1 00:00:00,200 --> 00:00:02,080 Speaker 1: This episode of Stuff you Should Know is brought to 2 00:00:02,120 --> 00:00:04,880 Speaker 1: you by square Space. Whether you need a landing page, 3 00:00:04,920 --> 00:00:08,200 Speaker 1: a beautiful gallery, a professional blog, or an online store, 4 00:00:08,560 --> 00:00:11,280 Speaker 1: it's all possible with a square Space website. And right now, 5 00:00:11,320 --> 00:00:13,080 Speaker 1: listeners to Stuff you Should Know can start a free 6 00:00:13,080 --> 00:00:16,079 Speaker 1: trial today. Just go to squarespace dot com and enter 7 00:00:16,120 --> 00:00:19,480 Speaker 1: the offer code stuff and you'll get ten percent off 8 00:00:19,560 --> 00:00:25,040 Speaker 1: your first purchase. Squarespace set your website apart. Welcome to 9 00:00:25,120 --> 00:00:34,559 Speaker 1: you Stuff you Should Know friendhouse Stuff Works dot com. Hey, 10 00:00:34,760 --> 00:00:37,640 Speaker 1: welcome to the podcast. I'm Josh Clark with Charles W. 11 00:00:38,000 --> 00:00:43,040 Speaker 1: Chuck Bryant, and there's Jerry. Did you see that squirreled 12 00:00:43,680 --> 00:00:48,560 Speaker 1: W Chuck Bryant picture. Yeah, it's pretty great. Big thanks 13 00:00:48,680 --> 00:00:53,040 Speaker 1: to Sally Ridge, illustrator Drawer of Things, who made this 14 00:00:53,120 --> 00:00:54,480 Speaker 1: one of We used to get a lot of fan 15 00:00:54,640 --> 00:00:56,760 Speaker 1: ar't have you noticed we don't get that much anymore. 16 00:00:57,360 --> 00:01:01,360 Speaker 1: Everybody take this for grana. Uh maybe no, we get 17 00:01:01,440 --> 00:01:03,840 Speaker 1: jingles now. Yeah, we get all kinds of cool stuff, 18 00:01:03,880 --> 00:01:05,640 Speaker 1: But we just used to get a ton of fan art, 19 00:01:05,760 --> 00:01:08,440 Speaker 1: and this is like one of the more delightful pieces 20 00:01:08,480 --> 00:01:10,480 Speaker 1: of pan art we've ever gotten. We posted it on 21 00:01:10,560 --> 00:01:14,120 Speaker 1: our Instagram actually yeah, and Facebook, So thank you Sally 22 00:01:14,200 --> 00:01:16,120 Speaker 1: for that and go to Sally rich dot net to 23 00:01:16,200 --> 00:01:19,720 Speaker 1: see her work. Uh and I'm a little squirrel, I'm 24 00:01:19,760 --> 00:01:22,160 Speaker 1: a weasel, which I don't know what to make of. Ye, 25 00:01:22,319 --> 00:01:24,240 Speaker 1: I'm just going with it. It's cute. I first saw 26 00:01:24,319 --> 00:01:26,960 Speaker 1: that too, and I was like, h r. It was 27 00:01:27,000 --> 00:01:28,680 Speaker 1: like if it was a weasel in the skunk could 28 00:01:28,680 --> 00:01:30,960 Speaker 1: be like, I really have to think it, think it through. 29 00:01:31,120 --> 00:01:33,440 Speaker 1: But you as a squirrel, you have a little beard 30 00:01:33,640 --> 00:01:36,240 Speaker 1: even too, it's pretty cute. It is very cute. Um, 31 00:01:36,560 --> 00:01:40,640 Speaker 1: so Chuck. We say all that to say, have you 32 00:01:40,720 --> 00:01:44,600 Speaker 1: ever seen a gene a grown gene naked? Can you? 33 00:01:45,280 --> 00:01:47,640 Speaker 1: Can you keep up with jeans and DNA and all 34 00:01:47,720 --> 00:01:50,520 Speaker 1: that nuclear tides? Do you remember this stuff? A little bit? 35 00:01:50,720 --> 00:01:52,840 Speaker 1: I had to go back and brush up on a little. 36 00:01:53,040 --> 00:01:54,960 Speaker 1: If you have a primer, feel free, because I have 37 00:01:55,040 --> 00:01:57,400 Speaker 1: a bit of a primer. I'll probably screwed up royally. Well. 38 00:01:57,440 --> 00:01:59,240 Speaker 1: I was gonna say, an alternate title for this show 39 00:01:59,320 --> 00:02:03,880 Speaker 1: could be called, um, how the crisper gene editing works? 40 00:02:04,200 --> 00:02:08,080 Speaker 1: Uh A, k A, what's gonna mess up? Yeah, it's 41 00:02:08,280 --> 00:02:11,079 Speaker 1: it's kind of I mean, it's sort of simple, but 42 00:02:11,160 --> 00:02:13,520 Speaker 1: it also is a little minded thing. It's simple. If 43 00:02:13,600 --> 00:02:18,639 Speaker 1: you are a geneticist, it's it's almost like laughably scarily simple. 44 00:02:19,280 --> 00:02:23,440 Speaker 1: But um, two people like us, it's it's like sure, um, 45 00:02:23,600 --> 00:02:25,399 Speaker 1: all right, well let's go back. Let's talk a little 46 00:02:25,440 --> 00:02:27,519 Speaker 1: bit about genes first, right to a little weasel in 47 00:02:27,560 --> 00:02:30,280 Speaker 1: a squirrel. So if you if you go into one 48 00:02:30,320 --> 00:02:33,600 Speaker 1: of those squirrels cells and you go into the nucleus 49 00:02:33,639 --> 00:02:38,000 Speaker 1: of the cell, you're gonna find a pair of chromosomes, right, 50 00:02:38,240 --> 00:02:40,880 Speaker 1: And these chromosomes are made up of DNA, and the 51 00:02:41,040 --> 00:02:45,760 Speaker 1: DNA itself is made up of nucleotide pairs. What is it? 52 00:02:45,919 --> 00:02:50,440 Speaker 1: G A t TC Is that right? Um? Add nine 53 00:02:50,960 --> 00:02:55,040 Speaker 1: goes to oh who is it? Yeah? Add nine goes 54 00:02:55,120 --> 00:02:59,480 Speaker 1: to thymine and guanine goes to cytoscene. Right, Okay, so 55 00:02:59,560 --> 00:03:02,799 Speaker 1: you got attica. Yes, And when you put these these 56 00:03:02,880 --> 00:03:05,800 Speaker 1: amino acids together, you have what are called nucleotide based 57 00:03:05,800 --> 00:03:08,080 Speaker 1: pairs and they make up d N A. Now, if 58 00:03:08,120 --> 00:03:10,840 Speaker 1: you take a strand of DNA, this thing from um 59 00:03:11,000 --> 00:03:14,000 Speaker 1: it's like a Stanford site for dummies. So it really 60 00:03:14,080 --> 00:03:16,880 Speaker 1: spoke to me. But it said it said that if 61 00:03:16,960 --> 00:03:20,320 Speaker 1: you could stretch out your d NA, it would be 62 00:03:20,400 --> 00:03:22,880 Speaker 1: like six ft long. Did you know that in the 63 00:03:23,040 --> 00:03:25,120 Speaker 1: nucleus of a cell. I thought you were about to 64 00:03:25,160 --> 00:03:28,000 Speaker 1: say it would be the exact exact height that you are. 65 00:03:28,240 --> 00:03:29,840 Speaker 1: That would be pretty neatly in my mind would have 66 00:03:29,880 --> 00:03:33,240 Speaker 1: been blown. Yeah, that would be something else. Wow, maybe 67 00:03:33,280 --> 00:03:35,920 Speaker 1: it is because I'm about six ft Because supposedly your 68 00:03:35,960 --> 00:03:39,000 Speaker 1: wingspan is a fingertip to fingertip is the same as 69 00:03:39,000 --> 00:03:41,280 Speaker 1: your height. I've heard that before. That's not true, though, 70 00:03:41,280 --> 00:03:43,920 Speaker 1: because some people have larger wingspans than others than their height, 71 00:03:44,800 --> 00:03:47,480 Speaker 1: like proportionately. I got you anyway, go ahead. So it's 72 00:03:47,480 --> 00:03:51,000 Speaker 1: just a dirty lie, I think. So. Huh. Well, if 73 00:03:51,040 --> 00:03:54,360 Speaker 1: you take this DNA right and you look at it, 74 00:03:54,600 --> 00:03:59,240 Speaker 1: you can see that there's different sequences and