Mechanistic modeling of a rewritable recombinase addressable data module

Many of the most important applications predicted to arise from Synthetic Biology will require engineered cellular memory with the capability to store data in a rewritable and reversible manner upon induction by transient stimuli. DNA recombination provides an ideal platform for cellular data storage and has allowed the development of a rewritable recombinase addressable data (RAD) module, capable of efficient data storage within a chromosome. Here, we develop the first detailed mechanistic model of DNA recombination, and validate it against a new set of in vitro data on recombination efficiencies across a range of different concentrations of integrase and gp3. Investigation of in vivo recombination dynamics using our model reveals the importance of fully accounting for all mechanistic features of DNA recombination in order to accurately predict the effect of different switching strategies on RAD module performance, and highlights its usefulness as a design tool for building future synthetic circuitry

Mechanistic modelling of a recombinase-based two-input temporal logic gate

Site-specific recombinases (SSRs) mediate efficient manipulation of DNA sequences in vitro and in vivo. In particular, serine integrases have been identified as highly effective tools for facilitating DNA inversion, enabling the design of genetic switches that are capable of turning the expression of a gene of interest on or off in the presence of a SSR protein. The functional scope of such circuitry can be extended to biological Boolean logic operations by incorporating two or more distinct integrase inputs. To date, mathematical modelling investigations have captured the dynamical properties of integrase logic gate systems in a purely qualitative manner, and thus such models are of limited utility as tools in the design of novel circuitry. Here, the authors develop a detailed mechanistic model of a two-input temporal logic gate circuit that can detect and encode sequences of input events. Their model demonstrates quantitative agreement with time-course data on the dynamics of the temporal logic gate, and is shown to subsequently predict dynamical responses relating to a series of induction separation intervals. The model can also be used to infer functional variations between distinct integrase inputs, and to examine the effect of reversing the roles of each integrase on logic gate output

Modeling the architecture of the regulatory system controlling methylenomycin production in Streptomyces coelicolor

The antibiotic methylenomycin A is produced naturally by Streptomyces coelicolor A3(2), a model organism for streptomycetes. This compound is of particular interest to synthetic biologists because all of the associated biosynthetic, regulatory and resistance genes are located on a single cluster on the SCP1 plasmid, making the entire module easily transferable between different bacterial strains. Understanding further the regulation and biosynthesis of the methylenomycin producing gene cluster could assist in the identification of motifs that can be exploited in synthetic regulatory systems for the rational engineering of novel natural products and antibiotics

Tracking Cell Fate with Synthetic Memory and Pulse Detecting Transcriptional Circuits

Synthetic biology aims to engineer biological systems to meet new challenges and teach us more about natural biological systems. These pursuits range from the building of relatively simple transcriptional circuits, to engineering the metabolism of an organism, to reconstructing entire genomes. While we are still emerging from the foundational stages of this new field, we are already using engineered cells to discover underlying biological mechanisms, develop new therapeutics, and produce natural products. In this dissertation, we discuss the application of synthetic biology principles to the development of memory and pulse-detecting genetic circuits. In Chapter 2, we use novel transcriptional positive-feedback based memory devices integrated in human cells to study heterogeneous responses to cellular stresses. We built doxycycline, hypoxia, and DNA damage sensing versions of the device, demonstrating its modularity. In Chapter 3, we discuss further applications of the memory device in the study of long-term responses to hypoxia, gamma radiation, and inflammation. Finally, in Chapter 4 we describe work leading to the future construction of a pulse-detecting genetic circuit integrated in the E. coli genome. The work presented here illustrates the general applicability of synthetic biology in the study of biological phenomena and brings us one step closer to achieving a more exquisite understanding and control of natural systems