1 00:00:00,040 --> 00:00:03,600 Speaker 1: M Hey everybody, it's me Josh And for this week's 2 00:00:03,760 --> 00:00:06,760 Speaker 1: S Y s K Selects, I've chosen How the Human 3 00:00:06,880 --> 00:00:10,480 Speaker 1: Microbiome Project Works, which we released back in May of 4 00:00:10,520 --> 00:00:14,040 Speaker 1: two thousand fourteen. And even after all these years, six 5 00:00:14,120 --> 00:00:17,919 Speaker 1: years on, this information is still just totally mind blowing 6 00:00:18,000 --> 00:00:19,919 Speaker 1: to me, and I love it. It's one of my 7 00:00:19,920 --> 00:00:22,560 Speaker 1: favorite episodes of all time. I've kind of forgotten about 8 00:00:22,560 --> 00:00:24,960 Speaker 1: it and discovered it again, so I hope you enjoy 9 00:00:24,960 --> 00:00:31,960 Speaker 1: it as much as I did. Welcome to Stuff. You 10 00:00:31,960 --> 00:00:41,120 Speaker 1: should know, a production of I Heart Radios How Stuff Works. Hey, 11 00:00:41,200 --> 00:00:44,559 Speaker 1: and welcome to the podcast. And Josh Clark, I almost 12 00:00:44,600 --> 00:00:48,519 Speaker 1: just forgot what I was gonna say your name. Yeah. Uh, 13 00:00:48,640 --> 00:00:52,440 Speaker 1: there's Charles W Chuck Bryant piping in ye and there's 14 00:00:53,280 --> 00:00:59,640 Speaker 1: the trio the Trifecta and it's terrible. Ikealy Uh do 15 00:00:59,680 --> 00:01:02,200 Speaker 1: you think, well, we are getting a little heat off 16 00:01:02,200 --> 00:01:04,000 Speaker 1: of it right now. It's just nice. Did you ever 17 00:01:04,040 --> 00:01:06,160 Speaker 1: see that IKEA commercial about the lamp that was thrown 18 00:01:06,200 --> 00:01:08,840 Speaker 1: out on the street. No, it was really good. Well 19 00:01:08,959 --> 00:01:10,680 Speaker 1: what happened to it? Was it like the monkey at 20 00:01:10,680 --> 00:01:13,080 Speaker 1: the I Kea? No, it was like a lamp gets 21 00:01:13,200 --> 00:01:16,280 Speaker 1: thrown out with like someone's just redoing parts of their 22 00:01:16,319 --> 00:01:19,800 Speaker 1: apartment and the lamp is uh kick to the curve, 23 00:01:20,120 --> 00:01:24,640 Speaker 1: computer animated, So it's it's a human formed not human formed. 24 00:01:24,640 --> 00:01:28,560 Speaker 1: What am I saying? Anthropogin anthropomorphized and like looks up 25 00:01:28,560 --> 00:01:30,160 Speaker 1: at the apartment that he was just thrown out of 26 00:01:30,240 --> 00:01:32,720 Speaker 1: it and stuff like that. Does he go back to Sweden? 27 00:01:33,240 --> 00:01:36,600 Speaker 1: I don't. I don't remember how it ends. Just remember 28 00:01:36,640 --> 00:01:38,800 Speaker 1: the lamp like turns at human. It was sad. It 29 00:01:38,920 --> 00:01:41,880 Speaker 1: was like sad. I got teared up. Did you go 30 00:01:42,000 --> 00:01:47,160 Speaker 1: buy one of those lamps? No, of course it didn't work. Um, so, 31 00:01:47,200 --> 00:01:49,040 Speaker 1: I guess you're feeling pretty good since you're talking about 32 00:01:49,080 --> 00:01:51,800 Speaker 1: lamps and everything. You know me and lamps I do. 33 00:01:52,000 --> 00:01:54,600 Speaker 1: That means it's a good day. A clear signal checks 34 00:01:54,640 --> 00:01:57,720 Speaker 1: in a good mood everybody. Uh, you know. One of 35 00:01:57,760 --> 00:02:01,280 Speaker 1: the reasons why you're in a good mood because your 36 00:02:01,320 --> 00:02:07,960 Speaker 1: guts are functioning properly. Yeah, yeah, ish, yeah, you know me, 37 00:02:08,080 --> 00:02:11,920 Speaker 1: it's day to day yeah with my stomach. Well that's 38 00:02:11,919 --> 00:02:16,480 Speaker 1: exactly right. Things change very quickly because of your stomach, 39 00:02:16,560 --> 00:02:18,280 Speaker 1: and your stomach can't affect your mood. As a matter 40 00:02:18,320 --> 00:02:20,960 Speaker 1: of fact, the vast majority of the serotonin, which is 41 00:02:21,000 --> 00:02:26,000 Speaker 1: a mood stabilizing neurotransmitter, is produced in your gut. Yeah. 42 00:02:26,040 --> 00:02:28,800 Speaker 1: And the way that things like serotonin and other stuff 43 00:02:29,520 --> 00:02:35,000 Speaker 1: uh is produced is thanks to our microbiome. Dude, Yeah, 44 00:02:35,760 --> 00:02:39,040 Speaker 1: our microbiome. This is the most fascinating thing going on 45 00:02:39,080 --> 00:02:42,560 Speaker 1: in medicine science right now. Yeah. I get the impression 46 00:02:42,560 --> 00:02:46,000 Speaker 1: reading various articles. When scientists talk about it, they all 47 00:02:46,040 --> 00:02:49,480 Speaker 1: seem really pumped up. It's like the breakthrough of the 48 00:02:50,120 --> 00:02:53,600 Speaker 1: century and this thing like just started. It's two and 49 00:02:53,680 --> 00:02:57,160 Speaker 1: like this could remain the breakthrough of the century. Yeah. 50 00:02:57,240 --> 00:02:59,760 Speaker 1: And I mean, if you think about the timeline up 51 00:02:59,760 --> 00:03:02,600 Speaker 1: in till the twentieth century, you were like a plant 52 00:03:02,680 --> 00:03:05,880 Speaker 1: or an animal, right, And then it was literally like 53 00:03:05,880 --> 00:03:09,400 Speaker 1: the nineteen fifties and sixties that they started saying maybe 54 00:03:09,440 --> 00:03:12,240 Speaker 1: we should break things down a little further, and they 55 00:03:12,280 --> 00:03:14,720 Speaker 1: came up with the five kingdoms, and I think they 56 00:03:14,760 --> 00:03:17,760 Speaker 1: are now even as a six kingdom. Well, there's three domains, 57 00:03:17,840 --> 00:03:22,920 Speaker 1: now eight kingdoms. There's eight, there's eight and three two 58 00:03:22,919 --> 00:03:25,680 Speaker 1: of the domains are account for two of the kingdoms 59 00:03:25,680 --> 00:03:29,480 Speaker 1: as well. Bacteria and archia and archia used to be 60 00:03:29,520 --> 00:03:33,399 Speaker 1: thought that they were the same as bacteria. Yes, then 61 00:03:33,400 --> 00:03:35,560 Speaker 1: they started looking into them a little more and they're like, oh, 62 00:03:35,600 --> 00:03:38,119 Speaker 1: these guys are made up of different amino acids and 63 00:03:38,400 --> 00:03:42,040 Speaker 1: they have different characteristics. And our chia, for example, are 64 00:03:42,080 --> 00:03:45,240 Speaker 1: the kind of um microbial life that you'll only find 65 00:03:45,280 --> 00:03:51,720 Speaker 1: around undersea, hot water, sulfur events. Yeah, like volcano crazy places. 66 00:03:52,480 --> 00:03:56,800 Speaker 1: Not not in your vagina or in your mouth. Well, no, 67 00:03:57,160 --> 00:03:59,920 Speaker 1: because they're extreme ophiles. And a vagina or a mouth 68 00:04:00,040 --> 00:04:03,280 Speaker 1: isn't that extreme? Well it is because our kia lives there, 69 00:04:03,400 --> 00:04:05,720 Speaker 1: that's right. So the fact that we figured out that 70 00:04:05,760 --> 00:04:09,240 Speaker 1: our kia are different than bacteria, and not only that 71 00:04:09,800 --> 00:04:13,640 Speaker 1: they don't just live in extreme environments, but also on 72 00:04:13,720 --> 00:04:17,479 Speaker 1: the human body, that was something we can thank the 73 00:04:17,560 --> 00:04:21,160 Speaker 1: Human Microbiome Project for. Yeah, and that wasn't I think 74 00:04:21,200 --> 00:04:24,000 Speaker 1: they didn't even discover our key until the nineteen seventies. 