Glycomics@ExPASy: Bridging the Gap

Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network

Glycosylation is described as a non-templated biosynthesis. Yet, the template-free premise is antithetical to the observation that different N-glycans are consistently placed at specific sites. It has been proposed that glycosite-proximal protein structures could constrain glycosylation and explain the observed microheterogeneity. Using site-specific glycosylation data, we trained a hybrid neural network to parse glycosites (recurrent neural network) and match them to feasible N-glycosylation events (graph neural network). From glycosite-flanking sequences, the algorithm predicts most human N-glycosylation events documented in the GlyConnect database and proposed structures corresponding to observed monosaccharide composition of the glycans at these sites. The algorithm also recapitulated glycosylation in Enhanced Aromatic Sequons, SARS-CoV-2 spike, and IgG3 variants, thus demonstrating the ability of the algorithm to predict both glycan structure and abundance. Thus, protein structure constrains glycosylation, and the neural network enables predictive in silico glycosylation of uncharacterized or novel protein sequences and genetic variants.

GlyComb: A novel glycoconjugate data repository that bridges glycomics and proteomics

The glycosylation of proteins and lipids is known to be closely related to the mechanisms of various diseases such as influenza, cancer, and muscular dystrophy. Therefore, it has become clear that the analysis of post-translational modifications of proteins, including glycosylation, is important to accurately understand the functions of each protein molecule and the interactions among them. In order to conduct large-scale analyses more efficiently, it is essential to promote the accumulation, sharing, and reuse of experimental and analytical data in accordance with the FAIR (Findability, Accessibility, Interoperability, and Re-usability) data principles. However, a FAIR data repository for storing and sharing glycoconjugate information, including glycopeptides and glycoproteins, in a standardized format did not exist. Therefore, we have developed GlyComb (https://glycomb.glycosmos.org) as a new standardized data repository for glycoconjugate data. Currently, GlyComb can assign a unique identifier to a set of glycosylation information associated with a specific peptide sequence or UniProt ID. By standardizing glycoconjugate data via GlyComb identifiers and coordinating with existing web resources such as GlyTouCan and GlycoPOST, a comprehensive system for data submission and data sharing among researchers can be established. Here we introduce how GlyComb is able to integrate the variety of glycoconjugate data already registered in existing data repositories to obtain a better understanding of the available glycopeptides and glycoproteins, and their glycosylation patterns. We also explain how this system can serve as a foundation for a better understanding of glycan function.

HumanLectome, an update of UniLectin for the annotation and prediction of human lectins

The UniLectin portal (https://unilectin.unige.ch/) was designed in 2019 with the goal of centralising curated and predicted data on carbohydrate-binding proteins known as lectins. UniLectin is also intended as a support for the study of lectomes (full lectin set) of organisms or tissues. The present update describes the inclusion of several new modules and details the latest (https://unilectin.unige.ch/humanLectome/), covering our knowledge of the human lectome and comprising 215 unevenly characterised lectins, particularly in terms of structural information. Each HumanLectome entry is protein-centric and compiles evidence of carbohydrate recognition domain(s), specificity, 3D-structure, tissue-based expression and related genomic data. Other recent improvements regarding interoperability and accessibility are outlined.

Glyceraldehyde-3-phosphate dehydrogenase Gh_GAPDH9 is associated with drought resistance in Gossypium hirsutum

Background

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is the central enzyme of glycolysis and plays important regulatory roles in plant growth and development and responses to adverse stress conditions. However, studies on the characteristics and functions of cotton GAPDH family genes are still lacking.

Methods

In this study, genome-wide identification of the cotton GAPDH gene family was performed, and the phylogeny, gene structures, promoter progenitors and expression profiles of upland cotton GAPDH gene family members were explored by bioinformatics analysis to highlight potential functions. The functions of GhGAPDH9 in response to drought stress were initially validated based on RNA-seq, qRT‒PCR, VIGS techniques and overexpression laying a foundation for further studies on the functions of GAPDH genes.

