Drosophila cells, we show that the pausing stability is influenced by downstream promoter sequences, but that the strongest contribution to Pol II pausing comes from the initiator sequence, in which a single nucleotide, a G at the +2 position, is critical for stable Pol II pausing. These results establish reporter-ChIP-nexus as a valuable tool to analyze Pol II pausing.RNA polymerase II (Pol II) pausing is a general regulatory step in transcription, yet the stability of paused Pol II varies widely between genes. Although paused Pol II stability correlates with core promoter elements, the contribution of individual sequences remains unclear, in part because no rapid assay is available for measuring the changes in Pol II pausing as a result of altered promoter sequences. Here, we overcome this hurdle by showing that ChIP-nexus captures the endogenous Pol II pausing on transfected plasmids. Using this reporter-ChIP-nexus assay in  RNA polymerase II (Pol II) pausing is a key regulatory step in metazoan gene regulation. After initiating transcription at the transcription start site (TSS), Pol II often pauses 30–50 bp downstream of the TSS, before being released by p-TEFb into productive elongation . Genome-Drosophila embryo, Pol II pausing is most frequently found at developmental control genes, and a large portion of these genes remain highly paused throughout embryonic development independently of their expression . This assay has the advantage of distinguishing Pol II signal at the site of initiation and pausing, and thus the Pol II half-life calculations are based on paused Pol II, rather than total Pol II at the promoter  . Since iTo validate that transcription on this promoter indeed begins at the initiator sequence and thus the accumulation of Pol II occurs downstream of transcription start site, we developed a gene-specific 5’ RNA sequencing protocol . This asDrosophila pseudoobscura into the reporter. D. pseudoobscura promoters are sufficiently different from those in the melanogaster genome (due to ~25 millions of years of divergence), thereby facilitating the unambiguous mapping of Pol II signal on the plasmid.To test whether the Pol II pausing profile on the plasmids recapitulates the pattern of endogenous promoters, we then cloned promoter sequences from D. melanogaster and D. pseudoobscura, we first performed Pol II ChIP-nexus analysis on a D. pseudoobscura cell line (ML83-63) and analyzed the stability of paused Pol II after 1 hr triptolide treatment. After 1 hr triptolide treatment, promoters with a Pol II half-life of ~5–10 min show strongly reduced Pol II pausing at the pause position and often show increased levels of Pol II at the site of initiation as previously observed (Since the promoter sequences might have diverged in function between observed . In contobserved .pseudoobscura promoters of ~250 bp in length that had a variety of known core promoter elements bound by TFIID (Table S1). We transfected each plasmid into D. melanogaster Kc167 cells and mapped the initiation start sites using gene-specific 5’ RNA sequencing  showed a strong reduction of paused Pol II after 1 hr triptolide treatment, while others (e.g pk) displayed minimal loss  and replaced the entire downstream promoter sequence with that of a stably paused promoter (pk or dve)  . We then or dve) . Since tTo quantify the difference in Pol II pausing stability, we first calculated the relative loss of paused Pol II between control and triptolide-treated samples for each construct. Since the same batch of transfected cells are used for this comparison, and the total read counts are normalized to the genomic DNA, the relative loss of paused Pol II is constant and independent of transfection efficiency. Indeed, we found that these measurements were highly reproducible across biological replicates, although the reproducibility was somewhat lower with shorter treatment times of triptolide, presumably because small experimental fluctuations have a larger effect. To compare two constructs, we then determined the difference of triptolide-induced Pol II loss between the mutant construct and the wild-type counterpart. These calculations show that replacing the downstream region in our promoters increased the half-life of paused Pol II around 2-fold .Taken together, these results confirm that downstream promoter sequences indeed influence the stability of Pol II pausing and we will now refer to MTE, DPE and PB collectively as pausing elements. We next focused on the role of the other TFIID-bound regions in Pol II pausing.hsp70 promoter, contain a TATA box and yet show a strong pausing profile .As expected, promoters with a pausing element or an Inr tended to have a long Pol II half-life (median ~25 min) and promoters with both elements displayed an even longer half-life (median ~30 min), consistent with them functioning together . Also copk, comm2 and dve with that of the TATA-containing promoter Act5C , we observed reduced Pol II in all constructs as compared to the wild-type promoter , this small change indeed reduced the stability of Pol II pausing, albeit to a lesser extent than when the entire upstream region was replaced  . We founreplaced . This suTo better understand how the TATA box may promote pause release in some promoter contexts, we turned our attention to the Inr. The Inr functions synergistically with the TATA box in transcription if the two elements are optimally spaced from each other , but on dve promoter, which only weakly responded to the TATA-region replacement and swapped both the upstream region and the Inr with the sequences from the TATA-containing Act5C promoter  with those of stably paused promoters without a TATA box . The results revealed a significant difference in the Inr sequence between the two promoter types . The Inr−46). This raises the possibility that the G at the +2 position of the Inr, which we refer to as Inr-G, plays an important role in stabilizing Pol II pausing.In contrast, Inr sequences of TATA-containing promoters are more degenerate with frequent mismatches to the Inr consensus sequences  right. T−48) or ~18 min for promoters with a pausing element (Wilcoxon p<10−24). When the Inr-G variant was found in combination with a pausing element, the median Pol II half-life was almost 60 min . This suggests that while the pausing elements contribute to Pol II pausing, they strongly depend on the Inr-G variant, which overall has the strongest effect on Pol II pausing.The discovery of the Inr-G variant prompted us to revisit our earlier analysis on how different combinations of promoter elements correlate with the half-life of paused Pol II. Strikingly, when we distinguished between Inr-G and Inr-nonG variants, the presence of the Inr-G variant correlated by far the strongest with Pol II pausing . Promote−7). This suggests that the Inr acts dominantly over TATA in its effect on Pol II pausing, which explains our earlier observations that introducing a TATA upstream region alone only had a small effect on stably paused promoters.Interestingly, the presence of TATA was still correlated with shorter Pol II half-lives (median ~13 min), but the variant of Inr that was present made a strong difference . While pdve, pk and the synthetic promoter SCP) and performed Pol II ChIP-nexus under control and triptolide treated conditions   . Importafor SCP) , consistfor SCP) .dve promoter showed an almost five-fold decrease when mutated to either T or A. Even the pk and SCP promoters, which have more downstream pausing elements (Table S1) showed a ~ 2 fold reduction. These results show that the G in the Inr is indeed critical for stable Pol II pausing in Drosophila. More generally, this discovery demonstrates that reporter ChIP-nexus can be used to analyze the role of promoter sequences in Pol II pausing and uncover previously unknown roles of promoter elements.Strikingly, we observed a dramatic reduction in the stability of paused Pol II in the mutated constructs relative to the wild-type construct . The dveGenome-wide correlations have suggested a role for promoter sequences in Pol II pausing , but funMost notably, we found that the Inr sequence played a strong role in the stability of Pol II pausing. This is surprising because the Inr sequence is thought to function synergistically with both the TATA box and the pausing elements , which hDrosophila and human promoters  was identified in comparative sequence . This susequence  and achisequence .Drosophila, human Inr sequences are often more degenerate and do not show a significant enrichment of G at the +2  and the downstream Gateway cloning cassette (sequence between attR1 and attR2) were removed by digesting with the SacI and AfeI restriction enzymes. A 6 x UAS sequence from pUASp (as found in DGRC #1189) was inserted between the SacI and Afel restriction sites using Gibson Assembly Master Mix. The resulting plasmid pAWG-UAS has the Act5c upstream regulatory region, 6 x UAS, a GFP coding sequence and an EcoRV restriction site between the UAS sequences and the GFP coding region. Promoter sequences of interests were inserted into pAWG-UAS at the EcoRV cutting site with Gibson Assembly Master Mix. Subsequent mutations of core promoter sequences were performed with the Q5 site-directed site mutagenesis kit. For plasmid amplification and purification, the DNA was transformed into NEB 5-alpha Competent E. coli (High Efficiency) or One Shot ccdB Survival 2 T1R Competent Cells and purified with IBI High Speed Plasmid Mini Kit. Clones were validated with Sanger sequencing using the sequencing primer GCACCGTGACCATCACAGCATA. See Table S6 and S7 for detailed constructs descriptions and sequences.The pAWG GFP reporter plasmid from the D. melanogaster Kc167 cells (DGRC #1) were grown in SFX media at 25°C. D. pseudoobscura ML83-63 cells (DGRC #33) were grown in M3 +BPYE + 10% FCS media at 25°C. Transcription inhibitors were added directly into culture media. Cells were treated with 500 μM Triptolide (TOCRIS Bioscience Cat. No. 3253 dissolved in DMSO) as done previously  for 10 min at room temperature with rotation, and then centrifuged and re-suspended in ChIP Buffer . Sonication was performed with a Bioruptor Pico for five rounds of 30 s on and 30 s off. Chromatin extracts were then centrifuged at 16000 g for 5 min at 4°C, and supernatants were used for ChIP.For each ChIP-nexus experiment, 10To couple Dynabeads with antibodies, 50 µl Protein A and 50 µl Protein G Dynabeads were used for each ChIP-nexus experiment and washed twice with ChIP Buffer. After removing all the liquid, Dynabeads were resuspended in 400 µl ChIP Buffer. 