C and Cl Isotope Fractionation of 1,2-Dichloroethane Displays Unique δ<sup>13</sup>C/δ<sup>37</sup>Cl Patterns for Pathway Identification and Reveals Surprising C–Cl Bond Involvement in Microbial Oxidation
Bibliographic record
Abstract
This study investigates dual element isotope fractionation during aerobic biodegradation of 1,2-dichloroethane (1,2-DCA) via oxidative cleavage of a C-H bond (Pseudomonas sp. strain DCA1) versus C-Cl bond cleavage by S(N)2 reaction (Xanthobacter autotrophicus GJ10 and Ancylobacter aquaticus AD20). Compound-specific chlorine isotope analysis of 1,2-DCA was performed for the first time, and isotope fractionation (ε(bulk)(Cl)) was determined by measurements of the same samples in three different laboratories using two gas chromatography-isotope ratio mass spectrometry systems and one gas chromatography-quadrupole mass spectrometry system. Strongly pathway-dependent slopes (Δδ13C/Δδ37Cl), 0.78 ± 0.03 (oxidation) and 7.7 ± 0.2 (S(N)2), delineate the potential of the dual isotope approach to identify 1,2-DCA degradation pathways in the field. In contrast to different ε(bulk)(C) values [-3.5 ± 0.1‰ (oxidation) and -31.9 ± 0.7 and -32.0 ± 0.9‰ (S(N)2)], the obtained ε(bulk)(Cl) values were surprisingly similar for the two pathways: -3.8 ± 0.2‰ (oxidation) and -4.2 ± 0.1 and -4.4 ± 0.2‰ (S(N)2). Apparent kinetic isotope effects (AKIEs) of 1.0070 ± 0.0002 (13C-AKIE, oxidation), 1.068 ± 0.001 (13C-AKIE, S(N)2), and 1.0087 ± 0.0002 (37Cl-AKIE, S(N)2) fell within expected ranges. In contrast, an unexpectedly large secondary 37Cl-AKIE of 1.0038 ± 0.0002 reveals a hitherto unrecognized involvement of C-Cl bonds in microbial C-H bond oxidation. Our two-dimensional isotope fractionation patterns allow for the first time reliable 1,2-DCA degradation pathway identification in the field, which unlocks the full potential of isotope applications for this important groundwater contaminant.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".