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. 2020 Jan 21;9:e50342. doi: 10.7554/eLife.50342

Figure 3. Experimental validation of EGF relative sensing by pAkt in MCF10A cells.

(a) The maximal pAkt responses after exposing cells to different background EGF levels (x axis) for 3 hr, followed by 2-, 3-, 4-, and 6-fold increases (different colors) in EGF. Inset shows experimental pAkt response over a wider range of background EGF levels. (b) Maximal pAkt responses (y axis) to fold changes in EGF depended approximately logarithmically on the fold change. Maximal pAkt responses induced by stimulation with various EGF background levels (data points with the same shape and color) were combined and plotted as a function of the EGF fold change (x axis). Dashed line represents log-linear fit to the data (Pearson’s r2 = 0.93, regression p value < 10−11). In all subpanels, error bars represent the standard deviation of n = 3 technical replicates. Source data: expt_data.mat (available in Source code 1).

Figure 3.

Figure 3—figure supplement 1. Dynamics of pAkt responses to step increases in EGF.

Figure 3—figure supplement 1.

(a) MCF10A cells pretreated with a certain level of background EGF (shown in the top right corner of each figure) for three hours were then subjected to an abrupt step increases in EGF. (b) Biological replicate of panel a). Different colors represent different EGF folds changes. In both panels, individual data points represent averages from n = 3 technical replicates and error bars represent the corresponding standard deviation.

Figure 3—figure supplement 2. The scatter plot of pAkt levels observed in the two biological replicates shown in Figure 3—figure supplement 1.

Figure 3—figure supplement 2.

Observed pAkt levels induced by EGF fold changes were highly reproducible between two biological replicates (Pearson’s correlation coefficient is r2 = 0.94, regression p<10−5). Error bars represent the standard deviation of n = 3 technical replicates.

Figure 3—figure supplement 3. Biological replicate of the experiment demonstrating relative sensing of EGF by pAkt (main text Figure 3).

Figure 3—figure supplement 3.

(a) The maximum of the measured pAkt response after exposing MCF10A cells to different background doses of EGF for 180 min followed by x2, x3, x4, or x6 fold change in background EGF exposure (shown on the logarithmic x-axis). Inset shows pAkt response over a wider range of background EGF exposures. (b) Maximum pAkt responses to fold changes in EGF depend log linearly on the fold change in EGF doses. Individual data series represent the same initial EGF concentration as shown in the legend. Dashed line represents log-linear fit to data (Pearson’s correlation coefficient is r2 = 0.95, regression p<10−12). Error bars represent the standard deviation of n = 3 technical replicates.

Figure 3—figure supplement 4. Maximal Akt phosphorylation response does not depend on the absolute EGF stimulus.

Figure 3—figure supplement 4.

Maximal Akt phosphorylation response plotted as a function of absolute level of EGF abrupt signal across different levels of background EGF stimulation. Different colors indicate different background EGF levels. Error bars represent the standard deviation of n = 3 technical replicates.

Figure 3—figure supplement 5. Time-integral of pAkt response exhibits relative sensing of EGF.

Figure 3—figure supplement 5.

(a) The time-integral of the measured pAkt response between 2.5 and 30 min after exposing MCF10A cells to different background doses of EGF for 180 min followed by x2, x3, x4, or x6 fold change in background EGF exposure (shown on the logarithmic x-axis). Inset shows pAkt response over a wider range of background EGF exposures. (b) Time-averaged pAkt response (between 2.5 to 30 min after a fold change in EGF) depends log linearly on the fold change. Individual data series represent the same initial EGF concentration as shown in the legend. Dashed line represents log-linear fit to data (Pearson’s correlation coefficient is r2 = 0.94, regression p<10−12). (c and d) are biological repeats of a) and b) (Pearson’s correlation coefficient is r2 = 0.94, regression p<10−12). (e and f) show similar plots for integrals computed on pAkt responses simulated in silico from top 10 best fit models (Pearson’s correlation coefficient is r2 = 0.92, regression p<10−10). Error bars represent the standard deviation of n = 3 technical replicates in subpanels a to d.

Figure 3—figure supplement 6. Dynamic time course of pAkt response exhibits relative sensing of EGF fold change.

Figure 3—figure supplement 6.

(a) The dynamic pAkt response (bold lines) averaged over multiple background EGF levels corresponding to stimulation with the same EGF fold change. The faint time courses of the same color represent individual pAkt responses to the same EGF fold change at different background stimulation levels. Error bars represent the standard deviation across n = 5 background EGF doses for the same fold. (b) The averaged squared difference of pAkt response timecourses calculated between multiple background stimulation levels for the same EGF fold changes (diagonal), and for different EGF fold changes (off-diagonal).