Transcriptional Regulation and Combinatorial Genetic Logic in Synthetic Bacterial Circuits

Citation

Cox, Robert Sidney, III (2008) Transcriptional Regulation and Combinatorial Genetic Logic in Synthetic Bacterial Circuits. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/KRW6-DH88. https://resolver.caltech.edu/CaltechETD:etd-03042008-130011

Abstract

We engineered several synthetic regulatory circuits to study transcriptional regulation in bacteria. We developed a new technique for DNA construction, built and characterized in vivo a library of genetic logic gates, examined the role of genetic noise transcriptional regulation using a fluorescent multi-reporter system, and characterized a synthetic circuit for the control of population density.

We used synthetic duplex DNA fragments and very short cohesive overhangs to direct ordered assemblies of diverse combinatorial libraries. Multiple DNA fragments were simultaneously ligated in a single step to produce random concatemers, without the need for amplification or product purification. We characterized the assembly process to identify optimal cohesive overhangs. We showed that the method was 97% efficient for assembling 100 base-pair concatemers from three duplex fragments.

We constructed a library of 10,000 prokaryotic promoters, containing over 1,000 unique 100 base-pair sequences. These promoters responded to up to three inputs, and contained diverse architectural arrangements of regulatory sequences. We characterized the logical input functions of 288 promoters in Escherichia coli, and analyzed the relationship between promoter function and architecture. We defined promoter function in terms of regulatory range, logic type, and input symmetry; and identified general rules for combinatorial programming of gene expression.

We built a synthetic three-color fluorescent reporter framework. This construct was non-toxic and extensible for synthetic and systems biology applications. Three spectrally distinct and genetically isolated reporter proteins allowed independent monitoring of genetic signals at the single-cell level. We showed that the simultaneous measurement of multiple genes can exploit genetic noise to sensitively detect transcriptional co-regulation.

Thesis Files