The Bioinformatics CRO Podcast

Episode 48 with Alex Shalek

Alex Shalek, Associate Professor of Chemistry at MIT, discusses new methods and technologies in systems biology that have enabled advances in the diagnosis and treatment of autoimmune diseases and cancer. 

On The Bioinformatics CRO Podcast, we sit down with scientists to discuss interesting topics across biomedical research and to explore what made them who they are today.

You can listen on Spotify, Apple PodcastsAmazon, and Pandora.

Alex is Associate Professor of Chemistry at MIT, where his multi-disciplinary research aims to create and implement broadly-applicable methods to improve prognostics, diagnostics, and therapeutics for autoimmune diseases and cancer. 

Transcript of Episode 48: Alex Shalek

Disclaimer: Transcripts may contain errors.

Grace Ratley: [00:00:00] Welcome to the Bioinformatics CRO Podcast. My name is Grace Ratley and I’ll be your host for today’s show. And today I’m joined by Alex Shalek, who is a faculty member at MIT, the Ragon Institute and the Broad Institute. Welcome.

Alex Shalek: [00:00:12] Thanks so much for having me, Grace.

Grace Ratley: [00:00:14] Yeah, it’s great to have you on. So your research is incredibly multidisciplinary. It spans fields such as microbiota research, cancer, immunology, nanotechnology, engineering and genomics. Can you tell us a little bit about how you tie these fields together?

Alex Shalek: [00:00:31] Oh, it’s a complicated question. I think that we’ve ended up spanning a number of different disciplines just because it’s necessary for the kinds of questions that we want to ask. If you asked me when I was an 18 year old, if I would be a faculty member studying the things that I’m studying now, I would have thought you were crazy. In college, I focused on chemistry, physics and math and actually originally went to graduate school to do some theory work. And due to a series of different events, ended up doing Nanobiotechnology, which got me into immunology and then into systems biology and then very concerned and confused by sort of heterogeneity among cells, which took me down this rabbit hole. And what it really taught me at the end of the day was that I had to be very careful when I was looking to system to make sure that I understood all of the components to measure as many of the components I could. I didn’t necessarily have the background to assume what was the most important factor. And so I just got very interested in how could we comprehensively profile as many things as was possible, understand how they might be working together in synergy, just so that there weren’t really those blank spaces in the microscope that could be incredibly important that we were just missing. And so you start studying for example, the gut and all of a sudden there’s this incredible amount of diversity among the microbiota that’s in your gut so it’s this big missing piece.

[00:01:52] And so you have to look at it in combination with some of the cells that you want to look at. Then even just thinking about the guy, that’s one part of your body that interacts with many other parts of your body. So you start to think about the assumptions that we make when we focus on any specific thing. It just made me uncomfortable. It was one of those things where as we started trying to be more comprehensive, we naturally had to bring in principles from lots of different places. One of the fantastic things about being in Boston is just the strength of this collaborative ecosystem where you can work with partners in genomics, at the broad immunology at the Ragon, all the different engineering disciplines at MIT, some incredible teams over the hospitals across the river. And we’ve just tried to take advantage of that, working in these collaborative networks to do things that would be hard to do in other contexts. I constantly get reminded of how little I know, but it’s also incredibly exciting because you’re learning new things every day and seeing things in the intersection that you might have missed otherwise.

Grace Ratley: [00:02:48] Going from theory to where you are now is I mean, those are two very opposite things because I mean, theory is pretty hands off and now you’re all applications and hands on. But still trying to understand the bigger picture. It’s really amazing how you’ve brought those two things together.

Alex Shalek: [00:03:03] It’s funny, I’ve ended up in a similar place. When I was going to graduate school, I’d really like the idea of theory because I was told that if I had an internet connection, I could work anywhere in the world as long as I could send along my research and make progress during my PhD. And then in the work that we’ve done, it’s become increasingly global, collaborating with people on six different continents and multiple different countries. And so the travel has become a big part of what we do, as has the international collaboration. But it’s very different than I originally envisioned, sort of this remote science being.

Grace Ratley: [00:03:33] Yeah, certainly. And we have the bioinformatics here. We’re very familiar with remote science. And then back on your research, like this concept of understanding all of the tiny pieces of the system really ties in with your research associated with single cell sequencing. Can you tell us a little bit about the developments you’ve made in single cell sequencing?

