Systems Glycobiology: Integrating Glycogenomics, Glycoproteomics, Glycomics, and Other ‘Omics Data Sets to Characterize Cellular Glycosylation Processes

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.

Single-cell Glycogenomics Deciphers Links Between Altered Transcriptional Regulation and Aberrant Glycosylation in Alzheimer's Disease

Glycosylation is increasingly recognized as a potential new therapeutic target in Alzheimer's disease. In recent years, evidence for Alzheimer's disease-specific glycoproteins has been established. However, the mechanisms of their dysregulation, including tissue and cell type specificity, are not fully understood. We aimed to explore upstream regulators of aberrant glycosylation by integrating multiple data sources and using a glycogenomics approach. We identified dysregulation by the glycosyltransferase PLOD3 in oligodendrocytes as an upstream regulator in cerebral vessels, and found that it is involved in COL4A5 synthesis, which is strongly correlated with amyloid fiber formation. Furthermore, COL4A5 was suggested to interact with astrocytes via ECM receptors as a ligand. This study suggests directions for new therapeutic strategies for Alzheimer's disease targeting glycosyltransferases.

Breakthrough of glycobiology in the 21st century

As modern medicine began to emerge at the turn of the 20th century, glycan-based therapies advanced. DNA- and protein-centered therapies became widely available. The research and development of structurally defined carbohydrates have led to new tools and methods that have sparked interest in the therapeutic applications of glycans. One of the latest omics disciplines to emerge in the contemporary post-genomics age is glycomics. In addition, to providing hope for patients and people with different health conditions through a deeper understanding of the mechanisms of common complex diseases, this new specialty in system sciences has much to offer to communities involved in the development of diagnostics and therapeutics in medicine and life sciences.This review focuses on recent developments that have pushed glycan-based therapies into the spotlight in medicine and the technologies powering these initiatives, which we can take as the most significant success of the 21st century.

Immunoglobulin G N-glycan Biomarkers for Autoimmune Diseases: Current State and a Glycoinformatics Perspective

The effective treatment of autoimmune disorders can greatly benefit from disease-specific biomarkers that are functionally involved in immune system regulation and can be collected through minimally invasive procedures. In this regard, human serum IgG N-glycans are promising for uncovering disease predisposition and monitoring progression, and for the identification of specific molecular targets for advanced therapies. In particular, the IgG N-glycome in diseased tissues is considered to be disease-dependent; thus, specific glycan structures may be involved in the pathophysiology of autoimmune diseases. This study provides a critical overview of the literature on human IgG N-glycomics, with a focus on the identification of disease-specific glycan alterations. In order to expedite the establishment of clinically-relevant N-glycan biomarkers, the employment of advanced computational tools for the interpretation of clinical data and their relationship with the underlying molecular mechanisms may be critical. Glycoinformatics tools, including artificial intelligence and systems glycobiology approaches, are reviewed for their potential to provide insight into patient stratification and disease etiology. Challenges in the integration of such glycoinformatics approaches in N-glycan biomarker research are critically discussed.

Comparing Urinary Glycoproteins among Three Urogenital Cancers and Identifying Prostate Cancer-Specific Glycoproteins

Prostate cancer, bladder cancer, and renal cancers are major urogenital cancers. Of which, prostate cancer is the most commonly diagnosed and second leading cause of cancer death for men in the United States. For urogenital cancers, urine is considered as proximate body fluid to the tumor site for developing non-invasiveness tests. However, the specific molecular signatures from different urogenital cancers are needed to relate changes in urine to various cancer detections. Herein, we utilized a previously published C4-Tip and C18/MAX-Tip workflow for enrichment of glycopeptides from urine samples and evaluated urinary glycopeptides for its cancer specificity. We analyzed 66 urine samples from bladder cancer (n = 27), prostate cancer (n = 4), clear cell renal cell carcinoma (ccRCC, n = 3), and benign plastic hyperplasia (BPH, n = 32) and then compared them with a previous publication that reported glycopeptides associated with aggressive prostate cancer (Gleason score ≥ 8). We further demonstrated the cancer specificity of the glycopeptides associated with aggressive prostate cancer. In this study, a total of 33 glycopeptides were identified to be specifically differentially expressed in prostate cancer compared to other urogenital cancer types as well as BPH urines. By cross-comparison with our previous urinary glycoproteomic dataset for aggressive prostate cancer, we reported a total of four glycopeptides from glycoproteins DSC2, MGAM, PIK3IP1, and CD55, commonly identified to be prostate cancer-specific. Together, these results deepen our understanding of the urinary glycoproteins associated with urogenital cancer types and expand our knowledge of the cancer specificity of urinary glycoproteins among urogenital cancer progression.

