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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

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
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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

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
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Description
Historically, studies of condition-dependent signals in animals have been male-centric, but recent work suggests that female ornaments can also communicate individual quality (e.g., disease state, fecundity). There has been a surge of interest in how urbanization alters signaling traits, but we know little about if and how cities affect signal

Historically, studies of condition-dependent signals in animals have been male-centric, but recent work suggests that female ornaments can also communicate individual quality (e.g., disease state, fecundity). There has been a surge of interest in how urbanization alters signaling traits, but we know little about if and how cities affect signal expression in female animals. We measured carotenoid-based plumage coloration and coccidian (Isospora spp) parasite burden in desert and city populations of house finches to examine urban impacts on male and female health and attractiveness. In earlier work, we showed that male house finches are less colorful and more parasitized in the city, and we again detected that pattern in this study for males. However, though city females are also less colorful than their rural counterparts, we found that rural females were more parasitized. Also, regardless of sex and unlike rural birds, more colorful birds in the city were more heavily infected with coccidia. These results show that urban environments can disrupt signal honesty in female animals and highlight the need for more studies on how cities affect disease and condition-dependent traits in both male and female animals.
ContributorsSykes, Brooke Emma (Author) / McGraw, Kevin (Thesis director) / Sweazea, Karen (Committee member) / Hutton, Pierce (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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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

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
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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

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
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There are two electrophysiological states of sleep in birds (rapid-eye-movement sleep [REM] and slow-wave sleep [SWS]), which have different functions and costs. REM improves memory consolidation, while SWS is neuro-restorative but also exposes the animal to more risk during this deep-sleep phase. Birds who sleep in more exposed microsites are known

There are two electrophysiological states of sleep in birds (rapid-eye-movement sleep [REM] and slow-wave sleep [SWS]), which have different functions and costs. REM improves memory consolidation, while SWS is neuro-restorative but also exposes the animal to more risk during this deep-sleep phase. Birds who sleep in more exposed microsites are known to invest proportionally less in SWS (presumably to ensure proper vigilance), but otherwise little else is known about the ecological or behavioral predictors of how much time birds devote to REM v. SWS sleep. In this comparative analysis, we examine how proportional time spent in SWS v. REM is related to brain mass and duration of the incubation period in adults. Brain mass and incubation period were chosen as predictors of sleep state investment because brain mass is positively correlated with body size (and may show a relationship between physical development and sleep) and incubation period can be a link used to show similarities and differences between birds and mammals (using mammalian gestation period). We hypothesized that (1) species with larger brains (relative to body size and also while controlling for phylogeny) would have higher demands for information processing, and possibly proportionally outweigh neuro-repair, and thus devote more time to REM and that (2) species with longer incubation periods would have proportionally more REM due to the extended time required for overnight predator vigilance (and not falling into deep sleep) while on the nest. We found, using neurophysiological data from literature on 27 bird species, that adults from species with longer incubation periods spent proportionally more time in REM sleep, but that relative brain size was not significantly associated with relative time spent in REM or SWS. We therefore provide evidence that mammalian and avian REM in response to incubation/gestation period have convergently evolved. Our results suggest that overnight environmental conditions (e.g. sleep site exposure) might have a greater effect on sleep parameters than gross morphological attributes.
ContributorsRaiffe, Joshua Sapell (Author) / McGraw, Kevin (Thesis director) / Deviche, Pierre (Committee member) / Hutton, Pierce (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Humans have greatly altered the night-time photic environment via the production of artificial light at night (ALAN; e.g. street lights, car traffic, billboards, lit buildings). ALAN is problematic because it may significantly alter the seasonal/daily physiological rhythms or behaviors of animals. There has been considerable interest in the impacts of

Humans have greatly altered the night-time photic environment via the production of artificial light at night (ALAN; e.g. street lights, car traffic, billboards, lit buildings). ALAN is problematic because it may significantly alter the seasonal/daily physiological rhythms or behaviors of animals. There has been considerable interest in the impacts of ALAN on health in humans and lab animals, but most such work has centered on adults and we know comparatively little about effects on young animals. We exposed 3-week-old king quail (Excalfactoria chinensis) to a constant overnight blue-light regime for 6 weeks and assessed weekly bactericidal activity of plasma against Escherichia coli - a commonly employed metric of innate immunity in animals. We found that chronic ALAN exposure significantly increased immune function, and that this elevation in immune performance manifested at different developmental time points in males and females. These results counter the pervasive notion that overnight light exposure is universally physiologically harmful to diurnal organisms and indicate that ALAN can provide sex-specific, short-term immunological boosts to developing animals.
ContributorsSaini, Chandan (Author) / McGraw, Kevin (Thesis director) / Hutton, Pierce (Committee member) / Sweazea, Karen (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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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

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
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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

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
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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

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