WEBVTT 00:01.410 --> 00:06.640 Prof: Welcome Orgo survivors, and others. 00:06.640 --> 00:10.420 I stuck this slide up, sort of outside the framework 00:10.415 --> 00:13.755 of the regular lecture, and I did so just to indicate 00:13.757 --> 00:16.247 that if you go through the scientific literature, 00:16.250 --> 00:19.300 you can probably find a neat case of coevolution, 00:19.300 --> 00:21.610 with some kind of beautiful biology in it, 00:21.610 --> 00:23.670 coming out every week. 00:23.670 --> 00:26.180 This one came out last week. 00:26.180 --> 00:30.410 This is a Proboscis fly that lives in South Africa, 00:30.410 --> 00:32.780 and it pollinates flowers. 00:32.780 --> 00:36.150 And you can see that it has evolved a very long proboscis, 00:36.150 --> 00:38.910 and the flower has evolved a very long nectary, 00:38.910 --> 00:41.010 and it looks, in fact, very much like 00:41.011 --> 00:44.531 Darwin's orchid, and that moth called Praedicta, 00:44.528 --> 00:48.488 that Darwin predicted would have a long proboscis. 00:48.490 --> 00:49.630 But this is a fly. 00:49.630 --> 00:52.210 This is not at all closely related to moths, 00:52.214 --> 00:55.764 and that flower is not at all closely related to orchids. 00:55.760 --> 00:57.600 So this is convergent evolution. 00:57.600 --> 01:00.160 And I think you'll remember, in reading the book, 01:00.158 --> 01:02.908 that there was a neat alternative hypothesis posed in 01:02.912 --> 01:07.472 the book saying, "Hey, it wasn't about the 01:07.471 --> 01:12.211 coevolution of the flower and the moth. 01:12.209 --> 01:16.839 There's a spider that sits on the orchid, and when the moth 01:16.843 --> 01:20.443 flies in, the spider tries to eat the moth; 01:20.438 --> 01:23.548 and so the moth kind of evolved a long proboscis so that it 01:23.546 --> 01:26.916 wouldn't touch that flower with anything but a ten-foot pole. 01:26.920 --> 01:28.130 Okay? 01:28.129 --> 01:30.489 So that was an alternative hypothesis, and there's actually 01:30.492 --> 01:32.532 some evidence for that in the case of the orchid on 01:32.528 --> 01:33.138 Madagascar. 01:33.140 --> 01:37.660 But in the case of this interaction, 01:37.660 --> 01:40.120 which is in Cape Province in South Africa, 01:40.120 --> 01:44.820 with a fly and something that is not at all an orchid, 01:44.819 --> 01:47.979 the data indicate that, in fact, a coevolutionary story 01:47.977 --> 01:50.307 works just fine; and that looks to be what's 01:50.307 --> 01:50.777 going on. 01:50.780 --> 01:55.180 The longer the nectary, the more likely the 01:55.182 --> 01:58.362 pollination; the longer the proboscis, 01:58.364 --> 02:02.204 the greater the energetic reward--and the two things feed 02:02.204 --> 02:04.404 back and forth to each other. 02:04.400 --> 02:09.380 So this indicates actually that Darwin's original idea was 02:09.378 --> 02:11.038 probably correct. 02:11.038 --> 02:13.248 And I would note that in the case of the orchid on 02:13.247 --> 02:15.637 Madagascar, the fact that there's a spider 02:15.637 --> 02:19.027 doesn't really mean that Darwin was wrong in generating his 02:19.033 --> 02:21.033 story, it just means that there is 02:21.026 --> 02:22.586 also something else going on. 02:22.590 --> 02:31.870 02:31.870 --> 02:33.130 Okay, so. 02:33.129 --> 02:42.249 02:42.250 --> 02:44.990 We spent the first part of the course talking about 02:44.988 --> 02:45.918 microevolution. 02:45.919 --> 02:48.659 We spent the second part of the course talking about 02:48.657 --> 02:49.567 macroevolution. 02:49.568 --> 02:52.798 And today and Monday, we're going to talk about 02:52.797 --> 02:56.867 coevolution and evolutionary medicine as two areas in which 02:56.866 --> 03:00.086 micro and macroevolution interact in generating 03:00.094 --> 03:02.134 explanations of things. 03:02.128 --> 03:06.278 And I think that you'll probably see, 03:06.280 --> 03:09.000 if you think about it, that in almost any reasonably 03:09.002 --> 03:11.622 complicated or large-scale biological pattern, 03:11.620 --> 03:15.560 both things have been involved; both micro and macroevolution. 03:15.560 --> 03:18.500 There's been some things that have been changing slowly and 03:18.503 --> 03:20.843 some things that have been changing quickly. 03:20.840 --> 03:28.570 Now the tight genetic definition of coevolution is 03:28.574 --> 03:29.684 this. 03:29.680 --> 03:33.060 In one species you have a change in a gene, 03:33.055 --> 03:36.185 and that--excuse me for missing this; 03:36.190 --> 03:37.900 I was doing proofreading this morning; 03:37.900 --> 03:41.300 there should be 't' there--it stimulates an evolutionary 03:41.303 --> 03:43.843 change in a gene in the other species, 03:43.840 --> 03:46.340 and that change in the other species stimulates another 03:46.340 --> 03:49.600 change in the first species; so that you have kind of a gene 03:49.595 --> 03:51.335 for gene succession in time. 03:51.340 --> 03:53.460 One thing happens here; that stimulates something here; 03:53.460 --> 03:55.460 that stimulates something here. 03:55.460 --> 03:59.450 That is the tight genetic definition of coevolution. 03:59.449 --> 04:02.769 If you could demonstrate that, I think everybody would agree, 04:02.774 --> 04:04.994 hey, you nailed it, it's really there. 04:04.990 --> 04:07.690 It's hard to do. 04:07.688 --> 04:10.878 The reason it's hard to do is that we don't normally know what 04:10.879 --> 04:12.449 the genes are that involved. 04:12.449 --> 04:15.029 We can see the phenotype, but we have difficulty 04:15.031 --> 04:16.241 inferring the genes. 04:16.240 --> 04:20.370 There are some cases of this that are well documented in 04:20.370 --> 04:23.150 rusts, rust fungi inhabiting wheat; 04:23.149 --> 04:25.699 Ustilago hordii is one of them. 04:25.699 --> 04:29.579 So, you know, pathogens of crop plants are 04:29.581 --> 04:35.171 things where this kind of coevolution is well documented. 04:35.170 --> 04:37.940 Another kind of coevolution is phylogenetic. 04:37.940 --> 04:41.950 So you use tree thinking to try to infer what's been going on. 04:41.949 --> 04:43.879 And you look at closely interacting organisms-- 04:43.879 --> 04:45.599 pathogens, parasites, pollinators, 04:45.603 --> 04:48.823 things like that-- and you see if the trees can be 04:48.815 --> 04:51.115 laid right on top of each other. 