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METABOLOMIC CHARACTERIZATION OF PSEUDOMONAS AERUGINOSA ISOLATES FROM CYSTIC FIBROSIS (CF) PATIENTS USING RAPID EVAPORATIVE IONISATION MASS SPECTROMETRY
Authors: E. Bardin, F. Bolt, S. Cameron, A. Bush, E. Alton, J. Davies, Z. Takats
Imperial College London, London, UK
Royal Brompton & Harefield NHS Foundation Trust, London, UK
Introduction
Rapid evaporative ionization mass spectrometry (REIMS) is a new technique that has been shown to accurately classify yeast and bacteria. Thermal stress is applied onto bacterial colonies which results in evaporation and ionisation of metabolites and structural lipids. The mass spectrometer detects and identifies analytes through spectral database comparison(Anal Chem. 2014;86:6555-62). Here, we described the application of REIMS to CF related pathogens and show that the technology can identify P. aeruginosawith 100% accuracy. Differences were observed in phospholipid range and rhamnolipids range; derivatives of quorum sensing molecules (QSM) were also detected.These may provide useful biomarkers for a non-invasive diagnostic tool using ambient mass spectrometric (MS) approachescurrently in development.
Methods
Isolates were collected from CF samples routinely processed at Royal Brompton Hospital (London, UK). These included 53 P.aeruginosaisolates and 51 isolates from 11 genera, including Achromobacterxylosoxidans, Staphylococcus aureus, Stenotrophomonasmaltophilia and Burkholderia spp. Genera were confirmed using Microflex LT MALDI TOF (BrukerDaltonics).REIMS analyses were performed in negative ionizationmode, on colonies grown on plate in appropriate species conditions. A small amount of biomass was sampled directly from the medium using bipolar forceps. On drawing the probes together, an electrical current of 70W was applied andtheresulting aerosol was channelled into aXEVO G2-XS Q-ToFinstrument (Waters Corporation). A minimum of three technicalmeasurements were acquired and averaged for each samples. Mass spectra were subjected to background subtraction and mass drift correction, unsupervised and supervised multivariate statistical analyses.
Results
Principal component analysis effectively separated P. aeruginosa from other the genera and prediction was100% accurate using linear discriminant analysis.Analysis of variance revealed separationwas mainly based upondifferences inthe mass over charge rangefrom 600 to 900 that comprises the phospholipids. Intra species diversity within P. aeruginosa was explored and rhamnolipids and QSM were found to differ between isolates.
Conclusions
REIMS clearly distinguished P. aeruginosafrom other CF pathogens supporting its role as a diagnostic tool. Intra species differences were also observed. The characteristic P. aeruginosafeatures identified as part of this study may serve as biomarkers for the development of a direct from sample diagnostic tool. Indeed, we are currently working on non-invasive detection approaches, based on direct MS analysis of skin secretions and exhaled breath. Such non-culture-based systems would save valuable time to diagnosis. Whole Genome Sequencing is also being undertaken in parallel and results will be used to seek relationships with clinical outcomes.
Supported by the Cystic Fibrosis Trust, Strategic Research Centre for P.aeruginosa