New Advances in Capillary Electrophoresis-Mass Spectrometry for Metabolomics: Multiplexed Separations for Biomarker Discovery

代谢组学毛细管电泳质谱新进展：生物标志物发现的多重分离

• 批准号: RGPIN-2014-03987
• 负责人: BritzMcKibbin, Philip
• 金额: $ 3.93万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=610765
• 关键词: New; Advances; Capillary; Electrophoresis; Mass

Metabolomics refers to the comprehensive analysis of low molecular weight compounds (i.e., metabolites) that exist in an organism, cell or biological specimen, such as blood. Since metabolites act as "real-world" molecular endpoints of gene expression that reflect environment, untargeted metabolite profiling (i.e., metabolomics) offers a promising way to make scientific discoveries relevant to human health, such as diagnostic biomarkers for early detection and treatment of diseases. However, new analytical strategies are needed due to the chemical diversity and wide concentration range of "the metabolome" that remains largely uncharacterized in complex biological samples. Our laboratory will make important contributions to fundamental research using state-of-the-art capillary electrophoresis-mass spectrometry (CE-MS) technology that address several major obstacles in metabolomics, namely its low sample throughput, poor sensitivity and/or limited selectivity. Our proposal will develop an innovative metabolomics workflow for biomarker discovery based on multiplexed separations that will bridge the major gap existing between sample throughput and data fidelity. Sample throughput is limited when using conventional MS-based separation platforms due time requirements for solute elution and column pre-conditioning when analyzing "one sample at a time". Thus, major efforts are devoted to quality assurance and data pre-processing to correct for long-term instrumental drift that is time-consuming and subject to bias. To address these challenges, our research will develop multi-segment injection (MSI)-CE-MS based on serial injection of seven or more discrete sample segments "within a single capillary" as a way to increase sample throughput for large-scale metabolomic studies without added infrastructure or operating costs. This method offers an unprecedented strategy to encode information temporally with sample throughput analogous to direct infusion-ESI-MS (3 min/sample) while retaining all the benefits of a high efficiency separation. Our research will implement non-aqueous MSI-CE-MS in conjunction with chemoselective derivatization reactions to dramatically expand metabolome coverage with exquisite selectivity and sensitivity. Also, a multivariate model will be used to accurately predict ion migration and ionization responses for various classes of metabolites and their derivatives for unambiguous identification and quantification of unknown compounds of clinical relevance (e.g., biomarkers) in cases when authentic standards do not exist. Notably, an accelerated metabolomics workflow for biomarker discovery will be developed when using MSI-CE-MS in order to elucidate differential responses to lifestyle interventions that elicit positive health benefits for type 2 diabetes prevention, as well as diagnostic biomarkers that can be used to confirm the onset of stroke or provide better ways to test for cystic fibrosis. In all cases, customized injection sequences in MSI-CE-MS will be designed to reject spurious data and reduce false discoveries as a way to enhance data quality for translation of scientific discoveries into clinical practice. In summary, no other instrumental technique offers such a diverse array of analytical merits for metabolomics (e.g., high sample throughout, high data quality, low infrastructure costs) that will lead to new advances in clinical diagnostics and personalized medicine.

代谢组学是指对存在于生物体、细胞或生物标本(如血液)中的低分子化合物(即代谢物)进行综合分析。由于代谢物是反映环境的基因表达的“真实世界”分子终点，非靶向代谢物图谱(即代谢组学)为做出与人类健康相关的科学发现提供了一条很有前途的途径，例如用于疾病早期发现和治疗的诊断生物标志物。然而，由于“代谢物”的化学多样性和广泛的浓度范围，需要新的分析策略，而这些代谢物在复杂的生物样品中仍未得到很大程度的表征。我们的实验室将使用最先进的毛细管电泳质谱(CE-MS)技术为基础研究做出重要贡献，该技术解决了代谢组学中的几个主要障碍，即样品吞吐量低、灵敏度差和/或选择性有限。我们的提案将开发一种创新的代谢组学工作流程，用于基于多重分离的生物标记物发现，这将弥合样本吞吐量和数据保真度之间存在的主要差距。 当使用传统的基于MS的分离平台时，由于分析“一次一个样品”时对溶质洗脱和柱预调节的时间要求，样品吞吐量受到限制。因此，主要致力于质量保证和数据预处理，以纠正长期的仪器漂移，这种漂移既耗时又容易产生偏差。为了应对这些挑战，我们的研究将开发基于连续进样的多段进样(MSI)-CE-MS，即“在一根毛细管内”连续进样七个或更多离散的样品段，作为一种在不增加基础设施或运营成本的情况下增加大规模代谢组研究的样品吞吐量的方法。这种方法提供了一种前所未有的策略，可以利用样品吞吐量对信息进行临时编码，类似于直接输注-ESI-MS(3分钟/样品)，同时保留了高效分离的所有好处。我们的研究将结合化学选择性衍生化反应实现非水MSI-CE-MS，以极高的选择性和灵敏度极大地扩大代谢组的覆盖面。此外，多变量模型将用于准确预测各类代谢物及其衍生物的离子迁移和电离反应，以便在没有可信标准的情况下明确识别和量化与临床相关的未知化合物(例如，生物标志物)。值得注意的是，在使用MSI-CE-MS时，将开发生物标记物发现的加速代谢组学工作流程，以阐明对生活方式干预的不同反应，这些干预措施对预防2型糖尿病产生积极的健康益处，以及可用于确认中风发作或提供更好的囊性纤维化测试方法的诊断生物标记物。在所有情况下，MSI-CE-MS中的定制注射序列将被设计为拒绝虚假数据和减少虚假发现，以此作为一种提高将科学发现转化为临床实践的数据质量的方式。总之，没有其他仪器技术为代谢组学提供如此多样化的分析优点(例如，高样本吞吐量、高数据质量、低基础设施成本)，这将导致临床诊断和个性化医学的新进展。