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- All Subjects: Immunology
- Creators: Borges Florsheim, Esther
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
Mast cells, components of the immune system, promote allergic symptoms such as itching, sneezing, and increased intestinal motility. Although mast cells have a detrimental role in allergies, they might have unrecognized physiological functions. Indeed, mast cells have been reported to protect against lethal envenomation. I hypothesized that mast cells have a protective role in the defense against toxins. Because toxin-induced diarrheal diseases are one of the top five causes of mortality in children worldwide (induced by cholera toxin, for example), I tested the role of mast cells in sensing relevant dietary toxins. My goals were to a) establish an in vitro model of mast cell activation using foodborne toxins and b) determine the mast cell transcriptional programs induced by these toxins. To establish the in vitro model, I generated mast cells from murine bone marrow precursors and cultured them in mast cell-specific media for 5 weeks. Mature mast cells were then stimulated with toxins from phylogenetically distinct origins. I found that, surprisingly, no toxin was able to induce significant cell death, even after 24h of culturing, suggesting that mast cells are resistant to the toxic effects of these compounds. To assess mast cell activation, I quantified the levels of TNF-α 6h after toxin exposure. None of the toxins were able to induce TNF-α production by mast cells, suggesting that toxins might not induce inflammation in mast cells. However, I found that mast cells induced expression of activation-related transcripts like Il1b, Tpsab1, Alox5, Egr1, Tnfa and Hdc in response to cholera toxin, when compared with controls. Mast cells stimulated with retrorsine induced the expression of Tph1, Alox5, Il1b and Hdc. Deoxynivalenol induced Ltc4, Il6, Tpsab1, Tnfa, Hdc, and Alox5 while okadaic acid induced Il6, Tnfa, Tph1, Alox5, Egr1, Il1b and Hdc expression. Aconitine only induced Il6, Hdc, and Tpsab1. Lastly, Ochratoxin A induced expression of Il1b, Il6, Tpsab1, Egr1 and Hdc. Altogether, these results suggest that mast cells directly sense and respond to food toxins, which was unknown. How exactly mast cells contribute to toxin defenses will be crucial to investigate as they impact both toxin-induced and inflammatory diseases.
ContributorsGalarza, Mayka (Author) / Borges Florsheim, Esther (Thesis advisor) / Lucas, Alexandra (Committee member) / Mana, Miyeko (Committee member) / Arizona State University (Publisher)
Created2023
Description
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative pathogen of Coronavirus Disease 2019 (COVID-19). Successful vaccination aims to elicit neutralizing antibodies (NAbs) which inhibit viral infection. Traditional NAb quantification methods (neutralization assays) are labor-intensive and expensive, with limited practicality for routine use (e.g. monitoring vaccination response). Thus, a rapid (10-minute) lateral flow assay (LFA) for quantification of SARS-CoV-2 NAbs was developed. Using the NAb LFA, an 18-month longitudinal study assessing monthly NAb titers was conducted in a cohort of over 500 COVID-19 mRNA vaccine recipients. Three NAb response groups were identified: vaccine strong responders (VSRs), moderate responders (VMRs), and poor responders (VPRs). VSRs generated high and durable NAb titers. VMRs initially generated high NAb titers but showed more rapid waning with time post-vaccination. Finally, VPRs rarely generated NAb titers ≥1:160, even after 3rd dose. Although strong humoral responses correlate with vaccine effectiveness, viral-specific CD4+ and CD8+ T cells are critical for long-term protection. Discordant phenotypes of viral-specific CD8+ and CD4+CXCR5+ T follicular helper (cTfh) cells have recently been associated with differential NAb responses. The second portion of this dissertation was to investigate whether/how SARS-CoV-2 T cell responses differ in individuals with impaired NAb titers following mRNA vaccination. Thus, phenotypic and functional characterization of T cell activation across NAb response groups was conducted. It was hypothesized that VPRs would exhibit discordant SARS-CoV-2 T cell activation and altered cTfh phenotypes. Peripheral blood mononuclear cells were isolated from VPRs, VMRs, VSRs, naturally infected, and normal donors. SARS-CoV-2 responsive T cells were characterized using in vitro activation induced marker assays, multicolor flow cytometry, and multiplex cytokine analysis. Further, CXCR5+ cTfh were examined for chemokine receptor expression (CCR6 and CXCR3). Results demonstrated that despite differential NAb responses, activation of SARS-CoV-2 responsive CD4+ and CD8+ T cells was comparable across NAb groups. However, double-positive CD4+CD8+, CD8low, and activated CD4+CXCR5+CCR6-CXCR3+ (Tfh1-like) T cells were expanded in VPRs compared to VMR and VSRs. Interestingly, a unique population of CD8+CXCR5+ T cells was also expanded in VPRs. These novel findings may aid in identification of individuals with impaired or altered immune responses to COVID-19 mRNA vaccination.
