Sugar Probed SRS Volumetric imaging of Metabolic Activities

项目摘要 在原位可视化代谢活动对于理解许多生物过程至关重要。它 是执行遗传蓝图和维持生命的新陈代谢。糖如 葡萄糖是人类和动物的必需营养素，不仅提供能量， 也是合成蛋白质、脂质、RNA/DNA等新生物质的基石， 糖原我们提出的研究是开发和优化新一代氘代 葡萄糖（[D]-葡萄糖）探测三维体积多重受激拉曼散射（SRS） 成像平台。在目的I中，各种类型的[D]-葡萄糖，包括[D1]、[D2]、[D5]、[D 7]和[D12]-葡萄糖。 葡萄糖将被研究和优化，以可视化代谢动力学和异质性， 动物新合成的分子中的碳氘（C-D）化学键， 由于C-D标记的蛋白质、脂质、DNA/RNA、碳水化合物将在“细胞沉默”中成像， “区域”的拉曼光谱。此外，根据代谢物的不同光谱模式 来自不同的同位素体，在多个时间点的代谢物合成将是 在一个单一的图像可视化。在Aim II中，新一代增强组织清除配方 将筛选和设计用于大规模3D体积成像（20倍更深的穿透） 的[D]-葡萄糖探测动物模型中的代谢活动和异质性。在Aim III中， 将建立定制设计的光谱分解算法和协议，以最大化 检测超过20个新合成的C-D标记分子的潜力，并最大限度地减少 背景信号。我们的计算资源和算法将优化许多 用于研究器官特异性代谢的复杂高光谱成像数据集中的变量 动态性和异质性。利用资源和算法，我们将优化一个平台 将多个旧的和新合成的分子分开， 注意事项完成拟议的研究将有可能揭示机械的基本原理 与不同器官中葡萄糖代谢相关的多种分子途径。

Project Summary Visualizing metabolic activities in situ is critical to understanding many biological processes. It is the metabolism which carries out the genetic blue print and maintain life. Sugar such as glucose is an essential nutrient for human being and animals, not only provides energy, but also is building blocks for synthesizing new biomass such as protein, lipid, RNA/DNA, and glycogen. Our proposed study is to develop and optimize a new generation of deuterated glucose ([D]-glucose) probed 3D volumetric multiplex stimulated Raman scattering (SRS) imaging platform. In aim I, various types of [D]-glucose including [D1], [D2], [D5], [D7], and [D12]- glucose will be studied and optimized for visualizing metabolic dynamics and heterogeneity in animals. The carbon-deuterium (C-D) chemical bond in the newly synthesized molecules such as C-D labeled proteins, lipids, DNA/RNA, carbohydrates will be imaged in the “cell silent region” of Raman spectra. In addition, based on diverse spectral patterns of metabolites derived from different isotopologues, metabolite synthesis in multiple time points will be visualized in a single image. In Aim II, a new generation of enhanced tissue clearing recipe will be screened and designed for large scale 3D volumetric imaging (20x deeper penetration) of [D]-glucose probed metabolic activities and heterogeneity in animal models. In Aim III, custom designed spectral unmixing algorithm and protocol will be established to maximize the potential of detecting more than 20 newly synthesized C-D labeled molecules and minimize the background signal. Our computational resources and algorithms will optimize numerous variables in complicated hyperspectral imaging datasets for studying organ specific metabolic dynamics and heterogeneity. Using the resources and algorithms, we will optimize a platform to unmix multiple old and newly synthesized molecules and quantitatively dissect the in situ detritions. Completion of the proposed study will potentially reveal mechanistic fundamentals of multiple molecular pathways related to glucose metabolism in different organs.