75 00:04:24,040 --> 00:04:28,080 Speaker 1: So this all this stuff is brand new, right and exciting. 76 00:04:28,200 --> 00:04:31,080 Speaker 1: And by the way, the three domains are bacteria, archia, 77 00:04:31,240 --> 00:04:35,080 Speaker 1: and eukaryotes. Are us, yes, or eukaryotes because we have 78 00:04:35,200 --> 00:04:41,080 Speaker 1: nucleus as nuclei. Yeah, let's talk about this man we 79 00:04:41,080 --> 00:04:43,680 Speaker 1: we have before. I'm sure you remember in the fecal 80 00:04:43,720 --> 00:04:47,599 Speaker 1: transplant episode, yes, because it definitely factors into it. You 81 00:04:47,640 --> 00:04:52,480 Speaker 1: can um hoop shakes. Yeah, you can cure Claustradium difficile, 82 00:04:52,640 --> 00:04:56,360 Speaker 1: which is something where that it's a gut microbe. It's 83 00:04:56,560 --> 00:05:01,400 Speaker 1: very harmful to humans that can colonize your guts after 84 00:05:01,480 --> 00:05:05,239 Speaker 1: you take antibiotics, which is basically just like a slash 85 00:05:05,240 --> 00:05:10,800 Speaker 1: and burn approach, which, again thanks to the Human Microbiome Project, UM, 86 00:05:11,000 --> 00:05:14,839 Speaker 1: we're starting to understand we might want to use antibiotics 87 00:05:14,920 --> 00:05:17,839 Speaker 1: because what we used to just think of is almost 88 00:05:17,960 --> 00:05:22,039 Speaker 1: entirely bad are actually mostly beneficial, and even some of 89 00:05:22,080 --> 00:05:27,000 Speaker 1: the bad bacteria a. Ka. Germs um are actually present 90 00:05:27,080 --> 00:05:30,520 Speaker 1: in our microbiome and normally live in harmony. It just 91 00:05:30,640 --> 00:05:33,640 Speaker 1: appears that when the microbiome gets out of whack, that's 92 00:05:33,680 --> 00:05:36,359 Speaker 1: when disease happens. Yeah, Like you may have E. Coli 93 00:05:36,440 --> 00:05:38,920 Speaker 1: in your body right now? Yeah, I probably do, but 94 00:05:39,000 --> 00:05:42,480 Speaker 1: it's not a big deal. If you're always talking about 95 00:05:42,480 --> 00:05:48,239 Speaker 1: stasis home, keeping things balanced in life is the key, yes, 96 00:05:48,480 --> 00:05:51,960 Speaker 1: and uh, it's definitely the key with your own personal microbiome, 97 00:05:52,400 --> 00:05:56,920 Speaker 1: which we have learned is very individualized, which we'll get 98 00:05:56,960 --> 00:06:00,200 Speaker 1: to with the project. Right, So, if you take human 99 00:06:00,279 --> 00:06:04,880 Speaker 1: body and you scanned all the genes in it, Well 100 00:06:04,960 --> 00:06:09,760 Speaker 1: you would find is there are about a hundred times 101 00:06:09,920 --> 00:06:16,040 Speaker 1: more microbial genes than human genes in a genetic scan 102 00:06:16,160 --> 00:06:19,640 Speaker 1: of a human body. Yeah, are are Human cells only 103 00:06:19,680 --> 00:06:21,839 Speaker 1: make up about ten of the cells in the body. 104 00:06:22,360 --> 00:06:27,880 Speaker 1: And here's another great stat We actually the healthiest person 105 00:06:27,960 --> 00:06:30,760 Speaker 1: on the planet has between two and five pounds of 106 00:06:30,800 --> 00:06:35,320 Speaker 1: bacteria pounds. Yeah, of your body weight, about up to 107 00:06:35,400 --> 00:06:40,719 Speaker 1: five pounds. Yes, what's crazy is is that that's even 108 00:06:40,800 --> 00:06:46,400 Speaker 1: considering that microbial cells are anywhere from a tenth to 109 00:06:46,480 --> 00:06:49,400 Speaker 1: a hundredth the size of an average human cell. Yes, 110 00:06:49,440 --> 00:06:51,559 Speaker 1: you do. You know how many? How much five pounds 111 00:06:51,600 --> 00:06:54,920 Speaker 1: would have to add quite a few. As a matter 112 00:06:54,960 --> 00:06:58,800 Speaker 1: of fact, there's um an estimated hundred trillion microbes on 113 00:06:59,160 --> 00:07:04,760 Speaker 1: an average human in person, just in on and a 114 00:07:04,839 --> 00:07:08,440 Speaker 1: part of such a such a part of us and 115 00:07:08,520 --> 00:07:12,160 Speaker 1: our our normal functioning that we're finding very quickly that 116 00:07:12,920 --> 00:07:16,800 Speaker 1: they're they're pretty much interchangeable. There, they are one with 117 00:07:16,920 --> 00:07:19,960 Speaker 1: us and um as their host. We are kind of 118 00:07:19,960 --> 00:07:23,240 Speaker 1: one with them. Yeah, like you have fungus on your skin, Yeah, 119 00:07:23,440 --> 00:07:25,560 Speaker 1: no big deal. Right, Well, that's another thing too, we 120 00:07:25,560 --> 00:07:28,800 Speaker 1: should talk about when people say microbe. Um, it's kind 121 00:07:28,840 --> 00:07:33,640 Speaker 1: of a catch all word for yeah, any tiny, typically 122 00:07:33,760 --> 00:07:37,360 Speaker 1: unicellular life. And that's the case here too. But it 123 00:07:37,400 --> 00:07:41,640 Speaker 1: doesn't just mean bacteria. The human microbiome is made up 124 00:07:41,680 --> 00:07:44,360 Speaker 1: of lots of bacteria and lots and lots of different 125 00:07:44,360 --> 00:07:48,280 Speaker 1: types of bacteria. Um. For example, the mouth may have 126 00:07:48,360 --> 00:07:53,160 Speaker 1: up to five thousand different species of bacteria. Yeah, and 127 00:07:53,240 --> 00:07:56,280 Speaker 1: they're not just lazing around in your body, like they 128 00:07:56,320 --> 00:08:01,600 Speaker 1: are responsible for keeping your body in chat or you know, 129 00:08:01,680 --> 00:08:04,360 Speaker 1: sometimes responsible for it being out of whack. But they're 130 00:08:04,400 --> 00:08:07,400 Speaker 1: all they're all doing something or laying there waiting to 131 00:08:07,440 --> 00:08:11,680 Speaker 1: do something. You also have a what's called a virume. 132 00:08:12,200 --> 00:08:15,920 Speaker 1: You have viruses in your microbiome, and they appear to 133 00:08:16,520 --> 00:08:21,680 Speaker 1: be present to keep the bacteria populations from getting out 134 00:08:21,680 --> 00:08:24,880 Speaker 1: of control. Like they're there to infect bacteria, to kill 135 00:08:24,920 --> 00:08:27,960 Speaker 1: them off. And they it's kind of like, um, they're 136 00:08:27,960 --> 00:08:33,199 Speaker 1: the lions to the gazelles of the microbiome. You take 137 00:08:33,240 --> 00:08:36,199 Speaker 1: away the lions, you've got too many gazelles. Yeah, they 138 00:08:36,240 --> 00:08:38,959 Speaker 1: all start to starve, they don't function correctly. They may 139 00:08:38,960 --> 00:08:40,839 Speaker 1: even eat each other. You don't want to see a 140 00:08:40,840 --> 00:08:44,120 Speaker 1: gazelle eat another gazelle. So you have lions there, and 141 00:08:44,160 --> 00:08:48,360 Speaker 1: the lions these apex predators keep the gazelle population and 142 00:08:48,480 --> 00:08:52,720 Speaker 1: check and ultimately healthy. Paradoxically, the same thing with the 143 00:08:52,800 --> 00:08:55,360 Speaker 1: virume in your microbiome. Yeah, I mean they we know 144 00:08:55,440 --> 00:08:58,920 Speaker 1: they aid like gut bacteria aids digestion, and we'll get 145 00:08:58,920 --> 00:09:01,760 Speaker 1: the gut bacteria more. I mean, they're discovering just all 146 00:09:01,840 --> 00:09:06,560 Speaker 1: kinds of things that affects uh, synthesized vitamins. Um. When 147 00:09:06,600 --> 00:09:09,640 Speaker 1: you poop in the toilet and you look at your poop, 148 00:09:09,720 --> 00:09:12,440 Speaker 1: which you should do by the way, like you know 149 00:09:12,520 --> 00:09:16,000 Speaker 1: on a regular basis, Um, how much is it? Is 150 00:09:16,000 --> 00:09:19,600 Speaker 1: it half? From a third to half? So a third 151 00:09:19,640 --> 00:09:23,400 Speaker 1: to half of that is microbial biomass. It's not food, No, 152 00:09:23,559 --> 00:09:27,240 Speaker 1: it's like dead and living bacteria that you're pooping out 153 00:09:27,640 --> 00:09:31,000 Speaker 1: about half half. I saw something that was kind of 154 00:09:31,040 --> 00:09:35,840 Speaker 1: mind blowing to um. It's it's really neat and accurate, 155 00:09:36,000 --> 00:09:40,040 Speaker 1: especially on a microbial level. To imagine your alimentary system, 156 00:09:40,040 --> 00:09:44,800 Speaker 1: your digestive system as the inside of that is technically 157 00:09:44,960 --> 00:09:48,960 Speaker 1: outside of your body. You have a hole, a trail 158 00:09:49,240 --> 00:09:55,040 Speaker 1: running through the middle of your body that's technically the outside. 