Matching Items (154)
Description
Microfluidic devices represent a growing technology in the world of analytical chemistry. Serial femtosecond crystallography (SFX) utilizes microfluidic devices to generate droplets of an aqueous buffer containing protein crystals, which are then fired out as a jet in the beam of an X-ray free electron laser (XFEL). A crucial part of the device is its method of droplet detection. This project presents a design for a capacitive sensor that uses a unique electrode configuration to detect the difference in capacitance between the aqueous and oil phases. This design was developed using MATLAB and COMSOL Multiphysics simulations and printed using high-resolution 3D printing. Results show that this design can successfully distinguish between the two immiscible liquids, confirming it as a possible detection method in future SFX experiments.
ContributorsCorder, Cameron Dean (Author) / Ros, Alexandra (Thesis director) / Williams, Peter (Committee member) / Hayes, Mark (Committee member) / School of Molecular Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Obtaining local electrochemical (EC) information is extremely important for understanding basic surface reactions, and for many applications. Scanning electrochemical microscopy (SECM) can obtain local EC information by scanning a microelectrode across the surface. Although powerful, SECM is slow, the scanning microelectrode may perturb reaction and the measured signal decreases with the size of microelectrode. This thesis demonstrates a new imaging technique based on a principle that is completely different from the conventional EC detection technologies. The technique, referred to as plasmonic-based electrochemical imaging (PECI), images local EC current (both faradaic and non-faradaic) without using a scanning microelectrode. Because PECI response is an optical signal originated from surface plasmon resonance (SPR), PECI is fast and non-invasive and its signal is proportional to incident light intensity, thus does not decrease with the area of interest. A complete theory is developed in this thesis work to describe the relationship between EC current and PECI signal. EC current imaging at various fixed potentials and local cyclic voltammetry methods are developed and demonstrated with real samples. Fast imaging rate (up to 100,000 frames per second) with 0.2×3µm spatial resolution and 0.3 pA detection limit have been achieved. Several PECI applications have been developed to demonstrate the unique strengths of the new imaging technology. For example, trace particles in fingerprint is detected by PECI, a capability that cannot be achieved with the conventional EC technologies. Another example is PECI imaging of EC reaction and interfacial impedance of graphene of different thicknesses. In addition, local square wave voltammetry capability is demonstrated and applied to study local catalytic current of platinum nanoparticle microarray. This thesis also describes a related but different research project that develops a new method to measure surface charge densities of SPR sensor chips, and micro- and nano-particles. A third project of this thesis is to develop a method to expand the conventional SPR detection and imaging technology by including a waveguide mode. This innovation creates a sensitive detection of bulk index of refraction, which overcomes the limitation that the conventional SPR can probe only changes near the sensor surface within ~200 nm.
ContributorsShan, Xiaonan (Author) / Tao, Nongjian (Thesis advisor) / Chae, Junseok (Committee member) / Christen, Jennifer Blain (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2011
Description
Pathogenic Gram-negative bacteria employ a variety of molecular mechanisms to combat host defenses. Two-component regulatory systems (TCR systems) are the most ubiquitous signal transduction systems which regulate many genes required for virulence and survival of bacteria. In this study, I analyzed different TCR systems in two clinically-relevant Gram-negative bacteria, i.e., oral pathogen Porphyromonas gingivalis and enterobacterial Escherichia coli. P. gingivalis is a major causative agent of periodontal disease as well as systemic illnesses, like cardiovascular disease. A microarray study found that the putative PorY-PorX TCR system controls the secretion and maturation of virulence factors, as well as loci involved in the PorSS secretion system, which secretes proteinases, i.e., gingipains, responsible for periodontal disease. Proteomic analysis (SILAC) was used to improve the microarray data, reverse-transcription PCR to verify the proteomic data, and primer extension assay to determine the promoter regions of specific PorX regulated loci. I was able to characterize multiple genetic loci regulated by this TCR system, many of which play an essential role in hemagglutination and host-cell adhesion, and likely contribute to virulence in this bacterium. Enteric Gram-negative bacteria must withstand many host defenses such as digestive enzymes, low pH, and antimicrobial peptides (AMPs). The CpxR-CpxA TCR system of E. coli has been extensively characterized and shown to be required for protection against AMPs. Most recently, this TCR system has been shown to up-regulate the rfe-rff operon which encodes genes involved in the production of enterobacterial common antigen (ECA), and confers protection against a variety of AMPs. In this study, I utilized primer extension and DNase I footprinting to determine how CpxR regulates the ECA operon. My findings suggest that CpxR modulates transcription by directly binding to the rfe promoter. Multiple genetic and biochemical approaches were used to demonstrate that specific TCR systems contribute to regulation of virulence factors and resistance to host defenses in P. gingivalis and E. coli, respectively. Understanding these genetic circuits provides insight into strategies for pathogenesis and resistance to host defenses in Gram negative bacterial pathogens. Finally, these data provide compelling potential molecular targets for therapeutics to treat P. gingivalis and E. coli infections.
