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Quantitative Proteomic Analysis of Gingival Crevicular Fluid in Different Periodontal Conditions

  • Carina M. Silva-Boghossian,

    Affiliations Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada, Department of Dental Clinic, Division of Graduate Periodontics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil, Institute of Microbiology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

  • Ana Paula V. Colombo,

    Affiliation Institute of Microbiology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

  • Marcia Tanaka,

    Affiliation Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada

  • Carolina Rayo,

    Affiliation Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada

  • Yizhi Xiao,

    Affiliation Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada

  • Walter L. Siqueira

    Affiliation Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada

Quantitative Proteomic Analysis of Gingival Crevicular Fluid in Different Periodontal Conditions

  • Carina M. Silva-Boghossian, 
  • Ana Paula V. Colombo, 
  • Marcia Tanaka, 
  • Carolina Rayo, 
  • Yizhi Xiao, 
  • Walter L. Siqueira



To quantify the proteome composition of the GCF in periodontal health (HH) and in sites with different clinical conditions in chronic periodontitis (CP) subjects.

Material and Methods

5 subjects with HH and 5 with CP were submitted to full-mouth periodontal examination, and GCF sampling. Sites in the CP group were classified and sampled as periodontitis (P, probing depth, PD>4 mm), gingivitis (G, PD≤3mm with bleeding on probing, BOP), and healthy sites (H, PD≤3mm without BOP). GCF proteins were subjected to liquid chromatography electrospray ionization mass spectrometry for identification, characterization and quantification.


230 proteins were identified; 145 proteins were detected in HH, 214 in P, 154 in G, and 133 in H. Four proteins were exclusively detected at HH, 43 proteins at P, 7 proteins at G, and 1 protein at H. Compared to HH group, 35 and 6 proteins were more abundant in P and G (p<0.001), respectively; and 4, 15 and 37 proteins were less abundant in P, G and H (p≤0.01), respectively.


There are marked differences in the GCF proteome according to disease profile. Comprehension of the role of the identified proteins in the etiopathogenesis of periodontal disease may lead to biomarkers definition.


Clinical periodontal conditions are described as periodontal health (PH), gingivitis (G) and periodontitis (P) [1]. Gingivitis induced by dental biofilm is the presence of gingival inflammation without clinical attachment loss (CAL) and with no radiographic evidence of alveolar bone loss. Periodontitis is the presence of gingival inflammation with CAL, and re-absorption of the alveolar bone. In most patients, the increased probing depth (PD) or the formation of periodontal pockets follows the development of the periodontitis [1,2]. Chronic periodontitis (CP) is the most common destructive periodontal disease in adults [3].

The etiological agent of periodontitis is the high levels and proportions of periodontopathic bacteria in the subgingival biofilm [4,5]. The interplay between the pathogenic biofilm and the periodontal tissues in susceptible subjects leads to immunological responses that can be detected in the tissues and in the inflammatory exudates of the gingival crevicular fluid (GCF) [6,7]. In the GCF, pro-inflammatory cytokines and a vast array of other proteins can be found, especially in diseased subjects [8]. Recent reports have shown that, even in healthy periodontal microenvironment, GCF contains local proteins derived from extracellular matrix components and degradation products, as well as serum-derived proteins [7,9,10].

As GCF is an oral cavity-specific fluid, it has been studied in order to determine which constituents could be used as biomarkers for periodontal diagnosis or prognostic for the progression of periodontitis [6,8]. In the recent years, i t is been recognized that the multivariate model is more promising than a single biomarker for risk assessment of disease [11]. The ability to screen and discover multiple biomarkers simultaneously may provide a more valid clinical diagnosis and may be more useful for recognizing molecular patterns predictive for disease development. This multi-biomarker approach has progressed by recent advances in clinical proteomics [1214]. Many studies have been performed in GCF analyzing its proteome profile through mass spectrometry (MS) technology [7,9,10,1519]. Those studies differed in relation to the clinical condition, including studies of experimental gingivitis [15,16], aggressive periodontitis subjects [7], CP subjects [9,18,19], and healthy subjects [10]. Different findings are reported in those studies, not only because of differences inherent to periodontal condition but also because of the MS technique employed. On the other hand, to the moment, proteomics of GCF is in its beginning and there is a vast array of possible biomarkers [8,14]. Thus, comprehensive studies of GCF in different clinical conditions would contribute to a better understanding of the diagnostic potential of the GCF, improving the ability to early detection of disease [6,8,14].

Based on it, we hypothesized that the GCF proteome of PH subjects qualitatively and quantitatively differs from the proteome of CP subjects. This working hypothesis was explored by using quantitative proteomics approach based on label-free LC-MS on GCF of subjects with PH and CP; in CP subjects, sites with different clinical conditions as periodontal health, gingivitis and periodontitis were assessed.

Materials and Methods

Subject Population

Ten subjects who sought dental treatment in December of 2011 at the Dental School of the Federal University of Rio de Janeiro were enrolled in the present study. All participants were informed about the nature of the study and a signed consent form was obtained from each individual prior to entering into the study. The study protocol (#148/11) was reviewed and approved by the Review Committee for Human Subjects of the Clementino Fraga Filho University Hospital of the Federal University of Rio De Janeiro.

In order to participate of the study, subjects had to present at least 14 teeth, ≥ 18 years of age, and clinical diagnosis of CP or PH. Exclusion criteria included smoking, pregnancy, nursing, periodontal therapy in the last year, and use of antibiotics in the previous six months, as well as any immunological condition that could affect the progression of periodontitis. Individuals who required antibiotic coverage for routine periodontal procedures were also excluded. Furthermore, PH subjects should present clinical attachment level (CAL) characteristics as described bellow in order to avoid potential incipient destructive periodontal disease.

