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» Bridging Systems and Synthetic Biology for the development of improved microbial cell factories

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 to help in the understanding the governing objectives that determine a particular physiological state. In this context, an innovative methodology that integrates the concept of Elementary Flux Modes (EFMs) with Projection to Latent Structures will be applied for elucidating major metabolic routes. 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.

Team

Universidade do Minho: Eugénio C. Ferreira (PI), Manuel Mota, Isabel Rocha, Lígia Rodrigues, Ana Cristina Veloso, Anália Lourenço, Leon Kluskens, Zita Soons, Carlos Daniel Machado, Sónia Carneiro, Rafael Costa, Pedro Evangelista, Paulo Silva, Miguel Rocha (CCTC/UM)

Universidade Nova de Lisboa: Rui Oliveira, Ana Teixeira, João Dias

Universidade do Porto: Filipe Mergulhão

MIT: Bruce Tidor

The project received support form BioTrend and Biotempo companies and will run for the next three years.

Este trabalho é financiado por Fundos FEDER através do Programa Operacional Factores de Competitividade – COMPETE e por Fundos Nacionais através da FCT – Fundação para a Ciência e a Tecnologia no âmbito do projecto MIT-Pt/BS-BB/0082/2008 (FCOMP-01-0124-FEDER-008433).