Microbial Analysis of Saliva to Identify Oral Diseases Using a Point-of-Care Compatible qPCR Assay

Bacteroides fragilis in saliva: investigating links with ulcerative colitis

BACKGROUND

Ulcerative colitis (UC) is a long-term bowel inflammation of unknown cause. Recent research points to gut microbiota, especially Enterotoxigenic Bacteroides fragilis (ETBF), in UC's development. This study examined the presence of Bacteroides fragilis (B. fragilis) and ETBF in the saliva of UC patients and Healthy Controls (HCs) in Iran.

METHODS

A total of 40 UC patients and 40 healthy controls were included in the study. Saliva samples were collected and analyzed for the presence of B. fragilis and ETBF using real-time polymerase chain reaction (PCR).

RESULTS

B. fragilis was more prevalent in HCs (70%) than UC patients (67.5%), but not significantly (p = 0.809). ETBF was significantly more prevalent in UC patients (50%) than HCs (10%) (p < 0.0001). The mean count of B. fragilis was higher in UC patients, but not significantly (p = 0.47). However, the mean count of ETBF was significantly higher in UC patients (p = 0.000089). In terms of gender, the number of B. fragilis in women was not significant (p = 0.16), but the number of ETBF was significantly higher in women with UC (p = 0.000458). For men, no significant differences were observed.

CONCLUSIONS

The present study suggest a higher prevalence of B. fragilis observed in UC patients compared to HCs. Further research is needed to confirm these findings and explore potential mechanisms underlying this association.

SARS-CoV-2 diagnosis in saliva samples: Usefulness and limitations

Saliva samples are important for diagnosis, because they are noninvasive and easy to acquire. The objective of this cross-sectional study was to investigate the value saliva samples have in detecting SARS-CoV-2 in comparison to nasal swabs and a new system named CovidCheck. A standard methodology identified the virus in 185 nasopharyngeal swabs and saliva samples revealing a sensitivity, specificity and positive and negative predictive values of 82,100,100 and 94.67%, respectively for saliva samples. Viral presence in saliva samples with the standard methodology in comparison to the CovidCheck system was evaluated in 67 samples with sensitivity, specificity and positive and negative predictive values of 68, 81, 68 and 81%, respectively. In conclusion, our results highlight the usefulness saliva samples have in detecting respiratory viral infections. However, presence of viral inhibitors and viral load in saliva, and the patient's clinical status should be considered as they might affect amplifying systems results.

Rapid multiplex real-time PCR assay using a portable device for the detection of oral pathogens

Colonization by several oral pathogens and the onset of oral diseases, such as dental caries and periodontal diseases, are closely related. Therefore, the analysis of pathogens in oral specimens would be helpful for the risk assessment of oral diseases. We developed a rapid multiplex real-time polymerase chain reaction (PCR) method using a portable device and newly designed probe/primer sets to detect the oral pathogens Streptococcus mutans, Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia. The theoretical minimum detectable cell numbers of S. mutans, P. gingivalis, T. denticola, and T. forsythia were 1, 1, 4, and 3, respectively. The multiplex real-time PCR system simultaneously detected the colonization of S. mutans and P. gingivalis in human saliva. These results suggest that the multiplex real-time PCR system may be useful for the risk assessment of oral diseases.

Mouthguard-Type Wearable Sensor for Monitoring Salivary Turbidity to Assess Oral Hygiene

Salivary turbidity is a promising indicator for evaluating oral hygiene. This study proposed a wearable mouthguard-type sensor for continuous and unconstrained measurement of salivary turbidity. The sensor evaluated turbidity by measuring the light transmittance of saliva with an LED and a phototransistor sealed inside a double-layered mouthguard. The sensor was also embedded with a Bluetooth wireless module, enabling the wireless measurement of turbidity. The mouthguard materials (polyethylene terephthalate-glycol and ethylene-vinyl acetate) and the wavelength of the LED (405 nm) were experimentally determined to achieve high sensitivity in salivary turbidity measurement. The turbidity quantification characteristic of the proposed sensor was evaluated using a turbidity standard solution, and the sensor was capable of turbidity quantification over a wide dynamic range of 1-4000 FTU (formazine turbidity unit), including reported salivary turbidity (400-800 FTU). In vitro turbidity measurement using a saliva sample showed 553 FTU, which is equivalent to the same sample measured with a spectrophotometer (576 FTU). Moreover, in vivo experiments also showed results equivalent to that measured with a spectrophotometer, and wireless measurement of salivary turbidity was realized using the mouthguard-type sensor. Based on these results, the proposed mouthguard-type sensor has promising potential for the unconstrained continuous evaluation of oral hygiene.

