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Record W2138307476 · doi:10.1128/jb.01086-07

Autoinducer-2-Regulated Genes in<i>Streptococcus mutans</i>UA159 and Global Metabolic Effect of the<i>luxS</i>Mutation

2007· article· en· W2138307476 on OpenAlexaff
Helena Sztajer, André Lemme, Ramiro Vilchez‐Vargas, Stefan Schulz, Robert Geffers, Cindy Ying Yin Yip, Céline M. Lévesque, Dennis G. Cvitkovitch, Irene Wagner‐Döbler

Bibliographic record

VenueJournal of Bacteriology · 2007
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQuorum sensingBiologyMutantAutoinducerStreptococcus mutansBiofilmHomoserineGeneBiochemistryGeneticsCell biologyMicrobiologyBacteria

Abstract

fetched live from OpenAlex

Autoinducer 2 (AI-2) is the only species-nonspecific autoinducer known in bacteria and is produced by both gram-negative and gram-positive organisms. Consequently, it is proposed to function as a universal quorum-sensing signal for interaction between bacterial species. AI-2 is produced as the by-product of a metabolic transformation carried out by the LuxS enzyme. To separate the metabolic function of the LuxS enzyme from the signaling role of AI-2, we carried out a global transcriptome analysis of a luxS null mutant culture of Streptococcus mutans UA159, an important cariogenic bacterium and a crucial component of the dental plaque biofilm community, in comparison to a luxS null mutant culture supplemented with chemically pure 4,5-dihydroxy-2,3-pentanedione, the precursor of AI-2. The data revealed fundamental changes in gene expression affecting 585 genes (30% of the genome) which could not be restored by the signal molecule AI-2 and are therefore not caused by quorum sensing but by lack of the transformation carried out by the LuxS enzyme in the activated methyl cycle. All functional classes of enzymes were affected, including genes known to be important for biofilm formation, bacteriocin synthesis, competence, and acid tolerance. At the same time, 59 genes were identified whose transcription clearly responded to the addition of AI-2. Some of them were related to protein synthesis, stress, and cell division. Three membrane transport proteins were upregulated which are not related to any of the known AI-2 transporters. Three transcription factors were identified whose transcription was stimulated repeatedly by AI-2 addition during growth. Finally, a global regulatory protein, the delta subunit of the RNA polymerase (rpoE), was induced 147-fold by AI-2, representing the largest differential gene expression observed. The data show that many phenotypes related to the luxS mutation cannot be ascribed to quorum sensing and have identified for the first time regulatory proteins potentially mediating AI-2-based signaling in gram-positive bacteria.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.299
Teacher spread0.289 · 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 designObservational
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

Citations127
Published2007
Admission routes1
Has abstractyes

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