Hao Jun-Di, Chen Yao-Yu, Wang Yan-Zhen, An Na, Bai Pei-Rong, Zhu Quan-Fei, Feng Yu-Qi
Department of Chemistry, Wuhan University, Wuhan 430072, China.
School of Public Health, Wuhan University, Wuhan 430071, China.
Anal Chem. 2023 Sep 5;95(35):13330-13337. doi: 10.1021/acs.analchem.3c02583. Epub 2023 Aug 23.
Peak alignment is a crucial step in liquid chromatography-mass spectrometry (LC-MS)-based large-scale untargeted metabolomics workflows, as it enables the integration of metabolite peaks across multiple samples, which is essential for accurate data interpretation. Slight differences or fluctuations in chromatographic separation conditions, however, can cause the chromatographic retention time (RT) shift between consecutive analyses, ultimately affecting the accuracy of peak alignment between samples. Here, we introduce a novel RT shift correction method based on the retention index (RI) and apply it to peak alignment. We synthesized a series of -acyl glycine (C2-C23) homologues via the amidation reaction between glycine with normal saturated fatty acids (C2-C23) as calibrants able to respond proficiently in both mass spectrometric positive- and negative-ion modes. Using these calibrants, we established an -acyl glycine RI system. This RI system is capable of covering a broad chromatographic space and addressing chromatographic RT shift caused by variations in flow rate, gradient elution, instrument systems, and LC separation columns. Moreover, based on the RI system, we developed a peak shift correction model to enhance peak alignment accuracy. Applying the model resulted in a significant improvement in the accuracy of peak alignment from 15.5 to 80.9% across long-term data spanning a period of 157 days. To facilitate practical application, we developed a Python-based program, which is freely available at https://github.com/WHU-Fenglab/RI-based-CPSC.
峰对齐是基于液相色谱 - 质谱联用（LC - MS）的大规模非靶向代谢组学工作流程中的关键步骤，因为它能够整合多个样本中的代谢物峰，这对于准确的数据解读至关重要。然而，色谱分离条件的微小差异或波动会导致连续分析之间的色谱保留时间（RT）发生偏移，最终影响样本间峰对齐的准确性。在此，我们介绍一种基于保留指数（RI）的新型RT偏移校正方法，并将其应用于峰对齐。我们通过甘氨酸与正构饱和脂肪酸（C2 - C23）之间的酰胺化反应合成了一系列酰基甘氨酸（C2 - C23）同系物作为校准物，这些校准物能够在质谱正离子和负离子模式下均有效响应。利用这些校准物，我们建立了一个酰基甘氨酸RI系统。该RI系统能够覆盖广阔的色谱空间，并解决由流速、梯度洗脱、仪器系统和液相色谱分离柱的变化引起的色谱RT偏移问题。此外，基于RI系统，我们开发了一个峰偏移校正模型以提高峰对齐的准确性。应用该模型使得在长达157天的长期数据中，峰对齐的准确性从15.5%显著提高到80.9%。为便于实际应用，我们开发了一个基于Python的程序，该程序可在https://github.com/WHU - Fenglab/RI - based - CPSC上免费获取。