Alex Shalek: [00:03:56] Yeah, of course. Happy to. We’ve just been a part of this. I think that there’s been this incredible effort among the community to develop a number of the different technologies that have now become standard and applying genomics to single cells. I happen to be at a very fortunate place and there was a moment of one of those things that serendipity. I wouldn’t say it’s purely fortune because you have to recognize the opportunity. But on the other hand, it was definitely in the right place at the right time. For me, through some of the technologies I developed with others in Hong Kong, Parkes lab and graduate school started doing some immunology and we were doing these genomic assays and they were really cool because now you could look at all of the genes. I didn’t have to pick one or two that I thought were really important. But as you know very well, whenever you’re doing genomics, you do these guilt by association analyses and you use correlations and you infer what networks are. And really what you have to do after that is you have to go back and systematically test your predictions through different perturbations.

[00:04:50] And unfortunately when I started doing these perturbations with others to try and understand whether the predictions we were making were in fact correct, I just see that every single cell was looking at looked a little different. They would express different levels of RNA as I thought were important or the protein abundance would be different or it would be localized differently, but cells just wouldn’t look quite the same. Or we’d be trying to kill all of a cancer and we would find that we could only kill some of the cells. So there was just this heterogeneity that I didn’t understand and where I was coming from and that chemistry, physics and math background. I had this idea that if you put one input like one drug on one system, it should give you one output. And so when you see that you’re getting this variety of different responses, it was really unsettling. And so in some of the work that I did in my postdoc with a number of others around the community and this large cloud project, I got very interested in trying to figure out whether or not there was any information in this variation. We could assume that all the cells are the same or just like scientists, they’re all scientists, but they all are very different. And if you just took the time to get to know each and every one of them, you might begin to understand a little bit more about the subspecializations and the things that go in their training.

Alex Shalek: [00:05:58] And so I did what at the time was a relatively insane postdoc trying to sequence individual cells, trying to just see if what you could measure was actually biological. And then even above and beyond that, if there was any information in it because you could have imagined it was just all noise due to the stochasticity of gene expression. Long story short, we profiled some cells and we started looking at sort of variation. And what we found was that there was actually a lot of structure in gene expression covariation. What that told us was that maybe there was some biological signals that we could pull out of this very complex data. And we went on to show that some of this derives from differences in cell states, and that derives from differences in cell circuits. Sometimes you have differences in subcellular processes. And when I think back on it, it’s not as surprising as you might think because what we’re really saying is that different cell types have different accessible regions of DNA and different proteins. And so they’re going to produce different transcripts and it’s going to look like these major differences. But at the time, the idea of sequencing like 0.1 picograms of RNA just seemed relatively nuts for lack of a better way of saying it. And once it turned out that there was going to be this hidden trove of treasures and looking at single cells in the same way you might think about like looking at people in any country. And then rather than just looking at like the average, they have 1.8 children or they have a median income of 50,000, like looking at each individual one and associated variables, we’re like, wow, there might be something really transformative we could do here.

[00:07:24] And so even though we started off with a really small number, we always were like, Oh, well, we’re probably going to have to hit these huge numbers and really get power. We’ve got trillions of cells in our body, how are we going to start doing the science that we want to really understand what’s happening there, to understand what’s happening in different bodies, to understand what’s happening in different diseases. And so from this initial demonstration that we did with a number of people around the Broad Community, it spurred us into this charge to try and develop technologies that would help us scale, you know, partnering with people originally on the West Coast at Fluidigm, trying to use microfluidics and then trying to develop things that worked on droplets here in Boston with a number of people across different institutions and different backgrounds ranging from computationalists to incredible experimentalists.

Alex Shalek: [00:08:08] It was just this group of people coming together to try and figure out how we could do more. And then from there,I got really interested for some of the stuff we were doing in our work over at the Ragon and how we could make these things more translationally oriented. I really like some of the basic biology, but my home department at MIT, I’m sort of joint appointed between the Institute for Medical Engineering and Science and the Department of Chemistry with affiliation at the Koch. But IMES really is sort of that bridge department between Harvard Medical School and MIT. So there’s really this biomedical engineering approach facing out into the community, trying to think about medical problems. And through my connection with the Ragon, where we were focusing on infectious diseases and kept on thinking these tools are really powerful, but they’re not addressing real world problems. They’re not having a major impact on human health. So one of my good friends and colleagues, Chris Love at the Koch, we tried to simplify some of the technologies to make them easier to use, limit the number of peripherals, make them simplified. And it turned out that was broadly enabling. And so we started teaching others how to do it. And all of a sudden, we were engaged in partnerships all around the world trying to apply these same technologies to address problems that are of global significance, but very often don’t get the same research time either because they’re not problems here in the United States or because practical parts associated with actually studying them is just daunting.

