Glycomics: an integrated systems approach to structure-function relationships of glycans

Extraction, physicochemical properties, bioactivities and application of natural sweeteners: A review

Natural sweeteners generally refer to a sweet chemical component directly extracted from nature or obtained through appropriate modifications, mainly secondary metabolites of plants. Compared to the first-generation sweeteners represented by sucrose and the second-generation sweeteners represented by sodium cyclamate, natural sweeteners usually have high sweetness, low-calorie content, good solubility, high stability, and rarely toxic side effects. Historically, researchers mainly focus on the function of natural sweeteners as substitutes for sugars in the food industry. This paper reviews the bioactivities of several typical natural sweeteners, including anti-cancer, anti-inflammatory, antioxidant, anti-bacterial, and anti-hyperglycemic activities. In addition, we have summarized the extraction, physicochemical properties, and application of natural sweeteners. The article aimed to comprehensively collate vital information about natural sweeteners and review the potentiality of tapping bioactive compounds from natural products. Hopefully, this review provides insights into the further development of natural sweeteners as therapeutic agents and functional foods.

Exploring snake venoms beyond the primary sequence: From proteoforms to protein-protein interactions

Snakebite envenomation has been a long-standing global issue that is difficult to treat, largely owing to the flawed nature of current immunoglobulin-based antivenom therapy and the complexity of snake venoms as sophisticated mixtures of bioactive proteins and peptides. Comprehensive characterisation of venom compositions is essential to better understanding snake venom toxicity and inform effective and rationally designed antivenoms. Additionally, a greater understanding of snake venom composition will likely unearth novel biologically active proteins and peptides that have promising therapeutic or biotechnological applications. While a bottom-up proteomic workflow has been the main approach for cataloguing snake venom compositions at the toxin family level, it is unable to capture snake venom heterogeneity in the form of protein isoforms and higher-order protein interactions that are important in driving venom toxicity but remain underexplored. This review aims to highlight the importance of understanding snake venom heterogeneity beyond the primary sequence, in the form of post-translational modifications that give rise to different proteoforms and the myriad of higher-order protein complexes in snake venoms. We focus on current top-down proteomic workflows to identify snake venom proteoforms and further discuss alternative or novel separation, instrumentation, and data processing strategies that may improve proteoform identification. The current higher-order structural characterisation techniques implemented for snake venom proteins are also discussed; we emphasise the need for complementary and higher resolution structural bioanalytical techniques such as mass spectrometry-based approaches, X-ray crystallography and cryogenic electron microscopy, to elucidate poorly characterised tertiary and quaternary protein structures. We envisage that the expansion of the snake venom characterisation "toolbox" with top-down proteomics and high-resolution protein structure determination techniques will be pivotal in advancing structural understanding of snake venoms towards the development of improved therapeutic and biotechnology applications.

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.

Triplex glycan quantification by metabolic labeling with isotopically labeled glucose in yeast

Mass spectrometry-based approaches encompass a powerful collection of tools for the analysis biological molecules, including glycans and glycoconjugates. Unlike most traditional bioanalytical methods focusing on these molecules, mass spectrometry is especially suited for multiplexing, by utilizing stable-isotope labeling. Indeed, stable isotope-based multiplexing can be regarded as the gold-standard approach in reducing noise and uncertainty in quantitative mass spectrometry and quantitative analyses generally. The increasing sophistication and depth of biological questions being asked continue to challenge the practitioners of mass spectrometry method development. To understand the biological relevance of glycans, many stable isotope labeling-based mass spectrometry methods have been developed. Based on the duplex MILPIG (metabolic isotope labeling of polysaccharides with isotopic glucose), we establish here a novel triplex isotope labeling method using baker's yeast as the model system. Two differentially isotope-labeled glucoses (medium: 1-13C1 and heavy: 1,2-13C2), in addition to natural abundance glucose (light), were successfully used to label each monosaccharide ring in N-linked glycans in three different cell culture conditions, that, after sample mixing, resulted in a predictable triplet spectrum amenable for relative quantitation. We demonstrate excellent accuracy and precision of relative quantitation for a 1:1:1 mixture of glycans labeled in such a fashion. In addition, we applied triplex MILPIG to interrogate differential N-glycan profiles in tunicamycin-treated and control yeast cells and show that different N-glycans respond differently to tunicamycin.

