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ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Commodity Utilization Research » Research » Research Project #436600

Research Project: Lipid Network Flux Cartography for Quantitative Control of Oil Accumulation and Composition

Location: Commodity Utilization Research

Project Number: 6054-41000-113-02-R
Project Type: Reimbursable Cooperative Agreement

Start Date: Oct 1, 2018
End Date: Aug 31, 2020

ARS SY, full-time technician, and part-time student will be responsible for completion of the creation of appropriate Arabidopsis plant genotypes necessary for Washington State University's (WSU) PI. WSU's planned metabolic flux analyses experiments and other genetic alterations that might improve fatty acid biosynthesis in general, and hydroxy fatty acid accumulation in particular. This will entail designed plant expression binary plasmids that contain the necessary genetic elements to knock out/knock down the RNA expression levels of targeted endogenous genes using RNAi and CRISPR/Cas9 based approaches. Also, some of these same plasmids will also contain specific castor bean genes, structured for overexpression in the seeds of transformed plants. ARS’ lab will be responsible for transforming plants with these plasmids and selecting transformed seeds for growth and analysis in future generations. ARS will share in the duties of extracting and analyzing lipids from the seeds and other tissues of these engineered plant lines, and will characterize some of castor enzymes and their reaction products by expression in other organisms (such as baker’s yeast) as necessary. ARS SY staff will also be primarily responsible for generating two-hybrid vectors and testing them for protein:protein interactions in lab strains of yeast. ARS SY will act as a mentor for WSU PI's graduate students and postdoctoral associates by assisting in training them in the necessary plant and microbial molecular techniques.

Our long term goals are to understand the control acyl fluxes through the lipid biosynthetic network into seed TAG, and use this information to develop quantitative models of lipid biosynthesis for predictive bioengineering. Here we propose a multifaceted approach to combine the power of plant genetics (mutant lines) with molecular biology (tissue-specific expression of transgenes), followed by in vivo analysis of the changes in lipid metabolism (metabolite labeling and flux analysis), and computer modeling of the plant lipid metabolic network. These hypothesis-driven systems biology approaches will allow us to address these specific objectives: Aim 1: Decipher the roles of the non-redundant diacylglycerol acyltransferase type-1 and type-2 (DGAT1 and DGAT2) TAG synthesizing enzymes in partitioning of de novo DAG into membranes or into oil production. Aim 2: Characterize the role of PC synthesis in partitioning of de novo DAG into different branches of the lipid biosynthetic network. Aim 3: Determine if a properly expressed DGAT2 can functionally complement the lethal dgat1/pdat1 knockout for TAG synthesis in pollen and other tissues required for plant viability. Aim 4: Develop quantitative kinetic models of glycerolipid fluxes in Arabidopsis.