Development of a rapid bacterial identification method based on direct mass spectrometric metabolic profiling

Lead Research Organisation: Imperial College London
Department Name: Dept of Surgery and Cancer

Abstract

The project is aimed at the development of new tools for the identifications of various microorganisms including bacteria causing a wide range of diseases from common cold to bloodstream infections. Knowing exactly which type of bacterium is involved in a disease is very important, since the choice of appropriate medication largely depends on it. Likewise, in case of public health or food safety, the correct classification of bacterial contaminations helps with the identification of their source and elimination of the contamination. Currently, samples containing bacterial cells are collected and sent to laboratories. Microbiologists grow the bacteria in Petri-dishes containing special nutrients. Based on the types of nutrients the bacteria can use and the results of multiple chemical tests, the bacterium is tentatively identified. If proper classification is necessary, nucleic acids are extracted from the bacterial cells, and their base-pair sequence is determined, which helps in the unambiguous identification. All of these processes are time consuming, which considerably delays the efficient intervention both in case of infectious diseases and in case of a waterborne disease outbreak.
The purpose of the proposed research is to develop an alternative, much faster technique for the identification of bacteria.
Mass spectrometry is an analytical technique capable of the measurement of the weight of molecules, and also the selective detection of hundreds of different molecules at the same time. We plan to use this well-established technique for looking at some special building blocks of bacterial cells. One novel aspect of the research is that mass spectrometers are not used in the traditional way, including a lengthy preparation of bacterial cells prior to analysis, but the cells are simply heated up, and electrically charged molecules formed on the boiling of cells are analysed using mass spectrometry. The idea of rapid mass spectrometric analysis by using simply heat has already been applied in case of surgery, where cancer tissue is identified in a similar way.
In course of the proposed project we plan the adopt this technology (Rapid Evaporative Ionization Mass spectrometry; REIMS) for the analysis of bacteria grown in the laboratory and also for the direct analysis of liquid samples (ranging from pond water to blood) containing bacterial agents. We plan to build a large library of the spectroscopic fingerprints of the bacteria, which will be used as a training set for computer based search algorithms. The method, the database and the algorithm together will enable the unambiguous identification of bacteria in considerably shorter timeframe than the current routine. Furthermore, the proposed research can potentially lead to an approach, where bacteria are directly identified in their natural environment (e.g. in urine for a urinary infection) without growing them in the laboratory for several hours or days.

Technical Summary

The proposed research is aimed at the development of a novel microbial identification and community analysis method. The method is based on the rapid evaporation of bacterial cells or matrix containing bacterial cells using high frequency alternating electric current followed by mass spectrometric analysis of electrically charged molecular species. The method - termed Rapid Evaporative Ionization Mass Spectrometry (REIMS) - is expected to yield spectral information featuring metabolic species and polar lipids. Since lipid synthesis pathways are conservative and specific to a given species, REIMS analysis of bacterial cells allows species-level identification, as it is already suggested by preliminary data. The REIMS data will be complemented by more traditional LC-MS data giving detailed information on the detected species. The proposed work comprises the development of corresponding analytical instrumentation followed by large scale data collection. Analysis of 150 bacterial strains (playing important role in food-borne diseases) is planned following culturing under a wide range of different conditions. The collected data will serve as a learning set for developing multivariate statistical machine learning algorithms in order to perform identification of unknown strains. Statistical models will also be utilized to understand the metabolic differences between different strains, species or families and correlate these with genetic differences. Community analysis methods based on REIMS and LC-MS will also be developed. Analytical and biological interferences will be studied using the two different mass spectrometric approaches and data processing approaches will be developed to compensate for these and achieve absolute quantification of different species in mixed communities. Effects of food and biofluid matrices will also be studied and the method will further be developed for the culturing free, quantitative detection of bacteria in various natural matrices.