Pregnancy diagnosis and sex identification with urinary glycopatterns of two mammal species

Glycome in urine could be promising biomarkers for detecting pregnancy diagnosis and sex noninvasively for animals, especially for rare species. We explore the applicability of grouping golden snub-nosed monkeys by sex or diagnosing pregnancy based on their urinary glycopatterns, which are determined via lectin microarray combining mass spectrometry analysis. Sprague-Dawley rats are used to verify whether this approach and whether the glycomic biomarkers can be generalized to other mammalian species. The results show that, for both species, lectin microarray combining mass spectrometry can distinguish individuals' pregnancy status and sex; significant differences are found in the types, amounts, and terminal modification of glycans between pregnant and non-pregnant females and between females and males. This indicates the approach could be generalized to other mammalian species to group sex and detect pregnancy, yet the glycopatterns appear to be species-specific and markers developed from one species may not be directly applicable to another.

6-Plex mdSUGAR Isobaric-Labeling Guide Fingerprint Embedding for Glycomics Analysis

Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex mdSUGAR isobaric-labeling guide fingerprint embedding (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex mdSUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 103 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.

Polyol recognition in catalysis: toward selective modification of glycosylated polypeptides with boronic acid-rhodium(II) catalysts

Proximity-induced methodologies for peptide and protein modification have been developed using recognition elements like inhibitors, antibodies, or affinity tags on amino acids. However, the recognition of saccharides for chemical modification remains widely unexplored. Studies exploring boronic acids and their derivatives have shown their alluring capabilities as selective molecular recognition elements for saccharides, and in this study we describe the application of these ideas to the discovery of a catalytic proximity-induced methodology for covalent modification of glycopeptides using boronic acids as a saccharide recognition element.

Chemoenzymatic synthesis of genetically-encoded multivalent liquid N-glycan arrays

Cellular glycosylation is characterized by chemical complexity and heterogeneity, which is challenging to reproduce synthetically. Here we show chemoenzymatic synthesis on phage to produce a genetically-encoded liquid glycan array (LiGA) of complex type N-glycans. Implementing the approach involved by ligating an azide-containing sialylglycosyl-asparagine to phage functionalized with 50-1000 copies of dibenzocyclooctyne. The resulting intermediate can be trimmed by glycosidases and extended by glycosyltransferases yielding a phage library with different N-glycans. Post-reaction analysis by MALDI-TOF MS allows rigorous characterization of N-glycan structure and mean density, which are both encoded in the phage DNA. Use of this LiGA with fifteen glycan-binding proteins, including CD22 or DC-SIGN on cells, reveals optimal structure/density combinations for recognition. Injection of the LiGA into mice identifies glycoconjugates with structures and avidity necessary for enrichment in specific organs. This work provides a quantitative evaluation of the interaction of complex N-glycans with GBPs in vitro and in vivo.

The biofilm matrix: multitasking in a shared space

The biofilm matrix can be considered to be a shared space for the encased microbial cells, comprising a wide variety of extracellular polymeric substances (EPS), such as polysaccharides, proteins, amyloids, lipids and extracellular DNA (eDNA), as well as membrane vesicles and humic-like microbially derived refractory substances. EPS are dynamic in space and time and their components interact in complex ways, fulfilling various functions: to stabilize the matrix, acquire nutrients, retain and protect eDNA or exoenzymes, or offer sorption sites for ions and hydrophobic substances. The retention of exoenzymes effectively renders the biofilm matrix an external digestion system influencing the global turnover of biopolymers, considering the ubiquitous relevance of biofilms. Physico-chemical and biological interactions and environmental conditions enable biofilm systems to morph into films, microcolonies and macrocolonies, films, ridges, ripples, columns, pellicles, bubbles, mushrooms and suspended aggregates - in response to the very diverse conditions confronting a particular biofilm community. Assembly and dynamics of the matrix are mostly coordinated by secondary messengers, signalling molecules or small RNAs, in both medically relevant and environmental biofilms. Fully deciphering how bacteria provide structure to the matrix, and thus facilitate and benefit from extracellular reactions, remains the challenge for future biofilm research.

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.

The preparation technology and application of xylo-oligosaccharide as prebiotics in different fields: A review

Xylo-oligosaccharide (XOS) is a class of functional oligosaccharides that have been demonstrated with prebiotic activity over several decades. XOS has several advantages relative to other oligosaccharide molecules, such as promoting root development as a plant regulator, a sugar supplement for people, and prebiotics to promote intestinal motility utilization health. Now, the preparation and extraction process of XOS is gradually mature, which can maximize the extraction and avoid waste. To fully understand the recent preparation and application of XOS in different areas, we summarized the various technologies for obtaining XOS (including acid hydrolysis, enzymatic hydrolysis, hydrothermal pretreatment, and alkaline extraction) and current applications of XOS, including in animal feed, human food additives, and medicine. It is hoped that this review will serve as an entry point for those looking into the prebiotic field of research, and perhaps begin to dedicate their work toward this exciting classification of bio-based molecules.

