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Issue No.04 - July-Aug. (2013 vol.10)
pp: 984-993
Onur Seref , Dept. of Bus. Inf. Technol., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
J. Paul Brooks , Dept. of Stat. Sci. & Oper. Res., Virginia Commonwealth Univ., Richmond, VA, USA
Stephen S. Fong , Dept. of Chem. & Life Sci. Eng., Virginia Commonwealth Univ., Richmond, VA, USA
ABSTRACT
Genome-scale reconstructions are often used for studying relationships between fundamental components of a metabolic system. In this study, we develop a novel computational method for analyzing predicted flux distributions for metabolic reconstructions. Because chemical reactions may have multiple reactants and products, a directed hypergraph where hyperarcs may have multiple tail vertices and head vertices is a more appropriate representation of the metabolic network than a conventional network. We use this view to represent predicted flux distributions by maximum generalized flows on hypergraphs. We then demonstrate that the generalized hyperflow problem may be transformed to an equivalent network flow problem with side constraints. This transformation allows a flux to be decomposed into chains of reactions. Subsequent analysis of these chains helps to characterize active pathways in a flux distribution. Such characterizations facilitate comparisons of flux distributions for different environmental conditions. The proposed method is applied to compare predicted flux distributions for Salmonella typhimurium to study changes in metabolism that cause enhanced virulence during a space flight. The differences between flux distributions corresponding to normal and enhanced virulence states confirm previous observations concerning infection mechanisms and suggest new pathways for exploration.
INDEX TERMS
network theory (graphs), biochemistry, cellular biophysics, chemical reactions, directed graphs, genomics, microorganisms, infection mechanism, flux distribution decomposition, metabolic pathway, genome-scale reconstruction, computational method, metabolic reconstructions, chemical reactions, directed hypergraph, metabolic network, generalized hyperflow problem, equivalent network flow problem, reaction chain, environmental conditions, Salmonella typhimurium, space flight, virulence states, Biochemistry, Bioinformatics, Vectors, IEEE transactions, Computational biology, Organisms, Biomass, flux balance analysis, Hypergraphs, maximum generalized hyperflow, flow decomposition, metabolic reconstruction
CITATION
Onur Seref, J. Paul Brooks, Stephen S. Fong, "Decomposition of Flux Distributions into Metabolic Pathways", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.10, no. 4, pp. 984-993, July-Aug. 2013, doi:10.1109/TCBB.2013.115
REFERENCES
[1] R. Ahuja, T.L. Magnanti, and J.B. Orlin, Network Flows: Theory, Algorithms, and Applications. Prentice Hall, 1993.
[2] E. Almaas, B. Kovács, T. Vicsek, Z.N. Oltvai, and A.-L Barabási, "Global Organization of Metabolic Fluxes in the Bacterium Escherichia coli," vol. 427, pp. 839-843, 2004.
[3] C.L. Barrett, M.J. Herrgard, and B.O. Palsson, "Decomposing Complex Reaction Networks Using Random Sampling, Principal Component Analysis and Basis Rotation," BMC Systems Biology, vol. 3, article 30, 2009.
[4] M.S. Bazaraa, J.J. Jarvis, and H.D. Sherali, Linear Programming and Network Flows, fourth ed., Wiley, 2010.
[5] D. Becker, M. Selbach, C. Rollenhagen, M. Ballmaier, T.F. Meyer, M. Mann, and D. Bumann, "Robust Salmonella Metabolism Limits Possibilities for New Antimicrobials," Nature, vol. 440, no. 7082, pp. 303-307, 2006.
[6] D. Bumann, "System-Level Analysis of Salmonella Metabolism during Infection," Current Opinion in Microbiology, vol. 12, no. 5, pp. 559-567, 2009.
[7] R. Cambini, G. Gallo, and M.G. Scutellà, "Flows on Hypergraphs," Math. Programming, vol. 78, no. 2, pp. 195-217, 1997.
[8] M. Dauner and U. Sauer, "Stoichiometric Growth Model for Riboflavin-Producing Bacillus subtilis," Biotechnology and Bioeng., vol. 76, no. 2, pp. 132-143, 2001.
[9] R. Durbin, S.R. Eddy, A. Krogh, and G. Mitchison, Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge Univ. Press, 1998.
[10] A.M. Feist and B.O. Palsson, "The Growing Scope of Applications of Genome-Scale Metabolic Reconstructions Using Escherichia coli," Nature biotechnology, vol. 26, no. 6, pp. 659-667, 2008.
[11] S.S. Fong and B.O. Palsson, "Metabolic Gene-Deletion Strains of Escherichia coli Evolve to Computationally Predicted Growth Phenotypes," Nature Genetics, vol. 36, no. 10, pp. 1056-1058, 2004.
[12] C.M. Gowen and S.S. Fong, "Linking RNA Measurements and Proteomics with Genome-Scale Models" Systems Metabolic Engineering: Methods and Protocols, vol. 985, H.S. Alper, ed., Springer, pp. 429-445, 2013.
[13] S. Klamt, U.-U. Hauw, and F. Theis, "Hypergraphs and Cellular Networks," PLoS Computational Biology, vol. 5, no. 5,article e1000385, 2009.
[14] R.G. Jeroslow, K. Martin, R.L. Rardin, and J. Wang, "Gainfree Leontif Substitution Flow Problems," Math. Programming, vol. 57, no. 1, pp. 375-414, 1992.
[15] V. Lacroix, L. Cottret, P. Theébault, and M.-F. Sagot, "An Introduction to Metabolic Networks and Their Structural Analysis," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 8, no. 3, pp. 732-747, May/June 2011.
