RESEARCH ARTICLE

Proteomic profiling of Cronobacter turicensis 3032,

a food-borne opportunistic pathogen

Paula Carranza1, Isabel Hartmann2, Angelika Lehner2, Roger Stephan2, Peter Gehrig3,Jonas Grossmann3, Simon Barkow-Oesterreicher3, Bernd Roschitzki3, Leo Eberl1

and Kathrin Riedel1

1 Department of Microbiology, Institute of Plant Biology, UZH, Zurich, Switzerland2 Institute for Food Safety and Hygiene, Vetsuisse, UZH, Zurich, Switzerland3 Functional Genomics Center Zurich, UZH/ETH, Zurich, Switzerland

Received: January 12, 2009

Revised: March 25, 2009

Accepted: April 5, 2009

Members of the genus Cronobacter are opportunistic pathogens for neonates and are often asso-

ciated with contaminated milk powder formulas. At present little is known about the virulence

mechanisms or the natural reservoir of these organisms. The proteome of Cronobacter turicensis3032, which has recently caused two deaths, was mapped aiming at a better understanding of

physiology and putative pathogenic traits of this clinical isolate. Our analyses of extracellular,

surface-associated and whole-cell proteins by two complementary proteomics approaches, 1D-SDS-

PAGE combined with LC-ESI-MS/MS and 2D-LC-MALDI-TOF/TOF MS, lead to the identification

of 832 proteins corresponding to a remarkable 19% of the theoretically expressed protein

complement of C. turicensis. The majority of the identified proteins are involved in central metabolic

pathways, translation, protein folding and stability. Several putative virulence factors, whose

expressions were confirmed by phenotypic assays, could be identified: a macrophage infectivity

potentiator involved in C. turicensis persistence in host cells, a superoxide dismutase protecting the

pathogen against reactive oxygen species and an enterobactin-receptor protein for the uptake of

siderophore-bound iron. Most interestingly, a chitinase and a metalloprotease that might act against

insects and fungi but no casein hydrolysing enzymes were found, suggesting that there is an

environmental natural habitat of C. turicensis 3032.

Keywords:

1D-SDS-PAGE-LC-ESI-MS/MS / 2D-LC-MALDI-TOF/TOF-MS / Bacterial proteomics /

Cronobacter turicensis / Pathogenicity

1 Introduction

Cronobacter sp., formerly named Enterobacter sakazakii, is a

Gram-negative opportunistic pathogen and known as rare

but important cause of live-threatening neonatal infections.

In 2008, the E. sakazakii species was assigned to the new

genus Cronobacter and divided into five species according to

ribotyping, 16S rRNA sequencing, f-AFLP and DNA-DNA

hybridisation [1].

Cronobacter sp. infections can lead to severe disease

manifestations such as brain abscesses, meningitis, necro-

tizing enterocolitis and systemic sepsis [2, 3] with fatal

mortality rates ranging from 40 to 80% [4]. Neonates and

infants under two months, born prematurely or with low

birth weight (o2500 g) are at highest risk for infection [5]

most commonly by Cronobacter sp. contaminated powdered

infant milk formulas. Notably, Cronobacter sp. is often found

in food preparation environments (i.e. chocolate, pasta,

cereal and dairy production areas) [6, 7], whereas cases in

Abbreviations: CAS, chromazurol S; CF, clumping factor; EC,

extracellular; GapDH, glyceraldehyde-3-phosphate dehydrogen-

ase; OMP, outer membrane protein; PDA, potato dextrose agar;

SF, surface-associated; SOD, superoxide dismutase; WHC,

whole-cell

Correspondence: Dr. Kathrin Riedel, Department of Micro-

biology, Institute of Plant Biology, University of Zurich, Winter-

thurerstrasse 190, CH-8057 Zurich, Switzerland

E-mail: kriedel@botinst.uzh.ch

Fax: 141-44-635-2920

& 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

3564 Proteomics 2009, 9, 3564–3579DOI 10.1002/pmic.200900016

which the organism has been isolated from the rhizosphere

or other natural environments [8] are rare. However, the

natural reservoir of this opportunistic pathogen remains

unknown.

Recently, it has been shown that some strains are able to

adhere to human epithelial and endothelial cells [9]. More-

over, Cronobacter sp. is capable of infecting and persisting in

human macrophages [10]. It is expected that bacterial viru-

lence factors such as toxins, iron chelators, secretion

systems and immune system evasion mechanisms are

involved in the infection process. However, only a few

studies have analysed virulence factors of Cronobacter sp.: (i)

certain strains of Cronobacter sp. have been demonstrated to

produce an enterotoxin, which is lethal for suckling mice

when injected intraperitoneally [11, 12], (ii) Mokracka et al.[13] showed that some Cronobacter species are able to

produce enterobactin, an iron-chelating compound, that

enables the strain to acquire the vital micronutrient under

iron-limiting conditions, (iii) Townsend et al. [10] speculated

whether superoxide dismutase (SOD) activity contributes to

Cronobacter sp. intracellular persistence and (iv) recent work

has shown that the Cronobacter sp. outer membrane

protein A (OmpA) is involved in the invasion of human

intestinal epithelial and brain endothelial cells [14, 15].

Nevertheless, detailed knowledge about the molecular

mechanisms involved in Cronobacter sp. pathogenicity is still

missing.

Screening of mutant libraries for mutants that are

impaired in persistence and/or infectivity in various patho-

genicity models [16, 17] is widely used to discover genes

coding for potential virulence factors. In case of Cronobactersp., investigations on the infection mechanism(s) are

hampered by the lack of a meaningful infection model [18].

Young pigs, rabbits and guinea pigs have been tested but

were found to be unsuitable as infection models [18].

Although not ideal, two mammalian infection models are

frequently employed: (i) neonatal rats used to mimic

meningitis by infecting the animals with intra-peritoneal

[10] and (ii) neonatal gerbils used to mimic oral infections.

However, high bacterial doses (109 CFU) are required to

establish an infection [18].

As an alternative approach to identify putative virulence

factors and to gain insights into the physiology and meta-

bolic versatility of Cronobacter sp. we thought to employ high

throughput proteomics. Moreover, a comprehensive

mapping of the bacterial proteome can contribute to the

detection of diagnostic biomarkers, construction of vaccines

or the development of novel antimicrobial therapies as it has

been demonstrated for other pathogenic organisms [19–21].

Former studies employed mainly 2-DE to analyse the entire

protein complement of microorganisms. More recently, the

combination of complementary proteomics technologies,

integrating gel-based and gel-free approaches, proved

increasingly useful to obtain high proteome coverage (e.g.34% of the Bacillus subtilis proteome [22] and 38% of the

Escherichia coli proteome [23]).

In this study, Cronobacter turicensis 3032, a strain that

caused the death of two new-born children [9], was chosen to

map the proteome of a representative and evidently patho-

genic member of the genus Cronobacter. Bacterial virulence

factors, which play an essential role in colonisation of host

cells, are often secreted into the extracellular (EC) medium

or expressed on the cell surface. To cover the entire

proteome of C. turicensis we thus decided to employ two

complementary shotgun proteomics approaches, a robust

one-dimensional gel electrophoresis combined with liquid

chromatography and electrospray ionization tandem mass

spectrometry (1D-SDS-PAGE-LC-ESI-MS/MS) to identify

EC and surface-associated (SF) proteins and a high-resolving

two-dimensional liquid chromatography coupled to matrix

assisted laser desorption/ionisation time-of-flight tandem

mass spectrometry (2D-LC-MALDI-TOF/TOF) to analyse

the complex whole-cell (WHC) protein fraction of

C. turicensis. The comprehensive characterisation of the

entirety of expressed proteins will contribute to unravel the

molecular mechanisms underlying virulence and persis-

tence of this opportunistic pathogen.

