Modulation of
Enterohemorrhagic Escherichia coli
Virulence by the Global Regulator
System
Jong-Chul Kim
The Graduate School
Yonsei University
Department of Biomedical
Laboratory Science
Modulation of
Enterohemorrhagic Escherichia coli
Virulence by the Global Regulator
System
A Dissertation
Submitted to the Department of Biomedical
Laboratory Science and the Graduate School of
Yonsei University
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
Jong-Chul Kim
December 2008
This certifies that the dissertation of Jong-Chul Kim is approved.
Thesis Supervisor : Jong-Bae Kim
Yong-Suk Ryang : Thesis Committee Member
Ok-Doo Awh : Thesis Committee Member
Bok-Kwon Lee : Thesis Committee Member
Kwan-Hee Yoo : Thesis Committee Member
The Graduate School
Yonsei University
December 2008
“ But he knows the way that I take; when he has
tested me, I will come forth as gold.”
(Job 23: 10)
iii
CONTENTS
LIST OF FIGURES AND TABLES------------------------------------------ix
ABBREVIATION--------------------------------------- -----------------------xvi
ABSTRACT IN ENGLISH---------------------------------------------------xxi
CHAPTER I. Epidemiologic and molecular research on shiga
toxin-producing Escherichia coli isolated in Korea---------------------1
1. INTRODUCTION---------------------------------------------------2
2. MATERIALS AND METHODS--------------------------------10
STEC strains isolated from stool specimen-------------------10
Bacterial strains and culture condition for enterohemolysin
expression----------------------------------------------------------10
Detection of virulence genes by PCR--------------------------11
iv
Reversed-passive latex agglutination (RPLA) test for the
detection of Shiga toxin------------------------------------------12
Serotyping of O antigen------------------------------------------12
Antimicrobial susceptibility test--------------------------------13
Pulsed-field gel electrophoresis for STEC O157 strains----14
3. RESULTS------------------------------------------------------------16
Prevalence of STEC isolates------------------------------------16
Serotypes of STEC isolates--------------------------------------17
Stx genes and toxin production---------------------------------24
Charaterization of adherence genes----------------------------24
Resistance of antibiotics-----------------------------------------25
Relationship between hemolysin type and human patients
with manifestation------------------------------------------------32
PFGE pattern of STEC O157 isolates--------------------------37
4. DISCUSSION----------------------------------------------------------39
v
CHAPTER II. LuxS mediated quorum sensing and expression of
virulence in Escherichia coli O157:H7-----------------------------------50
1. INTRODUCTION--------------------------------------------------51
2. MATERIALS AND METHODS--------------------------------58
Bacteria and growth conditions---------------------------------58
Construction of an E. coli O157:H7 luxS mutant strain-----58
Construction of complemented strain with pEXEP5-CT----59
Growth curves-----------------------------------------------------59
Motility assays----------------------------------------------------60
RNA preparation--------------------------------------------------60
cDNA microarray-------------------------------------------------61
Data analysis------------------------------------------------------62
Transmission electron microscopic analysis (TEM)-------- 62
Cell adherence assay---------------------------------------------63
Amplification of LEE genes by reverse transcriptase real
vi
ime PCR------------------------------------------------------------63
Cytotoxicity assays-----------------------------------------------65
Determina t ion of cyto ly t ic act i v i t y for human
erythrocytes--------------------------------------------------------65
3. RESULTS------------------------------------------------------------67
Identification of luxS from clinical isolate EHEC strain----67
Growth and utilization of carbohydrates----------------------72
Influence of luxS mutation on swarming motility in EHEC
strain----------------------------------------------------------------75
Morphological analysis of flagella-----------------------------75
Adherence assays-------------------------------------------------76
Overview of microarray analysis-------------------------------82
Regulation by luxS/QS of the EHEC LEE genes-------------86
LuxS/QS regulates Stx expression-----------------------------92
Quorum sensing controls cytotoxicity for erythrocytes-----92
vii
4. DISCUSSION----------------------------------------------------------95
CHAPTER III. Quorum sensing contribute to proteomic changes of
Escherichia coli O157:H7--------------------------------------------------110
1. INTRODUCTION------------------------------------------------111
2. MATERIALS AND METHODS-------------------------------114
Preparation of secreted proteins and cellular proteins------114
SDS-PAGE-------------------------------------------------------115
Isoelectric focusing (IEF)--------------------------------------115
Two dimensional gel electrophoresis (2-DE)---------------116
In gel proteolytic digestion and MALDI-TOF--------------116
Data analysis-----------------------------------------------------117
Statical analysis--------------------------------------------------118
3. RESULTS----------------------------------------------------------119
Patterns of proteome in clinical isolate and standard
viii
strain--------------------------------------------------------------119
SDS-PAGE and 2-DE analysis of luxS/QS related
strains-------------------------------------------------------------119
Proteome profiling wild-type, luxS mutant and complement
strains-------------------------------------------------------------123
Influence of luxS mutation on protein expression in EHEC
O157:H7--------------------------------------------------------123
4. DISCUSSION---------------------------------------------------------137
CONCLUSIONS---------------------------------------------------------------145
REFERENCES-----------------------------------------------------------------148
ABSTRACT IN KOREAN---------------------------------------------------191
ix
LIST OF FIGURES AND TABLES
Figure I-1. Prevalence of patients with STEC infections and distribution
of sex in South Korea.-------------------------------------------- 19
Figure I-2. Monthly isolation of STEC, from 1998 to 2006.------- 21
Figure I-3. Frequencies of STEC isolated and the localization of South
Korea from 1998 to 2006.---------------------------------------- 23
Figure I-4. Amplification of virulence factors and adherence factor
associated genes in STEC.-------------------------------------- 27
Figure I-5. Antimicrobial resistance of 223 representative STEC strains in
South Korea.----------------------------------------------------------30
x
Figure I-6. PCR analysis for hemolysin genes and hemolytic activity
on sheep blood agar plate.---------------------------------------- 34
Figure I-7. Dendrogram of XbaI macrorestriction eletrophoretic patterns
of the 26 isolates of STEC O157.-------------------------------38
Figure II-1. Scheme of construction luxS mutant EHEC O157:H7
strain ------------------------------------------------------------69
Figure II-2. Growth curves of EHEC strains.------------------------------- 74
Figure II-3. Motility assays of EHEC strains.------------------------------- 77
Figure II-4. Measured halo and rated the differnce of motility.---------- 78
Figure II-5.Morphological analysis of flagella using by transmission
electron microscope.---------------------------------------------79
xi
Figure II-6. Adherence assay to Hep-2 cell.--------------------------------- 80
Figure II-7. Adherence assay to HeLa cell.---------------------------------- 81
Figure II-8. Microarray analysis of CI03J, RL03J and ML03J strains.- 84
Figure II-9. The amplification curves and DNA standard curve of gapA
gene.---------------------------------------------------------------87
Figure II-10. Cytotoxic activity of shiga toxin on Vero cells by WST
assays.-----------------------------------------------------------93
Figure II-11. Dose-response of hemolysis phenotypes.-------------------- 94
Figure III-1. 2-DE images of EDL933 (ATCC43895) EHEC O157:H7
and CI03J (clinical isolate) EHEC O157:H7.---------------121
Figure III-2. SDS-PAGE of proteins in CI03J, ML03J and RL03J.----122
xii
Figure III-3. Comparative 2-DE of soluble proteins fraction of
CI03J, ML03J and RL03J.-------------------------------125
Figure III-4. Cellular proteomes and secreted proteomes of strains.----126
Figure III-5. Two dimensional gel electrophoresis images of differntially
expressed proteomes in strrains.------------------------------127
Tabel I-1. Distribution of clinical manifestations and ages in patiients
with STEC infections in south Korea-----------------------------20
Table I-2. Serogroups of STEC strains isolated between 1998 and 2006
from patients in south Korea---------------------------------------22
Table I-3. PCR primers and conditions for amplification of STEC
xiii
virulence genes----------------------------------------------------26
Table I-4.Disribution of the stx genes and production of shiga toxins---28
Table I-5. Genotypic trait of STEC strains from diarrhreal patients in
south Korea---------------------------------------------------------29
Table I-6. Multidrug resistance of STEC isolates---------------------------31
Table I-7. Distribution of the hemolysin genes and relevant phenotypes
on sBAP-------------------------------------------------------------35
Table I-8. Relationship between hemolysin types and patients with
clinical signs-------------------------------------------------------36
Table II-1. Bacterial strains and plasmids used in this study--------------70
Table II-2. Oligonucleotides used in this study------------------------------71
xiv
Table II-3. Utilization of carbohydrates in strains---------------------------73
Table II-4. Fold induction of transcrit in response to luxS/QS as
determined by microarray---------------------------------------85
Table II-5. PCR primers used in qualitative and quantitative real-time
PCR assays--------------------------------------------------------88
Table II-6. Quantification of DNA in housekeeping gene, gapA---------90
Table II-7. Comparative to LEE genes using by quantitative real-time
PCR assay----------------------------------------------------------91
Table III-1.Cellular proteome profiles of CI03J, RL03J and ML03J---128
Table III-2. Secreted proteome profiles of CI03J, RL03J and ML03J-133
xv
Table III-3. Differentially expressed cellular proteins in CI03J, RL03J
strain compared to luxS mutant ML03J strain------------------------------135
Table III-4. Differentially expressed secreted proteins in CI03J, RL03J
strain compared to luxS mutant ML03J strain------------------------------136
xvi
ABBREVIATION
ACN : acetonitrile
A/E : attaching and effacing
AI : autoinducer
BSA : bovine serum albumin
DMEM : Dulbecco’s modified eagle’s medium
DNA : deoxyribonucleic acid
dNTP : deoxyribonucleotide triphosphate
DTT : dithiolthreitol
EDTA : erthylene diamine tetra acetic acid
xvii
EHEC : enterohemorrhagic Eschrichia coli
EPEC : enteropathogenic Escherichia coli
FBS : fetal bovine serum
GI : gastrointestinal
HC : hemorrhagic colitis
HUS : hemolytic uremic syndrome
IEF : isoeletric focusing
IPG : immobilized pH gradients
LEE : locus of enterocyte effacement
MALDI-TOF/MS: matrix assisted laser desorption ionization-time of
flight mass spectrometry
xviii
MTT : 3- (4,5-dimethylthiazol-2yl)-2,5-diphenyl-2H
-tetrazolium bromide
ORF : open reading frame
PBS : phosphate buffered saline
PCR : polymerase chain reaction
PFGE : pulsed field gel electrophoresis
pI : isoelectric point
PMSF : phenylmethylsulfonyl fluoride
pO157 : plasmid O157
QS : quorum sensing
RNA : ribonucleic acid
xix
RPLA : reversed passive latex agglutination
RT-PCR : reverse transcriptase polymerase chain reaction
SAM : S-adenosyl methionine
sBAP : sheep blood agar plate
SDS-PAGE : sodium dodecyl sulfate-polyacrylamide gel
electrophoresis
STEC : shiga toxin-producing Escherichia coli
Stx : shiga toxins
TBE : tris-borate EDTA
TCA : trichloroacetic acid
TEM : transmission electron microscope
xx
TFA : trifluoroacetic acid
T3SS : type III secretion system
2-DE : two dimenssional electrophoresis
VTEC : verocytotoxin-producing Escherichia coli
xxi
ABSTRACT
Modulation of Enterohemorrhagic
Escherichia coli Virulence by the Global
Regulator System
Shiga toxin-producing Escherichia coli (STEC), also called,
enterohemorrhagic Escherichia coli (EHEC) have emerged as pathogens
that cause problems such as bloody diarrhea, non-bloody diarrhea and the
hemolytic uremic syndrome (HUS). The public health impact of STEC
(EHEC) infections is high because of their systemic complications, such
as HUS, an important cause of acute renal failure in childhood, and late
xxii
sequelae and their ability to cause large outbreaks.
This study investigated the relationship between phenotypic and
genotypic characteristics of STEC strains isolated in Korea. Subsequently,
in order to determine the effect on the phenotypic variations and
regulation of virulence factors in human pathogen E. coli O157:H7 by
quorum sensing which is a process of bacterial cell to cell communication.
In this study, a defined nonpolar luxS deletion in strain CI03J was
constructed, this strain was an EHEC O157:H7 human isolate in Korea,
and the goal of this study was to investigate the effect of luxS/QS system
on phenotypes related to EHEC virulence and infection. In cytotoxicity
appearance, isogenic luxS mutant strain has shown decreased cytotoxicity
levels for mammalian cells and hemolysis activites for human erythrocyte.
Among the virulence factors, the bacterial adherence to mammalian cells,
flagella motility, chemotaxis, and type III secretion system (T3SS) were
also activated by luxS dependent quorum sensing. The microarray data
xxiii
and RT-real time PCR also indicated that several genes encoding flagella,
chemotaxis-related and T3SS associated genes were less expressed in the
mutant strain.
The expression of virulence factors in these strains were analyzed
by 2-DE. Total of 205 spots, i. e., 145 spots of intracellular proteins and
60 spots of extracellular proteins were detected and analyzed. Among the
spots, 19 intracellular protein spots and 22 differential spots of
extracellular proteins were increased or decreased between the strains.
The most interesting outcome of this study is the identification of virulent
proteins involved in FliC, Flagellin, EspG and hemolysin in the
intracellular proteins. As a result of the three extracellullar proteins, it
contains SepD, Cytolysin A and Stx2 protein and these were known to
virulence factors of EHEC. These results indicated that several proteins
were up-regulated by LuxS.
In conclusion, these findings suggest that quorum-sensing
xxiv
regulation in EHEC strain is a global regulatory system that controls not
only genes and proteins involved in pathogenesis but also factors
involved in several bacterial metabolism and biosynthesis, among other
functions.
Key words: shiga toxin producing Escherichia coli (STEC),
enterohemorrhagic E. coli (EHEC), hemolytic yremic syndrome (HUS),
quorum sensing, luxS, microarray, reverse transcriptase real time
polymerase chain reaction (RT-real time PCR), two dimensional
electrophoresis( 2-DE)
1
CHAPTER I
Epidemiologic and molecular research on
shiga toxin-producing Escherichia coli
isolated in Korea
2
1. INTRODUCTION
Escherichia coli was first described in 1885 by Theodore Escherichia as
a pure culture of occasionally curved, slim, short rods ranging from 1~5
㎛ in length and 0.3~0.4 ㎛ in thickness (Bettelheim, 1986). As a part
of the normal gut microflora, this microorganism colonizes the
gastrointestinal tract of warm-blooded animals and humans within a few
hours after birth and plays an important role in maintaining gut
physiology (Doyle et al., 2001). However, some E. coli strains have
acquired specific virulence factors by means of mobile genetic elements
such as plasmids, transposons, bacteriophages, and pathogenicity islands,
and have evolved into pathogenic E. coli (Kaper et al. 2004). Shiga like
toxin-producing Escherichia coli (STEC), also called, verocytotoxin-
producing E. coli (VTEC) have emerged as pathogens that can cause
problems such as hemorrhagic colitis (HC), mild diarrhea, severe bloody
diarrhea with abdominal pain and, in up to 10% of cases, hemolytic-
uremic syndrome (HUS) (Nataro and Kaper, 1998).
Transmission of STEC to man occurs through the consumption of
contaminated food, including under-cooked beef and meat products, un-
pasteurized milk and ready-to-eat products, including cooked meats and
vegetables that have been contaminated (Besser et al., 1993; Griffin et al.,
3
1991; Thorpe, 2004). Disease outbreaks are frequently associated with
the ingestion of food or water contaminated by bovine feces. Examples
include under-cooked ground beef, private or municipal water sources,
and other food products such as un-pasteurized apple cider or milk, fresh
vegetables, sprouts, and salami (Griffin et al., 1991; Nataro and Kaper,
1998). Healthy cattle are the most important animal reservoir associated
with human infection (Albihn et al., 2003; Hancock et al., 1994),
although other healthy animals, including sheep, goats, pigs, dogs,
chickens, horses, deer, rats, and sea gulls can also carry STEC (Cizek et
al., 2000; Doyle et al., 2001; Kudva et al., 1996).
Direct or indirect contact with animals provides an alternative route
by which infection can be acquired (Beutin et al., 1995) and person-to-
person transmission of the organism occurs in families and institutional
settings (Nataro and Kaper, 1998). The potential for airborne
transmission has also been reported recently after an exposure to a
contaminated building at an animal exhibit (Cobeljic et al., 2005). The
various transmission routes may be explained by the very low infectious
dose (10-100 organisms) of this microorganism. Therefore, minimal
exposures can cause disease (Kaper et al., 2004). STEC was first
recognized as a human pathogen in 1982 (Nataro and Kaper, 1998). Since
then, this microorganism has been associated with many disease
outbreaks in the U.S. and other countries around the world (Beutin et al.,
4
2004; Boerlin et al., 2002; Galane et al., 2001). In the U.S., there are
approximately 70,000 infections annually and 2,000 hospitalizations,
with an overall cost of $405 million (Banatvala et al., 2001), which
makes STEC infections a serious problem. The largest outbreak in the
U.K. occurred in Central Scotland in 1996, resulting in more than 500
cases and 21 deaths (Evans et al., 2002); a series of related outbreaks in
Japan in 1996 involved more than 10,000 cases (Nataro and Kaper, 1998).
Although O157 is the most important STEC serogroup, more than 180
serotypes of E. coli have been shown to produce shiga like toxin(s)
(STXs). In Spain, STEC is a significant cause of sporadic cases of human
infection (Almirante et al., 2005; Blanco et al., 1999; Mora et al., 2007).
Some non-O157 have been associated with outbreaks of infection (Espie
et al., 2008). The public health impact of STEC infections is high because
of their systemic complications, such as HUS, an important cause of
acute renal failure in childhood, and late sequelae (Andreoli et al., 2002),
and their ability to cause large outbreaks.
Currently, STEC infections are not treated with antibiotics, as this
has been found to increase the development of HUS in infected children
(Tarr et al., 2005), as well as the increased release of shiga toxins (Olsson
et al., 2002; Beutin et al., 1996). The clinical manifestation of STEC
infections are best characterized for illnesses caused by STEC O157:H7.
The infectious dose for this pathogen is estimated to be well under 100
5
organisms (Karch et al., 2005). After a typical incubation period of 3-4
days (Andreoli et al., 2002), patients develop watery diarrhoea
accompanied by abdominal cramping pain for 1-3 days.
The cardinal trait of STEC is their ability to produce and release
Stxs, which are considered the major virulence factors produced by these
pathogens. Based on cytotoxicity neutralization assays and sequence
analysis of stx genes, two major Stx families, Stx1 and Stx2, can be
differentiated. Each of these holotoxins is composed of five glycolipid-
binding B subunits, and one enzymatically active A subunit, which
inhibits protein synthesis by cleaving ribosomal RNA (O'Brien et al.,
1992; O’Loughlin et al., 2001). In both major toxin groups, several toxin
variants have been identified, in addition to the major toxin types. The
Stx1 group presently consists of Stx1, Stx1c (Friedrich et al., 2003), and
Stx1d (O’Brien et al., 1992), recently found also in humans (Sandvig et
al., 2002). The more heterogeneous Stx2 group is comprised of Stx2c
(Pierard et al., 1998), Stx2c2 (Dell’Omo et al., 1998), Stx2d (Melton et
al., 1996; Pierard et al., 1998), Stx2e (Gannon and Gyles, 1990), Stx2f
(Schmidit et al., 2000), and Stx2g (Leung et al., 2003), which is not yet
found in humans. Gene encoding Stx1, Stx2, and certain Stx variants are
contained on temperate lambdoid bacteriophages that integrate into
different sites of the bacterial chromosome (Schmidit, 2001). In addition
6
to their role in virulence, Stxs are also targets with which to diagnose
STEC infections (Paton et al., 1998).
An important early step in the colonization of the human
gastrointestinal tract by bacteria is the adhesion of the organism to the
host surface. Most STEC strain produce a distinct histopathological
lesion on intestinal epithelial cells known as the attaching and effacing
(A/E) lesion. All the proteins associated with the formation of A/E lesion
are encoded on a chromosomal pathogenicity island known as the locus
of enterocyte effacement (LEE). The LEE contains the eae (E. coli
attaching and effacing) gene, encoding the outer membrane protein
intimin and several type III secretion system (T3SS) related genes.
Intimin is an outer membrane protein encoded by the eae gene within the
LEE, that is required for intimate adhesion to epithelial cells, for
cytoskeletal reorganization, and for full virulence in adult volunteers
(Jerse et al., 1990; Donnenberg et al., 1993). Among the various A/E
pathogens, multiple intimin alleles have been identified that differ in
antigenicity as well as in sequence (Agin and Wolf, 1997; Adu-Bobie et
al., 1998). To date, sequence variations of the C-terminus have been
proposed to define at least nine intimin subtypes [represented by the
Greek letters a through z(zeta)] (Adu-Bobie et al., 1998). This protein
mediates intimate adherence to target eukaryotic cells upon interaction
with its translocated receptor Tir (Miyake et al., 2005), a protein encoded
7
upstream of eae gene on the LEE (Schmidt and Hensel, 2004).
PCR analysis revealed that 223 STEC isolates tested positive for
several virulence genes and putative virulence genes. Together with
detection of the virulence genes, we compared the distribution pattern of
the genes associated with adherence. Several proteins were proposed to
be novel adhesion factors; these include ToxB (a protein identified from
large, 93-kb plasmid pO157 and required for full expression of adherence
of O157:H7 strain Sakai) (Stevens et al., 2004; Tatsuno et al., 2001;
Tozzoli et al., 2005), Saa (an autoagglutinating adhesion identified in
LEE-negative strains) (Paton et al., 2001; Tarr et al., 2000), Iha
(adherence-conferring protein similar to Vibrio cholerae IrgA) (Tarr et al.,
2000), and EfaI (EHEC factor for adherence) (Stevens et al., 2004).
These putative adhesions are encoded in the large plasmid harbored by
STEC strains.
A factor that may also affect the virulence of STEC is the
enterohemolysin Ehly, also called enterohemorrhagic E. coli hemolysin
(EHEC-HlyA), which is encoded by an ehxA gene (Beutin et al., 1996;
Boerlin et al., 1998; Eklund et al., 2001). Hemolysin production is a
common attribute of Escherichia coli strains and was shown to be
involved in defines a novel type of cytolysin(sheA) (Kerenyi et al., 2005;
Westermark et al., 2000) with regard to structure, secretion and activation
and is expected to display particular properties with regard to pore
8
formation. In E. coli isolates associated with diseases, pore-forming
cytolysins have been identified. To characterize the cytolysis of the
STEC-derived RTX (repeates in toxin) and other pore-forming toxins, we
compared its activities for lysis of RBC. In this study, we analyzed
various STEC isolates belonging to different phenotypes with regard to
the presence of hlyA, ehx, sheA. In addition, we investigated the
comparison between symptoms of patients and genetic profiles.
The first case of HUS due to STEC infection in Korea was isolated
in 1998 (Kim et al., 1998). The outbreak in Korea occurred in Kwang-ju
city in 2004, resulting in more than 70 cases. Infections caused by STEC
have increased in Korea, although prevalence remain low as compared to
other gastrointestinal pathogens, such as Salmonella, Shigella and Vibrio
(Cho et al., 2006). However, the potential severity of the disease results
in high patient morbidity and a significant economic cost. It is essential to
maintain and enhance surveillance to identify risk factors and to obtain
more evidence on the diversity of transmission routes. This information is
essential to implement measures to reduce STEC infection. Surveillance
of STEC-associated infection is now undertaken by several countries and
elsewhere, although the criteria and methods applied vary.
Since the last detailed report of laboratory surveillance in Korea,
there has been a rise in the number of infections caused by STEC and in
the number of outbreaks. Our current investigation is the first large study
9
in Korea on the prevalence of STEC in patients with diarrhea. The
objective of this study was to determine the prevalence and molecular
characterization of STEC in Korea from 1998 to 2006. The relationship
between STEC serotype, STEC virulence factors, Stx1 and Stx2, and the
clinical signs in the patients were investigated. To describe the
surveillance activities and epidemiological laboratory markers of STEC
that used at the clinical laboratory to investigate sporadic cases and
outbreaks of E. coli O157:H7 and non-O157 STEC in Korea.
10
2. MATERIALS AND METHODS
STEC strains isolated from stool specimen
Between 1998 and 2006, stool samples were collected from patients
with diarrhoea enrolled in an ongoing active surveillance system at
National Institute of Health (NIH) operated by Korea Centers for Disease
Control and Prevention (KCDC). 223 E. coli strains isolated from the
stool of symptomatic and asymptomatic patients between 1998 and 2006
were investigated in this study. Specimens were plated on MacConkey
agar (Difco Co., Ltd., Detroit, U.S.A.), eosin methylene blue agar (Difco
Co., Ltd., Detroit, U.S.A) and sorbitol MacConkey agar (Difco Co., Ltd.,
Detroit, U.S.A.). All isolates were biochemically characterized with the
API20E system (Biomerieux, Marcy l'Etoile, France).
Bacterial strains and culture condition for
enterohemolysin expression
Of the strains examined for ehx, hlyA, and sheA, among the 223 STEC,
221 were positive for hemolysin genes. For the detection enterohemolytic
activity, strains were inoculated from well-spaced single colony onto
washed human blood agar plates and the plates were incubated at 37 ℃
for 18 hrs, followed by 6hrs at room temperature. Defibrinated sheep
11
blood was washed three times in phosphate-buffered saline (pH 7.4) at
950 × g and added (5%, vol/vol) to Luria-Bertani (LB) medium agar
(Difco Co. Ltd., Detroit, U.S.A) cooled to 50 .℃
Detection of virulence genes by PCR
A loopful of human stool samples was directly inoculated into 3 ml of
LB medium (Difco Co., Ltd., Detroit, U.S.A) for enrichment and
incubated overnight at 37ºC under shaking conditions. After incubation,
enriched broth culture was centrifuged at 13,000 rpm (Sorvall Biofuge
Pico, Thermo Fisher Scientific Inc., Waltham, U.S.A.) for 1 min and the
pellet was heated at 100ºC for 10 min. Following centrifugation of the
lysate, 5 ㎕ of the supernatant was used in the PCR. To detect STEC,
PCR assays were performed using in the primers and anneling conditions
shown in Table I-3. PCR assays were carried out in a 50 ㎕ volume with
2 U DNA Taq polymerase (Takara Ex TaqTM, Kyoto, Japan) in a thermal
cycler (PTC-100, MJ Research, Watertown, U.S.A.) under the following
conditions: initial denaturation for 5 min at 94 , 30 cycles, each for 1 ℃
min, denaturation (94 ), ℃ annealing, extension (72 ) and final cycle ℃
72 for 5 min. Amplified PCR products were analysed by gel ℃
electrophoresis in 2% agarose gels stained with ethidium bromide,
visualized with UV illumination, and imaged with the Gel Doc 2000
12
documentation system (Bio-Rad, Hercules, U.S.A.).
Reversed-passive latex agglutination (RPLA) test for
the detection of Shiga toxin
The production of Stx1 and Stx2 by the isolates was determined by
using a reversed-passive latex agglutination kit (VTEC-RPLA; Denka
Seiken Co., Ltd., Tokyo, Japan) after having been grown and shaken in 5
ml of tryptone soy broth (TSB) (Difco Co. Ltd, Detroit, U.S.A.) overnight
at 37 . Of this suspension, 1 ml was centrifuged for 20 min at 13,000 ℃
rpm (Sorvall Biofuge Pico, Thermo Fisher Scientific Inc., Waltham,
U.S.A.). The titer of the supernatant was determined in the VTEC-RPLA
test according to the manufacture's instructions up to 1:256. All STEC
strains were tested for the production of Stx1 and Stx2. Titers lower than
1:2 were interpreted as negative control.
Serotyping of O antigen
The presence of O antigens was determined by microplate based
agglutination with the method of Guinée et al. (1972) employing all
available O (O1 to O181) antisera (E. coli O antisera kit, LREC
laboratory, Lugo, Spain). All antisera were absorbed with the
corresponding cross-reacting antigens to remove the nonspecific
13
agglutinins.
