Interlaboratory Comparison of Untargeted Mass Spectrometry Data Uncovers Underlying Causes for Variability

质谱法 轨道轨道 主成分分析 数据集 质量 代谢组学 样品(材料) 化学 分析化学(期刊) 质谱 色谱法 计算机科学 人工智能
作者
Trevor N. Clark,Joëlle Houriet,Warren S. Vidar,Joshua J. Kellogg,Daniel A. Todd,Nadja B. Cech,Roger G. Linington
出处
期刊:Journal of Natural Products [American Chemical Society]
卷期号:84 (3): 824-835 被引量:40
标识
DOI:10.1021/acs.jnatprod.0c01376
摘要

Despite the value of mass spectrometry in modern natural products discovery workflows, it remains very difficult to compare data sets between laboratories. In this study we compared mass spectrometry data for the same sample set from two different laboratories (quadrupole time-of-flight and quadrupole-Orbitrap) and evaluated the similarity between these two data sets in terms of both mass spectrometry features and their ability to describe the chemical composition of the sample set. Somewhat surprisingly, the two data sets, collected with appropriate controls and replication, had very low feature overlap (25.7% of Laboratory A features overlapping 21.8% of Laboratory B features). Our data clearly demonstrate that differences in fragmentation, charge state, and adduct formation in the ionization source are a major underlying cause for these differences. Consistent with other recent literature, these findings challenge the conventional wisdom that electrospray ionization mass spectrometry (ESI-MS) yields a simple one-to-one correspondence between analytes in solution and features in the data set. Importantly, despite low overlap in feature lists, principal component analysis (PCA) generated qualitatively similar PCA plots. Overall, our findings demonstrate that comparing untargeted metabolomics data between laboratories is challenging, but that data sets with low feature overlap can yield the same qualitative description of a sample set using PCA.
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