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High-throughput identification of protein localization dependency networks

机译:蛋白质定位依赖网络的高通量鉴定

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Bacterial cells are highly organized with many protein complexes and DNA loci dynamically positioned to distinct subcellular sites over the course of a cell cycle. Such dynamic protein localization is essential for polar organelle development, establishment of asymmetry, and chromosome replication during the Caulobacter crescentus cell cycle. We used a fluorescence microscopy screen optimized for high-throughput to find strains with anomalous temporal or spatial protein localization patterns in transposon-generated mutant libraries. Automated image acquisition and analysis allowed us to identify genes that affect the localization of two polar cell cycle histidine kinases, PleC and DivJ, and the pole-specific pili protein CpaE, each tagged with a different fluorescent marker in a single strain. Four metrics characterizing the observed localization patterns of each of the three labeled proteins were extracted for hundreds of cell images from each of 854 mapped mutant strains. Using cluster analysis of the resulting set of 12-element vectors for each of these strains, we identified 52 strains with mutations that affected the localization pattern of the three tagged proteins. This information, combined with quantitative localization data from epitasis experiments, also identified all previously known proteins affecting such localization. These studies provide insights into factors affecting the PleC/DivJ localization network and into regulatory links between the localization of the pili assembly protein CpaE and the kinase localization pathway. Our high-throughput screening methodology can be adapted readily to any sequenced bacterial species, opening the potential for databases of localization regulatory networks across species, and investigation of localization network phylogenies.
机译:细菌细胞是高度组织的,具有许多蛋白质复合物和DNA基因座,在细胞周期过程中动态定位到不同的亚细胞部位。这种动态蛋白质定位对于新月形杆菌细胞周期中的极性细胞器发育,不对称建立和染色体复制至关重要。我们使用了针对高通量优化的荧光显微镜屏幕,以在转座子产生的突变体文库中发现具有异常时空或空间蛋白质定位模式的菌株。自动化的图像采集和分析使我们能够鉴定出影响两个极性细胞周期组氨酸激酶PleC和DivJ以及极点特异性菌毛蛋白CpaE定位的基因,每个基因在单个菌株中均标记有不同的荧光标记。从854个作图突变菌株中的每一个中提取了数百个细胞图像的四个度量,这些度量表征了三种标记蛋白质中每种蛋白质的观察到的定位模式。使用这些菌株中每个菌株的12个元素载体的结果集的聚类分析,我们鉴定出52个突变的菌株,这些突变影响了三个标记蛋白的定位模式。该信息与来自流行病学实验的定量定位数据相结合,还确定了影响该定位的所有先前已知的蛋白质。这些研究为影响PleC / DivJ定位网络的因素以及菌毛组装蛋白CpaE的定位与激酶定位途径之间的调控联系提供了见解。我们的高通量筛选方法可以很容易地适应任何测序的细菌物种,从而为跨物种的本地化调控网络数据库以及对本地化网络系统发育的研究提供了潜力。

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