Proteomic analysis of gingival crevicular fluid for discovery of novel periodontal disease markers

Periodontal disease and emerging point-of-care technologies for its diagnosis

Periodontal disease (PD), a chronic inflammatory disorder that damages the tooth and its supporting components, is a common global oral health problem. Understanding the intricacies of these disorders, from gingivitis to severe PD, is critical for efficient treatment, diagnosis, and prevention in dental care. Periodontal biosensors and biomarkers are critical in improving oral health diagnostic skills. Clinicians may accomplish early identification, tailored therapy, and efficient tracking of periodontal diseases by using these technologies, ushering in a new age of accurate oral healthcare. Traditional periodontitis diagnostic methods frequently rely on physical probing and visual examinations, necessitating the development of point-of-care (POC) devices. As periodontal disorders necessitate more precise and rapid diagnosis, incorporating novel innovations in biosensors and biomarkers becomes increasingly crucial. These innovations improve our capacity to diagnose, monitor, and adapt periodontal therapies, bringing in the next phase of customized and effective dental healthcare. The review discusses the characteristics and stages of PD, clinical treatment techniques, prominent biomarkers and infection-associated factors that may be employed to determine PD, biomedical sensing, and POC appliances that have been created so far to diagnose stages of PD and its progression profile, as well as predicting future developments in this field.

Progression from healthy periodontium to gingivitis and periodontitis: Insights from bioinformatics-driven proteomics - A systematic review with meta-analysis

AIM

The current study aimed to: (1) systematically review the published literature regarding the proteomics analyses of saliva and gingival crevicular fluid (GCF) in healthy humans and gingivitis and/or periodontitis patients; and (2) to identify the differentially expressed proteins (DEPs) based on the systematic review, and comprehensively conduct meta-analyses and bioinformatics analyses.

METHODS

An online search of Web of Science, Scopus, and PubMed was performed without any restriction on the year and language of publication. After the identification of the DEPs reported by the included human primary studies, gene ontology (GO), the Kyoto encyclopedia of genes and genomes pathway (KEGG), protein-protein interaction (PPI), and meta-analyses were conducted. The risk of bias among the included studies was evaluated using the modified Newcastle-Ottawa quality assessment scale.

RESULTS

The review identified significant differences in protein expression between healthy individuals and those with gingivitis and periodontitis. In GCF, 247 proteins were upregulated and 128 downregulated in periodontal diseases. Saliva analysis revealed 79 upregulated and 70 downregulated proteins. There were distinct protein profiles between gingivitis and periodontitis, with 159 and 31 unique upregulated proteins in GCF, respectively. Meta-analyses confirmed significant upregulation of various proteins in periodontitis, including ALB and MMP9, while CSTB and GSTP1 were downregulated. AMY1A and SERPINA1 were upregulated in periodontitis saliva. HBD was upregulated in gingivitis GCF, while DEFA3 was downregulated. PPI analysis revealed complex networks of interactions among DEPs. GO and KEGG pathway analyses provided insights into biological processes and pathways associated with periodontal diseases.

CONCLUSION

The ongoing MS-based proteomics studies emphasize the need for a highly sensitive and specific diagnostic tool for periodontal diseases. Clinician acceptance of the eventual diagnostic method relies on its ability to provide superior or complementary information to current clinical assessment procedures. Future research should prioritize the multiplex measurement of multiple biomarkers simultaneously to enhance diagnostic accuracy and large study cohorts are necessary to ensure the validity and reliability of research findings.

A multi-platform analysis of human gingival crevicular fluid reveals ferroptosis as a relevant regulated cell death mechanism during the clinical progression of periodontitis

Ferroptosis is implicated in the pathogenesis of numerous chronic-inflammatory diseases, yet its association with progressive periodontitis remains unexplored. To investigate the involvement and significance of ferroptosis in periodontitis progression, we assessed sixteen periodontitis-diagnosed patients. Disease progression was clinically monitored over twelve weeks via weekly clinical evaluations and gingival crevicular fluid (GCF) collection was performed for further analyses. Clinical metrics, proteomic data, in silico methods, and bioinformatics tools were combined to identify protein profiles linked to periodontitis progression and to explore their potential connection with ferroptosis. Subsequent western blot analyses validated key findings. Finally, a single-cell RNA sequencing (scRNA-seq) dataset (GSE164241) for gingival tissues was analyzed to elucidate cellular dynamics during periodontitis progression. Periodontitis progression was identified as occurring at a faster rate than traditionally thought. GCF samples from progressing and non-progressing periodontal sites showed quantitative and qualitatively distinct proteomic profiles. In addition, specific biological processes and molecular functions during progressive periodontitis were revealed and a set of hub proteins, including SNCA, CA1, HBB, SLC4A1, and ANK1 was strongly associated with the clinical progression status of periodontitis. Moreover, we found specific proteins - drivers or suppressors - associated with ferroptosis (SNCA, FTH1, HSPB1, CD44, and GCLC), revealing the co-occurrence of this specific type of regulated cell death during the clinical progression of periodontitis. Additionally, the integration of quantitative proteomic data with scRNA-seq analysis suggested the susceptibility of fibroblasts to ferroptosis. Our analyses reveal proteins and processes linked to ferroptosis for the first time in periodontal patients, which offer new insights into the molecular mechanisms of progressive periodontal disease. These findings may lead to novel diagnostic and therapeutic strategies.

