CHARACTERIZING MARINE SUBSURFACE FUNGI from OLIGOTROPHIC SOUTH PACIFIC GYRE SEDIMENTS a Thesis by MORGAN STARR SOBOL BS, Texas A

CHARACTERIZING MARINE SUBSURFACE FUNGI FROM OLIGOTROPHIC SOUTH PACIFIC GYRE SEDIMENTS

A Thesis

MORGAN STARR SOBOL

BS, Texas A&M University-Corpus Christi, 2016

Submitted in Partial Fulfillment of the Requirements for the Degree of

MASTER OF SCIENCE

MARINE BIOLOGY

Texas A&M University-Corpus Christi Corpus Christi, Texas

August 2018

CHARACTERIZING MARINE SUBSURFACE FUNGI FROM OLIGOTROPHIC SOUTH PACIFIC GYRE SEDIMENTS

A Thesis

MORGAN STARR SOBOL

This thesis meets the standards for scope and quality of Texas A&M University-Corpus Christi and is hereby approved.

Brandi Kiel Reese, PhD Jeffrey W. Turner, PhD Chair Committee Member

Xavier Fonz Gonzales, PhD Committee Member

August 2018

ABSTRACT

Fungal communities from the deep marine subsurface may be important in global biogeochemical cycles through remineralization of sedimentary organic matter, but this has not yet been thoroughly observed. This study analyzes the fungal role in subsurface biogeochemical cycles and understands how these organisms have adapted to extreme environments, such as the nutrient and organic matter depleted sediments of the South Pacific Gyre. Sediment cores were collected during the Integrated Ocean Drilling Program Expedition 329 to the South Pacific Gyre on board the D/V JOIDES Resolution in the Fall of 2010. Two fungal isolates were cultured from 70 million year old sediments. Previous analysis found that the two isolates were closely related to Penicillium species. To fully characterize the isolates and test their physiological boundaries, we grew them at different temperatures, salinities and pH. Whole genomic analysis was used to understand the fungi’s physiology and metabolism on a molecular level. The fungi were found to prefer growth at mesophilic temperatures and low NaCl concentrations. Growth occurred between pH 3 and pH 8. The isolate from 12 mbsf grew optimally from pH 3 to pH 8 and the isolate from 124 mbsf grew optimally from pH 3 to pH 6. Fermentation of lactose and sucrose was confirmed, but not nitrate and sulfate reduction. The fungal isolates from the South

Pacific Gyre sediment had physiological capabilities that were consistent with the in situ subsurface conditions and contained genes that were capable of utilizing the recalcitrant carbon sources found in situ. The results from this study expand on the fungal limits of life and highlight their important role global carbon cycle.

DEDICATION

I would like to dedicate this work to everyone who has encouraged and supported my one dream to become a marine biologist.

ACKNOWLEDGEMENTS

First, I would like to thank to my advisor, Dr. Brandi Kiel Reese, for her immense support and guidance during my three years as her student. She introduced me to the small, close knit community of marine subsurface scientists and helped fueled my love for studying life in extreme environments. I am also grateful for the opportunities she has provided me with and for the future collaborations that will forever support my career as a scientist.

To Dr. Jeffrey Turner, Dr. Xavier Gonzales, Dr. Blair Sterba-Boatwright, and other Texas

A&M University – Corpus Christi professors, thank you for your support, mentorship, and kind use of equipment and supplies.

Many thanks to my lab mates in both the Reese and Turner labs for assisting me with my research both in the lab and on the command line, for constantly reminding me of things I had forgotten, but most importantly, for your friendship.

Thank you to Dr. Fumio Inagaki and Tatsuhiko Hoshino for providing the DNA extraction method and sequencing for the fungal genomes and to Dr. Martha Ariza and Dr. Heath

Mills for the early analyses of the fungal isolates. Also, thank you to the science party and crew of IODP Expedition 329 for sample collection and geochemical analysis.

I would like to thank the College of Science and Engineering for the graduate student scholarship which supported my first year of graduate school and the Ruth A. Campbell

Endowed scholarship for supporting my second year. I also appreciate the travel awards from the

Parent’s Council and the Marine Biology Program at Texas A&M University – Corpus Christi.

To my funding sources, the National Science Foundation, the NASA Astrobiology

Institute, the Center for Dark Energy Biosphere Investigations, and the Consortium of Ocean

Leadership, thank you very much for your support.

vii

Lastly, I would like to give special thanks to closest family and friends. Thank you, mom and dad for originally inspiring my love for the ocean and never letting me forget my true passion. I want to thank my sisters, other family, and friends for their unconditional love and support. Finally, I am greatly appreciative of Taylor for his continued understanding and moral support during this journey.

Without you all, reaching my goal of becoming a marine biologist would not have been possible. Thank you!

viii

TABLE OF CONTENTS

CONTENTS PAGE

ABSTRACT ...... v

DEDICATION ...... vi

ACKNOWLEDGEMENTS ...... vii

TABLE OF CONTENTS ...... ix

LIST OF FIGURES ...... xiii

LIST OF TABLES ...... xiv

INTRODUCTION ...... xv

Discovery of Fungi in Marine Subsurface ...... xvi

Energy Limitation ...... xvi

Role of Fungi in Carbon Cycle ...... xviii

Ecological Importance ...... xxiii

Summary ...... xxiv

CHAPTER I: ECOPHYSIOLOGY OF SOUTH PACIFIC GYRE FUNGI ...... 1

Abstract ...... 1

Introduction ...... 2

Materials and Methods ...... 3

Results ...... 9

Discussion ...... 18

Summary ...... 26

CHAPTER II: MOLECULAR CHARACTERIZATION OF FUNGI IN THE OLIGOTROPHIC

MARINE SUBSURFACE ...... 27

Abstract ...... 27

Introduction ...... 28

Materials and Methods ...... 30

Results ...... 34

Discussion ...... 43

Summary ...... 50

REFERENCES ...... 51

LIST OF APPENDICES ...... 68

Table A.1. NCBI accession numbers used...... 68

Table A.2. SPG-F1 media control pH and weights for 4ºC...... 70

Table A.3. SPG-F1 culture pH and weights for 4ºC...... 71

Table A.4. SPG-F15 media control pH and weights 4ºC...... 72

Table A.5. SPG-F15 culture pH and weights for 4ºC...... 73

Table A.6. Media control pH and weights for 10ºC...... 74

Table A.7. SPG-F1 culture pH and weights for 10ºC. Asterisks in the Final Weight column are

values that were negative and changed to zero...... 75

Table A.8. SPG-F15 culture pH and weights for 10ºC. Asterisks in the Final Weight column

are values that were negative and changed to zero...... 76

Table A.9. Media control pH and weights for 15ºC...... 77

Table A.10. SPG-F1 culture pH and weights for 15ºC...... 78

Table A.11. SPG-F15 culture pH and weights for 15ºC. Asterisks in the Final Weight column

are values that were negative and changed to zero...... 79

Table A.12. Media control pH and weights for 21ºC...... 80

Table A.13. SPG-F1 culture pH and weights for 21ºC...... 81

Table A.14. SPG-F15 culture pH and weights for 21ºC...... 82

Table A.15. Media control pH and weights for 26ºC...... 83

Table A.16. SPG-F1 culture pH and weights for 26ºC...... 84

Table A.17. SPG-F15 culture pH and weights for 26ºC...... 86

Table A.18. Media control pH and weights for 1% NaCl...... 88

Table A.19. SPG-F1 culture pH and weights for 1% NaCl...... 89

Table A.20. SPG-F15 culture pH and weights for 1% NaCl...... 91

Table A.21. Media control pH and weights for 2% NaCl...... 93

Table A.22. SPG-F1 culture pH and weights for 2% NaCl...... 94

Table A.23. SPG-F15 culture pH and weights for 2% NaCl...... 96

Table A.24. Media control pH and weights for 6% NaCl...... 98

Table A.25. SPG-F1 culture pH and weights for 6% NaCl...... 99

Table A.26. SPG-F15 culture pH and weights for 6% NaCl...... 101

Table A.27. Media control pH and weights for 8% NaCl...... 103

Table A.28. SPG-F1 culture pH and weights for 8% NaCl...... 104

Table A.29. SPG-F15 culture pH and weights for 8% NaCl...... 106

Table A.30. Media control pH and weights for pH 3...... 108

Table A.31. SPG-F1 culture pH and weights for pH 3...... 109

Table A.32. SPG-F15 culture pH and weights for pH 3...... 110

Table A.33. Media control pH and weights for pH 6...... 111

Table A.34. SPG-F1 culture pH and weights for pH 6...... 112

Table A.35. SPG-F15 culture pH and weights for pH 6...... 113

Table A.36. Media control pH and weights for pH 8...... 114

Table A.37. SPG-F1 culture pH and weights for pH 8...... 115

Table A.38. SPG-F15 culture pH and weights for pH 8...... 117

Table A.39. SPG-F1 and SPG F15 growth rates. Student’s T-test was used to compare SPG-F1

growth rates to SPG-F15 growth rates. The significance level was set to 0.050...... 119

Table A.39. The Student’s T-test p-values from a comparison of SPG-F1 and SPG-F15

individual growth rates at different conditions. The significance level was set to 0.050...... 120

Figure A.1. The percentage of CAZy families in the genome of SPG-F1...... 121

Figure A.2. The percentage of CAZy families in the genome of SPG-F15...... 122

xii

LIST OF FIGURES

FIGURES PAGE

Figure 1.1: Location of Holes U1371 and U1368 (highlighted in yellow). Whole round cores were taken from these sites during IODP Expedition 329 to the South Pacific Gyre from October

– December 2011 (Scientists, 2011). 11

Figure 1.2: Phylogenetic tree of 18S rRNA gene sequences from SPG fungi. The IDs for the isolates used in this study, SPG-F1 and SPG-F15, are in red. 12

Figure 1.3: Effect of temperature on SPG-F1 and SPG-F15 growth. 14

Figure 1.4: Effect of NaCl concentration on SPG-F1 and SPG-F15 growth. 16

Figure 1.5: Effect of pH on SPG-F1 and SPG-F15 growth. 18

Figure 2.1: Location of Holes U1371 and U1368 (highlighted in yellow). Whole round cores were taken from these sites during IODP Expedition 329 to the South Pacific Gyre from

October-December 2011 (Scientists, 2011). 36

Figure 2.2: Gene Ontology (GO) functional annotation of genes in SPG-F1 (Column A) and

SPG-F15 (Column B) biological, molecular and cellular processes. 41

xiii

LIST OF TABLES

TABLES PAGE

Table 1.1: Summarized table of the ecophysiology of SPG-F1 and SPG-F15. 13

Table 2.1: Assembly and Annotation Statistics. 38

Table 2.2: Repetitive elements found within SPG-F1 and SPG-F15. 39

Table 2.3: Comparative abundance of CAZy enzymes in their respective classes.

CBM=carbohydrate binding molecules. CE=carbohydrate esterases. GH=glycoside hydrolases.

GT=glycosyl transferase. PL=polysaccharide lyases. AA=auxiliary activities. 42

xiv

INTRODUCTION

The marine subsurface harbors a diverse community of microorganisms from all three domains of life. The metabolic activities of Bacteria and Archaea have been known to drive biogeochemical cycles within deep subsurface sediments, which ultimately impacts the fluxes of nutrient cycles globally (Jørgensen, 1982, Whitman et al., 1998, D'Hondt, 2003, Biddle et al.,

2008, Parkes et al., 2014). However, Eukaryotes have only recently been discovered in the deep subsurface biosphere in the past few decades (Damare et al., 2006, Edgcomb et al., 2011, Orsi et al., 2013, Rédou et al., 2015, Liu et al., 2017), and many questions remain unanswered about their abundance, diversity, and role in nutrient cycling. An estimate of Earth’s total biomass revealed that marine subsurface prokaryotes amount to approximately 10 gigaton of biomass in the form of carbon (~1.8% of the total) (Bar-On et al., 2018); however, this did not account for fungi and therefore the marine subsurface biosphere may be underestimated.

The oligotrophic marine subsurface contains greater concentrations of recalcitrant carbon due to the long-term burial and diagenesis of organic carbon over time (D'Hondt et al., 2009, Oni et al., 2015). However, it is unclear to what extent microbial communities in the deep biosphere remain active with very little organic carbon available. It has been hypothesized that marine subsurface fungi may provide nutrients to the surrounding microbial community through their necromass, or by transforming recalcitrant carbon into labile forms through respiration processes

(Edgcomb et al., 2011, Orsi et al., 2013). In order to answer these questions about the eukaryotic populations within deeply buried marine sediments, it is important to determine how they are actively involved in biogeochemical cycling. Cultured fungal representatives and molecular data

from these environments allow scientists to understand what roles fungi have in the marine subsurface biogeochemical cycles and to make inferences about their adaptation in nutrient limited environments. Here we examine the recent discoveries of fungi in marine subsurface sediments and their characteristics are examined with emphasis on what has yet to have been discovered.

Discovery of Fungi in Marine Subsurface

Fungi were first discovered in the top first meter of sediments in the Mariana Trench 20 years ago (Takami et al., 1997, Takami, 1999). In recent years, sequences related to eukaryotic fungi were found in deeper marine sediments of the Peru Margin, Canterbury Basin and off the

Shimokita Peninsula (Edgcomb et al., 2011, Rédou et al., 2015, Liu et al., 2017). Evidence that fungi are active in the marine subsurface has been shown with the detection of RNA transcripts

(Edgcomb et al., 2011, Orsi et al., 2013, Orsi et al., 2013, Pachiadaki et al., 2016) and visualization of branching fungal hyphae in sediments (Raghukumar et al., 2004, Damare et al.,

2006, Pachiadaki et al., 2016). There is a general consensus that fungi dominate the eukaryotic community of the deep biosphere and that the most abundant phyla are the Basidiomycota and

Ascomycota (Edgcomb et al., 2011, Rédou et al., 2015). Even though scientists have evidence that fungi are living in subseafloor sediments, it is still uncertain what their metabolic capabilities and restraints are.

Energy Limitation

Most of our knowledge of microbial growth and metabolism stems from organisms studied in environments with high productivity. In productive systems, microbes have fast growth rates and greater biomass as determined by cell abundance (Mason, 1935, Makarieva et

xvi

al., 2008, Hoehler & Jørgensen, 2013). Ocean margins (i.e., transitional regions between continents and the ocean) are known to have greater water column productivity because of increased nutrient input from coastal runoff. The sedimentary cell counts are generally several orders greater than less productive systems such as the North and South Pacific Gyres

(Kallmeyer et al., 2012). The Pacific gyres are described as oligotrophic, meaning they receive low concentrations of nutrients. The downwelling nature of the gyres and their long distance from continents mainly affects the amount of nutrients in the gyre’s water. Oligotrophic systems experience less productivity, which means that there will be less burial of organic nutrients in the sediment (Jahnke, 1996).

Microbial growth in the deep subsurface is limited by the availability of usable energy sources (Hoehler & Jørgensen, 2013). Knowing that organic nutrients and electron donors are limited in subsurface sediments, it is no surprise that prokaryotic growth is limited, and that cell size is smaller in this environment (Kallmeyer et al., 2012, Morono et al., 2013). Smaller cell size and limited organic nutrients leads to slower turnover rates for microbial generations. For example, turnover rates in the marine subsurface have been estimated to be on the order of 100 to

1,000 years (Hoehler & Jørgensen, 2013). Prokaryotic turnover rates in the marine subsurface are significantly slower than the estimated 6-25 days for microbes in the photic zone of oceans

(Whitman et al., 1998). Current turnover rate estimates do not consider generation times for

Eukaryotes.

Many filamentous fungi produce conidia (spores) in order to survive in harsh environmental conditions, such as low nutrients (Hagiwara et al., 2017). The spores are well equipped to survive in stressful environments because of a spore coat that encases the spore. A spore coat is electron dense (Tsukahara et al., 1966) and contains polymers like hydrophobin and

xvii

melanin and sugars such as mannitol and trehalose to help the spore survive for long periods of dormancy (Tsukahara et al., 1966, Hagiwara et al., 2017). Inside the spore, you will find important organelles such as the nucleus, mitochondria and endoplasmic reticulum (Tsukahara et al., 1966). Dormant, or metabolically inactive spores, will begin to grow hyphae and reproduce when conditions are good for growth. While some fungi simply tolerate extreme environments as vegetative spores, studies have shown that other fungal species can adapt rather quickly, and actively reproduce while living in harsh conditions as well (Selbmann et al., 2013). Consistent with this, active Ascomycota and Basidiomycota phyla were detected using 18S ribosomal RNA

(rRNA) from the marine subsurface of the Peru Margin, Hydrate Ridge, Eastern Equatorial

Pacific, North Pond, and Benguela Upwelling System (Orsi et al., 2013). Even with this information, whether fungi are mainly existing as dormant spores or actively reproducing in sediments is uncertain.

Role of Fungi in Carbon Cycle

Labile carbon is organic carbon that is easily broken down and used as nutrients, while the opposite exists for recalcitrant carbon. Recalcitrant carbon is made of numerous chemical bonds, which makes it harder to biodegrade. Microbes in marine sediments are more likely to consume labile carbon forms over recalcitrant carbon, which favors the buildup of recalcitrant carbon forms in these sediments (Cowie & Hedges, 1994, Wakeham et al., 1997, Oni et al.,

2015). Many fungi have ability to degrade and remineralize recalcitrant carbon such as carbonate, lignin, cellulose, and polycyclic aromatic hydrocarbons (PAH) which makes them important members of the carbon cycle (Verrecchia, 2000, Da Silva et al., 2003, Gubernatorova

& Dolgonosov, 2010). To degrade complex carbon compounds, fungi encode non-specific lignin

xviii

degradation and polycyclic aromatic hydrocarbon (PAH) degradation genes (lip, mnp, and lcs)

(Peng et al., 2008). Fungi isolated from marine environments, such as coral reefs and estuarine sediments off the coast of Brazil, were capable of degrading PAHs under laboratory conditions where various hydrocarbons were introduced into pure cultures (Da Silva et al., Passarini et al.,

2011). In both terrestrial soils and marine sediments, fungi have also been observed utilizing recalcitrant carbonate as needed for hyphal growth (Verrecchia, 2000). These studies used culture-dependent and in situ observations to study the remineralization of recalcitrant carbon.

However, to my knowledge, no study has used whole genomic methods alongside culture dependent PAH degradation assays to determine if fungi specifically isolated from subsurface sediments have the potential to breakdown PAH as a carbon nutrient source.

Total organic carbon (TOC) burial in the South Pacific Gyre is extremely low (i.e., 4.4 x

-10 -9 2 -1 10 to 8.2 x 10 mol C cm yr ) compared to other marine subsurface sites (D'Hondt et al.,

2009). Slow TOC burial rates have also led to a greater concentration of carbonates and other recalcitrant carbon forms to be stored below the sediment (D'Hondt et al., 2009). It is implied that fungi are utilizing organic carbon sources, and contributing to carbon storage or usage in marine sediments (Orsi et al., 2013). Sequences related to fungal species in the Ascomycota and

Basidiomycota phylum (80-97% similarity) from the Benguela Upwelling System, Hydrate

Ridge, and Peru Margin were greater in sediments with greater total organic carbon (TOC) concentrations (Orsi et al., 2013). Studies have also hypothesized that recalcitrant carbon is remineralized by fungi in the marine deep subsurface (Burgaud et al., 2009, Edgcomb et al.,

2011, Orsi et al., 2013). This remineralized carbon can be used as a primary carbon source for fungi and their prokaryotic neighbors, but more research is needed to better constrain this possibility.

xix

Fungal Ecophysiological Adaptations

Bacteria and Archaea have long been known to dominate extreme environments because the isolation of eukaryotic microorganisms had not been successful previously. Within the last twenty years, advancements in sequencing and culturing have made it possible to isolate fungi in many extreme environments. Fungi have been found in hypersaline, low and high temperature, low oxygen and low and high pH environments (Zajc, 2014; Gunde-Cimerman, 2009;

Maheshwari, 2000; Gunde-Cimerman, 2003; Hillman, 2015; Das, 2009; Oliveira, 2005). The production of spores is one way to exist in unfavorable conditions, but fungi have other adaptive mechanisms to thrive in a variety of environmental conditions. The study of such adaptations to an organism’s surrounding environment is called ecophysiology. The following paragraphs will outline fungi’s ecophysiological adaptations to withstand a variety of temperature, salinities, pH, and oxygen concentrations.

Temperature has the most profound effect on cell stability and function, thus organisms usually only grow within a moderate temperature range (de Oliveira et al., 2015). Majority of fungi are mesophilic which means they can only grow from the moderate temperatures of 15ºC to 45ºC, but there are some species that thrive in temperatures less than 15ºC, called psychrophiles, or greater than 50ºC, called thermophiles. Thermophiles and psychrophiles have several adaptations that allow them to grow and persist in extreme temperatures. The main difference between the two thermal classifications is the amount of unsaturated fatty acids. There is a correlation between the amount of unsaturated fatty acids and the temperature threshold of which fungi grow (Arthur & Watson, 1976, Maheshwari et al., 2000). In high temperatures, there is an increase in saturated fatty acids and a decrease in unsaturated; whereas, in colder temperatures, the opposite is observed (Arthur & Watson, 1976, Maheshwari et al., 2000).

Changes in fatty acid content maintain a constant membrane fluidity so that enzymes and transporters within the membrane can still function properly (Maheshwari et al., 2000). Some thermophilic fungi, like Talaromyces thermophilus, are only capable of growing in high temperatures because of a nonfunctional fatty acid desaturase which did not allow the fungi to convert to more unsaturated fatty acids (Wright et al., 1983). Other themophilic fungi have a wider range of growth and thus can alter their composition of fatty acids (Rajasekaran &

Maheshwari, 1993, Oberson et al., 1999). Other adaptations to combat thermal stress have been observed in psychrophilic fungi and some thermophiles. When introduced to cold temperatures, many fungi will produce cyroprotectant carbohydrates such as trehalose and mannitol in order to resist freezing (Hassan et al., 2016). This adaptive mechanism is also seen inside the spore coat surrounding fungal spores where the carbohydrates are playing a protective role as well

(Tsukahara et al., 1966, Hagiwara et al., 2017). Many prokaryotes and Eukaryotes also produce antifreeze proteins, which attach to ice crystals and minimize their growth. This is important because as water freezes, ice crystals are produced which are known to break apart cell walls and membranes. These proteins have been observed in both the Basidiomycetes and Ascomycota from regions such as the Antarctic (Hassan et al., 2016). The diversity of fungal adaptations to thermal stress is the reason why fungi are one of the only Eukaryotes to live in such extreme temperatures.

Fungi can be found growing in a large variety of environments where there are virtually no salts present, or in hypersaline environments such as salterns (Zajc et al., 2012). Most of these fungi can be classified as facultative halophiles, but in few examples, some fungi are obligate halophiles, requiring high concentrations of salt for growth. Interestingly, it was found that many fungi are actually halotolerant, meaning they can adapt and grow in a range of salinities, ranging

xxi

from 0% salinity to saturated conditions (Larsen, 1986). Adaptations enabling fungi to grow in a variety of salinities involve making changes due to senses of osmotic and ionic stress to the cell walls and interiors. If a fungus cannot adapt to high osmotic or ionic stress, typically the cells will shrink and/or become damaged because of the intense switch in internal and external solute concentrations (Petelenz-Kurdziel et al., 2011). Other fungi, employ many different mechanisms to control drastic changes in osmotic pressure which will be detailed in the following paragraphs.

The high osmolarity glycerol (HOG) signaling pathway is a highly conserved pathway that has been heavily studied in Saccharomyces cerevisiae (Schüller et al., 1994). This pathway controls responses to high extracellular stress in the cytoplasmic membrane (Schüller et al.,

1994, Saito & Posas, 2012). Simply put, the HOG pathway uses membrane bound osmosensors to sense increases in external osmolarity, which then triggers the production of glycerol to restore the internal osmotic pressure to normal conditions (Plemenitaš et al., 2014). This adaptation has also been observed in the extremely halotolerant fungi Hortaea werneckii

(Plemenitaš et al., 2014), the halophilic fungi Wallemia ichthyophaga (Plemenitaš et al., 2014), and common filamentous fungi Aspergillus (Krantz et al., 2006, Stoll et al., 2013), and

Penicillium (Stoll et al., 2013). There are also passive adaptations that fungi play employ to increase their resistance to stress caused by increased salinity. These include changes in morphology such as growing in multicellular clumps and thickening their cell walls by secreting extracellular polysaccharides and by melanization (Kogej et al., 2006, Kunčič et al., 2010). A mixture of these morphological and genetic adaptations is what makes fungi one of the most adaptable organisms.

Similar to temperature and salinity, many fungal species are considered pH tolerant, meaning they can grow over a range of acidic to alkaline pH. To successfully live in an

xxii

environment, fungi need to be adaptable to changes in pH. Microbial community composition seems to be greatly influenced by pH in terrestrial systems. For example, it has been shown that along pH gradients in soil, bacterial and fungal communities have different responses. As pH increased, so did Bacteria, but as pH decreased, fungal abundance increased (Rousk et al., 2009).

In environments where Bacteria and fungi compete, fungi are able to thrive and select diverse niches for growth because of their adaptive mechanisms.

Most adaptive mechanisms used for tolerating pH changes has been observed in human pathogenic fungi, but many of these mechanisms are highly conserved across species. An example of this is the widely distributed Rim101 pathway. Rim101, which is a zinc-finger protein transcription factor, responds to changing pH conditions by altering the form of the protein (Peñalva et al., 2008, Maeda, 2012). The different forms of Rim101 regulate gene expression responsible for altering membrane bound ion pumps. These ion pumps regulate the intake or output of ions into the cell to control internal pH levels (Lamb et al., 2000). The

Rim101 pathway is a homolog of the PacC pathway that functions in a similar way (Lamb et al.,

2000). These pathways have been studied specifically in S. cerevisiae (Peñalva et al., 2008), A. nidulans (Peñalva et al., 2008), C. albicans (Du & Huang, 2016), and P. chrysogenum (Suárez &

Peñalva, 1996).

