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Microbialites from the freshwater system of cuatro cinegas, mexico :
b genomic, molecular organic, and stable isotopic perspectives
h [electronic resource] /
by Anthony Nitti.
[Tampa, Fla] :
University of South Florida,
Title from PDF of title page.
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Thesis (MS)--University of South Florida, 2010.
Includes bibliographical references.
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ABSTRACT: Modern microbialites are carbonate-precipitating microbial mats and represent the closest living analogues to ancient stromatolites. These ancient carbonate formations are the oldest fossil evidence of life on Earth; however, our comprehension of their relationship to early earth ecosystems relies heavily on understanding the formation of modern microbialites. Research regarding these formation processes has suggested that chemical constraints of CaCO3 precipitation vary on sub-millimeter spatial scales within the living microbial community. In an attempt to shed light on the importance of these chemical microenvironments, this study focused on understanding the spatial distribution of the organisms and processes involved in the formation of modern microbialites. This was accomplished by isolating five visually distinct layers from the upper 2 3 cm of an actively forming microbialite found in the freshwater system of Cuatro Cinegas, Mexico. Each layer was analyzed using genomic, molecular organic, and stable isotopic techniques. Bacterial diversity was determined by 16S rRNA gene analyses, lipid biomarker content was detected by GC-MS, and carbon isotope composition of organic matter and CaCO3 were used as indicators of specific microbial processes. Results of the 16S rRNA gene analysis showed that there is little overlap in the community composition of individual layers. Approximately 90% of the ribotypes identified in the microbialite were unique to a single layer. Furthermore, the relative accretion of CaCO3 at each layer was used to connect the distribution of organisms and processes with two specific zones of CaCO3 precipitation. The first zone of CaCO3 accretion, which accounted for approximately 55% of total CaCO3 accumulation, is found in the surface two layers of the microbialites and dominated by photoautotrophic cyanobacteria and algae. The second zone of CaCO3 precipitation, found at the interior (layers 4 and 5), is composed primarily of heterotrophic proteobacteria and dominated by sulfate-reducing Deltaproteobacteria. The lipid content of the microbialite reflected the community structure as determined by genomics. Numerous photosynthetic biomarkers were detected and decreased in abundance with depth, indicating the important function of heterotrophic degradation. Additionally, the detection of sulfurized phytol compounds in layer 5 highlighted an important mechanism for the preservation of biogenic signatures, and reflected both the abundance of phototrophic organisms and sulfate-reducing bacteria. In combination, these interdisciplinary analyses provided an understanding of microbial community composition and metabolism while indicating the spatial relationship to CaCO3 formation and the preservation of distinct biochemical signatures.
Advisor: David Hollander, Ph.D.
x Marine Science
t USF Electronic Theses and Dissertations.
Microbialites from the Freshwater System of Cuatro CiÂŽnegas, Mexico: Genomic, Molecular Organic, and Stable Isotopic Perspective s by Anthony G. Nitti A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science College of Marine Science University of South Florida Co Major Professor: Mya Breitbart, Ph.D. Co Major Professor: David Hollander, Ph.D. Lisa Robbins, Ph.D. Date of Approval : September 27, 2010 Keywords: Stromatolite Cyanobacteria, Proteo bacteria, Carbonate, Lipid Copyright 2010, Anthony G. Nitti
! Acknowledgments I would like to thank the Government of the State of Coahuila, the City of Cuatro CiÂŽnegas, Semarnat, CONANP, Pronatura Noreste and the people of Cuatro CiÂŽnegas, Mexico for welcoming us to their town and allowing us to collect sample s in Rio Mesquites A great deal of thanks must also go to Dawn Goldsmith, Neilan Kuntz, Janet Sief ert and Vale ria Souza for assistance in sampling. Tony Greco, from the College of Marine Science Electron Microscopy Laboratory was also extremely helpful in obtaining SEM images. This project was funded by grants from the National Geographic Society and the Universit y of South Florida Internal Awards Program Additionally, personal financial assistance was provided by the USG S/USF Cooperative Assistantship, the Gulf Oceanographic Trust Fellowship, and the Von Rosenstiel Fellowship. Finally, I am endlessly grateful for the personal friendships and intellectual guidance of mem bers of the Breitbart M icr obiology Lab and the Paleoclimatology, Paleoceanograph y, and Biogeochemistry Laboratory Specifically, I would have been un able to complete this work with out the help of Camille Daniells, Ana Hoare, and Ethan Goddard.
! i Table of Contents List of Tables ................................ ................................ ................................ ........ i ii List of Figures ................................ ................................ ................................ ....... iv Abstract ................................ ................................ ................................ .................. v Introduction ................................ ................................ ................................ ........... 1 Materials and Methods ................................ ................................ .......................... 9 Sample Collection ................................ ................................ ...................... 9 DNA Extraction ................................ ................................ ......................... 11 Amplific ation, Cloning, and rRNA Sequencing ................................ ......... 11 Sequence Analysis ................................ ................................ ................... 12 Lipid Extraction ................................ ................................ ......................... 12 S epar ation of Compound Classes ................................ ........................... 13 Analysis by GC MS ................................ ................................ .................. 14 Stable Isotope Analysis ................................ ................................ ............ 15 Microscopy ................................ ................................ ............................... 16 Material Balance ................................ ................................ ...................... 16 Results ................................ ................................ ................................ ................ 18 Bacterial Clone Libraries ................................ ................................ .......... 18 Lipid Extracts ................................ ................................ ............................ 22 FAME Distribution ................................ ................................ ......... 22 Alcohol Distribution ................................ ................................ ........ 23 Hydrocarbon Distribution ................................ ............................... 23 Carbon Isotope Prof iles ................................ ................................ ............ 24 Microbialite Composition ................................ ................................ .......... 24 Discussion ................................ ................................ ................................ ........... 25 Phylogenetic Analysis ................................ ................................ .............. 25 Uniq ueness of 16S Clone Libraries ................................ ............... 25 Photo trophic Community Composition ................................ .......... 26 Non photo trophic Community Composition ................................ ... 28 Phylogeny Summary ................................ ................................ ..... 30 Molecular Or ganic Biomarkers ................................ ................................ 3 0 Hydrocarbons ................................ ................................ ................ 31
! ii Fatty Acids ................................ ................................ ..................... 32 Alcohols Phytol Degradation ................................ ...................... 34 Biomarker Summary ................................ ................................ ...... 36 Carbon Isotope Profiles ................................ ................................ ............ 36 Organic Carbon ................................ ................................ ............. 38 Inorganic Carbon ( CaCO 3 ) ................................ ............................ 40 Carbonate Accretion ................................ ................................ ................ 40 Summary ................................ ................................ ................................ ............. 44 An Integrated Perspective ................................ ................................ ........ 4 4 Significance ................................ ................................ .............................. 45 Conclusion ................................ ................................ ................................ .......... 49 References ................................ ................................ ................................ .......... 51 Appendices ................................ ................................ ................................ ......... 60 Appendix A: Extra Tables ................................ ................................ ......... 61 Appendix B: Extra Figures ................................ ................................ ....... 66
! iii List of Tables Table A1: FAME Distribution ................................ ................................ ............... 61 T able A2: Alcohol Distribution ................................ ................................ ............. 62 Table A3: Hydr o carbon Distribution ................................ ................................ .... 63 Table A4: Archaeal 16S rD NA Clone Identification ................................ ............. 64 Table A5: Eukaryotic 18S rD NA Clone Identification ................................ .......... 64 Table A6: Bacterial 16S rD NA Clone Diversity Results ................................ ...... 65
! iv List of Figures Figure 1: Site Loc ation ................................ ................................ .......................... 3 Figure 2: Layer Isolation ................................ ................................ ..................... 10 Figure 3: Bacterial Community Overlap ................................ .............................. 19 Figure 4: Bacterial Community Profile ................................ ................................ 21 Figure 5: Profile of Select Biomarkers ................................ ................................ 34 Figure 6: Carbon Isotope Profiles ................................ ................................ ....... 37 Figure 7: Carbonate Accretion Model ................................ ................................ 4 3 Figure 8: Su mmary Model ................................ ................................ ................... 4 8 Figure B1: Organic 15 N data ................................ ................................ .............. 66 Figure B2: Percent Sequ ence Identity (Top Blast Hit) ................................ ........ 67 Figure B3: Bacterial 16S r D NA Diversi ty Results (Layer 1) ................................ 68 Figure B4: Bacterial 16S rD N A Diversity Results (Layer 2) ................................ 69 Figure B5: Bacterial 16S r D N A Diversity Results (Layer 3) ................................ 70 Figure B6: Bacterial 16S rD N A Diversity Results (Layer 4) ................................ 71 Figure B7: Bacterial 16S rD NA Diversity R esults (Layer 5) ................................ 72 Figure B8: Bacterial 16S rD NA Diversity Results (Total Community) ................. 73
