Control of Cell Growth in Animal Development
Transcript of Part 1: Regulation of Cell Size
00:00:07.00 So I'm Martin Raff from the Medical Research Council Laboratory 00:00:11.01 for Molecular and Cell Biology at the University College London in the UK. 00:00:15.00 And the subject I want to talk about today is growth control or size control. 00:00:21.03 How is it that the size of an animal, or one of its organs, 00:00:25.00 is controlled. Why is it, for example, that we grow 00:00:27.00 to be so much larger than a mouse? The answer is that we haven't really a clue 00:00:33.00 why we grow to be larger than a mouse, and the reason for that is largely that this problem 00:00:40.28 has not captured the imagination of developmental biologists 00:00:43.00 the way some other aspects of development have. So size control has been relatively neglected 00:00:48.00 and we don't understand much about it. 00:00:51.00 But what we do understand is that the size of an animal 00:00:54.01 and one of its organs depends on two things 00:00:58.00 the total cell mass, which in turn depends on cell size and cell number, 00:01:02.00 and the extracellular materials, largely proteins in the form of extracellular matrix 00:01:08.00 that can be cuticle, or it can be a shell, or it can be bones and so on. 00:01:14.00 In the case of mammals it is largely cell numbers that matter most. 00:01:19.00 So we are about 3000 times larger than a mouse, 00:01:24.02 and we have about 3000 times more cells than a mouse. 00:01:28.00 So it is largely cell numbers that one needs to be concerned about in size control in a mammal. 00:01:34.00 Cell number in turn depends on two processes, one is cell division, 00:01:40.01 or cell proliferation, and the other is cell death. 00:01:43.00 Both of these contribute to determining the size of an animal or one of its organs. 00:01:50.00 Now, in thinking about the control of the size of an organ, there is two kinds of processes. 00:01:58.00 There are those that operate in intrinsically in the organ to help determine its size, 00:02:02.01 and then there is this systemic control, endocrine controls for example 00:02:06.00 that help control size. Don Metcalf working in Australia in the 1960's 00:02:12.02 did a series of very interesting experiments 00:02:15.00 that gives you some sense of internal versus extrinsic control. 00:02:21.00 In the first set of experiments, he took the thymus glands from newborn mice 00:02:27.01 and put multiple thymus glands into a newborn mouse 00:02:31.03 under the skin, under the kidney capsule, let the mouse grow up 00:02:35.00 and then took the thymuses out and asked what size they had grown to. 00:02:40.00 And the result was clear cut. They grew to be the size of a normal thymus. 00:02:44.01 It didn't matter how many thymuses 00:02:45.00 were growing in the mouse, each one grew to be its normal size. 00:02:49.00 So it seems that the thymus knew how big it should grow to 00:02:53.00 and did it independently of what was going on elsewhere in the animal. 00:02:57.00 On the other hand, when Metcalf looked at the spleen, 00:03:01.01 he got the opposite result. When he put multiple 00:03:03.00 spleens into a newborn mouse and let the mouse grow up 00:03:07.02 and then take the spleens out and measure their mass, 00:03:09.00 the total mass of all those spleens equaled the mass of a normal spleen in a normal mouse. 00:03:16.00 It looks as though the control was largely outside the spleen. 00:03:21.01 And for most organs its a combination of intrinsic control and systemic control or extrinsic control. 00:03:28.00 The systemic controls on growth that are best understood are those that operate 00:03:36.02 in the growth hormone insulin-like growth factor one, the IGF-1 pathway. 00:03:42.00 The way that the pathway works is the hypothalamus produces growth hormone stimulating 00:03:51.01 or releasing hormone. That acts on the anterior pituitary 00:03:55.00 causing it to secrete growth hormone into the blood. The growth hormone then 00:03:59.00 stimulates the liver and other cells in other tissues 00:04:02.03 to produce insulin-like growth factor 1, IGF-1, which in turn induces cells to grow, 00:04:09.00 promotes their survival, and in that way promotes the grow of tissues, organs, and the animal. 00:04:14.03 In mammals such as a mouse or us, this system accounts for about 2/3 of our growth. 00:04:20.00 If you would activate growth hormone, or IGF-1, and the receptors, 00:04:24.01 then a mouse would grow to about 1/3 the normal size. 00:04:28.00 This system accounts largely for variations in size within a species. 00:04:33.03 But it's really not that problem that interests me, it's why are we so much larger than the mouse? 