1 00:00:15,356 --> 00:00:15,796 Speaker 1: Pushkin. 2 00:00:20,756 --> 00:00:23,356 Speaker 2: There's this idea people have been waving their hands about 3 00:00:23,356 --> 00:00:25,716 Speaker 2: for a while. Now, what if we're about to have 4 00:00:25,796 --> 00:00:30,476 Speaker 2: a huge wave of technological progress in biology. On a 5 00:00:30,476 --> 00:00:33,556 Speaker 2: few recent episodes of this show, we've talked about one 6 00:00:33,636 --> 00:00:37,076 Speaker 2: obvious place we'd see that wave in medicine, with things 7 00:00:37,156 --> 00:00:40,156 Speaker 2: like new drugs and human tissues grown in the lab. 8 00:00:40,716 --> 00:00:43,676 Speaker 2: But the impact could be much broader than that. There's 9 00:00:43,716 --> 00:00:47,956 Speaker 2: this whole nascent industry called synthetic biology. People are trying 10 00:00:47,956 --> 00:00:51,516 Speaker 2: to genetically engineer yeast and bacteria to produce everything from 11 00:00:51,636 --> 00:00:56,836 Speaker 2: fertilizer to fragrances. Take, for example, indigo colored dye, the 12 00:00:56,956 --> 00:00:59,916 Speaker 2: dye used on billions of pairs of genes a year. 13 00:01:00,516 --> 00:01:05,916 Speaker 2: That's j E, A N S, not ge nes, unfortunate 14 00:01:05,956 --> 00:01:09,836 Speaker 2: hominem in this context today, that in goo colored dye 15 00:01:09,876 --> 00:01:12,796 Speaker 2: typically comes from petrochemicals, and it's made in a process 16 00:01:12,836 --> 00:01:15,716 Speaker 2: with lots of nasty byproducts. But what if you could 17 00:01:15,756 --> 00:01:19,596 Speaker 2: use bacteria to make industrial quantities of that dye and 18 00:01:19,676 --> 00:01:26,676 Speaker 2: get rid of all the nasty by products. I'm Jacob 19 00:01:26,676 --> 00:01:29,396 Speaker 2: Goldstein and this is What's Your Problem the show where 20 00:01:29,436 --> 00:01:32,836 Speaker 2: I talk to people who are trying to make technological progress. 21 00:01:33,396 --> 00:01:36,956 Speaker 2: My guests today are Tammy Sue and Michelle Jude. They 22 00:01:36,956 --> 00:01:40,356 Speaker 2: are the co founders of a company called Hugh hu 23 00:01:40,716 --> 00:01:44,316 Speaker 2: u Me. Michelle is the CEO and Tammy is the 24 00:01:44,356 --> 00:01:50,116 Speaker 2: CSO Chief Scientific Officer. Their problem is this, how can 25 00:01:50,156 --> 00:01:53,676 Speaker 2: you get bacteria to produce indigo dye? And how can 26 00:01:53,716 --> 00:01:56,636 Speaker 2: you do it cheaply and reliably enough to replace the 27 00:01:56,716 --> 00:01:59,316 Speaker 2: dye made from petrochemicals. 28 00:02:00,156 --> 00:02:00,756 Speaker 1: To start. 29 00:02:00,876 --> 00:02:04,196 Speaker 2: I asked Michelle and Tammy how they arrived at their problem. 30 00:02:04,396 --> 00:02:07,076 Speaker 2: As it turns out, they discovered the problem from very 31 00:02:07,116 --> 00:02:08,036 Speaker 2: different directions. 32 00:02:09,156 --> 00:02:14,556 Speaker 1: Shell answered first, So, my family, you know, we're immigrants 33 00:02:14,596 --> 00:02:18,236 Speaker 1: from China, came here to you know, move to la 34 00:02:18,356 --> 00:02:20,636 Speaker 1: when I was three years old, and that's when my 35 00:02:20,756 --> 00:02:25,156 Speaker 1: parents actually started their own kind of traditional, you know, 36 00:02:25,236 --> 00:02:28,836 Speaker 1: wholesale apparel business. So I really, I would say, I 37 00:02:29,116 --> 00:02:32,836 Speaker 1: grew up in this like fashion and apparel business, but 38 00:02:33,156 --> 00:02:39,796 Speaker 1: not in a very glamorous way. My experiences or or 39 00:02:39,996 --> 00:02:45,196 Speaker 1: recollections of the fashion industry. Growing up in this family 40 00:02:45,276 --> 00:02:49,756 Speaker 1: business was literally you know, traveling with my parents in 41 00:02:50,276 --> 00:02:54,916 Speaker 1: family vacations back to China over the summers and visiting 42 00:02:55,076 --> 00:03:01,076 Speaker 1: these mills or garment factories and really firsthand witnessing some 43 00:03:01,356 --> 00:03:07,636 Speaker 1: of the the negative impacts right of apparel manufacturing and 44 00:03:07,756 --> 00:03:11,636 Speaker 1: specifically you know, my parents their business was a they 45 00:03:11,636 --> 00:03:15,956 Speaker 1: were doing streetwear right in the nineties, and so Denham 46 00:03:16,076 --> 00:03:18,156 Speaker 1: was like a big part of that. And so you 47 00:03:18,196 --> 00:03:23,756 Speaker 1: know it was specifically denim mills and and denim manufacturing. 48 00:03:23,996 --> 00:03:26,556 Speaker 2: And so what did you see, like specifically when when 49 00:03:26,556 --> 00:03:30,476 Speaker 2: you mentioned that you saw saw that side of the industry, Like, 50 00:03:30,876 --> 00:03:33,276 Speaker 2: is there a particular trip or a particular thing that 51 00:03:33,316 --> 00:03:35,916 Speaker 2: you saw that that stands out in your memory. 