! v Abstract Mod ern microbialites are carbonate precipitating microbial mats and represent the closest living analogues to ancient stromatolites. T hese a ncient carbonate formations are the old est fossil evidence of life on E arth; however, our comprehension of their relations hip to early earth ecosystems relies heavily on understanding the formation of modern microbialites. Research regarding these formation processes has suggested that chemical constraints of CaCO 3 precipitation vary on sub millimeter spatial scales within th e living microbial community. In an attempt to shed light on the importance of these chemical microenvironments this study focused on understanding the spatial distribution of the organisms and processes involved in the formation of modern microbialite s This was accomplished by isolating f ive visually distinct layers from the upper 2 3 cm of an actively forming microbialite found in the freshwater system of Cuatro CiÂŽnegas, Mexico Each layer was analyzed using genomic, molecular organic, and stable iso topic techniques Bacterial diversity was deter mined by 16S rRNA gene analyses, l ipid biomarker content was detected by GC MS and carbon isotope composition of organic matter and CaCO 3 were used as indicators of specific microbial processes R esults of th e 16S rRNA gene analysis show ed that there is little overlap in the community composition of individual layers A pproximately 90% of the ribotypes identified in the microbialite
! vi were unique to a single layer. Furthermore, the relative accretion of CaCO 3 at each layer was used to connect the distribution of organisms and processes with two specific zones of CaCO 3 precipitation The first zone of CaCO 3 accretion, which accounted for approximately 55% of total CaCO 3 accumulation, is found in the surface two la yers of the microbialites and dominated by p hotoautotrophic cyanobacteria and alg ae T he second zone of CaCO 3 precipitation, found at the interior (layers 4 and 5) is composed primarily of heterotrophic proteobacteria and dominated by sulfate reducing p roteobacteria The lipid cont ent of the microbialite reflected the community structure as determined by genomics N umerous photosynthetic biomarkers were detected and decrease d in abundance with depth indicating the important function of heterotrophic degr adation. Additionally, t he detection of sulfurized phytol compounds in layer 5 highlighted a n impo rtant mechanism for the preservation of biogenic signatures, and reflected both the abundance of phototrophic organisms and sulfate reducing bacteria. In comb ination the se interdisciplinary analyse s provided an understanding of microbial commun ity composition and metabolism while indicating the spatial relationship to CaCO 3 formation and the preservation of distinct biochemical signatures
! 1 Introduction M icrobialites are organosedime n tary mats composed of diverse microbial communities that influence accretion by the trapping of sediment and formation of minerals precipitates (Burne & Moore, 1987) Though rare mic ro bialites are found in diverse marine and freshwater environments (Awramik & Grey, 2005) often characterized by extreme conditions. For instance, in S harks Bay, Australia microbialites are f orming in hyper saline water (Burns et al. 2004) Highborne Cay, Bahamas microbialites are found in a high energy wave dominated system (Andres & Reid, 2006) and numerous examples can be found from hot spring environments such as those in Yellowstone National Park U.S.A. (Walter et al. 1972) Additionally, the freshwater system of Cua tro CiÂŽnegas, Mexico, which is the focus of this study, supports the formation of microbialites under extreme ly low phosphorus conditions (Elser et al. 2005a) Throughout these environments, m icrobialites develop different structural form ation s including dendritic thrombolites (Kennard & James, 1986) and oncolites (Dean & Eggleston, 1984) as well as stromatolites which have a laminated morphology and are thought to be analogous to ancient microbialites that are preserved in the rock record (Awramik & Grey, 2005) S ome fossilized stromatolite s are thought to be greater than 3.4 billion years old (Allwood et al. 2006) indicating that these ancient carbonate formations are a product of some of the earliest biological communities (Schopf,
! 2 1999) Construct ing a robust understanding of modern microbialites can enhance our comprehension of the significance of similar communities within the ancient environment as well as their relationship to the evolution of life and ecosystems. While much remains unknown wit h respect to these ancient stromatolites, great strides have been taken over the past 30 years to describe the processes through which physical, chemical, and biological activity control the formation of modern microbialites. The primary objective of the research done here was to add to this growing understanding o f modern microbialite formation by investigating the actively accreting microbialites of Cuatro CiÂŽnegas, Mexico using an interdisciplinary approach Found in the Chihuahuan Desert of Co ahuila, Northern Mexico, the Cuatro CiÂŽnegas Basin (CCB) is a naturally isolated valley (Fig. 1) containing hundreds of permanent lakes, rivers, marshes, and springs as well as ephemerally flooding playas (Minckley & Cole, 1968) The numerous aquatic habitats within this karstic la ndscape primarily originate from thermal springs (25Â¡ 35Â¡ C), and are characteristically hard water environments containing high concentrations of SO 4 2 and NO 3 (Breitbart et al. 2009; Elser et al. 2005a; Minckley & Cole, 1968) Additionally, the CCB has the lowest phosphorus content reported for continental waters, exerting a selective pressure on the composition of the biological communities and enhancing m icrobialite formation due to poor grazing efficiency by snails and other eukaryotic predators (Elser et al. 2005a; Elser et al. 2005b)
! 3 The physiogeographic isolation of the CCB has led to a remarkably high level of endemism (Stein et al. 2000) In fact, the CCB has the greatest endemic diversity in North America, with more than 70 unique species (Badino et al. 2004) The b acteria, archaea and viruses of Cuatro CiÂŽnegas are also abundant as well as diverse (Breitbart et al. 2009; Desnues et al. 2008) N otably, the bacterial and viral communities are most closely related to marine phylotypes even though this region has been isolated from such systems for millions of years (Desnues et al. 2008; Souza et al. 2006) The CCB is a unique location for studying modern microbialite formation due to t his hypothesized association with an ancient marine system and the extremely low phosphorus content which indicates an intriguing similarity to early earth, where phosphorus was much less abundant (Bjerrum & Canfield, 2002) Figure 1: Site Location (A) Satellite image of North America, with Cuatro CiÂŽnegas indicated. (B) Satellite image of the Cuatro CiÂŽnegas valley, with Rio Mesquites indicated. (C) Actively forming microbialites within Rio Mesquites.
! 4 I n environment s that are conducive to CaCO 3 accretion such as the CCB, t he formation of carbonate deposits is strongly influenced by the microbial community (Casanova et al. 1999) Within modern microbialite s, t he se communities are composed of bacteria, archaea, and often eukaryotes that form vertically stratified layers based on light oxygen, and nutrient availability (van Gemerden, 1993) Though the microorganisms associated with microbialites from different environments are distinct there tends to be a conservation of the most dominant groups, at least at the phylum lev el. The p hylogenetic characterization s of bacteria in microbialites from Australia (Allen et al. 2009) the Bahamas (Baumgartner et al. 2009) and Spain (Santos et al. 2009) have all shown an abundance of Alphaproteobac teria, Bacteroidetes, Cyanobacteria, Deltaproteobacteria, and Planctomycetes. Essentially, i t is t he combined metabolic activity of this characteristic microbial community that alters the chemical and physic al composition of the matrix and thus controls th e formation of modern microbialites Individual metabolic processes utilized by the microorganisms within a microbialite can have discrete effects on the saturation of CaCO 3 and result in its net gain or loss (Visscher & Stolz, 2005) While numerous metabolic processes have the potential to affect CaCO 3 precipitation (Visscher & Stolz, 2005) the general interaction of photoautotrophic and heterotrophic organisms is a key factor in the formation of microbialites (Altermann et al. 2006) The prevalence of p hotosynthetic metabolism in microbialite communities primarily by C yanobacteria, plays an influential role in the formation process. Specifically, the
! 5 uptake of CO 2 during photosynthesis increase s the local pH through the buffering action o f bicarbonate (Visscher & van Gemerden, 1991) and the resulting alkaline state favors the precipitation of CaCO 3 Additionally, Cy anobacteria and other photosynthetic microorganisms produce copious amounts of extracellular polymeric substances (EPS) a complex organic matrix that is the structural backbone of many biofilms (Braissant et al. 2009; De Philippis et al. 2000; Decho et al. 2005; Sutherland, 1999) This carbohydrate rich material efficiently binds Ca 2+ restricting the amount available for CaCO 3 precipitation (Kawaguchi & Decho, 2002) However it is suspected that the subsequent degradation of EPS by heterotrophic organisms releases these bonds, flooding the local environment with Ca 2+ and thus, indirectly forcing the syst em into a state where CaCO 3 can precipitate spontaneously (Decho et al. 2005) Among this heterotrophic community, sulfate reducing bacteria are thought to contribute significantly to CaCO 3 formation both through the degradation of phototrophic material as well as the production of HCO 3 (Giblin et al. 1990; Visscher et al. 2000; Visscher et al. 1998) In fact, the research on Bahamian stromatolites by Visscher et al. (2000; 1998) gi ve s compelling evidence that sulfate reducing activity is the primary force behind CaCO 3 precipitation. Using SO 4 2 coated Ag foil techniques to detect distinct horizons of sulfate reduction and petrographic thin section analysis, they show a direct correlation between zones of elevated sulfate reducing activity and the formation of lithified micritic laminations (Visscher et al. 2000) The diverse heterotrophic and phototrophic metabolic processes within modern microbialites influence the
! 6 immediate chemical env ironment and thus are essentially responsible for the ir growth. T his microbial control over CaCO 3 formation has been depicted by microelectrode analyses of naturally forming microbialites. O bservations a t the interface of a microbialite and the ambient water column in Cuatro CiÂŽnegas reveal discrete changes in pH, as well as O 2 and Ca 2+ concentrations with proxim ity to the microbialite surface (Garcia Pichel et al. 2004) This demonstrates the ability of the microbial community to control the chemistry of its immediate surroundings, producing what are commonly referred to as chemical microenvironments. Additionally, the processes that drive carbonate precipitation and the formation of these chemical microenvi ronments are not constant in either time or space. The research in Cuatro CiÂŽnegas (Garcia Pichel et al. 2004) as well as work in Highborne Cay Bahamas (Vi sscher et al. 1998) shows d iel fluctuations of chem ical microenvironments occu r r ing on a sub millimeter scale s within the microbialite surfaces In a vertical profile of th e top 15 mm of the Highborne Cay microbialites Visscher et al. (1998) detect significant changes in pH, O 2 concentration, and HS concentration occurring over a span of 20 hours. The se chemical parameters are directly affected by the distribution of organism s and metabolic processes within the microbialite, and can influence CaCO 3 precipitation and dissolution Thus, it can be establish ed that the discrete processes relevant to the formation of modern microbialites occur within similar spatial scales