Clinical evaluation

A calibrated examiner performed all clinical examinations. The intra-class correlation coefficient for CAL at the site was 0.90, and for probing depth (PD), 0.92. Full-mouth measurements including PD, CAL, presence or absence of supragingival biofilm (SB) and bleeding on probing (BOP) were recorded at six sites per tooth in all teeth, but third molars. Clinical diagnosis of periodontal status was established for all subjects based on the following criteria: periodontal health (PH), ≤ 10% of sites with BOP, no PD or CAL > 3 mm, although PD or CAL = 4 mm in up to 5% of the sites without BOP was allowed; and chronic periodontitis (CP), > 10% of teeth with PD and/or CAL ≥ 5 mm and BOP [20]. CP subjects had to have at least 5 sites with gingivitis (PD ≤ 3mm with BOP) and 4 sites with clinical periodontal health (PD ≤ 3mm without BOP).

GCF sampling

Fourteen GCF samples from non-adjacent sites were collected from each participant. In CP subjects, different categories of sites were selected: 5 deep (PD >4 mm) sites (P), 5 shallow sites with BOP as gingivitis (G), and 4 shallow sites without BOP as health (H). In PH subjects, 14 buccal sites from the upper jaw were sampled (HH samples).

After removal of supragingival biofilm, the teeth were isolated with cotton rolls and a sterile Periopaper strip (ProFlow Inc., Amityville, NY, USA) was gently inserted into the selected subgingival sites and left there for 30s. Then, the volume of the GCF was measured using a Periotron 8000 (Oraflow Inc., Smithtown, NY, USA). The strips were stored in microcentrifuge tubes at -80°C.

Sample preparation

For each CP subject, the paper strips were pooled according to the clinical categories (H, G and P) in microcentrifuge tubes. For PH subjects, two pools were made, dividing the 14 strips in two tubes. Each tube was incubated with 150 µL of a solution containing 80% acetonitrile, 19.9% distilled water and 0.1% trifluoroacetic acid and sonicated for 1 min. This procedure was repeated three times, in order to elute all proteins from the paper strips. Eluted proteins from sites of the same clinical category were pooled. In the end, there were three pools for the 5 CP subjects as P, G and H, and there was one pool for the 5 PH subjects. The pools were concentrated by a rotary evaporator. The total protein concentration was assessed by Micro Bicinchoninic acid (Micro BCATM) Assay (Thermo Scientific, Rockford, USA). Equal protein amount (10 μg) from sites categories was dried by a rotary evaporator, denatured and reduced for 2 h by the addition of 200 µL of 4M urea, 10 mM dithiothreitol (DTT), 50 mM NH4HCO3, pH 7.8. After four-fold dilution with 50 mM NH4HCO3, pH 7.8, tryptic digestion was carried out for 18 h at 37°C, after the addition of 2% (w/w) sequencing-grade trypsin (Promega, Madison, WI, USA) [21].

Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS)

Equal amounts of all samples were dried by rotary evaporator and re-suspended in 20 µl of 97.5% H2O/2.4% acetonitrile/0.1% formic acid and then subjected to reversed-phase LC-ESI-MS/MS. Peptide separation and mass spectrometric analyses were carried out with a nano-HPLC Proxeon (Thermo Scientific, San Jose, CA, USA) which allows in-line LC with the capillary column, 75 µm x 10 cm (Pico TipTM EMITTER, New Objective, Woburn, MA, USA) packed in-house using Magic C18 resin of 5 µm diameter and 200 Å pores size (Michrom BioResources, Auburn, CA, USA) linked to mass spectrometer (LTQ Velos, Thermo Scientific, San Jose, CA, USA) using an electrospray ionization in a survey scan in the range of m/z values 390–2000 tandem MS/MS. The nano-flow reversed-phase HPLC was performed with linear 100 min gradient ranging from 5% to 55% of solvent B in 65 min (97.5% acetonitrile, 0.1% formic acid) at a flow rate of 300 nL/min with a maximum pressure of 280 bar. Electrospray voltage and the temperature of the ion transfer capillary were 1.8 kV and 250°C, respectively.

Enzyme-linked immunosorbent assay (ELISA)

To validate the differential protein level identified by quantitative mass spectrometry approach, ELISA was carried out on lysozyme, a protein with well-known characteristics and functions in the oral cavity. ELISA microtiter plate (96-wells) was coated with 100 µl of GCF protein material from each group (10 µg/ml) at 37°C for 1 hour. The plate was then washed three times with 250 µl Tris Buffered Saline (TBS) per well and 200 µl TBST containing 3% BSA added to each well to block uncoated sites, and incubated overnight at 4°C. Primary anti lysozyme antibody (50 µl; 1:1000 dilution, Abcam, ab97950, MA, USA) in TBST containing 1% BSA was added to each well and incubated at 37°C for 1.5 h, followed by washing three times, and incubation with horse radish peroxidase (HRP) linked Anti- MOUSE IgG (H&L) (GOAT) Antibody Peroxidase Conjugated (100µl; 1:5000 dilution, ROCKLAND, PA, USA) in TBST containing 1% BSA. After incubation in the dark for 1 h at room temperature OPD (o-phenylenediamine dihydrochloride, Sigma-Aldrich, MO, USA) was added and product was analyzed spectrophotometrically at 490 nm. The experiment was performed in triplicate.

Data analysis

A statistical program (SPSS Statistics 19, IBM Brazil, São Paulo, SP, Brazil) was used for clinical analysis. Full-mouth clinical data were averaged in each patient and within groups. Clinical parameters for the 14 sampled sites were also computed for each patient and averaged within groups. Significant differences in demographic and clinical parameters among groups were determined by Kruskal-Wallis, Mann-Whitney and χ2 tests. For MS data, each survey scan (MS) was followed by automated sequential selection of seven peptides for a standard collision-induced (CID) method, with dynamic exclusion of the previously selected ions. The obtained MS/MS spectra were searched against human protein databases (Swiss Prot and TrEMBL, Swiss Institute of Bioinformatics, Geneva, Switzerland, using SEQUEST algorithm in Proteome Discoverer 1.3 software (Thermo Scientific, San Jose, CA, USA), using at least two peptides. Search results were filtered for a False Discovery rate of 1% employing a decoy search strategy utilizing a reverse database [21]. The proteins identified were grouped into 9 different categories based on their known biological functions.

