Efficient and accurate glycopeptide identification pipeline for high-throughput site-specific N-glycosylation analysis.
Study of site-specific N-glycosylation in complex sample remains a huge analytical challenge because protein glycosylation is structurally diverse in post-translational modifications, resulting in an intricacy of N-glycopeptides. Here we have developed a novel approach for high-throughput N-glycopeptide profiling based on a network-centric algorithm for deciphering glycan fragmentation in mass spectrometry. We performed an extensive validation and a high-throughput N-glycosylation study on serum and identified thousands of N-glycopeptide spectra with high confidence. The results revealed a similar level of glycan microheterogeneity to that of conventional glycomics approach on individual proteins and provided the unique in-depth site-specific information that could only be studied through glycopeptide profiling.
Department of Chemistry, Fudan University , 220 Han Dan Road, Shanghai 200433, P. R. China.
Mingqi
M
Liu
Yang
Y
Zhang
Yaohan
Y
Chen
Guoquan
G
Yan
Chengping
C
Shen
Jing
J
Cao
Xinwen
X
Zhou
Xiaohui
X
Liu
Lei
L
Zhang
Huali
H
Shen
Haojie
H
Lu
Fuchu
F
He
Pengyuan
P
Yang
D020816:Amino Acid Motifs; D001798:Blood Proteins / Q000737:chemistry / Q000378:metabolism; D002236:Carbohydrate Conformation; D002240:Carbohydrate Sequence; D006023:Glycoproteins / Q000097:blood / Q000737:chemistry*; D006031:Glycosylation; D006801:Humans; D008969:Molecular Sequence Data; D010449:Peptide Mapping; D011499:Protein Processing, Post-Translational; D053719:Tandem Mass Spectrometry
D001798:Blood Proteins; D006023:Glycoproteins