Matching Items (16)
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- All Subjects: Synthetic Biology
- Creators: Wang, Xiao
- Creators: Chaput, John C
- Creators: Green, Alexander
- Member of: ASU Electronic Theses and Dissertations
Description
Synthetic biology is constantly evolving as new ideas are incorporated into this increasingly flexible field. It incorporates the engineering of life with standard genetic parts and methods; new organisms with new genomes; expansion of life to include new components, capabilities, and chemistries; and even completely synthetic organisms that mimic life while being composed of non-living matter. We have introduced a new paradigm of synthetic biology that melds the methods of in vitro evolution with the goals and philosophy of synthetic biology. The Family B proteins represent the first de novo evolved natively folded proteins to be developed with increasingly powerful tools of molecular evolution. These proteins are folded and functional, composed of the 20 canonical amino acids, and in many ways resemble natural proteins. However, their evolutionary history is quite different from natural proteins, as it did not involve a cellular environment. In this study, we examine the properties of DX, one of the Family B proteins that have been evolutionarily optimized for folding stability. Described in chapter 2 is an investigation into the primitive catalytic properties of DX, which seems to have evolved a serendipitous ATPase activity in addition to its selected ATP binding activity. In chapters 3 and 4 we express the DX gene in E. coli cells and observe massive changes in cell morphology, biochemistry, and life cycle. Exposure to DX activates several defense systems in E. coli, including filamentation, cytoplasmic segregation, and reversion to a viable but non-culturable state. We examined these phenotypes in detail and present a model that accounts for how DX causes such a rearrangement of the cell.
ContributorsStomel, Joshua (Author) / Chaput, John C (Thesis advisor) / Korch, Shaleen (Committee member) / Roberson, Robert (Committee member) / Ghirlanda, Gionvanna (Committee member) / Arizona State University (Publisher)
Created2011
Description
The principle of Darwinian evolution has been applied in the laboratory to nucleic acid molecules since 1990, and led to the emergence of in vitro evolution technique. The methodology of in vitro evolution surveys a large number of different molecules simultaneously for a pre-defined chemical property, and enrich for molecules with the particular property. DNA and RNA sequences with versatile functions have been identified by in vitro selection experiments, but many basic questions remain to be answered about how these molecules achieve their functions. This dissertation first focuses on addressing a fundamental question regarding the molecular recognition properties of in vitro selected DNA sequences, namely whether negatively charged DNA sequences can be evolved to bind alkaline proteins with high specificity. We showed that DNA binders could be made, through carefully designed stringent in vitro selection, to discriminate different alkaline proteins. The focus of this dissertation is then shifted to in vitro evolution of an artificial genetic polymer called threose nucleic acid (TNA). TNA has been considered a potential RNA progenitor during early evolution of life on Earth. However, further experimental evidence to support TNA as a primordial genetic material is lacking. In this dissertation we demonstrated the capacity of TNA to form stable tertiary structure with specific ligand binding property, which suggests a possible role of TNA as a pre-RNA genetic polymer. Additionally, we discussed the challenges in in vitro evolution for TNA enzymes and developed the necessary methodology for future TNA enzyme evolution.
ContributorsYu, Hanyang (Author) / Chaput, John C (Thesis advisor) / Chen, Julian (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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 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
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 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
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 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
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 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
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, 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
Description
The fundamental building blocks for constructing complex synthetic gene networks are effective biological parts with wide dynamic range, low crosstalk, and modularity. RNA-based components are promising sources of such parts since they can provide regulation at the level of transcription and translation and their predictable base pairing properties enable large libraries to be generated through in silico design. This dissertation studies two different approaches for initiating interactions between RNA molecules to implement RNA-based components that achieve translational regulation. First, single-stranded domains known as toeholds were employed for detection of the highly prevalent foodborne pathogen norovirus. Toehold switch riboregulators activated by trigger RNAs from the norovirus RNA genome are designed, validated, and coupled with paper-based cell-free transcription-translation systems. Integration of paper-based reactions with synbody enrichment and isothermal RNA amplification enables as few as 160 copies/mL of norovirus from clinical samples to be detected in reactions that do not require sophisticated equipment and can be read directly by eye. Second, a new type of riboregulator that initiates RNA-RNA interactions through the loop portions of RNA stem-loop structures was developed. These loop-initiated RNA activators (LIRAs) provide multiple advantages compared to toehold-based riboregulators, exhibiting ultralow signal leakage in vivo, lacking any trigger RNA sequence constraints, and appending no additional residues to the output protein. Harnessing LIRAs as modular parts, logic gates that exploit loop-mediated control of mRNA folding state to implement AND and OR operations with up to three sequence-independent input RNAs were constructed. LIRA circuits can also be ported to paper-based cell-free reactions to implement portable systems with molecular computing and sensing capabilities. LIRAs can detect RNAs from a variety of different pathogens, such as HIV, Zika, dengue, yellow fever, and norovirus, and after coupling to isothermal amplification reactions, provide visible test results down to concentrations of 20 aM (12 RNA copies/µL). And the logic functionality of LIRA circuits can be used to specifically identify different HIV strains and influenza A subtypes. These findings demonstrate that toehold- and loop-mediated RNA-RNA interactions are both powerful strategies for implementing RNA-based computing systems for intracellular and diagnostic applications.
ContributorsMA, DUO (Author) / Green, Alexander (Thesis advisor) / Mangone, Marco (Committee member) / Liu, Yan (Committee member) / Arizona State University (Publisher)
Created2019
Description
Advances in chemical synthesis have enabled new lines of research with unnatural genetic polymers whose modified bases or sugar-phosphate backbones have potential therapeutic and biotechnological applications. Maximizing the potential of these synthetic genetic systems requires inventing new molecular biology tools that can both generate and faithfully replicate unnatural polymers of significant length. Threose nucleic acid (TNA) has received significant attention as a complete replication system has been developed by engineering natural polymerases to broaden their substrate specificity. The system, however, suffers from a high mutational load reducing its utility. This thesis will cover the development of two new polymerases capable of transcribing and reverse transcribing TNA polymers with high efficiency and fidelity. The polymerases are identified using a new strategy wherein gain-of-function mutations are sampled in homologous protein architectures leading to subtle optimization of protein function. The new replication system has a fidelity that supports the propagation of genetic information enabling in vitro selection of functional TNA molecules. TNA aptamers to human alpha-thrombin are identified and demonstrated to have superior stability compared to DNA and RNA in biologically relevant conditions. This is the first demonstration that functional TNA molecules have potential in biotechnology and molecular medicine.
ContributorsDunn, Matthew Ryan (Author) / Chaput, John C (Thesis advisor) / LaBaer, Joshua (Committee member) / Lake, Douglas (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2015