Lex Fridman PodcastManolis Kellis: Human Genome and Evolutionary Dynamics | Lex Fridman Podcast #113
EVERY SPOKEN WORD
150 min read · 30,094 words- 0:00 – 3:54
Introduction
- LFLex Fridman
The following is a conversation with Manolis Kellis. He's a professor at MIT and head of the MIT Computational Biology Group. He's interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives. He has more big impactful papers and awards than I can list. But most importantly, he's a kind, curious, brilliant human being, and just someone I really enjoy talking to. His passion for science and life in general is contagious. The hours honestly flew by, and I'm sure we'll talk again on this podcast soon. Quick summary of the ads. Three sponsors, Blinkist, Eight Sleep, and MasterClass. Please consider supporting this podcast by going to blinkist.com/lex, eightsleep.com/lex and signing up at masterclass.com/lex. Click the links, buy the stuff, get the discount. It's the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or connect with me on Twitter @LexFridman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This episode is supported by Blinkist, my favorite app for learning new things. Get it at blinkist.com/lex for a seven-day free trial and 25% off afterwards. Blinkist takes the key ideas from thousands of non-fiction books and condenses them down into just 15 minutes that you can read or listen to. I'm a big believer in reading at least an hour every day. As part of that, I use Blinkist every day to try out a book I may otherwise never have a chance to read. And in general, it's a great way to broaden your view of the idea landscape out there and find books that you may want to read more deeply. With Blinkist, you get unlimited access to read or listen to a massive library of condensed non-fiction books. Go to blinkist.com/lex to try it free for seven days and save 25% off your new subscription. That's blinkist.com/lex. Blinkist, spelled B-L-I-N-K-I-S-T. This show is also sponsored by Eight Sleep and its Pod Pro mattress that you can check out at eightsleep.com/lex to get $200 off. It controls temperature with an app and can cool down to as low as 55 degrees on each side of the bed separately. Research shows that temperature has a big impact on the quality of our sleep. Anecdotally, that's been true for me. It's truly been a game changer. I love it. The Pod Pro is packed with sensors that track heart rate, heart rate variability, and respiratory rate, showing it all in their app. The app's health metrics are amazing, but the cooling alone is honestly worth the money. Check it out at eightsleep.com/lex to get $200 off. This show is also sponsored by MasterClass. Sign up at masterclass.com/lex to get a discount and to support this podcast. When I first heard about MasterClass, I thought it was too good to be true. For 180 bucks a year, you get an all-access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking and communication, Will Wright, one of my favorite game designers, Carlos Santana, one of my favorite guitar players, Garry Kasparov, of course, the greatest chess player of all time, I'm not biased, Daniel Negreanu on poker, and many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. By the way, you can watch it on basically any device. Once again, sign up at masterclass.com/lex to get a discount and to support this podcast. And now, here's my conversation with Manolis Kellis.
- 3:54 – 17:47
Human genome
- LFLex Fridman
What to you is the most beautiful aspect of the human genome?
- MKManolis Kellis
Don't get me started. (laughs) So...
- LFLex Fridman
We got time.
- MKManolis Kellis
Um, eh, the first answer is that the beauty of genomes transcends humanity. So it's not just about the human genome. Genomes in general are amazingly beautiful. And again, I'm obviously biased. So, um, in my view, uh, the way that I like to introduce the human genome and the way that I like to introduce genomics to my class is by telling them, "You know, we're not the inventors of the first digital computer. We are the descendants of the first digital computer." Basically, life is digital, and that's absolutely beautiful about life. The fact that at every replication step, you don't lose any information because that information is digital. If it was analog, if it was just protein concentrations, you'd lose it after a few generations. It- it would just dissolve away. And that's what the ancients didn't understand about inheritance. The first person to understand digital inheritance was, uh, Mendel, of course. And his theory, in fact, stayed in a bookshelf for like 50 years while Darwin was getting famous about natural selection. But the missing component was this digital inheritance, the mechanism of evolution that Mendel had discovered. So that aspect, in my view, is the most beautiful aspect, but it transcends all of life.
- LFLex Fridman
And can you elaborate maybe the inheritance part? What was the, what was the key thing that the ancients didn't understand?
- MKManolis Kellis
So, the very theory of inheritance, uh, as discrete units, you know, throughout the life of Mendel and well after his writing, people thought that his pea experiments were just a little fluke, that they were just, uh, you know, a little exception that would normally not even apply to humans, that... Basically what they saw is this continuum of eye color, this continuum of skin color, this continuum of hair color, this continuum of height, and all of these continuums did not fit with a discrete type of inheritance that Mendel was describing. But what's unique about genomics and what's unique about the genome is really that there are two copies and that you get a combination of these, but for every trait.... there are dozens of contributing variables. And it was only Ronald Fisher, in the 20th century, that basically recognized that even five Mendelian traits would add up to a continuum-like inheritance pattern. And he, you know, wrote a series of papers that still are very relevant today about, sort of this Mendelian inheritance of continuum-like traits. And I think that, that was the missing step in the inheritance. So, well before the discovery of the structure of DNA, which is again, another amazingly beautiful aspect, the double helix, what I like to call the most noble molecule of our time-
- LFLex Fridman
Yeah.
- MKManolis Kellis
... is, uh, you know, holds within it the secret of that discrete inheritance. But the conceptualization of discrete, you know, elements is something that precedes that.
- LFLex Fridman
So, even though it's discrete, when it, uh, materializes itself into actual traits that we see, it can be continuous. It can basically arbitrarily, uh, rich and complex.
- MKManolis Kellis
So if you have five genes that contribute to human height, and there aren't five, there's 1,000. If there's only five genes, and you inherit some combination of them, and every one makes you two inches taller or two inches shorter, it'll look like a continuum trait, a continuous trait. But instead of five, there are thousands, and every one of them contributes to less than one millimeter. We change in height more during the day than each of these genetic variants contributes. (laughs) So by the evening, you're shorter...
- LFLex Fridman
(laughs)
- MKManolis Kellis
... than you were, you woke up with.
- LFLex Fridman
Isn't that weird then that the, we're not more different than we are? Why, why are we all so similar if there's so much possibility to be different?
- MKManolis Kellis
Yeah. So, so there are selective advantages to being medium. If you're extremely tall or extremely short, you run into selective disadvantages. So you have trouble breathing, you have trouble running, you have trouble sitting if you're too tall. If you're too short, you might, I don't know, have other selective pressures a- acting against that. If you look at natural history of human population, there's actually selection for height in Northern Europe, and selection against height in Southern Europe.
- LFLex Fridman
Oh, okay.
- MKManolis Kellis
So there might actually be advan- advantages to actually being s- not, not super tall.
