Genome-Guided Investigation Provides New Insights into Secondary Metabolites of Streptomyces parvulus SX6 from Aegiceras corniculatum.

Whole-genome sequencing and genome mining are recently considered an efficient approach to shine more light on the underlying secondary metabolites of Streptomyces. The present study unearths the biosynthetic potential of endophytic SX6 as a promising source of biologically active substances and plant-derived compounds for the first time. Out of 38 isolates associated with Aegiceras corniculatum (L.) Blanco, Streptomyces parvulus SX6 was highly active against Pseudomonas aeruginosa ATCC® 9027™ and methicillin-resistant Staphylococcus epidermidis (MRSE) ATCC® 35984™. Additionally, S. parvulus SX6 culture extract showed strong cytotoxicity against Hep3B, MCF-7, and A549 cell lines at a concentration of 30 µg/ml, but not in non-cancerous HEK-293 cells. The genome contained 7.69 Mb in size with an average G + C content of 72.8% and consisted of 6,779 protein-coding genes. AntiSMASH analysis resulted in the identification of 29 biosynthetic gene clusters (BGCs) for secondary metabolites. Among them, 4 BGCs showed low similarity (28-67% of genes show similarity) to actinomycin, streptovaricin, and polyoxypeptin gene clusters, possibly attributed to antibacterial and anticancer activities observed. In addition, the complete biosynthetic pathways of plant-derived compounds, including daidzein and genistein were identified using genome mining and HPLC-DAD-MS analysis. These findings portray an exciting avenue for future characterization of promising secondary metabolites from mangrove endophytic S. parvulus.

R software package based statistical optimization of process components to simultaneously enhance the bacterial growth, laccase production and textile dye decolorization with cytotoxicity study.

The thermophilic bacterium, Bacillus licheniformis U1 is used for the optimization of bacterial growth (R1), laccase production (R2) and synthetic disperse blue DBR textile dye decolorization (R3) in the present study. Preliminary optimization has been performed by one variable at time (OVAT) approach using four media components viz., dye concentration, copper sulphate concentration, pH, and inoculum size. Based on OVAT result further statistical optimization of R1, R2 and R3 performed by Box-Behnken design (BBD) using response surface methodology (RSM) in R software with R Commander package. The total 29 experimental runs conducted in the experimental design study towards the construction of a quadratic model. The model indicated that dye concentration 110 ppm, copper sulphate 0.2 mM, pH 7.5 and inoculum size 6% v/v were found to be optimum to maximize the laccase production and bacterial growth. Whereas, maximum dye decolorization achieved in media containing dye concentration 110 ppm, copper sulphate 0.6 mM, pH 6 and inoculum size 6% v/v. R package predicted R2 of R1, R2 and R3 were 0.9917, 0.9831 and 0.9703 respectively; likened to Design-Expert (Stat-Ease) (DOE) predicted R2 of R1, R2, and R3 were 0.9893, 0.9822 and 0.8442 respectively. The values obtained by R software were more precise, reliable and reproducible, compared to the DOE model. The laccase production was 1.80 fold increased, and 2.24 fold enhancement in dye decolorization was achieved using optimized medium than initial experiments. Moreover, the laccase-treated sample demonstrated the less cytotoxic effect on L132 and MCF-7 cell lines compared to untreated sample using MTT assay. Higher cell viability and lower cytotoxicity observed in a laccase-treated sample suggest the impending application of bacterial laccase in the reduction of toxicity of dye to design rapid biodegradation process.