Antimicrobial susceptibility test
Once a single E. coli isolate was isolated and identified from each
sample collected, the standard Kirby-Bauer disk diffusion method was
used to determine the antimicrobial sensitivity profiles of the E. coli
isolates (Clinical and Laboratory Standard Institute, 2006) for 18
antimicrobial agents(BD, Franklin lakes, U.S.A.) (ampicillin; 10 ㎍,
amikacin; 30 ㎍, ampicillin-sulbactam; 10/10 ㎍, cephalothin; 30 ㎍,
cefazolin; 30 ㎍, cefepime; 30 ㎍, cefotetan; 30 ㎍, cefotaxime; 30 ㎍,
ciprofloxacin; 5 ㎍, chloramphenicol; 30 ㎍, gentamicin; 10 ㎍,
imipenem; 10 ㎍, nalidixic acid; 30 ㎍, tetracycline; 30 ㎍, ticarcillin;
75 ㎍, trimethoprim -sulfamethoxazole; 1.25 / 23.75 ㎍). A 150 mm
Mueller-Hinton agar (Difco Co., Ltd., Detroit, U.S.A) plate was swabbed
with TSB inoculated with E. coli and incubated to a turbidity of 0.5
McFarland standard. Eighteen commercially prepared antimicrobial agent
disks were place on the inoculated plates. The plates were incubated at
37 for 18 to 20 hrs. The diameters (in millimeters) of the clear zones of ℃
growth inhibition around the antimicrobial agent disks, including the 6
mm disk diameter, were measured by using precision calipers (CLSI,
2006). The breakpoints used to categorize isolates as resistant or not
14
resistant to each antimicrobial agent were those recommended by the
National Antimicrobial Resistance Monitoring System for E. coli. E. coli
ATCC 25922 (American Type Culture Collection) was used for quality
control. Data for the antimicrobial resistance of each bacterial isolate
were reported in two forms: either as the diameter of the zone of
inhibition (in millimeters) or as resistant or not resistant (based on CLSI
breakpoints).
Pulsed field gel electrophoresis (PFGE) for STEC
O157 strains
Bacterial cells were grown overnight at 37 on tryptic soy agar (Difco ℃
Co. Ltd., Detroit, U.S.A.). They were suspended in TE buffer (100 mM
Tris and 100 mM EDTA, pH 7.5) and partially embedded in low-melting-
temperature agarose (FMC Corp., Newyork, U.S.A.) and digested
overnight with 10 U of ProteinaseK (Invitrogen, Carlsbad, U.S.A.) at
55 . Briefly, DNA was digested with the enzyme ℃ XbaI (New England
Biolabs, Beverly, U.S.A.) following electrophoresis performed with the
Gene Path system (Bio-Rad Laboratories, Sunbyberg, Sweden) in a 1%
agarose gel in 0.5 × TBE (Tris Borate EDTA) buffer at 14 with a linear ℃
ramp time of 2.16 to 35.07 s over a period of 18 hrs, a 120 seitch angle,
and a gradient of 6.0 V per cm. After PFGE, the gels were stained with
15
ethidium bromide and photographed under UV transillumination. The
gels were also digitized for computer-aided analysis. The Molecular
analysis software package (Bionumerics, Applid Maths., Inc., Austin,
U.S.A.) was used for analysis. Calculation of the similarity matrix was
done with the Jacquard algorithm after defining each band between sizes
145 and 582 kb. Percent similarities were identified on a dendrogram
derived from the unweighted pair group method using arithmetic
averages and based Jacquard coefficients.
16
3. RESULTS
Prevalence of STEC isolates
The presence of STEC in stool specimen of patients with diarrhea or
other gastrointestinal alterations, symptoms and asymptomatic from 17
Institute of Health and Environment of Korea were analyzed. STEC
strains were detected in 223 cases, with a progressive increase in the
incidence from 0.4% (1 isolate) in 1998 to 46.2% (103 isolates) in 2004
(Fig. I-1). The isolation proportion for STEC were not significantly
different for male (57.4%, 128 cases) and female (43%, 96 cases) patients
(Fig. I-1). STEC strains were more frequently isolated during the summer
months. Of 223 strains that yielded STEC, 126 (56.5%) were isolated
from June through August (Fig. I-2). STEC strains were isolated
throughout the year with only a moderate seasonal variation, 92.3% of
cases being detected from March to September.
As shown in Table I-1 , age-specific patterns were observed in
these STEC infections, with a high rate of prevalence in children and the
elderly. The largest number of STEC isolates was obtained from children
0 to 10 years of age 123 (55.1%). The rate of bacterial isolation was
drastically lower in adults, especially in people from the 21- to 40-year-
old age group, where it was 6 (2.7%) and this climbed to 9 (4%) in people
17
greater than 60 years of age. STEC infections were distributed without an
obvious variation among the different age groups. In these results of the
symptoms of the STEC infected patients, diarrhea (37.2%) among most
of the patients showed the largest distribution, and other diverse
symptoms including bloody diarrhea (involved in hemolytic uremic
syndrome (HUS), 20.6%), headache (1.8%), flu-like symptoms (12.5%)
(involved in chill, fever, headache and cough) and vomiting (6.3%) were
recognized (Table I-1). Also, quite a number of the patients with the
complexity of these various symptoms were identified, and not a few
patients were confirmed to be subclinical without any symptoms (13.5%).
Of these strains, 223 were isolated from the metropolitan area and 6
providences (Fig. I-3). The geographical distribution of STEC showed a
concentration in the metropolitan area involved in Seoul (17%) and
Kyungki area (26.5%). This may indicate that the occurrence of person-
person carrying STEC is correlated to the geographical distribution of the
human population. The lagest distribution of STEC isolates was obtained
from patients in Cholla-do (39.9%). This result might be that the cases
contained isolates of outbreak (73 strains) in 2004. STEC infections were
distributed without an obvious variation among the different areas.
Serotypes of STEC isolates
STEC strains were identified in 186(83.4%) of the 233 STEC strains
18
analyzed, and the frequency varied among the different serogroups
studied (Table I-2). The STEC strains belonged mainly to serogroups
O91(75 of 233[33.6%]) and O26(20 of 233[9%]), but serogroups O4,
O14, O25, O44, O64, O69, O89, O106, O108, O115, O116, O121, O128,
O152 and O16 (one strain each) were also detected. Of all 223 STEC
isolates detected in Korea since 1998, 26(11.7%) strains were sorbitol
negative and belonged to the O157 serogroup and 37(16.6%) strains were
undetemined serogroup.
19
Figure I-1. Prevalence of patients with STEC infections and
distribution of sex in South Korea.
0
20
40
60
80
100
120
1998 1999 2000 2001 2002 2003 2004 2005 2006
year
No.
of S
TE
C is
olat
es
Male
Female
Cases
20
Table I-1. Distribution of clinical manifestations and ages in patients with STEC infections in South Korea
Age in years
Patients with Symptoms No. Positive(%)
Bloody diarrhea Diarrhea Abdominal pain Chill Fever Vomiting Asymtomatic Headache Cough Total
0-5 24(10.8) 59(26.5) 0(0) 0(0) 2(0.9) 4(1.8) 0(0) 0(0) 0(0) 89(39.9)
6-10 12(5.4) 9(4) 15(6.7) 0(0) 2(0.9) 0(0) 0(0) 0(0) 0(0) 34(15.2)
11-20 1(0.4) 7(3.1) 4(1.8) 2(0.9) 14(6.3) 9(4) 28(12.6) 2(0.9) 1(0.4) 75(33.6)
21-40 1(0.4) 4(1.8) 1(0.4) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 6(2.7)
41-60 2(0.9) 2(0.9) 1(0.4) 1(0.4) 1(0.4) 1(0.4) 2(0.9) 2(0.9) 1(0.4) 10(4.5)
60< 6(2.7) 2(0.9) 1(0.4) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 9(4)
Total 46(20.6) 83(37.2) 22(9.9) 3(1.3) 19(8.5) 14(6.3) 30(13.5) 4(1.8) 2(0.9) 223(100)
Age in years
Patients with Symptoms No. Positive(%)
Bloody diarrhea Diarrhea Abdominal pain Chill Fever Vomiting Asymtomatic Headache Cough Total
0-5 24(10.8) 59(26.5) 0(0) 0(0) 2(0.9) 4(1.8) 0(0) 0(0) 0(0) 89(39.9)
6-10 12(5.4) 9(4) 15(6.7) 0(0) 2(0.9) 0(0) 0(0) 0(0) 0(0) 34(15.2)
11-20 1(0.4) 7(3.1) 4(1.8) 2(0.9) 14(6.3) 9(4) 28(12.6) 2(0.9) 1(0.4) 75(33.6)
21-40 1(0.4) 4(1.8) 1(0.4) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 6(2.7)
41-60 2(0.9) 2(0.9) 1(0.4) 1(0.4) 1(0.4) 1(0.4) 2(0.9) 2(0.9) 1(0.4) 10(4.5)
60< 6(2.7) 2(0.9) 1(0.4) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 9(4)
Total 46(20.6) 83(37.2) 22(9.9) 3(1.3) 19(8.5) 14(6.3) 30(13.5) 4(1.8) 2(0.9) 223(100)
21
0
10
20
30
40
50
60
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
No.
of S
TE
C is
olat
es
Figure I-2. Monthly isolation of shiga toxin producing E. coli (STEC),
from 1998 to 2006.
22
Table I-2. Serogroups of STEC strains isolated during 1998-
2006 from patients in South Korea
2232220103441118311Total
385291255Unidentified
22O171
11O163
422O159
25266611111O157
11O152
624O146
22O145
11O128
21O121
11O116
11O115
1O112
4122O111
11O108
11O106
1311731O104
12125O103
767041O91
11O89
11O69
11O64
971O55
11O44
21925221O26
11O25
22O21
11O14
1O5
11O4
200620052004200320022001200019991998Total
YearsSerogroups
2232220103441118311Total
385291255Unidentified
22O171
11O163
422O159
25266611111O157
11O152
624O146
22O145
11O128
21O121
11O116
11O115
1O112
4122O111
11O108
11O106
1311731O104
12125O103
767041O91
11O89
11O69
11O64
971O55
11O44
21925221O26
11O25
22O21
11O14
1O5
11O4
200620052004200320022001200019991998Total
YearsSerogroups
23
Figure I-3. Frequencies (No. of isolates and percentages) of STEC
isolated and the localization of South Korea from 1998 to 2006.
Kangwon-do:8(3.6)
Kyongsang-do:20(8.9)
Jeju-do:3(1.3)
Cholla-do:89(39.9)
Chungchong-do:89(39.9)
Kyungki-do:59(26.5)
Seoul:38(17)Kangwon-do:8(3.6)
Kyongsang-do:20(8.9)
Jeju-do:3(1.3)
Cholla-do:89(39.9)
Chungchong-do:89(39.9)
Kyungki-do:59(26.5)
Seoul:38(17)
24
Stx genes and toxin production
In the present study 223 STEC isolates were charaterized (Table I-4). Of
the 223 STEC strains, 63(28.3%) carried the stx2 gene only, 45(20.2%)
isolates carried the stx1 gene only, and 115(51.5%) isolates carried both
genes. The corresponding toxin(s) shown by the reversed passive latex
agglutination test was produced by 220 of 223 strains, with the titers
varying from 1:2 to 1: 128 for Stx1 and 1:2 to 1:256 for Stx2.
Characterization of adherence genes
PCR showed that 91(40.8%) isolates carried putative adhesin genes
involved in saa gene, 181(81.2%) possessed iha gene, 132(59.2%) and
187(83.9%) strains carried toxB gene and efaI gene. Intimin (eae) genes
were detected in 209(93.7%). The eae-positive STEC strains could be
subtyped for their intimins by PCR with specific primers as previously
described(Reid et al., 1999). Three intimin types, namely intimin-α (0
strain), β(42 strain), γ(118 strains) were detected. Of the 209 eae-positive
STEC strains, 134(60.1%) isolates carried translocated intimin receptor
encode gene, tir. Also, the translocators encode genes espA (37.7%),
espD (34.1%) and espB (29.6%) were detected (Table I-5 and Fig. I-4).
25
Resistance of antibiotics
The resistance patterns of the 223 isolates from the point prevalence
study are shown in Fig. I-5. Most of the 196 isolates (87.9%) were
resistant to at least one antibiotic, whereas 27 isolates (12.1%) were
sensitive to all 16 antibiotics tested. The antibiotic for which resistance
was most frequently observed was tetracycline (51%), followed by
ampicillin (42.3%). The prevalence rate of resistance to cefepime,
cefotetan, cefotaxime and imipenem among the STEC isolates was 0.7%.
Multidrug resistance (defined as resistance to three or more classes of
antimicrobial agents) was common(33.6% of all STEC isolates) and
frequently(5.8%) included resistance to ampicillin, ampicillin and
sulbactam, cephalothin, tetracycline, and ticarcillin (Table I-6 ).
26
Table I-3. PCR primers and conditions for amplification of STEC virulence genes
S e q u e n c e ( 5 ' t o 3 ') T a r g e t g e n e s A m p l i c o n s i z e ( b p ) A n n ea l i n g t e p m p e r a t u r e R e f e r e n c e T A K A R A ™ f o r m a tT A K A R A ™ f o r m a tT A K A R A ™ f o r m a tT A K A R A ™ f o r m a t
C G T G A T G A A C A G G C T A T T G CA T G G A C A T G C C T G T G G C A A CC A G T T C A G T T T C G C A T T C A C C
G T A T G G C T C T G A T G C G A T GA T A C C T A C C T G C T C T G G A T T G AT T C T T A C C T G A T C T G A T G C A G C
G A G A C T G C C A G A G A A A GG G T A T T G T T G C A T G T T C A G
G T C T G C A A A G C A A T C C G C T G C A A A T A A AC T G T G T C C A C G A G T T G G T T G A T T A G
C A G T G A C G C A C A T A C A GT C G G G A T A T A T A A T C A T C C
G A G G C G A A T G A T T A T G A C T GA C T T C A G G T A C C T C A A A G A GC T G A A C G G C G A T T A C G C G A A
C C A G A C G A T A C G A T C C A GC T G G G A G T T G T C G A T G T T e a e a l l e l e -α 1 , 6 4 8
G T A A T T G T G G C A C T C C e a e a l l e l e -β 1 , 7 7 0G C C T C T G A C A T T G T T A C e a e a l l e l e -γ 1 , 9 2 6
G C T T G C A G T C C A T T G A T C C TG G G C T T C C G T G A T A T C T G A
G A C T G C G A G A G C A G G A A G T TC A G G T C T G C C C T T C T T C A T TG T T T T T C A G G C T G C G A T T C TA G T T T G G C T T T C G C A T T C T T
A A A A A G C A G C T C G A A G A A C AC C A A T G G C A A C A A C A G C C C AG C C G T T T T T G A G A G C C A G A AA A A G A A C C T A A G A T C C C C A
e s p A
K e r e n y i e t a l . , 2 0 0 5
T h i s s t u d y
5 5 ℃
9 1 7
C o m m e r c i a l k i t
P a t o n e t a l . , 2 0 0 1
5 3 ℃
5 7 ℃
5 6 ℃
e f a I
6 2 ℃9 2 0s h e A
e h x 2 1 2
1 4 5
e s p B
i h a
t o x B
h l y A
1 9 2
1 0 7
e s p D
l e r
t i r
s t x 1
s t x 2
s a a
1 0 6
e a e
1 , 3 0 5
6 0 2
4 7 9
1 8 7
5 6 1
3 4 9
1 1 9
4 0 4
6 0 ℃ S c h m i d t e t a l . , 2 0 0 2
T h i s s t u d y
6 2 ℃
6 0 ℃
R e i d e t a l . , 1 9 9 9
T a r r e t a l . , 2 0 0 2
N i c h o l l s e t a l . , 2 0 0 0
B o e r l i n e t a l . , 1 9 9 8
6 2 ℃
5 5 ℃
27
M 1 2 3 4 5 6 M 7 8 9 10 M M1 11 12 13 14 15 16 M1 17 18
1,000
1,600
100
200
300
400
500
600
700800900
1,200
2,0002,961
Sxt1 (349bp)
Sxt2 (404bp)
hlyA(561bp)
FliC(1,771bp)
ler(192bp)
tir(142bp)
saa(119bp)
iha(1,305bp)
efaI(479bp)
toxB(602bp)
1,000
1,600
100
200
300
400
500
600
700800900
1,200
2,0002,961
Sxt1 (349bp)
Sxt2 (404bp)
hlyA(561bp)
FliC(1,771bp)
ler(192bp)
tir(142bp)
saa(119bp)
iha(1,305bp)
efaI(479bp)
toxB(602bp)
ΒΒΒΒ-intimin(1,926bp)
αααα-intimin
(1,770bp)
eae(917bp)
ΓΓΓΓ-intimin
(1,770bp)
eae(917bp)
500
1,000
1,600
2,000
2,961
ΒΒΒΒ-intimin(1,926bp)
αααα-intimin
(1,770bp)
eae(917bp)
ΓΓΓΓ-intimin
(1,770bp)
eae(917bp)
500
1,000
1,600
2,000
2,961
Figure I-4. Amplification of virulence factors and adherence factor
associated genes in STEC. Lane M, 100bp DNA ladder; M1, 1kb DNA
ladder marker; lane 1 to 7, EDL933(STEC O157:H7); lane 8, ATCC
51434 (E. coli O91:H21); lane 9 to 10, EDL933(STEC O157:H7); lane
11 to 13, enteropathogenic E. coli(EPEC) O117; lane 14 to 16, EPEC
O162; lane 17 to 18, EDL933(STEC O157:H7). The size and positions of
DNA markers are indicated on the left.
28
Table I- 4. Distribution of the stx genes and production of shiga
toxins
1:12551.6115Shiga toxin 1,2stx1,2
1:6428.363Shiga toxin 2stx2
1:3220.245Shiga toxin 1stx1
Averages of RPLA titer*Distribution(%)No.ofpositive strainsEncoded proteinstx types
1:12551.6115Shiga toxin 1,2stx1,2
1:6428.363Shiga toxin 2stx2
1:3220.245Shiga toxin 1stx1
Averages of RPLA titer*Distribution(%)No.ofpositive strainsEncoded proteinstx types
* The titer of the supernatant was determined in the VTEC-RPLA test
according to manufacture’s instructions from 1:2 to 1: 256 ratios.
29
Table I- 5. Genotypic trait of STEC strains from diarrheal patients in
South Korea
Genes Categories Encoded protein No.of positive strainseae Intimin 209
Intimin-α 0Intimin-β 42Intimin-γ 118
saa Autoagglutination adhesin 91iha Adherence-conferring protein 181
toxB Potential adhesin ToxB 132efaI EHEC factor for adherence 187
eae-α, β, γ LEE*
non-LEE**
* LEE: encoded from LEE(locus of enterocytes effacement).
** Non-LEE: not encoded from LEE or independent LEE.
30
Figure I-5. Antimicrobial resistance of 223 representative STEC
strains in South Korea. The graph indicates the resistance of all isolates
to different antimicrobial agents, including ampicillin(AM),
amikacin(AN), ampicillin-sulbactam(SAM), cephalothin(CF),
cefazolin(CZ), cefepime(FEP), cefotetan(CTT), cefotaxime(CTX),
ciprofloxacin(CIP), chloramphenicol(C), gentamicin(GM),
imipenem(IPM), nalidixic acid(NA), tetracycline(TE), ticarcillin(TIC)
and trimethoprim –sulfamethoxazole(SXT).
0%
10%
20%
30%
40%
50%
60%
AM AN SAM CF CZ FEP CTT CTX CIP C GM IPM NA TE TIC SXT
Antimicrobial agents
Perc
enta
ge o
f res
ista
nce
31
Table I-6. Multidrug resistance of STEC isolates
Multidrug resistant toa: No. of isolates
AM, SAM, CF 12
SAM, CF, TIC 11
AM, AN, SAM, CF 8
AM, SAM, TE, TIC 6
AM, SAM, CF, TIC 1
AM, SAM, CF, TE, TIC 13
AM, SAM, CF, C, TE, TIC 6
AM, SAM, CF, CZ, C, TE, TIC 3
AM, SAM, CF, C, TE, TIC, SXT 2
AM, SAM, CF, CZ, TE, TIC, SXT 2
AM, SAM, CF, C, GM, TE, TIC, SXT 5
AM, AN, SAM, CF, CZ, CIP, C, TE, TIC 1
AM, AN, SAM, CF, CIP, GM, NA, TE, TIC, SXT 1
AM, AN, SAM, CF, CZ, CIP, C, NA, TE, TIC 3
AM, AN, SAM, CF, CZ, FEP, CTT, CTX, CIP, C, GM, IPM, NA, TE, TIC 1
Susceptible to all antimicrobial agents 27
Multidrug resistant toa: No. of isolates
AM, SAM, CF 12
SAM, CF, TIC 11
AM, AN, SAM, CF 8
AM, SAM, TE, TIC 6
AM, SAM, CF, TIC 1
AM, SAM, CF, TE, TIC 13
AM, SAM, CF, C, TE, TIC 6
AM, SAM, CF, CZ, C, TE, TIC 3
AM, SAM, CF, C, TE, TIC, SXT 2
AM, SAM, CF, CZ, TE, TIC, SXT 2
AM, SAM, CF, C, GM, TE, TIC, SXT 5
AM, AN, SAM, CF, CZ, CIP, C, TE, TIC 1
AM, AN, SAM, CF, CIP, GM, NA, TE, TIC, SXT 1
AM, AN, SAM, CF, CZ, CIP, C, NA, TE, TIC 3
AM, AN, SAM, CF, CZ, FEP, CTT, CTX, CIP, C, GM, IPM, NA, TE, TIC 1
Susceptible to all antimicrobial agents 27
AM, ampicillin; AN, amikacin ; SAM, ampicillin-sulbactam ; CF,
cephalothin ;CZ, cefazolin; FEP, cefepime ; CTT, cefotetan ; CTX,
cefotaxime ; CIP, ciprofloxacin; C, chloramphenicol ; GM, gentamicin;
IPM, imipenem; NA, nalidixic acid; TE, tetracycline; TIC, ticarcillin.
32
Relationship between hemolysin type and human
patients with manifestation
Correlating the hemolytic phenotype of STEC isolates with the presence
of hemolysin genes and relevant phenotypes were detected. In this study,
98.2% of the 219 STEC isolates contained the hlyA gene, 59.6%(ehx) and
99%(sheA) were founded by PCR analysis (Fig. I-6). Clinical data were
provided for 223 patients. The patients were divided into nine groups
according to their clinical status (Table I-8). A majority (83 cases)
suffered from nonbloody diarrhea, 46 patients had bloody diarrhea. A
group of asymptomatic excreters(30 cases) was formed from patients who
had recovered from diarrhea or were sampled in control investigations. A
few patients(94 cases) were reported to have disease other than bloody or
non-bloody diarrhea. Hemolysin type were arranged in six mainly
characteristics, type 1 to 6, which show Table I-7. These were type 1
(hlyA+, ehx+ and sheA+); type 2 (hlyA+ and sheA+), type 3(only hlyA+),
type 4 (only ehx+), type 5 (only sheA+), and type 6 (ehx+ and sheA+).
Severe disease, such as bloody diarrhea and HUS, was significantly
associated with ehx, hlyA, and sheA-positive STEC (type 1).
The characterization of hemolysis pattern in STEC by
detection hemolytic activity on human blood agar plates has shown that
the α hemolysis pattern in type I(Fig. I-6 and table I-7) and other patterns
33
were not observed the hemolysis(γ).
34
(A) (B)
Figure I-6. PCR analysis for hemolysin genes and hemolytic activity
on sheep blood agar plate. (A) Amplification of hemolysin genes. DNA
was extracted from STEC EDL933 and subjected to PCR amplification.
Lane M, 100bp DNA ladder; lane 1 to 3, PCR products for ehx (212bp)
amplification; lane 4 to 6 amplicon of hlyA gene(561bp); lane 7 to 9,
amplicon of sheA(920bp) gene. (B) Phenotypically, the bacteria
expressing hemolytic activity showed a clearance zone on sheep blood
agar plates. a: ehx+ and sheA+(type6) STEC strain, b: hlyA+, ehx+ and
sheA+(type1) STEC strain, c: hlyA+ and sheA+(type2) STEC strain.Arrow
indicate that partial hemolysis(α-hemolysis).
561bp
212bp
920bp
M 1 2 3 M 4 5 6 M 7 8 9
561bp
212bp
920bp
M 1 2 3 M 4 5 6 M 7 8 9
aaaa bbbb ccccaaaa bbbb cccc
35
Table I- 7. Distribution of the hemolysin genes and relevant
phenotypes on sBAP
49γor nonetype6 (ehx, sheA)
25γtype5 (sheA)
7γtype4 (ehx)
11γor nonetype3 (hlyA)
40γ**type2 (hlyA, sheA)
91α*type1 (hlyA, ehx, sheA)
No. of casesHemolysispatterns on sBAPTypes of hemolysingenes
49γor nonetype6 (ehx, sheA)
25γtype5 (sheA)
7γtype4 (ehx)
11γor nonetype3 (hlyA)
40γ**type2 (hlyA, sheA)
91α*type1 (hlyA, ehx, sheA)
No. of casesHemolysispatterns on sBAPTypes of hemolysingenes
* α: partial hemolysis, ** γ: no hemolysis.
36
Table I-8. Relationship between hemolysin types and patients with
clinical signs
Type1 (hlyA, ehx, sheA ) Type2 (hlyA, sheA )Type3 (hlyA )Type4 (ehx )Type5 (sheA )Type6 (ehx, sheA )bloody diarrhea( n =46 ) 40 2 - - 2 2
diarrhea( n =83 ) 17 14 4 3 13 32abdominal pain( n=22 ) 9 2 3 2 - 6
chill ( n=3 ) 2 - - - - 1fever ( n=19 ) 10 4 1 1 2 1
vomiting(n =14 ) 6 3 - - 2 3asymtomatic( n=30 ) 7 12 2 1 4 4
headache ( n=4 ) - 1 1 - 2 -cough( n=2 ) - 2 - - - -
SymtomesDistribution of cases( n )
37
PFGE pattern of STEC O157 isolates
A dendrogram based on similarities of XbaI digested DNA PFGE
patterns among STEC O157 strains was created with the Bionumerics
software (Applid Maths. Inc., Austin, U.S.A.) using Jaccard similarity
indices as described above. Digestion of chromosomal DNA with XbaI
yielded 17 to 24 bands. PFGE patterns were arranged in three mainly
clusters, A to C, which show more than 55% similarity in their band
patterns (Fig. I-7). These were cluster A (57.79% similarity, 6 strains
from metropolitan areas); cluster B (75.67% similarity, 4 strains carried
stx1 and stx2); cluster C (82.91% similarity, 4 strains possessed stx2 only)
38
Figure I-7. Dendrogram of XbaI macrorestriction electrophoretic patterns of the 26 isolates of STEC O157. Percent
similarities were identified on a dendrogram derived from the unweighted pair group method using arithmetic averages and
based Jaccard coefficients. a Pt means patient and stx means gene encode shiga toxin.
Pt1(R:seoul, stx1,2)Pt2(R:kangwon, stx1,2)Pt3(R:kyonsang, stx2)Pt4(R:chunchong, stx2)Pt5(R:seoul, stx2)Pt6(R:kyongki stx2)
Pt17(R:chungchong, stx2)
Pt20(R:cholla stx2)
Pt25(R:kyongsang, stx2)
Pt7(R:seoul, stx1)Pt8(R:kyungki, stx1,2)Pt9(R:seoul, stx1,2)Pt10(R:kyungki, stx1,2)Pt11(R:seoul, stx1,2)Pt12(R:seoul, stx1,2)Pt13(R:kyungki, stx1,2)Pt14(R:seoul, stx1,2)Pt15(R:cholla, stx1,2)Pt16(R:kyungki, stx2)
Pt18(R:kyungki, stx2)Pt19(R:kyungki, stx2)
Pt20(R:kyongsang, stx2)
Pt20(R:kyungki, stx2)Pt20(R:chungchong, stx2)Pt20(R:kyongsang, stx2)
Pt26R:kyongsang, stx2)
Cluster A (57.79%)
Cluster B (75.67%)
Cluster C (82.91%)
Pt1(R:seoul, stx1,2)Pt2(R:kangwon, stx1,2)Pt3(R:kyonsang, stx2)Pt4(R:chunchong, stx2)Pt5(R:seoul, stx2)Pt6(R:kyongki stx2)
Pt17(R:chungchong, stx2)
Pt20(R:cholla stx2)
Pt25(R:kyongsang, stx2)
Pt7(R:seoul, stx1)Pt8(R:kyungki, stx1,2)Pt9(R:seoul, stx1,2)Pt10(R:kyungki, stx1,2)Pt11(R:seoul, stx1,2)Pt12(R:seoul, stx1,2)Pt13(R:kyungki, stx1,2)Pt14(R:seoul, stx1,2)Pt15(R:cholla, stx1,2)Pt16(R:kyungki, stx2)
Pt18(R:kyungki, stx2)Pt19(R:kyungki, stx2)
Pt20(R:kyongsang, stx2)
Pt20(R:kyungki, stx2)Pt20(R:chungchong, stx2)Pt20(R:kyongsang, stx2)
Pt26R:kyongsang, stx2)
Cluster A (57.79%)
Cluster B (75.67%)
Cluster C (82.91%)
39
4. Discussion
The death rate for Koreans with intestinal infectious diseases is about 97
people per year. Thirteen (13.4%) deaths were attributed to bacterial
food-born disease (http://www.nso.go.kr). Most of the patients were
found to be children under 10, as well as those 60 and older. Fortunately,
those deaths with STEC infections have not been reported since 2003
(http://www.cdc.go.kr). However, STEC can cause severe disease and
death in humans (Kaper, 1998), and it has also emerged as an important
food-borne pathogen in humans in Korea (Cho et al., 2006; Kim et al.,
1989).
