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1 Systematic and Applied Microbiology xxx (2010) xxx xxx Contents lists available at ScienceDirect Systematic and Applied Microbiology journal homepage: Rapid identification of Legionella spp. by MALDI-TOF MS based protein mass fingerprinting Valeria Gaia a,b,, Simona Casati a,b, Mauro Tonolla a,c a Cantonal Institute of Microbiology, Bellinzona, Switzerland b National Reference Centre for Legionella, Bellinzona, Switzerland c Microbial Ecology, Microbiology Unit, Plant Biology Department, University of Geneva, Switzerland article Keywords: Legionella spp. MALDI-TOF MS mip Identification Sequencing Taxonomy info abstract A set of reference strains representing 38 different Legionella species were submitted to Whole Cell Mass Spectrometry (WCMS) with MALDI-TOF. The dendrogram computed from strain mass spectral patterns obtained by WCMS was compared to the phylogenetic tree obtained from macrophage infectivity potentiator (mip) sequences. The trees inferred from these two methods revealed significant homologies. Using 453 Legionella isolates previously characterized by genotyping, it was possible to create speciesspecific SuperSpectra, using appropriate sets of spectral masses, allowing unambiguous differentiation and identification of the most frequently isolated Legionella species. These SuperSpectra were tested for their suitability to identify Legionella strains isolated from water samples, cooling towers, potting soils and patient specimens deposited at the Swiss National Reference Centre for Legionella and previously identified by molecular methods such as mip gene sequencing. 99.1% of the tested strains isolated from the environment could be correctly identified by comparison with the new SuperSpectra. The identification of Legionella spp. by MALDI-TOF MS is rapid, easy to perform and has the advantage of being time- and cost-saving, in comparison to sequence-based identification Elsevier GmbH. All rights reserved. Introduction Species of Legionella cause severe forms of pneumonia called Legionnaires disease. The first outbreak occurred in 1976 in a hotel in Philadelphia, where the state convention of the American Legion was taking place: of 182 legionnaires who contracted the disease, 29 died. Legionella pneumophila was reported as the causal agent for the first time a few months later [10,26]. Legionella spp. are naturally present in water and soil, in association with amoebae and other protozoa and in biofilms [8,30]. The family Legionellaceae includes 53 recognized species in one genus, 20 of which are considered to be human pathogens [2,9]. The majority of cases of Legionnaires diseases in Europe are caused by L. pneumophila serogroup 1 [1]. The reference methods used for the identification of Legionella spp. include sequencing of specific genes, such as mip (macrophage Abbreviations: MALDI-TOF MS, Matrix Assisted Laser Desorption Ionization Time Of Flight Mass Spectrometry; SARAMIS TM, Spectral Archive And Microbial Identification System. Corresponding author at: Cantonal Institute of Microbiology, Bellinzona, Switzerland. Tel.: ; fax: address: valeria.gaia@ti.ch (V. Gaia). infectivity potentiator), rpob ( -subunit of DNA-dependent RNA polymerase) or gyra (gyrase A) [7,11,22], as well as immunological tests with species-specific antibodies (serotyping) [13 16]. L. pneumophila and L. anisa can be rapidly identified using commercially available agglutination tests that show a very high specificity (100% for L. pneumophila and 99.5% for L. anisa) [17,29]. For all other species, identification is usually performed by mip sequencing [28]. An internet-available database ( allows fast retrieval of known, deposited DNA sequences; sequencing, however, not only requires a considerable amount of time and work but is also coupled with relatively high costs. It is almost impossible to distinguish different Legionella species based on the appearance of the colonies on agar media. A rapid and inexpensive technique for direct screening of colonies would be very useful, in particular when studying environmental samples from cooling towers, potting soils, and composts, for example, where many non-l. pneumophila species, such as L. bozemanii, L. longbeachae, L. cincinnatiensis, L. jamestowniensis, L. micdadei and L. oakridgensis, can be simultaneously present [4,5,20,23,32]. Whole Cell MALDI-TOF MS (WCMS) is increasingly used for the identification of bacterial strains [3,6,18,19]. Only small amounts of cells are required; the procedure can be performed using the biomass from single colonies. A recent paper showed the usefulness /$ see front matter 2010 Elsevier GmbH. All rights reserved. doi: /j.syapm

