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David, I'm always amazed that at the end of the day, despite all of our technology,

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everything we're doing with speakers and electronics is still just magnets and copper

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wires.

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It's pretty remarkable when you think about all the intricate interactions and subtle

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divisions of labor that went into this thing that that you, the listener, are hearing in

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your ears right now.

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Um it's pretty mind blowing.

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Yeah, I just I think it's worth just pausing for a moment to appreciate that.

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Yeah, maybe we should have like a prayer, a meditative uh

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silence, yeah.

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Um but but during this silence, we can just reflect on the fact that this is a podcast.

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Yes.

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Um, and it's uh co-hosted by me, David Pinsoff, and uh my co-host Dave

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Petrozki.

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You said that like that might not be me, but it is me, right?

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That that would be you.

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I mean, unless there's another person named Dave Petrozowski who's been um showing up.

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There's only a couple of us.

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If you do a search, there's only a couple.

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There's no not many.

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So I think there's like five in the US.

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One of them, though, uh does GPS research.

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And so occasionally I get a graduate student application for somebody who's like interested

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in GPS technology on buoys in the Navy or something.

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And I I have to politely forward it along to the other David J.

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P.

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Trazewski, in fact.

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Yeah, I ironically, a person got lost looking for the GPS researcher.

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Yeah, exactly.

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First, first hoop not jumped through.

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Yeah.

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David, are there other David Pence offs?

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Uh not to my knowledge.

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It's a pretty rare last name, actually.

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Yeah.

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So is this all going in the intro?

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Is this going to be but are we eventually going to get to the title of the

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podcast?

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Uh what is the title?

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Uh it's Evolutionary Psychology the podcast.

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Yeah.

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Oh wait, we forgot to say actual evolutionary psychology by actual evolutionary

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psychologists.

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David, many times we have people on who do psychology

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or anthropology, um, but we're wading into new territory here with uh somebody

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who does work on the microbiome.

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Yeah.

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Um, it is the coolest, hottest topic in science now, if I could share that

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opinion.

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Do you agree?

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I feel like it's really an interesting topic.

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I have people are just uh I I have no idea what is the hottest topic in science

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other than artificial intelligence, which I think is.

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Well, yeah, that's a big one.

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But um I feel like I see microbiome stuff all the time.

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You know, uh probiotics.

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I feel like I see the stuff on on TikTok.

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The kids are talking about the microbiome.

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Are they?

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Yeah.

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Okay.

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Uh yeah.

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Well, you're in LA.

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We're in sleepy Santa Barbara, so we don't, yeah, we're like 10 years behind.

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Um I think this is the episode that uh sometimes people say, I wish the

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episodes had more practical advice for my everyday life.

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And if you want practical everyday advice for your life, I think this is the episode for

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you.

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Yeah, there's there's some really good practical advice.

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And also it's just a mind-blowing uh tour of what the microbiome

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is.

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Uh All the different details and facets of it.

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Like I found it absolutely fascinating.

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I feel like I learned so much listening to this.

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Um, I actually grocery shop differently, even though so I had seen so this is uh

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Katrina Weitzen, and she is um um at UC Irvine, and she

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gave a talk at the John Patton uh Memorial Symposium, and it just blew my mind.

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And so I wanted to invite her on the podcast and uh the work she's doing on the microbiome.

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She's like one of five labs doing this kind of work.

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It's incredible, cutting edge science with immediate real world implications.

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And again, it's coming from an evolutionary perspective, thinking about the ways in which

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our diet might be mismatched from the way that we're designed.

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Yeah.

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It's just incredibly mind expanding to think about the whole ecosystem of

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microbes that's living inside of you and how they've evolved symbiotically with us.

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And you know, we get into how you can often trace um the the genetics of a human better by

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looking at their microbiome than by looking at the human uh themselves and their DNA.

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Um uh it's just really fascinating stuff.

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Um, I think you'll really enjoy this one.

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Yeah.

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So uh enjoy along with your very, very large number of uh microbiomes that

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are also along for the ride as you listen to this episode.

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Yep.

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Enjoy.

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All right.

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Um, so today we have Katrina.

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Um, is it Whiteson?

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Is that Whiteson?

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Yeah.

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Whiteson.

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Um, I met you at John Patton's memorial seminar.

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Um, and I was just before we started recording, I was saying how just incredible um

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your talk was, and we got a chance to talk, and I think completely differently about

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which sounds like a boring thing, fiber.

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But but you study microbiome, you study your incredible, um just incredible research,

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and we want to get into it.

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But I want to start by asking the uh maybe as a lead-in to um John Patton.

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So you were can you talk us through how did you get involved working with John Patton?

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And what what is somebody who's studying microbiomes doing talking to John Patton.

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And how did you guys meet, or how did you start working together?

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What did you do?

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Great story and a great question.

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So when I so I started a lab at UCI in 2014, and I think I met John Patton within a couple

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years of that time.

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Um, right around the time I started my lab, uh the uh we recruited this um famous

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salivary scientist named Douglas Granger, and he started the salivary biosciences

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institute here.

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Wow, a salivary scientist.

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I was not even aware that such a field existed.

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And I'm there, I'm sure that uh Professor Granger has many titles beyond Salivary

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Scientist.

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Um, but he had a big research.

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I'm drooling to learn more about that.

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Salivating at the thought.

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Yeah.

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Yeah.

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In fact, they would do these workshops, and then you you'd get a mug that said something

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about saliva in really big letters, and then Eclastad is like drinking coffee out of this

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mug that says saliva on it.

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I can't imagine like the titles of papers in that literature.

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It just gotta be so funny.

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It's just like rife for a lot of spit ticks.

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Oh my gosh.

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So so John Patton um knew somehow was connected with Douglas Granger.

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I don't exactly know how they uh got to know each other, but um, but Douglas Granger, who

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was here ECI, facilitated my introduction to John Patton.

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And I remember we all met together, and John shared his story of the people he was working

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with in Ecuador and just the possibility that we could study the microbes living in the

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saliva samples, which then we extended to chicha, of course, and even to chica.

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What is what is chicha just for preparing?

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I don't think we've talked about I I don't know if we've talked about chicha.

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Uh yeah.

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I've heard some stories from Clark about chicha that were that were very fun, but it's

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worth um yeah worth repeating yeah yeah definitely.

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Um so chicha is a fermented beverage that people in Ecuador and other parts

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of South America make.

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And I mean, they really subsist on this bev on this fermented beverage, which is made by

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having the women of the household chew on um starchy root vegetables like yucca,

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and they chew the vegetable and then spit it into a vat, and it's like a communal activity,

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and then they let the vat ferment for a couple of days, and it gets to have mild

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alcohol content like a kombucha or a light beer.

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But the amazing thing about it is that people get something like 2,500 or 3,000 calories

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a day from drinking chicha.

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And it's it's like a water purification method, too.

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People really depend on it.

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Like when a hunting party goes on a trip for a few days, if they run out of chicha,

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everyone has this feeling of impending doom, like we're gonna die.

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And maybe they're right.

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If they drink water, they could get diarrheal illness.

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Like there's so many reasons why it's so important.

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Um, and anyhow, it's it's uh it's a fermented beverage that's really important to the food

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culture in Ecuador and nearby parts of the world.

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Amazing.

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So it's like a source of hydration.

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Uh yeah.

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Approximately.

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Sorry, sorry, David.

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Go ahead.

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Just out of curiosity, uh, what does it taste like?

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I for all the times I've spoken about it, I actually haven't tried it.

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I didn't go to Ecuador with John Patton.

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So I've just heard about it.

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I really should go.

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And yeah, that would be a good idea to go.

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I do personally brew kombucha at home, which I know is not the same thing, but you know.

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Um I do remember uh trying something that was advertised as chicha.

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I doubted it as the authentic thing.

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So I was in Nicaragua with my wife for our honeymoon at a resort, and they had something on

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the menu called Chicha.

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I doubt it's very similar to the one that um is actually made in these local communities.

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But um from what I remember, it was just kind of like really sour, kind of tasted like a

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sour beer.

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Yeah, I think it basically a sour beer is a great way to put it.

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And um actually Doghead Brewery, they made a single batch of chicha a few years

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ago that my grad student who worked on this project, he was really into brewing beer, and

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he I know he was really into that, but I didn't get to try it myself.

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Cool.

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So uh so John Patton, so we you the uh we cut you off, sorry.

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Yeah, we cut you off into the city.

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Too many exciting things to yeah.

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Well, I mean, there's a there's a lot to say, and you guys know John Patton was a talker,

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right?

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So I mean I've got I've absorbed a lot of his stories, even though I didn't go down there

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myself.

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I got to learn so much about it, you know.

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Yeah.

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So but what so for people who don't know, so I think like people know that, like, you know,

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John Patton was in Kanambo and we talked, we have talked to Brun Bowser about sort of what

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life is like there.

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Um, what what are you why?

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So we talked about saliva.

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What are you interested in?

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What did you and John realize you could do together that hadn't been done before?

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What were you guys doing?

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Yeah, great question.

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So um, you know, the people who live in Canambo are living in a there, it's a

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riverside community in Ecuador.

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There's no roads to cities.

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The people who live there, there's they subsist on chicha and whatever they can grow in

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their kitchen gardens and whatever they can hunt.

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Um so they are not eating processed food.

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So we live in a world where most of the industrialized world is consuming something like

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70% of our calories are processed foods.

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They can't just like go to the vending machine and buy a Coke and so forth.

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And so John had been studying or, you know, working in Canambo since the 90s.

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And I think his initial draw there was because the community there has a very high homicide

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rate.

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So it started from a more anthropology perspective in that sense.

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But in the meantime, he was the one providing vaccines and antibiotics to this community

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because they really were quite remote.

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And I and I've talked to Brenda about that a lot too.

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I mean, I don't think it's that nobody had ever eaten any processed food.

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I think that does happen occasionally, but it's not a regular thing.

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And so that fascinated me because I'm very interested in understanding the human history of

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the microbes that colonize our bodies.

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And so we know that in the last century that has changed dramatically.

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And it's not just from one thing, but a combination of things like antibiotics and smaller

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family sizes and sanitation.

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And this really big one about the food we eat being so different.

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The way most of our food is processed, the fiber, the complex carbs that are hard to break

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down are often removed.

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And so as a result, our microbiomes have just shifted really, really dramatically.

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And it's connected to all these other diseases.

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So I mean, on the one hand, it's we've avoided infectious disease and our lifespans have

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increased.

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So that is worth celebrating.

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And actually, we don't appreciate it enough.

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I'm not sure if we think about that so much.

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But I mean, because of vaccination and antibiotics and these other measures, you know,

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lifespan has expanded incredibly.

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Children in the West and the industrialized world rarely die of diarrheal illness.

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Um, so that's obviously really good.

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But the other side of that coin is that we are now pro more prone to autoimmune diseases,

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allergies.

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And there's even more health conditions that we're starting to understand could actually be

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quite connected to our microbiomes, like some cancer types, like why are so many young

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people getting colon cancer?

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Like even Parkinson's disease and potentially Alzheimer's disease and other

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neurodegenerative diseases could be connected.

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So understanding you know what what things looked like in human history is

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really important.

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And from talking to John uh Patton I learned that the people in Canombo don't get

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acne and they don't get eczema and they, you know, their skin is perfect, and

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um, and they don't have a lot of these other allergy and autoimmune diseases that are

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becoming more common in our part of the world.

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So getting to understand um what the microbiomes look like in that community is really

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valuable, especially as it's changing so quickly.

258
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I'm certainly not the only person who's thinking about that though.

259
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There's actually a really cool global movement to try to preserve the microbes of human

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history.

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For example, there's a group called the Global Microbiome Conservancy.

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And they've even been trying to build a vault where they store samples from all different

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human communities.

264
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Um, it might be somewhere in Switzerland, and they're going to try to like save these

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samples.

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And the people who are part of the communities are partners in all of this research.

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So they've done a really good job of, or they're trying to do a good job of making it so

268
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that the science and the technology is being shared throughout the whole process.

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Wow.

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So that was the initial interest with John Patton.

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And he clearly had thought about it a lot himself, actually.

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He had a lot of really good ideas.

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And he was really interested in weaning the children there with breastfeed for a

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couple of years.

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And he was really interested in understanding how eating chicha, because also infants like

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toddlers were eating chicha from a pretty early age.

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So he was really interested in knowing like how the moment of weaning and getting chicha

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microbes into the system would affect health.

279
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Um and so actually in our study we ended up focusing on the women and children in Canambo.

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And hind to be honest, years later we were like, why didn't we just collect the samples

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from the men also?

282
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But I think it also would have been harder.

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It was part of the thinking that the women and children were uh the the master's students

284
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that John brought down with him were working really closely with them.

285
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So it was an easier set of samples to collect, I think.

286
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Yeah.

287
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amazing.

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I mean, I there's so many questions, and I'm such an amateur, and I think other people are

289
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amateurs listening too.

290
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So stupid, stupid questions.

291
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So one is where is the microbiome?

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And I think people have an have like a I have a cartoonish view, which is sort of what I

293
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learned in high school biology was we digest food.

294
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Um, it's sort of what our body does in absorbing nutrients.

295
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There was very little, at least when I was in school, talking about these uh other

296
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bacteria, or maybe there's like bacteria in the gut and they sort of help us digest our

297
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food.

298
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That's about the extent I know.

299
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So how is it that there's this whole you alluded to the importance of the microbiome, but

300
00:16:02,850 --> 00:16:07,090
please disabuse me of the notion that it's simple and insignificant.

301
00:16:07,250 --> 00:16:10,140
Um, you know, like what what is the microbiome?

302
00:16:10,300 --> 00:16:10,700
Where is it?

303
00:16:10,780 --> 00:16:11,580
How do you see it?

304
00:16:11,740 --> 00:16:12,380
How do you present it?

305
00:16:12,620 --> 00:16:13,580
Yeah, great question.

306
00:16:14,460 --> 00:16:16,300
That's a really important place to start.

307
00:16:16,460 --> 00:16:22,220
So, I mean, first of all, a microbiome is a community of microbes that live in a particular

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environment.

309
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So nothing is sterile, despite what you might read in medical textbooks about, you know,

310
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the lungs or urine or eyes being sterile.

311
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Nothing is sterile.

312
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There are microbes everywhere.

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And they're just really good at living in all environments.

314
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They were here, you know, for billions of years before we were.

315
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And they're really good at living in every condition.

316
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No oxygen, no problem.

317
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They've got like a metabolic solution for that, you know?

318
00:16:47,090 --> 00:16:49,090
So you have microbes everywhere.

319
00:16:49,250 --> 00:16:54,370
But what makes a pile of microbes different from a microbiome is that a microbiome is a

320
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community of specific microbes that can thrive in a particular environment.

321
00:16:58,690 --> 00:17:04,420
So the moist part of the inside of your elbow has a different microbiome than the dry skin

322
00:17:04,420 --> 00:17:08,180
on the front of your forearm because the environment is different.

323
00:17:08,260 --> 00:17:12,100
So different types of microbes are able to grow in those communities.

324
00:17:12,340 --> 00:17:16,180
And it's there's all it's not just about whether the microbes can get there.

325
00:17:16,420 --> 00:17:20,740
You know, you could imagine that dispersal is never a limitation for microbes because

326
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they're little and they can just fly along on the clouds or something, which is actually

327
00:17:24,180 --> 00:17:24,500
true.

328
00:17:24,660 --> 00:17:27,220
But um, but they don't just get everywhere.

329
00:17:27,380 --> 00:17:29,570
So dispersal is a limitation.

330
00:17:29,730 --> 00:17:34,930
In fact, why don't we have the microbes that our human ancestors have anymore?

331
00:17:35,170 --> 00:17:38,450
Well, that's because they're not we're not being exposed to them anymore.

332
00:17:38,530 --> 00:17:40,930
So it's not just like everything is everywhere.

333
00:17:41,650 --> 00:17:46,850
Um but uh but anyway so a microbiome is the community of microbes living in a

334
00:17:46,850 --> 00:17:52,740
particular environment and um our gut is the most dense place

335
00:17:53,060 --> 00:17:58,180
where most of the microbes in our bodies live, but we do have microbiomes in our oral

336
00:17:58,180 --> 00:18:01,220
cavity, in our, you know, there's nowhere that's sterile.

337
00:18:01,380 --> 00:18:06,260
Um, and so different microbial communities are useful indicators of health, and we are

338
00:18:06,260 --> 00:18:10,420
hopefully going to be better at manipulating them to improve our health in the near future.

339
00:18:10,580 --> 00:18:15,890
I mean, I could definitely imagine a future where, like vaccination, we ensure that

340
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children have certain microbes at certain points in development.

341
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And maybe that's going to really help us avoid some of the autoimmune diseases that are

342
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becoming more and more common.

343
00:18:26,770 --> 00:18:29,810
But those are still still research questions for sure.

344
00:18:30,290 --> 00:18:33,010
But as far as the gut goes, I mean, it's like a whole organ.

345
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You've got some, you know, it's akin to the size of your brain worth of microbes living in

346
00:18:38,700 --> 00:18:39,340
your gut.

347
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And microbes have really creative metabolisms.

348
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So, like you throw a new food substance in there, there's probably going to be a microbe in

349
00:18:47,580 --> 00:18:50,540
there that contains the right enzymes to break it down.

350
00:18:50,780 --> 00:18:52,940
And so we were mentioning fiber.

351
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When you eat fiber, which is carbohydrates that are slow to break down.

352
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So when you eat them, they don't get absorbed quickly.

353
00:19:00,060 --> 00:19:02,780
Like you eat white rice, it's gone in 30 minutes.

354
00:19:02,940 --> 00:19:08,510
You eat beans or another food that has a lot of fiber in it, the fibrous part of the

355
00:19:08,510 --> 00:19:14,030
carbs will persist in your digestion down to your colon where most of the microbes live.

356
00:19:14,190 --> 00:19:20,190
And then they'll be able to produ like when microbes get contact with those fibers,

357
00:19:20,430 --> 00:19:25,710
they produce really healthy molecular byproducts that are important for your immune system

358
00:19:25,710 --> 00:19:26,830
and your colon.

359
00:19:27,780 --> 00:19:28,180
Amazing.

360
00:19:28,500 --> 00:19:28,900
Fascinating.

361
00:19:29,140 --> 00:19:35,060
Uh am I am I correct that um our odors uh are also related to our

362
00:19:35,060 --> 00:19:35,780
microbiome?

363
00:19:36,020 --> 00:19:41,220
And that, you know, when we sweat, like say in our armpits, um, the bacteria that will grow

364
00:19:41,220 --> 00:19:46,820
and feed on that sweat will emit various gases, and that is in fact responsible for for the

365
00:19:46,820 --> 00:19:49,460
smell uh more than say the sweat itself.

366
00:19:50,170 --> 00:19:50,890
A hundred percent.

367
00:19:50,970 --> 00:19:52,330
Yeah, that is definitely true.

368
00:19:52,490 --> 00:19:57,770
So you have an armpit microbiome, and um, and some people

369
00:19:57,930 --> 00:20:03,930
develop microbes that produce more volatile compounds that have strong odors.

370
00:20:04,250 --> 00:20:08,170
And so that is definitely uh microbiome related.

371
00:20:08,250 --> 00:20:11,290
And in fact, there's a Belgian scientist who goes by Dr.

372
00:20:11,450 --> 00:20:16,810
Armpit and he has done a study where he did an

373
00:20:16,810 --> 00:20:22,740
armpit um transplantation where he he he got twins where one twin

374
00:20:22,740 --> 00:20:27,940
had trouble with BO and the other one didn't and he did an armpit transplant and it it

375
00:20:27,940 --> 00:20:31,780
involved the my skin microbes actually don't live just right on the surface they actually

376
00:20:31,780 --> 00:20:36,660
live like in the top millimeter of your skin so you kind of have to rough the skin up a bit

377
00:20:36,740 --> 00:20:42,660
but he did that and he um took microbes from the nice smelling twin and

378
00:20:42,660 --> 00:20:48,550
transplanted them to the one who was having trouble with BO and it was pretty successful

379
00:20:48,630 --> 00:20:49,590
is my understanding.

380
00:20:50,310 --> 00:20:50,790
Interesting.

381
00:20:51,110 --> 00:20:55,830
Uh and and certainly, you know, uh psychologically we we find the smell of body odor to be

382
00:20:55,830 --> 00:20:58,070
quite revolting um and disgusting.

383
00:20:58,230 --> 00:21:03,830
Um presumably that is because we are uh sensing a pathogen risk that these are

384
00:21:03,830 --> 00:21:06,550
rival bacteria that could potentially infect us.

385
00:21:06,630 --> 00:21:09,270
Do does that sound plausible or or wh what's going on there?

386
00:21:09,830 --> 00:21:13,910
That might be the case, but it's those the microbes that are causing those smells are

387
00:21:13,910 --> 00:21:16,140
usually not terrible pathogens or anything.

388
00:21:16,220 --> 00:21:20,700
I mean, a lot of the really healthy microbes, like the gut anaerobes producing those

389
00:21:20,700 --> 00:21:25,020
fibers, the smells, we also smell them every time we fart, right?

390
00:21:25,180 --> 00:21:29,100
And those smells are not good, but they're definitely health associated.

391
00:21:29,580 --> 00:21:31,420
So that's a really good question.

392
00:21:31,580 --> 00:21:33,020
I don't fully understand that.

393
00:21:33,180 --> 00:21:38,780
Um yeah, because BO smells tend to come from pretty healthy microbes.

394
00:21:38,940 --> 00:21:43,570
They're not really um pathogens you would need to avoid from my perspective.

395
00:21:43,890 --> 00:21:44,050
Yeah.

396
00:21:44,210 --> 00:21:47,890
So it sounds like there's been like there's like almost like in the way that germ theory

397
00:21:47,890 --> 00:21:52,050
happened, and before that, everyone was sort of blind to like the microscopic world.

398
00:21:52,130 --> 00:21:56,210
It almost I hear what you're saying is like there's like microbiome blindness in the sense

399
00:21:56,210 --> 00:22:02,050
of both the evolved psychology or or our evolved phenotype is designed around the

400
00:22:02,050 --> 00:22:06,050
fact that these microbiomes are recurrent part of our evolutionary history.

401
00:22:06,210 --> 00:22:11,760
But then also scientifically, in the same way, if you don't understand germ theory, then

402
00:22:11,760 --> 00:22:15,440
you're just like, yeah, let's just, you know, throw the do gross stuff, right?

403
00:22:15,520 --> 00:22:16,640
Because we don't know about germs.

404
00:22:16,800 --> 00:22:22,080
If we don't know about microbiomes in the modern environment, or we're not appreciating how

405
00:22:22,080 --> 00:22:26,960
they work or how our evolved biology interacts with them, then yeah, we might be doing all

406
00:22:26,960 --> 00:22:29,680
kinds of things that are quite bad for the microbiome.

407
00:22:29,760 --> 00:22:34,080
And it sounds like what you're saying is that by understanding the microbiome, there's a

408
00:22:34,080 --> 00:22:39,810
new slice of the world that's interventions, that's preventative, that's like

409
00:22:39,810 --> 00:22:43,730
healing people or preventing diseases or helping with health.

410
00:22:43,890 --> 00:22:45,890
Um, yeah, that's that's that's yeah.

