1 00:00:00,520 --> 00:00:02,880 Speaker 1: I don't judge, but the Internet does. The Internet says 2 00:00:02,920 --> 00:00:08,600 Speaker 1: the worst people are somebody that's doing CrossFit or someone 3 00:00:08,600 --> 00:00:11,240 Speaker 1: who's mean. I was gonna say, let me get it. Vegans. 4 00:00:11,400 --> 00:00:17,599 Speaker 2: Yeah, Honestly, I feel like nobody loves talking about themselves 5 00:00:17,640 --> 00:00:21,280 Speaker 2: more than vegans. I don't have nothing against a vegan. 6 00:00:21,600 --> 00:00:23,560 Speaker 2: Whatever you want to eat, eat that, that's fine with me. 7 00:00:23,920 --> 00:00:25,720 Speaker 2: But they love talking about being vegan. 8 00:00:25,800 --> 00:00:27,800 Speaker 1: A lot of posts out there about being vegan. Yeah. 9 00:00:27,840 --> 00:00:31,000 Speaker 2: There are some aggressive vegans though, that are like, really 10 00:00:31,040 --> 00:00:34,159 Speaker 2: mean if you aren't vegan, And those are the ones 11 00:00:34,200 --> 00:00:36,199 Speaker 2: that I'm just like, Okay, well, I'm gonna just keep 12 00:00:36,200 --> 00:00:38,960 Speaker 2: my distance because I don't want no smoke. 13 00:00:39,400 --> 00:00:42,320 Speaker 1: Well, I gotta tell you I had an impossible burger recently, 14 00:00:42,600 --> 00:00:46,320 Speaker 1: and you might have to keep your distance from me. Okay, 15 00:00:46,440 --> 00:00:48,800 Speaker 1: you're gonna give me some plant blazed smoke. Yeah, you're 16 00:00:48,800 --> 00:00:52,839 Speaker 1: gonna get some. I'm gonna get these wood chips. Okay. Okay. 17 00:00:54,160 --> 00:00:57,200 Speaker 1: I'm t T and I'm Zachiah and from Spotify Studios. 18 00:00:57,240 --> 00:01:17,319 Speaker 1: This is Dope Laps. I am all on the plant 19 00:01:17,360 --> 00:01:19,240 Speaker 1: based meat alternative kick. 20 00:01:19,520 --> 00:01:22,160 Speaker 2: Okay, Yeah, we went and got that impossible whopper and 21 00:01:22,120 --> 00:01:25,880 Speaker 2: then all of a sudden, the Kia is soy everything, 22 00:01:26,480 --> 00:01:27,119 Speaker 2: soy life. 23 00:01:27,440 --> 00:01:30,360 Speaker 1: That's not true, Like what do you mean? 24 00:01:30,400 --> 00:01:30,520 Speaker 3: Oh? 25 00:01:30,560 --> 00:01:32,760 Speaker 1: This is impossible meat? And I'm like, m well, what 26 00:01:32,800 --> 00:01:37,840 Speaker 1: are we gonna do for the function? Because everybody no? Okay? Dogs? 27 00:01:38,040 --> 00:01:41,080 Speaker 1: We had. That is so funny because I posted the 28 00:01:41,080 --> 00:01:42,440 Speaker 1: other day that I was at the grocery store and 29 00:01:42,480 --> 00:01:45,240 Speaker 1: I saw some of the Beyond like the Beyond crumbles 30 00:01:45,280 --> 00:01:48,880 Speaker 1: that you can get, and I posted it on Instagram 31 00:01:49,160 --> 00:01:51,600 Speaker 1: and my friend Kate wrote me and said, is that 32 00:01:51,640 --> 00:01:54,240 Speaker 1: what you're making the turkey out of? That? Is that 33 00:01:54,280 --> 00:01:54,880 Speaker 1: what you're doing? 34 00:01:55,600 --> 00:01:58,000 Speaker 2: Because we have friends giving at your house, right m h? 35 00:01:58,680 --> 00:02:00,560 Speaker 2: And so yes, if I would have that, I would 36 00:02:00,600 --> 00:02:03,800 Speaker 2: have been alarmed to but we didn't have that, y'all. 37 00:02:03,840 --> 00:02:05,480 Speaker 2: We had a lot of really good food. This is 38 00:02:05,520 --> 00:02:07,040 Speaker 2: almost becoming a food podcast. 39 00:02:08,440 --> 00:02:10,600 Speaker 1: I know we got to change the category. But you 40 00:02:10,639 --> 00:02:13,040 Speaker 1: know I got even my dad. I got him eating 41 00:02:13,120 --> 00:02:17,919 Speaker 1: plant based. Let me tell you that is a meat eater. 42 00:02:18,760 --> 00:02:22,280 Speaker 1: He could eat six chicken thighs in one sitting. It's true. 43 00:02:22,480 --> 00:02:26,760 Speaker 2: He's very tall and very strong and he's powered by 44 00:02:26,840 --> 00:02:28,799 Speaker 2: chicken thighs. 45 00:02:29,840 --> 00:02:32,480 Speaker 1: He's gonna kill you. And so when you think about 46 00:02:32,520 --> 00:02:34,480 Speaker 1: taking someone like that, and I don't know what his 47 00:02:34,560 --> 00:02:40,160 Speaker 1: carbon footprint is, okay, Paul Bunyan carbon footprint. But when 48 00:02:40,160 --> 00:02:41,800 Speaker 1: you take someone like that and you say, all right, 49 00:02:41,880 --> 00:02:44,280 Speaker 1: I got this person to eat plant based meat alternative something, 50 00:02:44,320 --> 00:02:48,160 Speaker 1: you're doing something different because he's not gonna eat a 51 00:02:48,200 --> 00:02:51,560 Speaker 1: Boca Burger. No shade to Boca Burgers. I like those two, 52 00:02:51,760 --> 00:02:54,440 Speaker 1: but he's not going for it. Okay. I got him 53 00:02:54,440 --> 00:02:57,359 Speaker 1: that burrito bowl at Cadoba. He said, hey, you tell 54 00:02:57,400 --> 00:03:00,160 Speaker 1: me this right here, this is all vegetables. I'm in. 55 00:03:01,120 --> 00:03:05,919 Speaker 1: I can do it every day. 56 00:03:06,720 --> 00:03:09,840 Speaker 2: Even Oprah, she did a thirty day vegan challenge right right. 57 00:03:09,960 --> 00:03:11,880 Speaker 1: See, we're onto something. You have to follow on the 58 00:03:11,880 --> 00:03:17,720 Speaker 1: footsteps of the greats. Yes, Oprah Beyonce, impossible, man, you'll 59 00:03:17,720 --> 00:03:19,839 Speaker 1: get a burger. You don't get a burger. You'll get 60 00:03:19,840 --> 00:03:24,280 Speaker 1: a burger. That was t t I thought that was 61 00:03:24,320 --> 00:03:26,920 Speaker 1: an alright, Oprah impression. I thought it was good. But 62 00:03:27,880 --> 00:03:29,440 Speaker 1: affect this Opra impressions. 