Cheng Simin, Cao Chenxi, Qian Yao, Yao Huan, Gong Xiaoyun, Dai Xinhua, Ouyang Zheng, Ma Xiaoxiao
Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology Bejing 100029 China
State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University Beijing 100084 China
Chem Sci. 2024 Apr 4;15(17):6314-6320. doi: 10.1039/d3sc06573a. eCollection 2024 May 1.
Single-cell mass spectrometry (MS) is an essential technology for sensitive and multiplexed analysis of metabolites and lipids for cell phenotyping and pathway studies. However, the structural elucidation of lipids from single cells remains a challenge, especially in the high-throughput scenario. Technically, there is a contradiction between the inadequate sample amount ( a single cell, 0.5-20 pL) for replicate or multiple analysis, on the one hand, and the high metabolite coverage and multidimensional structure analysis that needs to be performed for each single cell, on the other hand. Here, we have developed a high-throughput single-cell MS platform that can perform both lipid profiling and lipid carbon-carbon double bond (C[double bond, length as m-dash]C) location isomer resolution analysis, aided by C[double bond, length as m-dash]C activation in unsaturated lipids by the Paternò-Büchi (PB) reaction and tandem MS, termed single-cell structural lipidomics analysis. The method can achieve a single-cell analysis throughput of 51 cells per minute. A total of 145 lipids were structurally characterized at the subclass level, of which the relative abundance of 17 isomeric lipids differing in the location of C[double bond, length as m-dash]C from 5 lipid precursors was determined. While cell-to-cell variations in MS-based lipid profiling can be large, an advantage of quantifying lipid C[double bond, length as m-dash]C location isomers is the significantly improved quantitation accuracy. For example, the relative standard deviations (RSDs) of the relative amounts of PC 34:1 C[double bond, length as m-dash]C position isomers in MDA-MB-468 cells are half smaller than those measured for PC 34:1 as a whole by MS abundance profiling. Taken together, the developed method can be effectively used for in-depth structural lipid metabolism network analysis by high-throughput analysis of 142 MDA-MB-468 human breast cancer cells.
单细胞质谱（MS）是用于细胞表型分析和通路研究中对代谢物和脂质进行灵敏且多重分析的一项重要技术。然而，单细胞脂质的结构解析仍然是一项挑战，尤其是在高通量情况下。从技术层面来讲，一方面用于重复或多次分析的样本量不足（单个细胞，0.5 - 20皮升），另一方面又需要对每个单细胞进行高代谢物覆盖度和多维结构分析，这两者之间存在矛盾。在此，我们开发了一种高通量单细胞MS平台，该平台借助不饱和脂质中碳 - 碳双键（C═C）通过帕特诺 - 布齐（PB）反应和串联质谱进行的C═C活化，能够同时进行脂质谱分析和脂质碳 - 碳双键（C═C）位置异构体解析分析，即单细胞结构脂质组学分析。该方法可实现每分钟51个细胞的单细胞分析通量。在亚类水平上总共对145种脂质进行了结构表征，其中确定了来自5种脂质前体的17种在C═C位置不同的异构体脂质的相对丰度。虽然基于MS的脂质谱分析中细胞间差异可能很大，但对脂质C═C位置异构体进行定量的一个优势是显著提高了定量准确性。例如，MDA - MB - 468细胞中PC 34:1 C═C位置异构体相对量的相对标准偏差（RSD）比通过MS丰度谱对PC 34:1整体测量的RSD小一半。综上所述，所开发的方法可通过对142个MDA - MB - 468人乳腺癌细胞进行高通量分析，有效地用于深入的结构脂质代谢网络分析。
