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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
ContributorsCarlisi, Daniel (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-07
ContributorsHan, Sarah (Performer) / Kim, Hyewon Rina (Performer) / Chen, Neilson (Performer) / ASU Library. Music Library (Contributor)
Created2018-04-07
Description
To address sustainability issues in wastewater treatment (WWT), Siemens Water Technologies (SWT) has designed a "hybrid" process that couples common activated sludge (AS) and anaerobic digestion (AD) technologies with the novel concepts of AD sludge recycle and biosorption. At least 85% of the hybrid's AD sludge is recycled to the AS process, providing additional sorbent for influent particulate chemical oxygen demand (PCOD) biosorption in contact tanks. Biosorbed PCOD is transported to the AD, where it is converted to methane. The aim of this study is to provide mass balance and microbial community analysis (MCA) of SWT's two hybrid and one conventional pilot plant trains and mathematical modeling of the hybrid process including a novel model of biosorption. A detailed mass balance was performed on each tank and the overall system. The mass balance data supports the hybrid process is more sustainable: It produces 1.5 to 5.5x more methane and 50 to 83% less sludge than the conventional train. The hybrid's superior performance is driven by 4 to 8 times longer solid retention times (SRTs) as compared to conventional trains. However, the conversion of influent COD to methane was low at 15 to 22%, and neither train exhibited significant nitrification or denitrification. Data were inconclusive as to the role of biosorption in the processes. MCA indicated the presence of Archaea and nitrifiers throughout both systems. However, it is inconclusive as to how active Archaea and nitrifiers are under anoxic, aerobic, and anaerobic conditions. Mathematical modeling confirms the hybrid process produces 4 to 20 times more methane and 20 to 83% less sludge than the conventional train under various operating conditions. Neither process removes more than 25% of the influent nitrogen or converts more that 13% to nitrogen gas due to biomass washout in the contact tank and short SRTs in the stabilization tank. In addition, a mathematical relationship was developed to describe PCOD biosorption through adsorption to biomass and floc entrapment. Ultimately, process performance is more heavily influenced by the higher AD SRTs attained when sludge is recycled through the system and less influenced by the inclusion of biosorption kinetics.
ContributorsYoung, Michelle Nichole (Author) / Rittmann, Bruce E. (Thesis advisor) / Fox, Peter (Committee member) / Krajmalnik-Brown, Rosa (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
ContributorsLougheed, Julia (Performer) / Novak, Gail (Pianist) (Performer) / Bayer, Elizabeth Kennedy (Performer) / Clifton-Armenta, Tyler (Performer) / Park, Julie (Performer) / Javier de Alba, Francisco (Performer) / Vientos Dulces (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-07
ContributorsSong, Yiqian (Performer) / Hankins, Kim (Performer) / Pendleton, Aaron (Performer) / Miller, Isaac (Performer) / Hsu, Gabrielle (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-08
ContributorsPercussion Jazz Ensemble (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-16
ContributorsASU Library. Music Library (Publisher)
Created2018-04-19
ContributorsASU Library. Music Library (Publisher)
Created2018-04-14