Measurement and analysis of expression costs of synthetic genetic circuits

Summary :

As the size and complexity of synthetic genetic circuits increase, they progressively become too burdensome for a single cell.  Consequently, many toy-model genetic circuits are easily lost to negative selection when the engineered organisms are exposed to more stressful environments. By contrast, natural systems are able to carry much larger programs by using complex regulatory mechanisms to keep the costs of expression in check. They do this by a combination of temporal control over gene expression and spatial distribution of functions in multicellular systems. In this work, we will develop experimental and theoretical methods to measure the cost of maintaining and executing synthetic genetic circuits inside cells. Quantitative models will be used to choose the most economical design architectures (with the least resource competition) for implementation of a genetic circuit with a specific function. The circuit designs will be studied under different growth and stress conditions to assess the relationship between the calculated costs and the long-term evolutionary stability of the circuits. These analyses will help inform decisions on the upper size-limit of circuits at which it would be more efficient to distribute them across multiple cells in a community. We expect the results of this work to have key implications not only for the scale-up of synthetic genetic circuits but also for the understanding of ecosystem functions in microbial communities and division of labour in multicellular organisms.

Contact :

• Maud Hofmann
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