ContributorsLeonetti, Cori (Author) / Shi, Yixin (Thesis advisor) / Stout, Valerie (Committee member) / Nickerson, Cheryl (Committee member) / Sandrin, Todd (Committee member) / Arizona State University (Publisher)
Created2013
Description
X-ray diffraction is the technique of choice to determine the three-dimensional structures of proteins. In this study it has been applied to solve the structure of the survival motor neuron (SMN) proteins, the Fenna-Mathews-Olson (FMO) from Pelodictyon phaeum (Pld. phaeum) protein, and the synthetic ATP binding protein DX. Spinal muscular atrophy (SMA) is an autosomal recessive genetic disease resulting in muscle atrophy and paralysis via degeneration of motor neurons in the spinal cord. In this work, we used X-ray diffraction technique to solve the structures of the three variant of the of SMN protein, namely SMN 1-4, SMN-WT, and SMN-Δ7. The SMN 1-4, SMN-WT, and SMN-Δ7 crystals were diffracted to 2.7 Å, 5.5 Å and 3.0 Å, respectively. The three-dimensional structures of the three SMN proteins have been solved. The FMO protein from Pld. phaeum is a water soluble protein that is embedded in the cytoplasmic membrane and serves as an energy transfer funnel between the chlorosome and the reaction center. The FMO crystal diffracted to 1.99Å resolution and the three-dimensional structure has been solved. In previous studies, double mutant, DX, protein was purified and crystallized in the presence of ATP (Simmons et al., 2010; Smith et al. 2007). DX is a synthetic ATP binding protein which resulting from a random selection of DNA library. In this study, DX protein was purified and crystallized without the presence of ATP to investigate the conformational change in DX structure. The crystals of DX were diffracted to 2.5 Å and the three-dimensional structure of DX has been solved.
ContributorsSeng, Chenda O (Author) / Allen, James P. (Thesis advisor) / Wachter, Rebekka (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2013
Description
The study of bacterial resistance to antimicrobial peptides (AMPs) is a significant area of interest as these peptides have the potential to be developed into alternative drug therapies to combat microbial pathogens. AMPs represent a class of host-mediated factors that function to prevent microbial infection of their host and serve as a first line of defense. To date, over 1,000 AMPs of various natures have been predicted or experimentally characterized. Their potent bactericidal activities and broad-based target repertoire make them a promising next-generation pharmaceutical therapy to combat bacterial pathogens. It is important to understand the molecular mechanisms, both genetic and physiological, that bacteria employ to circumvent the bactericidal activities of AMPs. These understandings will allow researchers to overcome challenges posed with the development of new drug therapies; as well as identify, at a fundamental level, how bacteria are able to adapt and survive within varied host environments. Here, results are presented from the first reported large scale, systematic screen in which the Keio collection of ~4,000 Escherichia coli deletion mutants were challenged against physiologically significant AMPs to identify genes required for resistance. Less than 3% of the total number of genes on the E. coli chromosome was determined to contribute to bacterial resistance to at least one AMP analyzed in the screen. Further, the screen implicated a single cellular component (enterobacterial common antigen, ECA) and a single transporter system (twin-arginine transporter, Tat) as being required for resistance to each AMP class. Using antimicrobial resistance as a tool to identify novel genetic mechanisms, subsequent analyses were able to identify a two-component system, CpxR/CpxA, as a global regulator in bacterial resistance to AMPs. Multiple previously characterized CpxR/A members, as well as members found in this study, were identified in the screen. Notably, CpxR/A was found to transcriptionally regulate the gene cluster responsible for the biosynthesis of the ECA. Thus, a novel genetic mechanism was uncovered that directly correlates with a physiologically significant cellular component that appears to globally contribute to bacterial resistance to AMPs.
ContributorsWeatherspoon-Griffin, Natasha (Author) / Shi, Yixin (Thesis advisor) / Clark-Curtiss, Josephine (Committee member) / Misra, Rajeev (Committee member) / Nickerson, Cheryl (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier.
ContributorsBuddi, Sai (Author) / Taylor, Thomas (Thesis advisor) / Cochran, Douglas (Thesis advisor) / Nelson, Randall (Committee member) / Duman, Tolga (Committee member) / Arizona State University (Publisher)
Created2012
Description
Polydimethyl siloxane is a commonly used fabrication material for microfluidic devices. However, its hydrophobic nature and protein adsorption on the surface restricts its use for microfluidic applications. Also, it is critical to control the electroosmotic flow for electrophoretic and dielectrophoretic manipulations. Therefore, surface modification of PDMS is essential to make it well suited for bioanalytical applications. In this project, the role of polyethylene oxide copolymers F108 and PLL-PEG has been investigated to modify the surface properties of PDMS using physisorption method. Measuring electroosmotic flow and adsorption studies tested the quality and the long-term stability of the modified PDMS surface. Static and dynamic coating strategies were used to modify the PDMS surface. In static coating, the PDMS surface was incubated with the coating agent prior to the measurements. For dynamic coating, the coating agent was always present in the solution throughout the experiment. F108 and PLL-PEG were equally effective to prevent the protein adsorption under both strategies. However, dynamic coating was more time saving. Furthermore, effective reduction of EOF was observed with F108 coating agent under dynamic conditions and with PLL-PEG coating agent under static conditions. Moreover, PLL-PEG dynamic coatings exhibited reversal of EOF. These important findings could be used to manipulate EOF and suggest optimal coating agent and strategies for PDMS surface treatment by the physisorption method.
