1 00:00:07,860 --> 00:00:13,590 Okay. Good morning, everyone. It's very good to see so many of you here. 2 00:00:14,730 --> 00:00:18,880 This is the second sort of theoretical physics morning that we've we've run. 3 00:00:18,900 --> 00:00:24,720 I noticed a couple of people who were present at the first one, so they obviously weren't completely put off by it, which is great. 4 00:00:27,090 --> 00:00:34,050 So so this, this, this is something slightly different. I mean, when I was a graduate student in theoretical physics, which was a while ago, 5 00:00:35,490 --> 00:00:39,210 you know, it was particles, it was things going on in semiconductors. 6 00:00:39,660 --> 00:00:47,070 Hall was still doing plasmas. And and then there was sort of hard, complicated astrophysics problems. 7 00:00:47,640 --> 00:00:52,020 And what we're going to be talking about today is something which is new from that point of view. 8 00:00:52,020 --> 00:00:58,740 And and the whole topic of biological physics is really emerged over about the last 20 years. 9 00:00:59,970 --> 00:01:05,970 And it's now become something which is, you know, mainstream business for big physics departments. 10 00:01:06,300 --> 00:01:11,520 So if you go to most big physics departments, you'll find that they have some kind of a biological physics. 11 00:01:11,640 --> 00:01:14,940 But it's still relatively small because it's it's growing. 12 00:01:15,000 --> 00:01:19,920 You know, there are many fewer people here doing biological physics than there are particle physics, for example. 13 00:01:20,730 --> 00:01:25,410 But but as time goes on, you know, the relative proportions will change. 14 00:01:25,890 --> 00:01:34,020 And it's an extremely light, like any neat, completely new area for theoretical physicists is sort of very exciting because, 15 00:01:34,020 --> 00:01:38,820 you know, there are lots of easy things to do. There are lots of things nobody's ever thought about before. 16 00:01:39,090 --> 00:01:45,209 There are lots of things which are actually amenable to the represent and so attacked by the methods of theoretical physics. 17 00:01:45,210 --> 00:01:51,750 But, you know, nobody's ever tried before. So so you're you're in completely and completely new territory. 18 00:01:52,050 --> 00:01:55,200 So I think this is a you know, I think this is a fascinating topic. 19 00:01:55,200 --> 00:02:02,700 I think it's it's a topic which will become increasingly important in the you know, in in this in the century. 20 00:02:03,600 --> 00:02:09,750 And I think we're probably only only just at the beginning of the applications of biological physics. 21 00:02:09,990 --> 00:02:15,780 You know, to real world medical problems, for example. So I'm very glad to see see so many of you here today. 22 00:02:16,440 --> 00:02:22,440 And so now I and welcome once again and I'll pass over to Roman, who's going to give the first talk. 23 00:02:24,410 --> 00:02:39,100 Okay. So good morning, everyone. My story and I'm going to tell the whole thing as a story so you won't see much technicalities in my talk. 24 00:02:39,110 --> 00:02:48,340 It will be basically trying to to to paint a picture about the kind of thing that well, 25 00:02:48,350 --> 00:02:55,820 the three speakers today and many physicists these days are beginning to to be interested in seriously. 26 00:02:57,020 --> 00:03:06,350 So the story starts from Erwin Schrödinger, who towards the end of his career became interested in biology, in fact. 27 00:03:09,410 --> 00:03:20,530 It was. Basically he gave a series of talks when he was in Dublin, I think it probably was after he moved on, after his very brief tenure at Oxford. 28 00:03:21,790 --> 00:03:25,030 And then he wrote this book based on those lectures. 29 00:03:25,750 --> 00:03:31,270 And on the first page of the book, he basically poses this very simple, fundamental question, 30 00:03:31,270 --> 00:03:38,729 which is how can we describe the events in space and time to take place within the boundary of a living organism? 31 00:03:38,730 --> 00:03:42,850 And that seems a very simple question, but in fact, it's very fundamental. 32 00:03:42,850 --> 00:03:51,700 And, you know, you can say, well, this is not really a helpful question because we can ask the same thing about, say, a. 33 00:03:53,890 --> 00:03:57,340 Sort of a chamber which has an ideal guest in it. 34 00:03:57,340 --> 00:04:04,899 Can we really track or chase individual atoms and molecules and is it really useful to do that kind of thing? 35 00:04:04,900 --> 00:04:10,240 And we know that we have developed physics so that we can stop worrying about those details. 36 00:04:10,240 --> 00:04:18,690 We can average over them and produce macroscopic quantitative information that we can test, we can probe and measure. 37 00:04:21,690 --> 00:04:25,610 Just a brief note about the history because it was mentioned also. 38 00:04:25,620 --> 00:04:33,120 So the book was written in 1944 and in fact, it was inspired by the work of another theoretical physicist, 39 00:04:33,330 --> 00:04:39,780 Max Delbruck, who was advised by Niels Bohr to start looking into biology. 40 00:04:39,780 --> 00:04:49,830 And he did. He worked on bacteria and the genetic mutations in bacteria, and basically he was very influential. 41 00:04:51,690 --> 00:05:03,059 Having Schrödinger inspired by his work conjectured in this book that genetic information, basically DNA is something like an episodic crystal. 42 00:05:03,060 --> 00:05:11,160 It has some sequence on it which carries the code of genetic information or the code of life, if you want. 43 00:05:11,580 --> 00:05:18,870 And it was this book was published about a decade before the work of Crick and Watson. 44 00:05:19,170 --> 00:05:28,709 So again, Francis Crick, who was a condensed matter physicist of the Cavendish, who basically put together the double helix structure of DNA. 45 00:05:28,710 --> 00:05:34,860 So although this history of molecular biology only stands a chance in this building and in this audience, 46 00:05:35,760 --> 00:05:38,249 I think it's based on a few factual statements. 47 00:05:38,250 --> 00:05:50,610 And it's still worth remembering that physicists have had a very important role in what's so perhaps a more approachable way of rewarding. 48 00:05:50,610 --> 00:05:54,570 This question is as follows Imagine you can. 49 00:05:56,140 --> 00:06:04,060 You know, get over the chemistry beat and synthesise all the molecules that, you know, they should be in a living cell. 50 00:06:04,360 --> 00:06:09,760 And then you put them together in the sack and make the sack of chemicals that is equivalent. 