Understanding inhibition of viral proteins on type I IFN signaling pathways with modeling and optimization.
The interferon system provides a powerful and universal intracellular defense mechanism against viruses. As one part of their survival strategies, many viruses have evolved mechanisms to counteract the host type I interferon (IFN-alpha/beta) responses. In this study, we attempt to investigate virus- and double-strand RNA (dsRNA)-triggered type I IFN signaling pathways and understand the inhibition of IFN-alpha/beta induction by viral proteins using mathematical modeling and quantitative analysis. Based on available literature and our experimental data, we develop a mathematical model of virus- and dsRNA-triggered signaling pathways leading to type I IFN gene expression during the primary response, and use the genetic algorithm to optimize all rate constants in the model. The consistency between numerical simulation results and biological experimental data demonstrates that our model is reasonable. Further, we use the model to predict the following phenomena: (1) the dose-dependent inhibition by classical swine fever virus (CSFV) N(pro) or E(rns) protein is observed at a low dose and can reach a saturation above a certain dose, not an increase; (2) E(rns) and N(pro) have no synergic inhibitory effects on IFN-beta induction; (3) the different characters in an important transcription factor, phosphorylated IRF3 (IRF3p), are exhibited because N(pro) or E(rns) counteracted dsRNA- and virus-triggered IFN-beta induction by targeting the different molecules in the signaling pathways and (4) N(pro) inhibits the IFN-beta expression not only by interacting with IFR3 but also by affecting its complex with MITA. Our approaches help to gain insight into system properties and rational therapy design, as well as to generate hypotheses for further research.
Zou
Xiufen
X
School of Mathematics and Statistics, Wuhan University, Wuhan, China.
Xiang
Xueshuang
X
Chen
Yan
Y
Peng
Tao
T
Luo
Xuelian
X
Pan
Zishu
Z
D033942:Adaptor Proteins, Vesicular Transport / Q000378:metabolism; D000818:Animals; D002460:Cell Line; D006692:Classical Swine Fever Virus / Q000187:drug effects / Q000276:immunology; D003198:Computer Simulation; D050835:Interferon Regulatory Factors / Q000378:metabolism; D007370:Interferon Type I / Q000235:genetics / Q000276:immunology*; D016899:Interferon-beta / Q000276:immunology; D008954:Models, Biological; D010957:Plasmids / Q000235:genetics; D011070:Poly I-C / Q000494:pharmacology; D012330:RNA, Double-Stranded / Q000378:metabolism; D029082:Sendai virus / Q000187:drug effects / Q000276:immunology; D015398:Signal Transduction / Q000187:drug effects / Q000276:immunology*; D013552:Swine; D013997:Time Factors; D014764:Viral Proteins / Q000037:antagonists & inhibitors* / Q000378:metabolism
D033942:Adaptor Proteins, Vesicular Transport; D050835:Interferon Regulatory Factors; D007370:Interferon Type I; D012330:RNA, Double-Stranded; D014764:Viral Proteins; D016899:Interferon-beta; D011070:Poly I-C