Statistical modeling and optimization for enhanced hyaluronic acid production by batch culture of Sreptococcus zooepidemicus via the supplement of uracil

Abstract

This work is aimed to achieve the optimal hyaluronic acid (HA) production by batch culture of Streptococcus zooepidemicus via the supplement of nucleotide bases using response surface methodology (RSM). First, the influence of nucleotide bases (adenine, guanine, cytosine, thymine, and uracil) on microbial HA production was investigated using fractional factorial design (FFD). By a 2^5−2 FFD, uracil was found to be the most significant factor for cell growth and HA production, while the other nucleotide bases were shown to have no significant effects on cell growth and HA production. Also, the impact of uracil on cell growth and HA production was further investigated by RSM, where two variables were considered: uracil concentration and supplement time. The optimal uracil concentration and supplement time were found to be 0.051g/L and 7h, respectively, and the predicted maximal HA production reached 6.42g/L. The maximal HA production increased from 5.0g/L of the control without uracil supplement to 6.31g/L at the optimal conditions in validation experiments.