Systems glycobiology: biochemical reaction networks regulating glycan structure and function

Cell- and tissue-specific glycosylation pathways informed by single-cell transcriptomics

While single-cell studies have made significant impacts in various subfields of biology, they lag in the Glycosciences. To address this gap, we analyzed single-cell glycogene expressions in the Tabula Sapiens dataset of human tissues and cell types using a recent glycosylation-specific gene ontology (GlycoEnzOnto). At the median sequencing (count) depth, ∼40-50 out of 400 glycogenes were detected in individual cells. Upon increasing the sequencing depth, the number of detectable glycogenes saturates at ∼200 glycogenes, suggesting that the average human cell expresses about half of the glycogene repertoire. Hierarchies in glycogene and glycopathway expressions emerged from our analysis: nucleotide-sugar synthesis and transport exhibited the highest gene expressions, followed by genes for core enzymes, glycan modification and extensions, and finally terminal modifications. Interestingly, the same cell types showed variable glycopathway expressions based on their organ or tissue origin, suggesting nuanced cell- and tissue-specific glycosylation patterns. Probing deeper into the transcription factors (TFs) of glycogenes, we identified distinct groupings of TFs controlling different aspects of glycosylation: core biosynthesis, terminal modifications, etc. We present webtools to explore the interconnections across glycogenes, glycopathways and TFs regulating glycosylation in human cell/tissue types. Overall, the study presents an overview of glycosylation across multiple human organ systems.

Universal Glycosyltransferase Continuous Assay for Uniform Kinetics and Inhibition Database Development and Mechanistic Studies Illustrated on ST3GAL1, C1GALT1, and FUT1

Chemical systems glycobiology requires experimental and computational tools to make possible big data analytics benefiting genomics and proteomics. The impediment to tool development is that the nature of glycan construction and mutation is not template driven but rests on cooperative glycosyltransferase (GT) catalytic synthesis. What is needed is the collation of kinetics and inhibition data in a standardized form to make possible analytics of glycan and glycoconjugate synthesis, mechanism extraction, and pattern recognition. Currently, kinetics assays in use for GTs are not universal in processing nucleoside phosphate UDP, GDP, and CMP donor-based glycosylation reactions due to limitations in accuracy and large substrate volume requirements. Here we present a universal glycosyltransferase continuous (UGC) assay able to measure the declining concentration of the NADH reporter molecule through fluorescence spectrophotometry and, therefore, determine reaction rate parameters. The development and parametrization of the assay is based on coupling the nucleotide released from GT reactions with pyruvate kinase, via nucleoside diphosphate kinase (NDK) in the case of NDP-based donor reactions. In the case of CMP-based reactions, the coupling is carried out via another kinase, cytidylate kinase in combination with NDK, which phosphorylates CMP to CDP, then CDP to CTP. Following this, we conduct kinetics and inhibition assay studies on the UDP, GDP, and CMP-based glycosylation reactions, specifically C1GAlT1, FUT1, and ST3GAL1, to represent each class of donor, respectively. The accuracy of calculating initial rates using the continuous assay compared to end point (noncontinuous) assays is demonstrated for the three classes of GTs. The previously identified natural product soyasaponin1 inhibitor was used as a model to demonstrate the application of the UGC assay as a standardized inhibition assay for GTs. We show that the dose response of ST3GAL1 to a serial dilution of Soyasaponin1 has time-dependent inhibition. This brings into question previous inhibition findings, arrived at using an end point assay, that have selected a seemingly random time point to measure inhibition. Consequently, using standardized Km values taken from the UGC assay study, ST3GAL1 was shown to be the most responsive enzyme to soyasaponin1 inhibition, followed by FUT1, then C1GALT1 with IC50 values of 37, 52, and 886 μM respectively.

Cell and tissue-specific glycosylation pathways informed by single-cell transcriptomics

