Yu Chunyu, Shen Boyan, You Kaiqiang, Huang Qi, Shi Minglei, Wu Congying, Chen Yang, Zhang Chaolin, Li Tingting
Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; School of Medicine, Tsinghua University, Beijing, China.
Brief Bioinform. 2021 May 20;22(3). doi: 10.1093/bib/bbaa187.
Phase separation is an important mechanism that mediates the spatial distribution of proteins in different cellular compartments. While phase-separated proteins share certain sequence characteristics, including intrinsically disordered regions (IDRs) and prion-like domains, such characteristics are insufficient for making accurate predictions; thus, a proteome-wide understanding of phase separation is currently lacking. Here, we define phase-separated proteomes based on the systematic analysis of immunofluorescence images of 12 073 proteins in the Human Protein Atlas. The analysis of these proteins reveals that phase-separated candidate proteins exhibit higher IDR contents, higher mean net charge and lower hydropathy and prefer to bind to RNA. Kinases and transcription factors are also enriched among these candidate proteins. Strikingly, both phase-separated kinases and phase-separated transcription factors display significantly reduced substrate specificity. Our work provides the first global view of the phase-separated proteome and suggests that the spatial proximity resulting from phase separation reduces the requirement for motif specificity and expands the repertoire of substrates. The source code and data are available at https://github.com/cheneyyu/deepphase.
相分离是一种重要机制,介导蛋白质在不同细胞区室中的空间分布。虽然相分离的蛋白质具有某些序列特征,包括内在无序区域(IDR)和类朊病毒结构域,但这些特征不足以进行准确预测;因此,目前缺乏对相分离的全蛋白质组理解。在这里,我们基于对人类蛋白质图谱中12073种蛋白质的免疫荧光图像的系统分析来定义相分离蛋白质组。对这些蛋白质的分析表明,相分离候选蛋白质表现出更高的IDR含量、更高的平均净电荷和更低的亲水性,并且倾向于与RNA结合。激酶和转录因子在这些候选蛋白质中也很丰富。引人注目的是,相分离的激酶和相分离的转录因子都表现出显著降低的底物特异性。我们的工作提供了相分离蛋白质组的首个全局视图,并表明相分离导致的空间接近性降低了对基序特异性的要求,并扩大了底物的种类。源代码和数据可在https://github.com/cheneyyu/deepphase获取。