Team:ETH Zurich/Project/Motivation

Why in this case simpler is better ...

Building new functions into cells is the goal of synthetic biology. To achieve this, circuits encoding for the desired behavior have to be inserted into an existing network of allready considerable complexity, where many of the interactions are not completely understood. By reducing the complexity of the target organism, this interdependencies can be reduced and more predictable results can be obtained.

One of the main engineering goals in this field is to make the design of new circuits more deterministic, allowing for predictive mathematical models and simulation of new functions before these are implemented in vivo. Cross-talk between the different pathways in the organism and the additionally implemented circuits can lead to interferences, making the behavior non-deterministic. In such cases "debugging" of the inserted circuit can be extremely hard. A minimal cell would provide a more predictable chassis when used as an engineering fundament.

Engineering chasis

Our main motivation is to develop a method to reduce the complexity of the target organism dramatically. This will allow to characterize the biochemical reactions that are necessary to sustain life, eliminating all the "balast" that may interfere with the inserted functions. We are trying to move from a network with many unknown interactions like this:

to something more in line with this:

File:Network2.jpg

Current approaches

As usual when takling engineering projects, two main approaches can be followed: bottom-up and top-down. In the first case we try to identify all the necessary functions for our system to work (in this case: to live). In this case we identify pathways to produce all necesary metabolites the cell needs, such as lipids, aminoacids, etc. A good example of this approach can be found in []. The second approach starts from a working syspem (such as a well characterized strain like K12). By identifying non-essential parts of the metabolism and deleting them, we reduce the complexity of the cell.