GlycoPep MassList: software to generate massive inclusion lists for glycopeptide analyses.
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.
Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Wenting
W
Hu
Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Xiaomeng
X
Su
Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Zhikai
Z
Zhu
Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Eden P
EP
Go
Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA. hdesaire@ku.edu.
Heather
H
Desaire
D002853:Chromatography, Liquid; D006020:Glycopeptides / Q000032:analysis*; D012984:Software; D053719:Tandem Mass Spectrometry
D006020:Glycopeptides
Data-dependent acquisition; Glycopeptide analysis; LC-MS/MS; N-linked glycosylation; Software tool