An Automated Approach to Assess Relative Galectin-Glycan Affinity Following Glycan Microarray Analysis

Numerous studies have highlighted the utility of glycan microarray analysis for the elucidation of protein-glycan interactions. However, most current glycan microarray studies analyze glycan binding protein (GBP)-glycan interactions at a single protein concentration. While this approach provides useful information related to a GBP's overall binding capabilities, extrapolation of true glycan binding preferences using this method fails to account for printing variations or other factors that may confound relative binding. To overcome this limitation, we examined glycan array binding of three galectins over a range of concentrations to allow for a more complete assessment of binding preferences. This approach produced a richer data set than single concentration analysis and provided more accurate identification of true glycan binding preferences. However, while this approach can be highly informative, currently available data analysis approaches make it impractical to perform binding isotherms for each glycan present on currently available platforms following GBP evaluation. To overcome this limitation, we developed a method to directly optimize the efficiency of assessing association constants following multi-GBP concentration glycan array analysis. To this end, we developed programs that automatically analyze raw array data (kdMining) to generate output graphics (kaPlotting) following array analysis at multiple doses. These automatic programing methods reduced processing time from 32.8 h to 1.67 min. Taken together, these results demonstrate an effective approach to glycan array analysis that provides improved detail and efficiency when compared to previous methods.

Advances in glycopeptide enrichment methods for the analysis of protein glycosylation over the past decade

Advances in bioanalytical technology have accelerated the analysis of complex protein glycosylation, which is beneficial to understanding glycosylation in drug discovery and disease diagnosis. Due to its biological uniqueness in the course of disease occurrence and development, disease-specific glycosylation requires quantitative characterization of protein glycosylation. We provide a comprehensive review of recent advances in glycosylation analysis, including workflows for glycoprotein digestion, glycopeptide separation and enrichment, and mass-spectrometry sequencing. We specifically focus on different strategies for glycopeptide enrichment through physical interaction, chemical oxidation, or metabolic labeling of intact glycopeptides. The recent advances and challenges of O-glycosylation analysis are presented, and the development of improved enrichment methods combining different proteases to analyze O-glycosylation is also proposed. This article is protected by copyright. All rights reserved.

GlyNet: a multi-task neural network for predicting protein-glycan interactions

Advances in diagnostics, therapeutics, vaccines, transfusion, and organ transplantation build on a fundamental understanding of glycan-protein interactions. To aid this, we developed GlyNet, a model that accurately predicts interactions (relative binding strengths) between mammalian glycans and 352 glycan-binding proteins, many at multiple concentrations. For each glycan input, our model produces 1257 outputs, each representing the relative interaction strength between the input glycan and a particular protein sample. GlyNet learns these continuous values using relative fluorescence units (RFUs) measured on 599 glycans in the Consortium for Functional Glycomics glycan arrays and extrapolates these to RFUs from additional, untested glycans. GlyNet's output of continuous values provides more detailed results than the standard binary classification models. After incorporating a simple threshold to transform such continuous outputs the resulting GlyNet classifier outperforms those standard classifiers. GlyNet is the first multi-output regression model for predicting protein-glycan interactions and serves as an important benchmark, facilitating development of quantitative computational glycobiology.

Oligosaccharides production from coprophilous fungi: An emerging functional food with potential health-promoting properties

Functional foods are essential food products that possess health-promoting properties for the treatment of infectious diseases. In addition, they provide energy and nutrients, which are required for growth and survival. They occur as prebiotics or dietary supplements, including oligosaccharides, processed foods, and herbal products. However, oligosaccharides are more efficiently recognized and utilized, as they play a fundamental role as functional ingredients with great potential to improve health in comparison to other dietary supplements. They are low molecular weight carbohydrates with a low degree of polymerization. They occur as fructooligosaccharide (FOS), inulooligosaccharadie (IOS), and xylooligosaccahride (XOS), depending on their monosaccharide units. Oligosaccharides are produced by acid or chemical hydrolysis. However, this technique is liable to several drawbacks, including inulin precipitation, high processing temperature, low yields, and high production costs. As a consequence, the application of microbial enzymes for oligosaccharide production is recognized as a promising strategy. Microbial enzymatic production of FOS and IOS occurs by submerged or solid-state fermentation in the presence of suitable substrates (sucrose, inulin) and catalyzed by fructosyltransferases and inulinases. Incorporation of FOS and IOS enriches the rheological and physiological characteristics of foods. They are used as low cariogenic sugar substitutes, suitable for diabetics, and as prebiotics, probiotics and nutraceutical compounds. In addition, these oligosaccharides are employed as anticancer, antioxidant agents and aid in mineral absorption, lipid metabolism, immune regulation etc. This review, therefore, focuses on the occurrence, physico-chemical characteristics, and microbial enzymatic synthesis of FOS and IOS from coprophilous fungi. In addition, the potential health benefits of these oligosaccharides were discussed in detail.

