MSACL 2017 EU Abstract

Laser Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS): An Automated High-Throughput Platform for Clinical Microbiology and Beyond

Simon Cameron (Presenter)
Imperial College London

Bio: I joined Prof. Zoltan Takats’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 coordinate the MicrobeID team at Imperial College London, which is developing rapid evaporative ionisation mass spectrometry (REIMS) as a high-throughput platform to assign taxonomic and functional classifications to microbial isolates and to the direct-from-sample profiling of mixed microbial communities.

Authorship: Simon Cameron (1), Alvaro Perdones-Montero (1), Frances Bolt (1), Adam Burke (1), Zsolt Bodai (1), 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 recently transitioned to using a CO2 laser to complete REIMS analysis; improving the sample throughput of our automated high-throughput REIMS platform by over 30%. This platform correctly classifies clinical isolates with an accuracy of >99% for Gram stain, >97% for genus, and >95% for species. This presentation will detail the optimisation of the LA-REIMS platform, the creation of a reference spectral database for over 50 microbial species, the determination of antimicrobial susceptibilities, and direct from clinical sample pathogen detection.

Long Abstract


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. 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 [1, 2]. 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 rapidly heating a microbial biomass, causing it to 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 initial application of REIMS to microbiology employed electrical diathermy as a mechanism for the rapid heating of a sample. Although this method proved highly successful in a range of applications [3, 4], it necessitates contact to be made between the sample and probe. This REIMS technology was 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. To remove the requirement for sample contact, laser assisted REIMS (LA-REIMS) has been incorporated into this automated high-throughput platform. This employs a CO2 laser to rapidly heat and evaporate a sample, from a distance of 2mm.


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. 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.

A CO2 laser was incorporated into the TECAN EVO Freedom liquid handling platform previously used for electrical diathermy REIMS. To determine the optimal setup, various operating parameters were tested on 15 microbial isolates. These included laser operating power, pulsing type and speed, distance of laser head from sample, movement of laser probe during heating, and cooling gas pressure. For all optimization steps, the vapour produced through laser-assisted heating was channelled to a Xevo G2-XS QToF MS (Waters Corporation).

To assess the ability of REIMS to accurately assign Gram stain, genus, and species level taxonomy to isolates, a total of 15 isolates from approximately 50 clinically important bacterial, yeast, and filamentous fungi species were analysed. Isolates were grown in appropriate culture conditions and then analysed using the high-throughput LA-REIMS platform. Classification models were then constructed using a Random Forest algorithm and used to assign classifications to each isolate. The classification model was then validation through the further analysis of approximately 200 isolates which were not used in its creation. The classification model then assigned species-level identifications to each isolate, which were used to calculate accuracy values.

Additionally, the optimised LA-REIMS platform was utilised to analyse a range of diagnostic samples to determine whether LA-REIMS could be used for direct from sample pathogen detection without culture. Furthermore, the platform was utilised for the detection of antimicrobial susceptibility profiles including methicillin-resistant and methicillin-sensitive Staphylococcus aureus without exposure to antibiotics, and in various Gram-negative bacteria.


The high-throughput LA-REIMS platform is highly suited to the workflow and workload of clinical microbiology laboratories. It is capable of processing over 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. Optimisation of the LA-REIMS platform identified parameters, including laser power, laser beam pulsing duration, and distance of laser head from sample which improved phospholipid region intensity three fold, and S/N ratios by more than 25%. These optimal parameters were subsequently applied to the species-level identification of 660 isolates, from 44 species. This improved identification accuracy from >93% to >95%, as compared to electrical diathermy REIMS.

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 300 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. Additional proof-of-principle studies on the direct-from-sample detection of pathogens without culture will also be presented.

Conclusions & Discussion

LA-REIMS offers a novel mass spectrometry platform for clinical microbiology. It is capable of accurate and robust species level identifications for bacteria, yeast, and filamentous fungi directly from culture; employing the same automated, high-throughput workflow for all culture types. In addition, LA-REIMS offers the potential to expand the application of mass spectrometry beyond routine identification, into areas including antimicrobial susceptibility testing, sub-species strain typing, and direct-from-sample pathogen detection.

References & Acknowledgements:


[1] Strittmatter, N. et al. Analysis of Intact Bacteria using Rapid Evaporative Ionisation Mass Spectrometry. Chem. Commun. 49, 6188–90 (2013).

[2] Strittmatter, N. et al. Characterization and Identification of Clinically Relevant Microorganisms using Rapid Evaporative Ionization Mass Spectrometry. Anal. Chem. 86, 6555–62 (2014).

[3] Bolt, F. et al. Automated High-Throughput Identification and Characterization of Clinically Important Bacteria and Fungi using Rapid Evaporative Ionization Mass Spectrometry. Anal. Chem. 88, 9419-9426 (2016).

[4] Cameron, SJS. et al. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) Provides Accurate Direct from Culture Identification within the Genus Candida. Sci. Reports. 6, 36788 (2016).


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.

Financial Disclosure

GrantsyesUK BBSRC Research Council and the Waters Corporation
Board Memberno

IP Royalty: no

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