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Alpha- and Gammaproteobacterial Methanotrophs Codominate the Active Methane-Oxidizing Communities in an Acidic Boreal Peat Bog

Kaitlin C. Esson,a Xueju Lin,a Deepak Kumaresan,b Jeffrey P. Chanton,c J. Colin Murrell,d Joel E. Kostkaa School of Biology, Georgia Institute of Technology, Atlanta, Georgia, USAa; School of Earth and Environment, University of Western Australia, Crawley, WA, Australiab; Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, Florida, USAc; School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, United Kingdomd

The objective of this study was to characterize metabolically active, aerobic methanotrophs in an ombrotrophic peatland in the Marcell Experimental Forest, in Minnesota. Methanotrophs were investigated in the field and in laboratory incubations using DNA-stable isotope probing (SIP), expression studies on particulate methane monooxygenase (pmoA) genes, and amplicon se- ␮ ؊1 ؊1 quencing of 16S rRNA genes. Potential rates of oxidation ranged from 14 to 17 mol of CH4 g dry weight soil day . Within DNA-SIP incubations, the relative abundance of methanotrophs increased from 4% in situ to 25 to 36% after 8 to 14 days. Phy- logenetic analysis of the 13C-enriched DNA fractions revealed that the active methanotrophs were dominated by the genera Methylocystis (type II; Alphaproteobacteria), Methylomonas, and Methylovulum (both, type I; Gammaproteobacteria). In field samples, a transcript-to-gene ratio of 1 to 2 was observed for pmoA in surface peat layers, which attenuated rapidly with depth, indicating that the highest methane consumption was associated with a depth of 0 to 10 cm. Metagenomes and sequencing of cDNA pmoA amplicons from field samples confirmed that the dominant active methanotrophs were Methylocystis and Methylo- monas. Although type II methanotrophs have long been shown to mediate methane consumption in peatlands, our results indi- cate that members of the genera Methylomonas and Methylovulum (type I) can significantly contribute to aerobic methane oxi- dation in these ecosystems.

ethane is the third most important greenhouse gas and has (encoding the alpha-subunit of the hydroxylase of sMMO) as well M28 times the potential of carbon dioxide to trap heat radia- as 16S rRNA genes have been used most often as molecular mark- tion on a molecular basis over a 100-year time scale (1, 2, 3). ers to characterize methanotrophs in peatlands and other envi- Wetlands, such as peatlands, represent the largest natural source ronments (6, 17, 18, 19, 20, 21, 22, 23). Previous studies point to a of methane to the atmosphere (4). Aerobic methanotrophic bac- codominance of Alpha- and Gammaproteobacteria and, in partic- teria live at the oxic-anoxic interface of wetland soils, and it has ular, the genera Methylocystis and Methylomonas; however, the been shown that they consume as much as 90% of the methane majority of past work in the field was conducted at the DNA level, produced belowground before it reaches the atmosphere, thus and less information is available on which microbial populations serving as a biofilter regulating emissions (3, 5, 6, 7). The response are actively involved in methane oxidation in situ. Using a combi- of methane dynamics in wetlands to global climate change is un- nation of stable isotope probing (SIP) and a functional gene certain, and climate models would be improved through quanti- (pmoA) array, Chen et al. (24) determined that Methylocystis pop- fication of the response of microbially mediated mechanisms of ulations predominated in the active methanotrophs in a range of methanotrophy to temperature and moisture variation. peatlands in the United Kingdom. Phospholipid fatty acid stable Aerobic methanotrophs are phylogenetically located in two isotope probing (PLFA-SIP) analysis was also utilized in conjunc- phyla: the Proteobacteria and Verrucomicrobia (8). The majority of tion with mRNA analyses to probe the active methanotrophic characterized methane-oxidizing organisms have been separated communities in peatlands in the United Kingdom and again into type I methanotrophs of the Gammaproteobacteria and type II found a community dominated by Methylocystis (6). Gupta et al. methanotrophs of the Alphaproteobacteria (9, 10, 11). The prevail- (7) also detected a