Analytical Resources Core, Bioanalysis and Omics Center, Colorado State University, Fort Collins, Colorado 80523, United States.
Waters Corporation, Milford, Massachusetts 01757, United States.
J Am Soc Mass Spectrom. 2021 Mar 3;32(3):661-669. doi: 10.1021/jasms.0c00375. Epub 2021 Feb 4.
Metabolomics is a powerful phenotyping platform with potential for high-throughput analyses. The primary technology for metabolite profiling is mass spectrometry. In recent years, the coupling of mass spectrometry with ion mobility spectrometry (IMS) has offered the promise of faster analysis time and greater resolving power. Our understanding of the potential impact of IMS on the field of metabolomics is limited by availability of comprehensive experimental data. In this analysis, we use a probabilistic approach to enumerate the strengths and limitations, the present and future, of this technology. This is accomplished through use of "model" metabolomes, predicted physicochemical properties, and probabilistic descriptions of resolving power. This analysis advances our understanding of the importance of orthogonality in resolving (separation) dimensions, describes the impact of the metabolome composition on resolution demands, and offers a system resolution landscape that may serve to guide practitioners in the coming years.
代谢组学是一个强大的表型平台，具有高通量分析的潜力。代谢物分析的主要技术是质谱。近年来，质谱与离子淌度谱（IMS）的结合有望实现更快的分析时间和更高的分辨率。我们对 IMS 对代谢组学领域的潜在影响的理解受到全面实验数据的限制。在这项分析中，我们使用概率方法来列举该技术的优势和局限性、现在和未来。这是通过使用“模型”代谢组、预测的物理化学性质和分辨率的概率描述来实现的。这项分析增进了我们对正交性在（分离）维度分辨率中的重要性的理解，描述了代谢组组成对分辨率要求的影响，并提供了一个系统分辨率景观，可能有助于指导从业者在未来几年的工作。
