ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Displaying 1 - 10 of 14
Filtering by
- All Subjects: Biology
- Creators: Kuang, Yang
- Creators: Liebig, Jürgen
Description
At the heart of every eusocial insect colony is a reproductive division of labor. This division can emerge through dominance interactions at the adult stage or through the production of distinct queen and worker castes at the larval stage. In both cases, this division depends on plasticity within an individual to develop reproductive characteristics or serve as a worker. In order to gain insight into the evolution of reproductive plasticity in the social insects, I investigated caste determination and dominance in the ant Harpegnathos saltator, a species that retains a number of ancestral characteristics. Treatment of worker larvae with a juvenile hormone (JH) analog induced late-instar larvae to develop as queens. At the colony level, workers must have a mechanism to regulate larval development to prevent queens from developing out of season. I identified a new behavior in H. saltator where workers bite larvae to inhibit queen determination. Workers could identify larval caste based on a chemical signal specific to queen-destined larvae, and the production of this signal was directly linked to increased JH levels. This association provides a connection between the physiological factors that induce queen development and the production of a caste-specific larval signal. In addition to caste determination at the larval stage, adult workers of H. saltator compete to establish a reproductive hierarchy. Unlike other social insects, dominance in H. saltator was not related to differences in JH or ecdysteroid levels. Instead, changes in brain levels of biogenic amines, particularly dopamine, were correlated with dominance and reproductive status. Receptor genes for dopamine were expressed in both the brain and ovaries of H. saltator, and this suggests that dopamine may coordinate changes in behavior at the neurological level with ovarian status. Together, these studies build on our understanding of reproductive plasticity in social insects and provide insight into the evolution of a reproductive division of labor.
ContributorsPenick, Clint A (Author) / Liebig, Jürgen (Thesis advisor) / Brent, Colin (Committee member) / Gadau, Jürgen (Committee member) / Hölldobler, Bert (Committee member) / Rutowski, Ron (Committee member) / Arizona State University (Publisher)
Created2012
Description
There has been important progress in understanding ecological dynamics through the development of the theory of ecological stoichiometry. This fast growing theory provides new constraints and mechanisms that can be formulated into mathematical models. Stoichiometric models incorporate the effects of both food quantity and food quality into a single framework that produce rich dynamics. While the effects of nutrient deficiency on consumer growth are well understood, recent discoveries in ecological stoichiometry suggest that consumer dynamics are not only affected by insufficient food nutrient content (low phosphorus (P): carbon (C) ratio) but also by excess food nutrient content (high P:C). This phenomenon, known as the stoichiometric knife edge, in which animal growth is reduced not only by food with low P content but also by food with high P content, needs to be incorporated into mathematical models. Here we present Lotka-Volterra type models to investigate the growth response of Daphnia to algae of varying P:C ratios. Using a nonsmooth system of two ordinary differential equations (ODEs), we formulate the first model to incorporate the phenomenon of the stoichiometric knife edge. We then extend this stoichiometric model by mechanistically deriving and tracking free P in the environment. This resulting full knife edge model is a nonsmooth system of three ODEs. Bifurcation analysis and numerical simulations of the full model, that explicitly tracks phosphorus, leads to quantitatively different predictions than previous models that neglect to track free nutrients. The full model shows that the grazer population is sensitive to excess nutrient concentrations as a dynamical free nutrient pool induces extreme grazer population density changes. These modeling efforts provide insight on the effects of excess nutrient content on grazer dynamics and deepen our understanding of the effects of stoichiometry on the mechanisms governing population dynamics and the interactions between trophic levels.
