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Speaker 1: According to some scientists, we are in the middle of

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Speaker 1: the sixth mass extinction, well past extinctions with the result

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Speaker 1: of things like giant asteroids. This one's probably on us.

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Speaker 1: Species go extinct on their own in the wild, but

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Speaker 1: scientists estimate the extinction rates are about one hundred times

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Speaker 1: greater than baseline extinction rates due to human impacts, and

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Speaker 1: this rate is increasing over time. When I was a kid,

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Speaker 1: I remember hearing the phrase extinction is forever? But is it?

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Speaker 1: With current and future technologies, can we undo the damage

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Speaker 1: we've done and bring back the species whose demise is

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Speaker 1: our causing. Today we're going to talk about the science

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Speaker 1: of d extinction. Welcome to Daniel and Kelly's Extraordinary Universe.

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Speaker 2: I'm Daniel. I'm a particle physicist, and I think I've

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Speaker 2: tasted eight different kinds of animals.

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Speaker 1: Hello. I'm Kelly Wiener Smith. I study space and parasites,

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Speaker 1: and I didn't expect you to start with that, so

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Speaker 1: I don't know that I have a good count. Give

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Speaker 1: me your list. What are the eight kinds of animals

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Speaker 1: you've eaten?

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Speaker 2: Let's see, of course, pork, I've eaten cows, I've eaten deer,

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Speaker 2: I've eaten snake, I've eaten alligator, chicken, turkey, duck, goose.

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Speaker 1: All right, that's nine?

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Speaker 2: Oh is that nine? Oh my gosh, I already beat

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Speaker 2: my record.

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Speaker 1: Yeah, it's a good job, Daniel, You're a winner. Let's

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Speaker 1: say I've done chickens and ducks and turkey and.

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Speaker 2: Moose, deer, pigs and cows.

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Speaker 1: Alligator, pigs and cows. We currently have deer in our

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Speaker 1: freezer from our property.

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Speaker 2: Really sheep?

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Speaker 1: Right, Yeah, that's right. And you've had sheep too, right, Yeah, so.

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Speaker 2: That's ten for me, and I've had goats. What's the

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Speaker 2: weirdest thing you've eaten?

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Speaker 3: Then?

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Speaker 1: Moose hearts?

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Speaker 2: Ooh yeah, it was dried oh, moose heart jerky.

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Speaker 1: Yeah, it was like moose heart jerky. And it was

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Speaker 1: in a paper bag and the host that I was

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Speaker 1: visiting pulled it out of the paper bag and there

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Speaker 1: was still fat on top of it and it looked,

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Speaker 1: you know, like a heart, and it got sliced and

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Speaker 1: then put on a cracker with some butter and if

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Speaker 1: I shut my eyes, it was delicious, but I kind

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Speaker 1: of had to like not make eye contact with the food.

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Speaker 2: Well that's my question for you today, is which extinct

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Speaker 2: animal do you think is the tastiest? Oh, what in

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Speaker 2: the past did humans really savor that we will never experience. Gosh,

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Speaker 2: I wonder how wooly mammoth tasted.

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Speaker 1: Yeah, well we might know soon, according to Colossal, in

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Speaker 1: five years we might be able to find out.

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Speaker 2: Do you think this is the real motivation for bringing

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Speaker 2: back species?

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Speaker 1: I don't know. But there's an interesting movement called invasive war.

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Speaker 1: I think it's what it's called. And the idea is

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Speaker 1: that if you have an invasive species, you try to

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Speaker 1: kick up a market around eating it. Some people will

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Speaker 1: help you bring those numbers down. I can't think of

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Speaker 1: any particularly delicious animal we drove to extinction.

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Speaker 2: I always wondered about that with Australia, because don't they

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Speaker 2: have a bunny infestation? And I thought a lot of

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Speaker 2: people eat rabbits. Yeah, don't they just eat the rabbits.

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Speaker 1: I mean, at some point there's a lot more rabbits

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Speaker 1: than people. I know some people who can't eat bunnies

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Speaker 1: because they're cute and they have like a cute filter

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Speaker 1: for what they'll eat, and so I think there are

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Speaker 1: some people who just can't have bunnies for that reason.

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Speaker 1: And maybe there's just not enough people. I don't know

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Speaker 1: I've eaten rabbit. There's another one, Have you eaten rabbit?

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Speaker 2: I don't think I've knowingly eaten rabbit, but I've eaten

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Speaker 2: at some French restaurants where I didn't understand the menu,

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Speaker 2: and so there's always a question there. Oh wait, snails,

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Speaker 2: I've had snails. Oh so boo, I'm up to eleven.

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Speaker 1: Yeah, snails get infected by lots of trema toad species,

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Speaker 1: and you can't get sick by eating the snails. But

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Speaker 1: that knowledge, I won't be able to ever eat a snail.

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Speaker 1: I don't think I also have a texture thing. I

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Speaker 1: don't think snails are for me.

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Speaker 2: Yeah, it's not sort of second serving kind of a

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Speaker 2: thing either.

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Speaker 1: I'm also not an oyster person, and I know loads

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Speaker 1: of people love oysters.

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Speaker 2: Yeah yeah, oh wait, we didn't even count the kinds

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Speaker 2: of fish. Oh, the whole other category of animals. Wow,

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Speaker 2: we've eaten a lot more than we imagine. Yeah, we

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Speaker 2: should do a thorough accounting.

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Speaker 1: We should. We should. I guess if you include plants

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Speaker 1: and herbs and stuff, I'm sure we've conde many many

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Speaker 1: species in our lives.

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Speaker 2: Katrina tries to eat thirty different kinds of plants every day.

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Speaker 1: Wow? Why why not? Okay, yeah, sure, sure.

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Speaker 2: I think the diversity is good for your gut, you know,

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Speaker 2: keep all those little microbes.

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Speaker 1: Yeah yeah, Oh wow. I would get on a Katrina

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Speaker 1: diet if she were like a fitness instructor, you know,

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Speaker 1: I think it would be science informed.

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Speaker 2: You know, she's working on a recipe book, Science Informed

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Speaker 2: Recipes for your Health.

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Speaker 1: Sign me up. I want that book.

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Speaker 3: You know.

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Speaker 1: Ever since we had her on the show, I do

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Speaker 1: make sure that I have a cup of beans every day.

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Speaker 2: There you go, all right to your health.

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Speaker 1: Zach does not say thank you, but I feel better.

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Speaker 2: All right. Well, we're not here to talk about what's

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Speaker 2: coming out of Kelly. We're here to talk about what's

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Speaker 2: coming out of a really interesting research project that's made

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Speaker 2: the news recently.

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Speaker 1: I love your transitions.

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Speaker 2: Sometimes it's a big step to get us back on track.

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Speaker 1: But do you always find the cleverest path between them.

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Speaker 1: So today we're talking about a company called Colossal, and

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Speaker 1: Colossal is all about de extinction. So they're trying to

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Speaker 1: bring back animals that have been driven to extinction in

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Speaker 1: every case by humans, and they made the news recently

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Speaker 1: because they are claiming to have brought back the dire wolf,

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Speaker 1: And so we asked our listeners did Colossal bring back

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Speaker 1: the dire wolf? And here's what they had to say.

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Speaker 2: I have no idea that you got me on that one.

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Speaker 4: No, they created something that will resemble the dire wolf

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Speaker 4: but is not actually a dire wolf.

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Speaker 5: Did Colossal bring back the dire wolf in the sense

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Speaker 5: of that a being is the product of using a

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Speaker 5: specific DNA recipe in an Earth environment to recreate a

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Speaker 5: member of the species.

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Speaker 2: Yes.

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Speaker 5: On the other hand, did they bring back the dire

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Speaker 5: wolf to be a staple resident of this planet? We're

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Speaker 5: far a cry from that.

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Speaker 2: Did what bring back?

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Speaker 3: The what philosof falling into a parallel universe is that

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Speaker 3: the gene.

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Speaker 2: Editing thing probably not clickbait. I'm not buying it.

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Speaker 4: It's a genetically modified gray wolf that happens to have

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Speaker 4: some traits of a dire wolf. So I did see

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Speaker 4: the headlines on this, and I guess it depends on

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Speaker 4: the quality of the sequence. If they didn't have a

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Speaker 4: complete sequence and had to splice in like regular wolf genes,

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Speaker 4: then maybe not. I saw a direwolf skeleton at the

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Speaker 4: Libret Tarpitz and on Game of Thrones, but I don't

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Speaker 4: know anything about Colossal. Seems to be like a rock

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Speaker 4: band touring, but with only one of the original band members.

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Speaker 6: They really only brought back certain traits of a dire wolf,

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Speaker 6: but not necessarily every single trait.

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Speaker 2: So it looks like a dire wolf, but we don't

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Speaker 2: really know if it has all the other traits of

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Speaker 2: a dire wolf.

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Speaker 6: Colossal brought back the dire wolf like Jurassic Hark brought

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Speaker 6: back to velociraptor.

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Speaker 2: I always thought dire wolves were fictions, so I didn't

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Speaker 2: know they could come back. I thought they were just

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Speaker 2: from like Game of Thrones and things. I'm going to say,

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Speaker 2: I don't know.

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Speaker 3: No, I didn't think so three individuals are not a population,

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Speaker 3: let alone any species. That doesn't mean that it's not interesting.

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Speaker 3: I'm sure they learn a lot about the phenotypical features

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Speaker 3: that make wolf differentiate extinct wolves from current wolves, so

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Speaker 3: I'm sure it's a very interesting work.

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Speaker 6: I think that they brought it mostly back, but I

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Speaker 6: think that because it had to be an animal from

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Speaker 6: today and DNA from a dire wolf, then technically it's

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Speaker 6: not actually the one hundred percent complete dire Wolf.

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Speaker 1: A lot of skepticism here, a lot of skepticism. The

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Speaker 1: answers either fell into I have no idea what you're

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Speaker 1: talking about mmmm, or no they did not. I don't

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Speaker 1: think anybody was like, yes they did. One person said

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Speaker 1: it was interesting, nonetheless, but they didn't completely bring back

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Speaker 1: the dire wolf.

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Speaker 2: So give us some background. Tell us about this project.

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Speaker 2: What is de extinctification and why would somebody want to

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Speaker 2: do it?

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Speaker 1: Okay, so you've added a lot of unnecessary syllables.

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Speaker 2: What do you mean de extinctification?

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Speaker 5: Is this?

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Speaker 1: Let's see a lot. We can get it by the

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Speaker 1: end of the show. I'm digging it. I think the

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Speaker 1: way that most people imagine the extinction is that you

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Speaker 1: are bringing back exactly the organism that we drove to

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Speaker 1: extinction at some point in the past, and so it

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Speaker 1: has the exact same genotype. You could PLoP it back

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Speaker 1: in the environment and it would be exactly the same.

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Speaker 1: Behave the same have the same genome, all the same.

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Speaker 2: All right, But if we're going to be really technical

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Speaker 2: and nerdy about what is and isn't de extinctificationism, then

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Speaker 2: you know, what does that even mean? Because when you

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Speaker 2: had an extent population. It's not like you had a

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Speaker 2: single genome that define the species, right, You had a variation,

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Speaker 2: you had diversity, and so what does it mean to

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Speaker 2: say I'm going to bring back the exact species in

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Speaker 2: that context anyway?

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Speaker 1: Yeah, so you're already starting to hone in on some

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Speaker 1: of the problems here. So, especially for long dead organisms,

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Speaker 1: you probably don't even have one complete genome from that organism,

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Speaker 1: let alone genomes from I don't know the one thousand

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Speaker 1: organisms that you would need to have a functioning population.

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Speaker 1: In the more near term, we are sort of raising

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Speaker 1: from the dead genotypes for for example, black ferret. So

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Speaker 1: the black ferret population is in decline. This is happening

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Speaker 1: right now. But every once in a while, some lab

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Speaker 1: or zoo will find a black ferret frozen in their

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Speaker 1: freezer and they'll extract genetic material from that black ferret

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Speaker 1: and bring to life of black ferret with that genome.

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Speaker 2: Is this something that happens to biologists? They just like

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Speaker 2: find black ferrets in their freezer, like, oh, what's this,

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Speaker 2: there's a chocolate pie from last week. Oh, here's a

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Speaker 2: black ferret.

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Speaker 1: I mean, Katrina has never found bags fecis in your

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Speaker 1: freezer that.

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Speaker 2: Got lost, yes, but never a ferris.

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Speaker 1: Oh okay, all right, Well she's not the right kind

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Speaker 1: of biologist. If you were dating the right kind of biologists,

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Speaker 1: there'd be ferrets in there.

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Speaker 2: Okay, So this is something you put in your freezer.

