MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, United Kingdom.
Section of Virology, Department of Medicine, Imperial College London, London W2 1PG, United Kingdom.
Epidemics. 2020 Dec;33:100406. doi: 10.1016/j.epidem.2020.100406. Epub 2020 Oct 3.
When analysing in vitro data, growth kinetics of influenza virus strains are often compared by computing their growth rates, which are sometimes used as proxies for fitness. However, analogous to mathematical models for epidemics, the growth rate can be defined as a function of mechanistic traits: the basic reproduction number (the average number of cells each infected cell infects) and the mean generation time (the average length of a replication cycle). Fitting a model to previously published and newly generated data from experiments in human lung cells, we compared estimates of growth rate, reproduction number and generation time for six influenza A strains. Of four strains in previously published data, A/Canada/RV733/2003 (seasonal H1N1) had the lowest basic reproduction number, followed by A/Mexico/INDRE4487/2009 (pandemic H1N1), then A/Indonesia/05/2005 (spill-over H5N1) and A/Anhui/1/2013 (spill-over H7N9). This ordering of strains was preserved for both generation time and growth rate, suggesting a positive biological correlation between these quantities which have not been previously observed. We further investigated these potential correlations using data from reassortant viruses with different internal proteins (from A/England/195/2009 (pandemic H1N1) and A/Turkey/05/2005 (H5N1)), and the same surface proteins (from A/Puerto Rico/8/34 (lab-adapted H1N1)). Similar correlations between traits were observed for these viruses, confirming our initial findings and suggesting that these patterns were related to the degree of human adaptation of internal genes. Also, the model predicted that strains with a smaller basic reproduction number, shorter generation time and slower growth rate underwent more replication cycles by the time of peak viral load, potentially accumulating mutations more quickly. These results illustrate the utility of mathematical models in inferring traits driving observed differences in in vitro growth of influenza strains.
当分析体外数据时，通常通过计算病毒株的增长率来比较其生长动力学，而增长率有时被用作适合度的替代指标。然而，类似于传染病的数学模型，增长率可以定义为机制特征的函数：基本繁殖数（每个感染细胞感染的平均细胞数）和平均世代时间（复制周期的平均长度）。我们根据先前发表的和新生成的来自人肺细胞实验的数据拟合模型，比较了六种甲型流感病毒株的增长率、繁殖数和世代时间的估计值。在先前发表的数据中，四种病毒株中，A/Canada/RV733/2003（季节性 H1N1）的基本繁殖数最低，其次是 A/Mexico/INDRE4487/2009（大流行 H1N1），然后是 A/Indonesia/05/2005（溢出 H5N1）和 A/Anhui/1/2013（溢出 H7N9）。这种病毒株的排序在世代时间和增长率上都得到了保留，这表明这两个数量之间存在正生物学相关性，而这一点以前没有观察到。我们使用具有不同内部蛋白的重配病毒的数据（来自 A/England/195/2009（大流行 H1N1）和 A/Turkey/05/2005（H5N1））和相同的表面蛋白（来自 A/Puerto Rico/8/34（实验室适应的 H1N1））进一步研究了这些潜在的相关性。这些病毒的特征之间也观察到了相似的相关性，证实了我们的初步发现，并表明这些模式与内部基因的人类适应程度有关。此外，该模型预测，基本繁殖数较小、世代时间较短、生长速度较慢的病毒株在达到病毒载量峰值时经历更多的复制周期，可能更快地积累突变。这些结果说明了数学模型在推断导致流感病毒株在体外生长差异的特征方面的实用性。
