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Identication of periodontitisassociated changes in theproteome of whole human salivaby mass spectrometric analysisGesell Salazar M, Jehmlich N, Murr A, Dhople V M, Holtfreter B, Hammer E,V olker U, Kocher T. Identication of periodontitis associated changes in the proteome of whole human saliva by mass spectrometric analysis. J Clin Periodontol 2013; 40: 825832. doi: 10.1111/jcpe.12130.

Abstract

Aim: Interest in human saliva proteomics for disease-specic biomarker screeningincreased in the last decade. We used whole saliva samples from periodontallyhealthy and diseased subjects with chronic periodontitis to screen for disease-asso-ciated differences in the protein pattern.Material and Methods: We selected 20 periodontally healthy and 20 periodontallydiseased subjects from the population-based cross-sectional Study of Health inPomerania (SHIP-2 and SHIP-Trend). Saliva collection was performed with com-mercially available Salivette (Sarstedt, N umbrecht, Germany). Whole saliva pro-

teins were analysed after trichloroacetic acid (TCA) precipitation and proteolyticdigestion with trypsin by LC-MS/MS. MS-data were analysed and quantiedusing the Rosetta Elucidator software package.Results: In whole saliva we identied 344 human protein groups across all sam-ples. For label free quantitation we only considered 152 proteins identied withmore than one unique peptide. In total, 20 proteins showed 1.5-fold difference inabundance between controls and patients ( p < 0.05); the majority of these pro-teins showed higher abundance in the periodontally diseased subjects. Functionalannotation of proteins linked the periodontally diseased status with acute phaseresponse and inammatory processes.Conclusion: Label free proteomic analysis of whole saliva is a powerful tool tocharacterize the periodontal disease status and differentiate between healthy andperiodontally diseased subjects.

Manuela Gesell Salazar 1 *, NicoJehmlich 1 *, Annette Murr 1 , Vishnu M.Dhople 1 , Birte Holtfreter 2 , ElkeHammer 1 , Uwe V olker 1 and ThomasKocher 21 Department of Functional Genomics,Interfaculty Institute for Genetics andFunctional Genomics, University MedicineGreifswald, Greifswald, Germany; 2 Unit ofPeriodontology, Department of RestorativeDentistry, Periodontology and Endodontology,University Medicine Greifswald, Greifswald,Germany

Key words: label free quantitation; LC-MS/ MS; periodontitis; protein candidates; wholesaliva proteomics

Accepted for publication 24 May 2013

Conict of interest and source of funding statement

There are no conicts of interest to declare. This work is part of the research project Greifswald Approach to IndividualizedMedicine GANI_MED. The GANI_MED consortium is funded by the Federal Ministry of Education and Research and theMinistry of Cultural Affairs of the Federal State of Mecklenburg West Pomerania (03IS2061A). SHIP is part of the Commu-nity Medicine Research net CMR of the University of Greifswald, Germany, which is funded by the Federal Ministry of Educa-tion and Research, the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-WestPomerania. The CMR encompasses several research projects which are sharing data of the population-based studies (http://ship.community-medicine.de). GABA, Switzerland, provided unrestricted education funds to support BH.

*Both authors contributed equally.

2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd 825

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Several attempts have been made toidentify biomarkers for diagnosisand prognosis of human diseasesusing non-invasive sampling of mate-rial (Good et al. 2007, Castagnolaet al. 2012). Besides plasma and urine,saliva is one of the major human

biouids that can be easily collectedand harbours important informationnot only of the oral but also the sys-temic disease status (Zhang et al.2009). Comprehensive proteomiccharacterization of human saliva,however, is challenging due to thebroad dynamic range of proteinabundances. Many experimentalstudies try to maximize the proteomecoverage and catalogue salivaryproteins using diverse protein/pep-tide fractionation techniques com-bined with large-scale LC-MS/MSapproaches (Xie et al. 2005, Guoet al. 2006, Bandhakavi et al. 2009).However, the required vast amountof protein and time-consuming pre-fractionations preclude analysis of large population-based studies, inwhich biouids from several thou-sand subjects were collected. In suchstudies, only small volumes are avail-able for proteomic analysis. Thus, itis necessary to elucidate whether lim-ited biobank material can be used toscreen for biomarkers.

