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Updated: May 6, 2026

Cellular Lipid Extraction for Targeted Stable Isotope Dilution Liquid Chromatography-Mass Spectrometry Analysis
Published on: November 17, 2011
Review of methods for the determination of cellular cholesterol content: principles, advantages, limitations,
Zihang Zhou1, Jiangyu Zong1, Ning Xu2
1Institute of Drug Development and Chemical Biology, College of Pharmaceutical Science, Zhejiang University of Technology, Huzhou, 313200, Zhejiang, People's Republic of China.
Abstract:
Imbalances in cellular cholesterol homeostasis are associated with various diseases, and accurate determination of cholesterol levels and distribution is essential for a thorough understanding of cellular physiopathology. In this review, we comprehensively analyzed various techniques for cellular cholesterol determination. They include indirect methods based on SREBP2 activity monitoring, gas chromatography-liquid chromatography coupling, enzyme analysis, improved Abell-Kendall method, cholesterol-specific probes such as filipin III and cholesterol-dependent cytolysin, and cholesterol analogs such as dehydroergosterol, BODIPY-cholesterol, label-free as well as labeling Raman assays and mass spectrometry imaging techniques such as matrix-assisted laser desorption/ionization mass spectrometry imaging, desorption electrospray ionization mass spectrometry imaging, and nanoscale secondary ion mass spectrometry technology. Principles, advantages, and limitations of each technique are discussed in detail, their characteristics in terms of sensitivity, spatial resolution, and temporal resolution are compared in detail. Finally, suggestions for selecting the technique for different experimental objectives are also given. These findings will help researchers choose the most suitable method according to their own needs, provide strong support for cellular cholesterol research, and promote the development of related fields to better elucidate the significance of cellular cholesterol in normal biologic activities and also its intrinsic relationship with diseases.

