Distinguishing N-acetylneuraminic acid linkage isomers on glycopeptides by ion mobility-mass spectrometry

Differentiating the structure of isobaric glycopeptides represents a major challenge for mass spectrometry-based characterisation techniques. Here we show that the regiochemistry of the most common N-acetylneuraminic acid linkages of N-glycans can be identified in a site-specific manner from individual glycopeptides using ion mobility-mass spectrometry analysis of diagnostic fragment ions

Cross Reactive Material 197 glycoconjugate vaccines contain privileged conjugation sites

Production of glycoconjugate vaccines involves the chemical conjugation of glycans to an immunogenic carrier protein such as Cross-Reactive-Material-197 (CRM197). Instead of using glycans from natural sources recent vaccine development has been focusing on the use of synthetically defined minimal epitopes. While the glycan is structurally defined, the attachment sites on the protein are not. Fully characterized conjugates and batch-to-batch comparisons are the key to eventually create completely defined conjugates. A variety of glycoconjugates consisting of CRM197 and synthetic oligosaccharide epitopes was characterised using mass spectrometry techniques. The primary structure was assessed by combining intact protein MALDI-TOF-MS, LC-MALDI-TOF-MS middle-down and LC-ESI-MS bottom-up approaches. The middle-down approach on CNBr cleaved glycopeptides provided almost complete sequence coverage, facilitating rapid batch-to-batch comparisons, resolving glycan loading and identification of side products. Regions close to the N- and C-termini were most efficiently conjugated.Full Tex

Glycomic analysis of gastric carcinoma cells discloses glycans as modulators of RON receptor tyrosine kinase activation in cancer

Background Terminal a2-3 and a2-6 sialylation of glycans precludes further chain elongation, leading to the biosynthesis of cancer relevant epitopes such as sialyl-Lewis X (SLe X ). SLe X overexpression is associated with tumor aggressive phenotype and patients' poor prognosis. Methods MKN45 gastric carcinoma cells transfected with the sialyltransferase ST3GAL4 were established as a model overexpressing sialylated terminal glycans. We have evaluated at the structural level the glycome and the sialoproteome of this gastric cancer cell line applying liquid chromatography and mass spectrometry. We further validated an identified target expression by proximity ligation assay in gastric tumors. Results Our results showed that ST3GAL4 overexpression leads to several glycosylation alterations, including reduced O-glycan extension and decreased bisected and increased branched N-glycans. A shift from a2-6 towards a2-3 linked sialylated N-glycans was also observed. Sialoproteomic analysis further identified 47 proteins with significantly increased sialylated N-glycans. These included integrins, insulin receptor, carcinoembryonic antigens and RON receptor tyrosine kinase, which are proteins known to be key players in malignancy. Further analysis of RON confirmed its modification with SLe X and the concomitant activation. SLe X and RON co-expression was validated in gastric tumors. Conclusion The overexpression of ST3GAL4 interferes with the overall glycophenotype of cancer cells affecting a multitude of key proteins involved in malignancy. Aberrant glycosylation of the RON receptor was shown as an alternative mechanism of oncogenic activation. General significance This study provides novel targets and points to an integrative tumor glycomic/proteomic-profiling for gastric cancer patients' stratification. This article is part of a Special Issue entitled "Glycans in personalised medicine" Guest Editor: Professor Gordan Lauc.We acknowledge the support from the European Union, Seventh Framework Programme, Gastric Glyco Explorer initial training network: grant number 316929. IPATIMUP integrates the i3S Research Unit, which is partially supported by FCT, the Portuguese Foundation for Science and Technology. This work is funded by FEDER funds through the Operational Programme for Competitiveness Factors-COMPETE (FCOMP-01-0124-FEDER028188) and National Funds through the FCT-Foundation for Science and Technology, under the projects: PEst-C/SAU/LA0003/2013, PTDC/BBB-EBI/0786/2012, and PTDC/BBB-EBI/0567/2014 (to CAR). This work was also supported by"Glycoproteomics" project grant number PCIG09-GA-2011-293847(to DK) and the Danish Natural Science Research Council and a generous grant from the VILLUM Foundation to the VILLUM Center for Bioanalytical Sciences at the University of Southern Denmark (to MRL). Grants were received from FCT, POPH (Programa Operacional Potencial Humano) and FSE (Fundo Social Europeu): SFRH/BPD/75871/2011 to AM; SFRH/BPD/111048/2015 to JAF; SFRH/BPD/96510/2013 to CG. The UPLC instrument was obtained with a grant from the Ingabritt and Arne Lundbergs Research Foundation (to NK). C.J. was supported by the Knut and Alice Wallenberg Foundation. The mass spectrometer (LTQ) was obtained by a grant from the Swedish Research Council (342-2004-4434) (to NK)

Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west african populations.