predominance of type II methanotrophs ing view has been that most methanotrophs grow only on meth- (Methylocystis, Methylosinus, Methylocapsa, and Methylocella)ina ane or methanol as a source of carbon and energy (4). However, peatland in New York using SIP. As reviewed by Dedysh (25), a more recently, a number of type II methanotrophs (Methylocella, Methylocapsa, and Methylocystis) have been characterized as fac- ultative methanotrophs capable of conserving energy for growth Received 18 November 2015 Accepted 3 February 2016 on multicarbon compounds such as acetate, pyruvate, succinate, Accepted manuscript posted online 12 February 2016 malate, and ethanol (12). Although members of the phylum Ver- Citation Esson KC, Lin X, Kumaresan D, Chanton JP, Murrell JC, Kostka JE. 2016. rucomicrobia have been widely detected in peatlands, none has Alpha- and gammaproteobacterial methanotrophs codominate the active methane-oxidizing communities in an acidic boreal peat bog. Appl Environ been definitively linked to methanotrophy, and thus more re- Microbiol 82:2363–2371. doi:10.1128/AEM.03640-15. search is needed to ascertain the role of Verrucomicrobia in the Editor: G. Voordouw, University of Calgary carbon cycle of peatlands (8, 13, 14, 15, 16). Address correspondence to Joel E. Kostka, [email protected]. Aerobic methane oxidation in proteobacterial methanotrophs Supplemental material for this article may be found at http://dx.doi.org/10.1128 is catalyzed by the enzyme methane monooxygenase (MMO), ei- /AEM.03640-15. ther particulate MMO (pMMO) or a soluble MMO (sMMO). The Copyright © 2016, American Society for Microbiology. All Rights Reserved. genes pmoA (encoding the 27-kDa subunit of pMMO) and mmoX

April 2016 Volume 82 Number 8 Applied and Environmental Microbiology aem.asm.org 2363 Esson et al. number of acidophilic and acidotolerant type II methanotrophs ϳ5 g of peat from the incubation. Samples were then dried in a drying have been cultivated from peatlands. The first acid-tolerant type I oven at 60°C until a stable mass was obtained (approximately 7 days). methanotroph was only recently isolated and described by Dani- Stable isotope probing: ultracentrifugation and gradient fraction- lova et al. (26); however, cultivation of both types might suggest ation. DNA was extracted from frozen peat samples with a MoBio PowerSoil DNA kit according to the manufacturer’s protocol and stored their involvement in active methane oxidation. Ϫ The objective of this study was to identify the microorganisms at 20°C until further analysis. Stable isotope probing was conducted as described previously (28, 29). In brief, extracted DNA was added to a actively involved in methane oxidation in climatically sensitive cesium chloride solution and centrifuged by ultracentrifugation at boreal peatlands using multiple, independent molecular ap- 177,000 ϫ g. After 40 h, samples were removed from the ultracentrifuge proaches in the field and laboratory. Based on previous studies, it and fractionated by needle fractionation into 12 or 13 fractions, and the was hypothesized that the alphaproteobacterial methanotrophs density of each fraction was determined with a digital refractometer were most active in methane oxidation, with only a minor contri- (Reichart AR200). 13C-enriched DNA was expected within the heavy frac- bution from the gammaproteobacterial methanotrophs. This tions (five to eight). DNA was precipitated from all fractions with poly- study was conducted at the Marcell Experimental Forest (MEF) in ethylene glycol and glycogen as a carrier (28, 29). Precipitated DNA was northern Minnesota, where the U.S. Department of Energy stored at Ϫ20°C until further analysis. (DOE) Oak Ridge National Laboratory and the USDA Forest Ser- Microbial community characterization in SIP incubations. All frac- vice are conducting a large-scale field climate manipulation tionated DNA samples from day 8 and day 14 time points were finger- known as Spruce and Peatland Response under Climatic and En- printed with automated ribosomal intergenic spacer analysis (ARISA). First, ARISA PCR was run on each sample with the S-D-Bact-1522-b-S-20 vironmental Change (SPRUCE). and L-D-Bact-132-a-A-18 primers (30). PCRs were performed with an initial denaturation step at 95°C for 5 min, followed by 30 cycles of 30 s at MATERIALS AND METHODS 