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Record W4391873707 · doi:10.1093/jcag/gwad061.037

A37 POSTBIOTIC BACTERIAL MEMBRANE VESICLES FROM <i>B. SUBTILIS</i> DELIVER NOD2 LIGANDS AND PROMOTE IN VITRO WOUND RE-EPITHLIALIZATION THROUGH RIPK2 SIGNALING

2024· article· en· W4391873707 on OpenAlexaff
Lauren Baerg, Dana J. Philpott, Radhakrishnan Mahadevan

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNOD2Cell biologyIn vitroChemistryVesicleMembraneBiologyBiochemistryInnate immune systemReceptor

Abstract

fetched live from OpenAlex

Abstract Background Bacterial membrane vesicles (MVs) are bilipid nanoparticles secreted as a conserved method of intercellular communication. MVs from Gram-positive bacteria carry diverse bacterial products and represent a unique opportunity in the growing field of postbiotics. This native machinery for mediating microbe-host interactions makes MVs a promising tool for intestinal drug delivery in the context of Crohn’s disease (CD). CD is a chronic inflammatory bowel disease characterized by relapsing inflammation of the digestive tract. CD is associated with (1) loss of function mutations in the host gene encoding the nuclear-binding oligomerization domain 2 (NOD2) pattern recognition receptor and (2) a gut microbiome with reduced capabilities to generate NOD2 stimulating muropeptides from peptidoglycan. Nod2-/- mice have decreased barrier integrity and impaired epithelial restitution upon challenge. However, there are currently no therapeutic strategies targeting NOD2 for CD management. Aims The aims of this study were to (1) leverage MVs as a biological system for NOD2 ligand delivery to intestinal epithelial cells and (2) determine the roll of probiotic MVs and bacterial ligand synergy in wound re-epithelialization. Methods MVs were purified from B. subtilis through filtration and ultracentrifugation. MVs were characterized through nanoparticle tracking analysis using NanoSight300. WT and NOD2-/- HCT116 cells, a human colorectal carcinoma cell line, were utilized for IL-8 secretion quantification by ELISA, gene expression by qPCR, and in vitro scratch wound assay by Incucyte quantification. Results Here, we demonstrate for the first time that MVs from B. subtilis deliver NOD2 ligands in vitro. Treatment with isolated MVs induces IL8 secretion and CXCL1 expression in a NOD2-dependent manner. Furthermore, MVs promote re-epithelialization after in vitro scratch wounding. This effect was completely blunted by the addition of an inhibitor for RIPK2, a downstream transducer required for NOD2 signaling. Through bacterial pathogen-associated molecular patterns (PAMPs) screening, we found that wound re-epithelialization is promoted by PAMP synergy but dependent on RIPK2 signaling. Conclusions This work suggests that delivery of muropeptides by probiotic-derived MVs is a promising strategy to promote epithelial regeneration during injury through targeting NOD2. Future directions will work towards validating these findings in human ileal primary cells and murine models of intestinal injury. Funding Agencies CIHRMedicine by Design

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.188
Teacher spread0.182 · 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
Published2024
Admission routes1
Has abstractyes

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