Front. Microbiol. Frontiers in Microbiology Front. Microbiol. 1664-302X Frontiers Media S.A. 10.3389/fmicb.2013.00256 Microbiology Original Research Article Complete genome sequence and phenotype microarray analysis of Cronobacter sakazakii SP291: a persistent isolate cultured from a powdered infant formula production facility Yan Qiongqiong 1 Power Karen A. 1 Cooney Shane 1 Fox Edward 1 Gopinath Gopal R. 2 Grim Christopher J. 2 Tall Ben D. 2 McCusker Matthew P. 1 Fanning Séamus 1 * 1UCD Centre for Food Safety, WHO Collaborating Centre for Research, Reference and Training on Cronobacter, School of Public Health, Physiotherapy and Population Science, University College Dublin Dublin, Ireland 2Division of Virulence Assessment, OARSA, Centre for Food Safety and Applied Nutrition, MOD 1 Facility, Virulence Mechanisms Branch (HFS-025), U.S. Food and Drug Administration Laurel, MD, USA

Edited by: Michael Gänzle, Alberta Veterinary Research Institute, Canada

Reviewed by: Stephen Forsythe, Nottingham Trent University, UK; Lifang Ruan, State Key Lab of Agricultural Microbiology, China

*Correspondence: Séamus Fanning, UCD Centre for Food Safety, UCD Centre for Molecular Innovation and Drug Discovery (Science Centre South), Room S1.04, University College Dublin, Belfield, Dublin 4, Ireland e-mail: sfanning@ucd.ie

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology.

 02 09 2013 2013 4 256 22 03 2013 13 08 2013 Copyright © 2013 Yan, Power, Cooney, Fox, Gopinath, Grim, Tall, McCusker and Fanning. 2013

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Outbreaks of human infection linked to the powdered infant formula (PIF) food chain and associated with the bacterium Cronobacter, are of concern to public health. These bacteria are regarded as opportunistic pathogens linked to life-threatening infections predominantly in neonates, with an under developed immune system. Monitoring the microbiological ecology of PIF production sites is an important step in attempting to limit the risk of contamination in the finished food product. Cronobacter species, like other microorganisms can adapt to the production environment. These organisms are known for their desiccation tolerance, a phenotype that can aid their survival in the production site and PIF itself. In evaluating the genome data currently available for Cronobacter species, no sequence information has been published describing a Cronobacter sakazakii isolate found to persist in a PIF production facility. Here we report on the complete genome sequence of one such isolate, Cronobacter sakazakii SP291 along with its phenotypic characteristics. The genome of C. sakazakii SP291 consists of a 4.3-Mb chromosome (56.9% GC) and three plasmids, denoted as pSP291-1, [118.1-kb (57.2% GC)], pSP291-2, [52.1-kb (49.2% GC)], and pSP291-3, [4.4-kb (54.0% GC)]. When C. sakazakii SP291 was compared to the reference C. sakazakii ATCC BAA-894, which is also of PIF origin, the annotated genome data identified two interesting functional categories, comprising of genes related to the bacterial stress response and resistance to antimicrobial and toxic compounds. Using a phenotypic microarray (PM), we provided a full metabolic profile comparing C. sakazakii SP291 and the previously sequenced C. sakazakii ATCC BAA-894. These data extend our understanding of the genome of this important neonatal pathogen and provides further insights into the genotypes associated with features that can contribute to its persistence in the PIF environment.

 complete genome plasmid Cronobacter sakazakii stress response antibiotic resistance toxic compounds Introduction

Cronobacter species (formerly Enterobacter sakazakii) is an opportunistic pathogen of the Enterobacteriaceae family. This organism was originally designated as E. sakazakii in 1980 (Farmer et al., 1980). Based on its recently revised taxonomy, the genus was renamed as Cronobacter in 2007 and now consists of seven species, C. sakazakii, C. malonaticus, C. turicensis, C. muytjensii, C. dublinensis (including three subspecies, dublinensis, lausannensis, and lactaridi), C. universalis and C. condimenti (Iversen et al., 2004, 2007, 2008; Joseph et al., 2011). Infections caused by Cronobacter can present as necrotizing enterocolitis, bacteremia and meningitis, with long term complications for those that survive, including delayed neurological development, hydrocephalus and permanent neurological damage. Life-threatening infections have been reported in neonates (of less than 28 days) (Bar-Oz et al., 2001; Gurtler et al., 2005; Mullane et al., 2007), as well as older infants, with lethality rates ranging between 40 and 80% (Bowen and Braden, 2006; Friedemann, 2009), and more recently in immune-compromised adults, mainly the elderly (Gosney et al., 2006; See et al., 2007; Hunter et al., 2008; Tsai et al., 2013).

Cronobacter can be isolated from a wide range of foods and environments (Baumgartner et al., 2009; Chap et al., 2009; El-Sharoud et al., 2009; Jaradat et al., 2009; Schmid et al., 2009). Specifically, contaminated powdered infant formula (PIF) has been epidemiologically linked with many of the neonatal and infant infections (Himelright et al., 2002; Bowen and Braden, 2006; Mange et al., 2006). Previous studies reported the isolation of Cronobacter from PIF, and the PIF production environment (Drudy et al., 2006; Mullane et al., 2008a,b), suggesting that this bacterium has the capacity to adapt to, survive and persist under desiccated environmental conditions. Comparison of environmental and clinical Cronobacter isolates, indicated that the desiccation tolerance exhibited might play a role in the persistence of Cronobacter in PIF and its associated low-moisture ingredients (Walsh et al., 2011; Beuchat et al., 2013). Stress response factors identified previously in Cronobacter, which include heat-shock, cold-stresses, survival in dry conditions, water activity (aw), and pH may contribute to this phenotype (Dancer et al., 2009a,b; Carranza et al., 2010; Chang et al., 2010; Arku et al., 2011). Genome sequencing efforts of Cronobacter species commenced in 2010. To date, 16 genomes are currently available, of which three, C. sakazakii ATCC BAA-894, C. sakazakii ES15 and C. turicensis z3032, are complete (Kucerova et al., 2010; Stephan et al., 2011; Joseph et al., 2012; Shin et al., 2012; Grim et al., 2013).

Following on-going surveillance of a PIF production facility in our laboratory, an interesting isolate C. sakazakii SP291 was identified which exhibited a thermo-adapted phenotype when compared with other Cronobacter and Salmonella species tested under laboratory conditions (Cooney, 2012). In an effort to better understand C. sakazakii SP291, its genome was completely sequenced and compared to that of a PIF isolate C. sakazakii ATCC BAA-894, a whole grain isolate C. sakazakii ES15, a clinical isolate C. turicensis z3032 and other selected draft genomes. Additionally, we interrogated the phenome of C. sakazakii SP291, to determine the functionality of strain-specific genotypic traits that may contribute to its adaption capacity in a PIF production environment.

 Materials and methods Bacterial isolates studied and their culture conditions

Seventeen Cronobacter isolates used in this study are listed in Table 1. Cronobacter sakazakii SP291 was assigned according to the classic rpoB method described previously (Stoop et al., 2009; Lehner et al., 2012). The isolate was cultured routinely in an Isotherm® Forced Convection Laboratory Incubator (Esco GB Ltd., Downton, UK) at 37°C on Trypticase Soy Agar (Oxoid Limited, Hampshire, UK) and stored at −80°C on cryo-beads (Technical Service Consultants Ltd., Lancashire, UK).

Cronobacter species, the strain identifier, source, country of origin, and accession numbers.

Species Strain identifiera Serogroupb Source Country of origin Accession number (GeneBank)
Cronobacter sakazakii ATCC BAA-894 Csak O1 PIFg USA CP000783-CP00785
Cronobacter sakazakii SP291 Csak O2 PIF manufacturing environment Ireland CP004091-CP004094
Cronobacter sakazakii ES15 NDf Whole grain Korea CP003312
Cronobacter sakazakii E899 Csak O2 Clinical USA AFMO01000001-AFMO01000385
Cronobacter sakazakii 680 NDf Clinical USA CALG01000001-CALG01000201
Cronobacter sakazakii 696 NDf Clinical France CALF01000001-CALF01000569
Cronobacter sakazakii 701 NDf Clinical France CALE01000001-CALE01000768
Cronobacter sakazakii ES35 Csak O1 Clinical Israel AJLC01000001-AJLC01000183
Cronobacter sakazakii 2151 Csak O2 Clinical, cerebrospinal fluid USA AJKT01000001-AJKT01000060
Cronobacter sakazakii ES713 Csak O2 PIF USA AJLB01000001-AJLB01000156
Cronobacter sakazakii E764 Csak O4 Clinical Czech Republic AJLA01000001-AJLA01000032
Cronobacter malonaticus LMG 23826 Cmal O2 Human, breast abscess USA CALC01000001-CALC01000171
Cronobacter turicensis z3032c Ctur O1 Neonate Switzerland FN543093-FN543096
Cronobacter dublinensis CFS 237d Cdub O1 PIF Ireland CAKZ01000001-CAKZ01000221
Cronobacter mutjensii ATCC 51329 CmuyO2 Unknown Unknown AJKU01000001-AJKU01000072
Cronobacter universalis NCTC 9529 Cuni O1 Water UK CAKX01000001-CAKX01000231
Cronobacter condimenti 1330e NDf Spiced meat Slovakia CAKW01000001-CAKW01000155

Strain information was selected from publications (Kucerova et al., 2010; Chen et al., 2011; Stephan et al., 2011; Joseph et al., 2012; Shin et al., 2012; Grim et al., 2013).

Serogroup designations were identified using primers described by Mullane et al. (2008a,b) and Jarvis et al. (2011, 2013).

Cronobacter turicensis species type strain LMG 23827.

Cronobacter dublinensis species type strain LMG 23823.

Cronobacter condimenti species type strain LMG 26250.

Not determined.

Isolate cultured from PIF, of which the PFGE pattern matched the blood sample of an infected neotate in a neonatal intensive care unit (NICU) in Tennessee in 2001. The infection cause the death of the neotate born 20 days previously.

