Microbial communities performing anaerobic oxidation of methane: diversity of lipid signatures and habitats

(1)

Microbial communities performing

anaerobic oxidation of methane:

diversity of lipid signatures and habitats

Dissertation

zur Erlangung des Doktorgrades

der Naturwissenschaften

- Dr. rer. Nat. -

Am Fachbereich Geowissenschaften

der Universität Bremen

vorgelegt von

Pamela E. Rossel Cartes

Bremen

Februar 2009

(2)

1. Gutachter: Prof. Dr. Kai-Uwe Hinrichs, University of Bremen, Germany

2. Gutachter: Prof. Dr. Antje Boetius, Max Planck Institute for Marine Microbiology, Bremen, Germany

(3)

No viniste de lejos, ni siquiera has llegado. Estabas desde siempre, como un lenguaje escrito en el fondo de mí…

(4)

(5)

THESIS ABSTRACT

The main aim of this thesis was to study different microbial communities involved in the process of anaerobic oxidation of methane (AOM) using lipid analysis. During this work a variety of globally distributed methane-bearing systems characterized by different environmental factors and anaerobic methanotrophic consortia were analyzed for intact polar lipid (IPL) and apolar lipid composition. Moreover, an experiment was designed in order to evaluate the stability of archaeal and bacterial IPLs in marine sediments.

The three phylogenetically distinct clusters of Euryarchaeota called ANME-1, -2 and -3, which have been observed in association with sulfate-reducing bacteria of the Desulfosarcina/Desulfococcus group (‘‘ANME-1/DSS and -2/DSS aggregates”) or Desulfobulbus spp (‘‘ANME-3/DBB aggregates”) could be clearly distinguished by IPL composition but not by apolar lipids. ANME-1/DSS was characterized by glyceroldialkylglyceroltetraethers (GDGTs) with glycosidic, phospho, as well as mixed of both , whereas diagnostic IPLs of ANME-2/DSS were archaeols with both glycosidic and phospho headgroups. Distinctly, ANME-3/DBB contained neither glycosidic-archaeols nor GDGT-based IPLs, but the phospho-archaeol composition was very similar to ANME-2/DSS. The main and distinguishing feature of ANME-3/DBB was the high contribution of the bacterial IPLs phosphatidyl-(N)-methylethanolamine (PME) and phosphatidyl-(N,N)-dimethylethanolamine (PDME). Other bacterial IPLs that were mainly found in ANME-2/DSS-dominated carbonate mats were IPLs with non-phospho headgroups such as ornithine lipids, surfactins and betaine lipids, the latter with odd fatty acid chains. In contrast, IPLs with phospho headgroups were generally more abundant in sediment environments. The high contribution of glycosidic archaeal IPLs and the presence of bacterial IPLs with non-phospho headgroups in carbonate mats can be explained by adsorption of phosphate onto calcium carbonate.

In addition to the general differences in IPL composition of each of three AOM-community types, the IPL distribution was also associated with several environmental factors, allowing the characterization of their different habitats. ANME-1/DSS dominates

(8)

habitats with high temperature and low oxygen content in bottom waters. For ANME-2/DSS systems, it was possible to differentiate between carbonate reef habitats and sediment settings, with the former characterized by low temperature, high oxygen content in bottom waters and high methane and sulfate concentrations, whereas the latter was associated with higher sulfate reduction rates. ANME-3/DBB presented similar environmental characteristics to ANME-2/DSS.

Furthermore, degradation of archaeal and bacterial IPLs was evaluated in marine sediments, showing a loss of 80% for the archaeal and ~50% for the bacterial IPL at 5°C after 465 days of incubation under sterile conditions. However, in non-sterile conditions at 5°C, an increase in concentration of both IPLs at the end of the experiment was observed. Therefore, biotic degradation of IPLs could not be proved because the pools of produced and degraded IPLs in the non-sterile conditions were indistinguishable.

The results obtained during this thesis support the distinction of microbial communities performing AOM based on IPL diversity and address the role of environmental factors in the distribution of three major AOM-community types. This work contributes substantially to the understanding of the distribution of AOM systems on a global scale.

(9)

KURZFASSUNG

Der Schwerpunkt dieser Doktorarbeit liegt auf der Untersuchung von unterschiedlichen Mikrobengemeinschaften, die an der anaeroben Oxidation von Methan (AOM) beteiligt sind mit Hilfe von Lipidanalysen. Die Zusammensetzung von apolaren und intakten polaren Lipiden (IPLs) wurde an einer breitgefächerten Auswahl von methangeladenen Systemen analysiert, die durch verschiedene Umweltfaktoren und anaerobische methanotrophische Konsortien charakterisiert sind. Außerdem wurde ein Experiment konzipiert, um die Stabilität von bakteriellen und von Archaeen stammenden IPLs in marinen Sedimenten zu untersuchen.

Die drei phylogenetisch unterschiedlichen Cluster von Euryarchaeen namens ANME-1, -2 und -3, die oft zusammen mit sulfatreduzierenden Bakterien der Gruppe Desulfosarcina/Desulfococcus (‘‘ANME-1/DSS und -2/DSS Aggregate”) oder Desulfobulbus spp (‘‘ANME-3/DBB Aggregate”) beobachtet worden sind, konnten eindeutig anhand der Zusammensetzung ihrer IPLs unterschieden werden, aber nicht durch ihre apolaren Lipide. Charakteristisch für ANME-1/DSS sind Glyceroldialkylglyceroltetraether (GDGT) mit sowohl glykosidischen, phospho und gemischten Kopfgruppen, wohingegen diagnostische IPLs für ANME-2/DSS Archaeole mit sowohl glycosidischen als auch phospho Kopfgruppen waren. Im Gegensatz dazu zeigten ANME-3/DBB weder glykosidische Archaeole noch GDGT-basierte IPLs, aber dafür eine zu ANME-2/DSS sehr ähnliche Zusammensetzung der Phosphoarchaeole. Der größte Unterschied von ANME-3/DBB waren die bakteriellen IPLs phosphatidyl-(N)-methylethanolamine (PME) und phosphatidyl-(N,N)-diphosphatidyl-(N)-methylethanolamine (PDME). Andere bakterielle IPLs, die hauptsächlich in ANME-2/DSS dominierten Karbonatmatten gefunden wurden waren IPLs ohne phosphatbasierende Kopfgruppe wie Ornithinlipide, Surfactin und Betainlipide, letztere mit ungeraden Fettsäureketten. Im Gegensatz dazu hatten Lipide mit phosphatbasierenden Kopfgruppen einen höheren Anteil in sedimentären Umgebungen. Der hohe Anteil von glykosidischen Archaeenlipiden und bakteriellen IPLs ohne phosphatbasierende Kopfgruppen in Karbonatmatten kann durch die Adsorption von Phosphat an Kalziumcarbonat erklärt werden.

(10)

Zusätzlich zu den allgemeinen Unterschieden der IPL Zusammensetzung der drei AOM-Gemeinschaften, war die Verteilung der IPLs auch mit verschiedenen Umweltfaktoren verknüpft, was die Charakterisierung deren unterschiedlichen Lebensräume ermöglicht. ANME-1/DSS dominiert Umgebungen mit hoher Temperatur und niedrigem Sauerstoffgehalt im Bodenwasser. Für ANME-2/DSS Systeme war es möglich zwischen Karbonatriffen und Sedimenten zu unterscheiden, wobei Erstere durch niedrige Temperaturen, hohen Sauerstoffgehalt im Bodenwasser und hohe Methan- und Sulfatkonzentrationen charakterisiert sind, während Letztere mit hohen Sulfatreduktionraten verbunden waren. ANME-3/DBB zeigte ähnliche Umweltcharakteristika wie ANME-2/DSS.

Zusätzlich wurde die Degradation von bakteriellen und von Archaeen stammenden IPLs in marinen Sedimenten untersucht. Nach Inkubation für 465 Tage unter sterilen Bedingungen bei 5°C wurde ein Abbau von 80% des Archaeen- und ~50% des Bakterienlipids beobachtet. Unter nicht sterilen Bedingungen bei 5°C hingegen wurde ein Anstieg der Konzentration von beiden IPLs am Ende des Experiments festgestellt. Deshalb konnte der biologische Abbau von IPLs nicht belegt werden, da die Pools von produzierten und abgebauten IPLs unter nicht-sterilen Bedingungen ununterscheidbar waren.

