[ODP4G] g. Omics, and Bioinformatics

[ODP-082/WS6-2] Single-cell level analysis of strain-level microbial diversity in human skin microbiome

○Tatsuya Saeki^1,2, Koji Arikawa^1,2, Takuya Yoda^1,2, Taruho Endoh¹, Keigo Ide^3,4, Masato Kogawa^3,4, Haruko Takeyama^2,3,4,5, Masahito Hosokawa^1,2,5 (¹bitBiome, Inc., ²Research Organization for Nano and Life Innovation, Waseda Univ., ³Dept. Life Science and Medical Bioscience, Waseda Univ., ⁴Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda Univ., ⁵Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda Univ.)

Human skin is colonized by a diverse microbial community. Recent studies have provided insights into their strain-level diversity associated with host skin health and diseases. These studies are conventionally conducted with culture-based microbial genome sequencing to recover whole-genome sequences of bacterial strains, limiting sample size and problems of cultivation bias. Although shotgun metagenomic sequencing is widely used to study uncultured microbes, it is difficult to reconstruct strain-level genomes from a complex mixture of fragmented genomic sequences.In this study, we applied the platform for single-cell genome sequencing of microbes, SAG-gel (Chijiiwa et al. 2020 Microbiome) or bit-MAP^®, to the human skin microbiome. Samples were collected by swabbing from the facial surfaces of healthy volunteers. Using bit-MAP^®, we obtained over 700 single-amplified genomes (SAGs) of single bacterial cells collected from 8 healthy males and females. From these, we have successfully obtained draft genome sequences of multiple strains of skin microbes. This enabled us to analyze the strain-level diversity of skin microbiome among individuals.Our bit-MAP^® generates a massive amount of SAGs without cultivation and enables strain-level analysis of skin microbiome. Such genomic data can accelerate the microbiome research for novel diagnostic and therapeutic approaches to skin disease.