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Applied and Environmental Microbiology, December 2005, p. 8191-8200, Vol. 71, No. 12
0099-2240/05/$08.00+0 doi:10.1128/AEM.71.12.8191-8200.2005
Copyright © 2005, American Society for Microbiology. All Rights Reserved.
Max Planck Institute for Terrestrial Microbiology, D-35043 Marburg, Germany
Received 12 April 2005/ Accepted 10 August 2005
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Although countless CH4 fluxes have been measured in northern peatlands (42, 49), little is known about methanogenic substrates and the dominating biochemical pathways. In general, H2-CO2 and acetate are the preferred substrates for methanogenesis. With carbohydrates as the main substrate, about two-thirds of the CH4 produced in nature should originate from acetate (8). In a northern peatland (Alaska, 60°N), acetate was found to be an end product that was not used at all by methanogens (12, 26). In contrast, acetoclastic methanogenesis accounted for up to 85% of the methanogenesis in a temperate peatland (42°N, Michigan), but there were large seasonal fluctuations (2).
Significant microbiological and physiological work has been done for temperate bogs (27), but we are not aware of a study of northern peatlands examining the methanogenic community, substrate usage, and the effect of temperature. In minerotrophic mires, Fe reduction may compete with methanogenesis for substrates. Hence, we focused on (i) methanogenesis and Fe(III) reduction, (ii) the carbon substrates and biochemical pathways involved, and (iii) the structure of the methanogenic community. Our experiments were conducted with acidic peat from a mire in northern Finland (68°N) and covered the temperature range from 4°C to 60°C in 2°C steps. We combined culture-independent approaches with process measurements. In a pilot study we became aware that ethanol was a major intermediate in the samples, and the concentrations were up to 10.5 mM. Methanogens are virtually unable to use primary alcohols (62), but they may take advantage of the H2 released during anaerobic oxidation of ethanol (32, 51, 59). To determine the most probable pathways involved in anaerobic ethanol oxidation, we combined inhibitor experiments with mass balance and thermodynamic calculations.
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Incubation.
The peat samples were diluted 1:1 (vol/vol) with O2-free autoclaved distilled water and blended. The resulting slurries (8 ml) were placed into sterile test tubes (16 ml), which were closed with butyl rubber stoppers and capped. All handling was done in an anaerobic box under an N2 atmosphere. The slurries were incubated in a custom-made temperature gradient block that was heated at one end and cooled at the other (28, 54). The gradient covered the range from 4°C to 60°C in 2°C steps. Two replicates per temperature were incubated for 4 weeks. The headspace concentrations of CH4 and CO2 were measured up to three times per week after shaking to equilibrate the gas and liquid phases. The concentration of H2 in the headspace was measured at the end of the experiment. Pore water samples were taken at the beginning and at the end of the experiment and were analyzed for fatty acids and alcohols. Similarly, slurry samples were taken to measure Fe(II) concentrations.
Acetoclastic methanogenesis was determined by inhibition with methyl fluoride (CH3F) (final mixing ratio, 1%), a specific inhibitor of acetoclastic methanogenesis (16, 29). An oxygen-free solution of sodium 2-bromoethanesulfonate (BES) (final concentration, 40 mM) was used to completely inhibit methanogenesis. In a pilot experiment with acidic peat a BES concentration of 40 mM was found to be necessary to inhibit methanogenesis completely. Two replicates were incubated for 4 weeks at 4, 10, 15, 25, 30, 37, and 45°C.
At temperatures between 15 and 30°C, the CH4 concentration increased linearly until day 15 to 20. After this, the rate of CH4 production decreased. At lower and higher incubation temperatures, the increase was linear with time during the whole incubation period (1 month). Hence, CH4 production was calculated (i) from the linear part of the curves by regression analysis (termed "rate") and (ii) from the amount of CH4 that accumulated until the end of the experiment after 1 month (termed "accumulation").
Analytical techniques.
