Shu Chien-Gene Lay Dept. of Bioengineering, University of California San Diego, La Jolla, CA, USA.
Dept. of Neurology, Northwestern University School of Medicine, Chicago, IL, USA.
Nat Commun. 2024 Feb 21;15(1):1599. doi: 10.1038/s41467-024-45576-6.
Lipids play crucial roles in many biological processes. Mapping spatial distributions and examining the metabolic dynamics of different lipid subtypes in cells and tissues are critical to better understanding their roles in aging and diseases. Commonly used imaging methods (such as mass spectrometry-based, fluorescence labeling, conventional optical imaging) can disrupt the native environment of cells/tissues, have limited spatial or spectral resolution, or cannot distinguish different lipid subtypes. Here we present a hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. Using this platform, we visualize and identify high density lipoprotein particles in human kidney, a high cholesterol to phosphatidylethanolamine ratio inside granule cells of mouse hippocampus, and subcellular distributions of sphingosine and cardiolipin in human brain. Our PRM-SRS displays unique advantages of enhanced chemical specificity, subcellular resolution, and fast data processing in distinguishing lipid subtypes in different organs and species.
脂质在许多生物过程中起着至关重要的作用。绘制空间分布图谱并研究细胞和组织中不同脂质亚型的代谢动力学，对于更好地理解它们在衰老和疾病中的作用至关重要。常用的成像方法（如基于质谱的方法、荧光标记、传统光学成像）可能会破坏细胞/组织的天然环境，空间或光谱分辨率有限，或者无法区分不同的脂质亚型。在这里，我们展示了一种基于惩罚参考匹配算法和受激拉曼散射（PRM-SRS）显微镜的高光谱成像平台。利用该平台，我们可视化并鉴定了人肾脏中的高密度脂蛋白颗粒、小鼠海马颗粒细胞中胆固醇与磷脂酰乙醇胺比值较高的颗粒内的物质，以及人脑中神经酰胺和心磷脂的亚细胞分布。我们的 PRM-SRS 在区分不同器官和物种中的脂质亚型方面具有增强的化学特异性、亚细胞分辨率和快速数据处理的独特优势。
