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[Preprint]. 2024 Jul 25:2024.07.24.604997.
doi: 10.1101/2024.07.24.604997.

"Comparative Analysis of Glycoproteomic Software Using a Tailored Glycan Database"

Reuben A Hogan  1 , Lauren E Pepi  2 , Nicholas M Riley  3 , Robert J Chalkley  1
Affiliations

"Comparative Analysis of Glycoproteomic Software Using a Tailored Glycan Database"

Reuben A Hogan et al. bioRxiv. .

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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 19,000 glycopeptide spectra were identified across three replicates of wild-type SH-SY5Y cells. There was substantial overlap among most software for glycoproteins identified, locations of glycosites, and glycans, although Byonic reported a suspiciously large number of glycoproteins and glycosites of questionable reliability. We show that Protein Prospector identified the most glycopeptide spectrum matches with high agreement to known glycosites in UniProt. Overall, our results indicate that glycoproteomic searches should involve more than one software to generate confidence. It may be useful to consider software with peptide-first approaches and with glycan-first approaches.

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Conflict of interest statement

Competing Interests The authors have no conflicts of interest to declare.

Figures

Figure 1:
Figure 1:. Establishing a Head-to-Head Comparison of Glycoproteomic Softwares.
Using Self-Generated Glycoproteomic Data. (A) Layout of the different softwares. (B) Workflow to generate glycopeptides. (C) Workflow for glycomic profiling.
Figure 1:
Figure 1:. Establishing a Head-to-Head Comparison of Glycoproteomic Softwares.
Using Self-Generated Glycoproteomic Data. (A) Layout of the different softwares. (B) Workflow to generate glycopeptides. (C) Workflow for glycomic profiling.
Figure 1:
Figure 1:. Establishing a Head-to-Head Comparison of Glycoproteomic Softwares.
Using Self-Generated Glycoproteomic Data. (A) Layout of the different softwares. (B) Workflow to generate glycopeptides. (C) Workflow for glycomic profiling.
Figure 2:
Figure 2:. Glycopeptide Spectrum Matches (GPSMs) and Their Overlap.
(A) The number of glycopeptide spectral matches that were identified by each software after filtering. (B) UpSet plot of the scan numbers reported for each GPSM.
Figure 3:
Figure 3:. Protein Prospector Captures More Information Content from the Data.
(A) Table showing the results from each software for peptide AGPNGTLFVADAYK. (B) UpSet plot of the unique protein-site-glycan combination (PSG IDs) by software.
Figure 4:
Figure 4:. Comparison of the Unique Glycoproteins.
(A) UpSet plot of the unique glycoprotein results from each software. (B) This is an example of a unique glycopeptide assignment by Byonic. The peptide Byonic assigns is KGNYSER with glycan HexNAc4Hex5. The peptide comes from HistoneH2A. Protein Prospector assigns this spectrum to an unglycosylated peptide from E3 Ubiquitin-protein ligase UHRF1. (C) Cytoscape network of the common 212 glycoproteins. (D) Functional enrichment for the common glycoproteins.
Figure 4:
Figure 4:. Comparison of the Unique Glycoproteins.
(A) UpSet plot of the unique glycoprotein results from each software. (B) This is an example of a unique glycopeptide assignment by Byonic. The peptide Byonic assigns is KGNYSER with glycan HexNAc4Hex5. The peptide comes from HistoneH2A. Protein Prospector assigns this spectrum to an unglycosylated peptide from E3 Ubiquitin-protein ligase UHRF1. (C) Cytoscape network of the common 212 glycoproteins. (D) Functional enrichment for the common glycoproteins.
Figure 4:
Figure 4:. Comparison of the Unique Glycoproteins.
(A) UpSet plot of the unique glycoprotein results from each software. (B) This is an example of a unique glycopeptide assignment by Byonic. The peptide Byonic assigns is KGNYSER with glycan HexNAc4Hex5. The peptide comes from HistoneH2A. Protein Prospector assigns this spectrum to an unglycosylated peptide from E3 Ubiquitin-protein ligase UHRF1. (C) Cytoscape network of the common 212 glycoproteins. (D) Functional enrichment for the common glycoproteins.
Figure 5:
Figure 5:. Comparison of the Unique Glycosites.
(A) UpSet plot of the unique glycosites by software. (B) Pie Chart for the percentage of proteins with multiple glycosites (C) Percentage of glycosites also reported by UniProt.
Figure 5:
Figure 5:. Comparison of the Unique Glycosites.
(A) UpSet plot of the unique glycosites by software. (B) Pie Chart for the percentage of proteins with multiple glycosites (C) Percentage of glycosites also reported by UniProt.
Figure 5:
Figure 5:. Comparison of the Unique Glycosites.
(A) UpSet plot of the unique glycosites by software. (B) Pie Chart for the percentage of proteins with multiple glycosites (C) Percentage of glycosites also reported by UniProt.
Figure 5:
Figure 5:. Comparison of the Unique Glycosites.
(A) UpSet plot of the unique glycosites by software. (B) Pie Chart for the percentage of proteins with multiple glycosites (C) Percentage of glycosites also reported by UniProt.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
Figure 6:
Figure 6:. Comparison of the Unique Glycans.
(A) Upset Plot of the glycans identified by each software. (B) Top 10 glycans identified by each software with pie charts displaying the percent of fucosylated and sialylated peptides. (C) Glycans from glycomic profiling split by features such as fucosylation and sialylation.
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