52 00:03:36,956 --> 00:03:39,316 Speaker 1: Yeah, I mean I think about you know, going to 53 00:03:39,956 --> 00:03:44,036 Speaker 1: the kind of literally like you know, textile manufacturing cities 54 00:03:44,156 --> 00:03:49,116 Speaker 1: right in southern China where it's just like, you know, 55 00:03:50,236 --> 00:03:52,996 Speaker 1: a bunch of kind of conglomertive factories all you know, 56 00:03:53,156 --> 00:03:57,476 Speaker 1: all together. The air quality kind of outside isn't great. 57 00:03:57,556 --> 00:04:01,476 Speaker 1: You go into the facility, it's even worse. Everybody has 58 00:04:01,636 --> 00:04:06,196 Speaker 1: kind of masks on. There are basically like blue particles. 59 00:04:05,676 --> 00:04:06,476 Speaker 3: In the air. 60 00:04:06,956 --> 00:04:10,396 Speaker 1: You know, it's just on people's skins, you know. And 61 00:04:10,436 --> 00:04:14,036 Speaker 1: I was a child right at this time, but those 62 00:04:14,036 --> 00:04:17,276 Speaker 1: are the kind of like images that are I think 63 00:04:17,356 --> 00:04:21,116 Speaker 1: still ingrained in my mind. I Mean, the dye industry 64 00:04:21,276 --> 00:04:25,236 Speaker 1: is a key kind of a fender, I would say 65 00:04:25,316 --> 00:04:30,116 Speaker 1: in terms of, like, you know, jobs that pose threats 66 00:04:30,196 --> 00:04:33,636 Speaker 1: to safety, both in terms of worker health as well 67 00:04:33,676 --> 00:04:37,996 Speaker 1: as community health. You know, dying and the effluence from dying, 68 00:04:39,476 --> 00:04:42,916 Speaker 1: you know, is a major source of water and kind 69 00:04:42,916 --> 00:04:45,796 Speaker 1: of community pollution. Right. And by the way, you know, 70 00:04:45,876 --> 00:04:49,476 Speaker 1: in the indigo process for example, right, specifically, you've got 71 00:04:49,716 --> 00:04:53,116 Speaker 1: you know, not just analine, which is a benzene derivative, 72 00:04:53,196 --> 00:04:58,516 Speaker 1: right that has true carcinogenic properties, but you've got you know, 73 00:04:58,916 --> 00:05:03,476 Speaker 1: sodamide and formaldehyde and you know, these harsh chemicals that 74 00:05:03,556 --> 00:05:08,556 Speaker 1: are going into the production process of these core dyes 75 00:05:09,636 --> 00:05:12,676 Speaker 1: have done a lot of innovation in the fashion industry, 76 00:05:12,716 --> 00:05:15,756 Speaker 1: but the kind of dye space itself hasn't seen a 77 00:05:15,756 --> 00:05:16,716 Speaker 1: whole lot of innovation. 78 00:05:17,076 --> 00:05:23,836 Speaker 2: Good. So that's your introduction to denim really early. The 79 00:05:23,876 --> 00:05:27,156 Speaker 2: seed is planted, right, yeah, Tammy, how do how do 80 00:05:27,276 --> 00:05:28,716 Speaker 2: you come into the story? 81 00:05:30,196 --> 00:05:34,356 Speaker 4: So my story and background is very different from Michelle's. 82 00:05:34,996 --> 00:05:38,356 Speaker 4: And so when I was in college, I was introduced 83 00:05:38,396 --> 00:05:42,516 Speaker 4: to this field of synthetic biology, which is how do 84 00:05:42,596 --> 00:05:46,356 Speaker 4: we take these microbes you know, e. Coli or yeast 85 00:05:47,116 --> 00:05:51,076 Speaker 4: and actually program them to make them produce useful chemicals 86 00:05:51,356 --> 00:05:52,756 Speaker 4: for for people. 87 00:05:52,996 --> 00:05:55,436 Speaker 2: So you're in you go to grad school, you go 88 00:05:55,436 --> 00:05:58,276 Speaker 2: to get a PhD in Berkeley, and you find yourself 89 00:05:58,316 --> 00:06:01,596 Speaker 2: in a lab. What's what's the sort of generally what's 90 00:06:01,636 --> 00:06:02,596 Speaker 2: the lab working on? 91 00:06:02,756 --> 00:06:06,476 Speaker 4: Yeah, so the lab I was in was working on 92 00:06:06,756 --> 00:06:11,076 Speaker 4: how do we develop tools for engineering E. Coli and 93 00:06:11,196 --> 00:06:18,476 Speaker 4: yeast microbes to produce things like drug precursors or colors 94 00:06:18,636 --> 00:06:22,756 Speaker 4: or kind of other biochemicals. 95 00:06:22,316 --> 00:06:26,556 Speaker 2: Get microbes to make useful stuff for people exactly exactly? 96 00:06:27,076 --> 00:06:29,356 Speaker 2: And how do you land on indigo? 