Mathematical modelling of SARS-CoV-2 infection of human and animal host cells reveals differences in the infection rates and delays in viral particle production by infected cells. (21st December 2021)

• Record Type: Journal Article
• Authors: Bernhauerová, Veronika; Lisowski, Bartek; Rezelj, Veronica V.; Vignuzzi, Marco
• Is Part Of: Journal of theoretical biology. Volume 531(2021)
• Publication Date: 2021-12-21
• Subjects: COVID-19 -- Viral dynamics -- Parameter estimation -- In vitro infection; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2021.110895
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: We measure infection of human (A549-ACE2) and animal (Vero-E6) cells by SARS-CoV-2. We use mathematical modelling to estimate SARS-CoV-2 infection parameters. SARS-CoV-2 infection rate of A549-ACE2 cells is lower than that of Vero E6 cells. Latent phase of infected A549-ACE2 cells is longer than that of Vero E6 cells. We conclude that Vero-E6 cells are not suitable for long-term drug screening assays. Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV -2), a causative agent of COVID-19 disease, poses a significant threat to public health. Since its outbreak in December 2019, Wuhan, China, extensive collection of diverse data from cell culture and animal infections as well as population level data from an ongoing pandemic, has been vital in assessing strategies to battle its spread. Mathematical modelling plays a key role in quantifying determinants that drive virus infection dynamics, especially those relevant for epidemiological investigations and predictions as well as for proposing efficient mitigation strategies. We utilized a simple mathematical model to describe and explain experimental results on viral replication cycle kinetics during SARS-CoV-2 infection of animal and human derived cell lines, green monkey kidney cells, Vero-E6, and human lung epithelium cells, A549-ACE2, respectively. We conducted cell infections using two distinct initial viral concentrations and quantified viral loads over time. We then fitted the model to our experimental data and quantified the viral parameters. We showed that such cellular tropism generates significant differences in the infection rates and incubation times of SARS-CoV-2, that is, the times to the first release of newly synthesised viral progeny by SARS-CoV-2-infected cells. Specifically, the rate at which A549-ACE2 cells were infected by SARS-CoV-2 was 15 times lower than that in the case of Vero-E6 cell infection and the duration of latent phase of A549-ACE2 cells was 1.6 times longer than that of Vero-E6 cells. On the other hand, we found no statistically significant differences in other viral parameters, such as viral production rate or infected cell death rate. Since in vitro infection assays represent the first stage in the development of antiviral treatments against SARS-CoV-2, discrepancies in the viral parameter values across different cell hosts have to be identified and quantified to better target vaccine and antiviral research.