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Record W4390080811 · doi:10.1101/2023.12.20.572362

Attenuating ABHD17 isoforms augments the <i>S</i> -acylation and function of NOD2 and a subset of Crohn’s disease-associated NOD2 variants

2023· preprint· en· W4390080811 on OpenAlexafffundabout
Charneal L. Dixon, Noah R. Martin, Micah J. Niphakis, Benjamin F. Cravatt, Gregory D. Fairn

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsDalhousie UniversitySt. Michael's Hospital
FundersNational Institutes of HealthCanadian Institutes of Health ResearchCoventry UniversityKenneth Rainin Foundation
KeywordsNOD2PalmitoylationCell biologyPeptidoglycanEndosomeSignal transductionBiologyChemistryBiochemistryIntracellularInnate immune systemReceptorEnzyme

Abstract

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ABSTRACT BACKGROUND AND AIMS NOD2 is an intracellular innate immune receptor that detects bacterial peptidoglycan fragments. Although nominally soluble, some NOD2 is associated with the plasma membrane and endosomal compartments for microbial surveillance. This membrane targeting is achieved through post-translational S - acylation of NOD2 by the protein acyltransferase ZDHHC5. Membrane attachment is necessary to initiate a signaling cascade in response to cytosolic peptidoglycan fragments. Ultimately, this signaling results in the production of antimicrobial peptides and proinflammatory cytokines. In most cases, S -acylation is a reversible post- translational modification with removal of the fatty acyl chain catalyzed by one of several acyl protein thioesterases. Deacylation of NOD2 by such an enzyme will displace it from the plasma membrane and endosomes, thus preventing signaling. METHODS To identify the enzymes responsible for NOD2 deacylation, we used engineered cell lines with RNA interference and small-molecule inhibitors. These approaches were combined with confocal microscopy, acyl-resin-assisted capture, immunoblotting, and cytokine multiplex assays. RESULTS We identified α/β-hydrolase domain-containing protein 17 isoforms (ABHD17A, ABHD17B, and ABHD17C) as the acyl protein thioesterases responsible for NOD2 deacylation. Inhibiting ABHD17 increased the plasma membrane localization of wild-type NOD2 and a subset of poorly acylated Crohn’s disease-associated variants. This enhanced NOD2 activity, increasing NF-κB activation and pro-inflammatory cytokine production in epithelial cells. CONCLUSIONS These findings demonstrate that ABHD17 isoforms are negative regulators of NOD2. The results also suggest that targeting ABHD17 isoforms could restore functionality to specific Crohn’s disease-associated NOD2 variants, offering a potential therapeutic strategy. Grant Support This work was supported by a Project Grant from the Canadian Institutes of Health Research (grant no.: PJT166010; to G.D.F.), an Innovator Award from the Kenneth Rainin Foundation, and a grant from the National Institutes of Health, (R01CA193994 to B.F.C). A Tier 1 Canada Research Chair supports G.D.F. in Multiomics of Lipids and Innate Immunity. C.L.D. was supported by a Breakthrough Accelerator Fellowship from the Dalhousie Medical Research Foundation/Medical Research Development Office. N.M is a recipient of a graduate scholarship from the I3V Wave and the Dalhousie Medical Research Development Office. Disclosures The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. SYNOPSIS The peptidoglycan sensor NOD2 requires post-translational S -acylation to associate with cellular membranes and transduce signals. This study identified the ABHD17 family of thioesterases as responsible for NOD2 deacylation and inactivation. Inhibiting or silencing ABHD17 isoforms increases S -acylation and functionality of NOD2 and a subset of Crohn’s disease-associated variants.

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 score0.005

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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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".

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Citations6
Published2023
Admission routes3
Has abstractyes

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