SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells

Genetics of glycosylation in mammalian development and disease

Glycosylation of proteins and lipids in mammals is essential for embryogenesis and the development of all tissues. Analyses of glycosylation mutants in cultured mammalian cells and model organisms have been key to defining glycosylation pathways and the biological functions of glycans. More recently, applications of genome sequencing have revealed the breadth of rare congenital disorders of glycosylation in humans and the influence of genetics on the synthesis of glycans relevant to infectious diseases, cancer progression and diseases of the immune system. This improved understanding of glycan synthesis and functions is paving the way for advances in the diagnosis and treatment of glycosylation-related diseases, including the development of glycoprotein therapeutics through glycosylation engineering.

Droplet-based single-cell sequencing: Strategies and applications

Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.

Highly Sensitive Spatial Glycomics at Near-Cellular Resolution by On-Slide Derivatization and Mass Spectrometry Imaging

Glycans on proteins and lipids play important roles in maturation and cellular interactions, contributing to a variety of biological processes. Aberrant glycosylation has been associated with various human diseases including cancer; however, elucidating the distribution and heterogeneity of glycans in complex tissue samples remains a major challenge. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is routinely used to analyze the spatial distribution of a variety of molecules including N-glycans directly from tissue surfaces. Sialic acids are nine carbon acidic sugars that often exist as the terminal sugars of glycans and are inherently difficult to analyze using MALDI-MSI due to their instability prone to in- and postsource decay. Here, we report on a rapid and robust method for stabilizing sialic acid on N-glycans in FFPE tissue sections. The established method derivatizes and identifies the spatial distribution of α2,3- and α2,6-linked sialic acids through complete methylamidation using methylamine and PyAOP ((7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate). Our in situ approach increases the glycans detected and enhances the coverage of sialylated species. Using this streamlined, sensitive, and robust workflow, we rapidly characterize and spatially localize N-glycans in human tumor tissue sections. Additionally, we demonstrate this method's applicability in imaging mammalian cell suspensions directly on slides, achieving cellular resolution with minimal sample processing and cell numbers. This workflow reveals the cellular locations of distinct N-glycan species, shedding light on the biological and clinical significance of these biomolecules in human diseases.

Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes

Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.

Twin Scholarships of Glycomedicine and Precision Medicine in Times of Single-Cell Multiomics

Systems biology and multiomics research expand the prospects of planetary health innovations. In this context, this mini-review unpacks the twin scholarships of glycomedicine and precision medicine in the current era of single-cell multiomics. A significant growth in glycan research has been observed over the past decade, unveiling and establishing co- and post-translational modifications as dynamic indicators of both pathological and physiological conditions. Systems biology technologies have enabled large-scale and high-throughput glycoprofiling and access to data-intensive biological repositories for global research. These advancements have established glycans as a pivotal third code of life, alongside nucleic acids and amino acids. However, challenges persist, particularly in the simultaneous analysis of the glycome and transcriptome in single cells owing to technical limitations. In addition, holistic views of the complex molecular interactions between glycomics and other omics types remain elusive. We underscore and call for a paradigm shift toward the exploration of integrative glycan platforms and analysis methods for single-cell multiomics research and precision medicine biomarker discovery. The integration of multiple datasets from various single-cell omics levels represents a crucial application of systems biology in understanding complex cellular processes and is essential for advancing the twin scholarships of glycomedicine and precision medicine.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5-500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

Droplet-Based Glycan and RNA Sequencing for Profiling the Distinct Cellular Glyco-States in Single Cells

Plate-based single-cell glycan and RNA sequencing (scGR-seq) is previously developed to realize the integrated analysis of glycome and transcriptome in single cells. However, the sample size is limited to only a few hundred cells. Here, a droplet-based scGR-seq is developed to address this issue by adopting a 10x Chromium platform to simultaneously profile ten thousand cells' glycome and transcriptome in single cells. To establish droplet-based scGR-seq, a comparative analysis of two distinct cell lines is performed: pancreatic ductal adenocarcinoma cells and normal pancreatic duct cells. Droplet-based scGR-seq revealed distinct glycan profiles between the two cell lines that showed a strong correlation with the results obtained by flow cytometry. Next, droplet-based scGR-seq is applied to a more complex sample: peripheral blood mononuclear cells (PBMC) containing various immune cells. The method can systematically map the glycan signature for each immune cell in PBMC as well as glycan alterations by cell lineage. Prediction of the association between the glycan expression and the gene expression using regression analysis ultimately leads to the identification of a glycan epitope that impacts cellular functions. In conclusion, the droplet-based scGR-seq realizes the high-throughput profiling of the distinct cellular glyco-states in single cells.

Beyond single cells: microfluidics empowering multiomics analysis

Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.

LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling

Glycosylation affects many vital functions of organisms. Therefore, its surveillance is critical from basic science to biotechnology, including biopharmaceutical development and clinical diagnostics. However, conventional glycan structure analysis faces challenges with throughput and cost. Lectins offer an alternative approach for analyzing glycans, but they only provide glycan epitopes and not full glycan structure information. To overcome these limitations, we developed LeGenD, a lectin and AI-based approach to predict N-glycan structures and determine their relative abundance in purified proteins based on lectin-binding patterns. We trained the LeGenD model using 309 glycoprofiles from 10 recombinant proteins, produced in 30 glycoengineered CHO cell lines. Our approach accurately reconstructed experimentally-measured N-glycoprofiles of bovine Fetuin B and IgG from human sera. Explanatory AI analysis with SHapley Additive exPlanations (SHAP) helped identify the critical lectins for glycoprofile predictions. Our LeGenD approach thus presents an alternative approach for N-glycan analysis.

In Situ Glycan Analysis and Editing in Living Systems

Besides proteins and nucleic acids, carbohydrates are also ubiquitous building blocks of living systems. Approximately 70% of mammalian proteins are glycosylated. Glycans not only provide structural support for living systems but also act as crucial regulators of cellular functions. As a result, they are considered essential pieces of the life science puzzle. However, research on glycans has lagged far behind that on proteins and nucleic acids. The main reason is that glycans are not direct products of gene coding, and their synthesis is nontemplated. In addition, the diversity of monosaccharide species and their linkage patterns contribute to the complexity of the glycan structures, which is the molecular basis for their diverse functions. Research in glycobiology is extremely challenging, especially for the in situ elucidation of glycan structures and functions. There is an urgent need to develop highly specific glycan labeling tools and imaging methods and devise glycan editing strategies. This Perspective focuses on the challenges of in situ analysis of glycans in living systems at three spatial levels (i.e., cell, tissue, and in vivo) and highlights recent advances and directions in glycan labeling, imaging, and editing tools. We believe that examining the current development landscape and the existing bottlenecks can drive the evolution of in situ glycan analysis and intervention strategies and provide glycan-based insights for clinical diagnosis and therapeutics.

Elucidating the glycan-binding specificity and structure of Cucumis melo agglutinin, a new R-type lectin

Plant lectins have garnered attention for their roles as laboratory probes and potential therapeutics. Here, we report the discovery and characterization of Cucumis melo agglutinin (CMA1), a new R-type lectin from melon. Our findings reveal CMA1's unique glycan-binding profile, mechanistically explained by its 3D structure, augmenting our understanding of R-type lectins. We expressed CMA1 recombinantly and assessed its binding specificity using multiple glycan arrays, covering 1,046 unique sequences. This resulted in a complex binding profile, strongly preferring C2-substituted, beta-linked galactose (both GalNAc and Fuca1-2Gal), which we contrasted with the established R-type lectin Ricinus communis agglutinin 1 (RCA1). We also report binding of specific glycosaminoglycan subtypes and a general enhancement of binding by sulfation. Further validation using agglutination, thermal shift assays, and surface plasmon resonance confirmed and quantified this binding specificity in solution. Finally, we solved the high-resolution structure of the CMA1 N-terminal domain using X-ray crystallography, supporting our functional findings at the molecular level. Our study provides a comprehensive understanding of CMA1, laying the groundwork for further exploration of its biological and therapeutic potential.

Integration of Web-Based Tools to Visualize, Integrate, and Interpret Glycogene Expression and Glycomics Data

Glycosylation is the most abundant and diverse post-translational modification occurring on proteins. Glycans play important roles in modulating cell adhesion, growth, development, and differentiation. Changes in glycosylation affect protein structure and function and contribute to disease processes. Therefore, understanding glycosylation patterns is key for the identification of targets for the diagnosis of diseases, cellular states, and therapy. Glycosylation is a non template-driven process governed by the action of numerous enzymes and substrate availability that varies among cell types and species. Therefore, qualitative and quantitative assessment of global glycosylation and individual glycans remains challenging because it requires integration of multiple complex data types. Glycan structure and quantity data are often integrated with assessments of gene expression to aid contextualization of observed glycosylation changes within biological processes. However, correlating glycogene expression to the glycan structure is challenging because transcriptional changes may not always concur with the final gene product; there is often a lack of information on nucleotide sugar pools, and the final glycan structure is the result of many different glycogenes acting in concert. To overcome these challenges, interactive online tools are emerging as key resources for facilitating the analysis and integration of glycomics and glycogene expression data. Importantly, these tools work in concurrence with glycan biosynthetic schemes and therefore provide a clear indication of the molecular pathways where the glycan and glycogene are involved. In this chapter, we describe the applications of four freely available online tools that can be used for integrated visualization, interpretation, and presentation of RNAseq and glycomics results.

