Rapid Genus and Species Specific Identification of Cronobacter spp by Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry

(1)JOURNAL OF CLINICAL MICROBIOLOGY, Aug. 2010, p. 2846–2851 0095-1137/10/$12.00 doi:10.1128/JCM.00156-10 Copyright © 2010, American Society for Microbiology. All Rights Reserved.. Vol. 48, No. 8. Rapid Genus- and Species-Specific Identification of Cronobacter spp. by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry䌤 Roger Stephan,1* Dominik Ziegler,2 Valentin Pflüger,2 Guido Vogel,2 and Angelika Lehner1 Institute for Food Safety and Hygiene, Vetsuisse Faculty University of Zurich, Zurich, Switzerland,1 and Mabritec AG, Riehen, Switzerland2 Received 25 January 2010/Returned for modification 15 March 2010/Accepted 9 June 2010. laborious. Although very recently Stoop et al. (14) described for the first time rpoB based PCR systems which enable the identification to the species level strains previously confirmed to belong to the genus Cronobacter, there is still a need for alternative procedures that allow rapid and reliable identification. In recent years, several reports have shown the feasibility of using matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) for identifying microorganisms (for a review, see reference 13). The detection of protein mass patterns has become a convenient tool for the rapid analysis of bacteria (5). The method analyzes the profiles of proteins that are extracted from whole bacteria. A MALDI mass spectrometer can efficiently detect numerous molecules simultaneously. Protein mass patterns can be used for identification of bacteria at the genus, species, and in some cases the subspecies level. The mass pattern detection method has been validated recently in several studies for food-borne pathogens, including the classification and identification of Arcobacter, Campylobacter, Clostridia, Listeria, Salmonella, Staphylococcus species and Vibrio parahaemolyticus (1, 2, 3, 4, 6, 7). The aim of the present study was to develop a reference MS database library of biomarker protein mass patterns (Spectral Archive and Microbial Identification System [SARAMIS] SuperSpectrum), including Cronobacter target strains as well as nontarget strains, and to perform thereafter a blind test using strains from various Cronobacter species and nontarget strains to validate the MALDI-TOF-based identification system.. The genus Cronobacter comprises six species, Cronobacter sakazakii, Cronobacter malonaticus, Cronobacter muytjensii, Cronobacter dublinensis, Cronobacter turicensis, and Cronobacter genomospecies 1, which have been recognized on the basis of a polyphasic approach using extensive geno- and phenotypic evaluations (8, 9). The definition of six species within the genus Cronobacter was further supported by a recent study in which a multilocus sequence analysis (MLSA) approach was used (11). Cronobacter spp. are Gram-negative opportunistic foodborne pathogens and are known as rare but important causes of life-threatening neonatal infections which can lead to severe disease manifestations such as brain abscesses, meningitis, necrotizing enterocolitis, and systemic sepsis (12). Neonates and infants under 2 months of age which are born prematurely are at greater risk of Cronobacter infections from consuming Cronobacter-contaminated powdered infant formulas (8). Rapid and reliable identification of strains of the genus Cronobacter and differentiation from phenotypically similar, apathogenic Enterobacter turicensis, Enterobacter helveticus, and Enterobacter pulveris are important for surveillance, prevention, and control of food-borne diseases. Moreover, for Cronobacter a species differentiation is relevant for epidemiological studies, and the different species show differences in sensitivities to chemical agents and antibiotics. However, identification of Cronobacter species by biochemical tests is very. * Corresponding author. Mailing address: Institute for Food Safety and Hygiene, Vetsuisse Faculty University of Zurich, Winterthurerstr. 272, CH-8057 Zurich, Switzerland. Phone: 41-44-6358651. Fax: 41-446358908. E-mail: stephanr@fsafety.uzh.ch. 䌤 Published ahead of print on 16 June 2010.. MATERIALS AND METHODS Bacterial strains. A first set of strains was used to define the superspectrum: 30 C. sakazakii strains (E266, E269, E272, E274, E280, E283, E292, E302, E309,. 2846. Downloaded from http://jcm.asm.org/ on May 16, 2020 by guest. Cronobacter spp. are Gram-negative opportunistic food-borne pathogens and are known as rare but important causes of life-threatening neonatal infections. Rapid and reliable identification of Cronobacter species and their differentiation from phenotypically similar, nonpathogenic Enterobacter turicensis, Enterobacter helveticus, and Enterobacter pulveris have become increasingly important. We evaluated here the application of matrixassisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) for rapid genus and species identification of the six Cronobacter species recognized so far. To this end, we developed a reference MS database library that includes 54 Cronobacter target strains as well as 17 nontarget strains. The strains provided reproducible and unique mass spectra profiles covering a wide molecular mass range (2,000 to 30,000 Da). Genus- and species-specific biomarker protein mass patterns were determined. The defined biomarker mass patterns (Spectral Archive and Microbial Identification System [SARAMIS] SuperSpectrum) were validated using 36 strains from various Cronobacter species as well as eight nontarget strains. For all strains the mass spectrometry-based identification scheme yielded identical results as with a PCR-based identification system. All strains were correctly identified, and no nontarget strain was misidentified as Cronobacter. Our study demonstrates that MALDI-TOF MS is a reliable and powerful tool for the rapid identification of Cronobacter strains to the genus and species level..

