[00:00:00.07] Hi Hello good morning and welcome to [00:00:02.22] [00:00:02.22] Nana fans 5 in our series It's a pleasure to have you here online and. [00:00:07.22] [00:00:08.23] Today is our 2nd there we are in our Nana France written a series in May And [00:00:15.02] [00:00:15.02] as you know we are focusing this month. [00:00:17.20] [00:00:18.23] In line with what's all going on around the world with the pandemic we're focusing [00:00:23.19] [00:00:23.19] on on technology in infectious diseases diagnostics and therapeutics [00:00:29.06] [00:00:29.06] is our carping draw we have the pleasure of having Dr Philip San Angelo he's [00:00:34.20] [00:00:34.20] one of the professors had the family going in the department He'll be speaking on [00:00:40.02] [00:00:40.02] are in their best drugs for treating influenza and sarce called 2 and [00:00:45.14] [00:00:45.14] then you know we'll have this month every Wednesday said [00:00:50.03] [00:00:50.03] Levon is our baby narced and next week we do have to give Kwang. [00:00:55.01] [00:00:56.17] He will talk on point of care diagnostics we are d.n.a. [00:01:00.23] [00:01:00.23] based I so their level of occasion and paper does trips and if you are not signed [00:01:05.11] [00:01:05.11] up go ahead and sign up and you will get the Remind the email birds [00:01:11.01] [00:01:11.01] the meeting id a day before the event and you know I want to share. [00:01:17.01] [00:01:18.09] A special reflection program at the Institute for electronics and [00:01:22.16] [00:01:22.16] the technology you know I am in charge I am as The whole host for [00:01:28.03] [00:01:28.03] the now defense I've been a series of the past 10 years and you know this [00:01:33.15] [00:01:33.15] program called Southeastern nanotechnology infrastructure card are in charge scenic. [00:01:38.05] [00:01:39.13] Is one of the 16 n.s.f. funded sites under a program [00:01:44.12] [00:01:44.12] called National than a technology coordinated infrastructure. [00:01:47.12] [00:01:48.15] You know I go this is a regional research resource that means it's a resource for [00:01:53.08] [00:01:53.08] not only Georgia Tech and our partners joint school of nanoscience and [00:01:57.19] [00:01:57.19] malinger nearing Intel and users but it's also a great resource for [00:02:03.04] [00:02:03.04] extremely users who will have the opportunity to cull go to one of these [00:02:07.10] [00:02:07.10] sites and use the facility for their own research and so in short what [00:02:12.08] [00:02:12.08] a scenic scene it is a partnership of 2 centers or asked to detect Institute for [00:02:17.12] [00:02:17.12] electronics and then a technology and our partners join school of nanoscience and [00:02:21.18] [00:02:21.18] the engineering which is the academic collaboration but. [00:02:25.02] [00:02:26.20] Green for All and not going to 19 of our city. [00:02:30.17] [00:02:30.17] So we have this large resource picture you see there is a $10000.00 square Ford [00:02:37.10] [00:02:37.10] semiconductor or inorganic cleaned role of class 1000 at the Marcus now building [00:02:43.23] [00:02:43.23] have the Georgia Tech campus though we do have a mind ours and [00:02:49.02] [00:02:49.02] our partner's a resource this estimated to be value $200000000.00 that's available [00:02:54.21] [00:02:54.21] for off campus uses both from academia as well as industries industries right from [00:02:59.17] [00:02:59.17] the start of companies to Fortune $500.00 industries will have the opportunity [00:03:04.09] [00:03:04.09] to access these resources for a very very nominal fee so [00:03:09.03] [00:03:09.03] what do we have as we do have tool sets that are located to the needs of [00:03:14.07] [00:03:14.07] our down and bottoms of micro now a fabrication research you know we do [00:03:19.05] [00:03:19.05] have a combine clean resources to the tune of $36500.00 square foot [00:03:24.17] [00:03:24.17] plane loads of available for use and access and then we do have to search for [00:03:29.16] [00:03:29.16] advance characterization of research materials characterization in that we [00:03:35.16] [00:03:35.16] do have advanced microscopic spectroscope in service and House sets then we have [00:03:41.09] [00:03:41.09] tools related to an article chemistry medical testing we do have a independent [00:03:47.02] [00:03:47.02] separate bio clean drug that bio users will have the opportunity to access and [00:03:52.14] [00:03:52.14] then there's a separate computation of morning and place of my commission in [00:03:55.23] [00:03:55.23] the labs so ultimately what do we do you know scenic provides easy [00:04:01.03] [00:04:01.03] user access to a wide variety of comprehensive micro Nana fabrication and [00:04:05.19] [00:04:05.19] characterization sets and process capabilities. [00:04:09.05] [00:04:10.11] The best thing is we don't let the users alone handle these tools it's after [00:04:14.18] [00:04:14.18] training asked after members process staff members technical staff members come along [00:04:19.14] [00:04:19.14] side with the users and support and help towards the success of their own research [00:04:24.10] [00:04:24.10] we also have a large program related to [00:04:27.19] [00:04:27.19] national educational outreach activities very number of school schedule 12 course. [00:04:32.13] [00:04:33.19] 2 year colleges will have the opportunity to make use of these capabilities and [00:04:38.22] [00:04:38.22] resources so how one would be able to access these stores that a number [00:04:43.20] [00:04:43.20] of ways are extremely use us will have the opportunity to access these tools that's [00:04:48.11] [00:04:48.11] one is on site where extra users will have the opportunity to go to one of these [00:04:53.10] [00:04:53.10] sites and then get trained on a piece of do they desire and then use that those [00:04:57.08] [00:04:57.08] themselves another one as remote jobs where users will have the opportunity [00:05:02.18] [00:05:02.18] to send the samples and then ask half members all will do the job for you and [00:05:07.17] [00:05:07.17] ship your samples after processing and the results as well and then we do [00:05:12.06] [00:05:12.06] have a number of training models like shark courses shark courses and. [00:05:16.06] [00:05:17.09] Micro and that of application we also have short courses and so [00:05:20.15] [00:05:20.15] after the graphic from microfluidics where our users Xstrata users will have [00:05:25.14] [00:05:25.14] the opportunity to sign up for these courses and learn about these techniques [00:05:29.22] [00:05:29.22] there's also a special program called scenic catalyst cactus program that offers [00:05:35.09] [00:05:35.09] a free access to the 1st lady you know for a user has a new idea to try it out and [00:05:41.19] [00:05:41.19] this is this is up late only to the extra academic users then you know [00:05:47.12] [00:05:47.12] if we're able to do it if the work the yes I just ing and proposing is feasible and [00:05:52.01] [00:05:52.01] we have enough bandwidth for our staff members to handle it then we'll go ahead [00:05:56.18] [00:05:56.18] and approve that proposal and then we'll do the job under that and [00:06:01.19] [00:06:01.19] as I said staff expertise a sort of best things that we could offer and [00:06:05.20] [00:06:05.20] the more information is available at these sites scenic dogmatic dock. [00:06:10.12] [00:06:10.12] You might want to check those that site as well with that said I have a very [00:06:15.12] [00:06:15.12] hard to introduce Prince Philip San Angelo to give [00:06:19.16] [00:06:19.16] a presentation on our In a best drugs for treating influenza hence our skull to. [00:06:25.05] [00:06:26.11] Dr sand Angelos currently a professor in the Wallace quarter department [00:06:31.17] [00:06:31.17] of biomedical engineering at Georgia Tech he graduated from Polytechnic University [00:06:37.19] [00:06:37.19] in 1901 with a b.s. in aerospace engineering in [00:06:41.21] [00:06:41.21] 1980 he obtained this ph d. in engineering from the University of California. [00:06:46.16] [00:06:47.21] And after that he had to post doctoral appointments one at Sandia National Labs [00:06:52.10] [00:06:52.10] and one in Georgia Tech and [00:06:55.06] [00:06:55.06] subsequently started as an assistant professor in 2007 at Georgia Tech and [00:07:00.20] [00:07:00.20] Dr Sandman's laconically the searchers in the area of their element of imaging and [00:07:06.21] [00:07:06.21] detection technology for the Study of our and their regulation and [00:07:10.12] [00:07:10.12] the pathogenesis of our in their whiteness and it's a pleasure to welcome. [00:07:14.07] [00:07:15.13] Professor San Angelo and let's. [00:07:17.20] [00:07:18.23] You know here it is dark and thank you for joining us. [00:07:22.13] [00:07:23.15] I'm really happy to be here that I actually am on campus today I'm actually [00:07:28.11] [00:07:28.11] in the b.b. he but I'm going to talk a little bit about our work on [00:07:33.05] [00:07:33.05] Arnie based drugs for treating flu and for SARS Kovi 2 and [00:07:38.05] [00:07:38.05] I thought I'd mention this maybe previous speakers have talked about this so [00:07:41.23] [00:07:41.23] when you talk about the virus itself its name is SARS Kovi 2 and [00:07:47.03] [00:07:47.03] the reason for that is that there was the original SARS virus in the early 2000 and [00:07:50.23] [00:07:50.23] it was SARS Kovi so and so because this virus is so similar in [00:07:56.02] [00:07:56.02] terms of its genetics it was just called the 2nd Kovi 2 it's it's very similar and [00:08:02.12] [00:08:02.12] so that's its official name now obviously when people refer to the disease they [00:08:08.01] [00:08:08.01] usually talk about coded 19 so just wanted to distinguish between when you talk about [00:08:12.04] [00:08:12.04] the disease because it's covert 19 you're talking about the virus the particular [00:08:16.07] [00:08:16.07] agent itself we usually it's now referred to as stars Coby 2 was also called and [00:08:21.02] [00:08:21.02] c.o.v. $2100.00 novel coronavirus but that was before they had had [00:08:26.08] [00:08:26.08] performed a sufficient amount of sequencing to understand whether or [00:08:30.14] [00:08:30.14] not it was very similar to the original SARS and it is similar not the same but [00:08:34.09] [00:08:34.09] it's similar Ok so when I talk about drugs my lab work specifically on synthetic [00:08:40.20] [00:08:40.20] m.r.s.a. based drugs we're working on both profile axis and therapeutics both for [00:08:45.07] [00:08:45.07] flu and now for Koby too and we really had the main questions that we wanted to ask [00:08:50.07] [00:08:50.07] was it could we make drugs that would allow the body to express preventatives or [00:08:55.05] [00:08:55.05] therapeutics exactly where we need them and could we even alter native gene [00:08:59.14] [00:08:59.14] expression to prevent infection or clear an infection and [00:09:03.11] [00:09:03.11] in our case I'm going to talk more about having the body express proteins that that [00:09:08.06] [00:09:08.06] essentially are therapeutic and that's where I'll focus it but we are working on [00:09:12.01] [00:09:12.01] ways of modulating host gene expression in order to prevent infections also and [00:09:16.23] [00:09:16.23] that's that work's being done with folks from Duke and from u.c.s.f. [00:09:21.02] [00:09:21.02] and a whole a whole gaggle of. [00:09:23.05] [00:09:23.05] Folks have actually involved in that part but our drug molecule choice is are not [00:09:28.02] [00:09:28.02] rival nucleic acids and we've been working on m.r.s.a. based therapeutics now for [00:09:32.21] [00:09:32.21] a few years and specifically my work is focused on developing these drugs for [00:09:37.19] [00:09:37.19] mucosal sites and I'll explain in a minute why that is but we we started out in [00:09:42.09] [00:09:42.09] the long actually we've been working on developing the ability to express and [00:09:47.07] [00:09:47.07] a body in the long and actually keep them in the long end and [00:09:50.03] [00:09:50.03] if by some chance in the near future we start to see some really good [00:09:54.13] [00:09:54.13] neutralizing antibodies against Kovi 2 we will probably work towards [00:09:59.17] [00:09:59.17] expressing those antibodies in the long as a way to prevent infection but [00:10:04.17] [00:10:04.17] then we also we realize that mucosal sites are are very important infectious disease [00:10:09.14] [00:10:09.14] so we actually recently published a paper on expressing and a body's against HIV [00:10:14.09] [00:10:14.09] in the female reproductive tract and so those are just some things to look at but [00:10:17.12] [00:10:17.12] we've gotten we're very interested in the coastal sites and [00:10:20.17] [00:10:20.17] delivering nucleic acid specifically m.r.s.a. and both preventing and [00:10:25.01] [00:10:25.01] treating infections and so now through our DARPA program so [00:10:29.18] [00:10:29.18] my work is funded this work is funded through the DARPA prepare program and [00:10:35.08] [00:10:35.08] we've been working specifically on developing has 13 based treatments of both [00:10:39.15] [00:10:39.15] flu and Coby 2 now and there's a bio archive paper that was posted just [00:10:44.21] [00:10:44.21] about a week or so ago Blanchard at all that you guys can find we're also working [00:10:49.17] [00:10:49.17] on Gene modulators and I think hopefully the story on Gene modulators you'll see in [00:10:54.00] [00:10:54.00] the very near future and I think it'll also be very exciting at least I hope so [00:10:58.15] [00:10:58.15] so so the next question you might ask is again why synthetic messenger r.n.a. [00:11:02.14] [00:11:02.14] And what do we even mean by that So [00:11:04.23] [00:11:04.23] I mean exactly what I'm saying we really make messenger r.n.a. [00:11:09.18] [00:11:09.18] in the lab and it's completely self free aids essentially made in a tube so [00:11:14.02] [00:11:14.02] to speak it looks just like a native messenger r.n.a. and [00:11:18.09] [00:11:18.09] that it's kept it has a 5 prime cap it has a 5 prime untranslated region that's in. [00:11:23.05] [00:11:23.05] Wharton for recruiting factors for translation actually to the m.r.s.a. [00:11:28.07] [00:11:28.07] it has an open reading frame so and we've expressed a wide variety of proteins [00:11:33.18] [00:11:33.18] everything from ion channels to transcription [00:11:38.16] [00:11:38.16] factors to antibodies I mean a wide variety of different types of proteins and [00:11:43.14] [00:11:43.14] then there's the 3 prime untranslated region that's important for [00:11:46.19] [00:11:46.19] regulating m r n a stability mostly does have some influence also [00:11:51.19] [00:11:51.19] on translational capability so how well the Artes translated in the poly tail [00:11:56.10] [00:11:56.10] which is very important for stability and so we make the r.n.a. from d.n.a. [00:12:01.14] [00:12:01.14] in the lab there's there's an art to it to some degree we've spent a lot of time [00:12:06.23] [00:12:06.23] optimizing the process so that we have very efficient capping that r.m.r. [00:12:13.04] [00:12:13.04] Naser translated well and that that that they that they are effective [00:12:18.13] [00:12:18.13] in potent and we've done comparisons with m r n a s from companies and have shown [00:12:23.16] [00:12:23.16] that we are as potent as they are if not better in some respects sometimes and so [00:12:28.12] [00:12:28.12] again why would we use an m.r.i. neighbors to say d.n.a. is a gene therapy or [00:12:33.03] [00:12:33.03] viral vectors and really the reason for using synthetic m.r.s.a. has a lot [00:12:37.05] [00:12:37.05] to do with safety One reason is that in general we get transient [00:12:41.19] [00:12:41.19] expressions of the expression doesn't last forever it's usually [00:12:46.04] [00:12:46.04] you can see it probably up to about a week of protein production but [00:12:50.20] [00:12:50.20] I would say it's only a week if you need months or years of production this is [00:12:55.12] [00:12:55.12] the wrong technique I would say that it's not appropriate for every problem but [00:12:59.13] [00:12:59.13] I think it has its niches where it can be very useful you'll see in the literature [00:13:04.09] [00:13:04.09] now there are a lot of companies making on m.r.s.a. based vaccines I think and [00:13:08.09] [00:13:08.09] I'm not going to talk about those as a whole that's a whole other discussion but [00:13:13.04] [00:13:13.04] but m.r.s.a. [00:13:13.21] [00:13:13.21] is a good platform for Vaccines and I think you'll see more information coming [00:13:18.13] [00:13:18.13] out from the journal by on tech services and others on our in a base vaccines. [00:13:23.08] [00:13:23.08] But again for gene therapy certainly it's transience that's helpful [00:13:26.18] [00:13:26.18] it's non integrating it in theory it is possible they could integrate but [00:13:30.12] [00:13:30.12] that possibilities extremely minute so I would say in general we [00:13:34.15] [00:13:34.15] don't consider them we see no evidence ever of integration and [00:13:37.22] [00:13:37.22] they have very low immunity necessity so are they itself can be imminent Janick so [00:13:42.20] [00:13:42.20] it's through basically optimization of the sequence through the corporation [00:13:47.15] [00:13:47.15] of modified nucleotides natural modified nucleotides you can really I don't to call [00:13:51.22] [00:13:51.22] them in a silent but you can really decrease the energy in a city of them so [00:13:56.11] [00:13:56.11] mucosal interfaces again why would we want to use r.n.a. [00:13:59.06] [00:13:59.06] if you cause interfaces because they're super important I mean the digestive [00:14:03.10] [00:14:03.10] system the restaurant system in the reproductive system are really the 1st [00:14:06.20] [00:14:06.20] lines of defense against a lot of pathogens SARS Kovi to being one h i b [00:14:13.04] [00:14:13.04] h s b 2 influenza r.s.v. lots of different pathogens [00:14:18.06] [00:14:18.06] rotavirus in the digestive tract and actually Kovi to has a certainly [00:14:23.09] [00:14:23.09] can looks like it can replicate in the day justice system because. [00:14:26.19] [00:14:27.23] Those cells express ace 2 in particular the the receptor [00:14:33.08] [00:14:33.08] that the virus uses So all of these surfaces are important and so [00:14:37.01] [00:14:37.01] we think we've been concentrating our work on a lot of our work on these [00:14:41.10] [00:14:41.10] mucosal interfaces because exactly for this reason and so I'm going to talk now [00:14:45.23] [00:14:45.23] about how we would modulating influenza and SARS Kovi to r.n.a. and [00:14:49.17] [00:14:49.17] directly in the long how would we use that as a treatment So let's think about 1st [00:14:54.17] [00:14:54.17] current anti-viral approaches why would we want to use the approach where we sing why [00:14:58.12] [00:14:58.12] not use typical ones well there's a lot of different drug classes and right now folks [00:15:03.18] [00:15:03.18] are really working very hard to find old drugs and repurpose them for this [00:15:09.03] [00:15:09.03] virus everything from entry inhibitors protease inhibitors Absolutely I think [00:15:13.16] [00:15:13.16] there's a large effort at Emory going on now to look for protease inhibitors. [00:15:16.17] [00:15:18.02] Nucleus side analogues also a very very important and [00:15:21.00] [00:15:21.00] that's these are the kinds of drugs that folk. [00:15:23.08] [00:15:23.08] Currently used and it is possible they will be useful for [00:15:26.20] [00:15:26.20] Kofi too we don't know that yet I would say in great detail but [00:15:30.02] [00:15:30.02] it does look like that in the you know there are certainly some indications that [00:15:34.07] [00:15:34.07] nuclear site analogs will be helpful but we'll see what happens but [00:15:38.06] [00:15:38.06] I think that this this is the kinds of drugs that people have been developing so [00:15:42.16] [00:15:42.16] what's the problem with them well one is resistance and [00:15:46.03] [00:15:46.03] folks haven't talked about that yet but resistance is an issue but [00:15:48.23] [00:15:48.23] I would say one issue is keeping up with replication dynamics and [00:15:52.07] [00:15:52.07] the other is solubility pharmacodynamic pharmacokinetics I mean especially in [00:15:57.03] [00:15:57.03] the long one problem with small molecules in the long is that if you especially if [00:16:00.13] [00:16:00.13] you deliver them by inhalation they will wash out along pretty quickly and [00:16:04.09] [00:16:04.09] even if you deliver them systemically you know it's going to be you're going to have [00:16:08.16] [00:16:08.16] to deliver a fair amount of drug a lot of it's still going to end up in the liver [00:16:11.08] [00:16:11.08] and kidneys and so you know not as much of a Gets The long as you'd like so [00:16:15.17] [00:16:15.17] this is one of the challenges I think [00:16:17.00] [00:16:17.00] especially for lung delivery but in general there can sometimes be issues [00:16:21.22] [00:16:21.22] like solubility in pharmacokinetics with these drugs delivery still an issue I [00:16:26.06] [00:16:26.06] think the one drug one bugging issue is is prevalent though I think you're starting [00:16:30.12] [00:16:30.12] to see more drugs that hit I would say multiple multiple viruses and [00:16:36.05] [00:16:36.05] I think that will be important short half life can be an issue [00:16:39.22] [00:16:39.22] high doses again as I mentioned earlier and sometimes side effects so [00:16:42.21] [00:16:42.21] this is this is sort of the state of affairs in current anti-virals So [00:16:47.03] [00:16:47.03] another class of anti-virals that we're nucleic acid base [00:16:50.00] [00:16:50.00] that people look at as I say r.n.a. and in general they haven't been that successful [00:16:54.07] [00:16:54.07] but I think there's a couple of reasons why that is I mean one is [00:16:57.23] [00:16:57.23] as I own a dozen amplify or sustain function and that can be difficult against [00:17:02.02] [00:17:02.02] the replicating pathogen so keeping pace with the virus can be an issue [00:17:06.19] [00:17:06.19] I think the livery outside the liver as of yet has been inefficient though I think [00:17:11.00] [00:17:11.00] some of that will be changing there's lots of companies working on [00:17:14.07] [00:17:14.07] in addition to my lab even working on with with other clubbers like [00:17:18.04] [00:17:18.04] James dolman and [00:17:18.23] [00:17:18.23] others working on ways to more efficiently deliver nucleic acids in the long. [00:17:23.08] [00:17:23.08] So some of this might be worked out for s.s.i. [00:17:25.17] [00:17:25.17] but I still it's still unclear whether it can keep pace with viral replication So [00:17:29.14] [00:17:29.14] what's our approach so it took me a long time to get to where exactly are we doing [00:17:34.05] [00:17:34.05] so we're working on what we call r.n.a. powered and we mean what we mean by that [00:17:38.10] [00:17:38.10] is that the drugs are made of r.n.a. we're working on activated all r.n.a. says so [00:17:42.23] [00:17:42.23] specifically focusing on Class 2 type 6 crisper casts molecules proteins. [00:17:49.13] [00:17:49.13] So these are in aces have some very interesting qualities one is that [00:17:53.18] [00:17:53.18] the are an Ace needs to be activated and they are an ace I would say the when [00:17:58.17] [00:17:58.17] it's in a functional fashion when it's functional it's the are an ace itself cast [00:18:03.10] [00:18:03.10] 13 plus a crisper r.n.a. which is a small stretch of nucleic acids that then forms [00:18:08.09] [00:18:08.09] an r n p Robyn nuclear protein complex with the with the cast 13 so [00:18:13.19] [00:18:13.19] you have cast 13 and you have the crisper r.n.a. we deliver them. [00:18:17.00] [00:18:18.02] Together but as an m.r.a. [00:18:19.23] [00:18:19.23] plus a crisper on a so this 2 Arnie's that we deliver simultaneously once the m.r. [00:18:25.02] [00:18:25.02] in a is translated into protein that protein complexes with a crisp r.n.a. [00:18:28.18] [00:18:28.18] and then you have a complex that is ready to go fight viruses and what they [00:18:33.02] [00:18:33.02] basically do is that once that crisper r.n.a. binds again it has to be attached [00:18:37.12] [00:18:37.12] to the caster teen once it binds to a target sequence it activates cast 13 and [00:18:42.04] [00:18:42.04] once it's active What does it do it chews up r.n.a. and so far we've seen that it's [00:18:46.15] [00:18:46.15] been very rapid so far effective again against a couple again both influenza and [00:18:52.10] [00:18:52.10] Coby 2 it appears to be very specific and I'm not going talk too much about that but [00:18:56.11] [00:18:56.11] it looks like it's it's very specific it persists so [00:19:00.18] [00:19:00.18] we've gone after 96 hours post infection and seen knocked down from it so [00:19:05.06] [00:19:05.06] that's nice to see and it's easy to tackle genetic to shift a drift because you [00:19:09.21] [00:19:09.21] just change the Gaidar name and you can multiplex guide our names and I'll talk [00:19:13.03] [00:19:13.03] about that so in general we're trying to we really wanted to come up with a tool [00:19:16.19] [00:19:16.19] box then sort of having to do develop a new drug every time a new pathogen new [00:19:21.09] [00:19:21.09] virus shows up instead we just swap out the guides and if we can deliver them [00:19:25.17] [00:19:25.17] to the effects to the right cell types we should be able to the knock down that [00:19:29.19] [00:19:29.19] virus and so in some sense this approach shows that because we were working on flu [00:19:34.23] [00:19:34.23] and then we had to switch over to Kovi to very quickly and we were able to do that [00:19:39.02] [00:19:39.02] really very fast I mean we were able to design new guides very quickly have [00:19:43.21] [00:19:43.21] this guide synthesized and [00:19:45.08] [00:19:45.08] then really was just hooking up with the right folks in the scientific. [00:19:49.06] [00:19:49.06] To work with these viruses like Jeff Hogan at u.g.a. [00:19:51.21] [00:19:51.21] and we were able to then test this out so I would say it's really about [00:19:56.11] [00:19:56.11] that fact getting access to the virus is probably our biggest limitation but [00:20:00.12] [00:20:00.12] let me explain how this works so again we made a number of differences that m. [00:20:04.03] [00:20:04.03] R.N.A.'s the ones I'm going to talk about today are our forecasts 13 a specifically [00:20:09.16] [00:20:09.16] to one particular variant the l b u variant even though we have others in [00:20:13.11] [00:20:13.11] the lab we have almost all of the current cast 30 people have discovered we have [00:20:18.13] [00:20:18.13] in the lab now and we make them within without a nuclear localization sequence so [00:20:22.21] [00:20:22.21] they can attack r.n.a. in the nucleus or in the side as a whole now for [00:20:26.07] [00:20:26.07] flu that's important because flu can be in both places [00:20:29.17] [00:20:29.17] it replicates mostly in the nucleus but you can find new click acids in both [00:20:33.22] [00:20:33.22] both compartments with Koby too we only use the cytoplasmic version because that's [00:20:37.22] [00:20:37.22] the only one we care about because that's where the virus replicates so [00:20:40.22] [00:20:40.22] the 1st thing we always do is we make our r.n.a. we then in vitro translated into [00:20:45.04] [00:20:45.04] protein we can complex it with the guide r.n.a. [00:20:47.20] [00:20:47.20] So the crisper r.n.a. as and then we tested in vitro literally in a to b. c. [00:20:51.20] [00:20:51.20] doesn't show up r.n.a. and that's the that is the 1st thing that we do and [00:20:55.17] [00:20:55.17] you can see that just we run both we look at r.n.a. degradation both by gelatin for [00:21:01.04] [00:21:01.04] rhesus and then through a fluorescent assaye and then we go into cells next and [00:21:04.20] [00:21:04.20] again we look at we can look at a post infection and we also look at it. [00:21:08.14] [00:21:09.16] When we compare that to an transected cells that are infected we also look at [00:21:14.14] [00:21:14.14] a number of different controls which I'll talk about 2 and then we've gone in vivo [00:21:19.10] [00:21:19.10] and I'll talk about in vivo last so