63 00:03:29,440 --> 00:03:31,920 Speaker 2: If I meet Oprah, Hey, Oprah, love to meet you, 64 00:03:32,000 --> 00:03:33,120 Speaker 2: and I better help you with that. 65 00:03:33,360 --> 00:03:39,200 Speaker 1: Yeah, I need my friend there. Okay, So I think 66 00:03:39,240 --> 00:03:43,040 Speaker 1: this episode we need to put meat alternatives under the microscope. 67 00:03:43,920 --> 00:03:46,400 Speaker 1: So let's get into the recitation. I want to know 68 00:03:47,080 --> 00:03:51,680 Speaker 1: has anyone out there tried some version of this from 69 00:03:51,880 --> 00:03:54,560 Speaker 1: I mean, it's in our local fast food establishment, So 70 00:03:54,600 --> 00:03:57,320 Speaker 1: it's that Cadoba that I know about World Burger King, 71 00:03:57,520 --> 00:04:00,160 Speaker 1: Burger King. I saw that KFC was trying to come 72 00:04:00,240 --> 00:04:03,520 Speaker 1: up with a plant based chicken. That seems tough, and 73 00:04:03,600 --> 00:04:05,560 Speaker 1: I feel like this is coming out of nowhere. Yeah. 74 00:04:05,600 --> 00:04:09,120 Speaker 1: It went from one hundred percent angus beef yeah, to 75 00:04:09,800 --> 00:04:14,880 Speaker 1: pea protein yeah, very quickly. Yeah. Me, I just want 76 00:04:14,920 --> 00:04:18,640 Speaker 1: to know, like, how is this stuff made? What? 77 00:04:18,839 --> 00:04:22,840 Speaker 2: I don't really understand how you can make pea protein 78 00:04:23,400 --> 00:04:24,600 Speaker 2: sizzle on the grill? 79 00:04:24,880 --> 00:04:27,599 Speaker 1: Yeah? How is it made? Is it better for you? 80 00:04:27,640 --> 00:04:29,480 Speaker 1: Because I know people think like, oh, if I get this, 81 00:04:29,480 --> 00:04:32,279 Speaker 1: this is a healthier option, is it? Is it? And 82 00:04:32,360 --> 00:04:35,640 Speaker 1: then not only is it better, but like what kind 83 00:04:35,640 --> 00:04:38,600 Speaker 1: of technology is this? Are they three D printing these burgers? 84 00:04:38,640 --> 00:04:40,719 Speaker 1: Like I want to know the how because I know 85 00:04:40,760 --> 00:04:43,560 Speaker 1: it's not like we harvested peas. You know, when you 86 00:04:43,560 --> 00:04:45,279 Speaker 1: get a veggie burger, you can see like, oh, there's 87 00:04:45,279 --> 00:04:46,960 Speaker 1: a little bit of it, there's a little bit of carrot, 88 00:04:47,040 --> 00:04:48,680 Speaker 1: here's a little bit of pee. Yeah, there's a little 89 00:04:48,680 --> 00:04:51,640 Speaker 1: onion and mushroom over here. It's not like that, not 90 00:04:51,720 --> 00:04:53,920 Speaker 1: at all. It looks like me this thing and even 91 00:04:53,960 --> 00:04:57,480 Speaker 1: some it has like stuff that looks like blood pink 92 00:04:57,520 --> 00:05:00,159 Speaker 1: to dark brown. What's happening? I don't get it, and 93 00:05:00,200 --> 00:05:01,960 Speaker 1: so we want to get to the bottom of it. 94 00:05:02,040 --> 00:05:04,360 Speaker 1: Let's take a big bite and jump into the dissection. 95 00:05:08,040 --> 00:05:11,120 Speaker 1: All right, it's time for the dissection. We invited doctor 96 00:05:11,200 --> 00:05:14,279 Speaker 1: Christina Agapacas to help us unpack all of our questions 97 00:05:14,320 --> 00:05:17,320 Speaker 1: behind plant based meat. My name is Christina Agapakis. 98 00:05:17,400 --> 00:05:20,080 Speaker 3: I am a synthetic biologist and the creative director at 99 00:05:20,080 --> 00:05:21,000 Speaker 3: Ginko Bioworks. 100 00:05:21,120 --> 00:05:24,080 Speaker 2: Ginkgo Bioworks is a biotech company that was founded in 101 00:05:24,120 --> 00:05:26,440 Speaker 2: two thousand and nine by a bunch of scientists from MIT. 102 00:05:27,160 --> 00:05:29,839 Speaker 2: Earlier this year, the company launched a new venture called 103 00:05:29,880 --> 00:05:33,200 Speaker 2: Motif to find the next big thing in laboratory based food, 104 00:05:33,520 --> 00:05:36,960 Speaker 2: and they did this by developing the key ingredients using 105 00:05:37,080 --> 00:05:41,320 Speaker 2: biotechnology and fermentation. But before we dive into the science 106 00:05:41,360 --> 00:05:44,279 Speaker 2: behind all these plant based meat options, we wanted to 107 00:05:44,400 --> 00:05:46,960 Speaker 2: zoom out and get a little bit more familiar with 108 00:05:47,000 --> 00:05:49,800 Speaker 2: the history and the industry of plant based meat. Plant 109 00:05:49,800 --> 00:05:53,000 Speaker 2: based meat is nothing new, but we are in sort 110 00:05:53,000 --> 00:05:56,560 Speaker 2: of a renaissance period where it's becoming way more popular. 111 00:05:56,800 --> 00:06:00,719 Speaker 2: I see these plant based paddies everywhere, and chances are 112 00:06:00,760 --> 00:06:03,240 Speaker 2: you can find them in your local supermarket in the 113 00:06:03,279 --> 00:06:06,240 Speaker 2: meat aisle. Back in April, Burger King announced their new 114 00:06:06,279 --> 00:06:09,760 Speaker 2: Impossible Whopper, and McDonald's is actually working on their own 115 00:06:09,839 --> 00:06:11,880 Speaker 2: version of a meatless burger alternative. 