2022 Annual Meeting
Controlling and Modeling Transcription Based on Promoter Spacer Length
Understanding and predicting transcription is crucial to creating robust and efficient genetic circuits and metabolic pathways within cells. A source of transcriptional variability are sigma factors, proteins that direct the start of mRNA transcription after forming a holoenzyme with RNA polymerase. Specifically, the spacer length between the two points on the promoter at which the holoenzyme complex binds is known to affect binding affinity, thus changing the expression of the associated downstream gene. In this work we sought to study the relationship between spacer length and output expression using experimental methods, resulting in the development of a predictive mathematical model for protein production. To accomplish our goal, promoter sequences with spacer lengths between 10 and 18 base pairs were evaluated for expression of green fluorescent protein (GFP) in Escherichia coli. Each promoter responds to a sigma factor native to Bacillus subtilis (B, F or G), which we also co-produce in E. coli. Using our results, we are creating a mathematical model that describes the general trends behind the spacer length of a promoter, the identity of the sigma factor used, and the expression of the associated gene. We intend to use our model to predict the output of a genetic circuit containing multiple sigma factors.