Influenza virus infection model with density dependence supports biphasic viral decay

Amanda P. Smith, David J. Moquin, Veronika Bernhauerova, Amber Smith

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Mathematical models that describe infection kinetics help elucidate the time scales, effectiveness, and mechanisms underlying viral growth and infection resolution. For influenza A virus (IAV) infections, the standard viral kinetic model has been used to investigate the effect of different IAV proteins, immune mechanisms, antiviral actions, and bacterial coinfection, among others. We sought to further define the kinetics of IAV infections by infecting mice with influenza A/PR8 and measuring viral loads with high frequency and precision over the course of infection. The data highlighted dynamics that were not previously noted, including viral titers that remain elevated for several days during mid-infection and a sharp 4-5 log10 decline in virus within 1 day as the infection resolves. The standard viral kinetic model, which has been widely used within the field, could not capture these dynamics. Thus, we developed a new model that could simultaneously quantify the different phases of viral growth and decay with high accuracy. The model suggests that the slow and fast phases of virus decay are due to the infected cell clearance rate changing as the density of infected cells changes. To characterize this model, we fit the model to the viral load data, examined the parameter behavior, and connected the results and parameters to linear regression estimates. The resulting parameters and model dynamics revealed that the rate of viral clearance during resolution occurs 25 times faster than the clearance during mid-infection and that small decreases to this rate can significantly prolong the infection. This likely reflects the high efficiency of the adaptive immune response. The new model provides a well-characterized representation of IAV infection dynamics, is useful for analyzing and interpreting viral load dynamics in the absence of immunological data, and gives further insight into the regulation of viral control.

Original languageEnglish (US)
Article number1554
JournalFrontiers in Microbiology
Volume9
Issue numberJUL
DOIs
StatePublished - Jul 10 2018

Fingerprint

Virus Diseases
Orthomyxoviridae
Influenza A virus
Infection
Viral Load
Viruses
Adaptive Immunity
Growth
Coinfection
Human Influenza
Antiviral Agents
Linear Models
Theoretical Models
Cell Count
Proteins

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Microbiology (medical)

Cite this

Influenza virus infection model with density dependence supports biphasic viral decay. / Smith, Amanda P.; Moquin, David J.; Bernhauerova, Veronika; Smith, Amber.

In: Frontiers in Microbiology, Vol. 9, No. JUL, 1554, 10.07.2018.

Research output: Contribution to journalArticle

Smith, Amanda P. ; Moquin, David J. ; Bernhauerova, Veronika ; Smith, Amber. / Influenza virus infection model with density dependence supports biphasic viral decay. In: Frontiers in Microbiology. 2018 ; Vol. 9, No. JUL.
@article{918181a655f34c86b89242181abb832f,
title = "Influenza virus infection model with density dependence supports biphasic viral decay",
abstract = "Mathematical models that describe infection kinetics help elucidate the time scales, effectiveness, and mechanisms underlying viral growth and infection resolution. For influenza A virus (IAV) infections, the standard viral kinetic model has been used to investigate the effect of different IAV proteins, immune mechanisms, antiviral actions, and bacterial coinfection, among others. We sought to further define the kinetics of IAV infections by infecting mice with influenza A/PR8 and measuring viral loads with high frequency and precision over the course of infection. The data highlighted dynamics that were not previously noted, including viral titers that remain elevated for several days during mid-infection and a sharp 4-5 log10 decline in virus within 1 day as the infection resolves. The standard viral kinetic model, which has been widely used within the field, could not capture these dynamics. Thus, we developed a new model that could simultaneously quantify the different phases of viral growth and decay with high accuracy. The model suggests that the slow and fast phases of virus decay are due to the infected cell clearance rate changing as the density of infected cells changes. To characterize this model, we fit the model to the viral load data, examined the parameter behavior, and connected the results and parameters to linear regression estimates. The resulting parameters and model dynamics revealed that the rate of viral clearance during resolution occurs 25 times faster than the clearance during mid-infection and that small decreases to this rate can significantly prolong the infection. This likely reflects the high efficiency of the adaptive immune response. The new model provides a well-characterized representation of IAV infection dynamics, is useful for analyzing and interpreting viral load dynamics in the absence of immunological data, and gives further insight into the regulation of viral control.",
author = "Smith, {Amanda P.} and Moquin, {David J.} and Veronika Bernhauerova and Amber Smith",
year = "2018",
month = "7",
day = "10",
doi = "10.3389/fmicb.2018.01554",
language = "English (US)",
volume = "9",
journal = "Frontiers in Microbiology",
issn = "1664-302X",
publisher = "Frontiers Media S. A.",
number = "JUL",