116 00:06:12,120 --> 00:06:15,440 Speaker 1: The plant based meat industry has grown so much over 117 00:06:15,480 --> 00:06:18,440 Speaker 1: the past I don't know, five to ten years. Yeah, 118 00:06:18,480 --> 00:06:21,279 Speaker 1: you know, I remember seeing like morning Star burgers and 119 00:06:21,279 --> 00:06:23,840 Speaker 1: stuff like that in the frozen isle, and every now 120 00:06:23,839 --> 00:06:25,840 Speaker 1: and then I get a black bean burger. I even 121 00:06:25,880 --> 00:06:27,640 Speaker 1: try to make my own black bean burger. No good. 122 00:06:28,040 --> 00:06:32,359 Speaker 1: But now that this is at Burger King and all 123 00:06:32,440 --> 00:06:34,880 Speaker 1: these other places and in the grocery stores like, have 124 00:06:34,960 --> 00:06:37,159 Speaker 1: we reached a peak? Is the growth going to slow 125 00:06:37,200 --> 00:06:39,480 Speaker 1: down now or are we on the trajectory to just 126 00:06:39,839 --> 00:06:40,960 Speaker 1: keep going well. 127 00:06:41,000 --> 00:06:44,799 Speaker 2: Analysts expect that the plant based protein or meat alternative 128 00:06:44,880 --> 00:06:48,719 Speaker 2: market is going to grow by twenty eight percent a year, 129 00:06:48,960 --> 00:06:53,599 Speaker 2: from four point six billion dollars in twenty eighteen to 130 00:06:53,760 --> 00:06:57,280 Speaker 2: eighty five billion dollars in twenty thirty, so twenty. 131 00:06:57,080 --> 00:07:04,240 Speaker 1: Eight percent of growth each year. Between thirty. Yeah, what 132 00:07:04,680 --> 00:07:09,400 Speaker 1: I need to buy some stock. Yeah, the next episode 133 00:07:09,440 --> 00:07:11,080 Speaker 1: will be about the stock market. 134 00:07:13,080 --> 00:07:16,520 Speaker 3: It has been really incredible to see the change in 135 00:07:16,000 --> 00:07:19,320 Speaker 3: the way that people kind of talk about vegetarian options 136 00:07:19,320 --> 00:07:22,520 Speaker 3: and vegan options and how much demand there's been. 137 00:07:22,960 --> 00:07:25,440 Speaker 1: It's been really really dramatic, and there are a bunch 138 00:07:25,520 --> 00:07:28,800 Speaker 1: of different reasons people are gravitating more towards plant based meat. 139 00:07:28,960 --> 00:07:30,920 Speaker 2: Right a few years ago, I feel like people didn't 140 00:07:30,920 --> 00:07:34,520 Speaker 2: eat meat for two main reasons, animal rights or for 141 00:07:34,640 --> 00:07:37,440 Speaker 2: their personal health, like they want to get their cholesterol 142 00:07:37,560 --> 00:07:41,800 Speaker 2: lower or whatever. But doctor Agapakis says there's another reason 143 00:07:41,840 --> 00:07:43,240 Speaker 2: why it's become more popular. 144 00:07:43,440 --> 00:07:47,080 Speaker 3: Climate ethics and environmental impact that you have is a 145 00:07:47,200 --> 00:07:51,160 Speaker 3: major factor. I think that in many people's decisions, and 146 00:07:51,480 --> 00:07:54,160 Speaker 3: that's been something that I think has changed pretty dramatically 147 00:07:54,160 --> 00:07:56,280 Speaker 3: in the past few years, where where people look at 148 00:07:56,320 --> 00:07:58,440 Speaker 3: the sort of impacts of their everyday things that they 149 00:07:58,520 --> 00:08:01,239 Speaker 3: do and they see meat to the top of the list, 150 00:08:01,800 --> 00:08:04,840 Speaker 3: and they see better options for them for things that 151 00:08:04,920 --> 00:08:08,280 Speaker 3: still taste good that they can have access to that 152 00:08:08,320 --> 00:08:11,520 Speaker 3: can can start chipping away at that impact that they 153 00:08:11,520 --> 00:08:12,520 Speaker 3: have as an individual. 154 00:08:12,840 --> 00:08:17,040 Speaker 2: So the demand is growing dramatically for different reasons. Let's 155 00:08:17,040 --> 00:08:21,280 Speaker 2: talk about supply. What are these meat substitutes actually made of. 156 00:08:21,400 --> 00:08:25,120 Speaker 3: It's basically like protein that comes from plants, right, and 157 00:08:25,160 --> 00:08:27,080 Speaker 3: so there's lots of ways that that can happen. 158 00:08:27,200 --> 00:08:29,880 Speaker 1: That's right. There are many different kinds of plant proteins though. 159 00:08:30,080 --> 00:08:33,200 Speaker 1: For example, Gardenburger, which was invented in the early nineteen eighties, 160 00:08:33,280 --> 00:08:36,120 Speaker 1: uses soy protein and it's burger patties, and those patties 161 00:08:36,120 --> 00:08:38,600 Speaker 1: came with like those grill marks, so you felt like 162 00:08:38,960 --> 00:08:43,720 Speaker 1: it was really grill what is it? But also peas, wheat, nuts, 163 00:08:43,760 --> 00:08:46,600 Speaker 1: and rice are popular crops that are used as meat substitutes, 164 00:08:47,040 --> 00:08:49,640 Speaker 1: but a lot of those earlier meat substitutes didn't quite 165 00:08:49,720 --> 00:08:50,240 Speaker 1: hit the mark. 166 00:08:50,360 --> 00:08:53,720 Speaker 3: You can do a lot with the texture from the 167 00:08:53,760 --> 00:08:56,880 Speaker 3: proteins that you can get from plants, but you can't 168 00:08:56,880 --> 00:09:01,080 Speaker 3: really do everything that meat or dare product does. You 169 00:09:01,120 --> 00:09:04,560 Speaker 3: can't get the full sort of sensory experience. You can't 170 00:09:04,600 --> 00:09:08,199 Speaker 3: get the kind of qualities, whether that's like how it foams, 171 00:09:08,280 --> 00:09:12,040 Speaker 3: how it feels in your mouth, how it cooks, all 172 00:09:12,080 --> 00:09:14,840 Speaker 3: of those things might that have different kinds of ingredients 173 00:09:14,840 --> 00:09:16,480 Speaker 3: that come from the meat that are important. 174 00:09:16,520 --> 00:09:19,320 Speaker 2: So while a lot of earlier meat substitutes tasted just 175 00:09:19,400 --> 00:09:23,080 Speaker 2: find there was no way you could ever confuse them 176 00:09:23,240 --> 00:09:28,040 Speaker 2: for the real deal. Yeah, especially with those fake sharpie 177 00:09:28,040 --> 00:09:28,720 Speaker 2: grow marks. 