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Electronic Theses, Treatises and Dissertations The Graduate School
2006 Microbial Community Diversity Associated with Carbon and Nitrogen Cycling in Permeable Marine Sediments Evan M. Hunter
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COLLEGE OF ARTS AND SCIENCES
MICROBIAL COMMUNITY DIVERSITY ASSOCIATED WITH CARBON AND
NITROGEN CYCLING IN PERMEABLE MARINE SEDIMENTS
By
EVAN M. HUNTER
A Thesis submitted to the Department of Oceanography in partial fulfillment of the requirements for the degree of Master of Science
Degree Awarded: Spring Semester, 2006 The members of the Committee approve the thesis of Evan Hunter on March 20th, 2006.
______Joel Kostka Professor Directing Thesis
______Heath Mills Committee Member
______Markus Huettel Committee Member
______Lee Kerkhof Committee Member
Approved:
______William K. Dewar, Chair, Department of Oceanography
The Office of Graduate Studies has verified and approved the above named committee members.
ii TABLE OF CONTENTS
List of Tables iv List of Figures v Abstract vii
INTRODUCTION 1
1. CHARACTERIZATION OF MICROBIAL DIVERSITY IN PERMEABLE MARINE SEDIMENTS OF THE SOUTH ATLANTIC BIGHT 8
2. PROFILING OF THE OVERALL, NITRIFYING, AND DENITRIFYING MICROBIAL COMMUNITY DIVERSITY IN PERMEABLE MARINE SEDIMENTS OF THE NORTHEASTERN GULF OF MEXICO 46
CONCLUSIONS 86
REFERENCES 89
BIOGRAPHICAL SKETCH 101
iii LIST OF TABLES
1.1 Summary of dissolved gases and nutrient concentrations in column experiments. 16
1.2 Statistical analyses of SSU rRNA, nosZ, and amoA gene clone libraries using standard ecological and molecular estimates of sequence diversity. 18
1.3 Summary of SSU rRNA gene sequences from SC#1, SC#3, LC#1, LC#3 and SAB clone libraries. 22
1.4 Summary of nosZ gene sequences from SC#1, SC#3, LC#1, LC#3 and SAB clone libraries. 33
1.5 Summary of amoA gene sequences from SC#1, SC#3, LC#1, LC#3 and SAB clone libraries. 37
2.1 Summary of amoA gene sequences from 3B02, 3B1820, 3G02, 3G1820, and Total clone libraries. 55
2.2 Statistical analyses of SSU rRNA and nosZ gene clone libraries using standard ecological and molecular estimates of sequence diversity. 58
2.3 Summary of SSU rRNA gene sequences from 3B02, 3B1820, 3G02, 3G1820, and Total clone libraries. 59
2.4 Summary of nosZ gene sequences from 3B02, 3B1820, 3G02, 3G1820, and Total clone libraries. 78
iv LIST OF FIGURES
1.1 The South Atlantic Bight sampling site (W27) located at 31o29’N, 80o26’W (Google Earth, 2006). 11
1.2 Experimental design of column incubations. 12
1.3 Rarefaction curves determined for the different RFLP patterns of SSU rRNA (A), nosZ (B), and amoA (C) gene clones from total, SC#1, SC#3, LC#1, LC#3 and SAB samples. 20
1.4 Frequencies of bacterial phylogenetic lineages detected in SSU rRNA gene clone libraries derived from SC#1, SC#3, LC#1, LC#3 and SAB samples. 25
1.5 Phylum Proteobacteria neighbor-joining phylogenetic tree, incorporating a Jukes-Cantor distance correction, of SSU rRNA gene from SC#1, SC#3, LC#1, LC#3 and SAB samples. 27
1.6 Non-Proteobacteria neighbor-joining phylogenetic tree, incorporating a Jukes-Cantor distance correction, of SSU rRNA gene from SC#1, SC#3, LC#1, LC#3 and SAB samples. 30
1.7 Neighbor-joining phylogenetic tree, incorporating a Jukes- Cantor distance correction, of nosZ gene from SC#1, SC#3, LC#1, LC#3 and SAB samples. 36
1.8 Neighbor-joining phylogenetic tree, incorporating a Jukes- Cantor distance correction, of amoA gene from SC#1, SC#3, LC#1, LC#3 and SAB samples 39
2.1 The St. George Island sampling sites located at 29o 44.885 N, 84o 42.594 W (Gulf site) and 29o 45.034 N, 84o 42.719 W (Bay site) (Google Earth, 2006). 49
v 2.2 Rarefaction curves determined for the different RFLP patterns of SSU rRNA (A), nosZ (B), and amoA (C) gene clones from total, 3B02, 3B1820, 3G02, and 3G1820 samples. 57
2.3 Frequencies of bacterial phylogenetic lineages detected in SSU rRNA gene clone libraries derived from 3B02, 3B1820, 3G02, 3G1820, and Total samples. 62
2.4 Phylum Proteobacteria neighbor-joining phylogenetic tree, incorporating a Jukes-Cantor distance correction, of SSU rRNA gene from 3B02, 3B1820, 3G02, and 3G1820 samples. 65
2.5 Non-Proteobacteria neighbor-joining phylogenetic tree, incorporating a Jukes-Cantor distance correction, of SSU rRNA gene from 3B02, 3B1820, 3G02, and 3G1820 samples. 67
2.6 T-RFLP fingerprints of March Bay 0-2 cm, Bay 2-4 cm, and Gulf 0-2 cm samples. 72
2.7 Sorensen’s based index dendrograms of SSU rRNA gene (A) and nosZ gene (B). 75
2.8 Neighbor-joining phylogenetic tree, incorporating a Jukes- Cantor distance correction, of nosZ gene from 3B02, 3B1820, 3G02, and 3G1820 samples. 77
vi ABSTRACT
Though a large fraction of primary production and organic matter cycling in the oceans occurs on continental shelves dominated by sandy deposits, the microbial communities associated with permeable shelf sediments remain poorly characterized. Therefore, the primary objective of this study was to provide the first detailed characterization of microbial diversity in representative marine sands of the South Atlantic Bight (SAB) and the northeastern Gulf of Mexico (NEGOM) through analyses of SSU rRNA gene (Bacteria), nosZ (denitrifying bacteria), and amoA (ammonia- oxidizing bacteria) sequences. Communities were analyzed by DNA extraction, clone library construction, and terminal restriction fragment length polymorphism (T-RFLP) community fingerprinting. Sediment characteristics, geochemical parameters, and rate measurements were obtained in parallel with microbial community analysis. Microbiological and biogeochemical approaches were coupled, allowing the structure- function relationships of key microbial groups involved in carbon and nitrogen cycling in continental shelf sediments to be examined. In the SAB study (Ch. 1), clone libraries were constructed from both sediment core material and manipulated sediment within column experiments. Rapid organic matter degradation and coupled nitrification-denitrification were observed in column experiments at flow rates and oxygen concentrations resembling in situ conditions. Numerous SSU rRNA gene phylotypes were affiliated with the phyla Proteobacteria (classes α-, δ-, and γ-Proteobacteria), Planctomycetes, Cyanobacteria, Chloroflexi and Bacteroidetes. Detectable sequence diversity of nosZ and SSU rRNA genes increased in stratified redox-stabilized columns compared to in situ sediments, with the α- Proteobacteria comprising the most frequently detected group. Alternatively, nitrifier communities showed a relatively low and stable diversity that did not co-vary with the other gene targets. In the NEGOM study (Ch. 2), high throughput techniques were developed and applied to extensively profile overall and denitrifying microbial communities in a large
vii number of sediment samples over various sediment depth intervals, contrasting sites, and sampling periods. Cloning/sequencing and community fingerprinting (T-RFLP) approaches were applied in parallel to characterize microbial diversity and phylogenetic composition. Statistical estimators including species richness, Shannon-Weiner and 1/D indices, nucleotide diversity, gene diversity, evenness, and θ (π) indicated little difference between four clone libraries constructed from selected depth intervals (0-2 cm, 18-20 cm) at each site in March. In contrast, T-RFLP profiles and robust phylogenetic analysis showed distinct trends in diversity according to site, depth, and time period sampled. The results elucidate predominant phylotypes that are likely to catalyze carbon and nitrogen cycling in marine sands. Several microbial groups (δ-Proteobacteria, γ- Proteobacteria, Planctomycetes) were confirmed as significant contributors to the microbial communities of permeable marine sediments in agreement with previous work. However, the robust sequence database of this study expanded current knowledge to reveal a large overall community diversity including additional groups (α- Proteobacteria, Bacteriodetes/Chlorobi, and Cyanobacteria) that had not been previously recognized using cultivation-independent methods with inherently lower resolution. The α-Proteobacteria, in particular, were shown to be relatively abundant in the overall and denitrifying communities at both SAB and NEGOM sites. Although overall diversity increased in response to redox stabilization and stratification in column experiments, the major phylotypes remained the same, indicating that the columns sufficiently mimic in situ conditions. While SSU rRNA gene phylotypes detected by clonal analysis were similar at the phylum level at all sites, the NEGOM site showed much higher species richness in comparison to SAB. At NEGOM, T-RFLP showed distinct differences in community diversity according to site, depth, and time. The sequence database from this thesis will facilitate the development of improved probes and primer sets to be used in quantifying the metabolically active members of permeable sand communities. Rapid community fingerprinting methods developed here should allow for more extensive comparisons across environmental gradients in order to better understand the factors controlling microbial diversity in permeable sediments
viii INTRODUCTION
THE PERMEABLE CONTINENTAL SHELF ENVIRONMENT AND IT’S SIGNIFICANCE TO ORGANIC MATTER CYCLING
Approximately one-third of oceanic primary production occurs in shelf and coastal environments that cover less than one-tenth of the ocean area (50) Due to the shallow water column in shelf areas, up to 50% of the organic matter produced as phytoplankton biomass settles to the seafloor and the majority is degraded by sedimentary-microorganisms, suggesting a key role of the shelf sediments for the global recycling of organic matter (49). Permeable sand sediments cover approximately 70% of continental shelves worldwide (23), thus, much of this organic matter cycling occurs in such environments. Until recently, however, permeable marine sediments were thought to be veritable deserts that supported little organic matter cycling. Recent geochemical investigations of in permeable shelf sediments have shown rapid rates of organic matter degradation and nutrient regeneration that are likely to fuel primary production through benthic-pelagic coupling. Rapid pore water advection likely enhances degradation leading to low organic matter contents in marine sands. Microorganisms predominate over the mineralization of organic matter and the release of nutrients fueling benthic-pelagic coupling in the coastal ocean (48, 50). However, sedimentary microbial communities remain poorly characterized, especially in permeable shelf environments. To begin to address the processes limiting organic matter cycling in shallow water marine ecosystems, the diversity of the organisms responsible for carrying out these various processes must be identified and characterized. The microbial ecology of permeable sediments is not well understood and the limited number of studies focusing on permeable shelf sediment microorganisms have detected a mixture of both aerobic and anaerobic microbial groups, many of which fall within the Proteobacteria (42, 62, 98). In particular, members of the Cytophaga-Flavobacterium, Planctomycetes, and δ-Proteobacteria taxa have been detected in the greatest abundance
1 (62, 98); however, there have been few extensive studies characterizing microorganisms to the genus or species level and current estimates of microbial diversity in the sands are likely underestimates. The “active” microbial communities that catalyze diagenesis in marine sands remain therefore largely unknown.
THE NITROGEN CYCLE IN COASTAL MARINE ECOSYSTEMS
In the coastal marine environment, bioavailable nitrogen plays a critical role in the regulation of primary production (99). The majority of nitrogen is delivered to the coast by rivers from natural and anthropogenic sources (21). The availability of inorganic nitrogen in the coastal ecosystem, predominantly as nitrate and ammonium, is modulated by microbial activities either in the water column or in the underlying sediments. Microbially-mediated reactions control the input and output of bioavailable nitrogen. Three pathways in particular are critical to nitrogen flow: nitrogen fixation, nitrification, and denitrification. This thesis will address two of these, nitrification and denitrification, that act together to control the removal of nitrogen from ecosystems. Understanding the mechanisms or controls of nitrogen cycling processes becomes very important to predict the effects that nitrogen loading may have on the marine ecosystem and therefore will be very beneficial to local management and conservation efforts. Because the continental shelf is the most productive, economically important of oceanic environments (35), it is critical that we understand the processes that help to sustain the food web in this region.
NITRIFICATION AND NITRIFYING BACTERIA
Nitrification serves as a critical link between the mineralization of organic nitrogen and the removal of nitrogen through denitrification. Nitrification is a two-step
2 process that is catalyzed almost exclusively by chemolithotrophic bacteria, resulting in
- + - the production of NO3 . The first step of the pathway is the oxidation of NH3 to NO2 by ammonia oxidizing bacteria (AOB) and proceeds as the result of two different reactions:
+ - 1.) 2H + NH3 + 2e + O2 NH2OH + H2O - + 2.) NH2OH + H2O HONO + 4e + 4H
This step is largely considered to be the rate-limiting step of nitrification. The first reaction is catalyzed by ammonia monooxygenase (Amo), which is a membrane-bound enzyme. Amo is a multi-subunit enzyme that consists of three subunits encoded by the genes amoA, amoB, and amoC. These genes are present in multiple copies in most AOB. The amoA gene is generally considered to have an average of 2.5 copies per ammonia- oxidizing bacterial cell (82), based on cultivation-independent experiments. The second reaction (Equation #2) is catalyzed by the periplasm-associated enzyme hydroxylamine oxidoreductase (Hao). AOB have recently been phylogenetically sub-divided into two distinct groups based on SSU rRNA gene sequence data from pure cultures. To date, there are 25 cultured representatives of AOB (54). One clade branches deep within the γ- Proteobacteria class and contains Nitrosococcus oceanus (122). The second group falls within the β-Proteobacteria class and includes the two clades Nitrosomonas spp. and Nitrosospira spp. (33, 122).
- - The second step of the nitrification process is the oxidation of NO2 to NO3 by nitrite-oxidizing bacteria (NOB) and is catalyzed by the enzyme nitrite oxidoreductase. The reaction occurs as:
- - 3.) NO2 + O2 NO3
NOB are mostly related to the α-Proteobacteria class, but are found in the β- and γ- Proteobacteria classes as well (54). Within the α-Proteobacteria class, Nitrobacter, Nitrosococcus, Nitrospina, and Nitrospira are all genera containing cultivated representatives capable of nitrite oxidation (5, 121). Currently, there are 8 identified
3 species of NOB (54). Overall, the principal microbial groups responsible for complete
- nitrification, from NH3 to NO3 , in shallow coastal marine environments are believed to be the Nitrosospira spp., Nitrosomonas spp. and the Nitrobacter spp. (124).
DENITRIFICATION AND DENITRIFYING BACTERIA
A second major pathway in the marine nitrogen cycle is denitrification, which is the process by which heterotrophic bacteria use oxidized nitrogen compounds, mainly
- NO3 , as electron acceptors for energy production. The intermediate products of this - reaction are NO2 , NO and N2O, with complete denitrification resulting in N2 formation.
Complete denitrification releases molecular nitrogen (N2) into the atmosphere, resulting in nitrogen losses from the surrounding environment. Additionally, the accumulation of
NO and N2O in the atmosphere, as a result of incomplete denitrification, leads to the depletion of the ozone layer and contributes to the greenhouse effect (19, 53). Denitrification also plays an important role in all coastal marine systems that receive large inputs of nitrogen from anthropogenic sources, by removing the excess nitrogen and helping to control the rate of eutrophication (79, 83, 105, 123). It is believed that up to 80% of the nitrogen that enters the coastal marine area is removed by denitrification (106). High rates of denitrification can affect primary productivity since the amount of nitrogen available is decreased. Denitrification involves more than sixty different genes that code for proteins responsible for the various reactions within this metabolic pathway (87, 125). Of these proteins that regulate and catalyze denitrification, few have been studied in detail in natural environments. The most commonly studied genes in this pathway are nosZ, nirS, nirK, and norB. The gene nosZ is responsible for encoding the enzyme nitrous oxide reductase, which catalyzes nitrous oxide reduction, the final step in the denitrification pathway (100). nirS and nirK encode the enzyme nitrite reductase, which reduces nitrite to nitric oxide (47). Although they are structurally different (i.e. nirK contains copper,
while nirS contains cytochrome cd1) (47), nirS and nirK are functionally and
4 physiologically equivalent (30, 125). nirS has been found to be more widely distributed, while nirK has been identified in only about 30% of the denitrifiers studied to date (8). However, nirK has been found in more diverse physiological groups (20). norB encodes the enzyme nitric oxide reductase, which is responsible for reducing nitric oxide to nitrous oxide (9). The diversity of denitrifying bacteria incorporates a wide variety of phylogenetic groups, which have very different physiological traits (125). Although there is no clear pattern of distribution, more denitrifiers have been identified in the α- and β- Proteobacteria classes of the phylum Proteobacteria (125). Denitrifiers are also fairly widespread throughout the Archaea domain and have even been reported in Eukarya (125). In total, denitrification capability has been found in approximately 50 genera of prokaryotes (125). One notable observation is that denitrifiers are not found in the enterobacteria, which respire nitrate to nitrite and direct the further reduction of nitrite to ammonia (125).
CULTIVATION-INDEPENDENT CHARACTERIZATION OF NITROGEN- TRANSFORMING MICROBIAL COMMUNITIES IN MARINE SEDIMENTS
Very few studies have focused on nitrifiers and denitrifiers in permeable sand sediments. A small number of studies have suggested the potential value of determining denitrifier diversity between different sampling sites or depth variations at the same site. The targeting of specific genes of denitrification such as nosZ by terminal restriction fragment length polymorphism (T-RFLP) has proven to be very beneficial for comparing denitrifiers by creating microbial fingerprints of the communities that are present (101). By using T-RFLP, horizontal heterogeneity of denitrifiers at the centimeter, meter, and kilometer scales was demonstrated off the coast of New Jersey (101). Nitrifiers and denitrifiers have been studied more extensively in the water column and in impermeable sediments or marine muds. By amplifying nirS and nirK, a high diversity of denitrifiers was reported for muds collected between the Puget Sound and
5 Washington continental margin (7, 10). It has also been suggested that geographic location and biogeochemical conditions help to determine the diversity of denitrifiers in muddy sediments (61). Again through analysis of nirS and nirK, it was found that denitrifier communities were more similar to each other in oxygen-deficient zones as compared to oxygenated zones, and that they were more similar to each other at stations that were closer together and had similar nitrate levels (61). Cloning and restriction fragment length polymorphism analysis (RFLP) is another commonly employed technique to examine microbial community diversity and has been used extensively to study nitrifiers in impermeable sediments. By using clonal analysis of amoA fragments, it was reported that the Chesapeake Bay has a very diverse β- Proteobacteria population, with over 70% of the clones being most closely related to previously cultivated nitrifiers of the Nitrosomonas and Nitrosospira genera (24). Using the amoA gene, Francis et al. (2005) also suggested that ammonia-oxidizing Archaea (AOA) may be intricately linked to denitrification and thus play an important role in coupled nitrification-denitrification. The amoA gene has also been useful in demonstrating that β-Proteobacteria AOB dominated marine sediments collected from the Pacific Northwest (81). Use of these techniques was also helpful in showing that phylotypes from these sediments formed a distinct branch that was evolutionarily separate from the Nitrosomonas and Nitrosospira lineages (81). The only known study of nitrifiers in permeable sediments showed that diversity of the amoA gene was very low (42). Impermeable marine sediments from Loch Duich, Scotland have been studied to determine the microbial community structure of nitrifiers using a combination of DGGE fingerprinting and clonal analysis of SSU rRNA gene targets (26, 27). Studies concluded that the nitrifier communities are very diverse and suggest the existence of new phylogenetic subgroups, possibly delineating uniquely within the β-Proteobacteria. Diverse communities of nitrifiers were also found in Elkhorn Slough, California using SSU rRNA and amoA genes, with the closest cultured relative being in Nitrosomonas marina (13). Microorganisms mediate organic matter cycling in continental shelf sediments, yet little attention has been paid to the microbial communities that catalyze carbon and
6 nutrient cycles in these systems. Therefore, an understanding of microbial diversity in shelf sediments will be critical to the determination of mechanisms or controls of nutrient exchange in coastal ecosystems. The objective of this thesis project was to analyze the community structure of microorganisms in continental shelf sandy sediments. Two regions of the continental shelf in the southeastern United States were chosen as representative study sites: the South Atlantic Bight off the coast of Savannah, Georgia, and Northeastern Gulf of Mexico near St. George Island, Florida. The overall goal of this study was to gain a more thorough understanding of the overall, nitrifying, and denitrifying bacterial communities and to examine the effects of environmental gradients on their community structure. By providing a robust phylogenetic database, this study sought to facilitate the development of genetic probes as well as to direct further cultivation efforts.
