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Welcome to CRISPR Unedited,

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a bite-sized bio podcast hosted by an Anthony Adamson.

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In this episode of Crisp Put Unedited, I'm joined by p Hanson,

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scientific coordinator at the Cell and gene therapy core at Lu University.

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And we answer your practical questions about crispr learning about the

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differences between CRISPR and RNAi.

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Often the on target efficiency is higher. With CRISPR Eye,

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we've actually had several, uh,

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occasions where we've had complete turning off.

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We discuss how to show if a gene is really knocked out, you

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Need some functional tests.

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So it could be that the protein is absent or some downstream. Uh,

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regulators, if you have some genes that you know are regulated by this,

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you can look at that.

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And we talk about off targets

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Making the same edit,

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but having two different guide iron because then they completely negate the

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problems. You have to look at both of them. They have to get the same phenotype,

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and if you get the same phenotype, that cannot come from an off target effect.

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All this and more in this episode are CRISPR edited.

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Hello everyone and welcome to this podcast from Bite-Size Bio.

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My name is Anthony Adamson and I'm run a core facility called the Genome

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Medicine Unit, where as you might imagine,

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we use CRISPR Cas nine an awful lot to engineer cultured cells.

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We make novel mouse models,

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and more recently we've been using this technology to make Jetta modified flies

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as well. Uh, I'm joined today by Pier Johansson,

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who is a fellow member of the CRISPR Core facility community. Um, so Pia,

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would you just like to take a minute to introduce yourself, please?

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Yes. Hello everyone. Uh, my name is Pira. I am in Lund in Sweden,

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and we have a core here called, uh, cell and gene therapy core.

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And we are actually producing tools for such things,

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and most of it is research based.

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So we make CRISPR edits in i p s cells,

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and I also design CRISPR red for all other cell types.

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We do cloning and vectors as well. So we also produce, uh,

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lentivirus and AAVs. And soon we might also set up mRNA, uh,

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production in our core.

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Fantastic, thank you. Uh, well, a couple of months ago,

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bite-sized bio hosted an online CRISPR method symposium, which pier and I both,

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uh, presented at. Uh, now let's face it,

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CRISPR is a bit of a game changer in discovery science. It's, well,

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it's enabled cause like ours to be established,

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and it allows us to build better and more representative models biology and

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disease. So,

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no surprise that there's enormous interest in this online symposium. And,

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you know,

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lots and lots of people out there were really excited to learn more about the

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technology and many people wanted to get CRISPR up and running in their own

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research. Uh, and many more of you were looking for advice and tips, uh,

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and hints on maximizing your success with the technique.

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So as a result on the day, we had loads and loads of brilliant questions, uh,

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but ultimately far, far too many to answer in that, uh, online symposium.

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So we thought we don't wanna disappoint everyone. Um,

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and it might be a really good idea for peer and I to get together and follow up.

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And in this CRISPR Clinic podcast, we're gonna go through some,

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some of the many questions you submitted, uh,

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both during the conference and afterwards and try and offer some advice and

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guidance. You know,

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the type of things that we might actually do if we were approaching, um, uh,

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your projects in the laboratory. Uh, just a quick reminder,

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there's loads of really useful resources and hints and tips and tricks and blogs

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over it. Biosis bios, crispr hub as well, uh,

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for you to look at in your own time.

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And for those of you who didn't attend the symposium, I,

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I believe the talks were were recorded and you'll be able to access them over

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there too at some point if you're interested. So, uh,

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I hope we find this CRISPR clinic useful. Uh, if it's successful,

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there's enough interest,

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we'll think about putting some more in over time as well.

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So there's a constant source of expertise for you to get in touch and ask for

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help about. Uh,

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but I think at that point in time it might be a great idea to go to the

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questions. Um, so Pierre,

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I'm gonna come to you first and you have to excuse me to look to the side all

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the time 'cause I've got a,

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an alternative screen to be working from with all the questions

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On that. I do too. I'm sorry.

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Uh, so we've got a question from Claudia who's saying,

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I'm gonna start my knockout experiments. And, um, from the look of the question,

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it looks like she's trying to make her cell lines constantly express Cass nine

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using the lentiviral construct. And she's asking, uh,

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how can this be done and does the Castine need to be in activated at some point

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as well?

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Well, it's a good question. Uh, the,

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I'm gonna say something very often during this, uh, q and A session.

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It's like one of all, it depends on the locus and yeah, the one is,

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it depends on the cell a little bit. But, um, so here it also depends like,

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you know, sort of what type of knockout experiments. So, but generally, um,

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you can, let's put it this way, you can inactivate it.

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So there is this Kama Cai kakai or something.

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It's called KA Cass nine, uh, that was done where you also,

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at the same time as you introduce your other guide R N A and the Cass nine,

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you also introduce a guide r n a against Cass nine.

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So that means that it will actually stop being expressed in the cells.

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There is however,

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not so much evidence maybe that Cass nine is actually toxic or bad

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for the cells.

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So I mean this is more if you want to take it therapeutically later,

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but for research, often it's not a huge problem,

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but it does of course keep cutting. So you know,

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you might not end up with the same population originally as you had a little bit

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later. So, uh, if you can't go clonal, uh, or even if you can go clonal,

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you might wanna know that this is what you've got and it stops here.

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In that case you can inactivate it with a guide n a and you can of course also

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if you just want to do a knockout experiment,

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you might not have to use a LTI virus, then you just use, uh,

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another type like a plasmid or mRNA based where you have transient,

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uh, a transient effect because with a knockout you don't need it to be there for

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longer.

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That's like different if you want to do CRISPR or CRISPR eye often you want to

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have it there all the time. Uh, but when it comes to this,

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you could actually potentially, uh,

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choose to use another one or even use r and p via,

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via nuclear affection for example.

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Then you don't have to worry about those things.

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Yeah. So I suppose if you change the delivery modality, like you say, and uh,

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and that's something that you'll hear me say an awful lot,

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all all about delivery. If you change that modality,

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do you need to have the Cass nine being expressed all the time?

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'cause that's what lentivirus will do. Uh,

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lentivirus will integrate in the genome and will give you constant production of

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the Cass nine protein. I suppose just to touch on what you said there, you know,

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Cass nine by itself relatively inert,

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it doesn't really do any damage in the absence of guide r n A.

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So suppose one thing you could do is you could lentiviral express the Cass nine,

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but just transitively deliver the guide iron names to the cells as well.

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And that might be a way to minimize constant activity of the,

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of the Cass nine in those cells. Mm-hmm. That's a good idea. Yeah,

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so just mix and match that kind of thing.

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I wasn't aware of this kamikaze Cass nine, but that, that makes perfect sense.

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You know, you could knock out Cass nine itself. Uh, so that, that's,

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that's a really nice approach.

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Yeah, I liked it a lot actually. Yeah.

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Uh, I think, you know,

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cloudy action has a couple of follow up questions as well. Um, and, uh,

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one of them all, they all really relate to lentivirus essentially. Mm-hmm.

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You know, this idea of an off switch, um, this idea of off targeting,

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if you've got the Cass nine, the guide and f too long. So yeah, I,

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I think it is a good idea to minimize the window of the actual editing,

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but the Cass nine can stay expressed and probably won't have too many effects on

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your cells. Um, in terms of that window of expression of the, of the guide,

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R N a 24 hours is generally speaking enough to get editing.

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So you could transfect in the guide r n A as an r n a molecule into the Cass

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nine expressing cells, and that will, that will achieve the editing. Um,

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I don't know if you get experienced this pier, but there is,

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there is definitely risk sometimes with lentiviral transduced cells that you can

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get silencing of the transgene.

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So you may make cells that are expressing Cass nine all the time,

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but if you keep culturing them, passaging them,

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they may not be suitable for gene editing after a few weeks where depending on

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the locus, that's the one of the things you've already said.

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But depending the locus of integration, uh,

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and the cell types you're working with,

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any kind of selection you put on the Yeah, the cas the CASS nine might turn off.

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Have you, you've experienced that in the past?

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Yeah, so I, I haven't used so much of the normal Cass nine, we dead Cass nine.

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I've used a lot of vir and there we have the CRISPR eye.

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So then like it's in that particular viral vector is super good.

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It doesn't get very much silenced. So at all,

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we've used it for like four months, you know, into organoids,

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all that sort of things.

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But we also used the lentivirus for CRISPR a and uh,

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there it got silenced.

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We used two different ones and they both got silenced really quickly or like

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sort of disappearing generally. Even the next sort, they were not po uh,

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not positive anymore. And then in particular,

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we found that when we added the guide R N A, because crisp bras are big,

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you can't have, it's difficult to have all in one plasmid.

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So we first made a little cell line with, with the Cass nine expressing cells,

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and then we added the guide r n a in a different one a little bit later.

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And then we found that despite the fact that these were sorted and supposedly

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pure, uh, they had already dropped a lot just by itself.

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And then adding another virus actually made the silencing even more actually,

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of the original virus, not the second one. 'cause that's a small,

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very good virus. So it really depends on the virus itself also it seems,

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and maybe what actually is in it. Um,

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so that was a big difference between things that are actually quite similar so,

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and in the same cells. So, so that always varies a little bit. And,

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and lentiviral constructs are, are quite different actually from each other.

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So one should try and dig around.

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Yeah, that's fascinating. So I mean,

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I know this is a q and A for people that questions,

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but I've got a question for you right now. What were the,

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what were the effectors on the, on the dead cast nine, uh, for the,

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the eye and the a, you know, one, obviously one silence and one didn't

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Yeah, exactly. So yeah, exactly. So it had the crab on the, uh,

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on the crispr eye and on the crispr a we had VP 64 and, uh,

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one that was VP R and both of them were, um, were silenced.

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And also it made pretty bad viruses, actually, because they're huge.

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They were just on the border and maybe a little bit over.

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So it was quite difficult actually to, to do that experiment.

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Okay. That's really interesting because we, we've done a bit of crispr eye,

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a little bit of crispie. Yeah. Not, not as much as you guys.

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So that's a really interesting, um, observation.

