Synthetic heparan sulfate standards and machine learning facilitate the development of solid-state nanopore analysis.

The application of solid-state (SS) nanopore devices to single-molecule nucleic acid sequencing has been challenging. Thus, the early successes in applying SS nanopore devices to the more difficult class of biopolymer, glycosaminoglycans (GAGs), have been surprising, motivating us to examine the potential use of an SS nanopore to analyze synthetic heparan sulfate GAG chains of controlled composition and sequence prepared through a promising, recently developed chemoenzymatic route. A minimal representation of the nanopore data, using only signal magnitude and duration, revealed, by eye and image recognition algorithms, clear differences between the signals generated by four synthetic GAGs. By subsequent machine learning, it was possible to determine disaccharide and even monosaccharide composition of these four synthetic GAGs using as few as 500 events, corresponding to a zeptomole of sample. These data suggest that ultrasensitive GAG analysis may be possible using SS nanopore detection and well-characterized molecular training sets.

GlycoPOST realizes FAIR principles for glycomics mass spectrometry data.

For the reproducibility and sustainability of scientific research, FAIRness (Findable, Accessible, Interoperable and Re-usable), with respect to the release of raw data obtained by researchers, is one of the most important principles underpinning the future of open science. In genomics and transcriptomics, the sharing of raw data from next-generation sequencers is made possible through public repositories. In addition, in proteomics, the deposition of raw data from mass spectrometry (MS) experiments into repositories is becoming standardized. However, a standard repository for such MS data had not yet been established in glycomics. With the increasing number of glycomics MS data, therefore, we have developed GlycoPOST (https://glycopost.glycosmos.org/), a repository for raw MS data generated from glycomics experiments. In just the first year since the release of GlycoPOST, 73 projects have already been registered by researchers around the world, and the number of registered projects is continuously growing, making a significant contribution to the future FAIRness of the glycomics field. GlycoPOST is a free resource to the community and accepts (and will continue to accept in the future) raw data regardless of vendor-specific formats.

Method comparison for N-glycan profiling: Towards the standardization of glycoanalytical technologies for cell line analysis.

The study of protein N-glycosylation is essential in biological and biopharmaceutical research as N-glycans have been reported to regulate a wide range of physiological and pathological processes. Monitoring glycosylation in diagnosis, prognosis, as well as biopharmaceutical development and quality control are important research areas. A number of techniques for the analysis of protein N-glycosylation are currently available. Here we examine three methodologies routinely used for the release of N-glycans, in the effort to establish and standardize glycoproteomics technologies for quantitative glycan analysis from cultured cell lines. N-glycans from human gamma immunoglobulins (IgG), plasma and a pool of four cancer cell lines were released following three approaches and the performance of each method was evaluated.

Standardization of PGC-LC-MS-based glycomics for sample specific glycotyping.

Porous graphitized carbon (PGC) based chromatography achieves high-resolution separation of glycan structures released from glycoproteins. This approach is especially valuable when resolving structurally similar isomers and for discovery of novel and/or sample-specific glycan structures. However, the implementation of PGC-based separations in glycomics studies has been limited because system-independent retention values have not been established to normalize technical variation. To address this limitation, this study combined the use of hydrolyzed dextran as an internal standard and Skyline software for post-acquisition normalization to reduce retention time and peak area technical variation in PGC-based glycan analyses. This approach allowed assignment of system-independent retention values that are applicable to typical PGC-based glycan separations and supported the construction of a library containing >300 PGC-separated glycan structures with normalized glucose unit (GU) retention values. To enable the automation of this normalization method, a spectral MS/MS library was developed of the dextran ladder, achieving confident discrimination against isomeric glycans. The utility of this approach is demonstrated in two ways. First, to inform the search space for bioinformatically predicted but unobserved glycan structures, predictive models for two structural modifications, core-fucosylation and bisecting GlcNAc, were developed based on the GU library. Second, the applicability of this method for the analysis of complex biological samples is evidenced by the ability to discriminate between cell culture and tissue sample types by the normalized intensity of N-glycan structures alone. Overall, the methods and data described here are expected to support the future development of more automated approaches to glycan identification and quantitation.

Glycoinformatics: Bridging Isolated Islands in the Sea of Data.

Glycoinformatics is an actively developing scientific discipline, which provides scientists with the means of access to the data on natural glycans and with various tools of their processing. However, the informatization of glycomics has a long way to go before catching up with genomics and proteomics. In this Viewpoint, we review the current situation in glycoinformatics and discuss its achievements and shortcomings, emphasizing the major drawbacks: the lack of recognized standards, protocols, data indices and tools, and the informational isolation of the existing projects. We reiterate possible solutions of the persistent issues and describe our vision of an ideal glycoinformatics project.

