NEB Podcast Episode #18 -
Interview with Jonathan Gootenberg and Omar Abudayyeh: Using gene editing technology to detect RNA targets
Interviewers: Lydia Morrison, Marketing Communications Writer & Podcast Host, New England Biolabs, Inc.
Interviewee: Jonathan Gootenberg and Omar Adudayyeh, McGrovern Fellows, McGovern Institute for Brain Research at MIT
Lydia Morrison: Hello and welcome to the Lessons From Lab and Life Podcast. I'm your host, Lydia Morrison, and I hope that our podcast offers you some new perspective. Today I am joined by Jonathan Gootenberg and Omar Adudayyeh who are the first McGovern fellows of the McGovern Institute for Brain Research at MIT and they're here with us to share their work, applying CRISPR gene editing technology to diagnostic reporter assays. Jonathan and Omar, thanks so much for joining me today.
Omar: Yeah, thanks for having us. Excited to be here.
Jonathan: It's great to be here. Thanks so much.
Lydia Morrison: Could you tell us about Cas13 and how you're using it as a tool to detect disease states?
Omar: Yes, so Cas13 is an enzyme that is associated with CRISPR systems and when the genome editing craze with CRISPR was taking off, most people were really excited about this one protein, Cas9, and how we could cut DNA and be used for genome editing. At the time we were really interested in whether there were other enzymes within CRISPR that could also be useful for biotechnology purposes. At the time we were more interested in DNA targeting, so we built a whole sort of computational pipeline of search, you know, you know, tens of thousands of bacteria for a new CRISPR enzymes. And out of that search we did indeed find more DNA targeting enzymes like Cas12 but there was this other enzyme that looked very different than them and actually targeted RNA that we ended up calling Cas13.
Omar: From that search we ended up characterizing this enzyme showing that they could actually cut RNA, degrade RNA and in fact, even detect RNA. So a lot of applications with Cas13 have to do with around really sensitive nucleic acid detection for RNA targets, whether that's RNA viruses or, taking DNA targets, converting them into RNA and also detecting them. So we've been able to show Cas13 for detecting bacteria from blood, detecting cancer DNA, even for agricultural applications, like being able to genotype plants that may have been modified. So you can either, figure out if you know there are soy beans that have a specific trait you're interested in or if you want to be able to make the engineering of plants easier and rapidly detect traits you may have introduced into your population, it's a, I think it's a really powerful enzyme and has applications from both healthcare, agriculture and even beyond. So yeah.
Lydia Morrison: So you mentioned really sensitive detection limits. What sort of sensitivity are you talking about?
Jonathan: We can essentially get down to the single molecule. If you have a single molecule in a solution and that, so the way you measure things is molar, right? And we need a prefix in front of that. So atto is 10 to the negative 18 so it goes nano, pico, femto, atto.
Lydia Morrison: I don't hear about atto a lot.
Jonathan: So attomolar levels. If you have a two attomolar concentration in one microliter of that is literally a single molecule and we can detect that. So you can't really get much more sensitive than that. And it allows us to do a lot of things like, you know, Omar mentioned there's all these different applications, infectious disease, in oncology, in agriculture where we can take these potentially very minute amounts of material or a very minor population and a certain type of sequence and detect it. So we're very interested in now is there's a lot of oncology applications where if you have a disease, if you have cancer and you're shedding this sequence into your blood, we can detect that at a very low frequency. So, I think it has many different applications that we're very excited about.
Lydia Morrison: Wow, that sounds incredibly powerful. Could you tell us about how you took the discovery of the Cas13 enzyme and applied that to create the SHERLOCK technology?
Omar: Yeah, so when we were first characterizing Cas13, it was really exciting to actually see it could programmably target RNA. But what we also saw was that when it was activated by target, it would end up cleaving any other molecules in solution. At first we thought it was contamination problem. And we have our in cases and solution, like we need to purify this again and again and try to get as clean as possible and you spent months on repeating this. And we kept finding the same result. So we realized that Cas13 operated very differently than other CRISPR enzymes that were known at the time. And that basically when it's bound and recognized in RNA target, it could end up just cleaving anything around it. We realized that while this might not make it the best cellular tool, if you want to specifically target mRNAs or specific genes, it could actually report on the presence of a target.
