Evidence map›Paper›PMID 20571061›Full record

ArticleMolecular & cellular proteomics : MCP2010

Sialic acid-focused quantitative mouse serum glycoproteomics by multiple reaction monitoring assay.

Masaki Kurogochi, Takahiko Matsushista, Maho Amano, Jun-ichi Furukawa, Yasuro Shinohara, Masato Aoshima, Shin-Ichiro Nishimura

Open access · hybridAbstract readEvaluation Study
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
6.2field-weighted citation impact, top 3% 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

42 citing papers in PubMed, 86 citations in OpenAlex.

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  17. Chemical Glycoproteomics.Chemical reviews · 2016
    Review
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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

7 authors at 1 institution in 1 country.

Masaki KurogochiGraduate School of Life Science, Frontier Research Center for the Post-Genomic Science and Technology, Hokkaido University, Kita-ku, Sapporo, Japan.
Takahiko Matsushista
Maho Amano
Jun-ichi Furukawa
Yasuro Shinohara
Masato Aoshima
Shin-Ichiro Nishimura
Hokkaido University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite increasing importance of protein glycosylation, most of the large-scale glycoproteomics have been limited to profiling the sites of N-glycosylation. However, in-depth knowledge of protein glycosylation to uncover functions and their clinical applications requires quantitative glycoproteomics eliciting both peptide and glycan sequences concurrently. Here we describe a novel strategy for the multiplexed quantitative mouse serum glycoproteomics based on a specific chemical ligation, namely, reverse glycoblotting technique, focusing sialic acids and multiple reaction monitoring (MRM). LC-MS/MS analysis of de-glycosylated peptides identified 270 mouse serum peptides (95 glycoproteins) as sialylated glycopeptides, of which 67 glycopeptides were fully characterized by MS/MS analyses in a straightforward manner. We revealed the importance of a fragment ion containing innermost N-acetylglucosamine (GlcNAc) residue as MRM transitions regardless the sequence of the peptides. Versatility of the reverse glycoblotting-assisted MRM assays was demonstrated by quantitative comparison of 25 targeted glycopeptides from 16 proteins between mice with homo and hetero types of diabetes disease model.

Indexed as

Amino Acid SequenceAnimalsCarbohydrate ConformationCarbohydrate SequenceChromatography, LiquidDiabetes MellitusDisease Models, AnimalFemaleGlycopeptidesGlycosylationMaleMass SpectrometryMiceMice, Inbred C57BLMolecular Sequence DataN-Acetylneuraminic AcidGlycopeptidesN-Acetylneuraminic Acid

Identifiers

PMID20571061
PMCPMC2984228
OpenAlexW2121049676

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.