}

TY - JOUR

T1 - Influenza virus infection model with density dependence supports biphasic viral decay

AU - Smith, Amanda P.

AU - Moquin, David J.

AU - Bernhauerova, Veronika

AU - Smith, Amber

PY - 2018/7/10

Y1 - 2018/7/10

N2 - Mathematical models that describe infection kinetics help elucidate the time scales, effectiveness, and mechanisms underlying viral growth and infection resolution. For influenza A virus (IAV) infections, the standard viral kinetic model has been used to investigate the effect of different IAV proteins, immune mechanisms, antiviral actions, and bacterial coinfection, among others. We sought to further define the kinetics of IAV infections by infecting mice with influenza A/PR8 and measuring viral loads with high frequency and precision over the course of infection. The data highlighted dynamics that were not previously noted, including viral titers that remain elevated for several days during mid-infection and a sharp 4-5 log10 decline in virus within 1 day as the infection resolves. The standard viral kinetic model, which has been widely used within the field, could not capture these dynamics. Thus, we developed a new model that could simultaneously quantify the different phases of viral growth and decay with high accuracy. The model suggests that the slow and fast phases of virus decay are due to the infected cell clearance rate changing as the density of infected cells changes. To characterize this model, we fit the model to the viral load data, examined the parameter behavior, and connected the results and parameters to linear regression estimates. The resulting parameters and model dynamics revealed that the rate of viral clearance during resolution occurs 25 times faster than the clearance during mid-infection and that small decreases to this rate can significantly prolong the infection. This likely reflects the high efficiency of the adaptive immune response. The new model provides a well-characterized representation of IAV infection dynamics, is useful for analyzing and interpreting viral load dynamics in the absence of immunological data, and gives further insight into the regulation of viral control.

AB - Mathematical models that describe infection kinetics help elucidate the time scales, effectiveness, and mechanisms underlying viral growth and infection resolution. For influenza A virus (IAV) infections, the standard viral kinetic model has been used to investigate the effect of different IAV proteins, immune mechanisms, antiviral actions, and bacterial coinfection, among others. We sought to further define the kinetics of IAV infections by infecting mice with influenza A/PR8 and measuring viral loads with high frequency and precision over the course of infection. The data highlighted dynamics that were not previously noted, including viral titers that remain elevated for several days during mid-infection and a sharp 4-5 log10 decline in virus within 1 day as the infection resolves. The standard viral kinetic model, which has been widely used within the field, could not capture these dynamics. Thus, we developed a new model that could simultaneously quantify the different phases of viral growth and decay with high accuracy. The model suggests that the slow and fast phases of virus decay are due to the infected cell clearance rate changing as the density of infected cells changes. To characterize this model, we fit the model to the viral load data, examined the parameter behavior, and connected the results and parameters to linear regression estimates. The resulting parameters and model dynamics revealed that the rate of viral clearance during resolution occurs 25 times faster than the clearance during mid-infection and that small decreases to this rate can significantly prolong the infection. This likely reflects the high efficiency of the adaptive immune response. The new model provides a well-characterized representation of IAV infection dynamics, is useful for analyzing and interpreting viral load dynamics in the absence of immunological data, and gives further insight into the regulation of viral control.

UR - http://www.scopus.com/inward/record.url?scp=85049857641&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049857641&partnerID=8YFLogxK

U2 - 10.3389/fmicb.2018.01554

DO - 10.3389/fmicb.2018.01554

M3 - Article

VL - 9

JO - Frontiers in Microbiology

JF - Frontiers in Microbiology

SN - 1664-302X

IS - JUL

M1 - 1554

ER -