Aerobic co-metabolism of sulfur, nitrogen and oxygen heterocycles by three marine bacterial consortia
Bibliographic record
Abstract
Bacterial samples were collected from three marine beaches in coastal Newfoundland, Canada, and enriched by growth on 1-methylnaphthalene. The most prominent bacterial cell type for each consortium was isolated in a serial dilutions test, and a substrate utilization profile was obtained for each using the Biolog MicroStation System. Each bacterial community was tested for its ability to co-metabolize sulfur heterocycles (benzothiophene: BT, 3-methylbenzothiophene: 3-MBT, and dibenzothiphene: DBT), a nitrogen heterocycle (carbazole: CARB), and an oxygen heterocycle (dibenzofuran: DBF). Co-metabolism of the starting material was determined using gas chromatography-mass spectroscopy (GC-MS), and formation of products was investigated by GC-MS and Fourier transform infrared (FTIR) spectroscopy. Bacterial growth was monitored turbidimetrically to determine the dry weight (microgram) of cells/ml. The 2-ringed heterocycles were co-metabolized faster and to a greater extent than the 3-ringed compounds. Co-metabolism of BT was not statistically different from that for 3-MBT and, likewise, a comparison of the 3-ringed heterocycles showed no significant differences in degradation rates. Statistical examination showed that no one culture demonstrated a significantly greater ability to co-metabolize the heterocycles studied. This study represents the first comprehensive investigation of the ability of local bacteria to co-metabolize a range of aromatic compounds and provides a preliminary understanding of their fate in sediments should contamination by these compounds occur.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".