Characterizing and controlling the inflammatory network during influenza A virus infection.
To gain insights into the pathogenesis of influenza A virus (IAV) infections, this study focused on characterizing the inflammatory network and identifying key proteins by combining high-throughput data and computational techniques. We constructed the cell-specific normal and inflammatory networks for H5N1 and H1N1 infections through integrating high-throughput data. We demonstrated that better discrimination between normal and inflammatory networks by network entropy than by other topological metrics. Moreover, we identified different dynamical interactions among TLR2, IL-1β, IL10 and NFκB between normal and inflammatory networks using optimization algorithm. In particular, good robustness and multistability of inflammatory sub-networks were discovered. Furthermore, we identified a complex, TNFSF10/HDAC4/HDAC5, which may play important roles in controlling inflammation, and demonstrated that changes in network entropy of this complex negatively correlated to those of three proteins: TNFα, NFκB and COX-2. These findings provide significant hypotheses for further exploring the molecular mechanisms of infectious diseases and developing control strategies.
School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.
Suoqin
S
Jin
School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.
Yuanyuan
Y
Li
State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan 430072, China.
Ruangang
R
Pan
School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.
Xiufen
X
Zou
D019277:Entropy; D053263:Gene Regulatory Networks; D006801:Humans; D007249:Inflammation / Q000150:complications / Q000235:genetics* / Q000473:pathology / Q000821:virology*; D053118:Influenza A Virus, H1N1 Subtype / Q000472:pathogenicity; D053124:Influenza A Virus, H5N1 Subtype / Q000472:pathogenicity; D007251:Influenza, Human / Q000150:complications / Q000235:genetics* / Q000473:pathology / Q000821:virology*; D008962:Models, Theoretical