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Speaker 2: It's not just something you discover. Oh my gosh, look

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Speaker 2: there's a ferret in my freezer.

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Speaker 1: Yeah, that's right, Like, you know, maybe it was part

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Speaker 1: of your zoo population. You thought maybe I could use

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Speaker 1: this for later, because that's something biologists think, and so

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Speaker 1: I ended up in a freezer and then it got

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Speaker 1: found and they're like, oh, that could help. So one

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Speaker 1: problem is that it's very hard to get the genetic

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Speaker 1: diversity that you need, especially when you're working with very

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Speaker 1: long dead organisms.

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Speaker 2: So I think you're saying that the population had diversity

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Speaker 2: and it's not easy to pull back the whole population. Yeah,

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Speaker 2: But I'm wondering, even on a more technical level, like

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Speaker 2: which individual would you pull back, and would any of

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Speaker 2: them qualify or would some sort of mixture of them qualify.

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Speaker 2: Like when you say de extinctification, you mean you've resurrected

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Speaker 2: an individual that previously existed or a representative individual from

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Speaker 2: that species. Like I want to know exactly what it

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Speaker 2: means and what qualifies.

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Speaker 1: Yeah, all right, so let's get to that. So let's

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Speaker 1: start with Colossal's definition of de extinctificationization and they are

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Speaker 1: calling it functional de extinction, and they say it's the

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Speaker 1: process of generating an organism that both resembles and is

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Speaker 1: genetically similar to an extinct species by resurrecting its lost

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Speaker 1: lineage of core genes, engineering natural resistances, and enhancing adaptability

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Speaker 1: that will allow it to thrive into day's environment of

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Speaker 1: climate change, dwindling resources, disease, and human interference. Wow, I

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Speaker 1: know it's low.

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Speaker 2: That's not a definition, it's an essay.

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Speaker 1: They've got a lot of words on their website, but

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Speaker 1: you can see already a couple things popping up. They're

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Speaker 1: not saying that they are bringing back the entire genome

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Speaker 1: or a diversity of different types of genomes. They are

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Speaker 1: bringing back core genes. So they are picking which genes

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Speaker 1: they think are critical to making a particular extinct species

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Speaker 1: and comparing that to the nearest living relative, and they're

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Speaker 1: bringing those genes back.

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Speaker 2: Do you think that they're doing this way because this

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Speaker 2: is all that's possible, or do you think, as maybe

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Speaker 2: implied by their little essay, they're doing it this way

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Speaker 2: because they want to create a version which could actually

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Speaker 2: survive in today's environment rather than something which died out

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Speaker 2: and lived in a previous environment.

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Speaker 1: It's probably both, I see, But that limitation in what's

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Speaker 1: possible is really important. So DNA degrades pretty quickly after

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Speaker 1: an animal dies, so by the time you're looking at

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Speaker 1: something like the dire wolf or mammoths, if you find

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Speaker 1: a specimen maybe that was frozen very soon after death,

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Speaker 1: there's going to be a lot of the genetic sequence

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Speaker 1: that you can still read if you're lucky, but you're

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Speaker 1: not going to have the entire genetic sequence. And with

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Speaker 1: mammoths in particular, we're lucky because there have been more

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Speaker 1: than one specimen where we can get some genetic material.

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Speaker 1: But you can't put together an entire exact genome for

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Speaker 1: the wooly mammoth. There's not enough intact genomes for organisms

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Speaker 1: that are long dead.

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Speaker 2: All right. So then before we dig into the dire

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Speaker 2: wolf real project, I just want to know from a

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Speaker 2: philosophical perspective, Kelly, say, if I gave you infinite resources,

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Speaker 2: there are no technical limitations. You could create any organism

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Speaker 2: you wanted, what would you consider de extinctification OFSM It

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Speaker 2: would be like you create a whole population. You pull back,

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Speaker 2: look the last time there was a thousand living entities

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Speaker 2: and you created all of them, or you just picked one,

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Speaker 2: or you like average them. Like, if you could do anything,

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Speaker 2: what would be the most pristine version of de extinctification.

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Speaker 1: My answer is also going to include my thoughts on

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Speaker 1: motivations for de extinction. I think that if you are

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Speaker 1: bringing an animal back into a world that it never

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Speaker 1: existed in and it can't fill its prior ecological role,

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Speaker 1: I think from a conservation standpoint, I'm not super interested

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Speaker 1: in that. And so if the blackfooted ferrets were to

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Speaker 1: go extinct tomorrow and you were able to bring back

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Speaker 1: enough individuals so that there wouldn't be in breeding problems,

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Speaker 1: and that would depend on how many and what kinds

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Speaker 1: of genomes you could get, I don't know, say it's

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Speaker 1: five hundred individuals, and then you could put them back

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Speaker 1: in their natural environment and somehow they'd be able to

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Speaker 1: still have their wild behaviors, which sometimes is you know,

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Speaker 1: through learning from other individuals, So that could be to

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Speaker 1: get back. But if you're able to get enough genetic

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Speaker 1: diversity where they won't decline because of inbreeding, and then

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Speaker 1: they can go back into their wild habitat and survive.

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Speaker 1: That to me would be successful de extinction. What do

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Speaker 1: you think?

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Speaker 2: Yeah, well, I think that's fascinating because it says something

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Speaker 2: about what a species really is. It's more than one individual,

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Speaker 2: it's a community, and it's also their environment and how

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Speaker 2: they interact and as you say, like learned behaviors that

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Speaker 2: are passed down. So it takes a lot to really

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Speaker 2: recreate a lineage. I guess my motivation would be different.

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Speaker 2: I'm not an ecologist. I would just be wondering how

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Speaker 2: many do you have to bring back so that I

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Speaker 2: could have a tasty burger of each kind, you know,

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Speaker 2: in a sustainable way. Of course.

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Speaker 1: Yeah. Absolutely, Let's jump a little bit more than into

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Speaker 1: motivation for de extinction before we get into the method.

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Speaker 1: So Colossal is pushing for de extinction as a method

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Speaker 1: to protect ecosystems that are in some form of decline.

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Speaker 2: For example, like bees are going extinct and we need

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Speaker 2: them as pollinators, so let's make sure we can bring

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Speaker 2: them back.

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Speaker 1: That kind of thing kind of although I can hear

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Speaker 1: a bunch of people saying, the honeybees that we use

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Speaker 1: are not native, and so you've already created something artificial.

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Speaker 1: But the big example that they use are mammoths. Mammoths

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Speaker 1: used to live in like tundras in Siberia, for example,

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Speaker 1: and as they walked across the landscape, they would crush

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Speaker 1: or knock over trees and their impact on the environment

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Speaker 1: resulted in a sustainable grassland. Oh interesting, Yeah, and that

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Speaker 1: grassland absorbed a lot of carbon dioxide. And I should

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Speaker 1: say I'm parroting exactly what I saw on their website.

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Speaker 1: So this is all assuming that they are correct on

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Speaker 1: their website, because this is out of my area of knowledge.

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Speaker 1: But these grasslands absorb a lot of carbon, which could

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Speaker 1: help us in this period of global climate change. And

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Speaker 1: having that grass there helps the permafrost not melt, and

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Speaker 1: as the permafrost melts, that releases more greenhouse gases and

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Speaker 1: is bad for a variety of other reasons. So they're

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Speaker 1: arguing that if you de extinct the wooly mammoth, who

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Speaker 1: can put it back into this environment which is maybe

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Speaker 1: still in the process of changing, and it can push

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Speaker 1: the environment back to a more ancestral state, and actually

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Speaker 1: that more ancestral state is better for the ecosystems and

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Speaker 1: the globe.

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Speaker 2: Wow, I'm even more skeptical after hearing that, because this

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Speaker 2: sounds to me not like we're going to resiss the

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Speaker 2: data species because we think it's cool or it's a tragedy,

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Speaker 2: but instead as an element of ecological planetary geoengineering, like

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Speaker 2: we think we bring this back, it can change the climate. Like, wow,

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Speaker 2: is that a huge Rube Goldberg machine that we do

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Speaker 2: not understand? And you start banging on those levers like

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Speaker 2: who knows what's going to happen? That seems very dangerous

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Speaker 2: to me. To me, that's as bonkers as like the

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Speaker 2: folks who want to put sulfur in the atmosphere to

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Speaker 2: make it more reflective and see what happens.

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Speaker 1: And I think they would argue that putting sulfur in

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Speaker 1: the atmosphere to see what happens is different than trying

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Speaker 1: to revert back to a state that once did exist.

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Speaker 1: I totally see your point. And I'm also skeptical that

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Speaker 1: you're going to be able to release wooly mammoths. I mean,

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Speaker 1: there's some parts of the world where they'll survive, but

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Speaker 1: there won't be a lot of people, and somebody in

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Speaker 1: Russia has put a side land that they've called Plistocene

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Speaker 1: Park for these mammoths. But you know, like in the US,

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Speaker 1: farmers were not happy when wolves were reintroduced. Can you

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Speaker 1: imagine suddenly needing to deal with wooly mammoths. I see

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Speaker 1: a lot of human animal problems if you actually try

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Speaker 1: to work this out.

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Speaker 2: I can imagine all sorts of videos on Twitter and

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Speaker 2: TikTok of a mammoth like crushing a playground, like walking

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Speaker 2: through a soccer game, or you.

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Speaker 1: Know, they kill people accidentally. Elephants do accidentally just because

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Speaker 1: they're big, lumbering giants. You know, people die to try to,

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Speaker 1: you know, give the colossal argument here. The other reasons

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Speaker 1: for why they do it are one along the way,

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Speaker 1: you learn things you didn't expect. And so I watched

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Speaker 1: a video from the chief science officer, her name is

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Speaker 1: Best Sapiro, arguing that along the way to studying elephants,

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Speaker 1: they came up with a vaccine for this virus that's

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Speaker 1: really bad for elephants today. So you have to understand

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Speaker 1: elephants today in order to edit them into being something

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Speaker 1: mammoth like. And then they explicitly make this space argument

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Speaker 1: that when we went to the moon there were all

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Speaker 1: of these side benefits along the way, and as we

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Speaker 1: shoot for this you know crazy dream of ours, there's

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Speaker 1: probably all sorts of cool stuff we're going to come

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Speaker 1: up with along the way. I feel like you could

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Speaker 1: also argue that if you really wanted to solve this

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Speaker 1: virus problem for the elephants, you should have just invested

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Speaker 1: in solving the virus problem for the elephants. But anyway,

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Speaker 1: so these are the current arguments for de extinction. You

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Speaker 1: and I discussed a book called Venomous Lumpsucker. It's a

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Speaker 1: fictional book, but it deals with some of the ethical

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Speaker 1: problems that might arise if people are like, oh, we

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Speaker 1: don't have to worry about driving that animal into extinction

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Speaker 1: because we can just bring it back. But you're not

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Speaker 1: bringing back the exact same thing. Any of the like

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Speaker 1: learned behaviors get lost when that last individual dies, and

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Speaker 1: they don't come back when you bring the last one back.

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Speaker 2: Yeah. I really did enjoy that book, Venomous Lumpsucker. It

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Speaker 2: talks about like the corporatization of it and how it

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Speaker 2: just gets folded into economic formulas. But it's fascinating to

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Speaker 2: me that none of the arguments you've made so far

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Speaker 2: about de extinctification and the motivations of it touch the

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Speaker 2: reason I think it's exciting, or the reason I would

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Speaker 2: be enthusiastic about it, which is this that every lost

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Speaker 2: species is like a lost bit of treasure. You know,

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Speaker 2: each one is evolved over millions or billions of years.

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Speaker 2: It's a solution to a really complex optimization problem. It's fascinating,

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Speaker 2: it's inherently valuable. It may be potentially that creates some medicines,

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Speaker 2: you know, like aspirin from the bark of a tree.

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Speaker 2: Who knows what solutions evolution has come up with that

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Speaker 2: might be useful. You know, we're just like the value

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Speaker 2: of a species to exist, and it's so tragic that

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Speaker 2: it seems so one directional. You know, once a species

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Speaker 2: is extinct, it's gone, maybe gone. I remember having that

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Speaker 2: drilled into my head as a kid. It just feels

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Speaker 2: so tragic. It's like a black hole almost right. Things

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Speaker 2: fall in and they never come out. So the idea

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Speaker 2: of being able to pull these things from beyond the

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Speaker 2: biological event horizon, to me, that's exciting because it opens

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Speaker 2: up a whole world of species that we could maybe

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Speaker 2: bring back I don't know if that's a terrible idea,

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Speaker 2: and I don't actually really want to eat burgers made

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Speaker 2: of these animals, But to me, there's an appeal to

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Speaker 2: just bringing things back from beyond the event horizon.

