Advertisement

Current Oral Health Reports

, Volume 4, Issue 4, pp 271–277 | Cite as

Proteomics of Periodontal Pocket

  • Dimitra SakellariEmail author
Epidemiology (M Laine, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Epidemiology

Abstract

Purpose of Review

This study aims to present and evaluate the findings of the literature referring to proteomic analysis of the periodontal pocket aimed to identify potential biomarkers for periodontal disease.

Recent Findings

A comprehensive examination of data from “shotgun” proteomic analysis has shown that a number of human proteins, previously not extensively investigated in the literature, have emerged as new candidates. Proteins relevant to various biological functions such as actin, profilin, hemoglobin, plastins, alpha-amylase, matrix metalloproteinases, keratins, histones, annexins, antimicrobial peptides including histatins, S-100A9, cathelicidin-related peptide-37 (LL-37), human neutrophil peptides (HNP)-1, -2, and -3, statherin, and cystatins are commonly identified in gingival crevicular fluid (GCF) by proteomic analysis and are upregulated in periodontal disease and therefore could serve as biomarkers.

Conclusions

Proteomic analysis has provided a new insight into the search for biomarkers of periodontal disease presence, progression, prognosis, and endpoints of treatment. Data derived should be validated by larger scale studies, including significant subject samples. These second-stage studies should focus on evaluating the importance of these proposed new biomarkers using standardized procedures.

