期刊
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES
卷 1071, 期 -, 页码 68-74出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jchromb.2017.08.015
关键词
MetaNetter; Ab-initio network; Mass spectrometry; Metabolomics
资金
- French Ministry of Research
- National Research Agency as part of the French MetaboHUB, the national metabolomics and fluxomics infrastructure [ANR-INBS-0010]
- Scottish Universities Life Science Alliance LEADERS Grant
- University of Glasgow
- Wellcome Trust [097821/Z/11/Z, 105614/Z/14/Z]
- Scottish Funding Council
- MRC [MR/N005813/1] Funding Source: UKRI
Metabolomics frequently relies on the use of high resolution mass spectrometry data. Classification and filtering of this data remain a challenging task due to the plethora of complex mass spectral artefacts, chemical noise, adducts and fragmentation that occur during ionisation and analysis. Additionally, the relationships between detected compounds can provide a wealth of information about the nature of the samples and the biochemistry that gave rise to them. We present a biochemical networking tool: MetaNetter 2 that is based on the original MetaNetter, a Cytoscape plugin that creates ab initio networks. The new version supports two major improvements: the generation of adduct networks and the creation of tables that map adduct or transformation patterns across multiple samples, providing a readout of compound relationships. We have applied this tool to the analysis of adduct patterns in the same sample separated under two different chromatographies, allowing inferences to be made about the effect of different buffer conditions on adduct detection, and the application of the chemical transformation analysis to both a single fragmentation analysis and an all-ions fragmentation dataset. Finally, we present an analysis of a dataset derived from anaerobic and aerobic growth of the organism Staphylococcus aureus demonstrating the utility of the tool for biological analysis.
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