Results

This study is the first systematic analysis of the cotton GAPDH gene family, which contains a total of 84 GAPDH genes, among which upland cotton contains 27 members. Quantitative, phylogenetic and covariance analyses of the genes revealed that the GAPDH gene family has been conserved during the evolution of cotton. Promoter analysis revealed that most cis-acting elements were related to MeJA and ABA. Based on the identified promoter cis-acting elements and RNA-seq data, it was hypothesized that Gh_GAPDH9, Gh_GAPDH11, Gh_GAPDH19 and Gh_GAPDH21 are involved in the response of cotton to abiotic stress. The expression levels of the Gh_GAPDH9 gene in two drought-resistant and two drought-sensitive materials were analyzed by qRT‒PCR and found to be high early in the treatment period in the drought-resistant material. The silencing of Gh_GAPDH9 based on virus-induced gene silencing (VIGS) technology resulted in significant leaf wilting or whole-plant dieback in silenced plants after drought stress compared to the control. The content of-malondialdehyde (MDA) in cotton leaves was significantly increased, and the content of proline (Pro) and chlorophyll (Chl) was reduced. In addition, the leaf wilting and dryness of transgenic lines under drought stress were lower than those of wild-type Arabidopsis, indicating that Gh_GAPDH9 is a positive regulator of drought resistance. In conclusion, our results demonstrate that GAPDH genes play an important role in the response of cotton to abiotic stresses and provide preliminary validation of the function of the Gh_GAPDH9 gene under drought stress. These findings provide an important theoretical basis for further studies on the function of the Gh_GAPDH9 gene and the molecular mechanism of the drought response in cotton.

Protein glycosylation and glycoinformatics for novel biomarker discovery in neurodegenerative diseases

Glycosylation is a common post-translational modification of brain proteins including cell surface adhesion molecules, synaptic proteins, receptors and channels, as well as intracellular proteins, with implications in brain development and functions. Using advanced state-of-the-art glycomics and glycoproteomics technologies in conjunction with glycoinformatics resources, characteristic glycosylation profiles in brain tissues are increasingly reported in the literature and growing evidence shows deregulation of glycosylation in central nervous system disorders, including aging associated neurodegenerative diseases. Glycan signatures characteristic of brain tissue are also frequently described in cerebrospinal fluid due to its enrichment in brain-derived molecules. A detailed structural analysis of brain and cerebrospinal fluid glycans collected in publications in healthy and neurodegenerative conditions was undertaken and data was compiled to create a browsable dedicated set in the GlyConnect database of glycoproteins (https://glyconnect.expasy.org/brain). The shared molecular composition of cerebrospinal fluid with brain enhances the likelihood of novel glycobiomarker discovery for neurodegeneration, which may aid in unveiling disease mechanisms, therefore, providing with novel therapeutic targets as well as diagnostic and progression monitoring tools.

Enhanced Detection of Charged N-Glycans in the Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometric Imaging

N-linked glycosylation represents a structurally diverse, complex, co- and posttranslational protein modification that bridges metabolism and cellular signaling. Consequently, aberrant protein glycosylation is a hallmark of most pathological scenarios. Due to their complex nature and non-template-driven synthesis, the analysis of glycans is faced with several challenges, underlining the need for new and improved analytical technologies. Spatial profiling of N-glycans through direct imaging on tissue sections reveals the regio-specific and/or disease pathology correlating tissue N-glycans that serve as a disease glycoprint for diagnosis. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is a soft hybrid ionization technique that has been used for diverse mass spectrometry imaging (MSI) applications. Here, we report the first spatial analysis of the brain N-linked glycans by IR-MALDESI MSI, leading to a significant increase in the detection of the brain N-sialoglycans. A formalin-fixed paraffin-embedded mouse brain tissue was analyzed in negative ionization mode after tissue washing, antigen retrieval, and pneumatic application of PNGase F for enzymatic digestion of N-linked glycans. We report a comparative analysis of section thickness on the N-glycan detection using IR-MALDESI. One hundred thirty-six unique N-linked glycans were confidently identified in the brain tissue (with an additional 132 unique N-glycans, not reported in GlyConnect), where more than 50% contained sialic acid residues, which is approximately 3-fold higher than the previous reports. This work demonstrates the first application of IR-MALDESI in N-linked glycan imaging of the brain tissue, leading to a 2.5-fold increase in the in situ total brain N-glycan detection compared to the current gold standard of positive-mode matrix-assisted laser desorption/ionization mass spectrometry imaging. This is also the first report of the application of the MSI toward the identification of sulfoglycans in the rodent brain. Overall, IR-MALDESI-MSI presents a sensitive glycan detection platform to identify tissue-specific and/or disease-specific glycosignature in the brain while preserving the sialoglycans without any chemical derivatization.

