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Predicting the binding sites of proteins has historically relied on the determination of protein structural data. However, the ability to utilize binding data obtained from a simple assay and computationally make the same predictions using only sequence information would be more efficient, both in time and resources. The purpose of this study was to evaluate the effectiveness of an algorithm developed to predict regions of high-binding on proteins as it applies to determining the regions of interaction between binding partners. This approach was applied to tumor necrosis factor alpha (TNFα), its receptor TNFR2, programmed cell death protein-1 (PD-1), and one of its ligand PD-L1. The algorithms applied accurately predicted the binding region between TNFα and TNFR2 in which the interacting residues are sequential on TNFα, however failed to predict discontinuous regions of binding as accurately. The interface of PD-1 and PD-L1 contained continuous residues interacting with each other, however this region was predicted to bind weaker than the regions on the external portions of the molecules. Limitations of this approach include use of a linear search window (resulting in inability to predict discontinuous binding residues), and the use of proteins with unnaturally exposed regions, in the case of PD-1 and PD-L1 (resulting in observed interactions which would not occur normally). However, this method was overall very effective in utilizing the available information to make accurate predictions. The use of the microarray to obtain binding information and a computer algorithm to analyze is a versatile tool capable of being adapted to refine accuracy.
ContributorsBrooks, Meilia Catherine (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Ghirlanda, Giovanna (Committee member) / Department of Psychology (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Vitellogenin (vg) is a precursor protein of egg yolk in honeybees, but it is also known to have immunological functions. The purpose of this experiment was to determine the effect of vg on the viral load of deformed wing virus (DWV) in worker honey bees (Apis mellifera). I hypothesized that a reduction in vg expression would lead to an increase in the viral load. I collected 180 worker bees and split them into four groups: half the bees were subjected to a vg gene knockdown by injections of double stranded vg RNA, and the rest were injected with green fluorescent protein (gfp) double stranded RNA. Half of each group was thereafter injected with DWV, and half given a sham injection. The rate of mortality in all four groups was higher than expected, leaving only 17 bees total. I dissected these bees' fat bodies and extracted their RNA to test for vg and DWV. PCR results showed that, out of the small group of remaining bees, the levels of vg were not statistically different. Furthermore, both groups of virus-injected bees showed similar viral loads. Because of the high mortality rate bees and the lack of differing levels of vg transcript between experimental and control groups, I could not draw conclusions from these results. The high mortality could be caused by several factors: temperature-induced stress, repeated stress from the two injections, and stress from viral infection. In addition, it is possible that the vg dsRNA batch I used was faulty. This thesis exemplifies that information cannot safely be extracted when loss of sampling units result in a small datasets that do not represent the original sampling population.
ContributorsCrable, Emma Lewis (Author) / Amdam, Gro (Thesis director) / Wang, Ying (Committee member) / Dahan, Romain (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
The free-base tetra-tolyl-porphyrin and the corresponding cobalt and iron porphyrin complexes were synthesized and characterized to show that this class of compound can be promising, tunable catalysts for carbon dioxide reduction. During cyclic voltammetry experiments, the iron porphyrin showed an on-set of ‘catalytic current’ at an earlier potential than the cobalt porphyrin’s in organic solutions gassed with carbon dioxide. The cobalt porphyrin yielded larger catalytic currents, but at the same potential as the electrode. This difference, along with the significant changes in the porphyrin’s electronic, optical and redox properties, showed that its capabilities for carbon dioxide reduction can be controlled by metal ions, allotting it unique opportunities for applications in solar fuels catalysis and photochemical reactions.
ContributorsSkibo, Edward Kim (Author) / Moore, Gary (Thesis director) / Woodbury, Neal (Committee member) / School of Molecular Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
In Apis mellifera, gustatory responsiveness to sucrose is a good indicator of learning ability \u2014 in that individuals with high sucrose responsiveness will typically form faster, longer-lasting associations with conditioned stimulus than individuals with a low sucrose responsiveness. The purpose of this study was to determine whether experience with olfactory conditioning had lasting effects on gustatory responsiveness. Groups were placed in an environment that would facilitate association of an odor to a sucrose reward, tested for retention, then tested for gustatory responsiveness. Control groups underwent the same testing schedule, but were not exposed to odor in the first environment. There was no significant difference in gustatory responsiveness between the two groups. Mann-Whitney tests were used to analyze the results, and though the mean GRS score was lower among the treatment group there was no significant trend, possibly due to small sample sizes.