2 Materials and methods

2.1 Bacterial culture conditions

C. turicensis 3032 ( 5 LMG 23827T (BCCM/LMG, Ghent,

Belgium)) was grown in LB medium [24] under vigorous

agitation at 371C. For 1D-PAGE-LC-ESI-MS/MS and 2D-LC-

MALDI-TOF/TOF sample preparation bacterial cultures

were grown in 1 L and 0.2 L cultures, respectively, until the

transition from late exponential to stationary growth phase

(OD600 of 4.0–6.0, see also Supporting Information Fig. S1)

at two different temperatures: 251C, mimicking growth, e.g.in food production sites and 371C, imitating growth in the

human body. Each growth experiment was performed three

times. Growth was monitored spectrophotometrically by an

Ultrospec Plus spectrophotometer (GE Healthcare) by

measurement of OD at 600 nm. Cells were harvested by

centrifugation at 6000 � g for 30 min at 41C. After extraction

(see section 2.2) proteins derived from the 25 and 371C

cultures were pooled to keep the number of samples in a

manageable range.

2.2 Protein extraction

2.2.1 EC proteins

For the preparation of EC proteins culture supernatants

were sterile filtered (Nalgene Labware, 0.2 mm pore size) and

the proteins were precipitated with 18% w/v trichloroacetic

acid at 41C overnight. The precipitate was harvested by

centrifugation (41C, 12 500 � g, 1 h) and washed twice with

acetone. For 1D-PAGE-LC-ESI-MS/MS sample preparation,

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the pellet was dried, resolved in 50 mM Tris/HCl, pH 7.5

and phenol extracted as described before [25]. The final

protein pellet was solubilised in 200 mL sample buffer (8 M

urea, 2% w/v CHAPS, 15 mM DTT). For 2D-LC-MALDI-

TOF/TOF sample preparation the pellet was kept at �201C

in acetone until it was finally resolved in 500 mM triethy-

lammonium bicarbonate buffer, pH 8.5 containing 0.05%

w/v SDS.

2.2.2 Cell surface proteins

SF proteins were extracted as described before [25].

Briefly, the cell pellet was washed twice with 50 mM Tris/

HCl, pH 7.5 and resuspended in 0.2 M glycine

hydrochloride, pH 2.2 (100 mL per 4 g pellet). The suspen-

sion was stirred at room temperature for 15 min and cells

were removed by centrifugation at 5500 � g for 20 min at

41C. The supernatant was neutralised with 10 M NaOH to

pH 7.5 and the extracted proteins were precipitated with

threefold volume of acetone at �201C overnight.

The precipitate was harvested by centrifugation (17 000 � g,

1 h, 41C), washed once with ethanol and once with

acetone and resolved in 50 mM Tris/HCl, pH 7.5. One

millilitre of aliquots was extracted with phenol as described

for the EC proteins [25]. The final pellet was resuspended

in sample buffer (8 M urea, 2% w/v CHAPS and 15 mM

DTT).

2.2.3 WHC proteins

For the preparation of WHC proteins the cell pellet was

resuspended in 100 mM HEPES buffer, pH 7.5 supple-

mented with 1% v/v Triton X-100 and protease inhibitor

(Protease Inhibitor Cocktail, Roche). Cell lysis was

performed by sonication using a Bandelin Sonopuls

HD2027 for 10 min at 6� 10% cycles and 40% power. Lysis

was controlled microscopically. Cell debris was separated

from the protein supernatant by centrifugation (17 000 � g,

1 h, 41C). Proteins were precipitated with six volumes ice-

cold acetone at �201C overnight. The precipitate was

harvested by centrifugation (12 500 � g, 1 h, 41C) and

washed once with ice-cold acetone. Proteins were kept at

�201C in acetone until they were finally resolved in 500 mM

triethylammonium bicarbonate buffer, pH 8.5 containing

0.05% w/v SDS.

2.2.4 Analytical procedures

Total protein concentrations were determined according to

the method of Bradford [26] using the Coomassie PlusTM

Protein Assay (Pierce). The absorbance was measured at

595 nm. The protein concentration was calculated using

BSA as standard.

2.3 Protein identification by MS

2.3.1 1D-PAGE-LC-ESI-MS/MS

2.3.1.1 Sample preparation

An aliquot (10 mg) of EC or SF proteins was separated using

standard SDS-PAGE [27]. Protein bands were excised from

the gel and digested with trypsin as follows: the excised gel

pieces were destained using 50% v/v methanol in 100 mM

(NH4)HCO3. Proteins were reduced in 50 mM (NH4)HCO3

containing 10 mM DTT for 30 min at 601C and carbamido-

methylated with 50 mM (NH4)HCO3 containing 50 mM

iodacetamide for 15 min in the dark at room temperature.

Subsequently, gel pieces were dehydrated with 100% ACN

and allowed to dry. Modified trypsin (sequencing grade,

Promega) was added in a concentration of 10 ng/mL in

25 mM (NH4)HCO3 and incubated at 371C overnight.

Peptides were extracted from the gel using 1 and 10% (v/v)

formic acid. Supernatants containing peptides were kept;

pooled and dried using a Speedvac concentrator (Eppendorf

AG). Samples were subsequently resolved in buffer A (5%

v/v ACN, 0.1% v/v formic acid) and desalted using ZipTips

(C18, Millipore).

2.3.1.2 LC-ESI-MS/MS

After ZipTip desalting, samples were resuspended in 5% v/v

ACN, 0.2% v/v formic acid and loaded onto a reverse-phase

capillary column (RP C18, 75mm� 8 cm; 200 A, AQ;

Bischoff GmbH) using a fully automated nanoflow LC

system consisting of a PAL autosampler (CTC Analytics AG)

and a binary Rheos 2000 pump (Thermo Scientific). Liquid

chromatography was performed using a 90-min gradient

using solvents A (5% v/v ACN, 0.2% v/v formic acid) and B

(80% v/v ACN, 0.2% v/v formic acid). Peptides were eluted

with the following linear gradient: 0–3 min, 0% solvent B;

3–53 min, 0–50% solvent B; 53–63 min, 50–100% B followed

by 100% B for 4 min and 100% A for 23 min. Average flow at

the tip was 0.25 mL/min after splitting. The LC system was

directly coupled to an ion trap mass spectrometer (LCQ

Deca, Thermo Scientific), equipped with a nanospray ioni-

zation source. Each MS full scan was followed by the

acquisition of up to three data-dependent MS/MS spectra of

the three most intense peaks. Parent masses used for MS/

MS were dynamically excluded for 0.5 min.

2.3.2 2D-LC-MALDI-TOF/TOF-MS

2.3.2.1 Trypsin digestion of proteins

Fifty microgram of EC or WHC proteins was reduced with

1 mM tri-(2-carboxyethyl) phosphine for 1 h at 601C.

Cysteines were blocked with 20 mM methyl methane thio-

sulfonate for 10 min at room temperature. Subsequently,

10 mL of sequencing grade modified trypsin solution

(Promega, 10 ng/mL in MilliQ) were added and the samples

were incubated at 371C overnight.