04:51.120 --> 04:55.400 Or, if you have one group over here-- 04:55.399 --> 04:57.059 so you have, say, the pathogens over here 04:57.057 --> 04:58.547 and you have the hosts over here-- 04:58.550 --> 05:02.050 you see if the trees line up and touch each other at the 05:02.053 --> 05:02.503 tips. 05:02.500 --> 05:04.820 That would indicate--without any crosses, 05:04.819 --> 05:08.389 so you don't see any lines kind of crossing over when you line 05:08.394 --> 05:11.024 them up-- that would mean that the trees 05:11.019 --> 05:14.889 have exactly the same topology, and that every time the host 05:14.894 --> 05:18.564 speciated, the pathogen speciated. 05:18.560 --> 05:21.860 And if you see crossing lines, it means that a pathogen has 05:21.857 --> 05:23.787 jumped from one host to another. 05:23.790 --> 05:27.250 So that kind of approach gives you another definition of 05:27.245 --> 05:30.695 coevolution, and another tool for trying to infer it. 05:30.699 --> 05:34.229 05:34.230 --> 05:36.260 Now before I get into coevolution proper, 05:36.259 --> 05:38.389 I want to talk a little bit about co-adaptation, 05:38.389 --> 05:42.409 because co-adaptation actually contains within it a message 05:42.406 --> 05:45.796 that's of general significance for coevolution. 05:45.800 --> 05:49.630 Right at the beginning of life, the first replicators had to 05:49.632 --> 05:52.942 co-adapt in order to generate say a well-functioning 05:52.944 --> 05:56.684 hypercycle; they had to co-adapt to each 05:56.680 --> 05:57.370 other. 05:57.370 --> 06:01.070 And at the level of the cell, when you're looking at key 06:01.071 --> 06:04.371 molecules in the cell, all these interactions have 06:04.367 --> 06:06.317 co-adapted to each other. 06:06.319 --> 06:11.269 So, for example, the ribosome here is in green, 06:11.269 --> 06:14.439 and you've got the mRNA coming into it like a ribbon, 06:14.439 --> 06:17.489 and you've got--the transfer RNA is pulling in the amino 06:17.490 --> 06:21.060 acids out at their tips, into the reaction center of the 06:21.060 --> 06:21.730 ribosome. 06:21.730 --> 06:25.210 And that brings the amino acids into close juxtaposition where 06:25.213 --> 06:27.843 an enzyme can operate on them to join them, 06:27.839 --> 06:31.269 and then clip them off of the incoming tRNAs, 06:31.269 --> 06:33.909 which then go on out, back into the cell to do their 06:33.906 --> 06:36.916 job again, and the protein grows out here. 06:36.920 --> 06:40.240 Well, this is a rough sketch of the structure of the ribosome. 06:40.240 --> 06:43.640 It's actually more complicated than that, and it has really a 06:43.637 --> 06:46.977 beautifully sculpted reaction center in the middle of it. 06:46.980 --> 06:52.020 And the message from this is that every single important 06:52.023 --> 06:56.613 biochemical step and morphological structure inside 06:56.608 --> 07:02.448 the cell is tightly co-adapted, so that form matches function, 07:02.451 --> 07:04.231 throughout the cell. 07:04.230 --> 07:08.950 And the reason that's the case is that these things are 07:08.951 --> 07:14.551 processing reactions that happen thousands of times a second, 07:14.550 --> 07:18.360 and that therefore accumulate to have big effects over the 07:18.355 --> 07:20.155 lifetime of the organism. 07:20.160 --> 07:24.770 If you've got something in you that is going to happen say 50 07:24.774 --> 07:29.014 billion times in your lifetime, and you get a very, 07:29.014 --> 07:32.784 very tiny, 1/1000^(th) of 1% change in it, 07:32.779 --> 07:34.979 that then accumulates 50 billion times, 07:34.980 --> 07:38.330 you have a massive result at the end of your life. 07:38.329 --> 07:42.219 So that things that are happening down at that level are 07:42.220 --> 07:45.050 driven by high frequency interactions. 07:45.050 --> 07:48.280 And the frequency with which things interact is one of the 07:48.279 --> 07:50.659 key elements of coevolution, in general. 07:50.660 --> 07:54.170 07:54.170 --> 07:57.680 If you look at a slightly higher level in the cell, 07:57.680 --> 08:00.770 you can find co-adaptation going on again. 08:00.769 --> 08:05.239 The axons that run into nerve fibers have different lengths, 08:05.240 --> 08:09.470 so that the signal coming from the brain will arrive at things 08:09.470 --> 08:12.730 that need to be coordinated at the same time. 08:12.730 --> 08:17.600 The muscles in electric eels have been turned into storage 08:17.598 --> 08:20.388 batteries, and the axons that run from the 08:20.389 --> 08:22.559 brain have had their lengths modified, 08:22.560 --> 08:25.350 so that they hit the different cells in the storage battery at 08:25.351 --> 08:28.371 exactly the same instance, so that the electrical charge 08:28.369 --> 08:30.959 goes out, all at the same time. 08:30.959 --> 08:34.829 A four- or five-foot electric eel can kill a horse; 08:34.830 --> 08:36.560 that's how much electricity they can store up. 08:36.558 --> 08:39.858 But they can only do it because it's released exactly at the 08:39.859 --> 08:40.529 same time. 08:40.529 --> 08:42.859 If it dribbled out, it wouldn't take the horse 08:42.856 --> 08:45.406 down; or the naturalist exploring the 08:45.413 --> 08:47.683 shallow river in South America. 08:47.679 --> 08:50.239 Right? 08:50.240 --> 08:52.010 Same kind of thing in your brain. 08:52.009 --> 08:55.639 There's very tight co-adaptation between your 08:55.644 --> 09:00.854 retina and its projections into the visual cortex at the back of 09:00.850 --> 09:02.090 your brain. 09:02.090 --> 09:08.110 So these connections have been sculpted by evolution so that 09:08.111 --> 09:13.321 the re-creation of the external world, in your head, 09:13.317 --> 09:14.847 is precise. 09:14.850 --> 09:18.830 And this has gone on in every organ of your body in one way or 09:18.827 --> 09:19.477 another. 09:19.480 --> 09:23.000 So the integration of the organism is achieved by 09:22.995 --> 09:25.115 co-adaptation of its parts. 09:25.120 --> 09:28.830 That's not precisely the gene for gene kind of interaction 09:28.825 --> 09:31.375 between species, that people think about in 09:31.379 --> 09:33.779 coevolution, but it is a gene for gene 09:33.782 --> 09:37.642 interaction in the determination of those organ systems. 09:37.639 --> 09:40.619 A gene changes over here, and another gene has to change 09:40.624 --> 09:41.334 over there. 09:41.330 --> 09:45.280 It's just that the process is going on inside a single genome, 09:45.275 --> 09:47.795 rather than in two different genomes. 09:47.798 --> 09:52.048 So that's not normally what biologists mean by coevolution. 