Prof. Steven Flavell on researching neural circuits in C. elegans and being named an HHMI Investigator
C. elegans is a little roundworm, about a millimeter long and barely visible to the naked eye. And it only has 302 brain cells.
Steven Flavell is an associate professor at MIT in the department of Brain and Cognitive Sciences, as well as an investigator in the Picower Institute for Learning and Memory. He was recently named an Investigator of the Howard Hughes Medical Institute (HHMI), along with three other MIT professors. Approximately 25 new HHMI Investigators are named every three years, and they are awarded $11 million in support for their research over seven years. The Tech sat down with Flavell to discuss his path to MIT studying neural circuits in C. elegans, his lab’s research plans moving forward, and what they look for in undergraduate researchers.
TT: What did your path look like to researching neural circuits?
I grew up in a science family. My mom was in math and computer science, and my dad was a molecular biologist. Naturally, as a teenager, I wanted to do the opposite of what my parents did. I tried—at college, I started off as an English major. English led to psychology, and psychology led to neuroscience and biology.
In graduate school, I was fortunate to work with an amazing mentor, Michael Greenberg, at Harvard Medical School. I studied the signaling mechanisms that allow neurons to change how they're wired based on experience during postnatal development. After graduate school, I wanted to continue to study very basic aspects of neural signaling and function, but I became interested in the way that the nervous system doesn't just wire, but that wiring allows neurons to talk to one another and ultimately generate behavior.
That's a pretty complicated thing. A behaving animal with a complicated brain is very hard to have very precise mechanistic control over in your experimental preparation. I wanted to study this, but to do so, I decided that it would be best to be doing this in a very simple animal model: a roundworm called C. elegans.
TT: What does your lab research today, and how will HHMI fit into that picture?
My lab is interested in trying to understand the neural mechanisms that generate the internal states of the brain—arousal, motivation and mood. Our interest is trying to understand the neural mechanisms that generate these states in the brain, and also trying to understand how these states then impact neural activity and ultimately the animal’s behavior.
All the work that I did as a postdoc at Rockefeller with my amazing mentor, Cori Bargmann, and now do in my own lab, is in this very small animal model where we have exquisite experimental control. C. elegans is a little roundworm, about a millimeter long and barely visible to the naked eye. And it only has 302 brain cells. We can find them in every animal and we know how they're wired up with one another, so we have the full blueprint of the animal's brain. To put this in perspective, the total number of synapses in the roundworm’s brain is less than the total number of synapses that form onto one neuron in our human cerebral cortex. But this animal can go to sleep, it can wake up, it can make memories. Using the amazing experimental control that's possible in the system, we can record the activity of every brain cell at the same time while the animal is behaving. We can use genetics to perturb genes and individual neurons, change things such as signaling pathways, and therefore really probe deeply into the mechanistic features of the brain cells in the nervous system and how they ultimately control behavior.
One of the amazing things about HHMI is that their philosophy for funding is that they fund “people, not projects.” That means that, with this funding, we can be pretty ambitious and take on directions that might be a little too risky for traditional funding. There's lots of things that we're excited about doing. We've been studying the neuromodulatory systems within the brain that give rise to internal states: think serotonin and dopamine. We're interested in scaling up to try to understand these systems better, to visualize the flow of serotonin through extracellular space, and to map out where the receptors are. That's going to require innovation on the technology and computational models that we've been building.
The roundworm is great because it gives us experimental control to study how one nervous system can be modulated to allow an animal to generate many different behaviors. However, it doesn't give us the ability to look at what happens when the wiring of the brain is different. So another thing that we're excited to do is to start studying other animals and use a comparative approach on different species of animals to ultimately see how nervous systems function differently when the wiring is different. That’s a long-term goal of ours that's going to require developing some technologies to be able to study these different animals and then make the biological discoveries.
TT: For our incoming students and students who are interested in your research, what does a day in your lab look like?
My lab is very multidisciplinary; we really run the gamut from molecular biology to systems neuroscience to computational neuroscience.
The animals that we examine are commonly animals where we've perturbed genetic pathways or inserted transgenes that allow us to turn neurons on and off remotely, so we do a lot of genetics and molecular biology in the lab. We clone plasmids, make transgenic animals and mutant animals, and do genetic crosses that allow us to ask very specific questions about causality and which features of the brain give rise to which features of neural activity and behavior.
We measure activity across the animal's brain through optical recordings of neural activity, and we make these optical recordings on microscopes that we engineered to move around with the worm so that we can keep imaging its brain while it's freely behaving. There's a lot of computation that's required to extract all of the interesting information from the imaging data and ultimately analyze it. All these brain-wide recordings and behavioral data require a lot of modeling, so we do a lot of computational modeling using statistical approaches as well as machine learning approaches.
It's always amazing to have undergraduate students involved in our research, especially students who are passionate about research and really want to get into the lab and make discoveries. That's going to be what makes it exciting for them, and will also propel them forward through the highs and lows of scientific research to do something interesting in the lab. We're happy to host students with molecular backgrounds, systems neuroscience interests, and computational machine learning backgrounds. There's many ways to contribute to our research. Curious and motivated to participate in scientific discovery are the main things we look for.