Genotypic and phenotypic characterisation of a collection of Cronobacter (Enterobacter sakazakii) isolates

Genotypic and phenotypic characterisation of a collection of Cronobacter (Enterobacter sakazakii) isolates

International Journal of Food Microbiology 139 (2010) 116–125 Contents lists available at ScienceDirect International Journal of Food Microbiology j...

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International Journal of Food Microbiology 139 (2010) 116–125

Contents lists available at ScienceDirect

International Journal of Food Microbiology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i j f o o d m i c r o

Short Communication

Genotypic and phenotypic characterisation of a collection of Cronobacter (Enterobacter sakazakii) isolates Rabeb Miled-Bennour a, Timothy C. Ells b,⁎, Franco J. Pagotto c, Jeffrey M. Farber c, Annaelle Kérouanton a, Thomas Meheut a, Pierre Colin d, Han Joosten e, Alexandre Leclercq f, Nathalie Gnanou Besse a a Agence française de sécurité sanitaire des aliments, Afssa Laboratoire d'Etudes et de Recherches sur la Qualité des Aliments et des Procédés agro-alimentaires (Afssa LERQAP), 23 Avenue du Général de Gaulle, 94706 Maisons Alfort cedex, France b Atlantic Food and Horticulture Research Centre, Agriculture and Agri-Food Canada, 32 Main Street, Kentville, Nova Scotia, Canada B4N1J5 c Listeriosis Reference Service, Bureau of Microbial Hazards, Health Canada, 251 Sir F.G. Banting Driveway, Ottawa, Ontario, Canada K1A0K9 d Ecole Supérieure de Microbiologie et de Sécurité Alimentaire (ESMISAB), Plouzane, France e Quality and Safety Department, Nestlé Research Centre, Vers-chez-les-Blanc, CH-1000 Lausanne, Switzerland f Institut Pasteur, 25 rue du Docteur Roux, Paris, France

a r t i c l e

i n f o

Article history: Received 5 October 2009 Received in revised form 27 January 2010 Accepted 30 January 2010 Keywords: Enterobacter sakazakii Cronobacter Powdered infant formula Genotyping Growth rate

a b s t r a c t Enterobacter sakazakii has been identified as the causative agent of serious neonatal infections, associated with high mortality rate. In many cases, powdered infant formula (PIF) has been identified as the source of infection. Recently, E. sakazakii was proposed to be classified in a new genus, Cronobacter. Since knowledge on this pathogen is still incomplete, there is a need for molecular characterization schemes in order to help with epidemiological investigation and evaluate strain variability. The objectives of this study were to combine genotypic (pulsed-field gel electrophoresis [PFGE], 16S rRNA gene sequencing, and automated ribotyping) methods with traditional phenotypic biochemical methods to characterize a collection of Cronobacter isolates from various origins. In addition, the relative growth dynamics were compared by estimating the growth rates for each isolate in non-selective broth (BHI) at 25 °C and 37 °C. According to biochemical test profiles the majority of isolates were identified as Cronobacter sakazakii, which seemed to be the most common species distributed in the environment of PIF production plants. Furthermore, the PFGE technique displayed very high discriminatory power as 61 distinct pulsotypes were revealed among the 150 Cronobacter isolates. Combining information on sample origin and pulse type, 64 isolates were deemed as unique strains. Although genetic typing data for the strains clearly delineated them into clusters closely corresponding to biochemical speciation results, it was not without discrepancies as some strains did not group as predicted. Important for quantitative risk assessment is the fact that despite the high genetic heterogeneity observed for this collection, most Cronobacter strains displayed similar growth rates irrespective of species designation. Crown Copyright © 2010 Published by Elsevier B.V. All rights reserved.

