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Pavia, M. J.

Publications and source records attributed to Pavia, M. J..

2 recordsLinked to original sources

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

The Pastaza-Maranon 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 oxic/anoxic 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 shows significant differences in C, N, P, and S acquisition genes. Further, 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. Similarly, we reconstructed 519 metagenome-assembled genomes spanning 28 phyla. Our analyses detail key differences across the nutrient 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 nitrogen oxide (NO) reduction strategies between sites with high and low N2O 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.

microbiology↗

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

Exploring metagenomic contigs and "binning" them are essential for delineating functional and evolutionary guilds within microbial communities. Despite available automated binners, researchers often find human involvement necessary to achieve representative results. We present BinaRena, an interactive graphic interface dedicated to aiding human operators to explore contigs via customizable visualization and to associate them with bins based on various data types, including sequence metrics, coverage profiles, taxonomic assignments and functional annotations. Binning plans can be edited, inspected and compared visually or using algorithms. Completeness and redundancy of user-selected contigs can be calculated real-time. We show that BinaRena facilitated biological pattern discovery, hypothesis generation and bin refinement in a tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely-related populations from human gut samples. It significantly improved overall binning quality after curation using a simulated marine dataset. BinaRena is an installation-free, client-end web application for researchers of all levels.

bioinformatics↗