Taking shape

Kat - At the University of Montreal in Canada, Professor Anja Geitmann is developing models to explain how tiny tubes grow out of pollen grains to fertilise flowers under different conditions, such as zero gravity - her work has featured in the media with headlines such as "sex in space!" and worse. Naked Scientist Simon Bishop spoke to her to find out what she's actually up to.

Anja - We try to understand how plants function. Plants consists of cells just like the human body does. Only that the difference between the cells of a plant and that of a human is that the cells are surrounded by a wall and this wall consists, for example, of cellulose microfibrils. So, this is the stuff your clothes are also made from. And so, in order for such a cell to grow, it has to deform its cellulose material. In order to form a particular shape, it has to regulate the material properties, just like a balloon that blows up and becomes a sphere or becomes something more interesting. The plant cell that we work with is a very, very long tube. It's a catheter-like delivery tool of the sperm cells that serves to bring the sperm cells from the pollen grains to the ovules where the egg cells are housed in the flower. And so, in order to understand how this tube is formed, we do all kinds of stuff to it. We use inhibitors, we use enzymes, but the fun stuff we do is when we put it in the centrifuge and expose it to altered gravity conditions.

Simon - So, what do you find out by putting a plant cell, a pollen tube into first a microscope and then put it inside a centrifuge?

安雅——所以,离心机分辨的目的ase gravity, the effect of gravity. What we found is that all kinds of processes that are necessary in the cell to allow it to grow are affected. So, in the cell, things have to be transported from one end of the cell to the other. That is the same process that occurs for example in neurons, the cells of the human brain. This transfer process was affected strongly by gravity either by hypergravity or by microgravity - so, the absence of gravity. What we found is that as a result of this, growth was compromised and cell shape was altered. And from that, we can conclude that intracellular processes, although they occur at a micron scale are affected by mechanical influences such as increased gravity or lack of gravity.

Simon - So obviously, plants in natural conditions wouldn't experience extreme gravitational forces, but what you're doing is testing this to the limit so you can understand the forces that are normally involved in building a pollen tube.

安雅——因此,再保险花粉管是至关重要的一步production of plants that delivers the sperm cells. Without pollen tube growth, we won't have fruit, we won't have the next generation of plants. This process is easily affected by all kinds of influences. And so, we can imagine that effect such as microgravity or hypergravity - microgravity would be the case on the international space station or any other space travelling vessel, or hypergravity on a planet bigger than ours would affect plant growth. And so, we simply try to understand how plants function and use this as a tool - altered gravity as a tool to affect cellular functioning from a mechanical point of view.

Simon - And where next?

Anja - Okay, so the pollen tube is the cell that has very simple geometry. It's long and cylindrical. But what we really want to understand is how much more complex shapes are formed. So for example, if you look at the surface of a leaf, it has most intricate cellular shapes and we would like to understand how these complex shapes are formed and how they become to be functional during the development of a plant embryo into an adult plant.

Simon - Any plans to put other leaves and other plants into centrifuges?

安雅,那将会很有趣,把整个工厂into a centrifuge. What has been done of course is that we have grown plants in space. That means microgravity conditions and plant functioning is affected by this process. It's very difficult to actually pull apart what is the effect of the absence of gravity and what is the effect for example of the absence of convection. Convection is the absence of air movement that is a result of the absence of gravity. And so, there's a whole lot of challenges that are out there for us.

Kat - That was Anja Geitmann from the University of Montreal. And now it's time for a roundup of this month's genetics news.

Scientists from the Max Planck Institute for Evolutionary Anthropology in Germany have used new techniques to extract and analyse DNA from the bones of human ancestors from 400,000 years ago - the oldest early human samples ever analysed, publishing their findings in the journal Nature. The bones were recovered from a cave in northern Spain called Sima de los Huesos, or the Bone pit, are from the genus Homo, and are much older than our own species, Homo sapiens. Using just two grams of powdered bone, the researchers managed to extract and sequence the DNA from mitochondria, the 'energy factories' of the cells.

Analysis showed the DNA was similar to that taken from Denisovans, extinct relatives of Neandertals that lived around 700,000 years ago in Siberia. This is unexpected, as the bones look more similar to Neandertal remains. It may be that the Sima ancestors are related to an even older common ancestor of both Neanderthals and Denisovans, or that another group of mysterious hominins brought their genes over from Siberia.

The new results suggests that the origins of modern humans are more complex than previously thought, and the scientists are carrying out further analysis to try and straighten out the relationships between us and our early ancestors.

Kat - Moving from plants to animals, Professor James Sharpe, at the Centre for Genomic Regulation in Barcelona, Spain is using mathematical models to understand how vertebrates like mammals and birds build a skeleton. I asked him to explain how he and his team start to model something as complex as this.

詹姆斯——所以,it probably is a complex thing. In our case, we're trying to address the very first basic steps that have to be taken so that it's not too complicated. It's a question of knowing how many bones to have in each position in your structure. So for example for the arm, we have one bone in the upper arm, we have two bones, the ulna and radius, in the lower arm, and then we have five fingers. Our research is to try and understand how that basic arrangement is laid out.

