Abstract
Tryptophan is one of the most extensively used amino acids in livestock industry owing to its effectiveness in enhancing the growth performance of animals. Conventionally, the production of tryptophan relies heavily on genetically modified Escherichia coli but its pathogenicity is a great concern. Our recent study demonstrated that a lactic acid bacterium (LAB), Pediococcus acidilactici TP-6 that isolated from Malaysian food was a promising tryptophan producer. However, the tryptophan production must enhance further for viable industrial application. Hence, the current study evaluated the effects of medium components and optimized the medium composition for tryptophan production by P. acidilactici TP-6 statistically using Plackett-Burman Design, and Central Composite Design. The optimized medium containing molasses (14.06 g/L), meat extract (23.68 g/L), urea (5.56 g/L) and FeSO4 (0.024 g/L) significantly enhanced the tryptophan production by 150% as compared to the control de Man, Rogosa and Sharpe medium. The findings obtained in this study revealed that rapid evaluation and effective optimization of medium composition governing tryptophan production by P. acidilactici TP-6 were feasible via statistical approaches. Additionally, the current findings reveal the potential of utilizing LAB as a safer alternative tryptophan producer and provides insight for future exploitation of various amino acid productions by LAB.
Highlights
Fermentation medium plays an indispensable role in the industrial fermentation process due to its impact on the formation of the desired products [1]
The production of tryptophan by P. acidilactici TP-6 in the control MRS medium (29.41 mg/L) was still significantly higher (p < 0.05) than those achieved in the Plackett-Burman Design (PBD)
Further optimization of the medium composition is mandatory to increase tryptophan yield by P. acidilactici TP-6
Summary
Fermentation medium plays an indispensable role in the industrial fermentation process due to its impact on the formation of the desired products [1]. A cost-effective medium formulation is crucial in ensuring the economic feasibility of the fermentation process. Optimization of the medium composition is important in order to minimize the cost of production without compromising the production. The conventional method of process optimization is known as one-factor-at-a-time method by varying one factor while keeping the other factors unchanged until an apparent optimum condition is achieved. The conventional optimization method often require large number of experiments and it could be time consuming and laborious. This method is not suitable for multifactor optimization because it is unable to elucidate the interactions between the factors and incapable to detect the true optimum condition [2]
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