蛋白激酶C ζ相互作用组的蛋白质组学和生物信息学分析。

IF 2.1 3区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS Proteome Science Pub Date : 2018-02-26 eCollection Date: 2018-01-01 DOI:10.1186/s12953-018-0134-8
Chunyu Hou, Yuan Li, Huiqin Liu, Mengjiao Dang, Guoxuan Qin, Ning Zhang, Ruibing Chen
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引用次数: 6

摘要

背景:蛋白激酶Cζ (PKCζ)是一种非典型蛋白激酶C的异构体,是癌症的关键调节因子。然而,PKCζ调节肿瘤发生和转移的分子和细胞机制尚不完全清楚。本研究通过蛋白质组学和生物信息学分析,建立了与PKCζ相关的蛋白-蛋白相互作用(PPI)网络,为进一步了解PKCζ的多种生物学作用奠定了基础。方法:采用共免疫沉淀法从乳腺癌细胞MDA-MB-231中纯化与PKCζ相关的蛋白复合物,并用LC-MS/MS进行鉴定。分析了2个生物重复和2个技术重复。使用CRAPome数据库过滤观察到的蛋白质,以消除潜在的假阳性。将蛋白质组学鉴定结果与PPI数据库检索相结合,构建相互作用组网络。通过PANTHER数据库和DAVID进行基因本体(GO)和通路分析。接下来,通过免疫共沉淀、Western blotting和免疫荧光验证PKCζ与蛋白磷酸酶2催化亚基α (PPP2CA)的相互作用。利用TCGA数据库和COSMIC数据库分析这两种蛋白在临床样品中的表达情况。结果:构建了以PKCζ为中心的包含178个节点和1225个连接的PPI网络。网络分析表明,鉴定的蛋白质与调节癌症相关细胞过程的几个关键信号通路显著相关。结论:通过结合蛋白质组学和生物信息学分析,构建了以PKCζ为中心的PPI网络,为PKCζ在癌症调控和细胞生物学其他方面的生物学作用提供了更完整的画面。
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Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics.

Background: Protein kinase C ζ (PKCζ), an isoform of the atypical protein kinase C, is a pivotal regulator in cancer. However, the molecular and cellular mechanisms whereby PKCζ regulates tumorigenesis and metastasis are still not fully understood. In this study, proteomics and bioinformatics analyses were performed to establish a protein-protein interaction (PPI) network associated with PKCζ, laying a stepping stone to further understand the diverse biological roles of PKCζ.

Methods: Protein complexes associated with PKCζ were purified by co-immunoprecipitation from breast cancer cell MDA-MB-231 and identified by LC-MS/MS. Two biological replicates and two technical replicates were analyzed. The observed proteins were filtered using the CRAPome database to eliminate the potential false positives. The proteomics identification results were combined with PPI database search to construct the interactome network. Gene ontology (GO) and pathway analysis were performed by PANTHER database and DAVID. Next, the interaction between PKCζ and protein phosphatase 2 catalytic subunit alpha (PPP2CA) was validated by co-immunoprecipitation, Western blotting and immunofluorescence. Furthermore, the TCGA database and the COSMIC database were used to analyze the expressions of these two proteins in clinical samples.

Results: The PKCζ centered PPI network containing 178 nodes and 1225 connections was built. Network analysis showed that the identified proteins were significantly associated with several key signaling pathways regulating cancer related cellular processes.

Conclusions: Through combining the proteomics and bioinformatics analyses, a PKCζ centered PPI network was constructed, providing a more complete picture regarding the biological roles of PKCζ in both cancer regulation and other aspects of cellular biology.

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来源期刊
Proteome Science
Proteome Science 生物-生化研究方法
CiteScore
2.90
自引率
0.00%
发文量
17
审稿时长
4.5 months
期刊介绍: Proteome Science is an open access journal publishing research in the area of systems studies. Proteome Science considers manuscripts based on all aspects of functional and structural proteomics, genomics, metabolomics, systems analysis and metabiome analysis. It encourages the submissions of studies that use large-scale or systems analysis of biomolecules in a cellular, organismal and/or environmental context. Studies that describe novel biological or clinical insights as well as methods-focused studies that describe novel methods for the large-scale study of any and all biomolecules in cells and tissues, such as mass spectrometry, protein and nucleic acid microarrays, genomics, next-generation sequencing and computational algorithms and methods are all within the scope of Proteome Science, as are electron topography, structural methods, proteogenomics, chemical proteomics, stem cell proteomics, organelle proteomics, plant and microbial proteomics. In spite of its name, Proteome Science considers all aspects of large-scale and systems studies because ultimately any mechanism that results in genomic and metabolomic changes will affect or be affected by the proteome. To reflect this intrinsic relationship of biological systems, Proteome Science will consider all such articles.
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