For quantitative proteome analysis, three MS raw files from each pooled clinical categories were analyzed using SIEVE software (Version 2.0 Thermo Scientific, San Jose, CA, USA). Signal processing was performed in a total of 12 MS raw files. The SIEVE experimental workflow was defined as ‘‘Control Compare Trend Analysis’’ where one class of samples are compared to one or more other classes of samples. In the present study, the HH group was compared to each of the other group (H, G and P). For the alignment step, a single MS raw file belonging to the HH group was selected as the reference file and all of the other files were adjusted to generate the best correlation to this reference file. After alignment, the feature detection and integration (or framing) process was performed using the MS level data with a feature called ‘‘Frames From MS2 Scans’’ only. When using this type of framing only MS mass-to-charge ratio (m/z) values that were associated with MS2 scan are used. Any m/z measurements that do not have MS2 were ignored. The parameters used consisted of a frame m/z width of 1500 ppm and a retention time width of 1.75 min. A total of 216,099 MS2 scans were present in all of the 12 RAW files that resulted in a total of 20,158 frames. Then peak integration was performed for each frame and these values were used for statistical analysis. Next, peptide sequences obtained from the database search using SEQUEST algorithm in Proteome Discoverer 1.3 were imported into SIEVE. A filter was applied to the peptide sequences during the import that eliminated all sequences with a Percolator q-value greater than 1% (false discovery rate). Peptides were grouped into proteins and a protein ratio and p-value were calculated, using a weighted average of the peptide intensities for the protein calculation. Only proteins observed in all four groups were quantified. HH group was used as the default group and all other three groups were compared with HH group. Relative abundance of an individual protein from HH group was considered significantly different protein level when the values observed were <0.75 for decreased abundance or >1.25 for increased abundance, and a p-value <0.05 as described previously [22,23].

For ELISA results, mean (± standard-deviation) values were calculated for each group. Afterwards, Analysis of Variance and Student-Newman-Keuls test for pairwise comparisons was carried out to identify significant differences among groups at a 5% level.


Demographic and clinical findings

Table 1 shows the demographic and clinical data of the sample population. CP subjects presented significantly higher mean age than HH subjects (p < 0.01, Mann-Whitney test). Full-mouth clinical data show that CP had significantly higher mean PD and CAL (p < 0.01), and mean % of sites with BOP and SB than HH subjects. In fact, HH subjects presented no sites with BOP or SB. Regarding the clinical data of the sampled sites, significantly differences among sites from diseased subjects and HH subjects were detected (p < 0.01, Kruskal-Wallis test). Sites with periodontitis (P) presented the highest means for PD and CAL than the other categories; and all sites with gingivitis (G) presented BOP. The volume of GCF samples differed significantly among groups (p = 0.016). The GCF mean volume obtained from P sites of the CP group (0.3 µL ± 0.06) was significantly higher than samples from the HH group (0.1 µL ± 0.03, p = 0.016, Mann-Whitney test), H sites (0.06 µL ± 0.02, p = 0.009), and G sites (0.1 ± 0.04, p = 0.028). However, there was no significant difference between the HH group and G or H sites of CP.

(n = 5)(n = 5)
Age (years)46.20 ± 4.8422.20 ± 0.66*
Gender - Females (%)100100
Full mouth
PD (mm)2.67 ± 0.131.16 ± 0.03*
CAL (mm)2.78 ± 0.121.16 ± 0.03*
BOP (%)51.51 ± 6.390*
Supragingival biofilm (%)39.25 ± 7.240*
Sampled sitesPGHHH
PD (mm)5.16 ± 0.271.89 ± 0.191.62 ± 0.121.03 ± 0.05
CAL (mm)5.24 ± 0.252.01 ± 0.161.78 ± 0.191.03 ± 0.05
BOP (%)75.0 ± 14.66100 ± 0.000
Supragingival biofilm (%)40.66 ± 12.9341.57 ± 13.8200
GCF volume (μL)0.3 ± 0.060.1 ± 0.040.06 ± 0.020.1 ± 0.03§

Table 1. Demographic and clinical data (full-mouth and sampled sites; mean ± SEM) of the study population.

* p < 0.01, p < 0.05, Mann-Whitney test; p < 0.01, §p= 0.016, Kruskal-Wallis test; CP: chronic periodontitis; PH: periodontal health; P: periodontitis; G: gingivitis; H: health in periodontitis; HH: healthy sites in healthy subjects; PD: Probing depth; CAL: Clinical attachment level; Bleeding on probing; GCF: gingival crevicular fluid.
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Protein identification

After protein elution from the paper strip and trypsinization, equal amounts of peptides were subjected to nanoscale LC-ESI-MS/MS. A total of 3 runs per group were carried out. The base-peak chromatogram for reversed-phase chromatography monitored by the mass spectrometer represents the intensity of all peptide ions in the sample in a single scan. GCF proteome from all four different groups showed a consistent elution of protein/peptides range from 20 to 60 min (Figure 1).

Figure 1. Examples of base-peak chromatograms of the clinical groups.

Peptide separation was achieved using a nano-flow reverse-phase HPLC column, with gradient elution ranging from 5 to 55% solvent B in 100 min. P: sites with probing depth >4 mm; G: sites with probing depth ≤3 mm and bleeding on probing; H: sites with probing depth ≤3 mm without bleeding on probing in periodontitis subjects; HH: sites with probing depth ≤3 mm without bleeding on probing in healthy subjects.

A total of 230 different proteins were identified in GCF of all four groups (Table 2). Seventy proteins were related to cell differentiation, 60 to cell organization, 3 to coagulation, 1 to enzyme regulation, 36 to immune response, 23 to metabolism, 11 to signal transduction, 16 to transport, and 11 had unknown function. The HH group presented 145 proteins, while in the CP group P sites showed 214 proteins, G 154 proteins, and H 133 proteins. One hundred and five proteins were identified in all four groups, indicating a high overlap in GCF proteins (Figure 2). Four proteins were detected exclusively in the HH group, including keratin type II cytoskeletal 7, neuroblast differentiation-associated protein AHNAK, and 2 glial fibrillary acidic proteins. On the other hand, only one protein (nucleoprotein TPR) was detected in H sites. Moreover, 7 proteins were found exclusively in G sites: histones H1.1, H1.5 and H1t, fibrinogen alpha and beta chain, cathelicidin antimicrobial peptide, and myosin-9. Forty-three proteins were only detected in P sites and were distributed as follows: 10 were related to cell differentiation, 3 to cell organization, 1 to coagulation, 8 to immune response, 9 to metabolism, 8 to signal transduction, 2 to transport, and 2 had non-specified function (Figure 1 and Table 2).

