Experimental validation of small mammal gut microbiota sampling from faeces and from the caecum after death
Language English Country Great Britain, England Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
34045683
PubMed Central
PMC8322053
DOI
10.1038/s41437-021-00445-6
PII: 10.1038/s41437-021-00445-6
Knihovny.cz E-resources
- MeSH
- Cecum MeSH
- Feces MeSH
- Mice MeSH
- RNA, Ribosomal, 16S genetics MeSH
- Mammals MeSH
- Gastrointestinal Microbiome * MeSH
- Animals MeSH
- Check Tag
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- RNA, Ribosomal, 16S MeSH
Data on the gut microbiota (GM) of wild animals are key to studies on evolutionary biology (host-GM interactions under natural selection), ecology and conservation biology (GM as a fitness component closely connected to the environment). Wildlife GM sampling often requires non-invasive techniques or sampling from dead animals. In a controlled experiment profiling microbial 16S rRNA in 52 house mice (Mus musculus) from eight families and four genetic backgrounds, we studied the effects of live- and snap-trapping on small mammal GM and evaluated the suitability of microbiota from non-fresh faeces as a proxy for caecal GM. We compared CM from individuals sampled 16-18 h after death with those in live traps and caged controls, and caecal and faecal GM collected from mice in live-traps. Sampling delay did not affect GM composition, validating data from fresh cadavers or snap-trapped animals. Animals trapped overnight displayed a slight but significant difference in GM composition to the caged controls, though the change only had negligible effect on GM diversity, composition and inter-individual divergence. Hence, the trapping process appears not to bias GM profiling. Despite their significant difference, caecal and faecal microbiota were correlated in composition and, to a lesser extent, diversity. Both showed congruent patterns of inter-individual divergence following the natural structure of the dataset. Thus, the faecal microbiome represents a good non-invasive proxy of the caecal microbiome, making it suitable for detecting biologically relevant patterns. However, care should be taken when analysing mixed datasets containing both faecal and caecal samples.
Faculty of Science Department of Zoology Charles University Prague Czech Republic
Institute of Vertebrate Biology Czech Academy of Sciences Brno Czech Republic
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