Soil samples were collected from two different areas, Caldeirão and Barro Branco. The Caldeirão experimental research station from Embrapa Amazôonia Ocidental is located in Iranduba County in the Brazilian Central Amazon (03°26′ 00^′′ S, 60°23′ 00^′′ W). The other sampling area near the Barro Branco community is located in the Manacapuru County in the Brazilian Central Amazon (03°18′ 12^′′ S, 60°31′ 45^′′ W). ADE soils and their adjacent soils were collected from both areas. In both cases, the distance between the ADE soil zone and the adjacent soil zone was ∼2 km.

The soils were classified based on the World Reference Base for Soil Resources (FAO, 1998). ADE soils were classified as Hortic Anthrosol (i.e., reference horizon that results from prolonged habitation with casual additions of domestic organic refuse and cultural material). The adjacent soil from Caldeirão was classified as Haplic Acrisol (i.e., clay-rich soils with low fertility and toxic amounts of Al). The adjacent soil from Barro Branco was classified as Oxisol (i.e., red or yellowish soils with <10% weatherable minerals and low cation exchange capacity). At both areas, ADE soil and adjacent soil were sampled from secondary forest sites and agricultural sites cultivated with manioc (Manihot esculenta). The forested ADE and adjacent soil sites at Caldeirão were under ∼40-year-old secondary forest stands. At Barro Branco, the secondary forests were about 20 years-old. The agricultural sites in ADE and adjacent soils at Caldeirão had been used for manioc cultivation for at least 40 years, whereas the sites at Barro Branco had been deforested 5-years previously for conversion to plantations.

Soil samples were collected in February 2013. Three environmental replicates were collected from each sampling site. The sample plot (location) at each site was determined by choosing a random point, and from this reference point three sampling points (sublocations) 5 m apart were chosen for the collection of intact soil cores of 5 cm in diameter and 15 cm in length. Soil samples were collected in triplicate from each sublocation, which were subsequently homogenized to produce a composite soil sample for each sublocation. A total of 24 samples corresponding to the four sites (forested ADE, cultivated ADE, forested adjacent, and cultivated adjacent) from each of the two areas (Caldeirão and Barro Branco) were prepared. The samples for DNA extraction were transported from the field to the laboratory in an insulated box with dry ice. Approximately 1 kg of soil samples were collected from each of the 24 sublocations and sent to the department of Soil and Plant Nutrition of Embrapa Western Amazon. The frozen and unsieved soil samples were used for DNA extraction, whereas the 1 kg samples of fresh soil were sieved (2 mm mesh diameter) and used for the determination of soil chemical properties and CH₄ oxidation potentials. Soil pH (H₂O, 1:1), soil extractable Al, Ca, Fe, K, Mg, Mn, P, Zn, soil organic carbon (SOC), total C, total N, and cation exchange capacity were determined according to the methods described by Embrapa (1997).

Potential CH₄ oxidation rates were measured using soil from each sampling point (sublocation). Ten grams of fresh sieved soil was placed into a 120 ml serum vial in duplicate (Bull et al., 2000; Horz et al., 2002; Shrestha et al., 2012). The bottles were sealed with butyl rubber stoppers, and final mixing ratios of 10, 100, 1000, and 10 000 ppmv of CH₄ was injected into the gas headspace of the vials. The incubation of soil microcosms was performed at 25°C in the dark with shaking at 150 rpm for up to 19 days. CH₄ concentrations were measured on a daily basis by gas chromatography with a flame ionization detector using 0.5 ml gas samples from the bottle headspaces, as described previously (Shrestha et al., 2012). CH₄ oxidation rates were calculated by linear regression of CH₄ consumption versus time for the incubations with 10 ppm CH₄.

Soil DNA extractions were carried out in triplicate from 0.3 g wet weight subsamples of each soil sample. Extractions were performed using the Nucleospin soil DNA extraction kit (Macherey-Nagel, Düren, Germany) according to the manufacturer’s instructions. DNA was quantified using a Qubit dsDNA HS Assay (Molecular Probes, Invitrogen, USA). The triplicate DNA extracts of each sampling sublocation were pooled.

