Comparative analysis of glycoproteomic software using a tailored glycan database.

Abstract

Glycoproteomics is a rapidly developing field, and data analysis has been stimulated by several technological innovations. As a result, there are many software tools from which to choose; and each comes with unique features that can be difficult to compare. This work presents a head-to-head comparison of five modern analytical software: Byonic, Protein Prospector, MSFraggerGlyco, pGlyco3, and GlycoDecipher. To enable a meaningful comparison, parameter variables were minimized. One potential confounding variable is the glycan database that informs glycoproteomic searches. We performed glycomic profiling of the samples and used the output to construct matched glycan databases for each software. Up to 17,000 glycopeptide spectra were identified across three replicates of wild-type SH-SY5Y cells. There was overlap among all software for glycoproteins identified, locations of glycosites, and glycans; but there was no clear winner. Incorporation of several comparative criteria was critically important for learning the most information in this study and should be used more broadly when assessing software. A single criterion, such as number of glycopeptide spectra found, is not sufficient. We present evidence that suggests Byonic reports many spurious results at the glycoprotein and glycosite level. Overall, our results indicate that glycoproteomic searches should involve more than one software, excluding the current version of Byonic, to generate confidence by consensus. It may be useful to consider software with peptide-first approaches and with glycan-first approaches.