Identification of biological processes that distinguish lethal from non-lethal influenza infection. Mus musculus

Identification of biological processes that distinguish lethal from non-lethal influenza infection and further use of these signatures in a top-down systems analysis investigating the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity to during lethal influenza infection. For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis together with these gene expression and flow data identified a chemokine-driven feed-forward circuit involving pro-inflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation but not ablation of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology. Overall design: Multiple mice were either sham infected, infected with the seasonal H1N1 influenza A virus TX91 (10^6PFU), or infected with various sublethal or lethal doses of the mouse pathogenic H1N1 strain PR8. Lung tissues were collected at various time points (24h, 48h, 72h and 240h post infection) and processed to yield whole lung RNA that was used for microarray analysis. The dataset contains 138 microarrays covering 20 experimental conditions with 7 biological replicates each. As an exception, the alternative non-infectious control condition (Alum treatment) contains 5 biological replicates. This dataset is linked to a dataset comparing the transcriptomes of 5 different cell types isolated from individual lungs of influenza A-infected or control animals (contains 75 microarrays covering 25 experimental conditions).

本研究旨在鉴定区分致死性与非致死性流感感染的生物学过程，并将这些特征应用于自上而下的系统生物学分析（top-down systems analysis），以探究致死性流感感染中，病毒对肺上皮细胞的直接损伤与免疫失调二者相对的致病贡献。
针对急性致死性流感感染，病毒对肺上皮细胞的直接损伤与免疫失调的相对致病贡献迄今尚未明确。为此，本研究采用自上而下的系统生物学策略开展相关研究。受感染肺部的多基因转录特征（transcriptional signatures）提示，炎症信号网络的过度激活可区分致死性与亚致死性感染。
通过对受感染肺部分离的细胞亚群进行流式细胞术（Flow Cytometry）与基因表达分析（gene expression analysis），结果表明中性粒细胞（neutrophil）浸润是该预测性转录特征的主要来源。结合自动成像分析（automated imaging analysis）与上述基因表达及流式细胞术数据，研究发现了一条由趋化因子（chemokine）驱动的前馈环路（feed-forward circuit），该环路涉及受未被有效抑制的致死性病毒强力激活的促炎性中性粒细胞（pro-inflammatory neutrophils）。
与上述数据一致，削弱（而非完全清除）中性粒细胞介导的免疫应答可提升宿主存活率，且不会改变病毒播散情况。本研究结果证实，至少在部分流感致死病例中，损伤性先天炎症反应是核心致病因素，并为系统性解析感染相关病理机制提供了研究框架。
实验设计：实验小鼠分为三组，分别为假感染组、感染季节性甲型H1N1流感病毒TX91株组（10^6PFU），以及感染不同亚致死或致死剂量的小鼠致病性H1N1毒株PR8组。分别于感染后不同时间点（24h、48h、72h及240h）采集肺组织，提取全肺总RNA用于基因芯片（microarray）分析。本数据集包含138个基因芯片样本，对应20种实验条件，每种条件设7个生物学重复（biological replicates）；仅非感染性对照条件（明矾佐剂（Alum）处理组）设5个生物学重复。本数据集与另一数据集相关联，后者用于比较甲型流感病毒感染动物及对照动物肺部分离的5种不同细胞类型的转录组，包含75个基因芯片样本，对应25种实验条件。