1 00:00:13,880 --> 00:00:19,800 Speaker 1: He's looking at bacteria in very, very salty ponge, and 2 00:00:20,640 --> 00:00:24,560 Speaker 1: he notices something when he's sequencing the genes. Because this 3 00:00:24,680 --> 00:00:27,040 Speaker 1: is getting in the late nineteen ninety when we finally 4 00:00:27,280 --> 00:00:28,960 Speaker 1: can gene sequence. But it's hard. 5 00:00:29,960 --> 00:00:33,360 Speaker 2: In science. Sometimes a world changing breakthrough arrives at the 6 00:00:33,440 --> 00:00:36,239 Speaker 2: end of a long chain of discovery, a chain that 7 00:00:36,280 --> 00:00:40,640 Speaker 2: starts with an obscure or even trivial seeming observation. So 8 00:00:40,720 --> 00:00:44,000 Speaker 2: it was that in nineteen ninety a young microbiologist named 9 00:00:44,040 --> 00:00:47,880 Speaker 2: Francisco Mohica began working on his PhD in his native 10 00:00:47,880 --> 00:00:51,879 Speaker 2: city of Alecante, on the Mediterranean coast of Spain, a 11 00:00:51,960 --> 00:00:55,600 Speaker 2: medieval port with narrow streets, colorfully painted houses, and sweeping 12 00:00:55,680 --> 00:00:59,120 Speaker 2: views across the sea to Algiers. Alcante was also the 13 00:00:59,120 --> 00:01:02,520 Speaker 2: home to a collection of salty ponds ten times saltier 14 00:01:02,520 --> 00:01:06,160 Speaker 2: than the ocean. Mohika's research focused on the genomes of 15 00:01:06,240 --> 00:01:10,720 Speaker 2: tiny bacteria like organisms thriving in the ponds, called archie. 16 00:01:11,800 --> 00:01:16,640 Speaker 1: He keeps seeing these repeated sequences in the genes of bacteria, 17 00:01:17,160 --> 00:01:21,520 Speaker 1: and they're clustered repeated sequences, and he can't He thinks 18 00:01:21,520 --> 00:01:24,440 Speaker 1: he's made a mistake. It's like if you type a 19 00:01:24,480 --> 00:01:27,399 Speaker 1: story and an old version of Microsoft word, and the 20 00:01:27,440 --> 00:01:30,680 Speaker 1: paragraph keeps repeating. You think, well, I didn't do that, 21 00:01:30,680 --> 00:01:33,760 Speaker 1: that's a mistake. But as he keeps testing it out, 22 00:01:33,840 --> 00:01:35,880 Speaker 1: he sees these repeat. 23 00:01:36,280 --> 00:01:41,240 Speaker 2: These repeats also read the same forwards and backwards, like palindromes. 24 00:01:41,440 --> 00:01:44,440 Speaker 2: Walter Isaacson writes, they look like tiny knots and a 25 00:01:44,440 --> 00:01:48,280 Speaker 2: string of otherwise regular genetic rope, and Mohika had no 26 00:01:48,360 --> 00:01:51,760 Speaker 2: idea what they were. Isaacson says that only got it 27 00:01:51,840 --> 00:01:52,440 Speaker 2: more curious. 28 00:01:53,400 --> 00:01:56,120 Speaker 1: He goes to the library. There's before you could google things, 29 00:01:56,160 --> 00:01:59,400 Speaker 1: before there's a database. So he goes to the library 30 00:01:59,520 --> 00:02:02,920 Speaker 1: and looks up indexes and a Japanese scientists had seen 31 00:02:02,960 --> 00:02:05,520 Speaker 1: this in a bacteria, and so soon you have a 32 00:02:05,560 --> 00:02:08,760 Speaker 1: few scientists say why are there these things? 33 00:02:12,680 --> 00:02:16,040 Speaker 2: The Japanese scientists who had also noticed these clustered sequences 34 00:02:16,400 --> 00:02:20,000 Speaker 2: was Yoshizumi is she No. A few years before Mohika. 35 00:02:20,160 --> 00:02:22,760 Speaker 2: Ishino had found the same clusters in a very different 36 00:02:22,800 --> 00:02:25,640 Speaker 2: type of bacteria. In his paper on the discovery, he 37 00:02:25,720 --> 00:02:30,800 Speaker 2: wrote that the biological significance of these sequences is not known. Still, 38 00:02:30,960 --> 00:02:33,480 Speaker 2: the fact that both researchers had found the same pattern 39 00:02:33,600 --> 00:02:37,400 Speaker 2: in extremely different organisms convinced Mohika that these clusters might 40 00:02:37,440 --> 00:02:41,079 Speaker 2: have an important purpose. For years, he kept experimenting with them, 41 00:02:41,280 --> 00:02:44,760 Speaker 2: leading a growing international network of scientists interested in figuring 42 00:02:44,760 --> 00:02:45,760 Speaker 2: out their significance. 43 00:02:46,080 --> 00:02:48,200 Speaker 1: And the first thing they do is they try to 44 00:02:48,200 --> 00:02:50,880 Speaker 1: figure out a name for it, and it's front Jay 45 00:02:50,880 --> 00:02:54,200 Speaker 1: Skill Mohico, driving back from his wife, was on the 46 00:02:54,200 --> 00:02:56,200 Speaker 1: beach and he was bored with the beach, goes back 47 00:02:56,240 --> 00:03:01,840 Speaker 1: to his lab and he says, well, their cluster repeated sequences. 48 00:03:02,280 --> 00:03:06,480 Speaker 2: Mohika's thesis adviser had suggested the name tandem repeats, not 49 00:03:06,600 --> 00:03:10,720 Speaker 2: exactly the catchist a colleague in the Netherlands suggested direct repeats. 50 00:03:11,120 --> 00:03:14,240 Speaker 2: That wasn't quite it either, So Mohika kept thinking and. 51 00:03:14,160 --> 00:03:16,760 Speaker 1: He comes up with the name Crisper. And he said, 52 00:03:16,800 --> 00:03:21,240 Speaker 1: because it's a memorable, fun name, it's not intimidating, And 53 00:03:21,280 --> 00:03:28,120 Speaker 1: he then back engineers it. I think it's clustered, repeated innerspace, palindropic, 54 00:03:28,240 --> 00:03:31,679 Speaker 1: repeated sequence, whatever it may be. But it was called 55 00:03:31,720 --> 00:03:33,800 Speaker 1: Crisper just because he liked the name crisper. And it 56 00:03:33,800 --> 00:03:36,400 Speaker 1: doesn't have an e it's Chrisper with an out an ease, 57 00:03:36,440 --> 00:03:39,920 Speaker 1: so it makes it look futuristic. So he's the guy 58 00:03:40,360 --> 00:03:46,600 Speaker 1: who first understands that bacteria have these repeated sequences and 59 00:03:46,640 --> 00:03:49,960 Speaker 1: he names them, but nobody knows why they exist, and 60 00:03:49,960 --> 00:03:51,280 Speaker 1: that's when the hunt begins. 