Transcriptional regulation by the numbers: models

Bintu, Lacramioara; Buchler, Nicolas E.; García, Hernán G.; Gerland, Ulrich; Hwa, Terence; Kondev, Jané; Phillips, Rob

doi:10.1016/j.gde.2005.02.007

Cited by 680 publications

(858 citation statements)

References 42 publications

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“…The human COX-2 gene was chosen as its regulation can be through either HIF and/or NF!B activity [4,8,28]. We constructed a thermodynamic model of transcriptional regulation to test the probability of RNA polymerase binding to the promoter as a result of transcription factor recruitment [32] and found that, while HIF and NF!B were acting independently on their respective response elements, there was also a 'greater-than-additive' transcriptional activity under dual stimulation, which would imply synergy. This suggests the capacity for increased recruitment of RNA polymerase arising from the effect of hypoxia on NF!B activity, as shown from our data using the pGluc-NRE construct under cytokine and hypoxic stimulation.…”

Section: Discussionmentioning

confidence: 99%

“…We used a thermo-statistical approach to modelling transcriptional activity as developed in [32,33]. Briefly, we consider the relative concentrations of transcription factors and the probability of these transcription factors binding to the promoter to initiate [33].…”

Section: Thermo-statistical Modelmentioning

confidence: 99%

“…(1) holds only under the assumption of independent activation. A key assumption that has been frequently made in the context of thermo-statistical modelling of the transcriptional machinery is that the rate of transcription initiation is proportional to the binding probability P [32][33][34]. Likewise, the transcription rate of the protein is assumed to be proportional to P. Let r X with X="0", "HIF", "NF!B", and "dual" denote the transcription rates observed in the respective conditions.…”

Section: Thermo-statistical Modelmentioning

confidence: 99%

“…Next, we constructed a thermodynamic model of transcriptional regulation (described in Methods) to test the probability of RNA polymerase binding to the promoter as a result of transcription factor recruitment [32]. According to the model, under independent dual activation, the binding probability equals the product of the binding probabilities observed during individual stimulation [33] (either TNF!…”

Section: Mathematical Model Of Tf Bindingmentioning

confidence: 99%

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NFκB and HIF display synergistic behaviour during hypoxic inflammation

Brüning

Fitzpatrick

Frank

et al. 2011

Cell. Mol. Life Sci.

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The oxygen-sensitive transcription factor Hypoxia Inducible Factor (HIF) is a key regulator of gene expression during adaptation to hypoxia. Crucially, inflamed tissue often displays regions of prominent hypoxia. Recent studies have shown HIF signalling is intricately linked to that of the pro-inflammatory transcription factor Nuclear factor kappa B (NF!B) during hypoxic inflammation. Here we describe the relative temporal contributions of each to hypoxia-induced inflammatory gene expression and investigate the level of crosstalk between the two pathways using a novel Gaussia princeps luciferase (Gluc) reporter system. Under the control of an active promoter, Gluc is expressed and secreted into the cell culture media, where it can be sampled and measured over time. Thus Gluc constructs under the control of either HIF or NF!B were used to resolve their temporal transcriptional dynamics in response to hypoxia and to cytokine stimuli respectively. We also investigated the interactions between HIF and NF!B activities using a construct containing the sequence from the promoter of the inflammatory gene cyclooxygenase 2 (COX-2), which includes functionally active binding sites for both HIF and NF!B. Finally, based on our experimental data, we constructed a mathematical model of the binding affinities of HIF and NF!B to their respective response elements to analyse transcriptional crosstalk. Taken together, these data reveal distinct temporal HIF and NF!B transcriptional activities in response to hypoxic inflammation. Furthermore, we demonstrate synergistic activity between these two transcription factors on the regulation of the COX-2 promoter, implicating a coordinated role for both HIF and NF!B in the expression of COX-2 in hypoxic inflammation.

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Section: Discussionmentioning

confidence: 99%

Section: Thermo-statistical Modelmentioning

confidence: 99%

Section: Thermo-statistical Modelmentioning

confidence: 99%

Section: Mathematical Model Of Tf Bindingmentioning

confidence: 99%

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NFκB and HIF display synergistic behaviour during hypoxic inflammation

Brüning

Fitzpatrick

Frank

et al. 2011

Cell. Mol. Life Sci.

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“…Precise and rich data like those shown in Figure 7A present a variety of theoretical challenges. Thermodynamic models of transcriptional regulation 111,112 have been used to extract the free energy of looping which is a measure of the cost of the looped configuration as a function of the distance between the operators. 102,[113][114][115] These models use equilibrium statistical mechanics to describe the probability of transcription as it is modulated by the presence of the repressor and its partner looped DNA.…”

mentioning

confidence: 99%

Biological consequences of tightly bent DNA: The other life of a macromolecular celebrity

et al. 2006

Self Cite

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The mechanical properties of DNA play a critical role in many biological functions. For example, DNA packing in viruses involves confining the viral genome in a volume (the viral capsid) with dimensions that are comparable to the DNA persistence length. Similarly, eukaryotic DNA is packed in DNA-protein complexes (nucleosomes) in which DNA is tightly bent around protein spools. DNA is also tightly bent by many proteins that regulate transcription, resulting in a variation in gene expression that is amenable to quantitative analysis. In these cases, DNA loops are formed with lengths that are comparable to or smaller than the DNA persistence length. The aim of this review is to describe the physical forces associated with tightly bent DNA in all of these settings and to explore the biological consequences of such bending, as increasingly accessible by single-molecule techniques.

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Spurious transcription factor binding: Non‐functional or genetically redundant?

Spivakov

2014

BioEssays

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Transcription factor binding sites (TFBSs) on the DNA are generally accepted as the key nodes of gene control. However, the multitudes of TFBSs identified in genome-wide studies, some of them seemingly unconstrained in evolution, have prompted the view that in many cases TF binding may serve no biological function. Yet, insights from transcriptional biochemistry, population genetics and functional genomics suggest that rather than segregating into ‘functional’ or ‘non-functional’, TFBS inputs to their target genes may be generally cumulative, with varying degrees of potency and redundancy. As TFBS redundancy can be diminished by mutations and environmental stress, some of the apparently ‘spurious’ sites may turn out to be important for maintaining adequate transcriptional regulation under these conditions. This has significant implications for interpreting the phenotypic effects of TFBS mutations, particularly in the context of genome-wide association studies for complex traits.

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Transcriptional regulation by the numbers: models

Cited by 680 publications

References 42 publications

NFκB and HIF display synergistic behaviour during hypoxic inflammation

NFκB and HIF display synergistic behaviour during hypoxic inflammation

Biological consequences of tightly bent DNA: The other life of a macromolecular celebrity

Spurious transcription factor binding: Non‐functional or genetically redundant?

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