designing the optimal ethanol producing E. Coli

Christian Jungreuthmayer, Metabolism modelling group, ACIB GmbH

Fossil fuels are a restricted resource that will ultimately run out. In addition, they increase the amount of CO2 in the atmosphere. Biofuels such as ethanol and biodiesel are a promising alternative to fossil fuels. Additionally, biofuels have a positive effect on global warming, as the only produce CO2 that was absorbed by their source plants in the first place.

However, biofuels are often made from agricultural products. Hence, biofuel production competes with food production. Consequently, the production of biofuels may result in increasing food prices. Therefore, the production efficiency of biofuels needs to be increased.

We address this important issue by designing microorganisms (e.g. E. Coli) that produce bioethanol as efficient as possible. This is achieved by genetic intervention. The genes to be knocked out to create an optimal producer are numerically identified. This identification process involves the computation of elementary flux modes and determining the minimal set of genes that need to be knocked out.

In my talk I will introduce the concept of elementary flux modes and minimal knockout sets. Furthermore, I will address the difficulties in using these methods and explain two novel approaches we have recently developed to speed up and simplify the design process of optimal producers.


Short CV

Christian Jungreuthmayer studied electrical engineering at the University of Liverpool and the Vienna University of Technology. He did his PhD with Thomas Brabec at the Department of Physics of the University of Ottawa in Canada and held a Postdoc position at the Royal College of Surgeons in Ireland and the Trinity College in Dublin.

He worked for many years as software designer, project manager and researcher for Siemens Austria and Siemens South Africa. Before joining the ACIB's metabolism modelling group he had been working as scientist at the Austrian Institute of Technology (AIT). His field of activity at the ACIB is metabolic modelling using pathway analysis tools and high performance computers.