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2.3.2.2 LC-SCX fractionation

Peptide samples were dried in a Speedvac concentrator, resolved

in buffer A (10 mM KH2PO4, 25% v/v ACN, pH 2.5–2.7), and

separated with an Agilent 1100 Series Nanoflow Proteome

Solution System equipped with a Poly-sulpho-ethyl A

200� 2.1 mm2 300 A column (PolyLC). Liquid chromatography

was performed with a flow rate of 0.3 mL/min using the

following gradient: 0–10 min, 100% buffer A; 10–40 min, 40%

buffer B; and 40–58 min, 100% buffer B (10 mM KH2PO4, 25%

v/v ACN, 0.35 M KCl, pH 2.5–2.7). After 23 min, 700mL frac-

tions were collected for 60 min. Fractions were vacuum dried,

pooled and cleaned using C18 Sep-Pak cartridges (Waters,

Milford, MASS, USA). Twenty-seven fractions were combined

to five (WHC proteins) or four (EC proteins) pools.

2.3.2.3 Nano-LC separation and MALDI target spot-ting of tryptic peptides

A second peptide separation was performed on an Ultimate

chromatography system (Dionex-LC Packings) equipped with a

Probot MALDI spotting device. Five microlitres of the pooled

SCX-fractions were injected by using a Famos autosampler

(Dionex-LC Packings) and loaded directly onto a 75mm� 150

mm reversed-phase column (PepMap 100, 3mm; Dionex - LC

Packings). Peptides were eluted at a flow rate of 300 nL/min by

using the following gradient: 0–10 min, 0% solvent B;

10–105 min, 0–50% solvent B and 105–115 min, 50–100%

solvent B. Solvent A contained 0.1% v/v TFA in 95:5 water/ACN

and solvent B contained 0.1% v/v TFA in 20:80 water/ACN. For

MALDI analysis, the column effluent was directly mixed with

MALDI matrix (3 mg/mL a-cyano-4-hydroxycinnamic acid in

70% v/v ACN/0.1% v/v TFA) at a flow rate of 1.1mL/min via a

m-Tee fitting. Fractions were automatically deposited every 10 sec

onto a MALDI target plate (Applied Biosystems, Foster City,

CA) using a Probot micro fraction collector. A total of 416 spots

were collected from each HPLC run.

2.3.2.4 MALDI-TOF/TOF mass spectrometry

MALDI plates were analysed on a 4800 MALDI TOF/TOF

system (Applied Biosystems) equipped with an Nd:YAG laser

operating at 200 Hz. All mass spectra were recorded in positive

reflector mode and generated by accumulating data from 800

laser shots. First, MS spectra were recorded from peptide

standards on each of the eight calibration spots and the default

calibration parameters were updated. Second, MS spectra were

recorded for all sample spots on the MALDI target plate (416

spots per sample, 4 samples per plate). The MS spectra were

recalibrated internally based on the ion signal of neurotensin

peptide (Sigma). Spectral peaks that met the threshold criteria

were included in the acquisition list for the MS/MS spectra. The

following threshold criteria and settings were used: Mass range:

800–4000 Da; minimum S/N for MS/MS acquisition: 100;

maximum number of peaks/spot: 8. Peptide CID was

performed at a collision energy of 1 kV and a collision gas

pressure of approximately 2.5� 10�6 Torr. During MS/MS data

acquisition, a method with a stop condition was used. In this

method, a minimum of 1000 shots (20 sub-spectra accumulated

from 50 laser shots each) and a maximum of 2000 shots (40

sub-spectra) were allowed for each spectrum. The accumulation

of additional laser shots was halted whenever at least six ion

signals with an S/N of at least 60 were present in the accu-

mulated MS/MS spectrum, in the region above m/z 200.

2.4 Data analysis

2.4.1 Database searching of 1D-PAGE-LC-ESI-MS/

MS data

MS and MS/MS data obtained by ESI-MS/MS were analysed

using MASCOT version 2.2.0 (Matrix Science) and X! Tandem

version 2007.01.01.1 (www.thegpm.org) by searching a data-

base containing all 4692 annotated proteins of Cronobactersakazakii ATCC BAA-894 (http://www.ncbi.nlm.nih.gov/

sites/entrez?db 5 genome&cmd 5 Retrieve&dopt 5 Overview

&list_uids 5 21336) as well as various keratin and trypsin

contaminants. Database searching was performed with the

following parameters: trypsin digestion of proteins (maximal

two missed cleavages allowed), a fragment ion mass tolerance

of 0.800 Da MASCOT and X! Tandem, a parent ion tolerance

of 3.0 Da, Pyro-glu from glutamine of the N-terminus,

S-carbamoylmethylcysteine cyclization of the N-terminus and

oxidation of methionine were specified in MASCOT and X!

Tandem as variable modifications.

Scaffold (version Scaffold_2_1_03, Proteome Software) was

used to validate MS/MS based peptide and protein identifica-

tions. Peptide identifications were confident when their prob-

ability was 495% as specified by the Peptide Prophet algorithm

[28]; protein identifications were confident if their probability

was 495%, contained at least 1 identified peptide and were

found in at least two of three replicates. Protein probabilities

were assigned by the Protein Prophet algorithm [29]. Proteins

that contained similar peptides and could not be differentiated

based on MS/MS analysis alone were grouped to satisfy the

principles of parsimony.

False positive identification rates were evaluated on a subset

of all data using a concatenated forward and reversed protein

database. False discovery rate was calculated by multiplying the

number of passing decoy hits by two and divided by all protein

hits passing the threshold. For the Scaffold workflow we

calculated a false discovery rate of about 3.5% for the SF and

3.0% for the EC fraction on the protein level prior filtering

proteins that were discovered in only one replicate.

2.4.2 Database searching of 2D-LC-MALDI-TOF/TOF

data

Protein Pilot Software 2.0.1, software revision number 50861

(Applied Biosystems) was used for submitting data acquired

with the MALDI-TOF/TOF mass spectrometer for database

searches. If not stated otherwise, the software default settings

were used. The MS/MS data were searched using the

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ParagonTM algorithm [30] as the search engine. The following

search settings were used: Methyl methanethiosulfonate deri-

vatisation of cysteine was specified as fixed modifications.

Trypsin was chosen as digesting reagent. Amino acid substi-

tutions were given as a variable modification. Search effort was

set to ‘‘thorough’’. Data were searched against the database

mentioned in 2.4.1. The protein confidence threshold cut-off

for this study is ProtScore 1.3 (which corresponds to a confi-

dence of 95% on the protein level) with at least one peptide

with 95% confidence. Protein grouping was performed by the

ProGroupTM algorithm within the ProteinPilotTM software

before final display.

Proteins were accepted if they were found in at least two

of three replicates with a protein threshold of 95%. Only

proteins identified by at least one unique peptide were

considered in the analysis. Decoy false discovery identifica-

tion rates were 1.6% for the whole cell fraction and 2.5% for

the EC fraction on the protein level.

2.4.3 In silico analysis of cellular protein localisation

All identified proteins were analysed by SignalP Version 3.0

(http://www.cbs.dtu.dk/services/SignalP/; [31]), Cello

Version 2.5 (http://cello.life.nctu.edu.tw/; [32]), PSORTb

Version 2.0.4 (http://www.psort.org/psortb/; [33]), and

Proteome Analyst Version 3.0 Beta (http://pa.cs.ualberta.

ca:8080/pa/pa/index.html, [34]) algorithms to determine

their subcellular localisation. Cello was able to rate the

subcellular localisation of 86% of all proteins of the recently

sequenced strain C. sakazakii BAA-894, and was thus

perfectly suited to predict the cellular origin of proteins

identified in this study.

