Modulation of protein-DNA binding reveals mechanisms of spatiotemporal gene control in early Drosophila embryos
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eLife assessment
This valuable work explores how transcription factors regulate transcription through cooperative binding to enhancers. Through experiments and modeling, the authors show convincingly that the cooperativity of transcription factor binding regulates transcriptional bursting and the extent of the amount of time that the target promoter remains in an active state.
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Abstract
It is well known that enhancers regulate the spatiotemporal expression of their target genes by recruiting transcription factors (TFs) to the cognate binding sites in the region. However, the role of multiple binding sites for the same TFs and their specific spatial arrangement in determining the overall competency of the enhancer has yet to be fully understood. In this study, we utilized the MS2-MCP live imaging technique to quantitatively analyze the regulatory logic of the snail distal enhancer in early Drosophila embryos. Through systematic modulation of Dorsal and Twist binding motifs in this enhancer, we found that a mutation in any one of these binding sites causes a drastic reduction in transcriptional amplitude, resulting in a reduction in mRNA production of the target gene. We provide evidence of synergy, such that multiple binding sites with moderate affinities cooperatively recruit more TFs to drive stronger transcriptional activity than a single site. Moreover, a Hidden Markov-based stochastic model of transcription reveals that embryos with mutated binding sites have a higher probability of returning to the inactive promoter state. We propose that TF-DNA binding regulates spatial and temporal gene expression and drives robust pattern formation by modulating transcriptional kinetics and tuning bursting rates.
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Author Response
Reviewer #2 (Public Review):
The work is very clearly designed, executed, and written. The transcription output data is rigorous and well quantified, and the fit of the TF binding model clearly shows agreement with experiments in the case of cooperativity, but not in its absence, making a strong case for the authors' conclusion.
How the Hidden Markov Model fit results (promoter kon and koff values) lead to the observed effects on transcription output is less clear. For instance, Dl1 deletion results in a small increase in kon and a moderate increase in koff, which seems at odds with the other variants. Yet all variants exhibit similar transcription output profiles. One other intriguing observation is that the promoter states in Fig. 4C&D do not look dramatically different in their kinetics, yet the input …
Author Response
Reviewer #2 (Public Review):
The work is very clearly designed, executed, and written. The transcription output data is rigorous and well quantified, and the fit of the TF binding model clearly shows agreement with experiments in the case of cooperativity, but not in its absence, making a strong case for the authors' conclusion.
How the Hidden Markov Model fit results (promoter kon and koff values) lead to the observed effects on transcription output is less clear. For instance, Dl1 deletion results in a small increase in kon and a moderate increase in koff, which seems at odds with the other variants. Yet all variants exhibit similar transcription output profiles. One other intriguing observation is that the promoter states in Fig. 4C&D do not look dramatically different in their kinetics, yet the input transcription traces exhibit a 3-fold amplitude difference. Maybe the authors can clarify these apparent discrepancies.
We thank the reviewer for insightful comments. The reduction in transcription output is mainly due to the decrease in transcription amplitude. We have done further analysis to demonstrate that the loading rate of Pol II, correlated to the initial slope of transcription, is significantly reduced in the mutants. We measured the initiation rate by calculating the slope of the MS2 traces and correlated it to the Pol II loading rate. As expected, the initiation rate in wildtype is higher than in mutant embryos. This additional analysis suggests that the drastic reduction in transcriptional amplitude is due to the reduced Pol II loading rate, not kon, and corroborates the previously shown results and conclusions (Bothma et al., PNAS 2014, PMID: 24994903; Garcia et al., Curr. Biol. 2013, PMID: 24139738). We have added this plot in Figure 4H in the revised manuscript, which shows the initiation rates of the wildtype and mutant embryos, and revised the manuscript as follows.
