Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches

Beniddir, M. A., Kang, K. B., Genta-Jouve, G., Huber, F., Rogers, S. and Van Der Hooft, J. J.J. (2021) Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches. Natural Product Reports, 38(11), pp. 1967-1993. (doi: 10.1039/D1NP00023C)

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Abstract

Covering: up to the end of 2020 Recently introduced computational metabolome mining tools have started to positively impact the chemical and biological interpretation of untargeted metabolomics analyses. We believe that these current advances make it possible to start decomposing complex metabolite mixtures into substructure and chemical class information, thereby supporting pivotal tasks in metabolomics analysis including metabolite annotation, the comparison of metabolic profiles, and network analyses. In this review, we highlight and explain key tools and emerging strategies covering 2015 up to the end of 2020. The majority of these tools aim at processing and analyzing liquid chromatography coupled to mass spectrometry fragmentation data. We start with defining what substructures are, how they relate to molecular fingerprints, and how recognizing them helps to decompose complex mixtures. We continue with chemical classes that are based on the presence or absence of particular molecular scaffolds and/or functional groups and are thus intrinsically related to substructures. We discuss novel tools to mine substructures, annotate chemical compound classes, and create mass spectral networks from metabolomics data and demonstrate them using two case studies. We also review and speculate about the opportunities that NMR spectroscopy-based metabolome mining of complex metabolite mixtures offers to discover substructures and chemical classes. Finally, we will describe the main benefits and limitations of the current tools and strategies that rely on them, and our vision on how this exciting field can develop toward repository-scale-sized metabolomics analyses. Complementary sources of structural information from genomics analyses and well-curated taxonomic records are also discussed. Many research fields such as natural products discovery, pharmacokinetic and drug metabolism studies, and environmental metabolomics increasingly rely on untargeted metabolomics to gain biochemical and biological insights. The here described technical advances will benefit all those metabolomics disciplines by transforming spectral data into knowledge that can answer biological questions.

Item Type:Articles
Additional Information:M. A. B. was supported by the National French Agency (ANR grants 15-CE29-0001 and 20-CE43-0010). K. B. K. was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF grant NRF-2020R1C1C1004046). G. G.-J. was supported by the Le Centre National de la Recherche Scientifique - Institute de chimie (CNRS-INC EMERGENCE@INC2020 project). S. R. was supported by the Biotechnology and Biological Sciences Research Council (BBSRC grant BB/R022054/1). F. H. and J. J. J. v. d. H. were supported by the Netherlands eScience Center (ASDI eScience grant ASDI.2017.030).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Rogers, Dr Simon and Van Der Hooft, Mr Justin
Creator Roles:
Rogers, S.Writing – original draft, Writing – review and editing
Van Der Hooft, J.Conceptualization, Writing – original draft, Writing – review and editing, Supervision, Validation
Authors: Beniddir, M. A., Kang, K. B., Genta-Jouve, G., Huber, F., Rogers, S., and Van Der Hooft, J. J.J.
College/School:College of Medical Veterinary and Life Sciences > School of Infection & Immunity
College of Science and Engineering > School of Computing Science
Journal Name:Natural Product Reports
Publisher:Royal Society of Chemistry
ISSN:0265-0568
ISSN (Online):1460-4752
Published Online:18 June 2021
Copyright Holders:Copyright © 2021 The Royal Society of Chemistry
First Published:First published in Natural Product Reports 38(11): 1967-1993
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
302697Combatting antimicrobial resistance through new software for natural product discoverySimon RogersBiotechnology and Biological Sciences Research Council (BBSRC)BB/R022054/1Computing Science