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 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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".