Identification of non fermenting Gram negative bacilli isolated in cystic fibrosis by

JCM Accepts, published online ahead of print on 6 August 2008 J. Clin. Microbiol. doi:10.1128/jcm.00569-08 Copyright 2008, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved. 1 2 Identification of non fermenting Gram negative bacilli isolated in cystic fibrosis by Matrix assisted laser desorption ionization time-of-flight mass spectrometry 3 4 5 6 7 8 9 10 11 12 13 Nicolas Degand 1,2, Etienne Carbonnelle 1, 2, Brunhilde Dauphin 2, Jean-Luc Beretti 1, Muriel Le Bourgeois 3, Isabelle Sermet-Gaudelus 4, Christine Segonds 5, Patrick Berche 1,2, Xavier Nassif 1,2, Agnès Ferroni 1*. 1 Assistance Publique-Hôpitaux de Paris, Laboratoire de Microbiologie, Hôpital Necker- Enfants Malades, Paris, France, 2 Université Paris Descartes, Faculté de médecine, Paris, France, 3 Service de Pneumologie Pédiatrique, 4 Service de Pédiatrie Générale, Hôpital Necker-Enfants Malades, Paris, France, 5 Observatoire Cepacia, Hôpital Purpan, Toulouse, France. Short title: Cystic fibrosis bacterial identification Key words : MALDI-TOF-MS, cystic fibrosis, bacterial identification, Gram negative bacilli * Corresponding author Agnès Ferroni Laboratoire de Microbiologie Hôpital Necker-Enfants Malades 149 rue de Sèvres 75015 Paris, France Tel: 33 1 44 49 49 62 Fax: 33 1 44 49 49 60 E-mail: agnes.ferroni@nck.aphp.fr 1

14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Abstract The identification of nonfermenting Gram-negative bacilli isolated from cystic fibrosis (CF) patients is usually achieved using phenotypic based techniques and eventually molecular tools. These techniques remain time consuming, expensive, and technically demanding. We used a method based on Matrix Assisted Laser Desorption Ionization Time-Of-Flight Mass spectrometry (MALDI-TOF-MS) for the identification of these bacteria. A set of reference strains belonging to 58 species of clinically relevant nonfermenting Gramnegative bacilli was used. To identify peaks discriminating between these various species, the profile of 10 isolated colonies obtained from 10 different passages was analyzed for each referenced strain. Conserved peaks with a relative intensity above 0.1 were retained. The spectra of 559 clinical isolates were then compared with that of each of the 58 reference strains : 400 Pseudomonas aeruginosa, 54 Achromobacter xylosoxydans, 32 Stenotrophomonas maltophilia, 52 Burkholderia cepacia complex (Bcc), 1 Burkholderia gladioli, 14 Ralstonia mannitolilytica, 2 Ralstonia picketti, 1 Bordetella hinzii, 1 Inquilinus limosus, 1 Cupriavidus respiraculi, 1 Burkholderia thailandensis. Using this database, 549 strains were correctly identified. Nine Bcc and 1 R. mannnitolilytica strains were identified as belonging to the appropriate genus but not the correct species. We subsequently engineered Bcc and Ralstonia specific databases using additional reference strains: using these databases, correct identification for these species increased from 83 to 98% and 94 to 100 % of cases, respectively. Altogether, these data demonstrates that, in CF patients, MALDI-TOF-MS is a powerful tool for rapid identification of nonfermenting Gram-negative bacilli. 36 37 38 2

