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Item Mathematical Modeling of Cellular Exhaustion to Guide Future Immunotherapy Research(2024) Simmons, Tyler; Levy, Doron; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Cellular exhaustion is a dysfunction found in various adaptive immune cells. In chronic settings, like cancer, antigen persistence and prolonged stimulation initiates the development of T cell exhaustion. The exhausted T cell population is a distinct lineage consisting of progenitor exhausted CD8+ T cells and terminally exhausted CD8+ T cells and is characterized by an upregulation of inhibitory receptor frequencies and diminished effector functions. The hypofunctionality of exhausted T cells prevents proper immunity and fails to eradicate the tumor. Recent years have shown a growing interest in targeting T cell exhaustion, attempting to reinvigorate effector functions, as a form of immunotherapy. Though beneficial responses have been reported in clinical settings, patient responses are inconsistent. Complementing the current biological understanding of T cell exhaustion and to advance immunotherapeutic efforts, novel research using mathematical modeling offers valuable insight. Constructing a foundational framework of an exhausted immune response to cancer provides an alternative approach to understanding the tumor-immune system. Presented here is the construction of a mathematical model detailing the development of progenitor and terminally exhausted CD8+ T cell populations in response to a growing tumor. Parameterization and simulation of this model captures biological dynamics observed in experimental and clinical settings. Analysis and conclusions of this model suggest population size and maintenance of progenitor exhausted CD8+ T cells should be a pillar of immunotherapy efforts. Stemming from these conclusions, it was theorized that targeting exhausted CD4+ helper T cells, which, under normal non-chronic conditions, contribute heavily to CD8+ T cell responses, would be a new and effective approach for immunotherapy. To test this hypothesis, the previously constructed model of CD8+ T cell exhaustion was expanded to incorporate CD4+ helper 1 T cells as well as immunosuppressive regulatory T cells. Simulation and analysis of this expanded model further emphasize the need to maintain progenitor exhausted CD8+ T cell numbers. Additionally, model analysis also indicated that the functionality of CD4+ T cells, both regulatory and exhausted CD4+ helper 1 T cells, played a crucial role in tumor persistence. From this work, research regarding CD4+ T cell exhaustion is strongly encouraged. With a better understanding of this dysfunction, CD4+ T cells may be a potentially effective target for future immunotherapy strategies.Item SCALABLE MODELING APPROACHES IN SYSTEMS IMMUNOLOGY(2020) Park, Kyemyung; Levy, Doron; Tsang, John S; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Systems biology seeks to build quantitative predictive models of biological system behavior. Biological systems, such as the mammalian immune system, operate across multiple spatiotemporal scales with a myriad of molecular and cellular players. Thus, mechanistic, predictive models describing such systems need to address this multiscale nature. A general outstanding problem is to cope with the high-dimensional parameter space arising when building reasonably detailed models. Another challenge is to devise integrated frameworks incorporating behavioral characteristics manifested at various organizational levels seamlessly. In this dissertation, I present two research projects addressing problems in immunological, or biological systems in general, using quantitative mechanistic models and machine learning, touching on the aforementioned challenges in scalable modeling. First, I aimed to understand how cell-to-cell heterogeneities are regulated through gene expression variations and their propagation at the single-cell level. To better understand detailed gene regulatory circuit models with many parameters without analytical solutions, I developed a framework called MAchine learning of Parameter-Phenotype Analysis (MAPPA). MAPPA combines machine learning approaches and stochastic simulation methods to dissect the mapping between high- dimensional parameters and phenotypes. MAPPA elucidated regulatory features of stochastic gene-gene correlation phenotypes. Next, I sought to quantitatively dissect immune homeostasis conferring tolerance to self-antigens and responsiveness to foreign antigens. Towards this goal, I built a series of models spanning from intracellular to organismal levels to describe the recurrent reciprocal relationships between self-reactive T cells and regulatory T cells in collaboration with an experimentalist. This effort elucidated critical immune parameters regulating the circuitry enabling the robust suppression of self-reactive T cells, followed by experimental validation. Moreover, by bridging these models across organizational scales, I derived a framework describing immune homeostasis as a dynamical equilibrium between self-activated T cells and regulatory T cells, typically operating well below thresholds that could result in clonal expansion and subsequent autoimmune diseases. I start with an introduction with a perspective linking seemingly contradictory behaviors of the immune system at different scales: microscopic “noise” and