Comparative Transcriptome Analysis of Bacillus subtilis Responding to Dissolved Oxygen in Adenosine Fermentation

Dissolved oxygen (DO) is an important factor for adenosine fermentation. Our previous experiments have shown that low oxygen supply in the growth period was optimal for high adenosine yield. Herein, to better understand the link between oxygen supply and adenosine productivity in B. subtilis (ATCC21616), we sought to systematically explore the effect of DO on genetic regulation and metabolism through transcriptome analysis. The microarrays representing 4,106 genes were used to study temporal transcript profiles of B. subtilis fermentation in response to high oxygen supply (agitation 700 r/min) and low oxygen supply (agitation 450 r/min). The transcriptome data analysis revealed that low oxygen supply has three major effects on metabolism: enhance carbon metabolism (glucose metabolism, pyruvate metabolism and carbon overflow), inhibit degradation of nitrogen sources (glutamate family amino acids and xanthine) and purine synthesis. Inhibition of xanthine degradation was the reason that low oxygen supply enhanced adenosine production. These provide us with potential targets, which can be modified to achieve higher adenosine yield. Expression of genes involved in energy, cell type differentiation, protein synthesis was also influenced by oxygen supply. These results provided new insights into the relationship between oxygen supply and metabolism

Adaptive multirate estimation and control of nutrient levels in a fed-batch fermentation using off-line and on-line measurements

A multirate adaptive estimation algorithm developed earlier (Gudi et al., 1995) is extended to perform estimation of nutrient levels using frequent on-line measurements of the carbon dioxide evolution rate (CER) and off-line, infrequent and delayed measurements of the biomass and substrate concentrations. It has been shown that the algorithm can be designed to track changing substrate yield coefficients as well. The estimation algorithm has been verified using simulations and industrial data from a fed-batch fermentation involving a Streptomyces specie. It has been coupled with a nonlinear control law designed to track prespecified optimal nutrient trajectories. The resulting closed loop control scheme is evaluated using simulation runs