Composition and short-term stability of gut microbiota in lean and spontaneously overweight healthy Labrador retriever dogs
Bibliographic record
Abstract
BACKGROUND: The gut microbiota and its metabolic end-products act in close collaboration with the nutrient metabolism of the animal. A relationship between excess adiposity and alterations in gut microbiota composition has been identified in humans and rodents, but data are scarce for overweight dogs. This study compared composition and temporal variations of gut microbiota in healthy lean and spontaneously overweight dogs. The analysis was based on three individual fresh faeces samples from each dog during a 10-day period. Twenty-seven healthy and intact male Labrador retriever dogs were included, 12 of which were classified as lean (body condition score (BCS) 4-5 on a 9-point scale) and 15 as overweight (BCS 6-8). Gut microbiota was analysed by Illumina sequencing of the V3-V4 region of the 16S rRNA gene. RESULTS: Lean and overweight groups of dogs were not separated by principal coordinate analysis (PCoA), analysis of similarity (one-way ANOSIM, P = 0.99) or species indicator analysis (IndVal) using operational taxonomic units (OTU) data. Gut microbial taxa at phylum, family or genus level did not differ between lean and overweight dogs in mixed-model repeated measures analyses. Short-term stability, evaluated by similarity index, did not differ between lean and overweight dogs over the 10-day period. Pooled Firmicutes/Bacteroidetes (F/B) ratio was 3.1 ± 3.7 in overweight dogs and 2.1 ± 1.2 in lean dogs (P = 0.83). Individual dogs, irrespective of body condition (lean or overweight), displayed variation in mean alpha diversity (Chao-1 index range 122-245, Shannon index range 2.6-3.6) and mean similarity index (range 44-85%). CONCLUSIONS: Healthy lean and spontaneously overweight Labrador retriever dogs had comparable gut microbiota composition and short-term stability over a 10-day sampling period. There were no alterations in microbial diversity or in relative abundance of specific taxa at phylum, family or genus level in overweight compared to lean dogs. Our findings suggest that there are few detectable differences in gut microbiota composition between healthy spontaneously overweight and lean dogs by the current method. Future application of metagenomic or metabolomic techniques could be used to investigate microbial genes or microbial end-products that may differ even when microbiota compositional analyses fail to detect a significant difference between lean and overweight dogs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".