The role of glycosylation in clinical allergy and immunology

While glycans are among the most abundant macromolecules on the cell with widespread functions, their role in immunity has historically been challenging to study. This is in part due to difficulties assimilating glycan analysis into routine approaches used to interrogate immune cell function. Despite this, recent developments have illuminated fundamental roles for glycans in host immunity. The growing field of glycoimmunology continues to leverage new tools and approaches to uncover the function of glycans and glycan-binding proteins in immunity. Here we utilize clinical vignettes to examine key roles of glycosylation in allergy, inborn errors of immunity, and autoimmunity. We will discuss the diverse functions of glycans as epitopes, as modulators of antibody function, and as regulators of immune cell function. Finally, we will highlight immune modulatory therapies that harness the critical role of glycans in the immune system.

In-capillary sample processing coupled to label-free capillary electrophoresis-mass spectrometry to decipher the native N-glycome of single mammalian cells and ng-level blood isolates

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we developed an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased characterization and quantification of single-cell surface N-glycomes were demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations were unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow was also applied to the profiling of ng-level amounts of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives

Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate anatomical structure of these regions poses considerable challenges to efficacious treatment strategies. Despite the availability of myriad treatment modalities, the overall therapeutic efficacy for HNTs continues to remain subdued. In recent years, the deployment of artificial intelligence (AI) in healthcare practices has garnered noteworthy attention. AI modalities, inclusive of machine learning (ML), neural networks (NNs), and deep learning (DL), when amalgamated into the holistic management of HNTs, promise to augment the precision, safety, and efficacy of treatment regimens. The integration of AI within HNT management is intricately intertwined with domains such as medical imaging, bioinformatics, and medical robotics. This article intends to scrutinize the cutting-edge advancements and prospective applications of AI in the realm of HNTs, elucidating AI's indispensable role in prevention, diagnosis, treatment, prognostication, research, and inter-sectoral integration. The overarching objective is to stimulate scholarly discourse and invigorate insights among medical practitioners and researchers to propel further exploration, thereby facilitating superior therapeutic alternatives for patients.

Glycome dynamics in T and B cell development: basic immunological mechanisms and clinical applications

Glycans cover the surfaces of all mammalian cells through a process called glycosylation. Nearly all proteins and receptors that integrate the intricate series of co-stimulatory/inhibitory pathways of the immune system are glycosylated. Growing evidence indicates that the development of the immune system at the origins of T and B cell development is tightly regulated by glycosylation. In this opinion, we hypothesize that the glycome composition of developing T and B cells is developmentally regulated. We discuss how glycans play fundamental roles in lymphocyte development and how glycans early define T and B cell functionality in multiple aspects of adaptive immunity. These advances can provide opportunities for the discovery of novel disease factors and more effective candidate treatments for various conditions.

Chemoenzymatic Measurement of LacNAc in Single-Cell Multiomics Reveals It as a Cell-Surface Indicator of Glycolytic Activity of CD8+ T Cells

Despite the rich information about the physiological state of a cell encoded in the dynamic changes of cell-surface glycans, chemical methods to capture specific glycan epitopes at the single-cell level are quite limited. Here, we report a chemoenzymatic method for the single-cell detection of N-acetyllactosamine (LacNAc) by labeling LacNAc with a specific DNA barcode. The chemoenzymatic labeling does not alter the transcriptional status of immune cells and is compatible with multiple scRNA-seq platforms. Integrated analysis of LacNAc and the transcriptome of T cells at the single-cell level reveals that the amount of cell-surface LacNAc is significantly upregulated in activated CD8+ T cells but maintained at basal levels in resting CD8+ T cells (i.e., naive and central memory T cells). Further analysis confirms that LacNAc levels are positively correlated with the glycolytic activity of CD8+ T cells during differentiation. Taken together, our study demonstrates the feasibility of the chemoenzymatic detection of cell-surface glycan in single-cell RNA sequencing-based multiomics with TCR sequence and cell-surface epitope information (i.e., scTCR and CITE-seq), and provides a new way to characterize the biological role of glycan in diverse physiological states.

Roles of Siglecs in neurodegenerative diseases

Microglia are resident myeloid cells in the central nervous system (CNS) with a unique developmental origin, playing essential roles in developing and maintaining the CNS environment. Recent studies have revealed the involvement of microglia in neurodegenerative diseases, such as Alzheimer's disease, through the modulation of neuroinflammation. Several members of the Siglec family of sialic acid recognition proteins are expressed on microglia. Since the discovery of the genetic association between a polymorphism in the CD33 gene and late-onset Alzheimer's disease, significant efforts have been made to elucidate the molecular mechanism underlying the association between the polymorphism and Alzheimer's disease. Furthermore, recent studies have revealed additional potential associations between Siglecs and Alzheimer's disease, implying that the reduced signal from inhibitory Siglec may have an overall protective effect in lowering the disease risk. Evidences suggesting the involvement of Siglecs in other neurodegenerative diseases are also emerging. These findings could help us predict the roles of Siglecs in other neurodegenerative diseases. However, little is known about the functionally relevant Siglec ligands in the brain, which represents a new frontier. Understanding how microglial Siglecs and their ligands in CNS contribute to the regulation of CNS homeostasis and pathogenesis of neurodegenerative diseases may provide us with a new avenue for disease prevention and intervention.