 DNA sequencing, annotation, and comparative genomic analysis

Total genomic DNA was purified using a DNeasy Blood and Tissue Kit (QIAGEN, Hilden, Germany) following the manufacturer's instructions. Concentrations were measured using a Nanodrop® (ND 1000) spectrophotometer (Labtech International Ltd., Luton, UK). Purified DNA was maintained at −20°C until required. The whole genome sequencing and assembly methodology is described elsewhere (Power et al., 2013). The complete chromosome and plasmid sequences were uploaded to the RAST (Rapid Annotation using Subsystem Technology) (Aziz et al., 2008) annotation server in a FASTA file format. The RAST server automatically identifies protein-encoding, tRNA and rRNA genes, assigns their functions, predicts the presence of subsystems in the genome, and reconstructs the metabolic network (Aziz et al., 2008). Genome to genome comparative analysis was performed in the SEED viewer as previously reported (Overbeek et al., 2005; Grim et al., 2013). Three complete genomes of C. sakazakii ATCC BAA-894 (Accession number CP000783-CP00785), C. sakazakii ES15 (Accession number CP003312) and C. turicensis z3032 (Accession number FN543093-FN543096) were uploaded and annotated in RAST, and used as reference sequences. Most probable insertion or deletion genome regions of C. sakazakii SP291 were identified as previously reported (Grim et al., 2013). In addition, nitrogen metabolism genes, stress-coding genes, as well as antibiotic and toxic compound resistant genes were determined based on significant identity alignments using BLAST. The genome sequence of C. sakazakii SP291 was deposited in GenBank under the accession numbers CP004091-CP004094. The accession numbers for other genome sequences studied were included in Table 1.

 Phenotype microarray analysis

Phenotype microarray (PM) analysis was performed on C. sakazakii ATCC BAA-894 and C. sakazakii SP291 using the OmniLog® automated incubator/reader (Biolog Inc., Hayward, USA) following manufacturer's instruction. All 20 plates (PM-1 through PM-20) inoculated with bacterial cell suspensions, were incubated at 37°C and cell respiration was measured every 15 min for 48 h. The tetrazolium redox dye is reduced when bacteria respire, which provides both amplification and quantitation of the phenotype. Analysis was carried out using OmniLog® phenotype microarray software v1.2 to determine the phenotypic differences. Negative control wells, which contained the inoculated Omnilog™ growth medium, but without any substrate, were measured to normalize differences in inocula and redox dye oxidation between samples. The respiration profiles for both strains were compared using PM's integration function software and a significant divergent phenotype was identified when a difference in Omnilog™ units of 20,000 ± 1800 or greater between the two strains was obtained.

 Results and discussion <italic>Cronobacter sakazakii</italic> SP291 genome

The complete genome sequence of C. sakazakii SP291 is composed of a single, circular chromosome, 4.34 Mb in length with an average GC content of 56.9% along with three plasmids (denoted as pSP291-1, 118.136 kb, 57.2% GC; pSP291-2, 52.134 kb, 49.2% GC and pSP291-3, 4.422 kb, 54.0% GC) (Accession number CP004091-CP004094). The general features of the genome are presented in Table 2. A total of 4129 genes were identified on the chromosome, including 82 tRNA and 22 rRNA genes. The protein coding sequence (CDS) represents 86.3% of the genome and is organized into 4025 CDS, with an average length of 931 nucleic acids (Figure A1). From the annotation of the three plasmids, it was determined that 116 genes cover 87.1% of pSP291-1, 74 genes cover 77.2% of pSP291-2 and 7 genes were located on pSP291-3 and accounts for 48.6% of this structure.

General features of the C. sakazakii SP291 genome.

Feature Chromosome Plasmids
pSP291-1 pSP291-2 pSP291-3
Size (bp) 4,344,092 118,136 52,134 4,422
Predicted CDS 4025 116 74 7
GC content (%) 56.9 57.2 49.2 54.0
Coding regions (%) 86.3 87.1 77.2 48.6
Average CDS length (bp) 931 887 544 307
tRNA 82 nil nil nil
rRNA 22 nil nil nil
Comparative genomic analysis of <italic>C. sakazakii</italic> SP291 with three other completed <italic>Cronobacter</italic> genomes

Cronobacter sakazakii SP291 and three other completed genomes: C. sakazakii ATCC BAA-894, C. sakazakii ES15 and C. turicensis z3032 were compared (Figure 1). For the purposes of this comparison, the C. sakazakii ATCC BAA-894 genome was used as the reference. Five genomic regions (denoted as GR-1 through −5, in Figure 1A) were identified and these were present in the other genomes but missing in C. sakazakii SP291 (Table S1). These GRs are discussed in detail below.

Genomic regions of C. sakazakii SP291 compared to three completed genomes consists of C. sakazakii ATCC BAA 894, C. sakazakii ES15, and C. turicensis z3032. (A) Regions absent in the genome of C. sakazakii SP291 compared to the other three genomes. Reference genome: C. sakazakii ATCC BAA-894; Outer circle: C. sakazakii ES15; Middle circle: C. sakazakii SP291; Inner circle: C. turicensis z3032, see also Table S1. (B) Regions present in the genome of C. sakazakii SP291 compared to the other three genomes. Reference genome: C. sakazakii SP291; Outer circle: C. sakazakii ATCC BAA-894; Middle circle: C. sakazakii ES15; Inner circle: C. turicensis z3032, see also Table S2.

Several unique prophages or phage-like elements of C. sakazakii ATCC BAA-894 were noted in GR-1 (genome positions 578,739…601,816), GR-3 (genome positions 2,245,990…2,272,660) and GR-4 (genome positions 2,962,630…3,022,134). Three specific genes were observed in GR-1, which included the DNA-methyltransferase subunit M and the S subunit of a type I restriction-modification system, along with a zinc binding domain/DNA primase, which is a phage P4-associated/replicative helicase denoted as RepA. A lambda phage portal protein, a large subunit of a terminase enzyme, along with some hypothetical proteins were noted in GR-3. In GR-4, a 1478 bp uncharacterized translocase gene required for O-antigen conversion and two-recombination genes, part of the bacteriophage ninR region, and denoted as ninB and ninG were identified. These annotations confirmed those previous reported (Kucerova et al., 2010). Interstingly, a putative bactoprenol glucosyl transferase was identified in C. sakazakii ATCC BAA-894, and shared with C. sakazakii ES15 and C. turicensis z3032, but not C. sakazakii SP291. Regulatory protein CII along with a phage Kil protein were annotated in C. sakazakii ATCC BAA-894 but not C. sakazakii SP291. Although protein CII was absent in C. turicensis z3032, the Kil protein was present (Stephan et al., 2011). A recently sequenced phage denoted as, phiES15, contained cII and kil (Lee et al., 2012). Unique transposon genes were noted in GR-2 (genome positions 1,722,846…1,742,692) and GR-5 (genome positions 4,196,138…4,222,295). In GR-2, a large part of the region containing tellurium resistance-encoding genes, including terX, terW, terA, terB, terC, and terD, were identified, a feature reported previously (Kucerova et al., 2010; Joseph et al., 2012; Grim et al., 2013). GR-5 contained heavy metal efflux and resistance genes, which consists of cusS, cusR, cusC, cusF, czcB, czcA, cusA, copG, pcoS, pcoB, and pcoA (Kucerova et al., 2010; Joseph et al., 2012). Further detailed information related to the corresponding phenotypes is outlined below (see also Table S1).

Genes unique to C. sakazakii SP291 were also noted and these were used as a reference to interrogate the genomes of the other strains. Six genomic regions (Figure 1B, denoted as GR-a through -f, Table S2) were identified as being unique to C. sakazakii SP291. GR-a (genome regions 319,823…350,809), GR-d (genome regions 1,643,874…165,774) and GR-e (genome regions 2,471,984…2,499,614) contained a set of phage- and phage-related proteins along with some hypothetical proteins. A phage regulatory CII-like protein was identified in C. sakazakii SP291 and mapped within GR-a, which also matched a similar homolog observed in C. turicensis z3032. A holin protein, which controls the length of an infective cycle for bacteriophage (Wang et al., 2000), together with membrane proteins related to metalloendopeptidases were present in C. sakazakii SP291 alone, being located in GR-e. In GR-b (genome regions 618,890…638,586), a YkfI toxin-encoding protein along a YfjZ-antitoxin encoding protein (the corresponding antitoxin to YpjF) were identified and unique to C. sakazakii SP291. This toxin-antitoxin protein pair was also reported in E. coli previously and was shown to regulate cell death through the disruption of essential cellular processes (Brown and Shaw, 2003). It has been proposed by Lewis (2000) that, under some circumstances, it may be evolutionarily advantageous for some cells in a population to undergo programmed cell death in order to provide nutrients for the remainder. Toxin-antitoxin pairs were noted in a previous study as most Cronobacter genomes contain a large number of them, which might be conserved, shared, or unique (Grim et al., 2013). GR-c (genome regions 891,557…912,700) contains seven interesting genes, which includes an uncharacterized protein YeeT, a NgrB protein, an ATP-dependent Clp protease, an ATP-binding subunit ClpA, a small HspC2 heat shock protein, a galactoside O-acetyltransferase-encoding gene and an anti-restriction protein KlcA which have been reported as a component part of a type I DNA restriction system (Serfiotis-Mitsa et al., 2010). A helicase protein, a glycerol dehydrogenase enzyme-encoding gene, and a DNA-cytosine methyltransferase were identified within GR-f (genome regions 3,363,441…3,392,072). Of note, a type I restriction-modification system, specificity the S-subunit-like gene, was identified in C. sakazakii SP291, a feature which was noted earlier in C. sakazakii ATCC BAA-894 (Kucerova et al., 2010; Joseph et al., 2012).

 Comparative genomic analysis of <italic>C. sakazakii</italic> SP291 and selected available genomes within this genus

Two earlier studies described the core genome of Cronobacter (Joseph et al., 2012; Grim et al., 2013). The availability of C. sakazakii SP291 genome has provided an opportunity to re-evaluate the content of the Cronobacter core gemome, comparing it to other currently available genome sequences within the genus. Thus, a comparison between C. sakazakii SP291 and 16 other Cronobacer genomes (Table 1) was performed in SEED viewer server.

Within the 11 Cronobacter sakazakii isolates compared, 57 annotated genes were present in C. sakazakii SP291, but absent in all other genomes, including 41 hypothetical proteins, 12 phage- and prophage-related genes/proteins and four other genes/proteins (Table S3). Among all seven Cronobacter species, there were 154 annotated genes/proteins absent in other species, including 122 hypothetical proteins, 4 phage- and prophage-related genes/proteins and 28 unique genes/proteins (Table S4). Interestingly, a conserved domain protein was identified that was unique to C. sakazakii SP291, which is associated with retron-type reverse transcriptase. Fifteen genes were shared with other species by C. sakazakii SP291, but were absent in all the C. sakazakii genomes compared to date, and these consisted of a retron-type RNA-directed DNA polymerase, a holin protein which controls the timing of bacteriophage infections as mentioned earlier, a topoisomerase IA-encoding protein, and 12 phage- and prophage-related proteins. There were 31 proteins, which are only shared with some of the C. sakazakii genomes by C. sakazakii SP291 and which were absent among the other six species. These included a sodium-dependent phosphate transporter protein, a RelE antibacterial toxin protein, a RelB protein (antitoxin to RelE), a probable poly (beta-D-mannuronate) O-acetylase protein, two putative periplasmic proteins, a possible secretory protein, a GTPase protein, denoted as NgrB, a mobile element protein, a galactoside O-acetyltransferase protein, a mannose-6-phosphate isomerase, class I protein, a different locus type I restriction-modification system, specificity the S subunit-like protein, a predicted transcriptional regulator COGs COG2378, permeases of the major facilitator superfamily, a superfamily II DNA/RNA helicases, SNF2 family, a DNA modification methylase, an IS1 transposase OrfA protein, a probable tonB-dependent receptor yncD precursor, a putative ORF-4 protein, a putative ORF (located using Glimmer/Genemark), seven beta-fimbriae probable major subunits, and four phage related proteins.

