Impact of probiotic supplementation in lactating sows on immune and oxidative stress biomarkers, short-chain fatty acids, piglet performance, and fecal microbiome
Notice bibliographique
Résumé
This clinical trial aimed to investigate the effects of probiotic supplementation in lactating sows on their serum immunoglobulin levels, milk yield, serum malondialdehyde (MDA), fecal short-chain fatty acid levels, piglet performance, and fecal microbiome. The research was conducted at a commercial swine breeding herd in central Thailand. The study included 109 Canadian Landrace × Yorkshire sows, with parity numbers ranging from 1 to 7. The sows were divided into two groups based on their parity numbers: control (n = 61) and treatment (n = 48). The control group sows received a conventional commercial lactation diet without any antibiotic supplementation, starting from 109.5 ± 1.6 days of gestation and continuing until weaning at 21 days of lactation. In contrast, the treatment group sows were fed a lactational diet supplemented with probiotics (Bacillus subtilis and Bacillus amyloliquefaciens) mixed in the feed during the same period. Additionally, piglets from the treatment group were provided with the same probiotics as a top dressing starting on the third day after birth and continuing until weaning. Blood samples were taken from the sows at the time of farrowing (n = 49) and from the piglets on days 7 (n = 59) and 14 (n = 60) of age. The concentrations of immunoglobulin (Ig), including IgG, IgA, and IgM, were determined using ELISA. Sow serum MDA quantification was performed. Fecal samples from sows were collected at entry, farrowing, and weaning for microbiome analysis. Fecal samples from piglets were collected at 3, 7, and 21 days of age to monitor changes in short-chain fatty acid levels via GC-FID and to analyze the fecal microbiome. Bacterial DNA from fecal samples was extracted using the QIAamp Power Fecal Pro DNA Kit, and 16S rRNA sequencing targeting the V3-V4 regions was performed by Illumina Miseq. Microbiome bioinformatics analyses were conducted using QIIME2 version 2023.9. Sow reproductive characteristics and piglet performance data were compared between the control and treatment groups. The supplementation of probiotics in sow and piglet feed did not show a difference in sow reproductive characteristics and piglet performance (P > 0.05). The sow serum IgM in the treatment group was higher than in the control group (5.19 ± 0.32 vs. 4.10 ± 0.36 mg/mL, P = 0.031), while there were no significant differences found in other sow immunoglobulins (P > 0.05) and serum MDA levels (P > 0.05) between the groups. Conversely, piglet IgM levels on day 7 of life were lower in the treatment group compared to the control group (0.36 ± 0.07 vs. 0.68 ± 0.07 mg/mL, P = 0.002), while on day 14 of life, there was no difference between the groups (P > 0.05). The analysis of alpha diversity in the sow fecal microbiome, the control group shown significantly higher in richness than treatment groups on days 7 and 28 (P < 0.05). Pielou’s evenness index and Shannon index showed no significant differences between sows in the control and treatment groups at any time point (P > 0.05). In the piglets' fecal microbiome, the treatment group shown significantly higher in richness than control group on day 21 of life (P < 0.05). The Shannon diversity also showed significant higher in treatment group than the control group on day 21 (P < 0.05). Evenness index showed no significant differences between piglets in the control and treatment groups at any time point (P > 0.05). Dominant phyla in both sow and piglet in both control and treatment group at every time point were Firmicutes and Bacteroidota. The sow fecal bacterial genera were predominantly composed of Oscillospiraceae UCG-005, followed by Prevotella and Lactobacillus. The dominant bacterial genera in the piglet fecal microbiome were Bacteroides and Lactobacillus. In conclusion, the supplementation of B. subtilis and B. amyloliquefaciens in the feed of sows and piglets influenced the response of IgM in both sows and piglets, albeit in different ways. The fecal short-chain fatty acids in piglets on day 7 showed a higher concentration in the treatment group than in the control group, while there was no difference at other time points. However, there were no observable effects on other aspects of sow reproductive health or piglet growth performance.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».