Salivary leukocyte esterase activity by SillHa is a risk indicator of periodontal disease

BACKGROUND

There is increasing evidence that diagnostic salivary tests measuring inflammatory biomarkers are being developed to assess inflammatory status for early detection, prevention, and progression of periodontal disease. Therefore, the aim of the present study was to investigate and identify the salivary biomarker that can predict the inflammatory status of periodontal disease.

METHODS

A total of 36 patients (28 women and 8 men) with an average age of 57 years were investigated. Unstimulated saliva was collected from the recruited subjects and analyzed using SillHa, a saliva-testing device that measures bacteria count, saliva buffer capacity, acidity, leukocyte esterase, protein, and ammonia. Periodontal parameters were then obtained by clinical examination and initial periodontal therapy was performed. Data obtained with SillHa were compared with clinical periodontal parameters at baseline, re-examination (three months from baseline), and final examination (six months from re-examination).

RESULTS

Leukocyte esterase activity in saliva measured by SillHa; BOP and PCR measured by clinical examination showed a significant difference between baseline and final examination and between re-examination and final examination. Patients in the lower median group (group 1) had a significant difference in leukocyte esterase activity between baseline and final examination and re-examination and final examination. In addition, patients in Group 1 had significantly lower BOP between baseline and final examination. While patients in the higher median group (group 2) showed a modest decrease in leukocyte esterase activity, which was significant only between baseline and final examination, no significant changes were observed concerning BOP. Furthermore, the associated systemic disease was observed in 30% and 81.2% of group 1 and 2 patients, respectively.

CONCLUSION

The results suggest that leukocyte esterase activity in saliva measured by SillHa could serve as a reliable diagnostic marker for monitoring inflammatory status in periodontal disease.

Precision periodontal care: from omics discoveries to chairside diagnostics

The interface of molecular science and technology is guiding the transformation of personalized to precision healthcare. The application of proteomics, genomics, transcriptomics, and metabolomics is shaping the suitability of biomarkers for disease. Prior validation of such biomarkers in large and diverse patient cohorts helps verify their clinical usability. Incorporation of molecular discoveries into routine clinical practice relies on the development of customized assays and devices that enable the rapid delivery of analytical data to the clinician, while the patient is still in session. The present perspective review addresses this topic under the prism of precision periodontal care. Selected promising research attempts to innovate technological platforms for oral diagnostics are brought forward. Focus is placed on (a) the suitability of saliva as a conveniently sampled biological specimen for assessing periodontal health, (b) proteomics as a high-throughput approach for periodontal disease biomarker identification, and (c) chairside molecular diagnostic assays as a technological funnel for transitioning from the laboratory benchtop to the clinical point-of-care.

qPCR Detection and Quantification of Aggregatibacter actinomycetemcomitans and Other Periodontal Pathogens in Saliva and Gingival Crevicular Fluid among Periodontitis Patients

OBJECTIVE

The detection of special bacterial species in patients with periodontitis is considered useful for clinical diagnosis and treatment. The aim of this study was to investigate the presence of specific periopathogens and investigate whether there is a correlation between the results of different bacterial species in whole saliva and pooled subgingival plaque samples (healthy and diseased sites) from individuals with periodontitis and periodontally healthy subjects.

MATERIALS AND METHODS

In total, 52 patients were recruited and divided into two groups: non-periodontitis and periodontitis patients. For each group, the following periodontal pathogens were detected using real-time polymerase chain reaction: A. actinomycetemcomitans JP2 clone, A. actinomycetemcomitans non JP2 clone, Porphyromonasgingivalis, and total eubacteria.