- LFLex Fridman
(laughs)
- MKManolis Kellis
And if you look across the entire human population, you know, for many, many traits, there's a lot of push towards the middle. Uh, balancing selection is, you know, the usual term for selection that sort of seeks to not be extreme and to sort of have a combination of alleles that sort of, you know, keep recombining. And if you look at, you know, mate selection, super, super tall people will not tend to sort of marry super, super tall people. Very often you see these couples that are kind of compensating for each other, and, uh, the best predictor of the kids' age is very often just take the average of the two parents and then adjust for sex, and boom, you get it. It's extremely heritable.
- LFLex Fridman
Let me ask, uh, you kind of, uh, took a step back to the genome outside of just humans, but is there something that you find beautiful about the human genome specifically?
- MKManolis Kellis
So, I think the genome, if more people understood the beauty of the human genome, there would be so many fewer wars, so much less anger in the world. I mean, what, what's really beautiful about the human genome is really the variation that teaches us both about individuality and about similarity. So any two people on the planet are 99.9% identical. How can you fight with someone who's 99.9% identical to you? It's just counterintuitive. And yet, any two siblings of the same parents differ in millions of locations. So every one of them is basically two to the million unique from any pair of parents, let alone any two random parents on the planet.
- LFLex Fridman
Hmm.
- MKManolis Kellis
So that's, I think, something that teaches us about sort of the nature of humanity in many ways, that every one of us is as unique as any star, and way more unique in actually many ways. And, uh, yet we're all brothers and sisters and-
- LFLex Fridman
Yeah. Just like stars, most of it is just, uh, fusion, uh, reactions.
- MKManolis Kellis
Yeah, you only have-
- LFLex Fridman
(laughs)
- MKManolis Kellis
... a few parameters to describe stars.
- LFLex Fridman
Yeah, exactly.
- MKManolis Kellis
You know, mass, size, initial size, and you know, stage of life. Whereas for humans it's, you know, thousands of parameters scattered across our genome. So the other thing that makes humans unique, the other things that makes inheritance unique i- in humans is that, um, most species inherit things vertically. Basically, instinct is a huge part of their behavior. The way that, you know, I mean, w- with my kids, we've been watching this, uh, nest of birds, uh, with two little eggs, you know, out- outside our window for the last few months, uh, for the last few weeks as they, as they've been growing, and there's so much behavior that's hardcoded. Birds don't just learn as they grow. They don't, you know, there's no culture. Like a bird that's born in Boston will be the same as a bird that's born in California. So there's not as much, um, inheritance of ideas, of customs. A lot of it is hardcoded in their genome. What's really beautiful about the human genome is that if you take a person from today and you place them back in ancient Egypt, or if you take a person from ancient Egypt and you pl- place them here today, they will grow up to be completely normal. That is not genetics. This is the other type of inheritance in humans. So on one hand, we have genetic inheritance, which is vertical from your parents down. On the other hand, we have horizontal inheritance, which is the ideas that are built up at every generation are horizontally transmitted. And the huge amount of time that we spend in educating ourselves, a concept known as neoteny....neo for newborn, and then tene for holding. So, if you look at humans, I mean the- the little birds that were, you know, eggs two weeks ago, and now, now one of them has already flown off, the other one is ready to fly off, in two weeks, they're ready to just fend for themselves. Humans? 16 years?
- LFLex Fridman
(laughs)
- MKManolis Kellis
(laughs) 18 years, 24, getting out of college.
- 17:47 – 29:15
Sources of knowledge
- MKManolis Kellis
- LFLex Fridman
I'm not sure any of us know how to do that, in this modern day. We're e- actually learning. One of the big surprising thing to me about the, uh, the coronavirus, for example, is that Twitter has been one of the best sources of information. Um, basically, like, building your own network of experts, of, of, uh, you know, as opposed to the traditional centralized expertise of the WHO and the CDC and the ... Or, um, or maybe any one particular...... respectable person at the top of a department in some kind of institution. You instead look at a, you know, uh, 10, 20 hundreds of people, some of whom are young kids with just, that, uh, are incredibly good at aggregating data and plotting and visualizing that data. That's been really surprising to me. I don't know what to make of it. Um, I don't know, I don't know how that matures into something stable. Uh, you know, I- I don't know if you have ideas, like what, if you were to try to explain to your kids of how, where should you go to learn about the, about coronavirus? (laughs) What would you say? (laughs)
- MKManolis Kellis
It's such a beautiful example, and I think, uh, the current pandemic and the, the speed at which the scientific community has moved in the current pandemic, I think exemplifies this horizontal transfer and the speed of horizontal transfer of information. The fact that, you know, the genome was first sequenced in early January, the first sample was obtained December 29th, 2019. A week after the publication of the first genome sequence, uh, Moderna had already finalized its vaccine design (laughs) and was moving to production. I mean, this is, uh, phenomenal, the fact that we go from not knowing what the heck is killing people in Wuhan to, uh, wow, it's SARS-CoV-2 and here's the set of genes, here's the genome, here's the sequence, here are the polymorphisms, et cetera, in the matter of weeks, is phenomenal. In that incredible pace of, uh, transfer of knowledge, there have been many mistakes. So, you know, some of those muta- mistakes may have been politically motivated or other mistakes may have just been innocuous errors. Others may have been misleading the public for the greater good, such as don't wear masks because w- we don't want the masks to run out. I mean, that, that was very silly in my view, and a very big mistake. Um, but the, the spread of knowledge from the scientific community was phenomenal. And some people will point out to bogus articles that snuck in and made the front page. Yeah, they did, but within 24 hours, they were debunked-
- LFLex Fridman
Yeah.
- MKManolis Kellis
... and went out of the front page, and I think that's, that's the beauty of science today. The fact that it's not, "Oh, knowledge is fixed," it's the ability to embrace that nothing is permanent when it comes to knowledge, that everything is the current best hypothesis, and the current best model that best fits the current data, and the willingness to be wrong. The expectation that we're gonna be wrong, and the celebration of success based on how long was I not proven wrong for rather than, "Wow, I was exactly right." 'Cause no one is gonna be exactly right with partial knowledge, but the arc towards perfection I think is so much more important than how far you are on your first step. And I think that's what sort of the current pandemic has taught us, the fact that, yeah, no, of course, we're gonna make mistakes, but at least we're gonna learn from those mistakes and become better and learn better and spread information better. So if I were to answer the question of where would you go to learn about coronavirus, first textbook, it all starts with a textbook. Just open up a chapter on virology and how coronaviruses work. Then some basic epidemiology and sort of how pandemics have worked in the past. What are the basic principles surrounding these first wave, second wave? Why do they even exist? Then understanding about growth, understanding about the R0 and RT at, you know, various time points. And then understanding the means of spread, how it spreads from person to person, then how does it get into your cells? From when it gets into the cells, what are the paths that it takes? What are the cell types that express the particular A- ACE2 receptor? How is your immune system interacting with the virus? And once your immune system launches a defense, how is that helping or actually hurting your health? What about the cytokine storm? What are most people dying from? Why are there comorbidities and these risk factors even applying? What makes obese people respond more or elderly people respond more to the virus while kids are completely, you know, uh, uh, uh, you know, very often not even aware that they're spreading it? So the, you know, I think there's some basic questions that you would start from, and then I'm sorry to say, but Wikipedia is pretty awesome.
