Danuta Jeziorska: Exploring the secrets of the ‘dark genome’
Courtesy of Dr. Danuta Jeziorska
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Kat: As Naomi has described, we need to look further than just the 2% of the genome that is genes if we’re to understand how changes in our DNA influence our risk of disease, and to find more effective treatments. But exploring this non-coding DNA, or ‘dark genome’, isn’t easy. Finding the connections between the many genes that are linked to most health conditions, the millions of possible DNA variations in the dark genome, their influence on gene activity and their impact on different cell types to cause disease has been an almost impossible task. Until now.
Danuta Jeziorska is the co-founder and CEO of Nucleome Therapeutics, a company that has spun out of Oxford University with a new set of technologies for exploring the dark genome in unprecedented detail to reveal new ideas for treatments for some of the most challenging health conditions where we still need to do much more.
Danuta: So if you think about it, we have 22,000 genes in our genome, and we can compare that to having 22,000 ingredients in the fridge. We use the same set of ingredients to create different meals, just like how we have the same DNA within each cell, but then we have hundreds of different cell types. So this dark genome determines the combination of ingredients of the genes that you take and at which level you use them, to produce the different cell types that build our body. And you can just imagine that if you make a mistake in that - so let's say that you add the wrong ingredients in the wrong meal, you can mess up the meal. And in this same way you can mess up the cell type. So if you, for example, if you don't produce enough of haemoglobin to transport oxygen around the body, you will end up with a genetic form of anaemia or if you turn on a gene that's not supposed to be turned on, like an oncogene, you may end up having cancer.
Danuta: So the dark genome is now very well understood as the mechanism that is causing diseases.
Kat: So tell me a bit about what's going on when genes and their switches are coming together.
Danuta: Those switches, those regulatory elements are often not really close to the genes they regulate, they can even be megabase pairs away, they can even be within a different gene, very much what happens is that when the gene is turned on, those regulatory switches come in close proximity and they physically interact to turn the gene on. So it's simply showing how the cell works and is able to change the shape of the DNA to be able to interpret the genome in a different way.
Kat: And I think as well then you have got this added layer of complexity. Because again, we can think about - okay, we've got a chromosome, it's one piece of DNA string, we're gonna make a loop, we're gonna bring the switch and the gene together. And there you go, "Right, cool, but every single cell has got like, two metres of DNA!"
Kat: It's not one string, it's a lot of strings, there's some really complicated three dimensional organisation, but presumably that's not the same in every cell, if every cell needs a different load of genes turned on and off.
Danuta: So there are multiple different layers. So there will be, as you know, chromosomes. There will be then the topological associated domains. But then, there will be also be within those domains, the loops, the enhancer-promoter interactions happening. Some of them are more stable across different cell types, but very much there is a lot of ongoing dynamics going there.
Danuta: The key here is that there is a lot of variation that exists between different humans, but there is also a lot of variation that is linked with diseases. And simply originally, again, it was quite surprising that not all of the variation is taking place within genes, but the disease-causing variation also is happening in the dark genome. And those genetic changes are impacting the function of those regulatory elements. Or also there are elements that are involved in determining the structure of the DNA, and then they translate into the dysregulation of the gene expression and different diseases.
Kat: I think this is something that a lot of people don't get, and it took me a lot longer to get it than maybe I should have done, because we're taught at school, you know, you have one gene that does a thing, it encodes a protein, you have a mutation in that gene, you get a mutation in the protein, and then you get a disease. But then when we started to have genome sequencing technology that we could look at loads and loads of genes, we could look across the whole genome and you find that, is it 10 percent of the variations that we know about linked to disease are only in genes?
Danuta: Exactly, exactly. There is also the fact that there are monogenic diseases that are caused by one mutation and those are more easy to interpret, although it's still sometimes very challenging. But also many common diseases that many of us struggle with are polygenic. So this is like rheumatoid arthritis, multiple sclerosis...