Real-time quantitative PCR (qPCR) with three technical replicates for each sublocation DNA sample was performed to determine the copy numbers of the pmoA genes. The qPCR assay using the primer set A189f-mb661r was used to target the conventional pmoA genes of Methylocystaceae and Methylococcaceae methanotrophs (Costello and Lidstrom, 1999; Kolb et al., 2003). The assay using primers A189f-Forest675r was used to target USCα pmoA genes (Kolb et al., 2003). The qPCRs were performed with the SYBR Green JumpStart Taq ReadyMix System (Sigma, Taufkirchen, Germany) on an iCycler instrument (Bio-Rad, Munich, Germany). The data were analyzed using Bio-Rad CFX Manager (version 3.0) software. PCR mixtures and thermal cycling conditions were performed as described previously by Kolb et al. (2003). Briefly, the A189f-Forest675r assay was performed in 25 μl reaction mixtures containing 12.5 μl of SYBR Green Jump-Start Taq Ready Mix (Sigma), 1 μM of each primer, 50 ng of BSA (Roche, Mannheim, Germany), and 4 mM MgCl₂ (Sigma). The assay for the abundance of conventional pmoA genes (A189f-mb661r) was performed in 25-μl reaction mixtures containing 12.5 μl of SYBR Green Jump-Start Taq Ready Mix (Sigma), 0.667 μM of each primer and 4 mM MgCl₂. Standards for qPCR were generated by serial dilution of stocks of a known number of plasmids containing a single cloned copy of a Methylococcus pmoA gene or a USCα pmoA gene, according to the assay. All samples from an experiment were run on a single plate.

PCR was performed using the primers A189f and A682r that amplify a broad range of pmoA, amoA, and related sequences (Holmes et al., 1995; Lüke and Frenzel, 2011). The PCR components and conditions were identical to that described previously (Angel and Conrad, 2009). Briefly, the 50 μl reaction contained 5 μl of 10x AccuPrime^TM PCR Buffer II (Invitrogen, Karlsruhe, Germany), additional 1.5 mM MgCl₂ (to a final concentration of 3 mM), 0.5 mM of each primer (Sigma), 50 ng of BSA (Roche) and 1 μl of Taq DNA polymerase (Invitrogen). All ADE samples could be amplified directly with the barcoded primer sets; however, it was not possible to obtain amplicons of the expected size for the adjacent soil samples using these primers. Therefore, a 2-step PCR procedure in which conventional primers (i.e., without barcodes) was used in the first step followed by a successive low-cycle-number amplification using the barcoded primers, as described by Berry et al. (2011). This approach successfully produced PCR amplicons of the expected size. To allow comparisons, the same 2-step PCR approach was used for all samples. Five replicate PCR reactions were performed for each sample. After amplification, PCR reactions were pooled and loaded on 1% agarose gel stained in GelRed^TM (Biotium Inc., Hayward, CA, USA). The DNA fragment of the correct size was excised from the agarose gel and eluted in 30 μl H₂O using the QIAquick gel extraction kit (Qiagen, Hilden, Germany). The purified PCR products from all samples were mixed in a 1:1 ratio and sequenced at the Max Planck-Genome-Centre Cologne (Cologne, Germany) using a Roche 454 Genome Sequencer FLX System.

A detailed description of the procedures used for sequence analysis was described previously (Dumont et al., 2014). In this study, only sequences with read lengths longer than 300 bp were used for further analysis. The sorting of sequences according to barcodes, trimming and quality filtering were processed using mothur version 1.29.2 (Schloss et al., 2009). Chimeric sequences were identified and removed using uchime (Edgar et al., 2011) implemented in mothur. Classification of pmoA sequences was performed using standalone TBLASTN version 2.2.26+ against a curated database of pmoA sequences and the lowest common ancestor (LCA) algorithm in MEGAN version 4.70.4 (Huson et al., 2011), as described previously (Dumont et al., 2014). A total of 110,437 sequences were obtained. 42,213 reads (a range from 9022 to 2977 reads per library) remained after basic quality filtering. The amplification of non-target sequences is common with these primers (Bourne et al., 2001) and these contaminants were identified by an absence of similarity to the reference database and removed from further analysis. The contaminants corresponded to an average of 57% from ADE samples and 87% from adjacent soil samples. A total of 13,595 reads remained after removing these contaminant sequences, corresponding to an average of 2802 reads from ADE and 597 from adjacent soil samples.

