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Optimizing Recombinant Protein Production for Domain Antibodies: Proof-of-Concept

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Recent studies in traumatic brain injury (TBI) have found a temporal window where therapeutics on the nanometer scale can cross the blood-brain barrier and enter the parenchyma. Developing protein-based therapeutics is attractive for a number of reasons, yet, the production

Recent studies in traumatic brain injury (TBI) have found a temporal window where therapeutics on the nanometer scale can cross the blood-brain barrier and enter the parenchyma. Developing protein-based therapeutics is attractive for a number of reasons, yet, the production pipeline for high yield and consistent bioactive recombinant proteins remains a major obstacle. Previous studies for recombinant protein production has utilized gram-negative hosts such as Escherichia coli (E. coli) due to its well-established genetics and fast growth for recombinant protein production. However, using gram-negative hosts require lysis that calls for additional optimization and also introduces endotoxins and proteases that contribute to protein degradation. This project directly addressed this issue and evaluated the potential to use a gram-positive host such as Brevibacillus choshinensis (Brevi) which does not require lysis as the proteins are expressed directly into the supernatant. This host was utilized to produce variants of Stock 11 (S11) protein as a proof-of-concept towards this methodology. Variants of S11 were synthesized using different restriction enzymes which will alter the location of protein tags that may affect production or purification. Factors such as incubation time, incubation temperature, and media were optimized for each variant of S11 using a robust design of experiments. All variants of S11 were grown using optimized parameters prior to purification via affinity chromatography. Results showed the efficiency of using Brevi as a potential host for domain antibody production in the Stabenfeldt lab. Future aims will focus on troubleshooting the purification process to optimize the protein production pipeline.

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2019-05

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Characterization and Optimization of Ion-Sensitive Field Effect Transistors for Rapid Personalized Diagnostics

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The growth of the medical diagnostic industry in the past several decades has largely been due to the creation and iterative optimization of bio sensors. Recent pushes towards value added as well as preventative health care has made point of

The growth of the medical diagnostic industry in the past several decades has largely been due to the creation and iterative optimization of bio sensors. Recent pushes towards value added as well as preventative health care has made point of care devices more attractive to health care providers. Rapid detection for diseases and cancers is done with a bio sensor, which a broad term used to describe an instrument which uses a bio chemical reaction to detect a chemical compound with the use of a bio recognition event in addition to a signal detection event. The bio sensors which are presented in this work are known as ion-sensitive field effects transistors (ISFETs) and are similar in function to a metal oxide field effect transistor (MOSFET). These ISFETs can be used to sense pH or the concentration of protons on the surface of the gate channel. These ISFETs can be used for certain bio recognition events and this work presents the application of these transistors for the quantification of tumor cell proliferation. This includes the development of a signal processing and acquisition system for the long term assessment of cellular metabolism and optimizing the system for use in an incubator. This thesis presents work done towards the optimization and implementation of complementary metal\u2014oxide\u2014semiconductor (CMOS) ISFETs as well as remote gate ISFETs for the continuous assessment of tumor cell extracellular pH. The work addresses the challenges faced with the fabrication and optimization of these sensors, which includes the mitigation of current drift with the use of pulse width modulation in addition to issues encountered with fabrication of electrodes on a quartz substrate. This work culminates in the testing of an autonomous system with mammary tumor cells as well as the assessment of cell viability in an incubator over extended periods. Future applications of this work include the creation of a remote gate ISFET array for multiplexed detection as well as the implementation of ISFETs for bio marker detection via an immunoassay.

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2017-05

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Utilization of Nanoparticles for Identifying Fibrin Deposition in Neural Tissue

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The main objective of this research is to develop and characterize a targeted contrast agent that will recognize acute neural injury pathology (i.e. fibrin) after traumatic brain injury (TBI). Single chain fragment variable antibodies (scFv) that bind specifically to fibrin

The main objective of this research is to develop and characterize a targeted contrast agent that will recognize acute neural injury pathology (i.e. fibrin) after traumatic brain injury (TBI). Single chain fragment variable antibodies (scFv) that bind specifically to fibrin have been produced and purified. DSPE-PEG micelles have been produced and the scFv has been conjugated to the surface of the micelles; this nanoparticle system will be used to overcome limitations in diagnosing TBI. The binding and imaging properties will be analyzed in the future to determine functionality of the nanoparticle system in vivo.

