Glutathione is a target in tellurite toxicity and is protected by tellurite resistance determinants in<i>Escherichia coli</i>
Bibliographic record
Abstract
Tellurite (TeO32-) is highly toxic to most microorganisms. The mechanisms of toxicity or resistance are poorly understood. It has been shown that tellurite rapidly depletes the reduced thiol content within wild-type Escherichia coli. We have shown that the presence of plasmid-borne tellurite-resistance determinants protects against general thiol oxidation by tellurite. In the present study we observe that the tellurite-dependent depletion of cellular thiols in mutants of the glutathione and thioredoxin thiol:redox system was less than in wild-type cells. To identify the type of low-molecular-weight thiol compounds affected by tellurite exposure, the thiol-containing molecules were analyzed by reverse phase HPLC as their monobromobimane derivatives. Results indicated that reduced glutathione is a major initial target of tellurite reactivity within the cell. Other thiol species are also targeted by tellurite, including reduced coenzyme A. The presence of the tellurite resistance determinants kilA and ter protect against the loss of reduced glutathione by as much as 60% over a 2 h exposure. This protection of glutathione oxidation is likely key to the resistance mechanism of these determinants. Additionally, the thiol oxidation response curves were compared between selenite and tellurite. The loss of thiol compounds within the cell recovered from selenite but not to tellurite.Key words: tellurite, resistance, thiol oxidation, heavy metal toxicity, selenite, glutathione.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".