Planned Impact

The proposed research is aimed at the development of new chemotaxonomic bacterial identification methods and corresponding extensions suitable for the analysis of microbial communities. The main advantages of the envisioned methods include the possibility of real-time analysis, culturing-free analysis, improved quantification of bacterial species in communities and extended amount of information on the actual phenotype of the species. This latter point is important when the question is not aimed at the taxonomical classification of the bacterial strains, but rather at their biochemical function.
Beneficiaries
The primary beneficiary of the research is the Mass Spectrometry Division of Waters Corporation (Manchester, UK), utilizing the developed technologies in the form of products marketed for bacterial identification for various customer groups. In this sense, the following groups can directly benefit from the expected results of proposed project:
- Microbiologist researchers
- Clinical microbiologists
- Biotechnology professionals/companies
- Food safety authorities/food industry
- Pharma industry
Indirectly the entire society can benefit from these developments by receiving quicker and more accurate medical care in case of infectious diseases, by consuming safer food (including drinking water) items containing harmful bacteria at lower probability, having access to new pharmaceuticals produced by more reliable biotechnological processes and living in a cleaner environment, just to mention a few of the broader impacts.

Publications


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Description The funding by this grant has allowed for both developing of diagnostic platforms, proof of their efficacy, and new findings to extend their clinical impact. Support from this grant has allowed the development of an automated, high-throughput rapid evaporative ionisation mass spectrometry (REIMS) platform, which is highly suited to modern clinical microbiology diagnostic laboratories. To support the development of a REIMS classification model to identify pathogens, we have collected approximately 5,000 isolates from approximately 400 microbial species, including bacteria, yeast, and filamentous fungi, alongside DNA speciation and whole genome sequence data for relevant isolates. We have also used the same REIMS platform for the detection of antimicrobial resistance in important human pathogens, including methicillin resistant Staphylococcus aureus and vancomycin-resistant Enterococcus spp. This is possible without exposing the bacterial isolates to antibiotics, which reduces the time to results by approximately 24 hours. This type of analysis is not currently possible with any commercially available mass spectrometry platform. Again, using exactly the same analytical set-up as for microbial identification, we have shown that REIMS is capable of the detection of sub-species types of bacteria, including the important human pathogens Escherichia coli, Clostridium difficile, and Pseudomonas aeruginosa. Establishing sub-species strain types of bacteria is very important for tracking outbreaks of pathogens in hospitals, and current methods rely on DNA sequencing which can take up to one week at best to receive results. Using REIMS, we have shown that we are able to achieve sub-species strain types at the same type as species identification is achieved. As before, this information cannot be collected using other commercially available mass spectrometry platforms.
Exploitation Route The work supported by this grant will benefit, and provide opportunities for, the wider research community in a number of ways. For example, the development of a comprehensive microbial metabolomic and genotype database which could be utilised in a diverse range of disciplines. Furthermore, the mass spectrometry platform, being developed in collaboration with the Waters Corporation, will be commercialised and available globally; thereby allowing it to be exploited by researchers.
Sectors Agriculture, Food and Drink,Energy,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology
URL http://pubs.acs.org/doi/abs/10.1021/acs.analchem.6b01016
 
