Secretion of an Argonaute protein by a parasitic nematode and the evolution of its siRNA guides
Bibliographic record
Abstract
Extracellular RNA has been proposed to mediate communication between cells and organisms however relatively little is understood regarding how specific sequences are selected for export. Here, we describe a specific Argonaute protein (exWAGO) that is secreted in extracellular vesicles (EVs) released by the gastrointestinal nematode Heligmosomoides bakeri, at multiple copies per EV. Phylogenetic and gene expression analyses demonstrate exWAGO orthologues are highly conserved and abundantly expressed in related parasites but highly diverged in free-living genus Caenorhabditis. We show that the most abundant small RNAs released from the nematode parasite are not microRNAs as previously thought, but rather secondary small interfering RNAs (siRNAs) that are produced by RNA-dependent RNA Polymerases. The siRNAs that are released in EVs have distinct evolutionary properties compared to those resident in free-living or parasitic nematodes. Immunoprecipitation of exWAGO demonstrates that it specifically associates with siRNAs from transposons and newly evolved repetitive elements that are packaged in EVs and released into the host environment. Together this work demonstrates molecular and evolutionary selectivity in the small RNA sequences that are released in EVs into the host environment and identifies a novel Argonaute protein as the mediator of this.
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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".