Journal
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
Volume 69, Issue -, Pages 52-61Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.trac.2015.04.002
Keywords
Fragmentation tree; Ion tree; Mass spectral tree; Mass spectrometry; Metabolite identification; Metabolomics; MSn; Multi-stage analysis; Tandem mass spectrometry; Unknown compound
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Funding
- Direct For Biological Sciences [1139644] Funding Source: National Science Foundation
- Division Of Integrative Organismal Systems [1139644] Funding Source: National Science Foundation
- Div Of Molecular and Cellular Bioscience
- Direct For Biological Sciences [1153491] Funding Source: National Science Foundation
- NIDDK NIH HHS [U24 DK097154] Funding Source: Medline
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Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations. (C) 2015 Elsevier B.V. All rights reserved.
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