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Signal Transduction: Environmental Stimulus to Changes in Global Transcription in Porphyromonas gingivalis

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Signal Transduction: Environmental Stimulus to Changes in Global Transcription in Porphyromonas gingivalis
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Journal of Undergraduate Research
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Smith, Corey James
Progulske-Fox, Ann ( Mentor )
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Gainesville, Fla.
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University of Florida
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Porphyromonas gingivalis is an anaerobic oral pathogen that has been associated with atherosclerosis and coronary heart disease. Genetic regulation in eubacteria occurs primarily at the level of transcription. The specificity of RNA polymerase for promoters is determined by the sigma subunit. Regulation of sigma factors is generally achieved by an attached proprotein sequence or an anti-sigma factor capable of responding to environmental cues. The string database was used to determine the genes in the operons containing putative sigma factors in the P. gingivalis genome. The putative sigma factors were tested for proprotein sequences using signalP peptide cleavage site prediction software. This test concluded that none of the putative sigma factors contained a cleavage site similar to any previously characterized system. The genes in cotranscriptional units with sigma factors were tested for transmembrane helicies using TMHMM, revealing that seven of the ten operons containing a sigma factor had an integral protein. These results provide a set of possible environmentally reactive transcriptional regulators that can be confirmed with a yeast two-hybrid test to confirm protein-protein and protein-DNA interactions.

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Signal Transduction: Environmental Stimulus to Changes in

Global Transcription in Porphyromonas gingivalis


Cory James Smith


College of Dentistry, University of Florida


Porphyromonas gingivalis is an anaerobic oral pathogen that has been associated with atherosclerosis and coronary heart disease.
Genetic regulation in eubacteria occurs primarily at the level of transcription. The specificity of RNA polymerase for promoters is
determined by the sigma subunit. Regulation of sigma factors is generally achieved by an attached proprotein sequence or an anti-
sigma factor capable of responding to environmental cues. The string database was used to determine the genes in the operons
containing putative sigma factors in the P. gingivalis genome. The putative sigma factors were tested for proprotein sequences using
signalP peptide cleavage site prediction software. This test concluded that none of the putative sigma factors contained a cleavage site
similar to any previously characterized system. The genes in cotranscriptional units with sigma factors were tested for transmembrane
helicies using TMHMM, revealing that seven of the ten operons containing a sigma factor had an integral protein. These results
provide a set of possible environmentally reactive transcriptional regulators that can be confirmed with a yeast two-hybrid test to
confirm protein-protein and protein-DNA interactions.


Within our bodies resides a dynamic population of
microbial cells that are estimated to outnumber human
cells ten to one (Backhed). This consortium of microbiota
and their fluctuating collective genomes encode
metabolic and physiological functions that are not
encoded by the human genome (Backhed). This new view
of the human body as a consortium consisting of
symbiotic eukarya, archaea, and eubacteria is forcing
scientists to redefine what is considered self. We are more
than just the familiar eukaryote with 23 diploid
chromosomes that we know as human but also all of our
microbial inhabitants living together symbiotically.
(Nicholson).
It has been estimated that 700 different species of
microorganisms can colonize the oral cavity (Aas).
Colonization of dental plaque occurs in distinct waves of
microbial species over time (Hasegawa N). The primary
colonization of the oral cavity occurs by streptococci and
actinomyces species (Aas, Janeway). The initial col-
onization alters the microenvironment of the mouth
permitting the establishment of gram positive rods and
gram negative bacteria such as Fusobacterium nucleatum.
The environment is again altered by its new colonizers
creating new a new niche that gram-negative anaerobes
such as Porphyromonas gingivalis can exploit (Hasegawa
N).
P. gingivalis is strongly implicated as an etiological
agent of periodontal disease, a chronic inflammatory
infection of the tissues that surround and support the teeth
(Dor). Historically periodontal disease has been an
associated risk factor with heart disease and theories