94°C, 1 min at 52°C, and 1 min at 72°C, with a 10-min final elongation step ϫ Site description and sample collection. Peat samples were collected at the at 72°C. PCR products were run on a 1.5% (wt/vol) agarose gel with 1 S1 bog located in the Marcell Experimental Forest (MEF; 47°30.476=N; Tris-borate-EDTA (TBE) buffer, and successful reaction products were 93°27.162=W) north of Grand Rapids, MN (27). This site has been de- cleaned with a MoBio PCR cleanup kit according to the manufacturer’s scribed in detail in other publications (14, 15). The S1 bog is acidic, with instructions. ARISA PCR products were then separated and analyzed us- an average pH of 3.5 to 4.0, and is oxygen limited, with oxygen levels ing an Agilent model 2100 Bioanalyzer, and unique bands in heavy frac- 13 decreasing to below detection (limit of approximately 20 ppb) within the tions were noted from CH4 samples to determine the success of the SIP top 5 cm of the bog (14). incubation. For use in DNA-SIP incubations, a 10- by 10- by 10-cm block of peat, Quantitative PCR (qPCR) was used to determine the abundance of 13 approximately 1 liter in volume, was sampled using a sterilized bread knife pmoA genes in different DNA fractions retrieved from the CH4-incu- in hollows from the S1 bog, transect 3, in July 2012. The collected peat was bated soil samples (after 14 days of incubation). To minimize effects of homogenized by hand in a sterile bag and stored at 4°C until used in inhibitors, DNA from SIP fractions was diluted to 1/20 of original con- experiments. Samples for nucleic acid extraction were collected in tripli- centrations. All fractions were analyzed with A189f/Mb661r PCR primers cate with a Russian peat corer as described by Lin et al. (14, 15). Each core as described by Kolb et al. (31) to target the abundance of pmoA genes in was subsectioned into 10-cm intervals and immediately placed on dry ice. 20-␮l reaction mixtures with 2 ␮l of template DNA (2.3 to 8.8 ng/␮l) Samples were then stored at Ϫ80°C in a portable freezer until nucleic acid added to 10 ␮l of SYBR green master mix to a final concentration of 1ϫ, extractions were performed. DNA and RNA extractions were performed 1.6 ␮l of each forward and reverse primer to a final concentration of 0.8 with MoBio PowerSoil DNA and total RNA extraction kits, respectively, ␮M, and 4.8 ␮l of PCR-grade water. Samples were run against a standard according to the manufacturer’s instructions. curve in a StepOnePlus instrument with 96 wells with the following pa- Microcosm incubations with 13C-labeled methane. Ten grams of ho- rameters: an initial denaturation step of 5 min at 95°C and 40 cycles of mogenized peat from a depth of 0 to 10 cm of the S1 peat bog midway denaturation at 95°C for 15 s, annealing at 64°C for 45 s, extension at 72°C along the third transect (S1T3M) was added to 150-ml serum bottles in for 45 s, and data acquisition at 86.5°C for 16 s. The quantity of pmoA duplicate for each treatment. This site was chosen for consistency with genes was normalized to the abundance of 16S rRNA genes, which were other field samples obtained from the S1 peat bog. Bottles were sealed with analyzed as described in Lin et al. (15) with a 1/20 dilution of DNA. 13 blue butyl rubber stoppers and crimped with aluminum crimp seals. Sam- DNA fractions from one CH4 sample from T1 (8-day incubation) 13 ples were stored in the dark at room temperature (approximately 24°C). and one CH4 sample from T2 (14 day incubation) were sequenced on an Treatments included those in which the headspace was amended with Illumina MiSeq platform at the Michigan State Sequencing Facility with 12 13 either 1% (vol/vol) 99.9% CH4 (Sigma) or 1% (vol/vol) 99.9% CH4 the 515F/806R primer set (32). Sequences were analyzed in QIIME, ver- (Sigma). This concentration is higher than in situ levels of methane in sion 1.8 (33), as follows: overlapping reads were merged with fastq-join order to obtain enough labeled DNA for subsequent analyses. Headspace (34), and quality filtering was performed with USEARCH, version 7.0, concentrations were monitored with a gas chromatograph-flame ioniza- rejecting reads with an expected error greater than 0.5 (35). Read length tion detector (GC-FID) equipped with a methanizer over 2 weeks of in- was limited to approximately 250 bp after primer removal, with the