Alumni profile: A conversation with Douglas Densmore

Douglas Densmore (BSE CE, 2001), an associate professor of electrical and computer engineering and biomedical engineering at Boston University, is working at a research intersection that may sound like sci-fi to the outside reader. Called synthetic biology, the discipline explores ways to manipulate biological organisms and tissues as though they were programmable computers.

In his Cross-disciplinary Integration of Design Automation Research (CIDAR) group, Densmore does just that. He and his team apply electronic design automation to improve how we do things like compiling code to DNA. He’s compiled the popular hardware description language Verilog directly to strands of DNA, and has designed new programming languages that let you manipulate biology with commands such as if, then, else statements. Among other groundbreaking developments, this research promises smart therapeutics that can be delivered directly where they’re needed in our body by pre-programmed organisms.

Densmore took the processes involved in this work from design all the way to fabrication as the founder of BU’s Design, Automation, Manufacturing, and Prototyping (DAMP) Lab, where DNA strands with various sets of instructions can be rapidly synthesized or assembled. His work has brought him to a leadership position on NSF’s “Living Computing” project. He’s also the co-founder of three companies and two nonprofit organizations, all specializing in synthetic biology research and technology.

We spoke with Densmore about his journey from a computer engineering undergrad, pulling all-nighters in the Duderstadt Center’s Media Commons, to a pioneering researcher and industry leader.

What is your lab trying to do?
Broadly speaking, what I try to do is to get biology to compute. When I say compute, I don’t mean that we’re trying to make biology be like a modern microprocessor. That’s an outdated analogy already, but intuitively we know biology is in some sense more powerful, because everything I’m saying to you right now is biology. My brain is a biological entity, making my vocal cords make noise that convey an idea that is really just chemicals in my head. So we kind of know what biological systems can do in the most extreme sense.

And so, can we start with very basic things? Can I make a bacteria move in a certain way, based on some inputs? If this input is true, then execute that output – the same as a computer. Can we make bacteria administer a therapeutic? If this condition is true, I’m in the gut. And if it’s this time of day, and if this biomarker is present, release some therapeutic.

I want to make cells compute in that way, to make decisions. I do it with software that reflects the same way we designed computers. You start with high level languages, but instead of compiling to ones and zeros it compiles to DNA.

My lab was created so that people can access the infrastructure to do that, like software and programs. Then, once that’s done at your desk, it needs to be physically made. That’s why I created the DAMP Lab at Boston University. This process allows in-silico designs to be sent to a foundry and manufactured automatically by robotics. I try to close the loop from design, all the way to fabrication and test.

What does it mean to compile code to DNA?
Let’s take that microbiome example. You have one little part of DNA that tells how to sense when you’re in the gut, one little part that says make a therapeutic, and another little part that says, “when I’m in the gut and I’ve made a therapeutic, burst the cell open and release the therapeutic.” Then you take these pieces and you stitch them together on the computer. All it is is a series of letters: A, T, C, and G. That’s it.

Then, the way you get the DNA out at the end is you can “print” it by sending it to a place to do chemical DNA synthesis, where they take those individual G’s, A’s, C’s, and T’s and put them together through a chemical process. Or, you can take it into your lab, and your lab will have those three little parts already in a test tube. You go through a process of enzymatic cloning steps, so those get cut out of the DNA and stuck back together.

There’s not 3D printing per se. It’s either that they’re chemically synthesized or you go through a process where you stitch DNA together in a lab with enzymes and other things.

A lot of what we’re talking about is like a philosophy as much as a process. For example, let’s say you worked out and got really in shape, and someone else did it differently, and someone else did it differently but there was no systematic way of getting an average person in shape. I would not consider this an “engineering” success. In the same way, people have been manipulating biology for a while – doing it this way, doing it that way. But with synthetic biology and design automation we’re talking about getting it to be consistently done same way.

Before there were 100 people all working out 100 different ways. Now what we’re trying to do is get 100 people working out the same way to get similar products, similar results.

What have been some of your key achievements to date?

The biggest thing I’m known for is taking Verilog, which is the same language an undergrad at U-M will use in logic courses, and compiling it to DNA. You can write a digital circuit in Verilog and compile that to the DNA. That’s probably my most notable paper.

I have also designed algorithms that helped put DNA together more efficiently. And if you can do that, you can make more DNA and you can do it more intelligently. You don’t really make one circuit or DNA process, you make lots and you figure out which one works. So I’ve made algorithms that help DNA get put together really efficiently.

I’ve made programming languages to program biology, so that you can actually say, “if this, then that.” And then we’ve also made software that designs small little devices called microfluidics that we can put together that help us test this system.

How did you get from computer engineering to synthetic biology?
I’m from outside of Kalamazoo. That’s one of the reasons I went to Michigan. I decided on computer engineering over computer science because I thought that was the tougher, more rigorous thing to do. My plan was to go work at Nintendo. I was like, “I’m going to do software, I’m going to work at Nintendo.” This was the mid 90’s and that’s what I wanted to do.

So I got to Michigan and I took EECS 270, the digital logic design course. In that class we put things on breadboards – this was before FPGAs were used – and I was like, “this is really cool, you can put circuits together and get it to light up the light, this is way better than software.” So I said I want to be a hardware person, forget Nintendo. I’m not artistic anyway, and I can’t speak Japanese, so my Nintendo chances are limited. Let me do this hardware thing.

Then I took EECS 427, the VLSI design class. I made a microprocessor in that class, and I loved it. I slept in the Media Union [now a part of the Duderstadt Center]. I think I slept in that building for a month, because we didn’t have laptops or personal internet much less the CAD software we needed.

I did four internships at Intel as an undergrad. I was an Intel GEM Fellow. While I was there I realized I didn’t like working an 8 to 5 job very much. So I applied to graduate school at Michigan and was accepted.

But I had also done these internships in California at Intel, I had friends in Northern California, and I was also accepted at the University of California at Berkeley. And so I ended up going to Berkeley for grad school, and focused on design automation for electronics for my whole PhD.

For personal reasons I decided to stay at Berkeley for a postdoc. I wanted to work on something new and looked outside of Berkeley, and found that people in the Bay Area had really gotten into synthetic biology.

Someone at the University of California San Francisco had put a NOR gate in a bacteria, so I went over the bridge and talked to this professor (Prof. Chris Voigt who’s now at MIT and a U of M alum). I learned that this synbio field was wide open.

You see, I had been working in CAD for electronics, the most mature, “already done” area. You had to work really hard to come up with new ideas. But in synthetic biology, every idea I had was new. I was like, oh, this is new, and this is new – I couldn’t fail. Every idea was like a stake in the ground. People were also really excited about it. I had to work really hard to get anyone to pay attention to my PhD work, but every time I wanted to give a talk in synbio I was the only electrical engineer. I felt wanted and needed, and that’s how I got into it.

So when I went on the job market, I learned that Boston is the place to do synthetic biology. That’s how I ended up here.

Did Michigan prepare you for what came after?
Michigan was the hardest thing I ever did. Grad school was much easier than undergrad. It’s typically easier, because of the different pacing, but Michigan…I was happy there, but I was also very stressed. That’s not a knock against Michigan. It was a lot of work. I have the undergrads whine at me here, and I’m like, listen, I heard it already. I did it, I remember. It definitely prepared me, I have nothing but good things to say about the rigor and the program. They’re tough. I was by far not the smartest kid there.

But a lot of the classes I liked were the ones that were on some level a function of effort, like the VLSI class. Did you get that layout to work, could you spend the time to do it, could you be in the lab, could you grind it out? I was never going to get a good grade on the exams. The exams I always got the mean, I was always in the middle. But then the projects or the homework, that’s where I excelled. If I was in a project course, I was probably going to do the best project in the class, or one of the better ones.

And Michigan gave me opportunities to do that. I love Michigan.

How do you feel your experience here was different as a Black student?
I was a student when Lee Bollinger was the U-M President, and the university was involved in a landmark affirmative action case. One of the key things I remember from that time was how much Michigan stood behind the President and the university’s admissions decisions. U-M wasn’t apologetic about their policies and really stood by them. So I always had good feelings about Michigan from that standpoint.

I’m from outside of Kalamazoo, in a predominantly white area, so I didn’t go to a predominantly Black high school. It wasn’t like the environment at Michigan was shocking to me. But what I thought was really nice when I was there was the Minority Engineering Program Office. That office set up study groups, tutoring sessions, and if you dropped by the people in the office knew your name. That was great.

