The transformative power of CRISPR in the lab, with John Doench and Ruth Hanna

John Doench, associate director of the Genetic Perturbation Platform (GPP) and institute scientist at the Broad Institute, and Ruth Hanna, research associate in GPP, discuss how the CRISPR system has revolutionized studies of gene function.


We know what the sequences of genes are. We have the As, Cs, Gs, and Ts that make up our genome, and we now are beginning to understand how changes to that sequence, how mutations or natural variation, can give rise to human disease.

John DoenchJohn Doench

But what we didn’t have until the advent of CRISPR was a really good way of manipulating that information in the laboratory in order to determine gene function — in order to determine why, if this gene is dysfunctional, how does that lead to disease?

My name is John Doench. I'm the associate director of the Genetic Perturbation Platform, or GPP, and an institute scientist here at the Broad Institute.


My name is Ruth Hanna. I'm a research associate in the Genetic Perturbation Platform.


And you’re listening to BioLogic: Conversations with Broad researchers exploring what they do and why they do it, a podcast from the Broad Institute of MIT and Harvard. I’m your host, Karen Zusi.

In this episode, we’re taking a look at the CRISPR system — but not at its future potential for one day treating disease, or at least not directly. Instead, we’re diving into the ways that CRISPR is already changing science. 

CRISPR enzymes can target genes with an accuracy we could have barely imagined less than ten years ago — and that system has dramatically expanded the questions we can ask, and the experiments we can do, in the lab.

John and Ruth, with their team in the Genetic Perturbation Platform at Broad, are developing new tools that harness the power of CRISPR — tools that let us pull apart the genome to understand disease biology.


I think one of the great things about GPP is that we do a lot of this technology development, but that enables all sorts of different kinds of research down the road.


I really like being in a place where technology development, you know, I like building hammers, but it’s not fun to build a hammer if you don’t have a lot of nails to hit. And this is a very nail-rich environment here at the Broad. 

And that feeds on itself. You don’t know what kind of hammer to build if you don’t know what the nails are. You can’t just go off and build tools if you don’t know what the applications are. So a lot of what drives the technology development we do is meeting with people in the community who have a particular problem, and then we think about, “Well, how might we solve that together?” And that’s what often leads to these collaborations that provide tremendous insight on the biology of whatever disease they’re studying.


But before we dive into how they use the CRISPR system to hit those nails, John shared an interesting story about a day in a yogurt factory.


The origins of CRISPR are, of course, varied. The discovery of anything is a lot of people knowing what else is going on in the field, and a lot of idiosyncratic “Gee, that’s kind of funny” observations. And one of the nicest stories about the early days of CRISPR starts with an interesting day in a yogurt factory.

Obviously, to make yogurt, you need bacteria. And one thing that happens in bacteria is they can be contaminated with viruses, with the viruses called bacteriophages that infect the bacteria needed to make yogurt. And so one day, there was a sad day in a yogurt factory, because their cultures had been contaminated. 

But they had some excellent molecular biologists employed there, and they realized that the small fraction of bacteria that survived this challenge from virus had incorporated sequences of the virus into their genome. So, they had snipped out parts of the virus and used that virus as, basically, an immune system, an acquired immune system in bacteria — which is something that no one had really thought possible.

And obviously, there were hints of it elsewhere in the literature. Other people were coming to this conclusion from multiple different paths. But this was one of the first examples of showing it in the lab and showing how this system might function. And it really gave people a way to start to study this system and dissect it.


And the CRISPR system has already revolutionized research. Scientists at Broad and elsewhere are using the CRISPR system to uncover insights into how disease works.


The promise of CRISPR is not that CRISPR will be a therapeutic intervention itself, in many cases. I mean, in some cases it absolutely will be, it is the right therapeutic intervention, but that’s obviously a long hill to climb.

But for CRISPR, the real promise is how it’s going to let us understand the genetics of every disease — even if the result, even if the eventual therapeutic intervention, has nothing to do with CRISPR. The nail we’re hitting with CRISPR technology is understanding what genes do.


