The lipase production ability of a newly isolated Acinetobacter sp. in submerged (SmF) and solid-state (SSF) fermentations was evaluated. The results demonstrated this strain as one of the rare bacterium, which is able to grow and produce lipase in SSF even more than SmF. Coconut oil cake as a cheap agroindustrial residue was employed as the solid substrate. The lipase production was optimized in both media using artificial neural network. Multilayer normal and full feed forward backpropagation networks were selected to build predictive models to optimize the culture parameters for lipase production in SmF and SSF systems, respectively. The produced models for both systems showed high predictive accuracy where the obtained conditions were close together. The produced enzyme was characterized as a thermotolerant lipase, although the organism was mesophile. The optimum temperature for the enzyme activity was 45°C where 63% of its activity remained at 70°C after 2 h. This lipase remained active after 24 h in a broad range of pH (6–11). The lipase demonstrated strong solvent and detergent tolerance potentials. Therefore, this inexpensive lipase production for such a potent and industrially valuable lipase is promising and of considerable commercial interest for biotechnological applications.

EIE of fats with MoO allowed nutritional and oxidative stable plastic fats to be obtained, suitable for possible use in industrial food applications. © 2015 Society of Chemical Industry.

Coconut oil is a rich source of beneficial medium chain fatty acids (MCFAs) particularly lauric acid. In this study, the oil was modified into a value-added product using direct modification of substrate through fermentation (DIMOSFER) method. A coconut-based and coconut-oil-added solid-state cultivation using a Malaysian lipolytic Geotrichum candidum was used to convert the coconut oil into MCFAs-rich oil. Chemical characteristics of the modified coconut oils (MCOs) considering total medium chain glyceride esters were compared to those of the normal coconut oil using ELSD-RP-HPLC. Optimum amount of coconut oil hydrolysis was achieved at 29% moisture content and 10.14% oil content after 9 days of incubation, where the quantitative amounts of the modified coconut oil and MCFA were 0.330 mL/g of solid media (76.5% bioconversion) and 0.175 mL/g of solid media (53% of the MCO), respectively. MCOs demonstrated improved antibacterial activity mostly due to the presence of free lauric acid. The highest MCFAs-rich coconut oil revealed as much as 90% and 80% antibacterial activities against Staphylococcus aureus and Escherichia coli, respectively. The results of the study showed that DIMOSFER by a local lipolytic G. candidum can be used to produce MCFAs as natural, effective, and safe antimicrobial agent. The produced MCOs and MCFAs could be further applied in food and pharmaceutical industries.

Normal feed forward back-propagation artificial neural network (ANN) and cubic backward elimination response surface methodology (RSM) were used to build a predictive model of the combined effects and optimization of culture parameters for the lipase production of a newly isolated Staphylococcus xylosus. The results demonstrated a high predictive accuracy of artificial neural network compared to response surface methodology. The optimum operating condition obtained from the ANN model was found to be at 30ºC incubation temperature, pH 7.5, 60 hrs incubation period, 1.8% inoculum size and 60 rpm agitation. The lipase production increased 3.5 fold for optimal medium. The produced enzyme was characterized biochemically and this is the first report about a mesophilic staphylococci bacterium with a high thermostable lipase which is able to retain 50% of its activity at 70ºC after 90 min and at 60ºC after 120 min. This lipase is also acidic and alkaline resistant which remains active after 24 hrs in a broad range of pH (4-11).

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