MétaCan
Menu
Back to cohort

A Novel Selenite- and Tellurite-Inducible Gene in <i>Escherichia coli</i>

2000· article· en· W2031862092 on OpenAlexafffund
Julie Guzzo, Michael S. DuBow

Bibliographic record

VenueApplied and Environmental Microbiology · 2000
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEscherichia coliSeleniumEscherichia coli ProteinsGeneBiologyMicrobiologyGeneticsComputational biologyChemistry

Abstract

fetched live from OpenAlex

Selenium is both an essential and a toxic trace element, and the range of concentrations between the two is extremely narrow. Although tellurium is not essential and is only rarely found in the environment, it is considered to be extremely toxic. Several hypotheses have been proposed to account for the toxic effects of selenite and tellurite. However, these potential mechanisms have yet to be fully substantiated. Through screening of an Escherichia coli luxAB transcriptional gene fusion library, we identified a clone whose luminescence increased in the presence of increasing concentrations of sodium selenite or sodium tellurite. Cloning and sequencing of the luxAB junction revealed that the fusion had occurred in a previously uncharacterized open reading frame, termed o393 or yhfC, which we have now designated gutS, for gene up-regulated by tellurite and selenite. Transcription from gutS in the presence of selenite or tellurite was confirmed by RNA dot blot analysis. In vivo expression of the GutS polypeptide, using the pET expression system, revealed a polypeptide of approximately 43 kDa, in good agreement with its predicted molecular mass. Although the function of GutS remains to be elucidated, homology searches as well as protein motif and secondary-structure analyses have provided clues which may implicate GutS in transport in response to selenite and tellurite.

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 score0.203
Threshold uncertainty score0.764

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 head0.008
GPT teacher head0.185
Teacher spread0.177 · 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

Citations42
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueApplied and Environmental MicrobiologySame topicSelenium in Biological SystemsFrench-language works237,207