2 research outputs found

    In-Gel Nonspecific Proteolysis for Elucidating Glycoproteins: A Method for Targeted Protein-Specific Glycosylation Analysis in Complex Protein Mixtures

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    Determining protein-specific glycosylation in protein mixtures remains a difficult task. A common approach is to use gel electrophoresis to isolate the protein followed by glycan release from the identified band. However, gel bands are often composed of several proteins. Hence, release of glycans from specific bands often yields products not from a single protein but a composite. As an alternative, we present an approach whereby glycans are released with peptide tags allowing verification of glycans bound to specific proteins. We term the process in-gel nonspecific proteolysis for elucidating glycoproteins (INPEG). INPEG combines rapid gel separation of a protein mixture with in-gel nonspecific proteolysis of protein bands followed by tandem mass spectrometry (MS) analysis of the resulting N- and O-glycopeptides. Here, in-gel digestion is shown for the first time with nonspecific and broad specific proteases such as Pronase, proteinase K, pepsin, papain, and subtilisin. Tandem MS analysis of the resulting glycopeptides separated on a porous graphitized carbon (PGC) chip was achieved via nanoflow liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (nano-LC/Q-TOF MS). In this study, rapid and automated glycopeptide assignment was achieved via an in-house software (Glycopeptide Finder) based on a combination of accurate mass measurement, tandem MS data, and predetermined protein identification (obtained via routine shotgun analysis). INPEG is here initially validated for O-glycosylation (κ casein) and N-glycosylation (ribonuclease B). Applications of INPEG were further demonstrated for the rapid determination of detailed site-specific glycosylation of lactoferrin and transferrin following gel separation and INPEG analysis on crude bovine milk and human serum, respectively

    Automated Assignments of N- and O‑Site Specific Glycosylation with Extensive Glycan Heterogeneity of Glycoprotein Mixtures

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    Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles
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