In order to investigate the effect of promoter architecture in the regulation by Fis and IHF, we evaluated the effect of 12 complex promoters constructed in early work (Monteiro et al., 2018) and we constructed 30 new combinatorial promoters with consensus DNA sequences for Fis (Fis-BS) and IHF (IHF-BS) binding sites positioned upstream of a weak core promoter (−35/−10 region) at specific positions (1–4) centered at the −61, −81, −101, and −121 regions related to the transcriptional start site (TSS) (Figure 1). For that, we generated double-strand DNA sequences for Fis-BS, IHF-BS, and a neutral sequence (Neg) with no related transcriptional binding site, which were combined for the generation of a library of synthetic promoters, merging the transcriptional binding sites for Fis, IHF, and/or neutral sequence for each position (Table 1). The complex promoters were assembled by DNA ligation and cloned into pMR1, a mid-copy number vector harboring mCherry and GFPlva as reporter fluorescent proteins (Figure 1). The resulting reporter plasmids (with each promoter controlling only by GFPlva expression) were used to transform competent E. coli wild-type strain (BW25113—WT) and/or E. coli mutants for ihfA (ΔihfA) and fis (Δfis) (from Keio collection) (Baba et al., 2006). Using these constructs, we assayed promoter activity for 8 h in minimal media (M9 complete), measuring the relative GFP expression (GFP/OD) in all strains in the plate reader fluorimeter Victor X3 (PerkinElmer). As a negative control, we used the Neg sequence occupying the 4 possible positions before the core promoter. All data presented in this work are referred to 4 h of cell growth. In the next sections, we present the results of the promoter analysis per category to uncover the cis-regulatory logic for each variant.

We analyzed the architecture effect for Fis cis-regulatory elements by evaluating the influence of position and sequence combination for Fis-BS. For that, we used promoters merging Fis-BS and Neg sequences to measure relative GFP expression (GFP/OD) levels after 4 h of cell growth in wild-type, Δfis, and ΔihfA E. coli strains, and normalized the results to our negative control (top bars in Figure 2). The results displayed in Figure 2 show that most of the promoters harboring Fis-BS exhibit low activity in wild-type E. coli, comparable to the negative control. However, when these promoters were assayed in E. coli Δfis strain (red bars), 4 of them displayed a significant increase in activity compared to the wild-type strain (green and gray in Figure 2). Particularly, in the presence of Fis protein, Fis could occupy Fis-BS and act as a repressor of promoter activity. However, not all architectures with Fis-BS at the 4th or 3rd positions display this promoter behavior. This phenomenon only occurs in two other cases with more than 1 Fis-BS combination (promoters shaded in green in Figure 2). This reveals a complex association between promoter architecture and expression profile, which seems to be dependent on the Fis-BS position and arrangement.

We also assayed Fis-BS promoters in the E. coli ΔihfA strain (blue bars) to evaluate the specificity of Fis for Fis-BS. Strikingly, despite most promoters display similar activity levels in the ΔihfA strain as in the wild-type, 1 single promoter variant harboring Fis-BS at the 3rd position (−101 relative to the TSS) displayed a substantial increase in activity in the ihfA mutant relative to the wild-type strain (promoter shaded in gray in Figure 2). This result indicates that IHF also acts as a repressor of this promoter variant. Although it was restricted to a single promoter variant, these results suggest that non-specific IHF binding to the Fis-BS exists, suggesting that promiscuous regulatory interaction could occur and seems to be dependent on promoter architecture, since this phenomenon is detected only for Fis-BS at the 3rd position. Altogether, these results suggest a complex interplay between the position and combination of Fis-BS and the regulation of gene expression.

