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Open AccessArticle

A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models

Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany
International Max Planck Research School for Computational Biology and Scientific Computing, Max Planck Institute for Molecular Genetics Berlin, 14195 Berlin, Germany
Institute for Automation Engineering, Otto-von-Guericke-Universität Magdeburg, 39106 Magdeburg, Germany
KU Leuven, Department of Chemical Engineering, 3001 Leuven, Belgium
Authors to whom correspondence should be addressed.
Metabolites 2017, 7(3), 47;
Received: 28 July 2017 / Revised: 30 August 2017 / Accepted: 4 September 2017 / Published: 6 September 2017
(This article belongs to the Special Issue Metabolism and Systems Biology Volume 2)
In this article, we present a protocol for generating a complete (genome-scale) metabolic resource allocation model, as well as a proposal for how to represent such models in the systems biology markup language (SBML). Such models are used to investigate enzyme levels and achievable growth rates in large-scale metabolic networks. Although the idea of metabolic resource allocation studies has been present in the field of systems biology for some years, no guidelines for generating such a model have been published up to now. This paper presents step-by-step instructions for building a (dynamic) resource allocation model, starting with prerequisites such as a genome-scale metabolic reconstruction, through building protein and noncatalytic biomass synthesis reactions and assigning turnover rates for each reaction. In addition, we explain how one can use SBML level 3 in combination with the flux balance constraints and our resource allocation modeling annotation to represent such models. View Full-Text
Keywords: constraint-based modeling; optimality; metabolic networks; SBML constraint-based modeling; optimality; metabolic networks; SBML
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MDPI and ACS Style

Reimers, A.-M.; Lindhorst, H.; Waldherr, S. A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models. Metabolites 2017, 7, 47.

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