Metabolic systems cost-benefit analysis for interpreting network structure and regulation.
BACKGROUND
Interpretation of bioinformatics data in terms of cellular function is a major challenge facing systems biology. This question is complicated by robust metabolic networks filled with structural features like parallel pathways and isozymes. Under conditions of nutrient sufficiency, metabolic networks are well known to be regulated for thermodynamic efficiency however; efficient biochemical pathways are anabolically expensive to construct. While parameters like thermodynamic efficiency have been extensively studied, a systems-based analysis of anabolic proteome synthesis 'costs' and the cellular function implications of these costs has not been reported.


RESULTS
A cost-benefit analysis of an in silico Escherichia coli network revealed the relationship between metabolic pathway proteome synthesis requirements, DNA-coding sequence length, thermodynamic efficiency and substrate affinity. The results highlight basic metabolic network design principles. Pathway proteome synthesis requirements appear to have shaped biochemical network structure and regulation. Under conditions of nutrient scarcity and other general stresses, E. coli expresses pathways with relatively inexpensive proteome synthesis requirements instead of more efficient but also anabolically more expensive pathways. This evolutionary strategy provides a cellular function-based explanation for common network motifs like isozymes and parallel pathways and possibly explains 'overflow' metabolisms observed during nutrient scarcity.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Carlson
Ross P
RP
Department of Chemical and Biological Engineering, Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717, USA. rossc@coe.montana.edu [corrected].
D005075:Biological Evolution; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism*; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism; D049490:Systems Biology / Q000379:methods
D020543:Proteome