1. Introduction Enterobacter sakazakii, a Gram-negative motile rod belonging to the Enterobacteriaceae family was formerly known as a “yellow pigmented Enterobacter cloacae”. It was initially designated as a unique species in 1980 (Farmer et al., 1980), and has subsequently been investigated (Iversen et al., 2007; 2008) to clarify its taxonomy. The proposed reclassification of this organism into a new genus, Cronobacter, was based on the results of independent molecular methods and of biochemical markers (Iversen et al., 2007; 2008). Cronobacter species are considered as emerging foodborne pathogens, and have been identified as the causative agent of several outbreaks

⁎ Corresponding author. Tel.: + 1 902 679 5388; fax: + 1 902 679 2311. E-mail address: [email protected] (T.C. Ells).

or sporadic cases of very serious neonatal infections causing meningitis, septicaemia or necrotising enterocolitis in infants (Arseni et al., 1987; Nazarowec-White and Farber, 1997a; Bar-Oz et al., 2001). The disease frequency is very low (only 76 cases were reported from 1961 to 2003) (Iversen and Forsythe, 2003; Gurtler et al., 2005), but the mortality rate has been reported to be as high as 20 to 50% (Anonymous, 2004; Lehner and Stephan, 2004) with surviving patients often suffering severe neurological sequelae (Biering et al., 1989; Anonymous, 2006a). In most cases, the source of infection was powdered infant formula (PIF) (Simmons et al., 1989; Clark et al., 1990; Van Acker et al., 2001; Lehner and Stephan, 2004; Anonymous, 2005). Moreover, the high resistance of C. sakazakii to osmotic stress (including drying), contributes to its persistence in PIF factories, products and environments (Breeuwer et al., 2003). C. sakazakii has been reported to be prevalent in 40% of dry environmental samples from PIF factories (Guillaume-Gentil et al., 2005). Like many other enterobacteriaceae, C. sakazakii has also been

0168-1605/$ – see front matter. Crown Copyright © 2010 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.ijfoodmicro.2010.01.045

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isolated from a wide range of foods and processing environments, as well as households (Kandhai et al., 2004a, 2004b). In order to facilitate epidemiological investigations, it is recommended that all Cronobacter isolates should be characterized both genotypically and phenotypically (Gurtler et al., 2005). In recent years, the quantitative risk assessment (QRA) has become a useful tool for improvement of the sanitary quality of food. Therefore, the acquisition of data concerning strain diversity among pathogens is essential. However, there is a general lack of information regarding differences between Cronobacter species (Anonymous 2004, 2006a). Several methods may be used to study bacterial biodiversity or source tracking. In particular, molecular based techniques have become important tools for the subtyping of bacteria. Among these, ribotyping, random amplification of polymorphic DNA, pulsed-field gel electrophoresis (PFGE), multiple-locus variable-number tandemrepeat analysis (MLVA) and repetitive sequence-based polymerase chain reaction (REP-PCR) have been successfully applied to the characterization of Cronobacter species (Nazarowec-White and Farber, 1999; Block et al., 2002; Drudy et al., 2006; Mullane et al., 2007; Proudy et al., 2008a, 2008b; El-Sharoud et al., 2008; Healy et al., 2008). Although a PFGE standardised protocol has not yet been validated for this pathogen, this method is considered the “gold standard” method for subtyping of foodborne bacteria, and the most discriminatory technique for genetic typing (Nazarowec-White and Farber, 1999; Healy et al., 2008). The objectives of this study were to apply genotypic and phenotypic methodologies to characterize a collection of Cronobacter strains from various origins including, PIF factories, PIF products and environments, as well as clinical samples. Our investigations included phenotypic characterization using biochemical tests and genetic profiling using PFGE, automated ribotyping and 16S rRNA gene sequencing. Additionally, in order to compare growth characteristics, growth rates were estimated for each strain in non-selective broth at 25 °C and 37 °C. 2. Materials and methods 2.1. Collection of Cronobacter isolates A collection of 150 isolates, originating from clinical samples, PIF products and environmental samples from PIF production plants (several European factories from France, Germany and Switzerland) were examined in this study. Of these 150 isolates, 70% were isolated from the PIF production environment, 20% PIF, and 10%, including clinical isolates, were received from the collections of other institutes. Isolates were previously identified as E. sakazakii using the ISO/TS 22964 standard method for the detection of E. sakazakii in PIF (Anonymous, 2006b; Gnanou Besse et al., 2006). Briefly, the method is based on pre-enrichment in buffered peptone water, followed by a selective enrichment procedure in modified lauryl sulfate tryptose broth and plating on the chromogenic selective isolation agar “Enterobacter sakazakii Isolation Agar” (ESIA). Typical colonies chosen were those with glucosidase activity (blue on chromogenic medium) and either white or yellow pigment on TSA. Presumptive isolates were further confirmed using ID 32E version 3.0 biochemical galleries (bioMérieux, Marcy l'étoile, France). These confirmation tests were repeated twice on each isolate, following a few months time interval. Stock cultures were maintained frozen at −80 °C using Cryobank tubes (AES Laboratoires, Combourg, France). Cultures were revived by plating onto tryptone soya agar with yeast extract (TSA-YE) before use. 2.2. Pulsed field gel electrophoresis (PFGE) typing In order to determine the genetic diversity within our collection, all Cronobacter isolates were subjected to PFGE, the current “gold