CH4 and CO2 were analyzed with a gas chromatograph with a flame ionization detector (SRI-9300; SRI Instruments, Torrance, Calif.) with H2 as the carrier gas; the instrument was equipped with a custom-made methanizer with an Ni-based catalyst. Calibration was done with certified standards (Messer-Griesheim, Krefeld, Germany). H2 was analyzed with a gas chromatograph equipped with a temperature-conductivity detector (SRI-9300; SRI Instruments, Torrance, Calif.) with N2 as the carrier gas.
Liquid samples were filtered through 0.2-µm membrane filters (Schleicher & Schuell, Dassell, Germany) and stored at 20°C until analysis. Organic acids (lactate, formate, acetate, propionate, butyrate, and caproate) were measured by high-performance liquid chromatography on an Aminex HPX-87H ion exclusion column (Bio-Rad Laboratories, Hercules, Calif.) with a refraction index detector (RI2000; Sykam, Gilching, Germany) and a UV detector (UVIS 205; Linear Instruments, Reno, Nev.). Acetone, methanol, propanol, 2-propanol, butanol, 2-butanol, and ethanol were measured by using a gas chromatograph equipped with a flame ionization detector (Carlo Erba 8000) and a BP 20 column (inside diameter, 0.32 mm; length, 25 m; 0.5 µm; SGE, Austin, Tex.) with 1-pentanol as an internal standard (final concentration, 10 mM). Chromatograms were analyzed with the Peak Simple software (SRI Instruments, Torrance, Calif.).
Samples used for Fe(II) analysis were taken from a peat slurry at the beginning and end of incubation at 4, 10, 15, 25, 30, 37, and 45°C (with and without BES). Fe(II) was extracted with 0.5 M HCl and measured as described by Phillips and Lovley (44), as modified by Ratering and Schnell (45).
DNA extraction and PCR amplification.
Slurries samples were obtained at the beginning of the experiment and after 4 weeks of incubation at 4, 10, 15, 25, 30, 37, and 45°C. The samples were homogenized with a pestle and mortar to break up macroscopic peat structures. DNA was extracted with a FastDNA SPIN kit for soil used according to the manufacturer's instructions (Qbiogene, Carlsbad, Calif.). To remove PCR-inhibiting compounds (mainly humic acids) from the extract, two further washing steps with guanidine thiocyanate (5.5 mM; Sigma) were necessary.
Archaeal 16S rRNA genes were amplified using primers Ar109f and Ar915r or Ar915r labeled at the 5' end with 6-carboxyfluorescein (56) (MWG Biotech, Ebersberg, Germany). The PCR was performed as follows: 30 s at 94°C, 45 s at 53°C, and 1.5 min at 72°C for 32 cycles, a primary denaturation step consisting of 3 min at 94°C, and final DNA synthesis for 5 min at 72°C. The gene encoding the
-subunit of the methyl-coenzyme M reductase was amplified using primers ME1 and ME2 (24) (MWG Biotech, Ebersberg, Germany). The PCR was performed as follows: 45 s at 94°C, 45 s at 50°C, and 1.5 min at 72°C, a primary denaturation step consisting of 3 min at 94°C, and final DNA synthesis for 5 min at 72°C. PCR products were purified with a QIAquick PCR purification kit (QIAGEN, Hilden, Germany).
For real-time PCR, DNA was extracted and purified as described above and was quantified using the PicoGreen assay (40). Archaeal small-subunit rRNA genes were quantified by real-time PCR by using an iCycler iQ real-time PCR system (Bio-Rad, Munich, Germany) and primers Ar109f and Ar915r (23).
T-RFLP analysis.