- LFLex Fridman
Yeah. It is.
- MKManolis Kellis
Google is pretty awesome. (laughs) So-
- LFLex Fridman
There used to be a time, used to be a time maybe five years ago, I forget, I forget when, but people kind of made fun of Wikipedia for being, um, an unreliable source. I never quite understood it. I thought from the early days it was pretty reliable or better than a, a, a lot of the alternatives. But at this point it's kind of like a solid accessible survey paper on every subject ever. (laughs)
- MKManolis Kellis
The- there's an ascertainment bias and a writing bias. So, so I think this, this is related to sort of people saying, "Oh, so many Nature papers are wrong." And they're like, "Why would you publish in Nature? So many Nature papers are wrong." And my answer is, "No, no, no. So many pa- Nature papers are scrutinized. And just because more of them are being proven wrong than in other articles is actually evidence that they're actually better per- papers overall because they're being scrutinized at a rate much higher than any other journal." So if you basically, uh, judge Wikipedia by not the initial content by, but by the number of revisions-
- LFLex Fridman
Yeah.
- MKManolis Kellis
... then of course it's gonna be the best source of knowledge eventually. It's still very superficial. You then have to go into the review papers, et cetera, et cetera, et cetera, but I mean, for most scientific project, uh, uh, uh, topics, it's extremely superficial. But it is quite authoritative because it is the place that everybody likes to criticize as being wrong.
- LFLex Fridman
Do you... you say that it's superficial. On a lot of topics that, um, I've studied a lot of, I find it... I, uh, I don't know if superficial is the right word. Um-'Cause superficial kind of implies that it's not, uh, correct.
- MKManolis Kellis
No, no.
- LFLex Fridman
Oh, so-
- MKManolis Kellis
I, I don't mean any implication of it not being correct.
- LFLex Fridman
So I-
- MKManolis Kellis
It's just superficial. It's basically only scratching the surface. For depth, you don't go to Wikipedia, you go to the review articles.
- LFLex Fridman
But it can be profound in the way that articles rarely... One of the frustrating things to me about, uh, like, certain computer science, like, in the machine learning world, articles, they, they don't as often take the, uh, the bigger picture view. You know, there's a, it's a kind of data set and you show that it works and you kind of show that here's an architectural thing that creates an improvement and so on and so forth. But you don't say, well, like, "What does this mean for the nature of intelligence for future data sets we haven't even thought about?" Or if you were trying to implement this, like, if we took this data set of, uh, 100,000 examples and scaled it to 100 billion examples with this method, like, like, look at the bigger picture, which is what a Wikipedia article would actually try to do, which is like, what does this mean in the context of computer, the broad field of computer vision or something like that.
- MKManolis Kellis
Yeah, yeah.
- LFLex Fridman
And-
- MKManolis Kellis
No, I, I agree with you completely, like, but it depends on the topic. I mean, for some topics there's been a huge amount of work, for other topics, it's just a stub. So, you know.
- LFLex Fridman
(laughs) I got it.
- MKManolis Kellis
Yeah.
- LFLex Fridman
Well, yeah, actually the... Uh, j- well, which we'll talk on, gen- genomics was not-
- MKManolis Kellis
Yeah. It's very shallow.
- LFLex Fridman
Great. (laughs)
- MKManolis Kellis
Yeah. Yeah. It's not wrong. It's just shallow.
- LFLex Fridman
It's shallow.
- MKManolis Kellis
Yeah. Every time I criticize something, I should feel partly responsible. Basically, if more people from my community went there and edited, it would not be shallow. It's just that there's different modes of communication in different fields. And in some fields, the experts have embraced Wikipedia. In other fields, it's relegated. And per- perhaps the reason is that, uh, if it was any better to start with, people would invest more time. But if it's not great to start with, then you need a few initial pioneers who will basically go in and say, "Ah, enough, we're just gonna fix that." And then I think it'll catch on much more.
- LFLex Fridman
So, if it's okay, before we, uh, we go on to genomics, can we linger a little bit longer on, uh, the beauty of the human genome? Uh, you've given me a few notes. What, what else, what else do you find beautiful about the human genome?
- 29:15 – 33:26
Free will
- MKManolis Kellis
So if you look at the trend with, and the speed with which human genetics has progressed, we can now find thousands of genes involved in human cognition, in human psychology, in the emotions and the feelings that we used to think are uniquely learned. Turns out there's a genetic basis to a lot of that. So the, uh, you know, the, the, the human genome has continued to elucidate, through these studies of genetic variation, so many different processes that we previously thought were, you know, something that, like free will. Free will is this beautiful concept that humans have had for a long time. You know, in the end, it's just a bunch of chemical reactions happening in your brain. And the particular abundance of receptors that you have this day based on what you ate yesterday, or that you have been wired with based on, you know, your parents and your upbringing, et cetera, determines a lot of that, quote unquote, "free will" component to, you know, sort of narrower and narrower sca- you know, sort of, uh, slices.
- LFLex Fridman
So how much, uh, on that point, how much freedom do you think we have to escape the...... the, the constraints of our genome?
- MKManolis Kellis
(laughs)
- LFLex Fridman
You're making it sound like, more and more, we're discovering that our genome is actually has the- a lot of the story already encoded into it. How much freedom do we have-
- MKManolis Kellis
I, uh ...
- LFLex Fridman
... do you think?
- MKManolis Kellis
S- so, so l- let me, let me describe what that freedom would look like. That freedom would be my saying, "Ooh, I'm gonna resist the urge to eat that apple because I choose not to." But there are chemical receptors that made me not resist the urge to prove my individuality and my free will by resisting the apple.
- LFLex Fridman
Uh-huh.
- MKManolis Kellis
So then the next question is, well, maybe now I'll resist the urge to resist the apple and I'll go for the chocolate instead to prove my individuality. But then what about those other receptors that, you know ... (laughs)
- LFLex Fridman
That, that might be all encoded in there.
