Identification of azurocidin as a potential periodontitis biomarker by a proteomic analysis of gingival crevicular fluid

Using SWATH-MS to identify new molecular biomarkers in gingival crevicular fluid for detecting periodontitis and its response to treatment

AIM

To identify new biomarkers to detect untreated and treated periodontitis in gingival crevicular fluid (GCF) using sequential window acquisition of all theoretical mass spectra (SWATH-MS).

MATERIALS AND METHODS

GCF samples were collected from 44 periodontally healthy subjects and 40 with periodontitis (Stages III-IV). In the latter, 25 improved clinically 2 months after treatment. Samples were analysed using SWATH-MS, and proteins were identified by the UniProt human-specific database. The diagnostic capability of the proteins was determined with generalized additive models to distinguish the three clinical conditions.

RESULTS

In the untreated periodontitis vs. periodontal health modelling, five proteins showed excellent or good bias-corrected (bc)-sensitivity/bc-specificity values of >80%. These were GAPDH, ZG16B, carbonic anhydrase 1, plasma protease inhibitor C1 and haemoglobin subunit beta. GAPDH with MMP-9, MMP-8, zinc-α-2-glycoprotein and neutrophil gelatinase-associated lipocalin and ZG16B with cornulin provided increased bc-sensitivity/bc-specificity of >95%. For distinguishing treated periodontitis vs. periodontal health, most of these proteins and their combinations revealed a predictive ability similar to previous modelling. No model obtained relevant results to differentiate between periodontitis conditions.

CONCLUSIONS

New single and dual GCF protein biomarkers showed outstanding results in discriminating untreated and treated periodontitis from periodontal health. Periodontitis conditions were indistinguishable. Future research must validate these findings.

Diagnostic value of aMMP-8 and azurocidin in peri-implant sulcular fluid as biomarkers of peri-implant health or disease

OBJECTIVE

The objective of this study was to investigate the effectiveness of testing for active matrix metalloproteinase-8 (aMMP-8) by a quantitative point-of-care (PoC), chairside lateral flow immunotest and azurocidin, in the peri-implant sulcular fluid (PISF), as biomarkers for the presence or absence of peri-implant diseases.

BACKGROUND

Current research indicates that proinflammatory cytokines and extracellular matrix-degrading enzymes may be of value to diagnose and predict peri-implant disease initiation and progression, but more data are needed.

METHODS

Eighty patients with implants were recruited. PISF samples were collected and quantitatively analyzed for aMMP-8 (chairside) and azurocidin with ELISA. Radiographic assessments and clinical indices (probing depth, probing attachment level, bleeding on probing, and plaque) were recorded after sampling. Kruskal-Wallis test and pairwise post hoc Dunn-Bonferroni test were used to relate aMMP-8 levels and azurocidin levels to clinical parameters. The diagnostic ability of aMMP-8 (ng/mL) and azurocidin was analyzed by receiver operator curve analysis. Area under the curve (AUC) was calculated and the Spearman's rho, and the coefficient of determination (R2) were used to calculate the correlations between aMMP-8, azurocidin, and periodontal parameters.

RESULTS

Statistically significant differences were observed for aMMP-8 levels but not for azurocidin between healthy implants, implants with mucositis, and those with peri-implantitis (13.65 ± 7.18, 32.33 ± 21.20, and 73.07 ± 43.93 ng/mL, respectively), (Kruskall-Wallis test p < .05). The aMMP-8 test with a threshold of 20 ng/mL has a sensitivity of 71.7% and a specificity of 77.8% to identify peri-implantitis and healthy implants, respectively. AUC was found to be 0.814, and the accuracy of the method reaches 73.8%. Above a cutoff value of 33.7 ng/mL of aMMP-8, the accuracy of the test to detect peri-implantitis reaches 77.5% in relation to 62.5% of BoP from the same site.

CONCLUSION

Taken collectively, present data indicate that the aMMP-8 PoC lateral flow immunotest can be a beneficial, adjunctive diagnostic quantitative tool for real-time screening for peri-implant diseases.

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.

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.

Detection of orthodontically induced inflammatory root resorption-associated biomarkers from the gingival crevicular fluid by proteomics analysis: a randomized-controlled clinical trial

Orthodontically induced inflammatory root resorption (OIIRR) is an undesirable complication of orthodontic treatment (OT) with an ambiguous aetiologic mechanism. This study aimed to identify OIIRR-associated biomarkers in the gingival crevicular fluid (GCF) using proteomic analysis. In this randomized clinical trial, the upper first premolars (UFP) were exposed either to light or heavy force. The GCF was collected at 1 h, 1 day, 7 days, 14 days, 21 days, and 28 days following force application. After extraction of UFP, roots were imaged and resorption premolar, was used to deliver either light forcecraters were measured. Proteomic analysis of GCF was performed using 2D gel electrophoresis with MALDI-TOF/TOF MS/MS. Results were further analyzed by bioinformatics analyses showing the biological functions and predicted pathways. The predicted canonical pathways showed that the expression of immunoglobulin kappa (IGKC), neutrophil gelatinase-associated lipocalin (NGAL), neurolysin mitochondrial (NEUL), keratin, type II cytoskeletal 1 (K2C1), S100-A9, and the extracellular calcium-sensing receptor (CASR) were significantly associated with a range of biological and inflammatory processes. In conclusion, up-regulation of S100A9, CASR, and K2C1 suggested a response to force-related inflammation, chemotactic activities, osteoclastogenesis, and epithelial cell breakdown. Meanwhile, the up-regulation of IGKC, NGAL, and K2C1 indicated a response to the inflammatory process, innate immunity activation, and epithelial cell breakdown.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03572-5.

Proteomic analysis of sialoliths from calcified, lipid and mixed groups as a source of potential biomarkers of deposit formation in the salivary glands

Salivary stones, also known as sialoliths, are formed in a pathological situation in the salivary glands. So far, neither the mechanism of their formation nor the factors predisposing to their formation are known despite several hypotheses. While they do not directly threaten human life, they significantly deteriorate the patient's quality of life. Although this is not a typical research material, attempts are made to apply various analytical tools to characterise sialoliths and search for the biomarkers in their proteomes. In this work, we used mass spectrometry and SWATH-MS qualitative and quantitative analysis to investigate the composition and select proteins that may contribute to solid deposits in the salivary glands. Twenty sialoliths, previously characterized spectroscopically and divided into the following groups: calcified (CAL), lipid (LIP) and mixed (MIX), were used for the study. Proteins unique for each of the groups were found, including: for the CAL group among them, e.g. proteins from the S100 group (S100 A8/A12 and P), mucin 7 (MUC7), keratins (KRT1/2/4/5/13), elastase (ELANE) or stomatin (STOM); proteins for the LIP group-transthyretin (TTR), lactotransferrin (LTF), matrix Gla protein (MPG), submandibular gland androgen-regulated protein 3 (SMR3A); mixed stones had the fewest unique proteins. Bacterial proteins present in sialoliths have also been identified. The analysis of the results indicates the possible role of bacterial infections, disturbances in calcium metabolism and neutrophil extracellular traps (NETs) in the formation of sialoliths.

Potential Impact of Prosthetic Biomaterials on the Periodontium: A Comprehensive Review

