Matching Items (9)
Filtering by

Clear all filters

156042-Thumbnail Image.png
Description
The portability of genetic tools from one organism to another is a cornerstone of synthetic biology. The shared biological language of DNA-to-RNA-to-protein allows for expression of polypeptide chains in phylogenetically distant organisms with little modification. The tools and contexts are diverse, ranging from catalytic RNAs in cell-free systems to bacterial

The portability of genetic tools from one organism to another is a cornerstone of synthetic biology. The shared biological language of DNA-to-RNA-to-protein allows for expression of polypeptide chains in phylogenetically distant organisms with little modification. The tools and contexts are diverse, ranging from catalytic RNAs in cell-free systems to bacterial proteins expressed in human cell lines, yet they exhibit an organizing principle: that genes and proteins may be treated as modular units that can be moved from their native organism to a novel one. However, protein behavior is always unpredictable; drop-in functionality is not guaranteed.

My work characterizes how two different classes of tools behave in new contexts and explores methods to improve their functionality: 1. CRISPR/Cas9 in human cells and 2. quorum sensing networks in Escherichia coli.

1. The genome-editing tool CRISPR/Cas9 has facilitated easily targeted, effective, high throughput genome editing. However, Cas9 is a bacterially derived protein and its behavior in the complex microenvironment of the eukaryotic nucleus is not well understood. Using transgenic human cell lines, I found that gene-silencing heterochromatin impacts Cas9’s ability to bind and cut DNA in a site-specific manner and I investigated ways to improve CRISPR/Cas9 function in heterochromatin.

2. Bacteria use quorum sensing to monitor population density and regulate group behaviors such as virulence, motility, and biofilm formation. Homoserine lactone (HSL) quorum sensing networks are of particular interest to synthetic biologists because they can function as “wires” to connect multiple genetic circuits. However, only four of these networks have been widely implemented in engineered systems. I selected ten quorum sensing networks based on their HSL production profiles and confirmed their functionality in E. coli, significantly expanding the quorum sensing toolset available to synthetic biologists.
ContributorsDaer, René (Author) / Haynes, Karmella (Thesis advisor) / Brafman, David (Committee member) / Nielsen, David (Committee member) / Kiani, Samira (Committee member) / Arizona State University (Publisher)
Created2017
136133-Thumbnail Image.png
Description
Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules that modify gene expression of a designated receiver cell. While

Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules that modify gene expression of a designated receiver cell. While useful, these three quorum sensing pathways exhibit a nontrivial level of crosstalk, hindering robust engineering and leading to unexpected effects in a given design. To address the lack of orthogonality among these three quorum sensing pathways, previous scientists have attempted to perform directed evolution on components of the quorum sensing pathway. While a powerful tool, directed evolution is limited by the subspace that is defined by the protein. For this reason, we take an evolutionary biology approach to identify new orthogonal quorum sensing networks and test these networks for cross-talk with currently-used networks. By charting characteristics of acyl homoserine lactone (AHL) molecules used across quorum sensing pathways in nature, we have identified favorable candidate pathways likely to display orthogonality. These include Aub, Bja, Bra, Cer, Esa, Las, Lux, Rhl, Rpa, and Sin, which we have begun constructing and testing. Our synthetic circuits express GFP in response to a quorum sensing molecule, allowing quantitative measurement of orthogonality between pairs. By determining orthogonal quorum sensing pairs, we hope to identify and adapt novel quorum sensing pathways for robust use in higher-order genetic circuits.
ContributorsMuller, Ryan (Author) / Haynes, Karmella (Thesis director) / Wang, Xiao (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
136851-Thumbnail Image.png
Description
Morphine is a commonly used analgesic in pain management. Opioid administration to a patient after surgery, such as spinal decompression surgery, can lead to adverse side effects. To demonstrate these adverse side effects could be decreased we created a model of how morphine and its metabolites are transported

Morphine is a commonly used analgesic in pain management. Opioid administration to a patient after surgery, such as spinal decompression surgery, can lead to adverse side effects. To demonstrate these adverse side effects could be decreased we created a model of how morphine and its metabolites are transported and excreted from the body. Using the of morphine and a standard compartment approach this thesis aimed at projecting pharmacokinetics trends of morphine overtime. A Matlab compartment model predicting the transport of morphine through the body can contribute to a better understanding of the concentrations at the systemic level, specifically with respect to a CSF, and what happens when you compare an intravenous injection to a local delivery. Other studies and models commonly utilized patient data over small periods of time2,3,5. An extended period of time will provide information into morphine’s time course after surgery. This model focuses on a compartmentalization of the major organs and the use of a simple Mechalis-Menten enzyme kinetics for the metabolites in the liver. Our results show a CSF concentration of about 1.086×〖10〗^(-12) nmol/L in 6 weeks and 1.0097×〖10〗^(-12) nmol/L in 12 weeks. The concentration profiles in this model are similar to what was expected. The implications of this suggest that patients who reported effects of morphine paste, a locally administered opioid, weeks after the surgery were due to other reasons. In creating a model we can determine important variables and dosage information. This information allows for a greater understanding of what is happening in the body and how to improve surgical outcomes. We propose this study has implications in general research in the pharmacokinetics and dynamics of pharmacology through the body.
ContributorsJacobs, Danielle Renee (Author) / Caplan, Michael (Thesis director) / Giers, Morgan (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
133517-Thumbnail Image.png
Description
Traumatic brain injury (TBI) is a major concern in public health due to its prevalence and effect. Every year, about 1.7 million TBIs are reported [7]. According to the According to the Centers for Disease Control and Prevention (CDC), 5.5% of all emergency department visits, hospitalizations, and deaths from 2002

Traumatic brain injury (TBI) is a major concern in public health due to its prevalence and effect. Every year, about 1.7 million TBIs are reported [7]. According to the According to the Centers for Disease Control and Prevention (CDC), 5.5% of all emergency department visits, hospitalizations, and deaths from 2002 to 2006 are due to TBI [8]. The brain's natural defense, the Blood Brain Barrier (BBB), prevents the entry of most substances into the brain through the blood stream, including medicines administered to treat TBI [11]. TBI may cause the breakdown of the BBB, and may result in increased permeability, providing an opportunity for NPs to enter the brain [3,4]. Dr. Stabenfeldt's lab has previously established that intravenously injected nanoparticles (NP) will accumulate near the injury site after focal brain injury [4]. The current project focuses on confirmation of the accumulation or extravasation of NPs after brain injury using 2-photon microscopy. Specifically, the project used controlled cortical impact injury induced mice models that were intravenously injected with 40nm NPs post-injury. The MATLAB code seeks to analyze the brain images through registration, segmentation, and intensity measurement and evaluate if fluorescent NPs will accumulate in the extravascular tissue of injured mice models. The code was developed with 2D bicubic interpolation, subpixel image registration, drawn dimension segmentation and fixed dimension segmentation, and dynamic image analysis. A statistical difference was found between the extravascular tissue of injured and uninjured mouse models. This statistical difference proves that the NPs do extravasate through the permeable cranial blood vessels in injured cranial tissue.
ContributorsIrwin, Jacob Aleksandr (Author) / Stabenfeldt, Sarah (Thesis director) / Bharadwaj, Vimala (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
135480-Thumbnail Image.png
Description
Compressed sensing magnetic resonance spectroscopic imaging (MRSI) is a noninvasive and in vivo potential diagnostic technique for cancer imaging. This technique undersamples the distribution of specific cancer biomarkers within an MR image as well as changes in the temporal dimension and subsequently reconstructs the missing data. This technique has been

Compressed sensing magnetic resonance spectroscopic imaging (MRSI) is a noninvasive and in vivo potential diagnostic technique for cancer imaging. This technique undersamples the distribution of specific cancer biomarkers within an MR image as well as changes in the temporal dimension and subsequently reconstructs the missing data. This technique has been shown to retain a high level of fidelity even with an acceleration factor of 5. Currently there exist several different scanner types that each have their separate analytical methods in MATLAB. A graphical user interface (GUI) was created to facilitate a single computing platform for these different scanner types in order to improve the ease and efficiency with which researchers and clinicians interact with this technique. A GUI was successfully created for both prospective and retrospective MRSI data analysis. This GUI retained the original high fidelity of the reconstruction technique and gave the user the ability to load data, load reference images, display intensity maps, display spectra mosaics, generate a mask, display the mask, display kspace and save the corresponding spectra, reconstruction, and mask files. Parallelization of the reconstruction algorithm was explored but implementation was ultimately unsuccessful. Future work could consist of integrating this parallelization method, adding intensity overlay functionality and improving aesthetics.
ContributorsLammers, Luke Michael (Author) / Kodibagkar, Vikram (Thesis director) / Hu, Harry (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
132664-Thumbnail Image.png
Description
Human potential is characterized by our ability to think flexibly and develop novel solutions to problems. In cognitive neuroscience, problem solving is studied using various tasks. For example, IQ can be tested using the RAVEN, which measures abstract reasoning. Analytical problem solving can be tested using algebra, and insight can