ContributorsSeemann, J. H. (Author) / Amdam, Gro (Thesis director) / Smith, Brian (Committee member) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Genetic counseling is a medical field that was established in the 1970s, but whose demand is now growing exponentially due to modern genetic technology. We now have the ability to look into the human genetic code, detect the genotype of individuals, and use this knowledge to our benefit. However, Genetic testing results in a need for new ethical boundaries to be drawn. The idea of the "best possible conditions" of conceiving a child and whether this child has a right to not know are the two major ethical issues that will be focused on in order to analyze the ethical boundary that needs to be drawn for genetic counseling. In order to analyze these ethical issues, a focus group of Arizona State University students was organized. After producing results for the focus group, there are no true conclusions that can be drawn that applied to all of society. The focus group sample size was too small to produce a broad range of results and the participants were all Arizona State University Undergraduate students. However, it did become apparent that knowledge on these ethical issues is crucial in order to ensure they do not hinder the field of genetic counseling. It is predicted that in order to have the best outcome for the field of genetic counseling, genetic counselors themselves need to draw the ethical boundaries for the issues studied.
ContributorsBarker, Samantha (Author) / Amdam, Gro (Thesis director) / Bang, Christofer (Committee member) / Wang, Ying (Committee member) / Barrett, The Honors College (Contributor)
Created2016-05
Description
ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the abovementioned techniques were optimized. In addition, MALDI mass spectrometry based peptide synthesis characterization on semiconductor microchips was developed and novel applications of a CombiMatrix (CBMX) platform for electrochemically controlled synthesis were explored. We have investigated performance of 2-(2-nitrophenyl)propoxycarbonyl (NPPOC) derivatives as photo-labile protecting group. Specifically, influence of substituents on 4 and 5 positions of phenyl ring of NPPOC group on the rate of photolysis and the yield of the amine was investigated. The results indicated that substituents capable of forming a π-network with the nitro group enhanced the rate of photolysis and yield. Once such properly substituted NPPOC groups were used, the rate of photolysis/yield depended on the nature of protected amino group indicating that a different chemical step during the photo-cleavage process became the rate limiting step. We also focused on electrochemically-directed parallel synthesis of high-density peptide microarrays using the CBMX technology referred to above which uses electrochemically generated acids to perform patterned chemistry. Several issues related to peptide synthesis on the CBMX platform were studied and optimized, with emphasis placed on the reactions of electro-generated acids during the deprotection step of peptide synthesis. We have developed a MALDI mass spectrometry based method to determine the chemical composition of microarray synthesis, directly on the feature. This method utilizes non-diffusional chemical cleavage from the surface, thereby making the chemical characterization of high-density microarray features simple, accurate, and amenable to high-throughput. CBMX Corp. has developed a microarray reader which is based on electro-chemical detection of redox chemical species. Several parameters of the instrument were studied and optimized and novel redox applications of peptide microarrays on CBMX platform were also investigated using the instrument. These include (i) a search of metal binding catalytic peptides to reduce overpotential associated with water oxidation reaction and (ii) an immobilization of peptide microarrays using electro-polymerized polypyrrole.