The success of a prosthetic treatment is closely related to the periodontal health of the individual. The aim of this article was to review and present the importance of prosthetic restorative materials on the condition of the periodontium, the changes that occur in the composition of the subgingival microbiota and the levels of inflammatory markers in gingival crevicular fluid. Articles on the influence of different prosthetic restorative materials on subgingival microbiota and proinflammatory cytokines were searched for using the keywords "prosthetic biomaterials", "fixed prosthesis", "periodontal health", "subgingival microbiota", "periodontal biomarkers" and "gingival crevicular fluid" in PubMed/Medline, Science Direct, Scopus and Google Scholar. The type of material used for prosthesis fabrication together with poor marginal and internal fit can result in changes in the composition of the subgingival microbiota, as well as increased accumulation and retention of dentobacterial plaque, thus favoring the development of periodontal disease and prosthetic treatment failure. Biological markers have helped to understand the inflammatory response of different prosthetic materials on periodontal tissues with the main purpose of improving their clinical application in patients who need them. Metal-free ceramic prostheses induce a lower inflammatory response regardless of the fabrication method; however, the use of CAD/CAM systems is recommended for their fabrication. In addition, it is presumed that metal-ceramic prostheses cause changes in the composition of the subgingival microbiota producing a more dysbiotic biofilm with a higher prevalence of periodontopathogenic bacteria, which may further favor periodontal deterioration.

Obesity affects the proteome profile of periodontal ligament submitted to mechanical forces induced by orthodontic tooth movement in rats

The prevalence of obesity has increased significantly worldwide. Therefore, this study aimed to evaluate the influence of obesity on the proteomic profile of periodontal ligament (PDL) tissues of rat first maxillary molars (1 M) submitted to orthodontic tooth movement (OTM). Ten Holtzman rats were distributed into two groups (n = 5): the M group (OTM), and the OM group (obesity induction plus OTM). Obesity was induced by a high-fat diet for the entire experimental periods After that period, the animals were euthanized and the hemimaxillae removed and processed for laser capture microdissection of the PDL tissues of the 1 M. Peptide extracts were obtained and analyzed by LC-MS/MS. Data are available via ProteomeXchange with identifier PXD033647. Out of the 109 proteins with differential abundance, 49 were identified in the OM group, including Vinculin, Cathepsin D, and Osteopontin, which were selected for in situ localization by immunohistochemistry analysis (IHC). Overall, Gene Ontology (GO) analysis indicated that enriched proteins were related to the GO component cellular category. IHC validated the trends for selected proteins. Our study highlights the differences in the PDL proteome profiling of healthy and obese subjects undergoing OTM. These findings may provide valuable information needed to better understand the mechanisms involved in tissue remodeling in obese patients submitted to orthodontic treatment. SIGNIFICANCE: The prevalence of obesity is increasing worldwide. Emerging findings in the field of dentistry suggest that obesity influences the tissues around the teeth, especially those in the periodontal ligament. Therefore, evaluation of the effect of obesity on periodontal tissues remodeling during orthodontic tooth movement is a relevant research topic. To our knowledge, this is the first study to evaluate proteomic changes in periodontal ligament tissue in response to the association between orthodontic tooth movement and obesity. Our study identified a novel protein profile associated with obesity by using laser microdissection and proteomic analysis, providing new information to increase understanding of the mechanisms involved in obese patients undergoing orthodontic treatment which can lead to a more personalized orthodontic treatment approach.

Antimicrobial peptides and proteins in human biological fluids

Antimicrobial peptides and proteins (AMPs) are endogenous compounds that have a direct antimicrobial effect on bacteria (e. g., by disrupting bacterial membranes), as well as on fungi and viruses. AMPs are the main component of the innate immunity of living organisms and are produced by both epithelial cells (skin cells, cells of respiratory tract, intestine, urinary and genital tracts) and cells of the immune system and are secreted into secretory fluids. AMPs can also act as chemoattractants for immunocompetent cells (neutrophils, monocytes, T lymphocytes, dendritic cells) in the inflammation site and affect the antigen presenting cells by modulating adaptive T cell immune responses. The representatives of the main 15 AMP classes, that we describe in this review, are the most studied group of the large pool of these compounds. We discuss their localization, expression, and concentration in various biofluids of humans under normal and pathological conditions.

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.

