The gut microbiota of Labrador retriever puppies: a longitudinal cohort study
Bibliographic record
Abstract
BACKGROUND: Most research into the development of the canine gut microbiota has featured cross-sectional studies, and there has been limited exploratory research into how it is affected by external factors. We aimed to longitudinally characterise the gut microbiota and its development in Labrador Retriever puppies and identify whether alterations in the gut microbiota are associated with factors related to demography, lifestyle, antibiotic usage and gastrointestinal health. RESULTS: 76 Labrador Retriever puppies were recruited via Dogslife, a UK-based online cohort study. Faecal samples were collected at three to four, seven, and 12 months of age and analysed using 16 S rRNA gene sequencing alongside questionnaire data. Alpha and beta diversity were assessed using linear mixed effects models and permutational multivariate analysis, accounting for repeated measures. Differential abundance was evaluated using multivariable association with linear models. Associations were identified between puppies' gut microbiota and age, sex, coat colour, household smoking status, dietary indiscretions (e.g. household waste, coprophagia), contact with other dogs and horses, recent oral/injected antibiotic use, and recent vomiting and diarrhoea. The greatest source of variation was individual identity, explaining approximately 25% of alpha diversity and 50% of beta diversity. Alpha diversity declined between three and 12 months, with age-related shifts in community composition and dispersion. Coprophagia was associated with increased alpha diversity and contributed to variation in community structure. Antibiotic use was associated with reduced alpha diversity, altered composition, and changes in taxa across Firmicutes, Proteobacteria, and Tenericutes. These effects were largely transient, with the largest shifts occurring within one week of treatment. Puppies with recent diarrhoea showed increased alpha diversity and differential abundance in several taxa within four weeks of the episode. Helicobacter was more frequently detected in samples from puppies with recent diarrhoea. CONCLUSIONS: This longitudinal study characterises the development of gut microbiota in Labrador Retriever puppies and identifies associations with demographic, environmental, and health-related factors. These findings underscore the value of longitudinal sampling in microbiome research, offer novel insights for owners and veterinarians, and lay a foundation for future studies investigating causal mechanisms and potential interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".