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Unbiased spatial proteomics with single-cell resolution in tissues
Molecular Cell ( IF 14.5 ) Pub Date : 2022-06-16 , DOI: 10.1016/j.molcel.2022.05.022
Andreas Mund 1 , Andreas-David Brunner 2 , Matthias Mann 3
Affiliation  

Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.



中文翻译:

组织中具有单细胞分辨率的无偏空间蛋白质组学

基于质谱 (MS) 的蛋白质组学已成为一种强大的技术,可用于量化细胞或组织中的全部蛋白质。在这里,我们回顾了基于 LC-MS 的微量蛋白质分析的挑战和最新进展,直至单细胞水平。该技术的应用表明,由于每个细胞的转录物数量非常少,单细胞转录组以随机噪声为主,而单细胞蛋白质组似乎是完整的。可以通过新兴技术研究组织中细胞的空间组织,包括多重成像和空间转录组学,这些技术现在可以与超灵敏的蛋白质组学相结合。结合高内涵成像、人工智能和单细胞激光显微切割,基于 MS 的蛋白质组学提供接近功能水平的无偏分子读数。潜在的应用范围从基本的生物学问题到精准医学。

更新日期:2022-06-16
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