Improved Metabolite ID by Cross-Platform HPLC Retention-Augmented MS Analysis

描述(由申请人提供)：高效液相色谱仪是所有生物科学中的重要工具。在代谢组学方面，高效液相色谱已演变为与质谱仪(MS)相结合的核心技术。代谢组学已经有助于更好地了解糖尿病、胰岛素抵抗和心血管疾病，并导致了癌症早期检测的生物标志物的发现。然而，这一领域的进一步进展在很大程度上取决于分析仪器的进步，这将改善对大量代谢物的识别。高效液相色谱保留值是一种与MS数据非常正交的特定化学指标。不幸的是，在代谢组学中，它在很大程度上没有被使用，因为LC保留的机制很复杂，更重要的是，梯度洗脱保留时间非常依赖于不同高效液相仪器之间的许多差异。初步工作表明，将LC保留数据与MS精确质量结合使用，显著提高了分析物识别概率；使用低端LC-单四极杆MS，明确识别从88(7,307个未知数)上升到3,232个-提高了LC-FTICR MS对相同未知数的识别能力。在这项建议中，一个新的方法，以建立一个强大的高效液相色谱保留数据库，以及一个新的保留“投影”系统。该系统使用一组精选的30种标准溶质的保留时间，添加到样品中来反算有效梯度和流速曲线，从而得出这些保留时间。然后，这些曲线可以用来以前所未有的精度计算其他化合物的保留值。它们解释了高效液相色谱仪器、梯度、流速和柱尺寸之间的差异。此外，我们将扩展该系统以解决保留漂移随柱老化而产生的问题。这一易于使用的保留投影系统精确度为0.23%的梯度时间(例如，在20分钟的梯度中为2.8秒)。有三个具体目标：1)选择一组最优的标准固定相和校正溶质，并确定高效液相保留投影系统的最终准确度；2)制定建立和使用保留数据库的标准方案，并在多个实验室/操作员之间确定投影系统的重现性；以及3)生成1,000个代谢物保留数据库，并确定其用于LC-MS鉴定代谢物的价值。由于其高准确度、广泛的适用性和易用性，高效液相保留投影系统将大大加速代谢组学和相关领域的研究，这些领域依赖于LC-MS识别未知数。这些领域在人类疾病的病因、诊断、预防和治疗方面即将有非凡的发现。该系统将提供比低端LC-MS仪器更强的识别能力，显著扩大能够进行这些尖端实验的实验室的基础。

DESCRIPTION (provided by applicant): High Performance Liquid Chromatography (HPLC) is a vital tool in all biological sciences. In metabolomics, HPLC has evolved to become, in conjunction with mass spectrometry (MS), the central technique. Metabolomics has already contributed to a greater understanding of diabetes, insulin resistance, and cardiovascular disease, and has lead to the discovery of biomarkers for early detection of cancer. However, further advances in this field are heavily dependent on advances in analytical instrumentation that will improve identification of large numbers of metabolites. HPLC retention is a chemically-specific metric that is very orthogonal to MS data. Unfortunately, in metabolomics it has largely gone unused because the mechanism of LC retention is complex and more importantly, gradient elution retention times are very dependent on many differences between HPLC instruments. Preliminary work shows that use of LC retention data in combination with MS exact mass dramatically improves analyte identification probability; using a low-end LC-single quadrupole MS, unambiguous identifications rose from 88 (of 7,307 unknowns) to 3,232-bettering the identification power of LC-FTICR MS on the same set of unknowns. In this proposal, a novel approach to a robust HPLC retention database is outlined along with a novel retention "projection" system. This system uses the retention times of a set of 30 judiciously chosen standard solutes spiked into the sample to back-calculate what the effective gradient and flow rate profiles must have been to give those retention times. Those profiles can then be used to calculate the retention of other compounds with unprecedented accuracy. They account for differences between HPLC instruments, gradients, flow rates, and column dimensions. Additionally, we will extend the system to account for retention drift with column aging. This easy-to-use retention projection system is accurate to ¿0.23% of the gradient time (e.g. ¿2.8 seconds in a 20 min gradient). There are three specific aims: 1) Select an optimal set of standard stationary phases and calibration solutes and determine the ultimate accuracy of the HPLC retention projection system, 2) Develop standard protocol for building and using the retention database and determine the reproducibility of the projection system among multiple labs/operators, and 3) Generate a 1,000 metabolite retention database and determine its value for metabolite identification by LC-MS. Due to its high accuracy, wide applicability, and ease of use, the HPLC retention projection system will considerably accelerate research in metabolomics and related fields that rely on the identification of unknowns by LC-MS. Such fields are on the brink of extraordinary discoveries in the causes, diagnosis, prevention, and cure of human diseases. This system will offer far more identification power out of even low-end LC-MS instruments, significantly broadening the base of labs capable of performing these cutting-edge experiments.