Center for Microflows and Nanoflows, School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China.
Joint International Laboratory of Optofluidic Technology and System, National Center for International Research on Green Optoelectronics, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou 510006, China.
Anal Chem. 2023 Aug 29;95(34):12875-12883. doi: 10.1021/acs.analchem.3c02182. Epub 2023 Aug 15.
Single-cell analysis has important implications for understanding the specificity of cells. To analyze the specificity of rare cells in complex blood and biopsy samples, selective lysis of target single cells is pivotal but difficult. Microfluidics, particularly droplet microfluidics, has emerged as a promising tool for single-cell analysis. In this paper, we present a smart droplet microfluidic system that allows for single-cell selective lysis and real-time sorting, aided by the techniques of microinjection and image recognition. A custom program evolved from Python is proposed for recognizing target droplets and single cells, which also coordinates the operation of various parts in a whole microfluidic system. We have systematically investigated the effects of voltage and injection pressure applied to the oil-water interface on droplet microinjection. An efficient and selective droplet injection scheme with image feedback has been demonstrated, with an efficiency increased dramatically from 2.5% to about 100%. Furthermore, we have proven that the cell lysis solution can be selectively injected into target single-cell droplets. Then these droplets are shifted into the sorting area, with an efficiency for single K562 cells reaching up to 73%. The system function is finally explored by introducing complex cell samples, namely, K562 cells and HUVECs, with a success rate of 75.2% in treating K562 cells as targets. This system enables automated single-cell selective lysis without the need for manual handling and sheds new light on the cooperation with other detection techniques for a broad range of single-cell analysis.
单细胞分析对于理解细胞的特异性具有重要意义。为了分析复杂血液和活检样本中稀有细胞的特异性，靶向单细胞的选择性溶解至关重要，但也极具挑战性。微流控技术，特别是液滴微流控技术，已成为单细胞分析的一种有前途的工具。在本文中，我们提出了一种智能液滴微流控系统，该系统借助微注射和图像识别技术，实现了单细胞的选择性溶解和实时分选。我们提出了一个基于 Python 的自定义程序，用于识别目标液滴和单细胞，同时协调整个微流控系统各部分的操作。我们系统地研究了施加在油水界面上的电压和注射压力对液滴微注射的影响。通过图像反馈，我们展示了一种高效且具有选择性的液滴注入方案，效率从 2.5%显著提高到约 100%。此外，我们证明了可以将细胞裂解溶液选择性地注入到目标单细胞液滴中。然后，这些液滴被转移到分选区域，对于单个 K562 细胞，分选效率高达 73%。最后，通过引入复杂的细胞样本，即 K562 细胞和 HUVECs，探索了该系统的功能，以 K562 细胞为目标的处理成功率达到了 75.2%。该系统实现了自动化的单细胞选择性溶解，无需手动操作，为与其他单细胞分析检测技术的广泛合作提供了新的思路。
