MSACL 2016 EU Abstract

Rapid Evaporative Ionisation Mass Spectrometry (REIMS) as a Novel Approach to Microbial Community Profiling

Adam Burke (Presenter)
Imperial College

Bio: I achieved a 1st class BSc in microbiology (2010) and MBiolSci in Biological Sciences (2011) from The University of Liverpool before completing a summer internship at the National Science and Technology Development Agency of Thailand, where I investigated a novel drug target against Plasmodium spp. I then worked as a Technical Scientist within a pharmaceutical company based in north Wales for one year. Following this, I began a Research Technician post with Prof. Takat’s research group at Imperial College London in 2014, before embarking on a PhD using Rapid Evaporative Ionisation Mass Spectrometry (REIMS) for microbial community profiling in 2015. My research interests are in the human microbiome and its role in health and disease, microbial diagnostics, and the application of mass spectrometry to this field.

Authorship: A Burke (1), SJS Cameron (1), F Bolt (1), Z Bodai (1), T Rickards (1,2), K Hardiman (1), A Perdones-Montero (1), A Abdolrasouli (1,2), M Rebec (2), T Karancsi (1), D Simon (1), Z Takats (1).
(1) Imperial College London, London, UK (2) Imperial College Healthcare NHS Trust, London, UK

Short Abstract Mass spectrometry has become an essential component of clinical microbiology diagnostic workflows, increasing productivity and improving clinical outcomes through reduced sample turnaround time. Present commercial systems depend on isolation of a pure microbial culture, followed by additional sample preparation for MALDI-ToF, leaving room for further improvement. Rapid evaporative ionisation mass spectrometry (REIMS) has demonstrated robust species level identification for a variety of clinically significant microorganisms. Species specific features have been identified in mixed eukaryotic/prokaryotic cultures, indicating potential for taxonomic classification in cross-domain samples. Work is in progress to optimise the application of REIMS direct to clinical samples, removing the requirement for preparatory isolation and culturing of microorganisms.

Long Abstract

This presentation will expand on a previous proof of principle study in which Rapid Evaporative Ionisation Mass Spectrometry (REIMS) was shown to distinguish between distinct, species-specific mass spectral features present within defined mixed bacterial cultures. This work is in collaboration with the MicrobeID project at Imperial College London and is intended to further demonstrate the capability of the technology in identifying distinct mass spectral peaks within controlled mixtures containing both bacterial and yeast species.

Introduction:

For over 40 years mass spectrometry (MS) has been utilised for microbial identification, although it has only recently became part of the workflow of clinical microbiology laboratories; where it has transformed microbial diagnostics through dramatic reduction of costs and time to identification (1). Systems available from Shimadzu and Bruker Daltronics offer equal or better results to conventional Vitek2 or API identification systems. MS for microbial identification is largely based on Matrix-assisted laser desorption ionisation Time of Flight (MALDI-TOF) technology, which utilises an irradiating UV laser along with a proton providing matrix to ionise microbial biomass resulting in mass spectra of protein fragments in the 2-20kDa mass range, of mainly ribosomal origin (2, 3). The spectra produced is compared to a reference library and matching algorithms allow analysed microbes to be classified based on their distinctive species level ‘fingerprint’, although drug resistance, serotype or virulence information is not available meaning traditional culturing techniques are still required in these instances. The technology also struggles to identify endospore producing bacteria such as Clostridium spp. owing to spectral interference, and capsule possessing microorganisms such as Streptococcus spp. Klebsiella pneumoniae and Haemophilus influenzae, due to the difficulty experienced in lysing cells resulting in reduced extraction yields and poor spectral quality (4). Some potential has been observed in using MALDI-TOF for direct blood and urine sample analysis, however only with monomicrobial samples as inaccurate classification of samples was observed for polymicorbial samples (5-8). The core limitation of current MS identification methods is that they still depend on the pre-culture and isolation of single microbial species before any pre-processing and analysis steps can begin, which is costly, inefficient and labour intensive.

The predominant molecular technique for microbial identification is 16S rRNA gene sequencing, as the gene is present across diverged phyla and contains variable regions to species or genus level as well as conserved regions well suited for PCR primer adherence (9). Consequently, it is ideal for the taxonomic classification of microorganisms which are fastidious and challenging to culture or have unclear biochemical test results. The technique is particularly useful in microbiome analysis when coupled with next generation sequencing platforms such as Roche 454 and Illumina MiSeq, and has been successfully utilised to ascertain the mixed species constituents of the gastrointestinal microbiota (10). Although molecular techniques are useful, they are seldom used in clinical laboratories due to high costs, time constraints and the requirement of substantial sample processing. Furthermore, due to the conserved nature of the 16S rRNA gene it is not possible to achieve species level resolution in some instances.