! 7 In addition to influencing chemical microenvironments, organisms within a microbialite also control the isotopic and molecular organic composition of the microbialite matrix. These geochemical signatures contain specific information about the community composition and the interaction of microbial metabolic processes, making them extremely useful for interpreting microbialite formation. The production and subsequent remineralization of organic matter generate s isotopic signatures that can be linked to specific enzymatic fractionation pathways or metabolic processes. For example, the examination of 13 C values from CaCO 3 crusts in Bahamian stromatolites (Andres et al. 2006) provides insight to the driving force be hind aragonit e precipitation, showing that heterotrophic processes, rather than photosynthesis, are primarily responsible. In addition, specific molecular organic compounds (lipids) used as indicators of discrete microbial groups have been observed in carbonate matric es as old as 2.7 Ga (Brocks et al. 19 99) and thus can allow for the comparison of modern a nd ancient microbialite systems. This is essential for improving our understanding of ancient microbialites, as genetic material is rarely pre served on geologic time scales (Poinar, 1998) The general goal of our research was to analyze the bacterial community composition and geochemical signatures in modern, actively accreting microbialites to better understand the processes by which they are form ing. However, this goal is complicated by th e millimeter scale variation of these organisms and processes across a depth profile in the microbialite surface Thus t o observe changes in microbial composition on similar spatial scales as the
! 8 previously noted change s in chemical microenvironments we isolated 5 vis ually distinct horizons (Fig. 2 ) from the surface (2 .5 c m) of a freshwater microbialite This work combines genetic, molecular organic, and stable isotopic analyses to facilitate a more complete understanding of how the distribution of organisms relates to microbialite formation and the preservation of biological signatures Specifically we analyze the 16S rRNA gene diversity to c haracterize the bacterial communiti es of each of the 5 layers We also examine the molecular composi tion of each layer to determine if the lipid conten t directly reflects the microbial community stru cture as determined by our genet ic analysis, and to better understand how the biomass is deg raded, preserved, or altered as it becomes buried with depth Organic matter 13 C analysis help s us interpret how different carbon cycling processes affect microbialite formation while inorganic 13 C profiles of CaCO 3 in each layer enabled us to understand the incorporation of biological signatures into the carbonate matrix We also look at the relative accretion of CaCO 3 within each layer to directly relate the distribution of different organisms and processes to microbialite formation Th ese interdisciplinary approaches, applied to individual layers within the microbialite provide a unique insight into the formation of modern microbialites and can be used to better understand how specific microbial processes are directly associated with ca rbonate precipitation
! 9 Material s and Methods Sample Collection All samples for this work were collected from Rio Mesquites (Fig. 1) in the CCB during a single sampling trip in July of 2008. Rio Mesquites the largest river in the CCB, is spring fed and ranges from 2 to 20 meters across, reaches up to 2.5 meters in depth, and contains many actively forming microbialites (Minckley, 1969) In order to isolate the individual layers a section of the microb ialite surface was removed then cut into slabs (~ 1 cm thick), exposing the vertical face of the sample. A scalpel was then used to separate the visually distinct horizons, resulting in layers 1 through 5 from the surface to the interior (Fig. 2) The 1 st layer was approximately 1 2 mm thick and was yellow ish green in color with a soft string like texture Layer 2 was more gelatinous 2 4 mm thick and had a dark green color. The 3 rd layer was bright white with a sandy texture and a thickness of about 5 mm. Layer 4 was grey to tan in color with a va rying thickness (~ 5 mm) and a firm er texture than layer 3. Finally, the 5 th layer was a dark red and brown color and extremely robust These 5 layers accounted for approximately the top 2 3 cm of microbial ites that are greater than 1 meter in height and between 0 .5 1 meter in diameter
! 10 Figure 2 : Layer Isolation A living microbialite in Rio M esquites is shown on the left and on the right an image of t he exposed vertical profile of the microbialite shows the 5 v isually distinct layers. S amples collected for genomic work were isolated in situ into 5 distinct layers (Fig. 2 ), immediately fixed in RNA Later (Applied Biosystem s/ Ambio n, Austin, TX USA) and then sto red on ice until return to the University of South Florida, College of Marine Science Upon return within 1 week of collection the RNA Later was drained off and the samples were frozen ( 80 Â¡ C) in accordance with the manufacturer s instructions Samples for molecular organic and isotopic work were placed on ice until return to the lab (within 1 week of collection) at which point they were frozen ( 20 Â¡ C).
! 11 DNA Extraction Individual layers (1 5) were homogenize d then approximately 30 mg of sample was extracted using an AllPrep DNA/RNA Mini Kit (Qiagen Inc., Valencia, CA USA) according to the manufacturer s protocol for samples stored in RNA Later (Applied Biosystems/Ambion). Purified DNA extracts were eluted in sterile H 2 0 (5 0 l ) and stored at 20 Â¡ C until further analysis Amplification Cloning, and rRNA Gene Sequencing The bacterial 16S gene was amplified using the Bact 27F ( 5' AGA GTT TGA TCM TGG CTC AG 3' ) and 1492R ( 5' ACG GCT ACC TTG TTA CGA CTT 3' ) primer set (Weisburg et al. 1991) acquired from Integrated DNA Technologies ( Coralville, IA, USA). All PCR mixtures had a total volume of 50 l and contained 5 l of target DN A, 1X RED Taq PCR buffer (10.0 mM Tris HCl [pH 8.3], 50.0 mM KCl, 1.1 mM MgCl 2 0.01% gelatin; Sigma Aldrich, St. Louis, MO, USA), 0.25 mM each deoxynucleoside triphosphate, 1 M of each primer, and 1 U RED Taq DNA polymerase (Sigma Aldrich ) The PCR conditi ons contained a 5 minute denaturation step at 95 Â¡ C, 30 cycles of (1 minute at 94 Â¡ C, 1 minute at 65 Â¡ C, and 2 minutes at 72 Â¡ C), and a final elongation step of 10 minutes at 72 Â¡ C. Bacterial 16S PCR products were cloned using the TOPO TA cloning kit according to the manufacturer's instructions (Invitrogen Corp. Carlsbad, CA USA ). Clones were grown on Luria Bertani (LB) plates with ampicillin (50 g ml 1 ) and X gal ( 20 g ml 1 ) (5 bromo 4 chloroindoly D galacto pyranoside in dimethyl formamide ). White colonies were further screened by PCR with the primer set
! 12 M13F ( 5' GTA AAA CGA CGG CCA GT 3' ) and M13R ( 5' CAG GAA ACA GCT ATG AC 3' ) to reaffirm that the insert was taken up. Colonies with inserts were t hen grown in g lycerol stock s (40 ml LB, 10 ml 50% glycerol, 50 l ampicillin (50 mg ml 1 ) ) and used for sequencing All gene sequencing was done through Beckman Coulter Genomics, formerly Agencourt Biosciences Corporation (Beverly, MA USA ). Sequence Analysis Raw s equ ences were trimmed of all vector sequence and any low quality ends using Seq uencher (GeneCodes, Ann Arbor, MI, USA) FastGroupII ( http://biome.sdsu.edu/fastgroup/ ) was used to dereplicate the trimmed 16S sequence libraries, grouping those sequences determined to be a single ribotype ( 97% PSI with gaps ) and removing those that were less than 300 base pairs in length (Yu et al. 2006). BLASTN ( http://www.ncbi.nlm.nih.gov/ ) was then used to compare individual ribotypes to previously described gene sequences found in the GenBank d atabase. Lipid Extraction Approximately 4 8 grams of each sample (layer 1 5) was homogenized in a pre cleaned mor tar with pestle. Samples were mixed with diatomaceous earth (2:1 D E to sample) then placed in a 2 2 ml stainless steel extraction vessel Total extractable lipids were then obtained by an Accelerated Solvent Extraction system (Dionex ASE 200, Sunnyvale, CA, USA). The ASE method utilized a 5
! 13 min ute prehe ating step to bring the sample to an ext raction temperature of 120 C followed by a 10 min ute static phase with an extraction cell pressure of 1500 PSI. The extraction program was performed three times; first with dichloromethane (DCM), followed by DCM/methanol (1:1 v/v), and finally with methanol only Following each extraction phase the cell was flushed with 60% of the total volume and purge d for 2 minutes with N 2 The three extracts from each sample were combined blown down to dryness under a gentle stream of N 2 and then re dissolved in DCM/ methanol (1:1). Elemental sulfur was removed from eac h sample with activated copper turnings (~5 g; 24hr). Separation of Compound Class Total lipid extracts were blown down to dryness under a gentle stream of N 2 then re dissolved in a 0.5N KOH in methanol solution (10 ml). Samples were heated (70 C) for 2 hrs in a well sealed 40 ml vial. After saponification, vials were allowed to cool to room temperature prior to opening to avoid any loss of sample N eutral and acidic compounds were separated by l iquid liquid extractions at a pH of 7 and 2, respe ctively Neutral compounds w ere separated into polar and a polar fractions on an activated silica gel column preconditioned with hexane. Hydrocarbons were eluted first with hexane (~12 ml), followed by the ketone compounds eluted in 10 ml hexane/DCM (6:4 v /v). Finally the alcohol fraction was eluted in 10 ml of DCM/methanol (1:1 v/v). The hydrocarbon fraction was immediately ready for analysis by GC MS after the volume was reduced under a gentle stream of N 2
! 14 The alcohol fraction was first converted to trimethylsilyl (TMS) derivatives by reducing the sample to dryness, re dissolving in a solution of bis(trimethylsilyl) trifluoroacetamide (BSTFA; 50 l) mixed with pyridine (50 l) and DCM (10 l) and heating to 70 C for 30 min utes The fatty acids were c onverted to methyl ester derivative s by reducing to dryness with N 2 and re dissolving in methanolic HCl (10 ml). The solution was heated to 60 C for 3 hours then allowed to cool prior to opening the vial and reducing to dryness. Methy l ester derivatives were re dissolved in hexane and then separated into polar and apolar fractions on an activated silica column conditioned with hexane. Non polar compounds were eluted with hexane (7 ml) followed by the fatty acid methyl esters (FAME), whi ch were eluted with 7 ml hexane/ethyl acetate (95:5 v/v). The FAME fraction was then reduced to dryness and re dissolved in hexane. Analysis by GC MS H ydrocarbon, FAME, and TMS alcohol fractions were analyzed by GC MS using a Varian CP 3800 GC equipped wi th a VF 5ms capillary column (V arian Inc., Palo Alto, CA, USA) and linked to a Varian 320 MS operating at 70 eV ionization energy. The GC MS was fitted with a Varian CP 8400 Autosampler. For hydrocarbon analysis, t he injector temperature was held constant at 240 C while the oven was kept at 50 C for 2 min utes then gradually raised to 310 C at a rate of 8 C min ute 1 A constant flow (1 ml min ute 1 ) of helium was used as a carrier gas. For the FAME fraction the injector temperature was held at 280 C
! 15 whi le the oven was kept at 50 C for 1 min ute then ramped to 120 C at a rate of 30 C min ute 1 where it was held for 5 min utes The oven temperature was then raised to 320 C at a rate of 8 C min ute 1 where it was again held constant for 10 min utes A constant flow (2 ml min 1 ) of helium was used as a carrier gas. The TMS derivatives of polar alcohol lipids were analyzed with an inj ector temperature of 25 0 C. The oven was kept at 60 C for 2 min utes then ramped to 2 50 C at a rate of 1 0 C min ute 1 and then to 320 C at 3 C min ute 1 The temperature was then held at 320 C for 30 min utes A constant flow (1.5 ml min ute 1 ) of helium was used as a carrier gas. All compounds were identified by comparison of mass spectra to know n compounds found in the literature. Quantification of identified compounds was done by comparison of total ion peaks to those of similar calibration standards. Stable Isotope Analysis Samples were prepared for isotopic analysis of organic matter by treatm ent with a mild acid solution (0.5 N HCl) until all carbonate was neutralized. Remaining organic matter was then filtered onto a pre combusted 0.7 m GF/F glass fiber filter, rinsed with deionized water, dried at a low temperature (60 Â¡C), and subsequently packed into tin capsules for 13 C analysis. Solid phase carbonate minerals were prepared for isotopic analysis by grinding samples to a fine powder and drying at low temperature. All isotopic analyses were conducted at the University of South Florida Pale oceanography, Paleoclimatology and Biogeochemistry Laboratory.
