Predicting the kinetic coordination of immune response dynamics in SARS-CoV-2 infection: implications for disease pathogenesis

A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter evaluation. The calibration of the mathematical model of SARS-CoV-2 infection is based on combining the parameter guesses from our earlier study of influenza A virus infection, some recent quantitative models of SARS-CoV-2 infection and clinical data-based parameter estimation of a subset of the model parameters. Hence, the calibrated mathematical model represents a theoretical exploration type of study, i.e., ‘in silico patient’ with mild-to-moderate severity phenotype, rather than a completely validated quantitative model of COVID-19 with respect to all its state-space variables. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the kinetics of immune responses with the clinical phenotypes of COVID-19. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to the pathogenesis of COVID-19, i.e., the sensitivity of the peak viral load to the parameters characterizing the antiviral specific response components, the kinetic coordination of the individual innate and adaptive immune responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e., the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds for variations of the innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination between them were identified.The reported study was funded by RFBR according to the research projects number 20-04-60157 and 20-01-00352. AM is also supported by the Spanish Ministry of Science and Innovation grant no. PID2019-106323RB-I00 AEI//10.13039/501100011033 and the Unidad de Excelencia María de Maeztu (AEI CEX2018-000792-M)

Additional file 5: Figure S3. of Characterization of secretomes provides evidence for adipose-derived mesenchymal stromal cells subtypes

ADSC response to hypoxia. A. – Representative Western blots showing the accumulation of HIF-1alpha after the incubation at 1 % O2 during 48 h. B. – Real time PCR analysis of VEGF mRNA in hypoxic and normoxic ADSCs (n = 20, * - p <0.05 vs. normoxia). (TIFF 100 kb

Additional file 2: Figure S1. of Characterization of secretomes provides evidence for adipose-derived mesenchymal stromal cells subtypes

Representative images of ADSCs undergoing adipogenic or osteogenic differentiation. A1-A7. – Cells incubated in adipogenesis inducing medium for 27 days. C1-C7. - Cells incubated in osteogenesis inducing medium for 21 day. A, B. – Cells stained with Oil-red O to detect lipid accumulations. C, D. - Cells stained with Alizarin red S to detect calcium accumulations. Nuclei were counterstained by hematoxilin. Scale = 100 μm. (TIFF 1643 kb