standard” for molecular typing of foodborne bacterial pathogens. In this study, isolates with different PFGE profiles, or isolates with identical PFGE patterns but from a different origin, were considered to be different strains. The PulseNet standardised PFGE protocol for the subtyping of Salmonella spp. was adapted to Cronobacter (Hunter et al., 2005; Ribot et al., 2006), by performing the following modifications: the quantity of restriction enzyme XbaI (Roche Diagnostics, Mannheim, Germany) used to digest genomic DNA was increased 1.5 fold compared to the current practice in our laboratory (from 50 to 75 U per sample). For strains known to be affected by DNA degradation (difficulties encountered for 11% of our isolates), the Tris was replaced by HEPES (N′-2-Hydroxyethylpiperazine-N′-2 ethanesulphonic acid) at the same concentration in all solutions; thiourea was added to the electrophoresis buffer to a final concentration of 100 µM (Liesegang and Tschäpe, 2002; Koort et al., 2002; Silbert et al., 2003). Salmonella serotype Braenderup (strain H9812) was used as the DNA size marker (Hunter et al., 2005) for comparative analysis. Comparisons were realised using Bionumerics 4.5 software (Applied Maths, Sint-Martens-Latem, Belgium). A dendrogram was obtained using the unweighted pair group method with arithmetic mean (UPGMA) and the DICE coefficient with 1% tolerance. 2.3. Biochemical differentiation of Cronobacter species Iversen et al. (2007), 2008 demonstrated that the important biochemical tests for the differentiation of Cronobacter spp. were indole production, malonate utilization and acid production from dulcitol and methyl-α-D-glucoside. These relevant biochemical tests were applied to all different strains (as determined by PFGE typing) in order to classify them presumptively into Cronobacter species. Briefly, to test the acid production from carbohydrate (dulcitol and methyl-αD-glucopyranoside), strains were incubated in phenol red broth (containing per litre of deionized water: 10 g peptone, 1 g yeast extract, 5 g NaCl, and 0.018 g phenol red) with addition of filtersterilized carbohydrate solution (final concentration: 0.5%). Sodium malonate broth (Difco) was used to determine malonate utilization. Indole production was measured by the addition of James reagent (bioMérieux), after growth in peptone water without indole (bioMérieux). All broths were incubated for 24 h at 37 °C. 2.4. Automated ribotyping Ribotyping was performed with the restriction enzyme EcoRI and the RiboPrinter microbial characterization system (Qualicon Inc., Wilmington, Del.), according to the manufacturer's manual and as previously described (Bruce et al., 1995; Bruce, 1996). A UPGMA dendrogram was created by downloading the riboprints to Bionumerics (version 5.0) using a DICE coefficient with optimization of 1% and a position tolerance of 1.5%. 2.5. 16S rRNA gene sequencing Total genomic DNA was extracted from overnight Luria Betani (LB) broth cultures grown at 37 °C using a commercial DNA extraction kit (Mo Bio Laboratories, Carlsbad, CA, USA). Near full-length (∼1.5 kb) 16S rRNA gene amplicons were generated by PCR in a T-gradient thermocycler (Biometra, Göttingen, Germany) using Taq DNA polymerase (Sigma-Aldrich Canada, Oakville, ON, Canada) and the primer pair, SDBACTF (5′-GAG TTT GAT CMT GCG TCA G-3′) and BAC1492R (5′-TAC GGY TAC CTT GTT ACG ACT T-3′) (Lane, 1985). Cycle conditions were as follows: initial denaturation at 95 °C for 2 min, followed by 30 cycles of denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s, and 2 min elongation at 72 °C. A final extension step of 5 min at 72 °C followed the final cycle. PCR products were diluted 100 fold in TE buffer and then cloned into E. coli using a