00:04:41.00 And no matter how much growth hormone you give a mouse, or how much IGF-1 you give a mouse, 00:04:45.03 you can increase it's size perhaps to double its size, but you cannot even make it the size of a rat 00:04:51.00 let alone the size of a human. So we still don’t' have any idea why we grow to be so much larger than a mouse. 00:04:59.00 I want to talk about two cell systems that we have used to assess growth control. 00:05:07.01 Both of them are glial cells, supporting cells in the nervous system. 00:05:12.00 One of those is the Schwann cell that wraps around axons 00:05:16.03 in the peripheral nervous system to myelinate them. 00:05:19.00 The other is the oligodendrocyte that myelinates axons in the central nervous system. 00:05:26.00 It's really the cells that give rise to the differentiated myelinating cells that I'm going to talk about. 00:05:33.00 So first I'm going to talk about cell size control and we'll use Schwann cells to address that problem, 00:05:42.00 and then I will turn to cell proliferation control and I will turn to 00:05:47.03 the oligodendrocyte precursors that give rise to oligodendrocytes. 00:05:52.00 Let's begin then by looking at cell size control. Here's the nature of the problem. 00:06:01.01 It's known in all organisms from bacteria to humans that the size of a cell 00:06:09.00 is roughly proportional to the ploidy, the number of chromosomes. 00:06:13.00 So a haploid cell in the same organism is generally smaller than a diploid cell 00:06:17.03 and a tetraploid cell is larger than a diploid cell. 00:06:21.00 But if you look at a single organism such as a mouse or a human, 00:06:25.01 most of the cells are diploid, and yet they vary enormously in size. 00:06:30.01 For example, this nerve cell in the retina of the monkey is very much larger 00:06:34.02 than the lymphocyte in the same animal, yet they are both diploid. 00:06:41.00 We have no idea why a cell such as a nerve cell grows to be so much larger than the lymphocyte. 00:06:48.00 It's a very important question, and there are very few people who have been studying this problem, 00:06:54.02 which is why we know so little about it. 00:06:57.00 But the problem that I want to talk about is a different one, 00:07:00.02 It's when a proliferating population of cells divide, generally they double their mass, 00:07:07.01 double the number of organelles, and then they divide in this way 00:07:12.01 to maintain the size of this typical proliferating cell. 00:07:15.00 So the question that one wants to know the answer to is how does a 00:07:21.01 proliferating cell coordinate its growth so that when it divides it maintains the appropriate size. 00:07:30.00 Now largely from studies in yeast, there are some ideas of how cells coordinate their growth, 00:07:36.02 but I should say that there is much less attention to cell growth than their has been to cell division itself. 00:07:44.00 Yet cell growth is as fundamental to life. Any organism, bacteria, plant, animal, it doesn't matter, 00:07:53.00 could not grow unless cells grow. If all that happened was cells divide 00:07:59.00 the cells would get smaller and smaller and smaller. So cell growth is as fundamental 00:08:04.00 to biology as cell division. Yet for each lab that studies cell growth there is probably 00:08:11.00 hundreds or thousands of labs that study cell division 00:08:13.00 and it's actually easier to study cell growth, and there is no rational reason why that should be so. 00:08:19.00 One of the problems is terminology. For example, the term "cell growth" is used by most biologists 00:08:29.02 to mean cell proliferation. So there isn't even a term that we have to mean cell enlargement and increase in cell mass. 00:08:37.00 There's a perfectly good phrase for cell proliferation: cell proliferation. So one should really use cell growth 00:08:44.00 to mean precisely that: cell enlargement, an increase in cell mass. Most people do not, but I will. 00:08:51.00 The other term that is confusing is "growth factor", which is used to describe extracellular signal molecules, 00:09:01.00 usually proteins, that stimulate cells to grow, stimulate cells to divide, 00:09:06.00 stimulate cells to survive, stimulate cells to differentiate, and often very little attempt 00:09:11.02 is made to distinguish whether a growth factor is stimulating cell cycle progression to division or cell growth. 00:09:19.00 So these are terminology problems within the field that has held it back and continues to do so. 00:09:25.00 Largely from studies in yeast, it is thought that one way that proliferating cells coordinate their growth 00:09:35.00 and division to maintain an appropriate size, is that cell growth limits progress through the cell cycle. 00:09:42.00 An extreme form of that is the notion that cells may have cell size checkpoints in the cell cycle control system. 