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- All Subjects: Immunology
Description
Human papillomavirus (HPV) is the causative agent of cervical cancer. Persistent infection with high-risk HPV 16, 18 or 45 species is associated with the development and progression of cervical cancer. HPV genotyping and Pap smear tests are the regular methods used to detect pre-invasive cervical lesions, but there is a need for developing a rapid biomarker to profile immunity to these viruses. The viral E7 oncogene is expressed in most HPV-associated cancers and anti-E7 antibodies can be detected in the blood of patients with cervical cancer. This research was focused on viral E7 oncogene expression to be used in development of low-cost point of care tests, enabling patients from low resource settings to detect the asymptotic stage of cervical cancer and be able to seek treatment early. In order to produce the E7 protein in vitro to measure antibody levels, GST tagged E7 genes from HPV 16, 18 and 45 species were inserted into the pDEST15 vector and expressed in E. coli BL21DE3 cells that were induced with 1mM of IPTG. The E7-GST fused expressed protein was then purified using glutathione beads and resolved on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Protein expression was 5.8 \u03bcg/ml for HPV 16E7 in 500 ml culture and for the 500 ml culture of HPV 18 E7 and 45 E7 were 10.5 \u03bcg/ml and 10.5 \u03bcg/ml for HPV 18E7 and 45E7 respectively. High yield values are showing high expression levels of GST-tagged E7 recombinant protein which can be used for serotyping a number of individuals. This shows that HPV E7 can be produced in large quantities that can potentially be used in point of care tests that can help identify women at risk of cervical cancer. In conclusion, the E7 protein produced in this study can potentially be used to induce humoral responses in patients\u2019 sera for understanding the immune response of cervical cancer.
ContributorsMakuyana, Ntombizodwa (Author) / Anderson, Karen (Thesis director) / Ewaisha, Radwa (Committee member) / Varsani, Arvind (Committee member) / Hou, Ching-Wen (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
Description
Poxviruses such as monkeypox virus (MPXV) are emerging zoonotic diseases. Compared to MPXV, Vaccinia virus (VACV) has reduced pathogenicity in humans and can be used as a partially protective vaccine against MPXV. While most orthopoxviruses have E3 protein homologues with highly similar N-termini, the MPXV homologue, F3, has a start codon mutation leading to an N-terminal truncation of 37 amino acids. The VACV protein E3 consists of a dsRNA binding domain in its C-terminus which must be intact for pathogenicity in murine models and replication in cultured cells. The N-terminus of E3 contains a Z-form nucleic acid (ZNA) binding domain and is also required for pathogenicity in murine models. Poxviruses produce RNA transcripts that extend beyond the transcribed gene which can form double-stranded RNA (dsRNA). The innate immune system easily recognizes dsRNA through proteins such as protein kinase R (PKR). After comparing a vaccinia virus with a wild-type E3 protein (VACV WT) to one with an E3 N-terminal truncation of 37 amino acids (VACV E3Δ37N), phenotypic differences appeared in several cell lines. In HeLa cells and certain murine embryonic fibroblasts (MEFs), dsRNA recognition pathways such as PKR become activated during VACV E3Δ37N infections, unlike VACV WT. However, MPXV does not activate PKR in HeLa or MEF cells. Additional investigation determined that MPXV produces less dsRNA than VACV. VACV E3Δ37N was made more similar to MPXV by selecting mutants that produce less dsRNA. By producing less dsRNA, VACV E3Δ37N no longer activated PKR in HeLa or MEF cells, thus restoring the wild-type phenotype. Furthermore, in other cell lines such as L929 (also a murine fibroblast) VACV E3Δ37N, but not VACV WT infection leads to activation of DNA-dependent activator of IFN-regulatory factors (DAI) and induction of necroptotic cell death. The same low dsRNA mutants demonstrate that DAI activation and necroptotic induction is independent of classical dsRNA. Finally, investigations of spread in an animal model and replication in cell lines where both the PKR and DAI pathways are intact determined that inhibition of both pathways is required for VACV E3Δ37N to replicate.