Future Drug Targets in Periodontal Personalised Medicine-A Narrative Review

Periodontal disease is an infection-driven inflammatory disease characterized by the destruction of tooth-supporting tissues. The establishment of chronic inflammation will result in progressive destruction of bone and soft tissue changes. Severe periodontitis can lead to tooth loss. The disease has complex pathogenesis with an interplay between genetic, environmental, and host factors and pathogens. Effective management consists of plaque control and non-surgical interventions, along with adjuvant strategies to control inflammation and disrupt the pathogenic subgingival biofilms. Recent studies have examined novel approaches for managing periodontal diseases such as modulating microbial signaling mechanisms, tissue engineering, and molecular targeting of host inflammatory substances. Mounting evidence suggests the need to integrate omics-based approaches with traditional therapy to address the disease. This article discusses the various evolving and future drug targets, including proteomics, gene therapeutics, vaccines, and nanotechnology in personalized periodontal medicine for the effective management of periodontal diseases.

Nano liquid chromatography, an updated review

Low flow chromatography has a rich history of innovation but has yet to reach widespread implementation in bioanalytical applications. Improvements in pump technology, microfluidic connections, and nano-electrospray sources for mass spectrometry have laid the groundwork for broader application, and innovation in this space has accelerated in recent years. This article reviews the instrumentation used for nano-flow liquid chromatography , the types of columns employed, and strategies for multi-dimensionality of separations, which is key to the future state of the technique to the high-throughput needs of modern bioanalysis. An update of the current applications where nano-LC is widely used, such as proteomics and metabolomics, is discussed. But the trend towards biopharmaceutical development of increasingly complex, targeted, and potent therapeutics for the safe treatment of disease drives the need for ultimate selectivity and sensitivity of our analytical platforms for targeted quantitation in a regulated space. The selectivity needs are best addressed by mass spectrometric detection, especially at high resolutions, and exquisite sensitivity is provided by nano-electrospray ionization as the technology continues to evolve into an accessible, robust, and easy to use platform.

Cationic Antimicrobial Peptides Are Leading the Way to Combat Oropathogenic Infections

Oral dental infections are one of the most common diseases affecting humans, with caries and periodontal disease having the highest incidence. Caries and periodontal disease arise from infections caused by oral bacterial pathogens. Current misuse and overuse of antibiotic treatments have led to the development of antimicrobial resistance. However, recent studies have shown that cationic antimicrobial peptides are a promising family of antibacterial agents that are active against oral pathogenic bacteria and also possess less propensity for development of antimicrobial resistance. This timely Review has a focus on two primary subjects: (i) the oral bacterial pathogens associated with dental infections and (ii) the current development of antimicrobial peptides targeting oral pathogens.

Dental, oral pH, orthodontic and salivary values in children with obstructive sleep apnea

OBJECTIVES

Mouth breathing is a key feature of obstructive sleep apnea (OSA). The current study evaluated dental, salivary and orthodontic characteristics of children with OSA, and compared them to those of children without OSA.

MATERIALS AND METHODS

Twenty-two children (mean age 5.3 years, 13 males) with OSA and 21 children without OSA who served as a control group (mean age 6.8 years, 11 males) underwent dental examinations. The OSA group was classified according to the apnea-hypopnea Index. Clinical examination included plaque index, gingival index, caries status, pH at 7 oral sites, salivary carries bacterial counts and inflammatory cytokine levels. Orthodontics measurements were calculated as the percentage of children with values in the normal range, in each group.

RESULTS

The mean values of the decayed, missing and filled teeth (DMFT)/dmft index, the gingival index and the plaque index were higher in the OSA than the control group. Salivary Mutans streptococci and lactobacilli counts were significantly higher in the OSA than the control group; as were pH values in the hard and soft palate, and in the posterior and middle tongue. Significantly lower values were observed in the OSA than the control group for most of the orthodontic variables examined. Similarly, stratification of AHI according to severity shows the lowest values among those with mild OSA, and the highest among those with severe AHI.

CONCLUSIONS

Compared to a control group, mouth breathing children with obstructive sleep apnea had differences in oral microbiota, greater acidity and poorer dental status.

CLINICAL RELEVANCE

Clinicians should be aware of the various oral disturbances that may accompany OSA, and implement preventive measures.

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.

