Team:ETH Zurich/Project/Model Relevant
From 2008.igem.org
Medal Relevant IssuesSilver RelevantGold RelevantWe propose a novel method of random gene deletion and chemostat-based selection of species with a reduced genome. For this we provide an algorithm described below. Modeling FrameworkThis algorithm requires a modeling framework consisting of four main parts:
Detailed description of the Modeling Framework
We want to identify a restriction enzyme for genome reduction that maximizes the probability of genome reduction and minimizes the probability to hit an (known) essential gene. Therefore, given a genome data of an E. Coli strain, the genome is digested using ca. 700 different restriction enzymes (with different recognition patterns). The resulting fragments are analyzed using the available annotation of the genome. The number of genes disrupted is calculated for each fragment. Statistical measures of the restriction enzyme effects, such as average size of the fragments and its variance, and the average number of (all and only essential) genes and its variance are calculated. According to these results, the most suitable restriction enzyme is chosen.
We model a chemostat using a system of coupled differential equations for a population of different mutants with different growth rates competing for a limited external thymidine concentration. By varying the time intervals between two pulses of restriction enzymes (where only a small amount of previous population survived and new mutants are generated) we control the number of different mutants considering for further gene deletions after the next pulse event, consequently the diversity of a population.
Using a novel pulsing mechanism consisting of two signals, start signal, which initiates the expression of restriction enzymes and stop signal, which switches off the expression, we are able to delete genome fragments in vivo. To simulate this system we developed a switch curcuit which works as follows (see Figure 1): by inducing the system with IPTG, the restriction enzyme (RE), which is under control of lacI, can be expressed. In order to stop the expression the system is induced with tet, which inhibits the binding of tetR to LacIS (a mutant of LacI, which is not inducable by IPTG), therefore activates the LacIS expression and consecutive termination of RE expression. This curcuit is modeled by ca. 40 reactions and is simulated using ODE solver and stochastic simulations.
|