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in a particular way. Basically the section of DNA that’s the synthetic instruction set for the cell comprises a whole series of what we call bioparts.
X: Meaning not just the parts of genes that code for proteins, but the code that tells the cell to cut, paste, copy, and do other things with the information?
DK: If you put [the bioparts] into a cell, and it doesn’t achieve what you want it to do, usually the reason is these parts are in the wrong order. They need to be changed around.
Doing this process in a one-off way would take a long time. But with synthetic biology you can produce a whole series of combinations of these instruction sets in parallel, the sort of thing that Twist Biosciences, Gen9, and others can do. Then you run them in parallel and see which ones produces the best results.
X: So if I place an order of synthetic DNA, I’m getting a series of potential combinations, and then it’s my job to test them all to see which one actually works?
DK: Frankly that’s a function of price. You can go to them and say, “I want this single realization of this sequence.” Or, “I want various combinations.” And they’ll do either of those for you.
X: What about the cell itself? Is anyone building new cells from the ground up?
DK: People are trying to do that. Craig Venter is trying. But 99.9 percent of people in synthetic biology use natural cells. That gets us to the next level. The cell is either called the chassis or the host in this field. E. coli and yeast are most common. Within that family of E. coli and yeast, there’s a whole series of different versions, or strains. In addition to doing all these parallel versions of DNA, typically one uses three or four different strains, until you get to a situation where the match between the DNA and the strain of E. coli, for example, is optimal.
X: To someone who has mainly covered biopharmaceuticals for the past decade, this sounds a bit like running a drug discovery screen, whittling down from an array of possibilities.
DK: That’s right, but remember as the field progresses—with thousands of people working on these aspects of synthetic biology—we’re converging on a much more systematic way of designing these synthetic biology devices. People run experiments, where they check the DNA in relation to how the cell responds, and that information is placed into a registry. For a particular type of scenario you can go to a registry and say, “I want a particular biopart that does something.” The information about that biopart has already been characterized in a detailed way.
X: Are you saying everyone working in the field is obliged to contribute their findings to a registry?
DK: We work closely with American colleagues; in the academic community of Imperial, MIT, Stanford, Berkeley, et cetera, there is a strong feeling to share with each other. It’s a whole open source movement on the academic side.
X: Is that what “Biobricks” is?
DK: Biobricks is associated with the iGEM competition, the international student competition in synthetic biology. That registry comprises about 20,000 biobricks—the different components. But they’re not properly characterized. In the field there’s a clear distinction between what’s done for iGEM— we’ve had a team in the competition since 2006, and I’m on the advisory board—and a professional movement where people are building out registries of fully characterized parts.
On the professional side, industrial translation is important. Tom Knight, one of the fathers of synthetic biology, has a company called Gingko Bioworks in Boston. When he gives a lecture, he comes in with a tome, the Texas Instruments transistor handbook from about 25 years ago, which has all these data sheets in it. When TI produced those transistors they had to be completely reliable. That’s the key difference between the iGEM registry and the professional registries.
If you go back to the 1950s, transistor characterization was not very reliable. I remember as a student, we would be in the lab, measuring the characteristics of transistors to find the one that was good. We don’t do that now. Intel is producing chips with billions of transistors. Biology is at the point where electronics was in the fifties. You’ve gotten a professional part out of a registry. Yes, it’s characterized as accurately as possible. But you still go back and check it.
X: Many years ago, I covered tech before I covered biotech. One thing I enjoy much more about the life sciences is the messiness of it.
DK: That will disappear, in my opinion, in the next 70 years!
X: Even with something as complex as the human immune system? It’s hard to imagine components of the immune system, for example, being modularized in that sense. But you feel it’s going to happen?
DK: I really do. It might take 50 or 100 years, but there’s a wave front moving through.
More to come in part two: A biosensor for urinary tract infections, imperfect analogies to automotive plants and electronic circuits, and the minister wants jobs.