Biogeochemistry of Microbial Coal-Bed Methane cd S o 1 B Dariusz StraDoc,1* Maria Mastalerz,2 Katherine Dawson,3 Jennifer Macalady,3 Amy V. Callaghan,4 Boris Wawrik,4 Courtney Turich,1 and Matthew Ashby5 ^onocoPhillips, Houston, Texas 77079 2Indiana Geological Survey, Indiana University, Bloomington, Indiana 47405 3Geosciences Department, Pennsylvania State University, University Park, Pennsylvania 16801 4Deptartment of Botany and Microbiology, University of Oklahoma, Norman, Oklahoma 73019 5Taxon Biosciences, Tiburon, California 94920 ^'Current address: Indiana Geological Survey, Indiana University, Bloomington, Indiana 41405; email: dstrapoc@indiana.edu S o O v ox CO Annu. Rev. Earth Planet. Sei. 2011. 39:617-56 The Annual Review of Earth and Planetary Sciences is online at earth.annualreviews.org This article's doi: 10.1146/annurev-earth-040610-133343 Copyright © 2011 by Annual Reviews. All rights reserved 0084-6597/11/0530-0617S20.00 Keywords CBM, biogenic gas, methanogenesis, isotopes, metabolites, FISH, 16S rRNA, DNA analysis, biodegradation Abstract Microbial methane accumulations have been discovered in multiple coal-bearing basins over the past two decades. Such discoveries were originally based on unique biogenic signatures in the stable isotopic composition of methane and carbon dioxide. Basins with microbial methane contain either low-maturity coals with predominantly microbial methane gas or uplifted coals containing older, thermogenic gas mixed with more recently produced microbial methane. Recent advances in genomics have allowed further evaluation of the source of microbial methane, through the use of high-throughput phylogenetic sequencing and fluorescent in situ hybridization, to describe the diversity and abundance of bacteria and methanogenic archaea in these subsurface formations. However, the anaerobic metabolism of the bacteria breaking coal down to methanogenic substrates, the likely rate-limiting step in biogenic gas production, is not fully understood. Coal molecules are more recalcitrant to biodegradation with increasing thermal maturity, and progress has been made in identifying some of the enzymes involved in the anaerobic degradation of these recalcitrant organic molecules using metagenomic studies and culture enrichments. In recent years, researchers have attempted lab and subsurface stimulation of the naturally slow process of methanogenic degradation of coal. 617 1. INTRODUCTION cd S o 1 B S o O CO Coal: a readily combustible rock containing >50 wt% and >70 vol% of carbonaceous material; is typically plant-derived organic matter at varying levels of chemical transformation, depending on thermal maturity Coal rank: level of physical and chemical transformation of organic matter known as coalification; progresses from peat through lignite, subbituminous coal, bituminous coal, semianthracite, to anthracite and meta-anthracite Methanogens: obligate anaerobic prokaryotic microorganisms that produce methane as a metabolic by-product. These archaea (not bacteria) reduce small molecules such as CO2, acetate, and methanol to methane to gain energy Coal-bed methane (CBM) production was initiated in the United States in the late 1980s and today accounts for approximately 10% of total production from all gas wells in this country (Figure 1). In 2009, the volume of produced CBM in the United States was 56 x 109 m3 or ~2 x 1012 ft3 (http://www.eia.gov). Early production of CBM focused on highly mature coals with thermogenic gas potential (e.g., Fruitland coals in the San Juan Basin). As CBM exploration progressed into less mature regions, methane was still found to be present in significant quantities, above what would be expected on the basis of thermogenic generation of gas. Even coals not mature enough to have begun generating thermogenic gas appeared to be methane rich (e.g., coals in the Powder River Basin). The universal abundance of methane in low-maturity coals and other organic-rich rocks, including shales and sandstones with organic debris, triggered geochemical studies, including gas isotopic analysis, to decipher the origin of the gas. Geochemistry repeatedly implied the microbial origin of gases in low-maturity rocks. Subsequently, some of the higher-maturity coals were discovered to contain mixtures of thermogenic hydrocarbons and microbial methane or secondary biogenic gas, e.g., the northern part of the San Juan Basin (Scott et al. 1994, Zhou et al. 2005). In multiple basins, regardless of coal rank, microbial methane generation was initiated or stimulated after the introduction of meteoric water into the system [e.g., Alberta (Bachu & Michael 2003) and Black Warrior (Pashin 2007)]. Furthermore, microbial methano-genesis is ongoing in multiple shallow coals [e.g., Powder River (Green et al. 2008)], dispersed organic matter-containing formations [e.g., Cook Inlet (Strqpoc et al. 2010a)], and shales [e.g., Michigan Basin (Martini et al. 2003)]. Global occurrences of microbial CBM are depicted in Figure 1. During the past several years, geomicrobiological and phylogenetic studies of subsurface coal beds, shales, and sandstones with organic debris have described the active microbial communities [e.g., Hokkaido (Shimizu et al. 2007), Powder River Basin (Green et al. 2008), and the Ruhr Basin (Krüger et al. 2008)]. Several studies have demonstrated the ability of these communities to convert coal to methane (Shumkov et al. 1999, Harris et al. 2008, Orem et al. 2010). In general, these processes involve groups of fermentative bacteria that are syntrophically associated with methanogenic archaea. Recent, and mostly industry-based, efforts have targeted enhanced CBM subsurface generation via amending indigenous communities with nutrients and/or via inoculation with microbial consortia (Pfeiffer et al. 2010). In this review, we describe how occurrences of microbial methane accumulations in coal beds are identified through the use of geochemical tools such as stable isotopes. Furthermore, geological and hydrogeological constraints of such accumulations are discussed. Detailed discussion about the microbial process of formation of methane from coal begins with a description of the origin and composition of coal as the substrate. Subsequently, we present current knowledge about and methods of analysis of microbial metabolic pathways and microbial communities involved in biodegradation of various moieties of coal's organic matter. Lastly, attempts of stimulation of enhanced microbial methane generation in coals are briefly described. 