Terminal restriction fragment length polymorphism (T-RFLP) analysis was performed as described previously (6). In short, purified 16S rRNA gene fragments were quantified by UV photometry (Biophotometer; Eppendorf, Hamburg, Germany). The fluorescently labeled PCR products (70 ng) were digested with TaqI (Promega, Mannheim, Germany) and analyzed with an ABI PRISM 373 DNA sequencer (Applied Biosystems, Weiterstadt, Germany). The electropherograms were analyzed with GeneScan, version 2.1 (Applied Biosystems). Relative amplicon frequencies were determined by determining relative signal intensities of terminal restriction fragments (T-RFs) from peak heights (40). Signals with a peak height that was less than 100 relative fluorescence units were regarded as background noise and excluded from the analysis. The percentages of fluorescence intensity represented by single T-RFs were calculated relative to the total fluorescence intensity of all T-RFs.
Cloning, sequencing, and phylogenetic analysis.
Gene libraries for archaeal 16S rRNA and mcrA sequences were constructed using DNA extracts from the original peat sample. PCR products were ligated into pGEM-T vector plasmids (Promega, Mannheim, Germany) and transformed into Escherichia coli JM109 competent cells (Promega, Mannheim, Germany) according to the manufacturer's instructions. 16S rRNA genes were directly amplified with the archaeon-specific primers Ar109f and Ar915r. The resulting amplicons were restricted with TaqI. Plasmid DNA was sequenced with an automated ABI Prism BigDye terminator cycle Ready Reaction kit with AmpliTaq polymerase FS (Applied Biosystems) according to the manufacturer's instructions using primers M13 rev-29 (5'-CAGGAAACAGCTATGACC-3') and T7 (5'-TAATACGACTCACTATAGGG-3'). 16S rRNA gene and mcrA sequences were assembled with SeqMan II (DNASTAR) and compared with the sequences available in the GenBank database using the BLAST network service to determine the approximate phylogenetic affiliations. Chimeric sequences of 16S rRNA genes were identified by Chimera Check of Ribosomal Database Project II (release 8.1) (7). Alignment and phylogenetic analysis of 16S rRNA gene sequences were done with ARB (38). Additional sequences that were potentially related to the retrieved clones were added to the existing tree using the ARB parsimony tool. 16S rRNA gene sequences (>790 bases) were selected to construct an archaeal base frequency filter (50 to 100% similarity), which was subsequently used to generate an initial maximum-likelihood tree with the Treepuzzle tool (10,000 puzzling steps; Schöniger-von Haeseler substitution model [52]; parameter estimation uses, neighbor-joining tree). In addition, the tree topology was evaluated using neighbor joining (Felsenstein distance correction), Phylip DNAPARS, and AxML as implemented in ARB. Aquifex pyrophilus was used as the outgroup.
An mcrA sequence database was constructed with 505 sequences which are publicly available from NCBI (http://www.ncbi.nlm.nih.gov/). The partial mcrA sequences obtained were assembled and checked with the LASERGENE software package (DNASTAR). After translation and alignment of the resulting amino acid sequences, an initial tree was constructed by neighbor joining with the PAM correction. Our sequences were added by quick add parsimony as implemented in ARB. For treeing, 85 McrA sequences were selected to construct a base frequency filter (25 to 100% similarity; 134 valid columns) (39), which was subsequently used to generate a maximum-likelihood tree with the Treepuzzle tool (1,000 puzzling steps; WAG substitution model [61]; parameter estimation by neighbor-joining tree). In addition, the tree topology was verified by PROTPARS (maximum parsimony) and PROTDIST with FITCH as the distance matrix, both from the PHYLIP package (version 3.573c; J. Felsenstein, University of Washington; http://evolution.genetics.washington.edu/phylip.html), and by neighbor joining with the PAM correction (ARB). Methanopyrus kandleri was used as the outgroup (accession no. AF414042).
Thermodynamic calculations.
Thermodynamic calculations were done for all of the reactions shown in Table 1 except ethanol oxidation with Fe(III) as the e acceptor. Because the concentration and speciation of Fe(III) were not known, no calculation was possible. Standard Gibbs free energies (
G0) were calculated from the standard Gibbs free energies of formation (Gf0) of the reactants and products (58) (Table 1). The standard reaction enthalpies (
H0) were calculated from the enthalpies of formation (Hf0) of the reactants and products (10, 11, 34).