! 16 A 50 g aliquot of each carbonate mineral sample was measured for inorganic 13 C using a ThermoFinnigan Delta Plus XL dual inlet mass spectrometer with an attached Kiel III carbonate preparati on device. Isotopic analyses of organic samples were performed using a continuous flow Finnigan Mat Delta Plus isotope ratio mass spectrometer coupled to a Carlo Erba elemental analyzer (EA). Samples were introduced via an autosampler into the combustion f urnace of the EA set at 1050Â¡C. Flash co mbustion converted all carbon in the sample to pure CO 2 which was eluted off a gas chromatograph column and carried by a stream of helium gas to the mass spectrometer, where the 13 C abundance was measured based on mass to charge ratios. Microscopy Scanning electron microscopy (SEM) was completed at the University of South Florida College of Marine Science Electron Microscopy Laboratory, using a Hitachi S 3500N variable pressure Scanning Electron Microscope. S amples were prepared for microscopic analysis by drying at a low temperature ( 60 Â¡C ) then coating with a thin layer of AuPd in a sputter coater. Material Balance The physical composition of individual layers of the microbialite was determined by analyzing the relative mass distribution of water, carbonate, and organic material, the sum of which are assumed to account for the entire microbialite matrix A sample of each layer was weighed, dried and then weighed
! 17 a second time to d etermine the water content. The dried material was then ground to a fine powder and subsamples were used for total carbon (TC) a nd total inorganic carbon (TIC) analysis by coulometric titration. Total organic carbon was determined as the difference between TC and TIC.
! 18 Results Bacterial clone l ibraries Bacterial 16S rRNA gene libraries wer e constructed for each of the 5 layers of the microbialite and contained between 62 and 91 clones each. In total 399 bacteria l clones were analyzed from the Cuatro CiÂŽnegas microbialite A pproximately 75% of the bacterial clones recovered from the microbialite were less than 97% identical to the most similar sequences found in GenBank suggesting a high abundance of novel species. Dereplication of the total bacterial clone library (layer 1 layer 5) with the FastGroupII application (Yu et al. 2006) revealed little overlap in community composition between the individual layers of the microbialite (Fig. 3). This pr ocess compared the sequences based on nucleotide similarity, and combined th e 399 quality 16S clones into 261 distinct ribotypes. Overlap in community composition was determined as ribotypes that contain sequences from multiple layers This process reveale d that layer 1 and layer 2 have the greatest overlap with 11 ribotypes containing sequences from both layers. Layer 1 did no t share a single ribotype with any o ther layer, while layer 2 shared only two with layer 3. The interior layers (3, 4, and 5) were m ore similar to one another than to the surface two layers, as there is a total of 12 ribotypes that contain ed sequences shared between some combination of layers 3, 4, and 5 However, the majority (90%) of ribotypes from the Cuatro CiÂŽnegas microbialite clone library contain ed sequences from only a single layer.
! 19 Figure 3 : Bacterial Community Overlap Phylogenetic overlap between layers as determined by a FastGroupII dereplica tion analysis of the entire bacterial community. Numbers represent the total number of individual ribotypes from a given layer(s). In addition to comparing the community overlap with in the Cuatro CiÂŽnegas microbialite these sequences were combined with 16S sequences from a Highborne Cay, Bahamas study (Havemann & Foster, 2008) and analyzed together Dereplication (FastGroupII) of this sequence set revealed that only a single ribotype contained se quences from both the Cuatro CiÂŽnegas and Highborne Cay clone libraries. That ribotype, containing clones from both environments, was composed of sequences that were determined to be most similar to the Cyanobacterial order Pleurocapsales Within the Cuatro CiÂŽnegas 16S rDNA clone libraries Cyanobacteria, Bacteroidetes, P roteobacteria, Nitrospiraceae, and Gemmatamonadetes comprise d some of the major phylogenetic groups, with disparate distribution throughout the 5 layers (Fig. 4 ) The microb ialite surface was characterized by the overwhelming dominance of phototrophic organism s, comprising
! 20 approximately 6 5% of the total bact erial 16S clones obtained from layer 1 and nearly 50% from layer 2. Cyanobacteria mad e up the largest portion of the sur face community in the Cuatro CiÂŽnegas microbi alite bacterial clone library (layer 1 >50%; layer 2 ~30%). Addition ally, 11% of the 16S clones in layer 1 had top BLAST hit s to chloroplast rR NA gene sequences of eukaryotic algae (diatoms). Sequences with top BLAST hits to proteobacteria account ed for approximately 10%, 20%, and 25% of clones in layer 1, 2, and 3 respectively many of which group ed closely with organisms in the family Rhodospirillaceae, the purple non sulfur (PNS) bacteria Following the Cyanobacteria, Bacteroidetes was the second most abu ndant phylum identified in the layer 1 and layer 2 clone libraries accounting for 18 % and 23%, respectively. The 3 rd through 5 th layers were primarily characterized by a dominance o f the p roteobacteria which make up about 45 50% of clones, including organisms from the # and $ sub phyla. The clone libraries of the interior layers (3 5) also include d numerous groups that were poorly represented (<5% of total clone s ) A phylogeneti c comparison of the abundant C yanobacteria sequences with those of cultured C yanobacte ria obtained from GenBank, showed that the Cuatro CiÂŽnegas clones fall into three separate orders. Nearly 60% of the sequences group ed with the order of filamentous Cyanobacteria Oscillatoriales, primarily in the Pseudanabaena and Leptolyngbya genera. Another 20% of the C yanobacterial clones were most similar to the Pleurocapsales, and 10% to the Nostocales orders of coccoid C yanobacteria. Additionally, 10% of the se quences did not appear to group with any specific phylogenetic group of Cyanobacteria
! 21 Figure 4 : Bacterial Community Profile Distribution of bacterial 16S clones for each individual layer. Color coded pie pieces represent the most similar phylogenetically described BLAST hits in the GenBank database.
! 22 Lipid Extracts The total extractable lipids from the Cuatro CiÂŽnegas microbialite accounted for 0.03 0.68% (Wt% Dry Material) of the individual layers. The distribution of compound classes was characterized by the dominance of fatty acids (analyzed as FAMEs), followed by the polar alcohol compounds including aliphatic and polycyclic constituents (analyzed as TMS derivatives) and a relatively small pool of apolar hydrocarbons. The total organ ic carbon (TOC) content of each individual layer was used to standardize lipid abundance. Overall there was a decrease in lipid content relative to TOC with depth, however layer 4 exhibited a high lipid concentration, comparable to that of layer 1. The sou rce of this anomaly was not determined FAME Distribution Saturated straight chain fatty acids were the most abundant compounds in all 5 layers, accounting for approximately 50% of the FAMEs analyzed. The saturated C16:0 FAME was the single most dominant compound within every layer's fatty acid profile (75 900 g g 1 TOC) Monounsaturated fatty acids, primarily C16:1 and C18:1 isomers were the second most abu ndant group of compounds, show ing a n overall decrease in concentratio n with depth (Fig. 5 A ) A similar reduction of polyunsaturated C18 and C20 FAMEs is observed between the microbialites surface and interior (Fig 5 B ). Branched chain fatty acids comprise d a significant but small er proportion of the total FAMEs in the top layer (343 g g 1 TOC ) however the relative concentration of these compounds increase d with depth
! 23 Alcohol Distribution The normal chain alkanols were the overwhelm ingly dominant compounds in the alcohol fraction. Sterols, i ncluding cholesterol, ergostanol, stigmasterol, and b sitosterol accounted for between 1 5 to 10 0 g g 1 TOC in each layer. Phytol ((2E,7R,11R) 3,7,11,1 5 tetramethyl 2 hexadecen 1 ol) was found in every layer but most abundant in the 1 st layer at 95 g g 1 TOC Hydrocarbon Distribution The hydrocarbon fraction displayed a bi modal distribution of saturated st raight chain compounds ranging in le ngth from 16 to 33 carbon atoms. Monounsaturated n C17:1 and n C19:1 were also observed in the hydrocarbon profile, with C19:1 becoming the most p rominent compound in layer 4 (37 g g 1 TOC). A series of mid chain methyl branched alkanes ranging from 18 to 20 carbon atoms were also abundant in the microbialite lipid extracts. Mono methyl ( 6 methyl, 7 methyl, and 3 methyl ) heptadecanes were found throughout Additionally, phyt ene, a derivative of the isoprenoid phytol was detected in layer 1 through layer 4, with the highest concentration (28 g g 1 TOC) in layer 3. Two C20 isoprenoid thiophene isomers, 3 methyl 2 (3,7,11 trimethyldodecyl) thiophen e and 3 (4,8,12 trimethyltridecyl) thiophene were observed in layer 5. Also present in the hydrocarbon extracts was the apolar hopanoid hop 22(29) ene ( diploptene )
! 24 Carbon Isotope Profiles The stable isotopic composition of organic carbon ( 13 C) was significantly depleted in 13 C with in every layer of the Cuatro CiÂŽnegas microbialite. Values ranged from approximately 12 to 23 between the five layers (Fig. 6 ). The 13 C values of inorganic (CaCO 3 ) carbon (Fig. 6 ) follow ed a similar trend to tha t of the organic pool, however they were significantly more enriched ( 1.06 to +3.02). Microbialite Composition The results of the material balan ce analysis can be observed in F igure 7A. Briefly, CaCO 3 accounted for 35% to 90% (by weight) of the microbialite matrix at every layer, with increasing relative abundance at depth. Alternately, organic matter and water constitute d a decreasing proportion of the matrix with depth. Organic matter made up 6% (by weight) at the surface and less than 3% in layer 5 Through this analysis t he formation of CaCO 3 was determined to occur in two primary zones, with the first zone (layer s 1 and 2) accounting for approximately 55% of the total carbonate accumulation (by mass) and the second zone (layers 4 and 5) responsible for 40%.
