Molecular and Cultivation-based Characterization of Ancient Algal Mats from the

McMurdo Dry Valleys,

A thesis submitted to Kent State University in partial fulfillment of the

requirements for the degree of Master of Science

by

Doug Antibus

December, 2009

Thesis written by

Doug Antibus

B.S., Kent State University, 2007

M.S., Kent State University, 2009

Approved by

Dr. Christopher B. Blackwood Advisor

Dr. James L. Blank Chair, Department of Biological Sciences

Dr. Timothy Moerland Dean, College of Arts and Sciences

iii

TABLE OF CONTENTS

LIST OF TABLES………………………………………………………………………..iv

LIST OF FIGURES ……………………………………………………………………...vi

ACKNOWLEDGEMENTS…………………………………………………………...... viii

CHAPTER I: General Introduction……………………………………………………….1

CHAPTER II: Molecular Characterization of Ancient Algal Mats from the McMurdo Dry

Valleys, Antarctica: A Legacy of Genetic Diversity

Introduction……………………………………………………………....22

Results and Discussion……………………………………………..……27

Methods…………………………………………………………………..51

Literature Cited…………………………………………………………..59

CHAPTER III: Recovery of Viable from Ancient Algal Mats from the

McMurdo Dry Valleys, Antarctica

Introduction………………………………………………..……………..78

Methods…………………………………………………………………..80

Results……………………………………………………………...…….88

Discussion…………………………………………………………...….106

Literature Cited………………………………………………………....109

CHAPTER IV: General Discussion…………………………………………………….120

iii

LIST OF TABLES

Chapter II: Molecular Characterization of Ancient Algal Mats from the McMurdo Dry

Valleys, Antarctica: A Legacy of Genetic Diversity

Table 1. DNA yield of samples during successive rounds of extraction…..…….28

Table 2. Diversity and richness estimates of bacterial 16S rRNA gene clone libraries …………………………………………………………….……33

Table 3. Results of permutation tests of RDA (Redundancy Analysis)

significance………………………………………………………………36

Table 4. Phylogenetic affiliation of groups unevenly distributed over sample age

classes…………………………………………………………………....42

Table 5. Distribution of families within the in 16S rRNA gene clone

libraries…………………………………………………………………..45

Table 6. Occurrence of selected phyla in 16S rRNA gene clone libraries from

Antarctic habitats………………………………………………………...46

Table 7. Sample 14 C ages…………………………………………………...……52

iv Chapter III: Recovery of Viable Bacteria from Ancient Algal Mats from the McMurdo

Dry Valleys, Antarctica

Table 8. Summary of bacterial recovery from algal mat samples……………….89

Table 9. Phylogenetic affiliation of recovered ARDRA types as determined by BLAST searches……………………………………………………...….93

Table 10. Sample genotype richness and G tests of genotype distribution by

temperature and medium…………………………………………..…..97

Table 11. Distribution of genotypes from sample 8643 among temperature

treatments……………………………………………………………..97

Table 12. Abundance of genotype temperature response classes across age classes

of samples………………………………………………………………105

Table 13. Unifrac distances (based on Euclidean distance of BOX-PCR profiles)

among genotype temperature response classes…………………..……..105

v LIST OF FIGURES

Chapter I: General Introduction

Figure 1. Location of the McMurdo Dry Valleys in Antarctica…………………26

Chapter II: Molecular Characterization of Ancient Algal Mats from the McMurdo Dry

Valleys, Antarctica: A Legacy of Genetic Diversity

Figure 2. DNA yield of algal mat samples………………………………………29

Figure 3. Bacterial 16S rRNA gene copy number of DNA templates…………...30

Figure 4. Rarefaction analysis of bacterial 16S rRNA gene clone libraries……..32

Figure 5. Composition of bacterial 16S rRNA gene clone libraries by phylum…35

Figure 6. Distribution of samples on the age class canonical axis from

redundancy analysis……………………………………………………...37

Figure 7 a-c. Abundance of 16S rRNA gene sequence groups distributed unevenly

among sample age classes………………………………………………..41

Chapter III: Recovery of Viable Bacteria from Ancient Algal Mats from the McMurdo

Dry Valleys, Antarctica

Figure 8. Growth curves of selected isolates in TSB at 15 °C……………..……..87

Figure 9 a-b. CFU abundance from heterotrophic plate counts on

a) R2A and b) 1/10 strength R2A medium………………………………90

vi Figure 10. Rarefaction analysis of BOX-PCR genotype occurrence by

sample…………………………………………………………………96

Figure 11. Estimated phylogeny of 16S rRNA sequences from ARDRA type 1

isolates……………………………..…………………………………..99

Figure 12. Correlation of pairwise BOX-PCR profile Euclidean distance with 16S

rRNA gene sequence p distance……………………………….….……100

Figure 13. Time to colony formation during growth temperature screening.….102

Figure 14. UPGMA tree of genotype BOX-PCR profiles.………….……...….109

vii ACKNOWLEDGEMENTS

This work would not have been possible without the assistance of many people at

Kent State and other institutions; too many to name, actually. I first of all would like to thank my guidance committee: Dr. Chris Blackwood, Dr. Laura Leff, and Dr. Christopher

Woolverton for their encouragement and assistance. I also need to thank colleagues at other institutions: Dr. Brenda Hall at the Univeristy of Maine, Orono and Dr. Jennifer

Baeseman at the University of Tromsø, Norway. I received a great deal of assistance, advice, and comaraderie from colleagues in the KSU Biology Department; I will certainly miss all of my friends in the department when I leave. I would particularly like to thank Larry Feinstein and Oscar Valverde who were always working alongside me and kept me company during long hours in the lab.

Funding for this research came from a Kent State startup grant to Dr. Chris

Blackwood and partially from a NSF grant to Dr. Jennifer Baeseman. I am also grateful for travel support received from Kent State University, the American Society for

Microbiology, and the NSF Office of Polar Programs.

viii

Chapter I

General Introduction

Terrestrial Antarctic habitats present a challenge to microbial growth and survival because of low temperatures, freeze-thaw cycles, and the scarcity of liquid water. In spite of these conditions, molecular and cultivation-based studies have revealed a diverse microbial flora on the Antarctic continent, including the McMurdo Dry Valleys

(reviewed in Vincent, 2000; Tindall, 2004). The McMurdo Dry Valleys represent a particularly harsh environment within the Antarctic in which resources needed for microbial metabolic activity are often unavailable (e.g. liquid water), forcing organisms to undergo periods of dormancy (Horowitz et al. , 1972; Kennedy, 1993; Treonis et al. ,

2002). For example, metabolic activity in Dry Valley cryptoendolithic communities may only be possible for 400-1050 hours per year (Friedman et al. , 1993). Sun and

Friedmann (1999) noted that in Dry Valley cryptoendolithic communities, ‘biological and geological time scales overlap’ due to the extremely short growing seasons.

Adaptation to withstand environmental stresses is thought to be a significant factor in the evolution of Antarctic microbes and an underlying cause for the existence of endemic Antarctic microbial taxa. The psychrophilic or psychrotolerant characteristics of

Antarctic microbes (and metazoans as well) have received a substantial amount of scientific interest (reviewed by Deming, 2002). Many Antarctic bacteria (Franzmann and

Dobson, 1993; Nadeau et al. , 2001; Spring et al. , 2003) and algae (Seaburg et al. , 1981)

1 2

possess lower optimal growth temperatures than related strains from temperate climates.

Other Antarctic microorganisms are closely-related to microbes isolated from non-

Antarctic cold environments including Arctic sea ice (Staley and Gosink, 1999), refrigerated foods (Franzmann et al. , 1991; Spring et al. , 2003), and permafrost (Fruhling et al. , 2002). Antarctic microbes also appear to be adapted to withstand stresses associated with dormancy and dormancy-inducing conditions, namely desiccation/rehydration and freeze/thaw cycles (Davey, 1989; Šabacká and Elster, 2006).

Antarctic algal mats can rapidly resume metabolic activity after years of dormancy

(Hawes et al. , 1992) and can survive nearly-intact after more than two decades of dormancy (McKnight et al. , 2007). In addition, long-term microbial dormancy has been examined in Arctic and Antarctic glacial ice and permafrost (Johnson et al. , 2007;

Willerslev et al. , 2004; reviewed in Price, 2007). Glacial ice and permafrost contain unusual environmental conditions which are likely to influence microbial preservation; hence, studies of dormancy in a desiccating environment provide a point of comparison to glacial ice and permafrost. In spite of this potential importance, the response of

Antarctic microbes to long-term (millennial-scale) dormancy imposed by desiccating conditions has not been studied. The research presented in this thesis was carried out to evaluate the possibility for Antarctic microbes and microbial DNA to be preserved under long-term desiccation-imposed dormancy. Emphasis was placed on evaluating factors affecting community composition within samples, including differences in the robustness of taxa to dormancy. Additionally, I sought to evaluate the relatedness of isolates from

3

ancient samples to those from the modern sample using both a genotyping technique

(BOX-PCR) and temperature-growth relationships.

Cellular Dormancy and Preservation

Dormant cells are commonly defined as cells that have ceased metabolic activity but retain viability (Roszak and Colwell, 1987). are the most well-known bacterial dormant state of bacteria (Gould, 2006), but other dormant cell types have been described for diverse bacterial groups, including cyanobacterial akinetes (reviewed in

Adams and Duggan, 1999) and cyst-like cells which occur in a variety of gram-negative and gram-positive bacteria (Suzina et al. , 2004). Dormancy may be considered an adaptation to withstand environmental stresses (e.g. formation; Gould, 2006) or as a condition imposed by environmental stresses (Potts, 1994, Roszak and Colwell,

1987).

The rate of chemical degradation of DNA and other macromolecules is thought to be the primary factor determining the survival of microorganisms over long-term dormancy (Kennedy et al. , 1994). Analysis of ancient DNA allows reserachers to directly examine the genetics of ancient organisms and answer questions which cannot be addressed by modern DNA (Hofreiter et al. , 2001). Because dead or dormant cells lack access to repair pathways used by metabolically active cells, they suffer increasing damage to DNA and other cellular components over time (Lindahl, 1993). Accumulated damage eventually limits cellular viability and the availability of DNA to be amenable to techniques such as PCR (Lindahl, 1993; Willerslev and Cooper, 2005). Degradation of

4

DNA in ancient materials is thought to limit the feasibility of recovery of ancient DNA older than 1 million years, even under ideal conditions, (Hofreiter et al. , 2001) and must be considered in the design and interpretation of ancient DNA studies.

Damage to ancient DNA arises from a variety of chemical and physical processes.

Hydrolytic reactions result in single strand breaks (SSBs) and double strand breaks

(DSBs) of the phosphodiester backbone, which prevent PCR amplification (Willerslev and Cooper, 2005). Hydrolytic reactions also produce abasic sites that can result in strand breaks after undergoing β-elimination (Paabo, 1989; Hofreiter et al. , 2001) and produce miscoding base derivatives from the deamination of bases (most frequently cytosine deamination to uracil; Hofreiter et al. , 2001b). Ionizing radiation can also cause strand breaks directly (Lindahl, 1993). Exposure to reactive oxygen and ionizing radiation produces a variety of base derivatives, including hydantoins, which inhibit

DNA polymerases (Hoss et al. , 1996). Condensation reactions (i.e. Maillard reactions) occur between reducing sugars and nucleic acids, resulting in glycosylation of nucleic acids (Potts, 2001). Interstrand cross-links (ICLs) resulting from alkylating agents are also potential pathways of DNA damage (Willerslev and Cooper, 2005). In addition to gradual damage to biological molecules during long-term dormancy, rapid damage can be caused by processes associated with dormancy (i.e. freezing/thawing or desiccation/rehydration; Potts, 2001).

Although rates of DNA degradation by individual chemical processes have been characterized in vitro (e.g. Lindahl and Nyberg, 1972; Lindahl, 1993), the rates and types of damage affecting natural ancient DNA are strongly influenced by prevailing

5

environmental conditions (Mitchell et al. , 2005). In general, low temperatures and dry conditions are expected to favor the preservation of biomolecules (Mitchell et al. , 2005;

Hoss et al. , 1996), despite the tendency of the initial desiccation process to cause damage.

Dry conditions limit the degradation of DNA by nucleases present in the cell along with spontaneous hydrolytic reactions and other aqueous reactions (Paabo, 1989). Low temperatures limit the rate of chemical reactions that spontaneously degrade DNA. For example, the rate of DNA depurination in aqueous solution decreases 1000-fold between

37°C and 0°C (Mitchell et al. , 2005).

