An integrated systems biology approach reveals differences in formate metabolism in the genus Methanothermobacter.

Methanogenesis allows methanogenic archaea to generate cellular energy for their growth while producing methane. Thermophilic hydrogenotrophic species of the genus Methanothermobacter have been recognized as robust biocatalysts for a circular carbon economy and are already applied in power-to-gas technology with biomethanation, which is a platform to store renewable energy and utilize captured carbon dioxide. Here, we generated curated genome-scale metabolic reconstructions for three Methanothermobacter strains and investigated differences in the growth performance of these same strains in chemostat bioreactor experiments with hydrogen and carbon dioxide or formate as substrates. Using an integrated systems biology approach, we identified differences in formate anabolism between the strains and revealed that formate anabolism influences the diversion of carbon between biomass and methane. This finding, together with the omics datasets and the metabolic models we generated, can be implemented for biotechnological applications of Methanothermobacter in power-to-gas technology, and as a perspective, for value-added chemical production.

A critical assessment of gene catalogs for metagenomic analysis.

MOTIVATION: Microbial gene catalogs are data structures that organize genes found in microbial communities, providing a reference for standardized analysis of the microbes across samples and studies. Although gene catalogs are commonly used, they have not been critically evaluated for their effectiveness as a basis for metagenomic analyses. RESULTS: As a case study, we investigate one such catalog, the Integrated Gene Catalog (IGC), however, our observations apply broadly to most gene catalogs constructed to date. We focus on both the approach used to construct this catalog and on its effectiveness when used as a reference for microbiome studies. Our results highlight important limitations of the approach used to construct the IGC and call into question the broad usefulness of gene catalogs more generally. We also recommend best practices for the construction and use of gene catalogs in microbiome studies and highlight opportunities for future research. AVAILABILITY AND IMPLEMENTATION: All supporting scripts for our analyses can be found on GitHub: https://github.com/SethCommichaux/IGC.git. The supporting data can be downloaded from: https://obj.umiacs.umd.edu/igc-analysis/IGC_analysis_data.tar.gz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Human Salivary Amylase Gene Copy Number Impacts Oral and Gut Microbiomes.

Host genetic variation influences microbiome composition. While studies have focused on associations between the gut microbiome and specific alleles, gene copy number (CN) also varies. We relate microbiome diversity to CN variation of the AMY1 locus, which encodes salivary amylase, facilitating starch digestion. After imputing AMY1-CN for ∼1,000 subjects, we identified taxa differentiating fecal microbiomes of high and low AMY1-CN hosts. In a month-long diet intervention study, we show that diet standardization drove gut microbiome convergence, and AMY1-CN correlated with oral and gut microbiome composition and function. The microbiomes of low-AMY1-CN subjects had enhanced capacity to break down complex carbohydrates. High-AMY1-CN subjects had higher levels of salivary Porphyromonas; their gut microbiota had increased abundance of resistant starch-degrading microbes, produced higher levels of short-chain fatty acids, and drove higher adiposity when transferred to germ-free mice. This study establishes AMY1-CN as a genetic factor associated with microbiome composition and function.