Identification and tracking of neural stem cells in vivo: a metabolomic approach

体内神经干细胞的识别和追踪：代谢组学方法

• 批准号: 7145549
• 负责人: MIRJANA MALETIC-SAVATIC
• 金额: $ 20.93万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-15 至 2008-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7145549
• 关键词: brain; cell type; human; hydrogen ions; metabolomics; stem cells; tissues

DESCRIPTION (provided by applicant): The ability to identify human neural stem cells (NSC) by brain imaging may have profound implications for diagnostic, prognostic, and therapeutic purposes. Currently, there are no clinical, high-resolution imaging techniques that enable investigations of the survival, migration, fate, and function of unlabeled NSC and their progeny. The study of human NSC in vivo is hindered by the absence of well-defined markers that can distinguish them from other neural cell types. The goal of this proposal is to define markers of NSC by characterizing metabolomic fingerprint of NSC both in vitro and in vivo. Our objectives are to develop novel imaging and signal processing methodologies that would enable non-invasive investigations of NSC behavior in healthy and disease states, from early human development to older age. We hypothesize that mammalian NSC have a specific metabolic marker that can be identified by spectroscopy. Our specific aims are: 1) to characterize a metabolomic fingerprint of NSC in vitro using proton nuclear magnetic resonance (1H-NMR) spectroscopy and to compare it to the neuronal and glial 1H-NMR fingerprints; 2) to develop high resolution proton MR spectroscopy (1H-MRS) acquisition protocols that will allow for characterization of the NSC fate in vivo; 3) to develop signal processing algorithms that will provide accurate estimates of cell densities even from data with low signal-to-noise ratio and limited spectral, spatial, and temporal resolutions. Our preliminary experiments have demonstrated that we are able to identify the NSC on the basis of their 1H-NMR metabolomic fingerprint. In addition, we can detect both endogenous and exogenous NSC in the living rat brain, using 1H-MRS and 9.4T mMRI scanner. We plan to further characterize the metabolomic signature of NSC and other neural cell types, and to further perform metabolomic profiling of the living rat brain. The signal processing algorithms for identification, quantification, and tracking of NSC in vivo will be based on singular value decomposition methodology and will exploit prior knowledge gained from in vitro experiments. This innovative research will not only demonstrate the feasibility of using 1H-MRS spectroscopy for metabolomic investigations in vivo, but will also lead to a breakthrough in the field of stem cell research. Most importantly, this research is an essential prerequisite for future clinical investigations of NSC. The ability to monitor the fundamental changes of the NSC in the human brain will instigate new studies of neurological disorders where NSC pathology might contribute to the etiology of the disease and will initiate developments of new treatments. The proposed research is intrinsically multidisciplinary and involves collaborations of neuroscientists, physicists, engineers, chemists, and imaging scientists. Each of them will provide unique yet complementary expertise and resources available at the Stony Brook University and Brookhaven National Laboratory.

描述（由申请人提供）：通过脑成像识别人类神经干细胞（NSC）的能力可能对诊断、预后和治疗目的具有深远的影响。 目前，还没有临床高分辨率成像技术能够研究未标记的 NSC 及其后代的生存、迁移、命运和功能。 由于缺乏可将人类 NSC 与其他神经细胞类型区分开来的明确标记，阻碍了人类 NSC 的体内研究。 该提案的目标是通过表征 NSC 体外和体内代谢组指纹来定义 NSC 标记物。 我们的目标是开发新颖的成像和信号处理方法，从而能够对从人类早期发育到老年的健康和疾病状态下的 NSC 行为进行非侵入性研究。 我们假设哺乳动物 NSC 具有可以通过光谱法识别的特定代谢标记。 我们的具体目标是：1) 使用质子核磁共振 (1H-NMR) 光谱表征 NSC 的体外代谢组指纹，并将其与神经元和神经胶质的 1H-NMR 指纹进行比较； 2) 开发高分辨率质子磁共振波谱 (1H-MRS) 采集方案，以表征 NSC 在体内的命运； 3）开发信号处理算法，即使根据低信噪比和有限的光谱、空间和时间分辨率的数据，也能准确估计细胞密度。 我们的初步实验表明，我们能够根据 1H-NMR 代谢组指纹识别 NSC。 此外，我们可以使用 1H-MRS 和 9.4T mMRI 扫描仪检测活体大鼠大脑中的内源性和外源性 NSC。 我们计划进一步表征 NSC 和其他神经细胞类型的代谢组学特征，并进一步对活体大鼠大脑进行代谢组学分析。 用于体内 NSC 识别、量化和跟踪的信号处理算法将基于奇异值分解方法，并将利用从体外实验中获得的先验知识。 这项创新研究不仅将证明使用 1H-MRS 光谱进行体内代谢组学研究的可行性，而且还将在干细胞研究领域带来突破。 最重要的是，这项研究是未来 NSC 临床研究的重要先决条件。 监测人脑中 NSC 基本变化的能力将引发对神经系统疾病的新研究，其中 NSC 病理学可能有助于该疾病的病因学，并将启动新疗法的开发。 拟议的研究本质上是多学科的，涉及神经科学家、物理学家、工程师、化学家和成像科学家的合作。 他们每个人都将提供石溪大学和布鲁克海文国家实验室独特但互补的专业知识和资源。