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Record W2980768728 · doi:10.1101/807917

(p)ppGpp directly regulates translation initiation during entry into quiescence

2019· preprint· en· W2980768728 on OpenAlexaff
Simon Diez, Jae-Wook Ryu, Kelvin Caban, Ruben L. Gonzalez, Jonathan Dworkin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsColumbia College
FundersNational Institutes of Health
KeywordsProtein biosynthesisGTP'Translation (biology)Stringent responseCell biologyBacillus subtilisAllosteric regulationGTPaseDownregulation and upregulationIn vivoBiologyChemistryBiochemistryBacteriaEnzymeMessenger RNAGeneEscherichia coliGenetics

Abstract

fetched live from OpenAlex

Summary Many bacteria exist in a state of metabolic quiescence where they must minimize energy consumption so as to maximize available resources over a potentially extended period of time. As protein synthesis is the most energy intensive metabolic process in a bacterial cell, it would be an appropriate target for downregulation during the transition from growth to quiescence. We find that when Bacillus subtilis exits growth, a subpopulation of cells emerges with very low levels of protein synthesis dependent on synthesis of the nucleotides (p)ppGpp. We show that (p)ppGpp inhibits protein synthesis in vivo and in vitro by preventing the allosteric activation of the essential GTPase Initiation Factor 2 (IF2) during translation initiation. Finally, we demonstrate that IF2 is an authentic in vivo target of (p)ppGpp during the entry into quiescence, thus providing a mechanistic basis for the observed attenuation of protein synthesis.

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 score0.001
Threshold uncertainty score0.003

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 head0.008
GPT teacher head0.206
Teacher spread0.197 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicBacterial Genetics and BiotechnologyFrench-language works237,207