Targeting galectin-driven regulatory circuits in cancer and fibrosis

Galectins are a family of endogenous glycan-binding proteins that have crucial roles in a broad range of physiological and pathological processes. As a group, these proteins use both extracellular and intracellular mechanisms as well as glycan-dependent and independent pathways to reprogramme the fate and function of numerous cell types. Given their multifunctional roles in both tissue fibrosis and cancer, galectins have been identified as potential therapeutic targets for these disorders. Here, we focus on the therapeutic relevance of galectins, particularly galectin 1 (GAL1), GAL3 and GAL9 to tumour progression and fibrotic diseases. We consider an array of galectin-targeted strategies, including small-molecule carbohydrate inhibitors, natural polysaccharides and their derivatives, peptides, peptidomimetics and biological agents (notably, neutralizing monoclonal antibodies and truncated galectins) and discuss their mechanisms of action, selectivity and therapeutic potential in preclinical models of fibrosis and cancer. We also review the results of clinical trials that aim to evaluate the efficacy of galectin inhibitors in patients with idiopathic pulmonary fibrosis, nonalcoholic steatohepatitis and cancer. The rapid pace of glycobiology research, combined with the acute need for drugs to alleviate fibrotic inflammation and overcome resistance to anticancer therapies, will accelerate the translation of anti-galectin therapeutics into clinical practice.

Proximity labeling technologies to illuminate glycan-protein interactions

Glycosylation is a ubiquitous post-translational modification read by glycan-binding proteins (GBP) to encode important functions, but a robust understanding of these interactions and their consequences can be challenging to uncover. Glycan-GBP interactions are transient and weak, making them difficult to capture, and glycosylation is dynamic and heterogenous, necessitating study in native cellular environments to identify endogenous ligands. Proximity labeling, an experimental innovation that labels biomolecules close to a protein of interest, has recently emerged as a powerful strategy to overcome these limitations, allowing interactors to be tagged in cells for subsequent enrichment and identification by mass spectrometry-based proteomics. We will describe this nascent technique and discuss its applications in the last five years with different GBP classes, including Siglecs, galectins, and non-human lectins.

(Glycan Binding) Activity‐Based Protein Profiling in Cells Enabled by Mass Spectrometry‐Based Proteomics

The presence of glycan modifications at the cell surface and other locales positions them as key regulators of cell recognition and function. However, due to the complexity of glycosylation, the annotation of which proteins bear glycan modifications, which glycan patterns are present, and which proteins are capable of binding glycans is incomplete. Inspired by activity-based protein profiling to enrich for proteins in cells based on select characteristics, these endeavors have been greatly advanced by the development of appropriate glycan-binding and glycan-based probes. Here, we provide context for these three problems and describe how the capability of molecules to interact with glycans has enabled the assignment of proteins with specific glycan modifications or of proteins that bind glycans. Furthermore, we discuss how the integration of these probes with high resolution mass spectrometry-based technologies has greatly advanced glycoscience.

A roadmap for translational cancer glycoimmunology at single cell resolution

Cancer cells can evade immune responses by exploiting inhibitory immune checkpoints. Immune checkpoint inhibitor (ICI) therapies based on anti-CTLA-4 and anti-PD-1/PD-L1 antibodies have been extensively explored over the recent years to unleash otherwise compromised anti-cancer immune responses. However, it is also well established that immune suppression is a multifactorial process involving an intricate crosstalk between cancer cells and the immune systems. The cancer glycome is emerging as a relevant source of immune checkpoints governing immunosuppressive behaviour in immune cells, paving an avenue for novel immunotherapeutic options. This review addresses the current state-of-the-art concerning the role played by glycans controlling innate and adaptive immune responses, while shedding light on available experimental models for glycoimmunology. We also emphasize the tremendous progress observed in the development of humanized models for immunology, the paramount contribution of advances in high-throughput single-cell analysis in this context, and the importance of including predictive machine learning algorithms in translational research. This may constitute an important roadmap for glycoimmunology, supporting careful adoption of models foreseeing clinical translation of fundamental glycobiology knowledge towards next generation immunotherapies.

Glycoinformatics in the Artificial Intelligence Era

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.