One of the reasons that the CRISPR system is so powerful is that you can really flexibly target it throughout the genome. And the way it works is that the Cas is guided by a guide RNA, which is a 20 nucleotide sequence. So, simply by changing out that guide RNA, you can send the Cas to whatever desired location in the genome you want, and it will go there, make the edit or cut, and it’s very easy to program.


And of course, even the ability to do that stands on the shoulders of all the work that had been going on. You know, if you didn’t know the sequence — but now we have the Human Genome Project. And as Eric Lander, the founder of the Broad, noted, “In seven words describe the human genome project,” and he said “Genome: Bought the book, hard to read.”

We had three billion bases but we didn’t really know what most of them do. And CRISPR provides a way to turn that sequence information into functional information about “Oh, what is our genome trying to tell us?”


It really has opened up a whole new set of questions that you can ask. With the ease of making edits and knocking out genes with CRISPR, genetic manipulation can be a first step in solving a problem, a way to generate new hypotheses.


John broke down what that means, to generate hypotheses and solve problems through genetic manipulation.


In many cases you’ll have a phenotype of interest: The cells will be doing something and you want to understand why. In a cancer cell, you want to understand why it continues to grow when it shouldn’t be. So you want to understand, “Well, what are the genes that I could shut off in cancer? What would be a good drug target that I can inhibit in this cancer cell such that they stop growing, or such that now the immune system recognizes them?” Or in infectious disease, “How does this pathogen get into a cell?”

So you can take all the genes in the genome, hit each one of them with your CRISPR hammer, and determine, “Well, when I knocked out this gene, now Vibrio parahaemolyticus no longer gets into the cell to cause seafood poisoning.” And that’s a good thing to know, because now you can start to understand, “How might we build a therapy that would prevent this pathogen from getting into cells? How do you understand the basic biology of that pathogen?”

Or, if you have a disease, how might you correct, how might you change, a gene to ameliorate some of the phenotypes associated with that disease?

So with CRISPR technology, you’re able to perturb every single gene in the genome in a relatively straightforward way to determine the functions of those genes and how they’re affecting the behavior of cells.

All biologists, at the end of the day, we love lists of genes. We want to look at genes and understand what genes are doing. And CRISPR provides the best way yet to understand the function of every single gene in the genome, across every single cell type, across every single disease state. And that’s just something that just wasn’t possible, with nearly the precision and scalability, with previous technologies.


Before the emergence of CRISPR as a lab tool, there was a technology to do this kind of work. It was called RNAi, or RNA interference, and it was used to turn off specific genes by neutralizing their messenger RNAs. But, to put it plainly — RNAi just isn’t as good.


Ruth and I were discussing this yesterday, and, you know, she’s only known a world with CRISPR. I mean, as you were saying, in your undergraduate days, you use CRISPR, because of course you use CRISPR. And the curmudgeon in me, that kind of makes me a little angry. I feel like everyone should have to suffer through RNAi before they’re allowed to use CRISPR. I feel like it would build character.

Certainly it was as — maybe not quite as — hyped as CRISPR was when it was discovered, but pretty close, when it was first discovered in 1998. So it became the tool of choice to determine gene function in human cells. 

But RNAi, it became clear over time — it wasn’t clear at the outset — but RNAi has an off-target effect problem, where if you try to target one gene with your small RNA, you will oftentimes target tens, or hundreds, or maybe even thousands. So it’s not clear what the relationship is between the gene you’re trying to target and then what the cells do at the end, the phenotype. It’s not obvious that it was due to the gene you wanted to target, or some of these other ones.

So that meant that using RNAi to determine gene function — progress was slow, because you often were chasing down false leads. And that can take time in the lab. Whereas with CRISPR technology, what’s great about it is that when you do an experiment, you can trust the result with a much higher degree of certainty. So you’re not moving around in this zone of uncertainty, of “Well, is this gene really involved in my phenotype? I need to spend 3 months validating this.”

