Matching Items (10)
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- All Subjects: Synthetic Biology
- Creators: Nielsen, David
- Creators: Kuang, Yang
- Status: Published
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
In our modern world the source of for many chemicals is to acquire and refine oil. This process is becoming an expensive to the environment and to human health. Alternative processes for acquiring the final product have been developed but still need work. One product that is valuable is butanol. The normal process for butanol production is very intensive but there is a method to produce butanol from bacteria. This process is better because it is more environmentally safe than using oil. One problem however is that when the bacteria produce too much butanol it reaches the toxicity limit and stops the production of butanol. In order to keep butanol from reaching the toxicity limit an adsorbent is used to remove the butanol without harming the bacteria. The adsorbent is a mesoporous carbon powder that allows the butanol to be adsorbed on it. This thesis explores different designs for a magnetic separation process to extract the carbon powder from the culture.
ContributorsChabra, Rohin (Author) / Nielsen, David (Thesis director) / Torres, Cesar (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor)
Created2015-05
Description
One of the primary bottlenecks to chemical production in biological organisms is the toxicity of the chemical. Overexpression of efflux pumps has been shown to increase tolerance to aromatic compounds such as styrene and styrene oxide. Tight control of pump expression is necessary to maximize titers and prevent excessive strain on the cells. This study aimed to identify aromatic-sensitive native promoters and heterologous biosensors for construction of closed-loop control of efflux pump expression in E. coli. Using a promoter library constructed by Zaslaver et al., activation was measured through GFP output. Promoters were evaluated for their sensitivity to the addition of one of four aromatic compounds, their "leaking" of signal, and their induction threshold. Out of 43 targeted promoters, 4 promoters (cmr, mdtG, yahN, yajR) for styrene oxide, 2 promoters (mdtG, yahN) for styrene, 0 promoters for 2-phenylethanol, and 1 promoter for phenol (pheP) were identified as ideal control elements in aromatic bioproduction. In addition, a series of three biosensors (NahR, XylS, DmpR) known to be inducible by other aromatics were screened against styrene oxide, 2-phenylethanol, and phenol. The targeted application of these biosensors is aromatic-induced activation of linked efflux pumps. All three biosensors responded strongly in the presence of styrene oxide and 2-phenylethanol, with minor activation in the presence of phenol. Bioproduction of aromatics continues to gain traction in the biotechnology industry, and the continued discovery of aromatic-inducible elements will be essential to effective pathway control.
ContributorsXu, Jimmy (Author) / Nielsen, David (Thesis director) / Wang, Xuan (Committee member) / School of Life Sciences (Contributor) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
p-Coumaric acid is used in the food, pharmaceutical, and cosmetic industries due to its versatile properties. While prevalent in nature, harvesting the compound from natural sources is inefficient, requiring large quantities of producing crops and numerous extraction and purification steps. Thus, the large-scale production of the compound is both difficult and costly. This research aims to produce p-coumarate directly from renewable and sustainable glucose using a co-culture of Yeast and E. Coli. Methods used in this study include: designing optimal media for mixed-species microbial growth, genetically engineering both strains to build the production pathway with maximum yield, and analyzing the presence of p-Coumarate and its pathway intermediates using High Performance Liquid Chromatography (HPLC). To date, the results of this project include successful integration of C4H activity into the yeast strain BY4741 ∆FDC1, yielding a strain that completely consumed trans-cinnamate (initial concentration of 50 mg/L) and produced ~56 mg/L p-coumarate, a resting cell assay of the co-culture that produced 0.23 mM p-coumarate from an initial L-Phenylalanine concentration of 1.14 mM, and toxicity tests that confirmed the toxicity of trans-cinnamate to yeast for concentrations above ~50 mg/L. The hope for this project is to create a feasible method for producing p-Coumarate sustainably.
