in combination with catalyzed reporter deposition (CARD)- fluorescence in situ hybridization (FISH) has proven to be very effective for the determination of metabolic capacity linked to phylogenetic identity at the single cell level (Behrens et al., 2008; Musat et al., 2008; Morono et al., 2011). However, a problem that remains is that this method still relies on incubation with labeled substrates with the inherent limitations of labeling-based incubations including labeling incubation time and cross-feeding of 13C metabolites produced by the primary consumers of the 13C substrate. Finally, in this thesis both specific lipid biomarkers for targeted groups (i.e. crenarchaeol for Thaumarchaeota, ladderane lipids for anammox) and bacterial and archaeal lipid characterization were performed in sediment samples with the aim of determining the abundance and activity (i.e. Lipid-SIP) of chemolithoautotrophs. However, I have seen that some of this biomarkers (i.e. HPH-crenarchaeol, PC-ladderane) are potentially preserved in deeper sediments invalidating their use as proxies of living biomass. In this regard, a recommendation would be to continue in the search of lipid biomarkers that can be more representative of living biomass and less prone to preservation. Laboratory cultures together with characterization of the microbial lipidome with methods similar to the ones applied in Chapter 6 (i.e. high resolution accurate mass spectrometry) to detect intact polar lipids would be key in improving this issue. Also in chapter 6, I have seen the potential recycling of IPLs by archaeal groups like the DPANN. Further studies need to carefully assess the effect of such lipid recycling in sediment and the interpretations derived from those results.

184

Summary

The role of chemolithoautotrophic microorganisms has been considered to be of minor importance in coastal marine sediments although it has not been investigated in depth. Additionally, the impact of seasonal hypoxic/anoxic conditions on microbial chemolithoautotrophy in coastal marine sediments has not been examined. Therefore, in this thesis the diversity, abundance and activity of specific groups of chemolithoautotrophic microorganisms involved in the nitrogen and sulfur cycling, as well as the total microbial community, has been determined in coastal sediments by using DNA/RNA- and lipid-based biomarker approaches. Results show the presence and potential importance of chemolithoautotrophs in the biogeochemical cycling of carbon, nitrogen and sulfur. Temporal changes of the diversity, abundance and activity of chemolithoautotrophic microorganisms coinciding with seasonal hypoxia in coastal sediments have been determined. The diversity, abundance and activity of chemolithoautotrophic microorganisms, such as ammonia oxidizing archaea (AOA) and bacteria (AOB), anammox and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing microorganisms, including sulfide dependent denitrifiers, have been determined. Additionally, the diversity and activity of chemolithoautotrophic microorganisms involved in the CBB and rTCA cycle as well as the metabolism of Thaumarchaeota and the abundance of Archaea have been addressed. In the following studies, we focused on coastal marine sediments, exposed to summer hypoxia, i.e. (1) the Oyster Grounds in the central North Sea, exposed to decreasing bottom water oxygen concentrations, (2) different sediment types (sand, clay, and mud) of the Iceland Shelf, and (3) seasonally hypoxic and sulfidic sediments of saline Lake Grevelingen (The Netherlands). In Oyster Grounds sediments (chapter 2), seasonal variations of archaeal and bacterial ammonia oxidizers (AOA and AOB) and anammox bacteria, as well as the environmental factors affecting these groups, were addressed. We examined the seasonal and depth distribution of the abundance and potential activity of these microbial groups in coastal marine sediments of the southern North Sea. We quantified specific intact polar lipids (IPLs) as well as the abundance and gene expression of their 16S rRNA gene, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) gene of anammox bacteria. AOA, AOB and anammox bacteria were detected and transcriptionally active down to 12 cm sediment depth. This study unraveled the