Saliva was collected using a Sali-vette because of (i) easy and repro-ducible handling, (ii) representationof a global proteome picture inwhole saliva and (iii) suitability forlarge population-based studies. Acomparative evaluation of three dif-ferent saliva sampling devices (pas-sive drooling, parafn gum andSalivette ) indicated similar proteincoverage of the whole saliva samples(Golatowski et al. 2013). However,the sampling protocol selected intro-duces a technical bias towards aselection of specic proteins (Topkaset al. 2012, Golatowski et al. 2013).

Therefore, for screening approachesin large scale studies the usage of the same type of collection devicefor quantitative proteome analysis isabsolutely required (Golatowskiet al. 2013).

Salivary proteomics are largelyfocused on diseases such as Sj ogrenssyndrome (Ambatipudi et al. 2012),diabetes mellitus (Rao et al. 2009,Caseiro et al. 2013) and cancer(Hu et al. 2008, de Jong et al. 2010,Streckfus et al. 2012). However,

there is an increasing clinical desire todetect oral cancer in time (Brinkmannet al. 2011) or to differentiate gingivi-tis from periodontitis (Gonc alveset al. 2010, 2011, Kim et al. 2010).Gingival crevicular uid (GCF) asan inammatory exudate has been

used for such research questions.GCF provides site specic informa-tion and represents prominentdisease-relevant proteins (Balibanet al. 2011, Choi et al. 2011, Kidoet al. 2012, Tsuchida et al. 2012).However, its collection is time-con-suming, and not feasible for largepopulation-based studies or in dailyclinical practice (Ramseier et al.2009). Whole saliva contains onlysmall amount of GCF besides vastamounts of salivary gland uid.Therefore, its analysis can be consid-ered as an overall assessment of theperiodontal disease status (Milleret al. 2006, Buduneli & Kinane2011). So far proteomic studies withwhole saliva samples are limited andonly a few periodontitis-associatedchanges have been reported (Wuet al. 2009, Haigh et al. 2010, Rangeet al. 2012). Saliva proteome studiesbased on extensively clinically char-acterized subjects might reveal high-quality prognostic and diagnosticprotein biomarker signatures. Thesebiomarkers may allow personaliza-tion of treatment paths (Giannobileet al. 2009, Kornman & Duff 2012)or monitoring of patients with ahigh susceptibility for periodontaldisease in their young adulthood priorto the clinical onset of tissue destruc-tion. Further areas of application maybe found at the interface of dental andgeneral medicine. If a family physiciantreats a patient with uncontrolled dia-betes and with an undiagnosed peri-odontitis, the patient will benet, if he is referred for periodontal treat-ment. Further applications of suchprotein biomarkers could be related

to the increase of predictability of periodontal diagnosis in epidemio-logical research (Rathnayake et al.2013).

In this study we intended to estab-lish a workow suitable for analysisof small sample volumes derivedfrom whole saliva collected in a largepopulation-based study cohort. Thestudy aims to identify characteristicprotein patterns that differ in wholesaliva of periodontally diseased andperiodontally healthy subjects using

a label free quantitative proteomeapproach analysis.

Material and Methods

Study of Health in Pomerania (SHIP)

SHIP is a population-based cohortstudy in Northeast Germany withexaminations held in 1997 2001 (Johnet al. 2001, Hensel et al. 2003).Within selected communities, 8016Caucasian subjects (20 79 years)with German citizenship and mainresidency in the area were randomlydrawn from population registries,stratied by age, gender and city/county of residence (Voelzke et al.2011). The 5-year examination fol-low-up (SHIP-1) was conductedbetween 2002 and 2006, including3300 subjects aged 25 85 years. The10-year examination follow-up(SHIP-2) was launched in 2008. Atthe time of saliva analysis, 2107 subjects aged 25 85 years were alreadyexamined within SHIP-2. SHIP-TREND is an ongoing population-based survey in Northeast Germanylaunched in 2008 (Voelzke et al.2011). A stratied random sample of 8016 adults aged 20 79 years wasdrawn. Stratication variables wereage, gender and city/county of resi-dence. At the time of data acquisi-tion, 3995 subjects were alreadyrecruited.

