L-Asparaginase (L-asparagine aminohydrolase, E.C. 3.5.1.1) has been proven to be competent in treating Acute Lymphoblastic Leukaemia (ALL), which is widely observed in paediatric and adult groups. Currently, clinical L-Asparaginase formulations are derived from bacterial sources such as Escherichia coli and Erwinia chrysanthemi. These formulations when administered to ALL patients lead to several immunological and hypersensitive reactions. Hence, additional purification steps are required to remove toxicity induced by the amalgamation of other enzymes like glutaminase and urease. Production of L-Asparaginase that is free of glutaminase and urease is a major area of research. In this paper, we report the screening and isolation of fungal species collected from the soil and mosses in the Schirmacher Hills, Dronning Maud Land, Antarctica, that produce L-Asparaginase free of glutaminase and urease. A total of 55 isolates were obtained from 33 environmental samples that were tested by conventional plate techniques using Phenol red and Bromothymol blue as indicators. Among the isolated fungi, 30 isolates showed L-Asparaginase free of glutaminase and urease. The L-Asparaginase producing strain Trichosporon asahii IBBLA1, which showed the highest zone index, was then optimized with a Taguchi design. Optimum enzyme activity of 20.57 U mL−1 was obtained at a temperature of 30 °C and pH of 7.0 after 60 hours. Our work suggests that isolation of fungi from extreme environments such as Antarctica may lead to an important advancement in therapeutic applications with fewer side effects.

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Optimization techniques are considered as a part of nature's way of adjusting to the changes happening around it. There are different factors that establish the optimum working condition or the production of any value-added product. A model is accepted for a particular process after its sustainability has been verified on a statistical and analytical level. Optimization techniques can be divided into categories as statistical, nature inspired and artificial neural network each with its own benefits and usage in particular cases. A brief introduction about subcategories of different techniques that are available and their computational effectivity will be discussed. The main focus of the study revolves around the applicability of these techniques to any particular operation such as submerged fermentation (SmF) and solid state fermentation (SSF), their ability to produce secondary metabolites and the usefulness in the laboratory and industrial level. Primary studies to determine the enzyme activity of different microorganisms such as bacteria, fungi and yeast will also be discussed. l-Asparaginase, the most commonly used drugs in the treatment of acute lymphoblastic leukemia (ALL) shall be considered as an example, a short discussion on models used in the production by the processes of SmF and SSF will be discussed to understand the optimization techniques that are being dealt. It is expected that this discussion would help in determining the proper technique that can be used in running any optimization process for different purposes, and would help in making these processes less time-consuming with better output.

The optimal conditions for biodiesel transesterification are 800 rpm stirring, 12 : 1 methanol to oil ratio, 3% catalyst loading, and 60 °C temperature.

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