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Record W2561828864 · doi:10.1128/msystems.00102-16

Transcriptional Profiling of the Oral Pathogen Streptococcus mutans in Response to Competence Signaling Peptide XIP

2017· article· en· W2561828864 on OpenAlexafffund
Iwona B. Wenderska, Andrew Latos, Benjamin W. Pruitt, Sara R. Palmer, Grace Spatafora, Dilani B. Senadheera, Dennis G. Cvitkovitch

Bibliographic record

VenuemSystems · 2017
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversity of Toronto
FundersNational Institute of Dental and Craniofacial ResearchCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyStreptococcus gordoniiStreptococcus mutansTranscriptomeGeneRegulation of gene expressionGene expressionGene expression profilingCell biologyGeneticsBiofilmBacteria

Abstract

fetched live from OpenAlex

Genetic competence provides bacteria with an opportunity to increase genetic diversity or acquire novel traits conferring a survival advantage. In the cariogenic pathogen Streptococcus mutans , DNA transformation is regulated by the competence stimulating peptide XIP (Com X - i nducing p eptide). The present study utilizes high-throughput RNA sequencing (RNAseq) to provide a greater understanding of how global gene expression patterns change in response to XIP. Overall, our work demonstrates that in S. mutans , XIP signaling induces a response that resembles the stringent response to amino acid starvation. We further identify a novel heat shock-responsive intergenic region with a potential role in competence shutoff. Together, our results provide further evidence that multiple stress response mechanisms are linked through the genetic competence signaling pathway in S. mutans .

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.044
GPT teacher head0.325
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2017
Admission routes2
Has abstractyes

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