Diverse yeast antiviral systems prevent lethal pathogenesis caused by the L-A mycovirus
Bibliographic record
Abstract
Recent studies show that antiviral systems are remarkably conserved from bacteria to mammals, demonstrating that unique insights into these systems can be gained by studying microbial organisms. Unlike in bacteria, however, where phage infection can be lethal, no cytotoxic viral consequence is known in the budding yeast Saccharomyces cerevisiae even though it is chronically infected with a double-stranded RNA mycovirus called L-A. This remains the case despite the previous identification of conserved antiviral systems that limit L-A replication. Here, we show that these systems collaborate to prevent rampant L-A replication, which causes lethality in cells grown at high temperature. Exploiting this discovery, we use an overexpression screen to identify antiviral functions for the yeast homologs of polyA-binding protein (PABPC1) and the La-domain containing protein Larp1, which are both involved in viral innate immunity in humans. Using a complementary loss of function approach, we identify new antiviral functions for the conserved RNA exonucleases REX2 and MYG1 ; the SAGA and PAF1 chromatin regulatory complexes; and HSF1 , the master transcriptional regulator of the proteostatic stress response. Through investigation of these antiviral systems, we show that L-A pathogenesis is associated with an activated proteostatic stress response and the accumulation of cytotoxic protein aggregates. These findings identify proteotoxic stress as an underlying cause of L-A pathogenesis and further advance yeast as a powerful model system for the discovery and characterization of conserved antiviral systems.
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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) | 0.001 | 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".