2. GEOCHEMISTRY AND GEOLOGICAL CONTROLS OF MICROBIAL COAL-BED METHANE 2.1. Geochemical Identification and Global Occurrence Microbial methane generation from any coal, regardless of its burial history, requires suitable physicochemical subsurface conditions. Isotopically, microbially generated gas has distinct 13C-and D-depleted signatures. These isotopic fingerprints were commonly utilized in gas origin 61S Strapac et al. cd S o 1 3 S o o V —' .20* at =-V^21 40°N .... ... ^ 3\ . fir*. ' • Pacific-Ocean lQcean I ^ ff Kf\.\i 7 ' '< > -• / v'_ • 20°S 22 23 1992 1996 2000 2004 2008 Year 26 25-W ^24 ^ Ä * 31 —27 Major coal-bearing regions ^ Main areas of active CBM production # Microbial CBM induced by freshwater influx ♦ Other microbial CBM occurrences ? No CBM data or no CBM exploration/production Figure 1 Global occurrences of microbial coal-bed methane (CBM). (1) Cook Inlet Basin, Alaska (Rice & Claypool 1981, Montgomery & Barker 2003, Strsipoc et al. 2010a). (2) Fort Yukon, Alaska (Harris et al. 2008). (3) Alberta Basin, Alberta (Bachu & Michael 2003). (4) Elk Valley, British Columbia (Aravena et al. 2003). (5) Maine Prairie, California (this review article). (6) Uinta Basin, Utah (Stark & Cook 2009, this review article). (7) Powder River Basin, Wyoming (Jin et al. 2007, Pfeiffer et al. 2010, Flores et al. 2008, Rice et al. 2008, Strarjoc et al. 2010a). ( * 4 'o Acetate fermentation and methanol/methyl utilization -55 3CcH. (%0 Figure 2 + Illinois Basin, Indiana + Illinois Basin, Kentucky + Maine Prairie, California Cook Inlet onshore, Alaska O Cook Inlet offshore, Alaska + Powder River, Wyoming + Uinta, Utah + San Juan, New Mexico O Hokkaido, Japan Carbon and hydrogen isotopic classification of methane showing differences between thermogenic gas and biogenic methane generated from different substrates. The arrow and red background color indicate increasing thermal maturity of thermogenic end-member methane. Dashed lines indicate examples of mixing lines. Data sources: Hokkaido, Shimizu et al. (2007); Illinois, Str^poc et al. (2007); Cook Inlet onshore and Powder River, Stra^poc et al. (2010a); Maine Prairie, Cook Inlet offshore, Uinta, and San Juan, this review article. v ox CO cd E -° -s Thermal maturity: a measure of degree of organic matter transformation in response to geothermal conditions Vitrinite reflectance (R0): a measure of thermal maturity of organic matter in rocks; a percentage of the incident light reflected from a polished surface of maceral vitrinite measured with a reflected light microscope using an oil immersion objective from coal beds with microbial methane, thermogenic gas, and mixed-gas origins. In contrast to the classification of microbial gas, the classification of thermogenic gases relies on both molecular and stable isotopic patterns of methane, ethane, propane and butanes, which vary according to increasing thermal maturity (Berner & Faber 1988, Chung etal. 1988). Additionally, within a certain range of maturity, thermogenic gas from coal is volumetrically significant. Early thermogenic gas generation starts at ~0.5% of vitrinite reflectance (R0)- Thermogenic gas production from coal reaches a transformation ratio (TR) value of 0.1 at ~0.7% RQ. The major thermal cracking of coal to gaseous hydrocarbons occurs at RQ between 0.7% and 1.6%, reaching a TR of 0.8 (Waples & Marzi 1998). However, generation of the remaining 20% of gas continues well into the anthracite maturity range (2.5-5% R0) (Schimmelmann et al. 2006). The 5D-513C plot (Figure 2) indicates that the position of the thermogenic end member of the mixed gas depends on the coal's thermal maturity. Therefore, a mix of high-maturity thermogenic gas with a relatively small fraction of biogenic methane (e.g., that of San Juan) (Figure 2) can plot identically as pure low-maturity thermogenic gas (e.g., that of Illinois Basin, Kentucky). Microbial gas, however, is unique for its high dryness, owing to the lack of significant microbial generation of C2+ hydrocarbon gases (Figure 3). In addition to coal beds with exclusively thermogenic gas [e.g., in the southern part of the Illinois Basin (Strgpoc et al. 2007)] or biogenic gas [e.g., in the Powder River Basin (Flores et al. 2008)], mixed origin of CBM is even more common [e.g., in the San Juan Basin (Scott et al. 1994), Sydney Basin (Faiz & Hendry 2006), and Hokkaido (Shimizu et al. 2007)]. Isotopic mixing diagrams can be used to estimate the contribution of each end member (Figure 3). All the above-mentioned gas isotopic classification plots (Figures 2 and 3) should be used with caution and in tandem with or in the context of other available geological and geochemical data. Strßpac et al. Additionally, carbon isotopic differences between CH4 and CO2 (A13Cco2-ch4) can be helpful in deciphering gas origin (Figure 3d). Thermogenic processes are characterized by low A13Cco2-ch4 owing to high temperatures. Low-temperature microbial enzymatic processes lead to 13 C enrichment in residual CO2 (Conrad 2005). In coals with a mixture of thermogenic and biogenic gases, A13Cco2-ch4 can be more suitable than the absolute value of 513 C for discriminating gas origin (Smith & Pallasser 1996, Strqpoc et al. 2007). In spite of the great utility of these isotopic methods, they cannot account for all three methanogenic pathways. Specifically, methane samples derived from acetate fermentation plot together with methane samples derived from methanol, methylamine, or methylsulfide utilization. The isotopic signatures of these two pathways are similar because the methane hydrogen and carbon atoms are derived from methyl groups that are either disproportionated from acetate or cleaved from methanol, methylamines, or methylsulfides. In contrast, the CO2 reduction pathway results in slightly lower <513Cch4 values and a distinct value corresponding to the 5D of formation water, which is typically deuterium enriched compared with carbon-bound hydrogen (Smith et al. 1992, Conrad 2005). Other substrates that can be utilized by methanogens include formate, carbon monoxide, and other simple alcohols (e.g., ethanol, isopropanol, and butanol), but their