1 00:00:15,396 --> 00:00:21,916 Speaker 1: Pushkin from Pushkin Industries. This is Deep Background, the show 2 00:00:21,956 --> 00:00:25,076 Speaker 1: where we explore the stories behind the stories in the news. 3 00:00:25,476 --> 00:00:29,036 Speaker 1: I'm Noah Feldman. Today we're going to talk about the 4 00:00:29,116 --> 00:00:36,036 Speaker 1: novel coronavirus and evolution. All viruses mutate and evolve, and 5 00:00:36,156 --> 00:00:40,876 Speaker 1: that includes SARS cove two, the virus that produces COVID nineteen. 6 00:00:41,436 --> 00:00:44,116 Speaker 1: The version of the virus that we saw when the 7 00:00:44,156 --> 00:00:49,196 Speaker 1: pandemic first started this winter is slightly different from the 8 00:00:49,316 --> 00:00:52,676 Speaker 1: version of the virus that has emerged today in ninety 9 00:00:52,716 --> 00:00:56,516 Speaker 1: five percent of the cases that we're seeing. But what 10 00:00:56,716 --> 00:01:01,756 Speaker 1: does that tiny, little single point difference mean one amino acid? 11 00:01:02,636 --> 00:01:05,076 Speaker 1: Is it something we should be concerned about? That is 12 00:01:05,116 --> 00:01:08,036 Speaker 1: something that scientists are in the process of figuring out 13 00:01:08,876 --> 00:01:12,396 Speaker 1: to day. We're joined by one of those scientists, Nevill. 14 00:01:12,476 --> 00:01:15,516 Speaker 1: Sanjana is a geneticist at the New York Genome Center 15 00:01:15,636 --> 00:01:19,436 Speaker 1: and New York University. He has been researching and publishing 16 00:01:19,716 --> 00:01:25,396 Speaker 1: about how the coronavirus is mutating. Nevill, thank you so 17 00:01:25,476 --> 00:01:29,356 Speaker 1: much for joining me. Let's start with the call it 18 00:01:29,436 --> 00:01:32,916 Speaker 1: the medium picture. Let's talk about the changes that we 19 00:01:33,036 --> 00:01:36,316 Speaker 1: know have happened through mutation in the stars. CoV two 20 00:01:36,396 --> 00:01:41,396 Speaker 1: virus since the original version surfaced in Wuhan over the 21 00:01:41,396 --> 00:01:44,876 Speaker 1: course of the spring. Sure, so I think there's several 22 00:01:44,916 --> 00:01:48,156 Speaker 1: different changes that have been found in different patient populations. 23 00:01:48,756 --> 00:01:51,356 Speaker 1: Like many RNA viruses, I think one thing that is 24 00:01:51,396 --> 00:01:54,076 Speaker 1: important to know about stars CoV two is it doesn't 25 00:01:54,076 --> 00:01:57,516 Speaker 1: say the same it does mutate. There's elements of how 26 00:01:57,556 --> 00:02:03,116 Speaker 1: the virus replicates where errors can be made during RNA transcription, 27 00:02:03,756 --> 00:02:06,596 Speaker 1: and those errors can get packaged into new viruses and 28 00:02:06,636 --> 00:02:09,676 Speaker 1: then propagated. Most of the time, most of those errors 29 00:02:09,916 --> 00:02:13,356 Speaker 1: changes or variants or mutations probably have very little effect. 30 00:02:13,516 --> 00:02:16,716 Speaker 1: But occasionally you have changes that really do have some 31 00:02:16,916 --> 00:02:21,356 Speaker 1: functional impact on the virus. So one of the mutations, 32 00:02:21,356 --> 00:02:24,636 Speaker 1: a single point mutation that you've been working on and 33 00:02:24,676 --> 00:02:26,796 Speaker 1: that's gotten a fair amount of coverage, not as much, 34 00:02:26,836 --> 00:02:31,036 Speaker 1: perhaps as it ought, is a mutation at the six 35 00:02:31,156 --> 00:02:36,316 Speaker 1: hundred and fourteenth place in the genome of the starscoby 36 00:02:36,356 --> 00:02:39,156 Speaker 1: two virus. Tell us about that one and tell us 37 00:02:39,156 --> 00:02:42,516 Speaker 1: how it's moved through the population, right, Yeah, So the 38 00:02:42,636 --> 00:02:46,356 Speaker 1: mutation that's in the spike protein. So Spike is really 39 00:02:46,516 --> 00:02:50,316 Speaker 1: amongst the coronavirus proteins, probably the most famous proteins. So 40 00:02:50,396 --> 00:02:54,036 Speaker 1: Corona just means crown. And the reason that coronavirus has 41 00:02:54,076 --> 00:02:57,276 Speaker 1: this name with crown in it is because the individual 42 00:02:57,356 --> 00:03:01,436 Speaker 1: viral particles, the varions are decorated with the spike protein 43 00:03:01,476 --> 00:03:03,676 Speaker 1: that kind of sticks out and gives it this crown 44 00:03:03,756 --> 00:03:06,156 Speaker 1: like appearance. So, just out of curiosity, because I've been 45 00:03:06,156 --> 00:03:08,436 Speaker 1: wondering about this, It's called the spike protein because it 46 00:03:08,556 --> 00:03:11,556 Speaker 1: literally spikes up and a number of spikes make the crown. 47 00:03:11,756 --> 00:03:13,916 Speaker 1: It looks yeah, it looks like a spike. Yeah, it's 48 00:03:13,956 --> 00:03:17,556 Speaker 1: by far the most distinguishable feature of any pictures we've 49 00:03:17,596 --> 00:03:20,956 Speaker 1: seen at the virus. So the spike protein, the RNA 50 00:03:21,036 --> 00:03:25,076 Speaker 1: port encodes a protein and that protein has thousands of 51 00:03:25,076 --> 00:03:28,916 Speaker 1: amino acids in the six fourteenth position. Is this mutation 52 00:03:28,956 --> 00:03:32,156 Speaker 1: that we've started to focus on, and the reason that 53 00:03:32,356 --> 00:03:36,636 Speaker 1: we've started to think about this is totally accidental. My 54 00:03:36,716 --> 00:03:39,876 Speaker 1: lab works on crisper and gene editing. We are very 55 00:03:39,916 --> 00:03:44,516 Speaker 1: interested in using those tools to understand what are the 56 00:03:44,556 --> 00:03:47,476 Speaker 1: host genes, what are the human genes that are essential 57 00:03:47,516 --> 00:03:50,116 Speaker 1: for viral entry? And by figuring out which are the 58 00:03:50,196 --> 00:03:53,196 Speaker 1: essential genes for viral entry, we were hoping that we 59 00:03:53,236 --> 00:03:55,676 Speaker 1: could find ways to maybe block some of those genes 60 00:03:55,836 --> 00:03:58,556 Speaker 1: or suppress the activity of some of those genes, and 61 00:03:58,836 --> 00:04:01,956 Speaker 1: by doing that protect people from the virus entering. And 62 00:04:02,076 --> 00:04:04,276 Speaker 1: this was just one of these accidents and science. You 63 00:04:04,356 --> 00:04:07,116 Speaker 1: often hear about science that when you tell the story 64 00:04:07,116 --> 00:04:09,596 Speaker 1: of science that it's like super linear, but when you're 65 00:04:09,596 --> 00:04:12,596 Speaker 1: actually doing science, it actually is not so linear. There's 66 00:04:12,916 --> 00:04:16,676 Speaker 1: twists and turns and different paths, sometimes dead ends. And 67 00:04:16,716 --> 00:04:19,236 Speaker 1: so with the what we were trying to do in 68 00:04:19,276 --> 00:04:22,036 Speaker 1: the lab to understand what are the host proteins that 69 00:04:22,076 --> 00:04:26,276 Speaker 1: are required from viral entry, we started using a very 70 00:04:26,356 --> 00:04:28,356 Speaker 1: safe virus that we use in the lab, and all 71 00:04:28,396 --> 00:04:30,996 Speaker 1: we did was we