Drew Endy talked about engineering biology for Edge. Most of the emphasis is still on standardization of biological parts and the importance of simplifying the process of creating a biological function. Still it would be nice to hear from him some new ideas about establishing processes of engineering biology. His whole speech seems focused on creating the hacker culture in biology. To transpose all the same concepts that would allow us to re-create the explosive growth of tinkering and production that we saw for electronics and computer programing within the biological sciences.
I agree with most of what he says, that we should: 1)focus on method development; 2)work on a registry of parts and 3) foster an "open source"/hacker culture in synthetic biology. In this text he did not mention for example the importance of modeling but it is implicit in the standardization of parts. Once you have a computer simulation of the process you wish to engineer that you should be able to reach into the parts list to implement it. The problem with this concept of standardized parts is the complexity that Drew Endy dislikes so much. There is still no way around it. We can take a part that has been very well defined in E. coli, plug into a yeast plasmid and it might not work at all.
If we are still far way from the ideal plug and play maybe we could try to take advantage of what biology can do very well, to evolve to a suitable solution. I would argue that we should develop engineering protocols that could take advantage of the evolutionary process.
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Lets say we want to implement a function and I know beforehand that I will not be able to get perfect parts to implement it. Can we design this function in a way that it will have a large funnel of attraction for the design properties that I am interested in ? Are there biological parts that are more amenable to a directed evolutionary experiment to reach that design goal ? How can I increase the mutation rate for a controlled period of time and only for the stretch of DNA that I want to evolve ? Maybe it is possible to place the parts in a plasmid and have the replication of this plasmid be under a different polymerase that is more error prone ?
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If we could answer some of these questions (maybe we have already), we could design the function of interest (modeling), pull parts that would be close to the solution, mutate/select until the best design is achieved and then freeze it by reducing the generation of diversity in some way.
Further reading:
Synthetic biology: promises and challenges
Molecular Systems Biology 3 Article number: 158 doi:10.1038/msb4100202