Accession/ functionProtein nameNumber of hits during three mass spectrometry runs
Cell differentiation
Q5T8M7Actin, alpha 1, skeletal muscle524114
Q5T8M8Actin, alpha 1, skeletal muscle527112
Q5T9N7Actin, alpha 2, smooth muscle, aorta (fragment)415112
A6NL76Actin, alpha skeletal muscle527117
E7EQV5Actin, alpha skeletal muscle1122112
P68133Actin, alpha skeletal muscle330114
P62736Actin, aortic smooth muscle327114
P60709Actin, cytoplasmic 1734136
C9JTX5Actin, cytoplasmic 1, N-terminally processed1212112
C9JUM1Actin, cytoplasmic 1, N-terminally processed215112
C9JZR7Actin, cytoplasmic 1, N-terminally processed1215112
E7EVS6Actin, cytoplasmic 1, N-terminally processed617112
F5GYT4Actin, cytoplasmic 1, N-terminally processed02200
P63261Actin, cytoplasmic 2734136
F5H0N0Actin, cytoplasmic 2, N-terminally processed1633116
B8ZZJ2Actin, gamma-enteric smooth muscle412112
C9JFL5Actin, gamma-enteric smooth muscle2715132
E9PG30Actin, gamma-enteric smooth muscle01784
P63267Actin, gamma-enteric smooth muscle327114
P13645Keratin, type I cytoskeletal 1061464162
C9JA77Keratin, type I cytoskeletal 133201825
P13646Keratin, type I cytoskeletal 1344232539
P02533Keratin, type I cytoskeletal 1436232633
A8MT21Keratin, type I cytoskeletal 152508
B3KRA2Keratin, type I cytoskeletal 1585013
P19012Keratin, type I cytoskeletal 1524161525
P08779Keratin, type I cytoskeletal 1630141621
Q04695Keratin, type I cytoskeletal 17128614
C9JM50Keratin, type I cytoskeletal 19272910
P08727Keratin, type I cytoskeletal 1916131316
P35900Keratin, type I cytoskeletal 207007
Q7Z3Z0Keratin, type I cytoskeletal 254472
Q7Z3Y8Keratin, type I cytoskeletal 274472
Q7Z3Y7Keratin, type I cytoskeletal 284472
P35527Keratin, type I cytoskeletal 928531149
Q9NSB2Keratin, type II cuticular Hb42200
P04264Keratin, type II cytoskeletal 186714088
Q7Z794Keratin, type II cytoskeletal 1b2200
P35908Keratin, type II cytoskeletal 2 epidermal22241930
Q01546Keratin, type II cytoskeletal 2 oral4577
P12035Keratin, type II cytoskeletal 34332
F5H8K9Keratin, type II cytoskeletal 401349
P19013Keratin, type II cytoskeletal 481349
E7EU87Keratin, type II cytoskeletal 50161428
P13647Keratin, type II cytoskeletal 525201730
E7EUE8Keratin, type II cytoskeletal 6A0222339
P02538Keratin, type II cytoskeletal 6A30222642
F5H6G5Keratin, type II cytoskeletal 6B0131434
P04259Keratin, type II cytoskeletal 6B30181940
E7EQV7Keratin, type II cytoskeletal 6C17212239
P48668Keratin, type II cytoskeletal 6C30212239
E7ES34Keratin, type II cytoskeletal 70800
F5GZD1Keratin, type II cytoskeletal 72000
P08729Keratin, type II cytoskeletal 738150
Q3SY84Keratin, type II cytoskeletal 710200
Q14CN4Keratin, type II cytoskeletal 720607
Q86Y46Keratin, type II cytoskeletal 734734
Q7RTS7Keratin, type II cytoskeletal 740202
O95678Keratin, type II cytoskeletal 75010713
Q5XKE5Keratin, type II cytoskeletal 795778
P05787Keratin, type II cytoskeletal 86802
Q9H552Keratin-8-like protein 10200
Q09666Neuroblast differentiation-associated protein AHNAK2000
Q0P5P4TMSB4X protein (fragment)2220
Q5VU58Tropomyosin 30200
Q5VU66Tropomyosin 30200
Q5VU61Tropomyosin 30200
Q5VU72Tropomyosin 30200
P06753Tropomyosin alpha-3 chain0200
P67936Tropomyosin alpha-4 chain0200
Cell organization
P02654Apolipoprotein C-I01320
P02655Apolipoprotein C-II0220
P02656Apolipoprotein C-III01026
B0YIW2Apolipoprotein C-III variant 121082
Q02539Histone H1.10020
P16403Histone H1.2108112
P16402Histone H1.3108112
P10412Histone H1.4108112
P16401Histone H1.50020
P22492Histone H1t0020
C9J386Histone H2A5604
A6NFA8Histone H2A0604
A6NKY0Histone H2A0606
A6NN01Histone H2A111038
C9J0D1Histone H2A410310
C9JE22Histone H2A2211139
P0C0S8Histone H2A type 112201715
Q96QV6Histone H2A type 1-A212139
P04908Histone H2A type 1-B/E6181714
Q93077Histone H2A type 1-C6181714
P20671Histone H2A type 1-D12201915
Q96KK5Histone H2A type 1-H12201915
Q99878Histone H2A type 1-J12201915
Q6FI13Histone H2A type 2-A12211915
Q8IUE6Histone H2A type 2-B311103
Q16777Histone H2A type 2-C12211915
Q7L7L0Histone H2A type 36181714
Q9BTM1Histone H2A.J12201915
Q71UI9Histone H2A.V010610
P16104Histone H2A.x212139
P0C0S5Histone H2A.Z010310
B4DR52Histone H2B41764
Q96A08Histone H2B type 1-A2300
P33778Histone H2B type 1-B71484
P62807Histone H2B type 1-C/E/F/G/I111784
P58876Histone H2B type 1-D111784
Q93079Histone H2B type 1-H71784
P06899Histone H2B type 1-J71484
O60814Histone H2B type 1-K31744
Q99880Histone H2B type 1-L71784
Q99879Histone H2B type 1-M71784
Q99877Histone H2B type 1-N71784
P23527Histone H2B type 1-O19142023
Q16778Histone H2B type 2-E71484
Q5QNW6Histone H2B type 2-F71784
Q8N257Histone H2B type 3-B6983
P57053Histone H2B type F-S111784
B4DEB1Histone H34040
P68431Histone H3.12240
Q16695Histone H3.1t2040
Q71DI3Histone H3.22440
P84243Histone H3.32040
P62805Histone H426302923
P35542Serum amyloid A-4 protein02110
P62328Thymosin beta-42220
A8MW06Thymosin beta-4-like protein 36220
P02671Fibrinogen alpha chain0030
P02675Fibrinogen beta chain0020
Q9BYX7Putative beta-actin-like protein 301000
Enzyme regulator
Immune response
P04083Annexin A117391810
Q5T3N0Annexin A1 (fragment)21983
Q5T3N1Annexin A1 (fragment)1028139
P06727Apolipoprotein A-IV02050
P49913Cathelicidin antimicrobial peptide0020
P08311Cathepsin G719174
A5JHP3Dermcidin isoform 222626
B4DL87Heat shock protein beta-132700
C9J3N8Heat shock protein beta-130300
P04792Heat shock protein beta-10800
P01857Ig gamma-1 chain C region0200
P0CG05Ig lambda-2 chain C regions03120
P0CG06Ig lambda-3 chain C regions0300
F5GWP8Junction plakoglobin07914
P30740Leukocyte elastase inhibitor0300
P59665Neutrophil defensin 181055
P59666Neutrophil defensin 381055
P12270Nucleoprotein TPR0002
P05109Protein S100-A851772
P06702Protein S100-A966816446
P3194614-3-3 protein beta/alpha0300
P3194714-3-3 protein sigma0300
P2734814-3-3 protein theta0300
F5H1C1Actin, alpha cardiac muscle 11124144
P68032Actin, alpha cardiac muscle 1330114
P02647Apolipoprotein A-I14956644
P02652Apolipoprotein A-II223159
P02649Apolipoprotein E0800
P61626Lysozyme C31372
P31949Protein S100-A113642
Q5JVS8Vimentin (fragment)01520
B0YJC4Vimentin variant 3737100
B0YJC5Vimentin variant 482230
Signal transduction
Q0491714-3-3 protein eta0300
P6198114-3-3 protein gamma0300
Q8IUK7ALB protein21555751
P12429Annexin A30500
P80511Protein S100-A120200
P31151Protein S100-A70200
E9PAX3Glial fibrillary acidic protein2000
P14136Glial fibrillary acidic protein2000
C9JKR2Albumin, isoform CRA-k4784955
P69905Hemoglobin subunit alpha031163
P68871Hemoglobin subunit beta0502420
E9PEW8Hemoglobin subunit delta023220
E9PFT6Hemoglobin subunit delta02380
P02042Hemoglobin subunit delta026116
P25815Protein S100-P0202
B7WNR0Serum albumin9978568
D6RHD5Serum albumin10637764
E7ESU5Serum albumin231139481
P02768Serum albumin281139481
D6RAK8Vitamin D-binding protein81200
D6RF35Vitamin D-binding protein81200
P02774Vitamin D-binding protein0900
Non specified
Q562R1Beta-actin-like protein 201000
B4DE78cDNA FLJ52141, highly similar to 14-3-3 protein gamma25300
B4E335cDNA FLJ52842, highly similar to Actin, cytoplasmic 12133136
B4DRW1cDNA FLJ55805, highly similar to Keratin, type II cytoskeletal 441389
Q6S8J3POTE ankyrin domain family member E01572
A5A3E0POTE ankyrin domain family member F01575
P0CG38POTE ankyrin domain family member I01072
P0CG39POTE ankyrin domain family member J0700
P02814Submaxillary gland androgen-regulated protein 3B4400
A6NBZ8Uncharacterized protein241069054
A8MW45Uncharacterized protein11794

