Cargando…
Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome
Murine models are widely used to explore host-microbe interactions because of the challenges and limitations inherent to human studies. However, microbiome studies in murine models are not without their nuances. Inter-individual variations in gut microbiota are frequent even in animals housed within...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6046200/ https://www.ncbi.nlm.nih.gov/pubmed/30013837 http://dx.doi.org/10.7717/peerj.5166 |
_version_ | 1783339787652956160 |
---|---|
author | Miyoshi, Jun Leone, Vanessa Nobutani, Kentaro Musch, Mark W. Martinez-Guryn, Kristina Wang, Yunwei Miyoshi, Sawako Bobe, Alexandria M. Eren, A. Murat Chang, Eugene B. |
author_facet | Miyoshi, Jun Leone, Vanessa Nobutani, Kentaro Musch, Mark W. Martinez-Guryn, Kristina Wang, Yunwei Miyoshi, Sawako Bobe, Alexandria M. Eren, A. Murat Chang, Eugene B. |
author_sort | Miyoshi, Jun |
collection | PubMed |
description | Murine models are widely used to explore host-microbe interactions because of the challenges and limitations inherent to human studies. However, microbiome studies in murine models are not without their nuances. Inter-individual variations in gut microbiota are frequent even in animals housed within the same room. We therefore sought to find an efficient and effective standard operating procedure (SOP) to minimize these effects to improve consistency and reproducibility in murine microbiota studies. Mice were housed in a single room under specific-pathogen free conditions. Soiled cage bedding was routinely mixed weekly and distributed among all cages from weaning (three weeks old) until the onset of the study. Females and males were separated by sex and group-housed (up to five mice/cage) at weaning. 16S rRNA gene analyses of fecal samples showed that this protocol significantly reduced pre-study variability of gut microbiota amongst animals compared to other conventional measures used to normalize microbiota when large experimental cohorts have been required. A significant and consistent effect size was observed in gut microbiota when mice were switched from regular chow to purified diet in both sexes. However, sex and aging appeared to be independent drivers of gut microbial assemblage and should be taken into account in studies of this nature. In summary, we report a practical and effective pre-study SOP for normalizing the gut microbiome of murine cohorts that minimizes inter-individual variability and resolves co-housing problems inherent to male mice. This SOP may increase quality, rigor, and reproducibility of data acquisition and analysis. |
format | Online Article Text |
id | pubmed-6046200 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60462002018-07-16 Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome Miyoshi, Jun Leone, Vanessa Nobutani, Kentaro Musch, Mark W. Martinez-Guryn, Kristina Wang, Yunwei Miyoshi, Sawako Bobe, Alexandria M. Eren, A. Murat Chang, Eugene B. PeerJ Bioinformatics Murine models are widely used to explore host-microbe interactions because of the challenges and limitations inherent to human studies. However, microbiome studies in murine models are not without their nuances. Inter-individual variations in gut microbiota are frequent even in animals housed within the same room. We therefore sought to find an efficient and effective standard operating procedure (SOP) to minimize these effects to improve consistency and reproducibility in murine microbiota studies. Mice were housed in a single room under specific-pathogen free conditions. Soiled cage bedding was routinely mixed weekly and distributed among all cages from weaning (three weeks old) until the onset of the study. Females and males were separated by sex and group-housed (up to five mice/cage) at weaning. 16S rRNA gene analyses of fecal samples showed that this protocol significantly reduced pre-study variability of gut microbiota amongst animals compared to other conventional measures used to normalize microbiota when large experimental cohorts have been required. A significant and consistent effect size was observed in gut microbiota when mice were switched from regular chow to purified diet in both sexes. However, sex and aging appeared to be independent drivers of gut microbial assemblage and should be taken into account in studies of this nature. In summary, we report a practical and effective pre-study SOP for normalizing the gut microbiome of murine cohorts that minimizes inter-individual variability and resolves co-housing problems inherent to male mice. This SOP may increase quality, rigor, and reproducibility of data acquisition and analysis. PeerJ Inc. 2018-07-12 /pmc/articles/PMC6046200/ /pubmed/30013837 http://dx.doi.org/10.7717/peerj.5166 Text en ©2018 Miyoshi et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Miyoshi, Jun Leone, Vanessa Nobutani, Kentaro Musch, Mark W. Martinez-Guryn, Kristina Wang, Yunwei Miyoshi, Sawako Bobe, Alexandria M. Eren, A. Murat Chang, Eugene B. Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
title | Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
title_full | Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
title_fullStr | Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
title_full_unstemmed | Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
title_short | Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
title_sort | minimizing confounders and increasing data quality in murine models for studies of the gut microbiome |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6046200/ https://www.ncbi.nlm.nih.gov/pubmed/30013837 http://dx.doi.org/10.7717/peerj.5166 |
work_keys_str_mv | AT miyoshijun minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT leonevanessa minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT nobutanikentaro minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT muschmarkw minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT martinezgurynkristina minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT wangyunwei minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT miyoshisawako minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT bobealexandriam minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT erenamurat minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome AT changeugeneb minimizingconfoundersandincreasingdataqualityinmurinemodelsforstudiesofthegutmicrobiome |