Die Ergebnisse dieser Doktorarbeit zeigen, dass es möglich ist die verschiedenen Mikrobengemeinschaften die an AOM beteiligt sind anhand ihrer IPL Zusammensetzung zu unterscheiden und deuten auf die Rolle von Umweltfaktoren bei der Verteilung der drei Typen von AOM Gemeinschaften hin. Diese Studie trägt wesentlich zum Verständnis der Verteilung von AOM Systemen im globalen Maßstab bei.

(11)

ACKNOWLEDGEMENTS

I started my scientific career as a marine biologist, followed by a master in oceanography, period during which I acquired the first knowledge about organic geochemistry. This small background was widely extended during the realization of my PhD under the supervision of Prof. Kai-Uwe Hinrichs, who gave me the opportunity to join his working group. Thanks Kai for providing me support and inspiration during these over three and half years. I would also like to thank the co-supervision of Marcus Elvert, who contributed to my knowledge in GC and GC-MS and for the interesting and helpful discussions. I am also grateful to Julius Lipp and Helen Fredricks for guiding my first steps with HPLC-MS and in the analysis of IPLs. I would also like to thank the thesis committee members for their review of my dissertation.

Additionally, I would like to thank all the colleges from the MPI in Bremen involved in the MUMM project especially Antje Boetius, Tina Treude, Katrin Knittel, Julia Arnds, Helge Niemann, Gunter Wegener, Janine Felden and Thomas Holler, for supplying samples and for the useful discussions. I am also indebted to Julia Arnds, Katrin Knittel, Antje Boetius and Alban Ramette for contributing in great part to the work included in this thesis. Moreover, I would like to thank my friend Beth! Orcutt for providing me samples from the Gulf of Mexico, together with some unpublished data from this setting. Thanks also to Helge Niemann, Tina Treude and Janine Felden for providing me some unpublished data. Thanks also to Florence Schubotz who helped me with her expertise in bacterial IPLs and also for sharing unpublished data from the Black Sea.

Thanks to Birgit Schmincke for being always so helpful with the administrative paper work.

A special thank to all my colleges and friends from the Organic Geochemistry and Geobiology groups in Bremen for providing a nice and pleasant working atmosphere. Thanks for the interesting collaboration work with our lab guests John Pohlman and Maria Pachiadaki. Thanks to Marcus and Xavi for technical support in the lab. I would like to thanks also my friends Marcos Yoshinaga, Julius Lipp and Julio Sepulveda for reading and reviewing part of my work.

(12)

Thanks to Julio to be my brother all these years, to share so many histories and experiences that I will never forget (gracias peladito espero que nuestros caminos se junten nuevamente). Thanks also to Annette and Amaya; you have been my family in Bremen, thanks for always being there in the good and bad moments, I will miss all of you very much.

Thanks to my German teacher and good friend Ursula, who made me enjoy so much the two hours of German lessons every Friday. I am very glad that I decided to stay in Bremen, so I will be able to continue with that.

Thanks to my family in Barcelona, Montserrat, Julià and Jordi, for receiving me as my own family, for taking care of me and giving me support during this PhD.

Thanks to my friends from South America, which despite the distance are always so close to me: Lilian Nuñez, Andrea Elgueta, Jaime Letelier, Klaudia Hernandez, Pamela Vaccari, Carlos Tapia and Marcelo Ayala. Thanks to my friends in Bremen for giving me many great moments and to make me feel at home: Claudia & Sven, Petra, Luisa, Elvan & Jerome, Cécile & Rick, Flo & Julius, Mathias & Susanne, Barbara & Marius, Xavier & Gulnaz, Catalina, Ilham and Jeroen. To my former advisors and friends Silvio Pantoja and Carina Lange, thanks for being always there.

A word of thanks to my family in Chile, Margarita, Gabriel, Soledad, Camila, Aylin and Gabriel son, thanks for believe in me and give me your support during these years. Especially to you mother for being a great friend and inspiring woman so strong and perseverant, despite all the things you have being through, without you I wouldn’t be this person.

Finalmente a Xavi, gracias por quererme tanto y por ser tan paciente en especial este ultimo año. Gracias por tu compañía y atenciones. Por tu risa, tus miradas y caricias. Espero seguir siendo tu compañera de viaje siempre en el polvo del tiempo. Este trabajo te lo dedico a ti.

(13)

LIST OF FIGURES

Figure I.1. Three-dimensional structure of the methane molecule………..2

Figure I.2. Gas hydrate stability zone in the marine environment...………3

Figure I.3. Model of methane hydrate structure…...……...………3

Figure I.4. Methane, temperature and past climate changes…...……….………....4

Figure I.5. Sources of atmospheric methane……….……...5

Figure I.6. Classification of natural methane sources………...…………...6

Figure I.7. Redox sequence in marine sediments………….………...7

Figure I.8. Phylogeny of archaea……….………....8

Figures I.9. Enzymatic pathway of CO2 reduction……….………...9

Figure I.10. Production and consumption of methane in marine sediments...10

Figure I.11. Phylogenetic tree of Euryarchaeota including anaerobic methanotrophic archaea (ANME)………...……12

Figure I.12. Methane-dependent sulfate reduction in ANME-1 and ANME-2 in response to temperature variability...13

Figure I.13. Community distribution in relation to fluid flow……….….………...14

Figure I.14. Global distribution of ANMEs based on phylogenetic data..………..15

Figure I.15. Apolar lipids derived from ANME-1 and ANME-2...20

Figure I.16. Phospholipid membrane bilayer.………….…………....………22

Figure I.17. General features of archaeal and bacterial membranes…………...23

Figure I.18. HPLC-MS chromatogram from an IPL mixture………...…………...25

Figure I.19. Diversity of IPLs..………..……...………...26

Figure I.20. Characteristic mass spectra of PE in positive and negative ion modes………..………27

Figure II.1. Composite mass chromatograms of samples dominated by different ANME communities……….…51

Figure II.2. Distribution of IPLs in AOM communities……….54

Figure II.3. Structure of IPLs………..………61

Figure III.1. Grouping of samples according to the dominance of GDGT- and AR-based IPLs……….78

(14)

Figure III.2. Principal Component Analysis showing the distribution

of IPLs among the analyzed samples………...………81

Figure III.3. Redundancy Analysis in function of environmental data………89

Figure III.4. Location of the samples included in the global survey………..106

Figure III.5. Principal Component Analysis showing the distribution of bacterial IPLs………...…..………107

Figure III.6. Principal Component Analysis showing the distribution of apolar lipids among the samples………108

Figure IV.1. Experimental design of the degradation study………...115

Figure IV.2. Degradation of archaeal and bacterial IPLs at 5°C and 40°C in sterile sediments………….……….………...117

Figure IV.3. Degradation of archaeal and bacterial IPLs at 5°C and 40°C in active sediments……….………...119

Figure IV.24 Variability of GDGT cores in sediments incubated at 5°C in active sediments …………..………..….………...120

Figure V.1. MS2 positive ion spectra of glycosidic archaeols...………...130

Figure V.2. MS2 positive ion spectra of glycosidic GDGTs...………...132

Figure V.3. MS2 positive ion spectra of phospholipid archaeols…………....….134

Figure V.4. MS2 positive ion spectra of phospholipid GDGTs…...……….135

Figure V.5. MS2 positive ion spectra of the phospholipids PE and its methyl derivates...………..136

Figure V.6. MS2 positive ion spectra of ornithine lipids………...….137

Figure V.7. MS2 positive ion spectra of betaine lipids………....….138

Figure V.8. MS2 positive ion spectra of surfactins…...………...….139

(15)

LIST OF TABLES

Table I.1. General guidelines to distinguish phospholipids……….27

Table II.1. Overview of analyzed samples and IPLs……….50

Table III.1. Overview of analyzed samples, with sample location and AOM-phylotypes………..….68

Table III.2. Environmental data selected for redundancy analysis……….72

Table III.3. Lipid code and source assignment of detected IPLs………75

Table III.4. Relative abundance of IPLs in percentage……….………....109

Table III.5. Concentration of apolar lipids……….………...110

Table IV.1. Frequency of analysis in experiments performed to test IPLs stability……….………...116

(16)