Description Clinical Impact 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. Currently available commercial systems require preparative steps and are currently reliant on cultured microbial material. Whilst early studies utilised bipolar forceps a high throughput adaptation, suitable for clinical laboratories, was recently described. As part of this project a customised colony picking robot (TECAN EVO Freedom instrument) with an integrated colony visualisation platform (Pickolo) was developed in collaboration with Waters Corporation. This provides a single platform for automated colony picking, REIMS analysis and molecular processing. Species specific mass spectral fingerprints are generated by applying a radiofrequency electrical current (100kHz - 4MHz) directly to the microbial colony using a stainless steel monopolar probe. The resulting vapour, containing gas phase ions of metabolites and structural lipids, is channelled to a Xevo G2-XS QToF instrument for REIMS analysis. This technology is amenable to high throughput workflows characteristic of clinical microbiology laboratories. Current REIMS workflows allow approximately 4,000 to 5,000 microbial colonies to be analysed over a 24 hour period, with species-level identifications given in near real-time. This level of throughput would streamline diagnostic workflows, increase productivity which, in turn, should improve turn around and diagnostic times. Further modifications to the automated, high-throughput REIMS have been completed as part of this project. This includes the addition of laser ablation to the REIMS modalities. To date, electricity has been used to rapidly heat and evaporate a sample. However, this necessitated contact to be made between the sample and analysis probe, and that the sample was capable of conducting electricity. However, using radiative heating removes both of these requirements and thus substantially increases analytical throughput. Current, commercially available MS platforms for microbial identification are limited to fingerprinting of cellular proteins; they are unable to perform additional analysis of clinically important characteristics, such as antimicrobial susceptibility testing and sub-species typing. Using our REIMS platform, we have been successful in developing a species-level identification database for a wide range of clinically important microorganisms. In addition, we have been successful in analysing Escherichia coli and Pseudomonas aeruginosa, both highly important human pathogens, and developing a classification model for assigning sub-species identifications. This is particularly useful for epidemiology and determining infection outbreaks within hospitals, and REIMS offers a system that would allow sub-species identifications in less than 24 hours, compared to approximately one week using current methods. Additionally, we have also used REIMS to identify biomarkers of antibiotic resistance in vancomycin resistant Enterococcus spp. and Staphylococcus aureus. These biomarkers are present without exposing the bacteria to antibiotics, thereby reducing the time to antimicrobial susceptibility testing by approximately 24 hours. Economic Impact Our industrial partnership with Waters Corporation; a global analytical instrument manufacturer will be pivotal in developing the commercialisation of this platform for a diagnostic and research market. Waters has pioneered the introduction of mass spectrometric methodology into the medical diagnostic field, with clear intentions to extend its current clinical operations to microbiome research. The technology resulting from the proposed research will be tested at the Department of Microbiology of the Imperial College Healthcare NHS Trust and will enter Waters Corporation's product development pipeline thereby boosting the UK economy. In addition, we are developing REIMS as a platform for microbial testing beyond clinical microbiology, in industries such as pharmaceutical manufacturing, food testing, and veterinary microbiology. Currently, these industry sectors rely on traditional biochemical and phenotypic testing for identifications, which are time-consuming and costly. REIMS could bring a wide range of cost-savings to these sectors, thereby increasing productivity and economic impact. Other societal impacts This project has already produced a significant biomarker database comprising nearly 3000 taxonomical markers. Their identification and further characterisation, using the UPLC-MS method described in the outputs section, is expected to form the basis to a direct from sample diagnostic tool. Initial data on mixed bacterial cultures looks promising as species specific biomarkers can be identified and thus it is likely that a REIMS based diagnostic tool could be developed for direct from sample testing. At present most traditional culture based diagnostic methods have low sensitivity and the time to identification is long; requiring at least 24-48 hours. A direct from sample technology would completely change the current paradigm; allowing clinicians timely decisions on whether to treat and how to treat. Clinicians often consider the use of antibiotics to be 'risk free' and they are more likely to initiate therapy as a precautionary measure. The decision of when to start and stop treatment is complicated by various factors; firstly many signs of infections are non-specific, secondly, confirmation of infection often relies upon time consuming culture based techniques and thirdly, the doctor has to balance the risk of delaying treatment. Rapid point of care diagnostic technologies will allow physicians to base their prescribing on evidence based data thereby improving clinical outcomes and costs. Furthermore, this will ensure that antibiotics are used appropriately, in a timely manner and the information can be integrated with current antimicrobial stewardship procedures. It is expected that this would be of great benefit to society as it will improve clinical outcomes, shorten the patient journey and will ensure the efficacy of antibiotics can be maintained by curbing the development of antibiotic resistance. Impact on research areas of great importance to society The REIMS spectral database, created as part of this project, provides a unique and novel tool for the investigation of microbial metabolites. This unique database, created in collaboration with Waters Corporation, provides spectral, 16S rRNA/ internal transcribed spacer region (ITS) and, in some instances, whole genome sequence data for thousands of microbial isolates. Once complete this database will be made publicly available and will therefore be a comprehensive platform for microbial research. By offering both metabolic and genotypic information this library can be used to examine the dynamic relationships between microbial genetics, metabolomics and both biological and phenotypic processes. As outlined earlier, we have successfully applied REIMS to the determination of antibiotic susceptibility of important human pathogens, including Staphylococcus aureus and vancomycin-resistant Enterococcus spp. Current, clinical methods take approximately 24 hours as exposure to antibiotics is required. However, REIMS is capable of detecting biomarkers of antibiotic resistance without exposure to antibiotics, thereby reducing the time to identification of resistance by approximately 24 hours; meaning patients will receive appropriate treatment sooner, improving their potential treatment outcomes. Antimicrobial resistance is a significant economic burden and numerous costs including increased infection control procedures such as side rooms, the use of for more expensive antimicrobials and poor patient outcome have been cited. Their rapid identification will allow for directed therapy which in turn will have a significant impact upon patients as it has been shown to reduce hospital stays and improve morbidity and mortality rates. If we consider that each year over 50,000 people are estimated to die from antimicrobial resistant infections and the World Economic Forum considers antimicrobial resistance to be one of the most pressing risks to human health it is clear that a rapid diagnostic tool and deeper understanding of resistance mechanisms is required. The creation of a REIMS-based biomarker and spectral database for microbial taxonomic classification will have obvious benefits to its development as a clinical diagnostic platform but such a database will have applications beyond clinical microbiology laboratories. For example, a rapidly developing field of microbiology research is characterisation of the taxonomic composition and functional capacity of microbiomes in humans, animals, and the natural and built environment. Current methods rely on DNA or RNA sequencing to characterise the microbiome, but these are time and resource intensive. The development of a REIMS-based biomarker and spectral database has utility to act as an alternative to sequencing-based approaches to reduce cost and time of analysis. Further potential applications of the database which will be developed in this project include the analysis of microbial contamination of controlled mixtures and reactions, such as animal cell lines, fermentation starting cultures, and pharmaceutical product manufacturing and quality control.
First Year Of Impact 2015
Sector Healthcare,Pharmaceuticals and Medical Biotechnology,Other
Impact Types Societal,Economic,Policy & public services
 
