CONTRIBUTIONS OF SIGMA-B AND PRFA TO STRESS RESPONSE AND
VIRULENCE GENE EXPRESSION IN LISTERIA MONOCYTOGENES
A Dissertation
Presented to the Faculty of the Graduate School
of Cornell University
in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
by
Mark Joseph Kazmierczak
August 2005
© 2005 Mark Joseph Kazmierczak
CONTRIBUTIONS OF SIGMA-B AND PRFA TO STRESS RESPONSE AND
VIRULENCE GENE EXPRESSION IN LISTERIA MONOCYTOGENES
Mark Joseph Kazmierczak, Ph.D.
Cornell University 2005
The food borne bacterial pathogen Listeria monocytogenes has several
mechanisms for regulating expression of stress response and virulence genes. The
alternative sigma factor σB is a global regulator of genes active under environmental
stress conditions and during stationary phase growth. I identified a large portion of the
genes regulated by σB using a promoter consensus sequence search and microarrays.
σB directly controls expression of at least 54 genes. The genes regulated by σB encode
proteins with a wide variety of functions, including basic metabolic pathways,
membrane solute transporters, and stress resistance. In addition, I found six virulence
genes, including bsh and five internalin genes, to be controlled by σB.
Another protein that regulates virulence gene expression in L. monocytogenes
is PrfA. I measured expression of PrfA-dependent and σB-dependent genes under
conditions that activate each regulator, using quantitative reverse transcription-PCR
(qRT-PCR). I found that σB is active preferentially under environmental stress
conditions, and activity decreases upon internalization of the bacteria by human
epithelial cells. Conversely, PrfA is not active under stress conditions, but is highly
active intracellularly. Additionally, I used qRT-PCR to determine that σB contributes
directly to prfA expression at the P2 promoter region.
One gene initially identified in the microarray analysis to be σB-dependent is
lmo1433, which is predicted to encode glutathione reductase, an enzyme used by some
bacteria to counteract oxidative stress. Characterizations of a strain bearing an in
frame polar deletion of lmo1433 (∆lmo1433), as well as a ∆sigB ∆lmo1433 strain,
showed no difference in the strains’ abilities to survive oxidative stress when
compared to their respective parent strains, although presence of an intact sigB allele
was important for survival. Likewise, the ∆lmo1433 and ∆sigB ∆lmo1433 strains did
not show a difference in total glutathione reductase activity or intracellular survival
and spread, as determined by plaquing ability on mouse L2 cell monolayers, when
compared to parent strains.
BIOGRAPHICAL SKETCH
Mark Joesph Kazmierczak was born on September 8, 1978 in Buffalo, NY.
From an early age, he was interested in science, a trait fostered in part by his father, a
chemical engineer. At Michigan State University, he studied microbiology and
bacterial genetics, earning a Bachelor of Science degree in May 2000. From there, his
experience in bacterial genetics and interest in microbial pathogenesis led him to the
laboratory of Dr. Martin Wiedmann. Mark is enthusiastically pursuing a career
studying the pathogenesis of microorganisms, and hopes to use this knowledge to
develop efficient methods of disease prevention and control.
iii
ACKNOWLEDGEMENTS
First and foremost, I am extremely grateful to my major advisor, Dr. Martin
Wiedmann, without whom this dissertation would not have been possible. My whole
time here, it was tremendous working with you, Martin. You always gave me the
confidence I needed to succeed. You have been a great mentor, not only in my
research, but in planning for a career and on a personal level. We always got along: in
the lab, at social gatherings, and on the soccer field. The impact you have had on my
life is tremendous and you will not be forgotten.
I also extend an enormous thank you to Dr. Kathryn Boor, who has been a
wonderful person to know and work with. Having you around, Kathryn, brought a
positive feeling into the room. I could always count on you to be excited about my
work and remind me that it is all worthwhile. Outside of the lab as well, you have
been an incredibly kind and generous person, and I am glad for the friendship we
have.
I gratefully acknowledge the support of my committee members, Dr. John
Helmann and Dr. Marci Scidmore. They have provided valuable insight into my work
and have been a pleasure to work with.
The Food Safety Laboratory has been an amazing place to work, and that is
because of the great, friendly, supportive people there. David Sue, you were a
wonderful friend and labmate. Esther Fortes, and Kendra Nightingale, and Barbara
Bowen were always up for great conversations. Having friends like you around made
it hardly seem like work.
The only reason I was able to endure all the ups and downs of my time at
Cornell is because of the incredible support network provided by my friends. The first
people I met at Cornell, my classmates, Soraya, Joe, and Garner, were the first to
iv
make me feel welcome and I value their friendship even more today. Others I met
quickly thereafter, and have developed a wonderful bond with. Phil, Anne, Pete,
Adela, and Craig, you have all been true friends for a long time now. Knowing that
you were there for me and still are has made a huge difference. Of course, as old
friends leave, new friends enter the picture. I cannot express enough how great my
Ithaca friends are. Fung, Sarah, thanks for being such good friends. Sam, Dre,
BeeDub, Paddy, Fran, we do everything together and it’s wonderful to have so many
people there to help relax the mind, not to mention help me out through the rough
times. Jule, through the short time we’ve known each other we’ve become best
friends, and I’m incredibly happy knowing we can always be there for each other.
Finally, and most importantly, I must thank my family for being ever so
supportive. Mom and Dad, you are the greatest and I love you. You have always
encouraged me in everything I do. Karen and Laura, we’ve always been great friends
and it’s great just knowing you’re behind me. Thank you all.
v
TABLE OF CONTENTS
Chapter 1
Alternative sigma factors and their roles in virulence
1
Chapter 2
Listeria monocytogenes σB regulates stress response
72
and virulence functions
Chapter 3
Contributions of Listeria monocytogenes σB and PrfA to
118
expression of virulence and stress response genes
during extra- and intracellular growth
Chapter 4
The putative glutathione reductase gene lmo1433 of
158
Listeria monocytogenes is σB-dependent
Chapter 5
Conclusions
174
vi
LIST OF FIGURES
Figure 1.1
sigB operon structure and σB regulation by Rsb proteins
9
Figure 1.2
Examples of regulatory networks involving sigma
16
factors and other transcriptional regulators
Figure 2.1
Scatter plots of normalized microarray spot intensities
85
for wild-type and sigB mutant strains
Figure 2.2
Graphical depiction of three operons represented on the
94
microarray
Figure 2.3
Determination of σB-dependent transcriptional start
95
sites by RACE-PCR
Figure 2.4
Promoter sequences of genes with σB-dependent
96
transcriptional start sites confirmed by RACE-PCR
Figure 2.5
L. monocytogenes consensus sequence logo
98
Figure 2.6
Comparison of expression ratios for two stress
100
conditions
Figure 3.1
cDNA copy numbers for σB-dependent genes
129
Figure 3.2
Micrographs of Caco-2 infection by L. monocytogenes
130
Figure 3.3
cDNA copy numbers for PrfA-dependent genes
133
Figure 3.4
Activity of PrfA in L. monocytogenes grown in
135
different conditions
Figure 3.5
RACE-PCR of the prfA promoter region
137
Figure 3.6
Location of TaqMan primers and probes in the plcA-
138
prfA region
Figure 3.7
Quantification of prfA transcription from its three
upstream promoters
vii
141
Figure 3.8
Model of σB- and PrfA-mediated regulation of virulence
149
genes
Figure 4.1
Expression of lmo1433
163
Figure 4.2
Survival of four L. monocytogenes strains after
165
exposure to CHP
Figure 4.3
Plaque assays to determine virulence of four L.
monocytogenes strains
viii
169
LIST OF TABLES
Table 1.1
Alternative sigma factors involved in virulence
4
Table 1.2
Virulence and virulence-associated genes regulated by
7
stress response sigma factors σB and σS and phenotypes
of sigma factor null mutations in select bacterial species
Table 1.3
Genes regulated by Mycobacterial alternative sigma
22
factors and phenotypes of sigma factor null mutants
Table 1.4
Virulence genes regulated by σN in multiple bacterial
34
species
Table 2.1
L. monocytogenes genes with significantly higher
84
expression in wild-type as compared to ∆sigB strain
under osmotic and stationary phase stresses
Table 2.2
Summary of genes with σB-dependent expression
87
patterns as identified by microarray analysis
Table 3.1
Strains used in this study
122
Table 3.2
TaqMan primers and probes used in this study
126
Table 3.3
Statistical comparisons of cDNA copy numbers among
131
select growth conditions
Table 3.4
Origins of prfA transcription and their contributions to
142
total prfA transcript level
Table 4.1
Glutathione reductase activity in four L. monocytogenes
strains
ix
168
CHAPTER ONE:
ALTERNATIVE SIGMA FACTORS AND THEIR ROLES IN VIRULENCE
INTRODUCTION
Sigma factors are a class of proteins constituting essential dissociable subunits
of prokaryotic RNA polymerase. The association of appropriate alternative sigma
factors with core RNA polymerase provides a mechanism for cellular responses
mediated through redirection of transcription initiation. Sigma factors provide
promoter recognition specificity to the polymerase and contribute to DNA strand
separation, then dissociate from RNA polymerase core enzyme following transcription
initiation (16). As the regulon of a single sigma factor can be comprised of hundreds
of genes, sigma factors provide effective mechanisms for simultaneously regulating
large numbers of prokaryotic genes. In some cases, the genes comprising a sigma
factor regulon have a clearly defined primary function (e.g., genes regulated by the
sporulation sigma factors in Bacillus subtilis; 167); in others, the genes comprising a
regulon contribute to multiple functions (e.g., the stationary phase and general stress
response genes regulated by σB in Listeria monocytogenes; 98). One newly emerging
field is identification of the specific roles of alternative sigma factors in regulating
expression of virulence and virulence-associated genes in bacterial pathogens.
Virulence and virulence-associated genes are those that contribute to at least
one aspect of bacterial disease transmission and infection processes. Specifically,
virulence genes encode proteins whose functions are essential for the bacterium to
effectively establish an infection in a host organism. Examples of virulence genes are
L. monocytogenes inlA, which encodes the internalin-A protein important for invasion
of non-professional phagocytes (127), and the spv gene cluster of Salmonella enterica,
which allows for bacterial growth inside macrophages (126). In contrast, virulence-
1
2
associated genes can contribute to bacterial survival in the environment, such as the
sporulation sigma factors of Bacillus anthracis, which are critically important for
survival of the pathogen outside of the host, or to survival in the host, such as bsh
(encoding bile salt hydrolase) of L. monocytogenes, which enhances bacterial survival
in the intestinal environment prior to intracellular infection (48). Therefore, activation
of virulence-associated genes may enhance the capacity of the bacterium to spread to
new individuals or to survive passage through a host organism. Alternative sigma
factors thus can make direct or indirect contributions to bacterial virulence. For
example, activation of virulence gene expression by an alternative sigma factor will
have a direct effect on virulence capacity. In contrast, activation of virulenceassociated genes may not contribute directly to specific host-pathogen interactions
essential for infection, but may, in some indirect manner, enhance the ability of the
pathogen to establish appropriate contact with the host.
Virulence factor expression is generally tightly regulated in bacterial
pathogens. In some cases, pathogens have a “master regulator” of virulence gene
expression, such as the positive regulatory factor A (PrfA) in L. monocytogenes, a
transcriptional activator that is required for expression of most of this bacterium’s
virulence genes. Additionally, alternative sigma factors often function to regulate
expression of virulence and virulence-associated genes in response to particular
stimuli. Alternative sigma factors may regulate a small number of genes, each of
which may be critical to infection (e.g., PvdS of Pseudomonas aeruginosa, discussed
below; 143) or they may regulate functions that contribute to virulence, but also have
physiological roles in the cell. For example, Salmonella Typhimurium σE regulates
genes that provide resistance to oxidative stress, which also aids bacterial survival in
macrophages (81). This review focuses on the various roles of alternative sigma
3
factors, both direct and indirect, in regulating virulence of bacterial pathogens of
plants and animals.
Sigma factors can be classified into two structurally unrelated families, the σ70
and the σ54 families. Sigma factor nomenclature in many instances has been
inconsistent in the literature; therefore, under such circumstances we will adhere to the
convention where families of sigma factors are referred to using a number (e.g., the
σ54 family) and specific sigma factors will be denoted with a letter (e.g., P. aeruginosa
σN). However, some sigma factors are referred to almost exclusively by their fourletter abbreviation (e.g., FliA), and for those we will continue such nomenclature. The
σ70 family includes the primary sigma factor present in all bacteria examined to date,
as well as related alternative sigma factors (141, 160). Table 1.1 lists sigma factors in
both the σ70 and the σ54 families that are currently recognized as contributing, either
directly or indirectly, to bacterial virulence. Alternative sigma factors within the σ70
family are further categorized by the physiological processes they control, e.g., stress
response. In general, these groupings by function also correlate with phylogenetic
relationships among the protein sequences (160). Within the σ70 family of sigma
factors is a large, phylogenetically distinct subfamily called the extracytoplasmic
function (ECF) factors. These sigma factors are responsible for regulating a wide
range of functions, all involved in sensing and reacting to conditions in the membrane,
periplasm, or extracellular environment (69). Structurally, σ70 family factors have
four major regions, with the highest levels of conservation in regions 2 and 4.
Subregions within region 2 are involved in promoter melting (region 2.3) and -10
sequence recognition (2.4). Region 4.2 is involved in -35 recognition. For a recent
review on the σ70 family of sigma factors, see Paget and Helmann (160).
4
Table 1.1: Alternative sigma factors involved in virulence
Sigma Factor
Bacterial Speciesa
σ70 Family
Stress Response
σB
Ban, Lmo, Mtu, Sau, Sep
σS
Eco, Pae, Sen, Sty
σF
Mtu
ECF
RpoE
Hin, Sen, Vch
AlgU
Pae
PvdS, FpvI
Pae
σC ,
Mtu
σD,
Mtu
σE
Mtu
H
Mtu
σ
HrpL
σ
Erw, Psy
28
FliA
Cje, Hpy, Sen, Vch, Yen
σ54 Family
σN
a
Cje, Hpy, Lmo, Pae, Psy, Vch, Vpa
Species discussed in this review that contain the given sigma factors. Abbreviations:
Ban, Bacillus anthracis; Cje, Campylobacter jejuni; Eco, Escherichia coli; Erw,
Erwinia spp.; Hin, Haemophilus influenzae; Hpy, Haemophilus pylori; Lmo, Listeria
monocytogenes; Mtu, Mycobacterium tuberculosis; Pae, Pseudomonas aeruginosa;
Psy, Pseudomonas syringae; Sau, Staphylococcus aureus; Sen, Salmonella enterica
sv, Typhimurium; Sep, Staphylococcus epidermidis; Sty, Salmonella Typhi; Vch,
Vibrio cholerae; Vpa, Vibrio parahaemoliticus.
5
Although no sequence conservation exists between the σ54 family sigma
factors and any of the σ70-like sigma factors, both types bind to core RNA polymerase.
However, the holoenzyme formed with σ54 sigma factors has different properties than
a σ70 holoenzyme. While the C-terminus (region III) of σ54 enables DNA binding, to
form an open promoter complex all σ54 species require a separate activator protein
along with the core RNAP. The σ54 N-terminus inhibits isomerization in the absence
of the appropriate activator, and stimulates initiation upon activation (19). Further,
promoter structures recognized by σ54-RNAP differ from those recognized by σ70RNAP. σ54 promoters are highly conserved, short sequences that are located at -24
and -12 upstream of the transcription initiation site, in contrast with σ70 promoter sites,
which typically are located at -35 and -10 upstream. σ54 promoters, which are called 24/-12 promoters, are almost completely invariant in their spacing and at the -24/-12
positions (GG and GC, respectively) in both Gram negative and Gram positive
bacteria. For reviews on the structure and function relationships of σ54, see Merrick et
al. (138) and Buck et al. (19).
For the duration of this review, we will discuss several examples of alternative
sigma factors that have been shown to have a role in virulence in at least one
organism. The discussion will be organized according to sigma factor, including three
subfamilies (stress response, σ28, and ECF) of the σ70 family, as well as the σ54 family.
For each sigma factor, examples will be drawn from multiple species when applicable.
STRESS RESPONSE ALTERNATIVE SIGMA FACTORS
The ability to reproduce, or simply survive, under a wide variety of
environmental conditions contributes to a microbial pathogen’s transmission potential
by various routes. For example, to establish a food borne infection in a human host, a
bacterium first must survive transit in a contaminated food. Following ingestion, the
bacterium then must survive exposure to rapid and dramatic changes in environmental
6
conditions, including the acidic pH within the stomach, followed by vastly differing
conditions during intestinal passage and/or infection (e.g., exposure to bile, vacuolar
stresses, etc.) Survival of these extreme and rapidly changing conditions requires
timely and appropriate alterations in gene expression and protein activity that occur in
a bacterial cell in response to stimuli signaling these new environmental conditions.
At the transcriptional level, these alterations are often controlled by changes in
associations between different alternative sigma factors and core RNA polymerase to
essentially reprogram promoter recognition specificities of the enzyme and allow
expression of new sets of target genes.
The general stress responsive alternative sigma factors σS (RpoS) and σB
transcribe genes contributing to bacterial survival under conditions of environmental
stress in Gram-negative and in Gram-positive bacteria, respectively (Table 1.2). σS
was identified in both Escherichia coli and in Salmonella Typhimurium (formerly
referred to as S. typhimurium) as an alternative sigma factor that activates the
expression of numerous genes required to maintain cell viability during stationary
phase (51, 117). σS also plays a key role in protecting E. coli and Salmonella
Typhimurium from different environmental stress conditions, including starvation,
hyperosmolarity, oxidative damage, and reduced pH (51, 117). Since its initial
discovery, the presence of σS and its role in stress response has been confirmed in
many Gram-negative bacterial species, including P. aeruginosa, Borrelia burgdorferi,
and Vibrio cholerae (49, 92, 223). Through enhancing environmental survival, as well
as by directly activating virulence genes, σB and σS have both direct and indirect roles
in bacterial pathogenesis.
7
Table 1.2: Virulence and virulence-associated genes regulated by stress response
sigma factors σB and σS and phenotypes of sigma factor null mutants in select
bacterial species
Sigma Factor
Genes Regulated by Sigma Factor
VirulenceVirulencea
Associateda
Phenotypeb
σB
decreased invasion
(101)
decreased spread to
spleen (147)
L.
monocytogenes
bsh (98, 195, 196)
gadA (98)
opuCA (56, 98, 195,
196)
inlA (98, 101,
196)
prfA (99, 147,
187)
S. aureus
cap genes (14)
clfA (14)
bbp (14)
ebpS (14)
icaA (173)
no difference (22,
78, 148)
sarA (13, 14, 44) caused more severe
arlRS (14)
arthritis, weight loss,
IL-6 production, and
mortality (91)
unknown
chromosomal
factors (51, 149)
spv (51, 67, 110,
153)
rhl (164, 214)
las (164, 214)
exotoxin A
(197)
alginate (192,
197)
Type IV pili
(192, 197)
σS
S. Typhimurium
P. aeruginosa
a
higher LD50 in mice
(35, 51, 149)
higher LD50 in G.
mellonella and mice
(192)
Virulence-associated genes and virulence genes directly regulated by σB or σS, as
defined in text.
b
Virulence-related phenotypes observed in sigB or rpoS null mutants. Relative
phenotypes are with respect to wild type.
8
Sigma B
σB (initially called σ37) of Bacillus subtilis was among the first bacterial
alternative sigma factors identified (64, 65). In B. subtilis and related species such as
L. monocytogenes and S. aureus, σB contributes to resistance to numerous
environmental stresses, including acid, ethanol, and heat (12, 22, 53). The σB regulon
in B. subtilis contains at least 125 genes, including those with functions in stress
resistance, transcriptional regulation, and membrane transport (165, 170). In B.
subtilis and L. monocytogenes, sigB, which encodes σB, is the seventh open reading
frame in an operon containing eight genes involved in σB regulation (rsbR, rsbS, rsbT,
rsbU, rsbV, rsbW, sigB and rsbX) (Fig. 1.1A; 54, 219). All eight genes, including
sigB, are co-transcribed from a housekeeping sigma factor (σA) dependent promoter
(PA) located upstream of rsbR. A σB-dependent promoter (PB), located upstream of
rsbV, is responsible for enhanced transcription of the four downstream genes in the
sigB operon (rsbV, rsbW, sigB and rsbX) under conditions that stimulate σB activity
(11, 12, 94).
While regulation of σB activity involves both transcriptional and
posttranslational control, predominant regulation occurs via the Rsb proteins.
Bacterial species differ in the numbers and identities of rsb genes encoded in their
genomes (Fig. 1.1A), suggesting divergent evolution of the sigB operon, in both its
overall components as well as in the sequences of its individual proteins, even among
closely related bacterial species (54). Differential evolution of the σB stress response
system among various genera may represent a mechanism that has enabled bacteria to
optimize cellular response and survival strategies for highly specific niches.
9
A.
rsbR
rsbS rsbT rsbU
PA
rsbV rsbW sigB
rsbX
PB
B. subtilis
PA
PB
L. monocytogenes
PB
PA
S. aureus
PA
PB
S. epidermidis
PB
B. anthracis
PB
B. cereus
B.
RsbS P
RsbX
RsbR
RsbS
RsbT
RsbV
RsbW
σB
RsbU
RsbV P
Figure 1.1: sigB operon structure and σB regulation by Rsb proteins
A. sigB operon structures in various Gram positive bacteria.
B. Posttranslational regulation of σB activity. Arrows indicate activation of protein
activity, and T-bars indicate repression of protein activity. “P” represents a phosphate
group.
10
Although all seven Rsb proteins identified in B. subtilis and L. monocytogenes
are not conserved among all bacterial species bearing σB, two key proteins (RsbV and
RsbW) are conserved among all species examined to date and thus appear to be
minimally essential for regulating σB activity (54). Specifically, in log phase, nonstressed B. subtilis cells, σB is inactivated by its association with the anti-σB protein,
RsbW (i.e., the “anti-sigma factor”). In stressed cells, however, the unphosphorylated
form of the anti-σB antagonist protein, RsbV, (i.e., the “anti-anti-sigma factor”)
competes for binding to RsbW. As the relative concentration of the RsbW-RsbV
complex increases, the concentration of free σB also increases, thus allowing σB to
bind to core RNA polymerase (47). In B. subtilis, both environmental and energy
stress signals induce dephosphorylation of RsbV. Environmental stress signals
specifically activate the B. subtilis RsbU serine phosphatase through involvement of
RsbR, RsbS, RsbT, and RsbX (207, 208, 219). In addition to its role in the partnerswitching regulation under environmental stress, B. subtilis RsbX also functions as a
feedback regulator for σB activity (Fig. 1.1B; 12). While both energy and
environmental stresses have been shown to activate L. monocytogenes σB (25) specific
interactions among the Rsb proteins have not yet been investigated. To date, specific
activation mechanisms have been most extensively reported for B. subtilis σB.
Pathogenic Bacillus species. At least two pathogenic species of Bacillus
encode σB (55, 204). In B. anthracis, only σB, RsbV and RsbW are encoded in the
sigB operon (Fig. 1.1A). A third rsb gene, rsbY, encodes a protein with low similarity
to B. subtilis RsbP. rsbY is located in close proximity to, but not within, the B.
anthracis sigB operon (55). As in B. subtilis and L. monocytogenes, the sigB operon is
auto-regulated by σB and is induced by heat shock and entry into stationary phase (55).
A B. anthracis sigB mutant strain is virulence attenuated, producing less than half the
mortality of the parent strain in the mouse model of anthrax (55). More detailed
11
studies have not been done to determine if the attenuation is due to direct or indirect
effects.
The organization of the B. cereus sigB operon is identical to that of B.
anthracis sigB, and likewise, the sigB operon is auto-regulated by σB and is induced
by heat shock and entry into stationary phase (204). Through a combination of 2-D
gels and northern hybridizations, 15 B. cereus genes and proteins were determined to
be σB-dependent, including RsbV and the KatE catalase (205). Activity of currently
recognized B. cereus virulence factors, including protease, lecithinase, hemolytic
activity, as well as production of nonhemolytic enterotoxin was not affected by
disruption of sigB (204), suggesting that σB does not directly contribute to B. cereus
virulence.
Staphylococcus species. Staphylococcus aureus was the first pathogenic
bacterium in which sigB was identified. (113, 220; Fig. 1.1A). In S. aureus, the sigB
operon is comprised of 4 genes, which are homologous to B. subtilis rsbU, rsbV,
rsbW, and sigB. As in B. subtilis, all genes in the operon are expressed during
exponential growth, presumably from the σA-dependent promoter. The internal PB
promoter was confirmed as σB-dependent through in vitro transcription analyses (44).