 Annotated plasmids contained in <italic>C. sakazakii</italic> SP291

Cronobacter sakazakii SP291 contains three plasmids, including pSP291-1, 118,136 bp (57.2% GC), pSP291-2, 52,134 bp (49.2%) and pSP291-3, 4,422 bp (54.0% GC). The predicted CDS of pSP291-1 was found to be 116, with the average length of 887 bp, while pSP291-2 has 74 CDS with an average length of 544 bp, and pSP291-3 has seven CDS and with the average length of 307 bp (Table 2). Comparision of all three plasmids with five previously published plasmid sequences (including pESA2 and pESA3 of C. sakazakii ATCC BAA-894; along with pCTU1, pCTU2, and pCTU3 of C. turicensis z3032) indicated two closely related plasmid groups. Plasmid group 1, contains pSP291-1, pESA3, and pCTU1, while plasmid group 2, consists of pSP291-2 and pCTU3 (Figures A2, A3, and Table S5).

Several common genes were identified in plasmid group 1, These consisted of a complete ABC transporter (which could function to transport iron; vitamin B12; siderophores and hemin), including the ATP-binding component, the periplasmic substrate-binding module and the permease element. These genes were identified in all three plasmids. An aerobactin siderophore receptor (the IutA/TonB-dependent siderophore receptor) was shared between the three plasmids, while a Cronobacter plasminogen activator (cpa) homolog has only been mapped to pESA3 and pSP291-1, but not pCTU1, which is in agreement with the results reported by Franco et al. (2011) and Grim et al. (2012) (Figure A2). Three arsenical resistance genes were identified on all three plasmids along with pCTU3. Genes corresponding to commonly shared proteins on all three plasmids included a C-terminal helicase protein, a HipA protein previously reported to be required for growth arrest and multi-drug resistance in Escherichia coli (Correia et al., 2006), a hypothetical-encoding gene ycgF reported to be a direct anti-repressor which acts in the blue-light response of E. coli (Tschowri et al., 2009), a starvation sensing protein RspA, a magnesium transporting P-type 1 ATPase protein, transcriptional regulators, including members of ArsR family, GntR family (Kucerova et al., 2010; Joseph et al., 2012), LysR family and TetR-family, a MFS superfamily transporter, a Trk system encoding the potassium uptake protein TrkG, and an uncharacterized protein ImpD. A two-component response regulator protein, a two-component system sensor protein, three uncharacterized proteins ImpB, ImpC, and ImpJ/VasE, a glutathione S-transferase protein, a membrane protein, suppressor for copper-sensitivity ScsB, a hypothetical ABC transport system, periplasmic component, a RND efflux transporter, a suppression of copper sensitivity: putative copper binding protein ScsA were shared between pSP291-1 and pESA3, but not pCTU1, which confirmed the findings from previous studies (Kucerova et al., 2010; Joseph et al., 2012). In plasmid group 2, 15 heavy metal (copper, cobalt, zinc, cadmium, lead, and mercury) resistance genes were shared by both plasmids (Figure A3). An osmosensitive K+ channel histidine kinase protein (KdpD), and a virulence-associated protein vagC were also present in both plasmids. PCR analysis confirmed the presence of a pCTU3 IncH1-like origin of replication gene, repA in C. sakazakii SP291 (data not shown).

Interestingly, pSP291-1 contained two unique proteins, a histone acetyltransferase HPA2 and related acetyltransferases protein, along with an uncharacterized protein ImpH/VasB. Six specific proteins were found in pSP291-2, which included a putative glutathione S-transferase protein, a LysR family transcriptional regulator, a putative phage-associated acyl carrier protein, a S-adenosylmethionine: tRNA ribosyltransferase-isomerase protein, permeases of the major facilitator superfamily and an abortive infection protein. Various pSP291-3 proteins including mobilization proteins MobB, MobC, MobD, and DNA relaxase MbeA, which were not shared with any of the other plasmids, were also identified.

 Comparative phenotypic profiling of <italic>C. sakazakii</italic> ATCC BAA-894 and SP291

The phenotypic microarray (PM) platform was used previously to support the re-classification of this bacterial genus (Iversen et al., 2008). By comparing the phenotypes of C. sakazakii ATCC BAA-894 and C. sakazakii SP291 expressed across the complete array, interesting differences were observed and these were subsequently assessed in light of comparisons made at the genome level despite of the same PIF orgin. General differences, noted in the phenotypes between the two strains were described in the form of a heat map shown in Figure 2 (the corresponding numerical data is shown in Table S6). Phenotypic differences based on the bacteria's ability to utilize carbon, nitrogen, phosphorous and sulfur sources, as well as other nutrient supplements were noted. Furthermore, growth responses to osmolytes and different pH growth environments, as measured by the array were also observed for both strains. Antibiotic resistance patterns and the ability to respire in the presence of toxic compounds differed.

(A–D) Heat map of phenotype microarray (PM). Left lane, C. sakazakii SP291; Right lane, C. sakazakii ATCC BAA-894.

 Carbon, nitrogen, phosphorous, and sulfur, other nutrient supplement metabolite utilization

Bacteria require a sufficient supply of various biomolecules to support their metabolic activity. In natural environments, where these bacteria are often found, it is to be expected that only limited amounts of these nutrients may be available. To support efficient adaptation and to enable growth in these conditions, bacteria will evolve redundant metabolic systems to support the utilization of a broad range of different substrates, with varying efficiencies. The PM array data gives an insight into how these features differ, between C. sakazakii SP291 and C. sakazakii ATCC BAA-894.

A number of phenotypic differences based on their ability to utilize a range of carbon sources were noted (Figure 2A and Table S6). When compared with C. sakazakii ATCC BAA-894, C. sakazakii SP291 could grow faster in m-inositol and slower in succinic acid, dulcitol, D,L-α-glycerol phosphate, D,L-malic acid, Tween 20, α-ketoglutaric acid, uridine, bromosuccinic acid, glycolic acid, inosine, and dextrin. In contrast there were little or no differences in growth rates when other carbon sources such as methyl pyruvate, mannose, and β-methyl-D-glucuronic acid were compared.

Differences in phenotypes based on the metabolism of carbon sources were compared at the genome level within the carbohydrate subsystem (Table S7). Interestingly, nine inositol catabolism genes were annotated in the C. sakazakii SP291 genome (Table S8), which supported the PM data. Furthermore, a pentose phosphate pathway gene, a lactose utilization gene, and a sucrose utilization gene were also annotated in the C. sakazakii SP291 genome specifically although no evidence to support their activity was found following PM analysis. Similarly, a maltose and maltodextrin utilization gene and a lactate utilization gene were annotated in C. sakazakii ATCC BAA-894 alone, with supporting evidence for the activity lacking from the PM array data. In all, 428 annotated genes related to carbon metabolism were shared between C. sakazakii ATCC BAA-894 and C. sakazakii SP291, which included 10 chitin and N-acetylglucosamine utilization genes, five fructoselysine (amadori product) utilization pathway genes, five dehydrogenase complexes genes, a dihydroxyacetone kinases gene, 14 Entner-Doudoroff pathway genes, and others.

Dancer et al. (2009a,b) reported that for Cronobacter species the availability and utilization of a nitrogen source was an important determinant for biofilm formation when growing in skim milk, and that strong biofilm formers were responsible for coagulation of skim milk (Dancer et al., 2009a). Data from the phenotypic microarray, showed no differences in nitrogen metabolism when C. sakazakii ATCC BAA-894 and C. sakazakii SP291 were compared (Figure 2B and Table S6). Interestingly, when regions of these two genomes known to encode genes associated with nitrogen metabolism were compared, a 16-kb locus, consisting of eight genes was found to be absent in C. sakazakii SP291 compared to C. sakazakii ATCC BAA-894 (Table 3). BLAST analysis of the region facilitated the identification of the corresponding genes located at this position. This locus, contained two nitrate transport proteins NrtB and NrtC, two nitrite reductase proteins NasB and NasA, a respiratory nitrate reductase NarL, a nitrate/nitrite-sensing protein NarX, a nitrite extrusion protein 1 NarK, and a nitrate reductase 1, alpha subunit NarG. This region was also present in C. sakazakii ES15 and C. turicensis z3032. Furthermore, 24 nitrate genes were broadly shared between both of the genomes, which was supported by data from the PM analysis.

Genes associated with nitrogen metabolism, comparing C. sakazakii SP291 and C. sakazakii ATCC BAA 894.

