Age-associated changes of microbiota diversity in healthy captive crab-eating macaques
The metadata of 16s rRNA gene sequencing of fecal DNA was summarized in Table S1. Rarefaction analysis of observed operational taxonomic units (OTUs) indicated that the sequencing efficiently captured the potential total OTUs in the fecal samples (Fig. S1). The top five phyla observed in the fecal samples of crab-eating macaques were Firmicutes (44.5%-61.1%), Bacteroidetes (26.4%-39.8%), Epsilonbacteraeota (2.3%-8.0%), Proteobacteria (1.9%-3.8%), and Spirochaetes (1.0%-2.7%) (Fig. 1a), with Firmicutes and Bacteroidetes as the two dominant phyla. Furthermore, compared to infants, the Firmicutes to Bacteroidetes (F/B) ratio was found significantly increased in adults (all P < 0.05), especially in the middle-aged and elderly. (Fig. 1b). The F/B ratio was the lowest in infants (median = 1.09), and increased in young adults (median = 1.28). The highest B/F ratio was observed in the middle-aged (median = 2.74), which slightly decreased in the elderly (median = 2.06) with no significant difference.
Comparison of metrics including the Shannon (Fig. 1c) index, Pielou’s evenness, observed OTUs, phylogenetic diversity and Simpson index (Fig. S2), showed no significant change in alpha diversity among the age groups. In line with alpha diversity, the Venn diagram in Fig. 1d showed that 275 (94.18%) genera detected in more than six fecal samples were shared across different ages. As for beta diversity, principle coordination analysis (PCoA) based on the Bray-Curtis distance matrix showed that, the infant samples mainly clustered separately from the adult groups (Fig. 1e). The two older adult groups clustered together. The young adult samples fell in-between. Furthermore, permutational multivariate analysis of variance (PERMANOVA) results based on unweighted UniFrac distance indicated significant difference among the four age groups (Fig. 1f). The intergroup unweighted UniFrac distance between adults and infants showed a trend similar to the F/B ratio (median = 0.42, 0.47 and 0.46 in young, middle-aged and elderly adults respectively), compared to the intragroup distance in infants (median = 0.38). These results thus pointed to remarkable microbial community changes associated with age.
The top abundant gut microbial genera in the four age groups
We then focused on the most abundant genera. Our results showed a trend of age-associated changes in top abundant genera, similar to that of the beta diversity. The heatmap in Fig. 2a showed the top 20 abundant genera from each of the age groups, which were mainly commensals (Fig. 2b). Half of these genera were shared by all age groups (Fig. 2c), including four genera from family Ruminococcaceae (Ruminococcus 1, Ruminococcaceae UCG-005, Ruminococcaceae UCG-014, and Subdoligranulum), three genera from family Prevotellaceae (Prevotella 9, Prevotella 2, and Prevotellaceae UCG-003), Lactobacillus, Blautia, and Dialister.
We also looked into Bacteroides, which had been reported to be abundant in gut microbiota of humans living in developed countries . However, the genus show a low mean abundance less than 0.1% in our captive macaques (data not shown).