Table 2. Gingival crevicular fluid proteome from periodontal health (HH, 145 proteins), chronic periodontitis in three categories P (deep probing depth sites, 214 proteins), G (shallow probing depth sites with bleeding on probing, 154 proteins) and H (shallow sites without bleeding on probing, 133 proteins), and number of hits of each protein achieved during three mass spectrometric runs.

The proteins identified were grouped into 9 different categories based on their known biological functions.
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Figure 2. Venn diagram summarizing the absolute number of proteins detected in gingival crevicular fluid samples from periodontally healthy (145 proteins), and chronic periodontitis subjects in three categories P (deep probing depth sites, 214 proteins), G (shallow probing depth sites with bleeding on probing, 154 proteins) and H (shallow sites without bleeding on probing, 133 proteins).

Relative quantitative abundance ratios of proteins in GCF

The relative abundance ratios of the detected proteins in GCF samples from the studied groups are displayed in Table 3. Thirty-five proteins were found to be significantly high abundant in P sites of the CP compared to the HH group (p < 0.001). Many of them (12 proteins) were related to immune response, followed by metabolism (8 proteins), transport (6 proteins), cell differentiation (3 proteins), cell organization (3 proteins), signal transduction (2 proteins), and enzyme regulation (1 protein). Only 4 proteins were significantly low abundant in P sites compared to the HH group: 2 proteins with cell organization function (histone H2A, serum amyloid A 4 protein), and 2 proteins related to immune response (apolipoprotein AIV and myosin-9) (p < 0.001). Conversely, the G and H site categories had most proteins significantly low abundant compared to the HH group. In G sites, 37 proteins were significantly low abundant, mainly proteins related to cell differentiation (21 proteins), followed by immune response function (6 proteins) (p ≤ 0.01); and only 6 proteins were significantly high abundant (p ≤ 0.01). In H sites, 15 proteins were significantly low abundant (p ≤ 0.01), which included 5 proteins with cell organization function and 4 proteins with immune response function.