51 00:06:09,790 --> 00:06:17,260 I mean, this is a hypothetical experiment is equivalent to what you expect a living cell to be made of. 52 00:06:18,460 --> 00:06:23,890 Now, if you do that, then the question is, how can we go from this sack of chemicals, 53 00:06:23,890 --> 00:06:31,930 which is basically just a collection of molecules to something which is a functioning living cell that does all the things that are living cell does. 54 00:06:31,930 --> 00:06:34,450 And that's I mean, when you look at it this way, 55 00:06:34,450 --> 00:06:40,779 I think it's clear that this is a question for condensed matter physicists to look into because it involves the interactions 56 00:06:40,780 --> 00:06:47,080 of all these molecules together and then forming these organised structures that eventually will lead to function. 57 00:06:49,150 --> 00:06:58,270 And we will talk more about that. But but I think it's clear that there is a very interesting story here for physicists to look into. 58 00:06:59,770 --> 00:07:04,569 And we as we will sort of move forward in this story, 59 00:07:04,570 --> 00:07:14,380 you will see even more how we can start to do sort of more practical things and not just a very hypothetical. 60 00:07:15,820 --> 00:07:19,540 Imaginary sort of question. Okay. 61 00:07:20,380 --> 00:07:27,120 So if there is a I mean, we are talking about a very fundamental thing here. 62 00:07:27,130 --> 00:07:33,400 So like in physics, where we go back to our fundamental governing equations, you know, 63 00:07:33,400 --> 00:07:37,930 shredding a question for quantum mechanics of Newton's equation for classical mechanics, 64 00:07:38,710 --> 00:07:45,570 perhaps we should start from the most fundamental governing rule in biology, which is evolution, to try and answer these questions. 65 00:07:45,570 --> 00:07:57,130 So, you know, can we basically start because evolution tells us the sort of dynamical rule, if we have something we can, 66 00:07:57,580 --> 00:08:03,340 you know, take it one step further and see how it evolves with time in terms of complication. 67 00:08:04,360 --> 00:08:10,570 Now, the problem with that approach is that you there's an arrow of time associated with evolution. 68 00:08:10,930 --> 00:08:20,140 You cannot really run evolution backwards and say, okay, I will sort of go backwards in time until I reach the simplest possible form of life, 69 00:08:21,250 --> 00:08:24,250 which is probably, you know, just made of one or two molecules. 70 00:08:24,250 --> 00:08:27,430 And then I will work my way back over that. 71 00:08:27,440 --> 00:08:38,280 There is this notion that evolution only propagates in the in the positive direction, and that's from the theory aspect, if you want. 72 00:08:38,460 --> 00:08:43,750 So so this is thinking about evolution in a theoretical sense. 73 00:08:46,190 --> 00:08:48,710 In terms of the evidence that actually exists. 74 00:08:50,990 --> 00:09:00,200 The story is even more interesting because if you look at this map, you know, you can call this the cosmology of evolution. 75 00:09:02,450 --> 00:09:13,609 Life apparently started somewhere around 3.8 billion years ago from a simple form of life, which is called the last universal common ancestor. 76 00:09:13,610 --> 00:09:19,729 And then all forms of life have evolved from that through evolution and led into things, 77 00:09:19,730 --> 00:09:24,320 you know, like simple bacteria all the way to very complicated mammals. 78 00:09:26,540 --> 00:09:37,819 But the problem with, you know, trying to incorporate this way of thinking in terms of evolution with that's cosmological math is 79 00:09:37,820 --> 00:09:44,390 that the first living cell is pretty much the same as any other living cell that you would find. 80 00:09:45,890 --> 00:09:49,490 And that's the problem, because that means you cannot go backwards. 81 00:09:49,820 --> 00:09:53,299 This is basically emphasising what I just mentioned in the previous slide. 82 00:09:53,300 --> 00:10:00,050 You cannot simplify things by running evolution backwards and say, okay, now I'm getting to two very, 83 00:10:00,050 --> 00:10:03,560 very, very simple forms of life which is made of one or two types of molecules. 84 00:10:04,070 --> 00:10:14,140 In other words, we are forced by the evidence to think of life as an emergent collective behaviour which can only exist once, you know, 85 00:10:14,150 --> 00:10:23,030 a large number of things put together their efforts and basically come up with this emergent behaviour which is, 86 00:10:23,750 --> 00:10:30,320 you know, pretty much is going to be the same as any other form of life that you can find. 87 00:10:30,860 --> 00:10:34,370 And this, incidentally, is something physicists might be able to help with, 88 00:10:34,370 --> 00:10:40,060 because physicists have a lot of experience with basically this kind of emergent behaviour. 89 00:10:40,070 --> 00:10:47,299 They have thought about phase transitions and macroscopic behaviours of materials and 90 00:10:47,300 --> 00:10:55,730 found things that you could not really trace back into individual molecular details to. 91 00:10:56,740 --> 00:11:00,680 Emphasise my point a little bit further. I will go back to the history of magnetism. 92 00:11:00,700 --> 00:11:09,850 Just a very brief slide on the transition from power magnetism to Ferro magnetism should be familiar to most of you. 93 00:11:10,420 --> 00:11:17,469 Basically, we say if we have a piece of magnets, a macroscopic piece of material, 94 00:11:17,470 --> 00:11:27,140 you can find these small microscopic spins as the individual elements in a very simplified theoretical picture of the 95 00:11:27,140 --> 00:11:34,900 individual elements that make the material in the most simple form of this model that is called the ising model. 96 00:11:34,900 --> 00:11:39,130 You can think of this spin as only having two degrees of freedom spin off or spin down. 97 00:11:40,300 --> 00:11:46,540 If the spins don't talk to each other at all, the system will behave in the paramagnetic sense, 98 00:11:46,540 --> 00:11:53,470 in the sense that if you apply an external magnetic field, they will align normally without a magnetic field, there will be thermal fluctuations, 99 00:11:53,800 --> 00:12:02,140 which means on average you would have equal number of spin offs as I spin downs and on average you will have no net magnetisation 100 00:12:02,500 --> 00:12:10,390 if you apply an external magnetic field to this thermally fluctuating macroscopic collection of microscopic spins, 101 00:12:11,230 --> 00:12:18,820 you will impose a bias. Things will become slightly biased towards spin up, let's say compared to spin down. 102 00:12:18,830 --> 00:12:21,309 On average you will start seeing a magnetisation. 