about the causes of coronary heart disease are changing to
include pathogenic factors (Dor). Recently, viable P.
gingivalis was isolated and proven invasive from
atherosclerotic plaque (Kozarov). Oral bacteria have an
entry route into the circulatory system in patients afflicted
with periodontitis simply when patients floss, brush or
chew (Sconyers).
Atherosclerosis is a chronic inflammatory disease
caused by prolonged damage from the accumulation of
immune cells along the arterial wall. (Libby) During the
course of atherosclerosis normal endothelial functions are
altered to express adhesion cytokines such as integrin and
selection that induce leukocyte recruitment and
inflammation (Libby).
Eubacterial RNA polymerase (RNAP) typically
consists of a four subunit core (3p'a2) and a sigma
subunit that reversibly binds with RNAP, forming an
active holoenzyme (pp'a20). The active holoenzyme is
capable of forming an open promoter complex and
initiating transcription. The sigma subunit is responsible
for direct contact and recognition with the -10 and -35
boxes of the promoter and determines promoter
specificity (Klimple). The number of sigma factors
encoded in studied eubacterial genomes is highly
variable, ranging from 1 in Mycoplasma sp. to as many as
65 in Streptomyces coelicolor (Manganelli). Each sigma
factor has unique specificity for a promoter sequence.
Often genes of related function are grouped into operons
with a single promoter that are transcribed in one
polycistronic mRNA. Regulons are sets of operons that
are expressed simultaneously because they share a similar


University of Florida I Journal of Undergraduate Research I Volume 11, Issue 1 I Fall 2009





CORY JAMES SMITH


promoter region that can be recognized by the same
sigma factor. Regulation of which sigma factors are
active serves as a master control switch in the coordinated
regulation of global gene expression.
Not only are sigma factors under strict transcriptional
control but they are also controlled post-translationally by
means of proprotein sequences and anti-sigma factors.
Proprotein sequences are segments of a nascent peptide
that must be proteolytically cleaved to activate the mature
functional sigma factor. Anti-sigma factors bind the
sigma factor preventing it from associating with RNAP
and transcribing its regulon. In response to specific
environmental signals the anti-sigma factor changes
conformation, releasing the sigma factor and allowing it
to transcribe its regulon.
The most common form of anti-sigma factor described
in the literature is the Extracellular function sigma factor.
ECF operons produce environmental response systems
that transduce stress signals to changes in global gene
regulation patterns (Missiakas, Helmann). The anti-sigma
factor is generally described as a transmembrane protein
that binds its cognate sigma factor sequestering it from
RNAP. This steric isolation prevents the transcription of
the regulon that is controlled by it's cognate sigma factor
(Helmann). In response to an environmental signal
specific to each anti-sigma factor, the integral protein
changes conformation, releasing the ECF sigma factor,
ans allowing it's re-association with the RNAP. The
active holoenzyme is now able to transcribe the regulon
of operons with the cognate promoter to the sigma factor
(Missiakas). The activated gene products respond to the
perceived environmental stress rendering the organism
viable for the new conditions.
The anti-sigma factor regulatory system shares many
aspects with the two-component regulatory system
characterized throughout eubacteria and in some
eukaryotes (Helmann, Stock). Two-component regulatory
systems typically consist of; a histidine kinase that binds
adenosine triphosphate and autophosphorylates at a
histidine residue, and a response regulator that receives
the phosphoryl group on an aspartate residue (Stock). The
histidine kinase is usually a membrane bound receptor
that autophosphorylates only in response to specific
environmental stimuli. Phosphoryl transfer from the
histidine kinase to an aspartate residue then activates the
response regulator. The phosphoryl group changes the
confirmation of the response regulator permitting it to
bind DNA at a specific sequence. The response regulator
alters transcription of genes in the local area.
Some virulence factors of P. gingivalis have been
shown to be controlled by two-component regulation.
FimA, a long fimbriae associated with invasion of host
cells, and a short fimbriae, mfal, shown to be involved in


interspecies communication Hayashi and, Wu are such
examples. These fimbrial genes are regulated by the
experimentally characterized two-component regulatory
system of FimR/FimS (Hasegawa N H). FimS is a
membrane bound sensor kinase and FimR is a response
regulator that is activated by FimS allowing it to bind
DNA, altering expression offimA, and mfa (Hasegawa N
H, Xie).
The regulator OxyR is directly involved in
transcriptional responses to oxidation in P. gingivalis
(Wu). OxyR changes conformation under oxidative
stress, allowing it to bind directly to the promoter offimA,
reducing transcription. OxyR also increases transcription
of sod, super-oxide dismutase, a critical enzyme involved
in the mild aerotolerance of P. gingivalis (Wu). Other
intracellular pathogens such as Mycobacterium
tuberculosis enter a dormant state upon oxidative stress in
an attempt to avoid the immune system (Manganelli).
Since the FimA protein is involved in TLR assisted
phagocytosis of P. gingivalis by macrophages, the
repression offimA by OxyR could be a form of antigenic
variation used to evade immunological response.


METHODS

Putative sigma factors were identified from the
complete annotated genome sequence of Porphyromonas
gingivalis strain W83 sequenced by The Institute for
Genomic Research (Frasier). The fully annotated
sequence can be obtained at the website for the National
Center for Biotechnology Information. The annotation
with features was viewed in the open source genome
viewer Artemis (Rutherford). Within Artemis a feature
search was conducted to identifying genes with "sigma"
in their putative descriptions. Manual reading of all terms
hitting sigma resulted in a list of putative sigma factor
genes.
The String database for known and predicted protein
interactions was then used to identify genes in operons
containing the putative sigma factors. The predictions are
made from genome context, high-throughput
experiments, conserved coexpression, and previous
knowledge. The predictions were viewed in Artemis to
ensure that the predicted genes are adjacent and in the
same transcriptional orientation as the putative sigma
factors.
The genes in predicted operons containing sigma
factors were further analyzed using several comparative
bioinformatics tools to detect the presence of hypothetical
transmembrane helices and proprotein cleavage sites. The
transmembrane domain prediction software TMHMM
was used to identify conserved membrane spanning helix


University of Florida I Journal of Undergraduate Research I Volume 11, Issue 1 I Fall 2009
2





SIGNAL TRANSDUCTION


domains that have been extensively characterized
throughout all domains of life.
SignalP, based on neural networks and hidden Markov
models, is used to predict the presence and location of
proprotein cleavage sites. Neural networks function in a
similar manor to the way biological neurons function in
processing information. Several inputs are taken in
(protein sequence) which are taken through several
calculations (statistical estimation, optimization, and
control theory) to output a single answer, in this case
whether or not the peptide contains a proprotein cleavage
site similar to other experimentally characterized systems
(Emanuelson).


RESULTS

The P. gingivalis W83 genome encodes 11 putative
sigma factors, four related to sigma-54 and seven related
to sigma-70. rpoD and rpoN are related to the classically
conserved primary sigma factors related to Escherichia
coli sigma-54 and sigma-70 respectively. Six of the sigma
factors are classified as ECF type related to
environmental response. Table 1 lists the 11 sigma factors
and their putative identification.
Ten of the 11 sigma factors are predicted to be
transcribed in an operon with an additional 1 to 7 genes
by the cotranscriptional prediction of the String database.


Although the majority of the genes in operons with sigma
factors are uncharacterized the few that are characterized
are generally involved in signal transduction. The results
of the string database prediction of functional
associations is available in Table 2. From the putative
description of genes in the operons of sigma factors
PG_0746, PG_0017, and PG_0151 are involved in signal
recognition of signal transduction. PG_0017 is a sensor
protein, PG_0746 is a sensor histidine kinase, and
PG_0151 is a signal recognition particle-docking protein.
However the majority of genes collocated in operons with
sigma factors are reported as uncharacterized hypothetical
proteins requiring further analysis using bioinformatics
tools newly developed since 2001 when the W83 genome
was annotated.
Of the 10 operons containing sigma factors, 7 of them
contain at least one predicted transmembrane protein as
determined by TMHMM. The data for TMHMM is
available in table 3. These integral proteins are likely
targets as anti-sigma factors because of the classically
conserved structure of the ECF operon.
The results of P. gingivalis sigma factors tested on the
signalP server for the presence of a signal peptide
cleavage site are listed in table 4. The results suggest that
none of the 11 sigma factors contain a cleavage site. For
each peptide two neural networks are used to predict
cleavage sites based on similarity to experimentally
characterized peptides.


Table 1: Putative sigma factors of P. gingivalis strain W83.


