Analysis of microbial dynamics in the soybean root-associated environments from community to single-cell levels

Masako Kifushi; Yohei Nishikawa; Masahito Hosokawa; Keigo Ide; Masato Kogawa; Toyoaki Anai; Haruko Takeyama

doi:10.1016/j.jbiosc.2024.02.007

Analysis of microbial dynamics in the soybean root-associated environments from community to single-cell levels

J Biosci Bioeng. 2024 Apr 2:S1389-1723(24)00077-X. doi: 10.1016/j.jbiosc.2024.02.007. Online ahead of print.

Authors

Masako Kifushi¹, Yohei Nishikawa², Masahito Hosokawa³, Keigo Ide¹, Masato Kogawa⁴, Toyoaki Anai⁵, Haruko Takeyama⁶

Affiliations

¹ Graduate School of Advanced Science and Engineering, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan; Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan.
² Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan; Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan.
³ Graduate School of Advanced Science and Engineering, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan; Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan; Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan; Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan.
⁴ Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan.
⁵ Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan.
⁶ Graduate School of Advanced Science and Engineering, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan; Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan; Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan; Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. Electronic address: haruko-takeyama@waseda.jp.

PMID: 38570219
DOI: 10.1016/j.jbiosc.2024.02.007

Abstract

Plant root-associated environments such as the rhizosphere, rhizoplane, and endosphere, are notably different from non-root-associated soil environments. However, the microbial dynamics in these spatially divided compartments remain unexplored. In this study, we propose a combinational analysis of single-cell genomics with 16S rRNA gene sequencing. This method enabled us to understand the entire soil microbiome and individual root-associated microorganisms. We applied this method to soybean microbiomes and revealed that their composition was different between the rhizoplane and rhizosphere in the early growth stages, but became more similar as growth progressed. In addition, a total of 610 medium- to high-quality single-amplified genomes (SAGs) were acquired, including plant growth-promoting rhizobacteria (PGPR) candidates while genomes with high GC content tended to be missed by SAGs. The whole-genome analyses of the SAGs suggested that rhizoplane-enriched Flavobacterium solubilizes organophosphate actively and Bacillus colonizes roots more efficiently. Single-cell genomics, together with 16S rRNA gene sequencing, enabled us to connect microbial taxonomy and function, and assess microorganisms at a strain resolution even in the complex soil microbiome.

Keywords: Bioinformatics; Plant growth-promoting rhizobacteria; Rhizosphere; Single-cell genomics; Soil microbiome; Soybean.