Enhancing the biotransformation of progesterone to the anticancer compound testololactone by Penicillium chrysogenum Ras3009: kinetic modelling and efficiency maximization.

Background: Biotransformation of steroid compounds into therapeutic products using microorganisms offers an eco-friendly and economically sustainable approach to the pharmaceutical industry rather than a chemical synthesis way. The biotransformation efficiency of progesterone into the anticancer compound testololactone using Penicillium chrysogenum Ras3009 has been investigated. Besides, maximization of testololactone formation was achieved by studying the kinetic modelling and impact of some fermentation conditions on the biotransformation process.

Results: The fungal strain Ras3009 was selected among twelve fungal strains as the most runner for the transformation of 81.18% of progesterone into testololactone. Ras3009 was identified phenotypically and genotypically as Penicillium chrysogenum, its 18 S rRNA nucleotide sequence was deposited in the GenBank database by the accession number OR480104. Studying the impact of fermentation conditions on biotransformation efficiency indicated a positive correlation between substrate concentration and testololactone formation until reaching the maximum velocity v_max. Kinetic studies revealed that v_max was [Formula: see text] gL^- 1hr^- 1 with high accuracy, giving R² of 0.977. The progesterone transformation efficiency generally increased with time, reaching a maximum of 100% at 42 h with testololactone yield (Y_pt/s) 0.8700 mg/mg. Moreover, the study indicated that the enzymatic conversion by P. chrysogenum Ras3009 showed high affinity to the substrate, intracellularly expressed, and released during cell disruption, leading to higher efficiency when using whole microbial cell extract.

Conclusions: Fungi can be promising biocatalysts for steroid transformation into valuable chemicals and pharmaceutical compounds. The study revealed that the new fungal isolate P. chrysogenum Ras3009 possesses a great catalytic ability to convert progesterone into testololactone. Kinetic modelling analysis and optimization of the fermentation conditions lead to higher transformation efficiency and provide a better understanding of the transformation processes.