Function Gene Size (bp) C. sakazakii SP291 C. sakazakii ATCC BAA-894
Nitrite-sensitive transcriptional repressor NsrR nsrR 426 166,807…167,232 171,773…172,198
Nitrogen regulatory protein P-II glnB 339 729,723…730,061 676,465…676,803
Flavohemoprotein (Hemoglobin-like protein) (Flavohemoglobin) (Nitric oxide dioxygenase) hmp 1191 731,488…730,298 677,084…678,274
Nitrate/nitrite response regulator protein narP 645 809,507…810,151 756,306…756,950
Nitrogen assimilation regulatory protein Nac nac 918 1,231,697…1,232,614 1,195,036…1,195,953
Response regulator NasT nasT 1203 1,528,174…1,529,376 1,450,050…1,451,252
Nitrate ABC transporter, nitrate-binding protein nrtA 1251 1,530,111…1,531,361 1,451,992…1,453,242
Nitrate ABC transporter, permease protein nrtB 881 Absent 1,453,252…1,454,133
Nitrate ABC transporter, ATP-binding protein nrtC 788 Absent 1,454,143…1,454,931
Nitrite reductase [NAD(P)H] large subunit nasB 4067 Absent 1,454,941…1,459,008
Assimilatory nitrate reductase large subunit nasA 2702 Absent 1,459,005…1,461,707
Nitrate/nitrite response regulator protein narL 651 Absent 1,463,744…1,464,394
Nitrate/nitrite sensor protein narX 1809 Absent 1,464,387…1,466,195
Nitrite extrusion protein 1 narK 1407 Absent 1,466,493…1,467,899
Respiratory nitrate reductase alpha chain narG 3747 Absent 1,468,317…1,472,063
Respiratory nitrate reductase beta chain narH 1311 1,531,371…1,532,681 1,472,060…1,473,595
Respiratory nitrate reductase delta chain narJ 711 1,532,678…1,533,388 1,473,592…1,474,302
Respiratory nitrate reductase gamma chain narI 678 1,533,388…1,534,065 1,474,302…1,474,979
Oxygen-insensitive NAD(P)H nitroreductase/Dihydropteridine reductase nfnB 645 1,851,923…1,852,567 1,807,325…1,807,969
ABC-type nitrate/sulfonate/bicarbonate transport systems, periplasmic components 1161 1,856,747…1,857,907 1,812,312…1,813,310
Fumarate and nitrate reduction regulatory protein fnr 753 1,932,047…1,932,799 1,887,404… 1,888,156
Hydroxylamine reductase hcp 1653 2,402,562…2,404,214 2,413,065…2,414,717
NADH oxidoreductase hcr hcr 969 2,404,225…2,405,193 2,414,728… 2,415,696
Oxygen-insensitive NADPH nitroreductase nfsA 723 2,428,664…2,429,386 2,434,920…2,434,198
Nitrilotriacetate monooxygenase component B 618 2,510,602…2,511,219 2,487,772…2,488,389
Nitrogen regulatory protein P-II glnK 339 2,833,540…2,833,878 2,792,459…2,792,797
PTS system nitrogen-specific IIA component, PtsN ptsN 534 3,536,000…3,536,533 3,531,047…3,531,580
Phosphocarrier protein, nitrogen regulation associated ptsO 273 3,537,449…3,537,721 3,532,496…3,532,768
Nitrogen regulation protein NR(I) glnG 1410 4,009,029…4,010,438 3,993,113…3,994,522
Nitrogen regulation protein NR(II) glnL 1050 4,010,447…4,011,496 3,994,531…3,995,580
Nitrite reductase [NAD(P)H] small subunit nirD 327 4,309,983…4,310,309 4,334,267…4,334,593
Nitrite reductase [NAD(P)H] large subunit nirB 2547 4,310,306…4,312,852 4,334,590…4,337,136

C. sakazakii SP291 was found to grow significantly slower in minimal media supplemented with phosphorous containing compounds (Figure 2A and Table S6), particularly in O-phospho-D-tyrosine, phospho-L-arginine, D,L-α-glycerol phosphate, β-glycerol phosphate, phosphoryl choline, phosphoenol pyruvate, D-glucose-6-phosphate, adenosine 3′-monophosphate, guanosine 2′-monophosphate, guanosine 3′-monophosphate, guanosine 5′-monophosphate, guanosine 2′,3′-cyclic monophosphate, cytidine 2′-monophosphate, cytidine 3′-monophosphate, thymidine 5′-monophosphate, and uridine 5′-monophosphate. Genome annotation provided a conflicting view as determined by the genes identified (Table S9). Twenty-nine phosphorus metabolism genes were broadly shared between C. sakazakii SP291 and C. sakazakii ATCC BAA-894, including eight high affinity phosphate transporters and control of pho-related regulon genes, 18 phosphate metabolism genes, and three polyphosphate genes. Cronobacter species cultured from a PIF production site were compared for their ability to grow in different food matrices (Cooney, 2012). Some demonstrated a slower growth rate compared to others, a feature that might contribute to their enhanced survival in this environment.

No differences in the metabolism of sulfur containing compounds were observed following a comparison of these strains after PM analysis (Figure 2A and Table S6). Forty-nine sulfur metabolism genes were shared by C. sakazakii ATCC BAA-894 and C. sakazakii SP291 (Table S10). These consisted of 17 inorganic sulfur assimilation genes, eight alkanesulfonate assimilation genes, five alkanesulfonates utilization genes, six L-cystine uptake and metabolism genes, four taurine utilization genes, three galactosylceramide and sulfatide metabolism genes, and six thioredoxin-disulfide reductase genes.

Iron is an essential nutrient for bacterial growth and the process of iron acquisition is generally thought to be a prerequisite for a pathogen to establish an infection when entering a host, a feature previously reported in Cronobacter species (Crosa and Walsh, 2002; Franco et al., 2011; Grim et al., 2012). High-affinity iron binding molecules, such as siderophores, and specific iron transport systems function to sequester iron from the environment when bacteria are subjected to iron-limiting growth conditions (Grim et al., 2012). Interestingly, analysis of the PM data showed no major differences between C. sakazakii SP291 and C. sakazakii ATCC BAA-894, in terms of their metabolism of iron or other nutrient supplements. Several transport systems were annotated in C. sakazakii SP291, and which are shared with C. sakazakii ATCC BAA-894 (Kucerova et al., 2010; Joseph et al., 2012), including a ferric hydroxamate ABC transporter denoted as FhuCDBA, 16 ferric enterobactin transporter proteins (including EntA, EntE, EntD, EntB, Fes, EntS, EntF, YbdZ, FepC, FepD, FepG, FepE, FepB, EntC, FepA2, and EntH), a ferrous iron transporter EfeUOB, along with a hemin transporter system, including a ferric reductase protein FhuF and a periplasmic binding protein TonB. A gene summary of iron acquisition and metabolism markers in C. sakazakii SP291 chromosome is shown in Table S11.

Additionally, iron acquisition and metabolism genes were also identified on pSP291-1 (Table S5), which were indistinguishable from that previously reported to be present on pESA3 of C. sakazakii ATCC BAA-894 (Kucerova et al., 2010; Joseph et al., 2012) and pCTU1 of C. turicensis z3032 (Franco et al., 2011; Grim et al., 2012). Target genes from previous reports, such as the RepFIB-like origin of replication gene repA, two plasmid-borne iron acquisition systems (eitCBAD and iucABCD/iutA), as well as the Cronobacter plasminogen activator cpa gene were all present in pSP291-1, with no evidence of the 17-kb type VI secretion system (T6SS) locus identified previously in pESA3 along with a 27-kb region encoding a filamentous hemagglutinin gene (fhaB), its specifc transporter gene (fhaC), and associated putative adhesins (FHA locus) identified in pCTU1 (Kucerova et al., 2010; Franco et al., 2011; Grim et al., 2012, 2013; Joseph et al., 2012). These features support the hypothesis that these plasmids have evolved from a single archetypal backbone that included an iron acquisition system. Our sequence analysis and those of other groups (Joseph et al., 2012; Grim et al., 2013) did not find evidence of plasmid mobilization genes associated with the several plasmid group 1 genomes.

 Osmolyte tolerance and survival in different pH environments

When present in different environments, bacteria must develop strategies that promote their survival. Genetic adaptation is derived from modifications of gene expression, via mutations, the acquisition of new and beneficial gene traits, or when these new traits are brought under control of a regulator that was already present in the core genome of the organism's ancestor (Maurelli, 2007). The outcome is that the organism is now better equipped to survive within the new ecological niche. It is generally thought that genes that are no longer compatible with the new lifestyle are selectively inactivated either by point mutation, insertion, or deletion and the contribution of gene loss to an organism's evolution is only now beginning to be appreciated (Maurelli, 2007). Based on our understanding of Cronobacter species epidemiology, these organisms are considered as environmental bacteria. Therefore their ability to survive adverse conditions would be critical. Phenotypes associated with growth in a range of osmolytes and in different pH growth environments were measured by PM analysis (Figure 2C and Table S6) as an indirect reflection of challenging environmental niches. In response to the presence of osmolytes, C. sakazakii SP291 could tolerate 100 mM sodium nitrate compared with C. sakazakii ATCC BAA-894. In contrast, the former grew slower in solutions containing 5% NaCl, 4% potassium chloride, 4% urea, 4–11% sodium lactate, 200 mM sodium phosphate at pH 7 and 20 mM sodium benzoate at pH 5.2. These observations are consistent with what has been suggested previously, in that when a selected adaptation event occurs, and the bacterium enters a new environment such as the human host, phenotypes change (Tall, unpublished observations). Comparing the ability of the environmental isolate C. sakazakii SP291 to survive over a range of different pH growth conditions with that of the PIF isolate C. sakazakii ATCC BAA-894, the former grew faster in a growth condition of pH 9.5 with phenylethylamine, whilst its growth was slower in pH 4.5 with L-proline. This example demonstrates the gain of one phenotype consistent with the inability to survive in the human host (ability to survive in high pH growth conditions) compared to the loss of a sufficient acid resistance response. In this case, the pathoadaptative event that resulted in an increased persistence in the environment comes at the expense of decreased commensal fitness of the microbe (a patent acid response) to survive the acidity of the stomach. However, a greater number of genomes and strains should be evaluated to rule out strain to strain variation.

Annotation of the genome suggested that C. sakazakii SP291 contained a repertoire of genes that could function to aid survival under stressed conditions, such as osmolyte tolerance and different pH environments (Table 4). One hundred and fifty-two annotated genes were identified as being involved with various stress responses. Their presence in the genome may provide early insights into how C. sakazakii SP291 adapts to and survives under different stressful growth conditions.

A selection of the stress response-encoding genes, the defined sub-system, together with the gene name, length of the ORF and correspondoing function, identified in C. sakazakii SP291.

