Matching Items (105)
DescriptionA
ContributorsLund, Michael (Author) / Varsani, Arvind (Thesis advisor) / Upham, Nathan (Committee member) / Harris, Robin (Committee member) / Arizona State University (Publisher)
Created2023
Description
The human gut microbiome is associated with health outcomes including gastrointestinal and metabolic health, autoimmune disease and cancer. However, the role of the microbiome in many disease processes, including in the preterm gastrointestinal tract and female genital tract, has yet to be defined. Further, the diverse community of viruses within the microbiome (the virome) is understudied compared to bacteria. Here, I examine the microbiome and virome in specific disease models that are poorly understood: necrotizing enterocolitis (NEC), discordant HIV shedding in women living with HIV (WHLIV), female genital tract inflammation and gammaherpesvirus infection. Specifically, I examined the gut virome longitudinally in a cohort of preterm infants at risk for NEC; the female genital tract (FGT) microbiome and virome longitudinally in a cohort of WLHIV from Lima, Peru; the FGT virome in women from Phoenix, Arizona with differing levels of genital inflammation and different microbiome compositions; and the gut microbiome in murine gammaherpesvirus 68 (MHV68) infection. Further, I contributed to research responding to the spread of SARS-CoV-2 in Arizona. I found that 1) gut virome beta diversity decreased before NEC onset in preterm infants, suggesting a role for the virome in NEC; 2) FGT microbiome instability was associated with discordant HIV shedding, while FGT virome composition changed in association with ART duration and immune recovery; 3) FGT virome composition was associated with inflammation and microbiome composition; and 4) MHV68 infection outcomes were independent of microbiome perturbation, which may reflect environmental influences. The results of this research advance understanding of the microbiome and virome in these specific disease processes, and support further investigation of the microbiome and virome in preterm infant gastrointestinal health and FGT health, as well as environmental effects in microbiome research.
ContributorsKaelin, Emily (Author) / Lim, Efrem (Thesis advisor) / Varsani, Arvind (Committee member) / Jacobs, Bertram (Committee member) / McFadden, Grant (Committee member) / Rahman, Masmudur (Committee member) / Arizona State University (Publisher)
Created2024
Description
Arachnids belong to the phylum Arthropoda, the largest phylum in the animal kingdom. Ticks are blood-feeding arachnids that vector numerous pathogens of significant medical and veterinary importance, while scorpions have become a common concern in urban desert cities due to the high level of toxicity in their venom. To date, viruses associated with arachnids have been under sampled and understudied. Here viral metagenomics was used to explore the diversity of viruses present in ticks and scorpions. American dog ticks (Dermacentor variabilis) and blacklegged ticks (Ixodes scapularis) were collected in Pennsylvania while one hairy scorpion (Hadrurus arizonensis) and four bark scorpions (Centruroides sculpturatus) were collected in Phoenix. Novel viral genomes described here belong to the families Polyomaviridae, Anelloviridae, Genomoviridae, and a newly proposed family, Arthropolviridae.
Polyomaviruses are non-enveloped viruses with a small, circular double-stranded DNA (dsDNA) genomes that have been identified in a variety of mammals, birds and fish and are known to cause various diseases. Arthropolviridae is a proposed family of circular, large tumor antigen encoding dsDNA viruses that have a unidirectional genome organization. Genomoviruses and anelloviruses are ssDNA viruses that have circular genomes ranging in size from 2–2.4 kb and 2.1–3.8 kb, respectively. Genomoviruses are ubiquitous in the environment, having been identified in a wide range of animal, plant and environmental samples, while anelloviruses have been associated with a plethora of animals.
Here, 16 novel viruses are reported that span four viral families. Eight novel polyomaviruses were recovered from bark scorpions, three arthropolviruses were recovered from dog ticks and one arthropolvirus from a hairy scorpion. Viruses belonging to the families Polyomaviridae and Arthropolviridae are highly divergent. This is the first more extensive study of these viruses in arachnids. Three genomoviruses were recovered from both dog and deer ticks and one anellovirus was recovered from deer ticks, which are the first records of these viruses being recovered from ticks. This work highlights the diversity of dsDNA and ssDNA viruses in the arachnid population and emphasizes the importance of performing viral surveys on these populations.
