Optimization of a real-time high-throughput assay for assessment of Streptococcus mutans metabolism and screening of antibacterial dental adhesives. Issue 3 (March 2020) - Esteban Florez, Fernando Luis; Hiers, Rochelle Denise; Zhao, Yan; Merritt, Justin; Rondinone, Adam Justin; Khajotia, Sharukh Soli
Abstract: Objective: The present work shows the optimization of a high-throughput bioluminescence assay to assess the metabolism of intact Streptococcus mutans biofilms and its utility as a screening method for nanofilled antibacterial dental materials. Methods: The assay was optimized by monitoring changes in bioluminescence mediated by variation of the experimental parameters investigated (growth media and sucrose concentration, inoculum:D-Luciferin ratio, dilution factor, inoculum volume, luminescence wavelength, replicate and luciferase metabolic activity). Confocal microscopy was then used to demonstrate the impact of biofilm growth conditions on the 3-D distribution of extracellular polymeric substance (EPS) within Streptococcus mutans biofilms and its implications as confounding factors in high-throughput studies (HTS). Results: Relative Luminescence Unit (RLU) values from the HTS optimization were analyzed by multivariate ANOVA ( α = 0.05) and coefficients of variation, whereas data from 3-D structural parameters and RLU values of biofilms grown on experimental antibacterial dental adhesive resins were analyzed using General Linear Models and Student–Newman–Keuls post hoc tests ( α = 0.05). Confocal microscopy demonstrated that biofilm growth conditions significantly influenced the quantity and distribution of EPS within the 3-D structures of the biofilms. An optimized HTS bioluminescence assay was developed and its applicability as a screening method in dentistry was demonstrated using nanofilled experimental antibacterial dental adhesive resins. Significance: The present study is anticipated to positively impact the direction of future biofilm research in dentistry, because it offers fundamental information for the design of metabolic-based assays, increases the current levels of standardization and reproducibility while offering a tool to decrease intra-study variability.