2 research outputs found
Functional Insights of Salinity Stress-Related Pathways in Metagenome-Resolved Methanothrix Genomes
Recently, methanogenic archaea belonging to the genus Methanothrix were reported to have a fundamental role in maintaining stable ecosystem functioning in anaerobic bioreactors under different configurations/conditions. In this study, we reconstructed three Methanothrix metagenome-assembled genomes (MAGs) from granular sludge collected from saline upflow anaerobic sludge blanket (UASB) reactors, where Methanothrix harundinacea was previously implicated with the formation of compact and stable granules under elevated salinity levels (up to 20 g/L Na+). Genome annotation and pathway analysis of the Methanothrix MAGs revealed a genetic repertoire supporting their growth under high salinity. Specifically, the most dominant Methanothrix (MAG_279), classified as a subspecies of Methanothrix_A harundinacea_D, had the potential to augment its salinity resistance through the production of different glycoconjugates via the N-glycosylation process, and via the production of compatible solutes as Nε-acetyl-β-lysine and ectoine. The stabilization and reinforcement of the cell membrane via the production of isoprenoids was identified as an additional stress-related pathway in this microorganism. The improved understanding of the salinity stress-related mechanisms of M. harundinacea highlights its ecological niche in extreme conditions, opening new perspectives for high-efficiency methanisation of organic waste at high salinities, as well as the possible persistence of this methanogen in highly-saline natural anaerobic environments
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A standardized quantitative analysis strategy for stable isotope probing metagenomics
Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes