Methane oxidation and diversity of aerobic methanotrophs in forest and agricultural soddy–podzolic soils

Applied Soil Ecology 119 (2017) 267–274

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Methane oxidation and diversity of aerobic methanotrophs in forest and agricultural soddy–podzolic soils

MARK

⁎

Irina Kravchenkoa, , Marina Sukhachevab a b

Winogradsky Institute of Microbiology, Research Center of Biotechnology of the Russian Academy of Sciences, 33, bld. 2 Leninsky Ave., 19071, Moscow, Russia Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, 33, bld. 2 Leninsky Ave., 119071, Moscow, Russia

A R T I C L E I N F O

A B S T R A C T

Keywords: Atmospheric CH4 oxidation Forest soils Uncultured methanotrophs pmoA

Soddy-podzolic soils are widely distributed in European Russia, but their role as a sink for atmospheric methane is poorly documented and there is no information on the methanotroph diversity. We analysed the potential CH4oxidation rates in soil samples and showed that the rate was significantly higher in forest soil than in arable soil, 1.21 and 0.40 ng CH4 g soil −1day−1, respectively. PCR-DGGE and clone library analysis indicated the distinct methanotrophic communities in these soils. The pmoA sequences associated with uncultured soil methanotrophs, referred to as NUSC, dominated forest soil, while in agricultural soil, type I (Methylobacter, Methylocaldum) and type II (Methylocystis, Methylosinus) methanotrophs were dominant. A newly developed primer set was applied in qPCR analysis and revealed that the copy number of pmoA genes of NUSC methanotrophs in forest soil was (9.2 ± 0.87) × 104 g soil−1, whereas the transcript number was (1.33 ± 0.31) × 106 g soil −1. We concluded that differences between the CH4 oxidation rates between forest and agriculture soils were driven by the structure of the methane-oxidizing community and that a novel group of methanotrophs may be an active participant in this process.

1. Introduction Methane (CH4) is an important trace gas, and its contribution to the greenhouse effect is estimated as high a 30% (Dlugokencky et al., 2011). The only recognized biological mechanism of regulation of methane content in Earth’s atmosphere is its oxidation by microbial communities of upland soils, up to 30 Тg year −1 (Denman et al., 2007). Many studies have investigated CH4 uptake in the soils of natural ecosystems and have found them to be the sink for atmospheric methane (Börjesson et al., 2001; Conrad and Rothfuss, 1991; Suwanwaree and Robertson, 2005). Conversion of natural undisturbed soils to arable cropping ecosystems has significantly reduced the CH4oxidising capacity of these soils (Le Mer and Roger, 2001). Agricultural practices also affect methanotrophic community structure (Knief et al., 2003; Seghers et al., 2003; Kravchenko et al., 2005). Biological methane oxidation is important for minimizing global climate change, and any negative impact or imbalance may be due to dramatic ecosystem change. Therefore, there is an insistent need for extensive research to study methanotrophic activity in various ecosystems. Methane oxidation is performed by methane oxidizing bacteria (MOB), which use methane both in energetic and constructive metabolism to the end products carbon dioxide and water (Hanson and

⁎

Corresponding author. E-mail address: [email protected] (I. Kravchenko).

http://dx.doi.org/10.1016/j.apsoil.2017.06.034 Received 13 February 2017; Received in revised form 23 June 2017; Accepted 28 June 2017 0929-1393/ © 2017 Elsevier B.V. All rights reserved.

Hanson, 1996).The methanotrophs are a subgroup of the methylotrophs and are generally characterized by their ability to use methane as their sole carbon and energy source (Hanson and Hanson, 1996). The key methanotrophic enzyme is methane monooxygenase (MMO), which occurs in both particulate (pMMO) and soluble (sMMO) forms. The pmoA gene encodes the β-subunit of pMMO and is included in the genome of the majority of known methanotrophs, except Methylocella and Methyloferula (Dedysh et al., 2000; Vorobev et al., 2011). For a long period, all methanotrophs were affiliated with Proteobacteria from the Methylocystaceae and Methylococcaceae families (Hanson and Hanson, 1996), but new aerobic methanotrophs were found in Gammaproteobacteria (Methylococcaceae, Crenothrix polyspora, and Clonothrix fusca), Alphaproteobacteria (Methylocystaceae and Beijerinckiaceae), the Verrucomicrobia phylum (“Methylacidiphilaceae”) and the candidate phylum NC10 (Stein et al., 2012). Like most other aerobic methane oxidizers, methane-oxidizing Verrucomicrobia (Methylacidiphilum and Methylacidimicrobium) use pMMO to catalyze the first step of the methane oxidation, but unlike most proteobacterial methanotrophs grow as autotrophs, using only carbon dioxide as the carbon source via the Calvin cycle (van Teeseling et al., 2014). The novel phylum NC10 represents bacteria capable of aerobic methane oxidation coupled to denitrification under anoxic conditions (Ettwig et al., 2010). In addition, a group

