Leishmania Exosomes Deliver Preemptive Strikes to Create an Environment Permissive for Early Infection
Bibliographic record
Abstract
Herein, we review evidence supporting a role for Leishmania exosomes during early infection. We suggest a model in which Leishmania secreted microvesicles released into the extracellular milieu deliver effector cargo to host target cells. This cargo mediates immunosuppression and functionally primes host cells for Leishmania invasion. Leishmania ssp. release microvesicles and the amount of vesicle release and the specific protein cargo of the vesicles is sensitive to changes in environmental conditions that mimic infection. Leishmania exosomes influence the phenotype of treated immune cells. For example, wild-type (WT) exosomes attenuate interferon-γ-induced pro-inflammatory cytokine production (TNF-α) by Leishmania-infected monocytes while conversely enhancing production of the anti-inflammatory cytokine IL-10. The Leishmania proteins GP63 and elongation factor-1α (EF-1α) are found in secreted vesicles and are likely important effectors responsible for these changes in phenotype. GP63 and EF-1α access host cell cytosol and activate multiple host protein-tyrosine phosphatases (PTPs). Activation of these PTPs negatively regulates interferon-γ signaling and this prevents effective expression of the macrophage microbicidal arsenal, including TNF-α and nitric oxide. In addition to changing macrophage phenotype, WT vesicles dampen the immune response of monocyte-derived dendritic cells and CD4+ T lymphocytes. This capacity is lost when the protein cargo of the vesicles is modified, specifically when the amount of GP63 and EF-1α in the vesicles is reduced. It appears that exosome delivery of effector proteins results in activation of host PTPs and the negative regulatory effects of the latter creates a pro-parasitic environment. The data suggest that Leishmania exosomes secreted upon initial infection are capable of delivering effector cargo to naïve target cells wherein the cargo primes host cells for infection by interfering with host cell signaling pathways.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".