39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 Introduction Pseudomonas aeruginosa is the main bacterial pathogen isolated from the sputum of patients suffering from Cystic Fibrosis (CF). Other non fermenting Gram negative bacilli of clinical importance that can be isolated from this location are Achromobacter xylosoxydans, Stenotrophomonas maltophilia or species belonging to the Burkholderia cepacia complex (Bcc). Other non fermenting bacteria belonging to the genus Ralstonia or Burkholderia are less likely to be isolated. Recently, novel bacterial species have been isolated from CF patients as Ralstonia mannitolilytica (6,10), Pandoraea apista (4,22), Inquilinus limosus (5,25). Bacteria isolated during CF do not have the same virulence, thus pointing out the importance of bacterial identification by routine clinical microbiology laboratories for the management of CF patients. Moreover, the emergence of new bacterial species requires accurate identification tools in order to understand their clinical relevance and distribution in CF. Conventional phenotypic methods and commercial kits are sometimes not suitable for strains isolated from CF patients. These pathogens often lack key phenotypic characters required for their identification (1,10,20,23,24,26). In addition, in some circumstances, misidentification is due to the fact that the species are not in the database of commercial kits (10,23). Molecular tools such as 16S rrna gene sequencing provide reliable results (10,16,26). Other techniques such as FISH (27) and amplified ribosomal DNA restriction assays are available (22). Despite their good accuracy, these molecular techniques cannot be used routinely as they are expensive, time consuming and technically demanding. Several studies have reported the use of Matrix Assisted Laser Desorption Ionization Time- Of-Flight Mass Spectrometry (MALDI-TOF-MS) for bacterial identification (8,9,13-15,17). MALDI-TOF-MS can examine the profile of proteins detected directly from intact bacteria. This technique, based on relative molecular masses, is a soft ionization method 3

64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 allowing desorption of peptides and proteins from whole different cultured microorganisms. Ions are separated and detected according to their molecular mass and charge. For a given bacterial strain, this approach yields reproducible spectrum within minute, consisting of a series of peaks corresponding to m/z ratios of ions released from bacterial proteins during laser desorption. Recently, we engineered a strategy to identify bacteria belonging to the Micrococaceae family (2). The aim of this present work is to extend this strategy to non fermenting bacilli recovered in CF patients, thus opening the path towards rapid, accurate and cheap means of bacterial identification in routine laboratories. Our first step was to build a complete database for all species belonging to the group of non fermenting Gram negative bacilli recovered in human, including those isolated in CF patients. We then validated this database using the identification by MALDI-TOF MS of clinical strains recovered from CF patients. Material and methods Bacterial strains. The reference strains used to engineer the MALDI-TOF MS database belonged to 58 species of non fermenting Gram negative bacilli that can possibly be recovered from CF patients. Three databases were engineered, and the 87 strains used to complete these databases are described in tables 1, 2 and 3. The tested strains used to validate the databases were : (i) 512 clinical isolates of non fermenting Gram negative bacilli recovered from the sputum of CF children attending the pediatric department of the Necker-Enfants malades hospital (Paris, France) between 01/01/06 and 31/12/06 : 400 P. aeruginosa strains (101 patients), 54 Achromobacter xylosoxydans (12 patients), 32 S. maltophilia (12 patients), 9 R. 4