Locus tag Gene Putative identification
PG_0016 - sigma-54 dependent DNA-binding response regulator
PG_0148 - sigma-54-dependent transcriptional regulator
PG_0162 - RNA polymerase sigma-70 factor, ECF subfamily
PG_0214 - RNA polymerase sigma-70 factor, ECF subfamily
PG_0594 rpoD RNA polymerase sigma-70 factor
PG_0747 - sigma-54 dependent DNA-binding response regulator
PG_0985 -RNA polymerase sigma-70 factor, ECF subfamily
PG_1105 rpoN RNA polymerase sigma-54 factor
PG_1318 -RNA polymerase sigma-70 factor, ECF subfamily
PG_1660 -RNA polymerase sigma-70 factor, ECF subfamily
PG_1827 -RNA polymerase sigma-70 factor, ECF subfamily


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CORY JAMES SMITH


Table 2: P. gingivalis predicted operons containing sigma factors


Sigma factors in W83 Operon
Locus tag Locus tag Description
PG 0016 PG 0017 Sensor protein (EC 2.7.13.3)


PG 0018


Putative uncharacterized protein


PG_0148 PG_0146 Putative uncharacterized protein
PG_0147 Putative uncharacterized protein
PG_0149 conserved domain protein
PG_0150 conserved hypothetical protein
PG_0151 Signal recognition particle-docking protein
PG_0152 Carboxynorspermidine decarboxylase
PG_0153 Aspartyl-tRNA synthetase (EC 6.1.1.12)

PG_0162 PG_0161 Putative uncharacterized protein
PG_0163 phosphofructokinase

PG_0214 PG_0215 Putative uncharacterized protein
PG_0216 Putative uncharacterized protein
PG_0217 Putative uncharacterized protein
PG_0218 Putative uncharacterized protein

PG_0594 PG_0543 htrA protein

PG_0747 PG_0745 Lactoylglutathione lyase, putative
PG 0746 Sensor histidine kinase

PG_0985 PG_0984 Putative uncharacterized protein
PG_0986 Putative uncharacterized protein
PG_0987 Putative uncharacterized protein

PG_1105 PG_1106 Putative uncharacterized protein

Peptidyl-prolyl cis-trans isomerase SlyD, FKBP-
PG_1318 PG_1315 type
PG_1316 Putative uncharacterized protein
PG_1317 Putative uncharacterized protein

PG_1660 PG_1659 Putative uncharacterized protein
PG_1661 Putative uncharacterized protein
PG_1662 Putative uncharacterized protein

PG 1827








University of Florida I Journal of Undergraduate Research I Volume 11, Issue 1 I Fall 2009





SIGNAL TRANSDUCTION


Table 3: TMHMM prediction of transmembrane helicies of sigma factor operon genes


Gene locus
PG 0017
PG 0018
PG 0146
PG 0147
PG 0149
PG 0150
PG 0151
PG 0152
PG 0153
PG 0161
PG 0163
PG 0215
PG 0216
PG 0217
PG 0218
PG 0543
PG 0745
PG 0746
PG 0984
PG 0986
PG 0987
PG 1106
PG 1315
PG 1316
PG 1317
PG 1659
PG 1661
PG 1662


Number of
predicted
TMH
2
0
1
1
1
0
0
0
0
0
0
1
1
0
0
0
0
2
0
1
0
0
0
0
1
2
0
2


a - A protein is considered a transmembrane protein if it contains 18 or more AA in transmembrane
helicies
b - probability that the active domain is on the cytoplasmic side of the membrane
















University of Florida I Journal of Undergraduate Research I Volume 11, Issue 1 I Fall 2009
5


# of AA in
TMH
47
25
17
23
21
0
0
0
0
0
0
20
20
10
3
0
5
50
0
21
2
0
0
14
23
43
0
45


n-in
probability
0.98899
0.65987
0.14824
0.71989
0.84813
0.04123
0.00296
0.02918
0.00252
0.38057
0.00235
0.97667
0.98486
0.44654
0.15684
0.54632
0.53876
0.99960
0.61118
0.94097
0.17779
0.02673
0.12121
0.67223
0.15081
1.00000
0.30846
0.98909


Transmembrane
protein?a
Yes
Yes
No
Yes
Yes
No
No
No
No
No
No
Yes
Yes
No
No
No
No
Yes
No
Yes
No
No
No
No
Yes
Yes
No
yes





CORY JAMES SMITH


Table 4: SignalP prediction of the presence of signal peptide cleavage loci.


