Quantification of the Dynamics of Enterovirus 71 Infection by Experimental-Mathematical Investigation

Abstract

Enterovirus 71 (EV71) is the causative agent of hand-foot-and-mouth disease and can trigger neurological disorders. EV71 outbreaks are a major public health concern in Asia-Pacific countries. By performing experimental-mathematical investigation, we demonstrate here that viral productivity and transmissibility but not viral cytotoxicity are drastically different among EV71 strains and can be associated with their epidemiological backgrounds. This is the first report demonstrating the dynamics of nonenveloped virus replication in cell culture using mathematical modeling. Human enteroviruses are nonenveloped viruses with a singlestranded positive-sense RNA genome that belong to the family Picornaviridae (1, 2). Enterovirus 71 (EV71) is one of the human enteroviruses and was first described in 1974 (3). It is well known that EV71 is the major causative agent of hand-foot-andmouth disease (HFMD), a common febrile disease occurring mainly in infants and young children (1, 4). Although HFMD is usually self-limiting, EV71 infection can result in neurological disorders such as aseptic meningitis, flaccid paralysis, and fatal encephalitis (1, 4). However, there are no specific therapies for severe EV71 infections.EV71 can be transmitted through the fecal-oral and respiratory routes (1). Since the 1970s, EV71 outbreaks have been periodically reported throughout the world (4, 5). In particular, since the late 1990s, severe EV71 outbreaks have occurred frequently in several countries in the Asia-Pacific region, including Taiwan, mainland China, Malaysia, and Vietnam, and are among the major concerns in the fields of epidemiology and public health in these countries (4, 5).The dynamics of virus replication is complex because this event is composed of the all-at-once creation and destruction of infected cells along with virus propagation. Mathematical analysis is one of the most powerful approaches used to reveal the complicated events in the viral life cycle. By applying mathematical analysis to experimental data, we are able to quantitatively understand the dynamics of virus replication as estimated numerical parameters such as the half-life of infected cells (log2/␦), the burst size of infectious viruses (p/␦; the net amount of virions produced by a cell during its lifetime), and the basic reproductive number (R 0 ϭ p␤T max /␦c; the number of cells newly infected by an infected cell). These parameters may provide novel insights into the dynamics of virus replication that cannot be addressed by conventional experimental techniques. So far, mathematical models have been used to study the replication dynamics of enveloped viruses such as human immunodeficiency virus type 1 (HIV-1) (6-8) and influenza virus (9-12) in in vitro cell culture. In order to obtain robust and reliable results by mathematical analysis, high-quality time course data are needed. Although some mathematical models of nonenveloped viruses focusing on viral replication kinetics in an infected cell have been reported (13-15), there is no report of the use of...

Zika viral dynamics and shedding in rhesus and cynomolgus macaques

“…To understand the dynamics of viral infection as reflected in the blood plasma VL, we used a standard acute viral infection model that includes an eclipse phase after viral infection of a cell, during which time the infected cell does not produce virus 51–53 . After the eclipse phase, infected cells produces new virus.…”

Quantification of Deaminase Activity-Dependent and -Independent Restriction of HIV-1 Replication Mediated by APOBEC3F and APOBEC3G through Experimental-Mathematical Investigation

“…So far, our experimental and mathematical approach has quantitatively revealed the replication dynamics of retroviruses (50,51) and enteroviruses (52). To the best of our knowledge, here we quantitatively determined the antiviral effect of cellular proteins, human APOBEC3, using the experimental data for the first time.…”

Decision letter: Cell-to-cell infection by HIV contributes over half of virus infection

“…Note that c, g, and δ include the removal of virus, and of the uninfected and infected cells, due to the experimental samplings. In our earlier works (Iwami et al, 2012a(Iwami et al, , 2012bFukuhara et al, 2013;Kakizoe et al, 2015), we have shown that the approximating punctual removal as a continuous exponential decay has minimal impact on the model parameters and provides an appropriate fit to the experimental data. In addition, we introduce the parameter ω, describing the infection rate via cell-to-cell contacts (Sourisseau et al, 2007;Sattentau, 2008;Sigal et al, 2011).…”