along this 75 00:03:59,640 --> 00:04:02,240 Speaker 1: these this very long six ft strand of d N A, 76 00:04:03,080 --> 00:04:06,520 Speaker 1: these sequences are broken down into what are called genes, right, 77 00:04:07,160 --> 00:04:10,040 Speaker 1: And so a gene is really just a string of 78 00:04:10,200 --> 00:04:15,760 Speaker 1: nucleotide base pairs that create or lead to the production 79 00:04:15,960 --> 00:04:20,440 Speaker 1: of a specific protein. And you say, okay, well, great protein, 80 00:04:20,720 --> 00:04:25,479 Speaker 1: we eat that it's steak done. No. Proteins do way 81 00:04:25,520 --> 00:04:28,040 Speaker 1: more than that. They're involved in just about every part 82 00:04:28,160 --> 00:04:30,640 Speaker 1: of your body, from like the building box of cells 83 00:04:30,720 --> 00:04:34,720 Speaker 1: to chewing to blinking, the thinking like, proteins are very 84 00:04:34,800 --> 00:04:40,000 Speaker 1: very important, and your proteins are expressed through your genes. Okay, 85 00:04:41,120 --> 00:04:44,320 Speaker 1: I think I got that fairly right. Every once in 86 00:04:44,400 --> 00:04:48,400 Speaker 1: a while, this code, especially when a cell divides and 87 00:04:48,520 --> 00:04:50,640 Speaker 1: the d n A that was in the original cell 88 00:04:50,760 --> 00:04:55,080 Speaker 1: is copied for to the new cell, that translation can 89 00:04:55,120 --> 00:04:57,560 Speaker 1: go a little bit wrong, and so all of a sudden, 90 00:04:58,279 --> 00:05:01,720 Speaker 1: along these billions of base hairs, there's a there's a 91 00:05:01,839 --> 00:05:04,880 Speaker 1: there's a mistranslation, and what you have then is a mutation. 92 00:05:05,320 --> 00:05:08,360 Speaker 1: For the most part, mutations are not problems. As a 93 00:05:08,400 --> 00:05:11,080 Speaker 1: matter of fact, Um, any one of us has something 94 00:05:11,200 --> 00:05:15,800 Speaker 1: like an estimated five to ten mutations deadly mutations in 95 00:05:16,160 --> 00:05:19,680 Speaker 1: our genes right now. But we only have one copy. 96 00:05:20,080 --> 00:05:22,080 Speaker 1: And there are very few diseases that you only need 97 00:05:22,200 --> 00:05:26,440 Speaker 1: one copy of a genetic defect for, right, So we're 98 00:05:26,839 --> 00:05:31,359 Speaker 1: basically fine. If you get two pairs of mutated problematic genes, 99 00:05:31,520 --> 00:05:33,479 Speaker 1: then you can have a disease. And there's a lot 100 00:05:33,600 --> 00:05:38,159 Speaker 1: of diseases that are genetic in origin. Everything from um 101 00:05:38,320 --> 00:05:43,240 Speaker 1: cystic fibrosis to cancer is the result of a gene 102 00:05:43,520 --> 00:05:48,400 Speaker 1: that's mutated and gone Haywire. The whole point of everything 103 00:05:48,480 --> 00:05:52,360 Speaker 1: I just said is that we from the dawn of humanity, 104 00:05:52,520 --> 00:05:57,560 Speaker 1: even before then, ever since we were little amiba, have 105 00:05:57,760 --> 00:06:02,320 Speaker 1: been subject to the ms and the vagaries of genetic mutations. 106 00:06:02,560 --> 00:06:05,800 Speaker 1: Sometimes they help us, sometimes they do nothing, sometimes they 107 00:06:06,040 --> 00:06:11,280 Speaker 1: create disease. But as of two thousand twelve, we are 108 00:06:11,520 --> 00:06:20,880 Speaker 1: technically leaving the thumb of genetic mutations tyranny potentially, yeah, 109 00:06:21,760 --> 00:06:25,800 Speaker 1: through Crisper Jean editing. Yeah. It's it's pretty remarkable, it 110 00:06:26,200 --> 00:06:28,680 Speaker 1: really is. It's very tough. I know, I say this 111 00:06:28,720 --> 00:06:31,520 Speaker 1: a lot. I think I said it's tough to underestimate 112 00:06:31,600 --> 00:06:34,360 Speaker 1: the craze of super balls or something stupid like that. 113 00:06:34,800 --> 00:06:40,839 Speaker 1: It's really tough to overstate how much the Crisper gene 114 00:06:41,080 --> 00:06:46,160 Speaker 1: editing um technique could change humanity in the world. If 115 00:06:46,200 --> 00:06:50,520 Speaker 1: everything goes well, hopefully within the next decade we'll see 116 00:06:51,279 --> 00:06:57,680 Speaker 1: real human trials for some of these applications. That's the hope. Yeah. Uh, 117 00:06:58,000 --> 00:06:59,960 Speaker 1: and it may happen because this is one of the 118 00:07:00,520 --> 00:07:06,680 Speaker 1: most heavily funded arms of scientific health medicinal research out 119 00:07:06,720 --> 00:07:08,840 Speaker 1: there right now. It's also one of the newest too, 120 00:07:09,000 --> 00:07:11,400 Speaker 1: and it's already one of the most heavily funded because 121 00:07:11,440 --> 00:07:14,440 Speaker 1: it's it's showing that much promise, Like everybody keeps looking 122 00:07:14,480 --> 00:07:16,040 Speaker 1: into it more and more and more, and they're like 123 00:07:16,240 --> 00:07:18,600 Speaker 1: every every time they look at it where they're like, 124 00:07:18,880 --> 00:07:22,640 Speaker 1: it's like we just unlocked a secret of life. Yeah, 125 00:07:22,880 --> 00:07:25,080 Speaker 1: we just figured it out, and we can make so 126 00:07:25,280 --> 00:07:28,800 Speaker 1: much money on it. So let's start a company and 127 00:07:28,920 --> 00:07:31,840 Speaker 1: invest a lot of money in its research. Alright. So 128 00:07:31,960 --> 00:07:36,160 Speaker 1: crisper c R I s p R all capitalized stands 129 00:07:36,200 --> 00:07:42,480 Speaker 1: for clustered regularly interspaced short palindromic repeats, which is why 130 00:07:42,560 --> 00:07:45,560 Speaker 1: they called it crisper, because that is a mouthful. And 131 00:07:45,960 --> 00:07:48,720 Speaker 1: unless you're a geneticist, like you said that, probably those 132 00:07:48,760 --> 00:07:52,080 Speaker 1: string of words together probably just make your head spin, right, 133 00:07:52,520 --> 00:07:54,120 Speaker 1: but if you if you take them in separate. And 134 00:07:54,200 --> 00:07:57,040 Speaker 1: I watched this video. I can't remember who did it, 135 00:07:57,200 --> 00:08:00,960 Speaker 1: but I'll post it on the podcast page, this Ted Talk. No, 136 00:08:01,120 --> 00:08:03,040 Speaker 1: it wasn't a Ted Talk. It was by a dude. 137 00:08:04,560 --> 00:08:09,680 Speaker 1: Oh um, oh, what's Bozeman Science? It was a Bozeman 138 00:08:09,760 --> 00:08:13,200 Speaker 1: science video. It was really good Bozeman Montana. It was 139 00:08:13,280 --> 00:08:16,400 Speaker 1: just Bozeman science. So now there's a Bozeman Montana and 140 00:08:16,520 --> 00:08:20,400 Speaker 1: a Bozeman Science But anyway, the guy on the video said, 141 00:08:20,840 --> 00:08:23,240 Speaker 1: just kind of take it separately, and it's actually to 142 00:08:23,680 --> 00:08:29,560 Speaker 1: two parts. You've got the short palindromic repeats are the thing, 143 00:08:30,200 --> 00:08:33,640 Speaker 1: and the clustered regularly inner space then kind of describes 144 00:08:34,040 --> 00:08:37,720 Speaker 1: what that thing is. Right, So the short palindromic repeats 145 00:08:37,800 --> 00:08:40,599 Speaker 1: is what you need to focus on the start. But 146 00:08:41,240 --> 00:08:43,520 Speaker 1: let's back up a little bit. Let's talk a little 147 00:08:43,520 --> 00:08:47,439 Speaker 1: bit about genetically modifying things. Uh, we've been doing this 148 00:08:47,520 --> 00:08:50,839 Speaker 1: for a while. Everyone knows about Dolly the sheep and 149 00:08:51,679 --> 00:08:57,680 Speaker 1: cloning and genetically modified fruits and vegetables. Um, even selective 150 00:08:57,720 --> 00:09:00,520 Speaker 1: breeding is a is a type of genetic model application. 