Dataset Information

Sources of Dietary Fiber Affect the SCFA Production and Absorption in the Hindgut of Growing Pigs.

ABSTRACT: Effects of different dietary fiber (DF) sources on short-chain fatty acids (SCFA) production and absorption in the hindgut of growing pigs were studied by an in vivo-vitro (ileal cannulated pigs and fecal inoculum-based fermentation) method. Thirty-six cannulated pigs (body weight: 48.5 ± 2.1 kg) were randomly allocated to 6 treatments containing the same DF content (16.5%), with either wheat bran (WB), corn bran (CB), sugar beet pulp (SBP), oat bran (OB), soybean hulls (SH), or rice bran (RB) as DF sources. Pigs were allowed 15 days for diet adaptation, and then, fresh ileal digesta and feces were collected to determine SCFA concentration which was normalized for food dry matter intake (DMI) and the hindgut DF fermentability. Fecal microbiota was inoculated into the freeze-dried ileal digesta samples to predict the ability of SCFA production and absorption in the hindgut by in vitro fermentation. The SH group had the largest concentration of total SCFA and propionate in ileal digesta and fecal samples of growing pigs (p < 0.05). Nonetheless, the predicted acetate, total SCFA production, absorption in the SBP group were the highest (p < 0.01), but the lowest in the OB group (p < 0.01) among all groups. Even SBP and OB group had a similar ratio of soluble DF (SDF) to insoluble DF (IDF). The CB group had high determined ileal and fecal butyrate concentration but the lowest butyrate production and absorption in the hindgut (p < 0.01). Overall, the source of DF had a great impact on the hindgut SCFA production and absorption, and SBP fiber had a great potential to increase hindgut SCFA production and absorption.

SUBMITTER: Bai Y

PROVIDER: S-EPMC8784547 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:This study was to investigate time-course effects of different types of dietary fiber on the energy values, fecal microbiota and short-chain fatty acid (SCFA) concentration in growing pigs. A total of 24 barrows (initial body weight, 19.8 ± 0.5 kg) were assigned to 4 dietary treatments based on body weight (BW) in a completely randomized design, including a basal diet (CON) and 3 fiber-rich diets replacing corn, soybean meal and soybean oil in the CON diet with 20% sugar beet pulp (SBP), defatted rice bran (DFRB) or soybean hull (SBH), respectively. Fresh feces were sampled on d 7, 14 and 21, followed by 5 d total feces and urine collections. The results showed that there were no differences in DE and ME between any of the fiber ingredients on d 7, 14 or 21. However, fiber inclusion decreased the DE and ME of the diet (P < 0.05) regardless of the time effect. Principal coordinate analysis (PCoA) revealed distinctly different microbial communities on the DFRB diet and SBH diet across different times (P < 0.05) and the fecal microbiota of the 4 diet groups demonstrated notably distinct clusters at each time point (P < 0.05). With adaptation time increased from 7 to 21 d, cellulose-degrading bacteria and SCFA-producing bacteria (e.g., Ruminococcaceae _UCG-014, Rikenellaceae _RC9_gut_group and Bifidobacterium) increased in the fiber inclusion diets, and pathogenic genera (e.g., Streptococcus and Selenomonas) were increased in the basal diet (P < 0.05). Furthermore, the gut microbiota of growing pigs adapted more easily and quickly to the SBP diet compared to the DFRB diet, as reflected by the concentration of propionate, butyrate, isovalerate and total SCFA which increased with time for growing pigs fed the DFRB diet (P < 0.05). Collectively, our results indicated at least 7 d adaptation was required to evaluate the energy values of fiber-rich ingredients, as the hindgut microbiota of growing pigs may need more time to adapt to a high fiber diet, especially for insoluble dietary fiber.

Project description:Microbial population in the gastrointestinal tract plays a central role in health and nutrient digestion. The objective of the present study was to investigate the relationships between microbiota and apparent digestibility coefficients with respect to age and diet. Pigs from Large-White, Duroc or Pietrain breeds were raised under the same housing conditions and fed alternately a low-fiber (LF) and a high-fiber diet (HF) during 4 successive 3-week periods. Data collection for digestibility measurements was achieved during the last week of each period. At the end of each period, fecal microbiota was collected for 16S rRNA gene sequencing. The microbiota remained stable across periods whereas digestibility of energy, crude proteins and cell wall components increased. The microbiota was resilient to diet effect and pigs fed the LF diet were discriminated to those fed the HF diet using 31 predicting OTUs with a mean classification error-rate of 3.9%. Clostridiaceae and Turicibacter were negatively correlated whereas Lactobacillus was positively correlated with protein and energy digestibility coefficients in the LF group. In addition, Lachnospiraceae and Prevotella were negatively correlated with cell wall component digestibility. In contrast, no significant correlation was found between microbiota composition and digestibility coefficients when pigs were fed the HF diet. Interestingly, it was also no longer possible to distinguish animals from different breeds once the animals were fed a HF diet, so that the microbiota could only trace the breed origin in the first period and in the LF group. In our experimental conditions, 3 weeks of adaptation to a new diet seems to be sufficient to observe resilience in growing pigs' microbiota. We demonstrated that fecal microbiota can be used to classify pigs according to their dietary treatment. Some bacteria are favorable or unfavorable to digestibility. This suggests that manipulations of bacterial populations can improve digestibility and feed efficiency.

Dataset Information

Sources of Dietary Fiber Affect the SCFA Production and Absorption in the Hindgut of Growing Pigs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets