Bioinformatics for glycomics: status, methods, requirements and perspectives

The term 'glycomics' describes the scientific attempt to identify and study all the glycan molecules - the glycome - synthesised by an organism. The aim is to create a cell-by-cell catalogue of glycosyltransferase expression and detected glycan structures. The current status of databases and bioinformatics tools, which are still in their infancy, is reviewed. The structures of glycans as secondary gene products cannot be easily predicted from the DNA sequence. Glycan sequences cannot be described by a simple linear one-letter code as each pair of monosaccharides can be linked in several ways and branched structures can be formed. Few of the bioinformatics algorithms developed for genomics/proteomics can be directly adapted for glycomics. The development of algorithms, which allow a rapid, automatic interpretation of mass spectra to identify glycan structures is currently the most active field of research. The lack of generally accepted ways to normalise glycan structures and exchange glycan formats hampers an efficient cross-linking and the automatic exchange of distributed data. The upcoming glycomics should accept that unrestricted dissemination of scientific data accelerates scientific findings and initiates a number of new initiatives to explore the data.     

Solid-phase chemical tools for glycobiology

Techniques involving solid supports have played crucial roles in the development of genomics, proteomics, and in molecular biology in general. Similarly, methods for immobilization or attachment to surfaces and resins have become ubiquitous in sequencing, synthesis, analysis, and screening of oligonucleotides, peptides, and proteins. However, solid-phase tools have been employed to a much lesser extent in glycobiology and glycomics. This review provides a comprehensive overview of solid-phase chemical tools for glycobiology including methodologies and applications. We provide a broad perspective of different approaches, including some well-established ones, such as immobilization in microtiter plates and to cross-linked polymers. Emerging areas such as glycan microarrays and glycan sequencing, quantum dots, and gold nanoparticles for nanobioscience applications are also discussed. The applications reviewed here include enzymology, immunology, elucidation of biosynthesis, and systems biology, as well as first steps toward solid-supported sequencing. From these methods and applications emerge a general vision for the use of solid-phase chemical tools in glycobiology.     

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

In comparison with genomics and proteomics, the advancement of glycomics has faced unique challenges in the pursuit of developing analytical and biochemical tools and biological readouts to investigate glycan structure-function relationships. Glycans are more diverse in terms of chemical structure and information density than are DNA and proteins. This diversity arises from glycans' complex nontemplate-based biosynthesis, which involves several enzymes and isoforms of these enzymes. Consequently, glycans are expressed as an 'ensemble' of structures that mediate function. Moreover, unlike protein-protein interactions, which can be generally viewed as 'digital' in regulating function, glycan-protein interactions impinge on biological functions in a more 'analog' fashion that can in turn 'fine-tune' a biological response. This fine-tuning by glycans is achieved through the graded affinity, avidity and multivalency of their interactions. Given the importance of glycomics, this review focuses on areas of technologies and the importance of developing a bioinformatics platform to integrate the diverse datasets generated using the different technologies to allow a systems approach to glycan structure-function relationships.     

GLYCOSCIENCES.de: an Internet portal to support glycomics and glycobiology research

The development of glycan-related databases and bioinformatics applications is considerably lagging behind compared with the wealth of available data and software tools in genomics and proteomics. Because the encoding of glycan structures is more complex, most of the bioinformatics approaches cannot be applied to glycan structures. No standard procedures exist where glycan structures found in various species, organs, tissues or cells can be routinely deposited. In this article the concepts of the GLYCOSCIENCES.de portal are described. It is demonstrated how an efficient structure-based cross-linking of various glycan-related data originating from different resources can be accomplished using a single user interface. The structure oriented retrieval options-exact structure, substructure, motif, composition and sugar components-are discussed. The types of available data-references, composition, spatial structures, nuclear magnetic resonance (NMR) shifts (experimental and estimated), theoretically calculated fragments and Protein Database (PDB) entries-are exemplified for Man(3.) The free availability and unrestricted use of glycan-related data is an absolute prerequisite to efficiently share distributed resources. Additionally, there is an urgent need to agree to a generally accepted exchange format as well as to a common software interface. An open access repository for glyco-related experimental data will secure that the loss of primary data will be considerably reduced.     

