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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
Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules that modify gene expression of a designated receiver cell. While

Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules that modify gene expression of a designated receiver cell. While useful, these three quorum sensing pathways exhibit a nontrivial level of crosstalk, hindering robust engineering and leading to unexpected effects in a given design. To address the lack of orthogonality among these three quorum sensing pathways, previous scientists have attempted to perform directed evolution on components of the quorum sensing pathway. While a powerful tool, directed evolution is limited by the subspace that is defined by the protein. For this reason, we take an evolutionary biology approach to identify new orthogonal quorum sensing networks and test these networks for cross-talk with currently-used networks. By charting characteristics of acyl homoserine lactone (AHL) molecules used across quorum sensing pathways in nature, we have identified favorable candidate pathways likely to display orthogonality. These include Aub, Bja, Bra, Cer, Esa, Las, Lux, Rhl, Rpa, and Sin, which we have begun constructing and testing. Our synthetic circuits express GFP in response to a quorum sensing molecule, allowing quantitative measurement of orthogonality between pairs. By determining orthogonal quorum sensing pairs, we hope to identify and adapt novel quorum sensing pathways for robust use in higher-order genetic circuits.
ContributorsMuller, Ryan (Author) / Haynes, Karmella (Thesis director) / Wang, Xiao (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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Description
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

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.
ContributorsHu, Hao (Author) / Wang, Xiao (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Current research into live-cell dynamics, particularly those relating to chromatin structure and remodeling, are limited. The tools that are used to detect state changes in chromatin, such as Chromatin Immunoprecipitation and qPCR, require that the cell be killed off. This limits the ability of researchers to pinpoint changes in live

Current research into live-cell dynamics, particularly those relating to chromatin structure and remodeling, are limited. The tools that are used to detect state changes in chromatin, such as Chromatin Immunoprecipitation and qPCR, require that the cell be killed off. This limits the ability of researchers to pinpoint changes in live cells over a longer period of time. As such, there is a need for a live-cell sensor that can detect chromatin state changes. The Chromometer is a transgenic chromatin state sensor designed to better understand human cell fate and the chromatin changes that occur. HOXD11.12, a DNA sequence that attracts repressive Polycomb group (PCG) proteins, was placed upstream of a core promoter-driven fluorescent reporter (AmCyan fluorescent protein, CFP) to link chromatin repression to a CFP signal. The transgene was stably inserted at an ectopic site in U2-OS (osteosarcoma) cells. Expression of CFP should reflect the epigenetic state at the HOXD locus, where several genes are regulated by Polycomb to control cell differentiation. U2-OS cells were transfected with the transgene and grown under selective pressure. Twelve colonies were identified as having integrated parts from the transgene into their genomes. PCR testing verified 2 cell lines that contain the complete transgene. Flow cytometry indicated mono-modal and bimodal populations in all transgenic cell colonies. Further research must be done to determine the effectiveness of this device as a sensor for live cell state change detection.
ContributorsBarclay, David (Co-author) / Simper, Jan (Co-author) / Haynes, Karmella (Thesis director) / Brafman, David (Committee member) / School of Life Sciences (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
The past decade has seen a drastic increase in collaboration between Computer Science (CS) and Molecular Biology (MB). Current foci in CS such as deep learning require very large amounts of data, and MB research can often be rapidly advanced by analysis and models from CS. One of the places

The past decade has seen a drastic increase in collaboration between Computer Science (CS) and Molecular Biology (MB). Current foci in CS such as deep learning require very large amounts of data, and MB research can often be rapidly advanced by analysis and models from CS. One of the places where CS could aid MB is during analysis of sequences to find binding sites, prediction of folding patterns of proteins. Maintenance and replication of stem-like cells is possible for long terms as well as differentiation of these cells into various tissue types. These behaviors are possible by controlling the expression of specific genes. These genes then cascade into a network effect by either promoting or repressing downstream gene expression. The expression level of all gene transcripts within a single cell can be analyzed using single cell RNA sequencing (scRNA-seq). A significant portion of noise in scRNA-seq data are results of extrinsic factors and could only be removed by customized scRNA-seq analysis pipeline. scRNA-seq experiments utilize next-gen sequencing to measure genome scale gene expression levels with single cell resolution.