Alex Shalek: [00:09:29] Like the idea of doing a study of Ebola, which we recently did with a couple of people down at Fort Detrick, the idea of doing genomics on a BSL-4 pathogen in vivo infection like it was just really hard to figure out how you would make that all come together. But given this community as challenges arose, we just had the opportunity to pull from all of these incredible scientists that were around us and start to think about collectively how we would start to begin to tackle these things. A lot of that’s been great and it’s been nice to see the entire community come and start doing similar stuff in the context of COVID. If there’s any silver lining to what’s happening right now, it’s that so many people are working on similar problems, bringing together different vantage points and different trainings to really try and make substantial inroads simultaneously and open sharing of data of ideas. And hopefully it’s a model for everything going forward because I feel like it’s amazing what the scientific community can do when they come together as a collective to try and tackle problems.

Grace Ratley: [00:10:24] Yeah, I think the research really addresses this problem of accessibility with things like sequencing and when sequencing was first available, it took years to sequence and it was incredibly expensive and only two labs could do it. And the cost of sequencing came down a lot and more studies and more publications and more research and everyone working on these problems together. And you’ve really through the development of SQL, your single cell sequencing platform, you’ve kind of made that sort of research available to more scientists, which hopefully will enable more reproducibility within science and the consideration of all of the cell differences in systems research.

Alex Shalek: [00:11:09] So I hope it does. But it’s not totally selfless. What we’ve learned from doing all this stuff is that it’s important to develop tools and then to give them to people, make them accessible and and see what sort of the failure modes are, because that actually gives you insights into what the next generation of tools are. So I’ve been a big believer in this idea of you find biological problems, you try and figure out how to address them, use tools that exist. But if there aren’t good tools and you go work on new tools and then you apply the tools and you figure out what they can teach you, but also why they suck, for lack of a better way of saying it. And so I think this has been a constant point in the science. We’ve done in a number of others. And so even thinking back to some of the early three prime barcoding work that was done to make massively parallel sequencing happen in dropsy, Evan Macosko and Steve McCarroll and others did this incredible job of creating resources and putting stuff out and making everything accessible to the community and having help lines. And so in a lot of those things, we were trying to follow sort of best practices. But as we saw and heard that there were needs obviously pushed us to try and figure out how to make it simpler and easier, to make it easier to move to a clinic, to make it easier to move to another country.

Alex Shalek: [00:12:19] I think one of the things that is not lost on me is that there’s been this tremendous advance in the molecular techniques that we’ve been able to use over the last little bit. And if we think about where we were a little bit ago and where we are now, if you think about our ability to edit and manipulate the genome and our ability to record and profile single cells, I mean there’s just been this quantum leap in what we can do both on the measurement and perturbation scales. But on the other hand, it’s also created increasing inequities in the science. And that’s because as you were saying, it used to be two labs that could do these things and now more labs can do stuff. But there really is this incredible concentration of some of these techniques in places like Boston and San Francisco and parts of the UK and others. It doesn’t mean that others can’t do it. It just means that the rate at which science accelerates in some of these regions is different than in going and working with partners in other parts of the world. You began to see how important the problems were. You know, but it’s not really tangible until you go visit. I remember that Bruce Walker, who is the co-director of the Ragon, took me down when I first started at MIT to Durban, South Africa, to Cape Wrath, which is now the African Health Research Institute to see what was happening in research there, to go out into the community, see these places that were hit very hard by the HIV pandemic and by tuberculosis.

Alex Shalek: [00:13:36] And just to see like what sample collection looks like, what were the questions that scientists were trying to address locally. And it’s this incredible facility. It’s beautiful. It could be the same thing that you would have in Boston, and it stands it stands out in a lot of ways. But on the other hand, it just helped me to understand if we wanted to really deliver on the things we were writing in papers, like this is going to be a transformative technology like what it would actually take to make it a transformative technology. Met a bunch of great people there, you know, bonded with them, and started trying to figure out what does it take to really move the needle, to move these technologies there, to make it so that these research questions that are incredibly important, that aren’t getting the same attention as they should have the opportunity to really be pushed. And you might say, well why don’t you just do it all in Boston? A big believer that you have to create local capacity and empowerment and create an entire community and get many people involved, as I said at the beginning, like have some training in various places.

