Matching Items (77)
Description
Infections caused by the Hepatitis C Virus (HCV) are very common worldwide, affecting up to 3% of the population. Chronic infection of HCV may develop into liver cirrhosis and liver cancer which is among the top five of the most common cancers. Therefore, vaccines against HCV are under intense study in order to prevent HCV from harming people's health. The envelope protein 2 (E2) of HCV is thought to be a promising vaccine candidate because it can directly bind to a human cell receptor and plays a role in viral entry. However, the E2 protein production in cells is inefficient due to its complicated matured structure. Folding of E2 in the endoplasmic reticulum (ER) is often error-prone, resulting in production of aggregates and misfolded proteins. These incorrect forms of E2 are not functional because they are not able to bind to human cells and stimulate antibody response to inhibit this binding. This study is aimed to overcome the difficulties of HCV E2 production in plant system. Protein folding in the ER requires great assistance from molecular chaperones. Thus, in this study, two molecular chaperones in the ER, calreticulin and calnexin, were transiently overexpressed in plant leaves in order to facilitate E2 folding and production. Both of them showed benefits in increasing the yield of E2 and improving the quality of E2. In addition, poorly folded E2 accumulated in the ER may cause stress in the ER and trigger transcriptional activation of ER molecular chaperones. Therefore, a transcription factor involved in this pathway, named bZIP60, was also overexpressed in plant leaves, aiming at up-regulating a major family of molecular chaperones called BiP to assist protein folding. However, our results showed that BiP mRNA levels were not up-regulated by bZIP60, but they increased in response to E2 expression. The Western blot analysis also showed that overexpression of bZIP60 had a small effect on promoting E2 folding. Overall, this study suggested that increasing the level of specific ER molecular chaperones was an effective way to promote HCV E2 protein production and maturation.
ContributorsHong, Fan (Author) / Mason, Hugh (Thesis advisor) / Gaxiola, Roberto (Committee member) / Chang, Yung (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
While the suicide rate in Mexico is relatively low when compared to countries throughout the world, it is increasing at an alarming pace. Unfortunately, the amount of suicide research focused on Mexican populations is relatively scarce. Using a sample of high school students living in Guanajuato, Mexico, this study explored the relationship between recent suicidal ideation and three factors that previous research in other countries has connected to suicide: Migration aspirations, religiosity, and sexual behavior. Using multiple and logistic regression, the results indicated the following: 1) Recent suicidal ideation predicted increased migration aspirations, 2) higher levels of external religiosity predicted lower odds of recent suicidal ideation, and 3) stronger parent-child relationships predicted lower odds of recent suicidal ideation. The findings are discussed in light of the Bronfenbrenner's ecological systems theory, Bogenschneider's risk/protection model, and Stark's religious commitment theory.
ContributorsHoffman, Steven (Author) / Marsiglia, Flavio F (Thesis advisor) / Ayón, Cecilia (Committee member) / García-Pérez, Maria Hilda (Committee member) / Arizona State University (Publisher)
Created2011
Description
A synbody is a newly developed protein binding peptide which can be rapidly produced by chemical methods. The advantages of the synbody producing process make it a potential human proteome binding reagent. Most of the synbodies are designed to bind to specific proteins. The peptides incorporated in a synbody are discovered with peptide microarray technology. Nevertheless, the targets for unknown synbodies can also be discovered by searching through a protein mixture. The first part of this thesis mainly focuses on the process of target searching, which was performed with immunoprecipitation assays and mass spectrometry analysis. Proteins are pulled down from the cell lysate by certain synbodies, and then these proteins are identified using mass spectrometry. After excluding non-specific bindings, the interaction between a synbody and its real target(s) can be verified with affinity measurements. As a specific example, the binding between 1-4-KCap synbody and actin was discovered. This result proved the feasibility of the mass spectrometry based method and also suggested that a high throughput synbody discovery platform for the human proteome could be developed. Besides the application of synbody development, the peptide microarray technology can also be used for immunosignatures. The composition of all types of antibodies existing in one's blood is related to an individual's health condition. A method, called immunosignaturing, has been developed for early disease diagnosis based on this principle. CIM10K microarray slides work as a platform for blood antibody detection in immunosignaturing. During the analysis of an immunosignature, the data from these slides needs to be validated by using landing light peptides. The second part of this thesis focuses on the validation of the data. A biotinylated peptide was used as a landing light on the new CIM10K slides. The data was collected in several rounds of tests and indicated that the variation among landing lights was significantly reduced by using the newly prepared biotinylated peptide compared with old peptide mixture. Several suggestions for further landing light improvement are proposed based on the results.
