An integrated strategy for high-sensitive and multi-level glycoproteome analysis from low micrograms of protein samples.
J Chromatogr A
; 1600: 46-54, 2019 Aug 30.
Article
em En
| MEDLINE
| ID: mdl-31036360
Glycosylation, as a biologically important protein post-translational modification, often alters on both glycosites and glycans, simultaneously. However, most of current approaches focused on biased profiling of either glycosites or glycans, and limited by time-consuming process and milligrams of starting protein material. We describe here a simple and integrated spintip-based glycoproteomics technology (termed Glyco-SISPROT) for achieving a comprehensive view of glycoproteome with shorter sample processing time and low microgram starting material. By carefully integrating and optimizing SCX, C18 and Concanavalin A (Con A) packing material and their combination in spintip format, both predigested peptides and protein lysates could be processed by Glyco-SISPROT with high efficiency. More importantly, deglycopeptide, intact glycopeptide and glycans released by multiple glycosidases could be readily collected from the same Glyco-SISPROT workflow for LC-MS analysis. In total, above 1850 glycosites in Ë1770 unique deglycopeptides were characterized from mouse liver by using either 100 µg of predigested peptides or directly using 100 µg of protein lysates, in which about 30% of glycosites were released by both PNGase F and Endos. To the best of our knowledge, this approach should be one of the most comprehensive glycoproteomic approaches by using limited protein starting material. One significant benefit of Glyco-SISPROT is that whole processing time is dramatically reduced from a few days to less than 6 h with good reproducibility when protein lysates were directly processed by Glyco-SISPROT. We expect that this method will be suitable for multi-level glycoproteome analysis of rare biological samples with high sensitivity.
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Base de dados:
MEDLINE
Assunto principal:
Glicoproteínas
/
Proteômica
Tipo de estudo:
Diagnostic_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article