Identification of bioactive metabolites using activity metabolomics

Abstract

The metabolome, the collection of small-molecule chemical entities involved in metabolism, has traditionally been studied with the aim of identifying biomarkers in the diagnosis and prediction of disease. However, the value of metabolome analysis (metabolomics) has been redefined from a simple biomarker identification tool to a technology for the discovery of active drivers of biological processes. It is now clear that the metabolome affects cellular physiology through modulation of other ‘omics’ levels, including the genome, epigenome, transcriptome and proteome. In this Review, we focus on recent progress in using metabolomics to understand how the metabolome influences other omics and, by extension, to reveal the active role of metabolites in physiology and disease. This concept of utilizing metabolomics to perform activity screens to identify biologically active metabolites — which we term activity metabolomics — is already having a broad impact on biology.

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Fig. 1: Metabolites as active modulators of gene and protein activity.
Fig. 2: Examples of macromolecule modification by the active metabolome.
Fig. 3: Mechanisms for non-covalent modification of macromolecules by the active metabolome.
Fig. 4: Workflow to elucidate metabolite bioactivity.
Fig. 5: Metabolite activity for phenotype modulation.

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Acknowledgements

M.M.R. was supported by a fellowship from the Deutsche Forschungsgemeinschaft (DFG-Ri2811/1-1 and Ri2811/1-2). This effort was partially funded by Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA), a Scientific Focus Area Program at the Lawrence Berkeley National Laboratory for the US Department of Energy, Office of Science, Office of Biological and Environmental Research under contract DE-AC02-05CH11231 (G.S.) and US National Institutes of Health grants R01 GM114368-03, P30 MH062261-17 P01 DA026146-02 and the NIH Cloud Credits Model Pilot, a component of the NIH Big Data to Knowledge (BD2K) program (G.S.).

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Nature Reviews Molecular Cell Biology thanks C. Burant, C. Frezza and M. Ralser for their contribution to the peer review of this work.

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Biocyc: https://www.biocyc.org

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KEGG: https://www.kegg.jp/

MetaboAnalyst platform: https://www.metaboanalyst.ca/

MetaboLights: https://www.ebi.ac.uk/metabolights/

Metabolomics repository Bordeaux: http://services.cbib.u-bordeaux.fr/MERYB/home/home.php

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MetExplore: https://metexplore.toulouse.inra.fr/metexplore2/

METLIN: https://metlin.scripps.edu

mzCloud: https://www.mzcloud.org

Pathview: https://pathview.uncc.edu/

Reactome: https://reactome.org

Recon: https://www.vmh.life/

SMPDB: http://smpdb.ca/

XCMS online: https://xcmsonline.scripps.edu

Glossary

Sirtuin

An enzyme that is involved in the deacetylation of proteins.

Cognitive computing

A term that describes computational platforms that are based on artificial intelligence.

Cloud-based computing

The use of computational resources that are not physically present but are deposited at a server at a remote location and are accessed via Internet connection.

Itaconate

An organic dicarbonic acid that has recently emerged as a modifier of cysteine residues and a modulator of inflammatory phenotypes.

Riboswitches

Parts of an mRNA molecule that change structure upon binding of small molecules.

Protein arrays

A high-throughput method used to determine the interactions of proteins (for example, with candidate metabolites).

Flux analysis

A mass-spectrometry-based technique that is used to examine production and consumption rates of metabolites by tracking isotopes.

Metabolite features

Peaks or a set of peaks across samples with a unique mass-to-charge ratio (m/z value) and retention time that define the metabolite and enable its unique identification.

Triple quadrupole mass spectrometer

A mass spectrometer consisting of three quadrupole mass spectrometers in a row designed for targeted metabolomics quantification.

High-resolution mass spectrometry

An Orbitrap or a quadrupole-time-of-flight mass spectrometer with high mass resolution and accuracy. It is a commonly used instrument for untargeted metabolomics acquisition.

Neural networks

A machine learning technique. Neural networks consist of artificial neurons that translate an input into an output.

Exploratory metabolomics

The use of (untargeted) metabolomics to identify global regulation states of molecules in a biological system.

Chemical space

The actual physico-chemical space (degree of freedom) defined by the chemical structure in which binding and/or activity might occur.

Law of mass action

A chemical law defining that a reversible chemical reaction in equilibrium is directly proportional to the product of the concentrations of the reactants.

Metabolite set enrichment

A method of identifying patterns of regulated metabolites using predefined metabolite lists. It is an analogue of gene set enrichment.

Untargeted metabolomics

A global method that attempts to measure all or as many molecules as possible in a sample. By contrast, targeted metabolomics is a method in which a specified, predefined entity of molecules is measured. Both methods can be based on mass spectrometry or NMR.

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Rinschen, M.M., Ivanisevic, J., Giera, M. et al. Identification of bioactive metabolites using activity metabolomics. Nat Rev Mol Cell Biol 20, 353–367 (2019). https://doi.org/10.1038/s41580-019-0108-4

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