Genetics and quantum chemistry as tools for unknown metabolite identification

总体而言：我们的项目结合了遗传模式生物的显著优势，复杂的途径 映射工具，高通量和准确的量子化学（QM），以及最先进的实验 测量.这将为未知化合物的鉴定提供一种高效、经济的方法 代谢组学，这是这个不断发展的医学科学领域面临的主要限制之一。 秀丽隐杆线虫在这项研究中有几个优势，包括超过10，000个可用的遗传基因， 突变体，成熟的CRISPR/Cas9技术，以及一组超过500种野生C.秀丽线虫分离株， 完整的基因组C的一半。线虫基因与人类疾病基因有同源性， 微生物是一个杰出的选择，以提高我们对人类疾病代谢途径的理解。我们 将开发一个自动化的样品制备管道，以重复测量成千上万的 我们将使用野生分离株进行代谢组范围的遗传学研究， 关联研究（m-GWAS）和SEM路径，使用偏相关来定位路径中的未知数。的 将通过测量UHPLC-MS/MS数据检测未知代谢物与特定途径的相关性 基因突变体的基因。分子式和途径信息将作为输入， 自动化的量子力学计算所有可能的结构，这将用于准确地 计算将与实验数据匹配的NMR化学位移。正确的结构将是 通过将它们与相同化合物的2D NMR数据进行比较来验证。经验证的计算结构 然后将用于改进基于QM的MS/MS片段预测，使用实验UHPLC-MS/MS 数据 该项目将增强蠕虫和模式生物以外的许多科学领域。首先，C. elegans是 最简单的动物模型，与其他动物和人类具有显著的同源性。我们的发现 代谢途径中的制造将对几种人类疾病的研究产生直接影响。二是我们 这种方法可以高度转移到其他遗传系统，并且只需很少的修改就可以应用于许多 其他应用。也许最重要的是与大规模人类精准医学研究的相关性。 野生C。线虫分离株是具有不同基因组的“个体”，是自然种群的模型 例如人类。的确，我们使用的是突变动物， 医学研究，但突变体主要用于验证完全由野生型构建的途径， 隔离数据。一旦这些方法得到充分开发和验证，突变体将不再是必要的。C. 线虫和其他遗传模式生物在现代基因组学的发展中起了重要作用， DNA测序技术。我们的前提是，蠕虫将在代谢组学方面产生类似的影响。

Overall: Our project combines the significant advantages of a genetic model organism, sophisticated pathway mapping tools, high-throughput and accurate quantum chemistry (QM), and state-of-the-art experimental measurements. The result will be an efficient and cost-effective approach for unknown compound identification in metabolomics, which is one of the major limitations facing this growing field of medical science. Caenorhabditis elegans has several advantages for this study, including over 10,000 available genetic mutants, well-developed CRISPR/Cas9 technology, and a panel of over 500 wild C. elegans isolates with complete genomes. Half of C. elegans genes have homologs to human disease genes, making this model organism an outstanding choice to improve our understanding of metabolic pathways in human disease. We will develop an automated pipeline for sample preparation to reproducibly measure tens of thousands of unknown features by UHPLC-MS/MS. We will use the wild isolates to conduct metabolome-wide genetic association studies (m-GWAS), and SEM-path to locate unknowns in pathways using partial correlations. The relevance of the unknown metabolites to specific pathways will be tested by measuring UHPLC-MS/MS data from genetic mutants of those pathways. Molecular formula and pathway information will be the inputs for automated quantum mechanical calculations of all possible structures, which will be used to accurately calculate NMR chemical shifts that will be matched to experimental data. The correct structures will be validated by comparing them with 2D NMR data of the same compound. The validated computed structures will then be used to improve QM-based MS/MS fragment prediction, using the experimental UHPLC-MS/MS data. This project will enhance many areas of science beyond worms and model organisms. First, C. elegans is the simplest animal model available with significant homology to other animals and humans. The discoveries we make in metabolic pathways will have a direct impact on studies of several human diseases. Second, our approach is highly transferable to other genetic systems and with little modification can be applied to many other applications. Perhaps most important is the relevance to large-scale human precision medicine studies. The wild C. elegans isolates are “individuals” with diverse genomes that are a model for natural populations such as humans. It is true that we are using mutant animals that would not be available in a human precision medicine study, but the mutants are used primarily to validate pathways that are constructed entirely by wild isolate data. Once the approaches are fully developed and validated, the mutants will not be necessary. C. elegans and other genetic model organisms were instrumental in the development of modern genomics and DNA sequencing technologies. Our premise is that the worm will have a comparable impact in metabolomics.