Group Title: BMC Microbiology
Title: Subgingival bacterial colonization profiles correlate with gingival tissue gene expression
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Title: Subgingival bacterial colonization profiles correlate with gingival tissue gene expression
Physical Description: Book
Language: English
Creator: Papapanou, Panos
Behle, Jan
Kebschull, Moritz
Celenti, Romanita
Wolf, Dana
Handfield, Martin
Pavlidis, Paul
Demmer, Ryan
Publisher: BMC Microbiology
Publication Date: 2009
 Notes
Abstract: BACKGROUND:Periodontitis is a chronic inflammatory disease caused by the microbiota of the periodontal pocket. We investigated the association between subgingival bacterial profiles and gene expression patterns in gingival tissues of patients with periodontitis. A total of 120 patients undergoing periodontal surgery contributed with a minimum of two interproximal gingival papillae (range 2-4) from a maxillary posterior region. Prior to tissue harvesting, subgingival plaque samples were collected from the mesial and distal aspects of each tissue sample. Gingival tissue RNA was extracted, reverse-transcribed, labeled, and hybridized with whole-genome microarrays (310 in total). Plaque samples were analyzed using checkerboard DNA-DNA hybridizations with respect to 11 bacterial species. Random effects linear regression models considered bacterial levels as exposure and expression profiles as outcome variables. Gene Ontology analyses summarized the expression patterns into biologically relevant categories.RESULTS:Wide inter-species variation was noted in the number of differentially expressed gingival tissue genes according to subgingival bacterial levels: Using a Bonferroni correction (p < 9.15 × 10-7), 9,392 probe sets were differentially associated with levels of Tannerella forsythia, 8,537 with Porphyromonas gingivalis, 6,460 with Aggregatibacter actinomycetemcomitans, 506 with Eikenella corrodens and only 8 with Actinomyces naeslundii. Cluster analysis identified commonalities and differences among tissue gene expression patterns differentially regulated according to bacterial levels.CONCLUSION:Our findings suggest that the microbial content of the periodontal pocket is a determinant of gene expression in the gingival tissues and provide new insights into the differential ability of periodontal species to elicit a local host response.
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Research article


Subgingival bacterial colonization profiles correlate with gingival
tissue gene expression
Panos N Papapanou*I, Jan H Behle1, Moritz Kebschull', Romanita Celenti1,
Dana L Wolff, Martin Handfield3, Paul Pavlidis4 and Ryan T Demmer2

Address: 'Division of Periodontics, Section of Oral and Diagnostic Sciences, College of Dental Medicine, Columbia University, New York, NY,
USA, 2Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA, 3Center for Molecular
Microbiology and Department of Oral Biology, University of Florida, College of Dentistry, Gainsville, FL, USA and 4Department of Psychiatry and
Center of High-Throughput Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
Email: Panos N Papapanou* ppl92@columbia.edu; Jan H Behle zahnschmerz@web.de; Moritz Kebschull endothel@googlemail.com;
Romanita Celenti rscl@columbia.edu; Dana LWolf- dlw2004@columbia.edu; Martin Handfield MHANDFIELD@dental.ufl.edu;
Paul Pavlidis paul@bioinformatics.ubc.ca; Ryan T Demmer rtd2106@mail.cumc.columbia.edu
* Corresponding author



Published: 18 October 2009 Received: 22 May 2009
BMC Microbiology 2009, 9:221 doi:10.1 186/1471-2180-9-221 Accepted: 18 October 2009
This article is available from: http://www.biomedcentral.com/1471-2180/9/221
2009 Papapanou et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.



Abstract
Background: Periodontitis is a chronic inflammatory disease caused by the microbiota of the
periodontal pocket. We investigated the association between subgingival bacterial profiles and gene
expression patterns in gingival tissues of patients with periodontitis. A total of 120 patients
undergoing periodontal surgery contributed with a minimum of two interproximal gingival papillae
(range 2-4) from a maxillary posterior region. Prior to tissue harvesting, subgingival plaque samples
were collected from the mesial and distal aspects of each tissue sample. Gingival tissue RNA was
extracted, reverse-transcribed, labeled, and hybridized with whole-genome microarrays (310 in
total). Plaque samples were analyzed using checkerboard DNA-DNA hybridizations with respect
to I I bacterial species. Random effects linear regression models considered bacterial levels as
exposure and expression profiles as outcome variables. Gene Ontology analyses summarized the
expression patterns into biologically relevant categories.
Results: Wide inter-species variation was noted in the number of differentially expressed gingival
tissue genes according to subgingival bacterial levels: Using a Bonferroni correction (p < 9.15 x 10-
7), 9,392 probe sets were differentially associated with levels of Tannerella forsythia, 8,537 with
Porphyromonas gingivalis, 6,460 with Aggregatibacter actinomycetemcomitans, 506 with Eikenella
corrodens and only 8 with Actinomyces naeslundii. Cluster analysis identified commonalities and
differences among tissue gene expression patterns differentially regulated according to bacterial
levels.
Conclusion: Our findings suggest that the microbial content of the periodontal pocket is a
determinant of gene expression in the gingival tissues and provide new insights into the differential
ability of periodontal species to elicit a local host response.






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Background
It is well established that the microbiota of the dental
plaque are the primary etiologic agents of periodontal dis-
ease in humans [1]. The complex consortium of bacteria
in the subgingival plaque biofilm [2] is in a state of
dynamic equilibrium with the inflammatory response
mounted in the adjacent gingival tissues, resulting in
interdependent shifts in the composition of both the bac-
terial community and the ensuing inflammatory infil-
trate. Indeed, it is known that microbial profiles of
plaques harvested from healthy gingival sulci differ from
those stemming from gingivitis or periodontitis lesions
[3,4]. Similarly, the cellular and molecular fabric of
healthy gingival tissues differs from that of an incipient,
early or established periodontitis lesion [5,6].

