Dietary fiber - A double-edged sword for balanced nutrition supply and environment sustainability in swine industry: A meta-analysis and systematic review

Zhao, Jinbiao; Wang, Junjun; Zhang, Shuai

doi:10.1016/j.jclepro.2021.128130

Cited by 8 publications

(3 citation statements)

References 118 publications

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“…Swine-associated microbial communities can have strong positive and negative effects on pig disease and health ( 40 ), nutrition ( 41 ), growth performance ( 42 ), physiological development ( 43 , 44 ), antimicrobial resistance ( 45 , 46 ), as well as on the environment ( 47 ). Generally speaking, the swine production cycle can be divided into four phases.…”

Section: Discussionmentioning

confidence: 99%

Meta-analysis reveals the predictable dynamic development of the gut microbiota in commercial pigs

Dong,

Ricker,

Holman

et al. 2023

Microbiol Spectr

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Understanding the mechanisms of microbiome assembly during host development is crucial for successful modulation of the gut microbiome to improve host health and growth. However, results from previous microbial intervention studies to improve swine growth have largely been inconsistent due to the constantly changing nature of the gut microbiota and limited longitudinal sampling. Detailed characterization of the swine gut microbiota through meta-analysis allows us to understand the dynamics of microbial community succession, as well as the transient and natural variations between time points and animals. A total of 3,313 fecal microbial communities from over 349 pigs covering 60 time points (from birth to market age) from 14 publications were included in this meta-analysis. Despite differences in animal breeds and management, generalizable patterns of community assembly were identified. Alpha diversity continuously increased during early stages of animal growth and more slowly in the later stages. Beta regression analysis revealed that more microbial taxa were enriched, while fewer were excluded by the gut microbiota. The microbial community structure also changed significantly between days at early ages and became more similar as pigs aged, as revealed by dissimilarity and distance metrics. Dirichlet multinomial mixtures analysis supported gradient microbial clustering in longitudinal pig fecal samples, and we found that the early samples spread to more clusters than those from older pigs. Random forest regression identified 30 operational taxonomic units as potential microbial biomarkers for modeling swine gut microbiota development. External validation showed this model could be generalized to future microbiome studies conducted in suckling and weaning pigs and adds to the toolkit to quantify community succession. IMPORTANCE The swine gut microbiome undergoes an age-dependent assembly pattern with a developmental phase at early ages and a stabilization phase at later ages. Shorter time intervals and a wider range of data sources provided a clearer understanding of the gut microbiota colonization and succession and their associations with pig growth and development. The rapidly changing microbiota of suckling and weaning pigs implies potential time targets for growth and health regulation through gut microbiota manipulation. Since swine gut microbiota development is predictable, swine microbiota age can be calculated and compared between animal treatment groups rather than relying only on static time-matched comparisons.

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Section: Discussionmentioning

confidence: 99%

Meta-analysis reveals the predictable dynamic development of the gut microbiota in commercial pigs

Dong,

Ricker,

Holman

et al. 2023

Microbiol Spectr

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“…Currently, the prevailing consensus is that short-chain fatty acids, represented by butyrate, were produced by commensal butyrate-producing bacteria in the large intestine [ 12 , 13 , 14 ] through fermentation of non-digestible dietary fibers [ 15 ] like polydextrose (PDX) [ 16 ] and fibersol-2 (FS2) [ 17 ]. Butyrate plays a critical role in maintaining gut epithelial cell homeostasis as their primary energy source, and it could inhibit CRC cells growth and promotes apoptosis by modulating the inhibition of histone deacetylases (HDAC) and NF-kB proinflammatory signaling pathways [ 18 , 19 ]. Interestingly, among four butyrate biosynthesis pathways, the pyruvate pathway [ 20 ] was predominantly identified in commensals bacteria, e.g., Ruminococcaceae [ 21 ], Roseburia [ 22 ], and Lachnospiraceae [ 23 ]; amino acids degrading pathways like 4-aminobutyrate [ 24 ] and lysine [ 25 ] were generally observed in Porphyromonas gingivalis [ 26 ], Megasphaera [ 27 ], Clostridioides difficile [ 28 ], and other carcinogenesis bacteria [ 29 ], while the glutarate pathway [ 30 ] was identified in both commensal and pathogenic bacteria [ 31 ], suggesting that the significant diversity of substrates, end-products, and side-products from different butyrate-producing pathways [ 32 ] might potentially impact the overall health of hosts and patients’ prognosis [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

The Pathogenicity of Fusobacterium nucleatum Modulated by Dietary Fibers—A Possible Missing Link between the Dietary Composition and the Risk of Colorectal Cancer