(2) VOL. 48, 2010. IDENTIFICATION OF CRONOBACTER BY MALDI-TOF MS. E314, E328, E393, E423, E468, E601, E602, E604, E607, E620, E622, E624, E627, E632, E736, E739, E750, E761, E768, E796, and E828), four C. malonaticus strains (E265, E621, E825, and E829), six C. turicensis strains (3032, E609, E626, E676, E681, and E688), two C. genomospecies strains (E680 and E797), six C. muytjensii strains (E456, E488, E603, E616, E769, and E888), and six C. dublinensis strains (E464, E465, E515, E791, E798, and E799), with isolates originating from human, food, and environmental origins included in this study. The selected strains were part of a taxonomy study (9, 10). This factor guaranteed the correct identification of all strains used for the definition of the superspectrum. Moreover, several nontarget strains were included in the study (Escherichia coli ATCC 25922, Escherichia hermanii DSM 4560, Escherichia vulneris DSM 4564, Enterobacter cloacae DSM 30054, Enterobacter kobei DSM 13645, Enterobacter ludwigii DSM 166889, Enterobacter cancerogenus DSM 17580, Enterobacter asburiae DSM 17506, Enterobacter radicincitans DSM 16656, Leclerica adecaboxylata DSM 5077, Enterobacter pyrinus DSM 12410, Enterobacter aerogenes DSM 30053, Enterobacter turicensis 508/05T [DSM 18397T], Enterobacter helveticus 513/05T [DSM 18396T]), Enterobacter pulveris 601/05T [DSM 19144T]), Enterobacter amnigenus DSM 4486, and E. cowanii DSM 18146). Second set of strains for validation purposes. After defining the superspectra for the different species, 44 additional strains isolated within a field study and identified by the recently described PCR system (14) were used for validation of the system in a blind test: 24 C. sakazakii, 7 C. malonaticus, 1 C. turicensis, 2 C. dublinensis, 2 C. muytensii, and 8 nontarget strains. The selected strains originated from food and environmental samples. Culture conditions. Standard conditions were used for bacterial culturing. All strains were streaked onto sheep blood agar (Difco Laboratories, Detroit, MI; 5% sheep blood from Oxoid, Hampshire, United Kingdom) and on tryptic soy agar (TSA) agar (BD, Sparks, MD) and incubated at 37°C for 24 and 48 h, and single colonies were selected. Preparation of samples for MALDI-TOF MS of whole bacterial cells. Cells from representative single bacterial colonies were directly smeared onto a target spot of a steel target plate by using a disposable loop, overlaid with 1 ␮l of matrix consisting of a saturated solution of sinapic acid (49508; Sigma-Aldrich, Buchs, Switzerland) in 60% acetonitrile (154601; Sigma-Aldrich, Buchs, Switzerland)– 0.3% trifluoroacetic acid (T6508; Sigma-Aldrich, Buchs, Switzerland), and air dried within minutes at room temperature. A first subset of strains grown on TSA and blood agar was tested after 24 and 48 h to compare the reproducibility of masses within eight replicates and to choose the optimized growth conditions for further studies. Additionally, replicates of each isolate were transferred onto two independent steel targets for mass accuracy and proof of external instrument. FIG. 2. Spectra of different Cronobacter species and three apathogenic Enterobacter species, grown on TSA. The spectra display high overall levels of similarity but slight