Objectives: The present work was carried out to check the capability of novel actinobacterium, Nonomuraea longicatena (VSM-16) for bioactive metabolite production and optimization of its process parameters by statistical and mathematical modeling. Methods: Response Surface Methodology (RSM) regression evaluation was done to fit the experimental data of each response with the aid of second order polynomial. Unstructured kinetic models had been developed for growth, substrate utilization and bioactive metabolite production (in terms of responses). Model based kinetic parameters were estimated and the profiles of bioactive metabolite production, substrate utilization and growth had been drawn. Results: The results have shown accurate interaction among process variables at optimized values of incubation time at 8-9 days, pH at 8-9, temperature at 30-31°C, concentrations of Mannitol at 2-2.2% and Biopeptone at 1.5-1.7% and the data have been effectively fitted into second-order polynomial models. Under these conditions, the responses (zones of inhibition) of various organisms Staphylococcus aureus, Streptococcus mutans, Xanthomonas campestris, Pseudomonas aeruginosa and Candida albicans have been also matched with experimental and predicted consequences. Conclusion: The zones of inhibition (responses) for the organisms had been also determined to be best fitted with experiment and model values.
Key words: Bioactive metabolites, Mathematical modeling, Nonomuraea longicatena, Optimization, Regression Analysis, Response Surface Methodology.