In the late 1990s, low STEC infection among patients with diarrhea
was reported. The reason for this might be the lack of proper surveillance
for STEC, or that STEC is present, but relatively few infections occurred
due to acquired immunity in the population. The present isolated
condition of STEC, since its designation as a first-grade legal epidemic in
2000, has been identified to increase from 2001 to 2004, and about 20 to
25 cases have been detected every year since its mass outbreak in 2004.
Because these isolated cases maintain the figure persistently, the
operation of a continuous lab surveillance network and the maintenance
of the diagnoses are necessary. This includes the long term research
40
through symptoms, the progress of patients, and the exchange of
information between research groups.
Our findings suggest that STEC strains are a significant cause of
human infections in Korea; infections by non-O157 STEC strains are
more common than those caused by O157 strains. Figure I-1 and Table I-
2 indicates that STEC strains were detected in 223 cases, with a
progressive increase from 0.4% (1 isolate) in 1998 to 46.2% (103
isolates) in 2004. Sex had no statistically significant influence on STEC
excretion for patients in each year. There was an insignificant tendency
for the number of male patients to be higher than female patients.
The seasonal prevalence of the isolated bacterial species was
analyzed. In general, the number of sporadic STEC infections peaks in
the summer (Almirante et al., 2005; Banatvala et al., 2001; Pradel et al.,
2000; Vaz et al., 2004). In Korea, the peak of cases occurred from June
through August (Fig. I-2). Recently, it was caused by high temperature
with a climate change, and infected patients were found in September and
October. In other studies (Banatvala et al., 2001; Beutin et al., 2004),
infections with STEC had seasonal peaks in the warmer months.
Human infection with involved in E. coli O157 has been reported
in at least 30 countries on six continents. In the U.S., 196 outbreaks or
sporadic cases were documented throughout 1998, and the number of
reported outbreaks increased from two cases in 1982 to 42 cases in 1998
41
(Nataro and Kaper, 1998). According to outbreak surveillance data from
the CDC, reported infections of E. coli O157 increased annually since
1994, had a peak of 4,744 individual patients in 1999, and then decreased
to 2,544 in 2004 and 2,621 in 2005. The distributions of isolates in
humans were markedly different in the U.S.A. comparison of increasing
tendency produced similar results to our own.
In the Korean outbreaks, the mode of transmission is most often
food, followed by person-to-person distribution, usually in elementary
school in 2004 (more than 70 cases). According to previous studies, large
outbreaks or sporadic cases of STEC O157 and non-O157 STEC strains
have been reported in Canada, Japan, and the U.K. (Nataro and Kaper,
1998). However, increasing data indicates that non-O157 STEC
infections may be more frequent than E. coli O157:H7 infections in
continental Europe, Australia, and Latin America, indicating the
possibility of differential geographic distribution(Beutin et al., 2004;
Boerlin et al., 2002; Cobelijic et al., 2005; Espie et al., 2008; Leotta et al.,
2008). In this study, a concentration in the metropolitan area involved in
Seoul and Kyungki-do was confirmed (Fig. I-3). This may indicate that
the occurrence of person-to-person STEC infection correlates with the
geographical distribution of the human population.
Since the early 1940s, it has been known that the antigenic
specificities of the bacterial cells could constitute a solid basis for a
42
refined subdivision into serotypes (Nataro and Kaper, 1998). A
classification system, in which E. coli was subdivided into different O
(lipopolysaccharide), K (capsular), and H (flagellar) antigens, was
proposed. Presently, 173 O, 56 H and 80 K antigens are recognized
(Blanco et al., 1996). In many developed countries, O157:H7 is the most
prevalent STEC serotype associated with severe disease in humans
(Kaper et al., 2004). The VTEC serotypes most frequently associated
with human disease include O26:H11, O111:H8, O157:NM, and
O157:H7 (http://www.microbionet.com.au). This study indicated that the
largest cases among all the strains were from the O91 serogroup, and it
was because the outbreak in Kwangju city in 2004 was included. In
addition, the serogroup of the strains that had many cases were
unidentified form. The undetermined serogroup that can not be detected
by the currently commercialized kit method and other undetermined
serogroups are on the rise. It is necessary that the detection method for
the O serogroup be improved. We also noted that the domestic cases of
O157 have been detected constantly every year. Most of serogroups were
O157 from STEC isolates in Korea.
The present study employed a range of all STEC organisms
isolated from symptomatic and asymptomatic patients in Korea with
virulence factor genes. Most of the STEC infections detected in this study
were sporadic, and the sources of infection were not identified in most
43
cases. In this study, 63(28.3%) STEC strains carried the stx2 gene only,
45 (20.2%) isolates carried the stx1 gene only, and 115 (51.5%) isolates
carried both genes. The key virulence factor for STEC is Stx, which is
also known as verocytotoxin (VT) (Nataro and Kaper, 1998). Previous
studies have shown that the virulence of STEC for humans may be
related to the type of Shiga toxin which is produced by gut bacteria
(Boerlin et al., 1999). In a study concerning Stx production as a single
microbial factor, the most pathogenic strains for humans have been found
to produce Stx2 only. The Stx2 toxin has been described as being 1,000
times more cytotoxic than Stx1 toward human renal microvascular
endothelial cells (O’brien and Holmes, 1987). In other studies, Stx2 was
found to be related to high virulence and was significantly associated
with STEC strains from bloody diarrhea and HUS patients (Bielaszewska
et al., 2007). Most previous studies (Beutin et al., 1996; Boerlin et al.,
1998; Eklund et al., 2001) on the distribution of virulence genes focused
on stx genes, enterohemolysin, and other putative virulence genes. Like
other authors (Blanco et al., 1996; James et al., 2006; Medellin et al.,
2007), these results indicated that STEC isolated from beef and human
STEC have similar virulence properties.
Production of intimin is not essential for pathogenesis because a
number of sporadic cases of HUS have been caused by eae-negative non-
O157 STEC strains (Scaletsky et al., 2005; Schmidt et al., 2001).
44
Additionally, by identifying the expression difference of the putative
adherence factors of eae-negative strains, the tests to confirm the
expression difference between the auxiliary factors which substitute LEE
based adherence factors as well as eae and tir could be performed
together. According to this result, the existence of LEE-based adherence
factors controls the expression difference of the putative genes (iha, toxB,
saa, and efaI) and substitutes their roles. Although an additional test is
necessary, it is possible to assume that they will take a critical role in the
pathogenic factor of STEC.
These results indicated that several genes were proposed to be
novel adhesion factors and putative adhesions, It might be that complex
mechanisms regulating among the several adhesion genes. Differentiation
of intimin alleles represents an important tool for STEC typing in routine
diagnostics as well as in pathogenesis, epidemiological, clonal, and
immunological studies (Karmali et al., 1989; Karmali et al 1983; Kim et
al., 1989; Leotta et al., 2008; Lu et al., 2006). This observation led to the
construction of allele-specific PCR primers, which has made it possible to
differentiate three variants of the eae gene encoding three different
intimin types (α, β, and γ). In this study, two eae variants were
differentiated: γ (in 118 isolates) and β (in 42 isolates). Also, type III
secretion system (T3SS) mediated and LEE-encoded genes from STEC
strains were detected; these genes were involved in ler (LEE-regulator),
45
tir, espA, espB, and mediated espD.
The surprising finding of this study was that 39 isolates from
bloody diarrheal patients tested, 36 cases possessed hlyA, ehx and sheA
carried all of them. As yet, the role of enterohemolysin as an E. coli
virulence factor has not been fully elucidated. It is likely that the
enterohemolysin is expressed during human infection and subsequent
disease, as patients suffering from O157-associated HUS produce serum
antibodies specific to the enterohemolysin from STEC O157 in almost all
cases (Schimidt et al., 2001). It might be that the complex mechanisms
regulating expression of hemolysin genes assist with each other, posing a
selective condition their coexistence in host cell. With in vitro culture on
washed human blood agar, a variety of enterohemolysin activity levels
were noted in this study (Fig. I-6B). It has also been suggested previously
the variation in levels of enterohemolysin secretion and, therefore, of
visible hemolysis may be a characteristic of double or single methionine
residue in the N-terminal region of EhxB (Taneike et al., 2002). However,
this possibility has not been substantiated, and additional work is required
to establish a correlation between the hemolysin genes.
An antibiotic susceptibility test for STEC strains was performed to
examine the resistance patterns. A total of 16 were used to examine the
patterns for the test, and the drugs used were composed of 4 β-lactams, 3
cephems, 4 aminoglycosides, 2 quinolones, and chloramphenicol,
46
tetracycline, and sulfamethoxazole. 51% of the total strains had a
tolerance to tetracycline; these were ampicilin (AM), ticarcillin (TIC),
and cepalothin (CF) in order of the highest tolerance rate. Most strains
among them showed multidrug resistance patterns, of more than 2 to 3
antibiotics. We found a high prevalence of antimicrobial resistance in our
study. The results for the multidrug resistant patterns are shown in Table
I-8. Previous studies reported that the majority of E. coli showed
resistance to ampicillin, aztreonam, cefaclor, cephalothin, cinoxacin, and
nalidixic acid, and all isolates were susceptible to chloramphenicol and
florfenicol. Mora et al. (2007) also detected, among STEC strains, an
association between higher levels of multiple resistances to antibiotics.
Antibiotics should not be administered to patients with definite or
possible EHEC infections, because antibiotics use during E. coli
O157:H7 infections has been associated with an increased risk of
developing HUS in children(Wong et al., 2000) and adults(Dundas et al.,
2001). Similarly, anti-motility diarrhoea, because these agents have also
been associated with an increased risk of HUS development (Cimolai et
al., 1994).
By PFGE, three distinct clusters were discovered among STEC
O157 strains isolated from 1998 to 2006. In addition, all O157 strains
found during the enhanced surveillance period differed from one another.
However, strains of the genotypes of the domestic STEC O157:H7
47
isolates detected during the enhanced surveillance period have been
found since then. The number of PFGE genotypes found in this study was
lower than the number found, for example, in a previous study in
Minnesota, U.S. (Tenover et al., 1995), where 317 O157:H7 STEC
isolates were subtyped by PFGE and XbaI digestion, and 143 distinct
PFGE patterns were generated with the software that the investigators
used. On the other hand, in a previous Japanese study, 825 STEC
O157:H7 isolates were similary subtyped but were classified into only six
PFGE types (Watanabe et al., 1999). Similarly, Kawano et al. (2008)
found that four clusters identified by PFGE using restriction enzyme XbaI,
stx genotypes, and clinical manifestations correlated with one another.
Reports of outbreaks and sporadic cases of STEC infection have
been increasing in recent years, in part due to better reporting and in part
due to a genuine increase in infections. Despite the increasing awareness
of STEC infections on the part of public health officials and the public in
general, the outbreak of STEC disease in Japan in the summer of 1996
was a great surprise because the size of the outbreak far exceeded any
reported outbreaks. Over 9000 cases were reported, which exceeded the
largest previously reported outbreak by an order of magnitude. Molecular
epidemiologic techniques, specifically pulsed-field gel electrophoresis
(PFGE) and random amplified polymorphic DNA polymerase chain
reaction (RAPD-PCR), showed that this large outbreak actually consisted
48
of multiple outbreaks with the largest cluster of cases (more than 6,000
cases) showing PFGE and random RAPD-PCR patterns different from
those found in isolates epidemiologically unrelated to this cluster (Vogel
et al., 2000). PFGE has also been used for routine surveillance to identify
otherwise undetected outbreaks (Beutin et al., 2005; Islam et al., 2007;
Manning et al., 2008; Schmidt et al., 2005) and is being adapted to
establish national databases for rapid strain comparison.
These results show the distribution of virulence genes and
serotypes of STEC isolated from symptomatic and asymptomatic patients
in Korea. Thus, this study can provide useful information about the trend
of STEC infections in the general population, and it represents an
important means to identifying serogroups and the distribution of
virulence genes that are highly pathogenic to human. The present study
has identified bacterial pathogens that are significantly associated with
diarrhea. This new knowledge regarding the etiology of diarrhea in the
surveyed patients will help us plan studies to investigate the various
aspects of diarrhea.
In conclusion, STEC represents a serious public health threat in
Korea in terms of the potential to cause life threatening human disease.
Prevention and control of STEC strains causing human illness is a high-
priority concern for Korea and is driven by the high associated medical
care costs, the loss of productivity, economic loss, and the increased
49
morbidity and mortality associated with this condition. This further
emphasizes the need for more rapid, sensitive, and simple methods to
improve diagnostic yield. We have been targeted to various virulence
genes and profiled them. Clinical laboratory in Korea have limitation for
diagnostic approaches and it should be improved. Profiling of virulence
factors is very important for STEC diagnosis and understanding of STEC
pathogenesis. General recommendations for optimal sampling should be
established so that cost-effective routines can be designed for both
epidemiological investigations and clinical use. Profiling of several
virulence genes could be a candidate for vaccine development, although
their roles as a factor for pathogenesis in STEC strains should be proved
experimentally. Continuous comparison and analysis between the
epidemiological data and the research on the molecular characteristics of
STEC in this study will help prepare the data and to understand the
etiological mechanism of STEC.
50
CHAPTER II
LuxS mediated quorum sensing and
expression of virulence in Escherichia coli
O157:H7
51
1. INTRODUCTION
Quorum sensing (QS) is an important mechanism of cell-to-cell
communication that involves density dependent recognition of signaling
molecules, resulting in modulation of gene expression. The first report of
a potential role for QS in gastrointestinal (GI) infections was published in
1999 (Surette et al., 1999), and many reports for different GI pathogens
have followed. QS was first characterized in the marine bacterium Vibrio
fischeri (Nealson et al., 1970). Since the initial description for V. fischeri,
QS has now been recognized to regulate a wide range of activities in
diverse bacteria, including plasmid transfer and plant tumor induction by
Agrobacterium tumefaciens, antibiotic production in Erwinia carotovora,
biofilm production and virulence gene expression in Pseudomonas
aeruginosa, competence for DNA uptake in Streptococcus pneumoniae,
and virulence gene expression in numerous pathogens, including
Staphylococcus aureus, Vibrio cholerae, and pathogenic E. coli(Anand et
al., 2003; Barrios et al., 2006; Clarke et al., 2003; Cloak et al., 2002;
Henke et al., 2004). Three major QS circuits have been described; one is
used primarily by gram-negative bacteria; another is used primarily by
gram-positive bacteria; and the third has been proposed to be universal
and allows interspecies communication and is found in both gram
52
negative and gram positives. This mechanism regulates important
microbial processes such as growth, toxin production, virulence,
sporulation, antibiotic synthesis, colonization and motility in a variety of
bacteria through alterations in the pattern of gene expression (Armitage et
al., 2005; Crepin et al., 2005; Delisa et al., 2001; Donnenberg et al.,
1998; Xu et al., 2006; Yang et al., 2006).
A recent breakthrough in the field of bacterial pathogenesis is that
bacterial virulence expression is controlled by quorum sensing, a
universal adaptive response triggered by small signaling molecules called
Autoinducers (AIs). AIs are secreted and accumulated outside the cells as
bacterial cell population increases. In bacteria, 4 different AI molecules
have been reported: AI-1, AI-2, AI-3, and AI-peptides like Streptococcal
pheromones. Among those molecules, however, AI-2 and -3 mediated QS
signaling have been extensively studied in EHEC O157:H7. The
synthesis of AI-2 requires a series of biochemical conversions of S-
adenosylmethionine to homocysteine catalyzed by the enzymes Pfs and
LuxS (Keersmaecker et al., 2006; Schauder et al., 2001; Zavilgelsky and
Manukhov, 2001). However, the LuxS function does not seem to be
limited to the production of AI-2 because increasing evidence suggests
that luxS mutation shows pleiotropic phenotypes, some of which could
not be restored by a simple addition of purified AI-2. Such phenotypes
include swarm motility and LEE expression.
53
Indeed, recent studies demonstrated that LuxS is involved in
the production of another signaling molecule AI-3, QS-dependent
motility, and LEE expression. Interestingly, it is known that both AI-2
and -3 are universal to many bacterial species as well as AI-3, and
mammalian hormones, such as epinephrine and norepinephrine, are
proposed to be recognized by the same receptor(s) such as QseBC and/or
QseEF component systems. However, the biological significance of both
AI-2 and -3 is not clearly understood; therefore, those signaling
molecules are important for both inter-species and inter-kingdom
communication. AI-3 has also been shown to regulate EHEC virulence
and flagellar gene expression (Sperandio et al. 2003) and function similar
to the human hormone epinephrine (Walters and Sperandio, 2006), on
EHEC virulence and infection has not been fully understood.
The ability to coordinate behaviour in a cell-density-
dependent fashion has several obvious advantages. In the case of
pathogenic microorganisms, the regulation of virulence determinants
throughout the infection process is believed to play an important role in
pathogenicity. Evading host defenses is a major goal of pathogens, and as
such, quorum sensing is an important asset because it enables bacteria to
appropriately time the expression of immune response activating products.
Using quorum sensing, bacteria can amass a high cell density before
virulence determinants are expressed, and in doing so, the bacteria are
54
able to make a concerted attack, produce ample virulence factors, and be
present in sufficient numbers to overwhelm the host defences (Kievit and
Iglewski, 2000). It has been shown that many pathogens use quorum
sensing to regulate virulence (Miller and Bassler, 2001). In this regard,
enterohaemorrhagic E. coli (EHEC), which have caused great concern to
the food industry, has an important case for establishing any such quorum
sensing-based system for virulence expression so that it may distinguish
between an intestinal environment containing large bacterial populations
and an extra-intestinal location where bacterial numbers would probably
be low. These organisms colonize the large intestine and produce a potent
toxin, Shiga toxin (Stx), resulting in haemorrhagic colitis and haemolytic
uremic syndrome in a significant proportion of infected people (Nataro
and Kaper, 1998).
The EHEC causes a histopathological lesion on intestinal
epithelial cells termed attaching and effacing (AE). This lesion is
characterized by the destruction of microvilli and the rearrangement of
the cytoskeleton to form pedestal-like structures that cup the bacteria
individually. The genes involved in the formation of the AE lesion are
located on a pathogenicity island termed the Locus of Enterocyte
Effacement (LEE) (McDaniel et al., 1995; Elliot et al., 1998). The region
contains (i) sep and esc genes encoding a type III secretion system (Jarvis
et al., 1995); (ii) the eae gene encoding an adhesin called intimin that is
55
responsible for the intimate attachment of bacteria to the epithelial cell
(Jerse and Kaper, 1991); (iii) the espABD genes, which encode proteins
secreted by the type III secretion system, including EspA, which forms a
filamentous secretion tube and EspBD, which are believed to facilitate
pore formation at the host surface and thereby complete the conduit for
delivery of proteins from the bacterium into the host cell cytoplasm
(Donnenberg et al., 1993; Kenny et al., 1996; Lai et al., 1997; Knutton et
al., 1998); (iv) the tir gene, which encodes the translocated intimin
receptor, the receptor for intimin (Kenny et al., 1997); and (v) the ler
gene (LEE-encoded regulator), which encodes a positive regulator of
LEE genes (Mellies et al., 1999). Sequence analysis of the conserved
sequence of LEEs for EHEC revealed 41 ORFs that are highly conserved
at the DNA and protein levels for the type III secretion genes, but were
more variable for the esp, eae, and tir genes.
The majority of the LEE genes were reported to be in five
major polycistronic operons named LEE1 through LEE4 and tir (Perna et
al., 1998; Mellies et al., 1999; Elliot et al., 1999). A definite role for
quorum sensing in the regulation of expression of the type III secretion
system in EHEC has been shown. Using lacZ reporter gene fusions, it
was shown that the expression of the LEE operons encoding the type III
secretion system, translocated intimin receptor, and intimin was regulated
by quorum sensing in enterohaemorrhagic E. coli (Sperandio et al., 1999).
56
Mutation and complementation studies showed the luxS gene
to be responsible for the production of autoinducer in both V. harveyi and
for the regulation of LEE operons in E. coli. It was also suggested that
intestinal colonization by E. coli O157:H7, which has a very low
infectious dose, could be induced by the quorum sensing of signals
produced by nonpathogenic E. coli and other organisms that possess the
luxS gene (e.g., Enterococcus and Clostridium), which are present as part
of the normal intestinal microflora. By hybridizing an E. coli gene array
with cDNA synthesized from RNA that was extracted from EHEC strain
86-24 and its isogenic luxS mutant, it was shown that expression of 404
genes were effected by the luxS mutation. The transcriptional regulation
was further confirmed using operon: lacZ fusions to class-I, -II, and -III
flagellar genes. Quorum sensing was suggested as a global regulatory
mechanism for basic physiological functions of E. coli, as well as for the
control of virulence factors (Sperandio et al., 2001).
Previously, several phenotypical studies were used to
understand LuxS/AI-2 mediated signaling in EHEC O157:H7 using a
defined luxS mutant strain (e.g., VS94) and in-vitro purified/synthesized
AI-2 molecules. However, the results might vary depending on the
culture conditions (i.e., culture media, growth phase, or anaerobiosis,
etc.) and the strains isolated from the different sources. In this study, a
defined nonpolar luxS deletion in strain CI03J was constructed, this strain
57
was an EHEC O157:H7 human isolate in Korea, and the goal of this
study was to investigate the effect of luxS/QS system on phenotypes
related to EHEC virulence and infection.
58
2. MATERIALS AND METHODS
Bacteria and growth conditions
The bacterial strains and plasmids used in this study are listed in table
II-1. All E. coli strains were grown at 37 with aeration at 200 rpm in ℃
Luria-Bertani medium (LB) or LB containing 0.2% glucose. When
necessary, the antibiotics were added into the media at the following
concentrations: ampicillin(Ap), 200 ㎍/ml; kanamycin(Km), 50 ㎍/ml;
chloramphenicol(Cm), 30 ㎍/ml.
Construction of an E. coli O157:H7 luxS mutant
strain
An clinical isolate EHEC O157:H7 luxS deletion mutant was
constructed by the linear recombination (λRed) method of Datsenko and
Wanner (2000). Briefly, the oligonucleotides (Table II-2) were used to
amplify by PCR the kanamycin resistance cassette from the nonpolar
plasmid template pKD13. The resulting product was then transformed by
electroporation into CI03J carrying pKD46, grown at 30 in the ℃
presence of 10 mM arabinose). Integrates cured of pKD46 and lacking
the luxS coding sequence were selected by growth on LB agar containing
59
ampicillin(100 ㎍/ml) and kanamycin(50 ㎍/ml) at 42 , and mutations ℃
were confirmed by PCR. More than 95% of coding sequence of luxS was
deleted, leaving behind the 5' and 3' ends of the gene encoded by the
oligonucleotides. The strain was designated ML03J.
Construction of complemented strain with pEXEP5-
CT
A strain having the luxS gene complemented was created using a
topoisomerase system. The luxS gene was amplified from purified CI03J
template by PCR using primers (Table II-2). The gene was inserted into
topoisomerase recognition sites of pEXEP5-CT and transformed by
electroporation into the donor strain ML03J, creating a strain called
RL03J. The strain RL03J were conjugated with ML03J. This resulted in
strain RL03J, which is the RL03J that carries a single copy of luxS on the
ampicillin at the topoisomerase recognition site and has restored luxS
expression.
Growth curves
Strains CI03J, ML03J, and RL03J were grown for 12hrs in Luria Bertani
medium (Difco, Detroit, U.S.A.) and 0.2% glucose containing LB
medium at 37 , diluted 1:500 in fresh LB medium, and grown at 37 ℃ ℃
60
with shaking at 200 rpm. OD600 measurements were taken every hour.
Motility assays
Motility assays were performed at 37 on 0.3% agar plates containing ℃
DMEM, DMEM without glucose, tryptone broth. Plates were inoculated
using sterilized toothpicks and incubated for 24 hrs. in a 37°C incubator
and the diameter of each motility halo was measured at 4, 7, 12, and 24
hrs.
RNA preparation
Bacterial strains were routinely grown at 37 in LB containing gl℃ ucose
(0.2%, vol/vol). Cultures were grown with good aeration (250 rpm) and
growth was measured at OD600 using a GeneQuatTM pro
spectrophotometer. RNA from 500 ㎕ of mid-logarithmic culture was
stabilized using the RNA protect reagent (Qiagen, Valencia, U.S.A.)
according to the manufacturer's instructions. Total RNA was isolated
using the RNeasy mini kit for total RNA isolation (Qiagen, Valencia,
U.S.A.).The eluted RNA was subjected to DNase I digestion using the
RQ1 RNase-free DNase (Promega, Wisconsin, U.S.A,) according to the
manufacturer's instructions, to remove the possibility of DNA
contamination.
61
cDNA microarray
The integrity of bacterial total RNA was checked by capillary
electrophoresis with an Agilent 2100 Bioanalyzer (Agilent, Palo Alto,
U.S.A.) and further purified with an RNeasy Mini Kit (Qiagen, Valencia,
U.S.A.). cDNA probes for cDNA microarray analysis were prepared by
the reverse-transcription of total RNA (50 ㎍) in the presence of
aminoallyl-dUTP and 6ug of random primers (Invitrogen, Carlsbad,
U.S.A.) for 3 hrs. The cDNA probes were cleaned up using Microcon
YM-30 column (Millipore, Bedford, U.S.A.) and then followed by
coupling of Cy3 dye (for reference) or Cy5 dye (for test sample)
(Amersham Pharmacia, Uppsala, Sweden). The Cy3 or Cy5-labeled
cDNA probes were purified with QIAquick PCR Purification Kit (Qiagen,
Valencia, U.S.A.). Dried Cy3 or Cy5 labeled cDNA probes were
resuspended in hybridizationbuffer containing 30% formamide, 5 × SSC,
0.1% SDS, 0.1 mg/ml salmon sperm DNA. The Cy3 or Cy5 labeled
cDNA probes were mixed together and hybridized to a microarray slide.
After overnight at 42 , the slide was washed twice with washing ℃
solution 1 containing 2 × SSC, 0.1% SDS for 5 min at 42 , and once ℃
with washing solution 2 containing 0.1 × SSC, 0.1% SDS for 10 min at
room temperature, and finally four times with 0.1 × SSC for 1 min at
room temperature. The slide was dried by centrifugation at 650 rpm for 5
62
min. Hybridization image on the slide was scanned by Axon 4000B
(Axon Instrument, Union City, U.S.A.).
Data analysis
Hybridization image was analyzed by GenePix Pro 3.0 software (Axon
Instrument, Union City, U.S.A.) to obtain gene expression ratios
(reference vs test sample). Gene expression ratios were normalized by
GenePix Pro 3.0 software (Axon Instrument, Union City, U.S.A.).
Clustering image was obtained from hierarchical clustering (Eisen et al.,
1998), which involves computing 'distances' between data elements.
Transmission electron microscopic (TEM) analysis
In general, samples were prepared for TEM by negative staining on glow
discharged Formvar-coated grids, using 3% uranyl acetate. A sample of
bacteria culture (5 ml) was centrifuged at 10,000 rpm for 1.5 min and the
cell pellet was resuspended in 1 ml 50 mM KH2PO4 buffer. 10 ml cell
suspensions were applied to cover the grid surface and sedimented for 2
minutes. 5 ml of 3% uranyl acetate was applied onto each grid and
staining for 1 min. Excess liquid was removed by using filter paper. Grids
were examined in a transmission electron microscope JEOL JEM1010 at
a voltage of KV80.
63
Cell adherence assay
Assessment of bacterial adherence to tissue culture cells was performed
as described by Cravioto et al. (1991) with HEp-2 and HeLa cells with
some modifications. Briefly, HEp-2 cells maintained in D-MEM
supplemented with 10% fetal bovine serum (FBS) and HeLa cells D-
MEM supplemented with 10% FBS, were plated onto coverslips in 24-
well tissue culture plates at a density of 2 × 105 cells per well and then
incubated at 37 for 16 h fo℃ r HEp-2 and HeLa cell in the presence of
5% CO2. Before infection, old medium was replaced with D-MEM
supplemented with 10% FBS for HEp-2 or HeLa cell, respectively, with
1% (w/v) D-mannose. E. coli cells were grown overnight at 37 in LB ℃
medium, and 107 bacterial cells were inoculated into each well. The cells
were incubated for 1.5 hrs at 37 in the presence of 5% CO℃ 2, washed 3
times with phosphate-buffered saline (PBS) to remove nonadherent
bacteria, and incubated an additional period of 5 h in the same medium.
Following the incubation period, cells were washed 5 times with PBS,
fixed in methanol, and stained with Giemsa solution (Gibco, Carlsbad,
U.S.A) for microscopic evaluation.
