Virus-induced perturbations in the mouse microbiome are impacted by microbial experience

TL;DR

This study shows that mice with diverse microbiomes react differently to viral infections compared to standard lab mice, which could improve preclinical research accuracy.

Contribution

The study introduces cohoused 'dirty' mice as a model to better understand microbiome variability and its interaction with infection.

Findings

Cohoused mice showed increased bacterial diversity in the small intestine and cecum.

Influenza A virus infection caused microbiome clustering by housing condition and infection status in the cecum and large intestine.

Baseline microbiome diversity influences how infections alter microbial communities.

Abstract

The bacterial microbiome has a major impact on health and can shape metabolism, host tolerance, immune responses, and the outcome of future infections. The bacterial microbiome is highly variable between individuals. Specific pathogen-free animals have reduced microbiome diversity, making it difficult to evaluate the impact of infection-induced microbiome disruption that would be observed in free-living animals, including people. Mice are commonly used as a preclinical model but unfortunately often fail to predict translation success or failure, particularly for immune and infectious disease-targeting therapies. Here, we utilize pet store mouse cohoused “dirty” mice with diverse microbial experience to explore how host variability and infection may be interacting to drive unique microbiome changes. We found that cohoused animals had significantly increased bacterial diversity in the small intestine and cecum but not in the large intestine. There were differentially abundant taxa between clean and dirty animals in all three tissues. After infection with influenza A virus, samples clustered by both housing condition and infection status in the cecum and large intestine, while small intestine samples clustered predominantly by infection. Altogether, these results highlight the differential impact of housing, infection, and interaction between the two in dictating community composition across the gastrointestinal microbiome.

Traditionally housed pathogen-free mouse models do not fully capture the natural variability observed among human microbiomes, which may underlie their poor translationally predictive value. Understanding the difference between pathogen-induced shifts in the bacterial microbiome and natural microbiome variance is a major hurdle to determining bacterial biomarkers of disease. It is also critical to understand how diverse baseline microbiomes may be differentially impacted by infection and contribute to disease. Pet store cohoused “dirty” mice have diverse microbial experiences and microbiomes, allowing us to evaluate how baseline variation, infection, and interaction between the two impact the microbiome.

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