Keywords

Proteomic analysis Gingival crevicular fluid Biomarkers 

Notes

Compliance with Ethical Standards

Conflict of Interest

The author declares that he has no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. 1.
    Global Burden of Disease. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2015;388:1545–602.Google Scholar
  2. 2.
    Tonetti MS, Jepsen S, Jin L, Otomo-Corgel J. Impact of the global burden of periodontal diseases on health, nutrition and wellbeing of mankind: a call for global action. J Clin Periodontol. 2017;44(5):456–62.  https://doi.org/10.1111/jcpe.12732.CrossRefPubMedGoogle Scholar
  3. 3.
    Petersen PE, Ogawa H. The global burden of periodontal disease: towards integration with chronic disease prevention and control. Periodontol. 2012;60(1):15–39.  https://doi.org/10.1111/j.1600-0757.2011.00425.x.CrossRefGoogle Scholar
  4. 4.
    Eke PI, Dye BA, Wei L, Thornton-Evans GO, Genco RJ. Prevalence of periodontitis in adults in the United States: 2009 and 2010. J Dent Res. 2012;91(10):914–20.  https://doi.org/10.1177/0022034512457373.CrossRefPubMedGoogle Scholar
  5. 5.
    UNFPA. Ageing. 2015. http://www.unfpa.org/ageing. Accessed 17 June 2017.
  6. 6.
    Flemmig TF, Beikler T. Economics of periodontal care: market trends, competitive forces and incentives. Periodontol. 2013;62(1):287–304.  https://doi.org/10.1111/prd.12009.CrossRefGoogle Scholar
  7. 7.
    Borgnakke WS, Ylöstalo PV, Taylor GW, Genco RJ. Effect of periodontal disease on diabetes: systematic review of epidemiologic observational evidence. J Clin Periodontol. 2013;40:S135–S52.  https://doi.org/10.1111/jcpe.12080.CrossRefPubMedGoogle Scholar
  8. 8.
    Dietrich T, Sharma P, Walter C, Weston P, Beck J. The epidemiological evidence behind the association between periodontitis and incident atherosclerotic cardiovascular disease. J Clin Periodontol. 2013;40:S70–84.  https://doi.org/10.1111/jcpe.12062.CrossRefPubMedGoogle Scholar
  9. 9.
    Ide M, Papapanou PN. Epidemiology of association between maternal periodontal disease and adverse pregnancy outcomes—systematic review. J Clin Periodontol. 2013;40:S181–S94.  https://doi.org/10.1111/jcpe.12063.CrossRefPubMedGoogle Scholar
  10. 10.
    Linden GJ, Lyons A, Scannapieco FA. Periodontal systemic associations: review of the evidence. J Clin Periodontol. 2013;40:S8–S19.  https://doi.org/10.1111/jcpe.12064.CrossRefPubMedGoogle Scholar
  11. 11.
    Champagne CME, Buchanan W, Reddy MS, Preisser JS, Beck JD, Offenbacher S. Potential for gingival crevice fluid measures as predictors of risk for periodontal diseases. Periodontol. 2003;31(1):167–80.  https://doi.org/10.1034/j.1600-0757.2003.03110.x.CrossRefGoogle Scholar
  12. 12.
    Delima AJ, Van Dyke TE. Origin and function of the cellular components in gingival crevice fluid. Periodontol. 2003;31(1):55–76.  https://doi.org/10.1034/j.1600-0757.2003.03105.x.CrossRefGoogle Scholar
  13. 13.
    Heitz-Mayfield LJA. Disease progression: identification of high-risk groups and individuals for periodontitis. J Clin Periodontol. 2005;32:196–209.  https://doi.org/10.1111/j.1600-051X.2005.00803.x.CrossRefPubMedGoogle Scholar
  14. 14.
    Loos BG, Tjoa S. Host-derived diagnostic markers for periodontitis: do they exist in gingival crevice fluid? Periodontol. 2005;39(1):53–72.CrossRefGoogle Scholar
  15. 15.
    Chapple ILC. Periodontal diagnosis and treatment—where does the future lie? Periodontol. 2009;51(1):9–24.  https://doi.org/10.1111/j.1600-0757.2009.00319.x.CrossRefGoogle Scholar
  16. 16.
    Buduneli N, Kinane DF. Host-derived diagnostic markers related to soft tissue destruction and bone degradation in periodontitis. J Clin Periodontol. 2011;38:85–105.  https://doi.org/10.1111/j.1600-051X.2010.01670.x.CrossRefPubMedGoogle Scholar
  17. 17.
    Wilkins MR, Pasquali C, Appel RD, Ou K, Golaz O, Sanchez J-C, et al. From proteins to proteomes: large scale protein identification by two-dimensional electrophoresis and amino acid analysis. Biotechnol. 1996;14(6):61–5.Google Scholar
  18. 18.
    Pandey A, Mann M. Proteomics to study genes and genomes. Nature. 2000;405(6788):837–46.CrossRefPubMedGoogle Scholar
  19. 19.
