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Speaker 1: Viruses are in the air we breathe, in the water

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Speaker 1: we drink. They're in the ground we walk on there,

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Speaker 1: on our skin, they're in our bellies. They have us surrounded,

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Speaker 1: and the wild thing is we've only identified a fraction

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Speaker 1: of them. In other words, not only are we surrounded

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Speaker 1: and permeated by viruses, we're surrounded and permeated by viral

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Speaker 1: dark matter, by viruses that we don't even know exist.

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Speaker 2: We have lots of viruses in us and we have

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Speaker 2: no idea what they're doing, and potentially in that dark matter,

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Speaker 2: there are some answers to the questions on what are

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Speaker 2: they doing there.

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Speaker 1: I'm Jacob Goldstein, and this is Incubation. Today, on our

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Speaker 1: final episode of season two, we're going out to the

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Speaker 1: scientific frontier to talk about all the viruses we don't

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Speaker 1: know about in the world and in our bodies. In

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Speaker 1: the second half of the show today, I'll be speaking

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Speaker 1: with a researcher who has recently discovered hundreds of families

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Speaker 1: of viruses that live inside the human gut, and he's

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Speaker 1: found a link that suggests some of those viruses could

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Speaker 1: actually help kids stay healthy. But first I'm going to

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Speaker 1: talk with Ken Steadman he's a professor of biology at

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Speaker 1: Portland State University. He studies viral dark matter, which basically

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Speaker 1: means he goes looking for viruses in wild places. To start,

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Speaker 1: I asked him, how do you look for a virus

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Speaker 1: that nobody knows exists?

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Speaker 2: A couple of different ways. All viruses that we know of,

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Speaker 2: by definition, have to have a host that they infect.

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Speaker 2: What we do is we'll go and collect samples in

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Speaker 2: the craziest places we can find, usually volcanic hot springs,

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Speaker 2: and then we bring them back to lab and see

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Speaker 2: if they infect our favorite microbes that also happen to

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Speaker 2: grow in these hot springs.

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Speaker 1: I've read a little bit about your work at last

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Speaker 1: in Volcanic National Park in northern California, So tell me

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Speaker 1: about what's going on there. Tell me about Boiling Springs Lake.

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Speaker 2: So, Boiling Springs Lake I like to describe as the

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Speaker 2: biggest hot spring in the world that nobody has ever

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Speaker 2: heard of. It's a slight exaggeration. The low temperature in

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Speaker 2: the lake is about one hundred and thirty hundred and

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Speaker 2: forty degrees fahrenheit.

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Speaker 1: And so what does that mean for finding weird viruses?

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Speaker 2: Well, hang on just a second, that's the temperature. I

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Speaker 2: haven't told you about the pH yet, have I Wait

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Speaker 2: a minute.

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Speaker 1: If you like the temperature, you're gonna love the pH exactly.

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Speaker 2: So the pH is about two.

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Speaker 1: pH of two means it's it's acidic. It's highly acidic.

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Speaker 1: So not great for soaking is what you're not great for.

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Speaker 2: We've seen people walking up there and they're a swimming

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Speaker 2: gear and we tell them not a real good idea.

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Speaker 1: So you go to this hot, acidic lake and what

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Speaker 1: what do you do there?

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Speaker 2: We just took about two hundred liters worth of water

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Speaker 2: from the lake and then purified all of the virus

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Speaker 2: sized particles in it, then determined what their genetic sequences were,

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Speaker 2: what we call them meta genome, but basically all the viruses,

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Speaker 2: what genes do they have in.

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Speaker 1: So you're basically just what pouring this acid into a

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Speaker 1: machine and saying, tell me all the genes that are in.

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Speaker 2: Here or or less. Yeah. So one of the things

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Speaker 2: about viruses which makes virus is incredibly unique is they

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Speaker 2: have what we like to call we call it a

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Speaker 2: very on it's the virus structure. So the lunar lander

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Speaker 2: module kind of thing.

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Speaker 1: Right, your classic virus looks like a little lunar lander

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Speaker 1: like a pod, and then little legs coming out right.

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Speaker 2: Absolutely, and it's relatively small.

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Speaker 1: So what you do is sayge right, that's the classic phase.

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Speaker 1: That's the thing that lands on the bacterium and then

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Speaker 1: inserts its genetic material.

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Speaker 2: Injects it exactly. But even if you think about no

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Speaker 2: Sarscobe two virus that causes COVID nineteen also is a

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Speaker 2: little bag which has genes on the inside of it.

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Speaker 2: So you break up in the bag and you throw

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Speaker 2: it into the machine and then it gives you back

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Speaker 2: hundreds of thousands of sequences in our case now millions

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Speaker 2: of sequences with the newest technology, so millions of genes,

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Speaker 2: hundreds of thousands of genes. But they're not genes, they're

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Speaker 2: gene fragments, they're little pieces. Now, at first you just

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Speaker 2: want to look at what those little pieces are relative

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Speaker 2: to known sequences.

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Speaker 1: Uh huh.

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Speaker 2: That the dark matter is going to be, you know,

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Speaker 2: those little pieces that don't match anything, and the light

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Speaker 2: matter is going to be stuff that does Ninety plus

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Speaker 2: percent of the sequences that we got back of our

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Speaker 2: hundreds of thousands of sequences didn't match anything.