attached to it the spike protein 72 00:04:31,076 --> 00:04:33,956 Speaker 1: on the outside of that virus from stars Kobe two, 73 00:04:34,316 --> 00:04:36,716 Speaker 1: because we know that the spike protein, because it spikes out, 74 00:04:36,996 --> 00:04:39,956 Speaker 1: is the first point of contact between human cells and 75 00:04:40,036 --> 00:04:44,396 Speaker 1: the coronavirus. And what we found actually was something pretty sad, 76 00:04:44,476 --> 00:04:47,316 Speaker 1: which was that we were really barely able to get 77 00:04:47,356 --> 00:04:50,396 Speaker 1: any cells infected with this virus that we had put 78 00:04:50,396 --> 00:04:54,156 Speaker 1: the spike protein on. And so at that time in April, 79 00:04:54,596 --> 00:04:57,316 Speaker 1: we had started to hear about this mutation that was 80 00:04:57,356 --> 00:05:00,276 Speaker 1: circulating the population and looked like it was increasing it 81 00:05:00,316 --> 00:05:04,916 Speaker 1: had come about sometime maybe in early February, likely in Europe, 82 00:05:05,236 --> 00:05:09,796 Speaker 1: based on the best viral population genomics work with sequences viruses, 83 00:05:10,236 --> 00:05:13,516 Speaker 1: and it looked very rapidly after it's kind of emerged 84 00:05:13,596 --> 00:05:16,756 Speaker 1: in early February that it started to take over kind 85 00:05:16,756 --> 00:05:19,236 Speaker 1: of the world populations. And that's true up to today 86 00:05:19,516 --> 00:05:22,276 Speaker 1: where it's greater than ninety five percent of the circulating 87 00:05:22,316 --> 00:05:27,516 Speaker 1: coronavirus today seems to be carrying the spike mutation, so 88 00:05:27,676 --> 00:05:30,476 Speaker 1: new in February, but now here in July, it really 89 00:05:30,476 --> 00:05:33,356 Speaker 1: seems to be quite dominant. So we thought, okay, let's 90 00:05:33,756 --> 00:05:35,876 Speaker 1: modify the spike protein that we have in the lab. 91 00:05:36,116 --> 00:05:39,916 Speaker 1: Let's just insert this little mutation that seems to be dominating. 92 00:05:39,916 --> 00:05:42,636 Speaker 1: This is back in April. We did this and let's 93 00:05:42,636 --> 00:05:44,236 Speaker 1: give it a try in the lab. And what we 94 00:05:44,356 --> 00:05:47,716 Speaker 1: found was indeed it solved our problem. Our problem is 95 00:05:47,756 --> 00:05:50,316 Speaker 1: we couldn't get the virus are kind of safe virus, 96 00:05:50,356 --> 00:05:52,956 Speaker 1: the pseudovirus that we have decorated with the spike protein, 97 00:05:52,956 --> 00:05:55,076 Speaker 1: we couldn't get it to enter our human cells. But 98 00:05:55,156 --> 00:05:58,516 Speaker 1: when we changed it to have this mutation, we were 99 00:05:58,556 --> 00:06:00,956 Speaker 1: able to see it enter much much better, five to 100 00:06:01,036 --> 00:06:04,196 Speaker 1: ten times better, and we thought, great, we've solved our 101 00:06:04,236 --> 00:06:06,476 Speaker 1: technical problem we had here in the lab. And then 102 00:06:06,516 --> 00:06:08,156 Speaker 1: a day or two later we started to think about 103 00:06:08,196 --> 00:06:11,516 Speaker 1: this and we said, wait a minute, this is pretty important. 104 00:06:11,556 --> 00:06:14,476 Speaker 1: Maybe instead of just running on from this technical problem, 105 00:06:14,516 --> 00:06:16,836 Speaker 1: we should maybe we should report this. Maybe we should 106 00:06:16,876 --> 00:06:19,756 Speaker 1: tell people like, look, this is a functional change in 107 00:06:19,796 --> 00:06:24,476 Speaker 1: how the virus infects humanselves. There are many fascinating things 108 00:06:24,476 --> 00:06:25,956 Speaker 1: in the story you just told, and I want to 109 00:06:25,956 --> 00:06:27,956 Speaker 1: just break them down a bit at a time. So 110 00:06:28,036 --> 00:06:32,436 Speaker 1: let's start with the kind of astonishing fact that in January, 111 00:06:32,516 --> 00:06:37,076 Speaker 1: when the first sequencing of the stars COVID two genome began, 112 00:06:38,316 --> 00:06:42,516 Speaker 1: almost none and maybe none of the viruses that were 113 00:06:42,796 --> 00:06:49,956 Speaker 1: sequenced had this mutation at place six fourteen. By March 114 00:06:50,076 --> 00:06:54,236 Speaker 1: the number was noticeable. By April, it was sufficiently noticeable 115 00:06:54,276 --> 00:06:57,076 Speaker 1: that your lab was thinking, let's try it out. By 116 00:06:57,116 --> 00:07:01,556 Speaker 1: May it was in seventy percent of reported cases, and 117 00:07:01,676 --> 00:07:04,676 Speaker 1: now it's at ninety five percent. So the first question 118 00:07:04,676 --> 00:07:08,116 Speaker 1: I want to ask is does this count as strong 119 00:07:08,236 --> 00:07:12,196 Speaker 1: evidence to you, as among other things such geneticist, that 120 00:07:12,276 --> 00:07:15,996 Speaker 1: there must be some adaptive feature of this change, or 121 00:07:16,076 --> 00:07:19,436 Speaker 1: is there some way that this could have happened without 122 00:07:19,476 --> 00:07:25,916 Speaker 1: this particular mutation helping the virus to replicate more successfully. Yeah, 123 00:07:25,916 --> 00:07:28,316 Speaker 1: so I think scientists are naturally very careful. So when 124 00:07:28,356 --> 00:07:31,836 Speaker 1: we got this first functional data in late April early May, 125 00:07:32,396 --> 00:07:34,676 Speaker 1: we weren't sure whether to believe it. And one of 126 00:07:34,716 --> 00:07:38,116 Speaker 1: the great things about science during the COVID era is 127 00:07:38,156 --> 00:07:40,316 Speaker 1: that there's been a lot of sharing and very rapid 128 00:07:40,316 --> 00:07:43,756 Speaker 1: sharing new results. And in May what we saw were 129 00:07:43,796 --> 00:07:47,476 Speaker 1: lots of different groups steadying the viral genomics and the 130 00:07:47,716 --> 00:07:51,796 Speaker 1: evolution of viral sampling through the world, and there was 131 00:07:51,876 --> 00:07:55,636 Speaker 1: really quite a dichotomy of views. There were folks who 132 00:07:55,636 --> 00:07:59,596 Speaker 1: thought this is clear evidence of selection going on for 133 00:07:59,636 --> 00:08:02,916 Speaker 1: the spike mutation, and then there was completely opposing views, 134 00:08:02,996 --> 00:08:05,916 Speaker 1: which is less so today, but was more then where 135 00:08:05,956 --> 00:08:08,196 Speaker 1: people thought, maybe it's something about a founder effect. You know, 136 00:08:08,596 --> 00:08:12,836 Speaker 1: if hasn't seen coronavirus before, but just the first introduction 137 00:08:12,836 --> 00:08:15,476 Speaker 1: of coronavirus into that country happens to be the one 138 00:08:15,476 --> 00:08:18,716 Speaker 1: that carries this variant, and then maybe the next introduction 139 00:08:18,756 --> 00:08:21,436 Speaker 1: into that country happens a week later. Well, you know, 140 00:08:21,516 --> 00:08:24,036 Speaker 1: exponential growth, So if you have a week of lead time, 141 00:08:24,396 --> 00:08:27,676 Speaker 1: that can really result in a lot more infections, especially 142 00:08:27,676 --> 00:08:30,916 