Team:Valencia UPV/Modeling/AlaDNA2.0

Valencia UPV iGEM 2015

The decision of biological components of the circuit, was very influenced by the time we had to test them in wet lab experiments. The red switch was extracted from articles that used the pair PIF6-PhyB as a red-far red toggle switch. This construction was supposed to work since experiments in literature were performed in protoplasts.

For the blue switch, the reliable option was using the pair AsLOVpep, that was finally used in wet-lab experiments. However, we considered the possibility of implementing another toggle switch as well as in the other optogenetically controlled part. This action would be provided by Dronpa145N-Dronpa145K, binding to each other with light of 390nm and dissociating with wavelength of 490nm. However, this toggle has not been tested in plants yet, which supposed much more work and putting in risk resources and disposable time.

Fortunately, modeling does not mean any waste of wet-lab resources, and time needed was nothing in comparison to biological experiments!

Dronpa145N-Dronpa145K switch.

This toggle works as a switch that is on with light of 390 nm wavelength. The activation could be implemented in the model by the same expression as in AsLOVpep:

Figure 1. Activation of D (Dronpa145N).

In addition, a reaction of tetramerization occurs with 390nm light irradiation. This means a loss in the amount of D* activator, and our model must contemplate that reaction in order to predict if the efficiency of this alternative circuit could be harmed.

How did we implement the possible tetramerization?

We included in our Matlab model the possibility that VP16 tetramerizes with the light pulse like this:

% dot{Dstar} = kBlue*D*Blue*(1-t4) - dDstar*Dstar

Being t4 the percentage ϵ (0 - 1) of Dronpa145N-VP16 that tetramerizes with the light pulse.

We have done several simulations with t4={0, 0.3, 0.5, 0.8} with the combination Red-Blue in order to obtain beta:

Figure 2. Results of simulating a random beta-sequence with different values of tetramerization percentage.

Tetramerization influence.

We can observe that the quantity of D* decreases with the percentage of t4, this makes sense because they are directly related. The quantity of D divides itself into D* and the tetramer. Apparently, in those graphs we cannot identify a big change in the production of the final products that should be affected by the formation of the tetramer: beta and Omega.

In order to be able to appreciate the influence of the tetramerization in products, we got data from our model of the production of beta and Omega: (We also made the numbers relative, dividing by the first one t4=0, in order to see better the influence)

Values for in t=800 (end of blue pulse)

Figure 3. Different concentrations of beta and Omega vs. tetramerization.

Figure 4. Graphic of relative concentrations vs. percentage of tetramerization.

In this graph it’s clear to see that the leakage values of Omega decrease more rapidly than the values of the product we want (beta). The leakage is more affected by tetramerization than the priority production.

This way we can see that tetramerization could even be a good way of decreasing the leakage for values of t4 around 0,4-0,5. The values are looked in t=800, because it’s the end of the second pulse, the maximum value of beta production.

Red-Far Red, Violet-Cyan toggle switches.

Biological infrastructures which provide this toggle, are actually those that we use in our circuit: PIF6 and PhyB. Here, the novelty would be implemented in the device, which should include a far red light, in order to switch off the toggle after red light irradiation.

If we also considered the blue toggle, then we will have an activation with 390nm light, and switch off with 490 nm

Figure 5. Reactions of red-far red and violet-cyan toggles.

In our model, this would make unnecessary the tagging of B and D. Their disappearance would be achieved by a third input that represents the far red light activation. When this input is activated, the red toggle would be switched off, increasing the grade of AladDNA’s optogenetic control.

function [dxdt] = model_switch_v1(t,x,input_t,input_u1,input_u2,input_u3,input_u4,param)

%Light input signals

Red = interp1(input_t,input_u1,t);

Blue = interp1(input_t,input_u2,t);

Far_Red = interp1(input_t,input_u3,t);

Cyan = interp1(input_t,input_u4,t);

Far_Red variable would be implemented as a product with Red, as well as Cyan with Blue:

% x5 = B* (Activated PhyB-VP16)

dxdt(m+4,1) = param.kRed.*x(m+1).*Red.*Far_Red - param.dBstar.*x(m+4); if ((x(m+4)<=0.0)&& dxdt(m+4,1)<0), dxdt(m+4,1)=0.0; end

%x6 = D* (Activated Dronpa145N-VP16)

dxdt(m+5,1) = param.kBlue.*x(m+3).*Blue.*Cyan.*(1-param.t4) - param.dDstar.*x(m+5); if ((x(m+5)<=0.0)&& dxdt(m+5,1)<0), dxdt(m+5,1)=0.0; end

Its input would be represented similarly to input_red and input_blue, with the difference that if Far Red is ON, then Far_Red=0. Whereas if it is OFF, Far_Red=1. It is comparable to Cyan and Blue light.

input_red =[zeros(length(input_t),1)];

Figure 6. Red input value.

input_blue =[zeros(length(input_t),1)];

Figure 8. Blue input value.

input_far_red =[zeros(length(input_t),1)];

Figure 9. Far red input value.

input_cyan =[zeros(length(input_t),1)];

Figure 10. Cyan input value.