103 00:12:21,310 --> 00:12:29,800 So the point I was talking about before was this point that the origin zero magnetisation zero external magnetic field, and now I'm running it. 104 00:12:30,140 --> 00:12:37,930 I'm running along this blue line here, producing an magnetisation, which is linear in the external magnetic field that I'm imposing. 105 00:12:39,010 --> 00:12:44,950 Ultimately, if the magnetic field is strong enough, I will align all of the spins and that means this will saturate somehow. 106 00:12:44,950 --> 00:12:55,659 So I cannot go linear forever. This is what we know as power magnetism now is the spin start to talk to each other and this is something local. 107 00:12:55,660 --> 00:13:01,420 This is an interaction between two neighbouring spins that maybe they will gain an energy of minus j. 108 00:13:01,420 --> 00:13:06,639 If they align parallel to each other, then there is this possibility. 109 00:13:06,640 --> 00:13:09,100 If J is stronger than a certain critical value, 110 00:13:09,100 --> 00:13:17,409 that when you start from the Magnetised state in which you apply an external magnetic field and you reduce the magnetic field to zero, 111 00:13:17,410 --> 00:13:22,389 there will be a residual so-called spontaneous magnetisation in the system. 112 00:13:22,390 --> 00:13:30,549 So that's a decision made by all of these spins collectively to pick up an orientation and magnetise all in that direction, 113 00:13:30,550 --> 00:13:35,740 despite the fact that there is no external magnetic field guiding that or imposing that, 114 00:13:36,640 --> 00:13:45,070 and that's known as spontaneous symmetry breaking because they could basically pick spin off or spin down one of these two orientations. 115 00:13:45,070 --> 00:13:58,709 So have. This is a very interesting phenomenon because basically it shows us how an emergent property in a macroscopic piece of material can come 116 00:13:58,710 --> 00:14:08,790 to life just because of the local interaction between them and without anything exposing externally imposing this behaviour on the system. 117 00:14:09,120 --> 00:14:16,920 Incidentally, this model was solved exactly by large Gonzaga on the same year that Schrodinger wrote that book. 118 00:14:18,450 --> 00:14:22,590 Now, this is a very, very simple system. 119 00:14:23,370 --> 00:14:26,909 I'll talk a little bit more about emergence on the next slide. 120 00:14:26,910 --> 00:14:35,640 But before going to that slide, I would like to draw your attention to this sort of critical curve in between the red one, 121 00:14:35,910 --> 00:14:42,780 which is which corresponds to when the coupling g is exactly equal to the critical value. 122 00:14:43,320 --> 00:14:48,360 You can see that that's to sum something in intermediate between the paramagnetic and the magnetic behaviour. 123 00:14:49,350 --> 00:14:56,339 It has a singular behaviour in the sense that when you apply the extent of magnetic field, you start seeing this very, 124 00:14:56,340 --> 00:15:04,170 very rapid or very sensitive response to the external magnetic field, almost divergence response, because the slope here is these 90 degrees. 125 00:15:04,500 --> 00:15:12,959 And so a little bit of magnetic field applied externally could excite a very sensitive and 126 00:15:12,960 --> 00:15:19,290 large response in the system and that's the kind of behaviour which is going to basically. 127 00:15:19,740 --> 00:15:24,930 So we will find other types of systems that behave like that. 128 00:15:24,930 --> 00:15:31,229 And that's a very interesting, it has some fundamental implications on, on the, 129 00:15:31,230 --> 00:15:35,550 on the behaviour of the system and that's something to to look into if you want to understand it. 130 00:15:36,430 --> 00:15:41,010 Okay. So imagine the way I described it. 131 00:15:41,610 --> 00:15:44,730 As I said, this was a very, very simple system. 132 00:15:45,270 --> 00:15:54,450 If you look at more complicated examples, you will see that in fact in in an emergent behaviour, 133 00:15:54,450 --> 00:16:02,090 it's not always the case that you can identify features in the behaviour that you see in the system, in the microscopic elements. 134 00:16:02,100 --> 00:16:06,590 For example, think about the phase transition between gas and liquid and solid. 135 00:16:06,600 --> 00:16:14,669 When you look at the solid made of the same molecule, it has a different kind of let's say a different kind of mechanical properties. 136 00:16:14,670 --> 00:16:20,730 It can stand shear stresses, whereas a liquid cannot. 137 00:16:22,170 --> 00:16:24,180 Yet both of them are made of the same molecule. 138 00:16:24,190 --> 00:16:32,060 So you cannot say that if I choose that particular molecule, the macroscopic imagine behaviour is going to be affected by it. 139 00:16:33,480 --> 00:16:44,250 Typically they will have these sharp onsets, very sensitive response and phase transition that will basically lead to macroscopic phases. 140 00:16:44,250 --> 00:16:53,100 So you will, you will go from one macroscopic behaviour to another macroscopic behaviour and also something which is quite common is that we 141 00:16:53,100 --> 00:17:00,719 cannot keep track of all the details in systems that want to study when we want to basically focus on the emergent properties. 142 00:17:00,720 --> 00:17:05,910 We need to find ways of minimising the degrees of freedom we put into this 143 00:17:05,910 --> 00:17:10,620 model and basically just keep the essence so that we can describe the system. 144 00:17:11,310 --> 00:17:14,580 But that doesn't mean that the details are not important. 145 00:17:14,580 --> 00:17:22,260 For example, when I built and ising model for a magnet, you know, I think I understand what the phase transition means. 146 00:17:23,160 --> 00:17:27,450 That doesn't mean that I can answer the question, for example, 147 00:17:27,450 --> 00:17:35,609 whether one type of atom can make a magnet a ferromagnetic or another type of, for example. 148 00:17:35,610 --> 00:17:40,589 But if you if you look into those details, eventually you can make a connection. 149 00:17:40,590 --> 00:17:48,719 For example, you can make a connection between those details and the value of that coupling constant j that I had in my previous case and say, 150 00:17:48,720 --> 00:17:57,000 okay, if I have this particular type of material, J will be strong enough to give me the ferromagnetic transition that I need. 151 00:17:57,870 --> 00:18:08,489 Or in more complicated examples, for example, superconductivity, you know, again, you will have some kind of macroscopic understanding of it, 152 00:18:08,490 --> 00:18:16,200 but that doesn't mean that, you know, that the details about what compounds the superconductivity, etc., is unimportant. 