Transcriptional regulation of the S. aureus sigB operon is complex, generating
multiple transcripts that appear to include a bicistronic sigB-rsbW transcript as well as
a sigB monocistronic transcript. In support of an autoregulatory role for S. aureus σB
under conditions of environmental stress, an rsbV-W-sigB transcript was induced
following exposure of cells to either 4% ethanol or a 48°C heat shock (113).
S. aureus σB activity is regulated posttranslationally by Rsb proteins. The ORF
immediately upstream of S. aureus sigB encodes the anti-sigma factor, RsbW (142).
As in B. subtilis, S. aureus σB also is activated via an RsbU pathway (61). An 11 bp
deletion in rsbU in the NCTC8325 strain generated some phenotypic characteristics
12
similar to those of a ∆sigB strain, (e.g., decreased H2O2 resistance; 112). Giachino et
al. (61) confirmed that NCTC8325 does not produce a functional RsbU, and that
complementation of this strain with a complete rsbU allele restored phenotypes to
those of the rsbU+ Newman wild type strain. However, some NCTC8325 phenotypes
were identical to other rsbU+ strains (e.g., lipase production, see below), suggesting
the existence of multiple S. aureus σB activation pathways, including at least one that
is RsbU-independent (112). As with RsbU, loss of RsbV results in a dramatic
decrease, although not complete loss, of S. aureus σB activity (161).
Through application of full genome microarray screens for σB-dependent genes
in three S. aureus strains, as many as 251 genes have been identified as σB-regulated
(14), including several genes encoding proteins involved in synthesis of capsular
polysaccharides. A number of adhesins, which are involved in Staphylococcus
virulence, were also found to be upregulated by σB. Multiple genes encoding
exoenzymes and toxins (e.g., hla, nuc) were downregulated as σB was activated (14).
These results may reflect σB’s role in regulating expression of virulence gene
regulators in S. aureus. For example, the quantity of RNAIII present is reduced as
activity of σB increases (13, 14). RNAIII is the effector RNA produced from the agr
locus of S. aureus. RNAIII negatively regulates expression of some virulence genes
while positively regulating others. Interestingly, the exoenzymes and toxins that were
downregulated in a σB-dependent fashion are upregulated in the presence of RNAIII
(200). Expression from the agrP3 promoter, which directs transcription of RNAIII, is
dependent on SarA (78). sarA itself has multiple promoters, one of which is σBdependent. Deora et al. (44) purified σB from S. aureus and showed that σB
holoenzyme is adequate and sufficient for transcription initiation of the sar locus at
P3, as predicted by promoter sequence (8). However, Horsburgh et al. (78) showed
that SarA levels remain constant in the presence or absence of functional σB,
13
suggesting that σB may not repress RNA III through SarA. Thus, while it is apparent
that increased σB activity results in lower quantities of RNAIII, the mechanism
responsible for this phenomenon remains unclear. Alternatively, either SarA or
RNAIII could be present but not active under certain conditions, potentially explaining
seemingly contradicting evidence, but no evidence has been presented to support this
hypothesis.
Multiple groups have described S. aureus ∆sigB mutants as having pigment
loss, decreased peroxide resistance, and higher α-hemolysin activity as compared to
wild type (27, 61, 78, 112, 148). Also, coagulase activity, clumping factor, and lipase
activity are higher in sigB mutants than in wild type (112, 148). With the exception of
pigment production, the remaining characteristics have been associated with S. aureus
virulence (60, 66, 96, 146, 180). It is likely that optimal levels of virulence factor
expression and activity are required for efficient S. aureus infection, and that too much
or too little activity, or expression at the wrong time is detrimental for the infection
process. These hypotheses remain to be rigorously tested. In various animal models,
wild type S. aureus and an otherwise isogenic ∆sigB strain showed no difference in
virulence (22, 148). In additional, conflicting studies, Horsburgh (78) found no
difference in virulence between rsbU+ and rsbU- strains in a murine skin abscess
model, while Jonsson et al. (91) showed that both rsbU- and sigB- strains displayed
decreased virulence phenotypes compared to the wild type strain in murine septic
arthritis, including reduced mutant persistence in kidneys, and reduced mouse
mortality, weight loss, arthritis, and IL-6 production.
The contradictory evidence surrounding the role of σB in S. aureus virulence
suggests that σB contributions to virulence may be indirect or not detectable in some
model systems. For example, σB may contribute indirectly to S. aureus virulence
through regulation of biofilm formation. Biofilm formation can be a prerequisite for
14
establishing infection by staphylococci, and σB has been shown to enhance
microcolony and biofilm formation in Staphylococcus species (5, 173). Two studies
have shown induction of S. aureus biofilm formation in a σB-dependent fashion (5,
173), although another showed that a ∆sigB strain formed biofilms and produced PIA
equally as well as wild type (203). S. aureus σB contributions to biofilm formation
likely occur through σB-dependent transcription of the ica operon, which encodes
essential elements of biofilm biosynthesis (173).
Staphylococcus epidermidis also encodes σB. The sigB operon of S.
epidermidis is similar to that of S. aureus (Fig. 1.1A), however, σB serves different
functions in the two species. Processing of lipase, a virulence factor, is dependent on
σB in S. epidermidis (100), while in S. aureus, lipase production is higher in a sigB
mutant than in the wild type strain (112). Multiple studies of σB and S. epidermidis
virulence suggest that σB’s effects are primarily mediated through biofilm formation in
this organism (33, 104, 105). Stress induction of σB in S. epidermidis increases
biofilm formation and synthesis of PIA, a polysaccharide adhesin that is synthesized
by the icaADBC gene products and is required for biofilm formation. An rsbU mutant
does not form biofilms or produce PIA (104). As in S. aureus, S. epidermidis σB
contributes to biofilm formation via regulating expression of ica genes. By
downregulating the icaR repressor, active σB causes an increase in icaA expression and
a biofilm positive phenotype (105).
L. monocytogenes. σB has also been well studied in the Gram positive
pathogen Listeria monocytogenes. While the sigB operon structures are identical in L.
monocytogenes and in B. subtilis (11, 215; Fig. 1.1A), signal transduction pathways
differ in the two organisms. In B. subtilis, environmental and energy stresses are
conveyed to σB through two inter-connected but separate pathways. The
environmental stimulus pathway is transmitted by regulatory proteins encoded in the
15
sigB operon (RsbT, RsbU, Rsb V and RsbW). In addition to requiring RsbV and
RsbW, the B. subtilis energy stress pathway also requires proteins encoded in a twogene operon (rsbQ-rsbP) that is physically separate from the sigB operon (18). This
latter operon is not present in L. monocytogenes. Instead, both energy stress and
environmental stress activation of σB in L. monocytogenes occurs through a single
pathway, which includes RsbT, RsbU, RsbV, and RsbW (25).
A genome-wide search for predicted σB-dependent promoters using a Hidden
Markov Model followed by application of a specialized, partial microarray, identified
54 genes under positive control of σB in L. monocytogenes, although the full regulon is
likely to be as large as that of B. subtilis (98). σB regulates expression of virulence and
virulence-associated genes in L. monocytogenes (Fig. 1.2A, Table 1.2). bsh encodes a
bile salt hydrolase that is important for virulence of L. monocytogenes (48) and is
directly regulated by σB (98, 195). Another recently identified virulence-associated
gene, hfq, also is σB-dependent (29). Deletion of the opuC osmotransporter negatively
affects L. monocytogenes virulence (190, 213), and the gene encoding this transporter
is σB-dependent, as well (56).
As in S. aureus, L. monocytogenes σB also controls expression of virulence
gene regulators (Fig. 1.2A). Of the two promoters directly upstream of the gene
encoding positive regulatory factor A (PrfA), P2prfA is σB-dependent. Dual deletion of
sigB and the σA-dependent P1prfA promoter (leaving only the σB-dependent P2prfA)
reduced hemolytic activity and intracellular growth to the same low levels as deletion
of both prfA promoters (147). σB activity at the P2prfA promoter was also directly
confirmed, both by qRT-PCR (99), and with GUS reporter fusions of prfA promoters,
which demonstrated σB- and growth phase-dependent expression from P2prfA (187).
16
Figure 1.2: Examples of regulatory networks involving sigma factors and other
transcriptional regulators.
A. The σB-PrfA network of L. monocytogenes.
B. The short sigma factor cascade regulating Type III secretion in P. syringae.
C. The complex interaction of several sigma factors that affect virulence in M.
tuberculosis. The interactions depicted here were deduced from global expression
profiles and may be the result of either direct or indirect regulation by the sigma
factor(s).
17
A.
+
B
σ
prfA
PrfA
opuCA
hfq
+
inlA
bsh
+
actA
hly
B.
cfa/CMA
cmaABT
+
hrpL
σN
Hrp
L
C.
hrp
avr
+
sigH
+
dnaK
σH
hsp
sigE
+
cspA
σE
+
htpX
+
sigB
sigC
mtrA
senX3
+
σC
+
σF
18
Several PrfA-regulated genes are also σB-dependent, suggesting interplay
between the two regulators (139; Fig. 1.2A). The PrfA-regulated inlA, which encodes
the cell surface protein internalin-A, is σB-dependent (98, 196). Internalins are cell
wall-anchored proteins with important roles in the intracellular pathogenesis of L.
monocytogenes, and several members of the internalin gene family show reduced
expression in a sigB mutant compared to wild type (98). Internalin-A, specifically, is
responsible for invasion of non-professional phagocytes (127). Loss of σB reduced
invasiveness of the mutant strain as compared to that of wild type L. monocytogenes in
two intestinal epithelial cell lines, Henle-407 and Caco-2 (101). In addition, inlA
transcription was greatly reduced in the ∆sigB strain, and internalin-A was
undetectable by western blot (101). None of the effects of the sigB deletion on inlA
were mediated through loss of σB-dependent transcription of PrfA, however, as a
∆P2prfA strain had the same level of invasiveness, inlA transcription and internalin-A
concentration as the wild type strain.
Wiedmann et al. (215) tested the effect of a sigB deletion on virulence in a
mouse model, and found a small, but significant, decrease in spread of the mutant
strain to the liver, as compared with that of the wild type strain. As may be the case
with S. aureus, complete discovery of the role of σB in L. monocytogenes virulence
may have been hampered by use of model systems that are not ideal for studying hostpathogen interactions. Mouse infection experiments have been widely used to
evaluate virulence characteristics of L. monocytogenes, including the preliminary
evaluations of the ∆sigB mutant (147, 215). In recent years, however, increasing
evidence suggests that the murine model does not appropriately represent human L.
monocytogenes infection by the oral route (119, 120). The gastric pH of mice is
higher than the pH of the human stomach (95), thus, the role of L. monocytogenes acid
tolerance is likely to be less important in mouse infection than in human infection.
19
More importantly, in the human, L. monocytogenes has the ability to cross the
intestinal barrier, the blood-brain barrier, and the fetoplacental barrier. Human Ecadherin acts as a L. monocytogenes internalin A receptor, and the interaction between
the receptor and the internalin A surface protein contributes to the ability of L.
monocytogenes to target and cross human intestinal and placental barriers (121).
Murine E-cadherin, which differs in amino acid sequence from human E-cadherin,
does not interact effectively with L. monocytogenes internalin-A, hence mice show
limited susceptibility to intragastric L. monocytogenes infection (119). In fact, in the
mouse, translocation of L. monocytogenes across the intestinal barrier is typically no
greater than that of the non-pathogenic L. innocua. Further, L. monocytogenes also
does not appear to target the murine brainstem or the fetoplacental unit, even
following intravenous injection (119, 120). L. monocytogenes strains do vary in their
ability to cause systemic infection in intragastrically infected mice (38) and some
strains of mice (A/J) are also more susceptible than others (C57BL/6) to intragastric
infection (39). However, as a consequence of the biological differences in murine and
human L. monocytogenes translocation across the intestinal barrier, data from mouse
infection experiments may under-estimate a given strain’s human virulence following
oral infection.
The guinea pig has emerged as a more appropriate model than the mouse for
studying L. monocytogenes infection by oral infection (119, 120). As in humans,
guinea pigs exhibit gastroenteritis following L. monocytogenes infection by the oral
route (120). Cultured guinea pig epithelial cells allow internalin A-dependent L.
monocytogenes entry and both guinea pig and human E-cadherin bear a proline at
critical amino acid position 16. When guinea pigs were inoculated orally with L.
monocytogenes strain EGD or an otherwise isogenic ∆inlA strain, significantly higher
numbers of the wild-type than of the ∆inlA strain were recovered from guinea pig liver
20
and spleen. In contrast, in the mouse model, low, statistically indistinguishable wildtype and ∆inlA numbers were recovered from mouse organs (119). Lecuit et al. (119)
also demonstrated that transgenic mice expressing human E-cadherin enable bacterial
invasion of host cells. Taken together, these results illustrate the importance of
appropriate internalin-A/E-cadherin interactions in the development of systemic
listeriosis following oral infection with L. monocytogenes.
Mycobacterium tuberculosis σB and σF. Mycobacterium tuberculosis, a high
G-C bacterium, has 13 sigma factors (for a review, see 134). Two of these thirteen, σB
and σF, appear to share an evolutionary origin (54). M. tuberculosis σF appears more
similar to σB of the low G-C Gram positive bacteria than to σF of B. subtilis, which is a
sporulation factor. Specifically, M. tuberculosis σF is antigenically closer to B. subtilis
σB (43), has the same consensus promoter recognition sequence (10, 59), and its gene
has similar gene expression patterns as B. subtilis sigB (42, 130). As with B. subtilis
σB, M. tuberculosis σF is regulated posttranslationally by an anti-sigma factor and antianti-sigma factor partner-switching mechanism (10). The gene encoding M.
tuberculosis σF is immediately downstream of the gene encoding its anti-sigma factor,
UsfX, as is the case with B. subtilis σB and its anti-sigma factor, RsbW. M.
tuberculosis sigB, on the other hand, is located 3 kb downstream of the gene for the
primary sigma factor, σA, and is not flanked by genes encoding sigma factor
regulatory proteins (45). sigB in M. tuberculosis and in L. monocytogenes also share
some characteristics. For example, expression of M. tuberculosis sigB is growth phase
dependent, as is expression of sigB in other species (42, 79). The same studies also
showed that sigB transcription is induced under a variety of stresses, including
peroxide stress, heat shock, and cold shock. In spite of these observations on σB stress
induction, no studies have been reported on contributions of this protein to either M.
tuberculosis stress resistance or virulence.
21
Microarray analysis of the M. tuberculosis σF regulon identified ahpC, a gene
implicated in virulence, as greatly reduced in expression in a ∆sigF mutant (59). In
addition, another sigma factor, sigC, which is required for M. tuberculosis lethality in
mice (198), is also σF-dependent (Table 1.3). Several studies have linked M.
tuberculosis σF with virulence. Mice infected with a ∆sigF strain displayed a longer
time to death then mice infected with the wild type strain, and the weight loss caused
by wild type M. tuberculosis did not occur in mice infected with the mutant strain
(26). In a separate study, CFU counts recovered in the lungs and spleens of infected
mice were approximately 40 times higher for the wild type than the ∆sigF strain.
Histopathological analyses showed that the ∆sigF mutant caused fewer, smaller
granulomas and less inflammation than the wild type (59) after 12 weeks. In
summary, multiple lines of evidence support direct and indirect roles for σF in M.
tuberculosis virulence. Further, M. tuberculosis σF appears to be more similar in
structure and function to the low G-C bacterial σB than does the M. tuberculosis σB.
Sigma S (RpoS)
In Gram negative bacteria, RpoS (σS) is functionally similar to σB in that it is
responsible for stationary phase and stress response gene expression. The
chromosomal organization of the rpoS and sigB loci, as well as the transcriptional and
post-transcriptional regulatory mechanisms for these genes and proteins are distinctly
different, however. Regulation of σS expression and activity is extremely complex,
relying on transcriptional, translational, and posttranslational mechanisms (for a
thorough review, see 74). Further, a sequence comparison of 31 σ70-family sigma
factors groups Escherichia coli σS separately from B. subtilis σB, indicating that while
σB and σS may have similar functions, they are not highly homologous proteins (129).
22
Table 1.3: Genes regulated by Mycobacterial alternative sigma factors and
phenotypes of sigma factor null mutants
Sigma Factor
σC
Genes Regulated by Sigma Factor
Virulence
a
Regulatory
Phenotypea
hspX
mtrA
senX3 (198)
[none identified]
sigB (198)
nonlethal (198)
Rv1816 (possible
tetR family
transcriptional
regulator) (175)
σE
sodA
hsp
htpX (131)
sigB
cspA
Rv0287 (possible
transcriptional
regulator) (131)
delayed time to
death (20, 175)
decreased lung
tissue damage and
granuloma
formation (175)
decreased survival
in macrophages
(131)
delayed time to
death (2, 133)
σF
ahpC (59)
sigC (59)
σH
MT1516-7,
MT4032-3,
MT0838 (possible
thioredoxins) (97)
MT2541, MT2063
(possible oxidative
stress response)
(97)
MT0265, dnaK
(97)
hsp, clpB (132)
MT3938 (possible
tetR family
regulator) (97)
sigE (97, 132)
sigB (97, 132)
Rv0142 (possible
transcriptional
regulator) (132)
σD
a
delayed time to
death (26)
decreased numbers
in lungs, milder
histopathology
(59)
nonlethal (97)
Relative phenotypes are with respect to wild type. All infections were done in mice.
23
Escherichia coli. A few reports have examined associations between σS and
E. coli virulence, but little direct evidence of a link exists. Wang and Kim (210)
demonstrated that E. coli K1 invasion of brain microvascular endothelial cells
(BMEC) was higher for stationary cells than for exponentially growing cells, possibly
due to stationary phase activity of σS. Indeed, complementation of rpoS into an rpoS
mutant significantly increased invasion for one E. coli isolate, but not for another
(210). σS is not essential for murine urinary tract colonization (37), and actually
appeared to be detrimental during competitive colonization experiments in the mouse
intestine (111). It is also possible that the lack of an appropriate animal model for
investigating all aspects of E. coli pathogenesis [e.g., absence of an appropriate model
for studying hemolytic uremic syndrome (HUS) infections caused by
enterohemorrhagic E. coli (189)] has impeded identification of a direct role for σS in
E. coli pathogenesis.
It is likely that σS contributes indirectly to E. coli pathogenesis. E. coli
O157:H7 strains tend to be acid resistant, and rpoS mutants show decreased acid
resistance and fecal shedding in mice and cattle (171). Several studies have shown
that rpoS transcription as well as σS activity are induced under stress conditions such
as osmotic shock, heat, and low pH, and that survival of rpoS mutants is reduced
under these same conditions (3, 37, 58, 73, 211). Thus, in addition to enabling
survival in high acid and high salt foods, σS may enhance E. coli host survival and
transmission.
Salmonella species. Salmonella enterica serovar Typhimurium (S.
Typhimurium) σS is highly similar to E. coli σS, in both function and regulation. In
contrast with E. coli, however, numerous studies have shown the unequivocal
dependence on σS for full virulence of S. Typhimurium. For example, the plasmid
borne spv gene cluster is required for S. Typhimurium virulence , and several studies
24
have demonstrated that transcription of this gene cluster is σS-dependent (51, 67, 110,
153; Table 1.2). In fact, an rpoS mutant is up to 10-fold less virulent than an rpoS+,
plasmid cured (spv -) strain, and the levels of plasmid cured rpoS+ bacteria in the
intestine were significantly higher than the plasmid cured rpoS mutants (51, 149),
indicating that the effect of σS on virulence is likely due to chromosomal genes in
addition to its effects on the plasmid-borne spv locus. In addition, mouse-based
virulence assays show that, in comparison to the wild type strain, the rpoS mutant has
a 3-4.5 log higher LD50 (35, 51, 149). Similarly, an rpoS aroA strain was more
virulence-attenuated than an aroA strain, which has been used in vaccine candidate
trials, as determined by spleen bacterial counts and time-to-death analyses (35). σS
does not contribute to levels of S. Typhimurium adherence, invasion, or intracellular
survival, however (149).
Further evidence for the role of σS in Salmonella virulence was obtained
through analysis of rpoS alleles from recognized avirulent or virulence attenuated
strains. For example, the Salmonella typhi vaccine strain Ty21a contains an rpoS
sequence that generates a nonfunctional σS (177). Virulence attenuation in the
Salmonella Typhimurium LT2 strain may be a consequence of low levels of rpoS
mRNA translation due to the presence of a rare UUG start codon on the transcript
(122, 199). As in laboratory-generated rpoS mutants, the LT2 strain is greatly
decreased in its ability to reach the spleen and liver of mice (217).
Pseudomonas aeruginosa. P. aeruginosa produces many exotoxins that
contribute to its pathogenesis. σS appears to have multiple regulatory roles in P.
aeruginosa. In some cases, σS positively regulates P. aeruginosa toxin expression; in
others, it negatively regulates expression, and in still others, it appears to have no
effect at all. For example, in an rpoS mutant, both exotoxin A and alginate production
are approximately 50% that of the wild type (192, 197; Table 1.2). However,
25
expression of pyocyanin, an antibiotic that also inhibits lymphocyte proliferation, is
increased 200% in the absence of σS, (192, 197), as well as in a mutant which
independently was found to have reduced rpoS expression, psrA (107). In two studies,
loss of σS was shown to have little to no effect on production of elastase or LasA
protease (192, 197). Some of the phenotypic effects on P. aeruginosa virulence factor
production that are associated with loss of σS may be indirect, for example, resulting
from reduced expression of quorum sensing systems (Table 1.2). σS contributes to
expression of members of the P. aeruginosa rhl and las quorum sensing systems (164,
214). These quorum sensing gene products are responsible for regulating production
of several virulence factors, including lectins (186, 218), aminopeptidase,
endoproteinase, and lipase (154), and rhamnolipid (162, 228). Several studies have
shown quorum sensing mutants to be avirulent or less virulent than the wild type strain
in mouse (163, 181, 191, 228), amoeba (34), and rat models (124). Finally, the role of
σS in P. aeruginosa virulence is highly dependent on the model system in which it is
assessed. For example, while an rpoS mutant was equally virulent than wild type in a
rat chronic lung model (197), it was approximately half as virulent as the wild type
strain in a Galleria mellonella (silk moth) larvae model (192).
SIGMA 28 SUBFAMILY
σ28 is a subfamily of the σ70-like sigma factors. Members of this subfamily are
structurally and functionally related, and span many genera of both Gram positive and
Gram negative bacteria. The primary regulatory role of the σ28 factors is to transcribe
genes required for flagellar synthesis and bacterial motility (68, 140). Examples of σ28
factors are FliA of enteric bacteria and σD of B. subtilis.
FliA
Salmonella Typhimurium. As in many enteric bacteria, the genes for
flagellar biosynthesis and function in S. Typhimurium are divided into 3 hierarchical
26
classes based on their temporal order of transcription (114). One operon, flhDC, is
categorized into class I. The flhDC operon encodes activators required for
transcription of the class II operons including fliA, which encodes the σ28 subfamily
sigma factor responsible for expression of the class III genes (83, 157), and flgM,
which encodes the FlgM anti-sigma factor that regulates activity of FliA (62, 158).
The remaining class II genes encode proteins responsible for formation of the flagellar
basal body and hook apparatus. Through an additional posttranslational regulatory
mechanism, following formation of the flagellar structure, FlgM is secreted through
the basal body/hook assembly, which enables de-repression of FliA and allows
subsequent transcription of the class III genes (80, 115). Inactivation of any of the
class II genes interrupts complete formation of the flagellum, and the accumulated
FlgM prevents further flagellar filament formation. Loss of FlgM results in an
approximate six-fold increase in transcription of the FliA-dependent class III genes
(116). Interestingly, while flgM mutants are virulence-attenuated, an additional
mutation that inactivates FliA function restores virulence to the strain (183). The
mechanism for this phenomenon is still unknown. Many studies have shown the
importance of flagella for virulence of S. enterica serovars (86, 178, 193), although the
specific aspect of flagellar function that contributes to virulence remains unclear. The
current absence of an optimal model system that accurately simulates conditions
relevant to the human body may hinder discovery of critical S. Typhimurium flagellar
contributions to human infection (184, 193).
FliA in other species. Regulation of flagellar gene expression in Yersinia
enterocolitica is similar to that in S. Typhimurium. fliA encodes a σ28 factor
responsible for motility of the bacterium, and the master regulators FlhC and FlhD are
required for expression of all genes encoding proteins active in subsequent flagellar
synthesis (84). Motility is also required for full Y. enterocolitica invasion efficiency
27
(224). However, another group of enteric bacteria has a different strategy for
regulating flagellar gene expression. Helicobacter pylori, Campylobacter jejuni, and
Vibrio cholerae do not have the flhDC master operon. Instead, early flagellar gene
expression is carried out via a σ54 factor, while later genes are transcribed by FliA (88,
103, 150). These species also encode one or more σ54 activator proteins, such as FlgR.
