High-throughput Glycomics Research Articles

Predicting glycan structure from tandem mass spectrometry via deep learning

Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throughput endeavors and relegating glycomics to a few experts. Trained on a newly curated set of 500,000 annotated MS/MS spectra, here we present CandyCrunch, a dilated residual neural network predicting glycan structure from raw liquid chromatography–MS/MS data in seconds (top-1 accuracy: 90.3%). We developed an open-access Python-based workflow of raw data conversion and prediction, followed by automated curation and fragment annotation, with predictions recapitulating and extending expert annotation. We demonstrate that this can be used for de novo annotation, diagnostic fragment identification and high-throughput glycomics. For maximum impact, this entire pipeline is tightly interlaced with our glycowork platform and can be easily tested at https://colab.research.google.com/github/BojarLab/CandyCrunch/blob/main/CandyCrunch.ipynb. We envision CandyCrunch to democratize structural glycomics and the elucidation of biological roles of glycans.

Warning signs from the crypt: Aberrant protein glycosylation marks opportunities for early colorectal cancer detection.

Colorectal cancer (CRC) remains a leading cause of cancer-related deaths despite being the most preventable and treatable forms of cancer when caught early through screening. There is an unmet need for novel screening approaches with improved accuracy, less invasiveness, and reduced costs. In recent years, evidence has accumulated around particular biological events that happen during the adenoma to carcinoma transition, especially focusing on precancerous immune responses in the colonic crypt. Protein glycosylation plays a central role in driving those responses and recently numerous reports have been published on how aberrant protein glycosylation, both in colonic tissue and on circulating glycoproteins reflects these precancerous developments. The complex field of glycosylation, which exceeds complexity of proteins by several orders of magnitude, can now be studied primarily because of the availability of new high-throughput technologies like mass spectrometry and artificial-intelligence (AI)-powered data processing. This has now opened new avenues to studying novel biomarkers for CRC screening.This review summarizes the early events taking place from the normal colon mucosa towards adenoma and adenocarcinoma formation and associated critical protein glycosylation phenomena both on tissue level and in the circulation. These insights will help establish an understanding in the interpretation of novel CRC detection modalities that involve high throughput glycomics.

High-Throughput Glycomic Methods.

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Developments and perspectives in high-throughput protein glycomics: enabling the analysis of thousands of samples.

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.

Understanding the structure and composition of recalcitrant oligosaccharides in hydrolysate using high-throughput biotin-based glycome profiling and mass spectrometry

Novel Immunological and Mass Spectrometry Methods for Comprehensive Analysis of Recalcitrant Oligosaccharides in AFEX Pretreated Corn Stover. Lignocellulosic biomass is a sustainable alternative to fossil fuel and is extensively used for developing bio-based technologies to produce products such as food, feed, fuel, and chemicals. The key to these technologies is to develop cost competitive processes to convert complex carbohydrates present in plant cell wall to simple sugars such as glucose, xylose, and arabinose. Since lignocellulosic biomass is highly recalcitrant, it must undergo a combination of thermochemical treatment such as Ammonia Fiber Expansion (AFEX), dilute acid (DA), Ionic Liquid (IL) and biological treatment such as enzyme hydrolysis and microbial fermentation to produce desired products. However, when using commercial fungal enzymes during hydrolysis, only 75–85% of the soluble sugars generated are monomeric sugars, while the remaining 15–25% are soluble recalcitrant oligosaccharides that cannot be easily utilized by microorganisms. Previously, we successfully separated and purified the soluble recalcitrant oligosaccharides using a combination of charcoal and celite-based separation followed by size exclusion chromatography and studies their inhibitory properties on enzymes. We discovered that the oligosaccharides with higher degree of polymerization (DP) containing methylated uronic acid substitutions were more recalcitrant towards commercial enzyme mixtures than lower DP and neutral oligosaccharides. Here, we report the use of several complementary techniques that include glycome profiling using plant biomass glycan specific monoclonal antibodies (mAbs) to characterize sugar linkages in plant cell walls and enzymatic hydrolysate, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) using structurally-informative diagnostic peaks offered by negative ion post-secondary decay spectra, gas chromatography followed by mass spectrometry (GC–MS) to characterize oligosaccharide sugar linkages with and without derivatization. Since oligosaccharides (DP 4–20) are small, it is challenging to mobilize these molecules for mAbs binding and characterization. To overcome this problem, we have applied a new biotin-coupling based oligosaccharide immobilization method that successfully tagged most of the low DP soluble oligosaccharides on to a micro-plate surface followed by specific linkage analysis using mAbs in a high-throughput system. This new approach will help develop more advanced versions of future high throughput glycome profiling methods that can be used to separate and characterize oligosaccharides present in biomarkers for diagnostic applications.

