eLife Episode 9: Redeye, Spies and Bacteria
In this episode of the eLife podcast we learn more about sleep, super Spy chaperones, swimming bacteria, orphan genes and the neuroscience of birdsong.
In this episode
00:36 - And so to sleep
And so to sleep
with Amita Seghal, University of Pennsylvania
Sleep - something that we spend a third of our lives doing, yet, we understand virtually nothing about. Amita Sehgal from the University of Pennsylvania has been studying the genetic mechanisms involved in sleep behaviour in the model organism, Drosophila melanogaster, and looking into the role of the newly-discovered RYE protein.
Amita - So, what we were trying to address is how sleep is regulated. The method we use is called a forward genetic screen. You mutagenise animals and then you look for ones that are altered in your process or behaviour of interest. In our case, that behaviour would be sleep. The system we use for these studies is the fruit fly D. melanogaster because it really lends itself beautifully to this type of approach.
Chris - And this sounds like a rather daft question, but do flies sleep in the same way that we do?
Amita - So, I don't know that I would go as far as to say that they sleep in the same way we do, but flies have a rest state that satisfies the criteria for sleep. We have been using it to figure out how sleep is regulated. A lot of what we're finding turns out to be also involved in controlling mammalian and human sleep.
Chris - So, you found some flies that took less sleep. I presume otherwise this paper wouldn't exist. So, what did you then do to try to find out why and how that was happening?
Amita - What we had used to generate these mutations, there's a chemical, it's called ethyl methanesulfonate, EMS for short. And so, what that does is, it makes changes in the DNA. So, what you then have to do is go and basically clone the gene that's responsible for the reduced sleep. And so, in other words, determine which of those many chemical changes in the DNA really accounts for the short sleep, and that is what we did.
Chris - So, what genes came to fruition? What did you find when you did this study?
Amita - So, at the end, we had it narrowed down to a region where there were 7 or 8 genes, and then we went through each of those to determine which was most likely. For various reasons, we were able to exclude all the others and then the one that we focused on was a change - a mutation - in a nicotinic acetylcholine receptor.
Chris - Tell us a little bit about that receptor. Was it linked to sleep before? What do you think that the mutation is doing to it and how did it affect the flies?
Amita - So, the nicotinic receptor has been implicated in sleep before. Acetylcholine is thought to generally be wake-promoting, as is nicotine. So, what was different about this one is that this turned out to be a receptor that does not promote wakefulness. It actually increases sleep. So, when you mutate it, you have less sleep.
Chris - Does this mean if you increase the expression of that gene where you found this mutation that this makes animals that need more sleep because it's a sleep-promoting gene?
Amita - Yeah, it's a great question and the answer is, no, with the caveat that you can never be absolutely certain that you have accomplished what you set out to do. So yes, we put this protein back in the fly. We tried to increase the expression to get more sleep and we didn't get it, but it could be that our protein never really was increased in expression in let's say, the right cell-type or the right parts of the brain. And that could be because the animal naturally controls the levels of this.
Chris - So, is it possible that in a normal fly, the expression of this gene is increased slowly over time as the animal becomes more relatively sleep-deprived until it reaches a threshold point where it makes the animal go to sleep? Is that what you see, because you would expect to see a sort of linear rise in the expression as an animal got sleepy, if it were the trigger? Do you see that?
Amita - That is in fact what we see. We see that the levels of this protein are high at times of sleep. The only thing is that, it does not seem to be a gradual rise. We need to do more experiments to determine whether maybe it is a gradual rise, but our experiments so far haven't seen that yet because we haven't looked at close enough time points.
Chris - Do you think the alternative is then that something might be tripping it to turn on? Could it be just not there at very high levels to start with because something else, which is sensitive to how sleep-deprived the animal is, is detecting the sleep deprivation level and when it reaches a critical threshold, it then triggers your protein to turn on and that's what triggers sleep?
Amita - That is the explanation we're currently favouring, yes. That it is not what we call the homeostatic signal, but maybe it is controlled by that other signal.
Chris - So, what have you christened this protein and how do you see it fitting into the genetic domino effect - for want of a better phrase - that we understand, makes the circadian oscillator that's in the brain?
Amita - So, we call this gene red eye, because that typically is associated with a sleep-deprived state. With respect to the circadian clock, we think that this is actually independent of the circadian clock. So, there are two systems that drive sleep. There's the circadian clock that makes sleep occur with a 24-hour rhythm and then there is the other system that just ensures that you get enough sleep. We think that this red eye protein is part of that other system.
06:16 - Flexible friends - protein chaperones
Flexible friends - protein chaperones
with James Bardwell, University of Michigan
Historically, a chaperone was someone who accompanied you when you went out and they made sure - in the words of University of Michigan scientist, James Bardwell - that inappropriate interactions didn't happen. Well proteins also have chaperones which are other proteins that help them to stay in shape and in the correct company, but how do they work?
James - Chaperones have been discovered back in the '60s and it's been known for a long time that they help proteins get their proper shape. But the real mystery is, how they could do that just not for one protein, but for a whole bunch of proteins because of course, every protein has a different shape and how can you have one particularl protein help a whole bunch of different shapes take place. There's been an idea for some time that these proteins that help other proteins fold have to be very flexible because they would have to of course, bind to proteins that have all different kinds of shapes to help them gain their proper shape. So, we just started out by taking this chaperone that had this, I think, lovely name, Spy. And we decided to try to make a better Spy.
Chris - So, how did you seek to explore what Spy was doing and then adjust it?
James - Well, we had developed a way to force organisms to fold proteins better. We actually linked the proper folding of a protein to antibiotic-resistance that an organism encoded. There's a gene that encodes resistance to ampicillin. So, we could set things up so that an organism was in sort of a fold or die situation. They'd have to either improve their folding or they would be killed.
Chris - So, how did you try to persuade the cells to optimise or improve this by?
James - Well, we just simply took Spy and we mutated it and then we demanded a higher level of antibiotic resistance than it had before. Nearly all of the bugs died, but those few lucky ones that had improved Spy survived. We looked to see what changes there were in those new Spies that work better than the Spy that nature had created.
Chris - So, if you were able to improve on Spy, why hadn't nature done that already?
James - That's a brilliant question actually and we wondered that for quite a while. So, what we did actually was, we went back and we looked to see what nature had done to Spy in other organisms. The organism we worked in was E. coli. Interestingly, in other organisms, nature has in many cases come up with the same solutions we did. So then the question becomes, well why isn't E. coli the best? I think it boils down to the fact that evolution optimises rather than maximises. For instance, I workout sometimes with a trainer and he's so muscle-bound that sometimes all his muscles just seize up and he can't even walk. So, he's incredibly strong, but he's not very agile.
Chris - But on the other hand, if you can see how it's improved and why it's improved under certain circumstances, you can then begin to infer how it's doing, what's it's doing, how it's achieving that improvement.
James - Exactly and that was the major motivation of our work, was to make something better and then maybe we'd understand how it worked in the first place.
Chris - So how did you do that? Did you have to then look at crystals of Spy to see what the structure was in its wild type, the original form, and then the mutant, the better form, to see what have changed?
James - Yes, so we had a structure so we could see at high resolution what the original Spy looked like and we knew what changes we had made. The changes we'd made that made Spy better were very, very specific.
Chris - If you look at those tweaks, do they give you some insights into what the function of Spy is in stabilising those proteins, how it's doing its job normally?
James - Yes, so if you look at them, a good number of them, in fact a majority of them, work by making an area in the centre of Spy. Now, Spy is a sort of very thin cradle-shaped structure. It looks kind of like a cupped hand. A lot of the changes were right in the middle of the palm and they made one part of the palm that we already knew was hydrophobic, in other words, sticky to oily substances, it made that part even oilier, even more hydrophobic. But it clearly wasn't just that, because it also seemed to make the protein much more flexible. So nearly, all the mutations we got made the protein more able to wrap around these other proteins and sort of cradle them and protect them.
Chris - And now, you've found this, what do you think are the key questions that you need to answer next?
James - Well, I think the real key question that we launched into in the paper was exactly what chaperones do to proteins and I think that's really the key question. So far, we're starting to get glimpses of that. I mean, we, meaning the whole chaperone community and it's a long-standing problem about exactly what chaperones do to proteins to help them fold. And so, I think that that's really the key question that this work opens up, that at least for this particular chaperone that we might be able to understand at anatomic resolution, what it looks like, a protein bound to a chaperone for instance.