We have added this in the Introduction (Page 4):
We find that mutating a single TF (Dl or Twi) binding site in the enhancer significantly reduces mRNA production of the target gene, mainly through lowering transcriptional amplitude by reducing RNA polymerase (Pol) II loading rate, without significantly delaying the timing of initiation or affecting the probability of activation.
We have added this in the Results (Page 15):
Previously, we demonstrated that the mutations affect mRNA production through transcriptional amplitude (Figure 2E). This could be because either the mutations hinder the Pol II loading rate or reduce the time the promoter is in the ON state….
In addition, we find that the Pol II loading rate is significantly reduced in the mutant embryos compared to the wildtype (Figure 4H). This confirms that the lower transcriptional amplitude mainly results from the promoter’s inability to effectively load Pol II, along with an additional contribution from the reduced time the promoter spends in the ON state.
We have added this in the Discussion (Page 16):
This reduction is mainly due to the decreased transcriptional amplitude, driven by a lower rate of Pol II loading… and, Since the amount of time the promoter spends in the ON state is not affected by the mutations, the lower transcriptional amplitude can be mainly attributed to the promoter’s inability to effectively load Pol II (Figure 2E, Figure 4D-F).
The HMM is utilized to tease apart the changes in transcriptional kinetics. Our analysis revealed that the HMM provides some explanation for the reduction in transcriptional output in TF binding site mutants. For this reason, we must examine the results in a broader context. As pointed out, Dl1 site deletion has a slightly different effect on kon and koff. However, its transcription output is similar to the other mutants (Figure 4D and E). This is due to the fact that the changes in kon and koff are significantly less drastic than the changes in the transcription amplitude and Pol II loading rates, contributing less to the mRNA production. In our analysis, the amplitude is a separate parameter than the kon and koff rates, which are calculated from the HMM.
We have added the following in the Discussion to address this concern (Page 17):
However, we note that the HMM only provides some explanation for the reduction in transcriptional activity since the changes in kon and koff are less drastic than the changes in transcriptional output. Since the amount of time the promoter spends in the ON state is not affected by the mutations, the lower transcriptional amplitude can be mainly attributed to the promoter’s inability to effectively load Pol II (Figure 2E, Figure 4D, H).
The authors observe cooperativity between TF binding sites and transcription output, which their model suggests is driven by TF binding cooperativity ("We propose that the cooperativity allows TF binding sites with moderate or weak affinities to recruit more TFs to the enhancer"). This is plausible and likely, but not rigorously demonstrated; another possibility could be cooperativity at the step of transcription activation. One could verify that the binding step is the cooperative one via ChIP-qPCR in the different variants, but given the cautious wording of the paper, this is not absolutely necessary.
We thank the reviewer for suggesting this experiment. Unfortunately, due to the experimental design, performing ChIP-qPCR was not feasible. There are two copies of snaSEmin enhancer region, one within the endogenous genome and the one within the transgene. For this reason, proper amplification in qPCR was challenging as the primers would recognize two distinct portions of the genome. We designed primers such that the forward primer would recognize both the endogenous and transgene enhancer region (inevitable) and the reverse primer would recognize only the transgene. Yet, we did not observe the expected fold change in amplification as the concentration of DNA was modulated. Hence, we did not proceed to perform ChIPqPCR.
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eLife assessment
This valuable work explores how transcription factors regulate transcription through cooperative binding to enhancers. Through experiments and modeling, the authors show convincingly that the cooperativity of transcription factor binding regulates transcriptional bursting and the extent of the amount of time that the target promoter remains in an active state.