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2. Materials and methods

of methanogen-like anaerobic CH4-oxidizing archaea (MOA) has been described (Hallam et al., 2003). These MOA contain mcrA genes and are involved in a consortium that couples denitrification with anaerobic CH4 oxidation (Raghoebarsing et al., 2006). Moreover, ammonia oxidizers were also shown to be able to convert methane to methanol using an enzyme homologous to the methane monooxygenase of methanotrophs. However, it appears that they cannot grow using this process (Hyman and Wood, 1983; Jones and Morita, 1983). Until 2005, methanotrophs were regarded as organisms whose growth was obligatorily one-carbon compound-utilizing, but it was reported that Methylocella can utilize multi-carbon compounds besides methane (Dedysh et al., 2005). Crenothrix polyspora, a sheathed γ-Proteobacteria, was identified as another possible candidate facultative methanotroph (Stoecker et al., 2006). More recently, a pMMO-possessing methanotroph of the genus Methylocapsa, as well as some Methylocystis species, were demonstrated to be able to grow on acetate as the sole substrate (Belova et al., 2011; Dunfield et al., 2010). The facultative lifestyle in methanotrophs indicates that broader substrate utilization might be more common in methanotrophs than previously thought. Methane uptake in upland soils is mediated by aerobic methaneoxidizing bacteria, which are the only known biological sink of CH4. Despite the active study, the ecological representativeness of the data available for methane oxidation in aerated soils is insufficient. It is especially important to understand the role of Russian soils, which are not usually included in the general reviews of atmospheric methane uptake in soil (Kirschke et al., 2013; Serrano-Silva et al., 2014) or soil methanotroph diversity (Aronson et al., 2013) due to the lack of published data. The majority of known aerobic methanotrophs are not capable of using low-concentration atmospheric methane. Some representatives of Methylocystis and Methylosinus showed the presence of two isoforms of methane monooxygenase—conventional MMO1 and high-affinity MMO2 (Baani and Liesack, 2008; Kravchenko et al., 2010; Belova et al., 2013). The culture-independent studies of methanotrophic communities of soils with high-affinity methane oxidation capacity have revealed their presence and a correspondingly frequent predominance of methanotrophs from the novel phylogenetic pmoA- lines from Alpha- and Gammaproteobacteria named USC-alpha (upland soil cluster) and USCgamma (Knief et al., 2003; Kolb et al., 2005). USC-alpha bacteria are related to Methylocapsa acidiphila (Ricke et al., 2005) and USC-gamma bacteria are distantly related to Methylococcaceae (Knief et al., 2003). Сluster I, another rooted phylogenetic branch of uncultured methanotrophic Alphaproteobacteria, was found in forest soils (Ricke et al., 2005). Uncultured methanotrophs forming a compact phylogenetic cluster were found in virgin forest and steppe soils (Kizilova et al., 2013). Uncultured methanotrophs are responsible for atmospheric methane oxidation, as shown by stable tracer investigations (Bengtson et al., 2009; Menyailo et al., 2010). To date, there are no any culturable high-affinity methanotrophs, so data regarding their phylogeny and participation in atmospheric methane oxidation are elusive. In this study we analysed potential methane oxidation rates under laboratory conditions, and also assessed the diversity of aerobic methanotrophs using a culture-independent approach consisting of amplification and cloning of pmoA gene fragments in forest and arable soddy-podzolic soil samples. We hypothesized direct connections between the shifts in the microbial communities and the rates of methane oxidation activity.

