PXD027820

PXD027820 is an original dataset announced via ProteomeXchange.

Title	The application of open searching based approaches for the identification of Acinetobacter baumannii O-linked glycopeptides decorated with diverse capsule derived glycans
Description	Protein glycosylation is being increasingly recognised as a common modification within microbial organisms, contributing to protein functionality and optimal infectivity of pathogenic species. Due to this, the interest in characterising microbial glycosylation events is increasing - requiring high-throughput robust analytical tools. Although bottom-up proteomics now readily enables the generation of rich microbial glycopeptide data, the breath and diversity of glycans observed in microbial species makes the identification of microbial glycosylation events extremely challenging. Traditionally, manual determination of glycan structures within proteomic datasets have been required, making this a largely bespoke analysis restricted to field specific experts. Recently, open searching (OS) based approaches have emerged as a powerful alternative for the identification of previously unknown modifications. OS techniques leverage the frequency of observations of unique modifications on multiple peptide sequences to enable their identification within complex samples. Within this article, we highlight a streamlined workflow for the generation of glycoproteomic data and demonstrate how OS techniques can be used to identify bacterial glycopeptides without prior knowledge of the glycan compositions. Using this approach, glycopeptides within samples can rapidly be identified to understand glycosylation differences, as well as to identify the glycoproteome within a microbe of interest. Using Acinetobacter baumannii as a model, we demonstrate how these approaches enable the comparison of glycan structures between strains and enable the identification of novel glycoproteins. Combined, this work demonstrates the versatility and robustness of open database searching techniques for the characterisation of microbial glycosylation, making characterisation of glycoproteomes easier than ever before.
HostingRepository	PRIDE
AnnounceDate	2021-11-02
AnnouncementXML	Submission_2021-11-02_06:35:56.976.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Nichollas Scott
SpeciesList	scientific name: Acinetobacter baumannii D1279779; NCBI TaxID: 945556; scientific name: Acinetobacter baumannii ACICU; NCBI TaxID: 405416; scientific name: Acinetobacter baumannii AB307-0294; NCBI TaxID: 557600;
ModificationList	complex glycosylation
Instrument	Orbitrap Fusion Lumos

Revision	Datetime	Status	ChangeLog Entry
0	2021-08-09 06:34:49	ID requested
⏵ 1	2021-11-02 06:35:57	announced

Dataset with its publication pending

submitter keyword: Glycopeptides, LC-MS, Proteomics

Nichollas E Scott
contact affiliation	Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Parkville, Victoria, Australia.
contact email	nichollas.scott@unimelb.edu.au
lab head
Nichollas Scott
contact affiliation	University of Melbourne
contact email	nichollas.scott@unimelb.edu.au
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD027820
     1. Label: PRIDE project
     2. Name: The application of open searching based approaches for the identification of Acinetobacter baumannii O-linked glycopeptides decorated with diverse capsule derived glycans