Aaron McKenna, who is a researcher and professor for the Geisel School of Medicine, recently received the National Institutes of Health New Innovator Award, which provides $1.5 million in funding. The New Innovator Award aims to fund breakthrough research by young researchers. McKenna studies cell fate mapping with his lab to investigate the nature of cell development errors that precipitate common medical conditions, such as cancer, neurologic diseases and autism spectrum disorders. McKenna worked as a software engineer for the Broad Institute of Harvard University and the Massachusetts Institute of Technology before earning his Ph.D. at the University of Washington in genomics in 2017.
The Dartmouth sat down with McKenna to discuss his journey to Geisel, the goals of his research and how the New Innovator Award will impact his lab’s work.
How did you decide on your path as a biological researcher?
AM: I took a circuitous route to biology. I was a computer science undergrad, and I was a software engineer in Boston for a couple of years, though I was always pretty interested in biology. I then did a master’s degree at Boston University. Then, I got a job at the Broad Institute, which conducts sizable genomics projects and transitioned to computational biology there. I did that for a couple of years, and I really loved it. I went to grad school at the University of Washington because I’d seen Jay Shendure speak at the Broad, and the work he was doing with genomics there was really fascinating. I went out to Seattle for like six, seven years and did my Ph.D. and a little postdoc period. Then, I landed a job at Geisel and at Dartmouth. The lab is continuing with that mission of developing both computational tools and molecular tools to figure out how cells make choices. Mainly, I’m part of the Dartmouth Cancer Center now, with a focus towards cancer but also normal development.
How has your background as a software engineer contributed to your success as a researcher?
AM: I think there’s a strong appreciation these days that you can’t get through biology, and certainly biomedical engineering or bioengineering, without a fair bit of computational skills. Having a background as a software engineer certainly helped. But I think at the same time, there’s an immense amount to learn about biology, and there are not a lot of programs out there that adapt computational people to be more mixed with lab and computational. There is a steep learning curve in that sense, but it was a strong background to come with — and there’s always a need for computational people, so you’re met with open arms.
The NIH takes on a considerable risk by investing in younger researchers. What about your research in particular caused NIH to deem that risk acceptable?
AM: We proposed to build on our existing technology that determines the relationship between cells over time and apply it to a fundamental question in biology, which is how cells make choices to produce fully formed organisms. How do hepatocytes in your liver know to become hepatocytes and not neurons, or any other combination of cells? And we know some of that is stochastic. There’s cell competition. There are many contributing factors. But pretty reliably, that process, starting from a single cell, makes a human or it makes a mouse or a bird. In developmental biology, there’s a huge question of how structured this is and when that structure comes into play. That’s what our research program is after: understanding that process. Our goal is to take the systems that we’ve shown work well in zebrafish and in cell culture, and apply it to a mouse, which is the most readily used, closest model organism to humans.
How will the New Innovator Award enhance your pursuit of cell fate mapping?
AM: There’s the obvious aspect in that it provides a lot of funding at a critical junction for our lab. But, moreover, one of the unique things about the New Innovator Award is that it’s much less structured than other NIH awards. They essentially give you the $1.5 million in two lump sums and provide you a lot more freedom than with a typical NIH award. The benefits of this are twofold; first, we can move quickly, and second, we can make dynamic choices about the best course of action. We can pivot quickly, or we can apply the technologies and the resources that come with that money to the question at hand quickly. Also, it’s a really nice sign that the NIH evaluated this research and thought, in a highly competitive pool, this is something that is valuable. As a faculty member or as someone proposing a moonshot of sorts, this is really gratifying to hear that both the NIH and your peers who reviewed your proposal thought highly of it and thought that this could be an important milestone for the field.
What implications could you envision your research having outside of your field?
AM: There are so many unanswered questions in development and many of those questions in terms of human health are questions of how development goes awry from diseases such as cancer, or more complex diseases when you think of neurologic diseases or autism spectrum disorders. All of these play out within the context of development. Oftentimes, they are really development gone awry, or development repurposed in the instance of cancer. The more we understand about those underlying fundamental processes, the better the therapies will be and, more importantly, the better the interventions can be. What we’re trying to do is really fill in this gap of knowledge of how cells are related, and how cells make those choices so that we can design better drugs and build better interventions to improve human health. Certainly, a lot of this will be discovered in mice, and there’ll be a long effort to translate these fundamental insights into patient care. But it’s vital to have this forethought about how we’ll shape things down the road and how we can backfill our understanding of how the world works. Accordingly, we envision that these long-term insights will be really powerful.
This interview has been edited and condensed for clarity and length.