178 00:09:30,800 --> 00:09:32,720 Speaker 1: And so that really brings us to why plant based 179 00:09:32,760 --> 00:09:35,760 Speaker 1: meat alternatives now are becoming so much more popular. So 180 00:09:35,840 --> 00:09:37,920 Speaker 1: let's use two of the most popular plant based meat 181 00:09:37,920 --> 00:09:41,640 Speaker 1: companies as an example, Impossible Burger and Beyond Meat. Both 182 00:09:41,640 --> 00:09:44,000 Speaker 1: companies still use plants and grains for the bulk of 183 00:09:44,040 --> 00:09:48,160 Speaker 1: their protein. Impossible uses soy protein concentrate and Beyond Meat 184 00:09:48,240 --> 00:09:49,280 Speaker 1: uses pea protein. 185 00:09:49,720 --> 00:09:53,000 Speaker 2: But what makes these so different from Gardenberger is the 186 00:09:53,120 --> 00:09:58,160 Speaker 2: specialty ingredients their scientists have developed. These ingredients are used 187 00:09:58,200 --> 00:10:03,120 Speaker 2: in much smaller quantities, but are what makes the product look, taste. 188 00:10:02,920 --> 00:10:04,320 Speaker 1: And smell like real meat. 189 00:10:04,840 --> 00:10:08,480 Speaker 2: In other words, these ain't the old school veggie burger patties. 190 00:10:08,600 --> 00:10:11,280 Speaker 1: What's an example of one of these specialty ingredients. 191 00:10:10,880 --> 00:10:13,360 Speaker 3: For Impossible foods? That was the heme. 192 00:10:13,559 --> 00:10:16,320 Speaker 1: Heme has been referred to as the magic ingredient in 193 00:10:16,360 --> 00:10:17,400 Speaker 1: the Impossible Burger. 194 00:10:17,559 --> 00:10:20,440 Speaker 2: So heme is the stuff that makes Impossible Burger cook 195 00:10:20,520 --> 00:10:23,600 Speaker 2: from pink to brown, right, just like a real burger. 196 00:10:24,040 --> 00:10:28,640 Speaker 1: So what is heme for real? For real? Heme is 197 00:10:29,040 --> 00:10:31,920 Speaker 1: most commonly recognized as one of the components and hemoglobin, right, 198 00:10:31,960 --> 00:10:34,679 Speaker 1: and that's what makes our blood red, and its primary 199 00:10:34,679 --> 00:10:37,560 Speaker 1: function is to just transport oxygen. So if scientists that 200 00:10:37,600 --> 00:10:42,520 Speaker 1: Impossible use heme to give their beef patties that meaty flavor. 201 00:10:42,240 --> 00:10:44,439 Speaker 3: And so being able to find a source of that 202 00:10:44,520 --> 00:10:48,120 Speaker 3: protein that's vegan was really important to the team at 203 00:10:48,160 --> 00:10:51,240 Speaker 3: Impossible Foods and is really a key ingredient for them. 204 00:10:51,400 --> 00:10:54,280 Speaker 2: So how did the scientists that Impossible use heme without 205 00:10:54,400 --> 00:10:59,719 Speaker 2: using animals as the source for hem That seems really 206 00:11:00,000 --> 00:11:01,280 Speaker 2: tricky and confusing for me. 207 00:11:01,480 --> 00:11:04,160 Speaker 1: When we tend to think about heme, people always go 208 00:11:04,240 --> 00:11:06,880 Speaker 1: to the example of hemoglobin and hemoglobin being in blood. 209 00:11:07,240 --> 00:11:10,040 Speaker 1: But the thing to remember, hem is also present in 210 00:11:10,120 --> 00:11:12,360 Speaker 1: plants and is present in one of our favorites. 211 00:11:12,600 --> 00:11:14,560 Speaker 2: Soy, we're going to take a quick break, but when 212 00:11:14,600 --> 00:11:16,480 Speaker 2: we get back, we're going to dive into the actual 213 00:11:16,520 --> 00:11:19,719 Speaker 2: process of finding and extracting these proteins that are then 214 00:11:19,880 --> 00:11:23,480 Speaker 2: used to make the magic ingredients in our plant based food. 215 00:11:23,600 --> 00:11:24,240 Speaker 1: Stay tuned. 216 00:11:40,840 --> 00:11:43,080 Speaker 2: We're back and we're ready to dive into the actual 217 00:11:43,160 --> 00:11:47,600 Speaker 2: process of engineering these plant based proteins that ultimately become 218 00:11:47,679 --> 00:11:52,160 Speaker 2: your impossible whopper. As doctor Agapakis says, it's an incredibly 219 00:11:52,760 --> 00:11:59,480 Speaker 2: multidisciplinary process that involves aspects of biology, chemistry, and genetics. 220 00:11:59,600 --> 00:12:04,800 Speaker 1: My friend, the kia is lighting up. It is a 221 00:12:04,840 --> 00:12:07,840 Speaker 1: wonderful symphony. Right. In order to get a plant based 222 00:12:07,840 --> 00:12:11,120 Speaker 1: burger patty just right, scientists have to go through a 223 00:12:11,160 --> 00:12:13,320 Speaker 1: lot of trial and error looking for the proteins they 224 00:12:13,320 --> 00:12:15,760 Speaker 1: have the best qualities. And before the break, we found 225 00:12:15,800 --> 00:12:18,079 Speaker 1: out that hem was the key ingredient in making impossible 226 00:12:18,120 --> 00:12:19,679 Speaker 1: burgers red and juicy. 227 00:12:20,160 --> 00:12:24,080 Speaker 2: Just like real meed. You can find heme in soy, 228 00:12:24,080 --> 00:12:28,080 Speaker 2: but only in small amounts, and so extracting it from 229 00:12:28,080 --> 00:12:31,959 Speaker 2: the soy would be really really inefficient. 230 00:12:32,320 --> 00:12:36,360 Speaker 1: So the scientist Impossible new that they couldn't just pull 231 00:12:36,400 --> 00:12:38,520 Speaker 1: the heme straight from the soy. That would kind of 232 00:12:38,559 --> 00:12:40,439 Speaker 1: cause a lot of problems. So they figured out a 233 00:12:40,480 --> 00:12:41,600 Speaker 1: way to make their own hem. 234 00:12:41,720 --> 00:12:44,520 Speaker 3: The way that they do that is actually sourcing the 235 00:12:44,720 --> 00:12:50,199 Speaker 3: gene for plant hemoglobin. So like the protein that binds 236 00:12:50,240 --> 00:12:53,920 Speaker 3: iron and blood is also used to buy iron in plants, 237 00:12:54,480 --> 00:12:57,400 Speaker 3: and so they took that same gene and then transferred 238 00:12:57,400 --> 00:13:00,360 Speaker 3: into yeast, and now yeast can start making that rotein 239 00:13:00,440 --> 00:13:02,360 Speaker 3: at high quantities and then that can be used as 240 00:13:02,360 --> 00:13:03,439 Speaker 3: an ingredient in the food. 241 00:13:03,679 --> 00:13:06,679 Speaker 2: Okay, I need to break this down a little bit. First, 242 00:13:06,880 --> 00:13:11,199 Speaker 2: they find the gene for the plant hemoglobin, where do 243 00:13:11,240 --> 00:13:14,240 Speaker 2: they find that? So in the sixties and seventies, scientists 244 00:13:14,320 --> 00:13:17,520 Speaker 2: used to use a very manual process to break down genomes. 