3.1. Three enterotypes were identified in the gut microbiome of elderly individuals.
In this study, we performed a metagenomics-based enterotype analysis in a cohort of 367 enrolled Chinese seniors between the ages of 60 and 94 years. After bioinformatic analyses, taxonomic assignment showed that 98.995%, 0.736%, 0.101%, and 0.001% of the sequencing reads corresponded to the domains Bacteria, Viruses, Archaea, and Eukaryota, respectively. Using JSD distance and the PAM clustering algorithm, we identified three enterotypes in this cohort (Supplementary Figure S1A). The predominant species identified by fivefold cross-validation analysis using a random forest model were Prevotella copri and Prevotella stercorea in enterotype 1 (designated ET-P. copri), Bacteroides uniformis and Bacteroides coprocola in enterotype 2 (designated ET-Bacteroides spp.) and E. coli in enterotype 3 (designated ET-E. coli) (Figure 1A and 1B). The gut microbial communities of the E. coli-dominated enterotype exhibited a distinctive taxonomic profile compared with those of ET-P. copri and ET-Bacteroides spp. (Figure 1C-1F). For β-diversity analysis, principal coordinate analysis (PCoA) plots demonstrated that sample clustering at the order level did not result in a notable separation between ET-P. copri and ET-Bacteroides spp., but most ET-E. coli samples were well separated from these other enterotypes (Supplementary Figure S1B), the separation of all three enterotypes became clearer with clustering at the species level (Supplementary Figure S1C). The 25 most dominant taxa showed significantly different abundance patterns across enterotypes (Supplementary Figure S2). Notably, F. prausnitzii, a key anti-inflammatory bacterium that is depleted in early frailty[17], was found to be significantly enriched in ET-P. copri but depleted in ET-E. coli, accounting for 8.31% of ET-P. copri, 6.88% of ET-Bacteroides spp. and 3.20% of ET-E. coli (Supplementary Figure S2B). The taxonomic differences across enterotypes are further summarized in Additional file 1. Overall, these results demonstrated enterotype variation in some older persons, characterized by a remarkable enrichment of E. coli in their gut microbiomes.
3.2. Enterotype variation in the older Chinese population is associated with older age.
To better understand the associations between enterotypes and health status in the elderly population, we examined 28 variables as potentially significant microbiota covariates, including demographic factors (2), chronic noncommunicable diseases (10), sleep time per day, habitual long-term diet information (11), and participation in physical work, daily indoor exercising, or outdoor sports (4). The RDA showed that age, frailty, sarcopenia, T2DM, and fruit consumption had a higher impact on ET-E. coli samples, while vegetable consumption and other potential covariates had opposite effects on gut community composition (Figure 2A). Among the variables tested in this study, the results of PERMANOVA clearly suggested that age was the strongest factor associated with the overall microbiota composition, with 3.61% explained variance (Adonis analysis calculated based on Bray–Curtis similarity, P < 0.001, Figure 2B). Additional variables achieving significance, in order, were constipation, egg consumption, bone loss, T2DM, vegetable consumption, gastrointestinal disturbances, soy consumption, and stroke. Our results indicated that the enterotype prevalence in the elderly population is related to age. Specifically, ET-P. copri was the most prevalent enterotype among people younger than 75 years of age, whereas people over 75 years of age tended to harbor ET-E. coli or ET-Bacteroides spp. The prevalence of the E. coli-dominant enterotype tended to increase dramatically with age. ET-Bacteroides spp. was present at similar rates across all ages studied (Figure 2C). Deployment of piecewise linear regression analysis enabled us to visualize a clear difference in the age-related trajectories of representative blood inflammatory and nutritional marker levels among enterotypes. Many of them showed generally different trends of associations with age in the older adults with ET-Bacteroides spp. or ET-E. coli, characterized by different slopes and age breakpoints of the relationships (Figure 2D), suggesting the inconsistent pace of aging in the individuals with different enterotypes.
We next integrated the Spearman correlation coefficients with other statistical analyses to quantify the associations between key distinguishing bacterial species for the three enterotypes with each variable (Figure 2E). The data showed that potential covariates explained 14.53% of the variation in abundance for P. copri across individuals but only 4.51% for E. coli, indicating that the abundance of P. copri in the elderly population is more susceptible to external influences. In addition to age, the relative abundance of unclassified Escherichia was positively correlated with fruit intake but negatively correlated with vegetable intake and constipation. These results indicated that the altered gut microbiome in older age might be a result of long-term adaptation to accumulated changes in dietary habits, gut physiology, and gastrointestinal motility.
