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摘要 : 两个研究小组对人体组织、体液和细胞进行质谱分析,标绘了人类蛋白质组的绝大部分。相关文章发表于2014年5月28日的《Nature》杂志上。




Akhilesh Pandey及同事识别出17,294个蛋白编码基因,并通过表达分析提供了存在受组织限制和受细胞限制的蛋白的证据。通过从注解的假基因、非编码RNA和未翻译的区域识别翻译的蛋白,他们显示了“蛋白基因组”分析的重要性。他们的数据集可以在http://www.humanproteomemap.org这个网址获得。

Bernhard Kuster及同事为“蛋白质组数据库”(ProteomicsDB,可在https://www.proteomicsdb.org这个网址获得)中的18,097个基因获得了蛋白证据,展示了这种数据的用途—— 如用于识别数百个翻译的lincRNAs和对药物敏感的标记以及用于发现mRNA和组织中的蛋白水平之间的定量关系等。

在本期Nature的其他地方,Vivien Marx报告了第三个大型蛋白质组项目,即基于抗体的“人类蛋白图集”(Human Protein Atlas)项目(。


A draft map of the human proteome

Min-Sik Kim, Sneha M. Pinto, Derese Getnet, Raja Sekhar Nirujogi, Srikanth S. Manda,Raghothama Chaerkady, Anil K. Madugundu, Dhanashree S. Kelkar, Ruth Isserlin, Shobhit Jain, Joji K. Thomas, Babylakshmi Muthusamy, Pamela Leal-Rojas, Praveen Kumar,Nandini A. Sahasrabuddhe, Lavanya Balakrishnan, Jayshree Advani, Bijesh George,Santosh Renuse, Lakshmi Dhevi N. Selvan, Arun H. Patil, Vishalakshi Nanjappa, Aneesha Radhakrishnan, Samarjeet Prasad, Tejaswini Subbannayya et al.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Mass-spectrometry-based draft of the human proteome

Mathias Wilhelm, Judith Schlegl, Hannes Hahne, Amin Moghaddas Gholami, Marcus Lieberenz, Mikhail M. Savitski, Emanuel Ziegler, Lars Butzmann, Siegfried Gessulat,Harald Marx, Toby Mathieson, Simone Lemeer, Karsten Schnatbaum, Ulf Reimer, Holger Wenschuh, Martin Mollenhauer, Julia Slotta-Huspenina, Joos-Hendrik Boese, Marcus Bantscheff, Anja Gerstmair, Franz Faerber & Bernhard Kuster

Proteomes are characterized by large protein-abundance differences, cell-type- and time-dependent expression patterns and post-translational modifications, all of which carry biological information that is not accessible by genomics or transcriptomics. Here we present a mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB. The information assembled from human tissues, cell lines and body fluids enabled estimation of the size of the protein-coding genome, and identified organ-specific proteins and a large number of translated lincRNAs (long intergenic non-coding RNAs). Analysis of messenger RNA and protein-expression profiles of human tissues revealed conserved control of protein abundance, and integration of drug-sensitivity data enabled the identification of proteins predicting resistance or sensitivity. The proteome profiles also hold considerable promise for analysing the composition and stoichiometry of protein complexes. ProteomicsDB thus enables navigation of proteomes, provides biological insight and fosters the development of proteomic technology.

对应Nature杂志: 2014年5月29日Nature杂志精选

来源: Nature中文 浏览次数:327


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