ContributorsCotsmire, Samantha (Author) / Jacobs, Bertram L (Thesis advisor) / Varsani, Arvind (Committee member) / Hogue, Brenda (Committee member) / Haydel, Shelley (Committee member) / Arizona State University (Publisher)
Created2021
Description
The human papillomavirus (HPV) is a double-stranded DNA virus responsible for causing upwards of 80% of head and neck cancers in the oropharyngeal region. Current treatments, including surgery, chemotherapy, and/or radiation, are aggressive and elicit toxic effects. HPV is a pathogen that expresses viral-specific oncogenic proteins that play a role in cancer progression. These proteins may serve as potential targets for immunotherapeutic applications. Engineered T cell receptor (TCR) therapy may be an advantageous approach for HPV-associated cancers. In TCR therapy, TCRs are modified to express a receptor that is specific to an immunogenic antigen (part of the virus/cancer capable of eliciting an immune response). Since HPV-associated oropharyngeal cancers typically express unique viral proteins, it is important to identify the TCRs capable of recognizing these proteins. Evidence supports that head and neck cancers typically experience high levels of immune cell infiltration and are subsequently associated with increased survival rates. Most of the immune cell infiltrations in HPV+ HNSCC are CD8+ T lymphocytes, drawing attention to their prospective use in cellular immunotherapies. While TCRs are highly specific, the TCR repertoire is extremely diverse; enabling the immune system to fight off numerous pathogens. In project 1, I review approaches to analyzing TCR diversity and explore the use of DNA origami in retrieving paired TCR sequences from a population. The results determine that DNA origami can be used within a monoclonal population but requires further optimization before being applied in a polyclonal setting. In project 2, I investigate HPV-specific T-cell dysfunction; I detect low frequency HPV-specific CD8+ T cells, determine that they are tumor specific, and show that HPV+HNSCC patients exhibit increased epitope-specific levels of CD8+T cell exhaustion. In project 3, I apply methods to expand and isolate TCRαβ sequences derived from donors stimulated with a previously identified HPV epitope. Single-cell analysis provide ten unique TCRαβ pairs with corresponding CDR3 sequences that may serve as therapeutic candidates. This thesis contributes to fundamental immunology by contributing to the knowledge of T cell dysfunction within HPV+HNSCC and further reveals TCR gene usage within an HPV stimulated population, thus identifying potential TCR pairs for adoptive cell therapies.
ContributorsUlrich, Peaches Rebecca (Author) / Anderson, Karen S (Thesis advisor) / Lake, Douglas (Committee member) / Maley, Carlo (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2020
Description
Elucidation of Antigen-Antibody (Ag-Ab) interactions is critical to the understanding of humoral immune responses to pathogenic infection. B cells are crucial components of the immune system that generate highly specific antibodies, such as IgG, towards epitopes on antigens. Serum IgG molecules carry specific molecular recognition information concerning the antigens that initiated their production. If one could read it, this information can be used to predict B cell epitopes on target antigens in order to design effective epitope driven vaccines, therapies and serological assays. Immunosignature technology captures the specific information content of serum IgG from infected and uninfected individuals on high density microarrays containing ~105 nearly random peptide sequences. Although the sequences of the peptides are chosen to evenly cover amino acid sequence space, the pattern of serum IgG binding to the array contains a consistent signature associated with each specific disease (e.g., Valley fever, influenza) among many individuals. Here, the disease specific but agnostic behavior of the technology has been explored by profiling molecular recognition information for five pathogens causing life threatening infectious diseases (e.g. DENV, WNV, HCV, HBV, and T.cruzi). This was done by models developed using a machine learning algorithm to model the sequence dependence of the humoral immune responses as measured by the peptide arrays. It was shown that the disease specific binding information could be accurately related to the peptide sequences used on the array by the machine learning (ML) models. Importantly, it was demonstrated that the ML models could identify or predict known linear epitopes on antigens of the four viruses. Moreover, the models identified potential novel linear epitopes on antigens of the four viruses (each has 4-10 proteins in the proteome) and of T.cruzi (a eukaryotic parasite which has over 12,000 proteins in its proteome). Finally, the predicted epitopes were tested in serum IgG binding assays such as ELISAs. Unfortunately, the assay results were inconsistent due to problems with peptide/surface interactions. In a separate study for the development of antibody recruiting molecules (ARMs) to combat microbial infections, 10 peptides from the high density peptide arrays were tested in IgG binding assays using sera of healthy individuals to find a set of antibody binding termini (ABT, a ligand that binds to a variable region of the IgG). It was concluded that one peptide (peptide 7) may be used as a potential ABT. Overall, these findings demonstrate the applications of the immunosignature technology ranging from developing tools to predict linear epitopes on pathogens of small to large proteomes to the identification of an ABT for ARMs.
ContributorsCHOWDHURY, ROBAYET (Author) / Woodbury, Neal (Thesis advisor) / LaBaer, Joshua (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2020