26 TMJ 2008, Vol. 58, No Michal Drevinek. abstract ORIGINAL ARTICLES

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1 ORIGINAL ARTICLES MASS SPECTROMETRY - A POWERFUL TOOL IN RAPID IDENTIFICATION OF BIOLOGICAL WARFARE AGENTS Michal Drevinek REZUMAT Identificarea rapid\ [i sigur\ a microorganismelor patogene este de importan]\ crucial\ pentru securitatea unei ]\ri. Metode utilizate n mod obi[nuit sunt ndeob[te laborioase [i de durat\. Recent, tehnici de spectrometrie de mas\, cum ar fi MALDI-ToF [i ESI au fost introduse n domeniul microbiologiei. n special amprentarea MALDI-ToF MS, prin care se ob]in profiluri tipice de spectrometrie de mas\, este o unealt\ puternic\ pentru identificarea rapid\ [i clasificarea microorganismelor. Astfel de amprente pot fi folosite pentru identificarea prin compara]ie cu baze de date de referin]\ dedicate. Aceast\ metod\ este adecvat\ pentru analize uzuale de nalt\ tehnicitate [i d\ rezultate sigure. n mod obi[nuit, se poate ob]ine identificarea p n\ la nivel de specie, uneori chiar p n\ la nivel de subspecie sau tulpin\. Tehnica relativ simpl\ de preg\tire a probelor, acurate]ea [i viteza cu care pot fi ob]inute datele fac din analiza celular\ MALDI-ToF MS un instrument puternic, potrivit n special pentru detectarea agen]ilor biologici. Mai mult, simplitatea procedurii reduce riscul de accidente n cursul proces\rii probelor. Cuvinte cheie: bacterie, patogen, MALDI, spectrometrie de mas\, analiz\ celular\ abstract Rapid and reliable identification of pathogenic microorganisms is of crucial importance for homeland security. Commonly used methods are usually laborious time consuming. Recently, mass spectrometric techniques like MALDI-ToF and ESI have been employed in the field of microbiology. Especially MALDI-ToF MS fingerprinting, where typical profile mass spectra are acquired, is a powerful tool for fast microorganism identification and classification. Such fingerprints can be used for the identification by comparison with dedicated reference databases. The method is suitable for high throughput routine analysis and gives reliable results. Commonly, identification to the species level, sometimes even subspecies or strain level can be obtained. Relatively simple sample preparation technique, the accuracy and speed with which data can be obtained makes whole-cell MALDI ToF MS a powerful tool especially suited for detection of biological agents. Furthermore, the simplicity of the overall procedure reduces a risk of an accident during laboratory sample processing. Key Words: bacteria, pathogen, MALDI, mass spectrometry, whole cell analysis INTRODUCTION The laboratories involved in protection against biological threats have to cover large number of pathogens of different nature - bacteria, viruses, rickettsia, fungi, toxins, GMOs etc. The ability to detect and identify pathogens and potential bioterrorism agents rapidly would greatly enhance response to these threats and aid in the timely treatment of individuals exposed. Laboratory of Biological Monitoring and Protection, National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic Correspondence to: Michal Drevinek, National Institute for Nuclear, Biological and Chemical Protection, Pribram - Kamenna, Milin, Czech Republic drevinek@sujchbo.cz Received for publication: Feb 05, Revised: May 07, Current diagnostics of biological agents is quite complicated and can be carried out using several methods. Unfortunately, none of them is sufficiently reliable, cheap or fast. Serological diagnostics is difficult because of the number of species; large numbers of antibodies are not commercially available and some of the species are difficult to identify due to cross-reactions. Molecular biology methods (mainly PCRa RNA/DNA hybridization) require large collection of primers and probes; reaction conditions are specific (time consuming in classical setup). Sequencing of specific genes, currently the only method for reliable identification and taxonomy, can be carried out only in large and well-equipped laboratory centres. FTIR, PYMS and other instrumental techniques are usually not sufficiently discriminative. Possible solution - use of microarray techniques is currently under development and is not routinely 26 TMJ 2008, Vol. 58, No. 1-2

