A multiscale model suggests that a moderately weak inhibition of SARS-CoV-2 replication by type I IFN could accelerate the clearance of the virus

Bouchnita, Anass; Tokarev, Alexey; Volpert,

doi:10.1101/2021.01.25.427896

Cited by 4 publications

(4 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Individual based models allow a more detailed description of intracellular regulation of virus replication and interferon production. It is also possible to consider more complete continuous models and hybrid discretecontinuous models [5]. There is an increasing interest for all these modelling approaches in relation with the new coronavirus disease.…”

Section: Discussionmentioning

confidence: 99%

Infection spreading in cell culture as a reaction-diffusion wave

et al. 2022

Self Cite

View full text Add to dashboard Cite

Infection spreading in cell culture occurs due to virus replication in infected cells and its random motion in the extracellular space. Multiplicity of infection experiments in cell cultures are conventionally used for the characterization of viral infection by the number of viral plaques and the rate of their growth. We describe this process with a delay reaction-diffusion system of equations for the concentrations of uninfected cells, infected cells, virus, and interferon. Time delay corresponds to the duration of viral replication inside infected cells. We show that infection propagates in cell culture as a reaction-diffusion wave, we determine the wave speed and prove its existence. Next, we carry out numerical simulations and identify three stages of infection progression: infection decay during time delay due to virus replication, explosive growth of viral load when infected cells begin to reproduce it, and finally, wave-like infection progression in cell culture characterized by a constant or slowly growing total viral load. The modelling results are in agreement with the experimental data for the coronavirus infection in a culture of epithelial cells and for some other experiments. The presence of interferon produced by infected cells decreases the viral load but does not change the speed of infection progression in cell culture. In the 2D modelling, the total viral load grows faster than in the 1D case due to the increase of plaque perimeter.

show abstract

Section: Discussionmentioning

confidence: 99%

Infection spreading in cell culture as a reaction-diffusion wave

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…For instance, they have helped estimate the withinhost basic reproductive ratio [60,74,75] and assess the effects of drugs and vaccines [26,43,[76][77][78][79][80]. Attempts have been made to capture the role of the immune system in disease progression and outcome [43,77,79,[81][82][83][84][85][86][87][88]. Some models have also analysed the same datasets that we have used here [38,43,60,75,77].…”

Section: Discussionmentioning

confidence: 99%

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

2022

View full text Add to dashboard Cite

SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. Empirical evidence points to the prominent roles of innate immune and CD8 T-cell responses in determining the outcomes. However, how these immune arms act in concert to elicit the outcomes remains unclear. Here, we developed a mathematical model of within-host SARS-CoV-2 infection that incorporates the essential features of the innate immune and CD8 T-cell responses. Remarkably, by varying the strengths and timings of the two immune arms, the model recapitulated the entire spectrum of outcomes realized. Furthermore, model predictions offered plausible explanations of several confounding clinical observations, including the occurrence of multiple peaks in viral load, viral recrudescence after symptom loss, and prolonged viral positivity. We applied the model to analyze published datasets of longitudinal viral load measurements from patients exhibiting diverse outcomes. The model provided excellent fits to the data. The best-fit parameter estimates indicated a nearly 80-fold stronger innate immune response and an over 200-fold more sensitive CD8 T-cell response in patients with mild compared to severe infection. These estimates provide quantitative insights into the likely origins of the dramatic inter-patient variability in the outcomes of SARS-CoV-2 infection. The insights have implications for interventions aimed at preventing severe disease and for understanding the differences between viral variants.

show abstract

“…For instance, they have helped estimate the within-host basic reproductive ratio (33,34,52) and assess the effects of drugs and vaccines (26,27,44,(54)(55)(56)(57). Attempts have also been made to capture the role of the immune system in disease progression and outcome (44,55,(57)(58)(59)(60)(61). Available models, however, have either not been shown to fit longitudinal patient data or have failed to describe the entire range of outcomes realized.…”

Section: Discussionmentioning

confidence: 99%

The relative strength and timing of innate immune and CD8 T-cell responses underlie the heterogeneous outcomes of SARS-CoV-2 infection

Chatterjee

Sandhu

Dixit

2021

Preprint

View full text Add to dashboard Cite

SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. While immunological correlates of disease severity have been identified, how they act together to determine the outcomes is unknown. Here, using a new mathematical model of within-host SARS-CoV-2 infection, we analyze diverse clinical datasets and predict that a subtle interplay between innate and CD8 T-cell responses underlies disease heterogeneity. Our model considers essential features of these immune arms and immunopathology from cytokines and effector cells. Model predictions provided excellent fits to patient data and, by varying the strength and timing of the immune arms, quantitatively recapitulated viral load changes in mild, moderate, and severe disease, and death. Additionally, they explained several confounding observations, including viral recrudescence after symptom loss, prolonged viral positivity before cure, and mortality despite declining viral loads. Together, a robust conceptual understanding of COVID-19 outcomes emerges, bearing implications for interventions.

show abstract

A multiscale model suggests that a moderately weak inhibition of SARS-CoV-2 replication by type I IFN could accelerate the clearance of the virus

Cited by 4 publications

References 39 publications

Infection spreading in cell culture as a reaction-diffusion wave

Infection spreading in cell culture as a reaction-diffusion wave

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

The relative strength and timing of innate immune and CD8 T-cell responses underlie the heterogeneous outcomes of SARS-CoV-2 infection

Contact Info

Product

Resources

About