Signal to noise
Building a baby is a complicated business, with millions of cells needing to work together. So how does it happen? Plus, how big data is making big strides in big genes, and our gene of the month is going round and round in circles.
In this episode
01:03 - Abbie Fearon - Signals in cells
Abbie Fearon - Signals in cells
with Abbie Fearon, ETH Switzerland
Kat - I've been off on my travels over the past month, including taking a trip to a Gordon Research Seminar at the Chinese University of Hong Kong, which was focusing on molecules known as fibroblast growth factors, or FGFs. But what are they? And what do they do? Abbie Fearon, a researcher from the Swiss Federal Institute of Technology in Zurich and co-chair of the meeting, gave me the low-down.
Abbie - Our cells need to be able to grow and divide, be able to form organs and basically make up the whole human body. To be able to grow, they need to be able to communicate with each other. And so, the growth factors are really important because that's how the cells communicate to each other. So, one cell will release growth factors and they will then go across to another cell and they'll bind to another protein that sits on the cell and then that transfers a message into the cell that tells the cell to grow and divide.
Kat - The conference that we're at is looking at fibroblast growth factors. What are they? I mean, what's a fibroblast for a start?
Abbie - So, fibroblasts are a specific cell type and the name fibroblast growth factor is actually slightly confusing. It's basically these proteins were originally found in fibroblasts. It's thought that the people who discovered them basically found these proteins, chucked them on a specific cell type, found that it made those cells grow and divide and so, just called them fibroblast growth factors. But they're actually really important in loads of different types of cells.
Kat - How many different sorts of these growth factors - these FGFs - are there?
Abbie - So, there are 23 different FGFs I think. There are probably 23 different FGFs and there are 4 different FGF receptors. And so, each of these different FGFs binds to another protein called an FGF receptor. And that's how the signal gets transmitted into the cell. Each of these different fibroblast growth factors binds to different receptors and so that's how you get sort of different signalling through the different pathways.
Kat - Because these were involved in making lots and lots of different parts of the body. So at some point, there has to be a - you're the signal to make that part of the brain and you're the signal to make that part of the body.
Abbie - Exactly and that's what's really important. So, FGF receptor 2 for example is what I worked on for my PhD and that's particularly expressed in the uterus. And so, only certain FGFs will bind to receptor 2 and will tell the uterine cells to grow and divide. But there can be other FGFs around and in the uterine cells that won't bind to that specific receptor and so therefore, you get this specificity that tells different cells to grow at different times and that's also important that the FGFs are released at different times which makes the cells grow at different stages.
Kat - It's all about getting the right cells doing the right thing at the right time in the right place to make an organism.
Abbie - Exactly, yeah. And that's one thing that goes wrong in cancer. So these FGFs are really important. They'll go wrong in cancer quite often so though they're really tightly regulated. So the signal only happens a specific time. But in cancer, we can have loads of these receptors for example that just signal without having any of the FGF bound to it. So then you'll lose all the specificity. And so then the cells just grow and divide uncontrollably.
Kat - It's just saying, "Go! Go! Go! And do this."
Abbie - Exactly, yeah.
Kat - And so, what are some of the things that we now know about these FGFs and how can we use that knowledge?
Abbie - And so, FGF receptors are particularly important for example in cancer. So there are drugs that will bind to the FGF receptors and can block them. And so, if we know that we can block the receptors then we know that we can - if this certain cancer is particularly reliant on that mutated FGF receptor, so the one that's over active, if we can block that using a drug then we can maybe treat patients who have got mutations in this specific receptor.
Kat - But how does the cell know which signals to listen and what's actually coming in if there's all these kind of signals and noise going on?
Abbie - There will always be a level of background noise. So you'll always have these multiple different proteins that are doing similar sort of things. But then you'll have a predominant pathway. So, that's particularly important when you have these different cells that are interacting. So you get some proteins, some FGFs that are released from a certain cell and you will have more of that protein in the mixture. So, that signal will be the predominant signal.
Kat - It's kind of like whoever is shouting loudest at that time gets heard.
Abbie - Exactly, yeah. That's an excellent way of putting it.
Kat - We're studying all these different kinds of signals and how cells communicate and how cells know what to do. Tell me a bit more about the work that you're doing? What are you studying particularly?
Abbie - So right now, for my post-doctoral research, I work on the liver and the liver has this amazing capacity to be able to regenerate so we can chop off about two thirds of the liver and it will grow back almost perfectly fine. It's the only organ that can do this so it's really interesting to understand how that happens. And whilst we have a broad overview of that knowledge, we really need to understand a little bit more how it does this. So, my work at the moment is predominantly focused on trying to figure out how the liver regenerates.
