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Evaluating Signal Response of Wsc2p and Wsc3p Cell Wall Stress Sensors in Yeast

2015· article· en· W1592849142 on OpenAlexaboutno aff
Vladimir Vélez, Jeanmadi del Rosario, Nelson Martínez, Luis Vazquez‐Quinonez, José R Rodríguez-Medina

Bibliographic record

VenueThe FASEB Journal · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsnot available
FundersNational Institutes of HealthDelaware IDeA Network of Biomedical Research Excellence
KeywordsSaccharomyces cerevisiaeYeastInteractorCell biologyBudding yeastMutantSignal transductionCellBiologyHeat shockHeat shock proteinChemistryGeneBiochemistry

Abstract

fetched live from OpenAlex

In the budding yeast Saccharomyces cerevisiae , the WSC2 and WSC3 genes encode plasma membrane proteins with structural features of cell wall stress sensors involved in maintenance of cell integrity and recovery from heat shock. These sensors detect changes in environmental conditions and stresses on the cell wall and/or the plasma membrane and activate a downstream PKC1 ‐dependent cell wall integrity pathway (CWIP) with a central Mitogen Activated Protein (MAP) kinase Slt2/Mpk1 module. The objective of our research is to evaluate which interactor proteins, among those previously identified by an integrated membrane yeast two‐hybrid (iMYTH) assay, are shared between the sensors and if these contribute to CWIP activation. We hypothesize that some signaling functions of Wsc2p and Wsc3p in Saccharomyces cerevisiae require specific interactions with couplers of the PKC1 pathway. A functional interaction network diagram was generated to visualize these interactions. To reinforce our analysis we performed bioinformatic analysis in order to identify orthologous proteins for these interactors in other fungal species. Viability assays were performed on null mutant strains of the interactors under normal culture conditions and during exposure to cell wall stress conditions. Growth constants for all the deletion mutants were calculated and compared to the constants calculated for the wild type. This research was supported in part by the Univ. of Puerto Rico, Univ. of Toronto, Univ. of Kentucky, and NIH awards from RCMI‐G12MD007600, and INBRE 8 P20 GM103475.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.331
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes1
Has abstractyes

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