Ecological Importance

Approximately less than 5% of fungal diversity has been described and examined in culture (Richards et al., 2012). Within this 5%, most species come from terrestrial systems and shallow coastal systems (Richards et al., 2012). Studies have shown that in these ecosystems fungi are saprotrophic, meaning they are capable of decomposing woody plant material, mutually symbiotic with plants and microbes, and act as parasites in other organisms (Kendrick, 2001,

xxiii

Richards et al., 2012). The ecological role of fungi in terrestrial systems is better understood than that of fungi in subsurface sediments, therefore it is important that these fungal communities be further evaluated to determine if their role in deep marine sediments is similar or different from terrestrial fungi.

Sequences of Eukaryotes from the marine subsurface show the occurrence of potential novel isolates as well as sequences with close similarity to terrestrial originated species within the Ascomycota and Basidiomycota phyla, therefore it has been hypothesized that fungi are of terrestrial origin, and evolved in the subsurface (Spatafora et al., 1998, Edgcomb et al., 2011,

Rédou et al., 2015). Based on the terrestrial to marine transition hypothesis, it is also hypothesized that fungi in deep marine sediments have ecological roles similar to their terrestrial ancestors, most importantly, degradation, and remineralization of recalcitrant carbon forms in organic nutrient limiting sediments (Edgcomb et al., 2011, Richards et al., 2012, Orsi et al.,

2013). It was found that sequences matching common terrestrial fungal species made up a community of shallow marine sedimentary fungi, but the marine sediment community was adjusted and able to grow at low ocean temperatures (4°C) and higher salinities (Mouton et al.,

2012). More evidence from subsurface fungal isolates is needed to determine if they originated in the ocean or were deposited into ocean sediments from land.

Summary

In conclusion, fungi are most likely to be ecologically important in deep marine sediments, where they were, until recently, not thought to exist. Microbial communities in marine sediments survive off low organic carbon for nutrients, but fungi may be capable of transforming recalcitrant carbon into labile forms for other organisms and their selves to consume. Culture dependent and culture independent methods are important for understanding

xxiv

the physiological conditions these fungi survive in, and what mechanisms they use to do so. It is also important to understand what they are capable of metabolically, and how they contribute to local and global biogeochemical cycles. There is still very little research combining the two methodologies to study marine subsurface fungi, but growing resources and awareness will make it possible to fully characterize these fungi while also pushing the boundaries of eukaryotic life.

xxv

CHAPTER I: ECOPHYSIOLOGY OF SOUTH PACIFIC GYRE FUNGI

Abstract

Active fungal communities have recently been confirmed living in the marine subsurface, yet there still remains a lack of knowledge when understanding the physiology of fungi in these sediments. On land and in other marine environments, fungi are capable of adapting to changes in their surroundings that would otherwise inhibit their growth. Fungi are also known for their ability to metabolize recalcitrant carbon that was previously thought to be biologically unavailable. Therefore, active fungal communities may be important in the marine subsurface by potentially supplying the surrounding prokaryotic population with an organic carbon source. Here, we cultivated fungi from subsurface sediment collected within the South

Pacific Gyre through the Integrated Ocean Drilling Program (IODP) Expedition 329. The South

Pacific Gyre is one of the most energy-limited systems on Earth where total organic carbon

(TOC) concentrations are below 0.02% on average in the sediment. Fungi were isolated from sediment that was collected from 12 meters below the seafloor (mbsf) and 124 mbsf, which was deposited approximately 11 and 70 million years before present (mybp), respectively. The fungal isolates were identified as Penicillium, which was determined through sequencing the 18S rRNA gene. To fully characterize the physiological boundaries, we grew them over a range of temperatures, salinities, and pH. Optimum growth was determined by comparing the time it took the isolates to germinate. The isolates grew optimally at 21ºC and at 1% - 2% NaCl, which was similar to the in situ conditions. We observed optimal growth between pH 3 and pH 8 for the isolate from 12 mbsf. The deeper isolate grew optimally from pH 3 to pH 6. Neither isolate could

grow above 30ºC, which is uncharacteristic of continental Penicillium. The isolates were capable of fermentation, but not dissimilatory nitrate and sulfate reduction. Overall, both fungal isolates had potential ecophysiological adaptations for survival in South Pacific Gyre oligotrophic sediments.

Introduction

Fungi are ubiquitous and can be found in aquatic, marine, and continental environments.

In these environments fungi are saprotrophic, meaning they drive nutrient cycles by decomposing organic material (Richards et al., 2012). In marine environments, the diversity and importance of fungi is overlooked, especially in deep sea sediments. Measurements of fungal diversity estimate that less than 1% has been described in marine environments, (Orsi et al.,

2015). In order to expand our knowledge on fungal ecological roles and diversity across the globe, the underexplored portion of fungi living in the deep biosphere needs to be examined.

Fungi were discovered in the top few centimeters of sediments from the Mariana Trench over two decades ago (Takami et al., 1997). Since this time, additional studies have expanded our knowledge of marine subsurface fungi into deeper marine sediments (i.e., ~1 to 2,000 mbsf) such as the Peru Margin (Biddle et al., 2008, Edgcomb et al., 2011, Orsi et al., 2013), Central

Indian Basin (Damare et al., 2006), Canterbury Basin (Rédou et al., 2015), and Eastern

Equatorial Pacific (Orsi et al., 2013). These studies suggest that sedimentary marine fungi are ubiquitous, active, and participating in biogeochemical cycling (Orsi et al., 2013). It is important to understand how fungi are surviving and remaining active under subsurface conditions in order to better understand their ecological roles.

Molecular-based studies have been crucial in closing the gap in knowledge about the potential activity of marine subsurface fungal communities. However, culture-based studies are necessary to further understand the ecophysiology of these fungi, which few studies have accomplished (Singh et al., 2010, Rédou et al., 2015, Liu et al., 2017).

This study presents the first ecophysiological characterization of two fungal isolates from the extremely oligotrophic subsurface sediments of the South Pacific Gyre. The South Pacific

Gyre sediments contain some of the lowest recorded organic carbon concentrations and the slowest microbial activity rates (Scientists, 2011). Sediment was collected via the Integrated

Ocean Drilling Program Expedition 329 to the South Pacific Gyre from two locations and two depths (U1371E at 124 meters below seafloor (mbsf) and U1368D at 12 mbsf). Taxonomy was assigned by 18S rRNA gene sequencing. Active in situ populations were confirmed and quantified through real-time PCR of the 18S rRNA transcripts. The two isolates were determined to be related to Penicillium chrysogenum (isolated from U1371E, referred to as SPG-F1) and

Penicillium brevicompactum (isolated from U1368D, referred to as SPG-F15). We evaluated the ecophysiology of each isolate by analyzing growth optimums at various temperatures, salinities, and pH. The SPG fungal isolates grew optimally at the in situ temperature and salinity of the sediment, suggesting that they are physiologically adapted to South Pacific Gyre energy-limited sediments. The characterization of active fungal populations within energy limited deep subsurface marine sediments will expand the known limits of eukaryotic life.

Materials and Methods

Sample collection and fungal isolation

Sediment was collected during the Integrated Ocean Drilling Program (IODP) Expedition

329 to the South Pacific Gyre using the drilling vessel D/V JOIDES Resolution. A total of six sites (U1365C, U1367D, U1368D, U1369E, U1370F and U1371E) were cored (Figure 1.1).

Potential biological contamination from drilling fluid and seawater intrusion was assessed by the presence of perfluorocarbon microsphere tracers within the interior and exterior of the sediment cores (Scientists, 2011).

Sediment cores were retrieved in 9.5 m sections that were divided into 1.5 m subsections.

These sections were immediately sub sectioned into 10 cm whole round cores and stored at -

80ºC for future molecular analyses. Sediment for enrichments were collected in cut sterile syringes and stored at in situ temperature of 4oC. General enrichments consisted of 30 g of sediment in 125 mL glass septum bottles with 100 mL of marine broth media diluted to 10%

(Difco 2216, BD Diagnostics; Franklin Lakes, New Jersey). Liquid media blanks containing only marine broth and no sediment were prepared to evaluate potential contamination. All bottles were sealed and incubated in the dark at 5ºC for one year while shaking at 150 rpm. After a one- year incubation, 100 µL of the slurries was transferred onto marine broth agar plates, sealed with parafilm, and stored at 5ºC. The enrichments yielded a total of 18 fungal isolates. Growth was maintained by transferring the fungi every 3 months onto plates containing marine broth agar and potato dextrose agar (Difco 254920, BD Diagnostics; Franklin Lakes, New Jersey). During the culture transfers, control plates containing marine broth agar and potato dextrose agar were left open to assess potential laboratory contamination. No fungal growth was found on the control bottles with liquid media and the control plates with the respective media agar.

Molecular analysis

RNA and DNA were simultaneously extracted from frozen (-80ºC) whole round cores and cultured fungi using the method described in Reese et al. (2013). Control extractions using

DNA/RNA-free water in place of template were extracted simultaneously to confirm lack of contamination during extraction method. The 18S rRNA was reverse transcribed for 30 mins at

37ºC using MMLV reverse transcriptase and the universal fungal 18S rRNA primer nu-SSU-

1196 to produce complementary DNA (cDNA). Fungal gene transcripts were quantified from the cDNA on an Applied Biosystems Step-One Plus (Life Technologies, Grand Island, NY, USA) using the Quantitect SYBR Green PCR kit (Qiagen, Foster City, CA) according to manufacturer’s recommended conditions followed by a melt curve for verification of single product amplification. Primers nu-SSU-0817 and nu-SSU-1196 (Borneman & Hartin) were used with the following program: 94ºC for 5 minutes followed by 40 cycles of 94ºC for 30 seconds,

56ºC for 30 seconds, and 72ºC for 30 seconds, with a final extension at 72ºC for 10 mins.

Standards were prepared from amplified 18S rRNA fungal genes purified by gel elution

(Qiaquick Gel Elution; Qiagen, Foster City, CA) and quantified using a Nanodrop ND-1000 spectrophotometer (ThermoFisher, Wilmington, DE). The 18S rRNA fungal standards were diluted over five orders of magnitude and amplified with four replicates at each dilution (r2 =

0.996). Sensitivity was calculated with precision to 101 target molecules per reaction. The standard curve was used to quantify the unknown samples. All controls were performed as customary for qPCR (Orcutt et al., 2013).

An aliquot of the 18S rRNA gene PCR product, produced using the same primers and program as described for qPCR, was gel purified (Qiaquick Gel Elution; Qiagen, Foster City,

CA) and cloned using the TOPO-TA 2.1 Kit (Invitrogen, Life Technologies, Grand Island, NY,

USA). Positive transformants were picked for plasmid miniprep using the PureLink Quick

Plasmid Miniprep Kit (Invitrogen, Life Technologies, Grand Island, NY, USA). Purified minipreps (500 ng) were amplified with T3 and T7 primers (5 pmol mL-1) following the manufacturer’s instructions, and sent to Retrogen sequencing facility (San Diego, CA, USA) for

Sanger sequencing.

Phylogenetic analysis

Sequences of the 18S rRNA gene from all SPG fungal isolates and retrieved sequences from GenBank (Benson et al., 2017) were aligned using Geneious version 8.1.9 (Kearse et al.,

2012). The alignment type used was a global alignment with free end gaps. The alignment was manually trimmed to 326 bp in Geneious. Phylogenetic relationships were determined using the

Jukes-Cantor genetic distance model and the Neighbor-joining tree building method. The support for each node was determined by 1,000 replications of bootstrap analysis.

Spore isolation

We isolated fungal asexual spores using a modified method from previously published protocols (Ho & Ko, 1997, Choi et al., 1999, Zhang et al., 2013). The fungi were inoculated in a sterile environment on 25% potato dextrose agar plates supplemented with streptomycin

(Thermo Fisher; Waltham, MA) to a final concentration of 50 µg mL-1. The plates were incubated for 7 days at 30°C for optimum spore production. Exposing a sterile potato dextrose agar plate nearby during inoculation was used to test for potential airborne contamination. Spores were only collected if the potato dextrose agar control plate contained no visible growth. A 5 mL aliquot of 0.2% sodium dodecyl sulfate was pipetted directly onto the cultures and a sterile

microscope coverslip was used to gently scrape the surface of the fungal colonies to release the spores. We filtered the spore suspensions through sterilized 315 µm filter mesh (General

Oceanics; Miami, FL) to remove larger fungal structures such as hyphae. The filtered spore suspension was centrifuged at 8228 x g for 3 minutes at 23ºC. The supernatant was discarded and the pellet was resuspended by adding 30 mL of sterile 18.2 MΩ ultrapure water (Thermo Fisher;

Waltham, MA). We centrifuged the spores again at 8228 x g for 3 minutes and the pellet was resuspended in 30 mL of sterile water. The spores were counted with a hemocytometer under a standard light microscope (Leica DM750; Leica Microsystems, Heerbrugg, Switzerland) to determine the final concentration.

Ecophysiological characterization

The current study focuses on two of the original 18 isolates, referred to hereafter as SPG-

F1 and SPG-F15. Fungal isolate SPG-F1 was isolated from U1371E-14H2 (45°57.8397′S,

163°11.0365′W) at 124 mbsf and SPG-F15 was isolated from U1368D-2H1 (27°54.9920′S,

123°9.6561′W) at 12 mbsf (Figure 1.1). We measured the growth rates of SPG-F1 and SPG-F15 at various temperatures (4, 10, 15, 21, 26, 30, 37, 45, and 60°C), salinities (1, 2, 4, 6, 8, and

23.4% NaCl) and pH (2, 3, 4, 6, 8, and 10). An aliquot of spores (1 x 104 final concentration) was inoculated in 10 mL of potato dextrose broth that was diluted to 20% of the manufacturer’s recommendation. The media was supplemented with streptomycin at a final concentration of 50

µg mL-1. Salinity was altered by adding NaCl to the potato dextrose broth. A minimum growth period of 10 days and a maximum of 30 days was used for each growth test. We included three biological replicates for each time point and triplicate potato dextrose broth media blanks (i.e., no spores added) for each test to assess contamination.

Growth was determined by measuring the dry weight of the fungal biomass using a modified protocol (Taniwaki et al., 2006). At the predetermined time points, each of the culture bottles were filtered onto pre-dried and pre-weighed GF/F filters (24 mm diameter, 1.1µm porosity). The pre-dried filters were dried at 80°C for 18 hours and upon cooling, the initial weight was recorded to a precision of 0.001 mg. The fungal biomass was gently filtered and dried at 80°C for 18 hours. The final dry weight for each replicate was determined by subtracting the pre-weight from the post-weight. The pH of the media was measured prior to filtration using a SevenCompact pH meter (Mettler Toledo; Hong Kong, China). Due to salt interferences with the salinity tests, the filters were rinsed twice with 5 mL of sterile water prior to filtration.

The ability to reduce nitrate via dissimilatory denitrification was analyzed using the

Greiss Reagent method (Knapp & Clark, 1984). A 1 mL aliquot of culture was inoculated in 25 x

150 mm test tubes that contained 25 mL of nitrate broth (pH 7.2) and Durham tubes were used to test for gas production. The ability to reduce sulfate, and ferment glucose, lactose, and/or sucrose was tested using Triple Sugar Iron (TSI) agar slants (Hajna, 1945).

Data Analysis

Average growth rates, measured as dry weight (milligrams) over time (hours), were determined during the exponential growth phase. Growth rates were calculated as the natural log from the difference in weights during the exponential phase, over time (Equation 1). N0 represents the dry weight of the fungi at the beginning of the exponential phase, Nt represents the dry weight at the end of the exponential phase, Dt represents the change in time, and � rate of change (Andersen, 2005).

ln N −N � = t 0 (Equation 1) ∆t

Student’s T-test were performed using Microsoft Excel® Analysis Tool-Pak to determine significant differences in growth rates using a p-value cutoff of 0.05. We created nonlinear mixed-effect models (nlme) to model the fungal growth trends over time using the nlme function in the nlme library in R (Version 1.1.383) (Pinheiro et al., 2017).

Results

Site description

The South Pacific Gyre is the largest of the five oceanic gyres and its center is furthest from any continent (Figure 1.1). The primary productivity within the water column was the least when compared to all other ocean regions (i.e., 0.05 - 0.12 chl a µg 1-1) (Behrenfeld &

Falkowski, 1997). The low productivity results in low organic carbon burial (4.4 x 10 -10 - 8.2 x

10 -9 mol C/cm2 yr -1) and low sedimentation rates (0.31 - 1.78 m million year (myr) -1) (D'Hondt et al., 2009). The sediment within site U1368D at 12 mbsf was calculated to be deposited approximately 11 million years before present (mybp) based on an estimated sedimentation rate of 1.11 m myr -1. Taking into account a sedimentation rate of 1.78 m myr -1 at site U1371E, the sediment at 124 mbsf was calculated to be deposited approximately 70 mybp.

Prokaryotic cell abundance within the sediment from the sites within the gyre (U1365 -

U1370) were 106 cells cm-3 at the surface, but declined with depth to less than 103 cells cm-3

(Scientists, 2011). Cell abundance from site U1371E, located in the upwelling region outside the gyre, also declined with depth but remained above 103 cells cm-3 throughout most of the sediment column (Scientists, 2011).

Site U1368D was oxygenated throughout starting at 156 - 159 µM at the surface and 140

µM at 12 mbsf (Scientists, 2011). In contrast, the oxygen concentration at site U1371 was no

longer detectable by ~1.5 mbsf. Oxygen concentration at Hole U1371E specifically was 54.92

µM at the surface, 0 µM at approximate mid-depth (62 mbsf) and 4 µM at 125.7 mbsf

(Scientists, 2011).

Dissolved nitrate at site U1368D was 35.84 µM at the surface and 33.87 µM at 15.48 mbsf; whereas, the dissolved nitrate concentration at U1371E was 15.8 µM at the surface and 2.9

µM at 122.85 mbsf (Scientists, 2011). Dissolved ammonium concentrations were measured in

U1371, but not in U1368. Ammonium concentration at the surface of U1371E was 0.35 µM and increased to ~55 µM between depths 30 and 65 mbsf (Scientists, 2011).

Total organic carbon (TOC), dissolved inorganic carbon (DIC) and calcium carbonate

(CaCO3) concentrations were measured at all sampling locations. At site U1368D, TOC decreased rapidly at the surface (0.085 wt% at 0.2 mbsf) and remained below detection limit

(<0.002 wt%) from 11.7 mbsf to 15.48 mbsf. The TOC concentration in U1371 decreases below

0.22 wt% at the surface (0.05 mbsf; to 0.01 wt% at 128.1 mbsf (Scientists, 2011). Site U1368D had detectable DIC throughout the core starting at 2.62 mM at the surface to 2.38 mM at the bottom (15.48 mbsf). The concentration of DIC at the surface of U1371E was 2.89 and decreased to 2.10 at the bottom (128.1 mbsf) (Scientists, 2011). The CaCO3 concentrations in U1368D sediment varied from 77.3 wt % at the surface, increased to 87.4 wt% at 4.36 mbsf and decreased to 61 wt% at 15.48 mbsf (Scientists, 2011). The CaCO3 concentrations in Hole U1371E were less, ranging from 0.04 wt% at the surface, 0.78 wt% at mid-depth (49.15 mbsf), and 0.25 wt% at the bottom (128 mbsf).

Figure 1.1. Location of Holes U1371 and U1368 (highlighted in yellow). Whole round cores were taken from these sites during IODP Expedition 329 to the South Pacific Gyre from October – December 2011 (Scientists, 2011).

The in situ temperature was collected during downhole logging (Scientists, 2011). The pH and chloride concentrations were collected after cores were brought on board. All physical properties of the sediment were reported in the IODP expedition report (Scientists, 2011). The in situ temperature in Hole U1371E was 21.2ºC at 123.65 mbsf and the pH was 7.69 at 123.65 mbsf. The in situ temperature in Hole U1368B was 21.4ºC at 12.01 mbsf, and the pH was 7.80 at

12.05 mbsf (Scientists, 2011). Chloride concentrations were used to estimate salinity. In Hole

U1368D at 12.05 mbsf the salinity was approximately 1.92% and in Hole U137E at 123.65 mbsf it was approximately 1.99% (Scientists, 2011).

Phylogenetic relationship

Phylogenetic analysis of SPG-F1 and SPG-F15 based on 18S rRNA sequences showed that both isolates were related to Penicillium (Figure 1.2). Specifically, SPG-F1 was 99% similar to continental Penicillium chrysogenum from metal contaminated soil (JF718786) as well as

Penicillium chrysogenum from Canterbury Basin subsurface sediment (KM222236). Isolate

SPG-F15 was 98% similar to an airborne Penicillium brevicompactum (AF548085) and

Penicillium brevicompactum from Canterbury Basin subsurface sediment (KM222210).

Figure 1.2. Phylogenetic tree of 18S rRNA gene sequences from SPG fungi. The IDs for the isolates used in this study, SPG-F1 and SPG-F15, are in red

Temperature

Isolates SPG-F1 and SPG-F15 grew from 4 to 30ºC. Growth was not observed at 37ºC after 30 days and therefore greater temperatures were not tested. The duration of the lag phase lasted 24 hours at 21ºC, 48 hours at 26ºC, 96 hours at 10ºC and 15ºC, and 192 hours at 4ºC. The exponential growth rates for SPG-F1 were fastest (4.39 x 10-3 mg hr-1) at 21ºC; whereas, at 4ºC, the exponential growth rate was the slowest (1.62 x 10-3 mg hr-1). The fastest exponential growth rate for SPG-F15 was also at 21ºC (4.81 x 10-3 mg hr-1), but the slowest at 10ºC (2.29 x 10-3 mg hr-1). Exponential growth rates were not significantly different (p > 0.05) when compared between isolates. This was verified using the predicted nlme model trends (Figure 1.3). The growth rates for SPG-F1 and SPG-F15 were not significantly different from each other at each temperature tested.

The biomass of SPG-F1 decreased after 264 hours at 4ºC, 216 hours at 10ºC, 240 hours at

15ºC, 168 hours at 21ºC, and 192 hours at 26ºC. In comparison, isolate SPG-F15 lost biomass after 648 hours at 4ºC, 264 hours at 10ºC, 216 hours at 15ºC, 96 hours at 21ºC, and 236 hours at

26ºC. A subsequent increase in biomass was observed in both isolates after the initial decrease.

Maximum dry weights did not correlate with optimum growth for both isolates; however, the dry weight of SPG-F15 was significantly greater than SPG-F1 (p=0.025).

Table 1.1. Summarized table of the ecophysiology of SPG-F1 and SPG-F15. NaCl Temperature pH Depth Range Nitrate Sulfate Isolate Range (ºC), Range, Ferment (mbsf) (%), Red. Red. optimum optimum optimum SPG-F1 124 4-30, 21 1-12, 1-2 3-8, 3-8 yes no no SPG-F15 12 4-30, 21 1-12, 1 - 2 3-8, 3-6 yes no no

Figure 1.3. Effect of temperature on SPG-F1 and SPG-F15 growth.

NaCl concentration

Both isolates were able to grow at salinities 0 to 12% NaCl, but neither grew at 23.4%

NaCl after 30 days. The length of time that both isolates remained in the lag phase of growth increased as NaCl concentrations increased. Both isolates began germinating 45.5 hours after inoculation at 1 and 2% NaCl, 115 hours at 6% NaCl, and 137 hours at 8% NaCl. Isolate SPG-

F15 germinated after 144 hours at 12% NaCl; whereas, SPG-F1 did not germinate until 432 hours at the same NaCl concentration.

The growth rate during the exponential phase did not correlate with optimum growth at 1 and 2% NaCl for both isolates. The fastest rate during the exponential growth phase for both

SPG-F1 and SPG-F15 occurred at 6% NaCl (1.51 x 10-3 mg hr-1 and 2.10 x 10-3 mg hr-1, respectively). The slowest exponential growth rate for SPG-F1 was at 8% NaCl (4.63 x 10-3 mg hr-1); whereas, the slowest exponential growth rate for SPG-F15 was at 2% NaCl (3.00 x 10-4 mg hr-1). According to Student’s T-test results, there was no significant difference (p>0.05) in growth rates when compared between the fungal isolates. The nlme models predicted no significant difference in growth rates between the isolates, except at 6% NaCl where a clear separation in the trend lines were observed (Figure 1.4). The growth rates for each isolate did not significantly differ at each concentration of NaCl (SPG-F1 p > 0.05; SPG-F15 p > 0.05).

The biomass of SPG-F1 decreased after 287 hours at 1% NaCl, 360 hours at 2% NaCl,

499.5 hours at 6% NaCl, and 354 hours at 8% NaCl. The biomass for SPG-F15 decreased after

402 hours at 1% NaCl, 360 hours at 2% NaCl, 332.5 at 6% NaCl, and 354 hours at 8% NaCl. No correlation was observed between the time of decrease in biomass and concentration of NaCl. An increase in biomass was observed after the initial decrease in biomass (354 hours) for both SPG-

F1 and SPG-F15 at 8% NaCl. There was no significant difference between the maximum dry weights for SPG-F1 and SPG-F15 (p=0.057).

Figure 1.4. Effect of NaCl concentration on SPG-F1 and SPG-F15 growth.

We observed growth at acidic (pH 3) to circumneutral (pH 8) in both SPG-F1 and SPG-

F15 isolates (Figure 1.5). Both isolates germinated after 48 hours at pH 3, and after 54 hours for pH 6. The lag phase lasted 47.5 hours for SPG-F15 at pH 8, but SPG-F1 remained in the lag phase for 96 hours at pH 8.

