A Cross-Sectional Study of Compositional and Functional Profiles of Gut Microbiota in Sardinian Centenarians

Abstract

Sardinia, Italy, has a high prevalence of residents who live more than 100 years. The reasons for longevity in this isolated region are currently unknown. Gut microbiota may hold a clue. To explore the role gut microbiota may play in healthy aging and longevity, we used metagenomic sequencing to determine the compositional and functional differences in gut microbiota associated with populations of different ages in Sardinia. Our data revealed that the gut microbiota of both young and elderly Sardinians shared similar taxonomic and functional profiles. A different pattern was found in centenarians. Within the centenarian group, the gut microbiota was correlated with the functional independence measurement of the host. Centenarians had a higher diversity of core microbiota species and microbial genes than those in the young and elderly. We found that the gut microbiota in Sardinian centenarians displayed a rearranged taxonomic pattern compared with those of the young and elderly, featured by depletion of Faecalibacterium prausnitzii and Eubacterium rectale and enriched for Methanobrevibacter smithii and Bifidobacterium adolescentis Moreover, functional analysis revealed that the microbiota in centenarians had high capacity for central metabolism, especially glycolysis and fermentation to short-chain fatty acids (SCFAs), although the gut microbiota in centenarians was low in genes encoding enzymes involved in degradation of carbohydrates, including fibers and galactose.IMPORTANCE The gut microbiota has been proposed as a promising determinant for human health. Centenarians as a model for extreme aging may help us understand the correlation of gut microbiota with healthy aging and longevity. Here we confirmed that centenarians had microbiota elements usually associated with benefits to health. Our finding of a high capacity of glycolysis and related SCFA production represented a healthy microbiome and environment that is regarded as beneficial for host gut epithelium. The low abundance of genes encoding components of pathways involved in carbohydrate degradation was also found in the gut microbiota of Sardinian centenarians and is often associated with poor gut health. Overall, our study here represents an expansion of previous research investigating the age-related changes in gut microbiota. Furthermore, our study provides a new prospective for potential targets for gut microbiota intervention directed at limiting gut inflammation and pathology and enhancing a healthy gut barrier.

Keywords: centenarian; gut microbiota; longevity; metagenomic sequencing.

FIG 1

Dynamic signature of gut microbiota components in the three age groups. (A) Relative abundance of the top 10 genera in the three age groups. Other low-abundant genera are summed into one group labeled “Subdominant_Sum.” The genera with significantly different distributions among the three age groups detected by ANOVA test (P < 0.05) are marked with an asterisk. (B) PCoA based on the Bray-Curtis distance derived from the relative abundance of the genus was plotted for the gut microbiota composition at the genus level. Ellipses with 95% confidence around the centroid of each age group are plotted in PCoA; the age groups are labeled C for the centenarian group, E for the elderly group, and Y for the young group. The genera that significantly correlated with the ordination in PCoA are shown as arrows (permutation test, P < 0.01), with the length of the arrow indicating the goodness of fit statistic, squared correlation coefficient. (C) Heatmap of the relative abundance of genera that are significantly correlated with the separation of the samples in PCoA in the three age groups. The base 10 logarithm of relative abundance was used as input, and complete linkage clustering was used. The distance matrix was created by the “Pearson” method. (D) Core microbiota species distribution in the three age groups. The core microbiota is defined as the species shared by more than 50% of the individuals in each age group. (E) Relative abundance of the species that showed significantly different distributions in the three age groups (Kruskal-Wallis followed by Dunn’s post-hoc multiple-comparison test, P < 0.05). Values that are significantly different are indicated by a bar and asterisks as follows: *, P < 0.05; **, P < 0.01.

FIG 2

Diversity of potential functional profiles of gut microbiota in the three age groups. (A and B) Boxplot of the distribution of KO richness (A) and of the distribution of KO Shannon diversity index (B). Variation between different age groups was detected by Kruskal-Wallis followed by Dunn’s post-hoc multiple-comparison test. Statistical significance symbols: *, P < 0.05; **, P < 0.01; ***, P < 0.001. (C and D) Dissimilarities of the functional profile of gut microbiota among the three age groups based on the Bray-Curtis distance derived from the relative abundance of KOs using PCoA (C) or derived from the relative abundance of gene pathways using NMDS (D).

FIG 3

Functional signatures of gut microbiota in the three age groups. Relative abundance of the gene pathways that are significantly different in the three age groups (ANOVA, P < 0.05). The centenarian group compared with the elderly group (C versus E [C/E]), the centenarian group compared with the young group (C versus Y [C/Y]), and the elderly group compared with the young group (E versus Y [E/Y]) are shown in each panel. The length of the bar indicates the base 2 logarithm value of the relative abundance ratio for each age group; 0 represents equal abundance in the two groups. Gene pathways are grouped in related pathways: central metabolism-related pathways (A), amino acid metabolism-related pathways (B), and carbohydrate degradation-related pathways (C).

FIG 3

Functional signatures of gut microbiota in the three age groups. Relative abundance of the gene pathways that are significantly different in the three age groups (ANOVA, P < 0.05). The centenarian group compared with the elderly group (C versus E [C/E]), the centenarian group compared with the young group (C versus Y [C/Y]), and the elderly group compared with the young group (E versus Y [E/Y]) are shown in each panel. The length of the bar indicates the base 2 logarithm value of the relative abundance ratio for each age group; 0 represents equal abundance in the two groups. Gene pathways are grouped in related pathways: central metabolism-related pathways (A), amino acid metabolism-related pathways (B), and carbohydrate degradation-related pathways (C).

FIG 4

Gut microbiota in centenarians correlates with clinical parameters. PCoA based on the Bray-Curtis distance derived from the relative abundance of species was plotted for the bacterial microbiota composition of centenarians at the species level. Each circle represents the value for an individual centenarian in PCoA, with the FIM index for the centenarian indicated by the color. Clinical parameters, including FIM (cognitive FIM [FIM_C] and motor FIM [FIM_M]), MMSE, MNA, BMI, age, and medication were used as factors to show correlation with the ordination configuration by EnvFit analysis. “Medication” indicates the number of drug types taken daily. The length of lines indicates the goodness of fit statistic, the squared correlation coefficient. The permutation test was used to test the significance of the fitness; the number of permutation was 999. Significance symbol: *, P < 0.05; **, P < 0.01.

FIG 5

The working model of gut microbiota in Sardinia centenarian. The schematic diagram showing the compositional and functional features in the gut microbiota in Sardinian centenarians that had a predicted longevity association. Observed high abundance (red) or low abundance (blue) of compositional (ellipse) and functional (round rectangle) features are shown. Potential metabolites (in orange triangles) released by the gut microbes and proposed possible contributions of the gut microbes to metabolites (dotted curve) and metabolic functions (arrow) are shown.