Fine Classification of Human Gut Microbiota by Using Hierarchical Clustering Approach

Human microbiota account for 1-3 % total human body mass. The gastro-intestinal tract, especially the gut, is rich in different microorganisms, which play important role in our health and diseases. Understanding our gut microbiome may help us to increase the precision of disease prediction and treatment. Traditional culture-based methods are time-consuming, expensive and incomplete. The 16S rRNA metagenomic approach provided a simple and culture-independent way to get more information of gut microbiota. In this study, we analyzed 30 human stool microbiome samples. The hierarchical clustering method was applied to classify the enterotypes. The results showed that: (1) There is a positive correlation between the original NGS data volume, rRNA read number and microbiota diversity. (2) Some bacterial genera presented dominantly in human gut, so that a sufficient sequencing depth is important to identify the minor microbiota component. (3) Bacteroides, Lachnospiracea_incertae_sedis and Ruminococcus2 are the most frequently presented genera. Bacteroides, Prevotella and Alistipes are the most abundant genera. (4) Clustering result showed that there are four main enterotypes: Parabacteroides, Prevotella, Ruminococcus, and Bacterioides. We can still divide Parabacteroides into 3 subclasses according to the composition of bacteria.