G0 values were corrected for temperature by using the Van't Hoff equation (10). The actual Gibbs free energy (
G) under nonstandard conditions was calculated by using the Nernst equation (10). H2, CH4, and CO2 were assumed to be gases. All other compounds were assumed to be dissolved. The concentrations and partial pressures that were actually measured were used to calculate
G at the beginning and end of the experiment. For H2 we had only endpoint measurements. We assumed a steady-state situation with constant partial pressures throughout the experiment and combined all measurements into one graph. For calculations we used values interpolated by a kernel-weighted regression of H2 against temperature (SYSTAT, version 11) (see Fig. 1).
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TABLE 1. Stoichiometries and Gibbs free energies for processes relevant for ethanol, acetate, and CH4 turnover
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FIG. 1. Accumulation of CH4 and fraction of CH4 produced from H2-CO2. (Left panel) Fraction of CH4 calculated from the initial rates with and without CH3F. (Right panel) H2 partial pressures after 1 month of incubation at different temperatures. The line indicates the overall trend calculated with a kernel-weighted regression. gDW, grams (dry weight).
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The lowest H2 partial pressures (4 Pa; 0.06 µmol g [dry weight]1 · day1) were observed at temperatures around the optimum temperature for methanogenesis (Fig. 1). At the lowest and highest temperatures, the H2 partial pressures were much higher (200 and 2,000 Pa at 4°C and 45°C, respectively). CO2 accumulated over the whole temperature gradient and particularly under nonmethanogenic conditions at temperature up to 60°C (Fig. 2). The increase was nonlinear and slowed with time.
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FIG. 2. CO2 accumulation after 1, 6, 12, 20, and 27 days. gDW, grams (dry weight).
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1.5 µM) at temperatures between 4 and 50°C, but it increased at higher temperatures at a rate of up to 40 µmol · g (dry weight)1 · month1 in the control experiment (data not shown). In the physiological temperature range, however, acetate and butyrate were the most important volatile fatty acids, and they accumulated at rates of 38 and 50 µmol · g (dry weight)1 · month1, respectively, at the optimum temperatures (Fig. 3).
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FIG. 3. Net turnover of Fe(II), ethanol, acetate, and butyrate (µmol · g [dry weight]1 · month1) with and without BES. A negative value indicates net consumption, and a positive value indicates accumulation. The slight ethanol accumulation at temperatures above 50°C is obscured by the symbols. CH4 concentrations (Fig. 1) are included for comparison. gDW, grams (dry weight).
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The actual Gibbs free energies of CH4 formation from both H2-CO2 and acetate were exergonic over the whole temperature range (Fig. 4). The
G for the oxidation of ethanol was negative at all temperatures. The
G values for homoacetogenesis were negative only at low and high temperatures.
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FIG. 4. Gibbs free energies under in situ conditions calculated with the initial and final concentrations. A, homoacetogenesis; B, syntrophic ethanol oxidation; C, butyrate synthesis; D, acetoclastic methanogenesis; E, hydrogenotrophic methanogenesis; F, ethanol oxidation to acetate and CH4. See Table 1 for stoichiometries.
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Structure and quantification of the archaeal community.
The T-RF frequencies were almost constant at temperatures between 4 and 30°C. At 37 and 45°C, the archaeal population became less diverse. When the experiment began, 60% of all T-RFs exhibited a 92-bp fragment, and 20% exhibited a 184-bp fragment. After 1 month of incubation the 92-bp fragment was still the most abundant T-RF at all temperatures (60 to 80%). The 184-bp fragment occurred only at temperatures between 4 and 30°C (frequency, 10 to 20%) (Fig. 5).
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FIG. 5. Compositions and percentages of terminal restriction fragments in the field sample (A) (from two extractions) and after 1 month of incubation at different temperatures (B).
