Novel protein identification methods for biomarker discovery via a proteomic analysis of periodontally healthy and diseased gingival crevicular fluid samples

The Evaluation of Gingival Crevicular Fluid Biomarkers as Predictors of Gingival Enlargement in Patients Undergoing Fixed Orthodontic Treatment: A Prospective Study

Introduction Gingival enlargement (GE) poses a significant problem during fixed orthodontic treatment (FOT). Thus, the primary aim of the current study was to evaluate the concentrations of biomarkers present in the gingival crevicular fluid (GCF) of individuals receiving FOT. The ancillary aim was to examine and compare biomarker levels among patients exhibiting GE undergoing FOT, those without GE undergoing FOT, and a control group comprising individuals not undergoing FOT and to assess the predictors for GE in patients undergoing orthodontic treatment. Materials and methods A cross-sectional observational study was conducted on 129 patients who were divided into three groups: group 1, controls (n=18); group 2, patients who underwent FOT without GE (n=89); and group 3, patients who underwent FOT with GE (n=22). The gingival index (GI), periodontal index (PI), and inflammatory biomarkers such as interleukin 6 (IL-6), transforming growth factor-beta 1 (TGF-β1), tumor necrosis factor-alpha (TNF-α), matrix metalloproteinase 9 (MMP-9), and prostaglandin E2 (PGE2) were estimated by enzyme-linked immunosorbent assay (ELISA) analysis at baseline (T0) and after one year of orthodontic treatment (T1). Results GE was observed in 22 (19.81%) of the 111 patients who were undergoing orthodontic treatment. No statistically significant differences were observed between the groups for GI, PI, and biomarkers at T0 (p>0.05), whereas there was a statistically significant increase in the levels of inflammatory biomarkers, GI, and PI in group 3, followed by group 2, compared to group 1 (p<0.05). Group 3 showed the greatest increase in the biomarker levels from T0 to T1 (IL-6, 3.66±1.91 pg/mL; TGF-β1, 7.52±3.85 pg/mL; TNF-α, 16.96±3.82 pg/mL; MMP-9, 30.72±7.07 pg/mL; PGE2, 78.29±20.53 pg/mL). GI and PI were strong predictors of GE, whereas biomarkers were weak predictors. Conclusion GE in patients with FOT was significantly associated with an increase in GI and PI due to insufficient oral hygiene, leading to increased levels of inflammatory biomarkers in the GCF.

Expression of Regulatory T Cell and Related Interleukins in Gingivitis Versus Stage 3, Grade B Generalized Periodontitis: Synergy or Cacophony—A Cross-Sectional Study

Aim:

To raise “personalized periodontal diagnosis and prognosis” knowledge, Tregs, pro/anti-inflammatory interleukins (ILs) beside vitamin D-binding protein (VDBP) in serum and gingival cervical exudate of periodontally healthy individuals, plaque-induced gingivitis, and stage 3, grade B periodontitis patients were evaluated.

Materials and Methods:

An observational trial of different periodontal statuses according to 2018 periodontal classification was established from 60 subjects segregated into three equivalent groups (control periodontally healthy, gingivitis, and stage 3, grade B periodontitis). Peripheral blood and gingival crevicular fluid (GCF) were collected, to get GCF samples, inserted paper point in the pocket of the patient's teeth then the samples were placed with phosphate-buffered saline in Eppendorf. The peripheral blood was collected in ethylenediaminetetraacetic acid-coated vacutainer tubes. Frequency of CD4+ CD25+High Tregs was detected using flow cytometry. Cytokines were measured using an enzyme-linked immunosorbent assay. Mann–Whitney U test analysis was manipulated to distinguish the statistical discrepancies. Pearson’s correlation coefficient test was utilized to tie in the studied parameters.

Result:

Frequency of CD4+ CD25+High T cells were significantly ascendant in periodontitis than gingivitis and healthy (P ≤ 0.01; P = 0.04) and significantly superior in gingivitis than healthy (P = 0.01). There was no interdependence between systemic IL-21, IL-33, IL-22, IL-35, and the periodontal conditions except systemic VDBP, which significantly increased with the progression of the periodontal tissue inflammation. GCF compartments of IL-21, IL-33, and VDBP significantly increased with progression inflammation and GCF compartments of IL-22 and IL-35 significantly decreased with periodontal breakdown.

Conclusion:

Local increase of Treg is positively associated with increased local pro-inflammatory cytokines. This increment is more aggravated in periodontitis. Therefore, Tregs may have synergistic effects with periodontal disease progression.

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.

