Evidence map›Paper›PMID 33077710›Full record

ArticleNature communications2020

A streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics.

Pan Fang, Yanlong Ji, Ivan Silbern, Carmen Doebele, Momchil Ninov, Christof Lenz, Thomas Oellerich, Kuan-Ting Pan, Henning Urlaub

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

44 citing papers in PubMed, 70 citations in OpenAlex.

  1. Article
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  4. Glycan Sequencing, A Brief Primer.Glycoscience & therapy · 2026
    Article
  5. Review
  6. Review
  7. Article
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  11. Review
  12. Article
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  14. Review
  15. Analytical and bioanalytical chemistry · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Can We BoostJournal of the American Society for Mass Spectrometry · 2024
    Article
  20. 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

9 authors at 3 institutions in 1 country.

Pan FangBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.
Yanlong JiBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.ORCID 0000-0002-9741-5119
Ivan SilbernBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.ORCID 0000-0001-8284-954X
Carmen DoebeleHematology/Oncology, Department of Medicine II, Johann Wolfgang Goethe University, 60590, Frankfurt am Main, Germany.
Momchil NinovBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.ORCID 0000-0002-0808-7003
Christof LenzBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.ORCID 0000-0002-0946-8166
Thomas OellerichHematology/Oncology, Department of Medicine II, Johann Wolfgang Goethe University, 60590, Frankfurt am Main, Germany.
Kuan-Ting PanHematology/Oncology, Department of Medicine II, Johann Wolfgang Goethe University, 60590, Frankfurt am Main, Germany. kuan-ting.pan@kgu.de.ORCID 0000-0001-6974-5324
Henning UrlaubBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany. henning.urlaub@mpibpc.mpg.de.ORCID 0000-0003-1837-5233
Goethe University Frankfurt · DEUniversitätsmedizin Göttingen · DEMax Planck Institute for Biophysical Chemistry · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regulation of protein N-glycosylation is essential in human cells. However, large-scale, accurate, and site-specific quantification of glycosylation is still technically challenging. We here introduce SugarQuant, an integrated mass spectrometry-based pipeline comprising protein aggregation capture (PAC)-based sample preparation, multi-notch MS3 acquisition (Glyco-SPS-MS3) and a data-processing tool (GlycoBinder) that enables confident identification and quantification of intact glycopeptides in complex biological samples. PAC significantly reduces sample-handling time without compromising sensitivity. Glyco-SPS-MS3 combines high-resolution MS2 and MS3 scans, resulting in enhanced reporter signals of isobaric mass tags, improved detection of N-glycopeptide fragments, and lowered interference in multiplexed quantification. GlycoBinder enables streamlined processing of Glyco-SPS-MS3 data, followed by a two-step database search, which increases the identification rates of glycopeptides by 22% compared with conventional strategies. We apply SugarQuant to identify and quantify more than 5,000 unique glycoforms in Burkitt's lymphoma cells, and determine site-specific glycosylation changes that occurred upon inhibition of fucosylation at high confidence.

Indexed as

Burkitt LymphomaGlycopeptidesGlycosylationHumansProteomicsTandem Mass SpectrometryGlycopeptides

Identifiers

PMID33077710
PMCPMC7572468
OpenAlexW3092934995

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.