153 00:18:17,280 --> 00:18:19,829 So the question is, can we do something like that for biology? 154 00:18:19,830 --> 00:18:28,590 And I emphasise this point about details because that's the first place that physicists hit the wall when they try to approach questions in biology, 155 00:18:28,590 --> 00:18:36,329 you know, get overwhelmed with all these details and immediately we propose these really simplified models and the biologists say, you know, 156 00:18:36,330 --> 00:18:44,399 you are too naive because in biology details matter and you cannot build in the model which is like an ising model and describe life. 157 00:18:44,400 --> 00:18:50,960 You know, that's not going to happen and. So, you know, we need to educate ourselves in the details. 158 00:18:51,380 --> 00:18:56,150 But as I said, it's going to to to be something like the question of self connectivity. 159 00:18:56,150 --> 00:19:04,280 Ultimately, we need to be able to find a description which is generic enough that will overcome this barrier. 160 00:19:05,180 --> 00:19:11,870 Okay. Let's go through the the features of a living cell that we want to describe physically. 161 00:19:12,980 --> 00:19:17,540 And and let's actually not worry about the names because, you know, 162 00:19:17,570 --> 00:19:22,100 that's something which is always a barrier for physicists, you know, remembering these names. 163 00:19:23,780 --> 00:19:27,679 And it for our purposes, they don't really matter too much. 164 00:19:27,680 --> 00:19:37,430 So let's just see what a living cell is made of and what kind of properties we we should expect to be able to describe. 165 00:19:38,150 --> 00:19:40,490 So first of all, a cell needs to keep to shape. 166 00:19:40,490 --> 00:19:48,830 It needs to have a structure because it's made of soft material, it's made of polymers and, you know, things that that bend easily. 167 00:19:48,850 --> 00:19:57,230 And actually that's on purpose as well because living systems work basically based on units of cables. 168 00:19:57,440 --> 00:20:02,960 So that's the thermal energy and they need to be able to deform and take advantage of energies in that level. 169 00:20:04,010 --> 00:20:11,840 And that means they have to be soft if you make a living system out of iron or carbon sheets or graphene and so on, 170 00:20:13,730 --> 00:20:25,370 you know something which is or I meant to say a diamond, it's not going to be able to function because it cannot deform easily at all. 171 00:20:25,400 --> 00:20:37,010 It has available its units of cavity. So the way it does it is basically it forms these sort of set side the skeletal structures, 172 00:20:37,010 --> 00:20:47,150 these filaments that form bundles and then these bundles basically make a backbone which holds the the overall shape of the cell. 173 00:20:47,750 --> 00:20:51,559 There's also some element that's keeping the boundary in shape. 174 00:20:51,560 --> 00:20:54,770 If it's and in fact, this is not a static structure. 175 00:20:55,370 --> 00:21:00,109 There are little motors in place that can deform the cell if it's needed. 176 00:21:00,110 --> 00:21:15,889 For example, if it if there's need for global motility or deformation in response to some environmental signals, then there's energy requirements. 177 00:21:15,890 --> 00:21:22,129 And basically most cells live on universal currencies of energy. 178 00:21:22,130 --> 00:21:26,450 And that's a very interesting notion as well. So ATP molecule, for example, 179 00:21:27,620 --> 00:21:36,130 it's an energetic molecule which is made in these factories where sugar glucose is 180 00:21:36,200 --> 00:21:42,439 broken down and are complicated chemical reactions basically eventually leading 181 00:21:42,440 --> 00:21:47,809 to this molecule that has around 12 KB of energy and then the entire cytosol is 182 00:21:47,810 --> 00:21:55,740 filled with this energetic molecule and then any anywhere that's basically a, 183 00:21:57,290 --> 00:22:02,089 you know, a chemical reaction or something is going to take place, a mechanical activity that requires energy. 184 00:22:02,090 --> 00:22:11,150 They will have access to this universal currency of of energy, and they will break down this molecule, ATP, into two components and take the energy. 185 00:22:11,480 --> 00:22:15,170 And those two components will make their way back to the energy factory and will 186 00:22:15,170 --> 00:22:20,690 be put together back into the universal currency and again released for use. 187 00:22:20,810 --> 00:22:29,389 So somehow there's a notion of a cycle in the system because there's also economy in the in the form of material that it uses. 188 00:22:29,390 --> 00:22:36,260 It's true that it has basically a lot of input and output of material with outside, 189 00:22:36,260 --> 00:22:47,989 but it's not a very economical way of living if it wants to completely import its energy source and always just turns it into waste and and sort of 190 00:22:47,990 --> 00:23:02,450 dispose of that in instead what it does is basically it circulates this form of energy inside by basically importing simpler forms of of energy, 191 00:23:02,720 --> 00:23:08,690 let's say chemical energy or in the case of green lights and so on. 192 00:23:09,860 --> 00:23:16,229 Then there's. A lot of function that is going to happen inside the cell. 193 00:23:16,230 --> 00:23:19,950 And that function requires these agents. I will describe them later. 194 00:23:19,950 --> 00:23:24,240 They are proteins and these proteins are synthesised on order. 195 00:23:24,300 --> 00:23:28,980 So if a function is needed for some reason. 196 00:23:31,950 --> 00:23:39,450 A protein needs to be synthesised for that function and the code for that is stored in the nucleus of the cell here in the DNA. 197 00:23:41,040 --> 00:23:50,190 So that's just a a repository of or or sort of a storage place in which this code can be found. 198 00:23:51,750 --> 00:23:58,330 And then very close to that, because you need to have access to that, there are these chambers that are where the proteins are made. 199 00:23:58,350 --> 00:24:05,790 So the code is read and then turned into this disposable agent. 200 00:24:06,570 --> 00:24:12,030 All of that requires raw material and then it will produce waste because it's chemical reaction. 201 00:24:12,980 --> 00:24:19,470 And that means you need to have some kind of transport system, which is basically not left to diffusion. 202 00:24:19,820 --> 00:24:26,160 It's guided by those sort of cytoskeleton structures. 203 00:24:26,160 --> 00:24:29,880 So there is a track connecting the centre of the cell to the boundary. 