2.1. Soil characteristics and sampling For this study, we chose two experimental sites at the Timiryazev Agricultural Academy, Moscow, Russia (55°49′ N., 37° 32. 24′ E). One experimental site (M1) was in a temperate mixed forest (Pinus spp., Abies spp., Betula spp.) inside the Forest Experimental Station and the other (M2) in a permanent barley (Hordeum vulgare) crop plot without fertilization inside the Long-term Field Experiment established by A.G. Doyarenko in 1912 on soddy-podzolic soils (Table 1). Soddy-podzolic soils (podzoluvisols according to FAO classification) are typical for a mixed forest zone from the 54–58° to 60° northern latitude and cover approximately 70% of the Moscow region’s territory. The mean temperatures of the coldest and warmest months are 2–14 and 9.5–16.5 °C, respectively, and the amount of annual precipitation ranges from 500 to 700 mm. The growing season varies from 120 to 174 days. Soddypodzolic soils are highly acidic (pH 3.5–5.5) with low base saturation, weak aggregation, considerable amounts of crude plant residue, and a predominance of brown humus. Preliminary studies from these sites indicated the surface CH4 uptake in the forest and the arable soil, respectively (Chistotin et al., 2012) (Table 1). On September 15, 2014, soil samples (0–20 cm) were collected from five points for each site, one in the centre and four at the corners of a 20 m × 20 m plot, and shipped to the lab in a cooler. Fresh soil samples were sieved (2 mm) and stored at 4–6 °C in aerated plastic bags before being analysed for potential methane oxidation. DNA and RNA extraction was performed immediately upon arrival to the laboratory (about three h) and stored at −80 °C until required for analysis. Both soils were characterized as deep soddy medium podzolic soils with a loamy, sandy texture (40% sand, 46% silt, and 14% clay) free of carbonate; the pH (1 M KCl) was 5.3 in the arable site and 4.2 in the forest site. 2.2. Potential rate of methane oxidation A radioisotope tracer technique with 14C-labeled methane was applied for evaluation of potential methane oxidation activity and assimilation processes according to a previously described protocol (Kravchenko et al., 2005). Briefly, 50 μl of an aqueous solution of 14CH4 (0.08 MBq; Izotop, Russia) was added to 5 g soil samples (fresh weight) in 20 ml Hungate tubes, and the final concentration was approximately 10 nL mL−1 (1.3 nmol CH4 g−1 or 10 ppm). After 72 h incubation at room temperature, soil samples were fixed in 2 ml of 1 N KOH. The separation and assays of 14C products were performed according a previously described protocol (Rusanov et al., 1998). 14CH4 was burned to 14CO2 in an oven over a catalyst (CoCl2-impregnated silica gel). 14 CO2 was captured in two traps (assembled before and after the oven with catalyst) containing a 10% solution of 2-phenylalanine in toluene scintillation liquid GS-106 (Monokristall, Ukraine). Upon removal of volatile products, the 14C content of organic matter was determined by the method of “wet” burning to 14CO2 in the presence of K2S3O8 at 105 °C. Radioactivity was measured with a RackBeta 1219 liquid scintillation counter (LKB, Sweden). Roughly, we considered the following parameters: amount of radioactive carbon dioxide, which formed during microbial oxidation of 14CH4, incorporation of 14C into

Table 1 Selected soil characteristics and field methane fluxes of studied sites. Shown are the mean values and standard deviations. Soil ID

Organic C, %

Total N, %

C:N

pH (1 M KCl)

NO3− + NH4+, (μg g−1)

16 s rRNA, (108 gene copies g−1)

pmoA (105 gene copies g−1)

CH4 flux,a (μg C m−2 h−1)

M1 M2

2.1 ± 0.3 1.2 ± 0.2

0.2 ± 0.04 0.1 ± 0.02

10.5 11.9

4.6 ± 0.05 5.3 ± 0.05

8.4 ± 0.2 8.3 ± 0.2

10.57 ± 1.26 8.64 ± 1.25

2.83 ± 0.25 0.46 ± 0.08

−19.0 ± 3.4 −2.6 ± 1.2

a

Chistotin et al. (2012).

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cells of the E. coli DH10 B strain. Transformed cells were spread over solid LB medium supplemented with ampicillin and X-gal and grown overnight at 37°. A total of 50 positive (white) clones were selected for each library (250 clones for site) and colony-based PCR with universal plasmid primers M13F and M13R was performed using these clones. The presence of the desired insert was checked using agarose (1.2%) electrophoresis.

microbial biomass and dissolved organic matter, and methane oxidation rate. Soil samples in which the NaOH solution was added before the radiotracer were used as the controls. All measurements were performed in triplicate. 2.3. DNA and RNA extraction and quantitative PCR DNA was extracted from 0.25 g of a soil sample with a Power Soil DNA Kit, and total RNA was extracted from a 1 g sample with a RNA Power Soil Isolation Kit (MO BIO Laboratories, Carlsbad, USA) according to manufacturer’s recommendations. Extraction was performed independently for each of the five sub-samples representing the same soil. The DNA and RNA were quantified using a NanoDrop spectrophotometer (Thermo Scientific, Wilmington, Germany). The RNA extracts were treated with an RTS DNase Kit (MO BIO Laboratories, Carlsbad, USA) and tested for complete removal of DNA by PCR targeting of the bacterial 16S rRNA gene. RNA extracts that did not result in amplification were reverse transcribed to cDNA using the MMLV RT Kit (Evrogen, Russia) according to the manufacturer instructions. Real-time quantitative PCR (qPCR) was performed with three technical replicates for each DNA (cDNA) sample using the primer set A189f–A682r for the total MOB community (Holmes et al., 1995) and EUB338f–EUB518r for the total bacterial community. The reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) was applied to detect and enumerate the active members of the microbial community. All PCR reactions were performed with 30 cycles and annealing temperatures of 56 °С, and 50 °С, respectively for qPCR and RTqPCR. The positive control was the pure culture of Methylosinus trichosporium OB3b; the negative control contained no DNA template. The PCR product of the pure culture was diluted serially from 102 to 108 copies μL−1 and amplified using real-time PCR to construct standard curves. Quantitative PCR (qPCR) was performed on a CFX96 Real-Time PCR Detection System (Bio-Rad, USA). The reaction mixture contained a ROX passive reference dye and SYBR GreenI (Syntol, Russia). At the completion of each run, melting curves for the amplicons were measured by raising the temperature in 0.5 °C-steps from 50 to 56 °С to 95 °С while monitoring fluorescence. The specificity of the PCR amplification was checked by examining the melting curves for Tm symmetry, and the lack of non-specific peaks. All reactions were performed in triplicate, and squared standard deviations ( ± SD) were calculated for each sample.