associated isotopic fractionations are not well-known. Nonetheless, in addition to coals with dominantly acetate- or CO2-utilizing methanogens, recent studies not only have shown the presence of obligate methyl/methanol-utilizing methanogens (Shimizu et al. 2007, Doerfert et al. 2009, Mochimaru et al. 2009, Toledo et al. 2010) but have even suggested that such methanogens have a leading role in methane production (Strqpoc et al. 2010a). Transformation ratio (TR): a level of conversion of organic matter into hydrocarbons during thermal maturation. Expressed as a fraction (values from 0 to 1); a value of 1 designates complete conversion Isotopic fractionation: the enrichment of one isotope relative to another in a chemical or physical process such as bond breaking 2.2. Impact of Burial History and Hydrogeology on Microbial Coal-Bed Methane Generation Numerous CBM basins containing microbial methane experienced microbial reinoculation during their postburial geological history. Exceptions could be basins that were never buried deeply enough to become temperature sterilized or basins that were never uplifted sufficiently after coalification. The most likely source of microbial inoculation is an influx of waters in contact with shallower environments containing microbial communities. Numerous examples include Forest City Basin (Mcintosh et al. 2008); Sydney Basin (Ahmed & Smith 2001, Faiz & Hendry 2006); Bowen Basin (Ahmed & Smith 2001); Surat Basin (Li et al. 2008); Alberta Basin (Bachu & Michael 2003); Elk Valley in British Columbia (Aravena et al. 2003); Uinta Basin (this review article); Cook Inlet (Montgomery & Barker 2003, Strgpoc et al. 2010a); Upper Silesian Basin in Poland (Kotarba & Pluta 2009); the Xinji area in China (Tao et al. 2007); and Hokkaido, Japan (Shimizu et al. 2007). In the Powder River Basin (Flores et al. 2008), the map of water 5D shows the impact of the Pleistocene water in the recharge areas of the basin. In the Black Warrior Basin (Pitman et al. 2003, Pashin 2007), two events of uplift, microbial inoculation and methane generation, were recorded by the precipitation of 13C-enriched calcite. In the San Juan Basin, uplift- and topography-driven recharge of meteoric water from the mountains inoculated coals and stimulated biomethane generation in the north and northwest parts of the basin (Scott et al. 1994, Ayers 2002, Zhou et al. 2005, this study). Additionally, artesian overpressure in the northern part of the basin allows for a larger gas capacity of the Fruitland coals. Similar artesian inflow has been observed in the western part of the Uinta Basin (Buzzards Bench and Drunkards Wash) along with its association with enhanced microbial methane along the freshwater conduits (Stark & Cook 2009). The formation water in the Ferron Member-containing coals was estimated to be ~30 ka using 14C. Alternative isotopic methods for the dating of older groundwaters are 36C1 (half-life, 301 ka) and 129I (half-life, 15.7 Ma) (for a detailed description, see Snyder et al. 2002 and Lu et al. 2008). www.annualreviews.org • Biogeockemistry of Coal-Bed Methane 621 co2 A Acetate and pathway mix methyl/methanol ♦ V° * amaa . a ■|o a a^ %0+ a a a^a a m a* ♦ Illinois Basin, Indiana ♦ Illinois Basin, Kentucky O Maine Prairie, California Cook Inlet onshore, Alaska a Cook Inlet offshore, Alaska A Powder River, Wyoming a Uinta, Utah a San Juan, New Mexico a Hokkaido, Japan a Lignites, Poland 2-0% 50 A1 40 ;CC0,-CHa (%0 100% biogenic *T A (•DC A.A A^ 2.0% 0-5% 6"CCH4(%o) In the Illinois Basin, the same types of coal from two parts of the basin with significantly different burial histories contain diametrically different types of gases. The southern part of the basin (western Kentucky) experienced deeper burial associated with an abandoned rift system and the potential impact of hydrothermal fluids. The resulting graben was never erosionally uplifted as much as the rest of the basin. As a result, this part of the basin generated exclusively thermogenic gas, whereas shallow and immature coals in the eastern flanks of the basin generated almost pure biogenic methane (Figure 4) (Strqpoc et al. 2008). Similar phenomena were documented for the occurrences of biogenic shale gas in which low salinity of diluted basinal brines coincided with isotopic signatures of microbial methane [Antrim Shale in the Michigan Basin (Martini et al. 2003), New Albany Shale (Strqpoc et al. 2010b)]. For global occurrences of microbial methane in coals, see Figure 1. 3. COAL COMPOSITION AND MATURITY: FROM PLANTS TO A MOLECULE Organic carbon, the dominant component of coals, is the primary source of coal-bed gas through its abiotic and biotic breakdown. Therefore, below we briefly review the composition of the organic coal fraction that depends on the makeup of the original plant material, the conditions of organic matter decomposition within a peat mire, and postdepositional chemical transformations. 3.1. Peat-Forming Plant Communities Peat, a precursor of coal, originates predominantly from plant communities on peat mires. The first indications of plants inhabiting the land came from Middle Ordovician to Late Silurian age strata, but they became widespread only in the Early Devonian (Traverse 2008, Taylor et al. 2009, and references therein). The formation of significant peat deposits required massive expansion and diversification of plant communities, and although coal deposits are known from the Middle Devonian from the Kuznetsk Basin in Russia (Gorsky 1964), only in the Early Carboniferous did large coal deposits form (Figure 5). In the Lower Carboniferous, representatives of most of the plant groups that would form the luxuriant vegetation of the upcoming coal age were present. The Upper Carboniferous (Pennsylvanian) featured further development of this vegetation, and during that period most of North America and Europe were covered by peat-forming mires (the Euro-American Coal Province). Located within 10° of the paleoequator, the paleomires were dominated by lower vascular plants such as lycopods, ferns, and calamites (Phillips et al. 1985, Winston 1989, Eble & Grady 1993, Willard 1993). The gymnosperm Cordaites appeared during that period and increasingly became a contributor to peats. Permian peat-forming plants were restricted mainly to the Gondwana supercontinent. Therefore, Permian