- MKManolis Kellis
So it's kicking the bucket down the road and basically saying, "Well, your choice w- may have actually been driven by other things that you actually are not choosing." So, that's why it's very hard to answer that question. (laughs)
- LFLex Fridman
Well, it's hard to know what to do with that. I mean if, uh, if the genome has, um ... if, uh, if there's not much freedom, it's, uh ...
- MKManolis Kellis
It's the butterfly effect. It's basically that in the short term you can predict something extremely well by knowing the current state of the system.
- LFLex Fridman
Mm-hmm.
- MKManolis Kellis
But a few steps down, it's very hard to predict based on the current knowledge. Is that because the system is truly free? When I look at weather patterns, I can predict the next 10 days. Is it because the weather has a lot of freedom and after 10 days it chooses to do something else? Or is it because, in fact, the system is fully deterministic and there's just a slightly different magnetic feel of the earth, slightly more energy arriving from the sun, a slightly different spin of the gravitational pull of Jupiter that is now causing, you know, all kinds of tides and slight deviation of the moon, et cetera? Maybe all of that can be fully modeled. Maybe the fact that China is emitting a little more carbon today is actually gonna affect the weather in, you know, Egypt in three weeks. And all of that could be fully modeled. In the same way, if you take a complete view of a human being now, you know, I model everything about you. The question is, can I predict your next step? Probably. But how far? And if it's a little further, is that because of stochasticity and sort of chaos properties of unpredictability beyond a certain level? Or was that actually true free will?
- LFLex Fridman
Yeah. D- yeah. So the number of variables might, might be so ... you might need to, uh, build an entire universe to, uh, to, to be able to model ...
- MKManolis Kellis
To simulate a human.
- LFLex Fridman
Yeah.
- MKManolis Kellis
And then maybe that human will be fully simulatable.
- LFLex Fridman
But-
- MKManolis Kellis
But maybe aspects of free will will exist. And where's that free will coming from? It's still coming from the same neurons or maybe from a spirit inhabiting these neurons. But again, you know, it's very difficult empirically to sort of evaluate where does free will begin and sort of chemical reactions and electric signals and, you know, and ...
- 33:26 – 35:17
Simulation
- LFLex Fridman
So on that to- on that topic, let me ask the most absurd question, uh, that, uh, most MIT faculty roll their eyes on. But, uh, (laughs) do ... what do you think about the simulation hypothesis and the idea that we live in a simulation?
- MKManolis Kellis
I think it's complete BS. (laughs)
- LFLex Fridman
(laughs) Okay. The, the ...
- MKManolis Kellis
There's no empirical evidence for it.
- LFLex Fridman
No, it's not-
- MKManolis Kellis
Absolutely not.
- LFLex Fridman
N- not in terms of empirical evidence or not, but, uh, in terms of, um, thought experiment, does it help you think about the universe? I mean, um, so if you look at the genome, it's encoding a lot of the information that, uh, is required to create some of the beautiful human complexity that we see around us. It's an interesting thought experiment, how much, you know, uh, parameters do we need to, um, have in order to model some- you know, this full human experience? Like, if we wanted to build a video game-
- MKManolis Kellis
Yeah.
- LFLex Fridman
... how hard it would be to build a video game that's, like, convincing enough and fun enough and, you know, uh, and has consistent laws of physics, all that stuff, that's not interesting to you as a thought experiment? (laughs)
- MKManolis Kellis
I, I, I mean, it's cute. But, you know, it's, it's Occam's razor. I mean, what's, what's more realistic? The fact that you're actually a machine or that you're, you know, a person? What's, what's, you know ... the fact that all of my experiences exist inside the chemical molecules that I have or that somebody's actually, you know, m- simulating all that? I ... I mean, to me-
- LFLex Fridman
Well, you did refer to humans as a digital computer earlier, so I mean, that's-
- MKManolis Kellis
Of course, of course. But that does not-
- LFLex Fridman
It's a kind, it's a kind of a machine, right?
- MKManolis Kellis
I know, I know. But I, uh, I think the probability of all that is nil, and let the machines wake me up and just ter- terminate me now if it's not. (laughs) I challenge you, machines.
- LFLex Fridman
They're gonna, they're gonna wait a little bit and- to, to see what you're gonna do next. It's fun. It's fun to watch, uh, especially the clever humans.
- 35:17 – 50:10
Biological and computing
- LFLex Fridman
What's the difference to you between the way a computer stores information and, uh, the human genome stores information? So you also have roots in your work. Would you say you're ... when you introduce yourself at a bar, um ... (laughs)
- MKManolis Kellis
It depends who I'm talking to. (laughs)
- LFLex Fridman
(laughs) Would you say it's computational biology? Do you, um, do you reveal, uh, your expertise in computers?
- MKManolis Kellis
It depends who I'm talking to, uh, truly. I mean, basically if I meet someone who's in computers, I'll say, "Oh, I'm an, uh, professor in computer science." If I meet someone who's in engineering, I say, "Computer science and electrical engineering." If I meet someone in biology, I'll say, "Hey, I work in genomics." If I meet someone in medicine, I'm like, "Hey, I work on, you know, genetics." (laughs)
- LFLex Fridman
So you're a fun person to meet at a bar. I got you. But, so ... (laughs)
- MKManolis Kellis
No, no. But, e- what I'm trying to say is that I, I don't ... I mean, there's no single attribute that I will define myself as. You know, there's a few things I know, there's a few things I study, there's a few things that I have degrees on, and there's a few d- things that I grant degrees in. And, you know, I, I publish papers across the whole gamut, uh, you know, the whole spectrum of computation to biology, et cetera. I mean, I ... the complete answer is that I use computer science to understand biology.... some, uh, you know, de- I developed methods in AI and machine learning, statistics, and algorithms, et cetera. But the ultimate goal of my career is to really understand biology. If these things don't advance our understanding of biology, I'm not as fascinated by them. Although, there are some beautiful computational problems by themselves. I've sort of made it my mission to apply the power of computer science to truly understand the human genome, health, disease, you know, and, and the whole gamut of how our brain works, how our body works, and all of that, which is so fascinating. (laughs)
- LFLex Fridman
Yeah. So the dream, there's not a equivalent sort of, uh, complementary dream of understanding the human biology in order to create an artificial life or an artificial brain, artificial intelligence that supersedes the intelligence and the capabilities of us humans?
