E. Mostovenko, H. C. Scott, O. Klychnikov, H. Dalebout, A. Deelder, Magnus Palmblad
{"title":"Protein Fractionation for Quantitative Plasma Proteomics by Semi-Selective Precipitation","authors":"E. Mostovenko, H. C. Scott, O. Klychnikov, H. Dalebout, A. Deelder, Magnus Palmblad","doi":"10.4172/JPB.1000239","DOIUrl":null,"url":null,"abstract":"Blood plasma is a highly complex mixture of proteins, metabolites and lipids, and a rich source of potential biomarkers for a range of diseases and conditions. The wide range in protein abundance poses a tremendous challenge for plasma proteomics. However, as a relatively small number of proteins make up most of the total protein pool, the concentration range can be compressed by depletion of abundant proteins, such as albumin. To reduce sample complexity and increase the protein coverage, we have developed a sample preparation method based on semi-selective precipitation with acetonitrile at different pH and built a data analysis pipeline, combining different search strategies. The method we propose is reproducible and easily parallelised (high throughput), and may be well suited to fractionate plasma for label-free quantitative proteomics in large clinical studies. Up to 90% of albumin and other abundant proteins were removed by adding an equal volume of acetonitrile to the samples adjusted to pH 5.","PeriodicalId":354602,"journal":{"name":"Journal of Proteomics & Bioinformatics","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteomics & Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/JPB.1000239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Blood plasma is a highly complex mixture of proteins, metabolites and lipids, and a rich source of potential biomarkers for a range of diseases and conditions. The wide range in protein abundance poses a tremendous challenge for plasma proteomics. However, as a relatively small number of proteins make up most of the total protein pool, the concentration range can be compressed by depletion of abundant proteins, such as albumin. To reduce sample complexity and increase the protein coverage, we have developed a sample preparation method based on semi-selective precipitation with acetonitrile at different pH and built a data analysis pipeline, combining different search strategies. The method we propose is reproducible and easily parallelised (high throughput), and may be well suited to fractionate plasma for label-free quantitative proteomics in large clinical studies. Up to 90% of albumin and other abundant proteins were removed by adding an equal volume of acetonitrile to the samples adjusted to pH 5.