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Updated: Dec 10, 2025

Exploring Adipose Tissue Structure by Methylsalicylate Clearing and 3D Imaging
Published on: August 19, 2020
Optimization of a MALDI-Imaging protocol for studying adipose tissue-associated disorders
A Fernández-Vega1, E Chicano-Gálvez2, B M Prentice3
1Dept. Cell Biology, Physiology, and Immunology, IMIBIC/University of Cordoba (UCO)/Reina Sofia University Hospital (HURS), Cordoba, Spain; CIBER Physiopathology of Obesity and Nutrition (CIBERobn), ISCIII, Spain.
Abstract:
Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) is increasingly recognized for its potential in the discovery of novel biomarkers directly from tissue sections. However, there are no MALDI IMS studies as yet on the adipose tissue, a lipid-enriched tissue that plays a pivotal role in the development of obesity-associated disorders. Herein, we aimed at developing an optimized method for analyzing adipose tissue lipid composition under both physiological and pathological conditions by MALDI IMS. Our studies showed an exacerbated lipid delocalization from adipose tissue sections when conventional strategies were applied. However, our optimized method using conductive-tape sampling and 2,5-dihydroxybenzoic acid (DHB) as a matrix, preserved the anatomical organization and minimized lipid diffusion from sample sections. This method enabled the identification of a total of 625 down-regulated and 328 up-regulated m/z values in the adipose tissue from a rat model of extreme obesity as compared to lean animals. Combination of MALDI IMS and liquid chromatography (LC)-MS/MS data identified 44 differentially expressed lipid species between lean and obese animals, including phospholipids and sphingomyelins. Among the lipids identified, SM(d18:0_18:2), PE(P-16:0_20:0), and PC(O-16:0_16:1) showed a differential spatial distribution in the adipose tissue of lean vs. obese animals. In sum, our method provides a valuable new tool for research on adipose tissue that may pave the way for the identification of novel biomarkers of obesity and metabolic disease.
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