Description Invited seminar and discussion at Food and Drug Administration
Geographic Reach North America 
Policy Influence Type Participation in a national consultation
 
Title High throughput Rapid Evaporative Ionisation Mass Spectrometry (REIMS) 
Description Rapid Evaporative Ionisation Mass Spectrometry (REIMS) for the identification and characterisation of microbes was first described in 2013. At this time the technique used bipolar forceps to collect and vapourise bacteria and fungi. Although this method accurately speciated bacteria and fungi with an accuracy of 95.9%, 97.8%, and 100% to species, genus, and gram stain level, respectively it needed to be optimised to suit the high throughput workflows of clinical diagnostic laboratories. High throughput REIMS was developed as part of this project in collaboration with Waters Corporation. A colony picking robot (Tecan FREEDOM 75 instrument), was customised, with Waters Corporation, to incorporate a colony visualisation platform (Pickolo) and a colony picking function. This adapted instrument provides an automated, high throughput method for REIMS analysis with reduced variability, and user input making it well suited to implementation in clinical microbiology laboratories. 
Type Of Material Biological samples 
Provided To Others? No  
Impact Once developed this technology will provide a novel platform for the identification and characterisation of microbes in a clinical laboratory. In contrast to other commercially available microbiology based mass spectrometry technologies REIMS does not require any preparative steps and thus it is envisaged that the platform will be able to analyse approximately 4,000 to 5,000 microbial colonies over a 24 hour period. This will have an impact on a laboratories turn around times and will improve time to identification, which in turn will have a significant economic and clinical impact. 
 
