A Concise Synthesis of Glycolipids Based on Aspartic Acid Building Blocks

L-Aspartic acid building blocks bearing galactosyl moieties were used to synthesise glycolipid mimetics of variable hydrocarbon chain length. The glycolipids were readily prepared through amide bond formation using the TBTU/HOBt coupling methodology. It was observed that, under these conditions, activation of the α-carboxylic acid of the intermediates led to near complete racemisation of the chiral centre if the reaction was carried out in the presence of a base such as triethylamine. The enantiomerically pure glycolipids were obtained after careful consideration of the synthetic sequence and by performing the coupling reactions in the absence of base

Automated, high-throughput serum glycoprofiling platform

Complex carbohydrates are rapidly becoming excellent biomarker candidates because of their high sensitivity to pathological changes. However, the discovery of clinical glycobiomarkers has been slow, due to the scarcity of high-throughput glycoanalytical workflows that allow rapid glycoprofiling of large clinical sample sets. To generate high-quality quantitative glycomics data in a high-throughput fashion, we have developed a robotized platform for rapid serum-based N-glycan sample preparation. The sample preparation workflow features a fully automated, rapid glycoprotein denaturation followed by sequential enzymatic glycan release, glycan purification on solid-supported hydrazide and fluorescent labelling. This allows accurate glycan quantitation by ultra-high performance liquid chromatography (UPLC). The sample preparation workflow was automated using an eight-channel Hamilton Robotics liquid handling workstation, allowing the preparation of almost 100 samples in 14 hours with excellent reproducibility and thus should greatly facilitate serum-based glyco-biomarker discovery

The sweet spot for biologics: recent advances in characterization of biotherapeutic glycoproteins

Introduction: Glycosylation is recognized as a Critical Quality Attribute for therapeutic glycoproteins such as monoclonal antibodies, fusion proteins and therapeutic replacement enzymes. Hence, efficient and quantitative glycan analysis techniques have been increasingly important for their discovery, development and quality control. The aim of this review is to highlight relevant and recent advances in analytical technologies for characterization of biotherapeutic glycoproteins. Areas covered: The review gives an overview of the glycosylation trends of biotherapeutics approved in 2016 and 2017 by FDA. It describes current and novel analytical technologies for characterization of therapeutic glycoproteins and is explored in the context of released glycan, glycopeptide or intact glycoprotein analysis. Ultra performance liquid chromatography, mass spectrometry and capillary electrophoresis technologies are explored in this context. Expert commentary: There is a need for the biopharmaceutical industry to incorporate novel state of the art analytical technologies into existing and new therapeutic glycoprotein workflows for safer and more efficient biotherapeutics and for the improvement of future biotherapeutic design. Additionally, at present, there is no ‘gold-standard’ approach to address all the regulatory requirements and as such this will involve the use of orthogonal glycoanalytical technologies with a view to gain diagnostic information about the therapeutic glycoprotein

N‑Glycosylation of Serum IgG and Total Glycoproteins in MAN1B1 Deficiency

MAN1B1-CDG has recently been characterized as a type II congenital disorder of glycosylation (CDG), disrupting not only protein N-glycosylation but also general Golgi morphology. Using our high-throughput, quantitative ultra-performance liquid chromatography assay, we achieved a detailed characterization of the glycosylation changes in both total serum glycoproteins and isolated serum IgG from ten previously reported MAN1B1-CDG patients. We have identified and quantified novel hybrid high-mannosylated MAN1B1-CDG-specific IgG glycans and found an increase of sialyl Lewis x (sLex) glycans on serum proteins of all patients. This increase in sLex has not been previously reported in any CDG. These findings may provide insight into the pathophysiology of this CDG

High-throughput and high-sensitivity N-Glycan profiling: A platform for biopharmaceutical development and disease biomarker discovery