A relatively new genomic tool that facilitates the study of
the biology of cells, tissues or diseases is gene expression
profiling, i.e., the systematic cataloging of messenger RNA
sequences, and has provided enormous insights in the
pathobiology of complex diseases, particularly in cancer
research [7,8]. Our group was the first to describe gingival
tissue transcriptomes in chronic and aggressive periodon-
titis [9] and recently provided a comprehensive descrip-
tion of differential gene expression signatures in clinically
healthy and diseased gingival units in periodontitis
patients [10]. To date, a limited amount of data are avail-
able characterizing oral tissue transcriptomes in response
to bacterial stimuli. In vitro experiments [11-15] demon-
strated a degree of specificity in the transcriptional
responses of epithelial cells challenged by commensal or
pathogenic species and have provided a foundation upon
which in vivo studies can further contribute [16]. A pilot
study including conventionally reared, germ free and
SCID mice demonstrated that commensal microbial colo-
nization influences the expression of innate host defense
mediators at both the mRNA and the protein level in the
periodontal tissues [17]. In a non-oral setting, a number
of studies have examined the transcriptional profiles in
response to microbial stimuli in intestinal [18-22], gastric
[23] and corneal epithelia [24].

In this publication, we expand our earlier work and inves-
tigate the association between the subgingival bacterial
profile of the periodontal pocket and the whole genome
transcriptome of the gingival tissue that is in intimate con-
tact with the microbial biofilm.

Methods
The study design was approved by the Institutional
Review Board of the Columbia University Medical Center.

Subjects
120 subjects with moderate to severe periodontitis [65
(54.2%) with chronic and 55 with aggressive periodonti-


tis] were recruited among those referred to the Post-doc-
toral Periodontics Clinic of the Columbia University
College of Dental Medicine. Eligible patients were (i) >13
yrs old; (ii) had >24 teeth; (iii) had no history of system-
atic periodontal therapy other than occasional prophy-
laxis, (iv) had received no systemic antibiotics or anti-
inflammatory drugs for >6 months, (v) harbored 24 teeth
with radiographic bone loss, (vi) did not have diabetes or
any systemic condition that entails a diagnosis of "Perio-
dontitis as a manifestation of systemic diseases" [25], (vii)
were not pregnant, and (ix) were not current users of
tobacco products or nicotine replacement medication.
Signed informed consent was obtained prior to enroll-
ment.

Clinical examination
All participants underwent a full-mouth examination of
the periodontal tissues at six sites per tooth by a single,
calibrated examiner. Variables recorded included pres-
ence/absence of visible dental plaque (PL), presence/
absence of bleeding on probing (BoP), probing depth
(PD), and attachment level (AL). Data were entered chair-
side to a computer and stored at a central server.

Gingival tissue donor areas and tissue sample collection
Subsequently to clinical data entry, a specially developed
software identified periodontally 'diseased' and 'healthy'
tooth sites based on the clinical data. 'Diseased' sites
showed BoP, had interproximal PD >4 mm, and concom-
itant AL >3 mm. 'Healthy' sites showed no BoP, had PD
<4 mm and AL <2 mm. Next, the software identified (i)
maxillary 'diseased' and 'healthy' interdental papillae,
based on the above criteria, and (ii) pairs of diseased
interdental papillae with similar clinical presentation (PD
and AL within 2 mm of each other). A posterior maxillary
sextant encompassing a pair of qualifying 'diseased' inter-
dental papillae was identified.

Periodontal surgery was performed at the identified sex-
tant with no prior supra- or subgingival instrumentation.
After local anesthesia, submarginal incisions were per-
formed, mucoperiosteal flaps were reflected, and the por-
tion of each interproximal gingival papilla that adhered to
the root surface was carefully dissected. This section com-
prised the epithelial lining of the interproximal periodon-
tal pockets and the underlying connective tissue. After
dissection, the gingival tissue specimens were thoroughly
rinsed with sterile normal saline solution and transferred
into Eppendorf tubes containing a liquid RNA stabiliza-
tion reagent (RNAlater, Ambion, Austin, TX). A minimum
of 2 diseased papillae were harvested from each sextant
and, whenever available, a healthy tissue specimen was
obtained from an adjacent site. After collection of the
specimens, pocket elimination/reduction periodontal sur-
gery was completed according to standard procedures. All


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patients received additional periodontal therapy accord-
ing to their individual needs.

RNA extraction, reverse transcription, in vitro cRNA
synthesis
The tissue specimens were stored in a liquid RNA stabili-
zation reagent (RNAlater) overnight at 4C, snap-frozen
and stored in liquid nitrogen. All further processing
occurred simultaneously for gingival biopsies originating
from the same donor. Specimens were homogenized in
Trizol (Invitrogen Life Technologies, Carlsbad, CA, USA).
After incubation with chloroform and centrifugation at
12,000 g, RNA collected in the upper aqueous phase was
precipitated by mixing with 75% isopropyl-alcohol and
additional centrifugation and washings. The extracted
RNA was purified using a total RNA isolation kit (RNeasy;
Qiagen, Valencia, CA, USA), quantified spectrophotomet-
rically, and 7.5 micrograms of total RNA were reverse-
transcribed using a one-cycle cDNA synthesis kit (Gene-
Chip Expression 3' amplification one-cycle cDNA synthe-
sis kit; Affymetrix, Santa Clara, CA, USA). Synthesis of
biotin-Labeled cRNA was performed using appropriate
amplification reagents for in vitro transcription (Gene-
Chip Expression 3'-Amplification Reagents for IVT labe-
ling kit; Affymetrix). The cRNA yield was determined
spectrophotometrically at 260 nm. Twenty jig of cRNA
were fragmented by incubation in fragmentation buffer at
94 0C for 35 min and stored at -80 0C until hybridizations.

