Whole genome sequencing and analysis of benzo(a)pyrene-degrading bacteria <i>Bacillus cereus</i> M72-4
Bibliographic record
Abstract
Benzo(a)pyrene produced by food during high-temperature process enters the body through ingestion, which causes food safety issues to the human body. To alleviate the harm of foodborne benzo(a)pyrene to human health, a strain that can degrade benzo(a)pyrene was screened from Kefir, a traditional fermented product in Xinjiang. Bacillus cereus M72-4 is a Gram-positive bacteria sourced from Xinjiang traditional fermented product Kefir; under benzo(a)pyrene stress conditions, there was 69.39% degradation rate of 20 mg/L benzo(a)pyrene by strain M72-4 after incubation for 72 h. The whole genome of M72-4 was sequenced using PacBio sequencing technology in this study. The genome size was 5754 801 bp and a GC content was 35.24%; a total of 5719 coding genes were predicted bioinformatically. Through functional database annotation, it was found that the strain has a total of 219 genes involved in the transportation and metabolism of hydrocarbons, a total of 9 metabolic pathways related to the degradation and metabolism of exogenous substances, and a total of 67 coding genes. According to the Kyoto Encyclopedia of Genes and Genomes database annotation results, a key enzyme related to benzo(a)pyrene degradation, catechol 2,3-dioxygenase, was detected in the genome data of Bacillus cereus M72-4, encoding genes dmpB and xylE, respectively. There are also monooxygenases and dehydrogenases. Therefore, it can be inferred that this strain mainly degrades benzo(a)pyrene through benzoate metabolic.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".