Application of bioanalytical and computational methods in decoding the roles of glycans in host-pathogen interactions

Host-pathogen interactions (HPIs) are complex processes that require tight regulation. A common regulatory mechanism of HPIs is through glycans of either host cells or pathogens. Due to their diverse sequences, complex structures, and conformations, studies of glycans require highly sensitive and powerful tools. Recent improvements in technology have enabled the application of many bioanalytical techniques and modeling methods to investigate glycans and their mechanisms in HPIs. This mini-review highlights how these advances have been used to understand the role glycans play in HPIs in the past 2 years.

Worldwide Glycoscience Informatics Infrastructure: The GlySpace Alliance

The GlySpace Alliance was formed in 2018 among the principal investigators of three major glycoscience portals: Glyco@Expasy, GlyCosmos, and GlyGen, representing Europe, Asia, and the United States, respectively. While each of these portals has its unique user interface, the aim is to provide the same basic data set of glycan-related omics data. These portals will be introduced with the aim to enable users to find their target information in the most efficient manner, in particular, in terms of the chemical structures of glycans and their functions.

Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery

Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

Potent SARS-CoV-2 neutralizing antibodies with therapeutic effects in two animal models

The use of therapeutic neutralizing antibodies against SARS-CoV-2 infection has been highly effective. However, there remain few practical antibodies against viruses that are acquiring mutations. In this study, we created 494 monoclonal antibodies from patients with COVID-19-convalescent, and identified antibodies that exhibited the comparable neutralizing ability to clinically used antibodies in the neutralization assay using pseudovirus and authentic virus including variants of concerns. These antibodies have different profiles against various mutations, which were confirmed by cell-based assay and cryo-electron microscopy. To prevent antibody-dependent enhancement, N297A modification was introduced. Our antibodies showed a reduction of lung viral RNAs by therapeutic administration in a hamster model. In addition, an antibody cocktail consisting of three antibodies was also administered therapeutically to a macaque model, which resulted in reduced viral titers of swabs and lungs and reduced lung tissue damage scores. These results showed that our antibodies have sufficient antiviral activity as therapeutic candidates.

Gb_ANR-47 Enhances the Resistance of Gossypium barbadense to Fusarium oxysporum f. sp. vasinfectum (FOV) by Regulating the Content of Proanthocyanidins

Anthocyanidin reductase (ANR) is an important regulator of flavonoid metabolism, and proanthocyanidins, the secondary metabolites of flavonoids, play an important role in the response of plants to pathogenic stress. Therefore, in this study, the expression analysis of the ANR gene family of Gossypium barbadense after inoculation with Fusarium oxysporum f. sp. vasinfectum (FOV) was performed at different time points. It was found that Gb_ANR-47 showed significant differences in the disease-resistant cultivar 06-146 and the susceptible cultivar Xinhai 14, as well as in the highest root expression. It was found that the expression of Gb_ANR-47 in the resistant cultivar was significantly higher than that in the susceptible cultivar by MeJA and SA, and different amounts of methyl jasmonate (MeJA) and salicylic acid (SA) response elements were found in the promoter region of Gb_ANR-47. After silencing GbANR-47 in 06-146 material by VIGS technology, its resistance to FOV decreased significantly. The disease severity index (DSI) was significantly increased, and the anthocyanin content was significantly decreased in silenced plants, compared to controls. Our findings suggest that GbANR-47 is a positive regulator of FOV resistance in Gossypium barbadense. The research results provide an important theoretical basis for in-depth analysis of the molecular mechanism of GbANR-47 and improving the anti-FOV of Gossypium barbadense.

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.

