The University of Copenhagen has developed a new method of O-link sugar proteomics - Glyco-DIA.

On August 5, 2019, Nature Methods published the latest research from Sergey Y. Vakhrushev's team at the Centre for Sugar Studies at the University of Copenhagen, Denmark (Copenhagen Center for Glycomics, CCG), with Glyco-DIA: a ponto for quantitative o-glycoproteomics with a sicco-boosted glycococos.
greatly improves the detection of sugar proteomics in different samples by introducing the new data non-dependent acquisition model (Data-Independent Acquisition, DIA) in mass spectrometry for the first time in O-sugar proteomics.
high-quality and comprehensive peptide spectrum library is one of the most central prerequisites for data analysis based on DIA technology.
in this study, based on the SimpleCell technology platform developed by CCG, the researchers first identified more than 11,000 complete glycopeptide sequences in more than 2,000 glycoproteins, including multiple SimpleCell cell lines, common cell lines, and human serums, greatly expanding the human O-sugar protein group, and converting these identified complete glycopeptides into a high-quality O-glycopeptide map.
the structure of these O-glycopeptides is limited to Tn structure or T structure due to the richness of coagulation.
and the researchers constructed an O-glycend spectrum with the same peptide segment sequence as these glycopeptides and many different sugar chain structures through the characteristics of high-energy induced dissocoutrageous (HCD) in mass spectrometry, and could theoretically be applied to more different sugar chain structures and other post-translation modifications.
built a large-scale O-glycopeptide spectrum library, the researchers first compared the DIA method with the traditional data-dependent acquisition (Data-Dependent Acquisition, DDA) method.
by analyzing the performance of a series of post-enrichment O-glycopeptide samples in DDA and DIA, the DIA method resulted in significantly more identification and demonstrated the ability to accurately quantify unlabeled.
then the researchers applied this method to human serum samples.
, by analyzing uncollected serum samples equivalent to just 1 microliter, the researchers identified nearly 100 glycoproteins.
and based on the development of an O-glycopeptide spectrum library in this study, the researchers were able to identify and quantify relatively many different sugar chain structures and corresponding non-glycogenized peptide segments at the same O-glycosinization site.
this study provides a powerful tool for sugar biologists to further study the role of glycosylation and is expected to be used in the coming clinical (sugar) proteomics research and clinical diagnosis.
dr. Ye Ye, of the Center for Sugar Studies at the University of Copenhagen in Denmark, is the first author of this paper, and Professor Mao Yang of the School of Pharmacy at Sun Yat-sen University is also involved in this work.
study background GalNAc-type O-glycosis, also known as mucin-type O-glycosylization, is one of the most common and complex and variable protein translation post-translation modifications.
common O-sugars have four different core structures (core1 - core4) and can also connect different monosaccharides to form more complex and diverse structures. O-glycosylation in
proteins has a wide range of biological functions, especially core1 and its associated types of O-sugar are most associated with disease.
for example, core1 (T-antigen), a single GalNAc (Tn-antigen) and high expression of their saliva acidification types are common features of a variety of tumor cells.
, although the study of proteomics based on biomass spectrum and sugar proteomics has made rapid progress, there are still significant challenges in the identification and quantification of complete glycopeptides at the sugar proteomiclevel level.
Source: BioArt.