00:09:52.00 For example, there is thought to be, at least in some yeast, a cell size checkpoint in G1, 00:09:59.01 where the cell cycle control system can pause 00:10:03.00 to assess the cell size and make sure it's large enough before entering S phase and replicating the DNA. 00:10:09.00 And in some yeast and in some other cells it is thought that there may be another cell size checkpoint in G2, 00:10:16.02 where the cell pauses to make sure it is large enough before it goes into mitosis and divides. 00:10:24.00 The studies I want to talk about were done by a very talented graduate student, Ian Conlon, 00:10:30.03 who has now left science and works for the Civil Service in Britain studying cell traffic control in London. 00:10:38.00 He studied the cell growth control of Schwann cells. 00:10:44.00 These were studies done many years ago by two post-docs, Kay Fields and Jeremy Brockes, 00:10:49.01 who showed that you can use antibodies to distinguish cells that are isolated from 00:10:55.01 the newborn rat optic sciatic nerve, peripheral nerve, and you find two main types of cells in those cultures. 00:11:04.02 You see these red Schwann cells and the green fibroblasts and if are labeled with different antibodies, 00:11:11.00 you can use these antibodies to not only distinguish the different cells, but also separate them. 00:11:17.02 In that way you can purify the Schwann cells, and Ian used purified Schwann cells from the rat newborn sciatic nerve. 00:11:26.00 In order to study cell growth independently of cell cycle progression and cell division, 00:11:35.00 he blocked cell cycle progression in S phase by using aphidicolin, 00:11:41.00 a drug that blocks DNA polymerase alpha that's required for DNA replication. 00:11:47.00 Therefore the cells are arrested in the cell cycle in S phase, 00:11:52.00 and he studies cell size by measuring the volume of the cell in a Coulter counter, 00:11:59.00 which measures cell volume by the displacement of fluid, so it doesn't matter what the shape of the cell is. 00:12:05.00 In this experiment he shows that cells proliferating in serum continue to divide and there is a 00:12:12.03 spread of cell volumes as you can see here. If you block the cells in aphidicolin after one day 00:12:20.02 the cells continue to enlarge even though they are no longer going through the cell cycle 00:12:26.00 and so the average volume of the cell has increased dramatically. 00:12:31.00 And so that is his assay: aphidicolin arrested cells to measure the growth of the cells. 00:12:38.00 To know that cell volume is of interest, because what you are actually interested in is cell mass, 00:12:47.02 to know that the volume is reflecting cell mass, 00:12:50.01 he collaborated with Graham Dunn at Kings College in London 00:12:54.00 to study the dry mass of Schwann cells growing under these same conditions. 00:12:59.01 He uses microinterferometry to do that. And you can see that the result 00:13:05.00 is the same: cells proliferating in serum without aphidicolin have an average dry cell mass 00:13:11.01 that is relatively low compared to the cells that have been arrested with aphidicolin for 24 hours. 00:13:17.00 So he's confident that he gets the same result measuring cell mass as he gets for measuring 00:13:22.02 Coulter counter volume and he continues to use volume because it is much more convenient. 00:13:28.00 Now these Schwann cells that are arrested in aphidicolin, they will continue to grow for days. 00:13:36.00 They get bigger and bigger and bigger and Ian never found an upper limit to the size of a Schwann cell. 00:13:43.00 Now there must be an upper limit, but I'm not aware of anyone who knows 00:13:47.02 or has asked the question: what is the upper limit size for any cell type within an organism. 00:13:55.00 And we still don't know if there is an upper limit, there must be for the Schwann cell, 00:13:58.02 and when you got to that upper limit what it is that's limiting growth at that point. 00:14:04.00 So now he asks, does cell growth require signals in the extracellular space to simulate the growth. 00:14:14.03 By and large cell divisions, cell survival, cell migration, 00:14:17.02 most activities of cells depend on being signaled by other cells 00:14:23.00 that's the way animals work, so that cells behave in a way that is appropriate for the entire organism. 00:14:29.00 And here he shows that it is indeed the case. So here the population of cells in heterogeneous volumes 00:14:35.01 growing in serum, you block them in aphidicolin, they continue to grow and so the cells are very much larger. 00:14:42.00 But if you block in aphidicolin and there is no serum there and no growth stimulant 00:14:48.00 in the extracellular fluid then the cells do not grow. 00:14:51.00 So growth, like cell division, cell migration, depends on signals from other cells. 00:14:57.00 Now he's in a position to look at known growth factors that have been shown 00:15:03.02 to be important for stimulating Schwann cell proliferation both in culture and in the animal. 