Background Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC. Methods Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis. Results Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages. Conclusions The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance

The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data

MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used in structural and functional studies of glycans in the scientific literature. As a sequel to the guidelines for sample preparation (Struwe et al. 2016, Glycobiology, 26:907–910) and mass spectrometry  data (Kolarich et al. 2013, Mol. Cell Proteomics, 12:991–995), here we present the first version of guidelines intended to improve the standards for reporting data from glycan microarray analyses. For each of eight areas in the workflow of a glycan microarray experiment, we provide guidelines for the minimal information that should be provided in reporting results. We hope that the MIRAGE glycan microarray guidelines proposed here will gain broad acceptance by the community, and will facilitate interpretation and reproducibility of the glycan microarray results with implications in comparison of data from different laboratories and eventual deposition of glycan microarray data in international databases

The Minimum Information Required for a Glycomics Experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data

MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics, and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used in structural and functional studies of glycans in the scientific literature. As a sequel to the guidelines for sample preparation (Struwe et al. 2016, Glycobiology, 26, 907-910) and mass spectrometry (MS) data (Kolarich et al. 2013, Mol. Cell Proteomics. 12, 991-995), here we present the first version of guidelines intended to improve the standards for reporting data from glycan microarray analyses. For each of eight areas in the workflow of a glycan microarray experiment, we provide guidelines for the minimal information that should be provided in reporting results. We hope that the MIRAGE glycan microarray guidelines proposed here will gain broad acceptance by the community, and will facilitate interpretation and reproducibility of the glycan microarray results with implications in comparison of data from different laboratories and eventual deposition of glycan microarray data in international databases

Insight into the Regulation of Glycan Synthesis in Drosophila Chaoptin Based on Mass Spectrometry

BACKGROUND: A variety of N-glycans attached to protein are known to involve in many important biological functions. Endoplasmic reticulum (ER) and Golgi localized enzymes are responsible to this template-independent glycan synthesis resulting glycoforms at each asparagine residues. The regulation mechanism such glycan synthesis remains largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: In order to investigate the relationship between glycan structure and protein conformation, we analyzed a glycoprotein of Drosophila melanogaster, chaoptin (Chp), which is localized in photoreceptor cells and is bound to the cell membrane via a glycosylphosphatidylinositol anchor. Detailed analysis based on mass spectrometry revealed the presence of 13 N-glycosylation sites and the composition of the glycoform at each site. The synthetic pathway of glycans was speculated from the observed glycan structures and the composition at each N-glycosylation site, where the presence of novel routes were suggested. The distribution of glycoforms on a Chp polypeptide suggested that various processing enzymes act on the exterior of Chp in the Golgi apparatus, although virtually no enzyme can gain access to the interior of the horseshoe-shaped scaffold, hence explaining the presence of longer glycans within the interior. Furthermore, analysis of Chp from a mutant (RNAi against dolichyl-phosphate alpha-d-mannosyltransferase), which affects N-glycan synthesis in the ER, revealed that truncated glycan structures were processed. As a result, the distribution of glycoforms was affected for the high-mannose-type glycans only, whereas other types of glycans remained similar to those observed in the control and wild-type. CONCLUSIONS/SIGNIFICANCE: These results indicate that glycan processing depends largely on the backbone structure of the parent polypeptide. The information we obtained can be applied to other members of the LRR family of proteins

Linkage Specific Fucosylation of Alpha-1-Antitrypsin in Liver Cirrhosis and Cancer Patients: Implications for a Biomarker of Hepatocellular Carcinoma

We previously reported increased levels of protein-linked fucosylation with the development of liver cancer and identified many of the proteins containing the altered glycan structures. One such protein is alpha-1-antitrypsin (A1AT). To advance these studies, we performed N-linked glycan analysis on the five major isoforms of A1AT and completed a comprehensive study of the glycosylation of A1AT found in healthy controls, patients with hepatitis C- (HCV) induced liver cirrhosis, and in patients infected with HCV with a diagnosis of hepatocellular carcinoma (HCC).Patients with liver cirrhosis and liver cancer had increased levels of triantennary glycan-containing outer arm (alpha-1,3) fucosylation. Increases in core (alpha-1,6) fucosylation were observed only on A1AT from patients with cancer. We performed a lectin fluorophore-linked immunosorbent assay using Aleuria Aurantia lectin (AAL), specific for core and outer arm fucosylation in over 400 patients with liver disease. AAL-reactive A1AT was able to detect HCC with a sensitivity of 70% and a specificity of 86%, which was greater than that observed with the current marker of HCC, alpha-fetoprotein. Glycosylation analysis of the false positives was performed; results indicated that these patients had increases in outer arm fucosylation but not in core fucosylation, suggesting that core fucosylation is cancer specific.This report details the stepwise change in the glycosylation of A1AT with the progression from liver cirrhosis to cancer and identifies core fucosylation on A1AT as an HCC specific modification

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics