Evidence-based validation of quorum quenching from <i>Lysinibacillus sphaericus</i> and <i>Geobacillus</i> sp. in bioremediation of oil sludge
Bibliographic record
Abstract
Many studies on quorum quenching focus on the discovery and characterization of novel acyl-homoserine lactonases (AHL-lactonases) because these enzymes could be used in the control of diseases caused by Gram-negative bacteria. The effects of quorum quenching are also remarkable in the performance of bacterial consortia in applications such as bioremediation. In the current work, we demonstrated the presence of a potential novel AHL-lactonase-encoding locus (Bsph_3377) from Lysinibacillus sphaericus and Geobacillus sp. The deduced amino acid sequences for this enzyme possess the characteristic domains and motifs involved in Zn-binding from AHL lactonases and were grouped into 1 clade within the phylogeny of the lactonases from firmicutes, showing 70% of identity with the lactonase AhlS from Solibacillus silvestris. We demonstrated the locus transcription by RT-qPCR and its relationship with the suppression of the pathogenicity of Pectobacterium carotovorum. Additionally, we analyzed the interaction of these bacilli with a commercial consortium in the bioremediation of a hydrocarbon-contaminated soil, showing inhibitory effects on its establishment. These results represent a new contribution in the understanding of the potential biotechnological applications of L. sphaericus and Geobacillus sp. as well as in the research on antibacterial techniques based on quorum-sensing disruption.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".