Accession/ functionProtein nameRatio HH/HHRatio P/HHp-valueRatio G/HHp-valueRatio H/HHp-value
Cell differenciation
E7EQV5Actin, alpha skeletal muscle12.19< 0.001----
F5GYT4Actin, cytoplasmic 1, N-terminally processed13.24< 0.001----
E9PG30Actin, gamma-enteric smooth muscle12.09< 0.0010.53< 0.0010.35< 0.001
P35527Keratin, type I cytoskeletal 91--0.71< 0.001--
P13645Keratin, type I cytoskeletal 101--0.65< 0.001--
C9JA77Keratin, type I cytoskeletal 131--0.66< 0.001--
P13646Keratin, type I cytoskeletal 131--0.38< 0.001--
P02533Keratin, type I cytoskeletal 141--0.66< 0.001--
A8MT21Keratin, type I cytoskeletal 151----0.48< 0.001
P08779Keratin, type I cytoskeletal 161--0.57< 0.001--
C9JM50Keratin, type I cytoskeletal 191--0.56< 0.001--
Q7Z3Z0Keratin, type I cytoskeletal 251--0.47< 0.001--
Q7Z3Y7Keratin, type I cytoskeletal 281--0.55< 0.001--
P04264Keratin, type II cytoskeletal 11--0.69< 0.001--
P35908Keratin, type II cytoskeletal 2 epidermal1--0.73< 0.001--
Q01546Keratin, type II cytoskeletal 2 oral1--0.560.008--
P19013Keratin, type II cytoskeletal 41--0.520.009--
P13647Keratin, type II cytoskeletal 51--0.62< 0.001--
E7EU87Keratin, type II cytoskeletal 51--0.65< 0.001--
E7EUE8Keratin, type II cytoskeletal 6A1--0.50< 0.001--
P02538Keratin, type II cytoskeletal 6A1--0.60< 0.001--
F5H6G5Keratin, type II cytoskeletal 6B1--0.51< 0.001--
E7EQV7Keratin, type II cytoskeletal 6C1--0.56< 0.001--
E7ES34Keratin, type II cytoskeletal 71--0.52< 0.001--
Cell organization
B0YIW2Apolipoprotein CIII variant 110.74< 0.001
P10412Histone H1.412.11< 0.0010.64< 0.0010.60< 0.001
P16401Histone H1.51--1.56< 0.001--
P22492Histone H1t1--0.430.016--
C9JE22Histone H2A10.70< 0.0010.68< 0.0010.44< 0.001
Q9BTM1Histone H2A.J1--1.67< 0.001--
P16104Histone H2A.x1------
B4DR52Histone H2B11.84< 0.001--0.740.001
B4DEB1Histone H31--0.47< 0.001--
P62805Histone H41----0.42< 0.001
P07737Profilin 112.83< 0.001----
P35542Serum amyloid A 4 protein10.11< 0.001----
Enzyme regulator
P04080Cystatin B11.78< 0.0010.61< 0.0010.27< 0.001
Immune response
P01009Alpha 1 antitrypsin12.16< 0.001--
D6RCA8Annexin11.59< 0.001----
P04083Annexin A110.74< 0.0010.70< 0.0010.690.003
P06727Apolipoprotein AIV11.56< 0.0010.51< 0.001--
P49913Cathelicidin antimicrobial peptide11.44< 0.001----
P08311Cathepsin G12.27< 0.001----
P31146Coronin-1A13.06< 0.001--0.66< 0.001
A5JHP3Dermcidin isoform 21--0.5< 0.0010.42< 0.001
B4DL87Heat shock protein beta-111.56< 0.001----
C9J3N8Heat shock protein beta-111.80< 0.001----
P05164Myeloperoxidase11.80< 0.001----
P35579Myosin 910.73< 0.0010.62< 0.001--
P59666Neutrophil defensin 311.77< 0.0010.48< 0.0010.44< 0.001
P05109Protein S100 A811.26< 0.001----
P06702Protein S100 A911.46< 0.0010.57< 0.001--
P02647Apolipoprotein AI11.36< 0.001--0.33< 0.001
P02652Apolipoprotein AII13.05< 0.001----
P02649Apolipoprotein E12.97< 0.001----
E9PLJ3Cofilin-112.81< 0.001----
P61626Lysozyme C12.13< 0.0010.71< 0.0010.29< 0.001
P31949Protein S100 A1112.77< 0.0010.51< 0.001--
F5H868Transthyretin11.65< 0.001----
B0YJC4Vimentin variant 312.20< 0.001----
Signal transduction
E9PAX3Glial fibrillary acidic protein1--1.47< 0.001--
P80511Protein S100 A1211.990.0020.500.020--
P69905Hemoglobin subunit alpha12.35< 0.0011.43< 0.001--
E9PFT6Hemoglobin subunit delta11.95< 0.001----
P02042Hemoglobin subunit delta1-1.330.005--
P25815Protein S100 P12.07< 0.0010.69< 0.001--
P02787Serotransferrin11.80< 0.001----
B7WNR0Serum albumin12.74< 0.001--0.68< 0.001
D6RF35Vitamin D-binding protein12.06< 0.0010.71< 0.001--
Non specified
A6NBZ8Uncharacterized protein1--1.52< 0.001--

Table 3. Abundance* ratios of the detected proteins in gingival crevicular fluid samples from periodontally health (HH) and chronic periodontitis subjects (P: deep probing depth sites; G: shallow probing depth with bleeding on probing sites; and H: shallow probing depth without bleeding on probing sites).

*Relative abundance of an individual protein from HH group was considered significant protein level when the values observed were < 0.75 for decreased abundance or > 1.25 for increased abundance, and a p-value < 0.05. The proteins identified were grouped into 9 different categories based on their known biological functions.
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A significant reduced protein level was observed by MS at H and HH concentration compared to control G and P groups (Table 3). By ELISA Lysozyme contents were demonstrated to decrease from 0.805 ± 0.021 μg/10 μg GCF total protein in the P group, to 0.15 ± 0.05, 0.05 ± 0.02 and 0.113 ± 0.04 in the G, H, HH groups, respectively (Figure 3).

