Metabolomics reveals differences of metal toxicity in cultures of Pseudomonas pseudoalcaligenes KF707 grown on different carbon sources
Bibliographic record
Abstract
Co-contamination of metals and organic pollutants is a global problem as metals interfere with the metabolism of complex organics by bacteria. Based on a prior observation that metal tolerance was altered by the sole carbon source being used for growth, we sought to understand how metal toxicity specifically affects bacteria using an organic pollutant as their sole carbon source. To this end metabolomics was used to compare cultures of Pseudomonas pseudoalcaligenes KF707 grown on either biphenyl (Bp) or succinate (Sc) as the sole carbon source in the presence of either aluminum (Al) or copper (Cu). Using multivariate statistical analysis it was found that the metals caused perturbations to more cellular processes in the cultures grown on Bp than those grown on Sc. Al induced many changes that were indicative of increased oxidative stress as metabolites involved in DNA damage and protection, the Krebs cycle and anti-oxidant production were altered. Cu also caused metabolic changes that were indicative of similar stress, as well as appearing to disrupt other key enzymes such as fumarase. Additionally, both metals caused the accumulation of Bp degradation intermediates indicating that they interfered with Bp metabolism. Together these results provide a basic understanding of how metal toxicity specifically affects bacteria at a biochemical level during the degradation of an organic pollutant and implicate the catabolism of this carbon source as a major factor that exacerbates metal toxicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".