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StrataClone PCR cloning kit according to the manufacturer's instructions (Stratagene, La Jolla, CA, USA). DNA sequencing reactions were carried out using the BigDye Terminator v3.1 cycle sequencing kit and run on an ABI 3130 genetic analyzer (Applied Biosystems, Foster City, CA) using a 36 cm capillary column containing POP7 polymer. M13 forward and reverse primers were used to sequence the cloned amplicons from both directions and the universal primer, 16SInternal (5′-TCA CRR CAC GAG CTG ACG A-3′), was incorporated to sequence the internal regions. Sequencer v4.5 (Gene Codes Corp, Ann Arbor, MI) was used to align fragments and sequences were aligned using ARB (Ludwig et al., 2004) and operational taxonomic units (OTU) using a 97% cut off were identified from a distance matrix generated by the ARB software. ARB software was used to generate an aligned sequences file and phylogenetic trees were created using PHYLO_WIN (Galtier et al., 1996). Twenty one additional reference sequences including both Cronobacter spp. as well as other closely related members of the Enterobacteriaceae were also included in the database. Settings for each tree included a Nearest Neighbour Algorithm with a Jukes–Cantor correction and pair-wise gap removal. To statistically evaluate the trees, bootstrap values were calculated using 2000 tree iterations. 2.6. Growth rates comparison Strains were propagated twice (respectively, 6 and 18 h cultures at 37 °C) in Brain Heart Infusion broth (BHI) before use. The final BHI culture was in stationary phase and contained approximately 1 × 109 CFU/ml. All dilutions were performed in BHI broth. Growth curves for each strain were determined in triplicate in BHI broth, at 25 °C and 37 °C, by measuring optical density (OD) at 600 nm using an automated spectrophotometer (Bioscreen C reader, Labsystems, France). The initial level of inoculum in the growth medium (BHI) was approximately 1 × 105 CFU/ml. Growth rates (µ) were estimated from the slope of the tangential line of Ln(OD) evolution in midexponential phase, and compared by a single factor analysis of variance (ANOVA). Though µ measurement through OD evolution does not ascertain the exact growth rates, it is convenient for its estimation and inter-strains comparison purposes. 3. Results and discussion Insight into the genetic and physiological variability of pathogens is a valuable prerequisite for improving the reliability of quantitative risk assessments. The acquisition of data concerning the diversity of strains of foodborne pathogens is an essential part of this framework. It has been proposed that E. sakazakii should be reclassified as five species and one genomospecies belonging to the genus Cronobacter. Recently, Iversen et al. (2007), 2008 applied ribotyping, amplified fragment length polymorphisms (AFLP) and 16S rRNA gene sequencing in combination with DNA–DNA hybridizations to a collection of 210 E. sakazakii isolates. Their results not only formed the basis for the reclassification of this pathogen into the new Cronobacter genus but also clarified species designations. Based on the new nomenclature we have characterized a collection of isolates of Cronobacter spp. For our collection, a high degree of genetic diversity was revealed as PFGE after genomic DNA restriction using XbaI resulted in 61 unique profiles (i.e., clustering by genetic relatedness between isolates was not observed at more than 60% of similarity) (Fig. 1). Moreover, isolates originating from the same processing facilities also varied in PFGE profiles, a trend that has been reported in other studies (Gadzov et al., 2006; Proudy et al., 2008b; Mullane et al., 2007; 2008b; Healy et al., 2008). This illustrates the variety of ecological niches and possible sources of contamination that could impact the sanitary quality of end products leaving PIF production facilities. In order to declare isolates as individual strains our criteria entailed that; 1) isolates must have a unique PFGE profile, or 2) isolates with the