Kat - So, you're studying the sort of signals that say, "Ahh! Something awful has happened. Quick! We need to grow."
Abbie - Exactly. So, these signals that are probably really important in development and then get switched off in normal healthy humans are then somehow reactivated once the liver has had this massive injury. For example, just chopping some of it off and those signals can be reinitiated. It's amazing that the liver can do this, but this isn't seen in other organs. So, there's lot of scope to why this might be relevant to lots of different tissues.
Kat - That could really be amazing, could it, if you could just add the right growth factors and "Ahh! I can grow my kidney back again because my kidney has become diseased or grow my arm back again, so chop my arm off." Is that a future that we could be looking at?
Abbie - I mean, I think that's very, very far in the future and far away, but I suppose - I mean, this is the great thing about basic sciences. You don't know where it's going to end up. There are lots of different research projects that had started off just being, because we don't understand what's happening and then it ended up being there are treatments for cancers. So in the future, that could be really interesting.
Kat - It's something that people don't really think about that all our cells have got this crackling network of communication and all these signals being sent around. Is that how you view biology - this sort of network of signals?
Abbie - Yeah, completely. It's really strange now when I sometimes think about. In the day, I'm so focused on this one small thing but then you'd like to see them out slightly and it's this whole network of everybody talking to each other and there's so much background noise, and how do we get the specificity. Yeah, it's very, very visual in my mind then we're all talking.
Kat - It must be like sort of sitting and being bombarded by a hundred different TV channels at once.
Abbie - Exactly. It's just one massive conversation and then trying to break that down. It's difficult but just absolutely fascinating to me.
Kat - Abbie Fearon from the Swiss Federal Institute of Technology in Zurich.
08:32 - Jennifer Symonds - Building glands
Jennifer Symonds - Building glands
with Jennifer Symonds, NIH National Institute of Dental and Craniofacial Research
Kat - To find out a bit more about how FGF signalling is involved in building different parts of the body as a baby grows in the womb, I spoke to Jennifer Symonds, from the National Institute of Dental and Craniofacial Research in Bethesda, Maryland, who's focusing on the role of these growth factors in making your mouth water - building the salivary glands that produce saliva - or spit, as it's more commonly known.
Jennifer - So, we want to understand what are the different stem cells within the human salivary gland. So, most people don't think about salivary glands every day because they work. But when they stop working, you really miss them. And so, with salivary glands, they provide saliva which lubricates the mouth that helps for you to eat. But it also just maintains your oral health. So a lot of people who have salivary gland issues, they have a lot of dental caries or cavities, and they have a lot of dental health issues, and their lives are very uncomfortable and can be very painful. And so, in our laboratory, we're trying to understand what's going on with the normal salivary glands so that we can develop therapies for patients who are not making enough saliva. And to do that, we are looking at the different stem cells so that maybe we could turn these stem cells back on after damage like radiation or due to other diseases that can cause defects in salivary flow.
Kat - So let's kind of go a little bit right back to basics. Where do our salivary glands come from? How do they start being made?
Jennifer - So you have 3 major salivary glands and the next time that you bite into something sour like an orange or if you take a sip of soda, you'll feel little pings in the side of your cheeks and those are your salivary glands turning on because it's time to eat. You'll never notice it until you think about it. Now, every time that I eat, I can feel them, these little tingly feelings in the sides of my cheeks. Those are the salivary glands turning on. And so, they develop really early in development. So, your tongue actually is two pieces and when your tongue fuses together, that is when your salivary glands start. So, right when your face is starting to look like a face, that's when the salivary glands start.
Kat - So, this is when like a human or an animal is growing in the womb and it's all kind of coming together.
Jennifer - Yes.
Kat - It's that early stage.
Jennifer - Very early stage, absolutely.
Kat - How do you go about studying and trying to figure out what's going on there?
Jennifer - So, we use mouse models in our laboratory but you can use other animal models too. And so, we also use pigs. We have micro pigs that we are looking at in collaboration. I, unfortunately don't get to work with the pigs. They look very cute. But yes, we study it in developing mouse embryos.
Kat - What are you starting to understand about how the salivary glands form and maybe what's going wrong in some cases?
Jennifer - So, the different cells within the salivary gland, they have to divide so that they can make up the salivary gland as it develops because it starts off as this very, tiny, tiny little thing and it has to grow to be quite large because the salivary glands in the human, they take up a good portion of your cheek.