Informatics Ecosystems to Advance the Biology of Glycans

Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential and has exhibited initial success, to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources and informatics ecosystems to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. Integrated data sets provide a foundation for novel methods of analysis such as machine learning and deep learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.

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.

An Overview of Glycosylation and its Impact on Cardiovascular Health and Disease

The cardiovascular system is a complex and well-organized system in which glycosylation plays a vital role. The heart and vascular wall cells are constituted by an array of specific receptors; most of them are N- glycosylated and mucin-type O-glycosylated. There are also intracellular signaling pathways regulated by different post-translational modifications, including O-GlcNAcylation, which promote adequate responses to extracellular stimuli and signaling transduction. Herein, we provide an overview of N-glycosylation and O-glycosylation, including O-GlcNAcylation, and their role at different levels such as reception of signal, signal transduction, and exogenous molecules or agonists, which stimulate the heart and vascular wall cells with effects in different conditions, like the physiological status, ischemia/reperfusion, exercise, or during low-grade inflammation in diabetes and aging. Furthermore, mutations of glycosyltransferases and receptors are associated with development of cardiovascular diseases. The knowledge on glycosylation and its effects could be considered biochemical markers and might be useful as a therapeutic tool to control cardiovascular diseases.

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.

Transcriptome analysis reveals important candidate gene families related to oligosaccharides biosynthesis in Morindaofficinalis

Morinda officinalis How (MO) is one of the best-known traditional herbs and is widely cultivated in subtropical and tropical areas for many years, especially in southern China. Oligosaccharides are the major constituents in the roots of MO, which is well known for its therapeutic effects with anti-depression, anti-osteoporosis, memory-enhancing, ect. To date, the main gene families that regulate the biosynthetic pathway of MO oligosaccharides metabolism yet have been published. In our study, six cDNA libraries generated from six plants of MO were sequenced utilizing an Illumina HiSeq 4000 platform. Corresponding totals of more than 132.60 million clean reads were obtained from the six libraries and assembled into 25,812 unigenes with an average length of 1288 bp. Moreover, 6036 unigenes were found to be allocated to 26 pathways maps using several public databases, and 2538 differential expression genes (DEGs) were screened. Among them, 25 genes from three families were selected as the mainly candidate genes related to MO oligosaccharides biosynthesis. Then, the expression patterns of six DEGs closely related to MO oligosaccharides biosynthesis were verified by quantitative real-time PCR (qRT-PCR). Besides, the MO was clustered more closely to Coffea arabica of Rubiaceae. In summary, the transcriptomic analysis was used to investigate the differences in expression genes of oligosaccharides biosynthesis, with the notable outcome that several key gene families were closely linked to oligosaccharides biosynthesis.

Post-synthesis of boric acid-functionalized magnetic covalent organic framework as an affinity probe for the enrichment of N-glycopeptides

A novel type of boric acid-functionalized magnetic covalent organic framework (mCOF) with polyethyleneimine (PEI) as a linker (denoted as mCOF@PEI@B(OH)₂) has been prepared through a post-synthesis strategy, which points out an achievable path for the construction of boronic acid-functionalized COFs. Based on the boric acid chemistry, the obtained core-shell structured mCOF@PEI@B(OH)₂ can selectively isolate glycopeptides through the modified boronic acid groups. The mCOF@PEI@B(OH)₂ exhibits excellent performance with good reusability (ten cycles), low detection limit (0.5 fmol·μL^-1), size-exclusion effect, and relatively high loading capacity (80 μg·mg^-1), recovery yield (94.9 ± 2.8%), and selectivity (HRP digests:BSA digests = 1:500). Detection is done by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). In addition, 37 endogenous glycopeptides are captured from human saliva with mCOF@PEI@B(OH)₂, providing effective proofs for its capability to capture low-abundance glycopeptides from actual biological samples.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review

The first corona-pandemic, coronavirus disease 2019 (COVID-19) caused a huge health crisis and incalculable damage worldwide. Knowledge of how to cure the disease is urgently needed. Emerging immune escaping mutants of the virus suggested that it may be potentially persistent in human society as a regular health threat as the flu virus. Therefore, it is imperative to identify appropriate biomarkers to indicate pathological and physiological states, and more importantly, clinic outcomes. Proteins are the performers of life functions, and their abundance and modification status can directly reflect the immune status. Protein glycosylation serves a great impact in modulating protein function. The use of both unmodified and glycosylated proteins as biomarkers has also been proved feasible in the studies of SARS, Zika virus, influenza, etc. In recent years, mass spectrometry-based glycoproteomics, as well as proteomics approaches, advanced significantly due to the evolution of mass spectrometry. We focus on the current development of the mass spectrometry-based strategy for COVID-19 biomarkers' investigation. Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

