4.8 Article

Two-Dimensional Multi-parameter Cytometry Platform for Single-Cell Analysis

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ANALYTICAL CHEMISTRY
卷 95, 期 35, 页码 13297-13304

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AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.3c02457

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A 2D flow cytometry platform called CytoLM Plus was developed for multi-parameter single-cell analysis. This platform combines fluorescence and side scattering optical detection with ICP-MS detection for a comprehensive analysis of single cells. The performance of CytoLM Plus was evaluated using fluorescent microspheres and cells, and it showed comparable results to a commercial flow cytometer.
A 2D flow cytometry platform, known as CytoLM Plus, was developed for multi-parameter single-cell analysis. Single particles or cells after hydrodynamic alignment in a microfluidic unit undergo first-dimension fluorescence and side scattering dual-channel optical detection. They were thereafter immediately directed to ICPMS by connecting the microfluidic unit with a high-efficiency nebulizer to facilitate the second-dimension ICP-MS detection. Flow cytometry measurements of fluorescent microspheres evaluated the performance of CytoLM Plus for optical detection. 6434 fluorescence bursts were observed with a valid signal proportion as high as 99.7%. After signal unification and gating analysis, 6067 sets of single-particle signals were obtained with 6.6 and 6.2% deviations for fluorescence burst area and height, respectively. This is fairly comparable with that achieved by a commercial flow cytometer. Afterward, CytoLM Plus was evaluated by 2D flow cytometry measurement of Ag+incubated and AO-stained MCF-7 cells. A program for 2D single-cell signal unification was developed based on the algorithm of screening in lag time window. In the present case, a lag time window of -4.2 +/- 0.09 s was determined by cross-correlation analysis and two-parameter optimization, which efficiently unified the concurrent single-cell signals from fluorescence, side scattering, and ICP-MS. A total of 495 sets of concurrent 2D signals were screened out, and the statistical analysis of these single-cell signals ensured 2D multi-parameter single-cell analysis and data elucidation.

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