Kinetic modeling and statistical optimization of submerged production of anti-Parkinson’s prodrug L-DOPA by Pseudomonas fluorescens

Abstract

L-DOPA, a precursor of dopamine, is the drug of choice for Parkinson’s disease, which persists due to decreased levels of dopamine in the brain. Present study emphasis the microbial production of L-DOPA rather than the biotransformation of L-DOPA by L-tyrosine. The production of L-DOPA by bacterial isolates had gained more acceptance due to its more straightforward extraction and downstream processes. Pseudomonas fluorescens was used to produce the L-DOPA in a bioreactor system under submerged condition. The design of experiment-based Taguchi orthogonal array method was adopted for the optimization of production. L-9 orthogonal array using the analysis of mean approach was used to study the effect of different factors viz NaCl, lactose, tryptone, and inducer on the microbial production of L-DOPA. The method mentioned above is less time consuming and does not require any harsh chemicals, proving it to be an eco-friendly process. After optimizing selected factors, i.e., NaCl (1.2 g/l), lactose (1.5 g/l), tryptone (4 g/l), and inducer (0.1 g/l), 16.9 % of enhancement in L-DOPA production with 66.6% of process cost saving was observed. The production of L-DOPA was increased from 3.426 ± 0.08 g/l to 4.123 ± 0.05 g/l after optimization. Subsequently, unstructured kinetic models were adopted to simulate the fermentation kinetics and understand the metabolic process. Fisher’ F test and determination coefficients (R 2) confirmed that the Velhurst–Pearl logistic equation, Luedeking–Piret equation, and modified Luedeking–Piret equation was best fitted with the biomass production, product formation, and substrate utilization, respectively.