糖生物信息学数据库

糖生物信息学是在糖生物学和糖组学发展的基础上,结合计算机技术,对生命活动过程中,参与糖链及与其相互作用的蛋白质等分子研究所产生的数据进行获取、储存、解析、模拟以及预测等内容的综合学科.糖生物信息学数据库是糖生物信息学发展到一定阶段,对糖组学等研究中产生的数据进行专门储藏与查询的应用工具.目前国际互联网中存在近百个糖生物信息学相关数据库,涉及内容包括糖链结构、参与糖链合成的基因或者蛋白质、糖结合蛋白、代谢通路、糖链或相互作用蛋白质等分子三维结构,或糖组学实验结果等领域.本文将归纳总结糖生物信息学数据库,为现有研究提供帮助.     

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.     

EUROCarbDB: An open-access platform for glycoinformatics

The EUROCarbDB project is a design study for a technical framework, which provides sophisticated, freely accessible, open-source informatics tools and databases to support glycobiology and glycomic research. EUROCarbDB is a relational database containing glycan structures, their biological context and, when available, primary and interpreted analytical data from high-performance liquid chromatography, mass spectrometry and nuclear magnetic resonance experiments. Database content can be accessed via a web-based user interface. The database is complemented by a suite of glycoinformatics tools, specifically designed to assist the elucidation and submission of glycan structure and experimental data when used in conjunction with contemporary carbohydrate research workflows. All software tools and source code are licensed under the terms of the Lesser General Public License, and publicly contributed structures and data are freely accessible. The public test version of the web interface to the EUROCarbDB can be found at http://www.ebi.ac.uk/eurocarb.     

Glycans as cancer biomarkers

Background

Non-invasive biomarkers, such as those from serum, are ideal for disease prognosis, staging and monitoring. In the past decade, our understanding of the importance of glycosylation changes with disease has evolved.

Scope of review

We describe potential biomarkers derived from serum glycoproteins for liver, pancreatic, prostate, ovarian, breast, lung and stomach cancers. Methods for glycan analysis have progressed and newly developed high-throughput platform technologies have enabled the analysis of large cohorts of samples in an efficient manner. We also describe this evolution and trends to follow in the future.

Major conclusions

Many convincing examples of aberrant glycans associated with cancer have come about from glycosylation analyses. Most studies have been carried out to identify changes in serum glycan profiles or through the isolation and identification of glycoproteins that contain these irregular glycan structures. In a majority of cancers the fucosylation and sialylation expression are found to be significantly modified. Therefore, these aberrations in glycan structures can be utilized as targets to improve existing cancer biomarkers.

General significance

The ability to distinguish differences in the glycosylation of proteins between cancer and control patients emphasizes glycobiology as a promising field for potential biomarker identification. Furthermore, the high-throughput and reproducible nature of the chromatography platform have highlighted extensive applications in biomarker discovery and allowed integration of glycomics with other -omics fields, such as proteomics and genomics, making systems glycobiology a reality. This article is part of a Special Issue entitled Glycoproteomics.     

GlycoWorkbench: a tool for the computer-assisted annotation of mass spectra of glycans

Mass spectrometry is the main analytical technique currently used to address the challenges of glycomics as it offers unrivalled levels of sensitivity and the ability to handle complex mixtures of different glycan variations. Determination of glycan structures from analysis of MS data is a major bottleneck in high-throughput glycomics projects, and robust solutions to this problem are of critical importance. However, all the approaches currently available have inherent restrictions to the type of glycans they can identify, and none of them have proved to be a definitive tool for glycomics. GlycoWorkbench is a software tool developed by the EUROCarbDB initiative to assist the manual interpretation of MS data. The main task of GlycoWorkbench is to evaluate a set of structures proposed by the user by matching the corresponding theoretical list of fragment masses against the list of peaks derived from the spectrum. The tool provides an easy to use graphical interface, a comprehensive and increasing set of structural constituents, an exhaustive collection of fragmentation types, and a broad list of annotation options. The aim of GlycoWorkbench is to offer complete support for the routine interpretation of MS data. The software is available for download from: http://www.eurocarbdb.org/applications/ms-tools.     

