4.7 Article

A microfluidic robot for rare cell sorting based on machine vision identification and multi-step sorting strategy

Journal

TALANTA
Volume 226, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.talanta.2021.122136

Keywords

Single-cell sorting; Machine vision; Microfluidic robot; Droplet-based microfluidics

Funding

  1. National Natural Science Foundation of China [21827806, 21435004]
  2. Key Research and Development Plan of Zhejiang Province [2020C03017]
  3. Fundamental Research Funds for the Zhejiang Province Universities [2019XZZX003-15]

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This study developed a microfluidic robot platform for sorting rare target cells from complex clinical blood samples, achieving high efficiency and purity through a novel multi-step sorting strategy. The platform automates the identification, capture, and droplet generation of rare cells, demonstrating the feasibility and potential application in the sorting and analysis of specific rare cells like circulating endothelial progenitor cells (CEPCs) in human blood.
The identification, sorting and analysis of rare target single cells in human blood has always been a clinically meaningful medical challenge. Here, we developed a microfluidic robot platform for sorting specific rare cells from complex clinical blood samples based on machine vision-based image identification, liquid handling robot and droplet-based microfluidic techniques. The robot integrated a cell capture and droplet generation module, a laser-induced fluorescence imaging module, a target cell identification and data analysis module, and a system control module, which could automatically achieve the scanning imaging of cell array, cell identification, capturing, and droplet generation of rare target cells from blood samples containing large numbers of normal cells. Based on the robot platform, a novel gold panning multi-step sorting strategy was proposed to achieve the sorting of rare target cells in large-scale cell samples with high operation efficiency and high sorting purity (>90%). The robot platform and the multi-step sorting strategy were applied in the sorting of circulating endothelial progenitor cells (CEPCs) in human blood to demonstrate their feasibility and application potential in the sorting and analysis of rare specific cells. Approximately 1,000 CEPCs were automatically identified from 3,000,000 blood cells at a scanning speed of ca. 4,000 cells/s, and 20 25-nL droplets containing single CEPCs were generated.

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