Matching Items (113)
Description
Ebola hemorrhagic fever (EHF) is a severe and often fatal disease in human and nonhuman primates, caused by the Ebola virus. Approximately 30 years after the first epidemic, there is no vaccine or therapeutic medication approved to counter the Ebola virus. In this dissertation, a geminiviral replicon system was used to produce Ebola immune complex (EIC) in plant leaves and tested it as an Ebola vaccine. The EIC was produced in Nicotiana benthamiana leaves by fusing Ebola virus glycoprotein (GP1) to the C-terminus of heavy chain of 6D8 monoclonal antibody (mAb), which is specific to the 6D8 epitope of GP1, and co-expressing the fusion with the light chain of 6D8 mAb. EIC was purified by ammonium sulfate precipitation and protein A or protein G affinity chromatography. EIC was shown to be immunogenic in mice, but the level of antibody against Ebola virus was not sufficient to protect the mice from lethal the Ebola challenge. Hence, different adjuvants were tested in order to improve the immunogenicity of the EIC. Among several adjuvants that we used, Poly(I:C), which is a synthetic analog of double-stranded ribonucleic acid that can interact with a Toll-like receptor 3, strongly increased the efficacy of our Ebola vaccine. The mice immunized with EIC co-administered with Poly(I:C) produced high levels of neutralizing anti-Ebola IgG, and 80% of the mice were protected from the lethal Ebola virus challenge. Moreover, the EIC induced a predominant T-helper type 1 (Th1) response, whereas Poly(I:C) co-delivered with the EIC stimulated a mixed Th1/Th2 response. This result suggests that the protection against lethal Ebola challenge requires both Th1 and Th2 responses. In conclusion, this study demonstrated that the plant-produced EIC co-delivered with Poly(I:C) induced strong and protective immune responses to the Ebola virus in mice. These results support plant-produced EIC as a good vaccine candidate against the Ebola virus. It should be pursued further in primate studies, and eventually in clinical trials.
ContributorsPhoolcharoen, Waranyoo (Author) / Mason, Hugh S (Thesis advisor) / Chen, Qiang (Thesis advisor) / Arntzen, Charles J. (Committee member) / Change, Yung (Committee member) / Ma, Julian (Committee member) / Arizona State University (Publisher)
Created2010
Description
Coronavirus disease 2019 (COVID-19), an illness caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2), has been responsible for significant social and economic
disruption, prompting an urgent search for therapeutic solutions. The spike protein of the virus
has been examined as an immunogenic target because of its role in viral binding and fusion
necessary for infection of host cells. Previous studies have identified a recombinant protein
(denoted as S1) that has been shown to potentially induce a neutralizing antibody response by
mimicking the structure of the SARS-CoV-2 spike protein. We have produced the S1 in plants
using agroinfiltration, a plant transformation technique whereby plasmid-containing
Agrobacterium tumefaciens is injected into Nicotiana benthamiana plants, resulting in transfer of
the desired gene from bacteria to plant cells. S1 was expressed to high levels within 5 days of
infiltration, and Western blot analysis showed recognition of the S1 by an anti-S1 antibody.
ELISA results exhibited increased binding activity to anti-S1 with increasing concentrations of
S1, indicating their specific interaction. This ongoing study will demonstrate the potential of a
plant-produced S1 as a vaccine, therapeutic, and diagnostic tool against COVID-19 that is not
only effective, but also cost-efficient and scalable in comparison to conventional mammalian cell
culture production methods.
coronavirus 2 (SARS-CoV-2), has been responsible for significant social and economic
disruption, prompting an urgent search for therapeutic solutions. The spike protein of the virus
has been examined as an immunogenic target because of its role in viral binding and fusion
necessary for infection of host cells. Previous studies have identified a recombinant protein
(denoted as S1) that has been shown to potentially induce a neutralizing antibody response by
mimicking the structure of the SARS-CoV-2 spike protein. We have produced the S1 in plants
using agroinfiltration, a plant transformation technique whereby plasmid-containing
Agrobacterium tumefaciens is injected into Nicotiana benthamiana plants, resulting in transfer of
the desired gene from bacteria to plant cells. S1 was expressed to high levels within 5 days of
infiltration, and Western blot analysis showed recognition of the S1 by an anti-S1 antibody.
ELISA results exhibited increased binding activity to anti-S1 with increasing concentrations of
S1, indicating their specific interaction. This ongoing study will demonstrate the potential of a
plant-produced S1 as a vaccine, therapeutic, and diagnostic tool against COVID-19 that is not
only effective, but also cost-efficient and scalable in comparison to conventional mammalian cell
culture production methods.
