Evidence map›Paper›PMID 39562646›Full record

ReviewNature reviews. Immunology2025

Integrating natural commensals and pathogens into preclinical mouse models.

Barbara Rehermann, Andrea L Graham, David Masopust, Sara E Hamilton

Abstract readReview
In one paragraph

Review in Nature reviews. Immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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

4 authors.

Barbara RehermannImmunology Section, Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA. rehermann@nih.gov.ORCID http://orcid.org/0000-0001-6832-9951
Andrea L GrahamDepartment of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA.ORCID http://orcid.org/0000-0002-6580-2755
David MasopustCenter for Immunology, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0002-9440-3884
Sara E HamiltonCenter for Immunology, University of Minnesota, Minneapolis, MN, USA.

Funding

Understanding the functional agility of effector memory CD8 T cellsR01AI155468 · NIAID · UNIVERSITY OF MINNESOTA · PI HAMILTON HART, SARA ELIZABETH · 2021 to 2025
$2.8M
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
NIAID NIH HHS R01 AI150600NIAID NIH HHS R01 AI155468
6 · The paper itself

Abstract

Fundamental discoveries in many aspects of mammalian physiology have been made using laboratory mice as research models. These studies have been facilitated by the genetic tractability and inbreeding of such mice, the large set of immunological reagents that are available, and the establishment of environmentally controlled, high-throughput facilities. Such facilities typically include barriers to keep the mouse colonies free of pathogens and the frequent re-derivation of the mice severely limits their commensal flora. Because humans have co-evolved with microorganisms and are exposed to a variety of pathogens, a growing community of researchers posits that preclinical disease research can be improved by studying mice in the context of the microbiota and pathogens that they would encounter in the natural world. Here, we provide a perspective of how these different approaches can be combined and integrated to improve existing mouse models to enhance our understanding of disease mechanisms and develop new therapies for humans. We also propose that the term 'mice with natural microbiota' is more appropriate for describing these models than existing terms such as 'dirty mice'.

Indexed as

Disease Models, AnimalMicrobiotaSymbiosisAnimalsHumansMice

Identifiers

PMID39562646
PMCPMC12126596

What OpenQuestion holds

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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.