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Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

机译:简单的数学模型无法准确预测早期的SIV动态

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摘要

Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available.
机译:感染新宿主后,人类免疫缺陷病毒(HIV)在粘膜组织中复制,通常在感染后的1-2周内无法在循环中检测到。在感染的这一最早阶段,针对艾滋病毒的几种干预措施包括疫苗和抗逆转录病毒预防,以病毒复制为目标。已经使用数学模型来了解艾滋病毒如何从粘膜组织系统扩散,以及疫苗接种和/或抗逆转录病毒预防对根除病毒有何影响。由于很少将此类模型的预测与实验数据进行比较,因此尚不清楚这些模型中包含的哪些过程对于预测早期HIV动态至关重要。在这里,我们修改了“ HIV”感染的“标准”数学模型,以包括两个受感染细胞群体:正在积极产生病毒的细胞和正在转变为病毒生产模式的细胞。我们评估了该模型中几种未知参数对感染结果的影响,并将模型预测与非人灵长类动物可变剂量猿猴免疫缺陷病毒(SIV)感染的实验数据进行了比较。首先,我们发现被感染细胞产生病毒的方式(萌芽与爆发)对于各种模型参数都对早期病毒动力学影响最小,只要这些参数受约束才能提供观察到的SIV速率感染动物血液的负荷增加。有趣的是,与先前的结果相反,我们发现病毒生产的爆发模式通常比病毒生产的萌芽模式导致更高的病毒灭绝概率。第二,该数学模型无法准确描述实验确定的宿主感染机率随病毒剂量增加的变化。第三,也是最后,该模型也无法准确解释随着病毒剂量增加病毒检测时间的减少。这些结果表明,为了适当地模拟早期HIV / SIV动态,在模型开发中必须考虑其他因素。这些可能包括猴子对感染的易感性变化,粘膜中病毒复制起始位点上不同病毒对靶细胞的宿主内部竞争,先天免疫应答,可能还包括几个不同的组织区室。令人震惊的消息是,尽管需要增加模型复杂度来解释可用的实验数据,但测试和拒绝更复杂的模型可能需要比当前可用的更多定量数据。

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