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MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

pmid: 23272111
pmc: PMC3522732
Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads.
- University of Groningen Netherlands
- University of Glasgow United Kingdom
- Virginia Commonwealth University United States
- University of Surrey United Kingdom
- University of Salford United Kingdom
GENE-CLUSTER, NETWORK ANALYSIS, CLAVULANIC ACID, Science, HETEROLOGOUS EXPRESSION, QUANTITATIVE PREDICTION, CONSTRAINT-BASED MODELS, Models, Biological, CELLULAR-METABOLISM, Species Specificity, STREPTOMYCES-COELICOLOR, Biomass, Genome, Computers, Q, R, Computational Biology, Gene Expression Regulation, Bacterial, IN-SILICO, Streptomyces, 004, Actinobacteria, Medicine, COBRA TOOLBOX, Algorithms, Genome, Bacterial, Metabolic Networks and Pathways, Software, Research Article
GENE-CLUSTER, NETWORK ANALYSIS, CLAVULANIC ACID, Science, HETEROLOGOUS EXPRESSION, QUANTITATIVE PREDICTION, CONSTRAINT-BASED MODELS, Models, Biological, CELLULAR-METABOLISM, Species Specificity, STREPTOMYCES-COELICOLOR, Biomass, Genome, Computers, Q, R, Computational Biology, Gene Expression Regulation, Bacterial, IN-SILICO, Streptomyces, 004, Actinobacteria, Medicine, COBRA TOOLBOX, Algorithms, Genome, Bacterial, Metabolic Networks and Pathways, Software, Research Article
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