Title Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing
Author Hyojung Kim1, Sora Kim2, and Sungwon Jung1,2,3*
Address 1Department of Health Sciences and Technology, Gachon University, Incheon 21999, Republic of Korea, 2Gachon Institute of Genome Medicine and Science, Gachon University Gil Medical Center, Incheon 21565, Republic of Korea, 3Department of Genome Medicine and Science, Gachon University College of Medicine, Incheon 21565, Republic of Korea
Bibliography Journal of Microbiology, 58(3),193-205, 2020,
DOI 10.1007/s12275-020-9556-y
Key Words microbiome, next-generation sequencing, 16S rRNA, bioinformatics, software pipeline
Abstract Recent studies on microbiome highlighted their importance in various environments including human, where they are involved in multiple biological contexts such as immune mechanism, drug response, and metabolism. The rapid increase of new findings in microbiome research is partly due to the technological advances in microbiome identification, including the next-generation sequencing technologies. Several applications of different next-generation sequencing platforms exist for microbiome identification, but the most popular method is using short-read sequencing technology to profile targeted regions of 16S rRNA genes of microbiome because of its low-cost and generally reliable performance of identifying overall microbiome compositions. The analysis of targeted 16S rRNA sequencing data requires multiple steps of data processing and systematic analysis, and many software tools have been proposed for such procedures. However, properly organizing and using such software tools still require certain level of expertise with computational environments. The purpose of this article is introducing the concept of computational analysis of 16S rRNA sequencing data to microbiologists and providing easy-to-follow and step-by-step instructions of using recent software tools of microbiome analysis. This instruction may be used as a quick guideline for general next-generation sequencing-based microbiome studies or a template of constructing own software pipelines for customized analysis.