Research Article
9 September 2014

Gammaproteobacterial Methanotrophs Dominate Cold Methane Seeps in Floodplains of West Siberian Rivers

ABSTRACT

A complex system of muddy fluid-discharging and methane (CH4)-releasing seeps was discovered in a valley of the river Mukhrinskaya, one of the small rivers of the Irtysh Basin, West Siberia. CH4 flux from most (90%) of these gas ebullition sites did not exceed 1.45 g CH4 h−1, while some seeps emitted up to 5.54 g CH4 h−1. The δ13C value of methane released from these seeps varied between −71.1 and −71.3‰, suggesting its biogenic origin. Although the seeps were characterized by low in situ temperatures (3.5 to 5°C), relatively high rates of methane oxidation (15.5 to 15.9 nmol CH4 ml−1 day−1) were measured in mud samples. Fluorescence in situ hybridization detected 107 methanotrophic bacteria (MB) per g of mud (dry weight), which accounted for up to 20.5% of total bacterial cell counts. Most (95.8 to 99.3%) methanotroph cells were type I (gammaproteobacterial) MB. The diversity of methanotrophs in this habitat was further assessed by pyrosequencing of pmoA genes, encoding particulate methane monooxygenase. A total of 53,828 pmoA gene sequences of seep-inhabiting methanotrophs were retrieved and analyzed. Nearly all of these sequences affiliated with type I MB, including the Methylobacter-Methylovulum-Methylosoma group, lake cluster 2, and several as-yet-uncharacterized methanotroph clades. Apparently, microbial communities attenuating methane fluxes from these local but strong CH4 sources in floodplains of high-latitude rivers have a large proportion of potentially novel, psychrotolerant methanotrophs, thereby providing a challenge for future isolation studies.

INTRODUCTION

Methane (CH4) is an important greenhouse gas responsible for about 20% of the warming induced by long-lived greenhouse gases (1, 2). Since the beginning of the Industrial Era, the atmospheric CH4 concentration has increased by a factor of 2.5 (2). A sustained increase in atmospheric CH4 levels in the 1980s was followed by a slowdown in the increase in the 1990s and a general stabilization from 1999 to 2006. Since 2007, CH4 levels have been rising again (3), indicating a recent imbalance between CH4 sources and sinks that is not yet fully understood (1, 4). The global methane emission is currently estimated between 550 and 678 Tg year−1 (1, 2). Natural wetlands are the largest source of atmospheric methane, contributing 175 to 217 Tg CH4 year−1 (1, 2). The second-largest natural source is geologic methane, which is emitted from coal beds, natural gas deposits, and gas hydrates. Recent estimates appraise the total methane emitted naturally from all geologic sources at more than 50 Tg year−1 and potentially approaching 80 Tg year−1 (5). The emission of geologic CH4 occurs from seepage, including microseeps, terrestrial macroseeps, geothermal/volcanic emissions from the Earth's crust, and marine seeps. Microseepage is the slow, diffuse loss of CH4 over wide areas on the order of 100 to 102 mg m2 day−1. Macroseeps are localized flows and gas vents, both on land and on the seafloor, which emit up to 102 tons CH4 year−1, while mud volcanoes represent the largest visible expression of geologic methane emission, producing flows of up to 103 tons CH4 year−1 (6, 7, 8). Major emissions are related to natural fossil methane formed in sedimentary basins (both microbial and thermogenic methane) and, subordinately, to geothermal areas (5).
The global seepage area and the number of seep sites on different continents remain uncertain. Thus far, mud volcanoes and microseepage in low-latitude countries, such as Italy, Greece, Romania, Azerbaijan, and Taiwan, have received the most research attention (7, 9, 10). Recently, however, 77 previously undocumented fossil seep sites, comprising more than 150,000 vents to the atmosphere, were mapped in Alaska (11). These seeps were characterized by anomalously high fluxes of methane (up to 8 tons CH4 site−1 day−1) and were located in regions of permafrost thaw and receding glaciers. Gases emanating from these seeps were mainly thermogenic in origin. In Greenland, Walter Anthony and colleagues (11) documented a number of seep sites associated with younger methane, originating from the decomposition of organic matter and located in zones of ice sheet retreat. These findings indicate that geologically sourced methane emissions may well increase as ice sheets, glaciers, and permafrost melt (12, 13).
Our knowledge of the microbiology of terrestrial methane vents is by far less advanced than that of marine methane seeps. Most of the currently available information was obtained for mud volcanoes in countries with warm climates (1416). The only exception is a study on microbial community composition in a hypersaline methane seep in the Canadian High Arctic (17). The molecular analysis revealed the presence of the anaerobic methane group 1a (ANME-1a) clade of anaerobic methane-oxidizing archaea, while bacterial methane oxidizers were absent from this extreme (∼24% salinity) habitat. Methanotrophs that attenuate methane fluxes from terrestrial methane vents require special attention. Although these microorganisms are unlikely to significantly affect CH4 fluxes from macroseeps, their role in reducing methane emissions from microseepage and small vents is more feasible.
Numerous small gas vents (0.5 to 5 cm in diameter) and natural structures similar to mud microvolcanoes (10 to 100 cm in diameter) were found during our field studies in floodplains of small rivers near Khanty-Mansiysk, West Siberia, Russia. This region in the subzone of Middle Taiga is relatively well characterized with regard to methane emissions from natural wetlands and anthropogenic sources related to gas field explorations (1821). Mud microvolcanoes, however, are still missing on the list of CH4 sources studied in these cold regions. In addition, our knowledge of methanotrophic bacteria (MB) that thrive in low-temperature environments remains limited. At present, only two representatives of obligately psychrophilic aerobic methanotrophs are known. These are the Antarctic methanotroph Methylosphaera hansonii (22) and the tundra methanotroph Methylobacter psychrophilus (23), both of which belong to type I, or gammaproteobacterial, methanotrophs. Several psychrotolerant methanotrophs have also been described. These include both type I MB (Methylobacter tundripaludum, Methylomonas scandinavica) and type II, or alphaproteobacterial, MB (Methylocystis rosea, Methylocella tundrae), but these organisms have growth optima at 15 to 20°C (24).
Our study, therefore, was initiated in order to map and to assess methane fluxes from mud microvolcanoes in floodplains of high-latitude rivers. In particular, we aimed to get insight into the aerobic methanotrophic community that develops around this previously unrecognized natural CH4 source and mitigates methane emission to the atmosphere.

