An Interactive Macrophage Signal Transduction Map Facilitates Comparative Analyses of High-Throughput Data

JOURNAL OF IMMUNOLOGY(2017)

引用 17|浏览11
暂无评分
摘要
Macrophages (Mfs) are key players in the coordination of the lifesaving or detrimental immune response against infections. The mechanistic understanding of the functional modulation of Mfs by pathogens and pharmaceutical interventions at the signal transduction level is still far from complete. The complexity of pathways and their cross-talk benefits from holistic computational approaches. In the present study, we reconstructed a comprehensive, validated, and annotated map of signal transduction pathways in inflammatory Mfs based on the current literature. In a second step, we selectively expanded this curated map with database knowledge. We provide both versions to the scientific community via a Web platform that is designed to facilitate exploration and analysis of high-throughput data. The platform comes preloaded with logarithmic fold changes from 44 data sets on Mf stimulation. We exploited three of these data sets-human primary Mfs infected with the common lung pathogens Streptococcus pneumoniae, Legionella pneumophila, or Mycobacterium tuberculosis-in a case study to show how our map can be customized with expression data to pinpoint regulated subnetworks and druggable molecules. From the three infection scenarios, we extracted a regulatory core of 41 factors, including TNF, CCL5, CXCL10, IL-18, and IL-12 p40, and identified 140 drugs targeting 16 of them. Our approach promotes a comprehensive systems biology strategy for the exploitation of high-throughput data in the context of Mf signal transduction. In conclusion, we provide a set of tools to help scientists unravel details of Mf signaling. The interactive version of our Mf signal transduction map is accessible online at https://vcells.net/macrophage.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要