Bisecting Lewis X in Hybrid-Type N-Glycans of Human Brain Revealed by Deep Structural Glycomics.

The importance of protein glycosylation in the biomedical field requires methods that not only quantitate structures by their monosaccharide composition, but also resolve and identify the many isomers expressed by mammalian cells. The art of unambiguous identification of isomeric structures in complex mixtures, however, did not yet catch up with the fast pace of advance of high-throughput glycomics. Here, we present a strategy for deducing structures with the help of a deci-minute accurate retention time library for porous graphitic carbon chromatography with mass spectrometric detection. We implemented the concept for the fundamental N-glycan type consisting of five hexoses, four N-acetylhexosamines and one fucose residue. Nearly all of the 40 biosynthetized isomers occupied unique elution positions. This result demonstrates the unique isomer selectivity of porous graphitic carbon. With the help of a rather tightly spaced grid of isotope-labeled internal N-glycan, standard retention times were transposed to a standard chromatogram. Application of this approach to animal and human brain N-glycans immediately identified the majority of structures as being of the bisected type. Most notably, it exposed hybrid-type glycans with galactosylated and even Lewis X containing bisected N-acetylglucosamine, which have not yet been discovered in a natural source. Thus, the time grid approach implemented herein facilitated discovery of the still missing pieces of the N-glycome in our most noble organ and suggests itself—in conjunction with collision induced dissociation—as a starting point for the overdue development of isomer-specific deep structural glycomics.

High-throughput glycomic analyses reveal unique oligosaccharide profiles of canine and feline milk samples

Oligosaccharides are important components of milk, serving as substrates for the intestinal microbiota, acting as antimicrobials that prevent pathogen colonization, and supporting the developing gastrointestinal immune system of neonates. Nutrient composition of canine and feline milk samples has been described previously, but little is known about the oligosaccharide content. Therefore, the objective of this study was to characterize canine and feline milk samples using a high-throughput glycomics approach. 23 dogs (9 Labrador retriever and 14 Labrador retriever x golden retriever crossbreed) and 6 domestic shorthair cats were recruited to the study. Milk samples were collected by manual expression at time points after parturition. Samples were collected across 2 phases per species, differentiated by maternal diet. Following extraction, oligosaccharide content was determined by liquid chromatography-mass spectrometry (LC-MS). In canine milk samples, 3 structures accounted for over 90% of all oligosaccharides detected across two diet groups. These were 3’-sialyllactose, 6’-sialyllactose, and 2’-fucosyllactose. In feline samples, a more diverse range of oligosaccharides was detected, with up to 16 structures present at relative abundance >1% of the total. Difucosyllactose-N-hexaose b, 3’-sialyllactose and lacto-N-neohexaose were all detected at abundances >10% in feline milk samples. Statistically significant differences (p<0.05) in oligosaccharide abundances were observed between collection time points and between diet groups within species. These data explore the oligosaccharide content of canine and feline maternal milk, representing an opportunity to generate a fundamental understanding of the nutritional needs of new-born puppies and kittens.

Exploring the scope of high throughput micro‐permethylation based glycomics.