coals are found on several continents, including Africa, Antarctica, Australia, China, and South America (Figure 5), and are known as the Gondwana Coal Province. Permian floras <- Figure 3 Gas origin classification and mixing diagrams. Dashed lines represent fractions of biogenic gas in mixture. Thermogenic gas is represented by a range of values corresponding to thermal maturity (expressed as vitrinite reflectance, i?0), and biogenic gas is represented by a range of values related to methanogenic pathways (CO2 reduction versus methylotrophic and acetotrophic pathways). (a) Gas dryness and isotopic fractionation between CO2 and CH4 (A13Cco2-CH4)- (f>) Gas dryness and 513C of methane. Data sources: Poland, Str^poc et al. (2010a); Hokkaido, Shimizu et al. (2007); Illinois, Stra^poc et al. (2007); Cook Inlet onshore and Powder River, Strapoc et al. (2010a); Maine Prairie, Cook Inlet offshore, Uinta, and San Juan, this review article. www.annualreviews.org • Biogeockemistry of Coal-Bed Methane 623 cd S o 1 B S o O v ox CO ™ Generation of small amounts of thermogenic gas Habitable temperature Uplift/erosion enable freshwater access Interglacial periods (freshwater influx) Brine dilution and slow inoculation Generation of microbial methane enabled ■ _I_I_i_ 100 10 1 0.1 Age (Ma, log scale) Figure 4 Conceptual diagram depicting uplift and freshwater influx diluting basinal brine and inoculating coals with microbes, yielding recent microbial methane generation. The example shown is from the eastern Illinois Basin. After erosional uplift exposed coals to shallow depths (of less than 300 m) ~5 Ma, slow influx of freshwater was initiated and was followed by a sequence of intense floods by inter- and postglacial melt waters characterized by low 5D values. Influx waters not only introduced the microbes to coals but also created habitable conditions for mesophiles by diluting the original Pennsylvanian basinal brines (which originally had a 2 M chloride concentration). generally resemble Late Pennsylvanian paleofloras, but notable differences include the increased contribution of coniferous plants and the expansion of the distinctive genus of conifers, Glossopteris (Traverse 2008, Taylor et al. 2009). The Early Mesozoic (Triassic and Jurassic) peat-forming communities of North America were dominated by cycads and cycadeoids, and therefore this period is referred to as the age of the cycads. Triassic and Jurassic coals are found on several other continents as well, notably in countries such as Australia and China. Late Cretaceous and Early Tertiary coal floras represent a fundamental change in mire composition; flowering plants (angiosperms) appear 624 Strapoc et al. cd S o 1 3 S o o V for targets that are highly similar to already known gene sequences. Much of the functional "| gene diversity of microbes in the environment remains undescribed. More traditional cloning | and end-sequencing approaches can be used to obtain genetic profiles from microbes for which | no a priori sequence data are available, and a great number of aerobic and anaerobic metabolic > ° genes were detected in San Juan Basin production water in this manner (Toledo et al. 2010). | 3 Nevertheless, survey methods that are based on sampling are susceptible to the typically skewed ■o | abundance class distribution of microbial communities (Figure 16a). This distribution is the 1 S result of the small number of abundant species and the large number of rare species. Sampling- | o based surveys are therefore burdened by the continued reisolation of abundant sequences at the O Q expense of identifying rare species. This phenomenon puts a premium on the ability to perform jg S DNA sequencing faster and cheaper. Both array and cloning technologies, however, are being t~ g rapidly replaced with metagenomic analysis that employs next-generation (NextGen) sequencing ^ o technologies. This is facilitated by the entrance of several companies into the marketplace that « 2 have developed novel and highly cost-effective sequencing approaches. The current leaders in this ° 3i area include Roche's 454 pyrosequencing technology [Roche Applied Science (Margulies et al. & § 2005)], Solexa [Illumina (Bennett 2004)], and Solid [Applied Biosystems (Shendure et al. 2005)]. S The 454 platform is currently the most widely adopted method due to its high fidelity and greater E -° read lengths compared with those of other NextGen technologies. This platform has enabled deeper, more comprehensive microbial surveys to be performed (Figure \6b). Panels c and d of Figure 16 show examples of reproducibility of 16S rRNA gene surveys generated by 454 analyses ^^Supplemental Material Q£ organjc matter-associated environmental samples. To provide an integrated view of microbial Figure IS Phylogenetic trees of 16S rRNA gene sequences of methanogens associated with coal-bed methane from six basins: Ishikari Basin (blue), Powder River Basin (orange), Ruhr Basin (brawn), Cook Inlet Basin (green), Alberta Basin (purple), Illinois Basin (red). See Supplemental Figure 1 for data on non-Proteobacteria bacterial groups; a.-, 5-, and £-Proteobacteria; and y- and p-Proteobacteria (follow the Supplemental Materials link from the Annual Reviews home page at http://www.annualreviews.org). The neighbor-joining dendrogram was generated in PAUP* v.4bl0. Bootstrap values from neighbor joining and maximum parsimony (in that order) are shown for each node. Sequences were aligned using the NAST aligner at http://greengenes.lbl.gov (DeSantis et al. 2006). NAST-aligned sequences were imported into ARB, a graphical software package with database tools for analyzing DNA sequences (Ludwig et al. 2004). Phylogenetic analyses were performed with distance and maximum-parsimony methods using PAUP* v.4bl0 (Swofford 2000). Neighbor-joining trees (neighbor-joining search, jukes-cantor distance, 2,000 bootstrap replicates) were compared against maximum-parsimony consensus trees (heuristic search, 2,000 bootstrap replicates). Abbreviations: str., strain; subsurf. sedim., subsurface sediment. -S 64 0 Straj) oc et al. cd S o 1 B S o O v ox CO Deep-sea sulfidic hydrothermal vent, clone L7A2 (EF644782) Minerotrophicfen, clone MH1492_1E (EU155958) Ishikari, Japan, deep coal, clone SWA01 (AB294257) Methanolobus sp., str. R15 (EF202842) Ishikari, Japan, deep coal, clone