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Record W2023177772 · doi:10.1128/aem.03132-14

A Regulatory Feedback Loop between RpoS and SpoT Supports the Survival of Legionella pneumophila in Water

2014· article· en· W2023177772 on OpenAlexaff
Hana Trigui, Paulina Dudyk, Jinrok Oh, Jong‐In Hong, Sébastien P. Faucher

Bibliographic record

VenueApplied and Environmental Microbiology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsMcGill University
Fundersnot available
KeywordsrpoSSigma factorMutantLegionella pneumophilaBiologyLegionellaMicrobiologyViable but nonculturableWild typeGeneticsCell biologyGeneBacteriaGene expressionPromoter

Abstract

fetched live from OpenAlex

Legionella pneumophila is a waterborne pathogen, and survival in the aquatic environment is central to its transmission to humans. Therefore, identifying genes required for its survival in water could help prevent Legionnaires' disease outbreaks. In the present study, we investigate the role of the sigma factor RpoS in promoting survival in water, where L. pneumophila experiences severe nutrient deprivation. The rpoS mutant showed a strong survival defect compared to the wild-type strain in defined water medium. The transcriptome of the rpoS mutant during exposure to water revealed that RpoS represses genes associated with replication, translation, and transcription, suggesting that the mutant fails to shut down major metabolic programs. In addition, the rpoS mutant is transcriptionally more active than the wild-type strain after water exposure. This could be explained by a misregulation of the stringent response in the rpoS mutant. Indeed, the rpoS mutant shows an increased expression of spoT and a corresponding decrease in the level of (p)ppGpp, which is due to the presence of a negative feedback loop between RpoS and SpoT. Therefore, the lack of RpoS causes an aberrant regulation of the stringent response, which prevents the induction of a successful response to starvation.

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 score0.073
Threshold uncertainty score0.345

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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

Citations39
Published2014
Admission routes1
Has abstractyes

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