Periodontal variables

The periodontal status was recordedaccording to the half-mouth methodwith four sites per tooth (excludingthird molars) on the right or left sidein alternating subjects (Hensel et al.2003) due to time and budget con-straint in large population-basedcohort studies where a variety of dif-ferent parameters are collected.Although half-mouth recordings

underestimate periodontal prevalenceand severity (Susin et al. 2005, King-man et al. 2008) any bias concerningdisease classication might be coun-terbalanced by the fact that peri-odontitis can be expected to besymmetrically distributed on sitelevel; periodontal conditions on oneside contribute relevantly to thoseon the contra-lateral side (Mombelli& Meier 2001). Thus, for half-mouthrecordings, this study might be lessprone to classication bias compared

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to other partial recordings. A man-ual periodontal probe (SHIP-2: PCP11; SHIP-TREND: PCPUNC 15,Hu-Friedy, Chicago, IL, USA) wasused. Probing depth (PD) and clinicalattachment level (CAL) were assessedat four sites per tooth (mesiobuccal,

midbuccal, distobuccal and midlin-gual/midpalatinal). Directly afterperiodontal probing, bleeding onprobing (BOP) was assessed half-mouth at the central incisor, canineand rst molar (four sites) andexpressed as the percentage of posi-tive sites. In case of missing teeth,the next distal tooth was assessed.The number of teeth excluding thirdmolars was counted.

Every 6 12 months, calibrationexercises were conducted on subjectswho are not associated with thestudy yielding in intra-rater reliabil-ity correlations between 0.70 and0.78 and an inter-rater correlation of 0.70 for PD measurements with thePCP-11 probe. Using the PCPUNC15 probe, intra-rater correlations forPD measurements ranged between0.68 and 0.88 and inter-rater correla-tion was 0.72. Previous history of diabetes was based on self-reportedphysicians diagnosis or anti-diabeticmedication. Smoking was catego-rized as never, former and currentsmoking.

Use of medication was recordedaccording to the Anatomical Thera-peutic Chemical (ATC) code (WorldHealth Organization 2008). We con-sidered medication with statins(ATC Code C10AA), calcium chan-nel blocker (ATC Code C08CA) andthrombocyte aggregation inhibitors(ATC Codes B01AC04, B01AC05,B01AC06).

Subject sample collection

In this study, we included only actualnon-smoking and non-diabetic sub-

jects, 35 64 years of age, with at least10 natural teeth and at least one sal-iva sample with a saliva volume of > 0.7 ml originating from eitherSHIP-2 or SHIP-TREND. Accord-ing to the literature, subjects weredened as being periodontallyhealthy (Gonc alves et al. 2010) orperiodontally diseased (Haigh et al.2010). However, cut-off values wereslightly adapted to the observed dis-tribution of PD and BOP measuresin SHIP-2 and SHIP-TREND, to

ensure properly sized groups and toincrease disparities in the level of periodontal burden between bothgroups. Consequently, subjects wereclassied as being periodontallyhealthy, if BOP was < 30% and max-imum PD was 3 mm. Subjects were

classied as being periodontally dis-eased, if BOP was > 10%, PD was 5 mm at 2 sites and PD was 4 mm at 40% of teeth. Amongthose subjects being classied asperiodontally healthy or diseased, werandomly selected 20 periodontallyhealthy subjects and 20 periodontallydiseased subjects, who were matchedaccording to age and gender(Table 1). The study was approvedby the local Institutional ReviewBoard.