some of the 1st things you do is when you do [00:21:23.13] [00:21:23.13] this in a 2 is you can do this fluorescent assays that's what you see a and b. [00:21:27.20] [00:21:27.20] and c. and you can see that very rapidly almost about as fast as [00:21:32.14] [00:21:32.14] as you can monitor the reaction that if you add a crisper r.n.a. [00:21:37.03] [00:21:37.03] to a caster teen and there's a target there that's what the t.r. [00:21:40.07] [00:21:40.07] is you get that red red line is the is the mean for us and so [00:21:44.06] [00:21:44.06] it's very fast I mean the kinetics are very quick in a tube and it'll start to. [00:21:49.06] [00:21:49.06] Up are in a very quickly and you can see Vin from the gel that there's a smear [00:21:53.13] [00:21:53.13] basically once the r.n.a. is being degraded and so that's what we we would [00:21:57.15] [00:21:57.15] hope to see we hope that these work well if this is just nasty to make sure that [00:22:01.12] [00:22:01.12] we have designed our m r n a appropriately and then choose a farthing and [00:22:05.16] [00:22:05.16] then the next thing we did is we actually started looking at and dodginess genes so [00:22:10.04] [00:22:10.04] and this was just a test to me there are other folks at mit and at u.c. [00:22:15.14] [00:22:15.14] Berkeley that have worked that basically discovered cast 13 and [00:22:20.05] [00:22:20.05] have tested it with some and dodginess genes and we actually looked at some of [00:22:24.03] [00:22:24.03] their guides and so what I'm showing you is data from Gene p.p.i. b. and [00:22:29.03] [00:22:29.03] we see roughly around 50 to 60 percent knockdown actually of of p.p. [00:22:34.03] [00:22:34.03] i.v. which is similar to what other folks have seen except they don't usually use [00:22:37.13] [00:22:37.13] m.r.s.a. And so that's one thing that's quite different and [00:22:40.09] [00:22:40.09] actually interesting enough it does look like our side of plasma Persian is working [00:22:43.18] [00:22:43.18] quite well and then we look at K.-Rock switches and [00:22:46.09] [00:22:46.09] on to Gene and we were able to see actually using the nuclear version [00:22:50.15] [00:22:50.15] again about 60 percent knockdown and this is a 24 hours and [00:22:54.13] [00:22:54.13] so we ran a number of controls and in general if you look at both of these [00:22:58.13] [00:22:58.13] genes the controls aren't too bad I mean we run a non targeted control so a guide [00:23:03.00] [00:23:03.00] that doesn't target anything in the genome we have a dead version of Castor team and [00:23:07.00] [00:23:07.00] it has no into Vatican action and then we even combine the guide alone with g.f.p. [00:23:11.11] [00:23:11.11] encoding m. r.n.a. and in general if you [00:23:14.01] [00:23:14.01] look at these are not bad I mean most of the controls look pretty good [00:23:17.03] [00:23:17.03] I mean they're pretty flat so we also read another gene so we looked we looked at [00:23:22.01] [00:23:22.01] the guy that had been published against the x e r 4 well interesting Lee enough we [00:23:26.02] [00:23:26.02] read all of our controls that you just compare it to the n.p.c. [00:23:29.08] [00:23:29.08] Our it looks great way into the non-target control it knocks the heck out of this [00:23:34.05] [00:23:34.05] gene the problem is when we looked at the Dead version or [00:23:37.03] [00:23:37.03] we looked at even the g.f.p. with it it still [00:23:39.19] [00:23:39.19] was knocking it down significantly so [00:23:41.12] [00:23:41.12] this was something that we found that was interesting that you know we really need [00:23:44.23] [00:23:44.23] to look carefully at our control because we want to make sure that. [00:23:49.06] [00:23:49.06] They are that Cassadine is actually meeting this not and it's not some other [00:23:53.09] [00:23:53.09] process that we don't understand this is this is something we've spent some time on [00:23:56.23] [00:23:56.23] and in all of our guides that we're using for anything all these guys are in a is [00:24:01.04] [00:24:01.04] a crisper Arnie's we always run a bunch of these different controls and so for [00:24:06.03] [00:24:06.03] flu we actually did we looked at a number of guide R.N.A.'s I'm just [00:24:10.23] [00:24:10.23] showing you some of them and actually many of them didn't work but [00:24:13.18] [00:24:13.18] what you can see is that the guide m 5 actually worked really well for [00:24:18.14] [00:24:18.14] r m 5 Guide against flu and this is being given so the way these experiments [00:24:22.21] [00:24:22.21] work is we infect the cells 1st the reason this is in a sense like a treatment so [00:24:27.09] [00:24:27.09] we fecht the cells 1st we actually waited day we give the virus a whole day to run [00:24:31.17] [00:24:31.17] amok in cells we then deliver our R.N.A.'s and then we wait another day to see if we [00:24:35.22] [00:24:35.22] can knock down the viral r.n.a. And in this case we could and so [00:24:39.15] [00:24:39.15] both using the Ls version the nuclear localization version and [00:24:44.01] [00:24:44.01] the side a positive version in both cases were Docky down at least 7580 percent so [00:24:48.14] [00:24:48.14] that was great we were really pleased to see that and [00:24:51.13] [00:24:51.13] there are a lot of guys who don't work why they don't work there's more to it as [00:24:54.23] [00:24:54.23] likely to do with not having access to the r.n.a. [00:24:58.18] [00:24:58.18] and that is certainly one of the reasons and we're investigating lots of guides to [00:25:02.06] [00:25:02.06] understand how they work and how they don't but then we also so we ran the 1st [00:25:06.09] [00:25:06.09] experiment where we just look at knockdown against the non-target guide we saw [00:25:10.11] [00:25:10.11] that then we ran all the other controls and the nice thing is that in general [00:25:14.05] [00:25:14.05] all the other controls look great it was you're seeing most all of the effect is [00:25:19.02] [00:25:19.02] really just due to ns Matic action of cast 13 the dead one isn't working the anti [00:25:24.13] [00:25:24.13] c.r. isn't working and I mean which is a good thing and certainly even the g.f.p. [00:25:29.03] [00:25:29.03] ver the g. of p. expression with the guide is not showing any knockdown So [00:25:33.18] [00:25:33.18] this is a good guide we consider this to be a very good guide. [00:25:36.20] [00:25:38.09] One problem though is that that particular guide hits a lot of flu strains but [00:25:42.10] [00:25:42.10] it doesn't hit all the flu strains in the world so [00:25:44.21] [00:25:44.21] instead what we did is we worked with some folks from the c.d.c. and [00:25:48.16] [00:25:48.16] we looked specifically at vaccine strains so we looked at about 100 and this was [00:25:54.12] [00:25:54.12] work mostly done by Ian York at the c.d.c. So we looked at 108 vaccine strains and [00:25:59.11] [00:25:59.11] we looked for regions in these vaccine strains that were that were conserved and [00:26:04.23] [00:26:04.23] we found to consider that a number of consensus sequence 6 Senses sequences [00:26:11.01] [00:26:11.01] say that 10 times fast and we found one specifically in p.v. 2 so p.v. [00:26:16.19] [00:26:16.19] 2 was one of the political race genes so influence is a negative stranded r.n.a. [00:26:22.01] [00:26:22.01] virus it has to come into the cell with its own r.n.a. dependent on a poem or [00:26:27.01] [00:26:27.01] an ace and so in the case of flu it has 3 components p a p v one in p.v. 2 so [00:26:32.11] [00:26:32.11] we found this conserved sequence in p v 2 and we made a bunch of different guides. [00:26:39.10] [00:26:39.10] And we'll get to the data in a minute but we found 2 that actually work well and [00:26:43.17] [00:26:43.17] when we looked at those 2 guides and we looked at now we expanded our [00:26:48.02] [00:26:48.02] search to sensually all of the each one n one each 3 and [00:26:52.06] [00:26:52.06] to use the 2 entries that had been sequenced over the last 100 years we found [00:26:56.22] [00:26:56.22] that those 2 guides would hit 99 point one percent of all flu strains all age one in [00:27:02.03] [00:27:02.03] ones h 3 n 202 and twos that had been sequenced in the last 100 years so [00:27:07.08] [00:27:07.08] we thought this is clearly not pan influenza I'm not saying it is but [00:27:11.09] [00:27:11.09] it's pretty darn close and that was really exciting to us I mean I think it was over [00:27:16.06] [00:27:16.06] sequences across like 65000 different sequences or something like that but [00:27:19.23] [00:27:19.23] it was or I guess we really looked at about 50 to 52000 sequences and [00:27:24.09] [00:27:24.09] we had 100 percent coverage with 51606 and 9999 point one percent so [00:27:29.13] [00:27:29.13] we were really excited by that because even though we don't have I wouldn't call [00:27:33.11] [00:27:33.11] it 100 percent clearly 99 point one but it's getting close and it certainly gives [00:27:38.12] [00:27:38.12] us the feeling that you know 100 percent with addition of a few guides could be [00:27:42.20] [00:27:42.20] very possible so having a pseudo pan influenza possibility is on the horizon so [00:27:48.15] [00:27:48.15] that was I think pretty exciting to us and we're looking at other other avian flu [00:27:53.14] [00:27:53.14] swine flu is and outside of this region but and many of these same guys [00:27:59.00] [00:27:59.00] actually hit a lot of h five's So I think that there's there's a lot to be