Will Thorsten, Helms Volkhard
Center for Bioinformatics and Graduate School of Computer Science, Saarland University, Saarbrücken, Germany.
Center for Bioinformatics and.
Bioinformatics. 2016 Feb 15;32(4):571-8. doi: 10.1093/bioinformatics/btv620. Epub 2015 Oct 27.
Protein-protein interaction networks are an important component of modern systems biology. Yet, comparatively few efforts have been made to tailor their topology to the actual cellular condition being studied. Here, we present a network construction method that exploits expression data at the transcript-level and thus reveals alterations in protein connectivity not only caused by differential gene expression but also by alternative splicing. We achieved this by establishing a direct correspondence between individual protein interactions and underlying domain interactions in a complete but condition-unspecific protein interaction network. This knowledge was then used to infer the condition-specific presence of interactions from the dominant protein isoforms. When we compared contextualized interaction networks of matched normal and tumor samples in breast cancer, our transcript-based construction identified more significant alterations that affected proteins associated with cancerogenesis than a method that only uses gene expression data. The approach is provided as the user-friendly tool PPIXpress.
PPIXpress is available at https://sourceforge.net/projects/ppixpress/.
蛋白质-蛋白质相互作用网络是现代系统生物学的重要组成部分。然而,相对较少有人致力于根据所研究的实际细胞状况来调整其拓扑结构。在此,我们提出一种网络构建方法,该方法利用转录水平的表达数据,从而不仅揭示由差异基因表达引起的蛋白质连接性变化,还揭示由可变剪接引起的变化。我们通过在一个完整但不依赖于特定条件的蛋白质相互作用网络中建立个体蛋白质相互作用与潜在结构域相互作用之间的直接对应关系来实现这一点。然后利用这些知识从主要蛋白质异构体推断特定条件下相互作用的存在情况。当我们比较乳腺癌中匹配的正常样本和肿瘤样本的情境化相互作用网络时,与仅使用基因表达数据的方法相比,我们基于转录本的构建方法识别出更多影响与癌症发生相关蛋白质的显著变化。该方法作为用户友好型工具PPIXpress提供。