Introduction
One of the goal of our project is to visualize the system “bring DNA closer” with the tri-partite GFP.
In a first place, we decide to focus the modeling part on the question “what is the optimal distance between the two dCas9 for fluorescence?”
Our system is divide in 4 parts:
- Two dCas9
- Two linker
- Tri-partite GFP
This question is essential because the distance between the dCas9 may cause major problem: if this system doesn’t work we may not see the effect of the other system. In fact, the 3D structure of our linker may interact with the dCas9 or the GFP because of steric hindrance.
3D Model
The first step of this is the 3D model.
We use the PDB website to find all proteins of our system and use Pymol to assemble all the system.
For this model we have:
- Two identical dCas9 from Streptococcus pyogenese instead of Streptococcus thermophiles and Neisseria meningitidus
- The wild type GFP with the 10th and 11th beta sheet remove
The first limit was the linker. We don’t have any information but is sequence. So we decide to use the software PEP-FOLD for having a 3D simulation.
The prediction was not usable for our model because the results were very improbable.
We decide to build 3 different models: one with a small end to end distance, one with a long distance and one last with the mean between this two values.
We had a first answer: the optimal distance lays between 73 and 110 base pairs.
Ideal Chain an Worm-Like Chain Models
We decide to simulate the end to end distance of our linker with mathematical model. The first was the Ideal Chain model (or freely jointed chain) which is the simplest model to describe polymers by assumes a polymer as a random walk.
For N segments with a length of l we have the contour length which is the total unfolded length:
R is the total end to end vector and it depends on the number of segments and the length of each segments:
The end to end distance is distributed according to this probability density function:
With this model, we lose the information of the spatial arrangement of the repeat units.
If we consider our real chain, the rotation of bonds around the backbone is restricted due to hindered internal rotation and due to excluded-volume effects.
With this consideration, we know that our results are biased.
We decide to continue our mathematical model and we considered the Worm-Like Chain model.
This model is suited for describing semi-flexible polymers. We used the paper Huan-Xiang Zhou (2004): Polymer Models of Protein Stability, Folding, and Interactions to have the probability density function:
With these two models we were able to construct a python program to have the first approximation for the end to end distance of our linker.
We see on this graph that we have two different behaviors and we can’t really develop our models because the information were really short: we just know the end to end distance.
So we decide to code our own model for describing the behavior of our linker. The free jointed model and the worm like chain model give us an idea for the results that we waited.
Modeling
Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.
Inspiration
Here are a few examples from previous teams: