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Record W2161594264 · doi:10.1101/gad.1228804

A dynamic transcriptional network communicates growth potential to ribosome synthesis and critical cell size

2004· article· en· W2161594264 on OpenAlexafffund
Paul Jorgensen, Ivan Rupeš, Jeffrey R. Sharom, Lisa Schneper, James R. Broach, Mike Tyers

Bibliographic record

VenueGenes & Development · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsRibosome biogenesisBiologyCell biologyRegulonSaccharomyces cerevisiaeRibosomeProtein biosynthesisRibosomal proteinCell cycleCell growthTranscription factorGeneGeneticsRNA

Abstract

fetched live from OpenAlex

Cell-size homeostasis entails a fundamental balance between growth and division. The budding yeast Saccharomyces cerevisiae establishes this balance by enforcing growth to a critical cell size prior to cell cycle commitment (Start) in late G1 phase. Nutrients modulate the critical size threshold, such that cells are large in rich medium and small in poor medium. Here, we show that two potent negative regulators of Start, Sfp1 and Sch9, are activators of the ribosomal protein (RP) and ribosome biogenesis (Ribi) regulons, the transcriptional programs that dictate ribosome synthesis rate in accord with environmental and intracellular conditions. Sfp1 and Sch9 are required for carbon-source modulation of cell size and are regulated at the level of nuclear localization and abundance, respectively. Sfp1 nuclear concentration responds rapidly to nutrient and stress conditions and is regulated by the Ras/PKA and TOR signaling pathways. In turn, Sfp1 influences the nuclear localization of Fhl1 and Ifh1, which bind to RP gene promoters. Starvation or the absence of Sfp1 causes Fhl1 and Ifh1 to localize to nucleolar regions, concomitant with reduced RP gene transcription. These findings suggest that nutrient signals set the critical cell-size threshold via Sfp1 and Sch9-mediated control of ribosome biosynthetic rates.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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 designObservational
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

Citations645
Published2004
Admission routes2
Has abstractyes

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