Proteomics of autophagy deficient macrophages reveals enhanced antimicrobial immunity via the oxidative stress response
Bibliographic record
Abstract
Abstract Defective autophagy is associated with chronic inflammation. Loss-of-function of the core autophagy gene Atg16l1 increases risk for Crohn’s disease by enhancing innate immunity in macrophages. However, autophagy also mediates clearance of intracellular pathogens. These divergent observations prompted a re-evaluation of ATG16L1 in antimicrobial immunity. In this study, we found that loss of Atg16l1 in macrophages enhanced the killing of virulent Shigella flexneri ( S.flexneri ), an enteric bacterium that resides within the cytosol by escaping all membrane-bound compartments. Quantitative multiplexed proteomics revealed that ATG16L1 deficiency significantly upregulated proteins involved in the glutathione-mediated antioxidant response to compensate for elevated oxidative stress, which also promoted S.flexneri killing. Consistently, myeloid cell-specific deletion of Atg16l1 accelerated bacterial clearance in vivo . Finally, pharmacological modulation of oxidative stress by suppression of cysteine import conferred enhanced microbicidal properties to wild type macrophages. These findings demonstrate that control of oxidative stress by ATG16L1 regulates antimicrobial immunity against intracellular pathogens. Impact statement Maculins et al utilize multiplexed mass spectrometry to show that loss of the autophagy gene Atg16l1 in macrophages enhances antimicrobial immunity against intracellular pathogens via the oxidative stress response.
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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 | 0.001 |
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".