Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Division of General Internal Medicine, New York University Langone Medical Centre, New York, NY, United States.
Front Immunol. 2021 Jul 14;12:691758. doi: 10.3389/fimmu.2021.691758. eCollection 2021.
Influenza is a serious global health threat that shows varying pathogenicity among different virus strains. Understanding similarities and differences among activated functional pathways in the host responses can help elucidate therapeutic targets responsible for pathogenesis. To compare the types and timing of functional modules activated in host cells by four influenza viruses of varying pathogenicity, we developed a new DYNAmic MOdule (DYNAMO) method that addresses the need to compare functional module utilization over time. This integrative approach overlays whole genome time series expression data onto an immune-specific functional network, and extracts conserved modules exhibiting either different temporal patterns or overall transcriptional activity. We identified a common core response to influenza virus infection that is temporally shifted for different viruses. We also identified differentially regulated functional modules that reveal unique elements of responses to different virus strains. Our work highlights the usefulness of combining time series gene expression data with a functional interaction map to capture temporal dynamics of the same cellular pathways under different conditions. Our results help elucidate conservation of the immune response both globally and at a granular level, and provide mechanistic insight into the differences in the host response to infection by influenza strains of varying pathogenicity.
流感是一种严重的全球健康威胁，不同病毒株的致病性存在差异。了解宿主反应中激活的功能途径的相似性和差异性有助于阐明导致发病机制的治疗靶点。为了比较四种不同致病性流感病毒在宿主细胞中激活的功能模块的类型和时间，我们开发了一种新的 DYNAmic MOdule (DYNAMO) 方法，该方法解决了需要随时间比较功能模块利用的问题。这种综合方法将全基因组时间序列表达数据叠加到免疫特异性功能网络上，并提取表现出不同时间模式或整体转录活性的保守模块。我们确定了对流感病毒感染的共同核心反应，该反应在不同病毒中存在时间上的偏移。我们还确定了差异调节的功能模块，这些模块揭示了对不同病毒株反应的独特元素。我们的工作强调了将时间序列基因表达数据与功能相互作用图相结合以捕获不同条件下相同细胞途径的时间动态的有用性。我们的研究结果有助于阐明全球和颗粒水平的免疫反应的保守性，并为不同致病性流感株感染宿主反应的差异提供机制上的见解。
