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Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy.
Cai, Wenxuan; Tucholski, Trisha; Chen, Bifan; Alpert, Andrew J; McIlwain, Sean; Kohmoto, Takushi; Jin, Song; Ge, Ying.
Afiliação
  • Cai W; Department of Cell and Regenerative Biology, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
  • Tucholski T; Molecular and Cellular Pharmacology Training Program, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
  • Chen B; Department of Chemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
  • Alpert AJ; Department of Chemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
  • McIlwain S; Department of Cell and Regenerative Biology, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
  • Kohmoto T; PolyLC Inc. , Columbia, Maryland 21045, United States.
  • Jin S; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
  • Ge Y; UW Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
Anal Chem ; 89(10): 5467-5475, 2017 05 16.
Article em En | MEDLINE | ID: mdl-28406609
Mass spectrometry (MS)-based top-down proteomics is a powerful method for the comprehensive analysis of proteoforms that arise from genetic variations and post-translational modifications (PTMs). However, top-down MS analysis of high molecular weight (MW) proteins remains challenging mainly due to the exponential decay of signal-to-noise ratio with increasing MW. Size exclusion chromatography (SEC) is a favored method for size-based separation of biomacromolecules but typically suffers from low resolution. Herein, we developed a serial size exclusion chromatography (sSEC) strategy to enable high-resolution size-based fractionation of intact proteins (10-223 kDa) from complex protein mixtures. The sSEC fractions could be further separated by reverse phase chromatography (RPC) coupled online with high-resolution MS. We have shown that two-dimensional (2D) sSEC-RPC allowed for the identification of 4044 more unique proteoforms and a 15-fold increase in the detection of proteins above 60 kDa, compared to one-dimensional (1D) RPC. Notably, effective sSEC-RPC separation of proteins significantly enhanced the detection of high MW proteins up to 223 kDa and also revealed low abundance proteoforms that are post-translationally modified. This sSEC method is MS-friendly, robust, and reproducible and, thus, can be applied to both high-efficiency protein purification and large-scale proteomics analysis of cell or tissue lysate for enhanced proteome coverage, particularly for low abundance and high MW proteoforms.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Proteômica Limite: Humans Idioma: En Revista: Anal Chem Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Proteômica Limite: Humans Idioma: En Revista: Anal Chem Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos