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- Genre: Doctoral Dissertation
Description
Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology. In particular many diffusive type processes in the cell have been observed to follow a power law $\left \propto t^\alpha$ scaling of the mean square displacement of a particle. This contrasts with the expected linear behavior of particles undergoing normal diffusion. \emph{Anomalous sub-diffusion} ($\alpha<1$) has been attributed to factors such as cytoplasmic crowding of macromolecules, and trap-like structures in the subcellular environment non-linearly slowing the diffusion of molecules. Compared to normal diffusion, signaling molecules in these constrained spaces can be more concentrated at the source, and more diffuse at longer distances, potentially effecting the signalling dynamics. As diffusion at the cellular scale is a fundamental mechanism of cellular signaling and additionally is an implicit underlying mathematical assumption of many canonical models, a closer look at models of anomalous diffusion is warranted. Approaches in the literature include derivations of fractional differential diffusion equations (FDE) and continuous time random walks (CTRW). However these approaches are typically based on \emph{ad-hoc} assumptions on time- and space- jump distributions. We apply recent developments in asymptotic techniques on collisional kinetic equations to develop a FDE model of sub-diffusion due to trapping regions and investigate the nature of the space/time probability distributions assosiated with trapping regions. This approach both contrasts and compliments the stochastic CTRW approach by positing more physically realistic underlying assumptions on the motion of particles and their interactions with trapping regions, and additionally allowing varying assumptions to be applied individually to the traps and particle kinetics.
ContributorsHoleva, Thomas Matthew (Author) / Ringhofer, Christian (Thesis advisor) / Baer, Steve (Thesis advisor) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Taylor, Jesse (Committee member) / Arizona State University (Publisher)
Created2014
Description
Pre-Exposure Prophylaxis (PrEP) is any medical or public health procedure used before exposure to the disease causing agent, its purpose is to prevent, rather than treat or cure a disease. Most commonly, PrEP refers to an experimental HIV-prevention strategy that would use antiretrovirals to protect HIV-negative people from HIV infection. A deterministic mathematical model of HIV transmission is developed to evaluate the public-health impact of oral PrEP interventions, and to compare PrEP effectiveness with respect to different evaluation methods. The effects of demographic, behavioral, and epidemic parameters on the PrEP impact are studied in a multivariate sensitivity analysis. Most of the published models on HIV intervention impact assume that the number of individuals joining the sexually active population per year is constant or proportional to the total population. In the second part of this study, three models are presented and analyzed to study the PrEP intervention, with constant, linear, and logistic recruitment rates. How different demographic assumptions can affect the evaluation of PrEP is studied. When provided with data, often least square fitting or similar approaches can be used to determine a single set of approximated parameter values that make the model fit the data best. However, least square fitting only provides point estimates and does not provide information on how strongly the data supports these particular estimates. Therefore, in the third part of this study, Bayesian parameter estimation is applied on fitting ODE model to the related HIV data. Starting with a set of prior distributions for the parameters as initial guess, Bayes' formula can be applied to obtain a set of posterior distributions for the parameters which makes the model fit the observed data best. Evaluating the posterior distribution often requires the integration of high-dimensional functions, which is usually difficult to calculate numerically. Therefore, the Markov chain Monte Carlo (MCMC) method is used to approximate the posterior distribution.