Virulence in these species is linked to production of flagella. In C. jejuni, virulence
proteins are secreted through the flagella, and full virulence requires a complete
flagellar export apparatus (108). Multiple studies have shown H. pylori virulence to
be dependent on expression of both flagellin proteins and on flagellar motility (93,
137).
ECF SIGMA FACTORS
Members of the extracytoplasmic function (ECF) subfamily of σ70 sigma
factors regulate functions related to sensing and responding to changes in the bacterial
periplasm and extracellular environment. These sigma factors are conserved in both
Gram positive and Gram negative species. The first ECF sigma factor identified was
E. coli σE, which was recognized as a second heat-shock sigma factor in this organism
(209). Though σE does not appear to affect virulence in E. coli, other ECF sigma
factors contribute to regulation of virulence and virulence-associated genes in a
number of bacteria, including S. Typhimurium, Pseudomonas aeruginosa, and
Mycobacterium tuberculosis. A recent review covers some aspects of ECF sigma
factors and their involvement in pathogenesis (4).
Sigma E (RpoE)
rpoE appears to influence S. Typhimurium through regulation of oxidative
stress resistance. To illustrate, inactivation of rpoE results in diminished ability of the
bacteria to survive and grow inside host macrophages (21, 81). Further, while an rpoE
28
mutant is severely attenuated in virulence in a mouse model of infection (81, 201), an
rpoE mutant strain appears fully virulent in gp91phox-/- mice, which are defective in
phagocyte oxidative burst (201). Expression of htrA, a gene required for oxidative
stress resistance, macrophage survival, and S. Typhimurium virulence (7, 23, 90) is
dependent on σE (50, 128). However, the survival and virulence defects in rpoE
mutants are not entirely due to loss of htrA expression, because the attenuated
virulence phenotype of an htrA mutant is less severe than that of the rpoE mutant (81).
σE appears to contribute to oxidative stress resistance in other Gram negative
pathogens. In Haemophilus influenzae, rpoE expression was discovered to increase
100-fold inside macrophages, and survival of an rpoE mutant was reduced relative to
that of the wild type in the macrophage (36). Vibrio cholerae rpoE mutants are
virulence attenuated, exhibiting a reduced ability to colonize the mouse intestine and
an LD50 3 logs higher than wild type (109). Although σE is not essential for growth in
H. influenzae or V. cholerae, interestingly, it is essential for growth in Yersinia
enterocolitica (75). σE in Y. enterocolitica also appears to regulate htrA, which is
important for virulence in this bacterium as well (76, 125).
AlgU of P. aeruginosa (also called AlgT) is homologous and functionally
equivalent to σE of E. coli (136, 225). As in the pathogens mentioned above, P.
aeruginosa algU mutants have increased sensitivity to oxidative stress (136) and
reduced survival in macrophages and neutrophils (226). Additionally, AlgU regulates
biosynthesis of alginate, a major virulence factor in P. aeruginosa infections of cystic
fibrosis patients. Expression of the major alginate biosynthesis gene algD and
production of alginate are dependent on algU (135, 185). Thus, it appears that P.
aeruginosa AlgU, a homolog of σE, has maintained its role in regulating oxidative
stress resistance, but has also evolved an additional role in virulence through the
regulation of alginate production.
29
PvdS and FpvI
In P. aeruginosa, secretion of the siderophore pyoverdine, a virulence factor, is
required for in vivo growth and virulence. Pyoverdine is released when cells
experience iron limiting conditions, which is common during host infection.
Pyoverdine enables P. aeruginosa to sequester iron from the environment. The
secreted pyoverdine chelates extracellular iron, and the resulting ferri-pyoverdine
complex is transported back into the bacterial cell (206) as described below.
The genes involved in pyoverdine synthesis are located in three clusters on the
P. aeruginosa chromosome, with the major genes comprising the pvd locus. Among
these genes is pvdS, which encodes an alternative sigma factor. PvdS appears to be
predominantly responsible for regulating genes in the pvd locus as well as other
pyoverdine synthesis genes (143, 156, 194). The binding of iron by pyoverdine
outside a cell initiates a signaling cascade which leads to enhanced expression of pvd
genes and additional secretion of pyoverdine and other virulence factors. Upon
forming a complex with iron, pyoverdine binds to the FpvA cell surface receptor
protein. FpvA is responsible for transporting the pyoverdine into the cell, but also
triggers a signal cascade to the membrane bound anti-sigma factor, FpvR, which
releases PvdS and allows it to transcribe the pvd genes. FpvR also controls the
activity of another sigma factor, FpvI (9). The signal from bound pyoverdine also
results in release (and hence, activation) of this factor, which is responsible for
expression of fpvA.
In addition to increasing pyoverdine synthesis and secretion, free PvdS also
activates transcription of genes encoding two more virulence factors, specifically those
encoding exotoxin A and PrpL endoprotease. Expression of genes responsible for
pyoverdine, exotoxin A, and PrpL production are also controlled by the regulator
PtxR; expression of ptxR is also controlled by PvdS. A pvdS deletion mutant
30
generates less PrpL (216) and only 5% of the exotoxin A produced by a wild type
strain (155).
Loss of PvdS results in decreased P. aeruginosa virulence in a rabbit aortic
endocarditis model (222). The PrpL endoprotease contributes to the ability of P.
aeruginosa to persist in a rat chronic pulmonary infection model (216). PvdS is
required for virulence and appears to only regulate virulence-related genes.
Mycobacterial ECF sigma factors
Mycobacterium tuberculosis has 13 recognized sigma factors; among these, 10
represent ECF sigma factors. At least six M. tuberculosis sigma factors affect
virulence, including the primary sigma factor (31), σF, and four ECF sigma factors, σC,
σD, σE, and σH (Table 1.3). The regulons of many of these sigma factors (σC, σD, σE,
σF, and σH) have been identified through application of M. tuberculosis genome arrays
(20, 59, 97, 131, 132, 175, 198). Surprisingly, M. tuberculosis ECF sigma factors do
not appear to control many currently characterized virulence genes. For example, σD
does not appear to directly regulate any virulence associated genes (20, 175).
However, it does control the putative transcriptional regulator, Rv1816. It is possible
that this putative regulator is responsible for direct control of virulence gene
expression, but no evidence currently exists to support this hypothesis (175). σC, σE,
and σH each control a relatively small number of virulence or virulence-associated
genes, as well as some regulatory genes that may influence expression of other
virulence genes. Several other ECF sigma factors also regulate a number of known or
putative regulatory genes (Table 1.3). Interestingly, in some cases, this group of
sigma factors contributes to regulation of other sigma factors within the group. For
example, sigB expression is affected by σC, σE and σH (97, 131, 132, 198). σC
activates expression of hspX, mtrA, and senX3 (198), three genes shown to be required
31
for virulence. mtrA and senX3 represent two-component system response regulators.
Other virulence-associated genes regulated by M. tuberculosis ECF sigma factors
include heat shock proteins and oxidative stress response proteins. For example, the
heat shock genes hsp and htpX are σE-dependent (131), and hsp, dnaK, and clpB are
regulated by σH (97, 132). A number of putative thioredoxins and other oxidative
stress genes are controlled by σH (97; Table 1.3), and sodA, encoding the superoxide
dismutase, is regulated by σE (131). The contributions of these ECF sigma factors to
expression of oxidative stress resistance genes may explain reduced survival of the
respective null mutant strains under oxidative stress or inside macrophages (131, 132).
Recently, deletion of sigC was shown to render M. tuberculosis unable to
cause death in infected mice (198). Deletion of another sigma factor gene, sigH, also
produced a nonlethal strain (97). Interestingly, despite the inability to cause fatalities,
both sigC and sigH mutants grew to wild type numbers in macrophages and murine
tissues (97, 132, 198). Although the reasons for the similar phenotypes between the
two different mutant strains are unknown, it is possible that a subset of virulence
associated genes is regulated by both factors. Alternatively, σC and σH may have
evolved to provide similar contributions to M. tuberculosis, but through different
mechanisms. σE appears to affect M. tuberculosis virulence differently than σC and
σH. As with sigH, sigE expression is induced inside macrophages (63, 89). Loss of
σE, however, does result in decreased strain survival in macrophages and a greater
susceptibility to killing by activated macrophages (131). In mouse infection models,
the sigE mutant is delayed in its ability to cause lethality, but is not completely
compromised, as with the sigC and sigH mutant strains (2, 133). Manganelli et al.
(133) reported a lower number of sigE mutants in the lungs as compared to wild type,
while Ando et al. (2) reported no difference. This discrepancy may be due to
32
differences in mouse strains used between the studies, and once again underscores the
importance of applying appropriate animal models to study infection processes.
Multiple studies suggest that σD also contributes to M. tuberculosis virulence.
Deletion studies of sigD show the mutant to be less virulent than the wild type in
BALB/c and C3H:HeJ mouse infections, allowing substantially longer mouse survival
(20, 175). The ∆sigD strain did not show a difference in time-to-death in SCID mice,
which lack T and B cells (20), suggesting that σD regulates pathogenicity in a manner
dependent on cell-mediated immunity. In addition, loss of σD resulted in much milder
tissue damage and granuloma formation in lung tissue histopathology in BALB/c mice
(175).
Several alternative sigma factors present in M. tuberculosis affect virulence,
whether through direct, indirect, or both types of strategies. In addition, some
alternative sigma factors of M. tuberculosis auto-regulate transcription of their own
genes. Many sigma factors also activate transcription of other alternative sigma
factors (Fig. 1.2C). In all, M. tuberculosis appears to have control over expression of
its virulence genes via a complex network of multiple alternative sigma factors.
HrpL
Pseudomonas syringae is a plant pathogen with several pathovars that display
selective host specificity. Infection of a plant by a specific pathovar will cause disease
in susceptible host species, while eliciting a programmed cell death termed the
hypersensitive response (HR) in resistant plants. The groups of genes responsible for
both of these reactions have been termed hrp and avr. These gene products encode
either the type III secretion machinery that translocates proteins into host plant cells or
the effector proteins that are delivered and that interact with host elements. Most of
the hrp genes are regulated by the alternative sigma factor, HrpL. Strains with
33
mutations in hrp genes cannot elicit disease or HR in plants (for a review, see 118).
Likewise, inactivation of HrpL decreases P. syringae pv. phaseolicola growth in
leaves (174). HrpL is an alternative sigma factor that is solely responsible for
virulence functions.
Another important phytopathogen, Erwinia amylovora, also utilizes a hrpencoded Type III secretion system. As in P. syringae, E. amylovora HrpL is an
alternative sigma factor that directs transcription of several hrp genes (102).
Inactivation of HrpL prevents E. amylovora from causing disease in susceptible plant
species or HR in resistant plants (212). E. amylovora also has a dsp, or “disease
specific,” gene cluster which is homologous to the avr genes of P. syringae (15).
dspA is dependent on HrpL for expression, and is required for virulence (57). In
addition to E. amylovora, several other members of the Erwinia genus encode hrpL
and other hrp genes, including the tumorigenic pathogen E. herbicola (145, 151, 152)
and the soft-rot pathogens E. carotovora (24, 123, 176) and E. chrysantemi (6). The
hrp-encoded Type III secretion system is thus a common virulence mechanism among
plant pathogens, and is widespread among several types of pathogens, including
tumorigenic, macerating, and soft rot-causing species.
SIGMA 54
σ54 forms a distinct subfamily of sigma factors, apart from the σ70-like family.
In almost all species, the σ54 factor is called σN. σN has been identified in many
species, spanning a diverse phylogeny, including Legionella pneumophila (87),
Pseudomonas spp. (71, 85, 106), Enterococcus faecalis (40), Campylobacter jejuni
(88), and Listeria monocytogenes (179). A physiological theme for σN-dependent
genes has not yet emerged, as the regulated genes described to date control a wide
34
Table 1.4: Virulence genes regulated by σN in multiple bacterial species
Species
Virulence mechanismsa
Genesb
H. pylori
C. jejuni
V. cholerae
P. syringae
E. carotovora.
P. aeruginosa
flagella
class II flagellar genes
(fliA and structural) (88,
150, 172)
hrpL (24, 82)
Type III secretion
flagella
alginate
class II flagellar genes
(regulatory and structural)
(41)
algD, algC (17, 229)
pili
pilA (202)
a
Virulence systems regulated by σN-dependent genes.
b
Specific genes or types of genes within a virulence system that are regulated by σN.
35
diversity of processes (Table 1.4). Often nitrogen metabolism is controlled by σN, but
other functions of σN-dependent genes can be found in several organisms.
Sigma N
Pseudomonas aeruginosa. Evidence of σN involvement in bacterial
pathogenesis and virulence is well documented in P. aeruginosa. Production of
alginate is a virulence factor important in strains colonizing cystic fibrosis patient
lungs. algD and algC, two important genes for the biosynthesis of alginate, are
controlled by σN (17, 229). In addition, through gene fusion and microarray studies,
expression of a large number of flagellar structural genes were shown to be dependent
on σN (41).
Flagellar motility and pili-mediated attachment are established virulence
factors in P. aeruginosa (144, 182). Pili are external structures responsible for
adhesion to host cells and interactions such as internalization. P. aeruginosa rpoN
mutants do not produce pilin or form pili (202), and demonstrate drastic loss of
adhesion to multiple cell types (28, 32, 168). Wild type P. aeruginosa also is
internalized more efficiently by host cells than an rpoN mutant (168), suggesting an
enhanced capacity of the wild type strain to invade host cells. Reduced virulence due
to loss of flagellar motility is also possible in rpoN disrupted strains, as mutants are
decidedly nonmotile (72, 202). rpoN mutants also do not produce the proteinacious
flagellin subunit or form flagella (202). Several studies have shown that P.
aeruginosa strains lacking flagella are severely attenuated (46, 52, 144).
P. aeruginosa rpoN mutants are also less virulent than wild type strains in
multiple infection models. An rpoN mutant strain showed diminished cytotoxicity to
Madin-Darby canine kidney (MDCK) cells (32) and reduced virulence in several
mouse models specifically developed to study P. aeruginosa pathogenicity; compared
to wild type, rpoN mutants cause lower mortality rates in infected mice (32, 72) and
36
reduced fecal carriage and recovery from GI tissues (166). In addition, no pathology
was observed following infection with an rpoN mutant in a murine corneal scratch
model (169). Cohn et al. (30) reported that rpoN mutants did not readily colonize
human tracheal epithelium xenografts implanted in mice, although the difference in
bacterial numbers was not statistically significant between the mutant and wild type
strains due to experimental limitations. In general, the defects associated with the
rpoN mutation were greater than with strains that were specifically pilin-negative,
indicating the existence of an additional, pili-independent mechanism through which
σN also contributes to virulence (28, 32, 166, 168).
Pseudomonas syringae. σN of P. syringae controls hrp gene expression and
influences virulence. Regulation occurs via a short regulatory cascade, wherein σN
and its enhancer-binding proteins HrpR and HrpS direct transcription of hrpL, the
product of which is the alternative sigma factor required for expression of the hrp and
avr genes (82; Fig. 1.2B). Xiao et al. (221) showed that while expression of hrpL and
HrpL-dependent genes requires hrpR and hrpS, constitutive expression of hrpL can
provide full expression of HrpL-dependent genes with or without hrpR and hrpS. In
addition, avrD, which is transcribed from a HrpL-dependent promoter, requires rpoN,
hrpL, and hrpS for its expression (188). Characterization of P. syringae pv.
maculicola rpoN mutants identified a more severe phenotype than hrpL mutants,
however (71). rpoN mutants were nonmotile, displayed nitrogen utilization defects,
and were unable to produce the phytotoxin coronatine, cause disease or HR, or induce
host defense mRNAs. Complementation of hrpL into this strain partially restored
some phenotypes, but did not restore coronatine production. Other studies have also
shown that σN is required for production of coronatine biosynthetic intermediates
(synthesized by the cfl/CMA and cmaABT gene products) as well as hrpL transcription
and HrpL-dependent gene expression (1, 70). Thus, σN regulates a range of virulence
37
factors in P. syringae, some via hrpL activation and others by HrpL-independent
mechanisms.
Vibrio species. σN plays a similar role in Vibrio species virulence as it does in
P. aeruginosa. V. cholerae rpoN mutants are completely nonmotile and lack flagella
(103). In a competitive infant mouse colonization trial, an rpoN mutant was 10-20
fold less able to colonize the intestine than wild type (103). This defect is not entirely
due to lack of flagella, because a flaA mutant, while inhibited in intestinal
colonization, was still superior in colonization relative to the rpoN mutant. Prouty et
al. (172) also demonstrated the involvement of σN in expression of several V. cholerae
flagellar structural genes. σN is required for flagellin production and motility in the
fish pathogen V. anguillarum, as well. A mutant lacking σN was also severely
impaired in its ability to infect fish immersed in contaminated water, but was not
virulence attenuated in an intraperitoneal injection model (159).
RpoN in other species. σN contributes to virulence in a number of Gram
negative pathogens. In addition to the examples provided above, the uropathogen
Proteus mirabilis is 1000-fold less virulent than the wild type when σN is inactivated,
but remains identical to wild type with respect to growth, glutamine synthesis, and
fimbriae production (227). σN does not share a common role among all pathogens,
however. For example, the plant pathogens, Pseudomonas syringae, Erwinia
carotovora, and Xanthomonas campestris all use type III secretion systems to cause
disease in host organisms, and σN has a substantial effect on virulence and hrp gene
expression in P. syringae and E. carotovora (24), but it is not required for expression
of hrp genes or for virulence in X. campestris (77). As with the low G-C bacterial
σN appears to be an alternative sigma factor that has evolved to regulate virulence
determinants in some species, but not in others.
B
,
38
CONCLUSIONS
Bacteria utilize alternative sigma factors to regulate a wide range of
physiological processes. In pathogenic bacteria, alternative sigma factors often affect
virulence. Virulence effects can be mediated either through direct virulence gene
regulation or indirectly, by regulating genes that increase fitness of the bacterium
during transmission and infection. Direct effects on virulence genes include σB
activation of the L. monocytogenes virulence genes inlA and prfA, and σS-dependent
expression of the S. Typhimurium spv genes. Indirect effects of sigma factors on
virulence may be more difficult to identify, but alternative sigma factors frequently
have roles in virulence by regulating virulence-associated genes that aid in a
bacterium’s survival during infection. For example, σE enhances survival of oxidative
stress and hence, aids in bacterial survival of the oxidative burst within macrophages.
The stress response sigma factors σB and σS contribute to survival of multiple stresses
(e.g., acid and osmotic stresses) important for bacterial survival of passage through a
host stomach and gastrointestinal tract. In addition, σB and σS contribute to
environmental survival, and thus transmission, of food borne pathogens in foods and
food processing environments. Another alternative sigma factor role that contributes
to environmental survival, and has virulence implications, is regulation of biofilm
formation, e.g., by σB in S. aureus and S. epidermidis.
Functional roles for alternative sigma factors can be clearly defined and highly
specific (e.g. sporulation sigma factors) or multi-functional. Some sigma factors
exclusively regulate virulence genes (for example, HrpL of Pseudomonas syringae).
Often, however, alternative sigma factor contributions to virulence can be a secondary
consequence of the factor’s primary role. For example, as σB is present and
contributes to stress resistance in the non-pathogens B. subtilis and Listeria innocua
(Raengpradub, S., unpublished data), which are both closely related to the pathogenic
39
L. monocytogenes, it is possible that virulence gene incorporation into the σB regulon
is a relatively recent evolutionary event. Likewise, as no evidence currently supports a
direct role for σS in E. coli virulence gene regulation, the inclusion of virulence genes
in the regulatory network of S. Typhimurium σS may have occurred after the species
divergence of S. Typhimurium and E. coli.
A comparison of homologous sigma factor functions among different bacterial
genera reveals that the roles of sigma factors vary greatly among bacterial species,
even for closely related species such as E. coli and S. Typhimurium. In some cases, as
with M. tuberculosis σF, distinct virulence-related phenotypes have been observed in
alternative sigma factor null mutants. For others, such as S. aureus σB, while
virulence genes are directly transcribed by the sigma factor, ∆sigB strains are not
severely virulence attenuated. Even more apparent are the different roles for σS. σS is
required for virulence in S. Typhimurium and yet does not demonstrate a pronounced
role in E. coli pathogenesis.
A common mechanism of virulence regulation by alternative sigma factors
involves coordinated networks of sigma factors along with other transcriptional
regulators. Alternative sigma factors may regulate not only individual genes involved
in virulence, but other sigma factors or transcriptional regulators that in turn regulate
virulence and virulence-associated genes (Fig. 1.2). For example, σB of L.
monocytogenes not only directly regulates bsh and inlA, but also contributes to
expression of PrfA, which is required for transcription of almost all of the currently
recognized L. monocytogenes virulence genes. σB of S. aureus also contributes to
expression of a virulence gene regulator, RNAIII. σN and HrpL of P. syringae present
a different type of regulatory network, in which one sigma factor controls expression
of another. HrpL also controls expression of the HrpR and HrpS two-component
40
system regulators. Regulatory networks can be very complex, as in the multiple sigma
factor interactions of M. tuberculosis.
Finally, to extrapolate bacterial pathogen research findings to ensure relevance
in human infection, the importance of identifying and applying suitable model systems
that accurately mimic interactions between pathogen and humans is essential. This
point is illustrated by the significant reduced traversal of the intestinal barrier by L.
monocytogenes in wild type versus (human) E-cadherin transgenic mice (119). In
addition, pathogens such as P. aeruginosa that can infect a multitude of different hosts
are likely to respond differently and to have different virulence requirements
depending on the host species. Significant efforts are still needed to identify or
develop appropriate model systems for exploration of virulence mechanisms important
in human infection.
ACKNOWLEDGEMENTS
This work was partially supported by National Institutes of Health award no.
RO1-AI052151-01A1 (to K.J.B.).
41
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CHAPTER TWO:
LISTERIA MONOCYTOGENES σB REGULATES STRESS RESPONSE AND
VIRULENCE FUNCTIONS*
ABSTRACT
While the stress responsive alternative sigma factor σB has been identified in
different species of Bacillus, Listeria, and Staphylococcus, the σB regulon has been
extensively characterized only in B. subtilis. We combined biocomputing and
microarray-based strategies to identify σB-dependent genes in the facultative
intracellular pathogen L. monocytogenes. Hidden Markov Model (HMM)-based
searches identified 170 candidate σB-dependent promoter sequences in the strain
EGDe genome sequence. These data were used to develop a specialized, 208-gene
microarray, which included 166 genes downstream of HMM predicted σB-dependent
promoters, as well as selected virulence and stress response genes. RNA for the
microarray experiments was isolated from both wild-type and ∆sigB null mutant L.
monocytogenes cells grown to stationary phase or exposed to osmotic stress (0.5 M
KCl). Microarray analyses identified a total of 55 genes with statistically significant
σB-dependent expression under the conditions used in these experiments, with at least
1.5-fold higher expression in the wild-type over the sigB mutant under either stress
condition (51 genes showed at least 2.0-fold higher expression in the wild-type). Of
the 55 genes exhibiting σB-dependent expression, 54 were preceded by a sequence
resembling the σB promoter consensus sequence. RACE-PCR was used to confirm the
* Kazmierczak, M. J., S. C. Mithoe, K. J. Boor, and M. Wiedmann. 2003. Listeria
monocytogenes σB regulates stress response and virulence functions. J. Bacteriol.
185:5722-5734.
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σB-dependent nature of a subset of 8 selected promoter regions. Notably, the σBdependent L. monocytogenes genes identified through this HMM/microarray strategy
included both stress response (e.g., gadB, ctc, and the glutathione reductase gene
lmo1433) as well as virulence genes (e.g., inlA, inlB, and bsh). Our data demonstrate
that, in addition to regulating expression of genes important for survival under
environmental stress conditions, σB also contributes to regulation of virulence gene
expression in L. monocytogenes. These findings strongly suggest that σB contributes
to L. monocytogenes gene expression during infection.
INTRODUCTION
In several low GC-content Gram positive bacteria, σB has been recognized as a
general stress responsive sigma factor. This alternative sigma factor contributes to the
ability of organisms such as Listeria monocytogenes, Bacillus subtilis and
Staphylococcus aureus to survive under environmental and energy stress conditions
(4, 10, 18, 19, 65). σB also contributes to biofilm formation in S. aureus and
Staphylococcus epidermidis (37, 55). Biofilm formation may further enhance survival
of these organisms under conditions of environmental stress. In L. monocytogenes, a
food-borne pathogen capable of causing mild to severe infections in humans, σB
confers stress resistance (e.g., under acid stress, osmotic stress) and contributes to
pathogenesis. To illustrate, a L. monocytogenes σB null mutant survives less well than
the wild-type parent at low pH (pH 2.5) and in a murine infection model (45, 67). σB
has been demonstrated to contribute to transcription of prfA, which encodes the central
virulence gene regulator PrfA in L. monocytogenes (45).