10 µg antibodies were added, and tubes were incubated at 4°C for 2 hr with rotation. After the incubation, antibody-bound beads were washed twice with ChIP Buffer.f exonuclease for generating Pol II footprints at high resolution. After each enzymatic reaction, the chromatin was washed with the Nexus washing buffers A to D and Tris buffer .For chromatin immunoprecipitation, chromatin extracts were added to the antibody-bound beads and incubated at 4°C overnight with rotation and then washed with Nexus washing buffer A to D . End repair and dA-tailing were performed using the NEBNext End Repair Module and the NEBNext dA-Tailing Module. ChIP-nexus adaptors with mixed fixed barcodes  were ligated with Quick T4 DNA ligase and converted to blunt ends with Klenow fragment and T4 DNA polymerase. The samples were treated with lambda exonuclease and RecJf exonuclease digestion, the chromatin was eluted and subjected to reverse crosslinking and ethanol precipitation. Purified single-stranded DNA was then circularized with CircLigase, annealed with oligonucleotides complementary to the BamHI restriction site and linearized by BamHI digestion. The linearized single-stranded DNA was purified by ethanol precipitation and subjected to PCR amplification with NEBNext High-Fidelity 2X PCR Master Mix and ChIP-nexus primers. The ChIP-nexus libraries were then gel-purified before sequencing with Illumina NextSeq 500.After RecJ7 Kc167 cells were diluted in 10 ml SFX media and seeded into a 10 cm cell culture dish. A mixture of 2.5 µg reporter plasmids, 20 µl FuGENE HD reagent and 500 µl Opti-MEM Reduced Serum Medium was then added to the cell culture. Transfected cells were cultured for 48 hr at 25°C to allow proper expression of the reporter. ChIP-nexus was performed on the whole cell extracts from transfected cells following standard ChIP-nexus procedure as described above. After sequencing, reporter-ChIP-nexus samples were aligned to the combined genome of dm3 and the specific reporter construct. Only reads that uniquely aligned to the reporter sequence were used for analysis and PCR duplicates with the same ChIP-nexus barcode were removed.To transform cells with the reporter plasmid, 1.5 × 10RpL30 locus, after normalizing for the difference in copy number between the reporter and the endogenous genome.Expression of the reporter was quantified by calculating the expression of GFP RNA from the reporter over the expression of the endogenous RNA from the 5 transfected cells were transferred into 1.5 ml tubes and washed with cold PBS. After removing all liquid, cells were lysed and incubated with 500 µl TRIzol Reagent at room temperature for 5 min. Total RNA was then extracted with 100 µl Chloroform and purified with a Direct-zol RNA MiniPrep kit. cDNA was generated with a High-Capacity RNA-to-cDNA Kit.For cDNA preparations, 5 × 105 transfected Drosophila Kc167 cells were transferred to 1.5 ml tubes and washed with cold PBS. After removing all liquid, cells were lysed with 50 µl ChIP buffer. Cell lysates were incubated with 150 Elution buffer , 100 µl TE buffer  and 4 µl RNAse A for 30 min at 37°C. Then, 2 µl Protease K was added to the mixture and incubated at 65°C for 2 hr. The DNA was then purified with an ethanol precipitation. qPCR on both the cDNA and DNA was performed using Fast SYBR Green Master Mix and primers against GFP and RpL30. The relative expression of the reporter was calculated using the following equations.For DNA preparations, 5 × 105 transfected cells each. Two technical replicates  were performed during qPCR.For this analysis, cDNA was prepared from two to three biological replicates (cells were transfected and processed on different dates) using 5 × 105 transfected cells as above, and cDNA was generated from the GFP RNA using SuperScript II Reverse Transcriptase and a primer against GFP that has partial TruSeq P5 sequences at the 5’ end (GFP_reversetx_primer). The cDNA was purified by treatment with RNAse A and RNAse H at room temperature for 30 min, followed by ethanol precipitation. The cDNA circularization, cutting and PCR amplification was then performed as in the ChIP-nexus protocol (thus without rolling circle amplifications), except that a new BamHI cutting oligo (reversetx_BamHI_cutting) was annealed before BamHI cutting, and a barcoded P7-GFP fusion primer (reversetx_barcode_primer_#1) was used in the PCR. After sequencing with TruSeq primers, the reads were aligned to the dm3-reporter combined genome, and the first bases of the P5 sequenced reads were recorded as the stop bases of the reverse transcriptase and correspond to the 5’ ends of the GFP RNA from the reporter plasmid.This method is similar to 5’ RNA amplification of cDNA ends (RACE) but uses reagents and steps from ChIP-nexus. Briefly, total RNA was isolated from 5 × 10Due to variations in the transfection efficiency, absolute Pol II signal on different plasmids is not comparable. As a result, paused Pol II stability needs to be accessed by comparing Pol II signal under control and triptolide-treated conditions. Because control and triptolide-treated samples come from the same pool of transfected cells, they have the same transfection efficiency and the same plasmid/Kc167 genome ratio. Therefore, Pol II signal on the plasmids under control and triptolide-treated conditions can be directly compared after normalizing for read counts.The changes in Pol II signal after triptolide treatment is calculated in the following way:Each sample is first normalized to reads/millions to account for differences in read coverage.For each sample, the total Pol II signal is calculated in a 301 bp window around the promoter region on the plasmid .The change in Pol II signal on the plasmid in response to triptolide treatment is then calculated as the ratio between Total_Pol_sig from the triptolide-treated sample over Total_Pol_sig from the corresponding DMSO-treated control sample.7 transfected cells each.It is likely that this method underestimates the changes of Pol II signal between control and triptolide-treated condition since the total occupancy of Pol II is slightly reduced after triptolide treatment , yet we In The same method was applied to Drosophila Kc167 cell, 132 promoters were defined as TATA promoters and 490 promoters were defined as stably paused promoters.TATA promoters and stably paused promoters were defined using the length of paused Pol II half-life  and the In https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116244).Raw and processed data associated with this manuscript are deposited in GEO under the accession number GSE116244 .All data analysis performed in this paper, including raw data, processed data, software tools, and analysis scripts, have been reproduced in a publicly accessible Linux virtual machine. Instructions for accessing the virtual machine can be found at  In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been evaluated by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Aviv Regev as the Senior Editor.Thank you for sending your article entitled "Reporter-ChIP-nexus reveals contribution of initiator sequence to RNA Polymerase II pausing" for peer review at Summary:D. pseudoobscura promoters in the reporter plasmid in a D. melanogaster genomic background, they show that initiation, pausing, and the stability of pausing are recapitulated on the plasmids. This is important validation of the usefulness of the system. Promoter swapping and targeted mutagenesis of reporter promoters then yielded three main results: 1) the downstream region of promoters was important for pause stability, 2) a TATA-box is associated with pause instability, and 3) a strong initiator consensus with a G at +2 was critical for pause stability.In this work, the Zeitlinger lab uses ChIP-nexus (a high-resolution form of ChIP-seq developed in the Zeitlinger lab) combined with a reporter system to study the contribution of promoter DNA sequence to the stability of paused polymerase. Using The reviewers all found the ChIP-nexus technique to be powerful, with the potential for high throughput screens with this strategy. However, as presented here, the assay is very low throughput. Incredibly, most of the authors conclusions are drawn from a single perturbation of single test promoter sequence. The work herein is thus considered preliminary, and requires additional validation prior to publication.In short, the very limited, highly context-dependent data presented in this manuscript reduces enthusiasm for both the assay and the strength of the authors' conclusions. If concerns can be addressed with additional experiments, however, the reviewers are happy to consider a revised manuscript.Essential revisions:1) The authors must test each of the promoter mutations in several promoter contexts to validate findings. We recommend that every mutation be tested in at least 3 different promoter backgrounds to allow for reasonable confidence in conclusions.2) The drug triptolide has been used by a number of groups to measure the stability of paused RNAPII and all data thus far converges towards a median half-life of paused RNAPII on the order of around 5-10 min. Genes that have polymerase remaining at 1 h of triptolide treatment are thus extreme outliers. As such, it is a shame that the authors have selected this type of hyper-stable promoter for use in their assay, as it makes it very difficult- if not impossible- to extrapolate from this extreme case to normal promoter behavior. In the absence of experiments on a more typical promoter, the reviewers are concerned that the results presented here will not be broadly applicable. Thus, when additional promoters are tested, we strongly recommend that the authors select promoters with decay rates more in line with the average gene, and use a more relevant time point for triptolide treatment, on the order of 5-20 min.melanogaster data from Kc cells +/- triptolide and should have plenty of sequencing depth given the number of plasmids analyzed. Thus, in theory, this would simply require analysis of the genomic reads without additional experimentation. This would serve to corroborate the results and generalize the model to more promoters.3) To better support the authors claims, they should perform a genomic analysis with their existing data on the stability of pausing at promoters with various combinations of the TATA and Inr elements. They already have the 4) The claim that the reporter assay recapitulates the genomic assay could also use strengthening. This point is supported by 8 genes in the current manuscript, which is probably not enough for statistically rigorous conclusions. Figure 2—figure supplement 2 shows the 8 examples, and there is quite some variability in them. The question is how much variability, how to quantify it, and whether or not conclusions can be made given this variability. Given that a lot of conclusions are drawn from comparing the shapes of these promoter distributions, I would think the extent to which they can be reliably made is important. dve, the gene selected for the majority of mutational tests, is an example that shows differences between genomic and reporter contexts.One idea is to bin the promoters into, say 10-20bp bins, and compare the normalized read counts across the bins for the reporter and genomic assay. Then the mean squared error or the correlation coefficient can be computed comparing the reporter and the genomic assay, and the degree of variability can be measured across more genes. This would at least give us some context for how much variability can be expected, and if the differences observed due to the mutations are significantly more than that baseline difference. This analysis or something similar is considered critical.5) The novelty of finding a strong initiator at highly paused genes is severely over-exaggerated and previous literature is inadequately cited. The connection between Initiator consensus elements, highly focused transcription initiation and high levels of paused RNAPII has appeared multiple times in the literature previously, at least as far back as 2008 , and also in 2010 .Further, pausing has been recapitulated on DNA sequences in vitro, thus we already know that DNA sequence is a major contributor to pausing. See many in vitro studies from the Gilmour lab (some cited) and also Adelman and Lis (2005).Drosophila Hsp70 promoter, by inserting sequences that changed the position of these elements. See Kwak et al., 2013. Given that there are so few studies like this and the level of detail covering other aspects of the literature, I think this experiment is worth discussing in this context.Finally, the authors mention in the Discussion that functional data supporting a role for promoter sequences and pausing are missing. While they are correct that there is a dearth of these important functional studies, the Lis lab did a functional analysis pause elements in the It doesn't take anything away from the authors' accomplishments to adequately cite previous research in a scholarly way. Appropriate citations must be added.6) Also related to the ambiguity in the number of promoters involved in each analysis: In the section "The Inr strongly contributes to the degree of Pol II pausing", I think it would be enhanced if the text listed the number of promoters examined for each group. For example, the text says "We first analyzed the naturally occurring Inr sequences from TATA-containing promoters versus those of stably paused promoters". I would like to know when reading this how