The effect of exposure to high altitude and low oxygen on intestinal microbial communities in mice

Abstract

This experiment was conducted to investigate the effect of exposure to high altitude and low oxygen on intestinal microbial communities using mice as an animal model. Fecal microbiota from mice housed in a control environment representing 2,200 meters (NC group) above sea level with 16% Oxygen and mice that were placed in a hypobaric chamber representing 5000 meters (HC group) above sea level with 11% Oxygen for 30 days, were analyzed by the HiSeq Illumina sequencing platform. The results showed a significant difference in beta diversity observed between the two groups, while no significant difference was observed in alpha diversity. Compared with the NC group, the relative abundance of class Epsilonproteobacteria, phlym Actinobacteria, class Erysipelotrichia and genus Helicobacter were significantly lower (P<0.05), while the relative abundance of genus Alistipes was increased in the HC group; Phenotypic analysis showed no significant difference in aerobic, anaerobic, facultatively anaerobic, potentially pathogenic, stress tolerant, mobile element, biofilms formation, gram negative and gram positive between HC group and NC group; Functional analysis results showed significant differences in 34 gene functional metabolic pathways (carbohydrate digestion and absorption, energy metabolism, arachidonic acid metabolism, flavonoid biosynthesis, RIG-I-like receptor signaling pathway, etc) between HC group and NC group. Together, these findings suggest that exposure to high altitude and low oxygen had the potential to change the intestinal microbial communities, which potentially may modulate metabolic processes in mice.

Fig 1. Rarefaction analysis.

Rarefaction curves of OTUs clustered at 97% sequence identity across the sample. The sample labeled with NC1, NC2, NC3, NC4, NC5 and NC6 correspond to six replicates of NC group; HC1, HC2, HC3, HC4, HC5 and HC6 correspond to six replicates of HC group.

Fig 2

Non-Metric Multi-Dimensional Scaling (NMDS) plot (A) and ANOSIM analysis (B). NMDS is a simple method for visual interpretations to compare the overall structure of fecal microbiota between two samples while ANOSIM is used to statistically test the significant difference between groups.

Fig 3

Relative abundance of bacterial phyla (A) in fecal (Top 10), and statistical significance between two groups at phylum, class and genus levels (B). Phylogenetic groups accounting for unclassified sequences are summarized in the artificial group ‘others’. Statistical differences between two groups were tested using t-test. Differences were considered significant at P < 0.05.

Fig 4. Phenotypic prediction based on BugBase analysis.

BugBase is a bioinformatics tool that infers community-wide phenotypes, and predict phenotypic differences from 16S rRNA sequence data. BugBase identified that phenotypes associated with aerobic, anaerobic, facultatively anaerobic, potentially pathogenic, stress tolerance, mobile element, biofilms formation, gram negative bacteria and gram positive bacteria.

Fig 5. Bacterial gene functions were predicted from 16S rRNA gene-based microbial compositions using the PICRUSt algorithm to make inferences from KEGG annotated databases.

Data from PICRUSt were imported into the statistical analysis of metagenomic profiles (STAMP) (version 2.1.3) package for statistical analysis and visualization. Differences were considered significant at P < 0.05 using t-test.