Identification of novel biomarkers for anti-Toxoplasma gondii IgM detection and the potential application in rapid diagnostic fluorescent tests

Toxoplasmosis, while often asymptomatic and prevalent as a foodborne disease, poses a considerable mortality risk for immunocompromised individuals during pregnancy. Point-of-care serological tests that detect specific IgG and IgM in patient sera are critical for disease management under limited resources. Despite many efforts to replace the T. gondii total lysate antigens (TLAs) by recombinant antigens (rAgs) in commercial kits, while IgG detection provides significant specificity and sensitivity, IgM detection remains comparatively low in sensitivity. In this study, we attempted to identify novel antigens targeting IgM in early infection, thereby establishing an IgM on-site detection kit. Using two-dimensional gel electrophoresis (2DE) and mouse serum immunoblotting, three novel antigens, including EF1γ, PGKI, and GAP50, were indicated to target T. gondii IgM. However, rAg EF1γ was undetectable by IgM of mice sera in Western blotting verification experiments, and ELISA coated with PGKI did not eliminate cross-reactivity, in contrast to GAP50. Subsequently, the lateral flow reaction employing a strip coated with 0.3 mg/mL purified rAg GAP50 and exhibited remarkable sensitivity compared with the conventional ELISA based on tachyzoite TLA, which successfully identified IgM in mouse sera infected with tachyzoites, ranging from 103 to 104 at 5 dpi and 104 at 7 dpi, respectively. Furthermore, by using standard T. gondii-infected human sera from WHO, the limit of detection (LOD) for the rapid fluorescence immunochromatographic test (FICT) using GAP50 was observed at 0.65 IU (international unit). These findings underline the particular immunoreactivity of GAP50, suggesting its potential as a specific biomarker for increasing the sensitivity of the FICT in IgM detection.

Utility of gingival crevicular fluid components for periodontal diagnosis

Periodontal diseases are highly prevalent chronic diseases, and severe periodontitis creates functional and esthetic problems and decreases self-esteem for a large percentage of the older population worldwide. In many cases of periodontitis, there is no distinct tell-tale pain that motivates a patient to seek treatment, rather the signs become clinically detectable late, and typically when the disease has progressed to a problematic level for the life of the dentition. Early periodontal screening and diagnostics tools will provide early recognition of periodontal diseases and facilitate timely management of the disease to reduce tooth loss. To this goal, gingival crevicular fluid is easily sampled, can be repeatedly and non-invasively collected, and can be tested for potential biomarkers. Moreover, the site specificity of periodontal diseases enhances the usefulness of gingival crevicular fluid sampled from specific sites as a biofluid for diagnosis and longitudinal monitoring of periodontal diseases. The present review aimed to provide up-to-date information on potential diagnostic biomarkers with utility that can be assayed from gingival crevicular fluid samples, focusing on what is new and useful and providing only general historic background textually and in a tabulated format.

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.

Mass spectrometry-based proteomic applications in dental implants research

Dental implants have been established as successful treatment options for missing teeth with steadily increasing demands. Today, the primary areas of research in dental implantology revolve around osseointegration, soft and hard tissue grafting as well as peri-implantitis diagnostics, prevention, and treatment. This review provides a comprehensive overview of the current literature on the application of MS-based proteomics in dental implant research, highlights how explorative proteomics provided insights into the biology of peri-implant soft and hard tissues and how proteomics facilitated the stratification between healthy and diseased implants, enabling the identification of potential new diagnostic markers. Additionally, this review illuminates technical aspects, and provides recommendations for future study designs based on the current evidence.

Accuracy of periodontitis diagnosis obtained using multiple molecular biomarkers in oral fluids: A systematic review and meta-analysis

AIM

To determine the accuracy of biomarker combinations in gingival crevicular fluid (GCF) and saliva through meta-analysis to diagnose periodontitis in systemically healthy subjects.

METHODS

Studies on combining two or more biomarkers providing a binary classification table, sensitivity/specificity values or group sizes in subjects diagnosed with periodontitis were included. The search was performed in August 2022 through PUBMED, EMBASE, Cochrane, LILACS, SCOPUS and Web of Science. The methodological quality of the articles selected was evaluated using the QUADAS-2 checklist. Hierarchical summary receiver operating characteristic modelling was employed to perform the meta-analyses (CRD42020175021).

RESULTS

Twenty-one combinations in GCF and 47 in saliva were evaluated. Meta-analyses were possible for six salivary combinations (median sensitivity/specificity values): IL-6 with MMP-8 (86.2%/80.5%); IL-1β with IL-6 (83.0%/83.7%); IL-1β with MMP-8 (82.7%/80.8%); MIP-1α with MMP-8 (71.0%/75.6%); IL-1β, IL-6 and MMP-8 (81.8%/84.3%); and IL-1β, IL-6, MIP-1α and MMP-8 (76.6%/79.7%).

CONCLUSIONS

Two-biomarker combinations in oral fluids show high diagnostic accuracy for periodontitis, which is not substantially improved by incorporating more biomarkers. In saliva, the dual combinations of IL-1β, IL-6 and MMP-8 have an excellent ability to detect periodontitis and a good capacity to detect non-periodontitis. Because of the limited number of biomarker combinations evaluated, further research is required to corroborate these observations.

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.

Impact of peri-implantitis on the proteome biology of crevicular fluid: A pilot study

BACKGROUND

The proteome of the peri-implant crevicular fluid (PICF) has not been systematically investigated. The aim of the present study was to reveal the proteome biology of dental implants affected with peri-implantitis.

METHODS

Patients with at least one diseased implant were included (probing depth ≥6 mm, ≥3 mm peri-implant radiological bone loss). Using sterile paper strips, samples were collected from healthy implants (I), healthy teeth (T) and peri-implantitis affected implants (P). Proteome analysis was performed using liquid chromatography - tandem mass spectrometry (LC-MS/MS) and data independent acquisition, allowing the identification and quantification of human and bacterial proteins as well as semi-specific peptides.