7 CHAPTER 1
CHARACTERIZATION OF MICROBIAL DIVERSITY IN PERMEABLE MARINE SEDIMENTS OF THE SOUTH ATLANTIC BIGHT
INTRODUCTION
Sandy sediments cover large areas of the shallow ocean and recent technological developments in marine geochemistry have revealed that these sediments rapidly recycle organic matter and have the potential to play a large role in global biogeochemical cycles (40, 45, 67, 93). In fine-grained sediments that have been studied more extensively, molecular diffusion limits aerobic and sub-oxic microbial metabolism to a thin surface layer (48). In contrast, the high permeability of sands allows for rapid pore water exchange driven by advection, thereby enhancing the transport of microbial substrates in and metabolic waste products out of the sediments. Hydrodynamic forces thus fuel high rates of microbial metabolism in permeable sands while supporting a low microbial abundance and organic matter content (12, 97, 98). In addition, such drastically different physicochemical parameters are likely to support a very different community composition of microorganisms in sands as compared with their fine-grained counterparts. However, the community composition of microorganisms inhabiting permeable sediments is poorly known. A few studies have investigated community composition in permeable sands using lipid biomarkers or fluorescent in situ hybridization (FISH) approaches (12, 62, 98). To our knowledge, few or no previous studies have examined community composition using genetic cloning/sequencing in marine sands.
8 Nitrification and denitrification are critical microbially-mediated processes in the nitrogen cycle that when coupled, link the mineralization of nitrogenous compounds to the removal of nitrogen from the continental shelf (16, 57, 107). Nitrification is a two-
+ - step process resulting in the oxidation of NH3 and the production of NO3 . The first step + - of the pathway, the oxidation of NH3 to NO2 by ammonia-oxidizing bacteria (AOB), is considered to be the rate-limiting step of nitrification and is catalyzed by the ammonia monooxygenase (Amo) enzyme. The amoA gene, which codes a subunit of the ammonia monooxygenase, has been utilized as a gene target to explore AOB diversity in a variety of marine environments (4, 24, 55, 78, 84). However, previous studies of amoA in marine sediments have focused on highly impermeable marine muds which generally contain much higher ammonium concentrations, are low in oxygen content, and rich in organic matter (4, 13, 24, 78, 81). To our knowledge, nothing is known about the diversity of nitrifying bacteria in marine sands, and few studies are available for denitrifiers in comparable environments (100). Numerous genes associated with denitrification have been identified and studied in detail, as reviewed by Philippot (2002). Previous community-based studies have targeted genes associated with the second step in the denitrification process, nirS and nirK (7, 10, 61). While nirS and nirK encode proteins earlier in the denitrification pathway, nosZ, encoding nitrous oxide reductase, is associated with the final step, thus representing the step directly related to the loss of biologically available nitrogen from the environment. Studies have frequently targeted nosZ with molecular techniques to characterize the denitrifying fraction of the microbial community, however, the database for marine sediments remains relatively small and past studies have often focused on methodological development (80, 90, 100-102). The overall goal of our study was to provide a detailed characterization of microbial diversity in an understudied marine sedimentary environment, permeable shelf sands, that plays a substantial role in global biogeochemical cycles. Our work was conducted in combination with a geochemical study of N cycling in permeable sediments, using packed sediment column experiments (92). Here we present results from the investigation of diversity in these column experiments and unmanipulated sediment cores collected from the same site. We hypothesized that the stabilization and
9 stratification of redox conditions in the columns would act to increase detectable community diversity and that we would observe a change in community composition across redox boundaries within the columns as in Vetriani et al. (2003). Our results have revealed predominant phylotypes that are likely to catalyze carbon and nitrogen cycling in marine sands. Although overall diversity increased in response to redox stabilization and stratification in column experiments, the major phylotypes remained the same in all of our libraries. Our results provide an initial sequence database for the development of improved probes and primer sets to be used in quantifying the metabolically active members of microbial communities in permeable shelf sediments.
MATERIALS AND METHODS
Site and Sample Description. Permeable sandy sediments were sampled from the South Atlantic Bight off the coast of Savannah, GA. The South Atlantic Bight (SAB) shelf seafloor is a high-energy, non-accumulating environment consisting of medium and coarse sands (94). Sediment and water column parameters at the time of sampling were characterized as follows: porosity = 0.5; median sediment grain size = 500 µm; permeability = 4.7 x 10-11 m2; porewater exchange = 0-4 cm; nearbottom current speed = 30 cm sec-1; surface water temperature = 27.5oC; salinity = 36.1 ppt; and percent surface PAR at the seafloor = 2-10%. The average water depth of the SAB sampling area was 27.9 m. A previous study determined that there were sufficient nutrients available for photosynthesis, including phosphorus, silicate, and ammonia (67). Sediment cores and grab samples were collected from the surface (0 to 5 cm depth interval) at the W27 site of the SAB shelf (31o29’N, 80o26’W) in June 2004 (Fig. 1.1). A detailed description of the sediment column experiments will be presented in Rao (92). In brief, sediment was homogenized and packed into short (8 cm) and long (32 cm) columns with seawater pumped through the columns from the bottom upward at a constant rate with pore water residence times of 2-3 and 10-12 hours, respectively (Fig. 1.2). Columns were constructed on the same day of sampling and equilibrated for 6 days prior to
10 FIG. 1.1 The South Atlantic Bight sampling site (W27) located at 31o29’N, 80o26’W. Water depth was 27.9 m with median sediment grain size = 500 µm.
11 LC#3
SC#3
SC#1 LC#1
Seawater
FIG. 1.2 Experimental design of column incubations. Columns were 8 and 32 cm, respectively, with a diameter of 7.6 cm.
12 geochemical analysis. Total incubation time was two weeks prior to sacrificing sediments for nucleic acid extraction. After sampling for chemical constituents, 20 µM 15 - of labeled NO3 was spiked into the column inflow to track the pathways of microbial nitrogen transformation. DNA was extracted from sediment collected adjacent to the inflow and outflow of the short column (SC#1 and SC#3) and the long column (LC#1 and LC#3; Fig. 1.2), as well as from the top 5 cm of duplicate pooled in situ core samples (SAB) from the same site.
DNA Extraction and Analysis of SSU rRNA, nosZ, and amoA Gene Targets. Microbial community DNA was extracted directly from the sediment using a method modified from the RNA/DNA extraction protocol described by Hurt et al. (2001) and then cleaned using a Qiagen RNA/DNA Midi Kit (Qiagen, Valencia, CA). Bacterial nosZ, amoA, and SSU rRNA genes were amplified by polymerase chain reaction (PCR) in an Eppendorf Mastercycler EP Gradient PCR machine. Standard PCR reaction mix included 1 PCR buffer containing 1.5 mM MgCl2 (Takara Bio Inc., Japan), 250 µM of each deoxynucleoside triphosphate (Takara Bio Inc., Japan), 1 pmol each of forward and -1 reverse primers, 0.025 U µl rTaq enzyme (Takara Bio Inc., Japan), and dH2O. To each reaction, 10-20 ng of DNA was added as template. For SSU rRNA gene amplification, primers 8F (5’-AGA GTT TGA TCM TGG CTC AG-3’) and 1392R (5’-ACG GGC GGT GTG TRC-3’) (56) were used with the following reaction conditions: an initial denaturation step of 95oC for 5 min, 30 cycles of 95oC (1 min), 55oC (1 min), and 72oC (1 min), and a final extension step of 72oC for 10 min. For the nosZ gene amplification, the primers nos752F (5’-ACC GAY GGS ACC TAY GAY GG-3’) and nos1773R (5’-ATR TCG ATC ARC TGB TCG TT-3’) (70) were utilized. The PCR reaction conditions for the nosZ amplification were as follows: an initial denaturation step of 94oC for 5 min, 35 cycles of 94oC (1 min), 55oC (1 min), and 72oC (1 min), and a final extension step of 72oC for 10 min. For the amoA gene amplification, the primers used were amoA-1F (5’- GGG GTT TCT ACT GGT GGT-3’) and amoA-2R (5’-CCC CTC KGS AAA GCC TTC TTC-3’) (96). The PCR reaction conditions for the amoA amplification were as follows: an initial denaturation step of 94oC for 5 min, 35 cycles of 94oC (1 min), 60oC (1.5 min), and 72oC (1.5 min), and a final extension step of 72oC for 10 min. PCR products were
13 cleaned using a Qiagen PCR Purification kit (Qiagen, Valencia, CA) and cloned using a TOPO TA Cloning kit (Invitrogen, Carlsbad, CA) as per manufacturer’s instructions. The cloned inserts of approximately 50-250 transformants from each clone library were amplified using the same PCR conditions as previously described. However, for the bacterial SSU rRNA gene clones, the vector specific primers M13F (5’-GTA AAA CGA CGG CCA G-3’) and M13R (5’-CAG GAA ACA GCT ATG AC-3’) (71) were used to avoid amplification of host E. coli SSU rRNA genes. The M13 PCR conditions were as follows: an initial denaturation step of 94oC for 5 min, 30 cycles of 94oC (1 min), 55oC (1 min), and 72oC (1 min), and a final extension step of 72oC for 10 min. Following amplicons size analysis, 1 µg of the clonal PCR product was digested using HaeIII (New England Biolabs, Inc., Beverly, MA), and MspI (Promega, Madison, WI) restriction enzymes for 2.5 h at 37oC as per manufacturer’s instructions. Digested DNA fragments were separated by a 2% agarose gel containing ethidium bromide and visualized using a Bio-Rad GelDoc XR system (Bio-Rad Laboratories, Inc., Hercules, CA). DNA fragment sizes were estimated by comparison to molecular weight standards (1 kb and 50 bp DNA ladder, Promega, Madison, WI). Clones were grouped into phylotypes according to banding patterns, with representatives of each phylotype purified using a Qiagen PCR Purification kit (Qiagen, Valencia, CA) and sequenced using an Applied Biosystems 3100 genetic analyzer at the Florida State University sequencing facility.
Phylogenetic and Statistical Analyses. Clone sequences were checked for chimeras using Chimera Check from Ribosomal Database Project II (66). Sequences from this study and reference sequences, as determined by BLAST analysis, were subsequently aligned using the Fast Aligner algorithm in the ARB package (112). All alignments were then visually verified and adjusted by hand according to E. coli SSU secondary structure. Neighbor-joining trees incorporating a Jukes-Cantor distance correction were created from the alignments using the ARB software package (112). An average of 500 (i.e., amoA) to 1000 (i.e., SSU rRNA and nosZ clones) nucleotides were included in the phylogenetic analyses. Bootstrap data represented 1,000 samplings. Rarefaction analysis was performed using equations described by Heck et al. (1975). Sorensen’s index and the Shannon-Weiner index were calculated using standard equations. Species richness
14 was determined by EstimateS (14, 17, 18). Additional statistical estimators, including gene (77) and nucleotide (77, 113) diversity, and θ(π) (113), were calculated using Arlequin (103).
Nucleotide Sequence Accession Numbers. The 88 nucleotide sequences reported here were submitted to the GenBank database under accession numbers DQ289896 to DQ289983.
RESULTS
Sediment Sampling and Geochemical Determinations. The composition of the Bacteria community in the South Atlantic Bight (SAB) was determined by SSU rRNA gene, nosZ, and amoA phylogenetic analyses of DNA-derived clone libraries extracted from sediments in two flow-through columns and two sediment cores. Extracted DNA concentrations were comparable for all 4 column samples, i.e., SC#1, SC#3, LC#1, LC#3, and the homogenized core sediment, noted SAB (data not shown). Rapid microbial mineralization of organic matter in SAB sediments was indicated by oxygen consumption and the production of ∑CO2 in column experiments (Table 1.1). Total oxygen consumed in the columns increased with residence time, resulting in outflow O2 concentrations at the outflow of 54.5 µM and 8.3 µM for the short and long columns, respectively. Therefore, strong oxygen gradients were observed in all columns with the long column outflow nearly anoxic. A hydrogen sulfide odor was detected in the outflow from the long columns and a black precipitate, indicative of iron sulfide, was observed on the outflow tubing (92). Nitrate release in the short column indicated net regeneration or ammonification followed by nitrification, while no nitrate was detected in the outflow of the long column (Table 1.1). Nearly all nitrogen leaving the columns in the outflow was in the form of
28 N2, indicating that the majority of regenerated N was being denitrified. Further, little or + 29 30 no NH4 , N2O, N2, or N2 accumulated in the column outflow (Table 1.1). Coupled 15 TABLE 1.1 Summary of dissolved gases and nutrient concentrations in column experiments. a 28 a 29 a 30 a - a + a a O2 N2 N2 N2 NO3 NH4 Total CO2 SC#1 - Inflow Unamended 214.8 ± 4.12b 415.94 ± 3.02 BDLc BDL BDL 0.33 ± 0.45 2071.65 ± 23.43 Amendedd 219.55 415.16 BDL BDL 17.95 0.31 2024.17
SC#3 - Outflow Unamended 101.14 ± 1.029 423.99 ± 0.478 BDL BDL 2.78 0.40 ± 0.19 2206.77 ± 19.26 Amended 54.53 422.95 0.13 0.15 16.57 0.82 2282.00
LC#1 - Inflow
16 Unamended 214.8 ± 4.12 415.94 ± 3.021 BDL BDL BDL 0.33 ± 0.45 2071.65 ± 23.43 Amended 219.55 415.16 BDL BDL 17.95 0.31 2024.17
LC#3 - Outflow Unamended 7.31 ± 1.26 413.72 ± 0.208 BDL BDL BDL 0.12 ± 0.08 2637.49 ± 2.69 Amended 8.26 418.28 3.47 2.88 BDL 1.05 2464.63 a Concentrations reported as µM. b Standard deviation. c BDL, below detection limit. d Single samples were analyzed for all amended columns. nitrification-denitrification was confirmed as a critical component of the marine N cycle in marine sands, representing a primary pathway for N removal from these ecosystems (92). Geochemical constituents in SAB sediments at the W27 sampling site closely resembled those observed in our column experiments. Pore water nitrate and ammonium concentrations in the surface sediments (0 to 5 cm depth) were in the low micromolar range over a seasonal cycle (67). Pore water oxygen concentrations ranged from 200 µM to near anoxia, decreasing with sediment depth (67).
RFLP and Statistical Analyses of SSU rRNA, nosZ, and amoA Libraries. Fifteen clone libraries constructed from SC#1, SC#3, LC#1, LC#3, and the SAB core sediments resulted in a total of 309 Bacteria SSU rRNA gene clones, 291 nosZ clones, and 202 amoA clones. Clones were analyzed and grouped into phylotypes according to observed RFLP patterns. The total percent coverage of all 5 SSU rRNA gene clone libraries was nearly 88%, with individual library coverages ranging from 58 to 89%, with the exception of SC#1 (41%; Table 1.2) (31, 74). Total percent coverage for the nosZ and amoA clone libraries were 93 and 99%, respectively (data not shown), with individual clone library percent coverages ranging between 66 and 89% for nosZ and 98 and 100% for amoA (Table 1.2). Rarefaction curves for the combined SSU rRNA gene and nosZ libraries, and the combined and individual amoA gene libraries suggested a sufficient number of clones were sampled to represent the diversity of these particular libraries (Fig. 1.3). The rarefaction curves for the SSU rRNA and nosZ genes in SC#1, SC#3, LC#1, LC#3, and SAB core did not indicate saturation, however, numerically dominant RFLP groups were observed. Estimation of species richness indicated that all of the column-derived SSU rRNA and nosZ gene libraries were more diverse than libraries from the SAB cores (Table 1.2). Shannon-Weiner and 1/D indices indicated a significant difference between the 4 column samples and the SAB core for both the SSU rRNA gene (P ≤ 0.05) and the nosZ gene (P < 0.01). Similar nucleotide and gene diversity, evenness, and θ (π) were calculated for all SSU rRNA and nosZ gene clone libraries (Table 1.2). All statistical estimators, including rarefaction and species richness, indicated low diversity in the 5 amoA gene clone libraries (Fig. 1.3 and Table 1.2). Shannon-Weiner
17 TABLE 1.2 Statistical analyses of SSU rRNA, nosZ, and amoA gene clone libraries using standard ecological and molecular estimates of sequence diversity.
Num. of clones Shannon-Weiner Nucleotide PCR target Sample % Coverage Species richness Evenness 1/D Gene diversity θ (π) (Phylotypes) index diversity
SSU rRNA SC#1 61(48) 41.0 120 (87, 195)a 0.84 4.01 158 0.98 ± 0.01b 0.22 ± 0.11b 279.4 ± 135.4b gene SC#3 62(40) 58.1 88 (67, 138) 0.86 3.84 86.1 0.98 ± 0.01 0.20 ± 0.10 248.7 ± 119.9 LC#1 48(29) 60.4 65 (40, 147) 0.76 3.18 32.2 0.95 ± 0.02 0.18 ± 0.09 217.8 ± 105.6 LC#3 70(37) 71.4 57 (44, 96) 0.85 3.42 39.0 0.97 ± 0.01 0.18 ± 0.09 229.3 ± 110.2 SAB 75(23) 89.3 32 (29, 45) 0.92 3.18 29.5 0.96 ± 0.01 0.19 ± 0.09 230.9 ± 110.9
nosZ SC#1 73(39) 69.2 67 (48, 120) 0.83 3.49 44.5 0.96 ± 0.01 0.23 ± 0.11 213.3 ± 102.6 SC#3 52(29) 65.9 46 (35, 82) 0.85 3.27 40.2 0.97 ± 0.01 0.22 ± 0.11 207.4 ± 100.6
18 LC#1 65(31) 78.5 43 (35, 73) 0.86 3.25 32.5 0.95 ± 0.01 0.24 ± 0.12 216.3 ± 104.4 LC#3 44(24) 71.2 52 (32, 127) 0.74 2.95 22.0 0.93 ± 0.02 0.22 ± 0.11 199.3 ± 97.1 SAB 57(21) 89.5 23 (21, 33) 0.90 2.82 17.9 0.93 ± 0.02 0.22 ± 0.11 208.8 ± 100.9
amoA SC#1 48(3) 100.0 3 (3, 3) 0.60 0.66 1.71 0.41 ± 0.07 0.007 ± 0.004 2.94 ± 1.74 SC#3 32(2) 100.0 2 (2, 2) 0.81 0.56 1.63 0.39 ± 0.08 0.006 ± 0.004 2.32 ± 1.45 LC#1 48(3) 97.9 3 (3, 3) 0.53 0.58 1.53 0.32 ± 0.07 0.005 ± 0.003 1.90 ± 1.22 LC#3 49(2) 97.9 2 (2, 2) 1.00 0.69 2.03 0.51 ± 0.02 0.008 ± 0.004 3.05 ± 1.79 SAB 25(2) 100.0 2 (2, 2) 0.85 0.59 1.72 0.42 ± 0.08 0.006 ± 0.004 2.52 ± 1.56 a The numbers in parentheses are 95% confidence intervals. b Mean ± standard deviation. FIG. 1.3 Rarefaction curves determined for the different RFLP patterns of SSU rRNA, nosZ, and amoA gene clones from total, SC#1, SC#3, LC#1, LC#3 and SAB samples. The number of different RFLP patterns was determined after digestion with restriction enzymes HaeIII and MspI. Rarefaction analysis was performed using equations reported Heck et al.
