Can you describe your research in the Subramaniam lab, and how your prior research experiences shaped your current interests?

I think my research in general is a bottom-up approach to how the brain works and how the brain aberrates—so how diseases arise in the brain. I started off my research by just looking at how neurons work. My first project was at the University of Oxford, and I was using CRISPR to study the development of neurons from stem cells. I asked the question, what are the processes that control neuronal development? My next research position was looking at C. elegans, which is a microscopic roundworm and actually regenerates its damaged neurons. So now we wanted to ask, how do neurons regenerate? If we can figure that out then we can hopefully have new approaches to cure conditions like paraplegia and central nervous system degeneration.

So we had this big laser table set up, big fancy microscopes, and we’d cut the neurons and see the way the neurons grew back. But really to me, both of those projects led up to what I’m doing now in Shankar’s lab, which is asking the questions: What are the mechanisms that are occurring in the brain during Alzheimer’s disease? What controls the onset and the progression of this disease? And then I’m asking the question, how can we actually study that? There are two divergent ideas that we took. The first was “well hey, if we look at all the data that’s out there in stem cell-derived neurons and in post-mortem brain tissue—and if we were to look at Alzheimer’s disease, ALS, Parkinson’s disease, Huntington’s disease—is there a common mechanism between neurodegenerative diseases? And if so, can we target them? So that’s my project that I’m working on now. And what’s really exciting is that we think the answer is yes. We believe there is a common mechanism that’s driving these diseases and is upstream of disease onset and pathogenesis. So if we can target that specific mechanism, then you can potentially help treat every major neurodegenerative disease with one drug—which would be pretty cool.

However, there are a lot of limitations in how we currently study neurodegeneration; namely, in the post-mortem brain, you are only looking at the late end of the disease, and in stem cell-derived neurons, you don’t really get the full cellular heterogeneity, the full neuronal morphology, or the full maturation—in terms of electrophysiology and other metrics. So to solve this problem, we started to look at brain organoids, which are essentially small spheres that roughly recapitulate the cellular heterogeneity and neuronal activity of a brain. And so using this model, we kind of went back to our roots and asked the question, what are the mechanisms that control the development of the brain organoid? Nobody really knows this; we’ve been working on developing protocols to just get us to the end stage, like our end point of a functional neuronal model. But we don’t know the mechanisms that control that process. And understanding it more will help us develop better organoids, and in fact learn more about the brain.

My main project in the lab right now is to take this organoid model that we have, and use it to study Alzheimer’s disease. And to give you a little bit of insight, nobody has ever shown spontaneous, widespread neuron death in any neuronal model that reasonably recapitulates Alzheimer’s disease. All of the models in current use that show late-stage phenotypes are the result of unnatural overexpression of Alzheimer’s disease genes, or exogenous toxic protein additions. But nobody’s ever been able to take a patient’s cell, without doing some kind of “protein assaults” or extensive genetic engineering, to show late-stage Alzheimer’s disease pathology. And so what we hope to do is grow late-stage Alzheimer’s disease organoids in an attempt to understand the disease onset and progression in an experimentally tractable and reasonably accurate model of the brain.

At the end of the day, there’s two big unsolved biomedical challenges: cancer and neurodegeneration. The reason we’ve been able to develop some good therapeutics for cancer is because we have good models for it. There isn’t a good model for Alzheimer’s disease, in my opinion, as we currently speak. The reason we’ve been able to develop some good therapeutics for cancer is because we have good models for it. There isn’t a good model for Alzheimer’s disease, in my opinion, as we currently speak. So developing the right model, asking the right questions, and most importantly, using these powerful technologies like bioinformatics, cerebral organoids, CRISPR-Cas9. That’s why I really love my research; it’s a culmination of all of those put into one project.

Mentorship is important in any field of study. Who inspires you to pursue bioengineering?

It’s gotta be Shankar, it really does. I have the most crazy story about how I met Shankar—I met him as a high school student. My ex-girlfriend’s best friend is friends with Shankar’s son, and so that’s how I met Shankar. I ended up getting his email, and shot him an email, and I was like, “Hey, I’m interested in bioengineering.” I’d applied to UCSD and so I knew he was faculty there, and really wanted to meet him. I never got a response, emailed him again, never got a response, emailed him again, never got a response. Then like four months later, I get an email from him saying, “Hey, sorry I missed your email, I’d love to meet up.” And I was like “Yes, anytime!”.

