Title: Bridging Systems and Synthetic Biology for the development of improved microbial cell factories Starting Date: May 2009
Expected Completion Date: April 2012 Principal Investigator: Eugénio C. Ferreira Institutions/Research Centers involved:
IBB – Center of Biological Engineering
Univ. Minho; Department of Chemical Engineering
Univ. Porto; Instituto de Biologia Experimental e Tecnológica (IBET) Companies involved: Biotrend, SA; Biotempo, Lda URL: http://biopseg.deb.uminho.pt/MIT-Project Keywords: Systems Biology, Synthetic Biology, Industrial Biotechnology Abstract: This project aims to develop and apply systems and synthetic biology tools for improving microbial cell factories for the production of amino acids. These compounds represent interesting case-studies for metabolic engineering, because they have been increasingly used as supplements for human food and animal feed with a special emphasis on L-glutamic acid and L-lysine. Moreover, they are good representatives of the success of Industrial Biotechnology; a few years ago only a small number were produced by bioprocesses, while nowadays almost all 20 natural L-amino acids are produced by fermentation or enzyme technologies.
The microorganism to be used is the bacterium Escherichia coli, for which sufficient knowledge has been accumulated in recent years to perform these tasks and also because this organism is able to produce naturally all the 20 amino acids from inorganic nitrogen sources.
The main tasks of the project encompass the entire cycle of metabolic engineering and are guided by advanced approaches from Systems and Synthetic Biology approaches.
The cycle of the project starts with the construction of improved mathematical models representing both metabolic and regulatory processes from different data sources and using state-of-the-art bioinformatics tools. Experiments on wild-type E. coli strains will be performed to adjust and validate the developed models and the refined model will then be used to predict in silico molecular targets for knockouts, gene addition and under/overexpression using advanced optimization algorithms developed in-house. These strategies will then be directly implemented in E. coli or further analyzed and advanced using Synthetic Biology approaches to program or enhance gene expression before implementation. Overall objectives: The primary goal of this project is to develop and apply systems and synthetic biology tools for improving E. coli microbial cell factories for the production of amino acids.
The overall project is organized into six tasks: - To construct a more reliable mathematical model and better simulation tools for an accurate prediction of E. coli phenotypes under different environmental and genetic conditions.
- To collect appropriate high-throughput experimental data measuring fluxomics, metabolomics and transcriptomics for the purpose of model improvement and validation.
- To apply advanced algorithms based on the concept of EFMs in order to elucidate major metabolic routes used under different environmental conditions
- To develop and apply mathematical and computational tools for identifying metabolic engineering targets
- To design Synthetic Biology strategies for programming gene expression in response to intracellular metabolic states
- To implement selected metabolic engineering and synthetic biology approaches in order to obtain in vivo improved microbial cell factories.
Highlights to date: The main output so far of this project is the open-source OptFlux Software tool (www.optflux.org). The software aims at allowing researchers both from industry and academia to simulate, in a user-friendly way, the behavior of industrially important microorganisms under a variety of conditions and also indicates which genetic modifications may lead to enhanced strains for a particular application. Therefore, the platform expedites research by decreasing significantly the number of experiments that have to be performed to achieve a better biotech industrial process. The article, "OptFlux: an open-source software platform for in silico metabolic engineering," (by Isabel Rocha, Paulo Maia, Pedro Evangelista, Paulo Vilaça, Simão Soares , José P. Pinto, Jens Nielsen, Kiran R. Patil, Eugénio C. Ferreira, and Miguel Rocha) was distinguished as the most-viewed article of the month in April 2010 by the journal BMC Systems Biology. Portuguese Institutional Research Members: CEB/IBB-UMinho: Eugénio Ferreira, Isabel Rocha, Manuel Mota, Lígia Rodrigues, Anália Lourenço, Leonardus Kluskens CCTC-UMinho: Miguel Rocha (20%) FEUP: Filipe Mergulhão IBET: Rui Oliveira
MIT Research Member: Bruce Tidor
MPP PhD/Master Students: Daniel Machado (PhD thesis: Novel modelling formalisms and simulation tools in Computational Biosystems), Paulo Maia (PhD thesis: Metabolic Control Analysis as a Framework for Strain Optimization) and Pedro Evangelista (PhD thesis on Computational Systems Biology)
Other Portuguese Researchers (PhD, Master, Post-Docs) in collaboration:
CEB/IBB-UMinho: Zita Soons, Sónia Carneiro, Rafael Costa, Ana Veloso IBET: Ana Teixeira, Rui Dias Publications: Rocha, I., Maia, P., Evangelista, P., Vilaça, P., Soares, S., Pinto, J.P., Nielsen, J., Patil, K.R., Ferreira, E.C., Rocha, M. OptFlux: an open-source software platform for in silico metabolic engineering. BMC Systems Biology 4:45, 2010.
Costa, R.S., Machado, D., Rocha, I., Ferreira, E.C. Hybrid dynamic modeling of E. coli central metabolic network combining Michaelis-Menten and approximate kinetic equations. Biosystems 100(2), 150-157, 2010.
Costa, R.S., Machado, D., Rocha, I., Ferreira, E.C. Reconstruction of dynamic metabolic networks: challenges, limitations and alternative solutions. Jornadas de Bioinformática 2009, Lisboa 3-6 de Novembro de 2009, pp. 51-55.
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