245 00:13:17,920 --> 00:13:20,480 Speaker 2: So remember that's all the genetic information in a plant 246 00:13:20,600 --> 00:13:24,000 Speaker 2: or in an organism into these tiny little pieces. And 247 00:13:24,040 --> 00:13:26,280 Speaker 2: then to say which of these pieces has the thing 248 00:13:26,320 --> 00:13:27,160 Speaker 2: I'm interested in? 249 00:13:27,480 --> 00:13:28,480 Speaker 1: That took forever. 250 00:13:28,800 --> 00:13:31,200 Speaker 3: But now with al Gore's Internet, now I just go 251 00:13:31,240 --> 00:13:32,880 Speaker 3: to my computer and type like I want the gene 252 00:13:32,880 --> 00:13:33,640 Speaker 3: for insulin, and. 253 00:13:33,559 --> 00:13:34,440 Speaker 1: Like, whoop, there it is. 254 00:13:34,480 --> 00:13:36,880 Speaker 3: I can actually search those databases now and say like 255 00:13:36,920 --> 00:13:39,360 Speaker 3: I want a hemoglobin gene, Show me all of them, 256 00:13:39,640 --> 00:13:42,480 Speaker 3: and like here's I don't know, a few thousands. 257 00:13:42,559 --> 00:13:45,400 Speaker 2: This has really widened the pool of potential genes when 258 00:13:45,400 --> 00:13:48,000 Speaker 2: it comes to sourcing for plant based proteins. 259 00:13:48,040 --> 00:13:50,840 Speaker 3: When it comes to sourcing those genes, it's all of 260 00:13:50,920 --> 00:13:55,240 Speaker 3: biological diversity, right, Like, those proteins can come from any kingdom, 261 00:13:55,840 --> 00:14:00,240 Speaker 3: any organism, and because of the how much people will 262 00:14:00,240 --> 00:14:04,520 Speaker 3: have sequenced and how much sequencing is out there, you 263 00:14:04,559 --> 00:14:08,400 Speaker 3: can source those genes from almost anywhere now and be 264 00:14:08,440 --> 00:14:10,920 Speaker 3: able to access that diversity and learn from it. 265 00:14:11,040 --> 00:14:13,800 Speaker 2: So let's say that you've scoured the database and done 266 00:14:13,840 --> 00:14:16,080 Speaker 2: a bunch of tests and you found the gene that 267 00:14:16,160 --> 00:14:20,880 Speaker 2: produced the protein you need to make the perfectly juicy meatball. 268 00:14:21,560 --> 00:14:22,400 Speaker 1: Then what do you do. 269 00:14:22,520 --> 00:14:24,720 Speaker 3: We can take those sequences that are on the computer, 270 00:14:25,760 --> 00:14:29,120 Speaker 3: the digital sequence of the DNA code, and synthesize it 271 00:14:29,160 --> 00:14:33,480 Speaker 3: into actual chemical DNA that now the yeast can read 272 00:14:33,520 --> 00:14:36,640 Speaker 3: and start producing. That yeast now is a factory that 273 00:14:36,840 --> 00:14:40,120 Speaker 3: copies itself, and in a tank that looks like a 274 00:14:40,160 --> 00:14:44,480 Speaker 3: brewery like tank sort of facility, you can have trillions 275 00:14:44,520 --> 00:14:46,640 Speaker 3: of each of these cells, each making their own and 276 00:14:46,680 --> 00:14:48,360 Speaker 3: so like that's where you can actually get to that 277 00:14:48,440 --> 00:14:49,240 Speaker 3: level of tons. 278 00:14:49,600 --> 00:14:53,560 Speaker 2: This process is called recombinant microbial technology, and it's the 279 00:14:53,600 --> 00:14:56,240 Speaker 2: ability to take genes from one source and put them 280 00:14:56,360 --> 00:14:58,040 Speaker 2: in another organism or plant. 281 00:14:58,240 --> 00:15:01,360 Speaker 3: You change the sort of apply chain, right, So now 282 00:15:01,400 --> 00:15:04,359 Speaker 3: instead of having to grow a ton of crops to 283 00:15:04,400 --> 00:15:06,800 Speaker 3: squeeze out the tiny bit of hemoglobe, and you make 284 00:15:06,880 --> 00:15:09,000 Speaker 3: something that makes tons of sugar, you put that into 285 00:15:09,040 --> 00:15:12,000 Speaker 3: the organism that's transforming that sugar into that protein. 286 00:15:12,120 --> 00:15:16,000 Speaker 1: This is really clever. Like, I don't think we appreciate 287 00:15:16,040 --> 00:15:18,680 Speaker 1: what scientists are doing here enough. And I'm not just 288 00:15:18,760 --> 00:15:21,760 Speaker 1: saying this because biologists do it. Break it down for 289 00:15:21,800 --> 00:15:25,440 Speaker 1: the people. Zee, If you have a gene that you 290 00:15:25,480 --> 00:15:27,600 Speaker 1: know encodes for a protein, and that protein is only 291 00:15:27,680 --> 00:15:30,880 Speaker 1: made in small amounts, you have to take so much 292 00:15:30,920 --> 00:15:34,360 Speaker 1: of that source material to get enough protein to be useful. 