Reductive Dechlorination of TCE by Chemical Model Systems in Comparison to Dehalogenating Bacteria: Insights from Dual Element Isotope Analysis (<sup>13</sup>C/<sup>12</sup>C, <sup>37</sup>Cl/<sup>35</sup>Cl)
Bibliographic record
Abstract
Chloroethenes like trichloroethene (TCE) are prevalent environmental contaminants, which may be degraded through reductive dechlorination. Chemical models such as cobalamine (vitamin B12) and its simplified analogue cobaloxime have served to mimic microbial reductive dechlorination. To test whether in vitro and in vivo mechanisms agree, we combined carbon and chlorine isotope measurements of TCE. Degradation-associated enrichment factors ε(carbon) and ε(chlorine) (i.e., molecular-average isotope effects) were -12.2‰ ± 0.5‰ and -3.6‰ ± 0.1‰ with Geobacter lovleyi strain SZ; -9.1‰ ± 0.6‰ and -2.7‰ ± 0.6‰ with Desulfitobacterium hafniense Y51; -16.1‰ ± 0.9‰ and -4.0‰ ± 0.2‰ with the enzymatic cofactor cobalamin; -21.3‰ ± 0.5‰ and -3.5‰ ± 0.1‰ with cobaloxime. Dual element isotope slopes m = Δδ(13)C/ Δδ(37)Cl ≈ ε(carbon)/ε(chlorine) of TCE showed strong agreement between biotransformations (3.4 to 3.8) and cobalamin (3.9), but differed markedly for cobaloxime (6.1). These results (i) suggest a similar biodegradation mechanism despite different microbial strains, (ii) indicate that transformation with isolated cobalamin resembles in vivo transformation and (iii) suggest a different mechanism with cobaloxime. This model reactant should therefore be used with caution. Our results demonstrate the power of two-dimensional isotope analyses to characterize and distinguish between reaction mechanisms in whole cell experiments and in vitro model systems.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".