89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 mannitolilytica (1 patient), 14 Bcc (2 patients ), 1 Burkholderia gladioli, 1 Bordetella hinzii and 1 I. limosus. These strains were identified by phenotypical tests or molecular method as previously described (10). Briefly, isolates displaying Green or Yellow-Green pigmentation, positive oxidase test, growth at 42 C, growth on cetrimide agar and susceptibility to colimycin (disk diffusion method) were identified as Pseudomonas aeruginosa. Isolates that did not express those criteria were identified using the API 20NE system (biomerieux, Marcy-l'Etoile, France). The results of the API 20NE tests were interpreted using the APILAB PLUS software package (biomerieux). When the API 20NE system did not identify a P. aeruginosa or a A. xylosoxydans or a S. maltophilia, the identification was further pursued by sequencing an internal fragment of the 16Sr RNA gene as previously described (10). Sixteen of the 400 P. aeruginosa strains and 26 of the 112 non P. aeruginosa strains required molecular methods for identification. B. cepacia strains were identified by 16SrDNA sequencing. Identification was confirmed by the Observatoire National des Cepacia using ARDRA (amplified rdna restriction analysis) (21,22). Species-specific reca PCR and/or Burkholderia cepacia complex-reca restriction analysis was used to circumvent the limitations of ARDRA within the Burkholderia cepacia complex (19). (ii) 47 clinical strains obtained from the Observatoire National des Cepacia (Toulouse, France): 38 Bcc strains (11 Burkholderia vietnamiensis, 10 Burkholderia multivorans, 8 B. cenocepacia, 5 Burkholderia stabilis, 1 Burkholderia dolosa, 1 Burkholderia pyrrocinia, 2 B. cepacia), 1 Burkholderia thailandensis, 5 R. mannitolilytica, 2 Ralstonia picketti, 1 Cupriavidus respiraculi. All bacterial strains used in the study were stored at -80 C in trypticase soy broth supplemented with 15% glycerol. MALDI-TOF-MS. The strains were grown on Mueller-Hinton agar and incubated for 24h at 37 C. Most of the isolates grew after 24h but some strains that didn t grow after 24h were 5

114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 further incubated for 48h or 72h. An isolated colony was harvested in 20 µl of sterile water. One µl of this mixture was deposited on a target plate (Bruker Daltonics, Bremen, Germany) in two replicates, and allowed to dry at room temperature. One microliter of absolute ethanol was then added in each well, and the mixture allowed to dry. One µl of matrix solution DHB (2,5-dihydroxybenzoic acid, 50 mg/ml, 30% acetonitrile, 0.1% trifluoroacetic acid) was then added and allowed to co-cristallize with the sample. Samples were processed in the MALDI- TOF-MS spectrometer (Autoflex, Bruker Daltonics) with the flex control software (Bruker Daltonics). Positive ions were extracted with an accelerating voltage of 20 kv in linear mode. Each spectrum was the sum of the ions obtained from 200 laser shots performed in five different regions of the same well. The spectra have been analyzed in an m/z range of 2,000 to 20,000. The analysis was performed with the flex analysis software and calibrated with protein calibration standard I (Bruker Daltonics). The data obtained with the two replicates were added to minimize random effect. The presence and absence of peaks were considered as fingerprints for a particular isolate. The profiles were analyzed and compared using the newly developed software BGP database available on the website http://sourceforge.net/projects/bgp. Numerical data obtained from the spectrometer acquisition software (peak value and relative intensity for each peak) are sent to the BGP software. This software identifies the number of common peaks between the spectra of the tested strain and each set of peaks specific of a reference strain contained in the database (i.e non fermenting Gram negative bacilli database). The software determines a percentage for each reference strain (100 x number of common peaks between the tested strain and the peaks specific of one reference strain/total number of peaks specific of one reference strain). The identification of the tested strain correspond to the species of the reference strain having the best match in the database. The greater the difference between the first and second match, the 6

138 139 better is the discrimination between species. A difference of at least 10% is required to obtain a good identification. 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 Results Engineering of the non fermenting Gram negative bacilli database. The database was engineered using a previously described strategy (2). A set of reference strains has been selected as belonging to clinically relevant nonfermenting Gram-negative bacilli, including those representative of the species routinely recovered from CF patients (table 1). Figure 1 shows the spectrum obtained with 6 species of non fermenting Gram negative bacilli. Ten isolates of each of these selected strains grown on Mueller Hinton 24H were analyzed by MALDI-TOF-MS as described in the material and methods section. For each strain, we retained only those peaks with a relative intensity above 0.1 that were constantly present in all 10 sets of data obtained for a given strain. The standard deviation for each conserved peak did not exceed 6 m/z value. Table 4 shows the m/z values of the selected peaks that have been retained for 8 reference strains. The set of peaks was specific of each selected strain. We next aimed at determining whether the above database could be used for the identification of non fermenting Gram negative bacilli, thus demonstrating that the set of peaks of each selected strain is, at least partially, conserved among isolates of the same species. The database was tested using the set of strains described in the material and methods section. For each isolate, all peaks with intensity 0.02 were retained and were compared with that of the specific peaks of each reference strain included in the database using the BGP-database software, taking into account a possible error of +/- 10 m/z value. Figure 2 shows the example of one P. aeruginosa strain. We next analyzed for all tested strains the percentage of common 7

