Team:RDFZ-China/Model
Introduction
Our cellular model develops on the characterization on srfA, comA and sfp gene expression pathway as well as trying to predict the final productivity of surfactin over time. The main tool wo used to build our model is Matlab,sponsored by Mathworks. To be more specific, we use Simbiology which is a plugin toolbox that specifically designed for computational system biology. By writing deterministic differential equations of reaction inside the cell, we can easily create the pathway that resemble real-life situations.
The signalling cascade
To start with characterization of our gene pathway, our model has been assumed to act as a standard three-component regulation pathway. This type of modelling is well established in the past(Chen, He and Church.1999)(Ingalls, Brian, 2012)
In our model, we assumed the biochemical reaction take place in sequence as shown below:
- srfA, comA and sfp are transcripedt and translated simultaneously.
- srfA activator,which is coded by comA, helps in transciption of srfA which codes for the synthesis of surfactin synthethase
- PPTase, which is coded by sfp, helps in activation of surfactin synthethase, making it become holo synthethase which will produce surfactin by binding with the amino acids.
Transcription
In real life situation, the transcription rate can be affected by many factors. However we found out through literature research that the major factor would be the initiation of transcription. Therefore we assumed that:
- The overall transcription rate is primarily determined by the strength of the promoter in the pathway
- The promoter strength is constant throught at maximum expression level the whole process
- For constitutive promoter, we assume that the expression level is at the maximum rate for all time
In our final construct, the sfp is under the control of pVEG. According to our literature research, pVEG is 100 times stronger than J23101 which has been characterized in terms of relative units by Berkeley iGEM2006 team. From the database entry we can see that J23101 is 1791 times stronger than promoter J23112 which has a value of 1. Therefore our promoter, pVeg, would be 1791*100 times stronger than J23112. Now, J23101 has been previously characterized by Kelly et al. 2009, whoe found that it has a value of 0.03PoPS(polymerase per second). Therefore, by multiplying 0.03PoPS with 100, we can get 3.00PoPS for the strength of pVEG. Finally, we conclude that sfp, under the control of pVEG, has a constitutive ranscription rate of 3.00PoPS per molecule of DNA construct, and this can be translated to