2.5. Design and evaluation of novel primers for the study of NUSC methanotrophs Nucleotide sequences of pmoA genes related to Native sites Uncultured Soil Cluster (NUSC) available in September 2014 from the GenBank (http://www.ncbi.nlm.nih.gov) and Integrated Microbial Genomes (http://img.igi.doe.gov) databases were aligned using ClustalW within the BioEdit suite and scanned for conserved regions within the pmoA gene for a suitable primer target site. Neighbourjoining phylogenetic trees were constructed from amino acid sequences to guide primer design using MEGA6 (Tamura et al., 2013). Nucleotide alignments were manually inspected for regions of homology and the degenerate primers UNF11 (CCTATTGCGCGACCA) andUNR1 (AGRAAGCCGGTRTARTCC) (330 bp) were designed for pmoAgene amplification. Self-complementarity and hairpin formation was avoided in primer design, and degeneracy was introduced to a maximum of three bases per primer. Primers were synthesized by Syntol (Moscow, Russia). The primer set was tested against a range of methanotrophs and nitrifiers, including Methylococcus capsulatus (Bath), Methylobacter whittenburyi, Methylomonas methanica S1, Methylosinus trichosporium OB3b, Methylocystis parvus OBBP, Nitrosomonas europaea and DNA isolated from chestnut soil, which were NUSC-like methanotrophs and were identified previously (Kizilova et al., 2013). The number of NUSC-pmoA gene copies in forest and agricultural soil was evaluated using modified primer concentrations and temperatures for fluorescence data acquisition. Twenty-five microliter PCR mixtures contained 5 pmol of each primer, 5 μl PCR buffer, and 5 μl template DNA. The PCR was performed under the following conditions: the initial denaturation step of 95 °C for 3 min was followed by 40 cycles of 95 °C for 15 s, 56 °C for 30 s, and 62 °C for 40 s. The final extension step was at 72 °C for 10 min. PCR-products were analysed by agarose gel electrophoresis, sequenced to confirm that the correct gene had been amplified, purified with a WizardSV Gel and PCR Clean-Up System (Promega, USA) and used to construct a standard curve and for clone library analysis. The specificity of the PCR amplification was checked by examining the melting curves for Tm symmetry, and a lack of non-specific peaks. All reactions were performed in triplicate, and squared standard deviations ( ± SD) were calculated for each sample. Amplification efficiencies for pmoA were calculated from the slopes of calibration curves and ranged from 93.4–94.8% (R2 = 0.9933–0.9972). The limit of quantification for pmoA in soil was determined to be 3 × 103copy numbers g −1. Molecular phylogenetic analysis of PmoA was performed using the maximum likelihood method. The evolutionary history was inferred using the Maximum Likelihood method based on the JTT matrix-based model (Jones et al., 1992). The tree with the highest log likelihood (−1338.7143) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree (s) for the heuristic search were obtained automatically by applying Neighbour-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model and selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 36 amino acid sequences. All positions containing gaps and missing data were eliminated. There were a total of 69 positions in the final dataset. Evolutionary analyses were conducted in MEGA6 (Tamura et al., 2013).

2.4. End-point PCR, DGGE and construction of clone libraries Methanotrophic communities were analysed based on the pmoA gene, which encodes a ß- subunit of the particulate methane monooxygenase (pMMO), and primers used were A189 and A682 (Holmes et al., 1995). Amplification was performed on a MyCycler thermocycler (Bio-Rad, USA). Amplification products were visualized on the 1.2% agarose gel, extracted from the gel and purified with a QIAquick Gel Extraction Kit (Qiagen, Germany). Purified PCR-products were separated using denaturing gradient gel electrophoresis (DGGE) in a nested PCR approach; therefore, a PCR template was amplified with internal primers A189GC and mb661 (Kizilova et al., 2013). DGGE was performed using the D-Code Universal Mutation Detection System (Bio-Rad, United States) at 60 °С and 200 V for 6 h with denaturing agents (formamide and urea) at 40–80%. After staining (ethidium bromide) and washing of the gel in sterile distilled water, all visible bands were excised, and DNA fragments were eluted from the gel by soaking in sterile MQ water for at least 24 h at 4 °С. Thereafter, the eluted DNA fragments were successfully reamplified with primers A189 and mb661 (Kizilova et al., 2013), and sequences were included in further analysis. Purified PCR products were also cloned into the pGEM-T vector using the Easy Vector System I (Promega, United States) and competent 269

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2.6. DNA sequencing and phylogenetic analysis

Table 2 Methane oxidation rates estimated by 14CH4 tracer technique in soil samples incubated with atmospheric methane concentrations. Given are the averages ± standard deviation.