ContributorsJohnson, Kaleigh Lynnae (Author) / Nielsen, David (Thesis director) / Thompson, Brian (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This dissertation focuses on the biosynthetic production of aromatic fine chemicals in engineered Escherichia coli from renewable resources. The discussed metabolic pathways take advantage of key metabolites in the shikimic acid pathway, which is responsible for the production of the aromatic amino acids phenylalanine, tyrosine, and tryptophan. For the first time, the renewable production of benzaldehyde and benzyl alcohol has been achieved in recombinant E. coli with a maximum titer of 114 mg/L of benzyl alcohol. Further strain development to knockout endogenous alcohol dehydrogenase has reduced the in vivo degradation of benzaldehyde by 9-fold, representing an improved host for the future production of benzaldehyde as a sole product. In addition, a novel alternative pathway for the production of protocatechuate (PCA) and catechol from the endogenous metabolite chorismate is demonstrated. Titers for PCA and catechol were achieved at 454 mg/L and 630 mg/L, respectively. To explore potential routes for improved aromatic product yields, an in silico model using elementary mode analysis was developed. From the model, stoichiometric optimums maximizing both product-to-substrate and biomass-to-substrate yields were discovered in a co-fed model using glycerol and D-xylose as the carbon substrates for the biosynthetic production of catechol. Overall, the work presented in this dissertation highlights contributions to the field of metabolic engineering through novel pathway design for the biosynthesis of industrially relevant aromatic fine chemicals and the use of in silico modelling to identify novel approaches to increasing aromatic product yields.
ContributorsPugh, Shawn (Author) / Nielsen, David (Thesis advisor) / Dai, Lenore (Committee member) / Torres, Cesar (Committee member) / Lind, Mary Laura (Committee member) / Wang, Xuan (Committee member) / Arizona State University (Publisher)
Created2016
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
The purpose behind this research was to identify unknown transport proteins involved in lactate export. Lactate bioproduction is an environmentally beneficial alternative to petroleum-based plastic production as it produces less toxic waste byproduct and can rely on microbial degradation of otherwise wasted biomass. Coupled with appropriate product refinement, industrial microbial producers can be genetically engineered to generate quantities of bioplastic approaching 400 million metric tons each year. However, this process is not entirely suitable for large investment, as the fermentative bottlenecks, including product export and homeostasis control, limit production metrics. Previous studies have based their efforts on enhancing cellular machinery, but there remain uncharacterized membrane proteins involved in product export yet to be determined. It has been seen that deletion of known lactate transporters in Escherichia coli resulted in a decrease in lactate production, unlike the expected inhibition of export. This indicates that there exist membrane proteins with the ability to export lactate which may have another similar substrate it primarily transports.To identify these proteins, I constructed a genomic library of all genes in an engineered lactate producing E. coli strain, with known transporter genes deleted, and systematically screened for potential lactate transporter proteins. Plasmids and their isolated proteins were compared utilizing anaerobic plating to identify genes through sanger sequencing. With this method, I identified two proteins, yiaN and ybhL-ybhM, which did not show any significant improvement in lactate production when tested. Attempts were made to improve library diversity, resulting in isopropyl-β-D-1-thiogalactopyranoside induction as a likely factor for increased expression of potential fermentation-associated proteins. A genomic library from Lactobacillus plantarum was constructed and screened for transport proteins which could improve lactate production. Results showed that isolated plasmids contained no notable inserts, indicating that the initial transformation limited diversity. Lastly, I compared the results from genomic screening with overexpression of target transporter genes by computational substrate similarity search. Induced expression of ttdT, citT and dcuA together significantly increased lactate export and thus production metrics as well as cell growth. These positive results indicate an effective means of determining substrate promiscuity in membrane proteins with similar organic acid transport capacity.
ContributorsLee-Kin, Jared (Author) / Wang, Xuan (Thesis advisor) / Nielsen, David (Committee member) / Varman, Arul (Committee member) / Arizona State University (Publisher)
Created2022