Does Physical Inactivity Induce Significant Changes in Human Gut Microbiota? New Answers Using the Dry Immersion Hypoactivity Model

Abstract

Gut microbiota, a major contributor to human health, is influenced by physical activity and diet, and displays a functional cross-talk with skeletal muscle. Conversely, few data are available on the impact of hypoactivity, although sedentary lifestyles are widespread and associated with negative health and socio-economic impacts. The study aim was to determine the effect of Dry Immersion (DI), a severe hypoactivity model, on the human gut microbiota composition. Stool samples were collected from 14 healthy men before and after 5 days of DI to determine the gut microbiota taxonomic profiles by 16S metagenomic sequencing in strictly controlled dietary conditions. The α and β diversities indices were unchanged. However, the operational taxonomic units associated with the Clostridiales order and the Lachnospiraceae family, belonging to the Firmicutes phylum, were significantly increased after DI. Propionate, a short-chain fatty acid metabolized by skeletal muscle, was significantly reduced in post-DI stool samples. The finding that intestine bacteria are sensitive to hypoactivity raises questions about their impact and role in chronic sedentary lifestyles.

Keywords: commensal bacteria; disuse; flora; hypoactivity; micro-gravity; muscle atrophy; phyla; weightlessness.

Figure 1

Participants’ flow chart. Twenty men were recruited to undergo dry immersion for 5 days. Before randomization, two participants were excluded. The remaining 18 men were divided in two groups: Control group (n = 9) and Cuffs group (with thigh cuffs; n = 9). Stool samples were collected at DI-0 and DI-5 for gut microbiota analysis. DI-0 = before Dry Immersion initiation; DI-5 = day 5 of Dry Immersion.

Figure 2

Gut microbiota composition analysis by qPCR. (a) “All bacteria” abundance evaluated by qPCR before (DI-0) and after 5 days of dry immersion (DI-5) in healthy men (n = 14). (b) Mean abundance of the three main gut microbiota phyla quantified by qPCR at DI-0 and DI-5 in healthy men (n = 14). (c) Mean abundance of each phylum by qPCR normalized to the “all bacteria” abundance at DI-0 and DI-5 in healthy men (n = 14). No significant difference between DI-0 and DI-5 for all panels (paired t-test); p = Phylum. Data are mean ± SEM.

Figure 3

α and β diversity indices before (DI-0) and after 5 days of Dry Immersion (DI-5) in healthy men (n = 14). (a) α-diversity evaluated with the Observed, Chao1, Shannon and InvSimpson indices. The paired t-test did not find any significant difference between time points. (b) Individual α-diversity evaluated with the Observed, Chao1, Shannon and InvSimpson indices. (c) β-diversity analysis using the Jaccard (p = 0.998), Bray–Curtis (p = 0.997) and UniFrac (p = 0.999) indices indicated no difference between DI-0 and DI-5 in microbial OTU absence/presence, abundance, or phylogeny (PERMANOVA analysis). Data are mean ± SEM.

Figure 4

Abundance of phyla by 16S rRNA sequencing. (a) Individual abundance of the four main gut microbiota phyla in humans before (DI-0) and after 5 days of dry immersion (DI-5) in healthy men (n = 14). (b) Comparison (t-test) of the abundance of these four phyla at DI-0 and DI5 in healthy men (n = 14). (c) Clostridiales order abundance is significantly increased by DI. (d) Lachnospiraceae family abundance is increased by 5 days of dry immersion. p = Phylum; O = Order; F = Family; * p < 0.05; ** p < 0.01 (paired t-test). Data are mean ± SEM.

Figure 5

SCFA quantification in stool samples (n = 14) collected before (DI-0) and after 5 days of dry immersion (DI-5). * p < 0.05 (paired Student-t test). Data are mean ± SEM.