Matching Items (106)
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
This dissertation focused on studying risks associated with emerging drinking water contaminants and tradeoffs related to water management interventions. The built environment impacts health, as humans on average spend ~90% of their time indoors. Federal regulations generally focus on drinking water at the water treatment plant and within the distribution system as opposed to when it enters buildings after crossing the property line. If drinking water is not properly managed in buildings, it can be a source or amplifier of microbial and chemical contaminants. Unlike regulations for chemical contaminants that are risk-based, for pathogens, regulations are either based on recommended treatment technologies or designated as zero, which is not achievable in practice. Practice-based judgments are typically made at the building level to maintain water quality. This research focuses on two drinking water opportunistic pathogens of public health concern, Legionella pneumophila and Mycobacterium avium complex (MAC). Multiple aspects of drinking water quality in two green buildings were monitored in tandem with water management interventions. Additionally, a quantitative microbial risk assessment framework was used to predict risk-based critical concentrations of MAC for drinking water-related exposures in the indoor environment corresponding to a 1 in 10,000 annual infection target risk benchmark. The overall goal of this work was to inform the development of water management plans and guidelines for buildings that will improve water quality in the built environment and promote better public health. It was determined that a whole building water softening system with ion exchange softening resin and expansion tanks were unexplored reservoirs for the colonization of L. pneumophila. Furthermore, it was observed that typical water management interventions such as flushing and thermal disinfection did not always mitigate water quality issues. Thus, there was a need to implement several atypical interventions such as equipment replacement to improve the building water quality. This work has contributed comprehensive field studies and models that have highlighted the need for additional niches, facility management challenges, and risk tradeoffs for focus in water safety plans. The work also informs additional risk-based water quality policy approaches for reducing drinking water risks.
ContributorsJoshi, Sayalee (Author) / Hamilton, Kerry A (Thesis advisor) / Abbaszadegan, Morteza (Committee member) / Conroy-Ben, Otakuye (Committee member) / Halden, Rolf (Committee member) / Arizona State University (Publisher)
Created2023
Description
Synthetic plastics are ubiquitously used in a broad range of applications, including food and drink packaging. Plastics often contain chemical additives, including bisphenols, phthalates, and terephthalic acid, which can degrade under thermal stress. The environmental presence of these chemicals is cause for public concern, especially in consumer products that utilize plastic packaging, as many have been identified as endocrine disruptors. This study sought to determine exposure to phthalates, bisphenols, and terephthalic acid by quantifying a broad spectrum of these analytes within three bottled water brands at varying temperature exposure levels using the combination of solid phase extraction followed by isotope dilution liquid chromatography-tandem mass spectrometry. Monobenzyl phthalate was detected in two of the three brands after bottles were heated to ~100 °C, ranging from 98 – 107 ng/L, and bisphenol A was detected in one brand at ~100 °C at an average concentration of 748 ± 36 ng/L. Subsequent mass loading calculations demonstrated that bioaccumulation of BPA from Brand C after high levels of temperature exposure well exceeded the tolerable daily intake (TDI). Findings in this study indicate that consumers should not be expected to incur harmful exposures to the target compounds under normal conditions as analytes were not measured in water bottle samples at 25 °C or 60 °C. Further studies should explore a more nuisance approach to heating over long durations, including that of ultraviolet exposure.
ContributorsZevitz, Jacob (Author) / Halden, Rolf (Thesis director) / Driver, Erin (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2022-12
Description
There is a need in the ecology literature to have a discussion about the fundamental theories from which population dynamics arises. Ad hoc model development is not uncommon in the field often as a result of a need to publish rapidly and frequently. Ecologists and statisticians like Robert J. Steidl and Kenneth P Burnham have called for a more deliberative approach they call "hard thinking". For example, the phenomena of population growth can be captured by almost any sigmoid function. The question of which sigmoid function best explains a data set cannot be answered meaningfully by statistical regression since that can only speak to the validity of the shape. There is a need to revisit enzyme kinetics and ecological stoichiometry to properly justify basal model selection in ecology. This dissertation derives several common population growth models from a generalized equation. The mechanistic validity of these models in different contexts is explored through a kinetic lens. The behavioral kinetic framework is then put to the test by examining a set of biologically plausible growth models against the 1968-1995 elk population count data for northern Yellowstone. Using only this count data, the novel Monod-Holling growth model was able to accurately predict minimum viable population and life expectancy despite both being exogenous to the model and data set. Lastly, the elk/wolf data from Yellowstone was used to compare the validity of the Rosenzweig-MacArthur and Arditi-Ginzburg models. They both were derived from a more general model which included both predator and prey mediated steps. The Arditi-Ginzburg model was able to fit the training data better, but only the Rosenzweig-MacArthur model matched the validation data. Accounting for animal sexual behavior allowed for the creation of the Monod-Holling model which is just as simple as the logistic differential equation but provides greater insights for conservation purposes. Explicitly acknowledging the ethology of wolf predation helps explain the differences in predictive performances by the best fit Rosenzweig-MacArthur and Arditi-Ginzburg models. The behavioral kinetic framework has proven to be a useful tool, and it has the ability to provide even further insights going forward.