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

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

Mass Spectrometry Imaging of N-Linked Glycans in a Formalin-Fixed Paraffin-Embedded Human Prostate by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization

N-Linked glycans are structurally diverse polysaccharides that represent significant biological relevance due to their involvement in disease progression and cancer. Due to their complex nature, N-linked glycans pose many analytical challenges requiring the continued development of analytical technologies. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is a hybrid ionization technique commonly used for mass spectrometry imaging (MSI) applications. Previous work demonstrated IR-MALDESI to significantly preserve sialic acid containing N-linked glycans that otherwise require chemical derivatization prior to detection. Here, we demonstrate the first analysis of N-linked glycans in situ by IR-MALDESI MSI. A formalin-fixed paraffin-embedded human prostate tissue was analyzed in negative ionization mode after tissue washing, antigen retrieval, and pneumatic application of PNGase F for enzymatic digestion of N-linked glycans. Fifty-three N-linked glycans were confidently identified in the prostate sample where more than 60% contained sialic acid residues. This work demonstrates the first steps in N-linked glycan imaging of biological tissues by IR-MALDESI MSI. Raw data files are available in MassIVE (identifier: MSV000088414).

OUP accepted manuscript

Glycans expand the structural complexity of proteins by several orders of magnitude, resulting in a tremendous analytical challenge when including them in biomedical research. Recent glycobiological research is painting a picture in which glycans represent a crucial structural and functional component of the majority of proteins, with alternative glycosylation of proteins and lipids being an important regulatory mechanism in many biological and pathological processes. Since interindividual differences in glycosylation are extensive, large studies are needed to map the structures and to understand the role of glycosylation in human (patho)physiology. Driven by these challenges, methods have emerged, which can tackle the complexity of glycosylation in thousands of samples, also known as high-throughput (HT) glycomics. For facile dissemination and implementation of HT glycomics technology, the sample preparation, analysis, as well as data mining, need to be stable over a long period of time (months/years), amenable to automation, and available to non-specialized laboratories. Current HT glycomics methods mainly focus on protein N-glycosylation and allow to extensively characterize this subset of the human glycome in large numbers of various biological samples. The ultimate goal in HT glycomics is to gain better knowledge and understanding of the complete human glycome using methods that are easy to adapt and implement in (basic) biomedical research. Aiming to promote wider use and development of HT glycomics, here, we present currently available, emerging, and prospective methods and some of their applications, revealing a largely unexplored molecular layer of the complexity of life.

Construction of InstantPC derivatized glycan GU database: A foundation work for high-throughput and high-sensitivity glycomic analysis

Glycosylation is well-recognized as a critical quality attribute of biotherapeutics being routinely monitored to ensure desired product quality, safety, and efficacy. Additionally, as one of the most prominent and complex post-translational modifications, glycosylation plays a key role in disease manifestation. Changes in glycosylation may serve as a specific and sensitive biomarker for disease diagnostics and prognostics. However, the conventional 2-aminobenzamide based N-glycosylation analysis procedure is time-consuming and insensitive, with poor reproducibility. We have evaluated an innovative streamlined 96-well-plate-based platform utilizing InstantPC label for high-throughput, high-sensitivity glycan profiling, which is user-friendly, robust, and ready for automation. However, the limited availability of InstantPC labelled glycan standards has significantly hampered the applicability and transferability of this platform for expedited glycan structural profiling. To address this challenge, we have constructed a detailed InstantPC labelled glycan glucose unit database through analysis of human serum and a variety of other glycoproteins from various sources. Following preliminary hydrophilic interaction liquid chromatography with fluorescence detection separation and analysis, glycoproteins with complex glycan profiles were subjected to further fractionation by weak anion exchange hydrophilic interaction liquid chromatography and exoglycosidase sequential digestion for cross-validation of the glycan assignment. Hydrophilic interaction ultra-performance liquid chromatography coupled with electrospray ionization mass spectrometry was subsequently utilised for glycan fragmentation and accurate glycan mass confirmation. The constructed InstantPC glycan GU database is accurate and robust. It is believed that this database will enhance the application of the developed platform for high-throughput, high-sensitivity glycan profiling, and eventually advance glycan-based biopharmaceutical production and disease biomarker discovery.