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Speaker 1: I think we should revisit this question at the very

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Speaker 1: end of the episode. You should decide if what it

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Speaker 1: is that is being brought back actually checks that box

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Speaker 1: that you're talking about, like this thing that's been lost

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Speaker 1: is back. So let's take a break and when we

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Speaker 1: get back, we'll talk about what exactly was done to

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Speaker 1: bring back the dire wolf, and we'll revisit your question.

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Speaker 1: All right, we're back, and we were just talking about

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Speaker 1: why you would bring an animal back from extinction. So

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Speaker 1: now let's go into a little bit of detail about

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Speaker 1: what Colossal did with the dire wolf. So what exactly

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Speaker 1: did they bring back. They had two dire wolves that

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Speaker 1: had died in a way that preserved some of their

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Speaker 1: genetic material.

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Speaker 2: And when did dire wolves go extinct?

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Speaker 1: Then went extinct about thirteen thousand years ago, which is

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Speaker 1: a lot of time for DNA to degrade.

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Speaker 2: Even when it's frozen, it still degrades.

438
00:20:56,200 --> 00:20:58,119
Speaker 1: Even when it's frozen, it can still degrade. Yeah, And

439
00:20:58,160 --> 00:21:00,000
Speaker 1: you know often if you're in an area that's frozen,

440
00:21:00,000 --> 00:21:01,600
Speaker 1: and every once in a while it will thaw out

441
00:21:01,640 --> 00:21:04,239
Speaker 1: a little bit and then it will freeze again, and

442
00:21:04,359 --> 00:21:06,040
Speaker 1: so you know, over time you get these sort of

443
00:21:06,080 --> 00:21:09,600
Speaker 1: fluctuations that break down the DNA. And so what they

444
00:21:09,600 --> 00:21:12,600
Speaker 1: did was, first they figured out what the most closely

445
00:21:12,640 --> 00:21:16,080
Speaker 1: related species alive today is and they determined that that's

446
00:21:16,119 --> 00:21:18,960
Speaker 1: the gray wolf. So they got the genome from the

447
00:21:18,960 --> 00:21:22,240
Speaker 1: gray wolf and they use that as a reference. And

448
00:21:22,280 --> 00:21:24,840
Speaker 1: so they put together the genome of the dire wolf

449
00:21:24,960 --> 00:21:28,040
Speaker 1: as best they could from the sequences that they had,

450
00:21:28,480 --> 00:21:30,960
Speaker 1: and they matched that up to the gray wolf so

451
00:21:30,960 --> 00:21:32,800
Speaker 1: that they could try to figure out where the like

452
00:21:32,920 --> 00:21:35,359
Speaker 1: chunks of DNA that they had collected, because a lot

453
00:21:35,359 --> 00:21:37,600
Speaker 1: of time the DNA gets like broken into pieces and

454
00:21:37,600 --> 00:21:39,119
Speaker 1: then it's like a puzzle. You need to figure out

455
00:21:39,119 --> 00:21:40,960
Speaker 1: where the pieces are supposed to go, and if you

456
00:21:41,160 --> 00:21:43,240
Speaker 1: match it up with the gray wolf, that kind of helps.

457
00:21:43,080 --> 00:21:45,159
Speaker 2: You, all right. So we don't have a complete genome

458
00:21:45,200 --> 00:21:48,000
Speaker 2: of the dire wolf. We have some snapshots and bits,

459
00:21:48,080 --> 00:21:51,160
Speaker 2: some snippets here and there from a couple of dire

460
00:21:51,160 --> 00:21:53,760
Speaker 2: wolves that were frozen thirteen thousand years ago, just from

461
00:21:53,800 --> 00:21:56,880
Speaker 2: two individuals. Yep, Wow, that's amazing. And so to fill

462
00:21:56,920 --> 00:21:58,879
Speaker 2: it out, they compare with the gray wolf, which they

463
00:21:58,880 --> 00:22:01,040
Speaker 2: think is similar, and it's sort of like sketching out

464
00:22:01,080 --> 00:22:03,640
Speaker 2: the bits that were missing and then also understanding the differences.

465
00:22:03,720 --> 00:22:04,439
Speaker 2: Is that what's going on?

466
00:22:04,720 --> 00:22:07,040
Speaker 1: Yes, And so to try to understand the differences, what

467
00:22:07,080 --> 00:22:09,639
Speaker 1: they did is they'd look at areas where the genomes

468
00:22:09,720 --> 00:22:13,400
Speaker 1: seemed to differ, and they would say, Okay, this genetic

469
00:22:13,520 --> 00:22:17,640
Speaker 1: code in other species has been associated with, for example,

470
00:22:18,200 --> 00:22:21,919
Speaker 1: white fur coats or with more muscular thighs, and so

471
00:22:21,960 --> 00:22:24,960
Speaker 1: they'd look for areas where the genomes differed and they

472
00:22:25,040 --> 00:22:27,000
Speaker 1: found Why does that make you laugh?

473
00:22:28,040 --> 00:22:31,040
Speaker 2: Because I'm imagining dire wolves with the like really chunky thighs,

474
00:22:31,080 --> 00:22:33,560
Speaker 2: like looking out the gym like direwolf says, don't skip

475
00:22:33,640 --> 00:22:34,480
Speaker 2: leg dais.

476
00:22:36,800 --> 00:22:39,040
Speaker 1: That is a trait that they honed in on.

477
00:22:39,160 --> 00:22:40,920
Speaker 2: How do we know that just from the frozen diar

478
00:22:40,960 --> 00:22:42,280
Speaker 2: Roves were like, wow, look at those.

479
00:22:42,840 --> 00:22:44,480
Speaker 1: I don't actually know if they were able to tell

480
00:22:44,520 --> 00:22:47,400
Speaker 1: from the frozen dire wolves, but they looked at the

481
00:22:47,520 --> 00:22:50,080
Speaker 1: genotypic sequences and they were like, Okay, this looks a

482
00:22:50,119 --> 00:22:52,240
Speaker 1: little different, and I think often they'd say this looks

483
00:22:52,240 --> 00:22:54,239
Speaker 1: a little different in ways that are consistent with more

484
00:22:54,320 --> 00:22:57,879
Speaker 1: muscular legs, So that's probably what they had. So they

485
00:22:57,960 --> 00:23:02,960
Speaker 1: ended up deciding that probably dire wolves differed from gray

486
00:23:03,000 --> 00:23:09,159
Speaker 1: wolves by having increased size, broader skulls, a white coat,

487
00:23:09,600 --> 00:23:13,520
Speaker 1: stronger shoulders and legs, and a thick and sort of

488
00:23:13,560 --> 00:23:14,359
Speaker 1: condensed coat.

489
00:23:14,720 --> 00:23:16,960
Speaker 2: They sound kind of awesome. Why did they go extinct?

490
00:23:17,040 --> 00:23:19,399
Speaker 1: They do sound awesome. I don't know why they went extinct.

491
00:23:19,520 --> 00:23:21,480
Speaker 1: Probably humans, that's my guest.

492
00:23:23,119 --> 00:23:24,640
Speaker 2: Too many dire wolf burgers.

493
00:23:24,640 --> 00:23:28,200
Speaker 1: It sounds like, yeah, well, animals can be delicious. It's

494
00:23:28,240 --> 00:23:31,520
Speaker 1: not their fault. And so they found twenty genes that

495
00:23:31,560 --> 00:23:34,480
Speaker 1: they thought, you know, it looks like these are important differences.

496
00:23:34,520 --> 00:23:37,560
Speaker 1: So we're going to take the gray wolf genome and

497
00:23:37,640 --> 00:23:40,679
Speaker 1: we're going to edit it in those twenty locations so

498
00:23:40,720 --> 00:23:44,120
Speaker 1: that it looks like the dire wolf genome. But it's

499
00:23:44,119 --> 00:23:47,320
Speaker 1: important to keep in mind that when an organism is

500
00:23:47,920 --> 00:23:52,359
Speaker 1: expressing a trait, it's not just about the genes that

501
00:23:52,440 --> 00:23:55,600
Speaker 1: it has. It's also about when those genes are turned

502
00:23:55,640 --> 00:23:57,840
Speaker 1: on and how long they're turned on. So you might

503
00:23:57,880 --> 00:24:00,719
Speaker 1: remember when we were talking about coat color when we

504
00:24:00,720 --> 00:24:04,280
Speaker 1: were answering our listener questions episode, Whether or not a

505
00:24:04,320 --> 00:24:08,040
Speaker 1: particular hair cell makes black or white is all about

506
00:24:08,040 --> 00:24:10,280
Speaker 1: whether or not this promoter for a gene is turned

507
00:24:10,280 --> 00:24:12,080
Speaker 1: on or off, whether or not a gene is getting

508
00:24:12,080 --> 00:24:15,119
Speaker 1: the message to make black or not. But none of

509
00:24:15,160 --> 00:24:20,600
Speaker 1: that timing information is probably incorporated in this technique. But

510
00:24:21,520 --> 00:24:25,120
Speaker 1: they did end up getting organisms that look like what

511
00:24:25,160 --> 00:24:27,960
Speaker 1: we imagine dire wolves look like. They sort of look

512
00:24:28,040 --> 00:24:30,000
Speaker 1: like the specimens we've collected. They look like what we

513
00:24:30,040 --> 00:24:32,960
Speaker 1: all saw in Game of Thrones. And so the stuff

514
00:24:33,000 --> 00:24:35,640
Speaker 1: that they took after they edited the genome is they

515
00:24:35,920 --> 00:24:40,919
Speaker 1: put that genetic information into an egg from a gray wolf,

516
00:24:40,960 --> 00:24:44,639
Speaker 1: and then they got that gray wolf pregnant, she carried

517
00:24:44,680 --> 00:24:47,320
Speaker 1: it to term, and she gave birth to a dire wolf.

518
00:24:47,359 --> 00:24:48,560
Speaker 1: And they did that three times.

519
00:24:48,880 --> 00:24:49,160
Speaker 5: Mm.

520
00:24:50,080 --> 00:24:52,680
Speaker 2: So this sort of answer is the deep philosophical question, right,

521
00:24:52,800 --> 00:24:55,800
Speaker 2: what came first the dire wolf for the puppy? I guess,

522
00:24:56,080 --> 00:24:59,840
Speaker 2: because here you implanted a dire wolf into another species

523
00:25:00,040 --> 00:25:02,560
Speaker 2: and it was able to gestate and give birth to it. Yeah,

524
00:25:02,720 --> 00:25:05,000
Speaker 2: and does that require the species to be similar? Like

525
00:25:05,000 --> 00:25:07,200
Speaker 2: you couldn't put that inside an elephant for example.

526
00:25:07,280 --> 00:25:09,840
Speaker 1: Right, that's right. It requires the species to be similar,

527
00:25:09,880 --> 00:25:13,080
Speaker 1: but this is another area where things could be different.

528
00:25:13,200 --> 00:25:17,320
Speaker 1: So maternal effects refers to all of the different ways

529
00:25:17,359 --> 00:25:20,200
Speaker 1: that a fetus is impacted by the mom's body. It

530
00:25:20,240 --> 00:25:22,960
Speaker 1: could be the hormones that she's producing, right, and you know,

531
00:25:23,000 --> 00:25:25,439
Speaker 1: subsequently it can be the bacteria that she passes on

532
00:25:25,560 --> 00:25:27,440
Speaker 1: to her offspring, or the things that you get from

533
00:25:27,440 --> 00:25:30,280
Speaker 1: the milk, including bacteria, and so any of that maternal

534
00:25:30,320 --> 00:25:33,160
Speaker 1: effects stuff that was dire wolf specific, they are now

535
00:25:33,200 --> 00:25:35,120
Speaker 1: getting gray wolf versions of.

536
00:25:35,480 --> 00:25:37,679
Speaker 2: And give us a sensum like the distance between these

537
00:25:37,680 --> 00:25:40,000
Speaker 2: two species. I mean, it's sort of amazing to me

538
00:25:40,080 --> 00:25:42,080
Speaker 2: that you can have one species give birth to another.

539
00:25:42,359 --> 00:25:44,800
Speaker 2: I mean, could you put a human baby inside a

540
00:25:44,840 --> 00:25:47,520
Speaker 2: gorilla for example. I'm not suggesting anybody do that. Yeah,

541
00:25:47,720 --> 00:25:50,080
Speaker 2: this is a thought experiment to think about the difference,

542
00:25:50,160 --> 00:25:52,719
Speaker 2: Like how far away from us could you get and

543
00:25:52,760 --> 00:25:53,800
Speaker 2: still have a live birth.

