859: Modeling How Ecological and Evolutionary Processes Drive Adaptation in a Changing World - Dr. Lawrence Uricchio

0:00Hey everyone, I'm Dr. Marie McNeely and I'm excited to welcome you to episode 859 of People Behind the Science. Today, I am joined by our guest, Dr. Lawrence Uricchio. I want to take a moment to thank you for listening today and give a special shout out to everyone out there who has subscribed to our show or left a rating or review. We truly appreciate it and we have a great episode for you today. So get ready to meet another one of our amazing People Behind the Science.

0:30Every day, discoveries are made that will change our understanding of the world around us. Dr. Marie McNeely is here to bring you the brilliant minds who are making these discoveries so they can share their incredible stories and take you on an amazing journey. Welcome to People Behind the Science.

0:52Hello, everyone, and welcome to People Behind the Science. Listeners, I am thrilled to have you here with me today and I'm thrilled to be speaking with our guest, Dr. Lawrence Uricchio. So Lawrence, welcome to the show today. How are you? I'm doing well. Thank you so much for having me. Well, Lawrence, we are delighted to have you with us and I'm excited to learn more about you and your research. But before we get into our official interview questions, let me first take a moment to tell our listeners a little bit more about your current position and the steps that you took to

1:25get to where you are today. So listeners, Lawrence is assistant professor and the Eunice Family Professor of Innovation in the Department of Biology at Tufts University. He completed his bachelor's degree in physics at Carleton College, and he received master's degrees in biophysical sciences and computer science from the University of Chicago. He was awarded his PhD in bioinformatics from the University of California, San Francisco. And while at UCSF, Lawrence was named a Discovery Fellow. Afterwards, Lawrence conducted postdoctoral research at Stanford University under a Center for Computational,

1:58Evolutionary, and Human Genomics Fellowship and an NIH Institutional Research and Academic Career Development Award. He also conducted postdoctoral research at the University of California, Berkeley before joining the faculty there at Tufts in 2021. And Lawrence, today we're excited to get to know you as a scientist, of course, but we also want to get to know you better as a person more generally. So can you take a moment to tell us what you like to do when you're not doing science? I'm a family guy, so I like to spend time with my son. He's nine years old. He's a soccer player,

2:29typical kind of soccer dad, drive around a lot from practice to practice. On my own, I like to run to be outside. I was a runner in college and kind of keep that going much slower than I used to, not that I was ever terribly fast, but even slower now. And I just like that engagement of the body and the mind that you get when you're outside and experiencing the space and trying to move as quick as you can, even if it's not so quick anymore. That's fair. Were you a distance runner or kind of more short track? I was, yeah. I was a mid-distance runner in high school, back in college and often injured and always striving to be a little better than I ever got

3:00to be, but still a big part of my life. Well, good. I think taking the time to get out there, be active, get away from the lab for a little bit can be tremendously helpful. And I think you're doing some remarkable research in the lab. So let's talk about that next. So Lawrence, how do you describe what you do in your work to somebody who's not familiar with your specific area of research or is outside of science altogether? We're kind of a funny lab. I think most labs you think about there's an organism or a particular type of measurement that you make in the lab and you get really good at that thing. And you're an absolute deep expert in that one type

3:33of thing. And we're a little bit different. We're a modeling lab. So we think about how evolutionary processes and ecological processes work and then how we can explain the observations we make in nature, whether that's which species are in a particular place at a particular time or what their DNA sequences might look like if certain different evolutionary processes are affecting how that variation is structured in the real world. So we do take a combination of experimental and observational approaches to generate data. But then most of our real research is on the modeling side. It's thinking about mathematical models and how we can understand nature through mathematical models.

4:05Cool. I'm excited to get into some more details of your research as we go through our conversation today. But let's talk a little bit about motivation first. I think as a scientist, there are a lot of challenges. There's a lot of motivation necessary to even get to this point in your career where you are a faculty member. So do you have a favorite quote or a saying or something that just really motivates and inspires you? I think something I'm often saying to myself, and this maybe isn't terribly motivational, but just get it done. Sometimes research is a slog, right? And sometimes the big questions that you have that

4:36are really what's actually motivating you are not the thing that you feel on a day-to-day basis all of the time. I think some people are really good at engaging their curiosity through every little thing that they're doing. But for me, sometimes it's like, well, I got to write another for loop in this script or another, you know, sort of mundane task that you do on a day-to-day basis. The thing you really want is around the corner past this thing that you have to do that might not be the most engaging, but as part of the process. And so I'm often telling myself, get it done. And then the reward is there and the payoff often is there. And it's really working with the people who are also very curious about these same questions and kind of getting to

5:09experience that little bit of insight that you get, having done all of those little tedious, mundane tasks that make up your day-to-day. Oh, definitely. And I think having that mindset of just get it done can be really helpful because I think oftentimes you sort of enter the state of decision paralysis or, you know, you feel that resistance where it's difficult or you want something to be perfect. But I think sometimes done is better than perfect. Absolutely. And I kind of had this naive vision that at this point in my career, not that I'm super advanced, but this far along, I wouldn't have that kind of paralysis anymore. But it actually is even worse because you work on so many different things once you're a faculty

5:42member and that kind of transition from one thing to the next. It's like, oh, well, now I got to go back that other mundane thing that I haven't thought about for a while and make some progress on that. So it's still very much a part of my life. Definitely. Well, this is an excellent motivational quote to keep in the back of your mind. And I think it's really helpful to have people who can motivate and inspire you along your scientific journey as well. And oftentimes these people can have a big impact on just the trajectory of your career. So Lawrence, when you look back over your experiences, are there particular role models or mentors or people who you looked up to who really helped

6:14you get to where you are today? There are so many, and I've been so remarkably lucky to work with a lot of really awesome people. My undergraduate advisors, Arjen Dupadmayak, who's at Carleton College, was a physicist. And I kind of knocked on his door a couple of times asking if I could do some research. And at first he was like, well, maybe I'm not sure. I'm not sure. But he took a real risk on me and kind of let me start playing with some code where I had no idea what I was doing, really. And I think even by the time I graduated as an undergraduate, I still was really just getting to the very surface of understanding some of the questions that he was asking in his research.