! 25 Discussion This project was very unique in that it combined genomic, molecular organic, and stable isotopic strategies in the analysis of discrete layers within a single microbialite. The layer s pecific approach of this project enables us to interpret how the discrete microbial communities within a single microbialite are spatially distributed and how they are connected by the production and decomposition of organic material. The results of this work indica t e that there are distinct differences between individual layers of the Cuatro CiÂŽ negas microbialite, both in community composit ion and geochemical signatures. T here was a tremendous amount of information obtained through these diverse analytica l approaches, and the major trends in these date lead to a better understanding of microbialite formation, determined by the accretion of CaCO 3 in spatially distinct layers. Phylogenetic Analysis Uniqueness of 16S clone libraries Dereplication of the Cuatro CiÂŽnegas 16S sequences supports the notion that while they are structurally continuous, the individual layers of the microbialite represent phylogenetically distinct communities. The small amount of overlap in community composition between individua l layers, as shown in Figure 3, is striking when considering that these 5 layers were isolated from a portion of the
! 26 microbialite no more than 3 cm thick. Furthermore, these results contest any concern that the sample isolation methods may have resulted in any significant cross contamination of material between individual layers. Comparison of t he bacterial 16S clone library to sequences within the GenBank database reveals a high level of similar ity to other calcareous microbial mat systems In particular, the surface show s the greatest similarity to other microbialite communities, as approximately 33% of the clones in layer 1 and layer 2 have a top BLAST hit to sequences recovered from such environments. T op BLAST hits of the Cuatro CiÂŽnegas clones display a wide geographical distribution, but in general there is a high frequency of hits to Sharks Bay Australia (Allen et al. 2009) Yellowstone hot springs (Fouke et al. 2003) and Highborne Cay Bahamas stromatolites (Havemann & Foster, 2008) Other environments with a high frequency of similarity to the Cuatro CiÂŽnegas clones are soil, caves, and karstic limestone systems. The similarity of Cuatro CiÂŽnegas clones to bacteria from other microbialite systems may be an indicator of a unique community that is common to carbonate accreting environments. Phototrophic Community Composition E ukaryotic algae, largely diatoms, are abundant in the microbialite surface as shown through hits to chlor oplast rR NA gene sequences from the layer 1 clone library (Fig. 4 ). This was confirmed through a eukaryotic 18S gen es analysis and the visual observation (by SEM) of numerous pe nnate diatoms on the microbialite surface. As displayed though 16S analysis, C yanobacteria make
! 27 up the gre atest portion of clones in the layer 1 and layer 2 libraries. This is in agreement with previous work (Breitbart et al. 2009) where a metagenomic analysis of bulk microbialite material (layers were not separated) from Rio Mesquites revealed that 74% of the total sequences recovered were from C yanobacteria. Among the Cyanobacteria, there is an abundance of clones that group most closely with the order Oscillatoriales These filamentous C yanobacteria are common in carbonate precipitating biofilms and observed ubiquitously in modern microbialites (Golubic, 1976; Myshrall et al. 2010) Additionally, the sharing of a Cyanobacterial ribotype through the dereplication of Cuatro CiÂŽnegas and Highborne Cay, Bahamas clones (Havemann & Foster, 2008) reveals some similarity in the Cyanobacteria of these individual communities This is of significant interest because Foster and colleagues suggested that Pleur ocapsales and other endolithic C yanobacteria are some of the primary C yanobacteria l groups involved in the formation and growth of stromatolites (Foster et al. 2009) The commonality of Cyanobacteria species found within the Cuatro CiÂŽnegas microbialite to other carbonate precipitating microbial mat environments is a potential indication the role that these specific organisms play in the formation of modern microbialites In addition to C yanobacteria and euka ryotic algae layers 1 through 3 contain a group of phototrophic proteobacterial (Fig. 4 ). T he majority of proteobacterial clones group most closely with species that are physiologically categorized as phototrophic p urple non s ulfur ( PNS ) bacteria It has been suggested that these bacteria which have the ability to function as either aerobic
! 28 chemoheterotrophs or anaerobic photoheterotroph s grow naturally under microaerophilic or alternating oxic and anoxic conditions (Bryant & Frigaard, 2006) The presence of such alternating O 2 conditions within the surface three layers of the microbialite could be expected, as was observed through chemical microprobe analyses by both Visscher et al. (1998) during a diel cycle study of Bahamian stromatolites and Garcia Pichel et al. (2004) during a similar study on Cuatro CiÂŽnegas microbialites The abundance of these organisms suggests that the surface community is dominantly phototrophic and composed of both oxygenic ( e.g. Cyanobacteria) and anoxygenic (e.g. PNS bacteria) bacteria Non phot otrophic Community Composition Though the surface community is primarily phototrophic in nature, there are many clones most similar to Bacteroidetes, a group of heterotrophic organisms of ten found in other epilithic biofilms and well adapted for such environments (Bruckner et al. 2008) Their presence in the microbialite surface community provides a possible mechanism for the initial cycling of photoautotrophically produced organic carbon, as they have been described as efficient degraders of EPS and carbohydrates (Bauer et al. 2006; Kirchman, 2002) T he ability of Bacteroidetes organisms to efficiently degrade polymeric substances, such as those compounds found in EPS, may also play an important role in CaC O 3 formation through the release of EPS bound Ca 2+ Additionally, t his initial decomposition of the complex organic matrix likely provides metabolic substrates for heterotrophic organisms found in the interior layers.
! 29 P roteobacteria dominate the microbial ite interior ( layers 3, 4, and 5 ), as shown by 16S analysis (Fig. 4 ) The overwhelming diversity of these organisms cannot be overstated, and is probably best described by Kersters et al. (2006) when noted that t he Proteobacteria accoun t for more than 40% of all prokaryotic gener a, show extreme metabolic diversity, and are of great ecological importance because they play key roles in the carbon, sulfur and nitrogen cycles Despite this extreme diversity the physiological function of some of th ese organisms can be resolved. As previously stated the proteobacteria, which dominate the 3 rd layer, group closely with PNS bacteria and likely utilize a for m of anoxygenic photosynthesis The proteobacteria make up the next largest portion of the layer 3 clone library and are the most abundant single bacterial group in layer 4, accounting for approximately 25% of the clones. T he proteobacteria sub phylum is dominated by anaerobic sulfate red ucing organisms, which account for 75% of the described species (Kersters et al. 2006) The abundance of sulfate reducing organisms in the Cuatro CiÂŽnegas microbialites is supported by the prior observation of numerous genes related to sulfate reduction within the micro bialite metagenome (Breitbart et al. 2009) While some sulfate reducing activity likely occur s throughout the microbialite evidence here suggests that it is the dominant process in layer 4. Nitrospira b acteria a group of nitrite oxidizers, are the second most abundant organisms in the 4 th layer of the microbialite, accounting for about 20% of the clone library. The prevalence of nitrite oxidizing bacteria in this zone is somewhat surprising since the dominant sulfate reducing bacteria though
! 30 capable of growth under aerobic conditions (Jonkers et al. 2005) typically only thrive in systems substantially depleted in O 2 (Cypionka, 2000) However it has been suggested that bacteria of the genus Nitrosp ira are competitive under low nitrite and oxygen conditions (Altmann et al. 2003; Daims et al. 2001; Schramm et al. 1999) Though the exact metabolic activity of the Nitrospira organisms is not know n in this case, it is likely that they are functioning under extremely low O 2 to anoxic conditions. Phylogeny Summary C lone libraries fro m the 5 distinct layers provide insight into the spatial distribution of the living microbial community. T he individual layers of t he Cuatro CiÂŽnegas microbialite contain discrete bacterial communities, transi tioning from one tha t is primarily phototrophic at the surface to a heterotrophic community at depth Additionally, while t he phylogenetic identity of bacteria does not necessarily reveal the ir metabolic activ ity, some interpretations of physiological roles are possible, espe cially if supported by geochemical evidence. Molecular Organic Biomarkers Analyzing the lipid composition of the microbialite provides a dual purpose in this study. First, the distribution of compounds in each individual layer is complimentary to the 16S rRNA gene analysis, providing an understanding of the community composition through specific biomarker abundances. Second, observing the relative change in biomarker distribution from layer 1 through layer
! 31 5 allows us to interpret the process es through which these microbial communities recycle themselves, as seen through the selective preservation or degradation of individual compounds. Additionally, among the total microbial biomass within the microbialite these lipid components typically have the grea test potential for long term preservation (Brocks & Banfield, 2009) making them useful for the interpretation of ancient systems Hydrocarbons With respect to the community composition, individual hydrocarbons are helpful in identifying specific types of organisms, while the distribution of a lkanes reveals more about the overall input of organic material. The shorter chain alkanes ( n C 16 through n C 22 ) are typically derived from a bacterial biomass, while the longer ( n C 27 through n C 33 ) alkanes with an odd over even chain length preference are common leaf waxes of higher plants (Eglinton & Hamilton, 19 67) indicating some allochthonous deposition of organic matter The overwhelming dominance of heptadecane ( n C 17 ) in layer 1 strongly supp orts the observed abundance of C yanobacterial clones in the 16S gene library, as it is a commonly obs erved compone nt of filamentous C yanobacteria (Thiel et al. 1997; Winters et al. 1969) Furthermore, the mid chain methyl branched hydrocarbons ranging from 18 to 20 carbon atoms and dominated by 7 methyl heptadecane, have been used as key indicators of C yanobacteria in microbial mats (Koster et al. 1999; Shiea et al. 1990; Thiel et al. 1997) The hydrocarbon profile of layer 2 presents an enigma as the abundance of heptadecane (relative to TOC) falls off
! 32 drastically, while the clone library continues to display a do minance of C yanobacteria (Fig 4 ). It is possible that this is a function of an increase in the non lipid component of TOC as a result of abundant EPS production, however this would suggest that there should be a similar decrease in the concentration of other lipid components as well. As heptadecane is the only hydrocarbon to display such a considerable decrease, it is likely that there is a different, unknown force controlling this observation. Thus, the series of mid chain methyl branched hydrocarbons provide a more depen dable link to the abundance of C yanobacterial biomass. The only hopanoid identified in the hydrocarbon extracts, diploptene is found in all layers While this compound can originate from higher plants such as ferns, it is prevalent in numerou s genera of bacteria including C yanobacteria (Prahl et al. 1992; Rohmer et al. 1984) Fatty Acids Compo unds common in photosynthetic bacteria and eukaryotes, along with numerous general bacterial biomarkers, dominated the fatty acids profile. The abundance of monounsaturated 16:1(n 7) and 18:1(n 9) in the surface correlates well with the genomic analysis as these compounds hav e primarily been attributed to C yanobacteria, though not exclusively (Buhring et al. 2009) Polyunsaturated fatty acids, 18:3( n 3) and 18:2( n 6) common in chlorophytes (green microalgae) and 20:5(n 3) and 20:4(n 6) found predominately in diatoms (Boschker & Middelburg, 2002; Harwood & Guschina, 2009) were obser ved at high concentrations (400 g g 1 TOC). These unsaturated fatty acids are among
! 33 the most abundant compounds in the surface layers, but are drastically reduced at the interior (Fig. 5), indicating that the heterotrophic community is able to efficiently degrade this material. T he change in community composition through the microbialite layers as determined by the 16S analysis is further supported by the observed changes in lipid content from layer 1 to layer 5. Figure 5C shows the relative increase in the ratio of 10 Methyl 16:0, a common fa tty acid of sulfate reducing bacteria (Taylor & Parkes, 1983) compared to 16:1 (n 5), a fatty acid ubiquitous to bacteria in general (Vestal & White, 1989) The peak in this ratio occurring in layer 4 coincides with th e dominance of proteobacteria within the 16S rRNA gene library, further suggesting the prevalence of sulfate reduction at the microbialite s interior. The relative increase in this sulf ate reducing bacteria biomarker in association with the decrease of 7 methyl heptadecane relative to total bacterial alkanes ( n C 16 through n C 22 ) (Fig. 5C ) reflects the shift in the bacterial regimes, from an aerobic photoautotrophically dominated community to one that is composed of anaerobic sulfate reducing organisms. Along with the reduction of unsaturated FAME concentrations (Fig. 5) this observation highlights that the photoautotrophic biomass produced at the surface is readily degraded and recycled by the successive generations of bacteria.