19 A. 100 90 80 70 60 Total SSU rRNA gene 50 SC#1 SSU rRNA gene OTUs 40 SC#3 SSU rRNA gene 30 LC#1 SSU rRNA gene 20 LC#3 SSU rRNA gene 10 SAB SSU rRNA gene 0 0 50 100 150 200 250 300 350 Number of Clones
B. 100 90 80 70 60 50 TotalTotal nosZnosZ
OTUs 40 SC1SC#1 nosZ nosZ SC3 nosZ 30 SC#3 nosZ LC1LC#1 nosZ nosZ 20 LC3LC#3 nosZ nosZ 10 SABSAB nosZnosZ 0 0 50 100 150 200 250 300 350 Number of Clones
C. 20 18 TotalTotal amoA amoA 16 SC1SC#1 amoA amoA 14 SC3SC#3 amoA amoA 12 LC1LC#1 amoA amoA 10 LC3LC#3 amoA amoA
OTUs 8 SABSAB amoA amoA 6 4 2 0 0 50 100 150 200 250 Number of Clones
20 and 1/D indices did not indicate a significant difference in diversity between the 5 amoA- derived clone libraries (P > 0.10).
Phylogenetic Analysis Based on the SSU rRNA Gene. Sequence analysis of 48 of the 88 SSU rRNA gene phylotypes (phylotypes comprised of more than a single clone) indicated 8 distinct phyla with a majority of the sequences most closely related to uncultured lineages from marine environments. Proteobacteria was the most frequently detected phylum, comprising 42% of the total SSU rRNA gene clones, with the α−Proteobacteria-related clones alone comprising 23% (Table 1.3 and Fig. 1.4). The Planctomycetes (11%), Actinobacteria (7%), and Cyanobacteria (8%) comprised approximately one-third of all SSU rRNA gene clones (Fig. 1.4). The other four lineages detected (Acidobacteria, Bacteroidetes/Chlorobi, Chloroflexi, and Firmicutes) comprised between 1 and 6% of all SSU rRNA gene clones (Fig. 1.4). Interestingly, clone sequences most closely related to the class β−Proteobacteria were not detected. Two separate distance-based neighbor-joining trees were constructed with the 19 Proteobacteria and 27 non-Proteobacteria-related sequences from this study and reference sequences from the GenBank database (Fig. 1.5 and Fig. 1.6). The Proteobacteria-related clones grouped into three classes, i.e., α-, δ-, and γ- Proteobacteria. Of the 19 phylotypes, 4 were most related to δ-Proteobacteria and with the exception of phylotype SC1-40, grouped within two families, Desulfoarculaceae and Desulfobulbaceae, of the order Desulfobacterales (Fig. 1.5). A similar taxonomic level was not able to be determined for phylotype SC1-40, however it was the most frequently detected δ-Proteobacteria-related phylotype and the only δ-Proteobacteria-related phylotype to be detected in the SAB core sediment (Table 1.3). Only 31% of the δ- Proteobacteria clones were found in SC#1 and LC#1 compared to 63% found in SC#3 and LC#3, with no single δ-Proteobacteria-related phylotype found in all 5 clone libraries (Table 1.3). Phylotype SC3-7, the second most frequently detected phylotype, 95% similar to clone SK1 from an intertidal mudflat in the Wadden Sea (76), was only detected in the two outflow samples, SC#3 and LC#3 (Fig. 1.5 and Table 1.3). A total of 7 of the 19 Proteobacteria-related phylotypes grouped within the class γ-Proteobacteria (Fig. 1.5). Compared to the δ-Proteobacteria phylotypes, the γ-
21 TABLE 1.3 Summary of SSU rRNA gene sequences from SC#1, SC#3, LC#1, LC#3 and SAB clone libraries. No. of Related Clones Phylogenetic Group Clone Nearest Relative % Similarity Total SC#1 SC#3 LC#1 LC#3 SAB α-Proteobacteria LC1-31 Sargasso Sea Isolate 5 99 17 2 1 4 5 5 LC1-30 SCB clone 131735 96 15 0 2 7 1 5 LC1-35 MV clone Kazan-2B-34/BC19-2B-34 99 12 1 2 2 5 2 LC1-28 FS clone DUNssu161 90 9 2 1 1 5 0 LC1-34 MS clone Nubeena268 98 9 2 1 1 2 3 LC1-25 Isolate MBIC3923 93 5 1 0 2 1 1 SC3-43 HA clone K2-19 95 3 0 1 1 0 1 SC3-5 HV clone IndB1-49 97 2 0 2 0 0 0 γ−Proteobacteria SC3-2 HV clone NDII1.1 94 16 3 2 3 3 5 SC3-6 Photobacterium sp. HAR72 96 9 2 5 0 2 0 22 SC3-20 HV clone NDII1.2 92 8 1 1 2 2 2 SC1-14 HV clone AT-s80 94 3 2 0 0 1 0 SC1-11 MV clone Kazan-2B-06/BC19-2B-06 91 3 2 1 0 0 0 LC3-5 MB clone EF100-91A10 94 2 0 0 0 2 0 SC1-44 DS clone A134 93 2 1 0 0 1 0 δ−Proteobacteria SC1-40 MV clone HMMVPog-12 91 7 1 1 0 4 1 SC3-7 MS clone SK1 95 4 0 3 0 1 0 LC1-19 MV clone Kazan-2B-31/BC19-2B-31 94 3 1 0 1 1 0 LC1-13 MV clone HMMVPog-8 91 2 0 0 1 1 0 Planctomycetes LC1-32 AC clone wb1 D18 96 8 1 0 2 0 5 LC1-1 AS clone 0319-7F4 89 4 1 1 1 0 1 SC3-24 GoM clone GoM GB425 02B-7 95 4 1 1 1 0 1 LC3-21 MV clone Amsterdam-2B-62 90 4 0 0 1 1 2 SC1-33 WW clone CY0ARA030F07 95 3 1 1 0 1 0 TABLE 1.3 -- Continued
LC3-44 WW clone CY0ARA030F07 91 2 0 0 0 2 0 SC1-36 MV clone Amsterdam-1B-32 97 2 1 1 0 0 0 SC3-3 MV clone Napoli-3B-28 97 2 0 2 0 0 0 SC3-8 OC clone FS142-21B-02 90 2 0 2 0 0 0 LC1-9 SM clone SIMO-2186 91 2 0 1 1 0 0 Actinobacteria SC1-10 PS clone EB 1077 90 9 2 2 1 2 2 SC3-41 AC clone wb1 P06 92 8 0 1 0 5 2 LC1-7 MV clone Kazan-1B-11/BC19-1B-11 96 5 0 0 1 1 3 Cyanobacteria SC3-15 Chloroplast Bacillaria paxillifer Strain p73 97 14 2 3 1 3 5 SC3-19 Cyanothece sp. PCC 8801 97 7 1 2 2 0 2 LC3-54 Chloroplast Haslea salstonica 97 3 0 0 0 2 1 SC1-42 Cyanobacterium sp. MBIC10216 94 2 1 1 0 0 0 Acidobacteria LC3-65 AC clone wb1 A08 94 6 0 0 1 1 4 SC1-23 SI clone SIMO-1943 96 3 2 1 0 0 0 LC3-26 HV clone AT-s36 92 2 0 0 0 2 0
23 SC1-4 HV clone AT-s65 90 2 1 1 0 0 0 Bacteroidetes/Chlorobi SC3-56 Endosymbiont Acanthamoeba sp. ATCC 30868 91 6 1 1 0 1 3 SC1-48 Cytophaga sp. BD1-15 92 3 2 0 0 1 0 SC1-26 Flexibacter aggregans Strain IFO 15974 92 3 1 2 0 0 0 LC3-28 CS clone MERTZ 21CM 53 98 7 0 0 1 1 5 Chloroflexi LC1-24 ME clone KM87 93 11 0 2 3 2 4 Firmicutes SC3-18 DS clone PS-B19 96 2 0 2 0 0 0 FIG. 1.4. Frequencies of bacterial phylogenetic lineages detected in SSU rRNA gene clone libraries derived from SC#1, SC#3, LC#1, LC#3 and SAB samples. Calculations were made based on the total number of clones associated with phylotypes from which a representative clone had been sequenced.
24 SC#1 SC#3 Firmicutes Acidobacteria Chloroflexi 4% Acidobacteria 4% 4% Alphaproteobacteria 7% Alphaproteobacteria 18% Bacteroidetes 20% 10% Bacteroidetes 6% Actinobacteria 5% Deltaproteobacteria Deltaproteobacteria 10% 9% Actinobacteria 11% Cyanobacteria 10% Cyanobacteria Planctomycetes 11% Gammaproteobacteria 16% 12% Gammaproteobacteria Planctomycetes 26% 17%
Chloroflexi LC#1 Chloroflexi Chlorobi Acidobacteria 3% Chlorobi LC#3 Acidobacteria 7% 2% 5% 2% 2% Bacteroidetes Alphaproteobacteria Actinobacteria 3% 31% 5% Alphaproteobacteria 45% Actinobacteria 13% Cyanobacteria 7%
Cyanobacteria Planctomycetes 8% 15% Deltaproteobacteria 11% 25 Deltaproteobacteria Planctomycetes Gammaproteobacteria 5% Gammaproteobacteria 6% 18% 12%
Chloroflexi Chlorobi 6% 8% Acidobacteria Alphaproteobacteria 6% 25%
Bacteroidetes 5% Deltaproteobacteria 2% Actinobacteria 11% Gammaproteobacteria 11%
Cyanobacteria Planctomycetes Total 12% 14% FIG. 1.5. Phylum Proteobacteria neighbor-joining phylogenetic tree of SSU rRNA gene as determined by distance Jukes-Cantor analysis from SC#1, SC#3, LC#1, LC#3 and SAB samples. Sequences were aligned by hand against close relatives from the Ribosomal Database Project with the ARB software package, as well as E. coli rRNA secondary structure. One thousand bootstrap analyses were conducted and percentages greater than 50% are indicated at the nodes. Methanococcus maripaludis was used as the outgroup. Scale bar = 0.10 change per nucleotide position.
26 Methanococcus maripaludis [U38941] Bacteriovorax stolpii Strain uki-2 [M34125] Nitrospina gracilis Strain Nb-211 [L35504] 98 LC1--13 66 LC1--19 97 MV clone HMMVPog-8 [AJ704690] MV clone Kazan-2B-31/BC19-2B-31 [AY592155] 99 SC1-40 99 Clone SM48 [AY771958] 91 MV clone HMMVPog-12 [AJ704672] Delta. Desulfobulbus rhabdoformis Strain M16 [U12253] 92 Desulfocapsa thiozymogenes Strain Bra2 [X95181] 90 Desulfocapsa sp. clone SB1 17 [AY177794] MS clone SK1 [AY771952] SC3--7 83 SC1--11 72 Shewanella algae Strain Bry [X81621] 75 SC3--6 51 Photobacterium leiognathi Strain RM1 [AY292947] Photobacterium sp. HAR72 [AB038032] 63 SC1--44 53 DS clone A134 [AY373400] 93 MV clone Kazan-2B-06/BC19-2B-06 [AY592131] 64 Clone JTB255 [AB015254] Pseudomonas sp. NB1-h [AB013829] HV clone OBII5 [AF170421] Pseudomonas stanieri Strain ATCC 27130T [AB021367] Kangiella koreensis Strain SW-125 [AY520560] Methylomicrobium pelagicum [L35540] Gamma. 54 SC3-2 HV clone NDII1.1 [AF170424] HV clone NDII1.2 [AF181991] SC3--20 56 HV clone AT-s80 [AY225635] SC1--14 LC3--5 Proteobacteria MB clone EF100-91A10 [AY627370] 65 LC1--28 LC1--34 93 MS clone Nubeena268 [AY627370] 98 Rhodovulum sulfidophilum Strain TW13 [D16422] SC3--43 LC1--30 SCB clone 131735 [AY922228] Oceanicola batsensis Strain HTCC 2597 [AY424898] HA clone K2-19 [AY345433] 57 Jannaschia rubra Strain 4SM3T [AJ748747] 64 72 Thalassobacter stenotrophicus Strain CECT 5294T [AJ631302] 91 Stappia stellulata Strain IAM12621 [D88525] 80 LC1--31
Sargasso Sea Isolate 5 [AY082665] Alpha. LC1--25 61 Ahrensia kielensis Strain IAM12618 [D88524] 82 Mesorhizobium sp. DG943 [AY258089] 87 Clone PI GH2.1.D5 [AY162047] Isolate MBIC3923 [AB016848] 99 HV clone IndB1-49 [AB100000] SC3--5 57 FS clone DUNssu161 [AY913368] Methylosinus sporium [M95665] 95 Hyphomicrobium denitrificans Strain DSM 1869 [Y14308] 73 LC1--35 MV clone Kazan-2B-34/BC19-2B-34 [AY592158]
0.10
27 Proteobacteria-related phylotypes were more diverse, representing multiple families and unclassified lineages. Although four phylotypes, represented by clones SC3-2, SC3-20, SC1-14, and LC3-5, grouped into a clade with no sequences from cultured isolates (Fig. 1.5), phylotypes SC3-2 and SC1-14 were most closely related to clone sequences associated with sulfur-oxidizing symbionts (Unpublished) (63), and SC3-20 was most closely related to a nitrogen-fixing symbiont (120) (Table 1.3). Phylotypes SC3-2 and SC3-20 were two of the three most frequently detected phylotypes and were the only γ- Proteobacteria-related phylotypes to be detected in the SAB core (Table 1.3). The remaining 8 Proteobacteria-related phylotypes were most closely related to the class α-Proteobacteria and represented 23% of the total SSU rRNA gene clones. Similar to the δ- and γ-Proteobacteria-related clones, the phylotypes that were most frequently detected overall, were detected in the SAB cores. A total of 5 of the 8 phylotypes grouped within the order Rhodobacterales and the family Rhodobacteraceae, including the two most numerically dominant phylotypes, represented by clones LC1-31 and LC1-30 (Table 1.3). Phylotype LC1-35, 99% similar to clone Kazan-2B-34/BC19- 2B-34, clustered with Hyphomicrobium denitrificans Strain DSM 1869 within the order Rhizobiales and family Hyphomicrobiaceae (Table 1.3 and Fig. 1.5). Hyphomicrobium denitrificans Strain DSM 1869 was previously characterized as a facultative methylotroph used in the denitrification of sewage (91). Phylotypes LC1-34 and LC1-28 clustered with Nubeena268, an uncultured marine sediment bacterium (Unpublished), in a distinct clade from the other orders of α-Proteobacteria on the tree, as supported by strong bootstrap values (Table 1.3 and Fig. 1.5). A second distance-based neighbor-joining tree was constructed with 27 non- Proteobacteria-related phylotypes grouping into 7 phyla (Fig. 1.6). Similar to the Proteobacteria-related phylotypes, a majority of sequences collected were closely related to non-cultured environmental clones from numerous marine habitats (Table 1.3). Of the 27 non-Proteobacteria-related phylotypes, 10 grouped within the phylum Planctomycetes. With the exception of phylotypes SC3-3 and SC1-36, all of the Planctomycetes-related phylotypes were <97% similar to any previously identified SSU rRNA gene sequence (Table 1.3). Although the phylum Planctomycetes has a single class, order, and family currently identified (28), three phylotypes, represented by LC1-
28 FIG. 1.6. Non-Proteobacteria neighbor-joining phylogenetic tree of SSU rRNA gene as determined by distance Jukes-Cantor analysis from SC#1, SC#3, LC#1, LC#3 and SAB samples. Sequences were aligned by hand against close relatives from the Ribosomal Database Project with the ARB software package, as well as E. coli rRNA secondary structure. One thousand bootstrap analyses were conducted and percentages greater than 50% are indicated at the nodes. Methanococcus maripaludid was used as the outgroup. Scale bar = 0.10 change per nucleotide position.