RESULTS

Higher levels of the various studied bacteria were present in both saliva and plaque samples from the periodontitis group in comparison to non-periodontitis subjects. There were significant differences in P. gingivalis and A. actinomycetemcomitans JP2 clones in the saliva of periodontitis patient compared to the control group. Subgingival plaque of diseased sites presented a significant and strong positive correlation between A. actinomycetemcomitans and P. gingivalis. In saliva samples, there was a significant positive correlation between A. actinomycetemcomitans JP2 clone and P. gingivalis (p ≤ 0.002).

CONCLUSION

Quantifying and differentiating these periodontal species from subgingival plaque and saliva samples showed a good potential as diagnostic markers for periodontal disease. Regarding the prevalence of the studied bacteria, specifically A. actinomycetemcomitans JP2 clone, found in this work, and the high rate of susceptibility to periodontal species in Africa, future larger studies are recommended.

Salivary biomarkers as key to monitor personalized oral healthcare and precision dentistry: A scoping review

Personalized Oral Healthcare has recently become the new trend word in medicine and dentistry. In this context, saliva diagnostics using various biomarkers seem to be the gateway to personalized dental diagnostics and therapy. But the terminology is not (yet) uniformly defined, furthermore it is unclear to what extent which salivary markers play a relevant role in the therapeutic decision making. In this Scoping Review, an electronic search was conducted in PubMed and Web of Science databases using medical subject headings (MESH terms) “saliva”, “biomarker”, “personality/persons”, and “dentistry”. Only human studies were included, in which repeated salivary measurements were performed to analyze monitoring effects with at least ten patients per group. PRISMA-ScR and Tricco guidelines were followed: (i) to examine what salivary biomarkers have been explored in terms of personalized oral healthcare and precision dentistry, (ii) to investigate the clinical relevance for oral health and its correlation to systemic health, and (iii) to summarize an outlook for future developments based on these results. Out of 899 studies, a total of 57 were included for data extraction in this Scoping Review, mainly focusing on periodontal therapy and patient monitoring. Salivary biomarkers have shown the potential to change the field of dentistry in all dental disciplines as a key for personalized workflows. The increasing interest in dental research is obvious, demonstrated by the growing number of publications in recent years. At this time, however, the predominant discipline is periodontology, which allows biomarker-based monitoring of the disease prevention and progression. The studies included showed heterogeneous methods using manifolds biomarkers. Therefore, no uniformly accepted concept can be presented today. Further clinical research with well-defined outcomes including standardized procedures is necessary.

OralDisk: A Chair-Side Compatible Molecular Platform Using Whole Saliva for Monitoring Oral Health at the Dental Practice

Periodontitis and dental caries are two major bacterially induced, non-communicable diseases that cause the deterioration of oral health, with implications in patients' general health. Early, precise diagnosis and personalized monitoring are essential for the efficient prevention and management of these diseases. Here, we present a disk-shaped microfluidic platform (OralDisk) compatible with chair-side use that enables analysis of non-invasively collected whole saliva samples and molecular-based detection of ten bacteria: seven periodontitis-associated (Aggregatibacter actinomycetemcomitans, Campylobacter rectus, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola) and three caries-associated (oral Lactobacilli, Streptococcus mutans, Streptococcus sobrinus). Each OralDisk test required 400 µL of homogenized whole saliva. The automated workflow included bacterial DNA extraction, purification and hydrolysis probe real-time PCR detection of the target pathogens. All reagents were pre-stored within the disk and sample-to-answer processing took < 3 h using a compact, customized processing device. A technical feasibility study (25 OralDisks) was conducted using samples from healthy, periodontitis and caries patients. The comparison of the OralDisk with a lab-based reference method revealed a ~90% agreement amongst targets detected as positive and negative. This shows the OralDisk's potential and suitability for inclusion in larger prospective implementation studies in dental care settings.

