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 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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".