Constraining flux balance analysis with genome-scale data

Lee, Dave and Smallbone, Kieran and Dunn, Warwick B. and Murabito, Ettore and Winder, Catherine L. and Kell, Douglas B. and Mendes, Pedro and Swainston, Neil (2012) Constraining flux balance analysis with genome-scale data. [MIMS Preprint]

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Abstract

Background Constraint-based analysis of genome-scale metabolic models typically relies upon maximisation of a cellular objective function such as the rate or efficiency of biomass production. Whilst this assumption may be valid in the case of microorganisms growing under certain conditions, it is likely invalid in general, and especially for multicellular organism such as mammals, where cellular objectives differ greatly both between and within cell types. Moreover, for the purposes of biotechnological applications, it is normally the flux to a specific metabolite or product that is of interest rather than the rate of production of biomass per se. Results An alternative objective function is presented, that is based upon maximising the correlation between experimentally measured absolute gene expression data and predicted internal reaction fluxes. Using quantitative transcriptomics data acquired from Saccharomyces cerevisiae cultures under two growth conditions, the method outperforms traditional approaches for predicting experimentally measured metabolic flux that are reliant upon maximization of the rate of biomass production. Conclusion Due to its improved prediction of experimentally measured metabolic fluxes, and of its lack of a requirement for knowledge of the biomass composition of the organism under the conditions of interest, the approach is likely to be of rather general utility. The method has been shown to reliably predict fluxes in single cellular systems, and is likely to be also to generate condition- and tissue-specific flux predictions in multicellular organisms.

Item Type:	MIMS Preprint
Uncontrolled Keywords:	Flux balance analysis, metabolic flux, metabolic networks, transcriptomics, RNA-seq, exometabolomics
Subjects:	MSC 2010, the AMS's Mathematics Subject Classification > 92 Biology and other natural sciences
Depositing User:	Dr Kieran Smallbone
Date Deposited:	12 Jan 2012
Last Modified:	20 Oct 2017 14:13
URI:	https://eprints.maths.manchester.ac.uk/id/eprint/1754

Available Versions of this Item

• Constraining flux balance analysis with genome-scale data. (deposited 12 Jan 2012) [Currently Displayed]
  • Improving metabolic flux predictions using absolute gene expression data. (deposited 17 Jun 2012)
    • Improving metabolic flux predictions using absolute gene expression data. (deposited 04 Dec 2012)

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