09:52.048 --> 09:57.488 It usually refers to the mutual adjustment of the genomes of 09:57.488 --> 09:59.238 separate species. 09:59.240 --> 10:00.800 And that's kind of arbitrary I think, 10:00.798 --> 10:04.878 and the reason I think it's arbitrary is that we now 10:04.879 --> 10:09.679 conceive of the organism as kind of a babushka doll of nested 10:09.678 --> 10:14.558 levels of hierarchies that have been assembled over the course 10:14.558 --> 10:19.438 of the evolution of life, and that things that we now see 10:19.437 --> 10:24.277 as being integrated organisms, earlier, were independently 10:24.283 --> 10:27.763 evolving systems, and at that point the 10:27.763 --> 10:31.773 coevolution, that we now see as co-adaptation, 10:31.769 --> 10:37.629 was actually coevolution sensu strictu. 10:37.629 --> 10:43.049 So I'm now going to talk about some intercellular symbioses. 10:43.048 --> 10:46.838 And the reason I picked intercellular symbioses as the 10:46.837 --> 10:50.627 first example of real coevolution is that these things 10:50.625 --> 10:54.195 are very intimate coevolutionary interactions. 10:54.200 --> 10:57.340 And you can see that in mitochondria and chloroplasts of 10:57.336 --> 10:57.846 course. 10:57.850 --> 11:01.120 Then there's this wonderful and interesting critter called 11:01.118 --> 11:04.098 Wolbachia, that does lots of things to arthropods. 11:04.100 --> 11:07.000 The whole issue of the symbiosis of algae in reef 11:07.004 --> 11:10.094 building corals contains a lot of beautiful biology, 11:10.091 --> 11:12.091 and some interesting puzzles. 11:12.090 --> 11:16.550 And in all of these cases the interacting parts are really 11:16.552 --> 11:18.122 closely connected. 11:18.120 --> 11:18.530 Okay? 11:18.528 --> 11:22.528 So there's been a lot of evolution at the level of 11:22.532 --> 11:24.822 intercellular metabolism. 11:24.820 --> 11:29.130 And I think that these tight symbioses are really major 11:29.128 --> 11:32.558 transitions in the process of being born. 11:32.558 --> 11:35.768 So one of the issues in a major transition is whether or not you 11:35.768 --> 11:38.568 have a change in the pattern of genetic transmission. 11:38.570 --> 11:42.620 And in these cases independent genomes are getting aligned, 11:42.620 --> 11:46.890 and in the extreme case of mitochondria or chloroplasts, 11:46.889 --> 11:51.289 they actually have the same pattern of transmission as the 11:51.294 --> 11:54.894 maternal nuclear genomes, of the host. 11:54.889 --> 11:56.199 Okay? 11:56.200 --> 11:59.360 So previously independent things are being integrated. 11:59.360 --> 12:02.460 Conflicts are being at least partially resolved; 12:02.460 --> 12:05.590 although there are traces of these conflicts--as I told you 12:05.589 --> 12:07.909 earlier, there are mitochondrial cancers; 12:07.908 --> 12:11.148 mitochondria do occasionally get out of control. 12:11.149 --> 12:15.179 And there are things like the petite mutation in yeast, 12:15.183 --> 12:17.653 which is a mitochondrial issue. 12:17.649 --> 12:21.409 And then this new more or less well integrated unit has a 12:21.408 --> 12:22.348 performance. 12:22.350 --> 12:25.180 That performance can vary among units, and therefore natural 12:25.177 --> 12:27.427 selection is starting to act on the new unit. 12:27.428 --> 12:30.328 So at the formation of the eukaryotes, 12:30.330 --> 12:33.930 when the mitochondria came in, you had a new unit, 12:33.928 --> 12:37.178 and then it was going to perform with respect to other 12:37.181 --> 12:39.351 such units, depending on how well the 12:39.350 --> 12:41.920 mitochondria were adapted to the nuclear genome; 12:41.918 --> 12:45.958 and that's a coevolutionary process. 12:45.960 --> 12:51.610 Okay, so with mitochondria you've got all kinds of 12:51.607 --> 12:56.447 communication and coordination going on. 12:56.450 --> 13:03.230 The cell membrane of the previously independent purple 13:03.230 --> 13:09.050 sulfur bacterium, out here, now has within it an 13:09.053 --> 13:15.693 inner membrane that has got all kinds of biochemical machinery 13:15.691 --> 13:17.651 on its surface. 13:17.649 --> 13:19.839 And this is where the citric acid cycle takes place, 13:19.840 --> 13:23.550 where electrons go down the electron transport chain, 13:23.548 --> 13:27.348 making ATP, and in the process letting a few protons leak out 13:27.346 --> 13:31.066 into the cytoplasm, which cause oxidative damage. 13:31.070 --> 13:33.790 So if you are worried about eating your blueberries and 13:33.793 --> 13:38.153 drinking your pomegranate juice, it is because mitochondria leak 13:38.149 --> 13:42.579 protons and basically create hydrogen peroxide in your 13:42.580 --> 13:45.580 cytoplasm, and hydrogen peroxide is highly 13:45.578 --> 13:47.998 oxidative and can do damage in the cell; 13:48.000 --> 13:51.770 and there's lots of kinds of repair machinery to deal with 13:51.767 --> 13:52.227 that. 13:52.230 --> 13:57.420 This process here of exporting energy to the cell and getting 13:57.417 --> 14:02.597 information and substrate into the mitochondrion is a tightly 14:02.604 --> 14:06.444 coordinated one, and there have been lots of 14:06.438 --> 14:10.178 modifications to the mitochondrial membrane to make 14:10.179 --> 14:14.369 it an appropriate filter for the transport of goods, 14:14.370 --> 14:15.640 in and out. 14:15.639 --> 14:19.059 So it's been heavily modified by coevolution. 14:19.059 --> 14:21.029 Now, Wolbachia. 14:21.028 --> 14:23.798 Wolbachia are very cool bacteria. 14:23.799 --> 14:25.819 They're cytoplasmic parasites. 14:25.820 --> 14:29.710 They live in the cytoplasm of arthropods. 14:29.710 --> 14:33.110 So they occur in insects and crustacea. 14:33.110 --> 14:35.680 They sometimes occur in nematodes. 14:35.678 --> 14:41.768 They seem to be able to get into things, generally speaking, 14:41.774 --> 14:47.044 in that large chunk of the tree, which is called the 14:47.043 --> 14:48.493 ecdysozoa. 14:48.490 --> 14:53.000 And if you just think about the interests of the Wolbachia, 14:53.000 --> 14:58.170 it can only get into the next generation if it is in a female, 14:58.168 --> 15:00.668 because it is transmitted, like other cytoplasmic 15:00.669 --> 15:03.709 organelles, only through eggs and not 15:03.711 --> 15:05.101 through sperm. 15:05.100 --> 15:09.420 Now this creates some issues for Wolbachia, 15:09.423 --> 15:14.473 because if they end up in a male, they're dead. 15:14.470 --> 15:18.000 So they have evolved some interesting ways out of that. 15:18.000 --> 15:20.460 They can induce parthenogenesis, 15:20.461 --> 15:21.891 in some species. 