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Automated quantitative analysis of lipid accumulation and hydrolysis in living macrophages with label-free imaging
Authors:Wei-Wen Chen  Chen-Hao Chien  Chiung-Lin Wang  Huai-Hsien Wang  Yuh-Lin Wang  Shih-Torng Ding  Tzong-Shyuan Lee  Ta-Chau Chang
Institution:1. Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan
2. Molecular Science and Technology Program, Taiwan International Graduate Program, Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan
3. Department of Chemistry, National Tsing Hua University, Hsinchu, 300, Taiwan
4. Institute of Biophotonics, National Yang-Ming University, Taipei, 112, Taiwan
5. Department of Physics, National Taiwan University, Taipei, 106, Taiwan
6. Department of Animal Science and Technology/Institute of Biotechnology, National Taiwan University, Taipei, 106, Taiwan
7. Department of Physiology, School of Medicine, National Yang-Ming University, Taipei, 112, Taiwan
Abstract:The accumulation of lipids in macrophages is a key factor that promotes the formation of atherosclerotic lesions. Several methods such as biochemical assays and neutral lipid staining have been used for the detection of lipids in cells. However, a method for real-time quantitative assessment of the lipid content in living macrophages has yet to be shown, particularly for its kinetic process with drugs, due to the lack of suitable tools for non-invasive chemical detection. Here we demonstrate label-free real-time monitoring of lipid droplets (LDs) in living macrophages by using coherent anti-Stokes Raman scattering (CARS) microscopy. In addition, we have established an automated image analysis method based on maximum entropy thresholding (MET) to quantify the cellular lipid content. The result of CARS image analysis shows a good correlation (R 2?>?0.9) with the measurement of biochemical assay. Using this method, we monitored the processes of lipid accumulation and hydrolysis in macrophages. We further characterized the effect of a lipid hydrolysis inhibitor (diethylumbelliferyl phosphate, DEUP) and determined the kinetic parameters such as the inhibition constant, K i. Our work demonstrates that the automated quantitative analysis method is useful for the studies of cellular lipid metabolism and has potential for preclinical high-throughput screening of therapeutic agents related to atherosclerosis and lipid-associated disorders.
Figure
Automated quantitative analysis for the label-free detection of lipid content in living cells
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