97 00:06:29,556 --> 00:06:32,876 Speaker 4: Yeah, there was there was this idea kind of floating 98 00:06:32,876 --> 00:06:37,196 Speaker 4: around the lab right before I joined, about how do 99 00:06:37,276 --> 00:06:42,276 Speaker 4: we produce indigo? Actually, I think it was because people 100 00:06:42,316 --> 00:06:44,596 Speaker 4: wanted to be able to see what was going on 101 00:06:44,676 --> 00:06:49,156 Speaker 4: inside the cells. Cells are really tiny, right, and often 102 00:06:49,196 --> 00:06:51,516 Speaker 4: you make these changes and you try to get the 103 00:06:51,756 --> 00:06:54,996 Speaker 4: enzymes to do different things, but you don't really know 104 00:06:55,556 --> 00:06:59,196 Speaker 4: exactly what's going on without doing some complicated assay. So 105 00:06:59,236 --> 00:07:02,276 Speaker 4: there was an idea that maybe we could use a 106 00:07:02,356 --> 00:07:05,036 Speaker 4: color output, Like we change an enzyme and we get 107 00:07:05,036 --> 00:07:08,476 Speaker 4: this color output, and indigo is kind of this natural 108 00:07:08,516 --> 00:07:10,356 Speaker 4: diet's found and plants, so they were like, maybe we 109 00:07:10,356 --> 00:07:12,996 Speaker 4: could use indigo to see what's kind of going on 110 00:07:13,076 --> 00:07:13,476 Speaker 4: in the cell. 111 00:07:14,036 --> 00:07:16,236 Speaker 2: So just to be clear. So just to be clear, 112 00:07:16,276 --> 00:07:20,716 Speaker 2: the idea of getting a cell to express indigo this 113 00:07:20,796 --> 00:07:24,196 Speaker 2: blue color. The idea wasn't oh, let's make clean or 114 00:07:24,236 --> 00:07:27,276 Speaker 2: dye for blue jens. It's let's make a tool for 115 00:07:27,676 --> 00:07:30,996 Speaker 2: scientists to use to understand what's going on inside the cell. 116 00:07:32,076 --> 00:07:35,596 Speaker 4: Initially, yeah, and then as we were kind of looking 117 00:07:35,596 --> 00:07:39,436 Speaker 4: into it, it actually seemed like indigo itself was a 118 00:07:39,516 --> 00:07:43,796 Speaker 4: really big problem in the textile industry. Pretty much all 119 00:07:43,796 --> 00:07:48,116 Speaker 4: indigos used for dnim genes and it we learned that 120 00:07:48,596 --> 00:07:51,436 Speaker 4: all of it, the vast majority of it, is sourced 121 00:07:51,436 --> 00:07:54,756 Speaker 4: from petrochemical sources right now, and so there was this 122 00:07:54,836 --> 00:07:58,196 Speaker 4: need to actually make it in a biologically sourced manner. 123 00:07:58,556 --> 00:08:02,156 Speaker 4: My advisor was on this fellowship and they published an 124 00:08:02,236 --> 00:08:06,156 Speaker 4: article showing some very preliminary results that we were having 125 00:08:06,196 --> 00:08:09,076 Speaker 4: in the lab on this project, and it was published 126 00:08:09,196 --> 00:08:13,476 Speaker 4: on the UC Berkeley website, and then Dune and brands 127 00:08:13,876 --> 00:08:16,636 Speaker 4: in the area actually started to reach out to him 128 00:08:16,716 --> 00:08:20,436 Speaker 4: and say, oh, I heard you're working on other ways 129 00:08:20,436 --> 00:08:23,876 Speaker 4: to make indigo. Can we talk what is it like? 130 00:08:23,996 --> 00:08:26,476 Speaker 4: How much you know? Can we do a little trial, so. 131 00:08:26,396 --> 00:08:31,276 Speaker 2: You decide to start the company. Tammy, you've done this research, Like, 132 00:08:31,516 --> 00:08:33,956 Speaker 2: what exactly had you already done? What did you know 133 00:08:33,996 --> 00:08:36,236 Speaker 2: how to do when you started the company. 134 00:08:36,876 --> 00:08:40,076 Speaker 4: So at the end of my PhD, the last figure 135 00:08:40,196 --> 00:08:44,356 Speaker 4: in the paper that we published was actually kind of 136 00:08:44,436 --> 00:08:47,836 Speaker 4: unusual for a research paper. I had died one piece 137 00:08:47,996 --> 00:08:52,756 Speaker 4: of fabric. It was a scarf with this indigo die. 138 00:08:53,356 --> 00:08:55,876 Speaker 4: It was definitely died in a way that was not 139 00:08:56,036 --> 00:09:00,436 Speaker 4: scalable and not industrially viable by any means. 140 00:09:00,796 --> 00:09:02,236 Speaker 3: It smelled a little bit funky. 141 00:09:02,556 --> 00:09:05,116 Speaker 2: How how was it died? Like, how did you how 142 00:09:05,156 --> 00:09:05,796 Speaker 2: did you diet? 143 00:09:06,516 --> 00:09:11,556 Speaker 4: I actually hung up a shoelace across across the hallway 144 00:09:12,396 --> 00:09:15,996 Speaker 4: and just kind of flopped this piece of fabric over it, 145 00:09:16,036 --> 00:09:19,596 Speaker 4: and I sprayed the dye against it and used the 146 00:09:19,596 --> 00:09:23,516 Speaker 4: bucket to catch the remaining dye at the bottom. It 147 00:09:23,556 --> 00:09:26,956 Speaker 4: was definitely an experience, but we at the end of 148 00:09:26,956 --> 00:09:30,476 Speaker 4: the day we got this nice blue fabric and it 149 00:09:30,516 --> 00:09:32,036 Speaker 4: was kind of our first proof of concept. 