Competitiveness of reutericyclin producing and nonproducing <i>Limosilactobacillus reuteri</i> in food and intestinal ecosystems: a game of rock, paper, and scissors?
Bibliographic record
Abstract
The ecological relationships among antimicrobial producing, resistant, and sensitive strains have been proposed to follow rock-paper-scissors dynamics, but evidence is mainly based on Gram-negative bacteriocins in vitro. The ecological relevance of antimicrobials in vivo or in situ has not been systematically studied. This study therefore aimed to analyze binary and ternary competitions among reutericyclin-producing strain Limosilactobacillus reuteri TMW1.656, its reutericyclin-resistant, nonproducing isogenic derivative L. reuteri TMW1.656∆rtcN, and the reutericyclin-sensitive, nonproducing L. reuteri TMW1.656∆rtcN∆rtcT in vitro (liquid culture and static plate), in situ (sourdough fermentation), and in vivo (gut of germ-free mice). In liquid culture, L. reuteri TMW1.656 had a higher fitness than TMW1.656∆rtcN and TMW1.656∆rtcN∆rtcT. Limosilactobacillus reuteri TMW1.656∆rtcN∆rtcT had a higher fitness than TMW1.656∆rtcN. On agar plates, L. reuteri TMW1.656 had a higher fitness than TMW1.656∆rtcN∆rtcT. In situ, reutericyclin production and resistance had no influence on the fitness of the strains. In vivo, TMW1.656 had an advantage over TMW1.656∆rtcN and TMW1.656∆rtcN∆rtcT. Ternary competitions showed reutericyclin production was ecologically beneficial in all ecosystems. The findings support the ecological importance of reutericyclin in a variety of environments/niches, providing an explanation for the acquisition of the reutericyclin gene cluster in L. reuteri and its contribution to the ecological fitness of Streptococcus mutans.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".