Alex Shalek: [00:14:31] And I’m sort of a jack of all trades, master of none. But the idea that I was going to all of a sudden tell people that were working on HIV research, that were these incredible luminaries that had these years of expertise, exactly what to do is foolish and ridiculous. And so it’s really about going down there, creating partnerships, figuring out what they need, going back and forth and trying to get people up and going. And so from that, that spawned into a number of different partnerships all around the world. But really, I feel like these technologies are as good as they are if we don’t bring them to bear on the problems that are important. We don’t make them accessible to everybody. It’s really not going to put us in the position that we want to be. And I think that another thing that the pandemic has taught us is that these things affect all of us. And it may be something that you previously could have said, oh, this is a remote thing that sits in some area. And maybe you read that one case happened in the United States. And something else I think back to like some of the Ebola outbreaks. But I think what this pandemic has taught us is how connected and interdependent we are and how important it is to not just focus on our local problems, but to also think about the importance of solving global ones simultaneously, whether it’s supply chain issues or vaccine creation issues or surveillance issues.

Alex Shalek: [00:15:37] And so excited by a lot of what these things have done. But it keeps on pushing me to think about how do we reach more people? How do we create more capacity, how do we get more people engaged in this and like I said, it’s not fully selfless. It’s one of those things where as people tell you this is why the technology has a problem. This is like the computational problem that we just need to solve. It’s an incredible substrate for research. I mean, there’s been really cool stuff that we’ve done over the last little bit along with others and trying to figure out how to use sequencing of single cells to figure out host pathogen interactions and co-dependencies. And a lot of that stuff comes out of conversations where people are saying, well, I’d love to know how the virus is hijacking some the cells. And you’re like, Oh, well, that’s a great computational problem. Why don’t we go try and put a little bit of time into it? And so I think what I’m trying to say and what I’m trying to emphasize here is that yeah this stuff is super powerful, but there’s this incredible value in networking and collaborating with the entire community, taking advantage of all of these people that think in very different ways and that can push you to tackle problems and to address things that are bigger and more important than you could have ever imagined.

Grace Ratley: [00:16:39] Yeah, and I’d really like to talk a little bit about your five step approach to studying systems biology like you do. Can you tell us a little bit about that?

Alex Shalek: [00:16:51] I think that my strength as a scientist if I was trying to be critical, is it’s this ability to merge together different fields and see how they’re going to mesh and understand particular problems and understand synergies. And I think in a lot of places, some of the ideas that I have in my head are very hard to bring across to others. And so in some places I’ve tried to distill some of them down. I mean, if I really think like fundamentally about what our lab is interested in and what we’re interested in is homeostasis in tissues. And so coming from chemistry and physics, like the idea of homeostasis or equilibrium is like this very basic concept that you would have been taught in high school and even potentially before that in like seventh grade science, Like you understand what that means. But if I ask you to say, what does homeostasis mean in a tissue? Like what does that mean? Like, what are the cells doing? What are the processes? Who depends upon whom? Like in the same way that you might think about your community, like what does it mean for it to be this state of of dynamic flux, but also stability? It’s this really hard concept. And then you might say, well, what are the things that disturb equilibrium? Well, those are the things that drive disease. And how can environmental factors whether it’s an infection or a high fat diet do that? And then you might ask yourself, well, how do you make a community more resilient? And those are things that we’re interested in, the questions that we want to ask, but the language to describe these sorts of things is very nebulous.

Alex Shalek: [00:18:08] I mean, I think there’s a lot of stuff we can learn from the social sciences and from what people have done in ecology. But there’s this approach to thinking about cellular communities that is hard to bring about. And I think similarly when I think about how we like to approach tackling problems, it’s hard to explain it perfectly. I don’t like to be too reductionist because I recognize sort of the multitudes. But on the other hand, it felt like it was easy to say, well, let me think about this in five pieces, that map very nicely, that chemistry and physics, which is like in chemistry and physics, we have this periodic table. We understand what the elements are, right? And so in biology, we really need to understand what the elements are. And so we always think about what are the identities of the cells in our systems. And we’re obviously not alone in this.

Alex Shalek: [00:18:50] There’s this entire grassroots international movement led by Sarah Teichmann, to do this human cell atlas that involves thousands of individuals across multiple different countries and continents and there’s a number of people that are interested in it. Once you know that there are differences, once you know that there are different elements of the periodic table, you might say, well, what are the characteristics that define those differences? And so we know if we look at the periodic table, it’s the number of protons and neutrons and electrons. But when you think about cells, it’s not quite so easy. And so you might say, well maybe it’s the epigenetic state, which could mean accessible chromatin, it could be marks, it could be methylation, it could be TCR sequence, it could be specific proteins. And so we’ve always thought about this first step of saying like, what are the things and then what are the things that differentiate them? So what are the identities and then what are the characteristics? But a lot of what is critical in biology, or at least in the human biology we like to study, is that these cells don’t work in isolation. We are very different than 10 to the 14 cells just hanging out in a pond. We have many different cell types that have these evolved social contracts where they’re dependent upon one another and we’re different, you and me. But we have roughly similar cells sitting in roughly similar places to a first approximation.