150 00:09:32,796 --> 00:09:35,396 Speaker 2: So it worked. It worked at least for one scarf, 151 00:09:35,436 --> 00:09:38,756 Speaker 2: one time in the hallway, at least once exactly good. 152 00:09:38,956 --> 00:09:41,996 Speaker 1: I want to clarify that even though it turned blue 153 00:09:42,676 --> 00:09:45,356 Speaker 1: that before. Right, we were literally telling the story yesterday 154 00:09:45,396 --> 00:09:47,596 Speaker 1: to the company. It was like that was like, okay, 155 00:09:47,956 --> 00:09:51,076 Speaker 1: blue is great. We had no idea you know, oh 156 00:09:51,116 --> 00:09:54,556 Speaker 1: it's kind of blue greenish, or like you know what 157 00:09:54,676 --> 00:09:59,636 Speaker 1: exactly all of that means. We had no capability to 158 00:09:59,676 --> 00:10:03,236 Speaker 1: measure or understand any of that. So really getting it 159 00:10:03,316 --> 00:10:06,316 Speaker 1: to those industrial specs, I would say, was probably the 160 00:10:06,396 --> 00:10:11,196 Speaker 1: first major challenge that the company that we as a 161 00:10:11,236 --> 00:10:12,276 Speaker 1: team had to tackle. 162 00:10:12,556 --> 00:10:16,156 Speaker 2: So tell me about that, right, Like, blue isn't good enough? Right, 163 00:10:16,156 --> 00:10:18,276 Speaker 2: you can't go to some genes manufacturer's going to make 164 00:10:18,316 --> 00:10:20,356 Speaker 2: one hundred thousand pairs of genes be like yeah, it's blue. 165 00:10:20,396 --> 00:10:22,196 Speaker 2: They're not gonna be like great, send it to us, right, 166 00:10:22,236 --> 00:10:24,236 Speaker 2: so what do you have to do to get it 167 00:10:24,236 --> 00:10:25,676 Speaker 2: to be the right kind of blue? 168 00:10:25,796 --> 00:10:28,716 Speaker 4: So kind of where where we were at when at 169 00:10:28,796 --> 00:10:31,956 Speaker 4: this first proof of concept was okay, so you have cells. 170 00:10:32,116 --> 00:10:35,556 Speaker 4: They're making this indigo molecule. We know it's literally indigo molecule. 171 00:10:35,676 --> 00:10:38,876 Speaker 4: The cells are growing in their own media. We just 172 00:10:38,916 --> 00:10:41,636 Speaker 4: try to like you know, break open the cells and 173 00:10:41,676 --> 00:10:44,396 Speaker 4: try to you know, get the blue onto the fabric. 174 00:10:44,636 --> 00:10:47,316 Speaker 3: But that's not necessarily good enough, right, so you've. 175 00:10:47,116 --> 00:10:50,996 Speaker 2: Got the right molecule, what do you have to what 176 00:10:51,036 --> 00:10:53,276 Speaker 2: do you have to fix when you're you know, starting 177 00:10:53,276 --> 00:10:56,596 Speaker 2: the company, leaving academia, going to make this industrial product. 178 00:10:56,756 --> 00:10:58,036 Speaker 2: What do you have to fix on the kind of 179 00:10:58,076 --> 00:10:58,916 Speaker 2: molecular level. 180 00:10:59,276 --> 00:11:01,796 Speaker 4: I think the main thing is how do we separate 181 00:11:01,876 --> 00:11:05,116 Speaker 4: out the indigo molecule away from all of the other things, 182 00:11:05,156 --> 00:11:06,836 Speaker 4: all of the cells and all of the things that 183 00:11:06,876 --> 00:11:11,036 Speaker 4: the cell is growing in. And so at the very beginning, 184 00:11:11,716 --> 00:11:15,196 Speaker 4: a lot of our methods were very rudimentary, using you know, 185 00:11:15,676 --> 00:11:20,596 Speaker 4: some off the shelf chemical engineering ways, and so that's 186 00:11:20,636 --> 00:11:23,156 Speaker 4: why our first dye turned out a little bit green. 187 00:11:23,916 --> 00:11:27,436 Speaker 4: And that's why kind of our first first hire was 188 00:11:27,476 --> 00:11:31,156 Speaker 4: in a downstream processing engineer so that he could help 189 00:11:31,236 --> 00:11:32,956 Speaker 4: us fix this problem. 190 00:11:33,236 --> 00:11:34,836 Speaker 2: So the problem is, how do you get rid of 191 00:11:34,956 --> 00:11:39,156 Speaker 2: everything that is not the indigo dye molecule, all the 192 00:11:39,316 --> 00:11:41,236 Speaker 2: cells that made it, all the stuff that the cells 193 00:11:41,236 --> 00:11:42,636 Speaker 2: were grown. You got to get rid of all that, 194 00:11:42,716 --> 00:11:46,756 Speaker 2: but keep the dye. That's the first hard problem, exactly exactly. 195 00:11:46,796 --> 00:11:49,116 Speaker 1: And then kind of pairing that, I think the other 196 00:11:49,236 --> 00:11:53,836 Speaker 1: key unlock for us was also bringing in actual textile 197 00:11:54,116 --> 00:11:58,036 Speaker 1: technical expertise, so no longer are we doing a visual 198 00:11:58,116 --> 00:12:00,636 Speaker 1: test of is it blue or not? But now we 199 00:12:00,676 --> 00:12:05,676 Speaker 1: can actually precisely quantify how green is it, how red 200 00:12:05,876 --> 00:12:09,636 Speaker 1: is it relative to the amount of blue, and how 201 00:12:09,676 --> 00:12:17,196 Speaker 1: close is that literally numerically compared to the synthetic standard 202 00:12:17,316 --> 00:12:18,316 Speaker 1: that we want to be match up. 203 00:12:18,396 --> 00:12:21,596 Speaker 2: So there's figuring it out at that level, and then 204 00:12:21,676 --> 00:12:26,996 Speaker 2: there's figuring out how to make thousands of pounds of 205 00:12:27,036 --> 00:12:30,916 Speaker 2: this die, right, which seems like a related but distinct 206 00:12:31,196 --> 00:12:32,996 Speaker 2: problem that you've got to be solving sort of at 207 00:12:32,996 --> 00:12:33,636 Speaker 2: the same time. 208 00:12:34,316 --> 00:12:35,196 Speaker 3: Yeah, exactly. 