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Speaker 1: And what did you think when you saw that, Oh.

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Speaker 2: It's like other environments, other people seemed very similar things.

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Speaker 2: So you do this with seawater, you do this with

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Speaker 2: things you find in soil. Ninety odd percent plus or

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Speaker 2: minus don't match anything.

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Speaker 1: Does that mean that we don't know about ninety percent

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Speaker 1: of the viruses that are out in the world. Is

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Speaker 1: that broadly what that implies?

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Speaker 2: That is exactly what it implies.

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Speaker 1: And it's not just in a weirdo boiling acid lake.

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Speaker 1: How about just in the dirt. If I just went

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Speaker 1: into my yard and dug up some dirt and send

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Speaker 1: it to somebody who could put it in one of

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Speaker 1: your machines. What percentage of the viruses in my backyard

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Speaker 1: are known to science?

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Speaker 2: Roughly?

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Speaker 1: Wow, eighty percent are dark matter are unknown. I love that.

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Speaker 2: It's keeps us employed.

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Speaker 1: Yeah, so okay, so you get this result back it's

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Speaker 1: ninety percent is unknown. What like? And so what you

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Speaker 1: just have is like a genetic mess that you don't

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Speaker 1: know what to do with, because it's not like each

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Speaker 1: little fragment is like, oh, that's a new virus. It's

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Speaker 1: just these are weird fragments that we don't understand.

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Speaker 2: Yeah, exactly weird fragments if we don't understand. But one

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Speaker 2: of the other things that we found is some of

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Speaker 2: the fragments that we could actually identify didn't look like

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Speaker 2: sequences that we should have found, Meaning not only are

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Speaker 2: they different than anythings that's been found before.

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Speaker 1: They are like too weird, They're like, wait, that doesn't

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Speaker 1: make any sense.

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Speaker 2: How could that even be? Exactly did you think you

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Speaker 2: had made a mistake of some sort so that the

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Speaker 2: machine was broken. We thought that we had absolutely screwed

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Speaker 2: up in this case. So we've got genetic material virus,

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Speaker 2: you've got RNA viruses, you got DNA viruses, right, So.

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Speaker 1: Basically a virus is just like a bag with genetic

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Speaker 1: material in it. And there's some viruses have DNA and

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Speaker 1: some viruses have RNA. And even though these are like

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Speaker 1: two types of viruses, sort of historically evolutionarily, they're like

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Speaker 1: really different from each other.

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Speaker 2: Right, DNA viruses and RNA viruses we always thought were

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Speaker 2: completely different relative to each other. And if you think

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Speaker 2: about the evolutionary relationship between between RNA viruses and DNA viruses,

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Speaker 2: there basically seems to be almost none.

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Speaker 1: Like how big is the gap? Sort of whatever evolutionarily,

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Speaker 1: how different are DNA and RNA viruses?

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Speaker 2: So the difference between DNA and RNA viruses is probably

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Speaker 2: billions of years evolutionarily speaking.

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Speaker 1: Okay, I was gonna say, like, it's like as big

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Speaker 1: as the difference between mammals and reptiles, but it's way

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Speaker 1: bigger than that.

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Speaker 2: It's probably more like the difference between you know, bacteria

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Speaker 2: and people, bacterian people exactly, much more like that in

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Speaker 2: terms of evolutionary difference.

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Speaker 1: Wow. Okay, So there are these profoundly different things.

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Speaker 2: So we sequenced a bunch of DNA put into our machine,

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Speaker 2: you know, said hey, get some DNA sequences, and then

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Speaker 2: some of those proxially a couple of thousand sequences that

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Speaker 2: actually match. Something in those sequences were things that look

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Speaker 2: like RNA viruses in terms of their sequence.

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Speaker 1: But it's DNA that you're But we sequenced DNA.

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Speaker 2: Yeah, but we and when I say we, mostly a

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Speaker 2: graduate student working in our group, Jeff Deemer. He then

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Speaker 2: started to try and put some of these pieces together.

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Speaker 2: What he found was those pieces that looked like RNA

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Speaker 2: viruses were connected genetically to sequences that looked like DNA viruses.

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Speaker 1: Okay, and connected like physically like that they were physically

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Speaker 1: almost like the one piece of a chain of genetic

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Speaker 1: material exactly.

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Speaker 2: And then what we did is we went back to

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Speaker 2: the samples that we collected from Boiling Springs Lake, and

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Speaker 2: instead of pouring them into the machine to get the sequences,

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Speaker 2: we then made many many copies of whatever this piece was.

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Speaker 2: And this piece was to show that were actual connected

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Speaker 2: to each other. So there are these what we're now

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Speaker 2: calling cruci viruses that appear to have evolved by DNA

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Speaker 2: viruses and RNA viruses coming together.

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Speaker 1: Okay, so we thought these were like totally different kinds

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Speaker 1: of viruses, but now you have discovered this new kind

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Speaker 1: of virus that's kind of like a cross between the

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Speaker 1: two of them. Right, what does that mean? Like, what

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Speaker 1: does it mean for how we think about RNA viruses

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Speaker 1: and DNA viruses.

