Characterization of Argonaute-containing protein complexes in Leishmania-infected human macrophages
Bibliographic record
Abstract
The intracellular protozoan parasite Leishmania causes leishmaniasis in humans, leading to serious illness and death in tropical and subtropical areas worldwide. Unfortunately, due to the unavailability of approved vaccines for humans and the limited efficacy of available drugs, leishmaniasis is on the rise. A comprehensive understanding of host-pathogen interactions at the molecular level could pave the way to counter leishmaniasis. There is growing evidence that several intracellular pathogens target RNA interference (RNAi) pathways in host cells to facilitate their persistence. The core elements of the RNAi system are complexes of Argonaute (Ago) proteins with small non-coding RNAs, also known as RNA-induced silencing complexes (RISCs). Recently, we have shown that Leishmania modulates Ago1 protein of host macrophages for its survival. In this study, we biochemically characterize the Ago proteins' interactome in Leishmania-infected macrophages compared to non-infected cells. For this, a quantitative proteomic approach using stable isotope labelling by amino acids in cell culture (SILAC) was employed, followed by purification of host Ago-complexes using a short TNRC6 protein-derived peptide fused to glutathione S-transferase beads as an affinity matrix. Proteomic-based detailed biochemical analysis revealed Leishmania modulated host macrophage RISC composition during infection. This analysis identified 51 Ago-interacting proteins with a broad range of biological activities. Strikingly, Leishmania proteins were detected as part of host Ago-containing complexes in infected cells. Our results present the first report of comprehensive quantitative proteomics of Ago-containing complexes isolated from Leishmania-infected macrophages and suggest targeting the effector complex of host RNAi machinery. Additionally, these results expand knowledge of RISC in the context of host-pathogen interactions in parasitology in general.
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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) | 0.000 | 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".