WEBVTT Kind: captions Language: en 00:00:00.320 --> 00:00:04.720 So I'm John Yin. I'm a professor of Chemical  and Biological Engineering at the Wisconsin-   00:00:05.280 --> 00:00:10.480 at the University of Wisconsin-Madison. I'm  also with the Wisconsin Institute for Discovery   00:00:10.480 --> 00:00:16.000 and I have the honor of sharing some of our  work. This is actually ongoing work for the   00:00:16.000 --> 00:00:22.960 last 15 years that we've pivoted to bring over  to coronavirus. It's about turning the dial on   00:00:22.960 --> 00:00:29.840 coronavirus infections. We have two awards.  One of these involves turning up the dial   00:00:30.560 --> 00:00:35.840 for infections and one involves turning down  the dial. I'll try to explain what that means. 00:00:35.840 --> 00:00:40.880 I didn't do any of the work. The people who did  the work are all here past and present many of   00:00:40.880 --> 00:00:49.600 them now in industry or academia. I think two  of my co-workers Nan Jiang and Huicheng Shi are   00:00:51.040 --> 00:00:56.320 on the call with us today. So these  are the people who do the actual work. 00:00:57.440 --> 00:01:02.480 To help you understand where I'm coming from, I  have to tell you how we quantify infectious virus.   00:01:02.480 --> 00:01:08.240 So there's a standard way to quantify infectious  virus. So we have a virus stock solution here that   00:01:08.240 --> 00:01:13.760 we'd like to figure out how much virus is actually  in there? Usually there are millions or tens of   00:01:13.760 --> 00:01:18.560 millions of particles we would like to figure out  how many particles and count them. And the way we   00:01:18.560 --> 00:01:24.400 do that is we do a series of dilutions known  dilutions it's kind of watering down the drink   00:01:24.400 --> 00:01:28.640 until we get a few tubes that just  have countable numbers of particles.   00:01:29.200 --> 00:01:35.360 Those tubes- known volumes from those high  dilution tubes are put on mono layers of cells   00:01:35.920 --> 00:01:43.440 shown here in the red and overlayered with agar  gel, and they are allowed to reproduce. The   00:01:43.440 --> 00:01:50.320 viruses spread locally and kill the cells. Then we  stain the cells blue and wherever this virus has   00:01:50.320 --> 00:01:55.760 killed the cells there's a little hole there. The  hole is called a plaque, a region of dead cells   00:01:55.760 --> 00:02:02.480 caused by a single virus which we can now see with  the naked eye. By counting those holes or plaques,   00:02:02.480 --> 00:02:07.680 we can deduce knowing what volumes we had and  how much we watered down the original stock,   00:02:07.680 --> 00:02:13.760 we can figure out how many particles we had in  the original stock. So this is a key tool that we   00:02:13.760 --> 00:02:22.800 use to quantify infection and that we will use to  characterize how we turn down or turn up viruses. 00:02:23.440 --> 00:02:28.240 So the first thing we did here was to try  to explore ways that we could get more   00:02:28.240 --> 00:02:34.160 signal out of this kind of assay and what  we did was instead of overlaying with agar   00:02:35.040 --> 00:02:39.120 so here I show on the no flow  cases these are sort of standard   00:02:39.120 --> 00:02:44.400 plates that you might see petri dishes where they  have plaques and you would count those plaques.   00:02:45.360 --> 00:02:51.440 We carried out the infection in the presence of  liquid rather than agar overlay and we found that   00:02:51.440 --> 00:02:57.760 if you don't touch the plates spontaneous flows  arise- outward radial flows and create comet like   00:02:59.600 --> 00:03:04.480 morphologies of these plaques. So there's  flow that's automatically happening in there   00:03:04.480 --> 00:03:09.840 that's helping to spread the virus. And for plates  that have the same level of virus, we see a lot   00:03:09.840 --> 00:03:16.080 brighter signal so we have a much higher signal  to noise. We've done some theoretical models-   00:03:16.080 --> 00:03:23.200 computational models of this process and in  essence we said this might be a useful tool   00:03:23.200 --> 00:03:31.840 to characterize drugs. So what happens if you add  drugs against the virus to this kind of signal? 00:03:32.400 --> 00:03:38.880 Here in the top left here we have a sample  that has no drug in it and then we have   00:03:38.880 --> 00:03:43.920 five other samples that have different degrees  increasing amounts of drug and what you find is   00:03:43.920 --> 00:03:49.280 the fireworks dim as we go to higher level  of drugs. That means we have less and less   00:03:49.280 --> 00:03:55.600 virus spreading and less infection. We can  quantify that here and on the plot you see a   00:03:55.600 --> 00:04:02.240 comet enhanced- flow enhanced comet assay versus  the plaque reduction assay, which is currently   00:04:02.240 --> 00:04:09.440 the gold standard. So our assay is about 20-fold  more sensitive and faster to run than the existing   00:04:10.400 --> 00:04:15.920 plaque assay for drugs. So this is something  that we patented five years ago and with the   00:04:15.920 --> 00:04:19.360 NIH [National Institute of Health] funding- sorry  NSF [National Science Foundation] funding. We are   00:04:19.360 --> 00:04:28.160 now going on to adapt this assay to test drugs  against coronavirus. That was turning up the   00:04:28.160 --> 00:04:33.440 infection and facilitating the spread. We're  also interested in turning down the infection. 00:04:33.440 --> 00:04:39.600 How do you dial down virus infections? It may be  happening in nature. Here are three scenarios.   00:04:39.600 --> 00:04:44.640 The first one is the virus infects the cell  and it makes a bunch of virus particles.   