Site-specific protein glycosylation analysis with glycan isomer differentiation View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-05

AUTHORS

Serenus Hua, Charles C. Nwosu, John S. Strum, Richard R. Seipert, Hyun Joo An, Angela M. Zivkovic, J. Bruce German, Carlito B. Lebrilla

ABSTRACT

Glycosylation is one of the most common yet diverse post-translational modifications. Information on glycan heterogeneity and glycosite occupancy is increasingly recognized as crucial to understanding glycoprotein structure and function. Yet, no approach currently exists with which to holistically consider both the proteomic and glycomic aspects of a system. Here, we developed a novel method of comprehensive glycosite profiling using nanoflow liquid chromatography/mass spectrometry (nano-LC/MS) that shows glycan isomer-specific differentiation on specific sites. Glycoproteins were digested by controlled non-specific proteolysis in order to produce informative glycopeptides. High-resolution, isomer-sensitive chromatographic separation of the glycopeptides was achieved using microfluidic chip-based capillaries packed with graphitized carbon. Integrated LC/MS/MS not only confirmed glycopeptide composition but also differentiated glycan and peptide isomers and yielded structural information on both the glycan and peptide moieties. Our analysis identified at least 13 distinct glycans (including isomers) corresponding to five compositions at the single N-glycosylation site on bovine ribonuclease B, 59 distinct glycans at five N-glycosylation sites on bovine lactoferrin, 13 distinct glycans at one N-glycosylation site on four subclasses of human immunoglobulin G, and 20 distinct glycans at five O-glycosylation sites on bovine κ-casein. Porous graphitized carbon provided effective separation of glycopeptide isomers. The integration of nano-LC with MS and MS/MS of non-specifically cleaved glycopeptides allows quantitative, isomer-sensitive, and site-specific glycoprotein analysis. More... »

PAGES

1291-1302

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00216-011-5109-x

DOI

http://dx.doi.org/10.1007/s00216-011-5109-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026520208

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21647803


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00216-011-5109-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00216-011-5109-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00216-011-5109-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00216-011-5109-x'


 

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