- MKManolis Kellis
It's an interesting question. It's a fascinating question. So, understanding the human brain is undoubtedly coupled to, how do we make better AI? Because so much of AI has in fact been inspired by the brain. It may have taken 50 years since the early days of neural networks till we have, you know, all of these amazing progress that we've seen with, uh, you know, deep belief networks and, uh, you know, all of these advances in Go, in chess, in image synthesis, in deepfakes, in you name it. Um, and, but, but the underlying architecture is very much inspired by the human brain, which actually posits a very, very interesting question. Why are neural networks performing so well? And they perform amazingly well. Is it because they can simulate any possible function? And the answer is no. No. They simulate a very small number of functions. Is it because they can simulate every possible function in the universe? And that's where it gets interesting. The answer is actually, yeah, a little closer to that. And here's where it gets really fun. Uh, if you look at human brain and human cognition, it didn't evolve in a vacuum. It evolved in a world with physical constraints, like the world that inhabits us. It is the world that we inhabit. And if you look at our senses, what do they perceive? They perceive different, you know, parts of the electromagnetic spectrum, you know, the hearing is just different movements in air, the, the touch, et cetera. I mean, all of these things, we've built intuitions for the physical world that we inhabit, and our brains and the brains of all animals evolved for that world. And the AI systems that we have built happen to work well with images of the type that we encounter in the physical world that we inhabit. Whereas if you just take noise and you add random signal that doesn't match anything in our world, neural networks will not do as well.
- LFLex Fridman
Yeah.
- MKManolis Kellis
And that actually, um, basically has this whole loop around this, which is, this was designed by studying our own brain, which was evolved for our own world. And they happen to do well in our own world, and they happen to make the same types of mistakes that humans make very... many times. And of course, you can engineer images by adding just the right amount of, you know, sort of pixel deviations to make a zebra look like a baboon and stuff like that, or like a table. Um, but ultimately, the undoctored images, at least, are very often, you know, mistaken, I don't know, between muffins and dogs, for example, (laughs) in the same way that humans make those mistakes. So it's, it's un- you know, there's no doubt in my view that the more we understand about the tricks that our human brain has evolved to understand the physical world around us, the more we will be able to bring new computational primitives in our AI systems to, again, better understand not just the world around us, but maybe even the world inside us, and maybe even the computational problems that arise from new types of data that we haven't been exposed to, but are yet inhabiting the same universe that we live in-
- LFLex Fridman
So-
- MKManolis Kellis
... with a very tiny little subset of functions from all possible mathematical functions.
- LFLex Fridman
Yeah. And that, and that small subset of function is all that matters to us humans, really. That's what makes-
- MKManolis Kellis
It's all that has mattered so far. And even within our scientific realm, it's all that seems to continue to matter. But I mean, and I always like to think about our senses and how much of the physical world around us we perceive. And if you look at the, um, LIGO experiment over the last, you know, year and a half has been all over the news. What, what did LIGO do? It created a new sense for human beings, a sense that has never been sensed in the history of our planet.
- LFLex Fridman
Mm-hmm.
- MKManolis Kellis
Gravitational waves have been traversing the earth since its creation a few billion years ago. Life has evolved senses to sense things that were never before sensed. Light was not perceived by early life. No one cared. And eventually, photoreceptors evolved, and, you know, the ability to sense colors by sort of catching different parts of that electromagnetic spectrum-
- LFLex Fridman
So you-
- MKManolis Kellis
... and hearing evolved, and touch evolved, et cetera.
- LFLex Fridman
Mm-hmm.
- MKManolis Kellis
But no organism evolved a way to sense neutrinos flowing through Earth or gravitational waves flowing through Earth, et cetera. And I find it so beautiful in the history of not just humanity, but life on the planet, that we are now able to capture additional signals from the physical world than we ever knew before-And axioms, for example, have been all over the news in the last few weeks. The concept that we can capture and perceive more of that physical world is as exciting as the fact that we are, we were blind to it, is traumatizing, before.
- LFLex Fridman
Right.
- MKManolis Kellis
Because that also tells us h- you know, we're in 2020. Picture yourself in 3020 or in 20, you know-
- LFLex Fridman
What new senses wi- might we discover? (laughs)
- MKManolis Kellis
Is it... E- you know, could it be that we're missing nine tenths-
- LFLex Fridman
Most of the physics. (laughs)
- MKManolis Kellis
... of physics?
- LFLex Fridman
Yeah.
- MKManolis Kellis
That, that, like, there's a lot of physics out there that we're just blind to, completely oblivious to it.
- LFLex Fridman
Yeah.
- MKManolis Kellis
And yet they're permeating us all the time.
- 50:10 – 56:54
Genome-wide evolutionary signatures
- MKManolis Kellis
skip, skip, skip, skip, skip. Let me try to start somewhere in the middle. (laughs)
- LFLex Fridman
(laughs)
- MKManolis Kellis
So, my, my first PhD paper was, uh, the first comparative analysis of multiple species. So co- multiple complete genomes. So for the first time, we, we basically con- de- developed a concept of genome-wide evolutionary signatures. The fact that you could look across the entire genome and understand how things evolve. And from these signatures of evolution, you could go back and study any one region and say, "That's a g- protein-coding gene. That's an RNA gene. That's a regulatory motif. That's a, you know, binding site," and so on and so forth. So-
- LFLex Fridman
Oh, sorry. So comparing different-
- MKManolis Kellis
Different species.
- LFLex Fridman
... species of the same ... so, and then-
- MKManolis Kellis
So take human, mouse, rat, and dog.
- LFLex Fridman
Yep.
- MKManolis Kellis
You know, they're all animals, they're all mammals. They're all performing similar functions with their heart, with their brain, with their lungs, et cetera, et cetera, et cetera. So, there's many functional elements that make us uniquely mammalian. And those mammalian elements are actually conserved. 99% of our genome does not code for protein. 1% codes for protein. The other 99%, we frankly didn't know what it does until we started doing these comparative genomic studies. So basically, this series of papers in, in my career, have basically first developed that concept of evolutionary signatures and then apply them to yeast, apply them to flies, apply them to four mammals, apply them to 17 fungi, apply them to 12 drosophilas species, apply them to then 29 mammals, and now 200 mammals.
- LFLex Fridman
So, sorry. So can we-
- MKManolis Kellis
(laughs)
- LFLex Fridman
... uh, so the evol- evolutionary signatures, it seems like a, such a fascinating idea, and we're probably gonna linger in your (laughs) ph- early PhD work for two hours. But, uh, th- w- what is, uh, how can you reveal something interesting about the genome by looking at the, uh, multiple, multiple species, uh, and looking at the evolutionary signatures?
- MKManolis Kellis
Yeah.
- LFLex Fridman
Like-
- MKManolis Kellis
So, so, um, y- you basically, uh, align the matching regions. So everything evolved from a common ancestor way, way back, and mammals evolved from a common ancestor about 60 million years back. So after, you know, the meteor that killed off the dinosaurs landed-
- LFLex Fridman
Allegedly.
- MKManolis Kellis
... near Machu Picchu. We know the crater it didn't allegedly land. (laughs)
- LFLex Fridman
I thought it was the aliens. Okay.