Danuta: Those diseases involve multiple genetic changes that often happen across the genome, and 90 percent of those are located within this dark genome. And simply what happens is that they most likely impact the process of gene regulation and they dysregulate different genes. And there is the cumulative effect that happens across pathways because those different genes are involved in signalling pathways and dysregulation accumulation of those changes are really causing diseases.
Danuta: And it's quite fascinating. When the human genome was sequenced back then it was quite challenging to interpret that.
Kat: So let's drill into what you're actually doing at Nucleome to understand this complexity. There are millions of variations in DNA not located in genes, that may or may not be linked to disease, may affect gene regulation, may affect DNA packing.
Kat: I mean, I remember when I was writing my book in 2016, I was like, "Oh God, that's a really big problem, I hope someone figures out how to make these connections between the switches and the genes, and figure out what's going on!"
Kat: And it sounds like you found a way to do that. So tell me about what you're actually doing.
Danuta: As you mentioned, there is a lot of variation between humans. So the key question: which one is really linked with disease? And then also which one is causal? This was quite hard to find.
Danuta: The next challenge was that you need to know in which cell type to look, because as we discuss, the dark genome defines cell type specificity, so you need to know in which cell type to look to be able to interpret that.
Danuta: The next one is that you need to know which gene is affected. So simply, as we mentioned, those genetic changes and regulatory elements, they can sometimes be really far away from the gene they affect. And in the past, historically, people were looking at DNA as a linear structure and they were not able to easily link those things together.
Danuta: And the last challenge is also the causality challenge. Is this variant really impacting this gene to translate to disease?
Danuta: Sometimes, I really compare that to Cluedo, the game. So it's simply the variant is the weapon, the cell type is the room, and the gene is the murder, and then the causality is the motive.
Danuta: You very much need to solve that, and you need to solve that at scale, because many diseases, especially the polygenic diseases, will have sometimes hundreds of those variants.
Kat: Can you tell me a bit more about the technologies that you've been developing to actually explore the impact of these genetic variations on disease in different cells?
Danuta: So Nucleome has a number of technologies simply to address those challenges, but also with very high precision and accuracy.
Danuta: So to find the right variant, and to find the right cell type, we use machine learning. So simply machine learning was trained to tell us what is functional within the dark genome. And the model is telling us what happens if you flip a letter, so what happens if you have genetic change. This enables us to prioritise what are the potential functional variants that are disease-causing and in which cell type. And as a company, we are a biology-first company, so we very much confirm everything that we do experimentally. So we confirm those predictions very quickly in the lab.
Danuta: The next challenge after that is with genes involved. And here the 3D genome analysis is coming to the picture. And this is really based on the fundamental principle of what we discussed, how the genes are turned on and off. So the technology, and we are very much leading in that space, is enabling us to map the 3D genome structure at base pair resolution.
Danuta: And finally, we also have a third technology that is enabling us to confirm the causality. And usually here you would use CRISPR-Cas9, you will introduce a genetic change to confirm the impact on the gene expression and we have a completely alternative way of doing it which does not require genetic engineering, and is done in primary cells, and it's also done at scale.
Danuta: So for example, we're looking at lupus as one of the diseases that we're investigating, and here we're looking at hundreds of those variants, mapping them through a large number of different immune cell types, and from that, we're then looking for therapeutic interventions.
Kat: And finally, what are your hopes for the future of this technology and where do you want to get to with Nucleome?
Danuta: So our near term goals is to really build a drug discovery pipeline. So we already discovered a number of targets that we are very excited about. For a number of them, we already confirmed the causality. So we confirm that the variant impacts indeed the function of the dark genome, impacts the expression of the gene and also the protein level in the specific cell types that we identified.
Danuta: And very much we're starting the journey of building those drug discovery programmes, and the aim is that we also develop assets, so develop drugs against it, and we go to clinic. So this is the key for the organisation, is that we really translate the outcomes and the insights from the platform to something that can create impact and help patients.
Thanks to Dr. Danuta Jeziorska