RESULTS

A total of 38 samples from 14 patients were included in the study; 2332 different human proteins were identified across all samples. No differentially expressed proteins between T and I were found. Comparing P to I, 59 proteins were found upregulated and 31 downregulated in P with significance. Upregulated proteins included proinflammatory proteins such as immunoglobulins, dysferlin, and S100P, as well as antimicrobial proteins, for example, myeloperoxidase or azurocidin. Gene ontology analysis further revealed higher activity of immunological pathways. Proteolytic patterns indicated the activity of inflammatory proteins such as cathepsin G. A total of 334 bacterial proteins were identified and quantified. Peri-implantitis showed elevated proteolytic activity.

CONCLUSION

I and T share similarities in their proteome, while diseased implants deviate strongly from healthy conditions. The PICF proteome of peri-implantitis affected sites exhibits an inflammatory fingerprint, dominated by neutrophil activity when compared with healthy implants.

Effect of interproximal home oral hygiene on clinical parameters and inflammatory biomarkers in patients receiving periodontal maintenance

BACKGROUND

The purpose of this 6-week, single-blinded, randomized clinical trial was to determine if the use of an interproximal brush, with or without a tracking device, is more effective than an oral irrigator in improving interproximal probing depth (PD), clinical attachment level (CAL), plaque index (PI), gingival index (GI), bleeding on probing (BOP), and inflammatory markers.

METHODS

Seventy-six patients with Stages III-IV, Grade B periodontitis and a 5-7 mm posterior interproximal PD with BOP were randomized: (1) interproximal brush alone (IB; n = 26), (2) interproximal brush with tracking device (TD; n = 23), (3) oral irrigator (OI; n = 27). Participants used devices once daily for 6 weeks. Clinical measurements (PD, CAL, PI, BOP, GI) and gingival crevicular fluid (GCF) samples were collected at baseline and 6 weeks.

RESULTS

All groups showed a significant reduction in PD and CAL (≥1.1 mm, p < 0.0001) and improvement in BOP (≥56%, p < 0.0001) and GI (≥82%, p < 0.001) at the experimental site with no differences among groups. The IB and IB+TD groups showed a significant reduction in PI (≥0.9, p ≤ 0.01). Interleukin (IL)-1β was reduced in all groups (p = 0.006), but IB+TB more than OI (p ≤ 0.05). IL-10 was reduced among all groups (p = 0.01), while interferon-gamma significantly increased (p = 0.01) in all groups.

CONCLUSIONS

IB and OI improved clinical parameters of PD and CAL and reduced inflammatory markers (BOP, GI, GCF IL-1β). IB had better interproximal plaque reduction. Tracking did not significantly improve clinical parameters compared with the IB and OI groups, suggesting future modifications are needed.

Label-Free Quantitative Proteomic Analysis Reveals Inflammatory Pattern Associated with Obesity and Periodontitis in Pregnant Women

Obesity and pregnancy may have synergistic effects on periodontal condition, and proteomics could be an ideal approach to highlight the pathophysiological mechanisms associated with these outcomes. This study analyzed the salivary proteomics related to obesity and periodontitis in women during pregnancy (T1) and after delivery (T2). Initially, 126 women were recruited and forty were allocated into groups: with obesity and periodontitis (OP); with obesity, but without periodontitis (OWP); with normal BMI, but with periodontitis (NP); with normal BMI and without periodontitis (NWP). Whole-mouth saliva was collected in T1 and T2, and proteins were extracted and individually processed by label-free proteomics (nLC-ESI-MS/MS). The up-regulations of Heat shock 70 kDa protein 1A, 1B, and 1-like were related to both obesity and periodontitis, separately. Albumin and Thioredoxin were up-regulated in periodontitis cases, while Cystatins (mainly S, SA, SN) and Lactotransferrin were down-regulated. The high abundances of Submaxillary gland androgen-regulated protein 3B, Protein S100-A8, Matrix metalloproteinase-9, Heat shock 70 kDa protein 2 and 6, Putative Heat shock 70 kDa protein 7, Heat shock 71 kDa protein, Haptoglobin and Plastin-1 were significant in the combination of obesity and periodontitis. Obesity and periodontitis remarkably altered the proteome of the saliva during pregnancy with substantial alterations after delivery.

Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study

Rheumatoid arthritis (RA), osteoarthritis (OA), and periodontal disease (PD) are chronic inflammatory diseases that are globally prevalent, and pose a public health concern. The search for a potential mechanism linking PD to RA and OA continues, as it could play a significant role in disease prevention and treatment. Recent studies have linked RA, OA, and PD to Porphyromonas gingivalis (PG), a periodontal bacterium, through a similar dysregulation in an inflammatory mechanism. This study aimed to identify potential gene signatures that could assist in early diagnosis as well as gain insight into the molecular mechanisms of these diseases. The expression data sets with the series IDs GSE97779, GSE123492, and GSE24897 for macrophages of RA, OA synovium, and PG stimulated macrophages (PG-SM), respectively, were retrieved and screened for differentially expressed genes (DEGs). The 72 common DEGs among RA, OA, and PG-SM were further subjected to gene–gene correlation analysis. A GeneMANIA interaction network of the 47 highly correlated DEGs comprises 53 nodes and 271 edges. Network centrality analysis identified 15 hub genes, 6 of which are DEGs (API5, ATE1, CCNG1, EHD1, RIN2, and STK39). Additionally, two significantly up-regulated non-hub genes (IER3 and RGS16) showed interactions with hub genes. Functional enrichment analysis of the genes showed that “apoptotic regulation” and “inflammasomes” were among the major pathways. These eight genes can serve as important signatures/targets, and provide new insights into the molecular mechanism of PG-induced RA, OA, and PD.

Dental Materials for Oral Microbiota Dysbiosis: An Update

The balance or dysbiosis of the microbial community is a major factor in maintaining human health or causing disease. The unique microenvironment of the oral cavity provides optimal conditions for colonization and proliferation of microbiota, regulated through complex biological signaling systems and interactions with the host. Once the oral microbiota is out of balance, microorganisms produce virulence factors and metabolites, which will cause dental caries, periodontal disease, etc. Microbial metabolism and host immune response change the local microenvironment in turn and further promote the excessive proliferation of dominant microbes in dysbiosis. As the product of interdisciplinary development of materials science, stomatology, and biomedical engineering, oral biomaterials are playing an increasingly important role in regulating the balance of the oral microbiome and treating oral diseases. In this perspective, we discuss the mechanisms underlying the pathogenesis of oral microbiota dysbiosis and introduce emerging materials focusing on oral microbiota dysbiosis in recent years, including inorganic materials, organic materials, and some biomolecules. In addition, the limitations of the current study and possible research trends are also summarized. It is hoped that this review can provide reference and enlightenment for subsequent research on effective treatment strategies for diseases related to oral microbiota dysbiosis.

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.

A comparative proteomic analysis to define the influencing factors on gingival crevicular fluid using LC-MS/MS

Gingival crevicular fluid (GCF) is a promising biofluid for disease identification and biomarker searching in periodontology. This study aimed to investigate the possible influencing factors, including tooth site, sex and age, on the normal GCF proteome. Forty periodontal healthy adults were randomly divided into a training group and a testing group. In the training group, GCF samples from 12 adults were analyzed using the iTRAQ 2D LC-MS/MS method. The influencing factors, tooth site (including periodontitis-susceptible and -insusceptible tooth sites), sex and age, and related differential proteins were defined and functionally annotated. The important differential proteins from 28 adults in the testing group were then validated by PRM analysis. An average of approximately 5 differential proteins were found between tooth sites of periodontitis-susceptible and -insusceptible sites. Eighty-five differentially expressed proteins were obtained between sexes in the young group, while only 7 sex-associated proteins were found in the old group. A total of 203 and 235 age-associated proteins were found in the male and female groups, respectively. The differential protein functional annotation showed that sex-related proteins were mainly related to immune function and metabolism, and age-related proteins were primarily associated with inflammation, lipid metabolism and immune function. In the testing group, a total of 4 sex-related proteins and 12 age-related proteins were validated by PRM analysis. SIGNIFICANCE: The influences of tooth site, sex and age in GCF proteomics in periodontal health were firstly analyzed using LC-MS/MS. Tooth site showed a small influence on the GCF proteome. The sex effect was significant in young adults, but its influence in old adults is small. Age is an important impact factor for the GCF proteome. These findings enrich the knowledge about the normal GCF proteome and might benefit future disease analyses.

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.

Scottish soldiers from the Battle of Dunbar 1650: A prosopographical approach to a skeletal assemblage

After the Battle Dunbar between English and Scottish forces in 1650, captured Scottish soldiers were imprisoned in Durham and many hundreds died there within a few weeks. The partial skeletal remains of 28 of these men were discovered in 2013. Building on previous osteological work, here we report wide-ranging scientific studies of the remains to address the following questions: Did they have comparable diet, health and disease throughout their lives? Did they have common histories of movement (or lack of movement) during their childhoods? Can we create a collective biography of these men? Strontium and oxygen isotope analysis of tooth enamel investigated childhood movement. Carbon and nitrogen isotope analysis of incrementally sampled dentine addressed childhood diet and nutrition. Metaproteomic analysis of dental calculus investigated oral microbiomes and food residues; this was complemented by microscopic analysis of debris in calculus from ingested materials. Selected individuals were examined for dental microwear. The extent of hydroxylation of proline in collagen was examined as a potential biomarker for scurvy. An osteobiography for each man was created using the full range of data generated about him, and these were synthesised using an approach based on the historical method for a collective biography or prosopography. The childhood residences of the men were primarily within the Midland Valley of Scotland, though some spent parts of their childhood outside the British Isles. This is concordant with the known recruitment areas of the Scottish army in 1650. Their diets included oats, brassicas and milk but little seafood, as expected for lowland rather than highland diets of the period. Childhood periods of starvation or illness were almost ubiquitous, but not simultaneous, suggesting regionally variable food shortages in the 1620s and 1630s. It is likely there was widespread low-level scurvy, ameliorating in later years of life, which suggests historically unrecorded shortages of fruit and vegetables in the early 1640s. Almost all men were exposed to burnt plant matter, probably as inhaled soot, and this may relate to the high proportion of them with of sinusitis. Interpersonal violence causing skeletal trauma was rare. Based on commonalities in their osteobiographies, we argue that these men were drawn from the same stratum of society. This study is perhaps the most extensive to date of individuals from 17^th century Scotland. Combined with a precise historical context it allows the lives of these men to be investigated and compared to the historical record with unprecedented precision. It illustrates the power of archaeological science methods to confirm, challenge and complement historical evidence.

