Gut microbiota contributes to high-altitude hypoxia acclimatization of human populations

Abstract

Background: The relationship between human gut microbiota and high-altitude hypoxia acclimatization remains highly controversial. This stems primarily from uncertainties regarding both the potential temporal changes in the microbiota under such conditions and the existence of any dominant or core bacteria that may assist in host acclimatization.

Results: To address these issues, and to control for variables commonly present in previous studies which significantly impact the results obtained, namely genetic background, ethnicity, lifestyle, and diet, we conducted a 108-day longitudinal study on the same cohort comprising 45 healthy Han adults who traveled from lowland Chongqing, 243 masl, to high-altitude plateau Lhasa, Xizang, 3658 masl, and back. Using shotgun metagenomic profiling, we study temporal changes in gut microbiota composition at different timepoints. The results show a significant reduction in the species and functional diversity of the gut microbiota, along with a marked increase in functional redundancy. These changes are primarily driven by the overgrowth of Blautia A, a genus that is also abundant in six independent Han cohorts with long-term duration in lower hypoxia environment in Shigatse, Xizang, at 4700 masl. Further animal experiments indicate that Blautia A-fed mice exhibit enhanced intestinal health and a better acclimatization phenotype to sustained hypoxic stress.

Conclusions: Our study underscores the importance of Blautia A species in the gut microbiota's rapid response to high-altitude hypoxia and its potential role in maintaining intestinal health and aiding host adaptation to extreme environments, likely via anti-inflammation and intestinal barrier protection.

Keywords: Blautia A; Hypoxia exposure; Intestinal health; Phenotype acclimatization; Time-series.

Fig. 1

Overview of high-altitude hypoxia exposure cohort and gut microbiota diversity characteristics. A Overview of study design, including longitudinal analysis of human fecal samples at seven timepoints. B–C Alpha diversity (Shannon and richness indices) of gut microbiota shows dynamic changes. D Intragroup Bray–Curtis distance at different timepoints. E Partial least squares discriminant analysis (PLS-DA) reveals significant differences in microbial community at different timepoints. F–H Alpha taxonomic diversity (TDα, via the Gini–Simpson index), alpha functional diversity (FDα, via Rao’s quadratic entropy), and alpha functional redundancy (FRα, as TDα minus FDα) were quantified at each timepoint using 1079 SGBs. For B–D and F–H, data represent the mean ± SE. Differences between specific timepoints and baseline are indicated with red lines. *P < 0.05, **P < 0.01, ***P < 0.001 by Wilcoxon rank sum test

Fig. 2

Time variations in gut microbiota composition of different taxa (phylum, genus, and species). Alluvial plot showing relative abundance dynamics in A six most abundant phyla and B 20 most abundant genera. Low-abundance taxa are grouped as “others”. Ordinate represents mean relative abundance at each timepoint. C Heat map showing detailed characteristics of 29 indicator species. Black box highlights details of 9 indicator SGBs from Blautia A genus. First column of left panel shows SGB IDs and corresponding genera of 29 indicator SGBs; second column shows group in which the indicator is enriched; third column shows significance of indicator SGBs (*P < 0.05, **P < 0.01, ***P < 0.001); last seven columns show fold changes in median abundance at each timepoint compared to baseline. Baseline group is set to 1. Middle panel shows log10(relative abundance) of each sample at 7 timepoints. “Indvl” in the right panel represents indicator values

Fig. 3

Dot plot showing enrichment of functional modules of 29 indicator SGBs at different timepoints. LS1, LS4, and CQ3 are not shown since no significant functional modules were enriched at these three timepoints. Left panel corresponds to KEGG metabolism categories. Dot size represents the number of enriched genes in functional modules. Dot color gradient reflects the magnitude of -log10(pFDR) value (Fisher’s exact test)

Fig. 4

Dynamics of core functional modules under different high-altitude hypoxia exposure stages based on 1079 SGBs. A Reaction steps of cobalamin biosynthesis. B Reaction steps of methanogenesis. KOs up-regulated or down-regulated (compared to the baseline) are in red or blue, respectively. KOs enriched in Blautia A genome are represented by solid line grid; missing KOs are represented by dotted line grid. The varying colors of the circles represent the classification of metabolites under the KEGG (Level 2) categorization

Fig. 5

Butyric acid production routes based on pan-genome analysis of Blautia A SGBs. Twelve high-quality Blautia A SGBs are used for pan-genome analysis. Several pan-genome pathway maps predicted by KEGG database are integrated. Compared with the background 1067 SGBs, the 12 SGBs of Blautia A is rich in the “Butanoate metabolism” pathway (pFDR = 0.03). The pink box in the ABC transporter column represents the polyol transport system substrate-binding protein that Blautia A can utilize. The orange background box represents the end product

Fig. 6

Gavage feeding of B. wexlerae suppresses intestinal inflammation and promotes high-altitude acclimatization.A Design of animal experiments. The three groups are as follows: (1) PBS-fed in normoxia for 8 weeks (NOR+PBS); (2) PBS-fed in normoxia for 4 weeks and hypoxia for another 4 weeks (HYP+PBS); (3) B. wexlerae-fed in normoxia for 4 weeks and hypoxia for another 4 weeks (HYP+Bw). B Peripheral oxygen saturation (SpO₂) of mice (n = 8 per group). C The quantification of pulmonary artery acceleration time (PAT) is converted by the formula [29] (detailed in “Methods”) (n = 6–7 per group). D Lung histological injury score of mice (n = 5 per group). E Representative H&E and Masson trichrome-stained of the mice lung sections (n = 5 per group). F Gross images of the mice distal ileum (n = 5 per group). G Representative H&E-stained sections of the mice distal ileum (n = 5 per group). H Statistical analysis of histological injury score of the mice distal ileum (n = 5 per group). I The relative mRNA expression levels of IL-1α and IL-1β in the ileum (n = 8 per group). J The relative mRNA expression level of ZO-1 in the ileum (n = 8 per group). Data are representative of at least three independent experiments (mean ± SE). *P < 0.05; **P < 0.01; ***P < 0.001; ns not significant (one-way ANOVA with Dunnett’s multiple comparisons test)