Figure 8. Proposed models of cargo trafficking through APPL and EEA1 compartments. (A) In model 2, cargo on PM follows either the clathrin pathway through CCPs to CCVs or the clathrin-independent route by CIVs. About 94% of Tf (blue) and 25% of EGF (red) follow CDE. Almost 75% of EGF and only 6% of Tf are internalized by CIVs. In line with model 1, A and B, we considered two pools of CCV that deliver cargo to APPL1-positive (36% EGF and 99.5%Tf) and EEA1-positive (64% EGF, 0.5%Tf) endosomes. The flux of Tf through CCV to EEA1 increased up to 22% by down-regulation of APPL1. The fit of model suggests that CIVs deliver cargo to APPL1+EEA1 and EEA1 endosomes. The dynamic of cargo traffic through EEA1-positive demonstrated complex behavior that cannot be explained in case of kinetically homogeneous compartments. The down-regulation of APPL1 and CHC revealed that cargo traffic consists of two components that can be separately inhibited. Therefore, we introduced in the model 2 two kinetically distinct EEA1 compartments, which we denote EEA1(ccv) and EEA1(civ) according to the main mode of cargo delivery. The corresponding double APPL1+EEA1 compartments were denoted A&E(ccv) and A&E(civ) accordingly. The sorting of cargo toward the recycling route occurs in the all three endocytic compartments APPL1, APPL1+EEA1, and EEA1. However, the delivery of EGF to the late endosomes (LE) and following degradation (∼70% of EGF degrade in 30 min) occurs only through EEA1 compartment. We denote the recycling endosomes en route to PM and perinuclear recycling endosome in accordance to the kinetic rates of either fast recycling endosomes (FRE) or recycling endosomes RE. The thin arrows denote the routes that transport less than 10% of cargo from compartment, however the removal of them makes the fit to the experimental data unsatisfactory (P < 0.01). (B–D) Tables present results of the best fit of model 1A (B), model 1B (C), and model 2 (D) to the experimental data in control and perturbed cell. X2/N denotes normalized χ2:. / χ 2 /N= 1 N ∑ i=1 N+1 ( f i − d i ) 2 σ i 2 , . / where fi and di are model prediction and experimental data, σi is SEM of experimental data, N = 167. The p-values were calculated by χ2 distribution. (B) The probability of null hypothesis that the deviation of the model prediction from the experiment is the result of random noise (p-value) is extremely low for all four conditions. Therefore, model 1A has to be rejected. (C) The probability of null hypothesis is very low for all conditions, although the logarithm of probability of model 1B (see Materials and methods) is much higher than those of 1A. Nevertheless, model 1B has to be rejected as well. (D) The probability of null hypothesis is high. Therefore, most probably the deviation of model 2 from the experiment is the result of experimental uncertainty. The model 2 is much more probable ln(P) > 100 than model 1B for all conditions. Therefore, the improvement of the quality of fit is statistically significant to justify three additional parameters.
Figure 8.

Proposed models of cargo trafficking through APPL and EEA1 compartments. (A) In model 2, cargo on PM follows either the clathrin pathway through CCPs to CCVs or the clathrin-independent route by CIVs. About 94% of Tf (blue) and 25% of EGF (red) follow CDE. Almost 75% of EGF and only 6% of Tf are internalized by CIVs. In line with model 1, A and B, we considered two pools of CCV that deliver cargo to APPL1-positive (36% EGF and 99.5%Tf) and EEA1-positive (64% EGF, 0.5%Tf) endosomes. The flux of Tf through CCV to EEA1 increased up to 22% by down-regulation of APPL1. The fit of model suggests that CIVs deliver cargo to APPL1+EEA1 and EEA1 endosomes. The dynamic of cargo traffic through EEA1-positive demonstrated complex behavior that cannot be explained in case of kinetically homogeneous compartments. The down-regulation of APPL1 and CHC revealed that cargo traffic consists of two components that can be separately inhibited. Therefore, we introduced in the model 2 two kinetically distinct EEA1 compartments, which we denote EEA1(ccv) and EEA1(civ) according to the main mode of cargo delivery. The corresponding double APPL1+EEA1 compartments were denoted A&E(ccv) and A&E(civ) accordingly. The sorting of cargo toward the recycling route occurs in the all three endocytic compartments APPL1, APPL1+EEA1, and EEA1. However, the delivery of EGF to the late endosomes (LE) and following degradation (∼70% of EGF degrade in 30 min) occurs only through EEA1 compartment. We denote the recycling endosomes en route to PM and perinuclear recycling endosome in accordance to the kinetic rates of either fast recycling endosomes (FRE) or recycling endosomes RE. The thin arrows denote the routes that transport less than 10% of cargo from compartment, however the removal of them makes the fit to the experimental data unsatisfactory (P < 0.01). (B–D) Tables present results of the best fit of model 1A (B), model 1B (C), and model 2 (D) to the experimental data in control and perturbed cell. X2/N denotes normalized χ2:

χ 2 / N = 1 N ∑ i = 1 N + 1 ( f i − d i ) 2 σ i 2 ,

where fi and di are model prediction and experimental data, σi is SEM of experimental data, N = 167. The p-values were calculated by χ2 distribution. (B) The probability of null hypothesis that the deviation of the model prediction from the experiment is the result of random noise (p-value) is extremely low for all four conditions. Therefore, model 1A has to be rejected. (C) The probability of null hypothesis is very low for all conditions, although the logarithm of probability of model 1B (see Materials and methods) is much higher than those of 1A. Nevertheless, model 1B has to be rejected as well. (D) The probability of null hypothesis is high. Therefore, most probably the deviation of model 2 from the experiment is the result of experimental uncertainty. The model 2 is much more probable ln(P) > 100 than model 1B for all conditions. Therefore, the improvement of the quality of fit is statistically significant to justify three additional parameters.

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