3.3. Distinctive pattern of the microbial co-occurrence network in ET-E. coli.
Most microorganisms living in the gut are auxotrophs whose growth relies both on external nutrients obtained from the diet or metabolism of the host and the exchange of electron donors, amino acids, vitamins, and other cofactors with other microbes[29]. Thus, a robust steady-state bacterial consortium is formed in the co-occurrence community based on cooperative interactions for low metabolic costs and efficiency within member species. In this study, co-occurrence network analysis was performed to predict biotic interactions such as resource competition and metabolic cross-feeding within the residing microbial community, as revealed by negative edges and positive edges, respectively. We investigated the difference in co-occurrence communities of the three enterotypes to look for potential influencing factors linked to transitions between the enterotypes (Figure 3). Approximately 82-145 species (nodes) and 117-502 connections (edges) were retained at a correlation cutoff of 0.4 in the co-occurrence network for an enterotype, and most nodes and edges were specific to each enterotype (Supplementary Figure S3). The maximum number of unique nodes and edges was found in the co‐occurrence network of ET-E. coli, which exhibited a highly complex co‐occurrence network (Figure 3A).
There was a significant difference among the network-level topological features of the co‐occurrence networks of the three enterotypes, including degree assortativity, average path length, and betweenness centralization (Kolmogorov–Smirnov test, P < 0.001, Additional file 2). Fourteen nodes with NESH score values > 2 were considered the key drivers facilitating the main changes between co-occurrence networks, and most of them showed significantly different enrichment or depletion across enterotypes, except Lactobacillus salivarius and Streptococcus salivarius (Supplementary Figure S4). To identify key factors affecting the diversity and stability of the human microbiome, external influencing factors were assessed based on their correlations with these fourteen key drivers and topological features. For the microbial network of ET-Bacteroides spp., constipation was positively correlated with average path length (Spearman’s r = 0.335, P <0.01) and negatively correlated with degree assortativity (Spearman’s r =-0.32, P <0.01). Interestingly, opposite associations with degree assortativity were also observed for vegetable and fruit consumption (Spearman’s r=-0.334, P <0.01, for vegetable consumption and Spearman's r= 0.304, P <0.01, for fruit consumption). Similarly, the relative abundance of S. salivarius was positively correlated with age and fruit consumption in seniors and negatively correlated with constipation and vegetable consumption (Spearman's r = 0.31, P <0.0001, for age, Spearman's r = -0.37, P <0.0001, for constipation, Spearman's r = -0.34, P <0.0001, for vegetable consumption, and Spearman's r= 0.33, P <0.0001, for fruit consumption). These results suggest that constipation symptoms and preference between fruits or vegetables may contribute to variations in microbial co-occurrence networks in different enterotypes by changing the interactions among several specific microbes, such as S. salivarius (Supplementary Figure S5).
To investigate the bacterial consortia in each co-occurrence community, we analyzed the five main microbial community groups (group I to group V) of co-occurring species that appeared across enterotypes, whose total members accounted for 36% of the nodes in ET-P. copri, 44% in ET-Bacteroides spp., and 45% in ET-E. coli (Supplementary Figure S6A). We found that these main microbial community groups consisted mainly of taxa from the same or closely related species (Supplementary Figure S6B). Specifically, 13 species appeared in group I across all three enterotypes, mainly from the genera Streptococcus, Veillonella, Granulicatella, Lactobacillus, and Rothia, 6 species mainly from the genus Alistipes in group II, and 7 species mainly from the genera Clostridium, Blautia, Coprobacillus, and Flavonifractor in group III. The main microbial community groups in ET-Bacteroides spp. and ET-P. copri consisted of similar components, suggesting high community homogeneity in their co-occurrence network when compared with that of ET-E. coli. In line with that hypothesis, the nodes of ET-E. coli showed significantly higher NESH scores than those of ET-Bacteroides spp. or ET-P. copri (Wilcoxon test, P < 0.001, Additional file 3 and Supplementary Figure S7). Notably, there were more oral microbes in co-occurrence group I of ET-E. coli co‐occurrence network.
The stability of the microbial co-occurrence network was quantified by the robustness of the microbial networks via a natural connectivity analysis. The data showed that the gut microbial network of ET-E. coli had the highest robustness and the strongest cohesion (Figure 3B-3E). In addition, ET-E. coli exhibited the lowest α-diversity indexes among the three enterotypes and the exclusive growth of one single co-occurrence group in an older individual, implying that many more out-group species were suppressed by a strong colonization resistance in ET-E. coli (Figure 3F-3H and Supplementary Figure S8). However, within ET-E. coli samples, Spearman’s test showed a significantly positive correlation between the positive cohesion value and Shannon index, suggesting that the more microbes that benefited from cooperative interactions within a group, the lower the potential risk of extinction due to environmental degradation (Figure 3I).
