Matching Items (12)
Description
Protein affinity reagents have aptly gained profound importance as capture reagents and
drugs in basic research, biotechnology, diagnostics and therapeutics. However, due to the
cost, labor and time associated with production of antibodies focus has recently changed
towards potential of peptides to act as protein affinity reagents. Affinity peptides are easy
to work with, non-immunogenic, cost effective and amenable to scale up. Even though
researchers have developed several affinity peptides, we are far from compiling library of
peptides that encompasses entire human proteome. My thesis describes high throughput
pipeline that can be used to develop and characterize affinity peptides that bind several
discrete sites on target proteins.
Chapter 2 describes optimization of cell-free protein expression using commercially
available translation systems and well-known leader sequences. Presence of internal
ribosome entry site upstream of coding region allows maximal expression in HeLa cell
lysate whereas translation enhancing elements are best suited for expression in rabbit
reticulocyte lysate and wheat germ extract. Use of optimal vector and cell lysate
combination ensures maximum protein expression of DNA libraries.
Chapter 3 describes mRNA display selection methodology for developing affinity peptides
for target proteins using large diversity DNA libraries. I demonstrate that mild denaturant
is not sufficient to increase selection pressure for up to three rounds of selection and
increasing number of selection rounds increases probability of finding affinity peptide s.
These studies enhance fundamental understanding of mRNA display and pave the way
for future optimizations to accelerate convergence of in vitro selections.
Chapter 4 describes a high throughput double membrane dot blot system to rapidly
screen, identify and characterize affinity peptides obtained from selection output. I used
dot blot to screen potential affinity peptides from large diversity of previously
ii
uncharacterized mRNA display selection output. Further characterization of potential
peptides allowed determination of several high affinity peptides from having Kd range 150-
450 nM. Double membrane dot blot is automation amenable, easy and affordable solution
for analyzing selection output and characterizing peptides without ne ed for much
instrumentation.
Together these projects serve as guideline for evolution of cost effective high throughput
pipeline for identification and characterization of affinity peptides.
drugs in basic research, biotechnology, diagnostics and therapeutics. However, due to the
cost, labor and time associated with production of antibodies focus has recently changed
towards potential of peptides to act as protein affinity reagents. Affinity peptides are easy
to work with, non-immunogenic, cost effective and amenable to scale up. Even though
researchers have developed several affinity peptides, we are far from compiling library of
peptides that encompasses entire human proteome. My thesis describes high throughput
pipeline that can be used to develop and characterize affinity peptides that bind several
discrete sites on target proteins.
Chapter 2 describes optimization of cell-free protein expression using commercially
available translation systems and well-known leader sequences. Presence of internal
ribosome entry site upstream of coding region allows maximal expression in HeLa cell
lysate whereas translation enhancing elements are best suited for expression in rabbit
reticulocyte lysate and wheat germ extract. Use of optimal vector and cell lysate
combination ensures maximum protein expression of DNA libraries.
Chapter 3 describes mRNA display selection methodology for developing affinity peptides
for target proteins using large diversity DNA libraries. I demonstrate that mild denaturant
is not sufficient to increase selection pressure for up to three rounds of selection and
increasing number of selection rounds increases probability of finding affinity peptide s.
These studies enhance fundamental understanding of mRNA display and pave the way
for future optimizations to accelerate convergence of in vitro selections.
Chapter 4 describes a high throughput double membrane dot blot system to rapidly
screen, identify and characterize affinity peptides obtained from selection output. I used
dot blot to screen potential affinity peptides from large diversity of previously
ii
uncharacterized mRNA display selection output. Further characterization of potential
peptides allowed determination of several high affinity peptides from having Kd range 150-
450 nM. Double membrane dot blot is automation amenable, easy and affordable solution
for analyzing selection output and characterizing peptides without ne ed for much
instrumentation.
Together these projects serve as guideline for evolution of cost effective high throughput
pipeline for identification and characterization of affinity peptides.