163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 peaks obtained with each of the reference strains. Only the first and second best matches were retained (Table 5). We considered a difference 10% as the minimum required to give a correct identification. A correct identification was obtained for all strains except those belonging to the Bcc and the Ralstonia genus (Table 5). The latter were identified as belonging to the Bcc or the Ralstonia genus but the species identification was not correct. Engineering of specific databases. In order to improve the identification of strains belonging to the Bcc and the Ralstonia genus, we engineered Bcc and Ralstonia specific databases. We hypothesized that including several reference strains for one given genospecies would improve identification of the tested strains. The Bcc specific database encompassed the 9 Bcc reference strains used to engineer the non fermenting Gram negative bacilli database and additional 21 Bcc reference strains provided by the LMG bacterial collection (table2), so that each species was represented by several reference strains. For each of these reference strains, only peaks with a relative intensity above 0.1 that were constantly present in all 10 sets of data were retained. However, in order to increase the ability of this database to discriminate between the species, only those peaks that were constantly conserved in all reference strains of the same species were retained in the database. This Bcc specific database was then tested using all clinical strains belonging to the Bcc. This approach improved the differentiation between Bcc species: only one B. dolosa strain was falsely identified as B. multivorans. Six B. cenopacia strains could not be differentiated from B. cepacia. However, we noticed that a peak (m/z 7546) was constantly present in B. cepacia strains and constantly absent in B. cenopacia. On the basis of this peak, a correct identification was obtained for all B. cenopacia strains. 8

187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 The same strategy as that used for Bcc database was thus applied to engineer a specific Ralstonia database, using supplementary reference strains provided by the LMG bacterial collection (table 3). This new database allowed the correct identification of all strains. Discussion The bacterial species responsible for infection in cystic fibrosis patients do not display the same pathogenicity and thus do not require the same clinical management, thus pointing out the need for a correct and rapid identification of the bacteria isolated. This study demonstrates that the strategy described above is suitable for accurate species identification of non fermenting Gram negative bacilli isolated in cystic fibrosis. Indeed, all CF P. aeruginosa strains were accurately identified. Prior to this study, we have tested 12 strains belonging to 4 species (P. aeruginosa, A. xylosoxidans, B. cenocepacia, S. maltophilia) using 3 different media (MH, chocolate agar and blood agar) and 2 times of culture (18 h and 24h). Identifications were the same regardless of the media used to grow the bacteria (data not shown). Furthermore, the spectra were similar after 18 or 24 H of growth. In addition, identification was not affected if the strain grew only after 48H of incubation. The mucoid character of the strains recovered from patients with chronic colonization is frequently an obstacle to the accurate identification using biochemical tests. Nevertheless, none of the mucoid strains in our study was misidentified. Only one mucoïd strain had a low percentage of matches with the P. aeruginosa reference strain (38%), but the MALDI-TOF-MS identification was correct as the profile gave 22% of matches with the second choice. All S. maltophilia and A. xylosoxydans were correctly identified. It should be pointed out that frequent misidentification occurs between these species and Bcc strains (20). Infection by Bcc species in CF patients has been shown to increase morbidity and premature 9