2.4.4 Functional assignment of proteins

Proteins were assigned to functional categories based on

clusters of orthologous groups of proteins (COG; http://

www.ncbi.nlm.nih.gov/COG/) and integrated into cellular

processes and metabolic pathways by employing the Kyoto

Encyclopaedia of Genes and Genomes (KEGG, http://

www.genome.jp/kegg/kegg1.html) or the Pathway Tools

Software Version 12.5 (http://bioinformatics.ai.sri.com/

ptools/; [35]).

2.5 Phenotypic assays

2.5.1 Detection of siderophores

Chromazurol S (CAS, [36]) agar was employed to test the

production of siderophores by C. turicensis. On CAS agar

plates a colour change from blue to orange indicates side-

rophore producing bacteria due to Fe31 removal from the

dye.

2.5.2 Detection of SOD activity

SOD activity was determined as described by Kukavica et al. [37].

Bacteria were grown in 30 mL LB media under vigorous agita-

tion for 4, 6, 8 and 18 h. Cells were harvested by centrifugation;

the supernatant was sterile filtered (Nalgene Labware, 0.2mm

pore size) and concentrated using a Vivaspin tube (5000 MW cut

off; Sartorius Biolab Products). EC SOD activity was determined

by specific staining of a native PAGE gel as described by

Beauchamp and Fridovich [38]. Briefly, concentrated super-

natant was loaded in a 10% native-PAGE gel and proteins were

separated with 25 mA for 2 h. After electrophoresis, gels were

incubated in reaction mixture (0.1 M EDTA, 0.098 mM NBT,

0.030 mM riboflavin and 2 mM TEMED in 0.1 M potassium-

phosphate buffer, pH 7.8) for 30 min in the dark. Subsequently,

the gel was washed in distilled water and incubated for 15 min

under dim day light until a violet colour appeared.

2.5.3 Evidence of clumping factor production

C. turicensis 3032 cells were tested for the production of

clumping factor (CF) as described before [39] by mixing a

drop of bacterial culture with rabbit plasma in EDTA

(Remel) on a glass slide, which was then slowly agitated. In

presence of CFs plasma clumping can be observed.

2.5.4 Galleria mellonella killing assay

Overnight cultures of the test strain C. turicensis 3032, the

negative control E. coli JM83 and the positive control Xenor-habdus nematophila ATCC 19061 (American Type Culture

Collection, Rockville) were inoculated in 5 ml LB, grown at 371C

under vigorous agitation and harvested after 2 h by centrifuga-

tion (6000 � g, 20 min, 41C). The cell pellets were then resus-

pended in 10 mM MgSO4. To determine the minimal number

of C. turicensis cells that had a visual effect on G. mellonella larvae

different concentrations (OD600) were tested (data not shown);

for in-depth analysis a concentration of OD600 of 1.0

(�7� 108 CFU/mL) was chosen. Larvae were injected via the

hindmost proleg with 10mL of C. turicensis, X. nematophila,

E. coli or sterile 10 mM MgSO4 solution; six insects were

infected per condition. Before and after injection a cotton swab

soaked in 70% ethanol was used to disinfect the injection site.

After injections larvae were incubated at 371C. The number of

dead larvae was scored 24, 48, 72 and 96 h after infection. Larvae

were recognized as dead if they turned dark due to melanisation

and/or did not respond to touch. Data are mean values of three

independent experiments.

2.5.5 Antifungal activity in vitro

Antagonistic activity of C. turicensis 3032 against Aspergillusnidulans (Austrian Center of Biological Resources and

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Applied Mycology no. MA5366) was assayed on potato

dextrose agar (PDA) and malt extract agar. A 5 mm agar

inoculum of A. nidulans was placed on the Petri dishes and

cultivated for 2 days at 251C in the dark. Subsequently, 10mL

of overnight cultures of C. turicensis 3032, E. coli JM83

(negative control), and chitinase-producing strain Serratialiquefaciens MG1 (positive control; [40]) were spotted on

three positions on the plate and cultivated at 371C in the

dark. Inhibition zones were recorded after 6 days.

3 Results and discussion

3.1 Protein extraction and analysis

It has been shown that cell-surface and secreted proteins

play an important role in bacterial virulence by mediating

interactions between pathogen and host cells [41, 42].

Therefore, the proteome of C. turicensis was separated into

EC, SF and WHC proteins prior to analysis as depicted in

the workflow (Fig. 1). Subsequently, two high-throughput

proteomics approaches, 1-D SDS-PAGE coupled to LC-ESI-

MS/MS (PAGE-LC-MS) and 2-D LC coupled to MALDI-

TOF-TOF-MS (2D-LC-MS), were applied to identify proteins

of all sub-cellular fractions aiming at a comprehensive

mapping of the C. turicensis 3032 proteome. EC and SF

proteins were analysed by robust PAGE-LC-MS, whilst 2D-

LC-MS was employed to identify WHC proteins as it exhi-

bits an enormous resolving power and is ideally suited to

analyse highly complex samples. In our hands, the gel-free

approach employing a 4800 MALDI TOF/TOF mass spec-

trometer appeared to detect lower protein amounts than the

gel-based approach and thus the EC proteins were addi-

tionally analysed by 2D-LC-MS to allow identification of low

abundant proteins. As a matter of fact, 123 EC proteins were

detected by PAGE-LC-MS, whereas the gel-free approach

identified 322 secreted proteins (Fig. 2A).

The comprehensive analysis of the different cellular

fractions resulted in the identification of 832 different

proteins based on 9424 different peptides (Supporting

Information Table S1), corresponding to 19% of all predic-

ted proteins of the recently sequenced strain C. sakazakiiBAA-894. Although our analysis did not reach the

impressing 38% proteome coverage obtained for E. coli [23],

pre-fractionation and application of complementary proteo-

mics approaches achieved a remarkably high coverage of the

C. turicensis 3032 proteome. Presumably, the number of

identified proteins would have been even higher if the MS

data could have been searched in an appropriate, but yet not

available, data set based on the genomic sequence of the

C. turicensis strain used in this study.

C. turicensis 3032 culture

snietorp-CHWsnietorp-FS EC-proteins

protein separation1D-SDS-PAGE

in gel trypsin digestion

peptide separation by RP C18

ESI-MS/MS

trypsin digestion

peptide separationSCX & RP C18

MALDI-Tof/Tof

PAGE-LC-MSidentified

SF proteins

PAGE-LC-MSidentified

EC proteins

2D-LC-MSidentified

EC proteins

2D-LC-MSidentified

WHC proteins

Figure 1. Schematic overview of the C. turicensis 3032 proteome

analysis workflow. Three biological replicates were analysed

within every experiment. SF, surface-associated; EC, extra-

cellular; WHC, whole-cell; SCX, strong cation exchange chro-

matography; RP C18, reverse phase C18 liquid chromatography.

ECPAGE-LC-MS

SFPAGE-LC-MS

WHC2D-LC-MS EC

2D-LC-MS

47530

153

3455

33

7

6

514

3

6

63

2

Cytoplasmic or unknownno signal peptide Extracellular or

cell-envelopesignal peptide

Cytoplasmic or unknownsignal peptide

Extracellular or cell- envelopeno signal peptide

24%36%

33%6%

A

B

Figure 2. (A) Venn diagram of the overlap of identified proteins

from different cellular fractions and methodological approaches.

The value within overlapping circles indicates the number of

proteins that have been found in one, two, three or all four

groups. Figure was not drawn to scale. (B) Prediction of cellular

localisation and presence of type II and V secretion system signal

peptides by the software packages Cello and SignalP 3.0 for

proteins that have been exclusively identified in the EC and SF

proteome. Proteins for which ‘‘cell-envelope’’ localisation was

predicted comprise periplasmic, outer membrane, SF and

secreted proteins.