15:21.889 --> 15:25.499 So they will take that female and they will make her asexual, 15:25.495 --> 15:27.895 and then she makes only female babies. 15:27.899 --> 15:31.649 So they get into the eggs of all of them. 15:31.649 --> 15:35.139 They can feminize male hosts, in pill bugs-- 15:35.139 --> 15:38.609 so Armadillidium, the little pill bug that you 15:38.606 --> 15:42.706 can find turning over logs-- it's an isopod and a 15:42.711 --> 15:47.821 crustacean--and when Wolbachia gets into Armadillidium, 15:47.820 --> 15:50.970 basically it takes males, and it has developed a method 15:50.966 --> 15:53.996 of interfering with its sex determination process and 15:53.999 --> 15:56.779 development, so that anything that's got a 15:56.779 --> 15:59.559 Wolbachia in it will grow up to be a female. 15:59.558 --> 16:02.328 Now, as Wolbachia--and by the way, this creates a huge 16:02.326 --> 16:05.346 reproductive advantage for those females, and they start to 16:05.354 --> 16:07.134 spread through the population. 16:07.129 --> 16:09.059 They're not suffering the twofold cost of sex. 16:09.058 --> 16:11.578 They're only making female children. 16:11.580 --> 16:14.250 They spread, and they take over the 16:14.249 --> 16:15.269 population. 16:15.269 --> 16:19.739 And then, because there aren't any males in the population, 16:19.736 --> 16:23.586 and it's still a sexual species, Armadillidium goes 16:23.589 --> 16:27.359 locally extinct; being driven to extinction by 16:27.360 --> 16:30.900 the selfish cytoplasmic parasite that it has. 16:30.899 --> 16:34.359 And the response of some, but not all, 16:34.361 --> 16:38.481 Armadillidium populations has been clever. 16:38.480 --> 16:42.130 They have cut out the sex determining part of the 16:42.131 --> 16:46.771 bacterial chromosome and put it into their nucleus and spliced 16:46.774 --> 16:49.974 it onto one of their own chromosomes, 16:49.970 --> 16:53.930 so that there is now vertical transmission of that selfish, 16:53.929 --> 16:55.419 sex-determining element. 16:55.418 --> 16:57.558 They don't really care very much about the rest of the 16:57.558 --> 16:59.818 bacterial genome that's been causing all this problem. 16:59.820 --> 17:02.290 The only thing that's really critical is that they got the 17:02.293 --> 17:06.953 sex determining part out, and they spliced it into their 17:06.950 --> 17:10.280 nuclear genome, through a process that we don't 17:10.276 --> 17:11.116 really understand. 17:11.118 --> 17:14.548 All we can see is that we can observe, in some populations, 17:14.546 --> 17:16.256 that today that's the case. 17:16.259 --> 17:20.139 This means that the conflict has been removed, 17:20.140 --> 17:22.470 at least for that sex-determining element, 17:22.470 --> 17:24.940 because now it's being vertically transmitted through 17:24.941 --> 17:29.411 both the male and female line, because it's in a nucleus. 17:29.410 --> 17:33.890 So the conflict disappears, and a 50:50 sex ratio is 17:33.886 --> 17:36.586 re-established; well after awhile, 17:36.592 --> 17:39.422 because now there's a new sex chromosome. 17:39.420 --> 17:39.690 Okay? 17:39.685 --> 17:42.555 So now you have three sex chromosomes, rather than two, 17:42.558 --> 17:45.698 for awhile, and so there's a bit of chaos in sex ratios. 17:45.700 --> 17:48.410 And then that stabilizes; you get back to 50:50 sex 17:48.413 --> 17:48.933 ratios. 17:48.930 --> 17:52.480 And then it gets infected by Wolbachia, and the whole thing 17:52.483 --> 17:53.713 starts over again. 17:53.710 --> 17:56.630 And in some cases you can take the genome of a Armadillidium 17:56.625 --> 17:58.415 pill bug, and sequence it, 17:58.423 --> 18:01.663 and you can find four or five fossilized, 18:01.660 --> 18:05.870 sex determining chunks of DNA, that have been stuck into it. 18:05.868 --> 18:09.088 So there's an interesting coevolutionary process going on 18:09.088 --> 18:09.548 there. 18:09.548 --> 18:13.648 In fruit flies and drosophila, they cause reproductive 18:13.650 --> 18:18.370 isolation, and they do that by cytoplasmic incompatibility. 18:18.368 --> 18:23.518 That means that a fruit fly is only going to be able to have 18:23.516 --> 18:27.116 offspring, if it's mating with a Wolbachia 18:27.117 --> 18:31.927 infested fruit fly, if it's got the same Wolbachia 18:31.934 --> 18:32.674 in it. 18:32.670 --> 18:36.660 So Wolbachia are biochemical geniuses and developmental 18:36.656 --> 18:37.466 geniuses. 18:37.470 --> 18:39.930 They have learned how to manipulate the sex ratios and 18:39.932 --> 18:42.632 mating success of their hosts, and they really haven't been 18:42.628 --> 18:43.418 domesticated. 18:43.420 --> 18:47.540 And this is kind of interesting if you go back to the whole 18:47.538 --> 18:51.658 issue of well what happened when mitochondria first started 18:51.657 --> 18:54.497 getting into the eukaryotic lineage? 18:54.500 --> 18:58.220 Was there a period 15 hundred million years when this kind of 18:58.218 --> 18:59.518 stuff was going on? 18:59.519 --> 19:00.859 Probably was. 19:00.858 --> 19:05.748 It probably took some time to resolve conflicts and really to 19:05.747 --> 19:10.387 integrate the mitochondria into the eukaryotic lineage. 19:10.390 --> 19:13.840 So when we think about that overall process of interacting 19:13.837 --> 19:17.107 genomes, as I mentioned the frequency of interaction is 19:17.105 --> 19:18.735 really quite important. 19:18.740 --> 19:22.770 You're not going to get tight co-adaptation of two different 19:22.768 --> 19:27.068 species unless they interact with each other very frequently. 19:27.068 --> 19:30.318 If they're only interacting with each other occasionally, 19:30.318 --> 19:32.718 then there's a lot of stuff going on, 19:32.720 --> 19:36.360 outside of the interaction, that has costs and benefits, 19:36.358 --> 19:40.198 that is going to be tweaking the interaction traits in other 19:40.202 --> 19:41.052 directions. 19:41.048 --> 19:45.398 So it's got to be a very consistent and persistent 19:45.402 --> 19:49.312 process, to result in tight co-adaptation. 19:49.309 --> 19:50.869 So frequency is important. 19:50.868 --> 19:54.368 And then, of course, when they interact it must make 19:54.374 --> 19:57.264 some difference to reproductive success. 