Optimization of Operating Conditions for the Production of Enhanced Antifungal Metabolites from Streptomonospora arabica VSM 25 by Full Factorial Design

    Published on:July 2017
    Journal of Young Pharmacists, 2017; 9(3):399-409
    Original Article | doi:10.5530/jyp.2017.9.80

    Ushakiranmayi Managamuri1, Muvva Vijayalakshmi1*, Sudhakar Poda2, Venkat Siva Rama Krishna Ganduri2,3, Satish Babu Rajulapati4

    1Department of Botany and Microbiology, Acharya Nagarjuna University, Nagarjuna nagar, Guntur-52510, Andhra Pradesh, INDIA.

    2Department of Biotechnology, Acharya Nagarjuna University, Nagarjuna nagar, Guntur-52510, Andhra Pradesh, INDIA.

    3Department of Biotechnology, K L University, Vaddeswaram, Guntur, Andhra Pradesh, INDIA.

    4Department of Biotechnology, National Institute of Technology, Warangal, Telangana, INDIA.


    Objectives: To execute the influence of the physico-chemical variables on the production of the bioactive metabolites by Streptomonospra arabica VSM-25 using Response Surface Methodology. Materials and Methods: An actinobacterium strain isolated from the deep sea marine sediment samples was identified as Streptomonospra arabica VSM-25 by conventional and molecular approaches. RSM was employed to study the impact of five variables, viz. incubation time, pH, temperature, galactose and peptone concentrations on the production of antifungal metabolites by VSM-25. Growth related production formation kinetics and substrate utilization in batch system was analysed using mathematical and unstructured kinetic models. Results: Statistical study showed that the incubation time, pH, Temperature, Concentration of galactose and peptone has a significant effect (p <0.0001) on the bioactive metabolite production at their individual and interactive level. A second order polynomial model provided a satisfied fit for experimental data with regard to the production of antifungal metabolites. Maximum antimycotic activity was achieved at incubation time (11 days), pH (8), temperature (30°C), galactose concentration (2%) and peptone concentration (1%). Unstructured mathematical kinetic model was developed and estimated kinetic parameters also exhibited good approximation in terms of model fitting and regression analysis. Conclusion: To the best of our knowledge this is the first report on the production of anti fungal metabolites from S. arabica using RSM and kinetic modelling studies which firmly support the application of RSM and kinetic modelling for optimization. The study may find potential application in rapid screening and production of novel drug molecules from unexploited natural sources.

    Key words: Streptomonospora arabica, Antimycotic Activity, Optimization, Kinetic Modelling, Response Surface Methodology, Bioactive Metabolites.

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