Representative sequences from each pmoA clade identified during the sequence analysis were selected for further analysis. These reads were translated into amino acid sequences and added to a reference pmoA/amoA phylogenetic tree using parsimony in ARB (Ludwig et al., 2004).

Sequences are available through the Metagenomics Rapid Annotation (MG-RAST) server ¹ with accession numbers 4577576.3 (TPISFBB2), 4577577.3 (TPISFBB3), 4577578.3 (TPISFBB4), 4577570.3 (TPIMBB2), 4577571.3 (TPIMBB3), 4577572.3 (TPIMBB5), 4577565.3 (ADJSFBB2), 4577566.3 (ADJSFBB3), 4577560.3 (ADJMBB2), 4577561.3 (ADJMBB3), 4577562.3 (ADJMBB4), 4577579.3 (TPISFC3), 4577580.3 (TPISFC4), 4577581.3 (TPISFC5), 4577573.3 (TPIMC2), 4577574.3 (TPIMC3), 4577575.3 (TPIMC4), 4577567.3 (ADJSFC2), 4577568.3 (ADJSFC4), 4577569.3 (ADJSFC5), 4577563.3 (ADJMC3), 4577564.3 (ADJMC4).

Differences in soil chemical properties were tested by one-way analysis of variance. Two-way analysis of variance model was used to assess differences in pmoA gene abundances between land uses and soil types. Test of proportions was used to observe significance of proportion difference in pmoA gene relative abundance generated by amplicon pyrosequencing between ADE and adjacent soils using prop.test in the R Stats Package ². Significance level of p < 0.05 was applied for all statistical analyses and performed using R version 3.03 (R Foundation for Statistical Computing).

The soil chemical properties are presented in Table 1. As previously reported, the measured soil chemical properties at the Caldeirão Experimental Station showed a clear distinction between ADE and adjacent soil samples (Taketani et al., 2013; Brossi et al., 2014). ADE soils from Barro Branco had similar properties to those at Caldeirão, with relatively high pH, Ca, CEC, K, Mg, Mn, P, SOC, and Zn compared to their adjacent soils. These characteristics indicate the potential for high agricultural productivity. In contrast, the adjacent soils (i.e., Haplic Acrisol and Oxisol) had lower pH and higher Al and Fe.

CH₄ oxidation was immediate at concentrations of 10 and 100 ppmv, but a lag phase of 6–10 days was observed for concentrations of 1000 and 10,000 ppmv (results not shown). Relatively high rates of high-affinity CH₄ oxidation (10 ppm CH₄) were observed in all soils from the forested sites and the ADE soil used for manioc cultivation at the Barro Branco area (Table 2). In contrast, the CH₄ oxidation rates were more than one-order of magnitude lower in both plantations in adjacent soil and the ADE plantation soil at Caldeirão. The precise history of these soils is not available, but members of the local communities indicated that manioc has been cultivated in ADE soil at the Caldeirão site for living memory (>40 years), whereas the Barro Branco ADE soil was only recently (5 years) converted from forest to agriculture by slash-and-burn.

Quantitative real-time PCR assays were used to determine the copy numbers of pmoA genes in ADE and adjacent soils from both secondary forest and the manioc cultivation sites (Figure 1). The pmoA qPCR assay with primers A189f-mb661r targets methanotrophs belonging to the Methylococcaceae and Methylocystaceae families and generally has poor specificity for the genes from other families of methanotrophs. The abundance of genes detected with this assay (Figure 1A) was not significantly affected by soil type or land use. Based on the diversity of pmoA genes detected in the soils (Figure 2), these results correspond to Methylocystis pmoA genes. Another qPCR assay was used to specifically enumerate USCα pmoA, which are a common uncultivated group associated with atmospheric CH₄ oxidation. In ADE soils, the abundances of USCα pmoA (Figure 1B) were more than two-orders of magnitude higher than Methylocystis pmoA genes (Figure 1A). USCα were below the detection limit (1 × 10⁴ copies g^-1 dry weight soil) in the plantations of adjacent soils. Taking the data from Barro Branco and Caldeirão sites together, the abundance of USCα pmoA was significantly higher in ADE than adjacent soil (ANOVA, p < 0.0001), but the difference in abundance based on land use (forested versus cultivated) was not significant (ANOVA, p = 0.77).

