Assessing in vivo the impact of gene context on transcription through DNA supercoiling

Abstract

Gene context can have significant impact on gene expression but is currently not integrated in quantitative models of gene regulation despite known biophysical principles and quantitative in vitro measurements. Conceptually, the simplest gene context consists of a single gene framed by two topological barriers, known as the twin transcriptional-loop model, which illustrates the interplay between transcription and DNA supercoiling. In vivo, DNA supercoiling is additionally modulated by topoisomerases, whose modus operandi remains to be quantified. Here, we bridge the gap between theory and in vivo properties by realizing in Escherichia coli the twin transcriptional-loop model and by measuring how gene expression varies with promoters and distances to the topological barriers. We find that gene expression depends on the distance to the upstream barrier but not to the downstream barrier, with a promoter-dependent intensity. We rationalize these findings with a first-principle biophysical model of DNA transcription. Our results are explained if TopoI and gyrase both act specifically, respectively upstream and downstream of the gene, with antagonistic effects of TopoI, which can repress initiation while facilitating elongation. Altogether, our work sets the foundations for a systematic and quantitative description of the impact of gene context on gene regulation.

Graphical Abstract

Figure 1.

Conceptual and experimental models. (A) The conceptual ‘twin transcriptional-loop model’ consists of a single gene delimited by two barriers that prevent the diffusion of supercoiling (17). A transcribing RNA polymerase generates negative supercoiling upstream and positive supercoiling downstream, which may eventually hinder further transcription due to torsional torques. In E. coli, just as in most bacteria, mainly two topoisomerases can resolve these constraints: TopoI, which relaxes negative supercoils, and DNA gyrase, which relaxes positive ones. (B) We implemented this model on a plasmid with two genes coding for fluorescent proteins, here indicated as upstream and downstream genes, and an antibiotics resistance gene. The upstream gene is flanked by tandems of LacI binding sites. In absence of IPTG, LacI forms two loops between which supercoiling cannot diffuse (22,23), thus insulating the upstream gene. (C) We built several such systems that differ by the promoter sequence of the upstream gene and the downstream and upstream distances from the promoter or terminator to the boundaries, which are joined by LacI in the closed system. (D) Expression rate of the downstream gene versus expression rate of the upstream gene for given distances but different promoters of the upstream gene (Supplementary Table S1), measured either in the open (in red) or closed (in yellow) system. Downstream expression rates are normalized by their largest value and upstream expression rates by that of the promoter used downstream when placed upstream. While the expression rates of the downstream and upstream genes are negatively correlated when the system is open, they become uncorrelated when it is closed, consistent with their transcriptional insulation.

Figure 2.

Susceptibility of gene expression to downstream and upstream contexts. Here, we change the context of the insulated gene by introducing a ∼3 kb sequence either downstream or upstream and consider promoters of varying strengths. (A) Susceptibility to downstream context versus promoter strength. The downstream susceptibility is defined as the ratio of the expression rate of the insulated gene with a long (3408 bp) distance to the downstream barrier over its expression rate with a short (320 bp) distance. Measurements involving weak promoters are less precise as indicated by the shaded area marking a deviation from unity by less than one standard deviation across replicate measurements (Materials and Methods). (B) Susceptibility to upstream context versus promoter strength. The upstream susceptibility is defined as the ratio of the expression rate of the insulated gene with a long (∼3200 bp) distance to the upstream barrier over its expression rate with a short (∼250 bp) distance. In contrast with downstream susceptibility, it is significantly larger than one for all but one of the strong promoters. The three promoters marked in color are further studied in Figure 3.

Figure 3.

Dependence on distance to the upstream barrier. (A) Relative expression rate when varying the distance to the upstream barrier for the three promoters marked in color in Figure 2B—each point corresponds to an independent measurement. The downstream distance is here 520 bp, while it is 320 bp in Figure 2B, explaining slight differences of upstream susceptibility at 3205 bp. (B) Susceptibility to upstream context for the same three promoters. The weak (green) and strong (red) promoters are found to have similar upstream susceptibilities despite having respectively a higher and lower promoter strength than the medium (blue) promoter.

Figure 4.

Schematic representation of our biophysical model of transcription under topological constraints – Transcription includes promoter binding by an RNAP, initiation of elongation which is divided into OC formation and promoter escape, elongation and termination. Elongating RNAPs behave as topological barriers and generate negative supercoils upstream (clockwise red arrows) and positive supercoils downstream (counterclockwise red arrows). The gene is embedded in a domain of length L that is topologically constrained at its extremities. If N RNAPs are elongating (here N = 2), N + 1 independent topological domains are present whose supercoiling densities are denoted by Σ_i (i = 1, .., N + 1). We further indicate the specific action of TopoI (green shape) and gyrase (blue shape) at the extremities of the gene. In addition, TopoI and gyrase may act non-specifically anywhere along the segment.

Figure 5.

Upstream susceptibilities in the biophysical model. (A) Susceptibility to upstream context versus promoter strength for the range of parameters indicated in Table 1. Horizontal lines of the violin plots indicate median values. (B) Upstream susceptibility as a function of the upstream distance obtained in experiments (i.e. results of Figure 3B) compared to the same quantity obtained in our model for three promoters indicated by colored dots in panel A (see Materials and Methods for the values of parameters).

Figure 6.

Simulation results rationalizing upstream susceptibilities. (A) Values of the DNA supercoiling density at the promoter over a window of time in the stationary regime for short upstream distance (d = 250 bp) and a promoter corresponding to the medium promoter of Figure 5B. The large positive jumps are the consequence of TopoI adding one supercoil (green arrow), while decreases are induced by RNAP translocations up to points where DNA supercoiling density is equal to the stalling threshold (σ_s, red dashed line; the red arrow indicates RNAP stalling). When the upstream supercoiling density is above σ_o (green dashed line), OC formation is repressed, preventing new initiations (vertical black dashed lines). (B) Same as in panel A but for a long upstream distance (d ∼ 3200 bp), in which case positive supercoils added by TopoI are damped and the upstream supercoiling density remains below σ_o. The blue arrow indicates a non-specific action of gyrase. (C) Same as in Figure 5A but considering promoters with σ_o = −0.05 and distinguishing between those limited by binding (k_b < k_o, in orange) and those limited by OC formation (k_o < k_b, in blue). (D) Same as in panel C but considering promoters with σ_o ≥ −0.02, showing no difference between binding-limited promoters and OC formation-limited promoters.