Amplification of LEE genes by reverse transcriptase
real time PCR
64
Cultures of strains CI03J, ML03J and RL03J were grown aerobically in
LB medium at 37 overnight and then were diluted 1:100 in LB and ℃
grown in a shaking incubator at 37 . RNA was extracted from each ℃
strain per condition at the late exponential growth phase (optical desity at
600 nm, 0.8~0.9) using the RNeasy mini kit (Qiagen, Valencia, U.S.A.).
For reverse transcriptase real time PCR, the 20㎕ reaction mixture was
prepared by 2㎕ of total RNA, 0.6 mM of each primer, respectively, and
reference dye SYBR Green. The number of copies was calculated, and
dilutions ranging from 100 pg to 100 ng copies of this standard wrer
prepared in a TE buffer. Aliquots of these dilutions were frozen at -20 . ℃
Throughout this study, the Quantitect SYBR Green master mix kit
(Qiagen, Valencia, U.S.A.) was used for all reactions with real time PCR.
The parameters for RT-PCR included 30min incubation at 50 for ℃
converting mRNA to cDNA. Subsequent amplification of cDNA was
carried out by using an initial cycle of 95 for 10 min followed by 40 ℃
cycles of 94 for 30s, 55 for 30s, and 72 for 60s. The final ℃ ℃ ℃
extension was carried out at 72 for 2 min. Reaction conditions for ℃
amplification and parameters for fluorescence data collection were
programmed into a Opticon Monitor Software package 1.4. (DNA engine
Opticon 2; MJ Research, Watertown, U.S.A.).
65
Cytotoxicity assays
The WST assay was carried out. In the present study, results obtained
with the WST assay are shown mainly because it is more sensitive than
the MTT assay, while the principle of the measurement is similar. The
WST assay is based on the conversion of the tetrazolium salt WST to
highly water soluble formazan by viable cells. Ten microliters of the Cell
Count Reagent SF (Nacalai Tesque, Wisconsin, U.S.A.), which consists
of 5 mM WST, 0.2 mM 1-methoxy-5-methylphenazinium methosulfate,
and 150 mM NaCl was added to each well. After incubation for 1 hr at
37℃ the absorbance of each well was measured at 450 nm with a
reference wavelength at 655 nm. For the purpose of calculating percent
cytotoxicity values, background release from tissue culture cells was
considered as low (media only) control and Triton-X 100 (0.01%) treated
cells as high control. In case of bacterial mixture, 105 bacteria cell per
well was treated and incubated for 6 hrs at 37°C. Verotoxin producing
EDL933 (EHEC O157:H7) was used as positive controls, and E. coli
JM109 was used as negative controls in all assays.
Determination of cytolytic activity for human
erythrocytes
Bacterium-mediated lysis of erythrocytes was scored by a clearance
66
zone on blood agar plates incubation for 16 to 17 hrs at 37℃. As a
convenient assay for hemolysin activity, the release of hemoglobin from
erythrocytes essentially were quantified as described previously. Fresh,
toxin-containing supernatants were serially diluted twofold in 0.85%
NaCl and incubated with a 1% (final concentration) suspension of human
RBC at 37 for 2 h℃ rs. Reactions were terminated and unlysed cells were
removed by centrifugation at 740 × g. The amount of lysis was
determined by measuring released hemoglobin spectrophotometrically at
A572. RBC were incubated in H2O to measure total lysis, and background
lysis was determined with RBC incubated in saline. Percent lysis was
calculated from A572 measurements as follows: 100 × (A572 of sample -
A572 of background) / (A572 of total - A572 of background). Each dose-
response curve was graphed to display the points from the lower dilutions
of supernatant.
67
3. RESULTS
Identification of luxS from clinical isolate EHEC
strain
In order to determine whether EHEC has a luxS-dependent QS system,
the available EHEC genome was examined information and identified a
candidate ORF whose predicted protein was 43% identical and 63%
similar to the V. harveyi LuxS protein. The luxS gene of EHEC is an
dependent ORF (Fig. II-1), and its promotor is most likely located
upstream of the ORF. To investigate the effect of luxS mutation in CI03J,
a clinical isolate of E. coli O157 in Korea, this strain was constructed its
isogenic luxS mutant strain missing the entire structural gene by standard
one-step gene inactivation technique (Datsenko et al., 2000). Defined
genomic deletion was analyzed by PCR (Fig. II-1) and further confirmed
by DNA nucleotide sequencing.
As show in Fig. II-1, the DNA sequence analysis revealed that
the 698 bp genomic region containing both 164 bp upstream and 20 bp
downstream nucleotides of the intact luxS gene in CI03J was deleted and
replaced by the 81 bp scar nucleotides originated from the template
plasmid pKD13, where all three forward stop codons but no translation
signals have been reported (Doublet et al., 2008). The resultant luxS
68
mutant of CI03J was designated ML03J and further analyzed in this study.
69
Figure II-1. Scheme of construction luxS mutant EHEC O157:H7
strain. DNA sequence analysis revealed that the 698 bp genomic region
containing both 164 bp upstream and 20 bp downstream nucleotides of
the intact luxS gene in CI03J was deleted and replaced by the 81 bp scar
nucleotides originated from the template plasmid pKD13.
emrA emrB luxS gshA
emrA gshA
3605644 3606159
3605625 3606322
luxS+
luxS-
emrA emrB luxS gshA
emrA gshA
3605644 3606159
3605625 3606322
luxS+
luxS-
1,100bp
403bp
1,100bp
403bp
70
Table II-1. Bacterial strains and plasmids used in this study
Complementation strainRL03J
IsogenicluxS mutantML03J
Clinical isolate from patient with EHEC O157:H7(stx1 and stx2 possesed)CI03J
DH5α carrying pKD46ECK-04
DH5α carrying pKD13ECK-01
DH5α carrying pCP20BT340
Competent cellBL21
Competent cellTopo One shot Top10
Prior to adaptation with topoisomerase I, expression vectorpEXP5-CT
Ampr, Cmr, temperature-sensitive replication and thermal induction of FLP synthesispCP20
Red recombinase expression plasmidpKD46
Kmr casettespKD13
DescriptionStrains and Plasmids
Complementation strainRL03J
IsogenicluxS mutantML03J
Clinical isolate from patient with EHEC O157:H7(stx1 and stx2 possesed)CI03J
DH5α carrying pKD46ECK-04
DH5α carrying pKD13ECK-01
DH5α carrying pCP20BT340
Competent cellBL21
Competent cellTopo One shot Top10
Prior to adaptation with topoisomerase I, expression vectorpEXP5-CT
Ampr, Cmr, temperature-sensitive replication and thermal induction of FLP synthesispCP20
Red recombinase expression plasmidpKD46
Kmr casettespKD13
DescriptionStrains and Plasmids
71
Table II-2. Oligonucleotides used in this study
Primers Sequence(5'-3')
ygaG-F TACGCATAAAACCAGCAAAC
ygaG-R CGGGTGGCGAAAACAATGAA
FRT-1 GTGCGCACTAAGTACAACTA
FRT-2 CAGCAACGAAGAACTGGCACT
Lux test B CGCGAGGCGTCTGAACGC
Lux test T GGATGACGCAACAGCAGG
LuxS F GCGGTGCGCACTAAGTACAACTAAGCCAGTTCATTTGGTGTAGGCTGGAGCTGCTTC
LuxS R TGCGGTGTGGCTGGAAAAACACGCCTGACAGAAAAGATTCCGGGGATCCGTCGACC
Primers Sequence(5'-3')
ygaG-F TACGCATAAAACCAGCAAAC
ygaG-R CGGGTGGCGAAAACAATGAA
FRT-1 GTGCGCACTAAGTACAACTA
FRT-2 CAGCAACGAAGAACTGGCACT
Lux test B CGCGAGGCGTCTGAACGC
Lux test T GGATGACGCAACAGCAGG
LuxS F GCGGTGCGCACTAAGTACAACTAAGCCAGTTCATTTGGTGTAGGCTGGAGCTGCTTC
LuxS R TGCGGTGTGGCTGGAAAAACACGCCTGACAGAAAAGATTCCGGGGATCCGTCGACC
72
Growth and utilization of carbohydrates
To test if the luxS mutation results in any metabolic burdens in E. coli
O157:H7, therfore bacterial growth in LB medium containing 0.2%
glucose as well as examined the bacterial ability to utilize various
carbohydrates were monitored. As shown in Fig. II-2(A), the luxS mutant
strain ML03J showed a similar growth kinetic in glucose-containing LB
media compares to wild type strain CI03J, indicating no obvious growth
and/or metabolic defects by luxS mutation.
In contrast, this result indicated that difference growth kinetics
between CI03J, RL03J and ML03J cultured in LB media (no glucose)
(Fig. II-2(B)). These results indicating obvious growth and/or metabolic
defects by luxS/QS system. Carbohydrates were measured availability to
examine the change of the microorganism by metabolism related to
luxS/QS system. Total 25 carbohydrates were used as metabolic
utilization. As a result, only exception was seen in utilization of sorbose
(Table II-3 ). Indeed, the luxS mutant strain ML03J was unable to utilize
sorbose whereas the wildtype strain CI03J and its complemented strain
with the pEXP5-CT/luxS could.
73
Table II-3 Utilization of carbohydrates (25 carbohydrates) in strains
SubstanceStrains
Cl03J ML03J RL03J
lactose + + +
xylose + + +
maltose + + +
fructose + + +
dextrose + + +
galactose - - -
raffinose + + +
trehalose + + +
melibiose + + +
sucrose - - -
L-arabinose + + +
mannose + + +
Inulin - - -
sodium gluconate + + +
glycerol + + +
salicin - - -
glucosamine + + +
dulcitol + + +
Inositol - - -
sorbitol - - -
mannitol + + +
adonitol - - -
α-methyl-D-glucoside - - -
ribose + + +
rhamnose - - -
cellobiose - - -
melezitose - - -
α-methyl-D-mannoside - - -
xylitol - - -
ONPG + + +
esculin + + +
D-arabinose + + +
citrate - - -
malonate - - -
sorbose + - +
SubstanceStrains
Cl03J ML03J RL03J
lactose + + +
xylose + + +
maltose + + +
fructose + + +
dextrose + + +
galactose - - -
raffinose + + +
trehalose + + +
melibiose + + +
sucrose - - -
L-arabinose + + +
mannose + + +
Inulin - - -
sodium gluconate + + +
glycerol + + +
salicin - - -
glucosamine + + +
dulcitol + + +
Inositol - - -
sorbitol - - -
mannitol + + +
adonitol - - -
α-methyl-D-glucoside - - -
ribose + + +
rhamnose - - -
cellobiose - - -
melezitose - - -
α-methyl-D-mannoside - - -
xylitol - - -
ONPG + + +
esculin + + +
D-arabinose + + +
citrate - - -
malonate - - -
sorbose + - +
74
(A)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12
Time(h )
Cel
l den
sity
(OD
600)
Cl03J
ML03J
RL03J
(B)
0
0.2
0.4
0.6
0.8
1
1.2
0 1 2 3 4 5 6 7 8 9 10 11 12
Time(h)
Cel
l den
sity
(OD
600)
CI03J
RL03J
ML03J
Figure II-2. Growth curves of EHEC strains. (A) Growth curves of
EHEC wild-type strain CI03J, ML03J(luxS-) and RL03J (ML03J
complemented with pEXP5-CT(luxS+) in LB with 0.4% glucose at 37 . ℃
(B) Growth curves of EHEC strains in LB without glucose at 37 . ℃
Growth curves were performed in triplicate.
75
Influence of luxS mutation on swarming motility in
EHEC strain
In motility assay, this resuls showed that luxS/QS system affects the
motility of strains, and the test of the culture medium with 0.4% glucose
and without glucose showed that while the culture medium with glucose
had almost no difference among the strains, the one without glucose had
apparent difference among them. The motility condition in the culture
medium is shown in Figure II-3, and halos were measured and rated the
difference of motility to measure the motility of the strain during each
hour (Fig. II-4 A and B). As a result, while the culture medium without
glucose showed almost same level of motility from 4 to 7 hrs, it showed
clear difference when it became over 10 and reached up to 24 hrs. The
culture medium with glucose showed the low level of motility until 12 h,
and it showed the difference after passing 24 hrs.
Morphological analysis of flagella
Provided there is a difference in the formation of flagella, the shape of
flagella was observed by TEM. As a result, this results showed that there
was no difference in the formation of flagella among the three strains.
The rates of formation or expression of flagella was not found under the
microscope and all the three strains showed no difference in their
76
formation and shape of flagella(Fig. II-5).
Adherence assays
The results were performed cell adherence assay to the influence
luxS/QS has on pathogenesis of EHEC. The luxS mutants formed smaller
microcolonies than the wild type and complemented strains on cultured
HeLa cells(Fig. II-7) and Hep-2 cells(Fig. II-6). The tests were conducted
5 times repeatedly and the results were the similar. 10 different field on
microscope were observed, respectively.
77
A
C
B
D
A
C
B
D
Figure II-3. Motility assays of EHEC strains. Panel A, motility test of
strains CI03J(wild-type strain), ML03J(luxS mutant), and RL03J(ML03J
complemented with pEXP5-CT) in DMEM with 0.3% agar; panel B,
motility test of strains in tryptone medium with 0.3% agar and 0.4%
glucose; panel C, motility test of strains in DMEM agar without glucose;
panel D, tryptone agar without glucose. All strains were incubated at
37 ℃, 24hrs.
78
(A)
0
2
4
6
8
10
12
14
16
18
4 7 10 12 24
Time(h )
Dia
met
er o
f ha
los(
mm
)
CI03J
ML03J
RL03J
(B)
0
5
10
15
20
25
30
35
4 7 10 12 24
Time(h )
Dia
met
er o
f ha
los(
mm
)
CI03J
ML03J
RL03J
Figure II-4. Measured halo and rated the difference of motility.
Motility assays were performed at 37 on 0.3% agar plates containing ℃
media and the diameter of each motility halo was measured at 4, 7, 10, 12,
24 hrs. Tryptone medium with glucose (0.4%) (A), without glucose (B).
79
Figure II-5. Morphological analysis of flagella using by transmission electron microscope. The arrows indicate that
bacterial flagella. Samples were prepared for TEM by negative staining on glow discharged Formvar-coated grids, using 3%
uranyl acetate.
500nm 1umX 12,000 X 5,000 X 8,000
C I03J(luxS+) M L03J(luxS -) RL03J(luxS+)
500nm 1umX 12,000 X 5,000 X 8,000
C I03J(luxS+) M L03J(luxS -) RL03J(luxS+)
80
Figure II-6. Adherence assay to Hep-2 cell. A: uninfected cell, B:
infected cell with CI03J , C: infected cell with ML03J, D: infected cell
with RL03J. Hep-2 cells D-MEM supplemented with 10% FBS, were
plated onto coverslips in 24-well tissue culture plates at a density of 2 ×
105 cells per well and then incubated at 37 for 16 h℃ rs for HEp-2 in the
presence of 5% CO2. Cells were washed 5 times with PBS, fixed in
methanol, and stained with Giemsa solution.
A
C
B
D
Hep-2
ⅹⅹⅹⅹ100
ⅹⅹⅹⅹ200
A
C
B
D
A
C
B
D
Hep-2
ⅹⅹⅹⅹ100
ⅹⅹⅹⅹ200
81
Figure II-7. Adherence assay to Hela cell. A: uninfected cell, B:
infected cell with CI03J ,C: infected cell with ML03J, D: infected cell
with RL03J. HeLa cells D-MEM supplemented with 10% FBS, were
plated onto coverslips in 24-well tissue culture plates at a density of 2 ×
105 cells per well and then incubated at 37 for 16 h℃ rs for HeLa cell in
the presence of 5% CO2. Cells were washed 5 times with PBS, fixed in
methanol, and stained with giemsa solution.
A B
C D
HeLa
ⅹⅹⅹⅹ400
ⅹⅹⅹⅹ400
A B
C D
A B
C D
HeLa
ⅹⅹⅹⅹ400
ⅹⅹⅹⅹ400
82
Overview of microarray analysis
404 of 4,290 genes were observed on the array were regulated at least
1.5 folds by quorum sensing, which comprise ca. 10% of the K-12 gene
array, suggesting that quorum sensing is a global regulatory mechanism
in E. coli. Of the 4,290 genes on the array, 144 were not expressed at
detectable levels and 3,886 genes were not affected by the luxS mutation.
Of the 404 genes regulated by luxS/QS, 235 were up-regulated and 169
were down-regulated in the wild-type strain compared to in the luxS
mutant. To investigate the role of LuxS in global genomic expression, the
E. coli O157:H7-specific whole genomic transcriptome profiling was
performed in both wildtype CI03J and its luxS mutant strain ML03J (see
Materials and Methods). The results revealed that total 35 genes were
differentially expressed by luxS/QS. Among them, 12 genes whose
functions are mostly associated with motility or chemotaxis were up-
regulated while the other 13 genes coding for charperons or some
metabolic enzymes were down-regulated. However, these results were
not found any virulence associated genes such as LEE genes. The
molecular basis underlying the effect of luxS/QS on ML03J chemotaxis,
motility, and other metabolic or virulence factors were analyzed by DNA
microarrays. ML03J was in the presence of 0.4% glucose, and cells were
isolated at mid-exponential phase. Genes whose expression was
decreased by 1.5-fold in ML03J were selected and sorted into operons or
83
various fuctional groups (e.g., flagellar genes, table II-4 ). Induction of
flagellar and fimbrial genes has been associated previously with virulence
(Sperandio et al.,1999; Sperandio et al., 2004; Sperandio et al., 2002),
and in these studies, 4 fimbrial genes were regulated by luxS/QS system
were observed.
84
(A) (B)
Figure II-8. Microarray analysis of CI03J, RL03J and ML03J strains.
(A): electrophoresis of preparated total RNA, land M: DNA ladder
marker, lane 1 and 2: CI03J, lane 3 and 4: ML03J, lane 5 and 6: RL03J
(B): plates of arrays.
M 1 2 3 4 5 6kb
5.7
4.0
2.0
1.0
0.5
0.1
M 1 2 3 4 5 6kb
5.7
4.0
2.0
1.0
0.5
0.1
5.7
4.0
2.0
1.0
0.5
0.1
85
Table II-4. Fold induction of transcript in response to luxS/QS as
determined by microarray
Reference ORF Gene_symbolFold difference(vs luxS) Description
CI03J ML03J
Z3013 fliC 5.6 flagellar biosynthesis; flagellin, filament structural protein
Z2936 cheY 2.9 chemotaxis regulator transmits chemoreceptor signals to flagelllar motor components
Z3014 fliD 2.8 flagellar biosynthesis; filament capping protein; enables filament assembly
Z2935 cheZ 2.6 chemotactic response; CheY protein phophatase; antagonist of CheY as switch regulator
Z2940 tar 2.5 methyl-accepting chemotaxis protein II, aspartate sensor receptor
Z2946 flhD 2.2 regulator of flagellar biosynthesis, acting on class 2 operons; transcriptional initiation factor
Z3012 fliA 2.2 flagellar biosynthesis; alternative sigma factor 28; regulation of flagellar operons
Z3011 fliZ 2.1 orf, hypothetical protein
Z3015 fliS 2.1 flagellar biosynthesis; repressor of class 3a and 3b operons (RflA activity)
Z5711 yjdA 2 putative vimentin
Z2942 cheA 2 sensory transducer kinase between chemo- signal receptors and CheB and CheY
Z4692 rpsJ 2 30S ribosomal subunit protein S10
Z3988 ygaG 8.8 orf, hypothetical protein
Z2591 asr -6.9 -2 acid shock protein
Z3886 clpB -4.4 -1.9 heat shock protein
Z5351 metE -3.4 1.5 tetrahydropteroyltriglutamate methyltransferase
Z1389 hyaA -3.2 hydrogenase-1 small subunit
Z0014 dnaK -3.1 -2 chaperone Hsp70; DNA biosynthesis; autoregulated heat shock proteins
Z4930 gadA -2.5 -2.2 glutamate decarboxylase isozyme
Z2769 osmE -2.4 -1.6 activator of ntrL gene
Z1390 hyaB -2.4 hydrogenase-1 large subunit
Z2215 gadB -2.3 -2.3 glutamate decarboxylase isozyme
Z4981 cspA -2.2 cold shock protein 7.4, transcriptional activator of hns
Z1418 cbpA -2.1 curved DNA-binding protein; functions closely related to DnaJ
Z5678 fdhF -2.1 selenopolypeptide subunit of formate dehydrogenase H
Z0606 ybaS -2.1 -1.6 putative glutaminase
Z5748 mopA -2.1 GroEL, chaperone Hsp60, peptide-dependent ATPase, heat shock protein
Z2712 ydiC -2.1 -1.5 orf, hypothetical protein
Z2711 ynhE -2 -1.5 orf, hypothetical protein
Z1391 hyaC -2 probable Ni/Fe-hydrogenase 1 b-type cytochrome subunit
Z3526 elaB -2 orf, hypothetical protein
Z4424 yqjI -2 orf, hypothetical protein
Z4972 yhjX -2 -1.6 putative resistance protein
Z5479 hslV -2 -1.7 heat shock protein hslVU, proteasome-related peptidase subunit
Z5747 mopB -2 -1.5 GroES, 10 Kd chaperone binds to Hsp60 in pres. Mg-ATP, suppressing its ATPase activity
Reference ORF Gene_symbolFold difference(vs luxS) Description
CI03J ML03J
Z3013 fliC 5.6 flagellar biosynthesis; flagellin, filament structural protein
Z2936 cheY 2.9 chemotaxis regulator transmits chemoreceptor signals to flagelllar motor components
Z3014 fliD 2.8 flagellar biosynthesis; filament capping protein; enables filament assembly
Z2935 cheZ 2.6 chemotactic response; CheY protein phophatase; antagonist of CheY as switch regulator
Z2940 tar 2.5 methyl-accepting chemotaxis protein II, aspartate sensor receptor
Z2946 flhD 2.2 regulator of flagellar biosynthesis, acting on class 2 operons; transcriptional initiation factor
Z3012 fliA 2.2 flagellar biosynthesis; alternative sigma factor 28; regulation of flagellar operons
Z3011 fliZ 2.1 orf, hypothetical protein
Z3015 fliS 2.1 flagellar biosynthesis; repressor of class 3a and 3b operons (RflA activity)
Z5711 yjdA 2 putative vimentin
Z2942 cheA 2 sensory transducer kinase between chemo- signal receptors and CheB and CheY
Z4692 rpsJ 2 30S ribosomal subunit protein S10
Z3988 ygaG 8.8 orf, hypothetical protein
Z2591 asr -6.9 -2 acid shock protein
Z3886 clpB -4.4 -1.9 heat shock protein
Z5351 metE -3.4 1.5 tetrahydropteroyltriglutamate methyltransferase
Z1389 hyaA -3.2 hydrogenase-1 small subunit
Z0014 dnaK -3.1 -2 chaperone Hsp70; DNA biosynthesis; autoregulated heat shock proteins
Z4930 gadA -2.5 -2.2 glutamate decarboxylase isozyme
Z2769 osmE -2.4 -1.6 activator of ntrL gene
Z1390 hyaB -2.4 hydrogenase-1 large subunit
Z2215 gadB -2.3 -2.3 glutamate decarboxylase isozyme
Z4981 cspA -2.2 cold shock protein 7.4, transcriptional activator of hns
Z1418 cbpA -2.1 curved DNA-binding protein; functions closely related to DnaJ
Z5678 fdhF -2.1 selenopolypeptide subunit of formate dehydrogenase H
Z0606 ybaS -2.1 -1.6 putative glutaminase
Z5748 mopA -2.1 GroEL, chaperone Hsp60, peptide-dependent ATPase, heat shock protein
Z2712 ydiC -2.1 -1.5 orf, hypothetical protein
Z2711 ynhE -2 -1.5 orf, hypothetical protein
Z1391 hyaC -2 probable Ni/Fe-hydrogenase 1 b-type cytochrome subunit
Z3526 elaB -2 orf, hypothetical protein
Z4424 yqjI -2 orf, hypothetical protein
Z4972 yhjX -2 -1.6 putative resistance protein
Z5479 hslV -2 -1.7 heat shock protein hslVU, proteasome-related peptidase subunit
Z5747 mopB -2 -1.5 GroES, 10 Kd chaperone binds to Hsp60 in pres. Mg-ATP, suppressing its ATPase activity
86
Regulation by luxS/QS of the EHEC LEE genes
Genes, which encoded a type III secretion system was diminished in the
luxS mutant (ML03J). This study indicated that CJ03J and RL03J induced
the expression of 22 virulence genes (belonging to all five LEE operons
LEE1 through LEE5) by an average of two folds (table II-7 ). To examine
the relationship between luxS/QS and LEE, strains were tested on the
expression difference of LEE related genes using reverse transcription
real-time PCR. All 22 genes were selected for the confirmation and
relative quantification was performed based on housekeeping gene of E.
coli. The DNA density of gapA, the housekeeping gene, was prepared
from 0.1 ng to 100 ng and was used as the standard sample. The standard
curve with the result were examed and confirmed for the 100 ng sample,
the Ct value on the basis of amplification of DNA was produced at
around cycle 11, and at 14 for 10 ng, at 18 for 1 ng, and at 21.3 for 0.1 ng,
respectively. The amplification curve and the standard curve are shown in
the Table 6. The result of relative quantification showed that almost all of
the LEE genes related to T3SS had differences. They consisted of the
genes expressing the structural protein and effector protein related to
T3SS, and also included the genes which are connected with the
adherence of the bacteria such as eae and tir. On the average these genes
showed high expression level in CI03J and RL03J, while the level
declined in ML03J.
87
(A) (B)
Figure II-9. The amplification curves(A) and DNA standard curve(B)
of gapA gene.