The methanotroph communities in the soils were analyzed by pmoA gene pyrosequencing. PCR using the A189f-A682r primer combination retrieves diverse pmoA-related genes, including the proteobacterial pmoA genes and those from uncultivated methanotrophs believed to be responsible for atmospheric CH₄ uptake in upland soils (McDonald et al., 2008). A known problem with these primers is a tendency to co-amplify non-specific sequences, which can make clone libraries useless (Bourne et al., 2001). Non-specific amplification with these primers was also observed in our pyrosequencing data, with an average of 87% of reads from adjacent soils corresponding to non-target reads. The advantage of relatively high number of reads obtainable by pyrosequencing compared with clone libraries meant that sufficient numbers of genuine pmoA sequences were still available to allow for comparisons in pmoA diversity between the samples.

Almost all sequences passing the quality-filtering steps were assigned to seven clades, which were defined and described previously (Lüke and Frenzel, 2011). Representative sequences from each of these clades were added to a database of pmoA and amoA sequences and are shown in a simplified phylogenetic tree (Figure 2). The most abundant clades identified were USCα, tropical upland soil cluster (TUSC) and Methylocystis. The other less abundant clades were RA21, M84-P105, AOB-rel, and the AOB-like group. AOB-rel is also referred to in the literature as Cluster 1 (Kolb et al., 2005).

The relative abundance of the clades from each of the sites is shown in Figure 3. A test of proportions indicated that, with the exception of AOB-like sequences, the relative abundances of these clades were significantly different (p < 0.05) between the ADE and the adjacent soils (Table S1).

Data from the pmoA qPCR assays and amplicon pyrosequencing approaches provided independent numbers to compare the relative abundance of pmoA clades in the soils. Based on the diversity of pmoA detected by pyrosequencing, Methylocystis was the only group present that was a target for the A189f-mb661r pmoA qPCR assay. Therefore, the abundance of pmoA detected with this qPCR assay was taken as the abundance of Methylocystis pmoA genes. Calculating the relative abundance of Methylocystis and USCα from the qPCR assays (Figure 4A) and the pyrosequencing dataset (Figure 4B) showed relatively good agreement.

The major difference between these data was that USCα in the cultivated adjacent soils was below the detection limit of the qPCR assay (Figure 1B) and therefore its relative abundance was calculated as 0 (Figure 4A); however, USCα sequences were detected of ∼20% of Methylocystis in the pyrosequencing dataset from these samples (Figure 4B).

The CH₄ oxidation rates were relatively high in forested sites. This is in agreement with other studies of tropical forests soils (Verchot et al., 2000; Veldkamp et al., 2008; Zhang et al., 2008; Dörr et al., 2010). Surprisingly, the ADE soil at the Barro Branco site under manioc cultivation showed a CH₄ oxidation rate similar to that of the forested sites. Many studies have shown that conversion of forest to agriculture diminishes CH₄ uptake. For example, after 2 years of agriculture a Norwegian soil showed a fivefold decrease in CH₄ oxidation rate (Jensen and Olsen, 1998). At the time of sampling, the ADE soil at Barro Branco had been used for manioc cultivation for ∼5 years, suggesting that it too should have shown a decreased CH₄ oxidation potential. The ADE soil at the manioc planation at the Caldeirão area, which has a longer history of cultivation, showed a decreased CH₄ oxidation potential. The cultivated ADE site at Barro Branco had been burned to clear the land, which may have also influenced in CH₄ oxidation capacity as in some cases fire has been shown stimulate atmospheric CH₄ oxidation (Jaatinen et al., 2004).

Differences in the methanotroph communities were found between ADE and adjacent soils under secondary forest and manioc cultivation, indicating that the methanotrophic community is altered depending on soil type and land use. USCα were the predominant methanotrophs in all ADE soils and the forested adjacent soils. This group is as yet uncultivated, but is believed to be responsible for atmospheric CH₄ consumption in many forest soils (Dunfield, 2007; Kolb, 2009; Nazaries et al., 2013). The abundance of USCα pmoA genes was ∼1 × 10⁷ per gram dry weight in the ADE soils, which was one-order of magnitude higher than in the forested sites of the adjacent soils. In comparison, the same assay used to quantify USCα in a German forest soil detected ∼1 × 10⁶ gene copies per gram dry weight of soil (Kolb et al., 2005), suggesting that their abundance in ADE was relatively high.