151 00:09:00,640 --> 00:09:02,760 Speaker 1: Sure you know. So it's nothing new, it's been going 152 00:09:02,840 --> 00:09:06,839 Speaker 1: on for a while. But um, in the early two thousand's, 153 00:09:07,280 --> 00:09:11,080 Speaker 1: there was a discovery of an enzyme. We'll not discovery 154 00:09:11,080 --> 00:09:12,840 Speaker 1: the enzyme, but a discovery of how to use an 155 00:09:12,920 --> 00:09:17,199 Speaker 1: enzyme called zinc finger nucleaise And what that would do 156 00:09:17,400 --> 00:09:22,720 Speaker 1: is replace, it would delete and replace very specific bad 157 00:09:22,880 --> 00:09:27,920 Speaker 1: genes that would make you get a disease, let's say. Right. 158 00:09:28,440 --> 00:09:32,480 Speaker 1: So it was a huge finding but really expensive. Yeah, 159 00:09:32,520 --> 00:09:34,480 Speaker 1: they were about five thousand dollars a piece, and they 160 00:09:34,480 --> 00:09:37,800 Speaker 1: didn't work every time for sure, and um, they were 161 00:09:37,840 --> 00:09:41,440 Speaker 1: just difficult to manufacture, difficult to understand, difficult to implement. 162 00:09:41,760 --> 00:09:44,240 Speaker 1: But they did do something pretty amazing, which was they 163 00:09:44,280 --> 00:09:47,360 Speaker 1: went in removed a gene from a strip of DNA 164 00:09:47,880 --> 00:09:51,360 Speaker 1: and could replace it with another gene that you wanted. 165 00:09:52,520 --> 00:09:54,720 Speaker 1: The thing is, it was just tough to use, basically, 166 00:09:54,840 --> 00:09:57,520 Speaker 1: So there was a big breakthrough, but it wasn't a 167 00:09:57,679 --> 00:10:02,080 Speaker 1: sweeping breakthrough because it was it was fragile and difficult 168 00:10:02,160 --> 00:10:05,240 Speaker 1: and expensive. That's right. Uh, fast forward to well, I 169 00:10:05,280 --> 00:10:10,520 Speaker 1: guess let's go back in time rather seven. Uh, sophomore 170 00:10:10,520 --> 00:10:14,920 Speaker 1: in high school. George Brett was the man. Yeah, sure 171 00:10:14,960 --> 00:10:20,040 Speaker 1: he was. Uh. John Cusack started say anything in seven 172 00:10:20,880 --> 00:10:23,360 Speaker 1: maybe something around there. I think that was eighty nine ish. 173 00:10:23,840 --> 00:10:29,360 Speaker 1: No singles was like no singles is definitely in the nineties, 174 00:10:29,360 --> 00:10:32,240 Speaker 1: because I was I think it's like ninety I'm gonna 175 00:10:32,240 --> 00:10:36,560 Speaker 1: go with one, all right, while you look that up. 176 00:10:36,640 --> 00:10:40,000 Speaker 1: So nine eight seven is when the word crisper first 177 00:10:40,040 --> 00:10:43,280 Speaker 1: appears in a journal article because the scientists said, you 178 00:10:43,320 --> 00:10:46,679 Speaker 1: know what, we found this thing in E. Coal i 179 00:10:47,280 --> 00:10:51,840 Speaker 1: these short repeats. What year was it? Uh? These short 180 00:10:51,880 --> 00:10:56,000 Speaker 1: repeats and the E. Coli bacteria UM of d n 181 00:10:56,120 --> 00:10:58,679 Speaker 1: A and that's weird. There should not be repeats of 182 00:10:58,760 --> 00:11:02,360 Speaker 1: DNA and this bacteria. So it was noteworthy. Yeah, it's 183 00:11:02,840 --> 00:11:05,079 Speaker 1: like what is that, right, it's a little weird. So 184 00:11:05,200 --> 00:11:07,560 Speaker 1: they took note, and I guess just say anything came 185 00:11:07,600 --> 00:11:10,120 Speaker 1: out and they decided to watch Cameron Crow movies for 186 00:11:10,160 --> 00:11:14,319 Speaker 1: the next decade. As they got bad, they started watching 187 00:11:14,559 --> 00:11:19,520 Speaker 1: singles and UM. In twelve is when Crisper and this 188 00:11:19,720 --> 00:11:22,680 Speaker 1: is just a few short years ago, is when Crisper 189 00:11:22,800 --> 00:11:25,560 Speaker 1: really came on the scene. Uh. And that's when all 190 00:11:25,640 --> 00:11:28,240 Speaker 1: this money started pouring into the research. And it's like 191 00:11:28,400 --> 00:11:30,959 Speaker 1: advanced light years in the last four years, right. And 192 00:11:31,000 --> 00:11:34,199 Speaker 1: the big, the big difference between what happened in seven 193 00:11:34,280 --> 00:11:36,360 Speaker 1: what happened in two dozen twelve is that they figured 194 00:11:36,400 --> 00:11:41,319 Speaker 1: out what these um short palindromic repeats were. Right, you 195 00:11:41,400 --> 00:11:44,160 Speaker 1: have these little strips of d n A in E. 196 00:11:44,280 --> 00:11:46,640 Speaker 1: Coli And then they found out later on you can 197 00:11:46,720 --> 00:11:49,719 Speaker 1: find it in most bacteria, if not at all. These 198 00:11:49,760 --> 00:11:53,720 Speaker 1: short little strips seemed to be separating out these these 199 00:11:54,000 --> 00:11:57,079 Speaker 1: what seemed to be like random strings of DNA, but 200 00:11:57,200 --> 00:12:02,040 Speaker 1: they separated them out in a red alert interspersed manner. Right, 201 00:12:02,520 --> 00:12:05,760 Speaker 1: So they looked at the little bits of random DNA 202 00:12:06,200 --> 00:12:10,440 Speaker 1: and they realized that it matched viral DNA, and they 203 00:12:10,800 --> 00:12:13,000 Speaker 1: totally weird, Yeah, because they're like, well, wait, this is 204 00:12:13,040 --> 00:12:16,079 Speaker 1: a bacteria. What is viral DNA doing in here? And 205 00:12:16,280 --> 00:12:21,199 Speaker 1: someone I'm not exactly sure who's just Eugene Conan was 206 00:12:21,480 --> 00:12:25,480 Speaker 1: a paradigm changing giant is the unsung hero in this. 207 00:12:26,440 --> 00:12:28,240 Speaker 1: Coonan said, you know what I think is going on. 208 00:12:28,600 --> 00:12:32,439 Speaker 1: I think what we're seeing here is essentially a database 209 00:12:32,880 --> 00:12:37,559 Speaker 1: that a bacteria houses in its own DNA where when 210 00:12:37,640 --> 00:12:42,200 Speaker 1: it's invaded by a virus, it captures that viruses DNA 211 00:12:42,440 --> 00:12:46,199 Speaker 1: or RNA, snips up some of it and stores it in. 212 00:12:46,320 --> 00:12:49,600 Speaker 1: It's the in this um genetic database, so that when 213 00:12:49,679 --> 00:12:53,360 Speaker 1: it sees that again, it will recognize the virus and 214 00:12:53,440 --> 00:12:56,479 Speaker 1: can attack it. Yeah, it's a it's a genetic adaptation 215 00:12:57,360 --> 00:13:00,640 Speaker 1: present and is not all bacteria, but in any bacteria 216 00:13:00,679 --> 00:13:04,920 Speaker 1: cells to help it survive, because the bacteria has like 217 00:13:05,080 --> 00:13:07,800 Speaker 1: a few minutes once it starts to get attacked by 218 00:13:07,800 --> 00:13:10,040 Speaker 1: a virus to live, right, Okay, so it's part of 219 00:13:10,080 --> 00:13:14,120 Speaker 1: its immune system, right, this database of what's called crisper. Yeah, 220 00:13:14,440 --> 00:13:17,920 Speaker 1: then there's another thing that they figured out about bacteria 221 00:13:17,960 --> 00:13:21,559 Speaker 1: that's associated with the Crisper database. In any given bacteria 222 00:13:21,679 --> 00:13:24,480 Speaker 1: and a bacteria that has it, it's called CAST nine. 223 00:13:25,120 --> 00:13:30,600 Speaker 1: It's Crisper associated um enzymes. I think C A S nine. 224 00:13:30,640 --> 00:13:33,800 Speaker 1: It's a it's a protein. It's an RNA guided enzyme 225 00:13:33,880 --> 00:13:36,320 Speaker 1: in protein, right, and it has this really neat function. 