Altitude-adaption of gut microbiota in Tibetan chicken

Abstract

Low oxygen levels and extremely cold weather in high-altitude environments requires more energy intake to maintain body temperature in animals. However, little is known about the characteristics of cecal and ileac microbiota in Tibetan chicken and how the high and low altitude environments affect the gut microbiota communities in Tibetan chicken. In the present study, In the present study, Tibetan chickens (Group HA, 3572 m, 578.5 Pa) and their introduced flatland counterparts (Group LA, 580 m, 894.6 Pa) in the cecum and ileum to identify the possible bacterial species that are helpful for their host in environmental adaption. High-throughput sequencing was used to sequence the V3 to V4 hypervariable regions of the bacterial 16S rRNA gene. By comparing the gut microbial diversity of HA chicken with that of LA, the results indicated that the microbial diversity of the cecum and ileum in group HA was significantly lower (P < 0.05) than those in group LA. The cecum microbiome maintained higher population diversity and richness than the ileum (P < 0.05). Four phyla Firmicutes, Bacterioidetes, Actinobacteria, and Proteobacteria were dominant in two groups. Interestingly, there were significant differences in abundance ratio among the four groups (P < 0.05). The predominant bacteria in HA and LA ileum belong to Proteobacteria and Firmicutes, whereas in cecum, Bacterioidetes and Actinobacteria were predominant in both groups (P < 0.05). Correlation analysis showed that Sporosarcina, Enterococcus, and Lactococcus were strongly related to air pressure, and Peptoclostridium and Ruminococcaceae_UCG-014 are related to altitude and gut microbiota of LA group was influenced by altitude, while HA group affected by air pressure. Meanwhile, the Ruminococcus-torques-group was negatively correlated with the relative abundance of Paenibacillus, and positive correlated with those of other microorganisms. Furthermore, HA has higher abundance of microbiota involved in energy and glycan biosynthesis metabolism pathway, while LA has higher abundance of microbiota involved in membrane transport, signal transduction, and xenobiotics biodegradation and metabolism. Generally, our results suggested that the composition and diversity of gut microbes changed after Tibetan chickens were introduced to the plain. Tibetan chicken may adapt to new environment via reshaping the gut microbiota. Gut microbes may contribute to the host adaption to high altitude environments by increasing host energy and glycan biosynthesis.

Keywords: 16S rRNA; Tibetan chicken; environment; gut microbiota; high-altitude adaption.

Figure 1

Microbial diversity and composition of cecum and ileum of chickens in HA and LA groups. HC and HI = the cecum and ileum of birds living in high altitude; LC and LI = the cecum and ileum of birds living in low altitude. *P < 0.05 and **P < 0.01.

Figure 2

Principal Coordinate Analysis (PCoA) of the community membership (A) and structure (B) using Jaccard and Bray Curtis distances, respectively. Red squares and circles represent HA Tibetan chickens’ cecum and ileum bacterial communities, green squares and circles represent LA Tibetan chickens’ cecum and ileum bacterial communities, respectively. Distances between symbols on the ordination plot reflect relative dissimilarities in community memberships or structures.

Figure 3

Relative abundance of top 20 OTUs at the phylum (A) and genus (B) level in ileal and cecal microbiota from HA and LA chickens. HC and HI = the cecum and ileum of birds living in high altitude; LC and LI = the cecum and ileum of birds living in low altitude.

Figure 4

Taxon's abundances between cecum and ileum of Tibetan chickens identified by linear discriminant analysis (LDA) coupled with effect size (LDA > 4) were shown in Part A and B (P < 0.05). The relative abundance of Bacteroidetes at genus level (g_Bacteroidetes) was compared among the four groups, shown in Part C. Microbiota abundances between different altitude birds was shown in Part D; some differentially distributed bacteria: e. g., f_Bifidobacterium and g_Lactobacillus were illustrated in Part D, respectively.

Figure 5

Canonical correspondence analysis of intestinal microbiota from Tibetan chickens responding to environmental factors. The scales on the horizontal and vertical coordinates were the values produced by sample or species when performing regression analysis with environmental factors; the dots represented samples; the red font indicated the top ten microbiota species at genus level; the blue and green arrows represent environmental factors, altitude and air pressure, respectively.

Figure 6

Network diagram is a form of correlation analysis at the genus level (r > 0.1). Circle represents the species, circle size represents the expression abundance of species; lines represent the correlation between the two species, line thickness represents the strength of the correlation, line color: orange represents positive correlation, green represents negative correlation.

Figure 7

Analysis of the differences in KEGG metabolic pathways between groups at class level. The left side of the graph indicated the ratios of abundance of samples LI to HI (Upper), and of samples HC to LC (Lower) in different functions. The right side of the graph shows the proportions of functional abundance in 95% confidence interval, respectively.

Figure 8

The body weight of the chickens in HA and LA groups were measured at 0, 2, 3, 4, and 6 weeks.*Difference in two groups (P<0.05).