Development of microfluidic flow cytometry capable of characterization of single-cell intrinsic structural and electrical parameters

Liang, Hongyan and Zhang, Yi and Chen, Deyong and Li, Yueying and Wang, Yixiang and Wang, Junbo and Chen, Jian (2022) Development of microfluidic flow cytometry capable of characterization of single-cell intrinsic structural and electrical parameters. Journal of Micromechanics and Microengineering, 32 (3). 035007. ISSN 0960-1317

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Abstract

Although single-cell intrinsic structural and electrical parameters (e.g. Dc of cell diameter, Dn of nuclear diameter, σcy of cytoplasmic conductivity and Csm of specific membrane capacitance) are promising for cell-type classification, they cannot be obtained simultaneously due to structural limitations of previously reported flow cytometry. This paper presented a microfluidic flow cytometry made of a double T-type constriction channel plus a predefined fluorescence detection domain, capable of high-throughput characterizing single-cell Dc, Dn, σcy and Csm leveraging a home-developed impedance-fluorescence model. As a demonstration, the microfluidic platform quantified Dc, Dn, σcy and Csm from ∼10 000 individual cells of three well-established tumor cell lines of A549, SW620 and HeLa where successful rates of cell-type classification were estimated as 54.5 ± 1.3% (Dc), 68.9 ± 6.8% (Dc + Dn) and 84.8 ± 4.4% (Dc, Dn, σcy + Csm) based on neural pattern recognition. Then Dc, Dn, σcy and Csm derived from ∼10 000 single cells of K562 vs Jurkat of leukemia and SACC-LM vs CAL 27 of oral tumor were quantified and compared, where successful rates of cell-type classification were estimated as 87.3% (K562 vs Jurkat) and 79.5% (SACC-LM vs CAL 27), respectively. In summary, the microfluidic platform reported in this study could quantify single-cell intrinsic structural and electrical parameters simultaneously, leading to significant increases in successful rates of cell-type classification.

Item Type: Article
Subjects: OA Library Press > Multidisciplinary
Depositing User: Unnamed user with email support@oalibrarypress.com
Date Deposited: 09 Jun 2023 05:53
Last Modified: 18 Jun 2024 07:13
URI: http://archive.submissionwrite.com/id/eprint/1140

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