A Genome-wide Small Interfering RNA (siRNA) Screen Reveals Nuclear Factor-κB (NF-κB)-independent Regulators of NOD2-induced Interleukin-8 (IL-8) Secretion
Bibliographic record
Abstract
NOD2 encodes an intracellular multidomain pattern recognition receptor that is the strongest known genetic risk factor in the pathogenesis of Crohn disease (CD), a chronic relapsing inflammatory disorder of the intestinal tract. NOD2 functions as a sensor for bacterial cell wall components and activates proinflammatory and antimicrobial signaling pathways. Here, using a genome-wide small interfering RNA (siRNA) screen, we identify numerous genes that regulate secretion of the proinflammatory cytokine IL-8 in response to NOD2 activation. Moreover, many of the identified IL-8 regulators are linked by protein-protein interactions, revealing subnetworks of highly connected IL-8 regulators implicated in processes such as vesicle formation, mRNA stability, and protein ubiquitination and trafficking. A TNFα counterscreen to induce IL-8 secretion in an NOD2-independent manner reveals that the majority of the identified regulators affect IL-8 secretion irrespective of the initiating stimuli. Using immortalized macrophages, we validate the ubiquitin protease, USP8, and the endosomal sorting protein, VPS28, as negative regulators of NOD2-induced cytokine secretion. Interestingly, several genes that affect NOD2-induced IL-8 secretion are present in loci associated with CD risk by genome-wide association studies, supporting a role for the NOD2/IL-8 pathway, and not just NOD2, in the pathogenesis of CD. Overall, this screen provides a valuable resource in the advancement of our understanding of the genes that regulate the secretion of IL-8.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".