NETs Are Double-Edged Swords with the Potential to Aggravate or Resolve Periodontal Inflammation

Periodontitis is a general term for diseases characterised by inflammatory destruction of tooth-supporting tissues, gradual destruction of the marginal periodontal ligament and resorption of alveolar bone. Early-onset periodontitis is due to disturbed neutrophil extracellular trap (NET) formation and clearance. Indeed, mutations that inactivate the cysteine proteases cathepsin C result in the massive periodontal damage seen in patients with deficient NET formation. In contrast, exaggerated NET formation due to polymorphonuclear neutrophil (PMN) hyper-responsiveness drives the pathology of late-onset periodontitis by damaging and ulcerating the gingival epithelium and retarding epithelial healing. Despite the gingival regeneration, periodontitis progression ends with almost complete loss of the periodontal ligament and subsequent tooth loss. Thus, NETs help to maintain periodontal health, and their dysregulation, either insufficiency or surplus, causes heavy periodontal pathology and edentulism.

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.

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.

Changes in the salivary proteome of beagle dogs after weight loss

Being overweight or obese represents an important health issue in humans and pets. The aim of this study was to investigate changes in the salivary proteome of overweight beagles after induced weight loss to better understand the physiological changes involved in this process. Five overweight/obese neutered males of pure breed beagles were evaluated. During the 3-mo period of weight loss, each animal received a strictly controlled amount of a low fat commercial diet per day. Body condition scores (BCS), body weight (BW), and serum biochemical parameters (total cholesterol, triglycerides, and C-reactive protein) were assessed weekly. Quantitative proteomics analysis by SWATH was used to evaluate the salivary proteome changes induced by weight loss treatment. BCS, BW, serum total cholesterol concentration, and abundances of 23 salivary proteins differed significantly between before and after treatment. Some of the altered protein amounts, namely of peptidyl-prolyl cis-trans isomerase, fructose-bisphosphate aldolase C, and 78-kDa glucose-regulated protein, increased after weight loss. These proteins are related with the immune system, inflammatory status, oxidative stress, and glucose metabolism. The results obtained suggest a potential use of salivary proteins in monitoring physiological changes in dogs subjected to weight loss. Moreover, the type of changes identified reinforces the postulated physiological improvements, which weight loss induces. Further research is needed to determine whether the changes observed in this study are due to weight loss, dietary changes, or a combination of both.

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.

An Evidence-Based Update on the Molecular Mechanisms Underlying Periodontal Diseases

Several investigators have reported about the intricate molecular mechanism underlying periodontal diseases (PD). Nevertheless, the role of specific genes, cells, or cellular mechanisms involved in the pathogenesis of periodontitis are still unclear. Although periodontitis is one of the most prevalent oral diseases globally, there are no pre-diagnostic markers or therapeutic targets available for such inflammatory lesions. A pivotal role is played by pro- and anti-inflammatory markers in modulating pathophysiological and physiological processes in repairing damaged tissues. In addition, effects on osteoimmunology is ever evolving due to the ongoing research in understanding the molecular mechanism lying beneath periodontal diseases. The aim of the current review is to deliver an evidence-based update on the molecular mechanism of periodontitis with a particular focus on recent developments. Reports regarding the molecular mechanism of these diseases have revealed unforeseen results indicative of the fact that significant advances have been made to the periodontal medicine over the past decade. There is integrated hypothesis-driven research going on. Although a wide picture of association of periodontal diseases with immune response has been further clarified with present ongoing research, small parts of the puzzle remain a mystery and require further investigations.

Host-microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome

Periodontal studies using transcriptomics, proteomics, and metabolomics encompass the collection of mRNA transcripts, proteins, and small-molecule chemicals in the context of periodontal health and disease. The number of studies using these approaches has significantly increased in the last decade and they have provided new insight into the pathogenesis and host-microbe interactions that define periodontal diseases. This review provides an overview of current molecular findings using -omic approaches that underlie periodontal disease, including modulation of the host immune response, tissue homeostasis, and complex metabolic processes of the host and the oral microbiome. Integration of these -omic approaches will broaden our perspective of the molecular mechanisms involved in periodontal disease, advancing and improving the diagnosis and treatment of various stages and forms of periodontal disease.

