Metagenomics and digital cell modeling facilitate targeted high-throughput sorting of anaerobic hydrogen-producing microorganisms

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.