226 00:13:36,760 --> 00:13:40,959 Speaker 1: It goes to a virus or viral DNA or viral RNA, 227 00:13:41,320 --> 00:13:45,679 Speaker 1: and it captures it. It unzips it, which is not 228 00:13:45,840 --> 00:13:48,760 Speaker 1: everything can do that now, and then it also precisely 229 00:13:48,840 --> 00:13:54,120 Speaker 1: snips it and then delivers that snip to the bacteria's 230 00:13:54,200 --> 00:13:57,880 Speaker 1: Crisper database for storage. Yeah, so what you have is 231 00:13:57,960 --> 00:14:00,360 Speaker 1: a it's an it's an edit as a p posed 232 00:14:00,400 --> 00:14:03,160 Speaker 1: to like we've been working with working with genetic addition 233 00:14:03,400 --> 00:14:09,000 Speaker 1: and transfer for years, like treating people with transferring into 234 00:14:09,120 --> 00:14:12,079 Speaker 1: like bone marrow. Let's say, but this is an actual edit, 235 00:14:12,240 --> 00:14:14,760 Speaker 1: like they like in it in this article, even though 236 00:14:14,800 --> 00:14:18,079 Speaker 1: our own article never mentioned CAST nine, which is like, 237 00:14:18,200 --> 00:14:20,360 Speaker 1: I can't even believe you can't really have one with 238 00:14:20,640 --> 00:14:24,360 Speaker 1: the other. It was weird, but uh, this CAST nine 239 00:14:24,440 --> 00:14:27,040 Speaker 1: is literally they liken it to an assassin like that 240 00:14:27,160 --> 00:14:29,760 Speaker 1: comes in very surgically with a pair of scissors, very 241 00:14:29,840 --> 00:14:34,600 Speaker 1: specifically removes ideally just that part. Yeah, the bad part. 242 00:14:34,920 --> 00:14:36,560 Speaker 1: So we'll talk a little more about this. We get 243 00:14:36,600 --> 00:14:38,440 Speaker 1: to take a break though, everybody. We're getting a little 244 00:14:38,440 --> 00:15:02,280 Speaker 1: work though, So Chuck, you you're calling the cast the 245 00:15:02,400 --> 00:15:05,560 Speaker 1: Crisper cast nine system, which is basically what it is, 246 00:15:06,240 --> 00:15:09,960 Speaker 1: a an assassin for bacteria, right, it goes after the 247 00:15:10,040 --> 00:15:13,720 Speaker 1: viruses cuts him up. Somebody figured out along the line 248 00:15:14,160 --> 00:15:20,120 Speaker 1: that you can take this natural bacterial immune response and 249 00:15:20,320 --> 00:15:25,160 Speaker 1: sick it on not just viruses, but other stuff, not 250 00:15:25,360 --> 00:15:32,360 Speaker 1: just somebody. Cal Berkeley scientist Jennifer Doodna. Yeah, she's gonna 251 00:15:32,400 --> 00:15:35,080 Speaker 1: win a she's gonna win a Nobel Prize one day. 252 00:15:35,240 --> 00:15:37,960 Speaker 1: She's totally up for it. She will and and I 253 00:15:38,200 --> 00:15:40,760 Speaker 1: would advise if anyone is into Ted Talks to watch 254 00:15:40,840 --> 00:15:44,200 Speaker 1: her Ted Talk on this. Yeah. It's really good. Yeah. So, um, 255 00:15:44,920 --> 00:15:48,760 Speaker 1: she is a Juda Dowdna. Uh well, I said Dudna, 256 00:15:48,840 --> 00:15:52,480 Speaker 1: but we'll go with down okay, one of those. Um. 257 00:15:52,680 --> 00:15:56,480 Speaker 1: She she was the first to suggest that you can 258 00:15:56,680 --> 00:16:00,240 Speaker 1: use this natural system to edit jeans and other things things. 259 00:16:00,720 --> 00:16:04,840 Speaker 1: And I think they started out in very simple organisms, 260 00:16:05,360 --> 00:16:09,560 Speaker 1: but what they found over time. Is that this seems 261 00:16:09,600 --> 00:16:12,920 Speaker 1: to be universal that as long as something has DNA 262 00:16:13,520 --> 00:16:17,000 Speaker 1: you can use the Crisper cast nine system on it 263 00:16:17,160 --> 00:16:21,040 Speaker 1: to edit genes. Yeah to uh. She likened it to 264 00:16:21,160 --> 00:16:23,520 Speaker 1: fixing a typo or she said it was like a 265 00:16:23,600 --> 00:16:28,600 Speaker 1: genetic vaccination card that yourself can have. Yeah, So it 266 00:16:28,720 --> 00:16:32,040 Speaker 1: goes in, it snips out the bad part, and sometimes 267 00:16:32,080 --> 00:16:35,120 Speaker 1: it just joins from there and just repairs it. But 268 00:16:35,240 --> 00:16:40,240 Speaker 1: other times it sticks uh, something else in it joins it. Right, 269 00:16:40,560 --> 00:16:43,800 Speaker 1: So depends Yeah, it depends on the system that you're using. 270 00:16:43,920 --> 00:16:46,680 Speaker 1: Like you can you can just stick a Crisper cast 271 00:16:46,760 --> 00:16:50,440 Speaker 1: nine thing, So you you give it a You basically 272 00:16:50,560 --> 00:16:56,080 Speaker 1: give this bacterial immune response a little piece of the 273 00:16:56,280 --> 00:17:00,120 Speaker 1: gene that you want edited, and it says, exam is 274 00:17:00,160 --> 00:17:02,160 Speaker 1: it just like it would if if it were in 275 00:17:02,240 --> 00:17:04,960 Speaker 1: a bacteria and it were being invaded by a virus. 276 00:17:05,320 --> 00:17:07,600 Speaker 1: So it examines this gene and says, Okay, this is 277 00:17:07,640 --> 00:17:09,639 Speaker 1: what I need to go find, And it goes and 278 00:17:09,760 --> 00:17:12,919 Speaker 1: finds it on a strand of DNA. And this thing 279 00:17:12,960 --> 00:17:15,560 Speaker 1: doesn't care what DNA it's looking at. It's just doing 280 00:17:15,640 --> 00:17:18,760 Speaker 1: its thing right, So if you stick it on any DNA, 281 00:17:18,840 --> 00:17:22,440 Speaker 1: it's going to go find that sequence, that genetic sequence 282 00:17:22,560 --> 00:17:26,160 Speaker 1: on whatever DNA it's exposed to, and then it's going 283 00:17:26,240 --> 00:17:28,280 Speaker 1: to un zip it. It's going to cut it out, 284 00:17:28,400 --> 00:17:30,120 Speaker 1: and then one thing you can do is just say 285 00:17:30,320 --> 00:17:32,440 Speaker 1: done and done, and then the DNA is going to 286 00:17:32,520 --> 00:17:35,600 Speaker 1: repair itself. But what you've just done is removed that 287 00:17:35,720 --> 00:17:38,960 Speaker 1: whole sequence of nucleotide base pairs that makes up a gene, 288 00:17:39,440 --> 