E. coli transcription factors regulate promoter activity by a universal, homeostatic mechanism

Abstract

Transcription factors (TFs) may activate or repress gene expression through an interplay of different mechanisms, including RNA polymerase (RNAP) recruitment, exclusion, and initiation. TFs often have drastically different regulatory behaviors depending on promoter context and interacting cofactors. However, the detailed mechanisms by which each TF affects transcription and produce promoter-dependent regulation is unclear. Here, we discover that a simple model explains the regulatory effects of E. coli TFs in a range of contexts. Specifically, we measure the relationship between basal promoter activity and its regulation by diverse TFs and find that the contextual changes in TF function are determined entirely by the basal strength of the regulated promoter: TFs exert lower fold-change on stronger promoters under a precise inverse scaling. Remarkably, this scaling relationship holds for both activators and repressors, indicating a universal mechanism of gene regulation. Our data, which spans between 100-fold activation to 1000-fold repression, is consistent with a model of regulation driven by stabilization of RNAP at the promoter for every TF. Crucially, this indicates that TFs naturally act to maintain homeostatic expression levels across genetic or environmental perturbations, ensuring robust expression of regulated genes.

Figure 1:. Modeling promoter dependence of TF function.

(a) A simple model of TF function predicts a distinct relationship between TF function and promoter strength that depends on the nature of interactions between the TF and RNAP. (b) TFs with stabilizing interactions $(\beta >1)$ produce lower fold-changes on stronger promoters, while TFs with de-stabilizing interactions ($\beta <1$) show the opposite. (c) The relationship collapses into two distinct curves for $\beta >1$ and $\beta <1$ when constitutive expression and fold-change are rescaled by the TF regulatory interactions. (d) Strong stabilizing interactions will buffer changes to constitutive expression while destabilizing interactions amplify them. (e) The TF, CpxR acting on three natural promoters demonstrates that regulatory function can have a strong dependence on the strength of the regulated promoter.

Figure 2:. Measuring the relationship between TF function and promoter activity for synthetic promoter variants.

(a) Experimental approach to measure fold-change and constitutive expression levels of random promoter variants. (b) Each data point in our plots represents the constitutive and regulated level of expression for one promoter variant. (c) For 8 TFs measured here, the relationship between TF function and promoter strength conforms well to the predicted scaling of strong stabilizing interactions (black dashed lines). Subplots (i)-(iv) show TFs binding downstream of the promoter, while (v)-(viii) show TFs binding upstream of the promoter. Furthermore, panels (i)-(v) show TFs considered to be repressors and (vi)-(viii) show activators. (d) As expected from the theory for stabilizing TFs, the regulation by both CpxR and LacI cause a robust level of regulated expression from promoters with diverse unregulated levels of expression.

Figure 3:. Scaling of regulation is conserved across different methods of perturbations to the constitutive expression.

(a) The constitutive expression level is altered via changes in the growth rate achieved by supplementing media with different carbon sources. The plot shows the measure of regulation when the promoter mutants of LacI (circles) and CpxR (squares) were grown in media containing a variety of carbon sources (different colors). (b) Distribution of slope obtained from a linear fit of fold-change as a function of constitutive expression for any single promoter in different media. Inset shows the straight-line fit to the data for one of the promoters grown in 6 different carbon sources. (c) Representative single-cell distribution of the fluorescence of unregulated (dotted lines) and regulated expression (dashed lines) across different growth media. The global perturbations alters the growth rate and the constitutive expression levels of the library of promoters but not the regulated expression levels both for activation (CpxR) and repression (LacI). (d) The constitutive expression is altered via specific perturbations to RNAP concentration (via changes to σ²⁸ concentration) or promoter sequence. Measure of regulation by LacI (i) and CpxR (ii) for specific perturbations. Each color on the plot is a different promoter and each data point is a fixed concentration of σ²⁸. (e) Single-cell distribution of regulated and un-regulated expression for changing σ²⁸ concentration (i), or promoter strength (ii). There is no change in the regulated expression (solid lines in each plot) for any specific perturbation to constitutive expression (dashed lines in each plot).

Figure 4:. Promoters with complex regulatory architecture show stabilizing relationship with mutant promoter library.

(a) The top panel shows three native promoters of E. coli regulated by SoxS. The relative position of the binding site is shown as a complete green square with the center of the binding site marked underneath. The bottom panel shows the plot of fold-change against the corrected constitutive expression level for the three native promoter mutant libraries. (b) The top panel is a schematic representation of the DNA looping mediated regulation by LacI. The bottom panel is the massively parallel reporter assay data from (43) plotted using un-induced/induced as a proxy for the fold-change and induced expression as the constitutive expression. Data corresponding to the strong proximal binding sites (LacO1(i) and LacOsym(ii)) and all of the 10 distal binding sites are plotted. (c) Measure of regulation for a promoter architecture with two binding sites for the TF of interest (dark blue squares) around the promoter (red square). (D) Measure of regulation for promoters with binding sites for other TFs (black squares) in addition to the binding site for the TF of interest.

Figure 5:. Universal collapse for all regulation data.

All data from Figs. 2–4 are renormalized using the $\alpha$ and $\beta$ obtained from each fit. We also include data from refs. (43, 44, 46) which we fit the same way as described above for $\alpha$ and $\beta$ values. The black line represents the zero-parameter theory line: $f\left(x\right)=1/(1+x)$. All data collapses to a single theory curve suggesting a conserved universal mechanism of action between all measured regulation. The inset shows a histogram of fold-change values for all points included in the figure.