Evidence map›Paper›PMID 38585881›Full record

ArticlebioRxiv : the preprint server for biology2024

Timing of standard chow exposure determines the variability of mouse phenotypic outcomes and gut microbiota profile.

Megan M Knuth, Carolina Vieira Campos, Kirsten Smith, Elizabeth K Hutchins, Shantae Lewis, Mary York, Lyndon M Coghill, Craig Franklin, Amanda MacFarlane, Aaron C Ericsson and 2 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 2 countries.

Megan M KnuthDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0001-8697-6036
Carolina Vieira CamposDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0002-6512-1159
Kirsten SmithDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Elizabeth K HutchinsDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Shantae LewisDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mary YorkUniversity of Missouri (MU) Bioinformatics and Analytics Core, Bond Life Sciences Center, Columbia, MO 65201, USA.ORCID 0009-0004-6428-3481
Lyndon M CoghillUniversity of Missouri (MU) Bioinformatics and Analytics Core, Bond Life Sciences Center, Columbia, MO 65201, USA.ORCID 0000-0002-6258-9194
Craig FranklinDepartment of Veterinary Pathobiology, MU, Columbia, MO 65201, USA.ORCID 0000-0002-9198-867X
Amanda MacFarlaneTexas A&M Agriculture, Food, and Nutrition Evidence Center, Fort Worth, TX 76102, USA.
Aaron C EricssonDepartment of Veterinary Pathobiology, MU, Columbia, MO 65201, USA.ORCID 0000-0002-3053-7269
Terry MagnusonDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Folami IderaabdullahDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0002-5754-2615
University of North Carolina at Chapel Hill · USMissouri College · USTexas Oncology · USUniversity of Missouri · US

Funding

UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa A. Troester · 2001 to 2026
$36.3M
UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SUSAN M. SMITH · 1999 to 2026
$31.6M
Resource Section - Core 001U42OD010924 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI TERRY R MAGNUSON · 2012 to 2026
$24.5M
UNC PREP in the Biomedical Sciences - Administrative SupplementR25GM089569 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBINSON, DONITA L, RODRIGUEZ-ROMAGUERA, JOSE · 2010 to 2024
$5.6M
Cancer Epigenetics Training GrantT32CA217824 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WEISSMAN, BERNARD E. · 2017 to 2021
$1.8M
Investigating the role of metabolic programming in vitamin D deficiency induced adiposityR21DK122242 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI IDERAABDULLAH, FOLAMI · 2020 to 2022
$552k
NCI NIH HHS T32 CA217824NIDDK NIH HHS P30 DK056350NIDDK NIH HHS R21 DK122242NIGMS NIH HHS R25 GM089569NIH HHS U42 OD010924
6 · The paper itself

Abstract

Standard chow diet contributes to reproducibility in animal model experiments since chows differ in nutrient composition, which can independently influence phenotypes. However, there is little evidence of the role of timing in the extent of variability caused by chow exposure. Here, we measured the impact of diet (5V5M, 5V0G, 2920X, and 5058) and timing of exposure (adult exposure (AE), lifetime exposure (LE), and developmental exposure (DE)) on growth & development, metabolic health indicators, and gut bacterial microbiota profiles across genetically identical C57BL6/J mice. Diet drove differences in macro- and micronutrient intake for all exposure models. AE had no effect on measured outcomes. However, LE mice exhibited significant sex-dependent diet effects on growth, body weight, and body composition. LE effects were mostly absent in the DE model, where mice were exposed to chow differences from conception to weaning. Both AE and LE models exhibited similar diet-driven beta diversity profiles for the gut bacterial microbiota, with 5058 diet driving the most distinct profile. Diet-induced beta diversity profiles were sex-dependent for LE mice. Compared to AE, LE drove 9X more diet-driven differentially abundant genera, majority of which were the result of inverse effects of 2920X and 5058. Our findings demonstrate that lifetime exposure to different chow diets has the greatest impact on reproducibility of experimental measures that are common components of preclinical mouse model studies. Importantly, weaning DE mice onto a uniform diet is likely an effective way to reduce unwanted phenotypic variability among experimental models.

Identifiers

PMID38585881
PMCPMC10996631
OpenAlexW4393355209

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.