coexistence and metabolic activity of AOA, AOB, and anammox bacteria in bioturbated marine sediments of the North Sea, leading to the conclusion that the metabolism of these microbial groups is spatially coupled based on the rapid consumption of oxygen that allows the coexistence of aerobic and anaerobic ammonia oxidizers. AOA outnumbered AOB throughout the year which may be caused by the higher oxygen affinity of AOA compared to AOB. Anammox bacterial abundance and activity were higher during summer, indicating that their growth and activity are favored by higher temperatures and lower oxygen available in the sediments due to summer stratifying conditions in the water column. During the summer, anammox bacteria are probably not in competition with AOA and AOB for ammonia as the concentrations were relatively high in the sediment pore water most likely as a result of ammonification processes and the activity of denitrifiers and DNRA. In Iceland Shelf sediments (chapter 3), we investigated the activity of Thaumarchaeota in sediments by supplying different 13C-labeled substrates which have previously been shown to be 187 incorporated into archaeal cells in water incubations and/or enrichment cultures. We determined the incorporation of 13C-label from bicarbonate, pyruvate, glucose and amino acids into thaumarchaeal intact polar lipid-glycerol dibiphytanyl glycerol tetraethers (IPL-GDGTs) during 4–6 day incubations of marine sediment cores from three sites on the Iceland Shelf. Thaumarchaeal IPLs were present in sediment cores recovered from the Iceland Shelf and the presence of labile IPL-biomarkers for Thaumarchaeota, such as hexose phosphohexose (HPH)-crenarchaeol, suggested the presence of living Thaumarchaeota. However, incubations with 13C-labeled substrates bicarbonate, pyruvate, glucose and amino acids did not result in any substantial incorporation of the 13C into the biphytanyl chains of these lipids. Turnover times and generation times of thaumarchaeal lipids were estimated to be at least several years, suggesting slow growth of sedimentary Thaumarchaeota in contrast to other sedimentary organisms, and/or a slow degradation of IPL-GDGTs, in contrast to bacterial or eukaryotic PLFAs. In Lake Grevelingen sediments (chapter 4), we evaluated the abundance, diversity and potential activity of denitrifying, anammox, and sulfide-dependent denitrifying bacteria in the sediments of the seasonally hypoxic saline Lake Grevelingen, known to harbor an active microbial community involved in sulfur oxidation pathways. Depth distributions of 16S rRNA gene, nirS gene of denitrifying and anammox bacteria, aprA gene of sulfur-oxidizing and sulfate-reducing bacteria, and ladderane lipids of anammox bacteria were studied in sediments impacted by seasonally hypoxic bottom waters. This study unraveled the coexistence and potential activity of heterotrophic and autotrophic denitrifiers, anammox bacteria as well as SOB/SRB in seasonally hypoxic and sulfidic sediments of Lake Grevelingen. The nirS-type heterotrophic denitrifiers were a stable community regardless of changes in oxygen and sulfide concentrations in different seasons and with a similar abundance to that detected in other sediments not exposed to high sulfide concentrations. Besides, nirS-type denitrifiers outnumbered anammox bacteria leading to the conclusion that anammox does not contribute significantly to the N2 removal process in Lake Grevelingen sediments. The anammox bacteria population seemed to be affected by the physicochemical conditions between seasons and their abundance and activity was higher in lower sulfide concentrations and low carbon input, also supporting a possible inhibition of anammox bacteria by sulfide. The sulfide-dependent denitrifiers in Lake Grevelingen sediments have proven to be abundant, but their expected sulfide-detoxification potential did not seem to alleviate the predicted inhibition of organoheterotrophic denitrifiers and anammox by sulfide. Both denitrifiers and anammox bacteria activity could be inhibited by the competition with cable bacteria and Beggiatoaceae for electron donors and acceptors (such as sulfide, nitrate and nitrite) before summer hypoxia but might be still supported by the potential sulfide detoxification of the sediment