In total, 750 clones were selected for analysis, and cloned inserts were completely sequenced on an ABI 3100 sequencing machine with Big Dye Terminator v.3 reagents (Applied Biosystems, USA). The subsequent sequences were checked against the GenBank using the megaBLAST tool to identify the closest matching sequence/organism and translated and aligned to a pmoA database using the BioEdit program. Phylogenetic analyses at the deduced amino acid sequence levels were performed using the MEGA5 (Tamura et al., 2011) program package. The results for NUSC-PmoA were depicted as a consensus tree, combining the results of neighbour-joining and maximum likelihood analyses. NUSC-pmoA sequences (OTU1) were deposited in the GenBank nucleotide sequence database with accession number KP271452.

Soil ID

14

CH4 transformation rate, (ng CH4 g soil−1 day−1) 14

М1 М2

СО2

0.70 + 0.10 0.28 + 0.1

14 C-biomass + dissolved

14

Potential methane oxidation rate, (ng CH4 g soil−1 day−1)

С

0.51 + 0.06 0.12 + 0.08

1.21 0.4

investigated methanotroph diversity in native and agricultural soils. 3.2. PCR-DGGE fingerprinting of methanotrophs DGGE profiles of methanotroph communities of forest biocenosis (M1) showed only 6–7 clearly visible bands, but in agricultural soils (M2) there were 12–13 bands (data not presented). Sequence analysis revealed that all dominant bands from M1 were distantly related (65–95% nucleotide similarity) to pmoA sequences of the uncultured methanotrophs from Hawaiian volcanic deposits and soils (King and Nanba, 2008) (Table 3). Methanotrophic communities in M2 soil appear to be more speciesrich. A diverse combination of Methylosinus, Methylocystis, and Methylocaldum were detected in M2 soil (Table 3). The increased diversity of methanotrophic bacteria in agricultural soils compared to native forest soils is in agreement with our findings for soils from the European part of Russia (Kravchenko et al., 2005; Kizilova et al., 2013), as well as soils from Thailand (Knief et al., 2003) and Brazil (Dörr et al., 2010).

2.7. Statistical analysis All data are expressed as the mean ± standard error. All of the results are given on a dry weight soil basis (oven dry, 24 h, and 105 °C). One-way analysis of variance was used to identify differences between unmanaged and arable sites at P < 0.05.The analysis was performed using Statistica software version 6.0. 3. Results 3.1. Potential methane-oxidizing activity in soil samples The rate of aerobic methane oxidation for unmanaged soddy-podzolic soil (M1) was recorded as 1.21 ng CH4 g soil −1 day−1, and agricultural soil (M2) showed a three-fold lower rate (Table 2). At the same time, the distribution of 14C between the CO2 and microbial biomass and metabolites was relatively similar in both soils. The primary product of bacterial methane oxidation was carbon dioxide, accounting for more than 50% of 14C introduced in either M1 or M2. The microbial biomass and dissolved carbon compounds incorporated 42 and 30% of 14C in forest and arable soils, respectively. We hypothesized that the differences in methanotrophic communities might be the reason for the distinction in actual carbon assimilation. Thus, we

3.3. Cloning analysis of pmoA To attempt to assess greater pmoA diversity in forest soil we varied amplification conditions, and the additional primer pairs A189/A682 and A189/A650 were used. We also applied 48 °C PCR annealing temperatures at which Verrucomicrobia pmoA have been amplified with the primer pair A189/A682 (Pol et al., 2007), but no amplification was

Table 3 Identification of closest relatives of pmoA genes fragments to GenBank sequences by sequencing of the excised dominant DGGE bands and megaBLAST analysis. Soil ID

Band ID

Nearest database neighbor in NCBI (accession number)

% DNA identity

Environmental location of the relative organism

М1

M1-2 M1-3 M1-4 M1-5 M1-6 M1-7 M1-8 M1-9 M1-10

Uncultured bacterium clone ML211 pmoAgene (EU723735) Uncultured bacterium clone ML211 pmoA (EU723735) Uncultured bacterium clone ML211 pmoA (EU723735) Uncultured bacterium clone ML211 pmoA (EU723735) Uncultured bacterium clone ML211 pmoA (EU723735) Uncultured bacterium clone ML211 pmoA (EU723735) Uncultured bacterium clone ML211 pmoA (EU723735) Nitrosospira sp. REGAU amoA (AY635572) Uncultured bacterial clone ML211 pmoA (EU723735)

95 97 97 69 95 87 77 73 77

Acacia koa forest soil Acacia koa forest soil Acacia koa forest soil Acacia koa forest soil Acacia koa forest soil Acacia koa forest soil Acacia koa forest soil Rendering plant activated sludge system Acacia koa forest soil

