奥地利科学院分子医学研究中心Stefan Kubicek研究组，报道了利用汇集多色标签实现亚细胞蛋白质动态可视化技术。该研究于2024年4月19日发表于国际学术期刊《自然-细胞生物学》杂志。

研究人员研发了一种结合高通量显微镜、计算机观察和机器学习的方法，以检测多色标记视觉蛋白质组学细胞（vpCell）池中由扰动引发的变化。研究人员利用全基因组和以癌症为中心的内含子靶向sgRNA文库，生成vpCell池和一个大型克隆阵列集合，每个克隆表达两种不同的内源性荧光标记蛋白。

利用标记蛋白的定位模式和表达水平作为视觉条形码，通过图像分析可识别vpCell池中的单个克隆，从而实现对大量蛋白质组的同步活细胞监测。为了证明该方法的广泛适用性和通量，研究人员测试了抗增殖化合物对癌症相关蛋白池的影响，并在此基础上确定了广泛的蛋白定位变化和核输入/输出机制的新抑制剂。通过时间分辨表征亚细胞定位和蛋白质丰度在扰动时的变化，凸显了vpCell方法在药物发现和作用机理研究方面的强大功能。

据介绍，成像方法以广泛用于研究活细胞中蛋白质的亚细胞定位。虽然成像是研究单个蛋白质的常规方法，但对扰动后蛋白质动态的监测则依赖于荧光标记的细胞系，这限制了其通量和可扩展性。

附：英文原文

Title: Pooled multicolour tagging for visualizing subcellular protein dynamics

Author: Reicher, Andreas, Reini, Ji, Ciobanu, Maria, Rika, Pavel, Malik, Monika, Siklos, Marton, Kartysh, Victoria, Tomek, Tatjana, Koren, Anna, Rendeiro, Andr F., Kubicek, Stefan

Issue&Volume: 2024-04-19

Abstract: Imaging-based methods are widely used for studying the subcellular localization of proteins in living cells. While routine for individual proteins, global monitoring of protein dynamics following perturbation typically relies on arrayed panels of fluorescently tagged cell lines, limiting throughput and scalability. Here, we describe a strategy that combines high-throughput microscopy, computer vision and machine learning to detect perturbation-induced changes in multicolour tagged visual proteomics cell (vpCell) pools. We use genome-wide and cancer-focused intron-targeting sgRNA libraries to generate vpCell pools and a large, arrayed collection of clones each expressing two different endogenously tagged fluorescent proteins. Individual clones can be identified in vpCell pools by image analysis using the localization patterns and expression level of the tagged proteins as visual barcodes, enabling simultaneous live-cell monitoring of large sets of proteins. To demonstrate broad applicability and scale, we test the effects of antiproliferative compounds on a pool with cancer-related proteins, on which we identify widespread protein localization changes and new inhibitors of the nuclear import/export machinery. The time-resolved characterization of changes in subcellular localization and abundance of proteins upon perturbation in a pooled format highlights the power of the vpCell approach for drug discovery and mechanism-of-action studies.

DOI: 10.1038/s41556-024-01407-w

Source: https://www.nature.com/articles/s41556-024-01407-w