An increasing body of evidence suggests a broad role for σB-dependent genes
in virulence of Gram positive bacteria. For example, σB has been linked with
regulation of virulence gene expression in S. aureus (6, 12). Specifically, σB
contributes to transcriptional regulation of sar in S. aureus. The sar locus partially
74
controls expression of the agr locus; agr and sar are both global regulatory elements
that control the synthesis of a variety of extracellular and cell surface proteins
involved in the pathogenesis of S. aureus (12, 38). A total of 23 proteins showed
increased expression in the presence of σB in a 2-dimensional (2-D) gel comparison of
proteins isolated from both the wild-type S. aureus strain and its isogenic sigB null
mutant (27). σB also has been shown to contribute to virulence in Bacillus anthracis.
Specifically, a B. anthracis ∆sigB strain is less virulent than its wild type parent (21).
Links between environmental stress responses and virulence in these bacteria suggest
a central role for σB in contributing to the ability of bacterial pathogens to survive
environmental stress conditions, to direct expression of virulence genes, and to cause
disease.
Identification of genes regulated by σB is the first step in deciphering specific
mechanisms through which this alternative sigma factor confers resistance to multiple
environmental stresses and contributes to virulence. Previous efforts at defining the
σB regulon have focused primarily on B. subtilis, a Gram positive, non-pathogenic
model organism. Through a combination of in vitro transcription, reporter fusion
transposon mutagenesis, 2-D protein gel electrophoresis, and RNA hybridizations
(reviewed in 52), a total of 75 genes and proteins with σB-dependent expression
patterns were identified in B. subtilis. Recently, full genome macroarray analyses
enabled two research groups to independently define over 120 B. subtilis genes that
showed σB-dependent expression profiles by comparing gene expression patterns of
wild-type strains with those of isogenic sigB null mutants (51, 53). In addition, use of
a full genome B. subtilis array allowed Helmann et al. (30) to identify 44 heat shockinduced genes preceded by previously unidentified potential σB-dependent promoters.
These transcriptome studies of the B. subtilis stress response illustrate the power of
genome-wide, array-based expression studies.
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The σB regulon in B. subtilis, as determined by Price et al. (53) and Petersohn
et al. (51), includes genes with a wide variety of functions. Approximately one
quarter of the B. subtilis σB-dependent genes encode proteins involved in metabolic
functions, including glucose metabolism, protein degradation, and lipid metabolism.
In addition, many genes regulated by σB in B. subtilis encode transporters, e.g., solute
transporters, permeases, and ATP-binding cassette (ABC) transport systems. The
broad range of gene functions associated with the σB regulon in B. subtilis suggests
that, in addition to enhancement of fundamental cellular processes, σB-mediated stress
resistance mechanisms are also responsible for targeted action against specific
stresses.
To better understand the role of σB in stress resistance and virulence in L.
monocytogenes, we combined promoter searches and DNA microarrays to identify
genes directly activated by σB from experimentally defined or predicted σB-dependent
promoter sequences. As some B. subtilis genes have shown apparent σB-dependent
induction in the absence of well-conserved σB-dependent promoter sequences, some
σB-mediated effects also may occur through indirect regulatory mechanisms (e.g.,
possibly through σB-dependent expression of additional transcriptional regulators; 51).
For the purposes of this study, we chose to focus specifically on defining L.
monocytogenes genes that are transcribed from σB-dependent promoters. To that end,
we first performed a Hidden Markov Model (HMM) similarity search for putative σBdependent promoters against the published complete L. monocytogenes genome
sequence (28). To allow a focused analysis of σB-dependent gene expression, a
microarray was constructed using the genes identified by the HMM search. To more
fully explore the role of σB in L. monocytogenes stress response and virulence, our
microarray also included previously identified stress response and virulence genes that
were not necessarily identified by HMM. To be classified as “under direct σB
76
control,” genes had to meet the following two independent criteria: (i) significantly
higher expression in the wild-type strain as compared to that in the sigB null mutant
under the conditions used for the microarray experiments; and (ii) the presence of an
identifiable σB-dependent promoter-like sequence upstream of the coding region.
Based on these criteria, we identified 54 genes under direct σB control. Although we
refer to these genes as “σB-dependent“, it is important to recognize that the genes
identified with this approach may not be exclusively σB-dependent, but also may be
regulated by σB-independent mechanisms. Interestingly, while the genes we found to
be under control of σB include many that had been identified previously as part of the
B. subtilis σB regulon, several virulence and virulence-related genes were also
identified (e.g., a gene encoding a bile salt hydrolase and genes encoding surface
molecules with possible or confirmed roles in host cell attachment). Our data provide
further evidence in support of σB’s contributions to L. monocytogenes stress resistance.
Importantly, identification of multiple σB-regulated virulence genes strongly suggests
that this alternative sigma factor also contributes to the ability of L. monocytogenes to
infect and survive within a host.
MATERIALS AND METHODS
Bacterial strains and media. The L. monocytogenes strain 10403S (7) and
the isogenic sigB null mutant (∆sigB) FSL A1-254 (67) were used throughout this
study. Cells were grown in brain heart infusion broth (BHI; Difco, Detroit, MI) at
37ºC with shaking unless indicated otherwise.
Hidden Markov model (HMM) searches. HMM searches were performed
using HMMER (http://hmmer.wustl.edu) essentially as described by Price et al. (53).
The training alignments included 29 B. subtilis σB dependent promoters (described in
53) as well as four confirmed (prfA, rsbV, opuCA) or likely (betL) L. monocytogenes
σB-dependent promoter sequences. The models were searched against the complete L.
77
monocytogenes strain EGD-e genome sequence (28). The output results were filtered
and only hits within 350 bp upstream of a coding region, as predicted by the ListiList
web server (http://genolist.pasteur.fr/ListiList; 44), and with an e-value of ≤ 0.006
were kept.
DNA and RNA isolation and treatment. RNA was extracted from L.
monocytogenes grown either to stationary phase or exposed to osmotic stress (as
described below) using the RNeasy Protect Bacteria Midi Kit (Qiagen, Valencia, CA).
The enzymatic and mechanical disruption protocol provided by the manufacturer was
used, with the exception that cell lysis was performed using sonication at 21W for 3 x
20 seconds (with cells iced between bursts) instead of bead-beating. RNA was eluted
from the column in RNase-free water and ethanol precipitated overnight at –20°C.
Precipitated RNA was centrifuged, washed in 70% ethanol, and resuspended in
RNase-free water. DNase treatment was performed with 30 U RQ1 RNase-free
DNase (Promega, Madison, WI) in the presence of 400 U RNase inhibitor (RNasin;
Promega) for 1 hour at 37ºC. The reaction was then extracted twice with an equal
volume of 50% phenol/50% chloroform, followed by one extraction with an equal
volume of 100% chloroform. RNA was ethanol precipitated from the aqueous layer
and stored at –20°C in ethanol.
Cultures for RNA isolation were inoculated from single colonies and grown
overnight at 37°C. The cultures were then diluted 1:200 in BHI and grown at 37°C to
specified growth phases. Specifically, for harvest of stationary phase cells, L.
monocytogenes was grown for one additional hour after reaching an OD600=0.8. At
OD600=0.8 + 1 hour, a 9 ml aliquot of culture was added to 18 ml RNA Protect
Bacteria Reagent (Qiagen) and RNA isolation was performed as described above. For
osmotic stress treatment, cells present in 40 ml of a culture grown to OD600 = 0.4 were
collected by centrifugation and resuspended in 8.25 ml prewarmed (37°C) BHI broth,
78
to which 1.25 ml 4M KCl was added to yield a final concentration of 0.5 M KCl.
After 7 minutes of incubation at 37°C, corresponding to the approximate peak of σBinduced transcriptional response reported in induction experiments in B. subtilis (64),
20 ml RNA Protect Bacteria Reagent was added and RNA isolation was performed as
described above.
Chromosomal DNA used for genomic DNA microarray control spots was
isolated as described by Flamm et al. (20) from an overnight culture of L.
monocytogenes. Briefly, cell walls were digested with lysozyme in 20% sucrose,
followed by cell lysis with SDS and proteinase K. DNA was purified with
phenol/chloroform extractions and ethanol precipitated. DNA was then resuspended in
spotting buffer (3X SSC + 0.1% sarkosyl) and quantified using UV-spectroscopy.
Microarray construction. DNA microarrays were constructed to include 208
L. monocytogenes genes spotted in triplicate, 30 mouse β-actin cDNA spots for nonhybridizing controls, and 60 spots of genomic DNA to aid in data normalization and
analysis. The 208 L. monocytogenes genes included 166 of the 170 genes identified
by HMM searches as including an upstream predicted σB-dependent promoter (PCR
amplification failed for 4 genes) as well as 36 genes previously reported to be
involved in virulence or stress response and 6 negative control genes (i.e.,
housekeeping genes predicted not to show σB-dependent expression). All 208 target
genes as well as the PCR primers used for their amplification are detailed in the
supplemental material available at
http://www.foodscience.cornell.edu/wiedmann/Mark%20supplemental%20table%20(4
-15).doc. PCR primers were designed with PrimeArray software (56) to amplify the
complete open reading frames of the selected genes. For ORF’s > 1 kb, primers were
selected to amplify a 1 kb fragment at the 5’ end of each ORF. PCR was performed
with AmpliTaq Gold (Applied Biosystems, Foster City, CA) using a L.
79
monocytogenes 10403S cell lysate (prepared as described in (24) as template DNA.
Appropriately sized products free of non-specific amplification or extraneous bands,
as determined by agarose gel electrophoresis, were purified by ethanol precipitation
and reconstituted in spotting buffer (3X SSC + 0.1% sarkosyl) to a final concentration
of 50-150 ng/µl. PCR was also used to generate a 1 kb PCR fragment of the mouse βactin gene using mouse β-actin cDNA (Sigma, St. Louis, MO) as template.
Arrays were spotted with a GMS 417 robotic arrayer (Affymetrix, Santa Clara, CA) on
GAPS2 glass slides (Corning, Corning, NY). Immediately before use, slides were
blocked in a solution of 1-Methyl-2-Pyrrolidinone containing 1.44% succinic
anhydride and 0.02 M Boric acid pH 8.0, as directed by slide manufacturer.
cDNA labeling and microarray hybridization. Precipitated, DNase-treated
RNA was centrifuged, washed once in 70% ethanol, once in 100% ethanol, and
resuspended in RNase-free water. The RNA was quantified on a UVspectrophotometer and checked for quality by A260/280 ratio and formaldehyde-agarose
gel electrophoresis. cDNA was generated from 10 µg RNA using random hexamers
and SuperScript II (Invitrogen, Carlsbad, CA) in the presence of Cy3-dUTP or Cy5dUTP (Amersham Biosciences, Piscataway, NJ). cDNA synthesis and labeling were
performed using a “dye swapping” design (sometimes referred to as reverse labeling;
62); each RNA sample was used for two separate labeling reactions, one using Cy3
and one using Cy5. Completed reactions were incubated with 1.5 µl 1N NaOH at
65ºC for 10 minutes to inactivate the enzyme and degrade the RNA. Reactions were
then neutralized with 1.5 µl 1N HCl. Wild-type and sigB mutant cDNA probes were
mixed and purified using the QIAquick PCR purification kit (Qiagen) as described by
the manufacturer with the addition of a 750 µl 35% Guanidine-HCl wash after
binding. The purified probes were then dried and reconstituted in 20 µl hybridization
buffer (3.5X SSC, 0.25% SDS, and 0.5 µg/µl salmon sperm DNA; Invitrogen). Probes
80
were boiled 2 minutes, applied to arrays, and hybridized overnight in a 60ºC water
bath. Before scanning, slides were washed in 2X SSC+0.1% SDS at 60°C for 5
minutes, followed by room temperature washes of 2X SSC+0.1% SDS, 2X SSC, and
0.2X SSC, for 5 minutes each. Slides were centrifuged to dry and scanned with a
Perkin Elmer Scan Array 5000 confocal laser scanner (Perkin Elmer, Wellesley, MA).
Microarray replicates and data analysis. For each stress condition described
above (osmotic stress or stationary phase), two independent RNA isolations (for both
wild-type and ∆sigB cells) were performed on separate days to provide true biological
replicates. Each set of independent RNA samples was used to perform two microarray
hybridizations using a “dye-swapping” design to correct for differences in Cy3/Cy5
dye incorporation and to provide experimental duplicates. Briefly, both wild-type and
∆sigB RNA from each of the two independent RNA isolations were labeled separately
with either Cy5 or Cy3 as described above. Labeled cDNA was used to perform two
independent microarray hybridizations, one with Cy3-labeled wild-type and Cy5labeled mutant cDNA and one with Cy5-labeled wild-type and Cy3-labeled mutant
cDNA. Thus, data for four microarray repetitions were collected for each stress
condition.
Raw TIFF images from the scanner were loaded into ScanAlyze
(http://rana.lbl.gov/EisenSoftware.htm) for analysis. Spot grids were manually fitted
to the microarray images. Spots were flagged and eliminated from analysis only in
obvious instances of high background or stray fluorescent signals.
Because our microarray contained a relatively small number of genes, most of which
were expected to show differential expression, proper normalization of the raw data
was critical. Equalizing the mean intensities of both channels of an array, the most
common method used for microarray normalization, would thus have provided
severely skewed data on an array with the majority of spots appearing to be unequally
81
expressed. Therefore, we normalized our data using the mean intensities of spots
containing genomic DNA. Data normalization was performed simultaneously on all
four array data sets for a given stress condition, as follows. For each channel (Cy3 or
Cy5), the mean intensity of all genomic DNA control spots was calculated
independently. A correlation factor comparing genomic means among channels was
calculated, and used to proportionally adjust all spot intensities (experimental and
control) so that the means of genomic spot intensities were equal across all arrays.
From these normalized values, a floor was calculated as the average intensity plus two
standard deviations of all β-actin spots in a channel. Spots with values below the floor
in both channels were eliminated from analysis; spots below the floor in only one
channel had that channel intensity raised to the floor value and the resulting data were
included in the analyses (16).
Floored and normalized channel intensities were analyzed using the
Significance Analysis for Microarrays (SAM) program (63). This statistical analysis
involves factoring the fold change of each gene relative to the standard deviation of all
replicates for that gene. Therefore, genes with a low fold change will not be
discounted if the ratios are consistent among repeats, effectively reducing false
negatives. False positives are also avoided when genes have poor reproducibility
between replicates. This method of statistical analysis maximizes both the quantity of
genes found and the reliability of the results. Spot intensities for all channels were
input in SAM as paired, unlogged values. All individual spots were considered
repetitions, generating 24 data points for each gene (3 spots per gene x 4 arrays x 2
channels per array). Delta values were chosen according to the lowest false discovery
rate. Only genes with expression ratios of >1.5 were considered biologically
significant.
82
RACE-PCR. Promoter regions were mapped using the 5’ RACE System
(Invitrogen) according to the manufacturer’s protocol. Briefly, gene specific first
strand cDNA was tailed with dCTP using terminal transferase. The products were
then amplified using a nested gene-specific primer and a poly-(G/I) primer in a
touchdown PCR reaction with AmpliTaq Gold (Applied Biosystems). PCR products
present in the wild-type L. monocytogenes, but absent in the ∆sigB strain, were
purified using the Qiagen QIAquick PCR purification kit and sequenced using the Big
Dye Terminator system and an Applied Biosystems 3700 sequencer at the Cornell
University Bioresource Center.
RESULTS
HMM search to identify potential σB promoters. A HMM developed with
29 B. subtilis and four L. monocytogenes σB-dependent promoter sequences was used
to search the L. monocytogenes EGD-e genome (28) to identify genes preceded by a
σB consensus promoter and thus potentially regulated by σB. A total of 170 genes met
the following criteria for putative σB-dependent genes: (i) location of a predicted σB
consensus promoter sequence within 350 bp upstream of a predicted open reading
frame and (ii) an e-value of ≤ 0.006. The presence of a sequence adequately fitting
the promoter consensus was confirmed visually at positions indicated by the HMM.
The results of this search were used to create a 208-gene microarray to specifically
study the σB-mediated stress response in L. monocytogenes. The array consisted of
166 of the 170 HMM-identified genes (PCR amplification failed for 4 genes), 36
genes involved in stress response or virulence, and 6 control genes.
Transcriptional analysis of potential σB-dependent genes. Microarray analyses
were performed using RNA isolated from wild-type L. monocytogenes and an isogenic
∆sigB strain grown to stationary phase or exposed to osmotic stress, two conditions
shown to activate σB (4, 19, 22). We identified 55 genes that showed significant
83
expression ratios, with >1.5-fold expression in the wild-type strain over that in the
mutant strain in at least one of the two stress conditions tested (Table 2.1). Fifty-one
of these genes displayed >2-fold induction; the highest relative induction was 27-fold.
Figure 2.1 shows scatter plots of wild-type vs. sigB mutant spot intensities. As the
microarray was predominantly comprised of genes predicted to be positively regulated
by σB, the distribution of the majority of the points above the diagonal, which
indicates that a large proportion of the genes in the microarray were expressed more
strongly in the wild-type than in the mutant, was expected. As the presence of points
falling far below the diagonal would signify increased gene expression in the absence
of σB, none to few were expected. For the purpose of this study and in accordance
with previous studies (31), we applied a cutoff of 1.5-fold induction to signify
biological significance. Two genes included in the microarray fell below this cutoff
(showing statistically significant expression ratios between 1.2- and 1.5-fold) and are
not further discussed here. As shown in Figure 2.1, a few genes showed higher
expression in the ∆sigB mutant as compared to the wild-type strain;
expression differences between strains for these genes were determined to be not
statistically significant.
Overall, 44 of the 169 genes (26%) in our microarray that were either (i)
predicted to be σB-dependent by HMM or (ii) members of operons previously
identified as being regulated by a σB-dependent promoter also showed σB-dependent
expression in our microarray experiments. There was no apparent correlation between
a promoter’s HMM e-value and the relative expression level of a corresponding gene
as determined by microarray (r2< 0.01 for correlations between HMM e-values and
relative expression levels under either osmotic stress or stationary phase conditions).
In addition, 11 of the 36 currently recognized stress response and virulence genes that
were included in the array even though they did not show an HMM predicted σB-
84
Table 2.1: L. monocytogenes genes with significantly higher expression in wildtype as compared to ∆sigB strain under osmotic and stationary phase stresses
Fold
Changea
a
Number of genes with statistically significant higher expression under:
Stationary
phase
Osmotic stress
(0.5 M KCl)
Stationary phase
and osmotic stress
Stationary phase
or osmotic stress
≥ 1.5
41
51
37
55
≥ 2.0
37
44
30
51
Fold change was calculated using SAM based on microarray data (see “Materials
and Methods”), and equals the average wild-type spot intensity divided by the
average mutant spot intensity for two separate arrays from each of two replicate
RNA isolations.
85
100000
Wild-type spot intensity
A.
10000
1000
1000
10000
100000
∆ sigB spot intensity
100000
Wild-type spot intensity
B.
10000
1000
1000
10000
100000
∆ sigB spot intensity
Figure 2.1: Scatter plots of normalized microarray spot intensities for wild-type
and sigB mutant strains.
A. RNA for microarray experiments was isolated from stationary phase cells.
B. RNA for microarray experiments was isolated from osmotically stressed cells.
86
dependent consensus promoter displayed σB-dependent expression patterns.
Subsequent visual inspection of the upstream regions for these 11 genes identified
putative σB consensus promoter sequences for 10 of them (see Table 2.2). Although
inlD showed σB-dependent expression in our microarray experiments, no putative σB
consensus promoter sequence was identified for this gene.
Overall, we identified 54 σB-dependent L. monocytogenes genes through
combined application of HMM and microarray analyses. Based on identification of
the predicted proteins, the genes were grouped into ten functional groups (Table 2.2).
The two most highly represented categories were transport and metabolism proteins,
which together comprised 20 of the 54 genes (Table 2.2, III-IV). Statistical analysis of
microarray data (SAM; 63) showed that, in addition to showing high expression ratios,
the putative oxidoreductase gene, lmo0669, also had the highest significance score for
differential expression of all genes represented in the microarray (Table 2.2). The
known σB-dependent betaine/carnitine transporter operon opuC also showed σBdependent expression, along with 8 other solute transport genes. The large proportion
of metabolism and transport genes regulated by σB underscores the importance of
maintaining proper cellular functions during exposure to stress conditions and
suggests that σB provides protection by enhancing operation of a specialized subset of
basic cellular processes, which may help to produce a more stress resistant state for the
cell.
