Predicting Promoter Activity from Sequence Analysis

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Lesley Foster, Christophe Ladroue and Sara Kalvala

University of Warwick, United Kingdom

The ability to design new biological parts, devices and systems, or redesign existing biological systems for useful purposes using engineering approaches is at the heart of synthetic biology. Although there have recently been a number of success stories, the ultimate goal of creating a selection of parts that can be picked off the shelf and assembled into functional devices is still tantalisingly out of reach. Living systems exhibit greater integration of parts than those in synthetic models, potentially causing unpredictability in device behaviour. We developed a tool to help predict relative promoter activity based on the underlying nucleotide sequence of promoters. We investigated the effects of device construction on the relative promoter activity. We found that standard promoters (which may have short nucleutide sequences) display device-dependent relative promoter activity, while the strength of insulated promoters strength is usually device-independent. Our simulations indicate that the RBS can affect the transcription initiation rate and well as the translational initiation rate in standard promoters. Our computational results are inline with experimental data for an example GFP device with various promoters. A part can effect the promoter preceding it in a device, because its upstream nucleotide sequence can extended into the ITR of the promoter, possibly effecting the elements that affect transcription initiation and promoter escape. Insulated promoters are protected from this device dependent behaviour because their underlying nucleotide sequence is designed to span the entire region that contains the majority of transcription factor-binding sites in natural bacterial promoters, and most of the elements that affect transcription initiation and promoter escape (positions -105 to +55). Our work indicates that an analysis of the nucleutide sequences of promoters allows us to predict more realistically the strength of the various promoters and therefore the dynamics of the designed systems.