6:47And having someone who, even though I was so naive, was so willing to spend time with me and engage my curiosity and sort of let me struggle through some of the technical aspects of the research that were just very difficult for me and brought me to scientific meetings and all that kind of exposure really made a big difference for me. And then since that time, so many others, I mean, my PhD advisor, Ryan Hernandez, postdoc advisor, Noah Rosenberg. I also found a home at Stanford in a lab that I wasn't even really part of, but they were so welcoming to let me hang out here in Mordecai's lab.

7:17And in addition to the curiosity that they really fostered all of these different mentors, it's that just willingness, the openness to see that you're engaged in the process and then repay that back to you by their own engagement with you, even though you're naive and struggling to understand throughout. Definitely. And I think having these mentors who are willing to give you a little bit of leeway to allow you to kind of struggle and solve these problems by yourself instead of micromanaging can be really powerful for your learning. Absolutely. Well, it sounds like you've had some great mentors over the course of your career, and it sounds like already in college you were expressing interest in science and research,

7:50but perhaps, Lawrence, we can rewind it back even further. Do you remember when your interest in science first began? When I was in high school, I don't think I really gravitated particularly much towards science. I was really interested in history. I was interested in English. I loved writing. I loved reading. And I think it really took until I got into college to start to have a little bit of attraction to science. And to be honest, the first kind of, I think, attraction about it to me was just that it was hard. And I was a distance runner and I kind of had this mentality that hard things are worth

8:21doing, which I've revised quite a bit since then. I think it's not always true that hard things are worth doing. But I had that mentality. And I think physics just really appealed to me because it was like, oh, this is just really challenging. It really forcing me to stretch my capacity to use my brain to solve problems. And it did. It really pushed me. And there were long nights in college where I was up really struggling with things and then assignments that were turned in where I still not really understood it by the time I was forced to turn something over to the professor. But that process of just being sort of pushed really engaged my competitive side.

8:53But through that, at some point, it also started to really engage my curiosity as well. And so I think that kind of came a little bit downstream of that sort of initial engagement with science through just thinking it was hard and challenging. That makes sense. And I think these undergrad classes can be really valuable for sparking interest in science and right. You're not looking for the boring lecture that you're sleeping through. It is these challenging classes that really grab your interest, I think. Absolutely. Well, I know you have had a particularly interesting path of training or career path where it was pretty multidisciplinary. So I'd love to talk about these different steps along the way.

9:25So after Carleton College, you went into a master's program. Can you talk a little bit about that transition and how you decided what to do next? As you alluded to, it's a little bit of a long and winding path. Towards the end of college, I had been really engaged in physics and I loved the questions. But I was looking at physics graduate school and I just wasn't sure it was quite for me. I couldn't really find a specific problem in physics that I wanted to devote my life to or anything. So I started to think that maybe there were these questions in biology that would be really interesting where I would use some of the similar tools and skills to approach the problems.

9:57But there was more area for creativity of these small teams where you're working on a particle collider or something like that. And I don't have the theoretician's brain to be a string theorist or anything like that. So maybe there was a space for me there in biology. So I really just applied to like every biology job that I could find in the place that I happen to be living after I graduated from college, which was Los Angeles. And eventually someone took a big enough risk to hire me as a lab tech. And I worked in an immunology lab for about two years, really knowing very little when I came in. And that got my hands well, but the process of what it's like to work in a laboratory

10:28and I met a lot of really interesting people. And from there, it really just kind of evolved as I want to combine these biological questions with sort of quantitative tools. And how can I do that? And I really just tried a number of different things and they were not all successes. I did wind up in this. So it was a master's program. It was actually a PhD program that I left with a master's from the University of Chicago. It was a biophysics program and a lot of really wonderful people there. But for whatever reason, at that point in my life, it did not gel with me. And so a year and a half in, I was very unhappy and wound up leading with the master's and thinking I was going to leave science altogether.

10:59And I thought, you know, well, the one thing I really do enjoy here is the computer science aspect, which I've been learning more and more about throughout my trajectory from physics into biophysics. And eventually I'm joining the computer science master's program at the University of Chicago, thinking that I would just go be a programmer. While I was there, I was fortunate enough to work in Carol Ober's lab at the University of Chicago, just what I thought would be a research scientist job. She's a geneticist. And I got really, really excited about some of the applications of computer science in biology and in genetics in particular. And that eventually led me back to go and pursue the PhD.

