Deciphering the human microbiome using next-generation sequencing data and bioinformatics approaches

Abstract

The human microbiome is one of the key factors affecting the host immune system and metabolic functions that are not encoded in the human genome. Culture-independent analysis of the human microbiome using metagenomics approach allows us to investigate the compositions and functions of the human microbiome. Computational methods analyze the microbial community by using specific marker genes or by using shotgun sequencing of the entire microbial community. Taxonomy profiling is conducted by using the reference sequences or by de novo clustering of the specific region of sequences. Functional profiling, which is mainly based on the sequence similarity, is more challenging since about half of ORFs predicted in the metagenomic data could not find homology with known protein families. This review examines computational methods that are valuable for the analysis of human microbiome, and highlights the results of several large-scale human microbiome studies. It is becoming increasingly evident that dysbiosis of the gut microbiome is strongly associated with the development of immune disorder and metabolic dysfunction.