Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics

peer-reviewed · Nature Communications · 2023

peer-reviewed · Nature Communications · 2023. Weiping Sun et al. Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact…
Date 2023-07-08
Type peer-reviewed
Venue Nature Communications
Publisher Springer Science and Business Media LLC
Contribution adjacent
DOI 10.1038/s41467-023-39699-5
Citations (OpenAlex) 58
Venue 2-year citedness 17.60

Abstract

Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact glycopeptides from mass spectrometry data. GlycanFinder integrates peptide-based and glycan-based search strategies to address the challenge of complex fragmentation of glycopeptides. A deep learning model is designed to capture glycan tree structures and their fragment ions for de novo sequencing of glycans that do not exist in the database. We performed extensive analyses to validate the false discovery rates (FDRs) at both peptide and glycan levels and to evaluate GlycanFinder based on comprehensive benchmarks from previous community-based studies. Our results show that GlycanFinder achieved comparable performance to other leading glycoproteomics softwares in terms of both FDR control and the number of identifications. Moreover, GlycanFinder was also able to identify glycopeptides not found in existing databases. Finally, we conducted a mass spectrometry experiment for antibody N-linked glycosylation profiling that could distinguish isomeric peptides and glycans in four immunoglobulin G subclasses, which had been a challenging problem to previous studies.

Authors

  1. Weiping Sun · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University
  2. Qianqiu Zhang · University of Waterloo
  3. Xiyue Zhang · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc.
  4. Ngoc Hieu Tran · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., University of Waterloo
  5. M. Ziaur Rahman · Bioinformatics Solutions Inc., University of Waterloo
  6. Zheng Chen · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc.
  7. Chao Peng · Baizhen Biotechnologies Inc.
  8. Jun Ma · Bioinformatics Solutions Inc.
  9. Ming Li · Bioinformatics Solutions Inc., Central China Institute of Artificial Intelligence, Peng Cheng Laboratory, University of Waterloo, University of Western Ontario
  10. Lei Xin · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University
  11. Baozhen Shan · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University

Methods and tools

Data used

  • Antibody N-linked glycosylation profiling with PEAKS GlycanFinder (as deposited) · PXD039787
  • Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies for Glycopeptid (as deposited) · PXD024101
  • Mouse glycoproteome - pGlyco 2 (as deposited) · PXD005555
  • Mouse glycoproteome - pGlyco 2 (PXD005553) (as deposited) · PXD005553
  • Mouse glycoproteome: Brain - pGlyco 2 (as deposited) · PXD005411
  • Mouse glycoproteome: Heart - pGlyco 2 (as deposited) · PXD005413
  • Mouse glycoproteome: Kidney - pGlyco 2 (as deposited) · PXD005412
  • Yeast glycoproteome - pGlyco 2 (as deposited) · PXD005565

Cites (4)

Cited by (3)

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