Optimization of a real-time high-throughput assay for assessment of Streptococcus mutans metabolism and screening of antibacterial dental adhesives

优化实时高通量检测方法以评估变形链球菌代谢并筛选抗菌牙科粘合剂

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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.

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