Centre National de la Recherche Scientifique (CNRS) FRE 3011 Virologie et Pathologie Humaine, Université Lyon 1, Lyon, France.
PLoS One. 2010 Oct 4;5(10):e13169. doi: 10.1371/journal.pone.0013169.
Classical antiviral therapies target viral proteins and are consequently subject to resistance. To counteract this limitation, alternative strategies have been developed that target cellular factors. We hypothesized that such an approach could also be useful to identify broad-spectrum antivirals. The influenza A virus was used as a model for its viral diversity and because of the need to develop therapies against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection by different influenza A virus subtypes which would allow the identification of potential antiviral drugs with a broad anti-influenza spectrum of activity. We analyzed the cellular gene expression response to infection with five different human and avian influenza A virus strains and identified 300 genes as differentially expressed between infected and non-infected samples. The most 20 dysregulated genes were used to screen the connectivity map, a database of drug-associated gene expression profiles. Candidate antivirals were then identified by their inverse correlation to the query signature. We hypothesized that such molecules would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified and their effects were tested in vitro on five influenza A strains. Six of the molecules inhibited influenza viral growth. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five out of the eight identified molecules, demonstrating that this strategy could contribute to identifying new broad anti-influenza agents acting on cellular gene expression. The identified infection signature genes, the expression of which are modified upon infection, could encode cellular proteins involved in the viral life cycle. This is the first study showing that gene expression-based screening can be used to identify antivirals. Such an approach could accelerate drug discovery and be extended to other pathogens.
经典的抗病毒疗法针对病毒蛋白，因此容易产生耐药性。为了克服这一限制，已经开发了针对细胞因子的替代策略。我们假设这种方法也可用于鉴定广谱抗病毒药物。甲型流感病毒被用作模型，因为它具有多种病毒多样性，并且由于最近 H1N1 大流行突显了需要开发针对不可预测病毒的疗法。我们提出鉴定与不同甲型流感病毒亚型感染相关的基因表达特征，这将允许鉴定具有广谱抗流感活性的潜在抗病毒药物。我们分析了感染五种不同的人源和禽源甲型流感病毒株后细胞基因表达的反应，并鉴定了 300 个差异表达的基因。最上调的 20 个基因被用于筛选连接图谱，这是一个药物相关基因表达谱数据库。候选抗病毒药物通过与查询特征的反向相关性来识别。我们假设这些分子会诱导不利于流感病毒复制的细胞环境。鉴定出 8 种潜在的抗病毒药物，包括利巴韦林，并在体外对 5 种甲型流感病毒株进行了测试。其中 6 种分子抑制了流感病毒的生长。新的大流行 H1N1 病毒未用于定义感染的基因表达特征，但被鉴定出的 8 种分子中的 5 种抑制了该病毒，这表明这种策略有助于鉴定新的广谱抗流感药物，这些药物通过作用于细胞基因表达来发挥作用。鉴定出的感染特征基因，其表达在感染后会发生改变，可能编码参与病毒生命周期的细胞蛋白。这是第一项表明基于基因表达的筛选可用于鉴定抗病毒药物的研究。这种方法可以加速药物发现，并可扩展到其他病原体。