411
00:22:45,970 --> 00:22:46,770
I mean a hundred percent.

412
00:22:46,850 --> 00:22:52,450
I mean, think about the era when we discovered antibiotics, it was like 1940s, it made a

413
00:22:52,450 --> 00:22:53,330
huge impact.

414
00:22:53,490 --> 00:22:58,930
So many World War II infections were had a better and different outcome than they would

415
00:22:58,930 --> 00:23:01,330
have if we hadn't made that discovery at that time.

416
00:23:01,620 --> 00:23:05,780
And we were so exuberant about antibiotics that we were just throwing them everywhere.

417
00:23:05,860 --> 00:23:09,700
I mean, we did the same thing with x-rays, really, actually, you know, like using them to

418
00:23:09,700 --> 00:23:10,740
measure shoe size.

419
00:23:11,220 --> 00:23:12,100
Oh my god, really?

420
00:23:12,260 --> 00:23:13,140
I didn't know about that.

421
00:23:13,300 --> 00:23:13,460
Yeah.

422
00:23:15,620 --> 00:23:20,100
If you went to like a really chic shoe store, they would x-ray your foot to get the size

423
00:23:20,180 --> 00:23:22,580
and like get the right shoe on there, you know.

424
00:23:22,870 --> 00:23:26,070
And uh anyway, so with antibiotics, kind of same thing.

425
00:23:26,150 --> 00:23:30,870
You're like anything that happened, you were given antibiotics, and we weren't thinking

426
00:23:30,870 --> 00:23:36,310
about the downside of hurting the microbiome because it wasn't even appreciated really.

427
00:23:36,710 --> 00:23:42,390
Um and so that I think we're better about now, although we still in the US use about 80% of

428
00:23:42,390 --> 00:23:43,910
our antibiotics for agriculture.

429
00:23:44,070 --> 00:23:48,150
So all of this careful vetting that we're doing, which we should do, of not giving people

430
00:23:48,150 --> 00:23:52,820
antibiotics for viral infections where they won't help and so on, will We'll only go so far

431
00:23:52,820 --> 00:23:56,020
unless we also change our agricultural policies.

432
00:23:56,820 --> 00:24:00,900
The agricultural thing is that uh I don't know much about that.

433
00:24:00,980 --> 00:24:01,780
Do you know more?

434
00:24:01,940 --> 00:24:07,620
Like is it is it preventative or yeah it's um it's prophylactic

435
00:24:07,700 --> 00:24:12,260
that antibiotics are often given because it helps farm animals grow more quickly.

436
00:24:12,500 --> 00:24:18,310
So pigs, cows, and chickens all will grow more quickly if they're given antibiotics,

437
00:24:18,470 --> 00:24:22,710
which is a pretty interesting experiment when you think about how we're also giving a lot

438
00:24:22,710 --> 00:24:24,310
of antibiotics to people.

439
00:24:24,470 --> 00:24:29,750
So maybe we're unintentionally fueling the obesity crisis with antibiotics.

440
00:24:30,070 --> 00:24:33,750
There's a lot of science questions there still that we don't know the answer to.

441
00:24:33,990 --> 00:24:39,320
There's multiple hypotheses about why farm animals grow more quickly when you give them

442
00:24:39,320 --> 00:24:40,120
antibiotics.

443
00:24:40,200 --> 00:24:44,840
And it's pretty interesting because it's true across vertebrates like cows, pigs, even

444
00:24:44,840 --> 00:24:45,480
birds.

445
00:24:45,880 --> 00:24:51,480
Um and a major hypothesis is that you put less energy into fighting infections when you

446
00:24:51,480 --> 00:24:53,160
have antibiotics on board.

447
00:24:53,720 --> 00:24:57,000
Um so that actually is pretty plausible.

448
00:24:57,160 --> 00:25:02,600
Um but there's other changes you could be making to your microbiome that could be changing

449
00:25:02,600 --> 00:25:04,280
how you process energy.

450
00:25:04,470 --> 00:25:05,430
yeah as well.

451
00:25:05,830 --> 00:25:09,750
One thing that I noticed, so we'll keep going on the John Patton story, but I want to

452
00:25:09,750 --> 00:25:14,310
interrupt it for a second because I realized from your talk that I didn't even know what

453
00:25:14,310 --> 00:25:15,270
fiber was.

454
00:25:15,830 --> 00:25:21,750
So you you explained that like fiber is like creaminess and avocado and lentils.

455
00:25:21,830 --> 00:25:22,710
It's not roughage.

456
00:25:22,870 --> 00:25:26,870
I had thought that roughage, like I think of like lettuce as fiber.

457
00:25:27,030 --> 00:25:28,470
Can you disabuse everyone?

458
00:25:28,630 --> 00:25:31,750
What is fiber and what's the difference between fiber and roughage?

459
00:25:32,800 --> 00:25:33,600
Deal, yes.

460
00:25:33,760 --> 00:25:39,680
Um, so fiber is the parts of carbohydrates that are big long chains

461
00:25:39,760 --> 00:25:44,640
that hum the linkages between those chains, human enzymes can't even break down.

462
00:25:44,800 --> 00:25:46,720
So that's a biochemical definition.

463
00:25:46,800 --> 00:25:52,080
That the that they're carbohydrates, they're like long chains of sugars, but the things

464
00:25:52,080 --> 00:25:56,400
connecting the sugars to each other cannot be broken by human enzymes at all.

465
00:25:56,480 --> 00:26:00,160
So without the help of microbes, they're just gonna stay intact and go through your

466
00:26:00,160 --> 00:26:00,960
digestion.

467
00:26:01,190 --> 00:26:06,950
There's also other names for fiber, like soluble as in dissolves in water, or insoluble

468
00:26:07,030 --> 00:26:09,190
as in does not dissolve in water.

469
00:26:09,350 --> 00:26:13,270
And there's a lot of like speculation about which ones are healthier.

470
00:26:13,670 --> 00:26:15,910
To be honest, I think they're all really healthy.

471
00:26:15,990 --> 00:26:19,350
And the key is just that we really need more fiber in our diet.

472
00:26:19,590 --> 00:26:24,960
So an average American is getting 10 to 15 grams of fiber a day when the the

473
00:26:25,120 --> 00:26:31,040
USDA recommends or like the daily government recommendations are 25 to 35 grams per day.

474
00:26:31,280 --> 00:26:35,760
But people in other parts of the world, like Kanambo, I don't know the fiber intake in

475
00:26:35,760 --> 00:26:40,240
Kanambo, but I do know in rural South Africa, in a comparable study, people were eating

476
00:26:40,240 --> 00:26:43,120
more than 70 grams of fiber a day without even trying.

477
00:26:43,760 --> 00:26:46,240
And so we're getting a lot less fiber.

478
00:26:46,400 --> 00:26:47,760
And like, where does it come from?

479
00:26:47,840 --> 00:26:51,920
Like, yes, some come you would get some fiber in lettuce, but just you would eat need to

480
00:26:51,920 --> 00:26:56,490
eat like 20 cups of fiber to get a pretty small 20 cups of lettuce to get a pretty small

481
00:26:56,490 --> 00:26:57,610
amount of fiber.

482
00:26:57,930 --> 00:27:03,210
So if you wanted to get, you know, most people have a gap in fiber of like 10 to 15 grams

483
00:27:03,210 --> 00:27:03,850
per day.

484
00:27:04,170 --> 00:27:08,970
And so if you look at the fiber content of foods that we're eating all the time, really my

485
00:27:08,970 --> 00:27:13,930
point about lettuce was just that you can't get enough fiber out of lettuce by eating like

486
00:27:13,930 --> 00:27:15,210
human amounts of lettuce.

487
00:27:17,290 --> 00:27:19,290
You'd have to go really overboard on the lettuce.

488
00:27:25,120 --> 00:27:30,080
Yeah, like so avocados are high in fiber, which I found so interesting because I before

489
00:27:30,080 --> 00:27:32,800
this also only knew that they were high in healthy fats.

490
00:27:32,960 --> 00:27:33,200
Yeah.

491
00:27:33,360 --> 00:27:38,160
Um, berries are really high in fiber, and so that's cool because they're so sweet, but they

492
00:27:38,160 --> 00:27:40,880
actually have a lot of fiber and they don't spike your blood sugar as much.

493
00:27:41,040 --> 00:27:43,680
Fiber can prevent blood sugar spike as well.

494
00:27:43,890 --> 00:27:49,170
So it's really good to be eating intact foods like fruits rather than juices because then

495
00:27:49,170 --> 00:27:50,930
you keep the fiber, for example.

496
00:27:51,170 --> 00:27:54,610
And you can buy frozen berries, so they're not that expensive.

497
00:27:54,850 --> 00:27:59,810
Um, another thing that is extremely high in fiber and not that expensive are dried beans

498
00:27:59,810 --> 00:28:00,690
and lentils.

499
00:28:01,170 --> 00:28:05,890
So a really good way to understand the fiber content is to look at the breakdown of the

500
00:28:05,890 --> 00:28:10,280
carbs on the nutrition label because it actually tells you how much fiber is there and then

501
00:28:10,280 --> 00:28:11,800
what the total carbs are.

502
00:28:11,960 --> 00:28:17,160
So you want to be looking at the total carbs and then the um the ratio with the fiber.

503
00:28:17,320 --> 00:28:22,920
So if you get white rice, it'll be like what zero to one grams out of 45 grams

504
00:28:23,320 --> 00:28:24,840
of the carbs are fiber.

505
00:28:25,000 --> 00:28:30,040
Brown rice, it'll be like four grams out of 40 grams of carbs are fiber.

506
00:28:30,370 --> 00:28:36,290
But uh beans, it'll be eight grams out of 15 grams of carbs in a half a cup

507
00:28:36,370 --> 00:28:37,010
are fiber.

508
00:28:37,170 --> 00:28:39,490
Half of the grams of carbs are fiber.

509
00:28:39,730 --> 00:28:42,370
So you can so quickly fill your fiber gap.

510
00:28:42,450 --> 00:28:46,850
Like if you just ate a cup of beans or lentils every day, you would fill your fiber gap.

511
00:28:47,170 --> 00:28:50,610
Um chia, chia seeds are like that too, actually.

512
00:28:50,920 --> 00:28:51,720
They're even better.

513
00:28:51,880 --> 00:28:57,800
Chia seeds, 10 out of the 12 grams of carbs in two tablespoons of chia seeds are

514
00:28:57,800 --> 00:28:58,280
fiber.

515
00:28:58,440 --> 00:29:01,560
So I've actually now done several studies, interventions.

516
00:29:01,640 --> 00:29:06,840
I did one in students and I did another one in breast cancer survivors where we had the

517
00:29:06,840 --> 00:29:10,840
intervention as two and a half tablespoons of chia seeds per day.

518
00:29:11,070 --> 00:29:15,870
And that's one of those studies ended a year ago, and I just did the like yearly follow up.

519
00:29:16,510 --> 00:29:21,550
And so many of the people in that study still eat two tablespoons of chia seeds every day.

520
00:29:21,630 --> 00:29:24,030
It's just like pretty easy to get yourself to do it.

521
00:29:24,190 --> 00:29:27,070
Um, it's funny because it's like a fad on the internet now, too.

522
00:29:27,310 --> 00:29:29,070
That wasn't so sometimes they're right.

523
00:29:29,230 --> 00:29:31,070
Broken clocks can be right twice the hour.

524
00:29:31,870 --> 00:29:32,190
Exactly.

525
00:29:32,830 --> 00:29:38,660
I I imagine there are a lot of internet fads related to this uh microbiome

526
00:29:38,900 --> 00:29:40,180
body of research.

527
00:29:40,340 --> 00:29:45,300
Um I would imagine there are a lot of misconceptions and and and there's a lot of misplaced

528
00:29:45,300 --> 00:29:45,700
hype.

529
00:29:45,860 --> 00:29:50,660
Uh I would be curious, since you're an expert in this field, if there are any things that

530
00:29:50,660 --> 00:29:54,500
you would like to correct, any things that you would like to debunk or set the record

531
00:29:54,500 --> 00:29:57,220
straight on, anything where people are getting too carried away with this stuff.

532
00:29:57,700 --> 00:29:59,540
Yeah, thank you for that opportunity.

533
00:29:59,700 --> 00:30:05,670
I mean I think the main one is that probiotics are really not what they say they are.

534
00:30:05,830 --> 00:30:10,310
So probiotics are like a $50 to $80 billion industry.

535
00:30:10,790 --> 00:30:16,790
And most of them claim that you're going to eat this, you know, tablet of microbes and

536
00:30:16,790 --> 00:30:19,430
it's going to become part of your microbiome.

537
00:30:19,510 --> 00:30:24,710
It's going to make your microbiome more diverse, and that's going to help your health in

538
00:30:24,710 --> 00:30:25,270
some way.

539
00:30:25,520 --> 00:30:30,240
But most of those microbes, first of all, are just representing a tiny sliver of the

540
00:30:30,240 --> 00:30:31,840
microbes in your microbiome.

541
00:30:31,920 --> 00:30:33,840
So they're not gonna increase your diversity.

542
00:30:34,000 --> 00:30:38,640
You're gonna like, if this were to be actually possible, you would be like skewing the

543
00:30:38,640 --> 00:30:40,720
diversity towards whatever was in the tablet.

544
00:30:40,800 --> 00:30:43,920
You wouldn't be like promoting diversity all around, you know?

545
00:30:44,160 --> 00:30:47,280
Um, and just they just don't they just don't stick.

546
00:30:47,360 --> 00:30:50,080
I mean, they just are transient and pass right through you.

547
00:30:50,320 --> 00:30:52,160
Most of them are not human microbes.

548
00:30:52,240 --> 00:30:53,830
They're like food microbes.

549
00:30:53,910 --> 00:30:58,630
They don't um they don't have adaptation to become part of a human microbiome.

550
00:30:59,030 --> 00:31:03,670
Um, they also are for the most part harmless, but there's actually times when they really

551
00:31:03,670 --> 00:31:07,830
can be not um just neutral, but they can actually cause harm.

552
00:31:07,990 --> 00:31:12,310
And for example, um, people who are undergoing cancer treatment, especially

553
00:31:12,310 --> 00:31:17,670
immunotherapies, if they take probiotics, it worsens the outcomes.

554
00:31:17,830 --> 00:31:22,390
It like literally makes you have worse chances of having a successful cancer treatment.

555
00:31:22,640 --> 00:31:26,480
And that's tragic because people are doing this to help their health and they don't

556
00:31:26,480 --> 00:31:30,080
understand that it's like just it's actually wrong.

557
00:31:30,960 --> 00:31:34,080
And then another case is after antibiotics.

558
00:31:34,160 --> 00:31:39,600
And I mean, you'll find many doctors who prescribe probiotics after antibiotics, thinking

559
00:31:39,600 --> 00:31:42,000
that it's going to like help restore your microbiome.

560
00:31:42,320 --> 00:31:48,160
But what happens is that then that probiotic is in there, taking up space in your gut in

561
00:31:48,160 --> 00:31:52,240
the moment that you want these other types of strains to be able to return.

562
00:31:52,490 --> 00:31:58,330
And so it actually slows the return to a normal healthy microbiome if you eat probiotics.

563
00:31:58,570 --> 00:32:01,050
Now it might not have long-term consequences.

564
00:32:01,130 --> 00:32:03,290
That might still be a pretty neutral outcome.

565
00:32:03,690 --> 00:32:06,410
And maybe it'll protect you from a pathogen.

566
00:32:06,570 --> 00:32:08,490
So there could be positive outcomes.

567
00:32:08,650 --> 00:32:13,770
But if you go and read the the actual guidelines coming from the physicians, they will

568
00:32:13,770 --> 00:32:18,970
correctly state that there's not enough evidence to to say that you should take probiotics

569
00:32:18,970 --> 00:32:20,090
after antibiotics.

570
00:32:20,400 --> 00:32:20,640
Wow.

571
00:32:20,800 --> 00:32:23,520
What should you do after antibiotics?

572
00:32:23,600 --> 00:32:29,040
Or what's the right metaphor for so if probiotics, like sticking the bugs

573
00:32:29,040 --> 00:32:31,760
themselves in doesn't work, what's the right metaphor?

574
00:32:31,840 --> 00:32:33,840
And what should you do after you take the antibiotics?

575
00:32:34,160 --> 00:32:37,280
Yeah, well, you eating fiber is actually the thing to do.

576
00:32:37,360 --> 00:32:41,600
And like to and actually, even before you take the antibiotics and while you're taking the

577
00:32:41,600 --> 00:32:45,070
antibiotics, if possible, getting fiber into your system.

578
00:32:45,230 --> 00:32:49,630
And I actually think eating fermented foods is really good too, which do have microbes in

579
00:32:49,630 --> 00:32:49,870
them.

580
00:32:50,590 --> 00:32:54,990
But and it's not that I think those microbes will engraft and become part of your gut

581
00:32:54,990 --> 00:32:55,550
microbiome.

582
00:32:55,710 --> 00:33:01,470
It's just that we know that people eating fermented foods and fiber have higher gut

583
00:33:01,470 --> 00:33:06,510
microbiome diversity and it can decrease inflammation when you eat fermented foods like

584
00:33:06,510 --> 00:33:06,750
that.

585
00:33:07,020 --> 00:33:11,580
So, you know, for example, let's say you knew you had to take antibiotics for like dental

586
00:33:11,580 --> 00:33:12,300
surgery or something.

587
00:33:12,380 --> 00:33:13,740
So it was planned.

588
00:33:14,060 --> 00:33:19,260
I would totally recommend eating really well, like in terms of getting the right amount of

589
00:33:19,260 --> 00:33:24,940
fiber, and you know, sleeping, all the things that you know to do right, they become even

590
00:33:24,940 --> 00:33:27,020
more important before you take antibiotics.

591
00:33:27,100 --> 00:33:32,770
And if you can do those things, then the disruption to your microbiome will be limited.

592
00:33:32,850 --> 00:33:37,810
Because basically, eating fiber when the antibiotics come in, it gives your microbes a

593
00:33:37,810 --> 00:33:38,690
place to hide out.

594
00:33:38,850 --> 00:33:43,970
So then they won't be able, like they won't be taken down in the same way.

595
00:33:44,050 --> 00:33:48,690
You're like giving them little territories to hide out in that the antibiotics won't get

596
00:33:48,690 --> 00:33:48,930
to.

597
00:33:49,090 --> 00:33:52,610
So then they'll still be there after the antibiotics are gone.

598
00:33:52,820 --> 00:33:53,380
That's amazing.

599
00:33:53,460 --> 00:33:54,340
And what about yogurt?

600
00:33:54,500 --> 00:33:59,140
I think like anecdotally, people I have this folk notion of like yogurt and the bacterian

601
00:33:59,140 --> 00:34:00,580
yogurt is like really good.

602
00:34:00,740 --> 00:34:01,780
Is that true?

603
00:34:02,100 --> 00:34:03,300
Yeah, I think that's true.

604
00:34:03,540 --> 00:34:06,740
I mean, I don't like nutrition is so complicated.

605
00:34:06,900 --> 00:34:08,900
I mean, we can't even agree if eggs are healthy.

606
00:34:08,980 --> 00:34:14,740
So I mean, I don't want to overstate the evidence we have, but um, but the evidence we have

607
00:34:15,150 --> 00:34:21,070
indicates that eating fermented foods together with fiber is the best thing we know to

608
00:34:21,070 --> 00:34:21,230
do.

609
00:34:21,390 --> 00:34:22,670
And that includes yogurt.

610
00:34:22,750 --> 00:34:27,710
And what's really interesting is that if you study the fecal microbiomes of people who have

611
00:34:27,710 --> 00:34:33,150
been eating fermented foods, it's not that you see long term that those yogurt

612
00:34:33,150 --> 00:34:39,000
microbes are part of the microbiome, But rather, I think it's like the molecules

613
00:34:39,000 --> 00:34:43,320
in the yogurt are nurturing the microbes that you want to have in your gut.

614
00:34:43,560 --> 00:34:49,400
And so probably there's like a whole level of diversity in our gut microbiomes that's below

615
00:34:49,400 --> 00:34:52,040
the limit of detection from the way we study them.

616
00:34:52,280 --> 00:34:57,480
But when you eat yogurt, the molecules in there will promote the growth of those bugs that

617
00:34:57,480 --> 00:34:59,160
we otherwise weren't detecting.

618
00:34:59,240 --> 00:35:03,870
And then they become more they then you it looks like your microbiome is more diverse.

619
00:35:04,030 --> 00:35:07,150
And it is because those bugs have become countable.

620
00:35:07,310 --> 00:35:10,990
Um, and it could be that you're getting the microbes from other humans around you.

621
00:35:11,150 --> 00:35:14,350
I mean, microbiomes are very much at a household level.

622
00:35:14,990 --> 00:35:19,550
So um, and like if you're doing animal studies, you have to take the cage effects into

623
00:35:19,550 --> 00:35:24,900
account big time because the mouse cage will all share the same microbes, and other cages

624
00:35:24,900 --> 00:35:27,940
will have different ones, and you'll think you're studying whatever intervention you're

625
00:35:27,940 --> 00:35:30,820
studying, but really you're just studying which cage each mouse is in.

626
00:35:31,060 --> 00:35:31,380
Wow.

627
00:35:31,540 --> 00:35:32,180
Wow, amazing.

628
00:35:32,340 --> 00:35:36,180
So the metaphor is like we're eating for billions, and we should feed our bugs.

629
00:35:36,260 --> 00:35:37,300
That's the bottom line.

630
00:35:37,380 --> 00:35:37,620
Yeah.

631
00:35:37,940 --> 00:35:38,980
Yeah, that's a good one.

632
00:35:39,380 --> 00:35:42,100
Feed the feed the right ones and don't feed the wrong ones.

633
00:35:42,180 --> 00:35:44,500
And so this is coming back to Kanambo then.

634
00:35:44,740 --> 00:35:49,540
So it sounds like the the thing that John was interested in, and that you and John were

635
00:35:49,540 --> 00:35:53,710
interested in, and you can tell tell us or correct this if this is wrong.

636
00:35:53,950 --> 00:35:59,870
Is this a natural experiment quickly changing of people eating a more quote unquote

637
00:35:59,950 --> 00:36:05,470
sort of maybe like evolutionarily recurrent type of diet without the processed food?

638
00:36:05,710 --> 00:36:10,750
So, what did you either do or what did you discover working with John?

639
00:36:11,150 --> 00:36:12,350
What what did you yeah?

640
00:36:12,590 --> 00:36:14,030
Yeah, well, exactly.

641
00:36:14,110 --> 00:36:19,470
We set up a study design that was at the household level because we know that microbes are

642
00:36:19,470 --> 00:36:21,150
shared in households.

643
00:36:21,500 --> 00:36:23,500
And this was really hard.

644
00:36:23,580 --> 00:36:28,380
And what John did was really impressive because we collected

645
00:36:28,940 --> 00:36:34,700
multiple samples from many people that lived in, it was 28 households that

646
00:36:35,180 --> 00:36:36,540
we were able to collect samples from.

647
00:36:36,620 --> 00:36:42,460
And we got saliva, chicha, and fecal samples from the women and children in those

648
00:36:42,460 --> 00:36:43,820
28 households.