mass shifts of peaks in the protein profiles (4,000 to 12,000 Da).. calibration. All strains included in this study were cultivated for 48 h on blood agar and TSA and were measured in eight replicates. For each strain, four distinct single bacterial colonies were spotted in duplicate onto two independent steel target plates. MALDI-TOF MS parameters. Protein mass fingerprints were obtained using a MALDI-TOF mass spectrometry Axima Confidence machine (Shimadzu-Biotech Corp., Kyoto, Japan), with detection in the linear, positive mode at a laser frequency of 50 Hz and within a mass range of 2,000 to 30,000 Da. Acceleration voltage was 20 kV, and the extraction delay time was 200 ns. A minimum of 10 laser shots per sample was used to generate each ion spectrum. For each bacterial sample, a total of 100 protein mass fingerprints were averaged and processed using the Launchpad v. 2.8 software (Shimadzu-Biotech Corp., Kyoto, Japan). This software was also used for peak processing of all raw spectra with the following settings: the advanced scenario was chosen from the Parent Peak Cleanup menu, peak width was set at 80 channels, the smoothing filter width was set at 50 channels, the baseline filter width was set at 500 channels and for peak detection method the threshold apex was chosen. For the threshold apex peak detection, the threshold type was set as dynamic and the threshold offset was set to 0.025 mV with a threshold response factor of 1.25. The processed spectra were exported as peak lists with m/z values and signal intensities for each peak in the ASCII format. Calibration was conducted for each target plate using spectra of the reference strain Escherichia coli DH5␣. MALDI-TOF MS spectral analysis. Reference spectra for the first set of 54 Cronobacter strains and 17 nontarget strains were analyzed in duplicates for each of the four representative single bacterial colonies. Generated protein mass fingerprints were analyzed with SARAMIS (AnagnosTec, Potsdam-Golm, Germany). In the first step biomarker mass patterns, called superspectra, were calculated for the genus Cronobacter as well as for each of the six Cronobacter species, using the SARAMIS SuperSpectrum tool. Therefore, peak lists for all 54 Cronobacter isolates (reference set) were imported into the SARAMIS software in octuplicates. Peak lists were trimmed to a mass range of 2 to 30 kDa, and peaks with a relative intensity below 1% were removed. Peak lists were binned, and average masses were calculated using the SARAMIS SuperSpectrum tool with an error of 800 ppm. For the identification of Cronobacter genus, respectively, species-specific protein mass patterns, all Enterobacteriaceae family biomarker masses were excluded by using the SARAMIS Enterobacteriaceae family exclusion list. From the remaining peaks only masses present in at least 50% of the spectra were selected for the genus superspectrum; alternatively, masses. Downloaded from http://jcm.asm.org/ on May 16, 2020 by guest. FIG. 1. Representative spectra of C. sakazakii E393 grown on blood agar (A) or TSA (B) and the corresponding superspectrum computed with the SARAMIS software (C). Selected biomarker masses (4,000 to 12,000 Da) and the corresponding peak numbers are as shown in Table 1.. 2847.