Speaker 1: because we know asymptomatic people can infect others, you know, 143 00:08:30,996 --> 00:08:33,676 Speaker 1: I think sitting where we are right now, especially with 144 00:08:33,756 --> 00:08:36,116 Speaker 1: all the functional data that's come out, there's about five 145 00:08:36,236 --> 00:08:39,356 Speaker 1: or six different groups that have shown functional data is 146 00:08:39,356 --> 00:08:42,316 Speaker 1: similar to what we did here in the lab, I 147 00:08:42,356 --> 00:08:45,156 Speaker 1: think it's pretty clear that this version of the virus 148 00:08:45,196 --> 00:08:48,756 Speaker 1: is more transmissible. And it's not just laboratory experiments, but 149 00:08:49,156 --> 00:08:51,396 Speaker 1: something that we do in our preprint is we look 150 00:08:51,396 --> 00:08:55,076 Speaker 1: at data from Sheffield University in the UK and also 151 00:08:55,116 --> 00:08:58,116 Speaker 1: the University of Washington in Seattle. So these are two 152 00:08:58,196 --> 00:09:02,636 Speaker 1: totally different groups sampling different populations UK population and US population, 153 00:09:03,316 --> 00:09:07,876 Speaker 1: and they're basically looking at data from the qPCR test, 154 00:09:08,196 --> 00:09:10,996 Speaker 1: which is the test that involves the nasal swab and 155 00:09:11,196 --> 00:09:15,596 Speaker 1: qPCR just stands for quantitative polymerate chain reaction. It's actually 156 00:09:15,636 --> 00:09:19,236 Speaker 1: quite a standard lab technique and because it's got that 157 00:09:19,356 --> 00:09:22,436 Speaker 1: q and it quantitative, it can actually detect how many 158 00:09:22,516 --> 00:09:26,196 Speaker 1: viral copies they are in a particular nasal swab. And 159 00:09:26,476 --> 00:09:30,516 Speaker 1: what's super consistent over the two sites is the difference 160 00:09:30,676 --> 00:09:33,916 Speaker 1: between the people who have the D variant or the 161 00:09:33,956 --> 00:09:36,596 Speaker 1: G variant. These are the two different spike variants. The 162 00:09:36,676 --> 00:09:38,476 Speaker 1: D is the original one, the G is the new one. 163 00:09:38,756 --> 00:09:41,876 Speaker 1: And what both the sites find is that there's about 164 00:09:41,876 --> 00:09:46,876 Speaker 1: a threefold increase in viral RNA detected in the nasal 165 00:09:46,916 --> 00:09:50,916 Speaker 1: swabs of people with this new G variant, and that's 166 00:09:51,076 --> 00:09:55,756 Speaker 1: consistent between Sheffield and the group in Seattle. And so 167 00:09:56,116 --> 00:09:58,276 Speaker 1: to me that that suggests, I mean, we can't say 168 00:09:58,316 --> 00:10:01,036 Speaker 1: something about person to person transmission, but something that we 169 00:10:01,076 --> 00:10:03,956 Speaker 1: can definitely say with that data is that perhaps within 170 00:10:03,996 --> 00:10:06,276 Speaker 1: the body, and remember the body is kind of a 171 00:10:06,356 --> 00:10:09,596 Speaker 1: collection of cells, independent cells, where you know, you can 172 00:10:09,636 --> 00:10:11,396 Speaker 1: have cells that are infected in cells that are not 173 00:10:11,436 --> 00:10:14,476 Speaker 1: that are just fine. So perhaps within the body there's 174 00:10:14,596 --> 00:10:19,316 Speaker 1: greater infection, greater distribution of the virus amongst cells when 175 00:10:19,396 --> 00:10:22,676 Speaker 1: they are carrying the SPIKE variant. That sounds like it's 176 00:10:22,716 --> 00:10:25,636 Speaker 1: a very powerful reason to think that the spike variant 177 00:10:26,196 --> 00:10:29,396 Speaker 1: is superior with respect from the virus perspective, inferior from 178 00:10:29,396 --> 00:10:33,996 Speaker 1: our perspective, and that it is adaptive. Let's talk about 179 00:10:34,036 --> 00:10:38,196 Speaker 1: the question of why it seems to be better at 180 00:10:38,476 --> 00:10:43,076 Speaker 1: effectuating transmission. What is it about the crown that works 181 00:10:43,116 --> 00:10:46,516 Speaker 1: better from the virus's perspective at latching on to your 182 00:10:46,556 --> 00:10:50,276 Speaker 1: cells in the G variant compared to the D variant 183 00:10:50,316 --> 00:10:53,196 Speaker 1: with which the virus began. That's a great question. Yet, 184 00:10:53,276 --> 00:10:55,756 Speaker 1: so if it is more infectious, like we show in 185 00:10:55,796 --> 00:10:58,436 Speaker 1: a few different cell types, why is it what's you know, 186 00:10:58,476 --> 00:11:02,276 Speaker 1: how does this one amino acid change create such a 187 00:11:02,276 --> 00:11:05,836 Speaker 1: big difference in infectivity. That's a great question. We have 188 00:11:05,916 --> 00:11:08,356 Speaker 1: the exact same question. And so when you look at 189 00:11:08,396 --> 00:11:12,476 Speaker 1: the structure of the protein, there's different functional domains across 190 00:11:12,556 --> 00:11:16,316 Speaker 1: the length of the protein. Something that we noticed is 191 00:11:16,356 --> 00:11:19,596 Speaker 1: that kind of the closest functional domain to where this 192 00:11:19,756 --> 00:11:24,036 Speaker 1: mutation is the receptor binding domain. That's the thing that 193 00:11:24,196 --> 00:11:28,956 Speaker 1: actually makes contact with the human receptor for coronavirus, which 194 00:11:28,996 --> 00:11:32,076 Speaker 1: we think is in a receptor called ACE two. So 195 00:11:32,116 --> 00:11:34,636 Speaker 1: we said, okay, it's it's not in the receptor binding domain, 196 00:11:34,676 --> 00:11:36,636 Speaker 1: but it's very close to. It's the closest kind of 197 00:11:36,916 --> 00:11:39,356 Speaker 1: domain of the protein that has this well defined function. 198 00:11:39,596 --> 00:11:41,996 Speaker 1: So it must be that, right, It must be. You know, 199 00:11:42,036 --> 00:11:44,956 Speaker 1: something that this mutation is doing. It's increasing its affinity 200 00:11:45,356 --> 00:11:47,876 Speaker 1: for ACE two. It's just like you know, if you're 201 00:11:47,916 --> 00:11:51,356 Speaker 1: able to have kind of a tighter handshake, then that's 202 00:11:51,396 --> 00:11:53,916 Speaker 1: a going to increase infection versus somebody that just kind 203 00:11:53,956 --> 00:11:57,156 Speaker 1: of waves from a distance. Right, So we set about 204 00:11:57,196 --> 00:11:59,756 Speaker 1: actually with some collaborators here at NYU to really to 205 00:11:59,836 --> 00:12:02,516 Speaker 1: test this. And you know, as is often the case 206 00:12:02,516 --> 00:12:05,396 Speaker 1: in science, you know, you have some very strong hypothesis 207 00:12:05,396 --> 00:12:08,356 Speaker 1: about here's what the data should look like, and you know, 208 00:12:08,476 --> 00:12:12,836 Speaker 1: reality and tells you, hey, you're wrong, And that's exactly 209 00:12:12,836 --> 00:12:15,836 Speaker 1: what happened here. You know, our hypausis going into this 210 00:12:15,956 --> 00:12:20,156 Speaker 1: was it was likely stronger binding to the receptor ACE two. 211 00:12:20,396 --> 00:12:22,676 Speaker 1: We found that there was basically no difference between the 212 00:12:22,756 --> 00:12:26,636 Speaker 1: purified spike or the spike variant with ACE two binding. 