High-Throughput Analysis and Automation for Glycomics Studies

Abstract

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics-for example in Genome Wide Association Studies-to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

Keywords: Analysis; Automation; Derivatization; Glycomics; High-throughput; Integration.

Fig. 1

2-AB-labeled A3 glycan standard from Ludger (CAB-A3-01) was analyzed by UPLC and MALDI–TOF–MS after ethyl esterification. a Overnight incubation at 37 °C of Ludger 2-AB-labeled A3 standard with buffer (red), α(2,3)-sialidase (green), α(2,3/6/8)-sialidase (blue), α(2,3/6/8)-sialidase + β(1,4)-galactosidase (orange). Separation was performed on a Waters Acquity UPLC H-class system using an Acquity BEH 1.7 µm 2.1 × 150 mm glycan column. b Linkage-specific assignment of the undigested UPLC data [100]. c MALDI–TOF–MS spectrum of the 2-AB-labeled A3 standard ([M + Na]⁺) after 1 h of ethyl esterification with EDC and HOBt at 37 °C and subsequent HILIC purification according to Reiding et al. [43]. Profiles obtained from both methods are highly comparable and show similar ratios with regard to sialic acid occupancy and linkage. HILIC peak assignments are based on the exoglycosidase digests, as well as use of internal standards. Structural schemes of glycans are depicted following the CFG notation: N-acetylglucosamine (blue square), fucose (red triangle), mannose (green circle), galactose (yellow circle), N-acetylneuraminic acid (purple diamond). Known N-acetylneuraminic acid linkages are indicated by a left angle (α2,3) or right angle (α2,6), and otherwise unspecified

Fig. 2

MALDI–TOF–MS spectrum of the ¹²C and ¹³C permethylated human-IgG N-glycan standards from Ludger (Cat# Cpm13C-IgG-01 and Cpm¹²C-IgG-01). ¹³C was spiked with ¹²C on the same sample spot to showcase the comparison of relative quantities of the major IgG N-glycans. The mass values shown in the spectra are [M + Na]⁺ of permethylated glycans, with ¹³C permethylated masses in parentheses

Fig. 3

a Workflow depicting validation study of semi-automated sample preparation of 48 replicates of human IgG samples, comprising digestion by PNGase F, 2-AB-labeling, HILIC SPE enrichment and preparation of samples for injection onto UHPLC performed with Hamilton Starlet liquid handling robot [73, 101, 102]. b Typical UHPLC chromatogram of 2-AB-labeled human IgG glycans prepared using the robot. Analysis of the data from these 48 samples showed CVs less than 5 % for all major peaks. The data shows that the automated, high-throughput method is repeatable. The liquid handling robot allows for fast, reliable and robust analyses of glycans. Glycan peaks in the chromatogram were assigned by exoglycosidase digestion, standard inclusion, and literature [103]