[Advances in enrichment of phosphorylated peptides and glycopeptides by smart polymer-based materials]

翻译后修饰是蛋白质组学研究的前沿和重点,它不仅调节着蛋白质的折叠、状态、活性、定位以及蛋白质间的相互作用,也能帮助科学家更全面地了解生物体的生命过程,为疾病的预测、诊断和治疗提供更加强大的支撑和依据。翻译后修饰产物(例如磷酸化肽和糖肽)丰度很低,且存在着强烈的背景干扰,很难直接用质谱进行分析,因此迫切需要开发高效的富集材料和技术来选择性富集翻译后修饰产物。近年来,智能聚合物基材料通过外部物理、化学或生物刺激可逆地改变其结构和功能,实现对磷酸化肽和糖肽高度可控的吸附和脱附,进而衍生开发出一系列新颖的富集方法,极大地吸引研究者们的兴趣。一方面,智能聚合物基材料的响应变化包括材料疏水性的增加或减少、形状和形貌的改变、表面电荷的重新分布以及亲和配体的暴露或隐藏等特性。这些特性使得目标物和智能聚合物基材料之间的亲和力可以通过简单改变外部条件(如温度、pH值、溶剂极性和生物分子等)实现更可控和更智能的精细调节。另一方面,智能聚合物基材料为集成功能模块提供了便捷的可扩展平台,例如特定的识别组件,显著提高了目标物质的分离选择性。智能聚合物基材料在分离方面展现出巨大的潜力,这为蛋白质翻译后修饰产物的分析和研究带来了希望。围绕上述主题,该文依据Web of Science近20年来近50篇代表性文献,概述了智能聚合物基材料在磷酸化肽和糖肽分离及富集中的发展方向。

Genetically encoded multivalent liquid glycan array displayed on M13 bacteriophage

The central dogma of biology does not allow for the study of glycans using DNA sequencing. We report a liquid glycan array (LiGA) platform comprising a library of DNA 'barcoded' M13 virions that display 30-1,500 copies of glycans per phage. A LiGA is synthesized by acylation of the phage pVIII protein with a dibenzocyclooctyne, followed by ligation of azido-modified glycans. Pulldown of the LiGA with lectins followed by deep sequencing of the barcodes in the bound phage decodes the optimal structure and density of the recognized glycans. The LiGA is target agnostic and can measure the glycan-binding profile of lectins, such as CD22, on cells in vitro and immune cells in a live mouse. From a mixture of multivalent glycan probes, LiGAs identify the glycoconjugates with optimal avidity necessary for binding to lectins on living cells in vitro and in vivo.

Effective Enrichment Strategy Using Boronic Acid-Functionalized Mesoporous Graphene-Silica Composites for Intact N- and O-Linked Glycopeptide Analysis in Human Serum

The heterogeneity and low abundance of protein glycosylation present challenging barriers to the analysis of intact glycopeptides, which is key to comprehensively understanding the role of glycosylation in an organism. Efficient and specific enrichment of intact glycopeptides could help greatly with this problem. Here, we propose a new enrichment strategy using a boronic acid (BA)-functionalized mesoporous graphene-silica composite (denoted as GO@mSiO₂-GLYMO-APB) for isolating intact glycopeptides from complex biological samples. The merits of this composite, including high surface area and synergistic effect from size exclusion functionality of mesoporous material, hydrophilic interaction of silica, and the reversible covalent binding with BA, enable the effective and specific enrichment of both intact N- and O-glycopeptides. The results from the enrichment performance of the strategy evaluated by standard glycoproteins and the application to global N- and O-glycosylation analyses in human serum indicate the robustness and potential of the strategy for intact glycopeptide analysis.

Cell surface-localized imaging and sensing

Systematically dissecting the molecular basis of the cell surface as well as its related biological activities is considered as one of the most cutting-edge fields in fundamental sciences. The advent of various advanced cell imaging techniques allows us to gain a glimpse of how the cell surface is structured and coordinated with other cellular components to respond to intracellular signals and environmental stimuli. Nowadays, cell surface-related studies have entered a new era featured by a redirected aim of not just understanding but artificially manipulating/remodeling the cell surface properties. To meet this goal, biologists and chemists are intensely engaged in developing more maneuverable cell surface labeling strategies by exploiting the cell's intrinsic biosynthetic machinery or direct chemical/physical binding methods for imaging, sensing, and biomedical applications. In this review, we summarize the recent advances that focus on the visualization of various cell surface structures/dynamics and accurate monitoring of the microenvironment of the cell surface. Future challenges and opportunities in these fields are discussed, and the importance of cell surface-based studies is highlighted.

