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Record W2064308123 · doi:10.1074/jbc.m110.179150

Temperature and Mg2+ Sensing by a Novel PhoP-PhoQ Two-component System for Regulation of Virulence in Edwardsiella tarda

2010· article· en· W2064308123 on OpenAlexaff
Smarajit Chakraborty, Mo Li, Chiradip Chatterjee, J. Sivaraman, Ka Yin Leung, Yu‐Keung Mok

Bibliographic record

VenueJournal of Biological Chemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsTrinity Western UniversityWestern University
Fundersnot available
KeywordsEdwardsiella tardaVirulenceSecretionChemistryBacteriaMicrobiologyBiochemistryBiologyGene

Abstract

fetched live from OpenAlex

The PhoP-PhoQ two-component system is commonly used by bacteria to sense environmental factors. Here we show that the PhoP-PhoQ system of Edwardsiella tarda detects changes in environmental temperature and Mg(2+) concentration as well as regulates the type III and VI secretion systems through direct activation of esrB. Protein secretion is activated from 23 to 35 °C or at low Mg(2+) concentrations, but it is suppressed at or below 20 °C, at or above 37 °C, or at high Mg(2+) concentrations. The effects of temperature and Mg(2+) concentration are additive. The PhoQ sensor domain has a low T(m) of 37.9 °C, and it detects temperatures through a conformational change of its secondary structure. Mutation of specific Pro or Thr residues increased the stability of the PhoQ sensor drastically, altering its temperature-sensing ability. The PhoQ sensor detects Mg(2+) concentration through the direct binding of Mg(2+) to a cluster of acidic residues (DDDSAD) and through changes that likely affect its tertiary structure. Here, we describe for the first time the use of PhoP-PhoQ as a temperature sensor for bacterial virulence control.

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 score0.004
Threshold uncertainty score0.365

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 integrity0.0000.000
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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

Citations82
Published2010
Admission routes1
Has abstractyes

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