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2014-05

DEVELOPMENT OF A BIOSENSOR FOR RAPID DIAGNOSIS OF NAVAJO NEUROHEPATOPATHY

Description

MPV17-related hepatocerebral mitochondrial DNA depletion syndrome, previously known as Navajo Neurohepatopathy (NNH), is a rare genetic disease affecting Navajo children of the American Southwest. These children can suffer from several severe symptoms like brain damage and liver disease, and a

MPV17-related hepatocerebral mitochondrial DNA depletion syndrome, previously known as Navajo Neurohepatopathy (NNH), is a rare genetic disease affecting Navajo children of the American Southwest. These children can suffer from several severe symptoms like brain damage and liver disease, and a diagnosis leads to death by age 10, on average. The only known effective therapy for NNH is a liver transplant. Currently, the disease is diagnosed through a lengthy and expensive process of gene sequencing, but oftentimes patients with the most severe forms of NNH deteriorate quickly; thus a rapid diagnostic would be beneficial to beginning the transplant process as early as possible. Here, Tentacle Probes, a novel technology to detect genetic mutations, were proposed to rapidly and accurately diagnose NNH. Because of Tentacle Probes' double binding site kinetics, they can detect mutations more accurately than other types of genetic probes. Probes specific to the NNH mutation were designed for use with a real-time polymerase chain reaction (PCR) detection platform. Initial synthetic DNA testing of Tentacle Trobes showed capable differentiation between mutated and non-mutated samples. However, experiments to validate those results at Phoenix Children's Hospital before moving to patient samples showed that test viability decreased over time. Efforts to diagnose the issues that led to decreased viability suggested four possible explanations that are as follows (in order of decreasing likelihood): first, undesired products from improper PCR primer design was supported by double bands in DNA gel electrophoresis; second, DNA may have degraded over time or due to repeated cycles of freezing and thawing stock solutions, and this was supported by smeared DNA gel electrophoresis; third, probe degradation, specifically of the fluorescent reporter, is possible; finally, contaminants that inhibit the PCR reaction may have been introduced. A combination of these factors may also have caused the change in assay viability. As a result of these most likely possibilities, new primers were designed and steps suggested to return viability to the assay. Thus, the various limitations and requirements for this Tentacle Probe diagnostic have been identified, and as assay development continues following the promising initial results achieved, we are confident that a rapid method if diagnosing NNH is on its way to help the children afflicted with this devastating disease receive timely access to treatment.

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Date Created
2016-05

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Markov Chain Monte Carlo (MCMC) Modelling of Diagnostics for Pandemic Planning Using JAGS Package in R

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Markov Chain Monte-Carlo methods are a Bayesian approach to predictive statistics, which takes advantage of prior beliefs and conditions as well as the existing data to produce posterior distributions of relevant parameters. This approach, implementable through the JAGS packaging in

Markov Chain Monte-Carlo methods are a Bayesian approach to predictive statistics, which takes advantage of prior beliefs and conditions as well as the existing data to produce posterior distributions of relevant parameters. This approach, implementable through the JAGS packaging in R, is promising for its impact on the diagnostics space, which is a critical bottleneck for pandemic planning and rapid response. Specifically, these methods provide the means to optimize diagnostic testing, for example, by determining whether it is best to test individuals in a certain locale once or multiple times. This study compares the expected accuracy of single and double testing under two specific conditions, a general and Icelandic test case, in order to ascertain the validity of MCMC methods in this space and inform decisionmakers and future research in the space. Models based on this platform may eventually be tailored to the priors of specific locales. Additionally, the ability to test multiple regimes of real or simulated data while maintaining uncertainty widens the pool of researchers that can impact the space. In future studies, ensemble methods investigating the full range of parameters and their combinations can be studied.

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2020-05

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The Making of a COVID Testing Laboratory: Deconstructing the Saliva Sample Collection Process and Preanalytical Standardization

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This thesis project is the result of close collaboration with the Arizona State University Biodesign Clinical Testing Laboratory (ABCTL) to document the characteristics of saliva as a test sample, preanalytical considerations, and how the ABCTL utilized saliva testing to develo

This thesis project is the result of close collaboration with the Arizona State University Biodesign Clinical Testing Laboratory (ABCTL) to document the characteristics of saliva as a test sample, preanalytical considerations, and how the ABCTL utilized saliva testing to develop swift COVID-19 diagnostic tests for the Arizona community. As of April 2021, there have been over 130 million recorded cases of COVID-19 globally, with the United States taking the lead with approximately 31.5 million cases. Developing highly accurate and timely diagnostics has been an important need of our country that the ABCTL has had tremendous success in delivering. Near the start of the pandemic, the ABCTL utilized saliva as a testing sample rather than nasopharyngeal (NP) swabs that were limited in supply, required highly trained medical personnel, and were generally uncomfortable for participants. Results from literature across the globe showed how saliva performed just as well as the NP swabs (the golden standard) while being an easier test to collect and analyze. Going forward, the ABCTL will continue to develop high quality diagnostic tools and adapt to the ever-evolving needs our communities face regarding the COVID-19 pandemic.

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2021-05