Quantification of cellular lipids in a reproducible and high-throughput manner is a key step in the development of therapeutics for lipid storage diseases. Niemann-Pick Disease Type C (NPC) is a genetic disorder characterized by the accumulation of unesterified cholesterol in late endosomes/lysosomes, which is usually measured by the filipin fluorescence assay. However, the nonspecific binding of filipin to other sterol derivatives, multiple assay steps, and difficulty in quantitation present limitations for high-throughput screening and accurate cellular cholesterol quantification. We report the development of an integrated and semiautomated protocol to extract and quantify cellular cholesterol in 384-well plates by utilizing a liquid handling platform in conjunction with a high-throughput mass spectrometry (MS) system. The 384-well plate format enables seamless lipid extraction and subsequent MS analysis in less than 2 h from a cell culture plate to final MS data. Cholesterol was extracted from neural stem cells differentiated from NPC induced pluripotent stem cells using methyl tert-butyl ether (MTBE), with (13)C-cholesterol serving as an internal standard for quantification and normalization of native cholesterol. This integrated platform showed excellent quantification linearity and reproducibility (intraday and interday, R(2) > 0.99) with a recovery rate between 83 and 107%. We employed this integrated platform to screen a collection of 241 investigational compounds at seven concentrations each, benchmarking the method as an efficient, label-free cellular cholesterol quantification assay for high-throughput applications. Furthermore, we demonstrated the capability to multiplex extraction and quantification of sphingosine/cholesterol in a single MS run, extending the applicability of this integrated workflow to other lipid storage diseases.
An Integrated Platform for High-Throughput Extraction and Mass Spectrometry-Based Quantification of Cholesterol and Sphingosine.
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作者:Lin Yi-Han, Fang Yuhong, Gosztyla Maya L, Zhu Edward, Kapoor Abhijeet, Dulcey Andrés E, Talley Daniel C, Yang Shu, Xu Miao, Hu Xin, Zheng Wei, Simeonov Anton, Marugan Juan J, Henderson Mark J, LeClair Christopher A, Baljinnyam Bolormaa, Tao Dingyin
| 期刊: | Analytical Chemistry | 影响因子: | 6.700 |
| 时间: | 2025 | 起止号: | 2025 Jul 15; 97(27):14177-14188 |
| doi: | 10.1021/acs.analchem.4c06628 | ||
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