2 2 V. Gaia et al. / Systematic and Applied Microbiology xxx (2010) xxx xxx Table 1 Reference strains obtained from culture collections and used in this study, and accession numbers for mip sequences. Species Strain No. NCBI sequence accession number (mip) 1 Legionella adelaidensis ATCC U Legionella anisa ATCC U Legionella beliardensis ATCC AF Legionella birminghamensis ATCC U Legionella bozemanii ATCC U Legionella brunensis ATCC U Legionella cherrii ATCC U Legionella cincinnatiensis ATCC U Legionella drozanskii ATCC AF Legionella dumoffii ATCC U Legionella erythra ATCC U Legionella fallonii ATCC AF Legionella feelei ATCC U Legionella geestiana ATCC FJ a 15 Legionella gormanii ATCC U Legionella gresilensis ATCC AF Legionella hackeliae ATCC U Legionella impletisoli DSM AB Legionella israelensis ATCC U Legionella jamestowniensis ATCC U Legionella jordanis ATCC U Legionella lansingensis ATCC U Legionella londiniensis ATCC U Legionella longbeachae ATCC X Legionella maceachernii ATCC U Legionella micdadei ATCC FJ Legionella moravica ATCC U Legionella oakridgensis ATCC U Legionella parisiensis ATCC U Legionella pneumophila ATCC AJ Legionella quinlivanii ATCC U Legionella rubrilucens ATCC U Legionella sainthelensi ATCC U Legionella steigerwaltii ATCC U Legionella taurinensis ATCC AF Legionella tucsonensis ATCC U Legionella wadsworthii ATCC U Legionella yabuuchiae DSM AB a Partial sequence of 194 nt. of WCMS for the rapid and inexpensive identification of twenty-one human pathogenic Legionella species [27]. The SARAMIS database (Spectral ARchiving And Microbial Identification System, AnagnosTec GmbH, Potsdam, Germany) was developed for the rapid identification of bacterial strains [21]. The database provides identification spectra for the majority of clinically important, pathogenic species, yet Legionella spp. are presently not enough represented. The aim of this study is to compare WCMS results obtained by SARAMIS with those obtained by mip gene phylogenetic analysis and to confirm the robustness of the clustering obtained by WCMS. Furthermore, we wanted to complement the WCMS database with the spectra of additional Legionella species. Materials and methods Bacterial strains Type strains from reference culture collections representing 38 different Legionella species (Table 1) were used in this study. We also included in our analysis 453 isolates from clinical specimens and environmental samples, such as water, cooling towers and soils that were split into two sets: 216 isolates were used to create species-specific SuperSpectra, whereas the remaining 237 served to test the performance of the new SuperSpectra (Table 2). These strains belong to the 14 Legionella species most frequently isolated during the last 10 years by the National Reference Centre (NRC) for Legionella in Bellinzona. To avoid variations in protein spectra that could result from the different ecological provenances of the isolates, all strains were purified and cultivated on buffered charcoal yeast extract agar (BCYE) (biomérieux, Geneva, Switzerland) at 36 C for h. Identification of the Legionella spp. studied Sequences of the mip gene of the 38 reference strains were obtained from NCBI GenBank (Table 1). Isolates of L. pneumophila and L. anisa (243 strains) were identified by the agglutination test (Slidex Legionella, biomérieux, Switzerland). Isolates for which no agglutination was observed (210 strains) were analyzed by mip-sequencing as previously described [28] and the sequences compared to those included in the mip identification database ( Sequence data analysis of reference strains The nucleotide (nt) sequences of the mip gene of the reference strains were downloaded from NCBI (Table 1). For most species sequences of 557 nt were obtained, whereas for L. yabuuchiae and L. impletisoli, only 417 nt were available. L. geestiana, which failed to produce an amplicon of the correct size (only 194 nt were available) [28] was not included in the alignment. The sequence similarities of strains were analyzed and phylogenetic trees were constructed, using the Neighbor joining algorithm, included in the MEGA 4 package. Confidence levels of inferred relationships were estimated following 1000 bootstrap iterations [24]. MALDI-TOF MS A small amount (approx. 0.5 l) of material was taken from freshly grown colonies and transferred with a plastic loop into a well of a 48-well stainless steel FLEXImass TM target plate (Shimadzu Biotech, Kyoto, Japan). Analyses were run in duplicate by spotting a colony into two different wells. The bacteria were overlaid with 0.5 l of matrix solution containing 75 mg/ml 2,5dihydroxybenzoic acid (DHB) in acetonitrile/ethanol/water (1:1:1) supplemented with 3% trifluoroacetic acid and allowed to dry at room temperature until the DHB crystals became visible. MS analyses were performed in positive linear mode in the range of ,000 masses-to-charge ratio (m/z), with an AXIMA Confidence TM Mass Spectrometer (Shimadzu Biotech). Average profile spectra, fulfilling the quality criteria (minimum intensity of the base peak: 10 mv; minimum signal to noise ratio: 10; minimum acceptable base peak resolution: 300), were collected from 20 laser shot cycles. For each sample, 2 50 averaged profile spectra were stored as mass spectra and used for analysis. Analysis of the spectra The peak lists of each strain were exported to the SARAMIS TM software package (Anagnostec, Potsdam, Germany) and submitted to single-linkage cluster analysis, using the Dice coefficient, to produce dendrograms of strain similarities (0.08% error, range from 2000 to 20,000 m/z). The SARAMIS TM software uses SuperSpectra for sample identification. SuperSpectra are computed from the mass spectra of multiple isolates belonging to the same species, by identifying consensus mass signals recorded in high frequency in the set of mass spectra, followed by weighting of the consensus peaks in accordance with their specificities. By this procedure, reliable species-specific mass patterns are extracted that can be used as reference data for automated ICMS-identification [21].

