Chen Deying, Zhao Shuang, Han Wei, Lo Elvis, Su Xiaoling, Li Liang, Li Lanjuan
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Department of Chemistry, University of Alberta, Edmonton, Canada.
J Mass Spectrom. 2021 Apr;56(4):e4589. doi: 10.1002/jms.4589. Epub 2020 Jun 11.
Metabolomics study of a biological system often involves the analysis of many comparative samples over a period of several days or weeks. This process of long-term sample runs can encounter unexpected instrument drifts such as small leaks in liquid chromatography-mass spectrometry (LC-MS), degradation of column performance, and MS signal intensity change. A robust analytical method should ideally tolerate these instrumental drifts as much as possible. In this work, we report a case study to demonstrate the high tolerance of differential chemical isotope labeling (CIL) LC-MS method for quantitative metabolome analysis. In a study of using a rat model to examine the metabolome changes during rheumatoid arthritis (RA) disease development and treatment, over 468 samples were analyzed over a period of 15 days in three batches. During the sample runs, a small leak in LC was discovered after a batch of analyses was completed. Reanalysis of these samples was not an option as sample amounts were limited. To overcome the problem caused by the small leak, we applied a method of retention time correction to the LC-MS data to align peak pairs from different runs with different degrees of leak, followed by peak ratio calculation and analysis. Herein, we illustrate that using C-/ C-peak pair intensity values in CIL LC-MS as a measurement of concentration changes in different samples could tolerate the signal drifts, while using the absolute intensity values (ie, C-peak as in conventional LC-MS) was not as reliable. We hope that the case study illustrated and the method of overcoming the small-leak-caused signal drifts can be helpful to others who may encounter this kind of situation in long-term sample runs.
对生物系统进行代谢组学研究通常需要在几天或几周的时间内分析许多比较样本。这种长期样本运行过程可能会遇到意想不到的仪器漂移,例如液相色谱 - 质谱联用仪(LC-MS)中的小泄漏、色谱柱性能下降以及质谱信号强度变化。理想情况下,一种强大的分析方法应尽可能容忍这些仪器漂移。在这项工作中,我们报告了一个案例研究,以证明差异化学同位素标记(CIL)LC-MS方法在定量代谢组分析中的高耐受性。在一项使用大鼠模型研究类风湿性关节炎(RA)疾病发展和治疗过程中代谢组变化的研究中,在15天内分三批分析了超过468个样本。在样本运行期间,一批分析完成后发现液相色谱有小泄漏。由于样本量有限,重新分析这些样本不是一个可行的选择。为了克服小泄漏引起的问题,我们对LC-MS数据应用了保留时间校正方法,以对齐来自不同运行且泄漏程度不同的峰对,然后进行峰比计算和分析。在此,我们表明,在CIL LC-MS中使用C-/C-峰对强度值作为不同样本中浓度变化的度量可以容忍信号漂移,而使用绝对强度值(即传统LC-MS中的C-峰)则不太可靠。我们希望所阐述的案例研究以及克服小泄漏引起的信号漂移的方法能够对其他在长期样本运行中可能遇到这种情况的人有所帮助。