00:15:10.00 One of those is insulin-like growth factor one, IGF-1 that I mentioned earlier, 00:15:14.00 and the other is the neuregulin glial growth factor, GGF. So here he's used the aphidicolin trick again, 00:15:23.01 blocks the cells with aphidicolin, and the only signaling molecule added in this case is IGF-1, 00:15:32.01 and that indeed in this 24 hour period in the aphidicolin blocked cells induces the cells to grow, to get larger. 00:15:39.00 Whereas glial growth factor, the neuregulin at subsaturating and saturating concentrations 00:15:46.01 has no effect on cell growth. Indeed, these, although they are called growth factors, 00:15:52.01 are not really growth factors for Schwann cells, whereas IGF-1 is. 00:15:58.00 Moreover, if you look at cells that have been stimulated to grow by IGF-1, 00:16:03.01 adding glial growth factor even at saturating concentration doesn't do anything, doesn't increase the growth. 00:16:11.00 So IGF-1 is a growth factor for Schwann cells, glial growth factor is not. 00:16:17.02 But I told you that both of these factors have been shown to promote the proliferation 00:16:21.00 of Schwann cells, both in culture and in the animal. So it turns out that glial growth factor is a mitogen, 00:16:29.02 and I'm using that term for an extracellular signal that simulates cells 00:16:34.00 to go through the cell cycle and in particular go through G1 into S phase. 00:16:40.00 Here he is using an assay incorporation of BrdU, bromodeoxyuridine, into DNA as a measure of the cells 00:16:49.01 moving through G1 into the S phase. And you can see that IGF-1 is pathetic at inducing cells 00:16:57.01 to move into the S phase. It is a weak mitogen on its own, hardly any activity, 00:17:02.03 whereas glial growth factor on its own is very potent 00:17:05.02 in inducing cells to progress through G1 into the S phase. 00:17:09.00 Surprisingly, when you add IGF-1 and GGF together, now you get a much bigger response, 00:17:16.01 so that IGF-1 on its own is weak, but it can synergize with GGF 00:17:21.00 to drive the cell through the cell cycle. This discrepancy between the activity of a growth factor on cell growth, 00:17:30.03 cell enlargement, and cell cycle progression has been shown by others in other cell systems. 00:17:36.01 This is not going to be confined to Schwann cells. 00:17:39.04 So Zetterberg studying mouse 3T3 cells showed IGF-1 stimulates growth, 00:17:45.00 whereas epidermal growth factor EGF stimulates cell cycle progression. Delue et. al. showed using 00:17:50.01 dog thyrocytes, IGF-1 stimulates growth, whereas thyroid stimulating hormone, TSH, 00:17:56.02 promotes cell cycle progression. So it looks that there will be a number of extracellular signals 00:18:03.00 that have different effects on growth and cell cycle progression. 00:18:07.00 One thing you would expect of a mitogen such as GGF, is that it would stimulate the production of 00:18:15.01 a G1 cyclin that is required to activate the CDKs, 00:18:19.02 the cyclin-dependent kinases that operate in G1 of the cell cycle. 00:18:24.00 Here Ian has looked using western blotting at two cyclin Ds, cyclin D1 and cyclin D2. 00:18:31.00 As you'd expect, GGF, which is a potent mitogen, stimulates the increase, the synthesis, 00:18:39.01 of cyclin D1 and cyclin D2 proteins in this 4 hour assay in GGF. Whereas IGF-1, which is a potent growth factor 00:18:48.00 but a weak mitogen has very little effect on cyclin D1. You can't see any stimulation 00:18:54.03 where there is a weak simulation of cyclin D2. Interestingly when you add IGF-1 and GGF 00:19:03.01 you don't see any greater stimulation of cyclin D1 and D2 proteins compared to GGF alone. 00:19:11.00 So this is not the location of the synergy. We don't understand, yet, 00:19:16.00 how IGF-1 synergizes with GGF to promote cell cycle progression. Now you might ask an interesting question, 00:19:27.13 why should glial growth factor and IGF-1 both of which bind to the same class of receptors, 00:19:34.02 receptor tyrosine kinases, which activate the same types of intracellular signaling molecules, 00:19:40.01 why should be they have such different effects on the Schwann cell, 00:19:45.00 one inducing growth, one stimulating cell cycle progression. Usually when you see that discrepancy on 00:19:50.02 receptor tyrosine kinases, it has to do with the kinetics of the responses inside the cell along signaling pathways. 00:19:59.27 So Ian looked at two signaling pathways. He looked at the activation of the MAP kinases, 00:20:07.02 ERK1 and ERK2 using western blotting again, using antibodies that recognize 00:20:13.01 the phosphorylated activated forms of ERK1 and ERK2. 