Artificial intelligence‐assisted automatic and index‐based microbial single‐cell sorting system for One‐Cell‐One‐Tube. Issue 4 (18th December 2022)

• Record Type: Journal Article
• Authors: Diao, Zhidian; Kan, Lingyan; Zhao, Yilong; Yang, Huaibo; Song, Jingyun; Wang, Chen; Liu, Yang; Zhang, Fengli; Xu, Teng; Chen, Rongze; Ji, Yuetong; Wang, Xixian; Jing, Xiaoyan; Xu, Jian; Li, Yuandong; Ma, Bo
• Is Part Of: MLife. Volume 1:Issue 4(2022)
• Page Start: 448
• Page End: 459
• Publication Date: 2022-12-18
• Subjects: artificial intelligence -- One‐Cell‐One‐Tube (OCOT) -- single‐cell analysis -- single‐cell printing -- single‐cell sorting; Microbiology -- Periodicals; Microbiology; Periodicals; 579; 579
• DOI: 10.1002/mlf2.12047
• Languages: English
• ISSNs: 2770-100X

Abstract

Abstract: Identification, sorting, and sequencing of individual cells directly from in situ samples have great potential for in‐depth analysis of the structure and function of microbiomes. In this work, based on an artificial intelligence (AI)‐assisted object detection model for cell phenotype screening and a cross‐interface contact method for single‐cell exporting, we developed an automatic and index‐based system called EasySort AUTO, where individual microbial cells are sorted and then packaged in a microdroplet and automatically exported in a precisely indexed, "One‐Cell‐One‐Tube" manner. The target cell is automatically identified based on an AI‐assisted object detection model and then mobilized via an optical tweezer for sorting. Then, a cross‐interface contact microfluidic printing method that we developed enables the automated transfer of cells from the chip to the tube, which leads to coupling with subsequent single‐cell culture or sequencing. The efficiency of the system for single‐cell printing is >93%. The throughput of the system for single‐cell printing is ~120 cells/h. Moreover, >80% of single cells of both yeast and Escherichia coli are culturable, suggesting the superior preservation of cell viability during sorting. Finally, AI‐assisted object detection supports automated sorting of target cells with high accuracy from mixed yeast samples, which was validated by downstream single‐cell proliferation assays. The automation, index maintenance, and vitality preservation of EasySort AUTO suggest its excellent application potential for single‐cell sorting. Impact statement: In this work, we developed an automatic and index‐based system called EasySort AUTO for single‐cell identification and sorting of microbial cells. Under a positive‐mount microscope, target single cells are identified via image‐based artificial intelligence algorithms and then moved from cell populations via optical tweezers, followed by exportation to PCR tubes through an automatic collection platform. During this process, a single cell is packaged in a microdroplet and automatically exported in a precisely indexed, "One‐Cell‐One‐Tube" manner. As it is automated, index‐based, and vitality preserved, the EasySort AUTO system can find broad applications in supplying target single cells from microbiome samples for single‐cell sequencing or cultivation.