Countervailing, time-dependent effects on host autophagy promote intracellular survival of Leishmania
Bibliographic record
Abstract
Autophagy is essential for cell survival under stress and has also been implicated in host defense. Here, we investigated the interactions between Leishmania donovani , the main etiological agent of visceral leishmaniasis, and the autophagic machinery of human macrophages. Our results revealed that during early infection—and via activation of the Akt pathway— Leishmania actively inhibits the induction of autophagy. However, by 24 h, Leishmania switched from being an inhibitor to an overall inducer of autophagy. These findings of a dynamic, biphasic response were based on the accumulation of lipidated light chain 3 (LC3), an autophagosome marker, by Western blotting and confocal fluorescence microscopy. We also present evidence that Leishmania induces delayed host cell autophagy via a mechanism independent of reduced activity of the mechanistic target of rapamycin (mTOR). Notably, Leishmania actively inhibited mTOR-regulated autophagy even at later stages of infection, whereas there was a clear induction of autophagy via some other mechanism. In this context, we examined host inositol monophosphatase (IMPase), reduced levels of which have been implicated in mTOR-independent autophagy, and we found that IMPase activity is significantly decreased in infected cells. These findings indicate that Leishmania uses an alternative pathway to mTOR to induce autophagy in host macrophages. Finally, RNAi-mediated down-regulation of host autophagy protein 5 (ATG5) or autophagy protein 9A (ATG9A) decreased parasite loads, demonstrating that autophagy is essential for Leishmania survival. We conclude that Leishmania uses an alternative pathway to induce host autophagy while simultaneously inhibiting mTOR-regulated autophagy to fine-tune the timing and magnitude of this process and to optimize parasite survival.
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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) | 0.001 | 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".