Comparative biogeography of the gut microbiome between Jinhua and Landrace pigs

Abstract

The intestinal microbiome is critically important in shaping a variety of host physiological responses. However, it remains elusive on how gut microbiota impacts overall growth and more specifically, adipogenesis. Using the pig as an animal model, we compared the differences in bacterial community structure throughout the intestinal tract in two breeds (Landrace and Jinhua) of pigs with distinct phenotypes. The Landrace is a commercial purebred and the Jinhua is a Chinese indigenous, slow-growing breed with high propensity for fat deposition. Using 16S rRNA gene sequencing, we revealed that the bacterial communities are more diverse in the duodenum, jejunum, and cecum of Jinhua pigs than in those of Landrace pigs, whereas the ileal and colonic microbiota show a similar complexity between the two breeds. Furthermore, a number of bacterial taxa differentially exist in Jinhua and Landrace pigs throughout the entire intestinal tract, with the jejunal and ileal microbiome showing the greatest contrast. Functional prediction of the bacterial community suggested increased fatty acid biosynthesis in Jinghua pigs, which could partially explain their adiposity phenotype. Further studies are warranted to experimentally verify the relative contribution of each enriched bacterial species and their effect on adipogenesis and animal growth.

Figure 1

Differences in body weight (A), backfat thickness (B) and intramuscular fat (C) between 240-day-old Jinhua and Landrace pigs. ***P < 0.001 (by unpaired Student’s t-test).

Figure 2

Community diversity in different intestinal segments of Jinhua and Landrace pigs. The cecum harbors the most diverse microbiome among all intestinal segments in both Jinhua and Landrace pigs. Jinhua pigs host more diverse bacterial communities in the duodenum, jejunum, and cecum than Landrace pigs.

Figure 3

Biogeography of gut microbiome in Jinhua pigs. Principal coordinate analysis (PCoA) shows bacterial community structures based on Bray-Curtis distances. On the PCoA plot, each symbol represents one gut microbiome. (A) The microbiota composition in five intestinal segments in Jinhua pigs. (B–E) Pair-wise comparison between the cecal microbiota vs the microbiota in the duodenum, jejunum, cecum and colon, respectively. The numbers of PC1 and PC2 shows the percent variation explained by the PCoA plot.

Figure 4

Biogeography of the gut microbiome in Landrace pigs. Principal coordinate analysis (PCoA) shows bacterial community structures based on Bray-Curtis distances. On the PCoA plot, each symbol represents one gut microbiome. (A) Microbiota in five intestinal segments in Landrace pigs. (B–E) show pair-wise comparison between the cecal microbiota vs the microbiota in the duodenum, jejunum, cecum and colon, respectively. (F) Microbiota in the duodenum and jejunum of Landrace pigs. The numbers of PC1 and PC2 shows the percent variation explained by the PCoA plot.

Figure 5

Biogeography of gut microbiome between Jinhua (circles) and Landrace (triangles) pigs. Principal coordinate analysis (PCoA) shows bacterial community structures based on Bray-Curtis distances. On the PCoA plot, each symbol represents one gut microbiome. (A) Gut microbiota in five intestinal segments in both Jinhua and Landrace pigs. (B–F) Pair-wise comparison (Jinhua vs Landrace) of the microbiota in duodenum, jejunum, ileum, cecum and colon, respectively. The numbers of PC1 and PC2 shows the percent variation explained by the PCoA plot.

Figure 6

Community composition of the gut microbiota in different intestinal segments of Jinhua and Landrace pigs at the phylum and genus levels, respectively.

Figure 7

Bacterial taxa differentially represented in ilum in Jinhua and Landrace pigs identified by LEFSe using a LDA score threshold of >2.0.

Figure 8

Predicted function of ileal microbiota between Jinhua (red bar) and Landrace (yellow bar) pigs. The third level of KEGG pathways were shown in the post-hoc plot. The significance of the gene distribution between the groups were performed using ANOVA test with a P value < 0.05.