A simplified protocol for deep quantitative proteomic analysis of gingival crevicular fluid for skeletal maturity indicators

Assessment of craniofacial skeletal maturity is of great importance in orthodontic diagnosis and treatment planning. Traditional radiographic methods suffer from clinician subjectivity and low reproducibility. Recent biochemical methods, such as the use of gingival crevicular fluid (GCF) protein biomarkers involved in bone metabolism, have provided new opportunities to assess skeletal maturity. However, mass spectrometry (MS)-based GCF proteomic analysis still faces significant challenges, including the interference of high abundance proteins, laborious sample prefractionation and relatively limited coverage of GCF proteome. To improve GCF sample processing and further discover novel biomarkers, we herein developed a single-pot, solid-phase-enhanced sample-preparation (SP3)-based high-field asymmetric waveform ion mobility spectrometry (FAIMS)-MS protocol for deep quantitative analysis of the GCF proteome for skeletal maturity indicators. SP3 combined with FAIMS could minimize sample loss and eliminate tedious and time-consuming offline fractionation, thereby simplifying GCF sample preparation and improving analytical coverage and reproducibility of the GCF proteome. A total of 5407 proteins were identified in GCF samples from prepubertal and circumpubertal groups, representing the largest dataset of human GCF proteome to date. Compared to the prepubertal group, 61 proteins were differentially expressed (31 up-regulated, 30 down-regulated) in the circumpubertal group. The six-protein marker panel, including ATP5D, CLTA, CLTB, DNM2, HSPA8 and NCK1, showed great potential to predict the circumpubertal stage (ROC-AUC 0.937), which provided new insights into skeletal maturity assessment.

Starch treatment improves the salivary proteome for subject identification purposes

Identification of subjects, including perpetrators, is one of the most crucial goals of forensic science. Saliva is among the most common biological fluids found at crime scenes, containing identifiable components. DNA has been the most prominent identifier to date, but its analysis can be complex due to low DNA yields and issues preserving its integrity at the crime scene. Proteins are emerging as viable candidates for subject identification. Previous work has shown that the salivary proteome of the least-abundant proteins may be helpful for subject identification, but more optimized techniques are needed. Among them is removing the most abundant proteins, such as salivary α-amylase. Starch treatment of saliva samples elicited the removal of this enzyme and that of glycosylated, low-molecular-weight proteins, proteases, and immunoglobulins, resulting in a saliva proteome profile enriched with a subset of proteins, allowing a more reliable and nuanced subject identification.

Proteomic profile of human gingival crevicular fluid reveals specific biological and molecular processes during clinical progression of periodontitis

BACKGROUND AND OBJECTIVE

There is no clear understanding of molecular events occurring in the periodontal microenvironment during clinical disease progression. Our aim was to explore qualitative and quantitative differences in gingival crevicular fluid (GCF) protein profiles from patients diagnosed with periodontitis between non-progressive and progressive periodontal sites.

METHODS

Five systemically healthy patients diagnosed with periodontitis were monitored weekly in their progression of the disease and GCF samples from 10 candidate sites were obtained. Two groups of five sites, matched from an equal number of teeth, were selected from the five patients: Progression (PG) and Non-Progression (NP). Global protein identification was performed with high-throughput proteomic approaches and label-free analysis determined their relative abundances. Proteins were identified by Proteome Discoverer v2.4 and searched against human SwissProt protein databases. Enrichment bioinformatic analyses were performed in STRING-DB and ShinyGO environment.

RESULTS

1504 and 1500 proteins were identified in NP and PG respectively. Forty-eight proteins were exclusively identified in PG, while 52 were identified in NP. Moreover, 35 proteins were more abundant in PG and 29 proteins in NP (twofold change, p < .05). The NP group was mainly represented by proteins from "response to biotic stimuli and other organisms," "processes of cell death regulation," "peptidase regulation," "protein ubiquitination," and "ribosomal activity" GO categories. The most represented GO categories of the PG group were "assembly of multiprotein complexes," "catabolic processes," "lipid metabolism," and "binding to hemoglobin and haptoglobin."

CONCLUSIONS

There are quantitative and qualitative differences in the proteome of GCF from periodontal sites according to the status of clinical progression of periodontitis. Progressive periodontitis sites are characterized by a protein profile associated with catabolic processes, immune response, and response to cellular stress, while stable periodontitis sites show a protein profile mainly related to wound repair and healing processes, cell death regulation, and chaperone-mediated autophagy. Understanding the etiopathogenic role of these profiles in progressive periodontitis may help to develop new diagnostic and therapeutic approaches.

Alpha-Defensin 1: An Emerging Periodontitis Biomarker

Background: Research on the development of reliable diagnostic targets is being conducted to overcome the high prevalence and difficulty in managing periodontitis. However, despite the development of various periodontitis target markers, their practical application has been limited due to poor diagnostic accuracy. In this study, we present an improved periodontitis diagnostic target and explore its role in periodontitis. Methods: Gingival crevicular fluid (GCF) was collected from healthy individuals and periodontitis patients, and proteomic analysis was performed. The target marker levels for periodontitis were quantified in GCF samples by enzyme-linked immunosorbent assay (ELISA). Mouse bone marrow-derived macrophages (BMMs) were used for the osteoclast formation assay. Results: LC-MS/MS analysis of whole GCF showed that the level of alpha-defensin 1 (DEFA-1) was higher in periodontitis GCF than in healthy GCF. The comparison of periodontitis target proteins galactin-10, ODAM, and azurocidin proposed in other studies found that the difference in DEFA-1 levels was the largest between healthy and periodontitis GCF, and periodontitis was more effectively distinguished. The differentiation of RANKL-induced BMMs into osteoclasts was significantly reduced by recombinant DEFA-1 (rDEFA-1). Conclusions: These results suggest the regulatory role of DEFA-1 in the periodontitis process and the relevance of DEFA-1 as a diagnostic target for periodontitis.