Dissection of the Glycosylation in the Biosynthesis of the Heptadecaglycoside Antibiotic Saccharomicin A

Oligosaccharide natural products have diverse biological activities and represent a potentially important source for drug development. In this study, we focus on the glycosylation pathway in the biosynthesis of saccharomicin A (SA-A), an oligosaccharide antibiotic containing 17 sugar moieties. By extensive gene-knockout studies with comparative metabolic profile analysis, we established a complete pathway in assembling the heptadecasaccharide chain of SA-A, the longest saccharide chain found in natural products.

Metabolic labeling of glycans with isotopic glucose for quantitative glycomics in yeast

Changes in glycan levels could directly affect the biochemical properties of glycoproteins and thus influence their physiological functions. In order to decode the correlation of glycan prevalence with their physiological contribution, many mass spectrometry (MS) and stable isotope labeling-based methods have been developed for the relative quantification of glycans. In this study, we expand the quantitative glycomic toolbox with the addition of optimized Metabolic Isotope Labeling of Polysaccharides with Isotopic Glucose (MILPIG) approach in baker's yeast (Saccharomyces cerevisiae). We demonstrate that culturing baker's yeast in the presence of carbon-13 labeled glucose (1-¹³C₁) leads to effective incorporation of carbon-13 to both N-linked and O-linked glycans. We established that metabolic incorporation of isotope-labeled glucose at a concentration of 5 mg/mL for three days is required for an accurate quantitative analysis with optimal isotopic cluster distribution of glycans. To validate the robustness of the method, we performed the analysis by 1:1 mixing of normal and isotope-labeled glycans, and obtained excellent linear calibration curves from various analytes. Finally, we quantitated the inhibitory effect of tunicamycin, a N-linked glycosylation inhibitor, to glycan expression profile in yeast.

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.

Potentiometric Determination of Circulating Glycoproteins by Boronic Acid End-Functionalized Poly(ethylene glycol)-Modified Electrode

Despite tremendous complexity in glycan structure, sialic acid (SA) provides an analytically accessible index for glycosylation, owing to its uniquely anionic nature and glycan-chain terminal occupation. Taking advantage of boronic acid (BA) based SA-recognition chemistry, we here demonstrate a label-free, no enzymatic, potentiometric determination of fetuin, a blood-circulating glycoprotein implicated in physiological and various pathological states. A phenylboronic acid (PBA) ω-end-functionalized poly(ethylene glycol) (PEG) with an α-tethering unit bearing pendent alkyne groups was "grafted-to" a gold electrode modified with 11-azide-undecathiol by a copper-catalyzed azide-alkyne cycloaddition reaction. Using the electrode, fetuin was potentiometrically detectable with a μM-order-sensitivity that is comparable to what is found in blood-collected specimen. Our finding may have implications for developing a remarkably economic hemodiagnostic technology with ease of downsizing and mass production.

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.

Relevance of glycans in the interaction between T lymphocyte and the antigen presenting cell

The immunological synapse promotes receptors and ligands interaction in the contact interface between the T lymphocyte and the antigen presenting cell; glycosylation of the proteins involved in this biological process favors regulation of molecular interactions and development of the T lymphocyte effector response. Glycans in the immunological synapse influence cellular and molecular processes such as folding, expression, and structural stability of proteins, they also mediate ligand-receptor interaction and propagation of the intracellular signaling or inhibition of uncontrolled cellular activation that could lead to the development of autoimmunity, among others. It has been suggested that altered glycosylation of proteins that participate in the immunological synapse affects the signaling processes and cell proliferation, as well as exacerbation of the effector mechanisms of T cells that trigger systemic damage and autoimmunity. Understanding the role of glycans in the immune response has allowed for advances in the development of immunotherapies in different fields through the controlled and specific activation of the immune response. This review describes the structural and biological aspects of glycans associated with some molecules present in the immunological synapse, providing information that allows understanding the function of glycosylation in the interaction between the T lymphocyte and the antigen-presenting cell, as well as its impact on signaling and development regulation of T lymphocytes effector response.

Highly stable folic acid functionalized copper-nanocluster/silica nanoparticles for selective targeting of cancer cells

