MétaCan
Menu
Back to cohort
Record W2053389510 · doi:10.1371/journal.pgen.1002353

Multiple Means to the Same End: The Genetic Basis of Acquired Stress Resistance in Yeast

2011· article· en· W2053389510 on OpenAlexafffund
David B. Berry, Qiaoning Guan, James Hose, Suraiya Haroon, Marinella Gebbia, Lawrence E. Heisler, Corey Nislow, Guri Giaever, Audrey P. Gasch

Bibliographic record

VenuePLoS Genetics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Human Genome Research InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyGeneContext (archaeology)YeastGeneticsComputational biology

Abstract

fetched live from OpenAlex

In nature, stressful environments often occur in combination or close succession, and thus the ability to prepare for impending stress likely provides a significant fitness advantage. Organisms exposed to a mild dose of stress can become tolerant to what would otherwise be a lethal dose of subsequent stress; however, the mechanism of this acquired stress tolerance is poorly understood. To explore this, we exposed the yeast gene-deletion libraries, which interrogate all essential and non-essential genes, to successive stress treatments and identified genes necessary for acquiring subsequent stress resistance. Cells were exposed to one of three different mild stress pretreatments (salt, DTT, or heat shock) and then challenged with a severe dose of hydrogen peroxide (H(2)O(2)). Surprisingly, there was little overlap in the genes required for acquisition of H(2)O(2) tolerance after different mild-stress pretreatments, revealing distinct mechanisms of surviving H(2)O(2) in each case. Integrative network analysis of these results with respect to protein-protein interactions, synthetic-genetic interactions, and functional annotations identified many processes not previously linked to H(2)O(2) tolerance. We tested and present several models that explain the lack of overlap in genes required for H(2)O(2) tolerance after each of the three pretreatments. Together, this work shows that acquired tolerance to the same severe stress occurs by different mechanisms depending on prior cellular experiences, underscoring the context-dependent nature of stress tolerance.

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 categoriesnone
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 score0.170
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.207
Teacher spread0.189 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations121
Published2011
Admission routes2
Has abstractyes

Explore more

Same venuePLoS GeneticsSame topicBioinformatics and Genomic NetworksFrench-language works237,207