Analysis of cellular response to drugs with a microfluidic single-cell platform based on hyperspectral imaging

被引:4
|
作者
Liu, Luyao [1 ]
Zhang, Lulu [1 ]
Zhang, Xueyu [3 ]
Dong, Xiaobin [1 ]
Jiang, Xiaodan [1 ]
Huang, Xiaoqi [3 ]
Li, Wei [3 ]
Xie, Xiaoming [2 ]
Qiu, Xianbo [1 ]
机构
[1] Beijing Univ Chem Technol, Inst Microfluid Chip Dev Biomed Engn, Sch Informat Sci & Technol, Beijing 100029, Peoples R China
[2] Beijing Univ Chem Technol, Sch Informat Sci & Technol, Beijing 100029, Peoples R China
[3] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China
关键词
Single-cell analysis; Drug response; Hyperspectral imaging; Microfluidics; High-throughput; MASS-SPECTROMETRY; SYSTEMS; A549;
D O I
10.1016/j.aca.2023.342158
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Background: Cellular response to pharmacological action of drugs is significant for drug development. Traditional detection method for cellular response to drugs normally rely on cell proliferation assay and metabolomics ex-amination. In principle, these analytical methods often required cell labeling, invasion analysis, and hours of co -culture with drugs, which are relatively complex and time-consuming. Moreover, these methods can only indicate the drug effectiveness on cell colony rather than single cells. Thus, to meet the requirements of personal precision medicine, the development of drug response analysis on the high resolution of single cell is demanded.Results: To provide precise result for drug response on single-cell level, a microfluidic platform coupled with the label-free hyperspectral imaging was developed. With the help of horizontal single-cell trapping sieves, hundreds of single cells were trapped independently in microfluidic channels for the purposes of real-time drug delivery and single-cell hyperspectral image recording. To significantly identify the cellular hyperspectral change after drug stimulation, the differenced single-cell spectrum was proposed. Compared with the deep learning classi-fication method based on hyperspectral images, an optimal performance can be achieved by the classification strategy based on differenced spectra. And the cellular response to different reagents, for example, K+, Epidermal Growth Factor (EGF), and Gefitinib at different concentrations can be accurately characterized by the differenced single-cell spectra analysis.Significance and novelty: The high-throughput, rapid analysis of cellular response to drugs at the single-cell level can be accurately performed by our platform. After systematically analyzing the materials and the structures of the single-cell microfluidic chip, the optimal single-cell trapping method was proposed to contribute to the further application of hyperspectral imaging on microfluidic single-cell analysis. And the hyperspectral char-acterization of single-cell with cancer drug stimulation proved the application potential of our method in per-sonal cancer medication.
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页数:14
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