How the Avidity of Polymerase Binding to the -35/-10 Promoter Sites Affects Gene Expression

Abstract

Although the key promoter elements necessary to drive transcription in Escherichia coli have long been understood, we still cannot predict the behavior of arbitrary novel promoters, hampering our ability to characterize the myriad of sequenced regulatory architectures as well as to design novel synthetic circuits. This work builds on a beautiful recent experiment by Urtecho et al. who measured the gene expression of over 10,000 promoters spanning all possible combinations of a small set of regulatory elements. Using this data, we demonstrate that a central claim in energy matrix models of gene expression -that each promoter element contributes independently and additively to gene expression -contradicts experimental measurements. We propose that a key missing ingredient from such models is the avidity between the -35 and -10 RNA polymerase binding sites and develop what we call a refined energy matrix model that incorporates this effect. We show that this the refined energy matrix model can characterize the full suite of gene expression data and explore several applications of this framework, namely, how multivalent binding at the -35 and -10 sites can buffer RNAP kinetics against mutations and how promoters that bind overly tightly to RNA polymerase can inhibit gene expression. The success of our approach suggests that avidity represents a key physical principle governing the interaction of RNA polymerase to its promoter. Significance StatementCellular behavior is ultimately governed by the genetic program encoded in its DNA and through the arsenal of molecular machines that actively transcribe its genes, yet we lack the ability to predict how an arbitrary DNA sequence will perform. To that end, we analyze the performance of over 10,000 regulatory sequences and develop a model that can predict the behavior of any sequence based on its composition. By considering promoters that only vary by one or two elements, we can characterize how different components interact, providing fundamental insights into the mechanisms of transcription.

Importance of the 5′ regulatory region to bacterial synthetic biology applications

“…In fact, conserved motifs such as the À10 and À35 region in bacteria might not have additive effects as it long was thought. Recently, Einav et al (2019) improved their computational model that predicts the behaviour of novel promoters by factoring in avidity between the À10 and À35 regions. Avidity describes how the two binding sites influence each other's binding strength.…”

Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems

“…In particular, we sought to learn how these sites may be manipulated to generate lacUV5 variants with minimal leakiness and maximal fold-change, properties that are generally desired in synthetic applications. In previous work, we have found that testing large libraries of promoters composed of various combinations of sequence elements allows us to characterize the contribution of individual sequence elements and reveal interactions between these elements 20,44 . We utilized our MPRA to uncover how tuning binding sites within the lacUV5 promoter affects the fold-change and leakiness of this system.…”

“…We designed and assayed a library of 1,600 inducible promoters, which we refer to as Pcombo, composed of all possible combinations of one of ten proximal LacI binding sites at +11, four -10 elements, four -35 elements, and ten distal LacI sites at -90 ( Figure 2A) . To cover a wide range of expression, we selected -10 and -35 element variants previously shown to span a range of RNAP binding affinities 6,20,44 . Similarly, we chose a range of LacI binding site variants from well-characterized genomic operator sites (O 1 , O 3 , O sym ) 10,18 , a variant of the natural O 2 site, O 2-var , and a series of novel LacI sites created from different combinations of the monomeric halves of each of these dimeric binding sites ( Table S2 ).…”

“…A variety of compelling approaches have been implemented to engineer inducible promoters, however, these strategies have their shortcomings. Previous studies have had great success implementing biophysical models to tune the relative behaviors of regulatory elements and explain promoter expression, but these do not tell us how the repositioning of binding sites influences expression [6][7][8][9][10] . Directed evolution is a promising strategy that leverages stepwise random mutagenesis and selection to identify favorable promoters, but is generally limited to optimizing within local, evolutionarily accessible sequence space 11,12 .…”

Short residence times of DNA-bound transcription factors can reduce gene expression noise and increase the transmission of information in a gene regulation system

“…Gene expression regulation is being studied by many researchers whose insights improve our capacity to control and modify living systems (11)(12)(13)(14). However, we still do not fully understand how some elementary properties of the interaction of a TF with its binding site on DNA affect the stochastic dynamics of gene expression and the acquisition of information (15). One of these properties is a TF's residence time on its DNA binding site -the mean time that a TF remains bound to DNA.…”