Matching Items (128)
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Description
Antibodies are the immunoglobulins which are secreted by the B cells after a microbial invasion. They are stable and stays in the serum for a long time which makes them an excellent biomarker for disease diagnosis. Inflammatory bowel disease is a type of autoimmune disease where the immune system mistakenly

Antibodies are the immunoglobulins which are secreted by the B cells after a microbial invasion. They are stable and stays in the serum for a long time which makes them an excellent biomarker for disease diagnosis. Inflammatory bowel disease is a type of autoimmune disease where the immune system mistakenly attacks the commensal bacteria and leads to inflammation. We studied antibody response of 100 Crohn’s disease (CD), 100 ulcerative colitis (UC) and 100 healthy controls against 1,173 bacterial and 397 viral proteins. We found some anti-bacterial antibodies higher in CD compared to controls while some antibodies lower in UC compared to controls. We were able to build biomarker panels with AUCs of 0.81, 0.87, and 0.82 distinguishing CD vs. control, UC vs. control, and CD vs. UC, respectively. Subgroup analysis based on the Montreal classification revealed that penetrating CD behavior (B3), colonic CD location (L2), and extensive UC (E3) exhibited highest antibody reactivity among all patients. We also wanted to study the reason for the presence of autoantibodies in the sera of healthy individuals. A meta-analysis of 9 independent biomarker study was performed to find 77 common autoantibodies shared by healthy individuals. There was no gender bias; however, the number of autoantibodies increased with age, plateauing around adolescence. Molecular mimicry likely contributed to the elicitation of a subset of these common autoantibodies as 21 common autoantigens had 7 or more ungapped amino acid matches with viral proteins. Intrinsic properties of protein like hydrophilicity, basicity, aromaticity, and flexibility were enriched for common autoantigens. Subcellular localization and tissue expression analysis indicated the sequestration of some autoantigens from circulating autoantibodies can explain the absence of autoimmunity in these healthy individuals.
ContributorsShome, Mahasish (Author) / LaBaer, Joshua (Thesis advisor) / Borges, Chad (Committee member) / Stephanopoulos, Nicholas (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Exposure of liquid biospecimens like plasma and serum (P/S) to improper handling and storage can impact the integrity of biomolecules, potentially leading to apparent quantitative changes of important clinical proteins. An accurate and quick estimate of the quality of biospecimens employed in biomarker discovery and validation studies is essential to

Exposure of liquid biospecimens like plasma and serum (P/S) to improper handling and storage can impact the integrity of biomolecules, potentially leading to apparent quantitative changes of important clinical proteins. An accurate and quick estimate of the quality of biospecimens employed in biomarker discovery and validation studies is essential to facilitating accurate conclusions. ΔS-Cys-Albumin is a marker of blood P/S exposure to thawed conditions that can quantitatively track the exposure of P/S to temperatures greater than their freezing point of -30 C. Reported here are studies carried out to evaluate the potential of ΔS-Cys-Albumin to track the stability of clinically important analytes present in P/S upon their exposure to thawed conditions. P/S samples obtained from both cancer-free donors and cancer patients were exposed to 23 C (room temperature), 4 C and -20 C degrees, and the degree to which the apparent concentrations of clinically relevant biomolecules present in P/S were impacted during the time it took ΔS-Cys-Albumin to reach zero was measured. Analyte concentrations measured by molecular interaction-based assays were significantly impacted when samples were exposed to the point where average ΔS-Cys-Albumin fell below 12% at each temperature. Furthermore, the percentage of proteins that became unstable with time under thawed conditions exhibited a strong inverse linear relationship to ΔS-Cys-Albumin, indicating that ΔS-Cys-Albumin can serve as an effective surrogate marker to track the stability of other clinically relevant proteins in plasma as well as to estimate the fraction of proteins that have been destabilized by exposure to thawed conditions, regardless of what the exposure temperature(s) may have been. These results indicated that P/S exposure to thawed conditions disrupts epitopes required for clinical protein quantification via molecular interaction-based assays. In continuation of this theme, a spurious binding event between two clinically important proteins, Apolipoprotein E (ApoE) and Interferon-  (IFN) present in human plasma under in vitro experimental conditions is also reported. The interaction was confirmed to be evident only when ApoE was expressed in vitro with a Glutathione-S-Transferase (GST) fusion tag. Future steps required to find the exact manner in which the GST fusion tag facilitated the association between ApoE and IFNγ are discussed with emphasis on the possible pitfalls associated with using fusion proteins for studying novel protein-protein interactions.
ContributorsKapuruge, Erandi Prasadini (Author) / Borges, Chad R (Thesis advisor) / LaBaer, Joshua (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks

The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more

Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more timely and underexplored problems. In SB's entire history, mathematical modeling has always been an indispensable approach to predict the experimental outcomes, improve experimental design and obtain mechanism-understanding of the biological systems. \textit{Escherichia coli} (\textit{E. coli}) is one of the most important experimental platforms, its growth dynamics is the major research objective in this dissertation. Chapter 2 employs a reaction-diffusion model to predict the \textit{E. coli} colony growth on a semi-solid agar plate under multiple controls. In that chapter, a density-dependent diffusion model with non-monotonic growth to capture the colony's non-linear growth profile is introduced. Findings of the new model to experimental data are compared and contrasted with those from other proposed models. In addition, the cross-sectional profile of the colony are computed and compared with experimental data. \textit{E. coli} colony is also used to perform spatial patterns driven by designed gene circuits. In Chapter 3, a gene circuit (MINPAC) and its corresponding pattern formation results are presented. Specifically, a series of partial differential equation (PDE) models are developed to describe the pattern formation driven by the MINPAC circuit. Model simulations of the patterns based on different experimental conditions and numerical analysis of the models to obtain a deeper understanding of the mechanisms are performed and discussed. Mathematical analysis of the simplified models, including traveling wave analysis and local stability analysis, is also presented and used to explore the control strategies of the pattern formation. The interaction between the gene circuit and the host \textit{E. coli} may be crucial and even greatly affect the experimental outcomes. Chapter 4 focuses on the growth feedback between the circuit and the host cell under different nutrient conditions. Two ordinary differential equation (ODE) models are developed to describe such feedback with nutrient variation. Preliminary results on data fitting using both two models and the model dynamical analysis are included.
ContributorsHe, Changhan (Author) / Kuang, Yang (Thesis advisor) / Wang, Xiao (Committee member) / Kostelich, Eric (Committee member) / Tian, Xiaojun (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Osteocalcin (Oc) is the most abundant non-collagen protein found in the bone, but its precise function is still not completely understood. Three glutamic acid (Glu) residues within its sequence are sites for vitamin K-dependent post-translational modification, replacing a hydrogen with a carboxylate located at the γ-carbon position, converting these to

Osteocalcin (Oc) is the most abundant non-collagen protein found in the bone, but its precise function is still not completely understood. Three glutamic acid (Glu) residues within its sequence are sites for vitamin K-dependent post-translational modification, replacing a hydrogen with a carboxylate located at the γ-carbon position, converting these to γ-carboxyglutamic acid (Gla) residues. This modification confers increased binding of Oc to Ca2+ and hydroxyapatite matrix. Presented here, novel metal binding partners Mn2+, Fe3+, and Cr3+ of human Oc were determined, while the previously identified binders to (generally) non-human Oc, Ca2+, Mg2+, Pb2+ and Al3+ were validated as binders to human Oc by direct infusion mass spectrometry with all metals binding with higher affinity to the post-translationally modified form (Gla-Oc) compared to the unmodified form (Glu-Oc). Oc was also found to form pentamer (Gla-Oc) and pentamer and tetramer (Glu-Oc) homomeric self-assemblies in the absence of NaCl, which disassembled to monomers in the presence of near physiological Na+ concentrations. Additionally, Oc was found to form filamentous structures in vitro by negative stain TEM in the presence of increased Ca2+ titrations in a Gla- and pH-dependent manner. Finally, by combining circular dichroism spectroscopy to determine the fraction of Gla-Oc bound, and inductively-coupled plasma mass spectrometry to quantify total Al concentrations, the data were fit to a single-site binding model and the equilibrium dissociation constant for Al3+ binding to human Gla-Oc was determined (Kd = 1.0 ± 0.12 nM). Including citrate, a known competitive binder of Al3+, maintained Al in solution and enabled calculation of free Al3+ concentrations using a Matlab script to solve the complex set of linear equations. To further improve Al solubility limits, the pH of the system was lowered to 4.5, the pH during bone resorption. Complementary binding experiments with Glu-Oc were not possible due to the observed precipitation of Glu-Oc at pH 4.5, although qualitatively if Glu-Oc binds Al3+, it is with much lower affinity compared to Gla-Oc. Taken together, the results presented here further support the importance of post-translational modification, and thus adequate nutritional intake of vitamin K, on the binding and self-assembly properties of human Oc.
ContributorsThibert, Stephanie (Author) / Borges, Chad R (Thesis advisor) / LaBaer, Joshua (Committee member) / Chiu, Po-Lin (Committee member) / Arizona State University (Publisher)
Created2021
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Description

