Elementary flux modes in a nutshell: properties, calculation and applications.

Elementary flux mode (EFM) analysis allows the unbiased decomposition of a metabolic network into minimal functional units, making it a powerful tool for metabolic engineering. While the use of EFM analysis (EFMA) is still limited by the size of the models it can handle, EFMA has been successfully applied to solve real-world metabolic engineering problems. Here we provide a user-oriented introduction to EFMA, provide examples of recent applications, analyze current research strategies to overcome the computational restrictions and give an overview over current approaches, which aim to identify and calculate only biologically relevant EFMs.

[1]  F. Srienc,et al.  Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism , 2009, Applied Microbiology and Biotechnology.

[2]  Mudita Singhal,et al.  COPASI - a COmplex PAthway SImulator , 2006, Bioinform..

[3]  Ping Ji,et al.  Decomposing flux distributions into elementary flux modes in genome-scale metabolic networks , 2011, Bioinform..

[4]  Stefan Schuster,et al.  YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities , 2005, BMC Bioinformatics.

[5]  R. Carlson,et al.  Fundamental Escherichia coli biochemical pathways for biomass and energy production: Identification of reactions , 2004, Biotechnology and bioengineering.

[6]  F. Srienc,et al.  Minimal Escherichia coli Cell for the Most Efficient Production of Ethanol from Hexoses and Pentoses , 2008, Applied and Environmental Microbiology.

[7]  Friedrich Srienc,et al.  Metabolic networks evolve towards states of maximum entropy production. , 2011, Metabolic engineering.

[8]  Desmond S. Lun,et al.  Analysis of complex metabolic behavior through pathway decomposition , 2011, BMC Systems Biology.

[9]  Komei Fukuda,et al.  Double Description Method Revisited , 1995, Combinatorics and Computer Science.

[10]  Friedrich Srienc,et al.  A Statistical Thermodynamical Interpretation of Metabolism , 2010, Entropy.

[11]  Minoru Kanehisa,et al.  Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis , 2006, BMC Bioinformatics.

[12]  Jörg Stelling,et al.  System-Level Insights into Yeast Metabolism by Thermodynamic Analysis of Elementary Flux Modes , 2012, PLoS Comput. Biol..

[13]  D. Fell,et al.  A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks , 2000, Nature Biotechnology.

[14]  Ronan M. T. Fleming,et al.  Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide. , 2010, EcoSal Plus.

[15]  D. Fell,et al.  Reaction routes in biochemical reaction systems: Algebraic properties, validated calculation procedure and example from nucleotide metabolism , 2002, Journal of mathematical biology.

[16]  Kornberg Hl.  The role and maintenance of the tricarboxylic acid cycle in Escherichia coli. , 1970 .

[17]  R. Carlson,et al.  Design, construction and performance of the most efficient biomass producing E. coli bacterium. , 2006, Metabolic engineering.

[18]  Jörg Stelling,et al.  Accelerating the Computation of Elementary Modes Using Pattern Trees , 2006, WABI.

[19]  Markus J. Herrgård,et al.  Integrating high-throughput and computational data elucidates bacterial networks , 2004, Nature.

[20]  H. Kornberg.  The role and control of the glyoxylate cycle in Escherichia coli. , 1966, The Biochemical journal.

[21]  Minoru Kanehisa,et al.  A quadratic programming approach for decomposing steady-state metabolic flux distributions onto elementary modes , 2005, ECCB/JBI.

[22]  Steffen Klamt,et al.  Computation of elementary modes: a unifying framework and the new binary approach , 2004, BMC Bioinformatics.

[23]  Leen Stougie,et al.  Modes and cuts in metabolic networks: Complexity and algorithms , 2009, Biosyst..

[24]  Angel Rubio,et al.  Do elementary flux modes combine linearly at the "atomic" level? Integrating tracer-based metabolomics data and elementary flux modes , 2011, Biosyst..

[25]  J. Stelling,et al.  Combinatorial Complexity of Pathway Analysis in Metabolic Networks , 2004, Molecular Biology Reports.

[26]  Christian Jungreuthmayer,et al.  regEfmtool: Speeding up elementary flux mode calculation using transcriptional regulatory rules in the form of three-state logic , 2013, Biosyst..

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

[28]  S. Schuster,et al.  ON ELEMENTARY FLUX MODES IN BIOCHEMICAL REACTION SYSTEMS AT STEADY STATE , 1994 .

[29]  Jörg Stelling,et al.  Large-scale computation of elementary flux modes with bit pattern trees , 2008, Bioinform..

[30]  Christoph Wittmann,et al.  Flux Design: In silico design of cell factories based on correlation of pathway fluxes to desired properties , 2009, BMC Systems Biology.