(3) 2848. STEPHAN ET AL.. J. CLIN. MICROBIOL.. TABLE 1. Selected genus- and species-identifying biomarker masses obtained by whole-cell MALDI-TOF-MS of Cronobacter spp. Present in superspectrum?b. Experimental avg mass (Da) ⫾ 800 ppm error. 1. 2. 3. 4. 5. 6. 7. 8. Identification category. 1 2 3 4 5. 2,059.7 ⫾ 1.65 2,853.2 ⫾ 2.28 2,869.8 ⫾ 2.30 3,150.1 ⫾ 2.52 3,636.6 ⫾ 2.91. Yes Yes Yes No Yes. No No No No Yes. No No No Yes No. No No No No Yes. Yes Yes No No No. Yes No No No Yes. Yes No No No Yes. No No No No No. GIBMs SIBMs SIBMs SIBMs GIBMs. 6 7 8 9 10. 3,657.6 ⫾ 2.93 3,679.1 ⫾ 2.94 4,041.8 ⫾ 3.23 4,065.9 ⫾ 3.25 4,139.4 ⫾ 3.31. No No No Yes No. Yes No No No Yes. No No Yes No Yes. No No No No No. No Yes No No Yes. No Yes No No Yes. No No No No Yes. No No No No No. SIBMs SIBMs SIBMs SIBMs GIBMs. 11 12 13 14 15. 4,364.5 ⫾ 3.49 4,445.8 ⫾ 3.56 4,613.1 ⫾ 3.69 4,502.5 ⫾ 3.60 4,627.7 ⫾ 3.70. No No No No No. No No Yes No No. No Yes No Yes No. No No Yes No No. No No No No No. No Yes No No Yes. No No No No No. Yes No No No No. EIBMs SIBMs SIBMs SIBMs SIBMs. 16 17 18 19 20. 4,738.1 ⫾ 3.79 4,773.8 ⫾ 3.82 5,046.4 ⫾ 4.04 5,144.2 ⫾ 4.12 5,382.1 ⫾ 4.31. No No No No No. No No No No No. No No Yes Yes No. No No No Yes No. No No No No No. No Yes No Yes No. No No No No No. Yes No No No Yes. EIBMs SIBMs SIBMs SIBMs EIBMs. 21 22 23 24 25. 5,701.4 ⫾ 4.56 5,710.8 ⫾ 4.57 5,716.5 ⫾ 4.57 5,744.7 ⫾ 4.60 5,858.0 ⫾ 4.69. No Yes No Yes No. Yes No No Yes No. No No No No Yes. Yes No No Yes No. No No Yes No No. No No No Yes No. Yes No No Yes No. No No No No No. GIBMs SIBMs SIBMs GIBMs SIBMs. 26 27 28 29 30. 5,905.0 ⫾ 4.72 5,918.0 ⫾ 4.73 5,924.3 ⫾ 4.74 5,951.4 ⫾ 4.76 6,257.5 ⫾ 5.01. No Yes No Yes No. Yes No No No No. No No No No No. No No No No No. No No Yes No No. No No No No No. No No No No No. No No No No Yes. SIBMs SIBMs SIBMs SIBMs EIBMs. 31 32 33 34 35. 6,306.1 ⫾ 5.04 6,322.3 ⫾ 5.06 6,385.6 ⫾ 5.11 6,414.5 ⫾ 5.13 6,511.5 ⫾ 5.21. No Yes No No No. No Yes No No No. Yes No No No Yes. No Yes No No No. No Yes No No No. Yes No No Yes Yes. No Yes No No No. No No Yes No No. SIBMs GIBMs EIBMs SIBMs SIBMs. 36 37 38 39 40. 6,521.8 ⫾ 5.22 6,538.8 ⫾ 5.23 6,590.7 ⫾ 5.27 6,624.2 ⫾ 5.30 6,859.2 ⫾ 5.49. No No No Yes No. Yes No No Yes No. No No No Yes No. No Yes No No No. No No Yes No No. No No No No No. No No No Yes No. No No No No Yes. SIBMs SIBMs SIBMs GIBMs EIBMs. 41 42 43 44 45. 7,027.5 ⫾ 5.62 7,041.2 ⫾ 5.63 7,063.0 ⫾ 5.65 7,160.8 ⫾ 5.73 7,197.8 ⫾ 5.76. No Yes No No No. No No Yes No No. No Yes No No No. Yes No No No Yes. No No Yes No No. No Yes No No No. No No No No No. No No No Yes No. SIBMs SIBMs SIBMs EIBMs SIBMs. 46 47 48 49 50. 7,212.1 ⫾ 5.77 7,275.7 ⫾ 5.82 7,292.4 ⫾ 5.83 7,320.2 ⫾ 5.86 7,354.7 ⫾ 5.88. No No Yes No No. No No No Yes No. No No No Yes No. No No No Yes No. Yes No No No Yes. No No No No No. No No No No No. No Yes No No No. SIBMs EIBMs SIBMs SIBMs SIBMs. 51 52 53 54 55. 7,364.3 ⫾ 5.89 7,483.2 ⫾ 5.99 7,499.6 ⫾ 6.00 7,526.6 ⫾ 6.02 7,561.6 ⫾ 6.05. No No Yes No No. No No No Yes No. Yes No No No No. No Yes No No No. No No No No Yes. Yes No No No No. No No No No No. No No No No No. SIBMs SIBMs SIBMs SIBMs SIBMs. Possible RPc identity and mass 关m/z ⫹ H兴⫹. 50S RP L36 关4,365兴. 50S RP L34 关5,381兴. 50S RP L32 关6,303 (-Met)兴 50S RP L32 关6,319 (-Met)兴 50S RP L30 关6,384 (-Met)兴. 50S RP L35 关7,159兴. 50S RP L29 关7,275兴 50S RP L35 关7,290兴. Continued on following page. Downloaded from http://jcm.asm.org/ on May 16, 2020 by guest. Peak no.a.