same profile must have different sample origins. Based on these requirements we designated 64 isolates as specific strains. Of this group, 66% had been isolated from PIF production environments, 8% from PIF, 3% from other foods, and 9% were of clinical origin. Information pertaining to sample origin could not be obtained for 14% of these strains. However, no relationship between pulsotype and sample type could be ascertained. The 64 strains were further subjected to discriminatory biochemical tests conducted in two independent laboratories. The results indicated that 82.5% of the strains were C. sakazakii, 8% C. malonaticus, 5% C. muyjtensii, 3% C. dublinensis, and 1.5% C. turicensis (Fig. 1, Table 1). Of the 47 strains isolated from either PIF products or environmental samples from PIF production plants, 91.5% were C. sakazakii, and 8.5% were C. malonaticus indicating the prevalence of C. sakazakii distributed in PIF factories, products and environments. A previous study on a collection of Cronobacter isolates from various origins also displayed a higher number of C. sakazakii and C. malonaticus strains from PIF products and production environments (Healy et al., 2008). Mullane et al. (2008a) also reported similar results for samples obtained from a unique powdered milk-protein factory. The phylogenetic relatedness of our isolates was investigated using a combination of 16S rRNA gene sequencing and automated ribotyping. Ribotyping results obtained here clearly defined groupings which corresponded to their speciation according to biochemical analysis conducted on the strains (Fig. 2). However, two notable exceptions were 05CHPL02 (CDC 28-83) and 05CHPL53. Although the former isolate was identified as C. sakazakii through biochemical tests, ribotyping placed it closer to the non-sakazakii strains in the collection. Conversely, 05CHPL53 was biochemically identified as C. malonaticus but ribotyping categorized it as C. sakazakii. These tests were repeated and performed in two independent labs to confirm these results. Sequencing of the 16S rRNA gene followed by phylogenetic analysis provided a level of discretion which separated C. sakazakii from other species within the genus (Fig. 3). In order to declare two isolates as separate species by 16S rRNA gene sequencing, it is necessary to sequence the entire 16S rRNA gene and the similarity between the two must be b98.3–99% (Stackebrandt and Ebers, 2006). Therefore ∼1.5 kb of the 16S rRNA gene was sequenced here and the GenBank accession numbers are given in Table 2. Within the C. sakazakii grouping there also appeared to be three sub-groups; with subgroup 1 containing 16 isolates including ATCC BAA894; subgroup 2 containing 19 members with reference strain E266 and; subgroup 3 having 22 isolates including reference strains ATCC 29544 and JMC 1233 (Fig. 3). However, attempts to further categorize these isolates at this level may be somewhat artificial since there is N99.3% similarity in the 16S rRNA gene sequence between the most distal members of subgroup 1 and 3. Further discretion could be achieved by employing a DNA–DNA hybridization assay (Iversen et al., 2007). Although most isolates phenotypically designated as C. sakazakii grouped into a defined cluster (three sub groupings), the other species did not fall completely into the other three clusters as we would have predicted according to results from our ribotyping and biochemical analysis. Nor were these categorizations as seamless as those described in the Iversen et al. study (2007). For example strains 05CHPL40 and 05CHPL53, phenotypically identified as C. malonaticus, clustered with the second C. sakazakii sub-group, and two other isolates of the C. malonaticus phenotype (05CHPL46, 07HMPA87A) appeared to be more closely related to the C. sakazakii group rather than forming their own cluster. Furthermore, collection strain 05CHPL02 (CDC 28-83) phenotypically characterized as C. sakazakii, also clustered outside its expected group. According to ribotyping results, 4 of these 5 strains were also separated from the C. sakazakii group, the exception being 05CHPL53 (Fig. 2). Fractionation of the other Cronobacter species into distinct clades by 16S rRNA sequencing also was not as clear. For example, C. muytjensii strains formed their own clade but strains identified as C. turicensis, C. dublinensis and C.

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Fig. 1. Dendrogram showing XbaI-mediated pulsed-field gel electrophoresis (PFGE) profiles of Cronobacter strains. The dendrogram was obtained using the unweighted pair group method with arithmetic mean (UPGMA) and the DICE coefficient with 1% tolerance.


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Table 1 List of Cronobacter strains used in this study along with their PFGE type, origin and growth rates in BHI at 25 °C and 37 °C. Species

PFGE type



Growth rates (h− 1)

Table 1 (continued) Species

ESXB001 05CHPL01


05CHPL36 05CHPL37 05CHPL94 05CHPL38 05CHPL41 05CHPL43 05CHPL45 05CHPL47 05CHPL48 05CHPL50 05CHPL51 05CHPL52 05CHPL54 05CHPL56 05CHPL93 05CHPL99 05CHPL97 05CHPL66 07HMPA41A 07HMPA87B 05CHPL18 08HMPA09


