色谱 ›› 2021, Vol. 39 ›› Issue (2): 112-117.DOI: 10.3724/SP.J.1123.2020.08023

• 微型述评 • 上一篇    下一篇

高通量蛋白质组学分析研究进展

吴琼, 隋欣桐, 田瑞军*()   

  1. 南方科技大学理学院化学系, 广东 深圳 518055
  • 收稿日期:2020-08-22 出版日期:2021-02-08 发布日期:2021-01-14
  • 通讯作者: 田瑞军
  • 作者简介:田瑞军: 博士,南方科技大学化学系终身教授,博士生导师,加拿大渥太华大学医学院及深圳市人民医院兼职教授,中国人类蛋白质组组织(CNHUPO)常务理事、中国化学会色谱专业委员会理事、中国质谱学会理事和中国分子系统生物学学会理事,科技部“国家重点研发计划”蛋白质机器专项子课题负责人。 2008年在中国科学院大连化学物理研究所获得分析化学博士学位,师从邹汉法研究员,并获得中国科学院院长优秀奖和中国科学院优秀毕业生奖励。同年加入加拿大渥太华系统生物学研究所进行博士后研究,师从Daniel Figeys教授。2010年加入加拿大多伦多大学和西奈山医院继续博士后研究,师从Tony Pawson院士,并获得加拿大国立卫生研究院(CIHR)博士后基金资助。2014年起受聘南方科技大学化学系副教授(研究员),并于2020年晋升终身正教授。致力于蛋白质组学的方法学和应用研究,在细胞信号转导和肿瘤微环境等生物医学方向开展了卓有成效的应用研究。已在国际主流学术期刊上发表论文70余篇,其中以责任作者在Nature, PNAS, Mol Cell Proteomics, Anal Chem, Angew Chem等上发表文章40余篇,作为客座主编组织专刊一期,SCI他引2000余次,H-index为27 (Google Scholar)。曾荣获由国际蛋白质结构分析和蛋白质组学协会(IAPSAP)颁发的2012 Young Investigator Award,并在第八届世界人类蛋白质组学大会(HUPO)等做邀请报告50余次。曾担任第五届中加系统生物学研讨会和第二届CNHUPO青年学者研讨会共同主席。担任《色谱》期刊青年编委和国际期刊Frontiers in Endocrinology编委。* Tel:(0755)88018303,E-mail: tianrj@sustech.edu.cn.
  • 基金资助:
    国家自然科学基金项目(91953118)

Advances in high-throughput proteomic analysis

WU Qiong, SUI Xintong, TIAN Ruijun*()   

  1. Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
  • Received:2020-08-22 Online:2021-02-08 Published:2021-01-14
  • Contact: TIAN Ruijun
  • Supported by:
    National Natural Science Foundation of China(91953118)

摘要:

基于质谱的蛋白质组学技术已经日趋成熟,可以对细胞和组织中的成千上万种蛋白质进行全面的定性和定量分析,逐步实现“深度覆盖”。随着生物医学日益增长的大队列蛋白质组学分析需求,如何在保持较为理想的覆盖深度下实现短时间、快速的“高通量”蛋白质组学分析已成为当前亟需解决的关键问题之一。常规的蛋白质组学分析流程通常包括样品前处理、色谱分离、质谱检测和数据分析。该文从以上4个方面展开介绍近10年以来高通量蛋白质组学分析技术取得的一系列研究进展,主要包括:(1)基于高通量、自动化移液工作站的蛋白质组样品前处理方法;(2)基于微升流速液相色谱与质谱联用的高通量蛋白质组检测方法;(3)利用灵敏度高、扫描速度快的质谱仪实现短色谱梯度分离下蛋白质组深度覆盖的分析方法;(4)基于人工智能、深度神经网络、机器学习等的蛋白质组学大数据分析方法。此外,对高通量蛋白质组学面临的挑战及其发展进行展望。总而言之,预期在不久的将来高通量蛋白质组学技术将会逐步“落地转化”,成为大队列蛋白质组学分析的利器。

关键词: 高通量, 蛋白质组学, 质谱, 色谱, 样品前处理

Abstract:

Proteomic analysis aims at characterizing proteins on a large scale, including their relative abundance, post-translational modifications, protein-protein interactions and so on. Proteomic profiling helps to elucidate the mechanisms of disease occurrence and to discover new diagnostic markers and therapeutic targets. Mass spectrometry (MS)-based proteomic technologies have advanced to allow comprehensive qualitative and quantitative proteome profiling across a myriad proteins in cells and tissues. High-throughput proteomics is the core technique for large-scale protein characterization. With the increased demand for large cohort proteomic analysis in the biomedical research field, high-throughput proteomic analysis has become a critical issue that needs to be urgently addressed. The standard shotgun proteomic workflow comprises four steps, including sample preparation, peptide separation, MS acquisition, and data analysis. Advances in these four steps have contributed to the development of high-throughput proteomics. In this review, we aimed at summarizing the current information on the state-of-the-art development of high-throughput proteomic analysis, mainly including the following topics: (1) High-throughput, automatic proteomic sample preparation methods based on liquid-handling workstations. The automation of the proteomic sample preparation steps is essential for high-throughput proteomic analysis, which will significantly reduce variation of manual operation and sample loss by multistep sample processing. The commercial liquid handling workstations, including King FisherTM Flex, Agilent Bravo, AssayMAP Bravo, and Biomek® NXP, perform the handling steps of 96- or 384-channel microplate formats using a mechanical arm that increases the throughput and robustness of sample preparation. (2) High-throughput proteomic detection methods based on microliter-flow-rate liquid chromatography coupled with mass spectrometry (micro-flow LC-MS/MS). Nanoliter-flow-rate liquid chromatography coupled with mass spectrometry (Nano-flow LC-MS/MS) is widely used in classic proteomic research due to its excellent sensitivity, which often comes at the expense of robustness. Owing to the improved robustness and decreased injection-to-injection overheads, micro-flow LC-MS/MS has become increasingly popular in high-throughput proteomic analysis. (3) Using MS instrumentation with high sensitivity and fast scanning speed to realize in-depth proteomic analysis coupled with short chromatographic gradient separation. In recent years, new MS instrumentation continues to exhibit speed of analysis and sensitivity enables the large-scale profiling of hundreds of samples. In particular, ion mobility-based MS, such as timsTOF Pro and Exploris 480 equipped with a front-end high field asymmetric waveform ion mobility spectrometry (FAIMS), which provides fast, sensitive, and robust proteome profiling, thus shifting proteomics to the high-throughput era. (4) Artificial intelligence-, deep neural network-, and machine learning-based proteome data analysis methods. These approaches have improved comprehensive proteomic analysis efficiency. Specifically, the emergence of new algorithms and the up gradation of search engines accelerate the process of high-throughput data analysis. Additionally, the challenges and future development of high-throughput proteomics are prospected. In conclusion, high-throughput proteomic technologies are expected to gradually “transform” and become powerful tools for large cohort proteomic analysis in the near future.

Key words: high-throughput, proteomics, mass spectrometry (MS), chromatography, sample preparation

中图分类号: