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- Member of: Theses and Dissertations
Description
A synbody is a newly developed protein binding peptide which can be rapidly produced by chemical methods. The advantages of the synbody producing process make it a potential human proteome binding reagent. Most of the synbodies are designed to bind to specific proteins. The peptides incorporated in a synbody are discovered with peptide microarray technology. Nevertheless, the targets for unknown synbodies can also be discovered by searching through a protein mixture. The first part of this thesis mainly focuses on the process of target searching, which was performed with immunoprecipitation assays and mass spectrometry analysis. Proteins are pulled down from the cell lysate by certain synbodies, and then these proteins are identified using mass spectrometry. After excluding non-specific bindings, the interaction between a synbody and its real target(s) can be verified with affinity measurements. As a specific example, the binding between 1-4-KCap synbody and actin was discovered. This result proved the feasibility of the mass spectrometry based method and also suggested that a high throughput synbody discovery platform for the human proteome could be developed. Besides the application of synbody development, the peptide microarray technology can also be used for immunosignatures. The composition of all types of antibodies existing in one's blood is related to an individual's health condition. A method, called immunosignaturing, has been developed for early disease diagnosis based on this principle. CIM10K microarray slides work as a platform for blood antibody detection in immunosignaturing. During the analysis of an immunosignature, the data from these slides needs to be validated by using landing light peptides. The second part of this thesis focuses on the validation of the data. A biotinylated peptide was used as a landing light on the new CIM10K slides. The data was collected in several rounds of tests and indicated that the variation among landing lights was significantly reduced by using the newly prepared biotinylated peptide compared with old peptide mixture. Several suggestions for further landing light improvement are proposed based on the results.
ContributorsSun, Minyao (Author) / Johnston, Stephen Albert (Thesis advisor) / Diehnelt, Chris Wayne (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
Understanding cellular processes can provide insight into disease pathogenesis and reveal critical information for prevention, diagnosis, and treatment. As key executors and signaling regulators, proteins carry relevant information not available from genomics and transcriptomics. Cell-to-cell differences significantly affect disease incidence and drug responses, generating a need for protein analysis at the single-cell level. However, quantitative protein analysis at the single-cell level remains challenging due to the low protein amount in a single cell and the proteome complexity. It requires sensitive detection techniques and appropriate sample preparation and delivery to the detection area. Here, a microfluidic platform in tandem with matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) has been developed for targeted intracellular protein analysis. The elastomeric multi-layer microfluidic platform, termed MIMAS, was designed as a series of 8.75 nL wells separated by pneumatic valves. The MIMAS platform allows cell loading, sample processing on-chip, and further in situ mass spectrometry analysis. The sample processing includes cell lysis, immunocapture, tryptic digestion and MALDI matrix solution loading for co-crystallization. This work demonstrates that the MIMAS approach is suitable for protein quantification by assessing the apoptotic protein Bcl-2 from MCF-7 breast cancer cells using an isotope-labeled peptide. The limit of detection was determined as 11.22 nM, equivalent to 5.91 x 10^7 protein molecules per well. Moreover, the MIMAS platform design was improved, allowing the successful quantification of Bcl-2 protein in small cell ensembles down to ~10 cells in 4 nL wells. Furthermore, the MIMAS platform was integrated with laser capture microdissection (LCM) for protein analysis from post-mortem human tissues. Intracellular amyloid-β peptide (Aβ), a hallmark of Alzheimer’s Disease, was assessed from human brain tissue using the LCM-MIMAS. The successful detection of Aβ from small cell ensembles (20 sliced pyramidal cells) demonstrated the LCM-MIMAS capability of assessing intracellular proteins from specific tissue cell subpopulations. The MIMAS approach is a promising tool for intracellular protein analysis from small cell ensembles, with the potential for single-cell analysis. It allows for protein analysis towards the understanding of biological phenomena for clinical and biological research.