649
00:36:44,060 --> 00:36:49,690
And so as a result, we were able to see how much was shared at the household level, how

650
00:36:49,690 --> 00:36:53,930
different the households were from each other, how s how similar the mothers were to their

651
00:36:53,930 --> 00:36:59,290
children, for example, how similar the saliva microbes were to the chicha

652
00:36:59,450 --> 00:37:05,370
microbes, because the chicha is um begun by chewing on the root

653
00:37:05,370 --> 00:37:05,930
vegetable.

654
00:37:06,010 --> 00:37:10,560
So obviously it gets completely seeded by all the saliva microbes.

655
00:37:10,720 --> 00:37:13,200
And so we got to like watch the fermentation go.

656
00:37:13,280 --> 00:37:19,280
And actually another thing that the master's students working with John did was they grew

657
00:37:19,280 --> 00:37:24,880
their own batch of chicha and took time points so we could actually see the succession of

658
00:37:24,880 --> 00:37:26,880
the microbes in the fermentation.

659
00:37:27,200 --> 00:37:31,120
They took samples every day for four days from several different batches.

660
00:37:31,200 --> 00:37:32,560
So that was really cool.

661
00:37:32,800 --> 00:37:38,630
And then we got to see what was in the gut microbes in the people in Conombo.

662
00:37:39,030 --> 00:37:43,350
And that on its own, I mean, to be honest, that part I was just really interested to see

663
00:37:43,350 --> 00:37:49,030
what was there, both the saliva and the fecal microbes, just to see how they

664
00:37:49,030 --> 00:37:54,790
compared to there had been a few studies of global, a few global studies of populations

665
00:37:54,790 --> 00:37:56,070
that were less contacted.

666
00:37:56,150 --> 00:37:59,910
Like for example, the Hadza hunter gatherers had been studied.

667
00:38:00,470 --> 00:38:04,630
Actually, that just happened around the time John and I started this study.

668
00:38:04,980 --> 00:38:08,820
And um, and so there have been a few other studies around the world.

669
00:38:09,060 --> 00:38:14,660
And what people were finding was that the microbes in the in the gut microbiome were,

670
00:38:14,820 --> 00:38:17,300
first of all, just super diverse.

671
00:38:17,540 --> 00:38:21,860
So many microbes that are missing from the industrialized world are present.

672
00:38:22,180 --> 00:38:25,300
And many of those microbes are fiber degraders.

673
00:38:25,620 --> 00:38:29,700
So um, so there's this one microbe called prevatella.

674
00:38:29,780 --> 00:38:32,660
There's a lot of different kinds of previtella, but there's one that's in the gut that

675
00:38:32,660 --> 00:38:36,790
breaks down fiber, And it's basically missing in the Western world.

676
00:38:36,870 --> 00:38:42,710
Like when I do studies in my UC Irvine students in classes, we basically don't really have

677
00:38:42,710 --> 00:38:45,190
any previtella in any of our samples.

678
00:38:45,670 --> 00:38:51,670
But the people in Canambo, more than 50% of the we the

679
00:38:51,670 --> 00:38:56,150
way we studied the microbes was by cracking open all the cells, extracting the DNA, and

680
00:38:56,150 --> 00:38:57,030
sequencing it.

681
00:38:57,220 --> 00:39:00,180
So our readout is sequencing reads.

682
00:39:00,420 --> 00:39:05,940
And more than half of the reads mapped to this vanishing microbe called Previtella.

683
00:39:06,020 --> 00:39:10,340
So I mean, that to me was just amazing to see that that is still happening.

684
00:39:10,420 --> 00:39:12,980
And I think these microbes are really ancient.

685
00:39:13,140 --> 00:39:18,580
I think it's this is like a hypothesis, but it's possible that the

686
00:39:18,580 --> 00:39:24,130
microbes in the people in Kanambo have been passed down human to human

687
00:39:24,290 --> 00:39:25,970
since people lived in Africa.

688
00:39:26,130 --> 00:39:30,050
Like all of those migrations, people kept the microbes with them.

689
00:39:30,770 --> 00:39:32,450
And there's other evidence of that.

690
00:39:32,530 --> 00:39:37,650
Like there's this one stomach bug called Helicobacter pylori, where you can actually trace

691
00:39:37,650 --> 00:39:43,090
human migration better from the mutations in the Helicobacter pylori than you can from the

692
00:39:43,090 --> 00:39:45,170
mutations in the human genome itself.

693
00:39:45,380 --> 00:39:49,220
And actually, that might not be true anymore because now we have more sequencing capacity,

694
00:39:49,300 --> 00:39:53,300
but there was a period where that was it was easier to learn from the microbes than from

695
00:39:53,300 --> 00:39:53,860
the humans.

696
00:39:54,100 --> 00:39:54,500
Wow.

697
00:39:54,820 --> 00:40:00,820
And uh so anyway, just seeing those privatella in Kanambo to me had this really

698
00:40:00,980 --> 00:40:06,820
like just very profound implication that the

699
00:40:06,820 --> 00:40:12,820
microbes could have potentially traveled through all those generations of people out of

700
00:40:12,820 --> 00:40:13,460
Africa.

701
00:40:13,700 --> 00:40:17,290
Um and we were getting fiber in all those generations.

702
00:40:17,610 --> 00:40:23,530
And it wasn't until basically the 20th century when we started like taking the fiber out

703
00:40:23,530 --> 00:40:29,450
of flour and packaging up all of these tasty treats and taking antibiotics and all these

704
00:40:29,450 --> 00:40:31,210
other things we did in the 20th century.

705
00:40:31,370 --> 00:40:35,130
But that's you know, a couple generations of that, and we totally lost it.

706
00:40:38,680 --> 00:40:43,800
what what do you think are the the health implications for this

707
00:40:44,120 --> 00:40:44,840
research?

708
00:40:45,000 --> 00:40:49,560
Um because you know, as we know in the modern world we have all sorts of health problems,

709
00:40:49,640 --> 00:40:51,240
we have an obesity crisis.

710
00:40:51,400 --> 00:40:57,000
Um presumably some of this might be linked to uh differences in the microbiome we would

711
00:40:57,000 --> 00:41:00,440
have had ancestrally versus the microbiome we have now.

712
00:41:00,680 --> 00:41:05,710
What what do you think are the best um ideas from this line of research, the best

713
00:41:05,710 --> 00:41:10,750
implications we might take from it in terms of uh modern health problems.

714
00:41:11,630 --> 00:41:13,230
They're all science questions.

715
00:41:13,470 --> 00:41:18,910
So um so it's it's kind of early to to even know how to answer the questions.

716
00:41:18,990 --> 00:41:24,270
But um but like I mean I really do think that there will be a future it might be decades

717
00:41:24,270 --> 00:41:29,550
from now where we are more intentional about cultivating the microbes in our guts and in

718
00:41:29,550 --> 00:41:35,160
other maybe in other parts of our bodies too so that we uh uh promote immune development in

719
00:41:35,160 --> 00:41:38,840
the right way and avoid cancer development, for example.

720
00:41:39,080 --> 00:41:44,760
Um, and so you know, there's there's a lot of different angles this research is taking.

721
00:41:44,920 --> 00:41:50,680
Um, but for example, there's a bifidobacteria that breaks down breast milk that is present

722
00:41:50,680 --> 00:41:56,040
in that has been present through most of human history and that we have lost in the 20th

723
00:41:56,040 --> 00:41:56,520
century.

724
00:41:56,840 --> 00:41:59,530
Um and so that means sorry.

725
00:41:59,610 --> 00:42:01,610
So literally can you explain what that means?

726
00:42:01,690 --> 00:42:04,410
That like so babies born now don't have it?

727
00:42:04,810 --> 00:42:09,210
Babies born in, you know, industrialized parts of the world.

728
00:42:09,450 --> 00:42:15,450
So the US and Europe, for the most part, they are completely lacking this bifidobacteria

729
00:42:15,450 --> 00:42:20,090
that contains genes that can break down breast milk sugars, which should be called fibers,

730
00:42:20,170 --> 00:42:20,410
actually.

731
00:42:20,490 --> 00:42:26,280
So it's the same 15% of the energy in breast milk is in the form of essentially a fiber, a

732
00:42:26,280 --> 00:42:29,240
complicated carbohydrate that humans can't break down.

733
00:42:29,400 --> 00:42:31,400
And you need a microbe to break it down.

734
00:42:31,560 --> 00:42:31,800
Wow.

735
00:42:31,960 --> 00:42:37,160
And through most of human history, that microbe has been present in the human communities

736
00:42:37,160 --> 00:42:38,360
that babies are born into.

737
00:42:38,440 --> 00:42:41,240
And it's not even necessarily that it had to come from the mom.

738
00:42:41,320 --> 00:42:46,570
I mean, imagine living in a village where there's lots of babies around and you know, you

739
00:42:46,570 --> 00:42:51,130
just would have multiple opportunities for becoming exposed and colonized, exposed to and

740
00:42:51,130 --> 00:42:52,570
colonized by this bifido.

741
00:42:53,210 --> 00:42:55,930
And so we have lost that in the 20th century.

742
00:42:56,170 --> 00:43:01,690
So I that's a place to start because immune development is so critical in the early part of

743
00:43:01,690 --> 00:43:02,890
our life like that.

744
00:43:03,130 --> 00:43:08,810
So I could imagine a future where we are very intentional about making sure that babies get

745
00:43:08,810 --> 00:43:12,890
this, whether it's only this bifido, maybe we'll learn that there's other bugs that can

746
00:43:12,890 --> 00:43:14,090
play this role too.

747
00:43:14,330 --> 00:43:20,180
But that if we could more intentionally colonize the infant microbiome with

748
00:43:20,660 --> 00:43:26,020
the same types of microbes that humans have had through their history, that might help

749
00:43:26,020 --> 00:43:31,860
reprogram our immune systems to avoid these allergies and eczema

750
00:43:32,020 --> 00:43:34,580
and autoimmune diseases that have become more common.

751
00:43:34,740 --> 00:43:39,010
So that to me is like a really potentially near-term thing that could change.

752
00:43:39,090 --> 00:43:40,530
And I mean, it's already happening.

753
00:43:40,690 --> 00:43:46,450
There's research out of UC Davis that led to a company called Avivo, where they are

754
00:43:46,450 --> 00:43:47,650
selling this bifido.

755
00:43:48,290 --> 00:43:50,530
So to me, that's a real opportunity.

756
00:43:50,690 --> 00:43:55,490
It's interesting though, like when I have a friend who's pregnant and I'm like not wanting

757
00:43:55,490 --> 00:44:01,220
to proselytize and also there's not decades of research where you can say

758
00:44:01,300 --> 00:44:06,020
you know what kind of outcomes this will have, but it seems like a good idea to make sure

759
00:44:06,020 --> 00:44:07,940
that babies are exposed to this bifido.

760
00:44:08,420 --> 00:44:12,500
How do we know that this company is cultivating the right one?

761
00:44:12,820 --> 00:44:16,100
I mean, that's a million-dollar question, or it's actually probably a hundred million

762
00:44:16,180 --> 00:44:18,900
dollar question to do a clinical trial to answer that question.

763
00:44:18,980 --> 00:44:20,820
And then you'd want to compare different ones.

764
00:44:20,980 --> 00:44:26,890
I mean, that's a really uh tough question, but it's something that we have

765
00:44:26,890 --> 00:44:28,170
power to do something about.

766
00:44:28,330 --> 00:44:31,770
So I really like that that it's uh actionable.

767
00:44:32,170 --> 00:44:37,130
Um, and then you know, you were asking questions about what other kind of near term health

768
00:44:37,130 --> 00:44:38,970
impact that this research could have.

769
00:44:39,130 --> 00:44:44,410
I mean, that's what I love about the suggestion about fiber, because it's really very

770
00:44:44,410 --> 00:44:47,770
likely to help and it's unlikely to hurt, you know.

771
00:44:47,850 --> 00:44:53,260
Um, so if you can get yourself to eat more fiber, And there now have been

772
00:44:53,260 --> 00:44:59,260
many intervention studies showing that even short term, you will push your microbiome

773
00:44:59,420 --> 00:45:02,540
towards a healthier state by eating more fiber.

774
00:45:02,780 --> 00:45:06,140
And I guess another piece of advice is to start slow.

775
00:45:06,300 --> 00:45:10,300
I mean, fiber can cause constipation, maybe anti-intuitively.

776
00:45:10,460 --> 00:45:12,300
You need water when you're eating fiber.

777
00:45:12,380 --> 00:45:16,620
So when we do these fiber interventions in the classes here, I have grad students TA ing

778
00:45:16,700 --> 00:45:21,450
the students, and they have to be like college counselor or sorry camp counselors getting

779
00:45:21,450 --> 00:45:24,330
the students to drink enough water and stuff.

780
00:45:24,570 --> 00:45:27,050
And uh so you know start slow.

781
00:45:27,130 --> 00:45:31,930
It's not that it has to be immediate, but you know, think of it like a year-long project.

782
00:45:32,010 --> 00:45:35,690
Like if you were going to the gym and wanted to lift heavier weights, you would start slow

783
00:45:35,690 --> 00:45:36,330
and build up.

784
00:45:36,490 --> 00:45:40,570
And so if you can do that with fiber, it's very likely to help your health.

785
00:45:40,730 --> 00:45:46,600
Um it could be helping not just immune related, but it could help

786
00:45:46,600 --> 00:45:47,960
prevent cancer, for example.

787
00:45:48,120 --> 00:45:53,800
I mean, if there's any diet, I mean, if you look at all the meta-analyses of tons of

788
00:45:53,800 --> 00:45:58,920
different studies, there's a lot of agreement that eating more plants and eating more fiber

789
00:45:58,920 --> 00:46:00,120
will help your health.

790
00:46:00,360 --> 00:46:05,080
And so I think it's just important to come up with something that you actually like that

791
00:46:05,080 --> 00:46:10,920
you can get yourself to do that will get you 10 or 15 grams of fiber per

792
00:46:10,920 --> 00:46:11,320
day.

793
00:46:11,650 --> 00:46:17,490
And um especially if you're having to take antibiotics or cancer therapy or to be honest,

794
00:46:17,650 --> 00:46:20,450
really any kind of drug or even microplastics.

795
00:46:20,530 --> 00:46:24,770
You'll you're protected from microplastics when you're eating fiber because it forms this

796
00:46:24,770 --> 00:46:29,090
matrix that will kind of help expel anything you take in like that.

797
00:46:29,410 --> 00:46:34,690
So it's a feels like a pretty easy way to to protect your health.

798
00:46:35,680 --> 00:46:40,240
And yeah, I mean that's that's kind of the edge of our knowledge.

799
00:46:40,400 --> 00:46:46,320
There's tons of research studies going on to try to in more detail understand the impact of

800
00:46:46,320 --> 00:46:51,600
the microbiome on many different cancer types and immune diseases,

801
00:46:51,840 --> 00:46:54,560
inflammatory bowel disease, for example.

802
00:46:56,560 --> 00:47:01,920
And there's definitely progress happening, but usually it takes decades before

803
00:47:02,210 --> 00:47:05,650
basic research knowledge makes it into people's lives.

804
00:47:05,890 --> 00:47:09,730
And I'm always heartened by that when I think about how much progress we've made in our

805
00:47:09,730 --> 00:47:14,690
fields, because it's only been about like maybe 10 or 15 years that this has been an active

806
00:47:14,690 --> 00:47:15,570
area of research.

807
00:47:15,730 --> 00:47:21,170
And if you look at the cancer immunotherapy example, for that one took about 50 years

808
00:47:21,170 --> 00:47:26,620
before the initial basic science discoveries and between the time when those were made and

809
00:47:26,620 --> 00:47:28,380
when the treatments became available.

810
00:47:28,780 --> 00:47:34,620
And actually the RNA vaccine that we had for COVID,

811
00:47:34,940 --> 00:47:38,460
that involved 20 years of basic research.

812
00:47:38,620 --> 00:47:42,380
And if we hadn't had that, we would never have been able to make the vaccine so quickly.

813
00:47:42,460 --> 00:47:47,980
And it was accelerated by the people who made that happen for all of us

814
00:47:48,460 --> 00:47:50,380
because there was such a demand for it.

815
00:47:51,260 --> 00:47:51,900
Yeah.

816
00:47:53,290 --> 00:47:59,290
so I'm curious about this link between um the microbiome

817
00:47:59,450 --> 00:48:02,010
and and specific diseases and disorders.

818
00:48:02,090 --> 00:48:07,050
So I can sort of intuitively understand why having a less diverse microbiome would make

819
00:48:07,050 --> 00:48:12,490
your digestive processes less effective, make you less able to extract the proper nutrients

820
00:48:12,490 --> 00:48:17,930
that you need out of food, um, and that I could understand how that could lead to

821
00:48:18,040 --> 00:48:19,160
health problems.

822
00:48:19,400 --> 00:48:25,000
But I'm a little less clear about what the causal pathway would be to something like, say,

823
00:48:25,240 --> 00:48:25,880
cancer.

824
00:48:26,120 --> 00:48:32,120
Like uh or um the auto uh the auto-dimmune autoimmune diseases, um, I could sort of

825
00:48:32,120 --> 00:48:36,440
understand why that would make sense and that your immune system is trained on the

826
00:48:36,440 --> 00:48:37,000
microbiome.

827
00:48:37,080 --> 00:48:38,120
Is that the idea?

828
00:48:38,390 --> 00:48:42,310
Um, but with with cancer, that's a little less clear to me what what the link would be

829
00:48:42,390 --> 00:48:42,550
there.

830
00:48:42,710 --> 00:48:46,790
Could you could you talk through some of the possible causal pathways that might uh be

831
00:48:46,790 --> 00:48:47,430
working here?

832
00:48:47,830 --> 00:48:52,950
Yeah, I mean I we are definitely like at the edge of human knowledge here.

833
00:48:53,110 --> 00:48:56,150
So some of the studies are more observational still.

834
00:48:56,390 --> 00:48:56,630
Yeah.

835
00:48:56,790 --> 00:49:02,550
Um, but you know, for example, let's take colon cancer as an example because it's

836
00:49:03,020 --> 00:49:06,220
adjacent to the location of all those gut microbes.

837
00:49:06,780 --> 00:49:12,780
When you are eating enough fiber, then the microbes in your colon are taking the

838
00:49:12,780 --> 00:49:17,100
fiber and producing these actually quite smelly volatile molecules.

839
00:49:17,180 --> 00:49:18,860
They're called short-chain fatty acids.

840
00:49:18,940 --> 00:49:22,860
And like some of them are household items that you're familiar with, like acetate,

841
00:49:24,410 --> 00:49:25,370
Butyrate.

842
00:49:26,170 --> 00:49:30,570
These molecules are the favorite fuels of the cells lining the colon.

843
00:49:30,810 --> 00:49:36,090
So they're used to running on acetate, and butyrate's the most abundant and probably the

844
00:49:36,090 --> 00:49:36,890
most important one.

845
00:49:37,050 --> 00:49:41,450
So if you're eating fiber and the microbes are turning it into butyrate, then those cells

846
00:49:41,450 --> 00:49:43,290
are running on their favorite fuels.

847
00:49:43,450 --> 00:49:47,290
So the metabolism of those cells is like going in the right direction.

848
00:49:47,530 --> 00:49:49,640
And now here's where my own knowledge is.

849
00:49:49,720 --> 00:49:54,520
Um, I don't have a lot more knowledge of each of these pathways, but I have colleagues, for

850
00:49:54,520 --> 00:49:59,800
example, who have devoted their careers to understanding, you know, particular types of

851
00:49:59,800 --> 00:50:02,840
metabolic signaling in the cells that live in our colon.

852
00:50:02,920 --> 00:50:08,360
And if that goes awry, then the chances that one of those cells will be able to take off in

853
00:50:08,360 --> 00:50:10,760
a cancerous direction increase.

854
00:50:11,240 --> 00:50:17,210
So if you keep the those cells in a healthy state, it um it helps to

855
00:50:17,210 --> 00:50:20,010
promote all the features that you want out of your cells.

856
00:50:20,090 --> 00:50:21,450
I mean, what is cancer?

857
00:50:21,610 --> 00:50:27,530
Cancer is when one cell becomes a renegade and takes off in a crazy direction with a crazy

858
00:50:27,530 --> 00:50:33,370
genome and unneighborly practices that just don't respect the cellular

859
00:50:33,370 --> 00:50:34,810
boundaries around them.

860
00:50:35,050 --> 00:50:40,840
And so if you are not fueling the cells lining your colon with

861
00:50:40,840 --> 00:50:46,360
the molecules that they have become accustomed to throughout our evolution, then you are

862
00:50:46,680 --> 00:50:50,600
making it easier for those cells to go off in a crazier direction.

863
00:50:52,040 --> 00:50:53,880
Um is it is part of it.

864
00:50:53,960 --> 00:50:58,930
Um but I mean the correlations exist for distant cancer types.

865
00:50:59,090 --> 00:51:04,050
And so, and actually, another thing that I should have said first is that one of the most

866
00:51:04,050 --> 00:51:09,890
important functions of our immune system is to survey and prevent cancer cells

867
00:51:09,890 --> 00:51:10,930
from taking off.

868
00:51:11,170 --> 00:51:16,690
And so this actually is probably a more important mechanism that when you keep your immune

869
00:51:16,690 --> 00:51:22,690
system humming along at its best possible function, then that will

870
00:51:23,330 --> 00:51:29,100
help promote the, you know, the surveillance and removal of precancerous cells.

871
00:51:29,420 --> 00:51:30,380
I did not know that.

872
00:51:30,700 --> 00:51:31,420
Wow, fascinating.

873
00:51:31,660 --> 00:51:33,100
That's crazy that I didn't know that.

874
00:51:33,180 --> 00:51:33,500
Yeah.

875
00:51:34,220 --> 00:51:35,580
Yeah, that is actually kind of crazy.

876
00:51:35,820 --> 00:51:41,660
And so so the the immune system could actually uh kill the the precancerous cells before

877
00:51:41,660 --> 00:51:45,580
they they take off just as they would another microbe pathogen?

878
00:51:45,980 --> 00:51:46,220
Yeah.

879
00:51:46,300 --> 00:51:51,020
Oh I mean that is a huge and like you know very very important function of our immune

880
00:51:51,020 --> 00:51:51,260
system.

881
00:51:51,340 --> 00:51:56,630
And think about when like maybe you have friends or colleagues who have had to take

882
00:51:56,630 --> 00:52:02,550
immunosuppressants either because of um an inflammatory bowel disease or after

883
00:52:02,710 --> 00:52:06,630
organ transplant or there's reasons that people have to take drugs that suppress their

884
00:52:06,630 --> 00:52:07,510
immune function.

885
00:52:07,750 --> 00:52:13,270
And one of the most um important consequences of taking immunosuppressants is increased

886
00:52:13,270 --> 00:52:18,390
cancer, like the increased likelihood of cancer developing, because then you don't have

887
00:52:18,390 --> 00:52:21,190
your immune system there to help protect you.

888
00:52:21,540 --> 00:52:21,780
Wow.

889
00:52:22,260 --> 00:52:26,820
And my understanding is that the immune system obviously, I mean, it was interesting to me

890
00:52:26,900 --> 00:52:29,460
and it's obvious in retrospect, but talks to the gut.