Saliva samplesStimulated saliva was collected with acommercially available collection sys-tem (Salivette ). The subjects cheweda plain cotton role exactly for 1 min.

to stimulate salivation. The roleswith the absorbed saliva were placedinto the Salivette and immediatelycentrifuged at 1000 g for 20 min. at4 C to remove food remnants, insol-uble material and cell debris. Theresulting supernatant was stored

at

80C.

Sample preparation for massspectrometry

A saliva aliquot of 500 l l was thawedand centrifuged at 16,200 g for30 min. at 4 C. To inhibit proteindegradation a protease inhibitorcocktail (v/v 1:5000, Sigma-Aldrich,St. Louis, MO, USA) was added priorto centrifugation. Proteins of super-natants were precipitated using tri-chloro acetic acid as described before(Jehmlich et al. 2013). Protein con-centrations were determined using aBradford assay (Bio-Rad, Hercules,CA, USA). Protein amounts precipi-tated of 500 l l whole saliva of peri-odontally healthy subjects ( n = 20)

Table 1. Clinical characteristics of groups of periodontally healthy and diseased individuals.Data are presented as mean standard deviation or percentages

Periodontallyhealthy ( n = 20)

Periodontallydiseased ( n = 20)

p*

SHIP-TREND participants 65% 60% 0.74Age, years 48.6 11.4 49.6 10.2 0.65Female gender 50% 50% 1.00Smoking status

Never smoker 50% 75%Ex-smoker 50% 25% 0.10

School education< 10 years 5% 10%

10 years 55% 70%> 10 years 40% 20% 0.36

Marital statusMarried, living together 60% 85%Married, living separated 5% 0%Single 15% 10%Divorced 20% 5% 0.28

Diabetes 0% 0%Medication with

Statins 5% 5% 1.00Calcium channel blocker 0% 5% 0.31Thrombocyte aggregation inhibitors 10% 5% 0.55

Bleeding on probing % 9.8 10.2 44.4 19.1 < 0.001Mean probing depth mm 2.09 0.16 3.13 0.36 < 0.001Maximum probing depth mm 3.0 0 6.2 1.0 < 0.001Percentage of sites with

probing depth 5 mm %0 0 12.1 8.2 < 0.001

Mean attachment loss mm 1.71 0.74 3.51 1.08 < 0.001Number of teeth 24 4.5 24 3.5 0.53

*Mann Whitney- U -test or chi-square test.SHIP-2: self-reported physicians diagnosis in SHIP-0, SHIP-1 or SHIP-2; SHIP-TREND:Self-reported physicians diagnosis in SHIP-TREND.Data are presented as mean standard deviation or percentages.


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ranged from 74 to 500 l g with anaverage of 191 120 l g and of periodontally diseased subjects(n = 20) from 40 to 514 l g with anaverage of 164 127 l g. Aliquotsof the protein extracts were stored at

80 C until further analysis.

LC-MS/MS data analysis

In total, 4 l g protein of each samplewas reduced (2.5 mM DTT, 1 h at60 C), alkylated (10 mM iodoaceta-mide, 30 min. at 37 C) and digestedwith trypsin (Promega, Madison,WI, USA) in a ratio of 1:25 over-night (37 C). Digestion was stoppedwith 1% acetic acid and peptidesolution was desalted with l C-18Zip Tip (Millipore Cooperation, Bill-erica, MA, USA) as described before(Hammer et al. 2011).

Subsequent mass spectrometricanalysis was performed by reversephase peptide separation on a nanoUPLC (Acquity UPLC system,Waters, Milford, MA, USA) andMS-data were generated using theOrbitrap Velos-MS (Thermo FisherScientic, Bremen, Germany) asdescribed before (Jehmlich et al.2013).