00:20:17.00 And then looked at signaling along the PI3 kinase Akt pathway by looking at phosphorylated and activated Akt. 00:20:27.00 And what he saw is that with GGF, which is a potent mitogen, there is sustained activation along 00:20:36.01 the MAP kinase pathway as seen here. For the full 24 hours in GGF you see activation of these two MAP kinases. 00:20:44.00 Whereas in IGF-1, you see a transient activation for only one or six hours and then it is gone. 00:20:54.00 For IGF-1 that stimulates cell growth and is a poor mitogen on its own, you see the opposite. You see a sustained 00:21:02.02 activation of the Akt kinase whereas you see a very transient one hour and then off 00:21:10.01 activation of Akt with GGF. So sustained activation along the PI3 kinase Akt pathways stimulates 00:21:20.01 growth in this situation, whereas sustained activation along the Ras MAP kinase pathway 00:21:25.01 seems to stimulate cell cycle progression, and that's been true in 00:21:28.03 other cell systems although not all cell systems. So now Ian is in a position to do the crucial experiment 00:21:37.02 that he was aiming at all along, which is what would happen if you kept cell growth constant 00:21:44.01 by keeping a constant concentration of IGF-1 at a saturating concentration, 100ng/ml. 00:21:51.00 So now growth is going to be constant, and now you vary the concentration of GGF the mitogen, 00:21:58.00 which has no effect on growth and ask what happens to cells when you increase the concentration 00:22:04.03 of GGF keeping cell growth constant. As you might expect in the high concentration in blue of GGF, 00:22:13.02 the cells go through the cell cycle faster even though they are growing at the same rate, 00:22:17.02 they go through the cycle faster. So cells accumulate faster at 48 and 72 hours 00:22:23.02 there are more cells in high GGF than there are in low GGF in red. Well if cells are going through the cycle faster 00:22:33.02 but they are growing at the same rate in high GGF compared to low GGF, 00:22:39.00 then the cells having less time to grow should be smaller. And indeed that is exactly what Ian sees. 00:22:45.03 In high GGF, at the saturating concentration, the cells are smaller on average than those cells proliferating 00:22:53.03 in low GGF, and that’s true at every phase of the cell cycle. If you look at cells that are rounding up to undergo mitosis, 00:23:01.02 you can see in high GGF the mitotic cells are smaller than in low GGF. 00:23:06.00 That is quantified in this graph here. If you do the experiment of labeling the cells with BrdU to label the S-phase cells 00:23:16.03 and then separate the S-phase cells in a fluorescence activated cell sorter and ask what about cells 00:23:23.03 that have been proliferating in high GGF compared to low GGF, you find again the S-phase cells 00:23:30.03 are smaller in the high GGF cells. So at all phases of the cell cycle, cells growing in high GGF and 00:23:40.01 proliferating in high GGF are in fact smaller as you'd expect, because they have less time to grow. 00:23:48.00 So the conclusion then from these studies of Ian's on Schwann cells is that the size of a Schwann cell, the time of division, 00:23:59.02 depends on how fast the cells are growing and how fast they are going into the cycle. They are going through 00:24:06.09 the cycle slowly and have more to grow, the cells will be bigger at division if they are going through faster, 00:24:11.10 they'll have less time to grow and they will be smaller. And the rates at which the cells go 00:24:15.02 through the cycle and the rate at which the cells grow depend on 00:24:20.01 extracellular signals and their concentrations. 00:24:22.00 Some of these signals stimulate growth primarily, that is enlargement, 00:24:26.03 some stimulate cell cycle progression primarily, and some stimulate both. 00:24:32.00 So in these studies, Ian saw no evidence for cell size checkpoints, but none of these experiments 00:24:42.01 exclude the possibility that there are cell size checkpoints operating in Schwann cells. 00:24:47.00 Now one reason for conceptually thinking there must be cell size checkpoints is that in a 00:24:56.00 population of animal cells or yeast cells proliferating in culture, there is a distribution of sizes 00:25:03.00 and that distribution remains constant if the conditions in the culture is constant 00:25:07.00 over weeks, months, and years as the cells proliferate. But if big cells grow faster than little cells, 00:25:14.01 and intuitively that’s what you would think because a big cell would have more ribosomes and so on, 00:25:20.00 then you would expect in a population of a distribution of cell sizes 00:25:26.00 the big cells growing faster than the little cells would get bigger and bigger 00:25:29.02 and separate from the little cells, and you would see this size distribution spreading over time and you do not. 00:25:37.00 That would argue cells must have some kind of cell size checkpoint. So the question then becomes, do big cells 00:25:46.06 grow faster than little cells and the reason for thinking they do other than intuitively is a very important experiment 00:25:53.00 done by Paul Nurse and Kim Nasmyth years ago when they were post-docs in Scotland. 