Updated project metadata. Mass spectrometry has become an indispensable tool for the characterisation of glycosylation across biological systems. Our ability to generate rich fragmentation data of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag be hide. This is especially true for the study of bacterial glycosylation where manual determination of glycopeptides is still heavily used. This dependence on manual assignment/identification is not scalable, extremely time consuming and limits accessibility of bacterial glycosylation studies to field specialists. As such computational approaches to examine bacterial glycosylation and determine glycan diversity within samples are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses prior to database searching. Utilising this approach, we demonstrate how wide tolerance searching can be used to compare glycan utilisation across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we also demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined these results show that open searching is a robust computational approach for the determination of glycan diversity within novel microbial glycosylation systems.