Paper Info
Title
A Toolbox Model of Evolution of Metabolic Pathways on Networks of Arbitrary Topology
Abstract
In prokaryotic genomes the number of transcriptional regulators is known to be proportional to the square of the total number of protein-coding genes. A toolbox model of evolution was recently proposed to explain this empirical scaling for metabolic enzymes and their regulators. According to its rules, the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger "universal" network formed by the union of all species-specific networks. It remained to be understood, however, how the topological properties of this universal network influence the scaling law of functional content of genomes in the toolbox model. Here we answer this question by first analyzing the scaling properties of the toolbox model on arbitrary tree-like universal networks. We prove that critical branching topology, in which the average number of upstream neighbors of a node is equal to one, is both necessary and sufficient for quadratic scaling. We further generalize the rules of the model to incorporate reactions with multiple substrates/products as well as branched and cyclic metabolic pathways. To achieve its metabolic tasks, the new model employs evolutionary optimized pathways with minimal number of reactions. Numerical simulations of this realistic model on the universal network of all reactions in the KEGG database produced approximately quadratic scaling between the number of regulated pathways and the size of the metabolic network. To quantify the geometrical structure of individual pathways, we investigated the relationship between their number of reactions, byproducts, intermediate, and feedback metabolites. Our results validate and explain the ubiquitous appearance of the quadratic scaling for a broad spectrum of topologies of underlying universal metabolic networks. They also demonstrate why, in spite of "small-world" topology, real-life metabolic networks are characterized by a broad distribution of pathway lengths and sizes of metabolic regulons in regulatory networks.
Year
DOI
Venue
2011
10.1371/journal.pcbi.1001137
PLOS COMPUTATIONAL BIOLOGY
Keywords
Field
DocType
numerical simulation,metabolic network,transcription regulation,metabolic pathway,enzyme,horizontal transfer,computer simulation,spectrum,regulon
Topology,Biology,Toolbox,Metabolic pathway,Quadratic equation,Metabolic network,KEGG,Network topology,Bioinformatics,Scaling,Scaling law
Journal
Volume
Issue
ISSN
7
5
1553-734X
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Tin Yau Pang121.75
Sergei Maslov21337.69