ContributorsShah, Pankti (Author) / Chaput, John (Thesis advisor) / Hecht, Sidney (Committee member) / Wachter, Rebekka (Committee member) / Arizona State University (Publisher)
Created2014
Description
Protein-surface interactions, no matter structured or unstructured, are important in both biological and man-made systems. Unstructured interactions are more difficult to study with conventional techniques due to the lack of a specific binding structure. In this dissertation, a novel approach is employed to study the unstructured interactions between proteins and heterogonous surfaces, by looking at a large number of different binding partners at surfaces and using the binding information to understand the chemistry of binding. In this regard, surface-bound peptide arrays are used as a model for the study. Specifically, in Chapter 2, the effects of charge, hydrophobicity and length of surface-bound peptides on binding affinity for specific globular proteins (&beta-galactosidase and &alpha1-antitrypsin) and relative binding of different proteins were examined with LC Sciences peptide array platform. While the general charge and hydrophobicity of the peptides are certainly important, more surprising is that &beta-galactosidase affinity for the surface does not simply increase with the length of the peptide. Another interesting observation that leads to the next part of the study is that even very short surface-bound peptides can have both strong and selective interactions with proteins. Hence, in Chapter 3, selected tetrapeptide sequences with known binding characteristics to &beta-galactosidase are used as building blocks to create longer sequences to see if the binding function can be added together. The conclusion is that while adding two component sequences together can either greatly increase or decrease overall binding and specificity, the contribution to the binding affinity and specificity of the individual binding components is strongly dependent on their position in the peptide. Finally, in Chapter 4, another array platform is utilized to overcome the limitations associated with LC Sciences. It is found that effects of peptide sequence properties on IgG binding with HealthTell array are quiet similar to what was observed with &beta-galactosidase on LC Science array surface. In summary, the approach presented in this dissertation can provide binding information for both structured and unstructured interactions taking place at complex surfaces and has the potential to help develop surfaces covered with specific short peptide sequences with relatively specific protein interaction profiles.
ContributorsWang, Wei (Author) / Woodbury, Neal W (Thesis advisor) / Liu, Yan (Committee member) / Chaput, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Immunosignaturing is a new immunodiagnostic technology that uses random-sequence peptide microarrays to profile the humoral immune response. Though the peptides have little sequence homology to any known protein, binding of serum antibodies may be detected, and the pattern correlated to disease states. The aim of my dissertation is to analyze the factors affecting the binding patterns using monoclonal antibodies and determine how much information may be extracted from the sequences. Specifically, I examined the effects of antibody concentration, competition, peptide density, and antibody valence. Peptide binding could be detected at the low concentrations relevant to immunosignaturing, and a monoclonal's signature could even be detected in the presences of 100 fold excess naive IgG. I also found that peptide density was important, but this effect was not due to bivalent binding. Next, I examined in more detail how a polyreactive antibody binds to the random sequence peptides compared to protein sequence derived peptides, and found that it bound to many peptides from both sets, but with low apparent affinity. An in depth look at how the peptide physicochemical properties and sequence complexity revealed that there were some correlations with properties, but they were generally small and varied greatly between antibodies. However, on a limited diversity but larger peptide library, I found that sequence complexity was important for antibody binding. The redundancy on that library did enable the identification of specific sub-sequences recognized by an antibody. The current immunosignaturing platform has little repetition of sub-sequences, so I evaluated several methods to infer antibody epitopes. I found two methods that had modest prediction accuracy, and I developed a software application called GuiTope to facilitate the epitope prediction analysis. None of the methods had sufficient accuracy to identify an unknown antigen from a database. In conclusion, the characteristics of the immunosignaturing platform observed through monoclonal antibody experiments demonstrate its promise as a new diagnostic technology. However, a major limitation is the difficulty in connecting the signature back to the original antigen, though larger peptide libraries could facilitate these predictions.