UniCarb-DB: a database resource for glycomic discovery

Glycosylation is one of the most important post-translational modifications of proteins, known to be involved in pathogen recognition, innate immune response and protection of epithelial membranes. However, when compared to the tools and databases available for the processing of high-throughput proteomic data, the glycomic domain is severely lacking. While tools to assist the analysis of mass spectrometry (MS) and HPLC are continuously improving, there are few resources available to support liquid chromatography (LC)-MS/MS techniques for glycan structure profiling. Here, we present a platform for presenting oligosaccharide structures and fragment data characterized by LC-MS/MS strategies. The database is annotated with high-quality datasets and is designed to extend and reinforce those standards and ontologies developed by existing glycomics databases. AVAILABILITY: http://www.unicarb-db.org     

UniCarbKB: putting the pieces together for glycomics research

Despite the success of several international initiatives the glycosciences still lack a managed infrastructure that contributes to the advancement of research through the provision of comprehensive structural and experimental glycan data collections. UniCarbKB is an initiative that aims to promote the creation of an online information storage and search platform for glycomics and glycobiology research. The knowledgebase will offer a freely accessible and information-rich resource supported by querying interfaces, annotation technologies and the adoption of common standards to integrate structural, experimental and functional data. The UniCarbKB framework endeavors to support the growth of glycobioinformatics and the dissemination of knowledge through the provision of an open and unified portal to encourage the sharing of data. In order to achieve this, the framework is committed to the development of tools and procedures that support data annotation, and expanding interoperability through cross-referencing of existing databases. Database URL: http://www.unicarbkb.org.     

KEGG as a glycome informatics resource

Bioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is a comprehensive resource for genome-scale bioinformatics analysis of glycan data. Although the accumulation of experimental data may be useful as a reference of biological and biochemical information on carbohydrates, this is insufficient for bioinformatics analysis. Thus, we have developed a glycome informatics resource (http://www.genome.jp/kegg/glycan/) in KEGG (Kyoto Encyclopedia of Genes and Genomes), an integrated knowledge base of protein networks, genomic information, and chemical information. This review describes three noteworthy features: (1) GLYCAN, a database of carbohydrate structures; (2) glycan-related pathways; and (3) Composite Structure Map (CSM), a map illustrating all possible variations of carbohydrate structures within organisms. GLYCAN includes two useful tools: an intuitive drawing tool called KegDraw, and an efficient glycan search and alignment tool called KEGG Carbohydrate Matcher (KCaM). KEGG's glycan biosynthesis and metabolism pathways, integrating carbohydrate structures, proteins, and reactions, are also a pivotal resource. CSM is constructed as a bridge between carbohydrate functions and structures. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner. In all the KEGG resources, various objects including KEGG pathways, chemical compounds, as well as carbohydrate structures are commonly represented as graphs, which are widely studied and utilized in the computer science field.     

Deciphering the glycocode: the complexity and analytical challenge of glycomics

Carbohydrates coat most types of cell in nature and are intimately involved in various biological events, including cell differentiation, homing to specific tissues, cell adhesion, cell recognition, microbial pathogenesis and immunological recognition. Carbohydrate structures are complex to analyze owing to their branched nature, the diversity of secondary modifications of monomers, their indirect relationship to the genome and the range of molecular contexts in which the modifications are found. Thus, whereas the fields of genomics and proteomics have become accessible to most scientists, technologies to assess glycan structures rapidly (i.e. glycomics) are still in the developmental stages. This review focuses on recent developments in glycomic technologies, including new high-throughput techniques for glycan purification and annotation that are advancing mass-spectrometry-based glycomics, and the latest work on microarray methodologies to decipher the glycome.     

糖类的生物信息学资源

生物信息学在推动遗传学和蛋白质科学的研究领域中,已发挥了举足轻重的作用.相比较而 言,糖科学产生的信息还比较有限,随着人们对糖类分子的关注,糖生物学的发展也出现新 的契机,其信息正在飞速地增长.对已经获得的糖类相关知识进行系统整合就显得越来越有 必要,许多研究型数据库和免费工具已应运而生,并且数目在不断扩大,正成为科学工作者 非常便利的工具.但到目前为止,许多数据库或者网络预测工具在文献中很少提及或难以找 到,给研究者带来了不少的麻烦.部分原因是数据库资源本身数据不断在更新,人机界面也 变得越方便和人性化,另外就是人们对于这些新型的研究工具了解较少.这篇综述介绍了 目前网络上最常用的糖类生物信息学资源,包括糖的一级结构,分析测试数据、构象,酶, 凝集素,糖蛋白等方面的各种数据库.     

