Simon Cameron (Presenter)
Imperial College London
Bio: I joined Prof. Zoltan Takat's research group in October 2015 as a Research Associate in Microbial Populations and Metabonomics in the Division of Computational and Systems Medicine at Imperial College London. I received my BSc (2011) and PhD (2015) from Aberystwyth University, Wales, UK. My research interests are in the broad fields of microbial ecology and metabolomics, with a focus on the human microbiome and metabolome and its response to disease and stress. I currently work as part of the MicrobeID team at Imperial College London, which is developing rapid evaporative ionisation mass spectrometry (REIMS) as a high-throughput, a to assign taxonomic and functional classifications to microbial isolates and to the direct-from-sample profiling of mixed microbial communities.
Authorship: Simon Cameron (1), Frances Bolt (1), Adam Burke (1), Alvaro Perdones-Montero (1), Zsolt Bodai (1), Tony Rickards (1,2), Kate Hardiman (1), A Abdolrasouli (1,2), Monica Rebec (2), Zoltan Takats (1)
(1) Imperial College London, London, UK (2) Imperial College Healthcare NHS Trust, London, UK
| Short Abstract Mass spectrometry (MS) has revolutionised the workflow of clinical microbiology laboratories; allowing a substantial reduction in diagnosis times. Unlike commercially available MS platforms, rapid evaporative ionisation MS (REIMS) requires no sample preparation, such as the addition of a matrix, before sample analysis. We have developed an automated, high-throughput REIMS platform which is capable of analysing up to 5,000 microbial colonies in 24 hours. This platform correctly classifies clinical isolates with an accuracy of >99% for Gram stain, >95% for genus, and >93% for species. This presentation will detail ongoing developments of the REIMS platform, including the creation of a reference spectral database, the functional classification of microbial isolates, such as antimicrobial/fungal resistance, and direct from biological sample analysis, such as from stool, blood, and sputum. |
Long Abstract
This presentation will encompass the on-going work within the MicrobeID team at Imperial College London to develop rapid evaporative ionisation mass spectrometry (REIMS) as a high-throughput, automated platform for the taxonomic identification and functional classification of microorganisms. Four main areas will be covered: (1) the construction of a REIMS mass spectral reference database; (2) its application to antimicrobial resistance profiling; (3) analysis of mixed microbial cultures; and (4) the direct-from-sample analysis of clinical samples, such as stool, blood, and urine.
INTRODUCTION: Before the widespread introduction of mass spectrometry platforms, such as matrix-assisted laser desorption ionisation time of flight (MALDI-ToF), into clinical microbiology laboratories, the majority of identifications relied upon extensive biochemical characterisations. These included sugar utilisation and fermentation; but were time consuming, variable, and required expertise to perform. The implementation of mass spectrometry platforms has allowed for rapid microbial identification; improving patient care through reduced diagnosis times, and targeted clinical interventions. MALDI-ToF based platforms are currently the primary systems used in clinical diagnostic laboratories. Microbial identifications using this method rely on the characterisation of ionised proteins within the mass range of 2−20 kDa; with over 50% of ribosomal origin [1,2]. Although, the introduction of MALDI-ToF has reduced the time to identification of microbial colonies, it still requires a user to add a matrix to assist in ionisation. Furthermore, in some instances, such as for yeasts, additional extraction steps are required for accurate species level identification. In the majority of investigations, it is still also reliant upon the isolation of pure microbial cultures before analysis can be carried out. This is frequently the major factor in determining the length of time required for microbial identification. MALDI-ToF based systems can also have difficulty in the species-level classification of some taxonomic groupings, such as Salmonella sp., and in sub-species analysis.
REIMS has previously been demonstrated to provide accurate species-level classification of bacteria and yeasts direct from colonies; without the need for additional preparative steps [3,4]. In comparison to MALDI-ToF based platforms, REIMS utilises the lipidomic profile of bacteria and fungi to determine their species-level classification. The REIMS technology works by applying a radiofrequency electrical current to a microbial biomass, causing it to heat rapidly and evaporate. The resulting vapour, containing gas phase ions of metabolites and structural lipids, is channelled to a mass spectrometer for analysis. This allows for a real-time mass spectral signal to be generated as detection of ions happens in less than one second of sample heating. The REIMS technology has recently been incorporated into a high-throughput, automated platform which includes culture plate handling, colony imaging and selection, and REIMS analysis using a monopolar probe. This platform is capable of processing up to 5,000 microbial colonies in a 24 hour period; making it highly suitable for a high-throughput clinical microbiology laboratory.