213 00:12:26,996 --> 00:12:30,156 Speaker 1: So this was definitely not the right answer. It's fascinating 214 00:12:30,196 --> 00:12:32,796 Speaker 1: to hear about a hypothesis that doesn't pan out, and 215 00:12:32,836 --> 00:12:34,836 Speaker 1: it helps the rest of the world to trust science, 216 00:12:34,876 --> 00:12:36,556 Speaker 1: to realize that it's not that the scientists start with 217 00:12:36,556 --> 00:12:38,516 Speaker 1: the hypothesis then claim to prove it. Some things work, 218 00:12:38,596 --> 00:12:41,316 Speaker 1: some things don't. That's part of the process. So what 219 00:12:41,356 --> 00:12:42,996 Speaker 1: did you do next when you realize that the ACE 220 00:12:43,036 --> 00:12:45,836 Speaker 1: two wasn't the answer? You know, there are other aspects 221 00:12:45,956 --> 00:12:48,276 Speaker 1: of what spike you know, which, after all, is just 222 00:12:48,316 --> 00:12:53,156 Speaker 1: this little micromachine that helps the virus. It is not 223 00:12:53,236 --> 00:12:56,596 Speaker 1: there just to have the handshake with the ACE two receptor, 224 00:12:56,916 --> 00:12:59,276 Speaker 1: it performs a lot of other functions that are very 225 00:12:59,316 --> 00:13:02,236 Speaker 1: important for the virus to actually enter an inject it's 226 00:13:02,236 --> 00:13:05,836 Speaker 1: genetic material into the human cell. The handshake is really 227 00:13:05,876 --> 00:13:09,516 Speaker 1: just the first part. After that, the spike protein actually 228 00:13:09,516 --> 00:13:13,436 Speaker 1: sheds kind of a piece of it and unveils this 229 00:13:13,636 --> 00:13:16,996 Speaker 1: very hydrophobic piece, which is a way to say it's fatty. 230 00:13:17,076 --> 00:13:20,436 Speaker 1: It's made of lipids, and why is that important. Lipids 231 00:13:20,516 --> 00:13:23,956 Speaker 1: like to stick to other lipids, and the membranes of 232 00:13:23,956 --> 00:13:27,156 Speaker 1: our cells are all fats, and so basically by unveiling 233 00:13:27,156 --> 00:13:31,116 Speaker 1: this hydrophobic piece, it can stick into the plasma membrane, 234 00:13:31,116 --> 00:13:34,396 Speaker 1: the fatty lipid by layer of our cells, and that 235 00:13:34,476 --> 00:13:37,716 Speaker 1: way fuse basically make kind of this fusion between the 236 00:13:37,796 --> 00:13:41,676 Speaker 1: viral membrane, which is also a lipid and the cell membranye. 237 00:13:41,956 --> 00:13:46,116 Speaker 1: But this little dance, you know, is well orchestrated, and 238 00:13:46,156 --> 00:13:49,516 Speaker 1: so what we eventually did find is that one difference 239 00:13:49,556 --> 00:13:52,476 Speaker 1: we could see between the variant, the mutant form of 240 00:13:52,516 --> 00:13:55,436 Speaker 1: spike and the original form of spike is that this 241 00:13:55,556 --> 00:13:58,076 Speaker 1: kind of processing that enables the protein to go through 242 00:13:58,116 --> 00:14:01,876 Speaker 1: this dance that in the end unveils. This piece that 243 00:14:01,996 --> 00:14:05,596 Speaker 1: sticks into the host cell seems to be different between 244 00:14:06,036 --> 00:14:09,236 Speaker 1: the wild type spike and the variant spike that it 245 00:14:09,276 --> 00:14:14,716 Speaker 1: seems to be more resistant to certain kinds of premature unveiling, 246 00:14:14,836 --> 00:14:18,156 Speaker 1: let's say, of this fatty region, and that actually might 247 00:14:18,236 --> 00:14:20,876 Speaker 1: help it, because if you think about it, these viral proteins, 248 00:14:21,036 --> 00:14:23,876 Speaker 1: they don't just come out and start to infect cells. 249 00:14:23,916 --> 00:14:27,956 Speaker 1: They're produced inside a cell that's already infected. And if 250 00:14:27,996 --> 00:14:29,756 Speaker 1: the spike protein has to go through this kind of 251 00:14:29,796 --> 00:14:33,236 Speaker 1: complicated dance where it changes its confirmation a little bit, 252 00:14:33,636 --> 00:14:37,356 Speaker 1: if that happens too early, it might be an irreversible change. 253 00:14:37,356 --> 00:14:40,196 Speaker 1: It might not be able to become functional again. And 254 00:14:40,236 --> 00:14:42,956 Speaker 1: so if that happens, say in the cell that produces 255 00:14:42,996 --> 00:14:46,556 Speaker 1: the spike, then maybe that's too early. It really has 256 00:14:46,556 --> 00:14:50,036 Speaker 1: to happen after it sees ACE two, it does the 257 00:14:50,076 --> 00:14:52,476 Speaker 1: handshake with ACE two, and then it can kind of 258 00:14:52,556 --> 00:14:55,476 Speaker 1: undergo this conformational change to stick itself into the membrane. 259 00:14:55,716 --> 00:14:58,516 Speaker 1: And if that's happening too early, which is something that 260 00:14:58,516 --> 00:15:03,996 Speaker 1: our data suggests, that might actually lead to varians that 261 00:15:04,116 --> 00:15:06,836 Speaker 1: have spike on them. But the spike is not really functional, 262 00:15:07,276 --> 00:15:09,556 Speaker 1: and perhaps what the mutant spike does is it just 263 00:15:09,636 --> 00:15:14,076 Speaker 1: leads to more functional spike on the surface of the viruses. Now, well, 264 00:15:14,156 --> 00:15:18,956 Speaker 1: let's turn now to the bigger picture consequences of these 265 00:15:18,996 --> 00:15:21,836 Speaker 1: really remarkable findings that you and your co authors have 266 00:15:21,956 --> 00:15:27,516 Speaker 1: contributed to making. When the ordinary person hears that possibly 267 00:15:27,596 --> 00:15:30,996 Speaker 1: the new version of stars covy two is five to 268 00:15:31,076 --> 00:15:35,116 Speaker 1: ten times better at transmitting itself than the old version, 269 00:15:35,596 --> 00:15:40,356 Speaker 1: the natural thought is, oh boy, that's scary. So first question, 270 00:15:40,836 --> 00:15:43,076 Speaker 1: is there any reason to think that an initial mutation 271 00:15:43,116 --> 00:15:46,196 Speaker 1: of that sort would be an indicator that there could 272 00:15:46,236 --> 00:15:51,276 Speaker 1: be future mutations that might similarly improve the transmission rate, 273 00:15:51,356 --> 00:15:53,956 Speaker 1: that is, make it worse for us better for the virus. 