YWA05 (AB294253) Ruhr Basin coal mine, clone 103 (AM850103) Qinghai oil field, clone YSSG1 (EF190079) Methanolobus sp., SD1 (identical to EU711413) Methanolobus oregonensis, str. WAL1 (U20152) Anaerobic reactor methanethiol degradation, clone IV-C8 (EU546843) Methanolobus bombayensis, str. B-1 (U20148) Methanolobus vulcani, str. PL-12/M (U20155) Methanosarcina acetivorans, str. C2A (AE010299) Biodegraded Canadian oil reservoir, clone PL-38A6 (AY570681) Powder River Basin coal-bed methane well, clone OTU-2 (EU071164) Powder River Basin coal-bed methane well, clone OTU-1 (EU071157) W.Canada subsurface coal bed, clone821 (EU073821) Ishikari, Japan, deep coal, clone YWA06 (AB294254) Acetate degrading methanogenic consortium, clone DAI 6 (AB092915) Methanosarcina frisia (M59138) Methanosarcina mazei, str. OCM26 (AJ012095) Ruhr Basin coal mine, clone 098 (AM850098) Methanosarcina siciliae, str. C2J (U89773) Ruhr Basin coal mine, clone 095 (AM850095) Ruhr Basin coal mine, clone 101 (AM850101) Ruhr Basin coal mine, clone 093 (AM850093) Methanosarcina sp., HB-1 (AB288262) Methanosarcina barkeri, str.OCM38 (AJ012094) Methanosarcina barkeri (M59144) Methanosarcina barkeri, str. Sar s[C] (identical to AF028692) Anoxic rice field, clone 8-5Ar23 (AY641448) Methanosarcina thermophila (M59140) Methanosarcina lacustris, str. MM (AY260430) Methanosarcina lacustris, str. MS (AY260431) Ruhr Basin coal mine, clone 100 (AM850100) Methanosarcina baltica, str. GS1-A (AJ238648) Japan natural gas field, clone MOB7-4 (DQ841239) Ruhr Basin coal mine, clone 096 (AM850096) Ruhr Basin coal mine, clone 099 (AM850099) Methanosaeta sp., str. 6Ac (AY970347) Ruhr Basin coal mine, clone 102 (AM850102) Japan natural gas field, clone NAK1-a3 (DQ867049) Methanothrix thermophila, str. PT (AB071701) Methanothrix thermophila, str. CALS-1 (M59141) Subsurf. sedim. milieu groundwater, clone HDBW-WA03 (AB237726) Methanocorpusculum parvum (AY260435) Illinois Basin coal bed, clone 242 (EU168242) Biodegraded Canadian oil reservoir, clone PL23-A11 (AY570678) Methanocorpusculum sp., T07 (Ab288279) Anaerobic rice paddy, clone NRP-Pro-A (AB236111) Subsurf. sedim. milieu groundwater, clone HDBW-WA02 (AB237725) Methanoculleus thermophilicus (M59129) Ishikari, Japan, deep coal, clone YWA01 (AB294249) Methanoculleus sp., str. IIE1 (AB089178) Methanoculleus marisnigri, str. CoCam (AF028693) W. Canada subsurface coal bed, clone 823 (EU073823) Methanoculleus chikugoensis, str. MG62 (AB038795) shikari, Japan, deep coal, clone YWA02 (AB294250) Methanoculleus bourgensis, str. NF-1 (DQ150254) Methanoculleus bourgensis, str. CB1 (AB065298) Anaerobic lake sediment, clone SL-Pro (AB236081) Methanoregula boonei, str. 6A8 (NC_009712) Methanosphaerula palustris, str. El -9c (EU156000) W. Canada subsurface coal bed, clone 825 (EU073825) Anaerobic rice paddy, clone TNR-H2-B (AB236090) W. Canada subsurface coal bed, clone 829 (EU073829) W. Canada subsurface coal bed, clone 826 (EU073826) Methanobacterium sp., str. GH (EU333914) Ishikari, Japan, deep coal, clone YWA04 (AB294252) Methanobacterium sp., TS2 (EU366499) Methanobacterium curvum (AF276958) Methanobacterium congolense (AF233586) Methanobacterium formicicum, str. FCam (AF028689) Methanobacterium subterraneum (DQ649330) Ishikari, Japan, deep coal, clone YWA03 (AB294251) Methanobacterium thermoautotrophicum (X68716) Methanobacterium wolfeii, str. DSM 2970 (AB104858) W.Canada subsurface coal bed, clone827 (EU073827) Methanococcusjannaschii, str. DSM 2661 (NC000909) Methanococcus infernus (AF025822) Methanococcus igneus (M59125) Methanococcus aeolicus, str. Nankai-3 (NC_009635) Sulfolobus acidocaldarius (U05018) 3.0 substitutions/site I Ishikari Basin I Powder River Basin I Ruhr Basin I Cook Inlet Basin I Alberta Basin I Illinois Basin www.annualreviews.org • Biogeochemistry of Coal-Bed Methane 641 Figure 16 (a) Rank abundance plot of a 16S rRNA gene-based survey of a microbial community. This survey comprised ~5,000 ribosomal sequence tags, of which 527 tags were unique and were derived from distinct species, (b) Theoretical accumulation plot of a sampling-based survey of a microbial community. The thick red horizontal bar represents the total number (richness) of species present. The horizontal arrows indicate the typical level of coverage achieved with traditional Sanger sequencing versus next-generation (NextGen) technologies, (c) Reproducibility of 16S rRNA gene surveys created with the 454 pyrosequencing technology; each point represents a unique 16S rRNA gene plotted as the number of times detected in two replicate sequencing runs, (d) The same analysis as in panel c, but of a different environmental sample. (a,b) Large onshore petroleum seep. (c,d) Shallow subsurface environmental samples. community metabolism in coal beds, future projects are therefore likely to combine intensive sequencing and bioinformatics efforts with enrichment studies, metabolite profiling, microscopy, and gene expression analysis (mRNA and proteomics). 5.4. Fluorescence In Situ Hybridization FISH is a culture-independent technique for the identification of bacteria and archaea in mixed communities. Oligonucleotide probes hybridize to specific regions of 16S or 23S rRNA in fixed cells. The labeled cells can then be imaged using epifluorescence microscopy. Advantages of this technique include the visualization of complex assemblages, the identification of the actively growing microbial community, and the ability to design probes with a range of taxonomic specificity from domain to species. A relatively recent modification to this method, magneto-FISH, allows Strßpac et al. cd S o 1 3 % g Figure 17 o - Q —; Epifluorescence micrographs depicting major bacterial and archaeal lineages observed in production water samples from the Cook Inlet Basin (Dawson et al. 2010). Probe specificities: EUBmix, all bacteria; Arc915, mostarchaea; Mlob828, genus Methanolobus; SRB385, some Firmicutes and 3-Proteobacteria; DAPI, general DNA stain. Samples were fixed in 1 % (w/v) paraformaldehyde, washed with lx phosphate-buffered saline (PBS), and stored in a 1:1 PBS/ethanol solution at —20°C. FISH experiments were carried out as described in Hugenholtz et al. (2001). (a) Bacterial cells (green) associated with archaeal cells (red), (b) Methanolobus ^ m cells (orange) among other archaeal cells (green) and bacterial