This study compared different commercially available viability reagents. The growth indicator reagents include p-iodonitrotetrazolium violet (INT), PrestoBlue, and Alamar Blue which were used for antimicrobial analysis against Streptococcus mutans, Prevotella intermedia, Propionibacterium acnes, and Mycobacterium tuberculosis. PrestoBlue and Alamar Blue are resazurin based reagents that resulted in a quick and easily distinguishable colour change that allowed for visual readings. INT and Sodium 3′-[1-(phenyl amino-carbonyl)-3,4-tetrazolium]-bis-[4-methoxy-6-nitro] benzene sulfonic acid hydrate (XTT) are tetrazolium based reagents which are converted to a formazan dye in the presence of metabolically active mitochondria enzyme. For cell viability analysis, reagents XTT and PrestoBlue were compared. PrestoBlue was able to clearly indicate the minimum inhibitory concentration (MIC) of various positive drug controls on various microbial strains. PrestoBlue was also a good indicator of the 50% inhibitory concentration (IC50) of positive drug controls on various cell lines.

The use of complementary and alternative medicine from plants in South Africa, as in the rest of the world, continues to increase. Heteropyxis natalensis, known as the Lavender tree, is indigenous to South Africa and is traditionally used for oral care. The ethanolic extract, of the leaves and twigs, of H. natalensis was investigated for antimicrobial activity against selected oral microorganisms. Actinomyces israelii was found to be the most sensitive oral microorganism to the extract, with a minimum inhibitory concentration (MIC) of 0.88 mg/ml and an MIC of 2.6 mg/ml against Streptococcus mutans. Five known compounds were identified from the ethanolic extract of H. natalensis. The compounds were identified as aurentiacin A (1), cardamomin (2), 5-hydroxy-7-methoxy-6-methylflavanone (3), quercetin (4) and 3,5,7-trihydroxyflavan (5). The MICs of the compounds 1 and 4 were found to be 0.06 mg/ml and 1 mg/ml, respectively, against A. israelii. The cytotoxicity, acute and sub-acute toxicity in pre-clinical studies were also determined for H. natalensis. The extract showed moderate cytotoxicity (35.56 ± 0.16 μg/ml) on human monocyte cells. The acute and sub-acute toxicity analysis of H. natalensis indicated the NOEL (no-observed-effect level) at 200 mg/kg. Interleukin-8 (IL-8) is a chemokine that stimulates the recruitment of leukocytes. A significant reduction of IL-8 production by macrophage cells was observed when exposed to the extract of H. natalensis. It is possible that H. natalensis can prevent excessive tissue damage in periodontal diseases through its reduction of inflammation. Enzymatic bioanalysis of lactic and acetic acid production from Streptococcus mutans and Lactobacillus paracasei was done. A reduction in the acid production from each bacterium was observed on exposure to the extract of H. natalensis. Consequently, this increased the pH, which could possibly reduce the demineralization of enamel which may help prevent the formation of dental caries. In addition the extract may be considered for preventing periodontal diseases.

BackgroundThere are several synergistic methods available. However, there is a vast discrepancy in the interpretation of the synergistic results. Also, these synergistic methods do not assess the influence the tested components (drugs, plant and natural extracts), have upon one another, when more than two components are combined.MethodsA modified checkerboard method was used to evaluate the synergistic potential of Heteropyxis natalensis, Melaleuca alternifolia, Mentha piperita and the green tea extract known as TEAVIGO™. The synergistic combination was tested against the oral pathogens, Streptococcus mutans, Prevotella intermedia and Candida albicans. Inhibition data obtained from the checkerboard method, in the form of binary code, was used to compute a logistic response model with statistically significant results (p < 0.05). This information was used to construct a novel predictive inhibition model.ResultsBased on the predictive inhibition model for each microorganism, the oral pathogens tested were successfully inhibited (at 100% probability) with their respective synergistic combinations. The predictive inhibition model also provided information on the influence that different components have upon one another, and on the overall probability of inhibition.ConclusionsUsing the logistic response model negates the need to ‘calculate’ synergism as the results are statistically significant. In successfully determining the influence multiple components have upon one another and their effect on microbial inhibition, a novel predictive model was established. This ability to screen multiple components may have far reaching effects in ethnopharmacology, agriculture and pharmaceuticals.

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