00:25:57.00 They studied a mutant fission yeast that is mutant and blocked in S-phase and not surprisingly 00:26:07.03 therefore as these cells proliferate cell number remains constant because 00:26:11.01 they are blocked in S-phase, DNA levels stay constant because they are blocked in S-phase, 00:26:15.02 but if they look at the amount of protein per cell, 00:26:19.00 it gets bigger and bigger and bigger, and big cells, these cells that are growing and getting bigger and bigger and bigger 00:26:27.00 are adding more protein per cell as they get bigger. Note this is an exponential Y-axis and 00:26:35.03 this looks like an exponential increase in the growth rate. Whether it is or not is uncertain, but what is certain is that 00:26:44.03 big yeast cells are growing faster than little yeast cells when they are blocked in S-phase by a mutation. 00:26:52.00 So Ian studied Schwann cells in this same sort of way to ask: do big cells grow faster than little cells? 00:27:01.00 And the surprising result is the answer is no. Unlike yeast cells, large Schwann cells and 00:27:07.09 small Schwann cells seem to grow at the same rate. 00:27:09.00 So here are cells that have been in aphidicolin now for 9 days, 00:27:13.02 so these cells are very much larger in volume as shown on the Y-axis here, 00:27:20.01 than these cells. But if you look at the amount of volume they are adding each day, 00:27:25.02 it's the same, whether the cell is large or the cell is small. So the cell must care to keep its growth rate, 00:27:34.02 the amount of volume it's adding per day, independent of how big the cell is. So one explanation for Schwann cells 00:27:44.02 growing at a linear rate independent of their size would be that maybe Schwann cells have an intrinsic growth rate 00:27:50.00 and it doesn't matter what their size is, that is their growth rate. Well it turns out that it doesn't work like that 00:27:57.00 because cells in 1% serum are growing at a particular rate but if you stimulate growth more with 3% fetal calf serum 00:28:04.01 the slope increases, it remains linear, big cells grow the same rate as little cells, 00:28:09.01 but the rate of growth is greater. At 10%, the rate is even greater and Ian's gone up to 40 or 50% 00:28:15.01 and the growth rate is even greater. So the growth rate is variable depending on the stimulus 00:28:22.00 but in each case, big cells and little cells are growing at the same rate. What that means is if big cells and 00:28:30.05 little cells grow at the same rate, and if they go through the cell cycle at the same rate, 00:28:34.00 then you don't need a cell size checkpoint to explain why the distribution of sizes remains fixed as cells proliferate. 00:28:42.00 But a question would be: why is it that yeast seem so different from these Schwann cells? Because there, 00:28:50.11 when you block in S-phase with a mutant, you see big cells growing at a much greater rate than the little cells. 00:28:57.00 So one possibility, because we are used to thinking that these basic phenomenon like cell division and cell growth are conserved 00:29:06.02 in their mechanisms from yeast through humans in evolution. So it was surprisingly to find this difference. 00:29:14.00 One possibility is the assays are different, so Ian is measuring growth by looking at the increase in cell volume, 00:29:21.02 and Nasmyth and Nurse were looking at proteins per cell. Another possibility is the use of aphidicolin 00:29:29.03 so Ian went back and did these experiments again now measuring, instead of volume increases. looking at protein per cell. 00:29:38.00 He found the same thing as when he measured with volume, that here cells growing in 3% grow at a rate 00:29:45.02 that is slower than when they are in 10%, but still the big cells and the little cells are growing 00:29:52.01 at the same rate, it's linear. So it seems very unlikely that it's that assay. 00:29:57.00 Another possibility though was aphidicolin. You always worry when you use drugs 00:30:01.01 that it's doing something you don't know, and could be disturbing and confounding the analysis. 00:30:06.00 So we looked through the literature to try to find an example where people looked in vivo 00:30:11.01 at the growth rate of mammalian cells, and it was surprising how hard it was to find, but we found one example of a paper 00:30:19.02 published but Hutson and Mortimore in 1982 where they used a model that has been used widely, 00:30:25.16 that if you starve the mouse or a rat the liver rapidly shrinks and over a two day period 00:30:32.01 it drops dramatically in size and that's because the hepatocytes, 00:30:36.03 the liver cells, shrink in size, not because there is cell death. 