Proteomics 2009, 9, 3564–3579 3569

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3.2 Subcellular location of identified proteins

Although we tried to avoid cross-contaminations, 37% of all

identified proteins were found in more than one cellular

fraction (Fig. 2A). The significant contamination of EC and

SF fractions by WHC proteins is most probably due to cell

lysis during protein extraction and has been observed before

in several other proteomics studies, e.g. [25, 43]. However, 6

and 40 proteins (Fig. 2A) were found to be exclusively

present in the SF and EC protein fraction, respectively, and

would have remained undiscovered in a simple WHC

protein analysis. A prediction of the cellular location of the

identified proteins with the Cello software (see section 2.4.3)

revealed that we have identified 23% (573) of the (predicted)

cytoplasmic proteins, 21% (21) of the OMPs, 32% (124) of

the periplasmic proteins and 24% (18) of the EC proteins

(numbers refer to proteins of C. sakazakii BAA-894;

Supporting Information Table S1).

The fact that 43% of the identified proteins, which were

exclusively detected in the EC and SF sub-cellular fractions, are

predicted to contain a type II or type V secretion system signal

peptide and to be located EC or on the cell surface (Fig. 2B)

confirms their cellular origin. Seven percent of the proteins that

were only identified in supernatant or surface fractions was

predicted to contain a signal peptide by SignalP, but their

cellular localisation was either unpredictable or cytoplasmic

according to Cello. For the majority of the EC and SF proteins

no signal peptide was found and the cellular localisation was

predicted as either EC/cell-envelope (33%) or cytoplasmic/

unknown (24%). The presence of proteins designated as

‘‘cytoplasmic’’ on the cell-surface or in the culture supernatant is

likely explained by cell lysis of a small proportion of the culture.

However, gene products lacking type II or V signal sequences

with unpredictable or EC localisation, which have been exclu-

sively found in the culture supernatant (e.g. the hypothetical

proteins ESA_00836, ESA_02956, ESA_03047, ESA_03061)

might be exported via alternative transport systems, e.g. the

postulated type VI secretion system (see section 3.8) or type I, III

or IV secretion systems.

3.3 Functional classification of identified proteins

Ninety-five percent of all identified proteins could be

assigned to functional categories according to COG (Fig. 3)

and are involved in various processes. Most of the proteins

belong to the following categories: translation (11.1%),

energy production and conversion (10.1%), amino acid

transport and metabolism (9.4%), carbohydrate transport

and metabolism (8.5%), and posttranslational modification

and chaperones (7.1%). Moreover, integration of the iden-

tified proteins into metabolic pathways revealed that most of

the central metabolic pathways are well represented (Fig. 4,

see also section 3.5). Remarkably, the proteome coverage is

most comprehensive for the translational apparatus; we

identified 46 of 47 ribosomal proteins (Supporting Infor-

mation Fig. S2) and 21 of 28 aminoacyl-tRNA biosynthesis

proteins (Supporting Information Fig. S3) that have been

predicted for C. sakazakii BAA-894. A similar high coverage

of proteins involved in translational processes has been

observed in B. subtilis, where 89% of the aminoacyl-tRNA

synthetases and 83% of the translation elongation factors

have been identified [44]. About 20% of the identified

proteins have been annotated as hypothetical or putative in

C. sakazakii BAA-894. Our study therefore provides the first

biochemical confirmation that they are actually expressed in

C. turicensis. In the following paragraphs selected functional

categories will be discussed in detail.

0.1

11.1

3.7

2.4

0.7

5.6

1.9

7.1

2.6

1.2

10.1

9.4

4.4

8.5

3.7

3.2

3.1

0.6

6.9

8.1

5.4

0.0 2.0 4.0 6.0 8.0 10.0 12.0

RNA processing and modification

Translation

Transcription

Replication, recombination and repair

Cell cycle control, mitosis and meiosis

Cell wall/membrane biogenesis

Cell motility and secretion

Posttranslational modification, chaperones

Signal transduction mechanisms

Intracellular trafficking and secretion

Energy production and conversion

Amino acid transport and metabolism

Nucleotide transport and metabolism

Carbohydrate transport and metabolism

Coenzyme transport and metabolism

Lipid transport and metabolism

Inorganic ion transport and metabolism

Secondary metabolites metabolism

General function prediction only

Function unknown

Not in COGs

Percent of proteins per category (%)

Information storage and processing

Poorly characterized

Metabolism

Cellular processes and signaling

Fu

nct

ion

al c

ateg

ory

Figure 3. Percentage of

identified proteins belong-

ing to different function

categories according the

COG functional annotation

of NCBI.

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3.4 Cell envelope and transporters

As neither PSORTb nor Cello Software was able to predict

all OMPs, putative OMPs were manually analysed and the

results of both programs were combined. Manual annota-

tion resulted in a total of 30 OMPs, 8 of which represent

pore-forming proteins (OmpA, OmpC, OmpF, OmpW,

OmpX, PhoE, LamB and TolC; ESA_02391, ESA_00974,

ESA_02413, ESA_01556, ESA_02526, ESA_00083,

ESA_00373; Supporting Information Table S1). Porins are

mainly involved in diffusion control of small molecules

(sugars, ions or amino acids), but are also known as

multifarious proteins and can be involved in pathogenicity

[45] as discussed in section 3.8.

Periplasmic solute binding and transport proteins play an

important role in the metabolism of Gram-negative bacteria by

providing them with a wide variety of nutrients. Thirty ABC

transporter proteins, involved in amino acid, sugar, inorganic

compounds and peptide trafficking, were identified (Supporting

Information Table S1); among them amino acid transporters,

i.e. various arginine and glutamine/glutamate transporters

(ESA_02473, ESA_02477, ESA_00906, ESA_02529, ESA_02680)

and spermidine and putrescine transporters (ESA_02224,

ESA_02483). Amino acid degradation products as spermidine

and putrescine can be toxic if they accumulate within cells and

have to be excreted actively [46]. Notably, D-galactose

(ESA_00188), L-arabinose (ESA_01330) and maltose

(ESA_00081) transporters have been found even though the

growth medium contains (if at all) only traces of these sugars,

which Cronobacter sp. can use as sole carbon source [47, 48]. The

fact that C. turicensis produces these transporters in LB medium,

suggests that they are either constitutively expressed in this

organism or that trace amounts of inducing sugars are present

in the medium.

3.5 Central metabolism and energy production

As depicted in Fig. 4, proteins involved in central metabolic

pathways and energy production are highly represented (see

also Supporting Information Table S1), among them: (i) the

complete set of glycolysis enzymes (Supporting Information

Fig. S4), (ii) 10 out of 13 postulated C. sakazakii BAA-894

enzymes catalyzing reactions of the TCA cycle (Supporting

Information Fig. S5), (iii) 17 of 24 enzymatic components

involved in the pentose phosphate pathway (Supporting

Information Fig. S6), (iv) 10 of 12 proteins involved in mixed

acid fermentation (Supporting Information Fig. S7) and (v)

all subunits of the F-type ATPase (F0F1) complex (Support-

ing Information Fig. S8).

3.6 Stress response, protein folding and stability

Cytoplasmic, periplasmic or membrane-associated proteolytic

enzymes are vital for bacteria as they are able to degrade

needless, mis-folded or damaged proteins. Although these

proteases are produced at low levels under normal conditions,

various stresses can greatly induce their expression. In our

proteome analysis 14 of these housekeeping factors were iden-

tified: (i) the membrane-bound zinc metalloproteases HptX

(ESA_01421) and FtsH (ESA_03569), which contribute to the

Figure 4. Schematic overview of the assignment of proteins identified to the different branches of cellular metabolism created by the

Pathway Tools Software. Bold red lines represent identified proteins. Central processes are labelled with different colours according to the

description included in the figure.

