2025-10-14 中国科学院(CAS)
AI-driven multi-phenotype, high-throughput cell screening platform – DCP. (Image by QIBEBT)
<関連情報>
- https://english.cas.cn/newsroom/research_news/life/202510/t20251014_1089412.shtml
- https://www.nature.com/articles/s41467-025-63929-7
マルチモーダル表現型による微生物株の分類のための AI 搭載ハイスループット デジタルコロニーピッカー プラットフォーム AI-powered high-throughput digital colony picker platform for sorting microbial strains by multi-modal phenotypes
Zhidian Diao,Qiqun Peng,Sijun Luo,Lingyan Kan,Anle Ge,Wei Gao,Runxia Li,Weiwei Bao,Xixian Wang,Yuetong Ji,Jian Xu,Shihui Yang & Bo Ma
Nature Communications Published:10 October 2025
DOI:https://doi.org/10.1038/s41467-025-63929-7
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 overexpression of ZMOp39x027, a canonical outer membrane autotransporter that promotes lactate transport and cell proliferation under stress. DCP provides a multi-modal phenotyping solution with spatiotemporal precision and scalable throughput, offering a generalizable strategy for accelerated strain engineering and functional gene discovery.
