Evidence map›Paper›PMID 30147434›Full record

ArticleInternational journal of mass spectrometry2018

Mass spectrometric analysis of the N-glycoproteome in statin-treated liver cells with two lectin-independent chemical enrichment methods.

Haopeng Xiao, Ju Eun Hwang, Ronghu Wu

Open access · greenAbstract read
In one paragraph

Article in International journal of mass spectrometry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Haopeng XiaoSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Ju Eun HwangSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Ronghu WuSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
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

Protein N-glycosylation is essential for mammalian cell survival and is well-known to be involved in many biological processes. Aberrant glycosylation is directly related to human disease including cancer and infectious diseases. Global analysis of protein N-glycosylation will allow a better understanding of protein functions and cellular activities. Mass spectrometry (MS)-based proteomics provides a unique opportunity to site-specifically characterize protein glycosylation on a large scale. Due to the complexity of biological samples, effective enrichment methods are critical prior to MS analysis. Here, we compared two lectin-independent methods to enrich glycopeptides for the global analysis of protein N-glycosylation by MS. The first boronic acid-based enrichment (BA) method benefits from the universal and reversible interactions between boronic acid and sugars; the other method utilizes metabolic labeling and click chemistry (MC) to incorporate a chemical handle into glycoproteins for future affinity enrichment. We comprehensively compared the performance of the two methods in the identification and quantification of glycoproteins in statin-treated liver cells. Based on the current results, the BA method is more universal in enriching glycopeptides, while with the MC method, cell surface glycoproteins were highly enriched, and the quantification results appear to be more dynamic because only the newly-synthesized glycoproteins were analyzed. In addition, we normalized the glycosylation site ratios by the corresponding parent protein ratios to reflect the real modification changes. In combination with MS-based proteomics, effective enrichment methods will vertically advance protein glycosylation research.

Indexed as

Boronic acid-based enrichmentClick chemistryGlycoproteomicsLC-MS/MSMetabolic labeling

Identifiers

PMID30147434
PMCPMC6103449
OpenAlexW2620305803

What OpenQuestion holds

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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.