Proteomics 2009, 9, 3564–3579 3571

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quality control of membrane proteins by degrading misas-

sembled gene products [49, 50]. (ii) The cytoplasmic proteases

Lon (ESA_02861) and ClpP (ESA_02859), which prevent the

formation of toxic protein aggregates during heat shock

response by degrading denatured proteins, and ClpA

(ESA_02456) and ClpX (ESA_02860), which present candidate

proteins to the ClpP enzyme [51, 52], (iii) the complex-forming

ATPase HslU (ESA_03829) and peptidase HslV (ESA_03828),

which mediate ATP-driven proteolysis during heat shock

response [53], (iv) two periplasmic serine proteases DegP

(ESA_03179) and DegQ (ESA_03620), which seem to be

involved in stress compensation [54] and (v) the two peptidases

TldE and TldD (ESA_00244, ESA_03632), which are suggested

to regulate DNA gyrase activity [55].

3.7 Motility and chemotaxis

Bacterial motility is mostly driven by flagella that consist of a

filament, basal body and motor [56]. We identified seven

filamental proteins (FliD, ESA_01287; FliC, ESA_01288;

FlgL, ESA_02264; FlgK, ESA_02265; FlgD, ESA_02272;

FlgE, ESA_ 02271; FliK, ESA_01255), 4 basal body proteins

(FlgG, ESA_02269; FlgF, ESA_02270; FlgC, ESA_02273;

FlgB, ESA_02274), but none of the motor proteins, most

probably due to their inner membrane localisation.

Chemotaxis enables motile bacteria to sense and respond to

changes in their environment and is crucial for metabolic,

symbiotic, infectious and other ecological interactions [57]. CheA

(ESA_01341), CheV (ESA_02190), CheW (ESA_01342), CheY

(ESA_01352), CheZ (ESA_01353), components of a two-

component signal transduction system, and the methyl-accept-

ing chemotaxis proteins MCP-I (ESA_03402) and MCP-III

(ESA_01710), have been found in the proteome.

3.8 Putative virulence factors

Potential virulence factors identified in this study

(summarized in Table 1) were classified according to their

assumed function and are described in the following para-

graphs. Putative pathogenic traits are involved in: (i) adhe-

sion, invasion and biofilm formation, (ii) iron acquisition,

(iii) protection against reactive oxygen species, (iv) secretion

and transport mechanisms and (v) insecticidal functions. No

proteolytic or lipolytic enzymes were detected in the secre-

tome. In accordance with this result we were also unable to

detect hydrolytic activity when C. turicensis was streaked on

casein or Tween 80 containing agar plates (data not shown).

3.8.1 Proteins involved in adhesion, invasion and

biofilm formation

Our proteomics analysis revealed the expression of the

FKBP-type peptidyl-prolyl cis-trans isomerase FkpA, also

designated as macrophage infectivity potentiator (MIP,

ESA_04394), in C. turicensis 3032. Several studies have

shown that MIP is involved in the persistence of Legionellapneumophila, Chlamydia trachomatis and Neisseria gonor-rhoeae in macrophages and other eukaryotic cells [58–60].

Recently, Townsend et al. [10] demonstrated the ability of

C. sakazakii to invade and persist in human macrophages.

Pre-treatment of C. turicensis with the MIP inhibitor FK506

resulted in a significant viability loss of the pathogen within

J-774 murine macrophages, which strongly suggests that

MIP contributes to the persistence of C. turicensis in

eukaryotic host cells (Iversen et al., unpublished).

The OmpA (ESA_02391) is known to participate in

various pathogenicity processes such as adhesion, invasion,

biofilm formation, evasion of host defences and acts as

immune reactant [45]. Two recent studies have demon-

strated that OmpA of C. sakazakii is required for the inva-

sion of intestinal epithelial and human brain microvascular

endothelial cells by inducing microtubule condensation [14,

45] and that OmpA mutants are significantly less invasive

than the wild type strain [15].

Moreover, an antigen 43 homologue (Ag43, ESA_02084)

was identified, known as type Va autotransporter protein

that promotes adhesion, auto-aggregation and biofilm

formation on abiotic surfaces and often constitutes an

important component of human vaccines [61, 62]. Interest-

ingly, OxyR, an Ag43 repressor protein, which is known to

inhibit Ag43 transcription by binding to unmethylated

regulatory DNA recognition sites [63], was also detected in

the proteome.

Two typical cytoplasmic proteins have been identified in

the EC protein fraction: enolase (ESA_00523) and glycer-

aldehyde-3-phosphate dehydrogenase (GapDH, ESA02170).

In good accordance with this result, it has been shown that

these enzymes are present on the cell surface or in the

supernatant of Streptococci, Staphylococcus aureus and

Listeria monocytogenes [64–66]; for the latter strain it has been

demonstrated that both proteins are able to bind plasmi-

nogen. Moreover, surface-expressed enolase of Aeromonashydrophila was shown to facilitate tissue-type plasminogen

activator (tPA) mediated activation of plasminogen to plas-

min [67]. One might therefore speculate that the C. turicensisenolase or GapDH are involved in adhesion to host blood

proteins. In order to test this hypothesis, rabbit plasma was

incubated with C. turicensis cells; a standard assay routinely

employed to test for the presence of the S. aureus CF. The

observation that C. turicensis provokes a moderate clumping

of rabbit blood cells (data not shown) suggests the presence

of surface proteins capable of binding fibrinogen. Additional

work will be required to investigate whether enolase or

GapDH or both are involved in this process.

Despite the observation that C. turicensis 3032 does not

exhibit any EC cellulolytic activity (data not shown), a

protein (ESA_04206) was exclusively identified in the WHC

proteome, which is identical to the endo-b-1,4-glucanase

BcsZ (CAM 32315.1) of C. sakazakii ES5 [68]. It has been

3572 P. Carranza et al. Proteomics 2009, 9, 3564–3579

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demonstrated that recombinant expressed BcsZ is able to

degrade carboxymethylcellulose. The fact that cellulose is

one of the major matrix compounds of C. sakazakii biofilms

and bcsZ is located in a cellulose biosynthesis operon [68]

suggest that the endo-b-1,4-glucanase does not degrade

plant cell wall-derived cellulose, but rather positively affects

cellulose synthesis as it has been demonstrated for the

endoglucanase CMCax of Gluconacetobacter xylinus [69].

