Overview
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Quorum Sensing
Introduction
For the iGEM project a toxin producing system has been made. We wanted to create a system where bacteria can produce toxin in waves and hereby create different cell populations. With the use of quorum sensing and a toxin/anti-toxin system, as shown in Figure 1, we expect to find different cell populations.
What is quorum sensing
Quorum sensing is a cell-cell communication system. The detection of chemical molecules allows the bacteria to distinguish between low and high cell densities, in this way control gene expression in response to changes in cell number 1.
Methods
During the research Matlab version R2016a has been used.
Because there was no data from the wet lab we assumed that all the parameters in the system were random.
The parameters are all obtained by latin hypercube Latin hypercube is a statistical method to get random numbers from a box of n by n numbers. For example x = 4 with x is divisions and n = 2 with n is number of samples. You will obtain a box with 4 square times 2 square, give you 24 random numbers. For each parameter one number out of this box is randomly chosen. samples.
How could quorum sensing develop spatial inhomogeneities in toxin/anti-toxin systems?
When quorum sensing ensures that the toxin is only produced when the density of bacteria is high enough to produce significant amounts of toxin, this ‘standardizes’ the amount of toxin produced by the bacteria. The toxin/anti-toxin system will be coupled to the quorum sensing system. Together, quorum sensing and forming of non-producing subpopulations by the toxin/anti-toxin system, allow bacteria to produce ‘waves’ of toxin.
Results
When lambda is present in big amounts the RFP response will be high. You need a lot more lambda than 434 to get high RFP responses. This can be expected when you look at the subpopulation system, the system is inhibited by 434 which represses the RFP production and lambda activates the RFP production. In the Heat Map 1 you can see that there is little difference between the 434 and lambda amounts that are present for the output of RFP. This means that the initial conditions do not have so much influence on the 434 and lambda. With this data we can conclude that the translation rates are more important for the RFP response than the initial conditions.
Quorum sensing system
References
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1. Eri Nasuno, Nobutada Kimura, Masaki J. Fujita, Cindy H. Nakatsu, Yoichi Kamagata, and Satoshi Hanada (2012). Phylogenetically Novel LuxI/LuxR-Type Quorum Sensing Systems Isolated Using a Metagenomic Approach
Vol, 78, number 22. ↩
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