many promoters are in each set leading to the observations e.g. that TATA-containing promoters have fewer Gs at the +2 position. In particular, when reading the caption for Figure 5A, it says n=132, and this implied that the other panels also used 132 promoters. However I expect that the other panels were based on a larger set (at least panel B). Ideally, more than 132 promoters would have been used for this analysis. Overall, added clarity on the number of promoter for Figure 5B and elsewhere would be helpful.eLife. This evaluation has been overseen by a Reviewing Editor and James Manley as the Senior Editor.Thank you for submitting your article "Reporter-ChIP-nexus reveals strong contribution of initiator sequence to RNA Polymerase II pausing" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:This revised version of the manuscript "Reporter-ChIP-nexus reveals strong contribution of initiator sequence to RNA Polymerase II pausing" is improved over the previous version as concerns the number of promoters and mutations analyzed. However, the way in which the data is discussed is still lacking in clarity, the caveats to interpretation are still not made clear, and the citation of prior literature is still lacking.Thus, the manuscript is not determined to be acceptable in its current format. However, at this point the main criticisms of the work can all be addressed with text changes. Thus, we invite a resubmission if such changes are comprehensively made.Essential revisions:1) As the authors acknowledge in the Introduction, pausing takes place at all  genes. The duration and stability of pausing varies, but pausing appears to be an obligate part of the transcription cycle. Thus, the statement in the Abstract that "a G at the +2 position, is critical for Pol II pausing", is not accurate. The authors should change this to clarify that they mean 'stable pausing' or something of this sort. But a G and +2 is certainly not critical for the fundamental process of pausing itself.2) The authors should note early in the Results section that 1h Triptolide treatment is a very long treatment, and that secondary effects are likely to occur during such extended intervals of transcription inhibition. Most labs use 2-20 minutes of Triptolide treatment to avoid such potential artifacts. We appreciate that the authors must rely on very long treatments to overcome the considerable noise in their assay, but this should be acknowledged as a potential source of artifact, and as a potential limitation to this study. This idea is briefly mentioned in the Discussion, but it must be noted in the Results section to make readers aware of this caveat.3) The Bentley lab has recently questioned the interpretation of Triptolide data , noting that at some genes the Triptolide-mediated block to initiation traps Pol II at the TSS. This effect is evident at the Pino and pepck genes in this study. The authors should cite the recent work from the Bentley lab, and explain whether their ChIP-nexus assay gives them the spatial resolution needed to separate paused from un-initiated Pol II. This will help place the current work in a proper context, and will be clarifying for the field.4) Based on the limited number of experiments aimed at testing the role of downstream promoter sequences, and the limitations in interpreting such experiments, the authors should be more circumspect in the conclusions drawn from these studies. We find it to be an over-reach that the authors conclude that downstream sequences affect pausing less than expected. Given the lack of data to this point, it is safest to note that this wasn't rigorously evaluated, and leave it at that.5) We understand that the authors went into this study expecting the TATA box to elicit a strong effect on pausing, and that they were surprised that this is not the case. However, the large amount of inconclusive data presented on this topic, and the discussion thereof, is confusing. If the main conclusion is that TATA doesn't seem to have a strong effect on pause stability, and that any effect is highly context dependent and easily over-ridden by other sequences, then there is a much more straightforward way to present this. We strongly suggest that the authors simplify the presentation of the TATA data to focus on the main conclusion, rather than enumerating all the inconclusive or contradictory findings they obtained.6) Given that computational assays have routinely defined the Inr consensus to have a G at +2, should this really be called the Inr-G variant? Instead, we recommend that this be considered the consensus. It should be clarified that this is the 'norm' and not something that deviates from the norm.7) The discussion of pausing in its genomic context versus on a plasmid at the beginning of the Discussion is difficult to understand in light of the literature.First, there have been a number of studies demonstrating that stable pausing does not involve downstream nucleosomes. The clearest of these demonstrations was Li and Gilmour, EMBO J, 2103). This paper should be cited and the authors should edit the first paragraph to reflect this work, and the fact that it is not at all surprising that pausing could take place on a plasmid or outside of the chromatin context.8) It was demonstrated many years ago that pausing is rarely inhibitory in its endogenous context, because of the positive effect of the paused polymerase on maintaining open chromatin (Gilchrist G and D 2008). In this study, it was specifically demonstrated that the positive effect of pausing was clear in the endogenous context, but did not occur on a plasmid. Thus, it has been previously established that the effect of pausing on gene output is different on a plasmid than in the genome, and that any minor inhibitory effect seen on a plasmid is NOT borne out in the endogenous locus. Thus, it is perplexing that the authors claim that pausing is inhibitory based on their reporter assay- since this is known to be an inaccurate read-out of endogenous activity. Thus, the comments in the Discussion suggesting that the +2 G version of Inr would be inhibitory to transcription because it promotes pausing are unfounded and should be removed. Essential revisions:1) The authors must test each of the promoter mutations in several promoter contexts to validate findings. We recommend that every mutation be tested in at least 3 different promoter backgrounds to allow for reasonable confidence in conclusions.We agree and have now tested 9 additional promoters . In addition to these experiments, we have dissected the role of various promoter combinations computationally in more detail and found that these data strengthen and refine our conclusions.As expected, we found that the downstream pausing elements stabilize pausing and that addition of a TATA box may reduce pausing. Interestingly though, the effect of TATA is not as strong and consistent as expected, and this can be explained by the strong effect of the Inr sequence (with a G at position +2). Mutating the G at the Inr on the other hand strongly reduces Pol II pausing. Consistent with such strong role in pausing, the type of Inr variant has the strongest correlation with the half-life of paused Pol II among all analyzed elements, an analysis we now added. Therefore, we have not only added additional experiments to support our conclusions, but we have strengthened our finding that the Inr plays an important role in Pol II pausing.2) The drug triptolide has been used by a number of groups to measure the stability of paused RNAPII and all data thus far converges towards a median half-life of paused RNAPII on the order of around 5-10 min. Genes that have polymerase remaining at 1 h of triptolide treatment are thus extreme outliers. As such, it is a shame that the authors have selected this type of hyper-stable promoter for use in their assay, as it makes it very difficult- if not impossible- to extrapolate from this extreme case to normal promoter behavior. In the absence of experiments on a more typical promoter, the reviewers are concerned that the results presented here will not be broadly applicable. Thus, when additional promoters are tested, we strongly recommend that the authors select promoters with decay rates more in line with the average gene, and use a more relevant time point for triptolide treatment, on the order of 5-20 min.D. mel. of 5 (Act5C), 10 (pino) and 10 (pepck) min, respectively, which are in line with “average” promoters. However, in order to detect significant differences in half-lives between hybrid promoters, we have to use the more stable paused promoters. This is because the accuracy and reproducibility of the assay is higher for promoters with longer half-lives. For promoters with shorter half-lives, we have to use shorter drug treatment times. As a result, small fluctuations in drug treatment time and drug penetration can produce considerable variability in the results. To accurately measure a half-life in the order of 5-20 min, we would need to perform tightly spaced time-course experiment in many replicates. In the future, this might be possible as we plan to automate the assay and reduce sequencing cost by isolating plasmid DNA. However, with the current low-throughput method, using sequences from stably paused promoters is a more feasible approach for obtaining clear and interpretable results.Apart from the stably paused promoters, we have tested the Pol II profile on plasmids using promoters with a half-life in Drosophila. Drosophila has a much larger fraction of promoters with clearly defined core promoter sequences that are associated with stable Pol II pausing. While pausing may not be as stable in mammalian genomes, the role of core promoter elements and the interaction between core promoter elements and TFIID is nevertheless conserved. For example, the excellent Cryo-EM structures of TFIID derived by Eva Nogales  is human TFIID on the Drosophila super core promoter (which includes “pausing elements” such as DPE and MTE). For this reason, we believe that the insights obtained from stably paused promoters will be broadly relevant.In fact, this is one of the reasons we pioneered this assay in We have now extensively rewritten the Introduction to better explain our reasoning behind the choice of promoters. In short, they are easy to study and due to known interactions with TFIID, are relevant for mammalian promoters. Finally, we point out current limitations of the assay in our Discussion at the end.3) To better support the authors claims, they should perform a genomic analysis with their existing data on the stability of pausing at promoters with various combinations of the TATA and Inr elements. They already have the melanogaster data from Kc cells +/- triptolide and should have plenty of sequencing depth given the number of plasmids analyzed. Thus, in theory, this would simply require analysis of the genomic reads without additional experimentation. This would serve to corroborate the results and generalize the model to more promoters.We liked the idea of performing a more combinatorial analysis of the promoter elements with regard to the paused Pol II half-lives, and this approach turned out to be very fruitful. While we had previously analyzed the genome-wide relationship between core promoter elements and paused Pol II half-lives , we had not specifically looked at how various combinations correlate with Pol II pausing. This new analysis now revealed that the Inr sequence with a G at the +2 position most strongly correlates with pausing, independently of which other core promoter elements are found in the promoter.We have now added the results from this new analysis to Figure 4A and Figure 7A with additional information found in Figure 4—figure supplement 1, Figure 7—figure supplement 1 and Table S6 in Supplementary file 1.4) The claim that the reporter assay recapitulates the genomic assay could also use strengthening. This point is supported by 8 genes in the current manuscript, which is probably not enough for statistically rigorous