ContributorsHalperin, Rebecca (Author) / Johnston, Stephen A. (Thesis advisor) / Bordner, Andrew (Committee member) / Taylor, Thomas (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
African Swine Fever (ASF), endemic in many African countries, is now spreading to other continents. Though ASF is capable of incurring serious economic losses in affected countries, no vaccine exists to provide immunity to animals. Disease control relies largely on rapid diagnosis and the implementation of movement restrictions and strict eradication programs. Developing a scalable, accurate and low cost diagnostic for ASF will be of great help for the current situation. CIM's 10K random peptide microarray is a new high-throughput platform that allows systematic investigations of immune responses associated with disease and shows promise as a diagnostic tool. In this study, this new technology was applied to characterize the immune responses of ASF virus (ASFV) infections and immunizations. Six sets of sera from ASFV antigen immunized pigs, 6 sera from infected pigs and 20 sera samples from unexposed pigs were tested and analyzed statistically. Results show that both ASFV antigen immunized pigs and ASFV viral infected pigs can be distinguished from unexposed pigs. Since it appears that immune responses to other viral infections are also distinguishable on this platform, it holds the potential of being useful in developing a new ASF diagnostic. The ability of this platform to identify specific ASFV antibody epitopes was also explored. A subtle motif was found to be shared among a set of peptides displaying the highest reactivity for an antigen specific antibody. However, this motif does not seem to match with any antibody epitopes predicted by a linear antibody epitope prediction.
ContributorsXiao, Liang (Author) / Sykes, Kathryn (Thesis advisor) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
Understanding the mechanisms of metalloproteins at the level necessary to engineer new functionalities is complicated by the need to parse the complex overlapping functions played by each amino acid without negatively impacting the host organism. Artificial or designed metallopeptides offer a convenient and simpler platform to explore metal-ligand interactions in an aqueous, biologically relevant coordination context. In this dissertation, the peptide SODA (ACDLPCG), a synthetic derivative of the nickel-binding pocket of nickel superoxide dismutase, is used as a scaffold to construct a variety of novel metallopeptides and explore their reactivity. In Chapter 2, I show that SODA binds Co(II) and the resulting peptide, CoSODA, reacts with oxygen in an unexpected two step process that models the biosynthesis of Co nitrile hydratase. First, the thiolate sulfur is oxidized and then the metallocenter is oxidized to Co(III). In Chapter 3, I show that both CoSODA and CuSODA form CN- adducts. Spectroscopic investigations of these metallopeptides are compared with data from NiSODA and Ni(CN)SODA to show the remarkable geometric versatility of SODA with respect to interactions with metallocenters. In Chapter 4, exploiting the propensity of sulfur ligands to form bridging structures, NiSODA is used as a metallosynthon to direct synthesis of hetero bi- and tri-metallic peptides as models for [NiFe]-hydrogenases and the A cluster of acetyl-CoA synthase carbon monoxide dehydrogenase. Building on this synthetic strategy, in Chapter 5, I demonstrate synthesis of NiRu complexes including a Ru(bipyridine)2 moiety and characterize their photochemistry.
