Integrated Chemoselective and Informatic Platform for Large-Scale Metabolomics

描述(申请人提供)：代谢组学技术的最新进展，特别是那些结合了质谱学(MS)和核磁共振谱(核磁共振)的互补技术，使快速分析代表数百种代谢物的数千个峰成为可能。然而，大规模代谢组学应用的关键障碍仍然存在，最显著的是：更高的产量和强大的代谢物分配和量化；未知代谢物的鉴定；低丰度/不稳定代谢物的分析；以及代谢网络和调控的重建。在这里，我们提出了一种综合的方法，使用关键代谢物官能团的化学选择性(CS)标记来提高代谢物识别的速度和准确性，并增强检测。这种标记的代谢物本身就适合通过稳定的同位素编码进行多重分析和可靠的相对定量。这一方法将加快分析吞吐量，同时扩大分析物的类别，包括代谢浓缩的同位素制剂，远远超出目前的限制。我们将通过以下具体目标实现我们的目标：SA1。为了开发针对官能团标记代谢物的CS探针：将开发基于疏水季铵(QA)的CS探针，用于标记代谢物中的羰基、氨基、硫醇和二醇官能团(FG)，优化了直接进样FT-ICR-MS检测和分配；SA2。开发一套同位素编码的CS探针，用于代谢物的鉴定和FT-ICR-MS和核磁共振的多重定量：开发13C编码的QA-CS探针将有助于通过13C编辑的2D NMR和FT-ICR-MS进行代谢物的综合结构分析，并通过FT-ICR-MS进行多重分析；SA3.为了开发用于大规模CS加合物代谢物指定和路径重建的基于网络的软件：将基于同位素集团、FG轮廓和分子式(MF)开发用于代谢物和标记同位素的稳健自动MS指定的算法。核磁共振衍生的亚结构&MF将与MS数据相结合，用于半自动指定代谢物等同分异构体和未知物。将完善原子分辨的人体代谢数据库，并开发基于标记代谢物图谱的途径重建工具；SA4。为了在三个基本和翻译项目中展示集成的CS图谱和生物化学信息学方法：将使用新开发的CS标记化学和自动分配工具增强的稳定同位素分辨代谢组学(SIRM)绘制由癌基因缺陷或酶缺失驱动的人类肺癌和肾癌的代谢重编程图谱。我们的长期目标是破译人类疾病代谢网络，以用于药物发现和早期诊断。

DESCRIPTION (provided by applicant): Recent advances in metabolomics technologies, especially those that combine the complementarily of mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) enables rapid analysis of thousands of peaks representing hundreds of metabolites. Yet, key barriers remain for large-scale metabolomics applications, most notably: even higher throughput with robust metabolite assignment and quantification; identification of unknown metabolites; analysis of low abundance/labile metabolites; and reconstruction of metabolic networks and regulation. Here, we propose an integrated approach that uses chemoselective (CS) tagging of key metabolite functional groups to boost the speed and accuracy of metabolite identification and enhance detection. Such tagged metabolites are inherently amenable for multiplexed analysis and reliable relative quantification via stable isotope encoding. This approach will accelerate analytical throughput while widening the classes of analytes, including metabolically enriched isotopologues, far beyond current limits. We will achieve our goals via the following specific aims: SA1. To develop CS probes for tagging metabolites by targeting functional groups: Hydrophobic quaternary ammonium (QA)-based CS probes will be developed for tagging carbonyl, amino, thiol, & diol functional groups (FG) in metabolites, optimized for direct infusion FT- ICR-MS detection & assignment; SA2. To develop a set of isotope-encoded CS probes for metabolite identification and multiplexed quantification by FT-ICR-MS and NMR: Developing 13C-encoded QA-CS probes will facilitate integrated structural analysis of metabolites by 13C edited 2D NMR and FT-ICR-MS, & multiplexed analysis by FT-ICR-MS; SA3. To develop web-based software for large-scale CS-adducted metabolite assignment & pathway reconstruction: Algorithm for robust automated MS assignment of metabolite & labeled isotopologues will be developed based on isotopologue cliques, FG profile, & molecular formula (MF). NMR- derived substructure & MF will be combined with MS data for semi-automated assignment of metabolite isotopomers & unknowns. Atom-resolved human metabolic database will be refined and tools developed for pathway reconstruction based on labeled metabolite profiles; SA4. To demonstrate the integrated CS profiling and biochemo-informatic approach in three basic and translational projects: Metabolic reprogramming driven by oncogenic gene defects or enzyme deletion in human lung and kidney cancers will be mapped using Stable Isotope-Resolved Metabolomics (SIRM) enhanced by newly developed CS tagging chemistry and automated assignment tools. Our long-term goal is to decipher human disease metabolic networks for drug discovery & early diagnosis.