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Team:Warsaw/Stage1/Modeling
From 2010.igem.org
Modeling
The RBS strength depends on RNA secondary structure. We were not sure if it is correct to assume that RBS, that is strong with GFP would be strong with other genes. One way to check it would be to investigate it experimentally - a brilliant but time consuming idea. Modeling has been developed to save biologist time, not it is time to explore its power.
1. First we discovered that suitable software has been very recently created. We are lucky this year.
2. Then we compared the software's prediction against our measurements - to find out if it gives reliable results.
3. Later we in silico measured strength of different RBS parts in various genetic set up - with different reporter genes.
People used to design computational programs that would automaticall locate bacterialribosome binding sittes, various techniques were used[] including neural networks[]. However the software was capable only of finding the sequence and didn't give any information about the strength of RBS. In 2009 Nature issue the revolutionary software has been described[]. RBS calculator allows prediction of RBS strength,
moreover it designs RBS of desired strength for specific gene sequence. In 2010 another RBS strength predictor was created[].
A mathematical mofdel for transcription initiation has been clearly describrd by ___ in 2010. Upon similare models are based the current predictors. Model contains lots of mathematics but it is based on biological common sense:
We all know that for transcription initiation the ribosome has to be recruted to the RNA.
First there must be accesible RNA molecue
Then the ribosome must
The
There are some events that has not been included in this model e.g.
We have evaluated the accuracy of the RBS calculator by comparing it to our measurements and the registry data from the registry. We prepared the in silico constructs comprasing of biobrick scar, RBS.E0040.B0015 to reflect the mRNA that was used in wet lab experiments. Then we made RBS strength predictions and expressed them as a percent of predicted B0034 strength. Below you can see that the results are more or less in agreement with wet lab measurements. However the program has its limitations. Each result returned by the program has a parameter that says how reliable the prediction is. For J61117 abd J61127 we didn't obtain reliable predictions and results were extreamly different from measured strength.
We decided to use only reliable predictions, that were confirmed by wet lab measurements in experiment 2
Fig 1.
Fig 2.
