pFind Studio: a computational solution for mass spectrometry-based proteomics
2024
NATURE COMMUNICATIONS2024. Klein, Joshua et al.
Program for Bioinformatics, Boston University, Boston, MA, US
ABSTRACT:Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft.
Use: pGlyco; pDeep
CARBOHYDRATE POLYMERS2024. Li, Jun et al.
Laboratory for Disease Glycoproteomics, College of Life Sciences, Northwest University, Xi'an 710069, PR China
ABSTRACT:High-abundance serum proteins, mostly modified by N-glycans, are usually depleted from human sera to achieve in-depth analyses of serum proteome and sub-proteomes. In this study, we show that these high-abundance glycoproteins (HAGPs) can be used as valuable standard glycopeptide resources, as long as the structural features of their glycans have been well defined at the glycosite-specific level. By directly analyzing intact glycopeptides enriched from serum, we identified 1322 unique glycopeptides at 48 N-glycosites from the top 12 HAGPs (19 subclasses). These HAGPs could be further classified into four major groups based on the structural features of their attached N-glycans. Immunoglobins including IGHG1/2/3/4, IGHA1/2 and IGHM were mostly modified by core fucosylated and bisected N-glycans with rarely sialic acids. Alpha-1-acid glycoproteins (ORM1/ 2) and haptoglobins (HP) were mainly modified by tri-and tetra-antennary (40 %) N-glycans with antennafucoses and sialic acids. Complement components C3 and C4A/B were highly modified by oligo-mannose glycans. The other HAGPs including SERPINA1, A2M, TF, FGB/G and APOB mainly contain bi-antennary complex glycans with the common core structure and (sialyl-) LacNAc branch structures. These HAGPs are easily detected by LC-MS analysis and therefore could be used as standard glycopeptides for glycoproteomic methodology studies as well as possible clinical utilities.
Use: pGlyco
Cell Reports Methods2024. TaewookKang et al.
State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, 200031, Shanghai, China
ABSTRACT:
Use: pGlyco
Glycobiology2024. Adams, Trevor M et al.
Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Road, Athens 30602, Georgia
ABSTRACT:Modern glycoproteomics experiments require the use of search engines due to the generation of countless spectra. While these tools are valuable, manual validation of search engine results is often required for detailed analysis of glycopeptides as false-discovery rates are often not reliable for glycopeptide data. Near-isobaric mismatches are a common source of misidentifications for the popular glycopeptide-focused search engine pGlyco3.0, and in this technical note we share a strategy and script that improves the accuracy of the search utilizing two manually validated datasets of the glycoproteins CD16a and HIV-1 Env as proof-of-principle.
Use: pGlyco
Acta Biochimica et Biophysica Sinica2024. Cao, Xinyi et al.
nstitutes of Biomedical Sciences and Shanghai Cancer Center, Fudan University,Shanghai200032, China
ABSTRACT:
Use: pQuant