204 00:24:30,120 --> 00:24:34,560 And then there are molecular motors that walk along it in a very controlled way, 205 00:24:34,860 --> 00:24:41,550 carrying these cargos that basically have the raw material on the way in and the waste material on the way out. 206 00:24:42,990 --> 00:24:46,920 The materials factory needs to be in the form of these convoluted chambers because you 207 00:24:46,920 --> 00:24:50,640 have a lot of reaction going on and you don't want them to interfere with each other. 208 00:24:51,030 --> 00:24:54,659 So you need to make these chambers the separate things. 209 00:24:54,660 --> 00:25:00,600 And also, if you have chambers in which chemical reactions take place, you can drive the system away from equilibrium. 210 00:25:00,600 --> 00:25:07,640 And that's something I will explain a bit later more easily, because you can just remove and incorporate these politicians. 211 00:25:07,650 --> 00:25:11,140 And that's the classic when we teach that. 212 00:25:11,160 --> 00:25:16,770 I mean, it's the classic thing that we do is we talk about free expansion of gas and so on, 213 00:25:16,780 --> 00:25:25,650 and that's the type of idea which is used in the design of these chambers, because they they basically evolve with time in a very dynamic way. 214 00:25:26,790 --> 00:25:31,350 So this is the picture of a living cell that we will need to take away. 215 00:25:32,250 --> 00:25:37,050 And the idea is to try and basically understand all of this using physics. 216 00:25:38,370 --> 00:25:44,550 So just to summarise what we saw, we saw a hierarchical structure both in space and time, 217 00:25:44,580 --> 00:25:53,460 time in the form of these cycles and in space in the form of these self-assembled structures, the sort of membrane chambers that I showed. 218 00:25:55,260 --> 00:26:01,670 Etc. The whole thing is very precise, despite being, you know, fluctuating all the time. 219 00:26:01,680 --> 00:26:10,860 This is room temperature, a lot of stochastic beauty, and yet there is precision down to the molecular detail of the sequence of the DNA, 220 00:26:10,860 --> 00:26:18,030 which is rather than transformed into the sequence of the amino acid, which is turned into a protein which will go and function somehow. 221 00:26:20,160 --> 00:26:25,680 If there is a mistake, it will be corrected. So there are even error correction mechanisms. 222 00:26:25,680 --> 00:26:30,870 There's a high flux of material both in and out and also energy. 223 00:26:30,870 --> 00:26:37,409 So this is a very non-equilibrium system, highly non-equilibrium. 224 00:26:37,410 --> 00:26:45,930 And we will basically talk about that in more detail. And as I said, there's this element of economy because the cell needs to be able to use its. 225 00:26:48,140 --> 00:26:51,890 You know what it has available economically. 226 00:26:52,140 --> 00:27:03,140 So many of the building blocks will have multi multiple functions and these multiple functions will basically happen in different times. 227 00:27:03,140 --> 00:27:07,250 So for example, the building block will be when the cell is dividing. 228 00:27:07,730 --> 00:27:13,700 Everything is dedicated to the cell division, which is a very important stage for the cell. 229 00:27:13,700 --> 00:27:19,070 And then when it's not dividing, the same building blocks are used in a in a different function. 230 00:27:19,900 --> 00:27:27,380 And I also it's interesting, the cartoon that I actually showed doesn't reflect this, but cell is in fact, 231 00:27:28,400 --> 00:27:36,860 not a sort of bubble in which one or two things are moving around in a in a random and very dispersed fashion. 232 00:27:36,860 --> 00:27:41,329 It's a very crowded environment, and yet it's very agile. 233 00:27:41,330 --> 00:27:45,680 And these two are not you know, it's not trivial that they can go together. 234 00:27:45,680 --> 00:27:50,989 And we will talk about that. But again, the idea is to understand these physically. 235 00:27:50,990 --> 00:27:55,310 So just to give you one example about the last point that I mentioned, 236 00:27:56,420 --> 00:28:05,030 let's look at how DNA is stored inside a living cell and just putting a few numbers to to have an idea about the situation. 237 00:28:05,030 --> 00:28:14,220 So. Human DNA is of about a metre in length and the radius of of DNA is about ten nanometres. 238 00:28:14,270 --> 00:28:23,709 If you just multiply a metre and two factors of a nanometre to calculate the actual volume of DNA that you have in every single cell, 239 00:28:23,710 --> 00:28:32,770 you get ten to the -18 cubic metres. And if you turn that into a sphere that volume, you get a micron for the radius. 240 00:28:32,770 --> 00:28:39,309 And that in fact, is the radius of the nucleus of the cell, which is enclosing that DNA. 241 00:28:39,310 --> 00:28:47,950 And that means basically DNA still pretty much at its close packed density inside the nucleus of the cell. 242 00:28:48,430 --> 00:28:52,140 And that's quite surprising, because if you think about it, this is a storage device. 243 00:28:52,150 --> 00:28:55,650 So how do we make storage devices? 244 00:28:55,660 --> 00:29:01,510 We make typically two dimensional matrices, and then we use the third dimension to go and have access to that point. 245 00:29:02,020 --> 00:29:08,349 Yet the cell has basically this close packed, three dimensional spherical structure, 246 00:29:08,350 --> 00:29:12,759 and it has to have access to every single point of it as and when it needs. 247 00:29:12,760 --> 00:29:16,090 And that's a very, very difficult process. 248 00:29:16,690 --> 00:29:22,719 But yet it can achieve that. And the way it does it is by using, again, hierarchical structure and dynamics. 249 00:29:22,720 --> 00:29:32,110 So this is not going to be a dead, you know, completely jammed, although it has the consistency of a chewing gum. 250 00:29:32,110 --> 00:29:39,790 If you if you push it and press it, it's not completely dead on and on accessible. 251 00:29:39,790 --> 00:29:43,179 It's actually quite easy because it's dynamically accessed. 252 00:29:43,180 --> 00:29:50,710 So, you know, there's a lot of clever. Mechanisms that are ongoing. 253 00:29:51,550 --> 00:29:57,850 Okay. Now, what do we know, you know, from physics that we can apply to these systems. 254 00:29:57,880 --> 00:30:02,500 Basically, the thing we know best is equilibrium, statistical physics. 255 00:30:02,500 --> 00:30:06,219 When we want to describe the behaviour of a few things that interact with each 256 00:30:06,220 --> 00:30:12,370 other at room temperature and form these collective structures and equilibrium, 257 00:30:12,370 --> 00:30:20,620 statistical physics tells us that if we know the interaction potential between these molecules that interact with each other, 258 00:30:20,620 --> 00:30:24,040 we can basically predict their collective phase behaviour. 