    Biomarkers Definition Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89–95.CrossRefGoogle Scholar
  20. 20.
    Amur S, Frueh FW, Lesko LJ, Huang S-M. Integration and use of biomarkers in drug development, regulation and clinical practice: a US regulatory perspective. Biomark Med. 2008;2:305–11.CrossRefPubMedGoogle Scholar
  21. 21.
    Sorsa T, Tervahartiala T, Leppilahti J, Hernandez M, Gamonal J, Tuomainen AM, et al. Collagenase-2 (MMP-8) as a point-of-care biomarker in periodontitis and cardiovascular diseases. Therapeutic response to non-antimicrobial properties of tetracyclines. Pharmacol Res. 2011;63(2):108–13.  https://doi.org/10.1016/j.phrs.2010.10.005.CrossRefPubMedGoogle Scholar
  22. 22.
    Rathnayake N, Gieselmann D-R, Heikkinen A, Tervahartiala T, Sorsa T. Salivary diagnostics—point-of-care diagnostics of MMP-8 in dentistry and medicine. Diagnostics. 2017;7(1):7.CrossRefPubMedCentralGoogle Scholar
  23. 23.
    Offenbacher S, Barros S, Mendoza L, Mauriello S, Preisser J, Moss K, et al. Changes in gingival crevicular fluid inflammatory mediator levels during the induction and resolution of experimental gingivitis in humans. J Clin Periodontol. 2010;37(4):324–33.  https://doi.org/10.1111/j.1600-051X.2010.01543.x.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Teles RP, Gursky LC, Faveri M, Rosa EA, Teles FRF, Feres M, et al. Relationships between subgingival microbiota and GCF biomarkers in generalized aggressive periodontitis. J Clin Periodontol. 2010;37(4):313–23.  https://doi.org/10.1111/j.1600-051X.2010.01534.x.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Aebersold R, Mann M. Mass spectrometry-based proteomics. Nature. 2003;422(6928):198–207.CrossRefPubMedGoogle Scholar
  26. 26.
    Proteomes [database on the Internet]. UniProt. 2017. Available from: http://www.uniprot.org. Accessed: 20 June 2017.
  27. 27.
    Eng JK, McCormack AL, Yates JR. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom. 1994;5(11):976–89.  https://doi.org/10.1016/1044-0305(94)80016-2.CrossRefPubMedGoogle Scholar
  28. 28.
    Frank A, Pevzner P. PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal Chem. 2005;77(4):964–73.  https://doi.org/10.1021/ac048788h.CrossRefPubMedGoogle Scholar
  29. 29.
    DiMaggio PA, Floudas CA. De novo peptide identification via tandem mass spectrometry and integer linear optimization. Anal Chem. 2007;79(4):1433–46.  https://doi.org/10.1021/ac0618425.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    DiMaggio JPA, Floudas CA, Lu B, Yates IIIJR. A hybrid method for peptide identification using integer linear optimization, local database search, and quadrupole time-of-flight or OrbiTrap tandem mass spectrometry. J Proteome Res. 2008;7(4):1584–93.  https://doi.org/10.1021/pr700577z.CrossRefPubMedGoogle Scholar
  31. 31.
    Nesvizhskii AI, Vitek O, Aebersold R. Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat Methods. 2007;4(10):787.CrossRefPubMedGoogle Scholar
  32. 32.
    Nesvizhskii AI. A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics. J Proteome. 2010;73(11):2092–123.  https://doi.org/10.1016/j.jprot.2010.08.009.CrossRefGoogle Scholar
  33. 33.
    Baliban RC, DiMaggio PA, Plazas-Mayorca MD, Young NL, Garcia BA, Floudas CA. A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry. Mol Cell Proteomics. 2010;9(5):764–79.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Lundy FT, Orr DF, Shaw C, Lamey PJ, Linden GJ. Detection of individual human neutrophil α-defensins (human neutrophil peptides 1, 2 and 3) in unfractionated gingival crevicular fluid—A MALDI-MS approach. Mol Immunol. 2005;42(5):575–9.  https://doi.org/10.1016/j.molimm.2004.09.008.CrossRefPubMedGoogle Scholar
  35. 35.
    Pisano E, Cabras T, Montaldo C, Piras V, Inzitari R, Olmi C, et al. Peptides of human gingival crevicular fluid determined by HPLC-ESI-MS. Eur J Oral Sci. 2005;113(6):462–8.  https://doi.org/10.1111/j.1600-0722.2005.00246.x.CrossRefPubMedGoogle Scholar
  36. 36.
    Ngo LH, Veith PD, Chen Y-Y, Chen D, Darby IB, Reynolds EC. Mass spectrometric analyses of peptides and proteins in human gingival crevicular fluid. J Proteome Res. 2010;9(4):1683–93.  https://doi.org/10.1021/pr900775s.CrossRefPubMedGoogle Scholar
  37. 37.
    • Bostanci N, Heywood W, Mills K, Parkar M, Nibali L, Donos N. Application of label-free absolute quantitative proteomics in human gingival crevicular fluid by LC/MSE (Gingival Exudatome). J Proteome Res. 2010;9(5):2191–9.  https://doi.org/10.1021/pr900941z. Pioneer report applying “shotgun” proteomic analysis in GCF. CrossRefPubMedGoogle Scholar
  38. 38.
    • Grant MM, Creese AJ, Barr G, Ling MR, Scott AE, Matthews JB, et al. Proteomic analysis of a noninvasive human model of acute inflammation and its resolution: the twenty-one day gingivitis model. J Proteome Res. 2010;9(9):4732–44.  https://doi.org/10.1021/pr100446f. Pioneer report applying “shotgun” proteomic analysis in GCF. CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Choi Y-J, Heo S-H, Lee J-M, Cho J-Y. Identification of azurocidin as a potential periodontitis biomarker by a proteomic analysis of gingival crevicular fluid. Proteome Sci. 2011;9:42.  https://doi.org/10.1186/1477-5956-9-42.CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Bandhakavi S, Stone MD, Onsongo G, Van Riper SK, Griffin TJ. A dynamic range compression and three-dimensional peptide fractionation analysis platform expands proteome coverage and the diagnostic potential of whole saliva. J Proteome Res. 2009;8(12):5590–600.  https://doi.org/10.1021/pr900675w.CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Gonçalves LDR, Soares MR, Nogueira FCS, Garcia C, Camisasca DR, Domont G, et al. Comparative proteomic analysis of whole saliva from chronic periodontitis patients. J Proteome. 2010;73(7):1334–41.  https://doi.org/10.1016/j.jprot.2010.02.018.CrossRefGoogle Scholar
  42. 42.
    Haigh BJ, Stewart KW, Whelan JRK, Barnett MPG, Smolenski GA, Wheeler TT. Alterations in the salivary proteome associated with periodontitis. J Clin Periodontol. 2010;37(3):241–7.  https://doi.org/10.1111/j.1600-051X.2009.01525.x.CrossRefPubMedGoogle Scholar
  43. 43.
    Gonçalves LR, Soares MR, Nogueira FCS, Garcia CHS, Camisasca DR, Domont G, et al. Analysis of the salivary proteome in gingivitis patients. J Periodontal Res. 2011;46(5):599–606.  https://doi.org/10.1111/j.1600-0765.2011.01378.x.Google Scholar
  44. 44.
    Zhang L, Henson BS, Camargo PM, Wong DT. The clinical value of salivary biomarkers for periodontal disease. Periodontol. 2009;51(1):25–37.  https://doi.org/10.1111/j.1600-0757.2009.00315.x.CrossRefGoogle Scholar
  45. 45.
    Giannobile WV, Beikler T, Kinney JS, Ramseier CA, Morelli T, Wong DT. Saliva as a diagnostic tool for periodontal disease: current state and future directions. Periodontol. 2009;50(1):52–64.  https://doi.org/10.1111/j.1600-0757.2008.00288.x.CrossRefGoogle Scholar
  46. 46.
    Carneiro LG, Venuleo C, Oppenheim FG, Salih E. Proteome data set of human gingival crevicular fluid from healthy periodontium sites by multidimensional protein separation and mass spectrometry. J Periodontal Res. 2012;47(2):248–62.  https://doi.org/10.1111/j.1600-0765.2011.01429.x.CrossRefPubMedGoogle Scholar
  47. 47.
    Bostanci N, Ramberg P, Wahlander Å, Grossman J, Jönsson D, Barnes VM, et al. Label-free quantitative proteomics reveals differentially regulated proteins in experimental gingivitis. J Proteome Res. 2013;12(2):657–78.  https://doi.org/10.1021/pr300761e.CrossRefPubMedGoogle Scholar
  48. 48.
    Baliban RC, Sakellari D, Li Z, DiMaggio PA, Garcia BA, Floudas CA. Novel protein identification methods for biomarker discovery via a proteomic analysis of periodontally healthy and diseased gingival crevicular fluid samples. J Clin Periodontol. 2012;39(3):203–12.  https://doi.org/10.1111/j.1600-051X.2011.01805.x.CrossRefPubMedGoogle Scholar
  49. 49.
    Tsuchida S, Satoh M, Umemura H, Sogawa K, Kawashima Y, Kado S, et al. Proteomic analysis of gingival crevicular fluid for discovery of novel periodontal disease markers. Proteomics. 2012;12(13):2190–202.  https://doi.org/10.1002/pmic.201100655.CrossRefPubMedGoogle Scholar
  50. 50.
    • Baliban RC, Sakellari D, Li Z, Guzman YA, Garcia BA, Floudas CA, et al. J Clin Periodontol. 2013;40(2):131–9.  https://doi.org/10.1111/jcpe.12037. Discovery of sets of biomarkers for periodontal health or disease, using qualitative “shotgun” analysis (presence or absence) and a mathematical model. CrossRefPubMedGoogle Scholar
