1-13: Applying systems biology and next-generation sequencing techniques for robust biocatalyst development: promises and limitations

Tuesday, May 1, 2012
Napoleon Ballroom C-D, 3rd fl (Sheraton New Orleans)
Min Zhang, National Bioenergy Center, National Renewable Energy Laboratory, Golden, CO
Significant efforts have been focused on developing the desired biocatalyst with essential characteristics such as robustness, substrate utilization, productivity and yield. Recently the rapid progress in such techniques as next-generation sequencing (NGS) and systems biology approaches have been extensively applied to understand the biocatalysts at a global level, and changed the paradigm strategies for biocatalyst development. However, each technique has inherent limitations to obtain complete metabolic and regulatory pictures for biocatalyst development. In this presentation, using Zymomonas mobilis as a model system, I will discuss our efforts to better understand the inhibitor tolerance and nonnative sugar utilization using NGS and systems biology approaches, the limitations of each approach, and the insights we obtained from these studies. Specifically, NGS-based genome resequencing has been applied to investigate the genetic differences among strains developed for acetate tolerance as well as xylose and arabinose utilization with potential candidate genetic features identified. We also use both chip-based high-density microarray and NGS-based strand specific RNA-Seq to study the short-term and long-term stress responses of Z. mobilis to the major inhibitors found in hydrolysate, acetate and furfural, when grown on different sugars.  The global transcriptional profiles and transcriptional architecture improvement obtained from these studies will expand our scientific understanding and directly help strain improvement efforts. In addition, comparative genomics among different Z. mobilis strains has also been explored to identify the core genetic features and the evolutionary forces shaping these strains resulting in different physiological phenotypes.
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