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Antagonistic regulation of motility and transcriptome expression by RpoN and RpoS in <i>Escherichia coli</i>

2010· article· en· W1597786221 on OpenAlexafffund
Tao Dong, Rosemary Yu, Herb E. Schellhorn

Bibliographic record

VenueMolecular Microbiology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsrpoNrpoSBiologySigma factorGeneticsRegulonGeneGene expressionPromoter

Abstract

fetched live from OpenAlex

Bacteria generally possess multiple σ factors that, based on structural and functional similarity, divide into two families: σ(70) and σ(N) . Many studies have revealed σ factor competition within the σ(70) family, while the competition between σ(N) and σ(70) families has yet to be fully explored. Here we report a global antagonistic effect on gene expression between two alternative σ factors, σ(N) (RpoN) and a σ(70) family protein σ(S) (RpoS). Mutations in rpoS and rpoN were found to inversely affect a number of cellular traits, such as the expression of flagellar genes, σ(N) -controlled growth on poor nitrogen sources, and σ(S) -directed expression of acid phosphatase AppA. Transcriptome analysis reveals that about 60% of genes in the RpoN regulon are under reciprocal RpoS control. Furthermore, loss of RpoN led to increased levels of RpoS, while RpoN levels were unaffected by the rpoS mutation. Expression of the flagellar σ(F) factor (FliA), another σ(70) family protein, is controlled positively by RpoN but negatively by RpoS. This positive control by RpoN is likely mediated through the flagellar regulator FlhDC, whose expression is RpoN-dependent. These findings unveil a complex regulatory interaction among σ(N) , σ(S) and σ(F) , which modulates motility, nitrogen utilization, stress response and many other cellular functions.

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 score0.013
Threshold uncertainty score0.584

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 science0.0000.000
Research integrity0.0010.000
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 head0.003
GPT teacher head0.194
Teacher spread0.192 · 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
Published2010
Admission routes2
Has abstractyes

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