{"title":"Advanced capillary liquid chromatography-mass spectrometry for proteomics","authors":"Yufeng Shen, J. Page, Richard D. Smith","doi":"10.1201/9781420060379.ch2","DOIUrl":null,"url":null,"abstract":"The liquid chromatography (LC)-mass spectrometric (MS) analysis of peptides has become a routine method for proteomics – the study of the entire complement of proteins e.g., expressed by a cell under a specific set of conditions at a specific time. Mixtures of peptides, such as those generated from enzymatic (e.g., trypsin) digestion of globally recovered proteins (i.e. a proteome), are typically very complex and >100,000 different molecular species may be observable using MS detection [1]. LC separations implemented prior to MS for broad protein identification have three major roles: 1) to isolate individual components or reduce complexity as much as possible, 2) to increase sensitivity by concentrating the components into narrow zones prior to MS, and 3) to eliminate or displace interfering species (e.g., salts and polymers) that may be present in proteomics samples. A desired quality of LC separation can be achieved from the use of either multiple steps of moderate quality separations, or fewer steps of high power separations. The former approach is generally more easily accessible for very high quality separations due to the variety of commercialized LC platforms available, while the latter still often requires considerable developmental efforts (for both columns and instrumentation). In addition tomore » proteomics data quality, other differences between these two approaches include proteomics analysis time and sample consumption (and subsequent analysis costs), as well as direct impact on potential proteomics applications that have special requirements in terms of analysis coverage, sample size, dynamic range, sensitivity, and throughput.« less","PeriodicalId":50873,"journal":{"name":"Advances in Chromatography","volume":"47 1","pages":"31-58"},"PeriodicalIF":0.0000,"publicationDate":"2009-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Chromatography","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1201/9781420060379.ch2","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Chemistry","Score":null,"Total":0}
引用次数: 4
Abstract
The liquid chromatography (LC)-mass spectrometric (MS) analysis of peptides has become a routine method for proteomics – the study of the entire complement of proteins e.g., expressed by a cell under a specific set of conditions at a specific time. Mixtures of peptides, such as those generated from enzymatic (e.g., trypsin) digestion of globally recovered proteins (i.e. a proteome), are typically very complex and >100,000 different molecular species may be observable using MS detection [1]. LC separations implemented prior to MS for broad protein identification have three major roles: 1) to isolate individual components or reduce complexity as much as possible, 2) to increase sensitivity by concentrating the components into narrow zones prior to MS, and 3) to eliminate or displace interfering species (e.g., salts and polymers) that may be present in proteomics samples. A desired quality of LC separation can be achieved from the use of either multiple steps of moderate quality separations, or fewer steps of high power separations. The former approach is generally more easily accessible for very high quality separations due to the variety of commercialized LC platforms available, while the latter still often requires considerable developmental efforts (for both columns and instrumentation). In addition tomore » proteomics data quality, other differences between these two approaches include proteomics analysis time and sample consumption (and subsequent analysis costs), as well as direct impact on potential proteomics applications that have special requirements in terms of analysis coverage, sample size, dynamic range, sensitivity, and throughput.« less