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Deforestation threatens the integrity of the Amazon biome and the ecosystem services it provides, including greenhouse gas mitigation. Forest-to-pasture conversion has been shown to alter the flux of methane gas (CH4 ) in Amazonian soils, driving a switch from acting as a sink to a source of atmospheric CH4 . This study aimed to better understand this phenomenon by investigating soil microbial metagenomes, focusing on the taxonomic and functional structure of methane-cycling communities. Metagenomic data from forest and pasture soils were combined with measurements of in situ CH4 fluxes and soil edaphic factors and analysed using multivariate statistical approaches. We found a significantly higher abundance and diversity of methanogens in pasture soils. As inferred by co-occurrence networks, these microorganisms seem to be less interconnected within the soil microbiota in pasture soils. Metabolic traits were also different between land uses, with increased hydrogenotrophic and methylotrophic pathways of methanogenesis in pasture soils. Land-use change also induced shifts in taxonomic and functional traits of methanotrophs, with bacteria harbouring genes encoding the soluble form of methane monooxygenase enzyme (sMMO) depleted in pasture soils. Redundancy analysis and multimodel inference revealed that the shift in methane-cycling communities was associated with high pH, organic matter, soil porosity and micronutrients in pasture soils. These results comprehensively characterize the effect of forest-to-pasture conversion on the microbial communities driving the methane-cycling microorganisms in the Amazon rainforest, which will contribute to the efforts to preserve this important biome.

Amazonian forest conversion into agricultural and livestock areas is considered one of the activities that contribute most to the emission of greenhouse gases, including methane. Biogenic methane production is mainly performed by methanogenic Archaea, which underscores the importance of understanding the drivers shaping microbial communities involved in the methane cycling and changes in methane metabolism. Here, we aimed to investigate the composition and structure of bacterial and archaeal communities in tropical soils in response to land-use changes, emphasizing the methanogenic communities. We collected soil samples from primary forest, pasture, and secondary forest of the Amazonian region and used a strategy based on the enrichment of the methanogenic community with three different methanogenic substrates followed by measurements of methane emission, quantification of mcrA gene copies by qPCR, and total 16 S rRNA gene sequencing (metataxonomics). We observed variations in the structure of bacterial and archaeal communities of soils under different uses. The richness of methanogenic communities was higher in pasture than forest soils and this richness remained during the incubation period, and as a consequence, the enrichment induced earlier methane emission in pastures-derived samples. Furthermore, pastures enrichments exhibited methanogenic archaea networks more complex than primary and secondary forests. In conclusion, pastures harbor a richer and more responsive methanogenic community than forest samples, suggesting that conversion of forest areas to pasture may boost methane emission.

Understanding the effects of forest-to-agriculture conversion on microbial diversity has been a major goal in soil ecological studies. However, linking community assembly to the ruling ecological processes at local and regional scales remains challenging. Here, we evaluated bacterial community assembly patterns and the ecological processes governing niche specialization in a gradient of geography, seasonality, and land-use change, totaling 324 soil samples, 43 habitat characteristics (abiotic factors), and 16 metabolic and co-occurrence patterns (biotic factors), in the Brazilian Atlantic Rainforest, a subtropical biome recognized as one the world's largest and most threatened hotspots of biodiversity. Pairwise beta diversities were lower in pastures than in forest and no-till soils. Pasture communities showed a predominantly neutral model, regarding stochastic processes, with moderate dispersion, leading to biotic homogenization. Most no-till and forest microbial communities followed a niche-based model, with low rates of dispersal and weak homogenizing selection, indicating niche specialization or variable selection. Historical and evolutionary contingencies, as represented by soil type, season, and dispersal limitation were the main drivers of microbial assembly and processes at the local scale, markedly correlated with the occurrence of endemic microbes. Our results indicate that the patterns of assembly and their governing processes are dependent on the niche occupancy of the taxa evaluated (generalists or specialists). They are also more correlated with historical and evolutionary contingencies and the interactions among taxa (i.e., co-occurrence patterns) than the land-use change itself.