Kat - Now, there's an existing model of how this works and that you have a gradient of a chemical that goes across the developing limb. It goes from one side to the other and that tells you where the fingers go. But you're coming at this from a different angle. What's that?

詹姆斯——所以,we're actually trying to resolve the fact that there have been two competing ideas to explain this. The alternative idea to the one you mentioned was an idea that was first proposed by Alan Turing in 1952, although he didn't propose it specifically for limb development. It was a general observation about how cells might be able to organise themselves. But his theory which was a self-organising theory rather than a positional information theory has not been considered so relevant for this question over most of the decades of research in this field. We and others are starting to realise and do research to show that in fact, this self-organising idea of his is probably the main mechanism underlying the initial distribution of fingers in your hand for example.

Kat - So, in its purest form, how does Turing's idea work? What sort of patterns does it generate?

詹姆斯——所以,it always generates patterns that are periodic, which is to say they're alternating states...

Kat - Stripy...

James - ...stripy or spotty. In two dimensions, that's stripy or spotty. It can only do that because it does not have information about what's going on over the whole field of cells. It works purely by a local communication between neighbouring cells. For this reason, it can only produce stripy or spotty patterns. But this is exactly the kind of pattern that our fingers are - it's essentially a collection of five stripes next to each other.

Kat - So, if you just leave cells to do their own thing, more or less, within certain parameters, they will just organise themselves into stripes and you had a lovely quote in your talk about how Turing said that explains the stripes of a zebra, but not the horse bit. How is your work trying to understand the horse bit skeleton underneath?

詹姆斯——所以,in this case, as I say, the horse bit is the skeleton, but it is essentially just another example of a set of stripes. So, it is exact theory, unchanged, can be equally applied to do something like the fingers as to the stripes on the outside of a zebra. So, we're simply doing computer simulations, modelling and experiments in the lab to actually test whether his hypothesis is a reasonable explanation of that process.

Kat - But the sort of patterns that Turing's mathematics generates, they're not the straight, regulated digits that we see on a hand - they're kind of a bit blobby and a bit funny. What else is going on in the development of an actual hand to give that more regular pattern?

James - So this is where we realised that to actually produce something useful like a hand, rather than just a random Turing pattern, we actually needed collaboration between a Turing-type self-organising system, and also we need some kind of positional constraint that control this system, which could loosely be considered as a kind of positional information. So our general conclusion about how these systems work is that actually, rather than being a conflict between two alternative possible theories, both of these theories are equally necessary to explain the final result.

Kat - So we already know that there are lots and lots of different genes that are turned on in the hands, in the limbs, in different places and at different times. So it's the interaction of those with the underlying pattern that's shaping our bodies, literally?

James - This is exactly what we think. We're still probably at early days and we have a lot further to go, but it is exactly those gene expression patterns, signalling pathways, gradients, which regionalise the tissue, which have different values in different places, which control the self-organising process.

Kat - In your talk you talked about the long bone of the arm, the two bones of the lower arm and then the five fingers. What about the wrist? There's loads of bones in there!

James - That's a very good question actually. It's been speculated that it might relate to something that was discussed in connection with Turing more explicitly, which is the difference between zebra stripes and leopard spots. So you can change a parameter of a Turing system to switch it from making stripes to making spots. In fact, the wrist bones are more like spots, and the other bones are like stripes. So it could well be that the parameter is tuned just in the wrist region to convert from stripes to spots.

Kat - So with the models you're generating, understanding the stripes, the spots, the parameters that they're tuned within - where ultimately do you want to take this work? To figure out how we can build a whole skeleton?

James - Well, in fact our interest is not to explain the skeleton of the rest of the embryo, but instead to focus on the limb and to bring in the other factors that are relevant for the limb. Our goal is to make a complete computer simulation or model of all the relevant important aspects of limb development. So we're dealing with the skeleton at the moment. We're also dealing with mechanical morphogenesis of the bud, we're also trying to understand the regionalisation - why the hand is different from the arm? And our real goal is to bring all of these together into a single computer simulation where we can then understand, potentially, the higher level more complicated aspect of how these different subsets, subsystems interact with each other to create the full organ. The real ultimate goal is to explain organogenesis as a whole.

Kat - Now we more commonly hear Turing's name mentioned with regard to his efforts in code-breaking and things like that. Many people don't know that he had these ideas about biological systems. Do you think more people should be aware of it?

James - Personally I obviously think more people should be aware of it. In fact, I went to the centenary meeting of Turing last year in Cambridge and even there I was shocked to discover that the vast majority of researchers that had come to the meeting were completely unaware of his contribution to this area of developmental biology, and in fact it was an area of mathematics that he contributed to. It spawned an entire new field of mathematics, and yet still - as you say - many people are not aware of his contribution.

Kat - And now, sixty years later, you're trying to bring it back?

James - Absolutely!

Kat - That was Professor James Sharpe from the Centre for Genomic Regulation in Barcelona.