88
Table II-5. PCR primers used in qualitative and quantitative real-
time PCR assays
Primers Genes Sequences ( 5' - 3' ) Described
EPA-FespA
CGGCACAAAAGATGGCTAATSecreted protein EspA
EPA-R ACCAGCGCTTAAATCACCAC
EPB-FespB
TCAGCATTGGGGATCTTAGGSecreted protein EspB
EPB-R CTGCGACATCAGCAACACTT
EPD-FespD
ACGAACGGTATTCGTTCTGCSecreted protein EspD
EPD-R TAACTCGCTTGCCGCTTTAT
EPF-FespF
AGCAGCCAGGTGACTTCATTSecreted protein EspF
EPF-R GGCGGGCTTAAAACCTAAAG
EPG-FespG
CGAGATTCGCACAGCAAATASecreted protein EspG
EPG-R GAAAGCGGATCTGTTTGAGC
TR-Ftir
ACTTCCAGCCTTCGTTCAGATranslocated intim receptor
TR-R TTCTGGAACGCTTCTTTCGT
GIT-Feae
CAACATGACCGATGACAAGGIntimin
GIT-R GATTAACCTCTGCCGTTCCA
LER-Fler
GACTGCGAGAGCAGGAGTTLEE encoded regulator
LER-R CAGGTCTGCCCTTCTTCATT
SPD-FsepD
TGCTTTCTTGCACGATTTTGType III secretion system protein
SPD-R ACATGTTTGCGCCATGATTA
SPL-FsepL
CAAAGGTAGCGCAAGGAAAGType III secretion system protein
SPL-R ATCGCCAAAGTAGGATCGTG
SPQ-FsepQ
GAGGTCAGCGGTCATGGTATType III secretion system protein
SPQ-R ACCTTCCGGTAAGGCAGTCT
Primers Genes Sequences ( 5' - 3' ) Described
EPA-FespA
CGGCACAAAAGATGGCTAATSecreted protein EspA
EPA-R ACCAGCGCTTAAATCACCAC
EPB-FespB
TCAGCATTGGGGATCTTAGGSecreted protein EspB
EPB-R CTGCGACATCAGCAACACTT
EPD-FespD
ACGAACGGTATTCGTTCTGCSecreted protein EspD
EPD-R TAACTCGCTTGCCGCTTTAT
EPF-FespF
AGCAGCCAGGTGACTTCATTSecreted protein EspF
EPF-R GGCGGGCTTAAAACCTAAAG
EPG-FespG
CGAGATTCGCACAGCAAATASecreted protein EspG
EPG-R GAAAGCGGATCTGTTTGAGC
TR-Ftir
ACTTCCAGCCTTCGTTCAGATranslocated intim receptor
TR-R TTCTGGAACGCTTCTTTCGT
GIT-Feae
CAACATGACCGATGACAAGGIntimin
GIT-R GATTAACCTCTGCCGTTCCA
LER-Fler
GACTGCGAGAGCAGGAGTTLEE encoded regulator
LER-R CAGGTCTGCCCTTCTTCATT
SPD-FsepD
TGCTTTCTTGCACGATTTTGType III secretion system protein
SPD-R ACATGTTTGCGCCATGATTA
SPL-FsepL
CAAAGGTAGCGCAAGGAAAGType III secretion system protein
SPL-R ATCGCCAAAGTAGGATCGTG
SPQ-FsepQ
GAGGTCAGCGGTCATGGTATType III secretion system protein
SPQ-R ACCTTCCGGTAAGGCAGTCT
89
Table II-5. (continued)
Primers Genes Sequences ( 5' - 3' ) Described
SPZ-FsepZ
GCGACCTCACTCAGTGGAAType III secretion system protein
SPZ-R ATTCTGTGCTGCTCGTCTCC
ECD-FescD
TGCAGGATGGGAAATACACAType III secretion system protein
ECD-R CTGCTGAAATGTACGGCTGA
ECF-FescF
GCGATTCTGTGCCAGAGTTAType III secretion system protein
ECF-R CGGTTAGAAATGGTTGAGAC
ECJ-FescJ
CCCGAAAAAGAAATTTGCAGType III secretion system protein
ECJ-R GACTAAAACGGCTGCTGAGG
ECN-FescN
CAACGTTTAGCCGAGGTGATType III secretion system protein
ECN-R GCATACAAGCTGCGTTCAAA
ECR-FescR
CTGTTACCGGCTTTCACGATType III secretion system protein
ECR-R ATAATTTTTGCCAGCCTCCA
ECS-FescS
CATAGCGGCCTCTGTTATCGType III secretion system protein
ECS-R TCACCTTCGGAATCATTTCA
ECT-FescT
GATGCGGCTGGACAGATTATType III secretion system protein
ECT-R TGCTTTGTATCCCACCATGA
ECU-FescU
AAAAACCCGACTCACATTGCType III secretion system protein
ECU-R TTGTGCCACAGGTTCAAAAA
CSD-FcesD
AACCGCAAGAAATCTATTCCAPutative type III secretion system protein
CSD-R AAGGCTTTCTTGGCCATTTT
CST-FcesT
TCCCTCTCGATGATGCTACCThe chaperon for Tir
CST-R TGTCGCTTGAACTGATTTCCT
Primers Genes Sequences ( 5' - 3' ) Described
SPZ-FsepZ
GCGACCTCACTCAGTGGAAType III secretion system protein
SPZ-R ATTCTGTGCTGCTCGTCTCC
ECD-FescD
TGCAGGATGGGAAATACACAType III secretion system protein
ECD-R CTGCTGAAATGTACGGCTGA
ECF-FescF
GCGATTCTGTGCCAGAGTTAType III secretion system protein
ECF-R CGGTTAGAAATGGTTGAGAC
ECJ-FescJ
CCCGAAAAAGAAATTTGCAGType III secretion system protein
ECJ-R GACTAAAACGGCTGCTGAGG
ECN-FescN
CAACGTTTAGCCGAGGTGATType III secretion system protein
ECN-R GCATACAAGCTGCGTTCAAA
ECR-FescR
CTGTTACCGGCTTTCACGATType III secretion system protein
ECR-R ATAATTTTTGCCAGCCTCCA
ECS-FescS
CATAGCGGCCTCTGTTATCGType III secretion system protein
ECS-R TCACCTTCGGAATCATTTCA
ECT-FescT
GATGCGGCTGGACAGATTATType III secretion system protein
ECT-R TGCTTTGTATCCCACCATGA
ECU-FescU
AAAAACCCGACTCACATTGCType III secretion system protein
ECU-R TTGTGCCACAGGTTCAAAAA
CSD-FcesD
AACCGCAAGAAATCTATTCCAPutative type III secretion system protein
CSD-R AAGGCTTTCTTGGCCATTTT
CST-FcesT
TCCCTCTCGATGATGCTACCThe chaperon for Tir
CST-R TGTCGCTTGAACTGATTTCCT
90
Table II-6. Quantification of DNA in housekeeping gene, gapA
SamplesAmt. of DNA Ct valuegapA-1 100 ng 11.8±0.5gapA-2 10 ng 14.09±1.2gapA-3 1 ng 17.8±0.8gapA-4 0.1 ng 21.3±0.3
91
Table II-7. Comparative to LEE genes using by quantitative real-
time PCR assay
GenesCI03J ML03J RL03J
Amt. of DNA Ct values Amt. of DNA Ct values Amt. of DNA Ct values
espA 47.3 12.01 23.2 13.8 58.4 11.9
espB 86.5 11.9 39.4 12.1 92.5 11.8
espD 31.05 13.01 7.3 17 15.2 12.9
espF 7.7 17.02 5.3 16.08 5.4 16.1
espG 54.6 11.9 37.8 12.9 53.8 11.9
tir 93.6 11.8 37.9 12.9 62.8 11.9
eae 110.8 11.75 50.9 12 95.6 11.8
ler 33.7 12.93 12 14.3 32.2 13.01
sepD 16.7 13.1 7.04 17 17.3 13.1
sepL 67.8 12 57.8 12 56.4 12
sepQ 92.6 11.8 35.2 12.9 66.7 11.9
sepZ 61.7 11.9 23.7 13.7 36.4 12.9
escD 50.4 11.9 29.2 13.03 30.4 13.03
escF 60.6 12 40.8 12.2 57.8 12
escJ 87.6 11.9 61.9 12 71.6 12
escN 74.9 12 38.6 12.4 40.5 12.2
escR 87.2 11.91 60.5 12 75.4 12
escS 60.9 12 32.3 13.01 46.7 12.01
escT 71.5 12 50.4 11.9 62.2 12
escU 24.4 13.9 7.3 17.2 10.3 14.1
cesD 43 12 31.3 13.04 50.7 11.9
cesT 44.5 12 17.6 13.1 20.2 13.2
GenesCI03J ML03J RL03J
Amt. of DNA Ct values Amt. of DNA Ct values Amt. of DNA Ct values
espA 47.3 12.01 23.2 13.8 58.4 11.9
espB 86.5 11.9 39.4 12.1 92.5 11.8
espD 31.05 13.01 7.3 17 15.2 12.9
espF 7.7 17.02 5.3 16.08 5.4 16.1
espG 54.6 11.9 37.8 12.9 53.8 11.9
tir 93.6 11.8 37.9 12.9 62.8 11.9
eae 110.8 11.75 50.9 12 95.6 11.8
ler 33.7 12.93 12 14.3 32.2 13.01
sepD 16.7 13.1 7.04 17 17.3 13.1
sepL 67.8 12 57.8 12 56.4 12
sepQ 92.6 11.8 35.2 12.9 66.7 11.9
sepZ 61.7 11.9 23.7 13.7 36.4 12.9
escD 50.4 11.9 29.2 13.03 30.4 13.03
escF 60.6 12 40.8 12.2 57.8 12
escJ 87.6 11.9 61.9 12 71.6 12
escN 74.9 12 38.6 12.4 40.5 12.2
escR 87.2 11.91 60.5 12 75.4 12
escS 60.9 12 32.3 13.01 46.7 12.01
escT 71.5 12 50.4 11.9 62.2 12
escU 24.4 13.9 7.3 17.2 10.3 14.1
cesD 43 12 31.3 13.04 50.7 11.9
cesT 44.5 12 17.6 13.1 20.2 13.2
92
LuxS/QS regulates Stx expression
In the cytotoxicity test to examine the expression difference of Stx, the
main virulence factor of EHEC, cytotoxicity reduced about 4 folds in
ML03J. The EDL933 was used as the positive control and JM109 strain
and the control group only with culture medium was used as the negative
control. As the result shows, the EDL933 strain produced the highest
cytotoxicity value, and CI03J and RL03J, the strains in this study, also
produced comparatively high cytotoxicity value.
Quorum sensing controls cytotoxicity for erythrocytes
In the test result of hemolysis assay with human RBC, while CI03J and
RL03J showed high hemolysis phase as in the result of vero cell
cytotoxicity, ML03J showed twice less value. The supernatant of the
culture fluid was filtered with the 0.2um syringe filter for the hemolysis
assay, and the prepared supernatant was diluted from 1 to 1:256 and the
hemolysis rate was measured at each density.
93
Figure II-10. Cytotoxic activity of shiga-like toxin on Vero cells by WST assays.
94
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
1 1:2 1:4 1:8 1:16 1:32 1:64 1:125 1:256
Dilution
hem
olys
is o
f RB
C(%
)
CI03J
RL03J
ML03J
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
1 1:2 1:4 1:8 1:16 1:32 1:64 1:125 1:256
Dilution
hem
olys
is o
f RB
C(%
)
CI03J
RL03J
ML03J
Figure II-11. Dose-response of hemolysis phenotypes
95
4. DISCUSSION
The gene encoding the AI-2 synthetase was cloned, sequenced, and
named luxS by Surette et al. (1999). Besides production of light, quorum-
sensing mechanisms have been demonstrated to regulate competence in
Streptococcus (Metritt et al., 2005; Sztajer et al., 2008), production of
hemolysins and other virulence genes in Staphylococcus (Villaruz et al.,
2008), production of elastase and biofilm formation in Pseudomonas
aeruginosa(Miller and Bassler, 2001), iron acquisition in V. harveyi(Mok
et al., 2003), and type III secretion in EHEC(Fuqua and Green berg,
1998; Gally et al., 2003; Kaper and Sperandio, 2005).
The different patterns of growth kinetic were found in the strains
cultured in the each medium with glucose. The observation of the growth
curves showed that CI03J and RL03J had a similar growth pattern
whether or not they had glucose. ML03J, however, showed a remarkably
reduced growth kinetics under the condition without glucose, while it
showed an almost similar growth to the other two strains under the
condition with glucose. The difference was apparent between 4~8 hours.
It showed a same level of cell density as the other two strains when it
reached the stationary phase. A hypothesis could be formed from this
result that, under conditions with abundant nutrition, QS-related genes
96
could substitute the role. Previous studies also have reported the change
in QS pattern through glucose, but the exact reason for this has not been
discovered. The presence of glucose in culture is important, as it is well
established that AI-2 uptake is regulated by catabolite repression in the
presence of glucose through down-regulation of lsr operon (Wang et al.,
2005; Xavier and Bassler, 2005); hence, glucose can mask the impact of
AI-2 on gene expression. In most bacteria examined, extracellular AI-2
activity peaks in mid-late exponential phase and declines precipitously in
stationary phase. This phenomenon has been most thoroughly studied in
E. coli and S. typhimurium, where AI-2 levels are further influenced by
environmental factors such as osmolarity, pH and carbohydrates(Kievit et
al., 2000; Liu and Ferenci, 2000; Turovskiy et al., 2006; Turovskiy et al.,
2007).
In their recent study, Kaper et al., (2005) have conducted research
on related gene and its mechanism based on the fact that QS can be
controlled by another mechanism under the condition in which all the
nutrition is exhausted. The diameters of halo actively motile from
cultures grown in the presence and absence of glucose were assessed.
Considering these results were found out that there is a close relationship
between motility and luxS/QS, and the change pattern of the phenotype
could be different depending on a nutritious element, including glucose.
This result also corresponds with the microarray result, and the 2~5.6
97
folds difference of genes related to flagella formation and motility, and
chemotaxis supports the fact.
The luxS mutant strain ML03J was able to produce the flagellum,
but it was less motile than the wild type strain. It is well known that the
luxS gene product is responsible for producing the quorum sensing
signaling molecules called AI-2 and -3. A recent study demonstrated that
AI-3 (not AI-2) mediated signaling transduces into the cells through the
QseB/C two-component system, which controls biosynthesis of the
flagellum in E. coli O157:H7. To compare the flagella biosynthesis and
their functionality in the wild type and luxS mutant strains, the bacterial
flagellum was studied via electron-microscopic analysis, and its
functionality in bacterial motility was examined on a 0.3% tryptone agar
plate (Fig. II-3). As shown in Figure II-5, interestingly, the TEM analysis
of both the wild type and luxS mutant strains revealed that they possessed
the flagella, although they did not quantitated. As expected, simple
complementation of the luxS mutant strain ML03J via intact luxS gene in
trans still retained the flagellum like the wild type and luxS mutant strains.
These results were unexpected because the previous studies demonstrated
that luxS mutation causes repression of several genes involved in flagella
biosynthesis. Therefore, the flagellum of the luxS mutant strain might not
be fully functional or that the luxS mutant strain has a reduced number of
flagella as compared to the wild type strain CI03J(Fig. II-5) were
98
hypothesized. To test this hypothesis, bacterial swamming motility was
examined. As expected, the luxS mutant strain ML03J was less motile
than the wild type strain CI03J and complemented strain RL03J,
indicating that ML03J was able to build up the flagellum, but was
somehow defective in its function. As in the study of Sperandio et al.
(2001) further research on motility activation factor, such as motA or
motB and chemotaxis related genes, such as cheA and cheW, is necessary.
This could also be solved by studying the relationship between the
different regulation factors, such as slyA and QS. The transcriptome
analysis data revealed that, in addition to altering the expression of genes
involved in virulence, AI-2 also controlled the expression of genes
involved in other phenotypes and functions (e.g., metabolism). In this
regard, have reported on the role of luxS-mediated AI-2 in metabolism
(Kendall et al., 2007; Wang et al., 2005).
Many bacteria swim by using flagella, helical propellers driven by
a reversible rotary motor in the cell membrane (Macnab, 1999, 2003).
Rotation is powered by a transmembrane gradient of ions, usually protons
(Berg, 2003), and the increase in the proton motive force strongly drives
the flagellar rotation (Kojima and Blair, 2004). In E. coli, the expression,
synthesis, assembly, and function of flagella and motility require the
expression of more than 50 genes divided among at least 17 operons,
constituting a large and coordinately regulated flagella regulon. It has
99
been known that flagellar proteins are transiently induced following heat
shock, salt, and acid stress of limitation of glucose (Kojima and Blair,
2004). It is also interesting to note that the synthesis of S-
ribosylhomocysteinase (LuxS), which is involved in the synthesis of
autoinducer-2(AI-2) from E. coli K-12, was significantly activated after
the luxS gene restored. It was reported that the luxS/AI-2 quorum-sensing
system activates the expression of genes involved in the assembly of
flagellar and motility through the activation of flhDC transcription
(Sperandio et al., 2002).
Genes potentially regulated by AI-2 in other species have been
identified by constructing a luxS mutant of comparing gene expression in
the wild type and luxS mutant. Among the phenotypes and functions
affected by luxS mutations are type III secretion system(T3SS) and
flagellum expression in EHEC O157:H7(Nataro et al., 2005; Sperandio et
al., 2002), expression of VirB in Shigella flexneri (Day and Manrelli,
2001), secretion of SepB cysteine protease in Streptococcus pyogenes
(Federle and Bassler, 2003), T3SS in V. harveyi and Vibrio
parahaemolyticus (Henke and Bassler, 2004). The most comprehensive
analysis published so far has been the analysis of E. coli, and two
microarray analyses by two different groups have compared genomic
differences in gene expression between luxS-negative mutants and their
isogenic luxS positive parent strains. Using an E. coli K-12 microarray
100
and mRNA and cDNA from EHEC, Sperandio et al. (2001) found that
approximately 10% of the genes in the K-12 genome were differentially
regulated fivefold in a wild-type EHEC strain and its isogenic luxS
mutant, with roughly equal numbers of genes being positively regulated
and negatively regulated (Sperandio et al, 2001). In separate study, Delisa
et al. (2001) regulated reported that about 5.6% of K-12 genome was
differentially regulated in a wild-type K-12 strain and its isogenic luxS
mutant. The difference in the number of genes regulated in the two
reports may have been due to differences in methodology, including
differences in growth temperature, nutrient availability, and E. coli strain
analyzed. The observation that up to 10% of the array genes are
differntially regulated in an EHEC wild-type strain and its isogenic luxS
mutant is not surprising if one considers the pleiotropic nature of a luxS
mutation.
A recent breakthrough in distinguishing the potential cell signaling
functions from general metabolic functions was the discovery of new
signaling molecule called AI-3(Kendall et al., 2007; Walters and
Sperandio, 2006; Walters et al., 2006), whose synthesis is dependent on
LuxS. Building on their previous studies showing that a luxS mutant of
EHEC was deficient in T3S and flagellum production, Sperandio et al.,
(2002 and 2004) showed that purified flagellum. These results suggest
that some of the phenotypes attributed to AI-2 signaling need to be
101
revised in light of the fact that LuxS is not devoted to AI-2 production; it
is in fact an important enzyme whose absence affects the metabolism of
SAM and various amino acid pathway.
Given the widespread nature of the luxS/AI-3 system in bacteria, an
interesting extrapolation is that the AI-3/luxS quorum sensing system
might have initially evolved to mediate microflora-host interactions but
was subsequently exploited by EHEC to activate its virulence genes. In
this manner, the AI-3/luxS system alerts EHEC to when it has reached the
large intestine, where large numbers of commensal E. coli, Enterococcus,
Clostridium, and Bacteroides, all of which contain the AI-3/luxS quorum
sensing system, reside. The most recent study in this series demonstrated
that an EHEC luxS mutant, which was unable to produce AI-3 and unable
to express the LEE-encoded T3SS at normal levels, nonetheless still
produced AE lesions on epithelial cells that were indistinguishable from
those seen with the wild type (Zhu et al., 2007). The luxS mutant still
responded to a eukaryotic cell signal to activate expression of the LEE
genes.
These results imply that there is potential cross-communication
between the luxS/AI-3 bacterial QS system and the epinephrine-
norepinephrine host signaling system. QS might be a "language" by
which bacteria and host cells communicate. Several features of the AI-2
biosynthetic pathway are intriguing because they suggest that AI-2
102
harbors information about cell number and also the growth phase and
prosperity of the cells in a population. AI-2 is well suited to be a signal
that specifies the growth phase of the population. Clostridium perfringens
uses AI-2/LuxS to regulate toxin production. The timing of production is
critical for virulence in C. perfringens and occurs at mid-late exponential
phase. Interestingly, this coincides with the timing of maximal AI-2
production. Analysis of toxin mRNA levels shows that compared with the
wild-type, C. perfringens luxS mutants have reduced toxin transcription at
mid-log phase, whereas at stationary phase, mutant and wild type toxin
mRNA levels are similar. Apparently, redundant regulatory mechanisms
exist for controlling toxin expression and timing. Stevenson and Babb
(2002) showed that LuxS from Borrelia burgdorferi proteins showed
altered expression following exogenous addition of AI-2. However, B.
burgdorferi did not produce detectable AI-2, suggesting that it is not
made under laboratory conditions and/or that AI-2 production requires a
signal from the host.
The type III secretion systems (T3SS) are utilized by gram-
negative pathogenic bacteria to deliver target-specific effector proteins
into eukaryotic cells. STEC O157:H7 strain had a well-defined T3SS
involved in attachment and critical for virulence (Schauder et al.,2001).
In general, the level of expression of most of the LEE genes such as
espABDFG and cesD, T, escD, F, J, N, R, S, T, and U, sepD, L, Q, G and
103
ler gene were not significantly changed. On the other hand, the level of
mRNA for the gene including escD (predicted to be major components of
the T3SS basal body) was higher in adherent bacteria, but their precise
biological functions and localizations in the STEC T3SS apparatus
remain still unclear. Recently, Ogino et al. (2006) demonstrated that escD
and escJ are required for the secretion of both the Esp proteins and the
translocated intimin receptor (Tir) effector. In addition, the global
regulator H-NS (Tavender et al., 2008) gene was recently to be negative
regulator of several LEE gene expressions.
Adherence of the luxS mutant was two orders of magnitude lower
than those of the wild-type and complemented strains (Fig. II-6 and 7).
These results are consistent with the lower transcription of the LEE genes
(LEE5 encodes both Tir and intimin) (Table II-7). Expression of flagella
was reduced in a luxS mutant, in agreement with this phenotype, the luxS
mutant showed reduced motility in both D-MEM without glucose and
tryptone medium (Fig. II-3 C and D). These phenotypes suggest that
successful microcolony formation and adhesion are dependent in the
correct timing and dosage of flagellar and LEE gene expression. While
flagella in EHEC are used mostly for swimming, they are involved in
adherence and microcolony formation in EPEC (Giron et al., 2002;
Sperandio et al., 2004), thus causing the need to coordinate transcription
of the LEE genes with flagellation. The results of the array indicated that
104
genes involved in cell growth and division are generally down-regulated
by quorum sensing.
We found that expression levels of LEE-encoded genes from each
strain, these genes were involved in espA, espB and mediated T3SS genes
(Table II-7). EspA composes the filament of the T3SS (Sekiya et al.,
2001), while EspB helps to form a pore in the eukaryotic memebrane that
is necessary to translocate effector proteins into the eukaryotic cell
(Sperandio et al., 2004).
The luxS gene is necessary for the efficient production of the AI-3
quorum sensing signal (Kendall et al., 2007).
The regulation of virulence genes (LEE genes) and several other
operons importance of luxS/QS system in EHEC infections. Several
studies (Anand and Griffiths, 2003; Lupp and Ruby, 2004; Qin et al.,
2007) have used whole transcriptome analysis to understand the effect of
luxS/QS system on gene expression in both nonpathogenic and
pathogenic bacteria. While the role of luxS/QS system in nonpathogenic
E. coli biofilm formation has been established (Iglewski and Kievit,
2000) its effect on EHEC phenotypes is less well understood. One study
(Cloak et al., 2002) recently observed that AI-2 down-regulated several
virulence genes including rpoS (positive regulator of LEE3 operon) and
prgH (cell invasion protein) in S. typhimurium delta luxS. However,
another recent study (Gonzalez and Keshavan, 2006; Hardie et al., 2003;
105
Holden et al., 2002; Ren et al., 2004) observed that several metabolism
genes, but only two virulence genes, espA and eae, belonging to LEE4
and LEE5, respectively. Irrespective of the effect exerted to luxS/QS or
the extent to which virulence genes were altered in expression, our data
and these studies clearly indicate that luxS/QS ia an important signal in
GI tract infections.
The chemotactic recognition of molecules mediated luxS/QS
system and increase in motility by EHEC in presence of AI-2 or AI-3 and
the suggest that this signal is involved in the initial migration of EHEC to
epithelial cells. Consistence with this increase in chemotaxis and motility,
the presence of luxS/QS system also causes an increase in adherence to
HeLa and Hep-2 cells. Given the direct correlation between colonization
to epithelial cells and increase virulence (Lyte et al. 1996; Lyte et al.
1997), these results strongly suggest that luxS/QS system leads to
increased EHEC colonization of host cells and virulence. This is also
corroborated by gene expression results showing that genes involved in
bacterial colonization and adherence are up-regulated by luxS/QS system.
The up-regulation of these genes is consistent with increased attachment
of EHEC to HeLa and Hep-2 cells in our experiments.
Previously, studies demonstrated that the genes encoding Stx1 and
Stx2 are located withn the late genes of a λ-like phage. Recently Kimmitt
et al., (2000) reported that induction of an SOS response in EHEC
106
induces the production of Stx2. Moreover, Fuchs et al., (2004) reported
that recA induction in vivo is involved in increased production of Stx2
phage induction, which is controlled by RecA. Genes encoding Stx are
induced by an SOS response were also regulated by quorum sensing
(Griffiths and Anand, 2003). Increased expression of Stx, using a RPLA
and Vero cytotoxicity assay in the wild-type and complemented strains
compared to that in the luxS mutant were observed (Fig. II-10 ).
Each strains have discrimination of cytolytic activity for human
erythrocytes were found (Fig. II-11). It might be mediated iron uptake or
correlations of other virulence mechanisms. Iron has been reported to
increase virulence of certain strains of E. coli along with other species
such as Vibrio, Neisseria, and Hemophilus, through the production of
cytotoxins and leukotoxins (Xavier and Bassler, 2003). These results
indicated that luxS/QS regulates the conclusive virulence factor, which
helps the bacteria cell adhere to the host, and, as in previous studies, that
luxS/QS influences the expression of LEE gene, resulting in the change of
adherence in the STEC strain. Although few specific studies have been
done previously on hemolysis phenomena and luxS/QS, a test using a
Serratia and Stapylococcus had similar results as these results did (Fig.
II-11).
The discovery of QS in human pathogens has led to considerable
interest in developing new therapeutic interventions to interfere with
107
these signaling molecules. Thus, instead of using an antibiotic to kill
pathogenic bacteria, a compound that interferes with the QS mechanism
would be used to repress expression of the virulence genes responsible
for the disease. Such an approach is particularly promising in light of
increasing resistance to conventional antimicrobial agents, and
encouraging results in animal models have been obtained with P.
aeruginosa and S. aureus (Schauder and Bassler, 2001). However, the
development of anti-QS therapy has been primarily directed towards
nonintestinal pathogens, which do not have to deal with the high numbers
of commensal organisms present in the GI tract. The presence of this
complex microbial flora and the variety of signaling molecules that might
be produced by the microbial flora or even the host itself greatly
complicate the application of this approach to GI pathogens. The
occurrence of C. difficile associated colitis after broad-spectrum antibiotic
use is an example of the negative consequences that can potentially result
from disruption of the normal intestinal flora.
There are at least three major strategies for the development of
drugs that interrupt bacterial QS (Nataro et al., 2005): (i) inhibition of QS
signal synthesis, (ii) destruction or degradation of the signal, and (iii)
inhibition of signal reception. As an example of the first approach, Parsek
and Greenberg (2005) used analogs of SAM to inhibit the synthesis of
AHL by the P. aeruginosa RhlI protein (Xavier and Bassler, 2006).
108
Several examples can be found for the second approach since
several naturally occurring compounds have been found that can degrade
signal molecules. One enzyme that catalyzes the hydrolysis of AHL
signals, called AiiA, is produced by Bacillus species (Jones and Blaser,
2003). Expression of AiiA in the plant pathogen Erwinia carotovora
resulted in reduced levels of AHL molecules and attenuated pathogenicity
in a variety of plant species. The application of the third approach,
inhibition of signal reception, has yielded several promising results in
animal models of disease due to human pathogens. Sun et al. (2004)
developed a synthetic derivative of natural furanone compounds that can
act as potent antagonist of bacterial QS in P. aeruginosa. In a mouse
pulmonary model of infection, addition of this compound 2 days after
inoculation with P. aeruginosa resulted in the down-regulation of
bacterial genes regulated by QS in the bacteria present in the mouse (Li et
al., 2006). Application of this compound also resulted in substantial
clearance of the organism from the lungs and rendered P. aeruginosa
present in biofilms significantly more susceptible to tobramycin, an
antibiotic routinely used to treat cystic fibrosis patients. Studies by other
investigators have resulted in the development of compounds that inhibit
QS-mediated virulence gene expression in S. aureus, thereby protecting
mice against S. aureus infection (Turovskiy et al., 2007). Fortunately, the
recent identification of AI-2 controlled genes in many different bacteria
109
provides us with the necessary outputs to monitor for the identification of
their cognate AI-2 sensory apparatuses.
This expands the knowledge on luxS/QS system in EHEC, showing
that luxS/QS is a global regulatory system that controls not only genes
involved in bacterial metabolism, DNA repair, nucleotide and protein
biosynthesis, and cell growth and division, among other functions. These
results suggest that quorum sensing is a very important regulatory
mechanism through which EHEC strain senses and adapts to a given
environment.
110
CHAPTER III
Quorum sensing contribute to proteomic
changes of Escherichia coli O157:H7
111
1. INTRODUCTION
Proteomics is widely accepted as a key technology in the postgenomic
era to investigate global protein synthesis and gene expression. Technical
developments in separation methods allow the simultaneous analysis of a
significant proportion of cell’s proteome. Improved methods of protein
identification can reliably link the proteome and genome to provide a
global picture of a cell’s metabolism. These technological advancements
have led to the continued expansion of proteomic applications in the
biomedical science and include studies on bacterial pathogenesis. The
characterization of the proteomes of bacterial pathogens growing in their
hosts remains a future challenge.
In the last decade, rapid advancements in sequencing technology
have lead to the completion of a whole tranche of bacterial genomes. Two
main routes to bacterial genomics have been followed. The first was
contingent upon the generation of a physical map using cloned genomic
fragments in a phage or plasmid library, with the individual cloned
fragments then being sequenced and aligned to the physical map. The
genome sequence of Escherichia coli was determined in this way
(Blattner et al., 1997). In the second, essentially random fragments of the
genome were cloned in plasmid and phage libraries, with the inserts’
112
terminal sequences then determined and the sequenced fragments
assembled into the complete genome sequence.
This methodology has been used to determine the genome
sequences of many other bacteria including Haemophilus influenzae
(Fleischmann et al., 1995), Mycoplasma genitalium (Fraser et al., 1995),
Methanococcus jannaschii (Bult et al., 1996), and Helicobacter pylori
(Tomb et al., 1997). The rest, of course, is history. Presently, the number
of completed or partially completed sequencing projects is in the region
of hundreds, rather than tens, of genomes (Paine et al., 2002). Once
determined, analysis of genome sequences using gene prediction
programs has identified large numbers of ORFs, many were previously
unknown. While, it proved possible to assign functions to proteins
encoded by the majority of ORFs on the basis of their homology to extant
sequences, a significant number of ORFs show no obvious similarity to
genes of known function.
