P150: Novel biosensors from bacterial regulatory proteins with altered effector specificity

Monday, July 25, 2011
Grand Ballroom, 5th fl (Sheraton New Orleans)
Christopher S. Frei1, Shuang Yan Tang2 and Patrick Cirino1, (1)Chemical Engineering, University of Houston, Houston, TX, (2)Chemical Engineering, Penn State University, UNIVERSITY Park, PA
Combinatorial design approaches to improve enzymatic or microbial production of a metabolite often rely on the throughput and/or selectivity of the screening system used. Regulatory proteins controlled by “effector” molecules naturally couple molecular recognition to changes in gene expression, providing a platform for linking in vivo molecular synthesis to a readily detectable phenotype (e.g. GFP expression).  We are developing customized molecular reporters by engineering regulatory protein effector recognition. In addition to enabling high throughput screening, customized regulatory proteins are useful tools in metabolic engineering applications.

We initially focused on the well-characterized regulatory protein AraC.  Using fluorescence-activated cell sorting, libraries of >108 AraC variants are rapidly screened for desired regulatory properties in the presence and absence of selected small molecules.  This strategy led to the isolation of AraC variants that selectively report in vivo concentrations of the metabolites mevalonate and triacetic acid lactone (TAL).  These reporters were subsequently used to screen for improved production of mevalonate and TAL by E. coli clones expressing mutants of the respective heterologous biosynthesis pathways.  The range of molecules accessible by variants of the AraC ligand binding pocket is now being explored. Other regulatory protein platforms are also being developed to further broaden our molecular reporting repertoire.  For example the regulators TetR and ActR serve as platforms for detecting natural and “unnatural” products such as antibiotics. We aim to better understand which residue positions are most effective for altering ligand binding, resulting in a streamlined design process with optimized protein libraries.

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