MATERIALS AND METHODS

Study site and methane flux measurements.

Our studies were performed in the Mukhrinskaya River Valley (60°53′N, 68°42′E), Khanty-Mansi Autonomous Okrug, West Siberia, Russia, where the mean annual temperature is −1.1°C and the mean annual precipitation is 596 mm. Other characteristics of the study site have been described previously (2527). This is one of the poorly accessible and virtually unpopulated taiga regions. Due to the high water level in the Irtysh River in spring and early summer, this area is largely flooded and represents a complex network of floodplains and forested wetlands. In early August, however, the water level begins to decline, and numerous gas ebullition sites become clearly visible in the floodplain as well as in the riverbed (see Fig. S1 in the supplemental material). In 2012, this time period was used to perform methane flux measurements at 28 bubbling pools, including both larger and smaller seeps (Fig. 1). Output of the bubbling gases was measured by means of a funnel connected to a graduated cylinder filled with water and by counting the time required to displace water out. This method is widely used for assessing methane emissions by bubbling (2830). The methane concentration in a gas released from seeps was measured using a Crystal 5000 gas chromatograph (Chromatek, Russia) equipped with a flame ionization detector (detector, 250°C, 3-m glass column filled with HayeSep N [Supelco, USA]; column temperature, 40°C). The stable isotopic composition of methane carbon (δ13C) was determined on a gas chromatograph (Thermo Electron, Karlsruhe, Germany), coupled with a Delta Plus mass spectrometer, by following the procedure described by Ivanov et al. (31). The isotopic analyses were carried out in triplicate; measurement error was ±0.1‰.
FIG 1
FIG 1 Methane fluxes and seep distribution in the Mukhrinskaya River Valley. Circles represent the relative magnitudes of individual fluxes from single seeps (g CH4 h−1) as follows: red, 0.9 to 5.5; yellow, 0.4 to 0.5; and green, 0.05 to 0.16. Each white circle represents a single seep, while the sites with numerous seeps are indicated by triangles; a big triangle represents 1,800 to 5,000 seeps, a medium triangle represents 150 to 500 seeps, and a small triangle represents 40 to 100 seeps. The two bubbling pools where the samples of muddy fluids were collected for 14CH4 oxidation rate measurements and molecular analyses are indicated by black stars. Scale bar, 800 m. (Inset) Location of the study site (black circle) on a map of West Siberia (adapted from 2GIS-City Expert [www.2gis.ru]). The base map is adapted from Bing. Microsoft product screen shot reprinted with permission from Microsoft Corporation.

Water sampling and analysis.

We sampled surface water (0 to 5 cm) from 5 bubbling pools, which were located at a distance of 100 to 300 m apart from each other. Sampling glass containers were rinsed with distilled water and then with the water from bubbling pools before sampling. The temperatures of muddy fluids were measured using temperature sensors (Termochron iButton DS 1921 and 1922 [Dallas Semiconductor, USA]). pH was determined using an SG-8 pH meter (Mettler Toledo, Switzerland); measurement error was ±0.002. Water conductivity was determined using an SG-7 electrical conductivity (EC) meter (Mettler Toledo, Switzerland); measurement error was ±0.5%. Concentrations of Li+, Na+, NH4+, K+, Mg2+, Mn2+, Ca2+, F, Cl, NO2, NO3, SO42−, and Br in upwelling water were determined by means of ion chromatography (Metrohn, Switzerland). Concentrations of CO32− and HCO3 were determined by titration with 0.05 M HCl.

Potential methane oxidation.