11:30Well, that makes sense. And to just jump back into that initial master's experience, I think a lot of people have a tough time in their first year or two of graduate school. But I think it's hard to make that decision of when to push and when to call it quits. So how did you decide that this biophysical sciences program isn't for me? It was tough. I really struggled from the very beginning there. It was a tough point in my life. I was living in a different place than my partner in a city I'd never lived in before. And I didn't anticipate how big the challenges would be around that combined with being in a program that was really pushing my limits and not always in the directions that I wanted

12:02to go. I think one of the things with interdisciplinary programs is they often incorporate aspects from very many different fields. And that can be sort of a hodgepodge of things the university happens to already have. And the people who have generously agreed to give their time to help this fledgling program. And it was a brand new program when I joined it. And just not all aspects of it really, really sat well with me. And this was no fault of people involved. I mean, they were all being very generous to give their time. But I didn't really necessarily want to take all of the courses that were offered. And I didn't necessarily want to do the exact set of lab rotations that were forced on

12:35us in the program. And just sort of having that appreciation of exactly being confronted with the reality of what graduate school could be like and was like in that particular case. And then having to decide, is this a time to call it quits? Or is this something that I can eventually ease my way into? And my mental state kind of gradually deteriorated to the point where I just knew I had to step away from it. And I eventually just thought, I've seen enough and this isn't going to work for me. So I'll take a step back. Definitely. And how did you find out about the computer science program and kind of decide to make that pivot? So the lab that very generously took me in at the University of Chicago was an actin

13:09cytoskeletal lab. We were thinking about how cells move around and how they sense their environment, those kinds of questions. And I couldn't get really deep into the research questions. I tried, I tried, and it just wasn't gelling with me. But there was this one aspect, which was writing these little scripts in Mathematica to sort of analyze our data and maybe write little tiny models to understand what might be going on that I really enjoyed. For some reason, it just engaged my curiosity. I could sit there all day and play with it. And, you know, the different parameters and see what happens with output. And somehow that really seemed to reinvigorate some joy in this process of doing science.

13:42And at the time, I wasn't thinking I wanted to go use it to do science. I just thought these are fun little puzzles. Coding is really fun. So why don't I just go kind of explore this computer science thing a little bit more? It seems to be the one aspect of this that I have some skills that I could take from physics that are at least a little bit applicable in this space. And I could learn more. And I could, you know, there's definitely jobs out there for programmers or software developers. And so I'll figure it out eventually. So the university had this program and it was for pre-professionals. It was not intended to be for people going on to do science, but just to go on and get

14:12jobs in the industry. And I applied to it and they selected me and I just thought, here we go. This will be fun. I'll give it a try. Definitely. And at the end of that program, how did you decide that you didn't just want to kind of go into industry, get a job doing computer programming or computer science, and instead you wanted to go get this PhD in bioinformatics? The program was entirely night classes and you could kind of do it at your own pace. So I had this big free chunk of time during the day and I thought I'm paying my way in this program and I might as well try to make a little bit of money while I'm doing it.

14:44I'm going to get a little bit of experience. So I applied to this job also at the University of Chicago and Carol Ober's lab. They were looking for a research programmer and I applied and didn't really expect to be selected, but I had a little bit of biology background and in addition to some of the programming skills. And so I was very, very fortunate. They hired me and almost right away, it wound up just being so fun. I mean, I was sitting with all these scientists who were doing interesting computational things with genetic data, which I had really never had any exposure to before. I was able to start writing a bunch of little scripts, algorithms to try and do things like

15:17analyze how pedigrees would result in particular genetic patterns, things like that. And I just fell back in love with it. And I started to think this is going to be something that I could make a career out of instead of really just jumping back into the computer science, software engineering space. And those questions really reinvigorated my love for science. And towards the end of that program, I was super lucky. So University of Chicago is this place that has this really, really amazing history of ecology and evolution, which when I was a biophysics student there, I was really, I just really didn't even know they existed. They were a little bit across the campus.

15:48I didn't really know much about them at all. But towards the end of my computer science program, they let me take this course with this preeminent population geneticist at the University of Chicago, who was towards the end of his time there, but teaching this amazing undergraduate course. And it was my first exposure to this kind of combination of evolutionary theory with population genetics and with some programming. And that really suggested to me, yes, this is a space where I would like to be. There's a lot of interesting questions here. Genomic data is suddenly becoming really widely available and probably a lot more opportunity

16:20for people who have these kinds of interests to have jobs and make contributions. From there, I was pretty much sold. Oh, very cool. Now, what was your experience like in the PhD program at UCSF? That's a really interesting place. It's a research institution more than it is like a university in some ways, because there's no undergraduates. And while I was there, I mean, the vibe is just so different because the graduate students, you know, and then the medical students are really kind of the educational training focus of the university. So you're not competing with the undergrads for aerospace.

16:51And I really liked that. I had a lot of really close interaction with my PhD advisor, who actually, as it turns out, is only a couple of years older than me. He took a very different trajectory. He went sort of straight, banged through, just a superstar prodigy all the way right through to his faculty position. So in some ways, we were almost life peers, even though I was very far behind him on my scientific trajectory and struggling to keep up with his brilliance. But it was just this place where there's a lot of really fantastic opportunity for graduate students to grow because we were the focus of the educational mission.

17:24Oh, cool. Well, and then afterwards, you decided to go on to do a postdoc and you ended up at Stanford. Can you talk a little bit about your experience there? At that point in my life, I was already married by then and we didn't really want to move around. I didn't want to ask my wife to keep moving around for these short term jobs. So, you know, luckily enough, being in the Bay Area, there are, you know, just a number of really great universities in the area and especially in this area of evolutionary biology and population genetics and genomics. So I applied to a couple of places, but one of the very first interviews I had was with Noah Rosenberg at Stanford.