Breakthrough of glycobiology in the 21st century

As modern medicine began to emerge at the turn of the 20th century, glycan-based therapies advanced. DNA- and protein-centered therapies became widely available. The research and development of structurally defined carbohydrates have led to new tools and methods that have sparked interest in the therapeutic applications of glycans. One of the latest omics disciplines to emerge in the contemporary post-genomics age is glycomics. In addition, to providing hope for patients and people with different health conditions through a deeper understanding of the mechanisms of common complex diseases, this new specialty in system sciences has much to offer to communities involved in the development of diagnostics and therapeutics in medicine and life sciences.This review focuses on recent developments that have pushed glycan-based therapies into the spotlight in medicine and the technologies powering these initiatives, which we can take as the most significant success of the 21st century.

What is the Sugar Code?

A code is defined by the nature of the symbols, which are used to generate information‐storing combinations (e. g. oligo‐ and polymers). Like nucleic acids and proteins, oligo‐ and polysaccharides are ubiquitous, and they are a biochemical platform for establishing molecular messages. Of note, the letters of the sugar code system (third alphabet of life) excel in coding capacity by making an unsurpassed versatility for isomer (code word) formation possible by variability in anomery and linkage position of the glycosidic bond, ring size and branching. The enzymatic machinery for glycan biosynthesis (writers) realizes this enormous potential for building a large vocabulary. It includes possibilities for dynamic editing/erasing as known from nucleic acids and proteins. Matching the glycome diversity, a large panel of sugar receptors (lectins) has developed based on more than a dozen folds. Lectins ‘read’ the glycan‐encoded information. Hydrogen/coordination bonding and ionic pairing together with stacking and C−H/π‐interactions as well as modes of spatial glycan presentation underlie the selectivity and specificity of glycan‐lectin recognition. Modular design of lectins together with glycan display and the nature of the cognate glycoconjugate account for the large number of post‐binding events. They give an entry to the glycan vocabulary its functional, often context‐dependent meaning(s), hereby building the dictionary of the sugar code.

High-Throughput Analyses of Glycans, Glycosites, and Intact Glycopeptides Using C4-and C18/MAX-Tips and Liquid Handling System

Protein glycosylation is one of the most common and diverse modifications. Aberrant protein glycosylation has been reported to associate with various diseases. High‐throughput and comprehensive characterization of glycoproteins is crucial for structural and functional studies of altered glycosylation in biological, physiological, and pathological processes. In this protocol, we detail a workflow for comprehensive analyses of intact glycopeptides (IGPs), glycosylation sites, and glycans from N‐linked glycoproteins. By utilizing liquid handling systems, our workflow could enrich IGPs in a high‐throughput manner while reducing sample processing time and human error involved in traditional proteomics sample processing techniques. Together, our workflow enables a high‐throughput enrichment of glycans, glycosites, and intact glycopeptides from complex biological or clinical samples. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Enzymatic digestion of glycoproteins using C4‐tips

Basic Protocol 2: Intact glycopeptide analysis using C18/MAX‐tips

Basic Protocol 3: Glycan and glycosite analysis

Systems glycobiology for discovering drug targets, biomarkers, and rational designs for glyco-immunotherapy

