Evidence map›Paper›PMID 38286428›Full record

ArticlemSphere2024

Comparison of mouse models of microbial experience reveals differences in microbial diversity and response to vaccination.

Autumn E Sanders, Henriette Arnesen, Frances K Shepherd, Dira S Putri, Jessica K Fiege, Mark J Pierson, Shanley N Roach, Harald Carlsen, David Masopust, Preben Boysen and 1 more

Open access · goldAbstract read
In one paragraph

Article in mSphere, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
6.6field-weighted citation impact, top 3% of its field
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

18 citing papers in PubMed, 17 citations in OpenAlex.

  1. A gavage-fomite based method to generate mouse models with natural microbiota.Journal of immunology (Baltimore, Md. : 1950) · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Diverse Microbial Exposure Enhances CD8bioRxiv : the preprint server for biology · 2026
    Article
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  11. Article
  12. Review
  13. Article
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  15. Article
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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

11 authors at 2 institutions in 2 countries.

Autumn E Sanders *Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Henriette Arnesen *Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway.ORCID 0000-0003-1173-4010
Frances K Shepherd *Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Dira S PutriDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Jessica K FiegeDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Mark J PiersonCenter for Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Shanley N RoachDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Harald CarlsenFaculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.
David MasopustDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-9440-3884
Preben BoysenFaculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway.ORCID 0000-0002-0084-1251
Ryan A LangloisDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-0515-571X
University of Minnesota · USNorwegian University of Life Sciences · NO

Funding

COLLABORATIVE INFLUENZA VACCINE INNOVATION CENTER: UNIVERSAL INFLUENZA VACCINE RESEARCH75N93019C00051 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KRAMMER, FLORIAN · 2019 to 2025
$105.4M
TRAINING-PULMONARY CELL &MOLECULAR BIOLOGY &PHYSIOLOGYT32HL007741 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI DUDLEY, R. ADAMS, INGBAR, DAVID H · 1994 to 2023
$13.9M
Minnesota Training Program in VirologyT32AI083196 · NIAID · UNIVERSITY OF MINNESOTA · PI Louis M Mansky · 2010 to 2026
$3.2M
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
NHLBI NIH HHS T32 HL007741NIAID NIH HHS 75N93019C00051NIAID NIH HHS R01 AI150600NIAID NIH HHS T32 AI083196
6 · The paper itself

Abstract

Specific pathogen-free (SPF) laboratory mice dominate preclinical studies for immunology and vaccinology. Unfortunately, SPF mice often fail to accurately model human responses to vaccination and other immunological perturbations. Several groups have taken different approaches to introduce additional microbial experience to SPF mice to better model human immune experience. How these different models compare is unknown. Here, we directly compare three models: housing SPF mice in a microbe-rich barn-like environment (feralizing), adding wild-caught mice to the barn-like environment (fer-cohoused), or cohousing SPF mice with pet store mice in a barrier facility (pet-cohoused); the two latter representing different murine sources of microbial transmission. Pet-cohousing mice resulted in the greatest microbial exposure. Feralizing alone did not result in the transmission of any pathogens tested, while fer-cohousing resulted in the transmission of several picornaviruses. Murine astrovirus 2, the most common pathogen from pet store mice, was absent from the other two model systems. Previously, we had shown that pet-cohousing reduced the antibody response to vaccination compared with SPF mice. This was not recapitulated in either the feralized or fer-cohoused mice. These data indicate that not all dirty mouse models are equivalent in either microbial experience or immune responses to vaccination. These disparities suggest that more cross model comparisons are needed but also represent opportunities to uncover microbe combination-specific phenotypes and develop more refined experimental models. Given the breadth of microbes encountered by humans across the globe, multiple model systems may be needed to accurately recapitulate heterogenous human immune responses.IMPORTANCEAnimal models are an essential tool for evaluating clinical interventions. Unfortunately, they can often fail to accurately predict outcomes when translated into humans. This failure is due in part to a lack of natural infections experienced by most laboratory animals. To improve the mouse model, we and others have exposed laboratory mice to microbes they would experience in the wild. Although these models have been growing in popularity, these different models have not been specifically compared. Here, we directly compare how three different models of microbial experience impact the immune response to influenza vaccination. We find that these models are not the same and that the degree of microbial exposure affects the magnitude of the response to vaccination. These results provide an opportunity for the field to continue comparing and contrasting these systems to determine which models best recapitulate different aspects of the human condition.

Indexed as

ImmunityVaccinationAnimalsDisease Models, AnimalHumansMiceSpecific Pathogen-Free Organismsmouse modelsnatural mouse virusespreclinical modelsvaccines

Identifiers

PMID38286428
PMCPMC10900878
OpenAlexW4391329008

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.