Correlations between gut microbiota community structures of Tibetans and geography

Abstract

Microbial communities of human gut directly influence health and bear adaptive potential to different geography environment and lifestyles. However, knowledge about the influences of altitude and geography on the gut microbiota of Tibetans is currently limited. In this study, fecal microbiota from 208 Tibetans across six different locations were analyzed by MiSeq sequencing; these locations included Gannan, Gangcha, Tianzhu, Hongyuan, Lhasa and Nagqu, with altitudes above sea level ranging from 2800 m to 4500 m across the Tibetan plateau. Significant differences were observed in microbial diversity and richness in different locations. At the phylum level, gut populations of Tibetans comprised Bacteroidetes (60.00%), Firmicutes (29.04%), Proteobacteria (5.40%), and Actinobacteria (3.85%) and were marked by a low ratio (0.48) of Firmicutes to Bacteroidetes. Analysis based on operational taxonomic unit level revealed that core microbiotas included Prevotella, Faecalibacterium, and Blautia, whereas Prevotella predominated all locations, except Gangcha. Four community state types were detected in all samples, and they mainly belong to Prevotella, Bacteroides, and Ruminococcaceae. Principal component analysis and related correspondence analysis results revealed that bacterial profiles in Tibetan guts varied significantly with increasing altitude, BMI, and age, and facultative anaerobes were rich in Tibetan guts. Gut microbiota may play important roles in regulating high-altitude and geographical adaptations.

Figure 1

Microbial diversity and richness in samples. (A–C) Chao index. (A) Different locations, (B) Altitude, (C) Ages; (D–F) Shannon index. (D) Different locations, (E) Altitude, (F) Ages. The small ‘abcd’ letters above the bars represent differences between groups, the same letter indicating that the difference is not significant, whereas the difference letter indicating that the difference is significant.

Figure 2

PCA analyses for detecting similarities between different samples. (A) Different locations, (B) Altitude, (C) BMI, (D) Ages.

Figure 3

VENN analyses among different locations.

Figure 4

LEfSe conducted based on bacterial community in all samples. (A) Different locations, (B) Altitude, (C) MBI, (D) Ages.

Figure 5

CCA of age, altitude, BMI, and location with community composition at the genus level.

Figure 6

Heat map of complete linkage clustering of samples based on genus composition and abundance in communities.

Figure 7

A map of sampling sites. Sampling sites are mapped using MapGIS 10.2 Desktop software (http://www.mapgis.com/index.php/index-view-aid-977.html, Chinese software).