It was surprising that USCα abundances were equally high in the cultivated and forested ADE soils (Figure 1B). This pattern was different for the adjacent soils where they were below the qPCR detection limit in the cultivated soils, indicating abundances at least two-orders of magnitude lower than the forested sites. In comparison, the manioc plantation in ADE soil at Caldeirão has a long history of agriculture use, yet the USCα abundance was only threefold lower than in the corresponding forested soil. To the best of our knowledge, this is the first study to detect a high absolute and relative abundance of USCα in agricultural soils. Priemé et al. (1997) showed that CH₄ oxidation rates took more than 100 years to reach pre-cultivation levels and that the highest rates were in the oldest (200 years) woodlands. The apparent resilience of USCα populations in ADE soil compared with other upland soils, possibly from a protective property of ADE, suggests that recovery of CH₄ oxidation capacity after agricultural abandonment might be faster in ADE than other types of upland soil.

Also of note in this study was that the CH₄ uptakes rates were relatively low in cultivated ADE soil at Caldeirão, but USCα abundance in this soil was relatively high. One possible explanation for this lack of correlation is that USCα methanotrophs can incorporate acetate and possibly other organic carbon substrates (Pratscher et al., 2011), suggesting that CH₄ oxidation is a facultative trait in these organisms and CH₄ is oxidized only under certain conditions. Evidence that USCα are not obligate methanotrophs include reported failures to sufficiently label their nucleic acids with ¹³CH₄ for stable isotope probing (Bengtson et al., 2009; Pratscher et al., 2011), and an ability of many of their closest cultivated relatives to grow using multicarbon compounds (Tamas et al., 2014). Another possibility is that the USCα methanotrophs in this ADE soil at Caldeirão have been able to remain dormant, or possibly that DNA from dead cells is relatively stable in ADE soil.

The diversity of methanotrophs observed in this study was similar to the observations 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 under conventional farming. Among the cultivated methanotrophs, we only detected Methylocystis pmoA and no conventional pmoA genes from Methylococcaceae methanotrophs; however, the unconventional M84-P105 pxmA sequences, which have been shown to belong to members of the Methylococceae (Tavormina et al., 2011), were detected in cultivated adjacent soils suggesting a low abundance of these methanotrophs in some soils (Figure 3). Although the relative abundance of Methylocystis was high in the adjacent soils from manioc plantation sites (Figure 3), no difference in their absolute abundance between ADE and adjacent soil, or between forested and cultivated sites was observed at this sampling time (Figure 1). Methylocystis have been shown to be important consumers of CH₄ in hydromorphic soils under dry conditions when CH₄ concentrations are relatively low (Knief et al., 2005). These Methylocystis possess an unconventional pMMO gene, termed pMMO2 (Ricke et al., 2004), which is expressed under low CH₄ (Baani and Liesack, 2008). We only detected two pmoA2 gene sequences in our pyrosequencing dataset (data not shown), suggesting that conditions in these Amazonian soils at the time of this analysis were not favorable for pMMO2-possessing oligotrophic Methylocystis species.

Other pmoA-related gene sequences were detected, such as TUSC, AOB-rel and AOB-like groups. The AOB-like sequences correspond to the amoA genes of Nitrosospira and Nitrosomonas (Figure 2). In ADE soils, these amoA sequences were only detected in plantation soil, which is likely a consequence of enrichment by ammonium fertilizer applied to the soil for manioc cultivation. The TUSC and AOB-rel groups have not been linked to cultivated organisms and the function of the enzyme encoded by these genes is not known (Lüke and Frenzel, 2011). TUSC or “tropical upland soil cluster” is also termed “Cluster 2” elsewhere (Knief et al., 2005). As the name implies, they were found to be abundant in some tropical upland soils (Knief et al., 2005), but have also been detected in temperate forest soil (Knief et al., 2003). It is noteworthy that the relative abundance of TUSC tended to mirror USCα in these Amazonian soils. One possibility to explain this correlation is that TUSC sequences are a divergent pmoA gene found in USCα methanotrophs, such as the case with M84-P105 pxmA in Methylomonas and pmoA2 in Methylocystis; however, other studies have not observed a correlation between USCα and TUSC relative abundances (Kolb, 2009; Dörr et al., 2010).