Protein glycosylation is involved in a broad range of biological processes that regulate protein function and control cell fate. As aberrant glycosylation has been found to be implicated in numerous diseases, the study and large-scale characterization of protein glycosylation is of great interest not only to the biological and biomedical research community, but also to the pharmaceutical and biotechnology industry. Due to the complex chemical structure and differing chemical properties of the protein/peptide and glycan moieties, the analysis and structural characterization of glycoproteins has been proven to be a difficult task. Large-scale endeavors have been further limited by the dynamic outcome of the glycosylation process itself, and, occasionally, by the low abundance of glycoproteins in biological samples. Recent advances in MS instrumentation and progress in miniaturized technologies for sample handling, enrichment and separation, have resulted in robust and compelling analysis strategies that effectively address the challenges of the glycoproteome. This review summarizes the key steps that are involved in the development of efficient glycoproteomic analysis methods, and the latest innovations that led to successful strategies for the characterization of glycoproteins and their corresponding glycans. As a follow-up to this work, we review innovative capillary and microfluidic-MS workflows for the identification, sequencing and characterization of glycoconjugates.
"Glycan analysis from a biological sample requires the release of an intact glycan from the protein followed by separation and detection using chromatography or mass spectrometry based glycan methods. Various combinations of methods are also used in glycan isolation and characterization as summarized in recent articles [62-72]. "
[Show abstract][Hide abstract] ABSTRACT: Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research.
"However, lectin affinity chromatography is far from ideal [32-34], as the enrichment efficiency of the method is unsatisfactory, is easily affected by buffer conditions, and non-specifically recognizes glycans [35,36]. In this study, we attempted to stabilize the binding and elution buffers, including adjustment of pH, concentration, and binding/eluting time, in different experiments, to overcome these disadvantages. "
[Show abstract][Hide abstract] ABSTRACT: The complexity of protein glycosylation makes it difficult to characterize glycosylation patterns on a proteomic scale. In this study, we developed an integrated strategy for comparatively analyzing N-glycosylation/glycoproteins quantitatively from complex biological samples in a high-throughput manner. This strategy entailed separating and enriching glycopeptides/glycoproteins using lectin affinity chromatography, and then tandem labeling them with 18O/16O to generate a mass shift of 6 Da between the paired glycopeptides, and finally analyzing them with liquid chromatography-mass spectrometry (LC-MS) and the automatic quantitative method we developed based on Mascot Distiller.
The accuracy and repeatability of this strategy were first verified using standard glycoproteins; linearity was maintained within a range of 1:10-10:1. The peptide concentration ratios obtained by the self-build quantitative method were similar to both the manually calculated and theoretical values, with a standard deviation (SD) of 0.023-0.186 for glycopeptides. The feasibility of the strategy was further confirmed with serum from hepatocellular carcinoma (HCC) patients and healthy individuals; the expression of 44 glycopeptides and 30 glycoproteins were significantly different between HCC patient and control serum.
This strategy is accurate, repeatable, and efficient, and may be a useful tool for identification of disease-related N-glycosylation/glycoprotein changes.
"The general workflow in glycoproteomics consists of glycoprotein or glycopeptide enrichment, multidimensional protein or peptide separation, tandem mass spectrometric analysis , and bioinformatic data interpretation  . Based on the general pipeline of glycoproteomics, two complementary strategies (the " bottom-up " and the " top-down " ) are currently widely used to identify proteins in glycoproteomics (Fig. 1) and each strategy has its own strengths and weaknesses (although sometimes a combination of these two complementary strategies being employed)   . "
[Show abstract][Hide abstract] ABSTRACT: Glycobioinformatics is a rapidly developing field providing a vital support for mass spectrometry based glycoproteomics research. Recent advances in mass spectrometry greatly increased technological capabilities for high throughput glycopeptide analysis. However, interpreting mass spectrometry output, in terms of identifying glycan structures, attachment sites and glycosylation linkages still presents multiple challenges. Here, we discuss current strategies used in mass spectrometry based glycoproteomics and bioinformatics tools available for mass spectrometry based glycopeptide and glycan analysis. We also provide a brief overview of recent efforts in glycobioinformatics such as the new initiative UniCarbKB directed toward developing more comprehensive and unified glycobioinformatics platforms. With regards to glycobioinformatics tools and applications, we do not express our personal preferences or biases, but rather focus on providing a concise description of main features and functionalities of each application with the goal of assisting readers in making their own choices and identifying and locating glycobioinformatics tools most suitable for achieving their experimental objectives.
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