Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, Nanjing 210009, PR China.
Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, Nanjing 210009, PR China; State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, PR China.
J Pharm Biomed Anal. 2024 Jun 15;243:116068. doi: 10.1016/j.jpba.2024.116068. Epub 2024 Feb 23.
The formidable challenge posed by the presence of extremely high amounts of compounds and large differences in concentrations in plasma significantly complicates non-targeted metabolomics analyses. In this study, a comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC×GC-qMS) method with a solid-state modulator (SSM) for non-targeted metabolomics in beagle plasma was first established based on a GC-MS method, and the qualitative and quantitative performance of the two platforms were compared. Identification of detected compounds was accomplished utilizing NIST database match scores, retention indices (RIs) and standards. Semi-quantification involved the calculation of peak area ratios to internal standards. Metabolite identification sheets were generated for plasma samples on both analytical platforms, featuring 22 representative metabolites chosen for validating qualitative accuracy, and for conducting comparisons of linearity, accuracy, precision, and sensitivity. The outcomes revealed a threefold increase in the number of identifiable metabolites on the GC×GC-MS platform, with lower limits of quantitation (LLOQs) reduced to 0.5-0.05 times those achieved on the GC-MS platform. Accuracy in quantification for both GC×GC-MS and GC-MS fell within the range of 85-115%, and the vast majority of intra- and inter-day precisions were within the range of 20%. These findings underscore that relative to the conventional GC-MS method, the GC×GC-MS method developed in this study, combined with SSM, exhibits enhanced qualitative capabilities, heightened sensitivity, and comparable accuracy and precision, rendering it more suitable for non-targeted metabolomics analyses.
在血浆中存在极高浓度的化合物和浓度差异极大的情况下，非靶向代谢组学分析面临着巨大的挑战。在这项研究中，首次基于 GC-MS 方法建立了用于比格犬血浆非靶向代谢组学的全面二维气相色谱-四极杆质谱联用（GC×GC-qMS）与固态调制器（SSM）联用方法，并比较了两个平台的定性和定量性能。通过 NIST 数据库匹配分数、保留指数（RI）和标准对检测到的化合物进行鉴定。半定量涉及到通过与内标计算峰面积比来进行。为两种分析平台的血浆样本生成了代谢物鉴定表，其中包含 22 个有代表性的代谢物，用于验证定性准确性，并进行线性、准确性、精密度和灵敏度的比较。结果表明，GC×GC-qMS 平台上可识别的代谢物数量增加了三倍，定量下限（LLOQ）降低到 GC-MS 平台的 0.5-0.05 倍。GC×GC-qMS 和 GC-MS 的定量准确性均在 85-115%范围内，绝大多数日内和日间精密度均在 20%范围内。这些发现表明，与传统的 GC-MS 方法相比，本研究中开发的结合 SSM 的 GC×GC-qMS 方法具有增强的定性能力、更高的灵敏度以及相当的准确性和精密度，更适合非靶向代谢组学分析。
