Inhibition of the ULK1 protein complex suppresses Staphylococcus-induced autophagy and cell death
Bibliographic record
Abstract
Autophagy plays multiple roles in host cells challenged with extracellular pathogens. Here, we aimed to explore whether autophagy inhibition could prevent bacterial infections. We first confirmed widely distinct patterns of autophagy responses in host cells infected with Staphylococcus aureus , as compared with Salmonella . Only infection with Staphylococcus produced strong accumulation of lipidated autophagy-related protein LC3B (LC3B-II). Infection with virulent Staphylococcus strains induced formation of p62-positive aggregates, suggestive of accumulated ubiquitinated targets. During Salmonella infection, bacteria remain enclosed by lysosomal-associated membrane protein 2 (LAMP2)-positive lysosomes, whereas virulent Staphylococcus apparently exited from enlarged lysosomes and invaded the cytoplasm. Surprisingly, Staphylococcus appeared to escape from the lysosome without generation of membrane-damage signals as detected by galectin-3 recruitment. In contrast, Salmonella infection produced high levels of lysosomal damage, consistent with a downstream antibacterial xenophagy response. Finally, we studied the Unc-51–like autophagy-activating kinase 1 (ULK1) regulatory complex, including the essential subunit autophagy-related protein 13 (ATG13). Infection of cells with either Staphylococcus or Salmonella led to recruitment of ATG13 to sites of cytosolic bacterial cells to promote autophagosome formation. Of note, genetic targeting of ATG13 suppressed autophagy and the ability of Staphylococcus to infect and kill host cells. Two different ULK1 inhibitors also prevented Staphylococcus intracellular replication and host cell death. Interestingly, inhibition of the ULK1 pathway had the opposite effect on Salmonella , sensitizing cells to the infection. Our results suggest that ULK1 inhibitors may offer a potential strategy to impede cellular infection by S. aureus .
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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 | 0.001 |
| 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".