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Engineering Responsive Yeast Systems Using Fungal G-Protein-Coupled Receptors

Communication is a ubiquitous component of life. While complexity and sophistication vary, both unicellular and multicellular organisms constantly interact with their environment. Unicellular organisms, once thought to be asocial, have since been demonstrated to display a multitude of social interactions and hierarchies. For example, quorum sensing enables a bacterial population to modulate gene expression in response to cell-population density, initiating social behavior and the exchange of resources. In eukaryotes, unicellular ascomycete fungi use mating GPCRs to detect secreted peptide pheromones, initiating changes in gene expression required for mating. An overview of communication in unicellular organisms is presented in Chapter 1.
In general, these communication systems are characterized by a high degree of fidelity, and as such have been harvested by synthetic biologists to organize communication in synthetic systems. Quorum sensing modules have been employed for pattern formation and to coordinate biosynthesis processes across a community. However, fungal mating remains underutilized as a source of synthetic biology tools.
In this dissertation, we leverage fungal mating G-protein-coupled receptors (GPCRs) and their peptide ligands to build responsive yeast systems. We use genome-mining to identify additional fungal peptide-GPCR pairs, which are then characterized in the yeast Saccharomyces cerevisiae. In Chapter 2, we exploit the high specificity and sensitivity of fungal mating GPCRs to design a yeast whole-cell biosensor that produces a visible output in response to detection of peptide biomarkers. In Chapter 3, we genome-mine additional peptide-GPCR pairs and use them as orthogonal signaling channels to build synthetic yeast communities. Finally, in Chapter 4, we use these synthetic yeast communities to provide sense-and-respond capabilities to an Engineered Living Material (ELM).

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-7xy5-ew67
Date January 2019
CreatorsBrisbois, James Ronald
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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