Multiplexed approach to elucidate sequence-function relationships of transcription factor-based biosensors
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Description
Transcription factor (TF)-promoter pairs are vital tools for measuring intracellular biochemical production titer and control gene expression in biotechnology. Most often, native TF-promoter systems require rigorous screening to obtain desirable characteristics optimized for biotechnological applications. Sort-seq provides a rational and less labor-intensive strategy to engineer user-defined TF-promoter pairs using FACS and deep sequencing methods. Based on the designed promoter library’s distribution characteristics, sort-seq elucidates sequence-function interactions between DNA-protein. A persistent challenge is the need for TF-promoter pairs with user-defined controls, including well-characterized promoters such as PBAD and PRha may not always be sufficient for certain applications, such as achieving maximum protein expression. Furthermore, utilization of high-throughput workflows for non-model organisms such as anaerobic Clostridium species are lagging resulting in frequent use of subpar inducible promoters in their native forms and remains relatively uncharacterized. In this work, we engineer six inducible promoters, spanning well-characterized to the least characterized, to improve biosensor characteristics, particularly improving the dynamic range. We use sort-seq to investigate sequence-function relationships at the promoter level for BmoR-PBMO (n-butanol), AraC-PBAD (L-arabinose), RhaS-PRha (L-rhamnose), BgaR-PBgaL (D-lactose), AraR-PPTK (L-arabinose), and TetR-PTETO1 (anhydrotetracycline). We constructed a mutagenized promoter library cloned upstream of the gfp reporter gene in E. coli, induced it with respective inducers, and then sorted the populations based on fluorescence activity. Deep sequencing of the sorted populations reveals mutations correlated with changes in gfp expression, enabling construction of synthetic promoters with desirable characteristics. Identified mutations were constructed and validated in E. coli. The best mutant promoters demonstrated from 2x to 4x increase in dynamic range over the native PBAD, PRha, and PBMO promoter sequence. We also validated the best performing PBgaL, PPTK, and PTETO1 promoter mutants in Clostridium acetobutylicum resulting in significant improvement in dynamic range over the native sequence. Our work provides a nucleotide level map of commonly used inducible promoters, serving as a guide for engineering complex promoter systems and enhancing the capability of Clostridium as a biotechnology platform.