The first screen we ever did, in collaboration with Feng Zhang’s group, I still remember sitting in bed — I mean, we ran the analysis overnight, and so I woke up, my laptop was sitting next to me, and I opened it up and I just looked at how clear the results were. 

It was not at all like looking at RNAi data, where you’re like, “Well, I need to apply some statistical tests to make sure that these top genes are real.” It was, “Oh wow, this is true. There’s no way that this is wrong.” The statistics just tell you that it’s a much cleaner technology. 

And you can quickly then Google your gene name and start to come up with hypotheses for why this gene is involved in this phenotype, this disease. And usually you’re right. Everyone who’s used CRISPR has come to this conclusion, that, “Wow, if you want to determine gene function, CRIPSR is not just the next step. It is a complete game changer.”


John gave a few examples of how the Genetic Perturbation Platform uses this technology, in collaboration with scientific groups across the Broad and other institutions. 


We’ve collaborated with groups studying infectious disease, studying cancer immunotherapy, and everywhere in between, to try use CRISPR to understand gene function and how gene dysfunction can lead to disease.

So one example is the question of cancer immunotherapy.


The general idea behind cancer immunotherapy is that tumor cells evolve ways to hide from the immune system, and immunotherapy kicks the immune system back into gear to recognize and destroy the cancer.  


The issue is that when you apply these immunotherapies — ten, twenty percent of patients respond in some tumor types. In other tumor types, that number is closer to zero or one percent. So the question is, “What are the tumor cells doing to prevent the immune system from recognizing it? What are additional genes that we could inactivate, let’s say, to allow the immunotherapy to work again, to allow the immune system to recognize the tumor?”

So, in collaboration with Nick Haining, professor at Dana Farber and Broad, we set up a system to study immunotherapy. We took mice, we inactivated a whole panel of genes in the mice using CRISPR technology, and we put the tumors back into the mice. And we asked, “Well, what are the genes that now allowed these tumor cells to respond to immunotherapy?” With the idea being that those might be additional good drug targets to go after to stimulate an immunotherapy response in humans.

Now, obviously, that’s target identification. That is, “Maybe these genes would be good targets.” There’s a lot of work to be done to actually turn that into a therapy. But, you know, the excitement is there. We have a good list of targets to go after. There are more targets to find, but it provides a great proof of principle that this is the area of biology we need to be looking at in order to re-stimulate the immune system to recognize the tumor.


And the team is constantly working on new methods that harness the CRISPR system, like shutting down multiple genes at the same time, to answer more complicated questions about cell circuitry. 

But to really achieve CRISPR’s potential as a transformative laboratory tool, to make all of this work, Ruth and John also highlighted the need for good model systems. 


One of the big challenges with using CRISPR to understand complex disease is getting a really good model system where you can read out, when you knock out this gene, it causes a particular phenotype. But what is the phenotype that you’re looking for if you’re studying psychiatric disease, or if you’re studying type 2 diabetes?

That’s not something that is quite as easy as culturing cancer cells in a lab. We know how to do that. But really fine-tuning the model systems is, I think, another big challenge for CRISPR.


Right, right, that’s a great point. And, you know, every day, we work on making the perturbations better, but that’s why it’s so important to be in an environment where people are building better models. Because it’s only when you bring the two of those things together — you know, the immunotherapy story I was discussing, that only worked because the Haining lab had built a really good model of cancer immunotherapy. Just having CRISPR wouldn’t have helped. You needed that good model to apply it to. 

I mean, that’s why we’re all at the Broad doing biology together. It’s not just data scientists, and people making big datasets, but clinicians and researchers and chemists and target-finders and protein biologists.

So, again, that’s exactly why having a good collaborative environment, a good back-and-forth between the people in the community, that’s how you really make progress quickly.

You can check out more about the Genetic Perturbation Platform, and ways that biomedical researchers at Broad are using CRISPR to learn more about disease biology, at

You can also find more episodes of BioLogic, with transcripts, on, and through SoundCloud, iTunes, Pocket Casts, and other podcast distributors. 

For the Broad, this is Karen Zusi. Thanks for listening!