液相色谱－串联质谱分析已经成为蛋白质组研究中应用最广泛的技术策略。但是，不同的实验室由于采用不同的仪器、不同的搜索引擎和不同的数据库，对同一样品的分析往往得到不同的结果。
为探讨这一问题，该中心钱小红研究员、贺福初院士课题组与国际蛋白质组学领域26家重要实验室，共同参与国际人类蛋白质组组织（HUPO）发起的针对以生物质谱为基础的蛋白质组学研究共性技术问题的系统分析，通过比较不同实验室对20种标准蛋白样本的鉴定结果，发现即使采用高度纯化的蛋白质作为样本，大部分实验室还是不能提供完全正确的鉴定结果。通过对原始数据的进一步分析表明，产生上述问题的关键在于所用数据库与搜索引擎的区别。随着数据库和搜索引擎的改进，蛋白质组分析结果的可靠性会大大提高。相关工作新近发表于《自然－方法》。（生物谷Bioon.com）
生物谷推荐原始出处：
Nature Methods 6, 423 - 430 (2009)17 May 2009 | doi:10.1038/nmeth.1333
A HUPO test sample study reveals common problems in mass spectrometry–based proteomics
Alexander W Bell1, Eric W Deutsch2, Catherine E Au1, Robert E Kearney3, Ron Beavis4, Salvatore Sechi5, Tommy Nilsson6, John J M Bergeron1 & HUPO Test Sample Working Group7
Abstract
We performed a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in liquid chromatography–mass spectrometry–based proteomics. We distributed an equimolar test sample, comprising 20 highly purified recombinant human proteins, to 27 laboratories. Each protein contained one or more unique tryptic peptides of 1,250 Da to test for ion selection and sampling in the mass spectrometer. Of the 27 labs, members of only 7 labs initially reported all 20 proteins correctly, and members of only 1 lab reported all tryptic peptides of 1,250 Da. Centralized analysis of the raw data, however, revealed that all 20 proteins and most of the 1,250 Da peptides had been detected in all 27 labs. Our centralized analysis determined missed identifications (false negatives), environmental contamination, database matching and curation of protein identifications as sources of problems. Improved search engines and databases are needed for mass spectrometry–based proteomics.