293 00:15:34,840 --> 00:15:36,840 Speaker 1: You know, many soy plants, we would need to get 294 00:15:36,920 --> 00:15:41,280 Speaker 1: enough hem to make blood for burger king supply of burgers, 295 00:15:42,560 --> 00:15:45,440 Speaker 1: a lot of plants. So instead you take that gene 296 00:15:45,440 --> 00:15:47,840 Speaker 1: and you say, I'm going to use something that can 297 00:15:48,440 --> 00:15:51,920 Speaker 1: grow really quickly, turn over really fast, won't really damage 298 00:15:51,920 --> 00:15:54,680 Speaker 1: the environment, and use that to produce the protein I want. 299 00:15:54,760 --> 00:15:56,920 Speaker 1: So that's the yeast. They use yeas, So you can 300 00:15:57,000 --> 00:15:59,040 Speaker 1: use microorganisms which are really small. You just got to 301 00:15:59,040 --> 00:16:01,480 Speaker 1: feed them some sugar, you know, a little bit of salt, 302 00:16:01,480 --> 00:16:05,200 Speaker 1: some amino acids, add some water. They're happy. And then 303 00:16:05,240 --> 00:16:08,240 Speaker 1: you like how I make cinnamon rolls. Oh well, I 304 00:16:08,280 --> 00:16:12,280 Speaker 1: would like to add that you are using yeasts in 305 00:16:12,320 --> 00:16:15,880 Speaker 1: your cinnamon rolls, and that's what helps it to puff up. Yes, 306 00:16:15,920 --> 00:16:18,680 Speaker 1: because they're releasing gases. That's what makes your dough rise. 307 00:16:18,800 --> 00:16:22,160 Speaker 1: Don't even get me going. So imagine you have huge 308 00:16:22,280 --> 00:16:25,800 Speaker 1: vats of these bacteria or yeasts however they're doing it, 309 00:16:25,960 --> 00:16:28,320 Speaker 1: producing this protein, and then you have a way that 310 00:16:28,400 --> 00:16:31,000 Speaker 1: you can select only the protein and none of the 311 00:16:31,040 --> 00:16:33,200 Speaker 1: other stuff is left behind. And so you just have 312 00:16:33,360 --> 00:16:36,520 Speaker 1: pure protein and a bunch of it, a bunch of it. 313 00:16:36,560 --> 00:16:40,640 Speaker 1: You can make those burgers bleed and sizzle on that grill. 314 00:16:40,760 --> 00:16:44,400 Speaker 1: Baby a meat taste. Yeah, just like that. 315 00:16:45,320 --> 00:16:47,600 Speaker 2: And what really surprised me is when doctor Agapak has 316 00:16:47,600 --> 00:16:52,360 Speaker 2: told us about this recombinant microbial technology process and the 317 00:16:52,440 --> 00:16:54,520 Speaker 2: fact that it's been around for a while. 318 00:16:54,800 --> 00:16:55,880 Speaker 1: She gave us an example. 319 00:16:56,160 --> 00:16:58,840 Speaker 3: One of the most sort of important and kind of 320 00:16:58,880 --> 00:17:02,240 Speaker 3: classic examples of this is how we used to get insulin. 321 00:17:02,920 --> 00:17:05,320 Speaker 3: So in insulin for diabetics used to come from the 322 00:17:05,359 --> 00:17:09,320 Speaker 3: pancreases of pigs. And like one of the earliest applications 323 00:17:09,359 --> 00:17:12,920 Speaker 3: of exactly that recombinant technology, the ability to take genes 324 00:17:13,240 --> 00:17:17,160 Speaker 3: and move them around and start thinking about them as 325 00:17:17,200 --> 00:17:20,160 Speaker 3: these different kinds of machines that can be moved into 326 00:17:20,240 --> 00:17:24,960 Speaker 3: sort of microbial factories. Is the gene for human insulin 327 00:17:25,119 --> 00:17:28,879 Speaker 3: being moved into bacteria. So now instead of pigs and 328 00:17:28,960 --> 00:17:32,440 Speaker 3: killing pigs to get insulin, you can get human insulin 329 00:17:32,560 --> 00:17:35,280 Speaker 3: directly from a bacteria that's growing in a tank. 330 00:17:35,400 --> 00:17:38,119 Speaker 1: Some people were allergic to insulin from pigs, and I 331 00:17:38,119 --> 00:17:42,720 Speaker 1: would imagine that someone who for religious reasons or dietary 332 00:17:42,840 --> 00:17:48,800 Speaker 1: reasons does not want pork anything to enter their body. 333 00:17:48,920 --> 00:17:51,280 Speaker 1: This was probably an issue, and this was a long 334 00:17:51,280 --> 00:17:54,320 Speaker 1: time ago. Did they started doing that synthetic human insulin 335 00:17:54,520 --> 00:17:57,840 Speaker 1: basically insulin produced by bacteria, that was first done in 336 00:17:57,920 --> 00:18:00,520 Speaker 1: nineteen seventy eight's born. 337 00:18:00,600 --> 00:18:03,560 Speaker 2: Okay, so let's get back to heme. This whole process 338 00:18:03,680 --> 00:18:06,720 Speaker 2: we've gone through is just to get one of the 339 00:18:06,880 --> 00:18:10,000 Speaker 2: ingredients for the plant based meat, right, but the majority 340 00:18:10,000 --> 00:18:12,639 Speaker 2: of the patty is still made up of plant proteins 341 00:18:12,680 --> 00:18:14,040 Speaker 2: from peas or soy. 342 00:18:14,160 --> 00:18:17,760 Speaker 1: They're still using plant based protein. They're still using pea 343 00:18:17,800 --> 00:18:21,600 Speaker 1: protein and soy, but they have these features that are 344 00:18:21,680 --> 00:18:24,200 Speaker 1: what we call the especially proteins like heme, which aren't 345 00:18:24,240 --> 00:18:28,199 Speaker 1: present in large amounts. This technology allows you to scale 346 00:18:28,320 --> 00:18:30,840 Speaker 1: up how much hem and how much of the rare 347 00:18:31,000 --> 00:18:33,480 Speaker 1: you know, the rare jewels. It's like a power up. 348 00:18:33,520 --> 00:18:35,600 Speaker 1: It basically allows you to collect way more, you know, 349 00:18:35,880 --> 00:18:37,399 Speaker 1: I don't know if use a place Saga Gena says, well, 350 00:18:37,520 --> 00:18:40,040 Speaker 1: let you collect way more rings, and so now you're like, 351 00:18:40,040 --> 00:18:43,439 Speaker 1: I have everything I need to make the ultimate patty. 352 00:18:43,480 --> 00:18:47,120 Speaker 1: This is a really great way to kind of tackle 353 00:18:48,240 --> 00:18:51,119 Speaker 1: the supplying demand issue right that we have with animals, 354 00:18:51,160 --> 00:18:54,280 Speaker 1: that we have with food in general. There's a demand 355 00:18:54,320 --> 00:18:56,879 Speaker 1: for food, but the cost to the environment to keep 356 00:18:56,960 --> 00:18:58,880 Speaker 1: that supply up is really high. 357 00:18:59,080 --> 00:19:03,879 Speaker 3: Often it is significantly lower impact because the efficiency is different. 