Journal
JOURNAL OF CHROMATOGRAPHY A
Volume 1382, Issue -, Pages 136-164Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2014.10.091
Keywords
Metabolite profiling and fingerprinting; Metabolite annotation and identification; Natural products; Liquid chromatography; Mass spectrometry and NMR; Metabolomics
Funding
- Swiss National Science Foundation [CRSII3_127187, 205320/135 190-1, CR23I3_143733/1, 200020_146200]
- Swiss National Science Foundation (SNF) [200020_146200, CR23I3_143733, CRSII3_127187] Funding Source: Swiss National Science Foundation (SNF)
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Metabolite profiling is critical in many aspects of the life sciences, particularly natural product research. Obtaining precise information on the chemical composition of complex natural extracts (metabolomes) that are primarily obtained from plants or microorganisms is a challenging task that requires sophisticated, advanced analytical methods. In this respect, significant advances in hyphenated chromatographic techniques (LC-MS, GC-MS and LC-NMR in particular), as well as data mining and processing methods, have occurred over the last decade. Together, these tools, in combination with bioassay profiling methods, serve an important role in metabolomics for the purposes of both peak annotation and dereplication in natural product research. In this review, a survey of the techniques that are used for generic and comprehensive profiling of secondary metabolites in natural extracts is provided. The various approaches (chromatographic methods: LC-MS, GC-MS, and LC-NMR and direct spectroscopic methods: NMR and DIMS) are discussed with respect to their resolution and sensitivity for extract profiling. In addition the structural information that can be generated through these techniques or in combination, is compared in relation to the identification of metabolites in complex mixtures. Analytical strategies with applications to natural extracts and novel methods that have strong potential, regardless of how often they are used, are discussed with respect to their potential applications and future trends. (C) 2014 Elsevier B.V. All rights reserved.
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