209 00:12:35,596 --> 00:12:39,956 Speaker 4: So you know, like when Dunham Brands came a knocking, 210 00:12:40,596 --> 00:12:42,516 Speaker 4: They're like, can you make a kilogram? 211 00:12:42,636 --> 00:12:43,756 Speaker 3: I was like, absolutely not. 212 00:12:44,956 --> 00:12:49,956 Speaker 4: And so one of the big limitations thus far in 213 00:12:50,236 --> 00:12:53,076 Speaker 4: this field of synthetic biology is, Okay, so you can 214 00:12:53,156 --> 00:12:56,116 Speaker 4: grow your microbe, you can grow it at larger scale, 215 00:12:56,636 --> 00:13:00,396 Speaker 4: but how do we actually get the space to produce 216 00:13:00,436 --> 00:13:04,476 Speaker 4: this at a large industrial scale over and over in 217 00:13:04,516 --> 00:13:05,636 Speaker 4: a really repeatable way. 218 00:13:06,436 --> 00:13:08,716 Speaker 3: And so for that you need really large scale equipment. 219 00:13:08,756 --> 00:13:12,036 Speaker 2: How do you truly industrialized how do you make lots 220 00:13:12,076 --> 00:13:15,636 Speaker 2: and lots of dye every day in a factory? For us? 221 00:13:15,636 --> 00:13:16,076 Speaker 3: Exactly? 222 00:13:16,676 --> 00:13:20,116 Speaker 4: And I think even that we with the growth of 223 00:13:20,116 --> 00:13:24,596 Speaker 4: the synthetic biology industry, there's been a lot more demand 224 00:13:24,676 --> 00:13:29,196 Speaker 4: and building out of these contract manufacturers where we can 225 00:13:29,236 --> 00:13:30,796 Speaker 4: we don't have to build our own facility. We can 226 00:13:30,876 --> 00:13:34,836 Speaker 4: kind of drop into an outsource facility and be able 227 00:13:34,876 --> 00:13:36,756 Speaker 4: to make use of that infrastructure. 228 00:13:39,076 --> 00:13:41,116 Speaker 2: Tammy and our team have now reached the point where 229 00:13:41,116 --> 00:13:44,196 Speaker 2: they can in fact make not just one kilogram of dye, 230 00:13:44,316 --> 00:13:49,396 Speaker 2: but hundreds of kilograms. Progress after the break, what they 231 00:13:49,436 --> 00:13:51,716 Speaker 2: still have to figure out to get their die out 232 00:13:51,756 --> 00:14:02,236 Speaker 2: into the real world. That's the end of the ads. 233 00:14:02,636 --> 00:14:03,756 Speaker 1: Now we're going back to the show. 234 00:14:04,516 --> 00:14:08,036 Speaker 2: So maybe for Michelle, Michelle, can you tell me just 235 00:14:08,236 --> 00:14:11,156 Speaker 2: where's the company now? What are you making now? And 236 00:14:11,276 --> 00:14:13,796 Speaker 2: like what can you not do yet that you need 237 00:14:13,836 --> 00:14:14,036 Speaker 2: to do? 238 00:14:14,876 --> 00:14:17,876 Speaker 1: M So, so maybe just taking a step back, I 239 00:14:18,116 --> 00:14:22,596 Speaker 1: would say, you know, from back then when Tammy thought 240 00:14:22,716 --> 00:14:25,516 Speaker 1: one killogram was too much, you know, I think we've 241 00:14:25,596 --> 00:14:31,436 Speaker 1: really been able to step up in production every year 242 00:14:31,836 --> 00:14:36,156 Speaker 1: as we've also refined and iterated on the process and 243 00:14:36,236 --> 00:14:40,516 Speaker 1: the product. So you know, have gone from making just 244 00:14:40,556 --> 00:14:44,956 Speaker 1: a couple of grams to a couple killograms to now, 245 00:14:45,116 --> 00:14:48,236 Speaker 1: you know, hundreds of kilograms, and we have an eye 246 00:14:48,276 --> 00:14:53,236 Speaker 1: towards you know, metric tons, so thousands of kilograms, so 247 00:14:53,276 --> 00:14:55,996 Speaker 1: that we can actually meet the industry in these needs, right, 248 00:14:56,036 --> 00:14:59,756 Speaker 1: which is the tens of thousands of metric tons kind 249 00:14:59,796 --> 00:15:00,276 Speaker 1: of level. 250 00:15:00,836 --> 00:15:04,036 Speaker 2: And so when do you think you'll be able to 251 00:15:04,076 --> 00:15:06,076 Speaker 2: make at a big enough scale that you can actually 252 00:15:06,356 --> 00:15:09,396 Speaker 2: sell it to somebody who's going to make g means 253 00:15:09,436 --> 00:15:11,276 Speaker 2: for me and the world. 254 00:15:12,196 --> 00:15:17,476 Speaker 1: Yeah, well, so we are. We have been testing and 255 00:15:17,556 --> 00:15:21,316 Speaker 1: trialing our product to make sure that we're approving kind 256 00:15:21,316 --> 00:15:24,116 Speaker 1: of the iterations of the product and designing something that 257 00:15:24,236 --> 00:15:27,956 Speaker 1: is truly drop in and usable for the denim industry. 