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Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics |
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| Authors: | Dunn Warwick B Erban Alexander Weber Ralf J M Creek Darren J Brown Marie Breitling Rainer Hankemeier Thomas Goodacre Royston Neumann Steffen Kopka Joachim Viant Mark R |
| Institution: | 1.Centre for Advanced Discovery & Experimental Therapeutics (CADET), Central Manchester NHS Foundation Trust, Manchester Academic Health Sciences Centre, University of Manchester, York Place, Oxford Road, Manchester, M13 9WL, UK ;2.School of Biomedicine, University of Manchester, Oxford Road, Manchester, M13 9PL, UK ;3.Max Planck Institute for Molecular Plant Physiology (MPIMP), Potsdam-Golm, Germany ;4.Centre for Systems Biology, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK ;5.School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK ;6.Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK ;7.Department of Biochemistry and Molecular Biology, University of Melbourne, Parkville, VIC, Australia ;8.Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK ;9.Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands ;10.Division of Analytical Biosciences, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands ;11.Netherlands Metabolomics Centre, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands ;12.Manchester Centre for Integrative Systems Biology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK ;13.School of Chemistry, Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK ;14.Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, 06120, Halle, Germany ; |
| Abstract: | Metabolomics has advanced significantly in the past 10 years with important developments related to hardware, software and methodologies and an increasing complexity of applications. In discovery-based investigations, applying untargeted analytical methods, thousands of metabolites can be detected with no or limited prior knowledge of the metabolite composition of samples. In these cases, metabolite identification is required following data acquisition and processing. Currently, the process of metabolite identification in untargeted metabolomic studies is a significant bottleneck in deriving biological knowledge from metabolomic studies. In this review we highlight the different traditional and emerging tools and strategies applied to identify subsets of metabolites detected in untargeted metabolomic studies applying various mass spectrometry platforms. We indicate the workflows which are routinely applied and highlight the current limitations which need to be overcome to provide efficient, accurate and robust identification of metabolites in untargeted metabolomic studies. These workflows apply to the identification of metabolites, for which the structure can be assigned based on entries in databases, and for those which are not yet stored in databases and which require a de novo structure elucidation. |
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