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Record W3134755218 · doi:10.1093/jcag/gwab002.029

A30 DIFFERENCES BETWEEN HUMAN AND MOUSE INTESTINAL EPITHELIAL CELLS IN THEIR INNATE IMMUNE RESPONSES TO BACTERIAL AND HOST STIMULI.

2021· article· en· W3134755218 on OpenAlexaff
Joannie M. Allaire, Art F. Y. Poon, Shauna M. Crowley, Martin Ståhl, Brian Bressler, Kevan Jacobson, Bruce A. Vallance

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsStemcell TechnologiesBC Children's Hospital
Fundersnot available
KeywordsInnate immune systemBiologyImmune systemImmunologyInnate lymphoid cellCell biologyInflammationChemokineCytokinePattern recognition receptorSignal transductionReceptor

Abstract

fetched live from OpenAlex

Abstract Background Intestinal epithelial cells (IEC) reside in close contact with the gut microbiota. It is thus important that IEC are hypo-responsive to bacterial products to prevent maladaptive inflammatory responses in the gut, such as those seen in Inflammatory bowel diseases (IBD). This suppression of innate immune signaling in IEC is in part due to their strong expression of Single Ig IL1 related receptor (SIGIRR), a negative regulator of interleukin (IL)-1 and toll-like receptor (TLR) signaling. IL37, a newly recognized anti-inflammatory cytokine has been shown to strongly inhibit innate signaling in cells by binding to, and signaling through SIGIRR, leading to suppression of various forms of inflammation in mice. Few studies have looked at the function of IL-37/SIGIRR in IEC and their potential use to balance inflammatory responses. Notably, while many groups have studied IEC immune response in vitro, using transformed IEC lines, our focus is on primary-derived IEC which more accurately reflect in vivo responses. Aims To characterize IEC intrinsic and species-specific immune responses elicited by bacteria and host products as well as the role of IL37/SIGIRR in regulating this innate signaling. Methods We used organoid to study the innate immune responses of primary IEC derived from human or mouse colon (colonoids). After stimulation with inflammatory stimuli (IL1β, FliC and LPS), qPCR, ELISA, Milliplex Multiplex Assay and Western blot were used to determine modification in signalling pathway and cytokine/chemokine secretion. Results Using colonoids derived from healthy donors, we demonstrated that unlike transformed cell lines or mouse IEC, human IEC respond only to the bacterial product FliC, and not to LPS or IL1β. We further characterized human colonoid innate immune responses and despite significant inter-individual variability upon FliC stimulation, all organoids released several chemokines (IL8, CXCL1, CXCL2, CCL2 and CCL20). We showed for the first time that IL37 attenuated these innate immune responses through inhibition of intracellular signaling pathways (p38 and NFkB). Using colonoids derived from wildtype and Sigirr deficient mice, we found that mice IEC were responsive to IL1b and FliC and that the suppressive effects of IL37 were Sigirr dependent. Conclusions Our results show that human IEC show variability among individuals in the magnitude of their innate immune responses, and these responses differ from those obtained from transformed cells and primary mouse IEC. For the first time, we show that IL37 suppresses IEC innate immune responses, through its ability to signal through Sigirr. Further investigations will assess the ability of IL37 to control inflammation of IEC derived from IBD patients, as a potential therapeutic to promote gut health. Funding Agencies CAG, CIHRMSFHR

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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