ContributorsRoeder, Alexa Jordan (Author) / Lake, Douglas (Thesis advisor) / McFadden, Grant (Committee member) / Borges Florsheim, Esther (Committee member) / Chang, Yung (Committee member) / Rahman, Masmudur (Committee member) / Arizona State University (Publisher)
Created2023
Description
Purinergic receptors sense extracellular nucleotide DAMPs such as ATP and adenosine, which are expressed in high concentrations in the tumor microenvironment (TME). A2AR, an adenosine receptor that is expressed on both T cells and tumor cells, promotes immunosuppression. However, the impact of the TME on changes in purinergic receptor expression on CD8 T cells, as well as the overall dynamic between A2AR expression and tumor control, have not been clearly elucidated. Using in vitro co-culture experiments and in vivo murine tumor models, we found that A2AR is significantly upregulated on effector, tumor-infiltrating CD8 T cells. This upregulation was independent of the hypoxia, which we identified via inhibition of HIF1A. We found that this upregulation was partially dependent on CD8 T cell-tumor contact, but independent of cognate antigen recognition, by using transwell co-cultures, as well as combinations of different transgenic lines of CD8 T cells and tumor cells. We confirmed this observation in vivo using transfer of activated OTI cells into B16.OVA-bearing mice. Ultimately, we observed that the upregulation depended on inhibitory receptors such as Tim3 via the antibody blockade of Tim3. Using CRISPR/Cas9-mediated knockout of A2AR on activated CD8 T cells, we found that tumor-bearing mice receiving A2AR knockout CD8 T cells had increased tumor control. Taken together, these results suggest that inhibitory receptor-dependent, TCR-independent signals in the TME promotes upregulation of A2AR on CD8 T cells, leading to impairment of CD8 T cell-mediated tumor control.
ContributorsZhou, Maggie (Author) / Borges da Silva, Henrique (Thesis director) / Borges Florsheim, Esther (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Economics Program in CLAS (Contributor)
Created2022-12
Description
Peptide-based vaccines represent a promising strategy to develop personalized treatments for cancer immunotherapy. Despite their specificity and low cost of production, these vaccines have had minimal success in clinical studies due to their lack of immunogenicity, creating a need for more effective vaccine designs. Adjuvants can be incorporated to enhance their immunogenicity by promoting dendritic cell activation and antigen cross-presentation. Due to their favorable size and ability to incorporate peptides and adjuvants, nanoparticles represent an advantageous platform for designing peptide vaccines. One prime example is RNA origami (RNA-OG) nanostructures, which are nucleic acid nanostructures programmed to assemble into uniform shapes and sizes. These stable nanostructures can rationally incorporate small molecules giving them a wide array of functions. Furthermore, RNA-OG itself can function as an adjuvant to stimulate innate immune cells. In the following study, self-adjuvanted RNA-OG was employed as a vaccine assembly platform, incorporating tumor peptides onto the nanostructure to design RNA-OG-peptide nanovaccines for cancer immunotherapy. RNA-OG-peptide was found to induce dendritic cell activation and antigen cross-presentation, which mobilized tumor-specific cytotoxic T cells to elicit protective anti-tumor immunity in tumor-bearing mice. These findings demonstrate the therapeutic potential of RNA-OG as a stable, carrier-free nanovaccine platform. In an attempt to further enhance the efficacy by optimizing the amount of peptides assembled, RNA-OG was complexed with polylysine-linked peptides, a simple strategy that allowed peptide amounts to be varied. Interestingly, increasing the peptide load led to decreased vaccine efficacy, which was correlated with an ineffective CD8+ T cell response. On the other hand, the vaccine efficacy was improved by decreasing the amount of peptide loaded onto RNA-OG, which may have attributed to greater complex stability compared to the high peptide load. These results highlight a simple strategy that can be used to optimize vaccine efficacy by altering the load of assembled peptides. These studies advance our understanding of RNA-OG as a peptide vaccine platform and provide various strategies to improve the design of peptide vaccines for translation into cancer immunotherapy.
ContributorsYip, Theresa (Author) / Chang, Yung (Thesis advisor) / Borges Florsheim, Esther (Committee member) / Lake, Douglas (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2024
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