Abstract
One of the paramount goals of synthetic biology is to have the ability to tune transcriptional networks to targeted levels of expression at will. As a step in that direction, we have constructed a set of unique binding sites for E. coli RNA Polymerase (RNAP) holoenzyme, designed using a model of sequence-dependent binding energy combined with a thermodynamic model of transcription to produce a targeted level of gene expression. This promoter set allows us to determine the correspondence between the absolute numbers of mRNA molecules or protein products and the predicted promoter binding energies measured in energy units. These binding sites adhere on average to the predicted level of gene expression over orders of magnitude in constitutive gene expression, to within a factor of in both protein and mRNA copy number. With these promoters in hand, we then place them under the regulatory control of a bacterial repressor and show that again there is a strict correspondence between the measured and predicted levels of expression, demonstrating the transferability of the promoters to an alternate regulatory context. In particular, our thermodynamic model predicts the expression from our promoters under a range of repressor concentrations between several per cell up to over per cell. After correcting the predicted polymerase binding strength using the data from the unregulated promoter, the thermodynamic model accurately predicts the expression for the simple repression strains to within . Demonstration of modular promoter design, where parts of the circuit (such as RNAP/TF binding strength and transcription factor copy number) can be independently chosen from a stock list and combined to give a predictable result, has important implications as an engineering tool for use in synthetic biology.
Highlights
The regulation of gene expression is one of the primary ways that cells respond to their environments
What are the sequence rules that govern promoter strength? Recent high throughput mutagenesis experiments present an improved method for constructing an energy function that maps sequence to protein-DNA binding energy
We use this energy function combined with a thermodynamic model to deliberately design different promoters with over three orders of magnitude difference in their mean expression, and measure the resulting level of expression at both the mRNA and protein level to test this design strategy
Summary
The regulation of gene expression is one of the primary ways that cells respond to their environments. Key biological tuning variables include the copy number of the transcription factors that act on a gene of interest, the strength of their binding sites, the strength of RNA polymerase binding, the strength of ribosomal binding sites and the degradation rates of the protein products of the gene of interest Many of these tuning parameters have been studied in quantitative detail. Salis et al [1] developed a model to describe the interaction energy between the ribosomal binding site (RBS) of an mRNA transcript and the 30S ribosomal subunit, which they relate to translation initiation rate using statistical thermodynamics Using this model, gene expression can be predictively tuned over 5 orders of magnitude by modulating translation efficiency for a given gene [1,2]
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