Composition and Prediction of Multi-Input Promoters | AIChE

Composition and Prediction of Multi-Input Promoters

Authors 

Zong, D. - Presenter, Rice University
Bennett, M. R., Rice University
Ott, W., University of Houston
Gupta, C., University of Houston
One commonly used part in synthetic biology to simultaneously integrate multiple signals is the hybrid promoter. Hybrid promoters contain operator sites for multiple different transcription factors. Recently, there have been efforts to engineer modular chimeric transcription factors that respond to different inducing ligands but bind the same operator site. In the presence of two or more of these chimera transcription factors, a target promoter’s output can be regulated by two chemical signals despite having only one operator site. Provided that the correct operator sites are present, chimeric transcription factors can be used in conjunction with hybrid promoters, increasing the number of potential input combinations. In light of these developments, the potential to create novel multi-input promoters with a higher number of inputs has become much simpler. However, the potential combinations of inputs rapidly outpaces our capability to fully characterize every possible combination. In this study, we describe a method to predict the output of multi-input systems as a function of varying concentrations of multiple inducing ligands by combining characterization data of single input systems. We first characterized the response curve of a library of modular LacI/GalR family chimera repressors across a range of cognate inducing ligand. We used this characterization data to construct a model for single input behavior. We then constructed two input systems by co-expressing a pair of chimera repressors and measured the response surface of each of the resulting two input cases over a range of both inducing ligands. We fit the two input data to a model that uses the pair of appropriate single input models as input. We demonstrate that this method can be used to predict both single operator promoters and hybrid promoters. Furthermore, we show that this method can scale to three input systems. Taken together, this method will provide synthetic biologists a method to better design systems that utilize multi-input promoters.