The fastest exponential growth rates were observed at pH 6 for both SPG-F1 (4.75 x 10-3 mg hr-1) and SPG-F15 (9.32 x 10-3 mg hr-1). The slowest growth rates for both fungi were at pH 8

(SPG-F1=2.22 x 10-3 mg hr-1; SPG-F15=4.78 x 10-3 mg hr-1). There was not a statistically significant difference in growth rates between the isolates at the pH range we tested. However, there was a significant difference in the growth rates of SPG-F1 and SPG-F15 at pH 6 and pH 8, according to nlme models (Figure 1.5). The growth rates compared at each pH were not significantly different for SPG-F1 (p > 0.05) and SPG-F15 (p > 0.05).

We observed a correlation between the fastest growth rates and the time that biomass decreased in both fungi. At pH 6, the biomass for SPG-F1 and SPG-F15 decreased after 97 hours and 166 hours, respectively. In comparison, the biomass of SPG-F1 decreased after 358.8 hours and 167 hours for SPG-F15 at pH 8. An increase in biomass after the initial decrease was observed at pH 3 for both isolates. Only SPG-F15 increased in biomass at pH 6 and pH 8 after a decline in biomass was observed. Maximum growth weights were statistically greater (p=0.045) for SPG-F15 than the maximum growth weights for SPG-F1.

Figure 1.5. Effect of pH on SPG-F1 and SPG-F15 growth.

Discussion

The purpose of this study was to characterize the growth of filamentous fungi from nutrient poor subsurface sediments and determine their ecophysiological limits. The fungal isolates were found to grow best at the in situ sediment temperature (21ºC) and salinity (1% to

2% NaCl). Phylogenetic analysis determined SPG-F1 was closely related to Penicillium chrysogenum; whereas, SPG-F15 was closely related to Penicillium brevicompactum.

Characterization of SPG fungi contributes to the growing knowledge of fungal physiology in

oligotrophic marine subsurface sediments and how they grow in comparison to continental and coastal marine fungi.

Phylogeny

The 18S rRNA gene sequences from isolates SPG-F1 and SPG-F15 were compared to sequences in the GenBank database (Benson et al., 2017) and the closest match (97%) was

Penicillium from continental, coastal, and marine subsurface environments. The genus

Penicillium is one of the most widespread fungi on Earth occurring in in a diversity of habitats such as soils (Pitt, 1973, Dhakar et al., 2014), vegetation (Magan & Lacey, 1984), mangroves

(Kathiresan & Manivannan, 2006), Antarctica (Gonçalves et al., 2013), and deep-sea sediments

(Damare et al., 2006, Rédou et al., 2015, Liu et al., 2017). In these environments, Penicillium exhibit a wide range of physiological capabilities that likely allow them to survive in a variety of conditions. More specifically, SPG-F1 and SPG-F15 were related to Penicillium chrysogenum and Penicillium brevicompactum, respectively. The fungal spores from which the current isolates germinated from were sequestered in the marine subsurface for millions of years; therefore, we expect the physiology to deviate from its taxonomic neighbor.

Temperature

Isolates SPG-F1 and SPG-F15 were psychrotolerant and mesophilic as demonstrated by growth from 4ºC to 30ºC; however, neither could grow at 37ºC. At 21ºC, both isolates grew optimally at the in situ temperature compared to all other temperatures. Many fungi can grow over a wide range of temperatures because of their ability to survive in a variety of environmental conditions. Penicillium species are notorious for this physiology (Maheshwari et

al., 2000, Gunde-Cimerman et al., 2003); which is why they have been found in all types of environments, including marine sediment.

In comparison to the SPG isolates, others found that P. chrysogenum and P. brevicompactum from continental environments grew from 5ºC to 37ºC and optimally at 25ºC to

30ºC (Pitt, 1973, Magan & Lacey, 1984, Sautour et al., 2001, Mahendiran et al., 2013).

Additionally, fungi from shallow marine sediments were found to be mesophilic and psychrotolerant (Singh et al., 2010). However, a Penicillium species from mangrove sediments grew optimally at 30ºC in comparison to the SPG isolates (Kathiresan & Manivannan, 2006).

Interestingly, P. chrysogenum, P. crustosum and P. canescens isolates from St. Helena Bay, a relatively cold bay (10ºC to 14ºC), grew from 4ºC ºC to 37ºC, and optimally between 26ºC and

37ºC (Mouton et al., 2012). Although SPG-F1 and SPG-F15 isolates were considered psychrotolerant and mesophilic, they differed from continental and coastal fungi because they did not grow at 37ºC. It may be possible that the fungi isolated in this study originated from nearby continents that were deposited via aeolian transport and sedimented over time

(Chandralata & Raghukumar, 1998, Spatafora et al., 1998). This has been posited in other marine subsurface environments such as Canterbury Basin sediments (Rédou et al., 2015), deep coalbeds off the Shimokita Peninsula in Japan (Liu et al., 2017), and the Central Indian Basin sediments (Damare et al., 2006).

We noted that previously isolated P. chrysogenum and P. brevicompactum from

Canterbury Basin subsurface sediments (12 to 403 mbsf), could also grow above 30ºC (Rédou et al., 2015). The lower temperature limit of SPG-F1 and SPG-F15 could be attributed to the differences in sediment age at the two sites. The reported sediment age for Canterbury Basin was comparatively much younger; the surface sediment of Canterbury Basin was 0-1.1 million years

old, and 0.05-4.3 million years old at the terminus (~800 mbsf) (Fulthorpe et al.). Additionally, differences in TOC concentrations between both subsurface sites may explain why SPG isolates have lost the ability to grow above 30ºC. TOC concentrations in Canterbury Basin sediments

(0.25-1 wt%) were 10 times greater than SPG sediments. Organic carbon availability has been previously linked to the thermal adaptation of soil fungal communities. In general, it seems that low organic carbon concentrations negatively impacted the ability of fungi to grow at higher temperatures (Kirschbaum, 2004, Hartley et al., 2007). The exact physiology behind this finding is uncertain, but another study suggested that differences in fatty acid abundance may distinguish fungi of the same species at different temperature (Stahl & Klug, 1996). Further study is needed about the fatty acids within the fungal isolates from the South Pacific Gyre, and whether the abundance could have impacted the fungi’s growth at higher temperatures.

Although SPG-F1 and SPG-F15 were isolated from sediments with extremely low TOC concentrations (~0.02 wt% at U1371E, <0.002% at U1368D} and at different sediment depths

(12 mbsf SPG-F15 versus 124 mbsf SPG-F1), they both grew at the same rate for all temperatures. This has been observed in one other study that compared three Penicillium isolates from continental soils (Abellana et al., 2001), but the reason for such variation was not investigated. It may be possible that differences in growth rates were not observed in the current study and in Abellana, et al. (2001) because growth rates were determined within the exponential phase of growth. It has been shown that fungi within the same genus have the least amount of variation in growth during the exponential phase (Meletiadis et al., 2001). The transitional periods between exponential growth and stationary growth better determine variation in growth of same genus (Meletiadis et al., 2001). Future growth rate analysis between similar species

isolated from different in situ conditions in the marine subsurface may provide more information on the small differences in their growth.

A second growth phase in which the biomass suddenly increased after a steady decline was consistently observed during this study, possibly explained by the process of autophagy (i.e.,

“to eat oneself”) (Levine & Klionsky, 2004). During this process, cells respond to stressful conditions such as nutrient starvation by breaking down cytoplasmic components and delivering it to the lysosome to be recycled for nutrients (Levine & Klionsky, 2004). A previous study of

Cryptococcus and Aspergillus isolated from Peru Margin subsurface sediments showed that genes related to autophagocytosis were upregulated compared to continental fungi (Orsi et al.,

2015). This increase in the expression of genes related to autophagy is likely due to the limited availability of labile carbon in the Peru Margin sediments (Orsi et al., 2015). The possibility of the fungal isolates in the current study to subsist on autophagy in the nutrient limited sediment of

SPG would be highly beneficial and may have played a role in their survival. Additionally, the delayed-logistic model (Hutchinson, 1948, Forsyth & Caley, 2006) could also explain the oscillating pattern of growth observed for both isolates. According to the model, when a population reaches peak abundance, past their carrying capacity, the population will decrease slightly before increasing again to a more stabilized capacity (Hutchinson, 1948, Forsyth &

Caley, 2006). However, there is currently no visual evidence of hyphae in the SPG sediment cores that would have provided evidence that the fungi are actually growing in the sediments to support these two ideas. The fluctuation of fungal biomass observed in this study was more likely an artifact of batch culture growth.

NaCl

Based on the results of the current study, both SPG-F1 and SPG-F15 isolates were defined as moderate halophiles because they were capable of growing at 12% NaCl. They also exhibited euryhaline growth because of their ability to grow from 1 to 12% NaCl. However, it was observed that increasing concentrations of NaCl above 2% reduced the growth rates of both isolates. It has been previously studied that fungi will reduce growth rates to meet the energy demands the cells experience under salt stress (Albertyn et al., 1994). This adaptive feature could explain why we still saw growth at higher NaCl concentrations, but reduced growth rates.

Growth at wide ranges of salinity has also been studied in many fungi, especially Penicillium

(Tresner & Hayes, 1971, Jones, 2000, Zajc et al., 2012). Penicillium, along with most other fungi, have the ability to change the concentrations of glycerol in their membranes to combat osmotic stress brought on by high concentrations of salt (Plemenitaš et al., 2014). The putative adaptation across a wide range of salinities may be another reason why Penicillium can be found in a variety of environments such as the marine subsurface.

We tested the ability of SPG-F1 and SPG-F15 to grow at hypersaline NaCl concentrations (~24% NaCl), but did not observe growth for either isolates. In comparison, one study found that continental P. chrysogenum could withstand concentrations of 25% NaCl or greater (Tresner & Hayes, 1971). Also, most continental Penicillium from the high-altitude soils of the Himalayans grew above 20% NaCl (Dhakar et al., 2014). When we compared these observations to Penicillium in marine environments, we found that marine isolates could also grow at NaCl above 20% NaCl. In marine salterns, and the Dead Sea, P. chrysogenum and P. brevicompactum both grow to at least 25% NaCl (Zajc, 2014}. Additionally, P. chrysogenum from mangrove sediments can grow from 0% to 20% NaCl (Nayak et al., 2012). This evidence

suggests that SPG-F1 and SPG-F15 may be physiologically different from continentally derived and coastally derived Penicillium because growth was not observed at ~24% NaCl.

The optimal growth of SPG-F1 and SPG-F15 was consistent with the in situ salinity concentration in SPG sediments. Similar to this finding, a study of P. chrysogenum and P. brevicompactum from Canterbury Basin subsurface sediments found that the isolates also grew best at the in situ sediment salinity (3% salt concentration) (Rédou et al., 2015). In comparison,

Penicillium from the coastal marine sediments of St. Helena Bay, had a larger range of optimal growth (1.5% - 6% salinity) (Mouton et al., 2012). In coastal marine sediments, salinity can change quickly due to large rain events and increases in atmospheric temperature (Atkinson et al., 2007). It may be possible that fungi from coastal sediments have wider salinity optimums in order to survive drastic changes in salinity. However, the marine subsurface is sequestered from such events and the salinity of the sediments does not change drastically. Based on this, it may be possible that marine subsurface fungi are better adapted to the in situ salinities than that of coastal sediment fungi (Rédou et al., 2015). The salinity preferences of fungi from other subsurface sediments will help determine if our results are a common occurrence in this environment.

At 8% NaCl, a sudden increase in biomass near day 15 was observed after a consistent decrease in biomass for both isolates. This is likely due to the rapid depletion of already-limited nutrients during batch culture cultivation. It is possible that the fungi used the process of autophagy (i.e., “to eat oneself”) to recycle their necromass into nutrients for themselves (Levine

& Klionsky, 2004). Autophagy is commonly induced under nutrient starvation (Levine &

Klionsky, 2004) or low organic carbon concentrations (Orsi et al., 2015) as a survival mechanism. The fluctuations in fungal biomass we observed could also be due to the fungi

stabilizing their growth after they had exceeded their carrying capacity inside the vials

(Hutchinson, 1948, Forsyth & Caley, 2006).

Isolates SPG-F1 and SPG-F15 were classified as acido-tolerant because they could grow from pH 3 to pH 8. Growth at wide ranges of pH have been documented in Penicillium before.

Continental Penicillium has been observed growing between pH 3 and pH 10 (Wheeler et al.,

1991). Similarly, in coastal marine sediments of St. Helena Bay, Penicillium grew from pH 5 to pH 10. Fungi are notorious for growing across several orders of pH because of the Rim101 pathway that regulates the intake or output of ions into the cell to control internal pH levels

(Lamb et al., 2000, Peñalva et al., 2008, Maeda, 2012). It is possible that SPG-F1 and SPG-F15 were capable of growing over a wide range of pH due to this highly conserved pathway, which warrants further genetic analysis.

The optimum growth for SPG-F15 could not be determined between pH 3-8 because, at every pH tested, SPG-F15 germinated approximately 2 days after inoculation. The same result was observed for SPG-F1, but only between pH 3 and pH 6. Oddly, germination for SPG-F1 at pH 8 did not begin until 4 days after inoculation. Previously reported pH tolerances for continental Penicillium species were compared to the pH tolerance of SPG-F1 and SPG-F15.

Likewise, in the study of continental P. chrysogenum, pH did not have a significant impact on germination (Sautour et al., 2001). Similar results have also been reported in coastal marine sediments. In St. Helena Bay sediments, pH did not have a significant impact on the optimal growth for P. chrysogenum, P. crustosum and P. canescens between pH 5 to pH 7 (Mouton et al., 2012). Furthermore, P. chrysogenum isolated from deep sea sediments of the East Pacific did

not exhibit significant changes in growth from pH 4 to pH 10 (Luo et al., 2014). When we examined the effects of pH on the growth of Penicillium in continental environments, coastal sediments, and deep-sea sediments and compared it to our results, we confirmed that pH does not seem to have a significant impact on growth. Again, this may be attributable to the adaptive mechanisms fungi have for tolerating a wide range of pH.

Oscillations in biomass were observed for both fungal isolates from pH 3 to pH 8. This trend may have been due to autophagy (Levine & Klionsky, 2004), or the population stabilizing their abundance after reaching carrying capacity (Hutchinson, 1948, Forsyth & Caley, 2006).

Either explanation could explain how fungi grow in batch culture when nutrients are limited.

Summary

We successfully cultured fungi from oligotrophic sediment within the South Pacific Gyre that were 11 to 70 million years old. The isolates were capable of surviving in a range of temperatures, salinity and pH but grew best at in situ SPG sediment conditions. However, both isolates could not grow at 37ºC nor at 25% NaCl, suggesting that they may be physiologically different from continentally derived and coastal marine sediment Penicillium. Overall, this study sheds light on the ecophysiology of two Penicillium isolates from SPG sediments and expands the currently known boundaries for eukaryotic life.

CHAPTER II: MOLECULAR CHARACTERIZATION OF FUNGI IN THE OLIGOTROPHIC MARINE SUBSURFACE

Abstract

The marine subsurface was previously thought to be devoid of eukaryotic life, but recent advances in molecular technology have unlocked the presence and activity of fungi in this isolated environment. In continental systems, fungi are important members of the global carbon cycle because of their ability to transform recalcitrant carbon into labile carbon. In order to understand the adaptations that have led to the fungal ecological and nutrient cycling roles within marine subsurface sediments, genomes of these fungi need to be analyzed. Here, we present the draft genomes of two fungi isolated from subsurface sediment collected within the South Pacific

Gyre through the Integrated Ocean Drilling Program Expedition 329. Total sedimentary organic carbon was generally less than 0.02 wt%, with recalcitrant carbon sources comprising the majority. Isolates from site U1371E (referred herein as SPG-F1) and U1368D (referred herein as

SPG-F15) were previously identified as Penicillium chrysogenum and Penicillium brevicompactum, respectively, via 18S rRNA gene sequencing. Here, we sequenced the genomes of both isolates using the high-throughput sequencing platform Illumina HiSeq. The resulting genome sizes were 32 megabase pairs (Mbp) for SPG-F1 and 36 Mbp for SPG-F15, which was comparable to continental Penicillium species. The transposable element content for each genome was 3% for SPG-F1 and 10% for SPG-F15. A total of 11,581 genes were predicted in the SPG-F1 genome and 11,243 genes in SPG-F15. Approximately 58% of the annotated genes were assigned to gene ontology for biological, cellular, and molecular functions. Both isolates contained approximately 600 genes assigned to carbohydrate-active enzymes, approximately 90

of which were specifically involved in recalcitrant carbon degradation, suggesting potential recalcitrant carbon degradation. Degrading inorganic carbon or recalcitrant carbon is crucial to sustain life in the deep subsurface. This sheds light on the need to target more fungal genomes to determine the extent fungi plays in the subsurface carbon cycle.

Introduction

It is estimated that the Earth’s biosphere contains ~550 gigatons of biomass in the form of carbon, yet Bacteria and Archaea in the marine subsurface make up ~1.8% of the total biomass (Bar-On et al., 2018). Even though these microbial communities only make up a fraction of the total global biomass, they play important roles in global biogeochemical cycles

(Jørgensen, 1982, Whitman et al., 1998, D'Hondt, 2003, Biddle et al., 2008, Parkes et al., 2014).

However, little is known about the fungal role in sedimentary biogeochemical cycles and their activity (Orsi et al., 2013). The paucity of fungal biomass estimates in the marine subsurface has resulted in their exclusion from previously reported total global estimates.

In continental environments, fungi are important members of the carbon cycle because of their ability to recycle recalcitrant carbon, such as hydrocarbon (Da Silva et al., 2003, Sanyal et al., 2016), lignin (Gubernatorova & Dolgonosov, 2010), and lignocellulose (Riley et al., 2014), into labile carbon. Previous studies have shown that many marine subsurface fungi are closely related to continental fungi (Edgcomb et al., 2011, Orsi et al., 2013, Rédou et al., 2015, Liu et al., 2017). If marine subsurface fungi are related to continental fungi, it is possible that they have similar metabolic capabilities. The ability for fungi to metabolize recalcitrant carbon in the oligotrophic marine subsurface would be beneficial to their survival since oligotrophic

subsurface sediment is low in organic carbon and enriched in recalcitrant carbon (D'Hondt et al.,

2009, Oni et al., 2015).

Sediments from the South Pacific Gyre (SPG) have been described as some of the most energy-limited on Earth, with cell abundances 3 to 4 orders of magnitude less than other deep- sea sediments (Scientists, 2011). Here, we interrogated the draft genomes of two marine subsurface fungi isolated from SPG sediments for genes related to recalcitrant carbon degradation and survival in oligotrophic sediments. Sediment was collected via the Integrated

Ocean Drilling Program (IODP) Expedition 329 to the South Pacific Gyre from two locations and two depths (U1371E at 124 meters below seafloor (mbsf) and U1368D at 12 mbsf).

Microscopy was used to identify the morphology of the isolates and targeted 18S rRNA gene sequencing was used to determine taxonomy. Active in situ populations were previously confirmed and quantified through real-time PCR of the 18S rRNA transcripts. The two isolates were closely related to Penicillium chrysogenum (isolated from U1371E, referred to as SPG-F1) and Penicillium brevicompactum (isolated from U1368D, referred to as SPG-F15). Both genomes contained genes that have been attributed to the degradation of aromatic compounds, lignin, lignocellulose, and carbonate. Genes related to stress response were found in both genomes as well. The presence of these genes suggests that both SPG fungi have the potential to influence the carbon cycle if they are actively growing in the sediments. This study highlights the importance that fungi play in carbon remineralization within the subsurface and the need to include subsurface fungi in global biomass estimates.

Materials and Methods

Sample collection and fungal isolation

Sediment samples were collected during the Integrated Ocean Drilling Program (IODP)

Expedition 329 to the South Pacific Gyre with the drilling vessel D/V JOIDES Resolution. Six sites (U1365C, U1367D, U1368D, U1369E, U1370F and U1371E) were cored for sediment microbiology (Figure 2.1). Potential biological contamination from drilling fluid and seawater intrusion was assessed by the presence of perfluorocarbon microsphere tracers within the interior and exterior of the sediment cores (Scientists, 2011).

Sediment cores were collected in 9.5 m sections and divided into 1.5 m subsections.

These sections were further sub-sectioned into 10 cm whole round cores and stored at -80ºC for future molecular analyses. Sediment for enrichments were collected into cut sterile syringes and stored at 4oC until they could be processed. The enrichments consisted of 30 g of sediment in

125 mL glass septum bottles with 100 mL of marine broth media diluted to 10% (Difco 2216,

BD Diagnostics; Franklin Lakes, New Jersey). Liquid media blanks containing only marine broth and no sediment were prepared to evaluate potential contamination. The enrichments were sealed and incubated in the dark at 5ºC for one year while shaking at 150 rpm. After a one-year incubation, 100 µL of the slurries was transferred onto marine broth agar plates, sealed with parafilm, and stored at 5ºC. The enrichments yielded a total of 18 fungal isolates. Growth was maintained by transferring the isolates every 3 months onto plates containing marine broth agar and potato dextrose agar (Difco 254920, BD Diagnostics; Franklin Lakes, New Jersey). During the culture transfers, control plates containing marine broth agar and potato dextrose agar were left open to assess potential laboratory contamination. No contamination was found in the control bottles with liquid media and the control plates with the respective media agar.

The current study focuses on two of the original 18 isolates, referred hereafter as SPG-F1 and SPG-F15. Fungal isolate SPG-F1 was isolated from U1371E-14H2 (45°57.8397′S,

163°11.0365′W) at 124 mbsf and SPG-F15 was isolated from U1368D-2H1 (27°54.9920′S,

123°9.6561′W) at 12 mbsf (Figure 2.1). Prior to this study, SPG-F1 and SPG-F15 were assigned as Penicillium chrysogenum and Penicillium brevicompactum, respectively, by 18S rRNA gene sequencing.

DNA extraction

High quality DNA (gDNA) was extracted from pure cultures of both SPG-F1 and SPG-

F15. Approximately 200 g of freeze-dried biomass was placed in a 2 mL bead beating tube and shaken at 2,285 x g for 60 seconds. Negative control extractions containing only sterile water and no culture were carried out throughout the extraction and sequencing process. A 500 µl aliquot of extraction buffer (0.25 M NaCl (Thermo Fisher; Waltham, MA) 0.2 M Tris-HCL, pH

8.5 (Promega; Madison, WI), 0.0025 M EDTA- 2Na (Biorad; Hercules, CA), and 0.5% sodium dodecyl sulfate (Thermo Fisher; Waltham, MA) was added to each extraction. The tubes were vortexed for 10 seconds and placed in a rotator for 30 minutes at room temperature. To each extraction, 350 µl of phenol (Thermo Fisher; Waltham, MA) was added. The tubes were turned by hand gently 200 times. An aliquot of 150 µl of chloroform was added (Thermo Fisher;

Waltham, MA). The tubes were rotated 200 times by hand. The tubes were centrifuged at 20817 x g for 5 minutes. We transferred the supernatant to a new tube containing 700 µl isopropanol

(Thermo Fisher; Waltham, MA) and centrifuged at 20,817 x g for 5 minutes. The DNA was rinsed with 70% ethanol (Thermo Fisher; Waltham, MA) and placed in a vacuum evaporator for two hours. The DNA pellet was resuspended in 240 µl of sterile water and 5 µl of RNase A (10

mg mL-1) (VWR; Radnor, PA). The extractions were incubated at 37 °C for one hour. An aliquot of 40 µl of 0.7 M of NaCl and 32 µl of a 10% cetrimonium bromide (MP Biomedical; Santa

Ana, CA) and 5 M NaCl solution was added to each tube. The extractions were incubated at

67°C for 10 minutes. To the tubes, 240 µl of chloroform was added before being centrifuged at

15,294 x g for 5 min. The supernatant was transferred to new tubes filled with 350 µl of phenol and 150 µl of chloroform. The tubes were turned by hand 200 times and centrifuged at 20817 x g for 5 minutes at 23°C. The DNA was precipitated by transferring the supernatant into new tubes containing 2.5 volumes of 100% ethanol and incubating for 5 minutes at ambient temperature.

The DNA was centrifuged at 20,817 x g for 5 minutes. The resulting DNA pellets were rinsed with 70% ethanol and placed into a vacuum evaporator to dry for two hours. The dried DNA was re-suspended in 50 µl of Tris-buffer (10 mM, pH 8) and placed into a vacuum evaporator to dry before being sent for sequencing.

DNA Sequencing

The DNA extractions for SPG-F1 and SPG-F15 were quality checked prior to library construction. An Illumina paired-end library was prepared following the manufacturers protocol

(TruSeq DNA PCR-Free Sample Preparation Guide, Part # 15036187 Rev. A) to generate 101 bp length paired-end reads. The samples were sequenced using an Illumina HiSeq 2000 sequencer

(Illumina, San Diego, CA) at Macrogen in Seoul, South Korea. The raw reads were quality checked using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Trim

Galore! was used to remove the Illumina adapters off the paired-end reads as well as low quality reads using a quality phred score of 20.

Genome assembly

De novo assembly was performed on the trimmed reads with two programs in order to optimize the assembly. Velvet v1.2.10 and SPAdes v3.11.0 were both run using default parameters, unless stated otherwise (Zerbino & Birney, 2008, Bankevich et al., 2012). Prior to using Velvet, KmerGenie was used to detect the appropriate k-mer length (Chikhi & Medvedev,

2013). Velvet was set to not form scaffolds by combining contigs. The coverage cutoff of the assembly was set to 10X to remove small coverage contigs and a minimum contig length of 500 bp was used to remove short contigs. In SPAdes, the coverage cut-off was also set to 10X and the careful mode turned on to reduce the number of mismatches and errors. The quality of both assemblies was compared using QUAST 4.1 (Gurevich et al., 2013). The number of contigs, the length of the assembly, the length of the longest contig, and the N50 value were used to choose the optimal assembly. The N50 value is a statistic that measures the minimum contig length needed to support 50% of the genome assembly.

