High-Throughput Single Cell Mechanomics

总结。细胞群体中的表型异质性可以导致其相应的差异 对生理和生化刺激的反应。为了评估单元格分辨率的异质性，有几个 虽然已经开发了一些方法，但还不能可靠地确定细胞未来行为的真正可预测性。至 应对这一挑战，拟议的工作将开发一种新的技术方法来解决块状电池 异质性问题被称为“单细胞机制组学”。这项技术将记录引起的压缩 单细胞的动态信号响应，以预测和/或驱动它们未来的行为。技术 创新包括一个智能的微流控设备，它带有光致微捕捉器，可以捕获和压缩 单个细胞，并同时评估它们的信号响应，然后释放和捕获每个个体 用于后续的下游单克隆化培养和分析。为了证明这项技术的可行性，人类 间充质基质细胞(MSCs)将作为一种具有代表性的高机械响应性细胞 异质细胞类型。目标1将设计和开发具有光致微捕捉器的智能微流控设备， 而目标2将建立一个框架，基于钙离子来预测和/或驱动单细胞的表型结果 机械压缩单细胞的振动动力学。将使用多变量预测分析来 确定压缩刺激、钙信号和表型结果之间的关系。新的 从这项工作中得出的关系将被用来根据目标细胞群体的未来来识别和分类 表型。目前，在文献中还没有关于这种技术的演示。这与 此次R21征集的高风险要求对未来产生重大影响。

Summary. Phenotypic heterogeneity in cellular bulk populations can result in consequential differences in their response to physical as well as biochemical stimuli. To assess heterogeneity at single cell resolution, several methods have been developed, yet true predictability of cells’ future behavior cannot be reliably determined. To address this challenge, the proposed work will develop a new technological approach to solve the bulk cell heterogeneity problem coined as ‘single cell mechanomics’. This technology will record compression induced dynamic signaling response of single cells to predict and/or drive their future behavior. The technological innovation consists of a ‘smart’ microfluidic device with light actuated microtraps that can capture and compress single cells, and concurrently assess their signaling response, before releasing and capturing each individual cells for subsequent downstream monoclonal culture and analysis. To prove feasibility of this technology, human mesenchymal stromal cells (MSCs) will be used as a representative mechanoresponsive and highly heterogeneous cell type. Aim 1 will design and develop ‘smart’ microfluidic devices with light-actuated mictraps, while Aim 2 will establish a framework to predict and/or drive single cells’ phenotypic outcome based on calcium oscillation dynamics of mechanically compressed single cells. Multivariate predictive analyses will be used to identify relationships between compressive stimuli, calcium signaling, and phenotypic outcome. New relationships derived from this work will be used to identify and sort target cell populations based on their future phenotypes. At present, there is no demonstration of such a technology in the literature. This aligns with the high-risk requirements of this R21 solicitation of having significant future impact.