544
00:25:54,040 --> 00:25:56,000
Speaker 1: I don't think enough experiments have been done where we

545
00:25:56,040 --> 00:25:57,320
Speaker 1: could have a good answer to that.

546
00:25:57,920 --> 00:26:00,280
Speaker 2: It sounds like you're suggesting some human experimentation in there.

547
00:26:00,280 --> 00:26:01,239
Speaker 2: I'm not signing on to that.

548
00:26:01,480 --> 00:26:04,760
Speaker 1: I have absolutely not suggesting that kind of human experimentation.

549
00:26:04,840 --> 00:26:08,560
Speaker 1: I think that's wildly unethical to be clear on the record,

550
00:26:09,200 --> 00:26:09,919
Speaker 1: shouldn't do that.

551
00:26:10,040 --> 00:26:11,600
Speaker 2: But you're saying that the only way to know is

552
00:26:11,600 --> 00:26:12,400
Speaker 2: to do the experiment.

553
00:26:12,560 --> 00:26:14,040
Speaker 1: Yeah, I think in a lot of cases that would

554
00:26:14,040 --> 00:26:15,360
Speaker 1: be the best way to know. I mean, I think

555
00:26:15,400 --> 00:26:20,040
Speaker 1: closer related species probably have similar requirements. It wouldn't surprise

556
00:26:20,160 --> 00:26:24,560
Speaker 1: me if a chimpanzee or a bonobo could well. But

557
00:26:24,640 --> 00:26:26,480
Speaker 1: so like, we're much bigger than them, and so at

558
00:26:26,480 --> 00:26:28,680
Speaker 1: some point you get to how big is the head

559
00:26:28,680 --> 00:26:31,719
Speaker 1: that's coming through a tiny opening? And like, chimpanzees might

560
00:26:31,760 --> 00:26:33,120
Speaker 1: not be able to survive that part.

561
00:26:33,320 --> 00:26:36,480
Speaker 2: You know, Well, do we know how much experimentation Colossal did,

562
00:26:36,560 --> 00:26:39,360
Speaker 2: Like is this their first attempt and their first success

563
00:26:39,480 --> 00:26:41,040
Speaker 2: or did they have a bunch of failures first?

564
00:26:41,359 --> 00:26:41,560
Speaker 5: Oh?

565
00:26:41,720 --> 00:26:45,640
Speaker 1: You know, I don't know that they have publicly reported

566
00:26:45,760 --> 00:26:48,800
Speaker 1: if there were gray wolves who had miscarriages or who

567
00:26:48,840 --> 00:26:51,639
Speaker 1: died in childbirth or anything. I don't remember seeing anything

568
00:26:51,680 --> 00:26:54,240
Speaker 1: like that. I think in general, they've kept this project

569
00:26:54,280 --> 00:26:56,520
Speaker 1: pretty close to the vest and haven't been releasing too

570
00:26:56,520 --> 00:26:58,880
Speaker 1: many details. But we know that it worked at least

571
00:26:58,880 --> 00:26:59,399
Speaker 1: three times.

572
00:26:59,600 --> 00:27:01,480
Speaker 2: And is this like a scientific project or they can

573
00:27:01,480 --> 00:27:04,080
Speaker 2: be publishing papers in peer review journals, or is it

574
00:27:04,119 --> 00:27:06,120
Speaker 2: a commercial project like they're going to be selling dire

575
00:27:06,119 --> 00:27:07,480
Speaker 2: wolf puppies both.

576
00:27:07,560 --> 00:27:10,040
Speaker 1: I don't have any evidence that they're selling dire wolf puppies.

577
00:27:10,240 --> 00:27:13,639
Speaker 1: They have been publishing scientific papers as they go. So

578
00:27:13,720 --> 00:27:16,280
Speaker 1: for example, they have a paper in review right now

579
00:27:16,720 --> 00:27:20,320
Speaker 1: showing that gray wolves are the closest living relatives to

580
00:27:20,440 --> 00:27:24,480
Speaker 1: the dire wolfs. Beth Shapiro does study ancient DNA, and

581
00:27:24,560 --> 00:27:27,840
Speaker 1: she works on these questions about relatedness between species, and

582
00:27:27,920 --> 00:27:30,439
Speaker 1: so as they go, they're doing a lot of science

583
00:27:30,440 --> 00:27:32,520
Speaker 1: and they're publishing it and sharing it as they go.

584
00:27:32,880 --> 00:27:34,560
Speaker 2: And do you get the sense that this is cutting

585
00:27:34,600 --> 00:27:36,520
Speaker 2: edge science? I know that a lot of times in

586
00:27:36,600 --> 00:27:39,720
Speaker 2: popular science we hear about something and we're told it's amazing,

587
00:27:39,760 --> 00:27:41,360
Speaker 2: and then people in the field are like, yeah, that's

588
00:27:41,359 --> 00:27:44,440
Speaker 2: not very impressive, and Bob over there at Georgia is

589
00:27:44,440 --> 00:27:46,879
Speaker 2: already doing that. Is this cutting edge science?

590
00:27:47,280 --> 00:27:49,440
Speaker 1: I would say that in addition to doing solid science,

591
00:27:49,520 --> 00:27:52,240
Speaker 1: they are doing pretty cutting edge stuff. I do feel

592
00:27:52,240 --> 00:27:57,560
Speaker 1: like bringing back these ancient genes is impressive. I'm not

593
00:27:57,600 --> 00:28:00,679
Speaker 1: feeling completely satisfied at an emotional level that we have

594
00:28:01,680 --> 00:28:04,399
Speaker 1: undone any damage our species might have done. Like, I

595
00:28:04,440 --> 00:28:07,520
Speaker 1: don't necessarily feel like this method does that, but I

596
00:28:07,560 --> 00:28:10,000
Speaker 1: do feel like they've done some pretty interesting stuff.

597
00:28:10,040 --> 00:28:11,840
Speaker 2: All right. So they've started from a gray wolf and

598
00:28:11,920 --> 00:28:15,959
Speaker 2: they've basically taken a big step towards dire wolf DNA,

599
00:28:16,119 --> 00:28:18,560
Speaker 2: not completely all the way there, only twenty edits, but

600
00:28:18,600 --> 00:28:21,280
Speaker 2: still in the sort of information space of DNA. They've

601
00:28:21,280 --> 00:28:23,720
Speaker 2: gone from the gray wolf towards a dire wolf and

602
00:28:23,760 --> 00:28:26,240
Speaker 2: then successfully given birth to this critter which is like

603
00:28:26,320 --> 00:28:28,720
Speaker 2: alive in running around and baying at the moon and

604
00:28:28,760 --> 00:28:31,280
Speaker 2: stuff like that. So I guess the question then is like,

605
00:28:31,720 --> 00:28:33,880
Speaker 2: is this a dire wolf? What is this thing?

606
00:28:34,400 --> 00:28:34,560
Speaker 5: Right?

607
00:28:34,640 --> 00:28:36,400
Speaker 1: Yeah, so that is the big question. And I want

608
00:28:36,440 --> 00:28:38,600
Speaker 1: to real quick say something that maybe I wish I

609
00:28:38,600 --> 00:28:40,600
Speaker 1: had mentioned earlier, which is that we don't yet have

610
00:28:40,680 --> 00:28:44,960
Speaker 1: the ability to print genomes. So even if you did have,

611
00:28:45,080 --> 00:28:48,680
Speaker 1: for example, the entire direwolf genome read out, we don't

612
00:28:48,720 --> 00:28:52,160
Speaker 1: have a machine that can print an entire genome at

613
00:28:52,200 --> 00:28:54,680
Speaker 1: a reasonable cost, like I think it would be like

614
00:28:54,680 --> 00:28:57,000
Speaker 1: a billion dollars or something. And so that's another reason

615
00:28:57,040 --> 00:29:00,479
Speaker 1: why you take gray wolf genomes and edit them and

616
00:29:00,520 --> 00:29:02,440
Speaker 1: then use that to make the next round of babies.

617
00:29:02,440 --> 00:29:05,520
Speaker 1: So it's possible that in ten twenty years or something,

618
00:29:05,880 --> 00:29:08,560
Speaker 1: you could print everything you know about the dire wolf

619
00:29:08,640 --> 00:29:11,000
Speaker 1: genome instead of picking these twenty genes to tinker with,

620
00:29:11,080 --> 00:29:13,040
Speaker 1: and then you could fill in the spaces with whatever

621
00:29:13,040 --> 00:29:14,800
Speaker 1: you know about the gray wolf genome and get a

622
00:29:14,800 --> 00:29:17,160
Speaker 1: little closer. But these are the techniques we have right now.

623
00:29:17,240 --> 00:29:20,240
Speaker 2: And so when you say print, you mean like synthetically

624
00:29:20,320 --> 00:29:23,400
Speaker 2: assemble from the basic amino acids, because in the end,

625
00:29:23,440 --> 00:29:25,640
Speaker 2: it is just chemistry, right, or like, let's bring these together,

626
00:29:25,680 --> 00:29:28,280
Speaker 2: click them together. This is a molecule we know can exist.

627
00:29:28,760 --> 00:29:30,480
Speaker 2: But you're saying that's still really expensive.

628
00:29:30,720 --> 00:29:33,360
Speaker 1: Exactly, Yeah, it is very expensive. And you know you've

629
00:29:33,400 --> 00:29:35,680
Speaker 1: got billions of base pairs or something in a genome.

630
00:29:35,760 --> 00:29:38,600
Speaker 1: So even if the cost is fairly minor, it adds

631
00:29:38,640 --> 00:29:39,280
Speaker 1: up pretty quick.

632
00:29:39,400 --> 00:29:41,840
Speaker 2: It's the kind of thing that feels like, in ten years,

633
00:29:41,920 --> 00:29:45,160
Speaker 2: it's going to cost seventeen cents. Yeah, maybe it's somebody's

634
00:29:45,200 --> 00:29:47,760
Speaker 2: Pahd thesis and it cost millions of dollars. But biology

635
00:29:47,960 --> 00:29:50,000
Speaker 2: makes these leaps and bounds all the time, where like

636
00:29:50,000 --> 00:29:52,120
Speaker 2: things that used to be Peachd thesis are now like

637
00:29:52,160 --> 00:29:53,880
Speaker 2: a little machine that sits on the bench and it

638
00:29:53,920 --> 00:29:55,720
Speaker 2: takes two minutes and you press the button.

639
00:29:55,560 --> 00:29:58,800
Speaker 1: And I imagine that's both frustrating and exhilarating if you're

640
00:29:58,800 --> 00:30:01,240
Speaker 1: a student who's like I, I spent five years on

641
00:30:01,320 --> 00:30:03,760
Speaker 1: something that now takes thirty minutes. But you know you

642
00:30:03,840 --> 00:30:06,240
Speaker 1: had to be part of the people who made the

643
00:30:06,280 --> 00:30:07,120
Speaker 1: path to get there.

644
00:30:07,280 --> 00:30:09,840
Speaker 2: Yeah, and that's why biology can do so many amazing

645
00:30:09,880 --> 00:30:12,840
Speaker 2: things because things that used to be impossible are now trivial,

646
00:30:13,000 --> 00:30:15,600
Speaker 2: which opens up the space of possibilities for like new

647
00:30:15,680 --> 00:30:19,560
Speaker 2: whole emergent concepts that nobody even imagined before. So yeah,

648
00:30:19,680 --> 00:30:20,600
Speaker 2: I look forward to that.

649
00:30:20,760 --> 00:30:21,000
Speaker 1: Yeah.

650
00:30:21,040 --> 00:30:23,160
Speaker 2: So let's get back to the question. Yeah, is this

651
00:30:23,240 --> 00:30:26,320
Speaker 2: thing that they made a diar wolf Kelly, what's your ruling?

652
00:30:26,600 --> 00:30:28,600
Speaker 1: Well, so before I give you my opinion, I'm going

653
00:30:28,680 --> 00:30:30,600
Speaker 1: to back up and say that, you know, when this

654
00:30:30,800 --> 00:30:33,800
Speaker 1: announcement first came out, apparently, I think it's the New

655
00:30:33,880 --> 00:30:37,960
Speaker 1: Yorker broke the embargo. So when a research group has

656
00:30:38,000 --> 00:30:40,400
Speaker 1: a finding that they want to share, they will send

657
00:30:40,440 --> 00:30:43,800
Speaker 1: a report out to major news organizations and they'll say,

658
00:30:43,840 --> 00:30:46,080
Speaker 1: you can't mention this until we tell you you can

659
00:30:46,120 --> 00:30:47,880
Speaker 1: mention it. But if you want to start writing the

660
00:30:47,920 --> 00:30:49,840
Speaker 1: story now, so that when we give the thumbs up

661
00:30:49,840 --> 00:30:52,480
Speaker 1: you're already ready to go, then we'd be happy to

662
00:30:52,520 --> 00:30:55,000
Speaker 1: talk to you now. And apparently the New Yorker broke

663
00:30:55,040 --> 00:30:58,240
Speaker 1: the embargo. And the way that I heard this story

664
00:30:58,480 --> 00:31:00,680
Speaker 1: was that they have brought back the die wolf. And

665
00:31:01,080 --> 00:31:02,640
Speaker 1: you know, Zach even sent it to me and he

666
00:31:02,720 --> 00:31:04,840
Speaker 1: was like, the dire wolf is back. How cool is that?

