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Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing

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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.

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Acknowledgments

This work was supported by the Gachon University research fund of 2019 (GCU-2019-0319).

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Authors and Affiliations

  1. Department of Health Sciences and Technology, Gachon University, Incheon, 21999, Republic of Korea

    Hyojung Kim & Sungwon Jung

  2. Gachon Institute of Genome Medicine and Science, Gachon University Gil Medical Center, Incheon, 21565, Republic of Korea

    Sora Kim & Sungwon Jung

  3. Department of Genome Medicine and Science, Gachon University College of Medicine, Incheon, 21565, Republic of Korea

    Sungwon Jung

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  1. Hyojung Kim
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  2. Sora Kim
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  3. Sungwon Jung
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Correspondence to Sungwon Jung.

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Kim, H., Kim, S. & Jung, S. Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing. J Microbiol. 58, 193–205 (2020). https://doi.org/10.1007/s12275-020-9556-y

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