61 00:03:52,000 --> 00:03:54,720 Speaker 2: Mohika had no way of knowing none, but this tiny 62 00:03:54,920 --> 00:03:58,920 Speaker 2: palindrome gene he'd found inside assault loving bacteria would become 63 00:03:58,960 --> 00:04:02,200 Speaker 2: the tiny engine. I think a new revolution in gene editing. 64 00:04:03,160 --> 00:04:05,960 Speaker 2: I'm Evan Ratliffe and this is on Crisper, the story 65 00:04:05,960 --> 00:04:12,800 Speaker 2: of Jennifer Downa, episode two Crisper. It goes back to 66 00:04:12,840 --> 00:04:16,919 Speaker 2: that sort of passion and obsession over these what seemed 67 00:04:16,960 --> 00:04:19,520 Speaker 2: like tiny questions to us. A guy in salt ponds 68 00:04:19,520 --> 00:04:22,440 Speaker 2: who's just obsessed with the bacteria that live there, which 69 00:04:22,880 --> 00:04:25,719 Speaker 2: kind of goes back to the sleeping grass and really 70 00:04:25,800 --> 00:04:28,840 Speaker 2: wanting to know. But this guy has no idea where 71 00:04:28,839 --> 00:04:29,960 Speaker 2: this discovery is going to lead. 72 00:04:30,080 --> 00:04:33,680 Speaker 1: This is the big deal, which is it's pure curiosity 73 00:04:33,760 --> 00:04:37,640 Speaker 1: about some quirk of nature, and you have no idea 74 00:04:37,880 --> 00:04:40,320 Speaker 1: that it's going to lead to a tool to fight viruses, 75 00:04:40,360 --> 00:04:42,360 Speaker 1: it's going to lead to a tool to edit jeens 76 00:04:42,440 --> 00:04:46,720 Speaker 1: or anything else. You're just curious why did nature do this? 77 00:04:47,400 --> 00:04:50,960 Speaker 2: And apparently the major journals also didn't know where it 78 00:04:50,960 --> 00:04:53,720 Speaker 2: would lead since his findings were initially rejected. 79 00:04:54,160 --> 00:04:58,839 Speaker 1: He's a sort of unknown junior scientist, I think in 80 00:04:59,640 --> 00:05:05,040 Speaker 1: Ali Spain. And so one of the problems is you 81 00:05:05,080 --> 00:05:07,960 Speaker 1: can't really make a discovery of science unless you can 82 00:05:08,040 --> 00:05:09,919 Speaker 1: publish it. I mean, that's the way we put the 83 00:05:10,000 --> 00:05:13,760 Speaker 1: stamp on it. And he's having trouble getting this published 84 00:05:13,800 --> 00:05:16,200 Speaker 1: in a journal, and so are other people who are 85 00:05:16,200 --> 00:05:19,200 Speaker 1: looking at Crisper because it's like, okay, fine, and even 86 00:05:19,279 --> 00:05:23,400 Speaker 1: his advisors at the university it's like fine, fine, fine, 87 00:05:23,480 --> 00:05:26,680 Speaker 1: you see bacteria repeat themselves a few times, but now 88 00:05:26,880 --> 00:05:28,400 Speaker 1: go on to something that's important. 89 00:05:29,200 --> 00:05:31,479 Speaker 2: But Mohika suspected that there had to be a reason 90 00:05:31,520 --> 00:05:35,000 Speaker 2: for these clustered sequences to keep showing up, and Isaacson 91 00:05:35,040 --> 00:05:37,920 Speaker 2: says it was an instinct driven by a fundamental piece 92 00:05:37,960 --> 00:05:38,599 Speaker 2: of knowledge. 93 00:05:39,520 --> 00:05:43,479 Speaker 1: Nature loves simplicity. It's not going to have some complexity 94 00:05:43,480 --> 00:05:47,440 Speaker 1: of repeated sequences unless there's a reason. I mean, bacteria 95 00:05:47,520 --> 00:05:50,760 Speaker 1: don't have that much genetic material, so you don't want 96 00:05:50,760 --> 00:05:54,039 Speaker 1: to waste it repeating yourself. So there must be a 97 00:05:54,279 --> 00:06:01,000 Speaker 1: reason that these things exist. As these basic scientists like 98 00:06:01,040 --> 00:06:05,279 Speaker 1: Francisco Molica are doing this out of pure curiosity. You 99 00:06:05,400 --> 00:06:08,839 Speaker 1: have two food scientists who work for Denisko, one of 100 00:06:08,839 --> 00:06:14,080 Speaker 1: these huge French food companies. It's Rudolph Bolngu and Phelippe Porvath. 101 00:06:14,240 --> 00:06:16,440 Speaker 1: They're both French, but one of them is moved to 102 00:06:16,480 --> 00:06:19,640 Speaker 1: North Carolina to study food. And I'm thinking, this is 103 00:06:19,680 --> 00:06:22,640 Speaker 1: the only guy I ever met who moved from Paris 104 00:06:22,680 --> 00:06:27,600 Speaker 1: to North Carolina to study food. And they make starters 105 00:06:27,920 --> 00:06:32,520 Speaker 1: cultures for yogurt and cheese, and the starter cultures or bacteria. 106 00:06:33,240 --> 00:06:38,560 Speaker 1: And one problem they have is that viruses attack bacteria. 107 00:06:38,880 --> 00:06:42,799 Speaker 1: You think we got a problem with viruses man. For 108 00:06:43,560 --> 00:06:48,000 Speaker 1: two billion years or so, bacteria have been fighting off viruses. 109 00:06:48,040 --> 00:06:51,760 Speaker 1: It's the biggest battle on this planet. It's ongoing. And 110 00:06:51,839 --> 00:06:55,400 Speaker 1: so these yogurt cultures are getting messed up by viruses. 111 00:06:55,960 --> 00:06:59,359 Speaker 1: And you have these two scientists who are sequencing the 112 00:06:59,440 --> 00:07:03,440 Speaker 1: genetic code. And the cool thing about DNISCO is it's 113 00:07:03,440 --> 00:07:07,400 Speaker 1: got a whole database of every culture they've had going 114 00:07:07,480 --> 00:07:10,360 Speaker 1: back to nineteen eighty or so, and so you can 115 00:07:10,400 --> 00:07:15,800 Speaker 1: look at how the DNA changes and they discover that 116 00:07:16,480 --> 00:07:20,640 Speaker 1: the crisper sequences or what's in between the crisper sequences 117 00:07:21,440 --> 00:07:26,080 Speaker 1: are mug shots of the genetic code of some viruses 118 00:07:26,200 --> 00:07:29,520 Speaker 1: that attack them. And every time a new virus attacks, 119 00:07:29,560 --> 00:07:33,720 Speaker 1: and every year or two or three, the bacteria that 120 00:07:33,800 --> 00:07:37,560 Speaker 1: survive have some of that genetic code in these repeated 121 00:07:37,600 --> 00:07:42,720 Speaker 1: sequences and clusters, and they realize this is a way 122 00:07:43,520 --> 00:07:48,360 Speaker 1: that bacteria have a mug shot to know if there's 123 00:07:48,400 --> 00:07:52,680 Speaker 1: a dangerous virus coming in and how will they kill it. 124 00:07:52,680 --> 00:07:56,040 Speaker 1: It meant that in the future the bacteria would know 125 00:07:56,640 --> 00:07:59,400 Speaker 1: how to ward off those virus So it was in 126 00:07:59,480 --> 00:08:07,080 Speaker 1: adaptive immune system against viruses, which may seem pretty technical, 127 00:08:07,440 --> 00:08:10,280 Speaker 1: but it was quite useful in saving the yogurt industry. 