Literature DB >> 22239700

Enhanced separation and characterization of deamidated peptides with RP-ERLIC-based multidimensional chromatography coupled with tandem mass spectrometry.

Piliang Hao1, Jingru Qian, Bamaprasad Dutta, Esther Sok Hwee Cheow, Kae Hwan Sim, Wei Meng, Sunil S Adav, Andrew Alpert, Siu Kwan Sze.   

Abstract

Deamidation of asparaginyl residues in proteins produces a mixture of asparaginyl, n-aspartyl, and isoaspartyl residues, which affects the proteins' structure, function, and stability. Thus, it is important to identify and quantify the products to evaluate the effects in biological systems. It is still a challenging task to distinguish between the n-Asp and isoAsp deamidation products in a proteome-wide analysis because of their similar physicochemical properties. The quantification of the isomeric deamidated peptides is also rather difficult because of their coelution/poor separation in reverse-phase liquid chromatography (RPLC). We here propose a RP-ERLIC-MS/MS approach for separating and quantifying on a proteome-wide scale the three products related to deamidation of the same peptide. The key to the method is the use of RPLC in the first dimensional separation and ERLIC (electrostatic repulsion-hydrophilic interaction chromatography) in the second, with direct online coupling to tandem MS. The coelution of the three deamidation-related peptides in RPLC is then an asset, as they are collected in the same fraction. They are then separated and identified in the second dimension with ERLIC, which separates peptides on the basis of both pI and GRAVY values. The coelution of the three products in RPLC and their efficient separation in ERLIC were validated using synthetic peptides, and the performance of ERLIC-MS/MS was tested using peptide mixtures from two proteins. Applying this sequence to rat liver tissue, we identified 302 unique N-deamidated peptides, of which 20 were identified via all three deamidation-related products and 70 of which were identified via two of them.

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Year:  2012        PMID: 22239700     DOI: 10.1021/pr201048c

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  11 in total

1.  Fast and easy phosphopeptide fractionation by combinatorial ERLIC-SCX solid-phase extraction for in-depth phosphoproteome analysis.

Authors:  Mostafa Zarei; Adrian Sprenger; Michal Rackiewicz; Joern Dengjel
Journal:  Nat Protoc       Date:  2015-12-03       Impact factor: 13.491

2.  Antibody characterization using novel ERLIC-MS/MS-based peptide mapping.

Authors:  Jing Zhen; John Kim; Ying Zhou; Ervinas Gaidamauskas; Shyamsundar Subramanian; Ping Feng
Journal:  MAbs       Date:  2018-09-11       Impact factor: 5.857

3.  LERLIC-MS/MS for In-depth Characterization and Quantification of Glutamine and Asparagine Deamidation in Shotgun Proteomics.

Authors:  Xavier Gallart-Palau; Aida Serra; Siu Kwan Sze
Journal:  J Vis Exp       Date:  2017-04-09       Impact factor: 1.355

Review 4.  Protein analysis by shotgun/bottom-up proteomics.

Authors:  Yaoyang Zhang; Bryan R Fonslow; Bing Shan; Moon-Chang Baek; John R Yates
Journal:  Chem Rev       Date:  2013-02-26       Impact factor: 60.622

5.  The Separation and Quantitation of Peptides with and without Oxidation of Methionine and Deamidation of Asparagine Using Hydrophilic Interaction Liquid Chromatography with Mass Spectrometry (HILIC-MS).

Authors:  Majors J Badgett; Barry Boyes; Ron Orlando
Journal:  J Am Soc Mass Spectrom       Date:  2017-01-03       Impact factor: 3.109

6.  Gas Phase Ion Chemistry to Determine Isoaspartate in a Peptide Backbone.

Authors:  S T Ayrton; X Chen; R M Bain; C J Pulliam; M Achmatowicz; T G Flick; D Ren; R G Cooks
Journal:  J Am Soc Mass Spectrom       Date:  2018-03-15       Impact factor: 3.109

7.  LC-MS/MS identification of the O-glycosylation and hydroxylation of amino acid residues of collagen α-1 (II) chain from bovine cartilage.

Authors:  Ehwang Song; Yehia Mechref
Journal:  J Proteome Res       Date:  2013-07-23       Impact factor: 4.466

8.  Online nanoscale ERLIC-MS outperforms RPLC-MS for shotgun proteomics in complex mixtures.

Authors:  Ebbing P de Jong; Timothy J Griffin
Journal:  J Proteome Res       Date:  2012-09-14       Impact factor: 4.466

Review 9.  Insight of brain degenerative protein modifications in the pathology of neurodegeneration and dementia by proteomic profiling.

Authors:  Sunil S Adav; Siu Kwan Sze
Journal:  Mol Brain       Date:  2016-11-03       Impact factor: 4.041

Review 10.  Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples.

Authors:  Peter Feist; Amanda B Hummon
Journal:  Int J Mol Sci       Date:  2015-02-05       Impact factor: 5.923

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