Quantitative Glycomics: A Combined Analytical and Bioinformatics Approach

Expression of placental glycans and its role in regulating peripheral blood NK cells during preeclampsia: a perspective

Preeclampsia is a pregnancy-related multisystem disorder characterized by altered trophoblast invasion, oxidative stress, exacerbation of systemic inflammatory response, and endothelial damage. The pathogenesis includes hypertension and mild-to-severe microangiopathy in the kidney, liver, placenta, and brain. The main mechanisms involved in its pathogenesis have been proposed to limit trophoblast invasion and increase the release of extracellular vesicles from the syncytiotrophoblast into the maternal circulation, exacerbating the systemic inflammatory response. The placenta expresses glycans as part of its development and maternal immune tolerance during gestation. The expression profile of glycans at the maternal-fetal interface may play a fundamental role in physiological pregnancy changes and disorders such as preeclampsia. It is unclear whether glycans and their lectin-like receptors are involved in the mechanisms of maternal-fetal recognition by immune cells during pregnancy homeostasis. The expression profile of glycans appears to be altered in hypertensive disorders of pregnancy, which could lead to alterations in the placental microenvironment and vascular endothelium in pregnancy conditions such as preeclampsia. Glycans with immunomodulatory properties at the maternal-fetal interface are altered in early-onset severe preeclampsia, implying that innate immune system components, such as NK cells, exacerbate the systemic inflammatory response observed in preeclampsia. In this article, we discuss the evidence for the role of glycans in gestational physiology and the perspective of glycobiology on the pathophysiology of hypertensive disorders in gestation.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

Mass Spectrometry Imaging for Glycome in the Brain

Glycans are diverse structured biomolecules that play crucial roles in various biological processes. Glycosylation, an enzymatic system through which various glycans are bound to proteins and lipids, is the most common and functionally crucial post-translational modification process. It is known to be associated with brain development, signal transduction, molecular trafficking, neurodegenerative disorders, psychopathologies, and brain cancers. Glycans in glycoproteins and glycolipids expressed in brain cells are involved in neuronal development, biological processes, and central nervous system maintenance. The composition and expression of glycans are known to change during those physiological processes. Therefore, imaging of glycans and the glycoconjugates in the brain regions has become a “hot” topic nowadays. Imaging techniques using lectins, antibodies, and chemical reporters are traditionally used for glycan detection. However, those techniques offer limited glycome detection. Mass spectrometry imaging (MSI) is an evolving field that combines mass spectrometry with histology allowing spatial and label-free visualization of molecules in the brain. In the last decades, several studies have employed MSI for glycome imaging in brain tissues. The current state of MSI uses on-tissue enzymatic digestion or chemical reaction to facilitate successful glycome imaging. Here, we reviewed the available literature that applied MSI techniques for glycome visualization and characterization in the brain. We also described the general methodologies for glycome MSI and discussed its potential use in the three-dimensional MSI in the brain.

High-throughput and high-sensitivity N-Glycan profiling: A platform for biopharmaceutical development and disease biomarker discovery

Protein glycosylation contributes to critical biological function of glycoproteins. Glycan analysis is essential for the production of biopharmaceuticals as well as for the identification of disease biomarkers. However, glycans are highly heterogeneous, which has considerably hampered the progress of glycomics. Here, we present an improved 96-well plate format platform for streamlined glycan profiling that takes advantage of rapid glycoprotein denaturation, deglycosylation, fluorescent derivatization, and on-matrix glycan clean-up. This approach offers high sensitivity with consistent identification and quantification of diverse N-glycans across multiple samples on a high-throughput scale. We demonstrate its capability for N-glycan profiling of glycoproteins from various sources, including two recombinant monoclonal antibodies produced from Chinese Hamster Ovary cells, EG2-hFc and rituximab, polyclonal antibodies purified from human serum, and total glycoproteins from human serum. Combined with the complementary information obtained by sequential digestion from exoglycosidase arrays, this approach allows the detection and identification of multiple N-glycans in these complex biological samples. The reagents, workflow, and Hydrophilic interaction liquid chromatography with fluorescence detection (HILIC-FLD), are simple enough to be implemented into a straightforward user-friendly setup. This improved technology provides a powerful tool in support of rapid advancement of glycan analysis for biopharmaceutical development and biomarker discovery for clinical disease diagnosis.