259 00:30:24,070 --> 00:30:31,390 For example, if you think about the Linear Jones interaction potential that has basically three parts, 260 00:30:32,320 --> 00:30:38,790 that's a typical interaction potential between, say, two molecules when they are very far from each other. 261 00:30:38,800 --> 00:30:43,750 It's it's very, very small when they get close to each other. 262 00:30:43,750 --> 00:30:46,870 There is an attractive element to Indiana Jones potential that comes from Panda, 263 00:30:46,870 --> 00:30:54,429 both interaction, which is the fluctuating dipoles in the molecules and atoms. 264 00:30:54,430 --> 00:31:01,419 And then when they get too close to each other, there is an excluded volume part and that's because of Fermi exclusion. 265 00:31:01,420 --> 00:31:06,310 So the electrons cannot really penetrate each other and that keeps them apart. 266 00:31:07,330 --> 00:31:21,220 So if on average the distance between two molecules in a system is in this range, we will end up having a gas dilute form of, of our, of our matter. 267 00:31:21,910 --> 00:31:27,970 If on average the distance between them is around that minimum energy attractive, well, 268 00:31:28,000 --> 00:31:34,180 we will get a liquid which is a very dense form of matter, but but very agile, very dynamic. 269 00:31:34,960 --> 00:31:40,480 And then if they get too close to each other so that they will feel the excluded volume part, they will form a solid if they can. 270 00:31:40,480 --> 00:31:49,480 If they have enough regularity, if they don't have enough regularity, they will end up forming a glass in a very jammed structure, 271 00:31:49,480 --> 00:31:56,920 which is which is, you know, behaves like a solid, but it's not completely ordered in terms of the lattice structure. 272 00:31:58,380 --> 00:32:05,220 We do have face separation and sensitive response of the type I just described in the ising model. 273 00:32:06,300 --> 00:32:12,660 But there are problems. And the problem is basically it's very simple when you have a phase transition in equilibrium. 274 00:32:13,020 --> 00:32:20,790 So this physics of the phase that you get is macroscopic, which means that, you know, if you have a, say, liquid gas coexistence, 275 00:32:20,790 --> 00:32:29,909 you get a macroscopic phase of liquid coexisting with the macroscopic phase of gas you can never have in equilibrium a system with microstructures, 276 00:32:29,910 --> 00:32:35,700 with the length scale, which is of the order of, let's say, a hundred nanometre micron, 277 00:32:35,700 --> 00:32:40,590 and basically remains in that scale dynamically and maybe in a few places. 278 00:32:41,040 --> 00:32:44,729 Same goes with temporal structure. If the phase transition is triggered, 279 00:32:44,730 --> 00:32:53,520 it goes all the way and you get the macroscopic phase in the new phase when say you change a parameter and you cannot get a system which oscillates, 280 00:32:53,520 --> 00:33:02,220 let's say, between two things or has a temporal structure in the form of, you know, changing between different states, let's say, as time goes on. 281 00:33:04,880 --> 00:33:12,080 The sensitivity you can have is controlled by macroscopic size of the system. 282 00:33:12,080 --> 00:33:15,560 So if you basically if you have a system which is small, 283 00:33:16,310 --> 00:33:24,610 then the response you can get from it is not as sensitive as, let's say, a macroscopic system with with larger size. 284 00:33:24,850 --> 00:33:29,809 So that degree of sensitivity is controlled by size and in living systems. 285 00:33:29,810 --> 00:33:35,270 This is not the case. Also, I mentioned the last point about dense structure. 286 00:33:35,280 --> 00:33:39,859 So basically if we put together everything we know about equilibrium, statistical physics, 287 00:33:39,860 --> 00:33:48,700 we expect the interior of a cell to be a completely jammed completely that structure. 288 00:33:48,710 --> 00:33:52,160 So in conclusion, equilibrium is is dead. 289 00:33:52,160 --> 00:33:55,940 And if we want to have something which is, you know, not dead, 290 00:33:55,940 --> 00:34:07,550 we need to bring in something else which is basically going to drive the system away from equilibrium, something you can call magic in quotation. 291 00:34:10,700 --> 00:34:16,819 Or another way of putting it is living matter is is active in the sense that it 292 00:34:16,820 --> 00:34:23,930 has a mechanism to go away from equilibrium in a continuous way all the time. 293 00:34:23,930 --> 00:34:34,190 The system basically is driven away from equilibrium and in a controlled way, and it does that via these agents that are in fact proteins. 294 00:34:36,080 --> 00:34:39,890 So these are the things that basically are synthesised in the system. 295 00:34:40,340 --> 00:34:48,620 And remember, the code that tells the cell how to synthesise these is is kept in the nucleus of the cell. 296 00:34:49,520 --> 00:34:53,810 They can have different kinds of function and drive the system away from equilibrium in different directions. 297 00:34:54,170 --> 00:34:59,050 It could be mechanical by exerting forces. There are proteins that act as motors. 298 00:34:59,060 --> 00:35:05,360 And I mentioned the sort of transport mechanism and also the cytoskeleton changing the shape of the cell. 299 00:35:06,950 --> 00:35:18,019 And that's a part of the activity. But the biggest the majority of agents in the cell are these enzymes, the ones that catalyse chemical reactions. 300 00:35:18,020 --> 00:35:20,960 And the main business of a living cell is basically. 301 00:35:23,710 --> 00:35:31,330 You know, these catalytic chemical reactions happening as and when needed, the consequences will be, 302 00:35:31,600 --> 00:35:37,060 you know, producing and maintaining gradients that will keep the system away from equilibrium. 303 00:35:37,390 --> 00:35:44,260 Let's say if you go to a mitochondrion, that's where ATP molecule is made. 304 00:35:44,260 --> 00:35:52,810 You will have proton gradients that are maintained and generated actively by using energy from the source of energy that you have from outside. 305 00:35:53,590 --> 00:36:00,370 And there are other mechanisms that will clearly create a non-equilibrium situation. 306 00:36:01,210 --> 00:36:06,880 I mentioned again this sort of close actions, nature of the cell. 307 00:36:07,510 --> 00:36:16,420 Again, that is going to be kept dynamic by mechanical activity, by by these mechanical agents. 