Associations of cytokine levels in gingival crevicular fluid of mobile teeth with clinical improvement after initial periodontal treatment

Studies suggest that analysis of gingival crevicular fluid (GCF) is useful for evaluating periodontal status. In this study, clinical variables related to tooth mobility, and multiple cytokine levels in proximate GCF, were measured at four time points during initial periodontal treatment: before treatment (baseline), after supragingival scaling, after occlusal adjustment, and after scaling and root planing (SRP); 20 teeth from 13 patients with periodontitis were included. Baseline interleukin (IL)-10 level in GCF was significantly higher around teeth that showed substantial improvement in periodontal epithelial surface area (PESA) after SRP than around teeth without PESA improvement. IL-3 and IL-16 levels in GCF at baseline were significantly higher around teeth with a periodontal inflamed surface area (PISA) of 0 mm² after SRP than around teeth without PISA improvement. In addition, baseline IL-7, IL-11, and IL-12p40 levels in GCF were significantly lower around teeth with decreased mobility after occlusal adjustment than around teeth without decreased mobility. These results suggest that pre-treatment cytokine levels in GCF are useful in predicting the effects of initial periodontal treatment.

Tracking the functional meaning of the human oral-microbiome protein-protein interactions

The interactome - the network of protein-protein interactions (PPIs) within a cell or organism - is technically difficult to assess. Bioinformatic tools can, not only, identify potential PPIs that can be later experimentally validated, but also be used to assign functional meaning to PPIs. Saliva's potential as a non-invasive diagnostic fluid is currently being explored by several research groups. But, in order to fully attain its potential, it is necessary to achieve the full characterization of the mechanisms that take place within this ecosystem. The onset of omics technologies, and specifically of proteomics, delivered a huge set of data that is largely underexplored. Quantitative information relative to proteins within a given context (for example a given disease) can be used by computational algorithms to generate information regarding PPIs. These PPIs can be further analyzed concerning their functional meaning and used to identify potential biomarkers, therapeutic targets, defense and pathogenicity mechanisms. We describe a computational pipeline that can be used to identify and analyze PPIs between human and microbial proteins. The pipeline was tested within the scenario of human PPIs of systemic (Zika Virus infection) and of oral conditions (Periodontal disease) and also in the context of microbial interactions (Candida-Streptococcus) and showed to successfully predict functionally relevant PPIs. The pipeline can be applied to different scientific areas, such as pharmacological research, since a functional meaningful PPI network can provide insights on potential drug targets, and even new uses for existing drugs on the market.

Proteomic analysis of whole saliva in chronic periodontitis

Periodontitis is a chronic inflammatory disease resulting from a dysbiosis of the dental biofilm and a dysregulated host response in susceptible individuals. It is characterized by periodontal attachment destruction, bone resorption and eventual tooth loss. Salivary biomarkers have been sought to predict and prevent periodontitis. This comparative study analyzed the salivary proteome of individuals with chronic periodontitis (CP) and periodontal health (PH) and correlated specific proteins with clinical parameters of disease by using mass spectrometry. Stimulated whole saliva was obtained 10 PH and 30 CP patients and pooled into 5 healthy control samples and 15 CP samples. After precipitation with TCA, samples were digested enzymatically with trypsin and analyzed by a LTQ Orbitrap Velos equipped with a nanoelectrospray ion source. A wide range of salivary proteins of various functions was significantly reduced in CP individuals, whereas salivary acidic proline-rich phosphoprotein, submaxillary gland androgen-regulated protein, histatin-1, fatty acid binding protein, thioredoxin and cystatin-SA were predominant in diseased patients and correlated significantly with signs of periodontal attachment loss and inflammation. In conclusion, few specific salivary proteins were associated with CP. These findings may contribute to the identification of disease indicators or signatures for the improvement of periodontal diagnosis. SIGNIFICANCE: Periodontitis is a chronic inflammatory disease that results in periodontal attachment destruction, bone resorption and eventual tooth loss. Salivary biomarkers have been sought to predict periodontitis. The analysis of the salivary proteome of individuals with chronic periodontitis indicated that several proteins of various functions were significantly reduced in these individuals, except for salivary acidic proline-rich phosphoprotein, submaxillary gland androgen-regulated protein, histatin, fatty acid binding protein, thioredoxin and cystatin. Differences in salivary proteome profiles between periodontal health and periodontitis may contribute to the identification of disease indicators and to the improvement of periodontal diagnosis and treatment.

Salivary proteome characterization of alcohol and tobacco dependents

BACKGROUND

Alcohol and substances found in tobacco may alter salivary flow and amount of saliva proteins. This study aimed to compare salivary proteins between alcohol dependent smokers and controls.

METHODS

This is a case-control study with men older than 18 years of age, matched by age. The alcohol-dependent group was composed by heavy smokers and alcohol consumers. Unstimulated whole saliva was collected from all subjects. Analysis of digested peptides was performed in mass spectrometer. Data were processed using ProteinLynx GlobalServer software. Results were obtained by searching theHomo sapiens database from the UniProt catalog. The search tool IBI-IMIM was used to identify candidate proteins for biomarkers.

