An In Vitro Barrier Model of the Human Submandibular Salivary Gland Epithelium Based on a Single Cell Clone of Cell Line HTB-41: Establishment and Application for Biomarker Transport Studies

The blood–saliva barrier (BSB) consists of the sum of the epithelial cell layers of the oral mucosa and salivary glands. In vitro models of the BSB are inevitable to investigate and understand the transport of salivary biomarkers from blood to saliva. Up to now, standardized, cell line-based models of the epithelium of the submandibular salivary gland are still missing for this purpose. Therefore, we established epithelial barrier models of the submandibular gland derived from human cell line HTB-41 (A-253). Single clone isolation resulted in five different clones (B2, B4, B9, D3, and F11). Clones were compared to the parental cell line HTB-41 using measurements of the transepithelial electrical resistance (TEER), paracellular marker permeability assays and analysis of marker expression for acinar, ductal, and myoepithelial cells. Two clones (B9, D3) were characterized to be of acinar origin, one clone (F11) to be of myoepithelial origin and one isolation (B4) derived from two cells, to be presumably a mixture of acinar and ductal origin. Clone B2, presumably of ductal origin, showed a significantly higher paracellular barrier compared to other clones and parental HTB-41. The distinct molecular identity of clone B2 was confirmed by immunofluorescent staining, qPCR, and flow cytometry. Experiments with ferritin, a biomarker for iron storage, demonstrated the applicability of the selected model based on clone B2 for transport studies. In conclusion, five different clones originating from the submandibular gland cell line HTB-41 were successfully characterized and established as epithelial barrier models. Studies with the model based on the tightest clone B2 confirmed its suitability for transport studies in biomarker research

Directed transport of CRP across in vitro models of the blood-saliva barrier strengthens the feasibility of salivary CRP as biomarker for neonatal sepsis

C-reactive protein (CRP) is a commonly used serum biomarker for detecting sepsis in neonates. After the onset of sepsis, serial measurements are necessary to monitor disease progression; therefore, a non-invasive detection method is beneficial for neonatal well-being. While some studies have shown a correlation between serum and salivary CRP levels in septic neonates, the causal link behind this correlation remains unclear. To investigate this relationship, CRP was examined in serum and saliva samples from 18 septic neonates and compared with saliva samples from 22 healthy neonates. While the measured blood and saliva concentrations of the septic neonates varied individually, a correlation of CRP levels between serum and saliva samples was observed over time. To clarify the presence of active transport of CRP across the blood–salivary barrier (BSB), transport studies were performed with CRP using in vitro models of oral mucosa and submandibular salivary gland epithelium. The results showed enhanced transport toward saliva in both models, supporting the clinical relevance for salivary CRP as a biomarker. Furthermore, CRP regulated the expression of the receptor for advanced glycation end products (RAGE) and the addition of soluble RAGE during the transport studies indicated a RAGE-dependent transport process for CRP from blood to saliva

Salivary biomarkers for dental caries detection and personalized monitoring

© 2021 by the authors. Licensee MDPI, Basel, Switzerland.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

Oraldisk: A chair-side compatible molecular platform using whole saliva for monitoring oral health at the dental practice

© 2021 by the authors. Licensee MDPI, Basel, Switzerland.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

Chair/bedside diagnosis of oral and respiratory tract infections, and identification of antibiotic resistances for personalised monitoring and treatment

textabstractGlobal healthcare systems are struggling with the enormous burden associated with infectious diseases, as well as the incessant rise of antimicrobial resistance. In order to adequately address these issues, there is an urgent need for rapid and accurate infectious disease diagnostics. The H2020 project DIAGORAS aims at diagnosing oral and respiratory tract infections using a fully integrated, automated and user-friendly platform for physicians' offices, schools, elderly care units, community settings, etc. Oral diseases (periodontitis, dental caries) will be detected via multiplexed, quantitative analysis of salivary markers (bacterial DNA and host response proteins) for early prevention and personalised monitoring. Respiratory Tract Infections will be diagnosed by means of DNA/RNA differentiation so as to identify their bacterial or viral nature. Together with antibiotic resistance screening on the same platform, a more efficient treatment management is expected at the point-of-care. At the heart of DIAGORAS lies a centrifugal microfluidic platform (LabDisk and associated processing device) integrating all components and assays for a fully automated analysis. The project involves an interface with a clinical algorithm for the comprehensive presentation of results to end-users, thereby increasing the platform's clinical utility. DIAGORAS' performance will be validated at clinical settings and compared with gold standards