Identification of nine signature proteins involved in periodontitis by integrated analysis of TMT proteomics and transcriptomics

Recently, there are many researches on signature molecules of periodontitis derived from different periodontal tissues to determine the disease occurrence and development, and deepen the understanding of this complex disease. Among them, a variety of omics techniques have been utilized to analyze periodontitis pathology and progression. However, few accurate signature molecules are known and available. Herein, we aimed to screened and identified signature molecules suitable for distinguishing periodontitis patients using machine learning models by integrated analysis of TMT proteomics and transcriptomics with the purpose of finding novel prediction or diagnosis targets. Differential protein profiles, functional enrichment analysis, and protein–protein interaction network analysis were conducted based on TMT proteomics of 15 gingival tissues from healthy and periodontitis patients. DEPs correlating with periodontitis were screened using LASSO regression. We constructed a new diagnostic model using an artificial neural network (ANN) and verified its efficacy based on periodontitis transcriptomics datasets (GSE10334 and GSE16134). Western blotting validated expression levels of hub DEPs. TMT proteomics revealed 5658 proteins and 115 DEPs, and the 115 DEPs are closely related to inflammation and immune activity. Nine hub DEPs were screened by LASSO, and the ANN model distinguished healthy from periodontitis patients. The model showed satisfactory classification ability for both training (AUC=0.972) and validation (AUC=0.881) cohorts by ROC analysis. Expression levels of the 9 hub DEPs were validated and consistent with TMT proteomics quantitation. Our work reveals that nine hub DEPs in gingival tissues are closely related to the occurrence and progression of periodontitis and are potential signature molecules involved in periodontitis.

Proteomics Disclose the Potential of Gingival Crevicular Fluid (GCF) as a Source of Biomarkers for Severe Periodontitis

Periodontal disease is a widespread disorder comprising gingivitis, a mild early gum inflammation, and periodontitis, a more severe multifactorial inflammatory disease that, if left untreated, can lead to the gradual destruction of the tooth-supporting apparatus. To date, effective etiopathogenetic models fully explaining the clinical features of periodontal disease are not available. Obviously, a better understanding of periodontal disease could facilitate its diagnosis and improve its treatment. The purpose of this study was to employ a proteomic approach to analyze the gingival crevicular fluid (GCF) of patients with severe periodontitis, in search of potential biomarkers. GCF samples, collected from both periodontally healthy sites (H-GCF) and the periodontal pocket (D-GCF), were subjected to a comparison analysis using sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). A total of 26 significantly different proteins, 14 up-regulated and 12 down-regulated in D-GCF vs. H-GCF, were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The main expressed proteins were inflammatory molecules, immune responders, and host enzymes. Most of these proteins were functionally connected using the STRING analysis database. Once validated in a large scale-study, these proteins could represent a cluster of promising biomarkers capable of making a valuable contribution for a better assessment of periodontitis.

Early Elevation of Cell-free DNA After Acute Mesenteric Ischemia in Rats

BACKGROUND

Acute mesenteric ischemia (AMI) is challenging to diagnose in the early phase. We tested the hypothesis that blood levels of cell-free DNA would increase early after AMI. In addition, proteome analysis was conducted as an exploratory analysis to identify other potential diagnostic biomarkers.

METHODS

Mesenteric ischemia, abdominal sepsis, and sham model were compared in Sprague-Dawley rats. The abdominal sepsis model was induced by cecum puncture and mesenteric ischemia model by ligation of the superior mesenteric artery. Blood levels of cell-free DNA were measured 2 h and 6 h after wound closure. Shotgun proteome analysis was performed using plasma samples obtained at the 2 h timepoint; quantitative analysis was conducted for proteins detected exclusively in the AMI models.

RESULTS

Blood cell-free DNA levels at 2 h after wound closure were significantly higher in the AMI model than in the sham and the abdominal sepsis models (P < 0.05). Cell-free DNA was positively correlated with the pathologic ischemia severity score (correlation coefficient 0.793-0.834, P < 0.001). Derivative proteome analysis in blood at 2-h time point revealed higher intensity of paraoxonase-1 in the AMI models than in the abdominal sepsis models; the significantly high blood paraoxonase-1 levels in the AMI models were confirmed in a separate quantitative analysis (P = 0.015).

CONCLUSIONS

Cell-free DNA was demonstrated to be a promising biomarker for the early diagnosis of mesenteric ischemia in a rat model of AMI. Paraoxonase-1 may also play a role in the differential diagnosis of mesenteric ischemia from abdominal sepsis. The current results warrant further investigation in human studies.

A qualitative and quantitative analysis of the human gingival crevicular fluid proteome and metaproteome

Gingival crevicular fluid (GCF) is an integral part of oral fluid that plays a special role in maintaining the structure of junctional epithelium and defending against bacterial infection. In this study, we comprehensively analysed the composition of the human GCF proteome and metaproteome simultaneously to obtain multidimensional information about GCF. A total of 3680 human proteins (2540 with at least two unique peptides) were identified in the normal GCF sample, and their functions were mainly associated with immune function and inflammation. Among these proteins, 1874 proteins could be quantified by the iBAQ algorithm, and their abundances spanned a dynamic range of six orders of magnitude. For the GCF metaproteome, a total of 3082 proteins and 69 genera were found. In addition, 16 genera were not identified by GCF metagenomic analysis. Compared to the saliva metaproteome, 32 genera were found to be in common. The protein quantitative analysis showed that the abundance of GCF metaproteome contributed to approximately 4.17% of the total GCF proteome. The top three most abundant genera were Fusobacterium, Corynebacterium, and Leptotrichia. The above data will be useful for future research on GCF-related diseases.

Pyruvate Kinase, Inflammation and Periodontal Disease

Pyruvate kinase (PK) is the final and rate-limiting enzyme in glycolysis. It has four isoforms PKM1, PKM2, PKL and PKR. PK can form homo tetramers, dimers or monomers. The tetrameric form has the most catalytic activity; however, the dimeric form has non-canonical functions that contribute to the inflammatory response, wound healing and cellular crosstalk. This brief review explores these functions and speculates on their role in periodontal disease.

Ubiquitination and Deubiquitination in Oral Disease

Oral health is an integral part of the general health and well-being of individuals. The presence of oral disease is potentially indicative of a number of systemic diseases and may contribute to their early diagnosis and treatment. The ubiquitin (Ub) system has been shown to play a role in cellular immune response, cellular development, and programmed cell death. Ubiquitination is a post-translational modification that occurs in eukaryotes. Its mechanism involves a number of factors, including Ub-activating enzymes, Ub-conjugating enzymes, and Ub protein ligases. Deubiquitinating enzymes, which are proteases that reversely modify proteins by removing Ub or Ub-like molecules or remodeling Ub chains on target proteins, have recently been regarded as crucial regulators of ubiquitination-mediated degradation and are known to significantly affect cellular pathways, a number of biological processes, DNA damage response, and DNA repair pathways. Research has increasingly shown evidence of the relationship between ubiquitination, deubiquitination, and oral disease. This review investigates recent progress in discoveries in diseased oral sites and discusses the roles of ubiquitination and deubiquitination in oral disease.

