Mathematical modeling of the microtubule detyrosination/tyrosination cycle for cell-based drug screening design
Fig 2
Parameterization of the computational model CDTP with HCI quantification combined with BIOCHAM parameter optimization procedures.
(A) Representative images of immunostaining of tyrosinated tubulin (Tyr) in green, detyrosinated tubulin (Detyr) in red in MEF cells and hTERT RPE-1 cells (left). Cells were co-stained with Hoechst. Scale bars: 20 μm. (B) Quantification of the tyrosination status by high-content imaging (Right). Tubulin and microtubule are predominantly observed in tyrosinated form (Z’-factor > 0.5). The plotted values are the average of single-cells values ± SD. (C) Best satisfaction degree obtained by the parameter search procedure by varying only one kinetic parameter independently, showing failure to reproduce the observed behaviour. The BIOCHAM command used is: search_parameters(F(Time == 5 /\ Tyr = factor1 * Detyr /\ F(Time == 20 /\ Tyr = factor2 * Detyr)), [0 <= p <= 100], [factor1 -> 10, factor2 -> 10]) where p is the kinetic parameter to optimize. (D) Best satisfaction degree obtained by the parameter search procedure by varying couples of two kinetic parameters simultaneously, showing perfect satisfaction of the specification with one couple of parameters only: (Vm2, km1). The BIOCHAM command used is: search_parameters(F(Time == 5 /\ Tyr = factor1 * Detyr /\ F(Time == 20 /\ Tyr = factor2 * Detyr)), [0 <= p1 <= 100, 0 <= p2<= 100], [factor1 -> 10, factor2 -> 10]) where p1 and p2 are two kinetic parameters to optimize. (E) Landscape of the satisfaction degree obtained by scanning the parameter values of the couple (Vm2, km1). The BIOCHAM command used to obtain the landscape is: scan_parameters(F(Time == 5 /\ Tyr = factor1 * Detyr /\ F(Time == 20 /\ Tyr = factor2 * Detyr)), (0 <= Vm2 <= 15), (0 <= km1 <= 30), [factor1 -> 10, factor2 -> 10], resolution:30). (F) Unperturbed numerical simulation of the CDTP model showing the maintenance of a high level of tyrosination. The FO-LTL formulae used to infer the new parameter values for has been updated to infer new parameters with minimal difference from their original values from the CDTN model: search_parameters(F(Time == 5 /\ Vm2 = VarVm2 /\ km1 = Varkm1 /\ Tyr = factor1 * Detyr /\ F(Time == 20 /\ Tyr = factor2 * Detyr)), [0 <= Vm2 <= 15, 0 <= km1 <= 30], [VarVm2 -> 0.2, Varkm1 -> 0.478, factor1 -> 10, factor2 -> 10]).