Progression of swine fecal microbiota during early stages of life and its association with performance: a longitudinal study
Bibliographic record
Abstract
BACKGROUND: It is vital to understand healthy gut microbiota composition throughout early life stages when environments are changing, and immunity is developing. There are limited large-scale longitudinal studies classifying healthy succession of swine microbiota. The objectives of this study were to (a) determine the microbiota composition of fecal samples collected from piglets within a few days after birth until one-week post-weaning, and (b) investigate the associations of early fecal microbiota with pig growth performance in nursery and later growing stages. Fecal samples were collected from nine cohorts of 40 pigs (n = 360) from distinct farrowing sources in Ontario and Quebec, Canada at four timepoints from birth to one-week post-weaning, with pig body weight was recorded at each fecal sampling. RESULTS: Microbiota was dominated by the phyla Firmicutes, Bacteroides and Proteobacteria. There were notable differences in genera abundance between pigs from different provinces and farming systems. Over the early life stage, the genera Bacteroides, Escherichia/Shigella, and Clostridium cluster XIVa were abundant preweaning, while Prevotella dominated post-weaning. Hierarchical clustering identified three major stages of microbiota development, each associated with distinct composition. Stage one occurs from birth to 7 days, stage two from 7 days after birth until weaning, and stage three from weaning to one-week post-weaning. Three enterotypes were identified in stage two that showed differences in growth before weaning, and in the grower production stage. Piglets with a microbiota enterotype characterized by higher abundance of Prevotella and unclassified Ruminococcaceae had lower growth performance in the pre-weaning stage, and the growing stage. CONCLUSION: These findings help identify the timing of microbiota shifts across early swine life which may be the optimal time for external intervention to shift the microbiota to a beneficial state. The project findings should help decrease antimicrobial use, increase animal welfare, and have positive economic impacts.
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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".