Literature DB >> 15142747

Mechanistic systems models of cell signaling networks: a case study of myocyte adrenergic regulation.

Jeffrey J Saucerman1, Andrew D McCulloch.   

Abstract

Signal transduction networks coordinate a wide variety of cellular functions, including gene expression, metabolism, and cell fate processes. Understanding biological networks quantitatively is a major challenge to post-genomic biology, and mechanistic systems models will be crucial for this task. Here, we review approaches towards developing mechanistic systems models of established cell signaling networks. The ability of mechanistic system models to generate testable biological hypotheses and experimental strategies is discussed. As a case study of model development and analysis, we examined the functional roles of phospholamban, the L-type calcium channel, the ryanodine receptor, and troponin I phosphorylation upon beta-adrenergic stimulation in the rat ventricular myocyte. Model analysis revealed that while protein kinase A-mediated phosphorylation of the ryanodine receptor greatly increases its calcium sensitivity, calcium autoregulation may adapt quickly by negating potential increases in contractility. Systematic combinations of in silico perturbations supported the conclusion that phospholamban phosphoregulation is the primary mechanism for increased sarcoplasmic reticulum load and calcium relaxation rate during beta-adrenergic stimulation, while both phospholamban and the L-type calcium channel contribute to increased systolic calcium. Combined with detailed experimental studies, mechanistic systems models will be valuable for developing a quantitative understanding of cell signaling networks. Copyright 2004 Elsevier Ltd.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15142747     DOI: 10.1016/j.pbiomolbio.2004.01.005

Source DB:  PubMed          Journal:  Prog Biophys Mol Biol        ISSN: 0079-6107            Impact factor:   3.667


  26 in total

Review 1.  Exploiting mathematical models to illuminate electrophysiological variability between individuals.

Authors:  Amrita X Sarkar; David J Christini; Eric A Sobie
Journal:  J Physiol       Date:  2012-04-10       Impact factor: 5.182

2.  Synergy between CaMKII substrates and β-adrenergic signaling in regulation of cardiac myocyte Ca(2+) handling.

Authors:  Anthony R Soltis; Jeffrey J Saucerman
Journal:  Biophys J       Date:  2010-10-06       Impact factor: 4.033

3.  β-adrenergic effects on cardiac myofilaments and contraction in an integrated rabbit ventricular myocyte model.

Authors:  Jorge A Negroni; Stefano Morotti; Elena C Lascano; Aldrin V Gomes; Eleonora Grandi; José L Puglisi; Donald M Bers
Journal:  J Mol Cell Cardiol       Date:  2015-02-25       Impact factor: 5.000

4.  Phospholemman is a negative feed-forward regulator of Ca2+ in β-adrenergic signaling, accelerating β-adrenergic inotropy.

Authors:  Jason H Yang; Jeffrey J Saucerman
Journal:  J Mol Cell Cardiol       Date:  2012-01-20       Impact factor: 5.000

5.  An optimal number of molecules for signal amplification and discrimination in a chemical cascade.

Authors:  Yoshihiro Morishita; Tetsuya J Kobayashi; Kazuyuki Aihara
Journal:  Biophys J       Date:  2006-06-23       Impact factor: 4.033

Review 6.  Computational biology in the study of cardiac ion channels and cell electrophysiology.

Authors:  Yoram Rudy; Jonathan R Silva
Journal:  Q Rev Biophys       Date:  2006-07-19       Impact factor: 5.318

7.  Systems analysis of PKA-mediated phosphorylation gradients in live cardiac myocytes.

Authors:  Jeffrey J Saucerman; Jin Zhang; Jody C Martin; Lili X Peng; Antine E Stenbit; Roger Y Tsien; Andrew D McCulloch
Journal:  Proc Natl Acad Sci U S A       Date:  2006-08-11       Impact factor: 11.205

8.  Coupling of a 3D finite element model of cardiac ventricular mechanics to lumped systems models of the systemic and pulmonic circulation.

Authors:  Roy C P Kerckhoffs; Maxwell L Neal; Quan Gu; James B Bassingthwaighte; Jeff H Omens; Andrew D McCulloch
Journal:  Ann Biomed Eng       Date:  2006-11-08       Impact factor: 3.934

Review 9.  Bigger, better, faster: principles and models of AKAP anchoring protein signaling.

Authors:  Eric C Greenwald; Jeffrey J Saucerman
Journal:  J Cardiovasc Pharmacol       Date:  2011-11       Impact factor: 3.105

10.  β-adrenergic stimulation activates early afterdepolarizations transiently via kinetic mismatch of PKA targets.

Authors:  Yuanfang Xie; Eleonora Grandi; Jose L Puglisi; Daisuke Sato; Donald M Bers
Journal:  J Mol Cell Cardiol       Date:  2013-02-26       Impact factor: 5.000

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.