While single cell studies have made significant impacts in various subfields of biology, they lag in the Glycosciences. To address this gap, we analyzed single-cell glycogene expressions in the Tabula Sapiens dataset of human tissues and cell types using a recent glycosylation-specific gene ontology (GlycoEnzOnto). At the median sequencing (count) depth, ~40-50 out of 400 glycogenes were detected in individual cells. Upon increasing the sequencing depth, the number of detectable glycogenes saturates at ~200 glycogenes, suggesting that the average human cell expresses about half of the glycogene repertoire. Hierarchies in glycogene and glycopathway expressions emerged from our analysis: nucleotide-sugar synthesis and transport exhibited the highest gene expressions, followed by genes for core enzymes, glycan modification and extensions, and finally terminal modifications. Interestingly, the same cell types showed variable glycopathway expressions based on their organ or tissue origin, suggesting nuanced cell- and tissue-specific glycosylation patterns. Probing deeper into the transcription factors (TFs) of glycogenes, we identified distinct groupings of TFs controlling different aspects of glycosylation: core biosynthesis, terminal modifications, etc. We present webtools to explore the interconnections across glycogenes, glycopathways, and TFs regulating glycosylation in human cell/tissue types. Overall, the study presents an overview of glycosylation across multiple human organ systems.

CytoCopasi: a chemical systems biology target and drug discovery visual data analytics platform

MOTIVATION

Target discovery and drug evaluation for diseases with complex mechanisms call for a streamlined chemical systems analysis platform. Currently available tools lack the emphasis on reaction kinetics, access to relevant databases, and algorithms to visualize perturbations on a chemical scale providing quantitative details as well streamlined visual data analytics functionality.

RESULTS

CytoCopasi, a Maven-based application for Cytoscape that combines the chemical systems analysis features of COPASI with the visualization and database access tools of Cytoscape and its plugin applications has been developed. The diverse functionality of CytoCopasi through ab initio model construction, model construction via pathway and parameter databases KEGG and BRENDA is presented. The comparative systems biology visualization analysis toolset is illustrated through a drug competence study on the cancerous RAF/MEK/ERK pathway.

AVAILABILITY AND IMPLEMENTATION

The COPASI files, simulation data, native libraries, and the manual are available on https://github.com/scientificomputing/CytoCopasi.

Forward Genetic Screens of Human Glycosylation Pathways Using the GlycoGene CRISPR Library

CRISPR-Cas9-based forward genetic screens represent a powerful discovery platform to uncover genes regulating specific biological processes. This article describes a method for utilizing a freely available GlycoGene CRISPR library to knock out any gene participating in human glycosylation in arbitrary cell types. The end product is a stable GlycoGene CRISPR knockout cell library, where each cell contains one or more sgRNA and lacks corresponding function. The cell library can be screened using various lectin/antibody reagents. It can also be applied in functional assays to establish glycan structure-glycogene-glycopathway relationships. This is a powerful systems glycobiology strategy for dissecting glycosylation pathways and processes. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Scale-up and NGS validation of the GlycoGene CRISPR plasmid library Basic Protocol 2: Preparation of a GlycoGene CRISPR lentivirus pool and an isogenic cell line stably expressing Cas9 nuclease Basic Protocol 3: Preparation of a GlycoGene CRISPR cell library, self-inactivation of Cas9, and library validation by NGS Basic Protocol 4: Enrichment of lectin-binding or non-binding cells and related multiplex NGS data acquisition Basic Protocol 5: Bioinformatics pathway analysis.

Comparative Glycomics Analysis of Mass Spectrometry Data

Glycan profiling is a common strategy that is used to determine the distribution of N-linked glycans, O-linked glycans and glycolipid associated complex carbohydrate structures that are part of various cell and tissue sources. Such data are central to our understanding of functional glycomics, and this knowledge can also be used for pathway construction and other applications in the field of Systems Glycobiology. Glycans released from cell/tissue samples are often studied in their free-form. They can also be functionalized with aglycones like 2-aminobenzamide (2AB) and procainamide to enhance separation and improve ionization during liquid chromatography/mass spectrometry. Additionally, these released glycans may be permethylated in order to improve glycan quantitation. In such work, besides studying the glycans in a single sample, there is also interest in comparing multiple samples in order to determine underlying similarities and differences, for example in terms of specific epitopes that are changed when cells of the same origin differentiate along different pathways. The current chapter describes the development and usage of cGlyco ("comparative Glycomics"), an open-source program that can be used to compare data from multiple mass spectrometry runs. As an example, we apply cGlyco to compare the glycan profile of multiple MALDI-TOF glycomics profiling data collected by core-C of the Consortium for Functional Glycomics (CFG).

