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Self-reinoculation with fecal flora changes microbiota density and composition leading to an altered bile-acid profile in the mouse small intestine

Bogatyrev, Said R. and Rolando, Justin C. and Ismagilov, Rustem F. (2020) Self-reinoculation with fecal flora changes microbiota density and composition leading to an altered bile-acid profile in the mouse small intestine. Microbiome, 8 . Art. No. 19. ISSN 2049-2618. PMCID PMC7017497.

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Background: The upper gastrointestinal tract plays a prominent role in human physiology as the primary site for enzymatic digestion and nutrient absorption, immune sampling, and drug uptake. Alterations to the small intestine microbiome have been implicated in various human diseases, such as non-alcoholic steatohepatitis and inflammatory bowel conditions. Yet, the physiological and functional roles of the small intestine microbiota in humans remain poorly characterized because of the complexities associated with its sampling. Rodent models are used extensively in microbiome research and enable the spatial, temporal, compositional, and functional interrogation of the gastrointestinal microbiota and its effects on the host physiology and disease phenotype. Classical, culture-based studies have documented that fecal microbial self-reinoculation (via coprophagy) affects the composition and abundance of microbes in the murine proximal gastrointestinal tract. This pervasive self-reinoculation behavior could be a particularly relevant study factor when investigating small intestine microbiota. Modern microbiome studies either do not take self-reinoculation into account, or assume that approaches such as single housing mice or housing on wire mesh floors eliminate it. These assumptions have not been rigorously tested with modern tools. Here, we used quantitative 16S rRNA gene amplicon sequencing, quantitative microbial functional gene content inference, and metabolomic analyses of bile acids to evaluate the effects of self-reinoculation on microbial loads, composition, and function in the murine upper gastrointestinal tract. Results: In coprophagic mice, continuous self-exposure to the fecal flora had substantial quantitative and qualitative effects on the upper gastrointestinal microbiome. These differences in microbial abundance and community composition were associated with an altered profile of the small intestine bile acid pool, and, importantly, could not be inferred from analyzing large intestine or stool samples. Overall, the patterns observed in the small intestine of non-coprophagic mice (reduced total microbial load, low abundance of anaerobic microbiota, and bile acids predominantly in the conjugated form) resemble those typically seen in the human small intestine. Conclusions: Future studies need to take self-reinoculation into account when using mouse models to evaluate gastrointestinal microbial colonization and function in relation to xenobiotic transformation and pharmacokinetics or in the context of physiological states and diseases linked to small intestine microbiome and to small intestine dysbiosis.

Item Type:Article
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URLURL TypeDescription CentralArticle
Bogatyrev, Said R.0000-0003-0486-9451
Rolando, Justin C.0000-0001-8948-319X
Ismagilov, Rustem F.0000-0002-3680-4399
Additional Information:© 2020 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated. Received: 26 September 2019; Accepted: 5 January 2020; Published online: 12 February 2020. We thank Karen Lencioni, Janet Baer, the Caltech Office of Laboratory Animal Resources, veterinary technicians at the Church Animal Facility for experimental resources. We thank Liang Ma for the introduction to 16S rRNA gene amplicon sequencing, Heidi Klumpe for her assistance with the preliminary MPN experiments, and Justin Bois for the introduction to data analysis in Python. S.R.B. would like to thank Kimberly Zhou for the personal feedback on the project and inspiration. This project benefited from the use of instrumentation made available by the Caltech Environmental Analysis Center and technical support from Nathan Dalleska. We thank Natasha Shelby for contributions to writing and editing this manuscript. Availability of data and materials: The datasets supporting the conclusions of this article are included within the article and its additional files. Sequencing data (paired end reads in FASTQ) and a manifest file for analysis in Qiime2 are available under a CC-BY license via CaltechDATA: Supplementary Information includes a zip file containing all sequencing sample metadata, numerical microbial quantification data (16S copies from the main study + MPN from the pilot study), Qiime2 sequencing output data, PICRUSt2 output data, numerical bile acid analysis data, numerical body weight data, numerical food intake data, and analytical scripts (iPython Notebooks) for all figures and statistical analyses in the manuscript. This work was supported in part by a Kenneth Rainin Foundation Innovator Award (2018–1207), Army Research Office (ARO) Multidisciplinary University Research Initiative (MURI) contract #W911NF-17-1-0402, and the Jacobs Institute for Molecular Engineering for Medicine. National Science Foundation (NSF) Emerging Frontiers in Research and Innovation Award Grant 1137089. The funders had no role in the design of the study, collection, analysis or interpretation of data, nor in the writing of the manuscript. Author Contributions: SRB Conception, mouse tail cup development, animal study execution, animal study sample processing for quantitative 16S rRNA gene amplicon sequencing, quantitative 16S rRNA gene amplicon sequencing and data analysis, animal study sample processing for metabolomic analysis, bile acid metabolomics data analysis, manuscript preparation. JCR Metabolomics method development and validation, animal study sample processing for metabolomic analysis, UPLC-MS instrument setup and sample analysis, chromatography and mass spectra data analysis. RFI Project supervision and administration, acquisition of funding, manuscript review and editing. All authors read and approved the final manuscript. Ethics approval and consent to participate: All animal handling and procedures were performed in accordance with the California Institute of Technology (Caltech) Institutional Animal Care and Use Committee (IACUC). Consent for publication: Not applicable. Competing interests: The contents of this article are the subject of a patent application filed by Caltech.
Group:Jacobs Institute for Molecular Engineering for Medicine
Funding AgencyGrant Number
Kenneth Rainin Foundation2018-1207
Army Research Office (ARO)W911NF-17-1-0402
Jacobs Institute for Molecular Engineering for MedicineUNSPECIFIED
Subject Keywords:Microbial quantification, Metabolomics analyses, Mouse models, Small intestine microbiota, Bile acids, Deconjugation, Coprophagy, Microbial colonization, 16S rRNA gene amplicon sequencing
PubMed Central ID:PMC7017497
Record Number:CaltechAUTHORS:20200212-152816065
Persistent URL:
Official Citation:Bogatyrev, S.R., Rolando, J.C. & Ismagilov, R.F. Self-reinoculation with fecal flora changes microbiota density and composition leading to an altered bile-acid profile in the mouse small intestine. Microbiome 8, 19 (2020).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101255
Deposited By: Tony Diaz
Deposited On:12 Feb 2020 23:46
Last Modified:04 Mar 2020 20:28

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