308 00:36:16,990 --> 00:36:22,270 There will be instabilities and patterns and dynamical order. And and basically these are the things that will. 309 00:36:23,780 --> 00:36:29,090 Make sure that the cell can respond in a sensitive way when there is a small molecular signal. 310 00:36:29,810 --> 00:36:36,860 It cannot rely on sensitivity of the type that I describe in a second order, in a phase transition for the magnetic system. 311 00:36:37,850 --> 00:36:43,219 And all of these things are basically the subject of of the relatively new field of active self matter, 312 00:36:43,220 --> 00:36:49,790 which is you will hear a lot more about it in Julius Talk right after mine. 313 00:36:51,830 --> 00:36:57,230 Okay. Let's have a look at one example. The case of mechanical activity. 314 00:36:57,240 --> 00:37:01,820 So the most important mechanical activity of any cell is division. 315 00:37:02,870 --> 00:37:07,990 And in many cells, it's done through a structure that's called mitotic spindle. 316 00:37:08,000 --> 00:37:14,990 You will have these cytoskeleton filaments formed from proteins called tubulin. 317 00:37:16,820 --> 00:37:18,559 But again, no names. So. 318 00:37:18,560 --> 00:37:29,900 So these filaments are formed and somehow they are attached to the DNA and why they are pushing apart this sort of interior of the cell. 319 00:37:29,900 --> 00:37:35,270 They are also pulling apart the two copies of DNA at the same time. 320 00:37:35,270 --> 00:37:37,040 And these copies are complementary. 321 00:37:37,040 --> 00:37:49,610 So that means each of them can acquire a complementary second strand, which will create basically two independent DNA copies of the original one. 322 00:37:50,090 --> 00:38:01,579 And all of this happens when the cell divides into two and eventually reaches a point at which it can draw the curtain and say, okay, you know, 323 00:38:01,580 --> 00:38:12,140 this is one cell and it's completely separate from the other one and they can go away, not basically worrying about association with each other. 324 00:38:13,370 --> 00:38:13,819 Now, 325 00:38:13,820 --> 00:38:22,970 it's interesting that when you take that materials to the microtubules and the molecular motors and you wait for clever enough to do the experiments, 326 00:38:23,300 --> 00:38:28,280 this was done recently in the group of Van Dijk in Brandeis, 327 00:38:28,670 --> 00:38:35,780 and you can say that's putting together the same elements that you you purify and basically 328 00:38:35,780 --> 00:38:45,889 make in the lab will create that dead jammed those pack structure that I depicted for you. 329 00:38:45,890 --> 00:38:51,410 If you don't provide fuel, that's ATP concentration written up there. 330 00:38:51,410 --> 00:38:55,250 That's at zero ATP concentration. 331 00:38:55,250 --> 00:38:59,450 As you increase the concentration of the the fuel molecule, 332 00:38:59,460 --> 00:39:05,390 you can see that this the structure starts to become dynamic and at relatively high concentration. 333 00:39:05,390 --> 00:39:07,520 So minimal concentrations of ATP, 334 00:39:07,820 --> 00:39:16,940 you can see that the same structure is completely dynamic and you can even begin to see similarities to to mitotic spindle. 335 00:39:16,950 --> 00:39:23,179 So in a sense that's a collection of proteins that will self-organize given 336 00:39:23,180 --> 00:39:27,950 the right condition into something which can do a mechanical task like that. 337 00:39:28,550 --> 00:39:32,930 It is made of something which is intrinsically unstable. 338 00:39:32,930 --> 00:39:40,579 And that's a very interesting point because if you want to have something which, you know, carries on relatively easily, 339 00:39:40,580 --> 00:39:50,840 which is the business of of of living systems, it's very clever to run them on unstable processes that you you basically control somehow. 340 00:39:50,840 --> 00:39:53,120 So so this is something which is unstable. 341 00:39:53,120 --> 00:40:01,429 If you have a macroscopic system with these proteins, it will it will give you a turbulent and completely out of control structure. 342 00:40:01,430 --> 00:40:10,249 If you keep a small enough subset of it, you can have a cycle in which you can control things. 343 00:40:10,250 --> 00:40:17,389 And that's exactly or seems to be exactly what is happening inside of a cell that is dividing. 344 00:40:17,390 --> 00:40:25,040 So in other words, there seems to be a notion that things will be kept dynamic yet in control through the instability, 345 00:40:25,400 --> 00:40:33,629 and also that will somehow select the length scale that's a fundamental ruler for the system because it knows what lengths, 346 00:40:33,630 --> 00:40:42,530 again, to choose such that you will have the right balance or combination between instability and, you know, 347 00:40:42,530 --> 00:40:48,950 and dynamic nature and the control that you want so that you can be sure where you end up with the process. 348 00:40:52,380 --> 00:40:55,240 Chemical reactions are similar. 349 00:40:55,260 --> 00:41:05,030 So you have these agents, so called enzymes, they basically catalyse chemical reactions where needed and this is how they work. 350 00:41:05,040 --> 00:41:12,180 So basically you should think about a typical reaction in the cell being like going from this state, 351 00:41:12,900 --> 00:41:20,700 which is a higher energy state to the lower energy state. So it's something which is ultimately designed to to happen, 352 00:41:20,700 --> 00:41:27,900 but over a very long period of time because of this barrier which is basically put in between. 353 00:41:28,860 --> 00:41:33,570 So it's something which is ready to to act, but it's waiting for the order if you want. 354 00:41:34,830 --> 00:41:40,680 And what the enzyme does is when it comes along to the right location, it will lower that barrier. 355 00:41:40,710 --> 00:41:50,780 So it's a mechanism, again, to have something which is it has the drive but is being kept away from what it wants to do unless the right time. 356 00:41:50,800 --> 00:41:58,800 Basically the door is open and the system can make the transition going from one state, high energy state to the lower energy state. 