891
00:52:29,620 --> 00:52:35,540
So for example, like I mean, uh, nut allergy, or or for example, if if if

892
00:52:35,620 --> 00:52:41,220
uh if a substance is detected in your gut, your immune system learns that that's food and

893
00:52:41,220 --> 00:52:44,420
not something to attack, for example, like in a simple way.

894
00:52:44,820 --> 00:52:50,410
Um so so is that right that the immune system is this

895
00:52:50,570 --> 00:52:56,250
sort of contingent evolved system that's surveying the contents of the gut,

896
00:52:56,410 --> 00:52:57,770
surveying everything?

897
00:52:58,330 --> 00:53:01,130
And and sort of is is that right?

898
00:53:01,530 --> 00:53:03,130
Yeah, that's definitely right.

899
00:53:03,290 --> 00:53:09,050
And um yeah, I mean, actually, there's a a book I recommend if you guys get if anybody

900
00:53:09,050 --> 00:53:11,290
listening gets interested in the fiber stuff.

901
00:53:11,370 --> 00:53:16,330
And there's a doctor in South Carol Carolina named Will Buschemitz, and he wrote a book

902
00:53:16,330 --> 00:53:17,850
called Fiber Fueled.

903
00:53:18,120 --> 00:53:23,240
And in this book, his goal is that everybody should be able to work towards eating

904
00:53:23,240 --> 00:53:23,640
everything.

905
00:53:23,800 --> 00:53:29,000
And it's such a cool way of putting it because everybody has all these food intolerances.

906
00:53:29,080 --> 00:53:30,440
And he's a gastroenterologist.

907
00:53:30,600 --> 00:53:33,880
He's come across people with all kinds of sensitivities.

908
00:53:34,200 --> 00:53:39,960
And a major reaction to those sensitivities is avoidance because who wants to

909
00:53:39,960 --> 00:53:41,720
be having reactions to their food?

910
00:53:41,800 --> 00:53:42,680
I mean, that's terrible.

911
00:53:42,760 --> 00:53:46,760
So it's very understandable that you avoid the foods that cause reactions.

912
00:53:47,370 --> 00:53:52,330
And there will be exceptions to this, like gluten for celiac disease or lactose intolerance

913
00:53:52,410 --> 00:53:53,130
and so forth.

914
00:53:53,290 --> 00:53:59,210
But in general, if you work towards it and have low

915
00:53:59,210 --> 00:54:05,130
amounts of exposure repeatedly through time, it's a reasonable goal that most people should

916
00:54:05,130 --> 00:54:06,890
be able to eat most things.

917
00:54:07,050 --> 00:54:12,120
And that's part of what you were just bringing up with the way that your immune system is

918
00:54:12,120 --> 00:54:13,800
sampling all the molecules in your gut.

919
00:54:13,880 --> 00:54:15,960
Because yeah, you have a ton of immune cells in your gut.

920
00:54:16,040 --> 00:54:18,520
You actually have a ton of nervous system cells in your gut too.

921
00:54:18,920 --> 00:54:20,440
Yeah, the most neurons.

922
00:54:20,600 --> 00:54:23,560
I remember that from neuroscience, and it was just sort of passing through, but it's always

923
00:54:23,560 --> 00:54:24,520
been like, why is that?

924
00:54:24,680 --> 00:54:28,600
More neurons outside of your brain are in your gut than anywhere else.

925
00:54:28,840 --> 00:54:29,960
Yeah, that's amazing.

926
00:54:30,120 --> 00:54:32,760
So all this stuff about butterflies in your stomach and so on.

927
00:54:32,840 --> 00:54:36,530
I mean, we really do have a lot of sensing capacity in our gut.

928
00:54:36,690 --> 00:54:41,970
We also have a network of neuroendocrine cells that produce all kinds of hormones and other

929
00:54:42,210 --> 00:54:43,170
important molecules.

930
00:54:43,330 --> 00:54:48,290
So, like 90% of the serotonin in our bodies is produced by cells in our gut.

931
00:54:48,370 --> 00:54:53,650
And they are human cells, but they are adjacent to this massive network of microbial cells.

932
00:54:53,970 --> 00:54:59,730
So that's another way that eating fiber will impact your health because by

933
00:54:59,730 --> 00:55:05,260
eating fiber and keeping those microbes humming along on their favorite fuels, all the meta

934
00:55:05,500 --> 00:55:10,860
all the metabolic byproducts are feeding the immune cells and the nervous system cells, the

935
00:55:10,860 --> 00:55:12,940
neuroendocrine cells in your gut.

936
00:55:13,100 --> 00:55:19,020
And that will push those cells towards, you know, giving you all the

937
00:55:19,020 --> 00:55:20,940
different good stuff.

938
00:55:21,340 --> 00:55:25,740
And when I just came across, like I didn't know what that stuff was, that's because that's

939
00:55:25,740 --> 00:55:27,100
the edge of scientific knowledge.

940
00:55:27,180 --> 00:55:30,860
Really, I mean, there's like a few molecules we've studied really well, like serotonin,

941
00:55:30,940 --> 00:55:34,220
which there's still plenty of mysteries around that one, but at least we can name it.

942
00:55:34,470 --> 00:55:38,710
A lot of these molecules are undiscovered by science, like truly.

943
00:55:38,870 --> 00:55:44,630
Like when I even when I get a sequence data set back, I can only identify usually

944
00:55:44,790 --> 00:55:47,750
like 30% of the data that comes back.

945
00:55:47,910 --> 00:55:49,110
The rest is just unknown.

946
00:55:49,270 --> 00:55:53,030
It's not that it's garbage, it's just that we haven't ever studied it before as a

947
00:55:53,030 --> 00:55:54,150
scientific community.

948
00:55:54,390 --> 00:55:57,030
And for molecules, that number is even higher.

949
00:55:57,190 --> 00:56:02,500
So like when I take a sample and run it through the state of the art, you know, how do you

950
00:56:02,500 --> 00:56:05,540
catch all the different molecules in a sample type of equipment?

951
00:56:05,860 --> 00:56:11,060
Maybe like five or 10% of the molecules can even be identified.

952
00:56:11,300 --> 00:56:16,500
So there's a lot of communication going on there that we don't understand yet.

953
00:56:16,980 --> 00:56:22,420
But I still think the advice that we could have given you a generation or two ago to like

954
00:56:22,580 --> 00:56:28,370
eat foods that your grandmother recognizes as food, or eat foods that you can

955
00:56:28,370 --> 00:56:30,450
read what the ingredients mean.

956
00:56:30,850 --> 00:56:35,970
So it's not something crazy and processed or like Michael Pollins, like eat food mostly

957
00:56:35,970 --> 00:56:37,090
plants, not too much.

958
00:56:37,250 --> 00:56:42,450
I still think that will honestly be the best advice for a long time, no matter how

959
00:56:42,450 --> 00:56:45,730
fancy our molecular identifications become.

960
00:56:45,890 --> 00:56:46,930
You know yeah.

961
00:56:47,240 --> 00:56:49,080
Um, one of what is the effect?

962
00:56:49,240 --> 00:56:54,040
So I think like um when I moved from Germany back to the US, I noticed that there's a lot

963
00:56:54,040 --> 00:57:00,040
more enriched flour, which as I understand it, is different than just milled flour, and

964
00:57:00,040 --> 00:57:01,880
then a lot more sugar in things.

965
00:57:02,280 --> 00:57:05,640
Um those are cheap things to make.

966
00:57:05,800 --> 00:57:11,800
What is the effect of sugar or enriched flour or or alcohol, for example, like

967
00:57:11,800 --> 00:57:14,920
high concentrations of alcohol on our microbiome?

968
00:57:15,550 --> 00:57:18,030
Well, I mean, everything affects our microbiome.

969
00:57:18,190 --> 00:57:21,230
So the answer will always be that there is an effect.

970
00:57:21,310 --> 00:57:26,750
Um, and then it starts to become more context dependent for that person and how much and so

971
00:57:26,750 --> 00:57:26,990
forth.

972
00:57:27,150 --> 00:57:32,750
So, I mean, you know, I personally am interested to know if people can mostly eat

973
00:57:32,750 --> 00:57:37,390
terribly, but then just like sprinkle some fiber on top, and then that will solve the

974
00:57:37,390 --> 00:57:37,630
problem.

975
00:57:37,870 --> 00:57:42,920
Or is that really still gonna be hard on your microbiome, and it's important to remove some

976
00:57:42,920 --> 00:57:45,400
of the more negative aspects of our diets.

977
00:57:45,480 --> 00:57:47,160
And I think that's a science question.

978
00:57:47,240 --> 00:57:51,560
But I mean, overall, eating all this processed stuff is probably not great for us,

979
00:57:51,720 --> 00:57:54,040
especially in larger quantities.

980
00:57:54,360 --> 00:57:58,760
Um, the way that food is processed in Europe and the US, there's some really big

981
00:57:58,760 --> 00:57:59,400
differences.

982
00:57:59,720 --> 00:58:02,120
Um, also in those strains of wheat.

983
00:58:02,360 --> 00:58:07,930
So you you've probably heard lots of anecdotal stories like I have of people who

984
00:58:08,410 --> 00:58:13,130
can't eat wheat in the United States, but they go to Europe and they can eat pasta in Italy

985
00:58:13,210 --> 00:58:14,570
and they can eat bread in Germany.

986
00:58:14,730 --> 00:58:16,810
And nobody quite understands why.

987
00:58:16,890 --> 00:58:22,170
And there's a bunch of hypotheses like the strains of wheat in the US have more gluten in

988
00:58:22,170 --> 00:58:22,330
them.

989
00:58:23,050 --> 00:58:25,290
So that's actually not a processing issue.

990
00:58:25,370 --> 00:58:28,170
It's just like the strains that have chosen to grow here.

991
00:58:28,250 --> 00:58:31,370
And that gluten helps with the texture being nicer, I guess.

992
00:58:31,610 --> 00:58:37,160
So that's the motivation, but maybe that's why people have a harder time eating gluten in

993
00:58:37,160 --> 00:58:39,480
the United States or eating wheat in the United States.

994
00:58:39,640 --> 00:58:44,760
Um there's so many nuances in the processing that I'm honestly not an expert in.

995
00:58:45,000 --> 00:58:49,880
But it still makes the advice stand to try to just like eat whole foods to the extent that

996
00:58:49,880 --> 00:58:50,360
you can.

997
00:58:50,680 --> 00:58:50,840
Yeah.

998
00:58:50,920 --> 00:58:54,920
And that feels like it's fighting I mean, the there's just this issue of profitability.

999
00:58:55,000 --> 00:58:59,390
Like Dave and I have talked about how as much as independent or individual people want to

1000
00:58:59,390 --> 00:59:01,550
do things and we can wag our fingers at people.

1001
00:59:01,710 --> 00:59:03,230
And I'm not saying we're doing this.

1002
00:59:03,390 --> 00:59:03,630
Yeah.

1003
00:59:03,790 --> 00:59:07,150
But it's it for me, it's tempting to sort of be like, you should be eating your fiber,

1004
00:59:07,230 --> 00:59:08,270
which is like a joke, right?

1005
00:59:08,350 --> 00:59:10,030
But um as a trope.

1006
00:59:10,110 --> 00:59:15,950
But it's this thing of you know, going to the store, um, or what even if everybody wants

1007
00:59:15,950 --> 00:59:21,900
there to be like whole, fresh foods that are healthy, cheap, abundant, you know, not high

1008
00:59:21,900 --> 00:59:22,860
in pesticides.

1009
00:59:23,020 --> 00:59:26,940
These are we're feeding our kids and our grandkids and our future.

1010
00:59:27,100 --> 00:59:32,220
Um, there's still just structural selection dynamics of like what's profitable.

1011
00:59:32,540 --> 00:59:36,620
Um, you know, and even as you said, like the probiotic thing, like it's a huge market.

1012
00:59:36,700 --> 00:59:39,900
And like, I don't know, are people going to make a lot of money if you're like eat beans?

1013
00:59:39,980 --> 00:59:45,820
You know, like so um in thinking about the discrepancy between what you see when you go

1014
00:59:45,820 --> 00:59:50,490
to a store versus what we know scientifically, yeah.

1015
00:59:50,650 --> 00:59:56,650
Like, should are we fighting the fact that profitability is in the way, or is that a

1016
00:59:56,650 --> 00:59:57,530
a false choice?

1017
00:59:57,610 --> 01:00:02,490
And is there a way to make align profitability with what's healthy for us?

1018
01:00:02,650 --> 01:00:04,650
Um I know I feel better.

1019
01:00:04,810 --> 01:00:10,010
I I I'm willing to pay, for example, like I feel better when I eat healthy.

1020
01:00:10,250 --> 01:00:15,080
And feeling better is a different thing than like something just like tastes good sort of

1021
01:00:15,240 --> 01:00:20,920
right like so yes yeah yeah often feel awful when after eating you know the the junk food

1022
01:00:20,920 --> 01:00:25,560
that I crave you know so it's definitely a trade-off yeah I mean processed food is

1023
01:00:25,560 --> 01:00:31,560
addictive I mean truly addictive the same way that other addictions that we treat

1024
01:00:31,560 --> 01:00:37,160
really seriously um and have therapies for in our country processed food uh

1025
01:00:37,480 --> 01:00:43,320
is certainly in the same category so I mean it's it's there's a lot of barriers

1026
01:00:43,320 --> 01:00:47,470
to to helping people avoid becoming addicted to processed food.

1027
01:00:47,630 --> 01:00:52,670
I mean, that's just basically a normal thing in our society that you're addicted to

1028
01:00:52,670 --> 01:00:54,430
processed food and it's around everywhere.

1029
01:00:54,590 --> 01:00:59,150
Our food environment makes it basically impossible not to be addicted to processed food is

1030
01:00:59,310 --> 01:01:03,070
is my experience of someone that's lived here most of my life.

1031
01:01:03,230 --> 01:01:05,150
And I mean I've lived in European cities too.

1032
01:01:05,230 --> 01:01:09,160
It's you're still having tons of access to processed food.

1033
01:01:09,240 --> 01:01:11,480
I mean, that's just how the modern world is right now.

1034
01:01:11,640 --> 01:01:11,880
Yeah.

1035
01:01:12,120 --> 01:01:17,240
So I don't know how we remove the processed food addiction part, but I mean, it doesn't

1036
01:01:17,240 --> 01:01:19,160
have to be expensive to get enough fiber.

1037
01:01:19,240 --> 01:01:24,600
So that's always the the message in my classes is that, you know, here's five things that

1038
01:01:24,600 --> 01:01:27,160
you all know what they are, and they are not expensive.

1039
01:01:27,320 --> 01:01:29,880
And so the barrier really is not cost.

1040
01:01:30,360 --> 01:01:34,760
Um, it might be time, but I think it's more about just like having it be part of your

1041
01:01:34,760 --> 01:01:35,160
routine.

1042
01:01:35,320 --> 01:01:35,640
Yeah.

1043
01:01:35,850 --> 01:01:41,850
So I I that's really my message is that, you know, pick something that you actually

1044
01:01:41,850 --> 01:01:46,010
like and that you can get yourself to do and just try to do it every day.

1045
01:01:46,090 --> 01:01:49,370
And even if you're still a little addicted to processed food, at least you'll have the

1046
01:01:49,370 --> 01:01:50,250
fiber in there too.

1047
01:01:50,330 --> 01:01:52,090
And I think that's better than not doing it.

1048
01:01:52,250 --> 01:01:57,130
I mean, right now we I there's a Starbucks out the window behind me right now, where they

1049
01:01:57,130 --> 01:02:01,770
sell 20,000 frappuccinos every month, or it might even be more than that by now.

1050
01:02:02,120 --> 01:02:03,800
And it is so much sugar.

1051
01:02:03,880 --> 01:02:09,720
I mean, the amount of sugar a person eats in a day today is more than the amount of sugar a

1052
01:02:09,720 --> 01:02:12,120
person would eat in a year 300 years ago.

1053
01:02:12,280 --> 01:02:14,840
Like sugar used to be this precious commodity.

1054
01:02:14,920 --> 01:02:18,840
Like the queen would have a key to the room that had the sugar in it, and nobody else could

1055
01:02:18,840 --> 01:02:19,560
go in there.

1056
01:02:19,720 --> 01:02:24,890
And it was a very um, you know, people were still addicted to it if they could get could

1057
01:02:24,890 --> 01:02:28,730
get their hands on it, but it just wasn't like everywhere in their environment the way it

1058
01:02:28,730 --> 01:02:30,250
is here, especially drinking it.

1059
01:02:30,410 --> 01:02:32,330
People just get so much sugar that way.

1060
01:02:32,650 --> 01:02:38,090
So I guess if I could say two things, it would be like not to drink sugar, because you just

1061
01:02:38,090 --> 01:02:39,530
get so much of it so fast.

1062
01:02:39,610 --> 01:02:43,690
And I mean, just find something else that you like to drink, but that doesn't have 60 grams

1063
01:02:43,690 --> 01:02:47,930
of sugar in a cup or whatever, because it's like a crazy amount of sugar you get that way.

1064
01:02:48,140 --> 01:02:51,820
And then the other one is just to pick something with fiber in it that you like.

1065
01:02:51,980 --> 01:02:57,020
So if it's beans, I mean, it's actually not that hard to buy a crock pot at the thrift

1066
01:02:57,020 --> 01:02:58,140
store for 10 bucks.

1067
01:02:58,300 --> 01:03:03,740
And on Sundays, you cook up a pot of beans and then you just like eat a cup of them one day

1068
01:03:03,740 --> 01:03:04,220
each week.

1069
01:03:04,300 --> 01:03:08,780
Somehow you put them in your salad, you bring them with you for lunch, like whatever it is.

1070
01:03:09,070 --> 01:03:10,990
that's to me kind of doable.

1071
01:03:11,070 --> 01:03:15,230
Or like for berries, which are quite expensive when they're fresh, they're not expensive

1072
01:03:15,230 --> 01:03:16,270
when they're frozen.

1073
01:03:16,510 --> 01:03:18,110
So maybe you like smoothies.

1074
01:03:18,270 --> 01:03:23,150
So put some frozen berries in your smoothie with some chia seeds in the mornings.

1075
01:03:23,390 --> 01:03:27,630
And then like all day you'll have this feeling like you did something right, you know, like

1076
01:03:27,710 --> 01:03:28,910
you got your fiber.

1077
01:03:29,300 --> 01:03:29,540
Yeah.

1078
01:03:29,860 --> 01:03:32,180
And berries are much cheaper than a Starbucks coffee.

1079
01:03:32,260 --> 01:03:33,780
I mean, you're you're in Europe.

1080
01:03:33,860 --> 01:03:38,340
I was used to like maybe one euro or two euro for a coffee out of a good espresso machine.

1081
01:03:38,420 --> 01:03:42,180
And like coming back to the US, I'm like, I I refuse to spend.

1082
01:03:42,260 --> 01:03:44,420
So I just like have a coffee machines around.

1083
01:03:44,500 --> 01:03:46,260
Like, you know, not everybody can do that.

1084
01:03:46,340 --> 01:03:47,380
But yeah, if you can, yeah.

1085
01:03:47,620 --> 01:03:50,820
Berries are cheap compared to um coffee.

1086
01:03:50,990 --> 01:03:51,230
Yeah.

1087
01:03:51,470 --> 01:03:51,870
You're right.

1088
01:03:51,950 --> 01:03:54,990
I mean, people are willing to spend a really large amount of money on coffee.

1089
01:03:55,070 --> 01:03:55,710
It's a good point.

1090
01:03:55,870 --> 01:03:59,390
Or like boba or whatever sugary drink they're into.

1091
01:03:59,630 --> 01:04:05,630
Another thing is you can make kombucha at home, um, which is I mean, maybe that's

1092
01:04:05,630 --> 01:04:06,750
like a fringe activity.

1093
01:04:06,830 --> 01:04:08,510
It's hard for me to tell anymore.

1094
01:04:08,670 --> 01:04:12,590
But but I mean it's actually not that hard and it's pretty fun and it tastes good.

1095
01:04:12,750 --> 01:04:18,430
And um, and that's like a way to have a kind of unusual, fun, nice beverage that's a little

1096
01:04:18,430 --> 01:04:23,580
bit sweet, but it's not gonna have like when you when you make kombucha, you start out with

1097
01:04:23,580 --> 01:04:27,980
about a cup of sugar in a gram, uh sorry, a gallon of black tea or whatever tea you're

1098
01:04:27,980 --> 01:04:28,300
using.

1099
01:04:28,540 --> 01:04:33,500
But then you give the microbes like a week to m to eat down a lot of the sugar.

1100
01:04:33,580 --> 01:04:37,180
So by the time you drink it, it's actually not that sweet, but it's flavorful.

1101
01:04:37,420 --> 01:04:41,260
So and kombucha has taken off in the probiotics industry.

1102
01:04:41,340 --> 01:04:45,570
So in terms of making profit, I mean there's actually quite a few of these beverages.

1103
01:04:45,650 --> 01:04:51,010
Like even the Super Bowl ads are full of ads for that poppy drink that has the fiber in

1104
01:04:51,010 --> 01:04:52,930
those poppy drinks is inulin.

1105
01:04:53,570 --> 01:04:55,410
And that is a plant fiber.

1106
01:04:55,890 --> 01:05:01,250
Um, so I mean, it's is that as good as making sure you're eating whole foods every day?

1107
01:05:01,330 --> 01:05:03,490
Like probably not, but it is fiber.

1108
01:05:03,570 --> 01:05:05,720
I mean, I I I'll take any fiber.

1109
01:05:05,880 --> 01:05:09,560
I think that counts in the positive category and those have become very profitable.

1110
01:05:10,040 --> 01:05:10,200
Yeah.

1111
01:05:10,360 --> 01:05:10,600
Yeah.

1112
01:05:10,680 --> 01:05:13,400
Because of your you oh sorry, David, just because of your talk.

1113
01:05:13,480 --> 01:05:19,480
I mean, I actually feed my son since I started talking berries and um uh soups with with

1114
01:05:19,480 --> 01:05:21,400
beans and lentils, and he loves it.

1115
01:05:21,560 --> 01:05:24,680
But I'm just like and I just feel like I'm constantly I'm like, this is great.

1116
01:05:24,760 --> 01:05:26,600
Like and it's it's super easy.

1117
01:05:26,840 --> 01:05:29,160
Um and uh yeah, so thank you.

1118
01:05:29,240 --> 01:05:33,010
Like I would not have known it if I if you didn't I I love I didn't hear that talk.

1119
01:05:33,090 --> 01:05:33,490
Yeah.

1120
01:05:33,730 --> 01:05:34,930
That's really cool.

1121
01:05:35,250 --> 01:05:35,650
Yeah.

1122
01:05:35,810 --> 01:05:40,130
Um I I feed my daughter one of my daughter's favorite snacks is just canned beans with like

1123
01:05:40,130 --> 01:05:41,570
a little bit of salt sprinkled on them.

1124
01:05:41,650 --> 01:05:43,410
That's like she it's her go to thing.

1125
01:05:43,490 --> 01:05:47,570
So I'm very glad to hear that that's that's good for her because she just coincidentally

1126
01:05:47,810 --> 01:05:48,530
really likes it.

