Schälte, Y. | Search bioRxiv

bioRxiv2021

HCV spread kinetics reveal varying contributions of transmission modes to infection dynamics

Hepatitis C virus (HCV) is capable of spreading within a host by two different transmission modes: cell-free and cell-to-cell. Although viral dissemination and diffusion of viral particles facilitates the infection of distant cells, direct cell-to-cell transmission to uninfected neighboring cells is thought to shield the virus from immune recognition. However, the contribution of each of these transmission mechanisms to HCV spread is unknown. To dissect the contribution of these different transmission modes to HCV spread, we measured HCV lifecycle kinetics and used an in vitro spread assay to monitor HCV spread kinetics after low multiplicity of infection in the absence and presence of a neutralizing antibody that blocks cell-free spread. By analyzing these data with a spatially-explicit mathematical model that describes viral spread on a single-cell level, we quantified the contribution of cell-free and cell-to-cell spread to the overall infection dynamics and show that both transmission modes act synergistically to enhance the spread of infection. Thus, the simultaneous occurrence of both transmission modes likely represents an advantage for HCV that may contribute to the efficient establishment of chronic infection. Notably, the relative contribution of each viral transmission mode appeared to vary dependent on different experimental conditions and suggests that viral spread is optimized according to the environment. Together, our analyses provide insight into the transmission dynamics of HCV and reveal how different transmission modes impact each other. ImportanceHepatitis C Virus can spread within a host by diffusing viral particles or direct cell-to-cell transfer of viral material between infected and uninfected cells. To which extend these cell-free and cell-to-cell transmission modes contribute to HCV spread, establishment of chronicity and antiviral escape is still unknown. By combining in vitro experimental HCV spread data with a multi-scale mathematical model we have disentangled the contribution and interplay of cell-free and cell-to-cell transmission modes during HCV infection. Our analysis revealed synergistic effects between the two transmission modes, with the relative contribution of each transmission mode varying dependent on the experimental conditions. This highlights the adaptability of the virus and suggests that transmission modes might be optimized dependent on the environment, which could contribute to viral persistence.

microbiology↗

bioRxiv2020

Benchmarking of numerical integration methods for ODE models of biological systems

Ordinary differential equation (ODE) models are a key tool to understand complex mechanisms in systems biology. These models are studied using various approaches, including stability and bifurcation analysis, but most frequently by numerical simulations. The number of required simulations is often large, e.g., when unknown parameters need to be inferred. This renders efficient and reliable numerical integration methods essential. However, these methods depend on various hyperparameters, which strongly impact the ODE solution. Despite this, and although hundreds of published ODE models are freely available in public databases, a thorough study that quantifies the impact of hyperparameters on the ODE solver in terms of accuracy and computation time is still missing. In this manuscript, we investigate which choices of algorithms and hyperparameters are generally favorable when dealing with ODE models arising from biological processes. To ensure a representative evaluation, we considered 167 published models. Our study provides evidence that most ODEs in computational biology are stiff, and we give guidelines for the choice of algorithms and hyperparameters. We anticipate that our results will help researchers in systems biology to choose appropriate numerical methods when dealing with ODE models.

systems biology↗