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Speaker 2: It means that there's communication between them, and there's this recombination.

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Speaker 2: So it's not billions of years of evolutionary difference, which

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Speaker 2: is what we thought. Now it looks as if they

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Speaker 2: can be exchanging genetic information with each other, which is

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Speaker 2: really kind of revolutionary in terms of thinking about virus

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Speaker 2: evolution and what it means is. We always thought DNA

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Speaker 2: viruses evolved like this and RNA viruses evolved like this,

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Speaker 2: But if they can exchange genes with each other, that

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Speaker 2: kind of throws a lot of what we think about

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Speaker 2: virus evolution kind of out the window. Turns out that

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Speaker 2: these viruses in and of them els are just so

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Speaker 2: different from any other virus anybody's ever seen before, in

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Speaker 2: terms of their shape, in terms of their genes, what

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Speaker 2: is in them?

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Speaker 1: So you and your colleagues found this, this crucivirus in

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Speaker 1: the boiling acid Lake. I know that since then a

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Speaker 1: number of other of these cruciviruses have been found. So

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Speaker 1: just give me the landscape. Give me what we know

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Speaker 1: so far of like where are they, what are they doing, etc.

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Speaker 2: We do not know what they're doing. Crucy virus has

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Speaker 2: been found in boiling Springs Lake, Antarctic lakes, in deep

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Speaker 2: sea sediments off the coast of Greenland, in Korean air samples,

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Speaker 2: isopods off the coast of Oregon, monkey feces, in dragonfly guts,

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Speaker 2: soil just outside the lab at Portland State University. Basically

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Speaker 2: anywhere that we have looked, we've found these crucy viruses.

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Speaker 2: Very low amounts of them, but seem to be very ubiquitous.

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Speaker 2: So where are the everywhere?

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Speaker 1: Love it?

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Speaker 2: What are they doing? We don't know.

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Speaker 1: Are they in my body right now?

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Speaker 2: Probably in your body right now.

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Speaker 1: So these things are all around us, all over the world,

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Speaker 1: possibly in our guts, and nobody knows what they're doing.

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Speaker 2: That is exactly correct. I love it me too.

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Speaker 1: So what do we know about like what they're doing.

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Speaker 2: We're trying to figure out what they infect. We think

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Speaker 2: they're infecting microbial EU carry out, So things like fungi

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Speaker 2: or protus, these paramesia things you know swimming around in lakes.

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Speaker 1: Are there are those things? Also? Are there also organisms

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Speaker 1: like that in our bodies?

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Speaker 2: There definitely are?

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Speaker 1: Is that part of the microflora?

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Speaker 2: Yeah, we have. We have a euchreytic microflora. Mostly these

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Speaker 2: are going to be fungi, some kinds of yeats, et cetera.

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Speaker 2: But there are many other of the And again this

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Speaker 2: is something which has been not very well studied, so

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Speaker 2: you kind of put in environmental viruses have not been

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Speaker 2: well studied. These microbial EU carry outs have not been

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Speaker 2: very well studied. So you put those two together, extremely

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Speaker 2: poorly studied.

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Speaker 1: Very dark. It's very dark matter.

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Speaker 2: Very dark matter, but at the same time really exciting

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Speaker 2: because there's so much to discover.

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Speaker 1: Like why does microbial dark matter matter?

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Speaker 2: Besides being cool, I think it's an area where we

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Speaker 2: can make discoveries. There's so much we don't know. We

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Speaker 2: have lots of viruses in US and we have no

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Speaker 2: idea what they're doing, and potentially in that dark matter

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Speaker 2: there are some answers to the questions on what are

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Speaker 2: they doing there? So I think that that's a very

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Speaker 2: important thing to think about.

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Speaker 1: Not just how are they making us sick, but how

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Speaker 1: are they keeping us healthy? How might they get out

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Speaker 1: of balance at times and contribute in indirect ways to sickness?

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Speaker 1: Certainly seems plausible. We know that happens with the bacteria

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Speaker 1: in our gut.

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Speaker 2: Yeah, I think that that's a very reasonable thing to

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Speaker 2: think about. And then just in a larger ecological sense,

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Speaker 2: you know, understanding the ecology. There's still so much that

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Speaker 2: we don't know. I think understanding that virus' role in

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Speaker 2: not just us, but also in life on our planet.

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Speaker 2: I think understanding that dark matter will really help us

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Speaker 2: understand what's going on with all of these different pirates.

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Speaker 1: I appreciate your time. It was a fun conversation.

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Speaker 2: Yeah, it was fun conversation for me too. I learned things,

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Speaker 2: So thank you for that good.

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Speaker 1: Ken Stedman is a biology professor and extreme virologist at

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Speaker 1: Portland State University. His work and his team's work are

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Speaker 1: expanding our idea of what a virus can be in

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Speaker 1: a minute, discovering hundreds of kinds of new viruses that

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Speaker 1: live in the human gut. I'm going to go out

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Speaker 1: on a limb and say the most underrated viruses are phages.

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Speaker 1: Phages are the viruses that infect bacteria. They're the most

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Speaker 1: abundant biological entity on Earth and their killers.

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Speaker 3: Every other bacterium on Earth gets killed by a virus

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Speaker 3: every day.

