Synthetic biology is a novel method that reengineers functional parts of natural genes of interest to build new biomolecular devices able to express as designed. There is increasing interest in synthetic biology due to wide potential applications in various fields such as clinics and fuel production. However, there are still many challenges in synthetic biology. For example, many natural biological processes are poorly understood, and these could be more thoroughly studied through model synthetic gene networks. Additionally, since synthetic biology applications may have numerous design constraints, more inducer systems should be developed to satisfy different requirements for genetic design.

This thesis covers two topics. First, I attempt to generate stochastic resonance (SR) in a biological system. Synthetic bistable systems were chosen because the inducer range in which they exhibit bistability can satisfy one of the three requirements of SR: a weak periodic force is unable to make the transition between states happen. I synthesized several different bistable systems, including toggle switches and self-activators, to select systems matching another requirement: the system has a clear threshold between the two energy states. Their bistability was verified and characterized. At the same time, I attempted to figure out the third requirement for SR – an effective noise serving as the stochastic force – through one of the most widespread toggles, the mutual inhibition toggle, in both yeast and E. coli. A mathematic model for SR was written and adjusted.

Secondly, I began work on designing a new genetic system capable of responding to pulsed magnetic fields. The operators responding to pulsed magnetic stimuli in the rpoH promoter were extracted and reorganized. Different versions of the rpoH promoter were generated and tested, and their varying responsiveness to magnetic fields was recorded. In order to improve efficiency and produce better operators, a directed evolution method was applied with the help of a CRISPR-dCas9 nicking system. The best performing promoters thus far show a five-fold difference in gene expression between trials with and without the magnetic field.

Synthetic biology is an emerging field which melds genetics, molecular biology, network theory, and mathematical systems to understand, build, and predict gene network behavior. As an engineering discipline, developing a mathematical understanding of the genetic circuits being studied is of fundamental importance. In this dissertation, mathematical concepts for understanding, predicting, and controlling gene transcriptional networks are presented and applied to two synthetic gene network contexts. First, this engineering approach is used to improve the function of the guide ribonucleic acid (gRNA)-targeted, dCas9-regulated transcriptional cascades through analysis and targeted modification of the RNA transcript. In so doing, a fluorescent guide RNA (fgRNA) is developed to more clearly observe gRNA dynamics and aid design. It is shown that through careful optimization, RNA Polymerase II (Pol II) driven gRNA transcripts can be strong enough to exhibit measurable cascading behavior, previously only shown in RNA Polymerase III (Pol III) circuits. Second, inherent gene expression noise is used to achieve precise fractional differentiation of a population. Mathematical methods are employed to predict and understand the observed behavior, and metrics for analyzing and quantifying similar differentiation kinetics are presented. Through careful mathematical analysis and simulation, coupled with experimental data, two methods for achieving ratio control are presented, with the optimal schema for any application being dependent on the noisiness of the system under study. Together, these studies push the boundaries of gene network control, with potential applications in stem cell differentiation, therapeutics, and bio-production.

Industries and research utilizing genetically-engineered organisms are often subject to strict containment requirements such as physical isolation or specialized equipment to prevent an unintended escape. A relatively new field of research looks for ways to engineer intrinsic containment techniques- genetic safeguards that prevent an organism from surviving outside of specific conditions. As interest in this field has grown over the last few decades, researchers in molecular and synthetic biology have discovered many novel ways to accomplish this containment, but the current literature faces some ambiguity and overlap in the ways they describe various biocontainment methods. Additionally, the way publications report the robustness of the techniques they test is inconsistent, making it uncertain how regulators could assess the safety and efficacy of these methods if they are eventually to be used in practical, consumer applications. This project organizes and clarifies the descriptions of these techniques within an interactive flowchart, linking to definitions and references to publications on each within an Excel table. For each reference, variables such as the containment approach, testing methods, and results reported are compiled, to illustrate the varying degrees to which these techniques are tested.

Industries and research utilizing genetically-engineered organisms are often subject to strict containment requirements such as physical isolation or specialized equipment to prevent an unintended escape. A relatively new field of research looks for ways to engineer intrinsic containment techniques- genetic safeguards that prevent an organism from surviving outside of specific conditions. As interest in this field has grown over the last few decades, researchers in molecular and synthetic biology have discovered many novel ways to accomplish this containment, but the current literature faces some ambiguity and overlap in the ways they describe various biocontainment methods. Additionally, the way publications report the robustness of the techniques they test is inconsistent, making it uncertain how regulators could assess the safety and efficacy of these methods if they are eventually to be used in practical, consumer applications. This project organizes and clarifies the descriptions of these techniques within an interactive flowchart, linking to definitions and references to publications on each within an Excel table. For each reference, variables such as the containment approach, testing methods, and results reported are compiled, to illustrate the varying degrees to which these techniques are tested.