#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

ACM REFERENCE FORMAT

Abigail Dommer 1† , Lorenzo Casalino 1† , Fiona Kearns 1† , Mia Rosenfeld 1 , Nicholas Wauer 1 , Surl-Hee Ahn 1 , John Russo, 2 Sofia Oliveira 3 , Clare Morris 1 , AnthonyBogetti 4 , AndaTrifan 5,6 , Alexander Brace 5,7 , TerraSztain 1,8 , Austin Clyde 5,7 , Heng Ma 5 , Chakra Chennubhotla 4 , Hyungro Lee 9 , Matteo Turilli 9 , Syma Khalid 10 , Teresa Tamayo-Mendoza 11 , Matthew Welborn 11 , Anders Christensen 11 , Daniel G. A. Smith 11 , Zhuoran Qiao 12 , Sai Krishna Sirumalla 11 , Michael O'Connor 11 , Frederick Manby 11 , Anima Anandkumar 12,13 , David Hardy 6 , James Phillips 6 , Abraham Stern 13 , Josh Romero 13 , David Clark 13 , Mitchell Dorrell 14 , Tom Maiden 14 , Lei Huang 15 , John McCalpin 15 , Christo- pherWoods 3 , Alan Gray 13 , MattWilliams 3 , Bryan Barker 16 , HarindaRajapaksha 16 , Richard Pitts 16 , Tom Gibbs 13 , John Stone 6 , Daniel Zuckerman 2 *, Adrian Mulholland 3 *, Thomas MillerIII 11,12 *, ShantenuJha 9 *, Arvind Ramanathan 5 *, Lillian Chong 4 *, Rommie Amaro 1 *. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing '21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis . ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI.

Advances in mass spectrometry-based glycoproteomics: An update covering the period 2017-2021

Protein glycosylation is one of the most common posttranslational modifications, and plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, host-pathogen interaction, and protein stability. Glycoproteomics is a proteomics subfield dedicated to identifying and characterizing the glycans and glycoproteins in a given cell or tissue. Aberrant glycosylation has been associated with various diseases such as Alzheimer's disease, viral infections, inflammation, immune deficiencies, congenital disorders, and cancers. However, glycoproteomic analysis remains challenging because of the low abundance, site-specific heterogeneity, and poor ionization efficiency of glycopeptides during LC-MS analyses. Therefore, the development of sensitive and accurate approaches to efficiently characterize protein glycosylation is crucial. Methods such as metabolic labeling, enrichment, and derivatization of glycopeptides, coupled with different mass spectrometry techniques and bioinformatics tools, have been developed to achieve sophisticated levels of quantitative and qualitative analyses of glycoproteins. This review attempts to update the recent developments in the field of glycoproteomics reported between 2017 and 2021.

Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome

Bacteria use carbohydrate-binding proteins (CBPs), such as lectins and carbohydrate-binding modules (CBMs), to anchor to specific sugars on host surfaces. CBPs in the gut microbiome are well studied, but their roles in the vagina microbiome and involvement in sexually transmitted infections, cervical cancer and preterm birth are largely unknown. We established a classification system for lectins and designed Hidden Markov Model (HMM) profiles for data mining of bacterial genomes, resulting in identification of >100,000 predicted bacterial lectins available at unilectin.eu/bacteria. Genome screening of 90 isolates from 21 vaginal bacterial species shows that those associated with infection and inflammation produce a larger CBPs repertoire, thus enabling them to potentially bind a wider array of glycans in the vagina. Both the number of predicted bacterial CBPs and their specificities correlated with pathogenicity. This study provides new insights into potential mechanisms of colonisation by commensals and potential pathogens of the reproductive tract that underpin health and disease states.

Genome-wide identification of the DUF668 gene family in cotton and expression profiling analysis of GhDUF668 in Gossypium hirsutum under adverse stress

Background

Domain of unknown function 668 (DUF668) may play a crucial role in the plant growth and developmental response to adverse stress. However, our knowledge of the function of the DUF668 gene family is limited.