said for [00:28:02.19] [00:28:02.19] that so then we tested a bunch of these and we did find 2 if you look at m 4 and [00:28:08.19] [00:28:08.19] g 2 both of those against p.v. [00:28:12.01] [00:28:12.01] 2 against that conserve region work really it's a pretty darned well we're seeing [00:28:16.12] [00:28:16.12] 7585 percent knockdown in that particular in that particular **** a so [00:28:22.03] [00:28:22.03] that was really nice see there are others that are close and so I certainly don't [00:28:25.23] [00:28:25.23] want to speak badly of them but in general the these 2 with the best and you might [00:28:31.16] [00:28:31.16] think you know we look at the nuclear and cytoplasmic Why do we see differences [00:28:35.14] [00:28:35.14] sometimes well the reason is that if you look at these if you look at the vice. [00:28:38.23] [00:28:38.23] Iris what I'm showing you in the slide is green is is the nuclear protein and [00:28:43.22] [00:28:43.22] and that's a marker for viral r.n.a. and so. [00:28:47.06] [00:28:48.08] It binds to the viral r.n.a. [00:28:49.21] [00:28:49.21] And so if we look at this is a function of m a y And that's a multiplicity of [00:28:53.07] [00:28:53.07] infection you can think of that is just the amount of virus we're using. [00:28:56.10] [00:28:57.15] For a given amount of cells that we're trying to in fact [00:29:00.09] [00:29:00.09] you can see that N.P.'s a lot of different locations in some cells it's very nuclear [00:29:04.14] [00:29:04.14] you can see that very clearly and other cells it's quite cytoplasmic And [00:29:08.12] [00:29:08.12] so that's why we see that variability in terms of. [00:29:11.15] [00:29:12.19] Targeting and it's really good for us to do basically target both compartments [00:29:17.12] [00:29:17.12] simultaneously and actually we've gone to doing that also some data where we [00:29:21.13] [00:29:21.13] actually combine the 2 but when we looked at both these g 2 and m. [00:29:24.18] [00:29:24.18] 4 guide they were both good guides I mean in general I would say the dead version [00:29:29.22] [00:29:29.22] we did see some effect in g. 2 and you might think is that bad well it's not [00:29:35.08] [00:29:35.08] terrible because in the end unless version we didn't see a lot of dead effects but [00:29:39.14] [00:29:39.14] we did see enzymatic activity so meaning we are seeing the enzyme working [00:29:44.06] [00:29:44.06] the dead if we see knocked down can mean that just finding alone of [00:29:49.01] [00:29:49.01] the cast 13 is halting the virus and that's not a bad thing we prefer [00:29:54.06] [00:29:54.06] the Ns amount of action but if you have some ns a magic action and some blocking [00:29:58.01] [00:29:58.01] do that due to just binding that's Ok but it helps us again basically gives us [00:30:03.01] [00:30:03.01] insight into how this how this particular guide is functioning if you look at m. [00:30:06.23] [00:30:06.23] 4 it's mostly really just By ends of magic action but I think this is important for [00:30:11.17] [00:30:11.17] us to understand because understand the mode of action of these different guides [00:30:15.15] [00:30:15.15] combined with Castleton is important and so the other experiment that we did is we [00:30:19.22] [00:30:19.22] want to look at time Christine I mean this is an enzyme So what do we see and [00:30:23.21] [00:30:23.21] I think if you look at the bottom graph this is probably the most important one to [00:30:27.02] [00:30:27.02] look at the question is as as the virus is replicating over time [00:30:32.05] [00:30:32.05] are we able to keep up with it and what the data shows in that 2nd graph [00:30:36.03] [00:30:36.03] is that we can we're staying about 90 percent. [00:30:39.00] [00:30:39.00] Sent actually lower then the virus so we're keeping viral viral r.n.a. [00:30:44.07] [00:30:44.07] levels about 90 percent below the max level and [00:30:47.15] [00:30:47.15] that's good to see I mean that was that was kind of exciting for [00:30:50.12] [00:30:50.12] us to see this that it could keep up now is it beating it not necessarily but [00:30:55.16] [00:30:55.16] at least it's keeping up with it and it's not outpacing us and so [00:30:59.09] [00:30:59.09] one of things we're looking now is that the modifications to the guides were [00:31:03.07] [00:31:03.07] looking at different cast 13 enzymes to see if any of them can be [00:31:06.08] [00:31:06.08] sort of supercharge and that sort of are our next approach but [00:31:09.12] [00:31:09.12] in general we can keep that level log lower essentially over a 96 hour period so [00:31:15.10] [00:31:15.10] that was exciting I think from our point of view. [00:31:18.15] [00:31:18.15] So let's talk about SARS Povey 2 so this is a completely different virus [00:31:23.18] [00:31:23.18] flu is a negative stranded r.n.a. virus replicates in the nucleus Kovi 2 [00:31:29.10] [00:31:29.10] is a corona virus obviously and it's a positive Strand are numerous It's a huge [00:31:33.16] [00:31:33.16] genome it's almost 30000 nucleotides long it replicates in the side of platinum so [00:31:38.22] [00:31:38.22] it's very different it's replication dynamics are quite different this virus [00:31:42.09] [00:31:42.09] actually replicates very fast in Detroit And it uses totally different [00:31:47.01] [00:31:47.01] compartments in general I mean flu really likes it replicates of the nucleus and [00:31:51.07] [00:31:51.07] there are reasons for that it requires splicing mechanisms that exist in [00:31:54.05] [00:31:54.05] the nucleus to replicate its r.n.a. gets trafficked on multiple. [00:31:58.13] [00:32:00.17] Bodies inside the cell could be to just different things that remodels the e.r. [00:32:05.21] [00:32:05.21] it does use vessels but in a very different way we did not know if we could [00:32:09.13] [00:32:09.13] hit this at all so we said Can we want to ask the question [00:32:14.01] [00:32:14.01] can we have this virus can we have an effect on it using Cas 13 so [00:32:17.21] [00:32:17.21] the 1st thing we did is we had got some very early sequences actually some folks [00:32:21.14] [00:32:21.14] from folks at the c.d.c. we combined them to the ridge and we actually compared them [00:32:25.23] [00:32:25.23] to the original SARS and the little green regions in the 1st graph or [00:32:30.13] [00:32:30.13] regions that have very high I'm ology with SARS and so with the original SARS and [00:32:35.11] [00:32:35.11] so we picked those regions we then we found a number of them we found. [00:32:40.11] [00:32:40.11] We would then again tile them we made a number of guides we always [00:32:44.23] [00:32:44.23] actually look at the folding of the guides so you can see actually the excepted [00:32:48.01] [00:32:48.01] are in a structure there is actually a guide that folds properly and [00:32:51.01] [00:32:51.01] that's the stuff that's what guides look like for 4 l.b. you cast 13 and [00:32:55.18] [00:32:55.18] we found ones that would would fold properly and then we said Ok [00:33:00.08] [00:33:00.08] let's try this in an asse way so this work is complicated because [00:33:05.07] [00:33:05.07] flu we can do in my lab Koby to work we have to do somewhere else that we've been [00:33:08.21] [00:33:08.21] telling with folks at University Georgia with Jeff Hogan and Eric La Fontaine and [00:33:13.17] [00:33:13.17] we use a real old school viral logy approach to this and [00:33:19.03] [00:33:19.03] so these are 6 well plates we're using of the rope the 6 models of [00:33:23.01] [00:33:23.01] the rose are a green monkey kidney cell that do not produce interferon and so [00:33:27.11] [00:33:27.11] this virus goes very rapidly in them has a basically the virus has a good time [00:33:31.18] [00:33:31.18] in the cells and it's very sidling meaning it kills cells and so [00:33:35.18] [00:33:35.18] what we did was an old school method we wanted to see if [00:33:39.07] [00:33:39.07] our drug cast 13 day with various guides would actually slow the virus down to [00:33:45.00] [00:33:45.00] the point that it would not cause what we call sidepath effect meaning could we stop [00:33:49.18] [00:33:49.18] the virus from killing cells real simple old school assaye but very informative [00:33:55.22] [00:33:55.22] it would tell us whether a guide worked and what you're seeing in this pictures is [00:34:00.08] [00:34:00.08] each one of those wells if you look at the mock each one of these wells has here at [00:34:05.13] [00:34:05.13] least 6 cells in it if it's blue it means that we were able to fix the cells and [00:34:10.08] [00:34:10.08] seen it with crystal violence all had to be done by simply Level 3 containment. [00:34:14.08] [00:34:15.19] The marks look blue because the cells are happy they're fine they're all there [00:34:19.13] [00:34:19.13] what happens when does it why does it look white in some places that's where [00:34:23.20] [00:34:23.20] the virus killed all the cells so if you look at virus only it kills all the cells [00:34:27.19] [00:34:27.19] this is 60 hours post infection so we did a similar assay is what we did with flu we [00:34:32.14] [00:34:32.14] delivered our cat Cassadine m.r.s.a. along with a number of different guides and [00:34:37.08] [00:34:37.08] fortunately we were able to find guides that's. [00:34:40.01] [00:34:40.01] Low the virus down so n 3.2 is a particularly good one and [00:34:45.01] [00:34:45.01] we even did a combination of n 3.2 an 11.2 not going to get into the details of [00:34:49.23] [00:34:49.23] what