ContributorsPringle, Jack Andrew McCracken (Author) / Anderies, John M (Thesis advisor) / Kuang, Yang (Committee member) / Milner, Fabio (Committee member) / Arizona State University (Publisher)
Created2022
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
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021
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 production and incineration of single-use micropipette tips and disposable gloves, which are heavily used within laboratory facilities, generate large amounts of greenhouse gasses (GHGs) and accelerate climate change. Plastic waste that is not incinerated often is lost in the environment. The long degradation times associated with this waste exacerbates a variety of environmental problems such as substance runoff and ocean pollution. The objective of this study was to evaluate the efficacy of possible solutions for minimizing micropipette tip and disposable glove waste within laboratory spaces. It was hypothesized that simultaneously implementing the use of micropipette tip washers (MTWs) and energy-from-glove-waste programs (EGWs) would significantly reduce (p < 0.05) the average combined annual single-use plastic micropipette tip and nitrile glove waste (in kg) per square meter of laboratory space in the United States. ASU’s Biodesign Institute (BDI) was used as a case study to inform on the thousands of different laboratory facilities that exist all across the United States. Four separate research laboratories within the largest public university of the U.S. were sampled to assess the volume of plastic waste from single-use micropipette tips and gloves. Resultant data were used to represent the totality of single-use waste from the case study location and then extrapolated to all laboratory space in the United States. With the implementation of EGWs, annual BDI glove waste is reduced by 100% (0.47 ± 0.26 kg/m2; 35.5 ± 19.3 metric tons total) and annual BDI glove-related carbon emissions are reduced by ~5.01% (0.165 ± 0.09 kg/m2; 1.24 ± 0.68 metric tons total). With the implementation of MTWs, annual BDI micropipette tip waste is reduced by 92% (0.117 ± 0.03 kg/m2; 0.88 ± 0.25 metric tons total) and annual BDI tip-related carbon emissions are reduced by ~83.6% (4.04 ± 1.25 kg/m2; 30.5 ± 9.43 metric tons total). There was no significant difference (p = 0.06) observed between the mass of single-use waste (kg) in the sampled laboratory spaces before (x̄ = 47.1; σ = 43.3) and after (x̄ =0.070; σ = 0.033) the implementation of the solutions. When examining both solutions (MTWs & EGWs) implemented in conjunction with one another, the annual BDI financial savings (in regard to both purchasing and disposal costs) after the first year were determined to be ~$7.92 ± $9.31/m2 (7,500 m2 of total wet laboratory space) or ~$60,000 ± $70,000 total. These savings represent ~15.77% of annual BDI spending on micropipette tips and nitrile gloves. The large error margins in these financial estimates create high uncertainty for whether or not BDI would see net savings from implementing both solutions simultaneously. However, when examining the implementation of only MTWs, the annual BDI financial savings (in regard to both purchasing and disposal costs) after the first year were determined to be ~$12.01 ± $6.79 kg/m2 or ~$91,000 ± $51,200 total. These savings represent ~23.92% of annual BDI spending on micropipette tips and nitrile gloves. The lower error margins for this estimate create a much higher likelihood of net savings for BDI. Extrapolating to all laboratory space in the United States, the total annual amount of plastic waste avoided with the implementation of the MTWs was identified as 8,130 ± 2,290 tons or 0.023% of all solid plastic waste produced in the United States in 2018. The total amount of nitrile waste avoided with the implementation of the EGWs was identified as 32,800 ± 17,900 tons or 0.36% of all rubber solid waste produced in the United States in 2018. The total amount of carbon emissions avoided with the implementation of the MTWs was identified as 281,000 ± 87,000 tons CO2eq or 5.4*10-4 % of all CO2eq GHG emissions produced in the United States in 2020. Both the micropipette tip washer and the glove waste avoidance program solutions can be easily integrated into existing laboratories without compromising the integrity of the activities taking place. Implemented on larger scales, these solutions hold the potential for significant single-use waste reduction.