Deep learning explains the biology of branched glycans from single-cell sequencing data

Glycosylation is ubiquitous and often dysregulated in disease. However, the regulation and functional significance of various types of glycosylation at cellular levels is hard to unravel experimentally. Multi-omics, single-cell measurements such as SUGAR-seq, which quantifies transcriptomes and cell surface glycans, facilitate addressing this issue. Using SUGAR-seq data, we pioneered a deep learning model to predict the glycan phenotypes of cells (mouse T lymphocytes) from transcripts, with the example of predicting β1,6GlcNAc-branching across T cell subtypes (test set F1 score: 0.9351). Model interpretation via SHAP (SHapley Additive exPlanations) identified highly predictive genes, in part known to impact (i) branched glycan levels and (ii) the biology of branched glycans. These genes included physiologically relevant low-abundance genes that were not captured by conventional differential expression analysis. Our work shows that interpretable deep learning models are promising for uncovering novel functions and regulatory mechanisms of glycans from integrated transcriptomic and glycomic datasets.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Proteomics approaches to characterize the immune responses in cancer

Despite the dynamic development of cancer research, annually millions of people die of cancer. The human immune system is the major 'guard' against tumor development. Unfortunately, cancer cells have the ability to evade the immune system and continue to grow. The proper understanding of the intricate immune response in tumorigenesis remains the holy grail of cancer immunology and designing effective immunotherapy. To decode the immune responses in cancer, in recent years, proteomics studies have received considerable attention. Proteomics studies focus on the detection and quantification of proteins, which are the effectors of biological functions, and as such, are proven to reflect the cell state more accurately, in comparison to genomic or transcriptomic studies. In this review, we discuss the proteomics studies applied to characterize the immune responses in cancer and tumor immune microenvironment heterogeneity. Further, we describe emerging single-cell proteomics approaches that have the potential to be applied in cancer immunity studies.

Reading the glyco-code: New approaches to studying protein-carbohydrate interactions

The surface of all living cells is decorated with carbohydrate molecules. Hundreds of functional proteins bind to these glycosylated ligands; such binding events subsequently modulate many aspects of protein and cell function. Identifying ligands for glycan-binding proteins (GBPs) is a defining challenge of glycoscience research. Here, we review recent advances that are allowing protein-carbohydrate interactions to be dissected with an unprecedented level of precision. We specifically highlight how cell-based glycan arrays and glyco-genomic profiling are being used to define the structural determinants of glycan-protein interactions in living cells. Going forward, these methods create exciting new opportunities for the study of glycans in physiology and disease.

Concerted Regulation of Glycosylation Factors Sustains Tissue Identity and Function

Glycosylation is a fundamental cellular process affecting human development and health. Complex machinery establishes the glycan structures whose heterogeneity provides greater structural diversity than other post-translational modifications. Although known to present spatial and temporal diversity, the evolution of glycosylation and its role at the tissue-specific level is poorly understood. In this study, we combined genome and transcriptome profiles of healthy and diseased tissues to uncover novel insights into the complex role of glycosylation in humans. We constructed a catalogue of human glycosylation factors, including transferases, hydrolases and other genes directly involved in glycosylation. These were categorized as involved in N-, O- and lipid-linked glycosylation, glypiation, and glycosaminoglycan synthesis. Our data showed that these glycosylation factors constitute an ancient family of genes, where evolutionary constraints suppressed large gene duplications, except for genes involved in O-linked and lipid glycosylation. The transcriptome profiles of 30 healthy human tissues revealed tissue-specific expression patterns preserved across mammals. In addition, clusters of tightly co-expressed genes suggest a glycosylation code underlying tissue identity. Interestingly, several glycosylation factors showed tissue-specific profiles varying with age, suggesting a role in ageing-related disorders. In cancer, our analysis revealed that glycosylation factors are highly perturbed, at the genome and transcriptome levels, with a strong predominance of copy number alterations. Moreover, glycosylation factor dysregulation was associated with distinct cellular compositions of the tumor microenvironment, reinforcing the impact of glycosylation in modulating the immune system. Overall, this work provides genome-wide evidence that the glycosylation machinery is tightly regulated in healthy tissues and impaired in ageing and tumorigenesis, unveiling novel potential roles as prognostic biomarkers or therapeutic targets.