128 00:08:10,520 --> 00:08:12,920 Speaker 1: And by the way, we didn't know it at the time, 129 00:08:13,680 --> 00:08:17,000 Speaker 1: but understanding and adaptive immune system, they could fight off 130 00:08:17,120 --> 00:08:20,440 Speaker 1: viruses that came in pretty handy for humans later on. 131 00:08:21,240 --> 00:08:23,320 Speaker 2: And that in and of itself, if you just told 132 00:08:23,320 --> 00:08:26,000 Speaker 2: that story, that's a fascinating bit of science. 133 00:08:26,240 --> 00:08:30,480 Speaker 1: It's a huge, huge thing for Denisko and for anybody 134 00:08:30,480 --> 00:08:33,960 Speaker 1: who eats yogurt and eats cheese. We'd be in trouble 135 00:08:34,040 --> 00:08:36,320 Speaker 1: every year, just like maybe we have trouble with bird 136 00:08:36,400 --> 00:08:38,840 Speaker 1: flu every now and then we can't get eggs. We'd 137 00:08:38,840 --> 00:08:41,760 Speaker 1: have trouble with yogurt and cheese if the entire billion 138 00:08:41,800 --> 00:08:45,000 Speaker 1: dollar industry of starter culture, you know, was wiped out. 139 00:08:45,520 --> 00:08:48,240 Speaker 2: So at this point in the story, we we sort 140 00:08:48,240 --> 00:08:51,720 Speaker 2: of know what crisper is and we know what it does, 141 00:08:52,280 --> 00:08:56,440 Speaker 2: but not how. And so that's when Jennifer Downer re 142 00:08:56,559 --> 00:09:00,040 Speaker 2: enters the picture for us, in that she has a 143 00:09:00,080 --> 00:09:03,040 Speaker 2: conversation with one of her colleagues that leads her down 144 00:09:03,040 --> 00:09:05,640 Speaker 2: the road to crisper because she wasn't studying crisper when 145 00:09:05,640 --> 00:09:06,520 Speaker 2: this started. 146 00:09:06,280 --> 00:09:11,720 Speaker 1: Right, Jennifer data had a colleague at Berkeley named Jillian Banfield. 147 00:09:11,760 --> 00:09:14,720 Speaker 1: They hadn't really met each other because Berkeley is so big, 148 00:09:14,720 --> 00:09:19,000 Speaker 1: but Jillian Banfield was just looking at bacteria from weird 149 00:09:19,480 --> 00:09:24,120 Speaker 1: places like Yellowstone and others and noticing this crispher and 150 00:09:24,120 --> 00:09:27,400 Speaker 1: they're trying to say, how does it work? So she 151 00:09:27,600 --> 00:09:32,160 Speaker 1: looks through the database at Berkeley for anybody who is 152 00:09:32,400 --> 00:09:37,199 Speaker 1: studying RNA and RNA interference, and who pops up, of course, 153 00:09:37,200 --> 00:09:42,640 Speaker 1: as Jennifer Dowder, because she's the RNA expert at Berkeley, 154 00:09:43,120 --> 00:09:46,960 Speaker 1: and Jennifer was a biochemist, in other words, looking at 155 00:09:46,960 --> 00:09:50,480 Speaker 1: the chemistry of how biology works. And there's a subtle 156 00:09:50,520 --> 00:09:55,640 Speaker 1: difference because Jillian Banfield was a microbiologist, meaning she looked 157 00:09:55,679 --> 00:09:58,800 Speaker 1: at small organism. She didn't look at test tubes. She 158 00:09:58,920 --> 00:10:02,240 Speaker 1: looked at real organisms and tried to figure out they work. 159 00:10:02,679 --> 00:10:08,520 Speaker 1: So you needed a combination of biochemistry and microbiology or 160 00:10:08,559 --> 00:10:12,800 Speaker 1: biology of small things to make this work. They met 161 00:10:12,920 --> 00:10:15,960 Speaker 1: one afternoon at the Free Speech Cafe. I love the 162 00:10:16,040 --> 00:10:17,839 Speaker 1: name of it because those of us who are old 163 00:10:17,960 --> 00:10:21,360 Speaker 1: enough to remember, Berkeley had a great free speech movement. 164 00:10:21,800 --> 00:10:23,840 Speaker 1: And so there's a cafe right as you come on 165 00:10:23,920 --> 00:10:28,319 Speaker 1: to the campus near the library. And Jillian Banfield has 166 00:10:28,360 --> 00:10:31,560 Speaker 1: been studying Crisper and trying to figure out we know 167 00:10:31,679 --> 00:10:36,640 Speaker 1: it tries to stop viruses that attack bacteria, but how 168 00:10:36,720 --> 00:10:40,000 Speaker 1: does he do it? What's the mechanism? And she brings 169 00:10:40,080 --> 00:10:42,960 Speaker 1: all these print outs and they talk about it, and 170 00:10:43,080 --> 00:10:47,359 Speaker 1: Jennifer gets it and says, I'm not sure it's RNA interference, 171 00:10:47,360 --> 00:10:54,840 Speaker 1: but there's a mechanism that these Crisper sequences in the bacteria. 172 00:10:54,960 --> 00:11:00,800 Speaker 1: Somehow or another, they have a mechanism that attacks viruses. 173 00:11:02,679 --> 00:11:06,800 Speaker 2: And she starts her lab looking into that question. So 174 00:11:06,800 --> 00:11:10,120 Speaker 2: she's intrigued enough to get her lab looking into it. 175 00:11:10,440 --> 00:11:13,760 Speaker 1: Right, she kind of is not absolutely sure. But she 176 00:11:14,000 --> 00:11:16,720 Speaker 1: likes Gillian Banfield when they meet at the cafe and 177 00:11:16,760 --> 00:11:20,439 Speaker 1: it's like, you're really you're passionate about your little bacteria 178 00:11:20,480 --> 00:11:24,120 Speaker 1: and you found in copper mine waste lands and something 179 00:11:24,120 --> 00:11:27,840 Speaker 1: that have these repeated sequences and yeah, I've now read 180 00:11:27,840 --> 00:11:30,520 Speaker 1: the papers and maybe, but she said, I don't think 181 00:11:30,559 --> 00:11:32,440 Speaker 1: I have anybody in my lab who can do it. 182 00:11:33,280 --> 00:11:36,880 Speaker 1: And that's when a guy, Blake Whedon Have walks into 183 00:11:36,960 --> 00:11:41,840 Speaker 1: Jennifer's lab and wants a job, and Jennifer's interviewing and 184 00:11:41,880 --> 00:11:43,760 Speaker 1: he's one of those guys who grew up near a 185 00:11:43,800 --> 00:11:47,840 Speaker 1: yellowstone and he loves collecting bacteria and he's sort of 186 00:11:47,840 --> 00:11:51,800 Speaker 1: a microbiologist too, and he says I'm interested in Crisper, 187 00:11:51,840 --> 00:11:54,240 Speaker 1: and Jennifer says being go, Okay, I got this project. 