29 Methanococcus maripaludis [U38941] AC clone wb1 D18 [AF317785] LC1--32 97 AS clone 0319-7F4 [AF234144] 96 LC1--1 LC1--9 68 SI clone SIMO-2186 [AY711552] 97 Planctomyces brasiliensis ATCC 49424 [X85247] 83 SC1--33 50 SC3--8 91 SC3--3 MV clone Napoli-3B-28 [AY592702] 73 OC clone FS142-21B-02 [AY704401] 96 Pirellula clone 5H12 [AF029076] 87 GoM clone GoM GB425 02B-7 [AY542549] SC3--24 Pirellula sp. Schlesner 384 [X81944] Planctomycetes LC3--21 LC3--44 WW clone CY0ARA030F07 [BX294820] Pirellula staleyi Strain ATCC 35122 [AF399914] MV clone Amsterdam-2B-62 [AY592419] MV clone Amsterdam-1B-32 [AY592336] SC1--36 Prochlorococcus clone PENDANT-4 [AF142917] 53 Prochlorococcus marinus Strain SSW5 [X63140] 88 Synechococcus sp. PCC 7117 [AB015060] 74 Cyanobacterium sp. MBIC10216 [AB058249] 63 SC1--42 93 Cyanothece sp. PCC8801 [AF296873] SC3--19 60 Chlorella kessleri Strain SAG 211-11g [X65099] LC3--54
94 Chloroplast Haslea salstonica [AF514854] Cyanobacteria 93 Chloroplast Bacillaria paxillifer Strain p73 [AJ536452] SC3--15
56 Chlorobaculum thiosulfatiphilum Strain 6230 [Y08102] Chloroplast 75 CS clone MERTZ 21CM 53 [AF424371] LC3--28 89 SC1-48 53 Cytophaga sp. clone BD1-15 [AB015524] Rhodothermus marinus Strain DSM 4252T [AF217494] Flexibacter sp. S22211 [D84584] 71 Cytophaga lytica [M62796] Flavobacterium johnsoniae [M59053] 94 Prevotella buccae Strain ATCC 33690 [L16478] Bacteroides sp. BV-1 [X89217] Bacteroides fragilis Strain 2393 [X83948] 80 SC1--26 53 Flexibacter aggregans Strain IFO 15974 [AB078038]
99 SC3--56 Bacteroidetes/Chlorobi 99 Candidatus Amoebophilus asiaticus [AF215634] Endosymbiont Acanthamoeba sp. ATCC 30868 [AY549546] 99 LC3--26 HV clone AT-s36 [AY225645] 57 HV clone AT-s65 [AY225644] 74 SC1--4 Acidobacterium capsulatum [D26171] Holophaga foetida Strain TMBS4-T (DSM 6591-T) [X77215] 99 AC clone wb1 A08 [AF317741] LC3--65
SC1-23 Acidobacteria SI clone SIMO-1943 [AY711309] Chloroflexus aurantiacus Strain J-10-fl [D38365] 80 Dehalococcoides ethenogenes Strain DSM 195 [AF004928] LC1--24
ME clone KM87 [AY216458] Chloro. 96 Streptococcus macedonicus Strain ACA-DC 206, LAB617 [Z94012] Clostridium tetani NCTC 279 [X74770] Fusibacter paucivorans Strain SEBR 4211 [AF050099]
DS clone PS-B19 [AY280415] Firm. SC3--18 62 Rubrobacter radiotolerans Strain DSM 46359-T [X87134] 58 Rhodococcus erythreus Strain DSM 43066 [X79289] 71 SC1--10 LC1--7 MV clone Kazan-1B-11/BC19-1B-11 [AY592088] SC3--41 63 Acidimicrobium ferrooxidans Strain ICP (DSM 10331) [U75647] Candidatus Microthrix parvicella clone 6 [89560] AC clone wb1 P06 [AF317769] PS clone EB 1077 [AY395396] Actinobacteria 0.10 30 32, LC1-1, and LC1-9 (42% of Planctomycetes-related sequences), clustered apart from the cultured Planctomycetes and was supported by good bootstrap values (Fig. 1.6). Phylotype LC1-32, the most frequently detected Planctomycetes-related phylotype, was detected in both inflow sediment samples and the SAB core sediment. The remaining 7 phylotypes clustered with members of the genera Planctomycetes and Pirellula. Of note, phylotype LC1-9 was most closely related (91%) to clone SIMO-2186 from a Sapelo Island, Georgia saltmarsh (Unpublished; Table 1.3). The 4 Cyanobacteria-related phylotypes (8% of the total clones) grouped into two clades (Fig. 1.6). Phylotypes SC1-42 and SC3-19 clustered within the order Chroococcales and were most closely related to the nitrogen fixing Cyanobacterium sp. MBIC10216 (94%; Unpublished) and Cyanothece sp. PCC 8801 (97%) (115) (Table 1.3). The remaining two phylotypes, represented by clones LC3-54 and SC3-15, were most similar (both 97%) to chloroplast DNA sequences from the diatoms Haslea salstonica and Bacillaria paxillifer, respectively (Unpublished; Table 1.3). Four additional non-Proteobacteria-related phylotypes grouped within the two Gram-positive phyla, Actinobacteria and Firmicutes. Although all 3 Actinobacteria- related phylotypes (7% of the total SSU rRNA clones) were detected in SC#3 and the SAB core clone libraries (Table 1.3), only phylotype SC1-10, the most frequently detected Actinobacteria-related phylotypes, was detected in all 5 clone libraries (Table 1.3). The only Firmicutes-related phylotype, SC3-18, was 96% similar to clone PS-B19 from a deep-sea vent chimney (85) and had limited similarity to Fusibacter paucivorans (90%; Table 1.3 and Fig. 1.6). The remaining 9 non-Proteobacteria-related phylotypes represented the phyla Acidobacteria, and Chloroflexi, and the superphyla Bacteroidetes/Chlorobi and less than one third of the total SSU rRNA clones. The four Acidobacteria-related phylotypes grouped within the class Acidobacteria, order Acidobacteriales, and family Acidobacteriaceae. Phylotype LC3-65, the most frequently detected Acidobacteria- related phylotype, was also the only Acidobacteria-related phylotype detected in the SAB sediment-derived clone library. Of note, phylotype SC1-23 had sequence similarity to clone SIMO-1943 from a Sapelo Island, Georgia saltmarsh (Unpublished).The only Chloroflexi-related phylotype, LC1-24 (4% of the total SSU rRNA clones), was 93%
31 similar to clone KM87 from estuarine wetland sediment (Unpublished; Table 1.3) and branched into a clade with the nitrogen fixing Dehalococcoides ethenogenes Strain 195 (69) (108). A total of 4 phylotypes grouped into the Bacteroidetes/Chlorobi superphyla. The most numerically dominant Bacteroidetes-related phylotype, SC3-56, was 92% similar to an uncharacterized endosymbiont (Unpublished; Table 1.3). The only Chlorobi-related phylotype, LC3-28, was 98% similar to clone MERTZ 21CM 53 (6) and branches into a clade with a green sulfur bacteria, Chlorobaculum thiosulfatiphilum str. 6230 (Table 1.3 and Fig. 1.6).
Phylogenetic Analysis Based on the nosZ Gene. Representatives of 37 of the 65 total phylotypes, i.e., the phylotypes comprised of more than a single clone, were sequenced and analyzed (238 total nosZ-derived clones). Percent similarity for all phylotypes compared to previously identified sequences ranged from 79 to 88%, however, intralibrary sequence similarity ranged from 48 to 99%. Interestingly, six of the top 10 most frequently detected phylotypes were identified in each of the 5 clone libraries (Table 1.4). Only 6 phylotypes were detected in a single clone library, and none of these phylotypes contained more than 3 clones. A distance-based neighbor-joining tree was constructed with the 37 nosZ sequences collected in this study (Table 1.4 and Fig. 1.7). Although nosZ has been detected in β- and γ-Proteobacteria, all sequences from this study were most closely related to nosZ genes from the class α-Proteobacteria (Fig. 1.7). However, due to low sequence similarity to nosZ genes from previously cultured lineages and the potential for the nosZ gene to be horizontallly transfered, distinct phylogenetic classification of the nosZ clones from this study cannot be determined (73, 104). Several deep branching clades were comprised solely of clones from this study (Fig. 1.7). The largest clade incorporated 21 of the 37 phylotypes (57% of the total nosZ clones) and was most similar to a nosZ clone, ProR, identified from San Clemente Island, California (100) (Table 1.4 and Fig. 1.7).
Phylogenetic Analysis Based on the amoA Gene. Analysis of the 202 amoA clones obtained from the 4 column samples and the in situ core indicated low phylogenetic
32 TABLE 1.4 Summary of nosZ gene sequences from SC#1, SC#3, LC#1, LC#3 and SAB clone libraries. % No. of Related Clones Phylogenetic Group Clone Nearest Relative Similarity Total SC#1 SC#3 LC#1 LC#3 SAB α−Proteobacteria SC1N-30 CSS clone ProR 83 24 4 2 6 4 8 SC1N-38 CSS clone ProV 83 17 4 5 3 3 2 SC3N-14 CSS bacterium 696M 81 15 1 1 2 4 7 SC1N-58 CSS bacterium 696H 82 14 2 0 4 2 6 SC1N-13 CSS clone ProG 85 12 6 0 5 0 1 SC1N-2 CSS clone ProR 82 12 6 0 5 0 1 SC1N-53 CSS clone ProR 84 12 3 1 5 1 2 SC3N-13 CSS clone ProP 80 10 4 3 0 2 1 SC3N-15 CSS clone ProR 88 9 3 1 1 1 3 SC1N-8 CSS clone ProR 83 9 1 1 2 2 3
33 SC1N-27 CSS clone ProR 83 9 2 0 0 7 0 SC3N-1 CSS clone ProR 86 8 1 3 0 1 3 SC3N-45 CSS clone ProR 81 8 1 2 3 0 2 LC1N-62 CSS clone ProG 84 6 0 0 1 1 4 SC1N-15 CSS clone ProP 79 6 2 3 0 1 0 SC1N-1 CSS clone ProR 83 6 3 1 2 0 0 SC1N-45 CSS clone ProR 86 6 2 1 1 1 1 LC3N-32 CSS clone ProR 80 5 0 0 0 3 2 SC3N-21 CSS clone ProR 80 5 2 3 0 0 0 LC1N-47 CSS clone ProR 82 5 0 0 3 0 2 SC1N-35 CSS clone ProR 82 4 2 1 0 1 0 SC3N-27 MS clone S321195A 84 3 2 1 0 0 0 SC1N-68 CSS bacterium 696W 81 3 1 0 2 0 0 SC3N-19 CSS clone ProO 82 3 1 2 0 0 0 TABLE 1.4 -- Continued
SC3N-10 CSS clone ProR 85 3 1 1 1 0 0 SC3N-8 CSS clone ProR 83 3 1 2 0 0 0 SC1N-18 CSS clone ProR 83 3 3 0 0 0 0 SC1N-6 CSS bacterium 696C 84 2 1 1 0 0 0 SC3N-41 CSS bacterium 696C 84 2 0 2 0 0 0 SC3N-24 CSS bacterium 696I 82 2 1 1 0 0 0 LC1N-21 CSS bacterium 696M 81 2 0 0 2 0 0 SC1N-32 CSS clone ProO 82 2 1 0 1 0 0 LC1N-45 CSS clone ProO 82 2 0 0 2 0 0 LC3N-27 CSS clone ProR 85 2 0 0 0 2 0 SC3N-12 CSS clone ProR 84 2 0 2 0 0 0 SC1N-11 CSS clone ProR 83 1 1 0 0 0 0 SC3N-11 CSS clone ProR 81 1 0 1 0 0 0 34 FIG. 1.7. Neighbor-joining phylogenetic tree of NosZ gene as determined by distance Jukes-Cantor analysis from SC#1, SC#3, LC#1, LC#3 and SAB samples. Sequences were aligned by hand against close relatives from the Ribosomal Database Project with the ARB software package, as well as E. coli rRNA secondary structure. One thousand bootstrap analyses were conducted and percentages greater than 50% are indicated at the nodes. Ralstonia eutropha Strain H16 was used as the outgroup. Scale bar = 0.10 change per nucleotide position.
35 Ralstonia eutropha Strain H16 [AY305378] Pseudomonas stutzeri [M22628] CSS clone ProL [AF119953]
Pseudomonas denitrificans [AF016059] Gamma. 99 Bradyrhizobium japonicum Strain USDA110 [AJ002531] Sinorhizobium meliloti 1021 [AE007253] 78 CSS clone 696G [AF119948] LC1N-21 SC3N-14 99 SC1N-58 CSS bacterium 696M [AF119944] CSS bacterium 696H [AF119947] CSS bacterium 696T [AF119940] SC1N-38 SC1N-15 SC3N-13 99 CSS bacterium 696I [AF119918] 80 SC3N-24 CSS clone ProP [AF119935] 56 CSS bacterium 696A [AF119954] 90 CSS bacterium 696K [AF119945] CSS clone ProV [AF119938] 71 SC3N-21 52 SC3N-45 74 CSS clone ProR [AF119937] SC1N-45 SC3N-1 SC1N-53 80 SC3N-8 SC3N-15 SC1N-30 SC3N-12 63 SC3N-10 Alpha. Proteobacteria 54 LC3N-27 SC1N-27 LC1N-47 SC1N-35 57 LC3N-32 SC3N-11 SC1N-2 SC1N-18 SC1N-1 SC1N-11 SC1N-8 SC1N-6 SC3N-41 CSS bacterium 696C [AF119951] 62 CSS bacterium 696J [AF119946] 99 CSS bacterium 696W [AF119925] SC1N-68 56 MS clone S321195A [AF016055] SC3N-27 LC1N-62 SC1N-13 76 CSS clone ProG [AF119924] Silicibacter pomeroyi DSS-3 plasmid [CP000032] CSS clone ProC [AF119921] 77 CSS clone ProO [AF119933] LC1N-45 SC1N-32 61 SC3N-19
0.10
36 TABLE 1.5 Summary of amoA gene sequences from SC#1, SC#3, LC#1, LC#3 and SAB clone libraries. % No. of Related Clones Phylogenetic Group Clone Nearest Relative Similarity Total SC#1 SC#3 LC#1 LC#3 SAB β−Proteobacteria LC1AG-1 MB Clone A10-99-S-15 97 141 35 24 38 26 18 SC3AG-1 MB Clone A10-99-S-15 97 59 12 8 9 23 7 SC1AG-11 MB Clone A10-99-S-15 96 1 1 0 0 0 0 37 FIG. 1.8. Neighbor-joining phylogenetic tree of amoA gene as determined by distance Jukes-Cantor analysis from SC#1, SC#3, LC#1, LC#3 and SAB samples. Sequences were aligned by hand against close relatives from the Ribosomal Database Project with the ARB software package, as well as E. coli rRNA secondary structure. One thousand bootstrap analyses were conducted and percentages greater than 50% are indicated at the nodes. Nitrosococcus oceanii sp. C-113 was used as the outgroup. Scale bar = 0.10 change per nucleotide position.
38 Nitrosococcus oceanii sp. C-113 [AF153344] Nitrosomonas cryotolerans [AF272402] 80 Nitrosomonas oligotropha [AF272406] WW clone BF2-21 [AF272502] 56 Nitrosomonas communis [AF272399] 98 Nitrosomonas nitrosa [AF272404] 99 Nitrosomonas europaea [AB070981] Nitrosomonas Nitrosomonas eutropha [U51630] 67 WW clone amoa17 [AF272507] 99 Nitrosospira briensis [U76553] 69 Agriculture DGGE band 6 [AY177943] 63 CB clone CB1-12 [AY352909]
89 Nitrosolobus multiformis [AF042171] Nitrosospira Soil clone NAB-0-38 [AF056067] 62 Lake Plussee clone [Z97850] HV clone 524EnPA17 [AY785994] 95 LC1AG-1 99 SC3AG-1 58 SC1AG-11 Betaproteobacteria 85 ES clone R8C-3 [AY702570] 98 MB clone A10-99-S-15 [AY736940] MB clone A10-99-S-25 [AY736946] MB clone A10-98-M-12 [AY736883] MB clone A10-99-S-8 [AY736935] 64 CB clone CB3-32 [AY352992] 70 91 Kysing Fjord clone K 2 [AF489631] Environmental Clones 66 ES clone P22-61 [AY702584] HV clone 460GPA14 [AY785983] 73 DGGE clone K 1 [AF489630] 78 CB clone CT2-32 [AY353054] ES clone P22-73 [AY702585]
0.10
39 diversity (Table 1.5). Representatives from all 3 phylotypes were sequenced and analyzed. Phylotypes LC1AG-1 and SC3AG-1 were detected in all 5 clone libraries and represented 99% of the total amoA clone sequences. Phylotype SC1AG-11 was only found in SC#1 and represented 1 clone (Table 1.5). A distance-based neighbor-joining tree was constructed with the three amoA sequences from this study (Fig. 1.8). All three sequenced clones clustered within the β- Proteobacteria amoA group and branched into a large clade of environmental clones (Fig. 1.8), distinct from previously identified Nitrosomonas and Nitrosospira amoA clades. All three sequenced clones were 96 to 97% similar to clone A10-99-S-15 from Monterey Bay (84) (Table 1.5). Interestingly, all three phylotypes branch into their own clade with intralibrary sequence similarity between 96 and 98% (Fig. 1.8).
DISCUSSION
Past studies have hypothesized that severe hydrodynamic conditions, lower specific surface area, lower organic matter content, and higher predation pressure contribute to lower bacterial abundance and fundamentally different microbial community composition in marine sands (12, 62, 97). Permeable sands undergo rapid pore water exchange resulting in physically unstable environments that tend to diminish the geochemical gradients, which are thought to stratify microbial communities in fine- grained muddy sediments. We examined microbial activity and diversity in continental shelf sands from the South Atlantic Bight off the coast of Georgia. In corroboration with results from group-specific FISH probes (12, 62, 98) applied to similar sedimentary environments, we observed abundant phylotypes affiliated with the phylum Proteobacteria (classes α-, δ- and γ-Proteobacteria). In addition, phylotypes related to Planctomycetes, Actinobacteria, Acidobacteria, Bacteroidetes/Chlorobi, and Firmicutes were detected, all of which are commonly found in less permeable sediments in the deep sea and estuaries (2, 6, 59, 63, 68, 88, 114). As is often the case in environmental
40 sequence analysis, the majority of phylotypes we detected were not closely related to any cultivated representatives and the sequences of several microbial groups were detected which have not been observed in past studies of permeable sands. We conclude that the microbial diversity of permeable sands has just begun to be revealed and our sequence database should provide a good starting point for the development of improved genetic probes designed to quantify the metabolically active microbial groups in these poorly studied but biogeochemically significant ecosystems. In addition, the data presented herein suggest previous reports of sandy sediment microbial diversity may be underestimated due to numerous lineages being below detection limits. Phylogenetic diversity was shown to be relatively constant and consistent with geochemical determinations in column experiments designed to mimic in situ carbon and nitrogen flow. Sands in column experiments were exposed to a stable, redox-stratified environment for a two-week incubation period. Geochemical change was evidenced by observed oxygen consumption and production of N2, TCO2, reduced Mn and Fe and sulfide. In contrast, organic matter degradation and coupled nitrification-denitrification, as indicated by net N2 and total CO2 production, did not vary substantially between the column experiments (Table 1.1) (92). Similarly, microbial community diversity remained relatively constant between column experiments and across geochemical gradients within the columns. Abundant phylotypes of all gene targets remained relatively the same across large gradients in oxygen content and nitrogen species, with the exception of an increase in δ-Proteobacteria sequences affiliated with S-transforming microorganisms from the inflow to the outflow of the long columns (Table 1.3). From these results, it appears that column experiments provide a fairly accurate representation of the in situ microbial diversity of permeable shelf sediments. The observed stable diversity may be a result of microbial community adaptations to large fluctuations in physicochemical parameters in permeable sands. Alternatively, due to the low organic matter content and potentially slow growth rates, cloning/sequencing targeted to DNA may not be sensitive enough to detect community change even after a two-week incubation period. Further analysis will be required using redesigned probes from our sequence database in order to confirm the ecological significance of our observations.
41 A surprising observation was that denitrification occurred under largely oxic conditions in the bulk phase of the short columns (92). Such “aerobic denitrification” has been demonstrated in pure cultures of classic denitrifiers and nitrifiers (124).
Denitrification of nitrite or nitrate to N2 can occur at near atmospheric concentrations of
O2 (95) and some strains show enhanced rates of aerobic denitrification at low oxygen concentrations (32). Column experiment results show that this process could be significant in permeable shelf sands. Therefore, as suggested by previous geochemical studies (11), denitrification, typically an anoxic process, may occur aerobically or within anaerobic micro-niches of otherwise aerobic sediment within the columns (92). Such micro-niches may have provided an environment suitable for denitrifiers that were below detection limits in the in situ SAB sediment, to be identified in clone libraries from the sediment columns. Microbial diversity was lower in the SAB core-derived clone libraries compared to any of the libraries constructed from column inflow or outflow sediment DNA extracts, as determined by species richness, Shannon-Weiner, and reciprocal of Simpson’s indices values (Table 1.2). Although less diverse, clones from the SAB core- derived library grouped in 10 of the 11 total phyla detected, including the most frequently detected phylotype in each of those phyla. Thus, the lack of SAB core library diversity was in the detection of multiple phylotypes within each phylum, not a lack of phyla, as was supported by similar gene and nucleotide diversity indices for all libraries. The lower diversity of the SAB core clone libraries may be explained by the geophysical properties of the shelf sediments. The highly permeable sediments of the South Atlantic Bight experience rapid, tidally-driven bottom currents and migrating sediment wave-forms (44). Tidal currents across migrating waveforms create variable advective flow rates into the sediments over short time periods (38, 39, 109). Such frequently changing environmental conditions have been shown to restrict bacterial population growth (97), keeping some lineages below detection limits using standard cloning and sequencing techniques. Therefore, we hypothesized that, within the microbial community, the detectable diversity would expand in response to the creation of a stable redox interface in the columns. Interestingly, only one δ-Proteobacteria- related phylotype was detected in the SAB core clone library. However, in stable,
42 stratified columns, numerous δ-Proteobacteria-related phylotypes were detected and were related to both aerobic sulfur oxidizers and anaerobic sulfate reducers. Therefore, a more complete description of the metabolic potential of the SAB permeable sediments was determined by examining the microbial diversity across redox stabilized geochemical gradients within the columns. Using quantitative techniques with lower detection limits, future analysis of in situ core sediments from specific redox zones will support the additional diversity described within the column libraries. While the column experiments provided a means to detect a wider range of phylogenetic groups, some groups may have been over represented or remained below detection limits. Cyanobacteria-related phylotypes were detected in the column SSU rRNA gene clone libraries, yet these sediments were incubated without light for two weeks. Although predominantly phototrophic, some species of Cyanobacteria are capable of heterotrophic growth, depending on geochemical conditions (43, 46, 60). Based on DNA-derived clone libraries alone, it is not possible to determine whether these dark-adapted, heterotrophic Cyanobacteria are endemic to SAB sediments or whether the DNA sequences obtained were from dead or dormant Cyanobacteria residual from sampling the SAB shelf sediments. Although nitrification was demonstrated in geochemical determinations, nitrifying β-Proteobacteria-related phylotypes were absent in the SSU rRNA gene libraries from either the SAB core or column sediments. The presence of nitrifiers within the SAB sediments was indicated initially by successful amplification of amoA and then confirmed by amplification and cloning of SSU rRNA gene amplicons using primer sets specific for known nitrifiers (data not shown). Similar to other studies of marine environments (2, 6, 37, 68, 72, 76, 114), β-Proteobacteria-related phylotypes, a group that plays a critical role in ecosystem function, were in low abundance. In our study, the lack of β- Proteobacteria-related phylotypes is believed to be the result of these taxa being below our detection limits rather than being absent, and thus are underrepresented in our SSU rRNA-derived clone libraries. This conclusion is supported by FISH studies which show a decreased abundance and detectability of major microbial taxa in marine sands in comparison to muds (12, 62, 97).