Kat - What do they actually look like and what's the sort of the structure of salivary gland? I can poke my face and I can't really feel anything. What does it look like inside?
Jennifer - It actually looks like a tree. And so, a salivary gland is a branching organ. And so, like the branches of a tree, if you imagine the branches of a tree are kind of like the highways of saliva that go into your mouth and then the leaves of the tree are where the saliva is formed. And so, it kind of looks like a bush or a tree, but it looks quite fluffy. It's actually a very pretty organ because it has all of these small circles at the end that make the saliva.
Kat - It's a fluffy tree full of spit.
Jennifer - It's a fluffy tree full of spit, absolutely. And you have three of them on each side of the face.
Kat - What do we now know about the kind of the genes that are controlling how these are made? What have we started to discover?
Jennifer - So we started to see that some of the genes that are important for other organs all over your body are also important in salivary glands which is very exciting for not just people who study salivary glands like me, but for people who study other organs that resembles salivary glands and some that don't. And so, there are certain markers of cells that we know marks the different progenitor stem cells within these different tissues. And a lot of them they're the same in mammary gland and in pancreas and in other tissues.
Kat - So you might not think that your mammary glands, your breasts have anything to do with your salivary glands, but they're kind of similar then.
Jennifer - They're very similar. And so, if you imagine the tree again, mammary glands are exactly like a tree that make milk. And so, the leaves make milk and it goes through the branches of the tree and then out the main duct. And so, many different organs in your body have that tree kind of shape which is why we call them branching organs.
Kat - As the salivary glands, mammary glands are developing, there have to be signals that say, "Okay, we're going to do this here. We're going to make this organ and do this branching." What are those signals? What have you discovered about how they're working?
Jennifer - So, there are specific proteins that are secreted by certain cells in these branching organs. One that I'm studying is called fibroblast growth factor and we call it FGF for short. What we found in the salivary gland and it's the same in other branching type tissues like mammary gland is that you need FGFs in order to steer these signals to make these branches because like when a tree grows, you start with one shoot, maybe a few leaves and then you get multiple different boughs and branches, and multiple leaves. We know that these factors - FGFs - are essential for this whole process.
Kat - Is it the same FGFs that are in the salivary glands or in the pancreas or in other tissues because there's lots and lots of different types of FGFs, isn't there?
Jennifer - That's right. There's many types of FGFs and what we have found is that certain FGFs are especially important for this branching. And so, my work has shown that FGF 10 and the signalling that happens downstream or what I mean is, after the growth factor, this FGF comes in contact with the cells, there's lots of activity inside the cell. And so, this particular FGF, FGF 10 is important for all of these branching organs.
Kat - I guess that's kind of quite clever evolutionary trick then. As if you need to make something that branched that releases fluid like pancreas or breasts or salivary glands, you kind of do it in the same way.
Jennifer - Yes. These mechanisms are absolutely conserved which is a brilliant trick of nature if you like to think of it that way. And so this way, you don't have to use all these different genes. It's nice in development because you only have certain pathways that you can use, but it's also nice for therapy. Because that means that what I find in the salivary gland could be used to help people who have problems with their pancreas or maybe with your tears. Your tears are also made from a branching organ. Your lungs are also a branching organ. And so, the things that I have found in the salivary gland could also be used to treat people with defects in their lungs, in their kidneys, pancreas, any branching organ.
Kat - So I guess by using these same kind of pathways, the same molecules, it means that really, there isn't such a thing as salivary gland gene that makes a salivary gland or a breast gene that makes your boobs.
Jennifer - That's absolutely right and sometimes I know that I wish there was a salivary gland gene. It would make my life a lot easier. But on the other hand, it's very fascinating to me that the same pathways are used in different organs that do different things at different stages of development, and even in different disease states. And so, it's also important to note that the pathways I study in salivary glands, these FGFs, they're really important for cancer because these same pathways that are essential for normal development get altered in cancer. And so, it's nice that the things that I learn about normal FGFs, I can apply to cancer. And so, it's kind of like piecing a part of the puzzle and you already know the pieces but they're going to fit together differently.
Kat - It's kind of the solution, isn't it to how we only have 20,000 genes but we may call these amazing different tissues. I sometimes think it makes biology really simple because you're only dealing with this many genes. But actually, it's really complicated because all these genes do lots and lots of different things.