Omar: The idea was if we could bring in a reporter molecule that when cleaved would fluoresce, we could spike that in. And when Cas13 found, Zika target for example, we cleave this reporter and release fluorescence. And so it was very like an unexpected route. We had never thought we'd go into the diagnostics field or you know, we were not even thinking about that. We were trying to make gene therapy, gene editing. And so we really followed this unexpected results. And what we started doing is just seeing, you know, can we apply Cas13, routines to all sorts of applications. You know, can we detect, you know, pseudomonas, can we detect Zika, can we detect melanoma mutations in the blood. We just kept applying it and just kept working. We even found it could work from saliva. It worked from blood, urine, all sorts of samples without even purification.
Omar: Like a lot of diagnostics. You have to take a human sample, you have to purify out the nucleic acid and then you put it through an instrument that's rather complex and it's a lot of many steps. It takes time. It takes a skilled personnel. And we were finding that this simple enzyme could make just a single step reaction where you could literally spit in a tube, maybe heat that tube up for a few minutes and then just spike it into this reaction. And you could have detection on a paper strip even. So it really made the whole idea of diagnostics becoming outside of a complex lab setting and more maybe the home into the field. And I think we have really big aspirations. You know, you can imagine being able to detect flu at home or being able to know if you actually have a viral disease or bacterial cold and whether you need to go into the hospital or not. So I think, we're really hopeful to see where we can take it.
Lydia Morrison: Yeah, that sounds like a really beneficial application of it. What are the advantages of SHERLOCK versus other molecular diagnostics?
Jonathan: That's a great question. There is a lot of different ways to actually detect nucleic acids and do molecular diagnostics. One of the really nice things about SHERLOCK is that we have basically this enzyme, Cas13, that does this detection and it's very specific so we can tune it so it can distinguish even a single base. And that's very nice because in these applications, like in cancer or certain viruses, like with drug resistance, we want to be able to actually detect a specific mutation. And so that makes it very specific and that's coupled with the fact that once the protein is activated by this detection, it's a kind of a very catalytic mechanism where it's going to cleave many copies of these reporter molecules.
Jonathan: So it really means that we have this very specific interaction that unlocks this very promiscuous and high turnover detection. So that means that we can dope in this reporter molecule, which we can make very cheaply, and get very good detection even when there's low levels or something that's very close in sequence to something else. I think that specificity and low cost and sensitivity combined makes it a really robust method. This is also coupled with the other things that Omar already discussed. Where we can take it to different outputs and we can multiplex it so we can read out many different things at once. But I think the true power is from this Cas13 specific detection and then activation that makes it really amazing.
Lydia Morrison: You mentioned that the activity can be kind of promiscuous. Does that mean that you observe a lot of off target events?
Omar: The actual activity is promiscuous, but the way the enzyme is activated is very specific. So the activity only activates when the Cas13 recognizes a target through its guide RNA. And the guide RNA is programmed to be complimentary to your nucleic acid target. So only if it finds the precise sequence match will the enzyme change in a way such that this enzyme can now start cutting anything in solution. And in that case it'll cut anything indiscriminately. But what we found, as Jonathan was talking about was that, even a single nucleotide mismatch can sort of inactivate the enzyme and not allow it to activate, giving us that ability to detect single base pair mutations really, really well. And that's really unique from a lot of other assays where detecting a single mismatch can be quite difficult and you can always have background signal from those assays. And so that's a really big advantage of this system and CRISPR enzymes in general.
RNA Editing RESCUE Technology
Lydia Morrison: Earlier today you gave a seminar at New England Biolabs which I attended, and you mentioned the RESCUE technology that you've recently developed. Can you tell us a little bit more about that?