ContributorsPeace, Angela (Author) / Kuang, Yang (Thesis advisor) / Elser, James J (Committee member) / Baer, Steven (Committee member) / Tang, Wenbo (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
The phycologist, M. R. Droop, studied vitamin B12 limitation in the flagellate Monochrysis lutheri and concluded that its specific growth rate depended on the concentration of the vitamin within the cell; i.e. the cell quota of the vitamin B12. The Droop model provides a mathematical expression to link growth rate to the intracellular concentration of a limiting nutrient. Although the Droop model has been an important modeling tool in ecology, it has only recently been applied to study cancer biology. Cancer cells live in an ecological setting, interacting and competing with normal and other cancerous cells for nutrients and space, and evolving and adapting to their environment. Here, the Droop equation is used to model three cancers.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
ContributorsEverett, Rebecca Anne (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Milner, Fabio (Committee member) / Crook, Sharon (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Arizona State University (Publisher)
Created2015
Description
In 1968, phycologist M.R. Droop published his famous discovery on the functional relationship between growth rate and internal nutrient status of algae in chemostat culture. The simple notion that growth is directly dependent on intracellular nutrient concentration is useful for understanding the dynamics in many ecological systems. The cell quota in particular lends itself to ecological stoichiometry, which is a powerful framework for mathematical ecology. Three models are developed based on the cell quota principal in order to demonstrate its applications beyond chemostat culture.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
ContributorsPacker, Aaron (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Smith, Hal (Committee member) / Kostelich, Eric (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
Social insect colonies exhibit striking diversity in social organization. Included in this overwhelming variation in structure are differences in colony queen number. The number of queens per colony varies both intra- and interspecifically and has major impacts on the social dynamics of a colony and the fitness of its members. To understand the evolutionary transition from single to multi-queen colonies, I examined a species which exhibits variation both in mode of colony founding and in the queen number of mature colonies. The California harvester ant Pogonomyrmex californicus exhibits both variation in the number of queens that begin a colony (metrosis) and in the number of queens in adult colonies (gyny). Throughout most of its range, colonies begin with one queen (haplometrosis) but in some populations multiple queens cooperate to initiate colonies (pleometrosis). I present results that confirm co-foundresses are unrelated. I also map the geographic occurrence of pleometrotic populations and show that the phenomenon appears to be localized in southern California and Northern Baja California. Additionally, I provide genetic evidence that pleometrosis leads to primary polygyny (polygyny developing from pleometrosis) a phenomenon which has received little attention and is poorly understood. Phylogenetic and haplotype analyses utilizing mitochondrial markers reveal that populations of both behavioral types in California are closely related and have low mitochondrial diversity. Nuclear markers however, indicate strong barriers to gene flow between focal populations. I also show that intrinsic differences in queen behavior lead to the two types of populations observed. Even though populations exhibit strong tendencies on average toward haplo- or pleometrosis, within population variation exists among queens for behaviors relevant to metrosis and gyny. These results are important in understanding the dynamics and evolutionary history of a distinct form of cooperation among unrelated social insects. They also help to understand the dynamics of intraspecific variation and the conflicting forces of local adaptation and gene flow.
ContributorsOverson, Rick P (Author) / Gadau, Jürgen (Thesis advisor) / Fewell, Jennifer H (Committee member) / Hölldobler, Bert (Committee member) / Johnson, Robert A. (Committee member) / Liebig, Jürgen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). I demonstrate that the inverse problem of parameter estimation might be too complicated and simply relying on data fitting can give incorrect conclusions, since there is a large error in parameter values estimated and parameters might be unidentifiable. I provide confidence intervals to give estimate forecasts using data assimilation via an ensemble Kalman Filter. Using the ensemble Kalman Filter, I perform dual estimation of parameters and state variables to test the prediction accuracy of the models. Finally, I present a novel model with time delay and a delay-dependent parameter. I provide a geometric stability result to study the behavior of this model and show that the inclusion of time delay may improve the accuracy of predictions. Also, I demonstrate with clinical data that the inclusion of the delay-dependent parameter facilitates the identification and estimation of parameters.
ContributorsBaez, Javier (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2017
Description
The most advanced social insects, the eusocial insects, form often large societies in which there is reproductive division of labor, queens and workers, have overlapping generations, and cooperative brood care where daughter workers remain in the nest with their queen mother and care for their siblings. The eusocial insects are composed of representative species of bees and wasps, and all species of ants and termites. Much is known about their organizational structure, but remains to be discovered.