LIST OF ABBREVIATIONS

16S Rrna Small ribosomal ribonucleic acid unit with a sedimentary unit of 16

ANME Anaerobic methanotrophic archaea

AOM Anaerobic oxidation of methane

APCI Atmospheric pressure chemical ionization

APT Phosphoaminopentatetrol AR Archaeol AS Arabian Sea Beg Beggiatoa BL Betaine lipids BS Black Sea Calyp Calyptogena

CARD-FISH Catalyzed reporter deposition fluorescent in situ hybridization

CH4 Methane concentration

Da Dalton

DAG Diacylglycerol

DAGEs sn-1,2-di-O-alkyl glycerol ethers

DCM Dichloromethane DEG Dietherglycerol

DNA Desoxyribonucleic acid

EMS Eastern Mediterranean Sea

ER Eel River Basin

ESI Electrospray ionization

FA Fatty acid

FAME Fatty acid methyl esters

FISH Fluorescent in situ hybridization

GB Guaymas Basin

GC-MS Gas chromatography-mass spectrometry

GDGT Glyceroldialkylglyceroltetraether

(17)

Gly Glycosyl

GOM Gulf of Mexico

HMMV Håkon Mosby Mud Volcano

HPLC-MS High performance liquid chromatography mass spectrometry

HR Hydrate Ridge

IPL Intact polar membrane lipid

m/z mass to charge ratio

MAGE sn-1, mono-O-alkyl glycerol ether

MAPT Phosphomethylaminopentatrol

MAR Macrocyclic archaeol

MeOH Methanol

MS1 Primary order mass spectrometry stage

MS2 Secondary order daughter ion mass spectra

MSn Higher order daughter ion mass spectra

MUMM Methane in the Geo/Bio-System-turnover, metabolism and microbes

O2 Oxygen concentration in bottom waters

OH-AR Hydroxyarchaeol

OL Ornithine lipids

OM Organic matter

PAF Platelet activation factor (1-O-hexadecyl-2-acetoyl-sn-glycero-3- -phosphatidylcholine)

PC Phosphatidylcholine

PCA Principal component analysis

PDME Phosphatidyl-(N,N)-dimethylethanolamine PE Phosphatidylethanolamine PG Phosphatidylglycerol PI Phosphatidylinositol PME Phosphatidyl-(N)-methylethanolamine PMI 2,6,15,19-pentamethylicosane PS Phosphatidylserine

(18)

rDNA Ribosomal ribonucleic acid

SMTZ Sulfate methane transition zone

SO42- Sulfate concentration

SOB Sulfide oxidizing bacteria

SR Sulfate reduction

SRB Sulfate reducing bacteria

SRR Sulfate reduction rate

Thio Thioploca TLE Total lipid extract

TOC Total organic carbon

TOF-SIMS Time of flight mass spectrometry

(19)

CHAPTER I

(20)

GENERAL INTRODUCTION

The first chapter provides an overview about the significance of methane in the global carbon cycle and a description of different processes during methane production and consumption. Furthermore, this section will give an introduction to the role of the oceans and the microorganism inhabiting marine sediments in the global methane budget. A dominant part is dedicated to the identification of diverse microbial communities involved in the anaerobic oxidation of methane (AOM) from widely distributed hydrocarbon rich sediments. Finally, the last part of this section includes the main objectives of this work.

I.1. Properties and importance of methane

Fig I.1. Three-dimensional tetrahedron

of the methane molecule.

Methane is the simplest organic molecule and the most reduced form of carbon. Methane represents the main component of natural gas, although this can occur with other hydrocarbons such as ethane, propane and butane. Methane has a molecular weight of 16.04 and consists of a central carbon atom covalently bonded to four hydrogen atoms (tetrahedron, Fig. I.1).

Methane solubility in water is rather low (~2,5 mM at 0°C and 1 atm of pressure) and it is negatively affected by temperature (Duan et al., 1992) and salinity (Yamamoto et al., 1976). Contrary to salinity and temperature, pressure has a positive effect on methane solubility according to Henry’s law. However, in the marine environment, the combination of low temperature and high pressure conditions enables the mixture of

(21)

methane and water molecules resulting in hydrate formation (Fig. I.2), which is a crystalline, ice-like structure known as methane clathrate (Fig. I.3). Three different methane clathrate structures have been described (I, II and H) and among these, structure I is based on pure methane, while the other ones also include ethane, propane or butane (Buffett, 2000). The stability of methane hydrates is also affected by the inclusion of various ions and additional gases such as hydrogen sulfide or carbon dioxide (Fig. I.2).

Fig. I.2. Gas hydrate stability zone in the marine

environment in relation to pressure and temperature (after Kvenvolden, 1998).

Fig. I.3. Model of methane hydrate structure I.

Gas and water molecules are displayed in green and blue, respectively (Rehder and, Suess, 2004).

Methane is an important greenhouse gas due to its ability to absorb and re-emit radiation, trapping the heat 25 times more efficiently than carbon dioxide (Lelieveld et al., 1998). Thus, several studies focused on the relation between methane inventory, i.e. fluctuations in atmospheric methane concentration, and temperature during glacial-interglacial cycles (Petit et al 1999, Wuebbles and Hayhoe 2002, Kasting, 2004). These studies provided strong evidence for the positive correlation of the greenhouse gas content in the atmosphere (CO2 and CH4) and the temperature record of Antarctica during

(22)

Fig. I.4. Variations of methane, CO2 and temperature recorded in the

Vostok ice core (Petit, 1999).

Past global warming events have been related to an increase in the emissions of methane gas to the atmosphere. Among the responsible sources for these releases, methane hydrate dissociation has been discussed. Dickens (2004) suggests that the depleted 13C values from several sediment cores from north and central Atlantic Ocean during the warming period of the initial Eocene maximum (IETM), at about 55 million years ago, can be explained by a methane release from gas hydrate source. Similarly, Kennett et al. (2002), based on the light 13C values of benthic and planktonic foraminifera recorded in a core from the Santa Barbara basin, proposed that the end of the last glacial maximum was caused by a big methane release due to a destabilization of gas hydrates, idea which is know as the clathrate gun hypothesis.

I.2. Production and consumption of methane

According to the Intergovernmental Panel on Climate Change (IPCC), methane concentration in the atmosphere has increased by ~150% since pre-industrial times (IPCC, 2001). Several sources have been identified which contribute to the release of methane to the atmosphere (Fig. I.5, Reeburgh, 2007). Among these, human-related sources such as rice cultivation contribute with 20%, production of coal with 7%, and

(23)

ruminant animals with 16%. Additionally, incomplete combustion of organic matter and degradation of organic carbon in landfills contribute with 11% and 8%, respectively.

Fig. I.5. Sources of atmospheric methane in Tg

(1012g) and relative contribution presented in percentages (in parentheses) of the total (Reeburgh, 2007).

Natural sources of methane include wetlands, termites, oceanic and geological sources. Wetlands contribute with 23%, while termites contribute only with 4% (based on cellulose utilization by methanogens living in their guts). Ocean and freshwater contributes with 2%, while geological sources, like hydrates and gas production (including seeps) contribute with 1% and 8% to the atmosphere methane budget, respectively. However, the real contribution of hydrates is still not very well constrained.

Several of the identified sources of methane release are not affected by microbial consumption such as animal production, biomass burning, coal production and venting or methane flaring. Contrary to these sources, the oceans play an effective role in controlling methane emissions to the atmosphere with only 2% of contribution in the methane global budget, although they cover 70% of the Earth surface (Reeburgh, 2007).

The use of stable isotopes to distinguish natural methane sources is a very common approach. The isotopic value of methane in nature can be affected by the contribution of the different isotopomers (12C, 13C and 1H, 2H). During the utilization of carbon by living organisms a discrimination against the heavier isotope (13C) results in products enriched in 12C (lower or more negative 13C value, Eq. 1). However, different metabolic pathways can discriminate differently against 13C. The 13C value is expressed as per mil (‰) deviation from VPDB (Vienna Pee Dee Belemnite standard) according to equation 1.

(24)

3 12 13 12 13 13 10 1 Standard / Sample / » ¼ º « ¬ ª C C C C C G Eq. 1

Fig. I.6. Bernard-diagram used for the classification

of natural methane sources (Whiticar, 1999).