that means but these are different guides and [00:34:51.22] [00:34:51.22] even combinations of guides that we used against the virus and [00:34:55.00] [00:34:55.00] one thing we found is that we could probably could basically halt prevent that [00:35:00.06] [00:35:00.06] death by about 80 percent and that was really exciting because we have to [00:35:05.10] [00:35:05.10] target the virus is complicated I should mention initially with very large genome [00:35:09.22] [00:35:09.22] it makes a bunch of these things called subs you know Macartney's smaller pieces [00:35:14.03] [00:35:14.03] they I think they are actually are good targets for us to go after but [00:35:18.20] [00:35:18.20] it's a complicated virus but we were able to see the difference so [00:35:21.20] [00:35:21.20] does this mean we have a drug against Kovi to the answer is No Not yet but [00:35:26.04] [00:35:26.04] it certainly gives us a lot of confidence that this is a an approach [00:35:30.18] [00:35:30.18] that has the ability to thwart the virus I will say we actually ran controls so [00:35:35.17] [00:35:35.17] there's a non targeted c.r. wells we also did a g.f.p. [00:35:40.00] [00:35:40.00] with 3.2 was our best one so we did a g.f.p. [00:35:43.03] [00:35:43.03] and we did a dead version neither the dead version or the g p version or the n.t. [00:35:47.16] [00:35:47.16] c.r. had really any effect on the virus and [00:35:50.02] [00:35:50.02] you can see that if the virus obliterated all the cells kind of sad but at the same [00:35:54.19] [00:35:54.19] time it showed us that our controls did not have an effect on the virus it [00:35:58.09] [00:35:58.09] only guides and you can see the different guides to different a fax differential [00:36:02.14] [00:36:02.14] effects on the virus but we certainly had some guys that worked very well. [00:36:05.23] [00:36:07.02] And that was really again very exciting to us I mean when we 1st saw this data I was [00:36:11.17] [00:36:11.17] probably jumping up and down a bit because I thought we didn't even know if we could [00:36:15.03] [00:36:15.03] target it and what it shows you can move so quickly using crisper beta [00:36:19.02] [00:36:19.02] based techniques from one virus to another and this is a totally different viruses [00:36:22.20] [00:36:22.20] are a positive Strand are about r.n.a. virus versus a negative strand so [00:36:26.14] [00:36:26.14] we were super excited it's it's we've done that I say a multiple multiple times over [00:36:31.15] [00:36:31.15] confident in it but I would say we still have a long way to go but this certainly [00:36:35.22] [00:36:35.22] gives us confidence to move forward and I will say this much this is a stranger. [00:36:40.01] [00:36:40.01] Model the virus grows very quickly and [00:36:42.06] [00:36:42.06] a blitter has high obviously a high degree of sidepath effect so [00:36:46.06] [00:36:46.06] it's a stringent model I think that gives us a lot of confidence that that [00:36:51.01] [00:36:51.01] if we're successful that we have some chance of being successful in vivo. [00:36:54.21] [00:36:56.12] I will say a lot of the small molecule work that's done you'll see they'll do it [00:37:00.01] [00:37:00.01] just when we have done a dose response it's coming but it will increase dose and [00:37:04.07] [00:37:04.07] look at effects but they don't use a strictly speaking controls they don't use [00:37:08.12] [00:37:08.12] a inactivated molecule very often or a very similar molecule they sometimes use [00:37:12.22] [00:37:12.22] there but whenever they have the drug the solvent the drugs dissolved in but [00:37:17.12] [00:37:17.12] that's about a vehicle control but that's it so I think our asset is quite stringent [00:37:22.07] [00:37:22.07] we've included a large number of can we've included controls so I think we feel [00:37:26.08] [00:37:26.08] pretty confident so hopefully we'll be able to move this forward in the future so [00:37:31.05] [00:37:31.05] the other data I want to show you is another question we had and [00:37:35.02] [00:37:35.02] that is 10 use this in vivo you know it's nice to do these cell based assays But [00:37:40.03] [00:37:40.03] can we take this further can we go into into an animal model and [00:37:45.00] [00:37:45.00] so what I'm showing you is and how we deliver this in a way that is [00:37:49.00] [00:37:49.00] translatable to human beings and I think we still have a lot of work to do and [00:37:52.23] [00:37:52.23] I always want to emphasize that but we started out. [00:37:56.08] [00:37:57.10] We in the past have done into tracheal spraying where literally we put a tube [00:38:02.00] [00:38:02.00] into the mouse is trachea and we spray r.n.a. [00:38:05.02] [00:38:05.02] into its lungs that is not a completely crazy thing to do has it but [00:38:10.04] [00:38:10.04] probably sounds it sort of would simulate a person being into baited and [00:38:15.04] [00:38:15.04] then you can if you could spray again into their trachea and [00:38:18.08] [00:38:18.08] into their lungs the problem with that is the person needs to be integrated and [00:38:21.11] [00:38:21.11] so we really wanted to take this different to a different level we want to say what's [00:38:25.18] [00:38:25.18] a more translatable approach could we use a nebulizer So [00:38:29.18] [00:38:29.18] in this case we came up with a very simple approach those tubes the animals can [00:38:35.05] [00:38:35.05] be mice can be put into those little tubes you can see the restraints there's a 3 d.. [00:38:40.01] [00:38:40.01] Into nose cone. [00:38:41.01] [00:38:42.07] That Darryl bent over in my lab actually made and allows the animals once they go [00:38:46.13] [00:38:46.13] into the little tubes they stick their heads in the nose cone and [00:38:49.07] [00:38:49.07] they can breathe what's on the other side of the nose cone and [00:38:52.00] [00:38:52.00] in that case we have a human nebulizer is a net vibrating mesh style nebulizer [00:38:56.16] [00:38:56.16] that's used it's commercially available to f.d.a. approved and what we do is we add [00:39:01.05] [00:39:01.05] a drug to the top of it are on a base drug it Debbie lies it and then the animals can [00:39:05.14] [00:39:05.14] breathe it in and in this case we're formulating we we formulated this with a. [00:39:10.12] [00:39:11.17] With a polymer Actually that was originally published by the Anderson lab [00:39:15.20] [00:39:15.20] the Ours is similar it's not exactly the same but it's similar to that polymer and [00:39:20.17] [00:39:20.17] we're in our lab where and with colleagues we're investigating a lot of different [00:39:25.18] [00:39:25.18] formulations so this case this was formulated by a polymer that we we made my [00:39:29.21] [00:39:29.21] lab we're also investigating liver data particle based liver that's getting better [00:39:34.08] [00:39:34.08] and better that's with teams Dallman who's also in by medical engineering and [00:39:38.17] [00:39:38.17] we're also working with a company guy therapeutics also on delivering l n p s [00:39:43.01] [00:39:43.01] and I think that that you know these Ellen Ellen piece are getting better and [00:39:46.09] [00:39:46.09] better and I think long term they're probably going to be the best approach but [00:39:49.18] [00:39:49.18] the polymer gives us a great baseline and a place to start and [00:39:53.17] [00:39:53.17] you know we did some optimization in terms of how much r.n.a. that we were basically [00:39:59.13] [00:39:59.13] how we were complex ing it and you can see the the in this graph essentially the flux [00:40:05.15] [00:40:05.15] means reporter are a nice to examine expression in the lungs and [00:40:10.18] [00:40:10.18] we have a number of different ones that we use we have [00:40:14.04] [00:40:14.04] some that are specifically good for being retained with the proteins retained in [00:40:18.05] [00:40:18.05] the long and this allows us to more quantitatively assess the delivery and [00:40:24.05] [00:40:24.05] so we were able to do some optimization that's what you see in b. and then in c. [00:40:28.06] [00:40:28.06] these are actually individual images of mouse lungs and so [00:40:31.04] [00:40:31.04] this is actually the expression of r. and r. in a mouse lens now in c. [00:40:35.12] [00:40:35.12] one of the questions we had is could we deliver post infection so this work. [00:40:40.02] [00:40:40.02] Done with influenza so the animals were infected and then at 12 hours and [00:40:44.04] [00:40:44.04] 24 hours post infection we delivered so similar to what we were doing in [00:40:48.15] [00:40:48.15] vitro except in this case we wanted to be sure that we could actually see expression [00:40:53.06] [00:40:53.06] because that wasn't clear I mean that was not something we do and if [00:40:56.06] [00:40:56.06] you look at the data in d. it really looks like it's pretty similar we don't see. [00:41:00.20] [00:41:02.01] Huge differences in terms of the transaction only and with and without [00:41:07.16] [00:41:07.16] infection in general they're really not big differences that was great to know so [00:41:12.13] [00:41:12.13] we answer we wanted to answer the question could we deliver post infection into long [00:41:16.04] [00:41:16.04] it's really different but different than delivery in cells in a dish and [00:41:19.14] [00:41:19.14] would we get similar expression levels and the answer was yes and so [00:41:22.17] [00:41:22.17] then we did a more complicated test we infected