Results

Our study was conducted based on the DUF668 gene family identified from cotton genome sequencing. Phylogenetic analysis showed that the DUF668 family genes can be classified into four subgroups in cotton. We identified 32 DUF668 genes, which are distributed on 17 chromosomes and most of them located in the nucleus of Gossypium hirsutum. Gene structure and motif analyses revealed that the members of the DUF668 gene family can be clustered in G. hirsutum into two broad groups, which are relatively evolutionarily conserved. Transcriptome data analysis showed that the GhDUF668 genes are differentially expressed in different tissues under various stresses (cold, heat, drought, salt, and Verticillium dahliae), and expression is generally increased in roots and stems. Promoter and expression analyses indicated that Gh_DUF668–05, Gh_DUF668–08, Gh_DUF668–11, Gh_DUF668–23 and Gh_DUF668–28 in G. hirsutum might have evolved resistance to adverse stress. Additionally, qRT-PCR revealed that these 5 genes in four cotton lines, KK1543 (drought resistant), Xinluzao 26 (drought sensitive), Zhongzhimian 2 (disease resistant) and Simian 3 (susceptible), under drought and Verticillium wilt stress were all significantly induced. Roots had the highest expression of these 5 genes before and after the treatment. Among them, the expression levels of Gh_DUF668–08 and Gh_DUF668–23 increased sharply at 6 h and reached a maximum at 12 h under biotic and abiotic stress, which showed that they might be involved in the process of adverse stress resistance in cotton.

Conclusion

The significant changes in GhDUF668 expression in the roots after adverse stress indicate that GhDUF668 is likely to increase plant resistance to stress. This study provides an important theoretical basis for further research on the function of the DUF668 gene family and the molecular mechanism of adverse stress resistance in cotton.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07716-w.

Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication

Characteristically, cells must sense and respond to environmental cues. Despite the importance of cell-cell communication, our understanding remains limited and often lacks glycans. Glycans decorate proteins and cell membranes at the cell-environment interface, and modulate intercellular communication, from development to pathogenesis. Providing further challenges, glycan biosynthesis and cellular behavior are co-regulating systems. Here, we discuss how glycosylation contributes to extracellular responses and signaling. We further organize approaches for disentangling the roles of glycans in multicellular interactions using newly available datasets and tools, including glycan biosynthesis models, omics datasets, and systems-level analyses. Thus, emerging tools in big data analytics and systems biology are facilitating novel insights on glycans and their relationship with multicellular behavior.

Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy

Glycosylation plays a crucial role in various diseases and their etiology. This has led to a clear understanding on the functions of carbohydrates in cell communication, which eventually will result in novel therapeutic approaches for treatment of various disease. Glycomics has now become one among the top ten technologies that will change the future. The direct implication of glycosylation as a hallmark of cancer and for cancer therapy is well established. As in proteomics, where bioinformatics tools have led to revolutionary achievements, bioinformatics resources for glycosylation have improved its practical implication. Bioinformatics tools, algorithms and databases are a mandatory requirement to manage and successfully analyze large amount of glycobiological data generated from glycosylation studies. This review consolidates all the available tools and their applications in glycosylation research. The achievements made through the use of bioinformatics into glycosylation studies are also presented. The importance of glycosylation in cancer diagnosis and therapy is discussed and the gap in the application of widely available glyco-informatic tools for cancer research is highlighted. This review is expected to bring an awakening amongst glyco-informaticians as well as cancer biologists to bridge this gap, to exploit the available glyco-informatic tools for cancer.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Examining and Fine-tuning the Selection of Glycan Compositions with GlyConnect Compozitor

A key point in achieving accurate intact glycopeptide identification is the definition of the glycan composition file that is used to match experimental with theoretical masses by a glycoproteomics search engine. At present, these files are mainly built from searching the literature and/or querying data sources focused on posttranslational modifications. Most glycoproteomics search engines include a default composition file that is readily used when processing MS data. We introduce here a glycan composition visualizing and comparative tool associated with the GlyConnect database and called GlyConnect Compozitor. It offers a web interface through which the database can be queried to bring out contextual information relative to a set of glycan compositions. The tool takes advantage of compositions being related to one another through shared monosaccharide counts and outputs interactive graphs summarizing information searched in the database. These results provide a guide for selecting or deselecting compositions in a file in order to reflect the context of a study as closely as possible. They also confirm the consistency of a set of compositions based on the content of the GlyConnect database. As part of the tool collection of the Glycomics@ExPASy initiative, Compozitor is hosted at https://glyconnect.expasy.org/compozitor/ where it can be run as a web application. It is also directly accessible from the GlyConnect database.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.