Protein Glycosylation Investigated by Mass Spectrometry: An Overview

The protein glycosylation is a post-translational modification of crucial importance for its involvement in molecular recognition, protein trafficking, regulation, and inflammation. Indeed, abnormalities in protein glycosylation are correlated with several disease states such as cancer, inflammatory diseases, and congenial disorders. The understanding of cellular mechanisms through the elucidation of glycan composition encourages researchers to find analytical solutions for their detection. Actually, the multiplicity and diversity of glycan structures bond to the proteins, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies make their detection much trickier than other kinds of biopolymers. An overview of the most prominent techniques based on mass spectrometry (MS) for protein glycosylation (glycoproteomics) studies is here presented. The tricks and pre-treatments of samples are discussed as a crucial step prodromal to the MS analysis to improve the glycan ionization efficiency. Therefore, the different instrumental MS mode is also explored for the qualitative and quantitative analysis of glycopeptides and the glycans structural composition, thus contributing to the elucidation of biological mechanisms.

Zinc Deficiency Disturbs Mucin Expression, O-Glycosylation and Secretion by Intestinal Goblet Cells

Approximately 1 billion people worldwide suffer from zinc deficiency, with severe consequences for their well-being, such as critically impaired intestinal health. In addition to an extreme degeneration of the intestinal epithelium, the intestinal mucus is seriously disturbed in zinc-deficient (ZD) animals. The underlying cellular processes as well as the relevance of zinc for the mucin-producing goblet cells, however, remain unknown. To this end, this study examines the impact of zinc deficiency on the synthesis, production, and secretion of intestinal mucins as well as on the zinc homeostasis of goblet cells using the in vitro goblet cell model HT-29-MTX. Zinc deprivation reduced their cellular zinc content, changed expression of the intestinal zinc transporters ZIP-4, ZIP-5, and ZnT1 and increased their zinc absorption ability, outlining the regulatory mechanisms of zinc homeostasis in goblet cells. Synthesis and secretion of mucins were severely disturbed during zinc deficiency, affecting both MUC2 and MUC5AC mRNA expression with ongoing cell differentiation. A lack of zinc perturbed mucin synthesis predominantly on the post-translational level, as ZD cells produced shorter O-glycans and the main O-glycan pattern was shifted in favor of core-3-based mucins. The expression of glycosyltransferases that determine the formation of core 1-4 O-glycans was altered in zinc deficiency. In particular, B3GNT6 mRNA catalyzing core 3 formation was elevated and C2GNT1 and C2GNT3 elongating core 1 were downregulated in ZD cells. These novel insights into the molecular mechanisms impairing intestinal mucus stability during zinc deficiency demonstrate the essentiality of zinc for the formation and maintenance of this physical barrier.

A GlycoGene CRISPR-Cas9 lentiviral library to study lectin binding and human glycan biosynthesis pathways

Glycan biosynthesis on cell surface proteins and lipids is orchestrated by different classes of enzymes and proteins including the following: i. glycosyltransferases that add saccharides; ii. glycosidases that trim glycans; iii. conserved oligomeric golgi complex members that regulate intracellular transport; iv. enzymes aiding the biosynthesis of sugar-nucleotides; and v. sulfotransferases. This manuscript describes a pooled "glycoGene CRISPR" lentiviral library that targets 347 human genes involved in the above processes. Approximately 10 single-guide RNA (sgRNA) are included against each glycogene, with the putative editing site spanning the length of the target. A data analysis scheme is presented in order to determine glycosylation pathways regulating biological processes. As proof of principle, forward genetic screen results are presented to identify penetrating glycogenes that regulate the binding of P-/E-selectin, anti-sialyl Lewis-X monoclonal antibody HECA-452 and selected lectins (phaseolus vulgaris leucoagglutinin, vicia villosa lectin, peanut agglutinin) to HL-60 promyelocytic cells. Besides validating previously established biology, the study identifies three enzymes, PAPSS1, SLC35B2 and TPST2, as key molecules regulating sulfation of the major P-selectin glycoprotein ligand-1 in leukocytes. Approximately 80-90% of the sgRNA used in this study displayed high editing efficiency, and the CRISPR library picked up entire gene sets regulating specific biosynthetic pathways rather than only isolated genes. These data suggest that the glycoGene CRISPR library contains high-efficiency sgRNA. Further, this resource could be useful for the rapid screening of glycosylation-related genes and pathways that control lectin recognition in a variety of contexts.