ContributorsZhao, Yuqin (Author) / Kuang, Yang (Thesis advisor) / Taylor, Jesse (Committee member) / Armbruster, Dieter (Committee member) / Tang, Wenbo (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
Understanding the diversity, evolutionary relationships, and geographic distribution of species is foundational knowledge in biology. However, this knowledge is lacking for many diverse lineages of the tree of life. This is the case for the desert stink beetles in the tribe Amphidorini LeConte, 1862 (Coleoptera: Tenebrionidae) – a lineage of arid-adapted flightless beetles found throughout western North America. Four interconnected studies that jointly increase our knowledge of this group are presented. First, the darkling beetle fauna of the Algodones sand dunes in southern California is examined as a case study to explore the scientific practice of checklist creation. An updated list of the species known from this region is presented, with a critical focus on material now made available through digitization and global aggregation. This part concludes with recommendations for future biodiversity checklist authors. Second, the psammophilic genus Trogloderus LeConte, 1879 is revised. Six new species are described, and the first, multi-gene phylogeny for the genus is inferred. In addition, historical biogeographic reconstructions along with novel hypotheses of speciation patterns within the Intermountain Region are given. In particular, the Kaibab Plateau and Kaiparowitz Formation are found to have promoted speciation on the Colorado Plateau. The Owens Valley and prehistoric Bouse Embayment are similarly hypothesized to drive species diversification in southern California. Third, a novel phylogenomic analysis for the tribe Amphidorini is presented, based on 29 de novo partial transcriptomes. Three putative ortholog sets were discovered and analyzed to infer the relationships between species groups and genera. The existing classification of the tribe is found to be highly inadequate, though the earliest-diverging relationships within the tribe are still in question. Finally, the new phylogenetic framework is used to provide a genus-level revision for the Amphidorini, which previously contained six valid genera and 253 valid species. This updated classification includes more than 100 taxonomic changes and results in the revised tribe consisting of 16 genera, with three being described as new to science.
ContributorsJohnston, Murray Andrew (Author) / Franz, Nico M (Thesis advisor) / Cartwright, Reed (Committee member) / Taylor, Jesse (Committee member) / Pigg, Kathleen (Committee member) / Arizona State University (Publisher)
Created2018
Description
Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to identify isolation-by-distance because it can impact the statistical analysis of population samples and it can help us better understand evolutionary dynamics. For this dissertation I investigated several aspects of isolation-by-distance. First, I looked at how the shape of the dispersal distribution affects the observed pattern of isolation-by-distance. If, as theory predicts, the shape of the distribution has little effect, then it would be more practical to model isolation-by-distance using a simple dispersal distribution rather than replicating the complexities of more realistic distributions. Therefore, I developed an efficient algorithm to simulate dispersal based on a simple triangular distribution, and using a simulation, I confirmed that the pattern of isolation-by-distance was similar to other more realistic distributions. Second, I developed a Bayesian method to quantify isolation-by-distance using genetic data by estimating Wright’s neighborhood size parameter. I analyzed the performance of this method using simulated data and a microsatellite data set from two populations of Maritime pine, and I found that the neighborhood size estimates had good coverage and low error. Finally, one of the major consequences of isolation-by-distance is an increase in inbreeding. Plants are often particularly susceptible to inbreeding, and as a result, they have evolved many inbreeding avoidance mechanisms. Using a simulation, I determined which mechanisms are more successful at preventing inbreeding associated with isolation-by-distance.