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FIG. 6. Maximum-likelihood tree for the 16S rRNA gene. The tree was constructed using the Treepuzzle tool as implemented in ARB. Sequences obtained in this study are indicated by boldface type. Because the corresponding clone sequences formed a coherent cluster, they were merged into one branch. Scale bar = 10% sequence divergence. The values at the nodes are Treepuzzle support values.
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FIG. 7. Maximum-likelihood tree for McrA. Sequences obtained in this study are indicated by boldface type. Scale bar = 10% sequence divergence. The values at the nodes are Treepuzzle support values. Methanopyrus kandleri was used as the outgroup (not shown).
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FIG. 8. Quantitative PCR with primers for the archaeal and bacterial 16S rRNA genes. The numbers of targets at the start of the experiment (horizontal lines) are compared to the numbers of targets recovered after 1 month of incubation at different temperatures (means ± standard errors; n = 9 to 28). gDW, grams (dry weight).
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Reactants and processes.
Part of the ethanol available at the beginning of our experiment may have been released from thefine roots collected together with the peat. However, a wide range of eukaryotic and prokaryotic microorganisms are able to produce ethanol under anoxic conditions (47) and may have provided the larger part of the ethanol. Ethanol fermentation is the physiological response of plants to hypoxia. Anaerobiosis becomes even more demanding in the dark, when enhanced ethanol release from submersed roots may occur (60). Hence, a supply of ethanol to a wetland soil or peat may be considered a natural process.
The molar ratio for ethanol consumption and CH4 accumulation was 4:1 at 25°C (Fig. 3). Direct utilization of ethanol by methanogens is quite unusual (66). Only the thermophilic marine isolate Methanogenium organophilum is known to grow on primary alcohols other than methanol, but the growth is less efficient than that on secondary alcohols (62, 63). More common is the syntrophic ethanol oxidation to acetate (Table 1) that may be coupled to different hydrogen-scavenging partners (32, 50, 59).
Direct oxidation of ethanol and hydrogenotrophic methanogensis were exergonic for both the initial and final conditions (after 4 weeks of incubation) (Fig. 4). The syntrophic oxidation of ethanol to acetate and H2 became less favorable at the end of incubation, mainly at temperatures around the optimum temperature (Fig. 4). This agrees with a decrease in the CH4 production rate with time, as observed in the temperature range between 15 and 30°C. In addition, the high concentrations of acetate (6 mM) and butyrate (5 mM) that accumulated at the optimum temperature may have inhibited CH4 production due to the formation of undissociated acids, as found in other acidic peats (27, 64). When preparations are treated with BES, the methanogenic precursors should accumulate with time, but the net accumulation of acetate was even lower withBES (Fig. 3). This observation is consistent with syntrophic ethanol oxidation to acetate that is suppressed when H2 is no longer consumed by methanogens.
The theoretical molar ratio of ethanol to CH4 is 2:1 for both direct and syntrophic ethanol oxidation (Table 1), but the observed ratio was 4:1 at 25°C (Fig. 3). Assuming that CH4 originated completely from H2 derived from ethanol, at least 50% of the ethanol consumed must have entered another metabolic pathway.
Fe(III) may be formed even below the water table in an otherwise anoxic environment, if O2 is released from plant roots (14). Fe(III) may accumulate at levels high enough to suppress methanogenesis for a prolonged time (17). However, CH4 production started at the beginning without a lag. Fe(II) accumulated at all temperatures and accumulated optimally at 25°C, the optimum temperature for methanogenesis (Fig. 4). The accumulation of up to 350 µmol Fe(II) · g (dry weight)1 ·month1 makes iron reduction a candidate for the missing ethanol sink. Theoretically, 4 mol Fe(III) is reduced per mol ethanol consumed (Table 1) (36). Fe(III)-reducing microorganisms may suppress methanogenesis competing for H2 (1, 8) or acetate (17), and methanogens themselves may divert electrons via extracellular quinones to Fe(III) (4). By reducing Fe(III), methanogens may metabolize H2 to levels that make CH4 production thermodynamically unfavorable (37). However, methanogenesis and Fe(III) reduction proceeded in parallel (Fig. 3), and conditions were permissive for hydrogenotrophic and acetoclastic methanogenesis at the beginning and end of the experiment (Fig. 4). The BES concentration used in the inhibition experiment was high, but it was necessary to inhibit methanogenesis completely, as found in a previous dose-response experiment (data not shown) and in pure cultures (67). Provided that BES had no nonspecific effect on Fe(III)-reducing microorganisms, Fig. 3 suggests that CH4 production and Fe(III) reduction were linked.