Industries and research utilizing genetically-engineered organisms are often subject to strict containment requirements such as physical isolation or specialized equipment to prevent an unintended escape. A relatively new field of research looks for ways to engineer intrinsic containment techniques- genetic safeguards that prevent an organism from surviving outside of specific conditions. As interest in this field has grown over the last few decades, researchers in molecular and synthetic biology have discovered many novel ways to accomplish this containment, but the current literature faces some ambiguity and overlap in the ways they describe various biocontainment methods. Additionally, the way publications report the robustness of the techniques they test is inconsistent, making it uncertain how regulators could assess the safety and efficacy of these methods if they are eventually to be used in practical, consumer applications. This project organizes and clarifies the descriptions of these techniques within an interactive flowchart, linking to definitions and references to publications on each within an Excel table. For each reference, variables such as the containment approach, testing methods, and results reported are compiled, to illustrate the varying degrees to which these techniques are tested.

Industries and research utilizing genetically-engineered organisms are often subject to strict containment requirements such as physical isolation or specialized equipment to prevent an unintended escape. A relatively new field of research looks for ways to engineer intrinsic containment techniques- genetic safeguards that prevent an organism from surviving outside of specific conditions. As interest in this field has grown over the last few decades, researchers in molecular and synthetic biology have discovered many novel ways to accomplish this containment, but the current literature faces some ambiguity and overlap in the ways they describe various biocontainment methods. Additionally, the way publications report the robustness of the techniques they test is inconsistent, making it uncertain how regulators could assess the safety and efficacy of these methods if they are eventually to be used in practical, consumer applications. This project organizes and clarifies the descriptions of these techniques within an interactive flowchart, linking to definitions and references to publications on each within an Excel table. For each reference, variables such as the containment approach, testing methods, and results reported are compiled, to illustrate the varying degrees to which these techniques are tested.

Recombinases are powerful tools for genome engineering and synthetic biology, however recombinases are limited by a lack of user-programmability and often require complex directed-evolution experiments to retarget specificity. Conversely, CRISPR systems have extreme versatility yet can induce off-target mutations and karyotypic destabilization. To address these constraints we developed an RNA-guided recombinase protein by fusing a hyperactive mutant resolvase from transposon TN3 to catalytically inactive Cas9. We validated recombinase-Cas9 (rCas9) function in model eukaryote Saccharomyces cerevisiae using a chromosomally integrated fluorescent reporter. Moreover, we demonstrated cooperative targeting by CRISPR RNAs at spacings of 22 or 40bps is necessary for directing recombination. Using PCR and Sanger sequencing, we confirmed rCas9 targets DNA recombination. With further development we envision rCas9 becoming useful in the development of RNA-programmed genetic circuitry as well as high-specificity genome engineering.

Fusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than deoxyribose nucleic acid (DNA) sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones, which are bound to DNA in eukaryotic nuclei and regulate gene expression states. In 2011, Haynes et al. showed that a synthetic regulator called the Polycomb chromatin Transcription Factor (PcTF), a fusion protein that binds methylated histones, reactivated an artificially-silenced luciferase reporter gene. These synthetic transcription activators are derived from the polycomb repressive complex (PRC) and associate with the epigenetic silencing mark H3K27me3 to reactivate the expression of silenced genes. It is demonstrated here that the duration of epigenetic silencing does not perturb reactivation via PcTF fusion proteins. After 96 hours PcTF shows the strongest reactivation activity. A variant called Pc2TF, which has roughly double the affinity for H3K27me3 in vitro, reactivated the silenced luciferase gene by at least 2-fold in living cells.

Gene circuit engineering facilitates the discovery and understanding of fundamental biology and has been widely used in various biological applications. In synthetic biology, gene circuits are often constructed by two main strategies: either monocistronic or polycistronic constructions. The Latter architecture can be commonly found in prokaryotes, eukaryotes, and viruses and has been largely applied in gene circuit engineering. In this work, the effect of adjacent genes and noncoding regions are systematically investigated through the construction of batteries of gene circuits in diverse scenarios. Data-driven analysis yields a protein expression metric that strongly correlates with the features of adjacent transcriptional regions (ATRs). This novel mathematical tool helps the guide for circuit construction and has the implication for the design of synthetic ATRs to tune gene expression, illustrating its potential to facilitate engineering complex gene networks. The ability to tune RNA dynamics is greatly needed for biotech applications, including therapeutics and diagnostics. Diverse methods have been developed to tune gene expression through transcriptional or translational manipulation. Control of RNA stability/degradation is often overlooked and can be the lightweight alternative to regulate protein yields. To further extend the utility of engineered ATRs to regulate gene expression, a library of RNA modules named degradation-tuning RNAs (dtRNAs) are designed with the ability to form specific 5’ secondary structures prior to RBS. These modules can modulate transcript stability while having a minimal interference on translation initiation. Optimization of their functional structural features enables gene expression level to be tuned over a wide dynamic range. These engineered dtRNAs are capable of regulating gene circuit dynamics as well as noncoding RNA levels and can be further expanded into cell-free system for gene expression control in vitro. Finally, integrating dtRNA with synthetic toehold sensor enables improved paper-based viral diagnostics, illustrating the potential of using synthetic dtRNAs for biomedical applications.

Based upon the idea of a "science fiction prototype" as originally designed by Brian David Johnson, Salomon’s House is a science fiction novella, written to be as scientifically accurate as possible and to present a balanced account of the potential social consequences of genetic engineering. It aims to explore the answers to some core questions that have plagued scientists and philosophers alike while entertaining its readers with a punchy, character-driven narrative.