[00:20:03] So you have to start to think about these things that you would think about in the social sciences all the time. Well, how does where a cell sits influence its behaviors? And so we like to think about those environments, those fluxes, like what is the milieu which could in this case be like cytokines and chemokines and metabolites. And then we like to think about like, well, who do cells talk to? So much of what’s important in immunology, for example, is conversations among cells, whether it’s an antigen presenting cell, activating a T-cell or something along those lines. And so you might ask yourself, well what are the interactions that exist? And in physics and chemistry, these are the coupling constants, the way in which different things link to one another. And so it’s very intuitive. And then you might say, well now that you’ve started to think about what are the pieces and what are the things that define them. And what do they sit in and who are they talking to? The question really becomes, well, as you start to scale that out and you start to think about it, what is the integration of the synthesis of that? Like how do you get communities and what are the things that drive it? And then you start to say to yourself, Well, when you look at it like this and you recognize that there are things that are going to drive disease. Can you begin to think about what it is that’s going wrong? Is it like that you have too many of one particular cell type? Is there some sort of failed communication? Is one cell not doing its job and another cell is trying to moonlight and so it’s not doing its job as well.

Alex Shalek: [00:21:20] And so those are the sorts of questions we like to ask. And so five steps, it’s one way of thinking about it. But at least when I’m trying to describe to people like holistically, this is where our head’s at. It works. But then there are so many places where you could be like, well, the technology that you’re talking about, is it really this or this? Because you might say, well where are cells in space as a characteristic? But on the other hand, you could say it also tells you something about who it interacts with. And so it gets fuzzy. But I think having some mushy frameworks or some lampposts are a good place for people to begin to say, Oh, well I kind of understand what you’re talking about and where your engineering towards.

Grace Ratley: [00:21:55] Very interesting to me at least just to see it written out because I think a lot of us think about it, but we don’t necessarily put it on paper. So I really like that.

Alex Shalek: [00:22:05] It’s so hard to put on paper. We spent so much time like sitting there going back and forth, Are these the right words? This is the right way of doing it, because you’d be like, Here are the million and a half ways in which this falls apart. And at a certain point, you just have to be like, Look, this is not perfect, but let’s put it out there. Let’s get feedback. Let’s see how people feel about the ideas and the way in which we’re expressing them. And in the same way that you’re doing science and you’re getting feedback on the science you’re doing, same idea here you put out like this is the framework we’re thinking about and we keep on refining it and trying to get to it. And some times people will be like, Hey, this is what we’re thinking. And then you’re like, Oh, well, that’s a much better way of thinking about it. I don’t know why I did that or I like that concept or that word. Let’s try and fold it in. I think it’s all about the synthesis, but you have to put some ideas out there and be resilient and listen to people and hear what they have to say, even if it’s not necessarily the greatest things about the way in which you’re thinking about something to begin.

Grace Ratley: [00:22:55] Yeah, it’s really great. And you put a lot of thought into how you display your research. I have been a fan of your website since I saw it like a year ago. I think everyone should just go and look at it because you have put a lot of time into thinking about your approach to research the way that you frame the different components. And also I really enjoy the section on mentorship and diversity.

Alex Shalek: [00:23:19] Well, it’s not just me. We’re very lucky. We got connected with Dirk and Sigrid at SciStories and they helped us to do a couple of different things with graphics in the past. And then we were thinking about how to describe our science and put it out there and explain it. I think that one of the most important things about science is accessibility. I feel like if you can’t explain what you’re doing in a way in which somebody understands it, if you don’t understand it that well, and I think many people like to make science really hard so that they seem very smart. But when you deeply understand something, you should be able to explain it in a simple way and you should be able to explain the nuances, but you should be able to give a concept across. And I know that it’s so hard because we’re so trained to be very precise and not to let things be squishy. And I think that in a way that’s been a problem during the pandemic when people have come for information, because even my parents have ask me things and I’m like, well I’m hedging and I’m saying these various things and they just want to know should I be double masking or what should I be doing? Or is it safe? And so it’s pulled me maybe a little bit out of my comfort zone in some places. But I do think that making science accessible and making it so that people can understand what you’re doing, give feedback, give thoughts, get engaged becomes critical to this entire thing. We were talking about before this idea of doing stuff as a community, learning from the collective expertise and knowledge of different people.

