Liu Pinghui, Chen Qinsheng, Zhang Lianglong, Ren Chengcheng, Shi Biru, Zhang Jingxian, Wang Shuaiyao, Chen Ziliang, Wang Qi, Xie Hui, Huang Qingxia, Tang Huiru
State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Wuhan Laboratory for Shanghai Metabolome Institute (SMI) Ltd, Wuhan 430000, China.
Biophys Rep. 2023 Dec 31;9(6):299-308. doi: 10.52601/bpr.2023.230042.
Efficient quantification of fatty-acid (FA) composition (fatty-acidome) in biological samples is crucial for understanding physiology and pathophysiology in large population cohorts. Here, we report a rapid GC-FID/MS method for simultaneous quantification of all FAs in numerous biological matrices. Within eight minutes, this method enabled simultaneous quantification of 50 FAs as fatty-acid methyl esters (FAMEs) in femtomole levels following the efficient transformation of FAs in all lipids including FFAs, cholesterol-esters, glycerides, phospholipids and sphingolipids. The method showed satisfactory inter-day and intra-day precision, stability and linearity (R > 0.994) within a concentration range of 2-3 orders of magnitude. FAs were then quantified in typical multiple biological matrices including human biofluids (urine, plasma) and cells, animal intestinal content and tissue samples. We also established a quantitative structure-retention relationship (QSRR) for analytes to accurately predict their retention time and aid their reliable identification. We further developed a novel no-additive retention index (NARI) with endogenous FAMEs reducing inter-batch variations to 15 seconds; such NARI performed better than the alkanes-based classical RI, making meta-analysis possible for data obtained from different batches and platforms. Collectively, this provides an inexpensive high-throughput analytical system for quantitative phenotyping of all FAs in 8-minutes multiple biological matrices in large cohort studies of pathophysiological effects.
对生物样本中的脂肪酸（FA）组成（脂肪酸组）进行高效定量分析，对于理解大规模人群队列中的生理学和病理生理学至关重要。在此，我们报告了一种快速气相色谱 - 火焰离子化检测器/质谱法（GC-FID/MS），用于同时定量多种生物基质中的所有脂肪酸。在八分钟内，该方法能够在将包括游离脂肪酸（FFA）、胆固醇酯、甘油酯、磷脂和鞘脂在内的所有脂质中的脂肪酸高效转化为脂肪酸甲酯（FAME）后，以飞摩尔水平同时定量50种脂肪酸。该方法在2 - 3个数量级的浓度范围内显示出令人满意的日间和日内精密度、稳定性和线性（R > 0.994）。然后在包括人类生物流体（尿液、血浆）和细胞、动物肠道内容物及组织样本等典型的多种生物基质中对脂肪酸进行定量分析。我们还建立了分析物的定量结构保留关系（QSRR），以准确预测它们的保留时间并辅助可靠鉴定。我们进一步开发了一种新型的无添加剂保留指数（NARI），以内源性脂肪酸甲酯将批次间差异降低至15秒；这种NARI的性能优于基于烷烃的经典保留指数，使得对来自不同批次和平台的数据进行荟萃分析成为可能。总体而言，这为大规模队列研究病理生理效应时在8分钟内对多种生物基质中的所有脂肪酸进行定量表型分析提供了一种廉价的高通量分析系统。