188 00:11:54,240 --> 00:11:56,080 Speaker 1: We're gonna work on it. So there's a lot of 189 00:11:56,120 --> 00:11:57,160 Speaker 1: serendipity there. 190 00:11:57,720 --> 00:12:00,200 Speaker 2: Isaacson had the chance to visit down his lab and 191 00:12:00,240 --> 00:12:02,440 Speaker 2: he told me that what he saw helped him understand 192 00:12:02,440 --> 00:12:05,840 Speaker 2: her process when it came to translating her initial curiosity 193 00:12:06,320 --> 00:12:07,040 Speaker 2: into research. 194 00:12:07,600 --> 00:12:10,600 Speaker 1: I never actually knew what a scientist did every day, 195 00:12:11,280 --> 00:12:13,320 Speaker 1: what scientists were, but what do they do like at 196 00:12:13,360 --> 00:12:16,960 Speaker 1: two in the afternoon, three in the air and especially 197 00:12:17,240 --> 00:12:19,920 Speaker 1: lab scientists, And so I got to go to the 198 00:12:20,120 --> 00:12:26,400 Speaker 1: lab at Berkeley where Jennifer Dowd works. One of the 199 00:12:26,440 --> 00:12:30,280 Speaker 1: things is there's long benches. It's called being a bench scientist, 200 00:12:30,360 --> 00:12:33,520 Speaker 1: where you're seating there next to each other, and you 201 00:12:33,600 --> 00:12:36,760 Speaker 1: have a sort of workspace that sometimes has a hood 202 00:12:36,880 --> 00:12:40,480 Speaker 1: that ventilates things, and you've got test tubes and pipe pats, 203 00:12:40,960 --> 00:12:43,800 Speaker 1: and you have a lab director like a Jennifer Dowd 204 00:12:44,440 --> 00:12:46,240 Speaker 1: who comes up with the ideas of what are we 205 00:12:46,240 --> 00:12:50,360 Speaker 1: going to test next, Let's try putting a little bit 206 00:12:50,400 --> 00:12:53,480 Speaker 1: of RNA into this mixture in this test tube and 207 00:12:53,520 --> 00:12:57,280 Speaker 1: see what happens. She's gotten office. She's looking at all 208 00:12:57,280 --> 00:13:00,560 Speaker 1: their results, but also she's putting on the white down 209 00:13:00,600 --> 00:13:03,360 Speaker 1: and she's putting on the latex gloves and going from 210 00:13:03,400 --> 00:13:07,440 Speaker 1: station to station, bench to bench, say what are you 211 00:13:07,480 --> 00:13:11,319 Speaker 1: doing with that experiment? And she had certain secrets she 212 00:13:11,440 --> 00:13:15,160 Speaker 1: sometimes used. She said, one of them is RNA and says, 213 00:13:15,200 --> 00:13:17,800 Speaker 1: when somebody's doing a big experiment and they can't figure 214 00:13:17,800 --> 00:13:20,839 Speaker 1: out what's happening, she'll just say, what's the RNA doing? 215 00:13:21,360 --> 00:13:24,079 Speaker 1: And she said that's always a clue that opens things up. 216 00:13:24,920 --> 00:13:29,480 Speaker 1: The other she said was enzymes. They spark an action. 217 00:13:29,960 --> 00:13:34,520 Speaker 1: They spark a neuron being or a muscle twitching, and 218 00:13:35,040 --> 00:13:39,880 Speaker 1: it is something that instigates things. It's like a match 219 00:13:39,960 --> 00:13:46,000 Speaker 1: or a spark that allows something to happen. And she says, 220 00:13:46,040 --> 00:13:49,600 Speaker 1: the two things you remember when you're doing science inside 221 00:13:49,640 --> 00:13:57,400 Speaker 1: of a cell or microbiology is enzymes RNA. Those are 222 00:13:57,440 --> 00:13:58,800 Speaker 1: the two keys. 223 00:13:59,160 --> 00:14:02,120 Speaker 2: Win in doubt in zionce and arna. You know, they 224 00:14:02,160 --> 00:14:04,480 Speaker 2: start on this journey. They're trying to figure out how 225 00:14:04,520 --> 00:14:06,720 Speaker 2: does crisper work, how does it do what we sort 226 00:14:06,760 --> 00:14:09,320 Speaker 2: of know that it does. And one of the first 227 00:14:09,320 --> 00:14:12,280 Speaker 2: things they do along the way is organize a conference 228 00:14:12,360 --> 00:14:14,240 Speaker 2: and bring in all these other people that study it. 229 00:14:14,800 --> 00:14:16,480 Speaker 2: And you could imagine it going the other way where 230 00:14:16,480 --> 00:14:18,920 Speaker 2: they say, we don't want to talk to anyone because 231 00:14:18,920 --> 00:14:22,280 Speaker 2: we are they're competitive. They might discover it before on. 232 00:14:22,360 --> 00:14:24,400 Speaker 1: One of the things that I wanted to convey in 233 00:14:24,440 --> 00:14:26,920 Speaker 1: the book is that science and discovery is a team 234 00:14:27,080 --> 00:14:33,040 Speaker 1: sport and conferences really matter. You bring people together, just 235 00:14:33,120 --> 00:14:35,760 Speaker 1: the hash things around, just to you know, go to 236 00:14:35,800 --> 00:14:40,400 Speaker 1: Alice Waters restaurant near Berkeley and sit upstairs and compare notes, 237 00:14:40,720 --> 00:14:45,480 Speaker 1: and it's dangerous because scientists are sometimes competitive. They want 238 00:14:45,520 --> 00:14:48,360 Speaker 1: to get their paper published first, they want to win 239 00:14:48,400 --> 00:14:51,280 Speaker 1: the prize, they want to get the patent. But if 240 00:14:51,280 --> 00:14:53,640 Speaker 1: you get them together at a conference, they can't help 241 00:14:54,040 --> 00:14:59,360 Speaker 1: but sharing information. And so people studying crisper decide, all right, 242 00:14:59,400 --> 00:15:02,000 Speaker 1: it's a brand field. What do you do. Let's start 243 00:15:02,000 --> 00:15:05,080 Speaker 1: a conference, and the first ones at Berkeley, and it's 244 00:15:05,120 --> 00:15:07,640 Speaker 1: done by one of the yogurt scientists. 