scholarly journals Information Flow in the Fibroblast Growth Factor Receptor Communication Channel

2021 ◽  
Author(s):  
José Díaz ◽  
Gustavo Martínez-Mekler

AbstractIn 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 ∼ 2.75 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 effector 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 0.96 bits/min.

Author(s):  
Xingzhe Yang ◽  
Feng Li ◽  
Jie Ma ◽  
Yan Liu ◽  
Xuejiao Wang ◽  
...  

AbstractIn recent years, the incidence of fatigue has been increasing, and the effective prevention and treatment of fatigue has become an urgent problem. As a result, the genetic research of fatigue has become a hot spot. Transcriptome-level regulation is the key link in the gene regulatory network. The transcriptome includes messenger RNAs (mRNAs) and noncoding RNAs (ncRNAs). MRNAs are common research targets in gene expression profiling. Noncoding RNAs, including miRNAs, lncRNAs, circRNAs and so on, have been developed rapidly. Studies have shown that miRNAs are closely related to the occurrence and development of fatigue. MiRNAs can regulate the immune inflammatory reaction in the central nervous system (CNS), regulate the transmission of nerve impulses and gene expression, regulate brain development and brain function, and participate in the occurrence and development of fatigue by regulating mitochondrial function and energy metabolism. LncRNAs can regulate dopaminergic neurons to participate in the occurrence and development of fatigue. This has certain value in the diagnosis of chronic fatigue syndrome (CFS). CircRNAs can participate in the occurrence and development of fatigue by regulating the NF-κB pathway, TNF-α and IL-1β. The ceRNA hypothesis posits that in addition to the function of miRNAs in unidirectional regulation, mRNAs, lncRNAs and circRNAs can regulate gene expression by competitive binding with miRNAs, forming a ceRNA regulatory network with miRNAs. Therefore, we suggest that the miRNA-centered ceRNA regulatory network is closely related to fatigue. At present, there are few studies on fatigue-related ncRNA genes, and most of these limited studies are on miRNAs in ncRNAs. However, there are a few studies on the relationship between lncRNAs, cirRNAs and fatigue. Less research is available on the pathogenesis of fatigue based on the ceRNA regulatory network. Therefore, exploring the complex mechanism of fatigue based on the ceRNA regulatory network is of great significance. In this review, we summarize the relationship between miRNAs, lncRNAs and circRNAs in ncRNAs and fatigue, and focus on exploring the regulatory role of the miRNA-centered ceRNA regulatory network in the occurrence and development of fatigue, in order to gain a comprehensive, in-depth and new understanding of the essence of the fatigue gene regulatory network.


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