From Dual Degrees to Neurosurgical Leadership: An Interview With Dr. Julie G. Pilitsis
June 19, 2024
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I had an early interest in all kinds of science, and it seemed like biology was really complicated and interesting, and I had a choice between analytic and synthetic. Analytics is observational and reductionistic, while synthetic is more constructive and it gets us closer to where we want to go in terms of fixing medical or environmental problems, and genetics is a nice partner for synthetic biology, as it allows us to very easily read and write and program all kinds of complex biological systems ranging from atoms to ecosystems.
Just by proximity you tend to either think your own mentors are the best mentors or you’ve had some problem with them, but I’m lucky enough that all my mentors have been terrific. I mention them as often as I can. Even in my thesis, I mentioned my high school mentors, Brayden Bedford and Don Snyder. they weren’t on my thesis topic, as they were on math and photography, but they made just a huge impact.
Then in college I was working with Sun Ho Kim. I did my first five scientific papers with him all on crystallography, and that got me thinking about nucleic acids. We happened to be doing crystallography on one of the first nucleic acid-folded molecules. He was just a great influence and he’s continued to be. He was there when I got into the National Academy of Sciences, just fairly recently relative to how long we’ve been working together for 50 years off and on. For my PhD, Wally Gilbert and Gail Martin were all exemplary people for being on the cutting edge of chemistry and biology.
I had a big grant proposal I was submitting, and I realized as I was doing it that we were inventing a new way to sequence DNA, which was approaching so fast that it seemed like we were likely to be reducing the cost of sequencing, maybe a million fold, but it turned out more like 20 million fold. And it was a good time to start dealing with important topics. And to my dismay, I learned about human subjects research for the first time and found a bunch of things that I felt were not as ethical as they should be.
These are sort of the ethics standards, and they were saying things like, “If you learn something extremely informative about somebody’s health, [00:04:30] you can’t communicate it with them, and you also can’t share the data, even if the patient wants you to share the data.” And so I explicitly figured out how to counter that in the Personal Genome Project and wanted to use that as an example for other people that were uncertain as to how to deal with these ethical issues. So they could share their cells or DNA sequences without [00:05:00] imposed restrictions. If they don’t want them or if they want their particular genetics and diseases to be at the front of the line, then they should be free to do that.
They’re not that demanding. They’re a lot of fun. They reinforce one another, and they synergize in such a way that I basically gain time by doing a good job at both of them. My contract at Harvard and MIT requires that I only spend 20% of my time outside of university activities, which is not hard to restrain myself because you can be pretty efficient when you put your mind to it and inside the university, the goal is not so much to be efficient; it’s just to try to help out students and postdocs and get research done.
I would say that one small possibility is that grant funding tends to focus on two extremes. One is the extreme basic science where it’s like you don’t have to justify; it’s just basic. And then the other extreme is it has to apply to human health. And in between, there are all kinds of basic and applied science, or there’s pure science sometimes to be distinguished from applied. But then there’s pure engineering. And I think those are quite interesting, especially if you focus on radical and fundamental technologies. By radical I mean something that is completely non-obvious but could change a lot of things. And fundamental is something that applies to many different fields like sequencing, synthesis, reading, writing, and editing. DNA allows you to do all kinds of organism-agnostics. It’s theory agnostic. It’s just very general tools.
Genetics and synthetic biology have a rich history of using computational methods in general, but we’re entering a new phase. My lab has published 10 or so papers on applying it mainly to protein nucleic acid and cell design.[00:09:00] You’re trying to design for function, which very often isn’t merely a matter of finding its 3D structure. Sometimes you can make radical departures in function without knowing the 3D structure and all things that it’s interacting with. So for example, we’ve used machine learning on gene therapy delivery mechanisms, like viral capsids where you’re trying to get it to go to position X in the body and not position Y, and you don’t really know all the possible things that it could be interacting with in exquisite detail, but you can nevertheless do that. And we’ve done this, for example, bCap 1at Dyno Therapeutics is amazingly targeted for the brain. I think there’s going to be just no end of it, but in a way, it’s just an extension of previous successes , prediction, and design in biology.
It’s a complicated lab. I would say maybe 80% of what we do is synthetic biology, and the other 20% is analytic, but they’re highly entangled. The analytic is mostly focused on in-situ methods or sometimes called spatial multiomics. But we do it by microscopy rather than other methods. So we directly observe things in-situ. On the synthetic side, we just recently showed that we could get resistance to all viruses by a simple re-coding scheme where we swap two codons from serine to leucine, and then we think that that could apply to pretty much any organism that has a virus, whether it is in agriculture, endangered species, humans, and so forth.
We’re not only making organs for transplants from pigs to humans, but making them enhanced so they won’t succumb to the diseases that got rid of the first organ, say resistance to pathogens, resistance to cancers, and so on. I teach a course called “How to Grow Almost Anything” at Harvard and MIT and actually worldwide through online. But we take that seriously, growing things is probably going to be less expensive and ultimately more atomically precise than just about any other engineering we can do.
I discovered somewhere along the line that I was a scientist/engineer, and one of the cool things about being both is it makes it hard to completely fail. So if you make this big engineering plan, and it works the first time, then you’re a competent, capable engineer. On the other hand, it fails and it’s a mystery why it failed, because you’ve carefully planned it. Then you’ve probably made a discovery, and in the process of following up that discovery, then you become a good scientist until you move on to the next thing.
Well, the first thing, before I give any advice,: don’t trust advice, especially if it’s “one size fits all.” So that’s the disclaimer and advice. And very often there’ll be a lot of pressure to conform. I think if you’re not the “one size fits all”, and if you are in the kind of place that I’m in, then you want to be bold and step away from the crowd. They’re either wrong or they’re so many of them that there’s no space to grow. You don’t have to step away, but I’m just saying that’s one way to succeed. There are many ways to succeed in science. Also, I think what happens is sometimes people think of science as being less social than the social sciences, and it’s almost the opposite. I find a lot of my professor friends in social sciences work pretty much by themselves with very few students, and they’re writing their next book, which requires focus, while a lot of my medical research friends are running labs with 20 or more people in them. So there’s a lot to be said for communication, clear communication – constant, but concise.
I can mention things that I appreciated among my mentors.So I think patience is one key attribute. Additionally, humility, sympathy, creativity, and working with people to encourage their creativity, not just your own, is important. There’s a lot at stake when you’re interviewing somebody. You’re not only figuring out if they’re a good match, but also you’re setting the tone, setting up what your principles are for the laboratory, and that can help them decide whether it’s a good fit, but it can also start the conversation about what they should be doing to conduct themselves responsibly.
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