ContributorsFurstenau, Tara N (Author) / Cartwright, Reed A (Thesis advisor) / Rosenberg, Michael S. (Committee member) / Taylor, Jesse (Committee member) / Wilson-Sayres, Melissa (Committee member) / Arizona State University (Publisher)
Created2015
Description
The complex life cycle and widespread range of infection of Plasmodium parasites, the causal agent of malaria in humans, makes them the perfect organism for the study of various evolutionary mechanisms. In particular, multigene families are considered one of the main sources for genome adaptability and innovation. Within Plasmodium, numerous species- and clade-specific multigene families have major functions in the development and maintenance of infection. Nonetheless, while the evolutionary mechanisms predominant on many species- and clade-specific multigene families have been previously studied, there are far less studies dedicated to analyzing genus common multigene families (GCMFs). I studied the patterns of natural selection and recombination in 90 GCMFs with diverse numbers of gene gain/loss events. I found that the majority of GCMFs are formed by duplications events that predate speciation of mammal Plasmodium species, with many paralogs being neutrally maintained thereafter. In general, multigene families involved in immune evasion and host cell invasion commonly showed signs of positive selection and species-specific gain/loss events; particularly, on Plasmodium species is the simian and rodent clades. A particular multigene family: the merozoite surface protein-7 (msp7) family, is found in all Plasmodium species and has functions related to the erythrocyte invasion. Within Plasmodium vivax, differences in the number of paralogs in this multigene family has been previously explained, at least in part, as potential adaptations to the human host. To investigate this I studied msp7 orthologs in closely related non-human primate parasites where homology was evident. I also estimated paralogs’ evolutionary history and genetic polymorphism. The emerging patterns where compared with those of Plasmodium falciparum. I found that the evolution of the msp7 multigene family is consistent with a Birth-and-Death model where duplications, pseudogenization and gene lost events are common. In order to study additional aspects in the evolution of Plasmodium, I evaluated the trends of long term and short term evolution and the putative effects of vertebrate- host’s immune pressure of gametocytes across various Plasmodium species. Gametocytes, represent the only sexual stage within the Plasmodium life cycle, and are also the transition stages from the vertebrate to the mosquito vector. I found that, while male and female gametocytes showed different levels of immunogenicity, signs of positive selection were not entirely related to the location and presence of immune epitope regions. Overall, these studies further highlight the complex evolutionary patterns observed in Plasmodium.
ContributorsCastillo Siri, Andreina I (Author) / Rosenberg, Michael (Thesis advisor) / Escalante, Ananias (Committee member) / Taylor, Jesse (Committee member) / Collins, James (Committee member) / Arizona State University (Publisher)
Created2016
Description
Swarms of low-cost, autonomous robots can potentially be used to collectively perform tasks over large domains and long time scales. The design of decentralized, scalable swarm control strategies will enable the development of robotic systems that can execute such tasks with a high degree of parallelism and redundancy, enabling effective operation even in the presence of unknown environmental factors and individual robot failures. Social insect colonies provide a rich source of inspiration for these types of control approaches, since they can perform complex collective tasks under a range of conditions. To validate swarm robotic control strategies, experimental testbeds with large numbers of robots are required; however, existing low-cost robots are specialized and can lack the necessary sensing, navigation, control, and manipulation capabilities.
To address these challenges, this thesis presents a formal approach to designing biologically-inspired swarm control strategies for spatially-confined coverage and payload transport tasks, as well as a novel low-cost, customizable robotic platform for testing swarm control approaches. Stochastic control strategies are developed that provably allocate a swarm of robots around the boundaries of multiple regions of interest or payloads to be transported. These strategies account for spatially-dependent effects on the robots' physical distribution and are largely robust to environmental variations. In addition, a control approach based on reinforcement learning is presented for collective payload towing that accommodates robots with heterogeneous maximum speeds. For both types of collective transport tasks, rigorous approaches are developed to identify and translate observed group retrieval behaviors in Novomessor cockerelli ants to swarm robotic control strategies. These strategies can replicate features of ant transport and inherit its properties of robustness to different environments and to varying team compositions. The approaches incorporate dynamical models of the swarm that are amenable to analysis and control techniques, and therefore provide theoretical guarantees on the system's performance. Implementation of these strategies on robotic swarms offers a way for biologists to test hypotheses about the individual-level mechanisms that drive collective behaviors. Finally, this thesis describes Pheeno, a new swarm robotic platform with a three degree-of-freedom manipulator arm, and describes its use in validating a variety of swarm control strategies.