Almost every step during analysis and quantification requires the use of an often empirically determined threshold, which makes quantification of noise less accurate. In addition, each research group often develops their own data analysis pipeline making it impossible to compare data from different groups. To remedy this problem a streamlined and standardized scRNA-seq data analysis and normalization protocol was designed and developed. After analyzing multiple experiments we identified the possible pipeline stages, and tools needed. Our pipeline is capable of handling data with adapters and barcodes, which was not the case with pipelines from some experiments. Our pipeline can be used to analyze single experiment scRNA-seq data and also to compare scRNA-seq data across experiments. Various processes like data gathering, file conversion, and data merging were automated in the pipeline. The main focus was to standardize and normalize single-cell RNA-seq data to minimize technical noise introduced by disparate platforms.
ContributorsBalachandran, Parithi (Author) / Wang, Xiao (Thesis advisor) / Brafman, David (Committee member) / Lockhart, Thurmon (Committee member) / Arizona State University (Publisher)
Created2017
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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
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
The human transcriptional regulatory machine utilizes hundreds of transcription factors which bind to specific genic sites resulting in either activation or repression of targeted genes. Networks comprised of nodes and edges can be constructed to model the relationships of regulators and their targets. Within these biological networks small enriched structural

The human transcriptional regulatory machine utilizes hundreds of transcription factors which bind to specific genic sites resulting in either activation or repression of targeted genes. Networks comprised of nodes and edges can be constructed to model the relationships of regulators and their targets. Within these biological networks small enriched structural patterns containing at least three nodes can be identified as potential building blocks from which a network is organized. A first iteration computational pipeline was designed to generate a disease specific gene regulatory network for motif detection using established computational tools. The first goal was to identify motifs that can express themselves in a state that results in differential patient survival in one of the 32 different cancer types studied. This study identified issues for detecting strongly correlated motifs that also effect patient survival, yielding preliminary results for possible driving cancer etiology. Second, a comparison was performed for the topology of network motifs across multiple different data types to identify possible divergence from a conserved enrichment pattern in network perturbing diseases. The topology of enriched motifs across all the datasets converged upon a single conserved pattern reported in a previous study which did not appear to diverge dependent upon the type of disease. This report highlights possible methods to improve detection of disease driving motifs that can aid in identifying possible treatment targets in cancer. Finally, networks where only minimally perturbed, suggesting that regulatory programs were run from evolved circuits into a cancer context.
ContributorsStriker, Shawn Scott (Author) / Plaisier, Christopher (Thesis advisor) / Brafman, David (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Cell fate is a complex and dynamic process with many genetic components. It has often been likened to “multistable” mathematical systems because of the numerous possible “stable” states, or cell types, that cells may end up in. Due to its complexity, understanding the process of cell fate and

Cell fate is a complex and dynamic process with many genetic components. It has often been likened to “multistable” mathematical systems because of the numerous possible “stable” states, or cell types, that cells may end up in. Due to its complexity, understanding the process of cell fate and differentiation has proven challenging. A better understanding of cell differentiation has applications in regenerative stem cell therapies, disease pathologies, and gene regulatory networks.
A variety of different genes have been associated with cell fate. For example, the Nanog/Oct-4/Sox2 network forms the core interaction of a gene network that maintains stem cell pluripotency, and Oct-4 and Sox2 also play a role in the tissue types that stem cells eventually differentiate into. Using the CRISPR/cas9 based homology independent targeted integration (HITI) method developed by Suzuki et al., we can integrate fluorescent tags behind genes with reasonable efficiency via the non-homologous end joining (NHEJ) DNA repair pathway. With human embryonic kidney (HEK) 293T cells, which can be transfected with high efficiencies, we aim to create a three-parameter reporter cell line with fluorescent tags for three different genes related to cell fate. This cell line would provide several advantages for the study of cell fate, including the ability to quantitatively measure cell state, observe expression heterogeneity among a population of genetically identical cells, and easily monitor fluctuations in expression patterns.
The project is partially complete at this time. This report discusses progress thus far, as well as the challenges faced and the future steps for completing the reporter line.
ContributorsLoveday, Tristan Andre (Author) / Wang, Xiao (Thesis director) / Brafman, David (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
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

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.
ContributorsDilly, Leon (Author) / Frow, Emma (Thesis director) / Vogel, Kathleen (Committee member) / Gillum, David (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Earth and Space Exploration (Contributor)
Created2022-05