Genome annotation

A MAKER2 pipeline was used for annotation without RNA-seq data on small eukaryotic genomes (Koutsovoulos et al., 2014). The pipeline utilizes several ab initio gene prediction programs to iteratively train the gene predictors and produce an accurate gene model. Repetitive elements were identified de-novo with RepeatModeler version 1.0.11 (Smit & Hubley, 2008).

RepeatMasker was used to mask the repeats in both genomes (Smit et al., 2017). RMBlast version 2.2.28 was used as the search engine instead of NCBI blastn. RMBlast was chosen over

NCBI blastn, because it is a version of NCBI blastn that is compatible with RepeatMasker, specifically. The RepeatMasker edition of RepBase was used as the database (Bao et al., 2015).

Benchmarking Universal Single-Copy Orthologs (BUSCO)(Simao et al., 2015) was used to check the completeness of the assembly as well as a training set for the gene predictor Augustus

(Stanke & Waack, 2003). BUSCO analysis was performed with the lineage-specific dataset fungi_odb9. The Augustus output from BUSCO was renamed to the individual isolates name and moved to the Augustus species folder within Augustus. An unsupervised training gene predictor specific for fungi, GeneMark-ES, was also used (Ter-Hovhannisyan et al., 2008). The MAKER2 version 2.31.9 was used to predict protein-coding genes from the masked assembly (Holt &

Yandell, 2011). Protein evidence was provided using the UniProt protein database (Consortium,

2018). The output from GeneMark-ES and the species folder in Augustus was provided to

MAKER2 to enhance the alignment-based gene models.

A BLASTp search was performed on the predicted gene models from MAKER2 using an e-value threshold of 10-3. The results were exported as an XML file and uploaded to

Blast2GO for putative Gene Ontology (GO) assignment (Conesa et al., 2005). InterProScan was used within Blast2GO to locate the protein domains and assign GO terms. InterProScan GO terms were merged with the BLASTp GO assignments. Enzyme codes (EC) were classified and mapped using the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways in

Blast2GO. Putative proteins were subjected to CAZy annotation with the DataBase for automated Carbohydrate-active enzyme Annotation (dbCAN) (Yin et al., 2012).

Results

Site Description

The South Pacific Gyre is the largest of the 5 oceanic gyres and its center is furthest from any continent (Figure 2.1). The gyre’s primary productivity within the water column is the least

when compared to all other ocean regions (i.e., 0.05 - 0.12 chl a µg 1-1) (Behrenfeld &

Falkowski, 1997). The low productivity results in low organic carbon burial (4.4 x 10 -10 - 8.2 x

10 -9 mol C/cm2 yr -1) and low sedimentation rates (0.31 - 1.78 m million year (myr) -1)

(Scientists, 2011). Based on a sedimentation rate of 1.11 m myr -1 at U1368D, the age of the sediment from which the fungus was isolated at 12 mbsf was calculated to be approximately 11 million years before present (mybp) in age. Based on a sedimentation rate of 1.78 m myr -1 at

U1371E, the age of the sediment from which the fungus was isolated at 124 mbsf was calculated to be approximately 70 mybp.

Prokaryotic cell abundance within the sediment from the sites within the gyre (U1365-

U1370) were 106 cells cm-3 at the surface, but declined with depth to less than 103 cells cm-3

(Scientists, 2011). Cell abundance from site U1371, located in the upwelling region outside the gyre, also declined with depth but remained above 103 cells cm-3 throughout most of the sediment column (Scientists, 2011).

Sediment within the gyre was generally oxygenated throughout the sediment column until the terminus at the basement (Scientists, 2011). Specifically, site U1368 was 156 - 159 µM at the surface and 140 µM at 12 mbsf (Scientists, 2011). In contrast, the oxygen concentration at site U1371 was no longer detectable by ~1.5 mbsf. Oxygen concentration at Hole U1371E specifically was 54.92 µM at the surface, 0 µM at approximate mid-depth (62 mbsf) and 4 µM at

125.7 mbsf.

Total organic carbon (TOC), dissolved inorganic carbon (DIC) and calcium carbonate

(CaCO3) sediment concentrations were measured for all sites from within and outside the SPG.

At all sites within SPG (U1365-U1370), TOC declines rapidly at the surface sediment and remains below 0.05 wt% throughout the sediment cores. TOC in U1371E declines rapidly at the

surface as well, but remains at a concentration of 0.1% throughout most of the sediment column until it further declines to ~0.05 wt% at 101 mbsf (Scientists, 2011). DIC remained detectable throughout the sediment columns of all sites (U1365-U1371) (~3 mM at surface and 2 mM at

~130 mbsf). CaCO3 concentrations in U1368D sediment varied from 70-87 wt % in the upper ~5 mbsf and decreased to ~ 60 wt% at 14 mbsf (Scientists, 2011). The CaCO3 concentrations in

U1371E sediments are significantly lower and range from 0.04 wt% at the surface, 0.78 wt% at mid-depth (49.15 mbsf) and 0.25 wt% at the bottom (128 mbsf).

Figure 2.1. Location of Holes U1371 and U1368 (highlighted in yellow). Whole round cores were taken from these sites during IODP Expedition 329 to the South Pacific Gyre from October-December 2011 (Scientists, 2011).

Genome Assembly

The total number total number of nucleotide base pairs (i.e. genome size) for U1371E-

14H2 was 149,610,352, and U1368D-2H1 had a genome size of 162,517,156. Assuming an average genome length of 32 megabase pairs (Mbp) for continental Penicillium, we estimated the sequencing coverage depth was 513X for SPG-F15 and 472X for SPG-F1. A total of 2.2% of all base pairs (bp) was trimmed from SPG-F15 and 3.0% of bp was trimmed from SPG-F1.

Quast determined that SPAdes produced the better genome assembly based on the number of contigs, the length of the contigs, the N50 value, and the total length of the assembly

(Table 2.1). The SPAdes assembly for SPG-F15 resulted in 348 contigs; whereas, the Velvet assembly resulted in 863 contigs. The total number of contigs from the SPAdes assembly for

SPG-F1 was 457 contigs, versus the 863 contigs Velvet produced. The SPAdes assembler constructed the largest contig for both isolates, 961,081 bp for SPG-F15 and 876,077 bp for

SPG-F1. The N50 value for SPG-F1 from SPAdes was 221,558 and 96,324 from Velvet. The

N50 value for SPG-F15 from SPAdes was greater (288,392) than Velvet (115,885). There was little difference in the total length of the draft assemblies between SPAdes and Velvet. The

SPAdes assembly length for SPG-F15 was 36.13 Mbp and the Velvet assembly was 36.15 Mbp.

The SPAdes assembly for SPG-F1 was 32.06 Mbp in length and the Velvet assembly was 32.13

Mbp. The GC % for SPG-F15 was 46.52% determined by SPAdes, and 46.49% determined by

Velvet. The genome for SPG-F1 had 48.26% GC content according to SPAdes and 48.25% GC content according to Velvet. Overall, the SPAdes assembly was determined to be the better quality assembly for both isolates. BUSCO analysis also confirmed that the SPAdes assembly was of high-quality. Out of 4046 BUSCOs, SPG-F1 had 3960 complete genes (97.9%) and SPG-F15 had 3973 complete genes (98.2%) (Table 2.1).

Table 2.1. Assembly and Annotation Statistics. SPG-F1 SPG-F15 Assembly Features SPAdes Velvet Assembly Features SPAdes Velvet N50 221,558 96,324 N50 288,392 115,885 L50 43 105 L50 37 95 No. of Contigs 457 863 No. of Contigs 348 863 Largest Contig (bp) 876,077 450,462 Largest Contig (bp) 961,081 484,964 Genome Size (Mbp) 32.06 32.13 Genome Size (Mbp) 36.13 36.15 GC Content 48.26% 48.25% GC Content 46.52% 46.49% Annotation Features Annotation Features BUSCO Completeness 97.90% BUSCO Completeness 98.20% Total No. of Genes 11,581 Total No. of Genes 11,243 Avg. Gene Length (bp) 1,514 Avg. Gene Length (bp) 479 Total No. of GOs 6,760 Total No. of GOs 6,618

Genome Annotation

Repeat Masking

A total of 3,550,914 bp (9.82%) of repetitive elements were masked in SPG-F15; whereas, SPG-F1 had 928,433 bp (2.90%) masked (Table 2.2). Transposable elements (TEs) made up most of the repeats for both isolates (SPG-F15 8.98%, SPG-F15 2.10%).

Approximately, 78% of TEs in SPG-F15 and 85% of TEs in SPG-F1 were unclassified. The rest of the repetitive elements were classified as simple repeats and low complexity repeats. Simple repeats made up 0.66% in SPG-F1 and 0.70% in SPG-F15. Low complexity repeats made up

0.14% in both genomes.

Table 2.2. Repetitive elements found within SPG-F1 and SPG-F15. SPG-F1 Repetitive Element Number Length Occupied (bp) Percentage Transposable 3,286 673,280 2.10% SINEs 0 0 0.00% LINEs 16 3,423 0.01% LTR 17 16,778 0.05% DNA 470 291,360 0.91% Unclassified 2,783 361,719 1.13% Simple Repeats 5,254 211,344 0.66% Low Complexity 933 43,809 0.14% Total 9,473 928,433 2.90% SPG-F15 Repetitive Element Number Length Occupied (bp) Percentage Transposable 5,396 3,246,037 8.98% SINEs 0 0 0.00% LINEs 116 83,938 0.23% LTR 864 1,430,400 3.96% DNA 188 192,008 0.53% Unclassified 4,228 1,539,691 4.26% Simple Repeats 5,863 253,699 0.70% Low Complexity 1,081 51,178 0.14% Total 12,340 3,550,914 9.82%

Gene model and gene ontology

MAKER2 predicted a total of 11,243 genes for SPG-F15 and 11,581 genes for SPG-F1

(Table 2.1). The average length of the genes was 1,514 bp for SPG-F1 and 479 bp for SPG-F15

(Table 2.1). BLASTp found 745 putative genes from SPG-F1 (~6% of the total) and 736 from

SPG-F15 (~6.5% of the total). The top three BLASTp hits for SPG-F1 and SPG-F15 were acyl- carrier-proteins, ubiquinones, and NADP+. Blast2GO annotation assigned genes to three GO categories: biological, cellular and molecular processes. There were a total of 6,760 GOs for

SPG-F1 (~58% of the total) and 6,618 for SPG-F15 (~59% of the total) (Table 2.1). Metabolic processes made up the largest portion of the genomes biological processes. Some of these

processes included: organic cyclic compound metabolic processes, cellular aromatic metabolic processes, cellular nitrogen metabolic processes, and cellular macromolecule metabolic processes (Figure 2.2). Genes related to cellular processes included intracellular organelles, integral membrane components, and the cytoplasmic proteins (Figure 2.2). Organic cyclic, heterocyclic, and ion binding genes constituted a majority of the molecular processes (Figure

2.2).

Enzyme code assignment and KEGG mapping The top three pathways identified for SPG-F1 and SPG-F15 were purine metabolism

(SPG-F1 378 genes, SPG-F15 354 genes), thiamine metabolism (SPG-F1 294 genes, SPG-F15

277 genes), and the biosynthesis of antibiotics (SPG-F1 192, SPG-F15 189 genes). Other metabolic pathways related to biogeochemical cycling included metabolism of xenobiotics by cytochrome P450 (map 00980), glyoxylate and dicarboxylate metabolism (map 00630), and assimilatory sulfur (map 00920) and nitrogen metabolisms (map 00910). The xenobiotic metabolism pathway included specific polycyclic aromatic hydrocarbon degradation pathways such as the degradation of benzo[a]pyrene, and naphthalene. Both genomes contained genes encoding cytochromes P450 monooxygenases (EC: CYP1B1; CYP1A1), epoxide hydrolases

(EC: 3.3.2.9), and glutathione transferases (EC: 2.5.1.18). Within the glyoxylate and dicarboxylate pathways for both fungi, were genes encoding malate dehydrogenase (EC:

1.1.1.37), malate synthase (EC: 2.3.3.9), citrate synthase (EC: 2.3.3.1), and isocitrate lyase (EC:

4.1.3.1) which are involved in oxalic acid production. Both fungi had nitrate (EC:1.7.1.1; 1.7.1.2;

1.7.1.3) and nitrite reductases (EC:1.7.1.4), specifically involved in assimilatory nitrate reduction. Also in both genomes were genes that encode for sulfate reduction enzymes such as

sulfate adenylyltransferases (EC: 2.7.7.4), adenylylsulfate kinase (EC: 2.7.1.25), and phosphoadenylyl-sulfate reductase (EC 1.8.4.8).

Biological Processes A Biological Processes Protein Metabolism Regulation of Nitrogen Compound Metabolism B Transport Phosphorus Metabolism Organonitrogen Compound Metabolism Nucleobase-Containing Compound Metabolism Regulation of Macromolecule Metabolism Cellular Biosynthetic Process Transport Organic Substance Biosynthetic Process Cellular Biosynthetic Process Heterocycle Metabolism Cellular Aromatic Compound Metabolism Organonitrogen Compound Metabolism Organic Cyclic Compound Metabolism Heterocycle Metabolism Cellular Macromolecule Metabolism Cellular Nitrogen Compound Metabolism Organic Cyclic Compound Metabolism Macromolecule Metabolism Macromolecule Metabolism 0 400 800 1200 1600 2000 0 500 1000 1500 2000 Number of GOs Number of GOs

Cellular Processes Cellular Processes

Intracellular Non-Membrane-Bounded Organelle Intracellular Non-Membrane-Bounded Organelle

Cytoplasmic Part Cytoplasmic Part

Cytoplasm Cytoplasm

Integral Component of Membrane Integral Component of Membrane

Intracellular Membrane-Bounded Organelle Intracellular Membrane-Bounded Organelle

0 400 800 1200 0 400 800 1200 Number of GOs Number of GOs Molecular Processes Molecular Processes

Drug Binding Drug Binding Cofactor Binding Cofactor Binding Carbohydrate Derivative Binding Carbohydrate Derivative Binding Transferase Activity Transferase Activity Protein Binding Protein Binding Oxidoreductase Activity Oxidoreductase Activity Small Molecule Binding Small Molecule Binding Hydrolase Activity Hydrolase Activity Ion Binding Ion Binding Heterocyclic Compound Binding Heterocyclic Compound Binding Organic Cyclic Compound Binding Organic Cyclic Compound Binding

0 400 800 1200 1600 2000 2400 0 400 800 1200 1600 2000 2400 Number of GOs Number of GOs

Figure 2.2. Gene Ontology (GO) functional annotation of genes in SPG-F1 (Column A) and SPG-F15 (Column B) biological, molecular and cellular processes.

Carbohydrate-active enzymes

A total of 653 proteins from SPG-F1 (~6% of the total) and 626 proteins from SPG-F15

(~6 of the total) encoded carbohydrate-active enzymes according to the CAZy annotation (Table

2.3). Both SPG isolates had similar abundances of CAZys. The enzymes within the CAZy database were divided into the following classes: carbohydrate-binding modules (CBM), carbohydrate esterases (CE), glycoside hydrolases (GH), glycosyl transferase (GT), polysaccharide lyases (PL), and auxiliary activities (AA). Each class in the CAZy database was subdivided into families and given a number. The resulting identification was class abbreviation followed by family number (i.e., AA1).

In SPG-F15, a total of 60 proteins encoded CBM, 116 proteins encoded CE, 253 proteins encoded GH, 97 proteins encoded GT, 9 proteins encoded PL, and 91 proteins encoded AA

(Table 2.3). In SPG-F1, a total of 62 proteins encoded CBM, 119 proteins encoded CE, 270 proteins encoded GH, 104 proteins encoded GT, 12 proteins encoded PL, and 86 proteins encoded AA (Table 2.3).

Table 2.3. Comparative abundance of CAZy enzymes in their respective classes. CBM=carbohydrate binding molecules. CE=carbohydrate esterases. GH=glycoside hydrolases. GT=glycosyl transferase. PL=polysaccharide lyases. AA=auxiliary activities. CAZy Classes Species Environment Total CAZy CBM CE GH GT PL AA SPG-F1 Marine Subsurface 653 62 119 270 104 12 86 SPG-F15 Marine Subsurface 626 60 116 253 97 9 91

SPG-F1 and SPG-F15 had similar proportions of the CAZy families for each class. The most abundant protein families within the AA class were AA3 and AA7 in both isolates (Figure

A.1, Figure A.2). CBM 50 and CBM 18 were the top two families in the CBM class (Figure

A.1). Also for both fungi, CE1 and CE10 were the top two families in the CE class (Figure A.1,

Figure A.2). In the GH class, families 3, 5, 13, 16, and 18 were the top hits and had similar abundances (9-12%). GT2 and GT32 were the most abundant for the GT class in both isolates

(Figure A.1, Figure A.2). PL1 outnumbered all the other families in the PT class for the fungi

(Figure A.1, Figure A.2). Notable differences in the presence of CAZy families between both fungi were observed (Figure A.1, Figure A.2). SPG-F1 included PL22, GT61, GT15, GH127,

GH88, GH23, CBM59, CBM53, and CBM 19, but SPG-F15 did not contain these families.

Families CBM 38 and GT33 were present in SPG-F15 but not SPG-F1.

Discussion

The purpose of this study was to investigate fungal genomes from extremely oligotrophic marine subsurface sediments. We investigated the genomes of two fungi from SPG subsurface sediments for genes involved in the metabolism of recalcitrant carbon compounds. Genes involved in hydrocarbon, lignin, lignocellulose, and carbonate degradation were present in both genomes. Genes related to stress response were also found. Evidence for antimicrobial production was observed in both genomes, but this was not the scope of this particular thesis and will be investigated further at a later date. The investigation of genomes from SPG fungi helps answer questions regarding the potential influence they have on the global carbon cycle and highlights their importance in SPG sediments.

Comparative genome statistics

There currently exist two genomes for P. chrysogenum and two genomes for P. brevicompactum in JGI’s MycoCosm database, which was used here for comparison to SPG-F1 and SPG-F15 (Grigoriev et al., 2013). The 32.06 Mbp genome of SPG-F1 was very similar in

size in to P. chrysogenum Wisconsin 54-1255 (32.22 Mbp) and P. chrysogenum v1.0 (31.34

Mbp). Isolate SPG-F15 had a larger genome (36.13 Mbp) compared to P. brevicompactum

AgRF18 (31.68 Mbp) and P. brevicompactum v2.0 (32.11 Mbp). One possible explanation for why SPG-F15 has a larger genome than the two P. brevicompactum references, could be due to different amounts of repetitive elements we found. Although, the percentage of repeats for the reference genomes was not reported and therefore not compared to SPG-F15, a previous study has shown that the percentage of repeats can vary within the same species of fungus (Castanera et al., 2016). Regardless, the genome size of SPG-F15 is still within range of Penicillium species in general, which are typically between 24 Mbp and 36 Mbp (Nielsen et al., 2017).

Isolate SPG-F1 had a total of 11,581 predicted genes which was comparable to P. chrysogenum Wisconsin 54-1255 which had 13,671 genes (van den Berg et al., 2008) and to P. chrysogenum v1.0 which had 11,396 predicted genes (de Vries et al., 2017). The number of predicted genes for SPG-F15 (11,243) was similar to P. brevicompactum AgRF18 (12,343) and

P. brevicompactum v2.0 (11,536) (Grigoriev et al., 2013). The genomes of both SPG fungi are similar to other genomes of Penicillium.

Repetitive Elements

The total percentage of repetitive elements in SPG-F15 (9.82%) and in SPG-F1 (2.90%) were within the typical range for both continental and marine fungi (3% to 10%) (Galagan et al.,

2005). Transposable elements made up the majority of the repeats in both genomes, but most

(~78% SPG-F15; ~85% SPG-F1) of these TEs were unclassified. A high proportion of unclassifiable TEs is not uncommon in whole genomic studies of fungi and plants (Lu et al.,

2014, Mirouze & Vitte, 2014, Amselem et al., 2015, Castanera et al., 2016). Identifying TEs is

often difficult due to their mutagenic and degenerative characteristics in the genome (Jurka et al.,

2005, Mirouze & Vitte, 2014, Castanera et al., 2016). TEs are important in eukaryotic evolution

(Castanera et al., 2016) and are known for changing gene expression and transcription as well as creating new proteins (Bureau & Wessler, 1994, Morgante et al., 2005, Thornburg et al., 2006,

Castanera et al., 2016). These responses have been correlated to stress induced by heavy metals, temperature, salinity, and concentrations of UV (Ogasawara et al., 2009, Chadha & Sharma,

2014, Makarevitch et al., 2015). TEs have also been linked to nutrient stress in plants (Secco et al., 2017). It may be possible that SPG fungi used TEs to respond to the low availability of nutrients in SPG sediments. More research on the transcription of TEs in SPG isolates under nutrient stress could provide more information on the importance of genomic TEs.

Cell Maintenance

The cellular processes predicted by Blast2GO were mostly dedicated to intracellular membrane-bounded organelles and other integral components of the membrane (Figure 2.2).

Other evidence of cell wall/membrane maintenance came from the CAZy assignments. There was a high abundance of CAZy family GH13 in both SPG-F1 and SPG-F15 (Figure A.1, Figure

A.2). This enzyme family is related to the production of α-1,3-Glucan and β-1,3-glucan which are major components of the cell wall and surfaces of conidia (spores) (Carrion et al., 2013,

Yoshimi et al., 2017). The GT2 family was the most abundant for both SPG fungi in the GT class (Figure A.1, Figure A.2). This family contains chitinases, which mediate chitin synthesis and are important for cell wall maintenance (Adams, 2004). More research is needed to determine the activity of proteins involved in cell wall maintenance as a response to cellular

stress for SPG fungi. Doing so would provide more information on how the conditions of SPG sediment effect the survival of these fungi.

KEGG metabolic analysis found that both isolates contained genes related to thiamine production. Thiamine is essential for all living organisms, but its production has also been linked to responses of cellular stress. Under oxidative, osmotic, and temperature stress, yeast have shown to produce greater amounts of thiamine (Wolak et al., 2015). Although thiamine responses to nutrient starvation have not been reported in fungi, E. coli has shown to increase thiamine production under carbon starvation (Gigliobianco et al., 2010). It is possible that both

SPG fungi utilize thiamine to combat stressful conditions, especially under carbon starvation due to the low (<0.02 wt%) TOC in SPG sediments.

Assimilation of sulfate and nitrate was also present in both SPG-F1 and SPG-F15 based on KEGG analysis. Nitrogen and sulfur are important for cell function since they are utilized in the production of amino acids. Nitrate is assimilated in fungi if ammonia, glutamine, and glutamate are not available (Marzluf, 1997). Sulfate assimilation ultimately creates cysteine or methionine, two amino acids important for cell growth maintenance (Marzluf, 1997). Ammonia was not reported in SPG sediments, but both nitrate and sulfate were (Scientists, 2011). It is likely that in SPG sediments, SPG-F1 and SPG-F15 could have utilized nitrate and sulfate for assimilatory metabolic demands.

Carbon Cycling

The South Pacific Gyre is the furthest away from productive oceans regions and continents than any other place on Earth (Scientists, 2011). Any organic carbon that makes it to the bottom of the gyre is consumed in the first layer of sediment. What is left behind is

recalcitrant carbon which is continually stored deeper in the sediment over time (D'Hondt et al.,

2009). Microbial cells in SPG sediments had very little organic carbon to metabolize because the majority of the carbon is inaccessible or recalcitrant (Scientists, 2011). Similarly, deep North Sea sediments had high concentrations of recalcitrant sources such as aromatic and unsaturated phenolic compounds (Oni et al., 2015). These compounds likely contained wood-derived plant matter such as lignin, lignocellulose, and tannins due to inputs of sediment from land (Oni et al.,

2015).

Fungi are well-known for degradation of recalcitrant carbon such as, polycyclic aromatic hydrocarbons (PAH), lignin, lignocellulose, and carbonate in continental and marine environments (Verrecchia, 2000, Da Silva et al., 2003, Gubernatorova & Dolgonosov, 2010,

Sanyal et al., 2016). Fungi have enzymes that can break apart the aromatic rings that make up recalcitrant carbon (van den Brink & de Vries, 2011). Due to the similarity of marine subsurface fungi to continental and coastal fungi, it has been proposed that marine subsurface fungi can metabolize recalcitrant carbon in deeply buried marine sediments if they are active (Edgcomb et al., 2011, Richards et al., 2012, Orsi et al., 2013). Here, we show multiple genes and enzymes capable of degrading recalcitrant carbon (e.g., carbonate, lignin, PAH) in the two isolates from

SPG sediments.

Based on GO ontology analysis, we found that a majority of biological and molecular GO assignments were related to the degradation of aromatic and cyclic compounds in both SPG-F1 and SPG-F15. Recalcitrant carbon is largely comprised of aromatic rings and so it is likely that this metabolism may be beneficial in oligotrophic subsurface sediments where labile carbon is not as abundant. KEGG metabolic analysis of SPG fungi found sequences related to enzymes in thiamine metabolism, xenobiotic metabolism by cytochrome P450, and glyoxylate and

dicarboxylate metabolism. Thiamine (also known as vitamin B1) is essential for carbohydrate metabolism and has been shown to play a role in fermentation by Aspergillus nidulans (Shimizu et al., 2016). Xenobiotic metabolism includes the metabolism of benzo[a]pyrene and other PAHs by cytochrome P450 enzymes which has been documented heavily in filamentous fungi (van den

Brink & de Vries, 2011). Cytochrome P450 enzymes are not specific to hydrocarbon degradation and have been shown to mediate the initial breaking of the rings in lignin; whereas, lignolytic enzymes degrade the rest of the compound (Bezalel et al., 1996). Cytochrome P450 enzymes could be important to SPG fungi in the initial stages of recalcitrant carbon degradation in the sediment.