Gene Chip hybridizations
Whole genome microarrays (Human Genome U- 133 Plus
2.0 arrays; Affymetrix) arrays, comprising 54,675 probe
sets to analyze more than 47,000 transcripts including
38,500 well-characterized human genes, were used.
Hybridizations, probe array scanning and gene expression
analysis were performed at the Gene Chip Core Facility,
Columbia University Genome Center. Each sample was
hybridized once and each person contributed with 2 to 4
(median 3) tissue samples.

Harvesting of bacterial plaque
After identification of the interproximal papillae to be
harvested and prior to periodontal surgery, subgingival
plaque samples were obtained from the mesial and distal
aspects of each gingival tissue sample using sterile
curettes. After careful removal of supra-gingival plaque,
the curette was placed subgingivally until the bottom of
the probable pocket was reached and subgingival plaque
was collected by a single scaling stroke. The individual
plaque samples were transferred into Eppendorf tubes
containing 200 [l of sterile T-E buffer (10 mM Tris HC1,
1.0 mM EDTA, pH 7.6) and were not pooled at any stage
of the processing described below.


Processing of plaque samples
Immediately after transfer to the laboratory the plaque
pellet was re-suspended, vigorously vortexed, and 200 1il
of a 0.5 M NaOH solution were added. Digoxigenin-
labeled, whole genomic probes were prepared by random
priming by the use of the High-Prime labeling kit (Roche/
Boehringer-Mannheim, Indianapolis, IN, USA) from the
following microbial strains: Aggregatibacter actinomycetem-
comitans (ATCC 43718), Porphyromonas gingivalis (ATCC
33277), Tannerella forsythia (ATCC 43037), Treponema
denticola (ATCC 35404), Prevotella intermedia (ATCC
25611), Fusobacterium nucleatum (ATCC 10953), Parvi-
monas micra (ATCC 33270), Campylobacter rectus (ATCC
33238), Eikenella corrodens (ATCC 23834), Veillonella par-
vula (ATCC 10790), and Actinomyces naeslundii (ATCC
49340). Further processing was carried out according to
the checkerboard DNA-DNA hybridization method [26]
as earlier described [27] with the following modifications:
The chemiluminescent substrate used for detection was
CSPD (Roche/Boehringer-Mannheim). Evaluation of the
chemiluminescence signal was performed in a Lumilm-
ager F1 Workstation (Roche/Boehringer-Mannheim) by
comparing the obtained signals with the ones generated
by pooled standard samples containing 106 or 105 of each
of the species. Standard curves were generated for each
species by means of the LumiAnalyst software (Roche/
Boehringer-Mannheim), and the obtained chemilumines-
cent signals were ultimately transformed into bacterial
counts and exported into Excel files.

Statistical Analysis
In all analyses, either R version 2.3.1 (Linux OS) or SAS
for PC version 9.1 (SAS Institute, Cary, NC) were used.
Gene expression data were normalized and summarized
using the log scale robust multi-array analysis (RMA, [28])
with default settings. Laboratory analysis provided a rela-
tive quantity of individual bacterial species for each
plaque sample by comparison to known standards.
Because the distribution of absolute bacterial counts was
skewed, values were natural logarithm (In) transformed,
averaged within mouth and standardized by dividing each
respective In(bacterial count) by the population standard
deviation for the respective species: one standard devia-
tion on the In scale (SDhI) was treated as equivalent across
microbes as previously described [29]. In addition to
standardized scores for each individual microbe, we also
defined three bacterial groupings ('etiologic burden' (EB),
'putative burden' (PB), and 'health-associated burden
(HAB), by summing the standardized values for the vari-
ous subsets of species as follows [29]: To define EB, we uti-
lized (i) the consensus report of the 1996 World
Workshop in Periodontics identifying three bacterial spe-
cies (P. gingivalis, T. forsythia and A. actinomycetemcomi-
tans) as causally related to periodontitis [30], and (ii)
Socransky's "Red Complex" [31] further identifying T.


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denticola as a species that closely co-varies with P. gingivalis
and T. forsythia in pathological periodontal pockets. The 5
bacterial species deemed putatively associated with perio-
dontal disease (C. rectus, E. corrodens, F. nucleatum, P.
micra and P. intermedia) were grouped as PB [30]. Finally,
HAB included two 'health-associated' bacterial species, A.
naeslundii and V. parvula [31].

Differential gene expression was the dependent variable
in standard mixed-effects linear regression models which
considered patient effects as random with a normal distri-
bution. Standardized bacterial count and gingival tissue
status ('healthy' vs. 'diseased') were modeled as fixed
effects. Bacterial count was defined as the average value
derived from two plaque samples collected from the
mesial and distal sites flanking each of harvested papilla,
respectively. Gingival tissue status was included in the
model to adjust for the confounding effects related to
unmeasured characteristics of disease vs. healthy tissue
(e.g., tissue properties affecting bacterial colonization or
levels of non-investigated bacterial species). To further
minimize the potential for confounding, we conducted
alternate analyses restricted to diseased tissue and further
adjusted for probing depth. Statistical significance for
each probe set was determined using both the Bonferroni
criterion and q-value [32]. For each probe set, a fold-
change was computed by taking the following ratio: raw
expression values among gingival tissue samples adjacent
to periodontal sites with fifth quintile bacterial coloniza-
tion levels vs. expression values in samples adjacent to
first quintile colonization levels. Therefore, fold-change
values represent relative RNA levels in tissues adjacent to
'high' vs. 'low' bacterial colonization sites.

