Proteomic analysis of the secretome of Leishmania donovani
Bibliographic record
Abstract
BACKGROUND: Leishmania and other intracellular pathogens have evolved strategies that support invasion and persistence within host target cells. In some cases the underlying mechanisms involve the export of virulence factors into the host cell cytosol. Previous work from our laboratory identified one such candidate leishmania effector, namely elongation factor-1alpha, to be present in conditioned medium of infectious leishmania as well as within macrophage cytosol after infection. To investigate secretion of potential effectors more broadly, we used quantitative mass spectrometry to analyze the protein content of conditioned medium collected from cultures of stationary-phase promastigotes of Leishmania donovani, an agent of visceral leishmaniasis. RESULTS: Analysis of leishmania conditioned medium resulted in the identification of 151 proteins apparently secreted by L. donovani. Ratios reflecting the relative amounts of each leishmania protein secreted, as compared to that remaining cell associated, revealed a hierarchy of protein secretion, with some proteins secreted to a greater extent than others. Comparison with an in silico approach defining proteins potentially exported along the classic eukaryotic secretion pathway suggested that few leishmania proteins are targeted for export using a classic eukaryotic amino-terminal secretion signal peptide. Unexpectedly, a large majority of known eukaryotic exosomal proteins was detected in leishmania conditioned medium, suggesting a vesicle-based secretion system. CONCLUSION: This analysis shows that protein secretion by L. donovani is a heterogeneous process that is unlikely to be determined by a classical amino-terminal secretion signal. As an alternative, L. donovani appears to use multiple nonclassical secretion pathways, including the release of exosome-like microvesicles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".