How and why plants and human N-glycans are different: Insight from molecular dynamics into the "glycoblocks" architecture of complex carbohydrates

The N-glycosylation is one of the most abundant and diverse post-translational modifications of proteins, implicated in protein folding and structural stability, and mediating interactions with receptors and with the environment. All N-glycans share a common core from which linear or branched arms stem from, with functionalization specific to different species and to the cells’ health and disease state. This diversity generates a rich collection of structures, all diversely able to trigger molecular cascades and to activate pathways, which also include adverse immunogenic responses. These events are inherently linked to the N-glycans’ 3D architecture and dynamics, which remain for the large part unresolved and undetected because of their intrinsic structural disorder. In this work we use molecular dynamics (MD) simulations to provide insight into N-glycans’ 3D structure by analysing the effects of a set of very specific modifications found in plants and invertebrate N-glycans, which are immunogenic in humans. We also compare these structural motifs and combine them with mammalian N-glycan motifs to devise strategies for the control of the N-glycan 3D structure through sequence. Our results suggest that the N-glycans’ architecture can be described in terms of the local spatial environment of groups of monosaccharides. We define these “glycoblocks” as self-contained 3D units, uniquely identified by the nature of the residues they comprise, their linkages and structural/dynamic features. This alternative description of glycans’ 3D architecture can potentially lead to an easier prediction of sequence-to-structure relationships in complex carbohydrates, with important implications in glycoengineering design.

UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands

Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein–Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glycoscience. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin.eu/unilectin3D.

Updates to the Symbol Nomenclature for Glycans guidelines

The Symbol Nomenclature for Glycans (SNFG) is a community-curated standard for the depiction of monosaccharides and complex glycans using various colored-coded, geometric shapes, along with defined text additions. It is hosted by the National Center for Biotechnology Information (NCBI) at the NCBI-Glycans Page (www.ncbi.nlm.nih.gov/glycans/snfg.html). Several changes have been made to the SNFG page in the past year to update the rules for depicting glycans using the SNFG, to include more examples of use, particularly for non-mammalian organisms, and to provide guidelines for the depiction of ambiguous glycan structures. This Glycoforum article summarizes these recent changes.

Reference glycan structure libraries of primary human cardiomyocytes and pluripotent stem cell-derived cardiomyocytes reveal cell-type and culture stage-specific glycan phenotypes

Cell surface glycoproteins play critical roles in maintaining cardiac structure and function in health and disease and the glycan-moiety attached to the protein is critical for proper protein folding, stability and signaling [1]. However, despite mounting evidence that glycan structures are key modulators of heart function and must be considered when developing cardiac biomarkers, we currently do not have a comprehensive view of the glycans present in the normal human heart. In the current study, we used porous graphitized carbon liquid chromatography interfaced with mass spectrometry (PGC-LC-MS) to generate glycan structure libraries for primary human heart tissue homogenate, cardiomyocytes (CM) enriched from human heart tissue, and human induced pluripotent stem cell derived CM (hiPSC-CM). Altogether, we established the first reference structure libraries of the cardiac glycome containing 265 N- and O-glycans. Comparing the N-glycome of CM enriched from primary heart tissue to that of heart tissue homogenate, the same pool of N-glycan structures was detected in each sample type but the relative signal of 21 structures significantly differed between samples, with the high mannose class increased in enriched CM. Moreover, by comparing primary CM to hiPSC-CM collected during 20-100 days of differentiation, dynamic changes in the glycan profile throughout in vitro differentiation were observed and differences between primary and hiPSC-CM were revealed. Namely, >30% of the N-glycome significantly changed across these time-points of differentiation and only 23% of the N-glycan structures were shared between hiPSC-CM and primary CM. These observations are an important complement to current genomic, transcriptomic, and proteomic profiling and reveal new considerations for the use and interpretation of hiPSC-CM models for studies of human development, disease, and drug testing. Finally, these data are expected to support future regenerative medicine efforts by informing targets for evaluating the immunogenic potential of hiPSC-CM and harnessing differences between immature, proliferative hiPSC-CM and adult primary CM.