05CHPL10 05CHPL78 05CHPL27 05CHPL62 05CHPL60 05CHPL29 05CHPL33 05CHPL95 05CHPL106 bis 07HMPA93A 05CHPL101 bis 05CHPL88 07HMPA88A 07HMPA87F 07HMPA87D 05CHPL82 05CHPL105 05CHPL106 05CHPL03

ESXB048 05CHPL02 ESXB049 ESXB050 ESXB051 ESXB052 ESXB055 ESXB056 ESXB057 ESXB058

05CHPL39 05CHPL57 05CHPL65 05CHPL59 07HMPA54 08HMPA06 08HMPA07 08HMPA08

ESXB059 08HMPA10

ESXB060 C. malonaticus ESXB004 ESXB008 ESXB014 ESXB042 ESXB054

08HMPA11 05CHPL40 05CHPL46 05CHPL53 07HMPA87A 08HMPA01

Clinical (type strain ATCC 29544); child's throat Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Collection strain PIF Environment PIF Clinical; child cerebrospinal fluid (French neonatal infection 2004) PIF Environment Environment PIF (NCTC 8155) Collection strain Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Environment Collection strain (CDC 4–85) Collection strain (CDC 28-83) Environment Environment Collection strain Collection strain Environment Environment Environment Clinical; Child cerebrospinal fluid (French neonatal infection 2004) Clinical; child stool (French neonatal infection 2004) PIF Environment Environment Environment Environment Clinical (type strain DSMZ 18702); breast abscess



0.33 0.33 0.35 0.31 0.34 0.31 0.27 0.32 0.33 0.28 0.29 0.26 0.33 0.32 0.34 0.38 0.35 0.35 0.21 0.25 0.29 0.32

0.59 0.66 0.64 0.67 0.71 0.66 0.68 0.65 0.71 0.58 0.69 0.65 0.68 0.63 0.64 0.61 0.53 0.65 0.54 0.49 0.64 0.63

0.32 0.36 0.29 0.34 0.36 0.31 0.32 0.33 0.30 0.31 0.20 0.32 0.32 0.33 0.28 0.35 0.32 0.36 0.30

0.64 0.67 0.58 0.63 0.66 0.68 0.64 0.63 0.59 0.64 0.38 0.61 0.62 0.66 0.53 0.66 0.65 0.68 0.63



0.34 0.33 0.28 0.35 0.33 0.30 0.30 0.34

0.64 0.65 0.51 0.80 0.68 0.65 0.63 0.64



0.29 0.31 0.32 0.31 0.35 0.29

0.62 0.66 0.63 0.65 0.63 0.60



Growth rates (h− 1) 25 °C 37 °C

C. muytjensii

25 °C 37 °C C. sakazakii

PFGE type

ESXB023 05CHPL63 ESXB032 05CHPL61 ESXB036 05CHPL67

C. dublinensis ESXB035 05CHPL64 ESXB053 08HMPA03 C. turicensis

ESXB060 08HMPA02

Food Collection strain Type strain (ATCC 51329) Rodent food (collection strain) Type strain (DSMZ 18705) Clinical (type strain DSMZ 18703); neonatal meningitis

