欧洲分子生物学实验室的Jan Ellenberg团队开发了一种高通量荧光相关光谱（HT-FCS）技术研究活细胞中蛋白质分子网络在活细胞中的动态变化。FCS是一种具单分子分辨率的分子机制定量分析技术，可在单个活细胞的特点时间和空间节点检测分子浓度、扩散系数/可运动性、相互作用等特性。传统FCS实验的人工数据采集和分析方法仅适用于较短时间内分析少数细胞中几个目标分子的特性。本论文作者开发的HT-FCS技术可实现目标细胞的自动筛选，并在单个活细胞的特点空间位点和时间节点自动进行荧光自相关（FACS）和交相关（FCCS）光谱数据的自动采集和分析。应用HT-FCS技术，研究团队在10000个人源细胞中进行了60000次FCS实验，分析了53个细胞核蛋白的动态分子机制。根据FCS实验获取的多种实验参数（浓度、可运动性、相互作用等），可将这些核蛋白根据与染色质结合情况归为三类：1）核蛋白与组蛋白结合形成染色质复合物；2）核蛋白未与染色质结合；核蛋白形成大小不均的分子复合物，但未与染色质结合。此外，应用HT-FCS技术研究了细胞有丝分裂过程中，Aurora B Kinase和INCENP蛋白质分子的动态变化。Aurora B Kinase和INCENP对染色质移动复合物（CPC）的形成具至关重要的调控作用。FCS实验结果表明，在细胞分裂中期（0/24hr），INCENP 与Aurora B Kinase结合是形成CPC的关键步骤。HT-FCS技术对活细胞的动态分子机制研究和药物研发具重要意义。

Abstract

To understand the function of cellular protein networks, spatial and temporal context is essential. Fluorescence correlation spectroscopy (FCS) is a single-molecule method to study the abundance, mobility and interactions of fluorescence-labeled biomolecules in living cells. However, manual acquisition and analysis procedures have restricted live-cell FCS to short-term experiments of a few proteins. Here, we present high-throughput (HT)-FCS, which automates screening and time-lapse acquisition of FCS data at specific subcellular locations and subsequent data analysis^1,2. We demonstrate its utility by studying the dynamics of 53 nuclear proteins^3,4. We made 60,000 measurements in 10,000 living human cells, to obtain biophysical parameters that allowed us to classify proteins according to their chromatin binding and complex formation. We also analyzed the cell-cycle-dependent dynamics of the mitotic kinase complex Aurora B/INCENP⁵ and showed how a rise in Aurora concentration triggers two-step complex formation. We expect that throughput and robustness will make HT-FCS a broadly applicable technology for characterizing protein network dynamics in cells.

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https://mp.weixin.qq.com/s?__biz=MzkzNzI0NTc5Mg==&mid=2247485718&idx=1&sn=6fd03c86779e2eae7cbfe1a6b4b2fdc7&chksm=c2932419f5e4ad0f6fee065dc7ec94e6ffda0ca5e7045777bd25efaaccd39844f1a4f908edcd&token=928242522&lang=zh_CN#rd