ContributorsNguyen, Katherine (Author) / Chen, Qiang (Thesis director) / Ghirlanda, Giovanna (Committee member) / Jugler, Collin (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Plant viral vectors have previously been used to produce high expression levels of antibodies and other proteins of interest. By utilizing a transformed Agrobacterium with the vector containing the protein of interest for infiltration, viral vectors can easily reach the plant cells making it an effective form of transient protein expression. For this project two different plant viral vectors were compared; the geminiviral vector derived from Bean yellow dwarf virus (BeYDV) and the MagnICON vector system derived from Tobacco Mosaic Virus(TMV) and Potato Virus X(PVX). E16, an antibody against West Nile virus, has previously been expressed using both systems but expression levels between the systems were not directly compared. Agrobacterium tumefaciens EHA105 cells were transformed with both systems and expression levels of E16 were quantified using ELISAs. Results showed very low expression levels of E16 using the geminiviral vector indicating a need for further investigation into the clone used as previous studies reported much higher expression levels with the system.
ContributorsMurphy, Skylar (Author) / Chen, Qiang (Thesis director) / Jugler, Collin (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Mitochondrial methionyl-tRNA-formyltransferase (MTFMT) is essential for mitochondrial protein translation. The MTFMT gene encodes for an enzyme of the same name, which acts to formylate the methionine of mitochondrial Met-tRNA(Met). In Homo sapiens, MTFMT-formylated-tRNA is an initiator and elongator for the synthesis of 13 mitochondrially-encoded proteins in complexes I, III and IV of the ETC. To understand this mechanism, it is necessary to perform a comprehensive analysis of energy metabolism and oxidative phosphorylation (OXPHOS) among impacted patients. Alterations to this gene vary, with the most documented as a single-splice-site mutation (c.626C>T). Here, we discuss MTFMT involvement in mitochondrial protein translation and neurodegenerative disorders, such as Leigh Syndrome and combined OXPHOS deficiency, in two families. We aim to delineate the impact of OXPHOS dysfunction in patients presenting with MTFMT mutation.
ContributorsChain, Kelsey (Author) / Chen, Qiang (Thesis director) / Rangasamy, Sampathkumar (Committee member) / Narayanan, Vinodh (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
A chimeric, humanized monoclonal antibody that recognizes a highly conserved fusion loop found on flaviviruses was constructed with a geminiviral replicon and transiently expressed in Nicotiana benthamiana plants through Agrobacterium tumefaciens infiltration. Characterization and expression studies were then conducted to confirm correct assembly of the antibody. Once the antibody was purified, an ELISA was conducted to validate that the antibody was able to bind to the flavivirus fusion loop.
ContributorsPardhe, Mary (Author) / Mason, Hugh (Thesis director) / Chen, Qiang (Committee member) / Mor, Tsafrir (Committee member) / School of Life Sciences (Contributor) / Department of Information Systems (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Biomarkers are the cornerstone of modern-day medicine. They are defined as any biological substance in or outside the body that gives insight to the body's condition. Doctors and researchers can measure specific biomarkers to diagnose and treat patients, such as the concentration of hemoglobin Alc and its connection to diabetes. There are a variety of methods, or assays, to detect biomarkers, but the most common assay is enzyme-linked immunosorbent assay (ELISA). A new-generation assay termed mass spectrometric immunoassay (MSIA) can measure proteoforms, the different chemical variations of proteins, and their relative abundance. ELISA on the other hand measures the overall concentration of protein in the sample. Measuring each of the proteoforms of a protein is important because only one or two variations could be biologically significant and/or cause diseases. However, running MSIA is expensive. For this reason, an alternative plate-based MSIA technique was tested for its ability to detect the proteoforms of a protein called apolipoprotein C-III (ApoC-III). This technique combines the protein capturing procedure of ELISA to isolate the protein with detection in a mass spectrometer. A larger amount of ApoC-III present in the body indicates a considerable risk for coronary heart disease. The precision of the assay is determined on the coefficient of variation (CV). A CV value is the ratio of standard deviation in relation to the mean, represented as a percentage. The smaller the percentage, the less variation the assay has, and therefore the more ability it has to detect subtle changes in the biomarker. An accepted CV would be less than 10% for single-day tests (intra-day) and less than 15% for multi-day tests (inter-day). The plate-based MSIA was started by first coating a 96-well round bottom plate with 2.5 micrograms of ApoC-III antibody. Next, a series of steps were conducted: a buffer wash, then the sample incubation, followed by another buffer wash and two consecutive water washes. After the final wash, the wells were filled with a MALDI matrix, then spotted onto a gold plate to dry. The dry gold target was then placed into a MALDI-TOF mass spectrometer to produce mass spectra for each spot. The mass spectra were calibrated and the area underneath each of the four peaks representing the ApoC-III proteoforms was exported as an Excel file. The intra-day CV values were found by dividing the standard deviation by the average relative abundance of each peak. After repeating the same procedure for three more days, the inter-day CVs were found using the same method. After completing the experiment, the CV values were all within the acceptable guidelines. Therefore, the plate-based MSIA is a viable alternative for finding proteoforms than the more expensive MSIA tips. To further validate this, additional tests will need to be conducted with different proteins and number of samples to determine assay flexibility.