Metaproteome and metabolome of oral microbial communities

The emergence of high-throughput technologies for the comprehensive measurement of biomolecules, also referred to as "omics" technologies, has helped us gather "big data" and characterize microbial communities. In this article, we focus on metaproteomic and metabolomic approaches that support hypothesis-driven investigations on various oral biologic samples. Proteomics reveals the working units of the oral milieu and metabolomics unveils the reactions taking place; and so these complementary techniques can unravel the functionality and underlying regulatory processes within various oral microbial communities. Current knowledge of the proteomic interplay and metabolic interactions of microorganisms within oral biofilm and salivary microbiome communities is presented and discussed, from both clinical and basic research perspectives. Communities indicative of, or from, health, caries, periodontal diseases, and endodontic lesions are represented. Challenges, future prospects, and examples of best practice are given.

Label-free quantitative proteomic analysis of gingival crevicular fluid to identify potential early markers for root resorption

Background

Orthodontically-induced root resorption is an iatrogenic effect and it cannot be examined regularly due to the harmful effects of sequential doses of radiation with more frequent radiography. This study aims to compare protein abundance (PA) of pre-treatment and during orthodontic treatment for root resorption and to determine potential early markers for root resorption.

Methods

Ten subjects (n = 10) who had upper and lower fixed appliances (MBT, 3 M Unitek, 0.022″ × 0.028″) were recruited for this study. Human gingival crevicular fluid (GCF) was obtained using periopaper strips at pre-treatment (T0), 1 month (T1), 3 months (T3), and 6 months (T6) of orthodontic treatment. Periapical radiographs of the upper permanent central incisors were taken at T0 and T6 to measure the amount of root resorption. Identification of changes in PA was performed using liquid chromatography-tandem mass spectrometry. Student’s t-test was then performed to determine the significance of the differences in protein abundance before and after orthodontic treatment.

Results

Our findings showed that all ten subjects had mild root resorption, with an average resorption length of 0.56 ± 0.30 mm. A total of 186 proteins were found to be commonly present at T0, T1, T3, and T6. There were significant changes in the abundance of 16 proteins (student’s t-test, p ≤ 0.05). The increased PA of S100A9, immunoglobulin J chain, heat shock protein 1A, immunoglobulin heavy variable 4–34 and vitronectin at T1 suggested a response to stress that involved inflammation during the early phase of orthodontic treatment. On the other hand, the increased PA of thymidine phosphorylase at T3 suggested growth promotion and, angiogenic and chemotactic activities.

Conclusions

The identified proteins can be potential early markers for root resorption based on the increase in their respective PA and predicted roles during the early phase of orthodontic treatment. Non-invasive detection of root resorption using protein markers as early as possible is extremely important as it can aid orthodontists in successful orthodontic treatment.

Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases

Given its intrinsic nature, gingival crevicular fluid (GCF) is an attractive source for the discovery of novel biomarkers of periodontal diseases. GCF contains antimicrobial peptides and small proteins which could play a role in specific immune-inflammatory responses to guarantee healthy gingival status and to prevent periodontal diseases. Presently, several proteomics studies have been performed leading to increased coverage of the GCF proteome, however fewer efforts have been done to explore its natural peptides. To fill such gap, this review provides an overview of the mass spectrometric platforms and experimental designs aimed at GCF peptidome profiling, including our own data and experiences gathered from over several years of matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF MS) based approach in this field. These tools might be useful for capturing snapshots containing diagnostic clinical information on an individual and population scale, which may be used as a specific code not only for the diagnosis of the nature or the stage of the inflammatory process in periodontal disease, but more importantly, for its prognosis, which is still an unmet medical need. As a matter of fact, current peptidomics investigations suffer from a lack of standardized procedures, posing a serious problem for data interpretation. Descriptions of the efforts to address such concerns will be highlighted.

Proteomics approach for biomarkers and diagnosis of periodontitis: systematic review

Quantitative proteomic workflow based on mass spectrometry (MS) is recently developed by the researchers to screen for biomarkers in periodontal diseases comprising periodontitis. Periodontitis is known for chronic inflammatory disease characterized by progressive destruction of the tooth-supporting apparatus, yet has a lack of clear pathobiology based on a discrepancy between specified categories and diagnostic vagueness. The objective of this review was to outlined the accessible information related to proteomics studies on periodontitis. The Preferred Reporting Items for Systematical Reviews and Meta-Analysis (PRISMA) statement guides to acquaint proteomic analysis on periodontal diseases was applied. Three databases were used in this study, such as Pubmed, ScienceDirect and Biomed Central from 2009 up to November 2019. Proteomics analysis platforms that used in the studies were outlined. Upregulated and downregulated proteins findings data were found, in which could be suitable as candidate biomarkers for this disease.

Differential proteomic analysis of serum exosomes reveals alterations in progression of Parkinson disease

Exosomes are nanometer-sized vesicles with intercellular communication functions, and their encapsulated proteins may participate in the pathological process of neurodegenerative disorders. The aim of this study was to identify the protein changes of serum exosomes in Parkinson disease (PD) patients with different disease progress types, and to identify potential biomarkers. The exosomes of PD patients with different severity and healthy control group were isolated from serum. The exosome proteins were analyzed by mass spectrometry with label-free quantitative proteomics. A total of 429 proteins were identified, of which 14 were significantly different in mild and severe PD patients. The expression levels of 7 proteins, including pigmented epithelium-derived factor, afamin, apolipoprotein D and J, were significantly increased in PD patients. The expression levels of 7 proteins, including complement C1q and protein Immunoglobulin Lambda Variable 1-33 (IGLV1-33)Cluster -33, were decreased in PD patients. These differentially expressed proteins were analyzed by gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, which confirmed that the interaction between prion diseases and ECM receptors was the most significant pathways of enrichment. The changes of proteins and pathways may be related to the pathophysiological mechanism of PD. Therefore, some of these proteins could be considered as potential biomarkers for early PD diagnosis.