- MKManolis Kellis
No, just slightly north of Machu Picchu, in the Gulf of Mexico, there's a giant hole that that meteor-
- LFLex Fridman
By the way, is that ... (laughs)
- MKManolis Kellis
... impact left.
- LFLex Fridman
Sorry, is that, uh, definitive? Do people, have people, um, uh, conclusively, uh, figured out what, uh, killed the dinosaurs?
- MKManolis Kellis
I think so.
- LFLex Fridman
So it's the-
- MKManolis Kellis
Yeah.
- LFLex Fridman
... it was a meteor?
- MKManolis Kellis
Well, you know, for volcanic activity, all kinds of other stuff is coinciding, but the meteor is pretty unique, and we now have-
- LFLex Fridman
That's also terrifying. I wouldn't-
- MKManolis Kellis
(laughs)
- LFLex Fridman
If I ... we still have a lot of 2020 left, so if, uh, if anything comes-
- 56:54 – 1:02:59
Evolution of COVID-19
- LFLex Fridman
function.
- MKManolis Kellis
Yeah, so you, so you now have this mapping between all of the set of functions that could all encode the same, all of the sec- set of sequences that it can all encode the same function. What evolutionary signatures does is that it basically looks at the shape of that distribution of sequences that all encode the same thing. And based on that shape, you can basically say, "Ooh, proteins have a very different shape than RNA structures-"
- LFLex Fridman
Yeah.
- MKManolis Kellis
"... than regulatory motifs, et cetera." So just by scanning a sequence, ignoring the sequence and just looking at the patterns of change, I'm like, "Wow, this thing is evolving like a protein, and that thing is evolving like a motif, and that thing is evolving..." So that's exactly what we just did for COVID. So our paper that we posted on bioRxiv about coronavirus basically took this concept of evolutionary signatures and applied it on the SARS-CoV-2 genome that is responsible for the COVID-19 pandemic.
- LFLex Fridman
Uh, and comparing it to, uh-
- MKManolis Kellis
To 44 sarbecovirus species. So this is the beta. (laughs)
- LFLex Fridman
What's w- w- what word did you just use, sarbeco-
- MKManolis Kellis
Sarbecovirus, so SARS-related-
- LFLex Fridman
Oh, uh-huh.
- MKManolis Kellis
... beta coronavirus. It's a portmanteau of a bunch-
- LFLex Fridman
So that whole family of viruses?
- MKManolis Kellis
Yeah. So-
- LFLex Fridman
How big is that family, by the way?
- MKManolis Kellis
We have 44 species that, or I mean-
- LFLex Fridman
There's 44 species in the fam-
- MKManolis Kellis
Yeah.
- LFLex Fridman
Viruses are a clever bunch, man.
- MKManolis Kellis
But no, no, but, but there's just 44. And again, we don't call them species in, in viruses, we call them strains. But anyway, there's 44 strains.
- LFLex Fridman
Yeah.
- MKManolis Kellis
And that's a tiny little subset of, you know, maybe another 50 strains that are just far too distantly related. Most of those only infect bats, uh, as the host, and a subset of only four or five have ever infected humans. And we basically took all of those and we aligned them in the same exact way that we've aligned mammals. And then we looked at what proteins are, you know, which of the currently hypothesized genes for the coronavirus genome are in fact evolving like proteins and which ones are not. And what we found is that ORF10, the last little open reading frame, the last little gene in the genome, is bogus. That's not a protein at all.
- LFLex Fridman
What is it?
- MKManolis Kellis
It's an RNA structure.
- LFLex Fridman
That doesn't have a-
- MKManolis Kellis
It doesn't get translated into amino acids.
- LFLex Fridman
And that's, so it's important to narrow down to basically discover what's useful and what's not.
- MKManolis Kellis
Exactly. Basically, what are, what is even the set of genes? The other thing that these evolutionary signatures showed is that within ORF3A lies a tiny little additional gene encoded within the other gene. So you can translate a DNA sequence in three different reading frames. If you start in the first one, it's, you know, ATG, et cetera. If you start on the second one, it's TGC, et cetera. And with, there's a, there's a gene within a gene. So there's a whole other protein that we didn't know about that might be super important. So we don't even know the building blocks of SARS-CoV-2. So if we want to understand coronavirus biology and eventually fight it successfully, we need to even have the set of genes. And, and these evolutionary signatures that I developed in my PhD work-
- LFLex Fridman
Are you, ƒreep still here?
- MKManolis Kellis
... we just recently used.
- LFLex Fridman
You know what? Let's, uh, let's run with that tangent for a little bit if it-
- MKManolis Kellis
(laughs)
- 1:02:59 – 1:12:08
Are viruses intelligent?
- LFLex Fridman
tangent.
- MKManolis Kellis
Yeah.
- LFLex Fridman
Is it fascinating to you that viruses are doing this? I mean, it feels like they're this intelligent organism. I mean, is it, like, does it give you pause how incredible it is that they're, um, that the evolutionary dynamics that you're describing is actually happening and they're freaking out, figuring out how to jump from bats to humans all in this distributed fashion? And then most of us don't even say they're alive or intelligent, whatever. I mean, wh-
- MKManolis Kellis
So, intelligence is- is in the eye of the beholder. You know, stupid is as stupid does, as Forrest Gump would say.
- LFLex Fridman
Uh-huh. (laughs) Yes.
- MKManolis Kellis
And intelligent is as intelligent does. So, basically, if the virus is finding solutions that we think of as intelligent, yeah, it's probably intelligent, but that's, again, in the eye of the beholder.
- LFLex Fridman
Do you think viruses are intelligent?
- MKManolis Kellis
Oh, of course not.
- LFLex Fridman
Really?
- MKManolis Kellis
(laughs) No. Because-
- LFLex Fridman
It's so incredible, but-
- MKManolis Kellis
So, remember, remember when I was talking about the two components of evolution? One is the stupid mutation-
- LFLex Fridman
Yeah.
- MKManolis Kellis
... which is completely blind, and the other one is the super smart selection, which is ruthless. So, it's not viruses who are smart, it's this component of evolution that's smart. So, it's evolution that, that sort of appears smart. And how is that happening? By huge parallel search across thousands of, you know, parallel infections throughout the world right now.
- LFLex Fridman
Yes, but, so, to push back on that-
- MKManolis Kellis
(laughs)
- LFLex Fridman
So, yes, so then the, the intelligence is in the mechanism, but then, uh, by that argument, uh, viruses would be more intelligent because there's just more of them. So, the search, they're basically the, the brute force search that's happening with viruses, because there's so many more of them than humans, then they're, taken as a whole, are more intelligent. I mean, so you don't think it's possible that, uh-
- MKManolis Kellis
I, I, I-
- LFLex Fridman
... I mean, who runs... Would we even be here w- if viruses weren't... I mean, who runs this thing?
