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Zijlstra, F.

Publications and source records attributed to Zijlstra, F..

2 recordsLinked to original sources

The GlycoPaSER prototype as a real-time N-glycopeptide identification tool based on the PaSER parallel computing platform

Real-time database searching allows for simpler and automated proteomics workflows as it eliminates technical bottlenecks in high throughput experiments. Most importantly, it enables results dependent acquisition (RDA) where search results can be used to guide data acquisition during acquisition. This is especially beneficial for glycoproteomics since the wide range of physicochemical properties of glycopeptides lead to a wide range of optimal acquisition parameters. We established here the GlycoPaSER prototype by extending the Parallel Search Engine in Real-time (PaSER) functionality for real-time glycopeptide identification from fragmentation spectra. Glycopeptide fragmentation spectra were decomposed into peptide- and glycan-moiety spectra using common N-glycan fragments. Each moiety was subsequently identified by a specialized algorithm running in real-time. GlycoPaSER can keep up with the rate of data acquisition for real-time analysis with similar performance to other glycoproteomics software and produces results that are in line with literature reference data. The GlycoPaSER prototype presented here provides the first proof-of-concept for real-time glycopeptide identification that unlocks future development of RDA technology to transcend data acquisition.

bioinformatics↗

Plasma glycoproteomics delivers high-specificity disease biomarkers by detecting site-specific glycosylation abnormalities

The human plasma glycoproteome holds enormous potential to identify personalized biomarkers to diagnose and understand disease. Recent advances in mass spectrometry and software development are opening novel avenues to mine the glycoproteome for protein- and site-specific glycosylation changes. Here, we describe a novel plasma N-glycoproteomics method for disease diagnosis and evaluated its clinical applicability by performing comparative glycoproteomics in blood plasma of 40 controls and a cohort of 74 patients with 13 different genetic diseases that directly impact the protein N-glycosylation pathway. The plasma glycoproteome yielded high-specificity biomarker signatures for each of the individual genetic defects. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and in specific diseases by protein-intrinsic factors. Our work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the mechanisms underlying human disease.

molecular biology↗