Cell-Free Synthetic Glycobiology: Designing and Engineering Glycomolecules Outside of Living Cells

Glycans and glycosylated biomolecules are directly involved in almost every biological process as well as the etiology of most major diseases. Hence, glycoscience knowledge is essential to efforts aimed at addressing fundamental challenges in understanding and improving human health, protecting the environment and enhancing energy security, and developing renewable and sustainable resources that can serve as the source of next-generation materials. While much progress has been made, there remains an urgent need for new tools that can overexpress structurally uniform glycans and glycoconjugates in the quantities needed for characterization and that can be used to mechanistically dissect the enzymatic reactions and multi-enzyme assembly lines that promote their construction. To address this technology gap, cell-free synthetic glycobiology has emerged as a simplified and highly modular framework to investigate, prototype, and engineer pathways for glycan biosynthesis and biomolecule glycosylation outside the confines of living cells. From nucleotide sugars to complex glycoproteins, we summarize here recent efforts that harness the power of cell-free approaches to design, build, test, and utilize glyco-enzyme reaction networks that produce desired glycomolecules in a predictable and controllable manner. We also highlight novel cell-free methods for shedding light on poorly understood aspects of diverse glycosylation processes and engineering these processes toward desired outcomes. Taken together, cell-free synthetic glycobiology represents a promising set of tools and techniques for accelerating basic glycoscience research (e.g., deciphering the "glycan code") and its application (e.g., biomanufacturing high-value glycomolecules on demand).

Robustness in glycosylation systems: effect of modified monosaccharides, acceptor decoys and azido sugars on cellular nucleotide-sugar levels and pattern of N-linked glycosylation

Small molecule monosaccharide analogs (e.g. 4F-GlcNAc, 4F-GalNAc) and acceptor decoys (e.g. ONAP, SNAP) are commonly used as metabolic glycoengineering tools to perturb molecular and cellular recognition processes. Azido-derivatized sugars (e.g. ManNAz, GlcNAz, GalNAz) are also used as bioorthogonal probes to assay the glycosylation status of cells and tissue. With the goal of obtaining a systems-level understanding of how these compounds work, we cultured cells with these molecules and systematically evaluated their impact on: (i) cellular nucleotide-sugar levels, and (ii) N-linked glycosylation. To this end, we developed a streamlined, simple workflow to quantify nucleotide-sugar levels using amide-based hydrophilic interaction liquid chromatography (HILIC) separation followed by negative-mode electrospray ionization mass spectrometry (ESI-MS/MS) using an Orbitrap detector. N-Glycans released from cells were also procainamide functionalized and quantified using positive-mode ESI-MS/MS. Results show that all tested compounds changed the baseline nucleotide-sugar levels, with the effect being most pronounced for the fluoro-HexNAc compounds. These molecules depressed UDP-HexNAc levels in cells by up to 80%, while concomitantly elevating UDP-4F-GalNAc and UDP-4F-GlcNAc. While the measured changes in nucleotide-sugar concentration were substantial in many cases, their impact on N-linked glycosylation was relatively small. This may be due to the high nucleotide-sugar concentrations in the Golgi, which far exceed the K_M values of the glycosylating enzymes. Thus, the glycosylation system output exhibits 'robustness' even in the face of significant changes in cellular nucleotide-sugar concentrations.

A Systematic Review on the Implications of O-linked Glycan Branching and Truncating Enzymes on Cancer Progression and Metastasis

Glycosylation is the most commonly occurring post-translational modifications, and is believed to modify over 50% of all proteins. The process of glycan modification is directed by different glycosyltransferases, depending on the cell in which it is expressed. These small carbohydrate molecules consist of multiple glycan families that facilitate cell-cell interactions, protein interactions, and downstream signaling. An alteration of several types of O-glycan core structures have been implicated in multiple cancers, largely due to differential glycosyltransferase expression or activity. Consequently, aberrant O-linked glycosylation has been extensively demonstrated to affect biological function and protein integrity that directly result in cancer growth and progression of several diseases. Herein, we provide a comprehensive review of several initiating enzymes involved in the synthesis of O-linked glycosylation that significantly contribute to a number of different cancers.

Translation of genome to glycome: role of the Golgi apparatus

Glycans are one of the four biopolymers of the cell and they play important roles in cellular and organismal physiology. They consist of both linear and branched structures and are synthesized in a nontemplated manner in the secretory pathway of mammalian cells with the Golgi apparatus playing a key role in the process. In spite of the absence of a template, the glycans synthesized by a cell are not a random collection of possible glycan structures but a distribution of specific glycans in defined quantities that is unique to each cell type (Cell type here refers to distinct cell forms present in an organism that can be distinguished based on morphological, phenotypic and/or molecular criteria.) While information to produce cell type-specific glycans is encoded in the genome, how this information is translated into cell type-specific glycome (Glycome refers to the quantitative distribution of all glycan structures present in a given cell type.) is not completely understood. We summarize here the factors that are known to influence the fidelity of glycan biosynthesis and integrate them into known glycosylation pathways so as to rationalize the translation of genetic information to cell type-specific glycome.