00:17:43,359 Speaker 1: and so when it's fuses back together, it's going to 289 00:17:43,440 --> 00:17:46,280 Speaker 1: be missing that gene. So you can delete a gene 290 00:17:46,400 --> 00:17:49,520 Speaker 1: is what that's called, or you can add a third 291 00:17:49,600 --> 00:17:53,040 Speaker 1: component to and say, here's what you're looking for, here's 292 00:17:53,119 --> 00:17:55,440 Speaker 1: the here's the guide RNA that you want to go find. 293 00:17:56,200 --> 00:17:59,520 Speaker 1: Um use the cast nine system to go cut it out, 294 00:17:59,600 --> 00:18:02,040 Speaker 1: un zip and cut it out, and then replace it 295 00:18:02,080 --> 00:18:05,439 Speaker 1: with this. Here's some blueprints for what you should install 296 00:18:06,000 --> 00:18:08,240 Speaker 1: in the in the place of the gene you just 297 00:18:08,480 --> 00:18:11,960 Speaker 1: edited out, so you can delete and then now add 298 00:18:12,560 --> 00:18:15,840 Speaker 1: whatever gene you want. And what they found, this incredibly 299 00:18:15,880 --> 00:18:18,639 Speaker 1: mind bobbling, chuck, is that you can take a gene 300 00:18:18,920 --> 00:18:23,359 Speaker 1: from a different organism and put it into another organism. 301 00:18:24,400 --> 00:18:27,080 Speaker 1: You can basically just copy and paste and cut and 302 00:18:27,160 --> 00:18:31,520 Speaker 1: paste DNA and that's what this system is allowing people 303 00:18:31,600 --> 00:18:33,800 Speaker 1: to do. So what does all this mean. It means 304 00:18:33,960 --> 00:18:38,000 Speaker 1: you could potentially remove a gene for blindness, You could 305 00:18:38,040 --> 00:18:43,480 Speaker 1: remove a gene for cystic fibrosis and repair. Uh. Well, 306 00:18:43,520 --> 00:18:46,040 Speaker 1: we'll talk about HIV a little bit more in a minute. Um, 307 00:18:47,080 --> 00:18:51,880 Speaker 1: you could create more disease resistant crops. Uh. You could 308 00:18:51,960 --> 00:18:54,680 Speaker 1: create a bioweapon that could wipe out a species. I 309 00:18:54,720 --> 00:18:57,160 Speaker 1: mean there are bad applications as well. Well. The people 310 00:18:57,200 --> 00:18:59,879 Speaker 1: have talked about that. And remember was zekea virus? Like 311 00:19:00,040 --> 00:19:03,720 Speaker 1: people are saying, well, let's just get mosquitoes to to 312 00:19:03,920 --> 00:19:07,520 Speaker 1: stop reproducing and then that'll stop the spread of zecra virus. 313 00:19:07,720 --> 00:19:10,399 Speaker 1: What they're talking about is using gene editing. Yeah, and 314 00:19:10,480 --> 00:19:13,640 Speaker 1: if you watch that uh ted talk from Jennifer down 315 00:19:14,000 --> 00:19:19,200 Speaker 1: she says, slow we need to slow it down. And um, 316 00:19:19,520 --> 00:19:21,960 Speaker 1: she and her I don't know she was partnered. She 317 00:19:22,040 --> 00:19:24,320 Speaker 1: said she co invented. I don't know if it was 318 00:19:24,400 --> 00:19:28,399 Speaker 1: Coonan or not, but whoever her partner and crime here 319 00:19:28,560 --> 00:19:32,720 Speaker 1: is I was a French, a French um researcher. So 320 00:19:32,800 --> 00:19:35,800 Speaker 1: it wasn't Emmanuel something I can't remember last name. So 321 00:19:35,920 --> 00:19:39,600 Speaker 1: she said they basically called for a moratorium for now 322 00:19:39,720 --> 00:19:42,960 Speaker 1: and said everyone just stopped for a minute. Yeah, and 323 00:19:43,000 --> 00:19:46,040 Speaker 1: everybody's like, well, how much money is There's a lot 324 00:19:46,080 --> 00:19:47,880 Speaker 1: of money at stakes, so we'll see where that goes. 325 00:19:47,960 --> 00:19:50,600 Speaker 1: But she she did call for a pause, is what 326 00:19:50,720 --> 00:19:53,760 Speaker 1: she called it. UM, so they could kind of set 327 00:19:53,840 --> 00:19:57,240 Speaker 1: up some guidelines on how to use and not misuse 328 00:19:57,359 --> 00:20:00,680 Speaker 1: this technology. Yeah. And the reason why UM, I mean, 329 00:20:00,800 --> 00:20:03,680 Speaker 1: I salute her for that. That's a big deal. But 330 00:20:04,240 --> 00:20:06,680 Speaker 1: that's a big problem that we're facing in this world 331 00:20:06,800 --> 00:20:10,400 Speaker 1: is that our technology is starting to outpace our understanding 332 00:20:10,520 --> 00:20:12,879 Speaker 1: of all of the things that can do. And then 333 00:20:13,480 --> 00:20:16,720 Speaker 1: in addition to that, it's becoming much more democratized to 334 00:20:16,880 --> 00:20:20,760 Speaker 1: where people can get their hands on incredibly advanced technology 335 00:20:21,400 --> 00:20:23,359 Speaker 1: UM in the comforts of their own home. And this 336 00:20:23,480 --> 00:20:26,160 Speaker 1: is a really good example of that because the Crisper 337 00:20:26,240 --> 00:20:29,280 Speaker 1: system you can send off for on the internet for 338 00:20:29,440 --> 00:20:32,520 Speaker 1: anywhere from like thirty bucks to seventy five bucks, and 339 00:20:32,800 --> 00:20:37,480 Speaker 1: you will have a bacteria that you can introduce your 340 00:20:37,560 --> 00:20:41,080 Speaker 1: guide RNA too or your host RNA too, and and 341 00:20:41,240 --> 00:20:46,359 Speaker 1: basically airstolize it and expose it to a mouse, and 342 00:20:46,520 --> 00:20:49,200 Speaker 1: that bacteria will go in and edit that mouse's Janes, 343 00:20:49,480 --> 00:20:51,360 Speaker 1: and you can do this if you know what you're 344 00:20:51,400 --> 00:20:55,440 Speaker 1: doing with a relatively clunky setup at your in your 345 00:20:55,480 --> 00:20:59,040 Speaker 1: home and in the So like the idea that we 346 00:20:59,119 --> 00:21:01,879 Speaker 1: need to stop in and talk about what direction we 347 00:21:01,920 --> 00:21:03,880 Speaker 1: should go with this or what restrictions we should place 348 00:21:03,920 --> 00:21:06,680 Speaker 1: on it. I think that's a fantastic idea. Well, yeah, 349 00:21:06,680 --> 00:21:08,879 Speaker 1: because we all we did a show on Designer Children. 