Automatic identification of site-specific glycosylation in proteomics using mass spectrometry and bioinformatics

Abstract

Protein glycosylation, one of the most time-honored posttranslational modifications in proteins, plays vital roles in organic systems through a variety of processes, such as adhesion, signaling via cellular recognition, and response to unusual biological states. However, due to the complexity and heterogeneity of a glycoprotein, contemporary analyses focus in most cases on the identification of both glycosites or the released glycans only. In this study, we have developed MS-based high throughput technique for intact N-glycopeptides analysis, named GlycoProteomeAnalyzer (GPA) for analysis of N-and O-glycosylation in proteomics, which combines tandem Mass Spectrometry (MS) with a database search and algorithmic suite. We created novel scoring algorithms for confident identification of N- and O-glycosylation of proteins with calculation of False Discovery Rate (FDR). In our approach, all amino acid sequence as well as glycosylation website records had been got from the Uniprot database. From the Swiss-Prot accession variety of human protein, our GPA software automatically construct tryptic N- and O-glycopeptide database for the proteins in human plasma sample. It lets in automatic identification of site-specific N- and O-glycopeptides of protein combos using HCD, CID, and ETD MS/MS spectra with GPA- DB from Uniprot with estimated FDR ≤ 1%. GPA has been designed to easily handle high -throughput glycoproteomic statistics with a graphical user interface and verified on internet site (https://www.igpa.kr/). It can also be integrated with cloud computing carrier that eliminates the need for local clusters and will increase throughput of data analysis. Glycosylation, a particular top-down analysis, which affords the most direct method for obtaining records on glycans in a glycoprotein. By calculating the molecular weight variations between the peaks, it is viable to decide the types of glycan modifications on that protein. Such an analysis, however, regularly lacks sensitivity and structure information. Because of this, glycoprotein analyses are often divided into two primary strategies for accumulating glycoprotein information using MS techniques. One entails an evaluation of launched glycans, while the other includes characterizing glycopeptides that are got by proteolytic digestion of the unique glycoprotein.