Polyomaviruses are non-enveloped viruses with a small, circular double-stranded DNA (dsDNA) genomes that have been identified in a variety of mammals, birds and fish and are known to cause various diseases. Arthropolviridae is a proposed family of circular, large tumor antigen encoding dsDNA viruses that have a unidirectional genome organization. Genomoviruses and anelloviruses are ssDNA viruses that have circular genomes ranging in size from 2–2.4 kb and 2.1–3.8 kb, respectively. Genomoviruses are ubiquitous in the environment, having been identified in a wide range of animal, plant and environmental samples, while anelloviruses have been associated with a plethora of animals.
Here, 16 novel viruses are reported that span four viral families. Eight novel polyomaviruses were recovered from bark scorpions, three arthropolviruses were recovered from dog ticks and one arthropolvirus from a hairy scorpion. Viruses belonging to the families Polyomaviridae and Arthropolviridae are highly divergent. This is the first more extensive study of these viruses in arachnids. Three genomoviruses were recovered from both dog and deer ticks and one anellovirus was recovered from deer ticks, which are the first records of these viruses being recovered from ticks. This work highlights the diversity of dsDNA and ssDNA viruses in the arachnid population and emphasizes the importance of performing viral surveys on these populations.
ContributorsSchmidlin, Kara (Author) / Varsani, Arvind (Thesis advisor) / Van Doorslaer, Koenraad (Committee member) / Stenglein, Mark (Committee member) / Arizona State University (Publisher)
Created2019
Description
Massive glycerol cluster ions with many charges (~ 106 Da, ~ ±100 charges) have been generated by electrospray to bombard biomolecules and biological sample surfaces. The low impact energy per nucleon facilitates intact sputtering and ionization of biomolecules which can be subsequently imaged. Various lipids, peptides and proteins have been studied. The primary cluster ion source has been coupled with an ion-microscope imaging mass spectrometer (TRIFT-1, Physical Electronics). A lateral resolution of ~3µm has been demonstrated, which is acceptable for sub-cellular imaging of animal cells (e.g. single cancer cell imaging in early diagnosis). Since the available amount of target molecules per pixel is limited in biological samples, the measurement of useful ion yields (ratio of detected molecular ion counts to the sample molecules sputtered) is important to determine whether enough ion counts per pixel can be obtained. The useful ion yields of several lipids and peptides are in the 1-3×10-5 range. A 3×3 µm2lipid bilayer can produce ~260 counts/pixel for a meaningful 3×3 µm2 pixel ion image. This method can probably be used in cell imaging in the future, when there is a change in the lipid contents of the cell membrane (e.g. cancer cells vs. normal cells).
ContributorsZhang, Jitao (Author) / Williams, Peter (Thesis advisor) / Hayes, Mark (Committee member) / Nelson, Randall (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cell heterogeneity is widely present in the biological world and exists even in an isogenic population. Resolving the protein heterogeneity at the single cell level is of enormous biological and clinical relevance. However, single cell protein analysis has proven to be challenging due to extremely low amount of protein in a single cell and the huge complexity of proteome. This requires appropriate sampling and sensitive detection techniques. Here, a new approach, microfluidics combined with MALDI-TOF mass spectrometry was brought forward, for the analysis of proteins in single cells. The detection sensitivity of peptides as low as 300 molecules and of proteins as low as 10^6 molecules has been demonstrated. Furthermore, an immunoassay was successfully integrated in the microfluidic device for capturing the proteins of interest and further identifying them by subsequent enzymatic digestion. Moreover, an improved microfluidic platform was designed with separate chambers and valves, allowing the absolute quantification by employing iTRAQ tags or an isotopically labeled peptide. The study was further extended to analyze a protein in MCF-7 cell lysate. The approach capable of identifying and quantifying protein molecules in MCF-7 cells is promising for future proteomic studies at the single cell level.
ContributorsYang, Mian (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Nelson, Randall (Committee member) / Arizona State University (Publisher)
Created2016
Description
Commercial buildings in the United States account for 19% of the total energy consumption annually. Commercial Building Energy Consumption Survey (CBECS), which serves as the benchmark for all the commercial buildings provides critical input for EnergyStar models. Smart energy management technologies, sensors, innovative demand response programs, and updated versions of certification programs elevate the opportunity to mitigate energy-related problems (blackouts and overproduction) and guides energy managers to optimize the consumption characteristics. With increasing advancements in technologies relying on the ‘Big Data,' codes and certification programs such as the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), and the Leadership in Energy and Environmental Design (LEED) evaluates during the pre-construction phase. It is mostly carried out with the assumed quantitative and qualitative values calculated from energy models such as Energy Plus and E-quest. However, the energy consumption analysis through Knowledge Discovery in Databases (KDD) is not commonly used by energy managers to perform complete implementation, causing the need for better energy analytic framework.
