Susumu Tonegawa
Professor, Nobel Laureate (1987 Nobel Prize In Physiology or Medicine)
Massachusetts Institute of Technology
Massachusetts, US
AsianScientist (Dec. 28, 2018) – In a world of hostile microbes, the immune system plays a critical role in fighting infection and keeping us alive. Despite being besieged by the millions of varieties of ‘enemies,’ the living defense system in our bodies manages to hold the fort. For a long time, scientists struggled to understand how this was possible. They knew that the dynamism of the immune system lay in its ability to generate an incredibly large repertoire of protective proteins known as antibodies, but the genetic basis of antibody diversity remained elusive.
It wasn’t until the 1980s that the complete picture of antibody diversity emerged, owing to seminal work done by Professor Susumu Tonegawa, who was then carrying out research at the Basel Institute for Immunology in Switzerland. In a series of elegant experiments involving the adept use of molecular genetics tools of this time, Tonegawa mapped out the process by which genes encoding the individual components of antibodies were assorted and recombined to give rise to the near limitless variety of the protective proteins. This process came to be known as V(D)J recombination and is now a staple chapter in immunology textbooks.
For his discoveries in immunology, Tonegawa was the sole recipient of the 1987 Nobel Prize in Physiology or Medicine, becoming the first Japanese person to win a Nobel Prize in that category. On the sidelines of the Singapore University of Technology and Design’s Iconic Voices from Massachusetts Institute of Technology (MIT) lecture series, Asian Scientist Magazine caught up with Tonegawa, who shared about his latest research interests and his views on science.
- You started your career in science as a virologist before embarking on your Nobel Prize-winning work on the immune system, and now you are studying neuroscience. How do you manage to be so versatile?
- You were originally drawn to the “great debate” on the genetic origins of antibody diversity. What is one great debate that you are working on now?
- How do you feel about the rise of artificial intelligence (AI) and the way neuroscience is informing machine learning?
- What are your thoughts on blue skies research and applied research?
- What are some of the challenges facing scientists today and how do you think these challenges may be overcome?
- What advice do you have for young or aspiring scientists?
I am best known for my research in the field of immunology, but I was never actually trained as an immunologist—I knew nothing about the immune system. My training was in molecular biology; I just happened to go into the field of immunology.
But once I had understood the genetic principle of antibody diversity, there was no strong reason for me to stay in immunology. I wanted to move on to something else which fascinated me, and that was neuroscience.
If you look at our species, how are we different from other organisms? We are not particularly better than some animals, for instance, in terms of ability to see, smell or run. We are different because of our brains, so if you want to know what human beings are, you have to find out how the human brain works. That was why I decided to move into the field of neuroscience.
So, you could call me versatile if you want to characterize it in a positive manner. I don’t see it that way. I just cannot stay in the same field for more than a certain number of years because I get bored!
I want to understand how memory works. To me, memory can be viewed in a much broader context. For instance, memory is very much associated with what we call consciousness.
If I were to ask you about your dinner last night, you are able to tell me where you had it, what you had, and with whom. You are conscious of the content of that memory. But seconds ago, before I asked you about it, you were not conscious of it although you had the exact same information in your brain.
In other words, the recall of episodic memory—of something you did—is very much linked to consciousness. Memories shuttle between consciousness and subconsciousness over time, and exactly how this happens remains to be fully understood.
We know that it has something to do with engram cells—a population of neurons that are activated specifically by an experience such as learning. In the process, this population of neurons undergoes enduring physical and chemical changes and can be reactivated by a part of the original stimulus or experience. But the engram cell isn’t all there is to memory research. How the brain produces emotional states and consciousness are still questions to be answered.
I think neuroscience and AI will mutually benefit each other. In fact, AI will have to take advantage of our knowledge about how the brain works. But the inverse is also true—AI can be used to help scientists understand the brain.
For example, if I can record everything that is happening in your brain before and after I triggered a specific memory, the difference between the two states could reflect the basis for consciousness. In principle, this can be pursued with AI. With classical methods, it’s a huge amount of work, but with AI, it may become something feasible.
Hence, the way we study the human brain and the way we do research itself will probably change. In the past, science has been heavily reliant on the ideas that a particular scientist has. In the future, scientists may depend on machines for insights. I find that kind of research less enjoyable. I believe in this mysterious thing called intuition.
I have always worked on the fundamental mechanisms without paying primary attention to the practical use of it. I want to know how nature works, and that’s what I’ve been doing. I’m not very good at translating the discovery into something that might be called useful. That is not what interests me.
But as a result of fundamental research, we now know where in the brain the crucial problem resides in diseases such as depression and Alzheimer’s disease. The connectivity of engram cells is abnormally reduced in these disorders.
Going forward, our hope is that non-invasive deep brain stimulation technology, like the one my colleague Ed Boyden at MIT is pioneering, may develop into an effective non-invasive therapy for diseases of the brain. An entirely new type of treatment for brain diseases—one that relies on electric or magnetic technology rather than the usual chemical- or medicine-based approaches—may arise.
First of all, there are more scientists, so there is more competition for research positions. If I were an assistant professor now, I don’t think I would do very well.
Science has also become very specialized, but if you go across two specialized areas, the people on both sides don’t really talk to each other. One side may be aware of a problem or an important scientific question that need to be explored, but they don’t know how to approach it. Meanwhile, the other side may have a very powerful research tool, but they may not be aware that a certain scientific problem exists.
So if you have knowledge of both sides, you can do something new with much less competition. It’s always good to work in a multidisciplinary area.
Do what you are curious about and focus on it. People often ask me “how do you find a good research project?” Well, if I knew the recipe, I would be doing that project! There is no real general recipe.
My advice is that you can learn what is scientifically important and what is not by observing creative scientists and how they do research. Try to seek out those kinds of opportunities when you are young, when your brain can incorporate information from the outside more effectively—it’s called plasticity. That’s the only way I know to do better science.
You also must have a willingness to learn new things. People become comfortable once they have achieved a certain status in a particular field. You get treated as an expert, you get more respect, and perhaps, more salary. But if you just stay there, it could be the end of your research path.
Once you become an expert in a certain field, and people look up to you, that is the time you should think about dropping it and doing new things. This is how I think one can get derive real joy from a research career.
This article is from a monthly series called Asia’s Scientific Trailblazers. Click here to read other articles in the series.
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Copyright: Asian Scientist Magazine; Photo: Cyril Ng/Asian Scientist Magazine.
Disclaimer: This article does not necessarily reflect the views of AsianScientist or its staff.