Using the same strategy as in Figure 2, we investigated the regulatory logic of promoters harboring multiple cis-regulatory elements for IHF, merging IHF-BS, and Neg sequences. Figure 3 shows that most promoters displayed low activity in the wild type strain of E. coli and higher activity in E. coli ΔihfA (blue bars), in agreement with previous data on complex IHF promoters (green and gray shaded) (Monteiro et al., 2018). However, when these promoters were assayed in E. coli Δfis strain (red bars), we observed that 4 promoter architectures also displayed higher activity in this mutant (promoters shaded in green in the figure), indicating that Fis was also able to repress these promoter variants, highlighting a possible crosstalk (Cepeda-Humerez et al., 2015; Friedlander et al., 2016) between these 2 TFs, which should be further investigated in the future. However, it is worth noticing that the promoter variants harboring cis-regulatory elements for IHF at 4th or 3rd and 4th positions (−101 and −121 relative to the TSS) displayed both a strong repression by IHF but no modulation by Fis (promoter shaded in gray in Figure 3). Again, these results reinforce that the gene expression pattern and the promiscuous or specific binding to transcriptional factors allows for the fine-tuning of promoter activities based on their architectures.

After we investigated the regulatory interactions for promoters harboring cis-regulatory elements for a single transcriptional factor (IHF or Fis), we constructed promoters combining binding sites for both TFs and Neg sequences. In order to systematically investigate the effect of combined transcriptional factor-binding sites on promoter logic, we first fixed 1 IHF-BS at the 1st position (−61) and varied Fis-BS for the 2nd, 3rd, and 4th positions. As shown in Figure 4A, 1 promoter harboring 1 single IHF-BS at the 1st position showed no activity in the wild-type E. coli strain but increased activity in the fis and ihfA mutant strains. However, adding Fis-BS at the 2nd or 3rd position resulted in promoters with reduced activity in the ihfA and fis mutant strains, compared to IHF-BS at the 1st position (promoters shaded in green in Figure 4A). Comparison of these green shaded promoters to promoters with 1 single Fis-BS at the 2nd or 3rd positions in Figure 2, we cannot observe any patterns between the merging of binding sites for these transcriptional factors, that is, the activity of promoters consisting of both Fis-BS and IHF-BS is not the sum of behaviors from Fis-BS and IHF-BS individually. When 1 single IHF-BS was fixed at the 4th position (−121), the resulting promoter displayed strong activity in ΔihfA strains (Figure 4B). However, when 1 single Fis-BS was added at the 1st position (−61), the resulting promoter displayed increased activity in the E. coli Δfis strain, while it showed no activity in the wild type and ΔihfA strains. Therefore, this promoter architecture may be being repressed, especially by Fis regulator (shaded in green). However, for promoters with Fis-BS fixed at the 1st position (Figure 2), we observed a reduction in the promoter activity in the Δfis strain, demonstrating that the presence of IHF in this specific position may influence a positive expression in the absence of Fis. Finally, the addition of 1 single or multiple Fis-BS at different positions completely blocked promoter activity, and this was not relieved in either Δfis or ΔihfA strains, showing that transcriptional factors and binding site sequences of IHF and Fis contribute to promoter complexity. A mutant for ihfA and fis should be a compelling model to completely understand this promoter logic, but a mutant for both TFs has proven to be difficult to construct. It is important to note that IHF and Fis, which are transcriptional factors, are also NAPs, so the gene expression identified here could be related to possible changes in the DNA geometry (Déthiollaz et al., 1996). Taken together, these results also suggest that Fis and IHF proteins and their binding sites exert complex regulatory patterns, hampering promoter behavior predictions.

In all promoters presented until this point, while the combination of different cis-regulatory genes was able to determine the regulatory logic displayed by IHF and Fis, the 2 TFs acted as repressors of promoter activity (Figures 2–4). However, this behavior shifted when we constructed promoter versions harboring IHF-BS at the 1st and 4th positions and varying sites for Fis-BS (Figure 5). As shown in this figure, when 1 single Fis-BS was added at the 2nd position (−81), the resulting promoter displayed a strong activity in the wild-type strain of E. coli, when compared to the version lacking this element (promoter in the green shaded region in Figure 5). Furthermore, when these promoters were assayed in E. coli Δfis or ΔihfA, we observed a substantial reduction in their activity, indicating that both TFs acted as activators of the combinatorial promoter. The same behavior was also observed for a promoter harboring 2 IHF-BS (at the 1st and 4th positions) and 2 Fis-BS (2nd and 3rd positions), where reduction in the gene expression was even more evident. The same does not occur for a promoter harboring the 2 sites of IHF-BS and Fis-BS at the 3rd position, indicating the dependence and complexity of the relationship between promoter architecture and gene expression. These results highlight the rise of emergent properties in complex promoters for global regulators (Monteiro et al., 2018), as increasing the number of cis-regulatory elements can drastically shift the final regulatory logic of the system.