245 00:15:07,480 --> 00:15:10,160 Speaker 2: The Denisko researchers who discovered that crisper was a kind 246 00:15:10,160 --> 00:15:13,440 Speaker 2: of immune system against viruses in their yogurt cultures. 247 00:15:13,760 --> 00:15:16,600 Speaker 1: The first speaker is Francisco Mohike. 248 00:15:16,560 --> 00:15:19,600 Speaker 2: The Spanish researcher who'd found crisper and salt loving bacteria 249 00:15:20,120 --> 00:15:20,840 Speaker 2: and named it. 250 00:15:21,000 --> 00:15:23,560 Speaker 1: It comes all the way over from Spain. And the 251 00:15:23,640 --> 00:15:26,920 Speaker 1: rule is you get to talk about work that you 252 00:15:27,040 --> 00:15:31,320 Speaker 1: haven't published, and you trust everybody not to try to 253 00:15:31,360 --> 00:15:34,720 Speaker 1: steal it and to beat you into the publication. And 254 00:15:34,840 --> 00:15:38,040 Speaker 1: back then things were competitive, but it was a small 255 00:15:38,160 --> 00:15:42,680 Speaker 1: enough community that they were good at sharing ideas. The 256 00:15:42,800 --> 00:15:47,480 Speaker 1: conferences on crisper in some ways reflected Jennifer's early experience, 257 00:15:47,840 --> 00:15:51,920 Speaker 1: which is getting invited to Cold Spring Harbor where James 258 00:15:51,920 --> 00:15:57,480 Speaker 1: Watson was convening conferences and doing them on genetics, but 259 00:15:57,680 --> 00:16:02,680 Speaker 1: doing it on RNA world. And she realized that gathering 260 00:16:02,720 --> 00:16:06,920 Speaker 1: in a place like Cold Spring Harbor with its Blackfoot bar, 261 00:16:07,080 --> 00:16:10,160 Speaker 1: where people would watch the Yankees at night but discuss uh, 262 00:16:10,520 --> 00:16:15,280 Speaker 1: you know, biochemistry. That's why she was interested in starting 263 00:16:15,480 --> 00:16:20,280 Speaker 1: this Crisper conference with some of the yogurt scientists, with 264 00:16:20,600 --> 00:16:22,400 Speaker 1: Francisco Mohico and others. 265 00:16:22,760 --> 00:16:26,320 Speaker 2: And these little personal interactions are how some of the 266 00:16:26,400 --> 00:16:28,120 Speaker 2: kind of light bulbs go off for people. 267 00:16:28,600 --> 00:16:32,680 Speaker 1: We talk about enzymes being a protein that sparks things, 268 00:16:32,960 --> 00:16:36,920 Speaker 1: that are a catalyst, and in some ways these conferences, 269 00:16:37,360 --> 00:16:44,040 Speaker 1: these are catalysts that spark ideas and coming out of 270 00:16:44,080 --> 00:16:47,080 Speaker 1: it people say, all right, I now see things in 271 00:16:47,120 --> 00:16:47,640 Speaker 1: a new way. 272 00:16:49,720 --> 00:16:56,160 Speaker 2: We'll be right back. The Chrisper Conference at Berkeley in 273 00:16:56,160 --> 00:16:59,360 Speaker 2: two thousand and eight, the first international gathering on the subject, 274 00:16:59,720 --> 00:17:03,600 Speaker 2: was success. Interest in RNA was growing and researchers were 275 00:17:03,600 --> 00:17:06,399 Speaker 2: finding new connections. But Isaacson tells me that it was 276 00:17:06,440 --> 00:17:08,840 Speaker 2: also around that time that doubtnas started to call into 277 00:17:08,920 --> 00:17:11,160 Speaker 2: question what she was doing and why. 278 00:17:11,840 --> 00:17:16,520 Speaker 1: All scientists, including Jennifer Dowdner, are human. They go through 279 00:17:16,560 --> 00:17:20,800 Speaker 1: a bit of a midlife crisis. She's depressed. She's working 280 00:17:20,840 --> 00:17:26,000 Speaker 1: on basic research at a lab at Berkeley, and even 281 00:17:26,080 --> 00:17:29,240 Speaker 1: though Crisper has come along and it seems pretty exciting, 282 00:17:29,920 --> 00:17:33,160 Speaker 1: she's like, what does it all mean? Am I really 283 00:17:33,200 --> 00:17:36,639 Speaker 1: doing anything useful? And she decides, well, maybe I should 284 00:17:36,680 --> 00:17:40,000 Speaker 1: just become a doctor and go to medical school or 285 00:17:40,119 --> 00:17:44,439 Speaker 1: other things. And she gets recruited to a company named Genentech, 286 00:17:44,520 --> 00:17:47,960 Speaker 1: a very famous company. Herbert Boyer and some of the 287 00:17:48,080 --> 00:17:53,440 Speaker 1: pioneers of recombinant DNA and genetic engineering in the seventies 288 00:17:53,920 --> 00:17:57,560 Speaker 1: had taken the intellectual property that they had created at 289 00:17:57,680 --> 00:18:02,440 Speaker 1: universities like Stanford and Berkeley and made companies that created 290 00:18:02,440 --> 00:18:08,840 Speaker 1: pharmaceuticals and other things based on recombinant DNA and genetic engineering. 291 00:18:09,600 --> 00:18:12,160 Speaker 1: And so she decides, I'm going to go to Genentech 292 00:18:12,920 --> 00:18:17,600 Speaker 1: and actually apply science. So it moves from the bench 293 00:18:18,160 --> 00:18:21,560 Speaker 1: to the bedside of the patient and that lasts about 294 00:18:21,600 --> 00:18:26,800 Speaker 1: two months. She realizes she's made a big mistake. That 295 00:18:26,920 --> 00:18:31,280 Speaker 1: she loves having graduates soon. She loves the research, the hunt, 296 00:18:31,400 --> 00:18:34,840 Speaker 1: the discovery. And she sits outside one night and it's 297 00:18:34,920 --> 00:18:38,440 Speaker 1: raining and she just keeps crying and crying, thinking she's 298 00:18:38,520 --> 00:18:43,680 Speaker 1: abandoned her post at Berkeley. She's now in Corporate America 299 00:18:44,359 --> 00:18:48,960 Speaker 1: and it's a great job, but it's not her. And 300 00:18:49,080 --> 00:18:52,320 Speaker 1: the head of the chemistry department at Berkeley, I think 301 00:18:52,480 --> 00:18:56,960 Speaker 1: Jennifer's husband, Jamie Cade, calls up and says, hey, Jennifer's 302 00:18:57,000 --> 00:18:59,120 Speaker 1: not doing well. And the head of the chemistry department 303 00:18:59,119 --> 00:19:01,560 Speaker 1: comes over and says, you want to come back to Berkeley. 