Alex Shalek: [00:24:27] So we spent a lot of time on building pieces of the website and actually we’re due for a refresh. I’m about to start doing some new stuff now because the lab has evolved and when we started we really were going to do some model system work and all of a sudden, we’re doing a lot of global work in infectious disease and cancer and various inflammatory conditions. And a lot of the things we’ve done relate to outreach and empowerment and some of the stuff that I’ve done with others through the Human Cell Atlas is really focused on aspects of that helped to co-lead the equity group. And so there are new things we have to put up there. We have to do a better job of explaining who we work with around the world, making space and championing their voices and saying, this is the science that they’re doing and it’s great and showing where they are. So we could do better with that. I think that tried to create a lot of resources, but we could do a much better job in making those accessible, putting educational content out. I think when it comes to some of the pieces around diversity, equity and inclusion, I won’t take credit for any of that. I mean, I obviously have tried to contribute, but a lot of it comes from the team who spent a lot of time engaging with these various things.

Alex Shalek: [00:25:26] And we’ve been very thoughtful about this and we’ve been having a lot of ongoing discussions internally and externally trying to figure out exactly what we value and why and thinking about what we want to be known for and what’s important to us and trying to put some of that out. And we obviously have been inspired by a number of others and we tried to give credit where credit is due and some of the things on our website. But I think that normalizing discussions around some of these points and making it clear like, here’s how we’re thinking about stuff and listening to feedback and being resilient to challenges that may arise. It becomes important because we want a place where everybody thrives and where different ideas can come together and where you can collectively tackle problems from multiple different angles so that you make inroads faster and more effectively. I wish that more people spent more time thinking about some of these things. And I’ve been told I’m a little crazy when it comes to figures like exactly what colors need to be used and how it’s done. And I’m like, Well, what are you trying to show me with this? I do think it’s critical. You have to think about how somebody on the other end is going to react to it. And it’s nice when people say that they’ve enjoyed it. And I also enjoy when people are like, Hey, I wish you had done a better job of this because I’m like, Oh, I wish I’d done a better job of that too.

Grace Ratley: [00:26:28] Yeah. So I’d really like to go into a little bit more depth about your path to science. And I know you mentioned you came from a math and theory background and physics and whatnot, but take me back a little bit further. Like, when did you know that you wanted to pursue science or math? And tell me a little bit about that journey.

Alex Shalek: [00:26:47] If I’m being honest, I never thought I was going to be a scientist. I always enjoyed understanding how the things around me worked. As somebody who was a very curious kid, I liked taking things apart. I liked building things. All the things where you would have said, Oh, that that dude’s going to be a scientist. But on the other hand, I was interested in everything. I loved history, I loved literature, I loved philosophy, I loved basically everything I’d say. I was always involved in doing science, but it was never like, hey, this is my passion. It was just like, Hey, I’m pretty good at this. And I sort of used it to try and think of this idea of how to be a little bit more balanced. And so I’d focus a little less on science so that I could try and work on the things that I wasn’t as good at. I think back to this really funny thing, and I always wonder whether it was the right thing to do or not. But where I changed my advisor in high school from somebody who was a math teacher to somebody who was an English teacher, because I wasn’t doing as well in English as I was in math. And I was like, Well I need to go interact with somebody that’s going to help me and do these various things.

Alex Shalek: [00:27:41] And so when I went to college, I didn’t go with the idea that I was going to do science. I actually went to Columbia because I wanted this core curriculum, this broad liberal arts education, where I would take literature and art and music and be in New York and go to a concert and be at the Met and have this experience plus enjoying New York when I was young and dumb as opposed to old and dumb. But while I was doing it, I was taking all these science classes and I was enjoying it, but I understood it. And like it wasn’t one of those things where I was like really going deep into it. And as I kept on doing stuff, just some stuff started to grab my attention. And so I had done a little bit of work at Columbia when I was in high school. And so when I went in I sort of got to start in some advanced classes and so working my way up through physics. And I was like, Well my father had been a physics major, told me that the science that smart people do. So I was like, Oh, I’m going to go do this.

Alex Shalek: [00:28:31] And so I started doing it and started pushing my way through it, taking graduate classes in it. And it just wasn’t anywhere near as fascinating as some of the things that I was doing over in Art and I knew I wasn’t going to be an artist, but I was really enjoying learning about it. I realized that some of the things that made me dissatisfied with what I was learning in physics is sort of the areas that I was studying. And so I started looking at some of the other stuff that was going on at the time. Brian Greene had written The Elegant Universe, and he was at Columbia. So I went and started looking at like string theory and math, and I was like, Oh, this is great. Like, I can push all the math. I understand how to do it and differential geometry is really cool. And I understand all these things. I can think about these things I can do well in the class, but it was never one of those things that really just gelled where I was like this is what I’m meant to do with my life. And so I had also been doing stuff in chemistry because it was part of the things you needed to do if you’re going to be pre-med.

