Theses Doctoral

Programming bacterial gene circuits for biocontainment and diagnostic production

Chien, Tiffany

Synthetic biology is a rapidly growing discipline that aims to rationally design the behavior of living organisms for an array of applications, ranging from environmental monitoring to one of particular interest –medicine. For instance, given bacteria’s inherent ability to passively localize to tumor sites and previous work of engineering bacteria to sense compounds of interest utilizing genetic circuits, synthetic biologists can engineer bacteria to proactively sense the tumor for various applications. In this dissertation, we will discuss two such critical applications; one is ensuring safety of living therapeutics by having bacteria limit their growth to disease sites in order to prevent off-target toxicity. The other is a novel method of diagnostic readout, using bacterial production of a volatile compound. The aim of this thesis is to develop safe and robust bacteria-based technologies as living therapies.

To confine bacterial growth within defined regions of interest, we engineer enhanced bacterial tropism with genetic circuits that couple bacterial sensing and growth in response to physiological signatures in vivo. Specifically, we construct oxygen, pH, and lactate biosensors with tunable features for activation at distinct physiological concentrations. We use these biosensors to control the expression of essential genes, which results in significant bacterial growth differences in permissive vs non-permissive conditions. Using pH and oxygen sensors, we demonstrate preferential growth in physiologically-relevant acidic and oxygen conditions. Upon oral delivery in mice, these engineered strains lowered bacteria numbers outside of the host. Multiplexing hypoxia and lactate biosensors with an AND logic-gate architecture resulted in improved performance, reducing bacterial off-target colonization in a syngeneic mouse tumor model. Taken together, these results demonstrate a synthetic biology approach to enhance precision localization of bacteria to specified organ niches.

In additional to engineering bacteria localization, we also want to take advantage of E. coli’s programmable nature to produce diagnostic molecules. The engineering of microbial metabolic pathways over the last two decades has led to numerous examples of cell factories used for the production of small molecules. These molecules have an array of utility in commercial industries and as in-situ expressed biomarkers or therapeutics in microbial applications. While most efforts have focused on the production of molecules in the liquid phase, there has been increasing interest in harnessing microbes’ inherent ability to generate volatile compounds.

Here, we optimized and characterized the production of methyl salicylate, an aromatic compound found mainly in plants, using a common lab strain of E. coli. We utilized genetic components from both microbes and plants to construct the volatile metabolite circuit cassette. In order to maximize production, we explored expressing methyl salicylate precursors, upregulating expression by increasing ribosomal binding strength and codon optimizing methyl transferase gene obtain from plant Petunia x hybrida. Lastly, we validated and quantified the production of methyl salicylate with liquid chromatography and gas chromatography mass spectrometry (LC-MS or GC-MS) and found that the codon optimized strain with precursor supplementation yield the highest production compared to the other strains. This work characterizes an optimized metabolite producing-genetic circuit and sets the stage for creation of an engineered bacteria diagnostic to be used in volatile assays.Finally we conclude by discussing the current efforts to adapt technology described in this thesis dissertation for clinical research and applying them in genetic mouse models for further validation. This underlying work contributes to rapidly growing field in synthetic biology to engineer microbial based living therapy.


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More About This Work

Academic Units
Biomedical Engineering
Thesis Advisors
Danino, Tal
Ph.D., Columbia University
Published Here
April 6, 2022