Category Sub-system Gene Size (bp) Function
Osmotic stress Choline and betaine uptake and betaine biosynthesis betB 1472 Betaine aldehyde dehydrogenase
Osmotic stress Choline and betaine uptake and betaine biosynthesis betA 1679 Choline dehydrogenase
Osmotic stress Choline and betaine uptake and betaine biosynthesis betI 608 HTH-type transcriptional regulator BetI
Osmotic stress Choline and betaine uptake and betaine biosynthesis betT 2030 High-affinity choline uptake protein BetT
Osmotic stress Choline and betaine uptake and betaine biosynthesis opuCA 1145 Glycine betaine/carnitine/choline transport ATP-binding protein OpuCA
Osmotic stress Choline and betaine uptake and betaine biosynthesis opuCB 647 Glycine betaine/carnitine/choline transport ATP-binding protein OpuCB
Osmotic stress Choline and betaine uptake and betaine biosynthesis opuCC 905 Glycine betaine/carnitine/choline transport ATP-binding protein OpuCC
Osmotic stress Choline and betaine uptake and betaine biosynthesis opuCD 713 Glycine betaine/carnitine/choline transport ATP-binding protein OpuCD
Osmotic stress Choline and betaine uptake and betaine biosynthesis proP 1506 L-Proline/Glycine betaine transporter ProP
Osmotic stress Choline and betaine uptake and betaine biosynthesis proV 1202 L-Proline/Glycine betaine ABC transport system permease protein ProV
Osmotic stress Choline and betaine uptake and betaine biosynthesis proW 1070 L-proline glycine betaine ABC transport system permease protein ProW
Osmotic stress Choline and betaine uptake and betaine biosynthesis proX 995 L-proline glycine betaine binding ABC transporter protein ProX
Osmotic stress Osmoprotectant ABC transporter YehZYXW of enterobacteriales yehX 941 Osmoprotectant ABC transporter ATP-binding subunit YehX
Osmotic stress Osmoprotectant ABC transporter YehZYXW of enterobacteriales yehZ 908 Osmoprotectant ABC transporter binding protein YehZ
Osmotic stress Osmoprotectant ABC transporter YehZYXW of enterobacteriales yehW 731 Osmoprotectant ABC transporter inner membrane protein YehW
Osmotic stress Osmoprotectant ABC transporter YehZYXW of enterobacteriales yehY 1133 Osmoprotectant ABC transporter permease protein YehY
Osmotic stress Osmoregulation aqpZ 695 Aquaporin Z
Osmotic stress Osmoregulation glpF 848 Glycerol uptake facilitator protein
Osmotic stress Osmoregulation osmY 614 Osmotically inducible protein OsmY
Osmotic stress Osmoregulation ompA 1076 Outer membrane protein A precursor
Osmotic stress Osmoregulation yiaD 662 Inner membrane lipoprotein yiaD
Osmotic stress Osmotic stress cluster yciM 1169 Heat shock (predicted periplasmic) protein YciM, precursor
Osmotic stress Osmotic stress cluster osmB 215 Osmotically inducible lipoprotein B precursor
Osmotic stress Osmotic stress cluster pgpB 764 Phosphatidylglycerophosphatase B
Osmotic stress Osmotic stress cluster yciT 800 Transcriptional regulatory protein YciT
Osmotic stress Synthesis of osmoregulated periplasmic glucans mdoH 2528 Glucans biosynthesis glucosyltransferase H
Osmotic stress Synthesis of osmoregulated periplasmic glucans mdoC 1157 Glucans biosynthesis protein C
Osmotic stress Synthesis of osmoregulated periplasmic glucans mdoD 1715 Glucans biosynthesis protein D precursor
Osmotic stress Synthesis of osmoregulated periplasmic glucans mdoG 1553 Glucans biosynthesis protein G precursor
Osmotic stress Synthesis of osmoregulated periplasmic glucans opgC 1220 OpgC protein
Osmotic stress Synthesis of osmoregulated periplasmic glucans mdoB 2294 Phosphoglycerol transferase I
Cold shock Cold shock, CspA family of proteins cspA 212 Cold shock protein CspA
Cold shock Cold shock, CspA family of proteins cspC 209 Cold shock protein CspC
Cold shock Cold shock, CspA family of proteins cspD 230 Cold shock protein CspD
Cold shock Cold shock, CspA family of proteins cspE 209 Cold shock protein CspE
Cold shock Cold shock, CspA family of proteins cspG 212 Cold shock protein CspG
Heat shock Heat shock dnaK gene cluster extended dnaJ 1139 Chaperone protein DnaJ
Heat shock Heat shock dnaK gene cluster extended dnaK 1700 Chaperone protein DnaK
Heat shock Heat shock dnaK gene cluster extended yggX 275 FIG001341:,Probable Fe(2+)-trafficking protein YggX
Heat shock Heat shock dnaK gene cluster extended gshB 947 Glutathione synthetase
Heat shock Heat shock dnaK gene cluster extended grpE 602 Heat shock protein GrpE
Heat shock Heat shock dnaK gene cluster extended rdgB 593 Nucleoside 5-triphosphatase RdgB (dHAPTP, dITP, XTP-specific)
Heat shock Heat shock dnaK gene cluster extended rpoH 857 RNA polymerase sigma factor RpoH
Heat shock Heat shock dnaK gene cluster extended hemN2 1136 Radical SAM family enzyme, similar to coproporphyrinogen III oxidase, oxygen-independent, clustered with nucleoside-triphosphatase RdgB
Heat shock Heat shock dnaK gene cluster extended rph 635 Ribonuclease PH
Heat shock Heat shock dnaK gene cluster extended rsmE 731 16S rRNA methyltransferase RsmE
Heat shock Heat shock dnaK gene cluster extended prmA 881 Ribosomal protein L11 methyltransferase
Heat shock Heat shock dnaK gene cluster extended hslR 401 Ribosome-associated heat shock protein implicated in the recycling of the 50S subunit (S4 paralog)
Heat shock Heat shock dnaK gene cluster extended lepA 1799 Translation elongation factor LepA
Heat shock Heat shock dnaK gene cluster extended yraL 860 rRNA small subunit methyltransferase I
Heat shock Heat shock dnaK gene cluster extended smpB 482 tmRNA-binding protein SmpB
Dessication stress O-antigen capsule important for environmental persistence yihT 875 Aldolase YihT
Dessication stress O-antigen capsule important for environmental persistence yihS 1241 Aldose-ketose isomerase YihS
Dessication stress O-antigen capsule important for environmental persistence yihQ 2030 Alpha-glucosyltransferase YihQ
Dessication stress O-antigen capsule important for environmental persistence yihW 806 DeoR-type transcriptional regulator YihW
Dessication stress O-antigen capsule important for environmental persistence yihO 1430 Glucuronide transport protein YihO
Dessication stress O-antigen capsule important for environmental persistence yihP 1406 Glucuronide transport protein YihP, homologous to YihO
Dessication stress O-antigen capsule important for environmental persistence yshA 686 Outer membrane sugar transport protein YshA
Dessication stress O-antigen capsule important for environmental persistence yihU 899 Oxidoreductase YihU
Dessication stress O-antigen capsule important for environmental persistence yihV 899 Sugar kinase YihV
Dessication stress O-antigen capsule important for environmental persistence yihR 866 Sugar-1-epimerase YihR
Detoxification D-tyrosyl-tRNA(Tyr) deacylase dtd 437 D-tyrosyl-tRNA(Tyr) deacylase
Detoxification Glutathione-dependent pathway of formaldehyde detoxification frmA 1118 S-(hydroxymethyl)glutathione dehydrogenase
Detoxification Glutathione-dependent pathway of formaldehyde detoxification yieG 830 S-formylglutathione hydrolase YeiG
Detoxification Tellurite resistance: chromosomal determinants ydsK 980 Uncharacterized acetyltransferase ydcK
Detoxification Tellurite resistance: chromosomal determinants tehB 593 Tellurite resistance protein TehB
Detoxification Tellurite resistance: chromosomal determinants ydcL 668 Uncharacterized lipoprotein ydcL
Detoxification Uptake of selenate and selenite dedA 659 DedA protein
Detoxification Uptake of selenate and selenite cysA 1094 Sulfate and thiosulfate import ATP-binding protein CysA
Detoxification Uptake of selenate and selenite tsgA 1187 TsgA protein homolog
Oxidative stress Glutaredoxins yebA 1331 Uncharacterized metalloprotease yebA
Oxidative stress Glutaredoxins yibP 1259 Uncharacterized protein yibP
Oxidative stress Glutaredoxins hmp 1190 Flavohemoprotein (Hemoglobin-like protein) (Flavohemoglobin) (Nitric oxide dioxygenase)
Oxidative stress Glutaredoxins grxB 647 Glutaredoxin 2
Oxidative stress Glutaredoxins grxC 251 Glutaredoxin 3 (Grx3)
Oxidative stress Glutaredoxins nrdH 245 Glutaredoxin-like protein NrdH, required for reduction of Ribonucleotide reductase class Ib
Oxidative stress Glutaredoxins grlA 347 Probable monothiol glutaredoxin GrlA
Oxidative stress Glutathione: biosynthesis and gamma-glutamyl cycle ggt 1766 Gamma-glutamyltranspeptidase
Oxidative stress Glutathione: biosynthesis and gamma-glutamyl cycle gshA 1556 Glutamate-cysteine ligase
Oxidative stress Glutathione: biosynthesis and gamma-glutamyl cycle gshB 947 Glutathione synthetase
Oxidative stress Glutathione: non-redox reactions rnhA 716 FIG005121: SAM-dependent methyltransferase
Oxidative stress Glutathione: non-redox reactions gst1 668 Glutathione S-transferase
Oxidative stress Glutathione: non-redox reactions yghU 866 Uncharacterized Glutathione S-transferase like protein yghU
Oxidative stress Glutathione: non-redox reactions gst 608 Glutathione S-transferase
Oxidative stress Glutathione: non-redox reactions yqjG 986 Uncharacterized protein yqjG
Oxidative stress Glutathione: non-redox reactions gloB 755 Hydroxyacylglutathione hydrolase
Oxidative stress Glutathione: non-redox reactions gloA 407 Lactoylglutathione lyase
Oxidative stress Glutathione: non-redox reactions yfcF 644 Probable glutathione S-transferase, YfcF homolog
Oxidative stress Glutathione: non-redox reactions yfcG 626 Probable glutathione S-transferase, YfcG homolog
Oxidative stress Glutathione: non-redox reactions yibF 608 Uncharacterized GST-like protein yibF
Oxidative stress Glutathione: non-redox reactions yliJ 626 Uncharacterized glutathione S-transferase-like protein
Oxidative stress Glutathione: redox cycle grxB 635 Glutaredoxin 2
Oxidative stress Glutathione: redox cycle grxC 251 Glutaredoxin 3 (Grx3)
Oxidative stress Glutathione: redox cycle nrdH 245 Glutaredoxin-like protein NrdH, required for reduction of Ribonucleotide reductase class Ib
Oxidative stress Glutathione: redox cycle btuE 551 Glutathione peroxidase
Oxidative stress Glutathione: redox cycle lpd 1427 Glutathione reductase
Oxidative stress Glutathione: redox cycle gor 1352 Glutathione reductase
Oxidative stress Glutathionylspermidine and Trypanothione yjfC 1187 Uncharacterized protein yjfC
Oxidative stress Glutathionylspermidine and Trypanothione ygiC 1160 Uncharacterized protein ygiC
Oxidative stress NADPH:quinone oxidoreductase 2 ytfG 854 Uncharacterized oxidoreductase ytfG
Oxidative stress NADPH:quinone oxidoreductase 2 qorR 380 Redox-sensing transcriptional regulator QorR
Oxidative stress Oxidative stress katG 2180 Catalase/peroxidase HPI
Oxidative stress Oxidative stress katE 2255 Hydroperoxidase II
Oxidative stress Oxidative stress fur 452 Ferric uptake regulation protein FUR
Oxidative stress Oxidative stress dps 503 DNA protection during starvation protein
Oxidative stress Oxidative stress fnr 752 Fumarate and nitrate reduction regulatory protein
Oxidative stress Oxidative stress oxyR 917 DNA-binding transcriptional regulator OxyR
Oxidative stress Oxidative stress dps 503 DNA protection during starvation protein
Oxidative stress Oxidative stress sodA 626 Manganese superoxide dismutase
Oxidative stress Oxidative stress nsrR 353 Nitrite-sensitive transcriptional repressor NsrR
Oxidative stress Oxidative stress dpS 503 Non-specific DNA-binding protein Dps
Oxidative stress Oxidative stress osmC 428 Organic hydroperoxide resistance
Oxidative stress Oxidative stress ohrR 548 Organic hydroperoxide resistance transcriptional regulator
Oxidative stress Oxidative stress yebS 1283 Inner membrane protein yebS
Oxidative stress Oxidative stress pqiA 1284 Paraquat-inducible protein A
Oxidative stress Oxidative stress yebT 2633 Uncharacterized protein yebT
Oxidative stress Oxidative stress ymbA 563 Uncharacterized lipoprotein ymbA
Oxidative stress Oxidative stress pqiB 1640 Paraquat-inducible protein B
Oxidative stress Oxidative stress katG 2180 Catalase/peroxidase HPI
Oxidative stress Oxidative stress soxR 458 Redox-sensitive transcriptional activator SoxR
Oxidative stress Oxidative stress soxS 323 Regulatory protein SoxS
Oxidative stress Oxidative stress sodC 518 Superoxide dismutase [Cu-Zn] precursor
Oxidative stress Oxidative stress zur 515 Zinc uptake regulation protein Zur
Oxidative stress Protection from reactive oxygen species katG 2180 Catalase/peroxidase HPI
Oxidative stress Protection from reactive oxygen species katE 2255 Hydroperoxidase II
Oxidative stress Protection from reactive oxygen species sodA 626 Manganese superoxide dismutase
Oxidative stress Protection from reactive oxygen species sodC 518 Superoxide dismutase [Cu-Zn] precursor
Oxidative stress Redox-dependent regulation of nucleus processes gapA1 995 NAD-dependent glyceraldehyde-3-phosphate dehydrogenase
Oxidative stress Redox-dependent regulation of nucleus processes gapA2 996 NAD-dependent glyceraldehyde-3-phosphate dehydrogenase
Oxidative stress Redox-dependent regulation of nucleus processes npdA 824 NAD-dependent protein deacetylase of SIR2 family
Oxidative stress Redox-dependent regulation of nucleus processes pncA 641 Nicotinamidase
Oxidative stress Redox-dependent regulation of nucleus processes pncB 1202 Nicotinate phosphoribosyltransferase
Periplasmic stress Periplasmic stress response htrA 1427 HtrA protease/chaperone protein
Periplasmic Stress Periplasmic stress response skp 494 Outer membrane protein H precursor
Periplasmic Stress Periplasmic stress response degQ 1367 Outer membrane stress sensor protease DegQ, serine protease
Periplasmic Stress Periplasmic stress response degS 1067 Outer membrane stress sensor protease DegS
Periplasmic Stress Periplasmic stress response rseA 650 Sigma factor RpoE negative regulatory protein RseA
Periplasmic Stress Periplasmic stress response rseB 854 Sigma factor RpoE negative regulatory protein RseB precursor
Periplasmic Stress Periplasmic Stress response surA 1286 Survival protein SurA precursor (Peptidyl-prolyl cis-trans isomerase SurA)
No subcategory Bacterial hemoglobins hmp 1190 Flavohemoprotein (Hemoglobin-like protein) (Flavohemoglobin) (Nitric oxide dioxygenase)
No subcategory Carbon starvation 2105 Carbon starvation protein A
No subcategory Carbon starvation cstA 2153 Carbon starvation protein A paralog
No subcategory Carbon starvation csrA 185 Carbon storage regulator
No subcategory Carbon starvation 584 Starvation lipoprotein Slp paralog
No subcategory Carbon starvation rspA 1316 Starvation sensing protein RspA
No subcategory Carbon starvation sspA 641 Stringent starvation protein A
No subcategory Carbon starvation sspB 491 Stringent starvation protein B
No subcategory Commensurate regulon activation marA 374 Multiple antibiotic resistance protein MarA
No subcategory Commensurate regulon activation gpmB 869 Probable phosphoglycerate mutase gpmB
No subcategory Commensurate regulon activation soxS 324 Regulatory protein SoxS
No subcategory Commensurate regulon activation ramA 344 Transcriptional activator RamA
No subcategory Flavohaemoglobin hmp 1190 Flavohemoprotein (Hemoglobin-like protein) (Flavohemoglobin) (Nitric oxide dioxygenase)
No subcategory Hfl operon hflX 1280 GTP-binding protein HflX
No subcategory Hfl operon hflC 1004 HflC protein
No subcategory Hfl operon hflK 1244 HflK protein
No subcategory Hfl operon yjeT 197 Putative inner membrane protein YjeT (clustered with HflC)
No subcategory Hfl operon hfq 308 RNA-binding protein Hfq
No subcategory Phage shock protein (psp) operon pspA 671 Phage shock protein A
No subcategory Phage shock protein (psp) operon pspB 224 Phage shock protein B
No subcategory Phage shock protein (psp) operon pspC 356 Phage shock protein C
No subcategory Phage shock protein (psp) operon pspD 242 Phage shock protein D
No subcategory Phage shock protein (psp) operon pspF 1001 Psp operon transcriptional activator
No subcategory Sugar-phosphate stress regulation sgrR 1664 SgrR, sugar-phosphate stress, transcriptional activator of SgrS small RNA
No subcategory Universal stress protein family uspA 437 Universal stress protein A
No subcategory Universal stress protein family uspB 335 Universal stress protein B
No subcategory Universal stress protein family uspC 422 Universal stress protein C
No subcategory Universal stress protein family uspE 956 Universal stress protein E
No subcategory Universal stress protein family uspG 428 Universal stress protein G