Cattle ranching is the largest driver of deforestation in the Brazilian Amazon. The rainforest-to-pasture conversion affects the methane cycle in upland soils, changing it from sink to source of atmospheric methane. However, it remains unknown if management practices could reduce the impact of land-use on methane cycling. In this work, we evaluated how pasture management can regulate the soil methane cycle either by maintaining continuous grass coverage on pasture soils, or by liming the soil to amend acidity. Methane fluxes from forest and pasture soils were evaluated in moisture-controlled greenhouse experiments with and without grass cover (Urochloa brizantha cv. Marandu) or liming. We also assessed changes in the soil microbial community structure of both bare (bulk) and rhizospheric pasture soils through high throughput sequencing of the 16S rRNA gene, and quantified the methane cycling microbiota by their respective marker genes related to methane generation (mcrA) or oxidation (pmoA). The experiments used soils from eastern and western Amazonia, and concurrent field studies allowed us to confirm greenhouse data. The presence of a grass cover not only increased methane uptake by up to 35% in pasture soils, but also reduced the abundance of the methane-producing community. In the grass rhizosphere this reduction was up to 10-fold. Methane-producing archaea belonged to the genera Methanosarcina sp., Methanocella sp., Methanobacterium sp., and Rice Cluster I. Further, we showed that soil liming to increasing pH compromised the capacity of forest and pasture soils to be a sink for methane, and instead converted formerly methane-consuming forest soils to become methane sources in only 40-80 days. Liming reduced the relative abundance of Beijerinckiacea family in forest soils, which account for many known methanotrophs. Our results demonstrate that pasture management that maintains grass coverage can mitigate soil methane emissions, compared to bare (bulk) pasture soil.

The Amazon rainforest is a biodiversity hotspot and large terrestrial carbon sink threatened by agricultural conversion. Rainforest-to-pasture conversion stimulates the release of methane, a potent greenhouse gas. The biotic methane cycle is driven by microorganisms; therefore, this study focused on active methane-cycling microorganisms and their functions across land-use types. We collected intact soil cores from three land use types (primary rainforest, pasture, and secondary rainforest) of two geographically distinct areas of the Brazilian Amazon (Santarém, Pará and Ariquemes, Rondônia) and performed DNA stable-isotope probing coupled with metagenomics to identify the active methanotrophs and methanogens. At both locations, we observed a significant change in the composition of the isotope-labeled methane-cycling microbial community across land use types, specifically an increase in the abundance and diversity of active methanogens in pastures. We conclude that a significant increase in the abundance and activity of methanogens in pasture soils could drive increased soil methane emissions. Furthermore, we found that secondary rainforests had decreased methanogenic activity similar to primary rainforests, and thus a potential to recover as methane sinks, making it conceivable for forest restoration to offset greenhouse gas emissions in the tropics. These findings are critical for informing land management practices and global tropical rainforest conservation.

The microbial composition of the rhizosphere and greenhouse gas (GHG) emissions under the most common input combinations in maize (Zea mays L.) cultivated in Brazil have not been characterized yet. In this study, we evaluated the influence of maize stover coverage (S), urea-topdressing fertilization (F), and the microbial inoculant Azospirillum brasilense (I) on soil GHG emissions and rhizosphere microbial communities during maize development. We conducted a greenhouse experiment and measured methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) fluxes from soil cultivated with maize plants under factorial combinations of the inputs and a control treatment (F, I, S, FI, FS, IS, FIS, and control). Plant biomass was evaluated, and rhizosphere soil samples were collected at V5 and V15 stages and DNA was extracted. The abundance of functional genes (mcrA, pmoA, nifH, and nosZ) was determined by quantitative PCR (qPCR) and the structure of the microbial community was assessed through 16S rRNA amplicon sequencing. Our results corroborate with previous studies which used fewer input combinations and revealed different responses for the following three inputs: F increased N2O emissions around 1 week after application; I tended to reduce CH4 and CO2 emissions, acting as a plant growth stimulator through phytohormones; S showed an increment for CO2 emissions by increasing carbon-use efficiency. IS and FIS treatments presented significant gains in biomass that could be related to Actinobacteria (19.0%) and Bacilli (10.0%) in IS, and Bacilli (9.7%) in FIS, which are the microbial taxa commonly associated with lignocellulose degradation. Comparing all factors, the IS (inoculant + maize stover) treatment was considered the best option for plant biomass production and GHG mitigation since FIS provides small gains toward the management effort of F application.

Amazonian rainforest is undergoing increasing rates of deforestation, driven primarily by cattle pasture expansion. Forest-to-pasture conversion has been associated with increases in soil methane (CH4) emission. To better understand the drivers of this change, we measured soil CH4 flux, environmental conditions, and belowground microbial community structure across primary forests, cattle pastures, and secondary forests in two Amazonian regions. We show that pasture soils emit high levels of CH4 (mean: 3454.6 ± 9482.3 μg CH4 m-2 d-1), consistent with previous reports, while forest soils on average emit CH4 at modest rates (mean: 9.8 ± 120.5 μg CH4 m-2 d-1), but often act as CH4 sinks. We report that secondary forest soils tend to consume CH4 (mean: -10.2 ± 35.7 μg CH4 m-2 d-1), demonstrating that pasture CH4 emissions can be reversed. We apply a novel computational approach to identify microbial community attributes associated with flux independent of soil chemistry. While this revealed taxa known to produce or consume CH4 directly (i.e. methanogens and methanotrophs, respectively), the vast majority of identified taxa are not known to cycle CH4. Each land use type had a unique subset of taxa associated with CH4 flux, suggesting that land use change alters CH4 cycling through shifts in microbial community composition. Taken together, we show that microbial composition is crucial for understanding the observed CH4 dynamics and that microorganisms provide explanatory power that cannot be captured by environmental variables.