258 00:15:28,516 --> 00:15:32,756 Speaker 1: We are already working with brands that you know, I 259 00:15:32,756 --> 00:15:36,716 Speaker 1: think listeners, you know and love. 260 00:15:37,236 --> 00:15:40,236 Speaker 2: Can you say the name? Can you say one name 261 00:15:40,276 --> 00:15:41,076 Speaker 2: of one brand? 262 00:15:41,876 --> 00:15:44,236 Speaker 1: We cannot share the name uncorriginately. 263 00:15:44,436 --> 00:15:47,156 Speaker 2: Okay, when do you think I can buy a pair 264 00:15:47,156 --> 00:15:48,676 Speaker 2: of genes? Died with your die? 265 00:15:48,996 --> 00:15:50,756 Speaker 1: So I'm not going to make any promises, but I 266 00:15:50,796 --> 00:15:54,036 Speaker 1: would say, you know, in the next couple years. 267 00:15:54,116 --> 00:15:58,756 Speaker 2: For sure, you just made a promise. I'll take it. 268 00:15:59,436 --> 00:16:06,156 Speaker 1: You're right, that's true? Cut out the foresure. Yeah, No, 269 00:16:06,436 --> 00:16:08,556 Speaker 1: I mean just to say, I think you know we 270 00:16:08,716 --> 00:16:13,876 Speaker 1: are in you know, we're working collaboratively with the brands, 271 00:16:14,156 --> 00:16:17,836 Speaker 1: and it's really a matter of our own capacity and 272 00:16:17,916 --> 00:16:20,596 Speaker 1: scaling and then kind of bringing the cost down over 273 00:16:20,676 --> 00:16:23,476 Speaker 1: time too, so that it can be something that continues 274 00:16:23,516 --> 00:16:26,436 Speaker 1: to be more and more accessible to the broader fashion industry. 275 00:16:26,716 --> 00:16:29,516 Speaker 2: So let's talk about the cost. Yeah, tell me about 276 00:16:29,556 --> 00:16:30,636 Speaker 2: the economics of it. 277 00:16:31,596 --> 00:16:35,596 Speaker 1: I mean, it's it's one of the big goals of 278 00:16:35,676 --> 00:16:38,556 Speaker 1: the business to make it write a success. You know, 279 00:16:38,636 --> 00:16:42,516 Speaker 1: I would say, we're definitely not there yet right to 280 00:16:42,596 --> 00:16:45,516 Speaker 1: your point, you know, probably and you know, order of 281 00:16:45,596 --> 00:16:50,636 Speaker 1: magnitude of productivity away. In order to get there, you. 282 00:16:50,596 --> 00:16:55,996 Speaker 2: Think it needs to be the same price as petrochemical dies. 283 00:16:56,356 --> 00:16:59,996 Speaker 1: So what I would say on the kind of price 284 00:17:00,156 --> 00:17:05,436 Speaker 1: side is I think we're making a bet that brands 285 00:17:06,476 --> 00:17:10,116 Speaker 1: in the greater supply chain understand the big picture here 286 00:17:11,436 --> 00:17:15,276 Speaker 1: and the opportunity is that, you know, luckily dies they 287 00:17:15,316 --> 00:17:19,396 Speaker 1: can make this huge visual impact, but again they're only 288 00:17:19,516 --> 00:17:25,476 Speaker 1: actually a very tiny fraction of what makes the garment itself. 289 00:17:25,996 --> 00:17:30,236 Speaker 1: And so we believe there's a path to commercializing early 290 00:17:30,636 --> 00:17:35,156 Speaker 1: even before we are cost neutral with the petrochemicals. But 291 00:17:35,236 --> 00:17:40,556 Speaker 1: we can commercialize early to help build the business before 292 00:17:40,636 --> 00:17:43,676 Speaker 1: we're there. At the cost side, because it just doesn't 293 00:17:43,716 --> 00:17:47,076 Speaker 1: make a huge difference on the end price of the 294 00:17:47,116 --> 00:17:50,076 Speaker 1: garment for example. Well as an example, it's like, are 295 00:17:50,156 --> 00:17:54,356 Speaker 1: you willing to pay five dollars more for a pair 296 00:17:54,396 --> 00:17:58,476 Speaker 1: of genes to help to facilitate that transition of the 297 00:17:58,596 --> 00:18:02,196 Speaker 1: industry to better materials before it becomes cost neutral? 298 00:18:02,356 --> 00:18:05,956 Speaker 2: And just to be clear, like five dollars more is 299 00:18:06,036 --> 00:18:10,076 Speaker 2: when your die is how much more expensive that petrochemical 300 00:18:10,116 --> 00:18:11,476 Speaker 2: based die. 301 00:18:12,116 --> 00:18:18,076 Speaker 1: Five dollars more is like is like ten x more 302 00:18:18,156 --> 00:18:20,996 Speaker 1: expensive chemical die. 303 00:18:20,476 --> 00:18:23,636 Speaker 2: The die The die cost is a very small percentage 304 00:18:23,756 --> 00:18:27,836 Speaker 2: of the overall cost of a paragenes exactly. Okay, So 305 00:18:27,996 --> 00:18:31,916 Speaker 2: presumably there's like the sort of classic early adopter curve 306 00:18:31,916 --> 00:18:35,036 Speaker 2: where there's a universe of people willing to pay more 307 00:18:36,116 --> 00:18:38,596 Speaker 2: because they care or because they want to signal to 308 00:18:38,636 --> 00:18:41,076 Speaker 2: people that they care whether they care or not. And 309 00:18:42,476 --> 00:18:44,876 Speaker 2: those people will be your early adopters who will allow 310 00:18:44,876 --> 00:18:46,836 Speaker 2: you to scale, and then you'll use that scale to 311 00:18:46,876 --> 00:18:50,596 Speaker 2: become a cost neutral. That's the dream. 