ABSTRACT
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.
Subject(s)
Disease Progression , Ferroptosis , Gingival Crevicular Fluid , Periodontitis , Humans , Gingival Crevicular Fluid/chemistry , Periodontitis/metabolism , Periodontitis/pathology , Female , Male , Proteomics , Cell Death , Adult , Middle Aged , Blotting, WesternABSTRACT
This study aimed to evaluate the impact of Candida albicans on subgingival biofilm formation on dental implant surfaces. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) were used to compare biofilm structure and microbial biomass in the presence and absence of the fungus after periods of 24, 48, and 72 h. Quantitative polymerase chain reaction (qPCR) was used to quantify the number of viable and total micro-organisms for each of the biofilm-forming strains. A general linear model was applied to compare CLSM and qPCR results between the control and test conditions. The biofilm developed with C. albicans at 72 h had a higher bacterial biomass and a significantly higher cell viability (p < 0.05). After both 48 and 72 h of incubation, in the presence of C. albicans, there was a significant increase in counts of Fusobacterium nucleatum and Porphyromonas gingivalis and in the cell viability of Streptococcus oralis, Aggregatibacter actinomycetemcomitans, F. nucleatum, and P. gingivalis. Using a dynamic in vitro multispecies biofilm model, C. albicans exacerbated the development of the biofilm grown on dental implant surfaces, significantly increasing the number and cell viability of periodontal bacteria.
Subject(s)
Candida albicans , Dental Implants , Cell Survival , Biofilms , Porphyromonas gingivalisABSTRACT
BACKGROUND: The long-term use of antifungal therapy in denture stomatitis (DS) treatment could be accompanied by antifungal-resistant strain onset, leading to compromised therapeutic procedure and disease reappearance. Photodynamic therapy (PDT) has shown the ability to eradicate oral infections and resistance strains. This prospective clinical study aimed to assess the PDT's effectiveness compared to the conventional treatment on clinical and microbiological parameters in patients with DS without denture wear during the treatment and follow-ups. METHODS: Forty-two patients diagnosed with DS were randomly assigned to one-session single PDT application (test group) or conventional antifungal therapy (control group). Clinical and microbiological parameters were assessed and analyzed before and at 3rd, 15th, and 30th day following the treatments. Microbiological samples were analyzed by a Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The data was statistically analyzed. RESULTS: Prior to the treatment, Candida species, including C. albicans (100%), C. glabrata (33%), C. tropicalis (31%), C. krusei (31%) were isolated in all patients. Both treatment procedures demonstrated a statistically significant reduction in C. albicans at all follow-up time intervals (p < 0.05). However, PDT displayed a statistically significant reduction in C. krusei compared to the conventional treatment at all follow-up periods (p < 0.05). Clinical parameters improved considerably in the test group compared to the control group at the 3rd and 15th day of follow-up. CONCLUSION: One-session single PDT application demonstrated significant improvement in both clinical and microbiological outcomes in a short-term period, resulting in complete Candida spp. eradication compared to conventional antifungal therapy.
Subject(s)
Photochemotherapy , Stomatitis, Denture , Humans , Antifungal Agents/therapeutic use , Stomatitis, Denture/drug therapy , Stomatitis, Denture/microbiology , Prospective Studies , Photochemotherapy/methods , Photosensitizing Agents/therapeutic use , Candida , Candida albicans , Candida glabrata , DenturesABSTRACT
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.
Subject(s)
Periodontitis , Proteome , Humans , Gingival Crevicular Fluid/chemistry , Proteomics , Periodontitis/metabolism , Disease ProgressionABSTRACT
Periodontitis is a chronic inflammatory disease associated with the presence of dysbiotic microbial communities. Several studies interrogating periodontitis pathogenesis have utilized the murine ligature-induced periodontitis (LIP) model and have further examined the ligature-associated microbiome relying on 16S rRNA-based sequencing techniques. However, it is often very challenging to compare microbial profiles across studies due to important differences in bioinformatic processing and databases used for taxonomic assignment. Thus, our study aim was to reanalyze microbiome sequencing datasets from studies utilizing the LIP model through a standardized bioinformatic analysis pipeline, generating a comprehensive overview of microbial dysbiosis during experimental periodontitis.We conducted a reanalysis of 16S rDNA gene sequencing datasets from nine published studies utilizing the LIP model. Reads were grouped according to the hypervariable region of the 16S rDNA gene amplified (V1-V3 and V4), preprocessed, binned into operational taxonomic units and classified utilizing relevant databases. Alpha- and beta-diversity analyses were conducted, along with relative abundance profiling of microbial communities. Our findings revealed similar microbial richness and diversity across studies and determined shifts in microbial community structure determined by periodontitis induction and study of origin. Clear variations in the relative abundance of bacterial taxa were observed starting on day 5 after ligation and onward, consistent with a distinct microbial composition during health and experimental periodontitis. We also uncovered differentially represented bacterial taxa across studies, dominating periodontal health and LIP-associated communities. Collectively, this reanalysis provides a unified overview of microbial dysbiosis during the LIP model, providing new insights that aim to inform further studies dedicated to unraveling oral host-microbial interactions.