Evidence map›Paper›PMID 36603588›Full record

ArticleCell host & microbe2023

Microbiota-dependent proteolysis of gluten subverts diet-mediated protection against type 1 diabetes.

Matthew C Funsten, Leonid A Yurkovetskiy, Andrey Kuznetsov, Derek Reiman, Camilla H F Hansen, Katharine I Senter, Jean Lee, Jeremy Ratiu, Shiva Dahal-Koirala, Dionysios A Antonopoulos and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in Cell host & microbe, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.3field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Islet Tissue Macrophages in Immunity Homeostasis and Type 1 Diabetes.Clinical reviews in allergy & immunology · 2025
    Review
  2. Review
  3. Article
  4. Advancing Animal Models of Human Type 1 Diabetes.Cold Spring Harbor perspectives in medicine · 2024
    Review
  5. 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

15 authors at 7 institutions in 3 countries.

Matthew C FunstenCommittee on Immunology, The University of Chicago, Chicago, IL 60637, USA; Department of Pathology, The University of Chicago, Chicago, IL 60637, USA.
Leonid A YurkovetskiyDepartment of Pathology, The University of Chicago, Chicago, IL 60637, USA; Committee on Microbiology, The University of Chicago, Chicago, IL 60637, USA.
Andrey KuznetsovDepartment of Pathology, The University of Chicago, Chicago, IL 60637, USA.
Derek ReimanToyota Technological Institute at Chicago, Chicago, IL 60637, USA.
Camilla H F HansenDepartment of Pathology, The University of Chicago, Chicago, IL 60637, USA; Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870 Frederiksberg C, Denmark.
Katharine I SenterDepartment of Pathology, The University of Chicago, Chicago, IL 60637, USA.
Jean LeeDepartment of Pathology, The University of Chicago, Chicago, IL 60637, USA; Committee on Cancer Biology, The University of Chicago, Chicago, IL 60637, USA.
Jeremy RatiuThe Jackson Laboratory, Bar Harbor, ME 04609, USA.
Shiva Dahal-KoiralaKG Jebsen Coeliac Disease Research Centre and Department of Immunology, University of Oslo and University of Oslo Hospital, 0372 Oslo, Norway.
Dionysios A AntonopoulosBiosciences Division, Argonne National Laboratory, Lemont, IL 60439, USA.
Gary M DunnyDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455, USA.
Ludvig M SollidKG Jebsen Coeliac Disease Research Centre and Department of Immunology, University of Oslo and University of Oslo Hospital, 0372 Oslo, Norway.
David SerrezeThe Jackson Laboratory, Bar Harbor, ME 04609, USA.
Aly A KhanCommittee on Immunology, The University of Chicago, Chicago, IL 60637, USA; Department of Pathology, The University of Chicago, Chicago, IL 60637, USA; Institute for Population and Precision Health, The University of Chicago, Chicago, IL 60637, USA; Department of Family Medicine, The University of Chicago, Chicago, IL 60637, USA.
Alexander V ChervonskyCommittee on Immunology, The University of Chicago, Chicago, IL 60637, USA; Department of Pathology, The University of Chicago, Chicago, IL 60637, USA; Committee on Microbiology, The University of Chicago, Chicago, IL 60637, USA. Electronic address: achervon@bsd.uchicago.edu.
University of Chicago · USJackson Laboratory · USOslo University Hospital · NOArgonne National Laboratory · USToyota Technological Institute at Chicago · USUniversity of Copenhagen · DKUniversity of Minnesota · US

Funding

ULTRASTRUCTURE AND CYTOMORPHOLOGY COREP30DK042086 · NIDDK · UNIVERSITY OF CHICAGO · PI CHANG, EUGENE B · 1990 to 2025
$29.8M
Molecular And Cellular Biology Training ProgramT32GM007183 · NIGMS · UNIVERSITY OF CHICAGO · PI GLICK, BENJAMIN S, RICE, PHOEBE A · 1985 to 2021
$23.9M
INTERDISCIPLINARY TRAINING PROGRAM IN IMMUNOLOGYT32AI007090 · NIAID · UNIVERSITY OF CHICAGO · PI Peter Aidan Savage · 1985 to 2026
$11.7M
The Jackson Laboratory Center for Precision Genetics: From New Models to Novel TherapeuticsU54OD020351 · OD · JACKSON LABORATORY · PI NISHINA, PATSY M · 2015 to 2019
$10.2M
Diabetogenic Role of MHC Class I Alleles in NOD MiceR01DK046266 · NIDDK · JACKSON LABORATORY · PI SERREZE, DAVID V · 2000 to 2018
$7.2M
B-lymphocyte Targeting Therapies for Autoimmune DiabetesR01DK095735 · NIDDK · JACKSON LABORATORY · PI SERREZE, DAVID V · 2013 to 2025
$6.2M
Type 1 diabetes: the role of commensal microbiotaR01AI082418 · NIAID · UNIVERSITY OF CHICAGO · PI CHERVONSKY, ALEXANDER V · 2010 to 2020
$4.3M
Enhancement of autoimmunity in type 1 diabetes by glutenR01AI158744 · NIAID · UNIVERSITY OF CHICAGO · PI CHERVONSKY, ALEXANDER V · 2021 to 2025
$2.9M
Diet and microbiota in type 1 diabetesR21AI115683 · NIAID · UNIVERSITY OF CHICAGO · PI CHERVONSKY, ALEXANDER V · 2015 to 2016
$435k
DIABETOGENIC ROLE OF H-2G7 CLASS I ALLELES IN NOD MICER29DK046266 · NIDDK · JACKSON LABORATORY · PI SERREZE, DAVID V. · 1993 to 1998
–
NIAID NIH HHS R01 AI082418NIAID NIH HHS R01 AI158744NIAID NIH HHS R21 AI115683NIDDK NIH HHS P30 DK042086NIDDK NIH HHS R01 DK046266NIDDK NIH HHS R01 DK095735NIDDK NIH HHS R29 DK046266NIGMS NIH HHS T32 GM007183NIH HHS U54 OD020351
6 · The paper itself

Abstract

Diet and commensals can affect the development of autoimmune diseases like type 1 diabetes (T1D). However, whether dietary interventions are microbe-mediated was unclear. We found that a diet based on hydrolyzed casein (HC) as a protein source protects non-obese diabetic (NOD) mice in conventional and germ-free (GF) conditions via improvement in the physiology of insulin-producing cells to reduce autoimmune activation. The addition of gluten (a cereal protein complex associated with celiac disease) facilitates autoimmunity dependent on microbial proteolysis of gluten: T1D develops in GF animals monocolonized with Enterococcus faecalis harboring secreted gluten-digesting proteases but not in mice colonized with protease deficient bacteria. Gluten digestion by E. faecalis generates T cell-activating peptides and promotes innate immunity by enhancing macrophage reactivity to lipopolysaccharide (LPS). Gnotobiotic NOD Toll4-negative mice monocolonized with E. faecalis on an HC + gluten diet are resistant to T1D. These findings provide insights into strategies to develop dietary interventions to help protect humans against autoimmunity.

Indexed as

Diabetes Mellitus, Type 1MicrobiotaAnimalsDietGlutensHumansMiceMice, Inbred NODProteolysisGlutensceliac diseasediet and autoimmunityinsulin secretion regulationmicrobial proteolysis of glutenmicrobiota and autoimmunitytype 1 diabetes

Identifiers

PMID36603588
PMCPMC9911364
OpenAlexW4313594545

What OpenQuestion holds

Textmetadata
LicenceTDM
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.