ContributorsCruz Villarreal, Jorvani (Author) / Ros, Alexandra (Thesis advisor) / Borges, Chad R (Committee member) / Buttry, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
Description
There are limited methods and techniques to quantitatively assess protein content in single cells or small cell populations of tissues. The standard protein insulin was used to understand how potential changes in the preparation or co-crystallization process could improve sensitivity and limit of detection through matrix assisted laser desorption ionization (MALDI) mass spectrometry analysis in Bruker’s Microflex LRF using polydimethylsiloxane (PDMS) reservoirs. In addition, initial imaging tests were performed on Bruker’s RapifleX MALDI Tissuetyper to determine the instrument’s imaging capabilities on proteins of interest through the use of a single layer “Christmas tree” microfluidic device, with the aim of applying a similar approach to future tissue samples. Data on 2µM insulin determined that a 95% laser power in the Microflex corresponded to 12-15% laser power in the RapifleX. Based on the experiments with insulin, the process of mixing insulin and saturated ɑ-Cyano-4-hydroxycinnamic acid (HCCA) matrix solvent in a 1:1 ratio using 10mM sodium phosphate buffer under area analysis is most optimized with a limit of detection value of 110 nM. With this information, the future aim is to apply this method to a double layer Christmas tree device in order to hopefully quantitatively analyze and image protein content in single or small cell populations.
ContributorsKow, Keegan (Author) / Ros, Alexandra (Thesis director) / Borges, Chad (Committee member) / Cruz-Villarreal, Jorvani (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2023-05
Description
Metabolomics focuses on the study of metabolic changes occurring in varioussystems and utilizes quantitative and semi-quantitative measurements of multiple metabolites in parallel. Mass spectrometry (MS) is the most ubiquitous platform in this field, as it provides superior sensitivity regarding measurements of complex metabolic profiles in biological systems. When combined with MS, multivariate statistics and advanced machine learning algorithms provide myriad opportunities for bioinformatics insights beyond simple univariate data comparisons. In this dissertation, the application of MS-based metabolomics is introduced with an emphasis on biomarker discovery for human disease detection. To advance disease diagnosis using MS-based metabolomics, numerous statistical techniques have been implemented in this research including principal component analysis, factor analysis, partial least squares-discriminant analysis (PLS-DA), orthogonal PLS-DA, random forest, receiver operating characteristic analysis, as well as functional pathway/enzyme enrichment analyses. These approaches are highly useful for improving classification sensitivity and specificity related to disease-induced biological variation and can help identify useful biomarkers and potential therapeutic targets. It is also shown that MS-based metabolomics can distinguish between clinical and prodromal disease as well as similar diseases with related symptoms, which may assist in clinical staging and differential diagnosis, respectively. Additionally, MS-based metabolomics is shown to be promising for the early and accurate detection of diseases, thereby improving patient outcomes, and advancing clinical care. Herein, the application of MS methods and chemometric statistics to the diagnosis of breast cancer, coccidioidomycosis (Valley fever), and senile dementia (Alzheimer's disease) are presented and discussed. In addition to presenting original research, previous efforts in biomarker discovery will be synthesized and appraised. A Comment will be offered regarding the state of the science, specifically addressing the inefficient model of repetitive biomarker discovery and the need for increased translational efforts necessary to consolidate metabolomics findings and formalize purported metabolic markers as laboratory developed tests. Various factors impeding the translational throughput of metabolomics findings will be carefully considered with respect to study design, statistical analysis, and regulation of biomedical diagnostics. Importantly, this dissertation will offer critical insights to advance metabolomics from a scientific field to a practical one including targeted detection, enhanced quantitation, and direct-to-consumer considerations.
ContributorsJasbi, Paniz (Author) / Johnston, Carol S (Thesis advisor) / Gu, Haiwei (Thesis advisor) / Lake, Douglas F (Committee member) / Sweazea, Karen (Committee member) / Tasevska, Natasha (Committee member) / Arizona State University (Publisher)
Created2022
Description
The movement of energy within a material is at the heart of numerous fundamental properties of chemistry and physics. Studying the process of photo-absorption in real time provides key insights into how energy is captured, stabilized, and dissipated within a material. The work presented in this thesis uses ultrafast time-of-flight mass spectrometry and computational modeling to observe and understand the properties of photo-excited states within molecules and clusters. Experimental results provide direct measurement of excited state lifetimes, while computational modeling provides a more thorough understanding of the movement of energy within an excited state. Excited state dynamics in covalent molecules such as n-butyl bromide (C4H9Br), presented in Chapter 4, demonstrate the significance of IVR of photo-excited states. Exciting to the high energy Rydberg manifold leads to predissociation into fragments of various lengths and degrees of saturation but the predissociation process is disrupted by energy redistribution into hot vibrational states. Experimental lifetimes show that IVR occurs over rapidly (~ 600 fs) leaving less energy for bond dissociation. Additionally, a long-lived feature in the dynamics of C4H9+ shows evidence of ion-pair formation – a known phenomenon which creates a stable A+/B- pair separated by several angstroms and occurring at energies lower than direct ionization. The results of this research show the dynamics of energy transfer into bond fragmentation, kinetic energy, and vibrational motion.
Metal-oxide clusters are unique materials which are representative of bulk materials but with quantized excited states instead of bands and as such can be used as atomically precise analogs to semiconducting materials. Excited state lifetimes and theoretical descriptors of electron-hole interactions of titanium oxide clusters, presented in Chapter 5, shows the significance of structure and oxidation of charge-transfer materials. Modeling the excited states of the photo-generated electrons and holes provides a window into the dynamics of charge-transfer and electron-hole separation and recombination in bulk materials. Furthermore, changes in the oxidation of the cluster have a dramatic impact on the nature of excited states and overall cluster properties. Such changes are analogous to oxygen defects in bulk materials and are critical for understanding reaction chemistry at defect sites.
ContributorsHeald, Lauren (Author) / Sayres, Scott G (Thesis advisor) / Seo, Dong-Kyun (Committee member) / Mujica, Vladimiro (Committee member) / Arizona State University (Publisher)
Created2022
Description
Short-lived radionuclides (SLRs) once present in the solar nebula can be used to probe the Solar System’s galactic formation environment. Isotopic analyses reveal that the first solids formed in the Solar System, calcium- and aluminum-rich inclusions (CAIs) in chondritic meteorites, formed with the live SLRs 10Be (t1/2 = 1.4 Ma) and 26Al (t1/2 = 0.7 Ma). Beryllium-10 is produced when high-energy ions, solar energetic particles or galactic cosmic rays (GCRs), spall nuclei in gas or dust. The most likely source of Solar System 10Be is inheritance of GCR-irradiated protosolar molecular cloud material, but only if all CAIs recorded the same initial 10Be abundance. The goal of this dissertation is to assess the homogeneity of 10Be by measuring CAIs for 10Be–10B isotope systematics, correlated to 26Al–26Mg and oxygen isotopes.
I synthesized appropriate standards for secondary ion mass spectrometry (SIMS) measurements of 10Be–10B, necessary for accurate determination of the 10Be/9Be ratio. I then analyzed 32 CAIs for 10Be–10B as well as 6 CAIs for 26Al–26Mg and 5 CAIs for oxygen isotopes within this sample set using SIMS. Previous studies analyzed CAIs primarily from CV3 chondrites, which are known to have experienced thermal metamorphism and aqueous alteration. My work included a variety of CAIs (Type A, B, fine-grained, igneous) from CV3oxidized, CV3reduced, CO3, CR2, and CH/CB chondrites. Finally, after evaluating my data and literature data consistently, I statistically tested whether all CAIs belong to a single 10Be population. I find that the majority (~85%) of the normal (i.e., without large isotopic fractionations or anomalies), 26Al-bearing CAIs recorded a single value, 10Be/9Be = (7.0 ± 0.2) × 10-4. Although 6 CAIs recorded higher or lower values, these are plausibly explained by secondary alteration processes. The galaxy-wide average value of 10Be/9Be from GCR interactions 4.56 billion years ago is predicted to be <2 × 10-4; the value I measured is more than 3 times higher. Because GCRs trace supernovae and star formation, my results suggest a similarly enhanced star formation rate in the molecular cloud within ~1 kpc of the Sun, in the ~15 Ma prior to the Sun’s birth.
I synthesized appropriate standards for secondary ion mass spectrometry (SIMS) measurements of 10Be–10B, necessary for accurate determination of the 10Be/9Be ratio. I then analyzed 32 CAIs for 10Be–10B as well as 6 CAIs for 26Al–26Mg and 5 CAIs for oxygen isotopes within this sample set using SIMS. Previous studies analyzed CAIs primarily from CV3 chondrites, which are known to have experienced thermal metamorphism and aqueous alteration. My work included a variety of CAIs (Type A, B, fine-grained, igneous) from CV3oxidized, CV3reduced, CO3, CR2, and CH/CB chondrites. Finally, after evaluating my data and literature data consistently, I statistically tested whether all CAIs belong to a single 10Be population. I find that the majority (~85%) of the normal (i.e., without large isotopic fractionations or anomalies), 26Al-bearing CAIs recorded a single value, 10Be/9Be = (7.0 ± 0.2) × 10-4. Although 6 CAIs recorded higher or lower values, these are plausibly explained by secondary alteration processes. The galaxy-wide average value of 10Be/9Be from GCR interactions 4.56 billion years ago is predicted to be <2 × 10-4; the value I measured is more than 3 times higher. Because GCRs trace supernovae and star formation, my results suggest a similarly enhanced star formation rate in the molecular cloud within ~1 kpc of the Sun, in the ~15 Ma prior to the Sun’s birth.
ContributorsDunham, Emilie T. (Author) / Wadhwa, Meenakshi (Thesis advisor) / Desch, Steven (Committee member) / Hervig, Richard (Committee member) / Bose, Maitrayee (Committee member) / Schrader, Devin (Committee member) / Arizona State University (Publisher)
Created2020
Description
The optimization of a blood-based assay for diagnosing tuberculosis which has been developed and validated in Dr. Hu’s lab, at Arizona State University, is important for ensuring its successful translation to a resource-limited setting of the developing world. Tuberculosis is most prevalent in the developing world with Sub-Saharan Africa having the highest cases of HIV/TB coinfections. The implementation of a blood-based assay for diagnosing Tuberculosis in the sub-Saharan would significantly improve the diagnosis and treatment monitoring of tuberculosis thereby managing or eliminating the pandemic altogether. The World Health Organization has called for robust diagnostic technologies that would resolve the shortfalls of the current technologies which include GeneXpert, X-ray, and smear microscopy. The blood-based diagnostic methodology heavily relies on Mass-spectrometry, a technology which could be entirely novel and expensive to implement in most laboratories in the Sub-Saharan. Despite virtual challenges in implementing the technology, the assay has demonstrated high specificity and sensitivity to HIV/TB coinfected patients and children in comparison to the available TB diagnostic assays. This study endorses the Blood-based Mass Spectrometry assay as one of the promising technologies to effectively improve the diagnosis of TB. The performance of the assay on detecting TB antigens was tested using different methods and materials. In the end, the use of DBS and miniaturized mass spectrometers have been discussed as possible routes for translating the assay to the developing world
ContributorsTwaibu, Jaffalie (Author) / Hu, Tony (Thesis director) / Shu, Qingbo (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Microsolvation studies have begun to shed the light on the impact that single water molecules have on the structure of a molecule. The difference in behavior that molecules show when exposed to an increasing number of water molecules has been considered important but remains elusive. The cluster distributions of formic acid were studied for its known importance as an intermediate in the water gas shift reaction. Implementations of the water gas shift reaction range from a wide range of applications. Studies have proposed implementations such as variety such as making water on the manned mission to mars and as an industrial energy source. The reaction pathway of formic acid favors decarboxylation in solvated conditions but control over the pathway is an important field of study. Formic acid was introduced into a high vacuum system in the form of a cluster beam via supersonic expansion and was ionized with the second harmonic (400nm) of a pump-probe laser. Mass spectra showed a ‘magic’ 5,1 (formic acid, water) peak which showed higher intensity than was usually observed in clusters with 1 water molecule. Peak integration showed a higher relative abundance for the 5,1 cluster as well and showed the increased binding favorability of this conformation. As a result, there is an enhanced probability of molecules sticking together in this arrangement and this is due to the stable, cage-like structure that the formic acid forms when surrounding the water molecule.
