Abstract

Bioactive metabolite production by marine Saccharothrix flava VSM-3 was modeled by RSM statistical optimization and kinetic parameter estimation was executed using unstructured models to depict the importance of growth-associated metabolite production. RSM based optimization of the variables and their interactions was analyzed where the modeled data and experimental data are in concurrence and yielded better responses in terms of inhibition zones for active metabolite with good regression coefficients. The regression model developed the significance of five variables and their influence on the bioactive metabolite production and its effect against the responses. Logistic, Luedeking-Piret equations were used for batch fermentation to produce bioactive metabolites by S. flava VSM-3 where the anticipated parameter data followed experimental data. Chemotype (using Ethyl acetate extract) analysis of actinobacterial isolate S. flava was elucidated for the first time by LC-QTOF-MS analysis. The main compounds identified in the positive ion mode were 7-Deazaadenosine, 5-Hydroxy-9-Methylstreptimidone, Amiclenomycin, Dihydroabikoviromycin, Epopromycin A, OAP Silane 55 and MKN-003B. In the present study, maritime silt specimen of Bay of Bengal comprising S. flava VSM-3 recorded prominent broad-spectrum activity against various plant pathogens and LC-QTOF-MS data also supported VSM-3 was the most active strain. This study also reveals that under explored Bay of Bengal of north coastal Andhra Pradesh should be continuously explored for extracting bioactive compounds from diverse strains.

Key words: Bioactive metabolites; Kinetic parameters; LC-QTOF-MS; Saccharothrix flava; Statistical modeling