Enhanced tameness by <i>Limosilactobacillus reuteri</i> from gut microbiota of selectively bred mice
Bibliographic record
Abstract
Abstract Domestication alters animal behaviour, primarily their tameness. In this study, we examine the effect of gut bacteria on mouse tameness. We previously conducted selective breeding for active tameness, defined as the motivation to approach a human hand, using genetically heterogeneous mice derived from eight wild inbred strains. We examined gut microbiota in the selectively bred mice by analysing faecal samples from 80 mice through shotgun metagenomic analysis. In the current study, we found that the selectively bred mice exhibit higher levels of active tameness as well as higher levels of blood oxytocin, which plays a key role in social behaviours. Selection for tameness did not substantially alter the taxonomic or functional diversity of the gut microbiota. However, we observed an increased abundance of Limosilactobacillus reuteri in the selected groups and higher pyruvate levels in their plasma. We isolated L. reuteri strains secreting extracellular pyruvate from mice faeces and administrated the cultured bacteria through drinking water. Mice treated with L. reuteri showed higher colonization of the bacteria in the gut, as well as higher levels of active tameness behaviour and blood oxytocin. Additionally, we generated 374 high-quality metagenome-assembled genomes (MAGs) of bacteria across 11 phyla. This collection includes 27 novel species level bacterial MAGs not previously known to exist in the mouse gut. This study elucidates the potential role of L. reuteri in the animal domestication process and explores the underlying mechanisms that may influence this process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".