Optimization and Modeling of AD119 Growth and 1,3-Propanediol Production Using Two-Step Statistical Experimental Design and Artificial Neural Networks.

1,3-propanediol (1,3-PD) has a wide range of industrial applications. The most studied natural producers capable of fermenting glycerol to 1,3-PD belong to the genera , , and . In this study, the optimization of medium composition for the biosynthesis of 1,3-PD by AD119 was performed using the one-factor-at-a-time method (OFAT) and a two-step statistical experimental design. Eleven mineral components were tested for their impact on the process using the Plackett-Burman design. MgSO and CoCl were found to have the most pronounced effect. Consequently, a central composite design was used to optimize the concentration of these mineral components. Besides minerals, carbon and nitrogen sources were also optimized. Partial glycerol substitution with other carbon sources was found not to improve the bioconversion process. Moreover, although yeast extract was found to be the best nitrogen source, it was possible to replace it in part with (NH)SO without a negative impact on 1,3-PD production. As a part of the optimization procedure, an artificial neural network model of the growth of and 1,3-PD production was developed as a predictive tool supporting the design and control of the bioprocess under study.