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Something I'll be looking out for as well in our own work. Um, okay.

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So I'll jump onto the next question now. So this one, um, is, uh, for you again,

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Pierre. Uh, what are your thoughts on the effect of off targets? Um, are you,

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are you concerned about, uh, hitting other genes, genomic instability? Uh,

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and especially with re with a perspective here by look of it as far as the

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clinic's concerned as well?

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Yes, that's a very clinic,

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this is clearly a problem and that's something that you really have to

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investigate like full on later. So off targets are a difficult thing. Uh,

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I've been in several discussion rooms lately where people feel like, yes,

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it's probably something we should consider, but it's hard to do.

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So I have two, two viewpoints here a little bit, which I feel both of them.

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One of them is that maybe we don't worry too much about them because if you,

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unless you have in a specific gene, you know, actually inside the gene,

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that seems to be important for your cell type.

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And obviously we try to avoid that. But otherwise,

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a small indel somewhere in the genome is probably nothing really to worry about.

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Because the thing is that when you do clonal expansion of,

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I work mostly with I p s, when you do the clonal expansion there,

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you get really quite a lot of changes in the genome just because of that.

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So when we do this molecular karyotyping,

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there are really big things that are different. First of all,

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from the reference genome, of course, you know,

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that we are not the reference genome,

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but also like a little bit from the parent clone.

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And what we do there is that anything that is like a deletion or a loss of

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heterozygosity or something like that, that is up to 400,000 base pairs,

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you sort of accept. So, so knowing that, I feel a bit like, okay,

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maybe we don't care so much about like a little indel in a random place,

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but of course you never know.

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But this is also the reason why you use first of all, more than one clone.

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So that, you know,

227
00:12:16.960 --> 00:12:20.240
they all have slightly different variations in the molecular karyotype.

228
00:12:20.780 --> 00:12:24.040
But also why I always recommend, but this is not always used,

229
00:12:24.100 --> 00:12:28.360
is why you would use another guide r n a. So you make two different lines,

230
00:12:28.540 --> 00:12:32.040
for example, in i p s one making the same edit,

231
00:12:32.220 --> 00:12:36.800
but having two different guide RNAs because then they completely negate the

232
00:12:36.800 --> 00:12:39.560
problems. You have to look at both of them, they have to get the same phenotype,

233
00:12:39.560 --> 00:12:43.360
and if you get the same phenotype, that cannot come from an off-target effect.

234
00:12:43.940 --> 00:12:45.440
So, so that is like, I think,

235
00:12:45.440 --> 00:12:48.480
better ways to sort of work around it in a research setting.

236
00:12:49.330 --> 00:12:50.500
Yeah, absolutely. Yeah.

237
00:12:50.890 --> 00:12:53.340
Yeah. In a clinical setting, uh,

238
00:12:53.740 --> 00:12:57.100
I mean obviously there you have to test it much more and maybe whole genome

239
00:12:57.190 --> 00:13:00.900
sequencing is the way to go. And then once again, you have to, you know,

240
00:13:00.900 --> 00:13:03.940
you have to do the parent cell and then you have to do the edited cell,

241
00:13:04.240 --> 00:13:07.580
and then you have to see what the differences are in the whole genome

242
00:13:07.590 --> 00:13:12.140
sequencing. And then somehow you have to be able to assess what does that mean,

243
00:13:12.200 --> 00:13:15.020
you know, these little changes, does it mean anything, you know,

244
00:13:15.440 --> 00:13:19.940
so that will be a more complex task. Um,

245
00:13:20.280 --> 00:13:22.620
but of course, also we have to remember that when it comes into the clinic,

246
00:13:22.650 --> 00:13:25.940
very unlikely is it gonna be pluripotent cells,

247
00:13:26.370 --> 00:13:28.780
it's going to be in a specific model system,

248
00:13:29.180 --> 00:13:33.180
specific cell type where you can sort of go, well, this gene is not even on, uh,

249
00:13:33.240 --> 00:13:35.700
in these cells, so it's nothing really to worry about.

250
00:13:35.800 --> 00:13:39.740
So then you can also be more specific. Whereas in i p s, we look at all of them.

251
00:13:39.920 --> 00:13:41.980
So that's my thoughts.

252
00:13:42.810 --> 00:13:44.820
Yeah. You, you, you, you touched upon something there,

253
00:13:44.820 --> 00:13:48.300
which I think is a bit of a, kind of a, a dirty secret in crispr,

254
00:13:48.300 --> 00:13:52.500
that we do these off-target predictions all the time using fantastic web tools

255
00:13:52.500 --> 00:13:55.300
that have been set up. Mm-hmm. But they're all against the reference genome. Um,

256
00:13:55.360 --> 00:13:58.500
and the reference genome is not the genome that you've got in your IPCs or in

257
00:13:58.500 --> 00:14:01.660
your stem cells are are, or the cells or the mouse you are working with. Mm-hmm.

258
00:14:02.040 --> 00:14:06.400
Um, so those predictions are gonna be largely inaccurate. Um, you know,

259
00:14:06.580 --> 00:14:09.560
to a degree inaccurate, I should say, not largely inaccurate. Uh,

260
00:14:09.660 --> 00:14:12.000
and I suppose the case of dig looking for them, um,

261
00:14:12.300 --> 00:14:14.800
and you can spend an awful of time effort going looking for them.

262
00:14:15.300 --> 00:14:18.360
So those kind of suggestions you just made there about making your knockout

263
00:14:18.360 --> 00:14:21.760
cells with one guide r n a, and then repeating the experiment,

264
00:14:21.820 --> 00:14:24.000
but using a different guide down there to make the same knockout.

265
00:14:24.260 --> 00:14:26.880
That's a really nice control. Uh, and I think that's, that,

266
00:14:26.880 --> 00:14:30.480
that will solve a lot of those problems. Mm-hmm. I do disagree with you.

267
00:14:30.700 --> 00:14:33.960
Is this something we should be worrying about largely because these days,

268
00:14:34.180 --> 00:14:36.920
you know, we can design the guides pretty well. Mm-hmm. Uh,

269
00:14:37.020 --> 00:14:41.520
we can deliver them using r and p. We touched on this in the first question.

270
00:14:42.220 --> 00:14:44.520
So that window of expression is really limited.

271
00:14:45.180 --> 00:14:49.200
That's been proven to reduce the likelihood of off targeting as well. Uh,

272
00:14:49.300 --> 00:14:53.200
and as you say, whenever you culture your cells, every time you massage them,

273
00:14:53.220 --> 00:14:54.760
you'll have more mutations in there.

274
00:14:55.220 --> 00:14:59.480
And that background de novo mutation rate will be ha probably higher

275
00:15:00.030 --> 00:15:03.960
than the induced mutation rate you're gonna get from Crispr Cass nine. Exactly.

276
00:15:03.960 --> 00:15:07.760
Um, it's something that we never used to worry about. Um, and these days we do,

277
00:15:08.080 --> 00:15:10.880
I mean, speaking from the perspective of the mouse community mm-hmm.

278
00:15:10.880 --> 00:15:15.000
People've been making mouse models using mouse enbr stem cells for 30 years.

279
00:15:15.500 --> 00:15:19.120
And we know they acquired mutations in culture. Um, but at the end of it,

280
00:15:19.120 --> 00:15:22.720
we hope to get the mouse model we wanted and then, you know, work from there.

281
00:15:22.940 --> 00:15:27.120
Mm-hmm. And, you know, no one really concerned themselves with, with those, um,

282
00:15:27.940 --> 00:15:30.120
issues, I suppose where mouse concerned,

283
00:15:30.620 --> 00:15:33.840
if you had a chromosomal rearrangement and then an abnormal karyotype,

284
00:15:33.840 --> 00:15:35.400
then you would not get a germline transmission.

285
00:15:35.540 --> 00:15:37.960
The mouse would not be able to breathe forward. Mm-hmm. Uh,

286
00:15:38.060 --> 00:15:39.480
but generally speaking, you know,

287
00:15:39.500 --> 00:15:42.400
it wasn't something people worried about at the editing stage. Uh,

288
00:15:42.500 --> 00:15:45.720
it was something people worried about at the breeding stage. So yeah,

289
00:15:45.840 --> 00:15:48.200
I think on balance off tag,

290
00:15:48.230 --> 00:15:51.840
it's a probably not as big a problem as people first worried about, you know,

291
00:15:51.840 --> 00:15:55.240
things have improved an awful lot in the techniques and the way we approach

292
00:15:55.240 --> 00:15:58.360
things. But I completely agree that when you're talking with the clinic,

293
00:15:58.500 --> 00:16:00.640
you're talking about, you know, patients, you know,

294
00:16:00.640 --> 00:16:03.880
what may be a really good guide r n a for one person in a therapeutic setting.

295
00:16:03.900 --> 00:16:06.240
It may not be a good guide down there for someone else.

296
00:16:06.540 --> 00:16:10.800
And maybe in the future we'll see, uh, pre-screening,

297
00:16:10.800 --> 00:16:12.120
like say whole genome sequencing,

298
00:16:12.120 --> 00:16:15.320
that kind of thing established to make sure that, uh,

299
00:16:15.440 --> 00:16:18.600
a treatment for one person is also gonna be safe in a second person as well.

300
00:16:19.060 --> 00:16:19.550
Mm-hmm.

301
00:16:19.550 --> 00:16:20.440
Yeah, absolutely.

302
00:16:21.400 --> 00:16:25.480
Excellent. Uh, okay, so let's have a look at the next questions. Uh,

303
00:16:25.540 --> 00:16:29.360
so we've done the off targets, now we've done a bit of delivery. Um,

304
00:16:32.330 --> 00:16:34.420
yeah, so I suppose this question here, pier, um,

305
00:16:35.010 --> 00:16:38.500
what can you do about guidewire air design if you cannot decrease off targets?

306
00:16:38.500 --> 00:16:38.860
Now?

307
00:16:38.860 --> 00:16:41.540
I suppose it probably relates more to maybe a gene knocking that kind of thing.

