Evidence map›Paper›PMID 27614974›Full record

ArticleAnalytical and bioanalytical chemistry2017

GlycoPep MassList: software to generate massive inclusion lists for glycopeptide analyses.

Wenting Hu, Xiaomeng Su, Zhikai Zhu, Eden P Go, Heather Desaire

Abstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2017. 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
0.9field-weighted citation impact, top 23% 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

5 authors at 1 institution in 1 country.

Wenting HuDepartment of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Xiaomeng SuDepartment of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Zhikai ZhuDepartment of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Eden P GoDepartment of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Heather DesaireDepartment of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA. hdesaire@ku.edu.
University of Kansas · US

Funding

Development of a rapid glycosylation profiling system using mass spectrometry datR01GM103547 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI DESAIRE, HEATHER R · 2012 to 2017
$1.8M
NIGMS NIH HHS R01 GM103547
6 · The paper itself

Abstract

Protein glycosylation drives many biological processes and serves as markers for disease; therefore, the development of tools to study glycosylation is an essential and growing area of research. Mass spectrometry can be used to identify both the glycans of interest and the glycosylation sites to which those glycans are attached, when proteins are proteolytically digested and their glycopeptides are analyzed by a combination of high-resolution mass spectrometry (MS) and tandem mass spectrometry (MS/MS) methods. One major challenge in these experiments is collecting the requisite MS/MS data. The digested glycopeptides are often present in complex mixtures and in low abundance, and the most commonly used approach to collect MS/MS data on these species is data-dependent acquisition (DDA), where only the most intense precursor ions trigger MS/MS. DDA results in limited glycopeptide coverage. Semi-targeted data acquisition is an alternative experimental approach that can alleviate this difficulty. However, due to the massive heterogeneity of glycopeptides, it is not obvious how to expediently generate inclusion lists for these types of analyses. To solve this problem, we developed the software tool GlycoPep MassList, which can be used to generate inclusion lists for liquid chromatography tandem-mass spectrometry (LC-MS/MS) experiments. The utility of the software was tested by conducting comparisons between semi-targeted and untargeted data-dependent analysis experiments on a variety of proteins, including IgG, a protein whose glycosylation must be characterized during its production as a biotherapeutic. When the GlycoPep MassList software was used to generate inclusion lists for LC-MS/MS experiments, more unique glycopeptides were selected for fragmentation. Generally, ∼30 % more unique glycopeptides can be analyzed per protein, in the simplest cases, with low background. In cases where background ions from proteins or other interferents are high, usage of an inclusion list is even more advantageous. The software is freely publically accessible. Graphical abstract Software increases the number of glycopeptides that get selected for MS/MS analysis.

Indexed as

SoftwareChromatography, LiquidGlycopeptidesTandem Mass SpectrometryGlycopeptidesData-dependent acquisitionGlycopeptide analysisLC-MS/MSN-linked glycosylationSoftware tool

Identifiers

PMID27614974
PMCPMC5521198
OpenAlexW2507343170

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.