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空间强度分布分析揭示单细胞中蛋白质的异常寡聚化。

Spatial Intensity Distribution Analysis Reveals Abnormal Oligomerization of Proteins in Single Cells.

作者信息

Godin Antoine G, Rappaz Benjamin, Potvin-Trottier Laurent, Kennedy Timothy E, De Koninck Yves, Wiseman Paul W

机构信息

Department of Physics, McGill University, Montréal, Québec, Canada; Institut Universitaire en Santé Mentale de Québec, Québec, Canada.

Department of Physics, McGill University, Montréal, Québec, Canada; Department of Neurology and Neurosurgery, Montréal Neurological Institute, McGill University, Montréal, Québec, Canada; Program in NeuroEngineering, McGill University, Montréal, Québec, Canada.

出版信息

Biophys J. 2015 Aug 18;109(4):710-21. doi: 10.1016/j.bpj.2015.06.068.

Abstract

Knowledge of membrane receptor organization is essential for understanding the initial steps in cell signaling and trafficking mechanisms, but quantitative analysis of receptor interactions at the single-cell level and in different cellular compartments has remained highly challenging. To achieve this, we apply a quantitative image analysis technique-spatial intensity distribution analysis (SpIDA)-that can measure fluorescent particle concentrations and oligomerization states within different subcellular compartments in live cells. An important technical challenge faced by fluorescence microscopy-based measurement of oligomerization is the fidelity of receptor labeling. In practice, imperfect labeling biases the distribution of oligomeric states measured within an aggregated system. We extend SpIDA to enable analysis of high-order oligomers from fluorescence microscopy images, by including a probability weighted correction algorithm for nonemitting labels. We demonstrated that this fraction of nonemitting probes could be estimated in single cells using SpIDA measurements on model systems with known oligomerization state. Previously, this artifact was measured using single-step photobleaching. This approach was validated using computer-simulated data and the imperfect labeling was quantified in cells with ion channels of known oligomer subunit count. It was then applied to quantify the oligomerization states in different cell compartments of the proteolipid protein (PLP) expressed in COS-7 cells. Expression of a mutant PLP linked to impaired trafficking resulted in the detection of PLP tetramers that persist in the endoplasmic reticulum, while no difference was measured at the membrane between the distributions of wild-type and mutated PLPs. Our results demonstrate that SpIDA allows measurement of protein oligomerization in different compartments of intact cells, even when fractional mislabeling occurs as well as photobleaching during the imaging process, and reveals insights into the mechanism underlying impaired trafficking of PLP.

摘要

了解膜受体组织对于理解细胞信号传导和运输机制的初始步骤至关重要,但在单细胞水平和不同细胞区室中对受体相互作用进行定量分析仍然极具挑战性。为了实现这一点,我们应用了一种定量图像分析技术——空间强度分布分析(SpIDA),它可以测量活细胞中不同亚细胞区室内的荧光颗粒浓度和寡聚化状态。基于荧光显微镜的寡聚化测量面临的一个重要技术挑战是受体标记的保真度。在实际操作中,不完美的标记会使在聚集系统中测量的寡聚化状态分布产生偏差。我们扩展了SpIDA,通过纳入针对非发射性标记的概率加权校正算法,能够从荧光显微镜图像中分析高阶寡聚体。我们证明,使用SpIDA对具有已知寡聚化状态的模型系统进行单细胞测量,可以估计单细胞中非发射性探针的比例。以前,这种假象是使用单步光漂白来测量的。该方法通过计算机模拟数据进行了验证,并在具有已知寡聚体亚基数量的离子通道的细胞中对不完美标记进行了量化。然后将其应用于量化COS-7细胞中表达的蛋白脂蛋白(PLP)在不同细胞区室中的寡聚化状态。与运输受损相关的突变PLP的表达导致在内质网中持续存在的PLP四聚体的检测,而野生型和突变型PLP在膜上的分布没有差异。我们的结果表明,即使在成像过程中出现部分错误标记以及光漂白的情况下,SpIDA也能够测量完整细胞不同区室中的蛋白质寡聚化,并揭示了PLP运输受损的潜在机制。

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