433625 Kinetic Modeling of Lignin Biosynthesis in Arabidopsis thaliana for Improved Biofuel Production

Thursday, November 12, 2015: 2:10 PM
150D/E (Salt Palace Convention Center)
Rohit Jaini1, Longyun Guo2, Peng Wang2, Rachel McCoy2, Natalia Dudareva2, Clint Chapple2 and John A. Morgan1,2, (1)School of Chemical Engineering, Purdue University, West Lafayette, IN, (2)Department of Biochemistry, Purdue University, West Lafayette, IN

Kinetic Modeling of Lignin Biosynthesis in A. thaliana for Improved Biofuel Production

Rohit Jaini1*, Longyun Guo2, Peng Wang2, Rachel McCoy2, Clint Chapple2, Natalia Dudareva2, John A. Morgan1,2

1School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, 2Department of Biochemistry, Purdue University, West Lafayette, Indiana 47907

Lignin is a hetero-phenolic polymer formed as a result of radical polymerization of monolignols namely coniferyl, syringyl and p-coumaryl alcohols – products of the phenylpropanoid pathway. It imparts structural strength, vascular integrity and pathogen resistance to plants.  Although lignin is essential for plant sustenance, it renders valuable lignocellulosic biofuel feedstock recalcitrant to chemical, mechanical and biological treatment. Several attempts to manipulate lignin monomer content and composition, to improve forage digestibility and saccharification efficiency, have revealed a lack of understanding of the dynamics and regulatory properties of monolignol biosynthesis. We are developing a kinetic model to elucidate the underlying mechanisms regulating carbon flux through the phenylpropanoid network. Kinetic parameters for the model will be obtained by non-linear least squares optimization of metabolomics data from Arabidopsis thaliana stem tissue fed with [ring-13C6]-phenylalanine, the pathway precursor.

As a first step, we developed a novel and comprehensive analytical method based on liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) for quantifying intermediates of the phenylpropanoid pathway. The experimental procedure entailed extraction of metabolites from A. thaliana stem tissue using 75% (v/v) methanol in water as a solvent. The extract was then analyzed using reverse phase LC-MS/MS by electrospray ionization in the negative ion mode with multiple reaction monitoring (MRM) of two ions (Q1–parent/Q3–daughter) per compound. The chromatography method was improved by tuning for chromatographic parameters such as buffer concentration, flow rate, pH of mobile phase, and column temperature. Transgenic Arabidopsis plants with knockdown or overexpression of the ferulate 5-hydroxylase gene were utilized to validate the analytical method. Next, isotopic feeding experiments with three different concentrations (100, 300 μM & 1 mM) of [ring-13C6]-phenylalanine were conducted to obtain kinetic parameters for the entry reactions to the phenylpropanoid network, starting at phenylalanine to p-coumaroyl CoA.

The analytical method allowed detection and quantification of 12 of the 17 compounds of the pathway for which standards were available in wild type tissue. Signal suppression due to matrix effects and analyte losses during sample preparation and extraction were accounted for by standard spiking studies to accurately quantify the pathway metabolites. A set of kinetic parameters were identified that simultaneously fit fractional label and pool sizes of the endogenous intermediates obtained using the analytical method. The model showed good agreement with experimental data allowing reliable parameter estimation. Model validation was conducted using an independent data set obtained on a pal1/pal2 knockout line. Our study has laid foundation to extend the kinetic model to the entire metabolic network and shows promise as a predictive tool to facilitate rational metabolic engineering of plants for improved biofuel production.

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