Zsolt Bodai (Presenter)
Imperial College London
Authorship: Zsolt Bodai (1), Simon Cameron (1), Frankie Bolt (1), Adam Burke (1), Kate Hardiman (1), Tony Rickards (1), Zoltan Takats(1)
(1) Imperial College London
| Short Abstract Sepsis is associated with a high morbidity and mortality rate, with the latter reaching up to 70%. However, conventional techniques, such as growth cultures from blood samples, can take several days for clinically informative results. Therefore, there is a pressing need for a fast, accurate, and reliable method for the early detection of sepsis and the identification of the causative pathogen. Here, we demonstrate a UPLC-MS method for the early detection of bacteria in a horse blood model, based upon analysis of the microbial lipidome, which is quick, easy, and pathogen specific. |
Long Abstract
Introduction: Within the United States, there are estimated to be 750,000 cases of sepsis per year; resulting in over 200,000 deaths. This carries an annual economic burden to the US health system in excess of $17 billion. Sepsis is associated with a high morbidity and mortality rate, with the latter reaching up to 70%. The analysis of patient blood cultures is essential for maximising the effectiveness of clinical interventions. However, blood cultures can take over 24 hours to confirm the presence of a pathogen and determine its antimicrobial susceptibility. The clinical utility of newly developed molecular tests for sepsis detection, such as PCR based assays, is still to be determined. Here, we demonstrate a quick, easy and selective method for the early detection of bacterial presence in spiked horse blood using lipid-based bacterial markers.
Methodology: Analysis of the most clinical relevant microbial species (Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Candida albicans) was modelled in this study. Defibrinated horse blood was inoculated with the five microbial species and incubated at 37oC for 24 hours on a shaking platform set at 150 rpm. A total of ten different clinically collected isolates were analysed for each microbial species. Non-inoculated horse blood were also prepared as a control. Samples were taken every hour and processed by adding organic solvent, then homogenizing through vortex mixing and sonicating, and subjecting to centrifugation at 14,000 x g for 5 minutes. An aliquot of the upper phase was transferred into glass HPLC vials and used as a source for subsequent analysis. Samples were injected onto reverse phase and HILIC (hydrophilic interaction chromatography) phase UPLC columns for lipid profiling. After chromatographic separation, a Xevo G2-XS Q-ToF (Waters Corporation, Wilmslow, UK) high resolution mass spectrometer was applied as a detector using a commercial electrospray ion source. For the reverse phase method, both positive and negative ionisation, and for the HILIC phase positive ionisation was applied. Acquisition was performed in MSe mode and product ion scan mode to identify lipid structures. Raw data files were converted into mzXML format for subsequent analysis using the XCMS package in the R statistical language.
Results and Discussion: High numbers of significant lipid biomarkers were identified through statistical analysis. These biomarkers were suitable for both the detection of microbial growth in the sepsis model and the identification of the causative pathogenic microorganisms. The structure of the most relevant biomarker lipids were determined based on exact mass and MS/MS fragmentation. This proof-of-principle work shows that UPLC-MS has the utility to act as a rapid, easy, and pathogen selective tool for the detection of blood-borne microbial infection. This may allow for the reduction in time to diagnosis to minutes, rather than days. Moreover, due to the species specificity of biomarkers, the most suitable antimicrobial agent can be administered in a short period of time.
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