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Speaker 1: Actually, that's wild to think about.

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Speaker 3: It really sucks for them.

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Speaker 1: Shiraz ali Sha studies the phages that live inside people.

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Speaker 1: Your researcher on a project called COPSAC, the Copenhagen Prospective

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Speaker 1: Studies for Asthma in Childhood. The project is following hundreds

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Speaker 1: of kids from birth into childhood to try to understand

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Speaker 1: the causes of asthma. Shiraz focuses on the human virum,

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Speaker 1: the universe of viruses that live in the human gut

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Speaker 1: and he told me that studying the viroom from birth

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Speaker 1: is really important.

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Speaker 3: In the first year of life, the baby has an

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Speaker 3: immune system that has not yet matured, so it does

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Speaker 3: not know how to distinguish friend from foe. What happens

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Speaker 3: in the first year of life is that the immune

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Speaker 3: system is still trying to get to know what is

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Speaker 3: it supposed to attack and what is it not supposed

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Speaker 3: to attack. And it seems that there's more and more

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Speaker 3: evidence showing that if you are not exposed to a

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Speaker 3: diverse array of good bacteria in the body and on

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Speaker 3: the body within the first year of life, then the

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Speaker 3: immune system is not properly trained, and then you're way

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Speaker 3: more prone to chronic inflammatory or immune diseases in the future,

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Speaker 3: like asthma like asthma, like allergy like asthma, even stuff

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Speaker 3: like depression and anxiety, inflammation linked heart disease, most definitely cancer,

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Speaker 3: most definitely diabetes, most definitely yes.

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Speaker 1: So okay, so now you're getting into some of what

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Speaker 1: you study, right, tell me about your work on this.

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Speaker 3: So this is a place called COPSAC Copenhagen Perspective Studies

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Speaker 3: for Asthma in Childhood.

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Speaker 1: It's a place where they're trying to understand how asthma

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Speaker 1: works in kids.

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Speaker 3: Exactly, Okay, and so and so. The way that they

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Speaker 3: do this is basically, they have a bunch of kids

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Speaker 3: that were born in twenty ten and they've been following

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Speaker 3: them since the moms got pregnant and today they're like

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Speaker 3: fifteen years old.

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Speaker 2: Right.

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Speaker 3: What they're doing is they're recording as much data on

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Speaker 3: these children as possible as humanly possible, like where do

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Speaker 3: they go to date hair, how many siblings do they have,

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Speaker 3: but also blood tests, you know, which chemicals do they

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Speaker 3: have in their bodies in their pee, what bacteria do

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Speaker 3: they have in their poop, in their lungs, et cetera,

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Speaker 3: et cetera. So we have like jigabtes upon jigabat also

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Speaker 3: their own genes, their own genomes we also have.

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Speaker 1: And so, just to be clear, it's the idea of

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Speaker 1: doing all this and starting before the child is even born.

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Speaker 1: Is the question they're trying to answer, why do some

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Speaker 1: people get asthma and others don't?

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Speaker 3: Exactly Because even though asthma is such a common childhood

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Speaker 3: kind of disease, it's very poorly understrue. And this is

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Speaker 3: not only the case for asthma. It's also the case

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Speaker 3: for all the other chronic diseases basically that kill adults,

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Speaker 3: like cancer, heart disease, diabetes, you know, chronic respiratory disease,

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Speaker 3: multiple scrosis, you know, all of these. And so maybe

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Speaker 3: by collecting all of this data on the children, we

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Speaker 3: can start predicting based on the data, who's going to

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Speaker 3: get which disease, and based on that, maybe we can

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Speaker 3: figure out, Okay, if we do this, this and this,

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Speaker 3: maybe we can avoid that and that and that chronic disease.

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Speaker 3: Every time the kids visit us, and they do so

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Speaker 3: once a year, we take as money samples as we

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Speaker 3: possibly can.

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Speaker 1: Right, So you have this whole poop library going over

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Speaker 1: the kid's whole lifetime that you can sort of examine

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Speaker 1: over time. Yes, and how many kids are in this cohort?

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Speaker 3: So we have two horts and what I'm going to

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Speaker 3: talk about today. The data is from the corps AC

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Speaker 3: twenty ten cohorts. So they were born in twenty ten.

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Speaker 3: They're like fourteen years old now, right, And the twenty

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Speaker 3: ten cohort is seven hundred kids.

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Speaker 1: So the cohort you're following is seven hundred kids who

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Speaker 1: were born in twenty ten. You're coming into this as

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Speaker 1: a person who has been studying viruses that attack bacteria

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Speaker 1: for purposes here, and so when you get there.

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Speaker 2: What do you do?

