Single-cell analysis and stochastic modelling unveil large cell-to-cell variability in influenza A virus infection.
Single-cell analysis and stochastic modelling unveil large cell-to-cell variability in influenza A virus infection.
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单细胞分析和随机建模揭示了流感病毒感染中大型细胞对细胞变异性。
DOI：
10.1038/ncomms9938
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发表时间：
2015-11-20
影响因子：
16.6
通讯作者：
Frensing T
中科院分区：
文献类型：
--
作者：
Heldt FS;Kupke SY;Dorl S;Reichl U;Frensing T
生化反应容易受到随机波动的影响，这可能会导致细胞间的可变性。然而，这种变异性如何影响病毒感染，这本身就涉及到嘈杂的反应，在很大程度上仍然难以捉摸。在这里，我们介绍了单细胞实验和随机模拟，揭示了甲型流感病毒(IAV)感染细胞之间的巨大异质性。特别是，实验数据显示，子代病毒滴度从1到970个空斑形成单位，细胞内病毒RNA(VRNA)水平跨越三个数量级。此外，IAV基因组的分割似乎增加了它们对噪声的复制敏感性，因为不同基因组片段的水平在一个细胞内可能有很大差异。此外，模拟表明，病毒入侵的流产和vRNAs的随机降解可以导致单次感染后很大一部分非生产性细胞。这些结果挑战了当前的信念，即细胞数量测量和确定性模拟是病毒感染的准确代表。病毒感染中细胞间的可变性意味着细胞数量的测量可能不能准确地反映这一过程。使用实验和模拟方法，作者证实了这一概念，表明流感病毒感染是受内在和外在噪声影响的可变过程。
Biochemical reactions are subject to stochastic fluctuations that can give rise to cell-to-cell variability. Yet, how this variability affects viral infections, which themselves involve noisy reactions, remains largely elusive. Here we present single-cell experiments and stochastic simulations that reveal a large heterogeneity between influenza A virus (IAV)-infected cells. In particular, experimental data show that progeny virus titres range from 1 to 970 plaque-forming units and intracellular viral RNA (vRNA) levels span three orders of magnitude. Moreover, the segmentation of IAV genomes seems to increase the susceptibility of their replication to noise, since the level of different genome segments can vary substantially within a cell. In addition, simulations suggest that the abortion of virus entry and random degradation of vRNAs can result in a large fraction of non-productive cells after single-hit infection. These results challenge current beliefs that cell population measurements and deterministic simulations are an accurate representation of viral infections. Cell-to-cell variability in viral infection means that cell population measurements may not be an accurate representation of the process. Using both experimental and modelling approaches the authors confirm this notion showing that influenza virus infections are variable processes affected by intrinsic and extrinsic noise.