For radioisotope and molecular analyses, the samples of muddy fluids were collected from the surfaces of two bubbling pools located at a distance of 300 m from each other (indicated by black stars in Fig. 1). Methane concentration in the samples was determined by the headspace method (32). Methane oxidation rates were determined by the radioisotope method with [14C]methane dissolved in degassed distilled water. Mud samples collected from the methane seep were subsampled (3 ml) by means of 5-ml-cutoff plastic syringes; the open end was then sealed with a gas-tight butyl rubber stopper. Labeled substrates (0.2 ml of [14C]methane solution, 1 μCi per sample) were injected through the stopper. The samples were incubated in the dark at the in situ temperature (4°C) for 24 h, fixed with 0.5 ml 2 M KOH, and transported to an isotope facility. For the analysis, the samples were adjusted to pH 2 with HCl, and released CO2 was trapped in a scintillation liquid containing 2-phenylethylamine. Organic matter was also completely oxidized by the persulfate method (33), and released CO2 was trapped again. Both CO2 portions trapped in the scintillation liquid were combined, and radioactivity was measured on a RackBeta scintillation counter (LKB, Sweden). The rates of methane oxidation were calculated using the equation I (rate) = r × C/R × T, where r is the radioactivity of the formed product, C is dissolved methane concentration in the sample, R is the total radioactivity of the added 14C-CH4, and T is the incubation time. Samples fixed with KOH and stored for 2 h prior to the injection of labeled substrates were used as controls.

FISH.

The fixation procedure was performed at the sampling site by adding ethanol (1:1, vol/vol) to the mud samples. The samples were then delivered to the laboratory and stored at −20°C prior to the analysis. In order to overcome the problem of high autofluorescence of clay particles, the protocol developed for fluorescence in situ hybridization (FISH) in soil (34) was employed. Briefly, 7 mg of polyvinylpolypyrrolidone (PVPP) was added to each sample, which consisted of 1.5 ml of a fixed mud suspension collected in a 2-ml Eppendorf tube. Following the addition of 5 mM Na2-EDTA, the tubes were shaken horizontally at 250 rpm for 20 min, after which large soil particles were allowed to settle for 5 min. Subsequently, 1 ml of the supernatant was transferred to new 2-ml Eppendorf tubes on top of a 1-ml Nycodenz cushion (1.3 g ml−1 in sterile water) (Gentaur, Belgium). The samples were centrifuged at 16,438 × g for 30 min at 18°C, and 1.8 ml was collected from the supernatant in a new tube. Samples were vortexed and immobilized on black membrane filters (pore size, 0.2 μm; diameter, 47 mm; Millipore, Germany) and washed with 4 ml PBS (in g/liter, NaCl, 8.0; KCl, 0.2; Na2HPO4, 1.44; NaH2PO4, 0.2; pH 7.0). To prevent pressure damage, black filters were placed onto nitrocellulose membrane filters (pore size, 0.45 μm; diameter, 47 mm; Millipore, Germany). These were further transferred into dishes containing absorbent paper soaked with ethanol and successively dehydrated in 50%, 80%, and 96% ethanol for 6 min each time. Filters were then air dried, cut into pieces, and placed on gelatin-coated (0.1%, wt/vol) and dried Teflon-laminated slides with eight wells for independent positioning of the samples (Magv, Germany). FISH was carried out using the Cy3-labeled oligonucleotide probes M84/M705 and M450. These have reported group specificities for type I and type II MB, respectively (35). Enumeration of Methylocella-like methanotrophs that are not targeted by the above-mentioned assays was carried out using the combination of probes Mcell-1026, Mcellt-143, and Mcells-1024 (36). In addition, the Bacteria-specific probe EUB338-mix was applied as described by Dedysh et al. (37). Following hybridization, the slides were stained with the universal DNA stain 4′,6-diamidino-2-phenylindole (DAPI; 1 μM) for 7 min in the dark, rinsed again with distilled water, and finally air dried. Cell counting was carried out with a Zeiss Axioplan 2 microscope (Zeiss, Jena, Germany) equipped with Zeiss filter 20 for Cy3-labeled probes and Zeiss filter 02 for DAPI staining.

PmoA pyrosequencing.

Six subsamples of mud material (3 samples from each of the two seeps studied), each of 0.5 g (wet weight), were taken for DNA extraction and processed separately. The extraction was performed using a FastDNA Spin kit for soil (Bio101, Carlsbad, CA, USA) according to the manufacturer's instructions. pmoA gene amplicons were generated using the two primer sets A189r/A682r (38) and A189f/mb661r (39). The A189f primer included a 454-A pyrosequencing adaptor and a sample-specific 6-bp barcode sequence, while both reverse primers incorporated 454-B pyrosequencing adaptors. PCR amplifications were performed in a thermal cycler (model Mastercycler gradient; Eppendorf, Hamburg, Germany) under the following conditions: an initial denaturation (5 min at 96°C) and 30 cycles consisting of denaturation (30 s at 94°C), primer annealing (1 min at 56°C), and elongation (1 min at 72°C), with a final elongation step for 5 min at 72°C. pmoA amplicons were generated in triplicate from each DNA extract, pooled in equal amounts, and purified using Wizard SV gel and a PCR clean-up system (Promega, Madison, WI, USA). Quantification of the PCR products was performed using a Quant-iT double-stranded DNA (dsDNA) BR assay kit and Qubit fluorometer (Invitrogen GmbH, Karlsruhe, Germany). The purified products were subjected to pyrosequencing at the Max Planck Genome Centre, Cologne, Germany.
Since the primer sets A189r/A682r and A189f/mb661r do not detect methanotrophs from the phylum Verrucomicrobia (40), an additional PCR assay was performed in order to assess the presence of these bacteria in our samples using the “Methylacidiphilum”-specific pmoA primers V170f/V631b designed by Sharp et al. (41).

