Matching Items (57)
Description
The influenza virus is the main cause of thousands of deaths each year in the United States, and far more hospitalizations. Immunization has helped in protecting people from this virus and there are a number of therapeutics which have proven effective in aiding people infected with the virus. However, these therapeutics are subject to various limitations including increased resistance, limited supply, and significant side effects. A new therapeutic is needed which addresses these problems and protects people from the influenza virus. Synbodies, synthetic antibodies, may provide a means to achieve this goal. Our group has produced a synbody, the 5-5 synbody, which has been shown to bind to and inhibit the influenza virus. The direct pull down and western blot techniques were utilized to investigate how the synbody bound to the influenza virus. Our research showed that the 5-5 synbody bound to the influenza nucleoprotein (NP) with a KD of 102.9 ± 74.48 nM. It also showed that the synbody bound strongly to influenza viral extract from two different strains of the virus, the Puerto Rico (H1N1) and Sydney (H3N2) strains. This research demonstrated that the 5-5 synbody binds with high affinity to NP, which is important because influenza NP is highly conserved between various strains of the virus and plays an important role in the replication of the viral genome. It also demonstrated that this binding is conserved between various strains of the virus, indicating that the 5-5 synbody potentially could bind many different influenza strains. This synbody may have potential as a therapeutic in the future if it is able to demonstrate similar binding in vivo.
ContributorsKombe, Albert E. (Author) / Diehnelt, Chris (Thesis director) / Woodbury, Neal (Committee member) / Legutki, Bart (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of International Letters and Cultures (Contributor)
Created2014-05
Description
One of the major challenges that were yet to be solved for solid phase peptide synthesis was the lack of an efficient peptide sequencing technique that was less hazardous, easier to perform , and was more cost-effective. Sequencing peptides were held important in the field of Chemistry and Biochemistry because it aided in drug discovery, finding ligands that bind to a specific target protein and finding alternative agents in transporting molecules to its desired location. Therefore, the overall purpose of this experiment was to develop a method of solid phase sequencing technique that was more environmental friendly, sequences at a faster rate, and was more cost-effective.
ContributorsCordovez, Lalaine Anne Ordiz (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Legutki, Joseph Barten (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05
Description
Background
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
ContributorsNandakumar, Vivek (Author) / Kelbauskas, Laimonas (Author) / Hernandez, Kathryn (Author) / Lintecum, Kelly (Author) / Senechal, Patti (Author) / Bussey, Kimberly (Author) / Davies, Paul (Author) / Johnson, Roger (Author) / Meldrum, Deirdre (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor) / Biodesign Institute (Contributor) / Center for Biosignatures Discovery Automation (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Department of Physics (Contributor)
Created2012-01-05
Description
Dielectrophoresis has been shown in the recent past to successfully separate bioparticles of very subtle differences at high resolutions using biophysical forces. In this study, we test the biophysical differences of methicillin resistant and susceptible Staph. aureus that are known to have very similar genomes by using a modified gradient insulator-based dielectrophoresis device (g-iDEP). MRSA is commonly seen in hospitals and is the leading killer of infectious bacteria, claiming the lives of around 10,000 people annually. G-iDEP improves many capabilities within the DEP field including sample size, cost, ease of use and analysis time. This is a promising foundation to creating a more clinically optimized diagnostic tool for both separation and detection of bacteria in the healthcare field. The capture on-set potential for fluorescently tagged MRSA (801 ± 34V) is higher than fluorescently tagged MSSA (610 ± 32V), resulting in a higher electrokinetic to dielectrophoretic mobility ratio for MRSA. Since the strains have proven to be genomically similar through sequencing, it is reasonable to attribute this significant biophysical difference to the added PBP2a enzyme in MRSA. These results are consistent with other bacterial studied within in this device and have proven to be reproducible.
ContributorsSmithers, Jared (Author) / Hayes, Mark (Thesis director) / Woodbury, Neal (Committee member) / School of Criminology and Criminal Justice (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Diabesity is a global epidemic affecting millions worldwide. Diabesity is the term given to the link between obesity and Type II diabetes. It is estimated that ~90% of patients diagnosed with Type II diabetes are overweight or have struggled with excess body fat in the past. Type II diabetes is characterized by insulin resistance which is an impaired response of the body to insulin that leads to high blood glucose levels. Adipose tissue, previously thought of as an inert tissue, is now recognized as a major endocrine organ with an important role in the body's immune response and the development of chronic inflammation. It is speculated that adipose tissue inflammation is a major contributor to insulin resistance particular to Type II diabetes. This literature review explores the popular therapeutic targets and marketed drugs for the treatment of Type II diabetes and their role in decreasing adipose tissue inflammation. rAGE is currently in pre-clinical studies as a possible target to combat adipose tissue inflammation due to its relation to insulin resistance. Metformin and Pioglitazone are two drugs already being marketed that use unique chemical pathways to increase the production of insulin and/or decrease blood glucose levels. Sulfonylureas is one of the first FDA approved drugs used in the treatment of Type II diabetes, however, it has been discredited due to its life-threatening side effects. Bariatric surgery is a form of invasive surgery to rid the body of excess fat and has shown to normalize blood glucose levels. These treatments are all secondary to lifestyle changes, such as diet and exercise which can help halt the progression of Type II diabetes patients.
ContributorsRobles, Alondra Maria (Author) / Woodbury, Neal (Thesis director) / Redding, Kevin (Committee member) / Allen, James (Committee member) / Hendrickson, Kirstin (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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
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