Bacteria are naturally endowed with complex promoters harboring multiple binding sites for several TFs. While several works based on mathematical modeling have argued that combinatorial regulation can be predicted from the characterization of individual promoter elements (Yuh, 1998; Bintu et al., 2005; Hermsen et al., 2006; Zong et al., 2018), along with the previous report (Monteiro et al., 2018) and here we provide growing evidence that small changes in the architecture of cis-regulatory elements can drastically change the final response of the system (Kreamer et al., 2016). The unpredictable behaviors observed in these studies might also depict a deeper evolutionary trend in gene regulation that has selected molecular systems/mechanisms capable of promoting both evolvability and robustness of gene expression levels through non-linear gene regulation (Steinacher et al., 2016). Thus, understanding the way the architecture of cis-regulatory elements determines gene expression behavior is pivotal not only to understand natural bacterial systems but also to provide novel conceptual frameworks for the construction of synthetic promoters for biotechnological applications (Monteiro et al., 2019b). Frequently, in genetic bioengineering applications, it is also necessary to fine-tune and balance specific gene expression due to the complexity of regulatory networks (Boyle and Silver, 2012; Scalcinati et al., 2012; Steinacher et al., 2016). Several recent studies have focused on the improvement of this strategy for diverse purposes (Egbert and Klavins, 2012; Siegl et al., 2013; Hwang et al., 2018). The present adjusting approach could be used as a strategy for the fine-tuning of genetic circuits to perform optimally in a given context. Our approach provided a library (from this study and from our previous work (Monteiro et al., 2018) of 74 promoter architectures characterized in different strains and conditions for in total of 230 outputs (different promoters in different strains and growth conditions) (Figure 6 and Table S1). Promoters from our synthetic promoter library with small adaptations could be used for diverse purposes in the biotechnological and bacterial network gene regulation fields.

Abstracting all the gene regulations investigated in this work, we are able to provide a visual summary of the findings reported here from a Boolean logic perspective (Figure 7). As shown in Figure 7A, changing a perfect Fis binding in 20 bp (from position –121 to –101) can turn a specific Fis-repressed promoter into a system repressed by both Fis and IHF. Using a more formal logic gate definition (Amores et al., 2015), this modification can turn a promoter with a NOT logic into one with an NOR logic. However, a promoter harboring 2 IHF-binding sites at positions –121 and –101 displayed specific IHF-repression, while changing the second binding site to position –61 resulted in a promoter repressed by both IHF and Fis (Figure 7B). In terms of promoter logic, this change in cis-element architecture also turns a promoter with NOT logic into one with an NOR logic. When a single IHF-binding site was presented at position –121, the final promoter was only repressed by IHF (Figure 7C). Yet, introducing an additional Fis-binding site at position –61 of this promoter turned it into a system exclusively repressed by Fis. This change maintained the NOT logic of the promoter but changed the TF able to repress the activity. Finally, and more remarkably, while a promoter with 2 IHF-BS (at positions –121 and –61) was repressed by both Fis and IHF, adding a third binding site for Fis at position –81 resulted in a promoter strongly activated by both TFs (Figure 7D). Therefore, this single-change cis-element architecture turned a promoter with NOR logic into an entirely OR promoter responsive to the same TFs. This remarkable regulatory versatility and unpredictability unveiled by synthetic combinatorial promoter shows that we only start to understand the complexity of gene regulation in bacteria. While the work presented here covers two of the main global regulators of E. coli, further studies are still necessary to uncover the hidden complexity of combinatorial gene regulation in this bacterium.