conclusions. Figure 2—figure supplement 2 shows the 8 examples, and there is quite some variability in them. The question is how much variability, how to quantify it, and whether or not conclusions can be made given this variability. Given that a lot of conclusions are drawn from comparing the shapes of these promoter distributions, I would think the extent to which they can be reliably made is important. dve, the gene selected for the majority of mutational tests, is an example that shows differences between genomic and reporter contexts.One idea is to bin the promoters into, say 10-20bp bins, and compare the normalized read counts across the bins for the reporter and genomic assay. Then the mean squared error or the correlation coefficient can be computed comparing the reporter and the genomic assay, and the degree of variability can be measured across more genes. This would at least give us some context for how much variability can be expected, and if the differences observed due to the mutations are significantly more than that baseline difference. This analysis or something similar is considered critical.We had a supplementary table (Table S3 in Supplementary file 1) that showed the correlation coefficient between the bp of the Pol II profiles from the plasmid versus those of the genomic region. They range from 0.77 to 0.96 (mean 0.92), which is very high given that we are not even binning the data into 10-20 bp bins (binning would presumably smooth the data and give higher correlations).To strengthen this point even further, we have now in the revised manuscript compared these correlation coefficients to those obtained between biological replicate experiments on the plasmids (Table S2 and S3 in Supplementary file 1). Overall, we found the correlations between plasmid and genomic context to be only slightly lower than those between replicates (on average 0.86 versus 0.92), suggesting that the plasmid recapitulates the genomic Pol II pausing profile remarkably well despite possible differences in chromatin or regulatory context. We have added this result to the main text , as well.5) The novelty of finding a strong initiator at highly paused genes is severely over-exaggerated and previous literature is inadequately cited. The connection between Initiator consensus elements, highly focused transcription initiation and high levels of paused RNAPII has appeared multiple times in the literature previously, at least as far back as 2008 , and also in 2010 .Further, pausing has been recapitulated on DNA sequences in vitro, thus we already know that DNA sequence is a major contributor to pausing. See many in vitro studies from the Gilmour lab (some cited) and also Adelman and Lis (2005).Finally, the authors mention in the Discussion that functional data supporting a role for promoter sequences and pausing are missing. While they are correct that there is a dearth of these important functional studies, the Lis lab did a functional analysis pause elements in the Drosophila Hsp70 promoter, by inserting sequences that changed the position of these elements. See Kwak et al., 2013. Given that there are so few studies like this and the level of detail covering other aspects of the literature, I think this experiment is worth discussing in this context.It doesn't take anything away from the authors' accomplishments to adequately cite previous research in a scholarly way. Appropriate citations must be added.The statistical association between the Inr and Pol II pausing has been described before, by ourselves in collaboration with Mike Levine’s lab (Hendrix 2008) and in Gilchrist et al., 2010 . However, this association could have been indirect since another pausing element, the DPE, requires the Inr to function properly . Due to the possible indirect effect, while the association between DPE (or PB) and pausing is more evident, the role of the Inr has been much less clear. In addition, the role of the Inr in Pol II pausing is further complicated by the observation that the Inr functions synergistically with the TATA box, which is associated with reduced Pol II pausing.Regardless of how one interprets these statistical associations, a causal role in Pol II pausing had not been adequately shown for any core promoter element. We believe our results are novel and significant as we provide strong evidence that core promoter elements impact Pol II pausing individually. To the best of our knowledge, such direct functional examinations have not been done before (the spacing experiments by the Lis lab are interesting but do not address which promoter element mediates the observed effects). Furthermore, in the revised manuscript, we not only provide evidence for a direct role of the Inr in Pol II pausing, but we also show that statistically speaking, the G in the Inr plays a dominant role in Pol II pausing, which is quite surprising.To provide more clarity for the reader, we have now rewritten the manuscript to better describe what was (or was not) known about the Inr, while citing the requested papers . This should help the reader better understand the significance of our finding.6) Also related to the ambiguity in the number of promoters involved in each analysis: In the section "The Inr strongly contributes to the degree of Pol II pausing", I think it would be enhanced if the text listed the number of promoters examined for each group. For example, the text says "We first analyzed the naturally occurring Inr sequences from TATA-containing promoters versus those of stably paused promoters". I would like to know when reading this how many promoters are in each set leading to the observations e.g. that TATA-containing promoters have fewer Gs at the +2 position. In particular, when reading the caption for Figure 5A, it says n=132, and this implied that the other panels also used 132 promoters. However I expect that the other panels were based on a larger set (at least panel B). Ideally, more than 132 promoters would have been used for this analysis. Overall, added clarity on the number of promoter for Figure 5B and elsewhere would be helpful.We had previously described this promoter selection in detail in the Materials and methods under subsection“Sequence analysis of TATA promoters and stably paused promoters”. To make it easier for the reader, we now describe the selection of the promoters briefly in the main text (subsection “The Inr strongly contributes to the degree of Pol II pausing”) and the Figure 5 legend. Furthermore, we perform a more general analysis of the combinatorial relationship between core promoter elements and pausing half-life , which places the above-mentioned figure into context.Essential revisions:1) As the authors acknowledge in the Introduction, pausing takes place at all  genes. The duration and stability of pausing varies, but pausing appears to be an obligate part of the transcription cycle. Thus, the statement in the Abstract that "a G at the +2 position, is critical for Pol II pausing", is not accurate. The authors should change this to clarify that they mean 'stable pausing' or something of this sort. But a G and +2 is certainly not critical for the fundamental process of pausing itself.We agree: in fact, in two out of four sentences we had said “critical for stable Pol II pausing”. We have now changed the remaining two sentences also to “critical for stable pausing”.2) The authors should note early in the Results section that 1h Triptolide treatment is a very long treatment, and that secondary effects are likely to occur during such extended intervals of transcription inhibition. Most labs use 2-20 minutes of Triptolide treatment to avoid such potential artifacts. We appreciate that the authors must rely on very long treatments to overcome the considerable noise in their assay, but this should be acknowledged as a potential source of artifact, and as a potential limitation to this study. This idea is briefly mentioned in the Discussion, but it must be noted in the Results section to make readers aware of this caveat.We appreciate the concern about side effects, which we share when using drug treatments. However, we have not observed concerning side effects of treating our cells with triptolide for 60 min  and note that many investigators have used such extended treatments:- The Bentley lab paper cited below used 10-60 min;- The Shilatifard lab paper  used a time-course of up to 120 min and performed most of their further analysis on the 60 min timepoint. Like ours, their control gels on polymerase abundance and phosphorylation show no detectable side effects;- The John Lis lab paper  used 12.5 min, 25 min and 50 min timepoints.We did not mean to convey the impression in our last response letter that our assay has “considerable noise”. As can be seen from the small error bars in the figures, biological replicates are very reproducible, even when treating for 5 min . Shorter triptolide treatment times may have more noise than longer treatment times, but this could be addressed by performing more replicates. In other words, using 60 min triptolide treatment was not born out of necessity, but a strategic choice, since it allowed us to choose promoters with maximal differences in Pol II pausing stability (and we had not encountered variability or other concerning side effects with 60 min treatment times).To be sure, we now mention the better accuracy for longer Pol II half-lives in the Results section: “… we found these measurements to highly reproducible across biological replicates, although the reproducibility is somewhat lower with shorter treatments times of triptolide, presumably because small experimental fluctuations have a larger effect.”3) The Bentley lab has recently questioned the interpretation of Triptolide data , noting that at some genes the Triptolide-mediated block to initiation traps Pol II at the TSS. This effect is evident at the Pino and pepck genes in this study. The authors should cite the recent work from the Bentley lab, and explain whether their ChIP-nexus assay gives them the spatial resolution needed to separate paused from un-initiated Pol II. This will help place the current work in a proper context, and will be clarifying for the field.We agree that it is curious that this paper seems to suggest that the long Pol II half-lives we observe are due to us measuring Pol II at the initiation site. As we clearly describe in our paper, the high resolution of ChIP-nexus allows us to distinguish paused Pol II from Pol II at the initiation site . While we observe increased Pol II at the site of initiation after triptolide treatment (this is not a novel finding in the Bentley lab paper), we are specifically measuring the exponential decay of paused Pol II at the site of Pol II pausing to determine the half-life of paused Pol II (the position of pausing is determined based on Pol II pausing after flavopiridol treatment).To make this clear in the present paper, we have made the following changes:Drosophila melanogaster genome using a high-resolution exonuclease-based ChIP-seq protocol (ChIP-nexus). This assay has the advantage that it distinguishes between Pol II at the site of initiation and pausing, and thus the Pol II half-life calculations are based on paused Pol II, rather than total Pol II at the promoter .”