Few generalizations are possible as to the dominant pathways of damage in natural ancient DNA. For example, Paabo (1989) failed to find a correlation between

DNA damage and age in desiccated materials ranging from 4-13,000 years old. Hoss et al. (1996) similarly failed to find a damage-age relationship among materials ranging from 40-50,000 years old. Paabo (1989) and Hoss et al. (1996) both found hydrolytic and oxidative damage pathways to be dominant in the ancient materials studied. Hansen et al. (2006) estimated that ICLs formed with a rate constant 100 times higher than single-strand breaks in ancient DNA from permafrost.

A number of repair strategies have been employed to address the problem of ancient DNA degradation. Treatment with a DNA polymerase in combination with a ligase has been used to repair single-strand breaks and abasic sites (Pusch et al. , 1998; Di

Bernardo et al. , 2002), and n-phenacylthiazolium bromide has been used to repair glycosylation products resulting from condensation reactions (Poinar et al. , 1998). Base derivatives can be removed by specific nucleases; Uracil-N-DNA glycosylase (UDG) has

6

been widely used in ancient DNA studies as uracil (resulting from the hydrolytic deamination of cytosine) is typically the most abundant miscoding base in ancient DNA

(Hofreiter et al. , 2001b; Brotherton et al. , 2007). Repair of ICLs has not been attempted for ancient DNA, and in living cells ICL repair is dependent on the homologous recombination repair system (reviewed in Sharova, 2005).

Recovery of Ancient Microoorganisms

The recovery of viable ancient microbes presents an exciting opportunity for researchers, as living microbes allow for more comprehensive studies than would be possible with DNA sequences alone. Additionally, studies of ancient microbes offer insights into microbial survival strategies in extreme environments, which can be interpreted as analogs for extraterrestrial environments (Abyzov et al. , 2006; Wynn-

Williams and Edwards, 2000). Reports of the recovery of cultivable bacterial cells have been made from a wide variety of ancient materials ranging from decades to millions of years of age (Renberg and Nilsson, 1992; reviewed in Kennedy et al. , 1994; Vreeland et al. , 2000; Cano and Borucki, 1995; Ronimus et al. , 2006; Gorbushina et al. , 2007). Due to the range of ages and materials of reported ancient bacteria, it has been difficult to establish consistent standards for the verification of recovery. Validation of the age of materials and sterilization procedures used are essential, and appropriate sterilization techniques vary depending on the material from which microbes are recovered (Kennedy et al. , 1994; Vreeland and Rosenzweig, 2002). As with the preservation of DNA, environmental conditions strongly influence the length of time over which microbes can

7

remain viable and cultivable, with cold and dry conditions favoring preservation

(Kennedy et al. , 1994).

Ancient DNA and Cultivable Microbes from Different Environments

Because prevailing environmental conditions influence the rate and type of damage experienced by microbial cells and DNA, attempts to compare patterns of preservation among different environments can be problematic. Glacial ice and permafrost have provided the most ancient environments from which microbial DNA and cultivable cells have been verifiably and consistently recovered. Fungal DNA and fungi were recovered from Greenland ice cores over 100,000 years old (Ma et al. , 1999).

Cultivable bacteria and bacterial DNA are apparently able to persist for several hundred thousand years, and possibly longer, in both ice and permafrost. Christner et al. (2003) recovered bacteria and 16S rRNA gene sequences from glacial ice approximately

750,000 years of age. Willerslev et al. (2004) amplified 600 bp fragments of the bacterial

16S rRNA gene from samples of Antarctic permafrost up to 400,000 years of age.

Johnson et al. (2007) recovered 4 kb PCR amplicons from permafrost samples 400,000-

600,000 years of age and were able to detect bacterial respiration in the same samples.

Metabolic activity has been detected in both ice (Price, 2007) and permafrost (Rivkina, et al. , 2000; Vishnivetskaya et al. , 2000; Johnson et al. , 2007), indicating that at least some cells are metabolically active and would contain ‘modern’ rather than ‘ancient’ DNA and macromolecules. Films or veins of liquid water which may support metabolic activity exist in both ice (Price, 2000) and permafrost (Rivkina, et al. , 2000). Willerslev et al.

8

(2004) and Johnson et al. (2007) found that high G+C Gram positive bacteria were better represented than low G+C Gram positive bacteria or Gram negative bacteria in permafrost samples greater than 400,000 years of age, suggesting that high G+C Gram positive bacteria persist due to continued metabolic activity.

Preservation of bacterial cells and DNA over long-term desiccation has not received attention comparable to cells in ice and permafrost, due in part to a lack of environments that represent suitable models for study (Billi and Potts, 2002). Gorbushina et al. (2007) recovered cells of Bacillus, Paenibacillus, and Aspergillus from 180 year- old dust. Postgate (1990) recovered thermoactinomycete endospores from Roman ruins approximately 1800 years old. Endospores of Bacillus and Thermoactinomyces have been isolated from a number of lake and ocean sediment samples 1000-7000 years old

(Nilsson and Renberg, 1992).

9

McMurdo Dry Valleys

The polar cold desert climate of the McMurdo Dry Valleys makes this an ideal site for the preservation of biological molecules. Mean annual air temperature in the Dry

Valleys ranges from -14.8 ºC to -30.0 ºC, and mean annual precipitation is less than 100 mm, all of which falls as snow (Doran et al. , 2002). DNA has been established to persist in Adelie penguin bones more than 5,000 years old (Ritchie et al. , 2004).

The Antarctic represents an important venue for microbiological research for several reasons. First, the Antarctic is likely an ‘indicator’ of climate change (Wall,

2005). Second, Antarctica presents the opportunity for discovering endemic species with useful properties to biotechnology, several of which have already been characterized

(Tindall, 2004). Finally, harsh Antarctic environments are potential analogs of extraterrestrial environments (Abyzov et al. , 2006; Wynn-Williams and Edwards, 2000).

Scientific understanding of Antarctic microbiology has been driven by examination of the distribution and evolutionary origins of Antarctic microbes.

Several distinct microbial habitats have been identified in the Dry Valleys and have been microbiologically characterized, including: soils, cryptoendolithic communities, lakes and streams, and algal mats (reviewed in Wynn-Williams, 1996; reviewed in Tindall, 2004). Understanding the distribution of microorganisms among community types and geographic areas has been a focus of research in Dry Valley microbiology and is an important component of understanding Antarctic microbiology

(Vincent 2000; Tindall, 2004).

10

Algal mat communities (consisting of , eukaryotic algae, and heterotrophic and autotrophic bacteria and Archaea) are common in Dry Valley lakes and streams and are major contributors to primary production and biogeochemical cycles

(Parker et al. , 1981; Wharton et al. , 1983; Ellis-Evans, 1996; Fernandez-Valiente et al. ,

2001, Brambilla et al. , 2001; Goosef et al. , 2004). The structure of mats inhibits the diffusion of oxygen, resulting in interior anoxic zones where denitrification (Gooseff et al. , 2004), sulfate reduction, and methanogenesis (Brambilla et al. , 2001) occur.

Anaerobic bacteria have been found to be abundant in algal mats (Brambilla et al. , 2001;

Spring et al. , 2003). Research on the response of mats to desiccation has predominately examined photosynthetic community members rather than heterotrophs (e.g. Davey,

1989; Hawes et al. , 1992). Specifically, Hawes et al. (1992) found cultivable cyanobacteria and green algae associated with a 3 year-old desiccated mat sample and

McKnight et al. (2007) found that algal mats in a Dry Valley stream resumed photosynthesis and N-fixation after more than two decades of dehydration.

Organization and Goals of this Thesis

I examined the effects of long-term dormancy on algal mat communities in the

McMurdo Dry Valleys, Antarctica, using samples representing a chronological age sequence from 8 years before present (yr bp) to 26539 yr bp. The points of focus of this thesis were 1) to determine whether bacterial DNA and cultivable bacterial cells were present in ancient materials, 2) to examine patterns of cellular and molecular preservation

11

in materials and 3) to examine factors influencing microbial diversity in ancient and modern samples.

In Chapter II, the results of molecular assays are presented. DNA extraction and quantitation, and Q-PCR of the bacterial 16S rRNA gene were used to examine the state of DNA preservation in samples. I hypothesized that the abundance of bulk DNA and the bacterial 16S rRNA gene copy number (scaled to DNA quantity) would be negatively correlated with sample age. Clone libraries of the bacterial 16S rRNA gene were examined to evaluate patterns of taxonomic distribution among samples. Redundancy analysis (RDA) (Legendre and Anderson, 1999) was used to test whether differences among samples were due to: a) differential preservation of taxa or b) differences in original abundance associated with the location of sample origin. Because ancient DNA is presumably damaged, I tested the effectiveness of a commercially-available DNA repair kit (PreCR kit, New England Biolabs, Ipswich, MA) on template DNA. The effectiveness of repair was evaluated by: a) comparison of the bacterial 16S rRNA gene copy number of repaired and unrepaired templates by Q-PCR and b) comparison of clone libraries of the bacterial 16S rRNA gene derived from repaired and unrepaired template.

Chapter III presents the results of cultivation-based assays. I hypothesized that number and diversity of cultivable bacterial cells would decline with increasing sample age. Autotrophic and heterotrophic enrichment cultures were performed to test for the presence of cultivable bacteria, and heterotroph colony forming unit abundance was measured by heterotrophic plate counts. The diversity of cultivable bacteria was examined by screening cultures by amplified ribosomal DNA restriction analysis

12

(ARDRA) and sequencing a portion of the 16S rRNA gene of selected ARDRA types. In order to optimize conditions for bacterial recovery, the effect of temperature and medium on heterotrophic plate count results was also tested. To further examine factors affecting the diversity of cultivable bacteria, genotyping was performed on isolates representing the most abundant ARDRA type by BOX-PCR (repetitive sequence-based PCR using the

BOX A1R primer; Koeuth et al. , 1995). Isolates screened by BOX-PCR were further screened by growth at different temperatures to examine: a) their broad temperature of growth requirements and b) differences in growth rate and optimal growth temperature among genotypes.

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Tindall BJ. Prokaryotic diversity in the Antarctic: the tip of the iceberg. Microbial

Ecology. 2004;47(3):271-283.

Treonis AM, Wall DH, Virginia RA. Field and Microcosm Studies of Decomposition and

Soil Biota in a Cold Desert Soil. . 2002;5(2):0159 - 0170.

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Vincent WF. Evolutionary origins of Antarctic microbiota: invasion, selection and endemism. Antarctic Science. 2000;12(3):374-385.

Vishnivetskaya T, Kathariou S, McGrath J, Gilichinsky D, Tiedje JM. Low-temperature recovery strategies for the isolation of bacteria from ancient permafrost sediments.

Extremophiles: Life Under Extreme Conditions. 2000;4(3):165-173.

Willerslev E, Hansen AJ, Poinar HN. Isolation of nucleic acids and cultures from fossil ice and permafrost. Trends in Ecology & Evolution. 2004;19(3):141-147

Willerslev E, Cooper A. Ancient DNA. Proceedings: Biological Sciences.

2005;272(1558):3-16.

Chapter II

Molecular Characterization of Ancient Algal Mats from the McMurdo Dry Valleys, Antarctica: A Legacy of Genetic Diversity 1

Abstract

The McMurdo Dry Valleys, an Antarctic cold desert, offer the opportunity to study the preservation of biological materials during long-term desiccation. Because the cold and dry climate of the Dry Valleys favors molecular preservation, and because some

Antarctic microbes possess adaptations that confer tolerance to desiccation, microbial biomolecules have the potential to persist over millennia in the Dry Valleys, although this possibility has not been investigated. In this study, I examined patterns of bacterial DNA preservation in modern to ancient (8 – 26,539 years old) algal mats from the Dry Valleys.

Additionally, the efficacy of DNA repair by a commercially-available kit was studied.

Observed patterns of DNA preservation were consistent with expectations for ancient materials. The composition of bacterial 16S rRNA gene clone libraries revealed potential differences in the preservation of DNA from different taxa: Firmicutes were abundant in ancient samples, but Cyanobacteria were absent. My results indicate that bacterial DNA may be preserved for several millennia in the Dry Valleys. The preservation of DNA has implications for the evolution of microbes in the Dry Valleys, as ancient materials could serve as a legacy source of genetic diversity to modern ecosystems.

1 This chapter represents a manuscript in preparation for submission to the journal Environmental Microbiology . 22

23

Introduction

Terrestrial Antarctic habitats are challenging for microbial growth and survival because of low temperatures, freeze-thaw cycles, and the scarcity of liquid water. The prevalence of unfavorable environmental conditions results in short growing seasons, and microbes are forced to undergo periodic dormancy. For example, Friedmann et al.