cells (blue), (c) Bacterial cells (green) including Firmicutes (orange/red) intertwined with archaeal cells (blue). CO for further isolation of target microorganisms and their physically associated partners (Pernthaler et al. 2008). Several previous studies have identified bacteria and methanogenic archaea associated with the breakdown of coal and the production of methane using both culturing and 16S rRNA cloning (Shimizu et al. 2007, Green et al. 2008, Krüger et al. 2008, Li et al. 2008, Strqpoc et al. 2008, Fry et al. 2009, Dawson et al. 2010, Midgley et al. 2010). These studies provided a first glimpse of the environmental microbes associated with coal beds but did not reflect the relative population sizes of the active bacterial and archaeal populations. FISH can be used to generate a quantitative measure of the population structure of in situ coal-bed communities, as well as to visualize associations between bacterial and archaeal cells such as syntrophic relationships. Information about spatial relationships and community structure derived from FISH provide important clues about the pathways and associated microbial taxa responsible for coal fragmentation, hydrocarbon fermentation, and methanogenesis. Examples of epifluoresence micrographs depicting close spatial associations of bacteria and archaea from the Cook Inlet Basin are shown in Figure 17. Short filamentous and rod-shaped bacterial cells intertwine with Methanosarcina and Methanolobus cocci, forming large clusters of cells. Based upon hybridization to FISH probes, the rod-shaped cells are a mixture of Bacteriodales www.annualreviews.org • Biogeockemistry of Coal-Bed Methane 643 and Acetobacterium, whereas the filamentous cells are a mixture of Firmicutes and other unidentified lineages. Previous studies of methanogenic environments show a similar co-occurrence of methanogens and acetogens (Kotelnikova & Pedersen 1998, Struchtemeyer et al. 2005) or methanogens and sulfate-reducing bacteria (Moser et al. 2005). Investigation of a deep coal seam (Shimizu et al. 2007) revealed clones of the genera Methanolobus, Acetobacterium, and Syntrophus. Thus, FISH provides a visual and quantitative picture of bacterial-archaeal associations and points to the metabolic potential of anaerobes at a studied site. 5.5. Geostatistical Methods of Exploring Microbial Assemblages Microbial assemblages can be also explored by statistical methods. Examples include various types of clustering using microbial population data. Figure 18 shows a 2D cluster analysis (PC-ORD, MjM software; McCune & Grace 2002) of samples from several coal basins and microbial 454 sequence counts. Particular samples, as well as specific microbial individuals, group into clusters, which may reflect their ecological or metabolic associations. For instance, bacterial sequence groupings in a cluster dominated by one type of methanogen reflect the potential association with hydrocarbon-degrading bacteria, which produce the substrates for methanogens (e.g., carbon dioxide/hydrogen-utilizing Methanobacterium). Ordination is another multivariate statistical method for determining the relationship between microbial communities and geochemistry and for extracting dominant patterns in complex data sets (Legendre & Legendre 1998). Nonmetric multidimensional scaling (NMDS) is a robust, unconstrained, nonparametric ordination method that plots similar objects close together in ordination space (Minchin 1987, Legendre & Legendre 1998). NMDS also provides a good method for overlaying environmental data. We used metaMDS in R (The R Project for Statistical Computing, http://www.r-project.org) and the vegan package, based on Kruskal's MDS (Oksanen 2011), using Wisconsin double standardization, where wells were standardized by maxima and then by species by total (Figure 19). The calculated stress is 10; stresses less than 10 are considered to yield reliable results (McCune & Grace 2002). The function envfit (vegan package) was used to overlay environmental factors and to determine the relationship between sequence data and geochemistry (temperature, pH, total dissolved solids, sulfate concentration, and gas carbon iso-topic parameters, <513Cch4 and A13Cco2-ch4)- Ordination of the Polish lignite and Maine Prairie microbial sequence counts form distinct clusters, whereas the Illinois Basin and one of the Powder River samples form a third dominant cluster. The environmental fit analysis shows the associations between geochemical parameters and the NMDS axes. For instance, temperature is the most significant parameter and is strongly correlated with both NMDS axes, with a p value of < 0.001 (based on 1,000 permutations of the environmental fit overlay). The other significant parameters are A13Cco2-ch4, <513Cch4, andTDS. The A13Cco2-ch4 increase in the main Illinois Basin cluster (with a strong negative correlation with NMDS axis 1) is related to the prevalence of CO2 reduction methanogenesis, with a typically high carbon isotopic fractionation between CO2 and CFL- Figure 18 2D cluster of example data set from several coal basins: PL, Polish lignites; PR, Powder River; IB, Illinois Basin; MP, Maine Prairie, California; WG, West Grimes, California. Shades of blue depict abundances of individual sequences: The darker the blue, the greater the abundance. Clustering of wells from the same basins is evident, as is clustering of bacterial groups associated with certain types of methanogens. All sequences of methanogens are labeled with genus name. Phylogenetic affiliation of bacterial sequences is not shown; sequences are labeled with generic numbers starting with the letter T. Some microbial clusters appear to be universally present in most samples (upper part of the diagram), whereas some clusters tend to be basin specific (e.g., bottom right). 