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Record W4213207054 · doi:10.1093/jcag/gwab049.039

A40 IDENTIFYING NOVEL ROLES FOR TLR2 SIGNALING IN THE INTESTINAL EPITHELIUM USING ORGANOIDS

2022· article· en· W4213207054 on OpenAlexaff
Y Chen, Joannie M. Allaire, Hongsheng Yang, Shauna M. Crowley, Bruce A. Vallance

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsTLR2BiologyCXCL1Innate immune systemOrganoidChemokineImmunologyToll-like receptorCCL20Intestinal epitheliumReceptorImmune systemCell biologyMicrobiologyEpitheliumChemokine receptor

Abstract

fetched live from OpenAlex

Abstract Background Inflammatory bowel disease (IBD) is thought to result from an imbalance between protective and damaging immune responses to the resident microbiota and other luminal antigens. Increasing evidence suggests that toll-like-receptor (TLR)-mediated innate immune dysfunction contributes to the pathogenesis of IBD. Among the receptors in the TLR family, TLR2 and its signalling pathway appears to play an important protective role in the gastrointestinal (GI) tract. Notably, our group previously discovered that Tlr2 expression by nonhematopoietic cells played an important protective role in the Citrobacter rodentium model of infectious colitis. Aims To determine if intestinal epithelial cells (IECs) control Tlr2 dependent tissue protective responses, we sought to characterize the role of Tlr2 signalling in intestinal organoids. In addition, to better define the role of Tlr2 during C. rodentium infection, we developed a novel in vitro model of C. rodentium infection using organoid-derived monolayers. Methods Organoids were derived from the colonic tissue of wild type (C57BL/6J) and Tlr2 deficient (-/-) mice and then stimulated with Tlr2 agonists, and their responses were evaluated by qPCR, ELISA, Western blot and immunostaining. In addition, 2D monolayers were grown from organoids, and infected with C. rodentium to explore whether Tlr2 signaling regulates other protective IEC functions such as barrier proteins and cell death in response to noxious stimuli. Results Stimulation of WT, but not Tlr2-/- mouse orgnaoids led to increased transcription of chemokine and cytokine genes Ccl20, Mcp-1, Cxcl1 and Tnf-α. This was accompanied by increased protein secretion through a NF-κB and p38 MAP kinase dependent mechanism. Interestingly, organoids derived from the distal colon displayed stronger Tlr2 responses than organoids from the proximal colon. During C. rodentium infection of monolayers, Tlr2 signaling had no effect on the distribution of tight junction proteins such as ZO-1 or Claudin3, however, Tlr2 did regulate levels of IEC apoptosis upon C. rodentium infection. Conclusions Our study demonstrates that colonic organoids express functional Tlr2, which upon stimulation, leads to pro-inflammatory responses as well as control over cell death. Our novel C. rodentium infection model enables us to further study the role of IEC in promoting host defense during bacterial infection. Futher work will examine how interactions with Tlr2 dependent cytokines (ie. IL-6, IL-22) impact IEC responses to C. rodentium. Funding Agencies CCC, CIHRCH.I.L.D

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.239
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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