Gene Ontology analysis was performed using ermineJ
[33] with the Gene Score Resampling method. P-values
generated from the aforementioned mixed-models, were
used as input to identify biologically-relevant groups of
genes showing differential expression in relation to bacte-
rial colonization. Gene symbols and descriptions were
derived from the Gemma System (HG-
U133_Plus 2 NoParents.an.zip) and downloaded from
http://chibi.ubc.ca/microannots/. Experimental details
and results following the MIAME standards [34] are avail-
able at the Gene Expression Omnibus (GEO, httpzlj
www.ncbi.nlm.nih.gov/geo/) under accession number
GSE16134.

Real-time RT-PCR Confirmations
To independently confirm the expression data generated
by the microarray experiments, we performed quantitative
real-time RT-PCR analyses for three genes strongly differ-
entially regulated by subgingival bacterial levels (Sperm-
associated antigen4 (Spag4), POU class 2 associating fac-
tor 1 (POU2AF1), and SLAM family member 7 (SlamF7),


while glyceraldehyd-3-phosphatedehydrogenase
(GAPDH) was used as a constitutively expressed control
gene. In this confirmatory step we used subset of five
patients, selected upon the basis of strong differential reg-
ulation of the above genes, each contributing with both a
'healthy' and a 'diseased' tissue sample.

In brief, quantitative real-time PCR was performed as
described previously [35]. The Taqman Gene Expression
Assays Hs00162127_ml, Hs00221793_ml,
Hs01573371_ml, and Hs99999905_ml were used for
Spag4, POU2AF1, SlamF7, and glyceraldehyd-3-phos-
phatedehydrogenase (GAPDH), respectively (Applied
Biosystems, Foster City, CA). Three technical replicates per
sample and gene were performed. Since in the Affymetrix
microarray platform, genes are often represented by mul-
tiple oligonucleotide probes, we calculated means of the
normalized expression data for all probes mapping to the
three genes in each gingival tissue specimen. Subse-
quently, we calculated Spearman correlation coefficients
for the mean microarray expression values and the Act val-
ues obtained by quantitative RT-PCR.

Results
The mean age of the enrolled patients was 39.9 years
(range 13-76). Sixty one patients (50.8%) were male.
Based on self-reported race/ethnicity, 39.2% of the partic-
ipants were White, 21.7% Black, 27.5% of mixed race, and
73.3% Hispanic.

Among the 310 harvested gingival tissue samples, 69 orig-
inated from periodontally healthy sites and 241 from per-
iodontally diseased sites. No healthy tissue samples were
available from 51 patients. Probing pocket depth values
ranged from 1 to 4 mm in the healthy tissue samples, and
between 5 and 11 mm in the diseased tissue samples.

Table 1 describes the subgingival bacterial load in the per-
iodontal pockets adjacent to the 310 harvested gingival
tissue samples. As indicated by the > 0 minimum values
for all bacteria, all tissue samples were in contact with bio-
films that were ubiquitously inhabited by all 11 investi-
gated species. However, the subgingival colonization level
by each species varied greatly. Median levels of P. interme-
dia, T. forsythia, and F. nucleatum were highest while levels
of A. actinomycetemcomitans, C. rectus and V. parvula were
lowest in the pockets adjacent to the obtained gingival tis-
sue specimens.

Regression models adjusted for clinical status (periodon-
tal health or disease) were used to identify probe sets
whose differential expression in the gingival tissues varied
according to the subgingival level of each of the 11 inves-
tigated species. Using a p-value of< 9.15 x 10-7 (i.e., using
a Bonferroni correction for 54,675 comparisons), the


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Table 1: Subgingival bacterial load" in the periodontal pockets adjacent to the harvested gingival tissue samples


Bacterial species

A. actinomycetemcomitans
P. gingivalis
T. forsythia
T. denticola
P. intermedia
F. nudeatum
P. micro
C. rectus
E. corrodens
V. parvula
A. naeslundii


Minimum 25th pctlb Median 75th pctl Maximum AVG SD


18.1
112.6
236.2
70.2
245.4
200.4
118.3
28.3
29.0
35.8
179.1


63.6
442.0
758.0
201.3
531.8
348.6
211.4
76.3
71.8
95.2


2306.9
9740.5
4867.5
3318.5
7189.3
6470.1
5606.5
2457.8
2801.0
3004.0
11353.1


58.5
379.3
543.2
190.8
470.2
270.4
189.1
89.1
74.9
105.1


154.5
821.5
762.9
360.5
762.7
399.5
351.9
219.1
185.6
238.9


434.4 1003.2


'Values are bacterial counts x 10 000, obtained through checkerboard DNA-DNA hybridization, and represent the average load of the two
pockets adjacent to each tissue sample.
b Percentile.