43 Using amoA sequence analysis, we determined that the ammonia-oxidizing bacteria (AOB) in permeable shelf sediments were most similar to sequences retrieved during past studies of marine environments, primarily the water column of Monterey Bay and a variety of estuarine sediments (4, 84). Although our AOB sequences were not closely related to any cultured AOB, all phylotypes were affiliated with Nitrosospira spp., providing further evidence that this AOB group is ubiquitous in marine sediments (4, 24, 78). A number of physicochemical factors have been implicated in the control of AOB species distribution in sediments including porosity, salinity, ammonium and oxygen concentrations (34). Salinity, in particular, was shown to correlate with changes in amoA sequence diversity in estuarine sediments (4, 24). In corroboration with Bernhard et al. (2005), we observed an AOB community that exhibited relatively low diversity at a high salinity site. In addition, the most abundant amoA phylotypes in our study were most closely affiliated with environmental clones from sites where the salinity did not deviate from full strength seawater (4, 84). Interestingly, sediment manipulation and redox stabilization in the column experiments did not increase the AOB community diversity and our results suggest that other environmental parameters beyond salinity warrant further study. All previous studies of AOB diversity focused on marine muds that contain high porosity, low oxygen tension, and much higher ammonium concentrations relative to the sands we studied. The majority of phylotypes from these muddy sediments formed a separate sister clade in comparison to the sequences we retrieved. The detection of nearly identical phylotypes from physicochemically different marine environments emphasizes the need for further cultivation of AOB that are well represented in clone libraries but underrepresented in culture collections. Such, physiological characterization of new marine isolates would greatly aid in predictions of niche differentiation and resource exploitation. In contrast to the lack of diversity observed in the amoA-derived clone libraries, the diversity estimations for denitrifiers in the nosZ-derived clone libraries approached the levels of diversity established for the SSU rRNA gene-derived clone libraries. Although SSU rRNA gene libraries contained clones related to γ-Proteobacteria, those clones were <93% similar to known denitrifiers. Therefore it is not surprising that no nosZ-derived clones were related to γ-Proteobacteria and all were related to previously
44 identified sequences from the α-Proteobacteria. Based on this analysis, both SSU rRNA and nosZ gene sequence data indicated that α-Proteobacteria are an important microbial group in permeable shelf sediments. Although intralibrary nosZ sequence similarity was as low as 52% between some clone sequences, all contained characteristic histidine residues (125). Therefore, these sequences may be assumed accurate, although the limited relatedness to previously identified α-Proteobacteria sequences will require characterization of nosZ genes from cultured isolates to determine the appropriate host taxa. Additionally, some sequences within our libraries were 99% similar, however we interpreted these sequences as separate phylotypes based on RFLP-phylotyping. Regardless, this study represents a significant contribution of nosZ sequences to a relatively small database from marine sediments. Similar high levels of nosZ diversity were previously reported by Scala and Kerkhof (1999) when characterizing denitrifiers in the coastal sediments of New Jersey and San Clemente Island. However, as indicated by the statistical estimators in this study, increased nosZ diversity was detected within the column sediments. Therefore, by stabilizing the geochemical gradients within the sediment columns, allowing community stratification, increased diversity in not only the total microbial community, but also the fraction associated with denitrification was identified.
45 CHAPTER 2
PROFILING OF THE OVERALL, NITRIFYING, AND DENITRIFYING MICROBIAL COMMUNITY DIVERSITY IN PERMEABLE MARINE SEDIMENTS OF THE NORTHEASTERN GULF OF MEXICO
INTRODUCTION
Though continental shelves cover a small area, they contribute roughly a third of global oceanic production and nearly 70 % of the shelf area is covered with permeable sands (49, 119). Nearly half of the biomass produced from primary production is thought to settle to the seafloor on the shallow shelf, where the organic matter is remineralized, thereby releasing inorganic nutrients to fuel further production (49). Despite their significance, sandy shelf environments were previously considered as biological deserts that were unimportant to the global carbon cycle. However, recent geochemical studies have shown that shelf sands contain highly active microbial communities that support the rapid cycling of organic matter in response to phytoplankton sedimentation events and benthic photosynthesis (39, 44, 93). Hydrodynamic forces are likely to play an important role in defining the microbial niches of permeable sands due to their higher permeability. Sands contain a lower specific surface area, lower organic matter content, and potentially higher predation rates in comparison to muddy sediments (98). Enhanced pore water exchange in sands may stimulate microbial metabolism through the delivery of substrates and the removal of metabolites. Microbial diversity may be impacted as redox zonation is diminished due to
46 advective transport driven by waves and tides (12). While a larger body of information is available on microbial communities present in impermeable, muddy sediments (48), few studies have investigated the microbiology of permeable sands. Thus far, members of the Proteobacteria, Planctomycetes, and Cytophaga-Flavobacterium phyla were detected in the greatest abundance in shelf sands (12, 62, 98). Most microbial groups have not been specifically identified below broad taxonomic levels; therefore, current representations of microbial diversity in marine sands are likely underestimated. Nitrification and denitrification are critical microbially-mediated processes in the nitrogen cycle that when coupled, link the mineralization of nitrogenous compounds to the removal of nitrogen (16, 57, 107). Coupled nitrification-denitrification is thought to comprise the predominant sink of N in the world ocean. Nitrification is a two-step
+ - process whereby primarily chemolithotrophic prokaryotes oxidize NH4 to NO3 . Denitrification is the reduction of nitrate to gaseous endproducts that is catalyzed by a diverse group of facultatively anaerobic heterotrophic prokaryotes. Very little is known about the diversity or quantity of the nitrifying bacteria in permeable sediments, and only a few studies are available for denitrifiers from shelf sands (100, 101). New nucleic acid-based methods allow for quantification of the metabolic capability as well as the diversity of N cycling microorganisms. These methods target functional genes that encode for enzymes involved in specific geochemical transformations, thus allowing for the direct quantification and identification of the “active” microorganisms involved in specific processes (89, 124). An example of such a functional gene is amoA, which encodes for the first subunit of ammonia
+ - monooxygenase, a protein involved in the first step of NH4 oxidation to NO2 . The amoA gene has been used to quantify and characterize AOB in numerous terrestrial and aquatic systems (4, 24, 55, 78, 84). The results of these studies have increased our knowledge of the diversity, habitats, and activities of this important group of microorganisms (89). Nevertheless, the amoA gene has not been studied extensively in marine sediments (81), although some 16S rRNA gene-based surveys of AOB in marine sediments have been performed (89, 111). To our knowledge, nothing is known about the diversity or quantity of amoA genes in permeable marine sediments.
47 Due to their broad phylogenetic diversity, approaches using SSU rRNA genes will not identify many denitrifiers, and therefore three functional gene targets (nirS, nirK, and nosZ) have been used to monitor the true denitrifying bacteria in marine environments (7, 10, 61, 100, 101). While nirS and nirK encode enzymes earlier in the denitrification pathway, nosZ encodes the enzyme nitrous oxide reductase, which catalyzes the final step in denitrification, thus representing the loss of biologically available nitrogen from the environment. Scala et al. (100-102) have begun to investigate the diversity of denitrifiers in continental shelf sediments. However, the database for marine sediments remains small and past studies have often focused on surficial sediments with little supporting biogeochemical data, as well as methodological development. The objective of this study was to extensively profile the overall, nitrifying, and denitrifying microbial communities in permeable shelf sediments across relevant environmental gradients. High throughput techniques were developed and applied and coupled with clonal analysis to characterize the microbial diversity and phylogenetic composition of this understudied environment. Two contrasting sampling sites were examined in the northeastern Gulf of Mexico that varied according to hydrodynamic conditions, sediment characteristics and organic matter content. Whereas no significant differences were observed between sediment samples using clonal analysis, T-RFLP profiles showed distinct trends in diversity according to site, depth, and time period sampled. These results are consistent with other studies suggesting clonal libraries can miss a significant fraction of T-RFLP peaks detected in a sample (86, 118). Rapid fingerprinting methods along with an improved sequence database should greatly facilitate the quantification of microbial groups that are active in carbon and nutrient cycles in permeable shelf environments.
MATERIALS AND METHODS
Site and sample description. Permeable sandy sediments were studied in the northeastern Gulf of Mexico off St. George Island, FL. The continental shelf near St.
48 ⊗ ⊗
FIG. 2.1. The St. George Island sampling sites located at 29o 44.885 N, 84o 42.594 W (Gulf site) and 29o 45.034 N, 84o 42.719 W (Bay site) (Google Earth, 2006). Water depth was 1.5 m and the bottom currents (<0.6 m s-1) are dominated by tidal and wave-induced currents.
49 George Island is considered to be pristine and unaffected by heavy anthropogenic impact. Sediments consisted of well-sorted quartz with a relatively low organic matter content (< 1%) and a porosity of 31 to 37 %. Water depths at the study site ranged from 1 to 3 m and bottom currents (<0.6 m s-1) were dominated by tidal and wave-induced currents. Sediment samples were collected in March and May, 2005 from the Gulf (29o 44.885 N, 84o 42.594 W) and Apalachicola Bay (29o 45.034 N, 84o 42.719 W) sides of St. George Island (Fig. 2.1). Sediment samples were collected at a water depth of 1.5 m from both the Bay and Gulf sides. The sediment surface on the Gulf side had sand ripples of 2-3 cm in height and were spaced 7-10 cm apart, while the Bay side contained sand ripples of 0.5-1 cm in height, with a spacing of 3-5 cm apart. In March, the water temperature was approximately 13.5 oC on the Gulf side and 14.5 oC on the Bay side and water temperatures increased to 26.1oC and 24.0 oC, respectively, in May. In March, salinity was 30 ppt on the Gulf side and 26 ppt on the Bay side. In May, salinity was 33 ppt and 26 ppt, respectively. Triplicate cores (20-25 cm long, Inner Diameter= 3.6 cm) were collected at each site by divers that gently pushed polycarbonate core liners into the sediment. All cores were immediately frozen on dry ice and cores or core sections were later stored at –80 oC. Each core was sectioned frozen into seven different depth intervals: 0-2 cm, 2-4 cm, 4-6 cm, 6-8 cm, 8-10 cm, 14-16 cm, and 18-20 cm.
DNA extraction and analysis of SSU rRNA, nosZ, and amoA gene targets. Following the sediment extractions, DNA from each of the triplicate cores was PCR amplified using primer sets specific for the SSU rRNA gene, nosZ, and amoA. Initial analysis of sediment associated microbial communities indicated little difference between each of the replicate cores. Therefore, individual extracts from each depth from the triplicate cores were combined prior to PCR amplification and used for further analysis, resulting in an array of 28 sediment samples that were subjected to microbial community profiling. Microbial community DNA was extracted directly from the sediment using a modified phenol-chloroform procedure from Kerkhof and Ward (1993). A sediment sample (~ 0.5 g) was re-suspended in Solution 1 [50 mM glucose, 10 mM EDTA (pH 8.0), 25 mM Tris-Cl (pH 8.0)] and freeze-thawed with liquid nitrogen and a 55oC heat block 8-10 times. A total volume of 150-200 µl of Solution 1, 100 ul of lysozyme
50 solution, and 50 µl of 500mM EDTA (pH 8.0) was added. The sample was incubated for 5-15 min., with periodic mixing. 50 µl of 10% SDS and 800 µl of phenol-chloroform (>pH 7.0) were added, and then vortexed for 1-2 min. The sample was then centrifuged at 16,000 x g for 3 min. The supernatant was removed and transferred to a new centrifuge tube containing 800 µl of phenol-chloroform. The tube was vortexed for 1 min. and then centrifuged for 3 min. The supernatant was removed and added to a new tube containing 20 µg glycogen. The DNA was precipitated by adding 50 µl of 3.0 M sodium acetate and 1 ml of 100% ethanol. The sample was then centrifuged at 16,000 x g for 15 min at 4oC. The supernatant was removed and the pellet will be resuspended in DEPC-treated water. The DNA solution was then cleaned using the Wizard DNA Clean- Up System (Promega, Madison, WI). Bacterial nosZ, amoA, and SSU rRNA genes were amplified by polymerase chain reaction (PCR) in an Eppendorf Mastercycler EP Gradient PCR machine. Standard PCR
reaction mix included 1 PCR buffer containing 1.5 mM MgCl2 (Takara Bio Inc., Japan), 250 µM of each deoxynucleoside triphosphate (Takara Bio Inc., Japan), 1 pmol each of forward and reverse primers, 0.025 U µl-1 rTaq enzyme (Takara Bio Inc., Japan),
and dH2O. To each reaction, 10-20 ng of DNA was added as template. For SSU rRNA gene amplification, primers 27F (5’-AGR GTT TGA TCM TGG CTC AG-3’) (29) and 1392R (5’-ACG GGC GGT GTG TRC-3’) (56) were used with the following reaction conditions: an initial denaturation step of 95oC for 5 min, 30 cycles of 95oC (1 min), 55oC (1 min), and 72oC (1 min), and a final extension step of 72oC for 10 min. For the nosZ gene amplification, the primers nos752F (5’-ACC GAY GGS ACC TAY GAY GG-3’) and nos1773R (5’-ATR TCG ATC ARC TGB TCG TT-3’) (70) were utilized. The PCR reaction conditions for the nosZ amplification were as follows: an initial denaturation step of 95oC for 5 min, 35 cycles of 95oC (0.5 min), 55oC (0.5 min), and 72oC (1.5 min), and a final extension step of 72oC for 10 min. For the amoA gene amplification, the primers used were amoA-1F (5’-GGG GTT TCT ACT GGT GGT-3’) and amoA-2R (5’-CCC CTC KGS AAA GCC TTC TTC-3’) (96). The PCR reaction conditions for the amoA amplification were as follows: an initial denaturation step of 94oC for 5 min, 35 cycles of 94oC (1 min), 60oC (1.5 min), and 72oC (1.5 min), and a final extension step of 72oC for 10 min.
51 PCR products were cleaned using a Qiagen PCR Purification kit (Qiagen, Valencia, CA) and cloned using a TOPO TA Cloning kit (Invitrogen, Carlsbad, CA) as per manufacturer’s instructions. The cloned inserts of approximately 50-250 transformants from each clone library were amplified using the same PCR conditions as previously described. However, for the bacterial SSU rRNA gene clones, the vector specific primers M13F (5’-GTA AAA CGA CGG CCA G-3’) and M13R (5’-CAG GAA ACA GCT ATG AC-3’) (71) were used to avoid amplification of host E. coli SSU rRNA genes. The M13 PCR conditions were as follows: an initial denaturation step of 94oC for 5 min, 30 cycles of 94oC (1 min), 55oC (1 min), and 72oC (1 min), and a final extension step of 72oC for 10 min. Following amplicons size analysis, 1 µg of the clonal PCR product was digested using HaeIII (New England Biolabs, Inc., Beverly, MA), and MspI (Promega, Madison, WI) restriction enzymes for 2.5 h at 37oC as per manufacturer’s instructions. Digested DNA fragments were separated by a 2% agarose gel containing ethidium bromide and visualized using a Bio-Rad GelDoc XR system (Bio-Rad Laboratories, Inc., Hercules, CA). DNA fragment sizes were estimated by comparison to molecular weight standards (1 kb and 50 bp DNA ladder, Promega, Madison, WI). Clones were grouped into phylotypes according to banding patterns, with representatives of each phylotype purified using a Qiagen PCR Purification kit (Qiagen, Valencia, CA) and sequenced using an Applied Biosystems 3100 genetic analyzer at the Florida State University sequencing facility.
Terminal Restriction Fragment Length Polymorphism (T-RFLP) Analysis. For T- RFLP, the SSU rRNA and nosZ genes were amplified from the community DNA as described above, except that the forward primers were labeled with 6-carboxyfluorescien (6-FAM; Applied Biosystems, Foster City, CA). Fluorescently labeled PCR product was run on a 1% agarose gel and the product was quantified by image analysis as described previously (51). Fifteen ng of PCR product was digested with MnlI endonuclease (New England Biolabs, Beverly, MA) for both SSU rRNA and nosZ amplicons. All digests were in 20 µl volumes for 6 h at 37oC. DNA was precipitated by adding 2.3 µl of 0.75 M sodium acetate and 5 µg of glycogen with 37 µl of 95% ethanol. The precipitated DNA was washed with 70% ethanol and dried for 30 min with a vacuum.
52 The dried DNA pellets were re- suspended in 19.7 µl de-ionized formamide and 0.3 µl ROX 500 size standard (Applied Biosystems, Foster City, CA) for 15 minutes before analysis. The sample was then denatured at 94oC for 2 min and submerged in ice before being run on the genetic analyzer. T-RFLP fingerprinting was carried out on an ABI 310 genetic analyzer (Applied Biosystems, Foster City, CA) using Genescan software. Peak detection was set at 25 arbitrary fluorescent units. For comparative analysis, all peaks within a fingerprint were normalized to the total area for that sample. Peaks < 1% of the total area were excluded from further analysis. Comparative analysis of the T-RFLP was performed based on the Sorenson’s similarity index (65, 75) and the unweighted-pair-group mean-average (UPGMA) analysis calculated using the COMbinatorial Polythetic Agglomerative Hierarchical clustering package (COMPAH96; http://www.es.umb.edu/edgwebp.htm). The genetic analyzer is essentially a capillary electrophoresis sequencer that uses laser-induced fluorescence to detect the digested fragments. The various fragments are displayed as a series of peaks, allowing different samples to be directly compared. These peaks were then analyzed using Sorenson’s index based on the presence or absence of peaks or by a Brays Curtis Analysis that takes into account peak area as well as presence/absence. By comparing peaks from different samples, phenograms of similarity indices were constructed and the diversity of organisms in the environment was examined. Fluorescent amplification of amoA for T-RFLP analysis was unable to be completed due to the amount of gene template being below our detection limit. We were able to detect low concentrations at a depth of 0-12 cm in the Bay March samples, 0-8 cm in the Bay May samples, and from 0-20 cm in both Gulf samples.
