Persistence of the Oral Probiotic Streptococcus salivarius M18 Is Dose Dependent and Megaplasmid Transfer Can Augment Their Bacteriocin Production and Adhesion Characteristics
Bibliographic record
Abstract
Bacteriocin-producing probiotic Streptococcus salivarius M18 offers beneficial modulatory capabilities within the oral microbiome, apparently through potent inhibitory activity against potentially deleterious bacteria, such as Streptococcus pyogenes. The oral cavity persistence of S. salivarius M18 was investigated in 75 subjects receiving four different doses for 28 days. Sixty per cent of the subjects already had some inhibitor-producing S. salivarius in their saliva prior to probiotic intervention. Strain M18's persistence was dependent upon the dose, but not the period of administration. Culture analysis indicated that in some individuals the introduced strain had almost entirely replaced the indigenous S. salivarius, though the total numbers of the species did not increase. Selected subjects showing either high or low probiotic persistence had their salivary populations profiled using Illumina sequencing of the V6 region of the 16S rRNA gene. Analysis indicated that while certain bacterial phenotypes were markedly modulated, the overall composition of the oral microbiome was not modified by the probiotic treatment. Megaplasmids encoding bacteriocins and adhesion factors were transferred in vitro to generate a transconjugant S. salivarius exhibiting enhanced antimicrobial production and binding capabilities to HEp-2 cells. Since no widespread perturbation of the existing indigenous microbiota was associated with oral instillation and given its antimicrobial activity against potentially pathogenic streptococci, it appears that application of probiotic strain M18 offers potential low impact alternative to classical antibiotic prophylaxis. For candidate probiotic strains having relatively poor antimicrobial or adhesive properties, unique derivatives displaying improved probiotic performance may be engineered in vitro by megaplasmid transfer.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".