Comprehensive and quantitative analysis of white and brown adipose tissue by shotgun lipidomics.
Mol. Metab. 22, 12-20 (2019)
OBJECTIVE: Shotgun lipidomics enables an extensive analysis of lipids from tissues and fluids. Each specimen requires appropriate extraction and processing procedures to ensure good coverage and reproducible quantification of the lipidome. Adipose tissue (AT) has become a research focus with regard to its involvement in obesity-related pathologies. However, the quantification of the AT lipidome is particularly challenging due to the predominance of triacylglycerides, which elicit high ion suppression of the remaining lipid classes. METHODS: We present a new and validated method for shotgun lipidomics of AT, which tailors the lipid extraction procedure to the target specimen and features high reproducibility with a linear dynamic range of at least 4 orders of magnitude for all lipid classes. RESULTS: Utilizing this method, we observed tissue-specific and diet-related differences in three AT types (brown, gonadal, inguinal subcutaneous) from lean and obese mice. Brown AT exhibited a distinct lipidomic profile with the greatest lipid class diversity and responded to high-fat diet by altering its lipid composition, which shifted towards that of white AT. Moreover, diet-induced obesity promoted an overall remodeling of the lipidome, where all three AT types featured a significant increase in longer and more unsaturated triacylglyceride and phospholipid species. CONCLUSIONS: The here presented method facilitates reproducible systematic lipidomic profiling of AT and could be integrated with further -omics approaches used in (pre-) clinical research, in order to advance the understanding of the molecular metabolic dynamics involved in the pathogenesis of obesity-associated disorders.
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Publication type
Article: Journal article
Document type
Scientific Article
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Keywords
Adipose Tissue ; Chow And High-fat Diet ; Lipid Extraction ; Lipid Remodeling ; Lipidomics ; Method Validation ; Mouse ; Shotgun Mass Spectrometry
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Language
english
Publication Year
2019
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2019
ISSN (print) / ISBN
2212-8778
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2212-8778
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Volume: 22,
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Pages: 12-20
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Elsevier
Publishing Place
Amsterdam
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Peer reviewed
Institute(s)
Institute of Pancreatic Islet Research (IPI)
POF-Topic(s)
90000 - German Center for Diabetes Research
Research field(s)
Helmholtz Diabetes Center
PSP Element(s)
G-502600-002
G-502600-008
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Erfassungsdatum
2019-03-15