Bioaugmentation with Distinct<i>Dehalobacter</i>Strains Achieves Chloroform Detoxification in Microcosms
Bibliographic record
Abstract
Chloroform (CF) is a widespread groundwater contaminant not susceptible to aerobic degradation. Under anoxic conditions, CF can undergo abiotic and cometabolic transformation but detoxification is generally not achieved. The recent discovery of distinct Dehalobacter strains that respire CF to dichloromethane (DCM) and ferment DCM to nonchlorinated products promises that bioremediation of CF plumes is feasible. To track both strains, 16S rRNA gene-based qPCR assays specific for either Dehalobacter strain were designed and validated. A laboratory treatability study explored the value of bioaugmentation and biostimulation to achieve CF detoxification using anoxic microcosms established with aquifer material from a CF-contaminated site. Microcosms that received 6% (v/v) of the CF-to-DCM-dechlorinating culture Dhb-CF to achieve an initial Dehalobacter cell titer of 1.6 ± 0.9 × 10(4) mL(-1) dechlorinated CF to stoichiometric amounts of DCM. Subsequent augmentation with 3% (v/v) of the DCM-degrading consortium RM to an initial Dehalobacter cell abundance of 1.2 ± 0.2 × 10(2) mL(-1) achieved complete DCM degradation in microcosms amended with 10 mM bicarbonate. Growth of the CF-respiring and the DCM-degrading Dehalobacter populations and detoxification were also observed in microcosms that received both inocula simultaneously. These findings suggest that anaerobic bioremediation (e.g., bioaugmentation) is a possible remedy at CF- and DCM-contaminated sites without CT, which strongly inhibited CF organohalide respiration and DCM organohalide fermentation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".