The glycosylation plays important roles in various molecular and cellular functions such as cell signaling, adhesion, development, immune recognition, lubrication, cellular defense etc. The protein glycosylation also contributes towards the stability, serum half‐life, immunogenicity and more importantly, biological activity of therapeutic glycoproteins, including antibodies, vaccines, biomarkers etc. This justifies the increasing demand for the qualitative and quantitative characterization and validation of glycosylation profile on glycoproteins. However, profiling of glycosylation is challenging owing to the glycosylation microheterogeneity, non‐template driven synthesis and their lower abundances. We have recently developed a high throughput N‐ and O‐glycomics strategy through a microscale permethylation based glycan derivatization followed by mass spectrometry (MS). Through this strategy facile but detailed quantitative structural profiling of glycans in a high throughput fashion can be attained. Here, we are reporting the wide applicability of our high throughput glycomics on glycoconjugates from various sources, including human serum, mammalian cells, milk oligosaccharides and purified glycoproteins via an automated tandem ESI‐MSn acquisition platform. The released or free glycans are permethylated in microscale in a 96‐well plate or microcentrifuge tubes and analyzed by an automated ESI‐MSn system after a C18 tip‐based cleanup. An internal standard based method was also incorporated for the absolute quantitation of glycan species. We have employed an in‐depth automated structural characterization MS program for N/O‐glycans through an automated ESI‐MSn acquisition up to MS5 level. Through this automated process, detailed glycan structural topology can be identified including glycan termini, branching, isomers, sialic acid linkages, and bisecting GlcNAc on the glycans. This approach can facilitate profiling of glycosylation on large sample sets, including clinical glycan biomarkers, milk oligosaccharides, and other glycoprotein therapeutics.Support or Funding InformationNational Institutes of Health grant (No. 1S10OD018530) to Dr. Parastoo Azadi

Simultaneous Release and Labeling of O- and N-Glycans Allowing for Rapid Glycomic Analysis by Online LC-UV-ESI-MS/MS.

Most glycoproteins and biological protein samples undergo both O- and N-glycosylation, making characterization of their structures very complicated and time-consuming. Nevertheless, to fully understand the biological functions of glycosylation, both the glycosylation forms need to be analyzed. Herein we report a versatile, convenient one-pot method in which O- and N-glycans are simultaneously released from glycoproteins and chromogenically labeled in situ and thus available for further characterization. In this procedure, glycoproteins are incubated with 1-phenyl-3-methyl-5-pyrazolone (PMP) in aqueous ammonium hydroxide, making O-glycans released from protein backbones by β-elimination and N-glycans liberated by alkaline hydrolysis. The released glycans are promptly derivatized with PMP in situ by Knoevenagel condensation and Michael addition, with peeling degradation almost completely prevented. The recovered mixture of O- and N-glycans as bis-PMP derivatives features strong ultraviolet (UV) absorbing ability and hydrophobicity, allowing for high-resolution chromatographic separation and high-sensitivity spectrometric detection. Using this technique, O- and N-glycans were simultaneously prepared from some model glycoproteins and complex biological samples, without significant peeling, desialylation, deacetylation, desulfation or other side-reactions, and then comprehensively analyzed by online HILIC-UV-ESI-MS/MS and RP-HPLC-UV-ESI-MS/MS, with which some novel O- and N-glycan structures were first found. This method provides a simple, versatile strategy for high-throughput glycomics analysis.

Automatic annotation and visualization tool for mass spectrometry based glycomics.

With the development of glycomics, a large number of glycan structures have been determined by using mass spectrometry (MS)-based techniques. However, most glycan MS data needs to be manually annotated which is time-consuming, unreliable and inaccurate. Herein we report a tool for automatically annotating and browsing N-glycan masses and isotopic distributions. We first constructed a training dataset using the Consortium for Functional Glycomics database, in conjunction with data preprocessing and filtering by composition matching. In addition, we improved a matching glycan isotope abundance algorithm through identifying potential overlap region and constructing an optimization model so that it can deconvolute the overlapped glycan isotopic clusters. In the matching process, if the m/z difference of two detected ions was close to an integer from 1 to 5, the m/z range was considered as a potential overlapped region, from the lower m/z to m/z+5. It was found that there were more than 20 potential overlap regions in each group of data from CHO sample and human testing sample. Because the training dataset was imbalanced, we combined the Supporting Vector Machines (SVMs) algorithm with different sampling techniques, including Synthetic Minority Over-sampling Technique (SMOTE), to classify all potential candidate compositions. The results demonstrated an average of 26.8% increase in annotation sensitivity through the SMOTE-SVMs algorithm. The source code can be obtained from https://sourceforge.net/projects/glycomaid/. We have developed a new tool which facilities high-throughput glycomics research and assists mass spectrometrists in the interpretation and annotation of glycan samples. Copyright © 2016 John Wiley & Sons, Ltd.

