J Vet Sci.  2018 Nov;19(6):798-807. 10.4142/jvs.2018.19.6.798.

Benefits of procyanidins on gut microbiota in Bama minipigs and implications in replacing antibiotics

• Zhao T
• Shen X
• Dai C
• Cui L

• KMID: 2427028
• DOI: http://doi.org/10.4142/jvs.2018.19.6.798

Abstract

Several studies have reported the effect of absorption of procyanidins and their contribution to the small intestine. However, differences between dietary interventions of procyanidins and interventions via antibiotic feeding in pigs are rarely reported. Following 16S rRNA gene Illumina MiSeq sequencing, we observed that both procyanidin administration for 2 months (procyanidin-1 group) and continuous antibiotic feeding for 1 month followed by procyanidin for 1 month (procyanidin-2 group) increased the number of operational taxonomic units, as well as the Chao 1 and ACE indices, compared to those in pigs undergoing antibiotic administration for 2 months (antibiotic group). The genera Fibrobacter and Spirochaete were more abundant in the antibiotic group than in the procyanidin-1 and procyanidin-2 groups. Principal component analysis revealed clear separations among the three groups. Additionally, using the online Molecular Ecological Network Analyses pipeline, three co-occurrence networks were constructed; Lactobacillus was in a co-occurrence relationship with Trichococcus and Desulfovibrio and a co-exclusion relationship with Bacillus and Spharerochaeta. Furthermore, metabolic function analysis by phylogenetic investigation of communities by reconstruction of unobserved states demonstrated modulation of pathways involved in the metabolism of carbohydrates, amino acids, energy, and nucleotides. These data suggest that procyanidin influences the gut microbiota and the intestinal metabolic function to produce beneficial effects on metabolic homeostasis.

Keyword

Illumina MiSeq; gastrointestinal microbiome; metabolic function; pigs; procyanidin

MeSH Terms

Absorption
Amino Acids
Anti-Bacterial Agents*
Bacillus
Carbohydrates
Desulfovibrio
Fibrobacter
Gastrointestinal Microbiome*
Genes, rRNA
Homeostasis
Intestine, Small
Lactobacillus
Metabolism
Nucleotides
Principal Component Analysis
Proanthocyanidins*
Swine
Swine, Miniature*
Amino Acids
Anti-Bacterial Agents
Carbohydrates
Nucleotides
Proanthocyanidins

Figure

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  Fig. 1 Operational taxonomic unit (OTU) classification levels and relative abundance of intestinal tract OTUs. The horizontal coordinate is arranged according to the sample name, and the ordinate is the number of OTUs that are classified into phylum, class, order, family, genus and species levels for each sample from the three study groups.

• 

  Fig. 2 Rarefaction curves (A) and rank-abundance curves (B) at 97% similarity levels. The number of operational taxonomic units (OTUs) acts as a function of the number of sequence tags sampled.

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  Fig. 3 The α diversity index in the antibiotic group compared with those in the procyanidin groups. (A) Shannon index, (B) Chao1, (C) ACE, and (D) Simpson index. A, antibiotic group; P1, procyanidin-1 group; P2, procyanidin-2 group. *p < 0.05 compared with the antibiotic group.

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  Fig. 4 Relative abundance of operational taxonomic units at the phylum level. Each color indicates one phylum. For each color, the height of the column indicates the abundance of reads.

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  Fig. 5 Microbial differences in the bacterial community among groups categorized according to antibiotic and procyanidin treatment. (A) Bacterial classification between the antibiotic (A), procyanidin-1 (P1), and procyanidin-2 (P2) groups of Bama minipigs; (B) Cladogram from the linear discriminant analysis (LDA) of the effect size (LEfSe) results in the three study groups.

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  Fig. 6 The principal component analysis (PCoA) analysis of the gut microbiota samples. Unweighted Unifrac separates the antibiotic (red), procyanidin-1 (blue), and procyanidin-2 (yellow) groups.

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  Fig. 7 Network of the co-occurring 90% cutoff operational taxonomic units based on correlation analysis. A connection indicates strong (Spearman's rho > 0.6) and significant (p < 0.01) correlations. The connection between nodes indicates that there is a correlation between the two species (red, positive correlation; green, negative correlation). The size of each node is proportional to the degree of connectivity.

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  Fig. 8 Prediction of bacterial metabolic function. (A) Comparison of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways predicted using phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) according to antibiotic or procyanidin treatment. (B) Venn diagram of the common functional groups. A, antibiotic group; P1, procyanidin-1 group; P2, procyanidin-2 group.

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