- Introduction: “We recently performed such time-course measurements of paused Pol II across the - When we first describe the Pol II profiles after triptolide treatment, we now point out the increased Pol II at the initiation site and cite our paper and the Bentley lab paper: “After 1 hour triptolide treatment, promoters with a Pol II half-life of ~5-10 min show strongly reduced Pol II pausing at the pause position and often show increased levels of Pol II at the site of initiation as previously observed . In contrast, stably paused promoters maintain high levels of Pol II at the pausing position with no noticeable increase of Pol II at the site of initiation.”4) Based on the limited number of experiments aimed at testing the role of downstream promoter sequences, and the limitations in interpreting such experiments, the authors should be more circumspect in the conclusions drawn from these studies. We find it to be an over-reach that the authors conclude that downstream sequences affect pausing less than expected. Given the lack of data to this point, it is safest to note that this wasn't rigorously evaluated, and leave it at that.We have now removed this section from the Discussion.5) We understand that the authors went into this study expecting the TATA box to elicit a strong effect on pausing, and that they were surprised that this is not the case. However, the large amount of inconclusive data presented on this topic, and the discussion thereof, is confusing. If the main conclusion is that TATA doesn't seem to have a strong effect on pause stability, and that any effect is highly context dependent and easily over-ridden by other sequences, then there is a much more straightforward way to present this. We strongly suggest that the authors simplify the presentation of the TATA data to focus on the main conclusion, rather than enumerating all the inconclusive or contradictory findings they obtained.We have now extensively revised the text for clarity and have taken out any unnecessary commentary or discussion of the effect of TATA . Instead, we focused on the role of the Inr.6) Given that computational assays have routinely defined the Inr consensus to have a G at +2, should this really be called the Inr-G variant? Instead, we recommend that this be considered the consensus. It should be clarified that this is the 'norm' and not something that deviates from the norm.Drosophila Inr consensus motif is TCAKTY, where K stands for T or G, and both the T and G at +2 are equally functional. Furthermore, the G is not over-presented among mammalian promoters, suggesting that the G is not the better nucleotide for Pol II initiation per se. The reason computational studies have predominantly found the G variant is presumably because the Inr-G variant is less degenerate, easier to identify and shows increased conservation. Therefore, we believe it is important to point out and emphasize the presence of the G at the +2 position and feel that it conveys the information more precisely.That is a good question, but based on biochemical studies, the 7) The discussion of pausing in its genomic context versus on a plasmid at the beginning of the Discussion is difficult to understand in light of the literature.First, there have been a number of studies demonstrating that stable pausing does not involve downstream nucleosomes. The clearest of these demonstrations was Li and Gilmour, EMBO J, 2103). This paper should be cited and the authors should edit the first paragraph to reflect this work, and the fact that it is not at all surprising that pausing could take place on a plasmid or outside of the chromatin context.Actually, there are many papers supporting a role for nucleosomes in Pol II pausing, but we agree that this is not a resolved issue and the field is quite split. Since this is not an important point in the paper, we therefore decided to take out this entire section from the Discussion.8) It was demonstrated many years ago that pausing is rarely inhibitory in its endogenous context, because of the positive effect of the paused polymerase on maintaining open chromatin (Gilchrist G and D 2008). In this study, it was specifically demonstrated that the positive effect of pausing was clear in the endogenous context, but did not occur on a plasmid. Thus, it has been previously established that the effect of pausing on gene output is different on a plasmid than in the genome, and that any minor inhibitory effect seen on a plasmid is NOT borne out in the endogenous locus. Thus, it is perplexing that the authors claim that pausing is inhibitory based on their reporter assay- since this is known to be an inaccurate read-out of endogenous activity. Thus, the comments in the Discussion suggesting that the +2 G version of Inr would be inhibitory to transcription because it promotes pausing are unfounded and should be removed.We have removed this part of the Discussion as well.


Escherichia coli’s gene expression. We studied if chromosome integration impacts on a gene’s sensitivity to these shifts, by comparing the single-RNA production kinetics of a PLacO3O1 promoter, when chromosomally-integrated and when single-copy plasmid-borne. At suboptimal temperatures their induction range, fold change, and response to decreasing temperatures are similar. At critically low temperatures, the chromosome-integrated promoter becomes weaker and noisier. Dissection of its initiation kinetics reveals longer lasting states preceding open complex formation, suggesting enhanced supercoiling buildup. Measurements with Gyrase and Topoisomerase I inhibitors suggest hindrance to escape supercoiling buildup at low temperatures. Consistently, similar phenomena occur in energy-depleted cells by DNP at 30 °C. Transient, critically-low temperatures have no long-term consequences, as raising temperature quickly restores transcription rates. We conclude that the chromosomally-integrated PLacO3O1 has higher sensitivity to low temperatures, due to longer-lasting super-coiled states. A lesser active, chromosome-integrated native lac is shown to be insensitive to Gyrase overexpression, even at critically low temperatures, indicating that the rate of escaping positive supercoiling buildup is temperature and transcription rate dependent. A genome-wide analysis supports this, since cold-shock genes exhibit atypical supercoiling-sensitivities. This phenomenon might partially explain the temperature-sensitivity of some transcriptional programs of E. coli.Temperature shifts trigger genome-wide changes in  Escherichia coli has evolved sophisticated regulatory programs to adapt to fluctuating environments that allow tuning gene expression so as to trigger appropriate responses2. In general, gene expression regulation occurs during transcription initiation3 and it can be performed, e.g., by transcription factors5, which act locally, affecting specific genes, and by σ factors9, which have more genome-wide effects.11 and is regulated by nucleoid associated proteins (NAPs)13. Interestingly, changes in DNA compaction has genome-wide effects15, causing the expression of some genes to increase while in others it decreases18.Similarly, environmental changes can affect chromosomal DNA compaction, which is associated to supercoiling19). One reason for this is that the chromosome has topologically constrained segments that allow supercoiling buildup22, as transcription occurs, since this process generates positive supercoiling ahead of the RNA polymerase (RNAP) and negative supercoiling behind it24. Meanwhile, plasmids lack discrete constraints. Thus, when positive and negative supercoiling emerge, they freely diffuse in opposite directions and annihilate each other19. Thus, in general, the transcriptional activity in plasmids is only affected by transient constraints due to, e.g., transient protein binding25. Exceptions are, e.g., plasmids encoding membrane-associated proteins that, by anchoring to the membrane29, can form longer lasting constraints. Other exceptions are plasmids carrying tandem copies of one or two DNA-binding sites30 and plasmids carrying the T7 promoter, when expressed in topA mutant strains31. Nevertheless, it is worth noting that in vivo measurements suggest that, prior to annihilation, transient supercoiling changes can influence transcription rates of both plasmid-borne and chromosomally-integrated promoters33.DNA compaction and supercoiling have distinct effects on plasmid-borne and chromosome integrated genes , which involves breaking interactions between the RNAP and the promoter, and between the RNAP and initiation factors38, which are energy dependent processes.Another temperature-dependent event in transcription is promoter escapein vivo kinetics of transcription of the PLacO3O1 promoter, when on a plasmid and when chromosomally-integrated . Further, we assessed the effects on the native lac promoter, whose transcription rate is weaker than PLacO3O1, although we located it in the same position in the chromosome.Given the above, we hypothesized that plasmid-borne and chromosomally-integrated genes can differ in sensitivity to temperature shifts and that these differences may be promoter strength-dependent. To test this, we compared quantitatively the effects of temperature shifts on the E. coli, along with a recently proposed methodology to resolve the rate-limiting steps governing the in vivo dynamics of initiation of prokaryotic promoters (similar to established steady-state assays to resolve the in vitro dynamics)40. Further, we studied this process at critically low temperatures (below 23 °C), a regime in which most cellular processes exhibit significant differences due to, e.g., globally-altered transcription rates37 and increased cytoplasmic viscosity41. Using these techniques, we characterized, with single-RNA sensitivity, the RNA production dynamics of these constructs at various temperatures, as well in the presence of Gyrase and Topoisomerase I inhibitors and of DNP-based energy depletion. Also, we made use of stochastic modelling to show that the observed differences in transcription kinetics between chromosome and plasmid integrated promoters at low temperatures are consistent with current stochastic models of transcription initiation that account for supercoiling buildup, provided that such low temperatures result in the hindrance to escape from DNA super-coiling. Finally, we made use of information of what genes in E. coli have their activity induced following cold-shocks42 and of what genes are supercoiling sensitive14, to assess if these two features are strongly correlated, as our results would suggest.For this, we used the MS2-GFP RNA tagging technique in LacO3O1 differs in response to temperature changes when the gene is single-copy F-plasmid-borne and when it is chromosome-integrated. For this, we made use of two identical constructs under the control of the PLacO3O1 promoter coding for multiple bindings sites for MS2-GFP followed by the coding region of mCherry.We studied at the single-RNA level if the kinetics of RNA production under the control of PBoth constructs, shown in Figs For each strain (carrying the target gene in the plasmid or in the chromosome) and each temperature condition, we performed 3 or more biological repeats and counted RNA-spots (MS2-GFP tagged RNAs) in each cell from the microscopy images . As we did not find statistically significant differences between repeats, the results shown here are from cells from all replicates.Since the two strains are not subject to the same antibiotics , we tested whether their growth curves differ. Results in Fig. 43. Also, for both constructs, the transcription rate does not increase beyond 500 µM IPTG, i.e., 1 mM IPTG suffices for full induction, in agreement with previous studies43.For each construct (chromosome integrated and single-copy plasmid borne) and IPTG concentration, we quantified the integer-valued RNA numbers in live cells at 30 °C by microscopy imaging, 1 hour after induction of the target promoter by IPTG . From Fig. However, the RNA production kinetics of the two constructs differs in some aspects. First, from Table cc and/or kunlock suffices to account for differences between them in RNA numbers at 30 °C.Nevertheless, the same model of transcription  fits both constructs, as tuning k2) of the RNA numbers in single cells  by microscopy at various temperatures . For each condition, from the absolute integer-valued RNA numbers in each cell, we calculated the mean and squared coefficient of variation  to obtain the mean RNA numbers relative to the control (30 °C) in cells under full induction (1 mM of IPTG) at 23, 16 and 10 °C Fig. . From Ta45 or of the nucleoids . Measurements at 10 °C and 30 °C , by making use of Lineweaver–Burk plots46 of the inverse of the RNA production rate against the inverse of the RNAP concentration (Supplementary sections “Lineweaver-Burk Plots” and “Tuning intracellular RNAP concentrations”).To investigate why the two constructs responded differently to lowering temperatures, we assessed whether the changes in the kinetics of transcription with decreasing temperature occur For this, we measured RNAP levels in individual cells in each temperature condition, and verified that they differ statistically between conditions .Next, from these plots, using the same methodology as inResults in Table in vitro measurements for the synthetic PLac-UV5 promoter4, the reduction in RNA production rate with lowering temperature is mostly due to a reduction in the rate of the events after commitment to open complex formation (with tafter increasing from being 92% to 98% of the Δt as temperature is lowered). Meanwhile, in the chromosome construct, the opposite occurs (with tafter decreasing from 91% to 73% of the Δt as temperature is lowered) suggesting that, in this construct, the events whose rates were most reduced occur prior to commitment to open complex formation, provided that the RNA production rate decreases with lowering temperature  from locked promoter states , or decrease the rate of unbinding of a repressor from a promoter , or both. Either of these possibilities is physically possible since lowering temperatures could affect the efficiency of repressors (see e.g.48), DNA packaging .To explain the increased time-length of the events preceding the open complex formation in the chromosome-integrated construct at lower temperatures, we considered the model of transcription initiation . This model allows for this, provided that decreasing temperatures decrease the rate of unlocking  should affect both the chromosome and plasmid constructs similarly since both constructs are affected by this mechanism. However, we observed divergent responses between these two constructs to the lowest temperatures, with the plasmid-borne construct being unable to turn off its RNA production as efficiently as the chromosome-integrated construct (Table unlock with lowering temperature are the most likely explanation for the observed behaviors).To determine whether it is kct Table . Thus, wunlock, causing different behaviors of the two constructs in response to lowering temperatures, are associated to DNA packaging and/or super-coiling. For that, we measured the nucleoid size in cells with one nucleoid (Supplementary Information) in the various temperature conditions. If decreasing temperature .19. Results in Fig. To validate this hypothesis, we performed several experiments. First, we compared the numbers of RNAs produced over time by cells of each strain. We expect this number to increase near-constantly in the cells carrying the plasmid-borne gene, but not in the cells of the other strain. For this, from the moment of activation of the target gene (t = 0 minutes), we measured integer-valued RNA numbers in individual cells at 10 °C every 15 minutes for 90 minutes . If the weaker activity of the chromosome-integrated promoter is due to increased propensity to be in the locked state due to the accumulation of DNA super-coiling, we expect its transcription activity to be blocked after a few events. At a population level, this would result in a sharp decrease in the rate of increase of RNA numbers in the cells, some time after the start of the measurements. Meanwhile, in the plasmid construct, we expect a constant RNA production rate over time, due to the lack of accumulation of local DNA super-coilingWe also performed measurements at 30 °C. Given the similar dynamics of transcription of the two constructs in this condition Table , we expe54. Gyrase releases positive supercoiling55 but not negative supercoiling56. According to the twin-supercoiled-domain model24, which predicts that negative/positive supercoils should accumulate in the absence of supercoil-relaxing enzymes, we expect cells with the chromosome construct to exhibit a similar behavior as when at 10 °C. Meanwhile, cells with the plasmid construct should again exhibit a constant rate of transcription over time19. Figure To further test the hypothesis, we next compared the activity of the two constructs at 30 °C when subjecting cells to Novobiocin, an inhibitor of Gyrase activity (Methods)acrA is present, and thus, Novobiocin is not expected to affect cell division rates57. To test this, we measured cell growth rates by OD600 for varying Novobiocin concentrations . We found the growth rates to not differ significantly between conditions (data not shown). These results also show that 100 ng/μl Novobiocin concentration suffices to affect  the transcription rate of the chromosome-integrated gene . Topoisomerase I releases negative, but not positive supercoiling60. We expect these cells to exhibit a similar behavior as when at 10 °C, which Fig. Then, we observed cells with the chromosome integrated gene at 30 °C, when subject to Topotecan, an inhibitor of Topoisomerase I activityThese results suggest that the activity of the chromosome-integrated gene at 10 °C is hampered by an increased difficulty in unblocking the DNA from supercoiled states, rather than due to a loss of functionality of Topoisomerases I (or Gyrases). Table Finally, in comparison, subjecting cells with the single-copy F-plasmid to Topotecan causes, qualitatively, the same behavior as adding Novobiocin (at 30 °C and 10 °C) Fig. .45 (Methods). In particular, we expect cells subject to this treatment to, even at 30 °C, be less able to maintain the chromosome integrated promoter active over time when compared to the control, similar to when at 10 °C.If the escape from DNA supercoiling buildup in the chromosomally-integrated construct at low temperatures is due to energy deficiency at low temperatures (the energy required for the necessary endothermic reactions to occur should be higher in such conditions), it should be possible to mimic the phenomena by, instead of lowering temperature, depleting cells of energy via DNP treatmentLacO3O1  prior to imaging (Methods). As expected, we observed similar RNA production dynamics Fig. , as in u3O1 Fig. . I.e., bLacO3O1 to two temperature shifts, first from high (30 °C) to low (10 °C) and then from low (10 °C) to high (30 °C), and measured the mean integer-valued RNA numbers in the cells over time.We performed an additional test to support the hypothesis that the escape from DNA supercoiling buildup in the chromosome construct at low temperatures is due to energy deficiency. Namely, we hypothesized that changing temperature to near-optimal conditions (e.g. 30 °C) should restore the cells’ ability to relax DNA supercoiling (as at higher temperature this process is expected to require less energy). To test this, we subjected cells with a chromosome integrated PResults in Fig. 38, particularly at low temperatures. In the case of IPTG, previous measurements suggest that this transient is ~15–30 minutes long61, in agreement with the results in Figs Note that in this particular experiment, following the shift from 30 °C to 10 °C, it does not follow a transient of ~15–30 minutes of reduced transcription activity that is visible in Figs E. coli43 a plausible explanation for the change with decreasing temperature in the average RNA numbers over time in cells with the chromosome integrated promoter , is reported in19. This value was then gradually lowered until the mean number of RNAs per cell at the end of the measurement period was similar to that observed in cells at 10 °C.For each value of knts Fig. . The valON , RNAp (as noted above), and RNA. Initial RNA numbers were drawn randomly from a Poisson distribution (0.7 RNA/cell) to match the here observed outcome of spurious RNA production events. We observed also  results in a similar behavior to that of the plasmid-borne construct, and thus to the chromosome integrated promoter at 30 °C (data not shown).Finally, note that setting k64, which will cause the effects of positive supercoiling buildup to differ. Meanwhile, we observed that temperature downshifts have weaker effects on the plasmid-borne PLacO3O1 than on the chromosome-integrated PLacO3O1, since the latter is affected by positive supercoiling buildup. This implies that temperature down-shifts affect the various steps in transcription initiation by different degrees (as suggested in44), with escape from positive supercoiling buildup being one of the most affected.The influence of positive supercoiling buildup on the dynamics of a chromosome-integrated gene differs with its location on the chromosome due to, among other, differences in the expression rates of operons in different DNA loopsLacO3O1, should be relatively less sensitive to temperature downshifts. I.e., its RNA production rate should be less reduced by a temperature downshift, relative to the control condition (i.e. more similar in behavior to the plasmid-integrated PLacO3O1).Further, from above, it is reasonable to hypothesize that the effects of temperature downshifts on RNA production rates may be positively correlated with the expression rate of the chromosome-integrated promoter of interest. Namely, consider that the expected time for a Gyrase to intervene is determined, among other, by its intracellular concentration. As such, when increasing the transcription rate of a gene, it should become less likely for Gyrase to remove positive supercoiling buildup between transcription events. Similarly, one can also hypothesize that a chromosome-integrated promoter similar in functioning to, but with weaker activity than PTo test the first hypothesis, we compared the effects of overexpressing Gyrase (Methods) on the mean RNA numbers in cells with the chromosome integrated promoter at 10 °C, when and when not induced. When induced (1 mmM IPTG), we find that overexpressing Gyrase increases the mean number of RNAs per cell by 154%. Meanwhile, when not induced (0 mmM IPTG), this mean number only increases by 107%. This agrees with the hypothesis that, the higher the expression rate, the bigger is the impact of lowering temperatures due to decreased probability that Gyrases can act in between transcription events.LacO3O1 chromosome-integrated promoter by the native lac, which has a similar repression-activation mechanism (Methods) but weaker activity65. First, to confirm that its transcription rate is weaker than PLacO3O1, we measured the mean number of RNA molecules per cell, 1 hour after induction, at 30 °C and at 10 °C, under full induction. We found that the native lac produces ~85% less RNAs than PLacO3O1 (both at 30 °C and at 10 °C). Next, to test the hypothesis, we compared the effects of overexpressing Gyrase in cells at 10 °C, when carrying the chromosome-integrated PLacO3O1 and when carrying the chromosome-integrated native lac. Given the above, we expect the overexpression of Gyrase to have a weaker impact on the transcription rate of the native lac. Results in Table LacO3O1. Meanwhile, measurements at 30 °C showed, as expected, that no construct is significantly affected by overexpressing Gyrase  should have atypical sensitivity to supercoiling buildup. I.e., these genes should be either significantly more responsive or significantly less responsive to supercoiling buildup than randomly selected genes.E. coli’s genome-wide sensitivity to supercoiling buildup (enhanced by repressing Gyrase)14, with information on genome-wide responsiveness to cold shocks42. Cold-shock responsive genes were classified as being associated to transient or to prolonged responses42. We find that the genes responsible for transient responses (70 genes) are two times more likely (~14% chances) to be supercoiling sensitive than a gene selected randomly from the genome . Meanwhile, genes responsible for long-term responses to cold-shocks (35 genes42) appear to be impervious to supercoiling (0% chances). The probability that these results would occur by random chance are 1.8% in the case of genes responsible for transient responses, and 8.5% in the case of genes responsible for long-term responses, as estimated from bootstrapped