bioRxivMicrobiology
Mathematical Modeling Identifies the Role of Adaptive Immunity as a Key Controller of Respiratory Syncytial Virus (RSV) Titer in Cotton Rats
D. Wethington, o. harder, K. Uppulury, W. Stewart, P. Chen, T. King, S. Reynolds, M. E. Peeples, S. Niewiesk, J. Das
Abstract
Respiratory syncytial virus (RSV) is a common virus that can have varying effects ranging from mild cold-like symptoms to mortality depending on the age and immune status of the individual. We combined mathematical modeling using ordinary differential equations (ODEs) with measurement of RSV infection kinetics in primary well differentiated human airway epithelial (HAE) cultures in vitro and in immunocompetent and immunosuppressed cotton rats to glean mechanistic details that underlie RSV infection kinetics in the lung. Quantitative analysis of viral titer kinetics in our mathematical model showed that the elimination of infected cells by the adaptive immune response generates unique RSV titer kinetic features including a faster time scale of viral titer clearance than viral production, and a monotonic decrease in the peak RSV titer with decreasing inoculum dose. Parameter estimation in the ODE model using a non-linear mixed effects approach revealed a very low rate (average single cell lifetime > 10 days) of cell lysis by RSV before the adaptive immune response is initiated. Our model predicted negligible changes in the RSV titer kinetics on earlier days (5 d.p.i) in silico. These predictions were in excellent agreement with the experimental results. Our combined approach quantified the importance of the adaptive immune response in suppressing RSV infection in cotton rats, which could be useful in testing RSV vaccine candidates.\n\nImportanceA major difficulty in developing vaccines against RSV infection is our rudimentary understanding of the mechanisms that underlie RSV infection. We addressed this challenge by developing a mechanistic computational model with predictive powers for describing RSV infection kinetics in cotton rats. The model was constructed synergistically with in vitro and in vivo measurements. The combined framework determined an important role for CD8+ T cells responses in reducing RSV titers in cotton rats. The framework can be used to design future experiments to elucidate mechanisms underlying RSV infection and test outcomes for potential vaccine candidates. In addition, estimation of the model parameters provides quantitative values for parameters of biological and clinical interest such as the replication rate of RSV, the death rate of infected cells, and the average number of new infections initiated by a single infected cell.
- organism: chicken / avian
- research focus: host-pathogen & immune response
- research focus: benchmarking
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Mathematical Modeling Identifies the Role of Adaptive Immunity as a Key Controller of Respiratory Syncytial Virus (RSV) Titer in Cotton Rats
Darren Wethington, Olivia Harder, … Jayajit Das·bioRxiv·Oct 24, 2018
- Inhibition of the TLR4 signalling pathway with TAK-242 reduces RSV infection and cytokine release in primary airway epithelial cells
L. Broadbent, G. C. Roberts, … the Breathing Together Consortium·bioRxiv·Nov 22, 2021
- Differential Antiviral Activities of RSV Inhibitors in Human Airway Epithelium
C. Mirabelli, M. Jaspers, … D. Jochmans·bioRxiv·Jan 19, 2018
- Antagonism between viral infection and innate immunity at the single-cell level
Frederic Grabowski, Marek Kochańczyk, … Tomasz Lipniacki·PLoS PathogensPeer-reviewed·Sep 5, 2023
- Depletion of TAX1BP1 amplifies innate immune responses during respiratory syncytial virus infection
D. Descamps, A. Peres de Oliveira, … M. Galloux·bioRxiv·Jun 3, 2021
- The specific features of the developing T cell compartment of the neonatal lung are a determinant of respiratory syncytial virus immunopathogenesis
T. Demoulins, M. Bruegger, … M. P. Alves·bioRxiv·Aug 14, 2020