3 V. Gaia et al. / Systematic and Applied Microbiology xxx (2010) xxx xxx 3 Table 2 Origin of the isolates used for the creation and validation of the Legionella SuperSpectra (SSP). Species a Type strains Patients Water Cooling towers Soil Total strains Strains used for creation of SSP Strains used for validation of SSP Discrepancy b L. pneumophila L. bozemanii L. londiniensis L. taurinensis L. anisa L. sainthelensi L. micdadei L. longbeachae L. oakridgensis L. cincinnatiensis L. dumoffii L. birminghamensis L. jamestowniensis L. rubrilucens Total a Identifications determined by conventional techniques. b One isolate identified by mip as L. micdadei was identified as L. oakridgensis by WCMS and one identified by mip as L. cincinnatiensis was identified as L. bozemanii by WCMS. SuperSpectra for each of the 14 most frequently isolated species of Legionella were created after identification of species-specific masses and integrated in the SARAMIS TM database for future rapid identification of new isolates. SuperSpectra were created only for species, for which at least three isolates were available, according to the Manufacturer s instructions (Table 2). Results All strains could be analyzed by WCMS and useful spectra could be produced. For the L. geestiana reference strains, only a 194 nt sequence was available in the NCBI database, because for this species mip cannot be amplified using standard primers [28]; thus, it was not included in the phylogenetic tree. SuperSpectra creation and validation The MALDI-TOF MS spectral data resulting from the analysis of 216 isolates were processed using the SARAMIS TM database software to identify species-specific masses that were then used to generate SuperSpectra for the identification of 14 Legionella species (Table 2). The robustness of the new SuperSpectra was tested by subjecting 237 isolates to the standardized automated identification procedure used for other clinical isolates. All but two environmental isolates could be identified using the new SuperSpectra with 99.9% confidence. The two isolates for which discrepant results were obtained corresponded to two isolates identified by mip as L. micdadei and L. cincinnatiensis; SARAMIS TM identified those isolates as L. oakridgensis and L. bozemanii, respectively. Comparison of mip and WCMS analysis of reference strains from culture collection In the dendrogram based on the mass spectral patterns (Fig. 1A), isolates belonging to the same species clustered consistently in the same groups. The threshold level of the inter-species variation was approximately 60% similarity, with the exception of two clusters: L. taurinensis, L. erythra and L. rubrilucens (referred as the red-fluorescent group); and L. anisa, L. bozemanii, L. parisiensis, L. tucsonensis, L. gormanii, L. cherrii, L. wadsworthii, L. steigerwalti and L. dumoffii (referred as the blue-fluorescent group). Nevertheless, the variation of the spectra for species within these two groups allowed good differentiation at the species level (mass fingerprint similarity thresholds of 40% and 50% for the for the blue and the red fluorescent species, respectively). In the mip tree, 7 clusters with bootstrap values higher than 90% were observed: two comprising the blue- and red-fluorescent groups, respectively; the cluster composed of L. sainthelensi, L. longbeachae and L. cincinnatiensis; and also 4 small clusters composed by L. beliardensis/l. gresilensis; L. birminghamensis/l. quinlivanii, L. micadei/l. maceachernii; and L. impletisoli/l. yabuuchiae (Fig. 1B). By comparing the WCMS dendrogram (Fig. 1A) with the phylogenetic tree obtained from the mip sequences (Fig. 1B), one can observe that 5 of the 7 clusters are supported by bootstrap values greater than 90%. In the WCMS dendrogram, the group composed of L. beliardensis/l. gresilensis is split and L. cincinnatiensis is separated from L. longbeachae/l. sainthelensi. Discussion For all reference strains of the 38 tested species of Legionella, spectra were produced, using standard extraction and analysis conditions. Seven groups were previously described by other authors using phylogenetic analysis of genes, such as rnpb [31], rpob [22] and 16S rrna [12,25]. Correspondingly, the WCMS analysis reflects the phylogenetic classification inferred by mip sequence analysis. The blue-fluorescent group observed with WCMS was identical