1127
01:05:49,250 --> 01:05:50,450
Her daughter's awesome, David.

1128
01:05:50,530 --> 01:05:52,450
She likes horror movies and canned beans.

1129
01:05:52,530 --> 01:05:53,170
This is awesome.

1130
01:05:53,330 --> 01:05:57,250
She's well that's really cool.

1131
01:05:57,410 --> 01:05:57,730
Yeah.

1132
01:05:57,970 --> 01:06:00,760
Yeah, no, I'm I'm a very proud father.

1133
01:06:01,160 --> 01:06:07,160
Uh I I wanna make sure I'm getting the the causal pathway here of why processed

1134
01:06:07,160 --> 01:06:08,040
foods are bad.

1135
01:06:08,280 --> 01:06:14,040
So is it because uh companies put in preservatives to keep the food from spoiling so it

1136
01:06:14,040 --> 01:06:17,800
could be transported uh to vast distances?

1137
01:06:17,960 --> 01:06:22,840
Um and those preservatives, while good at keeping the food from spoiling, at the same time

1138
01:06:23,080 --> 01:06:28,210
are damaging to the the microbiome because i while they prevent, you you know, bad bacteria

1139
01:06:28,210 --> 01:06:32,290
from growing on the food, they also kill the good bacteria w uh in us when we eat them.

1140
01:06:32,370 --> 01:06:36,690
Is that the logic of how we're that's one part of the logic, although it's actually not the

1141
01:06:36,690 --> 01:06:38,130
part I'm the most worried about.

1142
01:06:38,850 --> 01:06:44,770
To me, the major problem is that one pretty universal step in all

1143
01:06:44,770 --> 01:06:46,770
processed food is removing the fiber.

1144
01:06:47,250 --> 01:06:47,410
Okay.

1145
01:06:47,730 --> 01:06:53,010
And so basically you're simplifying the food to be a pile of sugar, essentially.

1146
01:06:53,330 --> 01:06:59,320
So um so I mean, white flour is still better than just pure cane sugar in terms of how it

1147
01:06:59,320 --> 01:07:04,200
will affect your blood sugar and what will be left for your microbes to eat in the colon.

1148
01:07:04,360 --> 01:07:10,040
But but when you process food and you remove the fiber, it means that there's nothing left

1149
01:07:10,040 --> 01:07:11,160
for your microbes to eat.

1150
01:07:11,320 --> 01:07:17,160
Like your microbes depend on getting fiber to your colon, um, which is where they

1151
01:07:17,160 --> 01:07:17,480
live.

1152
01:07:17,640 --> 01:07:22,120
The the most density of microbes is in the last part of your descending colon.

1153
01:07:22,280 --> 01:07:28,030
The it uh in good circumstances, you'll have like 10 to the ninth bacteria per

1154
01:07:28,030 --> 01:07:30,510
gram in your in that last part of your colon.

1155
01:07:30,670 --> 01:07:34,270
Whereas in your stomach, it's like 10 to the two, you that's hardly anything because it's

1156
01:07:34,270 --> 01:07:35,150
so acidic.

1157
01:07:35,390 --> 01:07:40,990
And then that number, the density of microbes kind of grows at as you go down the colon

1158
01:07:40,990 --> 01:07:42,350
until you get to the descending golden.

1159
01:07:42,430 --> 01:07:45,710
And that's where like the overwhelming majority of the microbes in your body live right

1160
01:07:45,790 --> 01:07:46,030
there.

1161
01:07:46,190 --> 01:07:46,350
Yeah.

1162
01:07:46,660 --> 01:07:51,620
So if you eat processed foods where the fiber has been removed, you are giving those there,

1163
01:07:51,780 --> 01:07:53,700
there's nothing there for the microbes to eat.

1164
01:07:53,780 --> 01:07:59,620
And so one signature of the gut microbiomes of people in the industrialized world

1165
01:07:59,860 --> 01:08:04,900
are microbes that eat gut mucus, which is an indicator that there's no fiber in there.

1166
01:08:05,060 --> 01:08:09,620
And the microbes have turned to eating the mucus that your human cells are producing to

1167
01:08:09,620 --> 01:08:10,580
line the colon.

1168
01:08:10,660 --> 01:08:14,420
That mucus layer is like what's between you and all the bacteria.

1169
01:08:14,750 --> 01:08:18,670
You want a really, really thick mucus layer for a lot of reasons.

1170
01:08:18,750 --> 01:08:20,910
It's like a sign of immune health in many ways.

1171
01:08:21,070 --> 01:08:26,270
But you know, if you if that barrier breaks down, then you end up with what we call a leaky

1172
01:08:26,270 --> 01:08:30,670
gut, which means you're prone to sepsis, and it means you're which is a blood infection,

1173
01:08:30,750 --> 01:08:35,710
and it means you're prone to just all these molecules getting into your blood, or like have

1174
01:08:35,710 --> 01:08:39,870
you ever known someone who was having appendicitis or a urinary tract infection and they

1175
01:08:39,870 --> 01:08:41,390
started hallucinating?

1176
01:08:41,600 --> 01:08:47,120
And that's because the molecules in their gut were leaking out and interfering with their

1177
01:08:47,120 --> 01:08:48,080
brain function.

1178
01:08:48,320 --> 01:08:50,640
So you want that barrier to be really strong.

1179
01:08:50,800 --> 01:08:54,880
Like one of my favorite stories in all these years of stories I've gotten to hear about

1180
01:08:54,880 --> 01:08:58,000
microbiomes was from a Swedish mucus biologist.

1181
01:08:58,240 --> 01:09:04,080
Um, and he took a he snuck a field mouse into his lab and he'd been studying

1182
01:09:04,080 --> 01:09:07,120
the mucus layer in lab mice his whole life.

1183
01:09:07,280 --> 01:09:12,790
And then he looked at this field mouse, and the mucus layer in there was like way

1184
01:09:12,790 --> 01:09:15,190
thicker, way more complicated.

1185
01:09:15,590 --> 01:09:20,870
And so that field mouse out in the world, having all of its exposures, was able to develop

1186
01:09:20,870 --> 01:09:23,830
a really, really good thick mucus lining of its gut.

1187
01:09:24,230 --> 01:09:29,030
So humans eating processed foods are basically like the lab mice.

1188
01:09:29,110 --> 01:09:34,870
Like we aren't giving our microbes the fuels they need and the our bodies the exposures

1189
01:09:34,870 --> 01:09:39,590
they need to build up a really good protective mucus layer in our gut, like that.

1190
01:09:39,820 --> 01:09:39,980
Yeah.

1191
01:09:40,220 --> 01:09:40,700
Interesting.

1192
01:09:40,860 --> 01:09:43,260
So in other words, it's not sugar per se that's bad.

1193
01:09:43,340 --> 01:09:46,220
It's sugar that's stripped of its fibrous content.

1194
01:09:46,460 --> 01:09:46,700
Exactly.

1195
01:09:46,940 --> 01:09:47,340
Which is bad.

1196
01:09:47,580 --> 01:09:47,660
Yeah.

1197
01:09:48,380 --> 01:09:49,900
And it's this oh yeah, sorry, go ahead.

1198
01:09:50,220 --> 01:09:55,980
Like juice versus or like an orange with all the fiber in it versus juice is a really big

1199
01:09:55,980 --> 01:09:56,300
difference.

1200
01:09:56,460 --> 01:10:01,020
Like if you look if you gave a bunch of people a glass of orange juice versus an orange and

1201
01:10:01,020 --> 01:10:06,620
measured their blood sugars, you would see the juice spikes everybody and the fiber um

1202
01:10:07,270 --> 01:10:08,710
buffers the spike.

1203
01:10:09,110 --> 01:10:09,510
Got it.

1204
01:10:09,750 --> 01:10:14,550
So why why are food companies uh stripping sugar of its fiber content?

1205
01:10:14,710 --> 01:10:19,350
Is it just that it give gives a more concentrated dose of sweetness or like what what is

1206
01:10:19,350 --> 01:10:20,310
the reasoning there?

1207
01:10:20,790 --> 01:10:26,390
Well I mean just think about the difference between a croissant made from white flour and

1208
01:10:26,710 --> 01:10:30,630
you know something that's really whole grainy and good.

1209
01:10:30,950 --> 01:10:36,760
And I mean I personally like whole grain like I prefer it um but but it's not the

1210
01:10:36,760 --> 01:10:37,240
standard.

1211
01:10:37,400 --> 01:10:43,320
I mean, if you go into the grocery store and most of the aisles of food, which are

1212
01:10:43,320 --> 01:10:46,600
based on what food companies think people will become addicted to.

1213
01:10:46,680 --> 01:10:50,440
I mean, they have they have done a lot of research on what people like to eat and what they

1214
01:10:50,440 --> 01:10:52,440
will become addicted to and buy more of.

1215
01:10:52,680 --> 01:10:57,000
And they that has landed them on foods that have very little fiber in them.

1216
01:10:57,160 --> 01:10:59,830
So I mean, it's it's just simpler.

1217
01:10:59,990 --> 01:11:04,150
And I mean, actually, the initial reason is kind of interesting because one of the first

1218
01:11:04,150 --> 01:11:09,830
times we started stripping wheat of fiber was around the time of the Great Depression.

1219
01:11:10,070 --> 01:11:15,270
And another and it's it's because the whole wheat it goes bad more quickly.

1220
01:11:15,430 --> 01:11:20,560
And so if you remove the fiber, which of course removes a lot of the nutrients, the fiber,

1221
01:11:20,720 --> 01:11:23,600
um, sorry, the flour will not go rancid as quickly.

1222
01:11:23,760 --> 01:11:29,200
And so during the Great Depression, I remember learning that they were processing a lot of

1223
01:11:29,200 --> 01:11:33,920
the wheat flour and putting it on unrefrigerated trucks and taking it to like the dust

1224
01:11:33,920 --> 01:11:38,080
bowl, basically, and making sure people had food, which obviously was a really good idea.

1225
01:11:38,400 --> 01:11:44,130
But um, but that was uh that was a bit of a turning point, I think, in when

1226
01:11:44,130 --> 01:11:49,570
we started having this like massive industrialized scale fiber removal

1227
01:11:49,570 --> 01:11:51,410
happening of our wheat.

1228
01:11:51,730 --> 01:11:51,970
Yeah.

1229
01:11:52,130 --> 01:11:57,010
And I like I and I keep always having my like Germany experience, but like coming back to

1230
01:11:57,010 --> 01:12:02,050
the US after 10 years away, my my overarching experience is like I feel like we're

1231
01:12:02,050 --> 01:12:07,820
children, like all the bread at the grocery store is enriched or refined

1232
01:12:07,820 --> 01:12:08,380
flour.

1233
01:12:08,540 --> 01:12:13,100
In Germany, none of it is like you can't buy something that has if you read enriched flour,

1234
01:12:13,180 --> 01:12:17,740
it means that they took the fiber out and they're just adding like stuff back, usually.

1235
01:12:17,820 --> 01:12:19,660
Like it's not usually whole grain.

1236
01:12:19,820 --> 01:12:25,010
Um, but the weird thing is when people visit Germany, or like if I like buy German bread

1237
01:12:25,010 --> 01:12:26,610
and I give it to people, people love it.

1238
01:12:26,770 --> 01:12:29,250
And people always say, I wish I could buy this here.

1239
01:12:29,410 --> 01:12:33,170
I've had so many conversations with people across the political divide.

1240
01:12:33,330 --> 01:12:33,570
Yeah.

1241
01:12:33,730 --> 01:12:38,370
You know, like even, you know, like even visiting family back home, like places that where

1242
01:12:38,370 --> 01:12:38,930
you wouldn't think.

1243
01:12:39,010 --> 01:12:41,890
And people like, oh my God, I wish like I could get German bread here.

1244
01:12:42,210 --> 01:12:47,360
I I even wonder like just this is an aside, but I even wonder if like the way people test

1245
01:12:47,680 --> 01:12:52,960
food preferences is wrong in the sense of like it's like what David said is like something

1246
01:12:52,960 --> 01:12:56,560
might taste good in a second, but then like you're like, ooh, do I want to eat more of

1247
01:12:56,560 --> 01:12:56,720
that?

1248
01:12:56,880 --> 01:12:59,280
Or do I want to come back to that or eat it a lot?

1249
01:12:59,520 --> 01:13:03,360
And I actually don't know the answer to this, but like if you just bring people in and

1250
01:13:03,360 --> 01:13:07,600
you're like, give them A, B, C, D, and E, and you're like, which do you prefer?

1251
01:13:08,400 --> 01:13:14,070
That's different than which do you feel better eating day in and day out?

1252
01:13:14,230 --> 01:13:18,390
Which do you prefer coming back to after you've felt the effects of it for a couple of

1253
01:13:18,390 --> 01:13:20,710
hours or a couple of days or a couple of weeks?

1254
01:13:20,950 --> 01:13:22,710
And I don't know if they're measuring that.

1255
01:13:22,870 --> 01:13:28,550
So like even from like a very like market-based capitalist perspective, I actually wonder

1256
01:13:28,550 --> 01:13:32,000
if like the way people are measuring desirability of food is wrong.

1257
01:13:32,160 --> 01:13:35,920
I don't know this, but this but they must also be measuring it based on what people buy.

1258
01:13:36,080 --> 01:13:37,840
I mean, those products would go out of business.

1259
01:13:38,000 --> 01:13:41,840
Like the fact that there is a waterbread section in every store means that people are

1260
01:13:41,840 --> 01:13:42,640
buying wonder bread.

1261
01:13:42,880 --> 01:13:44,720
Like I think, you know.

1262
01:13:45,040 --> 01:13:45,680
Yeah, yeah.

1263
01:13:45,760 --> 01:13:46,240
I don't know.

1264
01:13:46,400 --> 01:13:47,440
I always wonder that too.

1265
01:13:47,680 --> 01:13:51,440
Just as I'm going through the store and I see a whole section of stuff that I'm like, gosh.

1266
01:13:51,920 --> 01:13:52,320
This is garbage.

1267
01:13:52,560 --> 01:13:54,800
I might like yeah, my yeah, my head is like this is garbage.

1268
01:13:54,880 --> 01:13:56,480
You're feeding people garbage.

1269
01:13:56,720 --> 01:13:57,040
Yeah.

1270
01:13:57,280 --> 01:13:57,790
It's garb.

1271
01:13:58,110 --> 01:13:59,630
Like it's literally it's like not food.

1272
01:13:59,710 --> 01:13:59,950
Yeah.

1273
01:14:00,190 --> 01:14:00,430
Yeah.

1274
01:14:00,510 --> 01:14:03,390
But I but also it depends on how you grow up.

1275
01:14:03,470 --> 01:14:09,470
And so you know, you have to respect that, but also figure out how to

1276
01:14:09,470 --> 01:14:12,670
help people eat better, like in every situation, you know.

1277
01:14:13,070 --> 01:14:13,150
Yeah.

1278
01:14:17,070 --> 01:14:18,590
Like whatever that's money.

1279
01:14:18,750 --> 01:14:22,110
I mean, people just to be slightly political, like people talk about redistribute

1280
01:14:22,590 --> 01:14:24,780
redistribute redistribution of wealth.

1281
01:14:24,940 --> 01:14:25,180
Yeah.

1282
01:14:25,340 --> 01:14:30,860
But if you're if you're making money off of selling people unhealthy food, totally.

1283
01:14:31,100 --> 01:14:37,020
I'm paying for somebody that person's profit, I'm paying for that's money coming,

1284
01:14:37,100 --> 01:14:42,140
you know, if they get cancer or if they they're obese or whatever and they have health

1285
01:14:42,140 --> 01:14:47,950
effects and colon cancer or, you know, their kids unhealthy, whatever, we're all paying for

1286
01:14:47,950 --> 01:14:48,510
that, you know.

1287
01:14:48,590 --> 01:14:51,150
So that's a redistribution just as much as anything else.

1288
01:14:51,230 --> 01:14:51,390
Yeah.

1289
01:14:51,630 --> 01:14:52,990
That's a really interesting point.

1290
01:14:53,070 --> 01:14:54,110
I never thought about that.

1291
01:14:54,270 --> 01:14:54,910
Yeah.

1292
01:14:55,790 --> 01:15:01,470
So uh I mean, it could be that um when you strip away the fibrous content, it

1293
01:15:01,470 --> 01:15:05,550
becomes easier for your body to just quickly extract the energy from the food.

1294
01:15:05,630 --> 01:15:09,150
Whereas if there's a lot of fiber in it, as we know, if fiber sits in your gut for a long

1295
01:15:09,150 --> 01:15:12,350
time, it takes a long time to extract all the nutrients from it.

1296
01:15:12,430 --> 01:15:16,220
And so it could be that if you know, maybe we're making calculations where if we need the

1297
01:15:16,220 --> 01:15:21,020
energy right now and we're discounting the future, then more processed foods with less

1298
01:15:21,020 --> 01:15:24,220
fiber content are going to be more appealing to us because we're more concerned about

1299
01:15:24,220 --> 01:15:28,540
getting that energy boost right now versus accumulating a healthy microbiome in the long

1300
01:15:28,540 --> 01:15:28,700
run.

1301
01:15:28,780 --> 01:15:29,180
I don't know.

1302
01:15:29,260 --> 01:15:33,100
I mean, I I'm sure Daniel Nettle has lots of opinions on this because he does research on

1303
01:15:33,180 --> 01:15:39,100
uh how poverty affects uh uh uh temporal discounting and diet choices and obesity.

1304
01:15:39,180 --> 01:15:43,020
And so that that could be playing a role that if you're discounting the future more and and

1305
01:15:43,020 --> 01:15:47,690
you have more of a need for immediate energy and perhaps storing fat for future food

1306
01:15:47,690 --> 01:15:50,330
insecurity, uh, that that could contribute to this.

1307
01:15:50,730 --> 01:15:52,250
Yeah, I totally see that point.

1308
01:15:52,410 --> 01:15:57,610
And I mean, even just in terms of getting through the day, you know, it's more convenient

1309
01:15:57,610 --> 01:15:58,970
to eat processed foods.

1310
01:15:59,050 --> 01:15:59,930
You don't have to cook them.

1311
01:16:00,010 --> 01:16:02,570
I mean, it just all around just takes less resources.

1312
01:16:02,730 --> 01:16:03,450
That's true.

1313
01:16:03,690 --> 01:16:04,090
Yeah.

1314
01:16:04,250 --> 01:16:10,200
Um, but yeah, the the blood sugar, the point about the time for digestion has really

1315
01:16:10,200 --> 01:16:11,720
big blood sugar impacts.

1316
01:16:11,880 --> 01:16:17,640
And so um it's it is a good trick to know that if you include fiber in your meal,

1317
01:16:17,720 --> 01:16:23,000
um it will be much easier for your body to weather the sugar spike storm.

1318
01:16:23,160 --> 01:16:28,410
And so I think a lot of people don't know uh very much about that and that that could could

1319
01:16:28,410 --> 01:16:32,570
help people make decisions because they might not realize what the consequences are.

1320
01:16:32,730 --> 01:16:36,250
If everyone's just addicted to processed foods and not thinking about it from that

1321
01:16:36,250 --> 01:16:40,170
perspective, it's harder to make choices like that.

1322
01:16:40,410 --> 01:16:40,730
Yeah.

1323
01:16:40,970 --> 01:16:45,050
It's it's just it's funny because like it's sort of like cooking, you know, like cooking

1324
01:16:45,050 --> 01:16:48,890
with care and love and ingredients that matter is the solution.

1325
01:16:48,970 --> 01:16:51,480
And that's like a hard thing when people are busy.

1326
01:16:51,640 --> 01:16:54,920
Or I mean it's not that hard, but it you can you can imagine it's just sort of like

1327
01:16:54,920 --> 01:16:55,880
exercise and sleep.

1328
01:16:55,960 --> 01:17:01,960
You know, it's sort of like, you know, it's it's uh it's simple, straightforward, not

1329
01:17:01,960 --> 01:17:05,000
the easiest thing, maybe not the most profitable thing.

1330
01:17:05,320 --> 01:17:05,560
Yeah.

1331
01:17:05,800 --> 01:17:08,760
But but it's but it comes back to like taking an evolutionary approach.

1332
01:17:08,840 --> 01:17:13,000
Like I, you know, we we talk a lot about there's things you just wouldn't think of if you

1333
01:17:13,000 --> 01:17:14,120
don't take an evolutionary approach.

1334
01:17:14,200 --> 01:17:20,050
If you don't take the idea that we're really complicated and we evolved around a lot of

1335
01:17:20,050 --> 01:17:24,690
invariances in the environment, including the kind of food we're eating.

1336
01:17:25,010 --> 01:17:26,610
And there's a lot of ways in which we're better.

1337
01:17:26,690 --> 01:17:27,890
Like we're not killing each other.

1338
01:17:28,050 --> 01:17:32,530
We don't have to like, you know, as you said, like zoonotic infection is much lower.

1339
01:17:33,330 --> 01:17:38,770
Um, but but but it sounds like we just we're learning about this whole new area where we

1340
01:17:38,770 --> 01:17:44,260
can um we might have been doing high, high cost, low

1341
01:17:44,340 --> 01:17:45,780
benefit, dumb things.

1342
01:17:46,020 --> 01:17:51,780
And if we learn more about this new part of our phenotype that we didn't really know much

1343
01:17:51,780 --> 01:17:57,540
about, we still don't know much about, we can do some low-cost, high benefit possible.

1344
01:17:57,940 --> 01:18:01,780
Yeah, I mean, in the same way that we were just popping the antibiotics, thinking that were

1345
01:18:01,940 --> 01:18:04,420
there was only a positive outcome from that.

1346
01:18:04,990 --> 01:18:10,190
eating white flour has consequences we might not have really been aware of as we were

1347
01:18:10,190 --> 01:18:13,310
making that choice, you know, in processed foods without the fiber.

1348
01:18:13,630 --> 01:18:18,830
And I mean, we're I mean, we're PhDs in evolutionary sciences, we're learning stuff real

1349
01:18:18,830 --> 01:18:19,150
time.

1350
01:18:19,390 --> 01:18:23,630
And I mean, most people don't have the luxury of having that training.

1351
01:18:23,710 --> 01:18:24,750
And I mean, why would you think?

1352
01:18:24,990 --> 01:18:26,030
It's like it's bread, right?

1353
01:18:26,110 --> 01:18:27,630
Like bread is bread is bread, right?

1354
01:18:27,790 --> 01:18:27,950
Yeah.

1355
01:18:28,190 --> 01:18:30,510
Calories are calories are calories.

1356
01:18:30,670 --> 01:18:35,140
Um, and the idea that that's not true, you know, most people don't have the luxury of

1357
01:18:35,140 --> 01:18:38,580
learning that's not true, and there's not a lot of incentive right now.

1358
01:18:38,740 --> 01:18:42,020
Yeah, it sounds like to disabuse people of that idea.

1359
01:18:42,340 --> 01:18:47,700
Yeah, the other one that I think is kind of an important um piece of knowledge is the

1360
01:18:47,700 --> 01:18:50,580
difference between mirrorac and metamusal.