667
00:31:05,280 --> 00:31:08,520
Speaker 1: And we both actually should have been a little bit

668
00:31:08,560 --> 00:31:11,920
Speaker 1: more skeptical because we had interviewed Beth Shapiro, who's the

669
00:31:11,960 --> 00:31:14,920
Speaker 1: chief science officer for Colossal, for our book Soon Is,

670
00:31:15,000 --> 00:31:17,719
Speaker 1: because we had a little section on de extinction and

671
00:31:18,040 --> 00:31:20,120
Speaker 1: she had made very clear in that interview what the

672
00:31:20,160 --> 00:31:23,560
Speaker 1: process actually involves, which is not making an exact replica.

673
00:31:23,840 --> 00:31:27,120
Speaker 1: But in the days after that article that Zach sent

674
00:31:27,160 --> 00:31:30,000
Speaker 1: me from Time that was like, we have the dire wolf. Now,

675
00:31:30,040 --> 00:31:32,960
Speaker 1: there's been a lot of like anger heaped on Colossal

676
00:31:33,040 --> 00:31:35,760
Speaker 1: for being like, this isn't a dire wolf. And so

677
00:31:36,120 --> 00:31:39,840
Speaker 1: Beth Shapiro, again the chief science officer, has said, you know,

678
00:31:39,880 --> 00:31:43,080
Speaker 1: there's something like thirty definitions of a species out there,

679
00:31:43,080 --> 00:31:45,200
Speaker 1: and she's right, there's a big debate about what counts

680
00:31:45,240 --> 00:31:49,000
Speaker 1: as a species and the dire wolf that Colossal made

681
00:31:50,000 --> 00:31:54,160
Speaker 1: fits some of those definitions, but doesn't fit others I see.

682
00:31:54,280 --> 00:31:56,640
Speaker 1: And so the question is, you know, to what extent

683
00:31:56,640 --> 00:31:58,720
Speaker 1: should you be excited about this? And I think from

684
00:31:58,720 --> 00:32:02,360
Speaker 1: the standpoint of of wonder, you know, like bringing back

685
00:32:02,400 --> 00:32:05,239
Speaker 1: an organism that so many people want to see, like

686
00:32:05,280 --> 00:32:07,080
Speaker 1: from Game of Thrones for example. You know, I can

687
00:32:07,200 --> 00:32:10,600
Speaker 1: imagine you put these dire wolves in a zoo and

688
00:32:10,640 --> 00:32:13,920
Speaker 1: people get more excited about conservation. I can see some

689
00:32:14,040 --> 00:32:17,160
Speaker 1: benefits in that regard, but I guess again, my concern

690
00:32:17,200 --> 00:32:19,760
Speaker 1: is that people are going to feel like the moral

691
00:32:19,880 --> 00:32:22,360
Speaker 1: responsibility that should be on our shoulders for killing a

692
00:32:22,440 --> 00:32:25,080
Speaker 1: species could go away if we're able to bring these

693
00:32:25,080 --> 00:32:27,960
Speaker 1: species back. But again, we don't know if their behaviors

694
00:32:28,000 --> 00:32:30,920
Speaker 1: are natural. Maybe there were very unique behaviors that were

695
00:32:30,960 --> 00:32:33,040
Speaker 1: taught to them by their mothers that they'll never express

696
00:32:33,080 --> 00:32:35,160
Speaker 1: now because there's no one there to teach them those things.

697
00:32:35,360 --> 00:32:37,000
Speaker 1: And so you know, to me, they differ in ways

698
00:32:37,040 --> 00:32:39,000
Speaker 1: that matter because I don't think you could ever release

699
00:32:39,040 --> 00:32:41,320
Speaker 1: them back out into the wild. They'll never fill their

700
00:32:41,320 --> 00:32:43,880
Speaker 1: ecological role. They won't be what we lost.

701
00:32:44,200 --> 00:32:46,360
Speaker 2: Could be something else though, right like if they escape

702
00:32:46,360 --> 00:32:49,160
Speaker 2: into the wild. They could create some new niche from themselves.

703
00:32:49,200 --> 00:32:51,360
Speaker 2: They could be invasive, right, and we could be overrun

704
00:32:51,400 --> 00:32:54,240
Speaker 2: with dire wolves or you know, ancient guinea pigs with

705
00:32:54,400 --> 00:32:56,640
Speaker 2: really strong legs or whatever we're going to bring back next.

706
00:32:56,880 --> 00:33:01,160
Speaker 1: Yeah, what do you think they bring back the dire wolf?

707
00:33:01,160 --> 00:33:01,880
Speaker 1: Are you excited?

708
00:33:02,000 --> 00:33:04,560
Speaker 2: I think it's really cool and an awesome demonstration of

709
00:33:04,600 --> 00:33:07,960
Speaker 2: biological technology. It doesn't feel to me like they brought

710
00:33:08,000 --> 00:33:10,760
Speaker 2: back the direwolf. I mean, I imagine if humans went

711
00:33:10,800 --> 00:33:14,440
Speaker 2: extinct and then in the future AI brought back something

712
00:33:14,560 --> 00:33:17,280
Speaker 2: kind of similar to humans and they're like, look, yeah,

713
00:33:17,360 --> 00:33:19,680
Speaker 2: we didn't kill them all there back. I wouldn't really

714
00:33:19,680 --> 00:33:22,520
Speaker 2: feel like we're back. And so, yeah, it doesn't really

715
00:33:22,520 --> 00:33:25,719
Speaker 2: feel like the direwolf, but doesn't have to be, right, Like,

716
00:33:26,160 --> 00:33:29,200
Speaker 2: this shows that you can do biological engineering in a

717
00:33:29,240 --> 00:33:31,480
Speaker 2: really cool way. You can start from one animal. You

718
00:33:31,520 --> 00:33:34,720
Speaker 2: can move through that information space towards another animal you

719
00:33:34,720 --> 00:33:38,120
Speaker 2: think is interesting or useful or cool or worth bringing back,

720
00:33:38,280 --> 00:33:40,200
Speaker 2: and you could do that multiple times. Right, You could

721
00:33:40,200 --> 00:33:41,960
Speaker 2: go in the direwolf direction and you could add a

722
00:33:42,000 --> 00:33:44,560
Speaker 2: little bit of fox or something. I think this opens

723
00:33:44,640 --> 00:33:46,720
Speaker 2: up a whole new avenue. I think that's the exciting

724
00:33:46,800 --> 00:33:50,520
Speaker 2: thing about it, not like, oh, we have cleansed ourselves

725
00:33:50,680 --> 00:33:52,080
Speaker 2: of this crime we committed.

726
00:33:52,240 --> 00:33:53,760
Speaker 1: And I think that is a great point. So if

727
00:33:53,760 --> 00:33:57,560
Speaker 1: you're trying to understand what makes two species that are

728
00:33:57,560 --> 00:34:00,440
Speaker 1: closely related different, this now does get of us the

729
00:34:00,480 --> 00:34:02,920
Speaker 1: tools to answer those questions. You know, is it this gene?

730
00:34:03,000 --> 00:34:04,600
Speaker 1: Is it that gene? What happens if you take her

731
00:34:04,600 --> 00:34:06,680
Speaker 1: with this gene? And so we do now have this

732
00:34:06,760 --> 00:34:10,880
Speaker 1: amazing ability to better understand how the genome results in

733
00:34:10,920 --> 00:34:14,520
Speaker 1: differences in appearance and function for organisms. That's pretty cool.

734
00:34:14,640 --> 00:34:16,680
Speaker 2: And we could take chihuahuas and give them like really

735
00:34:16,680 --> 00:34:18,840
Speaker 2: strong legs, that would be really amazing. I'd like to

736
00:34:18,840 --> 00:34:20,600
Speaker 2: see that totally buff chihuahua's.

737
00:34:21,080 --> 00:34:23,400
Speaker 1: Yeah, my daughter would absolutely adopt one of those. But

738
00:34:23,440 --> 00:34:26,920
Speaker 1: she would adopt any chihuahua, no matter how pitiful they look.

739
00:34:27,280 --> 00:34:29,120
Speaker 2: You know, I used to be kind of anti chihuahua

740
00:34:29,160 --> 00:34:31,560
Speaker 2: because I thought about them as like little gappy dogs.

741
00:34:31,960 --> 00:34:35,000
Speaker 2: But the dog that we adopted, he's like forty percent chihuahua,

742
00:34:35,719 --> 00:34:38,279
Speaker 2: but he's really wonderful and he never barks. He's like

743
00:34:38,480 --> 00:34:41,320
Speaker 2: German shepherd and chihuahua, which is an interesting combination.

744
00:34:41,480 --> 00:34:42,400
Speaker 1: How did that happen?

745
00:34:42,480 --> 00:34:45,000
Speaker 2: Yeah, there was an interesting evening or somebody somewhere. Yeah,

746
00:34:45,120 --> 00:34:48,680
Speaker 2: one night in Mexico. But he's got this wonderful German

747
00:34:48,719 --> 00:34:51,279
Speaker 2: shepherd plus chihuahua face. It's like German shepherd but a

748
00:34:51,280 --> 00:34:53,239
Speaker 2: little bit of sad eyes. I don't know. Oh, I

749
00:34:53,280 --> 00:34:53,719
Speaker 2: love him.

750
00:34:53,840 --> 00:34:54,800
Speaker 1: That sounds wonderful.

751
00:34:55,160 --> 00:34:56,880
Speaker 2: Yeah, so I'm warming up the chihuahua.

752
00:34:57,120 --> 00:34:57,400
Speaker 5: All right.

753
00:34:57,440 --> 00:34:59,560
Speaker 1: Well, let's take a break and then when we come

754
00:34:59,600 --> 00:35:02,120
Speaker 1: back to talk a little bit more about their plans

755
00:35:02,120 --> 00:35:04,080
Speaker 1: for bringing back the mammoth, which we talked about a

756
00:35:04,120 --> 00:35:07,719
Speaker 1: little bit earlier. So start dreaming of mammoth steakes and

757
00:35:07,760 --> 00:35:27,120
Speaker 1: we'll be back to you soon. And we're back from

758
00:35:27,120 --> 00:35:29,920
Speaker 1: the commercial break, which seems like a fine time to

759
00:35:30,040 --> 00:35:32,920
Speaker 1: mention that. On Apple, if you subscribe to our podcast,

760
00:35:33,000 --> 00:35:35,719
Speaker 1: you can get this podcast without ads. But thank you

761
00:35:35,760 --> 00:35:37,880
Speaker 1: for listening to the ads because they allow us to

762
00:35:38,080 --> 00:35:39,880
Speaker 1: do all of the research that we love doing for

763
00:35:39,920 --> 00:35:40,279
Speaker 1: this show.

764
00:35:40,480 --> 00:35:42,040
Speaker 2: If you love the show and don't like the ads,

765
00:35:42,080 --> 00:35:43,600
Speaker 2: you can make the ads go extinct.

766
00:35:43,760 --> 00:35:48,319
Speaker 1: Check out, and if Apple changes their mind, they'll de

767
00:35:48,440 --> 00:35:49,680
Speaker 1: extinct the ads.

768
00:35:50,920 --> 00:35:53,359
Speaker 2: And you'll be forced to listen to them all retroactively.

769
00:35:54,480 --> 00:35:56,680
Speaker 2: Oh no, that's not what we're doing today. We're talking

770
00:35:56,680 --> 00:36:02,480
Speaker 2: about retroactive undeletion of animals called de extinctificationisism. Tell us

771
00:36:02,560 --> 00:36:04,640
Speaker 2: about how we might bring back the wooly mammoth. Now,

772
00:36:04,680 --> 00:36:07,120
Speaker 2: I've been joking about dire wolf steaks, but a lot

773
00:36:07,160 --> 00:36:09,320
Speaker 2: of humans made it through the winter on the meat

774
00:36:09,360 --> 00:36:11,440
Speaker 2: of the wooly mammoth. Isn't that true? It's really something

775
00:36:11,520 --> 00:36:12,880
Speaker 2: humans have eaten for a long time.

