controlling the response predictive modeling of a highly central, pathogen-targeted core response module in macrophage activation控制的响应预测建模一个高度中央,在巨噬细胞激活pathogen-targeted核心响应模块.pdf

Controlling the Response: Predictive Modeling of a Highly Central, Pathogen-Targeted Core Response Module in Macrophage Activation 1 . 1. 2 3 1 Jason E. McDermott * , Michelle Archuleta , Brian D. Thrall , Joshua N. Adkins , Katrina M. Waters 1 Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington, United States of America, 2 Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, United States of America, 3 Biological Separations and Mass Spectrometry, Pacific Northwest National Laboratory, Richland, Washington, United States of America Abstract We have investigated macrophage activation using computational analyses of a compendium of transcriptomic data covering responses to agonists of the TLR pathway, Salmonella infection, and manufactured amorphous silica nanoparticle exposure. We inferred regulatory relationship networks using this compendium and discovered that genes with high betweenness centrality, so-called bottlenecks, code for proteins targeted by pathogens. Furthermore, combining a novel set of bioinformatics tools, topological analysis with analysis of differentially expressed genes under the different stimuli, we identified a conserved core response module that is differentially expressed in response to all studied conditions. This module occupies a highly central position in the inferred network and is also enriched in genes preferentially targeted by pathogens. The module includes cytokines, interferon induced genes such as Ifit1 and 2, effectors of inflammation, Cox1 and Oas1 and Oasl2, and transcription factors including AP1, Egr1 and 2 and Mafb. Predictive modeling using a revers