MetaNetter: Inferring networks from high resolution mass spectrometry

Aim | Install | Documentation and tutorial | Download | Data | News | References | Authors

Supplementary material: Supplementary.pdf
Manual: MetaNetterManual.pdf

Aim[Top]

Presentation

Metabolomics aims at the identification and quantification of all metabolites that are present in a cell, tissue or biofluid at a given moment and under particular conditions. Various spectrometric technologies are capable of identifying thousands of metabolites. Recently, ultra high-resolution mass spectrometry (FTICR-MS or Orbitrap) has been successfully used in metabolomic studies. Such high-resolution data has also been used to predict ab initio biochemical interactions between metabolites. Moreover, perturbation studies allow the use of correlation analysis to infer/confirm links between metabolites that correlate across various conditions. The combination of these two inference methods generates networks containing hundreds of nodes (metabolites) and hundreds of predicted edges (biochemical reactions and/or high correlations). To analyze, explore and interpret these two kinds of relations, powerful visualization tools are required.

There is currently no available software that allows inference and visualization of such high-resolution metabolomic networks directly from raw data. Here we present a new plugin for Cytoscape dedicated to the inference and visualization of high-resolution metabolomic networks. Inference requires a list of potential biochemical transformations. Since the definition of this list is closely related to experimentation (i.e. the organism or perturbation under study), we propose facilities to edit/select putative biochemical transformations. The plugin also allows the extraction of parts of the network that contain a selected subset of reactions. Finally, to enrich the visual exploration, it is possible to visually render local topological properties of the network (e.g. degree or clustering index).

Install[Top]

Requirements:

  1. JAVA 1.5
  2. Cytoscape 2.3.1 or higher

Installation:

  1. Download and install. To do so go to Cytoscape dowload page: CYTOSCAPE
  2. Click on the following link to access the download page: DOWNLOAD PAGE
  3. Dowload lates version of MetaNetter ( right click on the link and select save target as)
  4. Note that Windows may change the extension into .zip. If so, delete “.zip” from the name of the file and replace with “ .jar”.
  5. Put the file in : C:\Program Files\Cytoscape_2.x.x\plugins (2.x.x is the version of Cytoscape, for instance 2.5)
  6. Download the other files, they are the data files

Documentation and tutorial[Top]

Supplementary material

This material contains: Click on the following link to get it Supplementary.pdf

Manual

Click on the following link to get MetaNetter user manual MetaNetterManual.pdf

Tutorial

Click the following link to access the tutorial page for version 1.1: TUTORIAL PAGE 1.1.
Click the following link to access the tutorial page for version 1.2: TUTORIAL PAGE 1.2.
Click the following link to access the tutorial page for version 2.0: TUTORIAL PAGE 2.0.

Adding a PUBCHEM link:

  1. Select menu: Edit->Preferences
  2. Select "Add" in the "Properties" panel
  3. You will be asked for a "Property Name" put:
    • For Cytoscape version 2.4 or higher: nodelinkouturl.Entrez.PubChem
    • For previous verions: linkouturl.Entrez.PubChem
  4. You will be asked for a "Value" put:
  5. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pcsubstance&term=%ID%%5Bmw%5D

File Formats:

  1. Simple mass list:
    All input files are standard text files. The format is quite simple, on each line put a mass.
    255.342
    786.1234
    345.567
  2. Quantitative data file:
    The format is similar to the one used for gene expression files: a tab-delimited text file, in which each column corresponds to one sample/condition. The first column contains the exact mass. You can use a first line describing the conditions but the plugin doesn't currently take this information into account.
    Note that you can easily export excel files in this file format. Choose save as-> File type ->text (separator:tabulation)
    255.342     7.57     1         6.19     7.02
    786.1234   1         13.45   1         23.2
    345.567     1         8.78     1.23     45.67

Download[Top]

 Go to :DOWNLOAD page.

News[Top]

Data[Top]

 With the MetaNetter plugin two sample data files are provided. They were generated for the metabolomic analysis of Trypanosoma Brucei response to various medium.

References[Top]
  1. Ab initio prediction of metabolic networks using Fourier Transform Mass Spectrometry data.
    2006. Rainer Breitling, Shawn Ritchie, Dayan Goodenowe, Mhairi L. Stewart and Michael P. Barrett. In Metabolomics (in press).

    ABSTRACT : Fourier Transform Mass Spectrometry has recently been introduced into the field of metabolomics as a technique that enables the mass separation of complex mixtures at very high resolution and with ultra high mass accuracy. Here we show that this enhanced mass accuracy can be exploited to predict large metabolic networks ab initio, based only on the observed metabolites without recourse to predictions based on the literature. The resulting networks are highly information-rich and clearly non-random. They can be used to infer the chemical identity of metabolites and to obtain a global picture of the structure of cellular metabolic networks. This represents the first reconstruction of metabolic networks based on unbiased metabolomic data and offers a breakthrough in the systems-wide analysis of cellular metabolism.

Authors[Top]

Contacts

Mike Barrett: [mail]
Rainer Breitling: [web page] [mail]
David Gilbert: [web page] [mail]
Fabien Jourdan: [web page] [mail]

Institutions