358 00:19:04,160 --> 00:19:06,000 Speaker 3: So like when you are you know, you take sugar 359 00:19:06,040 --> 00:19:09,080 Speaker 3: and you'd give it to the yeast, the conversion efficiency 360 00:19:09,119 --> 00:19:11,760 Speaker 3: of that yeast into the hem and the volumes that 361 00:19:11,760 --> 00:19:14,600 Speaker 3: you're talking about are much smaller. And similarly, like the 362 00:19:14,600 --> 00:19:20,000 Speaker 3: conversion of sunlight to p protein is a lot more 363 00:19:20,000 --> 00:19:24,040 Speaker 3: efficient than the conversion of sunlight via grass to cows 364 00:19:24,080 --> 00:19:25,160 Speaker 3: to meat protein. 365 00:19:25,320 --> 00:19:27,639 Speaker 1: We do have to consider the environment and there are 366 00:19:27,640 --> 00:19:31,040 Speaker 1: a couple of ways that this type of technology has 367 00:19:31,080 --> 00:19:33,800 Speaker 1: an impact. You do have to feed these organisms, so 368 00:19:33,840 --> 00:19:36,680 Speaker 1: it's not like, oh, this doesn't cost us anything. These 369 00:19:36,760 --> 00:19:41,119 Speaker 1: organisms don't just like yeast and microbes. Microbes don't just 370 00:19:41,240 --> 00:19:44,000 Speaker 1: produce stuff without any input. There always has to be 371 00:19:44,040 --> 00:19:46,320 Speaker 1: some type of input. I think the convenient or a 372 00:19:46,440 --> 00:19:49,760 Speaker 1: nice thing is that the input is so much lower here. 373 00:19:50,160 --> 00:19:52,920 Speaker 1: Do we need to build that, do we need special lines? 374 00:19:52,960 --> 00:19:55,080 Speaker 1: And you know, is there some stuff that's related to 375 00:19:55,160 --> 00:19:58,040 Speaker 1: the industrial nature of this, Yes, but I think the 376 00:19:58,040 --> 00:20:01,600 Speaker 1: industrial footprint and there's a couple of studies that have 377 00:20:01,680 --> 00:20:05,440 Speaker 1: shown this that the industrial footprint is lower than it 378 00:20:05,480 --> 00:20:10,280 Speaker 1: is for beef, pork, chicken, chicken. And I think the 379 00:20:10,320 --> 00:20:12,879 Speaker 1: other thing that we should consider is the source of 380 00:20:12,920 --> 00:20:17,919 Speaker 1: these materials a lot easier to harvest team from yeast 381 00:20:18,240 --> 00:20:24,840 Speaker 1: making hem than it is hem from big blood and yeah, right, 382 00:20:25,240 --> 00:20:28,719 Speaker 1: And I think that we have to acknowledge that, just 383 00:20:28,760 --> 00:20:33,680 Speaker 1: like doctor Agapacas said about the insulin, you know, there's 384 00:20:33,720 --> 00:20:37,840 Speaker 1: that added benefit. And so by using this recombinant technology 385 00:20:37,880 --> 00:20:40,119 Speaker 1: to let the microbes create what we need, we then 386 00:20:40,240 --> 00:20:42,480 Speaker 1: don't have to have such an impact on the environment. 387 00:20:42,480 --> 00:20:45,359 Speaker 1: Can you imagine growing all that soy, cutting it all down, 388 00:20:45,880 --> 00:20:48,600 Speaker 1: you know, but only only using such a small part 389 00:20:48,680 --> 00:20:52,320 Speaker 1: of it. Yeah, it was a huge waste. And so 390 00:20:53,320 --> 00:20:56,800 Speaker 1: the scientists have found a way, They've found a cheat code, 391 00:20:57,560 --> 00:21:01,199 Speaker 1: a shortcut to getting us it's the same product, but 392 00:21:01,480 --> 00:21:05,240 Speaker 1: with less waste. And I think that is something that 393 00:21:05,240 --> 00:21:07,760 Speaker 1: should not be overlooked, and I actually think this is something, 394 00:21:07,880 --> 00:21:09,359 Speaker 1: This is where we're going to head in the future. 395 00:21:10,160 --> 00:21:12,879 Speaker 1: Because now what we're talking about is just using this 396 00:21:13,000 --> 00:21:16,760 Speaker 1: technology to make one small component of a larger product. 397 00:21:16,960 --> 00:21:18,639 Speaker 1: But some people are starting to ask, well, if I 398 00:21:18,640 --> 00:21:20,640 Speaker 1: can use the lab to make this one thing, can 399 00:21:20,680 --> 00:21:24,320 Speaker 1: I make animal protein in the lab? Can I make 400 00:21:24,400 --> 00:21:28,560 Speaker 1: animal tissue? Can I make Yeah? And so now we're 401 00:21:28,560 --> 00:21:31,840 Speaker 1: talking about real funny about that they are, But you 402 00:21:31,920 --> 00:21:33,760 Speaker 1: don't feel funny when they grow the skin and give 403 00:21:33,800 --> 00:21:36,439 Speaker 1: you a skin graph that you don't You take that 404 00:21:36,480 --> 00:21:38,479 Speaker 1: skin graft and you walk out of that hospital. I 405 00:21:38,520 --> 00:21:41,840 Speaker 1: know that that's high. I know that's not the major 406 00:21:41,920 --> 00:21:43,960 Speaker 1: way that things are done now. Most people have skin 407 00:21:43,960 --> 00:21:46,560 Speaker 1: graphs from other areas on their body. But that is 408 00:21:46,600 --> 00:21:49,760 Speaker 1: a that's new technology, right, And so you really have 409 00:21:49,800 --> 00:21:52,280 Speaker 1: to ask where will we draw Where do you draw 410 00:21:52,320 --> 00:21:55,199 Speaker 1: the line? Yeah? I guess it's just basically up to you. 411 00:21:56,119 --> 00:22:00,480 Speaker 2: What do you feel comfortable with and what impacts do 412 00:22:00,480 --> 00:22:03,640 Speaker 2: you want to make on society? And once you weigh 413 00:22:03,640 --> 00:22:06,280 Speaker 2: those things out, you can make an informed decision. 