number of differentially expressed probe sets in the gingi-
val tissues according to the level of subgingival bacterial
colonization was 6,460 for A. actinomycetemonitans; 8,537
forP. gingivalis; 9,392 for T. forsythia; 8,035 for T. denticola;
7,764 forP. intermedia; 4,073 forF. nucleatum; 5,286 forP.
micra; 9,206 for C. rectus; 506 forE. corrodens; 3,550 for V.
parvula; and 8 for A. naeslundii. Table 2 presents the top 20
differentially expressed probe sets among tissue samples
with highest and lowest levels of colonization (i.e., the
upper and the lower quintiles) by A. actinomycetemcomi-
tans, P. gingivalis and C. rectus, respectively, sorted accord-
ing to decreasing levels of absolute fold change.
Additional Files 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 present all
the statistically significantly differentially expressed genes
for each of the 11 species. Overall, levels of bacteria
known to co-vary in the subgingival environment, such as
those of the "red complex" [311) species (P. gingivalis, T.
forsythia, and T. denticola) were found to be associated
with similar gene expression signatures in the gingival tis-
sues. Absolute fold changes in gene expression were size-
able among the top 50 probes sets for these three species
(range 11.2-5.5 for P. gingivalis, 10.4-5.3 for T. forsythia,
and 8.9-5.0 for T. denticola). Corresponding fold changes
for the top differentially expressed probe sets ranged
between 9.0 and 4.7 for C. rectus, 6.9-3.8 for P. intermedia,
6.8-4.1 for P. micra, 5.8-2.2 for A. actinomycetemcomitans,
4.6-2.9 for V. parvula, 4.3-2.8 for F. nucleatum, 3.2-1.8 for
E. corrodens, and 2.0-1.5 for A. naeslundii. Results for the
'etiologic', 'putative' and 'health-associated' bacterial bur-
dens were consistent with the those for the individual spe-
cies included in the respective burden scores, and the top
100 probe sets associated with each burden are presented
in Additional Files 12, 13, 14.

Additional regression models utilized data from diseased
gingival tissue samples only and included probing pocket
depth as an additional continuous covariate. These analy-


ses, despite attenuated p-values and fold changes, con-
firmed that colonization by specific bacteria remained
significantly associated with a differential gene expression
in the gingival tissues. For example, in this analysis,
among the top 50 differentially expressed probes sets
according to colonization levels by P. gingivalis, T. forsythia
or T. denticola, the ranges of absolute fold changes were
2.8 4.5, 3.3 5.5 and 2.5 4.3, respectively. All of the top
50 probe sets for each species maintained an FDR<0.05.

Table 3 presents the Spearman correlation coefficients
between microarray-generated expression data and Act
values (PCR cycles) of quantitative real-time RT-PCR for
three selected genes SPAG4, POU2AF1 and SLAMF7.
Since lower Act values indicate higher levels of expression,
the calculated highly negative correlation coefficients
between microrray-based expression values and Act values
represent strong and significant positive correlation
between data generated by the two platforms.

Gene ontology (GO) analyses identified biological proc-
esses that appeared to be differentially regulated in the
gingival tissues in relation to subgingival colonization.
Additional File 15 provides a complete list of all the statis-
tically significantly regulated GO groups for each of the 11
species. Table 4 exemplifies commonalities and differ-
ences in gingival tissue gene expression on the Gene
Ontology level with respect to colonization levels by A.
actinomycetemcomitans and the three "red complex" bacte-
ria. The left column of the Table lists the 20 most strongly
differentially regulated GO groups according to levels of
A. actinomycetemcomitans, while the next three columns
indicate the ranking of each particular GO group for P.
gingivalis, T. forsythia and T. denticola, respectively.
Although antigen processing and presentation was the
highest ranked (i.e., most strongly differentially regu-
lated) GO group for all four species, the second ranked



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Table 2: Top 20 differentially regulated genes in gingival tissues according to subgingival levels ofA. actinomycetemcomitans, P. gingivalis
and C. rectus.


Rank A. actinomycetemcomitans


Genea


P. gingivalis


C. rectus


Gene


Gene


I hypothetical protein MGC29506
2 tumor necrosis factor receptor
superfamily, member 17
3 sperm associated antigen 4

4 interferon, alpha-inducible protein 6

5 POU domain, class 2, associating factor
I
6 CD79a molecule, immunoglobulin-
associated alpha
7 FK506 binding protein I I, 19 kDa
8 hypothetical protein MGC29506
9 immunoglobulin lambda locus,
immunoglobulin lambda constant I
10 immunoglobulin heavy constant alpha I
I I KIAA0746 protein

12 CD79a molecule, immunoglobulin-
associated alpha
13 family with sequence similarity 46,
member C
14 non-annotated
15 interferon, alpha-inducible protein 6
16 potassium intermediate/small
conductance calcium-activated channel,
subfamily N, member 3
17 immunoglobulin lambda locus,
immunoglobulin lambda constant I
(Mcg marker)
18 KIAA0746 protein
19 SLAM family member 7


20 interferon, alpha-inducible protein 6


5.76 hypothetical protein MGC29506
4.23 non-annotated

4.01 tumor necrosis factor receptor
superfamily, member 17
3.91 immunoglobulin kappa variable 1-5

3.86 non-annotated

3.65 immunoglobulin kappa variable 1-5

3.58 immunoglobulin heavy variable 1-69
3.56 interferon, alpha-inducible protein 6
3.50 POU domain, class 2, associating
factor I
3.47 immunoglobulin kappa variable 1-5
3.41 interferon, alpha-inducible protein 6

3.39 non-annotated

3.34 immunoglobulin heavy constant
alpha I
3.34 interferon, alpha-inducible protein 6
3.26 Fc receptor-like 5
3.20 KIAA0125


3.16 immunoglobulin kappa variable 1-5


3.12 immunoglobulin lambda locus
3.11 immunoglobulin lambda locus,
immunoglobulin lambda constant I
(Mcg marker)
3.03 sperm associated antigen 4


11.21 hypothetical protein MGC29506 9.04
8.64 non-annotated 7.62

7.92 tumor necrosis factor receptor 6.48
superfamily, member 17
7.59 POU domain, class 2, associating 6.37
factor I
7.51 immunoglobulin heavy variable 1-69 6.34

7.42 sperm associated antigen 4 6.14

7.41 KIAA0125 6.10
7.38 interferon, alpha-inducible protein 6 5.93
7.18 immunoglobulin kappa constant, 5.92
immunoglobulin kappa variable 1-5
7.16 interferon, alpha-inducible protein 6 5.72
6.97 immunoglobulin heavy constant 5.65
alpha I
6.96 Fc receptor-like 5 5.60


