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. 2012 Sep 4:3:319.
doi: 10.3389/fmicb.2012.00319. eCollection 2012.

Identifying viral parameters from in vitro cell cultures

Shingo Iwami  1 , Kei Sato, Rob J De Boer, Kazuyuki Aihara, Tomoyuki Miura, Yoshio Koyanagi
Affiliations

Identifying viral parameters from in vitro cell cultures

Shingo Iwami et al. Front Microbiol. .

Abstract

Current in vitro cell culture studies of viral replication deliver detailed time courses of several virological variables, like the amount of virions and the number of target cells, measured over several days of the experiment. Each of these time points solely provides a snap-shot of the virus infection kinetics and is brought about by the complex interplay of target cell infection, and viral production and cell death. It remains a challenge to interpret these data quantitatively and to reveal the kinetics of these underlying processes to understand how the viral infection depends on these kinetic properties. In order to decompose the kinetics of virus infection, we introduce a method to "quantitatively" describe the virus infection in in vitro cell cultures, and discuss the potential of the mathematical based analyses for experimental virology.

Keywords: in vitro experiment; mathematical modeling; quantification; virus infection.

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Figures

Figure 1
Figure 1
A schematic representation of the mathematical model. The variables T and I are the number of target and infected cells, respectively, and V is the number of RNA copies of virus. The parameters δ, c, β and p represent the death rate of infected cells, the degradation rate of viral RNA, the rate constant for infection of target cells by virus, and the viral production rate of an infected cell, respectively.
Figure 2
Figure 2
The mathematical model describes the data well. HSC-F cells were inoculated with SHIV-KS661 24 h before t = 0 and each in vitro experimental quantity was measured daily from t = 0 d to 9 d. The curves depict the best fit of the model (Equation 1), to the experimental data of SHIV-KS661 infection in vitro (symbols) for the target cells, infected cells, and the viral load for the two different experiments conducted at different MOIs. All data were fitted simultaneously as described in “Materials and Methods.”
Figure 3
Figure 3
The burst size and the basic reproductive number of a virus. The burst size is defined as the expected number of virions produced by one infected cell over its life-time (e.g., p/δ = 9 in the figure). The basic reproductive number, R0, is defined as the expected number of newly infected cells resulting from one infected cell during its life-time (e.g., R0 = 6 in the figure).
Figure 4
Figure 4
Predicted virus infection kinetics with different parameters. The solid curves show the predicted kinetics of target cells (left), infected cells (middle) and virus load (right) following infection with SHIV-KS661 at an MOI 2 × 10−4 using the parameters in Tables 2 and 3. The time t = 0 corresponds to 24 h after inoculation of SHIV-KS661 to HSC-F. In the text we call this virus-A. The dashed and dotted curves show those of the variants virus-B and virus-A*, respectively. Virus-B is less cytopathic and has a 1.5-fold decreased death rate of infected cells (δ = 1.16). Cells infected with the more virulent “mutant” virus-A* die 3-fold faster than those infected with the wild-type A (i.e., δ = 5.25 vs. δ = 1.75, respectively), but produce 2-fold more virus (p = 6.72 × 104) per day than those infected with “wild-type” virus-A.
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