药物干扰肺癌培养物和组织中空间分辨亚细胞蛋白质-蛋白质相互作用组学

IF 26.8 1区 医学 Q1 ENGINEERING, BIOMEDICAL
Shuangyi Cai, Thomas Hu, Abhijeet Venkataraman, Felix G. Rivera Moctezuma, Efe Ozturk, Nicholas Zhang, Mingshuang Wang, Tatenda Zvidzai, Sandip Das, Adithya Pillai, Frank Schneider, Suresh S. Ramalingam, You-Take Oh, Shi-Yong Sun, Ahmet F. Coskun
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引用次数: 0

摘要

蛋白质-蛋白质相互作用(PPIs)调控信号通路和细胞表型,因此可视化 PPIs 的空间分辨动态将揭示信号网络的激活和串扰。在此,我们报告了一种方法,该方法利用连续近接测定法对参与多信号串扰通路的多达 47 个蛋白质的 PPI 进行多重分析。我们将该方法应用于表皮生长因子受体突变的非小细胞肺癌的细胞培养和组织中,然后进行传统的免疫荧光,以确定 PPIs 在亚细胞体积中的共定位,并重建 PPIs 在酪氨酸激酶抑制剂奥希替尼的扰动下亚细胞分布的变化。我们还表明,编码空间解析 PPIs 的图卷积网络可以准确预测单个细胞的细胞处理状态。在基于图的深度学习的辅助下进行的多重近接检测可以深入了解PPIs的亚细胞组织,从而设计出靶向蛋白质相互作用组的药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Spatially resolved subcellular protein–protein interactomics in drug-perturbed lung-cancer cultures and tissues

Spatially resolved subcellular protein–protein interactomics in drug-perturbed lung-cancer cultures and tissues

Protein–protein interactions (PPIs) regulate signalling pathways and cell phenotypes, and the visualization of spatially resolved dynamics of PPIs would thus shed light on the activation and crosstalk of signalling networks. Here we report a method that leverages a sequential proximity ligation assay for the multiplexed profiling of PPIs with up to 47 proteins involved in multisignalling crosstalk pathways. We applied the method, followed by conventional immunofluorescence, to cell cultures and tissues of non-small-cell lung cancers with a mutated epidermal growth-factor receptor to determine the co-localization of PPIs in subcellular volumes and to reconstruct changes in the subcellular distributions of PPIs in response to perturbations by the tyrosine kinase inhibitor osimertinib. We also show that a graph convolutional network encoding spatially resolved PPIs can accurately predict the cell-treatment status of single cells. Multiplexed proximity ligation assays aided by graph-based deep learning can provide insights into the subcellular organization of PPIs towards the design of drugs for targeting the protein interactome.

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来源期刊
Nature Biomedical Engineering
Nature Biomedical Engineering Medicine-Medicine (miscellaneous)
CiteScore
45.30
自引率
1.10%
发文量
138
期刊介绍: Nature Biomedical Engineering is an online-only monthly journal that was launched in January 2017. It aims to publish original research, reviews, and commentary focusing on applied biomedicine and health technology. The journal targets a diverse audience, including life scientists who are involved in developing experimental or computational systems and methods to enhance our understanding of human physiology. It also covers biomedical researchers and engineers who are engaged in designing or optimizing therapies, assays, devices, or procedures for diagnosing or treating diseases. Additionally, clinicians, who make use of research outputs to evaluate patient health or administer therapy in various clinical settings and healthcare contexts, are also part of the target audience.
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