308
00:16:42.170 --> 00:16:44.060
Yeah, yeah, exactly.

309
00:16:44.380 --> 00:16:47.380
'cause that's where you are much more limited if you want to knock something in,

310
00:16:47.400 --> 00:16:49.900
in specific place, or if you want Yeah, exactly.

311
00:16:49.960 --> 00:16:54.620
Do a snip or something like that. Uh, again, um, it's basically the same.

312
00:16:54.620 --> 00:16:57.820
Then you basically have to do it. If you're really concerned,

313
00:16:57.850 --> 00:17:00.500
then you have to do it with another guide as well. So,

314
00:17:00.840 --> 00:17:04.660
and if there are not another guy, let's, there isn't another one,

315
00:17:04.660 --> 00:17:08.380
there is just one and that one has high of target risks,

316
00:17:08.970 --> 00:17:13.950
well then, then you have to see where they are and you have to look,

317
00:17:14.610 --> 00:17:18.070
uh, in like maybe via P C R or some other method,

318
00:17:18.090 --> 00:17:22.630
you have to actually look in your cells if you have an edit in those, uh,

319
00:17:22.630 --> 00:17:23.950
in those locations or not.

320
00:17:24.490 --> 00:17:29.310
And then you have to decide whether or not those locations according to

321
00:17:29.310 --> 00:17:32.590
your knowledge, could cause a problem. Of course, uh,

322
00:17:32.690 --> 00:17:35.350
you don't really know that. I mean, people are like, oh, it's not in the Exxon,

323
00:17:35.350 --> 00:17:36.590
it's fine. But I mean, I used to,

324
00:17:36.790 --> 00:17:39.990
I worked a little bit with transposable elements and things, so you know, it,

325
00:17:40.010 --> 00:17:43.870
it, there is no such thing as a safe locus really, but I mean,

326
00:17:43.870 --> 00:17:47.550
so you just have to make an, an assumption like this is going to be okay.

327
00:17:47.570 --> 00:17:51.200
But also just because there are off predictions doesn't mean that it's cuts

328
00:17:51.200 --> 00:17:55.960
there. Uh, so you can look at the ones that are look seems most scary and,

329
00:17:56.060 --> 00:17:59.360
and look there if it actually has cut. But the thing here also is to,

330
00:17:59.460 --> 00:18:00.720
as Anthony also said,

331
00:18:01.060 --> 00:18:04.800
to limit the amount of time that the Cass nine is in there. So here,

332
00:18:05.280 --> 00:18:09.760
r and p is, is really a good way to go because then the less time it's in there,

333
00:18:10.770 --> 00:18:13.150
uh, the less of target, the fewer of targets you're gonna have.

334
00:18:13.650 --> 00:18:16.470
So I think that's the, the two ways about that.

335
00:18:17.100 --> 00:18:17.390
I'll,

336
00:18:17.390 --> 00:18:20.070
I'll just expand on that by r and p because both of you and I have said it quite

337
00:18:20.070 --> 00:18:22.630
a lot. And just for anyone watching that's Oh, yes, familiar. Uh,

338
00:18:22.630 --> 00:18:25.430
this is the rib nucleo protein method. Um,

339
00:18:25.430 --> 00:18:27.510
we talk about delivery modalities quite a lot.

340
00:18:27.540 --> 00:18:31.390
This is essentially rather than genetically encode the Cass nine and guide r a

341
00:18:31.390 --> 00:18:35.110
and say a plasmid or a virus, we simply buy Cass nine protein from a company.

342
00:18:35.330 --> 00:18:38.590
We buy the guide r n a from a company, we mix 'em together in a test tube,

343
00:18:38.590 --> 00:18:41.510
and that's what we transfect. So it's just the r n A and the protein.

344
00:18:41.970 --> 00:18:46.590
And as PIs highlighted, really, uh, uh, efficient, um, delivery method,

345
00:18:47.010 --> 00:18:51.750
really small window of expression and very high ONT tag activity and

346
00:18:51.750 --> 00:18:54.750
reduced off tag activity as well. And I'll, I'll be honest with you,

347
00:18:55.130 --> 00:18:57.150
we use this method across the board. I, I,

348
00:18:57.230 --> 00:19:01.390
I don't think there's many circumstances at all these days where we use some of

349
00:19:01.390 --> 00:19:05.470
the other delivery methods. It's pretty much r and p all the time for us. Um,

350
00:19:06.170 --> 00:19:09.070
I'm gonna go back to what you said about, you know, detecting those off targets.

351
00:19:09.090 --> 00:19:12.550
So you mentioned, you know, you can do P C r, you can do sequencing,

352
00:19:12.550 --> 00:19:13.383
that kind of thing.

353
00:19:14.690 --> 00:19:17.750
One of the challenges I think that's out there is there are some types of off

354
00:19:17.750 --> 00:19:21.790
targets that might be a chromosome translocation or a big deletion,

355
00:19:21.940 --> 00:19:25.070
that kind of thing. And they're a lot more difficult to detect Aren. I mean,

356
00:19:25.070 --> 00:19:26.310
how would you go about looking for those?

357
00:19:26.410 --> 00:19:27.990
Or would you even bother looking for those?

358
00:19:28.790 --> 00:19:32.910
Hmm, yeah. I mean, I think, uh, in the end, uh, once you're done, like,

359
00:19:32.910 --> 00:19:36.670
you know, you have, you, you need to check the karyotype, uh, and, uh,

360
00:19:36.730 --> 00:19:41.430
you can do that by molecular karyotyping or, or GB banding.

361
00:19:41.570 --> 00:19:42.670
And I think, uh,

362
00:19:43.670 --> 00:19:46.830
a lot of people suggest that you need to do both because they're not detecting

363
00:19:46.830 --> 00:19:48.590
the same things. Uh, I mean,

364
00:19:48.590 --> 00:19:52.590
this is in particular with I P s where we're very concerned about the fact that

365
00:19:52.590 --> 00:19:57.390
they have to, to stay completely the same. Um, so,

366
00:19:57.490 --> 00:20:00.710
so that one, it's one way to, to look for it. Um,

367
00:20:02.520 --> 00:20:04.050
what was the second part of your question?

368
00:20:04.310 --> 00:20:06.970
Uh, things like chromosome, well, obviously you've launched deletion,

369
00:20:06.970 --> 00:20:08.610
the chromosome translocations essentially. Oh, yes.

370
00:20:08.720 --> 00:20:11.090
Yeah, yeah, that's right. Yeah. So a lot of things you will see there.

371
00:20:11.150 --> 00:20:13.130
But what you also need to check, actually, uh,

372
00:20:13.350 --> 00:20:15.970
or maybe this is something that's come up recently, is this, uh,

373
00:20:15.970 --> 00:20:20.010
there was a paper showing that a lot of the things that we think are homozygous

374
00:20:20.180 --> 00:20:24.530
edits are actually hemizygous edits. So one part,

375
00:20:24.560 --> 00:20:26.370
like one let's just be cut out.

376
00:20:26.750 --> 00:20:30.130
And obviously for a lot of things that could cause problems,

377
00:20:30.130 --> 00:20:32.650
for some things maybe not, maybe it doesn't matter, it depends on where it is.

378
00:20:33.030 --> 00:20:35.810
But then what you can do there is that you have to find a way to,

379
00:20:35.970 --> 00:20:36.850
to look for that as well.

380
00:20:36.870 --> 00:20:41.690
And often this type of snip arrays that molecular karyotyping, uh,

381
00:20:42.200 --> 00:20:45.170
will find that, uh, the, the carrier,

382
00:20:45.280 --> 00:20:49.240
like G GB banding will probably not find it, but the other ones might find it.

383
00:20:49.580 --> 00:20:51.800
But if you're specifically, you know,

384
00:20:51.820 --> 00:20:56.520
you can look around your edit site and you have to do some sort of serial

385
00:20:57.600 --> 00:20:59.040
quantitative P C R,

386
00:20:59.040 --> 00:21:03.760
either digital droplet or some other quantitative way or some genome

387
00:21:03.770 --> 00:21:05.520
sequencing. If you do N G s,

388
00:21:05.520 --> 00:21:08.840
you can do paired sequencing and then you should see the difference. Um,

389
00:21:09.340 --> 00:21:11.560
we don't know how common it is anymore. I mean,

390
00:21:11.580 --> 00:21:13.880
in that paper they showed that it was quite common,

391
00:21:14.300 --> 00:21:18.440
but the majority of that was happening when you delivered Cass nine with the

392
00:21:18.440 --> 00:21:20.440
plasmid. But I mean, uh,

393
00:21:20.600 --> 00:21:24.240
a couple of of these networks are like the core U stem, for example.

394
00:21:24.380 --> 00:21:27.480
We have different core, uh, facilities that work with I P Ss, uh,

395
00:21:27.550 --> 00:21:28.920
have gathered in Europe. And,

396
00:21:29.870 --> 00:21:33.810
and what we're gonna do there is that we're gonna look at all our lines and see

397
00:21:33.870 --> 00:21:37.010
if we can actually detect this in any of them. And the, uh,

398
00:21:37.010 --> 00:21:40.690
with the ones that are made with r and p, for example, if it's a small change,

399
00:21:41.430 --> 00:21:44.570
um, then we will see if we can detect it anywhere. So may,

400
00:21:44.750 --> 00:21:48.970
if it is a concern or something that needs to be introduced to the standard, uh,

401
00:21:48.970 --> 00:21:52.930
quality control, uh, sort of, uh, panel or not.

402
00:21:53.030 --> 00:21:56.330
So that's something we are gonna look into a little bit. When you use plasmid,

403
00:21:56.330 --> 00:21:57.410
there's a bigger risk for sure,

404
00:21:57.470 --> 00:22:02.010
but often that means that you often want to introduce something that is

405
00:22:02.270 --> 00:22:06.410
he heterozygous anyway. Uh, and in that case, you of course sort of,

406
00:22:07.350 --> 00:22:09.960
yeah, often when you see that it's heterozygous, that's good,

407
00:22:10.310 --> 00:22:12.480
that means that you have the other alleles still there.