17:54Stanford and I certainly knew of him because he's just a massive figure in the field. I was, I think, pretty terrified, honestly, to go interview, but he's just the nicest person. And I think we had enough overlap and interest. He was very kind to, you know, invite me to be part of his lab. And it was just another very different place, right? Then UCSF is, you know, it's a massive university. UCSF is massive in its own way, but it feels much smaller, especially on that Mission Bay campus in San Francisco when I was there because the whole neighborhood wasn't even really built out at the time and there weren't that many buildings and everything was kind of close

18:25and you could walk everywhere in five minutes. And Stanford is this absolutely massive place where there's multiple different departments that all do different kinds of biology spread out over this huge campus, undergraduates everywhere. It's a very different kind of vibe. But then when I got into the lab, in a lot of ways, it felt very similar, right? This kind of close kinship with people who had similar interests and all kind of pushing the boundaries of what I could learn and keep up with and benefited so much being in that environment. Absolutely. And I think it's more and more common these days to do multiple postdoctoral experiences. What was that decision process like for you when you were kind of finishing

18:59up at Stanford and figuring out, do I want to apply for a faculty position or should I do another postdoc? What were you thinking? The reality is that I did apply and I applied and I applied and I applied. I think it's not uncommon, but I certainly I think took longer for me than it does for some others. But I think I went through four rounds of faculty applications. I did one very shortly after my Ph.D. thinking that maybe I could just take a quick crack at it and see what happens. I did get an interview, but they were wise enough to realize I was not ready for that. So that was a good experience. But then I think that kind of also made me think like, well, I applied to this small handful of jobs and I got an interview already. So certainly a couple of years in the postdoc

19:31and surely I'll be ready to move on and be very competitive. And it didn't work that way for me. I tried and I tried. And my list of schools was usually pretty small. The first couple of years that I applied, just the ones that were really close to what I was looking for. And then the year that I had finally got my faculty position, that was a much further down the road. But I applied to everything that year. I was like, this is my last job. I'm just going to see what happens and apply to everything. And getting the job that I actually got was a small miracle for me. It was one of the absolute top ones on my list to begin with. And I was really shocked that I wound up working out at that point after so many previous

20:04failed efforts. Definitely. Yeah. I think the job search is just one of the biggest challenges trying to get that first permanent faculty position is very difficult, but it sounds like you found a good fit there at Tufts. And I'd love to talk a little bit more about your current research. So Lawrence, is there a project that you're working on at the moment that you'd like to go into a little bit more detail on and tell us about? Our lab, we work on a number of different systems, as I kind of alluded to at the very beginning of this conversation. But the focal piece of the lab, the central system we work on is this snail system, the Atlantic Slipper Snail, also known as Carpidula fornicata. And it lives all up and down

20:39the eastern coast of the United States. And it's also invasive in a few parts of the globe. So it has some really interesting biology, which I'm happy to talk about a little bit, but I'm not really a Carpidula expert per se. We use it as a system in order for us to think about evolutionary genetics and especially the biology of thermal performance. And we're really interested in this question of how do life stages constrain evolution or do they constrain evolution? So the way that we could think about this is that lots of species have multiple life stages. Insects might have a larval stage and then an adult stage. And in Carpidula, it's similar with a larval and an adult

21:12stage. And there's a complete metamorphosis in between those stages. So the single genome is encoding for these two radically different body plans. And because of that, we might think there could be some constraints on evolution, right? Because you have this one genome, but you have to encode for these very, very, very different organisms effectively at the different life stages. And those organisms have potentially different environments. For the larvae in Carpidula, they're motile, they swim around, and they're really only present for a couple of weeks in the summer before they settle down and then metamorphose and eventually become adults. So they have this kind of warm thermal environment that is all they really experience. And then the

21:47adults are longer lived. They have to go through the winter. So they have this seasonal fluctuations and they're both subtitle and intertidal. So they're experiencing in some cases, quite extreme fluctuations in temperature that they have to survive. So we're interested in that question then of like, if an organism has these different body plans, they have very different shapes and different requirements, and they have potentially very different environments, how does that then affect their evolution? If they have to optimize in order to perform well in these warm waters as larvae, does that then constrain the best they can do as adults or vice versa? So we're doing a variety

22:18of kind of experiments at the organismal level, and then also some genomics to try to tease that apart along with some modeling. Very cool. So for our listeners who might not be familiar with these snails, can you kind of paint a picture? Are they big? Are they small? What do they look like? For anyone who happens to be on the East Coast of the United States and go to the beach, you'll find them quite regularly. They tend to grow on rocks. They're not huge. You kind of made a ring with your index finger and your thumb. They might be at the biggest, about as big as that ring, but potentially quite a bit smaller when they're younger. They're hermaphroditics, so they're all born as

22:50males and then some subset of them will transition to become female at some point during the life cycle. If you find them on the beach, they'll tend to grow in these stacks where at the bottom, you'll tend to find a female. And then on top of it, you'll find a few males growing on top and you can pry them apart. But if you being gentle with them, they'll feel very firm, like they're very firmly adhered to each other. They can move around, but they don't tend to move around a lot once they're adhered to a rock. Interesting. Well, this sounds like a fascinating system to study some of these cool questions and evolution. And I think there are challenges in the work that you're doing. And every scientist faces these

23:23challenges, these struggles. We touched a little bit earlier on just the struggle of finding a job in science, which I think is a big one. But Lawrence, do you have another example of something that you've struggled with or perhaps a major failure in your career that you could walk us through and talk about how you got through that difficult time? Maybe we'll come back to the failure part, but I think just in terms of challenges, I mean, I think academia is often not very forgiving to those who don't immediately fit in in one way or another. And there's all kinds of ways that can be right. Those can be the kind of conversations

23:53we've been having for a long time now in academia about diversity, equity and inclusion can also just be different perspectives. It can be because you don't want to spend your time in exactly the ways that academia wants. I mean, the thing that's so, I think about it to so many people, right, is this idea that you can pursue questions that are so interesting, exciting to you. But then you have to realize that academia also kind of imposes all these constraints. If you're on the faculty side, well, it depends on your university, but bring in funding, advise undergraduates, advise graduate students, teach, do service. And some of those things probably align very well