6.89 non-annotated


6.87 interferon, alpha-inducible protein 6 5.53
6.85 interferon, alpha-inducible protein 6 5.52
6.79 immunoglobulin lambda locus, 5.49
immunoglobulin lambda constant I
(Mcg marker)
6.70 interferon, alpha-inducible protein 5.39
6, immunoglobulin heavy locus
(G I m marker)
6.67 non-annotated 5.37
6.63 immunoglobulin lambda locus, 5.36
immunoglobulin lambda constant I
(Mcg marker)
6.59 immunoglobulin kappa constant, 5.35
immunoglobulin kappa variable 1-5


I Repeated occurrence of the same gene among the top ranked is due to multiple probe sets mapping to the same gene
b Fold change indicates ratio of expression in gingival tissues in the upper over the lower quintile of colonization by the particular species


Table 3: Correlation between microarray-based expression data
and real time RT-PCR Act values (PCR cycles) for three genes.


Gene


Spearman correlation coefficient p-value


Spag4
POU2AFI b
SlamF7 c


0.0004
0.0011
0.0058


I Sperm-associated antigen 4
b POU class 2 associating factor I
cSLAM family member 7


GO group in the A. actinomycetemcomitans column (apop-
totic mitochondrial changes) was ranked 96th, 101st and
96th, respectively, for the other three bacteria. Likewise,
the fifth ranked group in the A. actinomycetemcomitans col-
umn (phosphate transport) was ranked 56th, 63rd and 71st,
respectively for the three 3 "red complex" species. Protein-
chromophore linkage (ranked 8th for A. actinomycetem-
comitans) ranked between 147th and 152nd for the other
three species. Conversely, second-ranked regulation of
cell differentiation for the "red complex" species, ranked
19th for A. actinomycetemcomitans.

Figure 1 provides a visual illustration of a cluster analysis
that further underscores the level of similarity in gingival


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Table 4: Patterns of gene expression in gingival tissues, according to subgingival levels ofA. actinomycetemcomitans, P. gingivalis, T.
forsythia and T. denticola.


A. actinomycetemcomitans


P. gingivalis T. forsythia T. denticola


antigen processing and presentation
apoptotic mitochondrial changes
antigen processing and presentation of peptide antigen
antigen processing and presentation of peptide antigen via MHC class I
phosphate transport
muscle development
MAPKKK cascade
protein-chromophore linkage
hemopoietic or lymphoid organ development
hemopoiesis
immune system development
protein amino acid N-linked glycosylation
fatty acid biosynthetic process
regulation of anatomical structure morphogenesis
acute inflammatory response
humoral immune response
activation of immune response
regulation of cell adhesion
regulation of cell differentiation
hemostasis


The left column lists the top 20 differentially expressed Gene Ontology (GO) groups, according to levels of A. actinomycetemcomitans while columns
to the right describe the ranking of these particular GO groups for the other three species.


tissue gene expression according to colonization by each
of the 11 investigated species. The clusters identify bacte-
rial species whose subgingival colonization levels are
associated with similar patterns of gene expression in the
adjacent gingival tissues. The relative proximity of the
investigated species on the x-axis reflects the similarity
among the corresponding gingival gene expression signa-
tures. The color of the heat map indicates the relative
strength of differential regulation of each particular GO
group (i.e., each pixel row) among the 11 species, with
yellow/white colors indicating strong regulation and red
colors a weaker regulation. Not unexpectedly, "red com-
plex" bacteria clustered closely together, but were interest-
ingly far apart from A. actinomycetemcomitans, which
showed higher similarity with E. corrodens and A. naeslun-
dii.

Discussion
To the best of our knowledge, this is the first study to
examine the association between subgingival bacterial
colonization patterns and gingival tissue gene expression
in human periodontitis. Our data demonstrate that the
variable bacterial content of the periodontal pocket corre-
lates with distinct gene expression signatures in the adja-
cent gingival tissues. Importantly, even though we
examined colonization patterns by only a limited number
of bacterial species, we found that the variable subgingival
bacterial load by several -but clearly not all- species corre-
lated significantly with tissue gene expression. In other


words, and to paraphrase both Anton van Leeuwenhoek
and George Orwell, our data indicate that all subgingival
animalculess" are not "equal" in this respect.

In a recent publication [10], we presented transcriptomic
data from a subset of patients involved in the present
report (90 patients and 247 arrays out of the total of 120
patients and 310 arrays included here) and compared
gene expression profiles of clinically healthy and diseased
gingival tissues in patients with periodontitis. We docu-
mented substantial differential gene expression between
states of gingival health and disease that was reflected
both by genes that were a priori anticipated to be variably
expressed based on current knowledge (e.g., several
inflammatory, immune function- and apoptosis-related
genes), but also by genes that are not readily associated
with gingival inflammation (e.g., the transcription factor
POU2AF1, the sperm associated antigen 4 which appears
to be associated with apoptosis (own unpublished data),
the cell adhesion-mediating protein desmocollin 1, and
the signaling lymphocytic activation molecule family
member 7). In the present study, we sought to investigate
whether the bacterial content of the periodontal pocket is
also a determinant of gene expression in the adjacent gin-
gival tissues in order to enhance our understanding of the
host-bacterial interactions that take place in the interface
between the plaque biofilm and the periodontal pocket.
We realize that the above question can ideally be
addressed in a longitudinal prospective rather than a


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/ / ......................









