MetExplore

Category Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools and Metabolomics/Metabonomics>Metabolic Profiling/Analysis Systems/Tools

Abstract MetExplore is a web server that can be used to link metabolomic experiments and genome-scale metabolic networks.

MetExplore databases --

MetExplore stores metabolic networks of 107 organisms into a relational database (freely available on demand). Information about metabolic networks currently comes from BioCyc-like databases.

These databases are - AcypiCyc, ApiCyc, AraCyc, EcoCyc, HumanCyc, MicroCyc, Metabolome.jp, MetaCyc, MouseCyc, PlantCyc, TrypanoCyc, and YeastCyc.

Two of the BioCyc-like databases contain information about several organisms: PlantCyc and MetaCyc.

The manufacturers also included in MetExplore the information about metabolites stored in the Metabolome.jp database (as stated above).

Note: There is No information about reactions in this database and it is only useful to identify compounds from masses.

The manufacturers plan to include more metabolic networks, in particular from other sources such as, the Kyoto Encyclopedia of Genes and Genomes (KEGG) or HMDB.

HMDB - The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education.

MetExplore Filters --

Various filters can be applied in MetExplore to restrict the scope of the study, for example by selecting only particular pathways or by restricting the network to small-molecule metabolism.

MetExplore also allows filtering of currency metabolites, cofactors or generic reactions, often sources of misinterpretations in metabolic graph analysis and which also bring significant quantities of noise to the derived networks.

The filters available in MetExplore have three (3) main functions.

1) First, their implementation can allow investigation of selected subparts of metabolism;

2) Second, they can be used to avoid sources of misinterpretation in metabolic graph analyses; and

3) Third, they can aid in providing clearer visualizations of the network, by restricting analyses to only small molecule metabolites excluding cellular macromolecules (proteins, nucleic acids, glycoconjugates, etc.).

MetExplore Graph and other Functions --

MetExplore provides several functions that can be applied to filtered metabolic networks. MetExplore is thus able to deal with data from metabolomics experiments by mapping a list of masses or identifiers onto filtered metabolic networks.

MetExplore also provides several functions based on the modeling of the metabolic network by a graph model.

Two (2) functions are dedicated to the identification of “weak” points in the metabolic network to help the design of new drugs.

1) The first one identifies the ‘choke point reactions’, defined as reactions that either uniquely consume a specific substrate or uniquely produce a specific product.

2) The second one identifies the ‘choke point metabolites’, defined as metabolites that are either uniquely consumed by a specific reaction or uniquely produced by a specific reaction.

Scope Function -

The scope function allows you to compute the biosynthetic capacity of a set of metabolites.

The scope of a set of metabolites (so-called seeds) is defined as the sum of all metabolites that the seeds are able to produce using the reactions available in an organism. On the contrary of shortest paths computed in simple graphs, the scope concept takes into account the availability of all the substrates that happen to use a reaction.

The scope is computed in an iterative way, called an expansion process. At each step, the reactions using inputs are checked: if all the substrates are in the set of seeds, then they are fired and all their products join the set of seeds.

The process stops when No additional reaction can be fired. The metabolites contained in the final set of seeds represent the scope of the initial set of seeds.

The reverse of the scope function is also possible in MetExplore by identifying the set of precursors that lead to the production of a given set of metabolites.

Precursors of Metabolites -

This function allows you to compute the set of metabolites, called precursors, sufficient to produce a set of target metabolites. This is computed by the inverse of the expansion process described in the Scope function (see above...).

The process starts with a set of given target metabolites. At each step, the reactions producing targets are checked, then they are fired and all their substrates join the set of targets.

The process stops when No additional reaction can be fired. A metabolite is defined as a potential precursor of the set of target metabolites if it is Not produced by any reaction or produced only by one reversible reaction, and if there is a path between this compound and any of the target compounds selected.

Metabolome properties -

MetExplore also allows you to display information about the whole sets of metabolites present in a filtered metabolic network.

Apart from classical information such as mass, formula, reactions and pathways where each metabolite is involved, MetExplore also displays the topological properties of the metabolite in the filtered metabolic network.

It is then possible to know whether a metabolite is a source, an output or a choke point in the filtered metabolic network.

MetExplore Export --

The MetExplore user can export a filtered metabolic network into several graph models (compound graph, reaction graph or bipartite graph).

Download and Visualize function -

The MetExplore function “Download and Visualize” allows you to export a filtered metabolic network in several formats:

1) Classical Systems Biology Markup Language (SBML) format - the XML format dedicated to metabolic networks.

2) Extended SBML format: a SBML format with additional specificities pertaining to MetExplore.

3) Graph formats - available in Cytoscape format (sif)

Note: The user can also upload their own SBML file and export it into graph models.

Create Graph from SBML function -

This MetExplore function allows the user to upload their own SBML file and to export it into two (2) graph formats, compound graph and reaction graph.

MetExplore Common Features --

Topological information glyphs -

In the results of the MetExplore function, the topological information of the metabolites is displayed in the form of glyphs.

Glyphs - Glyphs are a pictorial form of data collection. You might be reminded of the term “hieroglyphics” and think about early picture writing. Different forms of glyphs are used in many medical situations to quickly record data about a patient in pictorial form.

Using Cytoscape with MetExplore -

MetExplore functions enable you to directly load a filtered metabolic network and its attributes into a version of Cytoscape tuned for MetExplore.

System Requirements

Contact manufacturer.

Manufacturer

Manufacturer Web Site MetExplore

Price Contact manufacturer.

G6G Abstract Number 20647

G6G Manufacturer Number 104300