19:57.259 --> 20:00.219 Then there's the issue of relative evolutionary potential: 20:00.215 --> 20:02.235 who's got the bigger population size; 20:02.240 --> 20:04.240 who has the shorter generation time; 20:04.240 --> 20:06.210 who has more genetic variation? 20:06.210 --> 20:08.590 Those things are certainly going to help determine the 20:08.589 --> 20:09.039 outcome. 20:09.038 --> 20:11.388 And then there's this issue of the Red Queen, 20:11.391 --> 20:12.621 which I will come to. 20:12.619 --> 20:16.239 20:16.240 --> 20:19.460 So there are some kinds of interactions, 20:19.461 --> 20:23.841 ecological interactions, that favor strong coevolution 20:23.838 --> 20:25.738 and specialization. 20:25.740 --> 20:29.100 Parasite host interactions, especially where the--this is 20:29.098 --> 20:32.638 normally a case where the whole live cycle is completed on a 20:32.640 --> 20:34.710 single host; plant/herbivore and 20:34.711 --> 20:39.271 predator/prey interactions, where you have got a fairly 20:39.268 --> 20:45.938 narrow range of species that are being eaten by the herbivore or 20:45.938 --> 20:47.948 by the predator. 20:47.950 --> 20:52.270 And there's one here--pandas just eat bamboo, 20:52.269 --> 20:55.219 and therefore that sixth appendage, 20:55.220 --> 20:58.320 the panda's thumb, which is there for handling the 20:58.317 --> 21:00.907 bamboo shoot, has evolved. 21:00.910 --> 21:05.840 Sage grouse basically just eat sage--they're herbivores--and 21:05.839 --> 21:10.519 sage has an awful lot of upsetting biochemistry in it. 21:10.519 --> 21:14.469 If you were to go out into the American West and try to live 21:14.473 --> 21:17.023 for a week on sage, in the Great Basin, 21:17.021 --> 21:19.101 you would become very sick. 21:19.099 --> 21:20.869 Sage grouse do it just fine. 21:20.868 --> 21:24.968 They've got all kinds of--it's probably Cytochrome P450s that 21:24.967 --> 21:28.587 are the enzymes that are denaturing the plant products 21:28.586 --> 21:30.496 that would make us sick. 21:30.500 --> 21:33.280 But the one which is really kind of sad and funny is the 21:33.275 --> 21:33.825 aardwolf. 21:33.828 --> 21:41.368 The aardwolf is a hyena that has specialized on eating ants 21:41.368 --> 21:44.778 and termites; that's the only thing it eats, 21:44.778 --> 21:45.408 as an adult. 21:45.410 --> 21:51.760 Baby aardwolves grow up with milk, from mom. 21:51.759 --> 21:53.809 And my friend, Tim Clutton-Brock, 21:53.805 --> 21:56.745 has watched the weaning process in an aardwolf, 21:56.746 --> 22:00.126 where mother is trying to convince baby to switch from 22:00.134 --> 22:01.354 milk to ants. 22:01.349 --> 22:03.599 > 22:03.599 --> 22:06.619 And baby is not happy. 22:06.619 --> 22:09.239 Those ants do not taste good. 22:09.240 --> 22:12.770 And fortunately baby probably doesn't realize that this is the 22:12.770 --> 22:15.410 rest of life; from here on out it's ants, 22:15.405 --> 22:16.775 all the way through. 22:16.778 --> 22:17.458 Okay? 22:17.455 --> 22:21.645 So that's real specialization. 22:21.650 --> 22:25.670 Another interaction that favors specialization is mutualism, 22:25.671 --> 22:29.281 where you have interactions that are already positive, 22:29.282 --> 22:31.262 or are becoming positive. 22:31.259 --> 22:33.919 They have symmetrical impacts on reproductive success, 22:33.921 --> 22:37.031 and these things are living in intimate contact for most or all 22:37.034 --> 22:38.244 of their life cycle. 22:38.240 --> 22:41.050 And mutualisms are very interesting and they make 22:41.050 --> 22:44.890 wonderful natural history, but they also carry the message 22:44.887 --> 22:47.507 that where it's a win-win situation, 22:47.509 --> 22:50.439 evolution is not always about competition. 22:50.440 --> 22:53.740 Evolution can be about both sides profiting from the 22:53.743 --> 22:56.463 interaction and doing better because of it, 22:56.464 --> 22:59.774 and that ends up in a mutualistic relationship. 22:59.769 --> 23:02.869 So the relative evolutionary potential basically is 23:02.865 --> 23:05.215 determined first by generation time; 23:05.220 --> 23:07.060 second by sexual mode. 23:07.058 --> 23:10.888 Sexual partners can evolve more rapidly than asexual partners, 23:10.890 --> 23:14.400 and the partner that therefore has more genetic variation, 23:14.400 --> 23:16.730 for the interaction trait, will evolve more rapidly. 23:16.730 --> 23:20.330 So to some degree we kind of predict how the coevolutionary 23:20.334 --> 23:21.644 process will occur. 23:21.640 --> 23:25.050 23:25.048 --> 23:27.928 Now the Red Queen, which comes from Through the 23:27.925 --> 23:30.735 Looking Glass, by Lewis Carroll--and I'll go 23:30.737 --> 23:34.137 into that a little bit more-- is the idea that there is an 23:34.144 --> 23:37.954 open-ended struggle that results in no long-term reduction in 23:37.951 --> 23:39.601 extinction probability. 23:39.598 --> 23:41.838 Here's an example of a Red Queen process; 23:41.839 --> 23:42.779 there are many. 23:42.779 --> 23:45.329 But this would be a host/parasite interaction. 23:45.328 --> 23:48.738 And what you see here is generation time for things that 23:48.736 --> 23:51.086 have about the same generation time. 23:51.088 --> 23:51.348 Okay? 23:51.348 --> 23:54.098 So we have a host and a parasite that have roughly the 23:54.103 --> 23:55.353 same generation time. 23:55.348 --> 23:57.128 This is the frequency of an allele. 23:57.130 --> 23:58.760 And these are interaction alleles. 23:58.759 --> 24:01.379 So these are genes that are determining how well that 24:01.378 --> 24:04.248 parasite will do on this host, and how well this host will 24:04.250 --> 24:05.510 resist that parasite. 24:05.509 --> 24:10.609 And what's going on here is that when a certain host allele 24:10.608 --> 24:15.028 goes up to high frequency, that turns out to be one that 24:15.031 --> 24:18.261 this orange parasite allele can attack very well. 24:18.259 --> 24:21.519 And so the host has gone into a state that's susceptible to 24:21.518 --> 24:24.358 parasite attack; therefore that parasite allele 24:24.363 --> 24:25.833 increases in frequency. 24:25.828 --> 24:29.848 But, because that parasite allele is going up here, 24:29.848 --> 24:34.748 it's killing a lot of hosts up here, that host allele drops in 24:34.753 --> 24:35.883 frequency. 24:35.880 --> 24:39.600 As soon as that one drops in frequency, it makes the host 24:39.602 --> 24:42.662 less susceptible, and the parasite allele drops 24:42.660 --> 24:43.790 in frequency. 