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The Landscape of Evolution: Reconciling Structural and Dynamic Properties of Metabolic Networks in Adaptive Diversifications
Author(s) -
Erin S. Morrison,
Alexander V. Badyaev
Publication year - 2016
Publication title -
integrative and comparative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.328
H-Index - 123
eISSN - 1557-7023
pISSN - 1540-7063
DOI - 10.1093/icb/icw026
Subject(s) - metabolic network , flux balance analysis , biology , lineage (genetic) , network dynamics , evolutionary biology , dynamic network analysis , phenotype , flux (metallurgy) , gene regulatory network , network structure , network analysis , biological network , computational biology , gene , genetics , computer science , gene expression , mathematics , theoretical computer science , physics , computer network , materials science , discrete mathematics , metallurgy , quantum mechanics
The network of the interactions among genes, proteins, and metabolites delineates a range of potential phenotypic diversifications in a lineage, and realized phenotypic changes are the result of differences in the dynamics of the expression of the elements and interactions in this deterministic network. Regulatory mechanisms, such as hormones, mediate the relationship between the structural and dynamic properties of networks by determining how and when the elements are expressed and form a functional unit or state. Changes in regulatory mechanisms lead to variable expression of functional states of a network within and among generations. Functional properties of network elements, and the magnitude and direction of evolutionary change they determine, depend on their location within a network. Here, we examine the relationship between network structure and the dynamic mechanisms that regulate flux through a metabolic network. We review the mechanisms that control metabolic flux in enzymatic reactions and examine structural properties of the network locations that are targets of flux control. We aim to establish a predictive framework to test the contributions of structural and dynamic properties of deterministic networks to evolutionary diversifications.

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