This has led to the development of many postgenomic strategies,
such as proteomics, which seek to determine function. Bacteria have
special features, generally lacking in other organisms, for proteomic
analysis, that result from the abundance of information on their genomes,
their low levels of functional redundancy, their relative simplicity of gene
regulation, and their experimental tractability. Within the context of
vaccinology, one of the key goals of postgenomic research is to
113
determine differences between two related microbes, or, more generally,
cells, or between the same microbe or cell under different growth
conditions (Grandi et al., 2001).
Recently, the application of global identification methodologies has
resulted in identification of quorum-regulated processes as well as the
characterization of quorum circuit archithcture in E. coli, Streptococcus
pneumoniae and Pseudomonas aeruginosa (Delisa et al., 2001). Among
these, transcriptom analysis using DNA microarray has resulted in a huge
amount of data in genes likely to be involved in virulence factors.
However, this method only represents mRNA levels, the transmitters of
genetic information, not levels of functional cellular and extracellular
proteins.
The aim of this study was to determine the protein changes of
EHEC strain by inactivated luxS gene. E. coli, a species with a well-
known protein patterns in proteomics databases (Han and Lee, 2006)
were chosen as a test organism. The results should contribute to the
understanding of the function of luxS gene and its biological effect on
bacterial proteins. The production of new proteins and/or changes in a
regulatory mechanism can have unforeseen effects on the physiology of
the host cells, with possibly detrimental consequences to the desired
application.
114
2. MATERIALS AND METHODS
Preparation of secreted proteins and cellular proteins
The bacterial cells were harvested by centrifugation for 40 min at 4 at ℃
8000 × g. The supernatant was discarded and the pellet was washed three
times with PBS. Following centrifugation, pellet was suspended in a lysis
buffer (40 mM Tris-HCl, 1% Triton X-100, 1 mM MgSO4• 7H2O, 1 mM
EDTA; pH 8.0) containing 1 mM PMSF. The cells were lysed on ice by
sonicating 5 to 6 times for 10s with an 80% pulse duration until a clear
solution was obtained. For the preparation of secreted proteins of
EHEC strains, overnight cultures in Nutrient broth were diluted 1:50 in
Dulbecco’s modified Eagle’s medium (DMEM) and were incubated for
12 hrs, respectively, at 37 in a 5%℃ (vol/vol) CO2 atmosphere. Bacterial
cells were removed from the culture by centrifugation (5,500 × g, 10 min,
4 ), and the supernatant was filtered through a 0.22 ℃ ㎛-pore size small-
protein binding filter (Millex; Millipore, Bedford, U.S.A). PMSF (3 mM)
was added when the cultures were harvested to prevent proteolysis during
sample preparation. The secreted protein fraction was isolated by
trichloroacetic acid precipitation, and the protein pellet was washed thrice
with -20 acetone and then℃ air dried. The protein pellet was solubilized
in ReadyPrep reagent 3 (5 M urea, 2 M thiourea, 2%[wt/vol] CHAPS,
115
2%[wt/vol] SB 3-10, 40 mM Tris, and 0.2% [wt/vol] Bio-Lyte 3/10
ampholyte; Bio-Rad, Richmond, U.S.A.) and was stored at -20℃ until
analysis. The protein concentration was determined by use of a Bio-Rad
protein assay kit, with bovine serum albumin as a standard.
SDS-PAGE
Protein concentration was measured by the method of Bradford (1976),
using bovine serum albumin (BSA) (Sigma, St. Louis, U.S.A.) as
standard. The specificactivity was expressed as the enzymatic activity (U)
per mg of protein. Polyacrylamide gel electrophoresis (PAGE) (12.5%,
w/w) in the presence of sodium dodecyl sulfate (SDS) was carried out by
the method of Laemmli (1970). The electrophoresed protein gels were
stained with Coomassie brilliant blue R250 (Sigma, St. Louis, U.S.A.).
Isoelectric focusing (IEF)
IEF was carried out using 13 cm, pH 4-7 linear Immobiline IPG gels
(Amersham Biosciences, Piscataway, U.S.A.). The sample was loaded by
in-gel rehydration by mixing 100 ㎍ of protein sample with re-swelling
solution containing 8 M urea, 2.0% w/v CHAPS, 0.3% w/v DTT, 2.0%
v/v pH 4-7 IPG buffer (Amersham Biosciences, Piscataway, U.S.A.), and
a trace of bromophenol blue, to a final volume of 350 ㎕. This final
116
sample mixture was applied to an IPG gel, which was incubated at room
temperature for 10 hrs. IEF was carried out for 76500 Vhr at 20 in a ℃
IPG phor (Amersham Biosciences, Piscataway, U.S.A.), whrerin the
voltage was linearly increased from 500 V to 3500 V over the first 5 hrs,
and then maintained at 3500 V for the final 17.5 hrs by an EPS 3500 XL
power supply (Amersham Biosciences, Piscataway, U.S.A.).
Two dimensional gel electrophoresis (2-DE)
After equilibration, the IPG gels were transferred to the top of 12 % SDS
gel, with the IPG gels pressed firmly to the slab gel surface to ensure
successful protein transfer. SDS-PAGE was carried out in a Pretean ll xi
Multi-Cell (Bio-Rad, Richmond, U.S.A.) at 40 mA per gel, using the
PlusOne Sliver Staining Kit (Amersham Biosciences, Piscataway,
U.S.A.).
In gel proteolytic digestion and MALDI-TOF
The sample preparation for MALDI-TOF/MS was performed using a
method described elsewhere. Briefly, the protein spots of interest were
excised and destained by washing with 25 mM ammonium bicarbonate
containing 50% CAN. The gels were dehydrated by adding 100% CAN,
rehydrated in ice by adding 20 ㎕ of 25 mM ammonium bicarbonate
117
containing 10 mg/mL of sequencing grade modified trypsin(Promega,
Madison, U.S.A.). After incubation at 37 for 20 hrs, the peptides were ℃
extracted with 0.1% TFA in 50% ACN. The supernatants were recovered
and dried in the Speed-Vac. The samples were reconstituted in 0.1% TFA
and concentrated with C18 ZipTipsTM (Millipore, Bedford, U.S.A.). The
purified peptides were eluted with a saturated matrix solution (CHCA in
60% CAN and 0.1% TFA). The monoisotopic masses(M + 1) of the
tryptic fragments were measured in a Perspective Biosystem MALDI-
TOF/MS voyager DE-STR Mass Spectrometer (Perspective Biosystem ,
Framingham, U.S.A.).
Data analysis
The spectra were searched and identified using the MS-Fit system
(http:// prospector.ucsf.edu/prospector/4.0.8/html/msfit.htm) and
MASCOT (http://matrixscience.com) with an E. coli subset of NCBI
database. The known keratin masses and trypsin autodigest products were
excluded from the searches. The parameters were set as either missed
cleavage or acrylamide modification. The protein identities were assigned
if at lease five peptide masses matched within a maximum error of 50
ppm, and the candidate agreed with the estimated pI and molecular
weight from the 2-DE gels. The fold difference changes were analyzed
using the Melanie 7.0 software (ExpaSy, Rosen, Switzerland).
118
Statical analysis
All experiments were conducted at least in triplicate. The effects of each
of the treatment were analyzed by ANOVA, followed by Duncan's test in
SAS software package (Version 9.1; SAS Inc., Cary, U.S.A.). The level
of significance was defined at p<0.05.
119
3. RESULTS
Patterns of proteome in clinical isolate and standard
strain
To examine the expression patterns of proteome between the clinical
isolate and standard strain, these strains were performed 2-DE with each
strain. As a result, about 360 proteome spots were identified from the
each strain, and all of them showed similar patterns. The mass and
thickness proteome spots were mainly related to the general metabolism
of the strains and showed similar expression patterns. The rest of the
different spots were also identified, which showed very similar
expression patterns, although it was the proteome analysis between the
different strains (Fig. III-1 ).
SDS-PAGE and 2-DE analysis of luxS/QS related
strains
Before strains were performed a proteome analysis between the strains,
the expression patterns of the protein were examined by SDS-PAGE. The
result of coomassie brilliant blue staining after SDS-PAGE by extracting
protein from the three strains (CI03J, ML03J, and RL03J) used for the
120
results showed that similar protein patterns existed for the three strains,
but a different protein was not found among them. In the case of cellular
proteins, a number of bands were identified, but relatively few bands
were identified in the result on extracellular proteins. Moreover, while the
band moved stably on the cellular protein gels, the smearing of the band
was noticeable in the case of secreted proteins (Fig. III-2). In the test
using 2-DE, meanwhile, exact identification of the expressed proteome
was possible.
121
Figure III-1. 2-DE images of EDL 933(ATCC43895) EHEC O157:H7
and CI03J(clinical isolate) EHEC O157:H7. Gel were stained with
silver nitrate and analysised with Melanin 2D program.
pH 4-7 pH 4-7
EDL933(ATCC43895) CI03J (clinical isolate)
10 10
250
(kDa)
250
(kDa)
pH 4-7 pH 4-7
EDL933(ATCC43895) CI03J (clinical isolate)
10 10
250
(kDa)
250
(kDa)
122
Figure III-2. SDS-PAGE of proteins in CI03J (wild-type strain),
ML03J (luxS mutant) and RL03J(ML03J complemented with
pEXP5-CT). Lane M, molecular weight marker proteins; lane 1 and 2,
cellular proteins of CI03J; lane 3 and 4, cellular proteins of ML03J; lane
5 and 6, cellular proteins of RL03J; lane 7 and 8, secreted proteins of
CI03J; lane 9 and 10, secreted proteins of ML03J, lane 11 and 12,
secreted proteins of RL03J.
M 1 2 3 4 5 6 7 8 9 10 11 12M 1 2 3 4 5 6 7 8 9 10 11 12
123
Proteome profiling wild-type, luxS mutant and
complement strains
After testing 2DE with the three strains, these were identified about 200
from the entire proteome. Although most proteome was related to
metabolism, these results were drew out the main pathogenic factors. The
identification of the entire proteome and the difference of expression
among the three germ strains are shown in Table III-1, 2. Fig.III-3 and 4
show the comparative analysis of the difference between proteins, and
this is indicated in Table III-1 and 2.
Influence of luxS mutation on protein expression in
EHEC O157:H7
Strains were further analyzed the proteome profiles in CI03J, its
isogenic luxS mutant strain ML03J, and complemented strain RL03J (Fig.
III-4 and 5). As summarized in Table III-3 and 4 , the total 41 proteins
were differentially expressed at least 2-fold by deletion of luxS.
For the entire extracted proteins, including the proteins for which a
difference was identified, the expression difference was examined using
an intensity-based analysis program. After comparing the relative protein
density of CI03J and ML03J, the spot with the biggest difference was
DNA primase, which showed about 150-fold density difference, and the
124
spot with the smallest difference was fliN, which showed about 1.2 times
difference. Most proteins showed up to 2~4 folds expression difference.
Among the proteins extracted, cytolysin A (2.1 folds), the pore forming
toxin, identified as virulence factor, SepD (4 folds), the effector molecule,
related to T3SS, and Shiga toxin II subunit B (3 folds) were found, the
toxin known as the main pathogenic factor of EHEC. Surprisingly, a
dramatic increase in expression of the pO157-encoded hemolysin in the
CI03J as compared to the luxS mutant ML03J were observed. In addition,
we identified some LuxS-dependent proteins, such as cytolysin A and
phospholipase A, which have not been previously reported.
125
Figure III-3. Comparative 2-DE of soluble proteins fraction of CI03J(wild-type), ML03J(luxS mutant) and
RL03J(complemented luxS gene)
pH4-7 pH4-7 pH4-7 pH4-7 pH4-7pH4-7
Area-1 Area-1 Area-1
Area-2Area-2 Area-2
Area-3 Area-3 Area-3
Area-4 Area-4Area-4
Area-5 Area-5 Area-5
Area-6Area-6Area-6
CI03J(cellular proteins)
ML03J(cellular proteins)
RL03J(cellular proteins)
CI03J(secreted proteins)
ML03J(secreted proteins)
RL03J(secreted proteins)
pH4-7 pH4-7 pH4-7 pH4-7 pH4-7pH4-7
Area-1 Area-1 Area-1
Area-2Area-2 Area-2
Area-3 Area-3 Area-3
Area-4 Area-4Area-4
Area-5 Area-5 Area-5
Area-6Area-6Area-6
pH4-7 pH4-7 pH4-7 pH4-7 pH4-7pH4-7pH4-7pH4-7 pH4-7pH4-7 pH4-7pH4-7 pH4-7pH4-7 pH4-7pH4-7pH4-7pH4-7
Area-1 Area-1 Area-1
Area-2Area-2 Area-2
Area-3 Area-3 Area-3
Area-4 Area-4Area-4
Area-5 Area-5 Area-5
Area-6Area-6Area-6
CI03J(cellular proteins)
ML03J(cellular proteins)
RL03J(cellular proteins)
CI03J(secreted proteins)
ML03J(secreted proteins)
RL03J(secreted proteins)
126
Figure III-4. A: Cellular proteomes(CPs) of strains, B: Secreted proteomes (ECPs) of strains.
ECP1ECP2
ECP3
ECP4 ECP5
ECP6ECP7 ECP8 ECP9
ECP10
ECP11
ECP12ECP13
ECP15
ECP14
ECP16
ECP17
ECP18
ECP22
ECP19
ECP20
CI03J(luxS+) ML03J(luxS-) RL03J(luxS+)
CP1
CP2
CP3
CP9CP5
CP8
CP14
CP12
CP13
CP15
CP16
CP6CP7
CP10CP11
CP4
CP19
CP17
CP18
ECP21
A
B
pI4-7 pI4-7 pI4-7
pI4-7 pI4-7
10
250
(Kda)
10
250
(Kda)
ECP1ECP2
ECP3
ECP4 ECP5
ECP6ECP7 ECP8 ECP9
ECP10
ECP11
ECP12ECP13
ECP15
ECP14
ECP16
ECP17
ECP18
ECP22
ECP19
ECP20
CI03J(luxS+) ML03J(luxS-) RL03J(luxS+)
CP1
CP2
CP3
CP9CP5
CP8
CP14
CP12
CP13
CP15
CP16
CP6CP7
CP10CP11
CP4
CP19
CP17
CP18
ECP21
A
B
pI4-7 pI4-7 pI4-7
pI4-7 pI4-7
10
250
(Kda)
10
250
(Kda)
127
Figure III-5. Two dimentional gel electrophoresis(2-DE) images of differntially expressed proteomes in strains.
CI03J(W), ML03J(M) and RL03J(R).
Cellular proteins
FliC
(CP4)
Flagellin
(CP7)
FliC
flagellin
EspG protein(CP10)
Hemolysin(CP14)
WWWW MMMM RRRR
Extracellular proteins
WWWW MMMM RRRR
Cytolysin A(ECP4)
CheA protein(ECP10)
SepD(ECP12)
Shiga toxin II subunit B(ECP17)
Cellular proteins
FliC
(CP4)
Flagellin
(CP7)
FliC
flagellin
EspG protein(CP10)
Hemolysin(CP14)
WWWW MMMM RRRR
Extracellular proteins
WWWW MMMM RRRR
Cytolysin A(ECP4)
CheA protein(ECP10)
SepD(ECP12)
Shiga toxin II subunit B(ECP17)
128
Table III-1. Cellular proteome profiles of CI03J, RL03J and ML03J
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-1 PCFO71 outermembrane usher protein 46369881 97136 5.7 51 - 4 51.0 12.8 4.0
C-2 transcriptional regulator 1789193M 83716 5.6 - 32 40 (32.0) (40.0) 1.3
C-3 type II secretion protein COG0060 3822148M 55930 5.9 188 191 165 (1.0) 1.1 (1.2)
C-4 ATPse involved in DNA repair 75513221M 61397 5.4 43 23 3 1.9 14.3 (7.7)
C-5 translation initiation factor IF2-3 12053635 78984 5.7 - 30 39 (30.0) (39.0) 1.3
C-6 phosphoenolpyruvate protein 18152906 58385 5.1 58 48 77 1.2 (1.3) 1.6
C-7 FliC 30059860M 68134 4.5 48 11 150 4.4 (3.1) 13.6
C-8 unnamed protein product 762929 52649 5.5 87 58 91 1.5 1.0 1.6
C-9 flagellin 6009845 57809 4.7 187 - 148 187.0 1.3 148.0
C-10 signal transduction histidine kinase 75196984M 50282 5.5 105 74 179 1.4 (1.7) 2.4
C-11 unreadable - - - 141 - 103 141.0 1.4 103.0
C-12 unnamed protein product 41563 52095 5.2 140 103 179 1.4 (1.3) 1.7
C-13 GroEL 18028158 57304 4.9 109 62 50 1.8 2.2 (1.3)
C-14 flagellin 33590252 52404 4.9 38 39 92 (1.0) (2.4) 2.4
C-15 LeoA 6653193 64942 5.1 23 17 43 1.4 (1.9) 2.5
C-16 flagellin 33590250 62353 4.5 48 - 83 48.0 (1.7) 83.0
C-17 translocated intimin receptor 63002564M 58009 5 109 94 115 1.2 (1.1) 1.2
C-18 K+ efflux antiporter, glutathione regulated 1786232M 67796 5.7 88 6 112 14.6 (1.3) 18.7
C-19 ManC 56122507 52311 5.7 140 74 134 1.9 1.0 1.8
C-20 alpha-D-fructohydrolase 44829550M 52589 5.2 143 128 161 1.1 (1.1) 1.3
C-21 biosynthesis; flagellin, filament structural protein 1788232M 51295 4.5 153 - 160 153.0 1.0 160.0
C-22 conserved hypothetical protein 85674993M 62803 5.7 74 70 4 1.1 18.5 (17.5)
C-23 unnamed protein product 41617M 57269 4.8 69 65 93 1.1 (1.3) 1.4
C-24 hypothetical protein pO157 p50 10955316M 71658 5.2 - - 63 - 63.0 63.0
C-25 RmlB 63033901 40516 5.5 102 89 109 1.1 (1.1) 1.2
C-26 aspartate aminotarnsferase 78214811 43579 5.5 149 73 157 1.2 (1.1) 2.2
C-27 hypothetical protein 85677000M 69578 5.8 - - 25 - 25.0 25.0
C-28 hypothetical protein pO157 p50 10955316M 39574 5.6 78 84 134 (1.1) (1.7) 1.6
C-29 biotin synthase and related enzymes 75511378M 39648 5.3 70 17 149 4.1 (2.1) 8.8
C-30 orf, hypothetical protein 1788606M 63634 5.7 167 78 162 2.1 1.0 2.1
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-1 PCFO71 outermembrane usher protein 46369881 97136 5.7 51 - 4 51.0 12.8 4.0
C-2 transcriptional regulator 1789193M 83716 5.6 - 32 40 (32.0) (40.0) 1.3
C-3 type II secretion protein COG0060 3822148M 55930 5.9 188 191 165 (1.0) 1.1 (1.2)
C-4 ATPse involved in DNA repair 75513221M 61397 5.4 43 23 3 1.9 14.3 (7.7)
C-5 translation initiation factor IF2-3 12053635 78984 5.7 - 30 39 (30.0) (39.0) 1.3
C-6 phosphoenolpyruvate protein 18152906 58385 5.1 58 48 77 1.2 (1.3) 1.6
C-7 FliC 30059860M 68134 4.5 48 11 150 4.4 (3.1) 13.6
C-8 unnamed protein product 762929 52649 5.5 87 58 91 1.5 1.0 1.6
C-9 flagellin 6009845 57809 4.7 187 - 148 187.0 1.3 148.0
C-10 signal transduction histidine kinase 75196984M 50282 5.5 105 74 179 1.4 (1.7) 2.4
C-11 unreadable - - - 141 - 103 141.0 1.4 103.0
C-12 unnamed protein product 41563 52095 5.2 140 103 179 1.4 (1.3) 1.7
C-13 GroEL 18028158 57304 4.9 109 62 50 1.8 2.2 (1.3)
C-14 flagellin 33590252 52404 4.9 38 39 92 (1.0) (2.4) 2.4
C-15 LeoA 6653193 64942 5.1 23 17 43 1.4 (1.9) 2.5
C-16 flagellin 33590250 62353 4.5 48 - 83 48.0 (1.7) 83.0
C-17 translocated intimin receptor 63002564M 58009 5 109 94 115 1.2 (1.1) 1.2
C-18 K+ efflux antiporter, glutathione regulated 1786232M 67796 5.7 88 6 112 14.6 (1.3) 18.7
C-19 ManC 56122507 52311 5.7 140 74 134 1.9 1.0 1.8
C-20 alpha-D-fructohydrolase 44829550M 52589 5.2 143 128 161 1.1 (1.1) 1.3
C-21 biosynthesis; flagellin, filament structural protein 1788232M 51295 4.5 153 - 160 153.0 1.0 160.0
C-22 conserved hypothetical protein 85674993M 62803 5.7 74 70 4 1.1 18.5 (17.5)
C-23 unnamed protein product 41617M 57269 4.8 69 65 93 1.1 (1.3) 1.4
C-24 hypothetical protein pO157 p50 10955316M 71658 5.2 - - 63 - 63.0 63.0
C-25 RmlB 63033901 40516 5.5 102 89 109 1.1 (1.1) 1.2
C-26 aspartate aminotarnsferase 78214811 43579 5.5 149 73 157 1.2 (1.1) 2.2
C-27 hypothetical protein 85677000M 69578 5.8 - - 25 - 25.0 25.0
C-28 hypothetical protein pO157 p50 10955316M 39574 5.6 78 84 134 (1.1) (1.7) 1.6
C-29 biotin synthase and related enzymes 75511378M 39648 5.3 70 17 149 4.1 (2.1) 8.8
C-30 orf, hypothetical protein 1788606M 63634 5.7 167 78 162 2.1 1.0 2.1
129
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-31 hypothetical protein 10955316M 71658 5.2 98 94 101 1.0 1.0 1.1
C-32 UDP-glucose-6-dehydrogenase 11464509M 43713 5.9 30 191 95 (6.4) (3.2) (2.0)
C-33 orf, hypothetical protein 1786897M 52781 4.8 185 103 135 1.8 1.4 1.3
C-34 EspG protein 54311594 43901 5.2 71 34 114 2.1 (1.6) 3.4
C-35 rOrf2 2865270 43919 5.2 92 - 146 92.0 (1.6) 146.0
C-36 IucA 71274418 65539 5.7 74 62 60 1.2 1.2 1.0
C-37 unnamed protein product 4467402M 58014 5.2 51 30 171 1.7 (3.4) 5.7
C-38 DNA gyrase subunit A 41642 97036 5.1 192 76 170 2.5 1.1 2.2
C-39 protein kinase 606149 87826 5 15 6 51 2.5 (3.4) 8.5
C-40 probable outer membrane porin protein 1786332M 95500 4.9 102 35 61 2.9 1.7 1.7
C-41 putative outer membrane proteinVpr 21307716 90584 4.9 22 20 91 1.1 (4.1) 4.6
C-42 unknown 598469 81571 5.9 - - 41 - (41.0) 41.0
C-43 KfoE hypothetical protein 21326781 60806 6.1 10 25 70 (2.5) (7.0) 2.8
C-44 orf, hypothetical protein 1788981M 62007 5.6 71 62 25 1.2 2.8 (2.5)
C-45 putative membrane protein 48994919M 91793 5.1 199 26 151 7.7 1.3 5.8
C-46 Malata synthase 75515234M 80489 5.8 - - 26 - (26.0) 26.0
C-47 Aconitase B 75511993M 93499 5.2 183 - 173 183.0 1.1 173.0
C-48 Rnase G 1789645M 56065 5.7 65 23 77 2.8 (1.2) 3.3
C-49 putative membrane protein 48994919M 91793 5.1 183 - 173 183.0 1.1 173.0
C-50 TraD 32470007M 81490 5.3 19 17 112 1.1 (5.9) 6.6
C-51 NAD-dependent DNA ligase 75515754M 73607 5.4 39 28 23 1.4 1.7 (1.2)
C-52 ATP-dependent protease binding subunit 147365 95544 5.3 82 - 72 82.0 1.1 72.0
C-53 WbrX 46487632 82231 5.3 25 20 29 1.3 (1.2) 1.5
C-54 HlyD protein 2208952 54466 5.7 154 69 158 2.2 1.0 2.3
C-55 Hemolysin secretion protein D, chromosomal 123194M 54591 5.8 77 70 137 1.1 (1.8) 2.0
C-56 transduction histidine kinase regulating citrate 75514713M 61685 5.8 40 21 39 1.9 1.0 1.9
C-57 endonuclease 45157173M 117088 5.8 8 - 6 8.0 1.3 6.0
C-58 unreadable - - - 100 90 144 1.1 (1.4) 1.6
C-59 Uncharacterized protein conserved in bacteria 75241710M 55656 5.4 95 175 138 (1.8) (1.5) (1.3)
C-60 predicted GTPase 85677092M 35660 4.8 64 - 134 64.0 (2.1) 134.0
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-31 hypothetical protein 10955316M 71658 5.2 98 94 101 1.0 1.0 1.1
C-32 UDP-glucose-6-dehydrogenase 11464509M 43713 5.9 30 191 95 (6.4) (3.2) (2.0)
C-33 orf, hypothetical protein 1786897M 52781 4.8 185 103 135 1.8 1.4 1.3
C-34 EspG protein 54311594 43901 5.2 71 34 114 2.1 (1.6) 3.4
C-35 rOrf2 2865270 43919 5.2 92 - 146 92.0 (1.6) 146.0
C-36 IucA 71274418 65539 5.7 74 62 60 1.2 1.2 1.0
C-37 unnamed protein product 4467402M 58014 5.2 51 30 171 1.7 (3.4) 5.7
C-38 DNA gyrase subunit A 41642 97036 5.1 192 76 170 2.5 1.1 2.2
C-39 protein kinase 606149 87826 5 15 6 51 2.5 (3.4) 8.5
C-40 probable outer membrane porin protein 1786332M 95500 4.9 102 35 61 2.9 1.7 1.7
C-41 putative outer membrane proteinVpr 21307716 90584 4.9 22 20 91 1.1 (4.1) 4.6
C-42 unknown 598469 81571 5.9 - - 41 - (41.0) 41.0
C-43 KfoE hypothetical protein 21326781 60806 6.1 10 25 70 (2.5) (7.0) 2.8
C-44 orf, hypothetical protein 1788981M 62007 5.6 71 62 25 1.2 2.8 (2.5)
C-45 putative membrane protein 48994919M 91793 5.1 199 26 151 7.7 1.3 5.8
C-46 Malata synthase 75515234M 80489 5.8 - - 26 - (26.0) 26.0
C-47 Aconitase B 75511993M 93499 5.2 183 - 173 183.0 1.1 173.0
C-48 Rnase G 1789645M 56065 5.7 65 23 77 2.8 (1.2) 3.3
C-49 putative membrane protein 48994919M 91793 5.1 183 - 173 183.0 1.1 173.0
C-50 TraD 32470007M 81490 5.3 19 17 112 1.1 (5.9) 6.6
C-51 NAD-dependent DNA ligase 75515754M 73607 5.4 39 28 23 1.4 1.7 (1.2)
C-52 ATP-dependent protease binding subunit 147365 95544 5.3 82 - 72 82.0 1.1 72.0
C-53 WbrX 46487632 82231 5.3 25 20 29 1.3 (1.2) 1.5
C-54 HlyD protein 2208952 54466 5.7 154 69 158 2.2 1.0 2.3
C-55 Hemolysin secretion protein D, chromosomal 123194M 54591 5.8 77 70 137 1.1 (1.8) 2.0
