Avoiding the enumeration of infeasible elementary flux modes by including transcriptional regulatory rules in the enumeration process saves computational costs

PLoS ONE

Volumn 10, Issue 6, 2015, Pages

  Jungreuthmayer, Christian ^a,b   Ruckerbauer, David E ^a,b   Gerstl, Matthias P ^a,b   Hanscho, Michael ^a,b   Zanghellini, Jürgen ^a,b  

^a AUSTRIAN CENTRE OF INDUSTRIAL BIOTECHNOLOGY   (Austria)

^b UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANALYTIC METHOD; ARTICLE; CALCULATION; COMPUTER ANALYSIS; COMPUTER PROGRAM; ELEMENTARY FLUX MODE; GENE CONTROL; GENE REGULATORY NETWORK; GENOME; METABOLISM; PREDICTIVE VALIDITY; PROBLEM SOLVING; PROCESS OPTIMIZATION; TRANSCRIPTION REGULATION; TRANSCRIPTIONAL REGULATORY NETWORK; BIOLOGICAL MODEL; BIOLOGY; GENE EXPRESSION REGULATION; GENETIC TRANSCRIPTION; PROCEDURES;

COMPUTATIONAL BIOLOGY; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORKS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; TRANSCRIPTION, GENETIC;

EID: 84939204410     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0129840     Document Type: Article

References (52)

