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Quantitative Mapping of Triacylglycerol Chain Length and Saturation Using Broadband CARS Microscopy

Journal article
Authors A. Paul
Y. J. Wang
Cecilia Brännmark
S. Kumar
M. Bonn
S. H. Parekh
V. P. Stria
Published in Biophysical Journal
Volume 116
Issue 12
Pages 2346-2355
ISSN 0006-3495
Publication year 2019
Published at Institute of Neuroscience and Physiology, Department of Physiology
Pages 2346-2355
Language en
Keywords intracellular lipid storage, fatty-acids, biochemical-composition, insulin-resistance, droplets, cell, biology, obese, accumulation, lipotoxicity, Biophysics
Subject categories Neurosciences


Lipid droplets (LDs), present in many cell types, are highly dynamic organelles that store neutral lipids, primarily triacylglycerols (TAGs). With the discovery of new LD functions (e.g., in immune response, protein clearage, and occurrence with disease), new methods to study LD chemical composition in situ are necessary. We present an approach for in situ, quantitative TAG analysis using label-free, coherent Raman microscopy that allows deciphering LD TAG composition in different biochemically complex samples with submicrometer spatial resolution. Employing a set of standard TAGs, we generate a spectral training matrix capturing the variation caused in Raman-like spectra by TAG backbone, chain length, and number of double bonds per chain, as well as the presence of proteins or other diluting molecules. Comparing our fitting approach to gas chromatography measurements for mixtures of standard TAGs and food oils, we find the root mean-square error for the prediction of TAG chemistry to be 0.69 CH2 and 0.15 #C=C. When progressing to more complex samples such as oil emulsions and LDs in various eukaryotic cells, we find good agreement with bulk gas chromatography measurements. For differentiated adipocytes, we find a significant increase in the number of double bonds in small LDs (below 2 mu m in diameter) compared to large LDs (above 2 mu m in diameter). Coupled with a relatively limited sample preparation requirement, this approach should enable rapid and accurate TAG LD analysis for a variety of cell biology and technological applications.

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