Rapid evaluation of the substrate specificity of 3-nitrobenzoic acid dioxygenase MnbAB via colorimetric detection using Saltzman reagent
Bibliographic record
Abstract
Nitroaromatic compounds are essential materials for chemical industry, but they are also potentially toxic environmental pollutants. Therefore, their sensitive detection and degradation are important concerns. The microbial degradation pathways of nitroaromatic compounds have been studied in detail, but their usefulness needs to be evaluated to understand their potential applications in bioremediation. Here, we developed a rapid and relatively sensitive assay system to evaluate the activities and substrate specificities of nitroaromatic dioxygenases involved in the oxidative biodegradation of nitroaromatic compounds. In this system, nitrous acid, which was released from the nitroaromatic compounds by the dioxygenases, was detected and quantified using the Saltzman reagent. Escherichia coli producing the 3-nitrobenzoic acid dioxygenase complex MnbAB from Comamonas sp. JS46 clearly showed the apparent substrate specificity of MnbAB as follows. MnbAB accepted not only 3-nitrobenzoic acid but also several other p- and m-nitrobenzoic acid derivatives as substrates, although it much preferred 3-nitrobenzoic acid to others. Furthermore, the presence of a hydroxy or an amino group at the ortho position of the nitro group decreased the activity of MnbAB. In addition, MnbAB accepted 2-(4-nitrophenyl)acetic acid as a substrate, which has one additional methylene group between the aromatic ring and the carboxy group of 3-nitrobenzoic acid. This is the first report about the detailed substrate specificity of MnbAB. Our system can be used for other nitroaromatic dioxygenases and contribute to their characterization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".