159 00:09:55,559 --> 00:09:58,800 Speaker 1: Uh yeah, I guess I see what you mean, it's 160 00:09:58,840 --> 00:10:01,199 Speaker 1: just chew on it from an Yeah, like the the 161 00:10:01,280 --> 00:10:04,720 Speaker 1: inside of your digestive system is technically the outside of 162 00:10:04,760 --> 00:10:11,640 Speaker 1: your body. That's outside of your body. Yeah, it's confusing, 163 00:10:11,760 --> 00:10:14,480 Speaker 1: it is, but once once your head wraps around it, 164 00:10:14,480 --> 00:10:17,120 Speaker 1: it's like one hand clapping kind of thing and you're 165 00:10:17,160 --> 00:10:21,640 Speaker 1: just like, whoa, that is neat. Uh all right, So 166 00:10:21,679 --> 00:10:25,920 Speaker 1: that's I guess the briefest of overviews of microbes in bacteria, 167 00:10:25,960 --> 00:10:28,880 Speaker 1: which we've talked about ad nauseum on the show in 168 00:10:28,920 --> 00:10:32,320 Speaker 1: our Great Digestion podcast that was one of my favorite ones. 169 00:10:33,040 --> 00:10:36,079 Speaker 1: And then we've already talked about the poop shakes. Uh. 170 00:10:36,280 --> 00:10:39,960 Speaker 1: So the National Institutes of Health came up with a plan, 171 00:10:40,679 --> 00:10:43,719 Speaker 1: got some money together and said, let's try and do 172 00:10:43,760 --> 00:10:46,760 Speaker 1: what the Human Genome Project did. Let's try and map 173 00:10:46,800 --> 00:10:51,800 Speaker 1: out the micro the human microbiome, which is a very 174 00:10:51,840 --> 00:10:57,079 Speaker 1: tough task because everyone is different. Yeah. Well, yeah, everyone's 175 00:10:57,120 --> 00:11:00,680 Speaker 1: microbiome is different. And I just saw today it was 176 00:11:00,720 --> 00:11:03,680 Speaker 1: released from the University of Michigan. They've kind of already 177 00:11:03,679 --> 00:11:09,680 Speaker 1: determined there is no such thing as a baseline healthy microbiome. Yeah, 178 00:11:09,720 --> 00:11:11,760 Speaker 1: and that was one of the goals of this project. 179 00:11:11,800 --> 00:11:14,920 Speaker 1: That was started in two thousand seven, was that UM 180 00:11:14,960 --> 00:11:19,920 Speaker 1: to fight to establish a baseline micro biome like they 181 00:11:20,000 --> 00:11:22,520 Speaker 1: didn't know what one looked like like. They knew that 182 00:11:22,600 --> 00:11:26,080 Speaker 1: people had tons of bacteria and protozoa and viruses all 183 00:11:26,080 --> 00:11:29,120 Speaker 1: over us and in us, But what is that's supposed 184 00:11:29,160 --> 00:11:31,559 Speaker 1: to look like? And when you figure out what it's 185 00:11:31,559 --> 00:11:35,160 Speaker 1: supposed to look like, then you can figure out what 186 00:11:35,160 --> 00:11:38,160 Speaker 1: what an unhealthy one looks like and then possibly how 187 00:11:38,160 --> 00:11:42,600 Speaker 1: to correct that by adjusting this this microbial ecosystem back 188 00:11:42,640 --> 00:11:45,760 Speaker 1: to a baseline. But I'm not surprised that they found 189 00:11:45,800 --> 00:11:48,560 Speaker 1: that there isn't a baseline that is two different And 190 00:11:48,600 --> 00:11:50,800 Speaker 1: that doesn't mean that they can't like learn a lot 191 00:11:50,840 --> 00:11:53,160 Speaker 1: and help us out a lot. What they're basically saying 192 00:11:53,280 --> 00:11:56,800 Speaker 1: is you take a dozen completely healthy people and their 193 00:11:56,800 --> 00:12:00,160 Speaker 1: microbiomes are going to be completely different still, and there 194 00:12:00,240 --> 00:12:06,160 Speaker 1: was UM. There is one huge revolution in UM in 195 00:12:06,760 --> 00:12:11,600 Speaker 1: the study of bacterial or microbial life that that made 196 00:12:11,640 --> 00:12:15,720 Speaker 1: this project possible, same with the human genome, but UM 197 00:12:15,920 --> 00:12:19,960 Speaker 1: much more for this it's called metagenomics. And prior to 198 00:12:20,120 --> 00:12:24,280 Speaker 1: the Evan and metagenomics, if you wanted to study bacteria, 199 00:12:24,520 --> 00:12:30,280 Speaker 1: you had to find a bacteria that could be replicated, cloned, cultured, Yeah, 200 00:12:30,320 --> 00:12:35,120 Speaker 1: in the laboratory setting, and UM disaccounted for just a 201 00:12:35,240 --> 00:12:39,200 Speaker 1: very very small fraction of the number of microbes out there. 202 00:12:39,760 --> 00:12:42,880 Speaker 1: What's more so, not only did you not have a 203 00:12:42,920 --> 00:12:48,120 Speaker 1: representative sample, but you also didn't have UM any kind 204 00:12:48,160 --> 00:12:52,120 Speaker 1: of anything less than an artificial setting. So even if 205 00:12:52,120 --> 00:12:55,360 Speaker 1: you did get these microbes, if you could replicate him 206 00:12:55,360 --> 00:12:58,600 Speaker 1: in the lab, UM, they weren't gonna behave the way 207 00:12:58,600 --> 00:13:01,200 Speaker 1: they would in their natural set, like on your body. 208 00:13:01,520 --> 00:13:05,559 Speaker 1: So what metagenomics did UM was you can now take 209 00:13:05,600 --> 00:13:08,800 Speaker 1: like a representative sample, say like a clump of soil 210 00:13:09,480 --> 00:13:13,760 Speaker 1: or a swab of somebody's earfold, and get all of 211 00:13:13,800 --> 00:13:17,480 Speaker 1: the microbe microbes in there, and then basically just do 212 00:13:17,600 --> 00:13:21,200 Speaker 1: this rough scan of them, separate all the DNA out 213 00:13:21,920 --> 00:13:26,400 Speaker 1: at these enzymes that go and clip coherent fragments of 214 00:13:26,440 --> 00:13:28,400 Speaker 1: this DNA out, and then you take it and you 215 00:13:28,440 --> 00:13:31,440 Speaker 1: put it into what's called a model organism, and that 216 00:13:31,520 --> 00:13:35,440 Speaker 1: model organism starts to replicate as cells, and then each 217 00:13:35,480 --> 00:13:39,760 Speaker 1: cell displays a certain characteristic associated with a different microbe. 218 00:13:40,040 --> 00:13:42,240 Speaker 1: So all of a sudden you can start studying the 219 00:13:42,280 --> 00:13:45,520 Speaker 1: different cells and say, oh, well, this has to do 220 00:13:45,679 --> 00:13:49,760 Speaker 1: with this microbe, and this means that this protozoa is present, 221 00:13:49,760 --> 00:13:52,160 Speaker 1: and so on and so forth, and now you can 222 00:13:52,240 --> 00:13:57,120 Speaker 1: get a truly representative sample of what's in a microbiome. 