The Use of Multiple Reaction Monitoring on QQQ-MS for the Analysis of Protein- and Site-Specific Glycosylation Patterns in Serum.

In recent years, high-throughput glycomics approaches have been developed and applied to either complete biofluids, cell lysates or tissues, or proteins isolated thereof. However, during such analyses the N-glycan are released from the protein backbone and therefore site- and protein-specific information is lost. There exists a need for high-throughput methods that allow quantification of site- and protein-specific glycosylation patterns from complex biological mixtures. We here describe the use of a multiple reaction monitoring mass spectrometry based method for the generation of glycopeptide profiles of the nine high abundance glycoproteins IgG, IgA, IgM, haptoglobin, alpha-1-antitrypsin, alpha-2-macroglobulin, alpha-1-acid glycoprotein, transferrin, and complement C3. We show that the sample preparation can be performed at the 96-well level, and using a 17-min gradient on a RP-UPLC-QQQ instrument, 96 samples can be analyzed within 3 days.

Alteration of serum N-glycan profile in patients with autoimmune pancreatitis.

The aims of this study were to determine the change in whole-serum N-glycan profile in autoimmune pancreatitis (AIP) patients and to investigate its clinical utility. We collected serum from 21 AIP patients before any treatment, and from 60 healthy volunteers (HLTs). Serum glycan profile was measured by comprehensive and quantitative high-throughput glycome analysis. Of the 53 glycans detected, 14 were differentially expressed in AIP patients. Pathway analysis demonstrated that agalactosyl and monogalactosyl bi-antennary glycans were elevated in AIP patients. Among the 14 glycans, #3410, #3510, and #4510 showed high area under receiver operating characteristic (AUROC) values (0.955, 0.964, and 0.968 respectively) for the diagnosis of AIP. These three glycans were mainly bound to immunoglobulin G; however, their serum levels were significantly higher, even in AIP patients who showed lower serum IgG4 levels, than in HLTs. We demonstrated, for the first time, whole-serum glycan profiles of AIP patients and showed that the levels of glycans #3410, #3510, and #4510 were increased in AIP patients. These glycans might be valuable biomarkers of AIP.

MALDI-MS 기반 당단백질 당쇄의 정량분석 기술 개발 연구 동향

Abnormal glycosylation can significantly affect the intrinsic functions (i.e., stability and solubility) of proteins and the extrinsic protein interactions with other biomolecules. For example, recombinant glycoprotein therapeutics needs proper glycosylation for optimal drug efficacy. Therefore, there has been a strong demand for rapid, sensitive and high-throughput glycomics tools for real-time monitoring and fast validation of the biotherapeutics glycosylation. Although liquid chromatography tandem mass spectrometry (LC-MS/MS) is one of the most powerful tools for the characterization of glycan structures, it is generally time consuming and requires highly skilled personnel to collect the data and analyze the results. Recently, as an alternative method, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-MS), which is a fast, robust and easy-to-use instrumentation, has been used for quantitative glycomics with various chemical derivatization techniques. In this review, we highlight the recent advances in MALDI-MS based quantitative glycan analysis according to the chemical derivatization strategies. Moreover, we address the application of MALDIMS for high-throughput glycan analysis in many fields of clinical and biochemical engineering.

High-throughput glycomics: optimization of sample preparation.

Glycosylation affects structure, folding, and function of numerous proteins. Aberrant glycosylation has been shown to be associated with different diseases. A wide range of analytical methods is available for glycan analysis of antibodies (mainly IgG), but analysis of plasma glycans is less established due to additional challenges encountered with higher complexity of the sample. Here we describe development and optimization of a high-throughput sample preparation method for hydrophilic interaction liquid chromatography and ultra-performance liquid chromatography analysis of plasma N-glycans. Clean-up of labeled glycans was found to be the largest source of variation, and we tested cellulose, silica gel, Bio-Gel, and hydrophilic GHP filter as stationary phases for solid-phase extraction. All stationary phases were shown to be suitable for purification of labeled glycans, but GHP filter plate in combination with cold 96% acetonitrile had the highest reproducibility and was easiest to work with. The method was further optimized with Plackett-Burman screening design and validated in terms of analysis of major step variation and between-day and between-person variation. The developed method is fast, cost-effective, and easy to perform, and it has very good reproducibility during long period of time, enabling the detection of biological variability of the plasma N-glycome.

