<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Diao Z</submitter><funding>National Natural Science Foundation of China (National Science Foundation of China)</funding><pagination>8769</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12514280</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>16(1)</volume><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</pubmed_abstract><journal>Nature communications</journal><pubmed_title>AI-powered high-throughput digital colony picker platform for sorting microbial strains by multi-modal phenotypes.</pubmed_title><pmcid>PMC12514280</pmcid><funding_grant_id>32030003</funding_grant_id><funding_grant_id>32170103</funding_grant_id><funding_grant_id>32370098</funding_grant_id><funding_grant_id>32470087</funding_grant_id><pubmed_authors>Bao W</pubmed_authors><pubmed_authors>Kan L</pubmed_authors><pubmed_authors>Li R</pubmed_authors><pubmed_authors>Xu J</pubmed_authors><pubmed_authors>Ma B</pubmed_authors><pubmed_authors>Diao Z</pubmed_authors><pubmed_authors>Peng Q</pubmed_authors><pubmed_authors>Gao W</pubmed_authors><pubmed_authors>Wang X</pubmed_authors><pubmed_authors>Ji Y</pubmed_authors><pubmed_authors>Luo S</pubmed_authors><pubmed_authors>Yang S</pubmed_authors><pubmed_authors>Ge A</pubmed_authors></additional><is_claimable>false</is_claimable><name>AI-powered high-throughput digital colony picker platform for sorting microbial strains by multi-modal phenotypes.</name><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</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Oct</publication><modification>2026-06-04T08:42:45.004Z</modification><creation>2026-05-07T03:09:14.418Z</creation></dates><accession>S-EPMC12514280</accession><cross_references><pubmed>41073418</pubmed><doi>10.1038/s41467-025-63929-7</doi></cross_references></HashMap>