DOI: 10.5061/dryad.stqjq2c79
title: Data from: Association between gut health and gut microbiota in a polluted environment

description: 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 the 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: Table files can be opened using any tabular data
 processor. .qza files can be opened and manipulated
 using QIIME 2 bioinformatic tools (https://qiime2.org/).
description: # Supporting dataset for "Association between gut health and gut
 microbiota in a polluted environment" --- 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](https://docs.qiime2.org/2024.2/concepts/#data-files-qiime-2-artifacts) and [https://biom-format.org/documentation/biom_conversion.html](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/](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/](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/](https://view.qiime2.org/)