1361
01:18:50,820 --> 01:18:55,940
So a lot of people have constipation, and even kids, I know families where the kid is

1362
01:18:55,940 --> 01:18:59,620
getting mirrorac every single day to help with constipation.

1363
01:18:59,970 --> 01:19:02,930
Mirlax it comes is polyethylene glycol.

1364
01:19:03,170 --> 01:19:09,010
It's not uh fiber at all, it's um it's a molecule that causes some goopiness

1365
01:19:09,090 --> 01:19:14,130
the same way that fiber does, it draws the water out of the system, but it also the way it

1366
01:19:14,130 --> 01:19:17,810
impacts your microbiome is actually quite negative.

1367
01:19:18,050 --> 01:19:23,810
And so, for example, if you give mice antibiotics and then you compare mirlax,

1368
01:19:23,890 --> 01:19:28,820
which is polyethylene glycol, versus metamucil, which is made from psilium husks.

1369
01:19:28,900 --> 01:19:30,900
Metamucil is actually fiber.

1370
01:19:31,060 --> 01:19:35,780
Metamucil is like, you know, it's processed a bit, but it's still fiber and it came from

1371
01:19:35,780 --> 01:19:36,340
plants.

1372
01:19:36,580 --> 01:19:42,180
If you give mice antibiotics and then you give them either mirloc miralax or metamucel,

1373
01:19:42,580 --> 01:19:47,540
the mice that get mirrorax will get a terrible infection and very likely die from sepsis.

1374
01:19:47,860 --> 01:19:53,030
Whereas the um the uh mice that get the mirror the

1375
01:19:53,030 --> 01:19:57,350
metamucle, which is the orangey flavored version of psyllium husks.

1376
01:19:57,430 --> 01:19:59,430
And I mean, you can just buy psyllium husks too.

1377
01:19:59,670 --> 01:20:02,390
That's fiber, and those mice will do better.

1378
01:20:02,630 --> 01:20:07,990
So even just like from a treating constipation in the hospital or at home or whatever

1379
01:20:08,230 --> 01:20:13,190
perspective, like you can really change your infection outcomes by knowing that piece of

1380
01:20:13,190 --> 01:20:13,510
information.

1381
01:20:13,670 --> 01:20:15,750
Like a lot of doctors I know don't know that.

1382
01:20:15,990 --> 01:20:16,470
Wow.

1383
01:20:16,790 --> 01:20:22,240
So very very cool stuff, uh uh and and interesting and useful.

1384
01:20:22,480 --> 01:20:28,400
Um I'm curious, I want to go back to this uh brain in our guts, because I

1385
01:20:28,400 --> 01:20:30,080
find this quite mysterious.

1386
01:20:30,320 --> 01:20:34,720
Uh what do we have neurons down there and what are they uh what are they doing?

1387
01:20:34,960 --> 01:20:39,280
Like w what kinds of computations are these gut neurons doing?

1388
01:20:39,440 --> 01:20:41,360
Why do we have so many neurons down there?

1389
01:20:41,440 --> 01:20:43,920
I'm curious uh if you have any ideas on this question.

1390
01:20:44,250 --> 01:20:50,170
I mean, I have mostly questions myself, but you're at UCLA and I can tell you that like

1391
01:20:50,330 --> 01:20:54,970
some of the best people in the world thinking about these questions are also at UCLA.

1392
01:20:55,050 --> 01:20:58,490
So I I mean you maybe you want to invite one of them on and like I want to listen to that

1393
01:20:58,490 --> 01:20:58,890
interview.

1394
01:20:59,050 --> 01:21:00,090
But um Yeah.

1395
01:21:00,330 --> 01:21:04,170
So I mean, what are some reasons we would have neurons in our guts?

1396
01:21:04,330 --> 01:21:06,480
I mean, I don't know.

1397
01:21:06,640 --> 01:21:07,360
I really don't know.

1398
01:21:07,520 --> 01:21:12,960
I mean, I I can feel it myself, like the whole thing about butterflies in your stomach, or

1399
01:21:13,280 --> 01:21:19,280
um, you know, using our guts as part of our intuition for for like how

1400
01:21:19,280 --> 01:21:20,160
we feel about things.

1401
01:21:20,320 --> 01:21:25,680
I mean, I have experienced that myself, but I don't I I also know that societies can be

1402
01:21:25,680 --> 01:21:31,650
very tricked by um what they know about their organs, like you know, maybe you've

1403
01:21:31,650 --> 01:21:35,890
heard how in Egypt everyone thought that their brain was their thinking center was in their

1404
01:21:35,890 --> 01:21:36,370
heart.

1405
01:21:36,610 --> 01:21:36,850
Yeah.

1406
01:21:37,090 --> 01:21:38,770
I always think about what that must have felt like.

1407
01:21:38,850 --> 01:21:41,570
I mean, I don't know what they thought was going on in their brain, but apparently they

1408
01:21:41,570 --> 01:21:47,330
just when they were m um preserving bodies, they would just throw their brains

1409
01:21:47,330 --> 01:21:47,890
away.

1410
01:21:48,690 --> 01:21:50,530
They didn't even think that was important.

1411
01:21:50,930 --> 01:21:55,490
So here we are kind of learning something massive about our own bodies that we have all

1412
01:21:55,490 --> 01:21:58,980
these neurons in our guts, and are they doing?

1413
01:21:59,060 --> 01:22:04,980
I mean, clearly they're gathering information and sending that information

1414
01:22:04,980 --> 01:22:06,420
back to our brains.

1415
01:22:08,980 --> 01:22:14,660
I really like this idea that, or I mean, I think it's really important to understand that

1416
01:22:14,660 --> 01:22:19,380
you have these neuroendocrine cells that are producing hormones that affect your well-being

1417
01:22:19,380 --> 01:22:20,900
in every possible way.

1418
01:22:21,220 --> 01:22:26,990
And so if you are eating foods that promote a healthy microbiome, then you're going to

1419
01:22:26,990 --> 01:22:30,990
promote healthy communication with those neuroendocrine cells.

1420
01:22:31,790 --> 01:22:37,710
One of the biggest discoveries in this area is that we have microbes that

1421
01:22:37,710 --> 01:22:39,870
can transport serotonin.

1422
01:22:40,430 --> 01:22:43,870
And this it UCLA is a center of this research.

1423
01:22:44,030 --> 01:22:46,510
Elaine Shaw's lab has made a lot of these discoveries.

1424
01:22:46,590 --> 01:22:50,990
And we found it, I've done an Alzheimer's disease research project, and we found the same

1425
01:22:50,990 --> 01:22:51,390
thing.

1426
01:22:52,100 --> 01:22:54,820
that these microbes can transport serotonin.

1427
01:22:54,900 --> 01:23:00,580
And in my mind, it could also be that when those microbes are being sustained,

1428
01:23:00,900 --> 01:23:06,420
they are signaling to the neuroendocrine cells to also produce more serotonin.

1429
01:23:06,500 --> 01:23:07,620
So it's like a loop.

1430
01:23:07,860 --> 01:23:13,700
And so I think part of how this is all working, and the reason you have so many

1431
01:23:13,700 --> 01:23:19,590
nervous system cells in your gut is that your brain wants to like have some

1432
01:23:19,590 --> 01:23:24,710
impact on the production of these hormones and the location of their production is your

1433
01:23:24,710 --> 01:23:25,030
gut.

1434
01:23:25,510 --> 01:23:28,070
So it's like a communication system.

1435
01:23:28,390 --> 01:23:28,950
Wow.

1436
01:23:29,190 --> 01:23:35,110
And um, and when you have the right microbe there transporting

1437
01:23:35,110 --> 01:23:37,590
the serotonin, it's probably releasing signals.

1438
01:23:37,670 --> 01:23:42,150
This I don't think this is known yet, but um, you know, it's probably releasing signals

1439
01:23:42,150 --> 01:23:47,720
that tell the neuroendocrine cells like, hey, get get us some more of that serotonin going,

1440
01:23:47,800 --> 01:23:53,720
please, you know, and then that has impact on your well being for lots

1441
01:23:53,720 --> 01:23:55,080
of known and unknown reasons.

1442
01:23:55,400 --> 01:23:58,760
So the gut is a is a hormone factory.

1443
01:24:00,040 --> 01:24:03,320
Or it's the fuel for the hormone factory.

1444
01:24:03,640 --> 01:24:07,560
Yeah, there's other locations of hormone production, so it's not the only one.

1445
01:24:08,040 --> 01:24:09,000
Yes, it is an important one.

1446
01:24:09,480 --> 01:24:10,040
Fuel, right?

1447
01:24:10,120 --> 01:24:11,240
It's yeah, wow.

1448
01:24:11,480 --> 01:24:11,640
Yeah.

1449
01:24:12,090 --> 01:24:15,770
You can think of it as like, you know, the the the trucks containing the materials to build

1450
01:24:15,770 --> 01:24:16,330
the power lines.

1451
01:24:16,570 --> 01:24:16,810
Exactly.

1452
01:24:17,050 --> 01:24:20,970
You know, it's like there needs to be some communication between the power lines and what

1453
01:24:20,970 --> 01:24:24,410
materials they need to sustain themselves and the and the trucks that transport the, you

1454
01:24:24,410 --> 01:24:25,210
know, those materials.

1455
01:24:25,530 --> 01:24:25,610
Yeah.

1456
01:24:25,690 --> 01:24:30,250
And like if the trucks all get flat tires, then somebody needs to like talk about that or

1457
01:24:30,490 --> 01:24:31,530
figure out, or you know.

1458
01:24:31,770 --> 01:24:31,930
Yeah.

1459
01:24:32,090 --> 01:24:33,050
It's a really good metaphor.

1460
01:24:33,130 --> 01:24:37,770
Yeah, doing like the take a step back and be an adaptationist about like if if there's an

1461
01:24:37,770 --> 01:24:42,840
organism, what are the functions that have to be hooked up to the material delivery system?

1462
01:24:42,920 --> 01:24:45,960
And what would you want to know about what materials are being delivered, which ones are

1463
01:24:45,960 --> 01:24:47,480
low, which ones are high?

1464
01:24:47,720 --> 01:24:51,800
I mean, I find the whole thing about like craving food to be magical.

1465
01:24:51,960 --> 01:24:56,120
Like, how does my body know right that I want cantaloupe?

1466
01:24:56,280 --> 01:25:00,680
Like, how does my like what in me sort of knows there's something missing that it's in

1467
01:25:00,680 --> 01:25:05,650
cantaloupe that somehow the system that knows what a cantaloupe is, which is outside my

1468
01:25:05,650 --> 01:25:07,810
body, some part like I find this magical.

1469
01:25:08,130 --> 01:25:12,050
Yeah, I mean that to me, I've always wondered how much truth there is in that.

1470
01:25:12,210 --> 01:25:15,090
I think I've I've also always been very interested in that question.

1471
01:25:15,170 --> 01:25:19,970
And I don't really know how much how much truth is in it, but it's very interesting.

1472
01:25:20,130 --> 01:25:26,020
I mean, we also we s we now have like urban cases of scurvy, for example, where people are

1473
01:25:26,020 --> 01:25:29,380
just like eating toast even of course we do, yes.

1474
01:25:29,540 --> 01:25:33,380
And I mean, of course and maybe they really don't have access to fresh foods and so that's

1475
01:25:33,380 --> 01:25:35,860
like a societal problem and not an individual problem.

1476
01:25:36,020 --> 01:25:42,020
But I mean to me is amazing that p it'll be difficult to diagnose because it's uncommon,

1477
01:25:42,100 --> 01:25:47,950
but um but that actually happens and so yeah yeah I is there is there research like

1478
01:25:48,030 --> 01:25:52,510
this is for all of us does anybody know like the feeling of like I feel good after getting

1479
01:25:52,510 --> 01:25:58,430
exercise or I feel good after eating this kind of food is there's is there research on that

1480
01:25:58,590 --> 01:26:04,590
like it feels like in the Venn diagram of psychology and physiology and microbiology like

1481
01:26:04,670 --> 01:26:09,710
as a psychology professor you know I teach intro psych yeah I mean I I I took a motivation

1482
01:26:09,710 --> 01:26:15,380
class and that talked about like hunger and thirst maybe I'm ignorant but yeah do does it I

1483
01:26:15,380 --> 01:26:16,740
don't know, does anybody know?

1484
01:26:16,820 --> 01:26:21,940
Like, is there is there research on like the feeling good you get when you eat well or you

1485
01:26:21,940 --> 01:26:24,900
get exercise and like what's up with like is is there?

1486
01:26:25,540 --> 01:26:31,300
Yeah, I mean here at UCI we have a physiology department and there's people that work on um

1487
01:26:31,620 --> 01:26:37,140
the post exercise high and like the molecules that are released with exercise.

1488
01:26:37,300 --> 01:26:39,220
So I on that side I definitely know.

1489
01:26:39,380 --> 01:26:42,980
I don't know as much about that on the food side, but I mean there is a lot of food

1490
01:26:42,980 --> 01:26:43,540
research.

1491
01:26:43,700 --> 01:26:44,020
Yeah.

1492
01:26:44,260 --> 01:26:45,390
So I don't know.

1493
01:26:45,470 --> 01:26:46,670
Do you know, David?

1494
01:26:47,710 --> 01:26:49,150
I I honestly have no idea.

1495
01:26:49,230 --> 01:26:49,470
Yeah.

1496
01:26:49,550 --> 01:26:55,550
It's just it's uh there's just so many questions, such a vast field to I mean,

1497
01:26:55,710 --> 01:26:58,750
even just like the subtlety of our food cravings.

1498
01:26:58,910 --> 01:27:03,310
Like I often have like a strong craving for pickles or something or or whatever, and like

1499
01:27:03,470 --> 01:27:08,430
uh and I I feel gross after like eating something that's like really greasy and heavy and I

1500
01:27:08,430 --> 01:27:11,660
just wanna you know get go into a food coma is the is the expression.

1501
01:27:11,820 --> 01:27:14,220
But other foods that they don't have that effect on me.

1502
01:27:14,300 --> 01:27:20,220
And the like just these subtle uh effects that that specific kinds of foods have on

1503
01:27:20,220 --> 01:27:20,380
us.

1504
01:27:20,460 --> 01:27:23,340
I feel like it's such an understudied and important topic.

1505
01:27:23,740 --> 01:27:23,980
Yeah.

1506
01:27:24,380 --> 01:27:29,180
Or just even the difference between cats and dogs, where like cats don't overdo it, and

1507
01:27:29,180 --> 01:27:32,140
dogs are more like us, and they'll just like eat themselves to death.

1508
01:27:32,540 --> 01:27:38,310
Although, although I had a cat who is a main part main coon, and boy, she would eat the The

1509
01:27:38,310 --> 01:27:41,270
vet was like, it was like, yeah, you can't give her all the food she wants.

1510
01:27:41,350 --> 01:27:42,630
Like, you can't do outlips.

1511
01:27:43,590 --> 01:27:48,710
Um, we before uh um, you know, we were we're not at the end yet, but we're getting closer

1512
01:27:48,710 --> 01:27:49,030
to the end.

1513
01:27:49,110 --> 01:27:53,910
I do want to ask you, you mentioned something about phages and amazing work you're doing on

1514
01:27:53,910 --> 01:27:54,070
that.

1515
01:27:54,390 --> 01:28:00,060
Can you talk a little bit about what is a phage and what are you doing with them to uh

1516
01:28:00,060 --> 01:28:01,020
help people?

1517
01:28:01,580 --> 01:28:02,140
Yeah.

1518
01:28:02,540 --> 01:28:03,020
Thank you.

1519
01:28:03,180 --> 01:28:06,700
Um, so phages are viruses that infect bacteria.

1520
01:28:06,780 --> 01:28:11,420
And so basically, every cell on the planet has viruses infecting them.

1521
01:28:11,500 --> 01:28:16,140
So we hear about the famous viruses like HIV and COVID, but they're rare.

1522
01:28:16,300 --> 01:28:19,820
Most viruses are not pathogens, but there are viruses everywhere.

1523
01:28:19,980 --> 01:28:23,660
So every single one of these bacteria that we've been talking about in our microbiomes

1524
01:28:23,900 --> 01:28:26,300
probably has about 10 viruses infecting it.

1525
01:28:26,730 --> 01:28:27,050
Wow.

1526
01:28:27,370 --> 01:28:29,610
That's very comp it's things are complicated.

1527
01:28:29,850 --> 01:28:30,170
Yeah.

1528
01:28:30,490 --> 01:28:32,890
We're just we're just Russian dolls of things inside of things.

1529
01:28:33,210 --> 01:28:33,690
Oh my God.

1530
01:28:34,010 --> 01:28:34,250
Exactly.

1531
01:28:34,410 --> 01:28:39,610
Russian dolls of sometimes it's almost like I wish I wasn't a Darwinian worldview person.

1532
01:28:39,770 --> 01:28:44,250
Just like everything is simple and like it's like, oh my God, like the have the bacteria

1533
01:28:44,250 --> 01:28:47,210
have this whole world of yeah that's crazy.

1534
01:28:47,290 --> 01:28:47,850
And that's wonderful.

1535
01:28:47,930 --> 01:28:52,810
But yeah, please well it's I mean it helped it's viruses like really help make the world

1536
01:28:52,810 --> 01:28:53,050
work.

1537
01:28:53,130 --> 01:28:58,400
You know, viruses can evolve quickly, they can like bring new traits really quickly.

1538
01:28:58,560 --> 01:29:03,840
Like if you give antibiotics to somebody and then you measure all the antibiotic resistance

1539
01:29:03,840 --> 01:29:08,560
genes that have emerged out of that system, a lot of them come from viruses moving between

1540
01:29:08,560 --> 01:29:10,080
cells and sharing that trait.

1541
01:29:10,240 --> 01:29:13,840
And then it's like that trait became pretty important right then because the antibiotic is

1542
01:29:13,840 --> 01:29:15,600
coming through and gets selected for.

1543
01:29:15,760 --> 01:29:20,480
And so then all of a sudden every bacteria that could take on a virus that could help it

1544
01:29:20,480 --> 01:29:22,400
get that trait is the one that would survive.

1545
01:29:22,480 --> 01:29:26,510
You know, so you could see how there's like sweeps of selection pressures where the viruses

1546
01:29:26,670 --> 01:29:30,670
bring traits that are like the money move that makes them survive, you know.

1547
01:29:31,070 --> 01:29:31,230
Yeah.

1548
01:29:31,310 --> 01:29:35,950
So viruses are like the closest thing to like pure natural selection almost.

1549
01:29:36,030 --> 01:29:41,470
They're just like this like really uh supernaturally selected minimal phenotype things,

1550
01:29:41,550 --> 01:29:41,870
like almost.

1551
01:29:42,110 --> 01:29:45,150
Yeah, I mean maybe they literally they're just selfish genes, that's all they are.

1552
01:29:45,630 --> 01:29:45,950
Yeah.

1553
01:29:47,390 --> 01:29:53,040
So as a result, I mean, just there are all these viruses, bacterial viruses,

1554
01:29:53,440 --> 01:29:57,600
and um and they are the enemy of our enemy sometimes.

1555
01:29:57,680 --> 01:30:03,040
So if you have an infection with a pathogen and antibiotics aren't working anymore, you

1556
01:30:03,040 --> 01:30:06,720
could use a virus, a phage, to kill that bacteria.

1557
01:30:06,880 --> 01:30:08,160
And it's not a new idea.

1558
01:30:08,320 --> 01:30:11,520
It's actually been known since before we had antibiotics.

1559
01:30:11,680 --> 01:30:16,310
And so before we had antibiotics, people were using phages to treat infections.

1560
01:30:16,790 --> 01:30:21,590
When Elizabeth Taylor was filming Cleopatra in England, she got a staph infection and they

1561
01:30:21,590 --> 01:30:24,150
treated her infection with a phage and she survived.

1562
01:30:24,470 --> 01:30:26,470
And there's like a lot of stories like that.

1563
01:30:26,950 --> 01:30:31,750
And actually, in the former Soviet republics, that type of treatment continued.

1564
01:30:31,830 --> 01:30:36,950
And so when antibiotics became big in the US and Europe, there was less access in the

1565
01:30:36,950 --> 01:30:40,280
USSR, and people kept going with phages.

1566
01:30:40,440 --> 01:30:46,040
So, for example, at the Eliava Institute in Tbilisi, Georgia, phages are produced to treat

1567
01:30:46,040 --> 01:30:50,520
infections, and that's like the most normal way to handle bacterial infections in that part

1568
01:30:50,520 --> 01:30:51,080
of the world.

1569
01:30:51,240 --> 01:30:52,680
So it's like really continued.

1570
01:30:52,760 --> 01:30:57,320
We have some evidence, or I mean, kind of a lot of evidence, but it's not been formally

1571
01:30:57,480 --> 01:31:01,160
clinically researched from all of that activity.

1572
01:31:01,650 --> 01:31:07,170
And then as more and more antibiotic resistant infections have started to emerge in our

1573
01:31:07,170 --> 01:31:10,850
part of the world, there's been a resurgence of interest in the phages.

1574
01:31:11,410 --> 01:31:15,650
And so I started studying them more like from an ecology perspective, like what kind of

1575
01:31:15,650 --> 01:31:20,050
viruses are there in people, like probably 10 or 15 years ago.

1576
01:31:20,530 --> 01:31:25,010
But then I started getting requests from people who had terrible infections, like, can you

1577
01:31:25,010 --> 01:31:28,450
find a phage that will infect my bacteria?

1578
01:31:28,690 --> 01:31:34,120
And so the student the students here at UC Irvine are very enthusiastic about the prospect

1579
01:31:34,120 --> 01:31:36,040
of helping someone in a wonderful way.

1580
01:31:36,120 --> 01:31:42,040
And so basically, I've had this team of students hunting phages against infecting pathogens

1581
01:31:42,040 --> 01:31:43,800
for like more than 10 years.

1582
01:31:43,960 --> 01:31:49,560
And so we get wastewater samples from local SoCal wastewater

1583
01:31:49,560 --> 01:31:50,760
treatment plants.

1584
01:31:51,000 --> 01:31:56,870
And wastewater actually is a wonderful summarized source of

1585
01:31:56,870 --> 01:32:01,910
information about all of the human infections and bacteria.

1586
01:32:02,310 --> 01:32:05,110
So there's tons and tons of phages in wastewater.

1587
01:32:05,190 --> 01:32:07,590
And this is a this is a common approach.

1588
01:32:07,750 --> 01:32:10,390
There's dozens of labs around the world doing this.

1589
01:32:10,630 --> 01:32:15,990
And so we'll get the pathogen from the clinical microlab, we'll hunt a phage out of the

1590
01:32:15,990 --> 01:32:16,870
wastewater.

1591
01:32:17,110 --> 01:32:21,860
We're usually able to find a phage, and now we have several hundred in our freezers from

1592
01:32:21,860 --> 01:32:23,540
all this year, all these years of searching.

1593
01:32:23,700 --> 01:32:27,380
So now when we get a new isolate in, we check our freezers first.

1594
01:32:27,460 --> 01:32:30,260
And if none of those work, then we'll go hunt a new phage.

1595
01:32:30,500 --> 01:32:34,820
And now we also I have a cold room with like a collection of wastewater, and the same way

1596
01:32:34,820 --> 01:32:38,900
some people collect wine, we did wastewater.