776
00:36:13,160 --> 00:36:14,960
Speaker 1: I think that is true. Yeah, I think we did

777
00:36:15,000 --> 00:36:17,120
Speaker 1: eat wooly mammoth. I mean they give you a large

778
00:36:17,200 --> 00:36:19,279
Speaker 1: quantity of food, whether it's delicious or not.

779
00:36:19,719 --> 00:36:22,719
Speaker 2: Based on my research, mostly from reading Farside comics, I

780
00:36:22,719 --> 00:36:24,600
Speaker 2: think a lot of humans have did with the mammoths.

781
00:36:25,600 --> 00:36:28,160
Speaker 1: I mean, Gary Larson never got anything wrong ever, I

782
00:36:28,200 --> 00:36:30,000
Speaker 1: think so I'm on board with that.

783
00:36:30,080 --> 00:36:32,319
Speaker 2: You have the best science consultants.

784
00:36:31,719 --> 00:36:36,320
Speaker 1: For sure, he did. He did so. Mammoths went extinct

785
00:36:36,320 --> 00:36:39,560
Speaker 1: about four thousand years ago, and so when you find

786
00:36:39,600 --> 00:36:42,080
Speaker 1: a specimen preserved the right way, you can get more

787
00:36:42,080 --> 00:36:44,560
Speaker 1: information out of it. And they tended to live in

788
00:36:44,640 --> 00:36:46,880
Speaker 1: cold areas like tundras, so I think you've got a

789
00:36:46,920 --> 00:36:50,200
Speaker 1: slightly better chance at getting their DNA in the first place,

790
00:36:50,400 --> 00:36:52,480
Speaker 1: and so we found a lot of mammoths that are

791
00:36:52,520 --> 00:36:54,720
Speaker 1: preserved in a way where you can get some DNA

792
00:36:54,760 --> 00:36:56,920
Speaker 1: from them. So we have a lot more information to

793
00:36:57,000 --> 00:36:59,520
Speaker 1: work with than we did with the dire wolf and

794
00:36:59,640 --> 00:37:02,319
Speaker 1: so in this case. But again it's still difficult, and

795
00:37:02,360 --> 00:37:03,960
Speaker 1: I just want to highlight a couple of reasons why

796
00:37:03,960 --> 00:37:06,520
Speaker 1: it's difficult. We talked about the DNA degrading, and that

797
00:37:06,640 --> 00:37:09,000
Speaker 1: makes it hard and it breaks into little pieces. But

798
00:37:09,120 --> 00:37:11,759
Speaker 1: you also have to be sure that you're not getting contamination.

799
00:37:11,960 --> 00:37:15,720
Speaker 1: So for example, when that mammoth died, bacteria probably started

800
00:37:15,760 --> 00:37:18,440
Speaker 1: to break it down before it completely froze through, So

801
00:37:18,480 --> 00:37:19,920
Speaker 1: you have to make sure you're not getting any of

802
00:37:19,960 --> 00:37:23,759
Speaker 1: those bacterial genomes in your genome. Or you know, some

803
00:37:23,880 --> 00:37:26,600
Speaker 1: clumsy scientists didn't have their gloves on the whole time.

804
00:37:26,880 --> 00:37:30,000
Speaker 1: Now you've got human DNA in there. So not only

805
00:37:30,000 --> 00:37:33,200
Speaker 1: do you have to try to find the ancient DNA

806
00:37:33,239 --> 00:37:34,600
Speaker 1: and figure out what to do with it, you need

807
00:37:34,600 --> 00:37:37,040
Speaker 1: to make sure that all of the DNA that's contaminating

808
00:37:37,120 --> 00:37:38,080
Speaker 1: it has been removed.

809
00:37:38,160 --> 00:37:40,520
Speaker 2: This sounds like an awesome update of the fly Guman

810
00:37:40,640 --> 00:37:45,440
Speaker 2: accidentally injects their DNA into the mammothtinctification project. Weird mammoth

811
00:37:45,480 --> 00:37:47,719
Speaker 2: baby comes out with like Jeff Goldbloom's head on.

812
00:37:47,680 --> 00:37:51,120
Speaker 1: It, I'd feel so weird about that. Jeff Goldbloom is

813
00:37:51,160 --> 00:37:52,240
Speaker 1: so handsome.

814
00:37:52,880 --> 00:37:56,400
Speaker 2: You'd make a great mammoth. I think, okay, all right, anyway, Netflix,

815
00:37:56,480 --> 00:37:57,800
Speaker 2: call us if you want to turn that into a

816
00:37:57,840 --> 00:37:58,440
Speaker 2: real project.

817
00:37:58,480 --> 00:38:00,000
Speaker 1: We've got lots of other ideas too.

818
00:38:02,040 --> 00:38:04,200
Speaker 2: Few more terrible than that, but yes, we do, right,

819
00:38:04,480 --> 00:38:07,240
Speaker 2: all right. So you get this DNA from the specimen,

820
00:38:07,280 --> 00:38:09,400
Speaker 2: and I think it is similar living species, right for

821
00:38:09,440 --> 00:38:11,319
Speaker 2: a reference, don't you? What are you using the case

822
00:38:11,360 --> 00:38:11,880
Speaker 2: of the mammoth.

823
00:38:12,080 --> 00:38:14,719
Speaker 1: So there are three living species of elephants. There are

824
00:38:14,719 --> 00:38:17,399
Speaker 1: two African elephants. One lives in the forest and one

825
00:38:17,400 --> 00:38:20,000
Speaker 1: lives in the grasslands or the savannahs, and then there

826
00:38:20,080 --> 00:38:23,680
Speaker 1: is an Asian elephant. The Asian elephant they think is

827
00:38:23,880 --> 00:38:27,879
Speaker 1: closer genetically to the wooly mammoths, and so they're using

828
00:38:27,920 --> 00:38:32,600
Speaker 1: the Asian elephant as their reference genome. They are trying

829
00:38:32,640 --> 00:38:36,720
Speaker 1: to essentially make a more cold adapted Asian elephant because

830
00:38:36,719 --> 00:38:39,200
Speaker 1: again they are saying that they want to release the

831
00:38:39,200 --> 00:38:42,400
Speaker 1: wooly mammoth into what would have been its native environment,

832
00:38:42,840 --> 00:38:45,160
Speaker 1: so they're trying to create a wooly mammoth that can

833
00:38:45,200 --> 00:38:48,440
Speaker 1: survive there, and so they're looking at things like shaggy hair,

834
00:38:49,120 --> 00:38:52,160
Speaker 1: fat deposits. They also want to bring back the curved tusks,

835
00:38:52,200 --> 00:38:54,440
Speaker 1: and I think maybe that's partly because those are just

836
00:38:54,480 --> 00:38:58,040
Speaker 1: like iconic mammoth things, but also maybe they're important for

837
00:38:58,120 --> 00:39:03,000
Speaker 1: knocking down trees. And so they've identified sixty five genes

838
00:39:03,200 --> 00:39:06,920
Speaker 1: that they think could make the Asian elephant more cold tolerant,

839
00:39:07,360 --> 00:39:09,759
Speaker 1: and so they're going to make these edits to the

840
00:39:09,800 --> 00:39:12,640
Speaker 1: Asian elephant genome. And then they're not sure if they're

841
00:39:12,640 --> 00:39:16,960
Speaker 1: going to impregnate an African elephant or an Asian elephant,

842
00:39:17,040 --> 00:39:20,920
Speaker 1: because the African elephant is bigger than the Asian elephant,

843
00:39:21,560 --> 00:39:23,640
Speaker 1: and so they think it might have a better time

844
00:39:23,920 --> 00:39:28,080
Speaker 1: giving birth to a wooly mammoth baby. And elephants are

845
00:39:28,120 --> 00:39:31,000
Speaker 1: pregnant for some crazy amount of time, like a whole

846
00:39:31,080 --> 00:39:33,279
Speaker 1: year or something. Maybe if it's even longer basically.

847
00:39:32,960 --> 00:39:35,200
Speaker 2: Like two years, two years, I think, yeah.

848
00:39:35,000 --> 00:39:37,440
Speaker 1: Yeah, I think it's something like twenty two months. Can

849
00:39:37,480 --> 00:39:42,240
Speaker 1: you imagine carrying around a wooly mammoth baby for twenty

850
00:39:42,280 --> 00:39:44,960
Speaker 1: two months If they're bigger than Asian elephants. That sounds

851
00:39:45,320 --> 00:39:51,000
Speaker 1: incredibly unpleasant. But anyway, and it's not even yours, and

852
00:39:51,080 --> 00:39:53,520
Speaker 1: it's not even yours, right, but in.

853
00:39:53,400 --> 00:39:55,080
Speaker 2: Some sense it is right you were saying earlier. The

854
00:39:55,120 --> 00:39:58,440
Speaker 2: maternal environment is an important factor. Right, It's not like

855
00:39:58,480 --> 00:40:02,240
Speaker 2: when you're the surrogate, you're just some sort of irrelevant host.

856
00:40:02,560 --> 00:40:04,760
Speaker 2: Like the maternal environment plays a role in the development

857
00:40:04,800 --> 00:40:05,280
Speaker 2: of the baby.

858
00:40:05,480 --> 00:40:07,080
Speaker 1: Yes, that's right, and the things you eat might be

859
00:40:07,120 --> 00:40:10,720
Speaker 1: playing a role. And then also after elephants are born,

860
00:40:11,360 --> 00:40:14,319
Speaker 1: Beth Shapiro was telling me that they often consume some

861
00:40:14,400 --> 00:40:17,520
Speaker 1: of the feces of family members to get their microbiome.

862
00:40:17,640 --> 00:40:20,520
Speaker 1: Makes sense, Yeah, And so if the wooly mammoth had

863
00:40:20,560 --> 00:40:24,080
Speaker 1: a wooly mammoth specific microbiome, they're going to be getting

864
00:40:24,160 --> 00:40:28,279
Speaker 1: an Asian or African elephant specific microbiome. But anyway, so

865
00:40:28,280 --> 00:40:30,360
Speaker 1: they're going to be growing up with an Asian or

866
00:40:30,440 --> 00:40:34,879
Speaker 1: African elephant parent. And then the plan is to yeah,

867
00:40:35,000 --> 00:40:37,440
Speaker 1: release them into the wild at some point to try

868
00:40:37,440 --> 00:40:39,839
Speaker 1: to recreate what the wooly mammoths were doing.

869
00:40:40,320 --> 00:40:42,879
Speaker 2: That's a whole fascinating other angle. I never even thought

870
00:40:42,880 --> 00:40:45,320
Speaker 2: about the microbiome of these creatures, right, which is usually

871
00:40:45,320 --> 00:40:48,479
Speaker 2: passed down from the parents. If you bring a species back,

872
00:40:48,680 --> 00:40:51,799
Speaker 2: it's microbiome has gone extinct with it, And obviously you

873
00:40:51,840 --> 00:40:54,040
Speaker 2: don't have the DNA or its microbiome unless you like

874
00:40:54,120 --> 00:40:57,120
Speaker 2: dug into its gut and found those bacteria and sequence

875
00:40:57,200 --> 00:41:00,560
Speaker 2: their DNA also, and that could somehow replicate that. That's

876
00:41:00,560 --> 00:41:03,200
Speaker 2: a whole other fascinating dimension it is. Or maybe you're

877
00:41:03,200 --> 00:41:05,600
Speaker 2: just going to end up with decincified species members with

878
00:41:05,719 --> 00:41:07,160
Speaker 2: like bad digestive problem.

879
00:41:07,360 --> 00:41:11,120
Speaker 1: Direwolf with IBD could be I mean, maybe they were

880
00:41:11,239 --> 00:41:15,680
Speaker 1: essentially the ecosystems that like cold adapted bacteria were thriving in,

881
00:41:16,040 --> 00:41:18,680
Speaker 1: and maybe you've lost those bacteria altogether. Maybe you can't

882
00:41:18,719 --> 00:41:20,160
Speaker 1: bring them back. I don't know, who knows.

883
00:41:20,320 --> 00:41:23,239
Speaker 2: We could end up with like wooly mammoths with horrible diarrhea.

884
00:41:23,320 --> 00:41:27,440
Speaker 1: Oh man, IBD wooly mammoths. That would be a bummer.

885
00:41:28,320 --> 00:41:30,640
Speaker 2: That'd be quite a science achievement, though, wouldn't it.

886
00:41:31,280 --> 00:41:31,959
Speaker 1: Yeah, I guess.

887
00:41:32,000 --> 00:41:36,040
Speaker 2: So, So where do we stand on this progress towards

888
00:41:36,320 --> 00:41:38,960
Speaker 2: creating these diarrhea spraying elephants.

