An N-glycopeptide MS/MS data analysis workflow leveraging two complementary glycoproteomic software tools for more confident identification and assignments.
Proteomics
; : e2300143, 2023 Jun 04.
Article
in English
| MEDLINE | ID: covidwho-20238282
ABSTRACT
Complete coverage of all N-glycosylation sites on the SARS-CoV2 spike protein would require the use of multiple proteases in addition to trypsin. Subsequent identification of the resulting glycopeptides by searching against database often introduces assignment errors due to similar mass differences between different permutations of amino acids and glycosyl residues. By manually interpreting the individual MS2 spectra, we report here the common sources of errors in assignment, especially those introduced by the use of chymotrypsin. We show that by applying a stringent threshold of acceptance, erroneous assignment by the commonly used Byonic software can be controlled within 15%, which can be reduced further if only those also confidently identified by a different search engine, pGlyco3, were considered. A representative site-specific N-glycosylation pattern could be constructed based on quantifying only the overlapping subset of N-glycopeptides identified at higher confidence. Applying the two complimentary glycoproteomic software in a concerted data analysis workflow, we found and confirmed that glycosylation at several sites of an unstable Omicron spike protein differed significantly from those of the stable trimeric product of the parental D614G variant.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Experimental Studies
Topics:
Variants
Language:
English
Journal:
Proteomics
Journal subject:
Biochemistry
Year:
2023
Document Type:
Article
Affiliation country:
Pmic.202300143
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