408
00:22:12.860 --> 00:22:14.840
So maybe that's the way to go also with, uh,

409
00:22:14.840 --> 00:22:18.360
with big insertions that you go for the heterozygous 'cause then you know that

410
00:22:18.360 --> 00:22:19.240
the other one is still there.

411
00:22:20.160 --> 00:22:22.360
It's a little bit tricky because normal sequencing,

412
00:22:22.360 --> 00:22:24.480
like a normal sango sequencing will not detect it.

413
00:22:24.480 --> 00:22:28.000
It just looks like it's homozygous, but in reality it's, uh, it's homozygous.

414
00:22:28.100 --> 00:22:30.320
So that's a big new thing that has happened.

415
00:22:30.660 --> 00:22:33.040
But that's like a weird thing 'cause it's sort of not really an off target.

416
00:22:33.190 --> 00:22:35.080
It's an toxic on target. Yeah,

417
00:22:35.320 --> 00:22:37.800
Absolutely. Yeah. No, it's, it's fascinating to hear you say that.

418
00:22:38.040 --> 00:22:40.400
Obviously this is still a relatively new field and mm-hmm.

419
00:22:40.550 --> 00:22:41.680
It's great to hear that, you know,

420
00:22:41.680 --> 00:22:44.840
these communities are getting together to establish what is the quality of

421
00:22:44.840 --> 00:22:46.720
control, what should we be looking for? Yes.

422
00:22:46.820 --> 00:22:49.440
And I certainly don't think that's set in stone yet. Um,

423
00:22:49.440 --> 00:22:52.240
and just to go back to the, this on target deletion, you know,

424
00:22:52.240 --> 00:22:54.920
this big deletion and wait, obviously it wipes out a primer site.

425
00:22:55.020 --> 00:22:59.280
So if you do a A P C I, you think, oh, I've got a homozygous, um,

426
00:23:00.140 --> 00:23:04.080
colony or homo homozygous mouse. And we've seen this a lot in mice as well.

427
00:23:04.140 --> 00:23:04.960
Mm-hmm. And of course,

428
00:23:04.960 --> 00:23:08.960
in mice it's actually easier to detect because when we have our founder mouse

429
00:23:09.020 --> 00:23:12.000
and we think, oh, we've got the homozygous point mutation, um,

430
00:23:12.500 --> 00:23:14.160
we breed it forward with the wild type mouse,

431
00:23:14.460 --> 00:23:17.480
and we only see the point mutation in half the, the litter.

432
00:23:17.740 --> 00:23:21.040
So clearly we know that, um, it was not homozygous founder,

433
00:23:21.180 --> 00:23:22.280
it was probably heterozygous,

434
00:23:22.280 --> 00:23:24.840
and we just were not detecting that change as well. Mm-hmm. Uh,

435
00:23:24.840 --> 00:23:28.040
so I think actually in, in the mouse community, this has been, uh,

436
00:23:28.110 --> 00:23:30.080
well observed for, for a number of years now as well.

437
00:23:30.660 --> 00:23:33.600
And now we are seeing it as well that in people that working cell lines,

438
00:23:34.400 --> 00:23:35.040
I have to say, you know,

439
00:23:35.040 --> 00:23:38.120
sometimes it's easier to make a mouse than it's to make a cell line because we

440
00:23:38.120 --> 00:23:40.960
can breed out a lot. You know, if we have potential words for off targets,

441
00:23:40.980 --> 00:23:44.800
we can breed them away. If we want to have, um, homozygous or heterozygous,

442
00:23:44.820 --> 00:23:49.160
we can establish our breeding pattern in such a way to get those genotypes. Uh,

443
00:23:49.220 --> 00:23:52.000
and obviously we can't do that with cells in a dish. So Yeah,

444
00:23:52.000 --> 00:23:54.680
in some ways it's actually easier these days to make a mouse than it's to make a

445
00:23:54.840 --> 00:23:58.280
modified cell line. It's a bit counterintuitive. Yeah. Um, yeah. Uh, but yeah,

446
00:23:58.280 --> 00:24:00.320
it's fantastic to hear about, you know, the, these, um,

447
00:24:00.500 --> 00:24:02.520
new drives to make sure the quality controls there.

448
00:24:02.640 --> 00:24:06.240
'cause I think ultimately we talk about CRISPR allowing us to make better

449
00:24:06.240 --> 00:24:07.073
models,

450
00:24:07.100 --> 00:24:10.000
we have to make sure that those better models are what we think they are in the

451
00:24:10.000 --> 00:24:10.660
first place.

452
00:24:10.660 --> 00:24:12.400
Oh, yes, absolutely. Hmm.

453
00:24:12.990 --> 00:24:15.680
Okay. Uh, so let's move on to the next question. So, um,

454
00:24:16.450 --> 00:24:18.160
we've got a question here asking, um,

455
00:24:18.620 --> 00:24:23.080
how is CRISPR different from R and AI as a technique? Um, and you know,

456
00:24:23.540 --> 00:24:25.910
whether or not you should choose CRISPR over RNAi?

457
00:24:26.660 --> 00:24:28.070
Yeah. Should I,

458
00:24:28.490 --> 00:24:29.710
Uh, yeah, please go for it. Yeah.

459
00:24:30.970 --> 00:24:33.790
Um, so the general idea is that, uh,

460
00:24:34.480 --> 00:24:38.990
there are fewer of targets with CRISPR eye than there is with, uh,

461
00:24:39.460 --> 00:24:44.190
RNAi or or other r n a, the other r n A type, uh,

462
00:24:44.320 --> 00:24:46.190
small heins and so on. Um,

463
00:24:46.510 --> 00:24:51.030
there've been papers that show that the off targets are, uh, fewer.

464
00:24:51.950 --> 00:24:55.850
And also often the on target efficiency is higher. With crispr, I,

465
00:24:55.850 --> 00:24:58.490
we've actually had several, uh,

466
00:24:59.090 --> 00:25:01.810
occasions where we've had complete turning off. I mean,

467
00:25:01.810 --> 00:25:03.770
that depends if that's something you want or not, you know,

468
00:25:03.770 --> 00:25:06.130
if you just want reduction or if you want it off.

469
00:25:06.430 --> 00:25:07.890
But we've had it off several times.

470
00:25:07.960 --> 00:25:12.130
Like actually we see that the activation peak when we look for, um,

471
00:25:12.540 --> 00:25:15.890
stone modifications is actually disappearing. Uh,

472
00:25:15.910 --> 00:25:18.650
and also we don't see any R n A and RNA-seq,

473
00:25:18.670 --> 00:25:22.050
but I thought the activation peak is gone, uh, is, is pretty cool actually.

474
00:25:22.390 --> 00:25:25.730
So sometimes it's completely off. So it depends on what you want a little bit.

475
00:25:25.830 --> 00:25:27.970
But, um, generally, uh, yeah,

476
00:25:28.140 --> 00:25:31.410
maybe higher efficiency and fewer of targets with CRISPR eye.

477
00:25:32.360 --> 00:25:36.510
So in terms of CRISPR eye, um, if you tag,

478
00:25:36.690 --> 00:25:41.270
say an essential gene and you want to remove that, uh, with crispy,

479
00:25:41.270 --> 00:25:42.630
you can't really do that, can you? Because you,

480
00:25:42.650 --> 00:25:45.270
if you knock out an essential gene, you're gonna kill the cells. Yeah.

481
00:25:45.270 --> 00:25:46.310
But with crisp, but crisper,

482
00:25:46.310 --> 00:25:50.190
I have you experiences where you're able to reduce the level that gene so that

483
00:25:50.210 --> 00:25:53.270
the cell can tolerate this and survive, but it still drives a phenotype,

484
00:25:53.270 --> 00:25:54.230
something you can investigate.

485
00:25:54.970 --> 00:25:56.550
Yes. Crisp rise actually really,

486
00:25:56.550 --> 00:25:59.110
really good like that because you can actually dose it,

487
00:25:59.130 --> 00:26:02.030
you can do it with the amount of virus that you put in. Uh,

488
00:26:02.030 --> 00:26:05.190
so it's sort of dose dependent all, and also different guides like,

489
00:26:05.190 --> 00:26:08.750
so we decide the guide design the guides within a certain region,

490
00:26:09.290 --> 00:26:11.230
and often there's one that just doesn't work as well.

491
00:26:11.370 --> 00:26:14.430
So then you can use that one. So it's actually quite good.

492
00:26:14.450 --> 00:26:17.790
You choose maybe three different ones and you can choose different amounts of

493
00:26:17.790 --> 00:26:22.630
your, um, of your virus as well. And then you can totally dose it.

494
00:26:23.810 --> 00:26:25.690
Excellent. No, it's fascinating. So, you know,

495
00:26:25.890 --> 00:26:29.370
RNA AI was around for a long time. Um, it's still a useful technology.

496
00:26:29.770 --> 00:26:34.610
I do tend to agree with you that it is being superseded a little bit by the

497
00:26:34.610 --> 00:26:37.330
CRISPR and CRISPR base technology that CRISPR eye. Um,

498
00:26:37.710 --> 00:26:41.290
but it is a useful complimentary assay to perform as well as the crispr. Um,

499
00:26:41.430 --> 00:26:42.970
so you know, if you get the same result from the,

500
00:26:43.000 --> 00:26:46.320
your RNA AI experiment as if from your CRISPR experiment, then you know,

501
00:26:46.460 --> 00:26:48.440
you are, you are onto a winning result basically.

502
00:26:48.520 --> 00:26:49.840
I think that's a good way of controlling

503
00:26:49.860 --> 00:26:50.720
For it. Exactly.

504
00:26:51.620 --> 00:26:52.960
Um, okay, the next question,

505
00:26:53.180 --> 00:26:56.760
can we use primary cells like human monocytes or is this only for cell lines?

506
00:26:57.220 --> 00:27:00.920
So I'll answer this because we've been doing a little bit of this. Um, yes,

507
00:27:00.940 --> 00:27:02.320
you absolutely can do. Um,

508
00:27:02.530 --> 00:27:05.200
there are obviously different challenges associated with different cell types.

