State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China.
School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Anal Chim Acta. 2024 Nov 15;1329:343262. doi: 10.1016/j.aca.2024.343262. Epub 2024 Sep 18.
N-acylethanolamines (NAEs) are a class of naturally occurring bioactive lipids that play crucial roles in various physiological processes, particularly exhibiting neuroprotective and anti-inflammatory properties. However, the comprehensive profiling of endogenous NAEs in complex biological matrices is challenging due to their low abundance, structural similarity and the limited availability of commercial standards. Here, we propose an integrated strategy for comprehensive profiling of NAEs that combines chemical derivatization and a three-dimensional (3D) prediction model based on quantitative structure-retention time relationship (QSRR) using liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS).
After acetyl chloride (ACC) derivatization, the detection sensitivity of NAEs was significantly improved. We developed a QSRR prediction model to construct an in-house database for 141 NAEs, encompassing information on RT, MS (m/z), and MS/MS spectra. Propargylamine-labeled fatty acids were synthesized as RT calibrants across various analytical conditions to enhance the robustness of the RT prediction model. NAEs in biological samples were then in-depth profiled using parallel reaction monitoring (PRM) acquisition. This integrated strategy identified and annotated a total of 50 NAEs across serum, hippocampus and cortex tissues from a 5xFAD mouse model of Alzheimer's disease (AD). Notably, the levels of polyunsaturated NAEs, particularly NAE 20:5 and NAE 22:6, were significantly decreased in 5xFAD mice compared to WT mice, as confirmed by accurate quantitation using ACC-d/d derivatization.
Our integrated strategy exhibits great potential for the in-depth profiling of NAEs in complex biological samples, facilitating the elucidation of NAE functions in diverse physiological and pathological processes.
N-酰基乙醇胺（NAEs）是一类天然存在的生物活性脂质，在各种生理过程中发挥着关键作用，特别是具有神经保护和抗炎特性。然而，由于其丰度低、结构相似以及商业标准的有限可用性，在复杂的生物基质中全面分析内源性 NAE 具有挑战性。在这里，我们提出了一种综合策略，结合化学衍生化和基于定量结构-保留时间关系（QSRR）的三维（3D）预测模型，使用液相色谱-高分辨率串联质谱（LC-HRMS）对 NAE 进行全面分析。
在乙酰氯（ACC）衍生化后，NAE 的检测灵敏度得到了显著提高。我们开发了 QSRR 预测模型，构建了一个包含 141 种 NAE 的内标数据库，其中包含 RT、MS（m/z）和 MS/MS 图谱的信息。合成了炔丙胺标记的脂肪酸作为各种分析条件下的 RT 校准剂，以增强 RT 预测模型的稳健性。然后使用平行反应监测（PRM）采集对生物样品中的 NAE 进行深入分析。这种综合策略共鉴定和注释了 5xFAD 阿尔茨海默病（AD）小鼠模型血清、海马和皮质组织中的 50 种 NAE。值得注意的是，与 WT 小鼠相比，5xFAD 小鼠中多不饱和 NAE，特别是 NAE 20:5 和 NAE 22:6 的水平显著降低，这通过 ACC-d/d 衍生化的准确定量得到了证实。
我们的综合策略在复杂生物样品中 NAE 的深入分析中具有巨大的潜力，有助于阐明 NAE 在各种生理和病理过程中的功能。
