438397 Developing a Strategy for Constructing Modular Biosensors

Monday, November 9, 2015: 2:10 PM
Ballroom H (Salt Palace Convention Center)
Neil C. Dalvie, Chemical and Biological Engineering, Northwestern University, Evanston, IL

The rapidly increasing toolbox of synthetic biology has allowed numerous advances in the engineering of metabolic pathways. One tool that is largely missing from this toolbox is the ability to dynamically sense the levels of a particular metabolite and output that signal in a living cell. Metabolomics can reveal bulk information about metabolites, but no current methods can actively report on metabolic flux through pathways in real time. In 2012, it was shown that a naturally occurring biosensor with such a function can be used to increase the production of biofuels from microbes by transcriptionally optimizing metabolic flux. Unfortunately, very few ligand dependent transcriptional regulators have evolved naturally. In order to obtain dynamic flux information, we need to construct biosensors capable of providing flux information if a naturally occurring biosensor is not available. To meet this need, we are developing Small molecule Responsive Transcriptional Regulator (SmaRTR) biosensors for metabolites in the industrially important mevalonate pathway in Escherichia coli. The mevalonate pathway produces farnesyl pyrophosphate, which is a precursor to many valuable industrial products, and to lycopene, an easily detectable red molecule.

Our approach builds upon a previous proof-of-concept construction of a SmaRTR biosensor using maltose binding protein (MBP), which regulates transcription of a reporter gene based on the presence of maltose. We explored several different strategies for developing the MBP biosensor, and all were tested with an extensive library of potentially matching promoters for the reporter gene. Computational feature selection methods were used to determine which promoter features in our library were important for DNA binding and transcriptional regulation. Here, we report the application of these methods to enzymes in the mevalonate pathway, further refining guidelines for design of SmaRTR biosensors from natural enzymes. Knowledge of the dynamic flux of metabolites would reduce the need for systemic overexpression of all the pathway enzymes and growth compromising knockouts of enzymes, resulting in less stress on cells and more robust production of valuable molecules.

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