Modeling cell infection via virus-producing cells rather than free infectious virus significantly improves fits of an in vitro viral kinetic data

Abstract

Chikungunya and Zika viruses are arthropod-borne viruses that pose significant threat to public health. Experimental data show that during in vitro infection both viruses exhibit qualitatively distinct replication cycle kinetics. Chikungunya viral load rapidly accumulates within the first several hours post infection whereas Zika virus begins to increase at much later times. We sought to characterize these qualitatively distinct in vitro kinetics of chikungunya and Zika viruses by fitting a family of mathematical models to time course viral load datasets. We demonstrate that the standard viral kinetic model, which considers that new infections result only from free virus penetrating susceptible cells, does not fit experimental data as well as a model in which the number of virus-infected cells is the primary determinant of infection rate. We provide biologically meaningful quantifications of the main viral kinetic parameters and show that our results support cell-to-cell or localized transmission as a significant contributor to viral infection with chikungunya and Zika viruses.\n\nImportanceMathematical modeling has become a useful tool to tease out information about virus-host interactions and thus complements experimental work in characterizing and quantifying processes within viral replication cycle. Importantly, mathematical models can fill in incomplete data sets and identify key parameters of infection, provided the appropriate model is used. The in vitro time course dynamics of mosquito transmitted viruses, such as chikungunya and Zika, have not been studied by mathematical modeling and thus limits our knowledge about quantitative description of the individual determinants of viral replication cycle. This study employs dynamical modeling framework to show that the rate at which cells become virus-infected is proportional to the number or virus-infected cells rather than free extracellular virus in the milieu, a widely accepted assumption in models of viral infections. Using the refined mathematical model in combination with viral load data, we provide quantification of the main drivers of chikungunya and Zika in vitro kinetics. Together, our results bring quantitative understanding of the basic components of chikungunya and Zika virus dynamics.