NEWS & ANALYSIS

An Audience With… Jennifer Doudna CRISPR–Cas gene editors are now both moving into the clinic and being embraced as a means to find and validate drug targets. But for Jennifer Doudna, who helped pioneer this promise with her work at UC Berkeley , the full potential of these tools will only be unleashed when they can be used at scale. To this end, Doudna and colleagues partnered last year with GlaxoSmithKline to launch the Laboratory for Genomic Research (LGR), a US$67 million effort aimed at industrializing the CRISPR–Cas workflow for the detailed exploration of human genetics. One year on, she spoke with Asher Mullard about her hopes for CRISPR–Cas editors as drug discovery tools, the types of projects the LGR is working on and the challenges they face. UC Berkeley Keegan Houser, Credit:

What prompted the creation of the LGR? Can you provide examples of the projects CRISPR has done is that now we can ask [GlaxoSmithKline’s CSO] Hal Barron and underway? some of those same questions with a tool I had a dinner, and we talked about using With the company-initiated​ projects, the goal that allows us to interrogate human primary CRISPR to identify drug targets, faster is to accelerate drug discovery efforts that are cells. And those cell types are more relevant and potentially more effectively than has already going on at GSK. They have a number directly to understanding human disease. been done in the past. This is one of the of small molecules where they need to either Furthermore, we can now use CRISPR real frustrations in drug discovery: how do figure out what the targets are for those drugs, to make animal models that are more we find drug targets and validate them? or better understand how they interact with representative of human disease. This is all And, importantly, how do we understand different types of genome. So we can use very enabling. how drugs will interact in the context CRISPR to figure out that sort of thing. I think we’re now at a point where of an individual’s genome, which has all For the second type, there are lots we’re going to see these CRISPR-based​ sorts of variability to it. We talked about of interesting synergies between the approaches really accelerating the pace of these interesting case studies where an programmes GSK is running and the projects genetic discovery. And not only in terms allele of a gene will cause disease in some ongoing in academic labs at UC Berkeley of the functions of individual genes, which individuals in a family, but not in all. So there and UCSF. And so we’ve identified primarily was one of the primary goals of a lot of the are suppressor genes in those unaffected cancer-related​ and neurodegeneration- original GWAS work, but also in terms of individuals, but how do you find them? ​related projects that focus on understanding understanding the complex nature of genetic And our idea was that it would be exciting the genetics of diseases, so that we can interactions. This brings us back to that to establish a pipeline to use CRISPR to do identify appropriate drug targets. conversation that I had with Hal about how those kinds of genetic investigations, with an For the investigator-initiated​ projects, individual genetic variants can affect how a eye towards much faster identification and we had several of our star, younger faculty drug acts in an individual patient, or how validation of drug targets. that we really wanted to encourage to get a particular genetic variant causes disease involved. So Martin Kampmann is running in one individual and not in another. How did you go about setting this up? a project on neurodegenerative diseases. It took a while to negotiate the terms And Dirk Hockemeyer is working on We’ve since learned some of the limitations of this partnership, because we were very carcinogenesis, and the ways in which of GWAS analyses. What factors do you think keen to make sure that it was set up in cancer cells escape the natural controls on are likely to limit the utility of CRISPR–Cas a way that would encourage innovation. cell growth. experiments? We ended up with a model where we We now want to have some early wins. It turns out that really understanding these would run three different types of project. We’re focused on having some key results enzymes — their mechanisms, how they The first are the company-initiated​ projects over the next 12–18 months. function in different cell types, what the that are of primary interest to GSK. The editing outcomes are in different cell second are kind of standard GSK–academic The ambition is reminiscent of the early types — are all things that you need deep partnerships, where labs at UCSF and UC hopes for genome-​wide association studies knowledge on. Berkeley would work with GSK scientists (GWASs), some 15 years ago. When it comes to effectively targeting a on projects. And third, which I think I think that’s a very reasonable comparison, wide collection of genes, whether it’s a whole are different from what you see in other and I think really we’re talking about different genome or a subset of genes, in such a way academia–industry partnerships, are generations of related technologies. that the effect is pretty uniform, that turns projects that strictly originate from academic In the initial days of GWASs, the approach out to be harder than one might think. groups here. We are providing funding was primarily phylogenetic comparisons and On the other end, we need to think about for those teams, and, while GSK gets to classical genetic experiments. But people had how to interpret data coming out of these see the work and the results, they don’t to rely on animal models or other surrogates types of studies. How do we how do we get automatic rights to license resulting for human disease in the laboratory to test interrogate those datasets? How do we look intellectual property. the resulting findings. And I think what for small but potentially very significant