24:25with your overall goals, what you were hoping to achieve in the position. And some of those things might not align super well with your personal goals, but you still have to do them. And especially at that career stage, when you're untenured, you really don't have a lot of choice in how you structure that time. So you can structure the questions, but you still have to get funding. So you don't have complete latitude there to do whatever you would like. And for us, I think our questions are in this space where there is certainly money to pursue these kinds of questions. There are things people are thinking about how will species evolve in response to climate is a big one. That's very, very important, right? We want to know which species will be able to evolve fast enough to keep up with

24:59their changing environments and which ones won't and how to predict that and how to know when evolution is even important for that and whether it's more just ecology and habitat change and things like that. I think those are all really big, important questions for which there is funding. But the funding landscape has changed recently. Grants are not coming as easily for some people as they did before. I think adapting to that changing landscape and making sure that you're able to contribute what you want to contribute to the field and to humanity, really, you know, whatever your goals are, your big picture goal, you're able to contribute that while kind of living within whatever

25:30constraints in this changing landscape of what academia is expecting out of you is a big, very difficult one for many people and certainly for me, and especially because it's changing so rapidly. And a good chunk of our work is in this space of thinking about education and science identity and how students decide to become scientists. And that work was something we pursued funding for at NSF. And most of those funding avenues have kind of tried up now. They're not so interested in those kinds of questions at the federal government level anymore. So there are big, big challenges there that we're still living through and confronting and trying to figure out how our work can make a contribution

26:03even without some of those resources being potentially available to us. Definitely. And I think your response there also highlighted just the challenge of dealing with the everyday mundane things that you have to get done every day while also keeping in mind this big picture and making sure you're making progress towards those bigger goals, which can be difficult when you just have this mile long list of things that need to be done today. That's right. And sometimes it's not even obvious that you are making progress, even though you think you're doing the thing that you need to be doing. But sometimes it's not obvious. That can be hard. That can weigh on you for sure. Definitely. And you said perhaps we could return to failures as

26:34well. Is there a particular failure story you had in mind? I think the reason this question is hard for me is I'm very persistent. So there are many things I would sort of cast as they were really hard. They were almost failures, but eventually you didn't give up. I'm trying to think of one that was just an out and out failure. And this is really more of a mental state, I think, that I'm trying to push myself into here. I think that honestly, the biggest failure really was my failed PhD program. I came into this biophysics program at the University of Chicago with a lot of energy and hope that like this was going to be the path for me to combine

27:08these biological questions with this physics skill set that I had developed as an undergraduate and just take off and really push myself and be super engaged. And it just wound up not being that. I got progressively less and less engaged as time went on. That's a combination of me and the environment. I don't think you can pin it on either one completely. And when I say the environment, I'm not trying to blame anyone for it. It's just an interaction effect, right? Some environments will work well for some people and less well for others. That environment didn't work for me. And I kept trying and there'd be a little burst, put myself back into it and think, you know, this week I'm going

27:41to push myself. I'm going to do really well on all these problem sets that I've been struggling with. I'm just going to sit down and I'm going to do I did an undergraduate. Just get it done, right? Get it done. Exactly. Thank you for that. But it didn't work. I just got progressively less and less happy. And to this day, I still can't fully explain it looking back. I mean, because there were certainly many things there that should have appealed to me on paper. And for whatever reason, I wasn't in the right headspace to be able to get there. And years later, I would look back and I wouldn't say I would regret it, per se, anything about it. But I would wonder, you know,

28:11was there a way that I could have made that work? And especially given that I eventually wound up in this kind of evolution and ecology space and they had this amazing department on the campus. And then the whole basis of that program, that biophysics program was to take people from the physical sciences and the biological sciences, which are two separate schools, I think, at the University of Chicago and have them work together. And for some reason, I just never found it. And it's been sort of a mystery for me as to why I couldn't make it work exactly. So yeah, I guess I would definitely cast that as a failure and one that definitely sat with me for a long time and left some scars that I've had to work through.

28:45Well, I appreciate you sharing the story. And I think it is so important to reflect on these experiences, figure out what you can learn from them, what lessons you can take away. And I think that's just failures in general. That's something that you have to do to be able to work through it and move on. And I think that's something it sounds like you've been successful understanding what may have happened, how that was just not the right fit or the right environment for you at that moment. And I'm so glad that you found your way back to a path that was working for you. And we don't just want to talk about these difficult times, though, in your career, Lawrence. We don't want to dwell on them. And I'd love to talk about some of your successes, because I think you've had

29:18some big successes to celebrate as well. So do you have a favorite success story, whether it was a big one or just a small but meaningful one that you want to share with us today? I think my two favorite success stories would be my two graduate students, Kestri Lele and Alejandro Calderon, who are both in their fifth year right now of their PhD program. And yeah, they're the reason I come in and do this every day. So just thinking about their progress through our program here and what they've accomplished over their trajectory, it just really means a lot to me. So they're both about to graduate within the next several months. And

29:49Kestri now has her first author paper published and Alejandro has his first manuscript that will be getting submitted very shortly, along with a bunch of subsequent things that we're still working on and trying to get out pretty soon. So just seeing how much they've accomplished and how much they've been able to learn. Alejandro came in as a plant ecologist with very little background in any kind of programming. And I naively thought that that was something that I would be able to through a couple of classes during a little bit here and there, kind of up to speed very quickly. And it took some time for us to speak the same language together and really appreciate what we were trying to

30:21achieve together. But then just watching how his growth accelerated with being able to code and being able to take complex models and analyze them and simulate them and being able to take genetic data and understand something about maybe or at least infer something about the evolutionary processes that have been shaping the patterns of variation in that species. And it's been fantastic to watch. And Kestri came in as a evolutionary microbial biologist, and she's taken this really complex data set from sourdough microbiomes and been able to use some mathematical modeling approaches to

30:52give us some pretty good insight into how community assembly works in that system and why it is that we get certain sets of species that coexist in sourdough and others don't. And then in addition to that, be able to take some of that data and then think about how that system may evolve in the future by using some mathematical models. And it's really incredible to be able to work with students who have that passion and that internal drive of their own to just learn and to push the boundaries of science and have those conversations where they, I think, students just express themselves in ways that faculty don't often and allows for a level of collaboration and conversation that you

31:28don't always get with other colleagues. That, to me, I think is the biggest success. Definitely. And I think just seeing students undergo this transformation almost towards becoming independent scientists, coming up with their own ideas, being independent as they sort of tackle these complex problems can be tremendously rewarding. And I think this story that you mentioned specifically about sourdough, so this was how I came across your research to begin with, but it's very different from the snail work we've talked about thus far. So what is the connection between snails and sourdough? If we're thinking about the framing of what the whole lab does, I came from this background in

32:00graduate school where I was thinking about human population genetics and how variation in humans can be used to understand patterns of disease or trait variation across the globe. And that's a really cool set of questions and things. But the thing about humans, right, is that we can take genomes, we can make predictions about which genetic variants affect things like height or other traits we might be interested in. Height's kind of a boring one, but it's easy to measure. So we have lots of data for that. But we can't at the end of the day do experiments, right? And we shouldn't do experiments for very obvious reasons. We're not going to go manipulate the genomes of people in order to understand whether

32:32these things that we predict actually really work. And ultimately, if we can predict height, sort of to some extent, who really cares, right? It's a nice conceptual problem that tells us a lot about how we can use genetic data, but it's not like a really pressing need for us to understand that in most cases. So I kind of got excited about, well, there's this cool set of questions and skills and tools. But maybe in the ecology space, there's more to be done with these tools. So that's kind of what motivated a lot of my second postdoc and later stages of my postdoc at Stanford was, you know, how can I start thinking about ecology in a way that wraps in some of this

33:04thinking about genomes and genomic variation? And I started out with really just trying to understand what the ecologists were talking about. How do we model population growth? And what are the different dynamic factors that might affect whether a population is growing or declining? And how do we wrap in an environment? And how do we think about species interactions and things like that? So those kind of two different backgrounds are really what motivates everything we do in the lab. And I'd say the big picture goal is for us to take some of those tools and questions from human evolutionary genetics and now apply them in a space where we're thinking about how populations do

33:37grow and evolve in response to changes in their environment, where we can actually do some experiments. We are not helping to do those experiments in humans, but we can do them in snails and we can do them in sourdough. So they're both really good systems for those kinds of questions. On the snail side, it's how do changes in the abiotic environment, so this temperature changes, how do they affect potentially performance and evolution? And then in the sourdough space, it's how does the biotic environment, so how does the interactions between species actually affect those processes? So there's kind of very similar actual conceptual framing for both of those sets of questions, but even though

34:09they are clearly different systems with very different sets of tools that we use for the actual experiments and all those kinds of things. So there's quite a lot of difference in the day-to-day work in those systems, but actually quite a lot of overlap in the concepts. Oh, cool. Well, thank you for sharing this work and telling us a little bit more about your amazing students. And I think in terms of the activities that you do as a scientist, mentoring is a key part of it, but also kind of in the bucket of mandatory activities of an academic is just reading a ton of literature, right? You spend a lot of your time reading papers, but we try to encourage our listeners

34:40to also read for fun to pick up a book when they can. So we love sharing book recommendations with everybody. So Lawrence, do you have a favorite book that you've enjoyed, whether it's related to science or not, that you want to share with us today? This is a textbook that got me into population genetics, and it's the book that was used at the University of Chicago by Dick Hudson, who taught the course that I took. It's called Population Genetics, A Concise Guide. It's by John Gillespie. And it's been sort of the standard, just like undergraduate, here's your first intro into the field kind of book. It's a little outdated in some

35:13ways. It's before the introduction of genomics, it's thinking about much more sort of modest scale genetic variation in some ways. But to me, just the way that the concepts are laid out in the book, it's what really sucked me into the field. It's just such a nice intersection of evolution and thinking about natural patterns that are happening in real species, but then with a little bit of math, not an overwhelming amount, but enough to kind of get you started and relating those patterns back to the math. And I really thought it was a fantastic book. It's one that I still have sitting on my

35:43shelf here in my office. And in fact, I just took it down to look at it while I was talking to you. So it's one that means a lot to me and I certainly enjoy. And if you're interested in a book that's free, Graham Coop with the University of California, Davis writes a population genetics book for undergraduates. That's just a free PDF online that I would recommend starting with the Gillespie if you can find it from your library or anything. But Graham Coop's book is this free PDF you'll find on his website. And it's just a fantastic book that goes a little bit deeper into a lot more contemporary things.