350 00:21:09,720 --> 00:21:14,119 Speaker 1: Uh jeez, was it before two thousand twelve? I don't know. 351 00:21:14,240 --> 00:21:16,000 Speaker 1: I would guess it came out of this because I 352 00:21:16,040 --> 00:21:18,880 Speaker 1: don't remember. I don't remember talking about the crisper jine 353 00:21:18,920 --> 00:21:21,840 Speaker 1: in that episode, but that's potentially one of the applications 354 00:21:21,960 --> 00:21:26,160 Speaker 1: is I don't want my child to have Huntington's disease, 355 00:21:26,320 --> 00:21:30,520 Speaker 1: and it's in there, so let's take it out. Oh 356 00:21:30,760 --> 00:21:32,159 Speaker 1: I also want my kid to be tall and have 357 00:21:32,240 --> 00:21:35,880 Speaker 1: blue eyes. Yeah, it gets a little dicey, it does. 358 00:21:36,760 --> 00:21:41,879 Speaker 1: Um Designer Humans, Well, just go back and listen of 359 00:21:41,920 --> 00:21:44,240 Speaker 1: that episode. It's fun fraught with complications. You start to 360 00:21:44,320 --> 00:21:47,920 Speaker 1: run into the idea of like genetic or eugenics. Well, yeah, 361 00:21:47,960 --> 00:21:49,960 Speaker 1: they have and they have nuts because obviously not everyone 362 00:21:50,000 --> 00:21:52,280 Speaker 1: could afford to do something like that, So then you 363 00:21:52,359 --> 00:21:55,520 Speaker 1: have you know, the wealthy uber races even taller and 364 00:21:55,600 --> 00:21:58,480 Speaker 1: blonder than ever, right exactly. But then they've also decided 365 00:21:58,520 --> 00:22:01,359 Speaker 1: that tall and blond is the ideal, So then they 366 00:22:01,440 --> 00:22:06,760 Speaker 1: start like editing people's jeans who aren't tall and blond, 367 00:22:07,240 --> 00:22:08,399 Speaker 1: and then all of a sudden, you have nothing but 368 00:22:08,480 --> 00:22:12,000 Speaker 1: tall and blonde people. Right, Like you said, I've never 369 00:22:12,000 --> 00:22:15,479 Speaker 1: even seen that movie. What's a good one? Is it? Really? Yeah? Man, 370 00:22:16,400 --> 00:22:21,080 Speaker 1: they're like a you know, a thinking person's reindeer game 371 00:22:21,160 --> 00:22:25,240 Speaker 1: sci fi. You bring that movie up way too much. Um, 372 00:22:25,920 --> 00:22:29,119 Speaker 1: just a thinking person's sci fi future movie. Have you 373 00:22:29,200 --> 00:22:34,120 Speaker 1: seen Equilibrium with Christian Bale? No? I haven't either. It's 374 00:22:34,160 --> 00:22:37,160 Speaker 1: got like three stars on Netflix, and that's not enough 375 00:22:37,240 --> 00:22:39,240 Speaker 1: for me to pull the trigger on I've never heard 376 00:22:39,280 --> 00:22:41,480 Speaker 1: of that, which is a bad sign. It seems like 377 00:22:41,640 --> 00:22:43,760 Speaker 1: it's from about the same time as Gadica make me 378 00:22:43,760 --> 00:22:47,560 Speaker 1: a little earlier. But it's Christian Bale. He's good. Yeah, 379 00:22:47,920 --> 00:22:51,359 Speaker 1: it's a little crazy, he's still good. We're done, you 380 00:22:51,480 --> 00:22:54,920 Speaker 1: and me. He's never gonna live that. What a great tirade. 381 00:22:56,119 --> 00:22:58,320 Speaker 1: He did it right before we shot our TV show too, 382 00:22:58,400 --> 00:23:00,080 Speaker 1: so like we walked around on set like say and 383 00:23:00,160 --> 00:23:03,600 Speaker 1: that all that was a running joke that was fun. Uh, 384 00:23:04,640 --> 00:23:06,320 Speaker 1: you want to take another break. Let's take a break 385 00:23:06,320 --> 00:23:08,479 Speaker 1: and we'll talk about kind of where we are right 386 00:23:08,520 --> 00:23:11,639 Speaker 1: now and and what some people think about his future. 387 00:23:32,200 --> 00:23:34,520 Speaker 1: All right, Chuck. So obviously we're on the verge of 388 00:23:35,359 --> 00:23:39,760 Speaker 1: UM great designer children like probably next week, right. I 389 00:23:39,800 --> 00:23:42,640 Speaker 1: don't think it's that quick, No, But I did read 390 00:23:42,680 --> 00:23:45,520 Speaker 1: this article because this sounded too good to be true 391 00:23:45,560 --> 00:23:47,880 Speaker 1: when I was reading it. It's like, Man, the Christopher gene. 392 00:23:47,960 --> 00:23:50,840 Speaker 1: That's it's going to solve everything from food shortage to 393 00:23:51,480 --> 00:23:55,480 Speaker 1: every disease known demand like cancer. Right. Cancer, Cancer is 394 00:23:55,560 --> 00:23:59,119 Speaker 1: basically the result of UM something called the P fifty 395 00:23:59,200 --> 00:24:02,960 Speaker 1: three protein not being expressed by a gene. And the 396 00:24:03,040 --> 00:24:06,119 Speaker 1: P fifty three protein goes in and says, hey, I 397 00:24:06,200 --> 00:24:09,560 Speaker 1: think you're a tumor. You stop multiplying. And if that, 398 00:24:09,880 --> 00:24:11,840 Speaker 1: if that protein is not there to tell the cell 399 00:24:12,040 --> 00:24:14,560 Speaker 1: to stop multiplying, it keeps multiplying, and all of a sudden, 400 00:24:14,640 --> 00:24:17,399 Speaker 1: you got a tumor, a k A cancer. Right, So 401 00:24:17,920 --> 00:24:21,200 Speaker 1: you could go in and and just edit that gene 402 00:24:21,240 --> 00:24:24,760 Speaker 1: to make sure the P fifty three UM protein is expressed. Bam, 403 00:24:24,880 --> 00:24:27,760 Speaker 1: you just cured cancer on the genetic level. So yes, 404 00:24:27,840 --> 00:24:32,800 Speaker 1: it could just improve the world. Correct sir, So I 405 00:24:32,840 --> 00:24:35,920 Speaker 1: read this article, I was all excited, um, and you 406 00:24:35,960 --> 00:24:39,359 Speaker 1: should still be excited. This isn't a complete poopoo, but 407 00:24:39,960 --> 00:24:42,600 Speaker 1: this was just like this week. Uh, the gene editor 408 00:24:42,640 --> 00:24:46,679 Speaker 1: Cristoper won't fully fix sick people anytime soon. And here's why. Um. 409 00:24:46,800 --> 00:24:50,399 Speaker 1: So this lady, Jocelyn Kaiser sort of throws a bit 410 00:24:50,440 --> 00:24:54,760 Speaker 1: of a wet blanket on it, um, but not completely there. 411 00:24:54,880 --> 00:24:56,960 Speaker 1: She's just sort of like, there's still a ways to go. 412 00:24:57,359 --> 00:25:01,240 Speaker 1: So here's one of the things, um, most diseases apparently, 413 00:25:02,359 --> 00:25:08,760 Speaker 1: uh like cystic fibrosis, muscular dystrophy um, where gene correction 414 00:25:09,000 --> 00:25:11,480 Speaker 1: is already kind of a thing, like where they require 415 00:25:11,560 --> 00:25:16,840 Speaker 1: gene correction. Um. Basically, what she's saying is it has 416 00:25:16,840 --> 00:25:18,960 Speaker 1: to be done in a living person. Like you can't 417 00:25:19,000 --> 00:25:21,280 Speaker 1: extract the cells and do it and then put the 418 00:25:21,320 --> 00:25:23,920 Speaker 1: cells back in like they currently do with gene transfer, 419 00:25:24,760 --> 00:25:28,520 Speaker 1: because uh, not enough of the cells will survive apparently. 420 00:25:29,240 --> 00:25:31,560 Speaker 1: So that's one of the roadblocks right now. You need 421 00:25:31,640 --> 00:25:34,639 Speaker 1: to treat the cells inside the body. Well, one thing 422 00:25:34,720 --> 00:25:36,920 Speaker 1: I have challenge, one thing I wondered maybe this this 423 00:25:37,200 --> 00:25:40,199 Speaker 1: um lady talks about it. But how do you how 424 00:25:40,240 --> 00:25:45,399 Speaker 1: do you direct the the Crisper CAST nine system to 425 00:25:45,640 --> 00:25:49,359 Speaker 1: the right cell? She just said it's I mean, in 426 00:25:49,440 --> 00:25:52,000 Speaker 1: her ted talk, she doesn't get super specific. She says, 427 00:25:52,040 --> 00:25:56,600 Speaker 1: it's an RNA guided protein. Um, that's what I ran 428 00:25:56,640 --> 00:25:58,679 Speaker 1: across too. I didn't run acress anybody said, oh well 429 00:25:58,760 --> 00:26:00,680 Speaker 1: this is how did that look for that too? I 430 00:26:00,720 --> 00:26:06,240 Speaker 1: think it will just call it the magic of science. Um. Yeah, 431 00:26:06,320 --> 00:26:08,240 Speaker 1: but I mean it's it's very precise though. You know, 432 00:26:08,320 --> 00:26:09,639 Speaker 1: it's not like they just throw it in there and 433 00:26:09,680 --> 00:26:13,080 Speaker 1: see what happens. So there there's something guiding it. Um. 434 00:26:13,880 --> 00:26:17,280 Speaker 1: It's a safety risk right now because when this this 435 00:26:18,000 --> 00:26:21,359 Speaker 1: Crisper cleaves it off with the scissors. Uh, it is 436 00:26:21,440 --> 00:26:24,360 Speaker 1: in a very specific location. But they don't know yet 437 00:26:24,440 --> 00:26:27,600 Speaker 1: if it could potentially, because once you've created these things, 438 00:26:27,680 --> 00:26:30,080 Speaker 1: you deliver it through a viral vector. It's in there 439 00:26:30,480 --> 00:26:32,919 Speaker 1: and this cast nine is going to keep replicating itself 440 00:26:33,000 --> 00:26:36,399 Speaker 1: for forever. So they don't know if fifteen years down 441 00:26:36,440 --> 00:26:39,960 Speaker 1: the line, if the thing starts cleaving causing cancer basically. 