Laboratoire de Biologie et Modé lisation de la Cellule, Ecole Normale Supé rieure de Lyon, CNRS, Université Lyon 1, Université de Lyon, 46 allée d'Italie, 69364 Lyon cedex 07, France.
Laboratoire de Biologie et Modé lisation de la Cellule, Ecole Normale Supé rieure de Lyon, CNRS, Université Lyon 1, Université de Lyon, 46 allée d'Italie, 69364 Lyon cedex 07, France.
Mol Cell Proteomics. 2020 Apr;19(4):701-715. doi: 10.1074/mcp.TIR119.001692. Epub 2020 Feb 3.
We present a technological advancement for the estimation of the affinities of Protein-Protein Interactions (PPIs) in living cells. A novel set of vectors is introduced that enables a quantitative yeast two-hybrid system based on fluorescent fusion proteins. The vectors allow simultaneous quantification of the reaction partners (Bait and Prey) and the reporter at the single-cell level by flow cytometry. We validate the applicability of this system on a small but diverse set of PPIs (eleven protein families from six organisms) with different affinities; the dissociation constants range from 117 pm to 17 μm After only two hours of reaction, expression of the reporter can be detected even for the weakest PPI. Through a simple gating analysis, it is possible to select only cells with identical expression levels of the reaction partners. As a result of this standardization of expression levels, the mean reporter levels directly reflect the affinities of the studied PPIs. With a set of PPIs with known affinities, it is straightforward to construct an affinity ladder that permits rapid classification of PPIs with thus far unknown affinities. Conventional software can be used for this analysis. To permit automated analysis, we provide a graphical user interface for the Python-based FlowCytometryTools package.
我们提出了一种用于估计活细胞中蛋白质-蛋白质相互作用(PPIs)亲和力的技术进步。引入了一组新的载体,可实现基于荧光融合蛋白的定量酵母双杂交系统。这些载体允许通过流式细胞术在单细胞水平上同时定量反应伙伴(诱饵和猎物)和报告蛋白。我们在一小部分但具有不同亲和力的 PPIs(来自六个生物体的十一个蛋白质家族)上验证了该系统的适用性;解离常数范围从 117 pm 到 17 μm。在仅两个小时的反应后,即使是最弱的 PPI 也可以检测到报告蛋白的表达。通过简单的门控分析,可以仅选择具有相同反应伙伴表达水平的细胞。由于这种表达水平的标准化,平均报告蛋白水平直接反映了所研究的 PPIs 的亲和力。通过一组具有已知亲和力的 PPIs,可以构建一个亲和力梯,从而可以快速分类具有迄今未知亲和力的 PPIs。可以使用传统软件进行此分析。为了允许自动分析,我们为基于 Python 的 FlowCytometryTools 包提供了一个图形用户界面。