223 00:13:57,400 --> 00:14:00,480 Speaker 1: And without metagenomics like this, none of this would be possible. 224 00:14:00,840 --> 00:14:03,400 Speaker 1: But now we're starting to find all sorts of new 225 00:14:03,960 --> 00:14:07,120 Speaker 1: uh not just information, but even new species of bacteria 226 00:14:07,200 --> 00:14:10,680 Speaker 1: and protozoan. Fun guy, from the study of this stuff, 227 00:14:11,400 --> 00:14:13,600 Speaker 1: which is a great thing. It is a great thing, 228 00:14:13,760 --> 00:14:15,680 Speaker 1: and we'll explain why it's a great thing right after 229 00:14:15,720 --> 00:14:35,480 Speaker 1: this break. Okay, so we're back. We're back, and uh. 230 00:14:35,760 --> 00:14:39,440 Speaker 1: We were talking about the microbiome project, which is being 231 00:14:39,520 --> 00:14:42,440 Speaker 1: rolled out in phases, the first of which obviously is 232 00:14:42,480 --> 00:14:45,880 Speaker 1: to get as many of those samples via this new 233 00:14:45,920 --> 00:14:51,520 Speaker 1: technology and basically just get a big reference set, throw 234 00:14:51,600 --> 00:14:54,480 Speaker 1: them out on the table like a like a crawfish 235 00:14:54,480 --> 00:14:58,160 Speaker 1: boil too, in the hopes of establishing that baseline, well 236 00:14:58,240 --> 00:15:02,560 Speaker 1: not just a baseline, just basically cataloging everything with the 237 00:15:02,640 --> 00:15:06,000 Speaker 1: ultimate goal of seeing what this means to our body 238 00:15:06,000 --> 00:15:08,600 Speaker 1: and how these different things interact. So they put the 239 00:15:08,640 --> 00:15:11,360 Speaker 1: word out on the street and I H said, Hey, 240 00:15:11,640 --> 00:15:14,320 Speaker 1: we need some volunteers. Do you think you're a very 241 00:15:14,360 --> 00:15:19,200 Speaker 1: healthy person. It's so come volunteer. And six people who 242 00:15:19,240 --> 00:15:22,640 Speaker 1: consider themselves very healthy showed up and said, I'm a 243 00:15:22,640 --> 00:15:25,640 Speaker 1: healthy person, and they were just made to learn that 244 00:15:25,920 --> 00:15:29,240 Speaker 1: half of them weren't healthy. Yeah apparently, Um, like yeah, 245 00:15:29,400 --> 00:15:32,920 Speaker 1: over half were rejected out right. And that doesn't mean 246 00:15:32,920 --> 00:15:36,040 Speaker 1: they're like super unhealthy. It just means for the purposes 247 00:15:36,080 --> 00:15:39,320 Speaker 1: of this they needed the healthiest of the healthy people. 248 00:15:39,360 --> 00:15:42,520 Speaker 1: And I read that even even still of the ones 249 00:15:42,560 --> 00:15:46,160 Speaker 1: that were accepted, the two and forty two that made 250 00:15:46,160 --> 00:15:52,359 Speaker 1: the cut, Um, those people still had to have periodontal 251 00:15:52,480 --> 00:15:58,160 Speaker 1: disease and cavities treated first, and then basically they had 252 00:15:58,200 --> 00:16:00,640 Speaker 1: to be treated for that stuff and then they were 253 00:16:00,800 --> 00:16:04,400 Speaker 1: deemed fully healthy. But like, that's that's how the level 254 00:16:04,440 --> 00:16:06,640 Speaker 1: of health they needed for this study, or that they 255 00:16:06,640 --> 00:16:08,760 Speaker 1: wanted for it. Yeah, And it surprised me they only 256 00:16:08,800 --> 00:16:11,960 Speaker 1: got um subjects from two cities. I thought it would 257 00:16:12,000 --> 00:16:15,560 Speaker 1: have been like spread out, but um, Houston, Texas and St. Louis, 258 00:16:15,640 --> 00:16:19,680 Speaker 1: Missouri or where the final subjects came from, and they 259 00:16:19,680 --> 00:16:22,920 Speaker 1: haven't been And they were all white too. They were 260 00:16:22,920 --> 00:16:26,120 Speaker 1: white men and women aged eighteen two forty I believe, 261 00:16:26,680 --> 00:16:29,520 Speaker 1: And um, they were in the they were the picture 262 00:16:29,560 --> 00:16:32,160 Speaker 1: of perfect health. After the dentists got finished with them, 263 00:16:32,720 --> 00:16:35,840 Speaker 1: people are wondering. I don't know, but um, it's not 264 00:16:35,920 --> 00:16:39,200 Speaker 1: that this has been that the Human Microbiome Projects has 265 00:16:39,240 --> 00:16:41,640 Speaker 1: been criticized for it. It's more just been like you, 266 00:16:42,080 --> 00:16:46,720 Speaker 1: so you guys got a swab of just these just 267 00:16:46,760 --> 00:16:49,920 Speaker 1: a small fragment of humanity. Yeah, maybe there's so much 268 00:16:50,000 --> 00:16:53,480 Speaker 1: starting point right, Well, yes, because they can't include like 269 00:16:53,600 --> 00:16:57,200 Speaker 1: every ethnic group in race when you're just starting out right, Okay, 270 00:16:57,360 --> 00:16:59,520 Speaker 1: But I mean it is surprising that we just went 271 00:16:59,560 --> 00:17:03,000 Speaker 1: with called Asian only. Uh. So they finally get these 272 00:17:03,000 --> 00:17:07,440 Speaker 1: healthy people, Um, a couple of hundred scientists, eighty different institutions. 273 00:17:07,440 --> 00:17:09,840 Speaker 1: It's a big group thing. It's not just like one 274 00:17:09,960 --> 00:17:13,639 Speaker 1: university that's running the show. Uh. Budget of about a 275 00:17:13,680 --> 00:17:16,280 Speaker 1: hundred and seventy million bucks to start out with, and 276 00:17:16,400 --> 00:17:21,640 Speaker 1: a bunch of uh cotton swabs, Yeah, lots of them, 277 00:17:21,680 --> 00:17:26,400 Speaker 1: over eleven thousand cotton swabs, generic cotton swabs. Right. They 278 00:17:27,760 --> 00:17:32,960 Speaker 1: they they swabbed each man in fifteen locations, women in 279 00:17:33,040 --> 00:17:35,720 Speaker 1: eighteen locations. Three of the locations were in the vagina. 280 00:17:36,119 --> 00:17:39,080 Speaker 1: Men don't have vaginas, they don't but men have ears 281 00:17:39,119 --> 00:17:44,840 Speaker 1: and armpits and folds mouths. Uh. So there's up your 282 00:17:44,840 --> 00:17:48,800 Speaker 1: nose stool stool samples they're they're getting, as you know, 283 00:17:48,840 --> 00:17:53,200 Speaker 1: they're swabbing all the moist places, right uh and yeah, 284 00:17:53,359 --> 00:17:56,239 Speaker 1: that's exactly right, and not just moist places. But I 285 00:17:56,240 --> 00:18:00,240 Speaker 1: think that's where you're gonna find the gold. Sure you know. Yeah, well, no, 286 00:18:00,359 --> 00:18:03,800 Speaker 1: it's true like your four arm actually uh is typically 287 00:18:03,800 --> 00:18:06,520 Speaker 1: pretty dry. Um, but it has one of the most 288 00:18:06,560 --> 00:18:11,000 Speaker 1: diverse array of bacterial species in your whole microbiome. Uh. 289 00:18:11,280 --> 00:18:14,800 Speaker 1: You have about an average of forty three. Yeah. And people, 290 00:18:14,880 --> 00:18:16,680 Speaker 1: when you hear this, don't think that didn't get the 291 00:18:16,760 --> 00:18:20,680 Speaker 1: reaction now is expecting? Well, that seemed low to me, Yeah, 292 00:18:20,800 --> 00:18:25,679 Speaker 1: because I'm used to hearing like thousands, thousands of bacteria, 293 00:18:25,720 --> 00:18:29,720 Speaker 1: not necessarily species. It's um, although I think the mouth 294 00:18:29,960 --> 00:18:32,040 Speaker 1: is going to top that. From what I remember, I 295 00:18:32,080 --> 00:18:34,760 Speaker 1: said like that it's like up to five thousand species. 