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Description
The portability of genetic tools from one organism to another is a cornerstone of synthetic biology. The shared biological language of DNA-to-RNA-to-protein allows for expression of polypeptide chains in phylogenetically distant organisms with little modification. The tools and contexts are diverse, ranging from catalytic RNAs in cell-free systems to bacterial

The portability of genetic tools from one organism to another is a cornerstone of synthetic biology. The shared biological language of DNA-to-RNA-to-protein allows for expression of polypeptide chains in phylogenetically distant organisms with little modification. The tools and contexts are diverse, ranging from catalytic RNAs in cell-free systems to bacterial proteins expressed in human cell lines, yet they exhibit an organizing principle: that genes and proteins may be treated as modular units that can be moved from their native organism to a novel one. However, protein behavior is always unpredictable; drop-in functionality is not guaranteed.

My work characterizes how two different classes of tools behave in new contexts and explores methods to improve their functionality: 1. CRISPR/Cas9 in human cells and 2. quorum sensing networks in Escherichia coli.

1. The genome-editing tool CRISPR/Cas9 has facilitated easily targeted, effective, high throughput genome editing. However, Cas9 is a bacterially derived protein and its behavior in the complex microenvironment of the eukaryotic nucleus is not well understood. Using transgenic human cell lines, I found that gene-silencing heterochromatin impacts Cas9’s ability to bind and cut DNA in a site-specific manner and I investigated ways to improve CRISPR/Cas9 function in heterochromatin.

2. Bacteria use quorum sensing to monitor population density and regulate group behaviors such as virulence, motility, and biofilm formation. Homoserine lactone (HSL) quorum sensing networks are of particular interest to synthetic biologists because they can function as “wires” to connect multiple genetic circuits. However, only four of these networks have been widely implemented in engineered systems. I selected ten quorum sensing networks based on their HSL production profiles and confirmed their functionality in E. coli, significantly expanding the quorum sensing toolset available to synthetic biologists.
ContributorsDaer, René (Author) / Haynes, Karmella (Thesis advisor) / Brafman, David (Committee member) / Nielsen, David (Committee member) / Kiani, Samira (Committee member) / Arizona State University (Publisher)
Created2017
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Description
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,

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.
ContributorsMenn, David J (Author) / Wang, Xiao (Thesis advisor) / Kiani, Samira (Committee member) / Haynes, Karmella (Committee member) / Nielsen, David (Committee member) / Marshall, Pamela (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Synthetic manipulation of chromatin dynamics has applications for medicine, agriculture, and biotechnology. However, progress in this area requires the identification of design rules for engineering chromatin systems. In this thesis, I discuss research that has elucidated the intrinsic properties of histone binding proteins (HBP), and apply this knowledge to engineer

Synthetic manipulation of chromatin dynamics has applications for medicine, agriculture, and biotechnology. However, progress in this area requires the identification of design rules for engineering chromatin systems. In this thesis, I discuss research that has elucidated the intrinsic properties of histone binding proteins (HBP), and apply this knowledge to engineer novel chromatin binding effectors. Results from the experiments described herein demonstrate that the histone binding domain from chromobox protein homolog 8 (CBX8) is portable and can be customized to alter its endogenous function. First, I developed an assay to identify engineered fusion proteins that bind histone post translational modifications (PTMs) in vitro and regulate genes near the same histone PTMs in living cells. This assay will be useful for assaying the function of synthetic histone PTM-binding actuators and probes. Next, I investigated the activity of a novel, dual histone PTM binding domain regulator called Pc2TF. I characterized Pc2TF in vitro and in cells and show it has enhanced binding and transcriptional activation compared to a single binding domain fusion called Polycomb Transcription Factor (PcTF). These results indicate that valency can be used to tune the activity of synthetic histone-binding transcriptional regulators. Then, I report the delivery of PcTF fused to a cell penetrating peptide (CPP) TAT, called CP-PcTF. I treated 2D U-2 OS bone cancer cells with CP-PcTF, followed by RNA sequencing to identify genes regulated by CP-PcTF. I also showed that 3D spheroids treated with CP-PcTF show delayed growth. This preliminary work demonstrated that an epigenetic effector fused to a CPP can enable entry and regulation of genes in U-2 OS cells through DNA independent interactions. Finally, I described and validated a new screening method that combines the versatility of in vitro transcription and translation (IVTT) expressed protein coupled with the histone tail microarrays. Using Pc2TF as an example, I demonstrated that this assay is capable of determining binding and specificity of a synthetic HBP. I conclude by outlining future work toward engineering HBPs using techniques such as directed evolution and rational design. In conclusion, this work outlines a foundation to engineer and deliver synthetic chromatin effectors.
ContributorsTekel, Stefan (Author) / Haynes, Karmella (Thesis advisor) / Mills, Jeremy (Committee member) / Caplan, Michael (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Over the past 20 years, the fields of synthetic biology and synthetic biosystems engineering have grown into mature disciplines, leading to significant breakthroughs in cancer research, diagnostics, cell-based medicines, biochemical production, etc. Application of mathematical modelling to biological and biochemical systems have not only given great insight into how these