Proteomic analysis of gingival crevicular fluid for novel biomarkers of pubertal growth peak

Background

Detection of pubertal growth peak is vital in orthodontic treatment timing and planning. Gingival crevicular fluid (GCF) contains abundant proteins from different sources and is an ideal source of biomarkers. The aim of this research is to detect candidate GCF biomarkers of pubertal growth by tandem mass tags (TMT) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to help diagnosis and treatment planning of functional treatment.

Methods

Forty subjects were recruited and were divided into pubertal and post-pubertal groups according to cervical vertebral maturation method. GCF samples were collected by paper points. GCF proteome of pubertal and post-pubertal subjects was compared by TMT labelling coupled with LC-MS/MS.

Results

A total of 537 proteins were detected in GCF samples, with 183 proteins detected in GCF for the first time. These proteins were involved in processes of immune response, ion transport, and signal transduction. The GCF concentration of vitamin D binding protein (DBP) and seroserotransferrin (Tf) was significantly higher in pubertal than that in post-pubertal subjects. DBP and Tf, therefore, were considered to be candidate biomarkers of pubertal growth. This result was validated using GCF samples from new subjects (P < 0.05).

Conclusion

Our results indicate that TMT labelling coupled with LC-MS/MS were proved to be a useful method for proteomic analysis of GCF with high accuracy. The expression of DBP and Tf was increased in children at circumpubertal stage and can be considered candidate biomarkers of pubertal growth.

Current Status of Proteomic Technologies for Discovering and Identifying Gingival Crevicular Fluid Biomarkers for Periodontal Disease

Periodontal disease is caused by bacteria in dental biofilms. To eliminate the bacteria, immune system cells release substances that inflame and damage the gums, periodontal ligament, or alveolar bone, leading to swollen bleeding gums, which is a sign of gingivitis. Damage from periodontal disease can cause teeth to loosen also. Studies have demonstrated the proteomic approach to be a promising tool for the discovery and identification of biochemical markers of periodontal diseases. Recently, many studies have applied expression proteomics to identify proteins whose expression levels are altered by disease. As a fluid lying in close proximity to the periodontal tissue, the gingival crevicular fluid (GCF) is the principal target in the search for periodontal disease biomarkers because its protein composition may reflect the disease pathophysiology. Biochemical marker analysis of GCF is effective for objective diagnosis in the early and advanced stages of periodontal disease. Periodontal diseases are also promising targets for proteomics, and several groups, including ours, have applied proteomics in the search for GCF biomarkers of periodontal diseases. This search is of continuing interest in the field of experimental and clinical periodontal disease research. In this article, we summarize the current situation of proteomic technologies to discover and identify GCF biomarkers for periodontal diseases.

Deep sequencing salivary proteins for periodontitis using proteomics

OBJECTIVES

Saliva is a bodily fluid transuded from gingival crevice fluid and blood and contains many proteins. Proteins in saliva have been studied as markers for periodontal diseases. Mass spectrometric analysis is applied to investigate biomarker proteins that are related to periodontitis.

MATERIAL AND METHODS

Saliva samples were collected from 207 participants including 36 pairs matched for age, sex, and smoking who joined Yangpyeong health cohort. Periodontitis was defined by 2005 5th European guideline. Shotgun proteomics was applied to detect proteins from saliva samples. Principal component analysis and Ingenuity Pathway Analysis for canonical pathway and protein pathway were applied. Protein-protein interaction was also applied. Enzyme-linked immunosorbent assay (ELISA) was used to verify the candidate protein markers among another matched participants (n = 80).

RESULTS

Shotgun proteomics indicated that salivary S100A8 and S100A9 were candidate biomarkers for periodontitis. ELISA confirmed that both salivary S100A8 and S100A9 were higher in those with periodontitis compared to those without periodontitis (paired-t test, p < 0.05).

CONCLUSION

Our proteomics data showed that S100A8 and S100A9 in saliva could be candidate biomarkers for periodontitis. The rapid-test-kit using salivary S100A8 and S100A9 will be a practical tool for reducing the risk of periodontitis and promotion of periodontal health.

CLINICAL RELEVANCE

A rapid-test-kit using salivary biomarkers, S100A8 and S100A9, could be utilized by clinicians and individuals for screening periodontitis, which might reduce the morbidity of periodontitis and promote periodontal health.

Quantitative gingival crevicular fluid proteome in type 2 diabetes mellitus and chronic periodontitis

OBJECTIVE

The aim of this study was to investigate the proteome of the gingival crevicular fluid comparing the relative abundance of proteins from type 2 diabetes mellitus (2DM) individuals and chronic periodontitis (CP) affected sites, subjects affected by both conditions and healthy individuals.

MATERIAL AND METHODS

Twenty individuals were equally allocated in four groups, 2DM with CP, 2DM periodontally healthy, CP without 2DM, and periodontally healthy without 2DM. The relative quantification of proteins was accessed with iTRAQ labeling and mass spectrometry.

RESULTS AND CONCLUSION

A total of 104 proteins showed significant differences in abundance in pairwise comparisons. Some presented different levels in all diseased groups as compared to control, either increasing (rap guanine nucleotide exchange factor, S100A8, S100A9, and immunoglobulins) or decreasing (actins, myristoylated alanine-rich C-kinase substrate, and glutathione S-transferase). Other differences were specific for a given condition: Titin, neutrophil elastase, and myeloperoxidase levels were higher in the DP group, cathelicidin antimicrobial peptide decreased in CP, and annexin decreased in DH. These differences in the proteome can provide clues for further studies that will validate the variation in their levels and their role in both diseases.