GlyTouCan: an accessible glycan structure repository.

Rapid and continued growth in the generation of glycomic data has revealed the need for enhanced development of basic infrastructure for presenting and interpreting these datasets in a manner that engages the broader biomedical research community. Early in their growth, the genomic and proteomic fields implemented mechanisms for assigning unique gene and protein identifiers that were essential for organizing data presentation and for enhancing bioinformatic approaches to extracting knowledge. Similar unique identifiers are currently absent from glycomic data. In order to facilitate continued growth and expanded accessibility of glycomic data, the authors strongly encourage the glycomics community to coordinate the submission of their glycan structures to the GlyTouCan Repository and to make use of GlyTouCan identifiers in their communications and publications. The authors also deeply encourage journals to recommend a submission workflow in which submitted publications utilize GlyTouCan identifiers as a standard reference for explicitly describing glycan structures cited in manuscripts.

Algorithms and design strategies towards automated glycoproteomics analysis.

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

Comparison of analytical methods for profiling N- and O-linked glycans from cultured cell lines : HUPO Human Disease Glycomics/Proteome Initiative multi-institutional study.

The Human Disease Glycomics/Proteome Initiative (HGPI) is an activity in the Human Proteome Organization (HUPO) supported by leading researchers from international institutes and aims at development of disease-related glycomics/glycoproteomics analysis techniques. Since 2004, the initiative has conducted three pilot studies. The first two were N- and O-glycan analyses of purified transferrin and immunoglobulin-G and assessed the most appropriate analytical approach employed at the time. This paper describes the third study, which was conducted to compare different approaches for quantitation of N- and O-linked glycans attached to proteins in crude biological samples. The preliminary analysis on cell pellets resulted in wildly varied glycan profiles, which was probably the consequence of variations in the pre-processing sample preparation methodologies. However, the reproducibility of the data was not improved dramatically in the subsequent analysis on cell lysate fractions prepared in a specified method by one lab. The study demonstrated the difficulty of carrying out a complete analysis of the glycome in crude samples by any single technology and the importance of rigorous optimization of the course of analysis from preprocessing to data interpretation. It suggests that another collaborative study employing the latest technologies in this rapidly evolving field will help to realize the requirements of carrying out the large-scale analysis of glycoproteins in complex cell samples.

MIRAGE: the minimum information required for a glycomics experiment.

The MIRAGE (minimum information required for a glycomics experiment) initiative was founded in Seattle, WA, in November 2011 in order to develop guidelines for reporting the qualitative and quantitative results obtained by diverse types of glycomics analyses, including the conditions and techniques that were applied to prepare the glycans for analysis and generate the primary data along with the tools and parameters that were used to process and annotate this data. These guidelines must address a broad range of issues, as glycomics data are inherently complex and are generated using diverse methods, including mass spectrometry (MS), chromatography, glycan array-binding assays, nuclear magnetic resonance (NMR) and other rapidly developing technologies. The acceptance of these guidelines by scientists conducting research on biological systems in which glycans have a significant role will facilitate the evaluation and reproduction of glycomics experiments and data that is reported in scientific journals and uploaded to glycomics databases. As a first step, MIRAGE guidelines for glycan analysis by MS have been recently published (Kolarich D, Rapp E, Struwe WB, Haslam SM, Zaia J., et al. 2013. The minimum information required for a glycomics experiment (MIRAGE) project - Improving the standards for reporting mass spectrometry-based glycoanalytic data. Mol. Cell Proteomics. 12:991-995), allowing them to be implemented and evaluated in the context of real-world glycobiology research. In this paper, we set out the historical context, organization structure and overarching objectives of the MIRAGE initiative.

Toolboxes for a standardised and systematic study of glycans.

BACKGROUND: Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. METHODS: Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the "objective" difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. RESULTS: Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. CONCLUSIONS: Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics.

The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting mass-spectrometry-based glycoanalytic data.

The MIRAGE guidelines are being developed in response to a critical need in the glycobiology community to clarify glycoanalytic results so that they are more readily evaluated (in terms of their scope and depth) and to facilitate the reproduction of important results in the laboratory. The molecular and biological complexity of the glycosylation process makes thorough reporting of the results of a glycomics experiment a highly challenging endeavor. The resulting data specify the identity and quantity of complex structures, the precise molecular features of which are sometimes inferred using prior knowledge, such as familiarity with a particular biosynthetic mechanism. Specifying the exact methods and assumptions that were used to assign and quantify reported structures allows the interested scientist to appreciate the scope and depth of the analysis. Mass spectrometry (MS) is the most widely used tool for glycomics experiments. The interpretation and reproducibility of MS-based glycomics data depend on comprehensive meta-data describing the instrumentation, instrument setup, and data acquisition protocols. The MIRAGE guidelines for MS-based glycomics have been designed to facilitate the collection and sharing of this critical information in order to assist the glycoanalyst in generating data sets with maximum information content and biological relevance.

