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![](https://webarchive.library.unt.edu/eot2008/20090508205253im_/http://www.ars.usda.gov/incme/images/Research_head.gif) |
Research Project:
Genomic Mechanisms of in Situ Detoxification of Biomass Conversion Inhibitors for Ethanologenic Yeast Saccharomyces Cerevisiae
Location: Crop Bioprotection Research
Project Number: 3620-41000-123-01
Project Type:
Reimbursable
Start Date: Sep 15, 2006
End Date: Sep 14, 2009
Objective:
The overall objective of this project is to elucidate genomic mechanisms of detoxification and tolerance of ethanologenic yeast to biomass conversion inhibitors furfural and 5-hydroxymethylfurfural (HMF), and thereafter to genome-wise manipulate and engineer more robust strains for low-cost biomass conversion to ethanol. This study will identify and characterize genes involved in pathways relevant to detoxification, biotransformation, and tolerance to furfural and HMF involved in biomass conversion to ethanol; and elucidate regulatory mechanisms of major gene interactions in relevant pathways involved in furfural and HMF detoxification and tolerance using computational prediction and mathematical modeling.
Approach:
We plan to study genomic regulatory mechanisms of inhibitor detoxification by yeast during ethanol production from dilute acid-hydrolyzed biomass. We propose to characterize the genomic transcriptional profiling of wild-type and several improved, more inhibitor-tolerant strains in response to furfural and 5-hydroxymethylfurfural (HMF) supplied in a defined culture medium. To accomplish this, yeast cells will be sampled in a time-course study to isolate total RNA and conduct microarray experiments using two-color microarray with spiking universal external RNA quality controls. Inhibitor and inhibitor-conversion products, glucose consumption, ethanol production, and other byproducts generated during the fermentation process will also be monitored during the time-course study to establish metabolic profiles for wild-type and more tolerant strains involved in detoxification of biomass conversion inhibitors. Based on data from culture time-course studies, we will propose computational models to predict the behavior of the gene function and expression of natural and genetically engineered networks under furfural and HMF stress. A dynamic mathematical model using difference equations and estimate parameters will be applied and tested for its ability to describe gene regulatory network behavior. Based on these approaches, we will form testable hypotheses to explain molecular and genomic mechanisms of yeast detoxification and tolerance to furfural and HMF.
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Last Modified: 05/06/2009
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