Identification of gut microbial species linked with disease variability in a widely used mouse model of colitis

Samuel C. Forster, Simon Clare, Benjamin S. Beresford-Jones, Katherine Harcourt, George Notley, Mark D. Stares, Nitin Kumar, Amelia T. Soderholm, Anne Adoum, Hannah Wong, Bélen Morón, Cordelia Brandt, Gordon Dougan, David J. Adams, Kevin J. Maloy, Virginia A. Pedicord, Trevor D. Lawley

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22 Citations (Scopus)


Experimental mouse models are central to basic biomedical research; however, variability exists across genetically identical mice and mouse facilities making comparisons difficult. Whether specific indigenous gut bacteria drive immunophenotypic variability in mouse models of human disease remains poorly understood. We performed a large-scale experiment using 579 genetically identical laboratory mice from a single animal facility, designed to identify the causes of disease variability in the widely used dextran sulphate sodium mouse model of inflammatory bowel disease. Commonly used treatment endpoint measures—weight loss and intestinal pathology—showed limited correlation and varied across mouse lineages. Analysis of the gut microbiome, coupled with machine learning and targeted anaerobic culturing, identified and isolated two previously undescribed species, Duncaniella muricolitica and Alistipes okayasuensis, and demonstrated that they exert dominant effects in the dextran sulphate sodium model leading to variable treatment endpoint measures. We show that the identified gut microbial species are common, but not ubiquitous, in mouse facilities around the world, and suggest that researchers monitor for these species to provide experimental design opportunities for improved mouse models of human intestinal diseases.

Original languageEnglish
Pages (from-to)590-599
Number of pages10
JournalNature Microbiology
Issue number4
Publication statusPublished - Apr 2022

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