Protein glycosylation contributes to critical biological function of glycoproteins. Glycan analysis is essential for the production of biopharmaceuticals as well as for the identification of disease biomarkers. However, glycans are highly heterogeneous, which has considerably hampered the progress of glycomics. Here, we present an improved 96-well plate format platform for streamlined glycan profiling that takes advantage of rapid glycoprotein denaturation, deglycosylation, fluorescent derivatization, and on-matrix glycan clean-up. This approach offers high sensitivity with consistent identification and quantification of diverse N-glycans across multiple samples on a high-throughput scale. We demonstrate its capability for N-glycan profiling of glycoproteins from various sources, including two recombinant monoclonal antibodies produced from Chinese Hamster Ovary cells, EG2-hFc and rituximab, polyclonal antibodies purified from human serum, and total glycoproteins from human serum. Combined with the complementary information obtained by sequential digestion from exoglycosidase arrays, this approach allows the detection and identification of multiple N-glycans in these complex biological samples. The reagents, workflow, and Hydrophilic interaction liquid chromatography with fluorescence detection (HILIC-FLD), are simple enough to be implemented into a straightforward user-friendly setup. This improved technology provides a powerful tool in support of rapid advancement of glycan analysis for biopharmaceutical development and biomarker discovery for clinical disease diagnosis

Validation of an automated ultraperformance liquid chromatography IgG N-glycan analytical method applicable to classical galactosaemia

Background: Classical galactosaemia (OMIM #230400) is a rare disorder of carbohydrate metabolism caused by deficiency of the galactose-1-phosphate uridyltransferase enzyme. The pathophysiology of the long-term complications, mainly cognitive, neurological and female fertility problems, remains poorly understood. Current clinical methods of biochemical monitoring lack precision and individualization with an identified need for improved biomarkers for this condition. Methods: We report the development and detailed validation of an automated ultraperformance liquid chromatography N-glycan analytical method of high peak resolution applied to galactose incorporation into human serum IgG. Samples are prepared on 96-well plates and the workflow features rapid glycoprotein denaturation, enzymatic glycan release, glycan purification on solid-supported hydrazide, fluorescent labelling and post-labelling clean-up with solid-phase extraction. Results: This method is shown to be accurate and precise with repeatability (cumulative coefficients of variation) of 2.0 and 8.5%, respectively, for G0/G1 and G0/G2 ratios. Both serum and processed N-glycan samples were found to be stable at room temperature and in freeze–thaw experiments. Conclusions: This high-throughput method of IgG galactose incorporation is robust, affordable and simple. This method is validated with the potential to apply as a biomarker for treatment outcomes for galactosaemia

Predicting physiological imbalance in Holstein dairy cows by three different sets of milk biomarkers

Blood biomarkers may be used to detect physiological imbalance and potential disease. However, blood sampling is difficult and expensive, and not applicable in commercial settings. Instead, individual milk samples are readily available at low cost, can be sampled easily and analysed instantly. The present observational study sampled blood and milk from 234 Holstein dairy cows from experimental herds in six European countries. The objective was to compare the use of three different sets of milk biomarkers for identification of cows in physiological imbalance and thus at risk of developing metabolic or infectious diseases. Random forests was used to predict body energy balance (EBAL), index for physiological imbalance (PI-index) and three clusters differentiating the metabolic status of cows created on basis of concentrations of plasma glucose, β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and serum IGF-1. These three metabolic clusters were interpreted as cows in balance, physiological imbalance and “intermediate cows” with physiological status in between. The three sets of milk biomarkers used for prediction were: milk Fourier transform mid-IR (FT-MIR) spectra, 19 immunoglobulin G (IgG) N-glycans and 8 milk metabolites and enzymes (MME). Blood biomarkers were sampled twice; around 14 days after calving (days in milk (DIM)) and around 35 DIM. MME and FT-MIR were sampled twice weekly 1−50 DIM whereas IgG N-glycan were measured only four times. Performances of EBAL and PI-index predictions were measured by coefficient of determination (R2cv) and root mean squared error (RMSEcv) from leave-one-cow-out cross-validation (cv). For metabolic clusters, performance was measured by sensitivity, specificity and global accuracy from this cross-validation. Best prediction of PI-index was obtained by MME (R2cv = 0.40 (95 % CI: 0.29−0.50) at 14 DIM and 0.35 (0.23−0.44) at 35 DIM) while FT-MIR showed a better performance than MME for prediction of EBAL (R2cv = 0.28 (0.24−0.33) vs 0.21 (0.18−0.25)). Global accuracies of predicting metabolic clusters from MME and FT-MIR were at the same level ranging from 0.54 (95 % CI: 0.39−0.68) to 0.65 (0.55−0.75) for MME and 0.51 (0.37−0.65) to 0.68 (0.53−0.81) for FT-MIR. R2cv and accuracies were lower for IgG N-glycans. In conclusion, neither EBAL nor PI-index were sufficiently well predicted to be used as a management tool for identification of risk cows. MME and FT-MIR may be used to predict the physiological status of the cows, while the use of IgG N-glycans for prediction still needs development. Nevertheless, accuracies need to be improved and a larger training data set is warranted