Protein-Based Salivary Profiles as Novel Biomarkers for Oral Diseases

The Global Burden of Oral Diseases affects 3.5 billion people worldwide, representing the number of people affected by the burden of untreated dental caries, severe periodontal disease, and edentulism. Thus, much more efforts in terms of diagnostics and treatments must be provided in the fight of these outcomes. In this sense, recently, the study of saliva as biological matrix has been identified as a new landmark initiative in the search of novel and useful biomarkers to prevent and diagnose these conditions. Specifically, saliva is a rich reservoir of different proteins and peptides and accessible due to recent advances in molecular biology and specially in targeted and unbiased proteomics technologies. Nonetheless, emerging barriers are an obstacle to the study of the salivary proteome in an effective way. This review aims at giving an overall perspective of salivary biomarkers identified in several oral diseases by means of molecular biology approaches.

Ubiquitination in Periodontal Disease: A Review

Periodontal disease (periodontitis) is a chronic inflammatory condition initiated by microbial infection that leads to gingival tissue destruction and alveolar bone resorption. The periodontal tissue's response to dental plaque is characterized by the accumulation of polymorphonuclear leukocytes, macrophages, and lymphocytes, all of which release inflammatory mediators and cytokines to orchestrate the immunopathogenesis of periodontal disease. Ubiquitination is achieved by a mechanism that involves a number of factors, including an ubiquitin-activating enzyme, ubiquitin-conjugating enzyme, and ubiquitin-protein ligase. Ubiquitination is a post-translational modification restricted to eukaryotes that are involved in essential host processes. The ubiquitin system has been implicated in the immune response, development, and programmed cell death. Increasing numbers of recent reports have provided evidence that many approaches are delivering promising reports for discovering the relationship between ubiquitination and periodontal disease. The scope of this review was to investigate recent progress in the discovery of ubiquitinated protein in diseased periodontium and to discuss the ubiquitination process in periodontal diseases.

Identification of salivary protein biomarkers for orthodontically induced inflammatory root resorption

PURPOSE

Orthodontically induced inflammatory root resorption (OIIRR) is one of the most prevalent and unavoidable consequence of orthodontic tooth movement. The aim of this study was to discover potential diagnostic protein biomarkers for detection of OIIRR in whole saliva (WS).

MATERIAL AND METHODS

Unstimulated WS was collected from 72 subjects: 48 OIIRR patients and 24 untreated, generally healthy, age and gender matched controls. Radiographic assessment of periapical x-rays of four upper incisors taken before and 9 months after bonding was done. High-abundance proteins were depleted followed by two-dimensional-gel-electrophoresis and quantitative mass spectrometry (qMS). Finally, to initially validate qMS results, Western blotting was performed.

RESULTS

qMS revealed differentially expressed proteins in the moderate-to-severe OIIRR group, which have never been found in WS before. Additionally, in the moderate-to-severe young OIIRR group, the pathogenetic mechanisms related to actin cytoskeleton regulation and Fc gamma R- mediated phagocytosis were detected, while in adults- to focal adhesion. Preliminary validation by Western blotting of fetuin-A and p21-ARC indicated expression profile trends similar to those identified by qMS.

CONCLUSION

The significance of WS novel proteomic methodologies is clearly demonstrated for detecting new OIIRR biomarkers as well as for unveiling possible novel pathogenetic mechanisms in both young and adult patients.

Human Gingival Crevicular Fluids (GCF) Proteomics: An Overview

Like other fluids of the human body, a gingival crevicular fluid (GCF) contains proteins, a diverse population of cells, desquamated epithelial cells, and bacteria from adjacent plaque. Proteomic tools have revolutionized the characterization of proteins and peptides and the detection of early disease changes in the human body. Gingival crevicular fluids (GCFs) are a very specific oral cavity fluid that represents periodontal health. Due to their non-invasive sampling, they have attracted proteome research and are used as diagnostic fluids for periodontal diseases and drug analysis. The aim of this review is to explore the proteomic science of gingival crevicular fluids (GCFs), their physiology, and their role in disease detection.

Qualitative and Quantitative Proteome Analysis of Oral Fluids in Health and Periodontal Disease by Mass Spectrometry

The significance of protein identification and characterization by classical protein chemistry approaches is clearly highlighted by our detailed understanding of the biological systems assembled over a time period of almost a century. The advent of state-of-the-art mass spectrometry (MS) with sensitivity, speed, and global protein analysis capacity without individual protein purification has transformed the classical protein chemistry with premise to accelerate discovery. These combined with the ability of the oral fluids such as whole saliva (WS) and gingival crevicular fluid (GCF) to reflect both systemic and locally derived proteins have generated significant interest to characterize these fluids more extensively by MS technology. This chapter deals with the experimental details of preanalytical steps using multidimensional protein separation combined with MS analysis of WS and GCF to achieve detailed protein composition at qualitative and quantitative levels. These approaches are interfaced with gold standard "stable-isotope" labeling technologies for large-scale quantitative MS analysis which is a prerequisite to determine accurate alterations in protein levels as a function of disease progression. The latter incorporates two stable-isotope chemistries one specific for cysteine containing proteins and the other universal amine-specific reagent in conjunction with oral fluids in health and periodontal disease to perform quantitative MS analysis. In addition, specific preanalytical steps demanded by the oral fluids such as GCF and WS for sample preparations to overcome limitations and uncertainties are elaborated for reliable large-scale quantitative MS analysis.