274 00:15:54,636 --> 00:15:56,796 Speaker 1: Or is it the case that just because this was 275 00:15:56,836 --> 00:16:00,076 Speaker 1: a random point mutation, there's just no reason to think 276 00:16:00,196 --> 00:16:02,676 Speaker 1: that there would be some other random mutation that would 277 00:16:02,716 --> 00:16:05,276 Speaker 1: make this an even better virus at transmitting itself. Yeah, 278 00:16:05,316 --> 00:16:07,636 Speaker 1: that's a fantastic question. I mean the real answer is, 279 00:16:07,676 --> 00:16:10,876 Speaker 1: of course, like many things COVID related, we really don't know. 280 00:16:11,716 --> 00:16:14,796 Speaker 1: I think based on this rapid evolution that we've seen 281 00:16:14,916 --> 00:16:18,076 Speaker 1: just you know, with months of this virus circulating, I 282 00:16:18,116 --> 00:16:21,236 Speaker 1: think it certainly is not beyond a shadow of a 283 00:16:21,276 --> 00:16:24,276 Speaker 1: doubt kind of possibility that there might be another mutation, 284 00:16:24,356 --> 00:16:26,436 Speaker 1: maybe in the spike protein, maybe in some of the 285 00:16:26,476 --> 00:16:29,996 Speaker 1: other twenty five odd proteins that are in this virus 286 00:16:30,036 --> 00:16:35,276 Speaker 1: that either leads to increased transmissibility or you could lead 287 00:16:35,316 --> 00:16:39,076 Speaker 1: to hopefully not but some sort of increased lethality of 288 00:16:39,076 --> 00:16:42,596 Speaker 1: the virus. And that sounds very scary. I don't think 289 00:16:42,636 --> 00:16:44,396 Speaker 1: it has to be scary. I mean, one thing that 290 00:16:44,516 --> 00:16:47,596 Speaker 1: is very great to see right now, which we certainly 291 00:16:47,596 --> 00:16:50,836 Speaker 1: didn't have during the nineteen eighteen you know, flu pandemic, 292 00:16:51,316 --> 00:16:54,796 Speaker 1: is the use of rapidly deployable genomics thing. It's like 293 00:16:54,796 --> 00:16:57,036 Speaker 1: the work that I'm talking to you about today, where 294 00:16:57,076 --> 00:17:00,476 Speaker 1: we've been able to very quickly functionally characterize the impact 295 00:17:00,476 --> 00:17:03,876 Speaker 1: of some of these mutations. There's a large scientific community 296 00:17:03,876 --> 00:17:06,636 Speaker 1: of people working on this right now, and I do 297 00:17:06,716 --> 00:17:09,636 Speaker 1: think we can either react in real time to a 298 00:17:09,676 --> 00:17:12,236 Speaker 1: lot of these mutations at least understand what their functional 299 00:17:12,236 --> 00:17:15,356 Speaker 1: impact is, or but the kinds of cool DNA synthesis 300 00:17:15,356 --> 00:17:19,516 Speaker 1: technologies and RNA synthesis technologies that exist, we can actually 301 00:17:20,196 --> 00:17:23,436 Speaker 1: make mutations and test them in a massively parallel way 302 00:17:23,636 --> 00:17:25,916 Speaker 1: to kind of figure out, hey, what does this mutation do, 303 00:17:25,956 --> 00:17:29,236 Speaker 1: what does that mutation do, and really fully characterize what's 304 00:17:29,316 --> 00:17:31,876 Speaker 1: kind of a broad spectrum of what these proteins are 305 00:17:32,076 --> 00:17:33,956 Speaker 1: capable of. And that way maybe we can start to 306 00:17:33,996 --> 00:17:36,796 Speaker 1: predict and already think about, well, how do we improve 307 00:17:36,796 --> 00:17:40,116 Speaker 1: our vaccines, how do we improve our therapeutics. And this 308 00:17:40,156 --> 00:17:42,516 Speaker 1: has been done before with highly mutating viruses, so this 309 00:17:42,596 --> 00:17:44,996 Speaker 1: is not a crazy idea to suggest. Perhaps the most 310 00:17:45,116 --> 00:17:49,476 Speaker 1: mutagenic RNA virus that everyone knows well is HIV, the 311 00:17:49,556 --> 00:17:54,276 Speaker 1: virus that causes aids. That virus is tremendously mutagenic, and 312 00:17:54,476 --> 00:17:56,996 Speaker 1: what was found in the in the early and mid 313 00:17:57,116 --> 00:18:01,516 Speaker 1: nineties was that drugs that were seemingly effective against HIV 314 00:18:02,316 --> 00:18:04,436 Speaker 1: didn't really work in the long term, meaning that the 315 00:18:04,476 --> 00:18:08,396 Speaker 1: virus was able to evolve ways around the drugs. You know. 316 00:18:08,436 --> 00:18:10,356 Speaker 1: The real break through was in the late nineties the 317 00:18:10,356 --> 00:18:12,996 Speaker 1: development of what we now referred to as the cocktail, 318 00:18:13,356 --> 00:18:16,316 Speaker 1: which was a few different attacks on the virus, three 319 00:18:16,356 --> 00:18:19,556 Speaker 1: different drugs brought together, and it turns out that even 320 00:18:19,556 --> 00:18:22,636 Speaker 1: though the virus is very good at mutating that RNA virus, 321 00:18:23,396 --> 00:18:25,636 Speaker 1: the three drugs together proved to be kind of a 322 00:18:25,716 --> 00:18:29,076 Speaker 1: knockout punch and still to this date, twenty years twus 323 00:18:29,156 --> 00:18:32,516 Speaker 1: after the development of the HIV cocktail, it is still effective. 324 00:18:32,876 --> 00:18:35,436 Speaker 1: And so I think that provides a really nice roadmap, 325 00:18:35,716 --> 00:18:38,076 Speaker 1: you know, I think it should inspire us that we've 326 00:18:38,116 --> 00:18:41,236 Speaker 1: been able to lead with science. Let's talk then about 327 00:18:41,396 --> 00:18:45,596 Speaker 1: vaccines and reinfection and what the practical consequences will be 328 00:18:45,676 --> 00:18:50,076 Speaker 1: for those of this observed mutation. Let's start with reinfection. 329 00:18:50,196 --> 00:18:51,996 Speaker 1: If you're in China, this may matter much more if 330 00:18:51,996 --> 00:18:53,596 Speaker 1: you're in China than if you're in Europe or the 331 00:18:53,636 --> 00:18:57,276 Speaker 1: United States. But you got the early version and now 332 00:18:57,396 --> 00:19:00,556 Speaker 1: here comes the mutated version back around it comes back 333 00:19:00,676 --> 00:19:03,596 Speaker 1: via Europe or the United States. I know there was 334 00:19:03,636 --> 00:19:06,636 Speaker 1: concern initially in China that it might be that whatever 335 00:19:06,676 --> 00:19:08,796 Speaker 1: immunity people have, and I realize we don't fully know 336 00:19:08,796 --> 00:19:10,836 Speaker 1: how much community people have when they have been infected, 337 00:19:10,996 --> 00:19:14,076 Speaker 1: but whatever immunity people did have might no longer be 338 00:19:14,076 --> 00:19:16,836 Speaker 1: sufficient to hold off this new mutation of the virus. 339 00:19:17,516 --> 00:19:19,076 Speaker 1: Is there data on that yet or do you have 340 00:19:19,116 --> 00:19:22,156 Speaker 1: an intuitive sense absent the data, what is likely to 341 00:19:22,156 --> 00:19:24,036 Speaker 1: be the case with respect your reinfection of people who 342 00:19:24,116 --> 00:19:27,796 Speaker 1: got it the first time. Yeah, there's not data from US, 343 00:19:27,796 --> 00:19:30,196 Speaker 1: But there's data from several other groups that have now 344 00:19:30,196 --> 00:19:33,756 Speaker 1: started to look either at therapeutic antibodies that are being 345 00:19:33,756 --> 00:19:37,436 Speaker 1: tested or antibodies isolated from patients who have had a 346 00:19:37,476 --> 00:19:41,516 Speaker 1: COVID nineteen disease. Course, what they found is that many 347 00:19:41,556 --> 00:19:44,556 Speaker 1: of these antibodies targets, say, for instance, that ACE two 348 00:19:44,556 --> 00:19:47,276 Speaker 1: binding domain, which is the part of spike that's kind 349 00:19:47,276 --> 00:19:49,556 Speaker 1: of on the farthest away from the virus. It's on 350 00:19:49,596 --> 00:19:53,636 Speaker 1: the surface really of the virus. And so the good 351 00:19:53,636 --> 00:19:56,276 Speaker 1: news is again because the mutation doesn't really seem to 352 00:19:56,316 --> 00:20:00,316 Speaker 1: alter that receptor binding domain so much that most of 353 00:20:00,356 --> 00:20:03,836 Speaker 1: those antibodies still are very effective against the mutant spike. 