Artificial intelligence‐assisted automatic and index‐based microbial single‐cell sorting system for One‐Cell‐One‐Tube

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...

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Bibliographic Details
Published in:	mLife Vol. 1; no. 4; pp. 448 - 459
Main 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
Format:	Journal Article
Language:	English
Published:	Australia John Wiley & Sons, Inc 01-12-2022 John Wiley and Sons Inc Wiley
Subjects:	Artificial intelligence Automation Cells Design Identification Method Microscopy One‐Cell‐One‐Tube (OCOT) single‐cell analysis single‐cell printing single‐cell sorting single‐cell printing single‐cell analysis One‐Cell‐One‐Tube (OCOT) artificial intelligence single‐cell sorting
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Summary:	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.
Bibliography:	Edited by Wenbin Du, Institute of Microbiology, Chinese Academy of Sciences, China ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Zhidian Diao, Lingyan Kan, and Yilong Zhao contributed equally to this study.
ISSN:	2770-100X 2097-1699 2770-100X
DOI:	10.1002/mlf2.12047