Evidence map›Paper›PMID 31025852›Full record

ArticleAnalytical chemistry2019

Surface Glycoproteomic Analysis Reveals That Both Unique and Differential Expression of Surface Glycoproteins Determine the Cell Type.

Suttipong Suttapitugsakul, Lindsey D Ulmer, Chendi Jiang, Fangxu Sun, Ronghu Wu

Open access · greenAbstract read
In one paragraph

Article in Analytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Dynamic profiling of medulloblastoma surfaceome.Acta neuropathologica communications · 2023
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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 1 institution in 1 country.

Suttipong SuttapitugsakulSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.ORCID 0000-0003-1395-835X
Lindsey D UlmerSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.
Chendi JiangSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.
Fangxu SunSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.
Ronghu WuSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.ORCID 0000-0001-9493-9462
Georgia Institute of Technology · US

Funding

Effective MS-Based Methods for Unraveling Cell Surface Protein InteractionsR01GM118803 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI WU, RONGHU · 2017 to 2024
$2.4M
NIGMS NIH HHS R01 GM118803
6 · The paper itself

Abstract

Proteins on the cell surface are frequently glycosylated, and they are essential for cells. Surface glycoproteins regulate nearly every extracellular event, but compared with global analysis of proteins, comprehensive and site-specific analysis of surface glycoproteins is much more challenging and dramatically understudied. Here, combining metabolic labeling, click-chemistry and enzymatic reactions, and mass spectrometry-based proteomics, we globally characterized surface glycoproteins from eight popular types of human cells. This integrative and effective method allowed for the identification of 2172 N-glycosylation sites and 1047 surface glycoproteins. The distribution and occurrence of N-glycosylation sites were systematically investigated, and protein secondary structures were found to have a dramatic influence on glycosylation sites. As expected, most sites are located on disordered regions. For the sites with the motif N-!P-C, about one-third of them are located on helix structures, while those with the motif N-!P-S/T prefer strand structures. There is almost no correlation between the number of glycosylation sites and protein length, but the number of sites corresponds well with the frequencies of the motif. Quantification results reveal that besides cell-specific glycoproteins, the uniqueness of each cell type further arises from differential expression of surface glycoproteins. The current research indicates that multiple surface glycoproteins including their abundances need to be considered for cell classification rather than a single cluster of differentiation (CD) protein normally used in conventional methods. These results provide valuable information to the glycoscience and biomedical communities and aid in the discovery of surface glycoproteins as disease biomarkers and drug targets.

Indexed as

Amino Acid MotifsAntigens, CDBiotinCell Line, TumorCell SeparationClick ChemistryGlycosylationHumansMass SpectrometryMembrane GlycoproteinsPeptide-N4-(N-acetyl-beta-glucosaminyl) Asparagine AmidaseProtein Structure, SecondaryProteomicsAntigens, CDBiotinMembrane GlycoproteinsPeptide-N4-(N-acetyl-beta-glucosaminyl) Asparagine Amidase

Identifiers

PMID31025852
PMCPMC6584960
OpenAlexW2940636649

What OpenQuestion holds

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Registered trials

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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.