Table 1. Identification of putative virulence factors that might be involved in C. turicensis pathogenicity

Protein designation C. sakazakiiBAA-894gene number

Accessionnumber

Cellular localisationpredicteda) experimentalb)

Referencec)

Adhesion, invasion, biofilm formation

Macrophage infection potentiator MIP ESA_04394 156936493 Periplasmic EC/SF/WHC [10, 58–60]Outer membrane protein A OmpA ESA_02391 156934557 Outer membrane EC/SF/WHC [45, 14, 15]Antigen 43 AG43 ESA_02084 156934254 Extracellular EC/SF/WHC [61, 62]Enolase ESA_00523 156932734 Cytoplasmic EC/SF/WHC [64–66]Glyceraldehyde-3-phosphate

dehydrogenase A GapDHESA_02170 156934339 Cytoplasmic EC/SF/WHC [64–66]

Endo-1,4-D-glucanase BscZ ESA_04206 156936306 Periplasmic WHC [68, 69]

Protection against reactive oxygen radicals

Superoxide dismutase SOD ESA_03843 156935949 Periplasmic EC/SF/WHC [10]Hydroperoxidase II (Catalase) ESA_02146 156934315 Unknown EC/WHC [84]Manganese catalase ESA_01872 156934046 Periplasmic EC/WHC [85]Delta-aminolevulinic acid dehydratase

HemBESA_02936 156935085 Cytoplasmic WHC [86]

Porphobilinogen deaminase HemC ESA_03753 156935870 Cytoplasmic WHC [87]Coproporphyrinogen III oxidase HemN ESA_04045 156936146 Cytoplasmic WHC [88]Uroporphyrinogen III C-methyltrans-

ferase HemXESA_03755 156935872 Periplasmic WHC [86]

Protoheme IX biogenesis protein HemY ESA_03756 156935873 Inner membrane WHC [86]Frataxin-like protein CyaY ESA_03751 156935868 Cytoplasmic WHC [88, 73]

Iron acquisition

Ferric enterobactin receptor FepA ESA_01552 156933726 Outer membrane EC [71]Bacterioferritin ESA_04406 156936505 Cytoplasmic WHC [89]Ferritin ESA_01318 156933498 Cytoplasmic WHC [70]Ferric uptake regulator FurA ESA_02653 156934813 Cytoplasmic EC/WHC [90]

Secretion and transport mechanisms

Preprotein translocase subunit SecA ESA_03240 156935382 Cytoplasmic WHC [91]Preprotein translocase subunit SecB ESA_04118 156936219 Cytoplasmic WHC [91]Preprotein translocase subunit SecG ESA_03566 156935697 Inner membrane WHC [91]Sec-independent translocase TatB ESA_03723 156935840 Unknown WHC [91]Serine/threonine protein kinase (T6SS) ESA_03920 156936026 Unknown WHC [92, 78]Chaperone ClpV (T6SS) ESA_03921 156936027 Cytoplasmic WHC [92, 78]ImpE homologe (T6SS) ESA_03925 156936031 Cytoplasmic WHC [92, 78]Forkhead-associated (FHA) protein (T6SS) ESA_03928 156936034 Periplasmic WHC [92, 78]Hemolysin coregulated protein Hcp (T6SS) ESA_03934 156936040 Extracellular EC/SF/WHC [92, 78]EvpB homologue (VCA0108 family, T6SS) ESA_03941 156936046 Cytoplasmic WHC [92, 78]SciH homologue (VCA0107 family, T6SS) ESA_03942 156936048 Cytoplasmic WHC [92, 78]VasK homologue (T6SS) ESA_03945 156936051 Outer membrane WHC [92, 78]Acriflavine resistance protein A AcrA ESA_02807 156934957 Unknown EC/WHC [93]

Outer membrane channel protein TolC ESA_00373 156932591 Outer membrane SF [93]

Hydrolytic enzymes

Extracellular metalloprotease Prt1 ESA_00752 156932949 Extracellular EC/WHC [80]Chitinase A1 ESA_03317 156935458 Extracellular EC/WHC [81]

a) Prediction of the cellular localisations were made with the Cello Software.b) EC, extracellular; SF, surface-associated; WHC, whole-cell indicate in which cellular fraction(s) the proteins were identified.c) References reporting a potential role of protein in the pathogenicity of Cronobacter sp. or other bacteria.

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3.8.2 Iron acquisition

Four proteins that seem to be involved in iron acquisition

and storage were identified (Table 1). In low-iron environ-

ments, e.g. mammalian host tissue bacteria employ sophis-

ticated mechanisms to compete for this essential

micronutrient. Notably, it has been demonstrated that the

pathogenic potential of some Enterobacteriae (i.e. Salmonellasp.) strongly depends on their ability to sequester iron [70].

Mokracka et al. [13] showed that Cronobacter sp. produce the

catecholic siderophore enterobactin, which enables the

bacteria to scavenge iron under limiting conditions.

Surprisingly, no enterobactin biosynthesis proteins were

found in the proteome; however, we identified the outer

membrane receptor FepA (ESA_01552), which is involved in

the cellular uptake of enterobactin [71]. In good accordance

with these results C. turicensis 3032 is positive for side-

rophore production on CAS agar plates (Fig. 5A). In the

cytoplasm iron accumulates often bound to specialized

proteins such as ferritin (ESA_01318) and bacterioferritin

(ESA_04406), which were both identified in the C. turicensis3032 WHC proteome. Finally, one further protein involved

in iron metabolism has been identified; FurA (ESA_02653),

a DNA-binding protein that regulates iron responsive genes.

3.8.3 Protection against reactive oxygen radicals

Our proteome analysis demonstrates that C. turicensis 3032 is

well armed against oxygen stress in eukaryotic host tissue.

SOD (ESA_03843), an enzyme involved in cellular protection

against toxic oxygen radicals, has been identified in all sub-

cellular fractions. These results are in good accordance with a

recent study of Townsend et al. [10], who measured SOD

activity in cell lysates of C. sakazakii spectrophotometrically.

Notably, we found highly active SOD in C. turicensis 3032

culture supernatants, albeit the enzyme does not contain a

typical transport signature. As shown in Fig. 5B SOD expres-

sion starts during early exponential growth, indicating that the

presence of this enzyme in the culture supernatant is not due

to cell lysis. Whether the enzyme is actively transported via an

alternative transport mechanism remains to be investigated.

Catalases protect bacterial cells against harmful hydrogen

peroxide by its decomposition to gaseous oxygen and water;

two potential catalases, a manganese catalase (ESA_01872)

and hydroperoxidase II (ESA_02146), were found in the

C. turicensis proteome. Heme, a tetrapyrrole heterocyclic

iron-containing ring, is essential for the functionality of

these enzymes. Five proteins (HemB, ESA_02936; HemC,

ESA_03753; HemN, ESA_04045; HemY, ESA_03756;

HemX, ESA_03755) were identified, which belong to a

cluster of seven proteins involved in the biosynthesis of

protoporphyrin IX, the non-ferrous precursor of heme, and

precorrin 2, an intermediate of the porphyrin metabolism.

Moreover, frataxin CyaY (ESA_03751), a small protein

providing iron-sulphur [Fe-S] cluster proteins with iron, was

identified in our proteome analysis. Recent studies

demonstrate that CyaY contributes to the cellular defence

against reactive oxygen species [72, 73].

3.8.4 Secretion and transport mechanism

The general secretion pathway (Sec) and the twin-arginine

translocation pathway (Tat) are responsible for the transport

of many proteins (among them many virulence factors and

cell appendixes) across the outer membrane of Gram-

negative bacteria (for review see [74]). We identified various

compounds of these protein translocation machineries:

the SecA ATPase (ESA_03240), the chaperone SecB

(ESA_04118), SecG (ESA_03566), a pore forming subunit of

the Sec system and TatB (ESA_03723) a subunit of the Tat

system.

Recently, a novel type VI secretion pathway (T6SS) has been

described for pathogens such as Pseudomonas aeruginosa,

Burkholderia mallei and Vibrio cholerae [75–77] that exports

proteins independently from the Sec translocase and N-terminal

signal peptides. In the genome of C. sakazakii BAA-894 a gene

cluster was found, which codes for various components of a

proposed T6SS (Fig. 6). Intriguingly, of 18 postulated T6SS

proteins 8 could be identified in our proteome analysis (Table 1,

Fig. 6), among them: (i) ESA_03920, a serine/threonine protein

kinase and ESA_03928, a FHA domain protein, both involved in

T6SS activation, (ii) ESA_03945 (VasK), involved in the adher-

ence to epithelial cells, (iii) ESA_03942 (SciH) implicated in

pathogenicity and protein secretion, (iv) ESA_03921 (ClpV), a

chaperone and (v) ESA_03934 (Hcp), an effector molecule

responsible for cytotoxicity (assigned functions adopted from

[78]). To our knowledge our report provides the first evidence

that Cronobacter employs a T6SS, albeit the transported effector

proteins remain to be elucidated.

