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, 19 (1), 236

Aging Progression of Human Gut Microbiota


Aging Progression of Human Gut Microbiota

Congmin Xu et al. BMC Microbiol.


Background: Human gut microbiota are important for human health and have been regarded as a "forgotten organ", whose variation is closely linked with various factors, such as host genetics, diet, pathological conditions and external environment. The diversity of human gut microbiota has been correlated with aging, which was characterized by different abundance of bacteria in various age groups. In the literature, most of the previous studies of age-related gut microbiota changes focused on individual species in the gut community with supervised methods. Here, we aimed to examine the underlying aging progression of the human gut microbial community from an unsupervised perspective.

Results: We obtained raw 16S rRNA sequencing data of subjects ranging from newborns to centenarians from a previous study, and summarized the data into a relative abundance matrix of genera in all the samples. Without using the age information of samples, we applied an unsupervised algorithm to recapitulate the underlying aging progression of microbial community from hosts in different age groups and identify genera associated to this progression. Literature review of these identified genera indicated that for individuals with advanced ages, some beneficial genera are lost while some genera related with inflammation and cancer increase.

Conclusions: The multivariate unsupervised analysis here revealed the existence of a continuous aging progression of human gut microbiota along with the host aging process. The identified genera associated to this aging process are meaningful for designing probiotics to maintain the gut microbiota to resemble a young age, which hopefully will lead to positive impact on human health, especially for individuals in advanced age groups.

Keywords: 16S rRNA sequencing; Aging; Human gut microbiota; Sample progression discovery.

Conflict of interest statement

The authors declare that they have no competing interests.


Fig. 1
Fig. 1
Sample overview using PCA. Using the relative abundance of 247 genera across all the 367 samples as input, we linearly transformed and visualized the data in a three-dimensional space. Each sample is represented by one dot, colored according to age. Samples from children younger than three (the dark blue dots) scattered most distantly, while older age groups were mixed together in the PCA space
Fig. 2
Fig. 2
SPD recovered aging progression with taxonomical composition of human gut microbiota. a Progression similarity matrix for all genera, with each element counting the number of progression orderings the two corresponding genera shared. b We manually picked the highlighted area from (a). These selected genera were consistent with a common set of putative progression orderings. c An overall minimal spanning tree of the 14 age groups based on the selected genera. Each node represents one age group
Fig. 3
Fig. 3
Genera that first increased and then decreased during aging, especially sharply decreased in the 13th or 14th age groups, or both
Fig. 4
Fig. 4
Genera that exhibited general increasing patterns during aging

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