Sources of methane can be classified as thermogenic or biogenic/bacterial (Fig. I.6, Whiticar, 1999 and references therein). Thermogenic methane is formed during thermocatalytic degradation of kerogen at temperatures above ~120°C (Tissot and Welte, 1984) and it is generally more enriched in 13C (13C > -50‰) than the methane from biogenic sources (13C < -50‰; Whiticar, 1999).

Methane derived from bacterial sources is restricted to lower temperatures (< 60°C, Ziebis and Haese, 2005) and shows carbon isotopic compositions which are dependent on the environment (freshwater and marine or saline sediments). Bacterial methane from marine environments is generally more depleted in 13C compared to freshwater ecosystems, resulting from the dominance of CO2-reduction as opposed to acetoclastic

methanogenesis. Furthermore, the relation between 13C values and the occurrence of longer chain hydrocarbons relative to methane expressed by the ratio C1/(C2+C3) also provides information about the methane source, with values of less than 50 and more than 100 for thermogenic and microbial origin, respectively (Whiticar, 1999).

During the microbial degradation of organic matter in sediments, macromolecular organic compounds are broken down into smaller molecules in a sequence of redox reactions (Fig. I.7, Jørgensen, 2001). This redox sequence ends with the generation of methane by methanogenic archaea, which either use carbon dioxide or other low molecular weight compounds (formate, acetate, methanol and methylated amines) as substrates under anaerobic conditions. Among the metabolic pathways used to produce methane (Eq. 2a-e), the production of methane by CO2 reduction (Eq. 2a) and acetoclastic

(25)

Fig. I.7. Redox sequence during the degradation of organic matter in marine sediments (Jørgensen, 2001). Methanogenic reactions: CO2 reduction: O H CH H CO₂ 4 ₂ o ₄2 ₂ , G0= -135.6 Eq.2a Methanol reduction: O H CH H OH CH₃ ₂ o ₄ ₂ , G0= -112.5 Eq.2b Disproportionation of formate: O H CO CH H HCOO 4 ₄ 3 ₂ 2 ₂ 4 o , G0= -130.1 Eq.2c Acetoclastic methanogenesis: 2 4 3COO H CH CO CH o , G0= -31.0 Eq.2d Disproportionation of methylamines: _o 4 2 4 2 3 3 2 3 4 4CH NH H O CH CO NH , G0= -75.0 Eq.2e

Methanogens are strictly anaerobic microorganisms, due to instability of the hydrogenase enzyme complex F420 in the presence of oxygen, nitrate and nitrite

(Schönheit et al., 1981). This coenzyme works as electron donor during the reduction of different one-carbon intermediates involved in CO and methanol reduction (Hedderich

(26)

and Whitman, 2006). Methanogens are represented by five orders of the Euryarchaeota: Methanobacteriales, Methanococcales, Methanomicrobiales, Methanosarcinales and Methanopyrus (Fig. I.8). Among these groups, different metabolic pathways have been described. The utilization of CO2, formate or methanol (Methanobacteriacea), CO2 or

formate (Methanococcacea), CO2, formate or alcohols (Methanomicrobiacea), as

substrate has been observed (Blotevogel and Fisher, 1985; Jones et al., 1987; Hedderich and Whitman., 2006). Additionally, Methanosarcinales can also disproportionate methanol, use acetate, methylamines and other methylated compounds to produce methane (Eq.2b, d and e) (Ferguson and Mah, 1983; Jones et al., 1987; Hedderich and Whitman., 2006).

Fig. I.8. Phylogeny of archaea. Euryarchaeotal methanogens are displayed in red

(27)

Fig. I.9. Enzymatic pathway of CO2 reduction

(Hedderich and Whitman, 2006). Abbreviations: MFR, methanofuran; H4MPT, tetrahydromethanopterin,

S-CoM, coenzyme M and B, CoM-S-S-CoB; reduced coenzyme F420H2

During methanogenic reactions a complex series of enzymes are involved (e.g., CO2

reduction, Fig. I.9). However, besides the different carbon sources used during methanogenesis, all methanogens share the same final step in which the methyl-coenzyme M reductase (mcr) catalyzes the reaction between the methyl-coenzyme M and the methyl-coenzyme B promoting the reduction of the methyl group into methane.

Methane oxidation in the troposphere and stratosphere is caused by the production of hydroxyl radicals during UV degradation of ozone (Lelieveld et al., 1998). In the biosphere, methane consumption is microbially-mediated under both aerobic and anaerobic conditions (Eq. 3a and b), thus reducing the escape of methane to the atmosphere. 1 0 2 2 2 4 2 2 , 842 ' o O CO H O G kJmol CH Eq. 3a 1 0 2 3 2 4 4 , 25 _o _' SO HCO HS H O G kJmol CH Eq. 3b

Aerobic methanotrophy is performed by bacteria utilizing the methane monooxygenase enzyme. Aerobic methanotrophs are members of the , and subdivision of the Proteobacteria (Hanson and Hanson, 1996). These bacteria are ubiquitously occurring in soils, sediments, water and also as endosymbionts of mussels. Based on different metabolic pathways used during the oxidation of methane and assimilation of formaldehyde, aerobic methanotrophs are classified as type I, II or X (Hanson and Hanson, 1996). Type I methanotrophs use the ribulose monophosphate (RuMP) pathway, whereas type II methanotrophs use the serine pathway. Methanotrophs

(28)

of the type X can use both pathways. The utilization of other carbon sources besides methane, such as chlorinated hydrocarbons, has also been observed in methanotrophs. The utilization of chlorinated hydrocarbons by this group of bacteria makes these microbes commercially interesting (e.g., Hanson and Hanson, 1996).

The recognition of anaerobic oxidation of methane (AOM) was reported for the first time in the mid 70’s in anoxic marine sediments (Martens and Berner, 1974; Barnes and Goldberg, 1976; Reeburgh, 1976). For a long time, oxidation of methane was assumed to take place only under oxic conditions. However, due to the rapid utilization of oxygen during the organic matter degradation, aerobic oxidation of methane is very limited in marine sediments.

The diffusion of methane from deep sediments and its disappearance before reaching the oxygen layer pointed to the utilization of methane in the presence of another electron acceptor.

Fig. I.10. Scheme showing production and consumption of

methane in marine sediments (figure obtained from ifm-geomar.de after Whiticar, 1999 and DeLong, 2000).

Barnes and Goldberg (1976) proposed sulfate as most possible electron acceptor in this process due to the simultaneous consumption of both methane and sulfate in the sulfate methane transition zone (SMTZ) of marine sediments (Fig. I. 10). The utilization of sulfate as electron acceptor during AOM was later confirmed by the detection of radioactively labeled products (i.e., sulfide and CO2) formed during

turnover of artificially labeled substrates (i.e., 14CH4 and 35SO42-)

in sediments from the SMTZ (Devol, 1983; Iversen and Jørgensen, 1985).

The process of AOM, contrary to aerobic methanotrophy, results in increased alkalinity (Eq. 3b, Barnes and Goldberg 1976), which favors the precipitation of

(29)

carbonate. The precipitates formed during AOM are mainly aragonites and Mg-rich calcites, which can vary in shape and size ranging from small crystals (Aloisi et al., 2000) to carbonate chimneys (Michaelis et al., 2002) and are preserved in time back to the Carboniferous (~300 My; Birgel et al., 2008).

O H HS CaCO Ca SO CH 3 2 2 2 4 4 o Eq. 4

After the first reports of AOM three decades ago, subsequent investigations have provided detailed evidence of Archaea and Bacteria involved in AOM. Based on field and laboratory studies, Hoehler et al. (1994) proposed for the first time the presence of a consortium of methanogenic archaea and sulfate reducing bacteria (SRB) in sediments of Cape Lookout Bight, North Carolina. These authors suggested that AOM is thermodynamically favorable at hydrogen concentrations below 0.3 nM. Because the energy yield produced during AOM is approximately half of the energy necessary to produce an ATP molecule (Eq. 3b), the growth rates of methanotrophic communities in natural environments has been of controversial debate. However, the discovery of large amounts of AOM biomass from different methane-rich environments has provided indisputable evidence for the feasibility of this process (Boetius et al., 2000; Michaelis et al., 2002).