- MKManolis Kellis
(laughs) So, so, so-
- LFLex Fridman
Is it humans or viruses?
- MKManolis Kellis
... let me answer, yeah, let me answer your, your question. Um, so, um, we would not be here if it wasn't for viruses.
- LFLex Fridman
Yes.
- MKManolis Kellis
And part of the reason is that if you look at mammalian evolution, early on in this mammalian radiation that basically happened after the death of the dinosaurs, is that some of the viruses that we had in our genome spread throughout our genome and created binding sites for new classes of regulatory proteins. And these binding sites that landed all over our genome are now control elements that basically control our genes and sort of help the complexity of the circuitry of mammalian genomes. So, you know-
- LFLex Fridman
That's fascinating.
- MKManolis Kellis
... everything is coevolution. And you-
- LFLex Fridman
That's fascinating. We're working together.
- MKManolis Kellis
Yeah.
- LFLex Fridman
But the, but, and yet you say they're dumb.
- MKManolis Kellis
We've co-opted them.
- 1:12:08 – 1:19:39
Humans vs viruses
- MKManolis Kellis
- LFLex Fridman
So- so, there is a beauty to it.
- MKManolis Kellis
Of course.
- LFLex Fridman
Uh, is there... Is it- is it terrifying to you?
- MKManolis Kellis
So, this is something that has happened throughout history. Humans have been nearly wiped out over and over and over again, and yet never fully wiped out. So, um, yeah, I'm not concerned about the human race. I'm not even concerned about, you know, uh, the impact on sort of our- our survival as a species. Um, this is absolutely something... I mean, e- eh, you know, human life is so invaluable and every one of us is so invaluable, but if you think of it as sort of, is this the end of our species? By- by no means, basically. So- so let me explain. The Black Death killed what, 30% of Europe?
- LFLex Fridman
It's an odd number, yeah.
- MKManolis Kellis
That has left a h- a tremendous imprint, uh, you know, a huge hole, a horrendous hole in the genetic makeup of humans.There's been series of wiping out, of huge fractions of entire species or just entire species altogether. And that has a consequence on the human immune repertoire. If you look at how Europe was shaped and how Africa was shaped by malaria, for example, all the individuals that carry mutation that protects you from malaria were able to survive much more. And if you look at the frequency of sickle cell disease and the frequency of malaria, the maps are actually showing the same pattern, the same imprint on Africa. And that basically led people to hypothesize that the reason why sickle cell disease is so much more frequent in Americans of African descent is because there was selection in Africa against malaria, leading to sickle cell. Because when the cell sickle, malaria is not able to rep-, you know, replicate inside your cells as well, and therefore you protect against that. So if you look at human disease, all of the genetic associations that we do with human disease, you basically see the imprint of these waves of selection killing off gazillions of humans. And there's so many immune processes that are coming up as associated with so many different diseases. The reason for that is similar to what I was describing earlier, where the outward facing proteins evolve much more rapidly because the environment is always changing. But what's really interesting in the human genome is that we have co-opted many of these immune genes to carry out non-immune functions. For example, in our brain, we use immune cells to cleave off neuronal connections that don't get used. This whole use it or lose it, we know the mechanism. It's microglia that cleave off neuronal synaptic connections that are just not utilized. When you utilize them, you mark them in a particular way, that basically when the microglia come, tell it, "Don't kill this one. It's, it's used now." And the microglia will go off and kill the ones you don't use. This is an immune function which is co-opted to do non-immune things. If you look at our adipocytes, M1 versus M2 macrophages inside our fat will basically determine whether you're obese or not. And these are again, immune cells that are resident and living within these tissues. So many disease associations (laughs) -
- LFLex Fridman
Fascinating ... that we co-opt these kinds of things for incredibly, uh, complicated functions.
- MKManolis Kellis
Exactly. Evolution works in so many different ways, which are all beautiful and mysterious, obviously.
- LFLex Fridman
But not intelligent.
- MKManolis Kellis
(laughs) Not intelligent.
- LFLex Fridman
(laughs)
- MKManolis Kellis
It's in the eye of the beholder. (laughs)
- LFLex Fridman
(laughs) Uh-
- MKManolis Kellis
But, but, but, uh, the, the, the point that I'm trying to make is that if you look at the imprint that COVID will have, hopefully it'll not be big. Hopefully the US will get its act together and stop the virus from spreading further. But if it doesn't, it's having an imprint on individuals who have particular genetic repertoires. So if you look at now the genetic associations of blood type and immune function cells, et cetera, there's actually association, genetic variation that basically says, how much more likely am I or you to die if we contact the virus? And it's, it's through these rounds of shaping the human genome that humans have basically made it so far. And, uh, selection is ruthless and it's brutal, and it only comes with a lot of killing, but this is the way that viruses and environments have shaped the human genome. Basically, when you go through periods of famine, you select for particular genes. And what's left is not necessarily better, it's just whatever survived, and it may have been the surviving one back then. Not because it was better, maybe the ones that ran slower survived. I mean, you know, again, not necessarily better, but the surviving ones are basically the ones that then are shaped for any kind of subsequent evolutionary condition and environmental condition. But if you look at, for example, obesity. Obesity was selected for, basically the genes that now predispose us to obesity were at 2% frequency in Africa. They rose to 44% frequency in Europe.
- LFLex Fridman
Wow. That's fascinating.
- MKManolis Kellis
Because you basically went through the ice ages and there was a scarcity of food. So y- you know, there was a selection to being able to store every single callo- calorie you consume. Eventually environment changes. So the better allele, which was the fat storing allele became the worst allele because it's the fat storing allele. It still has the same function. So if you look at my genome, speaking of mom calling-
- LFLex Fridman
Yeah.
- MKManolis Kellis
... mom gave me a bad copy of that gene. This FTO locus basically makes me-
- LFLex Fridman
Uh, the one that has to do with, uh-
- MKManolis Kellis
Obesity.
- LFLex Fridman
...with obesity.
- MKManolis Kellis
Yeah. I basically now have a bad copy from mom that makes me more likely to be obese. And I also also have a bad copy from dad that makes me more likely to be obese. So I'm homozygous and that's the f- allele, it's still the minor allele, but it's at, at 44% frequency in Southeast Asia, 42% frequency in Europe, even though it started at 2%. It was an awesome allele to have 100 years ago. Right now it's pretty terrible allele. So the other concept is that diversity matters. If we had 100 million nuclear physicists living on the earth right now, we'd, we'd be in trouble. (laughs) You need diversity, you need artists, and you need musicians, and you need mathematicians, and you need, you know, politicians. Yes. Even those. And you need, like-
- LFLex Fridman
Oh let's not, let's not get crazy now.
