Kotowska, A M; Zhang, Junting; Carabelli, A; Watts, J; Aylott, J W; Gilmore, Ian; Williams, P; Scurr, D J; Alexander, M R (2023) Towards comprehensive analysis of the 3D chemical makeup of Pseudomonas aeruginosa biofilms. Analytical Chemistry, 95 (49). pp. 18287-18294.

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Abstract

Bacterial biofilms are structured communities consisting of cells enmeshed in a self-generated extracellular matrix usually attached to a surface. They contain diverse classes of molecules including polysaccharides, lipids, proteins and nucleic acids which are organized to optimise survival and facilitate dispersal to new colonization sites. In situ characterisation of the chemical composition and structure of bacterial biofilms is necessary to fully understand their development on surfaces relevant to biofouling in health, industry and the environment. Biofilm development has been extensively studied using confocal microscopy using targeted fluorescent labels providing important insights into the architecture of biofilms. Recently, cryo-preparation has been used to undertake in situ chemical characterisation using secondary ion mass spectrometry (SIMS), although the spectral data analysis employed was focusing on mapping known molecules of interest. Here we analyse the same data generated from an unlabelled native biofilm prepared by high pressure freezing employing a chemical filtering process to assign secondary ions in an untargeted way to decipher the large number of fragments present in the SIMS spectra. To enable comprehensive analysis of different chemistries in the sample, we apply a molecular formula prediction (MFP) approach to assign 81% of the 3D OrbiSIMS spectrum. This enabled us to catalogue over 1,000 lipid fragments, 3,500 protein fragments, 71 quorum sensing molecules (quinolones and homoserine lactones), 150 polysaccharide fragments and glycolipids simultaneously from one dataset and map these separated molecular classes spatially through a Pseudomonas aeruginosa biofilm. In contrast to LC-MS or MALDI, which require solvent or matrix optimisation for different compound classes, SIMS has the potential to produce chemical information from several different compound groups simultaneously. Additionally, it allows in situ analysis with relatively high depth and lateral resolution.

Item Type:	Article
Subjects:	Nanoscience > Surface and Nanoanalysis
Divisions:	Chemical & Biological Sciences
Identification number/DOI:	10.1021/acs.analchem.3c04443
Last Modified:	02 Sep 2024 09:01
URI:	https://eprintspublications.npl.co.uk/id/eprint/9989