Metabolomic Analysis of Gingival Crevicular Fluid Using Gas Chromatography/Mass Spectrometry

Periodontitis is one of the most prevalent threats to oral health as the most common cause of tooth loss. In order to perform effective treatment, a clinical test that detect sites where disease activity is high and predicts periodontal tissue destruction is strongly desired, however, it is still difficult to prognose the periodontal tissue breakdown on the basis of conventional methods. The aim of this study is to examine the usefulness of gas chromatography/mass spectrometry (GC/MS), which could eventually be used for on-site analysis of metabolites in gingival crevicular fluid (GCF) in order to objectively diagnose periodontitis at a molecular level. GCF samples were collected from two diseased sites (one site with a moderate pocket and another site with a deep pocket) from each patient and from clinically healthy sites of volunteers. Nineteen metabolites were identified using GC/MS. Total ion current chromatograms showed broad differences in metabolite peak patterns between GCF samples obtained from healthy sites, moderate-pocket sites, and deep-pocket sites. The intensity difference of some metabolites was significant at sites with deep pockets compared to healthy sites. Additionally, metabolite intensities at moderate-pocket sites showed an intermediate profile between the severely diseased sites and healthy sites, which suggested that periodontitis progression could be observed with a changing metabolite profile. Principal component analysis confirmed these observations by clearly delineating healthy sites and sites with deep pockets. These results suggest that metabolomic analysis of GCF could be useful for prediction and diagnosis of periodontal disease in a single visit from a patient and provides the groundwork for establishing a new, on-site diagnostic method for periodontitis.

Advances of Proteomic Sciences in Dentistry

Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.

Absolute quantification of 35 plasma biomarkers in human saliva using targeted MS

BACKGROUND

Although the use of human saliva for diagnosing disease has been known to be of great clinical potential, few attempts have been made so far to develop its use. In this work, we developed an MRM-MS approach for 35 plasma biomarkers using human saliva in a clinical environment.

METHODS & RESULTS

A 30-min micro LC-MS/MS run in MRM mode was conducted in order to quantify the 35 plasma proteins in human saliva. Sample preparation procedures were performed in quadruplicate and analyzed in duplicate. Results show that 32 of the 35 plasma proteins were quantified in human saliva using calibration curves in the 2- log10 dynamic ranges with excellent linearity.

DISCUSSION/CONCLUSION

Our MRM method is compatible with routine measurements in daily clinical practice.

Functionality of HDL: antioxidation and detoxifying effects

High-density lipoproteins (HDL) are complexes of multiple talents, some of which have only recently been recognised but all of which are under active investigation. Clinical interest initially arose from their amply demonstrated role in atherosclerotic disease with their consequent designation as a major cardiovascular disease (CVD) risk factor. However, interest is no longer confined to vascular tissues, with the reports of impacts of the lipoprotein on pancreatic, renal and nervous tissues, amongst other possible targets. The ever-widening scope of HDL talents also encompasses environmental hazards, including infectious agents and environmental toxins. In almost all cases, HDL would appear to have a beneficial impact on health. It raises the intriguing question of whether these various talents emanate from a basic ancestral function to protect the cell.The following chapter will illustrate and review our current understanding of some of the functions attributed to HDL. The first section will look at the antioxidative functions of HDL and possible mechanisms that are involved. The second section will focus specifically on paraoxonase-1 (PON1), which appears to bridge the divide between the two HDL functions discussed herein. This will lead into the final section dealing with HDL as a detoxifying agent protecting against exposure to environmental pathogens and other toxins.

Gingival crevicular fluid proteomes in health, gingivitis and chronic periodontitis

OBJECTIVE

The aim of this study was to compare the proteome composition of gingival crevicular fluid obtained from healthy periodontium, gingivitis and chronic periodontitis affected sites.

BACKGROUND

Owing to its site-specific nature, gingival crevicular fluid is ideal for studying biological processes that occur during periodontal health and disease progression. However, few studies have been conducted into the gingival crevicular fluid proteome due to the small volumes obtained.

METHODS

Fifteen males were chosen for each of three different groups, healthy periodontium, gingivitis and chronic periodontitis. They were categorized based on clinical measurements including probing depth, bleeding on probing, plaque index, radiographic bone level, modified gingival index and smoking status. Gingival crevicular fluid was collected from each patient, pooled into healthy, gingivitis and chronic periodontitis groups and their proteome analyzed by gel electrophoresis and liquid chromatography electrospray ionization ion trap tandem mass spectrometry.

RESULTS

One hundred and twenty-one proteins in total were identified, and two-thirds of these were identified in all three conditions. Forty-two proteins were considered to have changed in abundance. Of note, cystatin B and cystatin S decreased in abundance from health to gingivitis and further in chronic periodontitis. Complement proteins demonstrated an increase from health to gingivitis followed by a decrease in chronic periodontitis. Immunoglobulins, keratin proteins, fibronectin, lactotransferrin precursor, 14-3-3 protein zeta/delta, neutrophil defensin 3 and alpha-actinin exhibited fluctuations in levels.

CONCLUSION

The gingival crevicular fluid proteome in each clinical condition was different and its analysis may assist us in understanding periodontal pathogenesis.

Increased cell proliferation and differential protein expression induced by low-level Er:YAG laser irradiation in human gingival fibroblasts: proteomic analysis

Erbium-doped yttrium aluminum garnet (Er:YAG) laser treatment has demonstrated favorable wound healing effect after periodontal therapy. One of the reasons may be the positive biological effect of the low-level laser on the irradiated tissues, although the mechanism remains unclear. The aim of this study was to investigate the effect of low-level Er:YAG laser irradiation on cell proliferation and laser-induced differential expression of proteins in human gingival fibroblasts (HGFs) by proteomic analysis. In the first experiment, HGFs were exposed to low-level Er:YAG laser irradiation and the laser-induced cell proliferation and damage were evaluated on day 3. In the second experiment, proteomic analysis was performed on day 1 after irradiation. The peptides prepared from HGFs were analyzed by a hybrid ion trap-Fourier transform mass spectrometer, Mascot search engine, and UniProtKB database. A significant increase in cell proliferation without cell damage after irradiation was observed. Among the total identified 377 proteins, 59 proteins, including galectin-7, which was associated with the process of wound healing, were upregulated and 15 proteins were downregulated in laser-treated HGFs. In the third experiment, the increase in messenger RNA (mRNA) and protein expression of galectin-7 in the irradiated HGFs was validated by various analytical techniques. In addition, the effect of recombinant human galectin-7 on the modulation of HGFs proliferation was confirmed. The results indicate that low-level Er:YAG laser irradiation can promote HGF proliferation and induce a significant change in protein expression and the upregulation of galectin-7 expression may partly contribute to the increase in cell proliferation.