(1993) estimated that cryptoendolithic communities in the Dry Valleys are metabolically active for only 400-1000 hours per year. In spite of these environmental stresses, molecular and cultivation-based studies have revealed a diverse microbial flora on the

Antarctic continent, including in the McMurdo Dry Valleys (reviewed by Vincent, 2000 and Tindall, 2004). Although the manner in which Antarctic biota are adapted to low temperatures has received a large amount of scientific attention (reviewed in Deming,

2002), adaptations to tolerate desiccation/rehydration and freeze/thaw cycles have received less attention (Davey, 1989; Šabacká and Elster, 2006) .

Algal mat communities (including eukaryotic algae, heterotrophic and autotrophic bacteria, and Archaea) are a common microbial growth form in the McMurdo Dry

Valleys and are major contributors to primary productivity and biogeochemical cycling

(Parker et al. , 1981; Wharton et al. , 1983; Ellis-Evans, 1996; Gooseff et al. , 2004).

Deposits of algal mats dating to the late Holocene are found in the Dry Valleys as remnants of glacial lakes (Doran et al. , 1994; Hall et al. , 2001; Hall et al. , 2002). These mats, in addition to other paleosediment deposits have been identified as “legacy” carbon sources to the Dry Valley ecosystems (Moorhead et al. , 1999; Burkins et al. , 2001). If microbes and microbial DNA are able to persist in these materials, they could also act as

24

a source of genetic diversity. Research on the response of these mats to desiccation has predominately examined photosynthetic community members (e.g. Davey, 1989) rather than heterotrophs. Specifically, Hawes et al. (1992) observed viable cyanobacteria in mats several years of age, and McKnight et al. (2007) observed microbial growth, carbon fixation, and nitrogen fixation upon rehydration of stream algal mat communities which had been desiccated for more than two decades. However, the potential for microbes and microbial DNA to persist over millennial-scale periods of desiccation-imposed dormancy in the Dry Valleys has not been investigated.

The McMurdo Dry Valleys are a favorable environment for the preservation of

DNA due to their cold desert climate. DNA has previously been recovered from Adelie penguin bones >5,000 years of age from the Dry Valleys (Ritchie et al. , 2004). Because the persistance of ancient DNA is limited by damage that accrues over periods of dormancy (Lindahl, 1993; Willerslev and Cooper, 2005), part of the criteria for evaluating the authenticity of ancient DNA is evaluating the manner in which DNA abundance and characteristics change in relation to material age (Willerslev and Cooper,

2005). The amount and integrity of DNA, as well as the diversity of retrievable sequences, are expected to decrease over time (Willerslev and Cooper, 2005). Viable bacterial cells and DNA have been recovered from glacial ice and permafrost that formed several hundred thousand years ago (Christner et al. , 2003; Vishnivestkaya et al. , 2000;

Willerslev et al. , 2004; Johnson et al. , 2007), but persistence in these environments may be due to metabolic activity in films of liquid water (Rivkina et al. , 2000; Johnson et al. ,

2007; Price, 2007). In contrast, preservation of bacterial cells and DNA over long-term

25

desiccation has not been extensively studied, due, in part, to a lack of suitable environments (Billi and Potts, 2002).

Because of the paucity of information on heterotrophic components of desiccated communities, I examined the occurrence of bacterial DNA in samples of ancient, desiccated algal mats. These samples were collected from Victoria, Taylor, and Wright

Valleys in the McMurdo Dry Valleys (Figure 1). Radiocarbon ( 14 C) dating was previously used to determine ages of these samples (Hall et al. , 2001; Hall et al. , 2002;

Hall et al. , 1997), which represent a chronological sequence from 8 to 26,539 years before present. Because of the accrual of macromolecular damage in ancient materials, I expected the quantity of bulk DNA, the quantity of PCR-amplifiable bacterial 16S rRNA templates (scaled to DNA quantity), and the richness of bacterial 16S rRNA templates to decline with increasing sample age (Willerslev and Cooper, 2005). This study had three primary purposes: 1) to establish whether algal mat samples displayed patterns of DNA preservation consistent with expectations for ancient materials, 2) to explain differences in microbial assemblages (as revealed by 16S rRNA gene sequences) based on sample age and geographical location, and 3) to evaluate the use of DNA repair as a means for recovering a greater diversity of gene sequences from ancient samples.

26

Figure 1: Location of Taylor, Wright, and Victoria Valleys. Inset shows the location of the Dry Valleys in Antarctica.

27

Results and Discussion

Bulk DNA abundance and 16S rRNA gene content

Bulk DNA concentrations were measured to assess differences in DNA content among samples. All samples were subjected to two rounds of DNA extraction and one sample (sample 12910) was subjected to a third round of extraction. DNA yields from the first round of extraction represented, on average, 75% of total DNA yield (Table 1).

The total DNA yield from all rounds of extraction is presented in Figure 2. Total DNA yield varied by two orders of magnitude among samples of different ages, ranging from

2.1 ng mg -1 (sample 8) to 0.026 ng mg -1 (sample 12303) (Figure 2), and was negatively correlated with sample age (p<0.001).

To assess the integrity of bulk DNA, bacterial 16S rRNA gene abundance was measured by Q-PCR (Figure 3). Bacterial 16S rRNA genes were detected in all samples except sample 12303. As expected, bacterial 16S rRNA gene copy number was negatively correlated with sample age (p<0.05). The results of DNA extraction and Q-

PCR are consistent with the expectations for ancient materials, namely, that the amount of DNA and its integrity would decline with increasing sample age (Willerslev and

Cooper, 2005).

28

Table 1: DNA yield (ng mg -1) of samples during successive rounds of extraction. Values ± SE of triplicate measurements. ND – below detection limit. Second Third Sample First Round Round Round Total 8 1.75± 0.157 0.334± 0.095 - 2.09 8619 0.95± 0.034 0.026± 0.036 - 0.979 8643 1.34± 0.159 0.156± 0.082 - 1.49 11164 0.067± 0.011 0.055± 0.039 - 0.123 11185 0.071± 0.018 ND - 0.071 12303 0.026± 0.009 ND - 0.026 12910 0.186± 0.004 0.194± 0.024 0.036± 0.008 0.414 26539 0.029± 0.006 ND - 0.029

29

10 ) -1 1

0.1 DNA (ng mg yield DNA 0.01 0 10000 20000 30000

Sample 14 C age

Figure 2: Bulk DNA yield of algal mat samples. Error bars represent SE of triplicate measurements.

30

6.0 Unrepaired -1 Template 5.5 Repaired 5.0 Template

4.5

4.0 bact. 16S 16S bact. copies (ngDNA)

10 3.5 0 10000 20000 30000 Log

14 Sample C age

Figure 3: Bacterial 16S rRNA gene copy number of DNA templates. Error bars represent SE of at least triplicate measurements.

31

Bacterial diversity and community composition

To examine the effects of sample age and location on bacterial community composition, clone libraries of the bacterial 16S rRNA gene were constructed from all samples except 12303 (which did not yield 16S rRNA gene PCR products). Clone libraries were also constructed using repaired template DNA from samples 8, 8619, and

26539; these libraries are referred to as 8R, 8619R and 26539R. These samples were selected to allow the effect of repair on samples of different ages to be evaluated. PCR reactions using extraction negative controls as templates did not yield products. A total of 751 non-chimeric sequences were acquired from libraries, which were classified into

215 OTUs using a 3.0% Jukes-Cantor distance cut-off. Rarefaction curves of Chao’s richness estimator (Chao 1) approached an asymptote for all libraries, indicating that sequencing adequately captured the richness of PCR products (Figure 4). Chao 1 varied from 152 OTUs in sample 8 to 27 OTUs in sample 11164 (Table 2). A greater number of phyla were detected from sample 8 (11) than from ancient samples (4 to 7). Although a decline in OTU richness with sample age was expected, richness was not significantly correlated with sample age (p=0.30). Richness estimates for ancient samples varied from

27 to 81 and were within the range of richness estimates for Dry Valley soils using

ARDRA screening of clone libraries: Aislabie et al. , 2006 (29-85) and Smith et al. , 2006

(49-57). The estimated richness of sample 8 was higher than the estimated richness of most ancient samples.

32

180 8 160 8R 140 8619 120 8619R 100 8643

80 11164 Richness

1 60 11185

40 Chao

20

0 0 20 40 60 80 100 120 140 Library size

Figure 4: Rarefaction analysis of bacterial 16S rRNA gene clone libraries. Rarefaction curves of Chao 1 were estimated using 50 iterations in Estimate S (Colwell, 2005).

33

Table 2: Diversity and richness estimates of bacterial 16S rRNA gene clone libraries. For S obs and Chao 1, 95% upper and lower confidence intervals are in parentheses.

Library Shannon's H Chao 1 Sobs Coverage 8 3.01± 0.15 152 (104-259) 66 (52-80) 0.70 8R 2.84± 0.1 73 (45-159) 31 (21-41) 0.71 8619 2.72± 0.13 49 (36-92) 30 (21-39) 0.73 8619R 2.83± 0.11 57 (40-113) 32 (22-42) 0.66 8643 2.3± 0.13 33 (23-76) 20 (12-28) 0.78 11164 2.08± 0.15 27 (20-58) 18 (10-26) 0.89 11185 2.78± 0.03 31 (23-61) 20 (12-28) 0.56 12910 3.06± 0.11 79 (57-136) 44 (32-56) 0.61 26539 2.91± 0.14 81 (64-125) 54 (42-66) 0.85 26539R 2.76± 0.11 61 (44-112) 35 (26-43) 0.71

34

Clone sequences were classified to phylum using the Ribosomal Database Project classifier tool (Wang et al. , 2007). Sequences classified with <80% confidence were considered ‘unclassified’. The composition of clone libraries by phyla is presented in

Figure 5. Clone libraries were dominated by sequences belonging to the

(25.7% of all sequences), Firmicutes (23% of all sequences), and (16.2% of all sequences). Sequences belonging to the Cyanobacteria were abundant in sample 8 but were not recovered from any ancient samples. Because heterotrophic community members of Antarctic algal mats have been studied less frequently than phototrophic community members (e.g. Taton et al. , 2003; Sabbe et al. , 2004; Jungblut et al. , 2005;

Taton et al. , 2006), there is a limited amount of information from comparable analyses.

However, Brambilla et al. (2001) found that a bacterial 16S rRNA gene clone library from a Lake Fryxell algal mat was dominated by members of the Firmicutes (41%),

Bacteroidetes (24%), (18%) and Verrucomicrobiales (11%).

35

8 Cyanobacteria 8R 8619 Proteobacteria 8619R unidentified 8643 Bacteroidetes 11164 11185 Firmicutes 12910 Actinobacteria 26539 Other 2653 …

0 20 40 60 80 100 Percentage of Library

Figure 5: Composition of bacterial 16S rRNA gene clone libraries by phylum.

36

Distance-based redundancy analysis (RDA) was used to test for effects of sample age and valley of origin (“location”) on sample community composition. The effect of age was tested by dividing samples into 4 age classes (Table 3). The effect of location was non-significant using either Hellinger distance calculated from OTU abundances or

Unifrac distance (Table 3) (Lozupone and Knight, 2005). Age was found to be nearly significant by both distance metrics (OTU distances: p=0.110, 23% of total variance;

Unifrac distance: p=0.150, 21% of total variance). The canonical ordination axis based on age class shows that the samples are relatively evenly distributed except for sample 8, which is farther away from the remainder of the samples (Figure 6). However, a greater amount of variation is explained by the first non-canonical ordination axis than by the canonical axis based on age class (Figure 6).

Table 3: Results of permutation tests of RDA significance (p values are given). Factor OTU distance Unifrac distance Age class 0.11 0.15 Location 0.357 0.57 Repair 0.9 0.95

37

1

0.8 11164 0.6 8619

0.4 8643

0.2

0 Axis (28.2%) 1 Axis -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 -0.2 26539 11185 -0.4

12910 -0.6 8 -0.8 Canonical Axis from Age Class (21%)

Figure 6: Distribution of samples on the age canonical ordination axis from redundancy analysis. Parentheses show the amount of variation explained by each axis.

38

Distribution of bacterial taxa across sample age

The analysis of lineages provided by Unifrac (Lozupone et al. , 2006) was used to determine which phylogenetic groups were unevenly distributed among age classes and nucleotide BLAST (Zhang et al. , 2000) was used to determine the nearest cultivated relatives of these groups (Table 4). Sequence groups which significantly varied in abundance with sample age tended to have one of three patterns of abundance: 1) two sequence groups were only present in sample age class 1 (represented by sample 8), 2) three sequence groups were overabundant in sample age classes 2 and 3, and 3) three sequence groups were overabundant in sample age classes 3 and 4.

