Elena Buglakova, Måns Ekelöf, Michaela Schwaiger-Haber, Lisa Schlicker, Martijn R. Molenaar, Mohammed Shahraz, Lachlan Stuart, Andreas Eisenbarth, Volker Hilsenstein, Gary J. Patti, Almut Schulze, Marteinn T. Snaebjornsson, Theodore Alexandrov
{"title":"Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer","authors":"Elena Buglakova, Måns Ekelöf, Michaela Schwaiger-Haber, Lisa Schlicker, Martijn R. Molenaar, Mohammed Shahraz, Lachlan Stuart, Andreas Eisenbarth, Volker Hilsenstein, Gary J. Patti, Almut Schulze, Marteinn T. Snaebjornsson, Theodore Alexandrov","doi":"10.1038/s42255-024-01118-4","DOIUrl":null,"url":null,"abstract":"While heterogeneity is a key feature of cancer, understanding metabolic heterogeneity at the single-cell level remains a challenge. Here we present 13C-SpaceM, a method for spatial single-cell isotope tracing that extends the previously published SpaceM method with detection of 13C6-glucose-derived carbons in esterified fatty acids. We validated 13C-SpaceM on spatially heterogeneous models using liver cancer cells subjected to either normoxia-hypoxia or ATP citrate lyase depletion. This revealed substantial single-cell heterogeneity in labelling of the lipogenic acetyl-CoA pool and in relative fatty acid uptake versus synthesis hidden in bulk analyses. Analysing tumour-bearing brain tissue from mice fed a 13C6-glucose-containing diet, we found higher glucose-dependent synthesis of saturated fatty acids and increased elongation of essential fatty acids in tumours compared with healthy brains. Furthermore, our analysis uncovered spatial heterogeneity in lipogenic acetyl-CoA pool labelling in tumours. Our method enhances spatial probing of metabolic activities in single cells and tissues, providing insights into fatty acid metabolism in homoeostasis and disease. Buglakova et al. present 13C-SpaceM, a method that combines stable isotope tracing with imaging mass spectrometry thus enabling spatial analysis of lipid dynamics with near-single-cell resolution in tissues.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":null,"pages":null},"PeriodicalIF":18.9000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42255-024-01118-4.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature metabolism","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s42255-024-01118-4","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
While heterogeneity is a key feature of cancer, understanding metabolic heterogeneity at the single-cell level remains a challenge. Here we present 13C-SpaceM, a method for spatial single-cell isotope tracing that extends the previously published SpaceM method with detection of 13C6-glucose-derived carbons in esterified fatty acids. We validated 13C-SpaceM on spatially heterogeneous models using liver cancer cells subjected to either normoxia-hypoxia or ATP citrate lyase depletion. This revealed substantial single-cell heterogeneity in labelling of the lipogenic acetyl-CoA pool and in relative fatty acid uptake versus synthesis hidden in bulk analyses. Analysing tumour-bearing brain tissue from mice fed a 13C6-glucose-containing diet, we found higher glucose-dependent synthesis of saturated fatty acids and increased elongation of essential fatty acids in tumours compared with healthy brains. Furthermore, our analysis uncovered spatial heterogeneity in lipogenic acetyl-CoA pool labelling in tumours. Our method enhances spatial probing of metabolic activities in single cells and tissues, providing insights into fatty acid metabolism in homoeostasis and disease. Buglakova et al. present 13C-SpaceM, a method that combines stable isotope tracing with imaging mass spectrometry thus enabling spatial analysis of lipid dynamics with near-single-cell resolution in tissues.
期刊介绍:
Nature Metabolism is a peer-reviewed scientific journal that covers a broad range of topics in metabolism research. It aims to advance the understanding of metabolic and homeostatic processes at a cellular and physiological level. The journal publishes research from various fields, including fundamental cell biology, basic biomedical and translational research, and integrative physiology. It focuses on how cellular metabolism affects cellular function, the physiology and homeostasis of organs and tissues, and the regulation of organismal energy homeostasis. It also investigates the molecular pathophysiology of metabolic diseases such as diabetes and obesity, as well as their treatment. Nature Metabolism follows the standards of other Nature-branded journals, with a dedicated team of professional editors, rigorous peer-review process, high standards of copy-editing and production, swift publication, and editorial independence. The journal has a high impact factor, has a certain influence in the international area, and is deeply concerned and cited by the majority of scholars.