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Speaker 3: I get there and then my boss he basically explains

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Speaker 3: me some of the studies that they've been doing on

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Speaker 3: the bacteria in the gut so far. And one of

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Speaker 3: the major studies that they did just like one year

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Speaker 3: before I came was that they found that in one

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Speaker 3: year old, when you're basically still a baby, the bacteria

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Speaker 3: that you have in your gut when you're a baby

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Speaker 3: end up determining whether or not you get asthma as

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Speaker 3: a five year old. And I was like, what, I mean,

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Speaker 3: how is that even possible? And so what the general

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Speaker 3: picture is that if you have only a few different

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Speaker 3: bacteria in your gut when you're one year old, then

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Speaker 3: you have much higher risk of getting asthma as a

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Speaker 3: five year old, right, But if you have like loads

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Speaker 3: and loads of different bacteria in your gut when you're

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Speaker 3: one year old, then you're much more protected from asthma

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Speaker 3: as a five year old. And so basically that that

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Speaker 3: got me thinking, Wow, that means that most bacteria are

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Speaker 3: actually good for us. I mean, there are few bacteria,

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Speaker 3: maybe one hundred species in total that can cause infection,

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Speaker 3: But the total number of bacteria in nature is like

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Speaker 3: one hundred million species at least, So those other one

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Speaker 3: hundred million are not causing. It's just one out of a

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Speaker 3: million bacterium.

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Speaker 1: That is bad and the other one in a million

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Speaker 1: gives him a bad name, and so go on.

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Speaker 3: So I was thinking, Okay, if that's the case for bacteria,

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Speaker 3: then what about viruses. What if it's the same for viruses.

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Speaker 3: What if the only viruses that we know about are

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Speaker 3: the ones that cause disease and there are loads of

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Speaker 3: other viruses that are actually good for us. That's what

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Speaker 3: I was thinking back then. But the funny thing is

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Speaker 3: that this other guy called Dennis Nielsen, who is a

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Speaker 3: professor at copenha University because he's an expert at figuring

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Speaker 3: out which viruses are in a sample, he basically said, Okay,

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Speaker 3: you guys found this thing with bacteria, why don't we

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Speaker 3: look at the viruses in the gut and maybe we

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Speaker 3: can find something similar or even cooler. And so when

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Speaker 3: I started copsack, this data set is already in the

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Speaker 3: pro being generated. Dennis has taken seven hundred fecal samples

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Speaker 3: extracted viral particles, and then he has basically put them

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Speaker 3: through a sequencer and we're getting in sequences from each.

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Speaker 1: Child's sequences, meaning genetic sequences that allows you to determine

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Speaker 1: what viruses. Yeah, exactly, So you get there in twenty seventeen,

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Speaker 1: and another researcher is already just starting to look for

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Speaker 1: what viruses are in the fecal samples of these kids

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Speaker 1: in the study. How do you get involved to what

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Speaker 1: do you do?

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Speaker 2: What happens back then?

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Speaker 3: What people used to do when they got gut VIRAM

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Speaker 3: data is that they would then take all the DNA

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Speaker 3: sequences that came out of that and they would then

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Speaker 3: blast it. Is what it is called against a public

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Speaker 3: database of viruses, viruses that scientists have already discovered and

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Speaker 3: know about, so that you can figure out which viruses

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Speaker 3: are in those samples. The problem is that most of

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Speaker 3: the viruses in the human gut at that time were

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Speaker 3: unknown to science by I love it. So by doing

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Speaker 3: that exercise, you're only going to get like a list

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Speaker 3: of contents of maybe ten virus, whereas the actual diversity

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Speaker 3: in each sample is going to be like maybe ten

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Speaker 3: thousand or maybe a thousand or something.

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Speaker 1: Right, But the problem is you don't know what you're

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Speaker 1: looking for, right, You just have this random strings of

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Speaker 1: genetic material, and if you're trying to find newly discovered viruses, well,

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Speaker 1: how do you even do that? In fact, how do

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Speaker 1: you do it?

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Speaker 3: So what we first do is we assemble all the

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Speaker 3: sequences like a piece of a puzzle and get extended

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Speaker 3: so that you get larger and larger fragments of DNA

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Speaker 3: that must have come from the same virus.

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Speaker 1: You have this weird set of little chains and you

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Speaker 1: need to put together like, ah, here is a virus

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Speaker 1: and here is a different virus.

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Speaker 3: Yeah, exactly, And so that's then what happens. Now we

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Speaker 3: got a bunch of DNA sequences from each child, so

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Speaker 3: that then what I do is I annotate all the

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Speaker 3: protein coding genes on these strands of DNA, so that

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Speaker 3: I know which proteins are encoded on each DNA fragment,

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Speaker 3: and by looking at those proteins, what they encode, what

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Speaker 3: kind of functions those protein code, I can start making

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Speaker 3: qualified guesses in terms of Okay, this one a virus

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Speaker 3: and this one must not.

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Speaker 1: Are you like actually looking at sequences and like look

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Speaker 1: at like at like one looks at jigsaw puzzle pieces

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Speaker 1: on a table.

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Speaker 3: Yeah, I guess you could say. I mean, I can

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Speaker 3: look at the protein coding genes that are encoded on

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Speaker 3: each cluster, and I manually look through ten thousand clusters

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Speaker 3: of sequences, and out of those ten thousand, around three

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Speaker 3: hundred of them were the ones that I could confidently

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Speaker 3: say were viruses and they correspond to viral families.

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Speaker 1: So when you're saying you're manually looking through ten thousand,

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Speaker 1: is that like years of work?

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Speaker 3: Yeah, it took five years, actually four years.

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Speaker 1: Yeah, And so you do this work, you spend four

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Speaker 1: or five years going through this data. How many viruses

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Speaker 1: do you find that live commonly in the human gut, in.