1. Schuster S, Fell DA, Dandekar T (2000) A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat Biotech 18:326-332.
2. Schuster S, Dandekar T, Fell DA (1999) Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends in Biotechnology 17:53-60. doi: 10.1016/S0167-7799 (98) 01290-6 PMID: 10087604
3. Zanghellini J, Ruckerbauer DE, Hanscho M, Jungreuthmayer C (2013) Elementary flux modes in a nutshell: Properties, calculation and applications. Biotechnology Journal 8:1009-1016. doi: 10.1002/biot. 201200269 PMID: 23788432
4. Klamt S, Stelling J (2002) Combinatorial complexity of pathway analysis in metabolic networks. Molecular Biology Reports 29:233-236. doi: 10.1023/A:1020394300385 PMID: 12241063
5. Gagneur J, Klamt S (2004) Computation of elementary modes: a unifying framework and the new binary approach. BMC Bioinformatics 5:175. doi: 10.1186/1471-2105-5-175 PMID: 15527509
6. Terzer M, Stelling J (2008) Large-scale computation of elementary flux modes with bit pattern trees. Bioinformatics 24:2229-2235. doi: 10.1093/bioinformatics/btn401 PMID: 18676417
7. Jevremovica D, Trinh CT, Srienc F, Sosad CP, Daniel B (2011) Parallelization of nullspace algorithm for the computation of metabolic pathways. Parallel Computing 37:261-278.
8. Hunt KA, Folsom JP, Taffs RL, Carlson RP (2014) Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition. Bioinformatics 30:1569-78. doi: 10.1093/bioinformatics/btu021 PMID: 24497502
9. Von Kamp A, Schuster S (2006) Metatool 5.0: fast and flexible elementary mode analysis. Bioinformatics Application Note 22:1930-1931.
10. Klamt S, Saez-Rodriguez J, Gilles ED (2007) Structural and functional analysis of cellular networks with cellnetanalyzer. BMC Systems Biology 1:2. doi: 10.1186/1752-0509-1-2 PMID: 17408509
11. Trinh CT, Thompson RA (2012) Elementary mode analysis: A useful metabolic pathway analysis tool for reprograming microbial metabolic pathways. In: Wang X, Chen J, Quinn P, editors, Reprogramming Microbial Metabolic Pathways, Dordrecht: Springer Netherlands, volume 64. pp. 21-42.
12. Open Source Initiative (2012) The BSD License. http://www.opensource.org/licenses/BSD-2-Clause.
13. ETH Zurich, Computational Systems Biology Group (2012) efmtool-Elementary Flux Mode Tool. http://www.csb.ethz.ch/tools/efmtool.
14. Schlitt T (2013) Approaches to modeling gene regulatory networks: A gentle introduction. In Silico Systems Biology, Methods in Molecular Biology 1021:13-35.
15. Saadatpour A, Albert R (2013) Boolean modeling of biological networks: A methodology tutorial. Methods 62:3-12. doi: 10.1016/j.ymeth.2012.10.012 PMID: 23142247
16. Kauffman S (1969) Homeostasis and differentiation in random genetic control networks. Nature 224:177-178. doi: 10.1038/224177a0 PMID: 5343519
17. Orth JD, Fleming RMT, Palsson BO (2010) Reconstruction and use of microbial metabolic networks: the core escherichia coli metabolic model as an educational guide. EcoSal Plus.
18. Wang RS, Saadatpour A, Albert R (2012) Boolean modeling in systems biology: an overview of methodology and applications. Physical Biology 9(5):055001. doi: 10.1088/1478-3975/9/5/055001 PMID: 23011283
19. Fukuda K, Prodon A (1996) Double description method revisited. Combinatorics and Computer Science 1120:91-111.
20. Larhlimi A, David L, Selbig J, Bockmayr A (2012) F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks. BMC Bioinformatics 13:57. doi: 10.1186/1471-2105-13-57 PMID: 22524245
21. Zolotykh NY (2012) New modification of the double describtion method for contstructing the skeleton of a polyhedral cone. Computational Mathematics and Mathematical Physics 52:146-156. doi: 10.1134/S0965542512010162
22. Jensen PA, Lutz KA, Papin JA (2011) TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks. BMC Systems Biology 5:147. doi: 10.1186/1752-0509-5-147 PMID: 21943338
23. Jungreuthmayer C, Ruckerbauer DE, Zanghellini J (2013) regEfmtool: speeding up elementary flux mode calculation using transcriptional regulatory rules in the form of a three-state logic. Biosystems 113(1):37-39. doi: 10.1016/j.biosystems.2013.04.002 PMID: 23664840
24. University of California, San Diego, Systems Biology Research Group (2012) The Core E. ColiModel. http://gcrg.ucsd.edu/Downloads/EcoliCore.
25. Jol SJ, Kümmel A, Terzer M, Stelling J, Matthias H (2012) System-level insights into yeast metabolism by thermodynamics analysis of elementary flux modes. PLoSComputBiol 8(3):1-9.
26. Van Den Berg MA, De Jong-Gubbels P, Steensma HY (1998) Transient mRNA responses in chemostat cultures as a method of defining putative regulatory elements: Application to genes involved in saccaromyces cerevisiae acetyl-coeenzyme a metabolism. Yeast 14:1089-1104. doi: 10.1002/(SICI) 1097-0061 (19980915) 14:12%3C1089::AID-YEA312%3E3.0. CO;2-K PMID: 9778795
27. Terzer M (2009) Large scale methods to enumerate extreme rays and elementary modes. Ph. D. thesis, ETH Zurich.
28. Palmieri L, Lasorsa FM, Vozza A, Agrimi G, Fiermonte G, Runswick MJ, et al. (2000) Identification and functions of new transporters in yeast mitochondria. Biochimica et Biophysica Acta (BBA)-Bioenergetics 1459:363-369. doi: 10.1016/S0005-2728 (00) 00173-0