Phylogenetic and statistical analyses. Sequence analysis of SGI SSU rRNA gene phylotypes (phylotypes having more than 1 clone representative and no matching SAB phylotype) and 21 SAB phylotypes (SGI sequences that matched SAB phylotypes) were included in the phylogenetic database in this study. Clone sequences were checked for chimeras using Chimera Check from Ribosomal Database Project II (66). Sequences from this study and reference sequences, as determined by BLAST analysis, were subsequently aligned using the Fast Aligner algorithm in the ARB package (112). All
53 alignments were then visually verified and adjusted by hand according to E. coli SSU secondary structure. Neighbor-joining trees incorporating a Jukes-Cantor distance correction were created from the alignments using the ARB software package (112). An average of 500 (i.e., amoA) to 1000 (i.e., SSU rRNA and nosZ clones) nucleotides were included in the phylogenetic analyses. Bootstrap data represented 1,000 samplings. Rarefaction analysis was performed using equations described by Heck et al. (1975). Sorensen’s index and the Shannon-Weiner index were calculated using standard equations. Species richness was determined by EstimateS (14, 17, 18). Additional statistical estimators, including gene (77) and nucleotide (77, 113) diversity, and θ(π) (113), were calculated using Arlequin (103).
Nucleotide sequence accession numbers. The 52 nucleotide sequences reported here were submitted to the GenBank database under accession numbers DQ431855 to DQ431906.
RESULTS
RFLP and statistical analyses of SSU rRNA, nosZ, and amoA libraries. Sediment sample names were designated based on sampling time (3 for March or 5 for May), site (B for Bay or G for Gulf), and depth (02 for 0-2 cm or 1820 for 18-20 cm). Eleven clone libraries constructed from 3B02, 3B1820, 3G02, and 3G1820 sediments resulted in a total of 249 Bacteria SSU rRNA gene clones, 231 nosZ clones, and 64 amoA clones. Clones were analyzed and grouped into phylotypes according to observed RFLP patterns obtained in a previous study from the South Atlantic Bight (SAB) (42). A total of 71 phylotypes were detected in all four SSU rRNA gene clone libraries, resulting in a total percent coverage of 66%, with individual library coverage ranging from 32 to 42%. The nosZ clone library included 38 phylotypes with a total percent coverage of 74%, and individual clone library percent coverages ranging between 39 and 65%. Only 2 phylotypes were detected in the three amoA clone libraries and percent coverage was 54 TABLE 2.1. Summary of amoA gene sequences from 3B02, 3B1820, 3G02, 3G1820, and Total clone libraries. No. of Related Clones Phylogenetic Group Clone Nearest Relative % Similarity Total 3B02AG 3B1820AG 3G02AG 3G1820AG β−Proteobacteria 3B02A-05 MB Clone A10-99-S-15 98 20 14 0 6 0 3G1820A-01 MB Clone A10-99-S-15 98 44 13 0 15 16 55 FIG. 2.2. Rarefaction curves determined for the different RFLP patterns of SSU rRNA (A), nosZ (B), and amoA (C) gene clones from total, 3B02, 3B1820, 3G02, and 3G1820 samples. The number of different RFLP patterns was determined after digestion with restriction enzymes HaeIII and MspI. Rarefaction analysis was performed using equations reported Heck et al.
56 A. 80 70 60 50 B 0-2 SSU rRNA gene 40 B 18-20 SSU rRNA gene OTUs 30 G 0-2 SSU rRNA gene 20 G 18-20 SSU rRNA gene 10 Total SSU rRNA gene 0 0 50 100 150 200 250 300 Number of Clones
B. 40 35 30 25 B 0-2 nosZ 20 B 18-20 nosZ OTUs 15 G 0-2 nosZ 10 G 18-20 nosZ 5 Total nosZ 0 0 50 100 150 200 250 Number of Clones
C. 20 18 B 0-2 amoA 16 G 0-2 amoA 14 G 18-20 amoA 12 Total amoA 10
OTUs 8 6 4 2 0 0 10 20 30 40 50 60 70 Number of Clones
57 TABLE 2.2 Statistical analyses of SSU rRNA and nosZ gene clone libraries using standard ecological and molecular estimates of sequence diversity.
Num. of clones % Shannon-Weiner Nucleotide PCR target Sample Species richness Evenness 1/D Gene diversity θ (π) (Phylotypes) Coverage index diversity
SSU rRNA 3B02 70(38) 42 64 (48, 101)a 0.83 3.44 40.3 0.97 ± 0.01b 0.20 ± 0.10b 264.5 ± 127.2b gene 3B1820 67(44) 36 85 (63, 132) 0.82 3.66 67.0 0.98 ± 0.01 0.19 ± 0.09 242.5 ± 116.9 3G02 55(34) 32 66 (47, 110) 0.80 3.34 38.1 0.97 ± 0.01 0.20 ± 0.10 252.4 ± 121.7 3G1820 57(31) 42 50 (38, 83) 0.83 3.25 34.0 0.97 ± 0.01 0.19 ± 0.09 243.4 ± 117.2 Total 249(71) 66 92 (80, 122) 0.86 3.89 42.2 0.97 ± 0.00 0.20 ± 0.10 261.7 ± 112.3
nosZ 3B02N 27(13) 54 18 (14, 39) 0.84 2.42 15.3 0.93 ± 0.02 0.26 ± 0.13 261.3 ± 128.4 3B1820N 33(18) 39 38 (23, 105) 0.74 2.68 17.6 0.94 ± 0.02 0.26 ± 0.13 258.1 ± 126.2 3G02N 81(27) 52 41 (31, 78) 0.72 2.67 8.2 0.86 ± 0.03 0.24 ± 0.12 246.7 ± 118.3 58 3G1820N 90(23) 65 28 (24, 48) 0.81 2.70 12.3 0.91 ± 0.02 0.27 ± 0.13 275.1 ± 131.6 Total 231(38) 74 46 (40, 66) 0.79 3.03 14.1 0.92 ± 0.01 0.27 ± 0.13 264.0 ± 125.4
a The numbers in parentheses are 95% confidence intervals. b Mean ± standard deviation. TABLE 2.3. Summary of SSU rRNA gene sequences from 3B02, 3B1820, 3G02, 3G1820, and Total clone libraries. No. of Related Clones Phylogenetic Group T-RFLP Clone Nearest Relative % Similarity Total 3B02 3B1820 3G02 3G1820 α−Proteobacteria 211 LC1-35 MV clone Kazan-2B-34/BC19-2B-34 99 14 6 4 2 2 224 3B02-43 MB clone 114 95 9 3 2 2 2 64 LC1-28 FS clone DUNssu161 90 8 3 3 1 1 265 LC1-25 Isolate MBIC3923 93 8 2 0 2 4 50 LC1-34 MS clone Nubeena268 98 7 0 3 2 2 135 LC1-30 SCB clone 131735 96 5 1 4 0 0 210 3G02-39 Hyphomicrobium sp. Ellin112 94 4 1 1 1 1 137 SC3-43 HA clone K2-19 95 3 0 1 1 1 211 LC1-31 Sargasso Sea Isolate 5 99 1 1 0 0 0 δ−Proteobacteria 133 3B1820-38 ES clone 4aFS 98 8 4 2 1 1 191 3G02-06 GH clone Hyd89-23 98 5 1 1 2 1
59 237 3G02-43 OAE clone 126I-1 94 3 0 0 1 2 134 SC3-7 MS clone SK1 95 2 2 0 0 0 217 LC1-13 MV clone HMMVPog-8 91 1 0 1 0 0 γ−Proteobacteria 194 SC3-6 Photobacterium sp. HAR72 96 10 0 1 5 4 143 3B02-35 AS clone SC-I-16 95 7 2 1 2 2 111 SC1-14 HV clone AT-s80 94 4 0 2 1 1 138 SC3-20 HV clone NDII1.2 92 2 0 1 0 1 215 3G02-10 HV clone AT-s3-1 94 2 0 0 1 1 178 LC3-5 MB clone EF100-91A10 94 2 0 1 1 0 Planctomycetes 326 3B1820-36 DSS clone E8 89 17 5 3 5 4 151 LC3-21 MV clone Amsterdam-2B-62 90 13 4 1 4 4 99 LC1-9 DSS clone E8 88 3 1 2 0 0 429 SC3-24 GoM clone GoM GB425 02B-7 95 3 1 0 1 1 TABLE 2.3 -- Continued 94 LC1-1 AS clone 0319-7F4 89 3 2 1 0 0 Actinobacteria 115 3G02-25 SAM clone Y194 99 4 1 0 1 2 73 3G1820-35 AC clone wb1 G04 92 3 0 1 1 1 191 3G02-16 MV clone Kazan-2B-20/BC19-2B-20 96 3 0 2 1 0 51 3G02-22 PWP clone A20 93 2 0 1 1 0 52 3G1820-55 DS clone BD2-10 95 2 0 0 1 1 Cyanobacteria 112 3B1820-43 Chloroplast Alnus incana 99 4 0 2 2 0 Acidobacteria 143 3B1820-07 MS clone Dover464 94 2 0 2 0 0 134 LC3-65 AC clone wb1 A08 94 2 0 0 1 1 Bacteroidetes/ 51 3G02-18 clone DG977 93 13 4 1 4 4 Chlorobi 51 3B1820-44 MV clone HMMVPog-16 97 6 3 3 0 0 49 SC3-56 Endosymbiont Acanthamoeba sp. ATCC 30868 91 3 2 1 0 0 52 3B02-26 HV clone PaswB03 96 3 2 0 1 0 190 LC3-28 CS clone MERTZ 21CM 53 98 2 1 1 0 0 31 3B02-03 ML clone ML617.5J-33 93 2 2 0 0 0 Chloroflexi 131 3G1820-58 MV clone Amsterdam-2B-25 95 5 2 0 1 2 226 LC1-24 ME clone KM87 93 3 0 1 1 1 60 193 3G02-01 HV clone LC1537B-77 89 2 0 0 1 1 Firmicutes 66 3G02-02 Brevibacillus agri Strain NCHU1002 98 4 1 1 1 1 192 3B1820-01 PEG clone PeM05 90 4 1 2 0 1 Gemmatimonadetes 215 3G1820-03 MV clone Kazan-1B-25/BC19-1B-25 94 7 1 0 1 5 56 3G1820-56 clone AKYG548 95 2 1 0 0 1 FIG. 2.3. Frequencies of bacterial phylogenetic lineages detected in SSU rRNA gene clone libraries derived from 3B02, 3B1820, 3G02, 3G1820, and Total samples. Calculations were made based on the total number of clones associated with phylotypes from which a representative clone had been sequenced.
61 Gemmatimonadetes March Bay 0-2 cm 3% March Bay 18-20 Firmicutes Firmicutes Chloroflexi 3% Bacteroidetes/Chlorobi 5% Chloroflexi 2% cm Alphaproteobacteria 15% Alphaproteobacteria 3% 29% 32% Bacteroidetes/Chlorobi Acidobacteria 22% 4%
Cyanobacteria Deltaproteobacteria 4% 12% Actinobacteria Actinobacteria Deltaproteobacteria 2% Gammaproteobacteria 7% 7% Planctomycetes 3% Planctomycetes Gammaproteobacteria 23% 13% 11%
Firmicutes Gemmatimonadetes Gemmatimonadetes Chloroflexi 2% 2% Firmicutes 11% Bacteroidetes/Chlorobi 6% Alphaproteobacteria 4% 9% 20% Chloroflexi Alphaproteobacteria 7% 23% Acidobacteria Deltaproteobacteria 2% 8% Cyanobacteria Bacteroidetes/Chlorobi Deltaproteobacteria 4% 7% 7% Acidobacteria Actinobacteria Gammaproteobacteria 2%
62 9% 19% Actinobacteria Planctomycetes Gammaproteobacteria Planctomycetes 7% 16% 16% 19% Firmicutes March Gulf 0-2 cm Chloroflexi 4% Gemmatimonadetes March Gulf 18-20 cm 4% 4% Alphaproteobacteria Bacteroidetes/Chlorobi 26% 14%
Acidobacteria 2% Cyanobacteria Deltaproteobacteria 2% 8% Actinobacteria 6% Gammaproteobacteria Planctomycetes 12% Total 17% 100% (Table 2.1). No amoA amplification was detected in the 3B1820 sample from three cores, thus no library was constructed. Rarefaction curves for the combined SSU rRNA gene and nosZ libraries, and the combined and individual amoA gene libraries suggested a sufficient number of clones were sampled to represent library diversity (Fig. 2.2). Statistical estimators including species richness, Shannon-Weiner and 1/D indices, nucleotide diversity, gene diversity, evenness, and θ (π) indicated little difference between the four clone libraries constructed (Table 2.2).
Phylogenetic analysis based on the SSU rRNA gene. Sequence analysis of 47 SSU rRNA gene phylotypes indicated 9 distinct phyla with a majority of the sequences most closely related to sequences of uncultured organisms obtained from other marine environments. Nearly half of the total SSU rRNA gene clones grouped within the phylum Proteobacteria (46%). α−Proteobacteria-related clones alone accounted for 56% of the total Proteobacteria (Table 2.3). As observed in Ch.1, no clone sequences closely related to the classes β−Proteobacteria and ε-Proteobacteria were detected in the clone libraries. The phyla Planctomycetes (17%) and Bacteroidetes/Chlorobi (14%) comprised approximately one-third of all SSU rRNA gene clones (Table 2.3 and Fig. 2.3). The other six lineages detected (Acidobacteria, Actinobacteria, Chloroflexi, Cyanobacteria, Firmicutes, and Gemmatimonadetes) comprised between 2 and 6% of all SSU rRNA gene clones (Fig. 2.3 and Table 2.3). Two separate distance-based neighbor-joining trees were constructed with the 20 Proteobacteria and 26 non-Proteobacteria-related sequences from this study and reference sequences from the GenBank database (Fig. 2.4 and Fig. 2.5). The additional sequences and stringent tree construction allowed for classification of most clones to the family taxonomic level. The 20 Proteobacteria-related phylotypes grouped into three classes, i.e., α-, δ-, and γ-Proteobacteria with 9 most related to the α−Proteobacteria (Fig. 2.4). Phylotypes 3G02-39 and LC1-35 clustered with Hyphomicrobium denitrificans Strain DSM 1869, within the family Hyphomicrobiaceae (92 and 94%, respectively; Fig. 2.4). Hyphomicrobium denitrificans is a facultative methylotroph that is capable of anaerobic growth in the presence of nitrate (117). These two phylotypes were found in all four samples and represented 31% of the α-Proteobacteria-related clones
63 FIG. 2.4. Phylum Proteobacteria neighbor-joining phylogenetic tree, incorporating a Jukes-Cantor distance correction, of SSU rRNA gene from 3B02, 3B1820, 3G02, and 3G1820 samples. Sequences from this study and close relatives were aligned using the Fast Aligner algorithm, verified by hand and compared to the E. coli SSU rRNA secondary structure using the ARB software package. Bootstrap analyses were conducted on 1,000 samples and percentages greater than 50% are indicated at the nodes. Methanococcus maripaludis was used as the outgroup. Scale bar = 0.10 change per nucleotide position. Abbreviations are as follows: Desulfobu, Desulfobulbaceae; Desulfoba.(F), Desulfobacteraceae; Desulfoba.(O), Desulfobacterales; Rhodo.(F), Rhodobacteraceae; Rhodo.(O), Rhodobacterales; Hyphomicr., Hyphomicrobiaceae; Ectothio, Ectothiorhodospiraceae; Chroma., Chromatiales.
64 Methanococcus maripaludis [U38941] 81 Nautilia lithotrophica strain 525 [AJ404370] 99 Campylobacter gracilis strain CCUG 27721 [AF550658]
Thiomicrospira denitrificans strain DSM 1251 [L40808] Epsilon. Bacteriovorax stolpii [M34125] Nitrospina gracilis [L35504] 99 LC1-13 MV clone HMMVPog-8 [AJ704690] Desulfobulbus rhabdoformis [U12253] 92 SC1-40 90 Desulfocapsa thiozymogenes [X95181] 99 SC3-7 Desulfobu. Desulfocapsa Clone SB 1.17 [AY177794] 51 MS clone SK1 [AY771952] Desulfoba.(O) 3G02-06 GH clone Hyd89-23 [AJ535245]
Desulfospira joergensenii strain DSM 10085 [X99637] Deltaaproteobacteria 61 Desulfobacter halotolerans [Y14745] 99 Desulfococcus biacutus strain DSM 5651T [AJ277887] 61 Desulfosarcina variabilis [M34407] Desulfoba.(F) 59 3G02-43 3B1820-38 ES clone 4aFS [AM039962] 57 LC1-28 LC1-34 73 MS clone Nubeena268 [AY499896] Thalassospira lucentensis [AF358664] Nitrobacteria iranicum strain 101 [AY578913] Nitrobacter vulgaris strain DSM 10236T [AM114522] 99 Rhodovulum sulfidophilum TW13 [D16422] SC3-43 56 HA clone K2-19 [AY345433] 74 Jannaschia rubra strain 4SM3T [AJ748747] Rhodo.(F) Rhodo.(O) Thalassobacter stenotrophicus strain CECT 5294 [AJ631302] 53 85 LC1-30 Oceanicola batsensis strain HTCC 2597 [AY424898] SCB clone 131735 [AY922228] 88 3B02-43 MB clone 114 [AY654755] LC1-25 Rhodobium orientis [D30792] 80 Mesorhizobium sp. DG 943 [AY258089] Alphaaproteobacteria 97 Clone PI GH2.1.D5 [AY162047] Isolate MBIC3923 [AB016848] Rhizobiales LC1-31 Sargasso Sea Isolate 5 [AY082665] 93 3G02-39 Hyphomicrobium denitrificans strain DSM 1869 [Y14308] 54 51 Hyphomicrobium sp. Ellin112 [AF408954] Hyphomicr. 94 Hyphomicrobium sulfonivorans strain 25S [AY305006] 58 LC1-35 MV clone Kazan-2B-06/BC19-2B-31 83 Denitrobacter permanens [Y12639] 99 Thiobacillus denitrificans strain NCIMB 9548 [AJ243144] Nitrosomonas marina [AF272418] 82 Nitrosomonas sp. C-56 [M96400] 3B02-35 AS clone SC-I-16 [AJ252619] Thioalcalomicrobium aerophilum [AF126548] Kangiella koreensis clone SW-125 [AY520560] Methylomicrobium pelagicum [L35540] 57 Oceanospirillum maris strain ATCC 27509 [AB006771] 73 Oceanimonas denitrificans strain F13-1 [DQ097665] 71 Shewanella alga [X81621] 99 Vibrio diazotrophicus strain UN 11816 [DQ068941] SC3-6 80 Vibrionaceae 97 Photobacterium leiognathi strain RM1 [AY292947] Photobacterium sp. HAR72 [AB038032] 76 SC1-44 51 Pseudomonas sp. NB1 hBD5-16 [AB013829] Pseudomonadaceae SC1-11 99 LC3-5 Gammaproteobacteria Beta. MB clone EF100-91A10 [AY627370] HV clone NDII1.2 [AF181991] SC3-20 Nitrosococcus oceani Isolate Nc1 [AJ298727] HV clone AT-s80 [AY225635] SC1-14 Thioalcalovibrio denitrificans [AF126545] Chromo. 86 SC3-2 Ectothio. 73 3G02-10 HV clone AT-s3-1 [AY225632]
0.10 65 FIG. 2.5. Non-Proteobacteria neighbor-joining phylogenetic tree, incorporating a Jukes- Cantor distance correction, of SSU rRNA gene from 3B02, 3B1820, 3G02, and 3G1820 samples. Sequences from this study and close relatives were aligned using the Fast Aligner algorithm, verified by hand and compared to the E. coli SSU rRNA secondary structure using the ARB software package. Bootstrap analyses were conducted on 1,000 samples and percentages greater than 50% are indicated at the nodes. Methanococcus maripaludid was used as the outgroup. Scale bar = 0.10 change per nucleotide position. Abbreviations are as follows: Plancto.(F), Planctomycetaceae; Plancto.(O), Planctomycetales; Chrooc., Chroocales; Chlorob.(F), Chlorobiaceae; Chlorob.(O), Chlorobiales; Sphingo., Sphingobacteriales; Flavo.(F), Flavobacteriaceae; Flavo.(O); Flavobacteriales; Gemma.(F), Gemmatimonadaceae; Gemma.(O), Gemmatimonadales; Acido.(F), Acidobacteriaceae, Acido.(O), Acidobacteriales; Paeni., Paenibacillaceae; Turici., Turicibacteraceae; Anaero.(F), Anaerolinaceae; Anaero.(O), Anaerolinales.