304 00:19:02,400 --> 00:19:07,800 Speaker 2: She says yes, and that seems to be that almost 305 00:19:08,960 --> 00:19:12,840 Speaker 2: move that then brings her back into basic science, basic 306 00:19:12,880 --> 00:19:15,600 Speaker 2: research that itself seems to be some kind of catalysts 307 00:19:15,880 --> 00:19:19,879 Speaker 2: like things really take off from there, starting with the 308 00:19:19,960 --> 00:19:22,959 Speaker 2: Puerto Rico meeting and she meets sort of her intellectual 309 00:19:22,960 --> 00:19:25,560 Speaker 2: and creative partner for the coming years. 310 00:19:26,960 --> 00:19:30,040 Speaker 1: We talk about how meetings and conferences and cold Spring 311 00:19:30,080 --> 00:19:33,280 Speaker 1: holder labs serve as a catalyst like an enzyme to 312 00:19:33,480 --> 00:19:38,400 Speaker 1: spark collaboration, and that happens at a Puerto Rico conference 313 00:19:38,440 --> 00:19:45,000 Speaker 1: where there's a French scientist named Emmanuel Champantier who's also 314 00:19:45,080 --> 00:19:50,040 Speaker 1: studying RNA and actually is understanding the mechanisms of RNA, 315 00:19:50,440 --> 00:19:55,639 Speaker 1: how it works within enzyme to cut DNA, and she 316 00:19:55,760 --> 00:19:59,040 Speaker 1: realizes that Jennifer Dowd is also doing it, and they 317 00:19:59,200 --> 00:20:03,480 Speaker 1: walk along the cobblesome streets of Puerto Rico and they say, 318 00:20:03,960 --> 00:20:10,000 Speaker 1: let's collaborate. And that's how this beautiful partnership. And Jennifer 319 00:20:10,119 --> 00:20:14,360 Speaker 1: says to me and says to Emmanuel when we're talking, 320 00:20:15,000 --> 00:20:18,119 Speaker 1: I almost became a French teacher. And I imagine myself, 321 00:20:18,720 --> 00:20:21,840 Speaker 1: as you know, being an elegant French person, and you're 322 00:20:22,040 --> 00:20:24,800 Speaker 1: that person, but you're a scientist. This will be a 323 00:20:24,800 --> 00:20:25,760 Speaker 1: perfect combination. 324 00:20:28,080 --> 00:20:30,919 Speaker 2: But Sarpentier also seemed to have a little bit of 325 00:20:30,960 --> 00:20:33,760 Speaker 2: this outsider perspective that you talked about earlier, feeling a 326 00:20:33,760 --> 00:20:36,520 Speaker 2: little bit excluded, always moving from lab to lab. 327 00:20:37,119 --> 00:20:41,280 Speaker 1: She was very parapatetic still is, never stayed at a 328 00:20:41,400 --> 00:20:43,719 Speaker 1: lab more than a year or two. She was at 329 00:20:43,760 --> 00:20:46,760 Speaker 1: the Max Plunk Institute in Berlin, but before that she 330 00:20:46,800 --> 00:20:49,639 Speaker 1: had been in Sweden. Before that she had been in Vienna, 331 00:20:49,880 --> 00:20:52,920 Speaker 1: and then she moves every two years. And in her 332 00:20:52,960 --> 00:20:57,640 Speaker 1: life she never made commitments, never got married, never had kids, 333 00:20:58,440 --> 00:21:01,760 Speaker 1: and that was just something about her. In fact, there 334 00:21:01,800 --> 00:21:04,840 Speaker 1: was always a slight distance, a shell around it. 335 00:21:05,320 --> 00:21:08,640 Speaker 2: But when they started out, clearly they found this commonality 336 00:21:08,720 --> 00:21:12,160 Speaker 2: around trying to understand Crisper. Can you walk us through 337 00:21:12,640 --> 00:21:16,040 Speaker 2: what it was that they jointly discovered. 338 00:21:16,560 --> 00:21:20,000 Speaker 1: For Crisper to work, it's got to use RNA, which 339 00:21:20,040 --> 00:21:22,800 Speaker 1: is the thing that goes into your cell and tells 340 00:21:23,000 --> 00:21:26,520 Speaker 1: the cell how to build a protein, and it can 341 00:21:26,560 --> 00:21:30,439 Speaker 1: be coded to do certain things. And in Crisper, the 342 00:21:30,720 --> 00:21:36,399 Speaker 1: RNA the coating had mundshots of various viruses. But the 343 00:21:36,480 --> 00:21:39,600 Speaker 1: question is then, how does it do something with it? 344 00:21:40,040 --> 00:21:44,000 Speaker 1: And the answer, as Jennifer always said, if something does something, 345 00:21:44,640 --> 00:21:48,440 Speaker 1: your first answers, it must be an enzyme, a Crisper 346 00:21:48,680 --> 00:21:50,760 Speaker 1: associated enzyme. 347 00:21:51,680 --> 00:21:54,600 Speaker 2: In other words, Down and Sharp were focused on really 348 00:21:54,640 --> 00:21:58,959 Speaker 2: breaking down and understanding the Crisper mechanism, specifically how the 349 00:21:59,080 --> 00:22:02,159 Speaker 2: RNA and it's a companying enzyme were able to work together. 350 00:22:02,840 --> 00:22:05,199 Speaker 2: And Isaacson tells me they were far from being the 351 00:22:05,200 --> 00:22:05,760 Speaker 2: only ones. 352 00:22:09,680 --> 00:22:14,119 Speaker 1: Everybody is racing to figure out what it called Crisper 353 00:22:14,200 --> 00:22:20,160 Speaker 1: cast systems. And one of the discoveries that Jennifer and 354 00:22:20,280 --> 00:22:25,320 Speaker 1: Emmanuel made is that there were actually two types of RNA. 355 00:22:26,160 --> 00:22:29,760 Speaker 1: One that you could consider a guide RNA that had 356 00:22:29,800 --> 00:22:32,199 Speaker 1: the little code and it was a guide that we 357 00:22:32,280 --> 00:22:36,000 Speaker 1: told it where to go. But there was another snippet 358 00:22:36,160 --> 00:22:39,840 Speaker 1: of RNA called tracer RNA, which was almost like a 359 00:22:39,880 --> 00:22:44,200 Speaker 1: scaffolding it. Now, this seems very technical, but you got 360 00:22:44,200 --> 00:22:48,119 Speaker 1: to know exactly how it works if you're going to 361 00:22:48,200 --> 00:22:51,240 Speaker 1: want to engineer it and make it a tool. So 362 00:22:51,280 --> 00:22:55,359 Speaker 1: there's a race around the world of people studying Chrisper 363 00:22:55,400 --> 00:22:59,560 Speaker 1: cast this and Chrisper cast that. But the breakthrough that 364 00:22:59,680 --> 00:23:02,320 Speaker 1: seemed I'm small, but is a big one is to 365 00:23:02,400 --> 00:23:06,160 Speaker 1: know all the ingredients and have it work in a test, 366 00:23:06,200 --> 00:23:09,119 Speaker 1: to not just say I can make