Team:Thessaloniki/Model/iffl
Attenuation iFFL
RNA - based regulation
We studied whether the IFFL network can work at the RNA level with the transcriptional attenuator-activating sRNA regulators who’s function, can efficiently regulate the expression of proteins in different network motifs. Although at the experimental level we could not work on this circuit due to time limitations, we still think it is interesting, and decided to add the modeling structure of IFFL to RNA level for future analysis after the end of the competition.
As mentioned in the design page and based on the literature [1], the Negative Autoregulation network motif was studied using sRNA regulators. This network includes an attenuator, which regulates the transcription of the sRNA repressor and the sfGFP gene reporter. Using differential equations to describe the system, it was proven that this particular network cannot maintain the production of sfGFP over different copy numbers. Nevertheless, the advantages it possesses such as reducing about half of the system response and protein derivation at a lower steady-state level can be used for the IFFL motif after rearrangement of the sequences as described below.
By analyzing the differential equations for the NAR network we would like to highlight the following features: NAR can include one or two tandem repressors in a series. Regarding the paper, it has been shown that a double repressor is one that displays the characteristics of a fast response and tighter repression. The sRNA requires time to mature, represented as a maturation step in the model, in order to be able to interact with the attenuator and repress its expression at the same time as repressing sfGFP. In the NAR network, due to the reason of repressing the production of the sRNA repressor, the production of the reporter gene cannot be dependent on the copy number. Using the same rates by changing the position of the attenuator so as not to affect the transcription of the sRNA, the network motif changes and is expressed as IFFL. Note that cooperativity for binding to sRNA is equal to 1 and the equations enter the probability limit where the RNA polymerase can continue transcription without disruption. The probability is raised in the N + 1 exponent for N number of sequences of the repressor sRNAs arranged.
The result of the differential equations simulations that express the NAR and the IFFL network by using two tandem repressors (N = 2) shows that under the same conditions expressed by the same rates for both networks, the concentration of sfGFP remains constant for our network.
The parameters used are all featured in literature [1]. The diagram above refers to the case where we use two tandem repressors as described in the design of the model. Note that in order to change the number of the repressor, three system parameters change. Changes in parameter values refer to the repressor degradation, the repressor maturation step from R * to R, and the dissociation constant in the hill equation.
Parameters
Parameters are differentiated for a single (first column values) and double repressor (second column values).
| Parameters | Biological meaning | Values | Values | units |
| bR | maximum transcription rate of Repressor | 39.4 | 39.4 | nM/sec |
| bM | maximum transcription rate of sfGFP | 4.9 | 4.9 | nM/sec |
| dR | degradation rate of repressor | 2.1 10-3 | 1.7 10 -3 | 1/sec |
| rm | maturation rate of double repressor | 6.9 10-5 | 7.5 10-5 | 1/sec |
| K | concentration of active Repressor R | 289.5 | 193.6 | nM |
| a | Maturation rate of sfGFP | 1.7 10-2 | 1.7 10-2 | 1/sec |
| kt | translation rate of sfGFP | 2.6 10-4 | 2.6 10-4 | 1/sec |
| dG | degradation of mature sfGFP | 19 10-2 | 19 10-2 | 1/sec |
| p(t) | inefficiency in transcription caused by atennuator | 0.18 | 0.18 | 1/sec |
| dM | Degradation rate of mRNA sfGFP | 5.9 10-4 | 5.9 10-4 | 1/sec |
| N | number of tandem repressors(single or double) | 1 | 2 | - |
In IFFL, the stabilization of the system is demonstrated for both cases with single or double repressor. The choice to use the double repressor is regardless of whether the result obtained in both is a stable sfGFP expression, is the fact that for N = 2 it reaches faster to steady-state and at a lower level of expression than N = 1.
As can be seen from the diagram