How Many proteins are Missed in Quantitative proteomics Based on Ms/Ms sequencing Methods?

Claire Mulvey, Bettina Thur, Mark Crawford, Jasminka Godovac-Zimmermann
{"title":"How Many proteins are Missed in Quantitative proteomics Based on Ms/Ms sequencing Methods?","authors":"Claire Mulvey,&nbsp;Bettina Thur,&nbsp;Mark Crawford,&nbsp;Jasminka Godovac-Zimmermann","doi":"10.4137/PRI.S5882","DOIUrl":null,"url":null,"abstract":"<p><p>Current bottom-up quantitative proteomics methods based on MS/MS sequencing of peptides are shown to be strongly dependent on sample preparation. Using cytosolic proteins from MCF-7 breast cancer cells, it is shown that protein pre-fractionation based on pI and MW is more effective than pre-fractionation using only MW in increasing the number of observed proteins (947 vs. 704 proteins) and the number of spectral counts per protein. Combination of MS data from the different pre-fractionation methods results in further improvements (1238 proteins). We discuss that at present the main limitation on quantitation by MS/MS sequencing is not MS sensitivity and protein abundance, but rather extensive peptide overlap and limited MS/MS sequencing throughput, and that this favors internally calibrated methods such as SILAC, ICAT or ITRAQ over spectral counting methods in attempts to drastically improve proteome coverage of biological samples.</p>","PeriodicalId":88975,"journal":{"name":"Proteomics insights","volume":"3 ","pages":"61-66"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4137/PRI.S5882","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proteomics insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4137/PRI.S5882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Current bottom-up quantitative proteomics methods based on MS/MS sequencing of peptides are shown to be strongly dependent on sample preparation. Using cytosolic proteins from MCF-7 breast cancer cells, it is shown that protein pre-fractionation based on pI and MW is more effective than pre-fractionation using only MW in increasing the number of observed proteins (947 vs. 704 proteins) and the number of spectral counts per protein. Combination of MS data from the different pre-fractionation methods results in further improvements (1238 proteins). We discuss that at present the main limitation on quantitation by MS/MS sequencing is not MS sensitivity and protein abundance, but rather extensive peptide overlap and limited MS/MS sequencing throughput, and that this favors internally calibrated methods such as SILAC, ICAT or ITRAQ over spectral counting methods in attempts to drastically improve proteome coverage of biological samples.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于Ms/Ms测序方法的定量蛋白质组学缺失了多少蛋白质?
目前基于MS/MS测序的自底向上定量蛋白质组学方法强烈依赖于样品制备。使用MCF-7乳腺癌细胞的细胞质蛋白,研究表明,在增加观察到的蛋白数量(947 vs 704)和每个蛋白的光谱计数数量方面,基于pI和MW的蛋白预分离比仅使用MW的蛋白预分离更有效。结合来自不同预分离方法的质谱数据,进一步改进(1238个蛋白)。我们讨论了目前MS/MS测序定量的主要限制不是MS敏感性和蛋白质丰度,而是广泛的肽重叠和有限的MS/MS测序通量,这有利于内部校准方法,如SILAC, ICAT或ITRAQ,而不是光谱计数方法,试图大幅提高生物样品的蛋白质组覆盖率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Phorbol 12-Myristate 13-Acetate-Induced Changes in Chicken Enterocytes. Expression and Characterization of Human Fragile X Mental Retardation Protein Isoforms and Interacting Proteins in Human Cells. An Improved 2-Dimensional Gel Electrophoresis Method for Resolving Human Erythrocyte Membrane Proteins. Characterization of Vitreous and Aqueous Proteome in Humans With Proliferative Diabetic Retinopathy and Its Clinical Correlation. Proteomic Changes in Chicken Plasma Induced by Salmonella typhimurium Lipopolysaccharides
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1