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A Formal Path Inference of Starch Biosynthesis via Mathematical Modelling of Metabolic Changes in Excess CO2 | OMICS International | Abstract
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

A Formal Path Inference of Starch Biosynthesis via Mathematical Modelling of Metabolic Changes in Excess CO2

Treenut Saithong1,3*, Asawin Meechai2,3, Supapon Cheevadhanarak1,3,4 and Sakarindr Bhumiratana2,3,5

1School of School of Bioresources and technology, King Mongkut’s University of Technology Thonburi, Thailand

2Department of Chemical Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

3Systems Biology and Bioinformatics research group (SBI), King Mongkut’s University of Technology Thonburi, Bangkuntien Campus, Bangkok, Thailand

4Pilot Plant Development and Training Institute (PDTI), King Mongkut’s University of Technology Thonburi, Bangkuntien Campus, Bangkok, Thailand

5National Science and Technology Development Agency (NSTDA), Pathumthani, Thailand

*Corresponding Author:
Dr. Treenut Saithong
School of Bio resources and Technology
Systems Biology and Bioinformatics research group (SBI)
King Mongkut’s University of Technology Thonburi
83 Moo 8 Thakam Bankhuntein Bangkok 10150, Thailand
Tel: +66 2 470 7714
E-mail: [email protected]

Received Date: January 21, 2012; Accepted Date: March 26, 2012; Published Date: March 28, 2012

Citation: Saithong T, Meechai A, Cheevadhanarak S, Bhumiratana S (2012) A Formal Path Inference of Starch Biosynthesis via Mathematical Modelling of Metabolic Changes in Excess CO2. J Comput Sci Syst Biol 5:024-037. doi:10.4172/jcsb.1000087

Copyright: © 2012 Saithong T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Great demand for plant starch has made starch biosynthesis one of the most studied pathways in the literature. Many attempts have been made to improve the yield and properties of starch, including research on CO2 elevation as a means of increasing production; however, the analyses often faced difficulty in transiently and simultaneously measuring the metabolites of interest. Our work aimed to break-through such restrictions by systematically investigating the changes in metabolism of starch throughout the pathway-from source to sink cells-with the aid of mathematical modelling. Monitoring changes in metabolite concentrations and flux distributions allowed us to propose a formal metabolic path (i.e. a preferential pathway in charge of a particular event) responsible for starch yield variation under excess carbon-substrate. Our findings not only supported many established hypotheses on the regulations of starch production, but also gave reasonable predictions of metabolic regulation of starch biosynthesis.

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