through sulfide oxidation, supporting at least a low activity. During summer hypoxia, sulfide inhibition and low nitrate and nitrite concentrations seem to limit the activity of heterotrophic and autotrophic (sulfide-dependent) denitrifiers and anammox bacteria. Additionally, we examined the changes in activity and structure of the sedimentary chemolithoautotrophic bacterial community in Lake Grevelingen under oxic (spring) and hypoxic (summer) conditions (Chapter 5). Combined 16S rRNA gene amplicon sequencing and analysis of phospholipid derived fatty acids indicated a major temporal shift in community structure. Chemolithoautotrophy rates in the surface sediment were three times higher in spring compared to summer. Besides, the depth distribution of chemolithoautotrophy was linked to the distinct sulfur oxidation mechanisms identified through microsensor profiling, i.e., canonical sulfur ox-

184 idation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae. The metabolic diversity of the sulfur-oxidizing bacterial community suggests a complex niche partitioning within the sediment probably driven by the availability of reduced sulfur compounds and electron acceptors regulated by seasonal hypoxia. In Lake Grevelingen sediments, we also compared the archaeal abundance and composition by DNA-based methods and the archaeal intact polar lipid (IPL) diversity in surface sediments to determine the potential biological sources of the archaeal IPLs detected in surface sediments under changing environmental conditions (Chapter 6). We observed a dramatic change in the archaeal community composition and lipid abundance in surface sediments of a seasonally hypoxic marine lake which corresponded to a switch from a Thaumarchaeota-dominated to a DPANN-dominated archaeal community, while the total IPLs detected were significantly reduced. Considering the reduced genome of the members of the superphylum DPANN and their apparent inability to synthesize their own membrane lipids, we hypothesize that they use the CLs previously synthesized by the Thaumarchaeota to form their membrane. Results indicate an active recycling of fossil IPLs in the marine surface sediment. Overall, the research presented in this thesis has provided new insights on the diversity, abundance and activity of chemolithoautotrophic microorganisms, such as AOA, AOB, anammox and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing microorganisms, including sulfide-dependent denitrifiers in coastal marine sediments. Hypoxia and increasing sulfide concentration have proven to be key factors restricting the presence and activity of the above mentioned groups. In addition, the interactions with other microbial groups and bioturbation seem to favor the presence of specific chemolithoautotrophs in unexpected sediment depths, such as the presence of AOA in depths where the oxygen concentration was expected to be undetectable, or the presence of anammox bacteria in bioturbated sediments where nitrate reducers could thrive and provide nitrite to fuel the anammox process. In general, the methods employed in these studies regarding the gene expression and abundance of key metabolic genes of chemolithoautotrophs under different environmental and physiological conditions have shed further light on the role of this group in the carbon and nitrogen cycle in coastal sediments. However, the connection between gene expression and the activity of the actual process is still be problematic and future studies should address the regulation of specific metabolic genes under different physiological and environmental conditions. Finally, the application of specific lipid biomarkers to detect the presence and abundance of specific chemolithoautotrophs in coastal sediments (i.e. crenarchaeol for Thaumarchaeota, ladderane lipids for anammox) has revealed a potential preservation effect of these biomarkers in deeper sediments potentially invalidating their use as proxies of living biomass. Further studies are needed to fully assess this effect as well as the recycling of intact polar lipids by specific archaeal groups.

189

Samenvatting