ContributorsManchanda, Shikha (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Liu, Yan (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation describes a novel, low cost strategy of using particle streak (track) images for accurate micro-channel velocity field mapping. It is shown that 2-dimensional, 2-component fields can be efficiently obtained using the spatial variation of particle track lengths in micro-channels. The velocity field is a critical performance feature of many microfluidic devices. Since it is often the case that un-modeled micro-scale physics frustrates principled design methodologies, particle based velocity field estimation is an essential design and validation tool. Current technologies that achieve this goal use particle constellation correlation strategies and rely heavily on costly, high-speed imaging hardware. The proposed image/ video processing based method achieves comparable accuracy for fraction of the cost. In the context of micro-channel velocimetry, the usability of particle streaks has been poorly studied so far. Their use has remained restricted mostly to bulk flow measurements and occasional ad-hoc uses in microfluidics. A second look at the usability of particle streak lengths in this work reveals that they can be efficiently used, after approximately 15 years from their first use for micro-channel velocimetry. Particle tracks in steady, smooth microfluidic flows is mathematically modeled and a framework for using experimentally observed particle track lengths for local velocity field estimation is introduced here, followed by algorithm implementation and quantitative verification. Further, experimental considerations and image processing techniques that can facilitate the proposed methods are also discussed in this dissertation. Unavailability of benchmarked particle track image data motivated the implementation of a simulation framework with the capability to generate exposure time controlled particle track image sequence for velocity vector fields. This dissertation also describes this work and shows that arbitrary velocity fields designed in computational fluid dynamics software tools can be used to obtain such images. Apart from aiding gold-standard data generation, such images would find use for quick microfluidic flow field visualization and help improve device designs.
ContributorsMahanti, Prasun (Author) / Cochran, Douglas (Thesis advisor) / Taylor, Thomas (Thesis advisor) / Hayes, Mark (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Most of the sunlight powering natural photosynthesis is absorbed by antenna arrays that transfer, and regulate the delivery of excitation energy to reaction centers in the chloroplast where photosynthesis takes place. Under intense sunlight the plants and certain organisms cannot fully utilize all of the sunlight received by antennas and excess redox species are formed which could potentially harm them. To prevent this, excess energy is dissipated by antennas before it reaches to the reaction centers to initiate electron transfer needed in the next steps of photosynthesis. This phenomenon is called non-photochemical quenching (NPQ). The mechanism of NPQ is not fully understood, but the process is believed to be initiated by a drop in the pH in thylakoid lumen in cells. This causes changes in otherwise nonresponsive energy acceptors which accept the excess energy, preventing oversensitization of the reaction center. To mimic this phenomenon and get insight into the mechanism of NPQ, a novel pH sensitive dye 3'6'-indolinorhodamine was designed and synthesized which in a neutral solution stays in a closed (colorless) form and does not absorb light while at low pH it opens (colored) and absorbs light. The absorption of the dye overlaps porphyrin emission, thus making energy transfer from the porphyrin to the dye thermodynamically possible. Several self-regulating molecular model systems were designed and synthesized consisting of this dye and zinc porphyrins organized on a hexaphenylbenzene framework to functionally mimic the role of the antenna in NPQ. When a dye-zinc porphyrin dyad is dissolved in an organic solvent, the zinc porphyrin antenna absorbs and emits light by normal photophysical processes. Time resolved fluorescence experiments using the single-photon-timing method with excitation at 425 nm and emission at 600 nm yielded a lifetime of 2.09 ns for the porphyrin first excited singlet state. When acetic acid is added to the solution of the dyad, the pH sensitive dye opens and quenches the zinc porphyrin emission decreasing the lifetime of the porphyrin first excited singlet state to 23 ps, and converting the excitation energy to heat. Under similar experimental conditions in a neutral solution, a model hexad containing the dye and five zinc porphyrins organized on a hexaphenylbenzene core decays exponentially with a time constant of 2.1 ns, which is essentially the same lifetime as observed for related monomeric zinc porphyrins. When a solution of the hexad is acidified, the dye opens and quenches all porphyrin first excited singlet states to <40 ps. This converts the excitation energy to heat and renders the porphyrins kinetically incompetent to readily donate electrons by photoinduced electron transfer, thereby mimicking the role of the antenna in photosynthetic photoprotection.
ContributorsBhushan, Kul (Author) / Gust, Devens (Thesis advisor) / Moore, Ana (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2012