Two groups found in sample 8 were not found in any ancient samples (Figure 7a):

Cyanobacteria , and a group of sequences belonging to the . Sequences belonging to the Cyanobacteria were related to the genera Leptolyngbya (95%) and

Phormidium (98%). Both Leptolyngbya and Phormidium commonly occur in Dry Valley lake algal mats (Gordon et al. , 2000; Taton et al. , 2003; Taton et al. , 2006), so recovery of these sequences was not unexpected. The Chloroflexi sequences had no cultured relatives with >85% maximum BLAST sequence identity, but were very similar (99%) to sequences collected by Gordon et al. (2000) from ice-entrapped algal mats from Lake

Bonney, Taylor Valley. In general, Chloroflexi can be found in algal mats from a variety of environments, and are thought to be important to the sulfur cycle in these mats

(reviewed in Paerl et al. , 2000). Chloroflexi have been found in Antarctic algal mats

(Brambilla et al. , 2001) and in some Antarctic soils and cryptoendolithic communities,

39

although this group is not dominant in soils (de la Torre et al. , 2003; Smith et al. , 2006;

Moodley, 2004).

Sequences belonging to the Firmicutes (including sequences affiliated to both the

Bacillales and Clostridiales ) and were significantly overabundant in age classes 2 and 3 (Figure 7 b). Actinobacteria sequences are common in 16S rRNA clone libraries from Dry Valley soils, typically constituting 10-40% of sequences (Smith et al. ,

2006; Moodley, 2004; Aislabie et al. , 2006). Actinobacteria have also been commonly recovered from Dry Valley soils by cultivation-based approaches (Siebert and Hirsch,

1988; Aislable et al. , 2006; Babalola et al. , 2009). Actinobacteria represented only 1% of clone library 16S rRNA gene sequences in the data of Brambilla et al. (2001), but have commonly been cultured from algal mats (Brambilla et al. , 2001; Van Trappen et al. ,

2002; Reddy et al. , 2003).

40

8

8619 8643

11164 Chloroflexi Sample 11185 Cyanobacteria 12910

26539

0 0.2 0.4 Proportion of Library

Figure 7 a: 16S rRNA gene sequence groups significantly overabundant in sample age class 1.

8

8619 Actinomycetales 8643

11164 Clostridiales Sample 11185 Bacillales 12910

26539

0 0.2 0.4 0.6 0.8

Proportion of Library

Figure 7 b: 16S rRNA gene sequence groups significantly overabundant in sample age classes 2 and 3.

41

8 8619 Bacteroidetes

8643 Chloroflexi 11164

Sample 11185 12910 26539

0 0.2 0.4 Proprtion of Library

Figure 7 c: 16S rRNA gene sequence groups significantly overabundant in sample age classes 3 and 4.

42

Table 4: Phylogenetic affiliation of groups unevenly distributed among sample age classes. Sequences from nearest cultured relatives were retrieved by BLAST. Multiple entries for a phylum represent separate OTUs within that phylum.

% Max. GenBank Phylum Nearest Relative Identity Accession Reference Firmicutes Lysinibacillus 100 GQ280035 Datta et al. , fusiformis unpublished Firmicutes Sporosarcina 99 AJ514408 Reddy et al. , 2003 macmurdoensis Firmicutes Planococcus 99 AF324659 Zhu et al. , psychrotoleratus unpublished Bacteroidetes Adhaeribacter 96 AJ626894 Rickard et al. , aquaticus 2005 Bacteroidetes Roseivirga 91 DQ080996 Lau et al. , 2006 spongicola Bacteroidetes Gillisia sp. ZS3-9 97 FJ889660 Ji et al. , unpublished Chloroflexi none greater than - - - 85% Cyanobacteria Phormidium sp. 98 EF654082 Siegesmund et al. , SAG 37.90 2008 Cyanobacteria Leptolyngbya 95 AY493575 Taton et al. , 2006 frigida Firmicutes Desulfosporosinus 98 AJ582757 Ramamoorthy et lacus al. , 2006 Firmicutes Clostridium 99 DQ296031 Suetin et al. , 2009 tagluense Firmicutes Psychrosinus 99 DQ767881 Sattley et al. , 2008 fermentans Firmicutes none greater than - - - 90% Firmicutes none greater than - - - 90% Firmicutes Desulfotomaculum 92 AJ577273 Morasch et al. , sp. Ox39 2004 Actinobacteria Kineococcus 97 DQ200982 Lee, 2006 marinus Actinobacteria Sporichthya 95 AB025317 Tamura et al. , polymorpha 1999 Actinobacteria Ornithinicoccus 99 AB098587 Hiraishi et al. , hortensis 2003

43

Table 4 (continued). % Max. GenBank Phylum Nearest Relative Identity Accession Reference Actinobacteria Cryobacterium 100 DQ515963 Zhange et al. , psychrotolerans 2007 Gemmatimon- none greater than - - - adetes 85% Chloroflexi Sphaerobacter 88 AJ420142 Hugenholtz and thermophilus Stackebrandt, 2004

44

Firmicutes , including anaerobic members of the Clostridiales , have been found to be common in 16S rRNA gene clone libraries from Antarctic algal mats (Brambilla et al. , 2001) and anoxic lake sediments (Bowman et al. , 2000). Members of the Firmicutes have also been cultured from algal mats, including members of the genera Sporosarcina

(Reddy et al. , 2003b), Planococcus (Reddy et al. , 2002), Bacillus (Van Trappen et al. ,

2002; Brambilla et al. , 2001), and Clostridium (Brambilla et al. , 2001; Spring et al. ,

2003). Studies using similar methodologies to this study have not found Firmicutes to be abundant in other Dry Valley habitats, including cryoconite holes (Christner et al. ,

2003b), cryptoendolithic habitats (Smith et al. , 2000; de la Torre et al. , 2003), and mineral soils (Moodley, 2004; Smith et al. , 2006; Aislabie et al. , 2006) (Table 6).

Firmicutes appear to be more abundant in coastal ornithogenic soils than in inland mineral soils (Aislabie et al. , 2008). Because Firmicutes are not known to be abundant in

Dry Valley soils, Firmicutes sequences recovered in this study are unlikely to have originated from contamination of the samples by exogenous soil bacteria, but rather are likely to represent bacteria endogenous to the mat samples. Most Firmicutes sequences obtained in this study which could be identified to were members of endospore- forming genera: Bacillus , Clostridium , Sporosarcina (Vos et al. , 2009),

Desulfosporosinus (Stackebrandt et al. , 1997), Lysinibacillus (Ahmed et al. , 2007),

Desulfotomaculum (Campbell and Postgate, 1965). The only apparent exception was the occurrence of sequences related to Psychrosinus fermentans , an endemic Antarctic genus which has not been observed to form endospores (Sattley et al. , 2008).

Table 5: Distribution of families within the Firmicutes in 16S rRNA gene clone libraries. Values represent percentage of total library. (-) represents not detected. 26539 Clostridiales 8 8R 8619 8619R 8643 11164 11185 12910 26539 R Clostridiaceae 3.3 3.8 26.6 21.5 13.7 - 4.0 - - - Ruminococcaceae - - 6.3 3.1 - 7.7 - - - - Veillonellaceae - - 15.6 12.3 - 1.5 - - - - Peptococcaceae - - 4.7 12.3 7.8 40.0 - - 0.6 - Total Clostridiales 3.3 3.8 53.1 49.2 21.6 49.2 4.0 - 0.6 -

26539 Bacillales 8 8R 8619 8619R 8643 11164 11185 12910 26539 R - 1.9 17.2 10.8 - 41.5 - - - 10.4 Paenibacillaceae ------4.0 - - - Total Bacillales - 1.9 17.2 10.8 - 41.5 4.0 - - 10.4

46

Table 6: Occurrence of selected phyla in 16S rRNA gene clone libraries from other Antarctic environments. Numbers represent proportional abundance in clone libraries. Study Smith et al., Smith et al., Smith et al., 2006 2006 2006 Site Miers Miers Bratina Valley Valley Island Environment soil soil soil Actinobacteria 15 40 25 Firmicutes - - - Cyanobacteria 40 - - Chloroflexi - 5 5 Bacteroides 15 5 5 Proteobacteria - - 10 Unclassified 20 25 30

Study Moodley Moodley Moodley Moodley Moodley 2004 2004 2004 2004 2004 Site MVT1 MVT5 MVT7 MVT9 MVT12 (Miers (Miers (Miers (Miers (Miers Valley) Valley) Valley) Valley) Valley) Environment soil soil soil soil soil

Actinobacteria 8 13 14 13 16 Firmicutes 3 - - - - Cyanobacteria 3 - - - 3 Chloroflexi - 6 - - - Bacteroides - - - - - Proteobacteria 19 25 7 9 17 Unclassified 54 53 67 66 55

47

Table 6 (continued).

Study Aislabie Aislabie Aislabie Aislabie Aislabie et al., et al., et al., et al., et al., 2006 2006 2006 2006 2006 Site Bull Lake Lake Marble Pass Vanda Vanda Point

Environment soil soil soil soil soil surface subsurface surface subsurface surface Actinobacteria 22 34 17 22 16 Firmicutes - - - - 2 Cyanobacteria 6 2 3 10 1 Chloroflexi - - - - - Bacteroides 23 15 29 23 21 Proteobacteria 33 25 16 11 14 Unclassified - - - - -

Study Aislabie et Smith et al., Smith et al., de la Torre al., 2006 2000 2000 et al., 2003 Site Marble Vestfold Vestfold Dry Point Hills Hills Valleys

Environment soil crypto- crypto- crypto- subsurface endolith endolith endolith Actinobacteria 4 18 17 5 Firmicutes 1 - - - Cyanobacteria - 70 65 30 Chloroflexi - - - - Bacteroides 20 - - 2 Proteobacteria 22 9 16 31 Unclassified - - - 5

48

Sequence groups that were significantly overabundant in sample age classes 3 and

4 included groups within the Chloroflexi , Bacteroidetes , and Gemmatimonadetes . The

Chloroflexi group was not closely related (9.6% distance) to the GNS bacterial sequences recovered from the sample 8, being more closely related to the Thermomicrobia .

Thermomicrobia sequences have been recovered from Antarctic environments (de la

Torre et al. , 2003; Niederberger et al. , 2008). Bacteroidetes sequences are common in clone libraries of Dry Valley soils (Moodley, 2004; Smith et al. , 2006; Aislabie et al. ,

2006) and have been cultured from Antarctic soils (Aislabie et al. , 2006; Aislabie et al. ,

2006b), cryoconite holes (Christner et al. , 2003b), and algal mats (Brambilla et al. , 2001;

Van Trappen et al. , 2002). The largest groups of Bacteroidetes sequences encountered in this study were related to genera predominately found in marine habitats: Roseivirga

(Nedashkovskaya et al. , 2005) and Gillisia, (Van Trappen et al. , 2004). The retrieval of sequences related to marine genera is not uncommon in Antarctic soils or algal mats (e.g.

Aislabie et al. , 2006; Smith et al. , 2006), and many microbes in these habitats are thought to have a marine origin (Tindall, 2004).

Repair of template DNA

I hypothesized that enzymatic repair of template DNA would result in an increase in bacterial 16S rRNA gene copies (per ng of DNA) and allow a greater diversity of 16S rRNA gene sequences to be amplified from template DNA. The effect of repair on template bacterial 16S rRNA gene content was evaluated by a mixed-effects linear model with variance constrained by sample. Bacterial 16S rRNA gene copy number of repaired

49

templates was on average 1.9 fold higher than unrepaired templates, but the effect of repair on copy number was only marginally significant (p=0.057). The interaction between sample age and repair was also non-significant (p=0.15). Additionally, the effects of the repair process on clone library richness (p=0.55) and composition (as tested by distance-based redundancy analysis, p=0.90) were non-significant. The repair kit used

(PreCR kit, New England Biolabs, Ipswich, MA) is designed to repair several forms of damage known to occur in ancient DNA: thymidine 49immers, abasic sites, single strand breaks, deaminated cytosine (by Uracil-N-DNA glycosylase), and oxidized guanine and pyrimidine bases (by endonuclease IV, endonuclease VII, and Fpg) (New England

Biolabs, Product Protocol M0309). It is similar to treatments previously used on ancient

DNA (Pusch et al. , 1998; Gilbert et al. , 2003), but contains a wider variety of repair processes. In spite of this breadth of coverage, a number of other forms of damage known to occur in ancient DNA are not repaired by this kit, namely glycosylation, DNA- protein cross-links, and inter-strand cross-links (Hofreiter et al. , 2001). Because environmental conditions strongly influence the type and rates of DNA damage, it is difficult to make predictive generalizations about the types of DNA damage expected in ancient materials (Mitchell et al. , 2005). It is possible that repair of DNA from samples in this study was non-effective because DNA was predominately damaged in ways not treatable by the repair process used.