Oxalic acid production in the glyoxylate and dicarboxylate metabolism pathway is one of the main organic acids produced by fungi (Gadd, 1999). In both terrestrial and marine environments, fungi use oxalic acid to degrade calcium carbonate in order to gain access to important minerals such as iron, manganese, and phosphate that are needed for growth

(Verrecchia, 2000). Once these minerals have been released from the calcium carbonate mineral complex, the calcium is then precipitated out onto the fungal hyphae and carbon dioxide is released (Verrecchia, 2000, Gadd, 2007, Gleason et al., 2017). Enzymes needed for complete production of oxalic acid were found in both SPG fungi; specifically, isocitrate lyase which breaks down isocitrate into glyoxylate and succinate (Munir et al., 2001), malate synthase which converts glyoxylate into malate (Munir et al., 2001), and malate dehydrogenase (Labrou &

Clonis, 1997) which converts malate into oxalic acid. If SPG fungi can actively grow in SPG sediments, they may have been able to use oxalic acid to release minerals from the calcium carbonate in the sediments. This evidence highlights the potential important role fungi have in the transformation of calcium carbonate in oligotrophic subsurface sediments.

Cellulose, hemicellulose, pectin, and lignin comprise the main composition of cell walls of plants and comprise the important components of natural lignocellulosic materials. The double bonded rings in the chemical structure of lignocellulose makes it inaccessible to most microorganisms (Cragg et al., 2015). A combination of CAZy enzymes such as laccases, peroxidases, hydrolases, and monooxygenases (Van Dyk & Pletschke, 2012, Cragg et al., 2015) are involved in the degradation of lignocellulose. Evidence of these enzymes was found in both

SPG fungi. The two most abundant AA families in both isolates, AA3 (glucose-methanol-choline oxidoreductase) and AA7 (glucooligosaccharide oxidase), have been documented in wood- decaying fungi for the oxidation of carbohydrates in lignocellulose (Levasseur et al., 2013, Riley et al., 2014 2014, Takahashi et al., 2015). Lignin specific degrading enzymes AA1 (laccase),

AA2 (peroxidases), and AA13 (monooxygenases) found in both SPG genomes, have also been reported in wood-decaying, white-rot fungi (Riley et al., 2014). Other lignocellulose degrading enzymes found in families GH3 and GH5, were abundant in both genomes. GH3 is a β-

Glucosidase/β-xylosidase and GH5 is an endoglucanase that have both been reported in wood decaying fungi (Nagy et al., 2016, Schneider et al., 2016). It is apparent that the genomes of

SPG-F1 and SPG-F15 have many genes involved the degradation of double bonded, aromatic compounds found in different recalcitrant carbon sources. Both SPG isolates are potentially important members of the carbon cycle if they metabolize and transform the recalcitrant carbon in SPG sediments; therefore, future studies of carbon cycling in the marine subsurface should take into account the carbon recycled by fungi.

Summary

The analysis of two fungal genomes from South Pacific Gyre nutrient-limited sediments has expanded what is known about their metabolic capabilities and survivability in extreme environments. Here we present evidence that SPG fungi have the potential to degrade recalcitrant carbon in SPG subsurface sediments. Other evidence highlights potential cell maintenance genes that would be important for survival in the oligotrophic marine subsurface. Overall, this study provides evidence for an important question about the influence marine subsurface fungi have on the global carbon cycle and highlights the need for fungi to be included in future marine subsurface biomass estimates.

REFERENCES

Abellana M, Sanchis V & Ramos AJ (2001) Effect of water activity and temperature on growth of three Penicillium species and Aspergillus flavus on a sponge cake analogue. International Journal of Food Microbiology 71: 151-157.

Adams DJ (2004) Fungal cell wall chitinases and glucanases. Microbiology 150: 2029-2035.

Albertyn J, Hohmann S & Prior BA (1994) Characterization of the osmotic-stress response inSaccharomyces cerevisiae: osmotic stress and glucose repression regulate glycerol-3-phosphate dehydrogenase independently. Current Genetics 25: 12-18.

Amselem J, Lebrun M-H & Quesneville H (2015) Whole genome comparative analysis of transposable elements provides new insight into mechanisms of their inactivation in fungal genomes. BMC Genomics 16: 141.

Andersen RA (2005) Algal culturing techniques. Elsevier.

Arthur H & Watson K (1976) Thermal adaptation in yeast: growth temperatures, membrane lipid, and cytochrome composition of psychrophilic, mesophilic, and thermophilic yeasts. Journal of Bacteriology 128: 56-68.

Atkinson CA, Jolley DF & Simpson SL (2007) Effect of overlying water pH, dissolved oxygen, salinity and sediment disturbances on metal release and sequestration from metal contaminated marine sediments. Chemosphere 69: 1428-1437.

Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S & Prjibelski AD (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. Journal of computational biology 19: 455-477.

Bao W, Kojima KK & Kohany O (2015) Repbase Update, a database of repetitive elements in eukaryotic genomes. Mobile DNA 6: 11.

Bar-On YM, Phillips R & Milo R (2018) The biomass distribution on Earth. Proceedings of the National Academy of Sciences 201711842.

Behrenfeld MJ & Falkowski PG (1997) Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and oceanography 42: 1-20.

Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Ostell J, Pruitt KD & Sayers EW (2017) GenBank. Nucleic acids research.

Berbee ML & Taylor JW (1992) Two ascomycete classes based on fruiting-body characters and ribosomal DNA sequence. Molecular Biology and Evolution 9: 278-284.

Bezalel L, Hadar Y & Cerniglia CE (1996) Mineralization of Polycyclic Aromatic Hydrocarbons by the White Rot Fungus Pleurotus ostreatus. Applied and environmental microbiology 62: 292- 295.

Biddle JF, Fitz-Gibbon S, Schuster SC, Brenchley JE & House CH (2008) Metagenomic signatures of the Peru Margin subseafloor biosphere show a genetically distinct environment. Proceedings of the National Academy of Sciences 105: 10583.

Borneman J & Hartin RJ (2000) PCR primers that amplify fungal rRNA genes from environmental samples. Applied and environmental microbiology 66: 4356-4360.

Bose T, Reynolds DR & Berbee ML (2014) Common, unsightly and until now undescribed: Fumiglobus pieridicola sp. nov., a sooty mold infesting Pieris japonica from western North America. Mycologia 106: 746-756.

Braun U, Crous PW, Dugan F, Groenewald JZ & Sybren De Hoog G (2003) Phylogeny and taxonomy of Cladosporium-like hyphomycetes, including Davidiella gen. nov., the teleomorph of Cladosporium s. str. Mycological Progress 2: 3-18.

Bureau TE & Wessler SR (1994) Mobile inverted-repeat elements of the Tourist family are associated with the genes of many cereal grasses. Proceedings of the National Academy of Sciences 91: 1411.

Burgaud G, Le Calvez T, Arzur D, Vandenkoornhuyse P & Barbier G (2009) Diversity of culturable marine filamentous fungi from deep-sea hydrothermal vents. Environmental Microbiology 11: 1588-1600.

Carrion SdJ, Leal SM, Ghannoum MA, Aimanianda V, Latgé J-P & Pearlman E (2013) The RodA Hydrophobin on <em>Aspergillus fumigatus</em> Spores Masks Dectin-1–

and Dectin-2–Dependent Responses and Enhances Fungal Survival In Vivo. The Journal of Immunology.

Castanera R, López-Varas L, Borgognone A, LaButti K, Lapidus A, Schmutz J, Grimwood J, Perez G, Pisabarro AG & Grigoriev IV (2016) Transposable elements versus the fungal genome: impact on whole-genome architecture and transcriptional profiles. PLoS genetics 12: e1006108.

Chadha S & Sharma M (2014) Transposable elements as stress adaptive capacitors induce genomic instability in fungal pathogen Magnaporthe oryzae. PLoS One 9: e94415.

Chandralata R & Raghukumar S (1998) Barotolerance of fungi isolated from deep-sea sediments of the Indian Ocean. Aquatic Microbial Ecology 15: 153-163.

Chikhi R & Medvedev P (2013) Informed and automated k-mer size selection for genome assembly. Bioinformatics 30: 31-37.

Choi Y-W, Hyde KD & Ho W (1999) Single spore isolation of fungi. Fungal diversity.

Conesa A, Götz S, García-Gómez JM, Terol J, Talón M & Robles M (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21: 3674-3676.

Consortium U (2018) UniProt: the universal protein knowledgebase. Nucleic acids research 46: 2699.

Cowie GL & Hedges JI (1994) Biochemical indicators of diagenetic alteration in natural organic matter mixtures.

Cragg SM, Beckham GT, Bruce NC, et al. (2015) Lignocellulose degradation mechanisms across the Tree of Life. Current Opinion in Chemical Biology 29: 108-119.

D'Hondt S, Spivack AJ, Pockalny R, Ferdelman TG, Fischer JP, Kallmeyer J, Abrams LJ, Smith DC, Graham D & Hasiuk F (2009) Subseafloor sedimentary life in the South Pacific Gyre. Proceedings of the National Academy of Sciences 106: 11651-11656.

D'Hondt SL, Jørgensen, B.B., Miller, D.J., et al. (2003) Leg 201 summary. Proceedings of the Ocean Drilling Program Initial Report.

Da Silva M, Cerniglia CE, Pothuluri JV, Canhos VP & Esposito E (2003) Screening filamentous fungi isolated from estuarine sediments for the ability to oxidize polycyclic aromatic hydrocarbons. World Journal of Microbiology and Biotechnology 19: 399-405.

Damare S, Raghukumar C & Raghukumar S (2006) Fungi in deep-sea sediments of the Central Indian Basin. Deep Sea Research Part I: Oceanographic Research Papers 53: 14-27. de Oliveira TB, Gomes E & Rodrigues A (2015) Thermophilic fungi in the new age of fungal taxonomy. Extremophiles 19: 31-37. de Vries RP, Riley R, Wiebenga A, Aguilar-Osorio G, Amillis S, Uchima CA, Anderluh G, Asadollahi M, Askin M & Barry K (2017) Comparative genomics reveals high biological diversity and specific adaptations in the industrially and medically important fungal genus Aspergillus. Genome biology 18: 28.

Dhakar K, Sharma A & Pandey A (2014) Cold, pH and salt tolerant Penicillium spp. inhabit the high altitude soils in Himalaya, India. World Journal of Microbiology and Biotechnology 30: 1315-1324.

Du H & Huang G (2016) Environmental pH adaption and morphological transitions in Candida albicans. Current genetics 62: 283-286.

Edgcomb VP, Beaudoin D, Gast R, Biddle JF & Teske A (2011) Marine subsurface eukaryotes: the fungal majority. Environmental microbiology 13: 172-183.

Forsyth DM & Caley P (2006) Testing the irruptive paradigm of large-herbivore dynamics. Ecology 87: 297-303.

Fulthorpe C, Hoyanagi K & Blum P the Expedition 317 Scientists (2011). Site U1352. Vol. 317 p.^pp.

Gadd GM (1999) Fungal production of citric and oxalic acid: importance in metal speciation, physiology and biogeochemical processes. Advances in microbial physiology, Vol. 41 p.^pp. 47- 92. Elsevier.

Gadd GM (2007) Geomycology: biogeochemical transformations of rocks, minerals, metals and radionuclides by fungi, bioweathering and bioremediation. Mycological Research 111: 3-49.

Galagan JE, Henn MR, Ma L-J, Cuomo CA & Birren B (2005) Genomics of the fungal kingdom: insights into eukaryotic biology. Genome research 15: 1620-1631.

Gigliobianco T, Lakaye B, Wins P, El Moualij B, Zorzi W & Bettendorff L (2010) Adenosine thiamine triphosphate accumulates in Escherichia coli cells in response to specific conditions of metabolic stress. BMC microbiology 10: 148.

Gleason FH, Gadd GM, Pitt JI & Larkum AWD (2017) The roles of endolithic fungi in bioerosion and disease in marine ecosystems. I. General concepts. Mycology 8: 205-215.

Gonçalves VN, Campos LS, Melo IS, Pellizari VH, Rosa CA & Rosa LH (2013) Penicillium solitum: a mesophilic, psychrotolerant fungus present in marine sediments from Antarctica. Polar Biology 36: 1823-1831.

Grigoriev IV, Nikitin R, Haridas S, Kuo A, Ohm R, Otillar R, Riley R, Salamov A, Zhao X & Korzeniewski F (2013) MycoCosm portal: gearing up for 1000 fungal genomes. Nucleic acids research 42: D699-D704.

Gubernatorova T & Dolgonosov B (2010) Modeling the biodegradation of multicomponent organic matter in an aquatic environment: 3. Analysis of lignin degradation mechanisms. Water Resources 37: 332-346.

Gueidan C, Villaseñor CR, de Hoog GS, Gorbushina AA, Untereiner WA & Lutzoni F (2008) A rock-inhabiting ancestor for mutualistic and pathogen-rich fungal lineages. Studies in Mycology 61: 111-119.

Gunde-Cimerman N, Sonjak S, Zalar P, Frisvad JC, Diderichsen B & Plemenitaš A (2003) Extremophilic fungi in arctic ice: a relationship between adaptation to low temperature and water activity. Physics and Chemistry of the Earth, Parts A/B/C 28: 1273-1278.

Gurevich A, Saveliev V, Vyahhi N & Tesler G (2013) QUAST: quality assessment tool for genome assemblies. Bioinformatics 29: 1072-1075.

Hagiwara D, Sakai K, Suzuki S, Umemura M, Nogawa T, Kato N, Osada H, Watanabe A, Kawamoto S & Gonoi T (2017) Temperature during conidiation affects stress tolerance, pigmentation, and trypacidin accumulation in the conidia of the airborne pathogen Aspergillus fumigatus. PloS one 12: e0177050.

Hajna A (1945) Triple-sugar iron agar medium for the identification of the intestinal group of bacteria. Journal of bacteriology 49: 516.

Hartley IP, Heinemeyer A & Ineson P (2007) Effects of three years of soil warming and shading on the rate of soil respiration: substrate availability and not thermal acclimation mediates observed response. Global Change Biology 13: 1761-1770.

Hassan N, Rafiq M, Hayat M, Shah AA & Hasan F (2016) Psychrophilic and psychrotrophic fungi: a comprehensive review. Reviews in Environmental Science and Bio/Technology 15: 147- 172.

Ho W-C & Ko W-H (1997) A simple method for obtaining single-spore isolates of fungi. Botanical Bulletin of Academia Sinica 38.

Hoehler TM & Jørgensen BB (2013) Microbial life under extreme energy limitation. Nature Reviews Microbiology 11: 83-94.

Hoffmann K, Telle S, Walther G, Eckart M, Kirchmair M, Prillinger H, Prazenica A, Newcombe G, Dölz F & Papp T (2009) Diversity, genotypic identification, ultrastructural and phylogenetic characterization of zygomycetes from different ecological habitats and climatic regions: limitations and utility of nuclear ribosomal DNA barcode markers. Current advances in molecular mycology Nova Science Publishers, Inc, New York 263-312.

Holt C & Yandell M (2011) MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC bioinformatics 12: 491.

Hutchinson GE (1948) Circular causal systems in ecology. Annals of the New York Academy of Sciences 50: 221-246.

Jahnke RA (1996) The global ocean flux of particulate organic carbon: Areal distribution and magnitude. Global biogeochemical cycles 10: 71-88.

Jones EG (2000) Marine fungi: some factors influencing biodiversity. Fungal Diversity 4: 53-73.

Jørgensen BB (1982) Mineralization of organic matter in the sea bed—the role of sulphate reduction. Nature 296: 643-645.

Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O & Walichiewicz J (2005) Repbase Update, a database of eukaryotic repetitive elements. Cytogenetic and Genome Research 110: 462-467.

Kallmeyer J, Pockalny R, Adhikari RR, Smith DC & D’Hondt S (2012) Global distribution of microbial abundance and biomass in subseafloor sediment. Proceedings of the National Academy of Sciences 109: 16213-16216.

Kathiresan K & Manivannan S (2006) -Amylase production by Penicillium fellutanum isolated from mangrove rhizosphere soil. African journal of Biotechnology 5.

Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S & Duran C (2012) Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28: 1647-1649.

Kendrick B (2001) Fungi and the history of mycology. eLS.

Kirschbaum MU (2004) Soil respiration under prolonged soil warming: are rate reductions caused by acclimation or substrate loss? Global Change Biology 10: 1870-1877.

Knapp J & Clark V (1984) Anaerobic growth of Neisseria gonorrhoeae coupled to nitrite reduction. Infection and immunity 46: 176-181.

Kogej T, Gorbushina AA & Gunde-Cimerman N (2006) Hypersaline conditions induce changes in cell-wall melanization and colony structure in a halophilic and a xerophilic black yeast species of the genus Trimmatostroma. Mycological research 110: 713-724.

Koutsovoulos G, Makepeace B, Tanya VN & Blaxter M (2014) Palaeosymbiosis revealed by genomic fossils of Wolbachia in a strongyloidean nematode. PLoS genetics 10: e1004397.

Krantz M, Becit E & Hohmann S (2006) Comparative genomics of the HOG-signalling system in fungi. Current genetics 49: 137-151.

Krüger M, Krüger C, Walker C, Stockinger H & Schüßler A (2011) Phylogenetic reference data for systematics and phylotaxonomy of arbuscular mycorrhizal fungi from phylum to species level. New Phytologist 193: 970-984.

Kunčič MK, Kogej T, Drobne D & Gunde-Cimerman N (2010) Morphological response of the halophilic fungal genus Wallemia to high salinity. Applied and environmental microbiology 76: 329-337.

Kurtzman Cletus P & Robnett Christie J (2006) Phylogenetic relationships among yeasts of the ‘Saccharomyces complex’ determined from multigene sequence analyses. FEMS Yeast Research 3: 417-432.

Labrou NE & Clonis YD (1997) l-Malate dehydrogenase fromPseudomonas stutzeri: purification and characterization. Archives of biochemistry and biophysics 337: 103-114.

Lamb TM, Xu W, Diamond A & Mitchell AP (2000) Alkaline response genes of S. cerevisiae and their relationship to the RIM101 pathway. Journal of Biological Chemistry.

Larsen H (1986) Halophilic and halotolerant microorganisms-an overview and historical perspective. FEMS Microbiology Letters 39: 3-7.

Levasseur A, Drula E, Lombard V, Coutinho PM & Henrissat B (2013) Expansion of the enzymatic repertoire of the CAZy database to integrate auxiliary redox enzymes. Biotechnology for biofuels 6: 41.

Levine B & Klionsky DJ (2004) Development by Self-Digestion: Molecular Mechanisms and Biological Functions of Autophagy. Developmental Cell 6: 463-477.

Li H, Zhang Y, Gao Y, Lan Y, Yin X & Huang L (2016) Characterization of UGPase from Aureobasidium pullulans NRRL Y-12974 and Application in Enhanced Pullulan Production. Applied Biochemistry and Biotechnology 178: 1141-1153.

Liu CH, Huang X, Xie TN, Duan N, Xue YR, Zhao TX, Lever MA, Hinrichs KU & Inagaki F (2017) Exploration of cultivable fungal communities in deep coal-bearing sediments from∼ 1.3 to 2.5 km below the ocean floor. Environmental microbiology 19: 803-818.

Liu WC, Li CQ, Zhu P, Yang JL & Cheng KD (2010) Phylogenetic diversity of culturable fungi associated with two marine sponges: Haliclona simulans and Gelliodes carnosa, collected from the Hainan Island coastal waters of the South China Sea. Fungal Diversity 42: 1-15.

Lu M-YJ, Fan W-L, Wang W-F, Chen T, Tang Y-C, Chu F-H, Chang T-T, Wang S-Y, Li M-y & Chen Y-H (2014) Genomic and transcriptomic analyses of the medicinal fungus Antrodia

cinnamomea for its metabolite biosynthesis and sexual development. Proceedings of the National Academy of Sciences 111: E4743-E4752.

Luo J-J, Ding J-F, Li G-W, Zheng T-L & Luo Z-H (2014) Characterization of a formaldehyde degrading fungus Penicillium chrysogenum DY-F2 isolated from deep sea sediment. International Biodeterioration & Biodegradation 89: 45-49.

Maeda T (2012) The signaling mechanism of ambient pH sensing and adaptation in yeast and fungi. The FEBS Journal 279: 1407-1413.

Magan N & Lacey J (1984) Effect of temperature and pH on water relations of field and storage fungi. Transactions of the British Mycological Society 82: 71-81.

Mahendiran B, Duraisamy V & Malarselvi AM (2013) Production, Optimization, Purification, Testing Anti-Microbial and Dye Decolorizing Properties of Penicillin G Acylase from Penicillium chrysogenum. European Journal of Biotechnology and Bioscience 1: 29-36.

Maheshwari R, Bharadwaj G & Bhat MK (2000) Thermophilic fungi: their physiology and enzymes. Microbiology and molecular biology reviews 64: 461-488.

Makarevitch I, Waters AJ, West PT, Stitzer M, Hirsch CN, Ross-Ibarra J & Springer NM (2015) Transposable elements contribute to activation of maize genes in response to abiotic stress. PLoS genetics 11: e1004915.

Makarieva AM, Gorshkov VG, Li B-L, Chown SL, Reich PB & Gavrilov VM (2008) Mean mass-specific metabolic rates are strikingly similar across life's major domains: evidence for life's metabolic optimum. Proceedings of the National Academy of Sciences 105: 16994-16999.

Marzluf GA (1997) Molecular genetics of sulfur assimilation in filamentous fungi and yeast. Annual Reviews in Microbiology 51: 73-96.

Marzluf GA (1997) Genetic regulation of nitrogen metabolism in the fungi. Microbiology and Molecular Biology Reviews 61: 17-32.

Mason MM (1935) A comparison of the maximal growth rates of various bacteria under optimal conditions. Journal of bacteriology 29: 103.

Meletiadis J, Meis JF, Mouton JW & Verweij PE (2001) Analysis of growth characteristics of filamentous fungi in different nutrient media. Journal of Clinical Microbiology 39: 478-484.

Miller KI, Qing C, Sze DM-Y, Roufogalis BD & Neilan BA (2012) Culturable Endophytes of Medicinal Plants and the Genetic Basis for Their Bioactivity. Microbial Ecology 64: 431-449.

Mirouze M & Vitte C (2014) Transposable elements, a treasure trove to decipher epigenetic variation: insights from Arabidopsis and crop epigenomes. Journal of experimental botany 65: 2801-2812.

Morgante M, Brunner S, Pea G, Fengler K, Zuccolo A & Rafalski A (2005) Gene duplication and exon shuffling by helitron-like transposons generate intraspecies diversity in maize. Nature Genetics 37: 997.

Morono Y, Terada T, Kallmeyer J & Inagaki F (2013) An improved cell separation technique for marine subsurface sediments: applications for high-throughput analysis using flow cytometry and cell sorting. Environmental microbiology 15: 2841-2849.

Mouton M, Postma F, Wilsenach J & Botha A (2012) Diversity and characterization of culturable fungi from marine sediment collected from St. Helena Bay, South Africa. Microbial ecology 64: 311-319.

Munir E, Yoon J-J, Tokimatsu T, Hattori T & Shimada M (2001) New role for glyoxylate cycle enzymes in wood-rotting basidiomycetes in relation to biosynthesis of oxalic acid. Journal of wood science 47: 368-373.

Nagy LG, Riley R, Tritt A, et al. (2016) Comparative Genomics of Early-Diverging Mushroom- Forming Fungi Provides Insights into the Origins of Lignocellulose Decay Capabilities. Molecular Biology and Evolution 33: 959-970.

Nayak SS, Gonsalves V & Nazareth SW (2012) Isolation and salt tolerance of halophilic fungi from mangroves and solar salterns in Goa-India.

Nielsen JC, Grijseels S, Prigent S, Ji B, Dainat J, Nielsen KF, Frisvad JC, Workman M & Nielsen J (2017) Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species. Nature Microbiology 2: 17044.

Oberson J, Rawyler A, Brändle R & Canevascini G (1999) Analysis of the heat-shock response displayed by two Chaetomium species originating from different thermal environments. Fungal Genetics and Biology 26: 178-189.

Ogasawara H, Obata H, Hata Y, Takahashi S & Gomi K (2009) Crawler, a novel Tc1/mariner- type transposable element in Aspergillus oryzae transposes under stress conditions. Fungal Genetics and Biology 46: 441-449.

Ogawa H, Wakabayashi K, Goto K & Okada G (2005) Multilocus DNA sequence analyses for the identification of Arthrinium and its allies. Unpublished: Direct submission to GenBank.

Oliveira M, Amorim MI, Ferreira E, Delgado L & Abreu I (2010) Main airborne Ascomycota spores: characterization by culture, spore morphology, ribosomal DNA sequences and enzymatic analysis. Applied Microbiology and Biotechnology 86: 1171-1181.

Oni OE, Schmidt F, Miyatake T, Kasten S, Witt M, Hinrichs K-U & Friedrich MW (2015) Microbial communities and organic matter composition in surface and subsurface sediments of the Helgoland mud area, North Sea. Frontiers in microbiology 6.

Orcutt BN, LaRowe DE, Biddle JF, Colwell FS, Glazer BT, Reese BK, Kirkpatrick JB, Lapham LL, Mills HJ & Sylvan JB (2013) Microbial activity in the marine deep biosphere: progress and prospects. Frontiers in microbiology 4.

Orsi W, Biddle JF & Edgcomb V (2013) Deep sequencing of subseafloor eukaryotic rRNA reveals active fungi across marine subsurface provinces. PLoS One 8: e56335.

Orsi WD, Richards TA & Santoro AE (2015) Cellular maintenance processes that potentially underpin the survival of subseafloor fungi over geological timescales. Estuarine, Coastal and Shelf Science 164: A1-A9.

Orsi WD, Edgcomb VP, Christman GD & Biddle JF (2013) Gene expression in the deep biosphere. Nature 499: 205-208.

Pachiadaki MG, Rédou V, Beaudoin DJ, Burgaud G & Edgcomb VP (2016) Fungal and prokaryotic activities in the marine subsurface biosphere at Peru margin and Canterbury basin inferred from RNA-Based analyses and microscopy. Frontiers in microbiology 7.