Comparative antler proteome of sika deer from different developmental stages

Antler is a special bone tissue that has the ability to regenerate completely periodically. It is the fastest growing bone in the animal kingdom. Antler provides a valuable research model for bone growth and mineralization. Antler grows longitudinally by endochondral ossification with their growth center located in its tip. Many scholars have carried out detailed studies on morphology and gene expression of antler tip. However, few scholars have analyzed the protein expression patterns of antler tip at different development stages. This study used label-free proteomics approach to analyze the protein expression dynamics of the antler tip in six developmental periods (15, 25, 45, 65, 100 and 130 days after the previous antler cast) and costal cartilage. In result, 2052 proteins were confidently quantified, including 1937 antler proteins and 1044 costal cartilage proteins. Moreover, 913 antler core proteins and 132 antler-special proteins were obtained. Besides, the stages special proteins and differentially expressed proteins (DEPs) in different development stages were analyzed. A total of 875 DEPs were determined by one-way AVOVA. It is found that the growth period (15, 25, 45 and 65 days) showed more up-regulated protein including several chondrogenesis-associated proteins (collagen types II, collagen types XI, HAPLN1, PAPSS1 and PAPSS2). In ossification stages, the up-regulated proteins related with lysosome (CTSD, CTSB, MMP9, CAII) indicated that the antler has higher bone remodeling activity. Given the up-regulated expression of immune-related molecules (S100A7, CATHL7, LTF, AZU1, ELANE and MPO), we speculate that the local immune system may contribute to the ossification of antler tip. In conclusion, proteomics technology was used to deeply analyze the protein expression patterns of antler at different development stages. This provides a strong support for the research on the molecular regulation mechanism of rapid growth and ossification of velvet antler.

Characterization of Extracellular Vesicle Cargo in Sjögren's Syndrome through a SWATH-MS Proteomics Approach

Primary Sjögren’s syndrome (pSS) is a complex heterogeneous disease characterized by a wide spectrum of glandular and extra-glandular manifestations. In this pilot study, a SWATH-MS approach was used to monitor extracellular vesicles-enriched saliva (EVs) sub-proteome in pSS patients, to compare it with whole saliva (WS) proteome, and assess differential expressed proteins between pSS and healthy control EVs samples. Comparison between EVs and WS led to the characterization of compartment-specific proteins with a moderate degree of overlap. A total of 290 proteins were identified and quantified in EVs from healthy and pSS patients. Among those, 121 proteins were found to be differentially expressed in pSS, 82% were found to be upregulated, and 18% downregulated in pSS samples. The most representative functional pathways associated to the protein networks were related to immune-innate response, including several members of S100 protein family, annexin A2, resistin, serpin peptidase inhibitors, azurocidin, and CD14 monocyte differentiation antigen. Our results highlight the usefulness of EVs for the discovery of novel salivary-omic biomarkers and open novel perspectives in pSS for the identification of proteins of clinical relevance that could be used not only for the disease diagnosis but also to improve patients’ stratification and treatment-monitoring. Data are available via ProteomeXchange with identifier PXD025649.

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.

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.

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.

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.

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.

Role of Calprotectin as a Biomarker in Periodontal Disease

Periodontal disease (PD) is a common infectious and inflammatory disease characterised by inflammation of tissues surrounding and supporting the teeth and destruction of the associated alveolar bone, eventually resulting in tooth loss. This disease is caused by periodontopathic bacteria in plaque biofilm and resultant innate and adaptive immune responses in periodontal tissues. Calprotectin (CLP) is a calcium-binding protein of the S-100 protein family and is found to be induced by activated granulocytes, monocytes, and epithelial cells. CLP has been shown to play an important role in numerous inflammatory diseases and disorders. Increasing evidence indicates that CLP is involved in the progression of PD, and its levels may be associated with disease severity and outcome of periodontal treatments. This review will summarise recent studies regarding the presence, regulation, and function of CLP in PD. The findings indicate that CLP may be an effective biomarker for diagnosis and treatment for the PD.

