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Unraveling mitotic protein networks by 3D multiplexed epitope drug screening

机译:通过3D多重表位药物筛选揭示有丝分裂蛋白网络

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摘要

Three‐dimensional protein localization intricately determines the functional coordination of cellular processes. The complex spatial context of protein landscape has been assessed by multiplexed immunofluorescent staining or mass spectrometry, applied to 2D cell culture with limited physiological relevance or tissue sections. Here, we present 3D SPECS, an automated technology for 3D Spatial characterization of Protein Expression Changes by microscopic Screening. This workflow comprises iterative antibody staining, high‐content 3D imaging, and machine learning for detection of mitoses. This is followed by mapping of spatial protein localization into a spherical, cellular coordinate system, a basis for model‐based prediction of spatially resolved affinities of proteins. As a proof‐of‐concept, we mapped twelve epitopes in 3D‐cultured spheroids and investigated the network effects of twelve mitotic cancer drugs. Our approach reveals novel insights into spindle fragility and chromatin stress, and predicts unknown interactions between proteins in specific mitotic pathways. 3D SPECS's ability to map potential drug targets by multiplexed immunofluorescence in 3D cell culture combined with our automated high‐content assay will inspire future functional protein expression and drug assays.
机译:三维蛋白质定位复杂地决定了细胞过程的功能协调。已通过多重免疫荧光染色或质谱法评估了蛋白质景观的复杂空间背景,并将其应用于具有有限生理相关性或组织切片的2D细胞培养。在这里,我们介绍3D SPECS,这是一种通过显微镜筛选对蛋白质表达变化进行3D空间表征的自动化技术。该工作流程包括迭代抗体染色,高内涵3D成像以及用于检测有丝分裂的机器学习。接下来是将空间蛋白质定位映射到球形细胞坐标系中,这是基于模型的蛋白质空间分辨亲和力预测的基础。作为概念验证,我们在3D培养的球体中绘制了十二个表位,并研究了十二种有丝分裂癌药物的网络效应。我们的方法揭示了纺锤体脆性和染色质应力的新颖见解,并预测了特定有丝分裂途径中蛋白质之间未知的相互作用。 3D SPECS通过在3D细胞培养中通过多重免疫荧光与我们的自动化高含量检测结合使用来绘制潜在药物靶标的能力将激发未来的功能蛋白表达和药物检测。

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