Parkes RJ, Cragg B, Roussel E, Webster G, Weightman A & Sass H (2014) A review of prokaryotic populations and processes in sub-seafloor sediments, including biosphere: geosphere interactions. Marine Geology 352: 409-425.

Passarini MR, Rodrigues MV, da Silva M & Sette LD (2011) Marine-derived filamentous fungi and their potential application for polycyclic aromatic hydrocarbon bioremediation. Marine pollution bulletin 62: 364-370.

Peñalva MA, Tilburn J, Bignell E & Arst Jr HN (2008) Ambient pH gene regulation in fungi: making connections. Trends in microbiology 16: 291-300.

Peng RH, Xiong AS, Xue Y, Fu XY, Gao F, Zhao W, Tian YS & Yao QH (2008) Microbial biodegradation of polyaromatic hydrocarbons. FEMS microbiology reviews 32: 927-955.

Petelenz-Kurdziel E, Eriksson E, Smedh M, Beck C, Hohmann S & Goksör M (2011) Quantification of cell volume changes upon hyperosmotic stress in Saccharomyces cerevisiae. Integrative Biology 3: 1120-1126.

Pinheiro J, Bates D, DebRoy S, Sarkar D, Heisterkamp S, Van Willigen B & Maintainer R (2017) Package ‘nlme’. Linear and nonlinear mixed effects models 3-1.

Pitt JI (1973) An appraisal of identification methods for Penicillium species: novel taxonomic criteria based on temperature and water relations. Mycologia 1135-1157.

Plemenitaš A, Lenassi M, Konte T, Kejžar A, Zajc J, Gostinčar C & Gunde-Cimerman N (2014) Adaptation to high salt concentrations in halotolerant/halophilic fungi: a molecular perspective. Frontiers in microbiology 5: 199.

Raghukumar C, Raghukumar S, Sheelu G, Gupta S, Nath BN & Rao B (2004) Buried in time: culturable fungi in a deep-sea sediment core from the Chagos Trench, Indian Ocean. Deep Sea Research Part I: Oceanographic Research Papers 51: 1759-1768.

Rajasekaran A & Maheshwari R (1993) Thermophilic fungi: an assessment of their potential for growth in soil. Journal of biosciences 18: 345.

Rédou V, Navarri M, Meslet-Cladière L, Barbier G & Burgaud G (2015) Species richness and adaptation of marine fungi from deep-subseafloor sediments. Applied and environmental microbiology 81: 3571-3583.

Richards TA, Jones MD, Leonard G & Bass D (2012) Marine fungi: their ecology and molecular diversity. Annual review of marine science 4: 495-522.

Riley R, Salamov AA, Brown DW, et al. (2014) Extensive sampling of basidiomycete genomes demonstrates inadequacy of the white-rot/brown-rot paradigm for wood decay fungi. Proceedings of the National Academy of Sciences 111: 9923.

Rousk J, Brookes PC & Bååth E (2009) Contrasting soil pH effects on fungal and bacterial growth suggest functional redundancy in carbon mineralization. Applied and Environmental Microbiology 75: 1589-1596.

Saito H & Posas F (2012) Response to Hyperosmotic Stress. Genetics 192: 289.

Sanyal O, Shinde VL, Meena RM, Damare S & Shenoy BD (2016) The ITS-based phylogeny of fungi associated with tarballs. Marine Pollution Bulletin 113: 277-281.

Sautour M, Rouget A, Dantigny P, Divies C & Bensoussan M (2001) Prediction of conidial germination of Penicillium chrysogenum as influenced by temperature, water activity and pH. Letters in Applied Microbiology 32: 131-134.

Schneider WDH, Gonçalves TA, Uchima CA, Couger MB, Prade R, Squina FM, Dillon AJP & Camassola M (2016) Penicillium echinulatum secretome analysis reveals the fungi potential for degradation of lignocellulosic biomass. Biotechnology for biofuels 9: 66.

Schüller C, Brewster J, Alexander M, Gustin M & Ruis H (1994) The HOG pathway controls osmotic regulation of transcription via the stress response element (STRE) of the Saccharomyces cerevisiae CTT1 gene. The EMBO journal 13: 4382-4389.

Scientists E (2011) South Pacific Gyre subseafloor life. Proceedings of Integrated Ocean Drilling Program 1-108.

Secco D, Whelan J, Rouached H & Lister R (2017) Nutrient stress-induced chromatin changes in plants. Current opinion in plant biology 39: 1-7.

Selbmann L, Egidi E, Isola D, Onofri S, Zucconi L, de Hoog GS, Chinaglia S, Testa L, Tosi S & Balestrazzi A (2013) Biodiversity, evolution and adaptation of fungi in extreme environments. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology 147: 237- 246.

Shimizu M, Masuo S, Itoh E, Zhou S, Kato M & Takaya N (2016) Thiamine synthesis regulates the fermentation mechanisms in the fungus Aspergillus nidulans. Bioscience, Biotechnology, and Biochemistry 80: 1768-1775.

Simao FA, Waterhouse RM, Ioannidis P, Kriventseva EV & Zdobnov EM (2015) BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31: 3210-3212.

Singh P, Raghukumar C, Verma P & Shouche Y (2010) Phylogenetic diversity of culturable fungi from the deep-sea sediments of the Central Indian Basin and their growth characteristics. Fungal Diversity 40: 89-102.

Smit A & Hubley R (2008) RepeatModeler Open-1.0. Available from http://repeatmasker.org.

Smit A, Hubley R & Green P (2017) Repeatmasker open–4.0. 2013–2015 (2013). URL http://repeatmasker.org.

SØChting U & Lutzoni F (2004) Molecular phylogenetic study at the generic boundary between the lichen-forming fungi Caloplaca and Xanthoria (Ascomycota, Teloschistaceae). Mycological Research 107: 1266-1276.

Song N, Wang F, Zhang C, Tang S, Guo J, Ju X & Smith DL (2013) Fungal Inoculation and Elevated CO2 Mediate Growth of Lolium Mutiforum and Phytolacca Americana, Metal Uptake, and Metal Bioavailability in Metal-Contaminated Soil: Evidence from DGT Measurement. International Journal of Phytoremediation 15: 268-282.

Spatafora JW, Volkmann-Kohlmeyer B & Kohlmeyer J (1998) Independent terrestrial origins of the Halosphaeriales (marine Ascomycota). American Journal of Botany 85: 1569-1580.

Stahl PD & Klug MJ (1996) Characterization and differentiation of filamentous fungi based on fatty acid composition. Applied and Environmental Microbiology 62: 4136-4146.

Stanke M & Waack S (2003) Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics 19: ii215-ii225.

Stoll D, Schmidt-Heydt M & Geisen R (2013) Differences in the regulation of ochratoxin A by the HOG pathway in Penicillium and Aspergillus in response to high osmolar environments. Toxins 5: 1282-1298.

Suárez T & Peñalva MA (1996) Characterization of a Penicillium chrysogenum gene encoding a PacC transcription factor and its binding sites in the divergent pcbAB–pcbC promoter of the penicillin biosynthetic cluster. Molecular microbiology 20: 529-540.

Sugiyama M, Ohara A & Mikawa T (1999) Molecular phylogeny of onygenalean fungi based on small subunit ribosomal DNA (SSU rDNA) sequences. Mycoscience 40: 251-258.

Takahashi K, Hirose Y, Kamimura N, Hishiyama S, Hara H, Araki T, Kasai D, Kajita S, Katayama Y & Fukuda M (2015) Membrane-associated glucose-methanol-choline oxidoreductase family enzymes PhcC and PhcD are essential for enantioselective catabolism of dehydrodiconiferyl alcohol. Applied and environmental microbiology 81: 8022-8036.

Takami H (1999) Isolation and characterization of microorganisms from deep-sea mud. Extremophiles in deep-sea environments Springer, Tokyo 3-26.

Takami H, Inoue A, Fuji F & Horikoshi K (1997) Microbial flora in the deepest sea mud of the Mariana Trench. FEMS Microbiology Letters 152: 279-285.

Tamura M (2000) Molecular phylogeny of Aspergillus and associated teleomorphs in the Trichocomaceae (Eurotiales). Integration of modern taxonomic methods for Penicillium and Aspergillus classification.

Taniwaki MH, Pitt JI, Hocking AD & Fleet GH (2006) Comparison of hyphal length, ergosterol, mycelium dry weight, and colony diameter for quantifying growth of fungi from foods. Advances in food mycology,p.^pp. 49-67. Springer.

Ter-Hovhannisyan V, Lomsadze A, Chernoff YO & Borodovsky M (2008) Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome research 18: 1979-1990.

Thornburg BG, Gotea V & Makałowski W (2006) Transposable elements as a significant source of transcription regulating signals. Gene 365: 104-110.

Tresner H & Hayes JA (1971) Sodium chloride tolerance of terrestrial fungi. Applied Microbiology 22: 210-213.

Tsukahara T, Yamada M & Itagaki T (1966) Micromorphology of conidiospores of Aspergillus niger by electron microscopy. Microbiology and Immunology 10: 93-107.

van den Berg MA, Albang R, Albermann K, et al. (2008) Genome sequencing and analysis of the filamentous fungus Penicillium chrysogenum. Nature Biotechnology 26: 1161. van den Brink J & de Vries RP (2011) Fungal enzyme sets for plant polysaccharide degradation. Applied Microbiology and Biotechnology 91: 1477.

Van Dyk J & Pletschke B (2012) A review of lignocellulose bioconversion using enzymatic hydrolysis and synergistic cooperation between enzymes—factors affecting enzymes, conversion and synergy. Biotechnology advances 30: 1458-1480.

Verrecchia EP (2000) Fungi and sediments. Microbial sediments,p.^pp. 68-75. Springer.

Wakeham SG, Lee C, Hedges JI, Hernes PJ & Peterson MJ (1997) Molecular indicators of diagenetic status in marine organic matter. Geochimica et Cosmochimica Acta 61: 5363-5369.

Wheeler KA, Hurdman BF & Pitt J (1991) Influence of pH on the growth of some toxigenic species of Aspergillus, Penicillium and Fusarium. International journal of food microbiology 12: 141-149.

Whitman WB, Coleman DC & Wiebe WJ (1998) Prokaryotes: the unseen majority. Proceedings of the National Academy of Sciences 95: 6578-6583.

Wolak N, Tomasi M, Kozik A & Rapala-Kozik M (2015) Characterization of thiamine uptake and utilization in Candida spp. subjected to oxidative stress. Acta Biochimica Polonica 62.

Wright C, Kafkewitz D & Somberg EW (1983) Eucaryote thermophily: role of lipids in the growth of Talaromyces thermophilus. Journal of bacteriology 156: 493-497.

Wu Z, Tsumura Y, Blomquist G & Wang X-R (2003) 18S rRNA Gene Variation among Common Airborne Fungi, and Development of Specific Oligonucleotide Probes for the Detection of Fungal Isolates. Applied and Environmental Microbiology 69: 5389-5397.

Yin Y, Mao X, Yang J, Chen X, Mao F & Xu Y (2012) dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Research 40: W445-W451.

Yoshimi A, Miyazawa K & Abe K (2017) Function and Biosynthesis of Cell Wall α-1, 3-Glucan in Fungi. Journal of Fungi 3: 63.

Zajc J, Zalar P, Plemenitaš A & Gunde-Cimerman N (2012) The mycobiota of the salterns. Biology of Marine Fungi,p.^pp. 133-158. Springer.

Zerbino DR & Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome research 18: 821-829.

Zhang K, Yuan-Ying S & Cai L (2013) An optimized protocol of single spore isolation for fungi. Cryptogamie, Mycologie 34: 349-356.

LIST OF APPENDICES

Table A.1. NCBI accession numbers used. GenBank Name Environment Reference ID Ctenomyces serratus FJ358347 Continental (Gueidan et al., 2008)

Fumiglobus pieridicola KC833053 Continental (Bose et al., 2014)

Aspergillus penicillioides KM582668 Coastal Marine (Liu et al., 2010)

Cladosporium allicinum AY251096 Continental (Braun et al., 2003) (SØChting & Lutzoni, Xanthoria candelaria AJ535294 Continental 2004) Chrysosporium indicum AB015780 Continental (Sugiyama et al., 1999)

Aureobasidium pullulans HM853990 Continental (Li et al., 2016)

Aspergillus terreus MG271916 N/A N/A

Umbelopsis ramanniana EU484256 Continental (Hoffmann et al., 2009)

Glomus coronatum FR773145 Continental (Krüger et al., 2011)

Aspergillus niger JN974017 N/A N/A

Penicillium oxalicum KT356199 N/A N/A

Chaetomium elatum M83257 Continental (Berbee & Taylor, 1992) (Kurtzman Cletus & Neurospora crassa AY046271 Continental Robnett Christie, 2006) Nigrospora oryzae AB220233 Continental (Ogawa et al., 2005)

Cladosporium species JQ390137 Continental (Miller et al., 2012)

Davidiella species JQ390167 Continental (Miller et al., 2012)

Cladosporium species GU322367 Continental N/A

Aspergillus versicolor AB002064 N/A (Tamura, 2000)

Emericella nidulans U77377 N/A N/A

Penicillium griseofulvum FJ717697 Atmosphere (Oliveira et al., 2010)

Penicillium griseofulvum KM605190 Coastal Marine (Liu et al., 2010)

Penicillium chrysogenum JF718786 Continental (Song et al., 2013) Marine Penicillium chrysogenum KM222236 (Rédou et al., 2015) Subsurface Penicillium AF548085 Atmosphere (Wu et al., 2003) brevicompactum Penicillium Marine KM222210 (Rédou et al., 2015) brevicompactum Subsurface

Table A.2. SPG-F1 media control pH and weights for 4ºC. SPG-F1 Control 4ºC Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.93 63.290 64.344 1.054 192 5.00 62.256 62.926 0.670 216 5.12 63.204 64.379 1.175 240 5.09 62.058 62.454 0.396 264 4.89 63.204 63.790 0.586 288 4.93 63.595 64.098 0.503 312 5.09 63.704 64.056 0.352 336 4.97 61.814 62.683 0.869 360 5.07 62.725 63.400 0.675 384 4.93 62.812 63.466 0.654

Table A.3. SPG-F1 culture pH and weights for 4ºC. SPG-F1 Growth 4ºC Time Avg. Std. Std. Pre – Post – Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 5.20 62.988 63.582 0.594 0 4.92 63.181 64.006 0.825 0 5.17 5.10 0.154 0.089 64.023 64.708 0.685 0.70 0.116 0.067 192 4.93 62.528 63.298 0.770 192 4.89 64.070 64.777 0.707 192 4.93 4.92 0.023 0.013 62.808 63.342 0.534 0.67 0.122 0.071 216 4.98 62.158 63.351 1.193 216 4.91 62.757 63.886 1.129 216 5.20 5.03 0.151 0.087 62.510 63.424 0.914 1.08 0.146 0.084 240 4.90 63.447 64.374 0.927 240 4.85 62.826 63.693 0.867 240 4.85 4.87 0.029 0.017 62.812 63.759 0.947 0.91 0.042 0.024 264 4.78 61.891 63.276 1.385 264 4.83 63.048 64.436 1.388 264 4.79 4.81 0.026 0.015 62.411 64.314 1.903 1.56 0.298 0.172 288 4.82 63.150 64.482 1.332 288 4.80 63.120 64.253 1.133 288 4.86 4.83 0.031 0.018 63.460 64.710 1.250 1.24 0.100 0.058 312 5.04 62.708 64.123 1.415 312 4.72 62.709 63.554 0.845 312 4.75 4.84 0.177 0.102 63.434 65.001 1.567 1.28 0.381 0.220 336 4.98 63.400 65.012 1.612 336 4.94 63.194 64.661 1.467 336 4.95 4.96 0.021 0.012 62.974 64.429 1.455 1.51 0.087 0.050 360 4.96 62.880 64.046 1.166 360 4.98 62.329 63.648 1.319 360 5.00 4.98 0.020 0.012 62.076 63.448 1.372 1.29 0.107 0.062 384 5.01 62.723 63.501 0.778 384 4.89 62.533 65.322 2.789 384 4.85 4.92 0.083 0.048 63.901 65.444 1.543 1.70 1.015 0.586

Table A.4. SPG-F15 media control pH and weights 4ºC. SPG-F15 Control 4ºC Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.77 23.661 24.104 0.443 192 4.73 23.078 23.542 0.464 238 4.84 23.370 24.003 0.633 285.5 4.85 23.573 23.666 0.093 336 4.85 22.943 23.328 0.385 433 4.85 23.790 24.238 0.448 525.5 4.72 23.554 24.010 0.456 648 5.02 23.860 24.291 0.431 694.5 4.87 23.303 23.777 0.474 718 4.82 23.761 24.357 0.596

Table A.5. SPG-F15 culture pH and weights for 4ºC. SPG-F15 Growth 4ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.86 23.840 24.331 0.491 0 4.80 22.933 23.391 0.458 0 4.82 4.83 0.031 0.018 23.658 24.137 0.479 0.48 0.017 0.010 192 4.77 23.023 23.503 0.480 192 4.82 22.656 23.016 0.360 192 4.84 4.81 0.036 0.021 23.354 23.953 0.599 0.48 0.120 0.069 238 4.80 23.495 24.090 0.595 238 4.80 23.541 24.123 0.582 238 4.84 4.81 0.023 0.013 23.688 24.343 0.655 0.61 0.039 0.022 285.5 4.79 23.762 24.118 0.356 285.5 4.85 23.887 24.192 0.305 285.5 4.82 4.82 0.030 0.017 23.438 23.659 0.221 0.29 0.068 0.039 336 4.73 23.090 24.089 0.999 336 4.69 23.065 24.266 1.201 336 4.66 4.69 0.035 0.020 22.873 24.116 1.243 1.15 0.130 0.075 433 4.64 23.563 25.705 2.142 433 4.65 23.312 25.261 1.949 433 4.65 4.65 0.006 0.003 23.085 25.229 2.144 2.08 0.112 0.065 525.5 4.56 23.154 25.915 2.761 525.5 4.55 23.452 26.284 2.832 525.5 4.55 4.55 0.006 0.003 23.428 26.275 2.847 2.81 0.046 0.027 648 4.50 23.572 26.738 3.166 648 4.47 23.536 26.405 2.869 648 4.53 4.50 0.030 0.017 24.145 26.823 2.678 2.90 0.246 0.142 694.5 4.65 23.212 25.934 2.722 694.5 4.65 23.256 25.880 2.624 694.5 4.53 4.61 0.069 0.040 23.773 26.379 2.606 2.65 0.062 0.036 718 4.59 23.548 26.280 2.732 718 4.63 23.530 25.889 2.359 718 4.48 4.57 0.078 0.045 23.914 26.728 2.814 2.64 0.243 0.140

Table A.6. Media control pH and weights for 10ºC. Media Control 10ºC Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.87 58.582 59.338 0.756 96 4.81 60.656 61.376 0.72 120 4.81 61.28 61.632 0.352 144 4.86 58.981 59.332 0.351 168 4.81 58.698 59.09 0.392 192 4.81 59.466 59.72 0.254 216 4.87 58.199 58.547 0.348 240 4.83 59.114 59.688 0.574 264 4.81 57.576 58.546 0.97 288 4.68 60.105 60.507 0.402

Table A.7. SPG-F1 culture pH and weights for 10ºC. Asterisks in the Final Weight column are values that were negative and changed to zero. SPG-F1 Growth 10ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.87 58.365 59.458 1.093 0 4.90 59.103 59.285 0.182 0 4.90 4.89 0.017 0.010 58.585 58.938 0.353 0.54 0.484 0.280 96 4.79 59.692 59.496 *0.000 96 4.80 60.414 60.160 *0.000 96 4.80 4.80 0.006 0.003 58.973 61.697 2.724 0.91 1.573 0.908 120 4.61 57.820 59.135 1.315 120 4.66 58.385 59.573 1.188 120 4.65 4.64 0.026 0.015 59.652 60.950 1.298 1.27 0.069 0.040 144 4.62 61.107 62.646 1.539 144 4.66 59.605 61.104 1.499 144 4.64 4.64 0.020 0.012 61.587 63.184 1.597 1.55 0.049 0.028 168 4.61 60.121 62.436 2.315 168 4.64 58.590 60.395 1.805 168 4.53 4.63 0.057 0.033 60.025 62.204 2.179 2.10 0.264 0.152 192 4.52 58.845 59.822 0.977 192 4.52 58.624 59.851 1.227 192 4.46 4.50 0.035 0.020 58.388 61.355 2.967 1.72 1.084 0.626 216 4.41 58.254 60.632 2.378 216 4.48 60.285 62.515 2.230 216 4.46 4.45 0.036 0.021 58.026 60.151 2.125 2.24 0.127 0.073 240 4.48 59.368 61.346 1.978 240 4.54 58.636 60.607 1.971 240 4.45 4.49 0.046 0.026 58.818 61.236 2.418 2.12 0.256 0.148 264 4.44 59.915 62.133 2.218 264 4.38 59.909 62.018 2.109 264 4.50 4.44 0.060 0.035 59.645 61.328 1.683 2.00 0.283 0.163 288 4.57 59.638 61.806 2.168 288 4.59 59.573 61.767 2.194 288 4.48 4.55 0.059 0.034 60.240 62.273 2.033 2.13 0.086 0.050

Table A.8. SPG-F15 culture pH and weights for 10ºC. Asterisks in the Final Weight column are values that were negative and changed to zero. SPG-F15 Growth 10ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.90 58.158 58.701 0.543 0 4.91 59.378 60.073 0.695 0 4.93 4.91 0.015 0.009 58.513 59.067 0.554 0.60 0.085 0.049 96 4.73 58.787 60.921 2.134 96 4.73 59.049 61.579 2.530 96 4.76 4.74 0.017 0.010 60.650 60.151 *0.000 1.55 1.361 0.786 120 4.72 60.948 62.291 1.343 120 4.74 59.899 61.074 1.175 120 4.71 4.72 0.015 0.009 61.177 62.483 1.306 1.27 0.088 0.051 144 4.63 60.786 62.467 1.681 144 4.63 60.821 62.838 2.017 144 4.69 4.65 0.035 0.020 60.730 62.376 1.646 1.78 0.205 0.118 168 4.54 58.973 60.999 2.026 168 4.59 59.008 60.878 1.870 168 4.56 4.56 0.025 0.015 58.958 61.268 2.310 2.07 0.223 0.129 192 4.53 60.185 61.101 0.916 192 4.62 60.086 62.182 2.096 192 4.57 4.57 0.045 0.026 60.258 61.947 1.689 1.57 0.599 0.346 216 4.54 59.362 61.205 1.843 216 4.45 60.109 62.370 2.261 216 4.48 4.49 0.046 0.026 60.322 62.315 1.993 2.03 0.212 0.122 240 4.47 58.751 60.999 2.248 240 4.53 59.860 60.901 1.041 240 4.47 4.49 0.035 0.020 59.258 61.453 2.195 1.83 0.682 0.394 264 4.46 59.666 61.908 2.242 264 4.43 58.665 61.514 2.849 264 4.49 4.46 0.030 0.017 59.134 61.849 2.715 2.60 0.319 0.184 288 4.57 59.896 62.260 2.364 288 4.45 59.678 61.100 1.422 288 4.53 4.52 0.061 0.035 59.700 61.645 1.945 1.91 0.472 0.272

Table A.9. Media control pH and weights for 15ºC. Media Control 15ºC Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.88 60.184 60.441 0.257 96 4.78 59.276 59.836 0.560 120 4.73 58.887 59.465 0.578 144 4.73 62.437 62.612 0.175 168 4.69 64.938 65.041 0.103 192 4.74 62.603 62.730 0.127 216 4.72 60.716 61.778 1.062 240 4.72 60.172 61.021 0.849 264 4.77 60.690 61.538 0.848 288 4.71 60.404 61.166 0.762

Table A.10. SPG-F1 culture pH and weights for 15ºC. SPG-F1 Growth 15ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.80 58.805 59.376 0.571 0 4.81 58.554 59.015 0.461 0 4.84 4.82 0.021 0.012 59.031 59.397 0.366 0.47 0.103 0.059 96 4.43 59.648 61.430 1.782 96 4.47 57.722 59.356 1.634 96 4.47 4.46 0.023 0.013 60.013 61.922 1.909 1.78 0.138 0.079 120 4.41 60.444 61.848 1.404 120 4.38 61.312 62.930 1.618 120 4.39 4.39 0.015 0.009 59.593 61.444 1.851 1.62 0.224 0.129 144 4.33 62.531 64.064 1.533 144 4.45 62.946 64.528 1.582 144 4.45 4.41 0.069 0.040 59.096 60.697 1.601 1.57 0.035 0.020 168 4.43 63.842 65.627 1.785 168 4.33 63.870 65.729 1.859 168 4.49 4.38 0.081 0.047 62.601 64.136 1.535 1.73 0.170 0.098 192 4.28 64.304 66.108 1.804 192 4.33 64.197 65.940 1.743 192 4.29 4.30 0.026 0.015 63.845 65.774 1.929 1.83 0.095 0.055 216 4.28 59.912 61.913 2.001 216 4.31 60.545 62.998 2.453 216 4.36 4.32 0.040 0.023 60.738 62.808 2.070 2.17 0.244 0.141 240 4.19 61.020 63.507 2.487 240 4.20 61.570 64.067 2.497 240 4.33 4.24 0.078 0.045 60.009 62.038 2.029 2.34 0.267 0.154 264 4.45 60.222 62.268 2.046 264 4.38 60.305 62.287 1.982 264 4.46 4.43 0.044 0.025 60.447 62.661 2.214 2.08 0.120 0.069 288 4.37 59.757 61.725 1.968 288 4.28 60.198 62.460 2.262 288 4.39 4.35 0.059 0.034 59.968 61.723 1.755 2.00 0.255 0.147