And I met up with him and basically had this dialogue, where I thought I knew a bunch about bio because I’d taken AP Bio and had looked up stuff on his lab website. And we basically had a conversation where he told me the history of bioengineering and early agriculture and Leonardo Da Vinci. Then we started talking about more modern bioengineering concepts like genetic engineering. And it was cool because he’d say something at a pretty basic level, and then I’d say something to let him know that I understood what he was talking about. Then he’d bring it up a notch, and I’d say something, then he’d bring it up another notch where I didn’t know it anymore. So it was cool.

Shankar challenged me, but more importantly, he made me feel heard. Like he made me feel like the contributions that I could make to the field could impact lives. And just the fact that I was an 18 year-old who had an excitement about biology, and then he helped me turn that into a research career—in giving me guidance on how to apply for a lab position, or how to apply for a co-op, getting into grad school, things like that—to now, of course I want him as my PI.

From a young age, he showed that I had value, and that if I applied myself I could make a difference in this field. And so that’s where it starts. That was the turning point for me where I was like, “Yeah I can do this, I could get really good at it”.

At a really young age, I was really interested in biology, so my Dad bought me a microscope. And that was pretty cool, because I got to look at a bunch of stuff. So that piqued my curiosity, but Shankar turned curiosity into a career. And I’ll always be grateful to him for that. And not only that, but he also cares about the other things in my life. Like he’s not just interested in me as a scientist, but as a person. So like developing my skills as a scientist, but also as a team member, as a leader, as a family member. So yeah, Shankar is the platinum standard when it comes to mentorship.

What is the most crucial lesson you have learned during graduate school?

It might sound overplayed, but really just being able to fail. Like the ability to work so hard at something, and then realize you messed it up. Like to work so hard to write a grant—spending 250 hours on it—just for it to get denied. Like what do you do with that? After you spend so much time and effort saying here is my work product”, and then having someone else say “it’s not good enough”. What do you do with that?

And I think this is a common theme, but it’s true. Being able to work so hard towards something, and fail, and then being able to say, “Okay, despite this, I’m going to keep going. I’m gonna look at the path I took, and ask the questions: Well what happened? What was beyond my control? How can I do better next time?”

In terms of that actually manifesting in research, this is the real lesson that I learned from that: the lesson was to become a more efficient planner. I think research is a very nonlinear process. You go from point A to point B, but along the way you’re taking all these detours, all these other routes. And part of that is necessary. Part of research is taking detours and rabbit holes to learn about a process and to be able to apply it. But being able to have clarity of thought and being able to take a step back from your research project and say, “Okay, what do I have? What do I need to have? And what are the steps I need to take to get there?” And I think this is something that a lot of young scientists struggle with because research is such a multifaceted job—there’s so many different components to consider.

And unlike any other job I’ve had in my life, nobody knows my project as well as I do. I mean Shankar is great for getting help; Andrew, a senior scientist in the lab, I wouldn’t be able to do my research project without him. But at the end of the day, when it comes to deciding directions for the project, the onus is on me to make sure that the path I take—the choices I choose to make—are going to get me to where I need to go in an efficient manner. Because if I just think, “Oh I can do this,” and then go do that, and it’s like, “Well, okay, I did this but it didn’t really get me to where I want to be.” So being able to take a step back, have clarity of thought about what I’m doing and where I need to go, I think that’s a really hard skill to learn as a scientist. But that is the most useful skill. And it’s only coming after I kept trying; you don’t learn it until you mess up. You can work for a month-and-a-half on something and then realize that it’s useless, and if you’d had a little better foresight then, you would have realized that sooner. So being able to learn that process is hugely valuable.

Work life balance is something that we all strive to achieve. How have you developed your sense of balance and what do you enjoy doing outside of the lab?

One thing I definitely didn’t realize as an undergrad when I got my first full-time research position—it was a co-op where I stopped going to school for six months and worked in Shankar’s lab—there was no time card, no one was keeping track of my little steps. No one knows when I leave lunch or when I get there. And it’s even more true in the age of work-from-home. I think the important thing to realize is that the only person who gets hurt if you aren’t making good progress is you. And so there’s a really big accountability there. Especially if you’re working on the same project for months and months, there’s times when I wake up and it’s like, I love my project, I love science and it’s frankly bonkers that I get paid to do this, but it can be hard to motivate myself to get in R and do some coding.