Cancer immunotherapy has revolutionized treatment and led to an unprecedented wave of immuno-oncology research during the past two decades. In 2018, two pioneer immunotherapy innovators, Tasuku Honjo and James P. Allison, were awarded the Nobel Prize for their landmark cancer immunotherapy work regarding “cancer therapy by inhibition of negative immune regulation” –CTLA4 and PD-1 immune checkpoints. However, the challenge in the coming decade is to develop cancer immunotherapies that can more consistently treat various patients and cancer types. Overcoming this challenge requires a systemic understanding of the underlying interactions between immune cells, tumor cells, and immunotherapeutics. The role of aberrant glycosylation in this process, and how it influences tumor immunity and immunotherapy is beginning to emerge. Herein, we review current knowledge of miRNA-mediated regulatory mechanisms of glycosylation machinery, and how these carbohydrate moieties impact immune cell and tumor cell interactions. We discuss these insights in the context of clinical findings and provide an outlook on modulating the regulation of glycosylation to offer new therapeutic opportunities. Finally, in the coming age of systems glycobiology, we highlight how emerging technologies in systems glycobiology are enabling deeper insights into cancer immuno-oncology, helping identify novel drug targets and key biomarkers of cancer, and facilitating the rational design of glyco-immunotherapies. These hold great promise clinically in the immuno-oncology field.

COVID-19 and Preparing Planetary Health for Future Ecological Crises: Hopes from Glycomics for Vaccine Innovation

A key lesson emerging from COVID-19 is that pandemic proofing planetary health against future ecological crises calls for systems science and preventive medicine innovations. With greater proximity of the human and animal natural habitats in the 21st century, it is also noteworthy that zoonotic infections such as COVID-19 that jump from animals to humans are increasingly plausible in the coming decades. In this context, glycomics technologies and the third alphabet of life, the sugar code, offer veritable prospects to move omics systems science from discovery to diverse applications of relevance to global public health and preventive medicine. In this expert review, we discuss the science of glycomics, its importance in vaccine development, and the recent progress toward discoveries on the sugar code that can help prevent future infectious outbreaks that are looming on the horizon in the 21st century. Glycomics offers veritable prospects to boost planetary health, not to mention the global scientific capacity for vaccine innovation against novel and existing infectious agents.

Promiscuity and specificity of eukaryotic glycosyltransferases

Glycosyltransferases are a large family of enzymes responsible for covalently linking sugar monosaccharides to a variety of organic substrates. These enzymes drive the synthesis of complex oligosaccharides known as glycans, which play key roles in inter-cellular interactions across all the kingdoms of life; they also catalyze sugar attachment during the synthesis of small-molecule metabolites such as plant flavonoids. A given glycosyltransferase enzyme is typically responsible for attaching a specific donor monosaccharide, via a specific glycosidic linkage, to a specific moiety on the acceptor substrate. However these enzymes are often promiscuous, able catalyze linkages between a variety of donors and acceptors. In this review we discuss distinct classes of glycosyltransferase promiscuity, each illustrated by enzymatic examples from small-molecule or glycan synthesis. We highlight the physical causes of promiscuity, and its biochemical consequences. Structural studies of glycosyltransferases involved in glycan synthesis show that they make specific contacts with ‘recognition motifs’ that are much smaller than the full oligosaccharide substrate. There is a wide range in the sizes of glycosyltransferase recognition motifs: highly promiscuous enzymes recognize monosaccharide or disaccharide motifs across multiple oligosaccharides, while highly specific enzymes recognize large, complex motifs found on few oligosaccharides. In eukaryotes, the localization of glycosyltransferases within compartments of the Golgi apparatus may play a role in mitigating the glycan variability caused by enzyme promiscuity.

