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RGal Increases Intestinal Epithelial Barrier Function in a PKC‐Dependent Manner and Drives an Inflammatory Gene Expression Profile

2019· article· en· W3175812618 on OpenAlexafffundabout
Judie Shang, Cristiane Hatsuko Baggio, Adamara Machado Nascimento, Thales R. Cipriani, Wallace K. MacNaughton

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Physiological Society
KeywordsBarrier functionProtein kinase CTight junctionUssing chamberInflammatory bowel diseaseGene expressionCaco-2InflammationChemistryCell biologyIntestinal permeabilityIntestinal mucosaEpitheliumSignal transductionMolecular biologyInternal medicineImmunologyBiologyGeneIn vitroMedicinePathologyBiochemistryDisease

Abstract

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Background Loss of intestinal epithelial barrier function has been linked to inflammatory bowel disease (IBD). We previously showed that the dietary fibre, rhamnogalacturonan (RGal), reduces inflammation in a murine model of DSS colitis. Additionally, apical treatment of Caco2 human intestinal epithelial cells with RGal increases transepithelial electrical resistance (TER) and accelerates wound‐healing, but the underlying mechanisms remain unknown. Aims We aimed to determine the mechanisms of the RGal mediated increase in epithelial barrier function. (1) Given the ability of PKC to modulate barrier permeability we aimed to determine the role of PKC in the RGal‐mediated increase in epithelial barrier function. (2) We aimed to determine changes in gene expression following RGal treatment. Methods (1) To determine the role of PKC in the RGal‐induced increase in epithelial barrier function, Caco2 monolayers were mounted in Ussing Chambers, pre‐treated with pan protein kinase C (PKC), PKCz‐specific, or classical PKC inhibitors (GFX, PKCz pseudosubstrate or Go6976 respectively) and then treated with RGal. Change in TER and FITC‐dextran flux in response to RGal were assessed. (2) To determine the transcriptionally dependent effects of RGal on epithelial barrier function, Caco2 monolayers were treated apically for 6, 12 and 24h with RGal and RNAseq was performed. Genes with changes in expression more than 3‐fold were entered into Enrichr for pathway analysis. In order to confirm changes in gene expression from RNAseq, a multi‐array immunoassay was performed. Results (1) RGal (1 mg/mL) reduced FITC‐dextran flux by 52.0% (n=5, p<0.05) 30 min post‐treatment. The effect of RGal on macromolecular permeability was reduced with GFX pre‐treatment (500 nM) by 75.3% (n=5, p<0.01). However, the ability of GFX to block the RGal‐mediated increase in barrier function was not mimicked in monolayers pre‐treated with PKCz pseudosubstrate inhibitor (10 mM, n=6) or Go6976 (10 nM, n=5). (2) While RGal had no significant effect on tight junction gene expression 6h post‐treatment, it upregulated the expression of inflammatory response genes including neutrophil regulatory genes such as CXCL8. Consistent with gene expression data, multiplex protein assay revealed an upregulation in CXCL8 family chemokines and G‐CSF as early as 2h in cell lysates and 6h in the supernatant. Conclusions The RGal‐mediated increase in intestinal epithelial barrier function is dependent on PKC. Transcriptionally, RGal upregulates the expression of inflammatory mediators such as CXCL8. Understanding the mechanism of the RGal‐induced increase in intestinal epithelial barrier function may allow for leverage of these mechanisms to treat IBD. Support or Funding Information Project supported by the NSERC (Canada), J.S. supported by an UGREF from the American Physiological Society. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.048
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.231
Teacher spread0.217 · 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 teacher head, 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".

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Citations0
Published2019
Admission routes3
Has abstractyes

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