509
00:27:05.660 --> 00:27:07.320
So with a cell line, generally speaking,

510
00:27:07.620 --> 00:27:10.680
you can deliver everything to that cell, then you can easily,

511
00:27:11.060 --> 00:27:12.000
for most cell lines,

512
00:27:12.070 --> 00:27:14.680
isolate a clone from that cell line and grow it up in assay.

513
00:27:14.680 --> 00:27:15.560
Has that got the change?

514
00:27:15.940 --> 00:27:18.760
You're not gonna be able to do that in the same way with primary cells.

515
00:27:19.100 --> 00:27:21.240
And our experience is, generally speaking,

516
00:27:21.240 --> 00:27:25.360
what we like to try and do is first of all, optimize the delivery, so get crisp,

517
00:27:25.360 --> 00:27:29.240
but working as well as we possibly can do in that primary cell line. Mm-hmm.

518
00:27:29.240 --> 00:27:32.520
And then once we've got that, we'll maybe screen guide RNAs and we'll say, well,

519
00:27:32.520 --> 00:27:35.440
this g a is really active and knocking the gene out, maybe this one isn't.

520
00:27:35.660 --> 00:27:38.200
And we'll do that kind of similar thing that you just said there.

521
00:27:38.340 --> 00:27:42.320
We get a knockdown population of cells where we may reduce the protein

522
00:27:42.320 --> 00:27:46.360
expression level overall to nine, you know, to, to less than, um,

523
00:27:46.620 --> 00:27:49.240
10% of the original amount of protein. And again,

524
00:27:49.300 --> 00:27:51.160
if that's enough to drive a phenotype,

525
00:27:51.160 --> 00:27:54.600
if that's enough to make the cells change their behaviors,

526
00:27:54.600 --> 00:27:57.480
and you can measure that change in behavior, then that's sufficient.

527
00:27:58.100 --> 00:27:59.040
But absolutely,

528
00:27:59.140 --> 00:28:03.120
it is more challenging to work in primary cells than it's in cell lines. Uh,

529
00:28:03.140 --> 00:28:07.120
but you can do it. Um, if you are new to CRISPR and you haven't done it before,

530
00:28:07.480 --> 00:28:10.680
I would not recommend jumping straight into primary cells. I would recommend,

531
00:28:10.680 --> 00:28:14.200
you know, let's get the technique established in a surrogate model system first.

532
00:28:14.300 --> 00:28:16.680
You know, you mentioned human monocytes. There,

533
00:28:16.680 --> 00:28:20.000
there are monocyte cell lines out there, like TP one. Mm-hmm. Uh,

534
00:28:20.440 --> 00:28:22.560
U nine 30 sevens as well, I think. Uh,

535
00:28:22.580 --> 00:28:25.280
and we've successfully applied crispr both these cell lines and there's

536
00:28:25.280 --> 00:28:28.600
published protocols out there. So that would be my recommendation. Um,

537
00:28:29.120 --> 00:28:31.600
p i I don't hear you got any experience with, with primary cells as well?

538
00:28:32.300 --> 00:28:34.600
Yes. Not hands-on, but I have designed, uh,

539
00:28:34.670 --> 00:28:36.760
experiments for people with primary cells and,

540
00:28:36.760 --> 00:28:39.800
and there is really important to have a good, uh, communication first.

541
00:28:39.820 --> 00:28:43.480
So you ask them exactly what is it that you want and what is the timeline here?

542
00:28:43.560 --> 00:28:46.080
I mean, I had somebody's like, yeah, we take the cells out of the,

543
00:28:46.540 --> 00:28:49.640
out of the mouth and then we have like seven days and then that's it, you know,

544
00:28:49.640 --> 00:28:52.880
something like that. So I'm like, okay, so we have to use r and p.

545
00:28:52.880 --> 00:28:54.640
There's nothing else that has enough time.

546
00:28:54.700 --> 00:28:58.480
You have to maybe be able to sort them because you can also use Cass nine that

547
00:28:58.480 --> 00:28:59.880
is like tagged or something like that.

548
00:28:59.900 --> 00:29:03.040
So at least you increase the ones that actually has the,

549
00:29:03.260 --> 00:29:07.320
the components in there, even if it hasn't necessarily cut. And, and, uh,

550
00:29:07.540 --> 00:29:09.520
and so you have to really talk about what's possible.

551
00:29:09.580 --> 00:29:13.240
And then exactly like you said, they have to set up the experiment first,

552
00:29:13.310 --> 00:29:15.600
like sort of trial version, you know,

553
00:29:15.600 --> 00:29:18.320
like try it and see if you can get the cells in there.

554
00:29:18.340 --> 00:29:21.440
And also look in the literature a lot, what works for your cells?

555
00:29:21.460 --> 00:29:22.800
And this is always the thing I'm like,

556
00:29:23.160 --> 00:29:25.480
I cannot really tell you how to live deliver it.

557
00:29:25.480 --> 00:29:29.480
You have to look into is it best with nuclear affection or is it lipo perfection

558
00:29:29.480 --> 00:29:32.360
we are gonna use and, and see if other people have used it.

559
00:29:32.360 --> 00:29:36.840
Then you take that protocol and, and you, you try it and exactly.

560
00:29:36.900 --> 00:29:39.680
Try different guides and things like that. But, but that particular one,

561
00:29:39.680 --> 00:29:43.560
it worked really well. They just sort of of did it and, and, uh, it worked. And,

562
00:29:43.560 --> 00:29:46.760
and that's the thing also, sometimes you just have to try. Yeah, absolutely.

563
00:29:46.760 --> 00:29:49.880
And be prepared for then do method development if it doesn't work, because this,

564
00:29:49.960 --> 00:29:52.720
I often say if it doesn't work, just come back to me.

565
00:29:52.720 --> 00:29:54.480
There are so many other options, like,

566
00:29:54.480 --> 00:29:57.000
there are so many other things you can do, so we can try something else,

567
00:29:57.100 --> 00:30:00.920
but this is what I, you know, sort of think might be the best one to try first.

568
00:30:01.220 --> 00:30:02.880
But it is also important, like you say,

569
00:30:02.880 --> 00:30:06.320
that you might not need a hundred percent of the cells being like edited either.

570
00:30:06.320 --> 00:30:10.000
Like sometimes people want to put back and, uh, cells into the animal and stuff,

571
00:30:10.300 --> 00:30:12.600
and I'm like, maybe it doesn't matter if like,

572
00:30:12.860 --> 00:30:15.920
as long as like maybe 80% of the cells show this phenotype,

573
00:30:15.940 --> 00:30:19.840
you will see a difference from wild type transplants, for example. So, uh,

574
00:30:19.860 --> 00:30:23.000
you know, you don't have to be a hundred percent, a lot of things is,

575
00:30:23.020 --> 00:30:25.880
is good enough, you know, and you will see the, the change anyway.

576
00:30:26.300 --> 00:30:28.440
So, and that's a, that's a really interesting point you made there. 'cause,

577
00:30:28.440 --> 00:30:29.720
and I, and I don't know how I feel about this,

578
00:30:29.720 --> 00:30:32.880
but I spoke to some people in the cancer community who when they're doing

579
00:30:32.890 --> 00:30:34.760
xenografts and they're editing cells, the dish,

580
00:30:34.760 --> 00:30:36.320
they don't want clonal cell lines.

581
00:30:36.320 --> 00:30:39.320
They don't want a hundred percent knockout because cancer is a heterogeneous

582
00:30:39.320 --> 00:30:42.880
disease. So they sometimes prefer to have, you know,

583
00:30:42.880 --> 00:30:46.760
50 or 60% knockout and then graph that, uh, into, into the mice,

584
00:30:47.020 --> 00:30:49.400
and then they can see what happens over time with,

585
00:30:49.400 --> 00:30:53.880
with the respective populations of know the wild type cells versus the mutated

586
00:30:53.880 --> 00:30:56.360
cells. Mm-hmm. So yeah, it, it's, it's,

587
00:30:56.360 --> 00:30:59.680
it's that experimental design all the time and you design the experiment to suit

588
00:30:59.680 --> 00:31:01.960
the model you're working with and what you're actually trying to find out.

589
00:31:02.100 --> 00:31:04.480
Mm-hmm. And you made the part about delivery there as well. The,

590
00:31:04.480 --> 00:31:08.600
the following question really nicely feeds into that regarding the delivery.

591
00:31:08.940 --> 00:31:12.400
Do you recommend transfect lipectomy or nuclei affection instead of vial

592
00:31:12.400 --> 00:31:14.840
transduction? Uh, and I think you've already answered it.

593
00:31:15.220 --> 00:31:17.360
You have to do it depending on your cell. You know,

594
00:31:17.360 --> 00:31:20.720
you optimize this based on what you're working with. Uh,

595
00:31:20.720 --> 00:31:21.920
typically I would say we,

596
00:31:22.380 --> 00:31:25.760
we generally speaking use nuclear affection rather than lip perfection. Mm-hmm.

597
00:31:25.760 --> 00:31:28.880
But there are certain, some cell lines we work with that prefer lip perfection.

598
00:31:29.680 --> 00:31:31.680
I assume if you are working in stem cells,

599
00:31:31.860 --> 00:31:33.360
you are all nuclear fiction all the time.

600
00:31:33.930 --> 00:31:36.440
We're Yeah, not always.

601
00:31:36.460 --> 00:31:38.120
May may, maybe not, maybe not. Well,

602
00:31:38.220 --> 00:31:40.000
We are, we are not very good at, uh,

603
00:31:40.060 --> 00:31:44.920
at using like with big plasmids to put in and if nucle infection is working.

604
00:31:45.060 --> 00:31:47.600
So, so it is working, but we're trying to optimize that.

605
00:31:47.620 --> 00:31:51.240
So what we're trying to do now is actually optimize the system where we need

606
00:31:51.240 --> 00:31:52.800
both R and p and a plasmid,

607
00:31:52.800 --> 00:31:55.840
because it's the big construct to maybe do lipo perfection first,

608
00:31:55.900 --> 00:31:59.560
and then we'll wait and then do the nuclear affection for the r p uh,

609
00:31:59.800 --> 00:32:03.520
'cause the, the timeline is different between those components and, uh, yeah.

