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      Deciphering metabolic crosstalk in context: lessons from inflammatory diseases

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          Abstract

          Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single‐cell omics techniques, flow cytometry‐based methods (Met‐Flow, single‐cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE‐Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease‐relevant contexts.

          Abstract

          The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization should be considered when studying immunometabolism. In this review, we discuss important challenges in immunometabolism research, highlight the state‐of‐the‐art techniques suited to address these challenges, and indicate advancements that can push the field forward.

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          Most cited references125

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          Large-scale simultaneous measurement of epitopes and transcriptomes in single cells

          Recent high-throughput single-cell sequencing approaches have been transformative for understanding complex cell populations, but are unable to provide additional phenotypic information, such as protein levels of cell-surface markers. Using oligonucleotide-labeled antibodies, we integrate measurements of cellular proteins and transcriptomes into an efficient, sequencing-based readout of single cells. This method is compatible with existing single-cell sequencing approaches and will readily scale as the throughput of these methods increase.
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            Succinate is an inflammatory signal that induces IL-1β through HIF-1α.

            Macrophages activated by the Gram-negative bacterial product lipopolysaccharide switch their core metabolism from oxidative phosphorylation to glycolysis. Here we show that inhibition of glycolysis with 2-deoxyglucose suppresses lipopolysaccharide-induced interleukin-1β but not tumour-necrosis factor-α in mouse macrophages. A comprehensive metabolic map of lipopolysaccharide-activated macrophages shows upregulation of glycolytic and downregulation of mitochondrial genes, which correlates directly with the expression profiles of altered metabolites. Lipopolysaccharide strongly increases the levels of the tricarboxylic-acid cycle intermediate succinate. Glutamine-dependent anerplerosis is the principal source of succinate, although the 'GABA (γ-aminobutyric acid) shunt' pathway also has a role. Lipopolysaccharide-induced succinate stabilizes hypoxia-inducible factor-1α, an effect that is inhibited by 2-deoxyglucose, with interleukin-1β as an important target. Lipopolysaccharide also increases succinylation of several proteins. We therefore identify succinate as a metabolite in innate immune signalling, which enhances interleukin-1β production during inflammation.
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              Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

              The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
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                Author and article information

                Contributors
                e.a.zaal@uu.nl
                c.r.berkers@uu.nl
                Journal
                Mol Oncol
                Mol Oncol
                10.1002/(ISSN)1878-0261
                MOL2
                Molecular Oncology
                John Wiley and Sons Inc. (Hoboken )
                1574-7891
                1878-0261
                26 January 2024
                July 2024
                : 18
                : 7 ( doiID: 10.1002/mol2.v18.7 )
                : 1759-1776
                Affiliations
                [ 1 ] Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine Utrecht University The Netherlands
                [ 2 ] Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine Utrecht University The Netherlands
                [ 3 ] Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research Utrecht University The Netherlands
                Author notes
                [*] [* ] Correspondence

                E. A. Zaal and C. R. Berkers, Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 2, Utrecht 3584 CM, The Netherlands

                E‐mail: e.a.zaal@ 123456uu.nl ; c.r.berkers@ 123456uu.nl

                Author information
                https://orcid.org/0000-0003-0746-8565
                Article
                MOL213588 MOLONC-23-0621.R1
                10.1002/1878-0261.13588
                11223610
                38275212
                958e9d43-a9e2-436f-994a-1464fa6acb6a
                © 2024 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 November 2023
                : 17 July 2023
                : 15 January 2024
                Page count
                Figures: 5, Tables: 1, Pages: 18, Words: 13336
                Categories
                Cancer Metabolism
                Inflammatory Diseases
                Tumor Microenvironment
                Review
                Review
                Custom metadata
                2.0
                July 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.5 mode:remove_FC converted:04.07.2024

                Oncology & Radiotherapy
                advanced metabolomics methods,immunometabolism,inflammatory diseases,metabolic crosstalk,metabolic heterogeneity,microenvironment

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