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

单细胞分辨率下蛋白激酶信号动力学的询问和解释

• 批准号: 10029413
• 负责人: Min Xue
• 金额: $ 28.92万
• 依托单位: UNIVERSITY OF CALIFORNIA RIVERSIDE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10029413
• 关键词: AKT inhibition; Address; Affinity; Behavior; Biological; Cell Line; Cells; Chemicals; Cyclic Peptides; Data; Disease; Epidermal Growth Factor Receptor; Glioblastoma; Heterogeneity; Human; Kinetics; Link; Malignant Neoplasms; Methods; Multivariate Analysis; Outcome; Pattern; Peptides; Pharmacotherapy; Phenotype; Phosphotransferases; Process; Protein Kinase; Proto-Oncogene Proteins c-akt; Reporting; Research; Resolution; Shapes; Signal Transduction; Signaling Protein; System; Technology; Testing; Work; analytical method; base; imaging probe; insight; kinase inhibitor; neural network algorithm; novel; response; single cell technology; therapy outcome; tool; translational impact

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.

抽象的 越来越多的证据表明激酶信号传导的动力学行为，即激酶信号传导的动力学模式 激活/失活过程可以决定细胞对不同扰动的反应。了解这样的 动力学可以帮助预测细胞命运，例如药物治疗的活/死结果。然而，这个任务 需要在细胞表型的背景下解决单细胞激酶信号动力学，即 技术上具有挑战性。虽然基因编码的报告系统可以满足一些需求，但它 实施仅限于易于转染的细胞系，从而限制了其转化影响。到 克服这些挑战，我们的小组开发了一种化学方法来研究激酶信号传导活动 在活的单细胞中，使用基于环肽的成像探针。在此 MIRA 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签并开发一系列高度特异性的 成像探头（项目 1a）。我们还将探索化学策略来设计通用探针递送标签 （项目 1b）。通过将这些工具与其他成熟的单细胞技术和多元技术相结合 分析方法，我们计划解决两个突出的生物学问题：独特的动力学特征如何 蛋白激酶信号传导活性与表型异质性相关（项目 2）？不同的激酶如何 信号动力学协调细胞对外部扰动的反应，例如活/死的结果 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，重点关注 使用人胶质母细胞瘤细胞系的 AKT 信号传导。我们发现抑制AKT或其上游信号蛋白 (EGFR) 都可以显着改变 AKT 信号传导的动力学特征。我们还证明了神经 网络算法可以利用 AKT 的动力学模式预测细胞是否能够在 AKT 抑制中存活 信令配置文件作为输入。根据我们的数据，我们提出两个假设：首先，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。二、早 激酶信号传导的反应控制靶向激酶抑制剂的治疗结果。在项目2和3中，我们将 通过研究一组细胞系中的激酶信号动力学（有或没有外部条件）来检验这些假设 扰动。我们将启动以 AKT 信号传导为重点的研究，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号模块。成功执行 拟议的研究将提供一套新颖的化学探针和用于询问的支持技术 单细胞分辨率的激酶信号动力学。它还将深入了解这种动态如何相互联系 表型异质性并控制特定的细胞反应。