macroscopic deterministic outcomes. By connecting these aspects in the adaptive immune system analogously with an ansatz from statistical physics, I introduced a view on how robust immune homeostasis ensues.Item RECEPTOR MOBILITY AND CYTOSKELETAL DYNAMICS AT THE IMMUNE SYNAPSE: THE ROLE OF ACTIN REGULATORY PROTEINS(2020) Rey Suarez, Ivan Adolfo; Upadhyaya, Arpita; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Spatial and temporal regulation of actin and microtubule dynamics is of utmost importance for many cellular processes at different sub-cellular length scales. This is particularly relevant for cells of the immune system, which must respond rapidly and accurately to protect the host, where B cells and T cells are the main players during the adaptive immune response. An understanding of the biophysical principles underlying cytoskeletal dynamics and regulation of signaling will help elucidate the fundamental mechanisms driving B and T cell immune response. B cell receptor (BCR) diffusivity is modulated by signaling activation, however the factors linking mobility and signaling state are not completely understood. I used single molecule imaging to examine BCR mobility during signaling activation and a novel machine learning based method to classify BCR trajectories into distinct diffusive states. Inhibition of actin dynamics downstream of the actin nucleating factors Arp2/3 and formins resulted decreased BCR mobility. Loss of the Arp2/3 regulator, N-WASP, which is associated with enhanced signaling, leads to a predominance of BCR trajectories with lower diffusivity. Furthermore, loss of N-WASP reduces diffusivity of the stimulatory co-receptor CD19, but not that of unstimulated FcγRIIB, an inhibitory co-receptor. Our results implicate the dynamic actin network in fine-tuning receptor mobility and receptor-ligand interactions, thereby modulating B cell signaling. Activation of T cells leads to the formation of the immunological synapse (IS) with an antigen presenting cell (APC). This requires T cell polarization and coordination between the actomyosin and microtubule cytoskeleton. The interactions between the different cytoskeletal components during T cell activation are not well understood. I use high-resolution fluorescence microscopy to study actin-microtubule crosstalk during IS formation. Microtubules in actin rich zones display more deformed shapes and higher dynamics compared to MTs at the actin-depleted region. Chemical inhibition of formin and myosin activation reduced MT deformations, suggesting that actomyosin contractility plays an important role in defining MT shapes. Interestingly MT growth was slowed by formin inhibition and resulting enrichment of Arp2/3 nucleated actin networks. These observations indicate an important mechanical coupling between the actomyosin and microtubule systems where different actin structures influence microtubule dynamics in distinct ways.Item Mechanobiology of T cell activation(2015) Hui, King Lam; Upadhyaya, Arpita; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Cells can sense and respond to the physical environment through generation and transmission of mechanical forces from the surroundings to the cell interior and from one cell to another. This dissertation focuses on mechanosensing by T cells, key players in the adaptive immune system, which form a strong line of defense against infections by their ability to recognize foreign molecules and develop an appropriate response. T cells form close contact with an opposing antigen presenting cell upon recognition of protein fragments derived from infecting pathogens (antigens). Recent studies have shown that externally applied forces can trigger biochemical signaling in T cells. How forces are internally generated by T cells, involved in signaling and transmitted at the level of the cell interface, remains unclear. In this thesis, we investigate the molecular mechanisms of force generation by T cells and their response to forces and the stiffness of the opposing surface. We have quantitatively characterized the initial phase of T cell contact with a model of antigen-bearing surfaces. We observe that T cells spread on such substrates and that the kinetics of spreading follows a universal function, with the spreading rate dependent on actin polymerization and myosin II activity. Altering cell-substrate adhesions leads to qualitative changes in cell spreading dynamics and wave-like patterns of actin dynamics. We then used soft elastic substrates with stiffness comparable to that of antigen presenting cells, to measure the forces generated by T cells during activation. Perturbation experiments reveal that these forces are largely due to actin assembly and dynamics, with myosin contractility contributing to the development of traction forces but not its maintenance. We find that Jurkat T-cells are mechanosensitive, with both traction forces and signaling dynamics exhibiting sensitivity to the stiffness of the substrate. We further demonstrate that dynamics of the T cell microtubule cytoskeleton also participates in regulating forces at the cell-substrate interface, through the Rho/ROCK pathway which regulates myosin II light chain phosphorylation. Overall, this work highlights physical force as an essential mediator that connects stiffness sensing to intracellular signaling, which then directs gene expression and eventually the immune response in T cells.