Simple method to identify bacteriocin induction peptides and to auto-induce bacteriocin production at low cell density
Bibliographic record
Abstract
The production of some bacteriocins by lactic acid bacteria is regulated by induction peptides (IPs) that are secreted by a dedicated secretion system. The IP gene cbaX, for carnobacteriocin A production by Carnobacterium piscicola LV17A, and a presumptive IP gene (orf6), associated with the genetic locus for enterocin B production in Enterococcus faecium BFE 900, were fused to the signal peptide of the bacteriocin divergicin A from Carnobacterium divergens LV13 to access the general secretory pathway. The culture supernatants of C. piscicola UAL26 and Lactococcus lactis MG1363 containing either of these constructs were used to induce bacteriocin production by Bac(-) cultures of C. piscicola LV17A or E. faecium CTC492. The cbaX fusion product induced bacteriocin production by Bac(-) C. piscicola LV17A, but the orf6 fusion product did not induce bacteriocin production by E. faecium CTC492. This represents a relatively simple method of confirming the role of presumptive IPs. The transformation of C. piscicola LV17A with the CbaX gene under expression of the P32 promoter from L. lactis resulted in constitutive production of bacteriocin by either the dedicated transport apparatus or the general secretory pathway.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".