inclu- cubation. Analysis of headspace gas (150 ␮l) was performed on a Shi- sion of only completely assembled reads. Subsequently, initial operational madzu GC-2014 with a Supelco custom-packed column (Packing 80/100 taxonomic units (OTUs) from the 16S rRNA gene sequence reads were Hayesep Q). The flow rate was 30 ml/min with the injector and detector at picked de novo based on 97% similarity, and representative sequences 100°C, the column at 40°C, and the methanizer at 380°C. Samples were were picked from each OTU. Representative sequences were filtered by taken on the day of preparation (day 0) and subsequently after 3, 8, 11, and comparison to the Greengenes database (http://greengenes.lbl.gov/cgi 14 days. The samples were not replaced due to the relatively short incu- -bin/nph-index.cgi) at 60% similarity. An OTU table was compiled and fil- 12 13 bation and minimal headspace sampling. In parallel, CH4 and CH4 tered by removing phylotypes comprising less than 0.05% of the library. samples were sacrificed at the initiation of the experiment (T0), after 8 Taxonomy was assigned to the parsed OTU table with the Greengenes days (T1), and after 14 days (T2). A subsample of 5 g was removed from database. 16S rRNA gene sequences assigned to the phylum Proteobacteria each sample and frozen at Ϫ80°C until DNA was extracted for further were screened for methanotrophs with a maximum-likelihood phyloge- analysis. netic tree. Sequences were aligned, and identity was determined at 95% The ratio of wet to dry weight (dwt) was determined by weighing out similarity to the nearest neighboring sequence in SILVA (36). The metha-

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FIG 1 pmoA gene and transcript abundance in copies per gram of dry weight at the indicated depths from the S1 peatland. Samples tested were from duplicate soil cores collected in July 2013. Error bars represent standard deviations. notrophs represented in DNA-SIP samples were identified with a nucleic Power SYBR green PCR master mix was used for all qPCR assays. acid maximum-likelihood tree with bootstrap analysis (1,000 replica- Plasmid DNA or cDNA standards with inserts of specific gene fragments tions). Analysis of variance and regression analysis of the shift in metha- were used to establish standard curves that were included in each run. The notroph community composition in heavy and light fractions were con- standard contains different quantities of cloned gene fragments, spanning ducted in R to test for significant differences in methanotroph 7 orders of magnitude from 101 to 107 gene copies per PCR well. To populations (37). minimize the effects of inhibitors in assays, peat DNA was diluted to 1/40 Metagenomic analysis of field samples. Libraries for metagenomic of original concentrations, and duplicate 20-␮l reaction mixtures, each sequencing were generated from field DNA extracts using a Nextera DNA containing 2 ␮l of diluted DNA, were run for each sample. The pmoA sample preparation kit (Illumina, Inc., San Diego, CA) as described in Lin amplicons from the synthesized environmental cDNA were sent to the et al. (15). Libraries were size selected using E-Gels (Life Technologies, University of Illinois at Chicago (UIC) for DNA sequencing using a 454 Inc.) for an insert size range of 400 to 800 bp. Libraries were then quanti- platform. fied, and quality was checked using an Invitrogen Qubit and Agilent Bio- Raw pmoA sequences were demultiplexed, trimmed, and quality fil- analyzer. FASTQ files from the metagenomic sequencing were loaded into tered in CLCbio. the MG-RAST server for quality filtering and downstream analysis (38). Nucleotide sequence accession numbers. Gene sequences from the The paired-end reads from each library were joined and then filtered analysis of SIP fractions were submitted to the GenBank database under with the default parameters. Protein and pathway searches were per- BioProject number PRJNA286313. Metagenomes have been submitted to formed with SEED annotations (E value of 10Ϫ5) in MG-RAST. The MG-RAST under identification numbers 4538779.3, 4538778.3, and amino acid sequences derived from the gene calling were downloaded to 4538997.3. Amplicon sequences for the pmoA gene were deposited in the screen for pmoA-encoded proteins. A hidden Markov model (HMM) for BioProject database under