0.33 0.35 0.35

0.60 0.60 0.63







malonaticus formed another group. There were also deviations from this pattern as strain 08HMPA03 (DSMZ 18705), identified as C. dublinensis according to ribotyping and phenotypic tests, clustered with the C. muytjensii group. However, according to the ribotyping results, strains that were phenotypically identified as C. dublinensis or C. muytjensii were more closely related to each other, whereas the C. malonaticus/C. turicensis group demonstrated closer similarity to C. sakazakii (Fig. 2). Moreover, strain 05CHPL65, identified as C. sakazakii according to phenotype, clustered with the mixed group according to 16S rRNA gene sequence. Ribotyping corroborated these findings as this strain branched from the same point as 08HMPA01, another strain identified as C. malonaticus. Irrespective of grouping it is important to note that, according to 16S rRNA gene sequence, the two most distal strains in our collection (05CHPL64 and 05CHPL50) still shared greater than 97% sequence identity. Another interesting observation from our phylogenetic tree was that other closely related species within the Enterobacteriacae, such as Escherichia coli displayed greater sequence similarity to Cronobacter spp. than did strains representative of Enterobacter cloacae (Fig. 3). For example, reference strain C. sakazakii ATCC 29544 had 96% sequence similarity with E. coli ATCC 29522, while only 94% similarity with the E. cloacae ATCC 13047T. Due to the limited resolution of the 16S rRNA gene at the species level, discrepancies in sequencing data are not uncommon (Konstantinidis and Tiedje, 2007). Other methods may be better suited for phylogenetic studies of Cronobacter. Recently, greater discretion for the speciation of Cronobacter spp. has been demonstrated using multilocus sequence analysis (MLST) (Baldwin et al. 2009; Kuhnert et al., 2009). In particular, sequencing of recN alone appears to provide a higher degree of utility over the 16S rRNA gene (El-Sharoud et al., 2009). In our study, 16S rRNA gene sequencing revealed that strains grouped in any of the three clusters outside of the C. sakazakii group had at least 98% sequence similarity with one another, thus illustrating the difficulty in accurate speciation using this method exclusively. However, the relatedness of individual strains within these genotype clusters can be further elucidated by conducting the appropriate regimen of biochemical tests. Farmer et al. (1980) described 15 biogroups for E. sakazakii based on 10 defining biochemical tests. Iversen et al. (2006) later demonstrated that these specific biogroups could be placed within specific genotype clusters based on partial 16S rRNA gene sequencing. It should also be noted that no relationship could be ascertained from the results in our study or previous work (Iversen et al., 2006) with respect to sample origin as strains from PIF, the processing environment or clinical samples did not form subclusters irrespective of the typing method utilized. Information regarding strain diversity, as well as the dynamics of the growth of these pathogens is essential for the mitigation of risk since different bacterial species may display different behaviours. Therefore, we determined the growth rates for each of our strains in BHI broth at 25 °C and 37 °C (Table 1). These temperatures were chosen in order to mimic conditions after reconstitution of PIF in feeding bottles at ambient

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Fig. 2. Automated ribotyping analysis of a collection of Cronobacter strains. Dendrogram was generated using a UPGMA algorithm and a DICE coefficient with optimization of 1% and a position tolerance of 1.5%. Species designations are given according to biochemical profiles. *05CHPL02 was identified as C. sakazakii by biochemical tests but grouped outside species cluster. **05CHPL53 was identified as C. malonaticus by biochemical tests but grouped with C. sakazakii.


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Fig. 3. Phylogenetic tree for a collection of Cronobacter strains and other closely related Enterobacteraceae based on 16S rRNA gene sequencing. A Nearest Neighbour algorithm was implemented with a Jukes–Cantor correction and pair-wise gap removal. Bootstrap values were calculated using 2000 tree iterations.

temperature or after warming, respectively. Growth rates ranged from 0.20 to 0.38/h at 25 °C and from 0.38 to 0.80/h at 37 °C (Table 1). Analysis of variance (ANOVA, single factor) revealed that although there

were significant differences (P b 0.05) in growth rates among individual strains, there was no significant difference (P N 0.05) in mean growth rate between the origin of the strain or between species (Table 1, Fig. 4).

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Table 2 GenBank accession numbers for the 16S rRNA gene. Isolate

GenBank accession #


GenBank accession #

07HMPA41A 07HMPA87A 07HMPA87B 07HMPA87D 07HMPA87F 07HMPA88A 07HMPA93A 07HMPA54 08HMPA01 08HMPA02 08HMPA03 08HMPA06 08HMPA07 08HMPA08 08HMPA09 08HMPA10 08HMPA11 05CHPL01 05CHPL02 05CHPL03 05CHPL10 05CHPL18 05CHPL27 05CHPL29 05CHPL33 05CHPL36 05CHPL37 05CHPL38 05CHPL39 05CHPL40 05CHPL41 05CHPL43

GU122166 GU122167 GU122168 GU122169 GU122170 GU122171 GU122172 GU122173 GU122174 GU122175 GU122176 GU122177 GU122178 GU122179 GU122180 GU122181 GU122182 GU122183 GU122184 GU122185 GU122186 GU122187 GU122188 GU122189 GU122190 GU122191 GU122192 GU122193 GU122194 GU122195 GU122196 GU122197