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Reviewer #1 (Public Review):
In this work, the authors were aiming to probe why enhancers tend to have multiple binding sites for the same transcription factor (TF). As a test bed, they use the snail distal enhancer, which drives a band of expression in the early Drosophila embryo and is composed of multiple, generally weak binding sites for several activating TFs. Using the MS2-MCP reporter system, the authors characterize the live mRNA dynamics driven by the wild-type and mutant enhancers, in which individual or pairs of binding sites have been deleted. They complement these experimental measurements with two computational models - a simple thermodynamic model to explore the cooperativity of TF binding to enhancers and a Hidden Markov Model to analyze the kinetic parameters of their dynamic measurements. The key finding from the …
Reviewer #1 (Public Review):
In this work, the authors were aiming to probe why enhancers tend to have multiple binding sites for the same transcription factor (TF). As a test bed, they use the snail distal enhancer, which drives a band of expression in the early Drosophila embryo and is composed of multiple, generally weak binding sites for several activating TFs. Using the MS2-MCP reporter system, the authors characterize the live mRNA dynamics driven by the wild-type and mutant enhancers, in which individual or pairs of binding sites have been deleted. They complement these experimental measurements with two computational models - a simple thermodynamic model to explore the cooperativity of TF binding to enhancers and a Hidden Markov Model to analyze the kinetic parameters of their dynamic measurements. The key finding from the experiments is that ablating any of several TF binding sites individually or in pairs dramatically reduces the expression levels, though not the spatial extent, of the snail distal enhancer. This effect holds true in a ~600 bp minimal enhancer and a ~1800 bp extended enhancer. The bulk of this effect is due to a marked decrease in transcriptional amplitude. A simple thermodynamic model confirms the intuition that synergy between the TF binding sites can explain the experimental results and further analysis shows that the modest decline in transcriptional burst duration in mutant enhancers is likely due to more frequent dissociation of the enhancer-promoter complex.
The paper's strengths include the use of well-established measurement and analysis techniques to uncover the surprisingly dramatic effect of single TF binding site mutations, even in the extended enhancer which contains ~20 TF binding sites. This work starts to chip away at the question of why multiple TF binding sites are so frequently observed in enhancers and complement studies of other similar enhancers. It is likely to be of interest to the enhancer biology community. It also sets the stage to explore whether this observation will generalize to other enhancers with different properties, e.g. those with stronger TF binding sites or whose activity is more strongly shaped by repressive TFs.
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Reviewer #2 (Public Review):
The work is very clearly designed, executed, and written. The transcription output data is rigorous and well quantified, and the fit of the TF binding model clearly shows agreement with experiments in the case of cooperativity, but not in its absence, making a strong case for the authors' conclusion.
How the Hidden Markov Model fit results (promoter kon and koff values) lead to the observed effects on transcription output is less clear. For instance, Dl1 deletion results in a small increase in kon and a moderate increase in koff, which seems at odds with the other variants. Yet all variants exhibit similar transcription output profiles. One other intriguing observation is that the promoter states in Fig. 4C&D do not look dramatically different in their kinetics, yet the input transcription traces exhibit a …
Reviewer #2 (Public Review):
The work is very clearly designed, executed, and written. The transcription output data is rigorous and well quantified, and the fit of the TF binding model clearly shows agreement with experiments in the case of cooperativity, but not in its absence, making a strong case for the authors' conclusion.
How the Hidden Markov Model fit results (promoter kon and koff values) lead to the observed effects on transcription output is less clear. For instance, Dl1 deletion results in a small increase in kon and a moderate increase in koff, which seems at odds with the other variants. Yet all variants exhibit similar transcription output profiles. One other intriguing observation is that the promoter states in Fig. 4C&D do not look dramatically different in their kinetics, yet the input transcription traces exhibit a 3-fold amplitude difference. Maybe the authors can clarify these apparent discrepancies.
The authors observe cooperativity between TF binding sites and transcription output, which their model suggests is driven by TF binding cooperativity ("We propose that the cooperativity allows TF binding sites with moderate or weak affinities to recruit more TFs to the enhancer"). This is plausible and likely, but not rigorously demonstrated; another possibility could be cooperativity at the step of transcription activation. One could verify that the binding step is the cooperative one via ChIP-qPCR in the different variants, but given the cautious wording of the paper, this is not absolutely necessary.
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