  51. 51.
    Bertoldi C, Bellei E, Pellacani C, Ferrari D, Lucchi A, Cuoghi A, et al. Non-bacterial protein expression in periodontal pockets by proteome analysis. J Clin Periodontol. 2013;40(6):573–82.  https://doi.org/10.1111/jcpe.12050.CrossRefPubMedGoogle Scholar
  52. 52.
    Silva-Boghossian CM, Colombo APV, Tanaka M, Rayo C, Xiao Y, Siqueira WL. Quantitative proteomic analysis of gingival crevicular fluid in different periodontal conditions. PLoS One. 2013;8(10):e75898.  https://doi.org/10.1371/J.pone.0075898.CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Carneiro LG, Nouh H, Salih E. Quantitative gingival crevicular fluid proteome in health and periodontal disease using stable isotope chemistries and mass spectrometry. J Clin Periodontol. 2014;41(8):733–47.  https://doi.org/10.1111/jcpe.12262.CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Huynh AHS, Veith PD, McGregor NR, Adams GG, Chen D, Reynolds EC, et al. Gingival crevicular fluid proteomes in health, gingivitis and chronic periodontitis. J Periodontal Res. 2015;50(5):637–49.  https://doi.org/10.1111/jre.12244.CrossRefPubMedGoogle Scholar
  55. 55.
    Ngo LH, Darby IB, Veith PD, Locke AG, Reynolds EC. Mass spectrometric analysis of gingival crevicular fluid biomarkers can predict periodontal disease progression. J Periodontal Res. 2013;48(3):331–41.  https://doi.org/10.1111/jre.12012.CrossRefPubMedGoogle Scholar
  56. 56.
    Moriya Y, Obama T, Aiuchi T, Sugiyama T, Endo Y, Koide Y, et al. Quantitative proteomic analysis of gingival crevicular fluids from deciduous and permanent teeth. J Clin Periodontol. 2017;44(4):353–62.  https://doi.org/10.1111/jcpe.12696.CrossRefPubMedGoogle Scholar
  57. 57.
    Guzman YA, Sakellari D, Floudas CA, editors. Discovery of biomarkers using high-throughput proteomics for temporal profiling of periodontitis. Atlanta: AIChE Annual Meeting; 2014.Google Scholar
  58. 58.
    Davis IJ, Jones AW, Creese AJ, Staunton R, Atwal J, Chapple ILC, et al. Longitudinal quantification of the gingival crevicular fluid proteome during progression from gingivitis to periodontitis in a canine model. J Clin Periodontol. 2016;43(7):584–94.  https://doi.org/10.1111/jcpe.12548.CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Schaefer AS, Richter GM, Groessner-Schreiber B, Noack B, Nothnagel M, Mokhtari N-EE, et al. Identification of a shared genetic susceptibility locus for coronary heart disease and periodontitis. PLoS Genet. 2009;5(2):e1000378.  https://doi.org/10.1371/J.pgen.1000378.CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Schaefer AS, Richter GM, Nothnagel M, Manke T, Dommisch H, Jacobs G, et al. A genome-wide association study identifies GLT6D1 as a susceptibility locus for periodontitis. Human Mol Genet. 2010;19(3):553–62.  https://doi.org/10.1093/hmg/ddp508.CrossRefGoogle Scholar
  61. 61.
    Divaris K, Monda KL, North KE, Olshan AF, Reynolds LM, Hsueh W-C, et al. Exploring the genetic basis of chronic periodontitis: a genome-wide association study. Human Mol Genet. 2013;22(11):2312–24.  https://doi.org/10.1093/hmg/ddt065.CrossRefGoogle Scholar
  62. 62.
    Feng P, Wang X, Casado PL, Küchler EC, Deeley K, Noel J, et al. Genome wide association scan for chronic periodontitis implicates novel locus. BMC Oral Health. 2014;14(1):84.CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Freitag-Wolf S, Dommisch H, Graetz C, Jockel-Schneider Y, Harks I, Staufenbiel I, et al. Genome-wide exploration identifies sex-specific genetic effects of alleles upstream NPY to increase the risk of severe periodontitis in men. J Clin Periodontol. 2014;41(12):1115–21.CrossRefPubMedGoogle Scholar
  64. 64.
    • Bostanci N, Bao K. Contribution of proteomics to our understanding of periodontal inflammation. Proteomics. 2017;17(3–4):1500518.  https://doi.org/10.1002/pmic.201500518. Review of the current literature which includes data from proteomic analysis of bacterial origin and describes host-bacterial interactions. CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Preventive Dentistry, Periodontology and Implant Biology, Dental SchoolAristotle University of ThessalonikiThessalonikiGreece

Personalised recommendations