Faculty of Biology and Biotechnology, HSE University, Moscow, Russia.
Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia.
PeerJ. 2023 Feb 1;11:e14828. doi: 10.7717/peerj.14828. eCollection 2023.
Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for data, which are less noisy and more reproducible. In this work we collected multiple data types for SARS-CoV-2-infected Caco-2 cell lines, including infectious virus titers, measurements of intracellular viral RNA, cell viability data and percentage of infected cells for the WT and Delta variants. We showed that standard models cannot explain some key observations given the absence of cytopathic effect in human cell lines. We propose a novel mathematical model for SARS-CoV-2 dynamics, which included explicit modeling of intracellular events such as exhaustion of cellular resources required for virus production. The model also explicitly considers innate immune response. The proposed model accurately explained experimental data. Attenuated replication of the Delta variant in Caco-2 cells could be explained by our model on the basis of just two parameters: decreased cell entry rate and increased cytokine production rate.
数学建模被广泛用于研究宿主内病毒动力学。然而，据我们所知，对于 SARS-CoV-2 这种情况，这种分析主要是使用病毒载量数据和病毒的野生型（WT）变体进行的。此外，只有少数研究分析了数据模型，这些模型噪声更小，重现性更好。在这项工作中，我们收集了 SARS-CoV-2 感染的 Caco-2 细胞系的多种数据类型，包括感染性病毒滴度、细胞内病毒 RNA 的测量、细胞活力数据和 WT 和 Delta 变体的感染细胞百分比。我们表明，由于人细胞系中没有细胞病变效应，标准模型无法解释一些关键观察结果。我们提出了一种新的 SARS-CoV-2 动力学数学模型，该模型包括对细胞内事件的明确建模，例如生产病毒所需的细胞资源的耗尽。该模型还明确考虑了先天免疫反应。所提出的模型准确地解释了实验数据。我们的模型可以基于两个参数解释 Delta 变体在 Caco-2 细胞中的复制减弱：细胞进入率降低和细胞因子产生率增加。