accession number PRJNA311735. the pmoA gene was created by using HMMER, version 3.0, tools (http: //hmmer.janelia.org/), based on HMM training sequences downloaded RESULTS from the functional gene pipeline and repository (http://fungene.cme Ϫ5 Abundance, activity, and community composition of metha- .msu.edu/). All HMM search hits with E values below a threshold of 10 notrophs in the field. The abundance of pmoA genes and tran- were counted and retrieved. For the taxonomic assignment of gene se- scripts decreased rapidly with depth in the peat column, decreas- quences, the corresponding blastp search outputs were uploaded for anal- ysis through the software Metagenome Analyzer (MEGAN) (39). ing by 2 orders of magnitude from a depth of 0 to 100 cm (Fig. 1). Quantification of pmoA genes and transcripts in field samples. The transcript-to-gene ratio, a proxy for pmoA expression or the Quantification of pmoA genes and transcripts was conducted with DNA activity of methanotrophs, decreased to background levels below a and cDNA extracted from field samples, respectively, according to meth- depth of 40 cm. ods described above for analysis of SIP fractions. cDNA standards and Multiple lines of evidence allowed us to determine the domi- cDNAs of environmental RNA samples were synthesized using a GoScript nant methanotrophs in the S1 bog soils (Fig. 2). In all of the soils reverse transcription system according to the manufacturer’s protocol sampled, sequences affiliated with the genus Methylocystis com- (Promega). The pmoA gene fragment used for constructing plasmid stan- prised over 75% of the pmoA sequences retrieved from meta- dards of qPCR was amplified from genomic DNA of Methylococcus cap- genomes and sequenced amplicons derived from cDNA (Fig. 2). sulatus Bath. The plasmid standard was prepared according to Lin et al. Overall, the remaining pmoA sequences were mainly affiliated (40). To prepare cDNA standards, plasmid DNA with a positive pmoA insert was linearized with an NcoI restriction enzyme according to the with the genus Methylomonas. At middepth (approximately 30 manufacturer’s protocol (Promega) and purified by a MinElute PCR pu- cm), Methylosinus-like sequences showed a higher relative abun- rification kit (Qiagen Inc., CA). RNA was synthesized from the linearized dance than Methylomonas-like sequences in the metagenomes, plasmid DNA using a Riboprobe in vitro transcription system according while Methylomonas-like sequences were second in relative abun- to the manufacturer’s protocol (Promega). dance to Methylocystis sequences in cDNA amplicons. However,

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this could be due to the slightly different depths sampled or to temporal variability since the metagenomes and cDNA amplicons were sampled in successive years. However, microbial community composition was shown to be temporally stable at the DNA level in extensive field studies of the S1 bog (14, 15). Stable isotope probing incubations. Within microcosm incu- bations, the most rapid methane oxidation rates were observed within the first 3 days of incubation at room temperature (approx- ␮ imately 24°C). Rates ranged from 13.8 to 17.3 mol of CH4 g Ϫ1 Ϫ1 13 12 dwt day . Samples amended with CH4 and CH4 demon- Ϯ ␮ strated potential consumption rates of 15.1 2.3 mol of CH4 g Ϫ1 Ϫ1 Ϯ ␮ Ϫ1 Ϫ1 dwt day and 15.9 1.6 mol of CH4 g dwt day , respec- tively. Rates of methane consumption were calculated in Excel utilizing the linest function from three-point linear regions in methane depletion with time. After 2 weeks, nearly all of the meth- ane in the headspace had been consumed (Fig. 3). Samples were sacrificed for DNA-SIP analysis after 8 days for time point 1 (T1), after peak methane consumption rates were observed, and after 14 days for time point 2 (T2), when nearly all of the methane had been consumed. FIG 2 Methanotroph community composition at the indicated depths in the SPRUCE S1 peat bog based on metagenomic and cDNA analysis of pmoA. Fingerprinting of the fractionated DNA was conducted with Methanotrophs detected included Methylocystis, Methylomonas, and Methylo- automated ribosomal intergenic spacer analysis (ARISA), which sinus. Samples for metagenomic analysis were collected at SPRUCE in July showed a clear shift in microbial communities, indicating incor- 2012 (SP0712), and samples for cDNA analysis were collected at SPRUCE in 13 July 2013 (SP0713). Values are percentages. poration of C into DNA within heavy fractions 7 and 8 (see Fig. S1 and S2 in the supplemental material). Potential enrichment of active methanotrophs within these fractions was supported by a relative enrichment in pmoA gene abundance as determined by

