Microbial Communities and Interactions of Nitrogen Oxides With Methanogenesis in Diverse Peatlands of the Amazon Basin

Nitrous oxide inhibition of methanogenesis represents an underappreciated greenhouse gas emission feedback

Methane (CH4) and nitrous oxide (N2O) are major greenhouse gases that are predominantly generated by microbial activities in anoxic environments. N2O inhibition of methanogenesis has been reported, but comprehensive efforts to obtain kinetic information are lacking. Using the model methanogen Methanosarcina barkeri strain Fusaro and digester sludge-derived methanogenic enrichment cultures, we conducted growth yield and kinetic measurements and showed that micromolar concentrations of N2O suppress the growth of methanogens and CH4 production from major methanogenic substrate classes. Acetoclastic methanogenesis, estimated to account for two-thirds of the annual 1 billion metric tons of biogenic CH4, was most sensitive to N2O, with inhibitory constants (KI) in the range of 18-25 μM, followed by hydrogenotrophic (KI, 60-90 μM) and methylotrophic (KI, 110-130 μM) methanogenesis. Dissolved N2O concentrations exceeding these KI values are not uncommon in managed (i.e. fertilized soils and wastewater treatment plants) and unmanaged ecosystems. Future greenhouse gas emissions remain uncertain, particularly from critical zone environments (e.g. thawing permafrost) with large amounts of stored nitrogenous and carbonaceous materials that are experiencing unprecedented warming. Incorporating relevant feedback effects, such as the significant N2O inhibition on methanogenesis, can refine climate models and improve predictive capabilities.

Genes and genome-resolved metagenomics reveal the microbial functional make up of Amazon peatlands under geochemical gradients

The Pastaza-Marañón Foreland Basin (PMFB) holds the most extensive tropical peatland area in South America. PMFB peatlands store ~7.07 Gt of organic carbon interacting with multiple microbial heterotrophic, methanogenic, and other aerobic/anaerobic respirations. Little is understood about the contribution of distinct microbial community members inhabiting tropical peatlands. Here, we studied the metagenomes of three geochemically distinct peatlands spanning minerotrophic, mixed, and ombrotrophic conditions. Using gene- and genome-centric approaches, we evaluate the functional potential of the underlying microbial communities. Abundance analyses show significant differences in C, N, P, and S acquisition genes. Furthermore, community interactions mediated by toxin-antitoxin and CRISPR-Cas systems were enriched in oligotrophic soils, suggesting that non-metabolic interactions may exert additional controls in low-nutrient environments. Additionally, we reconstructed 519 metagenome-assembled genomes spanning 28 phyla. Our analyses detail key differences across the geochemical gradient in the predicted microbial populations involved in degradation of organic matter, and the cycling of N and S. Notably, we observed differences in the nitric oxide (NO) reduction strategies between sites with high and low N2 O fluxes and found phyla putatively capable of both NO and sulfate reduction. Our findings detail how gene abundances and microbial populations are influenced by geochemical differences in tropical peatlands.

Diversity of Microbiomes Across a 13,000-Year-Old Amazon Sediment

The microbiome is fundamental for understanding bacterial activities in sediments. However, only a limited number of studies have addressed the microbial diversity of Amazonian sediments. Here, we studied the microbiome of sediments from a 13,000-year BP core retrieved in a floodplain lake in Amazonia using metagenomics and biogeochemistry. Our aim was to evaluate the possible environmental influence over a river to a lake transition using a core sample. To this end, we sampled a core in the Airo Lake, a floodplain lake in the Negro River basin. The Negro River is the largest tributary of the Amazon River. The obtained core was divided into three strata: (i) surface, almost complete separation of the Airo Lake from the Negro River when the environment becomes more lentic with greater deposition of organic matter (black-colored sediment); (ii) transitional environment (reddish brown); and (iii) deep, environment with a tendency for greater past influence of the Negro River (brown color). The deepest sample possibly had the greatest influence of the Negro River as it represented the bottom of this river in the past, while the surface sample is the current Airo Lake bottom. In total, six metagenomes were obtained from the three different depth strata (total number of reads: 10.560.701; sequence length: 538 ± 24, mean ± standard deviation). The older (deeper) sediment strata contained a higher abundance of Burkholderia, Chitinophaga, Mucilaginibacter, and Geobacter, which represented ~ 25% of the metagenomic sequences. On the other hand, the more recent sediment strata had mainly Thermococcus, Termophilum, Sulfolobus, Archaeoglobus, and Methanosarcina (in total 11% of the metagenomic sequences). The sequence data were binned into metagenome-assembled genomes (MAGs). The majority of the obtained MAGs (n = 16) corresponded to unknown taxa, suggesting they may belong to new species. The older strata sediment microbiome was enriched with sulfur cycle genes, TCA cycle, YgfZ, and ATP-dependent proteolysis in bacteria. Meanwhile, serine-glyoxylate cycle, stress response genes, bacterial cell division, cell division-ribosomal stress protein cluster, and oxidative stress increased in the younger strata. Metal resistance and antimicrobial resistance genes were found across the entire core, including genes coding for fluoroquinolones, polymyxin, vancomycin, and multidrug resistance transporters. These findings depict the possible microbial diversity during the depositional past events and provided clues of the past microbial metabolism throughout time.