Figure 3. ELISA experiment with 10 μg of GCF material for each group and anti-lysozyme antibody.

Bars represent standard deviation of the mean, calculated from three independent experiments. Different lower case letters denote statistical difference according to Analysis of variance and Student-Newman-Keels’ test. P: sites with probing depth >4 mm; G: sites with probing depth ≤3 mm and bleeding on probing; H: sites with probing depth ≤3 mm without bleeding on probing in periodontitis subjects; HH: sites with probing depth ≤3 mm without bleeding on probing in healthy subjects.


The aim of the present case-control study was to explore the human proteins present in GCF from healthy subjects as well as in subjects with CP. Additionally, analysis of GCF in different clinical conditions in CP subjects was possible because of the sampling strategy. Although, case-control studies may present limited level of evidence, they are often used to identify factors that may contribute to the disease development. The design experiment and the outcome data belong to the primary phase of five consecutive phases. Phase one, as preclinical exploratory studies, is the first (initial) step for the search of biomarkers [24].

The current study identified 230 proteins. In previous study [19], a similar amount of 231 proteins was identified; 168 proteins from those were identified in GCF samples from a healthy site, and 167 proteins were detected in periodontitis sites. Sixty-four proteins were contained only in the healthy samples, and 63 proteins were detected only in the periodontitis samples. In the current analysis, 4 proteins were detected exclusively in the HH group, and 43 proteins were only detected in P sites. The different amount of proteins detected in healthy subjects between studies could be explained by the number of subjects sampled, where in the previous study only one healthy subject was analyzed [19]. It has been demonstrated that when GCF is pooled from multiple sites, the site-specific variability in GCF constituents is reduced [10,17]. Perhaps, by increasing the number of subjects sampled, it is possible that the range of proteins detected increases. Other studies that evaluate the GCF from healthy or diseased subjects have reported a lower number of detected proteins [7,10,1517], while others have identified a higher amount [9,18]. In the study of Baliban et al. [9], 432 human proteins were found. From those, 79 were exclusively found in healthy subjects and 123 in periodontitis subjects. Another study have identified 327 human proteins in healthy subjects [18]. The difference in the amount of identified proteins can also be explained by the MS technique employed as well as the number of peptides used to identify the proteins. Studies that have used only one peptide to identify proteins may have increased the sensibility [9,18], however it may have reduced the specificity.

The most frequently detected proteins in the current study were actins, keratins, histones, annexins, protein S100-A9, apolipoprotein A-I, ALB protein, albumin and serum albumin. These findings are in accordance with a prior proteome study [9], in which the proteins more often detected in both healthy and CP samples were serum albumin, serotransferrin and α-2-macroglobulin. In that study, the authors have also found a wide variety of Type I and II keratins. The high frequency of these proteins observed in the current and other investigations may reflect the high turnover and rate of differentiation of oral epithelia [7,9]. In contrast, cytokines were not detected, as reported also by previous studies applying proteomic based mass spectrometric [7,9,16]. Possible explanations for this finding may be their low concentrations or low molecular weight, for which a drop of peptide signal is still a limiting factor for detection or being masked by the presence of other proteins as albumin [7,9,16,25].

An efficient periodontal biomarker should be able to predict future attachment loss in a susceptible subject. Therefore, the analysis of gingivitis sites in at risk subjects might help in the identification of which factors are already present and what might indicate future breakdown. Having that in mind, some proteins only found in G sites of CP subjects when two peptides were used should be highlighted as histones H1.1, H1.5 and H1t, fibrinogen alpha and beta chain, cathelicidin antimicrobial peptide, and myosin-9. Additionally, some other proteins that were relative more abundant in G compared to the HH group such as histone H2A.J, and glial fibrillary acidic protein might also be important (p <0.005). Proteins of the intermediate filament family as glial fibrillary acidic protein, peripherin, and desmin bind together to form intermediate filaments, providing support and strength to cells, and determining the placement of the nucleus and other specialized structures within the cell. Kido et al. [19] have described high levels of actin and myosin related proteins in GCF samples mainly from periodontitis subjects. Those proteins may be related to periodontal tissue degradation and inflammation [19]. Furthermore, myosin-9 can stimulate leukocyte migration and monocyte differentiation [10]. Myosin-9 and fibrinogen alpha chain were detected only in the resolution phase of experimental gingivitis, while histone H1.5 was detected in relative high frequency in both phases (induction and resolution) [15]. In another experimental gingivitis study, the authors also found myosin-9, fibrinogen alpha and beta chains, histone H1.5 and cathelicidin antimicrobial peptide [16]. Among those proteins, only cathelicidin antimicrobial peptide has been described as involved in periodontal disease [26]. Most recently, histones have been shown to play an important role in an extracellular defense mechanism, neutrophil extracellular traps (NETs) [27]. Moreover, in 2010 it was the first time that a histone protein was reported in GCF [17]. Low concentrations of histone H2A-histone H2B-DNA complexes may present antibacterial property against the species Shigella flexneri, Salmonella typhimurium, and Staphylococcus aureus [27]. Moreover, NETs contain other proteins such as neutrophil elastase, cathepsin G, myeloperoxidase, lactoferrin, and gelatinase [27]. Additionally, the outflow of GCF associate to NETs may be an important mechanism of clearance of the gingival sulcus or periodontal pocket [28].