Generating orthogonal glycosyltransferase and nucleotide sugar pairs as next-generation glycobiology tools

Protein glycosylation fundamentally impacts biological processes. Nontemplated biosynthesis introduces unparalleled complexity into glycans that needs tools to understand their roles in physiology. The era of quantitative biology is a great opportunity to unravel these roles, especially by mass spectrometry glycoproteomics. However, with high sensitivity come stringent requirements on tool specificity. Bioorthogonal metabolic labeling reagents have been fundamental to studying the cell surface glycoproteome but typically enter a range of different glycans and are thus of limited specificity. Here, we discuss the generation of metabolic 'precision tools' to study particular subtypes of the glycome. A chemical biology tactic termed bump-and-hole engineering generates mutant glycosyltransferases that specifically accommodate bioorthogonal monosaccharides as an enabling technique of glycobiology. We review the groundbreaking discoveries that have led to applying the tactic in the living cell and the implications in the context of current developments in mass spectrometry glycoproteomics.

Protein Glycopatterns in Bronchoalveolar Lavage Fluid as Novel Potential Biomarkers for Diagnosis of Lung Cancer

Lung cancer is one of the most prevalent and life-threatening neoplasias worldwide due to the deficiency of ideal diagnostic biomarkers. Although aberrant glycosylation has been observed in human serum and tissue, little is known about the alterations in bronchoalveolar lavage fluid (BALF) that are extremely associated with lung cancer. In this study, our aim was to systematically investigate and assess the alterations of protein glycopatterns in BALF and possibility as biomarkers for diagnosis of lung cancer. Here, lectin microarrays and blotting analysis were utilized to detect the differential expression of BALF glycoproteins from patients with 80 adenocarcinomas (ADC), 77 squamous carcinomas (SCC), 51 small cell lung cancer (SCLC), and 73 benign pulmonary diseases (BPD). These 281 specimens were then randomly divided into a training cohort and validation cohort for constructing and verifying the diagnostic models based on the glycopattern abundances. Moreover, an independent test was performed with 120 newly collected BALF samples enrolled in the double-blind cohort to further assess the clinical application potential of the diagnostic models. According to the results, there were 15 (e.g., PHA-E, EEL, and BPL) and 14 lectins (e.g., PTL-II, LCA, and SJA) that individually showed significant variations in different types and stages of lung cancer compared to BPD. Notably, the diagnostic models achieved better discriminate power in the validation cohort and exhibited high accuracies of 0.917, 0.864, 0.712, 0.671, and 0.781 in the double-blind cohort for the diagnosis of lung cancer, early stage lung cancer, ADC, SCC, and SCLC, respectively. Taken together, the present study revealed that the abnormally altered protein glycopatterns in BALF are expected to be novel potential biomarkers for the identification and early diagnosis of lung cancer, which will contribute to explain the mechanism of the development of lung cancer from the perspective of glycobiology.

Systems Glycobiology: Past, Present, and Future

Glycobiology is a glycan-based field of study that focuses on the structure, function, and biology of carbohydrates, and glycomics is a sub-study of the field of glycobiology that aims to define structure/function of glycans in living organisms. With the popularity of the glycobiology and glycomics, application of computational modeling expanded in the scientific area of glycobiology over the last decades. The recent availability of progressive Wet-Lab methods in the field of glycobiology and glycomics is promising for the impact of systems biology on the research area of the glycome, an emerging field that is termed “systems glycobiology.” This chapter will summarize the up-to-date leading edge in the use of bioinformatics tools in the field of glycobiology. The chapter provides basic knowledge both for glycobiologists interested in the application of bioinformatics tools and scientists of computational biology interested in studying the glycome.

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

Glycans, Glycosite, and Intact Glycopeptide Analysis of N-Linked Glycoproteins Using Liquid Handling Systems