A mechanism for bistability in glycosylation

Glycosyltransferases are a class of enzymes that catalyse the posttranslational modification of proteins to produce a large number of glycoconjugate acceptors from a limited number of nucleotide-sugar donors. The products of one glycosyltransferase can be the substrates of several other enzymes, causing a combinatorial explosion in the number of possible glycan products. The kinetic behaviour of systems where multiple acceptor substrates compete for a single enzyme is presented, and the case in which high concentrations of an acceptor substrate are inhibitory as a result of abortive complex formation, is shown to result in non-Michaelian kinetics that can lead to bistability in an open system. A kinetic mechanism is proposed that is consistent with the available experimental evidence and provides a possible explanation for conflicting observations on the β-1,4-galactosyltransferases. Abrupt switching between steady states in networks of glycosyltransferase-catalysed reactions may account for the observed changes in glycosyl-epitopes in cancer cells.

A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSⁿ proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MSⁿ data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MSⁿ spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data.

Biological roles of glycans

Simple and complex carbohydrates (glycans) have long been known to play major metabolic, structural and physical roles in biological systems. Targeted microbial binding to host glycans has also been studied for decades. But such biological roles can only explain some of the remarkable complexity and organismal diversity of glycans in nature. Reviewing the subject about two decades ago, one could find very few clear-cut instances of glycan-recognition-specific biological roles of glycans that were of intrinsic value to the organism expressing them. In striking contrast there is now a profusion of examples, such that this updated review cannot be comprehensive. Instead, a historical overview is presented, broad principles outlined and a few examples cited, representing diverse types of roles, mediated by various glycan classes, in different evolutionary lineages. What remains unchanged is the fact that while all theories regarding biological roles of glycans are supported by compelling evidence, exceptions to each can be found. In retrospect, this is not surprising. Complex and diverse glycans appear to be ubiquitous to all cells in nature, and essential to all life forms. Thus, >3 billion years of evolution consistently generated organisms that use these molecules for many key biological roles, even while sometimes coopting them for minor functions. In this respect, glycans are no different from other major macromolecular building blocks of life (nucleic acids, proteins and lipids), simply more rapidly evolving and complex. It is time for the diverse functional roles of glycans to be fully incorporated into the mainstream of biological sciences.

Predictive glycoengineering of biosimilars using a Markov chain glycosylation model

Biosimilar drugs must closely resemble the pharmacological attributes of innovator products to ensure safety and efficacy to obtain regulatory approval. Glycosylation is one critical quality attribute that must be matched, but it is inherently difficult to control due to the complexity of its biogenesis. This usually implies that costly and time-consuming experimentation is required for clone identification and optimization of biosimilar glycosylation. Here, a computational method that utilizes a Markov model of glycosylation to predict optimal glycoengineering strategies to obtain a specific glycosylation profile with desired properties is described. The approach uses a genetic algorithm to find the required quantities to perturb glycosylation reaction rates that lead to the best possible match with a given glycosylation profile. Furthermore, the approach can be used to identify cell lines and clones that will require minimal intervention while achieving a glycoprofile that is most similar to the desired profile. Thus, this approach can facilitate biosimilar design by providing computational glycoengineering guidelines that can be generated with a minimal time and cost.

Multi-level regulation of cellular glycosylation: from genes to transcript to enzyme to structure

Glycosylation is a ubiquitous mammalian post-translational modification that both decorates a majority of expressed proteins and regulates their function. Cellular glycan biosynthesis is facilitated by a few hundred enzymes that are collectively termed 'glycoenzymes'. The expression and activity of these enzymes is controlled at the transcription, translation and post-translation levels. New wet-lab advances are providing analytical methods to collect large-scale data at these multiple levels, relational databases are starting to collate these results, and computer models are beginning to integrate this information across scales in order to gain new knowledge. These activities are likely to enable the qualitative and quantitative mapping of pathways regulating glycan production and function in proteins, cells and tissue.