05CHPL45 05CHPL46 05CHPL47 05CHPL48 05CHPL50 05CHPL51 05CHPL52 05CHPL53 05CHPL54 05CHPL56 05CHPL57 05CHPL59 05CHPL60 05CHPL61 05CHPL62 05CHPL63 05CHPL64 05CHPL65 05CHPL66 05CHPL67 05CHPL78 05CHPL82 05CHPL88 05CHPL93 05CHPL94 05CHPL95 05CHPL97 05CHPL99 05CHPL105 05CHPL106 05CHPL101-bis 05CHPL106-bis

GU122198 GU122199 GU122200 GU122201 GU122202 GU122203 GU122204 GU122205 GU122206 GU122207 GU122208 GU122209 GU122210 GU122211 GU122212 GU122213 GU122214 GU122215 GU122216 GU122217 GU122218 GU122219 GU122220 GU122221 GU122222 GU122223 GU122224 GU122225 GU122226 GU122227 GU122228 GU122229

Moreover, no links between strain origin, genotype or phenotype (growth rate) could be established. Despite the high level of genetic heterogeneity between strains there was a high level of homogeneity in growth behaviour in BHI between both species and strain origin. Low intraspecific growth variability in broth at optimal or suboptimal temperature has also been observed for several other bacteria, including, Listeria monocytogenes, Escherichia coli, Clostridium perfringens and Bacillus cereus (Membré et al., 2005). In some studies, E. sakazakii intraspecific growth variability has been estimated, but for fewer strains (Nazarowec-White and Farber, 1997b; Lenati et al., 2008). In contrast to our results, Cooney et al. (2009) observed significant differences in growth rates at 37 °C in reconstituted PIF for Cronobacter species, but this trend may have been biased by the low number of strains used in the study. Also, Lenati et al. (2008), using nine E. sakazakii isolates, observed that the average generation time of clinical strains was longer at 37 °C, as compared to environmental and food isolates. Contrary to this, Nazarowec-White and Farber (1997b) did not observe significant differences between generation times for clinical or food isolates at 23 °C in infant formula. Certainly, growth rates will be impacted by temperature and choice of medium as Iversen et al. (2004) observed a broader doubling time at 37 °C for six strains of E. sakazakii using BHI rather than PIF. The relationship between growth rates in Cronobacter species, genotype or origin could be better evaluated by examining a much broader and diverse collection of isolates. The mean generation time for our isolates grown in BHI at 37 °C was approximately 1.1 h, which is quite similar to results found in other studies examining E. sakazakii in rich media, such as BHI or PIF at 37 °C (Iversen et al., 2004; Kandhai et al., 2006; Lenati et al., 2008; Cooney et al., 2009). At 25 °C, we obtained a mean generation time of 2.1 h. Previous work conducted using infant formula at similar temperatures demonstrates the variability in mean generation times (Nazarowec-White and Farber, 1997b; Iversen et al., 2004). Although no correlation between isolate

Fig. 4. Comparison of the mean growth rate (μ) for Cronobacter strains in BHI at 25 °C ( ) and 37 °C ( ), according to A.) species or B.) origin (n = number of tested strains). Growth rates of individual strains are presented in Table 1.

origin and growth rates could be drawn from our results we acknowledge that our collection was dominated with environmental strains. The inclusion of a greater number of clinical isolates would be required to provide a better assessment of possible relationships. Another important growth parameter is the lag phase duration. Kandhai et al. (2006) examined effects of pre-culturing conditions on lag times of E. sakazakii in PIF. In order to elucidate the true behaviour of foodborne pathogens within food samples, future studies should be performed on the lag phase distribution among the isolates using stressed cells in relevant media such as reconstituted infant formula since the microbiological quality of PIF is in question (Muytjens et al., 1988). Extreme temperature conditions, closer to the growth limits, are also likely to reveal differences between strains for bacterial growth (Barbosa et al., 1994; Lebert et al., 1998; Bergis et al., 2004; Rosset et al., 2007). Using a combination of biochemical and molecular techniques, we have characterized a collection of isolates previously identified as E. sakazakii. Results obtained here allowed for their designation into species within the new Cronobacter genus and the identification of unique strains. However, relationships between strain origins or growth dynamics were inconclusive. In the future, expanding this collection to include a greater number of strains from a diverse array of ecological niches, including more clinical isolates, as well as the evaluation of growth kinetics using realistic conditions will help us understand the potential risk of this emerging foodborne pathogen.


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