Two other notable functional categories of σB-dependent genes are stress
response and virulence genes (Table 2.2, I-II). The stress response genes, which have
apparent functions in bacterial stress resistance, but do not encode transporters or
proteins from other recognized categories included in Table 2.2, represented some of
the most highly differentially expressed genes. For example, in the SAM output,
87
Table 2.2: Summary of genes with σB-dependent expression patterns as
identified by microarray analyses
B. subtilis
homologueb
Gene
Function or closest homologue (e-value)
Fold
changec
Predicted σB promoter sequencea
ST
OS
I. Stress
lmo2230 arsenate reductase [Staphylococcus aureus] (1e-08)
gadB
GadB glutamate decarboxylase (Lmo2434)
sepA
metallo-beta-lactamase superfamily protein [Shewanella oneidensis] (e-173)
ltrC
low temperature requirement C protein
lmo1433 glutathione reductase (NADPH) [Methanosarcina acetivorans] (4e-91)
ctc
B. subtilis general stress protein Ctc (1e-27)
lmo1602 general stress protein [Oceanobacillus iheyensis] (6e-11)
TTTAATGTTTCTAGTAATTTAAAAAGGGTAGATATTACTGT-N108- arsC (7e-10)
ATG
TGAACGGTTTGTCTCTGTGGTTTAATGGGTATTGGTGAGAGA-N32ATG
CAAAAGGTTTTGAATAATTTTATGGAGGTATAAAAAGAAAGTN33-ATG
CCGTCCGTTTTTAGTTCGTGATGGCGGGGACTATGAACTTAT-N260- yutG (1e-53)‡
ATG†
TTTTTCGTTTGAAAGTGAAATCAGACGGGAAAACAAGCTAAGN14-GTG
TCCTTTGTTTTGCTATTTTTCTAAAGGGTAGATATAATGTA-N35- ctc (1e-33)‡
ATG
AAGAAAGTTTTAGAGGGGAATACTCAGGGTATAGAAAAAGGA- ytxG (6e-13)‡
N18-ATG
27.0 21.9
5.3
4.9
12.0 13.4
4.8
1.9
6.8
5.7
1.5
2.2
2.7
2.1
II. Virulence and Virulence-Associated
bsh
Bsh bile salt hydrolase (Lmo2067)
inlA
Internalin A
inlB
Internalin B
inlC2
Internalin C2
inlD
Internalin D
inlE
Internalin E
AATTATGTTTTACTCCAAACTCCGAGGGTACTGGTATACAT-N31ATG
CCATTAGTGTTATTTTGAACATAAAGGGTAGAGGATAACAT-N437GTG†
CCTTTTGTTAGGGTTATTAGCAGTAGGAACTGCAATGGCTC-N113GTG†
TTTTTTGTTAATTTGGTCTAAAAAAGGGTATCTATTATTAA-N55ATG†
none found
TAAATCGTTAACAAGTCTAATTTTAGTGATTAAACGAAATC-N84ATG†
10.8 20.1
6.2
3.9
4.6
2.1
11.4 7.3
3.3
2.3
3.7
2.4
88
97
Table 2.2 (Continued)
III. Transporters
opuC Operon
opuCA glycine betaine/carnitine/choline ABC transporter (ATP-binding protein)
TAAAAAGTTTAAATCTATACTAGTTAGGGAAATTAGTTATCG-N48GTG
opuCA (e-159) 5.3
6.5
opuCB glycine betaine/carnitine/choline ABC transporter (membrane protein)
opuCB (1e-74) 3.8
4.7
opuCC glycine betaine/carnitine/choline ABC transporter (osmoprotectant-binding)
opuCC (1e-92) 4.1
5.2
opuCD betaine/carnitine/choline ABC transporter (membrane protein)
opuCD (5e-66) 5.0
5.8
lmo0784 PTS enzyme IIAB, mannose-specific [Yersinia pestis KIM] (5e-34)
lmo2602 cation-transporting ATPase [Oceanobacillus iheyensis] (2e-12)
lmo0405 PHO4, Phosphate transporter family [Bacillus anthracis] (4e-76)
lmo2463 probable export protein (antibiotic) [Streptomyces coelicolor] (6e-80)
lmo1539 glycerol uptake facilitator [Bacillus halodurans] (8e-66)
lmo1421 ABC transporter [Bacillus anthracis A2012] (8e-98)
lmo0524 sulfate transporter [Mycobacterium tuberculosis CDC1551] (2e-50)
lmo0593 formate/nitrite transporter family protein [Streptococcus agalactiae] (7e-37)
AATTGCGTTTTCTGACTAATCTTTTAGGGTAATGTTGTATGT-N195- levD (1e-21)
ATG
TTGATTGTTTTGGTTTAATGCCAAAGGGAATATATTAACGT-N16- sapB (1e-09)
ATG
GATTCTTTTTATATTTGTATAAAAGGGGTATAGACAATAAA-N30ATG
AATGATGTTTGGCATATGTAAAAAAGAGGTATAAATTAGCGTG ydfJ (4e-30)
7.5
5.0
5.5
3.8
3.9
4.9
3.0
5.2
AAATGGGTTATAACTCTCGCGAATTGGGGTAAAAGTAAAGAG- glpF (5e-81)
N254-ATG
AATTAGGAATATTTAGGGATGATTTAGGGTAATTGGATGATA-N74ATG†
AGAGATGATTGTTCTATGTCAAAACGGGTAAATAGTATAAG-N65ATG
TTTTGTGTTTTAAGAGTTTGAAAACGGGGAAATTAACAACATywcJ (1e-18)
N146-TTG
2.4
2.3
2.5
2.1
2.0
2.9
2.9
2.3
IV. Metabolism
lmo0669 oxidoreductase [Oceanobacillus iheyensis] (3e-86)
lmo1694 Epimerase, NAD dependent family [Bacillus anthracis] (2e-62)
lmo1883 chitinase [Serratia marcescens] (e-117)
lmo2695 dihydroxyacetone kinase [Bacillus halodurans] (e-103)
lmo0956 N-acetylglucosamine-6-phosphate deacetylase [Bacillus anthracis] (e-110)
lmo2205 phosphoglycerate mutase [Neisseria meningitidis] (4e-86)
14.2 9.5
11.5 11.7
4.1
2.1
2.8
4.3
1.8
1.4
1.8
3.2
89
yhxD (3e-95)‡
TTAAACGTTTTAGCGTAAAACAGGAGGGAAGACATAAAGTAN139-ATG
AAAATGGTTTTAATACTACTAAAAAGGGAATAAACTAGTTA-N22- yfhF (5e-59)‡
TTG
TTTCTAGTTTTATTTTCACTATGTTGGGTATTTTCTAGTAG-N47ATG
AACCACGTTTTGACTTTCTAGTAAAGGGAAATTGAGGTAAG-N30ATG
TTTTTTGGTTATTTTACTTTTTTTCGGGTAAATAGGAAAAG-N71- nagA (1e-72)
ATG
AAAAAGGTTTGACACTTCACTTGAAAGGGAAAACTTTGGTTGN44-ATG
98
Table 2.2 (Continued)
pdhA
pyruvate dehydrogenase (E1 alpha subunit) [Bacillus subtilis] (e-151)
lmo1933 GTP cyclohydrolase I [Bacillus halodurans] (6e-67)
V. Transcriptional Regulation
rsbV Operon
ACCCATGTTTTCAATGAGGAATTTGTGGTAATAACTGGAGAGpdhA (e-162)
N231-ATG
TTAGTGGTTTTCTGTTTTAGAAATAGGGAATATAATTACGA-N113- mtrA (7e-73)‡
ATG
TTGAATGTTTTAATTTTATTTGTTAGGGTAAAATCGACAGT-N27ATG†
1.7
1.6
2.0
2.0
rsbV (3e-24)‡
2.1
2.0
rsbV
anti-anti-sigma factor (antagonist of RsbW)
rsbW
sigma-B activity negative regulator RsbW
rsbW (3e-42)‡
2.0
2.4
sigB
RNA polymerase sigma-37 factor (sigma-B)
sigB (7e-97)‡
2.2
2.3
‡
2.0
2.2
GCAAAAGTAGGAAATGGAATTATCAAGGTTTCTGAACTCGA-N42ATG
1.8
3.9
CTGGCTGTTTTCTTTTGCTGTTTTATGGGTATTTAATGATGT-N28ATG
TGTACGGTTTTTAACAAGCAAGTTGTGGGAACTATAAAGATAN26-ATG
14.7 10.7
rsbX
Indirect negative regulation of sigma B (serine phosphatase)
lmo2485 transcriptional regulator [Methanosarcina mazei Goe1] (1e-04)
rsbX (1e-26)
VI. Cell Wall Proteins
lmo2085 surface anchored protein (LPXTG motif) [Listeria innocua] (1e-18)
lmo0880 surface anchored protein (LPXTG motif) [Listeria innocua] (1e-26)
5.2
2.1
1.5
1.9
1.6
3.4
3.1
1.9
3.8
1.9
VII. Energy
qoxA
AA3-600 quinol oxidase subunit II
lmo2389 Pyridine nucleotide-disulphide oxidoreductase [Bacillus anthracis] (e-123)
TTTTTTGTTTCGAATTTCACAATCTAGGGAATAGTGAACAGA-N265- qoxA (3e-91)
GTG
GATATAGTTTGTAAGCTGTGAAATAGGGAATATATTGGTAC-N127- yumB (e-128)‡
ATG
VIII. Translation
90
lmo1698 ribosomal-protein (S5)-alanine N-acetyltransferase[Bacillus halodurans] (3e-42)TGGAAAGTTTATTTTTTAATAAAATGGGTATATAGAAAAAT-N72- yjcK (3e-55)
ATG
lmo2511 Ribosomal_S30, Sigma 54 modulation protein [Bacillus anthracis] (2e-53)
AAAGAGGTTTGCGGAAGCGGTATTAGTGGAATAAAATACTAA- yvyD (e-162)‡
N135-ATG
99
Table 2.2 (Continued)
IX. DNA Translocase
lmo1606 DNA translocase (spoIIIE) [Bacillus halodurans] (e-168)
TACCATGTTTAACCCCTCTATTACCAAGGTATTATAACGAAT-N97- ytpT (0.0)
ATG
2.4
2.6
CAACAGGTGTTCTAGAATATTTACGGGAACAAAAAGTCGA-N234- yvaZ (5e-09)
ATG
TTTTAAGATTGTAATAAATATGAGTGAAGGAGTGGTAGTCGTG
5.3
5.9
4.0
5.3
2.2
1.9
5.2
5.8
2.0
2.7
3.7
6.9
1.8
2.4
2.0
2.5
2.7
3.4
6.1
6.5
X. Hypothetical
lmo2570 hypothetical protein yvaZ - Bacillus subtilis (.023)
lmo2269 YhzC of Listria monocytogenes (9e-26)
lmo0911 BH2119~unknown [Bacillus halodurans] (1e-06)
lmo0794 conserved hypothetical protein ywnB - Bacillus subtilis (2e-50)
lmo1580 conserved hypothetical - ATP binding domain [Bacillus anthracis] (2e-40)
lmo2673 conserved hypothetical - ATP binding domain [Bacillus anthracis] (4e-28)
lmo2386 conserved hypothetical protein yuiD - Bacillus subtilis (1e-37)
lmo2399 hemolysin homolog yhdP - Bacillus subtilis (2e-89)
lmo0438 No similarity
lmo0994 No similarity
CATCTTGTTTTAACTTGCCCTCAGGCGGGTATTTATTATATG-N53ATG
ATAAATGTTTCCCAGTCCCCTCTTTCGGGAATAATTCTTCTA-N45- ywnB (5e-54)
ATG
TTTTATGGTTCTTTTAGGAAAAAGAGGGTAAAATATAAGTA-N35- yxiE (4e-11)
ATG
AATCATGCTTCTTTCTTTTATTTATGGGTATTAAGTAAATA-N30ATG
yuiD (1e-50)
GAATAGGTTTTTAATAAGCTCATTGTGGTAAAATAAGAATAGN22-ATG
CTTGTGGTTTAAACGCTAAGAACGGGTATAGAATGGGGA-N15ATG
ACTAACGAATCGCGTGGATGCGCTTCGGGAATTGTTGAAATAN157-GTG
GAAAGAGGTTATTTTTCACTAAATGGGGTAAAAATACGTTA-N257ATG
a
The promoter sequence as predicted by the HMM, genes without a HMM predicted promoter sequence are marked with †.
b
The closest homologue in the B. subtilis genome, along with the e-value in parentheses. Homologues that have been
determined to be σB-dependent in B. subtilis (51,53) are marked with ‡.
c
Fold change numbers in italics are not significantly different from a ratio of 1.0. ST, stationary phase; OS, osmotic stress.
91
98
92
which ranks differentially expressed genes based on the statistical significance
associated with the expression ratios, 4 of the 7 stress response genes ranked among
the 16 genes with the highest significance values for differential expression, using
RNA isolated from cells exposed to osmotic stress. The identified stress response
genes include gadB, which was ranked as the 3rd or 5th most significantly differentially
expressed gene in cells grown to stationary phase or exposed to osmotic stress,
respectively.
Three confirmed virulence genes were expressed at a higher level in the wildtype L. monocytogenes strain as compared to the ∆sigB mutant (Table 2.2). bsh
exhibited 20.1-fold higher mRNA levels in the wild-type as compared to the ∆sigB
strain under osmotic stress (Table 2.2); this expression ratio was determined to be
highly significant by SAM analysis (ranked as the 2nd most significant ratio for all the
genes in the array). The virulence genes inlA and inlB showed significantly higher
expression under osmotic and/or stationary phase stress in the wild-type as compared
to the mutant strain, with expression ratios consistently >2.0 (Table 2.2). In addition
to these confirmed virulence genes, three other internalins (inlC2, inlD, and inlE) also
showed significant expression ratios >2.0 under osmotic and/or stationary phase stress
(Table 2.2). PCR mapping showed that the L. monocytogenes strain used in our study
(10403S) bears an inlC2DE operon rather than an inlGHE operon, which is present in
the L. monocytogenes EGD-e strain (57). Each ORF of the inlC2DE gene cluster is
potentially transcribed independently from the others (13). We identified a σB
promoter consensus sequence upstream of each of inlC2 and inlE, but not upstream of
inlD. Only one previously described internalin (inlC) that was included in our array
and is present in strain 10403S did not show differential expression between the wildtype and the ∆sigB mutant strain.
93
Microarray identification of operons and known σB-dependent genes. For
putative σB-regulated genes that were identified only by HMM, only PCR products
from the genes most proximal to given HMM-predicted promoters were spotted on the
microarray. Therefore, downstream genes that may have been co-transcribed from a
given promoter were not tested for σB-dependence in this array. However, the
microarray did include genes comprising two operons (opuC and rsbV ) that were
known a priori to be σB-dependent (4, 22). All genes in these two operons were
expressed at significantly higher levels in the wild-type as compared to the ∆sigB
strain. Furthermore, expression ratios for each gene within these operons were
approximately equal (Fig. 2.2A-B). The inlAB operon was not previously known to be
regulated by σB, but inlA and inlB were among the virulence genes included on the
microarray. We found that both genes in this operon were expressed at higher levels
in the presence of σB, and that both inlA and inlB displayed similar expression ratios
(Fig. 2.2C).
Confirmation of predicted σB-dependent promoters by RACE-PCR. To
confirm that predicted σB-dependent promoters were in fact responsible for the
differential gene expression seen in the microarrays, we performed Rapid
Amplification of cDNA Ends (RACE)-PCR on eight selected genes. These genes
were chosen to represent highly differentially expressed genes and genes with high
significance scores in SAM, as well as known stress response or virulence genes.
Gene specific first strand cDNA was generated for each gene, and a 3’ poly(dC) tail
was added to each cDNA product using terminal transferase. The tailed cDNA
product was amplified by touchdown PCR with a poly(G/I) primer (Invitrogen) and a
nested gene specific primer. PCR bands from wild-type cDNA reactions that met the
following conditions were purified and sequenced (Fig. 2.3): (i) bands must have been
generated by reactions with wild-type cDNA; and (ii) equivalent bands must have
94
σ
A
B
σ
B
B
2.1
2.0
rsbV
rsbW
5.3
opuCA
C
σ
B
2.2
sigB
2.0
rsbX
3.8
4.1
5.0
opuCB
opuCC
opuCD
6.2
B
σ (?)
inlA
4.6
inlB
Figure 2.2: Graphical depiction of three operons represented on the microarray.
Numbers above genes indicate wild-type-to-mutant expression ratios in stationary
phase cells.
95
lmo2230
A.
1
B.
2
3
4 5
gadB
1
2
3
4
5
Poly(dC)-tail
Figure 2.3: Determination of σB-dependent transcriptional start sites by RACEPCR.
A. For each gel, lanes 1-5 represent the size marker, wild type negative control, wild
type positive reaction, ∆sigB positive reaction, and ∆sigB negative control,
respectively.
B. Electropherogram of a typical sequencing reaction.
96
bsh
♦
TTTTGTGAAAAAAACCACAAATTATGTTTTACTCCAAACTCCGAGGGTACTGGTATACATGTAAGGTGA
gadB
♦
ACAAATTATTGTGAAAAATTGAACGGTTTGTCTCTGTGGTTTAATGGGTATTGGTGAGAGAAGGTGATC
inlA
♦
TTTTAACAAAAATTCTCACACCATTATGTGTTATTTTGAACATAAAGGGTAGAGGATAACATAAGTTAA
opuCA
♦
AAGCTGTTTTTTTGTATTTAAAAAGTTTAAATCTATACTAGTTAGGGAAATTAGTTATCGATTGCCAAT
lmo2230
♦
CTTTTTTACAATTTCTTCATTTTAATGTTTCTAGTAATTTAAAAAGGGTAGATATTACTGTTACCATTA
lmo1433
♦
CATTCGTGTGTGGCAGTTTTTTTCGTTTGAAAGTGAAATCAGACGGGAAAACAAGCTAAGAAGGAGTGA
lmo0669
♦
AATTCTTTTTCAATTTGATGTTAAACGTTTTAGCGTAAAACAGGAGGGAAGACATAAAGTAATGGGGGG
lmo1421
♦
ATTCCATAGTTTTTTTCTTAAATTAGGAATATTTAGGGATGATTTAGGGTAATTGGATGATATGTTCTT
Figure 2.4: Promoter sequences of genes with σB-dependent
transcriptional start sites confirmed by RACE-PCR. Promoter sequences are
underlined and transcriptional start sites are indicated by diamonds.
97
been absent in sigB mutant cDNA reactions. For all genes tested, the transcriptional
start site determined by RACE was 10 nt (+/- 2 nt) downstream of the σB-dependent
promoter –10 region that had been predicted by HMM or by visual inspection (Fig.
2.4). The genes selected for promoter confirmation by RACE were bsh and inlA, both
virulence genes; lmo0669, a putative metabolic gene; lmo1421 and opuCA (which
encode putative and known compatible solute transporter proteins, respectively); as
well as lmo2230, lmo1433, and gadB, all putative or proven stress response genes.
L. monocytogenes σB promoter consensus sequence resembles that of B.
subtilis. Successful identification of specific σB-dependent genes in L. monocytogenes
provided new information needed to facilitate further refinement of the predicted
consensus sequence for σB-dependent promoters in L. monocytogenes. The 54 σBdependent promoter sequences described above were aligned and used to generate a
new consensus recognition site (Fig. 2.5). The –35 region (GTTT) is separated from
the –10 region (GGGWAT) by 13-17 nucleotides; most frequently by 15 or 16. The
guanidine in the –35 box is almost completely conserved (98%). Overall, the L.
monocytogenes σB consensus sequence resembles the consensus sequence for B.
subtilis σB, which was reported by Petersohn et al. (50, 51) as GTTTAA-N12-15GGGWAW. This finding is not surprising, as the majority of the sequences used to
train the HMM used in this study were obtained from B. subtilis genes. However, the
predicted L. monocytogenes σB consensus sequence does differ slightly from the B.
subtilis consensus promoter sequence. Specifically, the two adenosines at the 3’ end
of the B. subtilis –35 region are not conserved in L. monocytogenes. The differing
consensus sequences suggest that σB may vary in its ability to recognize certain
promoters in these two species.
98
A
.50 .19 .00 .08 .06 .08 .19 .31
.52.06.00.02 .50 .83 .33 .60 .33 .58
C
.10 .15 .00 .02 .00 .00 .13 .17
.17.00.00.00 .02 .04 .06 .04 .08 .02
G
.10 .25 .98 .06 .02 .02 .23 .19
.15.92.98.90 .00 .02 .06 .06 .19 .15
T
.29 .42 .02 .83 .92 .90 .46 .33
.17.02.02.08 .48 .10 .54 .29 .40 .25
-35 region
-10 region
Figure 2.5: L. monocytogenes consensus sequence logo. Generated with the
GENIO/logo RNA/DNA and Amino Acid Sequence Logos web server
(http://genio.informatik.uni-stuttgart.de/GENIO/logo). The height of a nucleotide
represents its frequency at that location. Numbers below selected residues indicate
nucleotide frequencies at that position.
99
Effect of induction condition on gene expression patterns. As σB-dependent
gene expression patterns were determined under two different stress conditions, we
also analyzed whether the magnitude of σB-dependence for individual genes varied
with condition. Comparison of the microarray data generated under different stress
conditions indicated that the relative magnitude of σB-dependent expression was
similar under the two conditions for the genes tested. The scatter plot in Figure 2.6
shows the wild-type–to–∆sigB mutant gene expression ratios obtained for stationary
phase cells plotted against the gene expression ratios for osmotically stressed cells.
The majority (67%) of σB-dependent genes defined as described above showed
significantly higher mRNA levels with expression ratios >1.5 in the wild-type L.
monocytogenes strain under both stress conditions (Table 2.1). For 5 genes, the
expression ratios between the two stress conditions varied from each other by more
than 2-fold; the largest difference was 2.5-fold (lmo0880, point “A” in Fig. 2.6).
However, the majority of the genes (39 out of 55) had expression ratios that differed
by less than 1.5-fold under the 2 stress conditions. These results suggest that the
majority of genes comprising the σB regulon are induced to a similar extent in relation
to each other regardless of the specific environmental stress. A subset of σBdependent genes (e.g., lmo0880) may also be subjected to additional transcriptional
regulation by other stress-specific mechanisms. This is not to say, however, that all
stress conditions activate σB to the same degree. While our specific conditions tested
resulted in similar induction levels among the targeted genes (slope of regression =
0.89), primer extension data suggests that induction of transcription from the σB-
100
100
Wild-type–to–⎠ sigB gene expression ratio
(Stationary phase)
Stronger induction
under stationary
phase
10
A
Stronger induction
under osmotic stress
1
0.1
1
10
100
0.1
Wild-type–to–∆sigB gene expression ratio
(Osmotic stress)
Figure 2.6: Comparison of expression ratios for two stress conditions. Crosses
represent genes not expressed significantly higher in the wild type, while squares
represent. significantly σB-dependent genes. The data point labeled “A” represents
lmo0880, which showed the largest difference in expression ratios.
101
dependent L. monocytogenes rsbV promoter may vary under the different stress
conditions (4).
DISCUSSION
To improve our understanding of the specific roles of the alternative sigma
factor σB in regulating gene expression and bacterial stress response, we used a
combination of whole genome HMM similarity searches and microarray-based
strategies to identify members of the σB regulon in the facultative intracellular
pathogen L. monocytogenes. A 208-gene microarray, which included 166 HMMidentified L. monocytogenes genes located downstream of putative σB-dependent
promoter sequences as well as selected additional virulence and stress response genes,
allowed us to identify 54 genes as directly regulated by L. monocytogenesσB.
Transcriptional start site mapping on selected genes confirmed the functionality of
putative σB-dependent promoters at the locations predicted by the HMM or by visual
inspection. Similar to the σB regulon previously defined for B. subtilis, a Gram
positive soil bacterium closely related to the genus Listeria, members of the L.
monocytogenesσB regulon were shown to encode a variety of protein functions
involved in metabolic pathways, transport, and other fundamental cellular functions.
As expected, many genes identified in this study encode proteins directly associated
with stress resistance. Interestingly, several genes identified as σB-dependent
represent putative or known virulence genes (e.g., inlE and bsh, respectively) or stress
response genes that have been shown to contribute to the ability of L. monocytogenes
to survive within an infected host (e.g., opuC; 60, 66) or under similar conditions (e.g.,
gadB; 11). These results suggest that σB, in addition to enhancing bacterial survival
under stress conditions, also contributes to virulence in L. monocytogenes.
Role of σB in L. monocytogenes stress resistance. Phenotypic
characterization of L. monocytogenes strains lacking sigB has shown that σB plays an
102
important role in resistance to osmotic, oxidative and acid stresses (4, 18, 19, 22, 67).
Similar studies using B. subtilis ∆sigB mutants also provided evidence of the
importance of a functional σB for survival under ethanol, oxidative, osmotic, and acid
stresses (2, 25, 65). The σB-dependent L. monocytogenes genes identified here
provide additional insight into the functional bases of the reduced stress resistance in
L. monocytogenes ∆sigB mutants. For example, gadB, which encodes a glutamate
decarboxylase important for acid stress survival in L. monocytogenes (11), was shown
in this work to be part of the L. monocytogenesσB regulon.
Interestingly, both the L. monocytogenes and the B. subtilis σB regulons
include multiple genes that have been shown experimentally to contribute to
protection against osmotic stress, including genes encoding several solute transporters.
The ABC transporter OpuC contributes to osmotic stress resistance by facilitating
uptake of the osmoprotectants choline and glycine betaine in both L. monocytogenes
and B. subtilis (1, 35, 36, 60), and expression of the encoding operon is σB-dependent
in L. monocytogenes. Similarly, lmo1421 and the B. subtilis homologue opuB, both
members of the σB regulon in the respective species, encode a putative choline
transporter, which may also contribute to osmotic stress resistance (22, 36). In
addition, ctc, which shows σB-dependent expression in both L. monocytogenes (this
study) and B. subtilis (29, 33), was recently shown to contribute to osmotolerance in L.
monocytogenes (26).
Finally, the σB regulon in both L. monocytogenes and B. subtilis also includes
genes that appear to contribute to oxidative stress resistance, consistent with the
observation that a L. monocytogenes ∆sigB mutant shows increased susceptibility to
oxidative stress (18). Based on our data, we propose that σB-dependent resistance to
oxidative damage in L. monocytogenes is likely due, at least in part, to glutathione
reductase, which is encoded by lmo1433. Glutathione reductase is an enzyme that
103
provides protection from oxidative stress by reducing glutathione disulfide to
glutathione (9). L. monocytogenes has been shown to accumulate glutathione,
supporting the possible activity of this enzyme during oxidative stress (47). While no
glutathione reductase homologue was found in B. subtilis, oxidative stress protection
in B. subtilis is dependent on the DNA-binding protein Dps, as well as on the essential
trxA-encoded thioredoxin, both of which are σB-dependent (59). Our HMM searches
did not identify L. monocytogenes trxA as bearing a σB-dependent promoter.
The role of σB in virulence gene expression. Characterization of L.
monocytogenes ∆sigB mutants in both tissue culture and murine models of infection
has provided initial evidence that σB contributes to the ability of L. monocytogenes to
cause infection. While it has been shown that transcription from one of three prfA
promoters (specifically, the P2 promoter) is abolished in a ∆sigB mutant, no additional
evidence for other functional contributions of σB to virulence have been reported. Our
results provide clear evidence that σB in L. monocytogenes directly contributes to
transcriptional activation of genes directly associated with virulence, as well as those
that likely contribute indirectly to virulence (58). Virulence genes defined as part of
the σB regulon include bsh (encoding a bile salt hydrolase) as well as two genes from
the internalin family (inlA and inlB). Although σB-dependent transcription of inlA and
bsh has also been independently verified by RT-PCR (Sue and Wiedmann,
unpublished), and while RACE-PCR confirmed the presence of functional σB
promoters for these genes, it is important to note that both genes also appear to be
transcribed from σB-independent promotors (14, 15). Interestingly, both bsh and inlA
are regulated by PrfA (14, 15), a positive transcriptional regulator of virulence gene
expression. While PrfA binding has been shown to activate transcription by binding
to the –35 promoter region, none of the PrfA binding boxes upstream of the σBdependent virulence genes described here overlap with the σB consensus promoter –35
104
region. However, the σB-dependent P2 promoter of prfA contains a sequence
resembling a PrfA box (23), and Milohanic et al. (42) report a gene, lmo0596, with a
putative PrfA box located at the –35 region of a predicted σB-dependent promoter. We
conclude that transcription of a subset of L. monocytogenes virulence genes is
regulated by a complex regulatory network that can include activation by both PrfA
and σB. We hypothesize that this PrfA/σB regulatory mechanism coordinates
transcriptional activation of subsets of L. monocytogenes virulence genes in specific
host environments, e.g., bsh and inlA have been shown to be critical for listerial
pathogenesis in the intestine (15, 39). Further studies using animal models appropriate
for the study of the intestinal pathogenesis of listeriosis (e.g., guinea pigs; 39) will be
necessary to test this hypothesis.
