A switch of chlorinated substrate causes emergence of a previously undetected native Dehalobacter population in an established Dehalococcoides-dominated chloroethene-dechlorinating enrichment culture
Bibliographic record
Abstract
Chlorobenzenes are soil and groundwater pollutants of concern that can be reductively dehalogenated by organohalide-respiring bacteria from the genera Dehalococcoides and Dehalobacter. The bioaugmentation culture KB-1® harbours Dehalococcoides mccartyi spp. that reductively dehalogenate trichloroethene to ethene. It contains more than 30 reductive dehalogenase genes; some of them are highly similar to genes found in the chlorobenzene-respiring Dehalococcoides mccartyi strain CBDB1. We explored the chlorobenzene dehalogenation capability of the KB-1 enrichment culture using 1,2,4-trichlorobenzene (1,2,4-TCB). We achieved adaptation of KB-1 to 1,2,4-TCB that is dehalogenated to a mixture of dichlorobenzenes, and subsequently to monochlorobenzene and benzene. Surprisingly, a native Dehalobacter population, and not a Dehalococcoides population, couples the dechlorination of 1,2,4-TCB to growth achieving an average yield of 1.1 ± 0.6 × 1013 cells per mole of Cl- released. Interestingly, the dechlorination of 1,2,4-TCB occurs alongside the complete dechlorination of trichloroethene to ethene in cultures fed both electron acceptors. Dehalobacter was not previously identified as a major player in KB-1, but its ecological niche was favoured by the introduction of 1,2,4-TCB. Based on 16S rRNA phylogeny, Dehalobacter populations seem to cluster into specialised clades, and are likely undergoing substrate specialisation as a strategy to reduce competition for electron acceptors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".