De rol die chemolithoautotrofe micro-organismen spelen in sedimenten van kustzeeën is nog steeds onduidelijk. Met name is het effect van het optreden van seizoensgebonden hypoxische/ anoxische condities op de microbiële chemolithoautotrofe gemeenschappen niet onderzocht. In dit proefschrift is de diversiteit, celaantallen en activiteit van specifieke groepen chemolithoautotrofe micro-organismen die actief zijn in de stikstof- en zwavelcyclus, in relatie tot de totale microbiële gemeenschap, in kustsedimenten onderzocht door gebruik te maken van op DNA/ RNA en lipiden gebaseerde biomarker benaderingen. Specifiek gaat het om ammonia-oxiderende archaea (AOA) en bacteriën (AOB), anammox en denitrificerende bacteriën, sulfaat-reducerende en zwavel-oxiderende micro-organismen (waaronder sulfide-afhankelijke denitrificerende bacteriën). Ook werden de diversiteit en activiteit van chemolithoautotrofe micro-organismen betrokken bij de CBB- en rTCA-cycli bestudeerd. De studie richtte zich op sedimenten van kustzeeën, d.w.z. (1) de Oestergronden in de centrale Noordzee, die gedurende de zomer blootgesteld zijn aan verlaagde zuurstofconcentraties, (2) verschillende soorten sedimenten (zand, klei en modder) van de IJslandse kustzeeën, en (3) hypoxische en sulfidische sedimenten van het zoute Grevelingenmeer (Nederland), blootgesteld aan seizoensgebonden hypoxia. De resultaten laten het belang van chemolithoautotrofe micro-organismen in de biogeochemische cycli van koolstof, stikstof en zwavel zien. Seizoensgebonden veranderingen in zuurstofconcentratie leiden tot grote tijdelijke veranderingen in het aantal, de diversiteit, en activiteit van chemolithoautotrofe micro-organismen. In de gebioturbeerde sedimenten van de Oestergronden in de zuidelijke Noordzee zijn de seizoensvariaties en diepteverdeling in concentratie van AOA en AOB en anammox-bacteriën in relatie tot omgevingsfactoren bestudeerd (hoofdstuk 2). Specifieke intacte polaire lipiden (IPL) zijn gekwantificeerd. Daarnaast werden specifieke 16S rRNA-genen, het ammoniakmonoox- ygenase subeenheid A (amoA) gen van AOA en AOB, en het hydrazine synthase (hzsA) gen van anammox bacteriën en hun expressie gekwantificeerd. AOA, AOB en anammox bacteriën werden gedetecteerd en waren actief tot 12 cm diepte in het sediment. Het metabolisme van deze microbiële groepen is ruimtelijk gekoppeld op basis van zuurstofverbruik, hetgeen de coëx- istentie van aërobe en anaërobe ammonia-oxiderende bacteriën mogelijk maakt. AOA waren gedurende het hele jaar meer dominant aanwezig dan AOB, hetgeen waarschijnlijk veroorzaakt wordt door de hogere zuurstofaffiniteit van AOA in vergelijking met AOB. De celaantallen en activiteit van anammox bacteriën waren hoger in de zomer. Dit wordt waarschijnlijk veroorzaakt door hogere temperaturen en lagere zuurstofbeschikbaarheid in de sedimenten gedurende de periode van zomerstratificatie. Gedurende de zomer zijn de anammox bacteriën waarschijnlijk niet in concurrentie met AOA en AOB voor ammonia omdat de concentraties betrekkelijk hoog waren in het poriewater van het sediment, waarschijnlijk als gevolg van ammonificatie processen. In sedimenten van IJslandse kustzeeën werden de activiteit van ammonia-oxiderende Thau- marchaeota onderzocht met behulp van verschillende 13C-gelabelde substraten, die in eerdere studies met incubatie met verrijkingsculturen en zeewater succesvol bleken (hoofdstuk 3). Sedi- mentkernen werden gedurende 4-6 dagen geïncubeerd met 13C-gelabeled bicarbonaat, pyruvaat, glucose en aminozuren en opname van het label in Thaumarchaeale in de membraanlipiden (intacte polaire glyceroldibiphytanylglyceroltetraethers; IPL-GDGTs) werd bepaald. De aanwezigheid van labiele IPL-GDGT membraanlipiden karakteristiek voor Thaumarchaeota, zoals 191 hexosefosfoshexose (HPH) -crenarchaeol, duidde op de aanwezigheid van levende Thaumar- chaeota. Incubatie met de 13C-gemerkte substraten leidde echter niet tot een substantiële inbouw van het 13C label in de bifytanylketens van deze membraanlipiden. Omzettijden en generatieti- jden van thaumarchaeale lipiden werden geschat op ten minste enkele jaren, hetgeen duidt op een trage groei van sedimentaire Thaumarchaeota of een langzame afbraak van IPL-GDGTs. Dit contrasteert met de bacteriële of eukaryotische membraanlipiden (vetzuren afkomstig van polaire lipiden) waar het label wel in terecht kwam. In het sediment van het Grevelingenmeer werden de diversiteit, celaantallen