to that seen in phylogenetic trees constructed with mip and rnpb [28,31], whereas the same group was split into two separate clades, using rpob and 16S rrna sequence analysis [12,22,25]. The redfluorescent cluster and the group L. micdadei/l. maceachernii were already previously observed by other authors in phylogenetic trees obtained from the rpob, rnpb and 16S rrna sequences [12,22,25]. L. birminghamensis/l. quinlivanni cluster in one group in the phylogenetic trees constructed with the rnpb and 16S rrna sequences [12,25], but not in the one produced from rpob sequence similarity analysis [22]. In general, WCMS correlates well with the previously described genotypic analyses. The only exception regards the cluster L. beliardensis/l. quinlivanii and L. cincinnatiensis, which is separated from L. longbeachae/l. sainthelensi by WCMS and not by sequence analysis. The high inter-species diversity observed within the WCSM spectra allowed reliable identification of all Legionella spp. SuperSpectra were created only for the 14 most frequently isolated species, for which at least three isolates were available. All

4 4 V. Gaia et al. / Systematic and Applied Microbiology xxx (2010) xxx xxx Fig. 1. Dendrogram obtained by WCMS (A) compared to the phylogenetic tree (B) obtained by mip sequence analyses of 38 type strains from culture collections. tested strains were identified with very high confidence values by the newly created SuperSpectra and only 2 discrepancies out of 237 isolates tested were observed. Our study has two limitations. First, the different species were unevenly represented with regard to the number of strains. The most frequent species, however, represent the majority of Legionella strains isolated from clinical and environmental samples in Switzerland by the NRC and for these SuperSpectra could be produced. Second, the application of cluster analysis based on m/z values produces a somewhat arbitrary divisions of taxa which cannot be directly correlated with phylogenetic distances. The dendrogram obtained from the analysis of MALDI-TOF MS data, on the other hand, correlates very well with the grouping produced by the genetic analysis of the mip sequences, indicating that species of Legionella can be reliably distinguished by protein fingerprinting. Even though a high degree of intra-specific variation in mass patterns was observed for L. pneumophila, it was not possible to differentiate and separate strains according to their serogroups. Further studies are needed to identify specific masses that could be useful for distinguishing serogroup 1 strains. On the other hand, variation in mass spectra was observed within different strains belonging to a given species. This heterogeneity of the spectra of isolates belonging to the same species suggests that further discrimination between serogroups or single strains should be possible using WCMS. In conclusion, MALDI-TOF MS, coupled with the use of Super- Spectra constructed using the SARAMIS TM database represents a rapid means for the reliable identification of clinically and environmentally relevant species of Legionella. The technique allows to perform a full analysis from a single colony in only few minutes, thus providing an inexpensive and rapid screening of a large number of colonies within a short time. Acknowledgment The authors are grateful to Guido Vogel (Mabritec, Basel), Martin Welker (AnagnosTec, Potsdam), and Orlando Petrini (ICM, Bellinzona) for fruitful discussions and support. References [1] Bartram, J., Chartier, Y., Lee, J.V., Pond, K., Surman-Lee, S. (Eds.), Legionella and the Prevention of Legionellosis, World Health Organization, Geneva, Switzerland. [2] Brenner, D.J., Steigerwalt, A.G., McDade, J.E. (1979) Classification of the Legionnaires disease bacterium: Legionella pneumophila, genus novum, species nova, of the family Legionellaceae, familia nova. Ann. Intern. Med. 90, [3] Bright, J.J., Claydon, M.A., Soufian, M., Gordon, D.B. (2002) Rapid typing of bacteria using matrix-assisted laser desorption ionisation time-of-flight mass spectrometry and pattern recognition software. J. Microbiol. Methods 48, [4] Casati, S., Conza, L., Bruin, J., Gaia, V. (2009) Compost facilities as a reservoir of Legionella pneumophila and other Legionella species. Clin. Microbiol. Infect. 16,

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