Asadian Marisa, Croslow Seth W, Trinklein Timothy J, Rubakhin Stanislav S, Lam Fan, Sweedler Jonathan V
Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.
Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.
Anal Chem. 2025 Jul 29;97(29):15864-15872. doi: 10.1021/acs.analchem.5c02092. Epub 2025 Jul 21.
Lipids are a diverse class of biomolecules essential for brain function, yet their cell-type-specific distributions remain underexplored, presenting significant knowledge gaps in the era of single-cell biology. Traditional bulk measurements provide valuable insights into lipid composition across brain regions but lack the resolution to distinguish lipid profiles at the single-cell level. To address this, we introduce fluorescence-guided sequential single-cell mass spectrometry (SSMS), an automated workflow combining untargeted lipid profiling with antibody-targeted protein detection via photocleavable mass tags, enabling neurolipidomic classification of cell types and cell states. We applied this approach to rodent hippocampal cells, analyzing over a thousand single cells and annotating more than a hundred lipid species with complementary liquid chromatography-mass spectrometry (LC-MS/MS) measurements. Our findings show that phosphatidylcholine (PC) species are predominantly enriched in oligodendrocytes and neurons compared to astrocytes, while hexosylceramide (HexCer) species are differentially expressed across these cell types. Furthermore, neuronal state analysis revealed an enrichment of phosphatidylethanolamines (PEs) in presynaptic neurons, while nonpresynaptic neurons exhibited a more diverse lipid composition, including HexCer, PC, sphingomyelin, triacylglycerol, and PE. Our findings provide new insights into brain lipid heterogeneity with cell-type and cell-state specificity and extend-capabilities of next-generation single-cell mass spectrometry to map brain biochemistry.
脂质是一类对脑功能至关重要的多样化生物分子，然而它们在细胞类型特异性分布方面仍未得到充分探索，这在单细胞生物学时代造成了重大的知识空白。传统的整体测量方法为了解脑区脂质组成提供了有价值的见解，但缺乏在单细胞水平区分脂质谱的分辨率。为了解决这一问题，我们引入了荧光引导的顺序单细胞质谱分析（SSMS），这是一种自动化工作流程，将非靶向脂质谱分析与通过光可裂解质量标签进行的抗体靶向蛋白质检测相结合，能够对细胞类型和细胞状态进行神经脂质组学分类。我们将这种方法应用于啮齿动物海马细胞，分析了一千多个单细胞，并通过互补的液相色谱 - 质谱联用（LC-MS/MS）测量对一百多种脂质种类进行了注释。我们的研究结果表明，与星形胶质细胞相比，磷脂酰胆碱（PC）种类在少突胶质细胞和神经元中主要富集，而己糖神经酰胺（HexCer）种类在这些细胞类型中差异表达。此外，神经元状态分析显示，突触前神经元中磷脂酰乙醇胺（PE）富集，而非突触前神经元表现出更多样化的脂质组成，包括HexCer、PC、鞘磷脂、三酰甘油和PE。我们的研究结果为具有细胞类型和细胞状态特异性的脑脂质异质性提供了新的见解，并扩展了下一代单细胞质谱分析绘制脑生物化学图谱的能力。