Bioinformatic analyses.

Raw sequence data were preprocessed prior to downstream analysis using PRINSEQ (lite version 0.20.3) (42). The settings were as follows: a minimum sequence length of 200 bp, a minimum mean quality score of 20, a maximum allowed rate of N′s of 1%, removal of characters other than ATGC, ends trimmed (from the 3′ end) by a quality score of less than 10, and a low-complexity threshold (entropy 7). Quality-controlled sequence data were analyzed using QIIME. Operational taxonomic units (OTUs) were picked using a sequence similarity threshold of 87%, which was found to be roughly equivalent to a 16S rRNA gene similarity of 97% (43). Using the default naive Bayesian classifier (44) of mothur (45) implemented in QIIME and a customized pmoA database (provided in the supplementary material of Deng et al. [46]), taxonomic assignments were done based on representative sequences of the individual OTUs. Alpha diversity and evenness were assessed by calculating Chao1 (47), Shannon (48), and Simpson (49) metrics. Sequences related to amoA were extracted and further analyzed by OTU clustering using UPARSE (50) and USEARCH (51) and a threshold of divergence of 0.05. Representative sequences from OTUs were randomly sampled and taxonomically assigned by BLASTX (52) searches against sequences in the NCBI nr database (53). Hits with more than 95% amino acid sequence identity over the complete read length to AmoA sequences of cultured representatives were considered to be valid taxonomic assignments.
For further quality check, alignment, and phylogenetic tree construction, the sequences were imported into the ARB software package (54). Sequences containing errors resulting in reading frame shifts and sequences shorter than 139 amino acids were manually excluded from further analysis. For a first overview, sequences were added to an existing neighbor-joining tree of 5,010 published pmoA and amoA sequences. A subset of 184 sequences covering the diversity in the study sites was selected for thorough tree construction, together with the reference data set of 5,010 published pmoA/amoA sequences. This neighbor-joining tree was constructed based on 126 amino acid positions using the Kimura correction.

Nucleotide sequence accession numbers.

The pyrosequencing reads (raw data) have been deposited under the study number SRP037754 in the NCBI Sequence Read Archive with the following accession numbers: SRR1168458 and SRR1169858.

RESULTS

Distribution of seeps and methane emission rates.

Numerous gas ebullition sites represented by either bubbling water pools or cone-shaped, muddy-fluid-discharging craters exposed to the surface were revealed in a valley of the river Mukhrinskaya (see Fig. S1 in the supplemental material). Most (99%) of these vents are relatively small (0.5 to 5 cm in diameter), while some of these structures achieve the size of 1 m. Overall, we were able to map over 25,000 seeps, with some of them occurring as single gas vents and others as groups composed of up to several hundred vents (Fig. 1).
Upwelling water and muddy fluids were characterized by near-neutral pH values of 6.8 to 6.9 and conductivity values of 543 to 627 μS cm−1 and had relatively high contents of Ca2+, Mg2+, and CO3 2−/HCO3 ions (Table 1). Water temperature ranged between 3.5 and 5°C. The gases released from these bubbling pools consisted primarily of methane (70 to 99%), with δ13C-CH4 values of −71.1 to −71.3 ‰, which are indicative of biogenic methane. CH4 emission was measured for 28 randomly chosen seeps (Fig. 1). While methane flux from most (90%) of these sites did not exceed 1.45 g CH4 h−1, some of the seeps emitted up to 5.54 g CH4 h−1 (see Fig. S2 in the supplemental material).
TABLE 1
TABLE 1 Chemical compositions of water samples from several individual seeps
SeepaConcn (mg liter−1) ofb:pHEC (μS/cm)
LiNaNH4KMgCaFClNO3SO4CO3HCO3
10.030 ± 0.0604.65 ± 0.348.18 ± 0.672.90 ± 0.6914.51 ± 0.5185.42 ± 5.940.39 ± 0.600.69 ± 0.0800.89 ± 0.0763.751,306.826.90627
20.005 ± 0.0168.90 ± 0.195.29 ± 0.498.58 ± 1.6114.41 ± 1.2394.52 ± 6.770.08 ± 0.030.53 ± 0.150.04 ± 0.120.20 ± 0.64006.81598
30.006 ± 0.0186.42 ± 0.287.17 ± 0.172.86 ± 0.7016.68 ± 0.7596.38 ± 1.430.07 ± 0.010.78 ± 0.130045.981,365.266.84618
40.005 ± 0.0174.89 ± 0.258.39 ± 0.823.18 ± 0.4716.76 ± 0.8791.55 ± 2.130.28 ± 0.660.99 ± 0.0800.39 ± 0.6257.481,352.516.91575
50.014 ± 0.0234.71 ± 0.186.94 ± 0.432.10 ± 0.4416.29 ± 1.1487.18 ± 16.160.08 ± 0.030.431 ± 0.00500.64 ± 0.0475.241,219.7026.82543
a
Seeps 1 and 2 are the sampling sites indicated by black stars in Fig. 1. Seeps 3 to 5 were located at a distance of 100 to 300 m apart from seeps 1 and 2 and from each other.
b
Concentrations of NO2, Br2+, and Mn2+ were below the detection limit (1 μg liter−1) in all the samples tested.