Hypoxia Alters Epigenetic and N-Glycosylation Profiles of Ovarian and Breast Cancer Cell Lines in-vitro

Background: Glycosylation is one of the most fundamental post-translational modifications. Importantly, glycosylation is altered in many cancers. These alterations have been proven to impact on tumor progression and to promote tumor cell survival. From the literature, it is known that there is a clear link between chemoresistance and hypoxia, hypoxia and epigenetics and more recently glycosylation and epigenetics. Methods and Results: Our objective was to investigate these differential parameters, in an in vitro model of ovarian and breast cancer. Ovarian (A2780, A2780cis, PEO1, PEO4) and triple negative breast cancer (TNBC) (MDA-MB-231 and MDA-MB-436) cells were exposed to differential hypoxic conditions (0.5–2% O2) and compared to normoxia (21% O2). Results demonstrated that in hypoxic conditions some significant changes in glycosylation on the secreted N-glycans from the ovarian and breast cancer cell lines were observed. These included, alterations in oligomannosylated, bisected glycans, glycans with polylactosamine extensions, in branching, galactosylation and sialylation in all cell lines except for PEO1. In general, hypoxia exposed ovarian and TNBC cells also displayed increased epithelial to mesenchymal transition (EMT) and migration, with a greater effect seen in the 0.5% hypoxia exposed samples compared to 1 and 2% hypoxia (p ≤ 0.05). SiRNA transient knock down of GATA2/3 transcription factors resulted in a decrease in the expression of glycosyltransferases ST3GAL4 and MGAT5, which are responsible for sialylation and branching, respectively. Conclusions: These glycan changes are known to be integral to cancer cell survival and metastases, suggesting a possible mechanism of action, linking GATA2 and 3, and invasiveness of both ovarian and TNBC cells in vitro

Abnormal N-glycan fucosylation, galactosylation, and sialylation of IgG in adults with classical galactosemia, influence of dietary galactose intake

Background: Classical galactosemia (CG) (OMIM #230400) is a rare disorder of carbohydrate metabolism, due to deficiency of galactose-1-phosphate uridyltransferase (EC 2.7.7.12). The pathophysiology of the long-term complications, mainly cognitive, neurological, and female infertility remains poorly understood. Objectives: This study investigated (a) the association between specific IgG N-glycosylation biomarkers (glycan peaks and grouped traits) and CG patients (n = 95) identified from the GalNet Network, using hydrophilic interaction ultraperformance liquid chromatography and (b) a further analysis of a GALT c.563A-G/p.Gln188Arg homozygous cohort (n = 49) with correlation with glycan features with patient Full Scale Intelligence Quotient (FSIQ), and (c) with galactose intake. Results: A very significant decrease in galactosylation and sialylation and an increase in core fucosylation was noted in CG patients vs controls (P < .005). Bisected glycans were decreased in the severe GALT c.563A-G/p.Gln188Arg homozygous cohort (n = 49) (P < .05). Logistic regression models incorporating IgG glycan traits distinguished CG patients from controls. Incremental dietary galactose intake correlated positively with FSIQ for the p.Gln188Arg homozygous CG cohort (P < .005) for a dietary galactose intake of 500 to 1000 mg/d. Significant improvements in profiles with increased galactose intake were noted for monosialylated, monogalactosylated, and monoantennary glycans. Conclusion: These results suggest that N-glycosylation abnormalities persist in CG patients on dietary galactose restriction which may be modifiable to a degree by dietary galactose intake