36:13Well, excellent, Lawrence. Thank you for these recommendations. We will add these books from John Gillespie and Graham Coop to our website for our listeners to find. And we talked about a variety of different aspects of the work that you've done over the years. But I think one of the things that's really wonderful about science is that you get to travel quite a bit, whether it's kind of going to these different institutions for different stages of your academic training or conferences or working with collaborators. So Lawrence, do you have a favorite place that you've been able to travel to for science? I was very fortunate to get an email from someone a few months ago inviting me to apply for a conference

36:45that was at the Biological Society in London. So the Linnaean Society. This is the society that Darwin and others were part of and sort of the founding of the field. It's a beautiful old London building that sort of evokes all those feelings of here's this rich history of this field. You can really feel it inside that building and portraits on the wall and all those sorts of things. And to be honest, it really did bring out a bit of imposter syndrome for me to be there and try to give a talk. And I think it was probably one of the worst talks I've ever given before in my life.

37:16But it was just such an amazing experience to be there in this space that has this rich history and in the middle of this incredibly cosmopolitan city that blends the old and the new so incredibly well. And I'd never been to London before. I was only there for one day, basically, to give this quick talk and then come back. But that was really a remarkable opportunity, I think, to be there. So why didn't you extend the trip to do some sightseeing, I have to ask? I wanted to. I wanted to very badly. But I think, as I said really early on, I'm a family guy and my kid had a soccer tournament. So we ultimately decided to just

37:48go right back and go to the tournament. So it's a rage I liked at a tournament. But yeah, I do hope to go again at some point in the near future. Absolutely. We'll put it on your travel list for later. That's right. This sounds like an amazing experience being able to kind of walk through these storied halls of the Linnaean Society. I think that's absolutely remarkable. And I think in science, not only do you get to go to cool places, you get to work with some really amazing people. We've kind of touched on this throughout our conversation, just the amazing students you've worked with, the great mentors you've had. And that's not often the reputation that scientists

38:18have in the media. There's these stereotypes that people still have and these ways that scientists are portrayed that are just not true to life. So we try to break those stereotypes by talking about the human moments, the funny things that happen, the creative people you meet and the quirky traditions that may spring up in different labs. So do you have an example, Lawrence, of one of these human moments in science that maybe goes against the stereotypes that people out there may still have? I wish I had a specific example, but what I'll just say is in my computational biology class. So this is a class that's taught for undergraduates at Tufts, and there's no expectation

38:51of any coding coming into this class. And my goal with this class was that students would be released from a little bit of that anxiety they feel when they step into a computer science class. And not everyone feels that, right? Some people are very at home there, but there are students who are anxious about math or about coding, and that anxiety can then be a barrier to them getting what they want out of those classrooms. And some students don't then have the opportunity to really learn some of those skills when they might actually really enjoy it if they were able to engage in a way that was more productive. So that's a huge goal of the class. And one of the ways we try to accomplish that is by bringing in counter-stereotypical kind of images of

39:26scientists. And we do that just really, I mean, it's not that hard, right? There's so many people in our field who don't align with those kind of stodgy old stereotypes. So what we do really is we just bring in the work and portraits of individuals. And sometimes the students read their actual academic work a little bit. Sometimes what they read is an interview with them or a podcast that they've done in the past, or maybe an opinion piece that they wrote about something important to them, like their own trajectory through science. And I find that those kind of experiences of having students engage with science in that way just changes their perspective on what they can get out of the

39:59classroom. I like as much as I can to try to make the expectation that we're not there in classrooms just to get through a curriculum and like a list of topics, because that's what's really the important thing. But that there's a human side to science and that we're trying to embrace that human side more than we are anything else. Like, why are we doing this? Why are we curious? What brought us to these problems in the first place? And that has effects not just on our own interpretation of what we're doing, but then also just on who gets to do things, right? And what things get studied. So in those more stereotypical views of scientists, if we looked historically back,

40:31the more science is controlled by neurodemographic groups, the more the interest and curiosity of those neurodemographic groups are what drives the things that we do. And that could mean that certain diseases don't get studied. That could mean that certain questions are framed in a very particular way. That could mean that there are assumptions that are made that are not very good. And so that's not to pick on any one particular group. I suppose we could, but that's not my aim really in having those counter stereotypical narratives in the class. It's more to just say there's many perspectives and those different perspectives all bring value. And those counter stereotypical

41:02narratives, they're not just valuable because people have differences, but also because those differences really enrich the science itself that we are doing. Definitely, Lawrence. I love that you incorporate this into the classroom. And I'm curious, was there someone that you met maybe early on in your own scientific career that helped really shatter that stereotype for you? I'll go back to my undergraduate advisor, Argandu, who he was just so welcoming to me. And in some ways, he was the stereotypical physicist because he was so quirky and he was so interested in these esoteric problems about nonlinear dynamics and stochastic resonance or decoherence in quantum

41:36physics. So in some ways, I was like, oh, yeah, this is what I was looking for. This is the stereotypical scientist. But then it turned out he really wasn't that he had all these other interests. He was interested in music. And even though he was quirky, he wasn't awkward, right? He was someone who could just talk and talk and talk and talk and talk. And that was not what I was really expecting, I think, from a physicist. And he brought me to these meetings where there were many different physicists, all with lots of very different personality traits and things. And just seeing that range of different approaches to science, different mentalities. Some people were obsessed with their science to the point of just doing it around the clock. Others had very balanced

42:11lives, right, where they're spending time outdoors or spending time on hobbies or spending time with their families. Being able to see that kind of range of different approaches, I think, through the lens of his perspective on physics. That definitely was influential for me. Awesome. Well, I appreciate you sharing that. And I think these different approaches and personalities and perspectives and backgrounds can be really helpful when you're trying to solve these big interdisciplinary kinds of questions that you're tackling in the work that you do. So we love talking about the big questions that remain unanswered, Lawrence. And if we took away the

