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病毒重配作为病毒片段之间的信息交流。

Viral reassortment as an information exchange between viral segments.

机构信息

The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540, USA.

出版信息

Proc Natl Acad Sci U S A. 2012 Feb 28;109(9):3341-6. doi: 10.1073/pnas.1113300109. Epub 2012 Feb 13.

Abstract

Viruses have an extraordinary ability to diversify and evolve. For segmented viruses, reassortment can introduce drastic genomic and phenotypic changes by allowing a direct exchange of genetic material between coinfecting strains. For instance, multiple influenza pandemics were caused by reassortments of viruses typically found in separate hosts. What is unclear, however, are the underlying mechanisms driving these events and the level of intrinsic bias in the diversity of strains that emerge from coinfection. To address this problem, previous experiments looked for correlations between segments of strains that coinfect cells in vitro. Here, we present an information theory approach as the natural mathematical framework for this question. We study, for influenza and other segmented viruses, the extent to which a virus's segments can communicate strain information across an infection and among one another. Our approach goes beyond previous association studies and quantifies how much the diversity of emerging strains is altered by patterns in reassortment, whether biases are consistent across multiple strains and cell types, and if significant information is shared among more than two segments. We apply our approach to a new experiment that examines reassortment patterns between the 2009 H1N1 pandemic and seasonal H1N1 strains, contextualizing its segmental information sharing by comparison with previously reported strain reassortments. We find evolutionary patterns across classes of experiments and previously unobserved higher-level structures. Finally, we show how this approach can be combined with virulence potentials to assess pandemic threats.

摘要

病毒具有非凡的多样化和进化能力。对于分段病毒来说,重配可以通过在共感染的菌株之间直接交换遗传物质,引入剧烈的基因组和表型变化。例如,多次流感大流行是由通常在不同宿主中发现的病毒的重配引起的。然而,尚不清楚驱动这些事件的潜在机制以及共感染产生的菌株多样性的内在偏差程度。为了解决这个问题,先前的实验寻找了在体外共感染细胞的菌株片段之间的相关性。在这里,我们提出了一种信息论方法作为这个问题的自然数学框架。我们研究了流感和其他分段病毒的情况,即在感染过程中和彼此之间,病毒的片段可以在多大程度上传递菌株信息。我们的方法超越了以前的关联研究,并量化了重配模式改变新出现菌株多样性的程度,偏差是否在多个菌株和细胞类型中一致,以及是否在两个以上的片段之间共享重要信息。我们将我们的方法应用于一项新的实验,该实验研究了 2009 年 H1N1 大流行株和季节性 H1N1 株之间的重配模式,并通过与先前报道的菌株重配进行比较,对其片段信息共享进行了背景化处理。我们发现了跨实验类别的进化模式和以前未观察到的更高层次结构。最后,我们展示了如何将这种方法与毒力潜力结合起来评估大流行威胁。

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