Aberrant glycosylation has been shown to associate with disease progression, and with glycoproteins representing the major protein component of biological fluids this makes them attractive targets for disease monitoring. Leveraging glycoproteomic analysis via mass spectrometry (MS) could provide the insight into the altered glycosylation patterns that relate to disease progression. However, investigation of large sample cohorts requires rapid, efficient, and highly reproducible sample preparation. To address the limitation, we developed a high-throughput method for characterizing glycans, glycosites, and intact glycopeptides (IGPs) derived from N-linked glycoproteins. We combined disparate peptide enrichment strategies (i.e., hydrophilic and hydrophobic) and a liquid handling platform allowing for a high throughput and rapid enrichment of IGP in a 96-well plate format. The C18/MAX-Tip workflow reduced sample processing time and facilitated the selective enrichment of IGPs from complex samples. Furthermore, our approach enabled the analysis of deglycosylated peptides and glycans from enriched IGPs following PNGase F digest. Following development and optimization of the C18/MAX-Tip methodology using the standard glycoprotein, fetuin, we investigated normal urine samples to obtain N-linked glycoprotein information. Together, our method enables a high-throughput enrichment of glycan, glycosites, and IGPs from biological samples.

Revisiting the Language of Glycoscience: Readers, Writers and Erasers in Carbohydrate Biochemistry

The roles of carbohydrates in nature are many and varied. However, the lack of template encoding in glycoscience distances carbohydrate structure, and hence function, from gene sequence. This challenging situation is compounded by descriptors of carbohydrate structure and function that have tended to emphasise their complexity. Herein, we suggest that revising the language of glycoscience could make interdisciplinary discourse more accessible to all interested parties.

Rise of Systems Glycobiology and Personalized Glycomedicine: Why and How to Integrate Glycomics with Multiomics Science?

Glycomics is a rapidly emerging subspecialty of system sciences that evaluates the structures and functions of glycans in biological systems. Moreover, glycomics informs allied scholarships such as systems glycobiology and personalized glycomedicine that collectively aim to explain the role of glycans in person-to-person and between-population variations in disease susceptibility and response to health interventions such as drugs, nutrition, and vaccines. For glycomics to make greater, systems-scale, contributions to biology and medical research, it is facing a new developmental challenge: transition from single omics to multiomics integrative technology platforms. A comprehensive map of all possible connections between glycomics and other omics types has not yet been developed. Glycomics aims to discover a complex interplay of molecular interactions; however, little is known about the regulatory networks controlling these complex processes. In addition, the glycomics knowledgebase is presently scattered across various publications and databases, and therefore does not enable a holistic or systems view of this study field. Therefore, researchers are not always aware, for example, that a given analyzed genetic locus is linked with glycans, and that there are also glycomics determinants of complex phenotypes in health and biology. This review presents several published examples of glycomics science in association with other omics levels, such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, ncRNomics, lipidomics, and interactomics. I also highlight the salient knowledge gaps and suggest future research directions. Understanding the interconnections of glycomics with other omics technologies will facilitate multiomics science and knowledge integration, enhance development of systems glycobiology and personalized glycomedicine.

ST3Gal3 confers paclitaxel‑mediated chemoresistance in ovarian cancer cells by attenuating caspase‑8/3 signaling

The aberrant expression of sialyltransferase has a role in cell differentiation, neoplastic transformation and the progression of various types of cancer. Our previous studies have shown that high expression of β-galactoside-α2,3-sialyltransferase III (ST3Gal3) in the metastatic ovarian cancer cell line HO8910PM attenuated cisplatin-induced apoptosis. The present study demonstrated that paclitaxel-induced chemoresistance in ovarian cancer cells upregulated the expression of ST3Gal3 and reduced the activity of caspase-8/3. The results of the present study revealed that the endogenous levels of ST3Gal3 mRNA and protein were significantly higher in HO8910PM cells compared with SKOV3 cells. A higher expression of ST3Gal3 was correlated with an increased resistance to paclitaxel, while the downregulation of ST3Gal3 resulted in paclitaxel-induced apoptosis. Paclitaxel upregulated ST3Gal3 expression at the mRNA and protein levels in HO8910PM cells, but not in SKOV3 cells. Silencing of ST3Gal3 by small interfering RNA reversed these effects and increased the protein levels of caspase-8/3, which may contribute to paclitaxel-induced apoptosis. The results of the present study suggested that ST3Gal3 was a target for paclitaxel-related resistance during ovarian cancer chemotherapy.