Jonathan: Yeah, so the RESCUE technology is one of our RNA editing technologies and it's complimentary to a repair technology that we published back in 2017. So RESCUE is a much more recent development and these are both technologies that rely on Cas13 being catalytically activated. So we make it so it doesn't cut RNA anymore, but it goes to RNA and then we can drag something with it. And what we drag with it is an RNA editing enzyme. So the repair technology dragged with it, an enzyme that goes from A to I and that allows us to correct certain mutations, but we wanted to do is expand the number of edits we could make. One big motivation for this is that if you want to make certain edits that can change your protein in a way that it functions differently, that's could be very interesting for a therapeutic application where we affect a pathway.
Jonathan: And as we mentioned before with RNA editing, it's temporary. So you could actually temporarily change a protein in a certain way. So what we did with RESCUE is that we took this protein that we're recruiting with Cas13, it's called ADAR and we actually did a lot of directed evolution and rational mutagenesis to modify it. So actually did C to U changes so it unlocks this entire new potential base transition. That was actually a long undertaking that we did and we found that we could actually get it to work effectively. Then we demonstrated that we could target certain pathways like the wnt signaling pathway, we could target beta-catenin which is a member of that, and we could actually activate that signaling and cause cells to grow just by delivering this targeted RNA editing approach. So that was very exciting and we're enthusiastic to see how people use this tool, this evolved tool for different applications, both in basic biology and in therapeutics.
Lydia Morrison: That's really interesting. So you mentioned that it's great at temporal regulation. If you wanted a more sustained regulation, is there a mechanism by which you could keep up more steady state level and maintain the repression or activation of a certain pathway?
Omar: Yeah. So if you really wanted a long-term modulation of these nucleotides, you have multiple options. So one is controlling how you deliver the system. So for example, if you deliver the system actually as a protein form, the protein will get turned over right after maybe a day or two. And so your modulation would be quite transient in that case. If you want something longer, you could then start thinking about maybe viral delivery. So for example, if you go for AAV's, those viruses can actually stick around for years. And so if you deliver this tool using that system, it would actually reach a steady state of editing within a cell and it would stick around for quite a long time. And then of course, if you really want permanent modulation, you could of course do DNA editing and use something like Cas9 or Cas12 where you can install the mutation instead of n RNA and DNA, in which case it would be permanent. And last for forever.
Lydia Morrison: So you did lots of screening to identify Cas13 and Cas12. Can you tell us how machine learning or artificial intelligence played into that data mining?
Jonathan: Yeah, so when we actually discovered these proteins, we went through a process of basically looking for certain anchors in the genomes of these different bacteria. We essentially compiled all of the sequences from thousands, tens of thousands actually, of bacteria and then looked for certain landmarks. Then near those landmarks we could find if there were proteins and if there proteins that we knew what they were, we could obviously say that. But if they were unknown proteins, we could start to cluster them together and say, well there's all these different proteins that kind of co-occur with these landmarks like CRISPR arrays, what are they? So that kind of clustering and finding similarity in the lining there was a little bit of, I'd say weak artificial intelligence process where we could cluster things and look for what was similar. Then what we did is we eventually found these clusters and then kind of look for them again and they turned out to be all the same protein and that was the Cas12 and Cas13 but I think one thing that we're very interested in moving forward is using much more of the additional genomes.
Jonathan: Of course now more genomes are sequenced every year and there are hundreds of thousands of genomes available now. Using those genomes along with more sophisticated ways of training, machine learning on what exactly does a protein look like in terms of just sequence or certain features of secondary structure and use that to actually go into these expanded data and look for proteins of interest, whether they be CRISPR proteins or other potential proteins that could be used for genome editing or other applications. So I think we're very excited about using both a ton of new data as well as new approaches in annotating and predicting similarity of proteins to delve into these data sets.
Lydia Morrison: And how are you planning to apply the knowledge that you've gained from Cas12 and Cas13 research and SHERLOCK and RESCUE technologies? How are you planning to apply that in your new lab at the McGovern Institute?
Omar: Yeah, so I think, a lot of what we've learned is how to explore natural diversity and ways evolution has already created useful proteins and enzymes and how they exploit them for biotechnology. I think a lot of what we're doing now is we're trying to maybe find more systems beyond CRISPR that could be useful for, gene editing and gene therapy. There's still a lot of limitations with how CRISPR is used now in terms of efficiency of editing and even being able to insert, large chunks of, you know, genetic material, like large genes for example, to get permanent replacement. And so, you know, a lot of what we're doing is maybe, you know, there are systems beyond CRISPR that can be used for phage defense, that could also be useful in this way.