644 Strapac et al. Individual wells sampled in 5 basins cd S o 1 B S o O v ox CO Relative sequence abundance Not, , Maximum present abundance Information remaining (%) _I _I _I _I Q_ Q_ Q_ Q_ □ ■ Methanobacterium T014554 T253880 T101700 ■ T101090 □ T101400 T102389 ■ Methanobacterium T024391 ■ Methanobacterium T145163 ■ T150470 T144054 □ T141973 T095307 □ T212871 T145832 T162621 T150545 T109666 T109854 □ T109794 IJ T071538 □ T134153 □ Methanobacterium □ T047137 T190583 T059998 Methanoregula Methanolinea □ T152546 I ] T178752 T143056 T143098 ■ T078076 TO10346 T045795 T010396 □ T193471 □ T252773 T1891 11 T131500 T154046 □ T154214 □ T253796 T086182 T168445 T133979 Methanoregula ■ T033787 ■ T033680 ■ T046179 ■ T142521 T086271 ■ T056172 T052866 T148960 ■ T050056 ■ T156407 ■ T044839 EST140936 T156317 O o- vi 30 www.annualreviews.org • Biogeockemistry of Coal-Bed Methane 645 0.2 6,3Cch4 _I_I_I_I_ -0.1 0.0 0.1 0.2 NMDS1 Figure 19 Nonmetric multidimensional scaling (NMDS) of microbial sequence counts, with an environmental overlay of geochemical parameters. The sample (black) and sequence (orange) identifiers are the same as in Figure 18, except that archaeal sequences here are also coded with generic numbers starting with the letter T. There are three distinct clusters: Polish lignites; Maine Prairie, California; and the Illinois Basin together with Powder River samples. The most significant environmental factors, which are correlated to the ordination axes, are temperature (p value <0.001), separating the cool Polish lignites from the hotter Illinois Basin; A13C (p value = 0.02), distincdy higher in the Illinois Basin, which is dominated by CO2 reduction methanogenesis (high associated carbon fractionation); and total dissolved solids (TDS) (p value = 0.05), highest in Maine Prairie. 6. STIMULATION OF MICROBIAL METHANE GENERATION FROM COAL Multiple researchers have performed methanogenic incubations with coal as a sole carbon source and without hydrogen addition (e.g., Shumkov et al. 1999, Menger et al. 2000, Pfeiffer et al. 2010, Green etal. 2008, Harris etal. 2008, Jones etal. 2008, Krüger etal. 2008, Orem etal. 2010; see also Figure 8 for a summary of published rates obtained from incubations of coal at different maturity ranks). Slow conversion rates often require multimonth or even multiyear incubations to obtain accurate coal-to-methane yields. In other words, in addition to finding out how quickly methane can be generated from coal, we need to ascertain what fraction of coal can be ultimately converted to methane by microbes. The yield will likely also depend on coal maturity. The conversion rates could be potentially improved by the addition of stimulating nutrients, but the ultimate yields might not be significantly improved. Several authors proposed chemical stimulation of methanogenesis from coal (Pfeiffer et al. 2010, Green et al. 2008, Krüger et al. 2008, Toledo et al. Strapoc et al. 2010). Tested nutrient additions included ammonia, phosphate, yeast extract, tryptone, milk, agar, trace metals, and vitamins (e.g., Jin etal. 2007, Pfeiffer etal. 2010). However, the addition of carbon sources other than coal may cause overestimation of the coal-degrading capability of the consortia. Nutrient additions typically applied in laboratory studies are similar to the enrichment media used for the targeted cultivation of specific microbes (for a compilation of growth media and access to numerous archaeal and bacterial isolates, see http://www.dsmz.de/microorganisms). In addition to chemical stimulation of microbial conversion of coal to methane, some authors have suggested and experimented with the addition of selected microbial consortia (e.g., Jin et al. 2007). Examples of consortia used for methanogenic inoculation with coal in laboratory settings include a cultivated consortium indigenous to studied coal (Pfeiffer et al. 2010), a consortium obtained from termite guts (Srivastava & Walia 1998,Menger et al. 2000), and a consortium obtained from an abandoned coal mine used as sewage disposal [Appalachian Basin (Volkwein 1995)]. Several researchers have proposed subsurface enhancement of microbial methane (Scott et al. 1994, Volkwein 1995, Scott 1999, Menger et al. 2000, Budwill 2003, Faiz et al. 2003, Scott & Guyer 2004, Thielemann et al. 2004, Jin et al. 2007). For example, a patent by Menger et al. (2000) suggested digestion of lignite in an underground chamber using termite microflora composed of acid formers and methanogens. Jin et al. (2007) suggested fracturing the reservoir for better simultaneous nutrient delivery and enhanced surface area of coal. The only description of a multiwell field trial was presented in a patent application by Pfeiffer et al. (2010) (see also http://www.lucatechnologies.com). In situ microbially enhanced CBM stimulation performed in the Powder River Basin showed an increase in methane production after nutrient treatment (e.g., phosphate) compared with the expected production decline curve. The addition of microbes preconcentrated from the same formations seemed to stimulate gas production from CBM wells as well. SUMMARY POINTS 1. Extensive review of multiple coal basins suggests that almost any relatively shallow coal bed at present-day temperatures of less than 80°C can contain methanogenic microbial communities capable of generating secondary microbial methane in addition to often preexisting thermogenic gas. Unsterilized, low-maturity coals (lignite and subbitumi-nous coals, as found in, e.g., Powder River and Cook Inlet) are less recalcitrant than higher-maturity coals. Therefore, low-maturity coal cannot be overlooked in coal-bed methane (CBM) exploration. Coals at intermediate maturity (high volatile bituminous) can be accessible and fertile environments as well. These bituminous coals typically have well-developed cleat and fracture systems (e.g., in the Illinois Basin) and therefore are more permeable than lignites. Consequently, larger surface areas are exposed to microbial attack, whereas the organic matter is still molecularly labile enough for microbial attack. However, in these burial-sterilized coals, reinoculation with microbes is likely required. Therefore, more microbial methane can be expected in the flanks of a basin and along the reinoculation paths (e.g., faults, areas with extensive groundwater recharge). Additionally, uplift and long exposure to relatively shallow depths can compensate for slow subsurface methanogenesis rates over geological time. Burial history, in tandem with hydrogeological regimes, can either promote (e.g., northern part of San Juan Basin) or exclude (e.g., southeast Illinois Basin) parts of a basin from microbial methane generation. Coals higher in rank than high volatile bituminous typically are not as favorable for microbial gas generation because of their recalcitrant character, although microbial generation may still occur locally. www.annualreviews.org • Biogeockemistry of Coal-Bed Methane 2. Recent developments in genetic and other microbiological methods enabled deep microbial surveys and detailed metabolic studies that shed light on the deep subsurface ecosystems. Through the use of a combination of molecular and culturing techniques, significant progress has also been made in deciphering the machinery of microbial processing of coal-derived intermediates as well as in gaining an understanding of specific syntrophic associations between bacteria and methanogens. The least-understood processes in coal-to-methane transformation are the initial steps of anaerobic coal degradation. 