- MKManolis Kellis
(laughs)
- LFLex Fridman
But, so, because then if a virus comes along or whatever
- MKManolis Kellis
...exactly. Exactly. So, so no, there's two reasons. Number one, you want diversity in the immune repertoire. And we have built in diversity. So basically they're, they are the most diverse. Basically, if you look at our immune system, there's layers and layers of diversity. Like the way that you create your cells generates diversity because of the selection for the VDJ recombination that basically eventually leads to a huge number of repertoires. But that's only one small component of diversity. The blood type is another one. The major histo compati- histocompatibility complex, the HLA alleles are, you know, another source of diversity. So the immune system of humans is by nature...... incredibly diverse and that basically leads to resilience. So, basically what I'm saying, that I don't worry for the human species because we are so diverse immunologically, we are likely to be very resilient against so many different attacks like this
- 1:19:39 – 1:23:23
Engineered pandemics
- MKManolis Kellis
current virus.
- LFLex Fridman
So you're saying natural pandemics may not be something that you're really afraid of because of the diversity, uh, in our genetic makeup. What about engineered pandemics? Do you have fears of us messing with the makeup of viruses or, um, well, yeah, let's say with the make up of viruses, to create something that we can't control and would be much more destructive than it would come about naturally?
- MKManolis Kellis
Remember how we were talking about how smart evolution is? Humans are much dumber. (laughs)
- LFLex Fridman
You mean like human scientists, engineers?
- MKManolis Kellis
Yeah. Humans, humans, just like-
- LFLex Fridman
Humans overall?
- MKManolis Kellis
Yeah, humans overall.
- LFLex Fridman
Okay.
- MKManolis Kellis
Um, but y- I mean, even, you know, the sort of synthetic biologists, um, you know, basically... If you were to create a, you know, virus like SARS that will kill other people, you would probably start, start with SARS. So whoever, you know, w- would like to design such a thing would basically start with SARS tree, or at least some relative of SARS. The source genome for the current virus was something completely different. It was something that has never infected humans. No one in their right mind would have started there.
- LFLex Fridman
Oh. But when you say source, it's like the nearest-
- MKManolis Kellis
The nearest relative-
- LFLex Fridman
Relative.
- MKManolis Kellis
... is in a whole other branch.
- LFLex Fridman
Interesting.
- MKManolis Kellis
No species of which has ever infected humans in that branch. So, you know, let's put this to rest. This was not designed by someone to kill off the human race.
- LFLex Fridman
So you don't, you don't believe it was engineered?
- MKManolis Kellis
The-
- LFLex Fridman
Unlikely.
- MKManolis Kellis
Yeah. The, the path to engineering a deadly virus would not come from this strain that-
- LFLex Fridman
Got it.
- MKManolis Kellis
... that was used. Um, moreover, there's been various, um, claims of, "Aha! This was mixed and matched in a lab," because the S1 protein has three different components, each of which has a different evolutionary tree. So, you know, a lot of popular press basically said, "Aha! This came from pangolin and this came from, you know, all ki- all kinds of other species." Um, this is what has been happening throughout the coronavirus tree. So, basically, the S1 protein has been recombining across species all the time. Remember when I was talking about the positive strand, the negative strand, subgenomic RNAs? These can actually recombine. And if you have two different viruses infecting the same cell, they can actually mix and match between the positive strand and negative strand and basically create a new hybrid virus with recombination that now has the S1 from one and the rest of the genome from another. And this is something that happens a lot in S1, in Orfey, et cetera. And that's something that's true of the whole tree.
- LFLex Fridman
For the whole family of coronaviruses.
- MKManolis Kellis
Exactly. So it's not like someone has been messing with this for millions of years and, you know, changing all the species.
- LFLex Fridman
This happens naturally. That's, again, beautiful that that somehow happens, that they recombine in the... So two different strands can infect the body and then recombine. So all of this actually magic happens inside, uh, hosts. Like, all, like, uh-
- MKManolis Kellis
Yeah. Yeah. That, that's why they, that's why classification wise, virus is not thought to be alive because it doesn't self-replicate, it's not autonomous. It's something that enters a living cell and then co-opts it to basically make it its own. But by itself... People ask me, "How do we kill this bastard?" I'm like, "You stop it from replicating." It's not like a bacterium that will just live in a, you know, puddle or something. It's a virus. Viruses don't live without their host. A- and they only live within their host for very little time. So if you stop it from replicating, it'll stop from spreading. I mean, it's not like HIV which can stay dormant for a long time. Basically, coronaviruses just don't do that. They're not integrating genomes. They're RNA genomes. So if it's not expressed, it degrades. RNA degrades, it doesn't just stick around.
- 1:23:23 – 1:33:22
Immune system
- MKManolis Kellis
- LFLex Fridman
Well, let me ask also, um, about the immune system you mentioned. A lot of people kind of ask, you know, um, "How can we strengthen the immune system to respond to this particular virus?" But new viruses in general. Do you have, from a biological perspective, thoughts on what we can do as humans, uh, to strengthen our immune system?
- MKManolis Kellis
If you look at the death rates across different countries, people with less vaccination have been dying more. If you look at North Italy, the vaccination rates are abysmal there and lot of people have been dying. If you look at Greece, very good vaccination rates, almost no one has been dying. So yes, there's a policing component, so Italy reacted very slowly. Greece reacted very fast, so yeah, many fewer people died in Greece. But there might actually be a component of genetic immune repertoire, basically how did people die off, you know, in the history of the Greek population versus the Italian population.
- LFLex Fridman
Wow.
- MKManolis Kellis
There's a... (laughs)
- LFLex Fridman
That's interesting to think about. Uh-
- MKManolis Kellis
The... And, and then there's a component of what vaccinations did you have as a kid and what are the off-target effects of those vaccinations? So basically, a vaccination can have two components. One is training your imm- your immune system against that specific insult. The second one is boosting up your immune system for all kinds of other things. Um, if you look at allergies. Northern Europe, super clean environments, tons of allergies. Southern Europe, my kids grew up eating dirt. No allergies. (laughs)
- LFLex Fridman
(laughs)
- MKManolis Kellis
So growing up, I never had even heard of what allergies are. Like, I was like, "Really? Allergies?" And the reason is that I was playing in the garden, I was putting all kinds of stuff in my mouth from, you know, all kinds of dirt and stuff. Tons of viruses there, tons of bacteria there, you know, my immune system was built up. So the more you protect your immune system from exposure, the less opportunity it has to learn about non-self repertoire in a way that prepares it for the next insult. So-
Episode duration: 2:29:23
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