Potential methane oxidation.

The samples of muddy fluids collected from the two bubbling pools (mapped by black stars in Fig. 1) were used for measuring in situ methane concentrations and potential methane oxidation rates. Methane concentration in muddy fluids was in the range 116 to 233 nmol CH4 ml−1. Potential methane oxidation rates determined at the in situ temperature of 4°C were highly similar for the two sets of samples and ranged between 15.5 and 15.9 nmol CH4 ml−1 day−1.

FISH-based analysis.

To determine the in situ abundance of methanotrophic bacteria, the probes M84/M705 and M450 with reported group specificity for type I and type II MB, respectively, were applied to mud slurries. This direct approach, however, turned out to be inefficient because we faced the problem of the high autofluorescence of soil particles masking the signal of the probes. To overcome this problem, we tested an earlier developed protocol for FISH in soil. It is based on separating microorganisms from soil particles by buoyant density centrifugation on Nycodenz and concentrating cells on membranes (34). This protocol worked well and allowed us to visualize numerous cells of various sizes and shapes that occurred singly or formed long cell chains or aggregates (Fig. 2).
FIG 2
FIG 2 Specific detection of type I aerobic methanotrophs in seep mud by FISH. Epifluorescence micrographs of in situ hybridizations with Cy3-labeled probes M84 and M705 (A) and DAPI staining (B). Panels 1 and 2 display two different microscopic fields of view. Bars, 5 μm.
In situ hybridization with probes M84 and M705 revealed that type I methanotrophs were present at a high abundance in the two seeps examined in our study. The number of cells targeted by these probes ranged between 2.74 × 107 and 4.29 × 107 per g of mud (dry weight) (Table 2). In contrast, only a very few randomly occurring cells were detected with the probe M450, which targets the Methylosinus/Methylocystis group of alphaproteobacterial type II MB. The number of cells revealed by this probe was only 2.84 × 105 to 11.70 × 105 cells per g of mud (dry weight). The attempt to detect Methylocella-like methanotrophs by using the probes Mcell-1026, Mcellt-143, and Mcells-1024 was unsuccessful. The abundance of these bacteria in mud slurries was below the detection limit (103 cells per g of dry mud). Therefore, 95.8 to 99.3% of all aerobic methanotrophs detected in mud by FISH were represented by type I MB, while type II MB were numerically insignificant.
TABLE 2
TABLE 2 Numbers of cells detected by FISH with methanotroph-specific probes in muddy fluids sampled from the seeps
SeepNo. of cells detected with the following oligonucleotide probe(s) (g−1 of dry mud):No. of DAPI-stained cells (108 g−1 of dry mud)% methanotrophs of DAPI-stained cells/% methanotrophs of EUB338-mix-hybridized cells
M84/M705a (107)M450b (105)EUB338-mix (108)
14.29 ± 0.102.84 ± 1.922.1 ± 1.43.98 ± 0.5710.9/20.2
22.74 ± 0.1811.70 ± 11.11.4 ± 3.42.33 ± 0.1812.2/20.5
a
The target specificity of probe M84 includes members of the genera Methylobacter, Methylomonas, Methylococcus, Methylomicrobium, Methylosarcina, and Crenothrix polyspora. Probe M705 targets Methylobacter, Methylomonas, Methylococcus, Methylosarcina, Methylosphaera, and Methylovulum. These probes do not target members of the family Methylothermaceae (i.e., thermophilic and halophilic methanotrophs of the genera Methylothermus, Methylohalobius, and Methylomarinovum).
b
Probe M450 targets all currently described members of the genera Methylosinus and Methylocystis.
As determined by FISH, the total number of aerobic methanotrophs in mud samples taken from the seeps was in the range of 2.86 × 107 to 4.32 × 107 cells per g of mud (dry weight), which accounted for 20.2 to 20.5% of all bacterial cells detected by EUB338-mix or 10.9 to 12.2% of all DAPI-stained cells (Table 2). The high abundance and unusually high proportion of methanotrophs among total bacteria indicate that methane is one of the major substrates that shape the microbial community structure in these unique habitats.

