Model-driven elucidation of synthetic and immune signaling mechanisms

Muldoon, Joseph Jacob

doi:https://doi.org/10.21985/n2-zsad-r426

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Model-driven elucidation of synthetic and immune signaling mechanisms

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This dissertation focuses on the development of quantitative approaches for characterizing endogenous signaling pathways and designing new pathways in mammalian cells. I demonstrate how mathematical descriptions that are formulated to explain gene expression patterns can also serve as a powerful springboard for deeper analyses into the properties and functions of pathways. Throughout, a recurring theme is that by measuring the behaviors of single cells and building models that directly incorporate these observations, we are better equipped (1) to uncover fundamental biological mechanisms and (2) to achieve genetic engineering design goals. To the first point, I investigated the macrophage response to pathogenic stimulus. Heterogeneity is a hallmark of this cell type, but whether or how this variation relates to protective immune functions is not well understood. By integrating single-cell tracking and dynamical systems modeling approaches, I identified a previously unrecognized form of intercellular coordination that we termed quorum licensing. I found that macrophages track the history of their density, and then in a manner independent of previous explanations for how cytokine production is amplified in this system, the cells preemptively decide on the proportion of the population that will become highly activated in response to an inflammatory cue. This behavior involves coordinating heterogeneous cellular activation states in a way that generates a nonlinear response at the population level. The role of this newly defined collective decision-making strategy might be to both amplify inflammatory responses and limit them within sites of injury. To the second point, cells have a vast capacity to be repurposed, and engineered cell-based devices are finding applications in the targeted treatment of diseases. Because the genetic components such as synthetic receptors and transcription factors for building cellular functions are nascent, quantitative principles governing their effective integration are very much needed. I developed statistical and dynamical modeling approaches to elucidate mechanisms by which a variety of genetic parts operate. I subsequently demonstrated an approach for predictively implementing complex genetic programs in mammalian cells. These efforts, and the collaborations they entail, comprise part of a transformation in the field of mammalian synthetic biology from a reliance upon biophysical intuition to the utilization of model-guided interpretation and design. By imparting greater specificity to activation and robust performance to heterogeneity, in the long-term these studies can inform more effective and sophisticated cell-based devices.

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