RESULTS

Alcohol-dependent and control groups were composed of nine participants each, with mean age of 36.89 ± 2.57 and 35.78 ± 1.64 years, respectively. 404 salivary proteins were found in both groups; 282 in the alcohol-dependent. Among the 96 proteins presented in both groups, 32 were up-regulated in the alcohol dependents (i.e. "Hemoglobin subunit beta" and "Forkhead box protein P2" were up-regulated at least 10-fold), 23 were down-regulated (i.e. "Statherin" and "RNA-binding protein 25" were down-regulated at least 10-fold), and 41 presented similar expression in both groups. 71 proteins were candidates for biomarkers of disorders 58 presented in alcohol dependents' saliva. The most common disorders were neoplasms, genetic, cardiovascular, metabolic and glandular diseases.

CONCLUSIONS

Salivary protein profile undergoes strong changes in alcohol and tobacco dependents. 34% of salivary proteins present in alcohol and tobacco dependents were present in controls; 14.5% of them were expressed in similar quantity.

Azurocidin in gingival crevicular fluid as a potential biomarker of chronic periodontitis

BACKGROUND AND OBJECTIVE

Azurocidin is a neutrophil-derived protein in gingival crevicular fluid (GCF) which, according to relevant studies, might correlate with periodontal disease. The aim of the present study was to evaluate azurocidin as a potential biomarker for chronic periodontitis.

MATERIAL AND METHODS

One hundred and one patients participated in the study, divided into two groups. Forty-eight were included in the periodontally healthy group (HP) and fifty-three in the chronic periodontitis group (CP). Clinical indices included probing depth (PD), recession (REC), clinical attachment level (CAL), bleeding on probing (BOP) and plaque (PL). Pooled GCF samples were collected with paper strips, freezed in liquid nitrogen (-196°C), stored at -80°C, and the levels of azurocidin were analyzed with ELISA. Values were transformed and expressed for comparisons in pg/30 s sample. Statistical comparisons were performed using non-parametric tests (Mann-Whitney) at the 0.05 level. Furthermore, the diagnostic accuracy of the procedure was assessed with receiver operator characteristic curves (ROC), areas under the curve (AUC), and the Youden's J Index calculated.

RESULTS

Demographic data were comparable between the two groups. Clinical parameters and the levels of azurocidin were statistically significantly higher in the CP group when compared to the HP group (Mann-Whitney test, P < .05). Quantitative data from ELISA demonstrated a high diagnostic accuracy of azurocidin, with AUC calculated higher than 0.9 at the 0.000 level.

CONCLUSION

Azurocidin in GCF is a promising biomarker for periodontal disease. The results of the present study agree with previous studies in the literature showing an up-regulated trend in the levels of azurocidin in periodontitis patients.

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.

Periodontal disease: From the lenses of light microscopy to the specs of proteomics and next-generation sequencing

Periodontal disease entails the inflammatory destruction of the tooth supporting (periodontal) tissues as a result of polymicrobial colonization of the tooth surface in the form of biofilms. Extensive data collected over the past decades on this chronic disease demonstrate that its progression is infrequent and episodic, and the susceptibility to it can vary among individuals. Physical assessments of previously occurring damage to periodontal tissues remain the cornerstone of detection and diagnosis, whereas traditionally used diagnostic procedures do neither identify susceptible individuals nor distinguish between disease-active and disease-inactive periodontal sites. Thus, more sensitive and accurate "measurable biological indicators" of periodontal diseases are needed in order to place diagnosis (e.g., the presence or stage) and management of the disease on a more rational less empirical basis. Contemporary "omics" technologies may help unlock the path to this quest. High throughput nucleic acid sequencing technologies have enabled us to examine the taxonomic distribution of microbial communities in oral health and disease, whereas proteomic technologies allowed us to decipher the molecular state of the host in disease, as well as the interactive cross-talk of the host with the microbiome. The newly established field of metaproteomics has enabled the identification of the repertoire of proteins that oral microorganisms use to compete or co-operate with each other. Vast such data is derived from oral biological fluids, including gingival crevicular fluid and saliva, which is progressively completed and catalogued as the analytical technologies and bioinformatics tools progressively advance. This chapter covers the current "omics"-derived knowledge on the microbiome, the host and their "interactome" with regard to periodontal diseases, and addresses challenges and opportunities ahead.

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.

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.

High-throughput proteomic analysis of candidate biomarker changes in gingival crevicular fluid after treatment of chronic periodontitis

BACKGROUND AND OBJECTIVE

Untargeted, high-throughput proteomics methodologies have great potential to aid in identifying biomarkers for the diagnosis of periodontal disease. The application of such methods to the discovery of candidate biomarkers for the resolution of periodontal inflammation after periodontal therapy has been investigated.

MATERIAL AND METHODS

Gingival crevicular fluid samples were collected from 10 patients diagnosed with chronic periodontitis at baseline and 1, 5, 9 and 13 weeks after completion of mechanical periodontal treatment. Clinical indices of periodontal disease, including probing depth, recession, clinical attachment level and bleeding on probing, were recorded at baseline and 13 weeks. Samples were analyzed using an online liquid chromatography-nanoelectrospray-hybrid ion trap-Orbitrap mass spectrometer. Spectra were processed with the PILOT_PROTEIN proteomics software suite.