I.3. Microbial communities performing AOM

During the last ten years subsequent studies have reported different microbial groups responsible for AOM in marine sediments. Because ANaerobic MEthanotrophs (ANME) have not been successfully isolated so far, information has been dominantly obtained from cultivation-independent techniques. Among these, the analysis of 16S rRNA and lipid biomarkers have been mostly applied, providing evidence for the occurrence of three main clusters in the Euryarchaeota named ANME-1, ANME-2 and ANME-3 (Fig. I.11). These cluster were found in close association with two dominant groups of SRB (SEEP-SRB1 and 4) involved in AOM (Hinrichs et al., 1999; Boetius et

(30)

al., 2000; Orphan et al., 2001 and 2002; Knittel et al, 2005; Niemann et al., 2006; Lösekann et al., 2007).

Fig. I.11. Phylogenetic tree of Euryarchaeota, including some methanogens and the groups

involved in AOM (Boetius et al., 2000; Knittel et al., 2005; Lösekann et al., 2007; MUMM project).

ANME-1, which is distantly related to Methanosarcinales and Methanomicrobiales, occurs in association with SRB of the Desulfosarcina-Desulfococcus (DSS) group from the G-proteobacteria (Michaelis et al., 2002; Knittel et al., 2005), as monospecific aggregates or as single cells (Orphan et al., 2001; Knittel et al., 2005). Both 2 and 3 belong to the order Methanosarcinales. ANME-2 has been observed in physical association with DSS (Boetius et al., ANME-2000; Knittel et al., 2005), while ANME-3 has been found in syntrophic partnership with Desulfobulbus sp. (DBB) (Niemann et al., 2006; Lösekann et al., 2007).

Physiological characteristics of AOM communities are based on a few in vitro studies (Nauhaus et al., 2002 and 2005) and mesocosm experiments (Guirguis et al., 2003 and 2005). Based on in vitro experiments Nauhaus et al. (2005) reported that changes in sulfate concentration, pH and salinity seem not to influence AOM activity, contrary to temperature. They concluded that ANME-2 is better adapted to cold temperatures than ANME-1, which shows highest methane-dependent sulfate reduction rates between 16°C

(31)

and 24°C (Fig. I.12). Furthermore, higher activity of ANME-2 community was observed at pH values of 7.4, whereas the pH optimum of ANME-1 showed a wide range between 6.8 and 8.1 (Nauhaus et al., 2005).

Fig. I.12. Methane-dependent sulfate reduction rates in ANME-1 and ANME-2 in response to

temperature variability (Nauhaus et al., 2005).

Mesocosm studies performed by Guirguis and collaborators (2005) evaluated the effect of fluid flow during growth of AOM consortia in sediments from seep and non-seep areas. They specifically observed that at higher fluid flows, AOM communities were stimulated by the advective methane, which induced higher growth rates of ANME-1 compared to ANME-2.

I.4. Distribution/Habitats of AOM communities

AOM can take place in a wide variety of environments in which methane and sulfate co-occur. Originally, AOM was studied in diffusive systems where low AOM and SR rates in the order of a few nmol cm-3 d-1 had been observed (Martens and Berner, 1977; Iversen and Blackburn, 1981; Iversen and Jørgensen, 1985; Hoehler et al., 1994). In these systems, the low rate of methane-rich fluids homogenously transported to the surface (Ziebis and Haese, 2005) enables AOM-communities to oxidize the methane almost completely (Iversen and Blackburn, 1981; Iversen and Jørgensen, 1985). Contrary, seeps or vents are controlled by advective fluid flow leading to much higher AOM and SR rates of the order of a few μmol cm-3 d-1 (Treude et al., 2003; Boetius and

(32)

Suess, 2004). AOM and SR rates are usually coupled in a 1:1 ratio (Hinrichs and Boetius, 2002; Nauhaus et al., 2002 and 2005). However, due to the fact that SR can as well be fueled by other carbon substrates, a decoupling of both processes has been observed in places where seepage of oil and higher hydrocarbon gases, such as ethane and propane, are detected (e.g., Gulf of Mexico, Joye et al., 2004).

Methane-rich fluids in advective systems are transported along permeable pathways (faults, cracks, scarps) induced by pressure gradients (Ziebis and Haese, 2005), which result in varying fluid flow regimes. This affects the small scale heterogeneity of seep communities which are dependent on hydrogen sulfide produced during AOM (Fig. I.13).

Fig. I.13. Community distribution in relation to fluid flow in sediments from

Hydrate Ridge (Sahling et al., 2002; Torres et al., 2002).

The input of methane, together with the sulfide rich fluids advected as a result of AOM, is the basis for the abundant communities of organism living in seeps such as sulfide oxidizing microbial communities and diverse benthic macrofauna with methanotrophic symbionts (Sahling et al., 2002; Levin, 2005).

Cumulative molecular data provide evidence of a global distribution of AOM communities (Fig. I.14). The occurrence of different AOM communities is observed in a wide range of natural habitats, which are dominated by one of the consortia described above. Hot spots of AOM communities are cold seep environments from

(33)

globally-distributed habitats including anoxic water bodies, mud volcanoes and oil fields, all of which are often found in conjunction with methane gas hydrates. Moreover, AOM has been observed at hydrothermal vent systems. A description of these environments is provided below.

Fig. I.14. Global distribution of AOM communities based on fluorescence in situ hybridization (FISH)

microscopy obtained during the projects MUMM I and II.

Cold seeps. Cold seeps are habitats where seepage of gases and methane-rich

fluids are transported by advective forces without a considerable increase in temperature. In contrast to hydrothermal vents, the fluid rates and temperatures at hydrocarbon seeps are dependent on the accumulation and burial of organic matter (Campbell, 2006). Since the first report of cold seeps 20 years ago (Paull et al., 1984), several new cold seeps have been found in passive (e.g., Suess et al., 1985, 1998; Yun et al., 1999) and active continental margins (e.g., Paull et al., 1995). In this environment, the supply of methane enables growth of diverse microbial communities such as methanotrophic archaea and SRB.

Hydrothermal vents. Hydrothermal vents are observed at mid-ocean ridges,

where abiotic methane is produced by serpentinization of iron and manganese minerals during the contact of basaltic material with sea water (Eq. 5a and b, Reeburgh et al.,

Black Sea Haakon Mosby Mud Volcano

Eel River Basin

Hydrate

Ridge Wadden _Sea

Eckernförder Bight Congo Basin Gulf of Mexico Guaymas Basin

(34)

2007). Once the sulfide- and sulfate-rich vent fluids get in contact with the cold seawater the precipitation of minerals produce the characteristic black smokers observed in hydrothermal systems (Haymon, 1983). Characteristic features of hydrothermal vent fluids are high temperatures (Lutz et al., 1994) and typically acidic pH values, although higher pH values have also been reported (pH >10, von Damm et al., 1985). Due to the presence of chemical and thermal energy produced in hydrothermal systems, this habitat is a major focus of interest because it represents an analog for the origin of life.

>

@

>

@

) (magnetite e) (serpentin (olivine) H O Fe OH O Si Mg 3 0 H 7 SiO Fe Mg 6 1.5 0.5 4 2 o 3 2 5 4 3 4 2 Eq. 5a O 2 H 4 2 4 2 2 CH H CO o Eq.5b

Hydrothermal vent fluids sustain diverse communities including tube worms, shrimps, clams and chemosynthetic microorganisms (Levin et al., 2005). Moreover, AOM has also been reported in the Guaymas Basin hydrothermal field where ANME-1 and ANME-2 communities occur (Teske et al., 2002).

Anoxic water bodies. The largest anoxic marine basin is the Black Sea

(Reeburgh et al., 1991). Concentration of methane in the anoxic water column are in the micromolar range (Reeburgh et al., 1991), which seems to facilitate the build-up of chimney-like structures that harbors carbonate-rich microbial mats of AOM communities (Michaelis et al., 2002; Treude et al., 2005). Both, lipid biomarkers strongly depleted in

13

C and FISH data confirm the presence of ANME-1/DSS and AMME-2/DSS utilizing methane as a carbon source (Michaelis et al., 2002; Blumenberg et al., 2004). Besides these structures, the occurrence of pockmarks, mud volcanoes and gassy sediments is also observed in the Black sea. Similarly, the occurrence of AOM in sediments and water column of Cariaco Basin has been documented (Reeburgh, 1976; Ward et al., 1987), although no evidence of chimney-like structures has been provided.