ContributorsSun, Minyao (Author) / Johnston, Stephen Albert (Thesis advisor) / Diehnelt, Chris Wayne (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
Immunosignaturing is a new immunodiagnostic technology that uses random-sequence peptide microarrays to profile the humoral immune response. Though the peptides have little sequence homology to any known protein, binding of serum antibodies may be detected, and the pattern correlated to disease states. The aim of my dissertation is to analyze the factors affecting the binding patterns using monoclonal antibodies and determine how much information may be extracted from the sequences. Specifically, I examined the effects of antibody concentration, competition, peptide density, and antibody valence. Peptide binding could be detected at the low concentrations relevant to immunosignaturing, and a monoclonal's signature could even be detected in the presences of 100 fold excess naive IgG. I also found that peptide density was important, but this effect was not due to bivalent binding. Next, I examined in more detail how a polyreactive antibody binds to the random sequence peptides compared to protein sequence derived peptides, and found that it bound to many peptides from both sets, but with low apparent affinity. An in depth look at how the peptide physicochemical properties and sequence complexity revealed that there were some correlations with properties, but they were generally small and varied greatly between antibodies. However, on a limited diversity but larger peptide library, I found that sequence complexity was important for antibody binding. The redundancy on that library did enable the identification of specific sub-sequences recognized by an antibody. The current immunosignaturing platform has little repetition of sub-sequences, so I evaluated several methods to infer antibody epitopes. I found two methods that had modest prediction accuracy, and I developed a software application called GuiTope to facilitate the epitope prediction analysis. None of the methods had sufficient accuracy to identify an unknown antigen from a database. In conclusion, the characteristics of the immunosignaturing platform observed through monoclonal antibody experiments demonstrate its promise as a new diagnostic technology. However, a major limitation is the difficulty in connecting the signature back to the original antigen, though larger peptide libraries could facilitate these predictions.
ContributorsHalperin, Rebecca (Author) / Johnston, Stephen A. (Thesis advisor) / Bordner, Andrew (Committee member) / Taylor, Thomas (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
African Swine Fever (ASF), endemic in many African countries, is now spreading to other continents. Though ASF is capable of incurring serious economic losses in affected countries, no vaccine exists to provide immunity to animals. Disease control relies largely on rapid diagnosis and the implementation of movement restrictions and strict eradication programs. Developing a scalable, accurate and low cost diagnostic for ASF will be of great help for the current situation. CIM's 10K random peptide microarray is a new high-throughput platform that allows systematic investigations of immune responses associated with disease and shows promise as a diagnostic tool. In this study, this new technology was applied to characterize the immune responses of ASF virus (ASFV) infections and immunizations. Six sets of sera from ASFV antigen immunized pigs, 6 sera from infected pigs and 20 sera samples from unexposed pigs were tested and analyzed statistically. Results show that both ASFV antigen immunized pigs and ASFV viral infected pigs can be distinguished from unexposed pigs. Since it appears that immune responses to other viral infections are also distinguishable on this platform, it holds the potential of being useful in developing a new ASF diagnostic. The ability of this platform to identify specific ASFV antibody epitopes was also explored. A subtle motif was found to be shared among a set of peptides displaying the highest reactivity for an antigen specific antibody. However, this motif does not seem to match with any antibody epitopes predicted by a linear antibody epitope prediction.
ContributorsXiao, Liang (Author) / Sykes, Kathryn (Thesis advisor) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
Each year, millions of aging women will experience menopause, a transition from reproductive capability to reproductive senescence. In women, this transition is characterized by depleted ovarian follicles, declines in levels of sex hormones, and a dysregulation of gonadotrophin feedback loops. Consequently, menopause is accompanied by hot flashes, urogenital atrophy, cognitive decline, and other symptoms that reduce quality of life. To ameliorate these negative consequences, estrogen-containing hormone therapy is prescribed. Findings from clinical and pre-clinical research studies suggest that menopausal hormone therapies can benefit memory and associated neural substrates. However, findings are variable, with some studies reporting null or even detrimental cognitive and neurobiological effects of these therapies. Thus, at present, treatment options for optimal cognitive and brain health outcomes in menopausal women are limited. As such, elucidating factors that influence the cognitive and neurobiological effects of menopausal hormone therapy represents an important need relevant to every aging woman. To this end, work in this dissertation has supported the hypothesis that multiple factors, including post-treatment circulating estrogen levels, experimental handling, type of estrogen treatment, and estrogen receptor activity, can impact the realization of cognitive benefits with Premarin hormone therapy. We found that the dose-dependent working memory benefits of subcutaneous Premarin administration were potentially regulated by the ratios of circulating estrogens present following treatment (Chapter 2). When we administered Premarin orally, it impaired memory (Chapter 3). Follow-up studies revealed that this impairment was likely due to the handling associated with treatment administration and the task difficulty of the memory measurement used (Chapters 3 and 4). Further, we demonstrated that the unique cognitive impacts of estrogens that become increased in circulation following Premarin treatments, such as estrone (Chapter 5), and their interactions with the estrogen receptors (Chapter 6), may influence the realization of hormone therapy-induced cognitive benefits. Future directions include assessing the mnemonic effects of: 1) individual biologically relevant estrogens and 2) clinically-used bioidentical hormone therapy combinations of estrogens. Taken together, information gathered from these studies can inform the development of novel hormone therapies in which these parameters are optimized.
