Model of Paradoxical Signaling Regulated T-Cell Population Control for Design of Synthetic Circuits

Paradoxical signaling occurs when the same signaling molecule can trigger antagonistic cell functions. For example, T-Cells secret cytokine IL-2 which promotes T-Cell proliferation and also affects cell death. It has been shown that cells with this signaling capability have bi-stable population dynamics. Cells can achieve identical levels of population homeostasis for initial cell concentrations within the region of attraction. These capabilities are desirable in the context of synthetic population control circuits designed for application in therapeutic treatment of various diseases. It thus becomes important to understand the dependence of the cell system on the intracellular paradoxical components and to develop accurate models to provide insight into optimal design characteristics. Here, we create a model that integrates three IL-2 driven intracellular mechanisms that trigger 1) T-cell proliferation 2) T-cell apoptosis and 3) IL-2 production. Using this model, we are able to explore the internal mechanisms necessary for paradoxical signaling in T-Cells. It was shown that the intracellular mechanisms considered were sufficient to produce population dynamic characteristics of paradoxical signaling consistent with published systems level models and data. Furthermore, analysis of parameters revealed dependency of population bistability on the production and activation of the specific intracellular proteins considered

Theoretical Design of Paradoxical Signaling-Based Synthetic Population Control Circuit in E. coli

We have developed a mathematical framework to analyze the cooperative control of cell population homeostasis via paradoxical signaling in synthetic contexts. Paradoxical signaling functions through quorum sensing (where cells produce and release a chemical signal as a function of cell density). Precisely, the same quorum sensing signal provides both positive (proliferation) and negative (death) feedback in different signal concentration regimes. As a consequence, the relationship between intercellular quorum sensing signal concentration and net growth rate (cell proliferation minus death rates) can be non-monotonic. This relationship is a condition for robustness to certain cell mutational overgrowths and allows for increased stability in the presence of environmental perturbations. Here, we explore stability and robustness of a conceptualized synthetic circuit. Furthermore, we asses possible design principles that could exist among a subset of paradoxical circuit implementations. This analysis sparks the development a bio-molecular control theory to identify ideal underlying characteristics for paradoxical signaling control systems

Synthetic mammalian signaling circuits for robust cell population control

In multicellular organisms, cells actively sense, respond to, and control their own population density. Synthetic mammalian quorum sensing circuits could provide insight into principles of population control and improve cell therapies. However, a key challenge is avoiding their inherent sensitivity to “cheater” mutations that evade control. Here, we repurposed the plant hormone auxin to enable orthogonal mammalian cell-cell communication and quorum sensing. Further, we show that a “paradoxical” circuit design, in which auxin stimulates and inhibits net cell growth at different concentrations, achieves population control that is robust to cheater mutations, controlling growth for 43 days of continuous culture. By contrast, a non-paradoxical control circuit limited growth but was susceptible to mutations. These results establish a foundation for future cell therapies that can respond to and control their own population sizes

Multicellular Synthetic Biology in Mammalian Systems

In multicellular organisms, different types of cells use intercellular signals to communicate and regulate population dynamics, and further coordinate complex behaviors. This presents a rarely tapped into potential for mammalian synthetic biology, which was largely restricted to engineering a single cell type in the past to mimic and use similar multicellular designs to achieve more functionalities. However, with current synthetic biology tools and designs, there are several major challenges to achieve a multicellular circuit. Challenges include precise and tunable control over cell type switching, having an orthogonal cell-cell communication signal, and robust control of cell populations. To address these challenges, this thesis presents a system for tunable regulating of gene expression with DNA methylation, an auxin-based module for mammalian cell-cell communication, and a robust circuit for population control in mammalian cells. I further applied these work to engineering immune cells to show the potential of multicellular circuits in immunotherapies. Together, these works demonstrated the possibility of constructing multicellular circuits in mammalian systems, and that multicellular circuit can further extend the scope of synthetic biology to achieve more complex functions.</p

Programming stress-induced altruistic death in engineered bacteria.

Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is 'altruistic': the killing of some cells can benefit the survivors through release of 'public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the 'Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment

Enzyme sequestration as a tuning point in controlling response dynamics of signalling networks

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications

Programmable protein circuits in living cells

Synthetic protein-level circuits could enable engineering of powerful new cellular behaviors. Rational protein circuit design would be facilitated by a composable protein-protein regulation system in which individual protein components can regulate one another to create a variety of different circuit architectures. In this study, we show that engineered viral proteases can function as composable protein components, which can together implement a broad variety of circuit-level functions in mammalian cells. In this system, termed CHOMP (circuits of hacked orthogonal modular proteases), input proteases dock with and cleave target proteases to inhibit their function. These components can be connected to generate regulatory cascades, binary logic gates, and dynamic analog signal-processing functions. To demonstrate the utility of this system, we rationally designed a circuit that induces cell death in response to upstream activators of the Ras oncogene. Because CHOMP circuits can perform complex functions yet be encoded as single transcripts and delivered without genomic integration, they offer a scalable platform to facilitate protein circuit engineering for biotechnological applications

Reverse genetics in Candida albicans predicts ARF cycling is essential for drug resistance and virulence

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