Functional Characterization of Reductive Dehalogenases by Using Blue Native Polyacrylamide Gel Electrophoresis
Bibliographic record
Abstract
Dehalococcoides mccartyi strains are obligate organohalide-respiring bacteria harboring multiple distinct reductive dehalogenase (RDase) genes within their genomes. A major challenge is to identify substrates for the enzymes encoded by these RDase genes. We demonstrate an approach that involves blue native polyacrylamide gel electrophoresis (BN-PAGE) followed by enzyme activity assays with gel slices and subsequent identification of proteins in gel slices using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). RDase expression was investigated in cultures of Dehalococcoides mccartyi strain BAV1 and in the KB-1 consortium growing on chlorinated ethenes and 1,2-dichloroethane. In cultures of strain BAV1, BvcA was the only RDase detected, revealing that this enzyme catalyzes the dechlorination not only of vinyl chloride, but also of all dichloroethene isomers and 1,2-dichloroethane. In cultures of consortium KB-1, five distinct Dehalococcoides RDases and one Geobacter RDase were expressed under the conditions tested. Three of the five RDases included orthologs to the previously identified chlorinated ethene-dechlorinating enzymes VcrA, BvcA, and TceA. This study revealed substrate promiscuity for these three enzymes and provides a path forward to further explore the largely unknown RDase protein family.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".