Title Laser Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) 
Description As previously detailed, as part of this funded project, optimisation of Rapid Evaporative Ionisation Mass Spectrometry (REIMS) was completed to incorporate the technology into a colony picking robot (Tecan FREEDOM 75 instrument), with Waters Corporation, to allow colony visualisation, colony picking, and direct REIMS analysis. This adapted instrument provides an automated, high throughput method for REIMS analysis with reduced variability, and user input making it well suited to implementation in clinical microbiology laboratories. As further modifications to this platform, we have recently inserted an additional REIMS modality in the form of radiative heating, using a laser, to further improve analytical sensitivity and throughput. The incorporation of a laser into the automated high-throughput REIMS platform removes the necessity to make contact between the sample undergoing analysis and the heating implement. This allows both an increased analytical throughput, and also a wider range of biological samples to be analysed. 
Type Of Material Biological samples 
Year Produced 2016 
Provided To Others? Yes  
Impact This LA-REIMS platform is currently be developed for a wide range of applications, in collaboration with a number of researchers. For example, it has been used in the analysis of faecal samples from patients with inflammatory bowel disease (IBD), to develop metabolomic profiling methods for disease stratification and treatment response prediction, and int he development of direct-from-sample pathogen detection. 
 
Title Creation of a REIMS culture collection 
Description The initial part of the project involved generating a library of micro-organisms to populate the spectral library so that fingerprint spectra, characteristic of each species, could be collected. At present the REIMS micro-organism collection comprises over 2500 isolates encompassing 105 genera and 296 species. These have been taxonomically classified using the Bruker Microflex LT, and 16S rRNA analysis is currently underway. This collection has been used to populate the REIMS spectral library which is currently being created so the identity of unknown organisms can assigned. Data analysis of this database has already lead to the identification of nearly 3000 species specific biomarkers that will be critical for the development of a direct from sample diagnostic device. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact This culture collection will form the basis to the REIMS spectral library and will therefore have the benefits described for output 1. 
 
Title Identification of species specific biomarkers 
Description As discussed in previous outputs, species specific biomarkers have been identified and characterised to enable the detection of individual microbes from mixed cultures. A graphical user interface for identifying bacterial specific biomarkers has been developed using a machine learning method (Random Forest). For each level of the taxonomy, a random forest model is built and cross-validated using a leave-one-out method and the peaks that better contributes to the classification are annotated using a single peak matching algorithm. A force-directed network between taxonomic terms and annotated peaks is built using Cytoscape.js and a html page is created to plot the network and the list of annotated peaks tabulated including the importance of each peak in the correct classification of the profiles. 
Type Of Material Data analysis technique 
Provided To Others? No  
Impact This work will provide a useful tool for research communities as it details well characterised microbial metabolites which can provide taxonomical information. 
 
Title Lipid biomarker database 
Description A curated lipids database with 2937 entries has been created, in collaboration with Waters Corporation, using a single peak matching algorithm for identifying metabolites. The algorithm identifies a metabolite when the mass of a peak is the lipid mass ± a tolerance. This unique biomarker database comprises well characterised metabolites from a diverse collection of micro-organisms. In the future these biomarkers will be used to diagnose infections directly from clinical samples. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The development of a well characterised, publicly available, species specific biomarker database will be be of great benefit to the research community. Using the information it will be possible to investigate these biomarkers in many biological processes such as antimicrobial resistance. The database will also allow the development of a REIMS based direct from sample diagnostic tool. 
 
