Multi-Scale Modeling of HIV Infection in vitro and APOBEC3G-Based Anti-Retroviral Therapy
Figure 6
HIV growth curves for WT and ΔVif viruses.
(A) Inoculation of cultures of 500,000 cells with WT HIV. Blue and red squares represent 1 and 10 ng p24 HIV input, respectively. For a given tv,1/2, values of burst size and virus infectivity rate were estimated such that the resulting simulated HIV growth curve fitted the blue data point with the minimum fitness error (shown as blue lines for tv,1/2 = 4, 8, 16, 24, 26, Inf hours). Then, the estimated numbers were used to predict experimental data points corresponding to 1 ng p24 (shown as red lines). (B) Inoculation by 10 ng p24 ΔVif HIV. For each triplet of (tv,1/2, B, kinf) from (A), the values of p and c between 0 and 1 were chosen such that the generated curve provided the smallest error. None of the values of tv,1/2 produced good fits to the blue circles except tv,1/2 = 24 hours where p and c were estimated to be 0.008 and 0.008, respectively. (C) The estimated parameters for tv,1/2 = 24 hours from (A) and (B) were used to examine how well they could generate a curve to fit experimental data points corresponding to 1 ng p24 ΔVif input (red circles). The red dashed line provided an acceptable fit to the data points except for the last circle where the line diverged. (D) All the experimental data points as well as their HIV growth curves are shown in red and blue colors corresponding to 1 and 10 ng p24 HIV input. Also, we included crowding effects in our simulation by using a logistic function. The two new curves drawn in light red (1 ng p24 ΔVif) and light blue (10 ng p24 ΔVif) show the HIV growth curves for this case. It can be seen that these curves provide a better fit to the experimental data than the curves in (C).