24:43.788 --> 24:46.408 And you can see there's a lag, there's a lag time between the 24:46.407 --> 24:46.667 two. 24:46.670 --> 24:50.560 Here it's sketched at about two or three generations. 24:50.558 --> 24:55.178 So this light rectangle here is indicating where the host is not 24:55.182 --> 24:58.512 having a problem, and the grey rectangle is 24:58.507 --> 25:01.997 indicating where the host is having a problem. 25:02.000 --> 25:05.730 So Leigh Van Valen is a paleontologist at the University 25:05.728 --> 25:09.998 of Chicago who came up with the Red Queen hypothesis in 1973. 25:10.000 --> 25:14.070 And he claimed that in fact it's not just hosts and 25:14.071 --> 25:16.931 parasites; he claimed all life on earth is 25:16.926 --> 25:19.526 in fact caught up in a coevolutionary web of 25:19.530 --> 25:20.500 interactions. 25:20.500 --> 25:24.910 And his evidence for that is that the long-term extinction 25:24.910 --> 25:26.380 rate is constant. 25:26.380 --> 25:29.450 If you look over the Phanerozoic, if you look over 25:29.450 --> 25:32.790 the last 550 million years, the probability that a species 25:32.786 --> 25:35.786 will go extinct, within a given period of time, 25:35.788 --> 25:37.988 has remained roughly constant. 25:37.990 --> 25:41.290 There's some slight evidence that maybe species have started 25:41.290 --> 25:42.970 to live a little bit longer. 25:42.970 --> 25:45.120 But, you know, broad brush, 25:45.122 --> 25:47.112 this claim is correct. 25:47.108 --> 25:50.708 Things have not gotten better at persisting, 25:50.705 --> 25:53.545 over the last 500 million years. 25:53.548 --> 26:00.178 So in some sense I think Leigh's claim is probably true. 26:00.180 --> 26:04.230 Every time a species on earth tries to get a leg up, 26:04.234 --> 26:06.864 some other species compensates. 26:06.859 --> 26:09.889 26:09.890 --> 26:12.810 So this is where that term comes from. 26:12.808 --> 26:17.548 This is an illustration from Through the Looking Glass 26:17.548 --> 26:20.468 by Charles Dodgson (Lewis Carroll). 26:20.470 --> 26:24.410 This--Alice is a pawn on a chessboard, 26:24.410 --> 26:27.970 and Alice is supposed to, in this mental game, 26:27.970 --> 26:31.050 march down the chessboard and get turned into a queen, 26:31.049 --> 26:32.609 when she reaches the end. 26:32.608 --> 26:34.638 And the Red Queen, who is next to her, 26:34.640 --> 26:37.130 says, "Alice, this is a game in which you run 26:37.131 --> 26:40.081 as fast as you can and you can only stay in place." 26:40.078 --> 26:42.708 So it's like one of those nightmares that you have, 26:42.711 --> 26:45.241 where you're running as fast as you possibly can, 26:45.238 --> 26:46.658 and you can't get away. 26:46.660 --> 26:49.060 That's Leigh Van Valen's metaphor for evolution: 26:49.058 --> 26:51.918 everybody is running as hard as they can and they're just 26:51.916 --> 26:55.886 staying in place; their fitness is not long-term 26:55.886 --> 26:56.946 improving. 26:56.950 --> 26:59.750 Now I'd like to give you a few striking outcomes of 26:59.753 --> 27:00.543 coevolution. 27:00.538 --> 27:03.468 I'm going to do butterfly mimics, reef-building corals, 27:03.472 --> 27:05.322 leafcutter ants, and rinderpest. 27:05.318 --> 27:08.928 And each of these is making a slightly different kind of 27:08.925 --> 27:13.115 point, but each of them involves some absolutely stunning natural 27:13.123 --> 27:13.913 history. 27:13.910 --> 27:16.320 So let's start with mimics and models. 27:16.318 --> 27:19.378 And these guys are, by the way, all from the 27:19.383 --> 27:21.453 Peabody Museum Collections. 27:21.450 --> 27:23.590 So, you know, if you love butterflies, 27:23.588 --> 27:25.968 you can go over and talk to the invertebrate curator at the 27:25.967 --> 27:28.847 Peabody Collections, and he can pull out tray after 27:28.854 --> 27:32.424 tray after tray of thousands of beautiful butterflies. 27:32.420 --> 27:34.840 We had one of the great butterfly biologists here, 27:34.840 --> 27:35.830 Charles Remington. 27:35.828 --> 27:38.468 And he was buddies with Vladimir Nabokov, 27:38.470 --> 27:40.020 who not only wrote Lolita, 27:40.015 --> 27:43.255 but was a lepidopterist, and so we've got some Nabokov 27:43.256 --> 27:45.856 butterflies in the collection as well. 27:45.858 --> 27:47.598 I don't know if any of these are from Nabokov. 27:47.599 --> 27:48.589 Okay? 27:48.588 --> 27:54.888 So in Batesian mimicry you've got an edible model that evolves 27:54.886 --> 28:00.046 to resemble a warningly colored noxious species. 28:00.049 --> 28:01.679 Okay? 28:01.680 --> 28:05.640 So actually what's going on--I've actually misphrased 28:05.636 --> 28:07.156 that a little bit. 28:07.160 --> 28:12.210 The noxious one is going to be the model, and the edible one is 28:12.205 --> 28:14.155 going to be the mimic. 28:14.160 --> 28:15.150 Sorry about that. 28:15.150 --> 28:16.810 I'm going to go back and correct that. 28:16.808 --> 28:21.758 So the mimic is good to eat and the model is bad to eat. 28:21.759 --> 28:27.019 And on Madagascar there aren't any models, and the male and the 28:27.019 --> 28:30.329 female look the same in this species. 28:30.328 --> 28:32.968 But as you go out, through Africa, 28:32.971 --> 28:37.141 you find that in different places in Africa there are 28:37.136 --> 28:42.276 different nasty tasting models, and the female turns into 28:42.280 --> 28:46.080 something that looks very much like them. 28:46.078 --> 28:50.078 So this thing has evolved into all of these other things, 28:50.084 --> 28:53.164 depending upon where they are, in Africa. 28:53.160 --> 28:54.840 Now this is not simple. 28:54.838 --> 28:57.978 It takes a lot of genes to turn something like that into 28:57.981 --> 28:59.241 something like that. 28:59.240 --> 29:02.190 And when you go into a neighboring race--it's still in 29:02.191 --> 29:04.911 the same species; the males are still looking 29:04.906 --> 29:08.276 like that--you have to have a whole bunch of coordinated 29:08.282 --> 29:10.802 changes to make it into the other one. 29:10.798 --> 29:13.988 So what's happened is that these genes have been pulled 29:13.990 --> 29:15.750 together, onto a chromosome, 29:15.748 --> 29:18.018 and turned into a super-gene complex, 29:18.019 --> 29:21.629 which has been inverted so that it doesn't recombine, 29:21.630 --> 29:22.980 and they're inherited as a package. 29:22.980 --> 29:28.020 29:28.019 --> 29:34.759 Now in Mullerian mimicry you have a process whereby things 29:34.759 --> 29:40.909 that all taste bad evolve to look like each other. 