889
00:41:40,440 --> 00:41:43,879
Speaker 1: So they are claiming that in five years they will

890
00:41:43,920 --> 00:41:47,560
Speaker 1: be able to bring a cold adapted Asian elephant into

891
00:41:47,560 --> 00:41:49,800
Speaker 1: the worlds that you could call the colossal wooly mammoth.

892
00:41:50,000 --> 00:41:51,320
Speaker 1: That's a pretty short timeframe.

893
00:41:51,680 --> 00:41:54,120
Speaker 2: How reliable are they with their predictions? Did they predict

894
00:41:54,239 --> 00:41:56,319
Speaker 2: their ability to do the Direwolf or is this sort

895
00:41:56,320 --> 00:41:58,200
Speaker 2: of like Elon Musk like projections.

896
00:41:58,480 --> 00:42:00,439
Speaker 1: I don't know that we have the data to make

897
00:42:00,480 --> 00:42:03,240
Speaker 1: those statements yet, because my sense was that the dire

898
00:42:03,320 --> 00:42:07,160
Speaker 1: Wolf surprised everybody, like they didn't really let folks know

899
00:42:07,280 --> 00:42:08,719
Speaker 1: where they were, and then all of a sudden they

900
00:42:08,760 --> 00:42:10,560
Speaker 1: were like, hey, we've done it. I don't know. This

901
00:42:10,680 --> 00:42:13,759
Speaker 1: sounds like an incredible amount of work. And additionally, you know,

902
00:42:13,880 --> 00:42:15,520
Speaker 1: I don't think they've gotten to the step yet where

903
00:42:15,560 --> 00:42:18,640
Speaker 1: you try to impregnate either of the elephants, and you know,

904
00:42:18,640 --> 00:42:22,200
Speaker 1: if you get halfway through that pregnancy and then it fails,

905
00:42:22,280 --> 00:42:24,480
Speaker 1: you've got another year to wait. And so I think

906
00:42:24,600 --> 00:42:27,160
Speaker 1: it's hard to figure out the timing for that stage

907
00:42:27,160 --> 00:42:29,239
Speaker 1: in particular, Like maybe they have a good handle on

908
00:42:29,239 --> 00:42:31,319
Speaker 1: how long the gene editing takes now, but if it's

909
00:42:31,360 --> 00:42:33,160
Speaker 1: going to take in the elephants or not, I don't

910
00:42:33,200 --> 00:42:35,839
Speaker 1: think we know yet. Fascinating one of the benefits that

911
00:42:35,880 --> 00:42:38,879
Speaker 1: they're touting to this technique is that along the way

912
00:42:39,000 --> 00:42:43,359
Speaker 1: they've done research on elephant endoheliotropic herpes viruses, which are

913
00:42:43,400 --> 00:42:46,160
Speaker 1: a leading cause of death in wild elephants. You'll note

914
00:42:46,239 --> 00:42:50,200
Speaker 1: I can't correctly say prions or prions, but I think

915
00:42:50,280 --> 00:42:54,479
Speaker 1: I got endoheliotropic herpes viruses out. Okay, sounded good, Yeah, great,

916
00:42:54,480 --> 00:42:56,920
Speaker 1: thank you. And so they've been working to understand that

917
00:42:56,960 --> 00:42:59,200
Speaker 1: this is a leading cause of death in wild elephants

918
00:42:59,200 --> 00:43:01,279
Speaker 1: and I think also in zoo populations. And so you know,

919
00:43:01,280 --> 00:43:03,239
Speaker 1: they're arguing that one of the benefits is all of

920
00:43:03,280 --> 00:43:06,120
Speaker 1: this science that comes along on the ride that they

921
00:43:06,120 --> 00:43:09,160
Speaker 1: figure out our moonshot. They say they're about five years away,

922
00:43:09,760 --> 00:43:11,719
Speaker 1: and we're gonna have to wait and see how they do.

923
00:43:11,840 --> 00:43:14,560
Speaker 1: They also have a project in the works on the

924
00:43:14,560 --> 00:43:16,880
Speaker 1: thylacine and another one on the dodo.

925
00:43:17,239 --> 00:43:19,640
Speaker 2: What's the thylacine? That sounds like an amino acid?

926
00:43:19,880 --> 00:43:22,439
Speaker 1: That does sound like an amino acid. Now you're making

927
00:43:22,440 --> 00:43:25,120
Speaker 1: me wonder today. Write the name wrong. It really sounds

928
00:43:25,160 --> 00:43:27,440
Speaker 1: like an amino acid. No, that's actually an animal.

929
00:43:27,520 --> 00:43:28,800
Speaker 2: Oh it's a Tasmanian tiger.

930
00:43:28,920 --> 00:43:31,439
Speaker 1: Yeah, and that only went extinct in nineteen thirty six,

931
00:43:31,719 --> 00:43:34,040
Speaker 1: and so I think we have a fair number of

932
00:43:34,080 --> 00:43:37,000
Speaker 1: specimens that were like stuck in freezers from animals that

933
00:43:37,000 --> 00:43:39,080
Speaker 1: were held in zoos back when we were like, oh wait,

934
00:43:39,120 --> 00:43:40,920
Speaker 1: we should try to turn this all around. Oh we

935
00:43:41,000 --> 00:43:43,919
Speaker 1: waited too long. So yeah, they're working on that. They're

936
00:43:43,920 --> 00:43:47,280
Speaker 1: working on the Dodo, and the Dodo went extinct something

937
00:43:47,320 --> 00:43:50,200
Speaker 1: like three hundred years ago, and so you know, both

938
00:43:50,200 --> 00:43:54,799
Speaker 1: of those projects, the animals are thousands of years less

939
00:43:54,840 --> 00:43:57,759
Speaker 1: dead than the others, but those projects are also in

940
00:43:57,800 --> 00:43:58,480
Speaker 1: the works.

941
00:43:58,360 --> 00:44:01,880
Speaker 2: And those feel like efforts to write some wrong, you know,

942
00:44:01,920 --> 00:44:04,760
Speaker 2: to undo some crime that we committed by like lazily

943
00:44:04,840 --> 00:44:08,400
Speaker 2: or sloppily or greedily or selfishly wiping out some species.

944
00:44:08,480 --> 00:44:11,520
Speaker 1: And you know, I should be clear that Colossal's website

945
00:44:11,600 --> 00:44:15,799
Speaker 1: isn't saying de extinction rights past wrongs. I think what

946
00:44:16,120 --> 00:44:19,080
Speaker 1: they are arguing is that the science is important. I'm

947
00:44:19,120 --> 00:44:20,719
Speaker 1: sure a lot of people go to work every day

948
00:44:20,760 --> 00:44:23,520
Speaker 1: because it sounds awesome to bring back the dire wolf,

949
00:44:23,520 --> 00:44:25,560
Speaker 1: and it's important to be excited about your job, and

950
00:44:25,719 --> 00:44:29,640
Speaker 1: they believe in this, like replacing of ecosystem processes that

951
00:44:29,680 --> 00:44:32,800
Speaker 1: were lost when the organisms went extinct. But I agree

952
00:44:32,840 --> 00:44:35,279
Speaker 1: that does feel to me also like a get out

953
00:44:35,280 --> 00:44:37,160
Speaker 1: a jail free card for the things that we've done

954
00:44:37,160 --> 00:44:37,680
Speaker 1: in the past.

955
00:44:37,960 --> 00:44:40,840
Speaker 2: Then let's revisit one of the Solar System's greatest crimes,

956
00:44:41,160 --> 00:44:44,040
Speaker 2: which is wiping out the dinosaurs sixty five million years ago.

957
00:44:44,360 --> 00:44:47,160
Speaker 2: So Kelly is Colossal going to open Jurassic Park at

958
00:44:47,200 --> 00:44:47,600
Speaker 2: some point.

959
00:44:48,000 --> 00:44:50,720
Speaker 1: So I asked Beth Shapiro this like a decade ago,

960
00:44:50,960 --> 00:44:54,600
Speaker 1: and her answer was no. And I was like, but

961
00:44:54,680 --> 00:45:00,560
Speaker 1: like maybe when the technology advances, and she was like, no, never, never, never,

962
00:45:00,800 --> 00:45:04,560
Speaker 1: why never? And she's like, look, you almost certainly can't

963
00:45:04,640 --> 00:45:07,799
Speaker 1: read DNA sequences that are over a million years old,

964
00:45:08,760 --> 00:45:11,399
Speaker 1: and so we just don't have the DNA to work

965
00:45:11,440 --> 00:45:16,120
Speaker 1: off of from fossils. And so what you could do

966
00:45:16,320 --> 00:45:18,839
Speaker 1: is you could say, all right, I know that this

967
00:45:18,960 --> 00:45:22,600
Speaker 1: gene controls feathers, and this gene controls teeth, and this

968
00:45:22,719 --> 00:45:26,560
Speaker 1: gene controls mouth size, and you could try using what

969
00:45:26,640 --> 00:45:30,920
Speaker 1: you knew and some dinosaur like reference genome to like

970
00:45:30,960 --> 00:45:35,279
Speaker 1: tinker with that and make something dinosaur oid. But she's like,

971
00:45:35,320 --> 00:45:38,600
Speaker 1: you're never gonna bring back t Rex as it was.

972
00:45:38,880 --> 00:45:41,960
Speaker 1: You could bring back some frank and Rex that was

973
00:45:42,000 --> 00:45:42,520
Speaker 1: your best.

974
00:45:42,560 --> 00:45:45,560
Speaker 2: Guess you could bring back t Rex with even stronger

975
00:45:45,680 --> 00:45:48,280
Speaker 2: thighs and diarrhea like the Wooly Mammoth.

976
00:45:48,840 --> 00:45:52,439
Speaker 1: You're really on the thigh thing. I'm guessing you never

977
00:45:52,440 --> 00:45:57,160
Speaker 1: skip thy day, Daniel or leg Day leg Day.

978
00:45:57,800 --> 00:45:59,600
Speaker 2: I think that's too personal a question, Kelly. I'm not

979
00:45:59,600 --> 00:46:00,600
Speaker 2: going to answer that on the pod.

980
00:46:00,719 --> 00:46:01,319
Speaker 1: I'm so sorry.

981
00:46:01,400 --> 00:46:04,239
Speaker 2: Daniel. No, I just want to cheat. I just want

982
00:46:04,239 --> 00:46:06,239
Speaker 2: to borrow the Direwolves DNA so I don't have to

983
00:46:06,239 --> 00:46:06,919
Speaker 2: do leg day.

984
00:46:07,640 --> 00:46:09,799
Speaker 1: No, that'd be great. Just a little crisper in your

985
00:46:09,840 --> 00:46:12,000
Speaker 1: thighs and so that it takes care of it for you.

986
00:46:12,160 --> 00:46:15,399
Speaker 2: Sounds like a menu option now, Daniel's crisper thighs. Would

987
00:46:15,440 --> 00:46:18,640
Speaker 2: you like it with barbecue sauced.

988
00:46:17,640 --> 00:46:21,320
Speaker 1: I know that question is too personal, right, Let's return

989
00:46:21,360 --> 00:46:23,440
Speaker 1: to this observation you made at the beginning of the show.

990
00:46:23,840 --> 00:46:28,000
Speaker 1: It is awesome to bring back, you know, something beautiful

991
00:46:28,000 --> 00:46:30,799
Speaker 1: that existed once and we lost it and now we

992
00:46:30,840 --> 00:46:33,440
Speaker 1: get a chance to interact with it again, and that's amazing.

993
00:46:33,560 --> 00:46:33,719
Speaker 2: Ya.

994
00:46:33,960 --> 00:46:38,400
Speaker 1: Do you still have that sense of wonder with the

995
00:46:38,520 --> 00:46:40,399
Speaker 1: version that we are able to bring back?

996
00:46:40,680 --> 00:46:44,200
Speaker 2: Doesn't feel like traveling to the past or undoing something

997
00:46:44,239 --> 00:46:46,600
Speaker 2: we've done. It feels like a simulation of that or

998
00:46:46,640 --> 00:46:50,440
Speaker 2: an approximation of that doesn't totally scratch that itch, but

999
00:46:50,480 --> 00:46:51,920
Speaker 2: it definitely goes in that direction.

