Evidence map›Paper›PMID 31637569›Full record

ArticleGlycoconjugate journal2019

Glycan size and attachment site location affect electron transfer dissociation (ETD) fragmentation and automated glycopeptide identification.

Kathirvel Alagesan, Hannes Hinneburg, Peter H Seeberger, Daniel Varón Silva, Daniel Kolarich

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Glycoconjugate journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Systems-Wide Site-Specific Analysis of Glycoproteins.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  4. Review
  5. Article
  6. Effective discrimination of gas-phase peptide conformers using TIMS-ECD-ToF MS/MS.Analytical methods : advancing methods and applications · 2021
    Article
  7. Article
  8. Article
  9. The Hitchhiker's guide to glycoproteomics.Biochemical Society transactions · 2021
    Review
  10. Glycoproteomics Technologies in Glycobiotechnology.Advances in biochemical engineering/biotechnology · 2021
    Article
  11. Article
  12. Article
  13. Optimal Dissociation Methods Differ forJournal of proteome research · 2020
    Article
  14. Influence of Protein Glycosylation onFrontiers in microbiology · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Kathirvel AlagesanInstitute for Glycomics, Griffith University, Building G26, Gold Coast Campus, Southport, QLD, 4222, Australia.
Hannes HinneburgDepartment of Biomolecular Systems, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.
Peter H SeebergerDepartment of Biomolecular Systems, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.
Daniel Varón SilvaDepartment of Biomolecular Systems, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.
Daniel KolarichInstitute for Glycomics, Griffith University, Building G26, Gold Coast Campus, Southport, QLD, 4222, Australia. d.kolarich@griffith.edu.au.ORCID 0000-0002-8452-1350
Max Planck Institute of Colloids and Interfaces · DEGriffith University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We established a small synthetic N-glycopeptide library to systematically evaluate the effect of glycosylation site location and glycan size on the efficiency of electron transfer dissociation (ETD) fragmentation and subsequent automated identification. The glycopeptides within this library differed in glycosylation site position and glycan size ranging from the pentasaccharide N-glycan core to fully sialylated, biantennary N-glycans. Factors such as glycan size, glycosylation site position within a glycopeptide and individual precursor m/z all significantly impacted the number and quality of assignable glycopeptide backbone fragments. Generally, high charge/low m/z precursors (>3+) and glycopeptides carrying neutral, smaller N-glycans gave better product ion spectra, while hardly any product ions were detectable for sialylated, triply charged N-glycopeptides. These factors impacted correct glycopeptide identification by proteomics software tools such as SEQUEST or Amanda. A better understanding how glycopeptide physico-chemical properties influence fragmentation will help optimizing fragmentation conditions and generate better data, which will facilitate software assisted glycopeptide data analyses.

Indexed as

ProteomicsAmino Acid SequenceElectronsElectron TransportGlycopeptidesGlycosylationHumansIonsPolysaccharidesSoftwareTandem Mass SpectrometryGlycopeptidesIonsPolysaccharidesElectron transfer dissociationETDGlycopeptideGlycoproteomics

Identifiers

PMID31637569
OpenAlexW2981537839

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.