Corresponding to the consumption of ethanol, equimolar accumulation of acetate was expected (Table 1), but this was not observed (Fig. 3). Inhibition with CH3F showed that acetoclastic methanogenesis accounted for 20% of the total methanogenesis and hence consumed some of the missing acetate. However, the concurrent accumulation of butyrate (Fig. 3) led us to suggest that most acetate was converted to butyrate (Table 1). This suggestion was supported by thermodynamic (Fig. 4) and mass balance calculations (Fig. 9) (see below). Interestingly, no butyrate accumulated with BES (Fig. 3), while it was expected to accumulate if it was used as a syntrophic substrate. Similarly, no butyrate accumulated in a rice field soil amended with 20 mM BES (20). However, fermentative butyrate formation seems not to be inhibited by BES, at least when the carbon supply is high (20).
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FIG. 9. Pathways proposed from the balance between the initial and final concentrations of substrates and products at 25°C and 4°C. The concentrations for pools (rectangles) are expressed in µmol · g (dry weight)1, and the flow rates are expressed in µmol · g (dry weight)1 · month1. The negative and positive numbers in the rectangles indicate net consumption and accumulation, respectively. The rhombuses represent the reactions, and the lowercase letters in the rhombuses indicate the following reactions: a, CH3CH2OH + H2O CH3COO + 2H2 + H+; b, CH3CH2OH + 4Fe3+ + H2O CH3COO + 4Fe2+ + 5H+; c, CH3COO + 8Fe3+ + 2H2O 2CO2 + 8Fe2+ + 7H+; d, 2CH3COO + H+ + 2H2 CH3(CH2)2COO +2H2O; e, CH3COO+ H+ CH4 + CO2; f, 4H2 + CO2 CH4 + 2H2O. The negative and positive numbers associated with the arrows indicate the amount of substrate leaving a pool and entering a reaction and the amount of product entering the subsequent pool, respectively. The question marks indicate an unknown source or sink.
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CO2 accumulation and hence overall mineralization even increased at temperatures above 35°C, when methanogenesis and net population growth of archaea decreased (Fig. 1, 2, and 8). A similar uncoupling of microbial growth and activity at nonphysiologically high temperatures has been found in upland soils (44a). Abiotic CO2 production linked to Fe reduction has been found in vitro at a very low pH (44b), but whether this occurs under in situ conditions is not known. In our experiment, Fe could be ruled out as an e acceptor, because Fe(II) accumulation decreased to nearly zero at temperatures above 35°C (Fig. 3). In addition, H2 (Fig. 1) accumulated in the same temperature range together with formate (data not shown). The peat never experiences temperatures as high as 50°C in situ, and organisms that might be involved in this activity are totally unknown.
Structure and quantification of the archaeal community.
Altogether, the diversity of archaeal 16S rRNA gene clones was low. More than one-half of the 16S rRNA gene clones clustered with uncultured Crenarchaeota (data not shown). Crenarchaeota are a diverse class of microorganisms which also occur in peatlands (30, 43). Because their physiology is mostly unknown, a detailed discussion of the phylogenetic affiliation would not contribute to our understanding of metabolic pathways.
