As one of best characterized and well studied bacteria, Escherichia coli has been the workhorse and model organism for biochemical, genetic and metabolic engineering researches. Since last ten years, spurred by the availability of its genome-scale in silico model [1], the research on this microbe has been further advanced within the context of systems biotechnology [2]. A multitude of applications demonstrating the predictive power of the model can be found at http://gcrg.ucsd.edu/In_Silico_Organisms/E_coli/E_coli_others. Currently, several software tools are also available for facilitating the quantitative analysis, thus allowing non-expert users to conduct in silico analysis [3]. However, none of them adopted a platform-independent web-based approach that is a new direction in software development with several advantages in terms of accessibility, software updates and computational capabilities [4]. In this study, we present a web application for in silico designing, analyzing and engineering E. coli systems. It is devised and implemented using the three-tier architecture in conjunction with emerging AJAX (Asynchronous JavaScript and XML) and Java Web Start technologies, thereby leading to tremendous increase in its usability and dynamic web accessibility. As a main feature, the present system provides a user-friendly rich web interface. It allows users to virtually create and synthesize mutant strains derived from the genome-scale wildtype E. coli model and to customize pathways of interest via a graph editor. In addition, constraints-based flux analysis can be conducted for predicting metabolic fluxes and charactering the physiological states under various genetic and/or environmental conditions in a comparative way. The usefulness and functionality of the system are demonstrated by applying to E. coli DH5α strain that was grown in 2-L batch culture provided with complex nutrient media [5]. Based on the consumption and production rates of measurable metabolites, flux analysis of virtually created E. coli DH5α mutant under the web-based environment was implemented to explore the relationship among various media components in external complex media and the internal metabolic fluxes. As a result, in silico analysis revealed that the cell utilized biosynthetic precursors for the cellular growth directly from the complex media through anabolic pathways. This indicated that the cell in complex media could be functioning in energetically more efficient manner, reducing the need to produce amino acids and saving required energy.
Acknowledgment:
This work was partially supported by the Academic Research Fund (R-279-000-258-112) from the National University of Singapore.
References:
[1] Reed, J.L., Vo, T.D., Schilling, C.H. and Palsson, B.O. 2003. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol. 4(9): R54.1-R54.12.
[2] Lee, S.Y., Lee, D.-Y. and Kim, T.Y. 2005. Systems biotechnology for strain improvement. Trends Biotechnol. 23: 349-358.
[3] Lee, D.-Y., Yun, H., Park, S. and Lee, S.Y. 2003. MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis. Bioinformatics 19: 2144-2146.
[4] Lee, D.-Y., Saha, R., Yusufi, F. N. K., Park, W. and Karimi, I. A. 2008. Web-based applications for building, managing and analyzing kinetic models of biological systems. submitted.
[5] Selvarasu, S., Ow, D. S.-W., Lee, S. Y., Lee, M. M., Oh, S. K.-W., Karimi, I. A. and Lee, D.-Y. 2008. Characterizing Escherichia coli DH5α growth and metabolism in complex media using genome-scale flux analysis. submitted.