ContributorsKumar, Pallav (Author) / Woodbury, Neal (Thesis advisor) / Allen, James (Committee member) / Johnston, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
Understanding why animals form social groups is a fundamental aim of sociobiology. To date, the field has been dominated by studies of kin groups, which have emphasized indirect fitness benefits as key drivers of grouping among relatives. Nevertheless, many animal groups are comprised of unrelated individuals. These cases provide unique opportunities to illuminate drivers of social evolution beyond indirect fitness, especially ecological factors. This dissertation combines behavioral, physiological, and ecological approaches to explore the conditions that favor group formation among non-kin, using as a model the facultatively social carpenter bee, Xylocopa sonorina. Using behavioral and genetic techniques, I found that nestmates in this species are often unrelated, and that non-kin groups form following extensive inter-nest migration.Group living may arise as a strategy to mitigate constraints on available breeding space. To test the hypothesis that nest construction is prohibitively costly for carpenter bees, I measured metabolic rates of excavating bees and used imaging techniques to quantify nest volumes. From these measurements, I found that nest construction is highly energetically costly, and that bees who inherit nests through social queuing experience substantial energetic savings. These costs are exacerbated by limitations on the reuse of existing nests. Using repeated CT scans of nesting logs, I examined changes in nest architecture over time and found that repeatedly inherited tunnels become indefensible to intruders, and are subsequently abandoned. Together, these factors underlie intense competition over available breeding space. The imaging analysis of nesting logs additionally revealed strong seasonal effects on social strategy, with social nesting dominating during winter. To test the hypothesis that winter social nesting arises from intrinsic physiological advantages of grouping, I experimentally manipulated social strategy in overwintering bees. I found that social bees conserve heat and body mass better than solitary bees, suggesting fitness benefits to grouping in cold, resource-scarce conditions. Together, these results suggest that grouping in X. sonorina arises from dynamic strategies to maximize direct fitness in response to harsh and/or competitive conditions. These studies provide empirical insights into the ecological conditions that favor non-kin grouping, and emphasize the importance of ecology in shaping sociality at its evolutionary origins.
ContributorsOstwald, Madeleine (Author) / Fewell, Jennifer H (Thesis advisor) / Amdam, Gro (Committee member) / Harrison, Jon (Committee member) / Pratt, Stephen (Committee member) / Kapheim, Karen (Committee member) / Arizona State University (Publisher)
Created2022
Description
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
Description
Speciation, or the process by which one population diverges into multiple populations that can no longer interbreed with each other, has brought about the incredible diversity of life. Mechanisms underlying this process can be more visible in the early stages of the speciation process. The mechanisms that restrict gene flow in highly mobile species with no absolute barriers to dispersal, especially marine species, are understudied. Similarly, human impacts are reshaping ecosystems globally, and we are only just beginning to understand the implications of these rapid changes on evolutionary processes. In this dissertation, I investigate patterns of speciation and evolution in two avian clades: a genus of widespread tropical seabirds (boobies, genus Sula), and two congeneric passerine species in an urban environment (cardinals, genus Cardinalis). First, I explore the prevalence of gene flow across land barriers within species and between sympatric species in boobies. I found widespread evidence of gene flow over all land barriers and between 3 species pairs. Next, I compared the effects of urbanization on the spatial distributions of two cardinal species, pyrrhuloxia (Cardinalis sinuatus) and northern cardinals (Cardinalis cardinalis), in Tucson, Arizona. I found that urbanization has different effects on the spatial distributions of two closely related species that share a similar environmental niche, and I identified environmental variables that might be driving this difference. Then I tested for effects of urbanization on color and size traits of these two cardinal species. In both of these species, urbanization has altered traits involved in signaling, heat tolerance, foraging, and maneuverability. Finally, I tested for evidence of selection on the urban populations of both cardinal species and found evidence of both parallel selection and introgression between the species, as well as selection on different genes in each species. The functions of the genes that experienced positive selection suggest that light at night, energetics, and air pollution may have acted as strong selective pressures on these species in the past. Overall, my dissertation emphasizes the role of introgression in the speciation process, identifies environmental stressors faced by wildlife in urban environments, and characterizes their evolutionary responses to those stressors.
ContributorsJackson, Daniel Nelson (Author) / McGraw, Kevin J (Thesis advisor) / Amdam, Gro (Committee member) / Sweazea, Karen (Committee member) / Taylor, Scott (Committee member) / Arizona State University (Publisher)
Created2023