357 00:42:00,810 --> 00:42:11,100 Ultimately, this will be put back in in place in another place in the cell when the system is prepared for the next round as as we talked about it. 358 00:42:12,340 --> 00:42:14,670 And that's very interesting because you can control this. 359 00:42:15,180 --> 00:42:24,740 So remember the code that is used to synthesise an enzyme that will basically appear late where it's needed and do this task is stored in the DNA. 360 00:42:24,750 --> 00:42:29,370 So that's a mechanism to program what is needed and what is not. 361 00:42:30,570 --> 00:42:36,090 And things can change depending on basically the requirement of the signals it get from the environment, etc. 362 00:42:36,720 --> 00:42:41,340 And another interesting aspect of this process is that it leads to a nonlinear process, 363 00:42:41,340 --> 00:42:53,790 because when you need the the enzyme at that location for that particular chemical reaction, it means that in the sort of rate equation type level, 364 00:42:54,480 --> 00:43:00,030 the rate at which this reaction will happen is proportional to the density of the enzyme and density of the 365 00:43:00,030 --> 00:43:04,930 chemical or the probability of finding the enzyme at that location times the intensity of the chemical. 366 00:43:04,950 --> 00:43:14,130 And that means you have a nonlinear process in in your system and nonlinear reactions. 367 00:43:16,920 --> 00:43:28,190 Especially when they are. Complemented with the reverse reaction, which is the concept of economy that I mentioned earlier, can lead to cycles. 368 00:43:29,600 --> 00:43:35,839 This is a very genetic phenomenon that when you have a cyclic and non-linear reaction, 369 00:43:35,840 --> 00:43:41,060 they can they can create oscillations and self-sustained oscillations. 370 00:43:41,900 --> 00:43:45,950 And in fact, cycles are ubiquitous in living systems. 371 00:43:45,950 --> 00:43:49,430 For example, the Krebs cycle, which is quite complicated. 372 00:43:49,760 --> 00:43:55,740 It has either of 17 elements involved and other cycles of. 373 00:43:56,900 --> 00:44:01,980 It's it provides a mechanism to select an intrinsic frequency. 374 00:44:02,000 --> 00:44:09,350 It's like a clock, because basically there is a natural selection of the function of the parameters in the system. 375 00:44:10,010 --> 00:44:16,100 When coupled with diffusion, it can provide also spatial information. 376 00:44:16,820 --> 00:44:26,040 It's known that reaction diffusion can create patterns like Turing patterns, and that will also give you a mechanism, for example, to find, you know, 377 00:44:26,120 --> 00:44:30,180 the right place for the middle of the cell to divide and, you know, 378 00:44:30,200 --> 00:44:37,760 things that are quite they need to be done quite accurately, that there are these natural nonlinear mechanisms for them to. 379 00:44:39,200 --> 00:44:42,529 To to perform those activities. 380 00:44:42,530 --> 00:44:45,649 And it's interesting that nonlinearity also brings in robustness, 381 00:44:45,650 --> 00:44:53,420 because there is this concept of of a limit cycle in this sort of field of dynamical systems. 382 00:44:53,420 --> 00:44:59,650 And that's, you know, if you have a dissipative process which has a, you know, 383 00:44:59,660 --> 00:45:06,230 has an equilibrium end point, if you start from a number of initial points, 384 00:45:06,440 --> 00:45:14,630 initial conditions, let's say in the configuration space, you will all always end up in that fixed point, which is where the equilibrium is. 385 00:45:15,140 --> 00:45:22,490 In an oscillating system like that, you could have a a closed loop which undergoes oscillation for the system, 386 00:45:22,490 --> 00:45:29,310 which is basically the end point of any starting. Initial point for the process. 387 00:45:29,470 --> 00:45:35,670 So somehow you have this ability to create stability depending on the initial conditions of the system. 388 00:45:36,660 --> 00:45:43,830 Okay. So just to sum up, it seems that from the point of view of condensed matter physics, 389 00:45:43,830 --> 00:45:48,420 you can say that living matter is an emergent collective phase of active self matter. 390 00:45:48,450 --> 00:45:55,080 It's controlled basically based on the information which is available to the 391 00:45:55,380 --> 00:46:00,660 to the cell to perform these chemical and mechanical activities via proteins, 392 00:46:00,660 --> 00:46:08,160 these agents that it synthesises. And it seems to be able to keep things in a robust way in this non-equilibrium condition. 393 00:46:09,450 --> 00:46:13,830 So does that mean that we know everything about a living cell and we can go away and just do it? 394 00:46:14,820 --> 00:46:23,340 The answer is no, because in fact, things are not obviously as easy as I described here. 395 00:46:23,360 --> 00:46:29,809 There is a problem. And that problem, it has to do with the hierarchical structure of of living systems. 396 00:46:29,810 --> 00:46:41,970 So what I described so far is that you have this information, which is almost like a sort of fixed set of rules that is embedded in the DNA. 397 00:46:42,330 --> 00:46:48,570 And then we just go to the information and get instructions and come back and perform this activity, let's say. 398 00:46:48,630 --> 00:46:57,610 But it's not quite as simple as that, because all of these things have influence on each other and in particular information itself 399 00:46:57,960 --> 00:47:02,730 can get influence from the environment and from the mechanical and chemical activities, 400 00:47:02,730 --> 00:47:06,480 which it basically is regulating. And it could change. 401 00:47:06,480 --> 00:47:11,610 And this is not something we have experience with in physics because, for example, 402 00:47:11,880 --> 00:47:16,980 when we when we make this course grained description of, let's say, a piece of magnets, 403 00:47:17,850 --> 00:47:26,969 ultimately this is only useful when we know that the microscopic detail, which is going into some tiny element at the molecular level, 404 00:47:26,970 --> 00:47:32,850 is going to be unimportant at the level of the sort of effective emergent theory that I'm describing. 405 00:47:33,180 --> 00:47:39,450 That will just give me some kind of you know, it will affect one of the parameters that I use. 406 00:47:40,230 --> 00:47:45,030 But in living systems, it's not like that because it's tiny molecular detail. 407 00:47:45,870 --> 00:47:51,089 Say something which happens to a protein can actually change the entire genetic 408 00:47:51,090 --> 00:47:54,690 code that is stored in the cell and is passed on to the next generation. 409 00:47:55,560 --> 00:47:57,870 So there is a dynamic process and if you want, 410 00:47:57,870 --> 00:48:04,920 this is equivalent to saying your imagined level description could change because of the molecular detail. 411 00:48:05,130 --> 00:48:12,420 And if you cross grain over everything and get rid of all those molecular details, then there is no way you can keep track of this kind of change. 412 00:48:12,960 --> 00:48:21,810 So this is quite a challenging problem for for us physicists and I think it will keep us busy for quite a while. 413 00:48:23,080 --> 00:48:26,940 And I think it's a good place for me to stop. And thanks for your attention.