Semi-Rational Genome Engineering

I recently had a chance to interview Harris Wang, a young researcher at Columbia University who is doing some very exciting work in synthetic biology. He recently published a new method called (MO)-MAGE, which makes it possible to deliver large numbers of targeted mutations in E. coli simultaneously. The implications are quite fascinating, both in terms of the conceptual frame shift the technology implies and its potential practical applications. In an interview I recently posted to the Department of Systems Biology’s website he explains:

The biggest problem with random mutagenesis is that the likelihood of a finding a beneficial mutation is astronomically low. (MO)-MAGE is not random, but it’s not a completely rational approach to engineering either. I like to think of it as a semi-rational approach whose beauty is that by allowing you to make many genetic variants very quickly, it opens up experimental opportunities that we’ve never really had before.

For example, computational analysis or the scientific literature might lead you to hypothesize that 5 genes are relevant in a specific biochemical process you are trying to optimize. But those genes exist within a complex molecular system and so identifying the ideal levels for all of these components in combination using traditional approaches poses a very difficult problem. By using (MO)-MAGE, however, you can quickly produce lots of genetic variants that you can just experimentally isolate and characterize. This allows you to tune the expression of all of the genes in an iterative way.

If you think about the traditional engineering pipeline that goes from design to building to testing, using this kind of semi-rational approach removes a historical bottleneck. Previously you might have been able to propose a variety of possible designs to optimize a specific biochemical activity, but it was never practical to build them all. (MO)-MAGE saves you from needing to put all your eggs in one basket with one design; it gives you a method to experimentally try hundreds of thousands or even millions of mutations and see what looks interesting.

In the interview Dr. Wang explains how (MO)-MAGE works, and what it could mean for both basic biological research and commercial applications of synthetic biology. Read the full interview here.