So for me, I think part of it was realizing when I work best. When you grow up people are like, “Oh, if you’re not waking up at 6am then you’re not trying hard enough”. But it’s like, my hours when I work best are from 11am to like 1am. I don’t work 14 hours a day, but that time period is when I get my best work done. So for me it was learning to wake up in the morning and workout. I really like rock climbing, so I like to go. To me it was a good way to accomplish a little thing. If you can accomplish a lot of little things, every day, then I think you’re going to be in a good place to make good progress towards the big milestones you have in your life. So if I can wake up in the morning, go rock climbing at the gym, and finish climbing a route that I’m working on, then it makes the other things that you need to get done on that day seem a little bit more doable. And for me a really big aspect of keeping my head on straight is my faith.

So for me, I think part of it was realizing when I work best. When you grow up people are like, “Oh, if you’re not waking up at 6am then you’re not trying hard enough”. But it’s like, my hours when I work best are from 11am to like 1am. I don’t work 14 hours a day, but that time period is when I get my best work done. So for me it was learning to wake up in the morning and workout. I really like rock climbing, so I like to go. To me it was a good way to accomplish a little thing. If you can accomplish a lot of little things, every day, then I think you’re going to be in a good place to make good progress towards the big milestones you have in your life. So if I can wake up in the morning, go rock climbing at the gym, and finish climbing a route that I’m working on, then it makes the other things that you need to get done on that day seem a little bit more doable .And for me a really big aspect of keeping my head on straight is my faith.

To me, science is my purpose in life—it’s why God put me here. It’s of those things that’s just so easy to forget, and so I’m making sure to devote a little bit of my time every day to my faith. And on a weekly basis, setting aside time to take a step back and touching base with my Creator is the way I can make it through the tough times. You know, like when Shankar and I were writing a grant and I pulled two all-nighters back-to-back on three hours of sleep. So when life gets crazy, when you have your life built on a solid foundation, you will survive. But building your life on a solid foundation is a daily process. So accomplish the small things, continue to accomplish the small things, and for me, to realign myself with the person who put me here; that’s how I maintain my work-life balance.

Is there any advice you have for students interested in pursuing academia and/or grad school?

Do your best to find a research position. And it’s hard. It’s really hard a lot of the time. There are also fiscal barriers associated with that. Not everybody has the privilege to be able to volunteer in a lab 10 hours a week because they may have to work a job and get paid. So if grad school is something you want to do, then 1) Do your best to find a research position, and 2) Do your best to find a mentor who is faculty in your department. Go to them and say, “Hey, I’m really excited about this topic area. I would love to pursue it in an academic research setting, or in grad school. Here’s what I’m thinking about doing, do you have any advice for me?” I think if there’s a hundred students who like the idea of going to grad school, 20 of them will actually go to somebody and say, “Hey, I want to do this.” If you wait for the opportunities to come to you, then odds are you’re too late. For me, I remember in high school I emailed like 25 faculty members at different universities trying to get an unpaid research position before I ended up getting a response from Shankar. So go out, try to find a research position, try to find a faculty mentor if possible.

The only other thing that I would say is that it’s not worth doing if you aren’t really excited about it. Academia is not a luxurious route. Grad school is a great way to be in poverty for an additional six years after you graduate. So if you really like the idea of research—of new, groundbreaking technologies—and if you find yourself falling asleep at night thinking about these research topics, then do it. Go for it; it’s one of the coolest jobs you’ll ever have. I get paid to look up stuff that I’m interested in. I don’t get paid a lot, but it’s a pretty cool position to be in. And the last thing I’d say is that not everyone’s route is going to look the same. There are people in my cohort who went directly from undergrad to grad school, like me. But I was privileged enough to be able to take an unpaid intern position in undergrad. I was also able to get two co-ops—I stopped going to school for two separate periods for six months—and that gave me the research experience I needed to be able to a PhD program right out of college. But not everybody’s path looks like that. Other people work in industry for two, three years. Some people work in industry for upwards of a decade before going into grad school. And I think that’s probably a little more difficult route because when you get used to industry, there’s a lot of luxuries associated with it, like a salary. So right now in grad school, everything is dependent on me—me being able to decide what I need to do next, and me staying on top of my work. Meanwhile, industry has a lot more structure—and obviously depending on the position—is like, “Here’s what I need from you” kind of a thing, so much more defined.

So the three things would be: 1) find a research position, 2) approach a faculty member and ask them for their advice, and 3) understand that not everyone’s path is going to look the same. Nobody knows your background, where you’re coming from, the specific things you’re struggling with at this moment. But that doesn’t mean you can’t go into a PhD program. It might just not happen in exactly the manner you might want it to. So I think those are the key things to keep in mind.