354 00:20:03,916 --> 00:20:06,516 Speaker 1: So that'll suggests that this one mutation probably doesn't wipe 355 00:20:06,556 --> 00:20:08,876 Speaker 1: out that kind of immunity. And just so I understand, 356 00:20:08,916 --> 00:20:11,236 Speaker 1: is that because you did a great job of describing 357 00:20:11,716 --> 00:20:14,476 Speaker 1: the two part process of how the virus gets you. 358 00:20:15,036 --> 00:20:17,476 Speaker 1: First it shakes hands and then it's in the door, 359 00:20:17,516 --> 00:20:19,556 Speaker 1: and then it takes off its hat or something like 360 00:20:19,596 --> 00:20:23,596 Speaker 1: that or its mask and reveals the fatty lipid bind 361 00:20:23,596 --> 00:20:25,556 Speaker 1: to you and then you're stuck. Are you saying that 362 00:20:25,596 --> 00:20:29,076 Speaker 1: the reason that the antibodies are likely to work. Nevertheless, 363 00:20:29,756 --> 00:20:33,276 Speaker 1: is that they primarily target the initial handshake, and as 364 00:20:33,316 --> 00:20:37,476 Speaker 1: you showed in your initial lab efforts, there's not actually 365 00:20:37,476 --> 00:20:39,756 Speaker 1: a major change in the nature of the handshake derived 366 00:20:39,756 --> 00:20:41,916 Speaker 1: from this mutation. It's the later part. It's the taking 367 00:20:41,916 --> 00:20:44,716 Speaker 1: off the mask. Yeah, I think that's that's exactly the case. 368 00:20:45,196 --> 00:20:48,956 Speaker 1: Let's talk about vaccines in that case. Sure. So. Obviously, 369 00:20:49,516 --> 00:20:53,356 Speaker 1: some of the vaccines seek to replicate precisely the antibodies 370 00:20:53,596 --> 00:20:55,996 Speaker 1: that occur naturally, but there are also different kinds of 371 00:20:56,076 --> 00:20:59,036 Speaker 1: vaccines that are being experimented with. Now. There are these 372 00:20:59,156 --> 00:21:02,956 Speaker 1: so called trojan horse vaccines like the Oxford approach, there's 373 00:21:02,996 --> 00:21:06,756 Speaker 1: the RNA vaccine like the Maderna approach. What does the 374 00:21:06,956 --> 00:21:11,476 Speaker 1: evolution in the virus suggest with respect to those vaccines 375 00:21:11,476 --> 00:21:14,036 Speaker 1: that would those also be just as effective on the 376 00:21:14,036 --> 00:21:16,276 Speaker 1: earlier version as the late version or is it trickier 377 00:21:16,276 --> 00:21:19,316 Speaker 1: than that? Yeah, I think the implication for vaccines is 378 00:21:19,356 --> 00:21:23,076 Speaker 1: something that definitely merits some research. So there's about one 379 00:21:23,156 --> 00:21:26,956 Speaker 1: hundred and thirty or so vaccines under in various stages 380 00:21:26,956 --> 00:21:29,916 Speaker 1: of clinical development right now. In terms of how we 381 00:21:29,956 --> 00:21:33,036 Speaker 1: think about virus manufacturing, one thing that I think was 382 00:21:33,036 --> 00:21:36,356 Speaker 1: really impressive was how quickly some of these, especially the 383 00:21:36,436 --> 00:21:39,676 Speaker 1: new clique acid based vaccines, the DNA and the RNA vaccines. 384 00:21:39,836 --> 00:21:42,676 Speaker 1: How quickly we can go from sequencing the virus, you know, 385 00:21:42,716 --> 00:21:47,156 Speaker 1: the first coronavirus sequence that was released in January, to 386 00:21:47,316 --> 00:21:50,796 Speaker 1: having a vaccine ready to go, which was also in January, 387 00:21:50,796 --> 00:21:53,996 Speaker 1: as you mentioned with maderna. And so what might be 388 00:21:54,076 --> 00:21:57,876 Speaker 1: more important than being too worried about is this vaccine 389 00:21:57,876 --> 00:21:59,396 Speaker 1: out of date? Has it kept up with all the 390 00:21:59,396 --> 00:22:02,396 Speaker 1: newest spike mutations? Is to think, how can we develop 391 00:22:02,436 --> 00:22:05,876 Speaker 1: a process or a pipeline where we can quickly capture 392 00:22:06,076 --> 00:22:10,876 Speaker 1: population genomic data and I mean circulating virus data, sequence 393 00:22:10,916 --> 00:22:14,356 Speaker 1: the genomes quickly, and then quickly update the vaccines to 394 00:22:14,396 --> 00:22:17,476 Speaker 1: take into account new restraints and this kind of whatever 395 00:22:17,516 --> 00:22:19,596 Speaker 1: you want to call it, like tightly closed loop sort 396 00:22:19,636 --> 00:22:22,196 Speaker 1: of system or something like that. You know, that's really 397 00:22:22,196 --> 00:22:24,356 Speaker 1: that could be a powerful process that doesn't just protect 398 00:22:24,396 --> 00:22:28,196 Speaker 1: against this spike variant, but perhaps any future spike variants 399 00:22:28,196 --> 00:22:32,556 Speaker 1: we might be worried about. Are there any general lessons 400 00:22:32,636 --> 00:22:36,516 Speaker 1: from other viruses and the course of their mutations that 401 00:22:36,596 --> 00:22:39,516 Speaker 1: are relevant to us here? Yeah? I think you know, 402 00:22:39,956 --> 00:22:43,796 Speaker 1: HIV is a great example because enormous resources were dedicated 403 00:22:43,876 --> 00:22:48,356 Speaker 1: starting the late eighties onwards to fighting HIV, and there 404 00:22:48,516 --> 00:22:50,636 Speaker 1: it still took more than ten years to have a 405 00:22:50,676 --> 00:22:53,796 Speaker 1: truly effective therapy. So that's I mean, that's one thing 406 00:22:53,836 --> 00:22:55,956 Speaker 1: to say, but we did end up with an effective therapy. 407 00:22:56,556 --> 00:22:59,156 Speaker 1: Another reason why HIV, I think is a particularly good 408 00:22:59,196 --> 00:23:02,876 Speaker 1: example is because, as some folks might know, there has 409 00:23:02,916 --> 00:23:06,556 Speaker 1: been a long, decades long quest for a vaccine for HIV. 410 00:23:07,076 --> 00:23:11,196 Speaker 1: But today, even though there's any promising candidates kind of 411 00:23:11,236 --> 00:23:14,556 Speaker 1: better time now than ever before, we still don't have 412 00:23:14,636 --> 00:23:17,756 Speaker 1: an approved vaccine. This is a virus where we've known 413 00:23:17,756 --> 00:23:21,156 Speaker 1: about it since the eighties, So that's you know, to 414 00:23:21,236 --> 00:23:23,236 Speaker 1: me that that's kind of a scary thing, right that 415 00:23:23,476 --> 00:23:26,916 Speaker 1: we can expend tremendous effort and many years and it 416 00:23:27,036 --> 00:23:30,556 Speaker 1: still can be difficult to have vaccines. Now, that's one case. 417 00:23:30,596 --> 00:23:32,676 Speaker 1: There are other cases where vaccines have been developed in 418 00:23:32,796 --> 00:23:36,356 Speaker 1: much shorter periods of time, just a few years here. 419 00:23:36,436 --> 00:23:38,356 Speaker 1: I mean, we really do have the whole world focused 420 00:23:38,356 --> 00:23:40,476 Speaker 1: on this, so I'm you know, I'm all for these 421 00:23:40,876 --> 00:23:45,516 Speaker 1: optimistic estimates that we hear from you respected infectious disease 422 00:23:45,876 --> 00:23:49,156 Speaker 1: doctors