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.

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.

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.

Salivary Protein Roles in Oral Health and as Predictors of Caries Risk

This work describes the current state of research on the potential relationship between protein content in human saliva and dental caries, which remains among the most common oral diseases and causes irreversible damage in the oral cavity. An understanding the whole saliva proteome in the oral cavity could serve as a prerequisite to obtaining insight into the etiology of tooth decay at early stages. To date, however, there is no comprehensive evidence showing that salivary proteins could serve as potential indicators for the early diagnosis of the risk factors causing dental caries. Therefore, proteomics indicates the promising direction of future investigations of such factors, including diagnosis and thus prevention in dental therapy.

Microproteome of dentoalveolar tissues

Proteomic analysis of extracellular matrices (ECM) of dentoalveolar tissues can provide insights into developmental, pathological, and reparative processes. However, targeted dissection of mineralized tissues, dental cementum (DC), alveolar bone (AB), and dentin (DE), presents technical difficulties. We demonstrate an approach combining EDTA decalcification and laser capture microdissection (LCM), followed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), to analyze proteome profiles of these tissues. Using the LCM-LC-MS/MS approach, a total of 243 proteins was identified from all tissues, 193 proteins in DC, 147 in AB, and 135 proteins DE. Ninety proteins (37% of total) were common to all tissues, whereas 52 proteins (21%) were overlapping in only two. Also, 101 (42%) proteins were exclusively detected in DC (60), AB (15), or DE (26). Identification in all tissues of expected ECM proteins including collagen alpha-1(I) chain (COL1A1), collagen alpha-1(XII) chain (COL12A1), biglycan (BGN), asporin (ASPN), lumican (LUM), and fibromodulin (FMOD), served to validate the approach. Principal component analysis (PCA) and hierarchical clustering identified a high degree of similarity in DC and AB proteomes, whereas DE presented a distinct dataset. Exclusively and differentially identified proteins were detected from all three tissues. The protein-protein interaction network (interactome) of DC was notable for its inclusion of several indicators of metabolic function (e.g. mitochondrial proteins, protein synthesis, and calcium transport), possibly reflecting cementocyte activity. The DE proteome included known and novel mineralization regulators, including matrix metalloproteinase 20 (MMP-20), 5' nucleotidase (NT5E), and secreted phosphoprotein 24 (SPP-24 or SPP-2). Application of the LCM-LC-MS/MS approach to dentoalveolar tissues would be of value in many experimental designs, including developmental studies of transgenic animals, investigation of treatment effects, and identification of novel regenerative factors.

Detection of inflammatory biomarkers in saliva and urine: Potential in diagnosis, prevention, and treatment for chronic diseases

Inflammation is a part of the complex biological response of inflammatory cells to harmful stimuli, such as pathogens, irritants, or damaged cells. This inflammation has been linked to several chronic diseases including cancer, atherosclerosis, rheumatoid arthritis, and multiple sclerosis. Major biomarkers of inflammation include tumor necrosis factor, interleukins (IL)-1, IL-6, IL-8, chemokines, cyclooxygenase, 5-lipooxygenase, and C-reactive protein, all of which are regulated by the transcription factor nuclear factor-kappaB. Although examining inflammatory biomarkers in blood is a standard practice, its identification in saliva and/or urine is more convenient and non-invasive. In this review, we aim to (1) discuss the detection of these inflammatory biomarkers in urine and saliva; (2) advantages of using salivary and urinary inflammatory biomarkers over blood, while also weighing on the challenges and/or limitations of their use; (3) examine their role(s) in connection with diagnosis, prevention, treatment, and drug development for several chronic diseases with inflammatory consequences, including cancer; and (4) explore the use of innovative salivary and urine based biosensor strategies that may permit the testing of biomarkers quickly, reliably, and cost-effectively, in a decentralized setting.