animals with influenza [00:41:28.16] [00:41:28.16] we infected them for about 6 to 8 hours and then we delivered our drugs and so [00:41:34.03] [00:41:34.03] they were infected we delivered and this was cast 13 using [00:41:40.01] [00:41:40.01] I think it was m $41.00 of the one of the guides that I mentioned previously and [00:41:44.15] [00:41:44.15] we wanted to see would it be in 5 it's actually in it's in the growth so [00:41:49.00] [00:41:49.00] it m 5 did we see knock down and the great thing is that we did so virus only. [00:41:54.10] [00:41:56.03] We see some knock down to the n.t. c.r. itself and that's not too surprising I [00:42:00.18] [00:42:00.18] mean you're adding a delivery vehicle it's going to have some effect on the virus but [00:42:04.01] [00:42:04.01] it's Mol it was only about a 10 percent real change in the virus the m.t.c. [00:42:08.06] [00:42:08.06] are the non-target control wasn't too bad but was really nice to see is with [00:42:12.13] [00:42:12.13] the with the guide we saw about an 86 percent knockdown of the virus in vivo and [00:42:18.04] [00:42:18.04] for us this was really exciting because we were able to show that this that Caster [00:42:23.05] [00:42:23.05] team is functional in vivo can knock out and actually about as well as what we see [00:42:27.11] [00:42:27.11] in vitro and we were able to see see this knockdown in vivo and so this to me gives [00:42:32.19] [00:42:32.19] us hope that we can move forward again to do to use this again with different guides [00:42:37.09] [00:42:37.09] of course the ones that we tested against Koby to and move this forward in in mouse [00:42:41.05] [00:42:41.05] at least in the hamster models we're using hamster model for for Kovi too and [00:42:46.03] [00:42:46.03] it gives us a lot of hope that we're going to be able to apply this and [00:42:49.09] [00:42:49.09] if we're successful in hampers then the more kind of keep going in the goal is to [00:42:52.18] [00:42:52.18] get this into people as soon as we possibly can and so we may change delivery [00:42:57.07] [00:42:57.07] vehicles we may go from this polymer into an l. and a look at nanoparticle but will. [00:43:01.18] [00:43:01.18] See we're going to keep looking at them we're making new polymers we're making new [00:43:05.06] [00:43:05.06] Alan peace with James Solomon's group and with God therapeutic So [00:43:08.20] [00:43:08.20] hopefully we're going to get better and better as that technology moves forward [00:43:12.14] [00:43:12.14] I will say that this approach that we have and that that device that we made which is [00:43:16.22] [00:43:16.22] a very simple device is really nice because it allows you to screen particles [00:43:21.12] [00:43:21.12] very rapidly we can even use to animals progress and you can clearly screen [00:43:25.21] [00:43:25.21] particles you can see who's a winner who's a loser in terms of delivery and so [00:43:29.15] [00:43:29.15] it's been very very helpful for us to optimize our delivery [00:43:34.08] [00:43:34.08] optimize our formulations and so there's a lot of work to do but [00:43:38.17] [00:43:38.17] I think that this approach is extremely promising and so it was really good for [00:43:42.21] [00:43:42.21] us to see that this is happening in vivo that's pretty much what I had for [00:43:47.19] [00:43:47.19] today I think the caster team has a lot of a lot of promise I [00:43:52.03] [00:43:52.03] do want to mention folks in my lab Emmeline Blanchard caravan over. [00:43:55.17] [00:43:56.20] Was no boy was pretty Tewari Laura was holo here as Earl and [00:44:02.04] [00:44:02.04] Hannah Peck lots of folks in the lab working really hard a lot of folks [00:44:07.01] [00:44:07.01] working on other projects that have been working on this one so that we could make [00:44:11.10] [00:44:11.10] as much progress as possible and then I need to acknowledge the folks at c.d.c. [00:44:15.21] [00:44:15.21] Tork in particular and then folks at u.g.a. Eric La Fontaine Frank Michele and [00:44:20.09] [00:44:20.09] Jeff Hogan and I have to obviously knowledge DARPA because they fund this war [00:44:25.02] [00:44:25.02] and so I mean we have a lot to do on cast 13 but I think you know this this work so [00:44:30.01] [00:44:30.01] far shows promise one nice thing is that you can easily combine guides for flu and [00:44:35.13] [00:44:35.13] for coding too so you could literally go after both viruses at the same time and [00:44:39.21] [00:44:39.21] eventually we hope to have this that will have a therapeutic that would work against [00:44:43.09] [00:44:43.09] multiple respiratory viruses and you know all the by swapping guides [00:44:47.18] [00:44:47.18] into multiple guides we can cover as many strains as possible so [00:44:52.09] [00:44:52.09] that's pretty much what I had for today I'm not sure what I'm supposed to do that. [00:44:57.00] [00:44:58.19] Thank you for all the. [00:44:59.13] [00:45:00.19] Thanks for your presentation and [00:45:03.02] [00:45:03.02] I have probably have some questions on the chalk mode let's see. [00:45:06.10] [00:45:07.11] There's a question from part this science is people are saying that this virus we [00:45:11.10] [00:45:11.10] were big very fast and the mutated strain is becoming dominant now that what do [00:45:16.12] [00:45:16.12] you think by mutating this virus is changing the it's and will of structure. [00:45:21.20] [00:45:23.00] On whole genome if the sure. [00:45:25.02] [00:45:26.03] It did using different McCown isms like frame shifting on any other mechanism then [00:45:30.17] [00:45:30.17] how many guides should be available Yeah that I mean that's it in general it's [00:45:34.22] [00:45:34.22] a really good question I mean so far I haven't been seeing I would say a whole [00:45:38.09] [00:45:38.09] genome type changes I mean the gene or the changes I've seen are specific [00:45:44.00] [00:45:44.00] specific Mino acid changes mostly in the spike there's been some in [00:45:48.09] [00:45:48.09] the replicates but very few in the regions that we've been looking at Cisco far we've [00:45:52.23] [00:45:52.23] not seen any mutations in any of the guides that we're looking at so as of yet [00:45:57.23] [00:45:57.23] the ones that we've been looking at should be able to should be able to target [00:46:02.20] [00:46:02.20] the the strains that are out there I would agree that we may end up having to go to 2 [00:46:07.13] [00:46:07.13] or 3 or so different guides in order to make sure we target it and [00:46:12.01] [00:46:12.01] how many could we use I don't think that's clear yet but I think 4 or [00:46:15.14] [00:46:15.14] 5 guides wouldn't be too difficult and so you know that's going to end up being [00:46:19.14] [00:46:19.14] a delivery issue more then than I would say you know making guides is [00:46:24.02] [00:46:24.02] not difficult so I don't think that's going to be a huge deal but [00:46:26.13] [00:46:26.13] that I agree I don't think it's clear but so [00:46:29.05] [00:46:29.05] far we haven't seen any mutations cropping up where you know where we're looking so [00:46:34.06] [00:46:34.06] you know the question from Osama philology is on the tests [00:46:37.11] [00:46:37.11] were done on animal cells can we expect a similar rest ponces in human cell culture. [00:46:42.16] [00:46:42.16] So I'm still. [00:46:43.10] [00:46:45.05] Going to I mean we we've done we are in the midst of looking at [00:46:50.11] [00:46:50.11] the 2 in human cell lines so with Margot Britton we're looking at a whole bunch [00:46:55.18] [00:46:55.18] of different cells we're looking at h u h seven's Keiko to Scalloway threes and [00:47:00.22] [00:47:00.22] that's also work that it's going on with Nick heat to it too so [00:47:05.12] [00:47:05.12] we're looking at those 3 human cell types also so and [00:47:09.20] [00:47:09.20] we're trying to make it $54.00 nines more susceptible than other human cell line [00:47:14.13] [00:47:14.13] susceptible but most likely we're going to be testing this in a more complex system [00:47:19.23] [00:47:19.23] there's an We're getting an emulate system here of emulate makes these [00:47:24.04] [00:47:24.04] Organon a chip model's Nikita's getting one of those 2 and so we're actually. [00:47:29.01] [00:47:30.06] Were actually working with the with with the with those folks to be testing it with [00:47:34.13] [00:47:34.13] donning bird too so I would say we're going to looking at better human models [00:47:38.23] [00:47:38.23] to see how well this works no question but I mean right now my personal opinion is I [00:47:43.00] [00:47:43.00] want their work as an amateur because right now they're the animal model where [00:47:45.22] [00:47:45.22] we're seeing at least viral rep where I should say we where I have seen data that [00:47:50.18] [00:47:50.18] suggests that there's viral replication in the long ferrets not as much another [00:47:54.19] [00:47:54.19] question from mention Chen from c.d.c. very nice and very interesting questions. [00:47:59.00] [00:48:00.17] Will it be possible that the whole is true do you see me understands serious trauma [00:48:05.07] [00:48:05.07] Dean's sick and would it be possible to create escape mutants of the virus so [00:48:11.03] [00:48:11.03] so there's a 2 great question so one of the reasons I am unclear about [00:48:16.03] [00:48:16.03] caste 13 certainly human beings it's been shown that a lot of folks have antibodies [00:48:21.06] [00:48:21.06] against caste 9 that is not precluded