Team:Manchester-Graz/Modeling
Modeling
Modeling a multidimensional expression system using quorum sensing
Figure 1 Schematic representation of our quorum sensing based regulatory system.
The system consists of two quorum sensing (QS) systems EsaR/I and CepR/I. The EsaR/I system belongs to the plant pathogen Pantoea stewartii (1). Contrary to common QS-systems EsaR/I uses a repressor based rather than an activator-based system. EsaR, the repressor, binds to its corresponding binding sites on the PesaRC promoter and represses the expression of the genes under the promoter’s control (2,3). When a certain concentration of 3-oxohexanoyl-homoserinelactone (3OC6-HSL) that is produced by the EsaI-synthase, is reached, it leads to an allosteric conformation change in EsaR’s structure that inhibits its repressor function. When positioned in the -60 region of the PesaS-promoter EsaR can also work as an activator, by facilitating RNA-polymerase recruitment (2).
The second QS-System we are using, CepR/I, belongs to the opportunistic pathogen Burkholderia cenocepacia. Similar to the LuxR/I system, CepR acts as an activator of its corresponding promoter, PaidA, when a certain level of octanoyl-homoserinelactone (C8-HSL) is reached (4). C8-HSL is produced by CepI. CepR also binds 3OC6-HSL, however will not work as an activator, as the additional two carbon-atoms are mandatory, for CepR’s RNA-Polymerase-recruiting ability (4). This way CepR works as a competitive binding site for 3OC6-HSL, that putatively allows us to reach higher cell densities and thus higher 3OC6-HSL concentration before the EsaR/I expression system gets activated.
Our system is designed in a way that EsaR, EsaI and CepR are constitutively expressed by the same promoter. As long as the 3OC6-HSL concentration is low enough, EsaR will additionally increase its own transcription, creating a positive feedback loop. When the 3OC6-HSL threshold is reached, transcription of the PesaRC initiates, while the PesaS-feedback loop is turned off. The activation of the promoter is shown and measured on the expression of cyan fluorescent protein (CFP). Additionally to the reporter gene also CepI gets expressed, resulting in the time-shifted activation of our second QS-system. When the C8-HSL threshold is reached, CepR can work as an activator of the PaidA promoter that transcribes monomer red fluorescent protein (mRFP) as a second reporter gene.
The Model
While planning our project we decided to model the system with Matlab to see what we expect to get. Modeling provides also a way to test if the system works as we planned it.
The quorum sensing system model was done using Matlab and Simbiology. The genetic setup was modeled graphically and parameters were taken from literature or estimated.
Figure 1 Diagram view of the system in Simbiology
The modeling was started on the DNA-basis. CepI, CepR, EsaR and EsaI are expressed constitutively and transcribed into mRNA which gets translated to Protein. The expression of EsaI, EsaR and CepR gets induced further by EsaR. The genetic setup is designed to by in a compartment called cell surrounded by a second compartment environment. The homoserinelactons are transported through the cell membrane into the environment due to diffusion. The diffusion into the environment and back are influenced by the size of the cell.
Cell growth and division
The Model is quite more complex as it seemed in the beginning. For simplification some things had to be assumed. The model cell population was estimated as a one cell organism surrounded by the environment. Since the amount of all species in the model increase during the simulation a division time had to be assumed (τ=45min). From the division time we get the rate the amount of DNA increases, which is ln2/τ.
To get no aggregation of species in the model all species are either divided by 2 after τ or decreasing by multiplying with a parameter constantly.
Diffusion through the cell wall was modeled because all species, except the DNA can diffuse through the cell membrane into the environment. To get the rate of the diffusion a new parameter “D” has to be introduced. D is the diffusion rate by which all species get through the cell membrane. D was estimated as 10min-1. The diffusion back into the cells is more complicated. It depends on how big the cells are. So a new parameter “r” which depends on the relation of cell volume to environment volume has to be defined. The total volume is the sum of cell volume (Vctot) and environment volume (Vext).
Parameters
Parameters were found in literature or estimated. For the parameters standardized prefixes were used to keep the model clear.
Species
The species used in the model are listed in the next table with a short description.
Some of the species also exist in the environment due to diffusion through the cell membrane. In the environment they get an additional “ext” ending.
Reactions
Equations
Sample equations:
2) Shong et al (2013) Engineering the esaR Promoter for Tunable Quorum Sensing- Dependent Gene Expression
3) Shong et al (2013) Directed Evolution of the Quorum-Sensing Regulator EsaR for Increased Signal Sensitivity
4) Weingart et al (2005) Direct binding of the quorum sensing regulator CepR of Burkholderia cenocepacia to two target promoters in vitro
5) https://2014.igem.org/Team:ETH_Zurich/modeling/parameters
6) Weber M., Buceta J., Dynamics of the quorum sensing switch: stochastic and non-stationary effects, BMC Systems Biology, 2013
