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  • P-III-0906

Chasing O-glycopeptides: comparison of two sample preparation methods

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Glycobiology Insights

Poster

Chasing O-glycopeptides: comparison of two sample preparation methods

Topic

  • Glycobiology Insights

Authors

Ádám Pap (Szeged / HU), Zsuzsanna Darula (Szeged / HU), Katalin Medzihradszky F. (Szeged / HU), Éva Hunyadi-Gulyás (Szeged / HU), Aladár Pettkó-Szandtner (Szeged / HU)

Abstract

Introduction

The successful analysis of post-translational modifications depends on multiple factors, such as complete digestion of the sample and efficient enrichment of the peptides of interest. This work focuses on the former factor by comparing two sample preparation methods: filter-aided sample preparation (FASP) and suspension trapping (S-Trap) for the characterization of O-glycosylation of human urinary proteins.

Method

Urine samples were pooled and 3-3 aliquots (5mg protein per aliquot) were processed using the FASP and the S-Trap protocol, respectively. Samples were digested with trypsin and subsequently with PNGaseF. After the enzymatic removal of N-glycans, O-glycopeptides were enriched using a two-round lectin affinity chromatography using wheat germ agglutinin. The enriched samples were analysed using LC-MS/MS and applying a HCD product ion-dependent EThcD data acquisition method. Glycopeptides were identified using the Protein Prospector Batch Tag Web search engine, semiquantitative comparison of the identified glycopeptides was performed using spectral counting.

Results

We observed no difference in the identified O-glycan pool between the results of the two sample preparation methods. The top 50% of the identified MS/MS spectra for both sample preparation methods belonged to O-glycopeptides carrying additive masses of 656 (HexNAcHexNeuAc), 947 (HexNAcHexNeuAc2) and 1312 (HexNAc2Hex2NeuAc2). The most interesting finding was that the S-Trap method covered a subset of the O-glycoproteins compared to the FASP protocol. This difference in the identified glycoproteins was observed for the HCD and the EThcD data as well.

Acknowledgements

This work was supported by the following grants: EU Horizon 2020 Grant No.: 739593; KIM NKFIA 2022-2.1.1-NL-2022-00005; GINOP-2.3.2-15-2016-00001; GINOP-2.3.2-15-2016-00020.

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