Interpretation support for multistage MS: a mathematical method for theoretical generation of glycan fragments and calculation of their masses

Glycan fragmentation forms an integral part of the current research in glycomics. Creation of a database of glycan fragments and their masses for known glycan structures is an important step in the interpretation of mass spectra for the identification of unknown glycan structures. This paper introduces the concept of positional nomenclature, gives a systematic representation of glycan structure of any size, and hence develops a method for theoretically generating all possible first and second generation fragments resulting from glycosidic and cross ring cleavages. Matrix equations are developed for the calculation of theoretical masses. Algorithm is presented for iterative generation of all fragments and calculation of their masses. This method is applicable to glycan analytical techniques using MS, MS/MS, and multistage MS (MSn) with different ionization methods, derivatives, or ions used. The method is adaptable to computer program and has been verified for theoretical masses reported in literature. Rules for the theoretical validation of the fragments are presented.     

Shedding light on black boxes in protein identification

Performing a well thought‐out proteomics data analysis can be a daunting task, especially for newcomers to the field. Even researchers experienced in the proteomics field can find it challenging to follow existing publication guidelines for MS‐based protein identification and characterization in detail. One of the primary goals of bioinformatics is to enable any researcher to interpret the vast amounts of data generated in modern biology, by providing user‐friendly and robust end‐user applications, clear documentation, and corresponding teaching materials. In that spirit, we here present an extensive tutorial for peptide and protein identification, available at http://compomics.com/bioinformatics‐for‐proteomics . The material is completely based on freely available and open‐source tools, and has already been used and refined at numerous international courses over the past 3 years. During this time, it has demonstrated its ability to allow even complete beginners to intuitively conduct advanced bioinformatics workflows, interpret the results, and understand their context. This tutorial is thus aimed at fully empowering users, by removing black boxes in the proteomics informatics pipeline.     

GlycReSoft: A Software Package for Automated Recognition of Glycans from LC/MS Data

Glycosylation modifies the physicochemical properties and protein binding functions of glycoconjugates. These modifications are biosynthesized in the endoplasmic reticulum and Golgi apparatus by a series of enzymatic transformations that are under complex control. As a result, mature glycans on a given site are heterogeneous mixtures of glycoforms. This gives rise to a spectrum of adhesive properties that strongly influences interactions with binding partners and resultant biological effects. In order to understand the roles glycosylation plays in normal and disease processes, efficient structural analysis tools are necessary. In the field of glycomics, liquid chromatography/mass spectrometry (LC/MS) is used to profile the glycans present in a given sample. This technology enables comparison of glycan compositions and abundances among different biological samples, i.e. normal versus disease, normal versus mutant, etc. Manual analysis of the glycan profiling LC/MS data is extremely time-consuming and efficient software tools are needed to eliminate this bottleneck. In this work, we have developed a tool to computationally model LC/MS data to enable efficient profiling of glycans. Using LC/MS data deconvoluted by Decon2LS/DeconTools, we built a list of unique neutral masses corresponding to candidate glycan compositions summarized over their various charge states, adducts and range of elution times. Our work aims to provide confident identification of true compounds in complex data sets that are not amenable to manual interpretation. This capability is an essential part of glycomics work flows. We demonstrate this tool, GlycReSoft, using an LC/MS dataset on tissue derived heparan sulfate oligosaccharides. The software, code and a test data set are publically archived under an open source license.     

Utility of mass spectrometry for proteome analysis: part II. Ion-activation methods,statistics, bioinformatics and annotation

This is the second article in a series, intended as a tutorial to provide the interested reader with an overview of the concepts not covered in part I, such as: the principles of ion-activation methods, the ability of mass-spectrometric methods to interface with various proteomic strategies, analysis techniques, bioinformatics and data interpretation and annotation. Although these are different topics, it is important that a reader has a basic and collective understanding of all of them for an overall appreciation of how to carry out and analyze a proteomic experiment. Different ion-activation methods for MS/MS, such as collision-induced dissociation (including postsource decay) and surface-induced dissociation, electron capture and electron-transfer dissociation, infrared multiphoton and blackbody infrared radiative dissociation have been discussed since they are used in proteomic research. The high dimensionality of data generated from proteomic studies requires an understanding of the underlying analytical procedures used to obtain these data, as well as the development of improved bioinformatics tools and data-mining approaches for efficient and accurate statistical analyses of biological samples from healthy and diseased individuals, in addition to determining the utility of the interpreted data. Currently available strategies for the analysis of the proteome by mass spectrometry, such as those employed for the analysis of substantially purified proteins and complex peptide mixtures, as well as hypothesis-driven strategies, have been elaborated upon. Processing steps prior to the analysis of mass spectrometry data, statistics and the several informatics steps currently used for the analysis of shotgun proteomic experiments, as well as proteomics ontology, are also discussed.