Correlation between differentially abundant gut microbes and age
To further determine age-associated gut microbes, we then identified OTUs with different abundance among age groups using STAMP (Fig. S3 and S4). The alluvial plots in Fig. 3a, 3b, 3c, 3d and 3e clearly illustrated age-associated shifts of these taxa at different phylogenetic levels. We further explored their correlation with age using Spearman correlation. At the phylum level (Fig. 3e and S4), Epsilonbacteraeota, Deferribacteres, Fusobacteria, Bacteroidetes, Patescibacteria, and Cyanobacteria were negatively associated with age, while Actinobacteria, Kiritimatiellaeota, Lentisphaerae, Firmicutes, WPS-2, Spirochaetes, Planctomycetes, Euryarchaeota, and Tenericutes were negatively associated with age. At the genus level, in total 115 genera were significantly associated with age, with 29 and 18 from family Lachnospiraceae and Ruminococcaceae respectively (Fig. S6). A large proportion of the genera negatively associated with age were from family Lachnospiraceae. The top 40 genera with the strongest correlations with age were shown in Fig. 3g. Among these microbes, 23 genera were negatively associated with age, most of which were potential commensals. These microbes includes night genera from family Lachnospiraceae (Lachnospiraceae UCG-001, Lachnospiraceae UCG-003, Lachnospiraceae UCG-004, Lachnospiraceae UCG-008, [Eubacterium] ventriosum group, Fusicatenibacter, GCA-900066575, [Ruminococcus] torques group, and Roseburia), two genera from family Prevotellaceae (Alloprevotella and Prevotella 2), two genera from family Ruminococcaceae (Faecalibacterium, and Fournierella), Actinobacillus, Campylobacter, Helicobacter, Mucispirillum, Veillonella, Cetobacterium, Brachyspira, and Gemella. These top age-associated genera also included seventeen genera positively associated with age, including six from the Ruminococcaceae family (Ruminococcaceae UCG-002, Ruminococcaceae UCG-010, Ruminococcaceae UCG-013, Ruminococcaceae NK4A214, CAG-352, and [Candidatus] Soleaferrea group), Treponema 2, Methanobrevibacter, the Rikenellaceae RC9 gut group, Christensenellaceae R-7 group, [Eubacterium] coprostanoligenes group, Lachnospiraceae UCG-007, Libanicoccus, Oscillibacter, Mogibacterium, and Stenotrophomonas.
In addition, we also found significantly correlation of with age in lactic acid bacteria known as probiotics in humans (Fig. S6). Bifidobacterium, which is important in breastfeeding, decreased with age (r = 0.34, P = 4.2 × 10-4), whereas Lactobacillus increased with age (r = 0.29, P = 0.0025).
Differential taxa of gut microbiota enriched in the four age groups
We then utilized LEfSe to identify differential taxa exclusively enriched in each of the four age groups. At the phylum level, Epsilonbacteraeota and Cyanobacteria were enriched in infants, Firmicutes, Actinobacteria, and Kiritimatiellaeota were enriched in the middle-aged, while Proteobacteria and Euryarchaeota were enriched in the elderly (Fig 4a). No phylum was enriched in young adults. At the genus level, the largest number (night-teen) of enriched genera were observed in infants, with helicobacter as the most enriched one (Fig. 4b). Other infant-enriched genera included seven genera from family Lachnospiraceae (Anaerostipes, Blautia, Dorea, Fusicatenibacter, Lachnospiraceae UCG-001, Lachnospiraceae UCG-004, and Roseburia), three genera from family Prevotellaceae (Alloprevotella, Prevotella 2, and Prevotellaceae UCG-001), five from family Ruminococcaceae (Butyricicoccus, Faecalibacterium, Fournierella, Ruminococcaceae UCG-008, and Subdoligranulum), Holdemanella, Phascolarctobacterium, and Sutterella. In contrast, Lactobacillus as the only one genus enriched in young adults. The middle-aged and the elderly had intermediate numbers of enriched genera. Seven genera were enriched in the middle-aged, including three genera from family Ruminococcaceae (Ruminococcaceae NK4A214 group, Ruminococcaceae UCG-002, and Ruminococcaceae UCG-010), Treponema 2, Rikenellaceae RC9 gut group, Christensenellaceae R-7 group, and Lachnospiraceae FCS020 group. Six genera were enriched in the elderly, including Prevotellaceae UCG_003, Megasphaera, Ruminococcaceae UCG-013, Coprococcus 3, and Desulfovibrio.
Age-associated gut microbiota networks and key driver genera
We then further used the Sparse Compositional Correlation (SparCC) analysis to explore the interaction among gut microbes in the four age groups (Fig. 5). All genera with relative abundance ≥ 0.1% were included in the networks. Surprisingly, although not preferentially selected, the age-associated genera were found to be the major components of these networks. The gut microbiota network in infants had the lowest connectivity of interactive in infants, as indicated by small Maximal Clique Centrality (MCC) scores (total MCC score = 56) (Fig. 5a and 6a). The network developed into a more mature stage in young adults (total MCC score = 274) (Fig. 5b and 6a), and had the highest connectivity in the middle-aged (total MCC score = 3688) (Fig. 5c and 6a). Unexpectedly, although similar gut microbiota diversities were found between the elderly and middle-aged, the network connectivity dramatically decreased in the elderly (total MCC score = 83) (Fig. 5d and 6a).
