4.7 Article

Development of microfluidic platform to high-throughput quantify single-cell intrinsic bioelectrical markers of tumor cell lines, subtypes and patient tumor cells

Journal

SENSORS AND ACTUATORS B-CHEMICAL
Volume 317, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2020.128231

Keywords

Single-cell analysis; Microfluidics; Intrinsic bioelectrical markers; Asymmetrical constriction channel; High throughput

Funding

  1. National Natural Science Foundation of China [61431019, 61825107, 61671430, 61922079]
  2. Key Project, Instrument Development Program, Youth Innovation Promotion Association and Interdisciplinary Innovation Team of Chinese Academy of Sciences [QYZDB-SSW-JSC011]
  3. Instrument Development of Beijing Municipal Science & Technology Commission [Z181100009518001]

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Although intrinsic bioelectrical markers of single cells (e.g. specific membrane capacitance of C-sm, cytoplasm conductivity of sigma(cy) and cell diameter of D-c) play key roles in cell-type classification and cell-status evaluation, due to technical limitations, data from large populations of single cells were not available. This paper presents a microfluidic platform to high-throughput quantify single-cell intrinsic bioelectrical markers of tumor cell lines, subtypes and patient tumor cells, where an asymmetrical constriction channel defined by a major and two side constriction channels was used as the sensitive unit. The developed microfluidic platform was used to quantify similar to 100,000 single-cell C-sm, sigma(cy) and D-c from (I) eight tumor cell lines of A549, Hep G2, SW620, AGS, PANC-1, Hela, CAL 27 and HL-60 with cell-type classification rates of 87.6 % +/- 9.1 % obtained; (II) tumor cell subtypes of 293 T with and without the transfection of the CRISPR knockout library where different distributions of C-sm were located; (III) patient tumor cells with classification rates of 96.1 % +/- 3.8 % obtained compared with tumor cell lines. In conclusion, the microfluidic platform developed in this study can function as a high-throughput tool in the field of single-cell analysis.

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