312 00:18:50,836 --> 00:18:53,356 Speaker 1: Yeah, I think so, I think we think about, you know, 313 00:18:53,476 --> 00:18:56,316 Speaker 1: the Tesla model for this right where you see. 314 00:18:56,076 --> 00:19:01,556 Speaker 2: Everybody loves the Tesla. Everybody, everybody who's not making software 315 00:19:01,596 --> 00:19:03,116 Speaker 2: everybody who's making a physical thing. 316 00:19:03,276 --> 00:19:03,596 Speaker 1: It is. 317 00:19:03,676 --> 00:19:08,556 Speaker 2: It is really remarkable how that metaphor is the It's 318 00:19:08,556 --> 00:19:10,556 Speaker 2: like it used to the uber but for X, but 319 00:19:10,636 --> 00:19:14,196 Speaker 2: now it's Tesla. But literally yesterday I was talking to 320 00:19:14,236 --> 00:19:16,316 Speaker 2: a guy who's doing that with houses. He's building these 321 00:19:16,356 --> 00:19:19,996 Speaker 2: little backyard houses. Cover. The companies called Cover and they're 322 00:19:19,996 --> 00:19:23,796 Speaker 2: building like really nice little backyard studio apartments. But they 323 00:19:23,796 --> 00:19:25,876 Speaker 2: want to build houses and they want them to be cheaper, 324 00:19:26,596 --> 00:19:28,356 Speaker 2: and it's a Tesla metaphor. 325 00:19:28,636 --> 00:19:30,956 Speaker 1: It's like you go to the premium and you go 326 00:19:31,156 --> 00:19:33,356 Speaker 1: down and it worked. 327 00:19:33,236 --> 00:19:36,956 Speaker 2: And it worked for them. They did it. Are you 328 00:19:36,956 --> 00:19:38,076 Speaker 2: working on other colors? 329 00:19:38,396 --> 00:19:42,916 Speaker 1: You know, there's a broader platform and kind of opportunity 330 00:19:42,996 --> 00:19:47,556 Speaker 1: here right to not just you know, disrupt denim, but 331 00:19:47,756 --> 00:19:52,276 Speaker 1: also the fashion industry and food and cosmetics in all 332 00:19:52,316 --> 00:19:57,076 Speaker 1: of these areas where color is infused into our daily lives. 333 00:19:57,436 --> 00:20:02,636 Speaker 1: And so we're actually now taking our learnings from you know, 334 00:20:02,716 --> 00:20:07,996 Speaker 1: bioengineering our first color product and looking at the broader 335 00:20:08,116 --> 00:20:11,036 Speaker 1: kind of platform that we've developed and saying, how can 336 00:20:11,076 --> 00:20:16,036 Speaker 1: we also create a broader palette that isn't kind of 337 00:20:16,076 --> 00:20:20,236 Speaker 1: one color at a time, knowing that there are tens 338 00:20:20,236 --> 00:20:24,276 Speaker 1: of thousands of different colors in use in these variety 339 00:20:24,316 --> 00:20:25,356 Speaker 1: of industries today. 340 00:20:25,756 --> 00:20:30,556 Speaker 2: Uh huh. Build a system that is more easily customizable 341 00:20:31,036 --> 00:20:34,516 Speaker 2: so that you can get the cells to make whatever 342 00:20:34,636 --> 00:20:35,916 Speaker 2: is the color of the season. 343 00:20:36,676 --> 00:20:37,156 Speaker 1: That's right. 344 00:20:40,116 --> 00:20:42,756 Speaker 2: In a minute, the lightning round with lots of questions 345 00:20:42,796 --> 00:20:53,876 Speaker 2: about genes and genes as in denim. Now back to 346 00:20:53,916 --> 00:20:58,076 Speaker 2: the show. Let's let's do a lightning round. Let me 347 00:20:58,156 --> 00:21:00,516 Speaker 2: just ask you a bunch of questions before it's time 348 00:21:00,556 --> 00:21:05,356 Speaker 2: to go. Oh gosh, Okay, they'll be different, they'll be 349 00:21:05,396 --> 00:21:10,236 Speaker 2: simpler and more fun. Okay for either of you. Why 350 00:21:10,396 --> 00:21:14,716 Speaker 2: are genes still almost always blue? 351 00:21:14,996 --> 00:21:17,236 Speaker 4: Because I don't know if this is a very chicken 352 00:21:17,276 --> 00:21:20,316 Speaker 4: and egg answer, but it's because it has to be 353 00:21:20,356 --> 00:21:24,276 Speaker 4: made with indigo, and I think an indigo is blue. 354 00:21:24,316 --> 00:21:27,676 Speaker 4: And indigo actually binds the yarns in such a way 355 00:21:27,716 --> 00:21:30,716 Speaker 4: that you can kind of flake it off from the 356 00:21:31,396 --> 00:21:34,516 Speaker 4: from the fabric, and you know, as you wear it, 357 00:21:34,516 --> 00:21:37,316 Speaker 4: it takes the shape of you know, your body or 358 00:21:37,476 --> 00:21:39,796 Speaker 4: you know, the wallet that you put in your back pocket. 359 00:21:40,876 --> 00:21:44,036 Speaker 4: And it's really rare to have a dye that has 360 00:21:44,076 --> 00:21:44,916 Speaker 4: these properties. 