Alex Shalek: [00:29:18] And a lot of doctors in my family, I just figured that’s what I’ll end up doing. And I started taking these graduate classes in chemistry and it was really strangely enough, these classes on statistical thermodynamics and statistical mechanics that really caught my attention, that really made me interested in science and have in retrospect been sort of what informs everything I’d done since. Because those classes are really focused on how interactions among like individual atoms can work together to drive macroscopic properties that we rely upon. When you think about magnetism or what is temperature or what is pressure, those observables that you can see in, how does like the physics that I’ve learned actually do something that I see in the real world and also, I was like, Aha, I get it. And so that’s what I wanted to study. I wanted to understand how you go from something that is very fundamental to something that really you can understand. And I think in the biology research that I do strangely enough, I’ve ended back in exactly the same spot where instead of thinking about atoms and particles and how they drive some of these physical properties like cells, and how do those cells drive these tissue level properties. Because I can see and understand what happens when somebody gets sick. You understand this basic idea of dysbiosis and you can really get down to this like molecular precision of, Oh, there’s this mutation here. But then like how does that mutation ramify through the activity of specific cells? And which cells and how does that change the community and how does that actually result in what happens? It drives poor health or in some cases maybe more robust health. And so we’ve gone through that. And it was one of those things where the steps in between were very serendipitous and like how it ended up. There was always this recurrent thread of trying to understand how these fundamental pieces like really these building blocks came together to put stuff into the hole. And so I remember my senior year applying to graduate school, applying to finance and consulting. And until the 25th hour, I was pretty sure that I was going to not be doing science. And then with a nudge from my parents and a desire to explore stuff in my 20s as opposed to trying to be a responsible adult or whatever that means.

Alex Shalek: [00:31:24] I ended up going to graduate school and struggled in the beginning. I would say that stuff was hard, particularly going from this theory mindset to trying to figure out how to get stuff done because it’s a big difference between doing things in books versus actually trying to create and learn a lot of stuff along the way. Messed a lot of stuff up, but got to a point where stuff started working well and relied a lot upon the community to get the training I needed and tried to pay it back. And so it’s one of those things where it’s been a very nonlinear narrative that couldn’t have envisioned. But I’ve always sort of been interested in these bigger concepts, and I’ve been less worried about exactly how I do it. I’m sure that there are lots of different jobs that I could do where I could study these basic principles. And that’s really what I’ve been trying to focus on, it is like, what are the big things that will make me happy? What are the big questions I want to address? And those microcosms manifest in multiple different spots and science is a great place to do it. It also lets me do the education, empowerment, community engagement, the kinds of things that I wanted to do in medicine. It’s just a different place. And so I’m incredibly happy with what I do and better than I could have ever imagined. But it’s definitely not I would have imagined at the beginning.

Grace Ratley: [00:32:32] As we wrap up the episode, a question that I usually end with is what sorts of advice would you give to an early career scientist or someone entering just the field of systems, biology or genetics, or one of the many fields that you work in?

Alex Shalek: [00:32:49] Oh, it’s so hard. I mean, I have so many nuggets of advice. Most of them are hard fought wisdom by messing stuff up along the way. I think the first thing that I’d say is follow your data. I mean, a lot of places like I’ve really focused on what I’ve seen and trying to understand what it is like if I think back to all the single cell stuff that I do now, I saw heterogeneity. And rather than just assuming it was a measurement error, I was like, What is going on here? What does this all mean? And it led me down this rabbit hole or thinking adjacently when I got into doing immunology because we were developing these little beds of nanowires that we could use to record from neurons. The idea is that we want to study networks of neurons so we can study how the brain works. But in order to do that, you need a lot of electrical presence. So we wondered if we could make these very, very small little needles using nanofabrication to shove into cells and record electrical activity. And we found out that it actually works. The idea is acupuncture needles for cells, not lances. But when we did, it was like, Hey, what else could we do if we can poke a cell? And so that got me into delivering perturbations, which got me into studying immunology, getting back this idea of testing some of those correlations.