414 00:22:06,440 --> 00:22:08,119 Speaker 1: I guess now we now we just gotta stick to 415 00:22:08,119 --> 00:22:10,680 Speaker 1: our crumbles. We gotta stick to those crumbles and patties. 416 00:22:11,280 --> 00:22:14,000 Speaker 1: But I hope to elevate up too. You think you 417 00:22:14,400 --> 00:22:18,680 Speaker 1: think you're gonna be a vegan. No, I'm sorry. Even 418 00:22:18,680 --> 00:22:21,199 Speaker 1: when I was, I liked the flavor. I don't have 419 00:22:21,240 --> 00:22:22,719 Speaker 1: to eat the meat, but I need it in there. 420 00:22:22,760 --> 00:22:26,320 Speaker 1: I need bacon flavor. I need bacon flavor. 421 00:22:26,800 --> 00:22:29,400 Speaker 2: If hey, scientists, wake up, If you can do that, 422 00:22:29,760 --> 00:22:32,720 Speaker 2: I'll be right on board. Yeah. I would put bacon 423 00:22:32,760 --> 00:22:34,840 Speaker 2: flavor on everything. I'd put it in my toothpaste. 424 00:22:35,040 --> 00:22:35,919 Speaker 1: Oh t T. 425 00:22:39,560 --> 00:22:41,440 Speaker 2: If you lick a burger patty, does that make you? 426 00:22:41,800 --> 00:22:43,680 Speaker 2: Does that mean you're eating meat? I think you gotta 427 00:22:44,240 --> 00:22:46,919 Speaker 2: like masticate like so, if I lick a patty, I 428 00:22:46,920 --> 00:22:48,040 Speaker 2: can be vegetarian. 429 00:22:48,840 --> 00:22:51,520 Speaker 1: If you're thinking about that, you're not committed to the 430 00:22:51,600 --> 00:22:56,240 Speaker 1: vegetarian lifestyle. Oh it's just so hard. Yeah, we won't. 431 00:22:56,760 --> 00:22:59,600 Speaker 1: Don't bother joining the group. I don't think you're gonna 432 00:22:59,600 --> 00:23:02,240 Speaker 1: make it. See now she's trying to challenge me. I 433 00:23:02,320 --> 00:23:05,240 Speaker 1: know my friend. If it's one thing my friend will 434 00:23:05,320 --> 00:23:07,760 Speaker 1: rise to. It is a challenge. She does not like 435 00:23:07,800 --> 00:23:09,159 Speaker 1: you telling her she can't do something. 436 00:23:09,280 --> 00:23:10,920 Speaker 2: That means I need to head to the grocery store 437 00:23:11,000 --> 00:23:14,280 Speaker 2: and buy those plant based meat crumbles or whatever they're called. 438 00:23:14,440 --> 00:23:17,679 Speaker 1: Oprah said ten days was enough. Lets you do a 439 00:23:17,840 --> 00:23:20,760 Speaker 1: ten day vegetarian challenge. 440 00:23:21,000 --> 00:23:23,800 Speaker 2: Okay, so we're gonna put it up on the instagrams 441 00:23:24,200 --> 00:23:28,000 Speaker 2: as we do, and whoever is opting in, you gotta 442 00:23:28,080 --> 00:23:28,919 Speaker 2: send us a picture of. 443 00:23:28,920 --> 00:23:33,840 Speaker 1: Your food every day. Yes, this is intense. I'm ready 444 00:23:35,040 --> 00:23:35,920 Speaker 1: put them on the stories. 445 00:23:36,000 --> 00:23:37,960 Speaker 2: I'm I'm gonna fail the first day because I'm gonna 446 00:23:37,960 --> 00:23:40,840 Speaker 2: forget and I'm gonna be like, I had eggs this morning. 447 00:23:41,240 --> 00:23:43,240 Speaker 1: That's like, did I tell you my dad we were 448 00:23:43,240 --> 00:23:45,240 Speaker 1: doing that thing? He said, Oh, I messed up. I 449 00:23:45,280 --> 00:23:49,919 Speaker 1: had brisket for breakfast. Who eats brisket for breakfast? That 450 00:23:50,040 --> 00:23:54,320 Speaker 1: sounds just right. That sounds just like Curtis. That sounds 451 00:23:54,560 --> 00:24:09,400 Speaker 1: just right. That's it for Lab nineteen. 452 00:24:09,800 --> 00:24:11,880 Speaker 2: Don't forget to check out our website for a cheat 453 00:24:11,920 --> 00:24:14,760 Speaker 2: sheet on today's episode. You can find it and sign 454 00:24:14,840 --> 00:24:18,080 Speaker 2: up for our newsletter at Dope Labs podcast dot com. 455 00:24:18,119 --> 00:24:20,879 Speaker 1: Also, we love hearing from you. What did you think 456 00:24:20,920 --> 00:24:23,440 Speaker 1: about today's lab? What are your ideas for future labs? 457 00:24:23,520 --> 00:24:26,200 Speaker 1: Our number is two zero two five six seven seven 458 00:24:26,320 --> 00:24:27,040 Speaker 1: zero two eight. 459 00:24:27,280 --> 00:24:29,560 Speaker 2: You can also find us on Twitter and Instagram. At 460 00:24:29,600 --> 00:24:30,680 Speaker 2: Dope Labs podcast. 461 00:24:30,840 --> 00:24:34,760 Speaker 1: TT is on Twitter at dr Underscore, t Sho and 462 00:24:34,800 --> 00:24:37,840 Speaker 1: you can find Zakia at z Said. So follow us 463 00:24:37,880 --> 00:24:40,640 Speaker 1: on Spotify or wherever else you listen to your podcast. 464 00:24:40,760 --> 00:24:43,680 Speaker 1: Special thanks to our guest doctor Christina Agapakis. Find out 465 00:24:43,720 --> 00:24:45,760 Speaker 1: more about her work in the show notes. Dope Labs 466 00:24:45,840 --> 00:24:48,480 Speaker 1: is produced by Jenny rattlet Mass of Wave Runner Studios, 467 00:24:48,800 --> 00:24:51,800 Speaker 1: mixing and sound design by Hannes Brown. Special thanks to 468 00:24:51,920 --> 00:24:52,640 Speaker 1: Jen Stanley. 469 00:24:52,840 --> 00:24:57,000 Speaker 2: Original theme music is by Taka Yasuzawa and Alex Sugiura, 470 00:24:57,480 --> 00:24:59,800 Speaker 2: with additional music by Elijah L. 471 00:25:00,119 --> 00:25:03,240 Speaker 1: Harvey. Dope Labs is a production of Spotify Studios and 472 00:25:03,280 --> 00:25:07,000 Speaker 1: Mega Owned Media Group and is executive produced by us T. T. 473 00:25:07,119 --> 00:25:08,479 Speaker 1: Shadiah and Zakiah Wattley. 474 00:25:11,800 --> 00:25:13,879 Speaker 2: I know what you're thinking, Oh, I don't want all 475 00:25:13,920 --> 00:25:15,880 Speaker 2: these GMOs. 476 00:25:15,920 --> 00:25:23,560 Speaker 1: Well, TT wants to fight you. Let me tell you 477 00:25:23,600 --> 00:25:23,919 Speaker 1: something