Table A.11. SPG-F15 culture pH and weights for 15ºC. Asterisks in the Final Weight column are values that were negative and changed to zero. SPG-F15 Growth 15ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 5.19 60.974 60.730 *0.000 0 5.18 57.937 58.398 0.461 0 4.86 5.08 0.188 0.108 60.597 60.387 *0.000 0.15 0.266 0.154 96 4.92 58.947 60.870 1.923 96 4.92 60.173 62.000 1.827 96 4.54 4.79 0.219 0.127 58.163 60.103 1.940 1.90 0.061 0.035 120 4.45 60.500 62.730 2.230 120 4.67 57.858 59.949 2.091 120 4.49 4.54 0.117 0.068 59.039 61.307 2.268 2.20 0.093 0.054 144 4.50 58.992 61.465 2.473 144 4.74 62.044 63.801 1.757 144 4.79 4.68 0.155 0.090 62.058 63.687 1.629 1.95 0.455 0.263 168 4.44 63.426 65.655 2.229 168 4.46 62.630 64.630 2.000 168 4.72 4.54 0.156 0.090 63.027 65.127 2.100 2.11 0.115 0.066 192 4.44 62.788 64.918 2.130 192 4.83 63.362 65.557 2.195 192 4.76 4.68 0.208 0.120 63.844 65.992 2.148 2.16 0.034 0.019 216 4.83 60.644 63.572 2.928 216 4.69 60.763 63.420 2.657 216 4.60 4.71 0.116 0.067 61.111 63.439 2.328 2.64 0.300 0.173 240 4.58 61.499 63.950 2.451 240 4.38 61.053 63.699 2.646 240 4.56 4.51 0.110 0.064 61.038 63.475 2.437 2.51 0.117 0.067 264 4.44 60.484 63.117 2.633 264 4.42 60.961 63.583 2.622 264 4.71 4.52 0.162 0.094 60.676 63.179 2.503 2.59 0.072 0.042 288 4.38 60.937 62.719 1.782 288 4.36 60.935 62.853 1.918 288 4.50 4.41 0.076 0.044 61.248 63.647 2.399 2.03 0.324 0.187

Table A.12. Media control pH and weights for 21ºC. Media Control 21ºC Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.83 58.612 59.885 1.273 24 4.70 59.621 60.068 0.447 48 4.69 60.057 60.535 0.478 72 4.72 58.113 58.553 0.440 96 4.74 59.832 60.244 0.412 120 4.80 59.601 59.922 0.321 144 4.74 58.410 58.673 0.263 168 4.80 58.765 59.221 0.456 192 4.76 58.492 58.959 0.467 216 4.81 59.963 60.218 0.255

Table A.13. SPG-F1 culture pH and weights for 21ºC. SPG-F1 Growth 21ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.75 58.042 59.440 1.398 0 4.74 59.222 60.924 1.702 0 4.76 4.75 0.010 0.006 59.574 60.459 0.885 1.33 0.413 0.238 24 4.61 60.249 61.143 0.894 24 4.61 58.558 59.592 1.034 24 4.64 4.62 0.017 0.010 57.685 58.760 1.075 1.00 0.095 0.055 48 4.49 60.583 62.066 1.483 48 4.51 59.957 61.344 1.387 48 4.53 4.51 0.020 0.012 58.823 60.313 1.490 1.45 0.058 0.033 72 4.36 58.061 59.877 1.816 72 4.43 58.112 60.046 1.934 72 4.43 4.41 0.040 0.023 57.224 58.912 1.688 1.81 0.123 0.071 96 4.43 58.633 60.355 1.722 96 4.40 57.740 59.271 1.531 96 4.46 4.42 0.030 0.017 59.012 60.758 1.746 1.67 0.118 0.068 120 4.32 59.923 61.775 1.852 120 4.49 59.160 60.573 1.413 120 4.41 4.41 0.085 0.049 59.818 61.803 1.985 1.75 0.299 0.173 144 4.29 58.562 60.281 1.719 144 4.41 57.680 59.562 1.882 144 4.37 4.36 0.061 0.035 57.930 59.944 2.014 1.87 0.148 0.085 168 4.37 58.765 61.786 3.021 168 4.38 59.116 60.679 1.563 168 4.47 4.41 0.055 0.032 59.380 60.875 1.495 2.03 0.862 0.498 192 4.39 59.864 61.490 1.626 192 4.36 57.987 59.506 1.519 192 4.26 4.34 0.068 0.039 58.868 61.084 2.216 1.79 0.375 0.217 216 4.35 58.595 60.229 1.634 216 4.26 60.469 62.056 1.587 216 4.30 4.30 0.045 0.026 58.442 60.630 2.188 1.80 0.334 0.193

Table A.14. SPG-F15 culture pH and weights for 21ºC. SPG-F15 Growth 21ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.76 59.826 61.429 1.603 0 4.79 59.257 60.583 1.326 0 4.80 4.78 0.021 0.012 60.368 61.519 1.151 1.36 0.228 0.132 24 4.64 57.947 59.155 1.208 24 4.59 60.563 62.280 1.717 24 4.61 4.61 0.025 0.015 58.133 59.478 1.345 1.42 0.263 0.152 48 4.38 60.153 62.356 2.203 48 4.48 59.781 61.085 1.304 48 4.46 4.44 0.053 0.031 58.880 60.429 1.549 1.69 0.465 0.268 72 4.42 59.635 61.715 2.080 72 4.46 59.390 61.118 1.728 72 4.42 4.43 0.023 0.013 59.392 61.031 1.639 1.82 0.233 0.135 96 4.37 58.865 60.620 1.755 96 4.42 59.089 61.180 2.091 96 4.33 4.37 0.045 0.026 58.332 60.445 2.113 1.99 0.201 0.116 120 4.52 58.504 60.019 1.515 120 4.51 57.922 59.611 1.689 120 4.52 4.52 0.006 0.003 58.645 59.996 1.351 1.52 0.169 0.098 144 4.46 59.163 60.662 1.499 144 4.44 58.559 60.183 1.624 144 4.47 4.46 0.015 0.009 59.812 61.162 1.350 1.49 0.137 0.079 168 4.46 58.472 60.246 1.774 168 4.48 59.357 60.956 1.599 168 4.42 4.45 0.031 0.018 58.410 60.105 1.695 1.69 0.088 0.051 192 4.47 58.813 60.096 1.283 192 4.43 59.692 61.226 1.534 192 4.32 4.41 0.078 0.045 59.791 61.584 1.793 1.54 0.255 0.147 216 4.43 59.943 61.851 1.908 216 4.43 57.916 59.569 1.653 216 4.33 4.40 0.058 0.033 58.860 60.224 1.364 1.64 0.272 0.157

Table A.15. Media control pH and weights for 26ºC. Media Control 26ºC Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.87 23.145 23.634 0.489 48 4.92 23.422 23.928 0.506 72 5.03 22.909 23.361 0.452 96 5.08 23.541 23.983 0.442 146 4.95 23.733 24.394 0.661 192 5.32 23.863 24.221 0.358 236 5.15 24.170 24.666 0.496 285.5 4.95 23.733 24.394 0.661 330 5.20 24.016 24.551 0.535 383.5 4.94 24.161 24.632 0.471 429 4.79 23.825 24.446 0.621 504.5 4.79 23.825 24.446 0.621

Table A.16. SPG-F1 culture pH and weights for 26ºC. SPG-F1 Growth 26ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.80 23.172 23.573 0.401 0 4.79 23.090 23.584 0.494 0 4.81 4.80 0.010 0.006 22.898 23.414 0.516 0.470 0.061 0.035 48 4.77 23.297 23.723 0.426 48 4.75 23.657 24.093 0.436 48 4.80 4.77 0.025 0.015 23.677 24.179 0.502 0.455 0.041 0.024 72 4.98 23.188 24.178 0.990 72 4.93 23.520 24.575 1.055 72 4.99 4.97 0.032 0.019 23.219 24.271 1.052 1.032 0.037 0.021 96 4.84 23.367 25.009 1.642 96 4.58 23.536 24.877 1.341 96 4.57 4.66 0.153 0.088 22.899 24.362 1.463 1.482 0.151 0.087 146 4.82 23.454 24.984 1.530 146 5.03 23.347 24.730 1.383 146 4.72 4.93 0.158 0.091 23.207 24.656 1.449 1.454 0.074 0.043 192 4.64 23.274 25.480 2.206 192 4.71 23.064 25.148 2.084 192 4.69 4.68 0.036 0.021 23.099 24.812 1.713 2.001 0.257 0.148 236 4.71 23.924 25.643 1.719 236 4.52 23.616 25.375 1.759 236 4.47 4.57 0.127 0.073 23.902 25.430 1.528 1.669 0.123 0.071 285.5 4.42 24.053 25.319 1.266 285.5 4.41 24.298 25.749 1.451 285.5 4.33 4.39 0.049 0.028 24.010 25.803 1.793 1.503 0.267 0.154 330 4.79 23.937 25.039 1.102 330 4.54 23.971 25.034 1.063 330 4.59 4.64 0.132 0.076 24.247 25.235 0.988 1.051 0.058 0.033 383.5 4.35 23.858 25.076 1.218 383.5 4.43 24.197 25.314 1.117 383.5 4.56 4.45 0.106 0.061 23.987 24.822 0.835 1.057 0.199 0.115 429 4.61 24.259 25.216 0.957 429 4.58 24.045 24.876 0.831 429 4.54 4.58 0.035 0.020 23.684 24.547 0.863 0.884 0.065 0.038 504.5 4.55 23.843 25.199 1.356 504.5 4.60 24.227 25.111 0.884

504.5 4.64 4.60 0.045 0.026 24.188 25.124 0.936 1.059 0.259 0.149

Table A.17. SPG-F15 culture pH and weights for 26ºC. SPG-F15 Growth 26ºC Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.88 23.895 24.416 0.521 0 4.87 23.655 24.187 0.532 0 4.85 4.87 0.015 0.009 23.222 23.857 0.635 0.563 0.063 0.036 48 4.69 23.777 24.559 0.782 48 4.74 23.428 24.016 0.588 48 4.72 4.72 0.025 0.015 23.805 24.516 0.711 0.694 0.098 0.057 72 4.67 22.887 24.727 1.840 72 4.52 23.426 24.980 1.554 72 4.54 4.58 0.081 0.047 23.102 24.528 1.426 1.607 0.212 0.122 96 4.64 23.772 25.494 1.722 96 4.43 23.073 24.985 1.912 96 4.42 4.50 0.124 0.072 23.077 25.031 1.954 1.863 0.124 0.071 146 4.45 23.064 25.023 1.959 146 4.92 23.123 24.671 1.548 146 4.85 4.74 0.254 0.146 23.161 24.813 1.652 1.720 0.214 0.123 192 4.52 23.542 26.167 2.625 192 4.50 23.931 26.517 2.586 192 4.49 4.50 0.015 0.009 23.795 26.194 2.399 2.537 0.121 0.070 236 4.61 23.610 26.075 2.465 236 4.33 23.773 26.591 2.818 236 4.33 4.42 0.162 0.093 23.923 26.495 2.572 2.618 0.181 0.105 285.5 4.63 24.060 24.936 0.876 285.5 4.58 24.624 25.191 0.567 285.5 4.64 4.62 0.032 0.019 23.877 24.349 0.472 0.640 0.211 0.122 330 4.55 24.226 26.253 2.027 330 4.57 23.997 25.253 1.256 330 4.53 4.55 0.020 0.012 24.142 25.646 1.504 1.596 0.394 0.227 383.5 4.52 23.934 25.077 1.143 383.5 4.46 23.852 24.808 0.956 383.5 4.42 4.47 0.050 0.029 24.199 26.418 2.219 1.439 0.682 0.394 429 4.35 24.029 25.388 1.359 429 4.41 24.117 25.542 1.425 429 4.38 4.38 0.030 0.017 23.695 25.252 1.557 1.447 0.101 0.058 504.5 4.53 24.021 25.511 1.490 504.5 4.54 24.414 25.899 1.485

504.5 4.43 4.50 0.061 0.035 23.950 25.507 1.557 1.511 0.040 0.023

Table A.18. Media control pH and weights for 1% NaCl. Media Control 1% NaCl Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.87 23.293 23.051 0.000 45.5 4.86 23.855 23.900 0.045 95.5 4.86 23.855 23.900 0.045 169 4.86 23.855 23.900 0.045 233.5 4.86 23.855 23.900 0.045 287 4.86 23.855 23.900 0.045 360 4.95 23.161 23.297 0.136 402 4.89 23.188 23.260 0.072 457 4.88 23.115 23.275 0.160 551.5 4.87 23.288 23.447 0.159 575 4.82 23.765 23.846 0.081 647 4.83 23.285 23.357 0.072

Table A.19. SPG-F1 culture pH and weights for 1% NaCl. SPG-F1 Growth 1% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 5.37 23.666 23.705 0.039 0 4.85 23.83 24.035 0.205 0 5.21 5.14 0.266 0.154 23.664 23.828 0.164 0.136 0.086 0.050 45.5 4.65 24.276 24.639 0.363 45.5 4.68 24.308 24.689 0.381 45.5 4.92 4.75 0.148 0.085 23.628 23.994 0.366 0.370 0.010 0.006 95.5 4.83 23.684 24.413 0.729 95.5 4.75 23.999 24.762 0.763 95.5 4.56 4.71 0.139 0.080 23.792 24.406 0.614 0.702 0.078 0.045 169 4.40 23.522 24.463 0.941 169 4.46 23.834 24.706 0.872 169 4.55 4.47 0.075 0.044 23.706 24.702 0.996 0.936 0.062 0.036 233.5 4.50 23.037 23.696 0.659 233.5 4.47 23.252 24.460 1.208 233.5 4.37 4.49 0.068 0.039 23.363 24.135 0.772 0.880 0.290 0.167 287 4.49 23.560 24.761 1.201 287 4.35 23.191 24.094 0.903 287 4.45 4.43 0.072 0.042 23.473 24.707 1.234 1.113 0.182 0.105 360 4.40 23.558 24.564 1.006 360 4.36 23.673 24.202 0.529 360 4.35 4.37 0.026 0.015 23.370 24.440 1.070 0.868 0.296 0.171 402 4.34 23.558 24.567 1.009 402 4.42 23.158 23.795 0.637 402 4.45 4.40 0.057 0.033 23.211 24.049 0.838 0.828 0.186 0.108 457 4.59 23.201 23.986 0.785 457 4.35 23.234 24.437 1.203 457 4.47 4.47 0.120 0.069 23.442 24.467 1.025 1.004 0.210 0.121 551.5 4.39 22.867 23.984 1.117 551.5 4.38 22.998 23.715 0.717 551.5 4.42 4.40 0.021 0.012 23.946 24.793 0.847 0.894 0.204 0.118 575 4.43 23.367 24.323 0.956 575 4.40 23.740 24.720 0.980 575 4.32 4.38 0.057 0.033 24.069 24.985 0.916 0.951 0.032 0.019 647 4.46 23.841 24.641 0.800 647 4.52 23.423 24.334 0.911

647 4.45 4.48 0.038 0.022 23.190 24.381 1.191 0.967 0.201 0.116

Table A.20. SPG-F15 culture pH and weights for 1% NaCl. SPG-F15 Growth 1% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 5.34 23.586 23.661 0.075 0 5.29 23.764 23.928 0.164 0 5.33 5.32 0.026 0.015 23.657 23.699 0.042 0.094 0.063 0.036 45.5 5.10 23.831 24.375 0.544 45.5 5.06 23.439 24.018 0.579 45.5 5.09 5.08 0.021 0.012 23.505 24.047 0.542 0.555 0.021 0.012 95.5 4.98 23.890 24.506 0.616 95.5 4.93 23.846 24.698 0.852 95.5 4.91 4.94 0.036 0.021 23.990 24.849 0.859 0.776 0.138 0.080 169 4.71 23.943 25.005 1.062 169 4.70 23.294 24.396 1.102 169 4.68 4.70 0.015 0.009 24.353 25.528 1.175 1.113 0.057 0.033 233.5 4.65 23.429 24.519 1.090 233.5 4.63 23.640 24.546 0.906 233.5 4.62 4.63 0.015 0.009 23.171 24.450 1.279 1.092 0.187 0.108 287 4.47 23.402 24.851 1.449 287 4.43 23.442 25.003 1.561 287 4.48 4.46 0.026 0.015 23.914 24.259 0.345 1.118 0.672 0.388 360 4.57 23.201 25.238 2.037 360 4.63 23.422 25.583 2.161 360 4.64 4.61 0.038 0.022 22.931 25.007 2.076 2.091 0.063 0.037 402 4.54 22.085 24.643 2.558 402 4.51 23.171 25.032 1.861 402 4.54 4.53 0.017 0.010 23.542 25.373 1.831 2.083 0.411 0.237 457 4.70 23.195 24.212 1.017 457 4.65 23.246 24.642 1.396 457 4.60 4.65 0.050 0.029 23.624 25.243 1.619 1.344 0.304 0.176 551.5 4.68 23.271 24.197 0.926 551.5 4.63 23.649 25.045 1.396 551.5 4.61 4.64 0.036 0.021 23.101 24.475 1.374 1.232 0.265 0.153 575 4.69 23.587 24.639 1.052 575 4.68 23.268 24.269 1.001 575 4.68 4.68 0.006 0.003 23.560 24.700 1.140 1.064 0.070 0.041 647 4.60 23.385 24.563 1.178 647 4.60 23.427 24.564 1.137

647 4.61 4.60 0.006 0.003 23.458 24.771 1.313 1.209 0.092 0.053

Table A.21. Media control pH and weights for 2% NaCl. Media Control 2% NaCl Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.79 23.686 23.871 0.185 45.5 4.79 23.610 24.005 0.395 95.5 4.79 23.610 24.005 0.395 169 4.79 23.610 24.005 0.395 233.5 4.79 23.610 24.005 0.395 287 4.79 23.610 24.005 0.395 360 4.79 23.610 24.005 0.395 402 4.75 23.327 23.636 0.309 457 4.77 23.219 23.361 0.142 551.5 4.95 23.285 23.644 0.359 575 5.11 23.531 23.548 0.017 647 4.77 23.725 23.884 0.159

Table A.22. SPG-F1 culture pH and weights for 2% NaCl. SPG-F1 Growth 2% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.72 23.447 23.640 0.193 0 4.76 23.878 24.334 0.456 0 4.75 4.66 0.006 0.003 23.678 24.243 0.565 0.405 0.191 0.110 45.5 4.67 23.845 24.173 0.328 45.5 4.66 23.930 24.275 0.345 45.5 4.66 4.59 0.006 0.003 23.460 23.864 0.404 0.359 0.040 0.023 95.5 4.59 24.294 24.974 0.680 95.5 4.59 23.886 24.620 0.734 95.5 4.60 4.44 0.012 0.007 23.768 24.301 0.533 0.649 0.104 0.060 169 4.45 23.789 24.327 0.538 169 4.43 23.840 24.333 0.493 169 4.45 4.41 0.026 0.015 23.831 24.489 0.658 0.563 0.085 0.049 233.5 4.44 23.528 24.241 0.713 233.5 4.39 23.530 24.358 0.828 233.5 4.40 4.36 0.006 0.003 23.191 23.907 0.716 0.752 0.066 0.038 287 4.36 23.285 24.284 0.999 287 4.35 23.258 24.162 0.904 287 4.35 4.32 0.026 0.015 23.486 24.151 0.665 0.856 0.172 0.099 360 4.34 23.489 24.413 0.924 360 4.29 23.318 24.436 1.118 360 4.33 4.32 0.026 0.015 23.359 24.402 1.043 1.028 0.098 0.056 402 4.27 23.115 24.099 0.984 402 4.25 23.444 24.457 1.013 402 4.27 4.26 0.012 0.007 22.692 23.486 0.794 0.930 0.119 0.069 457 4.28 23.198 23.883 0.685 457 4.27 23.739 24.560 0.821 457 4.23 4.26 0.026 0.015 23.382 24.450 1.068 0.858 0.194 0.112 551.5 4.27 23.250 23.740 0.490 551.5 4.29 23.230 23.858 0.628 551.5 4.31 4.29 0.020 0.012 23.177 23.748 0.571 0.563 0.069 0.040 575 4.28 23.171 23.767 0.596 575 4.22 23.751 24.497 0.746 575 4.30 4.27 0.042 0.024 23.356 24.119 0.763 0.702 0.092 0.053 647 4.29 23.420 24.202 0.782 647 4.25 23.161 23.846 0.685

647 4.26 4.27 0.021 0.012 23.195 23.899 0.704 0.724 0.051 0.030

Table A.23. SPG-F15 culture pH and weights for 2% NaCl. SPG-F15 Growth 2% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.80 23.891 24.472 0.581 0 5.25 23.876 24.454 0.578 0 5.27 5.11 0.266 0.153 23.876 24.448 0.572 0.577 0.005 0.003 45.5 4.73 23.577 24.015 0.438 45.5 4.70 23.654 24.199 0.545 45.5 4.90 4.78 0.108 0.062 23.847 24.348 0.501 0.495 0.054 0.031 95.5 5.03 23.969 24.652 0.683 95.5 5.04 24.285 25.383 1.098 95.5 4.63 4.90 0.234 0.135 23.873 24.968 1.095 0.959 0.239 0.138 169 4.80 23.258 24.142 0.884 169 4.51 23.645 24.074 0.429 169 4.76 4.69 0.157 0.091 23.170 24.050 0.880 0.731 0.262 0.151 233.5 4.34 23.065 23.778 0.713 233.5 4.72 23.142 24.022 0.880 233.5 4.67 4.58 0.206 0.119 23.410 24.707 1.297 0.963 0.301 0.174 287 4.35 23.138 24.175 1.037 287 4.42 23.062 24.018 0.956 287 4.42 4.40 0.040 0.023 23.299 24.072 0.773 0.922 0.135 0.078 360 4.49 23.255 25.157 1.902 360 4.63 23.882 25.500 1.618 360 4.35 4.49 0.140 0.081 23.424 24.686 1.262 1.594 0.321 0.185 402 4.41 23.564 25.113 1.549 402 4.46 23.625 24.444 0.819 402 3.90 4.26 0.310 0.179 23.532 30.627 7.095 1.184 0.516 0.298 457 4.39 23.035 24.025 0.990 457 4.35 23.485 24.573 1.088 457 4.35 4.36 0.023 0.013 23.360 24.345 0.985 1.021 0.058 0.034 551.5 4.35 23.101 23.695 0.594 551.5 4.33 23.319 23.975 0.656 551.5 4.57 4.42 0.133 0.077 23.266 24.350 1.084 0.778 0.267 0.154 575 4.61 23.423 24.162 0.739 575 4.34 23.419 24.452 1.033 575 4.55 4.50 0.142 0.082 23.775 24.746 0.971 0.914 0.155 0.089 647 4.37 23.153 23.839 0.686 647 4.48 22.945 24.286 1.341

647 4.43 4.43 0.055 0.032 23.281 24.196 0.915 0.981 0.332 0.192

Table A.24. Media control pH and weights for 6% NaCl. Media Control 6% NaCl Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.63 23.363 24.427 1.064 115 4.63 23.363 24.427 1.064 163 4.63 23.363 24.427 1.064 260 4.63 23.363 24.427 1.064 332.5 4.60 23.877 24.413 0.536 402 4.60 23.877 24.413 0.536 499.5 4.60 23.877 24.413 0.536 577 4.60 23.877 24.413 0.536 665.5 4.60 23.877 24.413 0.536 742 4.60 23.877 24.413 0.536 790 4.60 23.877 24.413 0.536 840 4.60 23.877 24.413 0.536

Table A.25. SPG-F1 culture pH and weights for 6% NaCl. SPG-F1 Growth 6% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.60 24.029 25.289 1.260 0 4.61 23.976 24.976 1.000 0 4.60 4.60 0.006 0.003 24.019 25.615 1.596 1.298 0.299 0.173 115 4.54 23.808 24.255 0.447 115 4.55 23.734 23.785 0.051 115 4.56 4.55 0.010 0.006 23.706 23.882 0.176 0.225 0.202 0.117 163 4.44 23.626 24.063 0.437 163 4.43 24.040 24.535 0.495 163 4.45 4.44 0.010 0.006 24.209 24.589 0.380 0.437 0.058 0.033 260 4.36 23.984 24.464 0.480 260 4.36 23.624 24.405 0.781 260 4.35 4.36 0.006 0.003 23.872 24.487 0.615 0.625 0.151 0.087 332.5 4.32 23.709 24.275 0.566 332.5 4.27 23.730 24.336 0.606 332.5 4.29 4.30 0.025 0.015 23.864 24.466 0.602 0.591 0.022 0.013 402 4.26 23.676 24.763 1.087 402 4.26 23.494 24.021 0.527 402 4.25 4.26 0.006 0.003 23.224 23.791 0.567 0.727 0.312 0.180 499.5 4.26 23.622 24.583 0.961 499.5 4.24 24.047 24.778 0.731 499.5 4.25 4.25 0.010 0.006 23.939 24.599 0.660 0.784 0.157 0.091 577 4.25 23.636 24.129 0.493 577 4.23 23.109 23.643 0.534 577 4.23 4.24 0.012 0.007 23.553 24.093 0.540 0.522 0.026 0.015 665.5 4.22 23.725 24.410 0.685 665.5 4.22 23.653 24.134 0.481 665.5 4.24 4.23 0.012 0.007 23.711 24.204 0.493 0.553 0.114 0.066 742 4.22 23.592 24.150 0.558 742 4.22 23.778 24.241 0.463 742 4.25 4.23 0.017 0.010 23.538 23.989 0.451 0.491 0.059 0.034 790 4.24 23.609 24.081 0.472 790 4.23 23.835 24.322 0.487 790 4.22 4.23 0.010 0.006 23.368 24.021 0.653 0.537 0.100 0.058 840 4.22 23.812 24.340 0.528 840 4.23 23.763 24.292 0.529