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Speaker 3: The children who we looked at? And that's all we

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Speaker 3: can really say anything about. There are ten thousand species

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Speaker 3: of viruses distributed in around two hundred and fifty viral families.

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Speaker 1: So so you discover all these new viruses, does that

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Speaker 1: mean you get to name them?

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Speaker 3: Super good question? So this is and this is this

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Speaker 3: was actually a huge issue for us. So now we're

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Speaker 3: finding two hundred and fifty new viral families. How are

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Speaker 3: we gonna present this in a paper?

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Speaker 1: Right? It can't just be like a b C. You're

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Speaker 1: gonna write out a letter Earth exactly.

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Speaker 3: And so a lot of different suggestions were on the table.

444
00:23:23,160 --> 00:23:24,400
Speaker 3: Pokemon was one of them.

445
00:23:24,440 --> 00:23:26,960
Speaker 1: Did you have a Pikachu in mind? That's the first question?

446
00:23:27,080 --> 00:23:29,480
Speaker 3: Who gets to me exactly like Pikachu veradee? You know,

447
00:23:30,000 --> 00:23:32,760
Speaker 3: Charmander Verde, et cetera, et cetera. And then a colleague

448
00:23:32,800 --> 00:23:34,879
Speaker 3: of mine, Jonathan, who's the third author of this paper,

449
00:23:34,880 --> 00:23:37,200
Speaker 3: he suggested, why not just name them after the kids?

450
00:23:37,680 --> 00:23:40,040
Speaker 1: Are the kids in the study? The kids? Who's who's

451
00:23:40,080 --> 00:23:41,679
Speaker 1: whose poop had the viruses in it?

452
00:23:42,000 --> 00:23:44,359
Speaker 3: Exactly? So we shuffled all the names and then we

453
00:23:44,440 --> 00:23:47,000
Speaker 3: just distributed them over the two undred and fifty viral families.

454
00:23:47,240 --> 00:23:51,159
Speaker 3: So what are some of the names Christian Verde, Ucas Verde,

455
00:23:51,520 --> 00:23:52,560
Speaker 3: Josephinea Verde.

456
00:23:52,880 --> 00:23:56,199
Speaker 1: Yeah, So you do this work, you identify all of

457
00:23:56,240 --> 00:23:59,320
Speaker 1: these previously undiscovered viruses that live in the guts of

458
00:23:59,359 --> 00:24:03,120
Speaker 1: these kids. Do you then start to try and understand

459
00:24:03,119 --> 00:24:07,720
Speaker 1: the health implications of different virmes et cetera.

460
00:24:08,280 --> 00:24:11,080
Speaker 3: That was the entire purpose of this exercise, right, So

461
00:24:11,240 --> 00:24:14,480
Speaker 3: those bacterial phages which were also by far most of

462
00:24:14,480 --> 00:24:15,640
Speaker 3: all the families.

463
00:24:15,240 --> 00:24:17,320
Speaker 1: The viruses that infect in bacteria.

464
00:24:17,480 --> 00:24:18,280
Speaker 2: Okay, exactly.

465
00:24:18,560 --> 00:24:21,280
Speaker 3: Those bacterial phage families can be divided into like two

466
00:24:21,440 --> 00:24:26,520
Speaker 3: broad categories. They are the virulent bacteriophages and the temperate bacteriophages. Right.

467
00:24:26,920 --> 00:24:30,480
Speaker 3: The virulent bacteriophages they just kill the bacteria, okay, whereas

468
00:24:30,480 --> 00:24:35,520
Speaker 3: the tempered bacteriophagies they integrate themselves as prophages on the

469
00:24:35,560 --> 00:24:37,000
Speaker 3: bacterial DNA.

470
00:24:37,640 --> 00:24:40,600
Speaker 1: So first you look at the viruses that infect bacteria,

471
00:24:40,960 --> 00:24:43,160
Speaker 1: and then you divide those into two categories, and you say,

472
00:24:43,160 --> 00:24:46,480
Speaker 1: there's the viruses that just destroy the bacteria, and there's

473
00:24:46,520 --> 00:24:49,199
Speaker 1: the viruses that infect the bacteria but don't destroy it.

474
00:24:49,520 --> 00:24:50,000
Speaker 3: Exactly.

475
00:24:50,080 --> 00:24:51,639
Speaker 1: Does that tell you anything clinically?

476
00:24:52,080 --> 00:24:52,320
Speaker 2: Yeah?

477
00:24:52,359 --> 00:24:55,159
Speaker 3: So Christina who was the first author of that paper

478
00:24:55,200 --> 00:24:57,480
Speaker 3: that came out in Nature Medicine earlier this year, she

479
00:24:57,520 --> 00:25:00,600
Speaker 3: found that it was the temperate bacterial phages that were

480
00:25:00,640 --> 00:25:03,080
Speaker 3: predictive of later asthma. For some reason, the children that

481
00:25:03,160 --> 00:25:05,360
Speaker 3: end up developing asthma by age five, they had way

482
00:25:05,400 --> 00:25:08,600
Speaker 3: more temperate phages by pacteriophages in their gut at age one.