In silico analyses of heparin binding proteins expression in human periodontal tissues

BACKGROUND

Periodontitis is described as a group of inflammatory diseases of the gingiva and supporting structures of the periodontium. The accumulation of plaque bacteria, which include putative periodontal pathogens, is known to initiate the disease but the host immune response is the major contributing factor for destruction of periodontal tissues. Proteins that bind to heparin heparin-binding protein (HBPs) play important roles in health and disease and interact with each other via networks known as 'heparin interactomes'. This study aimed at evaluating published datasets of HBPs and its role in periodontitis.

METHODS

To elucidate the role of HBPs in periodontitis, bioinformatics analyses of published data was used. In silico analyses of published datasets were used to construct a putative HBPs interactome using an online database resource, 'STRING' (Search Tool for the Retrieval of Interacting Genes).

RESULTS

PubMed searches identified 249 genes that were up regulated and 146 genes that were down regulated in periodontal disease, compared with periodontal disease-free gingival samples. In silico analyses using published datasets revealed 25 up-regulated and 23 down-regulated HBPs in periodontitis. Of these HBPs; chemokines, such as CXCL12 was up regulated where as some of the matrixmetalloproteinases (MMPs; MMP-2 and MMP9) were up-regulated while MMP-14 was down regulated.

CONCLUSIONS

The results indicate that HBP analyses will provide multiple targets for the biological mechanisms underlying periodontal disease (such as MMPs, cytokines and chemokines) that will have important clinical implications in the future drug design and management of periodontal disease.

Proteomics - The research frontier in periodontics

Periodontitis is an inflammatory condition resulting from the interplay between the infectious agents and host factors. Various protein molecules play a vital role in the initiation, progression and severity of periodontal diseases. The study of proteins as biomarkers in periodontal diseases has been highlighted during the last few years. In periodontitis multiple bacteria derived (e.g. collagen degrading enzymes, elastase like enzymes etc) and host derived mediators (eg. PGE2, TNF, IL1, IL6, MMP's etc) expressed in the saliva and gingival crevicular fluid, can be utilized as diagnostic markers for the disease. Another significant development regarding human genes and proteins has been the discovery of potential new drugs for the treatment of periodontal diseases. Therefore the information of the proteins involved in the pathogenesis of periodontal diseases can be utilized for its diagnosis, prevention and treatment.

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.

Matrix metalloproteinases and myeloperoxidase in gingival crevicular fluid provide site-specific diagnostic value for chronic periodontitis

AIM

To identify the diagnostic accuracy of gingival crevicular fluid (GCF) candidate biomarkers to discriminate periodontitis from the inflamed and healthy sites, and to compare the performance of two independent matrix metalloproteinase (MMP)-8 immunoassays.

MATERIALS AND METHODS

Cross sectional study. GCF (N = 58 sites) was collected from healthy, gingivitis and chronic periodontitis volunteers and analysed for levels of azurocidin, chemokine ligand 5, MPO, TIMP-1 MMP-13 and MMP-14 by ELISA or activity assays. MMP-8 was assayed by immunofluorometric assay (IFMA) and ELISA. Statistical analysis was performed using linear mixed-effects models and Bayesian statistics in R and Stata V11.

RESULTS

MMP-8, MPO, azurocidin and total MMP-13 and MMP-14 were higher in periodontitis compared to gingivitis and healthy sites (p < 0.05). A very high correlation between MPO and MMP-8 was evident in the periodontitis group (r = 0.95, p < 0.0001). MPO, azurocidin and total levels of MMP-8, MMP-13 and MMP-14 showed high diagnostic accuracy (≥0.90), but only MMP-8 and MPO were significantly higher in the periodontitis versus gingivitis sites. MMP-8 determined by IFMA correlated more strongly with periodontal status and showed higher diagnostic accuracy than ELISA.

CONCLUSIONS

MPO and collagenolytic MMPs are highly discriminatory biomarkers for site-specific diagnosis of periodontitis. The comparison of two quantitative MMP-8 methods demonstrated IFMA to be more accurate than ELISA.

