Stochastic vs. deterministic modeling of intracellular viral kinetics
Stochastic vs. deterministic modeling of intracellular viral kinetics
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DOI：
10.1006/jtbi.2002.3078
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发表时间：
2002-10-07
影响因子：
2
通讯作者：
Yin, J
中科院分区：
文献类型：
--
作者：
Srivastava, R;You, L;Yin, J
在其宿主细胞内，转录、翻译、基因组复制、组装和病毒释放过程的复杂耦合决定了病毒的生长速率。解释这些过程的数学模型可以帮助我们理解整个生长周期如何取决于其组成反应。基于常微分方程的确定性模型可以捕捉病毒组分之间的本质关系。然而，感染可以由单个病毒颗粒启动，该病毒颗粒将其基因组，单个DNA或RNA分子递送到其宿主细胞。在这种情况下，一个随机模型，允许固有的波动水平的病毒成分可能会产生定性不同的行为。为了比较建模方法，我们开发了一个通用病毒的细胞内动力学的简单模型，该模型可以确定性地或随机地实施。该模型解释了合成和消耗病毒核酸和结构蛋白的反应。线性稳定性分析的确定性模型表明存在两个节点，一个稳定和一个不稳定。单个随机模拟运行可以访问并保持在不稳定节点。此外，确定性和平均随机模拟产生了不同的瞬态动力学和不同的稳态水平的病毒成分，特别是对于低感染复数（MOI），其中很少有病毒颗粒启动感染。此外，双峰人口分布的病毒成分观察到低MOI随机模拟。低水平感染的细胞亚群的存在，可以作为一个病毒库，提出了一个潜在的病毒持久性机制。(C)2002爱思唯尔科技有限公司。保留所有权利。
Within its host cell, a complex coupling of transcription, translation, genome replication, assembly, and virus release processes determines the growth rate of a virus. Mathematical models that account for these processes can provide insights into the understanding as to how the overall growth cycle depends on its constituent reactions. Deterministic models based on ordinary differential equations can capture essential relationships among virus constituents. However, an infection may be initiated by a single virus particle that delivers its genome, a single molecule of DNA or RNA, to its host cell. Under such conditions, a stochastic model that allows for inherent fluctuations in the levels of viral constituents may yield qualitatively different behavior. To compare modeling approaches, we developed a simple model of the intracellular kinetics of a generic virus, which could be implemented deterministically or stochastically. The model accounted for reactions that synthesized and depleted viral nucleic acids and structural proteins. Linear stability analysis of the deterministic model showed the existence of two nodes, one stable and one unstable. Individual stochastic simulation runs could access and remain at the unstable node. In addition, deterministic and averaged stochastic simulations yielded different transient kinetics and different steady-state levels of viral components, particularly for low multiplicities of infection (MOI), where few virus particles initiate the infection. Furthermore, a bimodal population distribution of viral components was observed for low MOI stochastic simulations. The existence of a low-level infected subpopulation of cells, which could act as a viral reservoir, suggested a potential mechanism of viral persistence. (C) 2002 Elsevier Science Ltd. All rights reserved.