296 00:18:34,920 --> 00:18:37,199 Speaker 1: I believe it. Yeah, um, But I think one of 297 00:18:37,200 --> 00:18:39,040 Speaker 1: our goals here, and the goal of scientists, is to 298 00:18:39,080 --> 00:18:41,679 Speaker 1: stop people from like changing the tide of how you 299 00:18:41,720 --> 00:18:44,080 Speaker 1: even think about the stuff. So when you hear that 300 00:18:44,160 --> 00:18:46,200 Speaker 1: all the bacteria in your mouth and under your armpit. 301 00:18:46,520 --> 00:18:51,200 Speaker 1: Don't think gross, think awesome. Well yeah, for the most part, Yeah, 302 00:18:51,400 --> 00:18:55,600 Speaker 1: you know so. Um, the project, I guess is still 303 00:18:55,720 --> 00:19:00,240 Speaker 1: very much in its nascent stages, Chuck. Basically they project itself. Yeah, 304 00:19:00,280 --> 00:19:02,800 Speaker 1: they did the initial leg work, and then they did 305 00:19:02,800 --> 00:19:06,199 Speaker 1: the second phase, which is sequencing these things, which again, 306 00:19:06,240 --> 00:19:10,919 Speaker 1: like I just painted the broadest picture of metagenomic sequencing. 307 00:19:11,359 --> 00:19:17,720 Speaker 1: It is one of the most involved, insane complex processes 308 00:19:17,760 --> 00:19:21,600 Speaker 1: I've ever like tried to understand. It's more complex than 309 00:19:21,640 --> 00:19:27,080 Speaker 1: the breathalyzer. Remember that it used like kryptonite somehow. Yeah, 310 00:19:27,160 --> 00:19:29,360 Speaker 1: that was very surprising. Yeah, if you don't know we're 311 00:19:29,359 --> 00:19:31,760 Speaker 1: talking about, go listen to our Breathalyzers episode. It was 312 00:19:32,160 --> 00:19:35,680 Speaker 1: really those are complicated missions. I thought there were fairies 313 00:19:35,680 --> 00:19:39,080 Speaker 1: inside the little box that just pretty much smells like beer. Yeah, 314 00:19:39,359 --> 00:19:43,840 Speaker 1: metagenomics is it's better to just kind of understand it, 315 00:19:43,920 --> 00:19:47,639 Speaker 1: like little fairies performing magic than to really dive into it. 316 00:19:47,720 --> 00:19:52,880 Speaker 1: But um, the point is this project. They have all 317 00:19:52,960 --> 00:19:55,560 Speaker 1: this data. Now, now they have to sort through it. 318 00:19:55,680 --> 00:19:57,960 Speaker 1: They have what the problem of big data, whether it's 319 00:19:58,000 --> 00:20:00,800 Speaker 1: just an overwhelming amount of data, like truly some bytes 320 00:20:00,840 --> 00:20:03,240 Speaker 1: of data three point five trillion bytes of data, which 321 00:20:03,280 --> 00:20:06,679 Speaker 1: is about a thousand times more than the Human Genome project. 322 00:20:07,240 --> 00:20:09,600 Speaker 1: And at first you're like, oh, wait, that doesn't make sense. 323 00:20:09,600 --> 00:20:12,119 Speaker 1: We're talking about bacteria, and you go, oh, yeah, that's right. 324 00:20:12,400 --> 00:20:16,399 Speaker 1: We have about a hundred two times the genes in 325 00:20:16,440 --> 00:20:19,360 Speaker 1: our microbiome than we do in just the human genome. 326 00:20:19,480 --> 00:20:22,120 Speaker 1: So yeah, that's a lot of data. And now they're 327 00:20:22,119 --> 00:20:24,640 Speaker 1: starting to figure out how to how to sort through it. 328 00:20:25,520 --> 00:20:27,359 Speaker 1: All right, So I guess after this break we can 329 00:20:27,359 --> 00:20:47,200 Speaker 1: talk about some of the things we have learned thus far. Okay, 330 00:20:47,200 --> 00:20:49,080 Speaker 1: we're back, all right, So now I guess we can 331 00:20:49,080 --> 00:20:52,000 Speaker 1: talk about some of these great findings, some of the 332 00:20:52,000 --> 00:20:56,399 Speaker 1: newest findings in the last what ars it? Well, they 333 00:20:56,400 --> 00:20:59,359 Speaker 1: started two seven seven years old, and it seems like 334 00:20:59,440 --> 00:21:02,920 Speaker 1: the first crop of like amazing stuff started in about 335 00:21:02,960 --> 00:21:06,159 Speaker 1: two twelve. Yeah, so after they had categorized things and 336 00:21:06,200 --> 00:21:08,600 Speaker 1: got like thrown all the crawfish out on the table 337 00:21:08,840 --> 00:21:11,160 Speaker 1: right in the corn. Yeah, the little corn is good. 338 00:21:11,320 --> 00:21:15,040 Speaker 1: Have you ever done that? I've had that before. Yeah, 339 00:21:15,080 --> 00:21:17,919 Speaker 1: it's good stuff. It's fun go to a big party. 340 00:21:18,440 --> 00:21:23,600 Speaker 1: There's a place in um on Buford Highway called um 341 00:21:23,720 --> 00:21:26,120 Speaker 1: the Crawfish Shack. I've heard of that, but I haven't been. 342 00:21:26,640 --> 00:21:28,040 Speaker 1: Did they do it like that? Did they just dump 343 00:21:28,080 --> 00:21:30,119 Speaker 1: it on the table and it's all picnic tables. No, 344 00:21:30,240 --> 00:21:32,359 Speaker 1: it's in the bowls and stuff like that. But um, 345 00:21:32,400 --> 00:21:36,560 Speaker 1: but it's all picnic tables inside and um, just huge 346 00:21:36,600 --> 00:21:39,240 Speaker 1: rolls of paper towels and it's dude, that place is 347 00:21:39,320 --> 00:21:41,040 Speaker 1: so good. Yeah, I guess you can't do that as 348 00:21:41,080 --> 00:21:43,360 Speaker 1: a restaurant. But if you go to a true crawfish 349 00:21:43,400 --> 00:21:46,359 Speaker 1: boil at someone's home, you have the picnic table covered 350 00:21:46,400 --> 00:21:48,919 Speaker 1: with the plastic thing and you just dump it on 351 00:21:48,960 --> 00:21:51,440 Speaker 1: the table and everyone just stands around like a bunch 352 00:21:51,480 --> 00:21:55,960 Speaker 1: of animals, right, getting drunk and eating, like sucking the 353 00:21:56,000 --> 00:21:58,320 Speaker 1: heads of crawfish. But my my family used to do 354 00:21:58,400 --> 00:22:00,800 Speaker 1: something similar to that when I was a little in Toledo. 355 00:22:01,080 --> 00:22:04,440 Speaker 1: We would eat um my dad called it garbage pail stew. 356 00:22:05,400 --> 00:22:07,520 Speaker 1: Are you familiar? Is it like all the leftovers? No, 357 00:22:07,920 --> 00:22:10,880 Speaker 1: it's like you use a trash can to make it. Oh, 358 00:22:11,240 --> 00:22:14,119 Speaker 1: I've never heard of it over like a flame, and 359 00:22:14,200 --> 00:22:17,080 Speaker 1: obviously use a new trash can, like a brand new one. 360 00:22:17,400 --> 00:22:19,800 Speaker 1: So I guess when dad got a new trash can, 361 00:22:19,840 --> 00:22:22,960 Speaker 1: we would have garbage pails stew anyway, the metal trash can. 362 00:22:23,080 --> 00:22:26,120 Speaker 1: It was, Yes, it was more like a the plastic 363 00:22:26,200 --> 00:22:31,640 Speaker 1: just added just trying to like one of the old 364 00:22:31,640 --> 00:22:33,600 Speaker 1: timing ones. What kind of flame you got in your house? 365 00:22:33,640 --> 00:22:35,920 Speaker 1: And I don't remember what he cooked it on. Interesting, 366 00:22:36,000 --> 00:22:38,560 Speaker 1: I don't like in my in my mind's eye, I 367 00:22:38,640 --> 00:22:41,520 Speaker 1: can't look down. I can just see you just see 368 00:22:41,560 --> 00:22:43,560 Speaker 1: the kind of the top of it. But anyway, it 369 00:22:43,680 --> 00:22:46,720 Speaker 1: was like a Yankee northern Midwestern version of it. So 370 00:22:46,760 --> 00:22:49,480 Speaker 1: there's like lots of cabbage in it and like kill 371 00:22:49,560 --> 00:22:52,000 Speaker 1: Bossa and stuff like that. But it was essentially the 372 00:22:52,040 --> 00:22:55,679 Speaker 1: same thing and you would eat it on like like newspaper. 