Fast and accurate disulfide bridge detection.

EThcD FAIMS MAAH XlinkX/PD disulfide bridge

Journal

Molecular & cellular proteomics : MCP
ISSN: 1535-9484
Titre abrégé: Mol Cell Proteomics
Pays: United States
ID NLM: 101125647

Informations de publication

Date de publication:
02 Apr 2024
Historique:
received: 16 11 2023
revised: 08 03 2024
accepted: 01 04 2024
medline: 5 4 2024
pubmed: 5 4 2024
entrez: 4 4 2024
Statut: aheadofprint

Résumé

Recombinant expression of proteins, propelled by therapeutic antibodies, has evolved into a multi-billion-dollar industry. Essential here is quality control assessment of critical attributes such as sequence fidelity, proper folding, and post-translational modifications (PTMs). Errors can lead to diminished bioactivity and, in the context of therapeutic proteins, an elevated risk for immunogenicity. Over the years, many techniques were developed and applied to validate proteins in a standardized and high-throughput fashion. One parameter has, however, so far been challenging to assess. Disulfide bridges, covalent bonds linking two Cysteine residues, assist in the correct folding and stability of proteins and thus have a major influence on their efficacy. Mass spectrometry promises to be an optimal technique to uncover them in a fast and accurate fashion. In this work, we present a unique combination of sample preparation, data acquisition and analysis facilitating the rapid and accurate assessment of disulfide bridges in purified proteins. Through microwave-assisted acid hydrolysis (MAAH), the proteins are digested rapidly and artifact-free into peptides, with a substantial degree of overlap over the sequence. The nonspecific nature of this procedure, however, introduces chemical background which is efficiently removed by integrating ion mobility preceding the mass spectrometric measurement. The nonspecific nature of the digestion step additionally necessitates new developments in data analysis, for which we extended the XlinkX node in Proteome Discoverer (XlinkX/PD) to efficiently process the data and ensure correctness through effective false discovery rate correction. The entire workflow can be completed within one hour, allowing for high-throughput, high-accuracy disulfide mapping.

Identifiants

pubmed: 38574859
pii: S1535-9476(24)00049-5
doi: 10.1016/j.mcpro.2024.100759
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

100759

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests YH, YS, and RV are employees of Thermo Fisher Scientific, the manufacturer of the Orbitrap and the Proteome Discoverer platforms used in this work.

Auteurs

Søren Heissel (S)

Proteomics Resource Center, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA. Electronic address: sheissel@rockefeller.edu.

Yi He (Y)

Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States.

Andris Jankevics (A)

Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH Utrecht, The Netherlands; Structural Proteomics Group, Department of Biochemistry and Systems Biology, University of Liverpool.

Yuqi Shi (Y)

Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States.

Henrik Molina (H)

Proteomics Resource Center, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA.

Rosa Viner (R)

Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States. Electronic address: rosa.viner@thermofisher.com.

Richard A Scheltema (RA)

Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH Utrecht, The Netherlands; Structural Proteomics Group, Department of Biochemistry and Systems Biology, University of Liverpool. Electronic address: Richard.Scheltema@liverpool.ac.uk.

Classifications MeSH