! 34 Figure 5: Profile of S elect B iomarkers Both (A) m onounsaturated fatty acids found commonly in C yanobacteria and (B) polyunsaturated fatty acids common in eukaryotic algae decrease in concentration between layer 1 and Layer 5 P olyunsaturated fatty acid concentrations (B) are shown as the sum of 18:3( n 3), 18:2( n 6), 20:5(n 3), and 20:4(n 6). Panel (C) depicts the change in microbial community composition with the ratio of 7 methyl heptadecane to the sum of (C16 C22) alkanes (filled squares) decreasing with depth and the ratio of 10 m ethyl hexadecanoic acid to 16:1(n 5) (open circles) increasing down to layer 4. These changing ratios indicate a community shift from Cyanobacteria to sulfate reducing bacteria with depth. Alcohols P hytol D egradation Phytol, which is a component of chlorophyll a, the photosyntheti c pigment of plants, C yanobacteria, and algae (Bauer et al. 1993; Volkman & Maxwell, 1986) is particularly useful in the identification of phototrophic organisms and additional physiological processes occurring at depth. A common component of recent sediments (Grossi et al. 1998; Rontani et al. 1996) it has been speculated that phytol is the major source of other isoprenoids of 20 or fewer
! 35 carbon atoms in geological samples (Rontani & Volkman, 2003) N umerous isoprenoids, including hydrocarbons, fatty acids, and alcohols, fou nd among the Cuatro CiÂŽnegas microbialite lipid extracts, can be linked to the degradation of phytol and thus the cycling of photoautotrophically produced biomass. The abundance of phytol in the 1 st layer is likely a direct reflectio n of the numerous phot otrophic C yanobacteria and eukaryotic microalgae, an d the release of phytol from int act chlorophyll compounds during senescence of these organisms (Jeffrey & Hallergraeff, 1987) However, more interesting than the presence of phytol itself, is the obser vation of numerous intermediate metabolites that reflect specific degradation pathways. Sulfate reducing bacteria are able to efficiently degrade phytol (Rontani et al 1999) producing isomeric phytadienes and phytenes as metabolites (Grossi et al. 1998) Phytene was observed throughout the Cuatro CiÂŽnegas microbiali te with the highest concentrations occurring in Layer 3 This is in accordance with the dominance of sulfate reducing activity at the microbialite interior, while the presence of isoprenoid thiophenes detected in the 5 th layer further substantiates this co ncept These organic sulfur compounds are produced through the reaction of inorganic sulfur (H 2 S) with phytol (D e Graaf et al. 1992; Fukushima et al. 1992) Thus, the observation of isoprenoid thiophenes is indicative of both the dominant phototrophic community at the microbiali te surface as well as a sulfate reducing community within, which is necessary to produce sufficient amounts of H 2 S for this reaction to occur
! 36 Biomarker Summary In general the variety of biomarkers found throughout the microbialite layers support s the observation of community composition as determined by 16S analysis. Additional ly, this analysis reveals that the molecular composition of organic matter drastically changes between layer 1 and layer 5, with the majority of the photoautotrophic signa ture being degraded (Fig. 5). However, while many of the straight chain and unsaturat ed compounds are preferentially degraded (e.g. n C 17 unsaturated fatty acids, etc.) the preservation of some compounds within the layer 5 extracts, such as sulfurized derivatives of phytol and some mid chain methyl branched hydrocarbons indicates their po ssible utility as distinctive biomarkers. Organic matter sulfurization has been described as a key process within the early stages of diagenesis (Hebting et al. 2006) and one that likely leads to increased preservation of distinctive microbial biomarkers (Brocks & Banfield, 2009) Furthermore, the detection of isoprenoid thiophenes in cretaceous deposits (Sinninghe Damst et al. 1989) identifies the stability of such compounds on geologic timescales. Carbon Isotope Profiles Previous work (Breitbart et al. 2009) has discussed the isotopic signatures of the Rio Mesquites waters ( 13 C, 15 N, 34 S) and the process by which these signatures are incorporated into the microbialite matrix. In general, it was noted that the stable isotopic composition in the CCB waters is consistent with a system that is derived from the chemical weathering of ancient marine
! 37 limestone of which the region is formed Wh ile the previous analysis by Br e i tbart and colleagues allowed for interpre ting the enzymatic processes responsible for the isotopic signatures of the microbialite matrix, the layer specific examination applied here builds on that knowledge by providing a spatial context for understanding these processes. Figure 6 : Carbon Isotope Profiles O rganic (open squares) and inorganic (filled squares) carbon isotope values in the 5 layers of the microbialite.
! 38 Organic Carbon The profile of organic 13 C values (Fig. 6 ) support s the hypothesis that this system is dominated by photoautotrophic carbon fixation primarily by Cyanobacteria and eukaryotic algae The 13 C value in the 1 st layer ( 18.2) is typical of photosynthetic carbon fractionation patterns observed in both C yanobacteria (Calder & Parker, 1973; Pardue et al. 1976) and diatoms (Thompson & Calvert, 1994) when considering the 13 C value of the ambient DIC is approximately +4 (Breitbart et al. 2009) The relatively 13 C enriche d organic carbon value seen in layer 2 ( 12) is not typical of most photoautotrophically produced material, however a number of possible factors may be driving this observed trend. In hypersaline C yanobacterial mats, Wieland et al. (2008) observed a peak c oncentration of EPS at a depth of 2 4 mm, corresponding to the 2 nd layer in the CCB microbialite An abundance of EPS, which is composed of a high proportion of carbohydrates (Klock et al. 2007) that are typically enriched in 13 C relative to total cellular carbon (Deines, 1980) is a possible factor A second possibility is that this shift is caused by a change in the carbon substrate used for photosynthesis by the organisms at this position in the microbialite. Cyanobacteria which are the most abundant photoautotrophs in layer 2 are notorious for having highly variable 13 C fractionation during photosynthesis primarily constrained by CO 2 concentrations (Calder & Parker, 1973) H igh rates of photosynthesis within a dense microbial community can result in local CO 2 concentrations becoming depleted faster than they are replenished The result of this process, which was clearly shown by Staal et al.