373 00:22:55,960 --> 00:22:57,760 Speaker 1: I can't wait to get emails from people who were like, 374 00:22:57,800 --> 00:23:00,000 Speaker 1: we did that same thing. I've looked around, I'm never 375 00:23:00,119 --> 00:23:02,919 Speaker 1: seen it since. I'm sure that, yeah, that sounds like 376 00:23:02,920 --> 00:23:05,600 Speaker 1: a thing that although your dad is very unique person, 377 00:23:05,640 --> 00:23:08,760 Speaker 1: insane is the way to put it, all right, So 378 00:23:08,800 --> 00:23:13,439 Speaker 1: back to the project and the findings. Um. One of 379 00:23:13,440 --> 00:23:18,520 Speaker 1: the things they've learned is that periodontist this is gum disease. 380 00:23:19,240 --> 00:23:23,840 Speaker 1: Some bacteria are elevated if you have periodontists. So that's 381 00:23:23,840 --> 00:23:26,200 Speaker 1: gonna give you a little insight to maybe how you 382 00:23:26,240 --> 00:23:28,560 Speaker 1: can better take care of your mouth. What kind of 383 00:23:28,560 --> 00:23:31,760 Speaker 1: bacteria you need in there? What kind of you don't? Yeah, exactly, 384 00:23:31,920 --> 00:23:35,480 Speaker 1: And like for example, strip to Caucus mutans is responsible 385 00:23:35,520 --> 00:23:39,959 Speaker 1: for cavities, um, so you wanna take care of your 386 00:23:39,960 --> 00:23:43,679 Speaker 1: strep to Caucus muticans mutans. The thing is, Chuck, that 387 00:23:43,840 --> 00:23:46,040 Speaker 1: reading this made me wonder like, are we gonna go 388 00:23:46,160 --> 00:23:49,520 Speaker 1: the other direction now? Where it's like, we understand that 389 00:23:49,560 --> 00:23:52,240 Speaker 1: you can't just use antibiotics to get rid of everything, 390 00:23:52,760 --> 00:23:57,119 Speaker 1: But if we identify bacteria that's like, oh, well that 391 00:23:57,160 --> 00:23:58,919 Speaker 1: one gives you cavities, Let's get rid of all of 392 00:23:58,960 --> 00:24:01,440 Speaker 1: that and find some sort of medicine that just gets 393 00:24:01,480 --> 00:24:04,439 Speaker 1: rid of that. It could make things even worse than 394 00:24:04,480 --> 00:24:07,720 Speaker 1: a whole other direction. Like one thing that I I 395 00:24:07,840 --> 00:24:11,440 Speaker 1: figured out from this is that the the microbiome appears 396 00:24:11,480 --> 00:24:14,919 Speaker 1: to exist in balance, like stuff that should make us 397 00:24:14,920 --> 00:24:19,000 Speaker 1: sick E. Coli um, kinds of strepped staff, that kind 398 00:24:19,000 --> 00:24:22,520 Speaker 1: of thing, like it exists on a healthy person's microbiome 399 00:24:23,160 --> 00:24:25,760 Speaker 1: and it's just hanging out there. So it doesn't mean 400 00:24:25,800 --> 00:24:30,320 Speaker 1: that they're inherently disease causing for us, or that they're 401 00:24:30,400 --> 00:24:34,720 Speaker 1: they're inevitably disease causing um apparently if they exist in 402 00:24:34,880 --> 00:24:37,440 Speaker 1: harmony with their neighbors. That's the way it's supposed to be. 403 00:24:37,880 --> 00:24:40,040 Speaker 1: And we can't just root out just ones that make 404 00:24:40,040 --> 00:24:41,600 Speaker 1: a sick and get rid of those because I think 405 00:24:41,600 --> 00:24:44,639 Speaker 1: it will have repercussions. But they might. We might have 406 00:24:44,640 --> 00:24:47,760 Speaker 1: a future where instead of an antibiotic you take, you 407 00:24:47,800 --> 00:24:52,080 Speaker 1: actually take a bacteria that will attack the other bacteria 408 00:24:52,960 --> 00:24:56,080 Speaker 1: the bad stuff, right, or you can write exactly like 409 00:24:56,320 --> 00:25:00,240 Speaker 1: that that as long as we're not intervening and going 410 00:25:00,720 --> 00:25:04,320 Speaker 1: after a specific bacteria, if we can aid the bacteria 411 00:25:04,359 --> 00:25:07,360 Speaker 1: like you say that will fight it naturally, like by 412 00:25:07,400 --> 00:25:13,200 Speaker 1: eating some sort of sugary paste, you know, or probiotics, 413 00:25:13,200 --> 00:25:15,800 Speaker 1: I mean that's what that is, right, Yeah, and that 414 00:25:15,960 --> 00:25:19,440 Speaker 1: I mean, that's that's an issue that's being um examined 415 00:25:19,440 --> 00:25:24,320 Speaker 1: in more detailed thanks to the microbiome. Like do probiotics work? Uh, 416 00:25:24,320 --> 00:25:27,840 Speaker 1: And apparently the jury is still out in fury. They 417 00:25:27,880 --> 00:25:30,800 Speaker 1: should work, but it depends on, you know, whether these 418 00:25:30,800 --> 00:25:34,280 Speaker 1: things are actually colonizing your guts. And also I have 419 00:25:34,359 --> 00:25:38,199 Speaker 1: the impression that it's like you don't really know what 420 00:25:38,240 --> 00:25:40,760 Speaker 1: you're doing when you're adding like all these new people 421 00:25:40,800 --> 00:25:44,439 Speaker 1: of the neighborhood. Yeah, and because everyone's microbiome is so 422 00:25:44,520 --> 00:25:48,840 Speaker 1: different someone probiotics for one person might be great and 423 00:25:48,880 --> 00:25:51,600 Speaker 1: for another person might not do anything or make things worse. 424 00:25:51,640 --> 00:25:53,440 Speaker 1: I don't know. Yeah, which is another goal of the 425 00:25:53,520 --> 00:25:58,480 Speaker 1: Human Microbiome Project that if we start to understand, you know, 426 00:25:58,720 --> 00:26:02,440 Speaker 1: what a call any Maybe there's not a normal colony 427 00:26:02,520 --> 00:26:05,680 Speaker 1: for everybody, but what an individual's normal colony looks like, 428 00:26:06,160 --> 00:26:10,600 Speaker 1: then you can take blood or samples and make adjustments 429 00:26:10,760 --> 00:26:13,400 Speaker 1: based specifically on what you need. Right there, it could 430 00:26:13,400 --> 00:26:17,760 Speaker 1: be the end of pharmaceutical drugs conceivably. I know they're 431 00:26:17,760 --> 00:26:21,400 Speaker 1: doing a lot of research into, um, how your gut 432 00:26:21,440 --> 00:26:25,600 Speaker 1: bacteria affects ob cit and your weight. Um. They have 433 00:26:25,720 --> 00:26:31,640 Speaker 1: found obese mice and transferred micro microbes from their gut 434 00:26:31,680 --> 00:26:36,320 Speaker 1: into skinny mice, and the skinny mice gained weight. And Um, 435 00:26:36,359 --> 00:26:40,800 Speaker 1: there's just type in gut bacteria and obesity, And there 436 00:26:40,800 --> 00:26:43,199 Speaker 1: are a lot of studies going on now thinking that 437 00:26:43,320 --> 00:26:46,760 Speaker 1: maybe correcting your gut bacteria could actually help you help 438 00:26:46,800 --> 00:26:49,920 Speaker 1: your metabolism, you know, straighten out right, Like they think 439 00:26:49,960 --> 00:26:55,439 Speaker 1: the bacteria itself directly informs how the body uses their 440 00:26:55,560 --> 00:27:00,199 Speaker 1: stores energy. Yeah, yeah, Um, the one that blew me 441 00:27:00,280 --> 00:27:05,080 Speaker 1: away was there's a type of um bacteria that helps 442 