We then utilized cytoHubba to analyze hub genera, which were supposed to identified by ranking their centralities MCC and EcCentricity (EPC) scores. Among the hub genera shown in Fig. 6a, Prevotella 9 was the only one shared by all four age groups as well as the network constructed using all samples (Fig. 6a and 6b). The inter-genera interactions mediated by Prevotella 9 could be of potential importance. The strongest positive interactions in the microbial communities were found in Prevotella 2 and Alloprevotella with Prevotella 9 in infants. In addition to Prevotella 9, Helicobacter and Prevotella 2 were another two important hub genera in infants. The role of such interactions mediated by these genera, in particular Prevotella 9, gradually diminished with age, and were in part replaced by interactions mediated by hub genera negatively associated with age, such as Ruminococcaceae UCG-002 and Rikenellaceae RC9 gut group.
Moreover, we used NetShift analysis to detect rewiring between microbiota networks, and identified key driver microbes responsible for the changes (Fig. 6c and Table. S3). Prevotella 9 was found to be the only driver genus responsible for the microbial changes between infants and young adults. Novel interactions with Prevotella 9 were established in the gut microbiota of young adults compared to that of infants. As for adults, multiple potential drivers were identified. Among these drivers, Rikenellaceae RC9 gut group and Megasphaera are the two key driver genera that contribute to the long-term development of gut microbiota in adults. Another five genera including Dialister, Christensenellaceae R-7 group, [Eubacterium] coprostanoligenes group, Ruminococcaceae UCG-005 and Ruminococcaceae UCG-002 group are involved in the change of gut microbiota between young adults and the middle-aged. Another five genera including Ruminococcaceae UCG-014, Holdemanella, Succinivibrio, Alloprevotella, Lachnospiraceae UCG-007, and Prevotella 2 are involved in the change of gut microbiota between the middle-aged and the elderly.
Age-associated microbial phenotypes and functions and their correlations with gut microbiota
To understand the potential function impact of age-associated taxonomic changes in gut microbiota, the microbial phenotypes were predicted using BugBase and compared among age groups. Anaerobic and Gram-positive phenotypes was significantly up-regulated, whereas facultative anaerobic and Gram-negative phenotypes were down-regulated in the middle-aged and elderly groups compared to infants (all P < 0.01) (Fig. 7a). In line with these findings, Spearman correlation analysis showed that, the anaerobic and Gram-negative phenotypes significantly decreased (r = -0.37, P=1.2× 10-4 and r = -0.34, P = 4.3× 10-4 respectively) with age, whereas the facultative anaerobic and Gram-positive phenotypes significantly increased with age (r = 0.42, P = P = 8.7 × 10-6 and r = 0.34, P = 4.3 × 10-4 respectively) (Fig S6).
We also determined age-associated changes in gut microbial function using the software Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt), and identified 152 Kyoto Encyclopedia of Genes and Genomes (KEGG) modules to be significantly associated with age (Table. S2). The principle component analysis (PCA) plot derived from the abundance of KEGG modules revealed remarkable differences in microbial functions among age groups, showing a similar pattern with beta diversity (Fig. 7b). We observed significant correlation between these microbial functions and age. As shown in the heatmap in Fig. 7c, metabolic pathways that were the most positively associated with age were mainly involved in biosynthesis and metabolism of lipids and carbohydrates. And metabolic pathways that were the most negatively associated with age were mainly involved in biosynthesis of immunomodulating metabolites such as lipopolysaccharides, and metabolism of polyunsaturated fatty acids and vitamins such as folate and riboflavin. Noteworthy, strong correlations were found between these age-associated microbial functions and gut microbes, in particular the hub genera and drivers (Fig. S8). Prevotella 9, was the core genus that was involved in these functions.