Deficiency of the autophagy gene ATG16L1 induces insulin resistance through KLHL9/KLHL13/CUL3-mediated IRS1 degradation
Bibliographic record
Abstract
Connections between deficient autophagy and insulin resistance have emerged, however, the mechanism through which reduced autophagy impairs insulin-signaling remains unknown. We examined mouse embryonic fibroblasts lacking Atg16l1 (ATG16L1 KO mouse embryonic fibroblasts (MEFs)), an essential autophagy gene, and observed deficient insulin and insulin-like growth factor-1 signaling. ATG16L1 KO MEFs displayed reduced protein content of insulin receptor substrate-1 (IRS1), pivotal to insulin signaling, whereas IRS1myc overexpression recovered downstream insulin signaling. Endogenous IRS1 protein content and insulin signaling were restored in ATG16L1 KO mouse embryonic fibroblasts (MEF) upon proteasome inhibition. Through proximity-dependent biotin identification (BioID) and co-immunoprecipitation, we found that Kelch-like proteins KLHL9 and KLHL13, which together form an E3 ubiquitin (Ub) ligase complex with cullin 3 (CUL3), are novel IRS1 interactors. Expression of Klhl9 and Klhl13 was elevated in ATG16L1 KO MEFs and siRNA-mediated knockdown of Klhl9 , Klhl13 , or Cul3 recovered IRS1 expression. Moreover, Klhl13 and Cul3 knockdown increased insulin signaling. Notably, adipose tissue of high-fat fed mice displayed lower Atg16l1 mRNA expression and IRS1 protein content, and adipose tissue KLHL13 and CUL3 expression positively correlated to body mass index in humans. We propose that ATG16L1 deficiency evokes insulin resistance through induction of Klhl9 and Klhl13 , which, in complex with Cul3 , promote proteasomal IRS1 degradation.
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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) | 0.000 | 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) | 0.002 | 0.001 |
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".