00:27:06,119 --> 00:27:09,480 Speaker 1: that helps break down milk in humans and typically it's 443 00:27:09,520 --> 00:27:14,040 Speaker 1: in the gut, but um as a woman advances in pregnancy, Uh, 444 00:27:14,200 --> 00:27:18,520 Speaker 1: some of it moves down to the vagina. And they 445 00:27:18,920 --> 00:27:21,760 Speaker 1: at first, the researchers who found this were like, what's 446 00:27:21,800 --> 00:27:23,480 Speaker 1: the deal with that? And then they figured it out. 447 00:27:23,720 --> 00:27:27,080 Speaker 1: They think when a baby is born um and it 448 00:27:27,119 --> 00:27:32,119 Speaker 1: passes through the vagina, it basically it's becomes covered in 449 00:27:32,160 --> 00:27:36,400 Speaker 1: this bacteria, ingests some of it, and that bacteria goes 450 00:27:36,400 --> 00:27:39,560 Speaker 1: down and colonizes the baby's guts and prepares it almost 451 00:27:39,560 --> 00:27:43,920 Speaker 1: immediately to start breaking down breast milk. Yeah, evidently brand 452 00:27:43,920 --> 00:27:48,080 Speaker 1: new babies are just sponges. And like they're experimenting with 453 00:27:48,240 --> 00:27:52,600 Speaker 1: cesarean sections to just swab Like after you have the 454 00:27:52,640 --> 00:27:55,359 Speaker 1: cesarean section, you bring the baby out, swab it with 455 00:27:56,680 --> 00:28:00,600 Speaker 1: with vaginal mucus and basically it just looks right into 456 00:28:00,640 --> 00:28:02,720 Speaker 1: the skin and maybe have the same result, right, or 457 00:28:02,720 --> 00:28:06,640 Speaker 1: swab their mouth or something like that. Yeah, um another way, 458 00:28:06,640 --> 00:28:09,960 Speaker 1: And I guess that's kind of related to is um 459 00:28:10,000 --> 00:28:14,800 Speaker 1: with the immune system. Apparently the microbiome acts as kind 460 00:28:14,800 --> 00:28:18,679 Speaker 1: of like a teacher to the early immune system and 461 00:28:18,760 --> 00:28:21,160 Speaker 1: says like, hey, these are the good ones, these are 462 00:28:21,160 --> 00:28:23,919 Speaker 1: the bad ones. Um, why don't you go ahead and 463 00:28:23,960 --> 00:28:27,159 Speaker 1: produce some T killer cells or killer T cells, but 464 00:28:27,240 --> 00:28:31,280 Speaker 1: not too many, um, and uh, we'll just go ahead 465 00:28:31,280 --> 00:28:34,240 Speaker 1: and keep the homeostasis going. And they basically like teach 466 00:28:34,760 --> 00:28:38,800 Speaker 1: a young immune system how to operate at an optimal level. 467 00:28:39,160 --> 00:28:43,240 Speaker 1: And they found that by engineering mice that are like 468 00:28:43,360 --> 00:28:46,840 Speaker 1: totally germ free, their immune systems have a tendency to 469 00:28:46,920 --> 00:28:51,520 Speaker 1: go crazy, like they'll become inflamed in the presence of 470 00:28:51,560 --> 00:28:58,000 Speaker 1: what are say, um, non harmful fung gui. Um, They'll 471 00:28:58,120 --> 00:29:01,160 Speaker 1: they'll become so inflamed that they'll damage the surrounding tissue 472 00:29:01,800 --> 00:29:05,440 Speaker 1: or they'll have like irritable bowel syndrome or Crohn's disease. 473 00:29:05,480 --> 00:29:09,360 Speaker 1: They think also is a a flux state of the 474 00:29:09,440 --> 00:29:13,560 Speaker 1: microbiome in the gut, so apparently it directly impacts the 475 00:29:13,960 --> 00:29:17,400 Speaker 1: immune system as well, which my friend lends a lot 476 00:29:17,440 --> 00:29:21,800 Speaker 1: of weight to the hygiene hypothesis. Yeah, that's that's basically 477 00:29:21,840 --> 00:29:24,960 Speaker 1: the notion that, uh, here in the West and even 478 00:29:25,040 --> 00:29:30,520 Speaker 1: in developing countries now children are seeing such a decrease 479 00:29:30,520 --> 00:29:33,959 Speaker 1: in infection when they're when their kids that when they 480 00:29:34,000 --> 00:29:38,120 Speaker 1: grow up they have an increased number of allergies and 481 00:29:38,200 --> 00:29:43,640 Speaker 1: maybe autoimmune issues, and um, you kind of see it 482 00:29:43,640 --> 00:29:46,400 Speaker 1: playing out, you know, like it it's a real thing. 483 00:29:46,520 --> 00:29:49,120 Speaker 1: Like if you're slathering your child with pure l you're 484 00:29:49,120 --> 00:29:51,960 Speaker 1: not doing the many favors right. So they may have 485 00:29:52,000 --> 00:29:55,000 Speaker 1: asthma later on because of that exactly, And they are 486 00:29:55,080 --> 00:29:58,520 Speaker 1: becoming they're coming to think that it's because of the 487 00:29:58,520 --> 00:30:02,840 Speaker 1: the just a stunt to growth of the microbiome. Yeah, 488 00:30:02,880 --> 00:30:04,760 Speaker 1: and I think they've found now even they think they 489 00:30:04,760 --> 00:30:08,160 Speaker 1: have a direct link between your gut bacteria and allergies. 490 00:30:09,360 --> 00:30:12,200 Speaker 1: So if you're if you get hay fever, it may 491 00:30:12,200 --> 00:30:15,320 Speaker 1: be because of your gut bacteria. And it makes just 492 00:30:15,440 --> 00:30:19,160 Speaker 1: uttering complete sense too, Like your body has been exposed 493 00:30:19,200 --> 00:30:22,480 Speaker 1: to these things early on, learned that they're not harmful 494 00:30:22,920 --> 00:30:26,760 Speaker 1: and no longer produces antibodies as a result of their presence. 495 00:30:27,440 --> 00:30:30,320 Speaker 1: Because that's all analogy is. It's a a m it's 496 00:30:30,320 --> 00:30:33,160 Speaker 1: a case of mistaken identity. Your immune system thinks that 497 00:30:33,440 --> 00:30:36,880 Speaker 1: pollen or something is a harmful for an invader and 498 00:30:37,000 --> 00:30:41,360 Speaker 1: launches your your immune response. Pretty cool. Uh. Some of 499 00:30:41,400 --> 00:30:43,680 Speaker 1: the other interesting things they found so far is that 500 00:30:45,080 --> 00:30:48,840 Speaker 1: there wasn't a single microbe that everyone had in the study. Yeah, 501 00:30:48,920 --> 00:30:53,960 Speaker 1: which is pretty interesting. Um, And that microbes are most 502 00:30:54,040 --> 00:30:56,720 Speaker 1: similar on the same site of different people. So like 503 00:30:56,800 --> 00:30:59,600 Speaker 1: you and I have more similar microbes in our armpit 504 00:31:01,040 --> 00:31:03,720 Speaker 1: than even there were different people. Right then, you You're 505 00:31:04,000 --> 00:31:06,520 Speaker 1: microbes in your armpit has to do with your belly button. 506 00:31:07,520 --> 00:31:10,560 Speaker 1: Ours are more similar than the ones in different places 507 00:31:10,560 --> 00:31:13,880 Speaker 1: on your body. Yeah, that's pretty neat. And different microbes 508 00:31:13,920 --> 00:31:17,560 Speaker 1: can do completely different things, like the way you digest 509 00:31:17,600 --> 00:31:22,160 Speaker 1: food might use one microbe and I might use another, 510 00:31:22,520 --> 00:31:24,960 Speaker 1: or that same microbe might have a completely different function 511 00:31:24,960 --> 00:31:27,680 Speaker 1: in you than it doesn't mean right, so so personalized. 