Category Cross-Omics>Agent-Based Modeling/Simulation/Tools and Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools

Abstract OptFlux is an open-source software platform for in silico metabolic engineering.

It is one of the first tools to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing meta-heuristics or the previously proposed OptKnock algorithm.

OptFlux allows the use of stoichiometric metabolic models for:

1) Phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis (FBA), Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes;

2) Metabolic Flux Analysis (MFA), computing the admissible flux space given a set of measured fluxes; and

3) Pathway analysis through the calculation of Elementary Flux Modes (EFMs).

OptFlux also contemplates several methods for model simplification and other pre-processing operations, aimed at reducing the search space for optimization algorithms.

The software supports importing/exporting to several flat file formats and is compatible with the Systems Biology Markup Language (SBML) standard.

OptFlux has a visualization module (BioVisualizer) that allows the analysis of the model structure that is compatible with the layout information of CellDesigner - (see G6G Abstract Number 20159), allowing the superimposition of simulation results with the model graph.

The application allows the user to load a genome-scale model of a given organism. This will serve as the basis for simulating wild type(s) and mutants (the original strain with a set of selected gene deletions).

The simulation of these strains can be conducted using a number of approaches (e.g. Flux-Balance Analysis, Minimization of Metabolic Adjustment or Regulatory On/Off Minimization of metabolic fluxes) (as stated above...) that allow the set of fluxes in the organism's metabolism to be determined, given a set of environmental constraints.

The software also includes a number of optimization methods [e.g. Evolutionary Algorithms (EAs) or Simulated Annealing (SA)] (as stated above...) to reach the best set of gene deletions given an objective function, typically related to a given industrial goal.

The OptFlux application was developed based on the AIBench framework - (see G6G Abstract Number 20693).

The AIBench framework is an environment for the development of Data Mining/ Bioinformatics tools, using the Java programming language.

Given OptFlux’s plug-in based architecture it can be extended with new functionalities.

Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean Network based Regulatory models.

The main features of this OptFlux are as follows:

1) Open-source - it allows all users to use the tool freely and invites the contribution of other researchers;

2) User-friendly - facilitates its use by users with No/little background in modeling/informatics;

3) Modular - facilitates the addition of specific features by computer scientists, given its plug-in based architecture;

4) Compatible with standards - compatibility with SBML and the layout information of Cell Designer.

5) Version (2.0) of the software accommodates several tools and algorithms that have been developed for the manipulation of metabolic models:

OptFlux’s main capabilities can be grouped into distinct functional areas:

1) Model handling - OptFlux makes available a number of operations to visualize, import and export stoichiometric metabolic models, including reactions, metabolites, equations and, if available, gene-reaction associations.

It allows the loading of models either from flat text files (containing the lists of reactions, metabolites, the stoichiometric matrix and gene-reaction associations), from text files following the Metatool format or from files complying with the SBML standard.

The compatibility with SBML allows the use of models stored in public databases, e.g. BioModels - (see G6G Abstract Number 20295) or the BiGG database - (see G6G Abstract Number 20628), or built using other software tools, e.g. CellDesigner.

The process of loading a model is facilitated by the development of a wizard that encompasses several steps, where the user can choose from a number of options related to the format of the input files.

2) Simulation - The Simulation area encompasses the metabolic phenotype simulation methods implemented in OptFlux, i.e. the algorithms that calculate the values for the fluxes over the whole set of reactions in the model. It is also possible to perform simulations of the wild-type and mutant strains.

In the first case, the original model is considered with No additional constraints, while in the latter a number of user selected reactions (or genes, if the model includes gene-reaction associations) are removed from the original model before simulation.

The simulation results include, besides the flux values; net conversions and shadow price information and they are placed in OptFlux’s clipboard area, becoming easily accessible for further analysis or future operations.

3) Optimization - The strain optimization area provides the users with interfaces to identify sets of reaction deletions (or gene deletions, if gene-reaction associations are available) that maximize a given objective function related with a desired industrial objective.

The ultimate purpose of the implemented algorithms is to identify genetic modifications that force the microorganism to produce a particular metabolite, while still obeying the physiological aim of maximizing biomass production.

The OptKnock algorithm and two (2) meta-heuristic optimization methods, EAs and SA, are currently available.

Elementary Flux Modes (EFMs) analysis - Optflux also allows state-of-the-art EFM calculations provided by the EFMTool that implements one of the most efficient algorithms available.

Moreover, it provides a simple user interface that allows an intuitive filtering of the results that match given patterns.

The visualization of the EFMs is presented in a column-wise table, where each column corresponds to an EFM and each line to a reaction of the model. Each EFM, i.e. its flux values, can be exported to CellDesigner, if the model was created from a CellDesigner SBML file.

For each reaction in the EFM, the line in the CellDesigner layout is represented with a thickness that is proportional to the value of the flux.

4) Visualization - OptFlux allows the graphical visualization of the pathways through BioVisualizer, a visualization plug-in that was developed to represent metabolic networks as graphs, with a number of distinct node types (e.g. metabolites, enzymes, and reactions) and connections.

If a Cell Designer SBML file is loaded as the model source, automatically it will be used by BioVisualizer in the visualization operation, using the layout built previously in CellDesigner.

Also, if the original model is loaded from flat files or normal SBML, BioVisualizer can work if a CellDesigner SBML file is available, typically representing only a subset of the whole model (e.g. a pathway) with compatible names for the reactions.

One of the major features of this tool is its ability to associate numerical values to the different types of nodes and edges. This allows the visualization of the metabolic network overlapped by the values of the fluxes obtained in a given simulation.

Moreover, the flux values can be exported to CellDesigner, if the model was created from a CellDesigner SBML file.

System Requirements

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Manufacturer Web Site OptFlux

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G6G Abstract Number 20692

G6G Manufacturer Number 104267