A critical view of metabolic network adaptations

There has been considerable recent interest in deciphering the adaptive properties underlying the structure and function of metabolic networks. Various features of metabolic networks such as the global topology, distribution of fluxes, and mutational robustness, have been proposed to have adaptive significance and hence reflect design principles. However, whether evolutionary processes alternative to direct selection on the trait under investigation also play a role is often ignored and the selection pressures maintaining a given metabolic trait often remain speculative. Some systems‐level traits might simply arise as by‐products of selection on other traits or even through random genetic drift. Here, we ask which systems‐level aspects of metabolism are likely to have adaptive utility and which could be better explained as by‐products of other evolutionary forces. We conclude that the global topological characteristics of metabolic networks and their mutational robustness are unlikely to be directly shaped by natural selection. Conversely, models of optimal design revealed that various aspects of individual pathways and the behavior of the whole network show signs of adaptations, even though the exact selective forces often remain elusive. Comparative and experimental approaches, which so far have been relatively rarely employed, could help to distinguish between alternative adaptive scenarios.

[1]  Andy Purvis,et al.  Comparative methods for explaining adaptations , 1991, Nature.

[2]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[3]  F. Bruggeman,et al.  The nature of systems biology. , 2007, Trends in microbiology.

[4]  S. Oliver,et al.  Plasticity of genetic interactions in metabolic networks of yeast , 2007, Proceedings of the National Academy of Sciences.

[5]  Sarel J Fleishman,et al.  Comment on "Network Motifs: Simple Building Blocks of Complex Networks" and "Superfamilies of Evolved and Designed Networks" , 2004, Science.

[6]  E. Charnov,et al.  How fundamental are Fisherian sex ratios , 1988 .

[7]  B. Palsson,et al.  Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[8]  E. Raineri,et al.  Evolvability and hierarchy in rewired bacterial gene networks , 2008, Nature.

[9]  T. P. Weber Optimizing metabolic pathways. , 1998, Trends in ecology & evolution.

[10]  G. Church,et al.  Analysis of optimality in natural and perturbed metabolic networks , 2002 .

[11]  S. Bonhoeffer,et al.  Cooperation and Competition in the Evolution of ATP-Producing Pathways , 2001, Science.

[12]  C. Pál,et al.  Adaptive evolution of bacterial metabolic networks by horizontal gene transfer , 2005, Nature Genetics.

[13]  A. Basolo The Dynamics of Fisherian Sex-Ratio Evolution: Theoretical and Experimental Investigations , 1994, The American Naturalist.

[14]  Patrick C Phillips,et al.  The Opportunity for Canalization and the Evolution of Genetic Networks , 2004, The American Naturalist.

[15]  J. C. Aledo,et al.  The ATP Paradox Is the Expression of an Economizing Fuel Mechanism* , 2004, Journal of Biological Chemistry.

[16]  C. Pál,et al.  Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast , 2004, Nature.

[17]  Jan Kok,et al.  Overview on sugar metabolism and its control in Lactococcus lactis - the input from in vivo NMR. , 2005, FEMS microbiology reviews.

[18]  Edda Klipp,et al.  Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities. , 2002, European journal of biochemistry.

[19]  M. Lynch The evolution of genetic networks by non-adaptive processes , 2007, Nature Reviews Genetics.

[20]  R Heinrich,et al.  Kinetic and thermodynamic principles determining the structural design of ATP-producing systems , 1998, Bulletin of mathematical biology.

[21]  Richard E. Lenski,et al.  Experimental Tests for an Evolutionary Trade‐Off between Growth Rate and Yield in E. coli , 2006, The American Naturalist.

[22]  B. Palsson,et al.  Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110 , 1994, Applied and environmental microbiology.

[23]  H. Westerhoff,et al.  The danger of metabolic pathways with turbo design. , 1998, Trends in biochemical sciences.

[24]  Edda Klipp,et al.  Metabolic optimization by re-distribution of enzyme activities , 2002 .

[25]  Francisco J. Planes,et al.  Recovering metabolic pathways via optimization , 2007, Bioinform..

[26]  S. Schuster,et al.  Metabolic network structure determines key aspects of functionality and regulation , 2002, Nature.

[27]  K. H. Wolfe,et al.  Reproductive toxicology. Chemical mixture. , 1997, Environmental health perspectives.

[28]  Ran Kafri,et al.  The regulatory utilization of genetic redundancy through responsive backup circuits. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[29]  U. Sauer,et al.  Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli , 2007, Molecular systems biology.

[30]  M. Lynch The frailty of adaptive hypotheses for the origins of organismal complexity , 2007, Proceedings of the National Academy of Sciences.

[31]  F. Montero,et al.  Optimization of Metabolism: The Evolution of Metabolic Pathways Toward Simplicity Through the Game of the Pentose Phosphate Cycle , 1994 .

[32]  U. Alon,et al.  Optimality and evolutionary tuning of the expression level of a protein , 2005, Nature.

[33]  Colin D. Meiklejohn,et al.  A single mode of canalization , 2002 .

[34]  J. Nielsen,et al.  Metabolic network analysis. A powerful tool in metabolic engineering. , 2000, Advances in biochemical engineering/biotechnology.

[35]  B. Palsson,et al.  Genome-scale models of microbial cells: evaluating the consequences of constraints , 2004, Nature Reviews Microbiology.

[36]  Masanori Arita The metabolic world of Escherichia coli is not small. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[37]  Jens Nielsen,et al.  Metabolic Network Analysis , 1999 .