Identication and quanticationof proteins was performed usingRosetta Elucidator software (CeibaSolutions, Seattle, WA, USA). Spec-tral data were searched using the Uni-Prot/SwissProt database limited tothe human proteome set (v2010-11,forward-reverse 40,518 entries) usingthe SEQUEST algorithm v2.7.Search parameters are shown inTable S1. Peptides were annotatedusing a false positive rate of 1% cal-culated by PeptideTeller (Peptide-Prophet) embedded in Elucidatorsoftware version 3.3. Elucidator set-tings were used as described before(Hammer et al. 2011) and containedthe following steps (i) feature detec-

tion and alignment, (ii) feature anno-tation, (iii) median normalization bya feature set containing search resultsto discriminate features arising fromsingle-charged contaminants, (iv) l-tering for unique peptides, (v) statis-tical analysis by a two-sided unpairedt-test ( p < 0.05). Gene Ontology(GO) classication of function, bio-logical process and location was car-ried out using the Protein centersoftware (Thermo Scientic). Ingenu-ity Pathway Analysis v14197757

(Ingenuity Systems, Redwood City,CA, USA) was performed to inte-grate the quantied proteins into sig-nalling pathways and networks withbiological meaning.

Results

Sample characteristics

A comparable number of partici-pants of periodontally healthy anddiseased subjects of the two differentstudy cohorts SHIP-2 and SHIP-TREND were included in the study( p = 0.74, Table 1). Subjects did notdiffer signicantly regarding the per-centage of never and former smokersand the distribution of school educa-tion and marital status and medica-tion with statins, calcium channelblockers or thrombocyte aggregationinhibitors. Furthermore, both groupsdiffered signicantly with regard totheir periodontal status as classiedby BOP, PD and CAL measures( p < 0.001). The number of teethwas comparable (24 teeth respec-tively).

Label-free LC-MS/MS quantitation

Mass spectrometric analysis of 20whole saliva samples from each of theperiodontally healthy and diseasedsubjects was performed in single shot-gun LC-MS/MS runs. Identicationyielded in 1129 unique peptides(FDR < 1%) representing 344 dis-tinct human proteins (Table S2). Apartial least square (PLS) plot thatexplains the maximum multidimen-sional variance allowed a separationof periodontally healthy and dis-eased subjects. The subjects of eachgroup clustered together althoughfew subjects overlapped (Fig. 1). Toprovide a more detailed view, directlabel-free quantitation using peptideintensities was applied to monitor

protein abundances of 152 proteins,which were covered with more thanone unique peptide. In total, 20 pro-teins showed different abundancelevels in both groups using a twosided two sample t-test with a p-value < 0.05 and fold change greater> 1.5 (Fig. 2). The strongest differ-ences were observed for proteinS100-P (fold change 2.4), plastin-2(fold change 2.2) and neutrophildefensin (fold change 2.1). Represen-tative protein abundance distribu-

tions are shown for these threeproteins in Fig. 3 to visualize theinter-subject variability. Except lact-operoxidase all proteins that dis-played differential abundance amongthe two groups showed higher inten-sities in the periodontally diseasedgroup.

Gene ontology and ingenuity pathway

analysisHuman proteins ( n = 344) were fur-ther characterized in terms of theirGO categories to illustrate saliva pro-tein function using Protein Center(Thermo Scientic). Functional classi-cation indicated that the largestproportions of identied proteins ( 2unique peptides) belonged to thegroups of protein binding, catalyticactivity, metal ion binding and enzymeregulator activity (Figure S1a). GOanalysis of biological processesrevealed major categories of meta-

bolic processes and response to stim-ulus (Figure S1b). Most of proteinsare located in cytoplasm or areextracellular proteins (Figure S1c).

Subsequently, differentially abun-dant proteins ( n = 20) were catego-rized into the categories of molecularand cellular functions using Ingenu-ity Pathway Analysis (IPA). Thisanalysis revealed a signicant enrich-ment ( p < 0.05) of proteins involvedin cellular movement ( n = 16), cellu-lar function and maintenance

Periodontitis subjectsHealthy subjects

Comp. 1

Comp. 2

Comp. 3

Fig. 1. Partial Least Square (PLS) plot of analysed subjects ( n = 40). PLS was cho-sen to provide a dimensional reduction of the maximum covariance to predict theperiodontal status as the dependent vari-able. PLS linear transition analysis wasperformed on peptide intensities. Eachdata point represents a subject of theperiodontitis group (red) and the healthygroup (blue).



