Microbial oxidation of 1,2-dichloroethane under anoxic conditions with nitrate as electron acceptor in mixed and pure cultures
Bibliographic record
Abstract
Many organisms have been found to readily oxidize the prevalent contaminant 1,2-dichloroethane (1,2-DCA) to CO2 under aerobic conditions. Some organisms have also been isolated that can reduce 1,2-DCA to ethene via dihaloelimination under anaerobic, fermentative conditions. However, none have been described that can metabolize 1,2-DCA under anoxic, nitrate-reducing conditions. In microcosms prepared from aquifer material and groundwater samples from a contaminated site in eastern Louisiana, USA, 1,2-DCA was observed to degrade with nitrate as the terminal electron acceptor. Nitrate-dependent enrichment cultures were developed from these microcosms that sustained rapid 1,2-DCA degradation rates of up to 500 microM day(-1). This degradation was tightly coupled to complete reduction of nitrate via nitrite to nitrogen gas. A novel 1,2-DCA-degrading organism belonging to the Betaproteobacteria (affiliated with the genus Thauera) was isolated from this enrichment culture. However, degradation rates were much slower in cultures of the isolate than observed in the parent mixed culture. Complete mineralization of 1,2-DCA to CO2 was linked to cell growth and to nitrate reduction in both enrichment and isolated cultures. Monochloroacetate, a putative metabolite of 1,2-DCA degradation, could also be mineralized by these cultures.
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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) | 0.001 | 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 | 0.000 |
| 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".