Interrogation and interpretation of protein kinase signaling dynamics at single-cell resolution

摘要 越来越多的证据表明，激酶信号转导的动力学行为，即信号转导的动力学模式。 激活/去激活过程，可以决定细胞对不同扰动的反应。了解以下内容 动力学可以帮助预测细胞的命运，例如药物治疗的活/死结果。然而，这项任务 需要在细胞表型的背景下解析单细胞激酶信号动力学，这是 在技术上具有挑战性。尽管基因编码的报告系统可以满足一些需求，但其 实施仅限于容易转化的细胞系，从而限制了其翻译影响。至 克服这些挑战，我们的团队开发了一种化学方法来研究激酶信号活性 在活的单细胞中，使用基于环肽的成像探针。在这项米拉提案中，我们寻求扩大 化学工具包，包括基于多环肽的亲和标记，并开发高度特异的曲目 成像探头(项目1a)。我们还将探索化学策略，以设计一种通用的探针交付标签 (项目1b)。通过将这些工具与其他成熟的单细胞技术和多变量 分析方法，我们计划解决两个突出的生物学问题：如何获得独特的动力学特征 蛋白激酶信号活动是否与表型异质性有关(项目2)？不同的激酶是如何 信号动力学协调细胞对外部扰动的反应，例如 靶向激酶抑制剂(项目3)？为了回答这些问题，我们进行了初步研究，重点是 使用人脑胶质母细胞瘤细胞系的AKT信号。我们发现抑制AKT或其上游信号蛋白 (EGFR)均能显著改变AKT信号的动力学特征。我们还证明了一种神经 网络算法可以利用AKT的动力学模式来预测细胞是否能够经受AKT的抑制 作为输入的信令配置文件。基于我们的数据，我们提出了两个假说：第一，激酶的模式 信号动力学由上游信号蛋白的丰度和活性决定。第二，提早 激酶信号转导的反应决定了靶向的激酶抑制剂的治疗结果。在项目2和3中，我们将 通过在一组细胞系中研究激酶信号动力学来检验这些假设，无论有没有外源 微扰。我们将以AKT信号为重点启动研究，并作为Project的新成像探针 1可用后，我们将扩展我们的工作，以包括其他信令模块。成功执行了 拟议的研究将提供一套新的化学探针和使能技术用于审讯 单细胞分辨率下的激酶信号动力学。它还将产生对这种动态如何联系的洞察 表型异质性，并控制特定的细胞反应。

ABSTRACT Increasing evidence has demonstrated that the dynamical behaviors of kinase signaling, i.e., kinetic patterns of activation/deactivation process, can dictate the cells' responses to different perturbations. Understanding such dynamics can help to predict cell fates, such as live/dead outcomes of drug treatments. However, this task requires resolving single-cell kinase signaling dynamics in the context of cellular phenotypes, which is technologically challenging. Although genetically encoded reporting systems can address some of the needs, its implementation is restricted to easily transfectable cell lines, thereby limiting its translational impacts. To overcome those challenges, our group has developed a chemical method for studying kinase signaling activities in living single cells, using cyclic peptide-based imaging probes. In this MIRA proposal, we seek to expand the chemical toolkit to include multicyclic peptide-based affinity tags and develop a repertoire of highly specific imaging probes (Project 1a). We will also explore chemical strategies to devise a universal probe delivery tag (Project 1b). By combining these tools with other well-established single-cell technologies and multivariate analysis methods, we plan to address two outstanding biological questions: How do the unique kinetic features of protein kinase signaling activities link to phenotypical heterogeneity (Project 2)? How does diverse kinase signaling dynamics orchestrate cellular responses to external perturbations, such as live/dead outcomes of targeted kinase inhibitors (Project 3)? To answer those questions, we performed preliminary studies focusing on AKT signaling using a human glioblastoma cell line. We found that inhibiting AKT or its upstream signaling protein (EGFR) can both significantly change the kinetic features of AKT signaling. We also demonstrated that a neural network algorithm could predict whether a cell can survive AKT inhibition, using the kinetic patterns of AKT signaling profile as the input. Based on our data, we propose two hypotheses: First, the pattern of kinase signaling kinetics is shaped by the abundance and activities of upstream signaling proteins. Second, early responses in kinase signaling govern therapeutic outcomes of targeted kinase inhibitors. In projects 2&3, we will test those hypotheses by studying kinase signaling dynamics in a panel of cell lines, with and without external perturbations. We will initiate the studies with a focus on AKT signaling, and as new imaging probes from Project 1 become available, we will expand our work to include other signaling modules. Successful execution of the proposed research will provide a suite of novel chemical probes and enabling technologies for interrogating kinase signaling dynamics at single-cell resolution. It will also generate insights into how such dynamics connects to phenotypical heterogeneity and governs specific cellular responses.