Mass spectrometry-based quantitative lipidomics is an emerging field aiming to uncover the intricate relationships between lipidomes and disease development. However, quantifying lipidomes comprehensively in a high-throughput manner remains challenging owing to the diverse lipid structures. Here we propose a diazobutanone-assisted isobaric labelling strategy as a rapid and robust platform for multiplexed quantitative lipidomics across a broad range of lipid classes, including various phospholipids and glycolipids. The diazobutanone reagent is designed to conjugate with phosphodiester or sulfate groups, while accommodating various functional groups on different lipid classes, enabling subsequent isobaric labelling for high-throughput multiplexed quantitation. Our method demonstrates excellent performance in terms of labelling efficiency, detection sensitivity, quantitative accuracy and broad applicability to various biological samples. Finally, we performed a six-plex quantification analysis of lipid extracts from lean and obese mouse livers. In total, we identified and quantified 246 phospholipids in a high-throughput manner, revealing lipidomic changes that may be associated with obesity in mice.

基于质谱的定量脂质组学是一个新兴领域，旨在揭示脂质组学与疾病发展之间的复杂关系。然而，由于脂质结构的多样性，以高通量方式全面量化脂质组仍然具有挑战性。在这里，我们提出了一种重氮丁酮辅助的同量异位标记策略，作为一个快速而强大的平台，用于多种脂质类别（包括各种磷脂和糖脂）的多重定量脂质组学。重氮丁酮试剂旨在与磷酸二酯或硫酸酯基团结合，同时容纳不同脂质类别上的各种官能团，从而实现后续的同量异位标记以进行高通量多重定量。我们的方法在标记效率、检测灵敏度、定量准确性和对各种生物样品的广泛适用性方面表现出优异的性能。最后，我们对瘦小鼠和肥胖小鼠肝脏的脂质提取物进行了六重定量分析。总的来说，我们以高通量方式鉴定并定量了 246 种磷脂，揭示了可能与小鼠肥胖相关的脂质组学变化。