Proteomics for the discovery of biomarkers and diagnosis of periodontitis: a critical review

Periodontitis is a common chronic and destructive disease whose pathogenetic mechanisms remain unclear. Due to their sensitivity and global scale, proteomics studies offer the opportunity to uncover critical host and pathogen activity indicators and can elucidate clinically applicable biomarkers for improved diagnosis and treatment of the disease. This review summarizes the literature of proteomics studies on periodontitis and comprehensively discusses commonly found candidate biomarkers. Key considerations in the design of an experimental proteomics platform are also outlined. The applicability of protein biomarkers across the progression of periodontitis and unexplored areas of research are highlighted.

Salivary biomarker development using genomic, proteomic and metabolomic approaches

The use of saliva as a diagnostic sample provides a non-invasive, cost-efficient method of sample collection for disease screening without the need for highly trained professionals. Saliva collection is far more practical and safe compared with invasive methods of sample collection, because of the infection risk from contaminated needles during, for example, blood sampling. Furthermore, the use of saliva could increase the availability of accurate diagnostics for remote and impoverished regions. However, the development of salivary diagnostics has required technical innovation to allow stabilization and detection of analytes in the complex molecular mixture that is saliva. The recent development of cost-effective room temperature analyte stabilization methods, nucleic acid pre-amplification techniques and direct saliva transcriptomic analysis have allowed accurate detection and quantification of transcripts found in saliva. Novel protein stabilization methods have also facilitated improved proteomic analyses. Although candidate biomarkers have been discovered using epigenetic, transcriptomic, proteomic and metabolomic approaches, transcriptomic analyses have so far achieved the most progress in terms of sensitivity and specificity, and progress towards clinical implementation. Here, we review recent developments in salivary diagnostics that have been accomplished using genomic, transcriptomic, proteomic and metabolomic approaches.

One decade of salivary proteomics: current approaches and outstanding challenges

Efforts have been made in the last decade towards the complete characterization of saliva proteome using gel-based and gel-free approaches. The combination of these strategies resulted in the increment of the dynamic range of saliva proteome, which yield in the identification of more than 3,000 different protein species. Comparative protein profiling using isotope labeling and label free approaches has been used for the identification of novel biomarkers for oral and related diseases. Although progresses have been made in saliva proteome characterization, the comparative profiling in different pathophysiological conditions is still at the beginning if compared to other bodily fluids. The potential biomarkers identified so far lack specificity once common differentially expressed proteins were detected in the saliva of patients with distinct diseases. In addition, recent research works focused on saliva peptidome profiling already allowed a better understanding of peptides' physiological role in oral cavity. This review provides an overview of the major achievements in saliva proteomics giving emphasis to methodological concerns related with saliva collection, treatment and analysis, as well as the main advantages and pitfalls underlying salivary proteomic strategies and potential clinical outcomes.

Protease profiling of different biofluids in type 1 diabetes mellitus

OBJECTIVES

We aimed to disclose the proteolytic events underlying type 1 diabetes and related complication through protease profiling in the bodily fluids serum, urine and saliva.

DESIGN AND METHODS

Zymography followed by LC-MS/MS was performed for protease identification and quantitative comparison of proteolytic activity between healthy, type 1 diabetic patients with no complications and with retinopathy and nephropathy. Western blotting was also accomplished for MMP-9 and MMP-2 identification and expression analysis.

RESULTS

Only MMP-2 and MMP-9 were observed in serum with significantly increased levels and activity observed in diabetic patients. In urine and saliva other proteases besides MMPs were identified by MS and presented disease-dependent activity variations. Among these are complex MMP-9/Neutrophil gelatinase-associated lipocalin, aminopeptidase N, azurocidin and kallikrein 1 with more activity noticed in type 1 diabetes patients with nephropathy and/or retinopathy.

CONCLUSION

Our data highlight the usefulness of urine and saliva for the monitoring of type-1 diabetes-related proteolytic events, where aminopeptidase N, azurocidin and kallikrein 1 appear as promising screening targets for type 1 diabetes-related complications.