50

Conclusions

This study examined the preservation of bacterial DNA in ancient algal mat samples from the McMurdo Dry Valleys and factors influencing bacterial community composition as determined by 16S rRNA gene clone libraries. DNA abundance and integrity declined with sample age, matching expectations for ancient materials. When used as a canonical variable in redundancy analysis, age class explained a greater portion of variation (23%, p=0.110) than location (9%, p=0.357). Because the repair treatment used in this study did not alter clone library richness or composition, two confounded effects of sample age on clone library composition could not be statistically separated, namely: 1) differences in library composition resulting from differential preservation of

DNA from various taxa, and 2) differences in library composition resulting from differences in the bacterial assemblages originally present in samples. However, observed patterns of clone library composition point to possible differences in the responses of some taxa to long-term dormancy. Because Cyanobacteria are common in

Antarctic algal mat communities, the absence of Cyanobacteria 16S rRNA gene sequences from ancient clone libraries was unexpected. The absence of Cyanobacteria sequences may indicate that Cyanobacteria are poorly preserved compared to heterotrophic bacteria in ancient samples, and are less resilient than heterotrophic bacteria to long-term dormancy. Alternatively, this finding may be the result of Cyanobacteria being absent from the original microbial assemblages in ancient samples.

The abundance of Firmicutes sequences in ancient samples may be the result of

Firmicutes DNA being favorably preserved within endospores. Firmicutes endospores

51

are among the most stress-resistant cell types (Gould, 2006). Due to this stress- resistance, endospores are thought to be tolerant to long periods of dormancy, and intact endospores or Firmicutes DNA have been recovered from a variety of ancient materials

(Renberg and Nilsson, 1992; reviewed in Kennedy et al. , 1994; Gorbushina et al. , 2007;

Rollo et al. , 2007, Yung et al. , 2007). Within the Dry Valleys, Firmicutes , and specifically Clostridiales , sequences appear to be distinctive to algal mat systems. These sequences are unlikely to have originated from soil-borne contamination.

Methods

Sample collection and characterization

Ancient algal mat samples used in this study were collected from Victoria,

Wright, and Taylor valleys and 14 C ages were determined by Brenda Hall (Table 7).

Samples were located 5-15 cm below the soil surface at the time of collection. (Note: throughout this manuscript, individual samples are referred to by their 14 C age [e.g., the sample dated to 12303 years before present is referred to as sample 12303]). Sample

8619 was previously described in Hall et al. (2001), samples 8643, 11185, and 12303 were described in Hall et al. (2002), and sample 12910 was described in Hall et al.

(2000); samples 11164 and 26539 have not previously been described in publications.

Samples were collected aseptically and stored dry at room temperature until analysis.

Sample 8 was collected from Upper Victoria Lake in 2001; the age of this sample is based on the collection date rather than 14 C age.

52

Table 7: Sample 14 C ages (years before present) And locations of origin.

14 C age Location Age Class 8 Victoria Valley 1 8619± 66 Wright Valley 2 8643± 72 Victoria Valley 2 11164± 67 Victoria Valley 3 11185± 75 Victoria Valley 3 12303± 78 Victoria Valley 3 12910± 98 Taylor Valley 3 26539± 156 Wright Valley 4

53

DNA Extraction

DNA was extracted using Epicentre SoilMaster DNA kits (Epicentre

Biotechnologies, Madison, WI), following the manufacturer’s directions with modifications. DNA was extracted from 100-150 mg of material for ancient samples and

40 mg of material for the sample 8. Extracted DNA was dissolved in 100 L of 10 mM

Tris (pH 8.0) and stored at -20 ºC. DNA was divided into aliquots for quantitation, PCR amplification, and enzymatic repair and quantitative PCR (Q-PCR). Also, a second round of extraction was performed on all samples to assess efficiency of DNA recovery during the first round of extraction (Feinstein et al. 2009). To accomplish this, the microbial mat pellet remaining after cell lysis was stored at -20 ºC and subjected to a second round of extraction by the same procedure. One sample (sample 12910) was also subjected to a third round of extraction because the amount of DNA recovered was comparable in the first and second rounds of extraction (Table 2). Only DNA recovered from the first extraction was used for repair, Q-PCR, and cloning. All steps of extraction were carried out using aerosol barrier pipette tips. Negative controls consisted of sterile water and were performed alongside extractions at a ratio of 1 control to 4 extractions.

Extracted DNA was quantified by the Picogreen dye fluorescence assay

(Invitrogen Molecular Probes, Eugene, OR). Fluorescence was read at λex 480 nm and

λem 520 nm in a Synergy 2 plate reader (Biotek Instruments, Winooski, VT). DNA concentration was calculated by comparison to a standard curve of bacteriophage λ DNA diluted to 0.05 to 5.0 ng L-1.

54

DNA Repair

Bulk DNA extracts were repaired using the PreCR DNA repair kit (New England

Biolabs, Ipswich, MA). Repair reactions contained the following: 1X NEB Thermopol buffer (10 mM KCl, 10 mM (NH 4)2SO 4, 20 mM Tris-HCl, 2 mM MgSO 4, 0.1% Triton X-

100, pH 8.8), 1 g L-1 BSA, 0.1 mM each dNTP, 0.5 mM NAD +, and 1X repair enzyme mixture. Reactions were incubated for 120 minutes at room temperature (~22 ºC) and stored at -20 ºC until analysis. Repair negative controls (RNCs) consisted of the repair master mix including enzyme mixture plus 5 L sterile water in place of template.

Unrepaired negative controls (UNCs) were also performed and consisted of the repair master mix without enzymes plus 5 L sterile water. RNCs and UNCs were performed in duplicate. As a control for the effect of the repair buffer on Q-PCR reactions, C t values from reactions of repaired template were compared to C t values of reactions using the corresponding template diluted in repair buffer lacking enzymes.

Q-PCR

Q-PCR was performed using the primers Eub338F-0-III (Blackwood et al. , 2005) and 518R (Fierer et al. 2005). A Q-PCR standard was constructed by diluting a plasmid containing a bacterial ribosomal gene insert, in a 10-fold dilution series from 2.48x10 7 copies to 2.48x10 2 per L. Plasmid was diluted in repair mastermix lacking enzymes.

PCR reagent concentrations in a reaction volume of 25 L were as follows: 0.16 M each primer, 0.2 mM each dNTP, 0.025 U L-1 Taq DNA polymerase (Gene Choice,

Frederick, MD), 1x ammonium buffer (1.5 mM MgCl 2, 75 mM Tris-HCl, 20 mM

55

-1 (NH 4)2SO 4, 0.1% Tween 20, pH 8.5), 0.5 mM MgCl 2 (total 2.0 mM MgCl 2), 0.1 g L

BSA, 0.5-2.0 L template DNA, 0.167X Sybr Green, and 30 nM 5-ROX. Cycling conditions were as follows: an initial denaturation step of 3 minutes at 95 ºC, followed by

45 cycles of 30 seconds at 95 ºC, 30 seconds at 57 ºC, and 90 seconds at 72 ºC, and a final elongation step of 7 minutes at 72 ºC. Amplification was performed in a Stratagene

MX3005P thermal cycler (Agilent Technologies, Santa Clara, CA). Triplicate no- template controls (NTCs), in which water was used in place of template, were also performed. Sample copy number was calculated by comparing sample C t to the curve calculated from standard C t values. Starting template copy number of repair reactions was compared directly to that of unrepaired template DNA diluted to an identical level (1:5,

1:20, or 1:80) in repair buffer lacking enzymes. Template copy number of RNCs and

UNCs were also assayed. Calculated sample copy number was standardized per ng of template DNA.

Statistical Analyses of DNA yield and Q-PCR data

Samples ages were divided into 4 age classes for statistical analyses: 1 (8 ybp); 2

(8619 and, 8643 ybp); 3 (11164, 11185, 12303, and 12910 ybp) and 4 (26539 ybp). The relationship between DNA yield and age was tested with a Pearson product-moment correlation of yield and sample age (expressed in years before present). Q-PCR data were analyzed with a linear mixed model, with age (expressed as one of four age classes) designated a covariate, repair designated a fixed effect, and sample designated a random effect (with one repaired and one unrepaired value per sample). Q-PCR data were

56

expressed as 16S rRNA copies per ng DNA and was log10 transformed prior to analysis.

Statistical analyses were performed in R (Version 2.9.1, R Core Development Team,

2009).

Amplification and Cloning of Environmental 16S rRNA genes

Bacterial 16S rRNA genes were amplified by PCR using the primers Eub338F-0-

III (Blackwood et al. , 2005) and 1391R (Barns et al. , 1994). Reagent concentrations were identical to those for Q-PCR except that SybrGreen and ROX were not used.

Cycling was also identical to Q-PCR except that 35 cycles were used rather than 45, and cycling was carried out in a DNA Engine Dyad Cycler (BioRad, Hercules, CA). All PCR reactions were carried out in triplicate. Duplicate “no template” controls (NTCs), in which template was substituted with water, were included in each set of reactions. PCR reactions were analyzed by agarose gel electrophoresis.

Triplicate PCR products were pooled and treated with a MoBio Ultra-Clean PCR clean-up kit (MoBio Laboratories, Carlsbad, CA). PCR products were cloned into E. coli using the TOPO TA cloning kit (Invitrogen, Carlsbad, CA) according to manufacturer’s directions, and libraries of 96 clones were picked from each cloning reaction. Clone libraries of PCR products from unrepaired template DNA were obtained from all samples except 12303. Clone libraries of PCR products from repaired template DNA were obtained from 8, 8619, and 26539. Clone inserts were sequenced by the Genome

Sequencing Center at Washington University of Saint Louis. Sequencing reads were

57

obtained from both ends of inserts using primers T7F (5’- TAA TAC GAC TCA CTA

TAG GG) and M13R (5’- CAG GAA ACA GCT ATG AC).

Sequence data analysis

Sequences containing the 338F primer site were used for data analysis. Chimeric sequences were identified by Bellerophon v3.0 (Huber et al. , 2004); a total of 26 chimeric sequences were removed from the 338F data set. The final data set contained

751 sequences. In addition, 341 contiguous sequences were formed using 338F and

1391R reads. Contigs were used in BLAST searches to determine the taxonomic affiliation of selected sequence groups. Sequences were aligned using the GreenGenes

NAST alignment tool (DeSantiz et al. , 2006), and matrices of pairwise Jukes-Cantor corrected distances were calculated in MEGA (v 4.0) (Tamura et al. , 2007). Groups of operational taxonomic units (OTUs) were identified in DOTUR (Schloss, 2005) using a

3.0% distance cut-off. Rarefaction curves and richness/diversity statistics were calculated in Estimate S (Colwell, 2005). Distance-based redundancy analysis (RDA)

(Legendre and Anderson, 1999) was used to test for effects of sample age, the valley from which samples originated, and DNA repair. For RDA, the distance matrix among samples was subjected to principal coordinates analysis (PCoA) and the resulting PCoA matrix was corrected for negative eigenvalues by adding a constant before RDA was performed (Legendre and Anderson 1999). Steps of RDA were performed in CANOCO

(Version 4.5) (Microcomputer Power, Ithaca, NY) using a Monte-Carlo test of significance with 999 permutations. Separate RDA analyses were performed using each

58

of two distance metrics: a) the Hellinger distance of square-root transformed relative

OTU abundances and b) the Unifrac distance among samples incorporating the phylogenetic distance between sequences (Lozupone and Knight, 2005). The lineage analysis available in Unifrac was used to investigate the distribution of sequence groups with respect to sample age. This analysis performs a G-test based on the abundance of sequences among ‘environments’ and tests the null hypothesis that sequence groups are distributed evenly among environments (Lozupone et al., 2006).

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Zhang Z, Schwartz S, Wagner L, Miller W. A greedy algorithm for aligning DNA sequences. Journal of Computational Biology: A Journal of Computational Molecular

Cell Biology. 2000;7(1-2):203-214.

Zhang D, Wang H, Cui H, Yang Y, Liu H, Dong X, Zhou P. Cryobacterium psychrotolerans sp. nov., a novel psychrotolerant bacterium isolated from the China No. 1 glacier. International Journal of Systematic and Evolutionary Microbiology.

2007;57(4):866-869.

Zhu F, Liu H, Zhou P. Planococcus psychrotoleratus sp. nov is a new psychrotolerant species of Planococcus. Unpublished.