29. Van Den Berg MA, Steensma HY (1995) ACS2, a saccharomyces cerevisiae gene encoding acetylcoenzyme a synthetase, essential for growth on glucose. European Journal of Biochemistry 231:704-713. doi: 10.1111/j.1432-1033.1995.tb20751.x PMID: 7649171
30. Påhlman AK, Granath K, Ansell R, Hohmann S, Adler L (2001) The yeast glycerol 3-phosphatases gpp1p and gpp2p are required for glycerol biosynthesis and differentially involved in the cellular responses to osmotic, anaerobic, and oxidative stress. Journal of Biological Chemistry 276:3555-3563. doi: 10.1074/jbc. M007164200 PMID: 11058591
31. Mendoza L, Thieffry D, Alvarez-Buylla ER (1999) Genetic control of ower morphogenesis in arabidopsis thaliana: a logical analysis. Bioinformatics 15:593-606. doi: 10.1093/bioinformatics/15.7.593 PMID: 10487867
32. Albert R, Othmer HG (2003) The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in drosophilia melanogaster. Journal of TheoreticalBiology 223:1-18.
33. Herrgård MH, Lee BS, Portnoy V, Palsson BO (2006) Integrated analysis of regulatory and metabolic network reveals novel regulator mechanismn saccaromyces cerevisiae. Genome Research 16(5):627-635. doi: 10.1101/gr.4083206 PMID: 16606697
34. Christensen TS, Soberanode Oliveira AP, Nielsen J (2009) Reconstruction and logical modeling of glucose repression signaling pathways in saccaromyces cerevisiae. BMC Systems Biology 3:7:1-15.
35. Meister M, Saum S, Alber BE, Fuchs G (2005) L-malyl-coenzyme a/beta-methylmalyl-coenzyme a lyase is involved in acetate assimilation of the isocitrate lyase-negative bacterium rhodobacter capsulatus. Journal of Bacteriology 187:1415-1425. doi: 10.1128/JB.187.4.1415-1425.2005 PMID: 15687206
36. Han L, Reynolds KA (1997) A novel alternate anaplerotic pathway to the glyoxylate cycle in streptomycetes. Journal of Bacteriology 179:5157-5164. PMID: 9260959
37. Claassen PAM, Zehnder AJB (1986) Isocitrate lyase activity in thiobacillus versutus grown anaerobically on acetate and nitrate. Journal of General Microbiology 132:3179-3185.
38. Thomas R, D'Ari R (1990) Biological Feedback. Boca Raton: CRC Press.
39. Shlomi T, Eisenberg Y, Sharan R, Ruppin E (2007) A genome-scale computational study of the interplay between transcriptional regulation and metabolism. Molecular System Biology 3:101.
40. Kaleta C, De Figueiredo LF, Schuster S (2009) Can the whole be less than the sum of its parts? pathway analysis in genome-scale metabolic networks using elementary flux patterns. Genome Res 19:1872-1873. doi: 10.1101/gr.090639.108 PMID: 19541909
41. Kaleta C, De Figueiredo LF, Behre J, Schuster S (2009) EFMEvolver: computing elementary flux modes in genome-scale metabolic networks. In: Lecture Notes in Informatics (LNI) P-157-Proceedings of the German Conference on Bioinformatics.. Bonn: Gesellschaftfr Informatik, pp. 179-190.
42. Machado D, Soons Z, Patil KR, Ferreira EC, Rocha I (2012) Random sampling of elementary flux modes in large-scale metabolic networks. Bioinformatics 28:18:I515-I521. doi: 10.1093/bioinformatics/bts401 PMID: 22962475
43. Tabe-Bordbar S, Marashi SA (2013) Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism. Biotechnol Lett 35:12:2039-2044. doi: 10.1007/s10529-013-1328-x PMID: 24078125
44. Pey J, Planes FJ (2014) Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks. Systems Biology in press: 1-7.
45. Schwartz JM, Kanehisa M (2006) Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis. BMC Bioinformatics 7:1-20. doi: 10.1186/1471-2105-7-1
46. Jungreuthmayer C, Zanghellini J (2012) Designing optimal cell factories: integer programming couples elementary mode analysis with regulation. BMC Systems Biology 6:103. doi: 10.1186/1752-0509-6-103 PMID: 22898474
47. Hädicke O, Klamt S (2011) Computing complex metabolic intervention strategies using constrained minimal cut sets. Metabolic Engineering 13:204-213. doi: 10.1016/j.ymben. 2010.12.004 PMID: 21147248
48. Von Kamp A, Klamt S (2014) Enumeration of smallest intervention strategies in genome-scale metabolic networks. PLoSComputBiol 10:e1003378. doi: 10.1371/journal.pcbi.1003378 PMID: 24391481
49. Jungreuthmayer C, Beurton-Aimar M, Zanghellini J (2013) Fast computation of minimal cut sets in metabolic networks with a berge algorithm that utilizes binary bit pattern trees. IEEE/ACM Transactions on Computational Biology and Bioinformatics 10:1329-33. doi: 10.1109/TCBB.2013.116 PMID: 24062540
50. Jungreuthmayer C, Nair G, Klamt S, Zanghellini J (2013) Comparison and improvement of algorithms for computing minimal cut sets. BMC Bioinformatics 14:318. doi: 10.1186/1471-2105-14-318 PMID: 24191903
51. Covert MW, Knight EM, Reed JL, Herrgard MJ, Palsson BO (2004) Integrating high-throughput and computational data elucidates bacterial networks. Nature 429:92-96. doi: 10.1038/nature02456 PMID: 15129285
52. Chandrasekaran S, Price ND (2010) Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in escherichia coli and mycobacterium tuberculosis. Proceedings of the National Academy of Sciences.