A review of the current state of single-cell proteomics and future perspective

被引:46
作者
Ahmad, Rushdy [1 ]
Budnik, Bogdan [1 ]
机构
[1] Harvard Univ, Wyss Inst Biol Inspired Engn, 3 Blackfan Circle, Boston, MA 02115 USA
关键词
Single-cell proteomics; SCP; Review; Current state; Future perspective; MASS-SPECTROMETRY; HETEROGENEITY;
D O I
10.1007/s00216-023-04759-8
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.
引用
收藏
页码:6889 / 6899
页数:11
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