CHAPTER III

Recovery of Viable Bacteria from Ancient Algal Mats from the McMurdo Dry Valleys, Antarctica 2

Abstract

Desiccated algal mat deposits occur in the McMurdo Dry Valleys as relics of glacial lakes that occupied the valleys during the Holocene. These deposits may present an opportunity to study the long-term preservation of viable bacteria during dormancy in the Antarctic, and the characteristics of ancient bacteria. In this study, I examined the presence and characteristics of viable bacteria in mat samples representing a chronological sequence from 8 to 26,539 years of age. Samples were assayed for cultivable heterotrophic and autotrophic bacteria. Heterotrophic CFU abundance declined with increasing sample age. Ancient samples were dominated by members of the Firmicutes and Actinobacteria , whereas a modern sample contained a greater variety cultivable bacteria. Cultivable Cyanobacteria were present in the modern sample, but absent from ancient samples. Several isolates belonging to the Firmicutes genus

Sporosarcina were screened by BOX-PCR genotyping and assayed for growth at temperatures between 5 °C and 35 °C. Temperature relationship of growth was found to be related to genotype. Furthermore, genotypes rarely occurred in more than one sample, indicating that among-sample genotype richness (gamma richness) is higher than within- sample (alpha) richness. It is unclear whether the extent of gamma richness implied by

2 This chapter represents a manuscript in preparation for submission to the journal Extremophiles. 77

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these findings is associated with sample age or sample location. My findings indicate that bacteria, particularly endospore-forming Firmicutes , may remain viable over several millennia of dormancy in the McMurdo Dry Valleys. This finding is significant in that ancient viable bacteria may represent a Holocene ‘legacy’ of genetic diversity analogous to the legacy effect of organic carbon (Moorhead et al. , 1999) in the Dry Valleys.

Introduction

Algal mat communities are common in lakes and streams in the McMurdo Dry

Valleys of Antarctica, and are important contributors to primary productivity and biogeochemical cycles (Parker et al. , 1981; Wharton et al. , 1983; Ellis-Evans, 1996;

Brambilla et al. , 2001). Ancient desiccated algal mats formed in glacial lakes that occupied the valleys during the late Holocene are common in the Dry Valleys (Doran et al. , 1994; Hall et al. , 2000; Hall et al. , 2001; Hall et al. , 2002). Paleosediment deposits from Holocene glacial lakes have been identified as “legacy” carbon sources important for supporting biological activity in the Dry Valley ecosystems (Moorhead et al. , 1999;

Burkins et al. , 2001). Some Antarctic microorganisms are known to be tolerant to desiccation and freeze-thaw cycles (e.g. Davey, 1989; Hawes et al. , 1992; Šabacká and

Elster, 2006). Previous research has examined the survival of microorganisms from mats under short term desiccation: Hawes et al. (1992) observed viable cyanobacteria in mats several years of age, while McKnight et al. (2007) observed the recovery of microbes, including cyanobacteria, in mat communities after more than two decades of desiccation.

Viable bacterial cells have also been recovered from glacial ice and permafrost several

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hundreds of thousands of years of age (Christner et al. , 2003; Vishnivestkaya et al. ,

2000). However, the potential for bacterial cells to tolerate long-term (millennial-scale) desiccation-imposed dormancy in the Dry Valleys has not been examined.

Because some Antarctic microbes are able to withstand stresses associated with dormancy, and because the cold and dry climate of the McMurdo Dry Valleys favors preservation of biological materials, I hypothesized that microbial mats originating from the Holocene may contain viable and cultivable bacterial cells. The presence of cultivable cells in ancient samples would imply that the samples are a legacy source of genetic diversity in addition to organic carbon.

This study used culture-based methods to examine the abundance and diversity of cultivable bacteria present in a chronological series of algal mat samples ranging from

8,619 years of age to 26,539 years of age, as determined by 14 C dating. A modern day sample (dessicated upon collection 8 years before present), was included for comparison to ancient samples. Throughout this paper, samples are referred to by their respective 14 C ages.

The survival of viable bacterial cells over long periods of dormancy is limited by the accumulation of damage to DNA and other macromolecules (Kennedy et al. , 1994;

Billi and Potts, 2002). Hence, I expected that the abundance and diversity of viable cells in ancient samples would decline with increasing sample age. I used BOX-PCR, a high- resolution genotyping technique, to examine the relatedness of isolates from samples of different ages. In addition, physiological differences among isolates were evaluated by screening for growth on solid media at temperatures between 5°C and 35°C.

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Methods

Samples and Sample Collection

See Chapter 2 for a full description of samples and sample collection. Samples

(except for sample 8) were collected from Taylor, Wright, and Victoria valleys by Brenda

Hall and 14 C age analysis was also performed by B. Hall. Samples represent a chronological sequence of ages from 8 years before present to 26,539 years before present.

Bacterial Cultivation

Samples were assayed for cultivable bacteria by three methods: 1) autotrophic enrichment culture, 2) heterotrophic enrichment culture, and 3) heterotrophic plate counts. For all cultivation attempts, media, solutions, and all other materials were sterilized by autoclaving. Negative controls consisted of pieces of autoclaved glass fiber filters that were handled identically to samples and subsequently inoculated into the respective medium. Negative controls were performed at a ratio of 1 negative control to

3 samples.

Autotrophic enrichment cultures were performed in DYIY liquid medium

(Lehman, 1976) and incubated at 15 ºC under illumination from 40W broad-spectrum fluorescent lights. Cultures were performed in duplicate, and incubations were carried out for 60 days or until growth was observed. Autotrophic enrichments were inoculated with approximately 10 mg of sample per culture.

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Heterotrophic plate counts were performed using a factorial design, with medium and incubation temperature as factors. Medium was either R2A (Reasoner and

Geldreich, 1984) or 1/10 strength R2A medium. Incubation temperatures used were 5ºC,

15ºC, or 25ºC. Triplicate plates were performed at each combination of medium and temperature. To facilitate plating, portions of sample were homogenized in 0.85% NaCl by grinding with 5 mm steel beads. Sample homogenates were plated using a 10-fold dilution series; the amount of sample spread on plates ranged from 20 mg (sample 26539) to <0.01 mg (sample 8). Plates were incubated for 60 days or until growth was observed.

Plates that showed observable growth were counted and colony morphology was noted.

Plates were periodically re-counted until colony number reached a limit.

Heterotrophic enrichment cultures were carried out as factorial experiments with medium and temperature as factors. Triplicate enrichments were performed at each combination of medium and temperature. Heterotrophic enrichment cultures used tryptic soy broth (TSB), 1/5 strength TSB, or a marine nutrient medium (MN) with incubation at

5ºC, 15 ºC, or 25 ºC. The marine nutrient medium was based on the artificial sea water

(ASW) formulation of Keller et al. , (1987) supplemented with 1 g yeast extract and 5 g bacto-peptone per liter. Heterotrophic enrichment cultures were incubated for 60 days or until growth was observed. The mass of sample used to inoculate heterotrophic enrichments ranged from approximately 1mg (sample 26539) to 0.01 mg (sample 8).

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Culture Isolation and Screening

Colonies from plates were isolated by streaking to produce pure cultures and screened by amplified ribosomal DNA restriction analysis (ARDRA). Colonies were chosen for isolation in order to include one or more representatives of each colony morphology type. In addition, a single morphology type was observed to be common to

5 of the 8 samples. Colonies of this morphology type were randomly selected from each sample for BOX-PCR screening, with selection balanced among media and temperature treatments.

ARDRA Screening

Amplified ribosomal DNA restriction analysis (ARDRA) was used as a screening method to select specific isolates for further study. ARDRA was carried out on all bacterial isolates selected from the culture assays described above. For enrichment cultures, broth from cultures positive for growth was used as a template in PCR reactions.

For pure cultures isolated from heterotrophic plate counts, either colonies or DNA extracts were used as template for PCR. DNA extractions were carried out using a modified procedure from Surzycki (2000).

A 16S rRNA gene fragment was amplified by PCR using the primers Eub338F-0-

III (Blackwood et al. , 2005) and 1391R (Barns et al. , 1994). PCR conditions were as follows: 0.2 M each primer, 0.2 mM each dNTP, 0.025 U L-1 Gene Choice Taq DNA polymerase (Cat. No. T-28), 1x Gene Choice ammonium buffer (1.5 mM MgCl 2, 75 mM

Tris-HCl, 20 mM (NH 4)2SO 4, 0.1% Tween 20, pH 8.5), 0.5 mM MgCl 2 (total 2.0 mM

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-1 MgCl 2), 0.1 g L BSA, and 0.5-2.0 L template DNA, 0.167X Sybr Green, and 30 nM

5-ROX. PCR conditions were as follows: an initial denaturation step of 3 minutes at

95 ºC, followed by 45 cycles of 30 seconds at 95 ºC, 30 seconds at 57 ºC, and 90 seconds at 72 ºC, and a final elongation step of 7 minutes at 72 ºC. Approximately 50 ng of PCR product was digested by HaeIII or by HinP1I and MspI in combination. Digests used 3U of each enzyme and were carried out overnight (at least 12 hours) at 37°C. Restriction digests were analyzed by electrophoresis in a 3% NuSieve agarose gel at 185V (2.5

V/cm) for 150 minutes followed by staining in ethidium bromide (0.5 g mL -1). A standard consisted of 500 ng of a λ DNA – PstI ladder (Invitrogen, Carlsbad, CA).

Stained gels were photographed using a GelDoc imaging system (BioRad, Hercules, CA), and band identification and pattern matching was performed using GelCompare II (v. 4.6;

Applied Maths, Austin, TX).

BOX-PCR Screening

BOX-PCR was used to investigate the genetic relatedness of isolates sharing a common ARDRA type. Template DNA for BOX-PCR was extracted from cultures grown on R2A or TSA slants using a modified procedure from Surzycki (2000). DNA quantity and purity was assessed by absorbance at 260 nm and 280 nm in a Synergy 2 plate reader (Biotek Instruments, Winooski, VT). Replicate BOX-PCR profiles, representing separate DNA extractions and PCR reactions, were performed in order to establish a confidence interval for genotype identity (Cho and Tiedje, 2000). PCR reaction conditions were as follows: 2.0 M BOX A1R primer (Koeuth et al. , 1995), 0.5

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mM each dNTP, 1x Gene Choice ammonium buffer (1.5 mM MgCl 2, 75 mM Tris-HCl,

20 mM (NH 4)2SO 4, 0.1% Tween 20, pH 8.5), 3.0 mM MgCl 2 (total 4.5 mM MgCl 2), 0.05

U L-1 Gene Choice Taq DNA polymerase (Cat. No. T-28), and 0.5 g L-1 BSA.

Approximately 150 ng of DNA was used as template in a 25 L reaction. No template controls (NTCs), in which template was substituted by water, were included with all reactions. Reactions were cycled as follows: an initial denaturation step of 5 minutes at

95 ºC, followed by 35 cycles of 1 minute at 94ºC, 45 seconds at 46 ºC, and 8 minutes at

72 ºC, and a final extension of 12 minutes at 72 ºC. BOX-PCR profiles were acquired by electrophoresis in a 1.5% NuSieve agarose gel for 6 hours at 2.5 V cm -1. Gels were stained in ethidium bromide (0.5 g mL -1) and photographed on a GelDoc imaging system (BioRad, Hercules, CA).

BOX-PCR profiles were analyzed with the assistance of GelCompare II (v. 4.6;

Applied Maths, Austin, TX). Bands were identified, band intensities were scaled to the total intensity of each profile, and pairwise Euclidean distances among profiles were computed. Rarefaction analysis was performed using Estimate S (v. 7.5.2; Colwell,

2005).

16S rRNA gene sequencing

To determine the phylogenetic affiliation of isolates, a portion of the 16S rRNA gene of selected isolates was sequenced. One or more representatives of each ARDRA type were selected for sequencing. Additionally, one or more representatives of each genotype determined from BOX-PCR were selected for sequencing. A total of 65

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sequences were acquired (40 from BOX-PCR genotypes and 25 from other ARDRA types). PCR product for sequencing was obtained as described for ARDRA using the

Eub338F-0-III and 1391R primers. Sequencing was performed by the Genome

Sequencing Center at Washington University of Saint Louis using the Eub338F-0-III primer. The taxonomic affiliation of sequences was determined by identifying their nearest cultivated relative via nucleotide BLAST search (Zhang et al. , 2000). Sequences from BOX-PCR genotypes were aligned using MUSCLE (Edgar, 2004) and pairwise

Jukes-Cantor corrected distances were calculated in MEGA (v. 4.0; Tamura et al. , 2007).

