Adam Burke (Presenter)
Imperial College London
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 & 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 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), F Bolt (1), SJS Cameron (1), N Strittmatter (1), T Rickards (2), K Hardiman (1), P Inglese (1), D Galea (1), A Abdolrasouli (2), M Rebec (2), T Karancsi (1), D Simon (1), KA Veselkov (1),
(1) Imperial College London, London, UK (2) Imperial College Healthcare NHS Trust, London, UK
| Short Abstract Mass spectrometric methods are already integrated into diagnostic workflows of clinical microbiology laboratories; hastening and simplifying the turnaround for sample specimens and therefore leading to better patient outcomes. However, current commercial systems rely on isolating and culturing target microorganisms, followed by further sample preparation for MALDI-ToF, leaving room for further improvement. Rapid evaporative ionisation mass spectrometry (REIMS) has been shown to offer robust species identification for a range of clinically important microorganisms. Taxonomic markers have been identified in mixed cultures, demonstrating potential for taxonomic classification in non-pure samples. Work is currently underway to develop and optimise the application of the REIMS technology directly from samples, removing the need to first isolate and culture the microorganism of interest. |
Long Abstract
This poster presentation will expand on the work done by the MicrobeID project at Imperial College London by demonstrating the capability of the Rapid Evaporative Ionisation Mass Spectrometry (REIMS) technology in identifying distinct mass spectral peaks, of the species examined, within defined mixed cultures. This work is intended to be a proof of principle and will be applied to a range of clinical samples including urine, faeces, blood, sputum, saliva and vaginal swabs obtained from the Imperial College Healthcare NHS Trust clinical microbiology laboratory.
Introduction:
Although mass spectrometry (MS) has been used for microbial identification for over forty years, it has only recently been adopted in clinical microbiology laboratories; where it has revolutionised microbial diagnostics. Its introduction has had a dramatic effect on work flows, time to identification and costs (1). Commercialised systems developed by Bruker Daltonics and Shimadzu provide comparable or even superior results to conventional identification systems such as API or Vitek2. Matrix-assisted laser desorption ionisation Time of Flight MS (MALDI-TOF MS) for microbial classification is based upon the ionisation and analysis of predominantly ribosomal protein biomarkers of the 2−20 kDa mass range (2,3). The resulting mass spectra of protein fragments allows microorganisms to be classified based upon their unique species-level ‘fingerprint’. These fingerprints are compared to spectral reference libraries where pattern-matching algorithms enable the classification of the isolates. However, no information on clinically relevant phenotypes such as antibiotic-resistance, virulence or serotypes is provided in routine applications which makes additional conventional testing necessary. Other limitations of the technology include spectral interference due to the presence of endospores, for example in Clostridium spp., leading to poor classification results and requiring young cultures to be used in such instances. Microorganisms possessing capsules, such as Streptococcus spp., Haemophilus influenza and Klebsiella pneumoniae present difficulty with effective lysis of cells, resulting in poor extraction yields and classification due to weak spectral quality (4). In addition, current MS-based identification systems still rely on the isolation of a pure microbial culture which is time-consuming and labour-intensive.
The most common genomic method used in bacterial identification is 16S rRNA gene sequencing. This method provides a useful tool as the gene is ubiquitous throughout divergent phyla, has well-conserved regions for PCR primers, and contains genus- or species-level hypervariable region sequences (5). As such, it is well suited for classifying micro-organisms which are difficult to grow in culture or have ambiguous biochemical test results. It has been used successfully with next generation sequencing platforms, including Illumina MiSeq and Roche 454 in the analysis of mixed-community microbiome samples (6). Although molecular techniques are useful, they are infrequently used in clinical settings due to extensive preparation requirements and costs. Additionally, 16S rRNA gene based microbiome studies are not truly quantitative and can over-represent some taxa at the expense of others due to differences in gene copy numbers between species (7). In such studies it is necessary to correct for gene copy numbers through the use of bioinformatic tools which improve relative abundance estimates. A novel method of quickly identifying species and subspecies of the microbiota within tissue samples could therefore prove revolutionary to clinical microbiology and drastically improve disease outcomes of patients.