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(n = 16), cell to cell signalling andinteraction ( n = 13) and cell death(n = 14) (Table S3). In the categoryof diseases and disorders of biologi-

cal function inammatory response(n = 13) was pronounced pointing tothe characteristics of periodontallydiseases (Fig. 2). Furthermore, someof the differentially abundant pro-teins are known to be involved inskeletal and muscular disorders(n = 14), dermatological diseases andconditions ( n = 13) and connectivetissue disorders ( n = 11). Categoriesof physiological system developmentand function involve haematologicalsystem development and function,

immune cell trafcking, tissue mor-phology and tissue development(Table S3). In the category of canon-ical pathways acute phase response

(n = 5) and LXR/RXR activation(n = 4) signalling covered the highestnumber of differentially expressedproteins (Fig. 2).

Discussion

Proteomic screenings of saliva canprovide new insights into diseaseprocesses (Giannobile et al. 2009)and thus help to identify susceptiblesubjects. However, despite anincreasing number of potential useful

protein candidates until now, nobreak-through could be establishedto characterize periodontitis with ahigh specicity and sensitivity.

We applied a shotgun LC-MS/MSapproach with highly sensitive MSequipment to explore which disease

related information can be gainedfrom limited saliva material, becausevast protein amount and time-con-suming pre-fractionation approachesare not feasible for large-scale subjectanalyses. The number of identiedproteins ( n = 344) is comparablewith other studies of whole saliva(Xie et al. 2005) and of GCF (Car-neiro et al. 2012, Tsuchida et al.2012). In comparison to GCF thecollection of saliva is technically lessextensive. Furthermore, whole salivacontains proteins from salivaryglands, microorganisms, epithelialcells, PMN and GCF (Zia et al.2011) thereby representing a morecomprehensive appraisal of oralhealth status in opposite to site-specic characteristics of GCF anal-ysis.

Our results underline the sensitiv-ity of our analysis without any pre-fractionation. The complete datasetwas uploaded to ProteinCenter andfurther characterized in terms of GOcategories. Our ndings of GO classi-cation of function, biological pro-cess, and location are in goodagreement with previous analysis per-formed by Bandhakavi et al. (2009),that is, to date the most comprehen-sive description of the proteome of pooled saliva using a three-dimen-sional peptide fractionation.

Most periodontitis associatedproteomic studies used gingival cre-vicular uid. Over 90 different com-ponents in GCF have been presentedas possible biomarkers for diagnosisof periodontal diseases, which can bedivided into three major groups: (i)host derived enzymes and their inhibi-

tors, (ii) inammatory mediators andhost response modiers and (iii) prod-ucts of tissue breakdown (Buduneli &Kinane 2011). Based on discoverystudies in GCF some potential bio-markers like matrix metalloproteinas-es (MMP-2, -8, -9), tumour necrosisfactor (TNFA), interleukin-1 b, a-2-macroglobulin were examined andvalidated in saliva with immunologi-cal methods (Pederson et al. 1995,Christodoulides et al. 2007, Herret al. 2007, Rai et al. 2008, Zhang

2 1.5 1 0.5 0 0.5 1 1.5 2 2.5 3

CeruloplasminAlpha-2-HS-glycoprotein

Complement C3Alpha-2-macroglobulinFibrinogen alpha chain

Plastin-2Calreticulin

LactotransferrinProfilin-1Gelsolin

Peptidoglycan recognition protein 1Neutrophil defensin

Neutrophil collagenaseMatrix metalloproteinase-9

Protein S100-PRho GDP-dissociation inhibitor 2

CatalaseAdenylyl cyclase-associated protein 1

Leukotriene A-4 hydrolaseLactoperoxidase

Fold Change

Acute phase response signaling pathway

Fold change IPA top canonical pathway IPA biological function

Inflammatory response

Cellular movement

Fig. 2. Summary of proteins present in different abundance in whole saliva of peri-odontally diseased and healthy subjects ( 2 peptides per protein, p < 0.05, t-test, andfold change > 1.5). Primary protein name, fold change and IPA classication are indi-cated.