Figure I
Cluster analysis of Gene Ontology (GO) groups differentially expressed in gingival tissues according to subgin-
gival colonization by the I I investigated species. The clusters identify bacterial species whose subgingival colonization
levels are associated with similar patterns of gene expression in the adjacent gingival tissues. The color of the heat map indi-
cates the relative strength of differential regulation of each particular GO group (i.e., each pixel row) among the I I investigated
species, with yellow/white colors indicating strong regulation and red colors weaker regulation.



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ME mf-







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cross-sectional study. Thus, although our analyses consid-
ered bacterial colonization as the independent exposure
and tissue gene expression as the outcome, it is impossible
to rule out reverse causation, i.e., that the qualitative char-
acteristics of the gingival tissue are the determinants of
bacterial colonization. However, given that periodontitis
is a bacterially-induced infection, the former approach is
reasonable in the discussion of the observed correlations
between colonization patterns and tissue gene expression
signatures. We also want to draw the reader's attention to
the fact that, despite our inferences on each particular bac-
terial species' effect on the gingival tissue transcriptome,
we have not studied individual mono-infections. There-
fore, any properties ascribed to a particular species with
respect to its ability to regulate genes in the gingival tissues
cannot be entirely segregated from concomitant synergis-
tic or antagonistic effects of other covarying bacteria
among the ones studied or, most importantly, of the sev-
eral hundreds of cultivable and uncultivable species that
are known to colonize the periodontal pocket and were
not investigated in this work [36]. Instead, the differential
gene expression in the gingival tissues should more appro-
priately be attributed to the aggregate effect of the mixed
microbial burden, and the specific investigated bacteria
may simply serve as a surrogate for this mixed microbial
burden to which they contribute. It must be further recog-
nized that the gingival tissue transcriptomes are also influ-
enced by a plethora of additional factors beyond those of
bacterial origin, including biologically active host-derived
molecules and tissue degradation byproducts, that could
not be accounted for in our study.

In view of the above, and because the transcriptomic pro-
files analyzed originate from a mixed cell population
comprising gingival epithelial cells, connective tissue
fibroblasts and infiltrating cells, our data are not directly
comparable with observations from the aforementioned
in vitro studies of mono-infections of oral epithelial cell
lines. Nevertheless, our data corroborate and extent data
from these experimental settings. For example, ontology
analysis of epithelial cell pathways differentially regulated
after infection with F. nucleatum [ 14] identified MAPK sig-
naling and regulation of actin cytoskeleton among the
impacted pathways. Likewise, in line with observations by
Handfield et al. [11], apoptotic mitochondrial changes,
the second highest differentially regulated ontology group
according to levels of A. actinomycetemcomitans was ranked
96th according to subgingival levels of P. gingivalis. Indeed,
A. actinomycetemcomitans is known to exert strong pro-
apoptotic effects on various cell types encountered in
inflamed gingival tissues, such as gingival epithelial cells
[37] or invading mononuclear cells [38], attributed in part
to its potent cytolethal distending toxin [39]. On the other
hand, P. gingivalis was shown to inhibit apoptosis in pri-
mary gingival epithelial cells by ATP scavenging through


its ATP-consuming nucleoside diphosphate kinase [40].
In contrast, other in vitro studies involving oral epithelial
cells (for review see [41]) reported apoptotic cell death
induced by P. gingivalis atvery high (up to 1:50,000) mul-
tiplicities of infection [42], which arguably exceeds the in
vivo burden in the periodontal pocket.

Thus, our data indicate presence of pro-apoptotic altera-
tions in the gingival tissues in A. actinomycetemcomitans-
associated periodontitis, while the effects of P. gingivalis
appear to be primarily mediated by other pathways. Inter-
estingly, our data corroborate a recent study that explored
the hyper-responsiveness of peripheral blood neutrophils
in periodontitis and demonstrated a significantly
increased expression of several interferon-stimulated
genes [43]. As shown in Table 2, interferon alpha induci-
ble protein-6 was among the top commonly up-regulated
genes in gingival tissue lesions according to levels of A.
actinomycetemcomitans, P. gingivalis and C. rectus, and tis-
sue-infiltrating neutrophils are a conceivable source for
these transcripts.

In general, the magnitude of the differential expression of
host tissue genes according to levels of A. actinomycetem-
comitams (with a total of 68 genes exceeding an absolute
fold change of 2 when comparing tissue samples in the
upper and lowest quintiles of subgingival colonization;
Additional File 1) was more limited than that of bacteria
in the 'red complex' (488 genes for P. gingivalis, 521 genes
for T. forsythia, 429 genes for T. denticola; Additional Files
2, 3, 4) or C. rectus (450 genes; Additional File 8).

The null hypothesis underlying the present study, i.e., that
variable subgingival bacterial load by specific bacteria
results in no differential gene expression in the adjacent
pocket tissues, was rejected by our data. Indeed levels of
only 2 of the 11 species investigated appeared to correlate
poorly with differential gene expression in the tissues: A.
naeslundii, whose levels were statistically associated with
differential expression of only 8 probe sets out of the
approximately 55,000 analyzed, and E. corrodens with
<1% of the probe sets being differentially regulated
between pockets with the highest versus the lowest levels
of colonization. In contrast, 15-17% of the examined
probes sets were differentially expressed according to sub-
gingival levels of the "red complex" species and C. rectus,
whose levels were the most strongly correlated with gingi-
val tissue gene expression signatures among all investi-
gated species.

