小柯机器人

美国东北大学Nikolai Slavov小组发现，优先级质谱法可提高单细胞蛋白质组学的深度、灵敏度和数据完整性。相关论文于2023年4月3日在线发表在《自然—方法学》杂志上。

研究人员表示，单细胞蛋白质组学的主要目标包括提高蛋白质定量的一致性、敏感性和深度，特别是对生物感兴趣的蛋白质和修饰的定量。

为了同时推进所有这些目标，研究人员开发了优先考虑的单细胞蛋白质组学（pSCoPE）。pSCoPE在所有单细胞中持续分析数以千计的优先考虑的肽（从而提高数据完整性），同时最大限度地利用仪器时间分析可识别的肽，从而提高蛋白质组深度。这些策略将灵敏度、数据完整性和蛋白质组覆盖率提高了两倍以上。这些成果使研究人员能够量化未经处理的和经脂多糖处理的初级巨噬细胞中的蛋白质变化。在每个条件下，蛋白质在功能组中的共同变化，包括吞噬体成熟和质子运输，在两种处理条件下都是类似的。

这种共同变化与内细胞活动的表型变化有关。pSCoPE还能对蛋白分解产物进行量化，并表明在一个处理条件下，组织蛋白酶的活性是有梯度的。pSCoPE是免费提供的，适用范围广泛，特别是在不牺牲蛋白质组覆盖率的情况下分析感兴趣的蛋白质。对pSCoPE的支持可在http://scp.slavovlab.net/pSCoPE获取。

附：英文原文

Title: Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics

Author: Huffman, R. Gray, Leduc, Andrew, Wichmann, Christoph, Di Gioia, Marco, Borriello, Francesco, Specht, Harrison, Derks, Jason, Khan, Saad, Khoury, Luke, Emmott, Edward, Petelski, Aleksandra A., Perlman, David H., Cox, Jrgen, Zanoni, Ivan, Slavov, Nikolai

Issue&Volume: 2023-04-03

Abstract: Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE.

DOI: 10.1038/s41592-023-01830-1

Source: https://www.nature.com/articles/s41592-023-01830-1

Nature Methods：《自然—方法学》，创刊于2004年。隶属于施普林格·自然出版集团，最新IF：47.99
官方网址：https://www.nature.com/nmeth/
投稿链接：https://mts-nmeth.nature.com/cgi-bin/main.plex