11:53 - Twisting and turning: bacterial flagella
Twisting and turning: bacterial flagella
with Patrick Mears, University of Illinois, Urbana Champaign
Bacterial cells, such as Escherichia coli (E. coli), use their flagella, hair-like protrusions attached to their cell body, in order to navigate their way through the world. This allows them to avoid harmful environments or to move towards a positive source of nutrition. But how do bacteria control where they want to go? Or is it all down to probability?
Patrick - So the point of this study, we were interested in how the number of flagella on an E. coli cell affects its behaviour. So, E. coli are these single-celled organisms, small bacteria, that have flagella that help them to swim. The flagella basically look like corkscrews that rotate. They can rotate either clockwise or counterclockwise and they switch direction as the cell is swimming. And so, the direction of rotation of the flagella affects how the cell moves. And the cell, basically when it swims, it has two modes. There's one that we call a 'run' where the cell tries to swim in a straight direction and go forward. Occasionally, it does what we call a tumble. In the second tumbling mode, the cell pauses and sort of spins around and it eventually moves in a new direction.
Chris - So, that must introduce something of a problem for the bacterium to have to overcome because to produce meaningful net movement in one direction when it has variable numbers of these propulsion units which appear to be acting independently in this way. How does it surmount that? How do the bacteria end up producing a purposeful movement in a given direction?
Patrick - So generally, when the E. coli are swimming, all of the flagellum rotate in a counterclockwise direction. When they all rotate counterclockwise, they form a bundle where all of the flagella sort of wrap around each other and act as propeller. This pushes the cells forward. As I mentioned the flagella can switch direction. And so occasionally, one or maybe a few of the flagella will switch direction and rotate clockwise. When this happens, it breaks this bundle and that's when the cell pauses and changes direction. And so, the question we were interested in was, how does the number of flagella actually affect this behaviour because you might expect that a cell with more flagella would have a greater probability of having at least one of these flagella switch direction at any given time. And so, our basic prediction was that, cells with few flagella would only change direction once in a while but not very often. Whereas a cell with many flagella, we expected to change direction much more often.
Chris - And is that what you saw?
Patrick - No. To our surprise, what we saw was that a cell with one or two flagellum actually changed direction at about the same rate as the cell with 5, 6, or 7 flagella. So, this is a big surprise to us and it took us awhile to figure out what was actually going on. To look at this, we used two different strains. So, we used one strain in which the signal inside the cell that controls how frequently it's changing direction is controlled by the cell itself. And then we used the second mutant strain in which that signal was not controlled by the cell, but instead was fixed by a signal that we put into the cell.
Chris - Why should who has control make a difference? Why is that useful to you, being able to compare those two?
Patrick - So, in the strain where the cell controls it, these are the cells that are able to respond to an environment. And so, when a cell is going in a direction that's good, it wants to continue going in that direction. And so, it increases the probability of the flagella rotating counterclockwise. So basically, when a cell is going in a good direction, it tries to keep going in that direction. When the cell realises that it's going in a direction that's harmful or bad for the cell, it increases the probability of changing direction.
Chris - I see. So, this is quite neat. So basically, the bacterium is influencing the probability of any flagellum changing its activity and in this way, it is inducing a net change in direction. But it's not necessarily dictating which flagellum or cluster of flagella will do that.
Patrick - That's exactly correct. Then we looked at a second strain in which the signal is not controlled by the cell, but instead it's fixed in time. And so, the reason that we thought this might be affecting how cells of different number of flagella behave, is because in the strain in which the cell controls the signal, at any given time, the signal might be very high or very low. And so, if the signal is high, the probability of all of these flagella switching will be high. And so, many of the flagella can switch potentially at the same time. On the other hand, in the strain where the signal does not change, the probability is constant. And so, there is no compensation for the number of flagella. And basically, what we found was that in the strain where the cell controls the signal, cells with one or two flagella behaved very similar to cells with many flagella. They changed direction at about the same rate.
Chris - So, this is a rather natty and crafty, "clever" way for the bacteria to compensate for the fact they're continuously elaborating new flagella and they may have many, they may have few. But this means, the net result each time, regardless of number, is always going to be the same. It's going to be a purpose for swimming towards or away from an appropriate target.
Patrick - Yeah, that's correct. So, we have to refer to this type of feature as being robust because cells, regardless of how many flagella they have, behave similarly. Like you said, they develop this relatively clever system for compensating for that fact.