In recent studies involving Salmonella species, a picture of the transcriptome in low-moisture growth conditions has begun to emerge (Frossard et al., 2012; Finn et al., 2013). Allied to this, 25 genes involved in osmotic stress, and covering 16.4% of the stress response genes were identified in C. sakazakii SP291. Interestingly, the osmoprotectant ABC transporter denoted as YehZYXW in the Cronobacter genome, together with the L-proline glycine betaine MFS transporter ProP, and the ABC transporter ProU systems (composed of ProV, ProW, ProX) designed in Escherichia coli (Checroun and Gutierrez, 2004) and Salmonella Typhimurium (Cairney et al., 1985) were identified in the C. sakazakii SP291 genome. Moreover, an osmoregulator transporter including genes opuCA, opuCB, opuCC, and a fourth gene, which was also an ABC transporter denoted as opuCD here, was 77% similar to that of the osmU operon (osmVWXY) in Salmonella (Frossard et al., 2012) at the gene level. Other osmotically functioning genes identified included the betaine/carnitine/choline transporter (BCCT) family, which acts to transport betaine and choline. This operon consists of a high-affinity choline uptake gene betT, a helix-turn-helix (HTH)-type transcriptional regulator betI, which was previously identified in E. coli (Lamark et al., 1991), a betaine aldehyde dehydrogenase betB gene and a choline dehydrogenase gene betA. An in silico assessment of those loci involved in osomotolerance comparing Cronobacter sakazakii ATCC BAA-894 and E. coli K12 MG1655 identified these latter features also (Feeney and Sleator, 2011). Interestingly, several other genes linked to osmotic stress conditions were identified in the genome of C. sakazakii SP291, which included five osmoregulation genes (aqpZ, glpF, osmY, ompA, and yiaD), four osmotic stress cluster genes (yciM, osmB, pgpB, and yciT) and six osmoregulated periplasmic glucan genes (mdoH, mdoC, mdoD, mdoG, opgC and mdoB). None of these genes were identified previously by Feeney and Sleator (2011). Finally, ompA which encodes an outer membrane porin, was identified in C. sakazakii SP291 and is a recognized virulence marker (Kim et al., 2010).

Experiments to investigate the nature of the C. sakazakii responses to cold- and heat-shock conditions have been reported (Shaker et al., 2008; Carranza et al., 2010; Chang et al., 2010; Al-Nabulsia et al., 2011; Gajdosova et al., 2011). Following exposure to extreme temperatures of cold-shock at −20°C, or heat-shock at 47°C, survival of Cronobacter sakazakii was significantly enhanced (Chang et al., 2010). Carranza et al. (2010) reported that when exposed to higher temperatures, several potential virulence factors were up-regulated. The fact that the pathogenic potential of Cronobacter species may be related to its ability to survive at higher temperatures, warrents further investigation. From the genome sequence of C. sakazakii SP291, the cspA family of cold-shock genes (including cspA, cspC, cspD, cspE and cspG) along with 11 other genes annotated as heat-shock genes, part of the dnaK gene cluster, including dnaJ, dnaK, yggX, gshB, grpE, rdgB, rpoH, hemN2, rph, rsmE, prmA, hslR, yraL, and smpB genes were conserved.

Using a top-down proteomics approach, Williams et al. (2005) identified a candidate protein in C. sakazakii, known to be associated with thermotolerance in Methylobacillus flagelatum, and which was denoted as KT. In a recent study, the genomic region containing this presumptive marker of thermotolerance was compared to similar regions in other bacteria (Gajdosova et al., 2011). An in silico analysis showed that this thermotolerace KT-region was present in 4 of 14 isolates consisting of seven Cronobacter species studied by Joseph et al. (2012). Cronobacter sakazakii SP291 can survive desiccation for long periods of time at an average temperature of 56.7°C, similar to that recorded when spray drying is in operation during PIF production (Cooney, 2012). Interestingly, C. sakazakii SP291 was negative for the KT marker, as determined by PCR (data not shown). Apart from the locus between orfA-orfE, when the corresponding region of the SP291 genome was compared to that of C. sakazakii ATCC 29,544, this region was devoid of the KT-encoding homolog (Figure 3). In light of the thermo-adapted phenotype possessed by C. sakazakii SP291, this finding suggests that there may be other thermotolerance survival mechanisms expressed by C. sakazakii SP291.

The putative thermotolerance-containing DNA region of C. sakazakii ATCC 29544 compared with C. sakazakii SP291.

As mentioned above, Cronobacter species have the capacity to survive in desiccated environments for long periods, a phenotype that is linked to their epidemiology and routes of infection. As an example of genes linked to this phenotype, the yih-encoding operons, consisted of 10 annotated genes present in the genome of C. sakazakii SP291. Desiccation-related proteins YihU, YihT, YihR, YihS, YihQ and YihV have conserved domains which function in carbohydrate transport and metabolism. YihO is a glucuronide transport protein whilst YihP is homologous to it. YshA is an outer membrane sugar transport protein and YihW is a deoR-type transcriptional regulator, reported to negatively regulate the expression of yihU-oyshA in Salmonella (Gibson et al., 2006). This operon was reported to be up-regulated following desscication stress in Salmonella. Interstingly, the yih operon are conserved in 17 annotated Cronobacter genomes (strain information of the genomes are listed in Table 1) and noted previously (Grim et al., 2013).