! 39 (2007) is that the thickening of a natural microbial mat can cause a shift from CO 2 utilization towards more 13 C enriched HCO 3 (Emrich et al. 1970; Mook et al. 1974) as a substrate for photosynthesis The 13 C values obs erved in the 2 nd layer of the Cuatro CiÂŽnegas microbialite could easily be produced through the effect of high EPS production, causing both a change in the molecular composition of organic matter (increased EPS) as well as a shift in the primary carbon sub strate for photosynthesis. The steady decrease of organic matter 13 C values from 19 to 23 between layers 3 and 5 could reflect the addition of organic matter with a low 13 C content at depth however, h eterotrophic communities typically will produce a biomass with a 13 C composition that is enriched in 13 C relative to its substrate ( antR "# kovÂ‡ et al. 2000) Thus, assuming that the abundant heterotrophic bacteria at depth are utilizing the buried photoautotrophic biomass as a carbon substrate, we can conclude that t he incr ease of heterotrophic biomass does not produce this carbon isotope trend Rather, the driving force behind the observed 13 C depletion with depth (Fig. 6) is likely the continual remineralization of buried organic matter that is rich in 1 3 C, such as the carbohydrates of EPS. Microbial decomposition, by the heterotrophic community, results in the TOC pool gradually becoming more depleted in 13 C as the se enriched component are removed (Benner et al. 1987) Additionally, organic matter remineralization also affects the isotopic composition of the dissolved inorganic carbon (DIC) pool at depth
! 40 Inorganic Carbon (CaCO 3 ) While the stable isotopic composition of organic material provides insight to the nutrient cycling processes within the microbialite community, the observation of CaCO 3 13 C allows us to interpret how these organic signatures are incorporated into the inorganic carbonate matrix. The similarity in 13 C patterns between org anic and inorganic carbon from layer 1 through layer 5 (Fig. 6 ) suggest a direct link between these two car bon pools. As previously shown by Breitbart et al. (2009) the 13 C of CaCO 3 in the Cuatro CiÂŽnegas microbialites is depleted in 13 C relative to the water column DIC, indicating the incorporation of photoautotrophically derived carbon into the inorga nic matrix. Through our layer specific analyses we are able to observe that the 13 C of CaCO 3 becomes i ncreasingly depleted at depth ( Fig. 6 ). This observation highlights the process of organic matter remineralization by heterotrophic organisms, forcing a negative shift in the localized DIC 13 C with depth and the subsequent incorporation of this isotopic signature into the CaCO 3 matrix. Carbonate Accretion A primary goal of this research is to link the spatial distribution of bacteria and metabolic processes in the Cuatro CiÂŽnegas microbialites to the precipitation of CaCO 3 The mass distribution of the primary components of the microbialite matrix (Fig. 7A) provides a better understanding of how the composition changes with depth in the microbialite and how specific organisms and processes are related to those changes. T he decrease in OM with depth is indicative of
! 41 decomposition by heterotrophic bacteria. Calcium carbonate, as expected, accounts for a high proportion of the total mass, i ncreasing fro m approximately 35% in layer 1 to 90% (by weight) in layer 5 (Fig. 7A) This is important as it shows that CaCO 3 accumulate s throughout the 5 layers. Imaging the individual layers with SEM, also reveals this increase in CaCO 3 with depth (Fig. 7B), and a graphical illustration more easily depicts how the 5 th layer is composed of the accretion of individual generations of CaCO 3 Furthermore, the relative contribution of individual CaCO 3 generations to the total accumulation (lay er 5) can be calculated (Fig. 7C) using the results of the mass balance analysis. This reveals that the majority of CaCO 3 forms in two spatially distinct zones. Relative to the total accumulation of CaCO 3 the top two layers of the microbialite (layers 1 a nd 2) produce approximately 50% of the total CaCO 3 (by weight), likely a result of both in situ precipitation and accumulation through the deposition and trapping of allochthonous grains. The second zone of carbonate accretion is observed in the 4 th and 5 t h layers, where approximately 20% of the total CaCO 3 is added in each. These distinct zones of precipitation correspond to specific processes that influence precipitation, with the first zone falling within the photoautotrophically dominated portion of the mat and the second zone associated with the abundance of sulfate reducing heterotrophic organisms. Understanding the relative contribution of the individual generations of CaCO 3 precipitates is important for quantifying the incorporation of biogenic isotopic signatures into the inorganic carbonate matrix. The differences between CaCO 3 13 C values from any one layer of the microbialite to the next layer (Fig.
! 42 6) can be accounted for by the new ly precipitated generations of CaCO 3 Combining the mass balance analysis which gave an understanding of the relative mass of CaCO 3 added at each layer, with the CaCO 3 13 C data we are able determine the approximate 13 C value of the carbonate b eing added at each layer (Fig. 7D ). This reveals that the 13 C values of carbonate grains precipitated at layer 4 and 5 are extremely depleted ( 7 to 8 ) compared to the ambient DIC of +4 (Breitbart et al. 2009) The drastic depletion in CaCO 3 13 C precipitates suggests that up to 50% of the carbon in the DIC pool of these interior layers (4 and 5) is composed of remineralized photoautotrophic biomass. While the calculation s do not take into account the processes of CaCO 3 dissolution and reprecipitation, these estimations do predict a significant incorporation of biologically fractionated carbon into the inorganic matrix This isotopic signature can be preserved on geologic time scales and used in identifying a biogenic source of ancient carbonates
! 43 Figure 7 : Carbonate Accretion Model (A) Mass balance of organic matter (green) CaCO 3 (grey) and water (blue) a cross the 5 layers ( B ) A series of SEM images with an interpretational depiction of separate generations of CaCO 3 precip itated at each layer. (C ) T he mass contribution of each CaCO 3 generation relative to the total accumulation in layer 5, with t he grey boxes highlight ing the 2 primary zones of CaCO 3 precipitation. (D) The calculated 13 C of individual generations of CaCO 3
! 44 Summary An Integrated Perspective One utility of incorporating these interdisciplinary studies into a single project is that we can construct a interpretive model of how a microbialite forms (Fig. 8), while creating a better understand ing of how specific microorganisms contribute to the suite of molecular organic compounds, isotopic signatures, and the precipitation of CaCO 3 The results of this work show that the Cuatro CiÂŽnegas microbialite supports a diverse microbial community with differing composition fro m the surface to the interior T he general distribution of bacterial groups can be used to interpret the primary forces driving the accretion of CaCO 3 As determined in the 16S gene analysis, the microbial community transitions fro m one that is dominated at the surface by Cyanobacteria and other phototrophic organisms to a primarily heterotrophic community composed of abundant proteobacteria at depth (Fig. 8A). The presence of oxygenic photosynthesis in microbialites, specifically by C yanobacteria, is well documented (Burns et al. 2004; Jahnke et al. 2004; Jungblut et al. 2005) and in this study we were able to show that approximately 50% of the carbonate accumulation occurs within a zone (layers 1 and 2) that is overwhelmingly dominated by these organisms (Fig. 8 ) Additionally, in a recent study by Bosak et al. (2007) it was determined that anoxygenic photosynthesis increases carbonate precipitation. In combination, the dive rse photosynthetic
! 45 pathways occurring in the Cuatro CiÂŽnegas microbialite community undoubtedly promote the accretion of CaCO 3 Furthermore, t he degradation of photoautotrophic material by the heterotrophic community is also thought to be significant to th e formation of microbialites. This process occurs throughout the Cuatro CiÂŽnegas mi crobialites, with Bacteroidetes like organisms contributing significantly to the surface community. A naerobic heterotrophic decomposition also plays an important role in CaC O 3 precipitation at depth Specifically, s ulfate reduction is one of the physiological pathways thought to significantly contribute to the lithification of microbial mats. The prevalence of sulfate reduction in the Cuatro CiÂŽnegas microbialite community is well supported through the observation of n ot only an abundance of sulfate reducing proteobacteria (layer 4), but also the presence of sulfurized organic compounds (thiophenes) in the 5 th layer. The coupling of this process to the second zone of CaCO 3 precipitation (Fig. 8) suggests that sulfate reduction is vital to the formation of the Cuatro CiÂŽnegas microbialites In addition to facilitating CaCO 3 precipitation, the anaerobic heterotrophic organisms produce distinct 13 C depleted CaCO 3 13 C signatur es in the 4 th and 5 th layers of the microbialite (Fig. 8D) due to remineralization of organic matter Significance Compare d to the previous work by Breitbart et al (2009) which analyzed bulk material of microbialite s from Rio Mesquites, the laye r specific approach of this study confirmed many of the same results while adding a spatial context to