distributions (70 genes each) from 10000 random resamples with replacement using a non-parametric bootstrap method66. We thus conclude that both classes of cold shock-related genes have atypical sensitivity (even though opposite) to supercoiling.To test this, we combined information on E. coli’s mechanisms for sensing and responding to temperature shifts67. A previous study19 using single-molecule mRNA FISH assays to show that, at optimal temperatures, DNA supercoiling buildup eventually halts transcription initiation, which can be resumed upon release of the supercoiling by Gyrase. This buildup only has significant effects in chromosomal genes (in highly expressing operons61), since plasmids lack discrete topological constraints, allowing the negative and positive supercoiling emerging in transcription to diffuse freely in opposite directions, until nullifying one another19.Temperature-driven changes in genomic DNA supercoiling may be one of It is expected that both the time needed for Gyrase to find DNA regions requiring intervention as well as the energy required for this process are temperature-dependent. As such, it may be that the effects of lowering temperature differ both between chromosome-integrated and plasmid-borne genes, as well as between chromosome-integrated genes with different transcription rates.LacO3O1 promoter, under full induction, as a function of temperature . We showed that its response to temperature downshifts differs, depending on whether it is chromosomally-integrated or plasmid-borne. Specifically, the chromosome-integrated gene is more sensitive to critically low temperatures (below 23 °C), becoming weaker and noisier, and having comparatively longer-length steps preceding the open complex formation than the single-copy plasmid-borne gene. In particular, in these conditions, similar to when inhibiting Gyrase or Topoisomerase I, the transcription activity of the chromosomally-integrated gene is hampered, due to increased time to escape from positive supercoiling buildup. Overall, the results suggest that promoters’ in E. coli differ in sensitivity to shifts to critically low temperatures when chromosome-integrated and when plasmid-borne, due to the temperature-dependence of the kinetics of promoter locking due to positive supercoiling buildup. Simulations of a stochastic model of transcription with a temperature-dependent escape from the locked promoter state are consistent with these observations.We studied this phenomenon in the PE. coli62), while cells with locked promoters produced ~0 to 2 RNAs at most.An indirect evidence for the existence of promoter blocking at low temperatures in the chromosome-integrated gene is the high cell-to-cell variability in integer-valued RNA numbers at 10 °C, when compared to the plasmid-borne gene . Also, cells with energy depletion due to DNP treatment exhibit a similar transcription dynamics to when at low temperatures. Finally, subjecting cells to consecutive shifts between high and low temperatures results in smooth transitions in the transcription dynamics, which would not be possible if the population of Gyrases or Topoisomerases I had to be renewed.Importantly, we found evidence that the hampering of escape of PLacO3O1 is enhanced by the known overexpression at low temperatures of H-NS and similar NAP proteins present in the nucleoid, which, in these conditions, appear to selectively inhibit early step(s) in transcription initiation by binding to the promoter and acting as transcriptional repressors69. However, the fast recovery of the kinetics of RNA production under the control of PLacO3O1 observed in Fig. dskA and ppGpp, may prove to be of value to determine whether, e.g., the biophysical phenomena here reported are affected by these mechanisms.We do not know whether the transcriptional halting at low temperatures of the chromosome-integrated P64. The present study indirectly supports this, by showing that the sensitivity of a gene differs with its own transcription rate. In particular, when replacing the promoter (PLacO3O1) controlling the chromosome integrated gene by the native lac, of weaker activity, we observed much weaker effects when lowering temperature. Also, overexpressing Gyrase no longer had an effect, suggesting absence of positive supercoiling buildup. This can be explained by this gene’s longer time intervals between transcription events, which allow Gyrases to act so as to escape from positive supercoiling buildup70 prior to these having a significant impact. Thus, we hypothesize that the effects of temperature downshifts on positive supercoiling buildup are promoter activity dependent.It is well established that the influence of positive supercoiling buildup on a chromosome-integrated gene differs with its location in the chromosome, because this phenomenon is sensitive to the expression rates of the operons of a DNA loop64 and own activity level (among other variables), one can expect genome-wide heterogeneity in the response to temperature downshifts. Thus, it is possible that genes associated to the responses to cold-shocks have atypical sensitivity to positive supercoiling buildup. When investigating this possibility, we found that the number of genes that are responsible for transient responses to cold-shock and also have high-sensitivity to supercoiling buildup is above-expected. Further, the number of genes that are responsible for long-term responses that also have high-sensitivity is below-expected.Since the effects of temperature downshifts differ with the kinetics of positive supercoiling buildup, which itself differs with the gene location in the chromosomeLacO3O1 and native lac). Meanwhile, above average sensitivity to supercoiling is expected to contribute to (or be responsible for) the transient nature of the response exhibited by some genes associated to cold-shock. In particular, for a gene to remain active for ~1 hour42 and then have its activity reduced, there is a need for a mechanism of slow repression, which would be consistent to the ‘repression’ caused by positive supercoiling buildup , it may be possible for temperature shifts to generate heterogeneity in the responses of the component genes, which can be used to trigger changes in the state of the circuit.Overall, our results suggest that it may be possible that the temperature-dependence of the kinetics of promoter locking due to positive supercoiling buildup could be used as a means to introduce temperature sensitivity in some transcriptional programs of E. coli strain BW25993 (lacIq hsdR514 ΔaraBADAH33 ΔrhaBADLD78)71 cells carry the target and reporter genes. The target gene is controlled by PLacO3O1 and codes for an array of 48 binding sites for a modified viral coat protein, MS2-GFP74. PLacO3O1, inducible by IPTG, was engineered from the E. coli native lac promoter, by removing the O2 repressor binding site downstream of the transcription start site65. Due to lacking the site O2, we expect little to no formation of significant topological constraints30. Also, the repression strength of LacI is expected to be 2–3 fold weaker than on the wild-type lac promoter65. Finally, in one measurement, we made use of a chromosome-integrated native lac promoter, also followed by an identical array of binding sites for MS2-GFP.LacO3O1 when single-copy plasmid-borne and when chromosome-integrated, two strains were engineered from the original BW25993. One carries a single copy full F-plasmid (~11 kbp)75, pBELOBAC11 (target plasmid), unknown to form long-lasting bounds to the membrane and originally responsible for the expression of transient DNA-binding proteins77. In this, we inserted the target gene, PLacO3O1, coding for the bindings sites for MS2-GFP  , coding for the reporter protein MS2-GFP controlled by the BAD promoter. The multiple MS2-GFP binding sites in the target RNAs and the strong binding affinity of each site allow target RNAs to appear as bright spots, soon after produced , both strains overexpress LacI, reducing the possibility of significant effects due to shortage of repressors in the strain carrying the F-plasmid. Further, our measurements were conducted under full induction (except the induction curves), further reducing any possibility of effects of differences in number of available repressors.While the strain carrying the target gene in single-copy F-plasmid also contains a native rham-gyrAB, with ampicillin resistance) with the gyrA and gyrB genes under the control of a Rhamnose promoter (Supplementary Section “Gyrase overexpression”).For overexpressing Gyrase, we engineered a plasmid .79 or shortly after80 the chromosome. Further, we measured the plasmid copy numbers by RT-qPCR relative to the number of chromosomes at any given time . The measurements showed that the copy number of the single-copy F-plasmid (pBELO) relative to the chromosome copy number is 1.00 and 1.02 at 10 °C and 30 °C, respectively  , suggesting that these cells with the chromosome integrated promoter only carry two copies of the target gene for a relatively short period of time during their lifetime. The same assumption is applied to the cells carrying the gene of interest in the single-copy F-plasmid. This is because F-plasmids replicate at the same timeely Fig. , validat59. Cells were grown as described in Supplementary Information. Following induction of the reporter gene, cells were incubated at the appropriate temperature (10 °C or 30 °C), at 250 rpm for 15 minutes, prior to induction of the target gene. Afterwards, 1000 μM of IPTG and 100 ng/μl of Novobiocin or 100 μM of Topotecan were added to the cells.We quantified integer-valued RNA numbers in cells with repressed Gyrase activity and with repressed Topoisomerase I activity. For that, we used, respectively, Novobiocin and Topotecan81 the growth and activation of reporter genes were carried out as described above. Next, 1000 μM of IPTG and 200 μM of DNP were added to the media and cells were incubated at 30 °C.To determine RNA levels in cells treated with 2,4-Dinitrophenol (DNP) E. coli RL1314 strain to measure RNA polymerases (RNAP) intracellular concentrations, carrying RNAPs fused with GFP (RNAP-GFP)82. Changes in fluorescence levels   Fig. 70.43. In short, we made use of M9 media differing in Glycerol concentration . Specifically, cells were grown in media with 0.2, 0.4, 0.6 and 0.8% of Glycerol, denoted as 0.5X, 1X (control), 1.5X and 2X, respectively. These conditions allow cells to differ in RNAP concentration while not differing in mean growth rates (assessed from the OD600 over time by a spectrophotometer), as visible in Fig. We performed measurements in cells whose RNAP concentrations differ. To obtain such cells, we employed the method proposed in83 and CellAging85 (example Figs Images acquisition is described in Supplementary Information. It took, on average, ~3 minutes to move cells from the incubator to the microscope, assemble the imaging chamber with slides and cells, and start the observation. Images were then analyzed by the software iCellFusion86, a simulator of chemical reaction systems whose dynamics is driven by the Stochastic Simulation Algorithm87 that allows multi-time-delayed reactions88.Simulations of stochastic models of gene expression were performed by SGNSSupplementary Material