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.

Advances in the relationship between glycosyltransferases and multidrug resistance in cancer

Despite great progress in clinical treatment, cancer remains a serious health problem contributing to significant morbidity and mortality worldwide. Although chemotherapy is a common therapeutic measure, multidrug resistance (MDR) presents a major challenge that often leads to poor prognosis. The abnormal expression of glycosyltransferases (GTs) leading to aberrant glycosylation patterns are considered a marker of cancer. Furthermore, the biosynthesis of these glycoconjugates has been associated with tumor proliferation, invasion and metastasis. Recently, studies have found that GTs are involved in mediating MDR in cancer cells through complex mechanisms and can influence therapeutic effect. In this review, we focus on several types of cancers and summarize previous studies on the correlation between GTs and MDR.

Glycan-based biomarkers for diagnosis of cancers and other diseases: Past, present, and future

Glycans are essential biomolecules in regulating human physiology and pathology ranging from signal transduction to microbial infections. Developing complex human diseases, such as cancer, diabetes, and cardiovascular diseases, are a combination of genetic and environmental factors. Genetics dominates embryonic development and the passing of genes to the next generation whereas the information in glycans reflects the impact of internal and external environmental factors, such as diseases, lifestyle, and social factors, on a person's health and disease. The reason behind this is that glycans are not directly encoded in a genetic template. Instead, they are assembled dynamically by hundreds of enzymes organized in more than 10 complex biosynthetic pathways. Any environmental changes affecting enzymatic activities or the availability of high-energy monosaccharide donors in a specific location will disturb the final structure of glycans. The glycan structure-dependent biological activities subsequently enable or disable gene expressions, which partially explain that it is difficult to pinpoint specific genetic defects to aging-associated diseases. Glycan-based biomarkers are currently used for diagnosis of diabetes, cancers, and other complex diseases. We will recapitulate the discovery of glucose, glycated proteins, glycan-, and glycoprotein-based biomarkers followed by summarizing clinically used glycan/glycoprotein-based biomarkers. The potential serum/plasma-derived N- and O-linked glycans as biomarkers will also be discussed.

Glycans and glycosaminoglycans in neurobiology: key regulators of neuronal cell function and fate

The aim of the present study was to examine the roles of l-fucose and the glycosaminoglycans (GAGs) keratan sulfate (KS) and chondroitin sulfate/dermatan sulfate (CS/DS) with selected functional molecules in neural tissues. Cell surface glycans and GAGs have evolved over millions of years to become cellular mediators which regulate fundamental aspects of cellular survival. The glycocalyx, which surrounds all cells, actuates responses to growth factors, cytokines and morphogens at the cellular boundary, silencing or activating downstream signaling pathways and gene expression. In this review, we have focused on interactions mediated by l-fucose, KS and CS/DS in the central and peripheral nervous systems. Fucose makes critical contributions in the area of molecular recognition and information transfer in the blood group substances, cytotoxic immunoglobulins, cell fate-mediated Notch-1 interactions, regulation of selectin-mediated neutrophil extravasation in innate immunity and CD-34-mediated new blood vessel development, and the targeting of neuroprogenitor cells to damaged neural tissue. Fucosylated glycoproteins regulate delivery of synaptic neurotransmitters and neural function. Neural KS proteoglycans (PGs) were examined in terms of cellular regulation and their interactive properties with neuroregulatory molecules. The paradoxical properties of CS/DS isomers decorating matrix and transmembrane PGs and the positive and negative regulatory cues they provide to neurons are also discussed.