Title OMB development 
Description An integrated bioinformatics platform, called Offline Model Builder (OMB), has been developed by Waters Corporation for the streamlined spectral analysis of thousands of microbes analysed as part of this grant. This software, validated on model data provided by Professor Takat's team at Imperial College, first pre-processes the data by incorporating a lockmass correction and a background subtraction model. After normalising and binning, classification models are built using principle component analysis (PCA) and supervised linear discriminant analysis (LDA) for classification. It is envisaged that OMB would be used within a clinical diagnostic setting and thus the platform is user friendly and provides an output that is simple, clear and requires no further interpretation by the user. 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact The development of a user friendly software package for the analysis and interpretation of mass spectral analysis of micro-organisms will be beneficial when trying to develop REIMS technologies for clinical diagnostics. By creating a simple software package, that is easy to use and provides an output requiring no user interpretation, clinical workflows will be shortened and user related errors will be minimised. 
 
Title REIMS spectral library 
Description Over the last year a REIMS spectral library comprising nearly 3000 bacteria and fungi has been created. This will be an important resource for metabolomic research in micro-organisms and will also be key for the development of a clinical diagnostic device. As part of the REIMS process the spectrum, characteristic of each bacteria species, will be acquired and then compared to a database containing the spectral fingerprints from well characterised micro-organisms. A species assignment will be made by matching the spectrum to a lipidomic fingerprint within the REIMS library using a pattern recognition software, currently being developed by Waters Corporation. Both this spectral library and the biomarker library discussed in previous outputs, will be made publicly available thereby providing a unique research tool. 16S rRNA and, in some instances, whole genome sequence data, will also be available for each isolate. This unique database comprising thousands of entries, will boost research into diagnostics, antimicrobial resistance, and deepen our understanding of how microbial genetics and metabolomics influences biological and phenotypic processes. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The development of a publicly available REIMS spectral library which encompasses 16s rRNA and, in some instances, whole genome sequnce data, will have two significant impacts. Firstly, this output will be of great use to researchers in the future as it will provide a unique tool for the investigation of microbial metabolites and will assist in defining phenotypic features including virulence and antibiotic resistance. Secondly, its creation will form the basis to a REIMS tool for microbial identification and characterisation. Therefore, this will have a significant impact upon clinical diagnostics. 
 
Description Dr Gerald Larrouy-maumus 
Organisation Imperial College London (ICL)
Department Department of Life Sciences (encompassing Biology)
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Professor Takat's and his research group will be developing REIMS based analytical tools and will perform REIMS analysis on the Mycobacterium isolates provided by Dr Gerald Larrouy-maumus.
Collaborator Contribution Dr Gerald Larrouy-maumus is a Lecturer in Molecular Microbiology based at Imperial College. He has been characterising the cell wall envelope of a range of Mycobacterium species. He has provided these for use within this project.
Impact The well characterised Mycobacterium isolates provided by Dr Gerald Larrouy-maumus form part of the REIMS strain collection. This collaboration draws together expertise in analytical chemistry and molecular micorbiology.
Start Year 2015
 
Description Dr Lesley Hoyles 
Organisation Imperial College London (ICL)
Department Imperial College Trust
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Charity/Non Profit 
PI Contribution Professor Takat's and his team will develop REIMS for the characterisation of microbes and will perform REIMS based metabolomic profiling on bacteria and fungi. The group will also perform 16S rRNA based analysis on the isolate using an Illumina MiSeq platform.
Collaborator Contribution Dr Lesley Hoyles, a research fellow in in Data Science, has extensive experience in the genomic analysis of micro-organisms and is currently developing a metagenomic pipeline. She will advise on the analysis of our genetic data and is also providing well characterised strains of anaerobic bacteria.
Impact This multidisciplinary collaboration has enabled the incorporation of well characterised aerobic bacteria, provided by Dr Hoyles, into the REIMS database. The collaboration draws together expertise in analytical chemistry, clinical diagnostics, microbiology and metagenomic analysis.
Start Year 2015
 