ContributorsEngler-Chiurazzi, Elizabeth (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Sanabria, Federico (Committee member) / Olive, Michael F (Committee member) / Hoffman, Steven (Committee member) / Arizona State University (Publisher)
Created2013
Description
We propose a novel solution to prevent cancer by developing a prophylactic cancer. Several sources of antigens for cancer vaccines have been published. Among these, antigens that contain a frame-shift (FS) peptide or viral peptide are quite attractive for a variety of reasons. FS sequences, from either mistake in RNA processing or in genomic DNA, may lead to generation of neo-peptides that are foreign to the immune system. Viral peptides presumably would originate from exogenous but integrated viral nucleic acid sequences. Both are non-self, therefore lessen concerns about development of autoimmunity. I have developed a bioinformatical approach to identify these aberrant transcripts in the cancer transcriptome. Their suitability for use in a vaccine is evaluated by establishing their frequencies and predicting possible epitopes along with their population coverage according to the prevalence of major histocompatibility complex (MHC) types. Viral transcripts and transcripts with FS mutations from gene fusion, insertion/deletion at coding microsatellite DNA, and alternative splicing were identified in NCBI Expressed Sequence Tag (EST) database. 48 FS chimeric transcripts were validated in 50 breast cell lines and 68 primary breast tumor samples with their frequencies from 4% to 98% by RT-PCR and sequencing confirmation. These 48 FS peptides, if translated and presented, could be used to protect more than 90% of the population in Northern America based on the prediction of epitopes derived from them. Furthermore, we synthesized 150 peptides that correspond to FS and viral peptides that we predicted would exist in tumor patients and we tested over 200 different cancer patient sera. We found a number of serological reactive peptide sequences in cancer patients that had little to no reactivity in healthy controls; strong support for the strength of our bioinformatic approach. This study describes a process used to identify aberrant transcripts that lead to a new source of antigens that can be tested and used in a prophylactic cancer vaccine. The vast amount of transcriptome data of various cancers from the Cancer Genome Atlas (TCGA) project will enhance our ability to further select better cancer antigen candidates.
ContributorsLee, HoJoon (Author) / Johnston, Stephen A. (Thesis advisor) / Kumar, Sudhir (Committee member) / Miller, Laurence (Committee member) / Stafford, Phillip (Committee member) / Sykes, Kathryn (Committee member) / Arizona State University (Publisher)
Created2012
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method proposed to screen and detect lung cancer, eliminating the risks associated with LDCT scans. Known and blinded primary blood sera from participants with lung cancer and no cancer were run on peptide microarrays and analyzed. Immunosignatures for each known sample collectively indicated 120 peptides unique to lung cancer and non-cancer participants. These 120 peptides were used to determine the status of the blinded samples. Verification of the results from Vanderbilt is pending.
ContributorsNguyen, Geneva Trieu (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05
Description
Is it possible to treat the mouth as a natural environment, and determine new methods to keep the microbiome in check? The need for biodiversity in health may suggest that every species carries out a specific function that is required to maintain equilibrium and homeostasis within the oral cavity. Furthermore, the relationship between the microbiome and its host is mutually beneficial because the host is providing microbes with an environment in which they can flourish and, in turn, keep their host healthy. Reviewing examples of larger scale environmental shifts could provide a window by which scientists can make hypotheses. Certain medications and healthcare treatments have been proven to cause xerostomia. This disorder is characterized by a dry mouth, and known to be associated with a change in the composition, and reduction, of saliva. Two case studies performed by Bardow et al, and Leal et al, tested and studied the relationships of certain medications and confirmed their side effects on the salivary glands [2,3]. Their results confirmed a relationship between specific medicines, and the correlating complaints of xerostomia. In addition, Vissink et al conducted case studies that helped to further identify how radiotherapy causes hyposalivation of the salivary glands [4]. Specifically patients that have been diagnosed with oral cancer, and are treated by radiotherapy, have been diagnosed with xerostomia. As stated prior, studies have shown that patients having an ecologically balanced and diverse microbiome tend to have healthier mouths. The oral cavity is like any biome, consisting of commensalism within itself and mutualism with its host. Due to the decreased salivary output, caused by xerostomia, increased parasitic bacteria build up within the oral cavity thus causing dental disease. Every human body contains a personalized microbiome that is essential to maintaining health but capable of eliciting disease. The Human Oral Microbiomics Database (HOMD) is a set of reference 16S rRNA gene sequences. These are then used to define individual human oral taxa. By conducting metagenomic experiments at the molecular and cellular level, scientists can identify and label micro species that inhabit the mouth during parasitic outbreaks or a shifting of the microbiome. Because the HOMD is incomplete, so is our ability to cure, or prevent, oral disease. The purpose of the thesis is to research what is known about xerostomia and its effects on the complex microbiome of the oral cavity. It is important that researchers determine whether this particular perspective is worth considering. In addition, the goal is to create novel experiments for treatment and prevention of dental diseases.
ContributorsHalcomb, Michael Jordan (Author) / Chen, Qiang (Thesis director) / Steele, Kelly (Committee member) / Barrett, The Honors College (Contributor) / College of Letters and Sciences (Contributor)
Created2015-05