1000
00:46:52,080 --> 00:46:55,239
Speaker 1: Yeah, I think I would go to see the dire

1001
00:46:55,239 --> 00:46:58,560
Speaker 1: wolf exhibit at the Zool for sure, Or maybe i'd

1002
00:46:58,560 --> 00:47:01,239
Speaker 1: go to see a wooly mammoth exhibit at the Zoo

1003
00:47:01,400 --> 00:47:09,600
Speaker 1: where you're ring cook and bring your bleach wipes. There's

1004
00:47:09,680 --> 00:47:13,000
Speaker 1: part of me that feels a little sad thinking about,

1005
00:47:13,080 --> 00:47:15,399
Speaker 1: you know, like if only one wooly mammoth is brought back,

1006
00:47:15,440 --> 00:47:17,680
Speaker 1: because it turns out it was really dangerous for the

1007
00:47:17,680 --> 00:47:21,360
Speaker 1: elephants to go through that childbirthing process, and so we

1008
00:47:21,400 --> 00:47:23,239
Speaker 1: get one wooly mammoth and we decide that's all we're

1009
00:47:23,239 --> 00:47:23,799
Speaker 1: ever going to do.

1010
00:47:24,040 --> 00:47:25,680
Speaker 2: Oh, it's all alone.

1011
00:47:26,080 --> 00:47:29,240
Speaker 1: Something about that feels sad, like we're observing an animal

1012
00:47:29,280 --> 00:47:32,479
Speaker 1: going extinct all over again. And maybe I'm just being

1013
00:47:32,600 --> 00:47:34,719
Speaker 1: like too sentimental, but I don't know, what do you think?

1014
00:47:34,880 --> 00:47:38,080
Speaker 2: No, I think that's an important aspect. You're creating a creature,

1015
00:47:38,080 --> 00:47:40,759
Speaker 2: It has an experience. What have you created? And it's

1016
00:47:40,800 --> 00:47:43,480
Speaker 2: like in great pain because you've created some weird Frankin

1017
00:47:43,560 --> 00:47:45,880
Speaker 2: creature and it doesn't really work or it's miserable for

1018
00:47:45,960 --> 00:47:48,080
Speaker 2: some other reasons. So I think that's definitely something we

1019
00:47:48,080 --> 00:47:51,280
Speaker 2: should consider, especially the more intelligent species. I mean, wolves

1020
00:47:51,320 --> 00:47:54,560
Speaker 2: are smart, right, they're pack animals, they have emotions, they

1021
00:47:54,560 --> 00:47:57,440
Speaker 2: have relationships. Philosophically and morally, there are a lot of

1022
00:47:57,480 --> 00:47:58,160
Speaker 2: questions there.

1023
00:47:58,280 --> 00:48:00,719
Speaker 1: Yeah, Zach asked me, what would I think if we

1024
00:48:00,760 --> 00:48:04,360
Speaker 1: could bring back Neanderthals and try to, you know, figure

1025
00:48:04,360 --> 00:48:06,840
Speaker 1: out what a close human relative was like, you know,

1026
00:48:06,920 --> 00:48:09,840
Speaker 1: are they as intelligent as we are? Were we just

1027
00:48:09,880 --> 00:48:12,319
Speaker 1: more aggressive? And so we managed to like knock them

1028
00:48:12,320 --> 00:48:13,400
Speaker 1: out of the species pool.

1029
00:48:13,520 --> 00:48:13,839
Speaker 5: M hm.

1030
00:48:14,200 --> 00:48:17,759
Speaker 1: I feel like that is quite clearly unethical. But what

1031
00:48:17,840 --> 00:48:19,120
Speaker 1: do you think where is the line?

1032
00:48:19,520 --> 00:48:19,680
Speaker 3: Oh?

1033
00:48:19,880 --> 00:48:22,399
Speaker 2: Wow, that is a thorny question. Yeah. I mean even

1034
00:48:22,480 --> 00:48:25,120
Speaker 2: just like editing your own babies he's in crisper, is

1035
00:48:25,160 --> 00:48:28,840
Speaker 2: pretty unethical. But I feel like philosophically it's kind of fuzzy.

1036
00:48:28,880 --> 00:48:31,600
Speaker 2: I mean, you choose your mate. Also, that affects the

1037
00:48:31,680 --> 00:48:33,960
Speaker 2: DNA of your kids. You have some influence over it,

1038
00:48:34,160 --> 00:48:36,239
Speaker 2: but it's weird to edit it directly. I don't know

1039
00:48:36,320 --> 00:48:39,120
Speaker 2: exactly where that line is or why there's the line there.

1040
00:48:39,320 --> 00:48:41,480
Speaker 2: There's lots of things we do. Like I created children,

1041
00:48:41,520 --> 00:48:43,520
Speaker 2: brought them into this world. They didn't get to choose

1042
00:48:43,560 --> 00:48:46,560
Speaker 2: it at all. Maybe they're happy, maybe they're miserable. You know,

1043
00:48:46,600 --> 00:48:49,200
Speaker 2: it's sort of on me. I feel like having intelligent

1044
00:48:49,280 --> 00:48:53,399
Speaker 2: babies is already a philosophical quandary.

1045
00:48:54,000 --> 00:48:57,840
Speaker 1: Yeah, fair enough. Then bringing Neanderthals would be yeah, complicated too,

1046
00:48:57,920 --> 00:49:01,240
Speaker 1: because they're like a scientific creation. To be clear, Colossal

1047
00:49:01,239 --> 00:49:03,720
Speaker 1: has no plans to bring back the Neanderthals.

1048
00:49:03,120 --> 00:49:04,000
Speaker 2: That they've made public.

1049
00:49:04,960 --> 00:49:09,879
Speaker 1: Don't start trouble, don't start trouble. So let's say Gigantic

1050
00:49:09,960 --> 00:49:13,560
Speaker 1: Evil the corporation decides they're going to bring back Neanderthals,

1051
00:49:13,680 --> 00:49:16,440
Speaker 1: and they bring back two of them, and it turns

1052
00:49:16,440 --> 00:49:19,440
Speaker 1: out those two need a lot of support. Yeah, and

1053
00:49:19,440 --> 00:49:22,719
Speaker 1: then Big Evil goes out of business. What happens to

1054
00:49:22,760 --> 00:49:25,960
Speaker 1: those Neanderthals who would be responsible for them? Would they

1055
00:49:25,960 --> 00:49:29,600
Speaker 1: be happy in this world where they're the only two

1056
00:49:29,760 --> 00:49:31,520
Speaker 1: representatives of a different species?

1057
00:49:31,920 --> 00:49:34,400
Speaker 2: Sounds like a great Black Mirror episode. You should write.

1058
00:49:34,160 --> 00:49:35,799
Speaker 1: There, you go. Well, if somebody wants to pay me

1059
00:49:35,880 --> 00:49:38,799
Speaker 1: to write that, I am ready. I will always take

1060
00:49:38,840 --> 00:49:39,280
Speaker 1: your money.

1061
00:49:39,320 --> 00:49:42,400
Speaker 2: All right, Netflix, right to us. Two questions at Danielantlly.

1062
00:49:43,920 --> 00:49:47,960
Speaker 1: As you can see, we have loads of ideas. All right. Well,

1063
00:49:48,000 --> 00:49:50,719
Speaker 1: on that sort of dark note, that's all I have

1064
00:49:50,760 --> 00:49:52,759
Speaker 1: to say about the extinction today. I think I just

1065
00:49:52,800 --> 00:49:55,120
Speaker 1: like to bottom line by saying I am still excited

1066
00:49:55,160 --> 00:49:57,840
Speaker 1: about this. I think it's cool. I think they have

1067
00:49:57,960 --> 00:50:01,480
Speaker 1: made some interesting breakthroughs. I just have complicated feelings about

1068
00:50:01,520 --> 00:50:03,160
Speaker 1: the extinction in general, what about you.

1069
00:50:03,440 --> 00:50:05,560
Speaker 2: I think it also tells us something about the science

1070
00:50:05,600 --> 00:50:09,920
Speaker 2: communication universe. This is an impressive step forward technologically and

1071
00:50:10,080 --> 00:50:13,520
Speaker 2: fascinating scientifically, but it was over sold in the press

1072
00:50:13,520 --> 00:50:15,560
Speaker 2: a little bit, and now there's like this back reaction

1073
00:50:15,760 --> 00:50:18,440
Speaker 2: against it, and I think, you know, the whole science

1074
00:50:18,440 --> 00:50:22,279
Speaker 2: communication ecosystem encourages people to over sell every time you

1075
00:50:22,360 --> 00:50:25,880
Speaker 2: step forward as a revolutionary advance, which means that the

1076
00:50:25,920 --> 00:50:28,440
Speaker 2: folks out there don't really know what they're reading. Is

1077
00:50:28,440 --> 00:50:31,880
Speaker 2: this just overblown hype or not? And so there's a

1078
00:50:31,920 --> 00:50:34,319
Speaker 2: lot of sort of cynicism out there, and you can

1079
00:50:34,360 --> 00:50:36,440
Speaker 2: see that in people's responses to the questions. And we

1080
00:50:36,560 --> 00:50:38,359
Speaker 2: got a lot of emails, and I get emails all

1081
00:50:38,400 --> 00:50:40,759
Speaker 2: the time about science headlines, people like is this real?

1082
00:50:40,880 --> 00:50:43,560
Speaker 2: Daniel did now so really discovered thirty seven extra dimensions. No,

1083
00:50:43,840 --> 00:50:46,560
Speaker 2: they didn't. So you've got to become like a critical

1084
00:50:46,600 --> 00:50:50,640
Speaker 2: thinker and an educated consumer of this science news.

1085
00:50:50,800 --> 00:50:51,000
Speaker 5: Yeah.

1086
00:50:51,040 --> 00:50:53,239
Speaker 1: I think that's a great point, And I think conveying

1087
00:50:53,560 --> 00:50:56,920
Speaker 1: exactly what was done is a little bit more complicated

1088
00:50:56,960 --> 00:51:00,279
Speaker 1: and requires an attention span from the reader to like

1089
00:51:00,400 --> 00:51:03,080
Speaker 1: get through the entire description. But I think that if

1090
00:51:03,120 --> 00:51:06,880
Speaker 1: you fail in that goal, then you lose trust with

1091
00:51:06,960 --> 00:51:10,960
Speaker 1: your audience, and that has massive implications for any kind

1092
00:51:11,000 --> 00:51:14,200
Speaker 1: of science you're trying to communicating, like vaccines and stuff,

1093
00:51:14,239 --> 00:51:15,879
Speaker 1: for example. So I think you've got to be really

1094
00:51:15,880 --> 00:51:17,200
Speaker 1: careful about how you do this stuff.

1095
00:51:17,320 --> 00:51:19,480
Speaker 2: Big problem that we're not going to solve today on

1096
00:51:19,560 --> 00:51:21,800
Speaker 2: the pod. But thanks everybody for listening to our effort

1097
00:51:21,920 --> 00:51:24,920
Speaker 2: to communicate real science in a credible way to you,

1098
00:51:25,000 --> 00:51:27,320
Speaker 2: because we know you're interested in learning more and digging

1099
00:51:27,360 --> 00:51:30,520
Speaker 2: deeper beyond what's covered in the popsie articles, and that's

1100
00:51:30,520 --> 00:51:32,239
Speaker 2: what we try to bring you here on the pod.

1101
00:51:32,440 --> 00:51:33,600
Speaker 2: Thanks everyone for listening.

1102
00:51:33,920 --> 00:51:44,000
Speaker 1: Thank you so much. Daniel and Kelly's Extraordinary Universe is

1103
00:51:44,040 --> 00:51:47,080
Speaker 1: produced by iHeartRadio. We would love to hear from you,

1104
00:51:47,239 --> 00:51:48,200
Speaker 1: we really would.

1105
00:51:48,360 --> 00:51:51,120
Speaker 2: We want to know what questions you have about this

1106
00:51:51,320 --> 00:51:53,000
Speaker 2: extraordinary universe.

1107
00:51:53,120 --> 00:51:56,080
Speaker 1: We want to know your thoughts on recent shows, suggestions

1108
00:51:56,080 --> 00:51:59,080
Speaker 1: for future shows. If you contact us, we will get

1109
00:51:59,120 --> 00:51:59,480
Speaker 1: back to.

1110
00:51:59,440 --> 00:52:03,239
Speaker 2: You really mean it. We answer every message. Email us

1111
00:52:03,280 --> 00:52:06,120
Speaker 2: at Questions at Danielandkelly dot.

1112
00:52:05,920 --> 00:52:07,799
Speaker 1: Org, or you can find us on social media. We

1113
00:52:07,840 --> 00:52:11,719
Speaker 1: have accounts on x, Instagram, Blue Sky and on all

1114
00:52:11,760 --> 00:52:14,080
Speaker 1: of those platforms. You can find us at D and

1115
00:52:14,480 --> 00:52:15,480
Speaker 1: K Universe.

1116
00:52:15,600 --> 00:52:17,160
Speaker 2: Don't be shy, write to us