Description Imperial College Healthcare NHS Trust 
Organisation Imperial College Healthcare NHS Trust
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Hospitals 
PI Contribution The multidisciplinary team is led by Professor Takats and his research group who have extensive experience in analytical chemistry, the development of mass spectrometry based diagnostic technologies, clinical microbiology and molecular based methods including sequencing and PCR. Professor Takat's group are responsible for the development of a REIMS based tool for the metabolomic and lipidomic characterisation of microbes.
Collaborator Contribution Dr Hugo Donaldson and Monica Rebec, are based within Imperial College Healthcare NHS Trust (ICHNT) Microbiology department which operates centralised services from the Charing Cross Hospital site to all ICHT, Chelsea & Westminster and West Middlesex University Hospitals as well as surrounding GP services and clinics. The laboratory offers a comprehensive service for the diagnosis of infectious diseases. Dr Hugo Donaldson provides expertise in clinical microbiology and Monica Rebec advises on sample processing within a clinical laboratory. An agreement has been set up allowing members of the team to obtain micor-organisms and to utilise their facilities.
Impact The multidisciplinarycollaboration draws together expertise in analytical chemistry and clinical microbiology. As described in detail within the output section this collaboration has been central to the development of a REIMS culture collection. REIMS analysis of this collection will provide the metabolomic data required to populate the REIMS spectral library.
Start Year 2015
 
Description Royal Brompton Hospital 
Organisation Royal Brompton & Harefield NHS Foundation Trust
Department Royal Brompton Hospital
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Hospitals 
PI Contribution Professor Takat's and his team will be developing and performing REIMS analysis on the fugal isolates provided by Dr Darius James-Armstrong.
Collaborator Contribution Dr Darius James-Armstrong is an Infectious Disease clinician with an expertise in fungal infections. He has therefore been providing fungal samples and offering clinical advice on fungal diagnostics.
Impact As detailed within the outputs section fungal isolates, provided by Dr James-Armstrong, have been analysed using REIMS and form part of the spectral database.
Start Year 2015
 
Description American Society of Mass Spectrometry 2016 Annual Conference (San Antonio, USA) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Presentation at American Society of Mass Spectrometry 2016 annual conference. Due to the nature of the conference, this led to a number of discussions with international participants from both academic and industrial research organisations.This sparked a number of questions and discussions, leading to the development of a collaborative project.
Year(s) Of Engagement Activity 2016
 
Description Mass Spectrometry Applications to the Clinical Laboratory USA 2016 Annual Conference (California, USA) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Presentation at Mass Spectrometry Applications to the Clinical Laboratory 2016 annual conference. Due to the nature of the conference, this led to a number of discussions with international participants from both academic and industrial research organisations.This sparked a number of questions and discussions, leading to the development of acollaborative project.
Year(s) Of Engagement Activity 2016
 
Description Mass Spectrometry Applications to the Clinical Laboratory USA 2017 Annual Conference (California, USA) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Presentation at Mass Spectrometry Applications to the Clinical Laboratory 2016 annual conference. Due to the nature of the conference, this led to a number of discussions with international participants from both academic and industrial research organisations.This sparked a number of questions and discussions, leading to the development of acollaborative project.
Year(s) Of Engagement Activity 2017
 
Description Metabolomics Society 2016 Annual Conference (Dublin, Ireland) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Presentation at Metabolomics 2016 annual conference. Due to the nature of the conference, this led to a number of discussions with international participants from both academic and industrial research organisations.This sparked a number of questions and discussions, leading to the development of acollaborative project.
Year(s) Of Engagement Activity 2016
 
Description Microbiology Society UK Annual Conference (Manchester, UK) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact Presentation at Microbiology Society UK annual conference and related discussion with academic/industry researchers. This sparked a number of questions and discussions, leading to the development of two collaborative projects.
Year(s) Of Engagement Activity 2016