Interfacing systems and synthetic biology for advancements in bacterial biosensor engineering

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Miguez, April Marie
Styczynski, Mark P.
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Current detection platforms ranging from clinical diagnostics to environmental pollutant monitoring often require a time-intensive sample analysis process involving expensive equipment and highly-trained staff. This has led to growing demands for faster, less expensive, more user-friendly platforms. Bacteria have the potential to meet these needs, as they can serve as inexpensive, robust biosensors that can be engineered to detect target molecules while providing fast, easily measurable readouts; however, genetic engineering efforts can often incite metabolic changes that limit biosensing performance. Cell-free bacteria-based biosensors, which use a bacterial protein lysate to perform transcription and translation, can avoid many of the challenges of whole-cell biosensor development, but the uncharacterized metabolic activity in cell-free systems creates a new set of obstacles that must be addressed for effective biosensor design. In this work, I use metabolomics (the systems-scale study of small molecule intermediates involved in the chemical reactions within biological systems) to address these key challenges in whole-cell and cell-free systems to improve their development for biosensing applications. For whole-cell systems, I explore the metabolic effects linked to expression and optimization of a well-characterized biosensor reporter system. For cell-free systems, I characterize their endogenous, dynamic metabolic activity and explore the metabolic impacts of various system perturbations. For both platforms, I identify key metabolites that limit the utility of both whole-cell and cell-free systems and present strategies to address some of the limitations in each platform to facilitate improved biosensor engineering and ultimately broaden the reach of whole-cell and cell-free bacteria-based biosensors.
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