Quantifying the relative contribution of free virus and cell-to-cell transmission routes to the propagation of hepatitis C virus infections in vitro using an agent-based model

Abstract

Experiments have shown that hepatitis C virus (HCV) infections in vitro disseminate both distally via the release and diffusion of cell-free virus through the medium, and locally via direct, cell-to-cell transmission. To determine the relative contribution of each mode of infection to HCV dissemination, we developed an agent-based model (ABM) that explicitly incorporates both distal and local modes of infection. The ABM tracks the concentration of extracellular infectious virus in the supernatant and the number of intracellular HCV RNA segments within each infected cell over the course of simulated in vitro HCV infections. Experimental data for in vitro HCV infections conducted in the presence and absence of free-virus neutralizing antibodies was used to validate the ABM and constrain the value of its parameters. We found that direct, cell-to-cell infection accounts for 99% (84%-100%, 95% credible interval) of infection events, making it the dominant mode of HCV dissemination in vitro. Yet, when infection via the free-virus route is blocked, a 57% reduction in the number of infection events at 72 hpi is observed experimentally; a result consistent with that found by our ABM. Taken together, these findings suggest that while HCV spread via cell-free virus contributes little to the total number of infection events in vitro, it plays a critical role in enhancing cell-to-cell HCV dissemination by providing access to distant, uninfected areas, away from the already established large infection foci.

Spatial information allows inference of the prevalence of direct cell–to–cell viral infection

“…Our work is not the first in the literature to attempt to quantify the relative roles of cell–free and cell–to–cell infection routes. A number of mathematical modelling publications [ 7 , 11 , 12 , 14 , 15 , 17 , 18 ], along with experimental works [ 6 , 10 ] have applied varying models and methods to determine the prevalence of cell–to–cell infection. A common theme among the majority of these works is the use of data collected from infections where one mode of infection is inhibited: either the cell–to–cell mechanism [ 11 – 13 ], or the cell–free mechanism [ 6 , 10 , 15 ].…”

“…The extended model is used only in specified instances for the generation of observational data. For the basic spatial model, following other authors [ 15 , 17 , 18 , 34 ], we make the simplifying assumption that the dispersal of free virions over the computational domain is fast, and that the extracellular viral distribution can therefore be considered approximately uniform. As such, the equation for V in our spatial model changes only in notation from Eq (5) : …”

“…In Fig 3A we show a schematic of the model as well as the layout of the cell grid. This is not a novel model: this model structure, or slight variations thereof, has been used in a number of recent publications describing infection dynamics with two modes of viral spread and has become somewhat of a standard approach in the field in recent years [ 7 , 14 , 15 , 20 ].…”

“…In hepatitis C, modelling efforts led by Graw and Durso–Cain suggested that cell–free infection events were rare, yet worked synergistically with the cell–to–cell infection strategy to rapidly accelerate the overall rate of infection spread [ 7 , 14 ]. Blahut and coworkers used modelling to quantify the proportion of the two modes of spread using in vitro experimental data, and claimed that as little as 1% of the infection events observed were due to to–cell infection [ 15 ]. Experimental work by Kongsomros and colleagues suggested that the proportion of cell–to–cell infections in influenza was low, but elevated in more pathogenic strains of the virus [ 6 ].…”

“…These estimates in the literature for the relative contribution of cell–to–cell spread in infection are subject to substantial uncertainty, and share the common limitation that they rely on experiments which block one of the modes of viral spread, compared to a control case where both routes of infection are active [ 6 , 10 – 13 , 15 ]. This inhibition can be implemented in a number of ways, such as by conducting infection assays in the presence of an antiviral agent or a physical barrier to viral diffusion like methylcellulose to block cell–free infection [ 6 , 10 ], or by constantly shaking the cell culture to prevent the formation of virological synapses which enable cell–to–cell infection, in the case of HIV [ 11 – 13 ].…”