Omar: So we're trying to mind for additional signatures, we're trying to characterize those enzymes in high throughput. So ways to screen them, whether it's in vitro or in bacteria. Then once you have them and can show that there's activity, how do we continue to engineer them using our engineering tool set? So whether it's directed evolution or just screening through mutagenesis and to make these enzymes even better than how they've already evolved. And so we're doing a lot of that. We're also applying a lot of these tool sets to other things beyond just proteins from bacteria. I think we kind of hinted at this, but what you really need is ways to deliver these proteins to the right cells when you're doing gene therapy. And our tool set for getting cell are for getting these tools to the right cell type or right tissue type is quite limited.
Omar: And so we are applying a lot of these mining and engineering approaches towards the viruses to try to either find new viruses that have the properties that you want and then to engineer them to either hit the right brain cell type or to be able to get into muscle better. Or even bone marrow and hitting T cells, OR hematopoietic STEM cells, or whatever cell type you might want. So I think, there's a lot of problems that need solving and there's hundreds of thousands of bacteria and other organisms we can try to pull a solutions from.
Lydia Morrison: I was wondering if you could share with us your perspective on the use of CRISPR and gene editing technology in current clinical trials and therapeutic approaches such as agriculture?
Omar: Yeah, so I think, 2019 has been a big year for CRISPR's as two clinical trials, have begun. One from CRISPR Therapeutics another from Editas Medicine. So I think that time will tell whether the results are promising and if it'll actually work. But I think, in the next few years we'll start to see CRISPR technologies actually start to become approved and enter the clinic. And I think for agriculture we'll probably see results even sooner. People are already trying to make different types of crops either, taste better or improve yields, make them healthier. Like a lot of genome editing for like soy beans for example, to get rid of unhealthy oils and put more healthier oils in them, have already begun. And so I think, it's going to be- the next few years is going to be really exciting.
Lydia Morrison: And do you have any thoughts on the role or significance of RNA editors in addition to traditional DNA CRISPR technologies?
Jonathan: Yeah, so having RNA editing as a complimentary technology for DNA editing I think allows for a lot of additional things. I think they approach two different areas in a sense because in DNA editing, there's a lot of things that you can do where you can target things and you dose it once, but there's a lot of cases where it may be difficult to deliver or it may be something that you don't want permanently. So with RNA editing you have the capability to, in some fields use endogenous proteins inside of cells like the natural ADAR and just co-opt that for targeting.
Jonathan: In our case we introduced this protein, but I think that there's an exciting area, especially for things that you only may want to induce temporarily to have this capability where maybe you don't want to run forever. And of course in the safety aspect, with DNA that's great that you can do something permanently. But on the other side if you do something permanently, you don't want it there. That's a little bit of an issue. With RNA, if you have off targets, they're not as much of an issue. So I think that will play into a little bit of how these things are regulated. But I think the space is so large. If you think about just the medicines that we can do that both technologies will do quite well.
Lydia Morrison: Thank you both so much for joining me today and I want to offer my congratulations on the amazing success that you've seen so early in your career and I am super excited to see where your research lends itself to diagnostics and clinical therapeutics in the future. So thank you.
Omar: Great. Yeah, thanks for having us.
Jonathan: Yeah, thanks.
Lydia Morrison: And I want to make sure that our listeners know where to go to learn more about your research. So could you tell them where to find your website?
Jonathan: Yeah, so our website is abugoot.MIT.edu
Lydia Morrison: Awesome. Thanks so much guys. Thanks for listening to this episode of our podcast. I hope you learned something about the amazing possibilities CRISPR gene editing technology is enabling in healthcare and agriculture. As always, check out the transcript of this podcast for lots of informative links, including the link to Omar and Jonathan's new website. And don't forget to tune in next time when we'll be joined by Rupali Dabas of University College London's iGEM team will be turning over the interview reins as she sits down with her colleagues and professors to discuss public perceptions of engineering biology.
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