C-56 transduction histidine kinase regulating citrate 75514713M 61685 5.8 40 21 39 1.9 1.0 1.9
C-57 endonuclease 45157173M 117088 5.8 8 - 6 8.0 1.3 6.0
C-58 unreadable - - - 100 90 144 1.1 (1.4) 1.6
C-59 Uncharacterized protein conserved in bacteria 75241710M 55656 5.4 95 175 138 (1.8) (1.5) (1.3)
C-60 predicted GTPase 85677092M 35660 4.8 64 - 134 64.0 (2.1) 134.0
130
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-61 COG2186: transcriptional regulators 75258405M 29308 5 112 12 68 9.3 1.6 5.7
C-62 COG1494: transcriptional regulators 75242242M 29260 5.1 75 32 91 2.3 (1.2) 2.8
C-63 orf, hypothetical protein 1790330M 39295 5 136 - 133 136.0 1.0 133.0
C-64 unnamed protein product 40944 35556 5.9 10 99 9 9.9 1.1 (11.0)
C-65 acylneuraminate cytidylyltransferase 128091M 48737 5.9 34 38 155 1.1 (4.6) 4.1
C-66 unreadable - - - 53 52 91 1.0 (1.7) 1.8
C-67 EspB protein 57434443 33234 5.3 44 40 18 1.1 2.4 (2.2)
C-68 Ugd 56123321 43452 5.4 148 72 147 2.1 1.0 2.0
C-69 hypothetical protein 51465236M 32669 5.3 16 24 45 1.5 (2.8) 1.9
C-70 eprH 71388152 45247 4.9 45 40 48 1.1 (1.1) 1.2
C-71 pyruvate/2-oxoglutarate dehydrogenase complex 75511614 44012 5.6 44 42 78 1.1 (1.8) 1.9
C-72 lateral flagellar associates protein 59889774 35284 5.1 95 88 127 1.1 (1.3) 1.4
C-73 predicted tagatose 6-phosphate kinase 75186886M 47109 5.5 50 50 91 1.0 (1.8) 1.8
C-74 orf, hypothetical protein 1790865M 25259 5.6 89 106 63 (1.2) 1.4 (1.7)
C-75 isocitrate dehydrogenase 33383643 42913 5.2 105 191 115 (1.8) (1.1) (1.7)
C-76 mannonate hydrolase 1790778M 44838 5.4 92 91 168 1.0 (1.8) 1.8
C-77 putatuve TerA protein 24266667 32794 5.7 20 135 49 (6.8) (2.5) (2.8)
C-78 hypothetical protein yjiP 19859207 35888 6 67 70 96 (1.0) (1.4) 1.4
C-79 ClyA 18026879 33801 5.1 32 55 106 (1.7) (3.3) 1.9
C-80 fepC 41432 29869 6.2 105 96 122 1.1 (1.2) 1.3
C-81 cobalamin/Fe3+-siderophores transport components 75258674M 29784 6.1 93 83 109 1.1 (1.2) 1.3
C-82 hypothetical protein 75512106M 20589 5.2 40 - 28 40.0 1.4 28.0
C-83 dehydrogenase with different specificities 75512948M 26779 5.2 61 21 29 2.9 2.1 1.4
C-84 restriction of methylated adenine 1790811M 33520 5.7 49 84 73 (1.7) (1.5) (1.2)
C-85 RNA polymerase subunit sigma-38 55274877M 23057 5.3 89 56 42 1.6 2.1 (1.3)
C-86 orf, hypothetical protein 1788788M 22907 5.4 50 19 47 2.6 1.1 2.5
C-87 homoserin kinase 41057990 31689 5.8 16 11 93 1.5 (5.8) 8.5
C-88 O-antigen component of lipopolysaccharide chains 1736706M 36455 5.4 37 26 78 1.4 (2.1) 3.0
C-89 hemolysin 4704412 33555 5.2 166 - 174 166.0 1.0 174.0
C-90 orf, hypothetical protein 1788000M 27046 5.6 166 126 143 1.3 1.2 1.1
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-61 COG2186: transcriptional regulators 75258405M 29308 5 112 12 68 9.3 1.6 5.7
C-62 COG1494: transcriptional regulators 75242242M 29260 5.1 75 32 91 2.3 (1.2) 2.8
C-63 orf, hypothetical protein 1790330M 39295 5 136 - 133 136.0 1.0 133.0
C-64 unnamed protein product 40944 35556 5.9 10 99 9 9.9 1.1 (11.0)
C-65 acylneuraminate cytidylyltransferase 128091M 48737 5.9 34 38 155 1.1 (4.6) 4.1
C-66 unreadable - - - 53 52 91 1.0 (1.7) 1.8
C-67 EspB protein 57434443 33234 5.3 44 40 18 1.1 2.4 (2.2)
C-68 Ugd 56123321 43452 5.4 148 72 147 2.1 1.0 2.0
C-69 hypothetical protein 51465236M 32669 5.3 16 24 45 1.5 (2.8) 1.9
C-70 eprH 71388152 45247 4.9 45 40 48 1.1 (1.1) 1.2
C-71 pyruvate/2-oxoglutarate dehydrogenase complex 75511614 44012 5.6 44 42 78 1.1 (1.8) 1.9
C-72 lateral flagellar associates protein 59889774 35284 5.1 95 88 127 1.1 (1.3) 1.4
C-73 predicted tagatose 6-phosphate kinase 75186886M 47109 5.5 50 50 91 1.0 (1.8) 1.8
C-74 orf, hypothetical protein 1790865M 25259 5.6 89 106 63 (1.2) 1.4 (1.7)
C-75 isocitrate dehydrogenase 33383643 42913 5.2 105 191 115 (1.8) (1.1) (1.7)
C-76 mannonate hydrolase 1790778M 44838 5.4 92 91 168 1.0 (1.8) 1.8
C-77 putatuve TerA protein 24266667 32794 5.7 20 135 49 (6.8) (2.5) (2.8)
C-78 hypothetical protein yjiP 19859207 35888 6 67 70 96 (1.0) (1.4) 1.4
C-79 ClyA 18026879 33801 5.1 32 55 106 (1.7) (3.3) 1.9
C-80 fepC 41432 29869 6.2 105 96 122 1.1 (1.2) 1.3
C-81 cobalamin/Fe3+-siderophores transport components 75258674M 29784 6.1 93 83 109 1.1 (1.2) 1.3
C-82 hypothetical protein 75512106M 20589 5.2 40 - 28 40.0 1.4 28.0
C-83 dehydrogenase with different specificities 75512948M 26779 5.2 61 21 29 2.9 2.1 1.4
C-84 restriction of methylated adenine 1790811M 33520 5.7 49 84 73 (1.7) (1.5) (1.2)
C-85 RNA polymerase subunit sigma-38 55274877M 23057 5.3 89 56 42 1.6 2.1 (1.3)
C-86 orf, hypothetical protein 1788788M 22907 5.4 50 19 47 2.6 1.1 2.5
C-87 homoserin kinase 41057990 31689 5.8 16 11 93 1.5 (5.8) 8.5
C-88 O-antigen component of lipopolysaccharide chains 1736706M 36455 5.4 37 26 78 1.4 (2.1) 3.0
C-89 hemolysin 4704412 33555 5.2 166 - 174 166.0 1.0 174.0
C-90 orf, hypothetical protein 1788000M 27046 5.6 166 126 143 1.3 1.2 1.1
131
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-91 orf, hypothetical protein 1789816M 33268 5.9 78 184 151 (2.4) (1.9) (1.2)
C-92 actin-like ATPase involved in cell 75256620M 36953 5.2 20 10 119 2.0 (6.0) 11.9
C-93 homoserin kinase 51449662M 31114 5.3 127 194 162 (1.5) (1.3) 0.8
C-94 hemolysin coregulated protein 75513636M 19256 5.5 166 56 - 3.0 166.0 (56.0)
C-95 TraF 49868031 42888 4.9 126 - 132 126.0 1.0 132.0
C-96 nitrogen regulator I 455662 48908 5.7 45 42 67 1.1 (1.5) 1.6
C-97 ST04 protein 17384630 44254 5.7 82 77 115 1.1 (1.4) 1.5
C-98 pspA protein 42539 25578 5.5 126 - 146 126.0 (1.2) 146.0
C-99 Uncharacterized conserved protein 75255879M 26423 4.7 59 27 113 2.2 (1.9) 4.2
C-100 orf, hypothetical protein 1788151M 23687 5.3 30 - 52 30.0 (1.7) 52.0
C-101 orf, hypothetical protein 1788643M 34180 5.6 43 63 104 (1.5) (2.4) 1.7
C-102 RpoS 4100834 29636 5 12 6 52 2.0 (4.3) 8.7
C-103 RNA polymerase subunit sigma-48 54401878 27360 5.8 36 60 99 (1.7) (2.8) 1.7
C-104 NTP pyrophosphohydrolases containing a Zn-finger 75514763M 29689 5.5 137 141 138 (1.0) 1.0 1.0
C-105 P35 606106 35044 5.6 66 54 69 1.2 1.0 1.3
C-106 pseudouridine synthase 75513381M 35087 5.7 26 49 76 (1.9) (2.9) 1.6
C-107 orf, hypothetical protein 1788643M 34180 5.6 15 10 98 1.5 (6.5) 9.8
C-108 putative 2-component transcriptional regulator 1789402M 24678 6.5 78 189 150 (2.4) (1.9) (1.3)
C-109 predicted GTPase 85677092M 35660 4.8 121 98 104 1.2 1.2 1.1
C-110 unnamed protein product 42353 27585 5.1 8 165 30 (20.6) (3.8) (5.5)
C-111 orf, hypothetical protein 24051467M 17911 4.9 92 37 119 2.5 (1.3) 3.2
C-112 polymerase III subunit alpha 19548850 24092 5 135 147 142 (1.1) 1.0 1.0
C-113 orf, hypothetical protein 48995000M 34180 5.6 109 84 74 1.3 1.5 (1.1)
C-114 Fcf1 46487620 35595 5.6 70 28 158 2.5 (2.3) 5.6
C-115 malate/lactate dehydrogenase 75511868M 32338 5.6 50 57 106 (1.1) (2.1) 1.9
C-116 fructokinase 32329607 33021 5 189 170 166 1.1 1.1 1.0
C-117 probable fructokinase 1073355 33082 5.2 101 94 145 1.1 (1.4) 1.5
C-118 unnamed protein product 581223 21253 5.2 110 41 89 2.7 1.2 2.2
C-119 leucine/isoleucine/valine transporter subunit 85676589M 26310 5.6 109 44 140 2.5 (1.3) 3.2
C-120 TPA:hypothetical protein 86212233M 23254 5.3 141 35 145 4.0 1.0 4.1
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-91 orf, hypothetical protein 1789816M 33268 5.9 78 184 151 (2.4) (1.9) (1.2)
C-92 actin-like ATPase involved in cell 75256620M 36953 5.2 20 10 119 2.0 (6.0) 11.9
C-93 homoserin kinase 51449662M 31114 5.3 127 194 162 (1.5) (1.3) 0.8
C-94 hemolysin coregulated protein 75513636M 19256 5.5 166 56 - 3.0 166.0 (56.0)
C-95 TraF 49868031 42888 4.9 126 - 132 126.0 1.0 132.0
C-96 nitrogen regulator I 455662 48908 5.7 45 42 67 1.1 (1.5) 1.6
C-97 ST04 protein 17384630 44254 5.7 82 77 115 1.1 (1.4) 1.5
C-98 pspA protein 42539 25578 5.5 126 - 146 126.0 (1.2) 146.0
C-99 Uncharacterized conserved protein 75255879M 26423 4.7 59 27 113 2.2 (1.9) 4.2
C-100 orf, hypothetical protein 1788151M 23687 5.3 30 - 52 30.0 (1.7) 52.0
C-101 orf, hypothetical protein 1788643M 34180 5.6 43 63 104 (1.5) (2.4) 1.7
C-102 RpoS 4100834 29636 5 12 6 52 2.0 (4.3) 8.7
C-103 RNA polymerase subunit sigma-48 54401878 27360 5.8 36 60 99 (1.7) (2.8) 1.7
C-104 NTP pyrophosphohydrolases containing a Zn-finger 75514763M 29689 5.5 137 141 138 (1.0) 1.0 1.0
C-105 P35 606106 35044 5.6 66 54 69 1.2 1.0 1.3
C-106 pseudouridine synthase 75513381M 35087 5.7 26 49 76 (1.9) (2.9) 1.6
C-107 orf, hypothetical protein 1788643M 34180 5.6 15 10 98 1.5 (6.5) 9.8
C-108 putative 2-component transcriptional regulator 1789402M 24678 6.5 78 189 150 (2.4) (1.9) (1.3)
C-109 predicted GTPase 85677092M 35660 4.8 121 98 104 1.2 1.2 1.1
C-110 unnamed protein product 42353 27585 5.1 8 165 30 (20.6) (3.8) (5.5)
C-111 orf, hypothetical protein 24051467M 17911 4.9 92 37 119 2.5 (1.3) 3.2
C-112 polymerase III subunit alpha 19548850 24092 5 135 147 142 (1.1) 1.0 1.0
C-113 orf, hypothetical protein 48995000M 34180 5.6 109 84 74 1.3 1.5 (1.1)
C-114 Fcf1 46487620 35595 5.6 70 28 158 2.5 (2.3) 5.6
C-115 malate/lactate dehydrogenase 75511868M 32338 5.6 50 57 106 (1.1) (2.1) 1.9
C-116 fructokinase 32329607 33021 5 189 170 166 1.1 1.1 1.0
C-117 probable fructokinase 1073355 33082 5.2 101 94 145 1.1 (1.4) 1.5
C-118 unnamed protein product 581223 21253 5.2 110 41 89 2.7 1.2 2.2
C-119 leucine/isoleucine/valine transporter subunit 85676589M 26310 5.6 109 44 140 2.5 (1.3) 3.2
C-120 TPA:hypothetical protein 86212233M 23254 5.3 141 35 145 4.0 1.0 4.1
132
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-121 negative regulatorof sigma E activity 75513182 24322 5.1 82 86 10 (1.1) 8.2 (8.6)
C-122 KfiA 496605M 27332 5.3 12 - 16 12.0 (1.3) 16.0
C-123 typeIII secretion apparatus protein 62085064 22310 6 48 127 59 (2.7) (1.2) (2.2)
C-124 uncharacterized iron regulated protein 75512807M 25529 6 78 182 150 (2.3) (1.9) (1.2)
C-125 periplasmic component/domain 75512869M 26930 5.8 31 10 7 3.1 4.4 (1.4)
C-126 putative major fimbrial subunit 1850975 29302 4.9 66 52 78 1.3 (1.2) 1.5
C-127 uncharacterized stress induced protein 75514294M 33175 5.1 123 58 139 2.1 (1.1) 2.4
C-128 orf, hypothetical protein 1786725 28731 4.9 59 20 31 3.0 1.9 1.6
C-129 COG1309: transcriptional regulator 75514895 22776 4.9 146 37 147 4.0 1.0 4.0
C-130 orf, hypothetical protein 24054813 21931 4.9 123 46 109 2.7 1.1 2.4
C-131 unreadable - - - 64 68 84 (1.1) (1.3) 1.2
C-132 bacterioferritin 75511241M 18495 4.7 92 19 119 4.8 (1.3) 6.3
C-133 F0F1-type ATP synthase delta subunit 75258274M 19332 4.9 91 58 45 1.6 2.0 (1.3)
C-134 tryptophan synthase subunit B 37953704 37886 5.9 13 10 19 1.3 (1.3) 1.9
C-135 dehydrogenase 18266410M 43658 5.7 13 10 18 1.3 (1.4) 1.8
C-136 outer membrane protein 75231159M 38922 4.9 90 91 92 (1.0) 1.0 1.0
C-137 hypothetical protein 1789434 48389 5.7 49 43 63 1.1 (1.3) 1.5
C-138 VgrG protein 2920640 49845 6.1 - 25 40 (25.0) (40.0) 1.6
C-139 oligopeptide transport protein 89108090 57342 6.7 16 19 8 (1.2) 2.0 (2.4)
C-140 TraJ 51038823 42530 5.8 31 101 19 (3.3) 1.6 (5.3)
C-141 Orf_f408 606356 45130 5.3 162 158 168 1.0 1.0 1.1
C-142 TraC_4 4892 50124 5.6 80 48 146 1.7 (1.8) 3.0
C-143 phenylalanine tRNA synthetase 1742793 40142 5.3 163 134 118 1.2 1.4 (1.1)
C-144 hypothetical protein 89109723 46245 5.3 148 1.6 312.5 27.9 0.5 195.3
C-145 acyl-CoA thioesterase I 124530254 23563 4.6 134 4.2 (1.2) 29.1 (1.2) (0.3)
Spot number Protein name NCBI accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
C-121 negative regulatorof sigma E activity 75513182 24322 5.1 82 86 10 (1.1) 8.2 (8.6)
C-122 KfiA 496605M 27332 5.3 12 - 16 12.0 (1.3) 16.0
C-123 typeIII secretion apparatus protein 62085064 22310 6 48 127 59 (2.7) (1.2) (2.2)
C-124 uncharacterized iron regulated protein 75512807M 25529 6 78 182 150 (2.3) (1.9) (1.2)
C-125 periplasmic component/domain 75512869M 26930 5.8 31 10 7 3.1 4.4 (1.4)
C-126 putative major fimbrial subunit 1850975 29302 4.9 66 52 78 1.3 (1.2) 1.5
C-127 uncharacterized stress induced protein 75514294M 33175 5.1 123 58 139 2.1 (1.1) 2.4
C-128 orf, hypothetical protein 1786725 28731 4.9 59 20 31 3.0 1.9 1.6
C-129 COG1309: transcriptional regulator 75514895 22776 4.9 146 37 147 4.0 1.0 4.0
C-130 orf, hypothetical protein 24054813 21931 4.9 123 46 109 2.7 1.1 2.4
C-131 unreadable - - - 64 68 84 (1.1) (1.3) 1.2
C-132 bacterioferritin 75511241M 18495 4.7 92 19 119 4.8 (1.3) 6.3
C-133 F0F1-type ATP synthase delta subunit 75258274M 19332 4.9 91 58 45 1.6 2.0 (1.3)
C-134 tryptophan synthase subunit B 37953704 37886 5.9 13 10 19 1.3 (1.3) 1.9
C-135 dehydrogenase 18266410M 43658 5.7 13 10 18 1.3 (1.4) 1.8
C-136 outer membrane protein 75231159M 38922 4.9 90 91 92 (1.0) 1.0 1.0
C-137 hypothetical protein 1789434 48389 5.7 49 43 63 1.1 (1.3) 1.5
C-138 VgrG protein 2920640 49845 6.1 - 25 40 (25.0) (40.0) 1.6
C-139 oligopeptide transport protein 89108090 57342 6.7 16 19 8 (1.2) 2.0 (2.4)
C-140 TraJ 51038823 42530 5.8 31 101 19 (3.3) 1.6 (5.3)
C-141 Orf_f408 606356 45130 5.3 162 158 168 1.0 1.0 1.1
C-142 TraC_4 4892 50124 5.6 80 48 146 1.7 (1.8) 3.0
C-143 phenylalanine tRNA synthetase 1742793 40142 5.3 163 134 118 1.2 1.4 (1.1)
C-144 hypothetical protein 89109723 46245 5.3 148 1.6 312.5 27.9 0.5 195.3
C-145 acyl-CoA thioesterase I 124530254 23563 4.6 134 4.2 (1.2) 29.1 (1.2) (0.3)
133
Table III-2. Secreted (extracellular) proteome profiles of CI03J, RL03J and ML03J
Spots Protein name Accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
ECP-1 unreadable - - - 75 71 135 1.1 (1.8) 1.9
ECP-2 unreadable - - - 191 174 129 1.1 1.5 (1.4)
ECP-3 (rpoS)RNA polymerase sigma factor P13445 37972 4.9 132 5 150 26.4 (1.1) 30.0
ECP-4 (ybiK)putative L-asparaginase precursor P37595 33394 4.8 128 78 156 1.6 (1.2) 2.0
ECP-5 (traI)Tral protein(DNA helicase I) P22706 45168 5.6 150 106 87 1.4 1.7 (1.2)
ECP-6 (traC)DNA primase TraC P27190 40895 5.4 145 - 150 145.0 1.0 150.0
ECP-7 Lipoprotein 73853215M 42860 5.9 110 32 99 3.4 1.1 3.1
ECP-8 (rhsC)RhsC protein P16918 42777 6.2 166 82 147 2.0 1.1 1.8
ECP-9 unnamed protein product 10955265M 39574 5.6 45 - 63 45.0 (1.4) 63.0
ECP-10 cytolysinA 50953627M 33717 5.1 104 49 37 2.1 2.8 (1.3)
ECP-11 HsdM protein 4210349 36200 5.3 69 14 48 4.9 1.4 3.4
ECP-12 Hypothetical protein yeeJ P76347 24857 4.8 66 95 26 (1.4) 2.5 (3.7)
ECP-13 detergent resistant phospholipase A 148220 33171 5.2 153 41 56 3.7 2.7 1.4
ECP-14 dihydropteroate synthase 40548828 26585 5.3 69 24 54 2.9 1.3 2.3
ECP-15 Hypothetical protein ycjY P76049 34117 5.1 170 180 140 (1.1) 1.2 (1.3)
ECP-16 unnamed protein product 46811 34073 5 82 51 87 1.6 (1.1) 1.7
ECP-17 Hypothetical lipoprotein yfhM precursor P76578 25158 5.2 151 88 92 1.7 1.6 1.0
ECP-18 Probable ATP-dependent helicase Ihr P30015 23938 4.6 84 54 41 1.6 2.0 (1.3)
ECP-19 unreadable - - - 61 25 36 2.4 1.7 1.4
ECP-20 putative regulator 1787221M 24268 5.7 73 39 91 1.9 (1.3) 2.3
ECP-21 MbhA 984586M 23780 6.9 110 33 24 3.3 4.6 (1.4)
ECP-22 Cellulose synthase operon protein C P37650 22581 4.5 86 14 21 6.1 4.1 1.5
ECP-23 unreadable - - - 142 112 119 1.3 1.2 1.1
ECP-24 Nitrate reductase 1 alpha subunit P09152 23035 5.6 102 111 135 (1.1) (1.3) 1.2
ECP-25 Respiratory nitrate reductase 2 alpha chain P19319 23009 5.8 165 175 105 (1.1) 1.6 (1.7)
ECP-26 hypothetical protein P27190 23895 5.4 62 23 51 2.7 1.2 2.2
ECP-27 narZ P16918 24009 6.2 167 89 41 1.9 4.1 (2.2)
ECP-28 cheA protein 145519 23609 6.4 75 9 64 8.3 1.2 7.1
ECP-29 phenylacrylic decarboxylase like protein 4887557 21470 6.9 131 35 75 3.7 1.7 2.1
ECP-30 dnaE P10443 22990 5.1 62 64 103 1.0 (1.7) 1.6
ECP-31 yeaZ P76256 21181 5.1 75 64 32 1.2 2.3 (2.0)
ECP-32 yifB P32128 24177 5.2 112 60 31 1.9 3.6 (1.9)
Spots Protein name Accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
ECP-1 unreadable - - - 75 71 135 1.1 (1.8) 1.9
ECP-2 unreadable - - - 191 174 129 1.1 1.5 (1.4)
ECP-3 (rpoS)RNA polymerase sigma factor P13445 37972 4.9 132 5 150 26.4 (1.1) 30.0
ECP-4 (ybiK)putative L-asparaginase precursor P37595 33394 4.8 128 78 156 1.6 (1.2) 2.0
ECP-5 (traI)Tral protein(DNA helicase I) P22706 45168 5.6 150 106 87 1.4 1.7 (1.2)
ECP-6 (traC)DNA primase TraC P27190 40895 5.4 145 - 150 145.0 1.0 150.0
ECP-7 Lipoprotein 73853215M 42860 5.9 110 32 99 3.4 1.1 3.1
ECP-8 (rhsC)RhsC protein P16918 42777 6.2 166 82 147 2.0 1.1 1.8
ECP-9 unnamed protein product 10955265M 39574 5.6 45 - 63 45.0 (1.4) 63.0
ECP-10 cytolysinA 50953627M 33717 5.1 104 49 37 2.1 2.8 (1.3)
ECP-11 HsdM protein 4210349 36200 5.3 69 14 48 4.9 1.4 3.4
ECP-12 Hypothetical protein yeeJ P76347 24857 4.8 66 95 26 (1.4) 2.5 (3.7)
ECP-13 detergent resistant phospholipase A 148220 33171 5.2 153 41 56 3.7 2.7 1.4
ECP-14 dihydropteroate synthase 40548828 26585 5.3 69 24 54 2.9 1.3 2.3
ECP-15 Hypothetical protein ycjY P76049 34117 5.1 170 180 140 (1.1) 1.2 (1.3)
ECP-16 unnamed protein product 46811 34073 5 82 51 87 1.6 (1.1) 1.7
ECP-17 Hypothetical lipoprotein yfhM precursor P76578 25158 5.2 151 88 92 1.7 1.6 1.0
ECP-18 Probable ATP-dependent helicase Ihr P30015 23938 4.6 84 54 41 1.6 2.0 (1.3)
ECP-19 unreadable - - - 61 25 36 2.4 1.7 1.4
ECP-20 putative regulator 1787221M 24268 5.7 73 39 91 1.9 (1.3) 2.3
ECP-21 MbhA 984586M 23780 6.9 110 33 24 3.3 4.6 (1.4)
ECP-22 Cellulose synthase operon protein C P37650 22581 4.5 86 14 21 6.1 4.1 1.5
ECP-23 unreadable - - - 142 112 119 1.3 1.2 1.1
ECP-24 Nitrate reductase 1 alpha subunit P09152 23035 5.6 102 111 135 (1.1) (1.3) 1.2
ECP-25 Respiratory nitrate reductase 2 alpha chain P19319 23009 5.8 165 175 105 (1.1) 1.6 (1.7)
ECP-26 hypothetical protein P27190 23895 5.4 62 23 51 2.7 1.2 2.2
ECP-27 narZ P16918 24009 6.2 167 89 41 1.9 4.1 (2.2)
ECP-28 cheA protein 145519 23609 6.4 75 9 64 8.3 1.2 7.1
ECP-29 phenylacrylic decarboxylase like protein 4887557 21470 6.9 131 35 75 3.7 1.7 2.1
ECP-30 dnaE P10443 22990 5.1 62 64 103 1.0 (1.7) 1.6
ECP-31 yeaZ P76256 21181 5.1 75 64 32 1.2 2.3 (2.0)
ECP-32 yifB P32128 24177 5.2 112 60 31 1.9 3.6 (1.9)
134
Spots Protein name Accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
ECP-33 yahJ P77554 16854 6 149 58 109 2.6 1.4 1.9
ECP-34 agaS P42903 17192 5.1 127 103 55 1.2 2.3 (1.9)
ECP-35 Glutamine synthetase adenyltransferase P30870 20841 5 127 64 54 2.0 2.4 (1.2)
ECP-36 unreadable - - - 102 54 62 1.9 1.6 1.1
ECP-37 yjeO P39284 15837 6.1 117 62 175 1.9 (1.5) 2.8
ECP-38 acyl-CoA thioesterase I 1786702M 23622 6.9 120 31 114 3.9 1.1 3.7
ECP-39 Uncharacterized conserved protein 77475 17604 6.4 154 107 177 1.4 (1.1) 1.7
ECP-40 SepD 886476M 17563 7 178 45 108 4.0 1.6 2.4
ECP-41 MutS protein 8052216 14222 6.1 118 - 34 118.0 3.5 34.0
ECP-42 DNA polymerase I 18104428M 13024 7 81 138 53 (1.7) 1.5 (2.6)
ECP-43 Uncharacterized conserved protein 39383 8134 5.9 125 59 120 2.1 1.0 2.0
ECP-44 unreadable - - - 142 75 88 1.9 1.6 1.2
ECP-45 Shiga toxin II subunit B 13359153M 9157 6.2 34 102 94.4 (3.0) (2.8) (1.1)
ECP-46 orf, hypothetical protein 1786864M 37276 5 42 21 120 2.0 0.4 5.7
ECP-47 atoD P76458 23526 5.1 35 54 35 (1.5) 1.0 (1.5)
ECP-48 sgbE P37680 21561 5.2 51 80 36 (1.6) 1.4 (2.2)
ECP-49 manB P37755 50423 5.3 154 119 127 1.3 1.2 1.1
ECP-50 TDH P76251 40315 5.2 107 128 144 (1.2) (1.3) 1.1
ECP-51 aminopeptidase B 1799926M 46181 5.6 101 31 61 3.3 1.7 2.0
ECP-52 Uncharacterized conserved protein 75512766M 19536 6.1 82 36 18.3 2.3 4.5 (2.0)
ECP-53 Probable GTP-binding protein engB 67462332M 23561 6.9 63 18 26 3.5 2.4 1.4
ECP-54 fliN P15070 14855 5.3 67 58 42 1.2 1.6 (1.4)
ECP-55 unreadable - - - 63 49 10 1.3 6.3 (4.9)
ECP-56 Uncharacterized conserved protein 42604 14132 4.6 58 48 53 1.2 1.1 1.1
ECP-57 TraM 398515M 14508 5.3 60 29 65 2.1 (1.1) 2.2
ECP-58 Uncharacterized conserved protein 75894 14862 4.8 29 47 23 (1.6) 1.3 (2.0)
ECP-59 Uncharacterized conserved protein 75513951M 12265 5.3 42 17 7 2.5 6.0 (2.4)
ECP-60 hydroxymethylbilane synthase 41186 9816 6.3 9 55 46 (6.1) (5.1) (1.2)
Spots Protein name Accession number MW(Da) pICI03J ML03J RL03J Folds
(intensity) (intensity) (intensity) C vs M C vs R R vs M
ECP-33 yahJ P77554 16854 6 149 58 109 2.6 1.4 1.9
ECP-34 agaS P42903 17192 5.1 127 103 55 1.2 2.3 (1.9)
ECP-35 Glutamine synthetase adenyltransferase P30870 20841 5 127 64 54 2.0 2.4 (1.2)
ECP-36 unreadable - - - 102 54 62 1.9 1.6 1.1
ECP-37 yjeO P39284 15837 6.1 117 62 175 1.9 (1.5) 2.8
ECP-38 acyl-CoA thioesterase I 1786702M 23622 6.9 120 31 114 3.9 1.1 3.7
ECP-39 Uncharacterized conserved protein 77475 17604 6.4 154 107 177 1.4 (1.1) 1.7
ECP-40 SepD 886476M 17563 7 178 45 108 4.0 1.6 2.4
ECP-41 MutS protein 8052216 14222 6.1 118 - 34 118.0 3.5 34.0
ECP-42 DNA polymerase I 18104428M 13024 7 81 138 53 (1.7) 1.5 (2.6)
ECP-43 Uncharacterized conserved protein 39383 8134 5.9 125 59 120 2.1 1.0 2.0
ECP-44 unreadable - - - 142 75 88 1.9 1.6 1.2
ECP-45 Shiga toxin II subunit B 13359153M 9157 6.2 34 102 94.4 (3.0) (2.8) (1.1)
ECP-46 orf, hypothetical protein 1786864M 37276 5 42 21 120 2.0 0.4 5.7
ECP-47 atoD P76458 23526 5.1 35 54 35 (1.5) 1.0 (1.5)
ECP-48 sgbE P37680 21561 5.2 51 80 36 (1.6) 1.4 (2.2)
ECP-49 manB P37755 50423 5.3 154 119 127 1.3 1.2 1.1
ECP-50 TDH P76251 40315 5.2 107 128 144 (1.2) (1.3) 1.1
ECP-51 aminopeptidase B 1799926M 46181 5.6 101 31 61 3.3 1.7 2.0
ECP-52 Uncharacterized conserved protein 75512766M 19536 6.1 82 36 18.3 2.3 4.5 (2.0)
ECP-53 Probable GTP-binding protein engB 67462332M 23561 6.9 63 18 26 3.5 2.4 1.4
ECP-54 fliN P15070 14855 5.3 67 58 42 1.2 1.6 (1.4)
ECP-55 unreadable - - - 63 49 10 1.3 6.3 (4.9)
ECP-56 Uncharacterized conserved protein 42604 14132 4.6 58 48 53 1.2 1.1 1.1
ECP-57 TraM 398515M 14508 5.3 60 29 65 2.1 (1.1) 2.2
ECP-58 Uncharacterized conserved protein 75894 14862 4.8 29 47 23 (1.6) 1.3 (2.0)
ECP-59 Uncharacterized conserved protein 75513951M 12265 5.3 42 17 7 2.5 6.0 (2.4)
ECP-60 hydroxymethylbilane synthase 41186 9816 6.3 9 55 46 (6.1) (5.1) (1.2)
135
Table III-3. Differentially expressed cellular proteins in CI03J, RL03J strain compared to luxS mutant ML03J strain
Category Spot number Protein name NCBI accession number MOWSE score MW(Da) pI Coverage(%)
Fold Changes
C vs M C vs R R vs M
Cellular proteins
CP1 Aconitase B 75511993M 22.4 93499 5.2 22.4 183 1.06 173
CP2 K+ efflux antiporter, glutathione regulated 1786232M 24.4 67796 5.7 19.8 14.6 -1.27 18.7
CP3 ManC 56122507 23.2 52311 5.7 17.6 1.9 1.04 1.81
