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Regulation of alkaline metalloprotease promoter by N-acyl homoserine lactone quorum sensing in Pseudomonas fluorescens

2007· article· en· W1488370331 on OpenAlexafffund
Mei Liu, H. Wang, Mansel W. Griffiths

Bibliographic record

VenueJournal of Applied Microbiology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of Guelph
FundersDairy Farmers of OntarioUniversity of Guelph
KeywordsPseudomonas fluorescensQuorum sensingHomoserineBiochemistryMicrobiologyBiologyBacteriaChemistryGeneVirulenceGenetics

Abstract

fetched live from OpenAlex

AIMS: To examine the involvement of N-acyl homoserine lactone (AHL) quorum sensing in alkaline metalloprotease (aprX) promoter regulation in a Pseudomonas fluorescens milk isolate. METHODS AND RESULTS: N-acyl homoserine lactone signals from P. fluorescens strain 395 were separated and detected by thin layer chromatography (TLC). Further analysis of the AHL signals using liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) indicated the presence of C4-HSL and 3OC8-HSL. The expression of aprX in P. fluorescens 395 was investigated, using a transcriptional fusion between the aprX promoter and a mutated gfp variant gene (gfp[mut3]). The results demonstrated that the activity of the aprX promoter increased dramatically in the late exponential phase of growth, indicating growth phase-dependent regulation. The activity was repressed in an AHL-deficient environment, in which the signal molecules were hydrolysed by the enzyme AHL lactonase. CONCLUSIONS: N-acyl homoserine lactones produced by P. fluorescens 395 were identified to be C4-HSL and 3OC8-HSL. The protease gene in P. fluorescens is regulated by the AHL-based quorum sensing system at a transcriptional level during the late exponential growth phase. SIGNIFICANCE AND IMPACT OF THE STUDY: This study contributes to our understanding of the genetic regulation and ecology of P. fluorescens in the economically important system of food spoilage.

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)0.001
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 score0.016
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.219
Teacher spread0.214 · 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

Citations85
Published2007
Admission routes2
Has abstractyes

Explore more

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