V-ATPase is a universal regulator of LC3 associated phagocytosis and non-canonical autophagy
Bibliographic record
Abstract
Abstract Non-canonical autophagy is a key cellular pathway in immunity, cancer and neurodegeneration, characterised by C onjugation of A TG8 to endolysosomal S ingle- M embranes (CASM). CASM is activated by engulfment (endocytosis, phagocytosis), agonists (STING, TRPML1) and infection (influenza), dependent on the ATG16L1 WD40-domain, and specifically K490. However, the factor(s) associated with non-canonical ATG16L1 recruitment, and CASM induction, remain unknown. Here, we investigate a role for V-ATPase during non-canonical autophagy. We report that increased V0-V1 engagement is associated with, and sufficient for, CASM activation. Upon V0-V1 binding, V-ATPase directly recruits ATG16L1, via K490, during LC3-associated phagocytosis (LAP), STING- and drug-induced CASM, indicating a common mechanism. Furthermore, during LAP, key molecular players, including NADPH oxidase/ROS, converge on V-ATPase. Finally, we show that LAP is sensitive to Salmonella SopF, which disrupts the V-ATPase-ATG16L1 axis, and provide evidence that CASM contributes to the Salmonella host response. Together, these data identify V-ATPase as a universal regulator of CASM, and indicate that SopF evolved in part to evade non-canonical autophagy.
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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) | 0.001 | 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".