en potentiële activiteit van denitrificerende, anammox en sulfide-afhankelijke denitrificerende bacteriën bestudeerd (hoofdstuk 4). De concentratie van 16S rRNA-genen, het nirS-gen van denitrificerende en anammox bacteriën, het aprA-gen van zwavel-oxiderende (SOB) en sulfaat-reducerende (SRB) bacteriën en ladderaanlipiden van anammox bacteriën werd bepaald in sedimenten tot 5 cm diepte op drie verschillende plaatsen en op twee verschillende momenten in het jaar. De condities in de sedimenten van het Grevelingenmeer worden sterk beïnvloed door het seizoensgebonden optreden van hypoxia in het bodemwater. Deze studie toont de coëxistentie en po- tentiële activiteit van heterotrofe en autotrofe denitrificerende bacteriën, anammox bacteriën en SOB/SRB aan. De heterotrofe denitrificerende bacteriën van het nirS-type vormen een sta- biele gemeenschap, die onafhankelijk is van de veranderingen in zuurstof- en sulfideconcentratie gedurende de verschillende seizoenen. Hun celaantallen zijn even hoog als in sedimenten die niet gekenmerkt werden door hoge sulfideconcentraties. NirS-type denitrificerende bacteriën overtroffen in aantal de anammox bacteriën, hetgeen suggereert dat anammox niet significant bijdraagt aan stikstofverwijdering in sedimenten van het Grevelingenmeer. De gentranscriptie activiteit van denitrificerende en anammox bacteriën evenals van zwaveloxiderende, waaronder sulfide-afhankelijke denitrificerende en sulfaat-reducerende bacteriën, werden mogelijk door de accumulatie van sulfide in de zomer geïnhibeerd. Zowel de denitrificerende en anammox bac- - - teriën kunnen worden belemmerd door de concurrentie voor NO3 en NO2 met kabel- en Beg- giatoa-achtige bacteriën voor zomerhypoxia. Resultaten suggereren dat sulfide verwijdering door zwavel-oxiderende bacteriën onvoldoende is om de activiteit van denitrificerende en anammox bacteriën in de sedimenten van het Grevelingenmeer te ondersteunen. In hoofdstuk 5 is het effect van seizoensgebonden hypoxia op de activiteit en de gemeenschapsstructuur van chemolithoautotrofe bacteriën onderzocht in sedimenten van het Grevelin- genmeer voor (Maart) en tijdens (Augustus) het optreden van zomerhypoxia. Gecombineerde 16S rRNA gen amplicon sequencing en PLFA analyse onthulde een belangrijke temporale ver- schuiving in de gemeenschapsstructuur. Aërobe zwavel-oxiderende Gamma- en Epsilonproteo- bacteriën overheersten de chemolithoautotrofe gemeenschap in het voorjaar, terwijl Deltapro- teobacteriën veel meer voorkwamen tijdens de zomer. De bijdrage van chemolithoautotrofe bacteriën, bepaald m.b.v. PLFA-SIP, was drie maal hoger in de lente dan tijdens de zomer, vooral in oppervlaktesedimenten. De dominantie van cbbL (RuBisCO) en aclB (ATP-citraat lyase) genen liet een overheersing, onafhankelijk van het seizoen en plaats, van micro-organismen die de CBB cyclus gebruiken in vergelijking met de rTCA cyclus zien. De diepteverdeling in het sediment van chemolithoautotrofie was gekoppeld aan de verschillende zwavel-oxidatiemechanismen, die werden geïdentificeerd door middel van microsensorprofielen, d.w.z. kanonische zwavel-oxidatie, elektrogenische zwavel-oxidatie door kabelbacteriën en sulfide-oxidatie gekoppeld aan nitraatreductie door Beggiatoaceae. De metabolische diversiteit van de zwavel-oxiderende bacte-

192 riële gemeenschap suggereert een complexe verdeling van niches in het sediment, waarschijnlijk 0 2- veroorzaakt door de beschikbaarheid van gereduceerde zwavelverbindingen (H2S, S en S2O3 ) - en elektronacceptoren (O2 en NO3 ), gereguleerd door het optreden van seizoensgebonden hypoxia. In de oppervlakte sedimenten van het Grevelingenmeer is de op DNA-gebaseerde archaeale diversiteit en distributie vergeleken met die op basis van archaeale intacte membraanlipiden om de potentiële biologische bronnen van de archaeale IPLs te detecteren (hoofdstuk 6). De archaeale levensgemeenschap veranderde ten gevolge van de hypoxia van het bodemwater van een door Thaumarchaeota-gedomineerde in een door DPANN-gedomineerde archaeale levensgemeenschap. Tegelijkertijd nam de concentratie IPL-GDGTs met een orde van grootte af. Archaea in het superphylum DPANN worden gekenmerkt door een klein genoom en bezitten geen genen die coderen voor eiwitten die de synthese van membraanlipiden katalyseren. Op