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: [email protected]
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.
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& 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com
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.
Proteomics 2009, 9, 3564–3579 3573
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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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