Use of non-invasive serum glycan markers to distinguish non-alcoholic steatohepatitis from simple steatosis.

Serum glycans have been reported to be promising diagnostic markers for many inflammatory diseases and cancers. The aims of this study were to investigate whole glycan expression in patients with non-alcoholic fatty liver diseases and to evaluate the potential use of glycan profiles as new clinical biomarkers to distinguish non-alcoholic steatohepatitis (NASH) from simple steatosis (SS). We collected sera from 42 histologically proven NASH and 15 SS patients prior to treatment. Serum glycan profiles were measured by comprehensive, quantitative, high-throughput glycome analysis, and diagnostic values of serum glycans for NASH prediction were examined. Among the 41 serum glycans examined, the expression levels of 8 glycans in NASH were significantly higher than those of SS. Out of these eight glycans, three glycans (m/z 1955, 2032, and 2584) showed high areas under the receiver operating characteristic curve (0.833, 0.863, and 0.866, respectively) for distinguishing NASH from SS. In multivariate analyses with clinical parameters and serum glycans, these three glycans were significant predictive factors for distinguishing NASH from SS. The odds ratio of m/z 1955, 2032, and 2584 were 48.5, 6.46, and 11.8, respectively. These glycans also correlated significantly with lobular inflammation, ballooning, and fibrosis, but not with steatosis. We clearly demonstrated whole-serum glycan profiles in NASH patients, and the feasibility of serum glycans (m/z 1955, 2032, and 2584) as new noninvasive biomarkers for distinguishing NASH from SS.

Automated annotation and quantitation of glycans by liquid chromatography/electrospray ionization mass spectrometric analysis using the MultiGlycan-ESI computational tool.

Liquid chromatography/mass spectrometry (LC/MS) is currently considered to be a conventional glycomics analysis strategy due to the high sensitivity and ability to handle complex biological samples. Interpretation of LC/MS data is a major bottleneck in high-throughput glycomics LC/MS-based analysis. The complexity of LC/MS data associated with biological samples prompts the needs to develop computational tools capable of facilitating automated data annotation and quantitation. An LC/MS-based automated data annotation and quantitation software, MultiGlycan-ESI, was developed and utilized for glycan quantitation. Data generated by the software from LC/MS analysis of permethylated N-glycans derived from fetuin were initially validated by manual integration to assess the performance of the software. The performance of MultiGlycan-ESI was then assessed for the quantitation of permethylated fetuin N-glycans analyzed at different concentrations or spiked with permethylated N-glycans derived from human blood serum. The relative abundance differences between data generated by the software and those generated by manual integration were less than 5%, indicating the reliability of MultiGlycan-ESI in quantitation of permethylated glycans analyzed by LC/MS. Automated quantitation resulted in a linear relationship for all six N-glycans derived from 50 ng to 400 ng fetuin with correlation coefficients (R(2) ) greater than 0.93. Spiking of permethylated fetuin N-glycans at different concentrations in permethylated N-glycan samples derived from a 0.02 μL of HBS also exhibited linear agreement with R(2) values greater than 0.9. With a variety of options, including mass accuracy, merged adducts, and filtering criteria, MultiGlycan-ESI allows automated annotation and quantitation of LC/ESI-MS N-glycan data. The software allows the reliable quantitation of glycan LC/MS data. The software is reliable for automated glycan quantitation, thus facilitating rapid and reliable high-throughput glycomics studies.

Serum glycan markers for evaluation of disease activity and prediction of clinical course in patients with ulcerative colitis.

