Studies in the Amazon are being intensified to evaluate the alterations in the microbial communities of soils and sediments in the face of increasing deforestation and land-use changes in the region. However, since these environments present highly heterogeneous physicochemical properties, including contaminants that hinder nucleic acids isolation and downstream techniques, the development of best molecular practices is crucial. This work aimed to optimize standard protocols for DNA extraction and gene quantification by quantitative real-time PCR (qPCR) based on natural and anthropogenic soils and sediments (primary forest, pasture, Amazonian Dark Earth, and várzea, a seasonally flooded area) of the Eastern Amazon. Our modified extraction protocol increased the fluorometric DNA concentration by 48%, reaching twice the original amount for most of the pasture and várzea samples, and the 260/280 purity ratio by 15% to values between 1.8 to 2.0, considered ideal for DNA. The addition of bovine serum albumin in the qPCR reaction improved the quantification of the 16S rRNA genes of Archaea and Bacteria and its precision among technical replicates, as well as allowed their detection in previously non-amplifiable samples. It is concluded that the changes made in the protocols improved the parameters of the DNA samples and their amplification, thus increasing the reliability of microbial communities' analysis and its ecological interpretations.

Seasonal floodplains in the Amazon basin are important sources of methane (CH₄), while upland forests are known for their sink capacity. Climate change effects, including shifts in rainfall patterns and rising temperatures, may alter the functionality of soil microbial communities, leading to uncertain changes in CH₄ cycling dynamics. To investigate the microbial feedback under climate change scenarios, we performed a microcosm experiment using soils from two floodplains (i.e., Amazonas and Tapajós rivers) and one upland forest. We employed a two-factorial experimental design comprising flooding (with non-flooded control) and temperature (at 27 °C and 30 °C, representing a 3 °C increase) as variables. We assessed prokaryotic community dynamics over 30 days using 16S rRNA gene sequencing and qPCR. These data were integrated with chemical properties, CH₄ fluxes, and isotopic values and signatures. In the floodplains, temperature changes did not significantly affect the overall microbial composition and CH₄ fluxes. CH₄ emissions and uptake in response to flooding and non-flooding conditions, respectively, were observed in the floodplain soils. By contrast, in the upland forest, the higher temperature caused a sink-to-source shift under flooding conditions and reduced CH₄ sink capability under dry conditions. The upland soil microbial communities also changed in response to increased temperature, with a higher percentage of specialist microbes observed. Floodplains showed higher total and relative abundances of methanogenic and methanotrophic microbes compared to forest soils. Isotopic data from some flooded samples from the Amazonas river floodplain indicated CH₄ oxidation metabolism. This floodplain also showed a high relative abundance of aerobic and anaerobic CH₄ oxidizing Bacteria and Archaea. Taken together, our data indicate that CH₄ cycle dynamics and microbial communities in Amazonian floodplain and upland forest soils may respond differently to climate change effects. We also highlight the potential role of CH₄ oxidation pathways in mitigating CH₄ emissions in Amazonian floodplains.

Although floodplains are recognized as important sources of methane (CH₄) in the Amazon basin, little is known about the role of methanotrophs in mitigating CH₄ emissions in these ecosystems. Our previous data reported the genus Methylocystis as one of the most abundant methanotrophs in these floodplain sediments. However, information on the functional potential and life strategies of these organisms living under seasonal flooding is still missing. Here, we described the first metagenome-assembled genome (MAG) of a Methylocystis sp. recovered from Amazonian floodplains sediments, and we explored its functional potential and ecological traits through phylogenomic, functional annotation, and pan-genomic approaches. Both phylogenomics and pan-genomics identified the closest placement of the bin.170_fp as Methylocystis parvus. As expected for Type II methanotrophs, the Core cluster from the pan-genome comprised genes for CH₄ oxidation and formaldehyde assimilation through the serine pathway. Furthermore, the complete set of genes related to nitrogen fixation is also present in the Core. Interestingly, the MAG singleton cluster revealed the presence of unique genes related to nitrogen metabolism and cell motility. The study sheds light on the genomic characteristics of a dominant, but as yet unexplored methanotroph from the Amazonian floodplains. By exploring the genomic potential related to resource utilization and motility capability, we expanded our knowledge on the niche breadth of these dominant methanotrophs in the Amazonian floodplains.

Here, we report 17 metagenome-assembled genomes (MAGs) recovered from microbial consortia of forest and pasture soils in the Brazilian Eastern Amazon. The bacterial MAGs have the potential to act in important ecological processes, including carbohydrate degradation and sulfur and nitrogen cycling.

Peatlands are waterlogged ecosystems that store large amounts of carbon, harbor highly specialized endemic biodiversity, and play a crucial role in climate regulation. However, the microbial communities of tropical peatlands, particularly in the Atlantic Forest, remain largely unexplored. Molecular tools are essential for characterizing these communities, yet conventional DNA extraction kits are often ineffective for peat soils, likely due to their high organic matter content, low pH, and the presence of PCR inhibitors. This study aimed to optimize a conventional soil DNA extraction protocol to enhance DNA yield and purity from tropical peat soils, ensuring more reliable molecular analyses. The optimized protocol resulted in a four-times increase in DNA concentration compared to the conventional protocol and improved DNA purity. Agarose gel electrophoresis confirmed higher DNA integrity and also revealed the presence of RNA in samples subjected to the optimized protocol, indicating its potential for co-extraction of DNA and RNA. Quantitative PCR (qPCR) analysis showed significantly higher abundances of bacterial and archaeal 16S rRNA genes, as well as the mcr A gene, in optimized compared to conventional protocol, with statistically significant differences across soil profiles and depths. Furthermore, the optimized protocol yielded a lower coefficient of variation among replicates, enhancing reproducibility and consistency in microbial quantification. These findings demonstrate that the optimized protocol effectively extracts high-quality DNA from tropical peat soils, addressing common challenges associated with commercial kits. Its implementation can support improved future research on microbial-driven biogeochemical processes in tropical peatlands, particularly in the context of greenhouse gas emissions and climate change. IMPORTANCE: Tropical peatlands play a central role in carbon storage and greenhouse gas dynamics, yet their microbial communities remain largely unexplored due to analytical challenges. High organic matter content, low pH, and PCR inhibitors commonly limit the efficiency of molecular tools in these environments. This study presents an optimized DNA extraction protocol that improves yield, purity, and reproducibility across peat profiles. The protocol enhanced the detection of microbial marker genes, such as bacterial and archaeal 16S rRNA and mcrA , and showed potential for co-extraction of RNA, expanding possibilities for future multi-omic approaches. This methodological advance enables more accurate and consistent microbial analyses in tropical peat soils, contributing to a better understanding of microbial roles in biogeochemical cycles and climate-related processes.