Identification of <i>Dehalobacter</i> reductive dehalogenases that catalyse dechlorination of chloroform, 1,1,1-trichloroethane and 1,1-dichloroethane
Bibliographic record
Abstract
Two novel reductive dehalogenases (RDases) that are highly similar to each other but catalyse distinct dechlorination reactions were identified from Dehalobacter-containing mixed cultures. These two RDases were partially purified from crude protein extracts of anaerobic dechlorinating enrichment cultures using blue native polyacrylamide gel electrophoresis. Gel slices were assayed for dechlorinating activity, and associated proteins were identified using liquid chromatography tandem mass spectrometry with the metagenome of the parent culture as the reference database. The two RDases identified, annotated as CfrA and DcrA, share an amino acid identity of 95.2 per cent, but use different substrates: CfrA dechlorinates chloroform (CF) and 1,1,1-trichloroethane (1,1,1-TCA), but not 1,1-dichloroethane; DcrA dechlorinates 1,1-dichloroethane, but not CF or 1,1,1-TCA. These two novel RDases share no more than 40 per cent amino acid identity to any other known or putative RDases, but both have a twin-arginine motif and two iron-sulfur binding motifs conserved in most RDases. Peptides specific to two putative membrane anchor proteins, annotated as CfrB and DcrB, were also detected in gel slices.
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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) | 0.000 | 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 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".