Methanotrophic community analysis via pmoA pyrotag sequencing.

To obtain a more detailed view of methanotroph diversity in cold Siberian seeps, we applied amplicon pyrosequencing of pmoA genes. These encode the β-subunit of particulate methane monooxygenase (pMMO), the key enzyme of nearly all extant methanotrophs. Since Methylocella-like organisms, which lack this enzyme, were virtually absent from this habitat, a pmoA-based approach had a good potential to identify all numerically important methanotroph populations. A total of 53,828 quality-checked, partial (average length, ∼400 bp) pmoA gene sequences were retrieved from the mud samples. The read numbers obtained for each seep were nearly equal (27,398 and 26,430 reads for seeps 1 and 2, respectively).
The two reverse pmoA-specific primers used in our study, i.e., A682r and mb661r, are known to display some differences in their target specificities. This was reflected in the diversity patterns generated with each of the two primer sets (Fig. 3). The overall diversity recovered with A189f/A682r was higher than that revealed by using A189f/mb661r (Chao1 indices of 4,602 and 1,523, respectively). This is due to the fact that primer A682r has a broader detection range and targets not only pmoA but also the phylogenetically related amoA gene (38). The proportions of amoA sequences among all 454 reads recovered with A189f/A682r from seeps 1 and 2 were 27.3 and 24.9%, respectively. These amoA-related reads were removed from further methanotroph analysis, but the information regarding their phylogenetic affiliation is listed in Table S1 in the supplemental material. Other major groups of reads retrieved from the seeps with primer set A189f/A682r were Methylobacter-related pmoA sequences (16.4 to 25.6% of total reads), type Ib methanotroph sequences affiliated with lake cluster 2 (7.7 to 16.0%), and pmoA-like sequences from several as-yet-uncultured bacterial groups (24.1 to 30.4%), including those from Crenothrix-like organisms (Fig. 3). The pmoA libraries obtained with primer set A189f/mb661r were dominated by Methylobacter-related sequences (64.8 to 69.5%) and pmoA sequences from other type Ia methanotrophs, such as Methylomonas, Methylovulum, and Methylosoma (19.3 to 22.4%). Common to both primer sets, the proportion of pmoA sequences from type II MB did not exceed 5.5% of total reads, and most of them were affiliated with the genus Methylocystis. pmoA sequences assigned to Methylosinus trichosporium- and Methylocapsa-like MB and to cluster MO3 were detected at lower levels. Only a very few reads represented pmoA2 sequences, which were most similar to those of Methylocystis bryophila.
FIG 3
FIG 3 Relative abundances of different methanotroph groups in methane seeps based on pyrosequencing of pmoA gene fragments. AOB, ammonia-oxidizing bacteria.
Because the pmoA diversity patterns recovered from seeps 1 and 2 were similar for each of the two PCR assays, the 454 reads obtained with either A189f/A682r or A189f/mb661r were pooled for further analysis. In total, 1,850 and 771 species-level OTUs (defined at a nucleotide sequence identity of 87%) were detected in the seeps with primer sets A189f/A682r and A189f/mb661r, respectively. The most abundant OTUs detected with both primers sets affiliated with the genus Methylobacter, displaying 87 to 96% nucleotide sequence identity to pmoA sequences from M. psychrophilus and M. tundripaludum. Several abundant OTUs showed equal levels of sequence divergence (15 to 18%) from pmoA gene sequences of known representatives of the genera Methylobacter, Methylovulum, and Methylosoma. One of the most abundant OTUs represented lake cluster 2, displaying 83 to 84% sequence identity to pmoA gene fragments from members of the genera Methylococcus and Methylocaldum. Abundant OTUs detected exclusively with primer set A189f/A682r included Crenothrix-like and LW (Lake Washington) cluster pmoA sequences. Abundant OTUs detected exclusively with primer set A189f/mb661r were represented by Methylovulum- and Methylomonas-like pmoA sequences and the sequences from deep-sea cluster 1. Among type II MB, sequences of the most abundant OTU displayed 97 to 99% identity to pmoA gene fragments from Methylocystis hirsuta and Methylocystis rosea.
Sequence reads were manually checked for insertions or deletions (indels), in addition to their classification based on k-mers. Good-quality sequences without indels were used for phylogenetic tree construction. The overall pattern of the methanotroph diversity detected in the seeps is depicted in Fig. 4.
FIG 4
FIG 4 Neighbor-joining tree depicting major pmoA/amoA lineages consistent with those of Lüke and Frenzel (68). Clusters containing sequences from seep-inhabiting bacteria are indicated by dark gray. Lineages lacking isolates are named according to representative clones or to the environment in which they were predominantly or initially found (RPC, rice paddy cluster; JRC, Japanese rice cluster; OSC, organic soil cluster; LW, Lake Washington cluster; FW, freshwater cluster; TUSC, tropical upland soil cluster; USC, upland soil cluster; JR, Jasper Ridge, CA; MOB, methane-oxidizing bacteria; AOB, ammonia-oxidizing bacteria). GenBank accession numbers of representative clones are given in parentheses. The RPC-2 and deep-sea 4 lineages cluster within either type Ia or type Ib MB, depending on the subset of sequences or the method used for tree construction. Colored squares next to pmoA lineages depict the number of sequences retrieved with the A682r reverse primer (dark blue) or the mb661 reverse primer (light blue). The scale bar represents 0.1 change per amino acid position.
The tests for the presence of Verrucomicrobia-like methanotrophs in cold Siberian seeps gave negative results, which appears logical, since these bacteria have so far been detected only in geothermal acidic environments.

