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基于图像的聚焦行波表面声波细胞分选。

Image-based cell sorting using focused travelling surface acoustic waves.

机构信息

Max Planck Institute for the Science of Light & Max-Planck-Zentrum für Physik und Medizin, Erlangen, Germany.

Department of Chemistry, University of Tokyo, Tokyo, Japan.

出版信息

Lab Chip. 2023 Jan 17;23(2):372-387. doi: 10.1039/d2lc00636g.

Abstract

Sorting cells is an essential primary step in many biological and clinical applications such as high-throughput drug screening, cancer research and cell transplantation. Cell sorting based on their mechanical properties has long been considered as a promising label-free biomarker that could revolutionize the isolation of cells from heterogeneous populations. Recent advances in microfluidic image-based cell analysis combined with subsequent label-free sorting by on-chip actuators demonstrated the possibility of sorting cells based on their physical properties. However, the high purity of sorting is achieved at the expense of a sorting rate that lags behind the analysis throughput. Furthermore, stable and reliable system operation is an important feature in enabling the sorting of small cell fractions from a concentrated heterogeneous population. Here, we present a label-free cell sorting method, based on the use of focused travelling surface acoustic wave (FTSAW) in combination with real-time deformability cytometry (RT-DC). We demonstrate the flexibility and applicability of the method by sorting distinct blood cell types, cell lines and particles based on different physical parameters. Finally, we present a new strategy to sort cells based on their mechanical properties. Our system enables the sorting of up to 400 particles per s. Sorting is therefore possible at high cell concentrations (up to 36 million per ml) while retaining high purity (>92%) for cells with diverse sizes and mechanical properties moving in a highly viscous buffer. Sorting of small cell fraction from a heterogeneous population prepared by processing of small sample volume (10 μl) is also possible and here demonstrated by the 667-fold enrichment of white blood cells (WBCs) from raw diluted whole blood in a continuous 10-hour sorting experiment. The real-time analysis of multiple parameters together with the high sensitivity and high-throughput of our method thus enables new biological and therapeutic applications in the future.

摘要

细胞分选是许多生物学和临床应用中的一个基本步骤,如高通量药物筛选、癌症研究和细胞移植。基于细胞力学特性的细胞分选一直被认为是一种很有前途的无标记生物标志物,可以彻底改变从异质群体中分离细胞的方法。最近,基于微流控的图像细胞分析技术与芯片上的无标记分选相结合的方法的进步,证明了基于细胞物理特性进行分选的可能性。然而,高纯度的分选是以牺牲分选速度为代价的,分选速度落后于分析通量。此外,稳定可靠的系统运行是实现从小体积异质群体中分离小细胞分数的重要特征。在这里,我们提出了一种无标记细胞分选方法,该方法基于使用聚焦行波表面声波(FTSAW)与实时变形细胞术(RT-DC)相结合。我们通过基于不同物理参数对不同的血液细胞类型、细胞系和颗粒进行分选,证明了该方法的灵活性和适用性。最后,我们提出了一种基于细胞力学特性的新分选策略。我们的系统能够实现高达 400 个/秒的分选速度。在高细胞浓度(高达 3600 万/毫升)下仍能保持高纯度(>92%),适用于不同尺寸和力学特性的细胞在高粘性缓冲液中运动。通过处理小体积(10 μl)样本制备的异质群体中,也可以对小细胞分数进行分选,我们通过连续 10 小时的分选实验,实现了从原始稀释全血中对白细胞(WBC)的 667 倍富集,证明了这一点。我们的方法可以实时分析多个参数,具有高灵敏度和高通量,因此未来可以在生物学和治疗学领域有新的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff5e/9844123/17d8d9d13202/d2lc00636g-f1.jpg

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