Jennifer - I don't know if you played with Legos or building blocks as a child but I did. I love Legos. I still play with Legos. Biology is a lot like Legos. All the different pieces, they sound so simple. You have 22,000 genes that, it's not that many really especially you and I are both sitting here, we're both women. We're very different people. It's because of our 22,000 genes. It's the way the different Lego pieces are fitting together. And so, once you know some of the rules, you can see how you can take the same Lego pieces and you can build an airplane, you can build a castle, you can build a Star Wars thing like I did over Christmas. You can do lots of things with Legos and genes are the same way. And that's why you can use these same genes to develop a salivary gland, develop mammary gland, lots of different things because they're just like Legos.
Kat - What's going to be the journey from the kind of lab studies that you're doing to finding these treatments? Is this just the first steps along the pathway?
Jennifer - These are some of the first steps. In our laboratory, we have multiple projects to look at this. In one of them, we're treating with another secreted growth factor called Nuturin and it influences the nerves within the salivary gland. And so, one of our - it's a little closer to the clinic than where I'm currently working on is, we hope that if we can give Nuturin to patients in their salivary glands that have lost salivary gland function, that maybe we can turn back on the salivary gland. And so, that's a little bit closer to therapy than yes, the very early stages of my personal project on FGFs.
Kat - Now, you're having a quick sip of coffee, can you feel your salivary glands working?
Jennifer - Yes, we can. Coffee is rather bitter so they do turn on but seriously, everyone should take a sip of lemonade. It's beginning to be very hot. It's hot where we are here in Hong Kong. If you take a sip of cold lemonade, you'll be able to feel your salivary glands turn on. It's really fascinating that you can feel this. And so, the next time that you're eating, try to remember that your salivary glands are working really hard for you to have a healthy life. We should really care about salivary glands even though most of the time they work just fine and we don't even realise they're there.
Kat - Jennifer Symonds, from the US National Institute of Dental and Craniofacial Research.
19:17 - News - Happy birthday Dolly
News - Happy birthday Dolly
with Kat Arney
Happy birthday to youHappy birthday to youHappy birthday dear Dolly the SheepHappy birthday to you!
After 277 attempts, Dolly - the world's first cloned mammal, was born on the 5th July 1996 at the Roslin Institute in Edinburgh, thanks to the work of Ian Wilmut, Keith Campbell and their talented colleagues. However, her existence wasn't revealed to the world's media until several months later, in February 1997. Living until seven years of age before succumbing to lung disease and producing six normal lambs of her own in the usual biological way, Dolly was living proof of the power of reproductive cloning - taking the DNA of an adult cell, in this case from a mammary gland of an adult female sheep, and putting it into a sheep's egg cell from which the DNA had been removed.
Arguably the most famous sheep in the world, Dolly's creation sparked huge scientific and sociological discussions, with some people accusing scientists of 'playing God' and riding down a slippery slope to human cloning, while others saw potential advances for biomedical and agricultural research, as well as opening a door onto understanding how the unique environment of the egg can wind back the biological clock of an adult cell, and turn it back into an embryonic one. Since then, we've seen an entire menagerie of cloned animals appearing, from cloned cattle, camels and cats to dogs, mules and even monkeys. But - as yet - no cloned humans, due to an international moratorium on the practice.
We'll be bringing you a special edition of the Naked Genetics podcast from a symposium being held at the Roslin Institute in September, looking in detail at Dolly's scientific legacy, but for now - happy 20th birthday, Dolly.
21:25 - Timandra Harkness - Big genes, big data
Timandra Harkness - Big genes, big data
with Timandra Harkness, writer
Kat - Big data is the big thing in science right now, with researchers around the world generating and trawling through ever-bigger data sets in search of answers to ever-bigger questions. And, unsurprisingly, advances in gene sequencing technology have produced some huge piles of data for the number-crunchers to play with. So what are they doing? Timandra Harkness is the author of the new book "Big Data: Does size matter?" and I started by asking her, what exactly do we mean by 'big', when it comes to data?
Timandra - Part of the idea of it being big is obviously that there is a lot of it. That's one of the reasons we're able to do so much with the human genome is that, we're able to work through masses and masses of bits of information and computers are able to process it really fast and make sense of it. And that's why we've gone from the human genome taking years and costing billions of dollars to doing it within weeks for a thousand dollars. So that's one thing, but the other thing that a neuroscientist called Paul Matthews described to me as is the difference between large data and big data is, large data is just lots and lots of the same kind of data. But big data is different types of data that you could put together to get a more rounded picture. So for example, scientists like him might take genetic data but put it together with brain scans and even with the post codes of where people have lived, and weather reports from those areas so that you could get a picture of somebody's health that takes into account their genetics but also the environment they've been in and what illnesses they developed and really start to see how those factors interact.
Kat - What sort of information can we get out then? How is this useful, being able to make all these network of links rather than just going, "Okay, that links to that"?