In this paper, we present a novel strategy to construct folic acid functionalized conjugated Cu nanoclusters (CuNCs) and silica (SiO₂) nanocomposites for targeted detection of cancer cells. First of all, BSA capped CuNCs were encapsulated into a SiO₂ matrix. The resulting CuNCs@SiO₂ nanoparticles showed bright red fluorescence with an enhanced photoluminescence quantum yield compared with free CuNCs, as well as improved stability in a complex biological environment owning to the protection of the SiO₂ matrix. Upon attachment of folic acid via the poly-l-lysine conjugates (PLL-FA) on the surface of CuNCs@SiO₂ driven by electrostatic interaction, the as-prepared CuNCs@SiO₂/PLL-FA nanocomposites are capable of selectively recognizing folate receptor (FR) over-expressed cancer cells rather than FR-negative cells. The cell viability assay proved the low biotoxicity of CuNCs@SiO₂/PLL-FA nanocomposites toward living cells and the in vitro cellular imaging assay results demonstrated their selective endocytosis of FR-positive cells (KB cells), bringing about red fluorescence labeling within the cells. Intriguingly, our strategy provides a novel route to synthesize functional CuNCs@SiO₂/PLL-FA nanocomposites equipped with superior fluorescence properties, high stability against external stimuli and good biocompatibility, and have great application potential in bioimaging imaging and targeted cell detection.

Folic acid functionalized CuNCs@SiO₂ nanocomposites with superior fluorescence properties, high stability and good biocompatibility for targeted cell imaging.

Direct Observation of Cell Surface Sialylation by Atomic Force Microscopy Employing Boronic Acid-Sialic Acid Reversible Interaction

Tracing cell surface sialylation dynamics at a scale of the glycolipoprotein microdomain (lipid rafts) formations remains an intriguing challenge of cellular biology. Here, we demonstrate that this goal is accessible, taking advantage of a boronic acid (BA)-based reversible molecular recognition chemistry. A BA-end-functionalized poly(ethylene glycol) was decorated onto an atomic force microscopy (AFM) cantilever, which provided a dynamic and sialic acid (SA)-specific imaging mode. Using this technique, we were able to heat map the SA expression levels not only on protein-decorated substrates but also directly on the cell surfaces, with a submicrometer scale resolution that may be relevant to that of the lipid rafts formation. The SA specificity and the binding reversibility of the probe were confirmed from its pH-dependent characteristics and an inhibition assay using free state SA. This finding may provide a noninvasive means for assessing a variety of SA-involved glycosylation dynamics spanning from physiology to pathology.

CCMRD: a solid-state NMR database for complex carbohydrates

Carbohydrates are essential to various life activities in living organisms and serve as the central component in many biomaterials. As an emerging technique with steadily improving resolution, solid-state Nuclear Magnetic Resonance (NMR) spectroscopy has the unique capability in revealing the polymorphic structure and heterogeneous dynamics of insoluble complex carbohydrates. Here, we report the first solid-state NMR database for complex carbohydrates, Complex Carbohydrates Magnetic Resonance Database (CCMRD). This database currently holds the chemical shift information of more than four hundred solid-state NMR compounds and expects rapid expansion. CCMRD provides open portals for data deposition and supports search options based on NMR chemical shifts, carbohydrate names, and compound classes. With the timely implementation, this platform will facilitate spectral analysis and structure determination of carbohydrates and promote software development to benefit the research community. The database is freely accessible at www.ccmrd.org.

Identification of glycan branching patterns using multistage mass spectrometry with spectra tree analysis

Glycans are crucial to a wide range of biological processes, and their biological activities are closely related to the branching patterns of structures. Different from the simple linear chains of proteins, branching patterns of glycans are more complicated, making their identification extremely challenging. Tandem mass spectrometry (MS²) cannot provide sufficient structural information to deduce glycan branching patterns even with the assistance of various bioinformatic tools and algorithms.The promising technology to identify glycan branching patterns is multi-stage mass spectrometry (MSⁿ). The production-relationship among MSⁿ spectra of a glycan is essentially a tree, making deducing glycan structures from MSⁿ spectra a great challenge. In the present study, we report an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to fully exploit the information contained in the MSⁿ spectra tree for glycan identification. Using 14 glycan standards, including 2 pairs with isomeric sequence, and 16 complex N-glycans isolated from RNase B and IgG, we demonstrated the successful application of glyBranch to branching pattern analysis. The source code of glyBranch is available at https://github.com/bigict/glyBranch/. We have also developed a web-server, which is freely accessible at http://glycan.ict.ac.cn/glyBranch/. SIGNIFICANCE: Glycans are crucial in various biological processes and their functions are closely related to the details of their structures; thus, the identification of glycan branching patterns is of great significance to biological studies. Multistage mass spectrometry (MSⁿ) can provide detailed structural information by generating multiple-level fragments through consecutive fragmentation; however, the interpretation of numerous MSⁿ spectra is extremely challenging. In this study, we present an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to exploit the information contained in MSⁿ spectra tree for glycan identification. This approach will greatly facilitate the automated identification of glycan structures and related biological studies.

