Evidence map›Paper›PMID 39945519›Full record

ArticlemSphere2025

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

Shanley N Roach, Wendy Phillips, Lauren M Pross, Autumn E Sanders, Mark J Pierson, Ryan C Hunter, Ryan A Langlois

Abstract read
In one paragraph

Article in mSphere, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shanley N RoachDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-4186-0846
Wendy PhillipsMinnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota, USA.
Lauren M ProssDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Autumn E SandersDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Mark J PiersonDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Ryan C HunterDepartment of Microbiology and Immunology, University at Buffalo, Getzville, New York, USA.ORCID 0000-0003-3841-1676
Ryan A LangloisDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-0515-571X

Funding

TRAINING-PULMONARY CELL &MOLECULAR BIOLOGY &PHYSIOLOGYT32HL007741 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI DUDLEY, R. ADAMS, INGBAR, DAVID H · 1994 to 2023
$13.9M
Natural model for evaluating within- and cross-species virus transmissionR01AI173043 · NIAID · UNIVERSITY OF MINNESOTA · PI Ryan Langlois, Zhongde Wang · 2023 to 2026
$2.9M
New mouse model to better predict human immunity to influenza vaccination and infectionR01AI150600 · NIAID · UNIVERSITY OF MINNESOTA · PI LANGLOIS, RYAN, MASOPUST, DAVID · 2021 to 2024
$2.5M
HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID) R01 AI150600, R01 AI173043NHLBI NIH HHS T32 HL007741NIAID NIH HHS R01 AI150600NIAID NIH HHS R01 AI173043
6 · The paper itself

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.IMPORTANCETraditionally 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.

Indexed as

Gastrointestinal MicrobiomeMicrobiotaOrthomyxoviridae InfectionsAnimalsBacteriaCecumDisease Models, AnimalFemaleHousing, AnimalInfluenza A virusIntestine, LargeIntestine, SmallMiceMice, Inbred C57BLdirty micedysbiosisinfluenza virusmicrobiome

Identifiers

PMID39945519
PMCPMC11934326

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.