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Sequential fragment ion filtering and endoglycosidase-assisted identification of intact glycopeptides

Overview of attention for article published in Analytical & Bioanalytical Chemistry, March 2017
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Title
Sequential fragment ion filtering and endoglycosidase-assisted identification of intact glycopeptides
Published in
Analytical & Bioanalytical Chemistry, March 2017
DOI 10.1007/s00216-017-0195-z
Pubmed ID
Authors

Zixiang Yu, Xinyuan Zhao, Fang Tian, Yang Zhao, Yong Zhang, Yi Huang, Xiaohong Qian, Wantao Ying

Abstract

Detailed characterization of glycoprotein structures requires determining both the sites of glycosylation as well as the glycan structures associated with each site. In this work, we developed an analytical strategy for characterization of intact N-glycopeptides in complex proteome samples. In the first step, tryptic glycopeptides were enriched using ZIC-HILIC. Secondly, a portion of the glycopeptides was treated with endoglycosidase H (Endo H) to remove high-mannose (Man) and hybrid N-linked glycans. Thirdly, a fraction of the Endo H-treated glycopeptides was further subjected to PNGase F treatment in (18)O water to remove the remaining complex glycans. The intact glycopeptides and deglycosylated peptides were analyzed by nano-RPLC-MS/MS, and the glycan structures and the peptide sequences were identified by using the Byonic or pFind tools. Sequential digestion by endoglycosidase provided candidate glycosites information and indication of the glycoforms on each glycopeptide, thus helping to confine the database search space and improve the confidence regarding intact glycopeptide identification. We demonstrated the effectiveness of this approach using RNase B and IgG and applied this sequential digestion strategy for the identification of glycopeptides from the HepG2 cell line. We identified 4514 intact glycopeptides coming from 947 glycosites and 1011 unique peptide sequences from HepG2 cells. The intensity of different glycoforms at a specific glycosite was obtained to reach the occupancy ratios of site-specific glycoforms. These results indicate that our method can be used for characterizing site-specific protein glycosylation in complex samples. Graphical abstract Through integrating the information of intact glycopeptide, fragment ions filters and endoglycosidase digestion, the reliability of the identification could be significantly improved. We quantified the site-specific glycoforms occupancy ratios through the MS response signaling of each glycopeptide at the same time.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Other 2 14%
Unspecified 1 7%
Student > Master 1 7%
Researcher 1 7%
Other 1 7%
Unknown 3 21%
Readers by discipline Count As %
Chemistry 3 21%
Biochemistry, Genetics and Molecular Biology 2 14%
Unspecified 1 7%
Agricultural and Biological Sciences 1 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Other 2 14%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 April 2017.
All research outputs
#14,918,049
of 25,382,440 outputs
Outputs from Analytical & Bioanalytical Chemistry
#4,450
of 9,619 outputs
Outputs of similar age
#169,110
of 323,707 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#31
of 158 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 52% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 323,707 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.