An integrated approach to identify critical transcription factors in the protection against hydrogen peroxide-induced oxidative stress by Danhong injection

Publication date: November 2017
Source:Free Radical Biology and Medicine, Volume 112
Author(s): Jingjing Zhang, Feifei Guo, Junying Wei, Minghua Xian, Shihuan Tang, Ye Zhao, Mingwei Liu, Lei Song, Ya Geng, Hongjun Yang, Chen Ding, Luqi Huang
Oxidative stress plays a vital role in many pathological processes of the cardiovascular diseases. However, the underlying mechanism remains unclear, especially on a transcription factor (TF) level. In this study, a new method, concatenated tandem array of consensus transcription factor response elements (catTFREs), and an Illumina-based RNA-seq technology were integrated to systematically investigate the role of TFs in hydrogen peroxide (H2O2)-induced oxidative stress in cardiomyocytes; the damage was then rescued by Danhong injection (DHI), a Chinese standardized product approved for cardiovascular diseases treatment. The overall gene expression revealed cell apoptosis and DNA repair were vital for cardiomyocytes in resisting oxidative stress. By comprehensively integrating the transcription activity of TFs and their downstream target genes, an important TFs-target network were constructed and 13 TFs were identified as critical TFs in DHI-mediated protection in H2O2-induced oxidative stress. By using the integrated approach, seven TFs of these 13 TFs were also identified in melatonin-mediated protection in H2O2-induced damage. Furthermore, the transcription activity of DNA-(apurinic or apyrimidinic site) lyase (Apex1), Myocyte-specific enhancer factor 2D (Mef2d) and Pre B-cell leukemia transcription factor 3 (Pbx3) was further verified in pluripotent stem cell-derived cardiomyocytes. This research offers a new understanding of cardiomyocytes in response to H2O2-induced oxidative stress and reveals additional potential therapeutic targets. The combination of two parallel omics datasets (corresponding to the transcriptome and proteome) can reduce the noise in high-throughput data and reveal the fundamental changes of the biological process, making it suitable and reliable for investigation of critical targets in many other complicated pathological processes.

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