Signal
Locus tag Max Ca Max Sa Mean Sa Max yb Dc peptide?d
PG 0016 0.018 0.784 0.229 0.077 0.153 No
PG 0148 0.192 0.707 0.122 0.143 0.133 No
PG 0162 0.250 0.037 0.016 0.018 0.017 No
PG 0214 0.047 0.057 0.033 0.034 0.033 No
PG 0594 0.049 0.073 0.035 0.026 0.030 No
PG 0747 0.216 0.542 0.096 0.190 0.143 No
PG 0985 0.282 0.116 0.039 0.061 0.050 No
PG 1105 0.022 0.091 0.031 0.024 0.028 No
PG 1318 0.145 0.151 0.047 0.038 0.042 No
PG 1660 0.494 0.396 0.050 0.044 0.047 No
PG 1827 0.199 0.666 0.262 0.184 0.223 No


a C-score and S-score are the two neural networks used.
b Y-max is a derivative of the C-score combined with the S-score.
c D is an average of S-mean and Y-max that provides the best view of whether the peptide contains a
cleavage site.
d Determination if the protein is a signal peptide is determined by a summation of these values


DISCUSSION

Regulation of gene expression in eubacterial species
occurs primarily at the level of transcription
(Haldenwang). The specificity of the holoenzyme is
determined by the interaction of the sigma subunit with
the promoter region on the DNA directly upstream of the
transcription initiation site (Haldenwang). Non sigma
factor DNA binding proteins such as repressors can alter
the efficiency of transcription but it is the sigma factor
that determines when and where transcription occurs
(Haldenwang). Genetic regulation in P. gingivalis, up to
this point, has only characterized non-sigma factor DNA
binding proteins. This paper suggests eleven operons are
potentially involved in sigma factor creation and
regulation.
A primary sigma factor such as sigma-70, or sigma-54
in E. coli is one that is essential and cannot be deleted
from the genome (Manganelli). They tend to be conserved
across bacterial species and are represented in P.
gingivalis by PG_0594 (sigma-70 like) and PG_1105
(sigma-54 like). A lethal gene knockout of these two
genes would confirm their role as primary essential sigma
factors.
All of the identified sigma factors in P. gingivalis are
merely predicted, to confirm their actual role in the cell
molecular biology tools must be used. A yeast two-hybrid
test is a molecular biology technique used to determine


protein-protein, and protein-DNA interactions. The test
uses activation of a reporter gene (usually lacZ) promoted
by a transcription factor (Gal4) binding to upstream
activating sequence (UAS). The transcription factor
consists of two domains: a DNA binding domain (BD)
and an activating domain (AD). The two domains are split
and added to the proteins of interest that might have
interactions. If the two proteins of interest interact, then
the activating domain is brought into close enough
proximity to recruit RNAP and to transcribe the reporter
gene (Finley). A yeast two-hybrid test could confirm that
the putative sigma factors both bind to RNAP as well as
identify promoter specificity.
Extracellular function (ECF) sigma factors are
environmental response systems that transduce a signal
from the environment to enact global changes in
transcription. ECF sigma factors are usually kept in an
inactive state until the environmental cue is received to
activate them (Helmann). Inactivation can be
accomplished through several diverse mechanisms such as
physical sequestration by a membrane protein, or initial
translation with a pro-protein inhibition sequence, or both
(Missiakas). Vital to the functioning of an ECF system is
the membrane bound receptor that recognizes
environmental stresses and begins the signal transduction
cascade. The sigma factors in the P. gingivalis genome are
generally associated with a predicted transmembrane
protein that could fulfill this role. Further studies could be


University of Florida I Journal of Undergraduate Research I Volume 11, Issue 1 I Fall 2009
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SIGNAL TRANSDUCTION


conducted by genetic inactivation of the predicted
membrane proteins and testing the mutant's ability to
respond to various environmental stimuli.
From the analysis of signalP results, it is predicted that
none of the 11 sigma factors are secreted in an inactive
form requiring proteolytic activation. This result simply
means that the sigma factors in the P. gingivalis genome
do not have peptide cleavage sites similar in homology to
experimentally characterized cleavage sites. A novel
cleavage site signal in P. gingivalis would not be
recognized by the neural networks of signalP because it
has not been trained to recognize this signal. In most
organisms that have had their sigma factors extensively
studied such as E. coli, M tuberculosis, and B. subtilis,
they have shown signal recognition sites that must be
cleaved to be activated as a further regulation opportunity
to fine tune genetic regulation (Manganelli, Haldenwang).
The use of either a proprotein sequence or cognate
anti-sigma factor allows for an intricate regulatory system
that readily adapts to a constantly changing environment.
The genetic regulatory system of P. gingivalis remains
highly uncharacterized but through the advent of high
throughput sequencing technology and comparative
bioinformatics many insights can be revealed by its
similarity to characterized systems in other species. These
predictions will point researchers in the right directions to
make discoveries with experimental tools.



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