Abstract

Although single-cell intrinsic structural and electrical parameters (e.g. D c of cell diameter, D n of nuclear diameter, σ cy of cytoplasmic conductivity and C sm 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 D c, D n, σ cy and C sm leveraging a home-developed impedance-fluorescence model. As a demonstration, the microfluidic platform quantified D c, D n, σ cy and C sm 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% (D c), 68.9 ± 6.8% (D c + D n) and 84.8 ± 4.4% (D c, D n, σ cy + C sm) based on neural pattern recognition. Then D c, D n, σ cy and C sm 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.

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