like doctor Fauci and others of you know, six 423 00:23:49,196 --> 00:23:51,556 Speaker 1: months to a year, and I certainly hope that that's 424 00:23:51,876 --> 00:23:53,676 Speaker 1: the case. I mean, we all want our lives to 425 00:23:53,716 --> 00:23:57,036 Speaker 1: go back to normal, but I think it's important with 426 00:23:57,076 --> 00:23:59,556 Speaker 1: the historical perspective, we have to say that, you know, 427 00:23:59,636 --> 00:24:05,556 Speaker 1: developing safe, effective therapies, safe effective vaccines, it's not easy, 428 00:24:05,636 --> 00:24:08,396 Speaker 1: and I'm only hopeful that there's so much effort going 429 00:24:08,396 --> 00:24:13,916 Speaker 1: into it right now that it will greatly accelerate those efforts. Well, 430 00:24:13,956 --> 00:24:15,556 Speaker 1: thank you for the work that you're doing and for 431 00:24:15,636 --> 00:24:18,396 Speaker 1: explaining why we should be a concern about the irritation 432 00:24:18,476 --> 00:24:21,156 Speaker 1: and why we should also recognize that it's not necessarily 433 00:24:21,236 --> 00:24:23,196 Speaker 1: the end of the world. Thanks for the opportunity to 434 00:24:23,276 --> 00:24:32,356 Speaker 1: be here. To me, it's a rather remarkable fact that 435 00:24:32,436 --> 00:24:35,516 Speaker 1: we can see in real time how the stars Cove 436 00:24:35,676 --> 00:24:39,556 Speaker 1: two virus has been evolving the fact that the variation 437 00:24:39,676 --> 00:24:43,116 Speaker 1: at place six fourteen was not visible almost at all 438 00:24:43,116 --> 00:24:47,436 Speaker 1: in January, in February, was noticeable in March, was really 439 00:24:47,476 --> 00:24:50,396 Speaker 1: noticeable in April, was at seventy percent in May, and 440 00:24:50,396 --> 00:24:53,876 Speaker 1: it is now at ninety five percent provides significant reason 441 00:24:53,916 --> 00:24:57,196 Speaker 1: to think that it's actually doing something to help the 442 00:24:57,276 --> 00:25:01,276 Speaker 1: virus transmit itself. Nevland his group have suggested that by 443 00:25:01,276 --> 00:25:05,076 Speaker 1: improving the spike protein, the new version maybe five to 444 00:25:05,196 --> 00:25:08,596 Speaker 1: ten times better at transmitting the virus than the version 445 00:25:08,596 --> 00:25:12,556 Speaker 1: that existed before, and they've made significant progress in trying 446 00:25:12,556 --> 00:25:16,676 Speaker 1: to figure out where and why that is happening. The 447 00:25:16,716 --> 00:25:20,316 Speaker 1: consequences of this development are significant, and they're also subtle. 448 00:25:20,916 --> 00:25:23,516 Speaker 1: On the one hand, Nevil says we shouldn't assume that 449 00:25:23,636 --> 00:25:27,276 Speaker 1: just because there's been one mutation that made the disease 450 00:25:27,356 --> 00:25:30,196 Speaker 1: easier to spread, that there will be others. There might be, 451 00:25:30,316 --> 00:25:32,636 Speaker 1: there might not be. On the other hand, he says, 452 00:25:33,196 --> 00:25:36,916 Speaker 1: sometimes the reality is that we do get rapid evolution 453 00:25:36,996 --> 00:25:39,556 Speaker 1: in a virus in a way that makes it difficult 454 00:25:39,716 --> 00:25:43,716 Speaker 1: to contain the virus with a vaccine. The upshot is 455 00:25:43,756 --> 00:25:46,196 Speaker 1: that we need to watch the development of this virus quickly. 456 00:25:46,716 --> 00:25:49,516 Speaker 1: The good news is we can now do that. The 457 00:25:49,676 --> 00:25:54,156 Speaker 1: speed and cheapness of sequencing genomes now makes it possible 458 00:25:54,236 --> 00:25:57,476 Speaker 1: in almost real time, to track what's happening in a virus. 459 00:25:57,956 --> 00:26:00,036 Speaker 1: Never before in the history of pandemics has it been 460 00:26:00,076 --> 00:26:03,156 Speaker 1: possible to keep as close an eye on the genetic 461 00:26:03,276 --> 00:26:07,156 Speaker 1: variation and evolutionary pressures that are taking place within a 462 00:26:07,276 --> 00:26:10,836 Speaker 1: disease as it spreads. The worrisome bit is that no 463 00:26:10,916 --> 00:26:13,356 Speaker 1: matter how much science we have, and no matter how 464 00:26:13,396 --> 00:26:17,156 Speaker 1: sophisticated we are at understanding what's happening, we don't necessarily 465 00:26:17,476 --> 00:26:20,996 Speaker 1: have all the tools to solve the problem. We're going 466 00:26:21,036 --> 00:26:23,916 Speaker 1: to continue to watch this story. If the virus evolves more, 467 00:26:24,116 --> 00:26:25,836 Speaker 1: you can be sure that we will talk about it 468 00:26:26,036 --> 00:26:39,556 Speaker 1: right here on deep background. We'll be right back. Welcome 469 00:26:39,596 --> 00:26:43,436 Speaker 1: to this week's playback. Hi, this is Anne with the 470 00:26:43,516 --> 00:26:47,276 Speaker 1: Warranty Department. Our records show that your vehicle warranty has 471 00:26:47,356 --> 00:26:50,796 Speaker 1: expired or it's about to expire. That is a sound 472 00:26:50,836 --> 00:26:53,036 Speaker 1: that no one likes to hear, the sound of a 473 00:26:53,116 --> 00:26:57,356 Speaker 1: robocall reaching you on your mobile phone. The Supreme Court 474 00:26:57,356 --> 00:26:59,916 Speaker 1: weighed in on the robocall issued this past week in 475 00:26:59,916 --> 00:27:03,876 Speaker 1: a case where Justice Brett Kavanaugh wrote, Americans passionately disagree 476 00:27:03,876 --> 00:27:06,716 Speaker 1: about many things, but they are largely united in their 477 00:27:06,716 --> 00:27:10,876 Speaker 1: disdain for robocalls. The Supreme Court struck down a twenty 478 00:27:11,116 --> 00:27:14,156 Speaker 1: fifteen law that made an exception from the general ban 479 00:27:14,516 --> 00:27:18,036 Speaker 1: on robocalls to your cell phone for collection of debts 480 00:27:18,196 --> 00:27:21,356 Speaker 1: that are backed by the government, which would include, for example, 481 00:27:21,476 --> 00:27:25,396 Speaker 1: your student loans. On the surface, nothing could sound more straightforward. 482 00:27:25,636 --> 00:27:28,556 Speaker 1: How great that the Supreme Court, in the exercise of 483 00:27:28,556 --> 00:27:31,996 Speaker 1: its infinite wisdom, has protected us further from robocalls. But 484 00:27:32,236 --> 00:27:35,076 Speaker 1: that's not really what was going on. What was actually 485 00:27:35,076 --> 00:27:37,876 Speaker 1: happening at the Supreme Court was an intense fight between 486 00:27:37,916 --> 00:27:41,556 Speaker 1: the courts conservatives and the courts liberals about what standard 487 00:27:41,596 --> 00:27:45,436 Speaker 1: they should use to analyze questions about the freedom of speech. 