[31]  C. Trinh,et al.  Elementary mode analysis: a useful metabolic pathway analysis tool for reprograming microbial metabolic pathways. , 2012, Sub-cellular biochemistry.

[32]  D. Fell,et al.  Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. , 1999, Trends in biotechnology.

[33]  Wynand S. Verwoerd.  A new computational method to split large biochemical networks into coherent subnets , 2010, BMC Systems Biology.

[34]  B. Palsson,et al.  Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. , 2000, Journal of theoretical biology.

[35]  S. Schuster,et al.  Structural robustness of metabolic networks with respect to multiple knockouts. , 2008, Journal of theoretical biology.

[36]  Cong T. Trinh,et al.  Redesigning Escherichia coli Metabolism for Anaerobic Production of Isobutanol , 2011, Applied and Environmental Microbiology.

[37]  Stefan Schuster,et al.  Detecting and investigating substrate cycles in a genome‐scale human metabolic network , 2012, The FEBS journal.

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

[39]  Daniel Boley,et al.  Parallelization of Nullspace Algorithm for the computation of metabolic pathways , 2011, Parallel Comput..

[40]  Angel Rubio,et al.  Computing the shortest elementary flux modes in genome-scale metabolic networks , 2009, Bioinform..

[41]  V. Hatzimanikatis,et al.  Thermodynamics-based metabolic flux analysis. , 2007, Biophysical journal.

[42]  S. Schuster,et al.  Can the whole be less than the sum of its parts? Pathway analysis in genome-scale metabolic networks using elementary flux patterns. , 2009, Genome research.

[43]  Christian Jungreuthmayer,et al.  Designing optimal cell factories: integer programming couples elementary mode analysis with regulation , 2012, BMC Systems Biology.

[44]  Thomas Pfeiffer,et al.  Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae , 2002, Bioinform..

[45]  S Klamt,et al.  Algorithmic approaches for computing elementary modes in large biochemical reaction networks. , 2005, Systems biology.

[46]  Leen Stougie,et al.  A note on the complexity of finding and enumerating elementary modes , 2010, Biosyst..

[47]  H. Kornberg,et al.  The role and maintenance of the tricarboxylic acid cycle in Escherichia coli. , 1970, Biochemical Society symposium.

[48]  Stefan Schuster,et al.  Systems biology Metatool 5.0: fast and flexible elementary modes analysis , 2006 .

[49]  Friedrich Srienc,et al.  Predicting the adaptive evolution of Thermoanaerobacterium saccharolyticum. , 2012, Journal of biotechnology.

[50]  C. Wittmann,et al.  From zero to hero--design-based systems metabolic engineering of Corynebacterium glutamicum for L-lysine production. , 2011, Metabolic engineering.

[51]  Andreas Hoppe,et al.  Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks , 2007, BMC Systems Biology.

[52]  Steffen Klamt,et al.  A methodology for the structural and functional analysis of signaling and regulatory networks , 2006, BMC Bioinformatics.

[53]  F. Srienc,et al.  Trace: Tennessee Research and Creative Exchange Metabolic Engineering of Escherichia Coli for Efficient Conversion of Glycerol into Ethanol , 2022 .

[54]  Christoph Kaleta,et al.  Computing Elementary Flux Modes in Genome-scale Metabolic Networks , 2009, GCB.

[55]  S. Panke,et al.  Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data , 2006, Molecular systems biology.

[56]  Marie Beurton-Aimar,et al.  ACoM: A classification method for elementary flux modes based on motif finding , 2011, Biosyst..

[57]  B. Palsson,et al.  Transcriptional regulation in constraints-based metabolic models of Escherichia coli Covert , 2002 .

[58]  Eugénio C. Ferreira,et al.  Random sampling of elementary flux modes in large-scale metabolic networks , 2012, Bioinform..

[59]  Daniel Boley,et al.  On Algebraic Properties of Extreme Pathways in Metabolic Networks , 2010, J. Comput. Biol..

[60]  Friedrich Srienc,et al.  Rational design and construction of an efficient E. coli for production of diapolycopendioic acid. , 2010, Metabolic engineering.

[61]  Jibin Sun,et al.  Development of thermodynamic optimum searching (TOS) to improve the prediction accuracy of flux balance analysis , 2013, Biotechnology and bioengineering.

[62]  Steffen Klamt,et al.  Computing complex metabolic intervention strategies using constrained minimal cut sets. , 2011, Metabolic engineering.

[63]  Miguel Rocha,et al.  OptFlux: an open-source software platform for in silico metabolic engineering , 2010, BMC Systems Biology.

[64]  R. Carlson,et al.  Fundamental Escherichia coli biochemical pathways for biomass and energy production: creation of overall flux states , 2004, Biotechnology and bioengineering.