From the 214 proteins detected in P sites, 43 were exclusively detected in this category. It is known that greater pocket depths associated to clinical signs of inflammation (i.e. bleeding) may result in increased levels of protein-breakdown products expressed in GCF [17]. Those 43 proteins detected included actin cytoplasmatic, tropomyosins, plastin-2, putative beta-actin-like protein 3, peripherin, desmin, Ig gamma-1 and -3 chain C regions, lactoferroxin-C, lactrotransferrin, leukocyte elastase inhibitor, 14-3-3 protein beta/ alpha, 14-3-3 protein sigma, 14-3-3 protein theta, 14-3-3 protein eta, 14-3-3 protein gamma, apolipoprotein E, cofilin-1, calmodulin, annexin A3, protein S100-A12, protein S100-A7, serotransferrin, and vitamin D-binding protein. In another analysis, many proteins showed significant higher relative abundance in P sites when compared to the HH group as alpha 1 antitrypsin, annexin, apolipoprotein AIV, cathelicidin antimicrobial peptide, cathepsin G, coronin-1A, dermcidin isoform 2, heat shock protein beta-1, profilin 1, myeloperoxidase, neutrophil defensin 3, S100 A8, S100 A9, S100 P, vitamin D-binding, serotransferrin (p < 0.001). Two histones (H1.4 and H2B) had also higher relative abundance in P sites than sites from HH patients. Actin and actin binding proteins as profilin and cofilin were described for the first time in GCF samples, which may be representing an osteoblastic bone activity [17]. In addition, other GCF proteins were also identified previously and confirmed in the current investigation as alpha 1 antitrypsin, cofilin-1, profilin 1, cathelicidin antimicrobial peptide, and heat shock protein in chronic periodontitis subjects [17]. In another study, cathepsin G, cathelicidin antimicrobial peptide, protein S100-A7, 14-3-3 protein sigma and vitamin D-binding were found more frequently in chronic periodontitis when compared to healthy subjects [9]. All those proteins were identified and characterized in the current investigation. Moreover, dermcidin was identified only in chronic periodontitis subjects.

As it should be expected, proteins related to immune response as Ig gamma-1 chain C region, Ig gamma-3 chain C region, lactoferroxin-C, lactrotransferrin, leukocyte elastase inhibitor, apolipoprotein E, alpha 1 antitrypsin, annexin, cathelicidin antimicrobial peptide, cathepsin G, coronin-1A, dermcidin isoform 2, heat shock protein beta-1, myeloperoxidase, neutrophil defensin 3, S100 A8, and S100 A9 were present in samples from deep pockets and/or have elevated relative abundance compared to samples from healthy sites (Table 3). For instance, dermcidin isoform 2 displays antimicrobial activity and is highly effective against Escherichia coli, Enterococcus faecalis, S. aureus and Candida albicans [29]. Surprisingly, two proteins of the immune system, Annexin A1 and myosin 9, showed significantly decreased relative abundance in P sites compared to HH group (Table 3, p < 0.001). Conversely, other studies have shown that myosin 9 was found only in disease [7] or in higher frequency in GCF of periodontitis subjects [9]. In a study of periodontally healthy and generalized aggressive periodontitis subjects, a total of 101 human proteins was found in GCF, 35 from those were exclusively detected in aggressive periodontitis [7]. In accordance with the current findings, the authors found that annexin A3, cathepsin G, and S100 P were identified only in diseased subjects, and that myeloperoxidase and profilin 1 were up-regulated in disease. In contrast, the proteins serotransferrin and alpha 1 antitrypsin were low abundant in disease, while neutrophil defensin 3 was detected just in healthy subjects. However, comparisons between those studies should be interpreted carefully, given that aggressive periodontitis subjects may present a more severe condition which is modulated by a genetic pre-disposition and different factors compared to chronic periodontitis subjects [1,2,30].

Findings from the HH group showed that a total of 145 proteins were detected, and only 4 proteins were exclusively found in that group. In the analysis of abundance ratios, it was interesting to observe that all significant results showed that the detected proteins in H sites were low abundant compared to the HH group. Although, the sites sampled were clinically similar in both groups, with no attachment loss or BOP, metabolically they are completely different by the expression of the proteins actin, apolipoprotein, histones, cystatin B, annexin, coronin-1A, dermcidin isoform 2, neutrophil defensin 3, and lysozyme C. Many of those proteins are related to the immune system. Although there is a clinical similarity, in a susceptible diseased subject healthy sites may not be very effective in the immune response as in a healthy subject. Other authors have also found a great number of proteins in GCF from healthy subjects [7,9,10,18], where cofilin 1, profilin 1, plastin 1, lactotransferrin, myeloperoxidase, calmodulin and alpha 1 antitrypsin were more frequently detected in samples from health subjects compared to CP [9]. Surprisingly, they found leukocyte elastase inhibitor only in healthy subjects. In the current study, one type of heat shock protein beta-1 was detected in P sites, and higher frequency of detection of other two heat shock protein beta-1 was detected in HH patients. Likewise, other authors have identified heat shock protein beta-1 in healthy subjects [16]. Conversely, Bostanci et al. [7] detected heat chock protein only in aggressive periodontitis subjects. The proteins S100A8 and S100A9, which are produced by neutrophils and macrophages, can be found in plasma, but their levels in GCF may differ significantly during periodontal disease owing to the local inflammatory response and recruitment of those white cells [10]. This may reinforce the idea that even though serum contributes to its composition, the GCF from healthy periodontal sites is neither pure serum nor are its proteins all serum derived [10].

Although our sample size is not large, it was enough to show significant differences among the clinical groups through MS analysis. Moreover, the differential protein levels identified among groups were confirmed by ELISA on the levels of Lysozyme. On the other hand, the studies previously cited in the current report were performed in relatively small sample size as well. For instance, Bostanci et al. [7] have studied 5 healthy subjects and 5 aggressive periodontitis subjects; and Kido et al. [19] have studied 8 subjects with CP and 1 with periodontal health. Additionally, some studies have analyzed only 10 healthy subjects [10] or 12 CP subjects under maintenance therapy [17].

In general, an increase in gingival inflammation results in an increase in GCF flow, and differences exist between GCF obtained from stable and progressing sites [17]. The current results demonstrated that there are markedly differences in the human proteome of GCF according to disease profile. Therefore, more studies completing the phases described by Pepe et al. [24], including multicenter studies [31], are necessary to understand the role of this vast range of identified proteins in the etiopathogenesis of periodontal disease. Through that comprehension, the discrimination of biomarkers for diagnosis and prognosis of periodontal diseases might be possible.

Author Contributions

Conceived and designed the experiments: WLS CMSB APVC. Performed the experiments: WLS CMSB YX MHT CR. Analyzed the data: WLS CMSB. Contributed reagents/materials/analysis tools: WLS CMSB APVC. Wrote the manuscript: WLS CMSB APVC.


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