212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 mortality (7,18), and may represent a contraindication to lung transplantation (12). Furthermore, the risk associated with dissemination of B. cenocepacia strains requires specific means in order to prevent the bacterial spread (11). The rapid identification of B. cenocepacia using the Bcc database allows to immediately implement a specific clinical management before the results of molecular identification. Despite the good results achieved for Bcc strains, the wrong identification obtained for one strain points out the need of a larger set of clinical strains to improve the identification of Bcc species. R. mannitolilytica, I. limosus, B. hinzii and B. gladioli were correctly identified by MALDI- TOF-MS. Of note, the strain identified as B. gladioli matched also with the reference strain of B. cocovenenans (data not shown), a bacterial species that has been shown to be a junior synonym of B. gladioli (3). Conventional identification is not reliable for this species as well as for other species, such as R. mannitolilytica or I. limosus isolated during our study. API 20NE gave a very good identification of Inquilinus limosus as Sphingomonas paucimobilis, as previously described, which can thus lead to an underestimation of this emerging pathogen (25). The bacteria that are rarely isolated in CF patients can then be accurately identified using our database, as we make sure that the database is as complete as possible using many reference strains, even strains belonging to rarely isolated species CF patients. In our experience, all strains included in the database would have allowed identification of 100% of the non fermenting Gram negative bacilli isolated in the CF patients in our hospital. Emerging new bacterial species will give a spectrum that does not match with any of the reference spectra contained in the database. However, tested strains for which identification is not obtained by MALDI-TOF can be identified using a molecular biology approach, thus improving rapidly the database with new species. Such a rapid improvement is usually not 10

236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 achievable using biochemical kits. Moreover, when 2 bacterial cultures are mixed, the global spectrum results is the sum of the 2 spectra, with specific peaks of both. Actually, MALDI-TOF MS bacterial identification is a phenotypic method but analysis of the origin of the ions detected in the spectra show that the majority of the peaks correspond to ribosomal proteins (8), which are proteins that represent a great proportion of the whole bacterial proteome and that are constantly expressed and conserved in bacteria. Metabolic characters lack specificity since the result can either be positive or negative and many biochemical tests correspond to universal metabolic pathways that can be common to several bacteria. A laboratory technician, without spectrometric background, can easily use this method. After depositing the sample and matrix as described in the material and methods section, the spectrometer can be programmed so that the laser impact automatically over the entire surface of the matrix, and there is no human intervention on the software for the species identification. The calibration with the standard, and the treatment of data (selection of peaks with relative intensity 0.02 and calculation of peaks ratios between database and tested strains by the BGP software) are automatically processed. Therefore, this is a very basic software which does not require any expertise nor subjective process and can be easily performed even with a non experimented operator. The time required to run 50 samples is about 1 hour. 255 256 257 258 259 Altogether, these data show that bacterial identification by MALDI-TOF-MS may improve the clinical management of CF patients. As this is a very low-cost technique (about 0.9 euro /50 samples), it is likely that considering the speed with which reliable identification can be obtained, this technique ultimately replaces the actual routine phenotypic assays. 260 11

261 262 Acknowledgment The authors thank Gilles Quesnes and Eric Frapy for their beneficial technical assistance. 263 264 265 266 267 Potential conflicts of interest. All authors: no conflicts. 12

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355 Figures legends : 356 Figure 1 : MALDI-TOF-MS spectrum of 6 reference strains 357 358 Figure 2 : Identification of a P. aeruginosa strain using the BGP software. The best match was obtained with the P.aeruginosa reference strain. The second best match was with F. oryzihabitans 16

