Information Flow in the Fibroblast Growth Factor Receptor Communication Channel

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Citation: José Díaz, Gustavo Martínez-Mekler. Information Flow in the Fibroblast Growth Factor Receptor Communication Channel. Archives of Clinical and Biomedical Research 6 (2022): 639-655.

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In this work we analyze the flow of information through the Fibroblast Growth Factor Receptor (FGFR) communication channel when different types of signals are transmitted by the MAPK cascade to the Gene Regulatory Network (GRN) formed by the genes C-Myc, DUSP, and Cdc25A, which control fibroblast proliferation. We used the canonical mathematical model of the MAPK cascade coupled to a stochastic model for the activation of the gene regulatory network, subject to different types of FGF inputs (step, quadratic pulses, Dirac delta, and white noise), in order to analyze the response of the gene regulatory network to each type of signal, and determine the temporal variation of the value of its Shannon entropy in each case. Our model suggests that the sustained activation of the FGFR communication channel with a step of FGF > 1 nM is required for cell cycle progression and that during the G1/S transition the amount of uncertainty of the GRN remains at a steady value of ~ 2.25 bits, indicating that while the fibroblast stimulation with FGF continues the G1/S transition does not require an additional interchange of information between the emitter and the gene regulatory network to be completed. We also found that either low frequency pulses of FGF or low frequency noise, both with a frequency f ≤ 2.77 Hz, are not filtered by the MAPK cascade and can modify the output of the communication channel, i.e., the amount of the effectors proteins c-myc, cdc25A and DUSP. An additional effect suggested by our model is that o low frequency periodic signals and noise possibly blockage cell cycle progression because the threshold value concentration of cdc25A for the G1/S transition is not sustained in the in the nucleus during the 10 hours that this process lasts. Finally, from our model we can estimate the capacity of this communication channel in 0.038 bits/s.


Fibroblast Growth Factor; Gene Regulatory Networks; Information Theory; MAPK, C-myc; Nonlinear Dynamics

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