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effects of genetic knockdowns or intersections into a robust pipeline for interrogating genes of different genetic pathways? These are again on a much larger scale. not trivial to implement. I think we’re now at a point The volumes of data that you collect with where we’re going to see these GWAS analyses show that up to 90% all of these analyses must be staggering. of disease-​associated variations fall in How big a challenge is that? CRISPR-based​ approaches non-coding​ regions. Can CRISPR–Cas take Yes, you put your finger on it. I think that really accelerating the pace on these non-​coding elements? is the challenge, dealing with the amount of genetic discovery. And not I think it’s in a pretty good position to of data that we’re getting from these sorts of only in terms of the functions go after those kinds of non-coding​ targets. investigations. It’s not only doing the But, it depends on your pre-existing​ experimental work itself, but then it’s also of individual genes … but also knowledge about what parts of the genome taking the data that come out the other end in terms of understanding the are important to target. And, of course, and figuring out how to interrogate them. complex nature of genetic coming back to the previous question, And from any one experiment, we can get interactions how do you most effectively design guide such a deep, rich set of information that RNAs that will give you the desired outcomes applies not only to the question that we for those regions of the genome? But from set out to ask, but probably to lots of other You could also ask “well, isn’t every some of the initial academic work done in questions as well. company doing this?” And the answer is, this area, it’s been possible to target these We’re still in the process of setting that actually, they’re not. They probably would non-​coding regions more effectively than all up. But we’re pretty excited about the fact like to, but the devil is in the detail. And no was possible using earlier technologies such that we have access to some of the best data one’s really pulled all of that knowledge as RNA interference. And so that makes us scientists in the world. We’re feeling like kids together before. think that there’s a lot of runway. in a candy store right now. You also really have to hand it to people Would you consider expanding the LGR like Jonathan Weissman — who is one of the CRISPR–Cas editors have been embraced to include more industry partners? founders of the LGR — and his colleagues in part because they are so easy to use. Personally, I would love that. But it sort of and collaborators for taking CRISPR, But the application of these editors at scale depends on the science that comes out of it. which started as a genetic editing tool, and still sounds anything but accessible. Ask me again in a year, and I think you’ll have turning it into a technology for manipulating That’s probably true for lots of democratizing a much better sense. transcription as well. You can tune the technologies. At the most fundamental expression of individual genes or even level, [CRISPR] surely is a democratizing Do you foresee the LGR projects leading sets of genes in cells, not just by knocking tool because it’s simple enough to use that to CRISPR–Cas drugs, or mainly just new expression down with CRISPRi, but actually essentially any graduate student can use targets? by increasing expression as well with it to introduce changes in cells of interest. Everything’s on the table. CRISPRa. This is just extraordinary, right, And that’s why we’re seeing the kind When the long-​term history of CRISPR–Cas because it gives scientists a way to control of extraordinary advances in the pace of editors is written, will these have been more gene expression in a targeted way, and to do fundamental research that’s gone on over useful as tools to interrogate biology or as a it with not just one gene at a time but with the last few years with CRISPR and related therapeutic modality? whole sets of genes if they want to. technologies. But, that’s very different from I think they really go hand in hand. The other thing that has happened having an industrialized pipeline that allows We need both. But, frankly, what makes recently is that Jonathan and Aviv Regev at rapid implementation of this technology CRISPR so exciting to so many people is The Broad and colleagues have developed much more broadly. That’s a whole different the fact that it’s not just a discovery tool. Perturb-​seq, where it’s possible to interfere ball of wax. It’s potentially the fix as well. or disrupt a particular gene or even multiple I would argue that we need both. One of I believe we need to already be thinking genes and then ask what effect that has on our goals at the LGR is to create a pipeline about how we ensure that CRISPR as a the entire gene-expression​ pattern in cells. that can be rolled out elsewhere. I think we modality becomes available widely, that it’s This really takes the whole idea of genetic can come up with robust guide RNA libraries, not simply for the few and the very rich. discovery to the next level. And again, for example, and rules for how target sites for Just like it is a democratizing tool in the lab, this can be done not just in model cells or the CRISPR enzymes are selected. This has we’d like to see it be something that is organisms, but actually in patient-derived​ already been done to some extent in many democratizing in clinical practice as well. cells. So, this is where we want to go with places, but it’s not really been centralized Now, that’s easy to say and a lot harder to the LGR: to take that technology, which and standardized, and that’s what we’d like implement. But it is one of my motivations, was developed in academic labs, and turn it to do. to really think hard about how to do that.

nAture RevieWs | Drug Discovery volume 19 | June 2020 | 381