12 FIG 3 The consumption of methane with time in the stable isotope probing incubations. Circles represent CH4 treatments whereas triangles represent 13 ␮ Ϫ1 Ϫ1 CH4-amended treatments. The observed methane consumption rates ranged between 13.85 and 17.26 mol of CH4 g dwt day (calculated based on a three-point linear region within each sample distribution). Peat utilized was from a depth of 0 to 10 cm in hollows from the S1 bog, collected in July 2012.

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FIG 4 The relative abundance of alphaproteobacterial (type II) and gammaproteobacterial (type I) methanotrophs based on 16S rRNA genes in 13C-enriched fractions (H) and light fractions (L) after 8 days (T1) and 14 days (T2) of incubation. The difference between methanotrophic communities in heavy and light fractions was significant based on ANOVA (F ϭ 7.144, df ϭ 3, P ϭ 0.0439). qPCR (see Fig. S3 in the supplemental material). Within 13C-en- oxidation pathway (pmoA, encoding a subunit of particulate riched fractions from DNA-SIP incubations, an enrichment of methane monooxygenase) was used as a proxy for the activity of Proteobacteria was observed relative to levels in the 12C-enriched methanotrophs in the bog. Although pmoA genes could be de- fractions. The relative abundance of methanotrophs in the overall tected throughout the peat column, indicating the presence of community increased from approximately 4% in the field samples methanotrophs, transcript abundance decreased with depth, and (data not shown) to 36% in the 13C-enriched fractions after 8 days no pmoA transcripts were detected below a depth of 30 to 40 cm. of incubation (Fig. 4). The shift in the abundance of the metha- Biogeochemical characteristics of the S1 peat bog have been de- notrophic community between 13C-enriched fractions and 12C- scribed in detail by Tfaily et al. (27), including the distinct layers enriched fractions was shown to be significant by analysis of vari- within the peat column encompassing the acrotelm (0 to 30 cm), ance (ANOVA) (F ϭ 7.144, df ϭ 3, P ϭ 0.0439). Phylogenetic mesotelm (30 to 75 cm), and catotelm (75 cm and deeper). Oxy- analysis of 16S rRNA gene sequences showed a codominance of gen diffusion is limited within the bog due to the height of the alphaproteobacterial and gammaproteobacterial methanotrophs, water table but may extend lower in the acrotelm due to zones of and phylotypes were most closely related to the rRNA genes of the aeration within the rhizosphere of plant roots (3, 14). Thus, in genera Methylocystis, Methylomonas, and Methylovulum (Fig. 4 parallel with the availability of oxygen, methanotroph activity was and 5). None of the phylotypes was closely related to cultivated highest at the surface and limited to the acrotelm and mesotelm. members of each genus. Environmental sequences obtained in Although few studies have examined pmoA expression in wet- other peat bogs were similar to the sequences enriched in 13C; lands, Freitag et al. (41) observed that transcript-to-gene ratios however, phylotypes most closely related to Methylomonas and reflected methane dynamics in a United Kingdom peatland. Tran- Methylovulum, in particular, remained phylogenetically distinct script-to-gene ratios of this study were in agreement with those while phylotypes related to Methylocystis were phylogenetically determined by Freitag et al. (41). It should be noted that this study similar to sequences obtained in other acidic forest and peat soils does not address microbial groups that mediate anaerobic meth- (Fig. 5). The methanotrophic genera Methylocella and Methyl- ane oxidation (AOM), during which methanotrophy is coupled to oferula, possessing only the soluble methane monooxygenase, utilization of alternate electron acceptors such as sulfate, nitrate, were not detected. or nitrite (42, 43, 44). Given the scarcity of these alternate electron acceptors in the S1 bog (14), anaerobic methane oxidation would DISCUSSION not be favored. However, further studies of AOM are warranted in The community composition and activity of methanotrophic bac- this ecosystem. teria were interrogated in field samples from the S1 bog at Marcell Independent lines of evidence revealed the identity of active Experimental Forest in Minnesota using several cultivation-inde- methanotrophs in the surface (0- to 10-cm depth), where the pendent approaches. Expression of a key gene in the methane highest methane oxidation activity was detected. Results from