3.4. Gut microbial function differences among enterotypes.
For this analysis, genes were grouped based on functional pathways. We found that PAM clustering of ET-E. coli samples was also supported based on microbial functional profiles. Most ET-E. coli samples grouped into a cluster discrete from the cluster consisting of the adult-like enterotype ET-P. copri and ET-Bacteroides spp. samples (Figure 4A). The distinct functionality of the gut microbiome dominated by E. coli is shown in the heatmap in Supplementary Figure S9. Obviously, the functional profile of ET-E. coli varied markedly from those of ET-Bacteroides spp. and ET-P. copri. Our data showed that 319 of 431 microbial metabolic pathways presented statistically significant differences among the three enterotypes, as identified by the Wilcoxon rank-sum test (Figure 4B, Additional file 4). Of the 158 pathways with 100% prevalence in the cohort, 128 pathways presented significant differences in their abundance among enterotypes (Figure 4C). Overall, the core microbial functionality that facilitates bacterial survival is performed by generally different functional pathways in ET-E. coli and the adult-like enterotypes, with involvement of all metabolic categories (Supplementary Figure S10).
We next investigated the patterns of age-associated changes in the functional profile in each enterotype. The trend of the decreased relative abundance of metabolic pathways, such as glycolysis, glycerol degradation, stachyose degradation, and purine ribonucleoside degradation, with age was similar in ET-Bacteroides spp. and ET-P. copri. The relative abundance of several amino acid biosynthesis pathways involved in L-threonine, L-lysine, L-arginine, and L-ornithine biosynthesis diminished with age in ET-P. copri but gradually increased with age in ET-Bacteroides spp. and ET-E. coli (Figure 4D).
The SPIEC-EASI method was utilized to identify functional modules that were constructed by coabundant functional pathways (Figure 4E). Module I consisted of the highly abundant and highly prevalent functional pathways that were significantly enriched in the two adult-like enterotypes (ET-P. copri and ET-Bacteroides spp.), suggesting their particular importance for the core functionality of the human gut microbiome, whereas module II was composed mainly of the functional pathways significantly enriched in ET-E. coli, featuring many functional pathways involving cofactor, carrier, and vitamin biosynthesis (Supplementary Figure S9). Interestingly, vast negative correlations existed between most ET-P. copri-enriched pathways and five ET-Bacteroides spp.-enriched pathways in module I with some ET-E. coli-enriched pathways in module II, which indicated the potential participation of these microbial functions in the competition between the predominant bacteria of the enterotypes. The 336 negative correlations (edges) are listed in Additional file 5.
3.5. Factors associated with enterotype variations in the older population.
To investigate the factors associated with enterotype variations, especially for the overgrowth of E. coli in older individuals, we further analyzed differences in species–pathway and species–host associations among the three enterotypes. Application of Spearman correlation coefficient analysis showed that members of co-occurrence group I (mainly from Streptococcus and Veillonella) generally might have a niche overlap with Enterobacteriaceae members (e.g., Klebsiella pneumoniae, Enterobacter cloacae, E. coli, and unclassified Escherichia), who presented growth optima involving various metabolic pathways (Figure 5). Their close relationship existed in all enterotypes. In contrast, only in ET-P. copri, it was found that nine metabolic biosynthesis pathways showed a positive correlation with P. copri but a negative correlation with E. coli, suggesting their potential roles in the competition between microbes. These nine pathways were including queuosine, UMP, L-lysine (L-lysine biosynthesis III and L-lysine biosynthesis VI), and aromatic amino acid biosynthesis. We also observed similar relationships of E. coli with F. prausnitzii linked by genes involved in L-isoleucine biosynthesis I and Megamonas unclassified linked by genes involved in Calvin-Benson-Bassham cycle, pentose phosphate pathway (non oxidative branch), and stachyose degradation. These results indicated the growth of E. coli might be suppressed in ET-P. copri via a niche pre-emption generated by P. copri, F. prausnitzii, and Megamonas unclassified.
We further analyzed the correlation between the relative abundances of metabolic pathways and age and other external influencing factors (Figure 6). Consistent with the apparent age-associated increase in the relative abundance of several amino acid biosynthesis pathways involved in L-threonine, L-lysine, L-arginine, and L-ornithine biosynthesis in the enterotypes dominated by Bacteroides spp. and E. coli, significant positive correlations of these pathways with age were confirmed in the whole cohort using Spearman’s rank correlation test. Interestingly, inverse associations were observed in two polyamine biosynthesis pathways and two functional pathways involving the biosynthesis of proinflammatory components of bacterial wall components, such as O-antigen and UDP-N-acetyl-D-glucosamine, and their correlations with age and vegetable consumption were also inverted. In addition to two functional pathways involved in cell structure biosynthesis, most of the functional pathways involved in amino acid biosynthesis (except L-lysine biosynthesis) were positively correlated with age and fruit consumption but negatively correlated with vegetable consumption. Notably, the relative abundance of two functional pathways involved in L-lysine biosynthesis (L-lysine biosynthesis III and L-lysine biosynthesis VI) was negatively associated with age and frailty and positively associated with vegetable, milk, and soy food consumption.