Pathways from epigenomics and glycobiology towards novel biomarkers of addiction and its radical cure

The recent demonstration that addiction-relevant neuronal ensembles defined by known master transcription factors and their connectome is networked throughout mesocorticolimbic reward circuits and resonates harmonically at known frequencies implies that single-cell pan-omics techniques can improve our understanding of Substance Use Disorders (SUD's). Application of machine learning algorithms to such data could find diagnostic utility as biomarkers both to define the presence of the disorder and to quantitate its severity and find myriad applications in a developmental pipeline towards therapeutics and cure. Recent epigenomic studies have uncovered a wealth of clinically important data relating to synapse-nucleus signalling, memory storage, lineage-fate determination and cellular control and are contributing greatly to our understanding of all SUD's. Epigenetics interacts extensively with glycobiology. Glycans decorate DNA, RNA and many circulating critical proteins particularly immunoglobulins. Glycosylation is emerging as a major information-laden post-translational protein modification with documented application for biomarker development. The integration of these two emerging cutting-edge technologies provides a powerful and fertile algorithmic-bioinformatic space for the development both of SUD biomarkers and novel cutting edge therapeutics.

HYPOTHESES

These lines of evidence provide fertile ground for hypotheses relating to both diagnosis and treatment. They suggest that biomarkers derived from epigenomics complemented by glycobiology may potentially provide a bedside diagnostic tool which could be developed into a clinically useful biomarker to gauge both the presence and the severity of SUD's. Moreover they suggest that modern information-based therapeutics acting on the epigenome, via RNA interference or by DNA antisense oligonucleotides may provide a novel 21st century therapeutic development pipeline towards the radical cure of addictive disorders. Such techniques could be focussed and potentiated by neurotrophic vectors or the application of interfering electric or magnetic fields deep in the medial temporal lobes of the brain.

Screening of LDLR and APOB gene mutations in Mexican patients with homozygous familial hypercholesterolemia

BACKGROUND

Familial hypercholesterolemia (FH) is an autosomal dominant disorder that causes accumulation of serum low-density lipoprotein cholesterol and premature cardiovascular disease. It is mainly related to mutations in the LDLR gene. Homozygous FH (HoFH) patients have the most severe form of the disease accounting for a worldwide prevalence of 1:1,000,000. In Mexico, at least 5 cases of HoFH have been reported.

OBJECTIVE

The aim of this study was to describe the clinical, biochemical, and molecular data observed in patients with HoFH phenotype.

METHODS

We included 13 patients, belonging to 11 families, with clinical and biochemical diagnoses suggestive of HoFH. Molecular analyses of the LDLR and APOB genes were performed by means of polymerase chain reaction followed by Sanger sequencing.

RESULTS

The causal mutation of HoFH was found in 8 of 11 unrelated patients. Excepting 1, all were true homozygotes. Six different variants in LDLR were identified: c.-139delCTCCCCCTGC, p.Glu140Lys, p.Asp360His, p.Asn405Lys, p.Ala755Glyfs*7, and p.Leu759Serfs*6. Of these, p.Asp360His and p.Asn405Lys were detected for the first time in Mexico; p.Leu759Serfs*6 showed to be the most frequent (43.7% of the alleles 7/16), and c.-139delCTCCCCCTGC is a new variant located in the promoter region.

CONCLUSIONS

This work increases knowledge of biochemical and genetic features in Mexican patients with HoFH. A novel mutation in the LDLR gene promoter was detected: c.-139delCTCCCCCTGC, which possibly inhibits its expression.

Leveraging advances in biology to design biomaterials

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

CHO-Omics Review: The Impact of Current and Emerging Technologies on Chinese Hamster Ovary Based Bioproduction

CHO cells are the most prevalent platform for modern bio-therapeutic production. Currently, there are several CHO cell lines used in bioproduction with distinct characteristics and unique genotypes and phenotypes. These differences limit advances in productivity and quality that can be achieved by the most common approaches to bioprocess optimization and cell line engineering. Incorporating omics-based approaches into current bioproduction processes will complement traditional methodologies to maximize gains from CHO engineering and bioprocess improvements. In order to highlight the utility of omics technologies in CHO bioproduction, the authors discuss current applications as well as limitations of genomics, transcriptomics, proteomics, metabolomics, lipidomics, fluxomics, glycomics, and multi-omics approaches and the potential they hold for the future of bioproduction. Multiple omics approaches are currently being used to improve CHO bioprocesses; however, the application of these technologies is still limited. As more CHO-omic datasets become available and integrated into systems models, the authors expect significant gains in product yield and quality. While individual omics technologies provide incremental improvements in bioproduction, the authors will likely see the most significant gains by applying multi-omics and systems biology approaches to individual CHO cell lines.

