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Twoplex 12/13C6 aniline stable isotope and linkage-specific sialic acid labeling 2D-LC-MS workflow for quantitative N-glycomics

  • Simone Albrecht
  • , Stefan Mittermayr
  • , Josh Smith
  • , Silvia Millán Martín
  • , Margaret Doherty
  • , Jonathan Bones
    • National Institute for Bioprocessing Research and Training

    Research output: Contribution to journalArticlepeer-review

    14 Citations (Scopus)

    Abstract

    Quantitative glycomics represents an actively expanding research field ranging from the discovery of disease-associated glycan alterations to the quantitative characterization of N-glycans on therapeutic proteins. Commonly used analytical platforms for comparative relative quantitation of complex glycan samples include MALDI-TOF-MS or chromatographic glycan profiling with subsequent data alignment and statistical evaluation. Limitations of such approaches include run-to-run technical variation and the potential introduction of subjectivity during data processing. Here, we introduce an offline 2D LC-MSE workflow for the fractionation and relative quantitation of twoplex isotopically labeled N-linked oligosaccharides using neutral 12C6 and 13C6 aniline (Δmass = 6 Da). Additional linkage-specific derivatization of sialic acids using 4-(4,6-dimethoxy-1,3,5-trizain-2-yl)-4-methylmorpholinium chloride offered simultaneous and advanced in-depth structural characterization. The potential of the method was demonstrated for the differential analysis of structurally defined N-glycans released from serum proteins of patients diagnosed with various stages of colorectal cancer. The described twoplex 12C6/13C6 aniline 2D LC-MS platform is ideally suited for differential glycomic analysis of structurally complex N-glycan pools due to combination and analysis of samples in a single LC-MS injection and the associated minimization in technical variation.

    Original languageEnglish
    Article number1600304
    JournalProteomics
    Volume17
    Issue number1-2
    DOIs
    Publication statusPublished - 1 Jan 2017

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • DMT-MM
    • Glycan quantitation
    • Glycoproteomics
    • LC-MS
    • Sialic acid
    • Stable isotope aniline

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