3. Field-scale stimulation of microbial methane production requires knowledge of the geological history of the basin, the microbial populations present in the subsurface, and the geochemistry of the formation water. Stimulation techniques may include nutrient and microbe additions to enhance rate-limiting steps of coal biodegradation. Present-day generation of microbially enhanced CBM as a large natural gas resource remains to be evaluated in terms of rates, yields, and economic feasibility. Recent laboratory results and initiation of large-scale field trials may provide answers in upcoming years. FUTURE ISSUES Although much progress toward understanding microbial gas systems has been made in the past decade, many questions remain to be answered before this resource can be adequately explored and subsequently utilized. 1. What fraction of coal can be ultimately converted to methane by microbes? To what extent does maceral composition of coal influence microbial gas generation, and what makes a maceral more microbial methane prone? Is it possible, with analogy to thermogenic gas, to define a coal of a specific rank to be the best candidate for microbial gas generation? Or could a combination of rank and maceral composition perhaps be such a predictor? What role, if any, does mineral matter in coal play in microbial gas generation? 2. The initial steps of coal degradation need to be elucidated. Future developments in transcriptomics (mRNA) and proteomics (produced proteins), as well as the analyses of high-molecular-weight intermediates and extracellular enzymes, could shed light on the rate-limiting initial steps in coal biodegradation steps as well as on the entire cascade of reactions from coal to methane. 3. How can we better apply our laboratory discoveries to aid field-scale microbial methane stimulation? What are the limiting factors: access to large volumes or surfaces of kerogen, accommodation space, delivery of nutrients, and/or inherently slow rates of subsurface metabolism? Are the stimulated subsurface coal-to-methane rates using nutrients and specialized microbes high enough to convert vast global coal reserves into long-lived, microbially regenerating gas resources? DISCLOSURE STATEMENT C.T. is a ConocoPhillips stockholder; M.A. has significant stock holdings in Taxon Biosciences, Inc., which conducts activities in this field. Strcipoc et al. ACKNOWLEDGMENTS We thank Maxine Jones (ConocoPhillips) for preparation of biocoal samples. ConocoPhillips allowed access to formation water and gas samples from CBM fields. In particular, Rick Levinson provided field work assistance. Additionally, Mike Maler and Brad Huizinga (both ConocoPhillips) provided critical support. 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Chin ............................................. Deep Mantle Seismic Modeling and Imaging Thome Lay and Edward J. Garnero ........................................................ Using Time-of-Flight Secondary Ion Mass Spectrometry to Study Biomarkers Volker Thiel and Peter Sjovall .............................................................1 Hydrogeology and Mechanics of Subduction Zone Forearcs: Fluid Flow and Pore Pressure Demian M. Saffer and Harold J. Tobin ..................................................1 Soft Tissue Preservation in Terrestrial Mesozoic Vertebrates Mary Higby Schweitzer ....................................................................1! The Multiple Origins of Complex Multicellularity Andrew H. Knoll ............................................................................2 Paleoecologic Megatrends in Marine Metazoa Andrew M. Bush and Richard K. Bambach ...............................................2- Slow Earthquakes and Nonvolcanic Tremor Gregory C. Beroza and Satoshi Ide ........................................................2 Archean Microbial Mat Communities Michael M. Tice, Daniel C. 0. Thornton, Michael C. Pope, Thomas D. Olszewski, andjian Gong ..................................................2' Uranium Series Accessory Crystal Dating of Magmatic Processes Axel K. Schmitt .............................................................................3. Vlii A Perspective from Extinct Radionuclides on a Young Stellar Object: The Sun and Its Accretion Disk Nicolas Dauphas and Marc Chaussidon ...................................................351 Learning to Read the Chemistry of Regolith to Understand the Critical Zone Susan L. Brantley and Marina Lebedeva .................................................387 Climate of the Neoproterozoic R.T. Pierrehumbert, D.S. Abbot, A. Voigt, and D. Roll .................................417 Optically Stimulated Luminescence Dating of Sediments over the Past 200,000 Years so 0 Edward J. Rhodes ...........................................................................461 % S The Paleocene-Eocene Thermal Maximum: A Perturbation of Carbon •| Cycle, Climate, and Biosphere with Implications for the Future | Francesca A. Mclnerney and Scott L. Wing ...............................................489 | g Evolution of Grasses and Grassland Ecosystems | § Caroline A.E. Stromberg ...................................................................517 s o Rates and Mechanisms of Mineral Carbonation in Peridotite: .2 & Natural Processes and Recipes for Enhanced, in situ CO2 Capture 1 (2 and Storage ko C Peter B. Kelemen, Juerg Matter, Elisabeth E. Streit, John F. Rudge, ^? § William B. Curry, andjerzy Blusztajn .................................................545 ^ o a ° Ice Age Earth Rotation ~~ Jerry X. Mitrovica and John Wahr .......................................................577