ContributorsQuiroz, Lenin Mejia (Author) / Sayres, Scott G. (Thesis director) / Mills, Jeremy (Committee member) / Biegasiewicz, Kyle (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In shotgun proteomics, liquid chromatography coupled to tandem mass spectrometry
(LC-MS/MS) is used to identify and quantify peptides and proteins. LC-MS/MS produces mass spectra, which must be searched by one or more engines, which employ
algorithms to match spectra to theoretical spectra derived from a reference database.
These engines identify and characterize proteins and their component peptides. By
training a convolutional neural network on a dataset of over 6 million MS/MS spectra
derived from human proteins, we aim to create a tool that can quickly and effectively
identify spectra as peptides prior to database searching. This can significantly reduce search space and thus run time for database searches, thereby accelerating LCMS/MS-based proteomics data acquisition. Additionally, by training neural networks
on labels derived from the search results of three different database search engines, we
aim to examine and compare which features are best identified by individual search
engines, a neural network, or a combination of these.
(LC-MS/MS) is used to identify and quantify peptides and proteins. LC-MS/MS produces mass spectra, which must be searched by one or more engines, which employ
algorithms to match spectra to theoretical spectra derived from a reference database.
These engines identify and characterize proteins and their component peptides. By
training a convolutional neural network on a dataset of over 6 million MS/MS spectra
derived from human proteins, we aim to create a tool that can quickly and effectively
identify spectra as peptides prior to database searching. This can significantly reduce search space and thus run time for database searches, thereby accelerating LCMS/MS-based proteomics data acquisition. Additionally, by training neural networks
on labels derived from the search results of three different database search engines, we
aim to examine and compare which features are best identified by individual search
engines, a neural network, or a combination of these.
ContributorsWhyte, Cameron Stafford (Author) / Suren, Jayasuriya (Thesis director) / Gil, Speyer (Committee member) / Patrick, Pirrotte (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Medulloblastoma is the most common pediatric brain cancer and accounts for 20% of all pediatric brain tumors. Upon diagnosis, patients undergo tumor-resection surgery followed by intense chemotherapy and cerebrospinal irradiation (CSI) regimens. CSI therapy is highly toxic and poorly tolerated in pediatric patients and is known to cause long-term neurocognitive, endocrine, and developmental deficits that often diminish the quality of life for medulloblastoma patients. The development of targeted therapies is necessary for both increasing the chance of survival and reducing treatment-related morbidities. A potential therapeutic target of interest in medulloblastoma is the polyamine biosynthesis pathway. Polyamines are metabolites present in every living organism and are essential for cellular processes such as growth, survival, and differentiation. Recent studies have shown that polyamine production is dysregulated in several cancers, including brain cancers, and have highlighted polyamine biosynthesis as a potential cancer growth dependency. Dysregulated polyamine metabolism has also been linked to several oncogenic drivers, including the WNT, SHH, and MYC signaling pathways that characterize genetically distinct medulloblastoma subgroups. One way to target polyamine biosynthesis is through the inhibition of the rate-limiting enzyme ornithine decarboxylase with difluoromethylornithine (DFMO), an analog of the polyamine precursor ornithine. DFMO is well-tolerated in pediatric populations and exerts minimal toxicities, as shown through neuroblastoma clinical trials, and is a therapy of interest for medulloblastoma. While DFMO has been tested clinically in multiple cancers, few in vitro studies have been performed to understand the exact mechanisms of anti-proliferation and cytotoxicity. Our study screened two immortalized medulloblastoma cell lines, DAOY (SHH) and D283 (non-WNT/non-SHH), and three patient-derived medulloblastoma cell lines, SL00024 (SHH), SL00668 (non-WNT/non-SHH), SL00870 (Unknown subgroup), for DFMO sensitivity and profiled the immortalized medulloblastoma cell line metabolome to understand the interactions between inhibition of polyamine metabolism with other essential metabolic processes and tumor cell growth. We found that medulloblastoma cell lines are sensitive to DFMO and the adaptive response to DFMO in medulloblastoma may be caused by increased oxidative stress and free radical scavenging. Our study hopes to inform the use of DFMO as an anti-cancer therapy in medulloblastoma by understanding the drug’s single-agent anti-proliferative mechanisms.
ContributorsFain, Caitlyn (Author) / Buetow, Kenneth (Thesis director) / Pirrotte, Patrick (Committee member) / Pathak, Khyati (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2024-05