Dresden 2017 – scientific programme

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BP: Fachverband Biologische Physik

BP 4: Systems Biology & Gene Expression and Signalling

BP 4.9: Talk

Monday, March 20, 2017, 17:15–17:30, ZEU 250

Designing Synthetic Networks and Experimentation in silico: A Generalized Evolutionary Algorithm Approach — •Christian Fleck — Laboratory of Systems and Synthetic Biology, Wageningen University, The Netherlands

Evolution has led to the development of biological networks that reliably respond to environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates that satisfy defined objectives. By using a schema description of model properties and employing recombination between pairs of networks, the algorithm is able to explore large regions within the search space. We show the utility of our algorithm by finding robust synthetic oscillators, and, by using multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing competing objectives. Notably, we highlight that protein dimerisation is an important aspect of oscillating networks. We go on to discuss our results in the context of understanding network evolution in nature and in the laboratory. Furthermore, we suggest how in silico evolution can aid the efficiency of directed evolution experiments for designing synthetic circuits. The use of optimisation algorithms to design robust networks should enable synthetic biologists to construct new systems that produce increasingly complex responses.