The 5-year survival rate for late-stage metastatic melanoma is only ~30%. A major reason for this low survival rate is that one of the most commonly mutated genes in melanoma, NRAS, has no FDA-approved targeted therapies. Because the RAS protein does not have any targeted therapies, patients with RAS mutant

The 5-year survival rate for late-stage metastatic melanoma is only ~30%. A major reason for this low survival rate is that one of the most commonly mutated genes in melanoma, NRAS, has no FDA-approved targeted therapies. Because the RAS protein does not have any targeted therapies, patients with RAS mutant tumors have an ongoing need for treatments that indirectly target RAS. This thesis project aims to identify expression and phosphorylation levels of proteins downstream of RAS in melanoma cell lines with the most common driver mutations. By analyzing the protein-level differences between these genetic mutants, we hope to identify additional indirect RAS protein targets for the treatment of NRAS mutant melanoma. RAS has several downstream effector proteins involved in oncogenic signaling pathways including FAK, Paxillin, AKT, and ERK. 5 melanoma cell lines (2 BRAF mutant, 2 NRAS mutant, and 1 designated wildtype) were analyzed using western bloting for FAK, Paxillin, AKT, and ERK phosphorylation and total expression levels. The results of western blot analysis showed that NRAS mutant cell lines had increased expression of phosphorylated Paxillin. Increased Paxillin phosphorylation corresponds to increased Paxillin binding at the FAT domain of FAK. Therefore, cell lines with increased FAK FAT – Paxillin interaction would be more sensitive to FAK FAT domain inhibition. The data presented provide an an explanation for the reduction in cell viability in NRAS mutant cell lines infected with Ad-FRNK. This information also has significant clinical relevance as researchers work to develop synthetic FAK FAT domain inhibitors, such as cyclic peptides. Additionally, cell lines with high levels of phosphorylated AKT showed a significant reduction in the amount of phosphorylated ERK. The identification of this inverse relationship may help to explain why BRAF and NRAS mutations are mutually exclusive. To conclude, NRAS mutant cell lines have increased expression of phosphorylated Paxillin and AKT which may explain why NRAS mutant cell lines are more sensitive to FAK FAT domain inhibition.

ContributorsSherwood, Nicole (Author) / Gould, Ian (Thesis director) / LaBaer, Joshua (Committee member) / Marlowe, Timothy (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
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Description
Emerging pathogens present several challenges to medical diagnostics. Primarily, the exponential spread of a novel pathogen through naïve populations require a rapid and overwhelming diagnostic response at the site of outbreak. While point-of-care (PoC) platforms have been developed for detection of antigens, serologic responses, and pathogenic genomes, only nucleic acid

Emerging pathogens present several challenges to medical diagnostics. Primarily, the exponential spread of a novel pathogen through naïve populations require a rapid and overwhelming diagnostic response at the site of outbreak. While point-of-care (PoC) platforms have been developed for detection of antigens, serologic responses, and pathogenic genomes, only nucleic acid diagnostics currently have the potential to be developed and manufactured within weeks of an outbreak owing to the speed of next-generation sequencing and custom DNA synthesis. Among nucleic acid diagnostics, isothermal amplification strategies are uniquely suited for PoC implementation due to their simple instrumentation and lack of thermocycling requirement. Unfortunately, isothermal strategies are currently prone to spurious nonspecific amplification, hindering their specificity and necessitating extensive empirical design pipelines that are both time and resource intensive. In this work, isothermal amplification strategies are extensively compared for their feasibility of implementation in outbreak response scenarios. One such technology, Loop-mediated Amplification (LAMP), is identified as having high-potential for rapid development and PoC deployment. Various approaches to abrogating nonspecific amplification are described including a novel in silico design tool based on coarse-grained simulation of interactions between thermophilic DNA polymerase and DNA strands in isothermal reaction conditions. Nonspecific amplification is shown to be due to stabilization of primer secondary structures by high concentrations of Bst DNA polymerase and a mechanism of micro-complement-mediated cross-priming is demonstrated as causal via nanopore sequencing of nonspecific reaction products. The resulting computational model predicts primer set background in 64% of 67 test assays and its usefulness is illustrated further by determining problematic primers in a West Nile Virus-specific LAMP primer set and optimizing primer 3’ nucleotides to eliminate micro-complements within the reaction, resulting in inhibition of background accumulation. Finally, the emergence of Orthopox monkeypox (MPXV) as a recurring threat is discussed and SimCycle is utilized to develop a novel technique for clade-specific discrimination of MPXV based on bridging viral genomic rearrangements (Bridging LAMP). Bridging LAMP is implemented in a 4-plex microfluidic format and demonstrates 100% sensitivity in detection of 100 copies of viral lysates and 45 crude MPXV-positive patient samples collected during the 2022 Clade IIb outbreak.
ContributorsKnappenberger, Mark Daniel (Author) / Anderson, Karen S (Thesis advisor) / LaBaer, Joshua (Committee member) / Roberson, Robert (Committee member) / Lindsay, Stuart (Committee member) / Arizona State University (Publisher)
Created2023
Description
Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural

Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural landscape are expected. To understand these land use changes and their impact on carbon dynamics, our study quantified aboveground carbon storage in both cultivated and abandoned agricultural fields. To accomplish this, we employed Python and various geospatial libraries in Jupyter Notebook files, for thorough dataset assembly and visual, quantitative analysis. We focused on nine counties known for high cultivation levels, primarily located in the lower latitudes of Arizona. Our analysis investigated carbon dynamics across not only abandoned and actively cultivated croplands but also neighboring uncultivated land, for which we estimated the extent. Additionally, we compared these trends with those observed in developed land areas. The findings revealed a hierarchy in aboveground carbon storage, with currently cultivated lands having the lowest levels, followed by abandoned croplands and uncultivated wilderness. However, wilderness areas exhibited significant variation in carbon storage by county compared to cultivated and abandoned lands. Developed lands ranked highest in aboveground carbon storage, with the median value being the highest. Despite county-wide variations, abandoned croplands generally contained more carbon than currently cultivated areas, with adjacent wilderness lands containing even more than both. This trend suggests that cultivating croplands in the region reduces aboveground carbon stores, while abandonment allows for some replenishment, though only to a limited extent. Enhancing carbon stores in Arizona can be achieved through active restoration efforts on abandoned cropland. By promoting native plant regeneration and boosting aboveground carbon levels, these measures are crucial for improving carbon sequestration. We strongly advocate for implementing this step to facilitate the regrowth of native plants and enhance overall carbon storage in the region.
ContributorsGoodwin, Emily (Author) / Eikenberry, Steffen (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma

Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma growth. The study aims to explore key factors influencing tumor morphology and to contribute to enhancing prediction techniques for treatment.
ContributorsShayegan, Tara (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2024-05
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Description
MicroRNAs (miRNAs) are 17-22 nucleotide non-coding RNAs that regulate gene expression by targeting non-complementary elements in the 3’ untranslated regions (3’UTRs) of mRNAs. miRNAs, which form complex networks of interaction that differ by tissue and developmental stage, display conservation in their function across metazoan species. Yet much remains unknown regarding

MicroRNAs (miRNAs) are 17-22 nucleotide non-coding RNAs that regulate gene expression by targeting non-complementary elements in the 3’ untranslated regions (3’UTRs) of mRNAs. miRNAs, which form complex networks of interaction that differ by tissue and developmental stage, display conservation in their function across metazoan species. Yet much remains unknown regarding their biogenesis, localization, strand selection, and their absolute abundance due to the difficulty of detecting and amplifying such small molecules. Here, I used an updated HT qPCR-based methodology to follow miRNA expression of 5p and 3p strands for all 190 C. elegans miRNAs described in miRBase throughout all six developmental stages in triplicates (total of 9,708 experiments), and studied their expression levels, tissue localization, and the rules underlying miRNA strand selection. My study validated previous findings and identified novel, conserved patterns of miRNA strand expression throughout C. elegans development, which at times correlate with previously observed developmental phenotypes. Additionally, my results highlighted novel structural principles underlying strand selection, which can be applied to higher metazoans. Though optimized for use in C. elegans, this method can be easily adapted to other eukaryotic systems, allowing for more scalable quantitative investigation of miRNA biology and/or miRNA diagnostics.
ContributorsMeadows, Dalton Alexander (Author) / Mangone, Marco (Thesis advisor) / LaBaer, Joshua (Committee member) / Murugan, Vel (Committee member) / Wilson-Rawls, Jeanne (Committee member) / Arizona State University (Publisher)
Created2023