2 used in laboratories dealing with biological agents identification. There is a need of simpler, faster, more reliable and versatile method, which would be able not only to identify the species related to biological warfare, but also to discriminate them on the subtype and strain level. Mass spectrometric techniques used for analysis of biomolecules include mainly electrospray ionisation (ESI) and Matrix Assisted Laser Desorption/Ionization Time of Flight (MALDI-ToF) mass spectrometry. In MALDI-ToF mass spectrometry, sample preparation is relatively simple. Purified or crude sample is dispersed in a large excess of matrix material, which strongly absorbs the incident light, and co-crystallized on a target plate that is placed into the mass spectrometer. In most microbiological applications, a N 2 laser (337nm) is used to generate the ions. Short pulses of laser light focused onto the sample spot cause the sample and matrix to volatilize. The ions formed are accelerated by a high voltage supply and then allowed to drift down a flight tube where they separate according to mass. The use of MALDI-ToF mass spectrometry for the characterization of large biomolecules led to successful applications involving the analysis of isolated and purified bacterial proteins. Consequently, MALDI-ToF MS was applied directly to crude cellular fractions or cellular suspensions to produce data from these complex mixtures that could provide evidence for chemotaxonomic classification. Recently, this technique has been successfully applied to intact bacterial cells, providing reproducible spectral profiles. 1-8 MATERIALS AND METHODS A list of bacteria studied is given in Table 1. The analysis of sample starts with applying a small amount of biological material on a MALDI target. The starting material can be a single colony or a centrifuged portion of a liquid culture. According to the nature of starting material, the sample can be deposited on the target using 3 methods: - Thin film small amount of a culture is transferred onto a platform in a form of thin film - Supernatant small amount of a culture is dispersed in 50% MeCN, vortexed and centrifuged at rpm for 5 min. 1 μl of supernatant is transferred onto a platform - Pellet a pellet is deposited on a platform after decantation After the deposition the microbial sample is covered with a matrix solution and the mixture is airdried. A saturated solution of HCCA (alpha-cyano-4- hydroxycinnamic acid) in 50% acetonitrile with 2.5% TFA was used as MALDI matrix. About 105 cells can be measured accurately, but detection limits of 103 spores have been reported. To enhance sensitivity in the case of low sample amount, a concentration is possible and sensitivity can be increased by a factor of 10 to 40 fold. Mass spectra were acquired using Bruker AutoFlex MALDI-ToF mass spectrometer in linear positive mode at frequency Hz with pulsed ion extraction and automated spectra acquisition. Pattern matching for identification of unknown microorganisms was accomplished through comparison of the generated peak lists with a library of stored spectra that contain the characteristic spectral information of species. The library spectra were generated by measurement of known bacterial species and strains. The software automatically generates the peak lists from the whole set of spectra and extracts the typical peaks which are present in a certain number of spectra from one species. Additionally, the fully automated main spectra generation which starts with raw spectra, allows to manually input information before calculation of main spectra. Table 1. List of bacteria studied using whole-cell MALDI-ToF mass spectrometry. High risk biological agents Risk biological agents Other bacteria (genus) Bacillus anthracis, Brucella melitensis, Burkholderia mallei, Burkholderia pseudomallei, Clostridium botulinum, Francisella tularensis, Salmonella typhi, Shigella dysenteriae, Vibrio cholerae, Yersinia pestis Brucella melitensis bv. canis, Clostridium tetani, Legionella pneumophila, Mycobacterium africanum, Mycobacterium bovis, Mycobacterium microti, Mycobacterium tuberculosis, Mycobacterium ulcerans, Xanthomonas albilineans, Xanthomonas campestris pv. citri, Yersinia pseudotuberculosis Acinetobacter, Aeromonas, Alcaligenes, Arcanobacterium, Bacillus, Branhamella, Budvicia, Buttiauxella, Campylobacter, Cedecea, Citrobacter, Corynebacterium, Geobacillus, Legionella, Listeria, Proteus, Plesiomonas, Serratia, etc. Michal Drevinek 27

3 This enables manual spectra processing and peak list editing before the main spectra are generated for a database. Identification of unknown microorganisms was performed by comparing their individual peak lists with the database. A matching score based on identified masses and their intensity correlation was generated and used for ranking of the results. RESULTS Different compositions of growth media had little effect; in the peak pattern distribution in the range of 4000 to Da nearly no influence of culture medium was observed. This is based on the measurement of constantly expressed high-abundant proteins, i.e. ribosomal proteins. The presence of culture medium adhering to the colonies had no effect and no additional signals appear. More dependency on growth and environment conditions appear if measurements are focused on the lower mass range (i.e Dalton) where not proteins but also cell wall components and metabolites may appear. Despite of these facts, standard conditions were strictly followed during the procedure of database spectra generation - the cultures were grown always on appropriate media under controled conditions; the platform sample preparation method for each bacteria was always the same. The culturing and spectra acqusition were repeated at least three times for each bacterial strain; every culture giving at least nine samples. Spectra of the bacterial pathogenes listed in Table 1 were acquired and mathematical processing (mass correction, smoothing, baseline subtraction, normalized spectra and normalized signal generation) was applied. Figure 1 illustrates the differences among three pathogenic bacteria, while Figure 2 shows normalized signal intensities with normalized peak frequencies for Yersinia pestis. It is obvious that the spectra are complex and dedicated software for evaluation and comparison has to be employed. x x Figure 1. Comparison of Salmonella typhi, Vibrio cholerae and Brucella melitensis spectral profiles. Figure 2. Normalized signal intensities with normalized peak frequencies for Yersinia pestis SLin, Smoothed, Baseline subtracted(0.8) BioTyper (Bruker Daltonik) was used for spectra processing, peak list generation, generation of main spectra libraries, identification of unknown spectra etc. For the identification, two approaches are available: main spectra projection (MSP) and principal component analysis (PCA). 9 In MSP, the identification results are given as graphical output and as a table containing detailed identification information in a ranking list. (Table 2) After the spectral database creation, the spectra were compared to each other. PCA revealed inconsistencies in datasets corresponding to several species. Cluster analysis of these datasets and consecutive identification using PCR confirmed incorrect taxonomy of approximately 20% of the strains used for the reference database SLin, Smoothed, Baseline subtracted(0.8) SLin, Smoothed, Baseline subtracted(0.8) m/z Table 2. Identification of Yersinia pestis using spectral database. 28 TMJ 2008, Vol. 58, No. 1-2