Mud volcanoes. Mud volcanoes are another important habitat, with high, but

episodic gas escape (Reeburgh et al., 2007). Most mud volcanoes are found as submarine structures close to subduction zones and orogenic belts, in which high sedimentation rates and the formation of hydrocarbons and fluids occur (Dimitrov et al., 2002; Milkov et al.,

(35)

2003). Methane release from these structures is estimated in the order of 13 Tg and 15 Tg during inactive and eruptive periods, respectively (Milkov et al., 2003). At distinct mud volcanoes, such as the Haakon Mosby Mud Volcano (HMMV), up to 40% of the released methane is oxidized by aerobic and anaerobic methonotrophs (Niemann et al., 2006). Distinctive from other seep environments is the dominance of ANME-3/DBB communities at HMMV (Lösekann et al., 2007). A relative higher abundance of ANME-3, although accompanied by other ANME groups, has been also reported at the mud volcano from the Nile deep sea fan at the eastern Mediterranean Sea (Omoregie et al., 2008).

Oil fields. Shallow and deep oil fields have been observed at Gullfaks and in the

Gulf of Mexico, respectively. Gullfaks is a big Norwegian oil and gas field located in the northern North Sea at 140 m water depth (Hovland, 2007). This area is covered by sand, which was deposited during the last glacial maximum (Hovland and Judd, 1988). Microbial mats of sulfide oxidizing bacteria provide evidence of the occurrence of AOM just a few centimeters below the seafloor, in which ANME-2a and -2c dominated communities inhabit (Wegener et al., 2008). The northern Gulf of Mexico is a hydrocarbon gas reservoir positioned over salt deposits of Jurassic age (Roberts et al., 1999). The tectonic characteristics of this location produce conduits that allow the transport of gas through seeps, brine pools and mud volcanoes, as well as the formation of methane hydrates (Sassen et al., 1994). Large amounts of sulfide oxidizing bacteria, inhabiting surface of sediments, together with a high abundance of ANME-1/DSS have been observed at Gulf of Mexico seeps (Orcutt et al., 2005).

Gas hydrate environments. The occurrence of methane hydrates in cold seeps is

very well documented from several locations such as the Gulf of Mexico (Sassen et al., 1994), the Eel River Basin (Kvenvolden and Field, 1981) and the Cascadia continental margin (Suess et al., 1999). Among these locations, one of the most studied is Hydrate Ridge, a geological feature discovered at the Cascadia Margin in the mid ‘80s (Suess et al., 1985). Hydrate Ridge is characterized by high fluid flow and shallow deposits of gas hydrates (Suess et al., 1999; Torres et al., 2002). In this habitat, the consortium of ANMEs and SRB responsible of AOM was visually observed for the first time (Boetius et al., 2000) in agreement with previous findings of huge amounts of AOM-derived

(36)

carbonate structures (Ritger t al., 1987) and 13C-depleted lipid biomarkers (Elvert et al., 1999).

Besides the fact that AOM communities are widely distributed in various habitats in which methane and sulfate co-occur, the dominance of single communities has been reported. For example, ANME-1/DSS seems to dominate in subsurface sediments (Knittel et al., 2005) and microbial mat structures (Michaelis et al., 2002), ANME-2/DSS occurs in surface sediments related to methane hydrates (Knittel et al., 2005), and ANME-3/DBB in mud volcanoes (Niemann et al., 2006, Lösekann et al., 2007). This indicates that the selection of the respective groups depends on a yet unknown environmental conditions found at the sites.

I.5. Lipid signatures of communities performing AOM

The first description of a biomarker related to AOM came from the irregular tail-to-tail isoprenoid crocetane (2,6,11,15-tetramethylhexadecane), which was observed in the SMTZ of sediments in the Kattegat (Bian, 1994; Bian et al., 2001). Moreover, crocetane was reported from recent and ancient cold seep environments associated with marine gas hydrates (Elvert et al., 1999) and limestone formation (Peckmann et al., 1999; Thiel et al., 1999), respectively. In all of these studies, crocetane was suggested to be a biomarker of anaerobic methanotrophic archaea due to its structural characteristic and strong depletion in 13C relative to the assimilated methane. Together with the occurrence of crocetane in AOM environments, subsequent studies have provided a series of other biomarkers characterized by very low 13C values as a consequence of methane utilization. The first unambiguous evidence of archaea mediating AOM was the presence of archaeol and sn-2-hydroxyarchaeol with 13C values < -100‰, which were found in concert with ANME-1 sequences in methane rich sediments from the Eel River Basin (Hinrichs et al., 1999). In a following study, Hinrichs et al. (2000) provided evidence for not only archaeol and sn-2-hydroxyarchaeol as indicators of ANMEs but also bacterial-derived fatty acids as well as straight-chain monoalkyl and dialkyl glycerol ethers (MAGEs and DAGEs, respectively), which were less depleted in 13C compared to the archaeal lipids. The presence of these non-isoprenoidal lipid biomarkers was attributed to

(37)

the SRB partners associated with the ANMEs (Hinrichs et al., 2000). The occurrence of these and other biomarkers in various cold seep systems, including methane-hydrate environments (Elvert et al., 1999, 2003 and 2005; Boetius et al., 2000), hydrothermal vents (Teske et al., 2002), mud volcanoes (Pancost et al., 2000 and 2001; Niemann et al., 2006), carbonate reefs (Thiel et al., 2001; Michaelis et al., 2002; Blumenberg et al., 2004) and oil fields (Wegener et al., 2008), support the extensive distribution of these communities performing AOM.

Several diagnostic biomarkers have been related to the dominance of the different AOM communities in the marine environment. ANME-1 microbial mats from the Black Sea were characterized by a high abundance of GDGT-derived biphytanes and higher amounts of archaeol as opposed to hydroxyarchaeol (Fig. I.15A). In contrast, ANME-2 dominated mats were found to contain crocetane and crocetenes, and a higher abundance of hydroxyarchaeol relative to archaeol (Fig. I.15B). Similar conclusions were drawn by Elvert et al. (2005) who reported the diversity of biomarkers occurring in sediments from Hydrate Ridge off the coast of Oregon. Biomarker patterns observed were specifically related to different fluid flow regimes causing the development of distinct seep provinces, namely Beggiatoa mats, Calyptogena fields and Acharax fields (Fig. I.13). Besides archaeal biomarkers, high amounts of DSS-specific fatty acids (i.e., C16:15c and

cyC17:05,6) were detected at the Beggiatoa site (Fig. I.15C), where also high numbers of

ANME-2a/DSS aggregates were observed, whereas ANME-1 in deeper horizons of the Calyptogena site showed higher contents of the fatty acid ai-C15:0 (Fig. I.15D). Generally,

sediments from the Calyptogena site were dominated by ANME-2c and characterized by the additional occurrence of GDGTs containing 1 and 2 cyclopentyl rings, which have been frequently detected in AOM environments (e.g., Pancost et al., 2001; Wakeham et al., 2003). Carbon isotopic values of the biomarkers from ANME-2 were usually 20‰ more negative than the ones from ANME-1 dominated sediment horizons (Elvert et al., 2005). This carbon isotopic difference between the two communities was previously indicated in other studies (Hinrichs et al., 2000; Orphan et al., 2001; Blumenberg et al., 2004).

(38)

Fig. I.15. Characteristic apolar lipids derived from ANME-1 and ANME-2 dominated

chimney-like structures in the Black Sea (A and B, Blumenberg et al., 2004) and sediments underneath a

Beggiatoa mat from Hydrate Ridge (C and D, Elvert et al., 2005).

The differentiation of ANME-3 from ANME-1 and -2 is less obvious and was characterized by the sole presence of highly unsaturated 2,6,10,15,19-pentamethylicosanes (PMI:4 and PMI:5) together with archaeol and hydroxyarchaeol, but the absence of both crocetane and GDGTs (Niemann et al., 2006). The bacterial partner of the Desulfobulbus group, however, was indicated by the high abundance of the specific fatty acid C17:16c.