ContributorsDutta, Arnab (Author) / Jones, Anne K (Thesis advisor) / Moore, Ana L (Committee member) / Vermass, Willem (Committee member) / Arizona State University (Publisher)
Created2012
Description
Neurodegenerative diseases such as Alzheimer’s Disease, Parkinson’s Disease and Amyotrophic Lateral Sclerosis are marked by the loss of different types of neurons and glial cells in the central nervous system (CNS). Human Pluripotent Stem Cell (hPSC)-derived Neural Progenitor Cells (hNPCs) have the ability to self-renew indefinitely and to differentiate into various cell types of the CNS. HNPCs can be used in cell based therapies and have the potential to reverse or arrest neurodegeneration and to replace lost neurons and glial cells. However, the lack of completely defined, scalable systems to culture these cells, limits their therapeutic and clinical applications. In a previous study, a completely defined, robust, synthetic peptide- a Vitronectin Derived Peptide (VDP) that supports the long term expansion and differentiation of various embryonic and induced pluripotent stem cell (hESC/hIPSC) derived hNPC lines on two dimensional (2D) tissue culture plates was identified. In this study, the culture of hNPCs was scaled up using VDP coated microcarriers (MC). VDP MC were able to support the long term expansion of hESC and hiPSC derived hNPCs over multiple passages and supported higher fold changes in cell densities, compared to VDP coated 2D surfaces. VDP MC also showed the ability to support the neuronal differentiation of hNPCs, and produced mature neurons expressing several neuronal, neurotransmitter and cortical markers. Additionally, alzheimer’s disease (AD) relevant phenotypes were studied in patient hIPSC derived hNPCs cultured on laminin MC to assess if the MC culture system could be used for disease modelling and drug screening. Finally, a microcarrier based bioreactor system was developed for the large scale expansion of hNPCs, exhibiting more than a five-fold change in cell density and supporting more than 100 million hNPCs in culture. Thus, the development of a xeno-free, scalable system allows hNPC culture under standard and reproducible conditions in quantities required for therapeutic and clinical applications.
ContributorsRajaram Srinivasan, Gayathri (Author) / Brafman, David (Thesis advisor) / Wang, Xiao (Committee member) / Haynes, Karmella (Committee member) / Arizona State University (Publisher)
Created2017
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
While the entire human genome has been sequenced, the understanding of its functional elements remains unclear. The Encyclopedia of DNA Elements (ENCODE) project analyzed 1% of the human genome and found that the majority of the human genome is transcribed, including non-protein coding regions. The hypothesis is that some of the "non-coding" sequences are translated into peptides and small proteins. Using mass spectrometry numerous peptides derived from the ENCODE transcriptome were identified. Peptides and small proteins were also found from non-coding regions of the 1% of the human genome that the ENCODE did not find transcripts for. A large portion of these peptides mapped to the intronic regions of known genes, thus it is suspected that they may be undiscovered exons present in alternative spliceoforms of certain genes. Further studies proved the existence of polyadenylated RNAs coding for these peptides. Although their functional significance has not been determined, I anticipate the findings will lead to the discovery of new splice variants of known genes and possibly new transcriptional and translational mechanisms.
ContributorsWang, Lulu (Author) / Lake, Douglas (Thesis advisor) / Chang, Yung (Committee member) / Touchman, Jeffery (Committee member) / Arizona State University (Publisher)
Created2010
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
Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein target. The predictive performance of computational models of interactions of intermediate-length peptides with proteins can be improved by taking into account the stochastic nature of the encounter and binding dynamics. A theoretical case is made for the hypothesis that, because of the flexibility of the peptide and the structural complexity of the target protein, interactions are best characterized by an ensemble of possible bound configurations rather than a single “lock and key” fit. A model incorporating these factors is proposed and evaluated. A comprehensive dataset of 3,924 peptide-protein interface structures was extracted from the Protein Data Bank (PDB) and descriptors were computed characterizing the geometry and energetics of each interface. The characteristics of these interfaces are shown to be generally consistent with the proposed model, and heuristics for design and selection of peptide ligands are derived. The curated and energy-minimized interface structure dataset and a relational database containing the detailed results of analysis and energy modeling are made publicly available via a web repository. A novel analytical technique based on the proposed theoretical model, Virtual Scanning Probe Mapping (VSPM), is implemented in software to analyze the interaction between a target protein of known structure and a peptide of specified sequence, producing a spatial map indicating the most likely peptide binding regions on the protein target. The resulting predictions are shown to be superior to those of two other published methods, and support the validity of the stochastic binding model.
ContributorsEmery, Jack Scott (Author) / Pizziconi, Vincent B (Thesis advisor) / Woodbury, Neal W (Thesis advisor) / Guilbeau, Eric J (Committee member) / Stafford, Phillip (Committee member) / Taylor, Thomas (Committee member) / Towe, Bruce C (Committee member) / Arizona State University (Publisher)
Created2010