On the laws of virus spread through cell populations.
On the laws of virus spread through cell populations.
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关于病毒通过细胞群传播的规律。
DOI：
10.1128/jvi.02096-14
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发表时间：
2014
影响因子：
5.4
通讯作者：
Levy,DavidN
中科院分区：
文献类型：
--
作者：
Wodarz,Dominik;Chan,ChiN;Trinité,Benjamin;Komarova,NataliaL;Levy,DavidN
病毒感染的动力学已经被广泛研究，通常结合实验和数学方法。病毒通过细胞群传播的数学描述在文献中已经很好地建立，并产生了重要的见解，但病毒动力学模型的某些基本方面的制定仍然不确定和未经测试。在这里，我们研究了感染的过程，特别是不同的靶细胞群体大小对产生的有效感染细胞数量的影响。利用一个体外单轮HIV-1感染系统，我们发现所建立的建模框架不能准确拟合数据。如果模型拟合具有最低细胞数量的数据并用于预测用较大细胞群体产生的数据，则模型显著高估了产生的有效感染细胞的数量。有趣的是，这种偏差在促进细胞和病毒混合的实验条件下变得更强。出现这种偏差的原因是，标准模型对病毒的命运做出了某些过于简单的假设，这些病毒无法在其附近找到一个细胞。我们从随机过程中推导出一个不同的模型，该模型假设病毒同时进入多个靶细胞。在这种情况下，如果病毒所在的位置没有细胞可用，它就有机会与其他细胞相互作用，这一过程可以通过混合种群来促进。该模型可以准确地拟合实验数据，并建议在病毒动力学models.IMPORTANCEUnderstanding病毒生长的原则，通过细胞群体的质量作用的一个新的解释是至关重要的病毒学。它帮助我们对旨在预防病毒生长的干预策略做出明智的决定，例如药物治疗或疫苗接种方法，例如，在艾滋病毒感染方面，这是一个很大的挑战，但在这方面仍然存在很大的不确定性。在这种情况下，一个重要的变量是可用于病毒复制的易感细胞的数量。易感细胞的数量如何影响病毒的生长潜力？除了这些信息对临床反应的重要性外，彻底了解这些信息对于预测患者体内的病毒水平以及通过使用数学模型估计关键的患者参数也很重要。本文结合实验和数学方法研究了靶细胞可用性和病毒生长潜力之间的关系，并提供了重要的新见解。
The dynamics of viral infections have been investigated extensively, often with a combination of experimental and mathematical approaches. Mathematical descriptions of virus spread through cell populations are well established in the literature and have yielded important insights, yet the formulation of certain fundamental aspects of virus dynamics models remains uncertain and untested. Here, we investigate the process of infection and, in particular, the effect of varying the target cell population size on the number of productively infected cells generated. Using anin vitrosingle-round HIV-1 infection system, we find that the established modeling framework cannot accurately fit the data. If the model is fit to data with the lowest number of cells and is used to predict data generated with larger cell populations, the model significantly overestimates the number of productively infected cells generated. Interestingly, this deviation becomes stronger under experimental conditions that promote mixing of cells and viruses. The reason for the deviation is that the standard model makes certain oversimplifying assumptions about the fate of viruses that fail to find a cell in their immediate proximity. We derive from stochastic processes a different model that assumes simultaneous access of the virus to multiple target cells. In this scenario, if no cell is available to the virus at its location, it has a chance to interact with other cells, a process that can be promoted by mixing of the populations. This model can accurately fit the experimental data and suggests a new interpretation of mass action in virus dynamics models.IMPORTANCEUnderstanding the principles of virus growth through cell populations is of fundamental importance to virology. It helps us make informed decisions about intervention strategies aimed at preventing virus growth, such as drug treatment or vaccination approaches, e.g., in HIV infection, yet considerable uncertainty remains in this respect. An important variable in this context is the number of susceptible cells available for virus replication. How does the number of susceptible cells influence the growth potential of the virus? Besides the importance of such information for clinical responses, a thorough understanding of this is also important for the prediction of virus levels in patients and the estimation of crucial patient parameters through the use of mathematical models. This paper investigates the relationship between target cell availability and the virus growth potential with a combination of experimental and mathematical approaches and provides significant new insights.