Ultraviolet Photodissociation Mass Spectrometry for Analysis of Biological Molecules

The development of new ion-activation/dissociation methods continues to be one of the most active areas of mass spectrometry owing to the broad applications of tandem mass spectrometry in the identification and structural characterization of molecules. This Review will showcase the impact of ultraviolet photodissociation (UVPD) as a frontier strategy for generating informative fragmentation patterns of ions, especially for biological molecules whose complicated structures, subtle modifications, and large sizes often impede molecular characterization. UVPD energizes ions via absorption of high-energy photons, which allows access to new dissociation pathways relative to more conventional ion-activation methods. Applications of UVPD for the analysis of peptides, proteins, lipids, and other classes of biologically relevant molecules are emphasized in this Review.

Boronic acid sensors with double recognition sites: a review

Boronic acids reversibly and covalently bind to Lewis bases and polyols, which facilitated the development of a large number of chemical sensors to recognize carbohydrates, catecholamines, ions, hydrogen peroxide, and so on. However, as the binding mechanism of boronic acids and analytes is not very clear, it is still a challenge to discover sensors with high affinity and selectivity. In this review, boronic acid sensors with two recognition sites, including diboronic acid sensors, and monoboronic acid sensors having another group or binding moiety, are summarized. Owing to double recognition sites working synergistically, the binding affinity and selectivity of sensors can be improved significantly. This review may help researchers to sort out the binding rules and develop ideal boronic acid-based sensors.

Application of molecularly imprinted polymers as artificial receptors for imaging

Medical diagnostics aims at specific localization of molecular targets as well as detection of abnormalities associated with numerous diseases. Molecularly imprinted polymers (MIPs) represent an approach of creating a synthetic material exhibiting selective recognition properties toward the desired template. The fabricated target-specific MIPs are usually well reproducible, economically efficient, and stable under critical conditions as compared to routinely used biorecognition elements such as fluorescent proteins, antibodies, enzymes, or aptamers and can even be created to those targets for which no antibodies are available. In this review, we summarize the methods of polymer fabrication. Further, we provide key for selection of the core material with imaging function depending on the imaging modality used. Finally, MIP-based imaging applications are highlighted and presented in a comprehensive form from different aspects. STATEMENT OF SIGNIFICANCE: In this review, we summarize the methods of polymer fabrication. Key applications of Molecularly imprinted polymers (MIPs) in imaging are highlighted and discussed with regard to the selection of the core material for imaging as well as commonly used imaging targets. MIPs represent an approach of creating a synthetic material exhibiting selective recognition properties toward the desired template. The fabricated target-specific MIPs are usually well reproducible, economically efficient, and stable under critical conditions as compared to routinely used biorecognition elements, e.g., antibodies, fluorescent proteins, enzymes, or aptamers, and can even be created to those targets for which no antibodies are available.

Recent advances in glycoinformatic platforms for glycomics and glycoproteomics

Protein glycosylation is the most complex and prevalent post-translation modification in terms of the number of proteins modified and the diversity generated. To understand the functional roles of glycoproteins it is important to gain an insight into the repertoire of oligosaccharides present. The comparison and relative quantitation of glycoforms combined with site-specific identification and occupancy are necessary steps in this direction. Computational platforms have continued to mature assisting researchers with the interpretation of such glycomics and glycoproteomics data sets, but frequently support dedicated workflows and users rely on the manual interpretation of data to gain insights into the glycoproteome. The growth of site-specific knowledge has also led to the implementation of machine-learning algorithms to predict glycosylation which is now being integrated into glycoproteomics pipelines. This short review describes commercial and open-access databases and software with an emphasis on those that are actively maintained and designed to support current analytical workflows.

The Need for Multi-Omics Biomarker Signatures in Precision Medicine

Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses—which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas—have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.

Super-resolution imaging of cancer-associated carbohydrates using aptamer probes

Globo H, as one of the most crucial cancer-associated carbohydrates, is exclusively overexpressed in a variety of cancers. However, the accurate localization and detailed morphology of globo H at the molecular level remain unclear. Here, we applied direct stochastic optical reconstruction microscopy (dSTORM) and relied on fluorophore-conjugated aptamers to solve the problem. The results showed that globo H organized as clusters on cell membranes with irregular shapes and different sizes from 100 to 300 nm. Significantly, globo H was found to have a higher expression level and larger clusters on various cancer cells than on non-cancer cells, which hinted that its specific distribution could be utilized for cancer diagnosis. Moreover, dual-color dSTORM imaging revealed the colocalization of globo H and other cancer-associated carbohydrates, and the clustering of globo H could be disrupted by the treatment of corresponding glycosidases, which indicated that these carbohydrates might intertwine in spatial organization and function cooperatively in cancers. Our work clarified the clustered distribution of globo H at the nanometer scale and revealed the potential interactions between cancer-associated carbohydrates, which paves the way for further understanding the relationship between the spatial structures and functions of carbohydrates in cancers.