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

通过跨平台 HPLC 保留增强 MS 分析改进代谢物 ID

• 批准号: 8452164
• 负责人: Paul G Boswell
• 金额: $ 31.77万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-02 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8452164
• 关键词: Accounting; Age; Aging; Algorithms; Back; Biochemical; Biological; Biological Markers; Biological Sciences; Blood; Calibration; Carbohydrates; Cardiovascular Diseases; Chemicals; Clinical; Complement; Complex; Computer software; Data; Databases; Detection; Development; Diabetes Mellitus; Diagnosis; Dimensions; Drops; Fourier transform ion cyclotron resonance; Freedom; High Pressure Liquid Chromatography; Human; Insulin Resistance; Isomerism; Laboratories; Lead; Libraries; Lipids; Malignant Neoplasms; Mass Spectrum Analysis; Methodology; Metric; Modeling; Phase; Prevention; Probability; Proteins; Protocols documentation; Relative (related person); Reporting; Reproducibility; Research; Research Personnel; Rosa; Sampling; Science; Screening for cancer; Source; Stereoisomer; Steroids; System; Techniques; Time; Tissues; Urine; Work; analytical tool; base; biological research; cost; human disease; improved; indexing; instrument; instrumentation; metabolomics; novel; novel strategies; programs; research study; small molecule; solute; sound; sugar; theories; tool

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.

描述（由申请人提供）：高效液相色谱法（HPLC）是所有生物科学中的重要工具。在代谢组学中，HPLC与质谱（MS）一起发展成为核心技术。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，并导致发现早期检测癌症的生物标志物。然而，这一领域的进一步发展在很大程度上取决于分析仪器的进步，这将改善大量代谢物的鉴定。 HPLC保留是一种与MS数据非常正交的化学特异性指标。不幸的是，在代谢组学中，它在很大程度上未被使用，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HPLC仪器之间的许多差异。初步工作表明，使用LC保留数据结合MS精确质量大大提高了分析物鉴定概率;使用低端LC-单四极杆MS，明确的鉴定从88（7，307个未知物）上升到3，232-提高了LC-FTICR MS对同一组未知物的鉴定能力。在这个建议中，一个新的方法，一个强大的HPLC保留数据库概述沿着与一个新的保留“投影”系统。该系统使用一组30个加标到样品中的明智选择的标准溶质的保留时间来反算有效梯度和流速曲线必须是什么才能给出这些保留时间。然后，这些曲线可以用于计算其他化合物的保留，具有前所未有的准确性。它们解释了HPLC仪器、梯度、流速和色谱柱尺寸之间的差异。此外，我们将扩展该系统，以考虑色谱柱老化的保留漂移。这种易于使用的保留投影系统精确到梯度时间的<$0.23%（例如，在20分钟梯度中为<$2.8秒）。 有三个具体目标：1）选择一组最佳的标准固定相和校准溶质，并确定HPLC保留投影系统的最终准确度，2）开发用于构建和使用保留数据库的标准方案，并确定投影系统在多个实验室/操作员之间的再现性，以及3）生成1，000代谢物保留数据库，并确定其对LC-MS代谢物鉴定的价值。由于其准确性高，适用性广，使用方便，HPLC保留投影系统将大大加速代谢组学和相关领域的研究，这些领域依赖于通过LC-MS识别未知物。这些领域即将在病因，诊断，预防和治疗人类疾病。该系统将提供比低端LC-MS仪器更强大的识别能力，大大扩大了能够进行这些尖端实验的实验室的基础。