Reengineering E. coli’s Proteome for an Improved Integration of Synthetic Circuits

Nowadays, synthetic biology requires the generation of organisms in which standardized synthetic circuits can be integrated with reproducible and scalable results. To face this challenge, the idea of the design and creation of "chassis organisms" arises. The concept is based on the fact that the wild organisms that are currently employed, retain the native regulatory programs which have evolved to maximize their survival in typically variable natural environments. Consequently, even under optimum conditions, these organisms.express functions that allow them to hedge for upcoming changes. Using an ‘econometric’ approach, many studies have explained how bacterial hedging reduce fitness by the consumption of cellular resources. In consequence the global expression of useful proteins is affected.

In the present work, we exploit the current knowledge of the transcriptional regulatory network and proteome growth requirements to develop a methodology to engineer the allocation of cellular resources by reducing the expression of unneeded hedging proteome through the manipulation of the regulatory network. This methodology represents an advance in the creation of E. colichassis strains with better host-circuit interplay for an improved integration of synthetic functions.

Combining high-throughput proteomics information, regulatory network interactions and gene essentiality observations, a computational tool was developed which offers the possibility of finding the combination of genes capable of releasing a greater proteomic load in a particular condition. Some combinatorial mutants predicted by the tool were created, and later characterized in different carbon sources. By introducing a “capacity monitor", the rate of protein synthesis was measured in real time. Finally, to evaluate the predictability and performance of a synthetic circuit, a plasmid containing an inducible reporter protein was inserted. Results show that the combinatorial mutants display an increase of the growth rate in different carbon sources, along with a higher capacity to synthesize protein.