While bsh, inlA, and inlB represent experimentally verified virulence genes
which were identified as σB-dependent, we also defined as members of the σB regulon
additional putative L. monocytogenes virulence genes, including additional internalins.
The L. monocytogenes internalins represent a diverse group of surface proteins with
confirmed or putative virulence functions (39, 49, 57). While internalin B does not
display an LPXTG motif, the other internalins include this cell wall anchor domain.
Proteins with LPXTG motifs are common among Gram positive bacteria and their
functions are broad in range and frequently affect virulence (reviewed in 46). In
addition to inlA, we identified four other L. monocytogenes genes encoding putative
cell wall-anchored proteins displaying an LPXTG motif (including the internalin
genes inlC2 and inlE) as σB-dependent. While inlC2 and inlE, which are part of the
inlC2DE operon in L. monocytogenes 10403S, have not been shown experimentally to
contribute to virulence, members of the homologous inlGHE operon present in other
L. monocytogenes strains (e.g., EGD-e) have been shown to contribute to host cell
internalization (5, 57). In addition to two other σB-dependent genes encoding proteins
105
with LPXTG motifs (lmo2085 and lmo0880), we also identified one σB-dependent
gene (lmo0994) that is unique to L. monocytogenes (i.e., absent from L. innocua and
B. subtilis). Further studies using appropriate null mutants will be necessary to
determine the specific functions of these putative σB-dependent virulence genes.
In addition to the established or putative virulence genes discussed above, we
also identified σB-dependent stress response genes that had been shown previously to
contribute to L. monocytogenes virulence, infection, and intra-host survival. Examples
include the σB-dependent opuC operon; a L. monocytogenes LO28 opuC mutant
showed reduced colonization of the mouse upper small intestine following peroral
inoculation (60) and reduced numbers of bacteria in the spleens and livers of infected
mice (66), although the phenotype appears to be strain-specific (60). The σBdependent gadB was previously shown to contribute to L. monocytogenes acid
survival, including survival in synthetic gastric and ex vivo porcine stomach fluids
(11). In conjunction with our findings described above, these data support a broad
role for σB-dependent genes in L. monocytogenes virulence and intra-host survival.
Use of more appropriate recently described animal models to study L. monocytogenes
pathogenesis (e.g., guinea pigs, 39) may help us to more clearly define the in vivo
contributions of σB to L. monocytogenes virulence than has been possible by using the
mouse model of infections. The mouse lacks the appropriate E-cadherin receptor,
which is particularly critical for gastrointestinal invasion by L. monocytogenes (67).
Genome scale comparisons of the L. monocytogenes and the B. subtilis σB
regulons further suggest that the σB-dependent stress response system has adapted in
L. monocytogenes to facilitate pathogen-host interactions. Studies in other Gram
positive pathogens provide clear evidence of σB-dependent contributions in directing
gene expression during host infection. In S. aureus, the virulence determinant sarC is
expressed from a promoter that is strictly σB-dependent (6, 41). SarC specifically
106
activates transcription of agr, which encodes a positive regulator of extracellular
virulence gene expression (43, 48). In both S. aureus and S. epidermidis, σB is also
required for biofilm formation, a probable prerequisite for establishing infections (37,
54, 55). σB contributes to virulence in B. anthracis; a sigB mutation in B. anthracis
severely attenuates virulence in a murine model of infection (21). In addition to σB,
stress responsive sigma factors may broadly contribute to bacterial virulence. For
example, the Gram negative stress responsive alternative sigma factor RpoS also has
been shown to contribute to virulence in a variety of pathogens (including Yersinia,
Salmonella, Pseudomonas aeruginosa and Legionella pneumophila [3, 17, 34, 61]).
Comparative genomics of σB-dependent stress response. The definition of
54 σB-dependent genes in L. monocytogenes provides a unique opportunity for a
comparative evaluation of the predicted functions of the σB-dependent stress response
among low GC-content Gram positive bacteria. Overall, the range of protein
functions associated with the L. monocytogenes σB-dependent genes defined in this
work appears to be similar to the range of functions encoded by the genes described
for the B. subtilis σB regulon (51, 53). Through similarity searches, we determined
that a total of 31 of the 54 σB-dependent genes in L. monocytogenes have homologous
gene sequences in B. subtilis. A total of 12 of these 31 genes show σB-dependent
expression in both L. monocytogenes (this work) and in B. subtilis (51, 53). These 12
genes include the stress response genes ctc, ltrC, and lmo1602, the rsbV operon, and
metabolic genes (see Table 2.2).
The analysis of the S. aureus σB regulon performed by Gertz et al. (27)
identified predominantly uncharacterized proteins. While 20 of the 27 σB-dependent
S. aureus proteins identified had homologues in B. subtilis, only 7 of those
homologues were σB-dependent in B. subtilis. This finding parallels our own in that
only a portion of the B. subtilis genes that are homologous to the σB-dependent genes
107
identified in L. monocytogenes are also σB-dependent in B. subtilis. Taken together,
these observations suggest that the σB regulon has evolved to serve different roles
among these bacteria.
Towards defining the complete L. monocytogenes σB regulon. Stress
responsive alternative sigma factors, including RpoS in Gram negative bacteria (32)
and σB in low GC-content Gram positive bacteria, contribute to regulation of large sets
of genes, both directly and indirectly (51). As commercial, full genome microarrays
become available, more genes than those found here can be identified as σBdependent, including those not identified by the original HMM search. Still, defining
all genes regulated by an alternative sigma factor represents a significant challenge,
even with the availability of technologies such as 2-D gel electrophoresis and full
genome microarrays. While our identification of 54 σB-dependent genes likely
represents about one-third of the L. monocytogenes σB regulon, which is estimated to
contain around 150 genes, the functional diversity represented by the encoded proteins
of these genes provides valuable new insight into the specific functions of the L.
monocytogenes σB regulon. In addition to the 54 genes reported here, many additional
members of the L. monocytogenes σB regulon may have been correctly predicted by
our HMM search, but their detection may have been masked by redundant regulation
of transcription. Additional approaches such as in vitro transcription analyses using a
purified L. monocytogenes σB-RNAP complex (8) or transcriptional profiling of an L.
monocytogenes strain with an inducible sigB (53) will likely be necessary to identify
and confirm additional members of the σB regulon. We have demonstrated, however,
that a combination of HMM-based similarity searches followed by construction of a
microarray as described here represents an efficient and economic approach for
defining genes regulated by a specific mechanism, such as an alternative sigma factor.
108
ACKNOWLEDGEMENTS
We would like to thank Paul Debbie and Nai-Chun Lin for technical assistance
in creating and working with microarrays, and John Helmann for helpful discussions
about this project and manuscript. This research was supported in part by the Cornell
University Agricultural Experiment Station federal formula funds, Project No. NYC143422 received from Cooperative State Research, Education, and Extension Service,
U.S. Department of Agriculture. Any opinions, findings, conclusions, or
recommendations expressed in this publication are those of the authors and do not
necessarily reflect the view of the U.S. Department of Agriculture.
109
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CHAPTER THREE:
CONTRIBUTIONS OF LISTERIA MONOCYTOGENES σB AND PRFA TO
EXPRESSION OF VIRULENCE AND STRESS RESPONSE GENES DURING
EXTRA- AND INTRACELLULAR GROWTH
ABSTRACT
Listeria monocytogenes σB and PrfA are pleiotropic regulators of stress
response and virulence gene expression. We used quantitative RT-PCR to measure
transcript levels of σB- and PrfA-dependent genes in L. monocytogenes wild type and
∆sigB strains exposed to environmental stresses (0.3 M NaCl or growth to stationary
phase) or present in the vacuole or cytosol of human intestinal epithelial cells.
Stationary phase or NaCl-exposed L. monocytogenes showed σB-dependent increases
in opuCA (10- and 17- fold higher, respectively) and gadA transcript levels (77- and
14-fold higher, respectively) as compared to non-stressed cells. While PrfA activity,
as reflected by plcA transcript levels, was up to 95-fold higher in intracellular L.
monocytogenes as compared to non-stressed bacteria, σB activity was only slightly
higher in intracellular than in non-stressed bacteria. Increased plcA transcript levels,
which were similar in both host cell vacuole and cytosol, were associated with
increases in both prfA expression and PrfA activity. qRT-PCR assays designed to
measure expression of prfA from each of its three promoters showed that, under all
conditions, readthrough transcription from the upstream plcA promoter was
consistently very low and that the relative contribution from the σA-dependent P1prfA
promoter ranged from 17-30% of total prfA transcription. P2prfA, which appears to be
transcribed by both σA and σB, contributed 70-82%. In summary: (i) PrfA is activated
specifically during intracellular growth, while σB is activated primarily under
environmental stress; and (ii) the partially σB-dependent P2prfA promoter contributes
the majority of prfA transcripts in both intra- and extracellular bacteria.
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119
INTRODUCTION
Listeria monocytogenes is a foodborne intracellular pathogen responsible for
approximately 500 deaths each year in the United States alone (30). Several genes
contributing to L. monocytogenes virulence have been identified and characterized.
The majority of these virulence genes lie in a single cluster on the L. monocytogenes
chromosome and are controlled by the transcriptional activator PrfA (9, 14). Loss-offunction mutations in prfA result in significantly reduced expression of several
virulence genes (27, 32) as well as in reduced L. monocytogenes virulence in murine
and in tissue culture models of infection (9, 21).
In addition to regulation by PrfA, some virulence genes (e.g., inlA, bsh) are
also under the control of the alternative sigma factor σB (24, 25, 34, 49). σB is a stressresponsive, stationary phase sigma factor present in a number of Gram positive
bacteria. In L. monocytogenes, σB contributes to survival under a variety of lethal
environmental stresses (17). For example, σB and σB-dependent genes are important
for survival of acidic conditions mimicking mammalian gastric fluid (10, 12, 52). A
sigB deletion mutant exhibits reduced invasion of Caco-2 cells, probably due to
reduced
B
-dependent inlA expression (25) and is slightly virulence-attenuated in
mouse models (34, 52). Recent evidence suggests that σB activates transcription of
prfA from the P2prfA promoter (34, 40, 46). Although loss of expression from the
P2prfA promoter affects in vitro virulence phenotypes, such as hemolysin production
(34), it does not affect L. monocytogenes invasion capabilities in the Henle-407 human
intestinal epithelial cell line or in the Caco-2 human colorectal epithelial cell line (25).
In Stapylococcus aureus, σB contributes to expression of virulence factors such as
coagulase and clumping factor (35), other adhesins (4) and the virulence-associated
transcriptional regulator SarA (3). Interestingly, in Gram negative bacteria, the stress
responsive, stationary phase sigma factor σS (RpoS) also contributes to virulence,
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including RpoS-dependent transcription of the spv cluster in Salmonella Typhimurium
(13, 16, 36) and of exotoxin A in Pseudomonas aeruginosa (51). Links between
environmental stress responses and virulence in bacteria suggest a central role for
alternative sigma factors in the ability of bacterial pathogens to survive environmental
stress conditions, to direct the expression of virulence genes, and to cause disease.
Regulation of virulence gene transcription plays a crucial role in a pathogen’s
ability to cause infections, as supported by the observation that mutations in
transcriptional regulators can result in severe attenuation or complete virulence
abolition among different bacterial pathogens (9, 22, 37, 38, 41). We hypothesized
that coordinated regulation of virulence and stress response gene expression by
appropriate transcriptional regulators is likely to be particularly critical for foodborne
and enteric pathogens, which are exposed to a variety of different stress conditions
(e.g., reduced pH) before and during the infection process. To determine the specific
contributions of the σB and PrfA transcriptional regulators to expression of L.
monocytogenes virulence and stress response genes, we measured transcript levels of
selected σB- and PrfA-dependent genes under conditions mimicking critical stages of
infection in a mammalian host (e.g., bacterial presence in host cell vacuoles or
cytosol). As both σB and PrfA can be present in either active or inactive states,
measurement of transcript levels from σB- and PrfA-dependent genes allowed
evaluation of the activities of these two proteins under the different conditions tested.
MATERIALS AND METHODS
Bacterial strains and growth. All experiments were performed with L.
monocytogenes strain 10403S (5) or derivatives (Table 3.1). Strains FSL R3-001
(∆actA), FSL A1-254 (∆sigB), DP-L2161 (∆hly), and DP-L1956 (∆P1prfA) were
described previously (21, 23, 52). Strains FSL K3-017 (∆actA ∆sigB), FSL K4-001
(∆hly ∆sigB) and FSL B2-002 (∆P1prfA ∆sigB) were created as described below.
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Bacteria were grown at 37°C on BHI agar plates or in Brain Heart Infusion (BHI)
broth (Difco/BD, Sparks, MD) with shaking at 250 rpm unless otherwise noted.
Genetic manipulations. Strain FSL K3-017 (∆actA ∆sigB) was constructed by
introducing plasmid pEDF1 (containing the in-frame actA deletion allele used to
construct the ∆actA strain FSL R3-001) into FSL A1-254 (∆sigB) by electroporation,
as previously described (45). Transformants were serially passaged at 41°C in BHI
with 10 µg/ml chloramphenicol to select for chromosomal integration of the plasmid
by homologous recombination. Subsequently, chloramphenicol-resistant isolates were
serially passaged in BHI at 30 °C to allow plasmid excision. Isolates were replica
plated onto BHI plates with and without chloramphenicol, and chloramphenicol
sensitive colonies were screened by PCR for loss of the internal actA gene fragment.
Gene deletions were confirmed by sequencing PCR products. Strains FSL K4-001
(∆hly ∆sigB) and FSL B2-002 (∆P1prfA ∆sigB) were constructed by introducing
plasmid pTJA-57 (containing the in-frame sigB deletion allele used to construct the
∆sigB strain FSL A1-254) (52) into DP-L2161 (∆hly) or DP-L1956 (∆P1prfA) using
the approach described above.
Experimental growth conditions. L. monocytogenes 10403S or FSL A1-254
were inoculated from single colonies on BHI plates into BHI broth and grown
overnight, then sub-cultured 1:200 in BHI pre-warmed to 37oC, and grown to OD600
0.4. For harvest of stationary phase cells, cultures were grown to OD600 0.8 and then
incubated for one additional hour. Log phase cells and NaCl-stressed cells were
prepared and collected in parallel. One culture of each strain (10403S or FSL A1-254)
was divided into two 4 ml aliquots and centrifuged 3 min at 3400 x g. Cell pellets
were resuspended in 2 ml prewarmed BHI broth. Two ml of prewarmed BHI broth or
BHI plus 0.6 M NaCl was added to the cultures and each was incubated for 7 min at
37°C with shaking. For RNA isolation, 4 ml of each culture (log phase, stationary
122
Table 3.1: Strains used in this study
Strain
Genotype
Experiments
Reference
10403S
wild type
broth
(5)
FSL A1-254
10403S, ∆sigB
broth
(52)
DP-L2161
10403S, ∆hly
Caco-2 vacuole
(23)
FSL K4-001
10403S, ∆hly, ∆sigB
Caco-2 vacuole
this study
FSL R3-001
10403S, ∆actA
Caco-2 cytoplasm
(45)
FSL K3-017
10403S, ∆actA, ∆sigB
Caco-2 cytoplasm
this study
DP-L1956
10403S, ∆P1prfA
prfA RACE-PCR
(21)
FSL B2-002
10403S, ∆P1prfA, ∆sigB prfA RACE-PCR
this study
123
phase or NaCl-stressed cells) was added to 8 ml of RNA Protect Bacteria Reagent
(Qiagen, Valencia, CA), vortexed briefly, incubated at room temperature for 5
minutes, and centrifuged 3 min at 3400 x g. Cell pellets were frozen at -80°C for
subsequent RNA isolation as described below.
Cell culture infection experiments. Caco-2 human intestinal epithelial cells
were grown at 37°C in modified Eagle’s medium with Earle’s salts (Gibco, Grand
Island, NY), plus 20% fetal bovine serum, 2 mM L-glutamine, 0.1 mM non-essential
amino acids, 1 mM sodium pyruvate, and 0.15% sodium bicarbonate (MEM-E). To
obtain sufficient amounts of RNA for quantitative RT-PCR from intracellular L.
monocytogenes, Caco-2 cells were seeded into T-75 flasks (Corning, Inc., Corning,
NY). To allow monitoring of the infection progress in parallel with the T-75
infections, Caco-2 cells were also seeded into 6-well plates containing glass coverslips
(three round 12 mm coverslips were ethanol-sterilized and placed into each well prior
to seeding). Host cells were grown at 37°C to near confluency in both T-75 flasks and
in 6-well plates before infection experiments were initiated. Pairs of appropriate
mutant strains were selected for infection experiments to enable quantification of the
loss of σB on σB-dependent gene expression for L. monocytogenes cells in either host
cell vacuoles or host cell cytosol. Specifically, ∆hly or ∆hly ∆sigB L. monocytogenes
strains were used to harvest mRNA from bacterial cells arrested in the vacuole and
∆actA and ∆actA ∆sigB L. monocytogenes strains were used to harvest mRNA from
bacterial cells arrested in the cytosol of the primary infected Caco-2 cells. Inocula of
L. monocytogenes ∆hly, ∆hly ∆sigB, ∆actA and ∆actA ∆sigB strains were prepared as
described previously (39) and infections were performed with a multiplicity of
infection (MOI) of approximately 25.
For the infection studies, host cells infected with the ∆hly or ∆hly ∆sigB strains
were held for 30 min; then the medium was removed from the cell monolayers, cells
124
were washed with PBS, and then covered with prewarmed MEM-E containing 50
µg/ml gentamicin. At 1 hour after infection, cell monolayers in the flasks were
washed again with PBS and covered with 20 ml of lysis solution, consisting of 50%
RNA Protect Bacteria Reagent and 1% saponin in PBS. Cells were lysed for 5
minutes at room temperature, collected, centrifuged for 5 min at 2200 x g, and cell
pellets were frozen at -80°C for subsequent RNA purification. Infection with ∆actA
and ∆actA ∆sigB L. monocytogenes strains was performed as described above, except
that gentamicin treatment was performed at 1 h post infection and lysis and collection
were performed at 4 h post infection (to allow all bacterial cells to escape from the
vacuole and adapt to the cytosolic environment). In each experiment, coverslips from
Caco-2 cells infected in 6-well plates were stained with the Diff-Quik staining kit
(Baxter Diagnostics, Inc., McGraw Park, IL), and examined under a microscope to
verify progress of infection.
DNA and RNA purification. RNA was isolated from frozen cell pellets with
the RNeasy kit (Qiagen) according to the manufacturer’s protocol for enzymatic and
mechanical disruption, except that cells were sonicated on ice for three 30 second
bursts at 18-21 W. Two consecutive DNase treatments were performed during
purification with an on-column DNase kit (Qiagen) according to the manufacturer’s
protocol. Purified RNA was precipitated and stored at -20°C. Bacterial RNA isolated
from infected Caco-2 cells was further enriched from contaminating mammalian RNA
with the MICROBEnrich kit (Ambion, Austin, TX). DNA for TaqMan assay standard
curves was isolated from overnight cultures of L. monocytogenes by the procedure of
Flamm et al. (18).
Quantitative RT-PCR (qRT-PCR). All TaqMan primers and probes used were
designed using Primer Express software (Applied Biosystems, Foster City, CA) and
are listed in Table 3.2. Probes with MGB quencher dye were synthesized by Applied
125
Biosystems and probes with QSY7 quencher were synthesized by MegaBases, Inc.
(Evanston, IL). Quantitative RT-PCR was performed in 25 µl reactions as previously
described (50). For samples containing mixed bacterial and mammalian RNA, the
entire output from the MICROBEnrich kit was used in the TaqMan reactions for the 8
target genes; 150-250 ng of total RNA were used per reaction. All reactions were
performed in duplicate on at least three independent RNA preparations. For log phase
and NaCl-stressed bacterial cells, gap, rpoB, prfA-P1, and prfA-CDS transcripts were
quantified using two additional independent RNA preparations. For bacterial cells
harvested from the Caco-2 vacuolar environment, all target genes were quantified
using one additional independent RNA preparation. These additional experiments
were performed due to high variations observed among the initial three replicates.
A genomic DNA standard curve was generated for each set of TaqMan
reactions as previously described to allow for absolute quantification of mRNA levels
(50). Briefly, except for quantification of gap, dilutions corresponding to 107, 105, and
102 copies of genomic DNA per reaction were used for the standard curves. To
quantify the highly expressed gap, 108 copies were used for the standard curve instead
of 107. The term “cDNA copy numbers” is used throughout this manuscript to
describe mRNA levels, reflecting the fact that absolute copy numbers were calculated
using a DNA standard curve (50). As also previously described (50), transcript levels
for each gene (i.e., cDNA copy numbers) were determined as the difference between
the experimental reactions and the corresponding reverse transcriptase-negative
controls, which were used to quantify the amount of contaminating L. monocytogenes
DNA in each reaction. If the difference between the experimental reactions and the
corresponding reverse transcriptase-negative controls was less than twice the value of
the reverse transcriptase-negative control, the cDNA copy number was considered to
be equal to that of the negative control. This “flooring” approach is based on the
Table 3.2: TaqMan primers and probes used in this study
Target
Forward primera
TaqMan probeb
Reverse primer
Reference
gap
aaagctggcgctaaaaaagttg
atctccgctccagcaactggcgatat-QSY7c
ttcatggtttacattgtaaacgattg
(46)
rpoB
tgtaaaatatggacggcatcgt
ctgattcgcgcaaaacttctacgcg-QSY7
gctgtttgaatctcaattaagtttgg
(50)
plcA
gatttatttacgacgcacattagttt
cccattaggcggaaaagcatattcgc-QSY7
gagttctttattggcttattccagttatt
this study
prfA-P1
gcgtgactttctttcaacagcta
caattgttgttactgcctaat-MGB
cccccaatcgttttttatcg
this study
prfA-CDS
caatgggatccacaagaatattgtat
tgtaaattcatgatggtcccgttctcgct-QSY7
aataaagccagacattataacgaaagc
this study
opuCA
acatcgataaaggagaatttgtttgtt
cgttttcccacaaccacttggaccg-QSY7
gccggttaatcatcttcattgtt
(50)
tccgcattgttacgccagcgaaa-QSY7
tgcctgtatatccagacctcgtt
this study
tcttttgcgaaatcaa-MGB
gaaagtcacgctaaatgatgtttttt
this study
tggcggtttggcaatga
gadA
plcAcctcggaaccatatactaactctatttca
readthrough
a
all sequences are written in the 5’-3’ direction.
b
All probes have the FAM reporter dye on the 5’ end
c
QSY7 is a custom dark quencher dye. MGB is a minor groove binding dark quencher dye.
126
115
127
ability of the ABI PRISM 7000 and the TaqMan system to detect a minimum two-fold
difference in mRNA levels (ABI PRISM® 7000 Sequence Detection System
Specifications, Publication 117SP03-04, Applied Biosystems)
RACE-PCR. Transcriptional start sites were mapped within the prfA promoter
region using the 5' rapid amplification of cDNA ends (RACE) system (Invitrogen)
according to the manufacturer's protocol and as previously described (24). RNA for
the procedure was isolated as described above from L. monocytogenes 10403S and
DP-L1956 ( P1prfA) cells grown to stationary phase.
Statistical Analyses. Statistical analyses were performed with the Statistical
Analysis Software (SAS). Raw cDNA copy numbers were normalized to the
geometric mean of the two housekeeping genes, gap and rpoB. Data were log
transformed to provide a normal distribution. We performed standard regression
diagnostics (residual vs. predicted values, Cook's distance, and leverage) to assess the
validity of the model and identify outliers. The general linear model procedure was
used to assess the effect of stress, ∆sigB mutation, cell collection date, RNA collection
date, and assay date for each gene individually. In no instance did cell collection date,
RNA collection date, or assay date have a significant effect on the data. The general
linear model procedure followed by LSMEANS with Tukey's correction was then
used to determine the significance of each individual stress effect (0.3M NaCl, growth
to stationary phase, presence in host cell vacuole, presence in host cell cytosol) for
each gene. This analysis was performed on the wild type and ∆sigB data separately.
A final general linear model procedure and LSMEANS with Tukey's correction was
used to determine whether the ∆sigB mutation had a significant effect on gene
transcript levels under each stress condition. All results are reported as the average
log of the normalized copy numbers, unless otherwise noted.
128
RESULTS
Activity of σB-dependent genes during environmental stress and infection
of human epithelial cells. RNA collected from L. monocytogenes wild type and
∆sigB cells grown to (i) log phase, (ii) log phase followed by a 7-minute 0.3 M NaCl
exposure, (iii), early stationary phase, or (iv) isolated from the vacuole or (v) cytosol
of human intestinal epithelial cells, was used to quantify transcript levels of the σBdependent genes gadA (lmo2434) and opuCA (24, 50) using TaqMan qRT-PCR (Fig.