42:41barriers that would normally hold you back from answering them, whether it's funding, staff, technology, feasibility, time, number of students you have, whatever the case may be, and we gave you everything you could dream up, is there one particular question that you would most want to answer? That's just not how I think about science is what I would say. So I get excited about science through the excitement of the students and through the excitement of my colleagues. And yes, I do have questions that tried me and motivate me, but I'm not sure there's one single one where I'm like, I really need to know the answer to that

43:12question. And if I could just reallocate the world's resources to knowing the answer, then I would die happy. I think about science almost in the exact opposite way of like, we have a very limited set of things that we can actually use. I know we don't have that much money. You know, we're at a very privileged position here at our research university at Tufts, but that's not a ton of resources. And what's the most we can do with the least is often how I think about science. And in many ways, there's just so much you can do with just a computer in your curiosity, right? Or just a pencil and paper in your curiosity. And sometimes that winds up being

43:44something that isn't novel, right? Like you've spent all this time thinking about it. You're like, this is a really interesting question. I'm like, as far as I can. And then you figure out the whole thing. And then it turns out that actually this wasn't something that the field really needs to know because it turns out there's a bunch of literature on this. If I had only figured out where to look in the first place, I would have known that. But I think really what we're trying to do, right, is to think like with these very limited resources, with our curiosity, what's the direction we can push things that will be beneficial for the field. So I guess I think within the realm of those constraints, much more than I do in that unconstrained space.

44:18That said, the field of evolutionary genetics, we've spent like a particle collider's worth of money on GWAS, basically, on genome-wide association studies that, you know, are all these different traits, largely in humans, but also in other species as well. Now, you know, Arabidopsis and mice and even in some non-model species to some extent. And that tells us a lot about the genetic basis of some traits with some caveats, right, that we can't always interpret that data as well as we would like. But what I would really love for the field is that we had a better way to take all this data together and somehow synthesize it and really say what we have learned and what we cannot

44:49learn from this data. I think we keep doing this kind of study with a fairly limited set of tools, and there's been some advances there on the tool side of how we do these studies. But how could we integrate all this data together to really understand what evolutionary processes are shaping traits, why certain traits have higher heritability or lower heritability? How do we even think about heritability in evolutionary context? Or can we throw out heritability as a concept altogether? I think those are some of the big questions that do occupy my brain space. And I think I'll die very happy if I never know the answer to some of those questions. And it's not the thing that I need to

45:20know the answer to. But for the field, I would love to see us sort of stop throwing money at something that seems to be a little bit of a black hole and potentially reallocate some of those resources to understand the data we already have a little better. Absolutely. I think being able to bring all of the data, all the different studies over time together to identify where the gaps are even, what do we know, what don't we know would be tremendously valuable. So I appreciate you sharing that with us today. And you've shared so many insights throughout our conversation, but we'd love to end with advice. I think for our listeners out there, it can be helpful to hear from scientists who

45:53have walked the path already. So do you have a particular piece of advice that somebody gave you, Lawrence, at some point in your career that really helped you and you want to share with listeners today? Throughout my trajectory, the thing that my role models and mentors have modeled for me is this determination to follow their curiosity. So I think we often hear you follow your curiosity, and that's great. That can lead to a lot of wonderful things. You also can have curiosity as a hobby and not a career, right? Where you read and you engage in science or whatever else in the world

46:23you're curious about without having it be a thing that occupies your working life. But I think the thing that my mentors have been modeling for me is that it's not just following your curiosity, but then it's having a bit of determination and passion to advocate for why you think these ideas are important in addition to just doing the work. And that's something that I honestly struggle with a bit because I'm very much an introvert and I'm not going to be the person out there advertising, screaming to the world that what I'm doing is super important. But then seeing how the folks that I've worked with in the past, when they've gotten critical reviews or when they've hit a stumbling

46:57block in some way, a cramp wasn't funded or something, they didn't give up, right? They thought, you know what, this thing that I care about that I think is important and I think is interesting, I really still think it's very interesting. I'm not going to be dissuaded by the fact that somebody said it wasn't as exciting as I thought it was. I'm going to double down and I'm going to find a way to get this out so people can appreciate it. And I think largely when they do that, people are often successful. They're not always successful, right? There's plenty of ways that can go wrong. But I think it's sort of a basic requirement in science, right? If you really want to make it a career is that you have that curiosity, then you also have the ability to be a little bit

47:31determined with how you pursue it. Absolutely. Because I think no matter what direction you go in science, you're going to encounter obstacles. So if you're always giving up and turning tail at every obstacle, you're never going to make it very far. Totally agree. Well, I think that's wonderful advice. Is there any other last piece of advice, Lawrence, or a last note of inspiration that you want to end our conversation on today? I will say that there's a lot of paths to do science. And so if you're excited about science, I think that can be a career. It can be a hobby. And I think anybody who's really excited about it, I hope you find the way that you can bring joy to

48:03your life through science, because it's just something that opens up so many doors. I'm not talking about career doors. I'm talking about just engagement with the natural world or engagement with our own experience through life and this planet. I think it's a way of thinking that is just very enriching throughout life. So if you're looking for it, I hope you find it. Well, Lawrence, I love that sentiment. I appreciate everything you shared with us today. If our listeners want to learn more about you and the work that you do, what is the best way for them to do that? Yeah, our lab website is my last name. So u-r-i-c-c-h-i-o dot github dot i-o. So my last

48:36name dot github dot i-o. That's probably the best spot. Excellent. Listeners will definitely take some time to check out Lawrence's website. Lawrence, it's been such a pleasure to have you on the show today. Thank you so much for your time. Thank you so much for having me. It's been a real pleasure. It's been wonderful to learn more about you and your work and listeners. Always great to have you here with us as well. We hope you join us next time for another episode of People Behind the Science.