Matching Items (96)
Description
Human papillomavirus (HPV) is the causative agent of cervical cancer. Persistent infection with high-risk HPV 16, 18 or 45 species is associated with the development and progression of cervical cancer. HPV genotyping and Pap smear tests are the regular methods used to detect pre-invasive cervical lesions, but there is a need for developing a rapid biomarker to profile immunity to these viruses. The viral E7 oncogene is expressed in most HPV-associated cancers and anti-E7 antibodies can be detected in the blood of patients with cervical cancer. This research was focused on viral E7 oncogene expression to be used in development of low-cost point of care tests, enabling patients from low resource settings to detect the asymptotic stage of cervical cancer and be able to seek treatment early. In order to produce the E7 protein in vitro to measure antibody levels, GST tagged E7 genes from HPV 16, 18 and 45 species were inserted into the pDEST15 vector and expressed in E. coli BL21DE3 cells that were induced with 1mM of IPTG. The E7-GST fused expressed protein was then purified using glutathione beads and resolved on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Protein expression was 5.8 \u03bcg/ml for HPV 16E7 in 500 ml culture and for the 500 ml culture of HPV 18 E7 and 45 E7 were 10.5 \u03bcg/ml and 10.5 \u03bcg/ml for HPV 18E7 and 45E7 respectively. High yield values are showing high expression levels of GST-tagged E7 recombinant protein which can be used for serotyping a number of individuals. This shows that HPV E7 can be produced in large quantities that can potentially be used in point of care tests that can help identify women at risk of cervical cancer. In conclusion, the E7 protein produced in this study can potentially be used to induce humoral responses in patients\u2019 sera for understanding the immune response of cervical cancer.
ContributorsMakuyana, Ntombizodwa (Author) / Anderson, Karen (Thesis director) / Ewaisha, Radwa (Committee member) / Varsani, Arvind (Committee member) / Hou, Ching-Wen (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
The International Space Station (ISS) utilizes recycled water for consumption, cleaning and air humidity control. The Environmental Control and Life Support Systems (ECLSS) have been rigorously tested at the NASA Johnson Space Center. Despite the advanced engineering of the water recovery system, bacterial biofilms have been recovered from this potable water source. Microbial contamination of potable water poses a potential threat to crew members onboard the ISS. Because astronauts have been found to have compromised immune systems, bacterial strains that would not typically be considered a danger must be carefully studied to better understand the mechanisms enabling their survival, including polymicrobial interactions. The need for a more thorough understanding of the effect of spaceflight environment on polymicrobial interactions and potential impact on crew health and vehicle integrity is heightened since 1) several potential pathogens have been isolated from the ISS potable water system, 2) spaceflight has been shown to induce unexpected alterations in microbial responses, and 3) emergent phenotypes are often observed when multiple bacterial species are co- cultured together, as compared to pure cultures of single species. In order to address these concerns, suitable growth media are required that will not only support the isolation of these microbes but also the ability to distinguish between them when grown as mixed cultures. In this study, selective and/or differential media were developed for bacterial isolates collected from the ISS potable water supply. In addition to facilitating discrimination between bacteria, the ideal media for each strain was intended to have a 100% recovery rate compared to traditional R2A media. Antibiotic and reagent susceptibility and resistance tests were conducted for the purpose of developing each individual medium. To study a wide range of targets, 12 antibiotics were selected from seven major classes, including penicillin, cephalosporins, fluoroquinolones, aminoglycosides, glycopeptides/lipoglycopeptides, macrolides/lincosamides/streptogramins, tetracyclines, in addition to seven unclassified antibiotics and three reagents. Once developed, medium efficacy was determined by means of growth curve experiments. The development of these media is a critical step for further research into the mechanisms utilized by these strains to survive the harsh conditions of the ISS water system. Furthermore, with an understanding of the complex nature of these polymicrobial communities, specific contamination targeting and control can be conducted to reduce the risk to crew members. Understanding these microbial species and their susceptibilities has potential application for future NASA human explorations, including those to Mars.
ContributorsKing, Olivia Grace (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, Mark (Committee member) / School of Sustainability (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
The Heliobacterial Reaction Center (HbRC) is the simplest Type I Reaction Center (RC) known today. However, upon illumination it has been found to produce menaquinol, and this has led to experiments investigating the function of this reduction scheme. The goal of the experiment was to investigate the mechanisms of menaquinol production through the use of Photosystem II (PSII) herbicides that are known to inhibit the QB quinone site in Type II RCs. Seven herbicides were chosen, and out of all of them terbuthylazine showed the greatest effect on the RC in isolated membranes when Transient Absorption Spectroscopy was used. In addition, terbuthylazine decreased menaquinone reduction to menaquinol by ~72%, slightly more than the reported effect of teburtryn (68%)1. In addition, terbuthylazine significantly impacted growth of whole cells under high light more than terbutryn.
ContributorsOdeh, Ahmad Osameh (Author) / Redding, Kevin (Thesis director) / Woodbury, Neal (Committee member) / Allen, James (Committee member) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
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
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
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
Globally, about two-thirds of the population is latently infected with herpes simplex virus type 1 (HSV-1). HSV-1 is a large double stranded DNA virus with a genome size of ~150kbp. Small defective genomes, which minimally contain an HSV-1 origin of replication and packaging signal, arise naturally via recombination during viral DNA replication. These small defective genomes can be mimicked by constructing a bacterial plasmid containing the HSV-1 origin of replication and packaging signal, transfecting these recombinant plasmids into mammalian cells, and infecting with a replicating helper virus. The absence of most viral genes in the amplicon vector allows large pieces of foreign DNA (up to 150kbp) to be incorporated. The HSV-1 amplicon is replicated and packaged by the helper virus to form HSV-1 particles containing the amplicon DNA. We constructed a novel HSV-1 amplicon vector system containing lambda phage-derived attR sites to facilitate insertion of transgenes by Invitrogen Gateway recombination. To demonstrate that the amplicon vectors work as expected, we packaged the vector constructs expressing Emerald GFP using the replication-competent helper viruses OK-14 or HSV-mScartlet-I-UL25 in Vero cells and demonstrate that the vector stock can subsequently transduce and express Emerald GFP. In further work, we will insert transgenes into the amplicon vector using Invitrogen Gateway recombination to study their functionality.
ContributorsVelarde, Kimberly (Author) / Hogue, Ian B (Thesis advisor) / Manfredsson, Fredric (Committee member) / Sandoval, Ivette (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2021
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
Caracals (Caracal caracal) are a felid species native to regions of southern Africa and western and central Asia. Despite their relatively high prevalence, the majority of research conducted on caracals has been undertaken on captive individuals, which encounter significantly different environments and exhibit different behaviors in comparison to caracals in the wild. Thereby, they likely have a vastly different virome. The goal of this study was to identify known and unknown DNA viruses associated with free-ranging caracals. Caracal fecal and organ samples were obtained from a caracal surveillance study undertaken in the Western Cape region of South Africa. Parasitic ticks found feeding on caracals were also obtained. Using a viral metagenomic informed approach, a novel circovirus (family Circoviridae) was detected and characterized in caracal fecal, kidney, spleen, and liver samples, as well as in ticks feeding on the caracals. To our knowledge, this is the first circovirus identified in caracals. The novel circovirus was determined to be closely related to a canine circovirus. These findings expand the knowledge of viral diversity and caracals and are greatly important to caracal conservation efforts as well as conservation efforts of other animals within their ecosystem.
ContributorsCollins, Courtney (Author) / Varsani, Arvind (Thesis director) / Dolby, Greer (Committee member) / Kraberger, Simona (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2022-05
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