NKG7 Enhances CD8+ T Cell Synapse Efficiency to Limit Inflammation

Cytotoxic lymphocytes are essential for anti-tumor immunity, and for effective responses to cancer immunotherapy. Natural killer cell granule protein 7 (NKG7) is expressed at high levels in cytotoxic lymphocytes infiltrating tumors from patients treated with immunotherapy, but until recently, the role of this protein in cytotoxic lymphocyte function was largely unknown. Unexpectedly, we found that highly CD8+ T cell-immunogenic murine colon carcinoma (MC38-OVA) tumors grew at an equal rate in Nkg7^+/+ and Nkg7^-/- littermate mice, suggesting NKG7 may not be necessary for effective CD8+ T cell anti-tumor activity. Mechanistically, we found that deletion of NKG7 reduces the ability of CD8+ T cells to degranulate and kill target cells in vitro. However, as a result of inefficient cytotoxic activity, NKG7 deficient T cells form a prolonged immune synapse with tumor cells, resulting in increased secretion of inflammatory cytokines, including tumor necrosis factor alpha (TNF). By deleting the TNF receptor, TNFR1, from MC38-OVA tumors, we demonstrate that this hyper-secretion of TNF compensates for reduced synapse-mediated cytotoxic activity against MC38-OVA tumors in vivo, via increased TNF-mediated tumor cell death. Taken together, our results demonstrate that NKG7 enhances CD8+ T cell immune synapse efficiency, which may serve as a mechanism to accelerate direct cytotoxicity and limit potentially harmful inflammatory responses.

Tools for mammalian glycoscience research

Cellular carbohydrates or glycans are critical mediators of biological function. Their remarkably diverse structures and varied activities present exciting opportunities for understanding many areas of biology. In this primer, we discuss key methods and recent breakthrough technologies for identifying, monitoring, and manipulating glycans in mammalian systems.

Single-cell glycomics analysis by CyTOF-Lec reveals glycan features defining cells differentially susceptible to HIV

High-parameter single-cell phenotyping has enabled in-depth classification and interrogation of immune cells, but to date has not allowed for glycan characterization. Here, we develop CyTOF-Lec as an approach to simultaneously characterize many protein and glycan features of human immune cells at the single-cell level. We implemented CyTOF-Lec to compare glycan features between different immune subsets from blood and multiple tissue compartments, and to characterize HIV-infected cell cultures. Using bioinformatics approaches to distinguish preferential infection of cellular subsets from viral-induced remodeling, we demonstrate that HIV upregulates the levels of cell-surface fucose and sialic acid in a cell-intrinsic manner, and that memory CD4+ T cells co-expressing high levels of fucose and sialic acid are highly susceptible to HIV infection. Sialic acid levels were found to distinguish memory CD4+ T cell subsets expressing different amounts of viral entry receptors, pro-survival factors, homing receptors, and activation markers, and to play a direct role in memory CD4+ T cells' susceptibility to HIV infection. The ability of sialic acid to distinguish memory CD4+ T cells with different susceptibilities to HIV infection was experimentally validated through sorting experiments. Together, these results suggest that HIV remodels not only cellular proteins but also glycans, and that glycan expression can differentiate memory CD4+ T cells with vastly different susceptibility to HIV infection.

Applying transcriptomics to studyglycosylation at the cell type level

The complex multi-step process of glycosylation occurs in a single cell, yet current analytics generally cannot measure the output (the glycome) of a single cell. Here, we addressed this discordance by investigating how single cell RNA-seq data can be used to characterize the state of the glycosylation machinery and metabolic network in a single cell. The metabolic network involves 214 glycosylation and modification enzymes outlined in our previously built atlas of cellular glycosylation pathways. We studied differential mRNA regulation of enzymes at the organ and single cell level, finding that most of the general protein and lipid oligosaccharide scaffolds are produced by enzymes exhibiting limited transcriptional regulation among cells. We predict key enzymes within different glycosylation pathways to be highly transcriptionally regulated as regulatable hotspots of the cellular glycome. We designed the Glycopacity software that enables investigators to extract and interpret glycosylation information from transcriptome data and define hotspots of regulation.

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RNA-seq can provide information on the glycosylation metabolic network state

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It is possible to readout glycosylation capacity from single cell RNA-seq data

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Genes regulating the biosynthesis of common glycan scaffolds show little regulation

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Key enzymes in the glycosylation network are predicted to be regulatable hotspots

Bridging Glycomics and Genomics: New Uses of Functional Genetics in the Study of Cellular Glycosylation

All living cells are coated with a diverse collection of carbohydrate molecules called glycans. Glycans are key regulators of cell behavior and important therapeutic targets for human disease. Unlike proteins, glycans are not directly templated by discrete genes. Instead, they are produced through multi-gene pathways that generate a heterogenous array of glycoprotein and glycolipid antigens on the cell surface. This genetic complexity has sometimes made it challenging to understand how glycosylation is regulated and how it becomes altered in disease. Recent years, however, have seen the emergence of powerful new functional genomics technologies that allow high-throughput characterization of genetically complex cellular phenotypes. In this review, we discuss how these techniques are now being applied to achieve a deeper understanding of glyco-genomic regulation. We highlight specifically how methods like ChIP-seq, RNA-seq, CRISPR genomic screening and scRNA-seq are being used to map the genomic basis for various cell-surface glycosylation states in normal and diseased cell types. We also offer a perspective on how emerging functional genomics technologies are likely to create further opportunities for studying cellular glycobiology in the future. Taken together, we hope this review serves as a primer to recent developments at the glycomics-genomics interface.

