A Mathematical Model Linking Ca2+-Dependent Signaling Pathway and Gene Expression Regulation in Human Skeletal Muscle

Abstract

The physiological adaptation to aerobic endurance exercises is provided by activation of signaling pathways in skeletal muscle cells. Training-induced activation of specific signaling pathways results in significant transcriptional responses. Despite the ongoing endeavours to experimentally investigate regulatory mechanisms and signal transduction pathways involved in the contraction-induced adaptation, quantitative contribution of certain signal molecules in expression regulation of genes responsible for intracellular response has not been studied МОДЕЛЬ Ca 2+ -ЗАВИСИМОГО СИГНАЛЬНОГО ПУТИ И РЕГУЛЯЦИИ ГЕНОВ В КЛЕТКАХ СКЕЛЕТНОЙ МЫШЦЫ ЧЕЛОВЕКА comprehensively yet. The paper presents novel developed model linking Ca 2+dependent signaling pathway and downstream transcription regulation of early and late response genes in human skeletal muscle during exercise. Numerical analysis of the model enabled to reveal crucial steps in this signal transduction pathway for the adaptation and demonstrated the necessity of consideration of additional transcription factors regulating transcription of late response genes in order to adequately reproduce gene expression data that were taken in human vastus lateralis muscle during and after acute cycling exercise.

Transcriptomic Signatures and Upstream Regulation in Human Skeletal Muscle Adapted to Disuse and Aerobic Exercise

“…To put these pieces into a single picture, mathematical modeling seems to be a perspective approach. For this purpose, we have started to develop a complex mathematical model that links metabolic changes with the expression of some exercise-induced genes (namely NR4A2 , NR4A3 and PPARGC1A ) [ 92 ].…”

A modular mathematical model of exercise-induced changes in metabolism, signaling, and gene expression in human skeletal muscle

“…Collectively, these findings drove us to include in our model the Ca 2+ -dependent regulation of calmodulin, CREB1 (via CaMKII), CRTC (via calcineurin), and AMPK (via CaMKK2) (Figure 3). The amount of these proteins in human skeletal muscle was estimated using published proteomics and transcriptomics data (Murgia et al, 2017; Popov et al, 2019) ( see Supplementary data in (Akberdin et al, 2020)).…”

“…Moreover, in a genome-wide study on various human tissues, it was shown that the phosphorylation level of CREB Ser133 does not always correlate with its transcriptional activity (Zhang et al, 2005). Therefore, we suggested the expression of genes with delayed response (including PPARGC1A ) is regulated by increasing the expression of one of the early response genes encoding transcription factors leading to a rapid increase of corresponding protein (see Figure 1 and Figure 5 in (Akberdin et al, 2020). Analysis of contractile activity-specific transcriptomic data (Popov et al, 2019) showed that a rapid increase in the expression of genes encoding various TFs is observed already in the first hour after an exercise.…”

“…Analysis of contractile activity-specific transcriptomic data (Popov et al, 2019) showed that a rapid increase in the expression of genes encoding various TFs is observed already in the first hour after an exercise. It turned out that the binding motifs of some TFs (CREB-like proteins, as well as proteins of the AP-1 family: FOS and JUN) are located and intersected with each other both in the alternative and in the canonical promoters of the PPARGC1A gene (Akberdin et al, 2020), i.e. these TFs can act as potential regulators of this gene.…”

Evolution and extinction can occur rapidly: a modeling approach

“…The model has been developed using a modular approach where an investigated process or biological phenomenon is considered via combination of its subsystem’s models. This approach is widely used to construct diverse models of biological systems ( Kurata et al, 2014 ; Likhoshvai et al, 2014 ; Kazantsev et al, 2018 ; Kiselev et al, 2019 ; Akberdin et al, 2020 ). The model of a large ecosystem consists of two subsystems.…”