Literature DB >> 32809798

Mass Spectrometric Method for the Unambiguous Profiling of Cellular Dynamic Glycosylation.

Asif Shajahan1, Nitin T Supekar1, Han Wu2, Amberlyn M Wands2, Ganapati Bhat1, Aravind Kalimurthy1, Masaaki Matsubara1, Rene Ranzinger1, Jennifer J Kohler2, Parastoo Azadi1.   

Abstract

Various biological processes at the cellular level are regulated by glycosylation which is a highly microheterogeneous post-translational modification (PTM) on proteins and lipids. The dynamic nature of glycosylation can be studied through metabolic incorporation of non-natural sugars into glycan epitopes and their detection using bio-orthogonal probes. However, this approach possesses a significant drawback due to nonspecific background reactions and ambiguity of non-natural sugar metabolism. Here, we report a probe-free strategy for their direct detection by glycoproteomics and glycomics using mass spectrometry (MS). The method dramatically simplifies the detection of non-natural functional group bearing monosaccharides installed through promiscuous sialic acid, N-acetyl-d-galactosamine (GalNAc) and N-acetyl-d-glucosamine (GlcNAc) biosynthetic pathways. Multistage enrichment of glycoproteins by cellular fractionation, subsequent ZIC-HILIC (zwitterionic-hydrophilic interaction chromatography) based glycopeptide enrichment, and a spectral enrichment algorithm for the MS data processing enabled direct detection of non-natural monosaccharides that are incorporated at low abundance on the N/O-glycopeptides along with their natural counterparts. Our approach allowed the detection of both natural and non-natural sugar bearing glycopeptides, N- and O-glycopeptides, differentiation of non-natural monosaccharide types on the glycans and also their incorporation efficiency through quantitation. Through this, we could deduce interconversion of monosaccharides during their processing through glycan salvage pathway and subsequent incorporation into glycan chains. The study of glycosylation dynamics through this method can be conducted in high throughput, as few sample processing steps are involved, enabling understanding of glycosylation dynamics under various external stimuli and thereby could bolster the use of metabolic glycan engineering in glycosylation functional studies.

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Year:  2020        PMID: 32809798      PMCID: PMC8300872          DOI: 10.1021/acschembio.0c00453

Source DB:  PubMed          Journal:  ACS Chem Biol        ISSN: 1554-8929            Impact factor:   5.100


  37 in total

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