Table 1 : reference strains used to establish the MALDI-TOF-MS non fermenting Gram negative bacilli database Species Reference strain Species Reference strain Pseudomonas aeruginosa CIP 76.110 Ralstonia mannitolilytica CIP 107281 T Pseudomonas fluorescens CIP 69.13 T Ralstonia pickettii CIP 73.23 T Pseudomonas mosselii CIP 104061 Cupriavidus gilardii CIP 105966 T Pseudomonas putida CIP 52.191 T Cupriavidus pauculus CIP 105943 T Pseudomonas stutzeri CIP 103022 T Cupriavidus respiraculi LMG 21509 Pseudomonas mendocina CIP 75.21 T Bordetella avium CIP 103348 T Pseudomonas alcaligenes CIP 101034 T Bordetella bronchiseptica CIP 55.110 T Pseudomonas pseudoalcaligenes CIP 66.14 T Bordetella hinzii CIP 104527 T Pseudomonas oryzihabitans CIP 102996 T Alcaligenes faecalis subsp. faecalis CIP 60.80 T Pseudomonas luteola CIP 102995 T Aeromonas sobria CIP 74.33 T Stenotrophomonas maltophilia CIP 60.77 T Aeromonas hydrophila subsp. hydrophila CIP 76.14 T Achromobacter xylosoxydans subsp. xylosoxydans CIP 71.32 T Aeromonas veronii CIP 103438 T Achromobacter xylosoxydans subsp. denitrificans CIP 77.15 T Aeromonas caviae CIP 76.16 T Achromobacter piechaudii CIP 101223 Delftia acidovorans CIP 103021 T Burkholderia cepacia complex Shewanella putrefaciens CIP 80.40 T. Burkholderia cepacia CIP 80.24 T Plesiomonas shigelloides CIP 63.5 T. Burkholderia multivorans CIP 105495 T Chryseobacterium indologenes CIP 101026 T. Burkholderia cenocepacia CIP 108255 T Elizabethkingia meningoseptica CIP 60.57 T. Burkholderia stabilis CIP 106845 T Sphingobacterium multivorum CIP 100541 T. Burkholderia vietnamiensis CIP 105875 T Sphingobacterium spiritivorum CIP 100542 T. Burkholderia dolosa CIP 108406 Brevundimonas diminuta CIP 63.27 T. Burkholderia ambifaria CIP 107266 T Brevundimonas vesicularis CIP 101035 T. Burkholderia anthina CIP 108228 T Sphingomonas paucimobilis CIP 100752 T. Burkholderia pyrrocinia CIP 105874 T Inquilinus limosus CIP 108342 T Burkholderia gladioli CIP 105410 T Pandoraea apista CIP 106627 T Burkholderia cocovenenans ATCC 33664 Pandoraea norimbergensis LMG 13019 Burkholderia glumae NCPPB 2391 Pandoraea promenusa LMG 18087 Burkholderia plantarii ATCC 43733 Pandoraea pulmonicola LMG 18106 Burkholderia thailandenis LMG 20219 Pandoraea sputorum LMG 18100 Burkholderia glathei CIP 105421 T Burkholderia andropogonis ATCC 23060 CIP: Collection de l Institut Pasteur (Paris, France) NCPPB : National Collection of Plant Pathogenic Bacteria (York, U.K). LMG : Laboratorium voor Microbiologie Bacteriënverzameling (Ghent, Belgium) T: Type strain of the species.

Table 2 : reference strains used to establish the MALDI-TOF-MS Bcc database Species Reference strain Burkholderia cepacia CIP 80.24 T Burkholderia cepacia LMG 6889 Burkholderia cepacia LMG 2161 Burkholderia multivorans CIP 105495 T Burkholderia multivorans LMG 14273 Burkholderia multivorans LMG 14293 Burkholderia cenocepacia CIP 108255 T Burkholderia cenocepacia LMG 18863 Burkholderia cenocepacia LMG 21440 Burkholderia cenocepacia LMG 18829 Burkholderia cenocepacia LMG 18830 Burkholderia cenocepacia LMG 19230 Burkholderia cenocepacia LMG 19240 Burkholderia cenocepacia LMG 21462 Burkholderia stabilis CIP 106845 T Burkholderia stabilis LMG 6997 Burkholderia stabilis LMG 7000 Burkholderia vietnamiensis CIP 105875 T Burkholderia vietnamiensis LMG 6998 Burkholderia vietnamiensis LMG 6999 Burkholderia dolosa CIP 108406 Burkholderia dolosa LMG 18941 Burkholderia ambifaria CIP 107266 T Burkholderia ambifaria LMG 11351 Burkholderia ambifaria LMG 17828 Burkholderia anthina CIP 108228 T Burkholderia anthina LMG 16670 Burkholderia pyrrocinia CIP 105874 T Burkholderia pyrrocinia LMG 21822 Burkholderia pyrrocinia LMG 21823 CIP : Collection de l Institut Pasteur (Paris, France) LMG : Laboratorium voor Microbiologie Bacteriënverzameling (Ghent, Belgium) T: Type strain of the species.