Glycoproteins as diagnostic and prognostic biomarkers for neurodegenerative diseases: A glycoproteomic approach

Neurodegenerative diseases (NDs) are incurable and can develop progressively debilitating disorders, including dementia and ataxias. Alzheimer's disease and Parkinson's disease are the most common NDs that mainly affect the elderly people. There is an urgent need to develop new diagnostic tools so that patients can be accurately stratified at an early stage. As a common post-translational modification, protein glycosylation plays a key role in physiological and pathological processes. The abnormal changes in glycosylation are associated with the altered biological pathways in NDs. The pathogenesis-related proteins, like amyloid-β and microtubule-associated protein tau, have altered glycosylation. Importantly, specific glycosylation changes in cerebrospinal fluid, blood and urine are valuable for revealing neurodegeneration in the early stages. This review describes the emerging biomarkers based on glycoproteomics in NDs, highlighting the potential applications of glycoprotein biomarkers in the early detection of diseases, monitoring of the disease progression, and measurement of the therapeutic responses. The mass spectrometry-based strategies for characterizing glycoprotein biomarkers are also introduced.

Novel methods in glycomics: a 2019 update

Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.

glypy: An Open Source Glycoinformatics Library

Glycoinformatics is a critical resource for the study of glycobiology, and glycobiology is a necessary component for understanding the complex interface between intra- and extracellular spaces. Despite this, there is limited software available to scientists studying these topics, requiring each to create fundamental data structures and representations anew for each of their applications. This leads to poor uptake of standardization and loss of focus on the real problems. We present glypy, a library written in Python for reading, writing, manipulating, and transforming glycans at several levels of precision. In addition to understanding several common formats for textual representation of glycans, the library also provides application programming interfaces (APIs) for major community databases, including GlyTouCan and UnicarbKB. The library is freely available under the Apache 2 common license with source code available at https://github.com/mobiusklein/ and documentation at https://glypy.readthedocs.io/ .

Towards a standardized bioinformatics infrastructure for N- and O-glycomics

The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N- and O-linked glycans (N- and O-glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase.

Sweet and Sour Ehrlichia: Glycoproteomics and Phosphoproteomics Reveal New Players in Ehrlichia ruminantium Physiology and Pathogenesis

Unraveling which proteins and post-translational modifications (PTMs) affect bacterial pathogenesis and physiology in diverse environments is a tough challenge. Herein, we used mass spectrometry-based assays to study protein phosphorylation and glycosylation in Ehrlichia ruminantium Gardel virulent (ERGvir) and attenuated (ERGatt) variants and, how they can modulate Ehrlichia biological processes. The characterization of the S/T/Y phosphoproteome revealed that both strains share the same set of phosphoproteins (n = 58), 36% being overexpressed in ERGvir. The percentage of tyrosine phosphorylation is high (23%) and 66% of the identified peptides are multi-phosphorylated. Glycoproteomics revealed a high percentage of glycoproteins (67% in ERGvir) with a subset of glycoproteins being specific to ERGvir (n = 64/371) and ERGatt (n = 36/343). These glycoproteins are involved in key biological processes such as protein, amino-acid and purine biosynthesis, translation, virulence, DNA repair, and replication. Label-free quantitative analysis revealed over-expression in 31 proteins in ERGvir and 8 in ERGatt. While further PNGase digestion confidently localized 2 and 5 N-glycoproteins in ERGvir and ERGatt, respectively, western blotting suggests that many glycoproteins are O-GlcNAcylated. Twenty-three proteins were detected in both the phospho- and glycoproteome, for the two variants. This work represents the first comprehensive assessment of PTMs on Ehrlichia biology, rising interesting questions regarding ER–host interactions. Phosphoproteome characterization demonstrates an increased versatility of ER phosphoproteins to participate in different mechanisms. The high number of glycoproteins and the lack of glycosyltransferases-coding genes highlight ER dependence on the host and/or vector cellular machinery for its own protein glycosylation. Moreover, these glycoproteins could be crucial to interact and respond to changes in ER environment. PTMs crosstalk between of O-GlcNAcylation and phosphorylation could be used as a major cellular signaling mechanism in ER. As little is known about the Ehrlichia proteins/proteome and its signaling biology, the results presented herein provide a useful resource for further hypothesis-driven exploration of Ehrlichia protein regulation by phosphorylation and glycosylation events. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD012589.