Various strategies have been applied to replace the loss of cardiomyocytes in order to restore reduced cardiac function and prevent the progression of heart disease. Intensive research efforts in the field of cellular reprogramming and cell transplantation may eventually lead to efficient in vivo applications for the treatment of cardiac injuries, representing a novel treatment strategy for regenerative medicine. Modulation of cardiac transcription factor (TF) networks by chemical entities represents another viable option for therapeutic interventions. Comprehensive screening projects have revealed a number of molecular entities acting on molecular pathways highly critical for cellular lineage commitment and differentiation, including compounds targeting Wnt‐ and transforming growth factor beta (TGFβ)‐signaling. Furthermore, previous studies have demonstrated that GATA4 and NKX2‐5 are essential TFs in gene regulation of cardiac development and hypertrophy. For example, both of these TFs are required to fully activate mechanical stretch‐responsive genes such as atrial natriuretic peptide and brain natriuretic peptide (BNP). We have previously reported that the compound 3i‐1000 efficiently inhibited the synergy of the GATA4–NKX2‐5 interaction. Cellular effects of 3i‐1000 have been further characterized in a number of confirmatory in vitro bioassays, including rat cardiac myocytes and animal models of ischemic injury and angiotensin II‐induced pressure overload, suggesting the potential for small molecule‐induced cardioprotection. ANPatrial natriuretic peptideBNPbrain natriuretic peptideChIP‐seqchromatin immunoprecipitation‐sequencingCREPcAMP‐response element binding proteinERKextracellular signal‐regulated kinaseET‐1endothelin‐1GSK‐3βglycogen synthase kinase 3βhiPSChuman‐induced pluripotent stem cellsMAPKmitogen‐activated protein kinaseNMRnuclear magnetic resonancePDBprotein data bankPEphenylephrineSTAT‐1signal transducer and activator of transcription‐1SUMO‐1small ubiquitin‐like modifier‐1TFtranscription factorTGFtransforming growth factor1A network of cardiac transcription factor (TF) controls cardiac gene expression and has a central role in transcriptional regulation during cardiac differentiation and development and the adaptive pathophysiological processes in the adult heart.4) forming the protein domains involving two β‐sheets and one α‐helix. The stable N‐terminal zinc finger of GATA4 is primarily responsible for mediating physical interaction and gene repression via binding to friend of GATA2 protein (FOG2),Arabidopsis thaliana and 64 members in soya beans. Furthermore, a recent study in plants suggests that two important processes during plant development, greening and photosynthesis, as well as stomata formation, and thus, gas exchange, are regulated by plant GATA‐factors.In humans, the evolutionarily conserved GATA‐family of proteins consists of six GATA proteins (GATA1‐6), all sharing similar tertiary protein structures and high amino acid sequence identity over their two DNA binding zinc finger domains. Both N‐terminal‐ and C‐terminal zinc atoms in the GATA family are tetrahedrally coordinated and bound to four cysteine residues  has no globular structure and it remains completely disordered.The GATA4 protein was originally discovered as one of the earliest molecular markers associated with the initiation of cardiac gene expression.On one hand, it appears that total control of GATA4 mRNA levels is not a critical predictor of GATA4 activity in model systems of hypertrophy. Over the course of experiments, mRNA levels of GATA4 remained stable in response to arginine‐8‐vasopressin infusion, nephrectomy in vivo and treatment with endothelin‐1 (ET‐1) in vitro,The adult human heart has insufficient capacity to repair or regenerate cardiac cells after injury when a significant number of cardiomyocytes are lost. Scar formation and failure to regenerate the injured myocardium are the primary causes of the development of heart failure, arrhythmias and sudden death.2.1The function of GATA4 protein is modified by enzymes through post‐translational processes, where one or more functional groups are covalently attached to or detached from the protein. Experimental studies show that post‐translational modifications of GATA4 involve the assignment of acetyl‐, phosphoryl‐, sumo‐, and ubiquitin moieties.The sequence of GATA4 protein conveys seven potential phosphorylation sites that are modified by enzymes, such as glycogen synthase kinase 3β (GSK‐3β), extracellular signal‐regulated kinases (ERK), and p38 mitogen‐activated protein kinase (MAPK), extensively reviewed by Suzuki and Zhou et al. In response to hypertrophic stimuli , activation of the MAPK kinase signalling cascade significantly augments GATA4 phosphorylation and DNA binding efficiency.Histone acetyltransferases such as p300 and cAMP‐response element binding protein (CREP) have been shown to induce the acetylation of specific lysine residues through physically interacting with GATA4.GATA4 has been identified as a target protein for SUMOylation by small ubiquitin‐like modifier‐1 (SUMO‐1) and ubiquitination by the ubiquitin‐proteasome pathway.The study by Aries et al. demonstrated a specific case of the cellular effects of truncated GATA4 protein. Activation of caspase‐1 in cardiomyocytes by doxorubicin led to dominant‐negative GATA4 protein with a reduced ability to activate cardiac genes.2.2cis‐regulatory sequences in gene promoters and enhancers. The tissue‐specific TF GATA4 prefers to bind to the DNA sequence (A/T)GATA(A/G) through its carboxy‐terminal zinc finger and is responsible for mediating site‐specific physical interaction with the DNA sequence. A number of essential cardiac‐expressed genes contain the binding sequence for GATA in their promoter, including atrial natriuretic peptide (ANP),TFs regulate gene expression through coprotein assemblies together with basal transcriptional machinery by binding to specific In the adult heart, whole‐genome chromatin immunoprecipitation‐sequencing (ChIP‐seq) analysis with GATA4 antibody identified only 1,756 GATA4‐bound regions,Chromatin remodeling controls gene expression by modifying the access of regulatory transcription machinery proteins to condensed genomic DNA. This genome‐wide remodeling process occurs via two different mechanisms, either by covalent histone modifications or by moving, ejecting, or restructuring the nucleosomes. Since gene activation is regulated in a multifaceted manner by the interplay of the TF network and the dynamic modifications of the chromatin landscape, as well as by the interference of microRNA (miRNAs), GATA4 chromatin occupancy alone was not directly associated to increased cardiac gene expression levels in fetal or adult heart. However, a number of studies have revealed a high correlation of genome‐wide enrichment of GATA4 binding regions, particularly to acetylated histone H3 at lysine 27 (H3K27ac), a major active transcriptional enhancer marker, together leading to a strong combined effect on gene activation.In human and mouse, there are approximately 2,000 TFs, more than 100 different modifications of histone residues, and approximately 700 miRNAs that modulate the mRNA profiles corresponding to approximately 20,000 genes. The TF complexes that are associated with GATA4 have a comparable dependency on cofactor binding and modulation by histone modifications, as well as on regulation by miRNAs. Therefore, tissue‐specific chromatin co‐occurrence with distinct subsets of TFs are preferred to allow a logical and systematic initiation/repression of transcription. Distinct cardiac TFs, such as NKX2‐5, TBX5, SRF, and MEF2A, in addition to enhancers such as p300, have been shown to localize together with GATA4 at chromatin regions and coregulate cardiac gene expression.3Hereafter, we focus on GATA4 and its association with the interdependent cardiac TF system involving NKX2‐5, MEF2C, HAND2, SRF, and TBX5, which strictly controls the context‐dependent processes of cardiomyocyte development, maturation, and survival  is a cardiac specific homeobox gene family protein with a single helix‐turn‐helix motif responsible for binding to the specific consensus DNA sequence T(C/T)AAGTG. Evolutionarily conserved NKX2‐5 is a critical GATA4 cofactor and has an essential role in cardiac gene expression and normal heart development.Structural and functional data of key cardiac TF complexes are of major importance to enhance the understanding of molecular mechanisms and TF functions. Our previous study with GATA4–NKX2‐5 proteins showed that several single point mutations of GATA4 are capable of interfering or activating the GATA4–NKX2‐5 interaction,4.2N‐[4‐(diethylamino)phenyl]‐5‐methyl‐3‐phenylisoxazole‐4‐carboxamide (IC50 3 μM), and synergy activator compound N‐(4‐chlorophenyl)‐5‐methyl‐N‐‐3‐phenylisoxazole‐4‐carboxamide. The structure–activity relationship of inhibitory compounds demonstrated that ligand affinity associates to the two heavy atom linkers and hydrogen acceptors next to the five‐member ring, while the agonistic effect was achieved by introducing a substituted five‐member ring into the amide bond. The most potent inhibitory and activator compounds were tested in various hypertrophy assays. In cardiomyocyte cultures, the compounds either augmented or inhibited ET‐1‐ and PE‐induced increases in ANP and BNP gene expression, in line with inhibition or activation of the GATA4–NKX2‐5 interaction.Based on the structural and functional data of the GATA4–NKX2‐5 interaction, an extensive chemical screening project was established incorporating computational and experimental biology to uncover compounds acting on key cardiac TFs. Targeting a protein–protein interaction with a small molecule is challenging due to the large surface area involved in protein–protein binding and the lack of clear binding pockets at many protein–protein interfaces. Therefore, the discovery approach consisted of several recurring methods, including GATA4‐NKX2‐5 co‐immunoprecipitation and luciferase reporter assays specifically developed to explore chemical agents possessing either agonistic or antagonistic effects on GATA4–NKX2‐5 transcriptional synergy.In vivo experiments showed that inhibition of GATA4–NKX2‐5 transcriptional synergy has beneficial effects on cardiac function and gene expression in several experimental models of myocardial ischemia and pressure overload.It is also noteworthy to point out other challenges that would come from attempting to disrupt GATA4 activity. Beyond the fact that GATA4 is an essential TF in cardiac cells, it is also expressed and functional in many other tissues, prominent among these the pancreas, liver, and lung. In addition, the targeting should be specific for GATA4 and not interfere with activities of sister genes, particularly GATA5 and GATA6. Therefore, strategies to limit off‐targeting of other organs and other TFs should be developed. One opportunity to limit off‐targeting of other organs would be to develop nanotherapies targeted to the injured region of the myocardium with the potential for spatial and temporal control of drug delivery.5Current therapies for the treatment of myocardial remodeling are shown to attenuate symptoms and prolong lifespan by reducing the workload of the heart, for example, angiotensin converting enzyme inhibitors, angiotensin receptor blockers, beta‐blockers, and mineralocorticoid receptor antagonists. However, prognosis of patients remains poor with present‐day pharmacological treatments. Cell transplantation and virus‐mediated TF delivery therapies aim to replace damaged cells with new functional cardiomyocytes by utilizing hiPSC‐derived cardiomyocytes and stem cell transplantation, and by reprogramming nonmuscle cells towards cardiomyocytes. However, providing therapeutic value with cell transplants and virus‐carried TFs remains a challenge due to poor integration of new cells into the heart and the safety concerns of gene therapy. Modulation of cardiac signaling pathways and TF networks by chemical entities may represent another viable option for therapeutic intervention. Nonimmunogenic and cost‐effective small molecules possess significant advantages of cell permeability and management of standardized industrial production and quality assurance.Our recent results  demonstrate that compounds acting on GATA4‐NKX2‐5 transcriptional synergy can modulate the hypertrophic response in cardiomyocytes in vitro. In addition, we have shown that 3i‐1000, a small molecule inhibitor of GATA4‐NKX2‐5 transcriptional synergy, provides cardioprotective effects in vivo, indicating that modulators of protein–protein interactions of key TFs may present novel pharmaceuticals for cardiac remodeling and repair.M.J.V. and H.J.R. are inventors in a pending patent application “Pharmaceutical compounds” (PCT/FI2017/050661).