The dissertation utilizes Interval Data (ID) and establishes three different frameworks to identify electricity losses, predict electricity consumption and detect anomalies using data mining, deep learning, and mathematical models. The process of energy analytics integrates with the computational science and contributes to several objectives which are to
1. Develop a framework to identify both technical and non-technical losses using clustering and semi-supervised learning techniques.
2. Develop an integrated framework to predict electricity consumption using wavelet based data transformation model and deep learning algorithms.
3. Develop a framework to detect anomalies using ensemble empirical mode decomposition and isolation forest algorithms.
With a thorough research background, the first phase details on performing data analytics on the demand-supply database to determine the potential energy loss reduction potentials. Data preprocessing and electricity prediction framework in the second phase integrates mathematical models and deep learning algorithms to accurately predict consumption. The third phase employs data decomposition model and data mining techniques to detect the anomalies of institutional buildings.
The dissertation utilizes Interval Data (ID) and establishes three different frameworks to identify electricity losses, predict electricity consumption and detect anomalies using data mining, deep learning, and mathematical models. The process of energy analytics integrates with the computational science and contributes to several objectives which are to
1. Develop a framework to identify both technical and non-technical losses using clustering and semi-supervised learning techniques.
2. Develop an integrated framework to predict electricity consumption using wavelet based data transformation model and deep learning algorithms.
3. Develop a framework to detect anomalies using ensemble empirical mode decomposition and isolation forest algorithms.
With a thorough research background, the first phase details on performing data analytics on the demand-supply database to determine the potential energy loss reduction potentials. Data preprocessing and electricity prediction framework in the second phase integrates mathematical models and deep learning algorithms to accurately predict consumption. The third phase employs data decomposition model and data mining techniques to detect the anomalies of institutional buildings.
ContributorsNaganathan, Hariharan (Author) / Chong, Oswald W (Thesis advisor) / Ariaratnam, Samuel T (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2017
Description
Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases. I first contributed to the optimization of the immunosignature platform by introducing scoring metrics to select optimal parameters, considering performance as well as practicality. Next, I primarily worked on identifying a signature shared across various pathogens that can distinguish them from the healthy population. I further retrieved consensus epitopes from the disease common signature and proposed that most pathogens could share the signature by studying the enrichment of the common signature in the pathogen proteomes. Following this, I worked on studying cancer samples from different stages and correlated the immune response with whether the epitope presented by tumor is similar to the pathogen proteome. An effective immune response is defined as an antibody titer increasing followed by decrease, suggesting elimination of the epitope. I found that an effective immune response usually correlates with epitopes that are more similar to pathogens. This suggests that the immune system might occupy a limited space and can be effective against only certain epitopes that have similarity with pathogens. I then participated in the attempt to solve the antibiotic resistance problem by developing a classification algorithm that can distinguish bacterial versus viral infection. This algorithm outperforms other currently available classification methods. Finally, I worked on the concept of deriving a single number to represent all the data on the immunosignature platform. This is in resemblance to the concept of temperature, which is an approximate measurement of whether an individual is healthy. The measure of Immune Entropy was found to work best as a single measurement to describe the immune system information derived from the immunosignature. Entropy is relatively invariant in healthy population, but shows significant differences when comparing healthy donors with patients either infected with a pathogen or have cancer.
ContributorsWang, Lu (Author) / Johnston, Stephen (Thesis advisor) / Stafford, Phillip (Committee member) / Buetow, Kenneth (Committee member) / McFadden, Grant (Committee member) / Arizona State University (Publisher)
Created2018
Description
This work advances structural and biophysical studies of three proteins important in disease. First protein of interest is the Francisella tularensis outer membrane protein A (FopA), which is a virulence determinant of tularemia. This work describes recombinant expression in Escherichia coli and successful purification of membrane translocated FopA. The purified protein was dimeric as shown by native polyacrylamide gel electrophoresis and small angle X-ray scattering (SAXS) analysis, with an abundance of β-strands based on circular dichroism spectroscopy. SAXS data supports the presence of a pore. Furthermore, protein crystals of membrane translocated FopA were obtained with preliminary X-ray diffraction data. The identified crystallization condition provides the means towards FopA structure determination; a valuable tool for structure-based design of anti-tularemia therapeutics.