610
00:32:03.620 --> 00:32:06.120
So it, but mostly nuclear affection,

611
00:32:06.140 --> 00:32:08.080
but with a little bit of lipo perfection as well.

612
00:32:08.540 --> 00:32:11.720
So you stagger the delivery, so you made you, well, yeah, so you,

613
00:32:11.720 --> 00:32:14.920
you'll put the, the d n a donor in at different times to the Cass nine,

614
00:32:14.920 --> 00:32:15.760
the guide r n a,

615
00:32:16.430 --> 00:32:17.240
This is our plan,

616
00:32:17.240 --> 00:32:21.840
this is my key plan because we did it all together and it worked. But, uh,

617
00:32:21.980 --> 00:32:25.760
an extremely low efficiency. Okay. So I'm like, if it, if they're not green,

618
00:32:25.950 --> 00:32:27.880
then we cannot use this, right? Like if,

619
00:32:28.060 --> 00:32:32.120
and it's of course not all edits that turn on, uh, immediately in the I P S,

620
00:32:32.460 --> 00:32:36.480
so we have to find a better system. And that was my thinking was that, you know,

621
00:32:36.480 --> 00:32:39.160
if you nuclear effect something, the R N P is ready to go,

622
00:32:39.580 --> 00:32:43.920
the plasmid needs to be amplified first, so by the time it's amplified,

623
00:32:43.920 --> 00:32:47.360
the r p is gone. So I'm thinking if we put in the plasmid first, uh,

624
00:32:47.420 --> 00:32:48.480
but we'll see how that goes.

625
00:32:49.420 --> 00:32:51.840
No, we did that in one cell line several years ago, and it did work,

626
00:32:51.900 --> 00:32:54.560
but I'm not gonna claim it was the perfect setup because we didn't do a

627
00:32:54.560 --> 00:32:57.680
comparison with it all at the same time. So Yeah. Yeah, it definitely does work.

628
00:32:57.950 --> 00:33:00.160
It's interesting you say that though, about staggering the delivery,

629
00:33:00.160 --> 00:33:03.720
because one thing we're currently trying in, in our mouse embryos,

630
00:33:03.720 --> 00:33:05.720
which we're a little bit behind the curve on, I'll admit,

631
00:33:06.220 --> 00:33:11.200
is to change the d n a donor from being d n A into being adeno associated virus.

632
00:33:11.460 --> 00:33:14.480
So we're actually using virus as the donor, and in that situation,

633
00:33:14.480 --> 00:33:17.320
we are staggering. So we infect the embryos, um,

634
00:33:17.870 --> 00:33:20.800
with the virus that contains the homology, insert homology,

635
00:33:21.340 --> 00:33:26.000
and then we leave that infection to, um, pursue for about six hours or so.

636
00:33:26.420 --> 00:33:29.480
And then we ate in the cast iron and the guide r n a.

637
00:33:29.480 --> 00:33:30.440
So it is a staggered delivery,

638
00:33:30.940 --> 00:33:34.880
of course with a a v The big advantage is that it, it's almost like a,

639
00:33:34.920 --> 00:33:37.600
a self delivering modality. You know, you don't need lip affection,

640
00:33:37.600 --> 00:33:38.800
you don't need nucle perfection.

641
00:33:39.070 --> 00:33:44.000
It's job as a virus is to infect cells and the ITRs and the a AAV drag

642
00:33:44.000 --> 00:33:47.040
it straight to the nucleus so the donor ends up in the nucleus where it needs to

643
00:33:47.040 --> 00:33:50.000
be as well. And that appears to be really, um, you know, our,

644
00:33:50.020 --> 00:33:53.160
our preliminary data is successful, so, you know,

645
00:33:53.160 --> 00:33:55.040
we're looking to expand it on more projects.

646
00:33:55.390 --> 00:33:58.040
I've heard from other people in the MA community that works really nicely.

647
00:33:58.600 --> 00:34:01.320
I think you, you can do it in cell lines as well. It does work in cells and,

648
00:34:01.320 --> 00:34:04.080
and, and stem cells. So that could be an alternative,

649
00:34:04.090 --> 00:34:05.240
still staggering the delivery,

650
00:34:05.460 --> 00:34:09.280
but just changing it from plasma D n A into being, uh, a viral D n A instead.

651
00:34:09.550 --> 00:34:10.140
Yeah,

652
00:34:10.140 --> 00:34:13.280
No, absolutely. And I think as, as you say, lots of people have used that,

653
00:34:13.300 --> 00:34:16.200
and I think it is a very nice method. The thing is, of course,

654
00:34:16.340 --> 00:34:20.760
you have to make also the AAV in between. So, and we do that,

655
00:34:21.300 --> 00:34:25.320
so it's okay, but I think when we are trying to produce quite many cell lines,

656
00:34:25.420 --> 00:34:29.760
uh, as a service, if we can get away from not doing that,

657
00:34:30.860 --> 00:34:35.800
and also because, I mean, the a v still stays in there also for a while. So,

658
00:34:36.220 --> 00:34:40.640
so we, I try to get away from that, but it is there as an opportunity to,

659
00:34:40.700 --> 00:34:44.440
to deal if we have something that turns very difficult to, to deliver or so,

660
00:34:44.440 --> 00:34:47.040
because it's a, it's a very smart way actually to have it.

661
00:34:47.040 --> 00:34:50.360
And then it's there at high levels and uh, as you say,

662
00:34:50.360 --> 00:34:54.080
it goes straight into the new. So it's, it's very clever in many ways, but yeah.

663
00:34:54.220 --> 00:34:55.600
Oh, I mean, you raised a really good point about,

664
00:34:55.600 --> 00:34:59.320
about those practical considerations that a, if you want to use AAV as a donor,

665
00:34:59.660 --> 00:35:02.560
is that a whole new range of skill sets you have to develop in the laboratory?

666
00:35:02.560 --> 00:35:06.880
And you guys are well set to do that? We, we are not, we don't package a aav,

667
00:35:06.880 --> 00:35:08.960
we make Len virus, but we don't make a a v. Mm-hmm.

668
00:35:08.960 --> 00:35:12.920
So we've ended up outsourcing our a AAV production for the these applications.

669
00:35:13.110 --> 00:35:16.760
Yeah. And for the mouse projects, it seems to be cost effective. Um,

670
00:35:17.330 --> 00:35:19.880
there is a big question mark of the whether or not we're gonna use this

671
00:35:19.880 --> 00:35:21.440
technology in our cell projects,

672
00:35:21.820 --> 00:35:23.920
but I strongly suspect it will not be cost effective there.

673
00:35:23.930 --> 00:35:28.200
We'll need more a A V and there'll be a greater investment. And like you say,

674
00:35:28.300 --> 00:35:31.960
if your plasma based approach works at, let's just say, you know,

675
00:35:32.190 --> 00:35:35.520
5% efficiency and the AAV boost after to 10%,

676
00:35:35.870 --> 00:35:38.800
well actually 5% you could probably work with, um, yeah. And you know,

677
00:35:38.800 --> 00:35:41.400
especially selection markers and that kind of thing in there as well.

678
00:35:41.940 --> 00:35:44.200
So is it worthwhile that investment? Uh,

679
00:35:44.200 --> 00:35:47.480
and there's also the other aspects of using virus and that you'll have to

680
00:35:47.640 --> 00:35:49.640
probably adhere to some local, uh,

681
00:35:49.940 --> 00:35:52.160
GM requirements and put some application for health and safety,

682
00:35:52.190 --> 00:35:54.840
that kind of thing. Um, and, you know, uh,

683
00:35:54.990 --> 00:35:58.520
that could be a bit of a pain at times for people if you just wanna do one

684
00:35:58.520 --> 00:36:02.080
experiment. So yeah, it's a great option to have, um, again,

685
00:36:02.080 --> 00:36:05.810
tailor it to your experiment and what you're trying to achieve. Okay.

686
00:36:05.830 --> 00:36:08.090
So the next, um, uh, question.

687
00:36:08.820 --> 00:36:10.770
We've taught an awful lot about knocking out genes here,

688
00:36:10.790 --> 00:36:13.210
but this is a question here. Is it possible to knock out a promoter?

689
00:36:14.770 --> 00:36:15.190
So,

690
00:36:15.190 --> 00:36:16.790
Yeah. Yeah. Pierre, do you wanna answer this one?

691
00:36:17.730 --> 00:36:22.350
No, um, uh, I mean, yeah, sure.

692
00:36:23.130 --> 00:36:26.710
Uh, I think the easiest way with, uh, promoter is to, uh,

693
00:36:27.410 --> 00:36:29.150
you have to use two guides. So you knock out,

694
00:36:29.180 --> 00:36:33.030
like you cut out the section so you don't try to make, uh,

695
00:36:33.850 --> 00:36:37.630
an indel because often it's much more complicated with promoters, right?

696
00:36:37.660 --> 00:36:40.830
It's not just one or two little things that changes it,

697
00:36:40.850 --> 00:36:42.750
but you have to cut with two guides,

698
00:36:43.500 --> 00:36:47.680
cut out the region that you think is the promoter and uh, and that should work.

699
00:36:48.590 --> 00:36:51.480
Yeah. So I mean, it's that, you know, it's that how long is a piece of string,

700
00:36:51.780 --> 00:36:53.400
uh, how big is the promoter? Uh,

701
00:36:53.580 --> 00:36:56.840
and so the where you're gonna position those gather ass, I agree with you,

702
00:36:56.900 --> 00:37:00.480
cut out the entire thing using two guide ass is, is probably the way to do it.

703
00:37:00.660 --> 00:37:03.120
Um, we've cut our enhancers before, but mm-hmm.