To address these challenges, this thesis presents a formal approach to designing biologically-inspired swarm control strategies for spatially-confined coverage and payload transport tasks, as well as a novel low-cost, customizable robotic platform for testing swarm control approaches. Stochastic control strategies are developed that provably allocate a swarm of robots around the boundaries of multiple regions of interest or payloads to be transported. These strategies account for spatially-dependent effects on the robots' physical distribution and are largely robust to environmental variations. In addition, a control approach based on reinforcement learning is presented for collective payload towing that accommodates robots with heterogeneous maximum speeds. For both types of collective transport tasks, rigorous approaches are developed to identify and translate observed group retrieval behaviors in Novomessor cockerelli ants to swarm robotic control strategies. These strategies can replicate features of ant transport and inherit its properties of robustness to different environments and to varying team compositions. The approaches incorporate dynamical models of the swarm that are amenable to analysis and control techniques, and therefore provide theoretical guarantees on the system's performance. Implementation of these strategies on robotic swarms offers a way for biologists to test hypotheses about the individual-level mechanisms that drive collective behaviors. Finally, this thesis describes Pheeno, a new swarm robotic platform with a three degree-of-freedom manipulator arm, and describes its use in validating a variety of swarm control strategies.
ContributorsWilson, Sean Thomas (Author) / Berman, Spring M (Thesis advisor) / Artemiadis, Panagiotis (Committee member) / Sugar, Thomas (Committee member) / Rodriguez, Armando A (Committee member) / Taylor, Jesse (Committee member) / Arizona State University (Publisher)
Created2017
Description
Biogeography places the geographical distribution of biodiversity in an evolutionary context. Ants (Hymenoptera: Formicidae), being a group of ubiquitous, ecologically dominant, and diverse insects, are useful model systems to understand the evolutionary origins and mechanisms of biogeographical patterns across spatial scales. On a global scale, ants have been used to test hypotheses on the origin and maintenance of the remarkably consistent latitudinal diversity gradient where biodiversity peaks in the equatorial tropics and decreases towards the poles. Additionally, ants have been used to posit and test theories of island biogeography such as the mechanisms of the species-area relationship, being the increase of biodiversity with cumulative land area. However, there are still unanswered questions about ant biogeography such as how specialized life histories contribute to their global biogeographical patterns. Furthermore, there remain island systems in the world’s biodiversity hotspots that harbor much less ant species than predicted by the species-area relationship, which potentially suggests a place ripe for discovery. In this dissertation, I use natural history, taxonomic, geographic, and phylogenetic data to study ant biodiversity and biogeography across spatial scales. First, I study the global biodiversity and biogeography of a specialized set of symbiotic interactions between ant species, here referred to as myrmecosymbioses, with an emphasis on social parasitism where one species exploits the parental care behavior and social colony environment of another species. In addition to characterizing a new myrmecosymbiosis, I use a global biogeographic and phylogenetic dataset to show that ant social parasitism is distributed along an inverse latitudinal diversity gradient where species richness and independent evolutionary origins of social parasitism peak within the northern hemisphere where the least free-living ant diversity exists. Second, I study the unexplored ant fauna of the Vanuatuan archipelago in the South Pacific. Using approximately 10,000 Vanuatuan ant specimens coupled with phylogenomics, I fill in a historical knowledge gap of South Pacific ant biogeography and demonstrate that the Vanuatuan ant fauna is a novel biodiversity hotspot. With these studies, I provide insights into how specialized life histories and unique island biotas shape the global distribution of biodiversity in different ways, especially in the ants.