(4) VOL. 48, 2010. IDENTIFICATION OF CRONOBACTER BY MALDI-TOF MS. 2849. TABLE 1—Continued Present in superspectrum?b. Possible RPc identity and mass 关m/z ⫹ H兴⫹. Peak no.a. Experimental avg mass (Da) ⫾ 800 ppm error. 1. 2. 3. 4. 5. 6. 7. 8. Identification category. 56 57 58 59 60. 7,572.1 ⫾ 6.06 7,728.7 ⫾ 6.18 7,798.6 ⫾ 6.24 8,035.3 ⫾ 6.43 8,086.4 ⫾ 6.47. No No No No No. No No No No No. Yes Yes No No Yes. No No No Yes No. No No No No No. Yes No No No No. No No No No No. No No Yes No No. SIBMs SIBMs EIBMs SIBMs SIBMs. 61 62 63 64 65. 8,095.0 ⫾ 6.48 8,107.2 ⫾ 6.49 8,136.1 ⫾ 6.51 8,170.8 ⫾ 6.54 8,189.7 ⫾ 6.55. No No Yes No No. Yes No No No No. No No No No No. No No No No No. No Yes No No Yes. No No No Yes No. No No No No No. No No No No No. SIBMs SIBMs SIBMs SIBMs SIBMs. 66 67 68 69 70. 8,199.5 ⫾ 6.56 8284.7 ⫾ 6.63 8,374.2 ⫾ 6.70 8,508.1 ⫾ 6.81 8,569.8 ⫾ 6.86. No No No No No. Yes No No No No. No No No No Yes. No No No No No. No No No Yes No. No No No No No. No No No No No. No Yes Yes No No. SIBMs EIBMs EIBMs SIBMs SIBMs. 30S RP S21 关8,370 (-Met)兴. 71 72 73 74 75. 8,701.9 ⫾ 6.96 8,718.3 ⫾ 6.97 8,860.7 ⫾ 7.09 8,896.9 ⫾ 7.12 8,972.6 ⫾ 7.18. No No Yes No No. No Yes Yes No No. Yes No No No No. Yes No Yes No Yes. No No Yes No No. Yes No No No No. Yes No Yes No No. No No No Yes No. GIBMs SIBMs GIBMs EIBMs SIBMs. 30S RP S18 关8,856 (-Met)兴. 76 77 78 79 80. 9,012.8 ⫾ 7.21 9,194.0 ⫾ 7.36 9,234.2 ⫾ 7.39 9,242.0 ⫾ 7.39 9,260.6 ⫾ 7.41. No No No No Yes. No No No Yes No. No Yes Yes No No. No No Yes No No. No No Yes No No. No No No No Yes. No No Yes No No. Yes No No No No. EIBMs SIBMs GIBMs SIBMs SIBMs. 30S RP S16 关9,235兴. 81 82 83 84 85. 9,482.8 ⫾ 7.59 9,533.6 ⫾ 7.63 9,576.6 ⫾ 7.66 9,687.7 ⫾ 7.75 10,098.5 ⫾ 8.08. No No No No No. No No No No No. No No Yes No No. No No No No No. No Yes No No No. No No No No No. No No No No No. Yes No No Yes Yes. EIBMs SIBMs SIBMs EIBMs EIBMs. 30S RP S17 关9,574 (-Met)兴. 86 87 88 89 90. 10,289.1 ⫾ 8.23 10,622.9 ⫾ 8.50 10,715.7 ⫾ 8.57 10,842.1 ⫾ 8.67 11,198.5 ⫾ 8.96. No No No No No. No No No Yes Yes. No Yes Yes No Yes. No No No Yes No. No No No Yes No. No Yes No Yes No. No Yes No Yes No. Yes No No No No. EIBMs GIBMs SIBMs GIBMs SIBMs. 30S RP S19 关10,286 (-Met)兴. 91 92 93 94 95. 11,231.3 ⫾ 8.99 11,353.1 ⫾ 9.08 11,382.1 ⫾ 9.11 11,479.8 ⫾ 9.18 11,770.2 ⫾ 9.42. Yes No Yes No No. No No Yes No No. Yes Yes No Yes Yes. Yes No Yes No No. No No Yes No No. Yes No Yes No No. Yes No Yes No No. No No No No No. GIBMs SIBMs GIBMs SIBMs SIBMs. 50S RP L23 关11,127兴. 96 97 98 99 100. 11,980.8 ⫾ 9.58 12,082.2 ⫾ 9.67 12,795.1 ⫾ 10.24 13,104.7 ⫾ 10.48 15,453.6 ⫾ 12.36. No No No No No. No No No No No. Yes Yes No Yes Yes. No No No No No. No No No No No. No No Yes No No. No No No No No. No No No No No. SIBMs SIBMs SIBMs SIBMs SIBMs. 50S RP L31 关7,797兴. 30S RP S15 关10,093 (-Met)兴. 50S RP L25 关10,714兴 50S RP L24 关11,200 (-Met)兴. 30S RP S14 关11,479 (-Met)兴 30S RP S10 关11,767兴. a Data show whether or not the indicated species was found in the superspectrum, as follows: 1, C. sakazakii; 2, C. malonaticus; 3, C. turicensis; 4, C. dublinensis; 5, C. muytjensii; 6, C. genomospecies 1; 7, Cronobacter genus, 8, Enterobacteriaceae family exclusion list. b RP, ribosomal protein.. present in at least 75% of the spectra were selected for species superspectra. The specificity of these potential biomarker masses was determined by comparison against the whole SARAMIS spectral archive. Fourteen masses for the genus and between 19 and 33 masses for the different species were weighted and used as superspectrum for automated Cronobacter genus and species identification. For dendrogram generation, the SARAMIS Premium software package was used. The dendrogram was based on whole spectra, including all signals passing the peak detection criteria of the Launchpad software. A binary mass list was. calculated with an error of 800 ppm, and a single-link clustering algorithm was applied.. RESULTS AND DISCUSSION In order to establish a standardized analytical protocol, sample preparation and mass spectrometric parameters that could. Downloaded from http://jcm.asm.org/ on May 16, 2020 by guest. 50S RP L27 关9,009 (-Met)兴.