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FIG 5 Phylogeny of methanotrophs within SIP fractions from 8- and 14-day incubations (diamonds) showing organisms within the Alphaproteobacteria, Methylocystis sp., and the Gammaproteobacteria, Methylomonas and Methylovulum spp. based on 16S rRNA gene analysis. This phylogenetic tree was prepared with the maximum-likelihood method with bootstrap analysis of nucleic acid sequences (1,000 replications). metagenomes and next-generation sequencing of pmoA cDNA in methane oxidation but also the involvement of a second gam- amplicons from field samples indicated a predominance of the maproteobacterial methanotroph, Methylovulum. type II methanotroph, Methylocystis, at the surface. Since the se- Field results were confirmed in the laboratory using a combi- quencing of cDNA amplicons was conducted on the same samples nation of stable isotope probing and next-generation sequencing as those used for qPCR, the community composition should be of 16S rRNA genes in a series of microcosm incubations. The directly comparable to gene expression determinations. Methylo- active methanotrophic community was composed of a combina- cystis comprised over 75% of the metabolically active metha- tion of Methylocystis, Methylomonas, and Methylovulum popula- notrophs, with the type I methanotroph Methylomonas making up tions, the abundances of which were observed to shift with time the remainder of the active community. Thus, these groups appear (Fig. 4). As indicated previously, the presence of Methylocystis was to be the most abundant and the most active in mediating aerobic not surprising, given the well-documented presence, activity, and methanotrophy in the S1 bog. Previous metagenomic analysis of cultivated isolates from this methanotroph in acidic peatland eco- field samples from the S1 peat bog suggested the potential involve- systems (6, 17, 21, 24). The presence and abundance of Methylo- ment of Methylocystis and, to a lesser extent, Methylomonas in monas and Methylovulum were more surprising. While Methylo- methane oxidation processes (14, 15). The data presented in this monas has been detected in amplicon sequences and cultured study suggest not only active involvement of both of these genera from peatlands, this genus has not been definitively linked to ac-

2368 aem.asm.org Applied and Environmental Microbiology April 2016 Volume 82 Number 8 Codominant Active Methanotrophs in a Boreal Peat Bog tive methane oxidation in acidic boreal peatlands (23, 26, 45, 46). lovulum to the changing environmental conditions at the surface Through the use of SIP, Methylomonas has been shown to be active of boreal peatlands (52). This would not be the first example of an in methane oxidation in other environments, such as a cave sys- organism seemingly suited to one particular environment playing tem, a soda lake, and landfill cover soil (47, 48, 49), that are more a role in a wholly different environmental system. Rahman et al. neutral to alkaline in pH. Studies on methanotrophs in peatlands (53) showed in 2011 that Methylocella, a facultative methanotroph have utilized a variety of methods, including both cultivation- isolated from acidic soil, resides in many diverse environments dependent and cultivation-independent methods such as diag- encompassing a pH range of 4.3 to 10.0. Based on this example, it nostic microarrays, PLFA-SIP, clone libraries, and DNA-SIP; is not necessarily surprising to find a methanotroph commonly however, this study utilized DNA-SIP experiments where the 13C- found in more neutral environments actively participating in enriched DNA obtained was directly sequenced in combination methane oxidation in the acidic peat soil. Rather, this would en- with metagenomic and cDNA analyses of field samples. Within courage further