[16] C.T. Lopes, M. Franz, F. Kazi, S.L. Donaldson, Q. Morris, and G.D. Bader, "Cytoscape Web: An Interactive Web-Based Network Browser," Bioinformatics, vol. 26, no. 18, pp. 2347-2348, 2010.
[17] R. Mahadevan and C.H. Schilling, "The Effects of Alternate Optimal Solutions in Constraint-Based Genome-Scale Metabolic Models," Metabolic Eng., vol. 5, pp. 264-276, 2003.
[18] J.E. McDermott, H. Yoon, E.S. Nakayasu, T.O. Metz, D.R. Hyduke, A.S. Kidwai, B.O. Palsson, J.N. Adkins, and F. Heffron, "Technologies and Approaches to Elucidate and Model the Virulence Program of Salmonella," Frontiers in Microbiology, vol. 2, article 121, 2011.
[19] S.I. Miller, A.M. Kukral, and J.J. Mekalanos, "A Two-Component Regulatory System (PhoP PhoQ) Controls Salmonella typhimurium Virulence," Proc. Nat'l Academy of Sciences USA, vol. 86, no. 13, pp. 5054-5058, 1989.
[20] J.D. Orth, I. Thiele, and B.O. Palsson, "What Is Flux Balance Analysis?" Nature Biotechnology, vol. 28, no. 3, pp. 245-248, 2010.
[21] J.A. Papin, N.D. Price, J.S. Edwards, and B.O. Palsson, "The Genome-Scale Metabolic Extreme Pathway Structure in Haemophilus influenzae Shows Significant Network Redundancy," J. Theoretical Biology, vol. 215, pp. 67-82, 2002.
[22] J.M. Park, T.Y. Kim, and S.Y. Lee, "Constraint-Based Genome-Scale Metabolic Simulation for Systems Metabolic Engineering," Biotechnology Advances, vol. 27, no. 6, pp. 979-988, 2009.
[23] N.D. Price, J.L. Reed, J.A. Papin, I. Famili, and B.O. Palsson, "Analysis of Metabolic Capabilities Using Singular Value Decomposition of Extreme Pathway Matrices," Biophysical J., vol. 84, pp. 794-804, 2003.
[24] L.R. Prost, M.E. Daley, M.W. Bader, R.E. Klevit, and S.I. Miller, "The PhoQ Histidine Kinases of Salmonella and Pseudomonas spp. Are Structurally and Functionally Different: Evidence that pH and Antimicrobial Peptide Sensing Contribute to Mammalian Pathogensis," Molecular Microbiology, vol. 69, no. 2, pp. 503-519, 2008.
[25] A. Raghunathan, J. Reed, S. Shin, B. Palsson, and S. Daefler, "Constraint-Based Analysis of Metabolic Capacity of Salmonella typhimurium during Host-Pathogen Interaction," BMC Systems Biology, vol. 3, article 38, 2009.
[26] A. Samal, "Conservation of High-Flux Backbone in Alternate Optimal and Near-Optimal Flux Distributions of Metabolic Networks," Stems and Synthetic Biology , vol. 2, pp. 83-93, 2008.
[27] C.H. Schilling, D. Letscher, and B.O. Palsson, "Theory for the Systemic Definition of Metabolic Pathways and Their Use in Interpreting Metabolic Function from a Pathway-Oriented Perspective," J. Theoretical Biology, vol. 203, pp. 229-248, 2000.
[28] A. Schrijver, Combinatorial Optimization. Springer, 2003.
[29] O. Şeref, Y.-J. Fan, and W.A. Chaovalitwongse, "Mathematical Programming Formulations and Algorithms for Discrete $k$ -Median Clustering of Time Series Data," INFORMS J. Computing, doi: 10.1287/ijoc.2013.0554, 2013.
[30] T. Shlomi, M.N. Cabili, M.J. Herrgard, B.O. Palsson, and E. Ruppin, "Network-Based Prediction of Human Tissue-Specific Metabolism," Nature Biotechnology, vol. 26, no. 9, pp. 1003-1010, 2008.
[31] D.R. Sizemore, E.A. Warner, J.A. Lawrence, L.J. Thomas, K.L. Roland, and K.P. Killeen, "Construction and Screening of Attenuated $\Delta$phoP/Q Salmonella typhimurium Vectored Plague Vaccine Candidates," Human Vaccines & Immunotherapeutics, vol. 8, no. 3, pp. 371-383, 2012.
[32] B. Song, E. Büyüktahtakin, S. Ranka, and T. Kahveci, "Manipulating the Steady State of Metabolic Pathways," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 8, no. 3, pp. 732-747, May 2011.
[33] Y.T. Tang, R. Gao, J.J. Havranek, E.A. Groisman, A.M. Stock, and G.R. Marshall, "Inhibition of Bacterial Virulence: Drug-Like Molecules Targeting the Salmonella enterica PhoP Response Regulator," Chemical Biology & Drug Design, vol. 79, no. 6, pp. 1007-1017, 2012.
[34] R. Urbanczik, "Enumerating Constrained Elementary Flux Vectors of Metabolic Networks," IET System Biology, vol. 1, no. 5, pp. 274-279, 2007.
[35] S.J. Wiback, I. Famili, H.J. Greenberg, and B.O. Palsson, "Monte Carlo Sampling Can Be Used to Determine the Size and Shape of the Steady-State Flux Space," J. Theoretical Biology, vol. 228, pp. 427-447, 2004.
[36] J.W. Wilson et al., "Space Flight Alters Bacterial Gene Expression and Virulence and Reveals a Role for Global Regulator Hfq," Proc. Nat'l Academy of Sciences USA, vol 104, no. 41, pp. 16299-16304, 2007.
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