Table 3 : reference strains used to establish the MALDI-TOF-MS Ralstonia database Species Reference strain Cupriavidus gilardii CIP 105966 T Cupriavidus gilardii LMG 3399 Cupriavidus gilardii LMG 3400 Cupriavidus pauculus CIP 105943 T Cupriavidus pauculus LMG 3245 Cupriavidus pauculus LMG 3317 Cupriavidus respiraculi LMG 21509 Cupriavidus respiraculi LMG 21510 Ralstonia mannitolilytica CIP 107281 T Ralstonia mannitolilytica LMG 18098 Ralstonia mannitolilytica LMG 18102 Ralstonia pickettii CIP 73.23 T Ralstonia pickettii LMG 5942 Ralstonia pickettii LMG 7001 CIP: Collection de l Institut Pasteur (Paris, France) LMG : Laboratorium voor Microbiologie Bacteriënverzameling (Ghent, Belgium) T: Type strain of the species.

Table 4 : m/z of the selected peaks of 8 species of non fermenting Gram negative bacilli. Achromobacter xyloxosidans subsp xylosoxydans CIP 71.32T 2190 +/-1 2319 +/-1 2447 +/-1 2576 +/-1 2705 +/-1 2833 +/-1 2865 +/-1 2962 +/-1 4334 +/-2 4978 +/-2 5018 +/-1 5242 +/-2 6328 +/-2 6626 +/-1 6701 +/-2 7108 +/-1 7302 +/-1 8681 +/-2 9417 +/-2 9445 +/-2 10045 +/-2 10101 +/-2 Pseudomonas aeruginosa CIP 76.110 4436 +/-2 4544 +/-3 5213 +/-3 5742 +/-3 6051 +/-3 6353 +/-3 6682 +/-4 6918 +/-4 7211 +/-4 7586 +/-4 7621 +/-4 8575 +/-5 9100 +/-5 Pseudomonas fluorescens CIP 69.13T 4339 +/-1 6089 +/-1 6275 +/-2 6403 +/-1 6634 +/-2 7182 +/-1 7604 +/-2 7647 +/-1 9568 +/-1 Pseudomonas putida CIP 52.191T 3810 +/-1 4439 +/-1 4473 +/-1 5145 +/-1 6000 +/-2 6345 +/-2 6679 +/-2 7553 +/-2 7635 +/-2 8395 +/-2 8637 +/-2 9147 +/-3 9561 +/-3 Burkholderia cenocepacia CIP 108255T 3600 +/-2 4414 +/-2 4806 +/-2 5202 +/-2 5345 +/-2 5916 +/-3 6486 +/-3 6503 +/-4 7089 +/-3 7216 +/-3 7318 +/-3 7397 +/-3 7967 +/-3 9624 +/-4 Burkholderia gladioli CIP 105410T 4416 +/-1 4808 +/-1 5204 +/-1 5225 +/-3 6305 +/-1 6489 +/-2 6597 +/-1 6859 +/-2 6959 +/-2 7060 +/-2 7105 +/-2 7185 +/-2 7217 +/-3 7325 +/-2 7673 +/-1 7794 +/-2 8737 +/-2 9627 +/-2 10458 +/-4 Stenotrophomonas maltophilia CIP 60.77T 4541 +/-1 4862 +/-1 5276 +/-1 5898 +/-3 6108 +/-1 7161 +/-2 7578 +/-2 9349 +/-2 Ralstonia mannitolilytica CIP 107281T 3818 +/-3 4396 +/-1 4813 +/-4 5398 +/-4 6156 +/-4 7060 +/-5 7060 +/-5 7078 +/-5 7943 +/-4 9632 +/-4