Positive-unlabelled learning of glycosylation sites in the human proteome

BACKGROUND

As an important type of post-translational modification (PTM), protein glycosylation plays a crucial role in protein stability and protein function. The abundance and ubiquity of protein glycosylation across three domains of life involving Eukarya, Bacteria and Archaea demonstrate its roles in regulating a variety of signalling and metabolic pathways. Mutations on and in the proximity of glycosylation sites are highly associated with human diseases. Accordingly, accurate prediction of glycosylation can complement laboratory-based methods and greatly benefit experimental efforts for characterization and understanding of functional roles of glycosylation. For this purpose, a number of supervised-learning approaches have been proposed to identify glycosylation sites, demonstrating a promising predictive performance. To train a conventional supervised-learning model, both reliable positive and negative samples are required. However, in practice, a large portion of negative samples (i.e. non-glycosylation sites) are mislabelled due to the limitation of current experimental technologies. Moreover, supervised algorithms often fail to take advantage of large volumes of unlabelled data, which can aid in model learning in conjunction with positive samples (i.e. experimentally verified glycosylation sites).

RESULTS

In this study, we propose a positive unlabelled (PU) learning-based method, PA2DE (V2.0), based on the AlphaMax algorithm for protein glycosylation site prediction. The predictive performance of this proposed method was evaluated by a range of glycosylation data collected over a ten-year period based on an interval of three years. Experiments using both benchmarking and independent tests show that our method outperformed the representative supervised-learning algorithms (including support vector machines and random forests) and one-class learners, as well as currently available prediction methods in terms of F1 score, accuracy and AUC measures. In addition, we developed an online web server as an implementation of the optimized model (available at http://glycomine.erc.monash.edu/Lab/GlycoMine_PU/ ) to facilitate community-wide efforts for accurate prediction of protein glycosylation sites.

CONCLUSION

The proposed PU learning approach achieved a competitive predictive performance compared with currently available methods. This PU learning schema may also be effectively employed and applied to address the prediction problems of other important types of protein PTM site and functional sites.

Magnetic carbon nanocomposites as a MALDI co-matrix enhancing MS-based glycomics

More than 50% of all known proteins are glycosylated, which is critical for many biological processes such as protein folding and signal transduction. Glycosylation has proven to be associated with different mammalian diseases such as breast and liver cancers. Therefore, characterization of glycans is highly important to facilitate a better understanding of the development and progression of many human diseases. Although matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) offers several advantages such as ease of operation and short analysis times, however, due to the complexity of glycan structures and their low ionization efficiency, there are still challenges that need to be addressed to achieve sensitive glycan analysis. Here, magnetic carbon nanocomposites (CNPs@Fe₃O₄ NCs) were used as a new MALDI matrix or co-matrix for the analysis of glycans derived from different model glycoproteins and human blood serum samples. The addition of CNPs@Fe₃O₄ NCs to the matrix significantly enhanced glycan signal intensity by several orders of magnitude, and effectively controlled/reduced/eliminated in-source decay (ISD) fragmentation. The latter was attained by modulating CNPs@Fe₃O₄ NCs concentrations and allowed the simultaneous study of intact and fragmented glycans, and pseudo-MS³ analysis. Moreover, CNPs@Fe₃O₄ NCs was also effectively employed to desalt samples directly on MALDI plate, thus enabling direct MALDI-MS analysis of unpurified permethylated glycans derived from both model glycoproteins and biological samples. On-plate desalting enhanced sensitivity by reducing sample loss. Graphical abstract ᅟ.

Glycoengineering in CHO Cells: Advances in Systems Biology

For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post-translational modifications, particularly glycosylation, which unlike protein synthesis, is a non-templated process. Consequently, both native and recombinant glycoprotein production generate heterogeneous mixtures containing variable amounts of different glycoforms. Stability, potency, plasma half-life, and immunogenicity of the glycoprotein biologic are directly influenced by the glycoforms. Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g., heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling, and glycan and glycoprotein analysis that together will provide new strategies for glycoengineering of CHO cells with desired or enhanced glycosylation capabilities.

Characterization of isomeric glycan structures by LC-MS/MS

The characterization of glycosylation is critical for obtaining a comprehensive view of the regulation and functions of glycoproteins of interest. Due to the complex nature of oligosaccharides, stemming from variable compositions and linkages, and ion suppression effects, the chromatographic separation of glycans, including isomeric structures, is necessary for exhaustive characterization by MS. This review introduces the fundamental principles underlying the techniques in LC utilized by modern day glycomics researchers. Recent advances in porous graphitized carbon, reverse phase, ion exchange, and hydrophilic interaction LC utilized in conjunction with MS, for the characterization of protein glycosylation, are described with an emphasis on methods capable of resolving isomeric glycan structures.