00:04:46.080 --> 00:04:52.160 Typically for coronavirus, it makes about  100 coronavirus particles per cell. Among   00:04:52.160 --> 00:04:56.640 those virus particles, there may be some  defective ones. So the defective ones-   00:04:56.640 --> 00:05:01.200 this orange as I've shown in the orange here, if  it gets into a cell it does not make anything.   00:05:01.920 --> 00:05:07.920 It's not able to grow. However the defective  particle retains some aspects of the virus. The   00:05:07.920 --> 00:05:14.400 ability to use the virus replication machinery.  So if both an intact virus shown here in blue   00:05:14.400 --> 00:05:20.480 and the defective virus shown in orange get into  the same cell as a co-infection then you can   00:05:20.480 --> 00:05:27.120 have the defective virus reproducing stealing  resources from the growth of the normal virus.   00:05:27.680 --> 00:05:33.920 So these defective particles are called defective  interfering particles because they interfere with   00:05:33.920 --> 00:05:41.920 the normal growth of the virus. They've long been  known since the 1950s and in the 1970s I've taken   00:05:41.920 --> 00:05:48.640 this abstract from this review article- very  prominent review article in 1970. So 50 years ago,   00:05:48.640 --> 00:05:58.160 people were speculating that these might play some  role in viral diseases. So building on that, we   00:05:58.160 --> 00:06:03.280 thought it would be interesting to try to quantify  interference. How do you quantify interference? 00:06:03.840 --> 00:06:09.200 Well we set up something like the plaque assay  and the details here are not so important   00:06:09.200 --> 00:06:15.680 other than we had to make some dilutions  and instead of providing viruses- instead   00:06:15.680 --> 00:06:20.320 of providing live cell to viruses the way  we do for the plaque assay, we have to   00:06:20.320 --> 00:06:26.800 provide infected cells to defective particles.  That's what the defective particles prey on. 00:06:26.800 --> 00:06:36.720 So if I go to the next slide we can see the data  such that as we go to higher levels of these   00:06:36.720 --> 00:06:42.240 defective interfering particles going from left  to right on the x-axis here the virus production   00:06:42.240 --> 00:06:48.800 drops and then comes back up. If we look at the  production of the dips of the defective particles-   00:06:48.800 --> 00:06:53.840 how they depend on their own input levels,  we have this other kind of behavior that's   00:06:53.840 --> 00:07:00.400 increasing up to a point and then dropping  off very sharply. So the key point here   00:07:00.400 --> 00:07:07.520 is that dips exhibit a complex behavior with  respect to their ability to inhibit virus   00:07:08.080 --> 00:07:14.960 growth and also with respect to their ability  to influence their own replication. So to better   00:07:14.960 --> 00:07:21.920 understand this, we have studied a different kind  of virus a rabies-like virus and we've engineered   00:07:22.640 --> 00:07:30.720 two kinds of virus. One that is carrying a red  fluorescent protein, so when it infects cells,   00:07:30.720 --> 00:07:36.720 it turns the cells red, and one that's a defective  particle that carries a green fluorescent protein. 00:07:37.280 --> 00:07:41.920 So the scenario is here. There are two  different viruses. One is the virus   00:07:41.920 --> 00:07:48.560 red and one is the defective virus green. And what  we do is infect a single cell with both of those   00:07:48.560 --> 00:07:52.720 and then watch how they spread over  several generations. So in this dish,   00:07:53.360 --> 00:07:58.880 you can see at three hours post infection you see  no fluorescent protein and if you watch the top   00:07:58.880 --> 00:08:04.320 right hand corner you'll see the time ticking  off as we take images at various times. This   00:08:04.320 --> 00:08:11.840 is 300 microns or about a third of a millimeter.  Okay so watch the timer and watch the patterns.   00:08:14.240 --> 00:08:21.520 This is our pandemic in a petri dish. So millions  of cells are being infected from that single one   00:08:21.520 --> 00:08:27.760 virus particles and defective particles released  from that cell are spreading over this time period   00:08:27.760 --> 00:08:35.920 of less than a day or so. So we have used this  to study in depth what's happening at the single   00:08:35.920 --> 00:08:40.960 cell level and these sorts of patterns then  you'll see are quite complex. It's really   00:08:40.960 --> 00:08:47.120 a predator prey behavior in the sense that the  defective virus is preying on the infected cells. 00:08:49.760 --> 00:08:56.000 If we look at the extent of normal virus spread  in the absence of any defective particle,   00:08:56.000 --> 00:08:59.440 we can see the red expanding. In the  presence of defective particle alone,   00:08:59.440 --> 00:09:03.760 there's no infection, but in the presence  of both we get a co-infection spread   00:09:03.760 --> 00:09:08.320 that is inhibited relative to the normal  virus. So we wonder could defective   00:09:08.320 --> 00:09:15.680 coronavirus be used to treat COVID-19 in  a way to inhibit or slow down the spread? 00:09:16.800 --> 00:09:23.120 So today I've told you about two cases where we  dial up infection spread and this is good for   00:09:23.120 --> 00:09:28.880 antiviral testing because it gives us a more  sensitive assay and I've also talked about   00:09:28.880 --> 00:09:33.600 dialing down infection. There are natural  particles that arise from these infections   00:09:33.600 --> 00:09:38.800 that can inhibit the growth and spread of  viruses. We hope to investigate this for   00:09:39.520 --> 00:09:45.360 reducing the severity of COVID-1 COVID-19  I'm sorry that should be 19. If you'd like   00:09:45.360 --> 00:09:50.560 to learn more, I'd be happy to respond to  chat questions or email. Thanks very much.