Promoter Activity

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Promoter activity of the P-RM and P-R promoters vs RNA polymerase concentration in the enterobacteriophage lamda[1]

The promoter activity is a term that encompasses several meanings around the process of gene expression from regulatory sequences —promoters and enhancers[2]. Gene expression has been commonly characterized as a measure of how much, how fast, when and where this process happens[3]. Promoters and enhancers are required for controlling where and when an specific genes is transcribed[2].

Traditionally the measure of gene products (i.e. mRNA, proteins, etc) has been the major approach of measure promoter activity. However, this method confront with two issues: the stochastic nature of the gene expression[4] and the lack of mechanistic interpretation of the thermodynamical process involve in the promoter activation[3].

The actual developments in metabolomics as result of the developments of next-generation sequencing technologies and molecular structural analysis have enable the development of more accurate models of the process of promoter activation (e.g. the sigma structure of the polymerase holoenzyme domains[5]) and a better understanding of the complexities of the regulatory factors involved.

Promoter Binding

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The process of binding is central in determining the "strength" of promoters, that it is a relative estimation of how "well" a promoter perform the expression of a gene under specific circumstances. Brewster et al[6], using a simple thermodynamical based in the postulates that transcriptional activity is proportional to the probability of finding the RNA polymerase bound at the promoter, obtained predictions of the scaling of the RNA polymerase binding energy. This models support the relationship between the probability of binding and the output of gene expression[6]

 
Probability of binding for the T7 (green) and Lac Ecoli (blue) promoters by RNA polymerase concentrations.

Mathematical representation of promoter binding

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The problem of gene regulation could be represented mathematically as the probability of n molecules   — RNAP, activators, repressors and inducers  — are bound the a targeted regions[3].

The approach is based in statistical thermodynamics of two possible microscopic outcomes[3]:

  1. one state where all P polymerases molecules are distributed among all the non-specific sites (sites not participating in gene expression)
  2. a promoter occupied and the remaining P-1 polymerases distributed among the non-specific sites.

The statistical weigh of promoter unoccupied Z(P) is defined:

 

Where the first term is the combinatorial result of taken P polymerase of Nns non-specific sites available, and the second term are the boltzmann weights, where   is the energy that represents the average binding energy of RNA polymerase to the genomic background (non-specific sites).

Then, the total statistical weight Z(Ptotal), can be written as:

 

Where   is  the binding energy forRNA polymerase on the promoter (where the s stands for specific site).

To find the probability of a RNA polymerase to binding (  ) to an specific promoter we divide   by   which produces:

 

Where,  

An important result of this model is that any transcription factor, regulator or perturbation could be introduced as a term multiplying the P in the denominator the probability of binding equation.

Eukaryotes Promoter structure

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Core Promoter elemets

The process of activation and binding in eukaryotes is different from bacteria in the way that specific DNA elements bind the factors for a functional pre-initiation complex. In bacteria there is a single polymerase, that contain catalytic subunits and a single regulatory subunits known as sigma, which transcribe for different type of genes[7].

In eukaryotes, the transcription is performed by three different RNA polymerase, RNA pol I for ribosomal RNAs (rRNAs), RNA polymerase II for messenger RNAs (mRNAs) and some small regulatory RNAs, and the RNA polymeerase III for small RNAs such as transfer RNAs (tRNAs). The process of positioning of the RNA polymerase II and the transcriptional machinery require the recognition of a region know as "core promoter"[7]. The elements that could be found in the core promoter include the TATA element, the TFIIB recognition element (BRE), the initiatior (Inr), and the downstream core promoter element (DPE)[8]. Promoters in eukaryotes contain one or more of these core promotes elements (but any of them are absolutely essential for promoter function)[7], these elements are binding sites for subunits of the transcriptional machinery and are involve in the initiation of the transcription, but also they have some specific enhancer functions[8]. In addition, the promoter activity in eukaryotes include some complexities in the way of how they integrate signals from distal factors with the core promoter [9].

Evolutionary processes

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Unlike in protein coding regions, where the the assumption of sequence conservation of functionally homologous genes have been frequently proved, there is no a clear relationship of conservation between sequences and their functions for regulatory regions[10]. The transcriptional promoters regions are under less stringent selection, then have a higher substitutions rates, allowing transcription factor binding sites to be replaced easily be new ones arising from random mutations[10]. Notwithstanding the sequence changes, mainly the functions of regulatory sequences remain conserved[10].

In recents years with the increase of availability of genome sequences, phylogenetic footprining open the possibitlity to identify cis-elements, and then study their evolution processes. In this sense, Raijman et al[11], Dermitzakis et al[12] have developed techniques for analyzing evolutionary processes in transcription factor regions in Saccharomyces species promoters and mammalian regualatory networks respectively.