512 00:31:27,760 --> 00:31:31,120 Speaker 1: It's like it feels like the beginning of like hyper 513 00:31:31,160 --> 00:31:35,280 Speaker 1: personalized medicine. I think it is in the future. I 514 00:31:35,360 --> 00:31:38,040 Speaker 1: definitely think it is. I think it's also the beginning 515 00:31:38,040 --> 00:31:43,560 Speaker 1: of a kindler, kinder, gentler approach to treating disease at all. 516 00:31:43,640 --> 00:31:46,120 Speaker 1: Disease Like it's entirely possible, especially if you take a 517 00:31:46,160 --> 00:31:50,840 Speaker 1: brain based view of mental illness. It's possible that every 518 00:31:50,960 --> 00:31:55,600 Speaker 1: bit of disease can be cured by by understanding the microbiome, 519 00:31:55,640 --> 00:31:59,240 Speaker 1: even cancer. Apparently, they found from this that some types 520 00:31:59,280 --> 00:32:04,480 Speaker 1: of cancer managed to cloak themselves by taking like um 521 00:32:04,960 --> 00:32:08,920 Speaker 1: resin or residue from certain types of bacteria and basically 522 00:32:08,960 --> 00:32:14,400 Speaker 1: sneaking past your your immune system and going and lodging 523 00:32:14,400 --> 00:32:17,600 Speaker 1: itself into cells and hijacking them and creating tumors. But 524 00:32:17,760 --> 00:32:21,160 Speaker 1: it cloaks itself by getting buddy buddy with certain kinds 525 00:32:21,160 --> 00:32:24,320 Speaker 1: of bacteria. Cancer is a jerk. Yes, cancer is a 526 00:32:24,360 --> 00:32:26,280 Speaker 1: big time jerk. You know, we've kind of covered it 527 00:32:26,320 --> 00:32:28,920 Speaker 1: here and there, but uh, I could see more specific 528 00:32:28,960 --> 00:32:33,640 Speaker 1: cancer podcasting out, you know what. So like, so far 529 00:32:33,720 --> 00:32:36,920 Speaker 1: we've done too that specifically got into the microbiome, but 530 00:32:36,960 --> 00:32:40,320 Speaker 1: we've never done like a microbiome one. So I think 531 00:32:40,320 --> 00:32:42,160 Speaker 1: we should come back like a year from now and 532 00:32:42,200 --> 00:32:45,560 Speaker 1: even more stuff is out and do like the microbiome. Yeah, 533 00:32:45,560 --> 00:32:48,240 Speaker 1: it seems like they're they're making breakthroughs at a pretty 534 00:32:48,320 --> 00:32:52,360 Speaker 1: rapid pace. So in a year they might everyone might 535 00:32:52,360 --> 00:32:56,240 Speaker 1: be skinny. Yeah, because of the microbiome pill. Have you 536 00:32:56,280 --> 00:32:58,760 Speaker 1: seen a picture of like an obese mouse next to 537 00:32:58,880 --> 00:33:01,760 Speaker 1: like a skinny or normal eyes mouse. Yeah, it's pretty depressing. 538 00:33:01,880 --> 00:33:05,000 Speaker 1: It is um sad mouse. Okay, So I will see 539 00:33:05,040 --> 00:33:08,680 Speaker 1: you here at the end of next April. Uh, God 540 00:33:08,680 --> 00:33:12,040 Speaker 1: willing for the microbiome? One deal, all right? If you 541 00:33:12,080 --> 00:33:14,640 Speaker 1: want to learn more about the human microbiome, you can 542 00:33:14,640 --> 00:33:17,280 Speaker 1: type that well those words into the search bar at 543 00:33:17,280 --> 00:33:20,000 Speaker 1: how stuff works dot com. Uh And I said how 544 00:33:20,040 --> 00:33:24,800 Speaker 1: stuff works dot com. So it's time for the listener mail, Josh. 545 00:33:24,840 --> 00:33:28,960 Speaker 1: I'm gonna call this response from a creationist. Okay, we 546 00:33:29,040 --> 00:33:32,080 Speaker 1: got a few of these. Hey, guys, listen to your 547 00:33:32,080 --> 00:33:34,720 Speaker 1: podcast on natural selection and really enjoyed it. I'm a 548 00:33:34,760 --> 00:33:38,680 Speaker 1: biologist who is a Christian and creationist. Natural selection is 549 00:33:38,720 --> 00:33:41,160 Speaker 1: not what we disagree on. And when I say we, 550 00:33:41,360 --> 00:33:44,120 Speaker 1: I mean most creationist, but of course with every group 551 00:33:44,160 --> 00:33:48,720 Speaker 1: they are outliers. We agree with micro evolution, changes that 552 00:33:48,760 --> 00:33:53,000 Speaker 1: occur within the species, not macro evolution. Species developed into 553 00:33:53,040 --> 00:33:56,400 Speaker 1: a completely different species, which is what most people tend 554 00:33:56,400 --> 00:34:00,320 Speaker 1: to associate with evolution. The only major differences between creationists 555 00:34:00,800 --> 00:34:03,280 Speaker 1: an evolutionists is that we believe the Earth is between 556 00:34:03,320 --> 00:34:08,040 Speaker 1: six and ten thousand years old um and again excluding 557 00:34:08,040 --> 00:34:11,080 Speaker 1: the outliers, and that all organisms were created in their 558 00:34:11,120 --> 00:34:14,560 Speaker 1: basic form by our God. For example, we believe that 559 00:34:14,600 --> 00:34:17,200 Speaker 1: everyone came from Adam and Eve, who through methods of 560 00:34:17,280 --> 00:34:21,280 Speaker 1: natural selection, evolved into the many nationalities we have today. 561 00:34:21,600 --> 00:34:23,719 Speaker 1: Same thing with animals. We believe that a small number 562 00:34:23,760 --> 00:34:27,239 Speaker 1: of species were created by our God, and all the 563 00:34:27,320 --> 00:34:30,160 Speaker 1: forms we have today evolved through natural selection. So the 564 00:34:30,200 --> 00:34:33,560 Speaker 1: only main difference that we have with evolutionists is the 565 00:34:33,640 --> 00:34:36,840 Speaker 1: ultimate origin of species. The areas of evolution that we 566 00:34:36,880 --> 00:34:39,319 Speaker 1: can see clearly occurring in front of our eyes we 567 00:34:39,360 --> 00:34:42,480 Speaker 1: agree with. It's the areas the evolutionists theorized about that 568 00:34:42,520 --> 00:34:45,760 Speaker 1: we don't agree with. So while there are differences between 569 00:34:45,800 --> 00:34:49,799 Speaker 1: creationism and evolution, they're actually more similarities. And that is 570 00:34:49,960 --> 00:34:54,360 Speaker 1: Eric from South Bend, Indiana. Thanks a lot, Eric, very 571 00:34:54,400 --> 00:34:58,840 Speaker 1: salient points biologists. Yeah, I love it when like experts 572 00:34:58,880 --> 00:35:01,360 Speaker 1: come out of the out of the would work, especially 573 00:35:01,680 --> 00:35:05,480 Speaker 1: when they're experts with a twist. Yes, and we love 574 00:35:06,000 --> 00:35:10,239 Speaker 1: being refuted and refuting and reading refutations and uh, we'll 575 00:35:10,280 --> 00:35:14,200 Speaker 1: always read these things refutation life. That's right. If you 576 00:35:14,280 --> 00:35:16,799 Speaker 1: want to refute something we've said, or agree with us 577 00:35:16,840 --> 00:35:18,800 Speaker 1: or whatever. If you just want to get in touch 578 00:35:19,000 --> 00:35:21,120 Speaker 1: about anything, you can tweet to us at s y 579 00:35:21,160 --> 00:35:23,160 Speaker 1: s K Podcasts. You can join us on Facebook dot 580 00:35:23,160 --> 00:35:25,759 Speaker 1: com slash Stuff you Should Know, or on Pinterest or 581 00:35:25,880 --> 00:35:28,280 Speaker 1: on Instagram, and if you want to send an email 582 00:35:28,320 --> 00:35:31,239 Speaker 1: to Chuck, Jerry, and Me, you can address it to 583 00:35:31,600 --> 00:35:37,880 Speaker 1: Stuff podcast at how stuff works dot com. Stuff you 584 00:35:37,920 --> 00:35:40,120 Speaker 1: Should Know is a production of iHeart Radio's How Stuff 585 00:35:40,120 --> 00:35:42,600 Speaker 1: Works for more podcasts for my heart Radio because at 586 00:35:42,600 --> 00:35:45,279 Speaker 1: the iHeart Radio app, Apple Podcasts, or wherever you listen 587 00:35:45,320 --> 00:35:46,200 Speaker 1: to your favorite shows.