Isolate physiological screening

At least one representative of each BOX-PCR genotype was screened in order to evaluate relative growth rates at 5°C, 15°C, 25°C, and 35°C. A total of 36 isolates were screened in this manner. Isolates were initially grown as Tryptic soy broth (TSB) cultures at 15°C. Prior to screening on solid medium, growth curves of selected isolates in broth culture were acquired in order to predict the point at which broth cultures reached the exponential phase of growth (Figure 8). Growth curves were acquired from

TSB cultures incubated at 15 °C with shaking at 150 rpm. Optical density at 600 nm

(OD 600 ) of cultures was read on a Synergy 2 plate reader (Biotek Instruments, Winooski,

-1 VT). Growth curves indicated exponential growth at OD 600 values between 0.1 cm and

-1 -1 -1 0.5 cm . Cultures having an OD 600 between 0.1 cm and 0.2 cm were used to inoculate

Tryptic soy agar (TSA) plates. Plates were incubated at respective temperatures and inspected daily after inoculation. The time required for appearance of colonies was

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recorded to the nearest 24 hours. Unifrac analysis (Lozupone and Knight, 2005) was used to determine whether categories determined from physiological screening were non- randomly distributed over a neighbor-joining tree of BOX-PCR genotypes. The neighbor-joining tree was constructed from Euclidean distances using the Neighbor program in Phylip (v 3.68; Felsenstein, 2005).

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1.2

(8-1) 1

(8643-5) 0.8

600 0.6 (8619-6) OD

0.4 (11164- 6)

0.2

0 40 60 80 100 120 140 160

Time (hours)

Figure 8: Growth curves of selected isolates in TSB at 15 °°°C. In the legend, numbers preceeding the dash denote sample ages; numbers following the dash denote specific isolates from a sample. Data points are the mean of duplicate readings.

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Results

Heterotrophic Plate Counts

Heterotrophic plate counts were performed to determine whether cultivable cells were present in ancient samples and whether a relationship existed between sample age and cultivable cell abundance. Cultivable bacteria were recovered from all samples except 12303 (Table 8); CFU abundance varied by more than 4 orders of magnitude among samples (Figure 9 a-b). A mixed effects linear model was used to examine CFU count data. The model was fitted to log 10 transformed CFU abundance and incorporated effects of temperature, medium, and age class (and interactions among these effects) with variance constrained by sample. Medium (p<0.01) and age class (p<0.01) both had significant effects on CFU abundance by the mixed effects model. The interaction between temperature and age class also significantly affected CFU abundance (p=0.011).

CFU abundance on 1/10 R2A was on average 47% of CFU abundance on R2A.

Temperature was significant only for age classes 3 and 4. For samples 11164, 11185, and

26539, cultivable cells were not detected at 25°C.

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Table 8: Summary of bacterial recovery from algal mat samples. Numbers represent ARDRA types from cultures. (-) represents not detected. CFU mg -1 on R2A medium with incubation at 15°C. Heterotroph Autotroph Heterotroph Sample Location CFU mg-1 plate count Enrichment Enrichment Victoria 2.09± 0.32x10 4 1, 2, 3, 4, 5, 6, 8 7, 8, 9, 14, 15 8 1, 3 3 8619 Wright 3.72± 0.25x10 1, 2 1 1 8643 Victoria 110± 20 1 1 1 11164 Victoria 0.66± 0.13 1 - 1 11185 Victoria 2.34± 1.4 10, 11 - 10 12303 Victoria - - - - 12910 Taylor 126± 17 1, 12 12 - 26539 Wright 1.0± 0.02 13 - -

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5 5°C

4 15°C 25°C ) -1 3

(CFU mg (CFU 2 10 log 1

0 8 8619 8643 11164 11185 12910 26539 Sample

Figure 9 a: CFU abundance from heterotrophic plate counts on R2A medium. Data series represent incubation temperatures.

5 5°C 15°C 4 25°C ) -1 3

(CFUmg 2 10 log 1

0 8 8619 8643 11164 11185 12910 26539 Sample

Figure 9 b: CFU abundance from heterotrophic plate counts on 1/10 strength R2A medium. Data series represent incubation temperatures.

Autotrophic enrichment cultures

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Autotrophic enrichment cultures in liquid media were performed to assess the presence of cultivable Cyanobacteria in samples. Cyanobacteria were only recovered from sample 8. Other types of cultivable bacteria were recovered in autotrophic enrichment cultures from samples 8619, 8643, and 12910 (Table 8).

Heterotrophic Enrichment Cultures

Heterotrophic enrichment cultures in three types of liquid media (MN, TSB, and

1/5 strength TSB) were performed to allow a wider diversity of bacteria to be cultivated from ancient samples. Cultivable bacteria were recovered from samples 8, 8619, 8643,

11164, and 12910 by heterotrophic enrichment (Table 8). Growth occurred in all types of media and at all temperatures (5°C, 15°C, and 25°C), except for samples 11164 and

12910, which were positive for growth at 5°C and 15°C, but not 25°C.

Diversity of cultivable bacteria

Approximately 262 cultures were screened by ARDRA: 120 from heterotrophic enrichment cultures, 12 from autotrophic enrichment cultures, and 130 from heterotrophic plate counts. ARDRA patterns were used to classify cultivable bacteria into a total of 14 types (Tables 8 and 9). ARDRA types of bacteria recovered from autotrophic and heterotrophic enrichment cultures matched those recovered from heterotrophic plate counts from the same samples. A greater number of ARDRA types were cultivated from sample 8 (11 types) than from ancient samples (1 to 2 types).

Cultivable bacteria in sample 8 were dominated by ARDRA type 9, which represented

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>99% of CFUs. For sample 8619, the majority of colonies belonged to ARDRA type 1 and ARDRA type 2 was represented as a single colony. For sample 12910, ARDRA type

1 was represented by a single colony, with the remainder of colonies belonging to

ARDRA type 12. Small subunit ribosomal sequences of representative cultures of each

ARDRA type were obtained for identification of ARDRA types (Table 9). Cultivable bacteria from the ancient samples were classified as belonging to the Firmicutes ,

Bacteroidetes , and Actinobacteria . Sample 8 contained a greater variety of cultivable bacteria including members of the Proteobacteria , Cyanobacteria , and Deinococcus-

Thermus . ARDRA type 8 is a Cyanobacteria ARDRA type recovered from sample 8 which was not sequenced. Based on morphological analysis, ARDRA type 8 was identified as a Microcystis species. Microcystis stagnalis has been cultured from lakes and algal mats in the Dry Valleys (Spaulding et al. , 1994; Vincent, 2000b). ARDRA type

1, most closely related to the genus Sporosarcina, was recovered from 5 samples and isolates of this type were examined further by BOX-PCR.

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Table 9: Phylogenetic affiliation of recovered ARDRA types as determined by BLAST searches. When ranges of BLAST identity are given, these represent multiple sequences for an ARDRA type. Max. Nearest BLAST ARDRA Cultured Identity GenBank Type Relative (%) Accession Reference 1 Sporosarcina 98-100 AB490786 Velmurugan et sp. MB6 al. , unpublished 1 Planococcus 100 AY771711 Lee, unpublished psychrotoleratus 2 Micrococcus 98-100 GQ369519 Ternovoi et al. , luteus unpublished 3 Tetrasphaera 99 AF409018 Shoenborn et al. , sp. Ellin176 2004 4 Roseomonas 99 EU290160 Kim et al. , 2009 frigidaquae 5 Frigoribacterium 100 DQ652546 Lo Giudice et al. , sp. D21 2007 6 Polaromonas 99 EF423340 Wang et al. , sp. 3010 unpublished 7 Deinococcus 97 AM940971 Kämpfer et al. , aquatilis 2008 9 Micromonospora 99-100 GQ163478 Zhang et al. , chokoriensis unpublished 10 Paenibacillus sp. 98 EF451701 Hansen et al. , KAR72 2007 11 Paenibacillus 96 EF626690 Chou et al. , 2009 contaminans 12 Pedobacter 95-98 FJ897516 Oh et al. , sp. B4a-b5 unpublished 13 Arthrobacter 100 FN377733 Shivaji, sp. SH-61B unpublished 14 Janibacter 100 GQ280042 Datta et al. , anophelis unpublished 15 Massilia sp. M1 98 GQ200828 Mageswari et al. , unpublished

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BOX-PCR Genotyping

A total of 108 ARDRA type 1 isolates were recovered from samples 8, 8619,

8643, 11164, and 12910 and screened by BOX-PCR. To establish a BOX profile distance cut-off for genotype identity, 25 replicate BOX-PCR profiles were acquired.

The average Euclidean distance between replicate profiles was 0.135 (standard deviation=0.0321). A cut-off of 0.17 was chosen for genotype identity, resulting in classification of BOX-PCR profiles into a total of 28 genotypes. The Euclidean distance among genotype BOX-PCR profiles ranged from 0.17 to 0.82 (average distance = 0.443, standard deviation = 0.128). Rarefaction analysis using Chao’s richness estimator

(Chao 1) indicated that genotypes were thoroughly sampled for samples 8619, 8643, and

11164 (Figure 10). A single ARDRA type isolate was isolated from 12910, hence genotype recovery from 12910 could not be analyzed by rarefaction. This isolate was not included as in subsequent statistical analyses. Genotypes tended to be unique to individual samples; only 2 genotypes occurred in more than one sample.

To gain insight into possible physiological dissimilarities among genotypes, the effect of treatment factors used in the cultivation experiment on genotype recovery was examined. G tests were performed to assess whether genotypes were randomly distributed among temperature and medium treatments used for heterotrophic plate counts (Table 10) (Note: because some genotypes occurred in more than one sample, the combined number of genotypes is less than the sum of the number of genotypes in each sample). For the combined data set of all samples, genotypes were distributed non- randomly with respect to temperature (G test, p=0.0110, 28 degrees of freedom) and

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medium (G test, p=0.0180, 56 degrees of freedom). In Table 10, p values for tests on individual samples do not represent Bonferroni corrected values. Employing a

Bonferroni correction, only the effect of temperature for sample 8643 would be considered significant (0.002 multiplied by 8 post hoc tests = 0.016). These results indicate that culture conditions used for heterotrophic plate counts selected for the growth of certain genotypes. For sample 8643, genotype 13 occurred predominately below 25°C and genotype 14 occurred predominately at 25°C (Table 11).

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25 8 8619 20 8643 11164 15 Richness 1 1 10 Chao

5

0 0 10 20 30 40 50 Number of Isolates Sampled

Figure 10: Rarefaction analysis of BOX-PCR genotype occurrence by sample. Genotype Chao 1 richness was estimated using 50 iterations in Estimate S.

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Table 10: Sample richness and G tests of genotype distribtion by medium and temperature Number Number of of Sample Isolates Genotypes Medium Temperature 8 18 13 0.072 0.24 8619 30 9 0.019 0.23 8643 48 4 0.21 0.002 11164 12 4 0.14 0.23 Combined 108 28 0.018 0.011

Table 11: Distribution of genotypes from sample 8643 among temperature treatments. A total of 48 isolates were cultured from this sample. Genotype 4°C 15°C 25°C 4 0 1 2 9 1 0 0 13 12 12 2 14 3 2 13

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Partial 16S rRNA gene sequences were acquired from 40 isolates (including at least one representative of each genotype) to provide a comparison between BOX-PCR genotypic distance and 16S rRNA gene phylogenetic distance. The average pairwise

Jukes-Cantor corrected distance among genotype 16S rRNA gene sequences was 0.81%

(standard deviation of 1.4%). Phylogenetic analysis grouped isolates into 3 distinct clusters (Figure 11). Group 1 contained the majority (35 of 40) of isolate sequences and included isolates from all samples. Group 2 contained sequences of 4 isolates from sample 8. Group 3 contained a single sequence from an isolate (f1) from sample 11164.

Isolates from groups 1 and 2 were identified as members of the genus Sporosarcina by

BLAST (isolates showed 98-100% maximum identity to cultured Sporosarcina relatives).

Isolate f1 from 11164 was closely related to Planococcus species (100% maximum identity). Pairwise 16S rRNA gene sequence distance showed a much lower range of variability than pairwise BOX profile distance. The BOX profile distances and 16S rRNA gene sequence distances were not correlated (Pearson’s product-moment correlation, p=0.258) (Figure 12).

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Figure 11: Estimated phylogeny of 16S rRNA gene sequences from ARDRA type 1 isolates. UPGMA tree was constructed in MEGA (v. 4.0) using p-distance and a bootstrap test of phylogeny with 500 replicates. Genbank accession numbers of related sequences are given.

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Figure 12: Correlation of BOX-PCR profile Euclidean distance with 16S rRNA gene sequence p distance. Data shown represent pairwise comparisons of 40 isolates.