probing of the active microbial community, po- the top 10 cm of the S1 bog, potential rates of methanogenesis tentially with a transcriptomic approach, to more fully assess ␮ Ϫ1 Ϫ1 reach only 0.025 mol of CH4 g dwt day (27). If these poten- which microorganisms are present and active in each environ- tial rates are representative of in situ rates of methanogenesis, the mental system. methane concentrations in the headspace of SIP incubations after An important step in analyzing the potential impacts of chang- 14 days were more representative of the natural environment, ing climate on the methane cycle in peatlands is to first identify the lending greater significance to the observed shifts in populations microorganisms actively involved in methane cycling. These data of methanotrophs present (Fig. 3 and 4). The combination of take a step toward that goal by identifying the active methane- amplicon sequencing of SIP enrichment samples and metag- oxidizing bacteria at the S1 bog in the Marcell Experimental For- enomic sequence analysis of field samples, coupled with analysis est. Active methane oxidizers include representatives from both of multiple time points, enabled analysis of the gammaproteobac- the Alphaproteobacteria and Gammaproteobacteria, and we show terial (type I) methanotroph community, which can now be con- for the first time that Methylovulum and Methylomonas are di- sidered to be a key group of active methane oxidizers in an acidic rectly involved in methane oxidation at the surface of the peat bog. peatland ecosystem. Using these data, the key bacteria involved in methane oxidation Perhaps most remarkable is the presence of Methylovulum in can be targeted for cultivation for future studies to examine the the active methanotrophic community. The first isolate of this physiology of these organisms and subsequently the potential ef- genus, Methylovulum miyakonense, was obtained in 2011, and to fects of climate change on this methane-oxidizing community in date no new species within this genus have been characterized boreal peat bogs. (50). Although originally isolated from forest soil, M. miyakonense was also isolated from peatland soil (51), suggesting that Methyl- ACKNOWLEDGMENTS ovulum is present in other peatlands. The cultivation of a Methy- We acknowledge Stefan Green for his assistance in sequencing and Will lovulum-like methanotroph from another acidic peat bog by Kip Overholt for his assistance in sequence analysis. et al. (45) further supports this possibility. However, the strains This work was funded by the Office of Biological and Environmental did not appear to grow under acidic conditions, begging the ques- Research, Terrestrial Ecosystem Science Program, under U.S. Department tion of the extent of the role Methylovulum might be playing in of Energy contracts DE-SC0007144 and DE-SC0012088, as well as by a acidic peatland soil (50, 51). To our knowledge, these are the first U.S. Department of Education Graduate Assistance in Areas of National data directly linking Methylovulum to active methane cycling in Need Fellowship. peatlands. Although the relative abundance of Methylovulum was low in the SIP incubations, there was a distinct enrichment in the FUNDING INFORMATION 13 12 C-enriched samples compared to the levels in the C-enriched U.S. Department of Energy (DOE) provided funding to Kaitlin Esson, samples, suggesting active methane consumption (see Fig. S4 in Xueju Lin, and Joel E. Kostka under grant numbers DE-SC0007144 and the supplemental material). While microcosm experiments may DE-SC0012088. U.S. Department of Education (DoED) provided fund- induce enrichment of organisms normally low in abundance in ing to Kaitlin Esson. situ, other methanotrophic organisms detected at low abundance in the metagenomes, such as Methylosinus, were not enriched with REFERENCES 13 C over the course of the incubation, suggesting that Methylovu- 1. Intergovernmental Panel on Climate Change. 2015. Climate change lum actively participates in methane consumption, if at low abun- 2014: synthesis, report. Contribution of working groups I, II and III to the dance. Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland. Several possibilities may explain a seemingly neutrophilic 2. Bodelier PLE, Steenbergh AK. 2014. 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