The Metacode Project

Code-engineered new-to-nature microbial cell factories for novel and safety-enhanced bio-production

 

The Metacode consortium gathers forces from 8 partner organizations (including academia and SMEs) under the coordination of Prof. Dr. Nediljko Budisa (Berlin Institute of Technology/TU Berlin). It is supported by the European Union as a Collaborative Project in the Work Program KBBE.2011.3.6-04.

Objectives

METACODE will demonstrate the power of orthogonalization as a biosystems engineering strategy. It will solve industrially relevant bio-production problems, such as peptide and protein production beyond the canonical set of the 20 proteinogenic amino acids. Furthemore, it will expand the arsenal of biologically available chemical reactions. While the first opportunity has strong impact on pharmaceutical applications, the latter is essential to the transition of a chemical to a biochemical industry at the heart of the Knowledge-Based BioEconomy (KBBE).

Motivations

Current cell engineering efforts, despite the numerous notable successes, are fundamentally hampered by the complexity of biological systems which makes it nearly impossible to perform truly rational systems design. The analytic arsenal of systems biology has tremendously advanced our ability to deduce interactions in cells.  However, this knowledge still has to be translated into our ability to reliably construct systems capable of performing novel synthetic tasks (as opposed to doing naturally present syntheses better) and designing systems beyond the current part-by-part engineering.

Here, biological engineering faces a fundamental obstacle that more classical engineering disciplines like mechanical or electrical engineering have solved long ago - orthogonality. In matured engineering disciplines it is possible to add parts to a system without creating or propagating side effects. This way, even large systems containing huge numbers of single parts can be designed and actually operated successfully.

The notion of orthogonality is somewhat at odds with the canonical research focus in biology, where more effort is put on the detection and unraveling of more and more intricate networks of interactions. Synthetic biology aims at reversing this view and implies that system simplification might actually be at the heart of implementing a reliable and robust bioengineering. The prime route to this simplification goes through orthogonalization of biosystems to limit unpredictable interactions.