Nawab

Bao

et al. 2023

Microorganisms

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The dietary composition has been approved to be strongly associated with the risk of colorectal cancer (CRC), one of the most serious malignancies worldwide, through regulating the gut microbiota structure, thereby influencing the homeostasis of colonic epithelial cells by producing carcinogens, i.e., ammonia or antitumor metabolites, like butyrate. Though butyrate-producing Fusobacterium nucleatum has been considered a potential tumor driver associated with chemotherapy resistance and poor prognosis in CRC, it was more frequently identified in the gut microbiota of healthy individuals rather than CRC tumor tissues. First, within the concentration range tested, the fermentation broth of F. nucleatum exhibited no significant effects on Caco-2 and NCM460 cells viability except for a notable up-regulation of the expression of TLR4 (30.70%, p < 0.0001) and Myc (47.67%, p = 0.021) and genes encoding proinflammatory cytokines including IL1B (197.57%, p < 0.0001), IL6 (1704.51%, p < 0.0001), and IL8 (897.05%, p < 0.0001) in Caco-2 cells exclusively. Although no marked effects of polydextrose or fibersol-2 on the growth of F. nucleatum, Caco-2 and NCM460 cells were observed, once culture media supplemented with polydextrose or fibersol-2, the corresponding fermentation broths of F. nucleatum significantly inhibited the growth of Caco-2 cells up to 48.90% (p = 0.0003, 72 h, 10%) and 52.96% (p = 0.0002, 72 h, 10%), respectively in a dose-dependent manner. These two kinds of fibers considerably promoted butyrate production of F. nucleatum up to 205.67% (p < 0.0001, 6% polydextrose at 24 h) and 153.46% (p = 0.0002, 6% fibersol-2 at 12 h), which explained why and how the fermentation broths of F. nucleatum cultured with fibers suppressing the growth of Caco-2 cells. Above findings indicated that dietary fiber determined F. nucleatum to be a carcinogenic or antitumor bacterium, and F. nucleatum played an important role in the association between the dietary composition, primarily the content of dietary fibers, and the risk of CRC.

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“…With the ever-growing population, food security has become an urgent issue [1]. Feed cost accounts for 65%-75% of the total production costs in chicken farming, with energy ingredients being responsible for a large proportion [2,3].…”

Section: Introductionmentioning

confidence: 99%

Comparison of metabolizable energy values of wheat, paddy, and brown rice in roosters determined by free‐feeding and tube‐feeding methods

Li,

Bai,

Liu

et al. 2023

Animal Research and One Health

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The objective of this study was to evaluate the impact of the determination methods (free feeding [FF] and tube feeding [TF]) on the available energy of ingredients (wheat, paddy, and brown rice). A total of 101 adult Hy‐Line Brown roosters (35 weeks old) with an initial body weight of 2.72 ± 0.21 kg were used, in which 96 roosters were randomly assigned to the FF group and TF group, and the remaining five birds were selected to determine the endogenous energy loss. Each group consisted of 12 dietary treatments. In the FF group, each diet treatment comprised 2 replicates with 2 birds per replicate and 4 replicates with 1 bird per replicate for each diet in the TF group. The 12 dietary treatments included a basal diet (BD) and 11 test diets, in which wheat, paddy, and brown rice replaced 30% corn, soybean meal, and wheat bran in the BD. The experiment was performed three times. There was a significant effect of source on apparent metabolizable energy (AME) and true metabolizable energy (TME) in paddy (p < 0.05). Results showed that AME in wheat, paddy, and brown rice measured by the FF method were greater than those values gained by the TF method (p < 0.05). The average AME and TME values were 3537, 3140, and 3893 kcal/kg dry matter (DM) and 3555, 3163, and 3933 kcal/kg DM for wheat, paddy, and brown rice, respectively, measured by the FF method. The means of AME and TME evaluated by the TF method were 3270, 2988, and 3764 kcal/kg DM and 3642, 3357, and 4135 kcal/kg DM for wheat, paddy, and brown rice, respectively. In conclusion, the determination method has a considerable effect on available energy, and the TF method underestimates the AME of ingredients.

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Dietary fiber - A double-edged sword for balanced nutrition supply and environment sustainability in swine industry: A meta-analysis and systematic review

Cited by 8 publications

References 118 publications

Meta-analysis reveals the predictable dynamic development of the gut microbiota in commercial pigs

Meta-analysis reveals the predictable dynamic development of the gut microbiota in commercial pigs

The Pathogenicity of Fusobacterium nucleatum Modulated by Dietary Fibers—A Possible Missing Link between the Dietary Composition and the Risk of Colorectal Cancer

Comparison of metabolizable energy values of wheat, paddy, and brown rice in roosters determined by free‐feeding and tube‐feeding methods

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