Forest-to-agriculture conversion has been identified as a major threat to soil biodiversity and soil processes resilience, although the consequences of long-term land use change to microbial community assembly and ecological processes have been often neglected. Here, we combined metagenomic approach with a large environmental dataset, to (i) identify the microbial assembly patterns and, (ii) to evaluate the ecological processes governing microbial assembly, in bulk soil and soybean rhizosphere, along a long-term forest-to-agriculture conversion chronosequence, in Eastern Amazon. We hypothesized that (i) microbial communities in bulk soil and rhizosphere have different assembly patterns and (ii) the weight of the four ecological processes governing assembly differs between bulk soil and rhizosphere and along the chronosequence in the same fraction. Community assembly in bulk soil fitted most the zero-sum multinomial (ZSM) neutral-based model, regardless of time. Low to intermediate dispersal was observed. Decreasing influence of abiotic factors was counterbalanced by increasing influence of biotic factors, as the chronosequence advanced. Undominated ecological processes of dispersal limitation and variable selection governing community assembly were observed in this soil fraction. For soybean rhizosphere, community assembly fitted most the lognormal niche-based model in all chronosequence areas. High dispersal and an increasing influence of abiotic factors coupled with a decreasing influence of biotic factors were found along the chronosequence. Thus, we found a dominant role of dispersal process governing microbial assembly with a secondary effect of homogeneous selection process, mainly driven by decreasing aluminum and increased cations saturation in soil solution, due to long-term no-till cropping. Together, our results indicate that long-term no-till lead community abundances in bulk soil to be in a transient and conditional state, while for soybean rhizosphere, community abundances reach a periodic and permanent distribution state. Dominant dispersal process in rhizosphere, coupled with homogeneous selection, brings evidences that soybean root system selects microbial taxa via trade-offs in order to keep functional resilience of soil processes.

We analyzed the nucleotide variability and the expression profile of DREB genes from common bean, a crop of high economic and nutritional value throughout the world but constantly affected by abiotic stresses in cultivation areas. As DREB genes have been constantly associated with abiotic stress tolerance, we systematically categorized 54 putative PvDREB genes distributed in the common bean genome. It involved from AP2 domain location and amino acid conservation analysis (valine at the 14th position) to the identification of conserved motifs within peptide sequences representing six subgroups (A-1 to A-6) of PvDREB proteins. Four genes (PvDREB1F, PvDREB2A, PvDREB5A, and PvDREB6B) were cloned and analyzed for their expression profiles under abiotic stresses and their nucleotide and amino acid diversity in genotypes of Andean and Mesoamerican origin, showing distinct patterns of expression and nucleotide variability. PvDREB1F and PvDREB5A showed high relative inducibilities when genotypes of common bean were submitted to stresses by drought, salt, cold, and ABA. PvDREB2A inducibility was predominantly localized to the stem under drought. PvDREB6B was previously described as an A-2 (DREB2) gene, but a detailed phylogenetic analysis and its expression profile clearly indicated it belongs to group A-6. PvDREB6B was found as a cold- and dehydration-responsive gene, mainly in leaves. Interestingly, PvDREB6B also showed a high nucleotide and amino acid diversity within its coding region, in comparison to the others, implicating in several nonsynonymous amino acid substitutions between Andean and Mesoamerican genotypes. The expression patterns and nucleotide diversity of each DREB found in this study revealed fundamental characteristics for further research aimed at understanding the molecular mechanisms associated with drought, salt, and cold tolerance in common bean, which could be performed based on association mapping and functional analyses.

The conversion of native forest to agriculture is the main cause of microbial biodiversity loss in Amazon soils. In order to better understand this effect, we used metagenomics to investigate microbial patterns and functions in bulk soil and rhizosphere of soybean, in a long-term forest-to-agriculture conversion. Long-term forest-to-agriculture led to microbial homogenization and loss of diversity in both bulk soil and rhizosphere, mainly driven by decreasing aluminum concentration and increased cations saturation in soil, due to liming and fertilization in long-term no-till cropping. Data revealed that long-term no-till cropping culminated in a decrease in Acidobacteria, Actinobacteria and Proteobacteria abundances. However, α- and β-Proteobacteria abundances were higher in the rhizosphere than in bulk soil, regardless of the time after forest-to-agriculture conversion. Changes in functional potential occurred predominantly in bulk soil, with decreases in functions related to potassium metabolism and virulence, disease and defense, while functions related to nucleic acids metabolism increased. Functions in the soybean rhizosphere remained stable, except for those related to potassium metabolism, which decreased after 20-year no-till cropping. Together, our results show that the soybean root system selects microbial taxa via trade-offs, to maintain functional resilience in the rhizosphere microbiome over time.

We evaluated the bacterial and archaeal community dynamics and assembly in soils under forest, grassland and no-till cropping, using a high-throughput shotgun metagenomics approach. No significant alterations in alpha diversity were observed among different land uses, but beta diversity in grassland was lower than that observed in forest and no-till soils. Grassland communities showed assembly that predominantly followed the neutral model, i.e. high homogenizing selection with moderate dispersion, leading to biotic homogenization. Both no-till and forest soil communities were found to have assembly that predominantly followed a niche model, i.e. low rates of dispersal and weak homogenizing selection, resulting in maintenance of higher beta diversity relative to grasslands, indicating niche specialization or variable selection. Taken together, our results indicate that the patterns of assembly and their governing processes are dependent on the land use employed after deforestation, with consequences for taxa turnover and microbial functional potential.

Abstract Transporter proteins play an essential role in the uptake, trafficking and storage of metals in plant tissues. The Natural Resistance-Associated Macrophage Protein (NRAMP) family plays an essential role in divalent metal transport. We conducted bioinformatics approaches to identify seven NRAMP genes in the Phaseolus vulgaris genome, investigated their phylogenetic relation, and performed transmembrane domain and gene/protein structure analyses. We found that the NRAMP gene family forms two distinct groups. One group included the PvNRAMP1, -6, and -7 genes that share a fragmented structure with a numerous exon/intron organization and encode proteins with mitochondrial or plastidial localization. The other group is characterized by few exons that encode cytoplasmic proteins. In addition, our data indicated that PvNRAMP6 and -7 may be involved in mineral uptake and mobilization in nodule tissues, while the genes PvNRAMP1, -2, -3, -4 and -5 are potentially recruited during plant development. This data provided a more comprehensive understanding of the role of NRAMP transporters in metal homeostasis in P. vulgaris.

BackgroundThe genus Colletotrichum is one of the most economically important plant pathogens, causing anthracnose on a wide range of crops including common beans (Phaseolus vulgaris L.). Crop yield can be dramatically decreased depending on the plant cultivar used and the environmental conditions. This study aimed to identify potential genetic components of the bean immune system to provide environmentally friendly control measures against this fungus.Methodology and principal findingsAs the common bean is not amenable to reverse genetics to explore functionality and its genome is not fully curated, we used putative Arabidopsis orthologs of bean expressed sequence tag (EST) to perform bioinformatic analysis and experimental validation of gene expression to identify common bean genes regulated during the incompatible interaction with C. lindemuthianum. Similar to model pathosystems, Gene Ontology (GO) analysis indicated that hormone biosynthesis and signaling in common beans seem to be modulated by fungus infection. For instance, cytokinin and ethylene responses were up-regulated and jasmonic acid, gibberellin, and abscisic acid responses were down-regulated, indicating that these hormones may play a central role in this pathosystem. Importantly, we have identified putative bean gene orthologs of Arabidopsis genes involved in the plant immune system. Based on experimental validation of gene expression, we propose that hypersensitive reaction as part of effector-triggered immunity may operate, at least in part, by down-regulating genes, such as FLS2-like and MKK5-like, putative orthologs of the Arabidopsis genes involved in pathogen perception and downstream signaling.Conclusions/significanceWe have identified specific bean genes and uncovered metabolic processes and pathways that may be involved in the immune response against pathogens. Our transcriptome database is a rich resource for mining novel defense-related genes, which enabled us to develop a model of the molecular components of the bean innate immune system regulated upon pathogen attack.

Microsatellites and gene-derived markers are still underrepresented in the core molecular linkage map of common bean compared to other types of markers. In order to increase the density of the core map, a set of new markers were developed and mapped onto the RIL population derived from the ‘BAT93’ × ‘Jalo EEP558’ cross. The EST-SSR markers were first characterized using a set of 24 bean inbred lines. On average, the polymorphism information content was 0.40 and the mean number of alleles per locus was 2.7. In addition, AFLP and RGA markers based on the NBS-profiling method were developed and a subset of the mapped RGA was sequenced. With the integration of 282 new markers into the common bean core map, we were able to place markers with putative known function in some existing gaps including regions with QTL for resistance to anthracnose and rust. The distribution of the markers over 11 linkage groups is discussed and a newer version of the common bean core linkage map is proposed.