Assessing the Toxicity of Naphthenic Acids Using a Microbial Genome Wide Live Cell Reporter Array System
Bibliographic record
Abstract
Mixtures of naphthenic acids (NAs), which include cyclopentyl and cyclohexyl carboxylic acids, have been suggested to be toxic components in oils spills, effluents from the petrochemical industry and in oil sands process waters (OSPW). The present study demonstrated, for the first time, an application of a high throughput live bacterial cell array in a genome-scale investigation of the toxic mechanisms of environmental chemicals, a commercial NAs technical mixture extracted from crude oil. Real time gene profiling of time- and concentration- dependent responses of live cells exposed to NAs for three hours was conducted using a library of 1800 fluorescent transcriptional reporters for Escherichia coli (E. coli) growing in 384-well plates. The response patterns obtained after exposure to NAs suggested that the primary cellular responses were up-regulation of genes in the pentose phosphate pathway, involved in the molecular function of NADP or NADPH binding, and down-regulation of the ATP-binding cassette (ABC) transporter complex. Transcriptional networks that were significantly modulated by NAs included those that were regulated by transcriptional factors such as CRP-, RecA-, and GadE. Down-regulation of the SOS response pathway suggested that DNA damage might not be the direct result of NAs within the first three hours of exposure. However, CRP-dependent genes modulated by exposure to NAs indicated that the cellular level of cyclic AMP was altered immediately upon exposure of cells to NAs. Furthermore, the linear range of the concentration-response curve of the selected gene reporters encompassed a range of concentrations between 10 and 1000 mg NAs/L, which covers concentrations typically observed in the environment and makes this assay system ideal for the detection of environmental NAs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".