The ability of a bacterium to eliminate toxic compounds from the cell is an important survival mechanism. Nine genes involved in detoxification were identified in the C. sakazakii SP291 genome. These included a tellurite resistance-encoding gene tehB, which matches a 593 bp hypothetical protein in C. sakazakii ATCC BAA-894. However, a tellurite resistance region (terACDYZ) was reported only in C. sakazakii ATCC BAA-894 (Table 4), and with the exception of the terC-encoding marker in C. turicensis z3032, was not identified in any of the other Cronobacter species genomes sequenced (Kucerova et al., 2010; Joseph et al., 2012; Grim et al., 2013). Genes involved in the detoxification of organic pollutants, including a D-tyrosyl-tRNA (Tyr) deacylase-encoding dtd, two glutathione-dependent pathway formaldehyde detoxification genes (frmA and yieG), three genes involved in the uptake of selenate and selenite (dedA, cysA, and its homolog tsgA), and two uncharacterized genes (ydsK and ydcL), were also identified in C. sakazakii SP291. This feature supports an earlier report describing the ability of Cronobacter species to detoxify and survive in tannery wastewater effluents (Chandra et al., 2011).

Oxidative stress is an example of an important bacterial stress response, with 62 annotated genes covering 40.8% genome linked to this sub-system. These genes included the zinc uptake regulation zur, which was reported as involved in the oxidative stress response of Streptomyces coelicolor (Shin et al., 2007). Other stress-related genes included seven periplasmic stress related genes, a bacterial hemoglobin gene, seven genes involved in carbon starvation, four commensurate regulon activation genes, a flavohaemoglobin gene, five hfl operon genes, five phage shock protein (psp) operon genes, a sugar-phosphate stress regulation gene, and five universal stress protein family genes.

 Resistance to antibiotics and toxic compounds

C. sakazakii was originally reported to be susceptible to a panel of 69 antimicrobial agents (Stock and Wiedemann, 2002). Subsequently, a tetracycline-resistant C. sakazakii cultured from a Chilean freshwater salmon farm (Miranda et al., 2003) was isolated, followed by a report of a trimethoprim and neomycin resistance isolate cultured from fresh domiati cheese (El-Sharoud et al., 2009). More recently, isolates resistant to cephalothin were recovered from dried food (Chon et al., 2012). The emergence of strains that have become resistant to antimicrobial compounds is of great concern to public health (Dumen, 2010; Yan et al., 2012).

Figure 2D shows a heat map comparing C. sakazakii SP291 and C. sakazakii ATCC BAA-894 and Table 5 provides a summary of the significant changes in PM redox measurements, after bacterial growth in microtitre wells containing a number of antimicrobial compounds as part of the phenotypic microarray. Compared to C. sakazakii ATCC BAA-894, C. sakazakii SP291 exhibited more activity in the presence of 5,7-dichloro-8-hydroxyquinoline, 5-nitro-2-furaldehyde semicarbazone, hexamminecobalt (III) chloride, poly-L-lysine, protamine sulfate, ornidazole, tobramycin, streptomycin, apramycin, iodonitro tetrazolium violet, amoxicilin, neomycin, and sisomicin; while exhibiting a reduced activity in the presence of phleomycin, ciprofloxacin, cinoxacin, dichlofluanid, tolylfluanid, guanidine hydrochloride, colistin, methyl viologen, sodium azide, guanazole, rifamycin SV, glycine hydroxamate, D,L-methionine hydroxamate, cefmetazole, and cloxacillin.

Comparison of the differential phenotypes expressed by C. sakazakii SP291 and C. sakazakii ATCC BAA-894 related to antimicrobial and toxic compounds as determined by phenotype microarray.

Test compound Differencea Mode of action
PHENOTYPES GAINED BY C. sakazakii SP291 RELATIVE TO C. sakazakii ATCC BAA-894-
Amoxicillin 20,446 Wall, lactam
Neomycin 47,681 Protein synthesis, 30S ribosomal subunit, aminoglycoside
Sisomicin 40,297 Protein synthesis, 30S ribosomal subunit, aminoglycoside
Tobramycin 33,297 Protein synthesis, 30S ribosomal subunit, aminoglycoside
Sodium arsenate 22,155 Toxic anion, PO4 analog
Sodium metaborate 65,231 Toxic anion
EDTA 89,134 Chelator, hydrophilic
5,7-Dichloro-8-hydroxyquinoline 21,638 Chelator, lipophilic
5-Nitro-2-furaldehyde semicarbazone 40,348 DNA damage, multiple sites, nitrofuran analog
Protamine sulfate 27,720 Membrane, non-specific binding
Streptomycin 40,297 Protein synthesis, 30S ribosomal subunit, aminoglycoside
Potassium tellurite 27,025 Toxic anion
Sodium tungstate 50,849 Toxic anion, molybdate analog
Poly-L-lysine 43,324 Membrane, detergent, cationic
Sodium m-arsenite 28,927 Toxic anion
Sodium periodate 47,820 Toxic anion, oxidizing agent
Antimony (III) chloride 35,457 Toxic cation
Iodonitro tetrazolium violet 22,427 Respiration
Hexamminecobalt (III) Chloride 30,202 DNA synthesis
Apramycin 43,717 Protein synthesis, 30S ribosomal subunit, aminoglycoside
Ornidazole 22,594 Protein glycosolation
PHENOTYPES LOST BY C. sakazakii SP291 RELATIVE TO C. sakazakii ATCC BAA-894-
Cloxacillin −20,939 Wall, lactam
Colistin −35,638 Membrane, transport
Guanidine hydrochloride −47,347 Membrane, chaotropic agent
Cefmetazole −21,713 Wall, cephalosporin second generation
Phleomycin −45,183 DNA damage, oxidative, ionizing ratiation
Methyl viologen −81,565 Oxidizing agent
Sodium azide −22,375 Respiration, uncoupler
Dichlofluanid −42,205 Fungicide, phenylsulphamide
Cinoxacin −18,744 DNA unwinding, gyrase (GN), topoisomerase (GP), quinolone
Rifamycin SV −22,130 RNA polymerase
Glycine hydroxamate −64,946 tRNA synthetase
D,L−Methionine hydroxamate −38,317 tRNA synthetase
Sodium bromate −27,123 Toxic anion
Guanazole −33,164 Ribonucleotide DP reductase
Ciprofloxacin −22,172 DNA unwinding, gyrase (GN), topoisomerase (GP), fluoroquinolone
Tolylfluanid −18,317 Fungicide, phenylsulphamide

Denotes the following: a positive number indicates faster growth in C. sakazakii SP291 compared to C. sakazakii ATCC BAA-894; a negative number indicates faster growth in C. sakazakii ATCC BAA-894 compared to C. sakazakii SP291.

Careful analysis of the PM data showed an interesting phenotype, related to bioactive and toxic anions. C. sakazakii SP291 survived significantly better in sodium metaborate, potassium tellurite, sodium m-arsenite, sodium tungstate, sodium periodate, sodium arsenate, and antimony (III) chloride compared with C. sakazakii ATCC BAA-894. In contrast the latter bacterium, exhibited a distinct phenotype in sodium bromate. These observations suggested that C. sakazakii SP291 elaborates a greater ability to counter the effects of a broader range of heavy metals, a characteristic that could be facilitate adaptation in powered infant formula manufacturing environments where metallic compositions such as quaternary containing disinfectants are used for decontamination. This resistance phenotype may be globally regulated as well. Together, this information may explain how this organism adapted to the manufacturing environment.

Based in part on these phenotypes, a total of 44 genes were shared between C. sakazakii ATCC BAA-894 and C. sakazakii SP291. These consisted of adaptation to D-cysteine related genes (include yecC, yecS, and dcyD), a β-lactamase-encoding ampC gene, three cobalt-zinc-cadmium resistance genes (including feiF, zitB and a MerR family transcriptional regulator), 11 copper homeostasis genes (include cueO, yobA, copA, zntA, ccmF, ccmH, cutE, cutF, corC, cutA, and a copper resistance protein D gene), a fosfomycin resistance gene fosA, a lysozyme inhibitor mliC, a tripartite multidrug resistance system found in Gram-negative bacteria, 11 multidrug resistance efflux pumps (including macB, macA, acrA, acrE, norM, acrD, acrB, acrF, acrR, envR, and tolC), four genes encoding resistance to fluoroquinolones (including gyrA, gyrB, parC, and parE), and a multidrug resistance cluster (consisting of mdtB, mdtC, mdtD, mdtA, baeR, and baeS). All of these genes mapped to the bacterial chromosome. In addition three arsenic resistance genes were identified on pSP291-1 (Table S5). This latter feature confirmed the previous report on the copper/silver resistance determinants in Cronobacter species (Kucerova et al., 2010; Sivamaruthi et al., 2011; Joseph and Forsythe, 2012; Joseph et al., 2012; Grim et al., 2013). In contrast, eight cobalt-zinc-cadmium resistance genes (include cusA, cusC, cusF, czcA, czcB, cusS, cusR, and pcoS) and three copper homeostasis genes (including copG, pcoB and pcoA) were unique to C. sakazakii ATCC BAA-894, of which cusRCFBA/silRECBA and pcoABCDR were indicated as two copper and silver resistance regions. The previous region was shared among C. sakazakii, C. malonaticus, and C. turicensis; while the latter region was shared among C. sakazakii, C. malonaticus, C. turicensis and C. universalis (Joseph et al., 2012) (Table 6).

Genes related to resistance to antibiotics and toxic compounds annotated in C. sakazakii SP291 and C. sakazakii ATCC BAA-894.