Notably, two structural components of a multidrug-resistance

efflux pump belonging to the resistance nodulation division

family (reviewed in [79]) were identified: the periplasmic protein

AcrA (ESA_02807) and the outer membrane channel protein

TolC (ESA_00373). In clinical isolates of E. coli AcrAB–TolC

efflux pumps are often found to be overexpressed; their drug

substrate profile includes, e.g. chloramphenicol, fluoro-

quinolones, lipophilic b-lactam antibiotics, nalidixic acid, novo-

biocin, rifampin and tetracycline, acriflavine, ethidium bromide,

SDS, Triton X-100 and triclosan [79]. Interestingly,

C. turicensis 3032 exhibits resistance to chloramphenicol, nali-

dixic acid, SDS and Triton-X100 (data not shown). Whether

these antibiotic and biozidal compounds are indeed exported by

an AcrAB–TolC efflux pump system remains to be tested in

future experiments.

3.8.5 Hydrolytic enzymes

Two enzymes with potential proteolytic and chitinolytic activity

were identified in the proteome: metalloprotease Prt1

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(ESA_00752) and chitinase (ESA_03317). Prt1 belongs to the

metalloprotease M4 superfamily, shares 70% similarity to

protealysin and grimelysin of Serratia sp. and PrtS of Photo-rhabdus sp., respectively, and is involved in melanisation of

Drosophila melanogaster, Galleria mellonella and the tobacco

hornworm Manduca sexta [80]. The identified chitinase shares

58% similarity with a chitinase from Photorhabdus luminescens,which has been shown to hydrolyse b-1,4 bonds of N-acetyl-D-

glucosamine, a polysaccharide found in arthropodal exoskele-

tons and fungi [81]. We have therefore tested the effect of

C. turicensis 3032 on larvae of the greater wax moth G. mellonellaand the fungus Aspergillus nidulans. In the Galleria assay, a

characteristic melanisation on the back of the animals (Fig. 5C)

was observed. Moreover, after 72 and 96 h the number of dead

larvae was significantly higher than in the control group that

was treated with the avirulent strain E. coli JM83 (Fig. 5C).

Interestingly, C. turicensis 3032 also exhibited strong antifungal

activity when it was grown on malt extract agar or PDA agar in

presence of A. nidulans (Fig. 5D).

Considering these results together with the surprising

observation that C. turicensis 3032 does obviously not express

casein-degrading exoenzymes (data not shown) and the

recent finding, that the strain is able to colonize the rhizo-

sphere [82], it is tempting to speculate that the organism

evolved from a natural habitat.

4 Concluding remarks

The comprehensive proteome analysis of the opportunistic

food-borne pathogen C. turicensis 3032 by two independent

proteomics approaches (1D-SDS-PAGE-LC-ESI-MS/MS

and 2D-LC-MALDI-TOF/TOF) resulted in the identification

of 832 proteins corresponding to 19% of all theoretically

expressed proteins of C. sakazakii BAA-894. As

recently reported for the model organisms E. coli [23]

and B. subtilis [83] a major part of the identified proteins

comprise housekeeping enzymes involved in central meta-

bolic pathways such as glycolysis and TCA cycle, energy

conversion or belong to the translation machinery of the

cell.

Special attention was drawn to putative virulence deter-

minants, which might play an essential role during

C. turicensis infections; the expression of selected candidate

proteins was accessorily confirmed by phenotypical assays.

Among the most striking identified putative virulence

factors were: (i) MIP, a macrophage infectivity potentiator

protein, required for C. turicensis persistence in macro-

phages, (ii) surface-expressed enolase, which is able to bind

plasminogen and activate it to plasmin, thus leading to host-

tissue damage, bacterial penetration and invasion, (iii) SOD,

protecting the pathogen against reactive oxygen species

produced by its host, (iv) an enterobactin receptor protein,

involved in iron-acquisition under iron-limiting conditions

and (v) several components of a type 6 secretion system,

which might be involved in the secretion of so far unknown

effectors. Unfortunately, a thorough evaluation of the

impact of the identified virulence factors on C. turicensispathogenicity is difficult as all currently available model

systems have limitations and it is unclear to which degree

these models can be used to simulate the situation found in

an infected neonate. Nevertheless, our results provide strong

evidence that C. turicensis is armed to invade, persist and

even multiply in the human body, but we did not identify

BA

C

E. coli C. turicensis

E. coliControl X. nematophilaC. turicensis

C. turicensisE. coliC. turicensisE. coli

D

S. liquefaciensS. liquefaciens

Figure 5. Phenotypic assays confirming the expression of

putative virulence factors. (A) Siderophore production by

C. turicensis 3032 (right panel) visualized on CAS agar plates

after 16 h of growth at 371C, E. coli JM83 was used as negative

control (left panel). (B) Zymogram analysis of the presence of

SOD in supernatants of C. turicensis 3032 grown for 4, 6, 8 and

18 h. Colourless zones indicate enzymatic activity. (C) Insecticidal

effects of C. turicensis 3032 on larvae of the greater wax moth

G. mellonella. X. nematophila was used as positive control;

10 mM MgSO4 and E. coli JM83 were used as negative controls,

respectively. Results are the mean of at least three independent

experiments. The picture shows the typical melanisation pattern

observed for most animals after C. turicensis injection. (D)

Antifungal activity of C. turicensis 3032 against A. nidulans on

PDA (left panel) and malt extract agar (right panel). E. coli JM83

and the chitinase-producing S. liquefaciens MG1 were used as

negative and positive controls respectively. Pictures were taken

six days after inoculation of the fungus.

Proteomics 2009, 9, 3564–3579 3575

& 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

any pathogenic trait that would directly harm the host, such

as toxins or proteases.

An unexpected result of this study was the identification

of a chitinase, which might possess insecticidal and anti-

fungal activity. This finding together with the observation

that C. turicensis is not able to degrade casein and a recent

investigation that shows that the strain is able to colonize

the rhizosphere [82] suggest that the primary niche of this

strain may be the natural environment rather than the

production site of milk formula products.

Considering the following points it appears possible that

an even higher coverage of the Cronobacter sp. proteome

could be achieved: (i) the lack of genomic data has certainly

hampered the identification of strain-specific proteins; an

essential prerequisite for the detection of these proteins will

thus be the access to the C. turicensis 3032 genome

sequence. (ii) Alternative extractions and separation proto-

cols should be applied for the identification of inner

membrane proteins, most of which escaped our analysis.

(iii) It has to be considered that a substantial part of the

genome is exclusively expressed under specific conditions.

In spite of the limitations discussed previously in this

section, the presented data provide a comprehensive

proteomic database and open large scope for future studies

analysing the proteome of C. turicensis adhered to eukaryotic

host cells, grown under certain conditions (e.g. as biofilm),

or exposed to various environmental stresses, thereby

shedding further light on the molecular basis of Cronobactersp. persistence and pathogenicity.

We thank the Functional Genomics Center Z .urich for tech-nical support of the project, Ludwig Holzle for many helpfuldiscussions and experimental support, and Thomas Schneider

for critically reading the manuscript. The study was funded bythe Swiss National Science Foundation (Project 3100A0-110039).

The authors have declared no conflict of interest.

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