М2

M2-1

99

Landfill cover soil

M2-2 M2-3 M2-5 M2-6 M2-7 M2-9 M2-11 M2-12 M2-16

Uncultured bacterium isolate DGGE band particulate methane monooxygenase gene (EU292155) Methylocaldum sp. 05J-I-7 (EU275141) Methylosinus trichosporium (AJ459021) Nitrosospira sp. Wyke 2 AmoA (EF175098) Methylosinus trichosporium (AJ459021 Methylosinus trichosporium (AJ459021 Methylosinus trichosporium (AJ459021 Methylocystis sp. 10 (AJ459038) Methylosinus trichosporium (AJ459021) Uncultured soil bacterium partial amoA gene (AJ538174)

99 92 96 96 98 62 87 91 90

M2-17 M2-18 M2-19 M2-20

Methylocaldum sp. 05J-I-7 pmoA gene (EU275141) Nitrosospira sp. En13 amoA (EF175097) Uncultured ammonia-oxidizing bacterium clone slEASLc44 amoA (AY177930) Methylocystis sp. 10 (AJ459038)

92 92 78 95

Landfill upland soil Surface sediment Agricultural soil Surface sediment Surface sediment Surface sediment Agricultural soil Surface sediment Soil sample of maize plants growing in a greenhouse Landfill upland soil Craibstone soil Agricultural soil Agricultural soil

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observed. A189/A650 showed no product of the correct size, but amplification with A189/A682 was successful. This primer system is known to target not only the usual pmoA but also conventional versions, including uncultured and amoA. The majority of sequences (74%) in the clone library originated from the M1 soil were affiliated with pmoA and formed the compact group with high nucleotide similarity (98–100%) (Table 4). All other sequences were amoA. Phylogenetic analysis of PmoA demonstrated that dominant methanotrophs in the forest soil differed materially from the cultivated strains and formed a cluster with environmental clones from different ecosystems (Fig.1 ). We proposed that they are responsible for atmospheric methane oxidation in M1 soil and have developed a new pmoA-based primer system for their specific detection and quantification.

Table 4 Representative proportions of clones in each OTU group for each pmoA clone library. Soil ID

OTU # (clone type)

% of library

М1

1 (pmoA) 2 (amoA) 3 (amoA)

74 14 12

M2

1 2 3 4 5 6 7

6 24 14 14 16 6 20

(pmoA) (pmoA) (pmoA) (pmoA) (pmoA) (pmoA) (amoA)

Fig. 1. Phylogenetic dendrogram based on the derived amino acid sequences and indicating the relationship of the NUSC PmoA sequences with their closest match and known methanotrophs and ammonium oxidizers. The scale bar represents 0.1 substitutions per amino acid position. Bootstrap values which were < 55% are not shown.

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found between these methanotrophic communities, indicating that methanotroph diversity depends on the land use. Dominance of methanotrophs belonging to the NUSC-cluster was observed in forest soil with a high CH4 oxidation rate. This group is yet uncultivated, but we believe it to be responsible for atmospheric CH4 consumption. In agricultural soil with lower CH4 oxidation activity, the uncultured methanotrophs were displaced by diverse known methanotrophs belonging to Methylococcacea and Methylocystacea. Different hypotheses on the ecological strategies of high-affinity methanotrophs in well-aerated soils are discussed. They are: i) facultative methanotrophs dependent on multicarbon substrates (Nesbit and Breitenbeck, 1992); ii) ammonium-oxidizing bacteria in N-deficient environments (King, 1993), iii) cultivable methanotroph-induced highaffinity systems in response to starvation ((Dunfield and Conrad, 2000) or methanol addition (Benstead et al., 1998); and iv) uncultured true oligotrophs using atmospheric methane for energy and constructive metabolism (Bender and Conrad, 1992; Castro et al., 1995; Schnell and King, 1995). Cultivation-independent surveys of pmoA diversity, encoding a 27 kDa subunit of particulate methane monooxygenase (pMMO) have been successfully used to detect and identify methanotrophs in various environmental samples. This gene is present in almost all known aerobic methanotrophs and good correlation between phylogenies, inferred using pmoA and 16S rRNA genes, has been demonstrated (e.g., Heyer et al., 2002). Analysis of pmoA revealed the uncultured USC-α, USC-γ, JR-2, JR-3 and Cluster I as considerable or predominant groups of methanotrophs in aerated soils. In acidic forest soil, the number of USCα constituted 106–108pmoA gene copies g−1 or approximately 90% from total methanotrophs number and 2% of total bacteria number (Degelmann et al., 2010). Along with the results from other works, our data support a hypothesis that posits the presence or predominance of uncultured oligotrophic methanotrophs in native upland soils (Knief et al., 2003; Kolb et al., 2005; Ricke et al., 2005) and a pronounced shift in agricultural analogues to methanotrophs using high methane concentrations for growth. The results were in good agreement with the findings of Dörr et al. (2010), who observed in Brazilian ferralsols a prevalence of USCα in natural and afforested sites and higher relative abundances of Methylocystis and Methylococcus spp. in agricultural soil. In soddy-podzolic agricultural soil, Methylocystis-, Methylobacter- and Methylocaldum-like pmoA genes were found. In agricultural aerated soils (Kravchenko et al., 2002) and periodically drained paddy soils (Cai et al., 2016), emerging high-affinity CH4 oxidation activity was induced by incubation at elevated methane concentrations. These findings supported by metatranscriptome analysis suggest that atmospheric methane oxidation in these soils was catalysed by known methanotrophs (Cai et al., 2016). The important aspect of this study is that all uncultured methanotrophs from forest sites were affiliated with methanotrophic bacteria from different native ecosystems possessing pmoA with intermediary positions between methanotrophs and ammonium-oxidizers (amoA/ pmoA). Such pmoA sequences from uncultured bacteria were previously detected in aerated soils that oxidized atmospheric methane (Dörr et al., 2010; Barcena et al., 2011; Kizilova et al., 2013), but this is the first report of a dominance of these sequences in pmoA clone libraries. To study NUSC methanotrophs, we developed new pmoA-targeted primers. Their application allowed us to detect the presence, to evaluate the diversity, and to obtain quantitative information about this group of methanotrophs. The high content of NUSC pmoA transcripts gene copies indicates that these non-cultivable methanotrophs are an active component of the soil microbial community. Some uncultured methanotroph groups appear to have a restricted area distribution and may be used as biogeographical indicators. For example, USC-α were found mainly in acid soils, while USC-γ were found in soils with pH > 6 (Knief et al., 2003; Kolb, 2009); JR2 and JR3 have only been found in arid grasslands (Angel and Conrad, 2009; Judd et al., 2016). It is possible that NUSC methanotrophs are well adapted to the low methane concentrations characteristic of well-drained, low organic carbon forest