A Markov chain model for N-linked protein glycosylation--towards a low-parameter tool for model-driven glycoengineering

Glycosylation is a critical quality attribute of most recombinant biotherapeutics. Consequently, drug development requires careful control of glycoforms to meet bioactivity and biosafety requirements. However, glycoengineering can be extraordinarily difficult given the complex reaction networks underlying glycosylation and the vast number of different glycans that can be synthesized in a host cell. Computational modeling offers an intriguing option to rationally guide glycoengineering, but the high parametric demands of current modeling approaches pose challenges to their application. Here we present a novel low-parameter approach to describe glycosylation using flux-balance and Markov chain modeling. The model recapitulates the biological complexity of glycosylation, but does not require user-provided kinetic information. We use this method to predict and experimentally validate glycoprofiles on EPO, IgG as well as the endogenous secretome following glycosyltransferase knock-out in different Chinese hamster ovary (CHO) cell lines. Our approach offers a flexible and user-friendly platform that can serve as a basis for powerful computational engineering efforts in mammalian cell factories for biopharmaceutical production.

Mammalian protein glycosylation--structure versus function

Carbohydrates fulfil many common as well as extremely important functions in nature. They show a variety of molecular displays--e.g., free mono-, oligo-, and polysaccharides, glycolipids, proteoglycans, glycoproteins, etc.--with particular roles and localizations in living organisms. Structure-specific peculiarities are so many and diverse that it becomes virtually impossible to cover them all from an analytical perspective. Hence this manuscript, focused on mammalian glycosylation, rather than a complete list of analytical descriptors or recognized functions for carbohydrate structures, comprehensively reviews three central issues in current glycoscience, namely (i) structural analysis of glycoprotein glycans, covering both classical and novel approaches for teasing out the structural puzzle as well as potential pitfalls of these processes; (ii) an overview of functions attributed to carbohydrates, covering from monosaccharide to complex, well-defined epitopes and full glycans, including post-glycosylational modifications, and (iii) recent technical advances allowing structural identification of glycoprotein glycans with simultaneous assignation of biological functions.

Overexpression of α2,3sialyl T-antigen in breast cancer determined by miniaturized glycosyltransferase assays and confirmed using tissue microarray immunohistochemical analysis

Glycan structure alterations during cancer regulate disease progression and represent clinical biomarkers. The study determined the degree to which changes in glycosyltransferase activities during cancer can be related to aberrant cell-surface tumor associated carbohydrate structures (TACA). To this end, changes in sialyltransferase (sialylT), fucosyltransferase (fucT) and galactosyltransferase (galT) activity were measured in normal and tumor tissue using a miniaturized enzyme activity assay and synthetic glycoconjugates bearing terminal LacNAc Type-I (Galβ1-3GlcNAc), LacNAc Type-II (Galβ1-4GlcNAc), and mucin core-1/Type-III (Galβ1-3GalNAc) structures. These data were related to TACA using tissue microarrays containing 115 breast and 26 colon cancer specimen. The results show that primary human breast and colon tumors, but not adjacent normal tissue, express elevated β1,3GalT and α2,3SialylT activity that can form α2,3SialylatedType-IIIglycans (Siaα2-3Galβ1-3GalNAc). Prostate tumors did not exhibit such elevated enzymatic activities. α1,3/4FucT activity was higher in breast, but not in colon tissue. The enzymology based prediction of enhanced α2,3sialylated Type-III structures in breast tumors was verified using histochemical analysis of tissue sections and tissue microarrays. Here, the binding of two markers that recognize Galβ1-3GalNAc (peanut lectin and mAb A78-G/A7) was elevated in breast tumor, but not in normal control, only upon sialidase treatment. These antigens were also upregulated in colon tumors though to a lesser extent. α2,3sialylatedType-III expression correlated inversely with patient HER2 expression and breast metastatic potential. Overall, enzymology measurements of glycoT activity predict truncated O-glycan structures in tumors. High expression of the α2,3sialylated T-antigen O-glycans occur in breast tumors. A transformation from linear core-1 glycan to other epitopes may accompany metastasis.

Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling

Eukaryotic cell lines, including Chinese hamster ovary cells, yeast, and insect cells, are invaluable hosts for the production of many recombinant proteins. With the advent of genomic resources, one can now leverage genome-scale computational modeling of cellular pathways to rationally engineer eukaryotic host cells. Genome-scale models of metabolism include all known biochemical reactions occurring in a specific cell. By describing these mathematically and using tools such as flux balance analysis, the models can simulate cell physiology and provide targets for cell engineering that could lead to enhanced cell viability, titer, and productivity. Here we review examples in which metabolic models in eukaryotic cell cultures have been used to rationally select targets for genetic modification, improve cellular metabolic capabilities, design media supplementation, and interpret high-throughput omics data. As more comprehensive models of metabolism and other cellular processes are developed for eukaryotic cell culture, these will enable further exciting developments in cell line engineering, thus accelerating recombinant protein production and biotechnology in the years to come.

Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data

The glycome constitutes the entire complement of free carbohydrates and glycoconjugates expressed on whole cells or tissues. 'Systems Glycobiology' is an emerging discipline that aims to quantitatively describe and analyse the glycome. Here, instead of developing a detailed understanding of single biochemical processes, a combination of computational and experimental tools are used to seek an integrated or 'systems-level' view. This can explain how multiple biochemical reactions and transport processes interact with each other to control glycome biosynthesis and function. Computational methods in this field commonly build in silico reaction network models to describe experimental data derived from structural studies that measure cell-surface glycan distribution. While considerable progress has been made, several challenges remain due to the complex and heterogeneous nature of this post-translational modification. First, for the in silico models to be standardized and shared among laboratories, it is necessary to integrate glycan structure information and glycosylation-related enzyme definitions into the mathematical models. Second, as glycoinformatics resources grow, it would be attractive to utilize 'Big Data' stored in these repositories for model construction and validation. Third, while the technology for profiling the glycome at the whole-cell level has been standardized, there is a need to integrate mass spectrometry derived site-specific glycosylation data into the models. The current review discusses progress that is being made to resolve the above bottlenecks. The focus is on how computational models can bridge the gap between 'data' generated in wet-laboratory studies with 'knowledge' that can enhance our understanding of the glycome.

Engineering the supply chain for protein production/secretion in yeasts and mammalian cells

Metabolic bottlenecks play an increasing role in yeasts and mammalian cells applied for high-performance production of proteins, particularly of pharmaceutical ones that require complex posttranslational modifications. We review the present status and developments focusing on the rational metabolic engineering of such cells to optimize the supply chain for building blocks and energy. Methods comprise selection of beneficial genetic modifications, rational design of media and feeding strategies. Design of better producer cells based on whole genome-wide metabolic network analysis becomes increasingly possible. High-resolution methods of metabolic flux analysis for the complex networks in these compartmented cells are increasingly available. We discuss phenomena that are common to both types of organisms but also those that are different with respect to the supply chain for the production and secretion of pharmaceutical proteins.

Systems glycobiology for glycoengineering

Glycosylation serves essential functions on many proteins produced in biopharmaceutical manufacturing, making it mandatory to thoroughly consider its biogenesis during the production process. Glycoengineering efforts involve the rational design of glycosylation through adjustments in culturing conditions or genetic modifications. Computational models have been developed to aid this process, aiming to offer cheaper and faster alternatives to costly screening strategies. Recently, these models have been successfully utilized to predict glycosylation of products of industrial relevance. Furthermore, systems-level analyses of glycan diversity are elucidating deeper insights into the mechanisms underlying glycosylation. As computational models of glycosylation continue to be expanded, refined, and leveraged for detailed analysis of glycomics data, they will become invaluable resources for cell line development and glycoengineering.

A computational framework for the automated construction of glycosylation reaction networks

Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS) data. The features described above are illustrated using three case studies that examine: i) O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii) automated N-linked glycosylation pathway construction; and iii) the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme biochemistry. All the implemented features are provided as part of the Glycosylation Network Analysis Toolbox (GNAT), an open-source, platform-independent, MATLAB based toolbox for studies of Systems Glycobiology.

Distinct glycosyltransferases synthesize E-selectin ligands in human vs. mouse leukocytes

The binding of selectins to carbohydrate epitopes expressed on leukocytes is the first step in a multi-step cell adhesion cascade that controls the rate of leukocyte recruitment at sites of inflammation. The glycans that function as selectin-ligands are post-translationally synthesized by the serial action of Golgi resident enzymes called glycosyltransferases (glycoTs). Whereas much of our current knowledge regarding the role of glycoTs in constructing selectin-ligands comes from reconstituted biochemical investigations or murine models, tools to assess the impact of these enzymes on the human ligands are relatively underdeveloped. This is significant since the selectin-ligands, particularly those that bind E-selectin, vary between different leukocyte cell populations and they are also different in humans compared with mice. To address this shortcoming, a recent study by Buffone et al. (2013) outlines a systematic strategy to knockdown upto three glycoTs simultaneously in human leukocytes. The results suggest that the fucosyltransferases (FUTs) regulating selectin-ligand synthesis may be species-specific. In particular, they demonstrate that FUT9 plays a significant role during human, but not mouse, leukocyte-endothelial interactions. Overall, this article discusses the relative roles of the FUTs during human L-, E-, and P-selectin-ligand biosynthesis, and the potential that the knockdown strategy outlined here may assess the role of other glycoTs in human leukocytes also.