00:30:40.00 Now after 2 days of starvation, you refeed these starved animals and very rapidly 00:30:48.01 the liver regains its size and in fact it overshoots and becomes larger than normal. 00:30:54.00 And all of that growth is because the liver cells get bigger and bigger and bigger when you refeed them. 00:31:01.00 Notice this is a linear scale and this growth is linear. The big cells are growing at the same rate 00:31:09.02 as the little cells, so there is no aphidicolin these are liver cells not Schwann cells, and they are in vivo, 00:31:14.28 not in a culture system. So my suspicion is that for mammalian cells at least, cell growth is independent 00:31:22.24 of size at least for these types of cells. Now as I said a moment ago, if big cells and little cells grow 00:31:32.27 at the same rate and they go through the cycle at the same rate, then you don’t actually need 00:31:37.01 a cell size checkpoint to maintain the size distribution within a dividing population. 00:31:43.00 Robert Brooks pointed this out a number of years ago in 1981 where he pointed out if you just plot a model 00:31:52.00 take a cell that is 10 units in size, compared to a cell that is at 1 unit in size, 00:31:59.02 and suppose they are adding 5.5 units before they divide, 00:32:04.02 then the big cell at 10 will become 15.5 units and then divide to give you something a little over about 8 units 00:32:13.00 whereas the small cell at 1 unit adds 5.5, gets to 6 or 7, 00:32:17.01 and then divides into about 3 so you can see that the little cell is more than doubling its size 00:32:23.00 in a single cycle, whereas the large cell is not even doubling its size, and eventually with 00:32:29.03 more and more divisions, these cells will reach a common cell size over a number of days and a number of divisions 00:32:37.00 Even if there is no cell size checkpoint, the cells will hunt to a common cell volume. 00:32:45.00 Another reason for thinking that cells might have a cell size checkpoint in yeast is that 00:32:55.03 when you switch yeast from a rich nutrient environment to a less rich nutrient environment, 00:33:03.02 they very quickly change their growth rate and divide at a new cell size appropriate for the less good environment. 00:33:13.00 And if you do the opposite, growth them in a nutrient poor medium and then switch them to a rich medium, 00:33:19.02 they very quickly within one division start dividing at a new larger cell size. 00:33:24.00 So Ian did this experiment in Schwann cells. If cells are growing in no serum, 00:33:30.01 just with IGF-1 and with GGF, they will divide indefinitely in this culture system. But they divide at a relatively small size 00:33:39.00 because they are growing at a slower rate than when cells are dividing in such cultures in 3% serum. 00:33:46.00 In both cases they will continue to divide but the cells will be larger in the higher concentration of serum, 00:33:54.01 because they grow more in a single cycle than they do when they are not in serum. 00:33:58.00 So now he switches them from no serum conditions to 3% serum, 00:34:03.02 and unlike yeast cells which would switch to the new cell size immediately within a division, 00:34:09.02 these cells gradually over 4, 5, 6 days, and many cell cycles, 00:34:16.00 gradually come to the new cell size appropriate for the 3% fetal calf serum. So if they do have a cell size 00:34:23.15 checkpoint, it doesn't operate in the way that the yeast cell size checkpoint is thought to operate. 00:34:32.00 So we would argue that it is unlikely that they have cell size checkpoints. So then the question becomes: 00:34:37.02 why are yeast cells behaving differently in this respect in terms of cell size growth? 00:34:43.24 So growth control compared to the Schwann cells. Well one reason is technical 00:34:50.20 that the yeast experiments are done where the cells are growing in optimal nutrient 00:34:57.14 and yeast cells will divide and grow as fast as they can, they care only about nutrients they don't care about 00:35:02.27 other cells, and if you are in optimal nutrients, then the thing limiting your growth rate is inside the cell, 00:35:10.01 we don't know what it is, but it could be ribosomes, it could be genes you don't know. 00:35:13.00 In the Schwann cell situation we know it is not anything inside the cell because as you add higher and higher 00:35:20.14 concentrations of serum, which contains growth signals, growth factors, then the cells grow at a faster and faster rate. 00:35:29.00 So the control here is extracellular rather than intracellular, 00:35:32.02 and perhaps that is the fundamental different here. Of course yeast cells 00:35:38.02 are unicellular organisms and they grow and divide as fast as they can, they don't care about other cells, 00:35:44.02 but animal cells don't work that way. It would be a disaster if they worked that way. 00:35:48.01 In fact, they only grow and they only divide when other cells signal them to do so for the good of the organism as a whole, 00:35:56.01 so it isn't perhaps surprising that they behave so differently in this way. 00:36:01.00 Now what does it mean for a cell to actually be growing and increasing its protein content over time. 00:36:10.00 What it means is that it's making more protein than it's degrading and secreting. 