(39)

In summary, the occurrence of strongly 13C-depleted archaeal biomarkers in AOM studies is accompanied by the presence of slightly 13C-enriched bacterial lipid biomarkers. Among these bacterial lipids, the occurrence of complex fatty acids with 14-18 carbon atoms, with and without double bonds, methyl-branches and cyclopropyl isomers has been observed (Hinrichs et al., 2000; Elvert et al., 2003 and 2005). Also the presence of MAGEs and DAGEs with similar patterns to the ones detected in the fatty acids has been reported (Hinrichs et al., 2000; Elvert et al., 2005). However, all of these previous biomarker studies targeted GC-amenable lipids, which are assumed to represent only a minor fraction in living cells and may have only been found as a relict of deceased microbial communities. To reduce the obstacles associated with apolar lipids, we therefore targeted intact polar lipids (IPLs) which are the building blocks of the cyctoplasmic membrane of all living cells and which can be directly related to microbiological investigations using FISH or other techniques.

I.6. Intact polar membrane lipids (IPLs)

The cytoplasmic cell membrane acts as a semi-permeable barrier and protects the cell from the external environment. The membrane is composed of proteins and a lipid bilayer (Fig. I.16).

Proteins can play different roles in the cell membrane such as recognizing substrates, performing enzymatic activity and transporting substances (nutrients, ions and waste) between the cytoplasm and the exterior of the cell (Madigan et al., 2003). On the other hand, lipids are indispensable for the membrane structure due to their chemical properties (hydrophobicity and hydrophilicity), which directly involve these molecules in membrane permeability (Madigan et al., 2003). Because the cell membrane regulates the transport between the exterior and interior of the cell, it is also important in the conservation of cell energy (Madigan et al., 2003).

According with the fluid mosaic model, the cell membrane is composed of a double layer or bilayer of lipids. The bilayer formed by phospholipids contains a fatty acid tail (hydrophobic side) and a phosphate group in the polar part of the molecule (hydrophilic side). The hydrophobic side is oriented inwards, while the hydrophilic side

(40)

or head group is facing outwards (i.e. the aqueous cytosol of the cell or the environment) (Fig. I.16).

Fig. I.16. The phospholipid membrane bilayer (Tortora et al., 2004).

Lipids in the cell membrane of prokaryotes are represented by phospholipids, glycolipids and sometimes hopanoids (e.g., in methanotrophic bacteria, Madigan et al., 2003). In total, they represent up to 6% of the cell dry weight (Langworthy et al., 1983). Membrane lipids are good candidates to distinguish Bacteria and Archaea. Bacteria generally contain a phospholipid bilayer composed of fatty acids linked to a glycerol backbone via ester bonds in sn-1 and sn-2 position (ester-bond acyl chains, Fig. I.17). In sulfate reducers, these fatty acids may include methyl branching, double bonds and cyclopropyl isomers (Taylor and Parkes, 1983; Dowling et al., 1986). Archaeal membranes can occur both as a bilayer or monolayer (Fig. I.17). The bilayer of archaeal cells contains isoprenoidal chains linked to the glycerol backbone in sn-2 and sn-3 position via an ether bond (i. e., isoprenoidal alkyl chains) and is generally formed by two C20 hydrocarbon chains (phytanyl ethers) (Langworthy and Pond, 1986). Archaeal

monolayer membranes are composed of glycerol tetraethers, in which two glycerol molecules are linked via two C40 hydrocarbon chains (biphytanyl ethers) (Langworthy

(41)

and Pond, 1986). Generally, ether bonds from archaeal membranes are more resistant to higher temperature, pressure and pH (De Rosa et al., 1989) than the ester bonds present in bacteria.

Fig. I.17. General features of archaeal and bacterial lipid membranes (Valentine, 2007).

Because the cell membrane is affected by external conditions such as temperature, pH, pressure or salinity, several adaptations in prokaryotic cell membranes are related to cell evolution, physiology, biogeochemistry and ecology (Langworthy, 1982). Among these adaptations, changes in fatty acid compositions have been observed depending of the habitat temperatures. In contrast to shorter saturated and unsaturated fatty acids in psychrophilic bacteria, evidence of longer and saturated fatty acids, predominantly iso-branched, is found in thermophilic bacteria (Langworthy, 1982). Additionally, the effects of pH and temperature in a thermoacidophile were evaluated (De Rosa et al., 1974). At lower pH and increasing temperature, the proportion of iso- and anteiso-fatty acids

(42)

increases, whereas at higher pH and increasing temperature cyclohexyl fatty acids increase (De Rosa et al., 1974). Furthermore, the effect of temperature on polar head group compositions of a thermophilic organism (i.e., Bacillus caldotenax) has been investigated by Hasegawa et al. (1980). These authors reported a decrease in the amount of PE (from 57% to 37%) and increase of PG (from 27% to 46%) in the total phospholipid content induced by a temperature decrease from 65°C to 45°C.

Modifications observed in the hydrocarbon chains of archaeal-based tetraether lipids include the increase in membrane stability at higher growth temperatures by the formation of cyclopentane rings (Langworthy and Pond, 1986).

All the modifications in the membrane described above intent to protect the cell from the environment. In general, archaeal membranes are less permeable, thus they may be better adapted to hostile environments than bacterial ones (Valentine, 2007). Due to this characteristic of Archaea, these microorganisms were assumed to live in extreme environments in which low pH and high temperatures occur (Rothschild and Mancinelli, 2001). However, cumulative evidence shows that Archaea are not only prevalent in the deep biosphere (Biddle et al., 2006; Lipp et al., 2008), hydrothermal vents (Teske et al., 2002; Reysenbach et al., 2000; Schouten et al., 2003) and cold seeps (Boetius et al., 2000; Knittel et al., 2005), but are also widely distributed in ocean waters (Karner et al., 2001; DeLong, 2003).

The investigation on the diversity of intact polar membrane lipids (IPLs) from both Bacteria and Archaea was extended by the utilization of high-performance liquid chromatography mass spectrometry (HPLC-MS). Contrary to the other techniques (e.g., gas chromatography), the advantage of HPLC-MS is the possibility to study the intact membrane lipid molecules instead of core or side chain products. During the analysis, the chromatographic separation of IPLs is based on their polarity, which is mainly related to the molecule’s head groups (Fig. I. 18).

(43)

Fig. I.18. HPLC-MS chromatogram (A) and density map (B) of an IPL mixture of commercially

available standards mixed with an extract of microbial mat from the Black Sea. IPLs elution depends on their polarity, with less polar compound eluting at early retention times. Density map is a representation of the IPL peaks in relation to the retention time and the mass to charge ratio (range scanned from 500 to 2000 m/z). In it, the intensity of the black lines is correlated to the concentration of the IPL in the sample mixture. Bacterial-derived IPLs (PE, PG and PDME) in the density map are displayed in series due to the presence of different fatty acid chain lengths. Abbreviations of IPLs according to Fig. I.19

Diversity of polar head groups in IPLs has been described from cultures and environmental samples based on HPLC-ESI-MS (Fig. I.19A), providing taxonomic information that allows the distinction of different microorganisms (e.g., De Rosa et al., 1986; Koga et al., 1998; Sturt et al., 2004; Koga and Morii, 2005; Van Mooy et al., 2006; Koga and Nakano, 2008). HPLC-ESI-MS is equipped with an electrospray ionization source (ESI) that produces a soft ionization of the analytes, which is particularly appropriate for polar molecules like IPLs. Using this technique, the diversity of IPLs characteristic of archaea from marine systems has been reported, including archaeol- and GDGT-based IPLs with glycosidic head groups (Fig. I.19B, Sturt et al., 2004; Biddle et al., 2006; Lipp et al., 2008). Furthermore, a variety of phospholipids from Bacteria has been documented, including ether and ester phospholipids (Fig. I.19C) with diverse types of head groups (Rütters et al., 2002; Sturt et al., 2004; Van Mooy et al., 2006).

