Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand; Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
J Biol Chem. 2022 Oct;298(10):102445. doi: 10.1016/j.jbc.2022.102445. Epub 2022 Aug 31.
Two dimensional GC (GC × GC)-time-of-flight mass spectrometry (TOFMS) has been used to improve accurate metabolite identification in the chemical industry, but this method has not been applied as readily in biomedical research. Here, we evaluated and validated the performance of high resolution GC × GC-TOFMS against that of GC-TOFMS for metabolomics analysis of two different plasma matrices, from healthy controls (CON) and diabetes mellitus (DM) patients with kidney failure (DM with KF). We found GC × GC-TOFMS outperformed traditional GC-TOFMS in terms of separation performance and metabolite coverage. Several metabolites from both the CON and DM with KF matrices, such as carbohydrates and carbohydrate-conjugate metabolites, were exclusively detected using GC × GC-TOFMS. Additionally, we applied this method to characterize significant metabolites in the DM with KF group, with focused analysis of four metabolite groups: sugars, sugar alcohols, amino acids, and free fatty acids. Our plasma metabolomics results revealed 35 significant metabolites (12 unique and 23 concentration-dependent metabolites) in the DM with KF group, as compared with those in the CON and DM groups (N = 20 for each group). Interestingly, we determined 17 of the 35 (14/17 verified with reference standards) significant metabolites identified from both the analyses were metabolites from the sugar and sugar alcohol groups, with significantly higher concentrations in the DM with KF group than in the CON and DM groups. Enrichment analysis of these 14 metabolites also revealed that alterations in galactose metabolism and the polyol pathway are related to DM with KF. Overall, our application of GC × GC-TOFMS identified key metabolites in complex plasma matrices.
二维气相色谱（GC×GC）-飞行时间质谱（TOFMS）已被用于提高化学工业中代谢物鉴定的准确性，但该方法在生物医学研究中尚未得到广泛应用。在这里，我们评估和验证了高分辨 GC×GC-TOFMS 与传统 GC-TOFMS 用于分析两种不同血浆基质（来自健康对照（CON）和肾衰竭的糖尿病（DM 伴 KF）患者）代谢组学的性能。我们发现 GC×GC-TOFMS 在分离性能和代谢物覆盖度方面优于传统 GC-TOFMS。来自 CON 和 DM 伴 KF 基质的几种代谢物，如碳水化合物和碳水化合物缀合代谢物，仅使用 GC×GC-TOFMS 检测到。此外，我们应用该方法来表征 DM 伴 KF 组中的显著代谢物，对四个代谢物组进行重点分析：糖、糖醇、氨基酸和游离脂肪酸。我们的血浆代谢组学结果显示，与 CON 和 DM 组相比，DM 伴 KF 组中有 35 种显著代谢物（12 种独特代谢物和 23 种浓度依赖代谢物）（每组 N=20）。有趣的是，我们从这两种分析中确定了 35 个显著代谢物中的 17 个（14/17 通过参考标准验证），它们是糖和糖醇组的代谢物，在 DM 伴 KF 组中的浓度明显高于 CON 和 DM 组。对这 14 种代谢物的富集分析还表明，半乳糖代谢和多元醇途径的改变与 DM 伴 KF 有关。总体而言，我们应用 GC×GC-TOFMS 鉴定了复杂血浆基质中的关键代谢物。