488 00:27:45,996 --> 00:27:50,276 Speaker 1: The conservatives want to use the highest standard called strict scrutiny, 489 00:27:50,316 --> 00:27:53,676 Speaker 1: where the Court almost always strikes down a law that 490 00:27:53,836 --> 00:27:56,796 Speaker 1: is seen to implicate free speech, and the liberals are 491 00:27:56,796 --> 00:27:59,476 Speaker 1: concerned that the conservatives are going to use free speech 492 00:27:59,516 --> 00:28:04,556 Speaker 1: doctrine to overturn progressive regulation on things like food and 493 00:28:04,636 --> 00:28:09,356 Speaker 1: drug regulation, workplace safety, or the regulation of the al 494 00:28:09,476 --> 00:28:13,596 Speaker 1: of securities on the stock market. To understand what was 495 00:28:13,636 --> 00:28:15,996 Speaker 1: really going on beneath the service in the robotcall case, 496 00:28:16,236 --> 00:28:20,756 Speaker 1: you need thirty seconds on the constitutional law of free speech. Historically, 497 00:28:20,756 --> 00:28:23,996 Speaker 1: the Supreme Court applied its toughest level of scrutiny to 498 00:28:24,196 --> 00:28:27,956 Speaker 1: laws that seemed to treat different statements differently from each 499 00:28:27,956 --> 00:28:32,556 Speaker 1: other based on the ideas expressed in them. Sometimes the 500 00:28:32,596 --> 00:28:36,156 Speaker 1: Court called that viewpoint discrimination. That is a law that 501 00:28:36,196 --> 00:28:39,116 Speaker 1: treats two people differently based on their viewpoint. Perhaps one 502 00:28:39,156 --> 00:28:41,116 Speaker 1: is a Republican and one is a Democrat, and the 503 00:28:41,196 --> 00:28:44,996 Speaker 1: law treats them differently under those circumstances. The Court always said, 504 00:28:45,156 --> 00:28:47,676 Speaker 1: we're going to look at this law very carefully, and 505 00:28:47,676 --> 00:28:50,996 Speaker 1: we're almost certainly going to strike it down. That all 506 00:28:51,076 --> 00:28:53,156 Speaker 1: changed a few years ago in a case called Read 507 00:28:53,196 --> 00:28:55,956 Speaker 1: against the Town of Gilbert, when Justice Clarence Thomas wrote 508 00:28:55,956 --> 00:28:59,716 Speaker 1: an opinion saying that strict scrutinies should apply whenever a 509 00:28:59,796 --> 00:29:04,756 Speaker 1: law differentiated between different kinds of expression based on their content, 510 00:29:05,636 --> 00:29:08,316 Speaker 1: not based on the ideas they expressed, but just based 511 00:29:08,316 --> 00:29:12,196 Speaker 1: on their content at all. In the robocall case, the 512 00:29:12,236 --> 00:29:16,236 Speaker 1: Supreme Court relied on exactly that idea. The Court held 513 00:29:16,316 --> 00:29:18,636 Speaker 1: that what was wrong with the government giving an exception 514 00:29:18,716 --> 00:29:22,556 Speaker 1: to the robocall ban for government backed debt collection is 515 00:29:22,556 --> 00:29:24,836 Speaker 1: that to do so, it had to ask what is 516 00:29:24,876 --> 00:29:27,956 Speaker 1: the robocall about? The mine? You're asking what the robocall 517 00:29:28,036 --> 00:29:30,436 Speaker 1: is about, said the Court. You're looking at the content 518 00:29:30,756 --> 00:29:34,316 Speaker 1: of expression, and any law, the Court said, that looks 519 00:29:34,316 --> 00:29:37,836 Speaker 1: at the content of expression automatically gets stick scrutiny and 520 00:29:37,876 --> 00:29:42,676 Speaker 1: gets struck down. Writing in dissent, Justice Stephen Bryer forcefully 521 00:29:42,756 --> 00:29:46,276 Speaker 1: expressed his serious worry that applying that kind of content 522 00:29:46,316 --> 00:29:50,436 Speaker 1: based analysis to government regulations about speech could end up 523 00:29:50,476 --> 00:29:54,716 Speaker 1: invalidating the laws that tell companies you must disclose what's 524 00:29:54,756 --> 00:29:57,996 Speaker 1: in your product, you must tell the truth about your 525 00:29:58,036 --> 00:30:02,716 Speaker 1: security's offerings. You must provide workplace warnings to workers so 526 00:30:02,756 --> 00:30:04,756 Speaker 1: that they know what the dangers are that are facing 527 00:30:04,796 --> 00:30:08,516 Speaker 1: them in all of those instances. Brier pointed out, the 528 00:30:08,676 --> 00:30:12,396 Speaker 1: rule in question regulates content. It says that certain things 529 00:30:12,516 --> 00:30:15,196 Speaker 1: must be said and other things must not be said. 530 00:30:15,836 --> 00:30:17,956 Speaker 1: Bryer is worried that the Conservatives are going to use 531 00:30:17,996 --> 00:30:22,236 Speaker 1: this very idea that all content based rules deserve strict scrutiny, 532 00:30:22,316 --> 00:30:24,916 Speaker 1: to chip away and maybe go all in and strike 533 00:30:24,996 --> 00:30:29,676 Speaker 1: down huge swaths of government regulation. All of this may 534 00:30:29,716 --> 00:30:32,876 Speaker 1: sound to you pretty far from robo calls, but you 535 00:30:32,916 --> 00:30:35,596 Speaker 1: know what, that's often how things happen at the Supreme Court. 536 00:30:36,116 --> 00:30:38,436 Speaker 1: On the surface, a decision that seems to touch on 537 00:30:38,476 --> 00:30:42,316 Speaker 1: something relatively minor, the irritation of robocalls, and it seems 538 00:30:42,356 --> 00:30:45,196 Speaker 1: to give you a good result. Meanwhile, beneath the surface, 539 00:30:45,476 --> 00:30:49,276 Speaker 1: a long run battle between conservatives and liberals for the 540 00:30:49,276 --> 00:30:52,836 Speaker 1: future of our country and how government is allowed to 541 00:30:52,836 --> 00:30:56,756 Speaker 1: operate under the constraints of our constitution. They're going to 542 00:30:56,756 --> 00:30:59,196 Speaker 1: be several more Supreme Court decisions in the next week 543 00:30:59,276 --> 00:31:02,076 Speaker 1: or two, which are likely to be high profile and significant. 544 00:31:02,516 --> 00:31:06,276 Speaker 1: Will come back to those in a future playback. Until 545 00:31:06,356 --> 00:31:12,556 Speaker 1: next time, Be careful, be safe, Be well. Deep background 546 00:31:12,596 --> 00:31:15,436 Speaker 1: is brought to you by Pushkin Industries. Our producer is 547 00:31:15,516 --> 00:31:19,596 Speaker 1: Lydia Jane Cott, with mastering by Jason Gambrell and Martin Gonzalez. 548 00:31:19,956 --> 00:31:23,436 Speaker 1: Our showrunner is Sophie mckibbon. Our theme music is composed 549 00:31:23,436 --> 00:31:27,356 Speaker 1: by Luis GERA special thanks to the Pushkin Brass, Malcolm Gladwell, 550 00:31:27,476 --> 00:31:31,476 Speaker 1: Jacob Weisberg, and Mia Lobel. I'm Noah Feldman. I also 551 00:31:31,516 --> 00:31:34,196 Speaker 1: write a regular column for Bloomberg Opinion, which you can 552 00:31:34,196 --> 00:31:38,796 Speaker 1: find at Bloomberg dot com slash Feldman. To discover Bloomberg's 553 00:31:38,796 --> 00:31:43,396 Speaker 1: original slate of podcasts, wrote Bloomberg dot Com slash Podcasts 554 00:31:44,116 --> 00:31:46,396 Speaker 1: and one last thing. I just wrote a book called 555 00:31:46,516 --> 00:31:49,476 Speaker 1: The Arab Winter, a Tragedy. I would be delighted if 556 00:31:49,476 --> 00:31:52,076 Speaker 1: you checked it out. If you liked what you heard today, 557 00:31:52,436 --> 00:31:55,436 Speaker 1: please write a review, or tell a friend. You can 558 00:31:55,436 --> 00:31:57,356 Speaker 1: always let me know what you think. On Twitter, my 559 00:31:57,516 --> 00:32:10,076 Speaker 1: handle is Noah R. Feldman. This is deep background