17:32 - The mystery of orphan genes
The mystery of orphan genes
with Christian Schlotterer, Vetmed University, Vienna
Orphan genes - sections of protein-coding DNA that appear to have no detectable homology with peptides from genomes of other similar species. So, how do new or orphan genes crop up in a population and where do they come from?
Christian - My name is Christian Schlotterer. I work at Vetmed University in Vienna. I'm a population geneticist and my interest is understanding adaptation and innovation that helps populations to adapt to changing environments. That novel genes can arise at a high rate has been well-documented in the literature, but if new genes arise at a high rate, why doesn't the number of genes increase over time? Because that's not what you see.
Chris - And how do these orphan genes or new genes come about? What's their origin?
Christian - They arise from previously non-coding DNA. Basically, there is DNA there and is not coding for protein and then suddenly, it can acquire a few mutations and then it gets an open reading frame and it suddenly has a function.
Chris - So, at what rate are these orphan genes appearing? If you look in fruit flies for example, in each generation, how many do you expect to see?
Christian - You don't see them in generations. You need hundreds of years...
Chris - So, how did you actually approach this problem then, given that you've got that long time scale, they're appearing over hundreds of years to thousands of years? How did you do the study you've done?
Christian - Well, I should say, maybe taking one step back, how have the orphans been detected beforehand? People were looking at basically isolated phylogenetic images. They didn't look at closely related species. So, what is novel in our study is that we looked at closely related species that were close enough that we could detect these novel genes there as well. So, what we did, we used the set of related species, we looked at relatives within increasing divergence age. So, they were species that split from a common ancestor at different time points in the past. The key thing we were not so interested in was the origin of these new genes. We were interested in basically asking what is the persistence time, how long do they stay around.
Chris - In other words, by looking at an orphan gene that's cropped up, but then subsequently disappeared, you can ask, well how long do they persist in each given arm of the population or each individual species' branch. And this gives you some insight into the persistence time of those orphan genes, and you can then ask whether some persist for longer or not.
Christian - Exactly. What we found is that there are several indicators that give you a hint when genes are persisting for a longer time, one will see expression intensity. So, if a gene is more highly expressed at a higher level then this gene is more likely to be persisting. At the same time, we also find that if the gene has more expression in males than in females, then this gene also has a higher chance to persist over longer evolutionary timescales than genes that have no bias.
Chris - Well, how do you account for that then, given that you have seen that and if you think that it's a surprise that those genes should cling on? Why do you think they do?
Christian - Well, that's a good question. I wish I would have a good answer to this. One possibility could be that we can distinguish between spurious transcription and genuine transcription because the way we identify whether a gene is basically a real gene is based on transcription only. And then we look at parts of the gene that are transcribed and have an open reading frame, this means they have a capacity to encode for a protein, and then these are basically classified as orphans. Nevertheless, it's well-known that parts of the genome are just randomly transcribed, and so, it could be that if you have a strong expression, this indicates that you really look at the genuine signal rather than maybe a spurious signal. I'm pretty sure, what we have classified as orphans, there will be some noise in there that may not actually be real orphans.
Chris - What about the sex bias though as well because that's also very intriguing? Why should there be a favour on the male's side to keep these things going?
Christian - Obviously, you caught me on the wrong foot. I have no good explanation. There wasn't an explanation why you could think that new genes, when they originate among male-biased because the idea was that you need simpler architecture of the regulatory module that's basically is responsible for the expression pattern of a gene. But our data basically focuses upon this hypothesis. So, we're left with an observation that's very difficult to understand.
Chris - Broadly, what do you think the implications are of what you've discovered? How would you - in a nutshell - say, this is important because...?
Christian - The importance of novel genes has for a long time been neglected. And so, I think, really to understand novelty in evolution, these new genes are probably one of the key factors that we need to understand better. Our study has made a major step in showing that these genes can persist for some time, but not all of them do. These novel genes, we applied population genetic tests, we see that there is selection preventing mutations occurring in these genes, and those are the best indication that there's something really functional.
