Functional classification of skeletal muscle networks. I. Normal physiology
Author(s) -
Yu Wang,
Jack M. Winters,
Shankar Subramaniam
Publication year - 2012
Publication title -
journal of applied physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.253
H-Index - 229
eISSN - 8750-7587
pISSN - 1522-1601
DOI - 10.1152/japplphysiol.01514.2011
Subject(s) - skeletal muscle , biology , myosin , microbiology and biotechnology , actin , signal transduction , computational biology , neuroscience , bioinformatics , anatomy
Extensive measurements of the parts list of human skeletal muscle through transcriptomics and other phenotypic assays offer the opportunity to reconstruct detailed functional models. Through integration of vast amounts of data present in databases and extant knowledge of muscle function combined with robust analyses that include a clustering approach, we present both a protein parts list and network models for skeletal muscle function. The model comprises the four key functional family networks that coexist within a functional space; namely, excitation-activation family (forward pathways that transmit a motoneuronal command signal into the spatial volume of the cell and then use Ca(2+) fluxes to bind Ca(2+) to troponin C sites on F-actin filaments, plus transmembrane pumps that maintain transmission capacity); mechanical transmission family (a sophisticated three-dimensional mechanical apparatus that bidirectionally couples the millions of actin-myosin nanomotors with external axial tensile forces at insertion sites); metabolic and bioenergetics family (pathways that supply energy for the skeletal muscle function under widely varying demands and provide for other cellular processes); and signaling-production family (which represents various sensing, signal transduction, and nuclear infrastructure that controls the turn over and structural integrity and regulates the maintenance, regeneration, and remodeling of the muscle). Within each family, we identify subfamilies that function as a unit through analysis of large-scale transcription profiles of muscle and other tissues. This comprehensive network model provides a framework for exploring functional mechanisms of the skeletal muscle in normal and pathophysiology, as well as for quantitative modeling.
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