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Record W4289667118 · doi:10.1139/cjm-2022-0120

A mutation in the putative CRP binding site of the <i>dctA</i> promoter of <i>Salmonella enterica</i> serovar Typhimurium enables growth with low orotate concentrations

2022· article· en· W4289667118 on OpenAlexafffundvenue
Mohammad Ruhul Amin, Lisa Korchinski, Joshua K. Yoneda, Rishi Thakkar, Carla L.A. Sanson, Stephen Fitzgerald, Rod A. Kelln, Andrew D. S. Cameron

Bibliographic record

VenueCanadian Journal of Microbiology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSalmonella entericaMutantAuxotrophyBiologyEscherichia coliBiochemistryWild typeMutationMolecular biologyGene

Abstract

fetched live from OpenAlex

Salmonella enterica and Escherichia coli use the inner membrane transporter DctA to import the pyrimidine biosynthetic pathway intermediate orotate from the environment. To study the regulation of dctA expression, we used an S. enterica serovar Typhimurium pyrimidine auxotroph to select a mutant that could grow in an otherwise nonpermissive culture medium containing glucose and a low concentration of orotate. Whole genome sequencing revealed a point mutation upstream of dctA in the putative cyclic AMP receptor protein (CRP) binding site. The C→T transition converted the least favourable base to the most favourable base for CRP–DNA affinity. A dctA::lux transcriptional fusion confirmed that the mutant dctA promoter gained responsiveness to CRP even in the presence of glucose. Moreover, dctA expression was higher in the mutant than the wild type in the presence of alternative carbon sources that activate CRP.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.177
Teacher spread0.173 · 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 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

Citations4
Published2022
Admission routes3
Has abstractyes

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Same venueCanadian Journal of MicrobiologySame topicBacterial Genetics and BiotechnologyFrench-language works237,207