66 Methanococcus maripaludis [U38941] 94 LC1-9 3B1820-36 90 DSS clone E8 [AJ966588] AS clone 0319-7F4 [AF234144] 88 LC1-1 53 Gemmata obscuriglobus strain UQM 2246 [X56305] 75 Isosphaera pallida strain DSM 9630T [AJ231195] 59 Planctomyces brasiliensis ATCC 49424 [X85247] 94 SC3-3 Blastopirellula marina DSM 3645 [X62912] Pirellula sp, S384 [X81944] Plancto.(F) Plancto.(O) Pirellula staleyi strain ATCC 35122 [AF399914] MV clone Amsterdam-2B-62 [AY592419] LC3-21 98 Pirellula clone 5H12 [AF029076] Planctomycetes 98 GoM clone GoM GB425 02B-7 [AY542549] SC3-24 3B1820-43 80 chloroplast Alnus incana [U03555] SC3-15 Chloroplast 92 Chloroplast Bacillaria paxillifer [AJ536452] 98 Chloroplast Haslea salstonica [AF514854] 92 Prochlorococcus clone PENDANT-4 [AF142917] 84 Prochlorococcus marinus [X63140] 54 Synechococcus sp. PCC 7117 [AB015060] SC3-19 66 Cyanobacterium sp. MBIC10216 [AB058249] Chrooc.
54 SC1-42 Cyanobacteria CS clone MERTZ 21CM 53 [AF424371] 95 LC3-28 Chloroherpeton thalassium [AF170103] 70 Chlorobium limicola [Y08102] 92 Chlorobaculum parvum strain DSM 263T [Y10647] Chlorob.(F) Chlorob.(O) 93 Prosthecochloris vibrioformis strain UdG 6043 [Y10648] 63 Clathrochloris sulfurica strain 1 [X53184] Pelodictyon luteolum strain 2530 [Y08107] 88 Saprospira grandis strain ATCC 23116 [AY527408] 3B02-03 Saprospiraceae ML clone ML617.5J-33 [AF507866] Endosymbiont Acanthamoeba sp. ATCC 30868 [AY549546] 89 SC3-56 Sphingo. 89 Flexithrix dorotheae strain IFO 15987 [AB078077] 51 Flexibacter aggregans [AB078038] 98 3B02-26 Flexibacter. 99 HV clone PaswB03 [AB213188] 81 Bacteroides fragilis [X83948] 69 Prevotella buccae strain ATCC 33690 [L16478] 99 BM clone SB-5 [AF029041] 3B1820-44 66 MV clone HMMVPog-16 [AJ704702] 99 Flavobacterium johnsoniae [M59053] Bacteroidetes/Chlorobi 55 Cellulopha lytica [M62796] Flavo.(F) Flavo.(O) 55 Pibocella ponti clone SE51 [AY771762] 3G02-18 clone DG977 [AY258127] (P) 3G1820-03 MV clone Kazan-1B-25/BC19-1B-25 [AY592102] 52 Gemmatimonas aurantiaca [AB072735] 3G1820-56 Gemma.(F) Gemma.(O) clone AKYG548 [AY921936] 50 Solibacter usitatus strain Ellin6076 [AY234728] Holophaga foetida strain TMBS4-T [X77215] Gemma. Acidobacterium capsulatum [D26171] AC clone wb1 A08 [AF317741]
LC3-65 Acido.(F) Acido.(O) (P) 99 3B1820-07 50 MS clone Dover464 [AY499835] 80 LC3-26 SC1-4 79 Clostridium tetani NCTC 279 [X74770] Acido. 88 Fusibacter paucivorans [AF050099] Planifilum fulgidum strain C0170 [AB088363] 53 Marinococcus halophilus strain Iv4 [DQ093352] 76 Caryophanon latum strain DSM 14151T [AJ491302] Planococcus southpolaris strain CMS 84or [AJ314747] 57 Geobacillus pallidus strain Y25 [AB198976] 70 Salinicoccus marinus [AY328901] 3G02-02 Paeni. Brevibacillus agri strain NCHU1002 [AY319301] 97 3B1820-01 Bacillales Firmicutes 94 PEG clone PeM05 [AJ576377] Turici. Turicibacter sanguinis strain MOL361 [AF349724] 95 Pilibacter termitis [AY533171] 94 Lactococcus lactis strain G121 [DQ341261] Streptococcus macedonicus [Z94012] 68 Chloroflexus aurantiacus [D38365] Thermomicrobium roseum [M34115] 58 Dehalococcoides ethenogenes [AF004928] 94 Caldilinea aerophila strain STL-6-01 [AB067647] 98 LC1-24 64 ME clone KM87 [AY216458] 76 Anaerolinea thermophila strain UNI-1 [AB046413] Anaero.(F) Anaero.(O) 3G02-01 HV clone LC1537B-77 [DQ272585]
99 3G1820-58 Chloroflexi MV clone Amsterdam-2B-25 [AY592385] Rubrobacter radiotolerans [X87134] Denitrobacterium detoxificans strain MAJ1 [AF079507] 56 Bifidobacterium asteroides strain ATCC 29510 [M58730] 99 Rhodococcus erythreus strain DSM 43066 [X79289] 97 Cathayosporangium alboflavum strain IFO16009 [AB006158] 55 Sarraceniospora aurea strain IFO14752 [AB006177] Acidimicrobium ferrooxidans [U75647] 62 Ferrimicrobium acidiphilum strain T23 [AF251436] 77 Microthrix parvicella [X89560] 75 SC3-41 51 3G1820-35 3G02-16 99 MV clone Kazan-2B-20/BC19-2B-20 [AY592144] AC clone wb1 G04 [AF317765] 91
3G1820-55 Actinobacteria 96 DS clone BD2-10 [AB015539] 3G02-22 72 PWP clone A20 [AY373407] 99 3G02-25 SAM clone Y194 [AB116479] 0.10 67 (Table 2.3). Three phylotypes, represented by clones SC3-43, LC1-30, and LC1-31, clustered into the family Rhodobacteraceae of the order Rhodobacterales (Fig. 2.4). Phylotypes LC1-30 and LC1-31 represented 10% of the α-Proteobacteria-related clones and clustered with the aerobic chemoheterotrophs Oceanicola batsensis Strain HTCC 2597 and Stappia stellulata, respectively (15, 116) (Table 2.3 and Fig. 2.4). Two phylotypes, represented by clones LC1-25 and 3B02-43, clustered within the order Rhizobiales and represented 29% of the total α-Proteobacteria-related clones (Fig. 2.4). Phylotype LC1-25 clustered into a clade with Rhodobium orientis, a purple non-sulfur bacteria (36), and Mesorhizobium sp. DG 943, a nitrogen-fixing symbiont of leguminous plants (64) (Fig. 2.4). Two additional phylotypes, LC1-28 and LC1-34, accounting for one-quarter of the total α-Proteobacteria-related clones, branched into their own distinct clade; however, no cultured representatives were available to further classify these phylotypes (Fig. 2.4). A total of 6 of the 20 Proteobacteria-related phylotypes grouped within the class γ-Proteobacteria (Fig. 2.4). Two of the 6 phylotypes, represented by clones SC3-20 and 3G02-10, grouped into the family Ectothiorhodospiraceae and had high sequence similarity (91% and 92%, respectively) to the cultured isolate Thioalkalispira microaerophila strain ALEN 1, a lithoautotrophic sulfur-oxidizer (110) (Fig. 2.4). These phylotypes also branched with SAB clone SC3-2 (Ch. 1) and were detected using T- RFLP in this study. Phylotype SC1-14 clustered within the family Chromatiaceae and was 88% similar to Nitrosococcus oceani isolate Nc1 (1) (Fig. 2.4). The remaining 5 Proteobacteria phylotypes were affiliated with the class δ- Proteobacteria. Phylotypes 3G02-43 and 3B1820-38 represented 58% of the total δ- Proteobacteria-related phylotypes and clustered within the family Desulfobacteraceae, sharing a 92 % sequence identity to Desulfosarcina variabilis, a group II sulfate-reducer (64) (Table 2.3 and Fig. 2.4). Phylotype SC3-7 clustered with Desulfocapsa Clone SB 1.17 in the family Desulfobulbaceae, of group I sulfate reducers (64) (Fig. 2.4). Also branching within this family near Desulfobulbus rhabdoformis and detected using T- RFLP, was SAB clone SC1-40 (Ch. 1; Fig. 2.4). Representing 32% of the total δ- Proteobacteria-related phylotypes, 3G02-06 and LC1-13 formed their own clade and could not be further classified beyond the class level (Fig. 2.4). Phylotype 3G02-06
68 shared a 98% sequence identity to GH clone Hyd89-23 (52), while phylotype LC1-13 was 91% similar to MV clone HMMVPog-8 (Unpublished) (Table 2.3). A second distance-based neighbor-joining tree was constructed with 26 non- Proteobacteria-related phylotypes grouping into 8 phyla (Fig. 2.5). Similar to the Proteobacteria-related phylotypes, a majority of sequences collected were closely related to sequences from environmental clones of uncultured organisms associated with various marine habitats. Of the 26 non-Proteobacteria-related phylotypes, 5 grouped within the phylum Planctomycetes, typically facultative aerobic chemoorganotrophs (64) (Fig. 2.5). The phylum Planctomycetes has only a single class, order, and family currently identified (28), however, only 2 of the 5 phylotypes grouped into this clade (Fig. 2.5). These two phylotypes, represented by LC3-21 and SC3-24, accounted for 41% of the total Planctomycetes-related clones (Table 2.3). The other three phylotypes, represented by clones 3B1820-36, LC1-9, and LC1-1, diverged from the classified Planctomycetes (Fig 2.5) to form a second clade that was supported by strong bootstrap values. Phylotype 3B1820-36 was the most frequently detected phylotype (44% of the total Planctomycetes-related clones) and was found to be only 89% similar to it’s closest related clone, DSS clone E8 from deep Pacific Ocean sediment (Unpublished) (Table 2.3). The Bacteroidetes/Chlorobi superphylum contained 6 of the 26 total non- Proteobacteria-related phylotypes, accounting for 14% of the total SSU rRNA clones (Table 2.3). Two of these phylotypes, 3B02-26 and 3B1820-44, clustered into the family Flexibacteraceae (Fig. 2.5). However, the most numerically dominant phylotype, 3G02- 18 (45% of the total Bacteroidetes/Chlorobi-related clones), clustered into the family Flavobacteriaceae (Fig. 2.5). Both Flexibacteraceae and Flavobacteriaceae have aerobic and anaerobic members and are commonly found in marine environments. A third family, Saprospiraceae, was represented by the phylotype 3B02-03, which was 93% similar to ML clone ML617.5J-33 from Mono Lake, California (41) (Table 2.3 and Fig. 2.5). The remaining two phylotypes, SC3-56 and LC3-28, were able to only be classified to the order level, Sphingobacteriales and Chlorobiales, respectively. Two phyla, Acidobacteria and Actinobacteria, had all phylotypes cluster away from identified cultured isolates, providing no further classification (Fig. 2.5).
69 Phylotypes LC3-65 and 3B1820-07 in the phylum Acidobacteria, clustered apart from both of the previously identified classes, Acidobacteria and Solibacteres (Fig. 2.5). Two other phylotypes, LC3-26 and SC1-4, previously identified from a similar study in the SAB (42), also branched apart from these classes and into the same clade as LC3-65 and 3B1820-07 (Fig. 2.5). Five of the six phylotypes in the phyla Actinobacteria, clustered within their own clade and apart from any cultured isolates (Fig. 2.5). Clone SC3-41 (42) was most related to the genus Candidatus Microthrix parvicella (89%) and clustered within a mostly unclassified clade including the family Acidomicrobiaceae and the genus Ferrimicrobium acidiphilum strain T23 (Fig. 2.5). The remaining 8 phylotypes represented the phyla Cyanobacteria, Chloroflexi, Firmicutes, and Gemmatimonadetes. Only one phylotype, 3B1820-43, clustered within the phylum Cyanobacteria and was 99% similar to chloroplast DNA sequence from Alnus incana (Fig. 2.5 and Table 2.3). Three phylotypes, LC1-24, 3G02-01, and 3G1820-58, clustered within the family Anaerolinaceae in the phylum Chloroflexi (Fig. 2.5). Phylotypes 3G02-02 and 3B1820-01 clustered within the phylum Firmicutes (Fig. 2.5). Phylotype 3G02-02 was 98% similar to the aerobic microbe Brevibacillus agri Strain NCHU1002 in the family Paenibacillaceae, while phylotype 3B1820-01 clustered into the family Turicibacteraceae (Table 2.3 and Fig. 2.5). Both of these family clusters are in the order Bacillales and class Bacilli. The final two phylotypes, 3G1820-03 and 3G1820-56, branched into the phylum Gemmatimonadetes, which are aerobic chemoheterotrophs and currently only contains one class (Gemmatimonadetes), order (Gemmatimonadetes), and family (Gemmatimonadaceae) (Fig. 2.5).
T-RFLP analysis based on the SSU rRNA gene. The 5’ terminal fragment size in bases for each sequenced clone was determined by an in silico digest using the MnlI recognition site. The MnlI derived terminal fragment length was matched to the peak sizes from the T-RFLP analysis and representative phylotypes were designated to the peaks for each of the 28 sediment sample profiles (i.e., 7 depths, 2 sites, 2 months). Ten phylotypes were chosen at random to have in silico digests verified by individual T- RFLP analysis. Representative profiles are shown in Fig. 2.6. In all 28 profiles, approximately 50% of the peaks were identified.
70 FIG. 2.6. T-RFLP fingerprints of March Bay 0-2 cm, Bay 2-4 cm, and Gulf 0-2 cm samples.
71 March Bay 0-2 cm
72 March Bay 2-4 cm
March Gulf 0-2 cm While some phylotypes such as SC1-4, LC1-31, and LC1-35 were found throughout all cores, many of the identified SSU rRNA gene phylotypes were exclusive to either the Bay samples or the Gulf samples. Further, many phylotypes were only detected at certain depths in the sediment cores. Phylotypes LC3-65 and LC3-26, identified as Acidobacteria, were primarily detected in the upper depths of the sediment cores. The α- Proteobacteria-related phylotype LC1-30 was only detected at depths of 0-6 cm in all four samples. Phylotypes 3B1820-38 and LC1-13, identified as δ-Proteobacteria, were found deeper in the sediment cores. 3B1820-38 was detected at a depth of 14-16 cm in the 3B samples and at a depth of 14-20 cm in the 5G samples, while phylotype LC1-13 was detected at depths of 8-20 cm in both Bay samples and at a depth of 18-20 cm in both Gulf samples. Phylotypes 3B1820-43 and SC3-21 were both detected at mid to upper depths in the 3B and 5B samples and were more uniformly dispersed in the 3G and 5G samples. For each of the 28 SSU rRNA T-RFLP profiles generated, a Sorensen’s Index was calculated. A dendrogram was constructed based on the pair-wise analysis percent similarity (Fig. 2.7a). It is interesting to note, that all of the Gulf samples clustered together and all of the Bay samples clustered together with only 50% sequence similarity between the clades. Furthermore, all Gulf samples from March and May clustered in separate clades (63% similarity), and with the exception of Bay 4-6 cm May and Bay 6-8 cm May, all Bay samples from March and May formed distinct clusters (52% similarity). Additionally, the 0-2 and 2-4 cm depths clustered together within each of the 4 cores (76%), as well as the 8-10 and 18-20 cm depths in both of the Gulf cores (78% similarity in March and 80% similarity in May; Fig. 2.7a).
Phylogenetic and T-RFLP analysis based on the nosZ gene. Sequence analysis of 42 nosZ gene phylotypes indicated that a majority of the sequences were most closely related to uncultured sequences that clustered within the α-Proteobacteria (Fig. 2.8). Several deep branching clades were comprised solely of clones from SAB and NEGOM (Fig. 2.8). Phylotype 3G1820N-14, the third most frequently detected phylotype (10% of the total nosZ clones), was most closely related to Sinorhizobium meliloti 1021, a
73 FIG. 2.7. Sorensen’s based index dendrograms of SSU rRNA gene (A) and nosZ gene (B).
74 A.
B.
75 FIG. 2.8. Neighbor-joining phylogenetic tree, incorporating a Jukes-Cantor distance correction, of nosZ gene from 3B02, 3B1820, 3G02, and 3G1820 samples. Sequences from this study and close relatives were aligned using the Fast Aligner algorithm and verified by hand using the ARB software package. Bootstrap analyses were conducted on 1,000 samples and percentages greater than 50% are indicated at the nodes. Ralstonia eutropha Strain H16 was used as the outgroup. Scale bar = 0.10 change per nucleotide position.