704
00:37:03.200 --> 00:37:06.760
Those enhancers are quite clear boundaries. You know, we knew from, um,

705
00:37:07.020 --> 00:37:11.680
the genome browser dataset where the enhancer very likely start and ended and

706
00:37:11.960 --> 00:37:13.600
'cause it was in a intergenic region,

707
00:37:14.380 --> 00:37:17.720
we could be a little bit relaxed about where our guide RNAs were designed.

708
00:37:17.860 --> 00:37:19.880
So that made it relatively simple.

709
00:37:20.580 --> 00:37:23.960
We also did it by putting in a removable selection marker. Uh,

710
00:37:23.980 --> 00:37:28.680
so we had a homology flanked to repair template that removed the entire three or

711
00:37:28.680 --> 00:37:33.520
four kilobase of enhancer and it had a pg k cure mycin gene in there

712
00:37:33.670 --> 00:37:35.360
that was all flanked by locks p science.

713
00:37:35.780 --> 00:37:38.960
So we could select for the cells that had the deletion. Mm-hmm.

714
00:37:39.060 --> 00:37:42.640
And then afterwards we could put pre recombination in those cells and remove

715
00:37:42.640 --> 00:37:43.800
that selection marker afterwards.

716
00:37:43.800 --> 00:37:48.650
So basically gluing the genome back together again, um, after the, the,

717
00:37:48.650 --> 00:37:52.250
the recombination to get rid of that enhancer. That worked really effectively.

718
00:37:52.390 --> 00:37:53.650
But in terms of promoters,

719
00:37:53.650 --> 00:37:57.890
if we're thinking in terms of the sequences that regulate gene, uh,

720
00:37:58.240 --> 00:38:00.770
gene activation that close to the gene of interest, you know,

721
00:38:00.770 --> 00:38:04.410
right next to the gene, then you're gonna be a bit careful about, you know,

722
00:38:04.410 --> 00:38:07.250
where you design those guide RNAs. 'cause you might mm-hmm. You know,

723
00:38:07.250 --> 00:38:10.050
you might make other disruptions as well. Yeah. Uh, that,

724
00:38:10.080 --> 00:38:13.090
that you don't wanna make. I suppose in, in that circumstance,

725
00:38:13.740 --> 00:38:17.410
would you prefer to go down the route using CRISPR eye where you can modulate

726
00:38:17.410 --> 00:38:19.170
the promoter rather than knock it out?

727
00:38:19.560 --> 00:38:22.850
Yeah, exactly. I'm thinking that also like how often, I mean,

728
00:38:23.080 --> 00:38:25.930
it's not so often that you just want to get rid of the promoter,

729
00:38:25.930 --> 00:38:28.250
but then also have the rest of the gene intact. I mean,

730
00:38:28.490 --> 00:38:32.970
I suppose that could happen, but, uh, then if you, I don't know.

731
00:38:32.990 --> 00:38:35.320
I'm trying to think of a reason to do that, but I mean,

732
00:38:35.320 --> 00:38:37.080
if you want to like exchange to promoter,

733
00:38:37.080 --> 00:38:38.600
then that's sort of easier in a way actually.

734
00:38:38.720 --> 00:38:42.880
'cause then you just do homology directed repair there. But, uh, exactly.

735
00:38:42.900 --> 00:38:46.360
If you wanna keep the, keep it intact, uh, then it's quite hard. Exactly.

736
00:38:46.430 --> 00:38:49.920
Then you have to just cut and be hoping that your guide cuts in a very

737
00:38:49.920 --> 00:38:53.680
predictable way, uh, around there. Um, but yeah,

738
00:38:53.740 --> 00:38:56.840
crispr eye for sure there as well. Then, then you just sort of turn it off.

739
00:38:56.860 --> 00:38:58.960
But if, if it's just a turn off that you want,

740
00:38:58.960 --> 00:39:00.360
then you can do that in other ways.

741
00:39:00.380 --> 00:39:03.400
You can just cut out the transcription start site and, and things like that.

742
00:39:03.400 --> 00:39:07.600
That is much easier. So it depends on if, if you're studying promoters yes,

743
00:39:07.600 --> 00:39:08.640
then you have to do it and then,

744
00:39:09.060 --> 00:39:13.560
but then one can also do it homology repair thing actually there where you cut

745
00:39:13.580 --> 00:39:16.760
and then you put in a nonsense sequence or something like that. So

746
00:39:16.830 --> 00:39:19.560
Yeah, absolutely disappear As, and again, I,

747
00:39:20.140 --> 00:39:21.360
the question isn't phrased it this way,

748
00:39:21.380 --> 00:39:24.800
but suppose maybe you're interested in a particular transcription factor bin.

749
00:39:24.800 --> 00:39:28.000
Any site in the promoter you've already determined and you want to know how the

750
00:39:28.000 --> 00:39:30.920
gene turns are off, then yeah, you could do maybe, uh,

751
00:39:31.040 --> 00:39:35.360
a single guide r a in indel to disrupt that binary sequence to stop that, uh,

752
00:39:35.360 --> 00:39:37.440
working. So you're not knocking out the promoter per se,

753
00:39:37.740 --> 00:39:40.560
but you are changing the way the promoter will respond to different

754
00:39:40.720 --> 00:39:42.320
stimulations. And that's a really nice technique.

755
00:39:42.320 --> 00:39:45.240
That's something you could do quite easily, just a single guide, N H E J,

756
00:39:45.780 --> 00:39:49.160
you know, disruption of the transcription factor binary site. Uh, so yeah,

757
00:39:49.160 --> 00:39:53.600
we've done that as, as well, and that that will work quite effectively. Hmm. Um,

758
00:39:53.910 --> 00:39:57.520
okay. So the next question, uh, I'm just conscious of time right now, so we'll,

759
00:39:57.520 --> 00:39:59.560
we'll, we'll try and wrap through the last few questions here. We,

760
00:39:59.660 --> 00:40:04.360
we did have a lot. Um, so what is the percentage of cells that, that, uh,

761
00:40:04.500 --> 00:40:08.120
are gonna get an indel on both alleles? You know, I mean,

762
00:40:08.120 --> 00:40:11.880
this is again a bit of a difficult question to answer, but in your experience,

763
00:40:12.100 --> 00:40:14.280
how frequently do you get editing on both alleles?

764
00:40:16.110 --> 00:40:20.320
Yeah, so that totally depends on the locus, but when we do r and p

765
00:40:23.920 --> 00:40:26.220
And yeah, it, it's, it's pretty common actually.

766
00:40:26.220 --> 00:40:30.820
In some ways it's more common to have homo homozygous

767
00:40:30.820 --> 00:40:32.700
deletions than it is to have heterozygous.

768
00:40:33.020 --> 00:40:36.100
Heterozygous can actually be harder to get.

769
00:40:36.160 --> 00:40:39.580
So sometimes if we have a very high editing efficiency when we look in the bulk,

770
00:40:39.640 --> 00:40:42.500
so we look at like all alleles and then we get maybe like 90%,

771
00:40:43.490 --> 00:40:48.220
then it's more common. I would say that you get wild types and,

772
00:40:48.520 --> 00:40:52.340
and then the others being homozygous and actually getting a heterozygous in

773
00:40:52.340 --> 00:40:56.300
there. So there seems to be some level of all or nothing in there. Yeah.

774
00:40:56.800 --> 00:41:00.140
And we found that one way to do it, if you get too many homozygous,

775
00:41:00.320 --> 00:41:05.100
is to introduce a wild type template as well at the same time to,

776
00:41:05.200 --> 00:41:09.540
to sort of reduce the amount of, uh, homozygous clients that comes. So,

777
00:41:09.680 --> 00:41:12.620
so that's normally less of a problem than the other way around.

778
00:41:13.010 --> 00:41:14.140
Yeah. So it, it, I mean,

779
00:41:14.140 --> 00:41:16.420
it's great to hear you say things like that because that's exactly what we've

780
00:41:16.420 --> 00:41:17.940
been doing. And same our experience too,

781
00:41:17.960 --> 00:41:21.460
if a cell receives the CAS nine and the guide r n a, generally speaking,

782
00:41:21.530 --> 00:41:25.580
both alleles will get caught. Mm-hmm. Um, and if you're trying to make, say,

783
00:41:25.580 --> 00:41:26.380
point mutations,

784
00:41:26.380 --> 00:41:29.700
we've had some guys come to and say we've got a disease develop point mutation

785
00:41:29.890 --> 00:41:33.380
that is heterozygous in the patients heterozygous cell line.

786
00:41:33.790 --> 00:41:37.360
What we don't want to do is get that mutation we want on allele number one,

787
00:41:37.500 --> 00:41:39.600
and then knock out allele number two. We don't want that.

788
00:41:39.820 --> 00:41:41.640
And we've done exactly the same thing you've said there.

789
00:41:41.660 --> 00:41:45.880
We supply two repair templates, one that will encode the, uh,

790
00:41:45.880 --> 00:41:50.290
mutated sequence and the other one that will basically rebuild the wild type

791
00:41:50.650 --> 00:41:53.690
sequence. And quite often we put you, I dunno if you put like a, a,

792
00:41:53.850 --> 00:41:56.690
a synonymous mutation there to stop the pite, that kind of thing,

793
00:41:56.710 --> 00:42:00.130
so that you get a HDR R event on both alleles. Mm-hmm.

794
00:42:00.130 --> 00:42:02.330
But the template used on each allele is different,

795
00:42:02.350 --> 00:42:04.770
so you end up with a heterozygous cell at the end of it, and that that's,

796
00:42:04.770 --> 00:42:08.290
that's very effectively for us as well. Uh, but I completely agree, you know,

797
00:42:08.390 --> 00:42:10.970
if you are looking for a heterozygous change,

798
00:42:11.270 --> 00:42:14.130
that's actually more difficult to achieve than a homozygous change quite often.

799
00:42:14.370 --> 00:42:15.210
I know, I know.