442 00:26:41,119 --> 00:26:43,640 Speaker 1: But what they think now is they haven't seen that yet. 443 00:26:44,119 --> 00:26:46,080 Speaker 1: So it's just like, let's keep an eye out for 444 00:26:46,200 --> 00:26:49,159 Speaker 1: this so it's not like the worst news ever, but 445 00:26:49,280 --> 00:26:51,800 Speaker 1: so far these mice are doing well and that's not happening. Well. 446 00:26:51,920 --> 00:26:54,720 Speaker 1: This is like a very hot topic in bioethics as well, 447 00:26:54,840 --> 00:26:56,920 Speaker 1: and one of the things that people I'm sure like 448 00:26:57,200 --> 00:27:02,280 Speaker 1: um Dubner are um pressing for is figuring out how 449 00:27:02,320 --> 00:27:05,440 Speaker 1: to reverse engineer the stuff or reverse the effects of it, 450 00:27:06,000 --> 00:27:09,399 Speaker 1: to engineer it so it stops after a while, so 451 00:27:09,560 --> 00:27:12,520 Speaker 1: that if it it like if you did introduce it 452 00:27:12,600 --> 00:27:16,120 Speaker 1: into a wild population, it wouldn't just wipe that population 453 00:27:16,200 --> 00:27:19,240 Speaker 1: off the face of the earth. It would eventually slow. 454 00:27:19,760 --> 00:27:22,320 Speaker 1: Well that's exactly what they're hoping to do, is that 455 00:27:22,440 --> 00:27:25,639 Speaker 1: CAST nine will eventually stop doing it thing there's you 456 00:27:25,720 --> 00:27:28,399 Speaker 1: can hope in one hand and then figure it out scientifically. 457 00:27:28,480 --> 00:27:31,159 Speaker 1: And they're trying to figure it out. Okay, yeah, I 458 00:27:31,280 --> 00:27:33,760 Speaker 1: thought you were saying, like yeah, they just oh no, no, no, 459 00:27:33,920 --> 00:27:35,879 Speaker 1: that that they know that's an issue, and that's one 460 00:27:35,920 --> 00:27:38,920 Speaker 1: of the like roadblocks are trying to overcome. One of 461 00:27:38,960 --> 00:27:42,000 Speaker 1: the other things is the CAST nine um it's a 462 00:27:42,080 --> 00:27:44,720 Speaker 1: process that it can only be active when the cells 463 00:27:44,760 --> 00:27:49,440 Speaker 1: are like dividing actively dividing, and apparently that's just not 464 00:27:49,760 --> 00:27:54,040 Speaker 1: you know, the liver, you're stem cells, your eyes, your blood. 465 00:27:54,400 --> 00:27:58,280 Speaker 1: It's not always actively dividing. So they're trying to work 466 00:27:58,400 --> 00:28:03,560 Speaker 1: around that. Basically every limitation they found so far, they're saying, 467 00:28:04,160 --> 00:28:06,840 Speaker 1: it's not a it's not a deal Breaker's not a 468 00:28:06,880 --> 00:28:10,119 Speaker 1: deal breaker. Yeah, we think we can figure something out 469 00:28:10,200 --> 00:28:12,280 Speaker 1: to work around it. I'm sure they will. So that's 470 00:28:12,280 --> 00:28:14,960 Speaker 1: the good news. It's just too it seems to be 471 00:28:15,200 --> 00:28:18,080 Speaker 1: working too well, and it's just too easy to do. 472 00:28:19,280 --> 00:28:22,200 Speaker 1: There's this there's not just gonna like leave it on 473 00:28:22,280 --> 00:28:25,320 Speaker 1: the table. Well, no way. I couldn't get around the 474 00:28:25,400 --> 00:28:28,720 Speaker 1: liver cells not replicating. Uh. And then you know, we 475 00:28:28,800 --> 00:28:31,720 Speaker 1: mentioned HIV earlier. This article needs updating in our on 476 00:28:31,800 --> 00:28:36,720 Speaker 1: our site because it said that it kind of overcame HIV. Uh, 477 00:28:36,920 --> 00:28:40,520 Speaker 1: but that's not true. Now apparently HIV defeated the efforts 478 00:28:41,400 --> 00:28:46,160 Speaker 1: Christoper right now, but again they said that this isn't 479 00:28:46,320 --> 00:28:51,120 Speaker 1: this doesn't mean it's over. Um, we think we can 480 00:28:51,200 --> 00:28:54,520 Speaker 1: overcome this as well, and that eventually could be a 481 00:28:54,600 --> 00:28:57,760 Speaker 1: cure for HIV. So right now, and they said they 482 00:28:57,800 --> 00:29:00,640 Speaker 1: weren't too surprised because HIV. To go back and listen 483 00:29:00,680 --> 00:29:03,360 Speaker 1: to our episode on that it is a tough tough 484 00:29:04,240 --> 00:29:09,080 Speaker 1: cookie cookie and UM has a knack for mutating and 485 00:29:09,200 --> 00:29:12,440 Speaker 1: replicating in the face of all kinds of drugs. But 486 00:29:12,520 --> 00:29:14,160 Speaker 1: they think if they use those drugs along with this, 487 00:29:14,320 --> 00:29:19,360 Speaker 1: maybe that could be an alternative. UM. Yeah, I mean 488 00:29:19,400 --> 00:29:21,560 Speaker 1: the future is bright. I think they just it's so 489 00:29:21,760 --> 00:29:24,880 Speaker 1: early in the game, is the deal. But that's why 490 00:29:25,080 --> 00:29:27,280 Speaker 1: I think a pause is a good idea. I don't 491 00:29:27,320 --> 00:29:31,120 Speaker 1: know if I've gotten that across that. I feel like, Yeah, 492 00:29:31,480 --> 00:29:33,640 Speaker 1: there's one other thing I ran across and researching, something 493 00:29:33,680 --> 00:29:37,360 Speaker 1: called a DNA drive. You can take this Crisper gene 494 00:29:37,760 --> 00:29:43,000 Speaker 1: UM Crisper cast nine system, and UM you can add 495 00:29:43,080 --> 00:29:46,000 Speaker 1: this other component called a DNA drive. Right, And so 496 00:29:46,120 --> 00:29:49,800 Speaker 1: this DNA drive is basically like UM. It has the 497 00:29:49,880 --> 00:29:56,280 Speaker 1: ability to during reproduction two not only take the edited gene, 498 00:29:56,960 --> 00:29:59,680 Speaker 1: or not only to edit a gene in say a 499 00:29:59,720 --> 00:30:04,880 Speaker 1: miss guito, but when that mosquito reproduces the chromosomes that 500 00:30:04,920 --> 00:30:11,480 Speaker 1: are contributed with the edited gene, basically, UM break the 501 00:30:11,760 --> 00:30:16,960 Speaker 1: corresponding spot on the other parents chromosomes, and then when 502 00:30:17,080 --> 00:30:21,280 Speaker 1: it repairs itself inserts the blueprints so that the edited 503 00:30:21,360 --> 00:30:26,440 Speaker 1: gene is copied. So then the offspring has both two 504 00:30:26,520 --> 00:30:30,360 Speaker 1: pair or one pair of the edited gene, which means 505 00:30:30,400 --> 00:30:33,840 Speaker 1: when they reproduce and they reproduce to somebody else that 506 00:30:33,960 --> 00:30:38,240 Speaker 1: has both pairs of the same gene, um their offspring 507 00:30:38,320 --> 00:30:42,280 Speaker 1: has a chance of inheriting that gene and so it 508 00:30:42,360 --> 00:30:46,560 Speaker 1: can spread through a population of mosquitoes and fix it 509 00:30:46,640 --> 00:30:51,080 Speaker 1: for your family, fixes it or keeps you from reproducing 510 00:30:51,160 --> 00:30:54,720 Speaker 1: or whatever. The gene is. Yes, and in a large population, 511 00:30:54,800 --> 00:30:57,440 Speaker 1: say like a big mosquito population, that means you can 512 00:30:57,560 --> 00:31:00,240 Speaker 1: spread the edited gene and like a single growing reason. 