ContributorsZdrale, Gabriel (Author) / Mahant, Akhil (Co-author) / Halden, Rolf (Thesis director) / Biyani, Nivedita (Committee member) / Driver, Erin (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
Description
The production and incineration of single-use micropipette tips and disposable gloves, which are heavily used within laboratory facilities, generate large amounts of greenhouse gasses (GHGs) and accelerate climate change. Plastic waste that is not incinerated often is lost in the environment. The long degradation times associated with this waste exacerbates a variety of environmental problems such as substance runoff and ocean pollution. The objective of this study was to evaluate the efficacy of possible solutions for minimizing micropipette tip and disposable glove waste within laboratory spaces. It was hypothesized that simultaneously implementing the use of micropipette tip washers (MTWs) and energy-from-glove-waste programs (EGWs) would significantly reduce (p < 0.05) the average combined annual single-use plastic micropipette tip and nitrile glove waste (in kg) per square meter of laboratory space in the United States. ASU’s Biodesign Institute (BDI) was used as a case study to inform on the thousands of different laboratory facilities that exist all across the United States. Four separate research laboratories within the largest public university of the U.S. were sampled to assess the volume of plastic waste from single-use micropipette tips and gloves. Resultant data were used to represent the totality of single-use waste from the case study location and then extrapolated to all laboratory space in the United States. With the implementation of EGWs, annual BDI glove waste is reduced by 100% (0.47 ± 0.26 kg/m2; 35.5 ± 19.3 metric tons total) and annual BDI glove-related carbon emissions are reduced by ~5.01% (0.165 ± 0.09 kg/m2; 1.24 ± 0.68 metric tons total). With the implementation of MTWs, annual BDI micropipette tip waste is reduced by 92% (0.117 ± 0.03 kg/m2; 0.88 ± 0.25 metric tons total) and annual BDI tip-related carbon emissions are reduced by ~83.6% (4.04 ± 1.25 kg/m2; 30.5 ± 9.43 metric tons total). There was no significant difference (p = 0.06) observed between the mass of single-use waste (kg) in the sampled laboratory spaces before (x̄ = 47.1; σ = 43.3) and after (x̄ =0.070; σ = 0.033) the implementation of the solutions.When examining both solutions (MTWs & EGWs) implemented in conjunction with one another, the annual BDI financial savings (in regard to both purchasing and disposal costs) after the first year were determined to be ~$7.92 ± $9.31/m2 (7,500 m2 of total wet laboratory space) or ~$60,000 ± $70,000 total. These savings represent ~15.77% of annual BDI spending on micropipette tips and nitrile gloves. The large error margins in these financial estimates create high uncertainty for whether or not BDI would see net savings from implementing both solutions simultaneously. However, when examining the implementation of only MTWs, the annual BDI financial savings (in regard to both purchasing and disposal costs) after the first year were determined to be ~$12.01 ± $6.79 kg/m2 or ~$91,000 ± $51,200 total. These savings represent ~23.92% of annual BDI spending on micropipette tips and nitrile gloves. The lower error margins for this estimate create a much higher likelihood of net savings for BDI. Extrapolating to all laboratory space in the United States, the total annual amount of plastic waste avoided with the implementation of the MTWs was identified as 8,130 ± 2,290 tons or 0.023% of all solid plastic waste produced in the United States in 2018. The total amount of nitrile waste avoided with the implementation of the EGWs was identified as 32,800 ± 17,900 tons or 0.36% of all rubber solid waste produced in the United States in 2018. The total amount of carbon emissions avoided with the implementation of the MTWs was identified as 281,000 ± 87,000 tons CO2eq or 5.4*10-4 % of all CO2eq GHG emissions produced in the United States in 2020. Both the micropipette tip washer and the glove waste avoidance program solutions can be easily integrated into existing laboratories without compromising the integrity of the activities taking place. Implemented on larger scales, these solutions hold the potential for significant single-use waste reduction.
ContributorsMahant, Akhil (Author) / Zdrale, Gabriel (Co-author) / Halden, Rolf (Thesis director) / Biyani, Nivedita (Committee member) / Driver, Erin (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2022-05