Importantly, the above associations between bacterial col-
onization and gingival tissue gene expression signatures
were confirmed in analyses adjusting for clinical perio-
dontal status, although they were expectedly attenuated.
In other words, the difference in the tissue transcriptomes


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between periodontal pockets with high versus low levels
of colonization by the particular species identified as
strong regulators of gene expression cannot solely be
ascribed to differences in the clinical status of the sampled
tissues [10] which is known to correlate well with bacte-
rial colonization patterns [31]. Instead, our analyses
based on either statistical adjustment or restriction to 'dis-
eased' tissue samples consistently demonstrate that, even
among periodontal pockets with similar clinical charac-
teristics, the subgingival colonization patterns still influ-
ence the transcriptome of the adjacent gingival tissues.
Assuming a generally positive correlation between gene
and protein expression [44,45], this finding is conceptu-
ally important as it suggests that the 'phenotype' of the
periodontal pocket, and by extension its potential to expe-
rience additional periodontal tissue breakdown and/or an
unfavorable or favorable treatment response, is also
dependent on its bacterial content, and not merely on the
traditional clinical parameters (non-specific plaque accu-
mulation, bleeding on probing, probing depth and
attachment level). It also provides biology-founded
ammunition in favor of the controversial argument that
microbial diagnostics have a place in the decision-making
and therapeutic management of patients with periodonti-
tis [46].

Finally, we emphasize that the subject sample involved in
the present study included both chronic and aggressive
periodontitis patients and subjectsbelonging to various
race/ethnicity groups. It is conceivable that the typeof dis-
ease and race/ethnicity-related charactersitics may be
additional determinants of the gingival tissue transcrip-
tome and/or may act asmodifiers of the association
between bacterial colonization patterns andtissue gene
expression. We intend to explore these possibilities insub-
sequent reports.

Conclusion
Using data from 120 patients, 310 gingival tissue samples
and the adjacent 616 subgingival plaque samples, we
demonstrate a strong correlation between the bacterial
content of the periodontal pocket and the gene expression
profile of the corresponding gingival tissue. The findings
indicate that the subgingival bacterial load by several but
clearly not all investigated periodontal species may
determine gene expression in the adjacent gingival tissues.
These cross-sectional observations may serve as a basis for
future longitudinal prospective studies of the microbial
etiology of periodontal diseases.

Authors' contributions
PNP conceived of the study, is the Principal Investigator of
the grant that provided the funding, and authored the
manuscript; JHB and DLW recruited and treated the
patients, and harvested the microbial and gingival tissue


samples; MK carried out the laboratory work for the gene
expression assessments and RC for the microbiological
assessments; RD carried out the gene expression analysis
and assisted in the authorship of the manuscript; MH and
PP assisted in the data analysis and the authorship of the
manuscript. All authors read and approved the finalized
text.

Additional material


Additional file 1
Table S1. Statistically ., i. i- ,I,1. 'I l ,- expressed probe sets in
the gingival tissues according to levels of A. actinomycetemcomitans in
the adjacent pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S1.ZIP]

Additional file 2
Table S2. Statistically .ii. ni ii. ,,,, I, ii expressed probe sets in
the gingival tissues according to levels of P. gingivalis in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S2.ZIP]

Additional file 3
Table S3. Statistically I .. 1. ,I1, ,11,. 1. 11 ill, expressed probe sets in
the gingival tissues according to levels ofT. forsythia in the adjacent pock-
ets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S3.ZIP]

Additional file 4
Table S4. Statistically ., Inii. ,ii ,I,t.. 1.111 ii expressed probe sets in
the gingival tissues according to levels of T. denticola in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S4.ZIP]

Additional file 5
Table S5. Statistically I .. 1. ,i, 1i1.,. 1111 ill, expressed probe sets in
the gingival tissues according to levels of P. intermedia in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S5.ZIP]

Additional file 6
Table S6. Statistically .... ,i, I.,. ,1 i, expressed probe sets in
the gingival tissues according to levels of F. nucelatum in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S6.ZIP]


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Additional file 7
Table S7. Statistically ., i i. ,-,h hI.l. 11, ll expressed probe sets in
the gingival tissues according to levels of P. micra in the adjacent pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S7.ZIP]

Additional file 8
Table S8. Statistically ., ,,t .. .,.I, .hu... ,i, expressed probe sets in
the gingival tissues according to levels of C. rectus in the adjacent pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S8.ZIP]

Additional file 9
Table S9. Statistically ., "t1. l, ,II,... 1ii, expressed probe sets in
the gingival tissues according to levels of E. corrodens in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S9.ZIP]

Additional file 10
Table S10. Statistically., ,, .i. IHi, u,11... ,,,, ,11 expressed probe sets in
the gingival tissues according to levels of V. parvula in the adjacent pock-
ets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S10.ZIP]

Additional file 11
Table S11. Statistically .,.. 1n.. ,, 1, 11. .11, expressed probe sets in
the gingival tissues according to levels of A. naeslundii in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S11.ZIP]

Additional file 12
Table S12. A list of the top 100 1 .ii. .i, ill expressed probe sets in the
gingival tissues according to levels of 'Etiologic burden' in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S12.XLS]

Additional file 13
Table S13. A list of the top 100 ti ... ,ll expressed probe sets in the
gingival tissues according to levels of 'Putative burden' in the adjacent
pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S13.XLS]

Additional file 14
Table S14. A list of the top 100 1 i11. ,i, expressed probesets in the
gingival tissues according to levels of 'Health-associated burden' in the
adjacent pockets.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-
2180-9-221-S14.XLSX]


Acknowledgements
This work was supported by grant DE015649 and a CTSA Award
RR025158 (P.N.P.). Additional support was provided by K99 DE-018739
(R.T.D); GM076990, a Michael Smith Foundation for Health Research
Career Investigator Award, and an Award from the Canadian Institutes of
Health Research (P.P); DE16715 (M.H.); Neue Gruppe Wissenschaftsstif-
tung, Wangen/Allgau, Germany and IADR/Philips Oral Healthcare Young
Investigator Research Grant (M.K).

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