Grouping the pmoA sequences from the M2 clone library at a species level of 94% nucleotide similarity (Konstantinidis and Tiedje, 2004) revealed six phylotypes (Table 4). Sequence analysis has shown that 4 of these were affiliated with Gammaproteobacteria and closely related to Methylobacter (OTU 2, OTU 4 and OTU 5) and Methylocaldum (OTU 3). The OTU1 and OTU6 were closely related to Methylocystis. Consequently, in agricultural soils, high-affinity methanotrophs were displaced by low-affinity ones. This tendency was also specified in Brazil ferrosols by German researchers (Dörr et al., 2010). For all samples, no amplification product for soluble methane monooxygenase (sMMO) was obtained. We failed to detect USCα, USCγ or other clusters of uncultured methanotrophs or pmoA2-possessing bacteria. Thus, we concluded that sMMO-possessing and previously described groups of uncultured methanotrophs are likely to provide a minor contribution to atmospheric methane oxidation in soddy-podzolic soil. We hypothesized that dominant methane-oxidizing bacteria, which were only distantly related to known methanotrophs and formed a separate cluster with pmoA from different native environments, were responsible for atmospheric methane oxidation in soddy-podzolic soils. We named them NUSC (Native sites Uncultured Soil Cluster) and have designed the special primer set UNF11/UNR1for further study. Amplification of the DNA and cDNA from M1 soil with UNF11/ UNR1 primers resulted in a PCR product of 330 bp, and sequence analysis confirmed the NUSC cluster affiliation. We failed to obtain the PCR product with DNA extracted from M2 soil. Cloning analysis of the purified PCR product (three technical replicates, 50 clones) revealed 97–100% identity for all sequences, and we combined them into OTU1 for further phylogenetic analysis. We also successfully amplified NUSCpmoA on DNA isolated from soil samples stored for 6–8 years (air-dried and frozen at −18 °C). 3.4. pmoA genes abundance In M1 soil, the copy numbers of bacterial 16S rRNA and pmoA genes were found to be (10.57 ± 1.26) × 108 and (12.83 ± 0.25) × 105g soil −1, correspondingly (Table 1). In M2 soil, numbers of ribosomal genes were significantly lower (P < 0.05), and the number of pmoA genes was much lower than in M1 soil. A specific qPCR assay was used to enumerate NUSC-pmoA genes, which were found to be the dominant uncultivated group. The copy number of these putative pmoA genes was (9.2 ± 0.87) × 105 g soil −1 and the transcript number was (1.33 ± 0.31) × 106 g soil −1. 4. Discussion Atmospheric methane oxidation is a crucial processes for soil ecosystem functioning and has a very strong impact on global biogeochemistry. The soil methanotrophs that consume atmospheric methane, for example, in undisturbed forest soils, exhibit a high affinity for methane, and Michaelis–Menten constants (Km) are low, ranging from 2 to 348 ppmv. (Knief et al., 2003; Saari et al., 2004; Urmann et al., 2008). Current information on high-affinity methanotrophs is limited to pmoA gene sequences (Ricke et al., 2005; Degelmann et al., 2010; Bárcena et al., 2011; Martineau et al., 2014) and the phylogenetic identity of 16S rRNA gene is unknown. Thus, pmoA analysis is the only way to study uncultured soil methanotrophs. In the last decade, this problem has been intensively studied in different natural and semi-natural terrestrial ecosystems, and numerous data on atmospheric methane uptake by upland soils of forests and steppes and correlation to environmental parameters and land use were found (Smith et al., 2000; Dutaur and Verchot, 2007; Schaufler et al., 2010; Luo et al., 2013). At the same time, the characteristics of methanotrophic communities in such soils are poorly documented and there are no laboratory cultures of true high-affinity methanotrophs. Here, we characterized methanotrophs in native forest soddy-podzolic soil and soil under long-term land use. Important differences were 272