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Physiological Screening of Genotypes

To examine physiological differences among genotypes, 36 isolates, including at least one member of each genotype, were screened by growth on TSA plates at 5°C,

15°C, 25°C, and 35°C. All genotypes showed growth at 5°C and 15°C, and all but 5 genotypes showed growth at 25°C. No genotypes grew at 35°C. The effect of temperature on time to appearance of colonies was evaluated using a mixed effects

ANOVA with variance constrained by genotype. Temperature significantly affected time to colony appearance (p<0.001). Tukey’s HSD test was used to analyze differences in time to colony appearance among temperatures; time to appearance was significantly longer at 5°C than at 15°C or 25°C; time to appearance at 15°C and 25°C were not significantly different (Figure 13).

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A

B B

Figure 13: Time to colony formation during growth temperature screening. ‘Notches’ correspond to 95% confidence intervals. A and B denote significantly different groups.

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Genotypes were grouped into 3 categories based on screening results and on previous definitions of bacterial temperature relationships (e.g. Morita, 1975): 1)

Genotypes that did not show growth at 25°C were considered psychrophilic (5 genotypes); 2) genotypes that displayed a shorter time to appearance of colonies at 25°C than 15°C, or equal time to appearance of colonies at 15°C and 25°C were considered psychrotrophic (total of 8 genotypes); and 3) genotypes that showed a shorter time to appearance of colonies at 15°C than 25°C, but that still grew at 25°C, were considered somewhat psychrophilic (15 genotypes). A G test was used to examine whether temperature response classes were evenly distributed among sample age classes (using a uniform distribution as a null hypothesis) (Table 12). Temperature response classes were not evenly distributed among age classes (G test, p=0.024, 6 degrees of freedom).

Psychrotolerant isolates appeared to be more common in age class 1 (the modern sample) whereas psychrophilic isolates only occurred in age classes 2 and 3. Additional G tests were performed for each temperature response class; none of the individual temperature response classes were distributed unevenly over sample age classes.

To assess whether temperature response was related to genotype phylogeny as determined from BOX-PCR, Unifrac was used to test the null hypothesis that temperature response classes were distributed randomly over a UPGMA tree of BOX profiles (Figure

14). Unifrac revealed a significant relationship between BOX profile phylogeny and temperature response (Unifrac test of total significance, p<0.001). The Unifrac distance matrix (Table 13) revealed that pairwise distances among temperature response classes were similar.

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Figure 14: UPGMA tree of genotype BOX-PCR profiles. Tip labels correspond to genotypes. Temperature response classes described in the text are given in parentheses.

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Table 12: Abundance of genotype temperature response classes across age classes of samples. p values from G tests described in the text are given. Temperature Age Age Age p Response Class Class 1 Class 2 Class 3 value Psychrotolerant 6 1 1 0.13 Somewhat Psychrophilic 7 8 1 0.32 Psycrhophilic 0 3 2 0.32

Table 13: Unifrac distance (based on Euclidean distance of BOX-PCR profiles) among genotype temperature response classes Somewhat Psychrotrophic Pyschrophilic Psychrophilic Psychrotrophic - 0.893 0.897

Somewhat Psychrophilic - - 0.907

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Discussion

I examined the occurrence and diversity of cultivable bacterial cells in algal mat samples from the McMurdo Dry Valleys representing a chronological sequence from 8 years before present to 26,539 years before present. Due to the accumulation of cellular damage in dormant cells, the number and richness of cultivable bacteria were expected to decline with increasing sample age. The heterotrophic CFU count from sample 8 was similar to counts from modern algal mats from lakes Fryxell and Hoare in the Dry

Valleys (Van Trappen et al. 2002). Cultivable bacteria were recovered from all but one ancient sample (sample 12303), and heterotrophic CFU counts were negatively correlated with sample age. Sample 8 contained a wider phylogenetic diversity of cultivable bacteria than the ancient samples. Cultivable Cyanobacteria were found for sample 8, but not for any of the ancient samples. Ancient samples were dominated by members of the Actinobacteria and endospore-forming Firmicutes (Planococcus , Sporosarcina , and

Paenibacillus ). Several of the genera cultivated in this study have been previously cultivated from modern Antarctic algal mats: Micrococcus (Brambilla et al. , 2001; Van

Trappen et al. , 2002), Sporosarcina (Reddy et al. , 2003), Arthrobacter (Van Trappen et al. , 2002), Planococcus (Reddy et al. , 2002), and Frigoribacterium (Brambilla et al. ,

2001). These results indicate that viable bacterial cells may be preserved over several millennia of dormancy in the McMurdo Dry Valleys.

BOX-PCR genotyping was applied to Sporosarcina isolates from sample 8 and ancient samples to assess the genotypic diversity of these isolates and physiological differences among genotypes. Because temperature is considered an important selective

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force in the evolution of many Antarctic microbes (Franzmann and Dobson, 1993; reviewed in Vincent, 2000; reviewed in Deming, 2002), genotypes were screened for growth on solid media at temperatures between 5°C and 35°C. Temperature response classes of genotypes were found to be non-randomly distributed over a phylogenetic tree derived from BOX-PCR data, suggesting that temperature may be a selective force for

Sporosarcina genotypes. Genotype occurrence was influenced by both the temperature and medium treatments used for heterotrophic plate counts, suggesting that genotypes possess physiological differences in their responses to temperature and substrate availability. Genotype diversity not related to temperature response may reflect adaptations to substrate availability, interactions of temperature and substrate availability, or other environmental conditions. In particular, temperature and substrate availability are thought to have interacting effects on bacterial growth because low temperatures decrease substrate affinity (Weibe et al. , 1992; Nedwell, 1999).

A widely-used categorization (Morita, 1975) defines psychrophiles as possessing an optimal growth temperature (T opt ) near or below 15°C and a maximum growth temperature (T max ) near or below 20°C. Bacteria possessing a higher T opt and T max , but still capable of growth at temperatures below 15°C are considered psychrotrophs (Morita,

1975). By the above definition, the majority of genotypes in this study (23 of 28) can be considered psychrotrophic, while only 5 of 8 can be considered psychrophilic. No genotypes in this study were capable of growth at 35°C. The inability of isolates to grow at 35°C was not unexpected, as psychrotrophic strains cultured from the Antarctic commonly possess a T max below or near 30°C (e.g. Spring et al. , 2003; Van Trappen et

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al. , 2004; Shivaji et al. , 2004; Prabahar et al. , 2004; Yi et al. , 2005; Hong et al. , 2008). It is also not uncommon for psychrotrophic strains to be more abundant than psychrophilic strains in culture collections from terrestrial Antarctic habitats, or for novel Antarctic species to be psychrotrophic rather than psychrophilic (Franzmann and Dobson, 1993; reviewed in Tindall, 2004).

Rarefaction analysis revealed that BOX-PCR screening thoroughly sampled the richness of genotypes within each sample, although most genotypes occurred in only one sample. Because samples yielded mostly unique genotypes, the diversity of

Sporosarcina genotypes throughout the Dry Valleys is likely greater than represented in this study. To my knowledge, this is the first study to examine a large collection of

Antarctic bacterial isolates by a genotyping technique such as BOX-PCR. Some studies using the 16S rRNA gene as a marker have suggested that bacteria in the Dry Valleys are uniformly distributed (e.g. Gordon et al. , 2000) due, for example, to dispersion by winds.

I conclude that distinct genotypes may occur within groups of closely-related 16S rRNA gene sequences. As genotypic diversity was found to correlate with physiological diversity in this study, examination of bacterial diversity at the genotypic scale may prove to be relevant to understanding the forces influencing bacterial evolution within the

Antarctic.

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Chapter IV

General Discussion

I examined bacterial diversity in samples of ancient algal mats from the McMurdo

Dry Valleys, Antarctica, representing a chronological sequence from 8 to 26,539 years of age. Patterns of age dependence were found for bulk DNA abundance, DNA integrity, cultivable bacterial abundance, and cultivable bacterial diversity. These patterns would be expected for ancient materials where the persistence of DNA and viable cells is limited by the accrual of macromolecular damage.

Cultivation-based and molecular approaches introduce different biases to microbiological studies (Hugenholtz et al. , 1998; O’Donnell and Gorres, 1999).

However, many commonalities between molecular and cultivation data were apparent in this study. Both cultivable Cyanobacteria and Cyanobacteria DNA sequences were present in sample 8 and absent from ancient samples. Isolates related to Sporosarcina were the dominant cultivated bacteria from samples 8619, 8643, and 11164. DNA sequences similar to Sporosarcina were common in samples 8619 and 11164, but not

8643. Pedobacter was isolated from sample 12910 and sequences related to Pedobacter comprised 13% clone library from this sample. Sample 12303 was not found to contain either cultivable bacterial cells or bacterial DNA. The similarity between results from cultivation assays and clone libraries in this study may be a result of the extremely lowamount of viable cells and template DNA within ancient samples. Firmicutes were

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the most common phylum of cultivable bacteria isolated from ancient samples and were also well-represented in clone libraries from ancient samples. Firmicutes endospores and

DNA have been recovered from a wide range of ancient materials (Renberg and Nilsson,

1992; reviewed in Kennedy et al. , 1994; Gorbushina et al. , 2007; Rollo et al. , 2007, Yung et al. , 2007). My findings on the viability of Firmicutes endospores in ancient samples are comparable to other studies which have reported viable endospores from materials several thousand years of age (Renberg and Nilsson, 1992; Yung et al. , 2007). Because

Firmicutes are not common in Dry Valley soils (Seibert and Hirsch, 1988; Moodley,

2004; Smith et al. , 2006; Aislabie et al. , 2006), cultivable Firmicutes and Firmicutes

DNA found in this study are likely to represent bacteria endogenous to samples rather than soil-borne contaminants. Actinobacteria were also isolated from ancient samples.

Actinobacteria are common in ancient ice and permafrost, and some evidence suggests that Actinobacteria are more likely than Firmicutes to be preserved in very old (400,000 years and greater) permafrost (Willerslev et al. , 2004; Johnson et al. , 2007). Because

Actinobacteria are common in Dry Valley soils, cultivable Actinobacteria cells and DNA are more likely than Firmicutes to have originated from soil-born contamination of samples.

Previous studies have emphasized the resilience of Cyanobacteria in Antarctic mat communities to dormancy lasting years or decades (Hawes et al. , 1992; Šabacká and

Elster, 2006; McKnight et al. , 2007). The findings of this study suggest that

Cyanobacteria cells and DNA are less likely than heterotrophic bacteria, particularly

Firmicutes and Actinobacteria , to be preserved over extended periods of dormancy in the

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Dry Valleys. Alternatively, it is possible that Cyanobacteria were not originally present in the ancient samples examined in this study. However, Cyanobacteria are widespread in modern algal mats in the McMurdo Dry Valleys. Without more detailed information on the environmental conditions prevalent at the time samples were metabolically active, it is unclear why Cyanobacteria would be absent from the original microbial assemblages.

Studies on the preservation of ancient microorganisms are often not amenable to generalizations because a number of factors which are not readily known can influence cellular preservation (e.g. variation in environmental conditions during preservation and the metabolic state of cells prior to preservation) (Kennedy et al. , 1994; Billi and Potts,

2002). Dry Valley algal mat deposits may represent a useful model system in which to examine long-term microbial dormancy because a) samples can be collected so as to represent chronological sequences and b) conditions under which samples were preserved might be expected to be broadly similar. Such a system could be helpful in predicting the survival of biomolecules in extraterrestrial environments. This study also highlights some problematic aspects of using algal mat deposits as a model system to study long- term microbial preservation. Samples of similar age exhibited unexplained variation in

DNA and cultivable cell abundance, most notably samples 12303, 11185, and 11164. No cultivable cells or PCR-amplifiable DNA were recovered from sample 12303 although these were recovered from samples 11185 and 11164. The reason for this finding is not clear from this study. It is possible that sample 12303 was preserved under less favorable conditions than other samples, or perhaps had a greater inorganic material content (and

123

lower cell abundance) while it was active. Additionally, it remains to be shown that samples were not intermittently metabolically active since their respective 14 C ages.

Sample 14 C ages could reflect the incorporation of “old” carbon into cell biomass.

However, the hypothesis of samples being intermittently metabolically active does not explain the abundance of anaerobic bacteria, including sulfate-reducing bacteria, in ancient clone libraries, as these would not be expected to thrive under aerobic soil conditions.

In summary, these findings indicate that viable and cultivable bacterial cells and

DNA can be preserved in materials in the McMurdo Dry Valleys for at least several thousand years. At the same time, potential biases in preservation might exist (e.g. poor preservation of Cyanobacteria and good preservation of Firmicutes ) that could cause differential preservation of DNA from community members. This finding points to the potential for genetic diversity from ancient materials to enter and interact with modern ecosystems. The Dry Valleys have been considered recipients of “legacy” effects in regard to organic carbon (Moorhead et al. , 1999); this study, argues for the existence of a legacy of bacterial genetic diversity.

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