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Metagenome assembled genomes from mouse gut microbiota

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Mar 25, 2025 version files 5.74 GB

Abstract

The source of protein in a person's diet affects their total life expectancy. However, the mechanisms by which dietary protein sources differentially impact human health and life expectancy are poorly understood. Dietary choices impact the composition and function of the intestinal microbiota that ultimately modulate host health. This raises the possibility that health outcomes based on dietary protein sources might be driven by interactions between dietary protein and the gut microbiota. In this study, we determined the effects of seven different sources of dietary protein on the gut microbiota of male and female mice (C57BL/6J) using an integrated metagenomics-metaproteomics approach. In order of feeding, the diets were 20% soy protein, 20% casein protein, 20% brown rice protein, 40% soy protein, 20% yeast protein, 40% casein protein, 20% pea protein, 20% egg white protein, and 20% chicken bone protein. We fed a total of 10-12 mice each diet for one week and then collected a fecal sample at the end of the week before proceeding to the next diet. We then analyzed the fecal samples using an integrated metagenomics-metaproteomics approach that included generating a genome-resolved metagenome with metagenome assembled genomes (MAGs). This data set represents all the MAGs generated in this study. To generate the MAGs, we pooled DNA extracted from feces taken from each mouse cage (four cages in total) across four different diets (20% rice, 40% soy, 20% yeast, 40% casein). We sent the DNA to be sequenced at the NCSU GSL and generated between 51,152,549 and 74,618,259 paired-end reads (150bp x 2) per sample using a NovaSeq 6000 Sequencing System, Illumina. We analyzed these reads using a genome-resolved metagenomic pipeline, which included read QC, assembly using metaSPAdes and MEGAHIT, binning using MetaBAT 2, and bin quality checking using CheckM. This data set includes the metagenomic assemblies for each cage, a co-assembly, and 454 MAGs with a completion score of >30% and a contamination scores of <10% if the completion score was 50% and <5% if the completion score was between 30-50%. We also include a re-assembled Bacteroides thetaiotaomicron genome along with its associated reads and checkM scores and a BinGroupingTableWithGTDB.txt file that includes the bin identifiers, the species cluster group at 95% ANI, CheckM scores, and GTDB taxonomy information. This data set represents a group of MAGs that could be used along with other metagenomic measurements as part of a catalog of the C57BL/6J mouse microbiota.