Mass spectrometry analysis of gingival crevicular fluid in the presence of external root resorption

INTRODUCTION

In this study, we used liquid chromatography-mass spectrometry (LC-MS) to investigate the differences in the composition of gingival crevicular fluid between resorbing deciduous molars and nonresorbing permanent teeth. The main goal was to identify novel biomarkers associated with root resorption.

METHODS

Eleven children (4 boys, 7 girls) in the mixed dentition were selected to participate in this split-mouth design study, in which a deciduous second molar with radiographic evidence of root resorption served as the experimental site, and the permanent first molar on the contralateral quadrant was the control site. Gingival crevicular fluid was collected using absorbing strips. A total of 22 samples (11 root resorption, 11 control) were each analyzed with 1-dimensional LC-MS. The remaining samples were then pooled across the 11 patients and analyzed by 2-dimensional LC-MS. The output files were converted to mascot generic format, which can be used to perform protein identification with conventional search engines.

RESULTS

The 2-dimensional LC-MS protocol was able to identify 2789 and 2421 proteins in the control and resorption pooled samples, respectively. In this population, we detected significantly upregulated and downregulated proteins in the teeth with root resorption. Interestingly, many of these proteins are characteristically found in exosomes.

CONCLUSIONS

We identified novel proteins that might prove to be useful biomarkers of root resorption, individually or as part of a panel.

Uncovering the molecular networks in periodontitis

Periodontitis is a complex immune-inflammatory disease that results from a preestablished infection in gingiva, mainly due to Gram-negative bacteria that colonize deeper in gingival sulcus and latter periodontal pocket. Host inflammatory and immune responses have both protective and destructive roles. Although cytokines, prostaglandins, and proteases struggle against microbial burden, these molecules promote connective tissue loss and alveolar bone resorption, leading to several histopathological changes, namely destruction of periodontal ligament, deepening of periodontal pocket, and bone loss, which can converge to attain tooth loss. Despite the efforts of genomics, transcriptomics, proteomics/peptidomics, and metabolomics, there is no available biomarker for periodontitis diagnosis, prognosis, and treatment evaluation, which could assist on the established clinical evaluation. Nevertheless, some genes, transcripts, proteins and metabolites have already shown a different expression in healthy subjects and in patients. Though, so far, 'omics approaches only disclosed the host inflammatory response as a consequence of microbial invasion in periodontitis and the diagnosis in periodontitis still relies on clinical parameters, thus a molecular tool for assessing periodontitis lacks in current dental medicine paradigm. Saliva and gingival crevicular fluid have been attracting researchers due to their diagnostic potential, ease, and noninvasive nature of collection. Each one of these fluids has some advantages and disadvantages that are discussed in this review.

Quantitative gingival crevicular fluid proteome in health and periodontal disease using stable isotope chemistries and mass spectrometry

AIM

Application of quantitative stable isotope-labelling chemistries and mass spectrometry (MS) to determine alterations in gingival crevicular fluid (GCF) proteome in periodontal disease.

MATERIAL AND METHODS

Quantitative proteome of GCF from 40 healthy individuals versus 40 patients with periodontal disease was established using 320 GCF samples and stable isotope-labelling reagents, ICAT and mTRAQ, with MS technology and validated by enzyme-linked immunosorbent methods.

RESULTS

We have identified 238 distinct proteins of which 180 were quantified in GCF of both healthy and periodontal patients with additional 26 and 32 distinct proteins that were found only in GCF of healthy or periodontal patients. In addition, 42 pathogenic bacterial proteins and 11 yeast proteins were quantified. The data highlighted a series of proteins not quantified previously by large-scale MS approaches in GCF with relevance to periodontal disease, such as host-derived Ig alpha-2 chain C, Kallikrein-4, S100-A9, transmembrane proteinase 13, peptidase S1 domain, several collagen types and pathogenic bacterial proteins, e.g. formamidase, leucine aminopeptidase and virulence factor OMP85.

CONCLUSIONS

The innovative analytical approaches provided detailed novel changes in both host and microbial derived GCF proteomes of periodontal patients. The study defined 50 host and 16 pathogenic bacterial proteins significantly elevated in periodontal disease most of which were novel with significant potential for application in the clinical arena of periodontal disease.

Crevicular fluid biomarkers and periodontal disease progression

AIM

Assess the ability of a panel of gingival crevicular fluid (GCF) biomarkers as predictors of periodontal disease progression (PDP).

MATERIALS AND METHODS

In this study, 100 individuals participated in a 12-month longitudinal investigation and were categorized into four groups according to their periodontal status. GCF, clinical parameters and saliva were collected bi-monthly. Subgingival plaque and serum were collected bi-annually. For 6 months, no periodontal treatment was provided. At 6 months, patients received periodontal therapy and continued participation from 6 to 12 months. GCF samples were analysed by ELISA for MMP-8, MMP-9, Osteoprotegerin, C-reactive Protein and IL-1β. Differences in median levels of GCF biomarkers were compared between stable and progressing participants using Wilcoxon Rank Sum test (p = 0.05). Clustering algorithm was used to evaluate the ability of oral biomarkers to classify patients as either stable or progressing.

RESULTS

Eighty-three individuals completed the 6-month monitoring phase. With the exception of GCF C-reactive protein, all biomarkers were significantly higher in the PDP group compared to stable patients. Clustering analysis showed highest sensitivity levels when biofilm pathogens and GCF biomarkers were combined with clinical measures, 74% (95% CI = 61, 86).

CONCLUSIONS

Signature of GCF fluid-derived biomarkers combined with pathogens and clinical measures provides a sensitive measure for discrimination of PDP (ClinicalTrials.gov NCT00277745).

Quantitative proteomic analysis of gingival crevicular fluid in different periodontal conditions

AIM

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≤3 mm with bleeding on probing, BOP), and healthy sites (H, PD≤3 mm without BOP). GCF proteins were subjected to liquid chromatography electrospray ionization mass spectrometry for identification, characterization and quantification.

RESULTS

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.

CONCLUSIONS

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.