4 Figure 3 illustrates a 3D plot of Yersinia pestis strains based on PCA. As a result, a pilot project employing MALDI-ToF mass spectrometry for taxonomical purposes of a type culture collection was started; the results will be published elsewhere. Figure 3. Yersinia pestis cluster analysis 3D plot: strain 10029, (cluster 1), (cluster 2), 10329, 2028, 2868, 570, 5923 (cluster 3). DISCUSSIONS The results presented in this study demonstrate that bacterial pathogens can be analysed using MALDI- ToF MS to yield reproducible high intensisty intact protein ions in the range 2-20 kda, that are species specific and the combination of these ions spectral profiles can be used for unambiguous identification. Another advantage of the method lies in possibility to detect and identify multiple pathogenic species in mixed cultures. Due to the novelty of the technique no spectral library of studied microorganisms was available. Therefore a unique database corresponding to 287 strains belonging to 21 species of risk and high risk bacterial pathogenes was created. (Table 1) Because of the heterogenous composition of the samples, statistical approach employing (among other parametres) also frequency of peak occurrence requires sufficiently large dataset for each species/strain. For that reason each strain was typically cultured 5 times and 10 spectra acquired for each culture, resulting in more than 14,000 spectra of above mentioned strains and more than 30,000 spectra including non-pathogenic bacteria as a database input to guarantee high robustness and reliability of the method. Cross-comparison of appropriate datasets revealed a presence of several contaminated or previously incorrectly identified cultures obtained from type strain collections. Routinely used PCR methods, employed for the identification, were not able to detect the contamination; to overcome this drawback, each culture would have to be tested on presence of all possible contaminants, which would be tedious and in many cases unfeasible task. On the other hand, mass spectrometry uncovers the presence of contamination easily and reliably. Internal blind study, employing 94 samples of all 21 studied bacteria, was 100% accurate at the species level and proved high discriminating capability of the technique. On the strain level, the accuracy achieved was 74%. This lower level was caused by substantial similarity among some of the strains. However, as no genetic data were available for these strains, it is possible that these cultures were genetically identical. To prove discrimination capabilities of the method on the strain level, further investigation based on classification using genom sequencing will be necessery. CONCLUSION MALDI-ToF MS is a high throughput and reliable method for the classification and identification of pathogenic microorganisms. The robust method requires minimal sample preparation efforts and life cycle costs. This process, when utilized in combination with dedicated analysis software, allows the unambiguous identification of bacteria or spores. The general workflow of microorganism profiling is a straightforward approach starting from a single colony or other biological material, sample deposition and preparation with MALDI matrix is performed within a few minutes. After sample drying the spectra acquisition is completed rapidly and identification or classification is seamless and quick. MALDI-ToF MS needs no initial assessment (like gram staining, oxidase test of unknown samples or choice of PCR primers). A dedicated database for comparison of any new sample is sufficient for analysis. The method proved to be an attractive alternative to current routine microbiological technologies used for identification of pathogenic bacteria or their spores. REFERENCES 1. Vargha M, Takats Z, Konopka A, et al. Optimization of MALDI- TOF MS for strain level differentiation of Arthrobacter isolates, J Microbiol Met 2006;66(3): Pignone M, Greth KM, Cooper J, et al. Identification of mycobacteria by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry, J Clin Microbiol 2006;44(6): Donohue MJ, Smallwood AW, Pfaller S, et al. The development of a matrix-assisted laser desorption/ionization mass spectrometrybased method for the protein fingerprinting and identification Michal Drevinek 29

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