Elzawahry Asmaa, Patil Ashwini, Kumagai Yutaro, Suzuki Yutaka, Nakai Kenta
Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo, Japan. ; Graduate school of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba, Japan.
Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo, Japan.
Gene Regul Syst Bio. 2014 Jan 6;8:1-15. doi: 10.4137/GRSB.S12850.
Innate immune response involves protein-protein interactions, deoxyribonucleic acid (DNA)-protein interactions and signaling cascades. So far, thousands of protein-protein interactions have been curated as a static interaction map. However, protein-protein interactions involved in innate immune response are dynamic. We recorded the dynamics in the interactome during innate immune response by combining gene expression data of lipopolysaccharide (LPS)-stimulated dendritic cells with protein-protein interactions data. We identified the differences in interactome during innate immune response by constructing differential networks and identifying protein modules, which were up-/down-regulated at each stage during the innate immune response. For each protein complex, we identified enriched biological processes and pathways. In addition, we identified core interactions that are conserved throughout the innate immune response and their enriched gene ontology terms and pathways. We defined two novel measures to assess the differences between network maps at different time points. We found that the protein interaction network at 1 hour after LPS stimulation has the highest interactions protein ratio, which indicates a role for proteins with large number of interactions in innate immune response. A pairwise differential matrix allows for the global visualization of the differences between different networks. We investigated the toll-like receptor subnetwork and found that S100A8 is down-regulated in dendritic cells after LPS stimulation. Identified protein complexes have a crucial role not only in innate immunity, but also in circadian rhythms, pathways involved in cancer, and p53 pathways. The study confirmed previous work that reported a strong correlation between cancer and immunity.
天然免疫反应涉及蛋白质-蛋白质相互作用、脱氧核糖核酸(DNA)-蛋白质相互作用和信号级联反应。到目前为止,数千种蛋白质-蛋白质相互作用已被整理成一个静态相互作用图谱。然而,参与天然免疫反应的蛋白质-蛋白质相互作用是动态的。我们通过将脂多糖(LPS)刺激的树突状细胞的基因表达数据与蛋白质-蛋白质相互作用数据相结合,记录了天然免疫反应过程中相互作用组的动态变化。我们通过构建差异网络并识别在天然免疫反应各阶段上调/下调的蛋白质模块,确定了天然免疫反应过程中相互作用组的差异。对于每个蛋白质复合物,我们确定了富集的生物学过程和通路。此外,我们还确定了在整个天然免疫反应中保守的核心相互作用及其富集的基因本体术语和通路。我们定义了两种新的指标来评估不同时间点网络图谱之间的差异。我们发现,LPS刺激后1小时的蛋白质相互作用网络具有最高的相互作用蛋白比例,这表明具有大量相互作用的蛋白质在天然免疫反应中发挥作用。成对差异矩阵允许全局可视化不同网络之间的差异。我们研究了Toll样受体子网,发现LPS刺激后树突状细胞中的S100A8被下调。鉴定出的蛋白质复合物不仅在天然免疫中起关键作用,而且在昼夜节律、癌症相关通路和p53通路中也起关键作用。该研究证实了先前报道癌症与免疫之间存在强相关性的工作。