Nonstarch Polysaccharides Modulate Bacterial Microbiota, Pathways for Butyrate Production, and Abundance of Pathogenic <i>Escherichia coli</i> in the Pig Gastrointestinal Tract
Bibliographic record
Abstract
The impact of nonstarch polysaccharides (NSP) differing in their functional properties on intestinal bacterial community composition, prevalence of butyrate production pathway genes, and occurrence of Escherichia coli virulence factors was studied for eight ileum-cannulated growing pigs by use of terminal restriction fragment length polymorphism (TRFLP) and quantitative PCR. A cornstarch- and casein-based diet was supplemented with low-viscosity, low-fermentability cellulose (CEL), with high-viscosity, low-fermentability carboxymethylcellulose (CMC), with low-viscosity, high-fermentability oat beta-glucan (LG), and with high-viscosity, high-fermentability oat beta-glucan (HG). Only minor effects of NSP fractions on the ileal bacterial community were observed, but NSP clearly changed the digestion in the small intestine. Compared to what was observed for CMC, more fermentable substrate was transferred into the large intestine with CEL, LG, and HG, resulting in higher levels of postileal dry-matter disappearance. Linear discriminant analysis of NSP and TRFLP profiles and 16S rRNA gene copy numbers for major bacterial groups revealed that CMC resulted in a distinctive bacterial community in comparison to the other NSP, which was characterized by higher gene copy numbers for total bacteria, Bacteroides-Prevotella-Porphyromonas, Clostridium cluster XIVa, and Enterobacteriaceae and increased prevalences of E. coli virulence factors in feces. The numbers of butyryl-coenzyme A (CoA) CoA transferase gene copies were higher than those of butyrate kinase gene copies in feces, and these quantities were affected by NSP. The present results suggest that the NSP fractions clearly and distinctly affected the taxonomic composition and metabolic features of the fecal microbiota. However, the effects were more linked to the individual NSP and to their effect on nutrient flow into the large intestine than to their shared functional properties.
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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 | 0.001 | 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".