ContributorsGray, Kyle William (Author) / Rabeling, Christian (Thesis advisor) / Martins, Emilia (Committee member) / Taylor, Jesse (Committee member) / Pratt, Stephen (Committee member) / Wojciechowski, Martin (Committee member) / Arizona State University (Publisher)
Created2023
Description
The weevil genus Pachnaeus Schoenherr, 1826 (Coleoptera: Curculionidae: Entiminae: Eustylini Lacordaire) is revised to accommodate 21 species, including the following 10 new species from the northern Caribbean region: Pachnaeus andersoni sp. nov. (Little Cayman), Pachnaeus eisenbergi sp. nov. (Jamaica), Pachnaeus godivae sp. nov. (Cayman Brac), Pachnaeus gordoni sp. nov. (Jamaica), Pachnaeus howdenae sp. nov. (Bahamas), Pachnaeus ivieorum sp. nov. (Bahamas with adventive records from Florida), Pachnaeus maestrensis sp. nov. (Cuba), Pachnaeus morelli sp. nov. (Haiti), Pachnaeus obrienorum sp. nov. (Cuba and Bahamas), and Pachnaeus quadrilineatus sp. nov. (Jamaica).Pachnaeus can be distinguished from similar, co-occurring taxa such as Exophthalmus quadrivittatus (Olivier, 1807), Exophthalmus roseipes (Chevrolat, 1876), Exophthalmus vittatus (Linnaeus, 1758), and Diaprepes abbreviatus (Linnaeus, 1758) by (1) the presence of postocular vibrissae, (2) endophallus primarily membranous and sac-like proximally, and long (>3 × width), tubular, and sclerotized distally, (3) additional endophallic sclerites typically absent, (4) a never bicarinate, typically tricarinate, rostrum, and several additional characteristics of the pedon, endophallus, pronotal structure, rostral structure, and scaling. Based on these characters, Pachnaeus sommeri (Munck af Rosenschoeld in Schoenherr, 1840) comb, nov. and Pachnaeus gowdeyi (Marshall, 1926) comb. nov. are transferred into the genus from Exophthalmus Schoenherr and Lachnopus Schoenherr respectively.
This revision provides genus and species redescriptions, diagnoses, illustrations, and the first comprehensive key to all 21 species within the present circumscription of Pachnaeus, in addition to reviewing the known biology and observed intraspecific variation within species. The complex taxonomic history of the genus is reviewed, and the evolutionary relationships of its presumed constituent clades are proposed through the construction of informal species groups and subgroups based on diagnosable shared traits. Lectotypes for Pachnaeus citri Marshall, Pachnaeus costatus Perroud, and Exophthalmus sommeri Munck af Rosenschoeld in Schoenherr and paralectotypes of P. citri (3 specimens) and E. sommeri (4 specimens) are designated. New state and national records are reported for Pachnaeus azurescens Gyllenhal in Schoenherr for Florida, U.S.A. and new national records are reported for Pachnaeus litus (Germar) for the Bahamas. Validity of the names Docorhinus Schoenherr, 1823 and Pachnaeus Schoenherr, 1826 is treated. Generic placement of Pachnaeus roseipes Chevrolat, 1876 is explored.
ContributorsReily, Brian Herndon (Author) / Franz, Nico M (Thesis advisor) / Taylor, Jesse (Committee member) / Pigg, Kathleen (Committee member) / Johnston, Murray A (Committee member) / Arizona State University (Publisher)
Created2022
Description
Signaling cascades transduce signals received on the cell membrane to the nucleus. While noise filtering, ultra-sensitive switches, and signal amplification have all been shown to be features of such signaling cascades, it is not understood why cascades typically show three or four layers. Using singular perturbation theory, Michaelis-Menten type equations are derived for open enzymatic systems. When these equations are organized into a cascade, it is demonstrated that the output signal as a function of time becomes sigmoidal with the addition of more layers. Furthermore, it is shown that the activation time will speed up to a point, after which more layers become superfluous. It is shown that three layers create a reliable sigmoidal response progress curve from a wide variety of time-dependent signaling inputs arriving at the cell membrane, suggesting that natural selection may have favored signaling cascades as a parsimonious solution to the problem of generating switch-like behavior in a noisy environment.
ContributorsYoung, Jonathan Trinity (Author) / Armbruster, Dieter (Thesis advisor) / Platte, Rodrigo (Committee member) / Nagy, John (Committee member) / Baer, Steven (Committee member) / Taylor, Jesse (Committee member) / Arizona State University (Publisher)
Created2013
Description
Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
ContributorsOrr, Adam James (Author) / Cartwright, Reed (Thesis advisor) / Wilson, Melissa (Committee member) / Kusumi, Kenro (Committee member) / Taylor, Jesse (Committee member) / Pfeifer, Susanne (Committee member) / Arizona State University (Publisher)
Created2020