23:21 - Lost in music - how birds learn songs
Lost in music - how birds learn songs
with Richard Mooney, Duke University
Within the brain of finches, the premotor cortex contains nerve cells that appear to be crucial for birds producing and learning the song they sing. Critically, the auditory input to these cells is switched off when the bird sings itself; otherwise, owing to delays in processing, the auditory signals would arrive after each part of the song has been sung, as Duke University scientist Richard Mooney explains to Chris Smith...
Richard - A longstanding problem we are interested in solving is how the brain uses auditory information to guide vocal learning. In the region of the bird's brain we were recording from, neurons receive input from auditory parts of the brain. In fact, it can show that when the bird is quietly resting, those nerve cells will respond to complex auditory stimuli such as the bird's own song. But those same neurons are also active when the bird sings. And so the question was, are these neurons actually integrating auditory information as the bird sings, or are they flipping back and forth from an auditory function to a motor function as the bird goes from listening to singing? The latter turned out to be the case, but we had to go a long way to find out that answer because it's a really tricky problem to answer in a singing bird.
Chris - Yes, indeed. So, did you record and show that there was a sort of temporal relationship in terms of the activity in those sites to prove that?
Richard - Yes. So in fact, the recordings involved were recordings from the same nerve cell in both states. Recording with a method that is really, really challenging to use, even in a cultured neuron that's sitting in a dish, and that is something called intracellular recording, where we use a really, really fine glass micropipette. When I say 'fine', the tipped diameters are maybe a 50th of a micron. We can use these fine glass pipettes to poke inside of a small nerve cell and we can record the little chatter of connections that are made under that nerve cell, from auditory and motor regions. So, we can actually probe whether the auditory inputs are active when the bird was singing. That's the real breakthrough in this study.
Chris - So, in other words, it is the bird listening to itself as it sings.
Richard - Well, we certainly know from behavioural experiments that it does listen to itself. But what we didn't know is whether or not these nerve cells, which seem so well-suited to do that kind of self-monitoring, are actually listening as the bird sings. And they're not. Even though we can show they get auditory input when the bird is quietly resting and listening to its song played through a speaker, those nerve cells will get excited. But when the bird sings, the cells are active again, but the auditory input is switched off.
Chris - So, what do you think the point is, of having this feedback loop if most of time it's suppressed when sound is coming out? Are the modifications based on audition to those cells made when there is not a motor programme being executed? Is that how you think the system works?
Richard - So, there are two parts to that answer. I mean the first is that we think these nerve cells are doing something more than just controlling what the bird sings, but also, helping the bird to identify and recognise the songs of other birds that have songs very, very similar to its own song. So, that's part of the answer. The other kind of curious twist is that these nerve cells, their auditory properties are clearly shaped by what the bird hears. Over development, they become tuned to what the bird sings. And other birds' songs that are very similar to the bird's own song will excite those nerve cells. Because the animal learns how to sing, that tuning property must reflect some kind of learning. So, they're clearly responding to auditory experience, but when the bird is singing, the auditory input is turned off.
Chris - I read a study previously where scientists were looking at basketballers and they showed members of the audience a ball leaving a thrower's hand. Some of those audience members were professional basketballers. Others were coaches, others were just members of the public. The professional basketballers they found were effectively executing in their mind's eye, the same throwing manoeuvre through their motor cortex that the pro was doing on the basketball court to make predictions. They were getting it right whether or not the ball would go in the basket about 90% of the time, compared to no better than chance for the coaches and members of the public who weren't doing that. Do you think you've got a similar situation here where these birds are effectively executing a sensory stimulus through a motor circuit to ask, "Would my song sound like this?"? And in this way, they are marrying up their song with what the other birds like them, songs sounds like and doing a different comparison.
Richard - I bet it is. Just like that. This is a very, very powerful idea and there's a so-called motor theory of speech perception that listening to speech sounds engages the motor circuitry in our brain that produces similar speech sounds and that forms the basis of perception.
Chris - And if we were to put the whole thing together, can you sort of build us a model of actually how you see all this fitting together?
Richard - Right. So, in the region that we're looking at, we think that this is a critical node for producing song and you can demonstrate this; by switching this brain region off chemically with a local anaesthetic, the bird will stop singing. So, we know that it is essential for the bird to make a song. What we guess, is that this song motor region produces a copy of the motor command and sends it into the auditory system and that copy contains information about what should happen. If the two signals are highly congruent then nothing happens. But if there's a mismatch, then the brain can say, "I made a mistake" and can learn from it.