Determining host metabolic limitations on viral replication via integrated modeling and experimental perturbation.
Determining host metabolic limitations on viral replication via integrated modeling and experimental perturbation.
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DOI：
10.1371/journal.pcbi.1002746
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发表时间：
2012
影响因子：
4.3
通讯作者：
Covert MW
中科院分区：
文献类型：
--
作者：
Birch EW;Ruggero NA;Covert MW
病毒复制依赖于宿主的代谢机制和前体来产生大量的后代-通常非常迅速。一个基本的例子是噬菌体T7感染大肠杆菌。由病毒复制施加的资源抽取代表了对宿主代谢途径的广泛且相互关联的网络的显著且复杂的扰动。为了更好地理解这个系统，我们整合了一组结构化的常微分方程量化T7复制和E。大肠杆菌通量平衡分析代谢模型。此外，我们在这里提出了一个集成的模拟算法，强制执行相互约束的模型在整个噬菌体复制的持续时间。该方法使得能够定量动态预测病毒体生产，仅给出宿主营养环境的规格，并且预测与多种环境中噬菌体复制的实验测量相比是有利的。我们的计算预测的详细程度，有利于探索的动态变化，在主机的代谢通量，导致病毒资源消耗，以及限制过程的分析，决定最大的病毒后代生产。例如，虽然通常认为病毒感染动力学主要受宿主中蛋白质合成机制的限制，但我们的研究结果表明，在许多情况下，代谢限制至少同样严格。总之，这些结果强调了在宿主代谢的背景下考虑病毒感染的重要性。病毒感染是一个严重的问题，已知的解决方案相对较少。病毒感染的复杂性很大程度上是由病毒占用宿主自身的资源造成的。病毒缺乏复制所需的机制和前体，因此可以被认为是宿主的代谢产物。我们的目标是通过计算工具和定量动态测量系统水平的理解宿主-病毒代谢相互作用。在这里，我们提出了T7噬菌体病毒复制和宿主E。大肠杆菌代谢，预测噬菌体生产的变化，在整个媒体条件下，并提供洞察T7复制的潜在限制因素。我们的实验测量支持的模型模拟，突出了宿主代谢在确定病毒感染的动力学中的作用。
Viral replication relies on host metabolic machinery and precursors to produce large numbers of progeny - often very rapidly. A fundamental example is the infection of Escherichia coli by bacteriophage T7. The resource draw imposed by viral replication represents a significant and complex perturbation to the extensive and interconnected network of host metabolic pathways. To better understand this system, we have integrated a set of structured ordinary differential equations quantifying T7 replication and an E. coli flux balance analysis metabolic model. Further, we present here an integrated simulation algorithm enforcing mutual constraint by the models across the entire duration of phage replication. This method enables quantitative dynamic prediction of virion production given only specification of host nutritional environment, and predictions compare favorably to experimental measurements of phage replication in multiple environments. The level of detail of our computational predictions facilitates exploration of the dynamic changes in host metabolic fluxes that result from viral resource consumption, as well as analysis of the limiting processes dictating maximum viral progeny production. For example, although it is commonly assumed that viral infection dynamics are predominantly limited by the amount of protein synthesis machinery in the host, our results suggest that in many cases metabolic limitation is at least as strict. Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism. Viral infection is a serious problem with relatively few known solutions. Much of the complexity of viral infection is contributed by the host's own resources that the virus commandeers. Viruses lack the machinery and precursors required to replicate, and thus may be considered metabolic products of their host. Our goal is a systems-level understanding of host-viral metabolic interaction via computational tools and quantitative dynamic measurements. Here we present an integrated model of T7 phage viral replication and host E. coli metabolism that predicts phage production changes across media conditions and provides insight into the underlying limiting factors in T7 replication. The model simulations, supported by our experimental measurements, highlight the role of host metabolism in determining the dynamics of viral infection.
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