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Record W4213166923 · doi:10.1101/2022.02.14.480455

Diverse innate immune factors protect yeast from lethal viral pathogenesis

2022· preprint· en· W4213166923 on OpenAlexaff
Sabrina Chau, Jie Gao, Annette J. Diao, Shi Bo Cao, Amirahmad Azhieh, Alan R. Davidson, Marc D. Meneghini

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Interactions Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologySaccharomyces cerevisiaeYeastInnate immune systemVirologyRNARNA interferenceVirusGeneticsComputational biologyGeneImmune system

Abstract

fetched live from OpenAlex

Abstract In recent years, newly characterized anti-viral systems have proven to be remarkably conserved from bacteria to mammals, demonstrating that unique insights into these systems can be gained by studying microbial organisms. Despite the enthusiasm generated by these findings, the key microbial model organism Saccharomyces cerevisiae (budding yeast) has been minimally exploited for studies of viral defense, primarily because it is not infected with exogenously transmitted viruses. However, most yeast strains are infected with an endogenous double stranded RNA (dsRNA) virus called L-A, and previous studies identified conserved antiviral systems that attenuate L-A replication. Although these systems do not completely eradicate L-A, we show here that they do prevent proteostatic stress and lethality caused by L-A over-proliferation. Exploiting this new finding, we demonstrate that the genetic screening methods available in yeast can be used to identify additional conserved antiviral systems. Using these approaches, we discovered 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. We also identified new antiviral functions for the RNA exonucleases REX2 and MYG1 , both of which have distinct but poorly characterized human and bacterial homologs. These findings highlight the potential of yeast as a powerful model system for the discovery and characterization of conserved antiviral systems. Significance Statement The budding yeast Saccharomyces cerevisiae has been minimally exploited for investigation of host-virus interactions despite its chronic infection with a double-stranded RNA virus called L-A. Controverting its presumed harmless nature, we show here that L-A causes pathogenesis in cells lacking parallel-acting viral attenuation pathways. Taking advantage of the genetic tools available in budding yeast, we identify several highly conserved proteins to play a role in antiviral defense. Some of these have been recently identified in humans to be involved in viral innate immunity, thus highlighting the potential of budding yeast as a model organism to identify and investigate new antiviral systems.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.246
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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