Alex Shalek: [00:33:54] So what I’d say is, first off, follow your data. I think the second thing that I’d say is always think about what you want to be known for and what kinds of things are important to you. I think in many places we focus on tangibles like papers as opposed to training or outcomes. What are the things that you personally want to develop for yourself and what are the things that are going to make you feel as though it was a good use of your time and that you were successful? And I never promised people that are interested in joining the lab that, Oh, you’ll get all these papers that will just bring down and it will be fantastic. I’ll say, really my goal is to figure out what you want to accomplish, figure out how to mentor you towards that and to work with you to get to where you want to be. And so I think that if you can think of like going into science, this is an incredible opportunity to pursue something that you’re passionate about and just enjoy the experience and not get caught up in some of the rivalries and complexities. Competition is good. It drives innovation, all those sorts of things.

Alex Shalek: [00:34:48] But I really like the idea of collectively solving problems. And I recognize that I sell these things from a privileged position that it’s hard for many others to view these things in a similar way. But it still comes back to this idea that you should really focus on making sure that you’re doing things that develop you towards the person that you want to be and solve the kinds of problems that you want. I think also there’s too much emphasis on exactly the right problem or exactly the right thing. Science is one of those lifelong journeys where you keep on learning new skills and bringing them in. And so maybe you learn how to do some fundamental work in one area and to write papers and to do grants. You don’t want to overemphasize any piece. And the other thing I’d say is like, you only have one life to live. So don’t get caught up in these externalities of, oh, this is the system, this is how we have to do it. There’s always this idea that if you decide you don’t want to do graduate school that you’re failing or washing out. I don’t think that’s true. I think it takes a maturity to recognize that it might not be something that you want. And academia is great, but I’ve seen plenty of people go on to do biotech companies and do incredible things.

Alex Shalek: [00:35:47] I’ve seen people decide in the middle that they wanted to go to medical school and do great. I’ve seen people just leave to go do all kinds of stuff. And so I don’t think there’s any one path toward success. I think it’s really about taking the time and space to figure out what do you enjoy, why do you enjoy it and how should you do it. And I’m not saying that you don’t need a little bit of resilience and you don’t have to work through hard things because science sucks. I mean, it’s constant failure. I mean, if I think about it, I was describing this just the other day. It’s like the majority of it is here. It’s like you’re at 0% and everything’s failing and then you get a little blip and it feels this incredibly minor change. But on the other hand, it’s like an infinity percent improvement. You went from nothing to something and then getting up to 100 is like so much easier because it’s a small little jump. And so you have to recognize that everything’s always going to fail and it’s always going to be problematic. But if you love it and you love the discovery science, it’s great. That’s what I’d say. It’s really important to collaborate with people and to network within the community.

Alex Shalek: [00:36:41] Science is not like this, like intellectual pursuit where you’re supposed to be just by yourself working in this little room. And I know it works for some people, but all the really good things that I’ve seen in science or that I’ve been involved in have always involved people coming together, tackling problems collectively, supporting one another, building community. And so making some of that a little bit more clear like that. There are different ways of doing things and that they’re equally valuable and figuring out ways to reward that are critical. There are plenty of people that will tell you how bad this, Co-first author thing is with a specific order as opposed to something that randomly shuffles and highlighting that everybody can do it equivalently. I really liked a paper that came from I think it was Garry Nolan’s lab where the order was settled by a video game contest. So it was whoever won ended up in the first position of the Co-first authors. But it’s just one of those things that’s so hard. I’d say in the same way as many others would be like, think about the community that you want to be in and then think about how to be an active participant in trying to create it. And that involves outreach and engagement. And in a lot of places doing stuff for others and just being a supportive individual. There’s a ton of stuff that I’ve done that has not yielded anything, but there are times I’ve done things that I didn’t think were important at all. But they were meaningful to others, and they’ve come back to be incredibly important and transformative.

[00:37:55] I remember I helped somebody do something in graduate school. I wasn’t sure it was the greatest idea, but they were keen and I was like, I would love to help you because people help me. A few years later, when I was interviewing for a grant, that person had left science but was now working at a specific foundation and was on the other side of the table. And so when they were trying to figure out who they were going to fund, they were like, That guy’s very smart and you should support him. And that’s led to some incredible partnerships with people all around the world and a lot of funding. And so it’s one of those things where there are all these places where we call it karma, call it whatever you want, comeback and you never really know. But always err on the side of caution of being just a good dude. That’s just what I like to think of that. Like fundamentally, you just think about the community that you want to be part of and think about how you can go about making it as such.

Grace Ratley: [00:38:41] Well, thank you so much for joining me today Alex. I had an excellent time talking with you. You dropped some incredible wisdom and yeah, I hope you have a great rest of your day.