And the other thing was the National Society of Black Engineers. The U-M chapter was huge because Michigan recruited a number of students from Detroit. We had big meetings; there were 100 kids in there. It was a good community.

So between the MEPO office and NSBE I felt really supported. The other thing is, Michigan had some summer programs. One was called SCEEP [Summer College Engineering Exposure Program] and the other was called PTP [Professional Training Program]. I attended one of them the summer before my high school senior year, and the other after my senior year, before I started at Michigan. A key thing I remember was, thanks to those programs, when you began as a first year student at Michigan you already knew some juniors and seniors and you already had some upperclassmen mentors.

Long story short, I thought Michigan did a really good job of creating a community for folks and mentoring them.

How did your experiences as a student inform your philosophy now as an educator or research mentor?
It’s hard to say. I mentioned how at Michigan I liked being part of that community and making those connections. So I would have been comfortable if a faculty member said, hey, you seem like you’re struggling a little bit. Have you found the MEPO office, have you found this group, have you connected – I kind of liked that.

But as a faculty member, I’m in a situation where that can be a little dicey. A student might say, why did you point me to that just because I’m a Latino student or just because I’m Black? It’s 2021, where the rules are changing about everything, and I’m antiquated myself.

I think the main thing is, I just try to find students, see if those communities can help, and point people in the right direction. It’s a real issue, but it’s so heterogeneous even within the community.

For example, when I went to Berkeley I was very comfortable there. I thought it was a great place. I liked the Bay Area, I liked that hippie liberal culture. But a Black colleague of mine went to an HBCU. And they just had a hell of a time at Berkeley. They were very uncomfortable there and thought the people were unfriendly. So – two people, same kind of ethnic identities, but very different responses. It really depends a lot on what you’re looking for and where you’re from.

How do you feel the student experience, especially for Black students, differs now from your time as a PhD or as an undergrad?
It probably differs a lot. If you want to interact with somebody, form a study group – how do you do that now? When I was in school, I don’t think I had a cell phone. That was kind of what the MEPO offered. They facilitated these groups, you met people, you hung out with them. That became your cohort.

Now students don’t have to meet anybody to do anything. I think places like MEPO are still needed, but it’s a different way of doing things. How students network and interact is so different now.

I’d love to know what students think about the past four years and how America has changed in terms of its political climate. That was not what we had in the least, I didn’t have to deal with that same political climate. You’ve got a lot of racial unrest and students are trying to figure out how they can participate in it.

So, I think in some ways students have it a lot harder. They don’t have some of the same tools I had because politics and legislation have taken some of it away. I’m sympathetic to those a lot of the political causes students want to get involved with, but I’m a parent and older. I’m not in the streets protesting in Boston, but some of these kids might want to be involved in those kinds of protests and those movements. How do they balance that with an engineering course load?

Their anxiety is different. It’s a scary time for a lot of people when it comes to policy. And again, I feel a little bit more isolated because I feel like I’m a little bit more secure in my life. We did go through something like it; I felt a lot of uncertainty during that affirmative action process. Michigan was really a hot time in the 90s, too.

How is it different as a Black faculty member in this field compared to your experience as a student?
The reality is that, if you’re a person of color in science and engineering, to be successful you have to become somewhat comfortable being one of the only such people. It is a gradual process where at each subsequent level there are fewer people like you ethnically. So I’ve gotten gradually more used to that.

I think what’s interesting, though, is that I have moved from a very male-dominated place, electrical engineering, into biology which has more women. However, even though it’s more diverse in terms of gender, there aren’t many more Black people. So this has actually highlighted for me that we are still struggling.

That’s part of it. The other thing I think is, as you become a faculty member, you’re in an interesting position. My guess is that many students have never had a faculty member or teacher from an underrepresented group. They probably went to a place where the people in authority were majority folks. And then suddenly they’re in a position where the teacher of the class or the professor is not that. In my career I’ve had pretty good response. I haven’t had a lot of pushback, I haven’t had somebody upset about the position I’m in or who doesn’t think I should be there, at least not explicitly.

I think being in engineering helps, because it’s a quantitative field. That’s one reason I was attracted to it as a Black person. You don’t really argue with two plus two equals four. If I get up and read you a poem, or write a book, you can say that poem’s bad or that book is poorly written. But you can’t really argue with someone saying two plus two is four. That’s a sort of level playing field – science and engineering kind of levels that out. At least I hope it does.