483
00:25:08,960 --> 00:25:12,320
Speaker 1: Uh huh. And so the key data set is you're

484
00:25:12,359 --> 00:25:15,240
Speaker 1: looking at the virum of the kids at age one

485
00:25:15,840 --> 00:25:19,960
Speaker 1: and trying to understand is it predictive of asthma by

486
00:25:20,080 --> 00:25:24,080
Speaker 1: age five? And what answer do you and your colleagues

487
00:25:24,119 --> 00:25:24,960
Speaker 1: find to that question.

488
00:25:25,359 --> 00:25:27,800
Speaker 3: What we find is that there are more temperate phages

489
00:25:27,960 --> 00:25:30,399
Speaker 3: in the kids who end up developing asthma later. Then

490
00:25:30,440 --> 00:25:32,600
Speaker 3: we look at the temperate phages specifically, and look, we

491
00:25:32,640 --> 00:25:36,760
Speaker 3: look at which families of temperate phages are predictive of disease.

492
00:25:36,840 --> 00:25:39,000
Speaker 3: And then what we find, which is kind of surprising

493
00:25:39,040 --> 00:25:42,119
Speaker 3: and funny, is that nineteen of the two hundred and

494
00:25:42,160 --> 00:25:44,200
Speaker 3: fifty families we had in total two hundred and thirty

495
00:25:44,200 --> 00:25:46,400
Speaker 3: of the more tempered nineteen of them. If you look

496
00:25:46,440 --> 00:25:49,199
Speaker 3: at the amounts of those nineteen families in the children,

497
00:25:49,359 --> 00:25:52,000
Speaker 3: you can actually distinguish between kids that end up developing

498
00:25:52,040 --> 00:25:55,520
Speaker 3: asthma as five year olds or not. And what's interesting

499
00:25:55,680 --> 00:25:58,120
Speaker 3: is that the kids that develop asthma as five year

500
00:25:58,119 --> 00:26:01,240
Speaker 3: olds have less of these nineteen families than the healthy ones.

501
00:26:01,359 --> 00:26:01,639
Speaker 2: Aha.

502
00:26:01,800 --> 00:26:05,440
Speaker 1: So, so is it right that these nineteen families of

503
00:26:05,520 --> 00:26:09,840
Speaker 1: viruses seem to maybe be protective against asthma? Like having

504
00:26:10,000 --> 00:26:13,919
Speaker 1: more of these of these particular viruses is correlated with

505
00:26:14,000 --> 00:26:18,200
Speaker 1: a lower risk of asthma exactly. That's very interesting. Now

506
00:26:18,240 --> 00:26:20,880
Speaker 1: I get nervous that even though it passes some set

507
00:26:20,920 --> 00:26:24,040
Speaker 1: of statistical tests, this is going to be a fluke finding.

508
00:26:24,760 --> 00:26:26,880
Speaker 1: You know, It's going to be due to random chance.

509
00:26:26,920 --> 00:26:29,080
Speaker 1: And so what I really want you to do is

510
00:26:29,119 --> 00:26:31,480
Speaker 1: go run this test on some other kids at age one,

511
00:26:32,080 --> 00:26:34,480
Speaker 1: make your prediction, and have it come true by age five.

512
00:26:34,800 --> 00:26:37,320
Speaker 1: Is that a reasonable thought?

513
00:26:37,680 --> 00:26:40,359
Speaker 3: That is super reasonable, I have to say, Jacob. And

514
00:26:40,760 --> 00:26:42,879
Speaker 3: this is also something that Nature and Medicine asked us

515
00:26:42,880 --> 00:26:45,639
Speaker 3: to do, and we said, well, nobody else has virum

516
00:26:45,680 --> 00:26:48,280
Speaker 3: data for so many children. Unfortunately, such a cohord does

517
00:26:48,320 --> 00:26:51,359
Speaker 3: not exist. You know, COPSAC twenty ten is one of

518
00:26:51,359 --> 00:26:54,119
Speaker 3: the most deeply phenotype cohorts in the world, so we

519
00:26:54,119 --> 00:26:56,680
Speaker 3: were not able to replicate it in another cohort.

520
00:26:57,160 --> 00:27:00,000
Speaker 1: Yeah. Yeah, So you have this finding that a certain

521
00:27:00,200 --> 00:27:06,520
Speaker 1: family of virus seems to be protective against asthma. Are

522
00:27:06,520 --> 00:27:12,280
Speaker 1: you able to understand anything about what causes a kid

523
00:27:12,400 --> 00:27:16,680
Speaker 1: to have or not have this apparently protective family of

524
00:27:16,760 --> 00:27:18,760
Speaker 1: viruses in their gut?

525
00:27:19,400 --> 00:27:22,640
Speaker 3: Super good question. I don't know. I think it has

526
00:27:22,640 --> 00:27:25,320
Speaker 3: a lot to do with different environmental factors that end

527
00:27:25,400 --> 00:27:28,119
Speaker 3: up determining for random reasons, which viruses end up in

528
00:27:28,160 --> 00:27:29,159
Speaker 3: the guts of these children.

529
00:27:29,240 --> 00:27:30,840
Speaker 1: I mean, when you say you don't know, does that

530
00:27:30,880 --> 00:27:33,200
Speaker 1: mean there's no way in your data set to investigate

531
00:27:33,200 --> 00:27:33,639
Speaker 1: the question?

