Comprehensive bioinformatics analysis reveals kinase activity profiling associated with heart failure. Issue 9 (25th April 2021)

• Record Type: Journal Article
• Authors: Zhang, Zhen; Tian, Saisai; Wu, Chennan; Yan, Li; Wan, Jingjing; Zhang, Jinbo; Liu, Xia; Zhang, Weidong
• Is Part Of: Journal of cellular biochemistry. Volume 122:Issue 9(2021)
• Page Start: 1126
• Page End: 1140
• Publication Date: 2021-04-25
• Subjects: bioinformatics -- heart failure -- kinases -- phosphoproteomics -- transcriptomics; Cytochemistry -- Periodicals; 572
• DOI: 10.1002/jcb.29935
• Languages: English
• ISSNs: 0730-2312

Abstract

Abstract: Heart failure is a complex clinical syndrome originating from cardiac injury, which leads to considerable morbidity and mortality. Among the dynamic molecular adaptations occurring in heart failure development, aggravation of the disease is often attributed to global or local abnormality of the kinase. Therefore, the overall monitoring of kinase activity is indispensable. In this study, a bioinformatics analysis method was developed to conduct deep mining of transcriptome and phosphoproteome in failing heart tissue. A total of 982 differentially expressed genes and 9781 phosphorylation sites on 3252 proteins were identified. Via upstream regulator relations and kinase‐substrate relations, a dendrogram of kinases can be constructed to monitor its abnormality. The results show that, on the dendrogram, the distribution of kinases demonstrated complex kinase activity changes and certain rules that occur during heart failure. Finally, we also identified the hub kinases in heart failure and verified the expression of these kinases by reverse‐transcription polymerase chain reaction and Western blot analysis. In conclusion, for the first time, we have systematically analyzed the differences in kinases during heart failure and provided an unprecedented breadth of multi‐omics data. These results can bring about a sufficient data foundation and novel research perspectives. Abstract : A bioinformatics analysis method was developed to conduct in‐depth mining of the transcriptome and phosphoproteome to monitor abnormal kinase activity. At the same time, information about gene networks and specific phosphorylation sites regulated by kinases can be obtained. ​