29:40.910 --> 29:44.840 Can anybody tell me why things that all taste bad might evolve 29:44.843 --> 29:46.523 to look like each other? 29:46.519 --> 29:47.669 What's the advantage in that? 29:47.670 --> 29:48.490 Yes? 29:48.490 --> 29:57.810 Student: > 29:57.809 --> 29:58.809 Prof: Right, exactly. 29:58.808 --> 30:02.988 So basically what they're doing is they're making it as easy as 30:02.994 --> 30:06.844 possible for the predator's learning process to figure out 30:06.844 --> 30:10.224 that all things that look like this taste bad. 30:10.220 --> 30:13.730 They're reducing the mistake rate, in the things that are 30:13.734 --> 30:15.434 learning not to eat them. 30:15.430 --> 30:19.890 So these are the Heliconia butterflies of South America, 30:19.885 --> 30:23.365 and they live all on passion fruit vines. 30:23.368 --> 30:25.858 So there's a big radiation of different species of passion 30:25.855 --> 30:28.335 fruit in South America, and these butterflies all lay 30:28.337 --> 30:30.987 their eggs on those different species of passion fruit, 30:30.990 --> 30:34.300 and where they overlap, the different species have 30:34.296 --> 30:36.586 evolved to look like each other. 30:36.588 --> 30:42.208 So what we have here is Mullerian mimicry going on here, 30:42.205 --> 30:45.155 and here; and we have Batesian going 30:45.156 --> 30:47.896 on--excuse, me, this is all Mullerian; 30:47.900 --> 30:50.260 this is Batesian mimicry. 30:50.259 --> 30:53.559 So Mullerian is everybody distasteful. 30:53.558 --> 30:58.558 This is a Batesian mimic of all of these distasteful models. 30:58.558 --> 31:01.748 This is a Batesian mimic of all of these distasteful models; 31:01.750 --> 31:02.470 and so forth. 31:02.470 --> 31:05.590 31:05.588 --> 31:08.828 So, those are pretty precise adaptations. 31:08.828 --> 31:12.148 I mean, if it gets to the point where a good naturalist really 31:12.147 --> 31:15.357 has to puzzle for awhile to identify whether you're looking- 31:15.356 --> 31:17.856 dealing with the model or with the mimic, 31:17.858 --> 31:20.918 and has to really know their details of morphology, 31:20.920 --> 31:25.160 it means that natural selection has precisely adjusted virtually 31:25.160 --> 31:29.390 every part of the body, so that the mimic really looks 31:29.394 --> 31:30.724 like the model. 31:30.720 --> 31:34.530 Now a tight symbiotic relationship is between- is the 31:34.525 --> 31:37.005 one that's between dinoflagellates, 31:37.013 --> 31:40.823 that are called zooxanthellae, and their corals. 31:40.818 --> 31:44.858 And there are also--so here is a coral. 31:44.858 --> 31:48.138 And, by the way, there are also zooxanthellae 31:48.141 --> 31:51.051 living in the lip of this giant clam. 31:51.048 --> 31:56.328 So this giant clam and the coral are both farming algae. 31:56.328 --> 32:01.578 And the algae are photosynthesizing and delivering 32:01.575 --> 32:04.675 photosynthate, to the host. 32:04.680 --> 32:11.150 And you can see here the chloroplast of one of these 32:11.154 --> 32:17.504 algae, and its body is in here, and it is producing 32:17.503 --> 32:21.683 photosynthate; and these are the starches that 32:21.681 --> 32:22.841 it's accumulating. 32:22.838 --> 32:25.808 Now the relationship goes something like this. 32:25.808 --> 32:29.408 The dynoflagellates, which by the way look like this 32:29.410 --> 32:33.870 when they're out in open water; they're really quite lovely. 32:33.868 --> 32:36.078 And remember, these are some of the guys that 32:36.078 --> 32:38.688 have so many membranes around their chloroplasts, 32:38.690 --> 32:43.890 because they're the result of three or four ingestion events 32:43.886 --> 32:46.086 over evolutionary time. 32:46.088 --> 32:50.718 If they produce say 250 joules of energy, through 32:50.724 --> 32:54.884 photosynthesis, they export 225 of it to the 32:54.876 --> 32:59.206 corals; and they only put about .2 into 32:59.207 --> 33:02.577 growth and 25 into respiration. 33:02.578 --> 33:07.858 So they've been almost completely domesticated. 33:07.858 --> 33:11.048 Pig farmers have been trying for hundreds of years to get 33:11.045 --> 33:13.145 pigs that would be this efficient, 33:13.150 --> 33:16.380 for humans, and these corals have turned these 33:16.378 --> 33:20.608 dinoflagellates into a energy conversion machine that's just 33:20.614 --> 33:23.994 incredibly efficient, from their own point of view. 33:23.990 --> 33:26.170 The corals, of course, have tentacles, 33:26.170 --> 33:28.740 and they will feed on zooplankton and stuff which is 33:28.742 --> 33:30.932 out there, but they only get about 33:30.925 --> 33:34.175 1/10^(th) of their energy from feeding directly; 33:34.180 --> 33:35.860 they get most of it from photosynthesis. 33:35.858 --> 33:39.148 And then what they do is they put a little bit of it into 33:39.151 --> 33:39.681 growth. 33:39.680 --> 33:44.320 They put a lot of it into their calcified skeleton--so basically 33:44.324 --> 33:47.424 you're looking at where reefs come from; 33:47.420 --> 33:50.980 this is how a reef is produced--and then they lose 33:50.980 --> 33:55.340 quite a bit to respiration and to the mucus that they produce 33:55.343 --> 33:56.873 in their feeding. 33:56.868 --> 34:01.118 So they're getting about ten times the energy from their 34:01.117 --> 34:04.977 symbiotic algae as they are from direct feeding. 34:04.980 --> 34:09.750 Now one of the implications of this is this is why you do not 34:09.746 --> 34:13.716 find reef-building corals deeper than 20 meters. 34:13.719 --> 34:16.419 It's because there's not enough light for the algae, 34:16.418 --> 34:17.898 any deeper than 20 meters. 34:17.900 --> 34:20.430 Okay? 34:20.429 --> 34:25.869 Now the crazy thing about this system is that a baby coral has 34:25.869 --> 34:31.129 to acquire the algae in each generation, and the algae exist 34:31.132 --> 34:33.542 as independent species. 34:33.539 --> 34:37.589 So the algae are actually incredibly phenotypically 34:37.590 --> 34:40.870 plastic; they have a free-living form, 34:40.867 --> 34:45.627 and they have a domesticated form, and they can reproduce 34:45.632 --> 34:46.742 both ways. 34:46.739 --> 34:51.259 And that's very interesting because from the point of view 34:51.255 --> 34:54.425 of the algae, the free-living form is the 34:54.425 --> 34:58.145 source and the domesticated form is a sink; 34:58.150 --> 35:04.290 and it's therefore puzzling to see how it was that the corals 35:04.289 --> 35:07.769 were able to engineer the algae. 