(5) 2850. STEPHAN ET AL.. J. CLIN. MICROBIOL.. affect the reproducibility and accuracy of data were first evaluated. The influence of growth conditions on the MALDITOF MS patterns of different Cronobacter species was analyzed by subculturing strains on two different media. Depending on the culture medium, some variations in the pattern compositions and the measured relative intensities were observed (Fig. 1). Results were most reproducible when using bacterial strains grown on TSA agar for 48 h by applying the direct smear method. These conditions also showed a slightly better discrimination of species in a cluster analysis than samples grown on blood agar (data not shown). However, genus- and species-identifying biomarker masses were found to be present in all strains analyzed, independent of growth time and culture conditions. In a first step, 54 Cronobacter and 17 nontarget strains were analyzed eight times each. The spectra displayed high overall levels of similarity, but slightly different mass patterns for different Cronobacter species were detected (Fig. 2). The SARAMIS software was used to identify biomarker masses and to assign them to the following three categories: (i) biomarker masses that were present in most of the Cronobacter spectra but also in other Enterobacteriaceae and thus had no discriminatory power to identify the genus Cronobacter; these masses with discriminatory power only on the family level were des-. ignated Enterobacteriaceae-identifying biomarker masses (EIBMs); (ii) biomarker masses that were calculated as part of a protein mass pattern for the identification of the genus Cronobacter; these masses were reproducibly detected in the genus Cronobacter and were designated genus-identifying biomarker masses (GIBMs); (iii) biomarker masses that were calculated as part of protein mass patterns for the identification of Cronobacter species; these species identifying masses were assigned accordingly as SIBMs. In total, 17 masses were designated EIBMs. Fourteen biomarker masses were selected as biomarkers to unambiguously discriminate Cronobacter spp. from other genera (GIBMs), and 69 SIBMs were reproducibly detected, resulting in specific protein mass patterns and a clear discrimination of the six species. The designations of these EIBMs, GIBMs, and SIBMs are shown in Table 1. Based on the GIBMs and the SIBMs superspectra for Cronobacter sp., Cronobacter sakazakii, Cronobacter malonaticus, Cronobacter muytjensii, Cronobacter dublinensis, Cronobacter turicensis, and Cronobacter genomospecies 1 were defined. Additionally, from sequence database information (ExPASy), several masses could be expected for selected ribosomal proteins: the large ribosomal protein (RP) L36 (4,365 Da) was detectable in all Cronobacter species and is known as a prominent marker of Enterobacteriaceae. The small RP S18 (8,856 Da) was detect-. Downloaded from http://jcm.asm.org/ on May 16, 2020 by guest. FIG. 3. Cluster analysis of different target strains and three relevant nontarget strains (E. turicensis, E. helveticus, and E. pulveris), based on whole spectra (2,000 to 15,000 Da). Isolates of C. malonaticus, which was first described as a subspecies of C. sakazakii, show a distinct subcluster and confirm recent results reported by Iversen et al. (10)..

