Efficient single-cell oxygen consumption rate characterization based on frequency domain fluorescence lifetime imaging microscopy measurement and microfluidic platform

被引:4
|
作者
Kannan, Santhosh [1 ,2 ,3 ]
Ko, Ping-Liang [1 ,4 ]
Wu, Hsiao-Mei [5 ]
Tung, Yi-Chung [1 ,6 ]
机构
[1] Acad Sinica, Res Ctr Appl Sci, Taipei, Taiwan
[2] Natl Tsing Hua Univ, Dept Engn & Syst Sci, Hsinchu, Taiwan
[3] Acad Sinica, Nano Sci & Technol Program, Taiwan Int Grad Program TIGP, Taipei, Taiwan
[4] Natl Taiwan Univ, Dept Mech Engn, Taipei, Taiwan
[5] Natl Taiwan Univ, Dept Biomechatron Engn, Taipei, Taiwan
[6] Chang Gung Univ, Coll Engn, Taoyuan, Taiwan
关键词
CULTURE; GRADIENTS; DEVICES;
D O I
10.1063/5.0161752
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Cell metabolism is critical in regulating normal cell functions to maintain energy homeostasis. In order to monitor cell metabolism, the oxygen consumption rate (OCR) of cells has been characterized as an important factor. In conventional cell analysis, the cells are characterized in bulk due to technical limitations. However, the heterogeneity between the cells cannot be identified. Therefore, single-cell analysis has been proposed to reveal cellular functions and their heterogeneity. In this research, an approach integrating a microfluidic device and widefield frequency domain fluorescence imaging lifetime microscopy (FD-FLIM) for single-cell OCR characterization in an efficient manner is developed. The microfluidic device provides an efficient platform to trap and isolate single cells in microwells with the buffer saline containing an oxygen-sensitive phosphorescent dye. The oxygen tension variation within the microwells can be efficiently estimated by measuring the fluorescence lifetime change using the FD-FLIM, and the OCR values of the single cells can then be calculated. In the experiments, breast cancer (MCF-7) cells are exploited for the OCR measurement. The results demonstrate the functionality of the developed approach and show the heterogeneity among the cells. The developed approach possesses great potential to advance cellular metabolism studies with single-cell resolution.
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页数:11
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