18 research outputs found
Changes to serum sample tube and processing methodology does not cause inter-individual variation in automated whole serum N-glycan profiling in health and disease
Serum N-glycans have been identified as putative biomarkers for numerous diseases. The impact of different serum sample tubes and processing methods on N-glycan analysis has received relatively little attention. This study aimed to determine the effect of different sample tubes and processing methods on the whole serum N-glycan profile in both health and disease. A secondary objective was to describe a robot automated N-glycan release, labeling and cleanup process for use in a biomarker discovery system.25 patients with active and quiescent inflammatory bowel disease and controls had three different serum sample tubes taken at the same draw. Two different processing methods were used for three types of tube (with and without gel-separation medium). Samples were randomised and processed in a blinded fashion. Whole serum N-glycan release, 2-aminobenzamide labeling and cleanup was automated using a Hamilton Microlab STARlet Liquid Handling robot. Samples were analysed using a hydrophilic interaction liquid chromatography/ethylene bridged hybrid(BEH) column on an ultra-high performance liquid chromatography instrument. Data were analysed quantitatively by pairwise correlation and hierarchical clustering using the area under each chromatogram peak. Qualitatively, a blinded assessor attempted to match chromatograms to each individual.There was small intra-individual variation in serum N-glycan profiles from samples collected using different sample processing methods. Intra-individual correlation coefficients were between 0.99 and 1. Unsupervised hierarchical clustering and principal coordinate analyses accurately matched samples from the same individual. Qualitative analysis demonstrated good chromatogram overlay and a blinded assessor was able to accurately match individuals based on chromatogram profile, regardless of disease status.The three different serum sample tubes processed using the described methods cause minimal inter-individual variation in serum whole N-glycan profile when processed using an automated workstream. This has important implications for N-glycan biomarker discovery studies using different serum processing standard operating procedures
Towards automation of glycomic profiling of complex biological materials
Glycosylation is considered one of the most complex and structurally diverse post-translational modifications of proteins. Glycans play important roles in many biological processes such as protein folding, regulation of protein stability, solubility and serum half-life. One of the ways to study glycosylation is systematic structural characterizations of protein glycosylation utilizing glycomics methodology based around mass spectrometry (MS). The most prevalent bottleneck stages for glycomic analyses is laborious sample preparation steps. Therefore, in this study, we aim to improve sample preparations by automation. We recently demonstrated the successful application of an automated high-throughput (HT), glycan permethylation protocol based on 96-well microplates, in the analysis of purified glycoproteins. Therefore, we wanted to test if these developed HT methodologies could be applied to more complex biological starting materials. Our automated 96-well-plate based permethylation method showed very comparable results with established glycomic methodology. Very similar glycomic profiles were obtained for complex glycoprotein/protein mixtures derived from heterogeneous mouse tissues. Automated N-glycan release, enrichment and automated permethylation of samples proved to be convenient, robust and reliable. Therefore we conclude that these automated procedures are a step forward towards the development of a fully automated, fast and reliable glycomic profiling system for analysis of complex biological materials
Correction: changes to serum sample tube and processing methodology does not cause inter-individual variation in automated whole serum N-glycan profiling in health and disease.
ix+ 1-24 hlm.; 29,5 c
Automated High-Throughput Permethylation for Glycosylation Analysis of Biologics Using MALDI-TOF-MS
Monitoring
glycoprotein therapeutics for changes in glycosylation
throughout the drug’s life cycle is vital, as glycans significantly
modulate the stability, biological activity, serum half-life, safety,
and immunogenicity. Biopharma companies are increasingly adopting
Quality by Design (QbD) frameworks for measuring, optimizing, and
controlling drug glycosylation. Permethylation of glycans prior to
analysis by matrix-assisted laser desorption/ionization time-of-flight
mass spectrometry (MALDI-TOF-MS) is a valuable tool for glycan characterization
and for screening of large numbers of samples in QbD drug realization.
However, the existing protocols for manual permethylation and liquid–liquid
extraction (LLE) steps are labor intensive and are thus not practical
for high-throughput (HT) studies. Here we present a glycan permethylation
protocol, based on 96-well microplates, that has been developed into
a kit suitable for HT work. The workflow is largely automated using
a liquid handling robot and includes N-glycan release, enrichment
of N-glycans, permethylation, and LLE. The kit has been validated
according to industry analytical performance guidelines and applied
to characterize biopharmaceutical samples, including IgG4 monoclonal
antibodies (mAbs) and recombinant human erythropoietin (rhEPO). The
HT permethylation enabled glycan characterization and relative quantitation
with minimal side reactions: the MALDI-TOF-MS profiles obtained were
in good agreement with hydrophilic liquid interaction chromatography
(HILIC) and ultrahigh performance liquid chromatography (UHPLC) data.
Automated permethylation and extraction of 96 glycan samples was achieved
in less than 5 h and automated data acquisition on MALDI-TOF-MS took
on average less than 1 min per sample. This automated and HT glycan
preparation and permethylation showed to be convenient, fast, and
reliable and can be applied for drug glycan profiling and clinical
glycan biomarker studies
Correction: Changes to Serum Sample Tube and Processing Methodology Does Not Cause Inter-Individual Variation in Automated Whole Serum N-Glycan Profiling in Health and Disease
Correction: changes to serum sample tube and processing methodology does not cause inter-individual variation in automated whole serum N-glycan profiling in health and disease.
Mo1764 – Serum N-Glycomic Biomarkers Predict Treatment Escalation in Inflammatory Bowel Disease
Serum Tube types and Processing methods (RT = Room Temperature).
<p>Serum Tube types and Processing methods (RT = Room Temperature).</p
Qualitative matching of chromatograms.
<p>Samples that failed to be matched correctly are highlighted in italics. NGal: Profile similar to normal human gamma globulin; HGal: Higher galactosylation; MHGal: Much higher galactosylation; LGal: Lower galactosylation; MLGal: Much lower galactosylation CD: Crohn’s disease; UC: Ulcerative colitis; SC: Symptomatic control.</p><p>Qualitative matching of chromatograms.</p