1597
01:32:39,780 --> 01:32:42,580
And we know Riverside 2020, right?

1598
01:32:42,740 --> 01:32:43,540
Or something like that.

1599
01:32:43,620 --> 01:32:43,860
Yeah.

1600
01:32:44,180 --> 01:32:44,820
No, for real.

1601
01:32:44,900 --> 01:32:50,830
Like there's this one sample from Escondido in 2020 that always has

1602
01:32:50,830 --> 01:32:52,510
stenotropomonas phages in it.

1603
01:32:52,590 --> 01:32:55,550
So when we can't find a stenophage, we're like go back to that one.

1604
01:32:55,710 --> 01:33:00,910
And then, you know, the students have sometimes the students have connections to different

1605
01:33:00,910 --> 01:33:02,190
wastewater treatment plants.

1606
01:33:02,270 --> 01:33:05,470
Like one of them had a dad who worked at one, or another student.

1607
01:33:05,870 --> 01:33:06,190
Amazing.

1608
01:33:06,430 --> 01:33:06,590
Yeah.

1609
01:33:06,670 --> 01:33:10,030
And then they'll like know how to get a new kind of wastewater into the system for us.

1610
01:33:10,350 --> 01:33:11,950
So you're like a phage sommelier.

1611
01:33:12,110 --> 01:33:13,470
You're like, you're like, yeah.

1612
01:33:13,840 --> 01:33:17,120
I think we should do Escondino 2020 for this.

1613
01:33:17,200 --> 01:33:18,400
Maybe that's a good place to start.

1614
01:33:18,480 --> 01:33:18,640
Yeah.

1615
01:33:18,880 --> 01:33:23,520
And actually we had when the pandemic hit, we had wastewater from the Orange County

1616
01:33:23,520 --> 01:33:28,240
Sanitation District that we had collected every two weeks for the year before the pandemic

1617
01:33:28,240 --> 01:33:28,720
started.

1618
01:33:28,880 --> 01:33:34,160
And it got us into a whole wastewater sequencing project, um, which is a different story.

1619
01:33:34,320 --> 01:33:36,640
But um and that really has persisted.

1620
01:33:36,800 --> 01:33:41,210
Now there's actual wastewater surveillance happening at a national level with like real

1621
01:33:41,290 --> 01:33:42,570
relatively good infrastructure.

1622
01:33:42,650 --> 01:33:43,210
It's pretty cool.

1623
01:33:43,450 --> 01:33:43,610
Wow.

1624
01:33:43,690 --> 01:33:48,330
And just to clarify, so all this, the main mechanism is just differential reproductive

1625
01:33:48,330 --> 01:33:48,570
success.

1626
01:33:48,730 --> 01:33:53,690
So you basically expose something, you're like, this is the um the thing, the bacteria we

1627
01:33:53,690 --> 01:33:54,970
want to destroy.

1628
01:33:55,130 --> 01:34:01,130
Um we sort of just see uh if there's something that sort of can differentially infect it

1629
01:34:01,130 --> 01:34:02,090
or affect it.

1630
01:34:02,660 --> 01:34:02,820
Right.

1631
01:34:02,980 --> 01:34:08,420
Like if you if you have a bacterial community, an infection growing in your body and the

1632
01:34:08,420 --> 01:34:10,500
antibiotics are not are not working.

1633
01:34:10,580 --> 01:34:15,620
So the bacteria is resistant to the antibiotics, but you find a phage that can infect that

1634
01:34:15,620 --> 01:34:21,540
bacteria, you treat the person with that phage, the virus will infect the cells and pop

1635
01:34:21,540 --> 01:34:22,580
them open and kill them.

1636
01:34:22,870 --> 01:34:23,030
Right.

1637
01:34:23,190 --> 01:34:28,390
And even if it doesn't kill all of them, what what I hope for is just like a bit of a

1638
01:34:28,390 --> 01:34:28,710
boost.

1639
01:34:28,870 --> 01:34:33,510
So like sometimes we find that there's synergy where when you combine the antibiotics and

1640
01:34:33,510 --> 01:34:36,310
the phages, the antibiotics work a little better too.

1641
01:34:36,470 --> 01:34:39,750
So maybe like as a team, they can do the infection better.

1642
01:34:39,830 --> 01:34:41,430
And then you've got your immune system.

1643
01:34:41,590 --> 01:34:41,830
Yeah.

1644
01:34:41,990 --> 01:34:47,680
So between the antibiotic, the phage, and the immune system, you now have like a new handle

1645
01:34:47,680 --> 01:34:48,640
on the infection, basically.

1646
01:34:49,040 --> 01:34:49,440
Dream two.

1647
01:34:49,760 --> 01:34:50,240
Yeah, exactly.

1648
01:34:50,400 --> 01:34:56,160
How do you how do you so you have a sample of the bacteria and you have wastewater, how do

1649
01:34:56,160 --> 01:35:00,960
you tell which phage is or how do you get the how do you go from wastewater and your

1650
01:35:00,960 --> 01:35:01,360
sample?

1651
01:35:01,520 --> 01:35:01,920
What's that?

1652
01:35:02,160 --> 01:35:03,200
Yeah, great question.

1653
01:35:03,440 --> 01:35:07,680
So we grow up the bacteria that we want to be able to infect.

1654
01:35:07,950 --> 01:35:10,910
And then we add a little bit of wastewater to it.

1655
01:35:11,150 --> 01:35:16,190
And then we it we filter the wastewater so there's less bacterial cells and there's more

1656
01:35:16,430 --> 01:35:18,030
smaller viruses in there.

1657
01:35:18,270 --> 01:35:22,670
And then we pour an agar plate that you've probably seen an image of before.

1658
01:35:22,750 --> 01:35:27,070
And there's like some details that you have to like kind of change the texture of the agar

1659
01:35:27,230 --> 01:35:29,230
to make the phages be able to show up.

1660
01:35:29,470 --> 01:35:34,270
But then what you'll end up with if you succeed, the next day you'll come in and you'll

1661
01:35:34,270 --> 01:35:40,020
find a white bacterial lawn that has little clearance zones, little circles, and those

1662
01:35:40,020 --> 01:35:43,060
represent a phage eating the white bacterial background.

1663
01:35:43,540 --> 01:35:45,220
So if you come in and we call it a plaque.

1664
01:35:45,300 --> 01:35:49,620
So if you come in and you've done your plaque assay and you see some plaques, some little

1665
01:35:49,620 --> 01:35:53,140
clearances where the phage killed the bacteria, that's your phage.

1666
01:35:53,460 --> 01:35:58,740
And it's usually like a big mix the first t time, and then you have to like purify it a

1667
01:35:58,740 --> 01:36:01,220
bunch of times to try to get it down to being one phage.

1668
01:36:01,460 --> 01:36:01,620
Right.

1669
01:36:01,700 --> 01:36:03,540
So you're it's art it's artificial selection.

1670
01:36:03,620 --> 01:36:08,970
So you're basically just saying, like, look, here's the victim hopefully yeah the bacteria

1671
01:36:09,130 --> 01:36:13,850
and you're just making little battlefields and then you're just sort of like is there

1672
01:36:13,850 --> 01:36:19,610
something that is I'm gonna look to see that actually kills this that's replicating

1673
01:36:19,690 --> 01:36:23,530
based on the fact that it's killing it and that's how you discover it.

1674
01:36:23,850 --> 01:36:24,970
Yes, exactly.

1675
01:36:25,210 --> 01:36:25,450
Cool.

1676
01:36:25,530 --> 01:36:26,760
So you're artificially selecting.

1677
01:36:26,840 --> 01:36:26,920
Yeah.

1678
01:36:27,240 --> 01:36:31,320
And then from there, I mean, the amazing part is that there aren't just like companies

1679
01:36:31,320 --> 01:36:32,920
manufacturing phages right now.

1680
01:36:33,000 --> 01:36:36,360
And it and antibiotics have a weird economics to them.

1681
01:36:36,520 --> 01:36:38,440
Um, they're not chronic medicines.

1682
01:36:38,520 --> 01:36:44,040
Like blockbuster meds are like statins or you know, Ozempic, something people will need for

1683
01:36:44,040 --> 01:36:44,600
a long time.

1684
01:36:44,680 --> 01:36:47,480
So the they're chronic and can be profitable.

1685
01:36:47,640 --> 01:36:51,800
Antibiotics are these acute treatments and pharma has not been investing in them because

1686
01:36:51,800 --> 01:36:53,890
they don't pay back the RD.

1687
01:36:54,370 --> 01:36:57,330
And the government hasn't really been investing in them very much either.

1688
01:36:57,490 --> 01:37:01,490
So there's been a real lag in antibiotic discovery in the last couple of decades.

1689
01:37:01,890 --> 01:37:04,690
Meantime, the infections are getting worse and worse.

1690
01:37:04,770 --> 01:37:08,370
And so like the predictions for how many antibiotic-resistant infections we're going to

1691
01:37:08,370 --> 01:37:11,090
have in the next couple of decades are like staggering.

1692
01:37:11,170 --> 01:37:15,820
Like more people will die from antibiotic-resistant infections than cancer by the next

1693
01:37:15,820 --> 01:37:16,700
decade or two.

1694
01:37:16,940 --> 01:37:20,220
So there's like a lot of motivation to find alternatives.

1695
01:37:20,300 --> 01:37:24,460
And the phages are an alternative, but they're still a little bit homemade.

1696
01:37:24,540 --> 01:37:26,860
Like we don't have them at an industrial scale at all.

1697
01:37:27,020 --> 01:37:31,580
So literally, labs like mine, like academic labs, I am not a pharmaceutical person.

1698
01:37:31,660 --> 01:37:35,020
I'm like a I normally teach undergrads micro, you know what I mean?

1699
01:37:35,500 --> 01:37:39,050
And um people in my lab will produce the phage.

1700
01:37:39,450 --> 01:37:43,690
Um, and we'll follow we you each phage will be really finicky and we'll have to come up

1701
01:37:43,690 --> 01:37:47,610
with a kind of specific protocol that that particular phage will cooperate with.

1702
01:37:47,770 --> 01:37:53,130
And then we'll write down our method and send it to the FDA and ask them if they approve us

1703
01:37:53,130 --> 01:37:54,010
to use this treatment.

1704
01:37:54,090 --> 01:38:00,010
And we also take the phage and send it for third-party sterility and endotoxin testing so

1705
01:38:00,010 --> 01:38:03,690
that it's not just our lab saying, like, yep, we think it's sterile, you know.

1706
01:38:03,850 --> 01:38:04,170
Yeah.

1707
01:38:04,400 --> 01:38:09,440
Um, and then and then that's in the United States, there's three or four labs doing this.

1708
01:38:09,520 --> 01:38:14,400
And I'd say in the last five or ten years, like less than a hundred people have received

1709
01:38:14,400 --> 01:38:15,360
treatment like this.

1710
01:38:15,600 --> 01:38:20,880
Um, but we have we've we did one case last year and we have like about 20 cases that were

1711
01:38:20,960 --> 01:38:23,360
like in the middle of trying to produce phages for people.

1712
01:38:23,760 --> 01:38:28,080
And a case means like what's the one case like it's literally somebody who is like, I have

1713
01:38:28,080 --> 01:38:33,550
a a disease or an infection that I can't I that I don't know that the yeah, what is can you

1714
01:38:33,710 --> 01:38:35,070
yeah, what is Yeah, definitely.

1715
01:38:35,150 --> 01:38:39,710
So um it a case is we we asked for the cases to be more chronic.

1716
01:38:39,790 --> 01:38:43,790
Initially, we were taking on these really acute cases where someone was about to die from

1717
01:38:43,790 --> 01:38:48,030
an infection, and then my students would stay all weekend to find a phage and they would

1718
01:38:48,030 --> 01:38:51,070
find one and then the person would die and nobody helped anybody.

1719
01:38:51,230 --> 01:38:55,550
And it we did isolate phages that way, but I just realized this made no sense that we

1720
01:38:55,550 --> 01:38:56,750
weren't actually helping anyone.

1721
01:38:56,830 --> 01:39:01,260
It was like we were giving false hope to the family, and the students were like over

1722
01:39:01,820 --> 01:39:02,220
heartbreaking.

1723
01:39:02,300 --> 01:39:02,780
It's heartbreaking.

1724
01:39:03,100 --> 01:39:04,620
Heartbroken at the end of it, exactly.

1725
01:39:04,780 --> 01:39:10,300
So I changed tax about a year ago and I said that we would accept chronic cases.

1726
01:39:10,460 --> 01:39:14,860
So we would accept cases where it would be okay if it took us a year to produce the phage,

1727
01:39:14,940 --> 01:39:16,940
because in reality, that's what it takes.

1728
01:39:17,180 --> 01:39:22,860
And so um, so the case we did, we actually made it all the way through and actually got to

1729
01:39:22,860 --> 01:39:28,550
help someone last year was um a woman who had sinusitis and nose infection for 10

1730
01:39:28,550 --> 01:39:28,870
years.

1731
01:39:28,950 --> 01:39:30,470
And actually, your sinuses are amazing.

1732
01:39:30,550 --> 01:39:32,150
They like go way back into your head.

1733
01:39:32,390 --> 01:39:35,030
And she had staph in there for 10 years.

1734
01:39:35,190 --> 01:39:36,710
She kept getting fevers.

1735
01:39:36,870 --> 01:39:41,350
So she would just, she was living her life with like getting a terrible fever every week or

1736
01:39:41,350 --> 01:39:41,590
two.

1737
01:39:41,750 --> 01:39:45,510
And the antibiotics weren't really, they would maybe help a little, but then the fever

1738
01:39:45,510 --> 01:39:46,630
would be right back.

1739
01:39:46,870 --> 01:39:52,860
Um, and so the infectious disease doctor identified her as a good candidate because

1740
01:39:52,860 --> 01:39:55,500
it was chronic, but it was really affecting her life.

1741
01:39:55,820 --> 01:39:58,940
And so it was worth the risk of trying something new.

1742
01:39:59,180 --> 01:40:02,780
And so we got the staff isolate from the clinical microlab.

1743
01:40:02,860 --> 01:40:05,180
And actually, this that was a really hard phage to find.

1744
01:40:05,340 --> 01:40:07,980
Like I think we looked for about six months unsuccessfully.

1745
01:40:08,060 --> 01:40:12,780
And I have this one star student who trained a new medical resident one week.

1746
01:40:13,050 --> 01:40:17,210
And on that medical resident's first try, she found the phage.

1747
01:40:17,370 --> 01:40:21,130
So they're either she was lucky with whatever piece of wastewater she was using, or she

1748
01:40:21,130 --> 01:40:24,250
just had slightly different technique, or you know, we'll never know.

1749
01:40:24,410 --> 01:40:30,330
Um, and we named the phage Ludmilla, and then we spent about six months coming

1750
01:40:30,330 --> 01:40:35,130
up with all the methods for producing it and getting it checked and everything, and then we

1751
01:40:35,220 --> 01:40:39,220
submitted paperwork to the FDA, and that was a couple months.

1752
01:40:39,380 --> 01:40:44,820
Um, and then we had to get approval from the hospital here at UCI and the ethics board, and

1753
01:40:44,820 --> 01:40:45,540
that was a couple months.

1754
01:40:45,700 --> 01:40:49,140
So I don't know, it's like it's hard to see where a year went, but I actually made a

1755
01:40:49,140 --> 01:40:52,580
timeline and you can see just like what dates things happened.

1756
01:40:53,220 --> 01:40:55,620
There were just months between a lot of these steps.

1757
01:40:55,860 --> 01:41:00,420
But finally in July, we had permission, and I remember the day the student who had produced

1758
01:41:00,420 --> 01:41:02,740
the phage Ritwick is his name.

1759
01:41:03,510 --> 01:41:08,390
He like went and bought a fresh cooler and he he got fresh lab coats and anytime he opened

1760
01:41:08,390 --> 01:41:12,390
the fridge that we bought a special fridge that only this phage could go into and he he

1761
01:41:12,390 --> 01:41:14,470
only opened it twice, I think.

1762
01:41:14,630 --> 01:41:19,030
And he'd put a fresh lab coat on and get the phage out of that fridge and put it into the

1763
01:41:19,030 --> 01:41:19,750
brand new cooler.

1764
01:41:19,830 --> 01:41:22,390
We were like trying to just be really clean about everything, you know.

1765
01:41:22,940 --> 01:41:28,060
And uh and he drove it over to the hospital, and the pharmacist uh mixed up the right dose,

1766
01:41:28,140 --> 01:41:33,820
um, which was actually another whole project of getting the pharmacy to be okay with how we

1767
01:41:33,820 --> 01:41:34,380
were doing things.

1768
01:41:34,460 --> 01:41:37,740
So each step just took a lot of organization.

1769
01:41:37,900 --> 01:41:43,580
Um, but then the person finally got to try this phage, uh, she put it into her um

1770
01:41:43,900 --> 01:41:49,100
nasal rinse every evening, like essentially with a neti pot, but with distilled water, and

1771
01:41:49,100 --> 01:41:54,470
added the phage to that, and then she rinsed every night for six weeks.

1772
01:41:54,630 --> 01:41:58,390
And then the treatment ended last September.

1773
01:41:59,030 --> 01:42:04,470
And I just learned on like two days ago that the fevers have remained gone.

1774
01:42:04,630 --> 01:42:06,150
Like the fevers have not come back.

1775
01:42:06,310 --> 01:42:10,870
So that to me is like I wasn't like a month later, I was glad she was doing better, but I

1776
01:42:10,870 --> 01:42:12,310
wasn't like sure we had helped.

1777
01:42:12,870 --> 01:42:18,200
But now that it's been almost half a year and she still doesn't have the fevers, it feels

1778
01:42:18,200 --> 01:42:22,040
like that was just really good news that I mean, of course, I understand the infection can

1779
01:42:22,040 --> 01:42:25,320
come back, but it'd be nice if this effort had some impact.

1780
01:42:25,640 --> 01:42:31,000
And um and yeah, so I think that she hasn't had to take antibiotics again and her

1781
01:42:31,000 --> 01:42:34,120
inflammation is much better and she hasn't had the fevers come back.

1782
01:42:34,280 --> 01:42:35,960
She went on a trip to Italy, I heard.

1783
01:42:36,210 --> 01:42:36,610
Amazing.

1784
01:42:36,850 --> 01:42:38,130
So really live in, that's good.

1785
01:42:38,530 --> 01:42:44,210
You got to have some of the the better uh uh uh flour is is the difficulty it sounds like

1786
01:42:44,210 --> 01:42:49,410
it was it was it sounds like you're taking on a lot of costs to do this that you wouldn't

1787
01:42:49,410 --> 01:42:55,330
need to is that because there's not infrastructure to

1788
01:42:55,650 --> 01:43:01,600
do this and because you're basic because you're a basic scientist in a good way, like we're

1789
01:43:01,600 --> 01:43:02,960
big we're basic scientists too.

1790
01:43:03,120 --> 01:43:05,200
Yeah, you're you're doing this extra.

1791
01:43:05,440 --> 01:43:09,120
This is like you're at the the the pointy end of innovation.

1792
01:43:09,360 --> 01:43:15,360
And ideally in the future, there would be mechanisms to offload

1793
01:43:15,360 --> 01:43:20,890
this regulation work and the production work, but it's just because you're so new, this is

1794
01:43:20,890 --> 01:43:23,530
so early days that you have to do everything.

1795
01:43:23,930 --> 01:43:24,810
Yeah, in some ways.

1796
01:43:24,970 --> 01:43:27,130
In other ways, we've known about this for a hundred years.

1797
01:43:27,290 --> 01:43:30,010
And so why are there not companies doing this?

1798
01:43:30,170 --> 01:43:35,290
That just has to do with the way our medical system is organized, that there isn't really

1799
01:43:35,290 --> 01:43:36,730
room for an operation like this.

1800
01:43:36,890 --> 01:43:38,330
I mean, it's it's a bit crazy.

1801
01:43:38,410 --> 01:43:40,250
It's not going to be profitable.

1802
01:43:40,490 --> 01:43:46,090
Um, the reason I'm able to do it mainly in this case is because of this amazing student who

1803
01:43:46,090 --> 01:43:48,040
cared so much about doing it?

1804
01:43:48,200 --> 01:43:52,200
He's he he started working in my lab as a high school student and he's about to graduate

1805
01:43:52,200 --> 01:43:52,600
college.

1806
01:43:52,680 --> 01:43:55,240
So he had a lot of time to learn all these skills.

1807
01:43:55,480 --> 01:43:59,400
And to be honest, he is the driving force that the reason that this happened, because it

1808
01:43:59,400 --> 01:44:00,760
was a lot of work for him.

1809
01:44:01,000 --> 01:44:05,160
Um and it's the kind of work where if I tried to hire someone to do that work, it would

1810
01:44:05,160 --> 01:44:09,080
cost a lot more money than I could ever get to pay them because there aren't like research

1811
01:44:09,080 --> 01:44:10,920
grants to pay someone to do this.

1812
01:44:11,400 --> 01:44:17,230
But um, but most of the labs doing this have some secret source of money that they figured

1813
01:44:17,230 --> 01:44:21,390
out because it's not a typical research grant, or they're just kind of using their research

1814
01:44:21,390 --> 01:44:24,030
grants on the side to get this kind of work done.

1815
01:44:24,190 --> 01:44:26,510
Um, so that yeah, it's hard to get funding for it.

1816
01:44:26,670 --> 01:44:32,190
We just applied for a big ARPA H grant um to build a network across the country that would

1817
01:44:32,190 --> 01:44:35,710
help um give phages to people more quickly.

1818
01:44:35,950 --> 01:44:40,510
And we'd be, you know, we we would like to figure out how to build a network like that

1819
01:44:40,510 --> 01:44:40,910
better.

1820
01:44:41,460 --> 01:44:46,980
Do you feel like the regulations are reasonable given the

1821
01:44:47,300 --> 01:44:52,980
costs, or or is it just that the regulations are unwieldy and

1822
01:44:53,220 --> 01:44:58,500
designed for larger entities that might have more money than you?

1823
01:44:58,820 --> 01:44:59,540
You know what I mean?

1824
01:44:59,700 --> 01:45:05,460
Like yeah, I honestly the the FDA's compassionate exemption route is

1825
01:45:05,460 --> 01:45:07,460
functioning pretty well, in my opinion.

1826
01:45:07,620 --> 01:45:13,010
And in fact, um, yeah, we had an experience in the middle of all those amendments where

1827
01:45:13,010 --> 01:45:17,250
they disagreed with one of the steps in one of our protocols, or I don't know if disagree

1828
01:45:17,330 --> 01:45:19,330
is the right word, but they were like not gonna approve it.

1829
01:45:19,490 --> 01:45:22,930
But then they just like had an alternative suggestion that worked great.

1830
01:45:23,010 --> 01:45:24,530
So it wasn't it didn't stop us.

1831
01:45:24,610 --> 01:45:26,530
So I actually felt like that was pretty functional.

1832
01:45:26,690 --> 01:45:29,970
Like I was worried that we were gonna do all that work and then it was just gonna be

1833
01:45:30,040 --> 01:45:32,280
rejected and down the drain or something.

1834
01:45:32,440 --> 01:45:34,760
So I actually thought they worked pretty well with us.

