Leishmania infection upregulates and engages host macrophage Argonaute 1, and system-wide proteomics reveals Argonaute 1-dependent host response
Bibliographic record
Abstract
Leishmania donovani , an intracellular protozoan parasite, is the causative agent of visceral leishmaniasis, the most severe form of leishmaniasis in humans. It is becoming increasingly clear that several intracellular pathogens target host cell RNA interference (RNAi) pathways to promote their survival. Complexes of Argonaute proteins with small RNAs are core components of the RNAi. In this study, we investigated the potential role of host macrophage Argonautes in Leishmania pathogenesis. Using Western blot analysis of Leishmania donovani -infected macrophages, we show here that Leishmania infection selectively increased the abundance of host Argonaute 1 (Ago1). This increased abundance of Ago1 in infected cells also resulted in higher levels of Ago1 in active Ago-complexes, suggesting the preferred use of Ago1 in RNAi in Leishmania -infected cells. This analysis used a short trinucleotide repeat containing 6 (TNRC6)/glycine-tryptophan repeat protein (GW182) protein-derived peptide fused to Glutathione S-transferase as an affinity matrix to capture mature Ago-small RNAs complexes from the cytosol of non-infected and Leishmania -infected cells. Furthermore, Ago1 silencing significantly reduced intracellular survival of Leishmania , demonstrating that Ago1 is essential for Leishmania pathogenesis. To investigate the role of host Ago1 in Leishmania pathogenesis, a quantitative whole proteome approach was employed, which showed that expression of several previously reported Leishmania pathogenesis-related proteins was dependent on the level of macrophage Ago1. Together, these findings identify Ago1 as the preferred Argonaute of RNAi machinery in infected cells and a novel and essential virulence factor by proxy that promotes Leishmania survival.
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 | 0.001 |
| 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".