basis hiervan is de hypothese geponeerd dat zij zogenaamde core lipiden gebruiken die eerder door de Thaumarchaeota zijn gesynthetiseerd om hun membraan te vormen. Dit zou duiden op een actieve recycling van fossiele IPL-GDGTs in oppervlaktesedimenten. Samenvattend heeft het onderzoek in dit proefschrift nieuwe inzichten verschaft met betrekking tot de diversiteit, celaantallen en activiteit van chemolithoautotrofe micro-organismen. Hy- poxia en sulfideconcentratie zijn belangrijke factoren die hun aanwezigheid en activiteit beperken. Bovendien lijken de interacties met andere microbiële groepen en bioturbatie de aanwezigheid van specifieke chemolithoautotrofe microben op onverwachte sedimentdiepten te bevorderen, zoals de aanwezigheid van AOA in sedimentlagen waar zuurstof niet detecteerbaar was. In het algemeen hebben de methoden die in deze studies worden toegepast met betrekking tot de genexpressie en de overvloed aan belangrijke metabolische genen van chemolithoautotrophs onder verschillende milieu- en fysiologische omstandigheden, de rol van deze groep in de koolstof- en stikstofcyclus in kustsedimenten verder benadrukt. De directe koppeling tussen genexpressie en activiteit is echter nog steeds niet eenduidig en toekomstige studies zullen de regulering van specifieke metabolische genen onder verschillende fysiologische en milieuomstandigheden verder moeten bestuderen. Tenslotte heeft het onderzoek aangetoond dat specifieke lipide biomarkers de potentie hebben om specifieke chemolithoautotrofe microben in sedimenten van kustzeeën te detecteren (bijv. crenarchaeol voor Thaumarchaeota, ladderaan lipiden voor anammox bacte- riën). Omdat deze lipiden bewaard kunnen blijven in sedimenten hebben zij potentie om gebrui- kt te worden in de reconstructie van vroegere microbiële activiteit. De mogelijke recycling van intacte polaire lipiden door specifieke archaea is een proces dat dit gebruik mogelijk zou kunnen compliceren.

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Acknowledgements

During the past years, I have made experiences that I would have missed, if I would not have worked at the NIOZ on Texel. There are many people I’d like to thank for making it a good experience. First of all, to my supervisors, Laura, thank you so much for everything and especially for your outstanding support and patience over the past years. It has been a rocky road and I have learnt a lot from you scientifically but also about living far away of your family on a small island in the North Sea. Thank you very much for your open ears whenever I needed you for assistance or just to motivate myself again. You have been the best supervisor that I can imagine! This is not self-evident in this rushing times! Jaap, thanks a lot for your time and effort, reviewing the publications and the thesis, especially in the last phase of the process. It was a great pleasure to work with you. Stefan, thank you very much for your constructive comments and discussions especially during my first phase, I have learnt a lot from you, especially how to deal with scientific articles during our literature discussions. Thank you all for always leaving your door open! Elda, Harry, Judith and Anneke, thanks a lot for hosting and teaching me in the molecular lab. It was a great pleasure to work with you and as well to chat and sing along during long hours in the lab. You made me feel very welcome in the old and brown part of the building. Elda, thank you for offering your desk to me. It was my favorite spot! Ellen and Nicole, thanks a lot for sharing your expertise and teaching me in the lipid lab, where I was completely unexperienced before I came to the NIOZ. Jort, Monique, Denise, Anchelique and Irene, thanks for your help with extraction methods, machines and data analysis as well for cheering me up a lot! Marianne, thank you very much for your support in the lab, but especially for your help and nice chats during our cruise to and around Iceland. I will always remember that trip! Sebastiaan, thank you very much for technical and human support on the cruise and during my time at NIOZ, I’ve never met a gentler person with such a dry and clever sense of humor! Sabine, thanks a lot for the nice collaboration during the Iceland cruise. I have learnt a lot