Glycan Profiling by Sequencing to Uncover Multicellular Communication: Launching Glycobiology in Single Cells and Microbiomes

Glycans are essential building blocks of life that are located at the outermost surface of all cells from mammals to bacteria and even viruses. Cell surface glycans mediate multicellular communication in diverse biological processes and are useful as "surface markers" to identify cells. Various single-cell sequencing technologies have already emerged that enable the high-throughput analysis of omics information, such as transcriptome and genome profiling on a cell-by-cell basis, which has advanced our understanding of complex multicellular interactions. However, there has been no robust technology to analyze the glycome in single cells, mainly because glycans with branched and heterogeneous structures cannot be readily amplified by polymerase chain reactions like nucleic acids. We hypothesized that the generation of lectins conjugated with DNA barcodes (DNA-barcoded lectins) would enable the conversion of glycan information to gene information, which may be amplified and measured using DNA sequencers. This technology will enable the simultaneous analysis of glycan and RNA in single cells. Based on this concept, we developed a technology to analyze glycans and RNA in single cells, which was referred to as scGR-seq. Using scGR-seq, we acquired glycan and gene expression profiles of individual cells constituting heterogeneous cell populations, such as tissues. We further extended Glycan-seq to the profiling of the surface glycans of bacteria and even gut microbiota. Glycan-seq and scGR-seq are new technologies that enable us to elucidate the function of glycans in cell-cell and cell-microorganism communication, which extends glycobiology to the level of single cells and microbiomes.

Spatiotemporal diversity and regulation of glycosaminoglycans in cell homeostasis and human disease

Glycosaminoglycans (GAGs) are long, linear polysaccharides that are ubiquitously expressed on the cell surface and in the extracellular matrix of all animal cells. These complex carbohydrates play important roles in many cellular processes and have been implicated in many disease states, including cancer, inflammation, and genetic disorders. GAGs are among the most complex molecules in biology with enormous information content and extensive structural and functional heterogeneity. GAG biosynthesis is a nontemplate-driven process facilitated by a large group of biosynthetic enzymes that have been extensively characterized over the past few decades. Interestingly, the expression of the enzymes and the consequent structure and function of the polysaccharide chains can vary temporally and spatially during development and under certain pathophysiological conditions, suggesting their assembly is tightly regulated in cells. Due to their many key roles in cell homeostasis and disease, there is much interest in targeting the assembly and function of GAGs as a therapeutic approach. Recent advances in genomics and GAG analytical techniques have pushed the field and generated new perspectives on the regulation of mammalian glycosylation. This review highlights the spatiotemporal diversity of GAGs and the mechanisms guiding their assembly and function in human biology and disease.

The dynamic brain N-glycome

The attachment of carbohydrates to other macromolecules, such as proteins or lipids, is an important regulatory mechanism termed glycosylation. One subtype of protein glycosylation is asparagine-linked glycosylation (N-glycosylation) which plays a key role in the development and normal functioning of the vertebrate brain. To better understand the role of N-glycans in neurobiology, it's imperative we analyse not only the functional roles of individual structures, but also the collective impact of large-scale changes in the brain N-glycome. The systematic study of the brain N-glycome is still in its infancy and data are relatively scarce. Nevertheless, the prevailing view has been that the neuroglycome is inherently restricted with limited capacity for variation. The development of improved methods for N-glycomics analysis of brain tissue has facilitated comprehensive characterisation of the complete brain N-glycome under various experimental conditions on a larger scale. Consequently, accumulating data suggest that it's more dynamic than previously recognised and that, within a general framework, it has a given capacity to change in response to both intrinsic and extrinsic stimuli. Here, we provide an overview of the many factors that can alter the brain N-glycome, including neurodevelopment, ageing, diet, stress, neuroinflammation, injury, and disease. Given this emerging evidence, we propose that the neuroglycome has a hitherto underappreciated plasticity and we discuss the therapeutic implications of this regarding the possible reversal of pathological changes via interventions. We also briefly review the merits and limitations of N-glycomics as an analytical method before reflecting on some of the outstanding questions in the field.

Towards Tabula Gallus

The Tabula Gallus is a proposed project that aims to create a map of every cell type in the chicken body and chick embryos. Chickens (Gallus gallus) are one of the most recognized model animals that recapitulate the development and physiology of mammals. The Tabula Gallus will generate a compendium of single-cell transcriptome data from Gallus gallus, characterize each cell type, and provide tools for the study of the biology of this species, similar to other ongoing cell atlas projects (Tabula Muris and Tabula Sapiens/Human Cell Atlas for mice and humans, respectively). The Tabula Gallus will potentially become an international collaboration between many researchers. This project will be useful for the basic scientific study of Gallus gallus and other birds (e.g., cell biology, molecular biology, developmental biology, neuroscience, physiology, oncology, virology, behavior, ecology, and evolution). It will eventually be beneficial for a better understanding of human health and diseases.

