Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore.
School of Civil and Environmental Engineering, Nanyang Technological University, 639798 Singapore.
Environ Sci Technol. 2023 Aug 1;57(30):10962-10973. doi: 10.1021/acs.est.3c01830. Epub 2023 Jul 19.
Exposome is the future of next-generation environmental health to establish the association between environmental exposure and diseases. However, due to low concentrations of exposure chemicals, exposome has been hampered by lacking an effective analytical platform to characterize its composition. In this study, by combining the benefit of chemical isotope labeling and pseudo-multiple reaction monitoring (CIL-pseudo-MRM), we have developed one highly sensitive and high-throughput platform (CIL-ExPMRM) by isotope labeling urinary exposure biomarkers. Dansyl chloride (DnsCl), -methylphenylethylamine (MPEA), and their isotope-labeled forms were used to derivatize polar hydroxyl and carboxyl compounds, respectively. We have programmed a series of scripts to optimize MRM transition parameters, curate the MRM database (>70,000 compounds), predict accurate retention time (RT), and automize dynamic MRMs. This was followed by an automated MRM peak assignment, peak alignment, and statistical analysis. A computational pipeline was eventually incorporated into a user-friendly website interface, named CIL-ExPMRM (http://www.exposomemrm.com/). The performance of this platform has been validated with a relatively low false positive rate (10.7%) across instrumental platforms. CIL-ExPMRM has systematically overcome key bottlenecks of exposome studies to some extent and outperforms previous methods due to its independence of MS/MS availability, accurate RT prediction, and collision energy optimization, as well as the ultrasensitivity and automated robust intensity-based quantification. Overall, CIL-ExPMRM has great potential to advance the exposomic studies based on urinary biomarkers.
暴露组学是下一代环境健康的未来,可以建立环境暴露与疾病之间的关联。然而,由于暴露化学物质的浓度低,暴露组学受到缺乏有效分析平台来描述其组成的限制。在这项研究中,通过结合化学同位素标记和伪多重反应监测(CIL-pseudo-MRM)的优势,我们开发了一种高度敏感和高通量的平台(CIL-ExPMRM),通过同位素标记尿暴露生物标志物。丹磺酰氯(DnsCl)和 -甲基苯乙胺(MPEA)及其同位素标记形式分别用于衍生极性羟基和羧基化合物。我们编写了一系列脚本,以优化 MRM 转换参数、整理 MRM 数据库(>70,000 种化合物)、预测准确的保留时间(RT)并自动化动态 MRM。然后进行自动 MRM 峰分配、峰对齐和统计分析。最终,将计算流程纳入到一个用户友好的网站界面中,命名为 CIL-ExPMRM(http://www.exposomemrm.com/)。该平台的性能已经通过在不同仪器平台上具有相对较低的假阳性率(10.7%)得到了验证。CIL-ExPMRM 在一定程度上系统地克服了暴露组学研究的关键瓶颈,并且由于其独立于 MS/MS 的可用性、准确的 RT 预测和碰撞能优化以及超高灵敏度和自动化的基于强度的定量,优于以前的方法。总体而言,CIL-ExPMRM 具有很大的潜力来推进基于尿生物标志物的暴露组学研究。