Table 5 : identification of non fermenting Gram negative bacilli by MALDI-TOF-MS average % of common Number of average % of common number of strains for Number of strains for Number peaks between the tested strains for which peaks between the tested which the difference of which the of species strain and the best match the best match is strain and the second best common peaks between identification is tested of the general database the correct match of the general the best and second best correct using the Bcc strains (extreme) identification database (extreme) match is less than 10% or Ralstonia database P. aeruginosa 400 87 (ext : 38-100) 400 51 (ext : 18-83) 1 4 A. xylosoxydans 2 4 (2 nd choice : A. 54 89 (ext : 59-100) 54 73 (ext : 50-88) piechaudii) S. maltophilia 32 82 (ext : 63-100) 32 45 (ext : 29-67) 0 B. cenocepacia 22 82 (ext : 57-100) 18 1 70 (ext : 56-86) 7 22 B. vietnamiensis 11 83 (ext : 68-100) 9 2 59 (ext : 67-81) 4 11 B. multivorans 10 63 (ext : 92-100) 9 2 53 (ext : 74-87) 0 9 B. stabilis 5 72 (ext : 67-80) 4 2 64 (ext : 56-69) 2 5 B. cepacia 2 88 (ext : 81-94) 2 62 (ext : 59-64) 0 2 B. pyrrocina 1 94 1 67 0 1 B. dolosa 1 63 0 2 60 1 0 5 Ralstonia 14 79 (ext : 70-80) 13 3 14 66 (ext : 56-70) 4 mannitolilytica Ralstonia picketti 2 73 (ext : 70-80) 2 58 (ext : 42-75) 0 2 Cupriavidus respiraculi 1 1 56 1 43 0 multivorans 5 The misidentified strain was identified as B. B. gladioli 1 82 1 64 0 B. hinzii 1 90 1 56 0 I. limosus 1 60 1 25 0 B. thailandensis 1 85 1 73 0 1 The 4 misidentified strains were identified as 3 B. cepacia and 1 B. cocovenenans 2 The misidentified strain was identified as B. cepacia 3 The misidentified strain was identified as R. picketti 4 These strains were retested, and the second set of data provided the same identification as the initial one.

1461 4436 4451 5742 6051 6682 7586 7578 4862 5276 5898 6108 7161 7302 4334 4978 5242 6701 6328 7108 4414 5202 6503 3600 4806 5345 6486 7089 5916 4813 4396 7216 7397 7967 9100 9349 10045 9417 10101 9445 9624 5398 6156 7076 7060 7942 8757 9633 P. aeruginosa CIP 76.110 T S. maltophilia CIP 60.77 T A. xylosoxydans subsp.xylosoxydans CIP 71.32 T B. cenocepacia CIP 108255 T R. mannitolilytica CIP 107281 T 6000 6274 7163 9960 9984 I. limosus CIP 108342 T

Profile Name : P. aeruginosa Match : 13/13 1 Isolate database N 06178603 m/z values P. aeruginosa m/z values 4441 4436 4548 4544 5216 5213 5743 5742 6053 6051 6354 6353 6682 6682 6917 6918 7209 7211 7584 7586 7620 7621 8571 8575 9096 9100 Profile Name : F. oryzihabitans Match: 7/12 2 Isolate database N 06178603 m/z values F. orzyhabitans m/z values 4441 4435 6053 6053 6505 6503 6682 6680 7497 7498 7584 7581 9123 9126 1 : the 13 peaks obtained for tested isolate matched all 13 peaks of P. aeruginosa database 2 : seven peaks obtained for tested isolate matched 7/12 peaks of F. orizyhabitans database