Mark Hewlett

Research Scientist, University of Exeter

Below is the video transcript.

The Exeter Microbial Biofuels Group (EMBG) are a synthetic biology lab designing bacteria to produce custom alkanes for biofuels. Recently, we've also started doing a lot of work on alternative platform precursor chemicals. So, that's mostly about bioplastic precursors.

When I joined EMBG about seven years ago, there was already some use of JMP in the lab. I was using it basically to start off with to optimize some really simple lab processes. For example, we use a sonicator to lyse bacterial cells so that we can harvest the protein inside. We've changed our sonicator machine two times in the last 15 years. And each time we just kept the same protocol. So, I ran that through a screening design. And I got actually a three-fold increase in usable protein within, I think, just 12 experiments. So, it was a half-day's work, it was really simple, but it made a massive difference to the amount of time I was spending on lysis and the amount of yield I was getting.

The most common tool I use is design of experiments (DOE) to try and get away from the one-factor-at-a-time or full factorial experimental design. I think that's really important, especially with undergraduate students because they have such limited time in the lab, and such limited kind of financial resources behind their research that you want to get as much high-quality data as possible with the fewest amount of experimental runs, and I think that's where JMP really comes into its own. It forces you to understand your priorities in your experimental design in a way that if you just start a one-factor-at-a-time experiment, you miss out on some of those complexities.

I try quite hard to get my undergraduate and postgraduate students to use JMP to maximize the amount of experimental data they can get, and I think that the Easy DOE is probably the most useful way of having a really low-key introduction to JMP.

We host an iGEM team every year where we take 12 undergraduate students, and iGEM is a very prestigious synthetic biology competition where they come up with their own project to solve a real-world problem using synthetic biology. One team, called BoviTECT, that we had last year were looking at designing a veterinary diagnostic device for bovine tuberculosis. And an undergraduate student of mine took this project on and used JMP to optimize it. And she saw, I think, about a 60-fold improvement in sensitivity over three iterations of JMP. She's done a really great job of using JMP to optimize that diagnostic test.

What I really love about my job is that every day is a bit different. So, sometimes I'm doing genetic engineering, sometimes I'm doing protein biochemistry, sometimes I'm doing analytical chemistry. There's such a broad range of things, and I have so much freedom to take experiments from concept, to design, to analysis, to publication.

So, it's the variety and the kind of intellectual freedom to pursue really interesting questions, I think, that makes my job really exciting.