Whilst MALDI-TOF MS is based upon the examination of proteins, spectral analysis of lipids has also been an important tool for bacterial taxonomy. Bacterial lipodomic profiles can be analysed directly from colonies with REIMS, negating the requirement for added preparative steps (8). This innovative technique was originally developed as the iKnife surgical device to differentiate between healthy and malignant tissue during surgery (9). An adapted protocol was subsequently shown to provide rapid speciation of 28 clinically important bacterial species with 95.9%, 97.8%, and 100% accuracy to species, genus, and Gram-stain level, respectively (8). REIMS has also been applied to yeasts and preliminary data demonstrates that it can provide species-level resolution. Species-specific mass spectral fingerprints are produced by directly vaporising a microbial colony scraped from an agar plate using electrosurgical forceps and applying a radiofrequency electrical current (100kHz – 4MHz). Gas phase metabolites and lipids are generated and pass through to the mass spectrometer for REIMS analysis.
Materials and Methods:
Previous work on REIMS has been exploratory and the detection limit has not yet been determined. The minimum CFU is being determined by spiking horse blood liquid media with clinically relevant strains including Staphylococcus haemolyticus, Klebsiella pneumoniae, Escherichia coli, Moraxella catarrhalis and Pseudomonas aeruginosa. Blood cultures containing increasing CFUs of these bacteria are subjected to REIMS analysis to determine the limit of detection. Currently, the MicrobeID project is focusing on utilising REIMS to identify individual isolated bacteria and fungi. Therefore, work is currently being carried out on the analysis of controlled mixtures of solid and solidified liquid cultures containing clinically relevant isolates mentioned previously. A database is being constructed in conjunction with the MicrobeID project, covering 4000 distinct species, to share information on species specific mass spectral patterns, species specific biomarkers, and the associated validation via traditional culturing and DNA sequencing of the 16S rRNA gene hyper-variable V3 to V4 regions, using the Illumina MiSeq platform.
Results and Discussion:
Preliminary data shows distinct mass spectral peaks from the species examined in defined mixed cultures containing clinically relevant bacterial species. Although, database generation is ongoing, this suggests that the technology and methodology can be optimised and applied to clinical samples without the pre-requirement of isolation of culture of bacteria. REIMS has high potential in further improving and simplifying workflows within clinical microbiology laboratories by hastening time to species identification and possibly providing strain level resolution. These potential improvements on existing MS methods will be investigated by obtaining a range of clinical samples, including urine and faeces, and performing microbiome analysis alongside traditional culturing techniques, as well as REIMS, in order to develop a methodology for identification of microbiota direct from clinical samples without the need for prior culturing.
References & Acknowledgements:
1. Tan KE, Ellis BC, Lee R, Stamper PD, Zhang SX, Carroll KC. Prospective Evaluation of a Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry System in a Hospital Clinical Microbiology Laboratory for Identification of Bacteria and Yeasts: a Bench-by-Bench Study for Assessing the Impact on Ti. J Clin Microbiol. 2012/08/03 ed. 2012;50(10):3301–8.
2. Krause E, Wenschuh H, Jungblut PR. The dominance of arginine-containing peptides in MALDI-derived tryptic mass fingerprints of proteins. Anal Chem. 1999/10/12 ed. 1999;71(19):4160–5.
3. Ryzhov V, Fenselau C. Characterization of the protein subset desorbed by MALDI from whole bacterial cells. Anal Chem. 2001/03/16 ed. 2001;73(4):746–50.
4. UK Standards for Microbiology Investigations: Matrix-Assisted Laser Desorption/Ionisation - Time of Flight Mass Spectrometry (MALDI-TOF MS) Test Procedure [Internet]. 2015. Available from: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/466035/TP40_dzg_.pdf
5. Reller LB, Weinstein MP, Petti CA. Detection and Identification of Microorganisms by Gene Amplification and Sequencing. Clin Infect Dis. 2007;44(8):1108–14.
6. 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. Sci Transl Med. 2009;1(6):6ra14–6ra14.
7. Angly FE, Dennis PG, Skarshewski A, Vanwonterghem I, Hugenholtz P, Tyson GW. CopyRighter: a rapid tool for improving the accuracy of microbial community profiles through lineage-specific gene copy number correction. Microbiome. 2014;2(1):11.
8. Strittmatter N, Rebec M, Jones E a., Golf O, Abdolrasouli A, Balog J, et al. Characterization and identification of clinically relevant microorganisms using rapid evaporative ionization mass spectrometry. Anal Chem. 2014/06/05 ed. 2014;86(13):6555–62.
9. Balog J, Sasi-Szabó L, Kinross J, Lewis MR, Muirhead LJ, Veselkov K, et al. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Sci Transl Med. 2013 Jul 17;5(194):194ra93.
| Description | Y/N | Source |
| Grants | yes | 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 |