{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Diao Z"],"funding":["National Natural Science Foundation of China (National Science Foundation of China)"],"pagination":["8769"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12514280"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_abstract":["Phenotype-based screening remains a major bottleneck in the development of microbial cell factories. Here, we present a Digital Colony Picker (DCP), an AI-powered platform for automated, high-throughput screening and export of microbial clones based on growth and metabolic phenotypes at single-cell resolution, without agar or physical contact. Using a microfluidic chip comprising 16,000 addressable picoliter-scale microchambers, individual cells are compartmentalized, dynamically monitored by AI-driven image analysis, and selectively exported via laser-induced bubble technique. Applied to Zymomonas mobilis, DCP enabled en masse screening and identified a mutant with 19.7% increased lactate production and 77.0% enhanced growth under 30 g/L lactate stress. This phenotype was linked to overex"],"journal":["Nature communications"],"pubmed_title":["AI-powered high-throughput digital colony picker platform for sorting microbial strains by multi-modal phenotypes."],"pmcid":["PMC12514280"],"funding_grant_id":["32030003","32170103","32370098","32470087"],"pubmed_authors":["Bao W","Kan L","Li R","Xu J","Ma B","Diao Z","Peng Q","Gao W","Wang X","Ji Y","Luo S","Yang S","Ge A"],"additional_accession":[]},"is_claimable":false,"name":"AI-powered high-throughput digital colony picker platform for sorting microbial strains by multi-modal phenotypes.","description":"Phenotype-based screening remains a major bottleneck in the development of microbial cell factories. Here, we present a Digital Colony Picker (DCP), an AI-powered platform for automated, high-throughput screening and export of microbial clones based on growth and metabolic phenotypes at single-cell resolution, without agar or physical contact. Using a microfluidic chip comprising 16,000 addressable picoliter-scale microchambers, individual cells are compartmentalized, dynamically monitored by AI-driven image analysis, and selectively exported via laser-induced bubble technique. Applied to Zymomonas mobilis, DCP enabled en masse screening and identified a mutant with 19.7% increased lactate production and 77.0% enhanced growth under 30 g/L lactate stress. This phenotype was linked to overex","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Oct","modification":"2026-06-04T08:42:45.004Z","creation":"2026-05-07T03:09:14.418Z"},"accession":"S-EPMC12514280","cross_references":{"pubmed":["41073418"],"doi":["10.1038/s41467-025-63929-7"]}}