folks from moving forward with cas 9 in [00:48:26.00] [00:48:26.00] vivo we're using cast 13 I have not seen any studies on whether people have have [00:48:31.01] [00:48:31.01] antibodies against Castor teen I do think in our case this is not as big a deal and [00:48:35.23] [00:48:35.23] the reason is is that we're transiently expressing how Certina [00:48:40.07] [00:48:40.07] there are other folks that have suggested using System. [00:48:42.06] [00:48:42.06] Where they're expressing it much more strongly and for [00:48:44.18] [00:48:44.18] longer periods of time we do not advocate that approach we're using an m.r.i. r.m.r. [00:48:49.03] [00:48:49.03] in a based approach that it doesn't hang around that long so our thought would be [00:48:53.07] [00:48:53.07] if we can to minimize that we are looking very shortly we're going to be looking for [00:48:58.00] [00:48:58.00] at you know what probe what peptides are displayed on m.h.d. from has 13 but [00:49:02.18] [00:49:02.18] again our goal is to get it in there have it knock down the virus and [00:49:06.17] [00:49:06.17] not hang around too long and general escape means we're going to be looking at [00:49:10.22] [00:49:10.22] that so we're just able to get r.n.a. now out of d.s.l. [00:49:14.23] [00:49:14.23] 3 with a couple of different a couple of our colleagues so we're going to be [00:49:18.04] [00:49:18.04] looking to see if there are escape mutants are we seeing any new Taishan that [00:49:23.12] [00:49:23.12] are occurring due to this I mean in the end we're going to use multiple guides and [00:49:27.20] [00:49:27.20] so hopefully that will allow us to to prevent that from happening and [00:49:32.05] [00:49:32.05] knock it back but it's a great question it's still there certainly more work to do [00:49:35.23] [00:49:35.23] I've got Todd's question here holding by devices run through so. [00:49:40.12] [00:49:41.18] Delivering directly to infected cells and to deliver cells are not in the bag [00:49:45.14] [00:49:45.14] not I mean we can still be delivered to cells that are. [00:49:48.16] [00:49:49.20] You know uninfected I mean that's fine and we've done we've done infection we've done [00:49:54.19] [00:49:54.19] delivery pre infection and it works great I mean if it's in there it hangs out until [00:49:59.08] [00:49:59.08] it's activated and we've we've done those experiments certainly in a matter of fact [00:50:04.03] [00:50:04.03] I would say it's even more effective because if the virus shows up and [00:50:07.07] [00:50:07.07] there's caster team there it'll bind activate and start chewing and [00:50:10.19] [00:50:10.19] so it's even more effective we just want to show it could be done at and could be [00:50:14.12] [00:50:14.12] used afterwards just you know from that from that particular point of view but [00:50:19.06] [00:50:19.06] we're doing prophylactics too will be doing that animals more also so [00:50:24.19] [00:50:24.19] I would say there's certainly more to come in terms of that. [00:50:28.17] [00:50:30.23] And take another one from Ross if you say Ross and good to see you. [00:50:36.04] [00:50:37.13] Still let's see if you talk read that technical challenges for [00:50:40.14] [00:50:40.14] using multiple guides not a whole lot I mean multiple guides we just have to make [00:50:44.14] [00:50:44.14] sure they fold I mean that's been something we've been [00:50:47.04] [00:50:47.04] we've been we've found I think to be important and [00:50:50.09] [00:50:50.09] then at the same time to combining them as long as they don't bind to each other so [00:50:53.16] [00:50:53.16] we look to make sure there's no home ology with each other so they don't form [00:50:56.10] [00:50:56.10] duplexes but beyond that we haven't seen really any significant difficulties [00:51:01.13] [00:51:01.13] there how many could we really use I don't know yet I mean I think that's unclear but [00:51:06.10] [00:51:06.10] certainly we've been doing experiments with 2 pairs and we're going to be looking [00:51:10.16] [00:51:10.16] at more and more in the near future so I think there's more to go look at but [00:51:15.20] [00:51:15.20] I don't think there's any serious issues there were guarding that So [00:51:21.10] [00:51:21.10] let's see is it possible you know what I don't know Eugene. [00:51:24.02] [00:51:25.03] From Mars Altie is it possible to use these guides to develop a rocket sensor [00:51:29.15] [00:51:29.15] focal with 19 are these specific enough sure so [00:51:32.21] [00:51:32.21] I would say there are a lot of people at mit in particular working on [00:51:38.10] [00:51:38.10] caster team based sensors so you can look at papers on the Sherlock system and [00:51:43.02] [00:51:43.02] I think there's a number of names for other ones folks are already using Cas 13 [00:51:47.12] [00:51:47.12] as a part of sensor systems no question about that we haven't really pursued that [00:51:52.02] [00:51:52.02] great in great detail just because there are a lot of other folks too but [00:51:56.04] [00:51:56.04] I'm you know I've talked some with Marx's in ski and [00:51:59.18] [00:51:59.18] about doing some collaborating on sensors but I'm happy to talk to other folks about [00:52:03.14] [00:52:03.14] them too we may cast their team to make the protein we can make our M.P.'s [00:52:08.15] [00:52:08.15] none of that's a big deal so if people are interested in that we happy to help [00:52:13.05] [00:52:13.05] we've been mostly focused on therapeutics because that's what Grant That's what [00:52:17.18] [00:52:17.18] DARPA's that's what you get for we get paid to do but I'm certainly happy to [00:52:22.00] [00:52:22.00] help with with other efforts on detection and we will have access to r.n.a. [00:52:26.13] [00:52:26.13] so from Coby too so that might help folks out. [00:52:30.13] [00:52:30.13] And so let's take the last question [00:52:33.01] [00:52:33.01] maybe the last night's encounter of Garland I know that. [00:52:36.07] [00:52:37.15] It's all of 2017 shown that there was a noticeable collateral activity [00:52:42.02] [00:52:42.02] from c s 13 miners cells but [00:52:44.16] [00:52:44.16] have you been able to observe the same effect that this does yes. [00:52:48.08] [00:52:49.14] Yes absolutely and that's a great question because in a tube you do see collateral [00:52:53.04] [00:52:53.04] cleavage of r.n.a. we really haven't seen that at all either so I would say our [00:52:57.07] [00:52:57.07] results are consistent with other folks even though we're using m.r.i. [00:53:00.18] [00:53:00.18] as opposed to d.n.a. for expressing these things we have not seen a lot of cleavage [00:53:05.06] [00:53:05.06] though I will admit that we've done some r.n.a. seek to look for [00:53:09.14] [00:53:09.14] it we haven't seen it we haven't seen cell death from cats 13 I mean [00:53:14.04] [00:53:14.04] again some of the I will agree that it's it's a little surprising you [00:53:19.02] [00:53:19.02] don't see collateral cleavage but we haven't why I don't know yet [00:53:22.21] [00:53:22.21] and that's something that we're going to be looking at more detail but so far it [00:53:25.19] [00:53:25.19] does look like it's precise it looks like it sensitive to about 2 nucleotide [00:53:30.04] [00:53:30.04] differences and so it needs to be binding to you know a precise equines So [00:53:35.02] [00:53:35.02] it does look like if it has precision but I think that's something that [00:53:38.12] [00:53:38.12] we're going to be looking at in a lot more detail with sequencing [00:53:42.06] [00:53:42.06] we're doing a number of sequencing studies or our of are going to be happenings very [00:53:46.23] [00:53:46.23] shortly with Koby too and so that's going to tell us a lot of information so [00:53:50.19] [00:53:50.19] not just about native R.N.A.'s and whether or not they're being modulating but [00:53:54.11] [00:53:54.11] also what we're really doing to the virus so clearly we know we're chewing up r.n.a. [00:53:59.06] [00:53:59.06] exactly what we're doing still remains to be seen I mean [00:54:02.21] [00:54:02.21] there's a lot of mechanism of action work some of that we're doing with [00:54:06.17] [00:54:06.17] Margo Britton the Georgia state some of it we're doing out at u.g.a. so. [00:54:11.05] [00:54:12.12] Margo is a as an expert in positron r.n.a. viruses and has a lot of insights as [00:54:17.08] [00:54:17.08] she's she's been really helping us out I mean I know a reasonable man [00:54:20.17] [00:54:20.17] that viruses of the organ that wear them for a while but I will admit every virus [00:54:24.17] [00:54:24.17] is a new adventure and so finding folks who are really experts in a particular. [00:54:29.04] [00:54:30.07] Class of viruses is really really important so [00:54:33.03] [00:54:33.03] we've been collaborating with folks who have have those insights. [00:54:36.20] [00:54:36.20] Thank you Phil thank you for your time and thank you everyone for [00:54:40.04] [00:54:40.04] participating We'll have the next one venture to feel free to join and [00:54:43.12] [00:54:43.12] feel really deserve a great deal of our Plus I wish we could give a great [00:54:46.22] [00:54:46.22] physical of last but the very least I can give you is I watch a lot less Thanks. [00:54:51.01] [00:54:52.23] I hope everyone stays safe here away from coffee to. [00:54:56.20] [00:54:58.00] **** and stay safe but [00:55:00.04] [00:55:00.04] I hope this is used to Folks thank you thank you everyone and our great day by. [00:55:05.22]