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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=632616
• 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.

代谢组学是指对低分子量化合物（即，代谢物）存在于生物体、细胞或生物样本（例如血液）中。由于代谢物充当反映环境的基因表达的“真实世界”分子终点，因此非靶向代谢物谱分析（即，代谢组学）提供了一种有希望的方法，使科学发现与人类健康有关，如诊断生物标志物，用于早期发现和治疗疾病。然而，新的分析策略是必要的，由于化学多样性和广泛的浓度范围内的“代谢物组”，仍然在很大程度上不确定的复杂的生物样品。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，即低样品通量，低灵敏度和/或有限的选择性。我们的建议将开发一个创新的代谢组学工作流程的生物标志物发现的基础上，多路复用分离，将弥合样品通量和数据fidelity.Sample之间存在的主要差距时，使用传统的MS为基础的分离平台时，由于溶质洗脱和柱预处理的时间要求时，分析“一个样品在一个时间”的样品通量是有限的。因此，主要的努力是致力于质量保证和数据预处理，以纠正长期的仪器漂移，这是耗时和受偏见。为了应对这些挑战，我们的研究将开发多段进样（MSI）-CE-MS，该技术基于“在单个毛细管内”连续进样7个或更多离散样品段，作为一种在不增加基础设施或运营成本的情况下提高大规模代谢组学研究样品通量的方法。该方法提供了一种前所未有的策略，以类似于直接注入-ESI-MS（3分钟/样品）的样品通量对信息进行时间编码，同时保留了高效分离的所有优点。我们的研究将实施非水MSI-CE-MS结合化学选择性衍生反应，以极大地扩大代谢组覆盖范围，具有精致的选择性和灵敏度。此外，多变量模型将用于准确预测各种代谢物及其衍生物的离子迁移和电离响应，以明确识别和定量具有临床相关性的未知化合物（例如，生物标志物）。值得注意的是，当使用MSI-CE-MS时，将开发用于生物标志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差异反应，这些干预对2型糖尿病预防产生积极的健康益处，以及可用于确认中风发作的诊断生物标志物或提供更好的方法来测试囊性纤维化。在所有情况下，MSI-CE-MS中的定制进样序列将被设计为拒绝虚假数据并减少错误发现，以提高将科学发现转化为临床实践的数据质量。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，高采样率、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疗的新进展。