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

BACKGROUND

Exploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

RESULTS

We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

CONCLUSIONS

BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.

Inhibition of Methylmercury and Methane Formation by Nitrous Oxide in Arctic Tundra Soil Microcosms

Climate warming causes permafrost thaw predicted to increase toxic methylmercury (MeHg) and greenhouse gas [i.e., methane (CH₄), carbon dioxide (CO₂), and nitrous oxide (N₂O)] formation. A microcosm incubation study with Arctic tundra soil over 145 days demonstrates that N₂O at 0.1 and 1 mM markedly inhibited microbial MeHg formation, methanogenesis, and sulfate reduction, while it slightly promoted CO₂ production. Microbial community analyses indicate that N₂O decreased the relative abundances of methanogenic archaea and microbial clades implicated in sulfate reduction and MeHg formation. Following depletion of N₂O, both MeHg formation and sulfate reduction rapidly resumed, whereas CH₄ production remained low, suggesting that N₂O affected susceptible microbial guilds differently. MeHg formation strongly coincided with sulfate reduction, supporting prior reports linking sulfate-reducing bacteria to MeHg formation in the Arctic soil. This research highlights complex biogeochemical interactions in governing MeHg and CH₄ formation and lays the foundation for future mechanistic studies for improved predictive understanding of MeHg and greenhouse gas fluxes from thawing permafrost ecosystems.

Improved Quantitative Real-Time PCR Protocol for Detection and Quantification of Methanogenic Archaea in Stool Samples

Methanogenic archaea are an important component of the human and animal intestinal microbiota, and yet their presence is rarely reported in publications describing the subject. One of the methods of quantifying the prevalence of methanogens is quantitative real-time PCR (qPCR) of the methanogen-specific mcrA gene, and one of the possible reasons for detection failure is usually a methodology bias. Here, we refined the existing protocol by changing one of the primers and improving the conditions of the qPCR reaction. As a result, at the expense of a slightly lower yet acceptable PCR efficiency, the new assay was characterized by increased specificity and sensitivity and a wider linear detection range of 7 orders of magnitude. The lowest copy number of mcrA quantified at a frequency of 100% was 21 copies per reaction. The other validation parameters tested, such as reproducibility and linearity, also gave satisfactory results. Overall, we were able to minimize the negative impacts of primer dimerization and other cross-reactions on qPCR and increase the number of not only detectable but also quantifiable stool samples—or in this case, chicken droppings.

Analysis of the Bacterial Biocenosis of Activated Sludge Treated with Leachate from Municipal Landfills

The influx of toxic pollutants into wastewater treatment plants can negatively affect the quality of the activated sludge (AS). One source is landfill leachate. The identification of microorganisms present in AS is very important, e.g., while improving wastewater treatment technology. Therefore, the aim of the study was to investigate the effect of raw leachate and after purification of Phragmites australis and Ceratophyllum demersum on the composition of the AS bacterial biocenosis. In addition, AS status was assessed by LIVE/DEAD BacLight ™ fluorescent staining. The obtained results showed that the leachate did not significantly affect the cell membranes of AS bacteria, and even a slight improvement was noted. The research carried out using the next-generation sequencing method shows that the origin of the samples (active and closed storage) and the method of processing do not significantly affect the composition of the AS bacterial biocenosis at higher taxonomic levels. However, at the species level, the appearance of bacteria not previously present in AS was observed, namely: Flavobacterium luticocti, Candidimonas nitroreducens and Nitrobacter hamburgensis. The obtained results suggest that the leachate may be a source of microorganisms positively influencing the condition of AS bacteria.