CP4 FliC 30059860M 74.1 68134 4.5 19 4.4 3.13 13.6
CP5 hypothetical protein 89109723 42 46245 5.3 45.7 1.6 1 1
CP6 biosynthesis; flagellin, filament structural protein 1788232M 20.3 51295 4.5 28.5 153 -1.04 160
CP7 flagellin 6009845 67.8 57809 4.7 26.7 187 1.26 173
CP8 Unreadable - - - - - 1.1 -1.44 1.6
CP9 signal transduction histidine kinase 75196984M 39.3 50282 5.5 24.9 1.42 -1.7 2.42
CP10 EspG protein 54311594 9.25 43901 5.2 8 2.1 -1.6 3.35
CP11 biotin synthase and related enzymes 75511378M 57.6 39648 5.3 10.7 4.12 -2.13 8.76
CP12 Uncharacterized conserved protein 75255879M 3.59 26423 4.7 13.4 2.2 -1.915 4.185
CP13 acyl-CoA thioesterase I 124530254 56.2 23563 4.6 24.6 4.15 -1.2 4.96
CP14 hemolysin 4704412 35.1 33555 5.2 12 166 -1.05 174
CP15 orf, hypothetical protein 24051467M 18.9 17911 4.9 26.8 2.5 -1.3 3.21
CP16 putative 2-component transcriptional regulator 1789402M 24.4 24678 6.5 13.7 -2.42 -1.923 -1.26
CP17 unnamed protein product 4584722 61630 79535 5.8 30 1.7 -3.4 5.7
CP18 Fcf1 46487620 12.9 35595 5.6 16.8 2.5 -2.3 5.64
CP19 hemolysin coregulated protein 75513636M 34.7 19256 5.5 37.2 2.96 166 -56
Category Spot number Protein name NCBI accession number MOWSE score MW(Da) pI Coverage(%)
Fold Changes
C vs M C vs R R vs M
Cellular proteins
CP1 Aconitase B 75511993M 22.4 93499 5.2 22.4 183 1.06 173
CP2 K+ efflux antiporter, glutathione regulated 1786232M 24.4 67796 5.7 19.8 14.6 -1.27 18.7
CP3 ManC 56122507 23.2 52311 5.7 17.6 1.9 1.04 1.81
CP4 FliC 30059860M 74.1 68134 4.5 19 4.4 3.13 13.6
CP5 hypothetical protein 89109723 42 46245 5.3 45.7 1.6 1 1
CP6 biosynthesis; flagellin, filament structural protein 1788232M 20.3 51295 4.5 28.5 153 -1.04 160
CP7 flagellin 6009845 67.8 57809 4.7 26.7 187 1.26 173
CP8 Unreadable - - - - - 1.1 -1.44 1.6
CP9 signal transduction histidine kinase 75196984M 39.3 50282 5.5 24.9 1.42 -1.7 2.42
CP10 EspG protein 54311594 9.25 43901 5.2 8 2.1 -1.6 3.35
CP11 biotin synthase and related enzymes 75511378M 57.6 39648 5.3 10.7 4.12 -2.13 8.76
CP12 Uncharacterized conserved protein 75255879M 3.59 26423 4.7 13.4 2.2 -1.915 4.185
CP13 acyl-CoA thioesterase I 124530254 56.2 23563 4.6 24.6 4.15 -1.2 4.96
CP14 hemolysin 4704412 35.1 33555 5.2 12 166 -1.05 174
CP15 orf, hypothetical protein 24051467M 18.9 17911 4.9 26.8 2.5 -1.3 3.21
CP16 putative 2-component transcriptional regulator 1789402M 24.4 24678 6.5 13.7 -2.42 -1.923 -1.26
CP17 unnamed protein product 4584722 61630 79535 5.8 30 1.7 -3.4 5.7
CP18 Fcf1 46487620 12.9 35595 5.6 16.8 2.5 -2.3 5.64
CP19 hemolysin coregulated protein 75513636M 34.7 19256 5.5 37.2 2.96 166 -56
136
Table III-4. Differentially expressed secreted proteins in CI03J, RL03J strain compared to luxS mutant ML03J strain
Category Spot number Protein name NCBI accession number MOWSE score MW(Da) pI Coverage(%)
Fold Changes
C vs M C vs R R vs M
Extracellular proteins
ECP1 Lipoprotein 73853215M 2.70E+14 42860 5.9 77.1 3.44 1.11 3.09
ECP2 aminopeptidase B 1799926M 2.59E+19 46181 5.6 70.7 45 -1.4 63
ECP3 unnamed protein product 10955265M 1.26 39574 5.6 25.4 2.12 2.81 -1.32
ECP4 cytolysin A 50953627M 1.10E+07 33717 5.1 62 4.93 1.44 3.43
ECP5 HsdM protein 4210349 690 36200 5.3 39.1 3.73 2.73 1.37
ECP6 detergent resistant phospholipase A 148220 4.84E+09 33171 5.2 67.8 2.88 1.3 2.25
ECP7 dihydropteroate synthase 40548828 5.35 26585 5.3 18.6 1.87 -1.25 2.33
ECP8 putative regulator 1787221M 4.50E+05 24268 5.7 21 3.33 4.58 -1.38
ECP9 MbhA 984586M 147034 23780 6.9 65.4 8.3 1.17 7.1
ECP10 cheA protein 145519 8.23E+06 23609 6.3 68.4 3.74 1.75 2.14
ECP11 Probable GTP-binding protein engB 67462332M 1.56E+09 23561 6.9 92.4 3.87 1.05 3.68
ECP12 SepD 886476M 2.66E+09 17563 7 85.4 3.96 1.65 2.4
ECP13 DNA polymerase I 18104428M 9.99E+06 13024 7 96.5 118 3.47 34
ECP14 TraM 398515M 4.73E+09 14508 5.3 98.4 -1.7 1.53 -2.6
ECP15 Uncharacterized conserved protein 75513951M 1.19E+08 12265 5.3 96.2 -3 -2.41 -1.24
ECP16 hydroxymethylbilane synthase 41186 2.69E+06 9816 6.3 78.7 2 -2.86 5.7
ECP17 Shiga toxin II subunit B 13359153M 2.89E+05 9157 6.2 53 3.3 1.66 1.97
ECP18 phenylacrylic acid decarboxylase like protein 4887557 1.90E+08 21470 6.4 87.8 2.28 -1.8 4.1
ECP19 MutS protein 8052216 2.06E+08 14222 6.1 83.8 3.5 2.42 1.44
ECP20 Uncharacterized conserved protein 75512766M 1.41E+07 19536 6.1 78.7 2.1 -1.1 2.24
ECP21 acyl-CoA thioesterase I 1786702M 1.45E+10 23622 6.9 76.4 2.47 6 -2.43
ECP22 orf, hypothetical protein 1786864M 1.20E+12 37276 5 94.2 -6.1 -5.1 -1.2
Category Spot number Protein name NCBI accession number MOWSE score MW(Da) pI Coverage(%)
Fold Changes
C vs M C vs R R vs M
Extracellular proteins
ECP1 Lipoprotein 73853215M 2.70E+14 42860 5.9 77.1 3.44 1.11 3.09
ECP2 aminopeptidase B 1799926M 2.59E+19 46181 5.6 70.7 45 -1.4 63
ECP3 unnamed protein product 10955265M 1.26 39574 5.6 25.4 2.12 2.81 -1.32
ECP4 cytolysin A 50953627M 1.10E+07 33717 5.1 62 4.93 1.44 3.43
ECP5 HsdM protein 4210349 690 36200 5.3 39.1 3.73 2.73 1.37
ECP6 detergent resistant phospholipase A 148220 4.84E+09 33171 5.2 67.8 2.88 1.3 2.25
ECP7 dihydropteroate synthase 40548828 5.35 26585 5.3 18.6 1.87 -1.25 2.33
ECP8 putative regulator 1787221M 4.50E+05 24268 5.7 21 3.33 4.58 -1.38
ECP9 MbhA 984586M 147034 23780 6.9 65.4 8.3 1.17 7.1
ECP10 cheA protein 145519 8.23E+06 23609 6.3 68.4 3.74 1.75 2.14
ECP11 Probable GTP-binding protein engB 67462332M 1.56E+09 23561 6.9 92.4 3.87 1.05 3.68
ECP12 SepD 886476M 2.66E+09 17563 7 85.4 3.96 1.65 2.4
ECP13 DNA polymerase I 18104428M 9.99E+06 13024 7 96.5 118 3.47 34
ECP14 TraM 398515M 4.73E+09 14508 5.3 98.4 -1.7 1.53 -2.6
ECP15 Uncharacterized conserved protein 75513951M 1.19E+08 12265 5.3 96.2 -3 -2.41 -1.24
ECP16 hydroxymethylbilane synthase 41186 2.69E+06 9816 6.3 78.7 2 -2.86 5.7
ECP17 Shiga toxin II subunit B 13359153M 2.89E+05 9157 6.2 53 3.3 1.66 1.97
ECP18 phenylacrylic acid decarboxylase like protein 4887557 1.90E+08 21470 6.4 87.8 2.28 -1.8 4.1
ECP19 MutS protein 8052216 2.06E+08 14222 6.1 83.8 3.5 2.42 1.44
ECP20 Uncharacterized conserved protein 75512766M 1.41E+07 19536 6.1 78.7 2.1 -1.1 2.24
ECP21 acyl-CoA thioesterase I 1786702M 1.45E+10 23622 6.9 76.4 2.47 6 -2.43
ECP22 orf, hypothetical protein 1786864M 1.20E+12 37276 5 94.2 -6.1 -5.1 -1.2
137
4. DISCUSSION
In this study results were demonstrated that positive association
between regulatory mechanism known as quorum sensing and expression
of virulence proteins in EHEC. Strain was constructed an isogenic luxS
mutant and restoration strain in wild-type EHEC, clinical isolate. Also
strains were investigated that proteins involved in virulence factors were
regulated by quorum sensing through autoinducer-2, which is synthesis
by the product of luxS gene. In an attempt to understand the role of the
luxS gene, two-dimensional gel electrophoresis to compare the expression
profiles of soluble proteins of three different EHEC strains (luxS, luxS-
and luxS+) was used.
To obtain an overview of the protein distribution, pH 3-10 IPG
strips (180 mm) were used first. The results shows that almost all proteins
isoelectric point (pI) are located between 4 and 7. A comparison of the
proteomic profiles of E. coli O157:H7 clinical isolate, isogenic luxS
mutant strain and luxS restoration strain is shown in Fig. III-4. Total of
205 spots were detected and analysis. Among the proteins identified,
there are 145 spots of cellular proteins and 60 spots of extracellular
proteins. Many previous pathogenic bacterial studies were analyzed by
proteomics for extracellular proteins such as secreted proteins (Cortest et
al., 2005; Lelong et al., 2007; Mosterts et al., 2004). The experiment was
138
performed three times with two sets of independently grown cultures. The
gels of the wild-type crude extracts were used as standards and each spot
observed on mutant extracts and restoration strain extracts were
compared to the standard. Figure III-4A show that 19 intracellular protein
spots satisfying the following intensity increased, decreased, or even
disappeared, in comparison to the among the strains. Also, 22 differential
spots of extracellular protein are given in Figure III-4B. An enlargement
of portion of the gel illustrates this result (Fig. III-5).
Analysis of the proteomes obtained for these variants revealed that
forty-one proteins were expressed by the luxS mediated quorum sensing.
The proteomic profiles of strains with intracellular 11 proteins were
involved in enzymes, regulated proteins, metabolic proteins and three
proteins were structural proteins, such as FliC and Flagellin protein. The
most interesting outcome of our study is the identification of a virulent
protein involved in EspG and hemolysin (Fig. III-5, Table III-3 and 4 ).
As a result of the three extracellullar proteins, it contains SepD, cytolysin
A (SheA) and Stx2 protein and these were known to virulence factors of
EHEC. These results indicated that several proteins regulated by luxS
gene. These results were also observed that up-regulated proteins (CP16
and ECP22) in luxS mutant strain. Most of proteins were up-regulated in
restoration strain compared to mutant and wild-type strains.
In the test comparing the proteins of RL03J and CI03J, most
139
proteins showed similar expression patterns or sometimes RL03J showed
higher expression level. As the result proves in Chapter 2, interestingly,
the difference was also noticeable in the proteins related to motility,
chemotaxis, and flagella. Among the proteins inside the cell, which
showed distinctive difference among the three strains, EspG, FliC,
Flagellin, and hemolysin showed 2.1, 4.4, 1.6, and 166 folds difference
respectively. The case of hemolysin showed as same result as these
another test results, and this could be the evidence to prove that luxS/QS
system is also involved in the hemolysin expression. In case of hemolysin,
however, unlike our expectation that it would be detected mostly from the
protein outside the cell, it was identified to be detected from the protein
inside the cell, from which it was assumed that a great deal of protein in
the condition before it was being produced outside the cell was detected.
More detailed research on hemolysin and luxS/QS is needed. In case of
identified Shiga toxin II subunit B, it showed as same result as our cell
toxin test, and the expression difference of Shiga toxin II in the toxin
creation test using RPLA also were found.
Incurrent practice, proteomics encompasses four principal
application: protein mining (Pyndiah et al., 2007), protein expression
profiling (Phillip, 2000), protein network mapping (Plebani et al., 2005)
and protein modification mapping (Sarah et al., 2006; Schauder et al.,
2005). Using proteomics technology, it was demonstrated that quorum
140
sensing regulation in EHEC is far more regulates a number of basic
physiological functions, including enzymetic metabolisms and motility.
In their research on comparing the protein expression between clinical
isolate and standard strain, Kim et al. (1999) have reported to find about
360 protein spots. Although their research was not using DNA mutation,
similar proteins arrangement was identified when comparing their test
result and ours. Recent studies have found that E. coli O157:H7 uses AI-2
to control the expression of virulence factors, type III secretion,
chemotaxis, flagellar synthesis and motility (Kaper et al., 2002; Kaper et
al., 2003; Jordan et al., 2005). In addition, E. coli RP37 uses AI-2 to
control cell aggregation (Delisa et al., 2001). Several lines of evidence
suggest the existence of additional E. coli quorum-sensing signals besides
AI-2. Sperandio et al. (2001) reported that the luxS mutant grows faster
than the wild-type strains, previously studies. However, the growth rates
of both wild-type strain and mutant strain were similar under changes of
cellular proteins and extracellular proteins found in our study. While both
strains show a similar trend, restoration strain gives over-expressive
trends.
Constant patterns of motility, flagella synthesis and bacterial
metabolism were almost identical in phenotypical observations. As luxS
has only recently been discovered, there has not been sufficient time to
identify many of genes that are regulated by quorum sensing in luxS-
141
containing bacteria. A few pieces of information are currently available.
AI-2 has been reported to induce the expression of the LEE (locus of
enterocyte effacement) pathogenicity island in E. coli O157. This
pathogenicity island encodes a type III secretory apparatus that is
required for virulence. Previously, Sperandio et al. (2001) reported that
404 genes were regulated by luxS/QS at least five-fold. They confirmed
169 of these genes were down-regulated and 235 were up-regulated in the
wild-type strain compared to in the luxS mutant. Among the genes, down-
regulated genes included several in cell division. Up-regulated genes
included several involved in the expression and assembly of flagella,
motility, and chemotaxis. These results were also found that similar to
other results. Several proteins involved in expression and assembly of
flagella, as well as motility and chemotaxis, were up-regulated by
quorum sensing. The array data were able to confirm them. The luxS
mutant produces fewer flagella and motility related proteins (FliC,
flagellin and CheA) than wild-type and restoration strain (Fig. III-5,
cellular proteins). Aslo, increased expression of Stx2 and T3SS related
proteins that SepD and EspG in luxS mutant compared to that in wild-
type and restoration strain were observed (Fig. III-5, extracellular
proteins). The previous studies reported the proteins comprising the T3SS
are homologus to the flagella basal-body proteins, and since quorum
sensing regulates T3SS in EHEC, it was perhaps not too surprising that it
142
also regulates flagellar expression and motility (Sperandio et al., 2001).
In Salmonella, coupled regulation of type III secretion and flagella genes
has been described (Bassler et al., 1999; Sekiya et al., 2001; Sircili et al.,
2004).
Also, an increase in the production of hemolysin due to quorum
sensing in wild-type and restoration strain were observed. A previous
study noted that quorum sensing mechanisms have been demonstrated to
regulate production of hemolysins in Stapylococcus (Balaban and Novick,
1995). However, a Vibrio vulificus luxS mutant shows increased
hemolysin production and delayed protease production. Furthermore, the
LD50 for the V. vulificus luxS mutant is 20-fold higher than that of wild-
type V. vulificus (Roh et al., 2006).
The ability of pathogenic bacteria to cause disease in a susceptible
host is determined by multiple factors acting individually or together at
different stages of infection. Proteomics can provide an integrated view
of the gene products of certain bacteria for global analyses. Using
proteomics technology, the several proteins in EHEC strain and verified
its luxS related quorum sensing mechanisms were discovered. Combining
these studies were conclude that AI-2/AI-3 product by luxS gene may
play an important role in EHEC infection. These results do not represent
a definitive analysis of gene regulation by quorum sensing in EHEC
strain. Futher studies are neede to clarify whether this mechanism is
143
likely to be candidate protein changes of growth stages.
In summary, this 2-DE profile reveales that 41 proteins of STEC
O157:H7 were differentially regulated in the presence of luxS gene. To
the best of our knowledge, the first mutational study to show the
contribution of luxS gene products to the formation of an STEC O157:H7
quorum sensing. Significant changes in expression of the proteins had not
been reported in previous transcriptome-based studies (Sperandio et al.,
1999; Sperandio et al., 2001). This was probably due to the differences of
detection methods. In addition, due to limited techniques, these methods
were unable to observe on the regulations of high hydrophobic proteins
from membrane and extracellular proteins by luxS/QS system. Many of
the previously identified genes encode for memebrane bounded and
secreted proteins that often represent important virulence factors(Arevalo
et al., 2003; Nandakumar et al., 2005). Therefore, for novel targets of
antibacterial treatment, futher study is currently underway to determine
specific regulation on memebrane bounded and secreted STEC O157:H7
proteins controlled by luxS/QS system and compare to transcriptome-
based identification data.
In conclusion, proteomic analysis of the protein profiles of two
clones and wild-type strain, as well as the analysis of the proteomes of
these clones revealed distinct changes in the expression levels of multiple
proteins. These results support the use of proteomics to monitor and
144
investigate more understanding of functional luxS gene. Once the proteins
of interest are identified, a more precise description of the specific
mechanisms invoked in response to genetic inactivation can be developed
and optimization of the homologous recombination approach can be
pursued. These results suggest that quorum-sensing regulation in EHEC
strain, showing that quorum sensing is a global regulatory system that
controls not only proteins involved in pathogenesis but also proteins
involved in bacterial metabolism, biosynthesis, among other functions. In
this study, results were suggested that a definite understanding of the
difference between the strains by 2-DE, and the establishment of the
database through this proteome research is applicable to development of
the protein marker for diagnosis and can be used for effective protection
of a infectious disease. These results indicated that luxS/QS system was
closely involved in not only EHEC metabolism but also adjustment of the
virulence factor.
145
CONCLUSIONS
The purpose of this study was to determine epidemiological and
molecular charateristics the shiga toxin producing Escherichia coli
(STEC); enterohemorrhagic E. coli (EHEC) infection in Korean patients
with diarrhea, and to investigate the relationship between global
regulatory mechanism known as quorum sensing and expression of
virulence factors in STEC.
1. Current investigation is the first large study in Korea on the prevalence
of STEC in patients with diarrhea. These investigations show the
distribution of virulence genes and serotypes of STEC isolated from
patients in Korea.
2. In order to determine whether EHEC has a luxS-dependent QS system,
luxS in EHEC O157:H7 was knocked out.
3. The observation of the growth curves showed that CI03J and RL03J
had a similar growth pattern whether or not they had glucose. ML03J,
however, showed a remarkably reduced growth kinetics under the
condition without glucose, while it showed an almost similar growth to
146
the other two strains under the condition with glucose.
3. Genes potentially regulated by luxS/QS in other species have been
identified by constructing a luxS mutant of comparing gene expression in
the wild type and luxS mutant. Among the phenotypes and functions
affected by luxS mutations are type III secretion system (T3SS),
hemolysis phenotypes and flagellum expression in EHEC O157:H7.
4. By proteomic analysis, various proteins as known virulence factors in
EHEC were detected . Among the changed proteins, cytolysin A (2.1
folds), the pore forming toxin, identified as virulence factor, SepD (4
folds), the effector molecule, related to T3SS, and Shiga toxin II subunit
B (3 folds), the toxin were observed. Surprisingly, a dramatic increased in
expression of the pO157-encoded hemolysin in the CI03J as compared to
the luxS mutant ML03J.
In conclusion, these results suggest that useful information about the
trend of STEC infections in the general population. Molecular
characterization of STEC in this study will help prepare the data and to
understand the etiological mechanism of STEC. Global regulatory
mechanism known as quorum sensing associated EHEC pathogenesis
may influence in the development of acute disease. Quorum sensing in
147
EHEC may potentially play a direct or indirect role in the pathogenesis of
human infection.
148
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국문요약국문요약국문요약국문요약
장출혈성장출혈성장출혈성장출혈성 대장균의대장균의대장균의대장균의 특성특성특성특성 분석분석분석분석 및및및및 Global Global Global Global
Regulator SystemRegulator SystemRegulator SystemRegulator System 에에에에 의한의한의한의한
병원성병원성병원성병원성 인자인자인자인자 조절에조절에조절에조절에 관한관한관한관한 연구연구연구연구
쉬가 독소 생성 대장균(shiga toxin-producing Escherichia coli,
STEC), 또는 장출혈성 대장균(enterohemorrhagic Escherichia coli,
EHEC)은 혈액이 섞인 설사, 단순 설사, 용혈성 요독 증후군
(HUS) 등을 일으키는 위중한 병원체로 알려져 있다. STEC 감염
이 공중보건에 미치는 영향은 감염시 나타나는 전신성 질환인
용혈성 요독 증후군을 일으키고 특히, 영아와 노인에게서 급성
신부전을 유발하여, 이들을 통한 대규모의 집단 식중독 발생 위
험성이 높기 때문에 매우 중요하다.
본 연구는 우리 나라의 STEC 감염증 환자에서 분리한 STEC
223주의 유전적 특성과 표현형 특성 분석을 우선적으로 실시하
192
였다. 다음으로, 세균 세포 간의 의사소통 기작으로 알려져 있는
정족수 감지 체계(quorum sensing)가 위중한 인체 병원체로 알려
진 E. coli O157:H7 의 표현형의 변화와 병원성 요소의 조절에 미
치는 영향을 규명하고자 하였다. 본 연구에서는 국내에서 분리
한 장출혈성 대장균 O157:H7(CI03J)을 이용하여 비극성 luxS 유
전자 돌연변이 주를 제작하여 luxS 의존성 정족수 감지 체계와
장출혈성 대장균의 병원성 기작과의 상호 작용을 살펴보았다.
세포 독성 실험에서는, luxS 유전자를 결손시킨 균주가 동물 세
포와 사람의 적혈구에 대한 독성이 낮게 나타난 다는 사실을 확
인하였다. 병원성 요소들 중 세균의 동물 세포에 대한 부착능,
편모을 이용한 운동성, 주화성 인자, 그리고 type III secretion
system (T3SS) 등이 luxS 의존성 정족수 감지 체계에 의해 활성화
된다는 사실을 알 수 있었다. 또한 마이크로 어레이법과 RT-real
time PCR법을 이용한 실험에서의 결과들도 이러한 사실을 뒷받
침하고 있다.
LuxS 의존성 정족수 감지 체계에 의한 병원성 단백질 변화 양
상을 살펴보기 위하여 이차원 단백질 전기영동법(2-DE)을 실시
하였다. 총 205 단백질 점상(spot)을 검출하였으며, 그 중 세포
내 단백질 145개와 세포외 단백질 60개를 동정하고 분석하였다.
193
분석 결과, 유전자 돌연변이로 발현도의 차이가 나타난 세포내
담백질 19개와 세포 외 단백질 22개를 검출하였다. 이들 중
FliC, Flagellin, EspG와 hemolysin, SepD, Cytolysin A, 그리고 Stx2와
같은 장출혈성 대장균의 병원성 요소로 알려져 있는 단백질들이
확인되었다. 이 결과들로 볼 때, LuxS에 의해 세균의 다양한 단
백질들이 조절되고 있다는 사실을 알 수 있었다.
결론적으로, 이와 같은 결과들은 luxS 의존성 정족수 감지 체계
가 장출혈성 대장균의 병원성 유전자들과 병원성 단백질 발현
뿐 아니라, 세균의 생합성 등과 같은 여러가지 대사작용에 관여
하여 조절인자로써의 기능을 수행한다는 사실을 알 수 있었다.
핵심어: shiga toxin producing Escherichia coli (STEC),
enterohemorrhagic E. coli (EHEC), hemolytic yremic syndrome (HUS),
quorum sensing, luxS, microarray, reverse transcriptase real time
polymerase chain reaction (RT-real time PCR), two dimensional
electrophoresis( 2-DE)