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MetaNetter 2: A Cytoscape plugin for ab initio network analysis and metabolite feature classification
K E V Burgess1, Y Borutzki1, N Rankin2
1Glasgow Polyomics, University of Glasgow, Glasgow, United Kingdom; Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom.
Summary
MetaNetter 2 enhances metabolomics by creating biochemical networks from mass spectrometry data. This tool aids in identifying compound relationships and analyzing adduct patterns for biological insights.
Area of Science:
- Metabolomics and Bioinformatics
- Computational Chemistry
- Systems Biology
Background:
- Metabolomics generates complex high-resolution mass spectrometry data.
- Data analysis is challenging due to artefacts, noise, adducts, and fragmentation.
- Understanding compound relationships is crucial for biological interpretation.
Purpose of the Study:
- Introduce MetaNetter 2, an improved biochemical networking tool.
- Enhance data analysis by generating adduct networks and cross-sample pattern tables.
- Facilitate the study of compound relationships in complex metabolomic datasets.
Main Methods:
- Utilized Cytoscape plugin for ab initio network generation.
- Developed adduct network creation capabilities.
- Implemented tables for mapping adduct and transformation patterns across samples.
- Applied the tool to analyze adduct patterns under different chromatographic conditions.
- Performed chemical transformation analysis on single and all-ions fragmentation datasets.
Main Results:
- Demonstrated MetaNetter 2's ability to generate adduct networks.
- Showcased the creation of tables mapping adduct/transformation patterns.
- Analyzed the impact of buffer conditions on adduct detection.
- Applied chemical transformation analysis to fragmentation data.
- Successfully analyzed a Staphylococcus aureus growth dataset.
Conclusions:
- MetaNetter 2 provides significant improvements for metabolomic data analysis.
- The tool effectively reveals compound relationships through adduct and transformation networks.
- MetaNetter 2 is valuable for inferring biochemical processes and biological differences from metabolomic data.