Novel methods in glycomics: a 2019 update

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

Mass spectrometry-based qualitative and quantitative N-glycomics: An update of 2017-2018

N-glycosylation is one of the most frequently occurring protein post-translational modifications (PTMs) with broad cellular, physiological and pathological relevance. Mass spectrometry-based N-glycomics has become the state-of-the-art instrumental analytical pipeline for sensitive, high-throughput and comprehensive characterization of N-glycans and N-glycomes. Improvement and new development of methods in N-glycan release, enrichment, derivatization, isotopic labeling, separation, ionization, MS, tandem MS and informatics accompany side-by-side wider and deeper application. This review provides a comprehensive update of mass spectrometry-based qualitative and quantitative N-glycomics in the years of 2017-2018.

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

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

A Bioinformatics View of Glycan⁻Virus Interactions

Evidence of the mediation of glycan molecules in the interaction between viruses and their hosts is accumulating and is now partially reflected in several online databases. Bioinformatics provides convenient and efficient means of searching, visualizing, comparing, and sometimes predicting, interactions in numerous and diverse molecular biology applications related to the -omics fields. As viromics is gaining momentum, bioinformatics support is increasingly needed. We propose a survey of the current resources for searching, visualizing, comparing, and possibly predicting host–virus interactions that integrate the presence and role of glycans. To the best of our knowledge, we have mapped the specialized and general-purpose databases with the appropriate focus. With an illustration of their potential usage, we also discuss the strong and weak points of the current bioinformatics landscape in the context of understanding viral infection and the immune response to it.

Identification and expression analysis of the GDSL esterase/lipase family genes, and the characterization of SaGLIP8 in Sedum alfredii Hance under cadmium stress

Background

The herb Sedum alfredii (S. alfredii) Hance is a hyperaccumulator of heavy metals (cadmium (Cd), zinc (Zn) and lead (Pb)); therefore, it could be a candidate plant for efficient phytoremediation. The GDSL esterase/lipase protein (GELP) family plays important roles in plant defense and growth. Although the GELP family members in a variety of plants have been cloned and analyzed, there are limited studies on the family's responses to heavy metal-stress conditions.

Methods

Multiple sequence alignments and phylogenetic analyses were performed according to the criteria described. A WGCNA was used to construct co-expression regulatory networks. The roots of S. alfredii seedlings were treated with 100 µM CdCl₂ for qRT-PCR to analyze expression levels in different tissues. SaGLIP8 was transformed into the Cd sensitive mutant strain yeast Δycf1 to investigate its role in resistance and accumulation to Cd.

Results

We analyzed GELP family members from genomic data of S. alfredii. A phylogenetic tree divided the 80 identified family members into three clades. The promoters of the 80 genes contained certain elements related to abiotic stress, such as TC-rich repeats (defense and stress responsiveness), heat shock elements (heat stress) and MYB-binding sites (drought-inducibility). In addition, 66 members had tissue-specific expression patterns and significant responses to Cd stress. In total, 13 hub genes were obtained, based on an existing S. alfredii transcriptome database, that control 459 edge genes, which were classified into five classes of functions in a co-expression subnetwork: cell wall and defense function, lipid and esterase, stress and tolerance, transport and transcription factor activity. Among the hub genes, Sa13F.102 (SaGLIP8), with a high expression level in all tissues, could increase Cd tolerance and accumulation in yeast when overexpressed.

Conclusion

Based on genomic data of S. alfredii, we conducted phylogenetic analyses, as well as conserved domain, motif and expression profiling of the GELP family under Cd-stress conditions. SaGLIP8 could increase Cd tolerance and accumulation in yeast. These results indicated the roles of GELPs in plant responses to heavy metal exposure and provides a theoretical basis for further studies of the SaGELP family's functions.

SugarSketcher: Quick and Intuitive Online Glycan Drawing

SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The "quick mode" allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The "normal mode" integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.