{"title":"Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics.","authors":"Chunyu Hou, Yuan Li, Huiqin Liu, Mengjiao Dang, Guoxuan Qin, Ning Zhang, Ruibing Chen","doi":"10.1186/s12953-018-0134-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":20857,"journal":{"name":"Proteome Science","volume":"16 ","pages":"5"},"PeriodicalIF":2.1000,"publicationDate":"2018-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12953-018-0134-8","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proteome Science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s12953-018-0134-8","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 6
Abstract
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.
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.