Droplet microfluidics for functional temporal analysis and cell recovery on demand using microvalves: application in immunotherapies for cancer.
Droplet microfluidics for functional temporal analysis and cell recovery on demand using microvalves: application in immunotherapies for cancer.
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DOI：
10.1039/d2lc00435f
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发表时间：
2022-08-23
期刊：
影响因子：
6.1
通讯作者：
Konry, Tania
中科院分区：
文献类型：
--
作者：
Agnihotri, Sagar N.;Ugolini, Giovanni Stefano;Sullivan, Matthew Ryan;Yang, Yichao;De Ganzo, Agustin;Lim, Ji Won;Konry, Tania
最常见的细胞分析方法采用自上而下的方法（直接询问蛋白质组学或基因组学），从而破坏细胞，这不允许使用相同的细胞将基因组学与功能测定相关联。在此，我们描述了一种用于单细胞工具的方法，该方法用作自下而上的方法。我们的技术允许通过观察细胞的细胞毒性进行功能表型分析，然后探测潜在的生物学。我们已经开发了一种微滴微流控装置，能够捕获阵列中的液滴，并使用微阀选择性地释放感兴趣的液滴。阵列中的每个液滴封装自然杀伤细胞（NK细胞）和肿瘤细胞，用于实时监测单个NK细胞杀伤期间的爆发动力学和空间协调。最后，我们使用微阀致动来选择性地释放具有所需功能表型的液滴，例如NK细胞对靶肿瘤细胞的快速和连续杀伤。从这个角度来看，我们的设备允许询问第一次相互作用和动力学的实时监测，以及根据单细胞组学分析的需求进行细胞恢复，例如单细胞RNA测序（scRNA），迄今为止，主要基于对相对较少数量细胞的整个转录组的深入分析。
Most common methods of cellular analysis employ the top-down approach (interrogating proteomics or genomics directly), thereby destroying the cell, which does not allow the possibility of using the same cell to correlate genomics with functional assays. Herein we describe an approach for single-cell tools that serve as a bottom-up approach. Our technology allows to conduct functional phenotyping by observing cytotoxicity of cells and then probe the underlying biology. We have developed a droplet microfluidic device capable of trapping droplets in the array and release the droplet of interest selectively using microvalves. Each droplet in the array encapsulates natural killer cells (NK cells) and tumour cells for real-time monitoring of burst kinetics and spatial coordination during killing by single NK cells. Finally, we use the microvalve actuation to selectively release droplets with desired functional phenotype such as fast and serial killing of target tumour cells by NK cells. In this perspective, our device allows for interrogating first interactions and real-time monitoring of kinetics and later cell recovery on demand for single-cell omic analysis such as single-cell RNA sequencing (scRNA), which to date, is primarily based on in-depth analyses of the entire transcriptome of a relatively low number of cells.
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影响因子：
6.1
作者：
Faley S;Seale K;Hughey J;Schaffer DK;VanCompernolle S;McKinney B;Baudenbacher F;Unutmaz D;Wikswo JP
通讯作者：
Wikswo JP
影响因子：
6.1
作者：
Frimat, Jean-Philippe;Becker, Marco;West, Jonathan
通讯作者：
West, Jonathan
影响因子：
16.6
作者：
Dura, Burak;Dougan, Stephanie K.;Voldman, Joel
通讯作者：
Voldman, Joel
影响因子：
2.8
作者：
Agnihotri, Sagar N.;Raveshi, Mohammad Reza;Neild, Adrian
通讯作者：
Neild, Adrian
影响因子：
8.8
作者：
Darmanis S;Gallant CJ;Marinescu VD;Niklasson M;Segerman A;Flamourakis G;Fredriksson S;Assarsson E;Lundberg M;Nelander S;Westermark B;Landegren U
通讯作者：
Landegren U