3.1). To study expression of these two genes during the course of the L.
monocytogenes intracellular life cycle, we used strains bearing ∆hly or ∆actA
mutations, which remain in the host vacuole and cytosol, respectively. As a
consequence, L. monocytogenes strains with ∆hly or ∆actA mutations enable RNA
isolation from a large population of bacteria in the same stage of infection (7). Each
mutation (∆hly or ∆actA) was created in both wild type and ∆sigB backgrounds to
allow measurement of the relative contribution of σB to gene expression in both
intracellular compartments. Microscopic examination of infected Caco-2 cell cultures
verified predicted compartmentalization of each mutant strain (Fig. 3.2).
In log phase cells, gadA and opuCA cDNA copy numbers were lower in the
∆sigB strain than the wild type, although the difference was only statistically
significant for opuCA (Fig. 3.1). Upon exposure of log phase wild type cells to NaCl,
opuCA cDNA copy numbers increased significantly (17-fold) and gadA cDNA copy
numbers increased with borderline significance (14-fold; Fig. 3.1, Table 3.3). No
increase in expression of opuCA or gadA was observed in the ∆sigB mutant.
Stationary phase wild type cells also showed significant gadA and borderline
significant opuCA cDNA copy number increases (77 times and 10 times higher,
respectively; Fig. 3.1, Table 3.3), while no increased cDNA copy numbers were found
in the ∆sigB strain.
129
Log (normalized copy no.)
opuCA
0
-1
-2
-3
*
*
*
*
-4
log phase
NaCl stationary vacuole
stress
phase
cytosol
Log (normalized copy no.)
gadA
0
-1
*
-2
*
-3
*
-4
log phase
NaCl stationary vacuole
stress
phase
cytosol
Figure 3.1: cDNA copy numbers for σB-dependent genes. Dark and light bars
represent wild type and ∆sigB strains, respectively. Error bars represent one standard
deviation. An asterisk indicates the difference between wild type and ∆sigB cDNA
copy numbers is statistically significant for that condition.
130
Figure 3.2: Micrographs of Caco-2 infection by L. monocytogenes. Caco-2 cells
were infected with, clockwise from the top-left, ∆hly; ∆actA, ∆actA ∆sigB, and ∆hly
∆sigB. Micrographs were taken at 600X magnification.
A
B
D
131
Table 3.3: Statistical comparisons of cDNA copy numbers among select growth
conditions
Significance levels (p values) for expression differencesa
a
Gene
log-NaCl
log-sta
log-vac
log-cyt
NaCl-vac
vac-cyt
opuCA
0.0361b
0.0941
NS
NS
NS
NS
gadA
0.0591
0.0025
NS
NS
NS
NS
plcA
NS
0.0152
< 0.0001
< 0.0001
< 0.0001
NS
prfA
NS
0.0176
0.0001
< 0.0001
0.0014
NS
Multiple pair-wise comparisons of normalized cDNA copy numbers in wild type
bacteria among growth conditions were performed (see Materials and Methods).
Abbreviations: log = non-stressed log phase cells; NaCl = 0.3M NaCl; sta = stationary
phase cells; vac = Caco-2 vacuole; cyt = Caco-2 cytoplasm.
b
p values less than 0.05 were considered significant. p values between 0.1 and 0.05
were considered borderline significant. p values above 0.1 are listed as NS, not
significant.
132
opuCA and gadA cDNA copy numbers for L. monocytogenes present in the
host cell vacuole appeared higher than in log phase extracellular bacterial cells (Fig.
3.1) and lower than in bacterial cells exposed to 0.3 M NaCl, however, none of these
differences were statistically significant (Table 3.3). Expression of opuCA and gadA
in the ∆sigB strains was at or below the detection limit in both intracellular
compartments. cDNA copy numbers for opuCA and gadA were overall very similar in
L. monocytogenes arrested in either the vacuole or the cytosol (Fig. 3.1), with no
significant differences in cDNA copy number observed for either gene in either
compartment (Table 3.3).
Activity of PrfA-dependent genes during environmental stress and
infection of human epithelial cells. RNA collected from L. monocytogenes wild type
and ∆sigB cells under the same conditions described for gadA and opuCA
measurement was used to quantify transcript levels of prfA and the PrfA-dependent
plcA (9, 32) using TaqMan qRT-PCR (Fig. 3.3). L. monocytogenes cells exposed to
0.3M NaCl showed no significant increases in plcA or prfA cDNA copy numbers over
numbers present in log phase cells, while plcA and prfA cDNA copy numbers were
both significantly higher in stationary phase cells as compared to log phase cells
(Table 3.3). Neither plcA nor prfA transcript levels differed between wild type and
∆sigB mutant under any of the three extracellular growth conditions tested.
plcA cDNA copy numbers in bacteria present in the host cell vacuole were 95
and 83 times higher as compared to cDNA copy numbers in log phase and NaClstressed cells, respectively; these differences were highly significant (p<0.0001; Table
3.3). prfA cDNA copy numbers in vacuolar bacteria were also significantly higher as
compared to log phase and NaCl-stressed cells (11- and 7-fold higher, respectively).
plcA and prfA transcript levels did not differ between wild type and ∆sigB strains in
133
Log (normalized copy no.)
plcA
1
0
-1
-2
-3
-4
log phase
NaCl stationary vacuole
stress
phase
cytosol
Log (normalized copy no.)
prfA
0
-1
-2
-3
-4
log phase
NaCl stationary vacuole
stress
phase
cytosol
Figure 3.3: cDNA copy numbers for PrfA-dependent genes. Dark and light bars
represent wild type and ∆sigB strains, respectively. Error bars represent one standard
deviation. In no instance was the difference between wild type and ∆sigB cDNA copy
numbers statistically significant.
134
either intracellular compartment. As with the σB-dependent genes, cDNA copy
numbers in the vacuole and the cytosol showed no significant differences for either
plcA or prfA (Table 3.3).
In order to compare the levels of active PrfA found in bacteria exposed to
different environmental stress conditions or present in the host cell vacuole or the host
cell cytosol, we calculated PrfA activity, which we defined as the ratio of normalized
plcA cDNA copy numbers to normalized prfA cDNA copy numbers. Using this
approach we showed that PrfA activity is highest in bacteria found in the vacuole,
while PrfA activity is lowest in log phase bacteria. While exposure of log phase cells
to 0.3M NaCl did not increase PrfA activity, stationary phase bacteria showed
increased PrfA activity over log phase bacteria (Fig. 3.4).
Characterization of prfA promoters. The region immediately upstream of
prfA contains two previously identified promoters. One of these promoters, P2prfA,
has been suggested to be σB-dependent (34, 40, 46). A putative PrfA binding box is in
close proximity to P2prfA (21). We used RACE-PCR to map the transcriptional start
sites in the region immediately upstream of prfA in both the wild type and ∆sigB
strains. A transcript with a 5’ end corresponding to the previously described P1prfA
promoter (20, 21) was identified in both the wild type and the ∆sigB mutant (Fig.
3.5A; top arrow). A σA consensus sequence (5’TTGCGA – 12nt – TATAAT3’) for
P1prfA was identified 12 bp upstream of the 5’ transcript end identified by RACEPCR (Fig. 3.5C). A second 5’ transcript end, which correlates to the previously
identified P2prfA promoter, was identified in the wild type strain, but not in the ∆sigB
strain, however, the RACE-PCR band for the proposed P2prfA transcriptional start site
was weak and diffuse (Fig. 3.5A; bottom arrow). Therefore, RACE-PCR was
repeated using RNA from two strains bearing mutations that were created to eliminate
(i) transcription initiation from the σA-dependent P1prfA promoter in both strains, as
PrfA activity (plcA/prfA)
135
10
1
0.1
log phase
NaCl stationary vacuole
stress
phase
cytosol
Figure 3.4: Activity of PrfA in L. monocytogenes grown in different conditions.
PrfA activity is defined as the ratio of normalized plcA cDNA copy numbers to
normalized (total) prfA cDNA copy numbers.
136
well as (ii) σB-dependent transcription in one of the strains. Specifically, each strain
had a deletion in the -10 region of P1prfA (∆P1-10prfA; DP-L1956); one strain had a
second mutation (∆sigB ∆P1-10prfA; FSL B2-002). As expected, the larger RACEPCR product, corresponding to the P1prfA transcript, was not observed in either strain,
while the smaller product, corresponding to the P2prfA transcript, which was present
only in the ∆P1-10prfA strain (Fig. 3.5B), was more abundant than it had been in the
10403S wild type strain (Fig. 3.5A, bottom arrow). These results confirm that P2prfA
is σB-dependent under the conditions tested. Further, elimination of the -10 region
from the predicted σA-dependent P1prfA site prevented initiation of transcription from
P1prfA. The RACE-PCR results identified a consensus σB promoter sequence
(5’GTTA – 16nt – GGGTAT3’) 9 bp upstream of the P2prfA 5’ transcript end,
coinciding with the previously described P2prfA promoter (21). We also detected an
unexpected third RACE-PCR band that mapped between P2prfA and P1prfA (Fig.
3.5A; middle arrow), however, no putative promoter site for any recognized sigma
factor in L. monocytogenes (σA, σB, σH, or σ54) could be identified upstream of the 5’
end corresponding to this RACE-PCR product. This third RACE-PCR product was
only identified in the 10403S wild type prfA promoter background and not in either of
the ∆P1-10prfA strains. We propose that this signal either represents an artifact due to
incomplete reverse transcription of the P1prfA transcript or a P1prfA transcript
degradation product.
Expression of prfA from individual promoters. While RACE-PCR allows
for qualitative determination of transcription start sites, it does not allow accurate
quantitation of transcript levels, especially when different size RACE-PCR products
compete for amplification in a single RACE-PCR reaction, as in our experiments. To
allow quantification of prfA transcript levels, TaqMan primer and probe sets were
designed and used to measure relative transcription originating from each of the
137
A
B
1
2
3
4
5
1
2
3
4
5
C
P1►
CTTTTGCGAAATCAAAATTTGTATAATAAAATCCTATATGTAAAAAACATCATTTAGCGTGACTTTCTT
?►
P2►_
TCAACAGCTAACAATTGTTGTTACTGCCTAATGTTTTTAGGGTATTTTAAAAAAGGGCGATA-N22-ATG
Figure 3.5: RACE-PCR of the prfA promoter region.
A. Lanes 1-5 correspond to the DNA marker, wild type negative control, wild type
positive reaction, ∆sigB positive reaction, and ∆sigB negative control, respectively.
B. Lanes 1-5 correspond to the DNA marker, ∆P1-10prfA negative control, ∆P110prfA positive reaction, ∆P1-10prfA ∆sigB positive reaction, and ∆P1-10prfA ∆sigB
negative control, respectively.
C. DNA sequence of the prfA promoter region. The σA-dependent P1prfA promoter is
single underlined. At P2prfA, the σB-dependent promoter is double underlined, and
the proposed σA-dependent promoter is marked with wavy lines. Triangles indicate
transcriptional start sites. The unidentified reverse transcript is labeled with a question
mark (see text).
138
Figure 3.6: Location of TaqMan primers and probes in the plcA-prfA region.
Transcriptional start sites and terminators are indicated by bent arrows and stem loops,
respectively. Inverted arrows around a bar indicate locations of TaqMan primers and
probes.
139
promoters upstream of prfA (Fig. 3.6). A “plcA-readthrough” primer-probe set (Table
3.2 and Fig. 3.6, probe 2) was designed to detect only plcA readthrough transcription;
this probe specifically detects transcripts that originate from the plcA promoter but that
do not terminate at the predicted transcriptional terminator downstream of plcA (31).
A “prfA-P1” primer-probe set (Table 3.2 and Fig. 3.6, probe 3) was designed to detect
transcripts originating from P1prfA as well as plcA terminator readthrough transcripts.
To quantify levels of transcripts specifically originating from P1prfA, the plcAreadthrough transcript levels (detected by the “plcA-readthrough” primer-probe set)
were subtracted from transcript levels detected by the “prfA-P1” primer-probe set.
Transcript levels detected by the “prfA-CDS” primer-probe set (Table 3.2 and
Fig. 3.6, probe 4) represent all prfA transcripts regardless of origin; subtracting the
transcript levels detected by the “prfA-P1” primer-probe set from the transcript levels
detected by the “prfA-CDS” primer-probe set thus allowed us to determine transcript
levels originating from P2prfA (Fig. 3.6).
Overall, P1prfA cDNA copy numbers and plcA readthrough cDNA copy
numbers did not differ between wild type and ∆sigB strains under any of the extra- or
intracellular conditions tested (Fig. 3.7). On the other hand, P2prfA transcript levels
were 2 times higher in the wild type as compared to the ∆sigB strain for cells exposed
to 0.3M NaCl stress (significant at p=0.0276) and in cells grown to stationary phase
(not significant; Fig. 3.7A and C). No difference in P2prfA transcript levels between
the wild type and ∆sigB mutant strains were detected in bacteria arrested in the
vacuole or the cytosol (Fig. 3.7B and D). Transcription of P1prfA ranged from 16.8 –
30.0% of total prfA transcription (Table 3.4). Absolute expression from P1prfA
ranged from 0.0097 normalized copies to 0.1144 in the wild type and from 0.0046 to
0.0849 in the ∆sigB strain, but the differences were not statistically significant.
Transcript levels corresponding to readthrough transcription from the plcA promoter
140
were low in all conditions, ranging from 0.36% of total prfA transcript levels in nonstressed, broth-grown log phase cells to 2.92% in the intravacuolar bacteria (Table
3.4). By comparison, transcript levels originating from P2prfA ranged from 69.67%
(in wild type, log phase cells) to 82.43% (wild type, NaCl-stressed cells) of total prfA
transcript levels.
DISCUSSION
To better understand the contributions of the transcriptional regulators PrfA
and σB to L. monocytogenes pathogenesis, we determined transcript levels of selected
σB- and PrfA-dependent genes under conditions similar to critical stages of infection
in a mammalian host, including exposure to extracellular stress conditions and L.
monocytogenes presence in the vacuole or the cytosol of infected host cells. We
hypothesized that L. monocytogenes σB plays a critical role at the gastrointestinal hostpathogen interface since σB-dependent gene expression is activated under stress
conditions simulating the gastrointestinal environment and specific genes contributing
to gastrointestinal pathogenesis (e.g., bsh, inlA) are σB-dependent. Our results reveal
new insights into the relationship between σB and PrfA activity in L. monocytogenes,
demonstrating that (i) PrfA is activated specifically during intracellular growth, while
σB is activated primarily during environmental stress, and (ii) the partially σBdependent P2prfA promoter contributes the majority of prfA transcript levels in both
intra- and extracellular bacteria. We propose a model of L. monocytogenes gene
expression at the gastrointestinal host-pathogen interface, which involves a switch
from predominantly σB-dependent expression of genes required for gastrointestinal
survival to PrfA-dependent expression of genes required for intracellular survival,
spread, and multiplication.
0.5
0.15
0.1
readthrough
P1tx
P2tx
0.05
0
∆ sigB normalized copy no.
log phase
NaCl
stress
stationary
phase
0.2
0.15
0.1
0.05
0
log phase
NaCl
stress
stationary
phase
wt normalized copy no.
0.2
∆ sigB normalized copy no.
wt normalized copy no.
141
0.4
0.3
0.2
0.1
0
vacuole
cytosol
vacuole
cytosol
0.5
0.4
0.3
0.2
0.1
0
Figure 3.7: Quantification of prfA transcription from its three upstream
promoters. Abbreviations: readthrough, plcA readthrough transcription; P1tx,
P1prfA-initiated transcription; P2tx, P2prfA-initiated transcription.
142
Table 3.4: Origins of prfA transcription and their contributions to total prfA
transcript level
Percent of total prfA transcript levels
Condition
plcA readthrougha
P1prfAb
P2prfAc
log
0.36%
29.97%
69.67%
salt
0.25%
17.32%
82.43%
stationary
1.52%
20.99%
77.49%
vacuole
2.92%
16.83%
80.25%
cytoplasm
2.31%
21.41%
76.29%
a
calculated as (“plcA-readthrough” cDNA copy ÷ “prfA-CDS” cDNA copy) × 100
b
calculated as [(“prfA-P1” cDNA copy – “plcA-readthrough” cDNA copy) ÷ “prfA-
CDS” cDNA copy] × 100
c
calculated as [(“prfA-CDS” cDNA copy – “prfA-P1” cDNA copy) ÷ “prfA-CDS”
cDNA copy] × 100
143
PrfA is activated specifically during intracellular growth, while σB is
activated primarily during environmental stress. Our data show that
environmental stress conditions (e.g., exposure to 0.3M NaCl and growth to stationary
phase) induce σB activity as indicated by enhanced transcription of the σB-dependent
genes opuCA and gadA. Our results are consistent with previous reports that have
shown stress induction of σB activity in L. monocytogenes (19, 49, 50) and in Bacillus
subtilis (1, 6, 29), however, previous experiments characterizing induction of σB
activity in L. monocytogenes were conducted at 30°C or lower (2, 50). As L.
monocytogenes is a mammalian foodborne pathogen, one objective of this work was to
confirm σB activity induction under extracellular stress conditions at 37°C. Secondly,
to characterize relative σB activity in intracellular L. monocytogenes, we sought to
generate reference values for transcript levels of σB-dependent genes for extracellular
L. monocytogenes at 37°C in the presence and absence of conditions previously shown
to induce σB activity. We confirmed that both opuCA and gadA (12) are σB-dependent
in L. monocytogenes grown at 37°C. σB activity (as determined by measurement of
gadA and opuCA cDNA copy numbers) in intracellular L. monocytogenes arrested in
either the Caco-2 host cell vacuole or the host cell cytosol was higher than in
unstressed, exponentially growing bacteria, but lower than in bacteria exposed to
extracellular environmental stresses. The fact that transcript levels of σB-dependent
genes are lower in vacuolar bacteria than in bacteria exposed to extracellular stress
conditions may seem surprising, considering the well-documented occurrence of
stressful conditions in the vacuole (e.g., low pH, oxidative stress) that have been
shown to activate σB or to affect survival of a sigB mutant (10, 17, 29, 50). Bubert et
al. (7) showed previously that L. monocytogenes virulence gene expression differs in
professional versus non-professional phagocytes. Hence, it is possible that the
intravacuolar environment of professional phagocytes represents a more stressful
144
environment for intracellular bacterial pathogens, which, therefore, could lead to
greater activation of the stress responsive alternative sigma factor σB than in than
Caco-2 cell vacuoles. However, we chose to evaluate σB- and PrfA-dependent gene
expression in infected intestinal epithelial cells specifically to explore interactions
between stress response and virulence gene regulation under model conditions
stimulating the gastrointestinal host-pathogen interface. Future experiments with
professional macrophages will be needed to further characterize the role of σB for
survival and gene expression inside the host cell vacuole.
prfA and plcA transcript levels were independent of σB and showed expression
patterns distinct from those observed for σB-dependent genes. Although neither prfA
nor plcA transcript levels increased after exposure of log phase cells to 0.3M NaCl,
transcript levels for these two genes were higher in stationary phase cells as compared
to log phase cells, consistent with previous results that showed that PrfA activity in
extracellular L. monocytogenes is highest in stationary phase bacteria (48). Both prfA
and plcA transcript levels were highly significantly elevated in bacteria arrested in
Caco-2 cell vacuoles or in cytosol as compared to log phase cells, consistent with
previous reports that showed an increase in PrfA activity upon L. monocytogenes
interaction with host cells (7, 26, 33, 43). While we found similar plcA transcript
levels in bacteria present in the host vacuole as in the cytosol, Bubert et al. (7)
previously observed decreased expression of plcA after escape from the vacuole.
Differences between the studies could result from use of different bacterial strains and
mammalian cell lines. While it has previously been clearly demonstrated that PrfA
can be present in active and inactive forms (42, 44), further analysis of plcA and prfA
transcript levels measured in our study showed that increased transcript levels of the
PrfA-dependent plcA in intracellular L. monocytogenes result from both an increase in
prfA transcription and an increase in PrfA activity (Figs. 3.3 and 3.4). Our results
145
extend findings from previous studies that provided evidence for induction of
increased PrfA activity and for enhanced prfA transcription in intracellular L.
monocytogenes (7, 43) by showing that both increased prfA transcription and PrfA
activation contribute to the high level of activation of PrfA-dependent virulence genes
observed in L. monocytogenes upon host cell entry.
Based on the σB and PrfA activity profiles observed in this and other studies
(50), we propose that L. monocytogenes infection events at the gastrointestinal
interface involve a switch from σB-mediated expression of stress response and selected
virulence genes, triggered by stressful environmental conditions encountered inside
the gastrointestinal tract (e.g., low pH, high osmolarity), to PrfA-mediated expression
of virulence genes required for intracellular survival and multiplication (e.g., hly, plcA,
and actA). This switch may by be stimulated by L. monocytogenes attachment to host
epithelial cells, as Renzoni et al. (43) demonstrated an increase in the amount of PrfA
following 30 minutes of L. monocytogenes adherence to host cells. σB-mediated
activation of gene expression in the gastrointestinal environment appears to facilitate
both L. monocytogenes survival of gastrointestinal environmental stress conditions
(e.g. by regulating expression of gadA, an acid resistance gene, or bsh, which encodes
a bile salt hydrolase) as well as invasion of human gastrointestinal epithelial cells [by
regulating expression of inlA (24, 25, 50)].
The partially σB-dependent P2prfA promoter contributes the majority of
prfA transcript levels in both intra- and extracellular bacteria. Our data show that
the majority of prfA transcripts originate from the P2prfA promoter, which has
previously been shown to be at least partially σB-dependent (40, 46). While deletion
of sigB resulted in reduced P2prfA expression in L. monocytogenes exposed to 0.3M
NaCl, a condition that highly induces σB activity, overall prfA levels did not differ
significantly between the wild type and ∆sigB L. monocytogenes strains. Our data not
146
only confirm that P2prfA is at least partially σB-dependent, but are also consistent with
previous functional studies that have shown that L. monocytogenes can compensate for
loss of transcription at P2prfA (21, 34). Specifically, while previous studies found that
∆P2prfA ∆P1prfA and ∆sigB ∆P1prfA double mutants had reduced virulenceassociated characteristics (plaque size, intracellular growth, and hemolysis) compared
to wild type, mutations in either sigB or P2prfA alone had little to no effect on these
characteristics (34). Our data also suggest that compensation for loss of
B
-dependent
P2prfA transcription involves σB-independent transcription at either P2prfA or at
another promoter that either overlaps with P2prfA or is in close proximity to P2prfA,
as transcript levels at this putative promoter were not completely abolished in a ∆sigB
mutant (Fig. 3.7C and D). Taken together, our data support the existence of a third
promoter in the region upstream of prfA. Rauch et al. (40) proposed that P2prfA is
comprised of overlapping σA- and σB-dependent promoters, based on results from an
in vitro transcription system. The diffuse 5’ transcript end for the P2prfA transcript
that was identified by our RACE-PCR analyses in the wild type 10403S strain (Fig.
3.5A) is also consistent with the presence of multiple 5’ ends generated from
overlapping promoter sequences in the P2prfA region. Interestingly, Freitag and
Portnoy (21) previously described a PrfA box upstream of P2prfA. Based on all of
these observations, we propose a working model of P2prfA transcriptional regulation
that includes at least partial σB-dependent transcriptional activation in the region
upstream of prfA under environmental stress conditions, when σB is active and when
PrfA is not activated. When Listeria invades host cells, we hypothesize that the
resulting high level of active PrfA may allow positive regulation at a promoter
upstream of prfA, perhaps acting at the PrfA box upstream of P2prfA. Activation of
this proposed promoter appears to enable an organism to overcome the loss of σB.
While further experiments using in vitro transcription systems and purified σA, σB, and
147
PrfA will be necessary to further clarify regulation of transcription at P2prfA, it is
clear that this promoter region plays an important role in regulating prfA transcription
at the transition between environmental and intracellular stress conditions.
Transcription initiated at P1prfA contributed 16.8 – 30.0% of total prfA
transcripts under the conditions tested. Readthrough transcription from PplcA
contributed only a minor fraction of total prfA expression, as previously suggested by
Schwab et al. (46). The relative contribution of plcA readthrough to total prfA
transcript was greater in intravacuolar bacteria than in log phase extracellular bacteria,
however. While our results support the previous conclusion that readthrough
transcription from the plcA promoter aids in cell-to-cell spread (8), our quantitative
estimates contrast with another report, which suggested that increased readthrough at
the plcA promoter is largely responsible for the increase in prfA transcription observed
upon infection (43). Conclusions from the previous study were drawn by comparing
western blot measurements of PrfA protein levels in an L. monocytogenes wild type
strain and in a transposon mutant (in which plcA readthrough transcription was
predicted to be abolished) that had been exposed to host cell extracts (42). This
approach was both indirect and semi-quantitative. Further, use of a transposon
insertion may disrupt or introduce unidentified and unexpected regulatory elements,
producing unintended effects on gene expression. We conclude that while increased
plcA readthrough transcription does contribute to increased prfA transcription in
intracellular L. monocytogenes, the overall contribution of readthrough transcription to
prfA transcript levels is minimal.