Cross-comparison of protein recognition of sialic acid diversity on two novel sialoglycan microarrays.

DNA and protein arrays are commonly accepted as powerful exploratory tools in research. This has mainly been achieved by the establishment of proper guidelines for quality control, allowing cross-comparison between different array platforms. As a natural extension, glycan microarrays were subsequently developed, and recent advances using such arrays have greatly enhanced our understanding of protein-glycan recognition in nature. However, although it is assumed that biologically significant protein-glycan binding is robustly detected by glycan microarrays, there are wide variations in the methods used to produce, present, couple, and detect glycans, and systematic cross-comparisons are lacking. We address these issues by comparing two arrays that together represent the marked diversity of sialic acid modifications, linkages, and underlying glycans in nature, including some identical motifs. We compare and contrast binding interactions with various known and novel plant, vertebrate, and viral sialic acid-recognizing proteins and present a technical advance for assessing specificity using mild periodate oxidation of the sialic acid chain. These data demonstrate both the diversity of sialic acids and the analytical power of glycan arrays, showing that different presentations in different formats provide useful and complementary interpretations of glycan-binding protein specificity. They also highlight important challenges and questions for the future of glycan array technology and suggest that glycan arrays with similar glycan structures cannot be simply assumed to give similar results.

High-throughput quantitative analysis of total N-glycans by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Accurate and reproducible quantification of glycans from protein drugs has become an important issue for quality control of therapeutic proteins in biopharmaceutical and biotechnology industries. Mass spectrometry is a promising tool for both qualitative and quantitative analysis of glycans owing to mass accuracy, efficiency, and reproducibility, but it has been of limited success in quantitative analysis for sialylated glycans in a high-throughput manner. Here, we present a solid-phase permethylation-based total N-glycan quantitative method that includes N-glycan releasing, purification, and derivatization on a 96-well plate platform. The solid-phase neutralization enabled us to perform reliable absolute quantification of the acidic N-glycans as well as neutral N-glycans from model glycoproteins (i.e., chicken ovalbumin and porcine thyroglobulin) by only using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Furthermore, low-abundance sialylated N-glycans from human serum prostate specific antigen (PSA), an extremely valuable prostate cancer marker, were initially quantified, and their chemical compositions were proposed. Taken together, these results demonstrate that our all-inclusive glycan preparation method based on a 96-well plate platform may contribute to the precise and reliable qualitative and quantitative analysis of glycans.

Comparison of methods for profiling O-glycosylation: Human Proteome Organisation Human Disease Glycomics/Proteome Initiative multi-institutional study of IgA1.

The Human Proteome Organisation Human Disease Glycomics/Proteome Initiative recently coordinated a multi-institutional study that evaluated methodologies that are widely used for defining the N-glycan content in glycoproteins. The study convincingly endorsed mass spectrometry as the technique of choice for glycomic profiling in the discovery phase of diagnostic research. The present study reports the extension of the Human Disease Glycomics/Proteome Initiative's activities to an assessment of the methodologies currently used for O-glycan analysis. Three samples of IgA1 isolated from the serum of patients with multiple myeloma were distributed to 15 laboratories worldwide for O-glycomics analysis. A variety of mass spectrometric and chromatographic procedures representative of current methodologies were used. Similar to the previous N-glycan study, the results convincingly confirmed the pre-eminent performance of MS for O-glycan profiling. Two general strategies were found to give the most reliable data, namely direct MS analysis of mixtures of permethylated reduced glycans in the positive ion mode and analysis of native reduced glycans in the negative ion mode using LC-MS approaches. In addition, mass spectrometric methodologies to analyze O-glycopeptides were also successful.

Frontiers in glycomics: bioinformatics and biomarkers in disease. An NIH white paper prepared from discussions by the focus groups at a workshop on the NIH campus, Bethesda MD (September 11-13, 2006).

Key issues relating to glycomics research were discussed after the workshop entitled "Frontiers in Glycomics: Bioinformatics and Biomarkers in Disease" by two focus groups nominated by the organizers. The groups focused on two themes: (i) glycomics as the new frontier for the discovery of biomarkers of disease and (ii) requirements for the development of informatics for glycomics and glycobiology. The mandate of the focus groups was to build consensus on these issues and develop a summary of findings and recommendations for presentation to the NIH and the greater scientific community. A list of scientific priorities was developed, presented, and discussed at the workshops. Additional suggestions were solicited from workshop participants and collected using the workshop mailing list. The results are summarized in this White Paper, authored by the co-chairs of the focus groups.