The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides

Summary

Open searching enables the identification of glycopeptides decorated with previously unknown glycan compositions. Within this article, a streamlined approach for undertaking open searching and subsequent glycan-focused glycopeptide searches are presented for bacterial samples using Acinetobacter baumannii as a model.

Abstract

Protein glycosylation is increasingly recognized as a common modification within bacterial organisms, contributing to prokaryotic physiology and optimal infectivity of pathogenic species. Due to this, there is increasing interest in characterizing bacterial glycosylation and a need for high-throughput analytical tools to identify these events. Although bottom-up proteomics readily enables the generation of rich glycopeptide data, the breadth and diversity of glycans observed in prokaryotic species make the identification of bacterial glycosylation events extremely challenging.

Traditionally, the manual determination of glycan compositions within bacterial proteomic datasets made this a largely bespoke analysis restricted to field-specific experts. Recently, open searching-based approaches have emerged as a powerful alternative for the identification of unknown modifications. By analyzing the frequency of unique modifications observed on peptide sequences, open searching techniques allow the identification of common glycans attached to peptides within complex samples. This article presents a streamlined workflow for the interpretation and analysis of glycoproteomic data, demonstrating how open searching 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. Using Acinetobacter baumannii as a model, these approaches enable the comparison of glycan compositions between strains and the identification of novel glycoproteins. Taken together, this work demonstrates the versatility of open database-searching techniques for the identification of bacterial glycosylation, making the characterization of these highly diverse glycoproteomes easier than ever before.

Introduction

Protein glycosylation, the process of attaching carbohydrates to protein molecules, is one of the most common post-translational modifications (PTMs) in nature^1,2. Across all domains of life, a range of complex machinery has evolved dedicated to the generation of glycoproteins that impact a myriad of cellular functions^1,3,4,5. While protein glycosylation occurs on a range of amino acids^6,7, N-linked and O-li....

Protocol

NOTE: The preparation and analysis of bacterial glycopeptide samples can be divided into four sections (Figure 1). For this study, the glycosylation of three sequenced A. baumannii strains was assessed (Table 1). Proteome FASTA databases of each of these strains are accessible via Uniprot. Refer to Table 2 for the composition of buffers used in this protocol.

1. Preparation of protein samples for proteomic analysis

1. Isolation of proteome samples of interest
   1. If using whole cells, ensure that the cells have been washed wi....

Results

To illustrate the utility of open searching for bacterial glycopeptide analysis, the chemical diversity of O-linked glycans within three strains of A. baumannii-AB307-0294, ACICU, and D1279779-was assessed. The O-linked glycoproteomes are highly variable between A. baumannii strains as the glycans used for glycosylation are derived from the highly variable capsule loci^44,45,46. This chemical d.......

Discussion

Open searching is an effective and systematic method for the identification of unknown modifications. While the identification of unknown glycans within bacterial proteome samples has traditionally been a time-consuming and technically specialized undertaking, the recent developments of tools such as MSfragger^21,41 and Byonic^31,38 now enable the quick and effective identification of delta masses for furth.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
14 G Kel-F Hub point style 3	Hamilton company	hanc90514
2-Chloroacetamide	Sigma Aldrich Pty Ltd	C0267-100G
Acetonitrile	Sigma Aldrich Pty Ltd	34851-4L
Ammonium hydroxide (28%)	Sigma Aldrich Pty Ltd	338818-100ML
BCA Protein Assay Reagent A	Pierce	23228
BCA Protein Assay Reagent B	Pierce	23224
C8 Empore SPE	Sigma Aldrich Pty Ltd	66882-U	An alterative vendor for C8 material is Affinisep (https://www.affinisep.com/about-us/)
Formic acid	Sigma Aldrich Pty Ltd	5.33002
Isopropanol	Sigma Aldrich Pty Ltd	650447-2.5L
Methanol	Fisher Chemical	M/4058/17
SDB-RPS Empore SPE (Reversed-Phase Sulfonate)	Sigma Aldrich Pty Ltd	66886-U	An alterative vendor for SDB-RPS is Affinisep (https://www.affinisep.com/about-us/)
Sodium Deoxycholate	Sigma Aldrich Pty Ltd	D6750-100G
ThermoMixer C	Eppendorf	2232000083
trifluoroacetic acid	Sigma Aldrich Pty Ltd	302031-10X1ML
Tris 2-carboxyethyl phosphine hydrochloride	Sigma Aldrich Pty Ltd	C4706-2G
Tris(hydroxymethyl)aminomethane	Sigma Aldrich Pty Ltd	252859-500G
Trypsin/Lys-C protease mixture	Promega	V5073
Vacuum concentrator	Labconco	7810040
ZIC-HILIC material	Merck	1504580001	Resin for use in single use SPE columns can be obtain by emptying a larger form column and using the free resin