Metagenomics and digital cell modeling facilitate targeted high‐throughput sorting of anaerobic hydrogen‐producing microorganisms
Year: 2025
Type: article
Abstract: This study proposes a novel strategy that prioritizes functional recognition, followed by targeted high-throughput sorting, to enable the comprehensive, rapid, and efficient acquisition of target microorganisms. Using metagenomic sequencing and binning analysis, we identified 215 potential anaerobic hydrogen-producing strains from 12 large-scale biogas samples. Digital cell models were subsequently constructed from metagenome-assembled genomes, which guided the design of 14 selective culture media for enriching these hydrogen-producing bacteria. Flow cytometry-based high-throughput sorting successfully isolated 81 potential anaerobic hydrogen-producing strains, achieving a target acquisition rate above 37% and a survival rate exceeding 70%. This method holds broad potential for the discovery and sorting of functional microorganisms across diverse environments and may ultimately facilitate the development of synthetic microbiomes for industrial applications.
Source: iMeta
DOI: 10.1002/imt2.70082
Authors: Jianfeng Liu, Wei Xing, Xingyang Zhang, Nengyao Xu, Ran Xu, Junsha Gong, Jia Zhang, Fengai Yang, Shuang Gao, Yanan Hou, Yongping Shan, Bin Liu, Qianqian Yuan, Aijie Wang, Nanqi Ren, Cong Huang
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,320
OpenAlex ID: W4414396308