Fig. 3. Representation of inter-individual variation of intensities of three selected pro-teins in healthy and periodontally diseased subjects. Individual and median (black line)intensities are displayed. p-values have been derived with a two sided two samplet-test. perio periodontally diseased subjects; healthy healthy subjects.



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et al. 2009). Despite the promisingprospects of using whole saliva forscreening for periodontal diseases, sofar most proteomic studies havebeen conned to rather insensitive 2-D-gel electrophoresis approachesthat only used MALDI and electro-

spray mass spectrometry for identi-cation of protein spots (Wu et al.2009, Gonc alves et al. 2010, Haighet al. 2010, Chan et al. 2012). To ourknowledge highly sensitive gel freeLC-MS/MS approaches have so faronly been applied to GCF (Balibanet al. 2011, Tsuchida et al. 2012) buthave not been used for studies of periodontitis-related changes in thecomposition of whole saliva (Amadoet al. 2012).

In our study, groups of 20 peri-odontally healthy and 20 periodon-tally diseased subjects were randomlyselected from the SHIP study. Label-free quantitation on 152 human pro-teins ( 2 distinct peptides) wasapplied to differentiate periodontitissubjects from controls, which nallyyielded 20 proteins that were presentin different abundance in both groups(1.5-fold change, p-value < 0.05). Ournding that only rather small differ-ences distinguish the salivary proteo-mes of periodontally healthy fromperiodontally diseased subjects is ingood agreement with 2-D gel basedstudies, which included between fewto tenths of diseased subjects (Wuet al. 2009, Haigh et al. 2010, Kimet al. 2010, Chan et al. 2012, Rangeet al. 2012). Except one all of these20 proteins showed higher abun-dance in the periodontally diseasedsubjects. We conrmed previouslyreported potential biomarkers inwhole saliva for periodontal diseasessuch as a-2-macroglobulin, comple-ment C3, neutrophil collagenase,matrix metalloproteinase-9, plastin-2,prolin-1 or lactotransferrin (TableS2).

These 20 differentially abundantproteins reect pathways of peri-odontal tissue destruction (Armitage1999, Giannobile et al. 2009). Thesetissue destruction processes are alsoreected in our Ingenuity PathwayAnalysis. Higher levels of thirteenproteins in periodontally diseasedsubjects in comparison to controlsindicate active inammatory pro-cesses. In the grouping according tobiological function, sixteen proteinswere categorized to molecular cellu-

lar movement. An activated chemo-taxis of cells ( n = 6 proteins) andmigration of mononuclear leucocytes(n = 5 proteins) further strengthenthe observation of ongoing inamma-tory processes. Furthermore, theanalysis revealed that ve proteins

up-regulated in periodontally dis-eased subjects (alpha-2-macroglobu-lin, ceruloplasmin, complement C3,alpha-2-HS-glycoprotein, brinogenalpha chain) were involved in acutephase response signalling (Table S2).A rapid inammatory response canbe triggered by tissue injury to pro-tect against microorganisms usingnon-specic defense mechanisms.The correlation of chronic periodon-titis and acute phase response waspreviously described (Ebersole et al.1997, Craig et al. 2003). The glyco-protein alpha-2-macroglobulin, ageneral protease inhibitor, belongs tothe coagulation system and wasdescribed in the context of periodon-titis in GCF (Ozmeric 2004, Choiet al. 2011). Ceruloplasmin which isinduced by inammation was presentin higher levels in polymorphonu-clear leukocytes or serum frompatients with localized aggressiveperiodontitis (Iwata et al. 2009). Inaddition, complement C3 was dis-cussed as a possible salivary biomar-ker for diagnosis of periodontaldiseases (Ozmeric 2004).

