Design and Characterization of an Aequorin‐based Bacterial Biosensor for Detection of Toluene and Related Compounds
Bibliographic record
Abstract
An aequorin-based Escherichia coli strain JM109 biosensor was constructed and characterized for its potential to detect toluene and related compounds in aqueous solutions. The biosensor was constructed based on a PGL2 plasmid carrying the lower pathway promoter (Pu) of the xyl operon of Pseudomonas putida mt-2, which was incorporated with transcriptional activator xylR and fused to aequorin cDNA named pGL2-aequorin. Binding of xylR protein to a subset of toluene-like compounds activates transcription at the Pu promoter, thus expression of aequorin is controlled by xylR and Pu. In this work we have compared the effect of Shine-Dalgarno (SD) and T2 rrnβ terminator sequence in the expression of aequorin. According to the sensitivity of aequorin and increase in the signal-to-noise ratio, this reporter enzyme has reasonable sensitivity compared with other reporter systems. The results indicate higher expression of aequorin in the presence of SD and T2 rrnβ. The activity of aequorin in recombinant whole-cell biosensor was linear from 1 to 500 μm of toluene. The bioluminescence response was specific for toluene-like molecules, so this biosensor cells would be able to detect toluene derivative contamination in environmental samples, accurately.
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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) | 0.000 | 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) | 0.000 | 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".