METHODS: In order to utilise this technology for the identification of unknown microorganisms, a reference library comprising mass spectra is currently being developed; which will encompass the breadth of microbial taxonomy. To ensure the REIMS taxonomic designation is accurate, full-length 16S/18S rRNA gene and ITS region sequencing, MALDI-ToF mass spectrometry using the Bruker Biotyper system (Bruker Daltonics, Billerica, MA), and other species-specific biochemical and genetic tests are employed. For all reference microbial isolates, separate database entries for appropriate culture conditions (such as culture plate type, incubation length, and atmosphere) will be included. Furthermore, additional information and spectra for different analytical conditions will be collected, including high-throughput REIMS probe types, technical parameters such as solvent matrix, and heating power. In total, this mass spectral library will include approximately 50,000 isolates from across approximately 4,000 microbial species; collected from clinical diagnostic and non-clinical microbiology laboratories.
To assess the ability of REIMS to accurately assign Gram stain, genus, and species level taxonomy to isolates, a total of 15 isolates from over 40 clinically important bacterial and fungal species were analysed. Isolates were grown in appropriate culture conditions and then analysed using the high-throughput REIMS platform employing a stainless steel sharp point monopolar probe. Classification models were then constructed using a Random Forest algorithm and used to assign classifications to each isolate. In addition to the development of a mass spectral reference library, a substantial amount of application development work has also been completed. This includes the analysis of mixed microbial cultures, the analysis of filamentous fungi isolates directly from culture, the functional classification of antimicrobial resistant isolates, including methicillin resistant/sensitive and carbapenamase producing/non-producing isolates.
RESULTS AND DISCUSSION: The high-throughput REIMS platforms is highly suited to the workflow and workload of clinical microbiology laboratories. It is capable of processing up to 5,000 microbial colonies in a 24 hour period, with data generated in real-time. The platform requires minimal user input, thereby reducing variability and associated costs. Assessment of the ability of the high-throughput REIMS platform to accurately and robustly assign taxonomic classification to clinically important microbial species was completed through the analysis of 15 isolates for over 40 species. Random Forest classification models were used to assign Gram stain, genus, and species level classification for all isolates. Using this approach, classification accuracies of >99% for Gram stain, >95% for genus, and >93% for species were achieved.
For analysis of mixed cultures of bacteria and yeasts, a variety of species and concentration ratios were tested using both our high-throughput REIMS method and the previously reported handheld bipolar REIMS approach [3,4]. For all species combinations and ratios, species specific biomarkers were detected that act as a proof-of-principle that REIMS has the utility to detect clinically important microbial species from mixed cultures and/or communities.
Unlike other widely used clinical microbiology diagnostic MS platforms, REIMS requires no, or in rare circumstances minimal, preparative steps. This is exemplified by the analysis of filamentous fungi using REIMS; which only requires a short centrifugation step after culturing in a liquid medium before analysis can take place. Compared to other MS platforms, this allows for a much higher throughput volume with minimal user input. Approximately 400 filamentous fungi isolates have to date been analysed using REIMS, with high accuracy genus and species level classification models produced.
In addition to the taxonomic classification of clinically important microbes, REIMS possesses the potential to also give important functional information on isolates; such as identifying methicillin resistant or sensitive Staphylococcus aureus isolates, without exposure to the relevant antibiotic. Here, data on the analysis of 150 methicillin sensitive S. aureus and resistant S. aureus isolates will be presented, in addition to preliminary data on the analysis of carbapenamase producing/non-producing Enterobacteriaceae isolates.
References & Acknowledgements:
References:
[1] Krause, E., Wenschuh, H. & Jungblut, P. R. The Dominance of Arginine-Containing Peptides in MALDI-Derived Tryptic Mass Fingerprints of Proteins. Anal. Chem. 71, 4160–4165 (1999).
[2] Ryzhov, V. & Fenselau, C. Characterization of the Protein Subset Desorbed by MALDI from Whole Bacterial Cells. Anal. Chem. 73, 746–750 (2001).
[3] Strittmatter, N. et al. Analysis of Intact Bacteria using Rapid Evaporative Ionisation Mass Spectrometry. Chem. Commun. 49, 6188–90 (2013).
[4] Strittmatter, N. et al. Characterization and Identification of Clinically Relevant Microorganisms using Rapid Evaporative Ionization Mass Spectrometry. Anal. Chem. 86, 6555–62 (2014).
Acknowledgements:
This work is supported by a research grant from the UK Biotechnology and Biological Sciences Research Council (ref: BB/L020858/1). Additional financial (staff salaries at Imperial College London, provision and equipment of consumables, and other research funding) and technical support is given by the Waters Corporation. This abstract/presentation does not promote any commercially available product of the Waters Corporation.
| Description | Y/N | Source |
| Grants | yes | Research supported by BBSRC UK grant and funding from Waters Corporation |
| Salary | no | |
| Board Member | no | |
| Stock | no | |
| Expenses | no |
IP Royalty: no
| Planning to mention or discuss specific products or technology of the company(ies) listed above: | yes |