RECONSTRUCTION OF GENOME-SCALE METABOLIC NETWORK FOR ARABIDOPSIS THALIANA

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: TERMINATED
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 0199790
• Project No.: HAW00571-H
• Project Start Date: Apr 15, 2004
• Project End Date: Sep 30, 2006

Project Director
Fu, P.

Recipient Organization
UNIV OF HAWAII
3190 MAILE WAY
HONOLULU,HI 96822

Performing Department
MOLECULAR BIOSCIENCES & BIOSYSTEMS

Non Technical Summary
The fundamental understanding of metabolism in crop plants which can only be achieved by integrated studies on plant biology using systems biology approach will aid in the design of future metabolic engineering strategies. The purpose of our study is to reconstruct the Arabidopsis metabolic network to accommodate newly generated Arabidopsis genome information with our accumulated knowledge on biochemistry, genetics and physiology in published literature to provide insight into the cellular properties of Arabidopsis thaliana.

Animal Health Component

(N/A)

Research Effort Categories

Basic

(N/A)

Applied

100%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
201	2410	1060	100%

Knowledge Area
201 - Plant Genome, Genetics, and Genetic Mechanisms;

Subject Of Investigation
2410 - Cross-commodity research--multiple crops;

Field Of Science
1060 - Biology (whole systems);

Keywords

arabidopsis thaliana

cell culture

networks

genomes

plant metabolism

mathematical models

modeling techniques

hawaii

metabolic pathways

data bases

bioinformatics

enzyme activity

plant genetics

gene products

enzyme substrates

stoichiometry

protein dna interactions

gene expression

metabolic regulation

thermodynamics

plant biochemistry

Goals / Objectives
1) Establishment of an integrated genome-pathway database for Arabidopsis. 2) Development of a metabolic modeling of plant species, in particular Arabidopsis.

Project Methods
1) Analysis of metabolic annotation from electronic databases. This step will require analysis of large quantities of genomic, metabolic, enzymatic and other data relevant to Arabidopsis metabolism. The results of such analysis will be recorded into an Excel file with the links to the original electronic databases. The pathway genome database for Arabidopsis may contain the following information: the substrates, products, and stoichiometry of each metabolic reaction, the name of the enzyme catalyzing the reaction, the genes that code for the respective enzymes (alternate names are included), the EC number of each metabolic reaction. 2) Reconstruction of the underlying network. An annotated genome will contain the specific metabolic genes found in the organism. This list of metabolic genes can be used to reconstruct the particular organism's metabolic network. The major tasks in Objective 1 are to obtain such a list of Arabidopsis genes comprising the metabolic genotype. For the metabolic modeling, we simply include all of the possible reactions which the gene products are associated with. We will also include those reactions known to occur from experimental evidence and biochemical assays, for which no associated genes have been assigned in the genome. 3) Constraints under which the reconstructed network operates. We will consider the constraints under which the reconstructed Arabidopsis metabolic network operates. These constraints are based on enzyme capacity, reaction stoichiometry and thermodynamics associated with reaction directionality and biochemical loops, etc. Particularly, the following constraints need to be made: 1) The imposition of stoichiometric constraints that represent flux balances; 2) The utilization of limited thermodynamic constraints to restrict the directional flow through enzymatic reactions; 3) The addition of physicochemical capacity constraints to account for maximum flux through individual reactions; 4) The use of kinetic constraints to further restrict what states are attainable. 4) Simulations for the Arabidopsis model correspond to physiologically meaningful states. Once the model with appropriate constraints has been developed, we will run the simulations to study the model predictions. The model predictions will be used to quantitatively describe the metabolic behavior of arabidopsis thaliana under varying genetic variation and environmental conditions. The in silico model will also be used to interpret the microarray gene expression data in the public domain for the upgrading information contents. The model will be exploited to explore the metabolic capacities; to interpret the experimental data; to simulate cell growth and desirable product production under various conditions, and to evaluate hypotheses about possible physiological effects of genetic interventions (gene knockouts or new pathway insertions). Cell culture experiment for model validation Experimental system will be set up for Arabidopsis cell cultures. The cell culture experiments will be designed to provide data to validate the genome-scale model.

Progress 04/15/04 to 09/30/06

Outputs
This project aims at genome-scale modeling of the Arabidopsis thaliana metabolism for integrated studies of plant biology using systems biology approach. Arabidopsis is considered to be a "model" plant because it is easy to grow in the lab, it has a short life cycle and makes lots of seeds (which makes it good for genetics) and it has a relatively small genome compared to other higher plants (like maize). It can be transformed, meaning it is possible to introduce genes into a plant. For all of these reasons, many people have been working on this "weed" and have made major advances in our understanding of plant biology. We have reconstructed the Arabidopsis metabolic network based on newly available Arabidopsis thaliana genome information and our accumulated knowledge on biochemistry, genetics and physiology in published literature to provide insight into the cellular properties of the plant system. The reconstruction process was initiated by downloading the gene catalog of Arabidopsis thaliana from the KEGG metabolic pathway database: (http://www.genome.ad.jp/dbget-bin/get_htext?A.thaliana.kegg). Information contained in this gene catalog was organized into pathways, such as glycolysis, pentose phosphate, or any amino acid biosynthesis pathway, etc., and was used throughout the reconstruction process. The database was organized for the ORF name, enzyme name, EC number, and SWISS PROT entry name, etc. The genome-scale modeling software FBA 4.0 (developed by Professor Bernhard Palsson in University of California, San Diego) was used to establish the genome-scale Arabidopsis thaliana model.

Impacts
The database and the genome-scale model we have established can be used by researchers of plant biology for the study of plant cell metabolism, growth and differentiation. The tools we developed can be accessed by the Arabidopsis research community upon their requests. Two graduate students have been trained by their involvement of this project. They have learned how to use bioinformatic approaches to integrate all the biological resources available to establish in silico organisms for plant research. Which will be useful for their future career.

Publications

• No publications reported this period

Progress 10/01/04 to 09/30/05

Outputs
The integrated genome-pathway database for Arabidopsis thaliana has been established using the information from online biological databases, such as The Arabidopsis Information Resource (TAIR, http://www.arabidopsis.org/), The Institute for Genomic Research (TIGR, http://www.tigr.org), and the Munich Information Center for Protein Sequences Arabidopsis Database (MIPS, http://mips.gsf.de/projects/plants/proj/thal overview.html). It consists of 5145 biochemical reactions for this plant strain. The functional annotation has been curated item-by-item. The first draft of the Arabidopsis thaliana metabolic model has been examined. Further validation will be conducted.

Impacts
The database and the genome-scale model can be used by researchers of plant biology for the study of plant cell metabolism, growth and differentiation.

Publications

• No publications reported this period

Progress 10/01/03 to 09/30/04

Outputs
The systems-level analysis on Arabidopsis requires extensive bioinformatic use of the information from genomic, proteomic, metabolomic experiments and other resources to address biological problems in this organism. We have used online biological databases, such as The Arabidopsis Information Resource (TAIR, http://www.arabidopsis.org/), The Institute for Genomic Research (TIGR, http://www.tigr.org), and the Munich Information Center for Protein Sequences Arabidopsis Database (MIPS, http://mips.gsf.de/projects/plants/proj/thal_overview.html), to establish an integrated genome-pathway database for Arabidopsis thaliana. It consists of 5145 biochemical reactions for this plant strain. The genotype-phenotype relationships will be further examined item-by-item for functional annotation.

Impacts
The database can be used by researchers of plant biology for the study of plant cell metabolism, growth and differentiation.

Publications

• No publications reported this period