The basis for many of these evolutionary changes in nature are probably related with events within the cis-regulatory regions involve in gene expression[13] . The impact of variation in regulatory regions is important for desease risk[12] due their impact in the gene expression level. Furthermore, perturbations in the binding properties of proteins encoded by regulatory genes have been linked with phenotypes effects such as, duplicated structures, homeotic transformations and novel morphologies[13].

Measure of promoter activity

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The measure of the promoter activity has a broad meaning. The promoter activity could be measured for different situations or research questions, such as[3]:

  • estimation of the level of expression in comparison (relative) to some know value
  • how fast a gene is expressed after induction
  • the timing of expression relative to others genes
  • the specific spatial location of expression

Methods to study promoter activity commonly are based in the expression of a reporter gene from the promoter of the gene of interest[14]. Mutations and deletions are made in a promoter region, and their changes on couple expression of the reporter gene are measured[15].

The most important reporter genes are the fluorescence proteins as GFP. These reporters allow to measure promoter activation by increasing fluorescent signals, and deactivation by decrease in the rate of fluorescence[16].

See also

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References

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  1. ^ Shea, M; Akers, G (1985). "The 0, Control System of Bacteriophage Lambda A Physical-Chemical Model for Gene Regulation". Journal of Molecular Biology. 181: 211–230. {{cite journal}}: line feed character in |title= at position 46 (help)
  2. ^ a b Gilbert, S.F. (2000). Developmental Biology. http://www.ncbi.nlm.nih.gov/books/NBK10023/: Sinauer Associates. {{cite book}}: External link in |location= (help)CS1 maint: location (link)
  3. ^ a b c d e Bintu, L.; Buchler, N; Garcia, H; Gerland, U; Hwa, T; Kondev, J; Phillips, R (2005). "Transcriptional regulation by the numbers: models". Current Opinion in Genetics & Development. 15: 116–124.
  4. ^ Elowitz, M; Levine, A.J.; Siggia, E.; Swain, P. (2002). "Stochastic Gene Expression in a Single Cell". Science. 297: 1183-1186.
  5. ^ Borukhov, S.; Nudlery, E (2003). "RNA polymerase holoenzyme: structure, function and biological implications". Current Opinion in Microbiology. 6: 93-100. {{cite journal}}: line feed character in |title= at position 51 (help)
  6. ^ a b Brewster, R.; Jones, D.; Phillips, R. (2012). "Tuning Promoter Strength through RNA Polymerase Binding Site Design in Escherichia coli". PLOS Computational Biology. 8 (12): 1–10. doi:10.1371/journal.pcbi.1002811.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  7. ^ a b c Hahn, S. (2004). "Structure and mechanism of the RNA polymerase II transcription machinery". Nature Structural and Molecular Biology. 11: 394–403.
  8. ^ a b Butler, J.; Kodonaga, J. (2015). "The RNA polymerase II core promoter: a key component in the regulation of gene expression". Genes and Development. 16: 2583–2592.
  9. ^ Smale, S.; Kadonaga, T. (2003). "The RNA Polymerase II Core Promoter". Ann. Review in Biochemistry. 79: 449–479.
  10. ^ a b c Huang, W.; Nevins, J.; Ohler, U. (2007). "Phylogenetic simulation of promoter evolution: estimation and modeling of binding site turnover events and assessment of their impact on alignment tools". Genome Biology. 8 (10). {{cite journal}}: line feed character in |title= at position 62 (help)
  11. ^ Raijman, D.; Shamir, R.; Tanay, A. (2008). "Evolution and Selection in Yeast Promoters: Analyzing the Combined Effect of Diverse Transcription Factor Binding Sites". PLOS Computational Biology. 4 (1): e7. doi:10.1371/journal.pcbi.0040007.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  12. ^ a b Dermitzakis, E.; Clark, A. (2002). "Evolution of Transcription Factor Binding Sites in Mammalian Gene Regulatory Regions: Conservation and Turnover". Molecular Biology Evolution. 19 (7): 1114–1121.
  13. ^ a b Stone, J.; Wray, G.A. (2001). "Rapid Evolution of cis-Regulatory Sequences via local Point Mutations". Molecular Biology Evolution. 18 (9): 1754–1770.
  14. ^ Jeyaseelan, K.; Ma, D.; Armugan, A. (2001). "Real-time detection of gene promoter activity: quantitation of toxin gene transcription". Nucleic Acid Research. 29 (12).
  15. ^ ALLARD, S.T.; KOPISH, K. (2008). "LUCIFERASE REPORTER ASSAYS: POWERFUL, ADAPTABLE TOOLS FOR CELL BIOLOGY RESEARCH". Cell Notes (21).
  16. ^ Zaslaver, A.; Bren, A.; Ronen, M.; Itzkoviz, S.; Kikoin, I.; Shavit, S.; Leibesmeister, W.; Surette, M.; Alon, U. (2006). "A comprehensive library of fluorescent transcriptional reporters for Escherichia Coli". Nature Methods. 3 (8): 623–628.


Category:Gene expression Category:Evolutionary biology