00:36:16.00 Otherwise, it wouldn't be growing. So one possibility is for Schwann cells growing independent of size, 00:36:25.02 the big cells grow at the same rate as little cells, is that they make protein at the same rate 00:36:30.01 independent of their size. Well it turns out that's not right. 00:36:33.01 So Ian looked using a 2 hour pulse of 35S-methionine to look at protein synthesis rate 00:36:42.00 and when you look at cells that have been in aphidicolin for 1 day, 00:36:45.01 which are small compared to cells that have been in aphidicolin growing for 2 days or even 3 days 00:36:50.25 the amount of protein made in this two hour pulse is very much greater the bigger the cell. 00:36:57.00 So the cells are making protein at a greater rate if they are larger than do smaller cells. 00:37:05.00 But if big cells and little Schwann cells are growing at the same rate, they are adding the same amount of protein per day 00:37:14.00 it must be that they are degrading protein at a faster rate too, when they are larger. 00:37:20.00 And indeed that is true, so Ian pulses them with the 35S-methionine and chases it for a number of hours, 00:37:27.01 6.5 hours here, and if you look at the small cells that have been in aphidicolin for 2 days, 00:37:33.03 they are degrading the protein the loss is slower than in the large cells. 00:37:40.11 So the large cells are making protein faster, and they are degrading protein faster. 00:37:45.00 So how do cells control their rate of protein synthesis and their rate of protein degradation so that big cells 00:37:54.00 and little cells grow at the same rate. It is a remarkable thing and 00:37:56.02 there must be communication between the synthetic apparatus and the degradation apparatus. 00:38:03.00 So we know very little about this, but here's a bit that is known and 00:38:08.01 this is an experiment that was done a number of years ago by Franklin and Johnson. 00:38:12.03 They looked at sympathetic neurons and I should say these are the only cells I'm aware of in a mammal, 00:38:19.02 where we know something about what determines their size. 00:38:23.00 Sympathetic neurons depend on signals that they get from the target neurons 00:38:28.01 that they innervate and that signal is nerve growth factor, NGF. 00:38:33.00 In an adult rodent, if you give sympathetic neurons more NGF they become bigger, everything becomes bigger, 00:38:40.02 the axon, the cell body, the dendrites. If you give them less NGF by injecting antibodies against NGF 00:38:46.01 to neutralize it, the cells get smaller. So the cell is simply reading out how much NGF 00:38:51.02 it gets from its target cells to determine its size. Now the experiment that 00:38:57.01 Johnson and Franklin did was they treated sympathetic neurons in culture with a 00:39:02.03 protein synthetic inhibitor, cycloheximide. When they did that in the presence of NGF, 00:39:10.01 the cells maintain their normal size for up to a week or ten days. So that means you inhibit protein synthesis, 00:39:19.00 the cell can detect that and immediately shuts off degradation and therefore can maintain its normal size. 00:39:25.03 But now if you do the same experiment in the absence of NGF, 00:39:30.01 now when you inhibit protein synthesis, degradation carries right on and the cell shrinks down to hardly being 00:39:37.17 able to be seen again. Now you remove the cycloheximide or you add back the NGF and this cell will regain its normal size. 00:39:45.12 So this communication between protein synthetic machinery and protein degradation machinery, 00:39:51.00 this coupling in some way depends on extracellular signals, in this case NGF. 00:39:58.00 And finally, I just want to say that there has been great progress now in the intracellular signaling pathways 00:40:04.00 that stimulate cell growth and a key player here is this kinase mTOR, target of rapamycin. 00:40:13.00 So this kinase is activated in yeast only by nutrients, but in animal cells 00:40:20.02 its activated both by nutrients and by extracellular growth factors. 00:40:27.00 And it stimulates protein synthesis and it inhibits protein degradation. In that way, it stimulates cell growth 00:40:35.19 so here is one intracellular protein kinase that helps to coordinate protein synthesis and degradation, 00:40:45.11 and it turns up protein synthesis and turns down protein degradation to promote cell growth.
