Development of balanced medium composition for improved rifamycin B production by isolated Amycolatopsis sp. RSP-3

Bioprocess Optimization of L-Lysine Production by Using RSM and Artificial Neural Networks from Corynebacterium glutamicum ATCC13032

L-Lysine is one of the important amino acid required for humans and animals. It has a high commercial market. Large scale production of this amino acid is essential to meet the commercial demands. Typically, L-lysine is produced by batch fermentation. In the present study, the important process, as well as nutrient parameters such as glucose concentration (g/L), rpm, incubation temperature (°C), pH and incubation time for L-lysine production byCorynebacterium glutamicumATCC13032, were optimized by a combined approach of response surface methodology (RSM) with artificial neural network (ANN) method. Initially, 32 runs face central composite design was employed. In the first step, the data was analyzed by the RSM and the optimum conditions for L-lysine production were determined. In the second step, the same data was used to train the neural network. A feed-forward neural network with error backpropagation was used. The best network was obtained by optimizing the no of neurons in the hidden layer. From the best network, the optimized weights and predicted responses were used to optimize the conditions of the selected parameters by genetic algorithm (GA). Overall with the combination of RSM-ANN-GA onefold of L-lysine production fromCorynebacterium glutamicumATCC 13032 was improved.

Modeling improved production of the chemotherapeutic polypeptide actinomycin D by a novel Streptomyces sp. strain from a Saharan soil

The novel bioactive actinobacterial strain GSBNT10 obtained from a Saharan soil, was taxonomically characterized using a polyphasic approach. 16S rRNA gene sequence analysis supported the classification of the isolate within the genus Streptomyces indicating it as a novel species. The major metabolite responsible of the bioactivity was purified and structurally characterized as actinomycin D (act-D) by mass spectrometric and nuclear magnetic resonance analyses Plackett-Burman design (PBD) and response surface methodology (RSM) were applied in order to optimize the medium formulation for the production of this bioactive metabolite. By PBD experiments, NaNO₃, K₂HPO₄ and initial pH value were selected as significant variables affecting the metabolite production. Central Composite Design (CCD) showed that adjustment of the fermentative medium at pH 8.25, K₂HPO₄ at 0.2 gL^-1 and NaNO₃ at 3.76 gL^-1 were the values suiting the production of act-D. Moreover, the results obtained by the statistical approach were confirmed by act-D detection using the HPLC equipped with a diode array detector and coupled online with electrospray-mass spectrometry (ESIMS) technique. act-D production was highly stimulated, obtaining a good yield (656.46 mgL^-1) which corresponds to a 58.56% increase compared with the non-optimized conditions and data from LC-ESIMS technique efficiently confirmed the forecast from RSM.

Echinosporin antibiotics isolated from Amycolatopsis strain and their antifungal activity against root-rot pathogens of the Panax notoginseng

Actinomycete strain YIM PH20520, isolated from the rhizosphere soil sample of Panax notoginseng collected in Wenshang, Yunnan Province, China, exhibited antifungal activity against root-rot pathogens of the Panax notoginseng. The structures of bioactive molecules, isolated from the ethyl acetate extract of the fermentation broth of the strain, were identified as echinosporin (1) and 7-deoxyechinosporin (2) based on extensive spectroscopic analyses. 1 exhibited antifungal activity against four tested root-rot pathogens of Panax notoginseng include Fusarium oxysporum, Fusarium solani, Alternaria panax, and Phoma herbarum with the MIC value at 64, 64, 32, and 64 μg/mL, respectively. 2 exhibited antifungal activities against F. oxysporum, F. solani, A. panax, and P. herbarum with the MIC value at 128, 128, 64, and 128 μg/mL, respectively. Based on the phylogenetic analyses, the closest phylogenetic relative of strain YIM PH20520 is Amycolatopsis speibonae JS72^T (97.69%), so strain YIM PH20520 was identified as Amycolatopsis strain. To the best of our knowledge, this is the first report of echinosporin antibiotics isolated from Amycolatopsis strain besides Streptomyces strain and their antifungal activity against four tested root-rot pathogens of the Panax notoginseng. The results provide a reliable evidence for the following related biosynthetic investigations on Amycolatopsis strain YIM PH20520 due to echinosporins antibiotics' unique tricyclic acetal-lactone structures.

Role of feed forward neural networks coupled with genetic algorithm in capitalizing of intracellular alpha-galactosidase production by Acinetobacter sp

Alpha-galactosidase production in submerged fermentation by Acinetobacter sp. was optimized using feed forward neural networks and genetic algorithm (FFNN-GA). Six different parameters, pH, temperature, agitation speed, carbon source (raffinose), nitrogen source (tryptone), and K2HPO4, were chosen and used to construct 6-10-1 topology of feed forward neural network to study interactions between fermentation parameters and enzyme yield. The predicted values were further optimized by genetic algorithm (GA). The predictability of neural networks was further analysed by using mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R2-value for training and testing data. Using hybrid neural networks and genetic algorithm, alpha-galactosidase production was improved from 7.5 U/mL to 10.2 U/mL.

Production of alkaline protease by Bacillus altitudinis GVC11 using castor husk in solid-state fermentation

Castor (Ricinus communis L.) is an important oil seed crop having its main cultivated area in India, China, and Brazil in dry land farming. Castor husk is generated as waste in castor oil production. Use of castor husk waste as substrate is studied for alkaline protease production by Bacillus altitudinis GVC11 in solid-state fermentation. Various parameters like moisture content, incubation period, particle size, effect of carbon and nitrogen sources are studied and optimized for enzyme production. Highest enzyme production of 419,293 units per gram husk is obtained. Cost of enzyme production can be reduced by using castor husk as substrate.