it work against 367 00:23:09,160 --> 00:23:12,560 Speaker 1: this bacteria and yogurt culture, but say I'm putting these 368 00:23:12,880 --> 00:23:17,119 Speaker 1: three ingredients in and these three things make it work. 369 00:23:19,560 --> 00:23:22,240 Speaker 2: By this point, DUBTNA had another researcher on the case, 370 00:23:22,640 --> 00:23:26,119 Speaker 2: an RNA obsessed graduate student from the Czech Republic named 371 00:23:26,160 --> 00:23:30,359 Speaker 2: Martin Yenick. Yunich was an expert in crystallography, the same 372 00:23:30,400 --> 00:23:33,600 Speaker 2: technique Rosalind Franklin had used that allowed Watson and Krik 373 00:23:33,680 --> 00:23:35,080 Speaker 2: to understand the role of DNA. 374 00:23:35,320 --> 00:23:38,280 Speaker 1: And it's Martin Yenick, one of the graduate students, the 375 00:23:38,359 --> 00:23:41,199 Speaker 1: lead graduate student in Jennifer's lab who's working on this, 376 00:23:41,760 --> 00:23:44,920 Speaker 1: who sketches out on a whiteboard, here's what the trace 377 00:23:45,119 --> 00:23:49,000 Speaker 1: RNA does. Here's what the guide RNA does. And here 378 00:23:49,400 --> 00:23:52,400 Speaker 1: if you look at it and you see their chemical structure, 379 00:23:53,160 --> 00:23:56,840 Speaker 1: they could actually fit together. And let's figure out what's 380 00:23:56,880 --> 00:24:00,680 Speaker 1: the essential part of each and make it so that 381 00:24:00,760 --> 00:24:06,199 Speaker 1: you had a fused a single guide RNA that was 382 00:24:06,359 --> 00:24:11,679 Speaker 1: as simple as possible. The reason this is important is 383 00:24:11,720 --> 00:24:15,880 Speaker 1: it's not just a discovery about nature. Now you've done 384 00:24:15,920 --> 00:24:20,680 Speaker 1: an invention. You've done something that can be patented. It 385 00:24:20,760 --> 00:24:26,520 Speaker 1: is something that you've created, and that allows it to 386 00:24:26,600 --> 00:24:32,200 Speaker 1: move past just being a basic science discovery into being 387 00:24:32,359 --> 00:24:36,520 Speaker 1: a real breakthrough. That's a technology breakthrough. 388 00:24:37,320 --> 00:24:41,119 Speaker 2: And something so small and so tactical, there's actually so 389 00:24:41,240 --> 00:24:44,240 Speaker 2: much drama in it. There's so much drama in the 390 00:24:44,400 --> 00:24:48,840 Speaker 2: tracer RNA has two functions. Yeah, and it's who's going 391 00:24:48,920 --> 00:24:51,400 Speaker 2: to figure out that it has two functions? And then 392 00:24:51,560 --> 00:24:54,480 Speaker 2: who's going to publish the fact that it has two functions. 393 00:24:55,119 --> 00:24:57,760 Speaker 1: This is where we get back to the conferences. They're 394 00:24:57,840 --> 00:25:02,080 Speaker 1: all collaborating and figuring out you do this crasper cast system. 395 00:25:02,119 --> 00:25:04,439 Speaker 1: I'll work on this one. Maybe I'll look at this 396 00:25:04,560 --> 00:25:08,280 Speaker 1: room and they're sharing things. But suddenly as they get closer, 397 00:25:08,680 --> 00:25:13,800 Speaker 1: everybody wants to win the prize. Of how does crisper work? 398 00:25:14,600 --> 00:25:17,520 Speaker 1: And so you have this conference in twenty twelve and 399 00:25:17,560 --> 00:25:20,880 Speaker 1: a lot of people are racing to do the ingredients. 400 00:25:21,520 --> 00:25:26,080 Speaker 1: Jennifer and Emmanuel and their two graduate students have figured 401 00:25:26,080 --> 00:25:30,600 Speaker 1: out every single element of how it works, and that 402 00:25:30,840 --> 00:25:35,600 Speaker 1: weekend they're finishing off their paper. They're rushing it off 403 00:25:35,640 --> 00:25:37,680 Speaker 1: to a journal because it doesn't count unless you get 404 00:25:37,680 --> 00:25:41,200 Speaker 1: it published, and so they're rushing into the journal Science. 405 00:25:41,640 --> 00:25:45,480 Speaker 1: They're showing all of the elements the crisper, the enzymes 406 00:25:45,520 --> 00:25:49,720 Speaker 1: of cast, the trace RNA, the guide RNA, and they're 407 00:25:49,760 --> 00:25:52,919 Speaker 1: even showing a tool they've been able to make to 408 00:25:53,040 --> 00:25:56,880 Speaker 1: combine the two forms of their RNA to be a 409 00:25:57,080 --> 00:26:00,919 Speaker 1: single guide RNA. So, in other words, it's an engineered 410 00:26:01,080 --> 00:26:04,240 Speaker 1: tool that makes this simpler. And they're ready with all 411 00:26:04,280 --> 00:26:08,119 Speaker 1: those elements, and everybody's at this conference. They're all trying 412 00:26:08,160 --> 00:26:12,840 Speaker 1: to present, and Jennifer and Emmanuel want priority. They want 413 00:26:12,840 --> 00:26:15,000 Speaker 1: to be the first to publish, they want to be 414 00:26:15,080 --> 00:26:18,800 Speaker 1: the first to get patents, and so the competition comes 415 00:26:18,800 --> 00:26:19,679 Speaker 1: in man. 416 00:26:19,960 --> 00:26:25,680 Speaker 2: And how does the competition drive the discovery without poisoning 417 00:26:25,720 --> 00:26:27,320 Speaker 2: it is one of the questions that I feel like 418 00:26:27,400 --> 00:26:30,800 Speaker 2: comes to the book that without creating rancor without creating 419 00:26:31,200 --> 00:26:33,240 Speaker 2: bad feelings or even bad behavior. 420 00:26:33,840 --> 00:26:37,240 Speaker 1: Well, it sometimes does create bad feelings and bad behavior. 421 00:26:37,800 --> 00:26:42,800 Speaker 1: And this is how science advances, which is a mix 422 00:26:43,320 --> 00:26:48,119 Speaker 1: of cooperation and competition. You gotta have competition, because why 423 00:26:48,600 --> 00:26:52,800 Speaker 1: are Emmanuel Sharpentay, Jennifer down and their two graduates can 424 00:26:52,840 --> 00:26:55,440 Speaker 1: stay up twenty four hours a day around the clock, 425 00:26:55,520 --> 00:26:58,600 Speaker 1: working in Europe and in Sweden and in Berkeley and 426 00:26:58,600 --> 00:27:01,440 Speaker 1: the United States so that they can win the race. 427 00:27:01,560 --> 00:27:05,399 Speaker 1: That competition, and sometimes you're wondering what are they competing for? 428 00:27:05,880 --> 00:27:10,560 Speaker 1: Where they're competing for the prizes that matters. They're competing 429 00:27:10,800 --> 00:27:15,280 Speaker 1: for being published. First, I think mainly they're competing for 430 00:27:15,359 --> 00:27:18,560 Speaker 1: the recognition, but also they're competing for a lot of money. 