Development of a novel mathematical model that explains SARS-CoV-2 infection dynamics in Caco-2 cells

Abstract

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 in vitro 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 in vitro 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.

Keywords: COVID-19; Caco-2; Mathematical model; SARS-CoV-2.

Figure 1. Experimental data for SARS-CoV-2-infected Caco-2 cells.

TCID₅₀ assay and RT-qPCR data are shown for the WT (A) and the Delta (B) variants. Cell viability data is shown for the WT virus (C).

Figure 2. A schematic illustration of the proposed model for SARS-CoV-2 infection dynamics in Caco-2 cells.

Figure 3. Solutions of the discrete model accurately explain experimental data for the WT (A) and Delta (B) variants.

TCID₅₀ assay and RT-qPCR data are shown for the WT (A) and the Delta (B) variants. Cell viability data is shown for the WT virus.