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Team:ETH Zurich/Project
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| - | + | == Project outline == | |
| + | The overall theme of our project is to establish a new method to minimize the genome of an organism without losing its main property: life. That is, we want to engineer a synthetic biology method that leads to the discovery of “minimal genome(s)”. For convenience reasons we have chosen to work with ''Escherichia coli'' model organism. Currently we are investigating an approach that is outlined below. | ||
| + | === Biotechnology approach === | ||
| + | The general idea of this approach is to use induced synthetic evolution as a tool to minimize the organism’s genome. Our goal is to engineer a method that, cyclically and automatically, operates on the individuals of bacterial populations by randomly reducing their genome’s size through a process of cut out and ligation. Then putting a selective pressure on the bacteria with a smaller genome, we aim to select at each cycle for the individuals with smaller genomes. Since the approach can be seen as practical application of the computer science genetic algorithm concept, we divided the explanation accordingly with the three classical genetic algorithm phases: Mutating Function, Selection Function, and Fitness Function | ||
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| - | + | The approach can be separated in 3 parts. | |
| + | ==== The Mutating Function ==== | ||
| + | The mutating function is responsible for driving our population of the target organism away from its current state in a random manner, towards the wished goal state. Since for us the goal is a smaller genome, we like to reduce the genetic content within the cell. | ||
| + | We are trying to achieve this by the ''in vivo'' expression of restriction enzyme, in order to cut out some pseudo-random part of the genome and then re-ligate the chromosome. To ensure the survival of a sufficient amount of cells we are coupling the expression with constitutive overexpression of ligase and eventually an expression of a competing methylase. The plan is to control the expression of the restriction enzymes and eventually the methylase with a pulse generator. | ||
| - | + | ==== The Selection Function ==== | |
| - | + | This is the mechanism that selects for our preferred individuals within the population. We thought to use the most natural and by that simplest approach, which translates to just using the growth rate of the organism. Those organisms that replicate faster will prevail over time against competitors in the population with a lower growth rate. | |
| - | + | ==== The Fitness Function ==== | |
| - | + | The objective function is responsible for the evolutionary selection of strains with a smaller genome. We expect that for deletions of genes that even only slightly influence the growth rate in a negative way, there will be a big selection pressure and those individuals won’t stay in the population. To ensure that we can select also for those individual and by that have the ability to minimize more, we are trying to introduce a mechanism to amplify the benefits of a smaller genome. By this amplification we are hoping to cancel out the negative effects of these deletions and that way drive the minimization further. In general the reduction of the genome in this approach will only proceed till the point, where positive effects of genome reduction by the objective function and the negative effects of gene deletions combined influence the fitness negatively. | |
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Latest revision as of 13:28, 1 August 2008
Contents |
Project outline
The overall theme of our project is to establish a new method to minimize the genome of an organism without losing its main property: life. That is, we want to engineer a synthetic biology method that leads to the discovery of “minimal genome(s)”. For convenience reasons we have chosen to work with Escherichia coli model organism. Currently we are investigating an approach that is outlined below.
Biotechnology approach
The general idea of this approach is to use induced synthetic evolution as a tool to minimize the organism’s genome. Our goal is to engineer a method that, cyclically and automatically, operates on the individuals of bacterial populations by randomly reducing their genome’s size through a process of cut out and ligation. Then putting a selective pressure on the bacteria with a smaller genome, we aim to select at each cycle for the individuals with smaller genomes. Since the approach can be seen as practical application of the computer science genetic algorithm concept, we divided the explanation accordingly with the three classical genetic algorithm phases: Mutating Function, Selection Function, and Fitness Function
The approach can be separated in 3 parts.
The Mutating Function
The mutating function is responsible for driving our population of the target organism away from its current state in a random manner, towards the wished goal state. Since for us the goal is a smaller genome, we like to reduce the genetic content within the cell. We are trying to achieve this by the in vivo expression of restriction enzyme, in order to cut out some pseudo-random part of the genome and then re-ligate the chromosome. To ensure the survival of a sufficient amount of cells we are coupling the expression with constitutive overexpression of ligase and eventually an expression of a competing methylase. The plan is to control the expression of the restriction enzymes and eventually the methylase with a pulse generator.
The Selection Function
This is the mechanism that selects for our preferred individuals within the population. We thought to use the most natural and by that simplest approach, which translates to just using the growth rate of the organism. Those organisms that replicate faster will prevail over time against competitors in the population with a lower growth rate.
The Fitness Function
The objective function is responsible for the evolutionary selection of strains with a smaller genome. We expect that for deletions of genes that even only slightly influence the growth rate in a negative way, there will be a big selection pressure and those individuals won’t stay in the population. To ensure that we can select also for those individual and by that have the ability to minimize more, we are trying to introduce a mechanism to amplify the benefits of a smaller genome. By this amplification we are hoping to cancel out the negative effects of these deletions and that way drive the minimization further. In general the reduction of the genome in this approach will only proceed till the point, where positive effects of genome reduction by the objective function and the negative effects of gene deletions combined influence the fitness negatively.
