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Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies for Glycopeptide Analysis

ABSTRACT: Mass spectrometry-based glycoproteomics studies now routinely report thousands of intact glycopeptides. Diverse informatics solutions aiding the challenging glycopeptide identification process have recently appeared, but their strengths and weaknesses have not been established leaving a critical knowledge gap that prevents rapid progress in the field. This interlaboratory study comprising both expert users (13 teams) and developers (9 teams) of glycoproteomics software is the first to evaluate the relative performance of current informatics solutions for accurate and comprehensive N- and O-glycopeptide identification. Two LC-MS/MS datasets of intact glycopeptides from serum proteins were shared with all teams. The relative team performance for large-scale glycopeptide analysis was systematically established through 11 orthogonal performance tests based on the assigned spectra reported by each team. This study has found that a diversity of approaches exists for comprehensive glycopeptide data analysis, has demonstrated the team-to-team (vari)ability of identifying intact glycopeptides from shared datasets, and, importantly, has revealed several high-performance informatics solutions and search strategies that will be useful to improve the challenging glycoproteomics data analysis in the immediate future.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

SUBMITTER: Rebeca Kawahara

LAB HEAD: Morten Thaysen-Andersen

PROVIDER: PXD024101 | Pride | 2021-11-03

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	309_N-glycan_search_space_for_HGI.txt	Txt
	78_O-glycan_search_space_for_HGI.txt	Txt
	GP_reporting_template_HGI_Final.xlsx	Xlsx
	Human_ReviewedCanonical_20201Entries_25thJuly_2017.fasta	Fasta
	Team_10_GP_reporting_template_DEIDENTIFIED_FINAL.xlsx	Xlsx

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Project description:To unravel molecular targets involved in glycopeptide resistance, three isogenic strains of Staphylococcus aureus with different susceptibility levels to vancomycin or teicoplanin were subjected to whole-genome microarray-based transcription and quantitative proteomic profiling. Quantitative proteomics performed on membrane extracts showed exquisite inter-experimental reproducibility permitting the identification and relative quantification of >30% of the predicted S. aureus proteome. In the absence of antibiotic selection pressure, comparison of stable resistant and susceptible strains revealed 94 differentially expressed genes and 178 proteins. As expected, only partial correlation was obtained between transcriptomic and proteomic results during stationary-phase. Application of massively parallel methods identified one third of the complete proteome, a majority of which was only predicted based on genome sequencing, but never identified to date. Several over‑expressed genes represent previously reported targets, while series of genes and proteins possibly involved in the glycopeptide resistance mechanism were discovered here, including regulators, global regulator attenuator, hyper‑mutability factor or hypothetical proteins. Gene expression of these markers was confirmed in a collection of genetically unrelated strains showing altered susceptibility to glycopeptides. Our proteome and transcriptome analyses have been performed during stationary‑phase of growth on isogenic strains showing susceptibility or intermediate level of resistance against glycopeptides. Altered susceptibility had emerged spontaneously after infection with a sensitive parental strain, thus not selected in vitro. This combined analysis allows the identification of hundreds of proteins considered, so far as hypothetical protein. In addition, this study provides not only a global picture of transcription and expression adaptations during a complex antibiotic resistance mechanism but also unravels potential drug targets or markers that are constitutively expressed by resistant strains regardless of their genetic background, amenable to be used as diagnostic targets. Keywords: Molecular markers, antibiotic resistance, glycopeptides, growth-phase

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Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies for Glycopeptide Analysis

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