1835
01:45:35,000 --> 01:45:35,400
Agreed.

1836
01:45:35,720 --> 01:45:39,320
But I think science funding in general is in a bit of a crisis right now.

1837
01:45:39,480 --> 01:45:42,920
Like it's kind of a strange system that you guys are obviously very familiar with.

1838
01:45:43,080 --> 01:45:45,000
But you know, you get a job in a university.

1839
01:45:45,160 --> 01:45:47,160
If you're lucky, your own salary is paid.

1840
01:45:47,240 --> 01:45:53,240
But to actually do any science, you need funds to support staff and re resources for your

1841
01:45:53,240 --> 01:45:58,450
lab and like where those funds come from is those sources are like all

1842
01:45:58,450 --> 01:46:00,050
disappearing all the time.

1843
01:46:00,370 --> 01:46:00,770
Yeah.

1844
01:46:01,010 --> 01:46:05,650
So you know it's just it's hard to get to do stuff with science these days.

1845
01:46:06,210 --> 01:46:06,370
Yeah.

1846
01:46:06,530 --> 01:46:11,330
And it's just but it's and just to put the period on it, you literally change somebody's

1847
01:46:11,330 --> 01:46:11,570
life.

1848
01:46:11,730 --> 01:46:14,690
I mean, doing this basic science, it's really amazing.

1849
01:46:14,770 --> 01:46:15,090
Yeah.

1850
01:46:15,440 --> 01:46:15,760
Yeah.

1851
01:46:15,920 --> 01:46:20,640
That is a really cool thing about this about the microbiome field in general, that it's

1852
01:46:20,720 --> 01:46:25,360
like right at the edge of translation and like we know enough to be able to do things that

1853
01:46:25,360 --> 01:46:29,200
are actually directly causing a treatment for someone.

1854
01:46:29,440 --> 01:46:29,680
Yeah.

1855
01:46:29,840 --> 01:46:33,920
So yeah, that is pretty cool because a lot of basic science you don't get to see the

1856
01:46:33,920 --> 01:46:34,960
outcome for decades.

1857
01:46:35,200 --> 01:46:35,360
Yeah.

1858
01:46:35,600 --> 01:46:38,000
Do you have a good John Patton story?

1859
01:46:38,550 --> 01:46:41,110
Oh gosh, what a good question.

1860
01:46:41,510 --> 01:46:43,350
Oh, I probably have a lot.

1861
01:46:43,510 --> 01:46:47,910
Um well, I mean, maybe I'll just leave, I'll just share one.

1862
01:46:47,990 --> 01:46:52,790
Like he would often come by our lab and talk, and he'd stick around for hours and we loved

1863
01:46:52,790 --> 01:46:52,950
it.

1864
01:46:53,030 --> 01:46:54,150
It was very fun to talk to him.

1865
01:46:54,310 --> 01:46:58,870
In fact, he came to one of my students' defenses, the student who worked on Chicha, Andrew

1866
01:46:58,870 --> 01:47:02,020
Oliver, and he was full of so many stories.

1867
01:47:02,100 --> 01:47:07,540
But I guess one thing I'll just say is that John Patton invited my graduate student Andrew

1868
01:47:07,540 --> 01:47:11,620
Oliver down to Canambo to help collect the samples.

1869
01:47:11,700 --> 01:47:13,700
And I was really, you know, I was encouraging.

1870
01:47:13,780 --> 01:47:17,140
I was like thinking about if I could do it myself, but I had little kids at the time and

1871
01:47:17,140 --> 01:47:17,460
stuff.

1872
01:47:17,700 --> 01:47:20,740
And if you go there, you're like remote for the whole summer kind of thing.

1873
01:47:20,820 --> 01:47:22,660
It's like yeah, Brenda made it very clear.

1874
01:47:22,820 --> 01:47:25,700
Yeah, like it's a it's a serious thing.

1875
01:47:25,780 --> 01:47:26,020
Yeah.

1876
01:47:26,100 --> 01:47:27,620
To it's a serious commitment.

1877
01:47:27,950 --> 01:47:28,190
Yeah.

1878
01:47:28,350 --> 01:47:30,350
At minimum, that's a that's an understatement.

1879
01:47:30,430 --> 01:47:30,750
Yeah.

1880
01:47:30,990 --> 01:47:31,950
Yeah, exactly.

1881
01:47:32,110 --> 01:47:37,550
Um, and so and so John was describing the chicha and how it's like kind of

1882
01:47:37,550 --> 01:47:42,750
fibrous and you'd get like chunks of it stuck in your teeth, and you know, how it had a

1883
01:47:42,750 --> 01:47:44,350
really strong flavor and stuff like that.

1884
01:47:44,510 --> 01:47:47,870
But that if you go into someone's house, you have to drink the chicha.

1885
01:47:47,950 --> 01:47:53,950
I mean, you you really um there's no there would be no polite way to decline chicha without

1886
01:47:53,950 --> 01:47:58,020
causing like some serious um, you know hurt feelings.

1887
01:47:58,180 --> 01:48:03,940
And so anyway, he's like both trying to convince Andrew Oliver that he should come, but

1888
01:48:03,940 --> 01:48:09,940
also sharing all these like stories that made it seem like it was gonna be pretty tough to

1889
01:48:09,940 --> 01:48:10,740
survive.

1890
01:48:11,700 --> 01:48:17,060
So Andrew declined to go down there after hearing all about

1891
01:48:17,630 --> 01:48:19,870
flavors and chunks in the chicha.

1892
01:48:20,270 --> 01:48:20,670
Yes.

1893
01:48:20,910 --> 01:48:23,310
The downstream consequences of offending people.

1894
01:48:24,030 --> 01:48:28,430
David, I don't know if you m remember this differently, but my memory is the the cheerful

1895
01:48:28,430 --> 01:48:33,470
greeting from the canoe to somebody's house is I'm not gonna kill you in the night, you

1896
01:48:33,470 --> 01:48:35,070
know, something to that extent.

1897
01:48:36,110 --> 01:48:40,350
Like that's the best case, that's the best communicative event.

1898
01:48:40,430 --> 01:48:42,590
That's like a friendly communicative event.

1899
01:48:42,750 --> 01:48:44,670
I'm not gonna kill you in your sleep.

1900
01:48:45,040 --> 01:48:46,480
I feel like I want to use that.

1901
01:48:46,560 --> 01:48:47,360
That's really funny.

1902
01:48:47,680 --> 01:48:47,840
Yeah.

1903
01:48:48,080 --> 01:48:50,800
It's it's it's actually more alarming than saying nothing.

1904
01:48:52,560 --> 01:48:53,360
Well, maybe.

1905
01:48:53,520 --> 01:48:54,080
Maybe not.

1906
01:48:54,240 --> 01:48:56,560
Maybe if you like, oh, was there a possibility that you would?

1907
01:48:56,640 --> 01:48:58,960
Oh yeah, if you were actually worried about that, that would be a good idea.

1908
01:49:03,840 --> 01:49:04,880
But yeah, no, for us, right?

1909
01:49:04,960 --> 01:49:06,560
That's like I didn't even think of that.

1910
01:49:06,650 --> 01:49:06,890
Yeah.

1911
01:49:07,050 --> 01:49:09,930
So uh is there anything we should have asked you?

1912
01:49:10,010 --> 01:49:11,850
We we usually have to ask that question before.

1913
01:49:12,250 --> 01:49:13,210
Oh, that's nice of you to ask.

1914
01:49:13,290 --> 01:49:14,650
No, you guys asked great questions.

1915
01:49:14,730 --> 01:49:18,010
I got to um be on my fiber soap box for sure.

1916
01:49:18,090 --> 01:49:18,410
Thank you.

1917
01:49:18,730 --> 01:49:18,970
Great.

1918
01:49:19,050 --> 01:49:19,290
Yeah.

1919
01:49:19,370 --> 01:49:20,090
It's incredible.

1920
01:49:20,250 --> 01:49:21,770
I literally, yeah, I just cannot.

1921
01:49:21,930 --> 01:49:27,770
I mean, yeah, there's there's uh there's a small category people whose talks like forever

1922
01:49:27,770 --> 01:49:32,170
change the way I think about the world, and and you are in that category.

1923
01:49:32,330 --> 01:49:35,370
Um and it's just it's incredibly cool work.

1924
01:49:35,640 --> 01:49:41,400
It's a bonus that it's, I mean, you could from a basic perspective, it's a bonus that

1925
01:49:41,400 --> 01:49:46,200
there's this incredible real-world consequences to like what should you buy at the store

1926
01:49:46,200 --> 01:49:48,600
this week to like possibly help people.

1927
01:49:48,760 --> 01:49:51,880
And then from the applied perspective, it's cool that it's an evolutionary thing.

1928
01:49:51,960 --> 01:49:57,320
Like, you know, this is an evolutionary podcast, and it's nice that um this is uh the kind

1929
01:49:57,320 --> 01:50:02,090
of thing you wouldn't think of if you weren't coming from an evolutionary deep time

1930
01:50:02,410 --> 01:50:03,610
perspective.

1931
01:50:03,770 --> 01:50:06,730
Um so no matter how you look at this, it's just really cool work.

1932
01:50:06,810 --> 01:50:07,850
So thank you for doing it.

1933
01:50:07,930 --> 01:50:13,770
And I I hope that um people just rain more funding on this because unlike so

1934
01:50:13,770 --> 01:50:19,610
many things, it's so useful basically, but also really helpful um in

1935
01:50:19,610 --> 01:50:20,810
an applied perspective.

1936
01:50:20,970 --> 01:50:23,930
So just thanks for coming on and and thanks for doing this.

1937
01:50:24,250 --> 01:50:24,490
Yeah.

1938
01:50:24,730 --> 01:50:26,090
Thanks so much for inviting me.

1939
01:50:26,320 --> 01:50:26,560
Yeah.

1940
01:50:26,640 --> 01:50:31,600
And thank thank you for restoring my my faith and my sense of inspiration and hope about

1941
01:50:31,600 --> 01:50:36,480
the power of science to help us uh understand the world and actually help people.

1942
01:50:36,960 --> 01:50:37,760
So Yeah.

1943
01:50:37,840 --> 01:50:42,640
Uh and eat some beans this week or lentils or or um or fruit or uh berries.

1944
01:50:42,960 --> 01:50:43,040
Yeah.

1945
01:50:43,360 --> 01:50:45,120
Yeah, get get that fiber or the chia seeds.

1946
01:50:45,200 --> 01:50:45,840
I'll have to take it.

1947
01:50:48,970 --> 01:50:49,370
All right.

1948
01:50:49,530 --> 01:50:49,770
All right.

1949
01:50:49,850 --> 01:50:50,650
Thank you, Katrina.

1950
01:50:50,810 --> 01:50:51,930
Yeah, thank you very much.

1951
01:50:54,810 --> 01:51:00,730
So David, uh to sum up the ratio of carbs to fiber, um, don't

1952
01:51:00,890 --> 01:51:02,330
what uh what which is the one?

1953
01:51:02,410 --> 01:51:06,090
The poly don't polyethylene glycol, which doesn't sound good.

1954
01:51:06,170 --> 01:51:08,650
It actually sounds like um antifreeze.

1955
01:51:08,730 --> 01:51:10,090
Antifreeze, that's what it is.

1956
01:51:10,280 --> 01:51:11,640
It's ethylene glycol.

1957
01:51:12,040 --> 01:51:12,920
Um okay.

1958
01:51:13,080 --> 01:51:18,920
But polyethylene glycol is the stuff that uh you should not

1959
01:51:18,920 --> 01:51:23,000
use, but the psyllium husk or the derivatives are.

1960
01:51:23,240 --> 01:51:24,440
I'm just sort of reviewing.

1961
01:51:24,600 --> 01:51:28,680
Oh, the other thing to say is like berries often are very high in pesticides, so it's good

1962
01:51:28,680 --> 01:51:32,120
to get organic berries if you can, if you're gonna feed them to kids, especially.

1963
01:51:32,430 --> 01:51:33,470
Yeah, berries are great.

1964
01:51:33,550 --> 01:51:34,270
Beans are great.

1965
01:51:34,590 --> 01:51:36,110
Chia seeds to get some fiber.

1966
01:51:36,910 --> 01:51:42,830
Avocados high in so we're we're sponsoring all those uh whole foods and then Yeah,

1967
01:51:42,910 --> 01:51:46,270
this episode is brought to you by uh avocados.

1968
01:51:46,750 --> 01:51:47,870
Yeah, uh exactly.

1969
01:51:48,030 --> 01:51:49,310
Oh yeah, and Miralax.

1970
01:51:49,550 --> 01:51:53,550
We're I we're um we're not um uh Miralax Boo Miralax.

1971
01:51:53,710 --> 01:51:57,340
Yeah, boomerlax, we're we're unadvertising Muralaks, which I mean.

1972
01:51:57,580 --> 01:51:58,940
Yeah, and what was the the the good one?

1973
01:51:59,100 --> 01:52:00,380
Was Metamusil, right?

1974
01:52:00,460 --> 01:52:01,740
Yeah, I think it's Metamusil.

1975
01:52:01,820 --> 01:52:04,780
We're we're we're really I never metamusil I didn't look.

1976
01:52:05,580 --> 01:52:06,620
We know what we're talking about.

1977
01:52:06,700 --> 01:52:08,060
I think it's Metamusle.

1978
01:52:08,620 --> 01:52:11,340
Like, yeah, I mean really it's just psyllium husk.

1979
01:52:11,580 --> 01:52:14,700
It just gets some organic psyllium husk and yeah, psyllium.

1980
01:52:14,780 --> 01:52:17,100
Yeah, just doum Murphy.

1981
01:52:17,180 --> 01:52:18,300
Uh is a great actor.

1982
01:52:18,620 --> 01:52:19,660
I don't know who that is.

1983
01:52:19,980 --> 01:52:24,220
Oh, he was the uh the scarecrow in uh Batman Begins.

1984
01:52:24,630 --> 01:52:24,950
Okay.

1985
01:52:25,430 --> 01:52:27,110
He's in a lot of things, but that's what I'm saying.

1986
01:52:27,270 --> 01:52:27,830
Oh, that guy.

1987
01:52:27,910 --> 01:52:28,390
Oh, yeah, yeah.

1988
01:52:28,790 --> 01:52:30,150
He's got like a creepy face.

1989
01:52:35,350 --> 01:52:36,230
Yeah, he's Oppenheimer.

1990
01:52:36,310 --> 01:52:37,030
Yeah, he's Oppenheimer.

1991
01:52:37,350 --> 01:52:40,710
That's probably more relevant, but my memory for some reason is is more tuned to one of

1992
01:52:40,710 --> 01:52:40,870
those.

1993
01:52:41,110 --> 01:52:42,150
What did you think of that movie?

1994
01:52:42,310 --> 01:52:44,230
Oppenheimer I thought it was a little boring.

1995
01:52:44,310 --> 01:52:44,550
I don't know.

1996
01:52:44,630 --> 01:52:45,830
I thought it was overrated.

1997
01:52:46,070 --> 01:52:46,390
Okay.

1998
01:52:46,870 --> 01:52:47,180
All right.

1999
01:52:47,580 --> 01:52:47,980
Personally.

2000
01:52:48,380 --> 01:52:49,740
I mean, I watched it on the plane.

2001
01:52:49,820 --> 01:52:52,620
I don't really have time to watch movies except when I'm flying.

2002
01:52:52,940 --> 01:52:54,620
Yeah, that's a good airplane movie.

2003
01:52:54,860 --> 01:52:55,340
Yeah.

2004
01:52:55,580 --> 01:52:56,460
Yeah, I don't know.

2005
01:52:56,700 --> 01:52:57,020
I don't know.

2006
01:52:57,100 --> 01:52:59,740
I my expectations were high and they were not met.

2007
01:53:00,140 --> 01:53:03,900
I appreciated that it wasn't super unidimensional.

2008
01:53:04,140 --> 01:53:08,780
I appreciate movies that at the end of the movie you don't think, oh, I wish I was that

2009
01:53:08,780 --> 01:53:11,020
person or I lived at that time.

2010
01:53:11,820 --> 01:53:15,420
Yeah, I definitely don't wish I was Oppenheimer.

2011
01:53:15,660 --> 01:53:16,490
Yeah, Yeah.

2012
01:53:16,650 --> 01:53:20,730
There's some original recordings of Oppenheimer that are worth listening to.

2013
01:53:20,890 --> 01:53:24,490
Um one of the good things about YouTube and the internet is you can actually listen to

2014
01:53:24,490 --> 01:53:24,650
people.

2015
01:53:24,810 --> 01:53:28,010
Norbert Wiener, too, like the original cybernetics guy.

2016
01:53:28,090 --> 01:53:30,650
Like you can actually listen to some of these people talking.

2017
01:53:31,050 --> 01:53:31,290
Yeah.

2018
01:53:31,530 --> 01:53:32,010
That's cool.

2019
01:53:32,250 --> 01:53:34,570
I wish I could listen to a recording of Charles Darwin.

2020
01:53:34,650 --> 01:53:35,690
That would be awesome.

2021
01:53:37,210 --> 01:53:37,850
Yeah, maybe.

2022
01:53:37,930 --> 01:53:38,170
Yeah.

2023
01:53:38,810 --> 01:53:40,810
Maybe he had a bluegrass band or something.

2024
01:53:42,090 --> 01:53:44,010
Charles Darwin on the steel guitar.

2025
01:53:44,090 --> 01:53:44,490
Yeah.

2026
01:53:44,810 --> 01:53:46,520
I I mean, I bet he'd be very good.

2027
01:53:46,840 --> 01:53:47,080
Yeah.

2028
01:53:47,320 --> 01:53:48,680
Would you is that Darwin?

2029
01:53:48,760 --> 01:53:51,960
Is that one of your um if you can meet a historical figure?

2030
01:53:52,520 --> 01:53:52,920
Oh yeah.

2031
01:53:53,560 --> 01:53:53,960
Absolutely.

2032
01:53:54,200 --> 01:53:55,000
Top of my list.

2033
01:53:55,240 --> 01:53:55,880
Okay, really?

2034
01:53:56,360 --> 01:53:56,920
Oh yeah.

2035
01:53:57,080 --> 01:53:57,320
Okay.

2036
01:53:57,480 --> 01:54:02,040
I mean, to just tell him like all the stuff that's happened since he wrote on the origin of

2037
01:54:02,120 --> 01:54:06,840
species, and like tell him all the evidence that has confirmed and uh deepened and enriched

2038
01:54:06,840 --> 01:54:09,800
his theory, like just to watch his eyes light up, that would be awesome.

2039
01:54:09,960 --> 01:54:10,280
Yeah.

2040
01:54:10,490 --> 01:54:12,010
And he's just like he's just a great scientist.

2041
01:54:12,170 --> 01:54:17,210
If you read On the Origin, you know, descent of man, like expression of emotions in man and

2042
01:54:17,210 --> 01:54:18,890
animal, like he he's a really meticulous thinker.

2043
01:54:18,970 --> 01:54:22,810
I mean, yeah, he got a lot of stuff wrong, but like I don't know, just uh he's a great mind

2044
01:54:22,890 --> 01:54:24,250
and and a beautiful writer too.

2045
01:54:24,330 --> 01:54:25,210
Like Yeah, yeah, yeah.

2046
01:54:25,530 --> 01:54:29,210
That last passage of On the Origin, the the grandeur in this view of life.

2047
01:54:29,370 --> 01:54:29,770
Yeah.

2048
01:54:30,010 --> 01:54:31,690
It's a beautiful passage.

2049
01:54:32,840 --> 01:54:33,240
All right.

2050
01:54:33,320 --> 01:54:37,400
Well, on this note, um, I don't know, you know the spiel, you know.

2051
01:54:37,640 --> 01:54:43,480
Please like and subscribe and tell some about this podcast and Yeah, Patreon,

2052
01:54:43,640 --> 01:54:46,600
send us an email, write a review, all that all that bullshit.

2053
01:54:46,840 --> 01:54:52,680
Does Darwin do people um do leave reviews of like on the origin of species?

2054
01:54:53,150 --> 01:54:53,950
do you think?

2055
01:54:54,190 --> 01:54:55,070
Um, I don't know.

2056
01:54:55,150 --> 01:54:56,830
I haven't checked the the Amazon list.

2057
01:54:57,390 --> 01:55:00,270
Has there ever been a biopic about Charles Darwin?

2058
01:55:00,590 --> 01:55:01,710
Not that I'm aware of.

2059
01:55:01,790 --> 01:55:04,030
I would love to see a biopic of Darwin.

2060
01:55:04,270 --> 01:55:05,550
I think there's a voyage of the Beagle.

2061
01:55:05,630 --> 01:55:06,990
I think the BBC did something.

2062
01:55:07,230 --> 01:55:07,870
Oh, really?

2063
01:55:08,030 --> 01:55:08,670
Yeah.

2064
01:55:08,990 --> 01:55:09,790
Anyway.

2065
01:55:10,030 --> 01:55:10,430
All right.

2066
01:55:10,590 --> 01:55:16,480
Well, I mean, I my one of my favorite um books is uh back in the

2067
01:55:16,480 --> 01:55:16,720
day.

2068
01:55:16,800 --> 01:55:19,280
I read uh The Moral Animal by Robert Wright.

2069
01:55:19,760 --> 01:55:24,240
Uh that's a lot of people's intro gateway drug to Yeah, a lot of their gateway drugs.

2070
01:55:24,480 --> 01:55:29,680
Um and uh what the best shtick of that book is he weaves in a biography of Darwin

2071
01:55:30,400 --> 01:55:35,520
with with the chronicling of evolutionary psychology, and he sort of psychoanalyzes Darwin

2072
01:55:35,520 --> 01:55:37,040
through the lens of evolutionary psychology.

2073
01:55:37,200 --> 01:55:38,080
It's a really great shtick.

2074
01:55:38,400 --> 01:55:40,400
I as you can tell, I actually never read that one.

2075
01:55:40,560 --> 01:55:42,330
I was one of the ones I did not read.

2076
01:55:42,810 --> 01:55:43,290
It's really fun.

2077
01:55:43,450 --> 01:55:46,650
I mean, you know, there are a few few parts that don't hold up so well, but like it's it's

2078
01:55:46,650 --> 01:55:47,290
a really fun read.

2079
01:55:47,530 --> 01:55:47,690
Yeah.

2080
01:55:47,850 --> 01:55:52,890
No, many of the evolutionary psychologists that I respect very highly uh got got their it

2081
01:55:52,890 --> 01:55:55,130
got it got their hooks into them through that book.

2082
01:55:55,210 --> 01:55:55,690
So yeah.

2083
01:55:55,850 --> 01:55:57,930
Aaron Sell, I think was another one.

2084
01:55:58,170 --> 01:55:58,410
Yeah.

2085
01:55:58,570 --> 01:55:59,370
No, it's a great book.

2086
01:55:59,530 --> 01:56:00,010
Yeah, cool.

2087
01:56:00,250 --> 01:56:00,490
All right.

2088
01:56:00,570 --> 01:56:01,370
We'll see you guys next week.

2089
01:56:01,530 --> 01:56:02,010
See ya, David.

2090
01:56:03,210 --> 01:56:03,690
Bye.