Next, the nonstructural protein μNS of avian reoviruses was investigated using in vivo crystallization and serial femtosecond X-ray crystallography. Avian reoviruses infect poultry flocks causing significant economic losses. μNS is crucial in viral factory formation facilitating viral replication within host cells. Thus, structure-based targeting of μNS has the potential to disrupt intracellular viral propagation. Towards this goal, crystals of EGFP-tagged μNS (EGFP-μNS (448-605)) were produced in insect cells. The crystals diffracted to 4.5 Å at X-ray free electron lasers using viscous jets as crystal delivery methods and initial electron density maps were obtained. The resolution reported here is the highest described to date for μNS, which lays the foundation towards its structure determination.
Finally, structural, and functional studies of human Threonine aspartase 1 (Taspase1) were performed. Taspase1 is overexpressed in many liquid and solid malignancies. In the present study, using strategic circular permutations and X-ray crystallography, structure of catalytically active Taspase1 was resolved. The structure reveals the conformation of a 50 residues long fragment preceding the active side residue (Thr234), which has not been structurally characterized previously. This fragment adopted a straight helical conformation in contrast to previous predictions. Functional studies revealed that the long helix is essential for proteolytic activity in addition to the active site nucleophilic residue (Thr234) mediated proteolysis. Together, these findings enable a new approach for designing anti-cancer drugs by targeting the long helical fragment.
Next, the nonstructural protein μNS of avian reoviruses was investigated using in vivo crystallization and serial femtosecond X-ray crystallography. Avian reoviruses infect poultry flocks causing significant economic losses. μNS is crucial in viral factory formation facilitating viral replication within host cells. Thus, structure-based targeting of μNS has the potential to disrupt intracellular viral propagation. Towards this goal, crystals of EGFP-tagged μNS (EGFP-μNS (448-605)) were produced in insect cells. The crystals diffracted to 4.5 Å at X-ray free electron lasers using viscous jets as crystal delivery methods and initial electron density maps were obtained. The resolution reported here is the highest described to date for μNS, which lays the foundation towards its structure determination.
Finally, structural, and functional studies of human Threonine aspartase 1 (Taspase1) were performed. Taspase1 is overexpressed in many liquid and solid malignancies. In the present study, using strategic circular permutations and X-ray crystallography, structure of catalytically active Taspase1 was resolved. The structure reveals the conformation of a 50 residues long fragment preceding the active side residue (Thr234), which has not been structurally characterized previously. This fragment adopted a straight helical conformation in contrast to previous predictions. Functional studies revealed that the long helix is essential for proteolytic activity in addition to the active site nucleophilic residue (Thr234) mediated proteolysis. Together, these findings enable a new approach for designing anti-cancer drugs by targeting the long helical fragment.
ContributorsNagaratnam, Nirupa (Author) / Fromme, Petra (Thesis advisor) / Johnston, Stephen (Thesis advisor) / Van Horn, Wade (Committee member) / Liu, Wei (Committee member) / Arizona State University (Publisher)
Created2020
Description
One of the single-most insightful, and visionary talks of the 20th century, “There’s plenty of room at the bottom,” by Dr. Richard Feynman, represented a first foray into the micro- and nano-worlds of biology and chemistry with the intention of direct manipulation of their individual components. Even so, for decades there has existed a gulf between the bottom-up molecular worlds of biology and chemistry, and the top-down world of nanofabrication. Creating single molecule nanoarrays at the limit of diffraction could incentivize a paradigm shift for experimental assays. However, such arrays have been nearly impossible to fabricate since current nanofabrication tools lack the resolution required for precise single-molecule spatial manipulation. What if there existed a molecule which could act as a bridge between these top-down and bottom-up worlds?
At ~100-nm, a DNA origami macromolecule represents one such bridge, acting as a breadboard for the decoration of single molecules with 3-5 nm resolution. It relies on the programmed self-assembly of a long, scaffold strand into arbitrary 2D or 3D structures guided via approximately two hundred, short, staple strands. Once synthesized, this nanostructure falls in the spatial manipulation regime of a nanofabrication tool such as electron-beam lithography (EBL), facilitating its high efficiency immobilization in predetermined binding sites on an experimentally relevant substrate. This placement technology, however, is expensive and requires specialized training, thereby limiting accessibility.
