Multi-Glycomics Platform Approach for Cancer

Diseases as diverse as infection and cancer are known to involve changes in glycosylation. Therefore, systematic approach to monitor glycosylation based on specific glycan types are necessary for reliable biomarker discovery and better understanding of biological function implicated with glycans. In this study, we developed the method to enrich a specific class of glycans such as mannose and sialic acid and monitor the changes in cancers. Several glycans are identified as cancer specific

A versatile and scalable strategy for glycoprofiling bifidobacterial consumption of human milk oligosaccharides.

Human milk contains approximately 200 complex oligosaccharides believed to stimulate the growth and establishment of a protective microbiota in the infant gut. The lack of scalable analytical techniques has hindered the measurement of bacterial metabolism of these and other complex prebiotic oligosaccharides. An in vitro, multi-strain, assay capable of measuring kinetics of bacterial growth and detailed oligosaccharide consumption analysis by FTICR-MS was developed and tested simultaneously on 12 bifidobacterial strains. For quantitative consumption, deuterated and reduced human milk oligosaccharide (HMO) standards were used. A custom software suite developed in house called Glycolyzer was used to process the large amounts of oligosaccharide mass spectra automatically with (13)C corrections based on de-isotoping protocols. High growth on HMOs was characteristic of Bifidobacterium longum biovar infantis strains, which consumed nearly all available substrates, while other bifidobacterial strains tested, B. longum bv. longum, B. adolescentis, B. breve and B. bifidum, showed low or only moderate growth ability. Total oligosaccharide consumption ranged from a high of 87% for B. infantis JCM 7009 to only 12% for B. adolescentis ATCC 15703. A detailed analysis of consumption glycoprofiles indicated strain-specific capabilities towards differential metabolism of milk oligosaccharides. This method overcomes previous limitations in the quantitative, multi-strain analysis of bacterial metabolism of HMOs and represents a novel approach towards understanding bacterial consumption of complex prebiotic oligosaccharides

Automated Assignments of N- and O‑Site Specific Glycosylation with Extensive Glycan Heterogeneity of Glycoprotein Mixtures

Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles

Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data

Motivation: The development of better tests to detect cancer in its earliest stages is one of the most sought-after goals in medicine. Especially important are minimally invasive tests that require only blood or urine samples. By profiling oligosaccharides cleaved from glycosylated proteins shed by tumor cells into the blood stream, we hope to determine glycan profiles that will help identify cancer patients using a simple blood test. The data in this article were generated using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI FT-ICR MS). We have developed novel methods for analyzing this type of mass spectrometry data and applied it to eight datasets from three different types of cancer (breast, ovarian and prostate)

Improving <i>N</i>‑Glycan Coverage using HPLC-MS with Electrospray Ionization at Subambient Pressure

Human serum glycan profiling with mass spectrometry (MS) has been employed to study several disease conditions and is demonstrating promise in, for example, clinical biomarker discovery. However, the low glycan ionization efficiency and the large dynamic range of glycan concentrations in human sera can hinder comprehensive profiling. In particular, large glycans are problematic because they are present at low concentrations and are prone to fragmentation. Here we show that, following liquid chromatographic separation on graphite columns, subambient pressure ionization with nanoelectrospray (SPIN)-MS can expand the serum glycome profile in comparison with the conventional atmospheric pressure electrospray ionization (ESI)-MS with a heated capillary inlet. Notably, the ions generated by the SPIN interface were observed at higher charge states for approximately half of the annotated glycans. Out of a total of 130 detected glycans, 34 were only detected with the SPIN-MS, resulting in improved coverage of glycan families as well as of glycans with larger numbers of labile monosaccharides