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soils, but with the current data set and without culturable relatives we cannot give a confident explanation about the ecological roles for this group. For the first time, we received data on the predominance in native soddy-podzolic soil of a new group of active bacteria that are proposed to oxidize atmospheric methane. The designed primers can be successfully applied in future studies of these microorganisms in other environments to evaluate their diversity, interactions with other soil microorganisms, impact of environmental factors on population dynamics and correlation with methane-oxidizing activity in soils. 5. Conclusions This study provided evidence that soddy-podzolic soils are a potential sink for atmospheric CH4. Native forest soil harbours a low-diversity methanotrophic community with a high abundance of putative uncultured methanotrophs that most likely consume atmospheric CH4. In soil with an old agriculture history and relatively small CH4 uptake rates, the wealth of the NUSC group was below the detection limit, but a diverse methanotrophic community with known Type I and Type II methanotrophs was found. Our study has provided a set of novel primers that detect the target genes for uncultured methanotrophs, confirming their potential usefulness in future studies in microbial consortia and natural environments. Rapid and inexpensive nextgeneration genome sequencing is widely used in current microbial ecology, but the use of specific primers will continue to be needed for the detection of functional genes in heterogeneous environmental samples. It is clear that further studies will be necessary to examine the distribution of novel uncultured bacteria throughout upland soils and determine their role in mitigating the impact of methane in the context of global warming. Acknowledgments This work was supported by the RFBR grants (numbers 13-04-00603 and 16-04-00136). We highly appreciate the field assistance provided by Dr. Maxim Chistotin and 14C analysis by Dr. Leonid Dulov. References Angel, R., Conrad, R., 2009. In situ measurement of methane fluxes and analysis of transcribed particulate methane monooxygenase in desert soils. Environ. Microbiol. 11, 2598–2610. Aronson, E.L., Allison, S.D., Helike, B.R., 2013. Environmental impacts on the diversity of methane cycling microbes and resultant functions. Front. Microbiol. 4, 47–56. Bárcena, N.G., Finster, K.W., Yde, J.C., 2011. Spatial patterns of soil development, methane oxidation, and methanotrophic diversity along a Rrceding glacier forefield, Southeast Greenland. Arct. Antarct. Alp. Res. 43, 178––188. Börjesson, G., Chanton, J., Svensson, B.H., 2001. Methane oxidation in two Swedish landfill covers measured with carbon-13 to carbon-12 isotope ratios. J. Environ. Qual. 30, 369–376. Baani, M., Liesack, W., 2008. Two isozymes of particulate methane monooxygenase with different methane oxidation kinetics are found in Methylocystis sp. strain SC2. Proc. Natl. Acad. Sci. U. S. A. 105, 10203–10208. Belova, S.E., Baani, M., Suzina, N.E., Bodelier, P.L.E., Liesack, W., Dedysh, S.N., 2011. Acetate utilization as a survival strategy of peat-inhabiting Methylocystis spp. Environ. Microbiol. Rep. 3, 36–46. Belova, S.E., Kulichevskaya, I.S., Bodelier, P.L.E., Dedysh, S.N., 2013. Methylocystis bryophila sp. nov., a facultatively methanotrophic bacterium from acidic Sphagnum peat, and emended description of the genus Methylocystis (ex Whittenbury et al., 1970) Bowman et al., 1993. Int. J. Syst. Evol. Microbiol. 63, 1096––1104. Bender, M., Conrad, R., 1992. Kinetics of CH4 oxidation in oxic soils exposed to ambient air or high CH4 mixing ratios. FEMS Microbiol. Ecol. 101, 261–270. Bengtson, P., Basiliko, N., Dumont, M.G., Hills, M., Murrell, J.C., Roy, R., Grayston, S.J., 2009. Links between methanotroph community composition and CH4 oxidation in a pine forest soil. FEMS Microbiol. Ecol. 70, 356––366. Benstead, J., King, G.M., Williams, H.G., 1998. Methanol promotes atmospheric methane oxidation by methanotrophic cultures and soils. Appl. Environ. Microb. 64, 1091–1098. Cai, Y., Zheng, Y., Bodelier, P.L.E., Conrad, R., Jia, Z., 2016. Conventional methanotrophs are responsible for atmospheric methane oxidation in paddy soils. Nat. Commun. 7, 11728. Castro, M.S., Steudler, P.A., Melillo, J.M., Aber, J.D., Bowden, R.D., 1995. Factors controlling atmospheric methane consumption by temperate forest soils. Global Biogeochem. Cycle 9, 1––10.

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