! 46 our understanding. Much like the metagenomic analysis (Breitbart et al. 2009) the 16S rRNA gene analysis showed a diverse bacterial population while also revealin g little overlap in the communities of individual layers Additionally, Breitbart and colleagues (2009) discovered many genes for the production and utilization of EPS while results of this project further suggest that EPS is involved in the formatio n of distinct isotopic signatures and contributes to the precipitation of CaCO 3 through heterotrophic decomposition. These complimentary studies produce a broad base of knowledge with respect to the microbialites of Cuatro CiÂŽnegas. Together they produce a detailed portrayal of the diverse aerobic and anaerobic, phototrophic and heterotrophic organisms and processes responsible for the formation of the CCB microbialites and the preservation of distinct geochemical signatures. Beyond understanding the format ion of modern freshwater microbialites this work has also provided the opportunity to consider the integrated molecular and isotopic signatures that are a result of the sum of these organisms and processes. Understanding these signatures is a key step to forming a conceptual bridge between modern and ancient microbialite communities since genomic material is rarely preserved over geologic ally relevant timescales. The selective degradation, preservation, and alteration of distinctive biomarkers throughout t he microbialite results in the lipid composition of layer 5, which can be interpreted as a molecular fingerprint of the community as a whole. Though many details about the community are removed through heterotrophic degradation, t his research demonstrates that a portion of the microbialite 's organic matrix survives the initial
! 47 stages of decomposition and has potential utility for the interpretation of ancient systems
! 48 Figure 8 : Summary Model An integrated model of the Cuatro CiÂŽnegas microbialite showing how (A) the general distribution of photoautotrophic and heterotrophic communities affect ( B) the dominant metabolic processes occurring in the Cuatro CiÂŽnegas microbialites Panel (C ) depicts the 2 primary zones of CaCO 3 precipitation that are associate with specific metabolic processes (indicated by the solid arrows) and (D) shows the gradual de pletion of 13 C in CaCO 3 generations with depth, a product of heterotrophic remineralization of organic matter (indicated by the dashed arrow)
! 49 Conclusion Many previous studies have looked at the diversity of organisms and geochemical signatures in modern microbialites, however this study was one of the first to apply genomic, molecular organic, and both organic and inorganic isotopic analyses simultaneously to examine d iscrete horizons within a n actively accreting microbialite. This unique approach demonstrates the utility of micro scale analyses when examining the complex community structure of microbial mat systems Additionally, this work confirms that the complex microbial communities and metabolic processes, which essentially control CaCO 3 precipitation, are distinct between the individual layers of the microbialite The results of this work contribute to the current understanding of microbialite formation by sho wing that the spat ial distribution of bacteria is directly tied to the distribution of CaCO 3 precipitation and results in the preservation of distinct geochemical signatures. In Cuatro CiÂŽnegas the microbialite is composed of a diverse bacterial community with dominant populations of Cyanobacteria and photoautotrophic eukaryotes, anoxygenic phototrophic bact eria, and heterotrophic sulfate reducing bacteria This bacterial composition was found to be similar to that of other carbonate forming microbial mats supporting the concept that distinct microbial assemblages are influential to the formation of microbialites. T he photoautotrophic organisms account for the majority of the surface community,
! 50 producing a significant amount of biomass that can be identifi ed through both molecular organic and isotopic ( 13 C) sign a tures This organic matrix including extracellular polymeric substances, becomes the substrate for heterotrophic decomposition at depth, supporting an abundant sulfate reducing community that effi ciently degrades the photoautotrophic biomass and produces a molecular signature of its own. Through the process of photoautotrophic production, heterotrophic decomposition, and remineralization of organic matter a distinctively biogenic signature is incor porated into the inorganic CaCO 3 matrix. The photoautotrophic and heterotrophic communities both contribute to the precipitation of CaCO 3 and as previously suggested the tight coupling of these populations is vital to the formation of modern microbialites in Cuatro CiÂŽnegas
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! 60 Appendices
! 61 Appendix A: Extra Tables Table A1: FAME Distribution Concentration of FAME compounds detected in the microbialite lipid extracts. indicates an unidentified branching position Concentration ( g g 1 TOC) Saturated Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 C 12:0 34.3 22.7 17.8 31.9 20.3 C 13:0 20.2 18.1 14.5 24.6 16.2 C 14:0 232.7 72.6 50.7 141.9 23.7 C 15:0 47.6 32.6 20.7 44.8 16.3 C 16:0 880.8 363.2 232.1 565.0 78.5 C 17:0 27.6 17.9 15.5 28.3 11.4 C 18:0 120.9 56.5 54.9 95.2 20.9 C 21:0 23.1 22.6 20.4 29.7 21.6 C 22:0 15.7 24.0 18.5 42.6 17.1 C 26:0 4.5 16.0 12.9 33.8 9.9 Unsaturated L1 L2 L3 L4 L5 C 14:1, n 3 16.5 14.7 12.3 18.4 C 16:1, n 9 9.2 C 16:1, n 9 47.4 32.2 9.9 33.9 3.3 C 16:1, n 7 322.6 91.4 41.0 106.4 4.8 C 16:1, n 5 42.4 16.8 10.2 10.5 8.8 C 18:1, n 5 226.5 121.3 5.1 105.4 10.6 C 18:1, n 9 22.1 17.0 1.1 13.4 8.5 C 18:2, n 6 115.9 50.1 11.7 33.5 8.8 C 18:2, n x 14.9 14.4 0.4 16.0 8.8 C 18:3, n 6 14.7 10.0 8.2 14.8 C 18:3, n 3 203.4 92.1 41.5 112.5 11.0 C 18:4, n 3 19.6 10.6 8.4 13.2 C 19:1 n 9 28.4 34.2 25.3 54.2 7.1 C 20:1, n 9 38.0 C 20:4, n 6 28.7 24.6 20.1 30.8 C 20:5, n 3 40.5 24.6 20.1 30.9 Branched L1 L2 L3 L4 L5 10 Me 12:0 18.3 16.8 14.1 21.8 16.3 3,7,11 Me 12:0 15.7 13.9 11.7 18.5 13.4 12 Me 13:0 25.5 17.4 14.5 22.7 15.1 13 Me 14:0 142.1 56.7 45.9 69.0 23.2 12 Me 14:0 30.9 22.9 20.7 36.7 17.0 5,9,13 Me 14:0 10.3 8.7 14.0 9.3 10 Me 15:0 39.8 14.9 12.7 17.6 5.9 Me 16:0 21.3 16.4 18.2 28.5 17.0 Me 16:0 11.2 12.7 9.3 13.8 12.3 15 Me 16:0 41.4 23.4 21.8 31.3 12.3 14 Me 16:0 16.2 12.4 13.5 21.3 10.8 3 Me 18:0 19.0 17.7 28.5 38.9 17 Me 18:0 9.6 6.6 6.2 10.5 3.7 TOTAL 3104 1461 981 1999 467
! 62 Table A2: Alcohol Distribution Concentration of alcohol compounds detected in the microbialite lipid extracts. Concentration ( g g 1 TOC) Saturated Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 C 10:0 26.8 8.3 3.1 7.5 C 12:0 5.8 3.0 C 14:0 37.6 12.9 7.0 13.9 C 15:0 4.3 3.3 5.1 16.8 2.8 C 16:0 11.5 4.4 7.6 14.7 C 17:0 4.0 4.6 2.6 9.9 C 18:0 580.7 259.0 141.3 242.2 16.9 C 19:0 99.7 3.0 1.9 C 20:0 10.6 C 22:0 8.4 6.4 5.5 4.1 C 24:0 3.1 3.0 C 26:0 5.3 6.9 Unsaturated L1 L2 L3 L4 L5 C 14:1, n 12 7.2 C 20:1, n 17 7.5 Isoprenoid L1 L2 L3 L4 L5 Phyt 2 one 6.7 4.6 5.7 12.7 1.8 Phytol 94.5 30.3 20.7 93.2 3.2 Sterols L1 L2 L3 L4 L5 cholesterol 30.8 15.9 11.1 16.3 4.1 ergostanol 11.0 stigmasterol 45.2 18.1 21.5 25.1 4.4 sitosterol 21.7 11.3 11.5 16.9 6.1 TOTAL 1454 864 378 917 119
! 63 Table A3: Hydrocarbon Distribution Concentration of hydrocarbon compounds detected in the microbialite lipid extracts. Concentration ( g g 1 TOC) Straight Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 n C 16 2.0 2.1 2.1 2.8 2.2 n C 17 22.8 3.8 19.3 19.2 2.5 n C 18 2.1 2.3 3.2 8.6 2.7 n C 19 2.3 2.6 3.9 9.9 8.2 n C 20 2.3 2.5 3.0 5.8 7.4 n C 21 2.5 2.7 2.9 3.6 3.0 n C 22 2.7 2.7 2.8 3.6 2.9 n C 23 3.4 3.2 3.3 4.0 3.6 n C 24 3.4 3.1 3.1 3.7 3.2 n C 25 4.3 3.6 4.3 4.4 4.4 n C 26 4.0 3.5 3.4 4.1 3.5 n C 27 4.7 4.1 5.0 5.0 5.1 n C 28 4.5 3.7 3.9 4.6 3.8 n C 29 5.1 4.4 6.7 5.8 5.4 n C 30 4.6 3.9 4.5 5.1 3.9 n C 31 5.1 4.6 8.5 6.9 6.3 n C 32 4.4 4.0 3.9 4.8 3.7 n C 33 4.2 4.4 6.4 6.3 5.2 Unsaturated L1 L2 L3 L4 L5 n C 17:1 2.9 2.7 7.1 n C 19:1 8.1 5.0 20.6 37.2 3.7 Branched L1 L2 L3 L4 L5 7 Me 17 9.3 2.7 3.6 4.5 2.1 4 Me 17 3.9 2.1 2.8 3 Me 17 3.3 2.5 2.2 3.1 2.1 7 Me 18 2.2 2.8 2.0 2.8 6 Me 18 2.2 4 Me 18 4.6 2.9 2 Me 18 2.4 2.6 2.0 3.0 3 Me 18 2.4 3.1 2.4 4.2 2.1 3,4 Me 17 2.1 2.4 3.1 2,3 Me 17 2.0 2.2 5 Me 19 2.1 2.5 2.4 7.4 2.7 Isoprenoid L1 L2 L3 L4 L5 Phyt 2 ene 9.5 3.4 27.9 12.9 Thiophene A 2.7 Thiophene B 2.7 Hopanoids L1 L2 L3 L4 L5 Diploptene 7.4 8.9 17.8 12.0 4.5 TOTAL 175 120 195 245 105
! 64 Table A4: Archaeal 16S rD NA Clone Identification Phylogenetic distribution of Archaeal clones based on top BLAST hits. Table A5: Eukaryotic 18S rD NA Clone Identification Phylogenetic distribution of eukaryote clones based on top BLAST hits.
! 65 Table A6: Bacterial 16S rD NA Clone Diversity Results Expected ribotyp e abundance and Shannon Wiener d iversity calculate d by the FastGroupII application. Chao 1 (ribotypes) Shannon Wiener (nats) Layer 1 180 3.71 Layer 2 199 3.54 Layer 3 645 4.10 Layer 4 236 3.86 Layer 5 310 4.12 Total Community 1035 5.33
! 66 Appendix B: Extra Figures Figure B1: Organic 15 N data Isotopic composition of nitrogen in organic material from each layer. Data collected in the same analysis as organic carbon isotopic composition.
! 67 F igure B2: Percent Sequence Ident ity (Top Blast Hit) The percent identity distribution of bacterial, archaeal, and eukaryotic clones compared to the most similar sequences in the GenBank database. Values of 97% indicate they are f rom the same species, 92 96% indicates they are from a single genus, and values lower than 92% indicate novel organisms.
! 68 Figure B3: Bacterial 16S rDNA Diversity Results (Layer 1) The rank abundance and rarefaction curves showing the relative ribotype abundance and richness as calculated by FastGroupII.
! 69 Figure B4: Bacterial 16S rD NA Diversity Results (Layer 2) The rank abundance and rarefaction curves showing the relative ribotype abundance and richness, as calculated by FastGroupII.
! 70 Figure B5: Bacterial 16S rD NA Diversity Results (Layer 3) The rank abundance and rarefaction curves showing the relative ribotype abundance and richness, as calculated by FastGroupII.
! 71 Figure B6: Bacteri al 16S rD NA Diversity Results (Layer 4) The rank abundance and rarefaction curves showing the relative ribotype abundance and richness, as calculated by FastGroupII.
! 72 Figure B7: Bacterial 16S rD NA Diversity Results (Layer 5) The rank abundanc e and rarefaction curves showing the relative ribotype abundance and richness, as calculated by FastGroupII.
! 73 Figure B8: Bacterial 16S rD NA Diversity Results (Total Community) The rank abundance and rarefaction curves showing the relative ribotype abundance and richness, as calculated by FastGroupII.