Optimization of an ultra-bright real-time high-throughput renilla luciferase assay for antibacterial assessment of Streptococcus mutans biofilms.

ABSTRACT

OBJECTIVE: The present work demonstrates the optimization of a renilla-based real-time, ultra-bright, non-disruptive, high-throughput bioluminescence assay (HTS) to assess the metabolism of intact Streptococcus mutans biofilms and its utility in screening the antibacterial efficacy of experimental nanofilled dental adhesive resins containing varying concentrations of nitrogen-doped titanium dioxide nanoparticles (N_TiO2). METHODS: Optimization of the assay was achieved by screening real-time bioluminescence changes in intact Streptococcus mutans biofilms imposed by the various experimental biofilm growth parameters investigated (bacterial strain, growth media, sucrose concentration, dilution factor, and inoculum volume). The optimized assay was then used to characterize the antibacterial efficacy of experimental nanofilled dental adhesive resins. The assay's ability to discriminate between bacteriostatic and bactericidal approaches was also investigated. RESULTS: Relative Light Units (RLU) values from the HTS optimization were analyzed by multivariate ANOVA (α = 0.05) and coefficients of variation. An optimized HTS bioluminescence assay was developed displaying RLUs values (brightness) that are much more intense when comparing to other previously reported bioluminescence assays, thereby decreasing the error associated with bioluminescence assays and displaying better utility while investigating the functionalities of antimicrobial nanofilled experimental dental adhesive resins with proven long-term properties. SIGNIFICANCE: The present study is anticipated to positively impact subsequent research on dental materials and oral microbiology because it serves as a valuable screening tool in metabolic-based assays with increased sensitivity and robustness. The assay reported is anticipated to be further optimized to be used as a co-reporter for other Luc based assays.