Skip to main content
OSTI.GOVU.S. Department of Energy Office of Scientific and Technical Information
U.S. Department of Energy
Office of Scientific and Technical Information
 

A Toolbox Model of Evolution of Metabolic Pathways on Networks of Arbitrary Topology

Journal Article · · PLoS Computational Biology (Online)
 [1];  [2]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States). Dept. of Condensed Matter Physics and Materials Science; Stony Brook Univ., NY (United States). Dept. of Physics and Astronomy; DOE/OSTI
  2. Brookhaven National Lab. (BNL), Upton, NY (United States). Dept. of Condensed Matter Physics and Materials Science
+ Show Author Affiliations
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, reallife metabolic networks are characterized by a broad distribution of pathway lengths and sizes of metabolic regulons in regulatory networks.
Research Organization:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
AC02-98CH10886
OSTI ID:
1627212
Journal Information:
PLoS Computational Biology (Online), Journal Name: PLoS Computational Biology (Online) Journal Issue: 5 Vol. 7; ISSN 1553-7358
Publisher:
Public Library of ScienceCopyright Statement
Country of Publication:
United States
Language:
English

References (17)

An environmental perspective on metabolism journal June 2008
Economy of design in metabolic pathways: Further remarks on the game of the pentose phosphate cycle journal May 1988
Percolation processes: I. Crystals and mazes journal July 1957
The metabolic world of Escherichia coli is not small journal February 2004
Toolbox model of evolution of prokaryotic metabolic networks and their regulation journal May 2009
KEGG: Kyoto Encyclopedia of Genes and Genomes journal January 2000
Signatures of Arithmetic Simplicity in Metabolic Network Architecture journal April 2010
The Evolution of Connectivity in Metabolic Networks text January 2005
Evolution of complex modular biological networks text January 2007
The large-scale organization of metabolic networks text January 2000
Expanding Metabolic Networks: Scopes of Compounds, Robustness, and Evolution journal September 2005
Scaling laws in the functional content of genomes journal September 2003
The large-scale organization of metabolic networks journal October 2000
Propagation of large concentration changes in reversible protein-binding networks journal August 2007
The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes journal July 2001
The Evolution of Connectivity in Metabolic Networks journal June 2005
Evolution of Complex Modular Biological Networks journal February 2008

Cited By (6)

Supra-operonic clusters of functionally related genes (SOCs) are a source of horizontal gene co-transfers journal January 2017
Topology of molecular interaction networks journal January 2013
Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory journal July 2012
Family-specific scaling laws in bacterial genomes preprint January 2017
Universal distribution of component frequencies in biological and technological systems journal March 2013
Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment journal December 2018

Similar Records

A Toolbox Model of Evolution of Metabolic Pathways on Networks of Arbitrary Topology
Journal Article · Sun May 01 00:00:00 EDT 2011 · PLOS Computational Biology · OSTI ID:1026770
Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus
Journal Article · Wed Jun 15 00:00:00 EDT 2011 · BMC Genomics, 12(Suppl 1):Article No. S3 · OSTI ID:1018137
RegPrecise 3.0 – A resource for genome-scale exploration of transcriptional regulation in bacteria
Journal Article · Mon Dec 31 19:00:00 EST 2012 · BMC Genomics · OSTI ID:1626423

Related Subjects

59 BASIC BIOLOGICAL SCIENCES
97 MATHEMATICS AND COMPUTING
Biochemistry & Molecular Biology
Mathematical & Computational Biology