Tuesday, April 30, 2013
Exhibit Hall
Cofactor engineering, i.e., the modification of enzyme cofactor specificity, can be used as a method for both studying and engineering cellular metabolism. However, due to the intrinsic complexity of cofactor balance in microbial metabolism, cofactor engineering strategies by simple modification of target enzymes through site-directed mutagenesis have obtained limited success. One possible reason is that the introduced changes may be counteracted or bypassed by other pathways. Therefore, it would be more effective to design cofactor engineering strategies through metabolic network analysis. In this work we propose a system identification based framework to study the effect of various cofactor engineering strategies for xylose metabolisms in both Scheffersomyces stipitis and recombinant Saccharomyces cerevisiae. The NAD(P)H-dependent xylose reductase (PsXR) and NAD(P)+-dependent xylitol dehydrogenase (PsXDH) from S. stipitis are the two key enzymes for xylose fermentation, and have been cloned into S. cerevisiae. In order to eliminate the redox imbalance resulting from the preference of the enzymes to different cofactors, efforts have been made to alter the coenzyme specificity of PsXR and PsXDH. Given the industrial importance of PsXR and PsXDH, it is of interest to investigate the influence of cofactor engineering systematically. With the metabolic network models, we simulated possible metabolic changes by varying metabolic flux ratios through reactions that utilize different cofactors. The analysis results are validated with published experimental data. In addition, the reactions mostly influenced by a given cofactor engineering strategy can be identified, which provides key information to improve the design of cofactor engineering strategy.