Publications (2)6.58 Total impact
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Article: Exploring the effects of carbon sources on the metabolic capacity for shikimic acid production in Escherichia coli using in silico metabolic predictions.
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ABSTRACT: Effects of various industrially important carbon sources (glucose, sucrose, xylose, gluconate, and glycerol) on shikimic acid (SA) biosynthesis in Escherichia coli were investigated to gain new insight into the metabolic capability for overproducing SA. At the outset, constraints-based flux analysis using the genome-scale in silico model of E. coli was conducted to quantify the theoretical maximum SA yield. The corresponding flux distributions fueled by different carbon sources under investigation were compared with respect to theoretical yield and energy utilization, thereby identifying the indispensable pathways for achieving optimal SA production on each carbon source. Subsequently, a shikimate-kinase-deficient E. coli mutant was developed by blocking the aromatic amino acid pathway, and the production of SA on various carbon sources was experimentally examined during 5 l batch culture. As a result, the highest production rate, 1.92 mmol SA/h, was obtained when glucose was utilized as a carbon source, whereas the efficient SA production from glycerol was obtained with the highest yield, 0.21 mol SA formed per mol carbon atom of carbon source consumed. The current strain can be further improved to satisfy the theoretically achievable SA production that was predicted by in silico analysis.Journal of Microbiology and Biotechnology 12/2008; 18(11):1773-84. · 1.38 Impact Factor -
Article: Web-based applications for building, managing and analysing kinetic models of biological systems.
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ABSTRACT: Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.Briefings in Bioinformatics 10/2008; 10(1):65-74. · 5.20 Impact Factor