A critical analysis of research methods to study clinical molecular biomarkers in Endodontic research

The authors of this narrative review aimed to address various experimental methods and make recommendations for how research should move forward in the context of studying biomarkers in clinical Endodontic research. The approach adopted is exemplified using two prominent clinical problems, namely (a) the ‘reversible’ versus ‘irreversible’ pulpitis conundrum and (b) persistent idiopathic dentoalveolar pain (PIDAP). Pulpitis under deep caries or dentinal cracks is understood from a histological perspective, but clinical assessment tools to indicate irreversibly inflamed aspects of the dental pulp are elusive. PIDAP, on the other hand, is a diagnosis of exclusion; its pathophysiology is complex and not understood sufficiently to avoid unnecessary dental treatments. This review addresses how diagnostic biomarkers could further our understanding of those and other clinical problems, and how issues can be tackled from a methodological point of view. Hence, different methodological approaches to identify suitable diagnostic biomarker(s) or use known biomarkers are presented. The importance of asking a relevant research question, collecting the most suitable fluid and using the ideal collection vehicle for the research question under investigation is discussed based on the defined clinical problems.

Intervention with inulin prior to and during sanative therapy to further support periodontal health: study protocol for a randomized controlled trial

Background

Periodontal disease is a chronic state of inflammation that can destroy the supporting tissues around the teeth, leading to the resorption of alveolar bone. The initial strategy for treating periodontal disease is non-surgical sanative therapy (ST). Periodontal disease can also induce dysbiosis in the gut microbiota and contribute to low-grade systemic inflammation. Prebiotic fibers such as inulin can selectively alter the intestinal microbiota and support homeostasis by improving gut barrier functions and preventing inflammation. Providing an inulin supplement prior to and post-ST may influence periodontal health while providing insight into the complex relationship between periodontal disease and the gut microbiota. The primary objective is to determine if inulin is more effective than the placebo at improving clinical periodontal outcomes including probing depth (PD) and bleeding on probing (BOP). Secondary objectives include determining the effects of inulin supplementation pre- and post-ST on salivary markers of inflammation and periodontal-associated pathogens, as these outcomes reflect more rapid changes that can occur.

Methods

We will employ a single-center, randomized, double-blind, placebo-controlled study design and recruit and randomize 170 participants who are receiving ST to manage the periodontal disease to the intervention (inulin) or placebo (maltodextrin) group. A pilot study will be embedded within the randomized controlled trial using the first 48 participants to test the feasibility for the larger, powered trial. The intervention period will begin 4 weeks before ST through to their follow-up appointment at 10 weeks post-ST. Clinical outcomes of periodontal disease including the number of sites with PD ≥ 4 mm and the presence of BOP will be measured at baseline and post-ST. Salivary markers of inflammation, periodontal-associated pathogens, body mass index, and diet will be measured at baseline, pre-ST (after 4 weeks of intervention), and post-ST (after 14 weeks of intervention).

Discussion

We expect that inulin will enhance the positive effect of ST on the management of periodontal disease. The results of the study will provide guidance regarding the use of prebiotics prior to and as a supportive adjunct to ST for periodontal health.

Trial registration

ClinicalTrials.gov NCT04670133. Registered on 17 December 2020.

Salivary Biomarkers for Dental Caries Detection and Personalized Monitoring

This study investigated the potential of salivary bacterial and protein markers for evaluating the disease status in healthy individuals or patients with gingivitis or caries. Saliva samples from caries- and gingivitis-free individuals (n = 18), patients with gingivitis (n = 17), or patients with deep caries lesions (n = 38) were collected and analyzed for 44 candidate biomarkers (cytokines, chemokines, growth factors, matrix metalloproteinases, a metallopeptidase inhibitor, proteolytic enzymes, and selected oral bacteria). The resulting data were subjected to principal component analysis and used as a training set for random forest (RF) modeling. This computational analysis revealed four biomarkers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) to be of high importance for the correct depiction of caries in 37 of 38 patients. The RF model was then used to classify 10 subjects (five caries-/gingivitis-free and five with caries), who were followed over a period of six months. The results were compared to the clinical assessments of dental specialists, revealing a high correlation between the RF prediction and the clinical classification. Due to the superior sensitivity of the RF model, there was a divergence in the prediction of two caries and four caries-/gingivitis-free subjects. These findings suggest IL-4, IL-13, IL-2-RA, and eotaxin/CCL11 as potential salivary biomarkers for identifying noninvasive caries. Furthermore, we suggest a potential association between JAK/STAT signaling and dental caries onset and progression.