Timandra - Well obviously, there are some cases where there's one gene, you can identify it and say, "That will cause you to develop this disease." But most of genetics doesn't actually work like that, that what it does is gives you a propensity for something or a risk of something. And then you're starting really to look statistically in saying, "Okay, you're more at risk of this because of this gene" or "Well, we've noticed that a lot of people with this combination of genes are going to develop this but not all of them. So, maybe we need to look at other factors and see if perhaps there's some lifestyle thing that you could avoid and that would cut down your genetic risk or whether there's something else going on that we haven't found yet the same combination with the genes because it's a nice idea that genes are just a digital thing and if the gene is there, something will happen, if it's not, it won't. But that's really not at all how it works."
Kat - Is there a problem with too much data in genetics? I talked to scientists and they say, "Oh God! We're just getting so much sequencing data or so much data from our experiments that we don't have time or the computing power to get through it."
Timandra - I think that is a problem because it's almost as if the ease of gathering data and the ability to store loads of data that we didn't have before makes it the default - you think well I might as well collect this because I can. But then it doesn't necessarily get you closer to the answer. So yes, there is the problem of actually being able to meaningfully process it. but the other thing is, a few years ago, I think there was a first flush of excitement about big data and people started saying, "Oh well! Theory is dead. We don't theories now because we'll basically just take all our data into a massive computer and the computer will do all the work and spit out the answers. We won't even have to ask the questions."
Kat - Sequence all the things!
Timandra - Exactly! A correlation will just give us all the answers. We won't care why things happen because all we need to see is which things happen together and that will enable us to prevent things. I think people are calming down a bit now and going, "Well, when we said theory is dead, we just meant it was having a bit of a lie down. And obviously, we'll still need causality and actually, we will sometimes still need a hypothesis. But the two can work together." So, you might look at some data and you're - what's essentially an artificial intelligence driven computer which has been looking at it for you, you might say, "Here are some interesting patterns. You might want to look at these. There might be something here." And then you go and use your human judgment and think, "Oh, well. Now actually, I can see why it's flagged that up but there's a perfectly simple real world explanation why people who live in cold climates might have low vitamin D because there's less sunshine. And when the sun is out, it's too cold to expose your skin to it." Or there might be something genuinely new that you would never have spotted before and then you can form a hypothesis and go and investigate it, and then vice versa, you might think, "I have a feeling from my other research. There might be a link here. Now, let's go back and look at the masses of data and let the computer do the trawling to see if there really is something there."
Kat - Are we going to start to get closer to answering some of those really big questions like, how do you go from the code in DNA into building a baby?
Timandra - I think it certainly got massive potential and I think scientific research is one of the really big areas of potential for big data. And certainly, the people I've spoken to are very excited by it, being able to deal with a lot of information and also, to combine things that you could never practically have combined before. But as I say, I think the people who, a couple of years ago maybe were getting over excited and saying, "This will transform everything and you won't even really need scientists because the computers will just tell us everything" are now starting to say, "Actually, no. you still need the human minds to make sense of it. But now, we have some amazing new tools to get us there a lot quicker."
Kat - Timandra Harkness, and her book "
Big Data: Does size matter?" is out now, published by Bloomsbury Sigma. And also a quick reminder that my own book -
Herding Hemingway's Cats: understanding how our genes work - is also out now, available in hardback, e-book and audiobook, According to the journal Nature it's "A witty, clued-up report from the front lines of genetics", while one of my heroes, Radiolab presenter Robert Krulwich described it as "a gorgeously written, surprisingly gripping introduction to everything we've learned about genes since the famous Human Genome Project several years ago", so why not give it a read?
28:00 - Gene of the Month - Roundabout
Gene of the Month - Roundabout
with Kat Arney
And finally it's time for our gene of the month, and this time it's Roundabout. First discovered in fruit flies in the early 90s, Roundabout is responsible for making a molecule that helps to guide the growth of the long tails of nerve cells - called axons - in the developing embryo, enabling them to make the journey from one side of the fruit fly larva to the other. In animals with a faulty version of Roundabout, the nerve axons start heading out in a straight line, but double back on themselves and end up growing round in circles, just like a car driving round and round a roundabout.
Some human versions of Roundabout, known as Robo genes, and their receptors have been implicated in a process called angiogenesis - the way in which new blood vessels grow into a tumour - as well as other aspects of cancer growth. And there are even tentative links between variations in human Robo genes and dyslexia, or even psychopathy, but much more work is needed to figure out whether the link is real, or the scientists are just going round in circles.