The work described here introduces a method for bench-top, cleanroom/lithography-free, DNA origami placement in meso-to-macro-scale grids using tunable colloidal nanosphere masks, and organosilane-based surface chemistry modification. Bench-top DNA origami placement is the first demonstration of its kind which facilitates precision placement of single molecules with high efficiency in diffraction-limited sites at a cost of $1/chip. The comprehensive characterization of this technique, and its application as a robust platform for high-throughput biophysics and digital counting of biomarkers through enzyme-free amplification are elucidated here. Furthermore, this technique can serve as a template for the bottom-up fabrication of invaluable biophysical tools such as zero mode waveguides, making them significantly cheaper and more accessible to the scientific community. This platform has the potential to democratize high-throughput single molecule experiments in laboratories worldwide.
At ~100-nm, a DNA origami macromolecule represents one such bridge, acting as a breadboard for the decoration of single molecules with 3-5 nm resolution. It relies on the programmed self-assembly of a long, scaffold strand into arbitrary 2D or 3D structures guided via approximately two hundred, short, staple strands. Once synthesized, this nanostructure falls in the spatial manipulation regime of a nanofabrication tool such as electron-beam lithography (EBL), facilitating its high efficiency immobilization in predetermined binding sites on an experimentally relevant substrate. This placement technology, however, is expensive and requires specialized training, thereby limiting accessibility.
The work described here introduces a method for bench-top, cleanroom/lithography-free, DNA origami placement in meso-to-macro-scale grids using tunable colloidal nanosphere masks, and organosilane-based surface chemistry modification. Bench-top DNA origami placement is the first demonstration of its kind which facilitates precision placement of single molecules with high efficiency in diffraction-limited sites at a cost of $1/chip. The comprehensive characterization of this technique, and its application as a robust platform for high-throughput biophysics and digital counting of biomarkers through enzyme-free amplification are elucidated here. Furthermore, this technique can serve as a template for the bottom-up fabrication of invaluable biophysical tools such as zero mode waveguides, making them significantly cheaper and more accessible to the scientific community. This platform has the potential to democratize high-throughput single molecule experiments in laboratories worldwide.
ContributorsShetty, Rishabh Manoj (Author) / Hariadi, Rizal F (Thesis advisor) / Gopinath, Ashwin (Committee member) / Varsani, Arvind (Committee member) / Nikkhah, Mehdi (Committee member) / Tillery, Stephen H (Committee member) / Hu, Ye (Committee member) / Arizona State University (Publisher)
Created2019
Description
The human papillomavirus (HPV) is a double-stranded DNA virus responsible for causing upwards of 80% of head and neck cancers in the oropharyngeal region. Current treatments, including surgery, chemotherapy, and/or radiation, are aggressive and elicit toxic effects. HPV is a pathogen that expresses viral-specific oncogenic proteins that play a role in cancer progression. These proteins may serve as potential targets for immunotherapeutic applications. Engineered T cell receptor (TCR) therapy may be an advantageous approach for HPV-associated cancers. In TCR therapy, TCRs are modified to express a receptor that is specific to an immunogenic antigen (part of the virus/cancer capable of eliciting an immune response). Since HPV-associated oropharyngeal cancers typically express unique viral proteins, it is important to identify the TCRs capable of recognizing these proteins. Evidence supports that head and neck cancers typically experience high levels of immune cell infiltration and are subsequently associated with increased survival rates. Most of the immune cell infiltrations in HPV+ HNSCC are CD8+ T lymphocytes, drawing attention to their prospective use in cellular immunotherapies. While TCRs are highly specific, the TCR repertoire is extremely diverse; enabling the immune system to fight off numerous pathogens. In project 1, I review approaches to analyzing TCR diversity and explore the use of DNA origami in retrieving paired TCR sequences from a population. The results determine that DNA origami can be used within a monoclonal population but requires further optimization before being applied in a polyclonal setting. In project 2, I investigate HPV-specific T-cell dysfunction; I detect low frequency HPV-specific CD8+ T cells, determine that they are tumor specific, and show that HPV+HNSCC patients exhibit increased epitope-specific levels of CD8+T cell exhaustion. In project 3, I apply methods to expand and isolate TCRαβ sequences derived from donors stimulated with a previously identified HPV epitope. Single-cell analysis provide ten unique TCRαβ pairs with corresponding CDR3 sequences that may serve as therapeutic candidates. This thesis contributes to fundamental immunology by contributing to the knowledge of T cell dysfunction within HPV+HNSCC and further reveals TCR gene usage within an HPV stimulated population, thus identifying potential TCR pairs for adoptive cell therapies.
ContributorsUlrich, Peaches Rebecca (Author) / Anderson, Karen S (Thesis advisor) / Lake, Douglas (Committee member) / Maley, Carlo (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2020