BackgroundThe aims of this study were to determine the change of whole-serum N-glycan profile in ulcerative colitis (UC) patients and to investigate its clinical utility.MethodsWe collected serum from 75 UC patients at the time of admission and the same number of age/sex-matched healthy volunteers. Serum glycan profile was measured by comprehensive quantitative high-throughput glycome analysis and was compared with disease activity and prognosis.ResultsOut of 61 glycans detected, 24 were differentially expressed in UC patients. Pathway analysis demonstrated that highly sialylated multi-branched glycans and agalactosyl bi-antennary glycans were elevated in UC patients; in addition, the glycan ratio m/z 2378/1914, which also increased in UC, showed the highest Area under Receiver Operating Characteristic curve (0.923) for the diagnosis of UC. Highly sialylated multi-branched glycans and the glycan ratio m/z 2378/1914 were higher in the patients with total colitis, Clinical Activity Index >10, Mayo endoscopic score 3, or a steroid-refractory status. In particular, the glycan ratio m/z 2378/1914 (above median) was an independent prognostic factor for the need for an operation (hazard ratio, 2.67; 95% confidence interval, 1.04–7.84).ConclusionsWhole-serum glycan profiles revealed that the glycan ratio m/z 2378/1914 and highly sialylated multi-branched glycans increase in UC patients, and are correlated with disease activity. The glycan ratio m/z 2378/1914 was an independent predictive factor of the prognosis of UC.

Clinical utility of high-throughput glycome analysis in patients with pancreatic cancer

Most of the glycan changes reported in cancers were based on the examinations of a small number of patients or particular proteins. The aim of this study was to determine the changes of the serum N-glycan profile comprehensively in a large number of pancreatic cancer patients and investigate its clinical utility. Glycan levels in the serum of 92 pancreatic cancer patients and 243 healthy volunteers (HLT) were examined by comprehensive quantitative high-throughput glycome analysis and were compared with clinical parameters. Out of 66 glycans detected, 15 were differentially expressed in pancreatic cancer, and 10 out of the 15 glycans were significantly up-regulated in cases with distant metastasis. There was a clear increase in overall expression of serum glycans, especially highly-branched glycans with fucose moieties, in pancreatic cancer. Among these 15 glycans, a tri-antennary complex type glycan (m/z 3195) showed the highest area under the receiver operating characteristic curve (AUROC=0.799) for the diagnosis of pancreatic cancer. The ratio of pairs of glycans on the same path of the biosynthesis pathway (m/z 3195/1914) was found to be significantly higher in pancreatic cancer than in HLT (median=1.11 and 0.41, respectively; p<0.0001, AUROC=0.831). For this pair ratio, the hazard ratio for survival (2.60, 95% CI=1.44-4.79) was higher than that of any single glycan and 1-year survival of patients with a high and low ratio was 36.9 and 69.2%, respectively, (p=0.001). Comprehensive glycome analysis can be used to know the presence of pancreatic cancer, distant metastasis, and patient prognosis, simultaneously.

Is High Throughput Glycomics Possible?

The role of glycosylation and their biological functions whether as free oligosaccharides or glycoconjugates has been made possible by the recent advancements in the analyses of these compounds. The heterogeneity and the large structural diversity have made oligosaccharide analysis significantly more difficult than other biopolymers. The next stage of development is to achieve high throughput analysis. However, the structural elucidation of oligosaccharides remains an extremely difficult task. Recent reports reveal that the diversity of structures in a given biological system is finite and may not be large. It may be possible to create a database of structures that can be used to determine the identity of known compounds. This capability would therefore make high throughput glycomics possible. Achieving this task depends on the proper selection of chemical characteristics to identify the compound. In this presentation, nanoflow liquid chromatography retention times, accurate mass, and tandem MS is used to determine structure with a high degree of certainty. The method is used to determine the biological function of milk oligosaccharides as well as to discover glycan-based biomarkers for diseases.

Glycomics meets genomics, epigenomics and other high throughput omics for system biology studies

Majority of eukaryotic proteins are glycosylated and their glycan moieties have numerous important structural, functional and regulatory roles. Because of structural complexity of glycans and technological limitations glycomics, and particularly glycoproteomics was not able to follow rapid progress in genomics and proteomics over last 30 years. However, the field of glycan has been progressing rapidly and first large-scale studies of the glycome have been completed recently. These studies have revealed significant differences in glycome composition between individuals, which may contribute to the human phenotypic variability. The current state-of-the-art in high-throughput glycomics and its integration with genomics, epigenomics and lipidomics is reviewed in this article.