Over the past 20 years, the fields of synthetic biology and synthetic biosystems engineering have grown into mature disciplines, leading to significant breakthroughs in cancer research, diagnostics, cell-based medicines, biochemical production, etc. Application of mathematical modelling to biological and biochemical systems have not only given great insight into how these systems function, but also have lent enough predictive power to aid in the forward-engineering of synthetic constructs. However, progress has been impeded by several modes of context-dependence unique to biological and biochemical systems that are not seen in traditional engineering disciplines, resulting in the need for lengthy design-build-test cycles before functional prototypes are generated.In this work, two of these universal modes of context dependence – resource competition and growth feedback –their effects on synthetic gene circuits and potential control mechanisms, are studied and characterized. Results demonstrate that a novel competitive control architecture can be utilized to mitigate the effects of winner-take-all resource competition (a form of context dependence where distinct gene modules influence each other by competing over a shared pool of transcriptional/translational resources) in synthetic gene circuits and restore circuits to their intended function. Application of the fluctuation-dissipation theorem and rigorous stochastic simulations demonstrate that realistic resource constraints present in cells at the transcriptional and translational levels influence noise in gene circuits in a nonmonotonic fashion, either increasing or decreasing noise depending on the transcriptional/translational capacity. Growth feedback on the other hand links circuit function to cellular growth rate via increased protein dilution rate during exponential growth phase. This in turn can result in the collapse of bistable gene circuits as the accelerated dilution rate forces switches in a high stable state to fall to a low stable state. Mathematical modelling and experimental data demonstrate that application of repressive links can insulate sensitive parts of gene circuits against growth-fluctuations and can in turn increase the robustness of multistable circuits in growth contexts. The results presented in this work aid in the accumulation of understanding of biological and biochemical context dependence, and corresponding control strategies and design principles engineers can utilize to mitigate these effects.
ContributorsStone, Austin (Author) / Tian, Xiao-jun (Thesis advisor) / Wang, Xiao (Committee member) / Smith, Barbara (Committee member) / Kuang, Yang (Committee member) / Cheng, Albert (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Clustered regularly interspace short palindromic repeats (CRISPR) and CRISPR associated (Cas) technologies have become integral to genome editing. Canonical CRISPR-Cas9 systems function as a ribonucleic acid (RNA)-guided nucleases. Single guide RNAs (sgRNA) can be easily designed to target Cas9’s nuclease activity towards protospacer deoxyribonucleic acid (DNA) sequences. The relatively ease

Clustered regularly interspace short palindromic repeats (CRISPR) and CRISPR associated (Cas) technologies have become integral to genome editing. Canonical CRISPR-Cas9 systems function as a ribonucleic acid (RNA)-guided nucleases. Single guide RNAs (sgRNA) can be easily designed to target Cas9’s nuclease activity towards protospacer deoxyribonucleic acid (DNA) sequences. The relatively ease and efficiency of CRISPR-Cas9 systems has enabled numerous technologies and DNA manipulations. Genome engineering in human cell lines is centered around the study of genetic contribution to disease phenotypes. However, canonical CRISPR-Cas9 systems are largely reliant on double stranded DNA breaks (DSBs). DSBs can induce unintended genomic changes including deletions and complex rearrangements. Likewise, DSBs can induce apoptosis and cell cycle arrest confounding applications of Cas9-based systems for disease modeling. Base editors are a novel class of nicking Cas9 engineered with a cytidine or adenosine deaminase. Base editors can install single letter DNA edits without DSBs. However, detecting single letter DNA edits is cumbersome, requiring onerous DNA isolation and sequencing, hampering experimental throughput. This document describes the creation of a fluorescent reporter system to detect Cytosine-to-Thymine (C-to-T) base editing. The fluorescent reporter utilizes an engineered blue fluorescent protein (BFP) that is converted to green fluorescent protein (GFP) upon targeted C-to-T conversion. The BFP-to-GFP conversion enables the creation of a strategy to isolate edited cell populations, termed Transient Reporter for Editing Enrichment (TREE). TREE increases the ease of optimizing base editor designs and assists in editing cell types recalcitrant to DNA editing. More recently, Prime editing has been demonstrated to introduce user defined DNA edits without the need for DSBs and donor DNA. Prime editing requires specialized prime editing guide RNAs (pegRNAs). pegRNAs are however difficult to manually design. This document describes the creation of a software tool: Prime Induced Nucleotide Engineering Creator of New Edits (PINE-CONE). PINE-CONE rapidly designs pegRNAs based off basic edit information and will assist with synthetic biology and biomedical research.
ContributorsStandage-Beier, Kylie S (Author) / Wang, Xiao (Thesis advisor) / Brafman, David A (Committee member) / Tian, Xiao-jun (Committee member) / Nielsen, David R (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Ecology has been an actively studied topic recently, along with the rapid development of human microbiota-based technology. Scientists have made remarkable progress using bioinformatics tools to identify species and analyze composition. However, a thorough understanding of interspecies interactions of microbial ecosystems is still lacking, which has been a significant obstacle