Over forty years of bladder cancer glycobiology: Where do glycans stand facing precision oncology?

The high molecular heterogeneity of bladder tumours is responsible for significant variations in disease course, as well as elevated recurrence and progression rates, thereby hampering the introduction of more effective targeted therapeutics. The implementation of precision oncology settings supported by robust molecular models for individualization of patient management is warranted. This effort requires a comprehensive integration of large sets of panomics data that is yet to be fully achieved. Contributing to this goal, over 40 years of bladder cancer glycobiology have disclosed a plethora of cancer-specific glycans and glycoconjugates (glycoproteins, glycolipids, proteoglycans) accompanying disease progressions and dissemination. This review comprehensively addresses the main structural findings in the field and consequent biological and clinical implications. Given the cell surface and secreted nature of these molecules, we further discuss their potential for non-invasive detection and therapeutic development. Moreover, we highlight novel mass-spectrometry-based high-throughput analytical and bioinformatics tools to interrogate the glycome in the postgenomic era. Ultimately, we outline a roadmap to guide future developments in glycomics envisaging clinical implementation.

Comparison of Enrichment Methods for Intact N- and O-Linked Glycopeptides Using Strong Anion Exchange and Hydrophilic Interaction Liquid Chromatography

Heterogeneity of protein glycosylation poses great challenges for analysis that is key to understand structure and function of glycoproteins. Resolving this conundrum requires efficient and specific enrichment of intact glycopeptides for identification and quantitation. To this end, hydrophilic interaction chromatography (HILIC) has been commonly used to enrich intact N- and O-linked glycopeptides. However, its effectiveness to enrich isobarically labeled glycopeptides remains unclear. Here, we studied three different enrichment methods for enrichment of N- and O-linked glycopeptides. It was found that removal of N-glycans prior to enrichment of O-linked glycopeptides by HILIC improved identification of O-linked glycopeptides by mass spectrometry. We also compared the enrichment of intact N- and O-linked glycopeptides using other chromatography methods and found that using cartridges containing materials for strong anion exchange (SAX) chromatography increased yield and identification of N- and O-linked glycopeptides. The enrichment of O-linked glycopeptides was further improved when a Retain AX cartridge (RAX) was used. In particular, isobaric tag labeled glycopeptides after C18 desalting could be readily enriched by SAX and RAX cartridges but not by HILIC to enable quantitative glycoproteomics. It is anticipated that the use of SAX and RAX cartridges will facilitate broad applications of identifications and quantitation of glycoproteins.

Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions

BACKGROUND

Genome-wide association studies (GWAS) is a major method for studying the genetics of complex diseases. Finding all sequence variants to explain fully the aetiology of a disease is difficult because of their small effect sizes. To better explain disease mechanisms, pathway analysis is used to consolidate the effects of multiple variants, and hence increase the power of the study. While pathway analysis has previously been performed within GWAS only, it can now be extended to examining rare variants, other "-omics" and interaction data.

SCOPE OF REVIEW

1. Factors to consider in the choice of software for GWAS pathway analysis. 2. Examples of how pathway analysis is used to analyse rare variants, other "-omics" and interaction data.

MAJOR CONCLUSIONS

To choose appropriate software tools, factors for consideration include covariate compatibility, null hypothesis, one- or two-step analysis required, curation method of gene sets, size of pathways, and size of flanking regions to define gene boundaries. For rare variants, analysis performance depends on consistency between assumed and actual effect distribution of variants. Integration of other "-omics" data and interaction can better explain gene functions.

GENERAL SIGNIFICANCE

Pathway analysis methods will be more readily used for integration of multiple sources of data, and enable more accurate prediction of phenotypes.