Predicting Transcriptional Output of Synthetic Multi-input Promoters

Abstract

Recent advances in synthetic biology have led to a wealth of well-characterized genetic parts. As parts libraries grow, so too does the potential to create novel multi-input promoters that integrate disparate signals to determine transcriptional output. Our ability to construct such promoters will outpace our ability to characterize promoter performance, due to the vast number of input combinations. In this study, we examine the input-output relations of recently developed synthetic multi-input promoters and describe two methods for predicting their behavior. The first method uses 1-dimensional induction data obtained from experiments on single-input systems to predict the n-dimensional induction responses of systems with n inputs. We demonstrate that this approach accurately predicts Boolean (on/off) responses of multi-input systems consisting of novel chimeric transcription factors and hybrid promoters in Escherichia coli. The second method uses only a small amount of multi-input response data to accurately predict analog system response over the entire landscape of input combinations. Taken together, these methods facilitate the design of synthetic circuits that utilize multi-input promoters.

Multiplex transcriptional characterizations across diverse bacterial species using cell‐free systems

“…However, recent advances in cell‐free methodologies such as the use of degradation tags or continuous exchange of reaction contents would provide a better mimic of in vivo processes while maintaining the simplicity of the in vitro format (Niederholtmeyer et al , ; Garamella et al , ; Swank et al , ). Such approaches could also expedite the characterization of promoters controlled by multiple regulators (Belliveau et al , ) and facilitate their integration into complex regulatory networks (Chen et al , ; Zong et al , ). Transcriptional profiles of entire genetic circuits could also be characterized in cell‐free reactions using whole‐transcriptome library preparation methods, which have been employed in vivo to aid debugging of individual components and dynamic circuit behaviors (Gorochowski et al , ).…”

Programming Escherichia coli to function as a digital display

“…An example of such a prediction is shown in Fig 1C (yellow lines) and compared to experimental data obtained when the circuit is constructed. This was repeated for the complete set of 20 circuits (20 × 4 = 80 predictions), and the data are plotted in Fig 1D and Appendix Fig S4. Promoters in series, even when spatially separated, have the potential for transcriptional interference, where one has a suppressive effect on the other (Sneppen et al, 2005;Hao et al, 2017;Zong et al, 2018). Notably, when a repressor is bound tightly to its operator and has a slow off-rate relative to the RNAP elongation rate, RNAPs originating upstream may not be able to dislodge it, referred to as "roadblocking" (Deuschle et al, 1986;Sellitti et al, 1987;Ahlgren-Berg et al, 2016).…”

“…Promoters in series, even when spatially separated, have the potential for transcriptional interference, where one has a suppressive effect on the other (Sneppen et al , ; Hao et al , ; Zong et al , ). Notably, when a repressor is bound tightly to its operator and has a slow off‐rate relative to the RNAP elongation rate, RNAPs originating upstream may not be able to dislodge it, referred to as “roadblocking” (Deuschle et al , ; Sellitti et al , ; Ahlgren‐Berg et al , ).…”

Multiplex transcriptional characterizations across diverse and hybrid bacterial cell-free expression systems

“…In these cases, additional regulatory proteins could be co-expressed with a library of regulatory DNA variants in the same in vitro reaction and their ligand-response dynamics could be monitored over time. Such approaches could also expedite the characterization of promoters controlled by multiple regulators 47 and facilitate their integration into complex regulatory networks 51,55 .…”