Getting more for less: new software solutions for glycoproteomics

Construction of dual-hydrophilic metal-organic framework with hierarchical porous structure for efficient glycopeptide enrichment

As an important role in life activities, it is necessary and important to study protein glycosylation. The pre-enrichment of N-glycopeptides is a significant step in glycoproteomics research. According to the inherent size, hydrophilicity and other properties of N-glycopeptides, affinity materials designed to match them will be able to separate N-glycopeptides from complex samples. In this work, we designed and prepared dual-hydrophilic hierarchical porous metal-organic frameworks (MOFs) nanospheres by metal-organic assembly (MOA) based template method and post-synthesis modification strategy. The hierarchical porous structure significantly improved the diffusion rate and binding sites for N-glycopeptide enrichment. Furthermore, the combination of hydrophilic MOFs and small molecules endowed the as-prepared MOFs nanospheres excellent hydrophilicity, which is conducive to the enrichment of N-glycopeptides based on hydrophilic interaction liquid chromatography (HILIC). Therefore, the nanospheres showed surprising enrichment ability for N-glycopeptides such as excellent selectivity (1/500, human serum immunoglobulin G/bovine serum albumin, m/m) and extremely low detective limitation (0.5 fmol). Meanwhile, 550 N-glycopeptides were identified from rat liver samples, proving its application potential in glycoproteomics research and providing design idea for porous affinity materials.

pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19-89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

What Can N-glycomics and N-glycoproteomics of Cerebrospinal Fluid Tell Us about Alzheimer Disease?

Proteomics-large-scale studies of proteins-has over the last decade gained an enormous interest for studies aimed at revealing proteins and pathways involved in disease. To fully understand biological and pathological processes it is crucial to also include post-translational modifications in the "omics". To this end, glycomics (identification and quantification of glycans enzymatically or chemically released from proteins) and glycoproteomics (identification and quantification of peptides/proteins with the glycans still attached) is gaining interest. The study of protein glycosylation requires a workflow that involves an array of sample preparation and analysis steps that needs to be carefully considered. Herein, we briefly touch upon important steps such as sample preparation and preconcentration, glycan release, glycan derivatization and quantification and advances in mass spectrometry that today are the work-horse for glycomics and glycoproteomics studies. Several proteins related to Alzheimer disease pathogenesis have altered protein glycosylation, and recent glycomics studies have shown differences in cerebrospinal fluid as well as in brain tissue in Alzheimer disease as compared to controls. In this review, we discuss these techniques and how they have been used to shed light on Alzheimer disease and to find glycan biomarkers in cerebrospinal fluid.

Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.