Several differential regulated pro-teins such as a-defensin, lactotransfer-rin and lactoperoxidase are knownto have antibacterial activity againstperiodontopathic bacteria (Lonner-dal & Iyer 1995, Groenink et al.1999, Abiko et al. 2003, Wakabay-ashi et al. 2010, Shimizu et al. 2011).Increased levels of a-defensin werefound in patients with periodontitisand support our observations (Abikoet al. 2003, Baliban et al. 2011).S100 proteins are a group of cal-cium-binding proteins with various

regulatory functions (Donato 2001),which showed an increased abun-dance in periodontitis patients. Ournding concurs with reported results(Zhang et al. 2009, Haigh et al.2010, Choi et al. 2011, Heo et al.2011). The higher abundance of pla-stin-2 in patients with chronic peri-odontitis compared to periodontallyhealthy subjects is in agreement withprevious studies (Bostanci et al.2010, Choi et al. 2011, Chan et al.2012) that reported the contribution

of leukocyte adhesion and signaltransduction in periodontal disease.Furthermore, prolin-1 which isinvolved in actin polymerization inresponse to extracellular signals wasincreased in periodontally diseasedsubjects in our study. Even if the

role of prolin-1 in inammatoryprocesses has not been elucidatedyet, proling-1 levels have beenreported to be associated with peri-odontitis progression (Kim et al.2010, Choi et al. 2011).

Matrix metalloproteinases arezinc-dependent endopeptidases thatare considered to be key initiators inextracellular matrix degradation innormal physiological processes (e.g.embryonic development, reproduc-tion or tissue remodelling) but alsoinvolved in disease processes (Raiet al. 2008, Mirrielees et al. 2010).They have been described as majortissue destructive enzymes in peri-odontitis present at higher abundancein periodontally diseased subjects(Sorsa et al. 2004, Miller et al. 2006,Christodoulides et al. 2007, Rein-hardt et al. 2010, Gursoy et al. 2013).In line with these reports, our studyrevealed increased protein levels of MMP-8 (neutrophil collagenase) andMMP-9 in diseased subjects. Otherbiomarker candidates involved inbone resorption or turnover in peri-odontitis (Kinney et al. 2007) werenot covered by our study.

Conclusion

We were able to characterize the sal-ivary proteome from subjectsselected from a population-basedcohort and found proteins that werepresent in periodontally healthy anddiseased subjects at different abun-dance. We conrmed eight previ-ously reported potential biomarkersin whole saliva for periodontal dis-eases. Further specic protein signa-

tures in our analysis display thecharacteristics of chronic periodonti-tis, that is, host response to micro-bial challenge and inammatoryprocesses. For potential periodontitismarkers a validation in large cohortsand by using independent analyticalmethods is necessary.

Acknowledgement

The authors thank Jette Anklam forher excellent technical assistance.



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Supporting Information

Additional Supporting Informationmay be found in the online versionof this article:

Figure S1. Gene ontology classica-tion of identied human salivaryproteins. (A) molecular function, (B)biological process and (C) cellularcomponent.Table S1. Description of parameterfor identication and quantitation of proteinsTable S2. List of protein identica-tions from LC-MS/MS analysisTable S3. Categorization of proteins

showing different abundance in peri-odontally healthy and diseasedsubjects using IPA

Address:Manuela Gesell SalazarUniversity Medicine Greifswald, InterfacultyInstitute for Genetics and Functional GenomicsDepartment of Functional GenomicsFriedrich-Ludwig-Jahn-Str. 15a, 17487 Greifswald GermanyE-mail: [email protected]

Clinical Relevance

Scientic rationale for the study :Because of the high prevalence of periodontal diseases among adultsthe investigation of periodontitis isof high interest. A central questionto be addressed in salivary proteo-mics is the identication of proteinbiomarker candidates to assess theperiodontal status of subjects.

Principal ndings : Periodontallyhealthy and diseased subjects can bedistinguished by label-free quantita-tive LC-MS/MS analysis. A set of dif-ferentially expressed human proteinbiomarker candidates is reportedindicating periodontally diseasestatus.Practical implications : In whole sal-iva analysis, multiple proteins can

act as useful marker candidates indiagnostic detection of periodonti-tis. Periodontitis markers have tobe validated with large cohorts andby an independent analyticalplatform.



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