液相色譜－串聯(lián)質(zhì)譜分析已經(jīng)成為蛋白質(zhì)組研究中應(yīng)用最廣泛的技術(shù)策略。但是,，不同的實(shí)驗(yàn)室由于采用不同的儀器,、不同的搜索引擎和不同的數(shù)據(jù)庫(kù)，對(duì)同一樣品的分析往往得到不同的結(jié)果,。
為探討這一問(wèn)題,，該中心錢(qián)小紅研究員、賀福初院士課題組與國(guó)際蛋白質(zhì)組學(xué)領(lǐng)域26家重要實(shí)驗(yàn)室,，共同參與國(guó)際人類蛋白質(zhì)組組織（HUPO）發(fā)起的針對(duì)以生物質(zhì)譜為基礎(chǔ)的蛋白質(zhì)組學(xué)研究共性技術(shù)問(wèn)題的系統(tǒng)分析,，通過(guò)比較不同實(shí)驗(yàn)室對(duì)20種標(biāo)準(zhǔn)蛋白樣本的鑒定結(jié)果，發(fā)現(xiàn)即使采用高度純化的蛋白質(zhì)作為樣本,，大部分實(shí)驗(yàn)室還是不能提供完全正確的鑒定結(jié)果,。通過(guò)對(duì)原始數(shù)據(jù)的進(jìn)一步分析表明，產(chǎn)生上述問(wèn)題的關(guān)鍵在于所用數(shù)據(jù)庫(kù)與搜索引擎的區(qū)別,。隨著數(shù)據(jù)庫(kù)和搜索引擎的改進(jìn),，蛋白質(zhì)組分析結(jié)果的可靠性會(huì)大大提高。相關(guān)工作新近發(fā)表于《自然－方法》,。（生物谷Bioon.com）
生物谷推薦原始出處：
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.