800
00:42:16.190 --> 00:42:17.970
Now, again, to come back to the example of using mice,

801
00:42:17.970 --> 00:42:20.770
it's great because we mice, if we, we, you know, we will often see,

802
00:42:21.230 --> 00:42:23.890
say we're trying to knock in G F P onto an on one allele,

803
00:42:23.890 --> 00:42:25.650
we'll get that knock to work in allele number one,

804
00:42:25.870 --> 00:42:30.010
and we'll have adle on allele number two, doesn't matter in mice, we breed the,

805
00:42:30.110 --> 00:42:30.650
uh,

806
00:42:30.650 --> 00:42:33.490
knocking allele forward and we gen attack the pups for the ones that have got

807
00:42:33.490 --> 00:42:36.970
the G F P and we just ignore the other ones. Yeah. So yeah,

808
00:42:36.970 --> 00:42:41.910
definitely more of a challenge in sales. Yeah. Okay. So,

809
00:42:42.210 --> 00:42:43.950
um, that's the next question.

810
00:42:44.850 --> 00:42:47.930
Is it enough to prove a knockout via P C R?

811
00:42:50.880 --> 00:42:51.480
No,

812
00:42:51.480 --> 00:42:52.313
No.

813
00:42:53.700 --> 00:42:56.300
I would, I would, I you need some functional tests,

814
00:42:56.600 --> 00:43:01.220
so it could be that the protein is absent or some downstream, uh,

815
00:43:01.490 --> 00:43:04.980
regular later. If you have some genes that you know are regulated by this,

816
00:43:04.980 --> 00:43:09.140
you can look at that, uh, some in vitro assay, something like that. Yeah,

817
00:43:09.220 --> 00:43:10.860
absolutely. I would say, what do you think, Anthony? Yeah.

818
00:43:11.000 --> 00:43:13.260
Oh, absolutely. Yeah. Uh, I mean I think we're,

819
00:43:13.380 --> 00:43:17.860
I think there's a bit of a concern of mine is that we're gonna get people and if

820
00:43:17.860 --> 00:43:21.380
a couple of years time publishing knockout cell lines and they're not knockouts,

821
00:43:21.440 --> 00:43:24.060
um, they think the knockouts because the genetic disruption's been there,

822
00:43:24.760 --> 00:43:28.420
but that just a disruption does not necessarily mean the protein has been lost.

823
00:43:28.640 --> 00:43:32.100
No. We've seen a few studies over the last few years now where, you know,

824
00:43:32.390 --> 00:43:35.620
we've got these genes in our cells through evolution because they're useful to

825
00:43:35.620 --> 00:43:38.660
us and it looks like the cells are desperately trying to hold onto it in,

826
00:43:38.660 --> 00:43:41.660
in some circumstances. And they can do some really strange things like,

827
00:43:41.660 --> 00:43:45.220
you know, skip over the, the exome that contains the indel. Um,

828
00:43:45.530 --> 00:43:50.180
they can make artificial exons in the middle of introns that will allow 'em to

829
00:43:50.180 --> 00:43:53.700
start producing the protein products. Mm-hmm. So yeah, functional validation is,

830
00:43:53.720 --> 00:43:54.660
is vital. You know,

831
00:43:54.660 --> 00:43:58.260
Western BLO may be using antibodies directed against different region of

832
00:43:58.260 --> 00:43:59.780
protein, especially N N C terminus.

833
00:44:00.080 --> 00:44:02.300
If you see a truncated products on your western block,

834
00:44:02.490 --> 00:44:06.940
that could be a residual protein being expressed that retains some function.

835
00:44:07.080 --> 00:44:09.620
So your cells are not a bonafide knockout. So yeah,

836
00:44:09.640 --> 00:44:14.580
it is not enough to just do PCR alone and sequencing the PCR and sequencing is a

837
00:44:14.580 --> 00:44:17.380
great indication to, to, um, let you know your CRISPR working,

838
00:44:18.090 --> 00:44:20.030
but the end product, you want the knockout cells,

839
00:44:20.420 --> 00:44:22.390
it's not an indication of that at all. You know,

840
00:44:22.910 --> 00:44:25.150
functional tests are really important. I agree. Uh,

841
00:44:25.150 --> 00:44:27.590
and there's a follow up question from the same individual who's asking,

842
00:44:27.930 --> 00:44:29.310
you know, how do you, uh, what,

843
00:44:29.310 --> 00:44:32.250
how do you approach cells that have got different aneuploidies, different, um,

844
00:44:32.300 --> 00:44:36.930
you know, K types, that kind of thing. So there's multiple alleles to target.

845
00:44:37.900 --> 00:44:41.080
Oh, you mean like in some sort of hala cells or something?

846
00:44:41.080 --> 00:44:41.913
Yeah, exactly. Yeah.

847
00:44:43.400 --> 00:44:46.360
I dunno, I, no, I mean, I suppose it's just the,

848
00:44:46.380 --> 00:44:50.680
the same there somehow you just have to like, uh, get all four of them.

849
00:44:51.180 --> 00:44:54.840
Uh, you know, you just have to make sure that it's, it's all gone. Like,

850
00:44:54.840 --> 00:44:56.480
it doesn't matter where it comes from really,

851
00:44:56.590 --> 00:44:59.040
like which allele it is and all that. You just have to,

852
00:44:59.260 --> 00:45:03.240
it should all work the same. So if there's more than one copy or two,

853
00:45:03.240 --> 00:45:05.640
then it should work the same. And uh,

854
00:45:06.020 --> 00:45:07.800
and then you just have to check that it's gone.

855
00:45:08.110 --> 00:45:11.840
Yeah, absolutely. So if you've got four alleles and on one allele,

856
00:45:11.840 --> 00:45:15.240
one you get a minus two deletion, allele two, you get a plus five, you know,

857
00:45:15.240 --> 00:45:18.000
as long as you've got frameshift mutations on, on each allele. Mm-hmm.

858
00:45:18.260 --> 00:45:20.320
And then you validate it as we've just said.

859
00:45:20.320 --> 00:45:22.800
Then with the protein level expression as well as, you know,

860
00:45:22.800 --> 00:45:26.240
make sure you do that functional validation, then it is possible.

861
00:45:26.260 --> 00:45:29.560
And we've already highlighted that if you get the Cass nine and the guide iron

862
00:45:29.670 --> 00:45:33.200
into the cells, generally speaking, every LE gets targeted. Mm-hmm. Um,

863
00:45:33.340 --> 00:45:35.440
so it is, um, I,

864
00:45:35.520 --> 00:45:38.000
I wouldn't actually say it's more challenging to make a knockout in cells with

865
00:45:38.160 --> 00:45:41.280
abnormal karyotype. I think, you know, it works reasonably well, um,

866
00:45:41.860 --> 00:45:46.680
for knocking, obviously, you know, you are less likely to get that knocking, uh,

867
00:45:46.700 --> 00:45:48.680
to happen every single allele. Um mm-hmm.

868
00:45:48.860 --> 00:45:52.080
Do you need an every allele if you don't have an every allele,

869
00:45:52.100 --> 00:45:54.680
do you need to think about what has happened to the other ones as well? So,

870
00:45:54.820 --> 00:45:56.960
you know, these are, these are bigger questions actually,

871
00:45:56.960 --> 00:46:00.120
and ones that you may need to factor into, again, that functional validation,

872
00:46:00.120 --> 00:46:03.520
what you're doing afterwards. Okay. So, uh,

873
00:46:03.620 --> 00:46:07.240
I'm gonna move to this last question now. Um, and this is about Cass 13,

874
00:46:07.300 --> 00:46:12.280
and someone's asking, when would you use Cass 13 instead of Cass nine? And, um,

875
00:46:12.340 --> 00:46:14.840
in, I'll answer this, it is a great opportunity for me to say, um,

876
00:46:14.910 --> 00:46:17.480
this is a subject beyond what this, uh,

877
00:46:17.640 --> 00:46:20.560
q and A is set up for about CAS nine g and editing. Um,

878
00:46:20.730 --> 00:46:24.640
we've been using CAS 13 ourselves and it's great for r n a targeting. Uh,

879
00:46:24.820 --> 00:46:28.970
and there's so many derivative applications of CRISPR based technologies, um,

880
00:46:29.510 --> 00:46:32.370
for, for different approaches. And you, we've talked about crispr, Ike,

881
00:46:32.370 --> 00:46:34.810
and how we can knock down gene expression, uh,

882
00:46:34.810 --> 00:46:38.010
using crispr i Cas 13 can be used in a similar kind of way, you know,

883
00:46:38.010 --> 00:46:41.810
so we degrade the transcripts being produced. You may not full knockout,

884
00:46:41.830 --> 00:46:43.890
but you may get a nice reduction. Um,

885
00:46:44.100 --> 00:46:49.010
there is a fantastic blog on the bite-size bio website on using CAST 13 and

886
00:46:49.030 --> 00:46:53.210
how you approach that with some extra information, um, um, about, uh,

887
00:46:53.270 --> 00:46:54.770
how you might set those experiments up.

888
00:46:55.150 --> 00:46:58.890
But I actually think that actually brings us to a great endpoint and allows us

889
00:46:58.910 --> 00:47:03.370
to, to stop this q and a now. Um, I'm pretty tired. I about you, Pia.

890
00:47:03.830 --> 00:47:06.170
Uh, but it's brilliant. It's been some fantastic questions.

891
00:47:06.170 --> 00:47:07.170
It been really great to, uh,

892
00:47:07.190 --> 00:47:10.330
to try and answer them for you and if there's enough interest, you know,

893
00:47:10.330 --> 00:47:14.330
we're happy to put on more of these kind of events as well. Um, so for now, Pia,

894
00:47:14.350 --> 00:47:16.890
I'm gonna say thank you for joining me today. Really enjoyed this. Thank you.

895
00:47:16.890 --> 00:47:17.330
Thanks for having

896
00:47:17.330 --> 00:47:17.500
Me.

897
00:47:17.500 --> 00:47:19.690
Thank you very much and see you y'all later. Bye everyone.

898
00:47:21.250 --> 00:47:25.310
You've been listening to CRISPR Unedited. To access more thoughts,

899
00:47:25.380 --> 00:47:27.030
help and advice on crispr,

900
00:47:27.160 --> 00:47:31.950
visit bitesize bio.com/crispr-unedited.