Sansbury Stephanie E, Serebrenik Yevgeniy V, Lapidot Tomer, Burslem George M, Shalem Ophir
bioRxiv. 2023 Jul 14:2023.07.13.548611. doi: 10.1101/2023.07.13.548611.
System-level understanding of proteome organization and function requires methods for direct visualization and manipulation of proteins at scale. We developed an approach enabled by high-throughput gene tagging for the generation and analysis of complex cell pools with endogenously tagged proteins. Proteins are tagged with HaloTag to enable visualization or direct perturbation. Fluorescent labeling followed by sequencing and deep learning-based image analysis identifies the localization pattern of each tag, providing a bird's-eye-view of cellular organization. Next, we use a hydrophobic HaloTag ligand to misfold tagged proteins, inducing spatially restricted proteotoxic stress that is read out by single cell RNA sequencing. By integrating optical and perturbation data, we map compartment-specific responses to protein misfolding, revealing inter-compartment organization and direct crosstalk, and assigning proteostasis functions to uncharacterized genes. Altogether, we present a powerful and efficient method for large-scale studies of proteome dynamics, function, and homeostasis.
对蛋白质组组织和功能的系统层面理解需要能够大规模直接可视化和操纵蛋白质的方法。我们开发了一种由高通量基因标签实现的方法,用于生成和分析带有内源性标记蛋白质的复杂细胞库。蛋白质用卤代标签进行标记,以实现可视化或直接扰动。荧光标记后进行测序以及基于深度学习的图像分析可识别每个标签的定位模式,提供细胞组织的全景视图。接下来,我们使用一种疏水性卤代标签配体使标记的蛋白质错误折叠,诱导空间受限的蛋白毒性应激,通过单细胞RNA测序来检测这种应激。通过整合光学和扰动数据,我们绘制出特定区室对蛋白质错误折叠的反应图谱,揭示区室间的组织和直接串扰,并为未表征的基因赋予蛋白质稳态功能。总之,我们提出了一种强大而高效的方法,用于蛋白质组动力学、功能和稳态的大规模研究。