The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
ContributorsRodríguez Messan, Marisabel (Author) / Kang, Yun (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Kuang, Yang (Committee member) / Page Jr., Robert E (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2018
Description
The most abundantly studied societies, with the exception of humans, are those of the eusocial insects, which include all ants. Eusocial insect societies are typically composed of many dozens to millions of individuals, referred to as nestmates, which require some form of communication to maintain colony cohesion and coordinate the activities within them. Nestmate recognition is the process of distinguishing between nestmates and non-nestmates, and embodies the first line of defense for social insect colonies. In ants, nestmate recognition is widely thought to occur through olfactory cues found on the exterior surfaces of individuals. These cues, called cuticular hydrocarbons (CHCs), comprise the overwhelming majority of ant nestmate profiles and help maintain colony identity. In this dissertation, I investigate how nestmate recognition is influenced by evolutionary, ontogenetic, and environmental factors. First, I contributed to the sequencing and description of three ant genomes including the red harvester ant, Pogonomyrmex barbatus, presented in detail here. Next, I studied how variation in nestmate cues may be shaped through evolution by comparatively studying a family of genes involved in fatty acid and hydrocarbon biosynthesis, i.e., the acyl-CoA desaturases, across seven ant species in comparison with other social and solitary insects. Then, I tested how genetic, developmental, and social factors influence CHC profile variation in P. barbatus, through a three-part study. (1) I conducted a descriptive, correlative study of desaturase gene expression and CHC variation in P. barbatus workers and queens; (2) I explored how larger-scale genetic variation in the P. barbatus species complex influences CHC variation across two genetically isolated lineages (J1/J2 genetic caste determining lineages); and (3) I experimentally examined how CHC development is influenced by an individual’s social environment. In the final part of my work, I resolved discrepancies between previous findings of nestmate recognition behavior in P. barbatus by studying how factors of territorial experience, i.e., spatiotemporal relationships, affect aggressive behaviors among red harvester ant colonies. Through this research, I was able to identify promising methodological approaches and candidate genes, which both broadens our understanding of P. barbatus nestmate recognition systems and supports future functional genetic studies of CHCs in ants.
ContributorsCash, Elizabeth I (Author) / Gadau, Jürgen (Thesis advisor) / Liebig, Jürgen (Thesis advisor) / Fewell, Jennifer (Committee member) / Hölldobler, Berthold (Committee member) / Kusumi, Kenro (Committee member) / Arizona State University (Publisher)
Created2016
Description
Dominance behavior can regulate a division of labor in a group, such as that between reproductive and non-reproductive individuals. Manipulations of insect societies in a controlled environment can reveal how dominance behavior is regulated. Here, I examined how morphological caste, fecundity, group size, and age influence the expression of dominance behavior using the ponerine ant Harpegnathos saltator. All H. saltator females have the ability to reproduce. Only those with a queen morphology that enables dispersal, however, show putative sex pheromones. In contrast, those with a worker morphology normally express dominance behavior. To evaluate how worker-like dominance behavior and associated traits could be expressed in queens, I removed the wings from alate gynes, those with a queen morphology who had not yet mated or left the nest, making them dealate. Compared to gynes with attached wings, dealates frequently performed dominance behavior. In addition, only the dealates demonstrated worker-like ovarian activity in the presence of reproductive individuals, whereas gynes with wings produced sex pheromones exclusively. Therefore, the attachment of wings determines a gyne’s expression of worker-like dominance behavior and physiology. When the queen dies, workers establish a reproductive hierarchy among themselves by performing a combination of dominance behaviors. To understand how reproductive status depends on these interactions as well as a worker’s age, I measured the frequency of dominance behaviors in groups of different size composed of young and old workers. The number of workers who expressed dominance scaled with the size of the group, but younger ones were more likely to express dominance behavior and eventually become reproductive. Therefore, the predisposition of age integrates with a self-organized process to form this reproductive hierarchy. A social insect’s fecundity and fertility signal depends on social context because fecundity increases with colony size. To evaluate how a socially dependent signal regulates dominance behavior, I manipulated a reproductive worker’s social context. Reproductive workers with reduced fecundity and a less prominent fertility signal expressed more dominance behavior than those with a stronger fertility signal and higher fecundity. Therefore, dominance behavior reinforces rank to compensate for a weak signal, indicating how social context can feed back to influence the maintenance of dominance. Mechanisms that regulate H. saltator’s reproductive hierarchy can inform how the reproductive division of labor is regulated in other groups of animals.
ContributorsPyenson, Benjamin (Author) / Liebig, Jürgen (Thesis advisor) / Hölldobler, Bert (Committee member) / Fewell, Jennifer (Committee member) / Pratt, Stephen (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2022
Description
Efforts to treat prostate cancer have seen an uptick, as the world’s most commoncancer in men continues to have increasing global incidence. Clinically, metastatic
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
ContributorsReckell, Trevor (Author) / Kostelich, Eric (Thesis advisor) / Kuang, Yang (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2020