REIMS provides an almost real time analysis from intact cells, with no pre sample processing or extraction required. Microbial colonies can be ionised directly from culture media by applying a radiofrequency electrical current (100kHz – 4MHz) which rapidly heats and vaporises the biomass. The vapour contains ionised lipids and metabolites which are introduced to the mass spectrometer for analysis using the instruments native vacuum. An electrical current is applied to the biomass using either handheld bi-polar or automated mono-polar probes, adapted from the iKnife surgical device used to differentiate between malignant and healthy tissue during surgery (11). In the automated method, user input and thus error is reduced as the system is capable of picking up petri dishes and selecting colonies for analysis automatically. Currently, a total of 44 clinically significant species have been analysed with taxonomic classification accuracy of >93% at species level, and >99%/>95% for Gram stain and genus level respectively. Preliminary data also suggests that yeasts can be resolved to species level. Classification thus far has been based on the unique spectral signatures produced by each species or sub-species, however work is now underway to identify specific biomarkers for use in mixed culture analysis.

Materials and Methods:

The following clinically significant and cross-domain microorganisms; Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Enterococcus faecalis and Candida albicans were collected from the Imperial College Healthcare clinical microbiology laboratory (Charing Cross National Healthcare Service hospital) and identified according to the normal lab workflow with a Bruker Microflex LT instrument. Isolates were subsequently grown in broth culture and inoculated in 1:1, 1:2 and 3:1 ratios onto Columbia Blood agar and grown concurrently for 24 hours. Previously, isolates were also grown singularly and colonies mixed post-culturing in identical ratios. Mixtures were then analysed on a Xevo G2-XS QToF instrument (Waters, Wilmslow, UK) using REIMS hand-held bipolar and high-throughput automated monopolar ionisation methods. Data processing and analysis was performed using both custom proprietary Waters software and open-source metabolomic data analysis tools. Significant features were investigated further by fragmentation with tandem MS and identified as preliminary species specific biomarkers. Work is ongoing to build a database of 4000 distinct species level mass spectral fingerprints, species specific biomarkers and validation information with 16S rRNA next generation gene sequencing through the Illumina MiSeq system.

Results and Discussion:

Preliminary results demonstrate the ability of REIMS to detect species specific biomarkers within controlled mixed cultures of varying ratios spanning diverged domains. Database population is in progress, however the technology displays high potential in direct from clinical sample applications, potentially removing the requirement of pre-culturing pure microbial isolates in the future and offering significantly reduced time to identification and thus improved clinical outcomes for patients. Further method optimisation is required to apply the technique directly to clinical samples such as blood, urine and sputum, and this will be the focus of future investigations. Microbiome analysis through 16S rRNA gene sequencing, alongside traditional culturing techniques, will validate the data obtained through direct from sample REIMS and enable the technique to offer an attractive real-time alternative to the current labour intensive practice of culturing each individual isolate. The continuing development of both the mixed species identification and the high throughput automated monopolar ionisation method by the MicrobeID project will allow the system to identify microbial populations to species or even sub-species level from clinical samples loaded into the instrument. The installation of this system into clinical laboratories could revolutionise workflows and drastically improve patient outcomes by providing almost real-time classification results to physicians, who may then make targeted clinical decisions, for example on antimicrobial drugs.

References & Acknowledgements:

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2. Krause E, Wenschuh H, Jungblut PR. The dominance of arginine-containing peptides in MALDI-derived tryptic mass fingerprints of proteins. Analytical chemistry. 1999;71(19):4160-5.

3. Ryzhov V, Fenselau C. Characterization of the protein subset desorbed by MALDI from whole bacterial cells. Analytical chemistry. 2001;73(4):746-50.

4. The Standards Unit MS, PHE. UK Standards for Microbiology Investigations: Matrix-Assisted Laser Desorption/Ionisation - Time of Flight Mass Spectrometry (MALDI-TOF MS) Test Procedure 2015.

5. Wang XH, Zhang G, Fan YY, Yang X, Sui WJ, Lu XX. Direct identification of bacteria causing urinary tract infections by combining matrix-assisted laser desorption ionization-time of flight mass spectrometry with UF-1000i urine flow cytometry. Journal of microbiological methods. 2013;92(3):231-5.

6. Ferreira L, Sanchez-Juanes F, Munoz-Bellido JL, Gonzalez-Buitrago JM. Rapid method for direct identification of bacteria in urine and blood culture samples by matrix-assisted laser desorption ionization time-of-flight mass spectrometry: intact cell vs. extraction method. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases. 2011;17(7):1007-12.

7. Tadros M, Petrich A. Evaluation of MALDI-TOF mass spectrometry and Sepsityper Kit (TM) for the direct identification of organisms from sterile body fluids in a Canadian pediatric hospital. Can J Infect Dis Med. 2013;24(4):191-4.

8. Christner M, Rohde H, Wolters M, Sobottka I, Wegscheider K, Aepfelbacher M. Rapid Identification of Bacteria from Positive Blood Culture Bottles by Use of Matrix-Assisted Laser Desorption-Ionization Time of Flight Mass Spectrometry Fingerprinting. Journal of clinical microbiology. 2010;48(5):1584-91.

9. Petti CA. Detection and identification of microorganisms by gene amplification and sequencing. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. 2007;44(8):1108-14.

10. Turnbaugh PJ, Ridaura VK, Faith JJ, Rey FE, Knight R, Gordon JI. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Science translational medicine. 2009;1(6):6ra14.

11. Balog J, Sasi-Szabo L, Kinross J, Lewis MR, Muirhead LJ, Veselkov K, et al. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Science translational medicine. 2013;5(194):194ra93.

Financial Disclosure

IP Royalty: no

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