76 Ralstonia eutropha [AY305378] 99 Pseudomonas denitrificans [AF016059] Pseudomonas stutzeri [M22628] 3G1820N-30 Gamma. 60 Bradyrhizobium japonicum [AJ002531] 94 3G1820N-14 90 Sinorhizobium meliloti [AE007253] 51 3G02N-12 CSS clone 696G [AF119948] 72 SC1N-58 CSS bacterium 696M [AF119944] 99 CSS bacterium 696H [AF119947] CSS bacterium 696T [AF119940] 3B1820N-11 LC1N-21 3B1820N-17 59 93 3G02N-02 SC3N-14 3B02N-19 85 CSS bacterium 696C [AF119951] CSS bacterium 696J [AF119946] 97 SC1N-6 SC3N-41 3G1820N-20 66 SC1N-68 53 3G1820N-12 CSS bacterium 696W [AF119925] 3G1820N-18 3G1820N&27 Silicibacter pomeroyi DSS-3 plasmid [CP00003] 3G1820N-48 84 CSS clone ProG [AF119924] MS clone S321195A [AF016055] 3B02N-24 3B02N-05 SC3N-27 LC1N-62 SC1N-13 94 CSS clone ProC [AF119921] 62 CSS clone ProO [AF119933] LC1N-45 SC1N-32 SC3N-19 87 3G1820N-05 CSS bacterium 696I [AF119918] SC3N-24 3B1820N-01 88 CSS clone ProP [AF119935] Alphaproteobacteria CSS bacterium 696A [AF119954] 73 CSS bacterium 696K [AF119945] CSS clone ProV [AF119938] 3G1820N-03 3G1820N-06 96 3B1820N-06 83 LC1N-47 SC1N-35 97 SC1N-15 SC3N-13 SC1N-38 88 3B1820N-14 60 3G1820N-08 92 LC3N-32 SC3N-11 94 3G1820N-23 SC1N-18 76 SC1N-02 75 SC1N-01 57 SC1N-11 SC1N-08 67 3B02N-21 CSS clone ProR [AF119937] 56 SC3N-21 SC3N-45 58 SC1N-45 3G02N-16 SC3N-01 SC1N-53 50 LC3N-27 54 SC1N-27 SC3N-10 67 SC3N-8 99 SC3N-15 66 3G02N-46 96 SC3N-12 3G02N-56 3G02N-14 SC1N-30
0.10 77 TABLE 2.4. Summary of nosZ gene sequences from 3B02, 3B1820, 3G02, 3G1820, and Total clone libraries. No. of Related Clones Phylogenetic Group T-RFLP Clone Nearest Relative % Similarity Total 3B02N 3B1820N 3G02N 3G1820N α−Proteobacteria 143 3G02N-02 CSS bacterium 696M 81 37 3 2 25 7 97 3G1820N-08 CSS clone ProP 83 35 4 6 9 16 140 3G1820N-14 S. meliloti plasmid 86 86 21 2 3 2 14 121 3G1820N-27 CSS bacterium 696W 84 13 0 0 4 9 213 3G02N-14 CSS clone ProR 83 12 3 2 5 2 140 3B1820N-17 CSS bacterium 696M 80 10 1 1 4 4 261 3G1820N-06 CSS bacterium 696K 80 10 1 1 0 8 254 3G1820N-03 CSS bacterium 696K 80 10 1 3 2 4 153 3B02N-19 CSS clone ProR 82 8 2 4 2 0 127 3G1820N-18 CSS bacterium 696W 82 8 0 1 2 5 123 3G02N-16 CSS clone ProR 85 5 0 0 3 2 226 3B02N-05 CSS clone ProG 82 5 3 1 1 0
78 123 3B1820N-01 CSS clone ProV 82 5 4 1 0 0 319 3B1820N-06 CSS clone ProR 82 4 0 1 1 2 226 3G02N-12 CSS clone ProR 83 4 0 0 3 1 225 3B02N-24 CSS clone ProG 83 4 1 1 1 1 171 3G1820N-48 CSS clone ProG 82 3 0 0 2 1 361 3G1820N-05 CSS bacterium 696I 85 3 0 0 2 1 227 3G02N-46 CSS clone ProR 83 3 0 2 1 0 319 3G1820N-20 CSS bacterium 696W 84 2 0 0 0 2 360 3G1820N-23 CSS clone ProR 84 2 0 0 1 1 98 3B1820N-14 CSS clone ProP 83 2 1 1 0 0 226 3G02N-56 CSS clone ProR 84 2 0 0 2 0 221 3G1820N-12 CSS bacterium 696W 82 2 0 0 0 2 224 3B02N-21 CSS clone ProR 87 1 1 0 0 0 439 3G1820N-30 CSS clone ProR 81 1 0 0 0 1 143 3B1820N-11 CSS bacterium 696M 81 1 0 1 0 0 nitrogen-fixing soil bacterium (3) (Table 2.4). The most frequently detected phylotype (17% of the total nosZ clones), 3G02N-02, was 81% similar to CSS bacterium 696M, identified off the coast of New Jersey (100) (Table 2.4). Interestingly, 87% of 3G02N-02 phylotypes detected were in the Gulf samples and 78% of these were in 3G02N (Table 2.4). Phylotype 3G1820N-08 (16% of the total nosZ clones) was most similar to a nosZ clone, ProP, identified from San Clemente Island, California (100) (Table 2.4 and Fig. 2.8). Similar to the community fingerprints of the SSU rRNA gene, approximately half of the T-RFLP peaks from the nosZ fingerprints were identified and given a corresponding phylotype. Numerous phylotypes were detected in both the Bay and Gulf samples. Phylotypes SC3N-21, SC1N-18, 3G1820N-12, and SC3N-19 were detected nearly uniformly throughout all cores. Other phylotypes were exclusive to one site, certain samples, or at limited depths within the cores. Ten phylotypes were detected only in Bay samples, while others were only found in Gulf samples. For example, phylotype SC3N-27 was primarily detected only in the upper depths in the 3G (2-6 cm), while phylotypes SC3N-1, SC1N-38 SC1N-45 were found nearly uniformly throughout the 3G and 5G samples. A similar Sorensen’s based dendrogram was created for the 28 nosZ T-RFLP profiles (Fig. 2.7b). As found in the SSU rRNA dendrogram, all Gulf and Bay samples clustered separately from each other and had a sequence similarity of only 38%. The Bay samples from March and May also showed a very distinct clustering between them and had a sequence similarity of 52% (Fig. 2.7b). The Gulf samples from March and May showed a less distinct clustering between the two sampling dates. Interestingly, the 2-4 and 8-10 cm depths branched together between each of the two sampling dates (72% and 82% sequence similarity; Fig. 2.7b).
79 DISCUSSION
Microbial communities in permeable marine sediments are understudied with respect to those of muddy or impermeable sedimentary environments. In contrast to organic-rich muds, microorganisms in permeable sands are present in lower abundance but show a high metabolic activity (12, 98). Metabolic activity is believed to be enhanced in more permeable environments due to the increased delivery of growth substrates and the removal of metabolites by advective exchange (22). Permeable sediments may support an especially dynamic microbial niche, where redox gradients are diminished due to rapid flushing caused by waves and tides. The overall objective of this study was to expand the analysis of microbial communities in permeable marine sediments to include an extensive characterization across environmental gradients (flushing rates, organic matter content) that are likely to define microbial niches on the continental shelf. Two sites were investigated in the shallow ocean in the northeastern Gulf of Mexico (NEGOM). Sediments from the Bay and Gulf sites are subjected to similar water and weather conditions. The primary difference between the two sites is the extent of porewater flux into the sediment due to wind and wave propagation. At the Gulf site, sediments are exposed to higher flushing rates due to increased exposure to waves, while the Apalachicola Bay site is exposed to more quiescent conditions. Sediments at the Bay site therefore contain a higher organic matter content, support higher rates of organic matter cycling, and the oxic-anoxic boundary, as visualized by the reduction of brown Fe (III) oxides to black Fe sulfides, is nearly always located several centimeters closer to the sediment surface in Bay vs. Gulf cores. The Bay site is exposed to less mixing forces and thus remains stratified, allowing a more defined oxic/anoxic boundary layer. Microbial community composition was determined by T-RFLP profiling and robust phylogenetic analysis. Few studies have examined spatial variability of denitrifiers in sandy sediments (101) and no
80 environmental study to date compared denitrifier diversity to the overall bacterial community.
Clonal Analysis of Permeable Shelf Sediment Communities
This study provides the most detailed sequence database yet collected from any permeable sedimentary environment. The diversity of overall and denitrifying bacterial communities was high as determined by clonal analysis of SSU rRNA and nosZ genes, respectively, in corroboration with previous work from our laboratory (Ch. 1). The robust sequence database of this study expanded current knowledge to show the contribution of taxa (Actinobacteria, and Cyanobacteria, Acidobacteria, Bacteroidetes/Chlorobi, Chloroflexi, and Firmicutes) that had not been previously recognized in marine sands using cultivation-independent methods with inherently lower resolution (12, 62, 98). In agreement with previous studies, the majority of phylotypes retrieved from permeable marine sediments were most closely related to three subclasses within the phylum Proteobacteria (i.e., α-, δ-, and γ-Proteobacteria), and phylum Planctomycetes. As shown for the SAB site (Ch. 1), the α-Proteobacteria, in particular, were a relatively abundant group in the overall and denitrifying community clone libraries associated with the NEGOM sites. By targeting the nosZ gene, a vast diversity was uncovered within the α- Proteobacteria. To date, few marine denitrifiers have been cultured and isolated, making classification beyond the sub-class level, i.e., α-Proteobacteria, impossible. However, phylogenetic analysis of the nosZ sequences revealed tight clustering with clone sequences obtained in our previous SAB study (Ch.1), as well as with sequences from a previous study by Scala et al. (1999). Interestingly, only two known phylotypes capable of denitrification, sharing 92 and 94% sequence similarity with Hyphomicrobium denitrificans strain DSM 1869 (91), were detected with SSU rRNA gene analysis. Analysis of the amoA gene showed a low diversity in NEGOM sediments in comparison with previous studies of marine muds (4, 13, 24, 78, 81); with a comparably
81 low number of phylotypes detected as in our previous study of the SAB (Ch. 1). Clonal analysis of the amoA gene revealed two similar phylotypes to those detected in SAB sandy sediments (42) and ubiquitous to both NEGOM sites. Since nitrification plays a critical role in the coastal nutrient cycling and β-Proteobacteria-related species have been detected in other marine habitats (2, 6, 37, 68, 72, 76, 114), the detection of amoA genes within these sediments suggest that we are under-representing these taxa in our SSU rRNA clone libraries. In addition, the lack of amoA diversity within this study may be explained by recent reports suggesting that nitrifier diversity may instead lie within ammonia-oxidizing archaea (AOA), rather than ammonia-oxidizing bacteria (AOB) in marine environments (25).
Development of High Throughput Techniques and Their Application to the Determination of Niche Specialization in Permeable Shelf Sediments
An understanding of microbial diversity in marine sediments and it’s significance to ecosystem function has been hampered by the excessive time and cost of sample processing. Extracting and analyzing gene sequences from sediments is tedious, and the majority of previous studies have lacked replication or have based interpretation of microbial community composition on relatively few samples. Therefore, one of the major goals of this study was to develop a method for the accurate screening of microbial communities in large numbers of sediment samples that is both time and cost efficient. Here we combined an existing sequence database from our previous work (42), novel clonal analysis, with a modified nucleic acid extraction procedure and T-RFLP analysis to obtain a quick and cost efficient means of high resolution profiling the microbial communities in permeable sediments of the NEGOM. Over 84 samples were extracted and analyzed for SSU rRNA gene and nosZ sequences. Quantitative T-RFLP comparisons of communities from various combinations of subsampling and pooling of nucleic acid extracts showed no substantial differences between triplicate cores taken at a single site. Therefore, determinations of
82 diversity and phylogenetic composition were based upon combined DNA extracts from triplicate cores taken at each site and time, resulting in a database of 28 fingerprints for SSU rRNA gene and nosZ sequences. By standardizing the amount of nucleic acid and PCR amplicon used in the analysis, these results indicate that highly replicable T-RFLP profiles of structural and functional gene targets may be obtained from multiple core samples taken at the same site, depth, and time. The utility of the abovementioned high throughput methods was further supported by extensive T-RFLP profiling in sediment samples from the NEGOM sites, and the results provide evidence for microbial niche specialization in permeable sands. By using T-RFLP analysis and applying statistical estimators such as Sorensen’s Index to the resulting profiles, we were able to see distinct differences in the microbial communities at each sampling site, as well between sampling dates and depths within each core. Clonal analysis of SSU rRNA genes limited to phylum level indicated little difference between the two sampling sites (Fig. 2.3) with few variations in the presence and frequency of the 9 detected phyla. In general, classification beyond the phylum level is critical to the understanding of structure-function relationships, but most studies do not classify environmental sequences to higher resolution (58, 63, 72); therefore, by classifying many of our clones down to the family level, differences in physiology were observed that were not evident with the clone libraries and phylogenetic trees alone. Statistically based comparisons of the T-RFLP profiles indicated a distinct difference between the two NEGOM sites. Many SSU rRNA phylotypes had limitations on where or when they were detected, suggesting differences in environmental conditions within and between sediment cores. For example, most of the δ-Proteobacteria-related phylotypes, grouping into the obligate anaerobic families Desulfobulbaceae and Desulfobacteraceae, were detected at depths below 8 cm in the Bay and below 14 cm in the Gulf, which is consistent with the oxic/anoxic boundary visualized within the cores. Similar site and month specificity was apparent in the overall communities and within the denitrifiers. A distinct split between the Bay and Gulf samples and with the exception of only a couple of samples, a split between the March and May samples at each site. As was seen with the SSU rRNA gene analysis, many phylotypes were only detected at certain sites and depths, indicating niche specialization within the microbial
83 community. While it is generally assumed that denitrification occurs under anoxic conditions, aerobic denitrification has been observed in pure cultures and sandy sediments (32, 92, 95, 124) and thus may be occurring in the Gulf sediments. Anoxic micro-niches may also be present in the sediments, allowing zones of activity for anaerobic denitrifiers. Another theory is that not all of these denitrifiers are active and similar to phylotypes detected by SSU rRNA analysis, were only detected because of transport and mixing. To test this theory, methods targeting active members of the community, i.e., FISH or mRNA analysis, should be utilized. The majority of phylotypes retrieved from NEGOM sediments were not closely related to any cultivated organisms and the phylogenetic relationships of many of these phylotypes is uncertain. Often the interpretation of our results is limited by the existing sequence database. For many of the SSU rRNA phylotypes that we detected (52%), we were able to classify the sequence to the family level; however, some of our phylotypes clustered apart from any previously cultured isolates, limiting further classification. For example, three of our phylotypes formed a distinct clade within the phylum Planctomycetes, separate from the single, currently recognized class (Planctomycetacia), order (Planctomycetales), and family (Planctomycetaceae) (28). Therefore, we are limited in our knowledge of these three phylotypes (11% of the total SSU rRNA clones) until an isolate more closely related is cultured and characterized. The results suggest that certain bacterial lineages localize to specific permeable sediment environments in the NEGOM. Higher species richness was observed in the more shallow, organic-rich sediments sampled at NEGOM sites in comparison to SAB. In addition, the Bay site showed a slightly higher species richness in comparison to the more organic-poor Gulf site. Community fingerprinting by T-RFLP also detected distinct differences in diversity between sites. The Apalachicola Bay site is exposed to more quiescent hydrodynamic conditions, the sediment contains a higher organic matter content, and oxygen is consumed closer to the sediment surface in comparison to the Gulf site. Microbial groups that tolerate frequent oxygen inputs and are adapted for lower carbon concentrations would localize and survive better on the Gulf side, compared to the more stratified, higher carbon adapted communities on the Bay side. Thus, differences in diversity are to be expected and their relationship to these environmental gradients will
84 be explored as more geochemical information becomes available from the sites. The phylogenetic composition of microbial communities will be further diagnosed from T- RFLP profiles through continued in silico modeling of cloned DNA sequences. SSU rRNA has already been extracted and cloned from NEGOM sediments by our group. Through parallel analysis of rRNA and DNA targets, the “metabolically active” community members will also be elucidated.
85 CONCLUSIONS
Permeable sediments cover vast areas of the shallow continental shelf where a large fraction of primary production and organic matter cycling occurs in the oceans. Though permeable sandy sediments have a low porosity and organic matter content relative to marine muds, geochemical studies have shown that these environments are very active in the remineralization of carbon and nutrients. Despite their potential significance, microbial communities in permeable marine sediments remain poorly characterized. Therefore, the overall goal of this study was to provide a comprehensive investigation of the diversity and phylogenetic composition of microbial communities in marine sands of the continental shelf. Utilizing cloning/ sequencing and community fingerprinting approaches with a number of key gene targets, microbial diversity was examined extensively across gradients in sediment characteristics and geochemical parameters at two representative locations in the southeastern United States. Clonal analysis of the SSU rRNA gene revealed high diversity among the sediment-associated microorganisms of both the South Atlantic Bight (SAB) and northeastern Gulf of Mexico (NEGOM). The robust sequence database of this study expanded current knowledge to show the contribution of phyla (Actinobacteria, Cyanobacteria, Acidobacteria, Bacteroidetes/Chlorobi, Chloroflexi, and Firmicutes) that had not been previously recognized in marine sands using cultivation-independent methods with inherently lower resolution. In corroboration with previous studies, the majority of phylotypes retrieved from permeable marine sediments were most closely related to the phylum Planctomycetes and three subclasses within the phylum Proteobacteria (i.e., α-, δ-, and γ-Proteobacteria). The α-Proteobacteria, in particular, were shown to be a relatively abundant group in the overall and denitrifying community clone libraries at both SAB and NEGOM sites. No β-Proteobacteria-related phylotypes were detected using SSU rRNA gene analysis. However, since this group is known to be critical to marine ecosystems, it is believed that this class was below our detection limit, rather than being absent. Analysis of the amoA gene showed a low diversity in 86 comparison with previous studies of marine muds, with only three different phylotypes detected in the SAB sediments and only two phylotypes detected in the NEGOM sediments. The only different phylum detected between the sites of this study was Gemmatimonadetes, which composed 4% of the total NEGOM clones. Analysis of the nosZ gene showed a high diversity among the denitrifying microbial community that rivaled that of the overall community (as indicated by the SSU rRNA gene analysis) in the SAB and NEGOM sediments. Both sites contained a large number of nosZ gene phylotypes that were most closely related to α-Proteobacteria. Phylogenetic diversity was shown to be relatively constant and consistent with geochemical determinations in column experiments designed to mimic in situ carbon and nitrogen flow. In parallel with rates of organic matter degradation and coupled nitrification-denitrification, microbial community diversity remained relatively constant between column experiments and across geochemical gradients within columns. Abundant phylotypes of all gene targets remained relatively the same across large gradients in oxygen content and nitrogen species, with the exception of an increase in δ- Proteobacteria sequences affiliated with S-transforming microorganisms. High throughput techniques were developed and applied to extensively profile overall and denitrifying microbial communities in a large number of sediment samples across environmental gradients at the NEGOM site. Cloning/sequencing and community fingerprinting (T-RFLP) approaches were applied in parallel to characterize microbial diversity and phylogenetic composition. No distinct differences were observed in community fingerprint analysis between triplicate cores taken at a single site. Therefore, determination of diversity was based upon combined DNA extracts from triplicate cores taken at each site. Whereas no significant differences were observed between sediment samples using clonal analysis, T-RFLP profiles showed distinct trends in diversity according to site, depth, and time period sampled. Differences in diversity were particularly apparent between sites in the NEGOM study. The Apalachicola Bay site is exposed to more quiescent hydrodynamic conditions, the sediment contains a higher organic matter content, and oxygen is consumed closer to the sediment surface in comparison to the Gulf site. Thus, differences in diversity are to be expected and their
87 relationship to these environmental gradients will be explored as more geochemical information becomes available from the sites. The results of this study provide further evidence that hydrodynamic conditions intimately affect the structure and function of microbial communities. Permeable sands undergo rapid pore water exchange resulting in physically unstable environments that tend to diminish geochemical gradients, which are thought to stratify microbial communities. In the SAB sediments, all four of the samples from redox-stratified columns contained a higher level of detectable diversity of microorganisms than did the in situ sediment sample, as determined by both SSU rRNA and nosZ gene analysis. It is proposed that redox stabilization allows for stratification in the microbial community and the creation of new niches, allowing an increased number of phylotypes to thrive. Conversely, in the natural permeable shelf environment, the sediments are constantly being disturbed and mixed, perhaps allowing only fast growing and adapting microorganisms to be detected at the DNA level using clonal analysis. Organic matter input is also likely to influence structure-function relationships. Higher species richness was observed at the NEGOM sites, which have more shallow water depths and more organic-rich sediments, in comparison to the SAB site. In addition, the Bay site showed a slightly higher species richness in comparison to the more organic-poor Gulf site. Employing our method of T-RFLP community fingerprinting analysis allows a higher resolution comparison that detects changes in phylogenetic composition along gradients caused by hydrodynamics. The high throughput methods developed here revealed substantial changes in the diversity of microbial communities across relevant environmental gradients in permeable sands, whereas clonal analysis alone did not resolve such changes. Rapid fingerprinting methods along with an improved sequence database from this thesis should greatly facilitate the quantification of microbial groups that are active in carbon and nutrient cycles in permeable shelf environments. Since the majority of sequences retrieved from permeable sediments were affiliated with clone sequences found in other marine environments and were not closely related to the sequences of any cultivated organisms, further molecular analysis should be accompanied by cultivation of key groups so that structure-function relationships may be confirmed.
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100 BIOGRAPHICAL SKETCH
Evan M. Hunter was born on September 6th, 1980 in Cleveland, Ohio. After graduating from Mentor High School in 1998, he enrolled at the University of Cincinnati where he majored in Biology. He completed his Bachelor’s of Science degree in 2002 and continued to work as a laboratory technician alongside Dr. Kenji Fukasawa during the following year. In the fall of 2003, Evan enrolled in the graduate program at Florida State University and began studying biological oceanography. In the spring of 2006, he graduated with a Master’s of Science degree. He hopes to work in the field of environmental consulting and permitting so that he can apply his knowledge of Florida’s coastal ecosystems to help conserve these critical environments.
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