Departments of Medicine and Bioengineering, University of California San Diego, La Jolla, CA, USA.
Mol Syst Biol. 2012 Jan 17;8:565. doi: 10.1038/msb.2011.99.
Protein and genetic interaction maps can reveal the overall physical and functional landscape of a biological system. To date, these interaction maps have typically been generated under a single condition, even though biological systems undergo differential change that is dependent on environment, tissue type, disease state, development or speciation. Several recent interaction mapping studies have demonstrated the power of differential analysis for elucidating fundamental biological responses, revealing that the architecture of an interactome can be massively re-wired during a cellular or adaptive response. Here, we review the technological developments and experimental designs that have enabled differential network mapping at very large scales and highlight biological insight that has been derived from this type of analysis. We argue that differential network mapping, which allows for the interrogation of previously unexplored interaction spaces, will become a standard mode of network analysis in the future, just as differential gene expression and protein phosphorylation studies are already pervasive in genomic and proteomic analysis.
蛋白质和遗传相互作用图谱可以揭示生物系统的整体物理和功能结构。迄今为止,这些相互作用图谱通常是在单一条件下生成的,尽管生物系统会根据环境、组织类型、疾病状态、发育或物种形成而发生差异变化。最近的几项相互作用图谱研究表明,差异分析对于阐明基本生物学反应具有强大的作用,揭示了在细胞或适应性反应过程中,相互作用组的结构可以进行大规模的重新布线。在这里,我们回顾了使大规模差异网络图谱绘制成为可能的技术发展和实验设计,并强调了从这种分析中获得的生物学见解。我们认为,差异网络图谱分析可以用于探究以前未知的相互作用空间,将来它将成为网络分析的一种标准模式,就像差异基因表达和蛋白质磷酸化研究已经在基因组和蛋白质组分析中无处不在一样。