Conclusions. We propose a model of L. monocytogenes gene expression at the
gastrointestinal host-pathogen interface that involves a switch from predominantly σBdependent expression of genes required for gastrointestinal survival to PrfA-dependent
expression of genes required for intracellular survival, multiplication, and spread. It is
148
possible that σB-dependent expression at P2prfA following stress exposure primes prfA
transcription during the transition from gastrointestinal extracellular survival to host
cell invasion. The resulting availability of PrfA upon L. monocytogenes entry into the
intracellular environment could enhance PrfA-dependent expression of virulence
genes such as hly and actA, which is required for L. monocytogenes survival. Our
model is consistent with emerging evidence that genes contributing to L.
monocytogenes virulence and intra-host survival can be grouped into categories that
are regulated by either PrfA, σB, or σB and PrfA (Fig. 3.8), with σB-dependent (Class
B) genes involved in gastrointestinal survival, PrfA and σB-dependent (Class C) genes
involved in functions at the gastrointestinal interface and PrfA-dependent (Class A)
genes involved in intracellular survival, spread, and multiplication. Virulence genes
dependent exclusively on PrfA for their expression include plcA, actA, and hly (Class
A genes, Fig. 3.8). Genes with potential functions during infection, which are
regulated by σB and appear to contribute to survival under host-associated stress
conditions such as those encountered in the gastrointestinal tract, include opuCA (47)
and hfq (11) (Class B genes, Fig. 3.8). Finally, L. monocytogenes genes with a role in
virulence that are regulated by both σB and PrfA, either simultaneously or
independently, include inlA (24, 28), encoding internalin-A, which is required for
invasion of intestinal epithelial cells, and bsh (15, 24). In addition, further regulation
occurs through PrfA and σB auto-regulation (2, 21, 52) and σB-dependent transcription
of PrfA, further supporting the importance of an interactive PrfA and σB regulatory
network in L. monocytogenes virulence.
149
σB
PrfA
Class A
plcA
hly
actA
Class B
Class C
inlA
bsh
opuCA
hfq
Figure 3.8: Model of σB- and PrfA-mediated regulation of virulence genes. Class
A genes are activated only by PrfA, Class B genes only by σB, and Class C genes by
both. Arrows indicate activation by σB at the P2prfA promoter and auto-regulation by
each factor.
150
ACKNOWLEDGEMENTS
We would like to thank H. Kim and A. Roberts for creation of mutant strains
FSL K4-001 and FSL R3-001. Caco-2 cells were kindly provided by H. Marquis.
Thanks also go to D. Fink and K. Nightingale for assistance with statistical analyses.
This work was supported in part by the National Institutes of Health Award No. RO1AI052151-01A1 (to K. J. B.).
151
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CHAPTER FOUR:
THE PUTATIVE GLUTATHIONE REDUCTASE GENE LMO1433 OF LISTERIA
MONOCYTOGENES IS σB-DEPENDENT
ABSTRACT
A gene (lmo1433) encoding a putative stress response protein, glutathione
reductase, was found to be regulated by the alternative sigma factor σB in Listeria
monocytogenes. Expression of lmo1433 was induced in stationary phase and during
osmotic stress in a wild type but not a ∆sigB strain. A non-polar deletion in lmo1433
did not affect total glutathione reductase activity, oxidative stress survival, or
virulence in a tissue culture model. A search of the genome for homologous
sequences indicated that another gene may encode a similar enzyme, thus masking the
effect of the lmo1433 deletion.
INTRODUCTION
Listeria monocytogenes is a food borne bacterium capable of causing a range
of disease symptoms from gastroenteritis to septicemia and encephalitis. L.
monocytogenes is also able to withstand many environmental stresses including low
pH and high salt concentrations (2, 9, 10, 23). The resistance of L. monocytogenes to
stress aids in survival in the gastrointestinal tract of infected host organisms, thus
contributing to its ability to cause disease. Central to the capacity of L.
monocytogenes to survive environmental stress is the alternative sigma factor σB (2, 9,
10, 23). Activity of σB is induced under several environmental stresses and upon entry
into stationary phase (2). Once active, σB directs transcription of many genes
important for stress survival (15).
Previously, we identified a number of σB-dependent genes using a combination
approach involving bioinformatics and microarrays (15). One of these newly
discovered σB-dependent genes, lmo1433, is predicted to encode glutathione
158
159
reductase, an enzyme that aids in survival of oxidative stress. Glutathione is an
important molecule for keeping a reduced state inside the cell. Glutathione reductase
catalyzes the reduction of glutathione disulfide to glutathione while oxidizing NADPH
to NADP+ (6). In this report, we demonstrate quantitatively the regulation of lmo1433
by σB, and show that deletion of lmo1433 does not have a pronounced effect on stress
survival or virulence.
MATERIALS AND METHODS
Bacterial strains and growth conditions. All experiments were performed
with L. monocytogenes strain 10403S (4) or derivatives. Strain FSL A1-254 (∆sigB)
was described previously (23). Strains FSL F5-002 (∆lmo1433) and FSL F5-003
(∆lmo1433 ∆sigB) were created as described below. Bacteria were grown at 37°C on
BHI agar plates or in Brain Heart Infusion (BHI) broth (Difco/BD, Sparks, MD) with
shaking at 250 rpm. Unless otherwise noted, BHI broth cultures were inoculated from
single colonies and grown overnight, sub-cultured 1:100 in fresh BHI, grown to OD600
0.4, sub-cultured again 1:100 in fresh BHI, and grown to exponential phase (OD600
0.4), early stationary phase (OD600 2.0), or late stationary phase (12 hours after the
second sub-culture).
Genetic manipulations. A non-polar internal deletion mutant allele of
lmo1433 was created in the E. coli-L. monocytogenes shuttle vector pKSV7 by SOE
(splicing by overlap extension) PCR as previously described (23) and was introduced
into L. monocytogenes 10403S or FSL A1-254 by allelic exchange mutagenesis.
Primers SOE-A (5’-AAACTGCAGATCATTTCACGCGGCTTTATCTAC-3’) and
SOE-B2 (5’-GGGTAGGCAAAAATAACAGATAACCCTGCTGCCTGTGCTTCA3’) were used to create a 5’ flanking fragment and primers SOE-C (5’ATCTGTTATTTTTGCCTACCC-3’) and SOE-D (5’CGCGGATCCATCTGCGGAATCTTCATAGTTA-3’) were used to create a 3’
160
flanking fragment. Subsequent PCR amplification of the initial SOE PCR products
with SOE-A and SOE-D created a 785 bp fragment with a 1200 bp in-frame deletion
of lmo1433. This fragment was purified with the QIAquick PCR Purification kit
(Qiagen, Valencia, CA) and cloned into pKSV7 to create pSF07. pSF07 was
transformed into E. coli One-Shot cells (Invitrogen, Carlsbad, CA) and subsequently
electroporated into L. monocytogenes 10403S and FSL A1-254. Transformants were
selected on chloramphenicol plates and chromosomal integration was directed as
previously described (23). Allelic exchange mutagenesis was confirmed by PCR
amplification of the mutant allele and direct sequencing of the PCR product.
Quantitative RT-PCR. RNA was isolated from L. monocytogenes 10403S
and FSL A1-254 cultures grown to exponential phase, with or without an added 0.3 M
NaCl stress, or to early stationary phase as described previously (15). Exponential
phase NaCl-stressed and non-stressed cells were prepared and collected in parallel.
One culture of each strain was divided into two 4 ml aliquots and centrifuged 3 min at
3400 x g. Cell pellets were resuspended in 2 ml prewarmed BHI broth. Two ml of
prewarmed BHI broth or BHI plus 0.6 M NaCl was added to the cultures and each was
incubated for 7 min at 37°C with shaking. Stationary phase cells were grown to OD600
O.8 and then for one additional hour. For RNA isolation, 4 ml of each culture
(exponential phase, stationary phase or NaCl-stressed exponential phase cells) was
added to 8 ml of RNA Protect Bacteria Reagent (Qiagen), vortexed briefly, incubated
at room temperature for 5 minutes, and centrifuged 3 min at 3400 x g. Cell pellets
were frozen at -80°C. RNA was isolated from thawed cell pellets with the RNeasy kit
(Qiagen). Two consecutive DNase treatments were performed during purification
with an on-column DNase kit (Qiagen) according to the manufacturer’s protocol.
Purified RNA was ethanol precipitated and stored at -20°C. Chromosomal DNA was
isolated from overnight cultures of L. monocytogenes by the procedure of Flamm et al.
161
(11) and used for qRT-PCR assay standard curves. Quantitative RT-PCR was
performed in 25 µl reactions as previously described (15). Reactions were performed
in duplicate on three independent RNA preparations. TaqMan primers and probes
used were MJK04 (lmo1433-F; 5’-GGAATGGGAATCTTGGAAGCTA-3’), MJK05
(lmo1433-R; 5’-TGTGCCAGAAAGTCGTTTGG-3’), and MJK06 (lmo1433-probe;
5’ FAM-TCAATCCCAGCTTC-MGB 3’). For data normalization, the housekeeping
genes gap and rpoB were also quantified in each sample using primers and probes
previously described (21, 22).
Oxidative stress survival assay. Oxidative stress resistance of the wild-type
and mutant strains was assessed using the oxidative agent cumene hydroperoxide
(CHP) (Aldrich, St. Louis, MO). CHP survival assays were conducted as described by
Ferreira et al. (9). Briefly, 100 µl of 140 mM CHP diluted in dimethyl sulfoxide
(DMSO; MP Biomedicals, Aurora, OH), was added to 900-µl portions of cultures
grown to exponential phase, early stationary phase, or late stationary phase (as
described above) yielding a final CHP concentration of 14 mM. Control cultures
received 100 µl of dimethyl sulfoxide. All tubes were then incubated for 15 min at
37°C with shaking. Cell viability was assessed by standard plate counting on BHI
agar plates. Data were collected from at least two independent experiments.
Glutathione reductase activity assay. Glutathione reductase activity was
determined in all strains using the Trevigen (Gaithersburg, MD) glutathione reductase
assay kit. Briefly, 10 ml of cells grown to either exponential phase or early stationary
phase were collected by centrifugation, washed in 10 ml PBS, and resuspended in 3 ml
homogenization buffer. Cells were then lysed by sonication on ice at 18 W for five 30
second bursts. Cell debris was pelleted by centrifugation and the supernatant
collected. Glutathione reductase activity was determined from the reduction in
absorbance at 340 nm using 6220 M-1cm-1 as the molar extinction coefficient of
162
NADPH. Results are expressed per total protein in the sample, as determined using
the Bio-Rad (Hercules, CA) total protein assay.
Tissue culture virulence assay. A previously described plaque assay (13)
was used to characterize infective ability of all strains. Briefly, mouse fibroblast L2
cells were grown to confluence in 2 ml of DMEM containing 10% fetal bovine serum
in six-well cell culture plates. Bacteria were grown overnight at 30°C in BHI broth,
pelleted, and resuspended in PBS. For each bacterial strain tested, one well was
infected with 1 x 105 CFU and one well was infected with 3 x 104 CFU. After a 1hour incubation at 37°C, the cell monolayers were washed three times with PBS and
overlaid with 3 ml of DMEM containing 10 µg/ml gentamicin and 1.4% Bacto agar
(Difco, Sparks, MD). After 3 days of incubation at 37°C, a second 2-ml overlay of
DMEM containing 6% neutral red solution and 1.4% Bacto agar was added. After a
final day of incubation, plates were imaged using an Epson Perfection 1650 digital
scanner (Epson, Long Beach, CA) and plaque areas were measured using SigmaScan
Pro v.5.0 software (Statistical Solutions, Saugus, MA).
RESULTS AND DISCUSSION
Expression of lmo1433 is σB-dependent. In a previous report, we
demonstrated that lmo1433 is expressed via σB (15). Here, we used quantitative
reverse transcription-PCR (qRT-PCR) to quantify the transcription of lmo1433 in both
a wild type and a ∆sigB strain under conditions known to activate σB. Both strains
grown to exponential phase showed low lmo1433 transcript levels. Transcript levels
in the wild type increased 4.0-fold when the cells were exposed to 0.3M NaCl and 5.3fold when grown to early stationary phase (Fig. 4.1). These increases were significant
at α=0.05 as determined by one-way ANOVA with Tukey’s correction. Transcript
levels in the ∆sigB strain were statistically indistinguishable among all three
conditions. In addition, the differences in transcript levels between the wild type and
163
normalized copy no.
0.01
B,b
B,b
0.001
A,a
A,a
A,a
A,a
0.0001
Exponential
phase
NaCl stress
Stationary
phase
Figure 4.1: Expression of lmo1433. Error bars indicate standard deviations. Bars
with different capital letters indicate significantly different copy numbers between the
two strains within a given stress. Bars with different lowercase letters indicate
significantly different copy numbers between conditions for a given strain.
164
∆sigB strains were statistically significant under osmotic stress and stationary phase,
but not during exponential growth (p<0.01; t test). Thus, lmo1433 is induced under
conditions known to activate σB (2). This confirms our initial observations about the
σB-dependence of lmo1433 (15), and reemphasizes the paradigm that σB activates
genes involved in stress resistance.
sigB, but not lmo1433, is required for full resistance to oxidative stress. To
assess the contributions of lmo1433 to the stress resistant phenotype of L.
monocytogenes, we created a non-polar deletion within the coding region of lmo1433
in both wild type and ∆sigB backgrounds. We then determined the ability of the two
mutant strains, along with wild type and ∆sigB strains to survive oxidative stress using
the oxidative agent cumene hydroperoxide (CHP). Cells were grown to exponential
phase, early stationary phase, or late stationary phase and exposed to CHP for 15
minutes (Fig. 4.2). Exponential phase cells did not survive in high enough numbers to
be detected (data not shown). In early and late stationary phase, both strains with the
wild type sigB allele showed a higher percent survival than the two strains harboring
the sigB deletion. We observed a 2.2-2.7 log reduction in survival of wild type cells,
which is in agreement with previously reported data (7, 9). Likewise, ∆lmo1433
displayed a 1.6-2.7 log reduction in survival. Deletion of lmo1433 did not have an
effect on CHP survival, as similar numbers of the mutant survived as wild type, and
∆sigB had similar survival rates to the ∆sigB ∆lmo1433 double mutant.
Li et al. (17) found a direct correlation between oxidative stress resistance and
glutathione availability, but not necessarily glutathione reductase activity, in
Lactococcus lactis. L. monocytogenes has been shown to accumulate glutathione,
although at low levels, which may be one reason for the lack of detectable difference
in survival among the strains (19). It was reported previously that glutathione
reductase mutants of Escherichia coli and Streptococcus mutans are also not affected
165
Early Stationary Phase
Survival (CFU/ml)
1.00E+10
1.00E+08
1.00E+06
1.00E+04
1.00E+02
1.00E+00
wild type
sigB
lmo1433
sigB lmo1433
Late Stationary Phase
Survival (CFU/ml)
1.00E+10
1.00E+08
1.00E+06
1.00E+04
1.00E+02
1.00E+00
wild type
sigB
lmo1433
sigB lmo1433
Figure 4.2: Survival of four L. monocytogenes strains after exposure to CHP.
Values in early stationary phase are the average of two independent experiments, and
error bars represent the range. Values in late stationary phase are the average of three
independent experiments, and error bars represent the standard deviation.
166
in their resistance to CHP and other oxidative agents (3, 24). It may be the case that
the major stress conferred by CHP is not due to oxygen radicals alone. Indeed,
Bacillus subtilis has several systems for dealing with peroxide stress, and they are
active under different conditions. Some, such as aphC and mrgA, are repressed by the
PerR regulator and can be induced by organic hydroperoxides and H2O2 (8, 18).
However, ohrA is induced only by organic hydroperoxides (12). Thus, as in B.
subtilis, L. monocytogenes may have multiple proteins for resistance to oxidative
stress, and perhaps an organic-specific peroxiredoxin is more important than lmo1433
for resistance to CHP.
In both wild type and ∆lmo1433, early stationary phase cells showed decreased
survival when compared to late stationary phase cells. However, neither ∆sigB nor
∆sigB ∆lmo1433 showed much difference in survival between the two growth stages.
It seems likely that the difference seen in the two strains with an intact sigB is due to a
higher level of σB activity in late stationary phase than early stationary phase. Many
of the peroxide resistance systems in B. subtilis have two components, one of which is
regulated by σB, and the other by a specific regulator. For example, katA, and mrgA
are regulated by PerR (5, 8), allowing stress-specific inducible expression in
conditions without σB, while their counterparts katX, and dps are expressed via σB
during stationary phase or general stress (1, 20).
Glutathione reductase activity is not affected by the absence of sigB or
lmo1433. The inability to detect any effect of lmo1433 on oxidative stress survival
could mean that Lmo1433 is not the major factor in oxidative stress resistance, but
does not rule out the possibility that lmo1433 encodes a functional glutathione
reductase. We therefore determined the glutathione reductase activity in the same four
strains at two different growth stages, exponential phase and early stationary phase.
We performed an assay that utilizes the decrease in absorbance that occurs when
167
NADPH is oxidized during reduction of glutathione disulfide. All four strains showed
similar levels of glutathione reductase activity when corrected for total protein, during
either growth phase (Table 4.1). In addition, there was no significant difference
between glutathione reductase activity levels in the two growth stages for any of the
four strains. Thus, it seems possible that glutathione reductase is encoded elsewhere
in the genome, perhaps in addition to lmo1433. Interestingly, the level of activity
detected in these L. monocytogenes strains is on the order of 20 times higher than that
of the highest activity reported in a number of Lactococcus lactis strains (17). It may
be the case that glutathione is protective for types of stress other than that caused by
oxygen radicals, and it would be interesting to see if L. monocytogenes is particularly
resistant to such stresses.
Neither sigB nor lmo1433 are required for virulence in a tissue culture
model of infection. L. monocytogenes likely encounters oxidative stress when inside
the host vacuole during intracellular infection (14). To test if loss of lmo1433 has an
effect on survival within host cells, we performed a tissue culture-based plaque assay.
The four L. monocytogenes strains were independently added to mouse L2 cell
monolayers and incubated at 37°C. As L. monocytogenes cells multiply and spread
cell to cell, they leave a plaque in the monolayer. Infective ability can be measured as
both the number of plaques formed and the size of the plaques. None of the four
strains differed in their ability to cause plaques or the size of the plaques formed (Fig.
4.3). In following with the other phenotypic assays described in this report, deletion
of lmo1433 appears not to have an affect on survival of oxidative stress as presented
inside host cells. In addition, σB does not seem to have a role in plaquing ability on
mouse L2 cells. This is in agreement with previous studies from our laboratory
168
Table 4.1: Glutathione reductase activity in four L. monocytogenes strains
mU per µg total protein (± S.D.)a
Strain
OD600 0.4
OD600 2.0
wild type
0.11 (±0.028)
0.15 (±0.013)
∆sigB
0.12 (±0.017)
0.14 (±0.016)
∆lmo1433
0.09 (±0.036)
0.14 (±0.020)
∆sigB ∆lmo1433
0.10 (±0.033)
0.13 (±0.021)
a
Glutathione reductase activity values are the average of two independent experiments
done in duplicate.
169
Figure 4.3: Plaque assays to determine virulence of four L. monocytogenes
strains. Rows show, from top to bottom, representative infections for wild type
(10403S), ∆sigB (FSL A1-254), ∆lmo1433 (FSL F5-002), and ∆sigB ∆lmo1433 (FSL
F5-003). Two independent experiments were performed in quadruplicate for each
strain.
170
showing that σB is not highly active during intracellular infection (16) and that
deletion of sigB does not greatly affect L. monocytogenes virulence in mice (23).
Homologous genes may provide redundancy and account for lack of
phenotype of ∆lmo1433. Due to the lack of observable phenotypes in the ∆lmo1433
strains, we attempted to identify in the L. monocytogenes genome potential genes that
may encode similar enzymes that could compensate for the loss of glutathione
reductase activity. Using the BLAST2 program on the ListiList web server
(http://genolist.pasteur.fr/ListiList/), we searched for protein sequences similar to that
encoded by lmo1433. The most similar coding region, lmo0906, potentially encodes a
glutathione reductase that is 47% similar to the protein encoded by lmo1433. This
gene is actually more similar to other glutathione reductase genes than is lmo1433
(89% vs. 62%). No potential σB-dependent promoter sequence could be found
upstream of lmo0906. If this gene encodes another glutathione reductase that is not
regulated by σB, it could possibly be compensating for any loss of lmo1433 expression
in either of the ∆sigB or ∆lmo1433 single or double-mutant strains. More detailed
biochemical studies would need to be performed to definitely conclude the functions
of both of these proteins.
ACKNOWLEDGEMENTS
We would like to thank Juliane Ollinger for assistance with the qRT-PCR and
Esther Fortes for performing plaque assays.
171
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Chaturongakul, S., and K. J. Boor. 2004. RsbT and RsbV contribute to σB -
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Ferreira, A., D. Sue, C. P. O'Byrne, and K. J. Boor. 2003. Role of Listeria
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Gray, M. J., R. N. Zadoks, E. D. Fortes, B. Dogan, S. Cai, Y. Chen, V. N.
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Kazmierczak, M. J., and M. Wiedmann. 2005. Contributions of Listeria
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CHAPTER FIVE:
CONCLUSIONS
As described in chapters 2 and 3, I identified stress response and virulence
genes that are regulated by σB, and demonstrated the temporal regulation by σB and
PrfA of genes important for infection. While this work is largely conclusive in its own
right, chapter 4 presents preliminary work characterizing a putative stress response
gene, lmo1433.
The predicted protein sequence encoded by lmo1433 bears similarity to
glutathione reductases, which are used by some bacteria to counteract oxidative stress.
Deletion of lmo1433, however, did not affect the organism’s ability to survive
exposure to the oxidative agent cumene hydroperoxide (CHP). Nor did the deletion
affect total glutathione reductase activity in the cell or intracellular survival and
spread.
There are many possible explanations for the lack of phenotype observed in the
∆lmo1433 mutant strains. The first is that CHP may not be a suitable agent for
assessing oxidative stress resistance in L. monocytogenes. The organic nature of CHP
could be toxic to the cell in ways apart from the creation of oxygen radicals. Another
agent that could be used instead of CHP is diamide, which causes thiol stress. Thiol
stress is more typical of the type of stress that glutathione reductase protects the cell
from.
In B. subtilis, there are multiple proteins that aid in resistance to damage
brought about by organic or inorganic peroxides. One system, consisting of the
homologous proteins OhrA and OhrB, provides resistance to organic hydroperoxides
such as CHP (1). Analysis of the contributions of L. monocytogenes genes
homologous to ohrA and ohrB would be more appropriate when testing CHP
174
175
resistance. In B. subtilis, ohrA and ohrB are regulated differently from one another.
ohrA is controlled by the OhrR repressor, providing organic hydroperoxide-inducible
expression of ohrA (1). On the other hand, ohrB is controlled by σB, which serves to
provide peroxide resistance under general environmental stresses and during stationary
phase (2, 3). If L. monocytogenes encodes homologues of OhrA and OhrB, they may
also be similarly regulated. It would be an interesting study to identify these genes
and characterize the phenotypes of mutations in these genes, as well as determine the
role of σB in their regulation.
I found that the genome of L. monocytogenes contains another gene, lmo0906,
which also putatively encodes a glutathione reductase. The predicted protein sequence
encoded by this gene is actually more similar to known glutathione reductases than the
sequence encoded by lmo1433. Thus, to truly identify the contributions of glutathione
reductase to oxidative stress survival, one would need to create a mutation in lmo0906,
as well as a ∆lmo0906 ∆lmo1433 double mutant. A ∆sigB ∆lmo0906 ∆lmo1433 triple
mutant might also be used to study the effects of σB on glutathione reductase activity
as well. These mutants could then be characterized using the same methods I used to
measure glutathione reductase activity, intracellular survival and spread, and oxidative
stress survival (ideally with a more suitable oxidative agent).
The ability of L. monocytogenes to resist a number of environmental stresses is
brought about by numerous different proteins, many of which are regulated by σB, but
some of which may not be. Regulation of stress response gene expression can thus be
expected to be complex. Likewise, expression of virulence determinants in L.
monocytogenes is intricately regulated by at least two factors, PrfA and σB. This
illustrates not only that regulation of gene expression is an important function in
bacteria, but that multiple systems can interact and overlap to co-regulate genes with
functions that may be important in several different instances and environments. The
176
involvement of both stress response and virulence regulatory proteins in virulence
gene expression of L. monocytogenes depicts what may be a common theme among
bacterial pathogens, of relationship between and interdependence of stress response
and virulence.
177
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