<i>Leishmania donovani</i> modulates host macrophage mitochondrial metabolism, integrity, and function
Bibliographic record
Abstract
Abstract To colonize macrophages, Leishmania promastigotes employ virulence factors, including lipophosphoglycan (LPG), to impair host cell processes. Whereas previous studies revealed that Leishmania alters signaling axes that regulate mitochondrial function, scarce attention has been paid to the characterization of host cell mitochondrial metabolism during Leishmania infection and to the effectors involved therein. In this study, we addressed the hypothesis that L. donovani modulates host cell mitochondrial metabolism and function in an LPG-dependent manner. To this end, we infected bone-marrow-derived macrophages with metacyclic promastigotes and we assessed the expression kinetics of host cell nuclear and mitochondrial genes that control mitochondrial biogenesis, and we measured host mitochondrial metabolic fluxes. We found that host cell nuclear and mitochondrial genes that control mitochondrial biogenesis are upregulated in an LPG-dependent manner. We also observed that IRG-1, the enzyme that synthesizes itaconate, is highly induced during infection in an LPG-dependent manner and this response was independent of endosomal TLRs. We next found that L. donovani induces a doubling in the mtDNA/nDNA ratio in an endosomal TLRs and IFNAR-dependent manner, suggesting that L. donovani promotes host mitochondrial biogenesis in an inflammatory context. Metabolic flux analyzes showed that the OCR/ECAR ratio is modulated multiple times during infection, independently of β-oxidation, suggesing that L. donovani promastigotes induce the Warburg effect to promote energetic metabolic changes. Collectively, our data indicate that L. donovani alters host cell mitochondrial dynamics during the colonization process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".