GlycoPep Grader: A web-based utility for assigning the composition of N-linked glycopeptides

GlycoPep Grader (GPG) is a freely-available software tool designed to accelerate the process of accurately determining glycopeptide composition from tandem mass spectrometric data. GPG relies on the identification of unique dissociation patterns shown for high mannose, hybrid, and complex N-linked glycoprotein types, including patterns specific to those structures containing fucose or sialic acid residues. The novel GPG scoring algorithm scores potential candidate compositions of the same nominal mass against MS/MS data through evaluation of the Y1 ion and other peptide-containing product ions, across multiple charge states, when applicable. In addition to evaluating the peptide portions of a given glycopeptide, the GPG algorithm predicts and scores product ions that result from unique neutral losses of terminal glycans. GPG has been applied to a variety of glycoproteins, including RNase B, asialofetuin and transferrin, and the HIV envelope glycoprotein, CON-S gp140 CFI. The GPG software is implemented predominantly in PostgreSQL, with PHP as the presentation tier, and is publically accessible online. Thus far, the algorithm has identified the correct compositional assignment from multiple candidate N-glycopeptides in all tests performed

Software for Automated Interpretation of Mass Spectrometry Data from Glycans and Glycopeptides

The purpose of this review is to provide those interested in glycosylation analysis with the most updated information on the availability of automated tools for MS characterization of N-linked and O-linked glycosylation types. Specifically, this review describes software tools that facilitate elucidation of glycosylation from MS data on the basis of mass alone, as well as software designed to speed the interpretation of glycan and glycopeptide fragmentation from MS/MS data. This review focuses equally on software designed to interpret the composition of released glycans and on tools to characterize N-linked and O-linked glycopeptides. Several websites have been compiled and described that will be helpful to the reader who is interested in further exploring the described tools

MS/MS Analysis and Automated Tool Development for Protein Post-Translational Modifications

Protein post-translational modifications (PTMs) are important for a variety of reasons. PTMs confer the final protein product and biological functionality onto a nascent protein chain. Two common PTMs are glycosylation and disulfide bond formation. Both glycosylation and disulfide bond formation contribute to a variety of biological processes, including protein folding and stabilization. Mass spectrometry (MS) has shown to be an essential technique to study PTMs, especially when tandem mass spectrometry (MS/MS) experiments are performed. In the characterization of PTMs using MS/MS, different fragmentation techniques are often used. Regardless of the dissociation method that is employed, MS/MS data interpretation is a tedious and lengthy process. To render this analysis more efficient, the use of automated tools is necessary. In this work, collision induced dissociation (CID) MS/MS experiments were carried out in order to create a set of fragmentation rules applicable to any N-linked glycopeptide. These rules were then used to develop an algorithm to power publicly available software that accurately determines glycopeptide composition from MS/MS data. This program greatly reduces the time it takes researchers to manually assign the identity of an N-linked glycopeptide to an acquired CID spectrum. In addition, electron transfer dissociation (ETD) experiments were performed in order to devise a computational approach that works to determine precursor charge state directly from MS/MS data of peptides containing disulfide bonds. Lastly, alternate fragmentation patterns found to be detected in glycopeptides containing labile monosaccharide residues such as sialic acid are discussed. These patterns, along with other trends noticed after extensive analysis of N-linked glycopeptide CID data, were then used to propose future updates to the GPG analysis tool

Characterizing O-linked glycopeptides by electron transfer dissociation: fragmentation rules and applications in data analysis

Studying protein O-glycosylation remains an analytical challenge. Different from N-linked glycans, the O-glycosylation site is not within a known consensus sequence. Additionally, O-glycans are heterogeneous with numerous potential modification sites. Electron transfer dissociation (ETD) is the method of choice in analyzing these glycopeptides since the glycan side chain is intact in ETD, and the glycosylation site can be localized on the basis of the c and z fragment ions. Nonetheless, new software is necessary for interpreting O-glycopeptide ETD spectra in order to expedite the analysis workflow. To address the urgent need, we studied the fragmentation of O-glycopeptides in ETD and found useful rules that facilitate their identification. By implementing the rules into an algorithm to score potential assignments against ETD-MS/MS data, we applied the method to glycopeptides generated from various O-glycosylated proteins including mucin, erythropoietin, fetuin and an HIV envelope protein, 1086.C gp120. The site-specific O-glycopeptide composition was correctly assigned in every case, proving the merits of our method in analyzing glycopeptide ETD data. The algorithm described herein can be easily incorporated into other automated glycomics tools

On the Use of DHB/Aniline and DHB/N,N-Dimethylaniline Matrices for Improved Detection of Carbohydrates: Automated Identification of Oligosaccharides and Quantitative Analysis of Sialylated Glycans by MALDI-TOF Mass Spectrometry

This study demonstrates the application of 2,5-dihydrohybenzoic acid/aniline (DHB/An) and 2,5-dihydroxybenzoic acid/N,N-dimethylaniline (DHB/DMA) matrices for automated identification and quantitative analysis of native oligosaccharides by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Both matrices are shown to be superior to pure DHB for native glycans in terms of signal intensities of analytes and homogeneity of sample distribution throughout the crystal layer. On-target formation of stable aniline Schiff base derivatives of glycans in DHB/An and the complete absence of such products in the mass spectra acquired in DHB/DMA matrix provide a platform for automated identification of reducing oligosaccharides in the MALDI mass spectra of complex samples. The study also shows how enhanced sensitivity is achieved with the use of these matrices and how the homogeneity of deposited sample material may be exploited for quick and accurate quantitative analysis of native glycan mixtures containing neutral and sialylated oligosaccharides in the low-nanogram to mid-picogram range

GlycoPep Detector: A tool for assigning mass spectrometry data of N-linked glycopeptides based on their ETD spectra

Electron transfer dissociation (ETD) is commonly used in fragmenting N-linked glycopeptides in their mass spectral analyses to complement collision induced dissociation (CID) experiments. The glycan remains intact through ETD, while the peptide backbone is cleaved, providing the sequence of amino acids for a glycopeptide. Nonetheless, data analysis is a major bottleneck to high throughput glycopeptide identification based on ETD data, due to the complexity and diversity of ETD mass spectra compared to CID counterparts. GlycoPep Detector (GPD) is a web-based tool to address this challenge. It filters out noise peaks that interfere with glycopeptide sequencing, correlates input glycopeptide compositions with the ETD spectra, and assigns a score for each candidate. By considering multiple ion series (c-, z- and y-ions) and scoring them separately, the software gives more weighting to the ion series that matches peaks of high intensity in the spectra. This feature enables the correct glycopeptide to receive a high score while keeping scores of incorrect compositions low. GPD has been utilized to interpret data collected on six model glycoproteins (RNase B, avidin, fetuin, asialofetuin, transferrin and AGP) as well as a clade C HIV envelope glycoprotein, C.97ZA012 gp140ΔCFI. In every assignment made by GPD, the correct glycopeptide composition earns a score that is about two-fold higher than other incorrect glycopeptide candidates (decoys). The software can be accessed at http://glycopro.chem.ku.edu/ZZKHome.php