532
00:27:34,040 --> 00:27:35,920
Speaker 3: There definitely is, and this is what we're doing is

533
00:27:35,960 --> 00:27:39,080
Speaker 3: ongoing basically, right. So what we do see is that

534
00:27:39,119 --> 00:27:42,200
Speaker 3: there's a huge correlation in, for example, where the kids live,

535
00:27:42,200 --> 00:27:44,320
Speaker 3: whether they live in a rural environment or like a

536
00:27:44,359 --> 00:27:46,480
Speaker 3: city environment. Okay, the ones that really live in a

537
00:27:46,520 --> 00:27:49,400
Speaker 3: rural environment have a much more diverse, you know, ecosystem

538
00:27:49,400 --> 00:27:51,320
Speaker 3: in the gut. In terms of the bacteria. We haven't

539
00:27:51,320 --> 00:27:54,320
Speaker 3: looked at the viruses directly yet, but we have an

540
00:27:54,359 --> 00:27:57,639
Speaker 3: intuition that the same might apply for viruses as well. Also,

541
00:27:57,760 --> 00:27:59,920
Speaker 3: there's there are huge, you know, kind of links to

542
00:27:59,960 --> 00:28:01,880
Speaker 3: the diet, the kind of food that you eat, whether

543
00:28:01,920 --> 00:28:05,000
Speaker 3: it's very processed food or whether it's like whole foods.

544
00:28:05,160 --> 00:28:08,920
Speaker 3: Whole foods are generally associated with way way higher diversity.

545
00:28:09,080 --> 00:28:10,920
Speaker 3: So if you want to increase your chances of having

546
00:28:11,000 --> 00:28:13,160
Speaker 3: the good viruses in your gut, then it's a good

547
00:28:13,160 --> 00:28:15,440
Speaker 3: idea to live you know, rurally or at least spend

548
00:28:15,520 --> 00:28:17,200
Speaker 3: some time in nature. It's a good idea to eat

549
00:28:17,200 --> 00:28:18,960
Speaker 3: whole foods instead of process foods, et cetera.

550
00:28:19,680 --> 00:28:22,920
Speaker 1: Okay, so that's based on what we know about bacteria

551
00:28:23,040 --> 00:28:27,840
Speaker 1: and what you suspect is true also for viruses. Let

552
00:28:27,840 --> 00:28:32,080
Speaker 1: me ask you this, when you think about the future,

553
00:28:33,280 --> 00:28:38,600
Speaker 1: what do you hope we know about the virme in five, ten,

554
00:28:39,560 --> 00:28:41,760
Speaker 1: twenty years that we don't know now.

555
00:28:43,360 --> 00:28:46,720
Speaker 3: I'm hoping in the future that we have a much

556
00:28:46,760 --> 00:28:50,840
Speaker 3: better overview in terms of what kinds of chronic diseases

557
00:28:51,160 --> 00:28:55,640
Speaker 3: are caused by deficits in which viruses, but also in bacteria,

558
00:28:55,800 --> 00:28:59,080
Speaker 3: so that we can prevent maybe ten twenty thirty years

559
00:28:59,120 --> 00:29:00,800
Speaker 3: from now, we can prove event a lot of time

560
00:29:00,880 --> 00:29:03,640
Speaker 3: diseases that cause a lot of problems today that those

561
00:29:03,640 --> 00:29:07,360
Speaker 3: can just be prevented by giving babies viruses or bacteria

562
00:29:07,440 --> 00:29:08,200
Speaker 3: or even adults.

563
00:29:13,560 --> 00:29:15,240
Speaker 1: Thank you so much for your time. It was great

564
00:29:15,280 --> 00:29:15,800
Speaker 1: to talk with you.

565
00:29:16,040 --> 00:29:21,200
Speaker 3: Good to talk to you too.

566
00:29:21,720 --> 00:29:25,320
Speaker 1: Shiraz Shaw is a senior researcher at the Copenhagen University

567
00:29:25,320 --> 00:29:28,800
Speaker 1: Hospital ghenth HOFTA. Thanks to both of my guests today,

568
00:29:28,920 --> 00:29:44,040
Speaker 1: Shiraz Shah and Ken Steadman. Incubation is a co production

569
00:29:44,120 --> 00:29:48,280
Speaker 1: of Pushkin Industries and Ruby Studio at iHeartMedia. It's produced

570
00:29:48,280 --> 00:29:51,440
Speaker 1: by Kate Furby and Brittany Cronin. The show is edited

571
00:29:51,440 --> 00:29:55,320
Speaker 1: by Lacey Roberts. It's mastered by Sarah Buguer, fact checking

572
00:29:55,400 --> 00:29:59,040
Speaker 1: by Joseph friedman Or. Executive producers are Lacey Roberts and

573
00:29:59,080 --> 00:30:02,640
Speaker 1: Matt Romano. I'm Jacob Goldstein. Thanks very much for listening

574
00:30:02,640 --> 00:30:05,120
Speaker 1: to this season of Incubation. I hope we'll be back

575
00:30:05,160 --> 00:30:28,800
Speaker 1: next year with Season three.