Team:UANL Mty-Mexico/Modeling

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<p>Aside from the common objection that they are not suitable to describe systems that show a low number of particles, we believe that a deterministc model at a molecular level of these kind of systems and the degree of certainty with which they can be used for inter-system comparison or usage, do not outweigh the costs of the experimental determination of parameters.</p>
<p>Aside from the common objection that they are not suitable to describe systems that show a low number of particles, we believe that a deterministc model at a molecular level of these kind of systems and the degree of certainty with which they can be used for inter-system comparison or usage, do not outweigh the costs of the experimental determination of parameters.</p>
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<p>Here we propose a model for the description and comparison of the behavior of the effect of RNA thermometers or RNATs on the expression of a reporter protein. The model is tested with relative fluoroscence units data; an extension for protein concentration units is also proposed and waits for experimental validation.</p></div>
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<p>Here we propose a model for the description and comparison of the behavior of the effect of RNA thermometers or RNATs on the expression of a reporter protein. The model is tested with relative fluoroscence units data, which should be enough for inter-system comparisons, i.e., to compare the temperature-dependent gene regulation features of different RNATs; an extension for protein concentration units is also proposed and waits for experimental validation.</p></div>
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Revision as of 21:42, 7 September 2013

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Mathematical models that represent the dynamic behavior of biological systems are a quite prolific field of work and are pilar for Systems Biology. A number of deterministic and stochastic formalisms have been developed at different abstraction levels that range from the molecular to the population levels.

In principle, a model that is simple but that englobes enough information to describe and make predictions, with a degree of certainty, about the phenomenon under scrutiny, would be desirable.

Deterministic mathematical models that describe the behavior of genetic circuits and the interactions of the proteins they encode are usually built upon mass action kinetics and Hill equations.

Aside from the common objection that they are not suitable to describe systems that show a low number of particles, we believe that a deterministc model at a molecular level of these kind of systems and the degree of certainty with which they can be used for inter-system comparison or usage, do not outweigh the costs of the experimental determination of parameters.

Here we propose a model for the description and comparison of the behavior of the effect of RNA thermometers or RNATs on the expression of a reporter protein. The model is tested with relative fluoroscence units data, which should be enough for inter-system comparisons, i.e., to compare the temperature-dependent gene regulation features of different RNATs; an extension for protein concentration units is also proposed and waits for experimental validation.

After considering the effect of their metallothioneins (As-binding proteins), GlpF, ArsB and ArsR, they ended with the following time derivative:


\begin{equation} \large\frac{\mathrm{d[As(III)in] } }{\mathrm{d} x} = -ArsR_{As}-MBPArsR_{As} -n_{f}\cdot fMT_{As} -k_{1} ArsB_{As} + \frac{k_{2}V_{s}GlpF_{As}}{V_{c}} \end{equation}


RNA thermometers (RNATs) are RNA sequences that range from 40 to more than a 100 nucleotides commonly found in the 5' untranslated region of some genes and that regulate in cis their translation without the need of other factors [Kortmann and Narberhaus, (2012); Narberhaus, (2009)]. These RNAT sequences show certain three dimensional structures, some of which interact with the ribosome binding site (RBS) of their regulated genes and hinders the proccessivity of the ribosome complex at certain temperatures. The dynamics of the formation of these structures is temperature dependent and is the basis of the regulation of the translation rate of a given transcript [Chowdhury, S., et al.,(2006); Narberhaus, F., et al.,(2006)].

Functional RNAT have been found in different organisms, mainly pathogenic bacteria, and many others have been predicted in almost everyfrom a number of bioinformatic studies. They have been found to regulate the expression of virulence factors, heat and cold shock response factors and even proteins involved the development of some bacteriophages.

Their apparent widespread presence in living organisms has made RNATs attractive for some applications, specially the ones related to the replacement of chemical inducers and for the development of new drugs.

However, from the experience of those who have been working extensively with RNAT in the later years, the accurate bioinformatic prediction of functional RNAT has proven to be an exceptionally difficult task; the reasons for this are pointed to be the poor sequence conservation observed among RNATs and the gaps in our current understanding of the RNAT function, their structural diversity and the effect of other regulatory sequences far from the RBS region [Kortmann and Narberhaus, (2012); Waldminghaus, et al., (2007)].

The discovery of new RNATs has relied on a mixed approach that involves bioinformatics and experimental validation, as well as approaches that involve mutational libraries, synthetic constructions and directed evolution.

Even when the naturally found RNATs usually regulate the expression of transcription factors, the synthetic constructions made so far have focused mainly to characterize the effect of a given RNAT using a reporter protein (LacZ or a fluorescent protein) directly downstream of a RNAT. In our work, we intend to prove that RNATs can also be employed to effectively regulate the expression of transcription factors in synthetic circuits and point at possible applications for the circuit topologies that would be made feasible with this new kind of synthetic regulatory device.

Although RNATs show almost no sequence similarity among them, a number of structural features can be used to classify them. Here we enlist the most described RNATs structural groups described to date [Kortmann and Narberhaus, (2012)]:

  1. ROSE.- ROSE stands for "Regulation Of heat Shock Expression". ROSE elements are 60 to >100 nucleotide sequences found upstream of heat shock proteins. They have been found to be conserved in alpha and gamma-proteobacteria. Among the structural features of the ROSE element family are: a) their folding in 2 to 4 stemloop structures; b) a short conserved sequence (UU/CGCU) near the Shine-Dalgarno sequence; and c) the presence of a number of non-cannonical base interactions (the G83-G94 pair; a triple bair among U96-C80-C81; the U79-U97; and the interaction of the AUG codon and C71, G72 and U73. Functional ROSE elements have been found in E. coli (rpoH and ibpA) and B. japonicum (hspA).

  2. FourU elements.- these elements are characterized by a short motif composed of four uridines that pair with the Shine-Dalgarno region and is embedded in a hairpin that shows temperature-induced conformational changes. FourU elements have only one A-G non-cannonical base interaction. Among the structural features that characterize FourU elements are a) the A-G pair and b) the G34-C46 pair that regulates melting. Functional FourU elements have been described in Salmonella (agsA) and Yersina pseudotuberculosis (lcrF).

  3. Synechocystis hsp17 element.- with a length of 46 nucleotides, this is the shortest RNAT described so far. The distinctive structural features essential for the function of this element are a) the pairing of a UCCU sequence with the AGGA in the Shine-Dalgarno sequence and b) the presence of two loops in its stems.

  4. Coding region spanning RNATs.- RNATs are not exclusively found in the 5'UTR of genes; they can also span into the coding region and even be intergenic. Functional coding region spanning RNATs have been found in E. coli (rpoH), phage lambda (cIII) and Lysteria monocytogenes (prfA).

  5. Cold shock RNATs.- cold shock RNATs also depend on the dynamics of the folding of different loops, but in contrast to heat shock RNATs, the conformation that prevents the binding of the ribosome is found at high temperatures, while at low temperatures, the RNAT folds into a conformation that allows for the ribosome to proceed. An example of a cold shock RNAT is the element found upstream and inside the coding region of E. coli gene cspA.