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Stephan, and H. Joosten. 2008. Cronobacter gen. nov., a new genus to accommodate the biogroups of Enterobacter sakazakii, and proposal of Cronobacter sakazakii gen. nov. comb. nov., C. malonaticus sp. nov., C. turicensis sp. nov., C. muytjensii sp. nov., C. dublinensis sp. nov., Cronobacter genomospecies 1, and of three subspecies, C. dublinensis sp. nov. subsp. dublinensis subsp. nov., C. dublinensis sp. nov. subsp. lausannensis subsp. nov., and C. dublinensis sp. nov. subsp. lactaridi subsp. nov. Int. J. Syst. Evol. Microbiol. 58:1442–1447. Kuhnert, P., B. M. Korczak, R. Stephan, H. Joosten, and C. Iversen. 2009. Phylogeny and whole genome DNA-DNA similarity of Cronobacter (Enterobacter sakazakii) and related species by multilocus sequence analysis (MLSA). Int. J. Food Microbiol. 136:152–158. Lehner, A., and R. Stephan. 2004. Microbiological, epidemiological and food safety aspects of Enterobacter sakazakii. J. Food Prot. 67:2850–2857. Sauer, S., and M. Kliem. 2010. Mass spectrometry tools for the classification and identification of bacteria. Nat. Rev. Microbiol. 8:74–82. Stoop, B., A. Lehner, C. Iversen, S. Fanning, and R. Stephan. 2009. Development and evaluation of rpoB based PCR systems to differentiate the six proposed species within the genus Cronobacter. Int. J. Food Microbiol. 136:165–168.. Downloaded from http://jcm.asm.org/ on May 16, 2020 by guest. able in four Cronobacter species and thus is a marker for Cronobacter. Finally, the large RP L32 observed in C. turicensis (6,303 Da) carried a mutation in 1 amino acid, resulting in a measurable mass shift of 16 Da in comparison to C. sakazakii (6,319 Da) (Table 1). In a next step, the defined superspectra were used to identify 36 Cronobacter and 8 nontarget strains grown on TSA as well as on blood agar in a blind test. For all strains the mass spectrometry-based identification scheme yielded identical results as a PCR-based identification system (14). All these 44 strains were correctly identified as Cronobacter on the genus as well as on the species level or as nontarget strains, respectively. Moreover, a dendrogram was calculated using MALDI-TOF MS whole spectra of Cronobacter strains, and three nontarget type strains were identified by using the SARAMIS software (Fig. 3). The topology obtained using MALDI-TOF MS profiling strongly resembled the topologies of dendrograms constructed using a 16S rRNA gene phylogenetic tree, fluorescent amplified fragment length polymorphism analysis, and ribotype dendrograms of Cronobacter (9). Supporting recent results, and visible in the dendrogram, is C. malonaticus, which was first described as a subspecies of C. sakazakii (9) and defined as a separate species by DNA:DNA analysis (10) only later. It is in close relation to C. sakazakii but in a distinct subcluster. In summary, our study demonstrates that MALDI-TOF MS is a reliable and powerful tool for the rapid, reliable, and relatively inexpensive identification of Cronobacter strains to the genus and species level. The major advantages of MALDITOF MS-based bacterial identification compared to other identification methods are the ease and speed of the procedure and the possibility of automation and high-throughput analysis. The costs of consumables are minimal, and the whole process takes less than 5 min per sample.. 2851.

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