Improved ClickTags Enable Live-cell Barcoding for Highly Multiplexed Single-cell Sequencing

Click chemistry-enabled DNA barcoding of cells provides a universal strategy for sample multiplexing in single-cell RNA-seq (scRNA-seq). However, current ClickTags are limited to fixed samples as they only label cells efficiently in methanol. Herein, we report the development of a new protocol for barcoding live cells with improved ClickTags. The optimized reactions barcoded live cells without perturbing their physiological states, which allowed sample multiplexing of live cells in scRNA-seq. The general applicability of this protocol is demonstrated in diversified types of samples, including murine and human primary samples. Up to 16 samples across these two species are successfully multiplexed and demultiplexed with high consistency. The wide applications of this method could help to increase throughput, reduce cost and remove the batch effect in scRNA-seq, which is especially valuable for studying clinical samples from a large cohort.

A versatile and highly reproducible approach for live cell sample multiplexing is achieved by DNA barcoding via “click chemistry” in single-cell RNA-seq.

Finding the sweet spot: glycosylation mediated regulation of intestinal inflammation

Glycans are essential cellular components that facilitate a range of critical functions important for tissue development and mucosal homeostasis. Furthermore, specific alterations in glycosylation represent important diagnostic hallmarks of cancer that contribute to tumor cell dissociation, invasion, and metastasis. However, much less is known about how glycosylation contributes to the pathobiology of inflammatory mucosal diseases. Here we will review how epithelial and immune cell glycosylation regulates gut homeostasis and how inflammation-driven changes in glycosylation contribute to intestinal pathobiology.

Glycowork: A Python package for glycan data science and machine learning

While glycans are crucial for biological processes, existing analysis modalities make it difficult for researchers with limited computational background to include these diverse carbohydrates into workflows. Here, we present glycowork, an open-source Python package designed for glycan-related data science and machine learning by end users. Glycowork includes functions to, for instance, automatically annotate glycan motifs and analyze their distributions via heatmaps and statistical enrichment. We also provide visualization methods, routines to interact with stored databases, trained machine learning models and learned glycan representations. We envision that glycowork can extract further insights from glycan datasets and demonstrate this with workflows that analyze glycan motifs in various biological contexts. Glycowork can be freely accessed at https://github.com/BojarLab/glycowork/.

Integrated analysis of glycan and RNA in single cells

Single-cell sequencing has emerged as an indispensable technology to dissect cellular heterogeneity but never been applied to the simultaneous analysis of glycan and RNA. Using oligonucleotide-labeled lectins, we first established lectin-based glycan profiling of single cells by sequencing (scGlycan-seq). We then combined the scGlycan-seq with single-cell transcriptome profiling for joint analysis of glycan and RNA in single cells (scGR-seq). Using scGR-seq, we analyzed the two modalities in human induced pluripotent stem cells (hiPSCs) before and after differentiation into neural progenitor cells at the single-cell resolution. The combination of RNA and glycan separated the two cell types clearer than either one of them. Furthermore, integrative analysis of glycan and RNA modalities in single cells found known and unknown lectins that were specific to hiPSCs and coordinated with neural differentiation. Taken together, we demonstrate that scGR-seq can reveal the cellular heterogeneity and biological roles of glycans across multicellular systems.

The glycobiology of uropathogenic E. coli infection: the sweet and bitter role of sugars in urinary tract immunity

Urinary tract infections (UTI) are among the most prevalent infectious diseases and the most common cause of nosocomial infections, worldwide. Uropathogenic E. coli (UPEC) are responsible for approximately 80% of all UTI, which most commonly affect the bladder. UPEC colonize the urinary tract by ascension of the urethra, followed by cell invasion, and proliferation inside and outside urothelial cells, thereby causing symptomatic infections and quiescent intracellular reservoirs that may lead to recurrence. Sugars, or glycans, are key molecules for host–pathogen interactions, and UTI are no exception. Surface glycans regulate many of the events associated with UPEC adhesion and infection, as well as induction of the host immune response. While the bacterial protein FimH binds mannose‐containing host glycoproteins to initiate infection and UPEC‐secreted polysaccharides block immune mechanisms to favour intracellular replication, host glycans on the urothelial surface and on secreted glycoproteins prevent or limit infection by inhibiting UPEC adhesion. Given the importance of glycans during UTI, here we review the glycobiology of UPEC infection to highlight fundamental sugar‐mediated processes of immunological interest for their potential clinical applications. Interdisciplinary approaches incorporating glycomics and infection biology may help to develop novel non‐antibiotic‐based therapeutic strategies for bacterial infections as the spread of antimicrobial‐resistant uropathogens is currently threatening modern healthcare systems.