DISCUSSION

The type of methane-emitting vents reported here has not been studied before. The bubbling pools in a floodplain of the river Mukhrinskaya cannot be referred to as a microseepage, given that a microseepage does not form visible manifestations and is characterized by much lower emission rates (10 mg m−2 day−1 on average and 1 g m−2 day−1 at a maximum) (6, 7). They also do not fulfill the criteria used to define macroseeps, including mud volcanoes, which emit between several hundred kilograms and several thousand tons of methane per year. The average vent of those mapped in our study emits about 16 g CH4 per day, but these structures seem to be widely distributed in a valley of the river Mukhrinskaya. Most of these vents are difficult or even impossible to map during “high-water” seasons. Although our field studies were performed after the water level dropped down, the real number of gas vents in the riverbed may have remained underestimated. Further research will show whether these methane vents are characteristic of other rivers in poorly accessible regions of the West Siberian taiga.
Methane emanating from these seeps was biogenic (or microbial) in origin. This is not very common for CH4 emitted from geologic sources and suggests that Siberian seeps release methane that originated from decomposition of organic matter in sedimentary basins which are located in zones of permafrost retreat.
The upwelling water had relatively high contents of Ca2+, Mg2+, and CO32−/HCO3 ions but low or undetectable concentrations of NO2, NO3, and SO42−. This water composition excludes the occurrence of NO2/NO3- or SO42−-dependent anaerobic methane oxidation (55, 56) and suggests the leading role of aerobic processes in attenuating methane emissions from the seeps. Indeed, the bubbling water pools examined in our study were abundantly colonized by aerobic methanotrophic bacteria that actively oxidized CH4 released from the subsurface. This was evidenced by relatively high rates of methane oxidation measured in muddy fluids at the in situ temperature of 4°C and also by the high number of methanotroph cells detected by FISH. These accounted for up to 20.5% of total bacterial cell counts. The probe-conferred fluorescence of the cells targeted with methanotroph-specific probes was very bright (Fig. 2), suggesting high ribosome contents in these bacteria. According to the results of our FISH analysis, muddy fluids collected from the seeps were dominated by type I MB, which accounted for 96 to 99% of all methanotroph cells detected by the probes. These estimations were confirmed by the pyrosequencing-based analysis of pmoA gene amplicons, because only 0.5 to 5% of total pmoA sequences retrieved from the samples affiliated with type II MB. The predominance of type I over type II MB has rarely been observed and occurs mainly in cold freshwater ecosystems (5759) and in permafrost environments (60, 61). Generally, type I MB are very responsive to substrate availability and are believed to be indicative of environments with a high methane source strength (62, 63). This is exactly the situation in Siberian river seeps.
A large proportion of pmoA sequences retrieved in our study belonged to type Ia methanotrophs of the genera Methylobacter, Methylovulum, and Methylosoma. These sequences formed a phylogenetic continuum with poorly defined cutoffs between the genus-level groups. The psychrophilic nature of Methylobacter-like methanotrophs is well documented. Two described species of this genus, Methylobacter psychrophilus (23) and Methylobacter tundipaludum (64), were isolated from permanently cold, arctic tundra environments. Using stable isotope probing, Methylobacter species were identified as a major group of metabolically active methanotrophs in arctic wetlands (65) and arctic lakes (58). Notably, members of the genera Methylovulum and Methylosoma were also detected among the active methanotrophs in arctic lake sediments (58), a habitat similar to that of cold river seeps as described here. Apparently, these methanotroph genera accommodate a number of as-yet-undescribed psychrotolerant species. The only currently described species of the genus Methylosoma, Methylosoma difficile, was isolated from littoral sediment of Lake Constance and does not grow below 10°C (66). Methylovulum miyakonense, a methanotroph from a forest soil, does grow at 5°C, but its growth optimum is at 24 to 32°C (67). None of the pmoA sequences retrieved from the cold Siberian seeps could be unambiguously assigned to either Methylosoma difficile or Methylovulum miyakonense. Apparently, they represent novel species within these genera.
Type Ib MB were also detected in our study sites. None of these, however, belonged to the currently recognized genera, i.e., Methylococcus, Methylocaldum, and Methylogaea. This is not surprising given that all characterized members of these genera are mesophilic or moderately thermophilic bacteria that do not develop at low temperatures. The pmoA sequences retrieved in our study affiliated with two major environmental clades, freshwater lineage 1 and freshwater lineage 2 (Fig. 4), which are not represented by cultivated methanotrophs. Freshwater lineage 1 can be separated into smaller clusters, such as RPC-1 (rice paddy cluster 1), LW cluster, and OSC (organic soil cluster) (68). Only pmoA sequences belonging to the LW cluster were detected in our study. Similar pmoA sequences are often retrieved from lake sediments but can also be detected in paddy fields (57, 69, 70). Freshwater lineage 2 includes lake cluster 2, FW cluster (freshwater cluster), and a number of RPCs (rice paddy clusters) (68). A large proportion of pmoA sequences from seeps 1 and 2 belonged to lake cluster 2, which is composed of sequences retrieved mostly from freshwater lake sediments (71, 72).
The fact that pmoA sequences from type II MB represented only a minor proportion of our data sets suggests that these bacteria play only a secondary role in the oxidation of methane in Siberian microseeps. Although several Methylocystis species, including M. rosea, M. bryophila, and M. heyeri, were isolated from cold environments, all currently described members of this genus display a preference for relatively high growth temperatures of 25 to 30°C (73). Only a very few pmoA2 sequences from Methylocystis spp. were detected in our study, which appears logical given the high CH4 availability in this particular habitat.
Approximately 100 reads displayed 95 to 96% sequence identity to the pmoA gene from Crenothrix polyspora (74). This bacterium is commonly found in stagnant water environments and lake sediments. Some filamentous cell forms observed in our FISH experiments could potentially belong to these methanotrophs since they are targeted by the M84 probe. Furthermore, sequences from two new lineages were retrieved (new-1 and new-2 in Fig. 4). Remarkably, sequences related to the alkane monooxygenases of Nocardioides and Mycobacterium were amplified. They are only distantly related to known pmoA and amoA sequences, and the primer sets used in this study did not amplify alkane monooxygenase genes from pure cultures of Nocardioides and Mycobacterium (75, 76). The fact that these sequences were obtained from the methane seep samples may be indicative of a high number of alkane oxidizers in these environments.
In summary, the community composition of aerobic methanotrophs that attenuate CH4 emissions from the Siberian seeps was quite similar to that found at methane seeps in the littoral and profundal zones of oligotrophic freshwater Lake Constance, Germany (57), and in sediments of various boreal and arctic freshwater lakes (58, 77, 78). All these environments are characterized by the predominance of Methylobacter-like organisms and type Ib MB from as-yet-uncultivated clades. Apparently, these methanotrophs are the major CH4 oxidizers in cold eco-niches with high methane source strength. The isolation and characterization of potentially novel, psychrotolerant methanotrophs from these environments represent a challenge for future cultivation studies.