Subsystem Start Stop Size (bp) Gene Role
RESISTANCE TO ANTIBIOTIC AND TOXIC COMPUNDS GENES SHARED BY C. sakazakii SP291 AND C. sakazakii ATCC BAA-894-
Adaptation to D-cystine 1,345,012 1,345,764 752 yecC Cystine ABC transporter, ATP-binding protein
Adaptation to d-cystine 1,344,347 1,345,015 668 yecS Cystine ABC transporter, permease protein
Adaptation to d-cystine 1,343,343 1,344,323 980 dcyD D-cystine desulfhydrase
Beta-lactamase 1,853,746 1,852,619 1127 ampC Beta-lactamase
Cobalt-zinc-cadmium resistance 4,087,380 4,088,282 902 fieF Cobalt-zinc-cadmium resistance protein
Cobalt-zinc-cadmium resistance 733,136 733,498 362 Transcriptional regulator, MerR family
Cobalt-zinc-cadmium resistance 2,570,193 2,571,155 962 zitB Zinc transporter ZitB
Copper homeostasis 2,643,555 2,645,219 1664 cueO Blue copper oxidase CueO precursor
Copper homeostasis 1,433,730 1,434,104 374 yobA Copper resistance protein C precursor
Copper homeostasis 1,434,109 1,434,978 869 Copper resistance protein D
Copper homeostasis 2,766,031 2,768,538 2507 copA Copper-translocating P-type ATPase
Copper homeostasis 4,209,899 4,207,683 2216 zntA Zinc/cadmium/mercury/lead-transporting ATPase
Copper homeostasis 924,321 926,270 1949 ccmF Cytochrome c heme lyase subunit CcmF
Copper homeostasis 926,821 927,282 461 ccmH Cytochrome c heme lyase subunit CcmH
Copper homeostasis: copper tolerance 2,651,936 2,653,477 1541 cutE Copper homeostasis protein CutE
Copper homeostasis: copper tolerance 3,053,870 3,053,172 698 cutF Copper homeostasis protein CutF precursor
Copper homeostasis: copper tolerance 2,651,056 2,651,931 875 corC Magnesium and cobalt efflux protein CorC
Copper homeostasis: copper tolerance 130,149 129,802 347 cutA Periplasmic divalent cation tolerance protein CutA
Fosfomycin resistance 1,712,546 1,712,959 413 fosA Fosfomycin resistance protein FosA
Lysozyme inhibitors 1,973,845 1,973,522 323 mliC Membrane-bound lysozyme inhibitor of c-type lysozyme
Multidrug resistance, tripartite systems found in gram negative bacteria 2,468,114 2,466,543 1517 emrB2 Inner membrane component of tripartite multidrug resistance system
Multidrug resistance, tripartite systems found in gram negative bacteria 2,469,268 2,468,111 1157 Membrane fusion component of tripartite multidrug resistance system
Multidrug resistance, tripartite systems found in gram negative bacteria 2,466,541 2,465,000 1541 nodT Outer membrane component of tripartite multidrug resistance system
Multidrug resistance efflux pumps 2,397,113 2,395,170 1943 macB Macrolide export ATP-binding/permease protein MacB
Multidrug resistance efflux pumps 2,398,222 2,397,110 1112 macA Macrolide-specific efflux protein MacA
Multidrug resistance efflux pumps 2,799,127 2,800,332 1205 acrA Membrane fusion protein of RND family multidrug efflux pump
Multidrug resistance efflux pumps 3,599,205 3,600,347 1142 acrE Membrane fusion protein of RND family multidrug efflux pump
Multidrug resistance efflux pumps 1,999,315 2,000,688 1373 norM Multi antimicrobial extrusion protein (Na(+)/drug antiporter), MATE family of MDR efflux pumps
Multidrug resistance efflux pumps 809,372 806,256 3116 acrD Probable aminoglycoside efflux pump
Multidrug resistance efflux pumps 2,800,354 2,803,503 3149 acrB Acriflavine resistance protein B
Multidrug resistance efflux pumps 3,600,357 3,603,476 3119 acrF Acriflavine resistance protein F
Multidrug resistance efflux pumps 2,798,982 2,798,317 665 acrR HTH-type transcriptional regulator acrR
Multidrug resistance efflux pumps 3,598,827 3,598,180 647 envR Transcription repressor of multidrug efflux pump acrAB operon, TetR (AcrR) family
Multidrug resistance efflux pumps 374,805 373,318 1487 tolC Type I secretion outer membrane protein, TolC precursor
Resistance to fluoroquinolones 1,021,753 1,024,389 2636 gyrA DNA gyrase subunit A
Resistance to fluoroquinolones 3,931,538 3,929,124 2414 gyrB DNA gyrase subunit B
Resistance to fluoroquinolones 383,132 385,402 2270 parC Topoisomerase IV subunit A
Resistance to fluoroquinolones 377,546 379,438 1892 parE Topoisomerase IV subunit B
The mdtABCD multidrug resistance cluster 1,153,120 1,149,998 3122 mdtB Multidrug transporter MdtB
The mdtABCD multidrug resistance cluster 1,149,997 1,146,908 3089 mdtC Multidrug transporter MdtC
The mdtABCD multidrug resistance cluster 1,146,904 1,145,489 1415 mdtD Multidrug transporter MdtD
The mdtABCD multidrug resistance cluster 1,154,367 1,153,120 1247 mdtA Probable RND efflux membrane fusion protein
The mdtABCD multidrug resistance cluster 1,144,071 1,143,349 722 baeR Response regulator BaeR
The mdtABCD multidrug resistance cluster 1,145,492 1,144,068 1424 baeS Sensory histidine kinase BaeS
RESISTANCE TO ANTIBIOTIC AND TOXIC COMPUNDS GENES SPECIFIC TO C. sakazakii ATCC BAA-894-
Cobalt-zinc-cadmium resistance 4,206,746 4,209,892 3146 cusA Cation efflux system protein CusA
Cobalt-zinc-cadmium resistance 4,203,563 4,204,948 1385 cusC Cation efflux system protein CusC precursor
Cobalt-zinc-cadmium resistance 4,204,976 4,205,329 353 cusF Cation efflux system protein CusF precursor
Cobalt-zinc-cadmium resistance 4,206,746 4,209,892 3146 czcA Cobalt-zinc-cadmium resistance protein CzcA
Cobalt-zinc-cadmium resistance 4,205,443 4,206,735 1292 czcB Cobalt/zinc/cadmium efflux RND transporter, membrane fusion protein, CzcB family
Cobalt-zinc-cadmium resistance 4,202,505 4,201,219 1286 cusS Copper sensory histidine kinase CusS
Cobalt-zinc-cadmium resistance 4,203,373 4,202,693 680 cusR Copper-sensing two-component system response regulator CusR
Cobalt-zinc-cadmium resistance 4,219,774 4,221,174 1400 pcoS Heavy metal sensor histidine kinase
Copper homeostasis 4,209,979 4,210,419 440 CopG CopG protein
Copper homeostasis 4,217,266 4,217,688 422 pcoB Copper resistance protein B
Copper homeostasis 4,214,975 4,216,792 1817 pcoA Multicopper oxidase
Conclusions

Stress responses and resistance to antibiotic and toxic compounds are interesting phenotypes identified in C. sakazakii SP291, when compared to C. sakazakii ATCC BAA-894, based on the comparative phenotypic microarray analysis in parallel with the annotation of its genome. Given this the fact that the PIF production environment is a stressful ecological niche, the osmoprotectant ABC transporters including YehZYXW, ProP, ProU, and OpuCABCD can be expected to play a role to support bacterial survival, as reported in other microorganisms previously (Cairney et al., 1985; Checroun and Gutierrez, 2004; Frossard et al., 2012; Finn et al., 2013). Notably, C. sakazakii SP291 possesses a greater ability to survive in a broader range of heavy metals, as quaternary containing disinfectants which include metallic compositions are often used for PIF manufacturing environment disinfection. In conclusion, genome analysis of C. sakazakii SP291 along with its metabolome highlighted a number of potential features, which might be considered as candidates for future studies to extend our understanding of the persistence and virulence mechanisms deployed by this bacterium in the production environment. These data provide an early insight into how a factory isolate may survive in a desiccation condition and adapt to the PIF production environment and associated food matrices.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

We thank Drs. Marta Martins and Orla Condell for their assistance with the PM data analysis and to Ms. Sarah Finn for critical reading of the manuscript.

 Supplementary material

The Supplementary Material for this article can be found online at: http://www.frontiersin.org/Food_Microbiology/10.3389/fmicb.2013.00256/abstract

Genomic regions missing in C. sakazakii SP291 when compared to the other three completed genomes of C. sakazakii ATCC BAA-894 (as the reference sequence), C. sakazakii E15 and C. turicensis z3032.

Genomic regions present only in C. sakazakii SP291 (as the reference sequence) when compared to the other three completed genomes of C. sakazakii ATCC BAA-894, C. sakazakii ES15 and C. turicensis z3032.

Genome comparison of C. sakazakii SP291 with other available C. sakazakii genomes, which include C. sakazakii SP291, ATCC BAA-894, ES15, E899, 680, 696, 701, ES35, 2151, ES713, and E764.

Genome comparison of C. sakazakii SP291 with Cronobacter isolate of other six species, which consist of C. dublinensis LMG 23823, C. malonaticus LMG 23826, C. muytjensii ATCC 51329, C. turicensis z3032, C. universalis NCTC 9529, and C. condimenti 1330.

Annotated plasmid clusters of three complete genome, which include pSP291-1, pSP291-2, and pSP291-3 of C. sakazakii SP291, pESA2 and pESA3 of C. sakazakii ATCC BAA-894, as well as pCTU1, pCTU2, and pCTU3 of C. turicensis z3032. Plasmid group 1: pSP291-1, pESA3, and pCTU1; plasmid group 2: pSP291-2 and pCTU3.

Numerical data for all 20 PM plates of C. sakazakii SP291 and C. sakazakii ATCC BAA-894, along with the phenotype differences (greater than 20,000±1,800 unit) generated by Omnilog® software.

Genes assigned to defined bacterial sub-systems and their distribution among these functional categories for C. sakazakii SP291 along with other three completed genome, C. sakazakii ATCC BAA-894, C. sakazakii ES15, and C. turicensis z3032.

Genome annotation: Carbohydrate metabolism of C. sakazakii SP291 and C. sakazakii ATCC BAA-894.

Genome annotation: Phosphorus metabolism of C. sakazakii SP291 and C. sakazakii ATCC BAA-894.

Genome annotation: Sulfur metabolism of C. sakazakii SP291 and C. sakazakii ATCC BAA-894.

Iron acquisition systems identified in the chromosome of C. sakazakii SP291.

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Circular representation of the C. sakazakii SP291 genome. The first circle represents the scale in kilobases starting with the origin of replication at position 0. The second circle shows the distribution of CDS (Goldman and Green, 2009) in forward strand. The third circle indicates the distribution of CDS (blue) in reverse strand. rRNA operons are colored in red on the fourth circle. tRNA operons are colored in purple on the fifth circle. The sixth circle indicates the deviation of the GC content average, with values greater than zero in green and those less than zero in purple. The innermost circle displays the GC skew ([G + C]/[G − C]), with values greater than zero in light blue and those less than zero in orange. The figure was generated using DNAPlotter (Carver et al., 2009).

Comparision of plasmid group 1 (pESA3, pSP291-1, and pCTU1) using Artemis comparison tool (ACT).

Comparision of plasmid group 2 (pSP291-2 and pCTU3) using Artemis comparison tool (ACT).