(44)

O O P OH O O O O O P OH O O O O O P OH O O O R' R'' R'' R'' O R' O R' O Diacylglycerophospholipid DAG Acyl/ether glycerophospholipid AEG Dietherglycerophospholipid DEG

OO O

X=H, Diglycosyl archaeol X=OH, Diglycosyl hydroxyarchaeol

X O O O _O OH O Diglycosyl glyceroldialkylglyceroltetraether GDGT with 0 cyclopentyl rings O HO OH O P OH O O HO NH2 O Phosphatidylserine PS Phosphatidylglycerol PG O P OH O O OH HO HO HO OH Phosphatidylethanolamine PE O P OH O O N Phosphatidylcholine PC _{Phosphatidylinositol PI} O P O O O H2N O P OH O O N O P OH O O N H O P OH O Phosphatidyl-(N)-methylethanolamine PME Phosphatidyl-(N,N)-dimethylethanolamine PDME O HO OH HO O O HO HO HO OH O HO OH HO O O HO HO HO OH O HO HO OH O OH O HO HO HO OH O O _O OH O Diglycosyl glyceroldialkylnonitoltetraether GDNT with 0 cyclopentyl rings HO O P OH O Phosphatiddic acid PA O O P OH O HO OH NH2 OH Phosphoaminopentatetrol APT O O P OH O H2N O OH HO HO O O P OH OH Glyco-phosphoethanolamine GPE HO O OH HO HO O O O O O n=1 Monogalactosyldiacylglycerol MGDG n=2 Digalactosyldiacylglycerol DGDG n HO3S O OH HO HO O O O O O Sulfoquinovosyldiacylglycerol SQDG A C B

Fig. I.19. Diversity of IPL-head groups present in Bacteria and Archaea (A), glycolipids commonly observed

in Archaea (B), and ester and ether linkages observed in phospholipids (C).

Structural information of IPLs can be obtained by ion-trap mass spectrometry (IT-MS) configured to trap ions of interest which are later fragmented producing daughter ion mass spectra (MSn). Identification of IPLs is based on fragmentation patterns obtained from MSn experiments in positive and negative modes, and by comparison with previously reported mass spectral data (Table I.1) (Sturt et al., 2004) and molecular structures (Koga and Nakano, 2008 and references therein). Most of the structural characteristics of IPLs can be obtained in MS2 (Fig. I.20). However, additional information is obtained by analyzing the sample under positive and negative ionization modes. IPLs positively ionized frequently loose the head groups providing information of the lipid class (Fig. I.20A), whereas IPLs negatively ionized loose the fatty acid chain located in the sn-2 position (Fig. I.20B). Structural information of diverse IPLs from Archaea and Bacteria observed in this study are provided in the Chapter V of this work.

(45)

Positive ion mode [M +H]+ Negative ion mode [M -H]

-Headgroup AEG, DAG DEG AEG, DAG DEG PE 141 Da loss (phosphoethanolamine) 43 Da loss (ethanolamine) 43 Da loss (ethanolamine) APT 231 Da loss

(phospho-APT) 133 Da loss (APT)

AEG-P; loss of sn-2 fatty acid 133 Da loss (APT) PG 189 Da loss (phosphoglycerol + NH4+ adduct) 75 Da loss (glycerol) DAG-P; loss of head group+ sn-2 fatty acid 75 Da loss (glycerol) PI 162 Da loss hexose Major ion m/z 241 (phosphoglycosyl – H2O)

PS 185 Da loss (phosphoserine) 87 Da loss

(serine) 87 Da loss (serine) PC All give a major ion m/z 184 (phosphocholine) All show 60 Da loss (CH3+ HCOO

-adduct)

Table I.1. Characteristic headgroup losses of common phospholipids under HPLC-ESI-MS conditions in

positive and negative ion modes (Sturt et al., 2004).

Fig. I.20. Mass spectra of phosphatylethanolamine (PE) diacylglycerol (DAG). Difference of mass

between the positive (A) and negative ion mode (B) are explained by the addition and lost of one proton in the molecule, respectively. MS2 data in positive ion mode indicate the lost of 141 Da (PE) from the glycerol and fatty acid core with C31:2 (sum of both fatty acids). Negative ion mode indicates the lost of

C15:2 from sn-2 position of the glycerol first (lyso fragment 434 Da) and the presence of the fatty acid C16:0

(46)

I.7. Methods

Most samples analyzed in this study were freeze-dried and extracted according to a modified Bligh and Dyer protocol (Sturt et al., 2004) by microwave-assisted extraction system (MARS-X, CEM, USA) for 15 min at a temperature of 70°C, while a few others were extracted by ultrasonication. A mixture of standards covering different lipid classes was added to the samples. The standards included cholestane (hydrocarbons), behenic acid methyl ester (ketones), C-19 alcohol (alcohols) and C19-fatty acid (fatty acids) for

GC-amenable lipids, and C16-PAF for IPL analysis. The solvent mixture used during the

extractions was methanol:dichloromethane:buffer in a proportion of 2:1:0.8. The volume of the solvent mixture used was 40 mL per every 10 g of dry sediment and 1 g of dry mat. The first two extraction steps were performed with phosphate buffer, whereas the last two were performed with trichloroacetic acid buffer (TCA). After collection of all supernatants, the organic phase was separated from the aqueous one by multiple additions of dichloromethane (DCM) and milli-Q water. This liquid-liquid extraction was performed by using the same amount of water and DCM than the total solvent mixture added during the extractions, starting with DCM (3 times) and then with water (3 times). The organic phase or total lipid extract (TLE) was evaporated to dryness under a stream of nitrogen and re-dissolved in a mixture of DCM:methanol (1:1), which was finally injected into the HPLC-ESI-MS.

Due to the nature of the sample (e.g., oily etc.), additional clean-up steps were performed on Eel river Basin, Guaymas Basin and two sediment samples from Gulf of Mexico. Here, separation of the TLE into apolar, glyco- and phospholipids was carried out on activated silica column (2 g of silica for 50-200 mg of extract) by elution with 20 mL of DCM, 40 mL of acetone and 40 mL of methanol, respectively. Acetone and methanol eluted fractions were combined and evaporated under a nitrogen stream and re-dissolved in DCM:methanol (1:1) prior to analysis. This procedure allows the detection of IPLs previously not observed in the TLE probably due to matrix problems and ion suppression. It is well documented that ESI signal can be affected by the sample matrix, which, if contain endogenous material (in this case hydrocarbons), could interfere in the ionization of the analytes of interest (Mallet et al., 2004). This problem can be solved to some degree by additional clean-up steps (Mallet et al., 2004).

(47)

Parallel analyses of apolar lipid biomarkers were performed in order to compare both intact (IPLs) and non-intact lipids (GC-amenable lipids). For the analysis of apolar lipids, a fraction of the TLE was added to a Pasteur pipette with glass wool and separated into maltene and asphaltene fraction, eluting the first of them with 2.5 mL hexane and the second with 4 mL of DCM. The maltene fraction was further separated into four fractions of increasing polarity on Supelco LC-NH2 glass cartridges (500 mg sorbent) using 4 mL of hexane (hydrocarbons), 6 mL hexane/DCM (3:1; ketones/esters), 7 mL DCM/acetone (9:1; alcohols) and 8 mL of 2% formic acid in DCM (free fatty acids). Each fraction was evaporated to dryness under a stream of nitrogen and re-dissolved in hexane prior to analysis. Previously alcohols were derivatized into trimethylsilylesters (TMS-derivatives) by addition of N,O-bis(trimethylsilyl) fluoracetamide (BSTFA) and pyridine. Similarly, fatty acids were transformed to methylesters (FAME) before analysis, using 20% Boron trifluoride (BF3) in methanol. Both reactions were performed at 70°C for 1h. All fractions were analyzed via gas chromatography-mass spectrometry (MS) and GC-flame ionization detection (GC-FID). Identification of GC-amenable lipids was based on the comparison of retention times, mass spectra of commercial standards and from literature.

I.8. Hypothesis and objectives

The aim of this PhD work is the elucidation of the microbial community structures in different marine methane-rich environments based on the diversity of lipid signatures. This work is part of the MUMM II (Methane in the Geo/bio-System-Turnover, Metabolism and Microbes) project, a multidisciplinary BMBF project which started in a first phase already in January 2001.

AOM is, based on current knowledge, associated with the presence of three phylogenetic clusters of methanotrophic archaea (ANME) and two groups of SRB (DSS and DBB) in various marine environments (gas hydrate, mud volcanoes, hydrothermal sediments and coastal subsurface environments). Different biogeographical patterns of these clusters are probably related to varying environmental conditions found in a wide range of settings (e.g., Arabian Sea, Black Sea, Eastern Mediterranean Sea, Eel River

Microbial communities performing anaerobic oxidation of methane: diversity of lipid signatures and habitats