386 Effects of Different Soy Protein Sources on Gut Microbiome Composition and Relationship with Performance in Pigs in Regular Nursery and F4 Enterotoxigenic <i>Escherichia Coli</i> (ETEC) Challenged Conditions
Bibliographic record
Abstract
Abstract Provisoy, produced by hydro, thermal, and mechanical process using soybean meal (SBM) has been shown to improve both post-weaning pig growth and gut health compared with SBM. It was hypothesized that Provisoy could improve the utilization of both protein and fiber fractions along the gastrointestinal tract of a nursery pig resulting in a more balanced nutrient environment and robust microbiome in the hindgut compared with SBM. A total of 268 weaned pigs (body weight, 6.82 ± 0.85 kg) were allotted to either a regular nursery condition (5 pigs/pen, 10-11 pens/treatment) or subjected to ETEC challenge (3 pigs/pen, 12 pens/treatment, 1 pig per pen was orally gavaged with O149:K91:K88 strain on d 5 post-weaning). Pigs received one of the following diets: SBM, Provisoy or HP300 (soy protein from Hamlet Protein, used as a benchmark). A standard wheat-barley-SBM based diet was used, and test soy products were added to replace SBM in the treatment diets during the first three weeks of nursery program. All diets were isocaloric with the same standardized ileal digestible lysine level in a three-phase (38 days) nursery program. Fecal samples were collected on d 13 or d 14 post-weaning and subjected to DNA extraction and Nanopore shotgun sequencing. Data were center-log-ratio transformed and subjected to statistical analysis. Microbiome composition was affected by dietary treatment (P < 0.01) and challenge (P < 0.05), but their interaction was not significant. In regular nursery condition, both Provisoy and HP300 tended (P < 0.10) to have greater microbiome alpha-diversity compared with SBM, but no difference was observed between these two treatments. Only SBM fed pigs subjected to ETEC challenge had greater (P = 0.02) alpha-diversity compared with their non-challenged counterparts. Compared with the SBM treatment, pigs that received Provisoy in the regular condition had greater abundance of Coprococcus and Dialister, which were positively correlated with greater average daily gain (ADG; r = 0.53, P < 0.01, and r = 0.45, P = 0.01, respectively). Under ETEC challenge, an increase in abundance of Dialister was observed in pigs that received Provisoy treatment with a positive correlation with ADG (r = 0.42, P = 0.01). In conclusion, dietary inclusion of Provisoy or HP300 improved microbiome alpha-diversity compared with SBM. Provisoy helped promote the growth of beneficial bacteria in the hindgut of nursery pigs which were positively correlated with gain.
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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) | 0.000 | 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) | 0.001 | 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".