Integrating multiplex immunofluorescent and mass spectrometry imaging to map myeloid heterogeneity in its metabolic and cellular context.

Autor:	Goossens P; Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands. Electronic address: pieter.goossens@maastrichtuniversity.nl., Lu C; Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands., Cao J; Maastricht MultiModal Molecular Imaging institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, the Netherlands., Gijbels MJ; Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands; Department of Medical Biochemistry, Amsterdam UMC-Location AMC, Amsterdam, the Netherlands., Karel JMH; Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, the Netherlands., Wijnands E; Central Diagnostic Laboratories, Maastricht University Medical Center+, Maastricht, the Netherlands., Claes BSR; Maastricht MultiModal Molecular Imaging institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, the Netherlands., Fazzi GE; Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands., Hendriks TFE; Maastricht MultiModal Molecular Imaging institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, the Netherlands., Wouters K; Cardiovascular Research Institute Maastricht, Department of Internal Medicine, Maastricht University, Maastricht, the Netherlands., Smirnov E; Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, the Netherlands., van Zandvoort MJM; Department of Genetics & Cell Biology - Molecular Cell Biology, Maastricht University, Maastricht, the Netherlands; Institute for Molecular Cardiovascular Research, RWTH Aachen University, Aachen, Germany., Balluff B; Maastricht MultiModal Molecular Imaging institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, the Netherlands., Cuypers E; Maastricht MultiModal Molecular Imaging institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, the Netherlands., Donners MMPC; Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands., Heeren RMA; Maastricht MultiModal Molecular Imaging institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, the Netherlands., Biessen EAL; Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands; Institute for Molecular Cardiovascular Research, RWTH Aachen University, Aachen, Germany.
Jazyk:	angličtina
Zdroj:	Cell metabolism [Cell Metab] 2022 Aug 02; Vol. 34 (8), pp. 1214-1225.e6. Date of Electronic Publication: 2022 Jul 19.
DOI:	10.1016/j.cmet.2022.06.012
Abstrakt:	Cells often adopt different phenotypes, dictated by tissue-specific or local signals such as cell-cell and cell-matrix contacts or molecular micro-environment. This holds in extremis for macrophages with their high phenotypic plasticity. Their broad range of functions, some even opposing, reflects their heterogeneity, and a multitude of subsets has been described in different tissues and diseases. Such micro-environmental imprint cannot be adequately studied by single-cell applications, as cells are detached from their context, while histology-based assessment lacks the phenotypic depth due to limitations in marker combination. Here, we present a novel, integrative approach in which 15-color multispectral imaging allows comprehensive cell classification based on multi-marker expression patterns, followed by downstream analysis pipelines to link their phenotypes to contextual, micro-environmental cues, such as their cellular ("community") and metabolic ("local lipidome") niches in complex tissue. The power of this approach is illustrated for myeloid subsets and associated lipid signatures in murine atherosclerotic plaque. Competing Interests: Declaration of interests The authors declare no competing interests. (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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