A mixed-integer optimization framework for the synthesis and analysis of regulatory networks
Motivation: A novel mixed-integer optimization framework is proposed for the design and analysis of regulatory networks. The model combines gene expression data and prior biological knowledge regarding the potential for regulatory interactions between genes and their corresponding transcription factors. The formalism provides significant advantages over available modeling methodologies in that the complexity of the regulatory network can be explicitly taken into account, multiple alternative structures can be systematically generated and finally robust and biological significant regulators can be rigorously identified. The original non-convex mixed integer reformulation is appropriately linearized and the resulting MILP is effectively optimized using standard solvers. The versatility is demonstrated using gene expression and binding data from an E. coli case study during transition from glucose to acetate as the sole carbon source.
KeywordsBioinformatics Mixed integer linear optimization Gene regulation
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- Biegler, L.T., Grossmann, I.E. et al.: Systematic Methods of Chemical Process Design. Prentice Hall (1997)Google Scholar
- Brooke, A., Kendrick, D. et al.: GAMS A user’s guide. GAMS Development Corporation (2004)Google Scholar
- Calvo, J.M., Matthews, R.G.: The leucine-responsive regulatory protein, a global regulator of metabolism in Escherichia coli. Microbiol. Rev. 58(3), 466–490 (1994)Google Scholar
- DiRusso, C.C., Heimert, T.L. et al.: Characterization of FadR, a global transcriptional regulator of fatty acid metabolism in Escherichia coli. Interaction with the fadB promoter is prevented by long chain fatty acyl coenzyme A. J. Biol. Chem. 267(12), 8685–8691 (1992)Google Scholar
- Drazinic, C.M., Smerage, J.B. et al.: Activation mechanism of the multifunctional transcription factor repressor-activator protein 1 (Rap1p). Mol. Cell. Biol. 16(6), 3187–3196 (1996)Google Scholar
- Gervais, F.G., Phoenix, P. et al.: The rcsB gene, a positive regulator of colanic acid biosynthesis in Escherichia coli, is also an activator of ftsZ expression. J. Bacteriol. 174(12), 3964–3971 (1992)Google Scholar
- Landini, P., Hajec, L.I. et al.: Structure and transcriptional regulation of the Escherichia coli adaptive response gene aidB. J. Bacteriol. 176(21), 6583–6589 (1994)Google Scholar
- Lawley, B., Pittard, A.J.: Regulation of aroL expression by TyrR protein and Trp repressor in Escherichia coli K-12. J. Bacteriol. 176(22), 6921–6930 (1994)Google Scholar
- Lawley, B., Fujita, N. et al.: The TyrR protein of Escherichia coli is a class I transcription activator. J. Bacteriol. 177(1), 238–241 (1995)Google Scholar
- Rolfes, R.J., Zalkin, H.: Escherichia coli gene purR encoding a repressor protein for purine nucleotide synthesis. Cloning, nucleotide sequence, and interaction with the purF operator. J. Biol. Chem. 263(36), 19653–19661 (1988)Google Scholar
- Savageau, M.A.: Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology. Addison-Weslet, Reading (1976)Google Scholar
- Wang, X.D., de Boer, P.A. et al.: A factor that positively regulates cell division by activating transcription of the major cluster of essential cell division genes of Escherichia coli. Embo. J. 10(11), 3363–3372 (1991)Google Scholar