Comparative evaluation of subgingival microbiome in healthy periodontium and gingivitis using next-generation sequencing technology: A case-control study.

Background: Human dental plaque is a complex microbial community containing millions of species. Gingivitis is a dysregulated immune-inflammatory response induced by dysbiotic plaque biofilm that interrupts symbiosis. The emergence of next-generation sequencing with 16S rRNA gene has greatly contributed in understanding the complexity of microbiota. However, studies focusing on microbiome in gingivitis are limited. The whole bacterial community is important in causing periodontal disease than a small number of periodontal pathogens. In this study, we attempted to profile the subgingival microbiome from individuals with healthy gingiva and in patients with gingivitis using next-generation sequencing technology. Materials and Methods: Subgingival plaque samples from 15 healthy periodontium (Group I) and 15 gingivitis (Group II) were collected and 16s rRNA sequencing was done in Illumina Solexa Sequencer. Data analysis using 16s metagenomics tool from BaseSpace onsite operational taxonomic units was assigned to each sequence using HOMD database. Individual variation in the microbiome of the subgingival samples between the two groups was also evaluated. Results: The comparison of top 20 species between Group I and Group II revealed no significant species group between them. Synergistetes was absent in Group I samples but found in Group II. At the genus level, HACEK group species were found in both the groups, while Dialister and Aneroglobus were found abundantly in the Group II. Conclusion: The presence of unique genera and species seen in Group II samples could point toward a dysbiotic shift that could be taking place in the subgingival environment leading to gingivitis.

Implications in the quantification of SARS-CoV2 copies in concurrent nasopharyngeal swabs, whole mouth fluid and respiratory droplets.

OBJECTIVE: Association of SARS-CoV2 burden in the aerodigestive tract with the disease is sparsely understood. We propose to elucidate the implications of SARS-CoV2 copies in concurrent nasopharyngeal swab (NPS), whole mouth fluid (WMF) and respiratory droplet (RD) samples on disease pathogenesis/transmission. METHODS: SARS-CoV2 copies quantified by RT-PCR in concurrent NPS, WMF and RD samples from 80 suspected COVID-19 patients were analysed with demographics, immune response and disease severity. RESULTS: Among the 55/80 (69 %) NPS-positive patients, SARS-CoV2 was detected in 44/55 (80 %) WMF (concordance with NPS-84 %; p = 0.02) and 17/55 (31 %) RD samples. SARS-CoV2 copies were similar in NPS (median:8.74 × 10^5) and WMF (median:3.07 × 10^4), but lower in RD (median:3.60 × 10^2). The 25-75 % interquartile range of SARS-CoV2 copies in the NPS was significantly higher in patients who shed the virus in WMF (p = 0.0001) and RD (p = 0.01). Multivariate analyses showed that hospitalized patients shed significantly higher virus copies in the WMF (p = 0.01). Hospitalized patients with more severe disease (p = 0.03) and higher IL-6 values (p = 0.001) shed more SARS-CoV2 virus in the RD. CONCLUSIONS: WMF may be used reliably as a surrogate for diagnosis. High copy numbers in the NPS probably imply early disease onset, while in the WMF and RD may imply more severe disease and increased inflammation.

Estimation of TNF-α Levels in Saliva and Serum of Patients with Periodontal Health and Chronic Periodontitis: A Case-control Study.

AIM: The aim of this case-control study is to estimate the circulatory levels of tumor necrosis factor alpha (TNF-α) in saliva and serum of patients with chronic periodontitis and periodontally healthy subjects. MATERIALS AND METHODS: Forty-four patients were screened, and based on biofilm-gingival interface (BGI) index, they were grouped into group I healthy periodontium [BGI-H (20)] and group II periodontitis [BGI-P3 (24)]. Venous blood and salivary samples were collected and analyzed using solid-phase enzyme-linked immunosorbent assay. Independent sample t test was performed to determine the association. RESULTS: Overall, there were differences in both the saliva and the serum TNF-α levels in healthy and periodontitis subjects. The average serum TNF-α concentration in group I healthy subjects was 23.12 pg/mL and in group II periodontitis was 24.06 pg/mL. In the saliva, the mean TNF-α level in group I healthy subjects was 45.69 pg/mL and in group II diseased subjects was 46.58 pg/mL. However, the values were not statistically significant (p > 0.05). CONCLUSION: Circulatory and salivary TNF-α levels were found in detectable quantities. They showed a marginal increase in chronic periodontitis patients when compared with normal healthy patients in the absence of systemic diseases. Further studies are required in a large scale and with different methodologies to substantiate the role of TNF-α in the progression of periodontal diseases. CLINICAL SIGNIFICANCE: Clinical significance of this study is to analyze the TNF-α levels in saliva and serum, which may be the aggravating factor in causing periodontal disease, thereby helping to treat periodontitis.

Evaluation of mRNA expression of the transcription factors of Th1 and Th2 subsets (T-bet and GATA-3) in periodontal health and disease - A pilot study in south Indian population.

BACKGROUND: Based on their respective pro- or anti-inflammatory cytokine profiles, the Th1/Th2 paradigm explains pathogenic mechanisms involved in periodontal disease. Establishment of Th1 and Th2 subsets from a naive T-cell precursor depends on transcriptional regulation. The aim of this study was to compare the expression of master transcription factor regulators T-bet and GATA-3, respectively, to indicate the predominance of Th1 and Th2 subsets in the presence and absence of periodontal disease. MATERIALS AND METHODS: A gingival tissue biopsy sample was obtained from each of 10 severe periodontitis patients (>5 mm attachment loss) and 10 periodontally healthy patients (no attachment loss). Biopsies were immediately processed by real-time reverse transcriptase polymerase chain reaction and the difference in mRNA expression of T-bet and GATA-3 was assessed for each group. RESULTS: The mRNA expression of T-bet was marginally increased about 1.31-fold in disease, while the GATA-3 levels showed a significant decrease of 4.39-fold in disease. CONCLUSION: The advanced periodontal lesions lack Th2 cells, which produce anti-inflammatory cytokines. The biopsies were therefore dominated by Th1 cells, which activate macrophages and osteoclasts.

Evaluation of circulatory and salivary levels of heat shock protein 60 in periodontal health and disease.

BACKGROUND: Self-antigens such as heat shock protein 60 (HSP 60) have recently been implicated in the periodontal disease pathogenesis. There is scant evidence regarding HSP 60 levels in circulation and saliva following periodontal disease and its possible relation to systemic inflammation. AIM OF THE STUDY: The aim was to evaluate the circulatory and salivary levels of HSP 60 in periodontal health and disease and to correlate it with high sensitivity C-reactive protein (hs-CRP). MATERIALS AND METHODS: Forty-five peripheral blood samples were collected from two groups of patients (periodontally healthy - Group A [22 patients] and periodontal disease - Group B [23 patients]). Serum, cell lysates, and saliva samples were used to detect HSP 60 levels in both groups by enzyme linked immunosorbent assay technique. Measurement of hs-CRP was performed using an immunoturbidimetric assay. Statistical analysis was done using the student t-test and Pearson's correlation. RESULTS: Circulatory HSP 60 was significantly increased in periodontal disease compared to health (P - 0.038). There was a significant correlation between the totals circulating HSP 60 and hs-CRP (P - 0.052), but there was no significant correlation between the salivary HSP 60 and hs-CRP levels in periodontal disease. CONCLUSION: Circulating HSP 60 levels may play a role in the systemic inflammatory state produced by periodontal disease. Salivary HSP 60 may not be used as a surrogate to determine systemic inflammation.