Oral Diagnostic Methods for the Detection of Periodontal Disease

Periodontitis is a common immune-inflammatory oral disease. Early detection plays an important role in its prevention and progression. Saliva is a reliable medium that mirrors periodontal health and is easily obtainable for identifying periodontal biomarkers in point-of-care diagnostics. The aim of this study is to evaluate the effectiveness of diagnostic salivary tests to determine periodontal status. Whole saliva (stimulated/unstimulated) from twenty healthy and twenty stage III grade B generalized periodontitis patients was tested for lactoferrin, alkaline phosphatase, calcium, density, osmolarity, pH, phosphate, buffer capacity, salivary flow rate and dynamic viscosity. A semi-quantitative urinary strip test was used to evaluate markers of inflammation in saliva (erythrocytes, leukocytes, urobilinogen, nitrite, glucose, bilirubin, and ketones), clinical periodontal parameters and pathogenic bacteria. Concentrations of lactoferrin, hemoglobin, and leukocytes were found to be significantly higher in the stimulated and unstimulated saliva in periodontitis patients compared to healthy patients, whereas alkaline phosphatase levels were higher in unstimulated saliva of periodontitis patients (p < 0.05). Periodontal biomarker analysis using test strips may be considered rapid and easy tool for distinguishing between periodontitis and healthy patients. The increase in lactoferrin, hemoglobin, and leucocytes-determined by strip tests-may provide a non-invasive method of periodontal diagnosis.

Prediction of Chronic Periodontitis Severity Using Machine Learning Models Based On Salivary Bacterial Copy Number

Periodontitis is a widespread chronic inflammatory disease caused by interactions between periodontal bacteria and homeostasis in the host. We aimed to investigate the performance and reliability of machine learning models in predicting the severity of chronic periodontitis. Mouthwash samples from 692 subjects (144 healthy controls and 548 generalized chronic periodontitis patients) were collected, the genomic DNA was isolated, and the copy numbers of nine pathogens were measured using multiplex qPCR. The nine pathogens are as follows: Porphyromonas gingivalis (Pg), Tannerella forsythia (Tf), Treponema denticola (Td), Prevotella intermedia (Pi), Fusobacterium nucleatum (Fn), Campylobacter rectus (Cr), Aggregatibacter actinomycetemcomitans (Aa), Peptostreptococcus anaerobius (Pa), and Eikenella corrodens (Ec). By adding the species one by one in order of high accuracy to find the optimal combination of input features, we developed an algorithm that predicts the severity of periodontitis using four machine learning techniques. The accuracy was the highest when the models classified “healthy” and “moderate or severe” periodontitis (H vs. M-S, average accuracy of four models: 0.93, AUC = 0.96, sensitivity of 0.96, specificity of 0.81, and diagnostic odds ratio = 112.75). One or two red complex pathogens were used in three models to distinguish slight chronic periodontitis patients from healthy controls (average accuracy of 0.78, AUC = 0.82, sensitivity of 0.71, and specificity of 0.84, diagnostic odds ratio = 12.85). Although the overall accuracy was slightly reduced, the models showed reliability in predicting the severity of chronic periodontitis from 45 newly obtained samples. Our results suggest that a well-designed combination of salivary bacteria can be used as a biomarker for classifying between a periodontally healthy group and a chronic periodontitis group.

Healthcare Challenges and Future Solutions in Dental Practice: Assessing Oral Antibiotic Resistances by Contemporary Point-Of-Care Approaches

Antibiotic resistance poses a global threat, which is being acknowledged at several levels, including research, clinical implementation, regulation, as well as by the World Health Organization. In the field of oral health, however, the issue of antibiotic resistances, as well as of accurate diagnosis, is underrepresented. Oral diseases in general were ranked third in terms of expenditures among the EU-28 member states in 2015. Yet, the diagnosis and patient management of oral infections, in particular, still depend primarily on empiric means. On the contrary, on the global scale, the field of medical infections has more readily adopted the integration of molecular-based systems in the diagnostic, patient management, and antibiotic stewardship workflows. In this perspective review, we emphasize the clinical significance of supporting in the future antibiotic resistance screening in dental practice with novel integrated and point-of-care operating tools that can greatly support the rapid, accurate, and efficient administration of oral antibiotics.