513 00:31:01,000 --> 00:31:03,200 Speaker 1: But that's one reason why people are like, we need 514 00:31:03,240 --> 00:31:04,600 Speaker 1: to figure out how to be able to turn this 515 00:31:04,760 --> 00:31:08,320 Speaker 1: off because maybe we need mosquitoes. That turns out we 516 00:31:08,360 --> 00:31:10,280 Speaker 1: shouldn't just wipe them off the face of the earth, 517 00:31:10,680 --> 00:31:12,320 Speaker 1: although we remember we did a show on that, and 518 00:31:13,160 --> 00:31:15,240 Speaker 1: some scientists think, no, we don't need them. Yeah, I 519 00:31:15,320 --> 00:31:18,280 Speaker 1: remember that. Are you got anything else? I got nothing else. 520 00:31:18,440 --> 00:31:20,080 Speaker 1: I'm sure we can do a follow up on this 521 00:31:20,240 --> 00:31:22,880 Speaker 1: if we want. If you want to know more about 522 00:31:22,880 --> 00:31:27,160 Speaker 1: the Crisper gene editing, sweet, you can type that word 523 00:31:27,240 --> 00:31:29,240 Speaker 1: into the search part house to works dot com and 524 00:31:29,320 --> 00:31:34,600 Speaker 1: insisted search parts time for listener mail. I'm gonna call 525 00:31:34,680 --> 00:31:37,080 Speaker 1: this l s D. We've got a lot of great 526 00:31:37,080 --> 00:31:41,320 Speaker 1: emails from well, I just read this from people who 527 00:31:41,560 --> 00:31:44,400 Speaker 1: use it and like it. Hey, guys, love the show, 528 00:31:44,480 --> 00:31:46,200 Speaker 1: but UH, it's been great to learn so much about 529 00:31:46,200 --> 00:31:48,680 Speaker 1: a variety of topics to and from work. I recently 530 00:31:48,680 --> 00:31:50,920 Speaker 1: listened to LSD. I got to share my story. Three 531 00:31:51,000 --> 00:31:54,240 Speaker 1: years ago, my father died unexpectedly a stroke, and it 532 00:31:54,280 --> 00:31:57,800 Speaker 1: took my whole family by surprise. And became very depressed 533 00:31:57,840 --> 00:32:00,520 Speaker 1: for MutS and felt like I was diving into on 534 00:32:00,640 --> 00:32:02,880 Speaker 1: autopilot and wasn't finding any enjoyment in my day to 535 00:32:02,960 --> 00:32:04,800 Speaker 1: day life. One night, I was hanging out with my 536 00:32:04,840 --> 00:32:07,600 Speaker 1: friends and was offered some LSD. I had taken some 537 00:32:07,720 --> 00:32:10,120 Speaker 1: years ago and had a wonderful experience with it, so 538 00:32:10,240 --> 00:32:12,440 Speaker 1: I thought maybe this could be helpful. Turned out to 539 00:32:12,480 --> 00:32:15,160 Speaker 1: be the best decision I ever made. I had several 540 00:32:15,200 --> 00:32:18,720 Speaker 1: powerful revelations about life and developed a deeper appreciation for 541 00:32:19,040 --> 00:32:21,440 Speaker 1: my friends and family and for the love that binds 542 00:32:21,520 --> 00:32:24,120 Speaker 1: us all together. Also gained a fresh perspective on how 543 00:32:24,200 --> 00:32:26,320 Speaker 1: much beauty there is in the world and how I 544 00:32:26,360 --> 00:32:29,680 Speaker 1: am a part of it. This experience really helped UH 545 00:32:29,800 --> 00:32:31,240 Speaker 1: set me back on the right path and is a 546 00:32:31,320 --> 00:32:34,880 Speaker 1: moment in my life that can point to as life changing. 547 00:32:35,280 --> 00:32:36,880 Speaker 1: I believe the drug has a lot of potential for 548 00:32:36,960 --> 00:32:40,720 Speaker 1: psychiatric use, can be immensely beneficial with helping people work 549 00:32:40,760 --> 00:32:44,840 Speaker 1: through serious psychological and emotional issues. I truly hope that 550 00:32:44,960 --> 00:32:47,720 Speaker 1: it is reclassified from Schedule one so it can be 551 00:32:47,840 --> 00:32:51,200 Speaker 1: further studied and seen as a medicinal aid and not 552 00:32:51,400 --> 00:32:55,520 Speaker 1: a harmful chemical. Uh. And that I'm gonna just say 553 00:32:55,720 --> 00:32:58,400 Speaker 1: is from anonymous because I didn't hear back whether or 554 00:32:58,440 --> 00:33:00,479 Speaker 1: not this dude wanted his name right on the air. 555 00:33:00,680 --> 00:33:04,520 Speaker 1: Thanks a lot, anonymous, anonymous man, and thanks to everybody 556 00:33:04,560 --> 00:33:06,880 Speaker 1: who sending emails like that. We heard from a lot 557 00:33:06,920 --> 00:33:09,160 Speaker 1: of people who are like, yeah, I really love acid, 558 00:33:09,840 --> 00:33:13,360 Speaker 1: you know, and you know they weren't stories from people 559 00:33:13,400 --> 00:33:15,720 Speaker 1: that hurt, like you're going to hear this man. Yeah, 560 00:33:15,760 --> 00:33:18,640 Speaker 1: it was like, hey, I enjoy taking LSD sometimes and 561 00:33:18,680 --> 00:33:22,320 Speaker 1: I'm a responsible, growing up adult and nothing that helps 562 00:33:22,360 --> 00:33:24,240 Speaker 1: me out. I don't think we got a single one 563 00:33:24,360 --> 00:33:30,239 Speaker 1: like that was just a jackass taking LSD, Like all 564 00:33:30,280 --> 00:33:33,680 Speaker 1: of them are very thoughtful and because that's our audience, buddy, Yeah, 565 00:33:34,480 --> 00:33:38,840 Speaker 1: full drug users, if you want to get in touch 566 00:33:38,920 --> 00:33:41,520 Speaker 1: with us to let us know what's just about anything. 567 00:33:41,600 --> 00:33:43,880 Speaker 1: You can tweet to us at s y s K Podcast. 568 00:33:44,200 --> 00:33:46,960 Speaker 1: You can join us on Instagram That's s y s 569 00:33:47,000 --> 00:33:49,480 Speaker 1: K Podcast as well. You can join us on Facebook 570 00:33:49,520 --> 00:33:51,560 Speaker 1: dot com slash stuff you Should Know. You can send 571 00:33:51,640 --> 00:33:53,840 Speaker 1: us an email to Stuff Podcast at how stuff Works 572 00:33:53,880 --> 00:33:55,800 Speaker 1: dot com and has always joined us at our home 573 00:33:55,840 --> 00:34:03,000 Speaker 1: on the web, Stuff you Should Know dot com. For 574 00:34:03,120 --> 00:34:05,640 Speaker 1: more on this and thousands of other topics, visit how 575 00:34:05,680 --> 00:34:13,440 Speaker 1: staff works dot com. M