Most of the other sequences were related to the Methanobacteriales, which use only H2 or formate as an e donor. They were closely affiliated with the type strain of Methanobacterium bryantii (Fig. 6), which was isolated from a syntrophic ethanol-oxidizing coculture of "Methanobacterium omelianskii" (5). The ability to utilize ethanol directly for CH4 production is known for Methanogenium organophilum, a member of the Methanomicrobiales. However, none of the clones could be affiliated with the Methanomicrobiales. These results indicate that syntrophic instead of direct ethanol oxidation was the prevailing process. Confirming this further, the McrA sequences clustered in the Methanobacteriaceae (Fig. 7). The phylogenetic affiliations of the clones were the same with all treeing methods applied.
The 16S rRNA gene-based T-RFLP patterns shown in Fig. 8did not indicate any temperature-dependent change in the population structure. The 92-bp T-RF, which exhibited the highest relative abundance, could be assigned to the 16S rRNA gene clone sequences clustering with the order Methanobacteriales (Fig. 6), corresponding to the high proportion of hydrogenotrophic methanogenesis. Real-time PCR showed that there was conspicuous temperature-dependent net population growth. The levels of both archaeal and bacterial targets were highest at 25°C, in accordance with the optimum temperature for CH4, ethanol, and Fe turnover.
Balance calculations.
We suggest that at 25°C the ethanol pool was split into the following two main branches: (i) syntrophic oxidation of ethanol in cooperation with methanogens, which was confirmed by thermodynamic calculations and was supported by phylogenetic analysis, and (ii) oxidation of ethanol by Fe(III) reduction (Fig. 9). Hydrogenotrophic methanogenesis contributed 80% of the total methanogenesis. Hence, a minor fraction of acetate was consumed by acetoclastic methanogenesis, while butyrate synthesis accounted for the larger fraction. The in situ conditions were thermodynamically favorable for all the processes mentioned above (Fig. 4).
We are aware of the limitations of this approach, which does not account for the ongoing production of fermentation products (e.g., ethanol and acetate). However, because of the large amount of ethanol that was available at the beginning of the experiment, this may be a minor problem. However, we cannot decide if the ethanol was consumed directly by Fe-reducing bacteria (36) or indirectly via an interspecies H2 transfer to Fe-reducing bacteria or by a drain of reducing equivalents from methanogens via extracellular electron shuttles to Fe(III) (4). In summary, the proposed split of the ethanol pool at 25°C into two main branches was strongly supported by the balance between ethanol and the end products (Fig. 9). Some H2 needed for butyrate synthesis lacks in the balance, but the flow of carbon is fairly well constrained.
At 4°C the substrate flow was different (Fig. 9). The net production of Fe(II) was negligible (Fig. 3). The balance of ethanol and acetate agreed well with the proposed syntropohic ethanol oxidation. This was further supported by thermodynamic calculations (Fig. 4). However, the balance cannot account for the H2 produced (Fig. 9). One may speculate that organic matter (humin) acted as an electron acceptor, but we have no evidence for this yet. Similarly, humin may be the unknown electron donor at 25°C (Fig. 9).
In summary, the microbial populations were well adapted to low temperatures, as evident from the high activity and the theoretical lower temperature limit for methanogenesis, 5°C. Ethanol played a major role in the flow of carbon and reductants. Syntrophic oxidation to acetate was the key process leading to CO2 reduction at all temperatures. At low temperatures, most H2 resulting from ethanol oxidation ended up in CH4, while at the optimum temperature an equal amount was used to reduce Fe(III). According to the T-RFLP analysis and clone libraries, the peat methanogens were affiliated with the Methanobacteriales. Some lines of evidence led us to speculate that methanogens may be involved in Fe reduction. The archaeal diversity was not affected by temperature even when population growth occurred, suggesting that the archaeal population was remarkably resistant to perturbations. The close correspondence between structure and function is exciting, but the following challenge for future work remains: to go beyond analysis of structure and function and to explain why a population exists at a particular site but not at other sites.
This study was supported by a grant from the Deutsche Forschungs Gemeinschaft (SFB 395, "Interaction, Adaptation and Catalytic Capabilities of Microorganisms in Soil").
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13C values of pore water methane in a Michigan peatland. Global Biogeochem. Cycles 13:475-484.
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