Research output: Contribution to journal › Article › peer-review
A modular mathematical model of exercise-induced changes in metabolism, signaling, and gene expression in human skeletal muscle. / Akberdin, Ilya R.; Kiselev, Ilya N.; Pintus, Sergey S. et al.
In: International Journal of Molecular Sciences, Vol. 22, No. 19, 10353, 01.10.2021.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - A modular mathematical model of exercise-induced changes in metabolism, signaling, and gene expression in human skeletal muscle
AU - Akberdin, Ilya R.
AU - Kiselev, Ilya N.
AU - Pintus, Sergey S.
AU - Sharipov, Ruslan N.
AU - Vertyshev, Alexander Yu
AU - Vinogradova, Olga L.
AU - Popov, Daniil V.
AU - Kolpakov, Fedor A.
N1 - Funding Information: Funding: The study was financially supported by RFBR grants (No. 17-00-00308(K): 17-00-00296, 17-00-00242) and in part by Sirius University. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - Skeletal muscle is the principal contributor to exercise-induced changes in human metabolism. Strikingly, although it has been demonstrated that a lot of metabolites accumulating in blood and human skeletal muscle during an exercise activate different signaling pathways and induce the expression of many genes in working muscle fibres, the systematic understanding of signaling– metabolic pathway interrelations with downstream genetic regulation in the skeletal muscle is still elusive. Herein, a physiologically based computational model of skeletal muscle comprising energy metabolism, Ca2+, and AMPK (AMP-dependent protein kinase) signaling pathways and the expression regulation of genes with early and delayed responses was developed based on a modular modeling approach and included 171 differential equations and more than 640 parameters. The integrated modular model validated on diverse including original experimental data and different exercise modes provides a comprehensive in silico platform in order to decipher and track cause– effect relationships between metabolic, signaling, and gene expression levels in skeletal muscle.
AB - Skeletal muscle is the principal contributor to exercise-induced changes in human metabolism. Strikingly, although it has been demonstrated that a lot of metabolites accumulating in blood and human skeletal muscle during an exercise activate different signaling pathways and induce the expression of many genes in working muscle fibres, the systematic understanding of signaling– metabolic pathway interrelations with downstream genetic regulation in the skeletal muscle is still elusive. Herein, a physiologically based computational model of skeletal muscle comprising energy metabolism, Ca2+, and AMPK (AMP-dependent protein kinase) signaling pathways and the expression regulation of genes with early and delayed responses was developed based on a modular modeling approach and included 171 differential equations and more than 640 parameters. The integrated modular model validated on diverse including original experimental data and different exercise modes provides a comprehensive in silico platform in order to decipher and track cause– effect relationships between metabolic, signaling, and gene expression levels in skeletal muscle.
KW - BioUML
KW - Ca-dependent signaling pathway
KW - Mathematical model
KW - Physical exercise
KW - Regulation of expression
KW - RNA sequencing
KW - Skeletal muscle
KW - Transcriptome
UR - http://www.scopus.com/inward/record.url?scp=85115733978&partnerID=8YFLogxK
U2 - 10.3390/ijms221910353
DO - 10.3390/ijms221910353
M3 - Article
C2 - 34638694
AN - SCOPUS:85115733978
VL - 22
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
SN - 1661-6596
IS - 19
M1 - 10353
ER -
ID: 34322091