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基于化学特征对细胞进行分类:单细胞质谱分析的进展。

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry.

机构信息

Department of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.

出版信息

J Am Chem Soc. 2017 Mar 22;139(11):3920-3929. doi: 10.1021/jacs.6b12822. Epub 2017 Feb 13.

Abstract

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

摘要

细胞群体中单个细胞之间的化学差异为研究生物体内稳态和疾病状态的发展提供了独特的信息。即使是遗传上完全相同的细胞谱系,由于局部微环境和随机过程的影响也会出现分化。细胞内某些成分的样本体积小且含量低,这阻碍了我们对细胞异质性的理解。尽管扩增方法促进了单细胞基因组学和转录组学的发展,但代谢物和蛋白质的特征仍然具有挑战性,这既是因为缺乏有效的扩增方法,也是因为细胞成分的广泛多样性。质谱分析以其极高的灵敏度、大动态范围和能够鉴定数百到数千种化合物的能力,已成为研究单个细胞代谢物图谱的一种重要技术手段。尽管仪器的进步提高了衡量标准,但在高通量获取测量值和对大量细胞群体进行采样方面仍未成为常规操作。在本文中,我们重点介绍了基于质谱的单细胞分析的当前趋势和进展,以及将实现下一代单细胞测量的技术。

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