Alteration of plasma galactose/N-acetylgalactosamine level after irradiation

Although glycoproteins possess a variety of functional and structural roles in intracellular and intercellular activities, the effect of ionizing radiation (IR) on glycosylation is largely unknown. To explore this effect, we established a sandwich assay in which PHA-L, a phytohaemagglutinin that agglutinates leukocytes, was used as a coating layer to capture glycoproteins containing complex oligosaccharides; the bound glycoproteins were then measured. C57BL/6 mice were exposed to 0, 3, 6, or 10 Gy, and the plasma was collected at 6, 12, 18, 24, 48, 72, or 168 h and then analyzed for galactose/N-acetylgalactosamine (Gal/GalNAc) containing proteins. We found that (1) the sandwich assay accurately measured the level of glycoproteins, (2) 6-12 h after IR, the amount of glycoproteins containing GalNAc increased, and (3) at 72 and 168 h, 10 Gy was associated with a decrease in Gal/GalNAc. These IR-induced alterations might relate to the release of glycoproteins into the blood and the damage of the proteins and genes that are related to the glycosylation process.

Glycosylation Network Analysis Toolbox: a MATLAB-based environment for systems glycobiology

Systems glycobiology studies the interaction of various pathways that regulate glycan biosynthesis and function. Software tools for the construction and analysis of such pathways are not yet available. We present GNAT, a platform-independent, user-extensible MATLAB-based toolbox that provides an integrated computational environment to construct, manipulate and simulate glycans and their networks. It enables integration of XML-based glycan structure data into SBML (Systems Biology Markup Language) files that describe glycosylation reaction networks. Curation and manipulation of networks is facilitated using class definitions and glycomics database query tools. High quality visualization of networks and their steady-state and dynamic simulation are also supported.

AVAILABILITY

The software package including source code, help documentation and demonstrations are available at http://sourceforge.net/projects/gnatmatlab/files/.

The computing platelet: integrating environmental cues

In this issue of Blood, Flamm et al combine high-throughput experimental methods and multiscale computer simulations to predict patient-specific thrombus formation potential.(1) Their studies reveal a novel thromboxane receptor mutation (TP-V241G) in humans that confers resistance to indomethacin.

Integrated approach toward the discovery of glyco-biomarkers of inflammation-related diseases

Glycobiology has contributed tremendously to the discovery and characterization of cancer-related biomarkers containing glycans (i.e., glyco-biomarkers) and a more detailed understanding of cancer biology. It is now recognized that most chronic diseases involve some elements of chronic inflammation; these include cancer, Alzheimer's disease, and metabolic syndrome (including consequential diabetes mellitus and cardiovascular diseases). By extending the knowledge and experience of the glycobiology community regarding cancer biomarker discovery, we should be able to contribute to the discovery of diagnostic/prognostic glyco-biomarkers of other chronic diseases that involve chronic inflammation. Future integration of large-scale "omics"-type data (e.g., genomics, epigenomics, transcriptomics, proteomics, and glycomics) with computational model building, or a systems glycobiology approach, will facilitate such efforts.

Understanding glycomechanics using mathematical modeling: a review of current approaches to simulate cellular glycosylation reaction networks

Following the footsteps of genomics and proteomics, recent years have witnessed the growth of large-scale experimental methods in the field of glycomics. In parallel, there has also been growing interest in developing Systems Biology based methods to study the glycome. The combined goals of these endeavors is to identify glycosylation-dependent mechanisms regulating human physiology, check points that can control the progression of pathophysiology, and modifications to reaction pathways that can result in more uniform biopharmaceutical processes. In these efforts, mathematical models of N- and O-linked glycosylation have emerged as paradigms for the field. While these are relatively few in number, nevertheless, the existing models provide a basic framework that can be used to develop more sophisticated analysis strategies for glycosylation in the future. The current review surveys these computational models with focus on the underlying mathematics and assumptions, and with respect to their ability to generate experimentally testable hypotheses.