Abstract
Mathematical models of the cellular metabolism have become an essential tool for the optimization of biotechnological processes. They help to obtain a systemic understanding of the metabolic processes in the used microorganisms and to find suitable genetic modifications maximizing the production performance. In particular, methods of stoichiometric and constraint-based modeling are frequently used in the context of metabolic and bioprocess engineering. Since metabolic networks can be complex and comprise hundreds or even thousands of metabolites and reactions, dedicated software tools are required for an efficient analysis. One such software suite is CellNetAnalyzer, a MATLAB package providing, among others, various methods for analyzing stoichiometric and constraint-based metabolic models. CellNetAnalyzer can be used via command-line based operations or via a graphical user interface with embedded network visualizations. Herein we will present key functionalities of CellNetAnalyzer for applications in biotechnology and metabolic engineering and thereby review constraint-based modeling techniques such as metabolic flux analysis, flux balance analysis, flux variability analysis, metabolic pathway analysis (elementary flux modes) and methods for computational strain design.
Highlights
Industrial biotechnology uses cells or parts of cells for the production of chemicals, biofuels, pharmaceuticals, nutraceuticals, enzymes or other industrially relevant products
The COBRA toolbox for MATLAB provides a comprehensive set of functions for constraint-based modeling. This includes several methods for computational strain design based on bi-level Mixed Integer Linear Programming problems (bi-level MILPs (Maia et al, 2015; Machado et al, 2015; Zomorrodi et al, 2012)); those methods are not supported by CellNetAnalyzer
All functions have to be started from command line and methods for metabolic pathway analysis are not available
Summary
Industrial (white) biotechnology uses cells or parts of cells for the production of chemicals, biofuels, pharmaceuticals, nutraceuticals, enzymes or other industrially relevant products. Methods of stoichiometric and constraint-based modeling have been successfully applied in metabolic and bioprocess engineering (Gutierrez and Lewis, 2015; King et al, 2015; Maia et al, 2015; Simeonidis and Price, 2015; Kim et al, 2015; Machado and Herrgard, 2015) These methods include, for example, metabolic flux analysis (MFA; characterization of metabolic fluxes under controlled conditions), flux balance analysis (FBA; analysis of optimal flux distributions), flux variability analysis (FVA; analysis of feasible ranges of metabolic fluxes), metabolic pathway analysis (discovery and analysis of metabolic pathways) and methods for computational strain design (computation of metabolic engineering strategies optimizing the production behavior of the organism). We will present key functionalities of CellNetAnalyzer for applications in biotechnology and metabolic engineering and thereby briefly review constraint-based modeling techniques
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