361 00:21:45,276 --> 00:21:48,036 Speaker 2: I've seen numbers that seem wild for the number of 362 00:21:48,236 --> 00:21:51,276 Speaker 2: jeans made in a year? Do you does either you 363 00:21:51,356 --> 00:21:53,036 Speaker 2: know a true number for that? 364 00:21:54,316 --> 00:21:58,556 Speaker 1: So our latest estimates are number of gens every year 365 00:21:58,756 --> 00:22:02,916 Speaker 1: made is about two to four billion garments. 366 00:22:02,756 --> 00:22:07,316 Speaker 2: Billion, Like that's billion. That's wild, right, Like yes, I 367 00:22:07,316 --> 00:22:08,916 Speaker 2: mean what are we at for the world? 368 00:22:08,916 --> 00:22:09,276 Speaker 1: Now? 369 00:22:09,316 --> 00:22:10,276 Speaker 2: Eight billion people? 370 00:22:10,636 --> 00:22:11,556 Speaker 1: Is that? Is that right? 371 00:22:11,636 --> 00:22:13,916 Speaker 2: So it's like in a few years you have a 372 00:22:13,916 --> 00:22:16,556 Speaker 2: pair of genes for every single man, woman, and child 373 00:22:16,556 --> 00:22:16,996 Speaker 2: on earth. 374 00:22:17,156 --> 00:22:17,956 Speaker 3: Yeah, exactly. 375 00:22:19,036 --> 00:22:23,036 Speaker 2: Okay, here's one for both of you. And I want 376 00:22:23,076 --> 00:22:25,116 Speaker 2: you to try and answer at the same time. So 377 00:22:25,156 --> 00:22:28,396 Speaker 2: I'm gonna ask the question and then I'm gonna say one, two, three, 378 00:22:28,796 --> 00:22:30,476 Speaker 2: and then when I get to three, I want you 379 00:22:30,556 --> 00:22:33,996 Speaker 2: to just give a yes or no answer. Can you 380 00:22:34,076 --> 00:22:37,596 Speaker 2: wear a jean jacket with jeans? Yes? 381 00:22:37,716 --> 00:22:37,876 Speaker 4: Or no? 382 00:22:38,156 --> 00:22:38,356 Speaker 1: One? 383 00:22:38,436 --> 00:22:38,996 Speaker 2: Two three? 384 00:22:39,916 --> 00:22:47,996 Speaker 1: Yes? Oh, it's coming back. It's a trend that is 385 00:22:48,076 --> 00:22:50,116 Speaker 1: coming back. Now, I'm telling. 386 00:22:49,876 --> 00:22:53,076 Speaker 3: You that may be true. That may be true. 387 00:22:53,436 --> 00:22:56,076 Speaker 2: Michelle, you came to hear from the business world. What 388 00:22:56,076 --> 00:22:58,116 Speaker 2: do you know about science now that you didn't know 389 00:22:58,156 --> 00:22:59,236 Speaker 2: when you started the company? 390 00:22:59,596 --> 00:23:06,076 Speaker 1: Ooh, too much? I know. I know so much about science. 391 00:23:06,156 --> 00:23:08,996 Speaker 1: I know enough to be dangerous to talk about by 392 00:23:09,276 --> 00:23:15,236 Speaker 1: engineering and chemical engineering. And you know the bio manufacturing 393 00:23:16,276 --> 00:23:19,516 Speaker 1: to be to be really dangerous. So just to say, 394 00:23:19,996 --> 00:23:22,716 Speaker 1: you know, I think there's a lot of great science, 395 00:23:22,796 --> 00:23:26,676 Speaker 1: a lot of great ideas out there, but actually, you know, 396 00:23:26,716 --> 00:23:30,196 Speaker 1: I have a lot of respect for the chemical engineers 397 00:23:30,356 --> 00:23:34,356 Speaker 1: and the folks who actually go from R and D 398 00:23:34,476 --> 00:23:37,956 Speaker 1: to actually turn it into something that has a commercial 399 00:23:38,036 --> 00:23:41,236 Speaker 1: case around it. And you know, we need to make 400 00:23:41,316 --> 00:23:45,716 Speaker 1: those tough decisions and work on those optimization problems to 401 00:23:45,836 --> 00:23:49,556 Speaker 1: actually get it to be something that's adaptable for the industry. 402 00:23:49,836 --> 00:23:52,156 Speaker 2: So I just want to shout out your dog, who's 403 00:23:52,196 --> 00:23:57,196 Speaker 2: really doing amazing work back over your shoulder. What kind 404 00:23:57,236 --> 00:23:58,036 Speaker 2: of dog is it? 405 00:23:59,596 --> 00:24:03,756 Speaker 1: She's a Congress Spaniel. This is one of her better days. 406 00:24:04,036 --> 00:24:10,316 Speaker 1: She really loves showing her just just all sides of her. 407 00:24:10,436 --> 00:24:13,036 Speaker 1: Let's say to the camera whenever I am on. 408 00:24:12,956 --> 00:24:20,796 Speaker 2: Camera, what's her name? Her name's Daisy, Daisy Classic. Michelle 409 00:24:20,876 --> 00:24:24,436 Speaker 2: Zou and Tammy Sue are the co founders of Hugh. 410 00:24:25,396 --> 00:24:28,556 Speaker 2: Today's show was produced by Edith Russello. It was edited 411 00:24:28,556 --> 00:24:32,756 Speaker 2: by Sarah Nix and Robert Smith and engineered by Amanda 412 00:24:32,876 --> 00:24:36,036 Speaker 2: k Wong. I'm Jacob Goldstein. You can find me on 413 00:24:36,076 --> 00:24:39,196 Speaker 2: Twitter at Jacob Goldstein, or you can email us at 414 00:24:39,356 --> 00:24:43,356 Speaker 2: problem at Cushkin dot fm. We'll be back next week 415 00:24:43,396 --> 00:24:49,556 Speaker 2: with another episode of What's Your Problem.