from you scientifically, but also about life! It was my pleasure to meet you and get to know you a bit closer. You are an amazing person! Don’t ever change for others! Marcel and Sandra, I would like to thank you for the nice collaboration during the Grevelingen campaign. It was funny and exciting! Additionally, a big thanks goes to the people from NIOZ Yerseke. Eric and Filip, thanks for inviting us to join the Grevelingen campaign. Diana, a special thanks to you for the excellent collaboration and your support. Dorina, Fatimah and Mathilde, thank you very much for the good collaboration and your support with data. Alexandra Vasquez Cardenas, thanks a lot for providing Figure 2 of the introduction. The crazy thing about this small island in the North Sea and the NIOZ is, that I got to know the nicest people from all over the world. Some of them stay friends forever! Jenni, Martina, Marta, Catia, Claudia, Santi and Mireia, you will be always on my mind! Alex, Tristan, Maram, Johann, Santi and Sergio, thank you very much for being the nicest neighbors and friends in the special Potvis situation, which welds together! Thank you for sharing so many things with me, good and bad times! I am looking forward to see you again! 223 A big thanks to all the people in the MMB department (and others) making work and life more enjoyable; Marc, Daniela, Yuki, Andreas, Darci, Sabine, Petra, Raquel, Elisabeth, Lisa, Eli, Sandra, Dave, John, Marcel, Sebastian, Cindy, Rob, Luke, Frederike, Rodrigo, and Kevin thanks for your company! My office mates over the past years had to stand me and my moody phases, but they did well and cheered me up a lot! Lisa, Cecile, Sandra, Mireia, Eva and Michel, thanks for the nice time! Down at NIOZ tropical, I have met some amazing people; Christine, Francesc, Francesco and Michele, it was very nice to talk about other things than science and enjoy your culinary skills. Ashes over my head, but I have spent some time in the smoking room, and as usual, smokers make friends quite quickly. Kees, Ronald, Geert-Jan, Anneke and Edward, thanks a lot for nice chats and a bit of distraction. For the “new” PhD students, Julie, Marijke, Gabriella, Saara, Laura, Caitlyn and Sophie; Success for your future and good luck with your thesis! Michael Hagemann, Danke für Deine Hilfe in den letzten Zügen! Ohne Deinen scharfen Verstand und die Bereitschaft zu helfen, hätte ich es nicht gepackt! Dieser Dank gilt allen meinen Freundinnen, die mich auf dem Weg ermutigt und unterstützt haben (wenn auch manchmal nur am Telefon); Miri, Helena, Moni, Svenja, Anni und Marén, ihr seid großartige Wegbegleiter! Miri, Du bist die einzige, die wirklich versteht, was es heißt, auf Texel zu wohnen! Schön, daß wir die Erfahrung teilen! Jetzt aber das Wichtigste, die Familie! Mama, Reimund und Papa, euch verdanke ich wer und wo ich bin! Ohne Eure langjährige Unterstützung und eure Geduld, hätte ich es nicht geschafft! Danke für Alles! Tobias, mein Bruderherz, Du bist der beste Bruder der Welt! Danke für Deine Unterstützung und Treue! Klausi, mein Herz, Danke, daß Du immer für mich da warst! Es war eine lange Reise, ich bin gespannt wo es als nächstes hingeht!

224 About the Author Yvonne Antonia Lipsewers was born on the 18th of July 1977 in Salzkotten, Germany. During her Abitur she gained interest in aquatic biology and was motivated by her biology teacher with a seminar about hydrology. After leaving secondary school, she first started studying food technology before finally, studying Biology at the University of Bielefeld from 2003 until 2007. After- wards, she was specializing in Marine Microbiology during her Master’s at the Institute of Chem- istry and Biology of the Marine Environment associated to the Carl-von-Ossietzky Universität in Oldenburg from 2008 until 2010. She completed a Master’s research project investigating the shift of the heterotrophic bacterial community composition during the aggregation of a diatom bloom in the North Sea. After graduating in 2010, Yvonne started a PhD project at NIOZ in 2011, focused on tracing chemolithoautotrophic microorganisms in coastal sediments, under the supervision of Dr. Laura Villanueva, which finally led to the composition of this thesis.

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