Ecology has been an actively studied topic recently, along with the rapid development of human microbiota-based technology. Scientists have made remarkable progress using bioinformatics tools to identify species and analyze composition. However, a thorough understanding of interspecies interactions of microbial ecosystems is still lacking, which has been a significant obstacle in the further development of related technologies. In this work, a genetic circuit design principle with synthetic biology approaches is developed to form two-strain microbial consortia with different inter-strain interactions. The microbial systems are well-defined and inducible. Co-culture experiment results show that our microbial consortia behave consistently with previous ecological knowledge and thus serves as excellent model systems to simulate ecosystems with similar interactions. Colony patterns also emerge when co-culturing multiple species on solid media. With the engineered microbial consortia, image-processing based methods were developed to quantify the shape of co-culture colonies and distinguish microbial consortia with different interactions. Factors that affect the population ratios were identified through induction and variations in the inoculation process. Further time-lapse experiments revealed the basic rules of colony growth, composition variation, patterning, and how spatial factors impact the co-culture colony.
ContributorsChen, Xingwen (Author) / Wang, Xiao (Thesis advisor) / Kuang, Yang (Committee member) / Tian, Xiaojun (Committee member) / Brafman, David (Committee member) / Plaisier, Christopher (Committee member) / Arizona State University (Publisher)
Created2022
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Description
The mutual inhibition between synthetic gene circuits and cell growth produces growth feedback in the host-circuit system. Previous studies have demonstrated that the growth feedback has an marked impact on the molecular dynamics of the host-circuit system. However, the complexity of the growth feedback effect is not fully understood. A

The mutual inhibition between synthetic gene circuits and cell growth produces growth feedback in the host-circuit system. Previous studies have demonstrated that the growth feedback has an marked impact on the molecular dynamics of the host-circuit system. However, the complexity of the growth feedback effect is not fully understood. A theoretical framework was developed to study the dynamics of the coupling between growth feedback and synthetic gene circuits. The study’s results reveal three major points about the impact of growth feedback. First, a nonlinear emergent behavior mediated by growth feedback. The unexpected behavior depends on the dynamic ribosome allocation between gene circuit expression and host cell growth. Second, the emergence and loss of unexpected qualitative states on the host-circuit system generated by ultrasensitive growth feedback. Third, the growth feedback-induced cooperativity behavior in synthetic gene modules competing for resources. In addition, growth feedback attenuated the winner-takes-all rules on resource competition between the two self-activating modules. These results demonstrate that growth feedback plays an important role in the host-circuit system’s molecular dynamics. Characterizing general principles from the effect of growth facilitates the ability to minimize or even harness unexpected gene expression behaviors derived from the effect of growth feedback.
ContributorsMelendez-Alvarez, Juan Ramon (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Kuang, Yang (Committee member) / Arizona State University (Publisher)
Created2022
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Description
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

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.
ContributorsZhang, Qi (Author) / Wang, Xiao (Thesis advisor) / Green, Alexander (Committee member) / Brafman, David (Committee member) / Tian, Xiaojun (Committee member) / Plaisier, Christopher (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more

Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more timely and underexplored problems. In SB's entire history, mathematical modeling has always been an indispensable approach to predict the experimental outcomes, improve experimental design and obtain mechanism-understanding of the biological systems. \textit{Escherichia coli} (\textit{E. coli}) is one of the most important experimental platforms, its growth dynamics is the major research objective in this dissertation. Chapter 2 employs a reaction-diffusion model to predict the \textit{E. coli} colony growth on a semi-solid agar plate under multiple controls. In that chapter, a density-dependent diffusion model with non-monotonic growth to capture the colony's non-linear growth profile is introduced. Findings of the new model to experimental data are compared and contrasted with those from other proposed models. In addition, the cross-sectional profile of the colony are computed and compared with experimental data. \textit{E. coli} colony is also used to perform spatial patterns driven by designed gene circuits. In Chapter 3, a gene circuit (MINPAC) and its corresponding pattern formation results are presented. Specifically, a series of partial differential equation (PDE) models are developed to describe the pattern formation driven by the MINPAC circuit. Model simulations of the patterns based on different experimental conditions and numerical analysis of the models to obtain a deeper understanding of the mechanisms are performed and discussed. Mathematical analysis of the simplified models, including traveling wave analysis and local stability analysis, is also presented and used to explore the control strategies of the pattern formation. The interaction between the gene circuit and the host \textit{E. coli} may be crucial and even greatly affect the experimental outcomes. Chapter 4 focuses on the growth feedback between the circuit and the host cell under different nutrient conditions. Two ordinary differential equation (ODE) models are developed to describe such feedback with nutrient variation. Preliminary results on data fitting using both two models and the model dynamical analysis are included.
ContributorsHe, Changhan (Author) / Kuang, Yang (Thesis advisor) / Wang, Xiao (Committee member) / Kostelich, Eric (Committee member) / Tian, Xiaojun (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2021