Figure 1

Computational approach for the automated design of synthetic genome sequences. (A) Steps designed to construct the regulatory network of E. coli required to sense environmental changes. (B) A scheme of the algorithm used to re-design the E. coli TRN [17]. The wild-type genome was used as the starting point for an optimization process based on Monte Carlo Simulated Annealing. During the in silico evolution, we modified gene regulation (Figure 2) and computed the resulting genome fitness as a function combining the genome modularity and the distance between the gene expression levels of the re-engineered and wild-type genomes.