ContributorsTieu, Luc (Author) / Borges, Chad (Thesis director) / Nedelkov, Dobrin (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Open source image analytics and data mining software are widely available but can be overly-complicated and non-intuitive for medical physicians and researchers to use. The ASU-Mayo Clinic Imaging Informatics Lab has developed an in-house pipeline to process medical images, extract imaging features, and develop multi-parametric models to assist disease staging and diagnosis. The tools have been extensively used in a number of medical studies including brain tumor, breast cancer, liver cancer, Alzheimer's disease, and migraine. Recognizing the need from users in the medical field for a simplified interface and streamlined functionalities, this project aims to democratize this pipeline so that it is more readily available to health practitioners and third party developers.
ContributorsBaer, Lisa Zhou (Author) / Wu, Teresa (Thesis director) / Wang, Yalin (Committee member) / Computer Science and Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Virus-Like Particles (VLPs) are self-assembling structures that lack the viral genetic material. Therefore they are safer and more immunogenic than other forms of vaccines. The Hepatitis B core (HBc) VLPs are a novel mechanism through which delivery of DNA-based human vaccines are plausible. Production of VLPs require recombinant, rapidly replicating, plant-based systems such as the geminiviral replicon system. This project entails the cloning process of HBc-DIII fusion protein, a VLP that should form Domain III of the Envelope protein on West Nile Virus, into deconstructed geminiviral vector. The cloning process includes the HBc-DIII fusion protein DNA isolation, restriction enzyme digestion with NcoI and SacI, PCR changing the NcoI site on the HBc-DIII insert to XbaI, sequencing, ligation into geminiviral vector and transformation into an agrobacterium strain. The major impediment to the cloning process was the presence of multiple bands instead of the expected two bands while doing restriction enzyme digests. The troubleshooting process enabled speculating that due to the excess of restriction enzymes in the digestion volume, some of the DNA was not digested completely. Hence, multiple bands were observed. However, sequencing analysis and further cloning process ensured the presence of HBc-DIII insert band (approximately 800bp) in the Gemini vector. Lastly, the construct HBc-DIII in Gemini vector was ensured to be in agrobacterium for further experiments such as agro-infiltration.
ContributorsSuresh Kumar, Reshma (Author) / Chen, Qiang (Thesis director) / Zhang, Peiming (Committee member) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Video object segmentation (VOS) is an important task in computer vision with a lot of applications, e.g., video editing, object tracking, and object based encoding. Different from image object segmentation, video object segmentation must consider both spatial and temporal coherence for the object. Despite extensive previous work, the problem is still challenging. Usually, foreground object in the video draws more attention from humans, i.e. it is salient. In this thesis we tackle the problem from the aspect of saliency, where saliency means a certain subset of visual information selected by a visual system (human or machine). We present a novel unsupervised method for video object segmentation that considers both low level vision cues and high level motion cues. In our model, video object segmentation can be formulated as a unified energy minimization problem and solved in polynomial time by employing the min-cut algorithm. Specifically, our energy function comprises the unary term and pair-wise interaction energy term respectively, where unary term measures region saliency and interaction term smooths the mutual effects between object saliency and motion saliency. Object saliency is computed in spatial domain from each discrete frame using multi-scale context features, e.g., color histogram, gradient, and graph based manifold ranking. Meanwhile, motion saliency is calculated in temporal domain by extracting phase information of the video. In the experimental section of this thesis, our proposed method has been evaluated on several benchmark datasets. In MSRA 1000 dataset the result demonstrates that our spatial object saliency detection is superior to the state-of-art methods. Moreover, our temporal motion saliency detector can achieve better performance than existing motion detection approaches in UCF sports action analysis dataset and Weizmann dataset respectively. Finally, we show the attractive empirical result and quantitative evaluation of our approach on two benchmark video object segmentation datasets.
ContributorsWang, Yilin (Author) / Li, Baoxin (Thesis advisor) / Wang, Yalin (Committee member) / Cleveau, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
Learning from high dimensional biomedical data attracts lots of attention recently. High dimensional biomedical data often suffer from the curse of dimensionality and have imbalanced class distributions. Both of these features of biomedical data, high dimensionality and imbalanced class distributions, are challenging for traditional machine learning methods and may affect the model performance. In this thesis, I focus on developing learning methods for the high-dimensional imbalanced biomedical data. In the first part, a sparse canonical correlation analysis (CCA) method is presented. The penalty terms is used to control the sparsity of the projection matrices of CCA. The sparse CCA method is then applied to find patterns among biomedical data sets and labels, or to find patterns among different data sources. In the second part, I discuss several learning problems for imbalanced biomedical data. Note that traditional learning systems are often biased when the biomedical data are imbalanced. Therefore, traditional evaluations such as accuracy may be inappropriate for such cases. I then discuss several alternative evaluation criteria to evaluate the learning performance. For imbalanced binary classification problems, I use the undersampling based classifiers ensemble (UEM) strategy to obtain accurate models for both classes of samples. A small sphere and large margin (SSLM) approach is also presented to detect rare abnormal samples from a large number of subjects. In addition, I apply multiple feature selection and clustering methods to deal with high-dimensional data and data with highly correlated features. Experiments on high-dimensional imbalanced biomedical data are presented which illustrate the effectiveness and efficiency of my methods.
ContributorsYang, Tao (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013