840 4.23 4.23 0.006 0.003 23.718 24.233 0.515 0.524 0.008 0.005

100

Table A.26. SPG-F15 culture pH and weights for 6% NaCl. SPG-F15 Growth 6% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.60 23.476 25.285 1.809 0 4.60 23.072 24.996 1.924 0 4.59 4.60 0.006 0.003 23.347 24.941 1.594 1.776 0.168 0.097 115 4.55 24.064 24.190 0.126 115 4.54 23.389 23.830 0.441 115 4.57 4.55 0.015 0.009 23.772 24.446 0.674 0.414 0.275 0.159 163 4.43 23.600 24.078 0.478 163 4.42 23.745 24.124 0.379 163 4.42 4.42 0.006 0.003 23.724 24.216 0.492 0.450 0.062 0.036 260 4.27 24.094 24.628 0.534 260 4.25 23.744 24.178 0.434 260 4.28 4.27 0.015 0.009 24.166 24.669 0.503 0.490 0.051 0.030 332.5 4.23 23.465 24.314 0.849 332.5 4.21 23.830 24.770 0.940 332.5 4.22 4.22 0.010 0.006 23.560 25.095 1.535 1.108 0.373 0.215 402 4.18 23.598 24.377 0.779 402 4.30 23.409 24.324 0.915 402 4.19 4.22 0.067 0.038 23.814 24.474 0.660 0.785 0.128 0.074 499.5 4.18 23.929 24.620 0.691 499.5 4.21 23.817 24.659 0.842 499.5 4.19 4.19 0.015 0.009 23.877 24.920 1.043 0.859 0.177 0.102 577 4.14 23.860 24.600 0.740 577 4.19 23.907 24.982 1.075 577 4.15 4.16 0.026 0.015 23.752 24.971 1.219 1.011 0.246 0.142 665.5 0.15 23.925 24.707 0.782 665.5 4.14 23.363 24.406 1.043 665.5 4.14 2.81 2.304 1.330 23.293 24.696 1.403 1.076 0.312 0.180 742 3.60 23.394 24.033 0.639 742 4.12 24.028 24.772 0.744 742 4.13 3.95 0.303 0.175 23.629 24.506 0.877 0.753 0.119 0.069 790 4.11 23.495 24.261 0.766 790 4.01 23.553 24.569 1.016 790 4.17 4.10 0.081 0.047 23.573 24.744 1.171 0.984 0.204 0.118 840 4.06 23.020 23.834 0.814 840 4.10 23.474 24.545 1.071

101

840 4.12 4.09 0.031 0.018 23.600 24.700 1.100 0.995 0.157 0.091

102

Table A.27. Media control pH and weights for 8% NaCl. Media Control 8% NaCl Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 4.55 23.469 24.825 1.356 137 4.55 23.819 24.460 0.641 214 4.55 23.819 24.460 0.641 285 4.55 23.819 24.460 0.641 354 4.55 23.819 24.460 0.641 473 4.55 23.819 24.460 0.641 545.5 4.54 23.861 24.636 0.775 615 4.54 23.861 24.636 0.775 712.5 4.54 23.861 24.636 0.775 790 4.54 23.861 24.636 0.775 878.5 4.54 23.861 24.636 0.775 946 4.54 23.861 24.636 0.775

103

Table A.28. SPG-F1 culture pH and weights for 8% NaCl. SPG-F1 Growth 8% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.54 23.658 23.668 0.010 0 4.55 23.526 24.258 0.732 0 4.54 4.54 0.006 0.003 23.593 25.503 1.910 0.884 0.959 0.554 137 4.51 23.773 23.480 0.000 137 4.53 23.749 24.240 0.491 137 4.53 4.52 0.012 0.007 23.928 24.569 0.641 0.377 0.335 0.194 214 4.46 23.701 24.962 1.261 214 4.44 23.593 24.198 0.605 214 4.45 4.45 0.010 0.006 23.740 24.121 0.381 0.749 0.457 0.264 285 4.36 23.703 24.356 0.653 285 4.35 23.658 24.665 1.007 285 4.35 4.35 0.006 0.003 24.338 25.402 1.064 0.908 0.223 0.129 354 4.26 23.608 24.865 1.257 354 4.31 23.671 24.993 1.322 354 4.30 4.29 0.026 0.015 23.430 24.658 1.228 1.269 0.048 0.028 473 4.28 23.653 24.304 0.651 473 4.32 23.707 24.202 0.495 473 4.29 4.30 0.021 0.012 23.376 23.855 0.479 0.542 0.095 0.055 545.5 4.30 24.284 25.093 0.809 545.5 4.36 22.983 23.625 0.642 545.5 4.30 4.32 0.035 0.020 23.797 24.525 0.728 0.726 0.084 0.048 615 4.29 23.530 24.714 1.184 615 4.29 23.596 24.216 0.620 615 4.28 4.29 0.006 0.003 23.774 24.468 0.694 0.833 0.307 0.177 712.5 4.25 23.769 25.219 1.450 712.5 4.30 23.407 24.490 1.083 712.5 4.26 4.27 0.026 0.015 23.752 24.500 0.748 1.094 0.351 0.203 790 4.31 23.343 23.699 0.356 790 4.29 23.700 23.892 0.192 790 4.30 4.30 0.010 0.006 23.602 24.218 0.616 0.388 0.214 0.123 878.5 4.29 23.825 24.084 0.259 878.5 4.25 23.794 25.242 1.448 878.5 4.27 4.27 0.020 0.012 23.544 24.810 1.266 0.991 0.640 0.370 946 4.29 23.259 24.114 0.855 946 4.24 23.595 24.257 0.662

104

946 4.28 4.27 0.026 0.015 23.917 24.484 0.567 0.695 0.147 0.085

105

Table A.29. SPG-F15 culture pH and weights for 8% NaCl. SPG-F15 Growth 8% NaCl Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 4.55 23.616 25.322 1.706 0 4.55 23.615 25.508 1.893 0 4.56 4.55 0.006 0.003 23.862 25.612 1.750 1.783 0.098 0.056 137 4.50 23.911 24.022 0.111 137 4.48 23.939 24.661 0.722 137 4.49 4.49 0.010 0.006 23.738 23.973 0.235 0.356 0.323 0.186 214 4.31 23.451 24.233 0.782 214 4.33 24.409 25.638 1.229 214 4.34 4.33 0.015 0.009 23.940 25.338 1.398 1.136 0.318 0.184 285 4.22 23.863 25.295 1.432 285 4.22 24.185 25.420 1.235 285 4.23 4.22 0.006 0.003 23.585 24.756 1.171 1.279 0.136 0.079 354 4.13 23.833 25.365 1.532 354 4.21 23.529 24.813 1.284 354 4.17 4.17 0.040 0.023 23.684 25.357 1.673 1.496 0.197 0.114 473 4.20 23.626 24.340 0.714 473 4.15 23.621 24.442 0.821 473 4.19 4.18 0.026 0.015 23.792 24.607 0.815 0.783 0.060 0.035 545.5 4.17 23.778 24.711 0.933 545.5 4.18 24.930 25.231 0.301 545.5 4.18 4.18 0.006 0.003 23.655 25.563 1.908 1.047 0.810 0.467 615 4.17 23.552 24.355 0.803 615 4.18 23.511 24.440 0.929 615 4.16 4.17 0.010 0.006 23.784 24.747 0.963 0.898 0.084 0.049 712.5 4.18 23.678 25.498 1.820 712.5 4.19 23.709 25.066 1.357 712.5 4.18 4.18 0.006 0.003 23.446 24.840 1.394 1.524 0.257 0.149 790 4.19 23.279 23.800 0.521 790 4.21 23.480 23.949 0.469 790 4.22 4.21 0.015 0.009 23.522 24.087 0.565 0.518 0.048 0.028 878.5 4.18 23.256 24.227 0.971 878.5 4.18 23.824 24.518 0.694 878.5 4.20 4.19 0.012 0.007 23.747 24.320 0.573 0.746 0.204 0.118 946 4.18 23.925 24.827 0.902 946 4.02 23.937 24.891 0.954

106

946 4.15 4.12 0.085 0.049 23.626 24.567 0.941 0.932 0.027 0.016

107

Table A.30. Media control pH and weights for pH 3. Media Control pH 3 Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 3.01 23.496 24.114 0.618 48 2.96 22.996 23.470 0.474 100 2.96 23.420 23.992 0.572 195.5 2.97 23.542 24.136 0.594 267 2.98 22.707 23.230 0.523 362 2.95 23.176 23.615 0.439 388.5 2.95 23.881 24.404 0.523 460 3.00 23.657 24.092 0.435 555 2.93 23.599 24.205 0.606 604.5 2.94 23.190 23.686 0.496 626 2.92 23.602 24.186 0.584

108

Table A.31. SPG-F1 culture pH and weights for pH 3. SPG-F1 Growth pH 3 Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 3.00 23.344 23.976 0.632 0 3.00 23.643 24.226 0.583 0 2.97 2.99 0.017 0.010 23.215 23.644 0.429 0.548 0.106 0.061 48 2.92 23.278 23.891 0.613 48 2.91 23.152 23.985 0.833 48 2.93 2.92 0.010 0.006 23.552 24.184 0.632 0.693 0.122 0.070 100 2.90 23.549 25.174 1.625 100 2.89 23.530 25.295 1.765 100 2.88 2.89 0.010 0.006 23.557 25.141 1.584 1.658 0.095 0.055 195.5 2.93 23.769 25.651 1.882 195.5 2.94 23.936 25.823 1.887 195.5 2.96 2.94 0.015 0.009 23.474 25.253 1.779 1.849 0.061 0.035 267 2.94 23.187 25.087 1.900 267 2.96 23.319 25.112 1.793 267 2.97 2.95 0.015 0.009 23.061 24.827 1.766 1.820 0.071 0.041 362 2.98 23.820 25.376 1.556 362 2.88 24.004 25.407 1.403 362 2.91 2.92 0.051 0.030 23.419 24.863 1.444 1.468 0.079 0.046 388.5 2.94 23.226 24.690 1.464 388.5 2.92 23.729 25.425 1.696 388.5 2.91 2.92 0.015 0.009 23.593 25.361 1.768 1.643 0.159 0.092 460 2.87 23.748 25.360 1.612 460 2.87 23.439 24.967 1.528 460 2.87 2.87 0.000 0.000 23.755 25.316 1.561 1.567 0.042 0.024 555 2.95 23.400 25.047 1.647 555 2.90 23.460 25.264 1.804 555 2.90 2.92 0.029 0.017 23.430 25.005 1.575 1.675 0.117 0.068 604.5 2.87 23.423 24.861 1.438 604.5 2.88 23.525 25.148 1.623 604.5 2.89 2.88 0.010 0.006 23.670 25.083 1.413 1.491 0.115 0.066 626 2.88 23.580 25.104 1.524 626 2.87 23.105 24.624 1.519 626 2.88 2.88 0.006 0.003 23.393 24.989 1.596 1.546 0.043 0.025

109

Table A.32. SPG-F15 culture pH and weights for pH 3. SPG-F15 Growth pH 3 Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 2.98 23.835 24.522 0.687 0 2.97 23.399 24.088 0.689 0 2.98 2.98 0.006 0.003 23.804 24.494 0.690 0.689 0.002 0.001 48 2.97 23.589 24.543 0.954 48 2.93 23.185 24.139 0.954 48 2.94 2.95 0.021 0.012 23.426 24.326 0.900 0.936 0.031 0.018 100 2.90 23.560 25.735 2.175 100 2.89 24.074 26.920 2.846 100 2.87 2.89 0.015 0.009 23.652 25.728 2.076 2.366 0.419 0.242 195.5 2.96 23.412 25.445 2.033 195.5 2.94 23.862 25.789 1.927 195.5 2.92 2.94 0.020 0.012 23.661 25.624 1.963 1.974 0.054 0.031 267 2.94 23.442 24.902 1.460 267 2.94 22.960 24.858 1.898 267 2.94 2.94 0.000 0.000 23.002 24.878 1.876 1.745 0.247 0.142 362 2.95 23.525 24.854 1.329 362 2.97 23.475 24.997 1.522 362 2.95 2.96 0.012 0.007 23.589 25.065 1.476 1.442 0.101 0.058 388.5 2.98 23.472 25.154 1.682 388.5 2.92 23.053 24.614 1.561 388.5 2.94 2.95 0.031 0.018 23.367 24.858 1.491 1.578 0.097 0.056 460 2.91 23.808 25.366 1.558 460 2.89 23.582 25.088 1.506 460 2.89 2.90 0.012 0.007 23.806 25.325 1.519 1.528 0.027 0.016 555 2.93 23.602 25.063 1.461 555 2.96 23.702 25.295 1.593 555 2.91 2.93 0.025 0.015 23.749 25.139 1.390 1.481 0.103 0.059 604.5 2.91 23.749 25.100 1.351 604.5 2.89 23.533 24.945 1.412 604.5 2.92 2.91 0.015 0.009 23.597 25.018 1.421 1.395 0.038 0.022 626 2.88 23.306 24.549 1.243 626 2.89 23.526 25.042 1.516 626 2.90 2.89 0.010 0.006 23.240 24.943 1.703 1.487 0.231 0.134

110

Table A.33. Media control pH and weights for pH 6. Media Control pH 6 Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 5.46 23.489 23.895 0.406 54 5.73 23.739 24.207 0.468 74 5.73 23.567 24.084 0.517 97 5.54 23.003 23.603 0.600 118 5.55 23.478 23.902 0.424 166 5.53 23.851 24.399 0.548 223.5 5.50 22.860 23.281 0.421 263 5.52 23.633 24.214 0.581 313.5 5.45 23.795 23.952 0.157 356 5.51 23.342 24.006 0.664

111

Table A.34. SPG-F1 culture pH and weights for pH 6. SPG-F1 Growth pH 6 Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 5.62 23.397 23.715 0.318 0 5.44 23.322 23.716 0.394 0 5.40 5.49 0.117 0.068 23.542 23.904 0.362 0.358 0.038 0.022 54 5.10 23.586 24.941 1.355 54 5.04 23.737 25.401 1.664 54 5.16 5.10 0.060 0.035 23.413 24.865 1.452 1.490 0.158 0.091 74 4.77 23.874 25.937 2.063 74 4.86 23.630 25.762 2.132 74 4.93 4.85 0.080 0.046 23.571 25.771 2.200 2.132 0.069 0.040 97 4.80 23.611 25.944 2.333 97 4.78 23.395 25.851 2.456 97 4.76 4.78 0.020 0.012 23.934 26.298 2.364 2.384 0.064 0.037 118 4.61 23.259 25.566 2.307 118 4.68 23.466 25.963 2.497 118 4.61 4.65 0.040 0.023 23.678 26.143 2.465 2.423 0.102 0.059 166 4.41 23.534 26.122 2.588 166 4.45 23.506 26.139 2.633 166 4.49 4.45 0.040 0.023 23.578 26.031 2.453 2.558 0.094 0.054 223.5 4.56 23.725 25.997 2.272 223.5 4.52 23.521 25.925 2.404 223.5 4.72 4.60 0.106 0.061 23.616 25.824 2.208 2.295 0.100 0.058 263 4.38 23.813 26.094 2.281 263 4.60 23.890 26.099 2.209 263 4.68 4.55 0.155 0.090 23.673 25.790 2.117 2.202 0.082 0.047 313.5 4.54 23.594 25.336 1.742 313.5 4.38 23.595 25.599 2.004 313.5 4.57 4.50 0.102 0.059 23.375 25.097 1.722 1.823 0.157 0.091 356 4.42 23.715 25.413 1.698 356 4.62 23.469 25.359 1.890 356 4.55 4.53 0.101 0.059 23.564 25.491 1.927 1.838 0.123 0.071

112

Table A.35. SPG-F15 culture pH and weights for pH 6. SPG-F15 Growth pH 6 Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 5.34 23.947 24.383 0.436 0 5.30 23.826 24.255 0.429 0 5.47 5.37 0.089 0.051 23.404 23.776 0.372 0.412 0.035 0.020 54 5.03 23.304 25.518 2.214 54 5.03 23.219 25.116 1.897 54 5.00 5.02 0.017 0.010 24.297 26.110 1.813 1.975 0.211 0.122 74 4.77 23.543 26.152 2.609 74 4.94 23.124 25.791 2.667 74 4.88 4.86 0.086 0.050 23.487 26.214 2.727 2.668 0.059 0.034 97 4.69 23.656 26.639 2.983 97 4.62 23.452 26.067 2.615 97 4.69 4.67 0.040 0.023 23.496 26.524 3.028 2.875 0.227 0.131 118 4.60 23.469 26.085 2.616 118 4.59 23.275 26.182 2.907 118 4.56 4.58 0.021 0.012 23.644 26.593 2.949 2.824 0.181 0.105 166 4.55 23.274 25.908 2.634 166 4.60 23.375 26.161 2.786 166 4.69 4.61 0.071 0.041 23.752 26.197 2.445 2.622 0.171 0.099 223.5 4.46 23.337 26.150 2.813 223.5 4.62 23.765 26.260 2.495 223.5 4.53 4.54 0.080 0.046 23.251 26.118 2.867 2.725 0.201 0.116 263 4.55 23.901 26.368 2.467 263 4.49 23.668 26.076 2.408 263 4.68 4.57 0.097 0.056 23.726 26.342 2.616 2.497 0.107 0.062 313.5 4.47 23.600 25.686 2.086 313.5 4.51 23.420 25.801 2.381 313.5 4.53 4.50 0.031 0.018 23.485 25.997 2.512 2.326 0.218 0.126 356 4.57 23.614 26.006 2.392 356 4.45 23.490 26.132 2.642 356 4.54 4.52 0.062 0.036 23.467 25.664 2.197 2.410 0.223 0.129

113

Table A.36. Media control pH and weights for pH 8. Media Control pH 8 Time (hrs) pH Pre - Wt. Post - Wt. Final Wt. 0 7.56 24.154 24.542 0.388 47.5 7.44 23.955 24.361 0.406 72 7.41 24.246 24.588 0.342 96 7.21 23.874 24.275 0.401 125.5 7.29 23.806 24.208 0.402 143.5 7.13 24.143 24.613 0.470 167 7.31 24.143 24.613 0.470 190 7.47 24.273 24.639 0.366 214 7.26 23.956 24.023 0.067 238.5 7.24 23.629 23.593 0.000 358.5 7.23 23.874 24.204 0.330 382.5 7.19 23.767 24.158 0.391

114

Table A.37. SPG-F1 culture pH and weights for pH 8. SPG-F1 Growth pH 8 Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 7.59 23.829 24.155 0.326 0 7.56 24.295 24.725 0.430 0 7.64 7.60 0.040 0.023 24.457 24.897 0.440 0.399 0.063 0.036 47.5 7.42 24.235 24.683 0.448 47.5 7.53 23.746 24.225 0.479 47.5 7.46 7.47 0.056 0.032 23.747 24.251 0.504 0.477 0.028 0.016 72 7.46 23.798 24.164 0.366 72 7.41 24.072 24.469 0.397 72 7.33 7.40 0.066 0.038 23.995 24.374 0.379 0.381 0.016 0.009 96 7.03 23.881 24.226 0.345 96 7.42 23.815 24.263 0.448 96 7.41 7.29 0.222 0.128 24.306 24.724 0.418 0.404 0.053 0.031 125.5 6.51 24.105 24.704 0.599 125.5 5.99 23.830 24.927 1.097 125.5 6.92 6.25 0.466 0.269 24.234 24.692 0.458 0.718 0.336 0.194 143.5 6.08 24.205 24.949 0.744 143.5 6.23 23.999 25.036 1.037 143.5 6.09 6.13 0.084 0.048 23.994 25.039 1.045 0.942 0.172 0.099 167 6.16 23.671 24.517 0.846 167 6.50 23.096 23.793 0.697 167 6.56 6.41 0.216 0.125 23.898 24.448 0.550 0.698 0.148 0.085 190 6.14 24.120 24.723 0.603 190 5.96 24.532 25.323 0.791 190 5.82 5.97 0.160 0.093 23.932 24.985 1.053 0.816 0.226 0.130 214 5.69 23.934 25.309 1.375 214 5.79 23.835 24.942 1.107 214 5.79 5.76 0.058 0.033 24.238 25.360 1.122 1.201 0.151 0.087 238.5 5.76 23.960 25.140 1.180 238.5 5.74 24.102 25.327 1.225 238.5 5.73 5.74 0.015 0.009 24.453 25.840 1.387 1.264 0.109 0.063 358.5 5.65 23.050 25.531 2.481 358.5 5.62 24.078 25.721 1.643 358.5 5.41 5.56 0.131 0.075 23.086 25.851 2.765 2.296 0.583 0.337 382.5 5.64 23.881 25.177 1.296 382.5 5.64 23.891 25.257 1.366

115

382.5 5.68 5.65 0.023 0.013 24.475 25.515 1.040 1.234 0.172 0.099

116

Table A.38. SPG-F15 culture pH and weights for pH 8. SPG-F15 Growth pH 8 Time Avg. Std. Std. Pre - Post - Final Avg. Std. Std. pH (hrs) pH Dev. Err. Wt. Wt. Wt. Wt. Dev. Err. 0 7.62 24.115 24.272 0.157 0 7.60 23.708 24.183 0.475 0 7.53 7.58 0.047 0.027 23.961 24.389 0.428 0.353 0.172 0.099 47.5 7.23 23.960 24.452 0.492 47.5 6.92 23.962 24.723 0.761 47.5 7.18 7.11 0.166 0.096 23.959 24.596 0.637 0.630 0.135 0.078 72 6.10 24.069 25.459 1.390 72 6.05 24.143 25.623 1.480 72 6.13 6.09 0.040 0.023 24.335 25.754 1.419 1.430 0.046 0.027 96 5.79 24.050 25.565 1.515 96 5.78 24.000 26.153 2.153 96 5.79 5.79 0.006 0.003 23.641 25.348 1.707 1.792 0.327 0.189 125.5 5.67 24.212 26.960 2.748 125.5 5.63 24.343 26.282 1.939 125.5 5.32 5.54 0.192 0.111 24.305 27.015 2.710 2.466 0.457 0.264 143.5 5.77 24.089 26.230 2.141 143.5 5.50 24.105 26.158 2.053 143.5 5.64 5.64 0.135 0.078 23.897 26.485 2.588 2.261 0.287 0.166 167 5.75 23.740 25.727 1.987 167 5.68 23.580 26.488 2.908 167 5.66 5.70 0.047 0.027 23.506 26.319 2.813 2.569 0.507 0.292 190 5.67 23.526 25.248 1.722 190 5.67 23.776 26.967 3.191 190 5.56 5.63 0.064 0.037 23.520 25.124 1.604 2.172 0.884 0.510 214 5.67 23.489 24.890 1.401 214 5.46 23.691 25.594 1.903 214 5.35 5.49 0.163 0.094 24.061 25.543 1.482 1.595 0.270 0.156 238.5 5.60 24.134 26.148 2.014 238.5 5.52 24.141 26.299 2.158 238.5 5.49 5.54 0.057 0.033 24.122 26.113 1.991 2.054 0.091 0.052 358.5 5.50 24.050 26.443 2.393 358.5 5.24 24.000 26.415 2.415 358.5 5.42 5.39 0.133 0.077 23.641 26.152 2.511 2.440 0.063 0.036 382.5 5.50 23.787 26.142 2.355 382.5 5.24 23.593 25.630 2.037

117

382.5 5.42 5.39 0.133 0.077 23.505 25.569 2.064 2.152 0.176 0.102

118

Table A.39. SPG-F1 and SPG F15 growth rates. Student’s T-test was used to compare SPG- F1 growth rates to SPG-F15 growth rates. The significance level was set to 0.050. Temperature SPG-F1 Growth SPG-F15 Growth p-value Rate Rate (mg hr-1) (mg hr-1) 4ºC 1.619 x 10-3 2.743 x 10-3 0.282 10ºC 2.647 x 10-3 2.293 x 10-3 0.474 15ºC 2.608 x 10-3 4.494 x 10-3 0.675 21ºC 4.390 x 10-3 4.813 x 10-3 0.443 26ºC 3.043 x 10-3 4.272 x 10-3 0.339 NaCl SPG-F1 Growth SPG-F15 Growth p-value Rate Rate (mg hr-1) (mg hr-1) 1% 0.106 x 10-3 1.925 x 10-3 0.326 2% 1.273 x 10-3 0.303 x 10-3 0.208 6% 1.508 x 10-3 2.104 x 10-3 0.796 8% 0.046 x 10-3 0.604 x 10-3 0.441 pH SPG-F1 Growth SPG-F15 Growth p-value Rate Rate (mg hr-1) (mg hr-1) 3 2.445 x 10-3 5.188 x 10-3 0.828 6 4.750 x 10-3 9.322 x 10-3 0.894 8 2.217 x 10-3 4.775 x 10-3 0.156

119

Table A.39. The Student’s T-test p-values from a comparison of SPG-F1 and SPG-F15 individual growth rates at different conditions. The significance level was set to 0.050. SPG-F1 SPG-F15 Temperature p-value p-value 4 vs. 10ºC 0.331 0.952 4 vs. 15ºC 0.939 0.979 4 vs. 21ºC 0.289 0.606 4 vs. 26ºC 0.748 0.943 10 vs. 15ºC 0.990 0.433 10 vs. 21ºC 0.739 0.719 10 vs. 26ºC 0.495 0.610 15 vs. 21ºC 0.974 0.572 15 vs. 26ºC 0.251 0.711 21 vs. 26ºC 0.707 0.929 SPG-F1 SPG-F15 NaCl p-value p-value 1 vs. 2% 0.326 0.908 1 vs. 6% 0.492 0.238 1 vs. 8% 0.676 0.798 2 vs. 6% 0.308 0.184 2 vs. 8% 0.681 0.563 6 vs. 8% 0.346 0.074 SPG-F1 SPG-F15 pH p-value p-value 3 vs. 6 0.178 0.432 3 vs. 8 0.725 0.640 6 vs. 8 0.067 0.624

120

Figure A.1. The percentage of CAZy families in the genome of SPG-F1.

121

Figure A.2. The percentage of CAZy families in the genome of SPG-F15.

122