Human potential is characterized by our ability to think flexibly and develop novel solutions to problems. In cognitive neuroscience, problem solving is studied using various tasks. For example, IQ can be tested using the RAVEN, which measures abstract reasoning. Analytical problem solving can be tested using algebra, and insight can be tested using a nine-dot test. Our class of problem-solving tasks blends analytical and insight processes. This can be done by measuring multiply-constrained problem solving (MCPS). MCPS occurs when an individual problem has several solutions, but when grouped with simultaneous problems only one correct solution presents itself. The most common test for MCPS is known at the CRAT, or compound remote associate task. For example, when given the three target words “water, skate, and cream” there are many compound associates that can be assigned each of the target words individually (i.e. salt-water, roller-skate, whipped-cream), but only one that works with all three (ice-water, ice-skate, ice-cream).
This thesis is a tutorial for a MATLAB user-interface, known as EEGLAB. Cognitive and neural correlates of analytical and insight processes were evaluated and analyzed in the CRAT using EEG. It was hypothesized that different EEG signals will be measured for analytical versus insight problem solving, primarily observed in the gamma wave production. The data was interpreted using EEGLAB, which allows psychological processes to be quantified based on physiological response. I have written a tutorial showing how to process the EEG signal through filtering, extracting epochs, artifact detection, independent component analysis, and the production of a time – frequency plot. This project has combined my interest in psychology with my knowledge of engineering and expand my knowledge of bioinstrumentation.
ContributorsCobban, Morgan Elizabeth (Author) / Brewer, Gene (Thesis director) / Ellis, Derek (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the future compact x-ray free electron laser (CXFEL) XPCI source. The signal was reported in tonal values (“counts”), where MATLAB and MATLAB App Designer were the computing environments used to develop the simulations. The experimental setup’s components included a yttrium aluminum garnet (YAG) scintillating screen, mirror, and Mako G-507C camera with a Sony IMX264 sensor. The main function of the setup was to aim the X-rays at the YAG screen, then measure its scintillation through the photons emitted that hit the camera sensor. The resulting quantity used to assess the signal strength was tonal values (“counts”) per pixel on the sensor. Data for X-ray transmission through water, air, and polyimide was sourced from The Center for X-ray Optics’s simulations website, after which the data was interpolated and referenced in MATLAB. Matrices were an integral part of the saturation calculations; field-of-view (FOV), magnification and photon energies were also necessary. All the calculations were compiled into a graphical user interface (GUI) using App Designer. The code used to build this GUI can be used as a template for later, more complex GUIs and is a great starting point for future work in XPCI research at CXFEL.
ContributorsDela Rosa, Trixia (Author) / Graves, William (Thesis director) / King, Dakota (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
164640-Thumbnail Image.png
Description

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the future compact x-ray free electron laser (CXFEL) XPCI source. The signal was reported in tonal values (“counts”), where MATLAB and MATLAB App Designer were the computing environments used to develop the simulations. The experimental setup’s components included a yttrium aluminum garnet (YAG) scintillating screen, mirror, and Mako G-507C camera with a Sony IMX264 sensor. The main function of the setup was to aim the X-rays at the YAG screen, then measure its scintillation through the photons emitted that hit the camera sensor. The resulting quantity used to assess the signal strength was tonal values (“counts”) per pixel on the sensor. Data for X-ray transmission through water, air, and polyimide was sourced from The Center for X-ray Optics’s simulations website, after which the data was interpolated and referenced in MATLAB. Matrices were an integral part of the saturation calculations; field-of-view (FOV), magnification and photon energies were also necessary. All the calculations were compiled into a graphical user interface (GUI) using App Designer. The code used to build this GUI can be used as a template for later, more complex GUIs and is a great starting point for future work in XPCI research at CXFEL.

ContributorsDela Rosa, Trixia (Author) / Graves, William (Thesis director) / King, Dakota (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
164641-Thumbnail Image.jpg
Description

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the future compact x-ray free electron laser (CXFEL) XPCI source. The signal was reported in tonal values (“counts”), where MATLAB and MATLAB App Designer were the computing environments used to develop the simulations. The experimental setup’s components included a yttrium aluminum garnet (YAG) scintillating screen, mirror, and Mako G-507C camera with a Sony IMX264 sensor. The main function of the setup was to aim the X-rays at the YAG screen, then measure its scintillation through the photons emitted that hit the camera sensor. The resulting quantity used to assess the signal strength was tonal values (“counts”) per pixel on the sensor. Data for X-ray transmission through water, air, and polyimide was sourced from The Center for X-ray Optics’s simulations website, after which the data was interpolated and referenced in MATLAB. Matrices were an integral part of the saturation calculations; field-of-view (FOV), magnification and photon energies were also necessary. All the calculations were compiled into a graphical user interface (GUI) using App Designer. The code used to build this GUI can be used as a template for later, more complex GUIs and is a great starting point for future work in XPCI research at CXFEL.

ContributorsDela Rosa, Trixia (Author) / Graves, William (Thesis director) / King, Dakota (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05