A Novel Selenite- and Tellurite-Inducible Gene in <i>Escherichia coli</i>
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".