Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
J Am Soc Mass Spectrom. 2021 Apr 7;32(4):872-894. doi: 10.1021/jasms.0c00439. Epub 2021 Mar 3.
Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.
生物系统由异质细胞群体组成，这些细胞相互交流，形成具有功能的活体组织。生物功能在细胞群体之间存在很大差异，因为每个单个细胞都有独特的转录组、蛋白质组和代谢组，这导致了同一物种内和不同物种之间的功能差异。在过去的十年中，我们在单细胞水平上对组学谱进行特征描述的能力取得了实质性的进展，包括多种光谱和基于质谱（MS）的技术。在这些技术中，包括质谱成像（MSI）在内的空间分辨质谱方法在单细胞蛋白质组学和代谢组学方面取得了最大的进展。例如，使用重金属标记的基于报告基因的方法允许对亚细胞水平的蛋白质组进行靶向 MS 研究，并且诸如激光烧蚀电喷雾电离质谱（LAESI-MS）之类的技术的发展意味着可以在原位进行动态代谢组学研究。在本观点文章中，我们展示了过去十年中单细胞空间代谢组学和蛋白质组学的进展，并强调了与高通量筛选、数据分析等相关的重要方面，这些方面对于在单细胞水平上实现蛋白质组学和代谢组学分析的成功至关重要。最后，我们利用广泛的文献综述，就单细胞 MS 基蛋白质组学和代谢组学领域的未来十年可能如何发展提供了一个观点。