431 00:27:18,680 --> 00:27:22,240 Speaker 1: Because you get a patent, you know you've hit the jackpot. 432 00:27:22,800 --> 00:27:25,359 Speaker 1: If you want to win the Nobel Prize, you're no 433 00:27:25,400 --> 00:27:28,040 Speaker 1: longer going to be as cooperative of other people in 434 00:27:28,080 --> 00:27:28,840 Speaker 1: the same field. 435 00:27:29,080 --> 00:27:31,400 Speaker 2: It was at that Chrisper conference in twenty twenty one 436 00:27:31,840 --> 00:27:35,359 Speaker 2: that Jennifer Downa and Emmanuel Sharpga finally submitted their paper 437 00:27:35,440 --> 00:27:38,360 Speaker 2: on Crisper Cast nine. The first part of the name 438 00:27:38,400 --> 00:27:41,960 Speaker 2: referring to the repeated clusters and cast nine, referring to 439 00:27:42,040 --> 00:27:46,400 Speaker 2: the specific enzymes that essentially created these genetic scissors. Isaacson 440 00:27:46,440 --> 00:27:48,119 Speaker 2: says this was a pivotal moment. 441 00:27:49,119 --> 00:27:51,879 Speaker 1: At the end of Watson and Crick's paper on the 442 00:27:51,880 --> 00:27:55,560 Speaker 1: structure of DNA, they do a breathtaking sentence it goes 443 00:27:55,600 --> 00:27:58,720 Speaker 1: down in history, which is sort of, as I paraphrase 444 00:27:58,800 --> 00:28:02,800 Speaker 1: it, it's not escaped our notice that what we have discovered 445 00:28:02,840 --> 00:28:07,280 Speaker 1: by the structure can be a system for passing along 446 00:28:07,359 --> 00:28:11,280 Speaker 1: genetic information. In other words, a sentence that says, hey, 447 00:28:11,520 --> 00:28:14,800 Speaker 1: this isn't just about RNA being fused. This could have 448 00:28:14,840 --> 00:28:17,320 Speaker 1: a big deal. So at the end of the paper 449 00:28:17,440 --> 00:28:21,399 Speaker 1: that Bonte and Dowd know Wright in twenty twelve, they 450 00:28:21,440 --> 00:28:26,199 Speaker 1: basically mimic that sentence and it says, basically, it's not 451 00:28:26,440 --> 00:28:29,520 Speaker 1: escaped our notice that this could become a tool to 452 00:28:29,760 --> 00:28:31,040 Speaker 1: edit our DNA. 453 00:28:31,440 --> 00:28:35,159 Speaker 2: It's not escaped our notice it. So it's simultaneously a 454 00:28:35,160 --> 00:28:38,880 Speaker 2: little bit understated but also a little bit grandiose. 455 00:28:39,680 --> 00:28:44,840 Speaker 1: Yes, because the paper itself was just how does crisper 456 00:28:45,960 --> 00:28:51,200 Speaker 1: form the right ingredients to cut the genetic material of 457 00:28:51,240 --> 00:28:54,720 Speaker 1: a virus? Well, that's really important to know, especially when 458 00:28:54,720 --> 00:28:58,880 Speaker 1: we're finding viruses, But one order of magnitude more important 459 00:28:59,280 --> 00:29:01,840 Speaker 1: is say, can we that into a tool where we 460 00:29:02,000 --> 00:29:05,320 Speaker 1: can program it to edit our own DNA. 461 00:29:06,440 --> 00:29:09,200 Speaker 2: Doubton and Sharpenter had accomplished what just a decade ago 462 00:29:09,240 --> 00:29:13,640 Speaker 2: seemed impossible. The clustered sequences that Francisco Mohica had found 463 00:29:13,680 --> 00:29:16,760 Speaker 2: in the salty ponds of his hometown were now fully 464 00:29:16,840 --> 00:29:20,240 Speaker 2: understood as a mechanism for gene editing. But they still 465 00:29:20,240 --> 00:29:22,320 Speaker 2: needed to make the leap to turn the Crisper cast 466 00:29:22,400 --> 00:29:26,640 Speaker 2: nine system into an active gene editing tool. And Isaacson 467 00:29:26,640 --> 00:29:30,200 Speaker 2: tells me Doubtna and Sharpenter faced one particularly fierce competitor. 468 00:29:33,000 --> 00:29:37,240 Speaker 1: The person at MI T Harper who is racing against 469 00:29:37,280 --> 00:29:42,240 Speaker 1: them is Fung Jean. Fung Jong originally sends an email 470 00:29:42,320 --> 00:29:44,600 Speaker 1: to Jennifer Downa say I've read your piece. I want 471 00:29:44,600 --> 00:29:47,360 Speaker 1: to figure out how it's gonna work. But they soon 472 00:29:47,840 --> 00:29:52,719 Speaker 1: realized the stakes are too high, and they all become 473 00:29:53,000 --> 00:29:56,600 Speaker 1: more secretive and more competitive. 474 00:29:57,880 --> 00:30:02,840 Speaker 2: That next time on douta on DOWDNA. The Story of 475 00:30:02,920 --> 00:30:06,800 Speaker 2: Jennifer DOWDNA is a production of Kaleidoscope and iHeart. This 476 00:30:06,880 --> 00:30:09,640 Speaker 2: show is based on the writing and reporting of Walter Isaacson. 477 00:30:10,160 --> 00:30:13,120 Speaker 2: It's hosted by me Evan Ratliffe and produced by Adrianna 478 00:30:13,160 --> 00:30:16,400 Speaker 2: Tapeia with assistance from Alex Jan Unveld. It was mixed 479 00:30:16,400 --> 00:30:19,480 Speaker 2: by Kyle Murdoch and our studio engineer was Thomas Walsh. 480 00:30:19,680 --> 00:30:23,440 Speaker 2: Our executive producers are Kate Osbourne and Mangashatigudor from Kaleidoscope 481 00:30:23,520 --> 00:30:27,320 Speaker 2: and Katrina Norvel from iHeart Podcasts. If you enjoy hearing 482 00:30:27,360 --> 00:30:30,360 Speaker 2: stories about visionaries and science and technology, check out our 483 00:30:30,440 --> 00:30:34,080 Speaker 2: other series based on biographies by Walter Isaacson. On Musk 484 00:30:34,320 --> 00:30:36,600 Speaker 2: for an intimate dive into all the facets of Elon 485 00:30:36,720 --> 00:30:40,400 Speaker 2: Musk and on Benjamin Franklin to understand how his scientific 486 00:30:40,440 --> 00:30:43,880 Speaker 2: curiosity shape society as we know it. Thanks for listening.