Division of Chemical Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Department of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany.
Department of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany; Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas.
Biophys J. 2019 Jun 18;116(12):2346-2355. doi: 10.1016/j.bpj.2019.04.036. Epub 2019 May 11.
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 CH 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 μm in diameter) compared to large LDs (above 2 μm 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.
脂质滴（LDs）存在于许多细胞类型中，是一种高度动态的细胞器，可储存中性脂质，主要是三酰基甘油（TAG）。随着对 LD 新功能（例如在免疫反应、蛋白质降解以及与疾病相关）的发现，需要新的方法来原位研究 LD 的化学成分。我们提出了一种使用无标记相干拉曼显微镜原位定量分析 TAG 的方法，该方法允许在具有亚微米空间分辨率的不同生物化学复杂样本中解析 LD 的 TAG 组成。使用一组标准的 TAG，我们生成了一个光谱训练矩阵，该矩阵捕获了由 TAG 主链、链长和每链双键数以及蛋白质或其他稀释分子的存在引起的拉曼光谱的变化。将我们的拟合方法与标准 TAG 和食用油混合物的气相色谱测量进行比较，我们发现预测 TAG 化学的均方根误差为 0.69 CH 和 0.15 #C=C。当进展到更复杂的样本，如油乳液和各种真核细胞中的 LD 时，我们发现与批量气相色谱测量结果吻合较好。对于分化的脂肪细胞，我们发现与大 LD（直径大于 2 μm）相比，小 LD（直径小于 2 μm）中的双键数量显著增加。这种方法与相对有限的样品制备要求相结合，应该能够为各种细胞生物学和技术应用提供快速准确的 TAG LD 分析。
