Improved and semi-automated reductive β-elimination workflow for higher throughput protein O-glycosylation analysis

PLoS One. 2019 Jan 17;14(1):e0210759. doi: 10.1371/journal.pone.0210759. eCollection 2019.

Abstract

Protein O-glycosylation has shown to be critical for a wide range of biological processes, resulting in an increased interest in studying the alterations in O-glycosylation patterns of biological samples as disease biomarkers as well as for patient stratification and personalized medicine. Given the complexity of O-glycans, often a large number of samples have to be analysed in order to obtain conclusive results. However, most of the O-glycan analysis work done so far has been performed using glycoanalytical technologies that would not be suitable for the analysis of large sample sets, mainly due to limitations in sample throughput and affordability of the methods. Here we report a largely automated system for O-glycan analysis. We adapted reductive β-elimination release of O-glycans to a 96-well plate system and transferred the protocol onto a liquid handling robot. The workflow includes O-glycan release, purification and derivatization through permethylation followed by MALDI-TOF-MS. The method has been validated according to the ICH Q2 (R1) guidelines for the validation of analytical procedures. The semi-automated reductive β-elimination system enabled for the characterization and relative quantitation of O-glycans from commercially available standards. Results of the semi-automated method were in good agreement with the conventional manual in-solution method while even outperforming it in terms of repeatability. Release of O-glycans for 96 samples was achieved within 2.5 hours, and the automated data acquisition on MALDI-TOF-MS took less than 1 minute per sample. This largely automated workflow for O-glycosylation analysis showed to produce rapid, accurate and reliable data, and has the potential to be applied for O-glycan characterization of biological samples, biopharmaceuticals as well as for biomarker discovery.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Automation
  • Cattle
  • Glycoproteins / chemistry*
  • Glycosylation
  • High-Throughput Screening Assays / methods*
  • Humans
  • Limit of Detection
  • Mucins / chemistry
  • Polysaccharides / analysis*
  • Reproducibility of Results
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / methods*
  • Submandibular Gland / chemistry
  • Workflow

Substances

  • Glycoproteins
  • Mucins
  • Polysaccharides

Grants and funding

Authors: M.K, R.P.K, R.A.G, M.W, D.I.R.S. This work was supported by the European Commission, Horizon 2020 GlyCoCan programme under grant agreement number 676421 (https://glycocan.eu/) and Ludger Ltd (https://www.ludger.com/). The funder provided support in the form of salaries for authors MK, RPK, RAG, DIRS, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.