E. coli DH10B was used for cloning procedures, while E. coli BW25113 was used as the wild-type strain (WT); E. coli JW1702-1 was used as a mutant for the IHF transcription factor (TF), and E. coli JW3229 was used as a mutant for the Fis TF. All strains were obtained from the Keio collection. For the procedures and analyses, E. coli strains were grown in M9 minimal media (6.4 g/L, Na₂HPO₄•7H₂O, 1.5 g/L KH₂PO₄, 0.25 g/L NaCl, 0.5 g/L NH₄Cl) supplemented with chloramphenicol at 34 μg/mL, 2 mM MgSO₄, 0.1 mM casamino acids, and 1% glycerol as the sole carbon source (Complete M9) at 37°C. Plasmids, bacterial strains, and primers used in this study are listed in Table 1.

The construction of synthetic promoters was performed by the ligation reaction of 5′–end phosphorylated oligonucleotides acquired from Sigma Aldrich (Table 1). The design of all single strands was projected to carry a 16 bp sequence containing the Fis binding site (F), IHF binding site (I), or a neutral motif (N), which is a sequence where any TF is able to bind (Figure 1A). These locations were identified as positions 1, 2, 3, and 4, respectively (Figure 1B) and to be located at −61, −81, −101, or −121 bp upstream of the core promoter (Figure 1C). In addition to the 16 bp oligonucleotides, all single strands were designed to contain 3 base pairs overhang for its corrected insertion on the promoter (Figure 1C). Additionally, a core promoter based on the lac promoter, which is a weak promoter and therefore requires activation. The design of the synthetic promoters and the positions of the cis-elements were made based on strategies already performed by our group (Monteiro et al., 2018), aiming to arrange the cis-elements aligned to the transcription initiation site, considering the DNA curvature. To assemble the synthetic promoters, the 5′ and 3′ strands corresponding to each position were mixed at equimolar concentrations and annealed by heating at 95°C for 5 min, followed by gradual cooling to room temperature (25°C) for 5 min, and finally maintained at 0°C for 5 min. The external overhangs of the cis-element at position 4 and the core promoter were designed to carry EcoRI and BamHI digested sites. In this way, it was allowed to ligate to a previously digested EcoRI/BamHI pMR1 plasmid. All five fragments (4 cis-elements positions plus core promoter) were mixed equally in a pool with the final concentration of 5′ phosphate termini fixed at 15 μM. For the ligase reaction, 1 μL of the fragment pool was added to 50 ng EcoRI/BamHI pMR1 digested plasmid in the presence of ligase buffer and ligase enzyme to a final volume of 10 μL. Ligation was performed for 1 h at 16°C, after which the ligase reaction was inactivated for 15 min at 65°C. Two μL of the ligation was used to electroporate 50 μL of E. coli DH10B competent cells. After 1-h regenerating in 1 mL LB media, the total volume was plated in LB solid dishes supplemented with chloramphenicol at 34 μg/mL. Clones were confirmed by colony PCR with primers pMR1-F and pMR1-R (Table 1) using pMR1 empty plasmid PCR reaction as further length reference on electrophorese agarose gel. Clones with a potential correct length were submitted to Sanger DNA sequencing to confirm correct promoter assembly.

Promoter activity was measured for all 42 promoters at different genetic backgrounds and conditions. For each experiment, the plasmid containing the promoter of interest was used to transform E. coli wild type, E. coli ΔihfA mutant, or E. coli Δfis mutant, as indicated. Freshly plated single colonies were selected with sterile loops and then inoculated in 1 mL of M9 media. After 16 h 10 μL of this culture was assayed in 96 wells microplates in biological triplicate with 190 μL of M9 media. Cell growth and GFP fluorescence were quantified using a Victor X3 plate reader (PerkinElmer) that was measured for 8 h at intervals of 30 min. All graphics were constructed based on 4 h of cell growth since under our experimental setup and previous work (Monteiro et al., 2018), most promoters reach maximal activity at 4 h of growth. Therefore, this is the best time point to compare maximal promoter activity. Promoter activities were calculated as arbitrary units dividing the GFP fluorescence levels by the optical density at 600 nm (reported as GFP/OD₆₀₀) after background correction. Technical triplicates and biological triplicates were performed in all experiments. Raw data were processed using ad hoc R script (https://www.r-project.org/), and plots were constructed using R (version R-3.6.3). For all analyses, we calculated fold-change expression using pMR1-NNNN as the promoter reference.