Attenuating ABHD17 Isoforms Augments the S-acylation and Function of NOD2 and a Subset of Crohn’s Disease-associated NOD2 Variants
Bibliographic record
Abstract
BACKGROUND & 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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".