ACKNOWLEDGMENTS

I.Y.O. and S.N.D. were supported by the program Molecular and Cell Biology of the Russian Academy of Sciences and the Russian Foundation for Basic Research (project no. 12-04-00768). M.V.G. was supported by the Tomsk State University Competitiveness Improvement Program. C.-E.W. is a member of the International Max Planck Research School for Environmental, Cellular, and Molecular Microbiology (Marburg, Germany). W.L. was supported by the LOEWE Center for Synthetic Microbiology (SYNMIKRO).
We greatly appreciate the help of E. D. Lapshina (Yugra State University) and also thank A. F. Sabrekov (Tomsk State University), N. Shnyrev (Yugra State University), and I. E. Kleptsova (Tomsk State University).

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cover image Applied and Environmental Microbiology
Applied and Environmental Microbiology
Volume 80Number 191 October 2014
Pages: 5944 - 5954
Editor: J. E. Kostka
PubMed: 25063667

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Received: 10 May 2014
Accepted: 10 July 2014
Published online: 9 September 2014

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Authors

Igor Y. Oshkin
S. N. Winogradsky Institute of Microbiology, Russian Academy of Sciences, Moscow, Russia
Carl-Eric Wegner
Max-Planck-Institut für terrestrische Mikrobiologie, Marburg, Germany
Claudia Lüke
Radboud University Nijmegen, Nijmegen, The Netherlands
Mikhail V. Glagolev
Moscow State University, Moscow, Russia
Laboratory of Computational Geophysics, Tomsk State University, Tomsk, Russia
Yugra State University, Khanty-Mansiysk, Russia
Institute of Forest Science, Russian Academy of Sciences, Uspenskoe, Russia
Illiya V. Filippov
Yugra State University, Khanty-Mansiysk, Russia
Nikolay V. Pimenov
S. N. Winogradsky Institute of Microbiology, Russian Academy of Sciences, Moscow, Russia
Werner Liesack
Max-Planck-Institut für terrestrische Mikrobiologie, Marburg, Germany
Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, Marburg, Germany
Svetlana N. Dedysh
S. N. Winogradsky Institute of Microbiology, Russian Academy of Sciences, Moscow, Russia

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J. E. Kostka
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Notes

Address correspondence to Svetlana N. Dedysh, [email protected].

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  • Citation counts come from the Crossref Cited by service.

Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download.

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