RESULTS

Clinical parameters were significantly improved 13 weeks after treatment (Wilcoxon signed ranks test, P < .05). From the substantial number of identified proteins, a small subset was extracted by filter methods that included temporal pattern matching, logistic function fitting and mixed-integer linear optimization. This subset includes azurocidin, lysozyme C and myosin-9 as candidate biomarkers prominent at baseline and alpha-smooth muscle actin as prominent 13 weeks after treatment. Cross-validation studies yielded average predictive accuracy and area under the curve of 0.900 and 0.930, respectively.

CONCLUSION

High-throughput proteomic analysis can contribute to identifying endpoints of periodontal therapy. These candidate biomarkers should be evaluated for clinical efficacy.

Targeted Proteomics Guided by Label-free Quantitative Proteome Analysis in Saliva Reveal Transition Signatures from Health to Periodontal Disease

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. Here we carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n = 67, including individuals with health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n = 82). The LFQ platform led to the discovery of 119 proteins with at least 2-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 functionally related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases with maximum area under the receiver operating curve >0.97 (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1). This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum leap brought into the field of periodontal diagnostics by this study is the application of the biomarker discovery-through-verification pipeline, which can be used for validation in further cohorts.

Antimicrobial peptide gene expression in periodontitis patients: A pilot study

AIM

Antimicrobial peptides (AMPs) are one of the most active components of innate immunity and have characteristics that could place them at the heart of the pathogenesis of periodontal disease. This study investigated differences in the expression of AMP coding genes obtained using a simple harvesting technique, gingival smear, between two groups of patients: chronic periodontitis subjects versus healthy ones.

MATERIALS AND METHODS

Twenty-three patients were enrolled in two groups: 12 were diagnosed with moderate or severe generalized chronic periodontitis, and 11 were diagnosed as clinically healthy. Gingival smears were retrieved and studied using reverse transcription-quantitative PCR (RT-qPCR) after mRNA purification.

RESULTS

Fifteen gene expressions were obtained using real-time RT-qPCR. Three AMP genes, histatin 3 (HTN3), α-defensin 4 (DEFA4) and lysozyme C (LYZ), presented different expression levels in periodontitis patients compared with healthy subjects. The relative expression level of DEFA4 appeared to be a protective factor against periodontitis.

CONCLUSION

Gingival smears studied by RT-qPCR may be used to assess the expression of AMPs coding genes. A lack of expression of DEFA4 could be a potential indicator of periodontitis status.

Oral microbiome and peri-implant diseases: where are we now?

Peri-implant infective diseases (PIIDs) in oral implantology are commonly known as peri-implant mucositis (PIM) and periimplantitis (PI). While PIM is restricted to the peri-implant mucosa and is reversible, PI also affects implant-supporting bone and, therefore, is very difficult to eradicate. PIIDs in clinical outcome may resemble gingivitis and periodontitis, as they share similar risk factors. However, recent study in the field of proteomics and other molecular studies indicate that PIIDs exhibit significant differences when compared to periodontal diseases. This review aims to elucidate the current knowledge of PIIDs, their etiopathology and diversified microbiology as well as the role of molecular studies, which may be a key to personalized diagnostic and treatment protocols of peri-implant infections in the near future.

Preservation of the metaproteome: variability of protein preservation in ancient dental calculus

Proteomic analysis of dental calculus is emerging as a powerful tool for disease and dietary characterisation of archaeological populations. To better understand the variability in protein results from dental calculus, we analysed 21 samples from three Roman-period populations to compare: 1) the quantity of extracted protein; 2) the number of mass spectral queries; and 3) the number of peptide spectral matches and protein identifications. We found little correlation between the quantity of calculus analysed and total protein identifications, as well as no systematic trends between site location and protein preservation. We identified a wide range of individual variability, which may be associated with the mechanisms of calculus formation and/or post-depositional contamination, in addition to taphonomic factors. Our results suggest dental calculus is indeed a stable, long-term reservoir of proteins as previously reported, but further systematic studies are needed to identify mechanisms associated with protein entrapment and survival in dental calculus.

Gingival crevicular fluid as a source of biomarkers for periodontitis

In evaluating the pathogenesis of periodontal diseases, the diagnostic potential of gingival crevicular fluid has been extensively explored during the last twenty years, from initially just confirming health and disease states to more recently investigating it as a potential prognostic tool. As host susceptibility is a critical determinant in periodontal disease pathogenesis, the inflammatory mediator levels present in gingival crevicular fluid represent relevant risk indicators for disease activity. Considerable work has been carried out to identify the many different cytokine inflammatory pathways and microbial stimuli that are associated with periodontal disease pathogenesis. Now, 'omics' approaches aim to summarize how these pathways interact and probably converge to create critical inflammatory networks. More recently, gingival crevicular fluid metabolomics appears promising as an additional diagnostic method. Biofilm structure and the host inflammatory response to the microbial challenge may induce specific inflammatory signatures. Host genetics and epigenetics may also modulate microbial colonization, adding to the multiplicity of potential causal pathways. Omics analyses of gingival crevicular fluid, measuring microbial and host interactions in association with the onset and progression of periodontal diseases, still show the potential to expand the landscape for the discovery of diagnostic, prognostic and therapeutic markers.

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.