Animals host complex bacterial communities in their gastrointestinal tracts, with which they share a mutualistic interaction. The numerous effects these interactions grant to the host include regulation of the immune system, defense against pathogen invasion, aid in digestion of otherwise indigestible foodstuffs and even changing host behaviour. Stress, such as environmental pollution, parasites, predators and intraspecies competition, can alter the composition of the gut microbiome, which in turn can change host-microbiome interactions in ways that are detrimental to the host such as causing metabolic dysfunction and inflammation. While host-microbiome interactions have been extensively studied in humans and captive animals, studies into wild animal microbiomes have been scarce. We assessed effects of disturbed environment on gut health of bank voles exposed to radionuclides in natural habitat using a combined approach of transcriptomics, microbial community analysis by 16S amplicon sequencing, histological staining analyses of colon tissue and quantification of gut microbiota -produced short-chain fatty acids in faecal matter and blood that act as mediators of host-microbiome interactions. We found signs of weakened mucus layer and related changes in Clca1 and Agr2 gene expression and microbiome composition in animals exposed to radionuclides. These results imply that disturbed environment can have widely reaching effects through gut health.

Description of the data and file structure

This DRYAD repository contains large transcriptomic and metataxonomic datafiles for Association between gut health and gut microbiota in a polluted environment. QIIME2 artifact files (.qza) are a zip-compressed data form standard for use in the QIIME2 analysis framework to improve reproducibility. QIIME2 artifacts can be inspected by using qiime tools export within QIIME2, or by extracting the .biom files from within using any file compression software. For more information, please see https://docs.qiime2.org/2024.2/concepts/#data-files-qiime-2-artifacts and https://biom-format.org/documentation/biom_conversion.html.

• Metadata.xlsx - Sample metadata and relative abundances of 16S data.
• RSEM.gene.counts.annot.matrix - Non-normalized transcript count table. Recommended to use Bioconductor tools for downstream RNAseq analyses.
• rarefied_tabletrans_microbe_dada2.qza - Rarefied ASV count table of 16S sequencing data for use in QIIME2 applications. Provenance previewable using QIIME2view https://view.qiime2.org/
• rooted-tree-dada2-trans-microbe.qza - Rooted tree generated from ASV sequence diversity for use in QIIME2 applications. Provenance previewable using QIIME2view https://view.qiime2.org/
• dada2-trans-microbe-taxonomy.qza - ASV taxonomic classifications for use in QIIME2 applications. Provenance previewable using QIIME2view https://view.qiime2.org/