[38]  Bas Teusink,et al.  Analysis of Growth of Lactobacillus plantarum WCFS1 on a Complex Medium Using a Genome-scale Metabolic Model* , 2006, Journal of Biological Chemistry.

[39]  R Heinrich,et al.  Theoretical approaches to the evolutionary optimization of glycolysis: thermodynamic and kinetic constraints. , 1997, European journal of biochemistry.

[40]  O. Tenaillon,et al.  Evolution of Mutational Robustness in an RNA Virus , 2005, PLoS biology.

[41]  Elmer S. West From the U. S. A. , 1965 .

[42]  Sebastian Bonhoeffer,et al.  The Evolution of Connectivity in Metabolic Networks , 2005, PLoS biology.

[43]  B. Palsson,et al.  Properties of metabolic networks: structure versus function. , 2005, Biophysical journal.

[44]  A. Grossman,et al.  An original adaptation of photosynthesis in the marine green alga Ostreococcus , 2008, Proceedings of the National Academy of Sciences.

[45]  Johannes H. de Winde,et al.  Prolonged Maltose-Limited Cultivation of Saccharomyces cerevisiae Selects for Cells with Improved Maltose Affinity and Hypersensitivity , 2004, Applied and Environmental Microbiology.

[46]  P. Iynedjian Glycolysis, turbo design and the endocrine pancreatic β cell , 1998 .

[47]  Robert P. St.Onge,et al.  The Chemical Genomic Portrait of Yeast: Uncovering a Phenotype for All Genes , 2008, Science.

[48]  U. Sauer,et al.  Article number: 62 REVIEW Metabolic networks in motion: 13 C-based flux analysis , 2022 .

[49]  Nevan J Krogan,et al.  Backup without redundancy: genetic interactions reveal the cost of duplicate gene loss , 2007, Molecular systems biology.

[50]  S. Oliver,et al.  Chance and necessity in the evolution of minimal metabolic networks , 2006, Nature.

[51]  M. A. de Menezes,et al.  Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity , 2007, Proceedings of the National Academy of Sciences.

[52]  Peter F. Stadler,et al.  Relevant cycles in Chemical reaction Networks , 2001, Adv. Complex Syst..

[53]  D. Fell,et al.  Is maximization of molar yield in metabolic networks favoured by evolution? , 2008, Journal of theoretical biology.

[54]  L. Olsson,et al.  Increasing NADH oxidation reduces overflow metabolism in Saccharomyces cerevisiae , 2007, Proceedings of the National Academy of Sciences.

[55]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[56]  R. Lenski,et al.  Microbial genetics: Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation , 2003, Nature Reviews Genetics.

[57]  C. Hutchison,et al.  Essential genes of a minimal bacterium. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[58]  W. D. de Vos,et al.  The unique features of glycolytic pathways in Archaea. , 2003, The Biochemical journal.

[59]  Costas D Maranas,et al.  OptStrain: a computational framework for redesign of microbial production systems. , 2004, Genome research.

[60]  R. Lenski,et al.  Pervasive joint influence of epistasis and plasticity on mutational effects in Escherichia coli , 2004, Nature Genetics.

[61]  U. Sauer,et al.  Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast , 2005, Genome Biology.

[62]  B. Palsson,et al.  Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth , 2002, Nature.

[63]  A. Wagner Robustness against mutations in genetic networks of yeast , 2000, Nature Genetics.

[64]  Tatsuya Akutsu,et al.  Correlation between structure and temperature in prokaryotic metabolic networks , 2007, BMC Bioinformatics.

[65]  R. Helling,et al.  Why does Escherichia coli have two primary pathways for synthesis of glutamate? , 1994, Journal of bacteriology.

[66]  J. C. Nuño,et al.  Optimal stoichiometric designs of ATP-producing systems as determined by an evolutionary algorithm. , 1999, Journal of theoretical biology.

[67]  J. Krebs,et al.  An introduction to behavioural ecology, 2nd ed. , 1987 .

[68]  J. Krebs,et al.  An introduction to behavioural ecology , 1981 .

[69]  P. Bork,et al.  Variation and evolution of the citric-acid cycle: a genomic perspective. , 1999, Trends in microbiology.

[70]  Ziheng Yang,et al.  Statistical methods for detecting molecular adaptation , 2000, Trends in Ecology & Evolution.

[71]  Jan Ihmels,et al.  Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae , 2004, Nature Biotechnology.

[72]  J. M. Smith,et al.  Optimality theory in evolutionary biology , 1990, Nature.

[73]  Jochen Förster,et al.  Modeling Lactococcus lactis using a genome-scale flux model , 2005, BMC Microbiology.

[74]  C. Francke,et al.  Reconstructing the metabolic network of a bacterium from its genome. , 2005, Trends in microbiology.

[75]  Bas Teusink,et al.  Modelling strategies for the industrial exploitation of lactic acid bacteria , 2006, Nature Reviews Microbiology.

[76]  R. Heinrich,et al.  Mathematical analysis of enzymic reaction systems using optimization principles. , 1991, European journal of biochemistry.

[77]  R. Metcalf Sex Ratios, Parent-Offspring Conflict, and Local Competition for Mates in the Social Wasps Polistes metricus and Polistes variatus , 1980, The American Naturalist.

[78]  R. MacLean,et al.  The tragedy of the commons in microbial populations: insights from theoretical, comparative and experimental studies , 2008, Heredity.

[79]  U. Alon,et al.  Just-in-time transcription program in metabolic pathways , 2004, Nature Genetics.