Abstract
Synthetic biology has successfully advanced our ability to design and implement complex, time-varying genetic circuits to control the expression of recombinant proteins. However, these circuits typically require the production of regulatory genes whose only purpose is to coordinate expression of other genes. When designing very small genetic constructs, such as viral genomes, we may want to avoid introducing such auxiliary gene products while nevertheless encoding complex expression dynamics. To this end, here we demonstrate that varying only the placement and strengths of promoters, terminators, and RNase cleavage sites in a computational model of a bacteriophage genome is sufficient to achieve solutions to a variety of basic gene expression patterns. We discover these genetic solutions by computationally evolving genomes to reproduce desired gene expression time-course data. Our approach shows that non-trivial patterns can be evolved, including complex patterns where the relative ordering of genes by abundance changes over time. We find that some patterns are easier to evolve than others, and comparable expression patterns can be achieved via different genetic architectures. Our work opens up a novel avenue to genome engineering via fine-tuning the balance of gene expression and gene degradation rates.
Author summary Viruses that infect bacteria, commonly called bacteriophages, typically have small genomes that encode as few as 10 genes. From the perspective of understanding genome design and regulation, these organisms are important model systems. Similar to cellular species, the genes encoded on a phage genome often must be expressed at different levels and at particular times during the phage lifecycle. Given their unique size constraints, it may be advantageous for phages to accomplish differential gene expression without having to produce a variety of dedicated regulatory molecules—which are frequently encoded on the larger and more complex genomes of free-living species. Here, we use a computational simulation of phage infection coupled with an evolutionary selection algorithm to illustrate that phage genomes can encode complex time-dependent gene expression patterns without the need for dedicated regulatory molecules. We anticipate that this simulation framework may additionally aid future phage genome design and engineering efforts.
Competing Interest Statement
The authors have declared no competing interest.
