Genetic stability and costs of engineered biological constructs - Nyström, A (2017)
Synthetic Biology applies engineering principles to biology in order to formalise and facilitate the design of biological systems. Current applications of Synthetic Biology include agriculture, tissue engineering, chemical sensors, drug discovery and manufac- turing. One of the field’s primary foci is the construction of complex biological entities with predictable behaviours from sets of standardised components. However, the inser- tion of engineered biological entities causes fitness costs to their host which engenders a disadvantageous selection pressure and favours loss of function mutations. This is a key challenge to the robust engineering of biology as it reduces the construct’s genetic stability and functional lifetime. Moreover, many end goals of Synthetic Biology are applications which involve close contact with humans, other living organisms and the environment as a whole. As such, system designs need to be trusted as operating faith- fully to specification. Previous work has focussed on enhancing construct stability and lifetime by reducing the mutational frequency of engineered DNA sequences. This thesis focuses on burden and costs in order to improve the stability of engineered functions. To this aim a variety of methods are investigated, ranging from deterministic models of cellular resource allocation to stochastic evolutionary models for engineered constructs. A design model is presented for predicting and identifying burden due to unfavourable design ratios between transcription initiation rates, translation initiation and elongation efficiency. This was tested against high-throughput data from an automated experimen- tal protocol, which identified a need for improved quantification methods of burden. A dynamic resource allocation model was formulated to investigate how burden manifests during growth-phase transitions. When tested against growth data this model identified three new parameters for burden from engineered constructs: delayed signal response to a new environment; peak ribosome expression levels during growth-phase transitions; and the rate of ribosome loss during adverse growth conditions. Lastly, a stochastic evolutionary model was developed for how hosts can adapt to accommodate engineered constructs, i.e. to reduce the fitness cost while preventing function loss. The adaptive model was used to inform time cycles, population sizes and colony picking protocols that enhanced such accommodation. Favourable conditions were found to be dependent on the culture environment and engineered construct parameters.