Simulated Swine Digestion and Gut Microbiota Fermentation of Hydrolyzed Copra Meal.
Jurairat RungruangsaphakunFrancis AyimbilaMassalin NakphaichitSuttipun KeawsompongPublished in: Animals : an open access journal from MDPI (2024)
This study aimed to compare the effects of hydrolyzed copra meal (HCM) inclusion at 1% on its in vitro digestibility and the microbiota and cecum fermentation using the gut microbiota of weaned swine, targeting microbial community and short-chain fatty acids (SCF). For this reason, three treatments were considered: control (no copra meal), 1% non-hydrolyzed copra meal (CM), and 1% HCM. Non-defatted copra meal was hydrolyzed and analyzed (reducing sugars and total carbohydrates) in our laboratory. For digestion, microbiota identification, and fermentation assays, fresh fecal samples from two weaned pigs (1 month old) were used. Three replicates of each treatment were employed. HCM was more digestible, with approximately 0.68 g of hydrolysate recovered after simulated digestion compared to 0.82 g of hydrolysate recovered from CM. This was shown by Scanning Electron Microscope (SEM) images. Also, the three swine shared the majority of microbial species identified at the phylum and family levels. There were no differences ( p > 0.05) between treatments in the microbial community and SCFA during fermentation. However, higher Chao-1 and Shannon indexes were observed in CM and HCM treatments. HCM was also found to be capable of preserving Actinobacterota and Proteobacteria at the phylum level, while at the family level, both treatments may help Lactobacillaceae , Peptostreptococcaceae , Lachnospiraceae , and Ruminococcaceae survive in the long term. Also, there was a potential trend of increasing acetic acid and butyric acid in the CM and HCM treatments. While HCM shows promise in potentially modulating the gut microbiota of weaned swine, additional research is required to investigate the effects of higher doses of HCM on swine performance parameters.
Keyphrases
- microbial community
- hypertrophic cardiomyopathy
- left ventricular
- antibiotic resistance genes
- saccharomyces cerevisiae
- lactic acid
- high throughput
- heart failure
- machine learning
- signaling pathway
- combination therapy
- big data
- optical coherence tomography
- anaerobic digestion
- human health
- artificial intelligence
- climate change
- bioinformatics analysis