35:07.768 --> 35:10.778 There's got to be some kind of coupling of the cycle so that 35:10.780 --> 35:14.100 what goes on in the coral feeds back into the free-living form; 35:14.099 --> 35:19.159 otherwise you couldn't get this tight adaptation. 35:19.159 --> 35:23.309 They're re-domesticated in each generation, in the coral. 35:23.309 --> 35:28.829 Okay, now for a macroevolutionary, 35:28.831 --> 35:32.681 coevolutionary story. 35:32.679 --> 35:36.349 How many of you have been in the Tropics and have seen 35:36.353 --> 35:37.673 leafcutting ants? 35:37.670 --> 35:39.690 Four or five, six. 35:39.690 --> 35:43.380 These guys are great, and they form huge colonies. 35:43.380 --> 35:47.600 The chamber that they can form is the size of this dais up 35:47.601 --> 35:48.121 here. 35:48.119 --> 35:50.279 It will be three or four feet high, 35:50.280 --> 35:53.150 and if you're out in a rainforest, the cutting 35:53.150 --> 35:56.920 activities of the workers will actually clear all the leaves 35:56.916 --> 35:58.916 off the trees, over the chamber, 35:58.916 --> 36:02.026 right to the canopy; so you kind of exist in a well 36:02.034 --> 36:05.254 in the forest, where the ants have essentially 36:05.253 --> 36:07.973 punched right through, 200,250 feet up, 36:07.972 --> 36:10.192 taking out all the leaves. 36:10.190 --> 36:13.020 And they take them down, into their underground chamber, 36:13.023 --> 36:15.963 where they chew them up and they feed them to a fungus. 36:15.960 --> 36:21.060 And they domesticated this fungus 50 million years ago. 36:21.059 --> 36:21.329 Okay? 36:21.327 --> 36:24.257 Humans figured out how to domesticate wheat 10,000 years 36:24.264 --> 36:24.644 ago. 36:24.639 --> 36:28.249 The ants domesticated the fungus 50 million years ago. 36:28.250 --> 36:31.430 They're the first farmers; well the corals probably did it 36:31.427 --> 36:31.947 earlier. 36:31.949 --> 36:32.379 Okay? 36:32.380 --> 36:35.910 But this is another domestication event. 36:35.909 --> 36:40.629 So they cultivate this fungus clonally. 36:40.630 --> 36:44.980 The fungus can't reproduce sexually, in the colony, 36:44.978 --> 36:49.498 and it looks like it's been asexual ever since it was 36:49.501 --> 36:50.981 domesticated. 36:50.980 --> 36:52.800 It's a monoculture. 36:52.800 --> 36:56.580 Now in human agriculture, a monoculture is incredibly 36:56.583 --> 36:58.843 vulnerable to plant diseases. 36:58.840 --> 37:02.120 Having a continent covered by a single strain of wheat, 37:02.119 --> 37:06.379 or a single strain of sorghum, or a single strain of sugarcane 37:06.382 --> 37:09.192 is a bad idea, because pathogens will evolve 37:09.190 --> 37:11.650 onto that particular monoculture genotype, 37:11.650 --> 37:14.040 and they can go through in an epidemic and wipe the whole 37:14.038 --> 37:14.548 thing out. 37:14.550 --> 37:18.770 So having a mix of genotypes in agriculture is a very good idea. 37:18.768 --> 37:22.748 Well that's not what the leafcutter ants did. 37:22.750 --> 37:26.790 37:26.789 --> 37:30.389 They have a pathogen that can attack their own--okay?--and 37:30.391 --> 37:31.721 it's also a fungus. 37:31.719 --> 37:34.069 So there's another fungus that can come into the colony and 37:34.072 --> 37:35.252 take over their own fungus. 37:35.250 --> 37:38.870 But to fight it, they cultivate a bacterium, 37:38.871 --> 37:43.671 and they use that bacterium as a defense against the enemy 37:43.672 --> 37:44.602 fungus. 37:44.599 --> 37:48.309 And they have a- they've evolved a special morphological 37:48.309 --> 37:51.209 pouch in which they carry this bacterium. 37:51.210 --> 37:53.990 And you'll notice that because it's a bacterium, 37:53.994 --> 37:55.954 it has a short generation time. 37:55.949 --> 37:59.919 So they have the coevolutionary arms race matched up in terms of 37:59.922 --> 38:00.492 timing. 38:00.489 --> 38:04.079 They have a bacterium that can evolve as fast, 38:04.079 --> 38:07.829 or faster, than the fungus that infects them. 38:07.829 --> 38:11.559 So they have not only domesticated their food supply, 38:11.561 --> 38:15.581 they've also invented a health delivery system to keep it 38:15.579 --> 38:17.159 healthy; they have a pharmacy. 38:17.159 --> 38:20.889 38:20.889 --> 38:26.219 Now if you look at the macroevolution of this system, 38:26.219 --> 38:30.709 what you see here basically is the phylogeny of the ant, 38:30.710 --> 38:34.050 the phylogeny of their fungus, and the phylogeny of their 38:34.052 --> 38:36.872 parasite, over here. 38:36.869 --> 38:40.639 And the thing that I want you to notice is that although it's 38:40.639 --> 38:43.839 not absolutely precise, these things match up pretty 38:43.844 --> 38:44.414 well. 38:44.409 --> 38:46.799 So the parts that are in blue--I mean, 38:46.800 --> 38:51.170 sometimes you find a few more parasites, 38:51.170 --> 38:56.150 hitting a few more cultivars, but roughly speaking if there's 38:56.150 --> 38:59.720 a branch at a certain point in the tree, 38:59.719 --> 39:02.409 it is a branch for all three things. 39:02.409 --> 39:05.569 It's not precisely matched, but it's pretty close. 39:05.570 --> 39:07.380 This is an amazing system. 39:07.380 --> 39:11.270 And when Ulrich Mueller, who has worked on it--and this 39:11.266 --> 39:14.646 is actually-- he's a co-author on this paper. 39:14.650 --> 39:18.780 He's a professor at the University of Texas in Austin. 39:18.780 --> 39:21.310 When he visited and gave a talk on it, I asked Ulrich, 39:21.306 --> 39:23.496 "How did you come to this system?" 39:23.500 --> 39:25.970 And he said, "Well, about twenty-five 39:25.965 --> 39:29.105 years ago I took an OTS course, and we were sitting there in 39:29.108 --> 39:31.818 Costa Rica, and we played the 50 Questions 39:31.824 --> 39:34.424 game, and my question was about 39:34.422 --> 39:36.342 leafcutter ants." 39:36.340 --> 39:38.440 And that's his career. 39:38.440 --> 39:39.570 Okay? 39:39.570 --> 39:43.510 Questions have profound influence. 39:43.510 --> 39:48.160 Okay, rinderpest, the final one in this series. 39:48.159 --> 39:50.219 The point about rinderpest is this. 39:50.219 --> 39:53.389 I'm giving you this example to show you what happens when 39:53.394 --> 39:56.574 evolution has not occurred; and that gives you a feel for 39:56.570 --> 39:59.050 what has happened when evolution has occurred. 39:59.050 --> 40:01.030 Okay? 40:01.030 --> 40:04.570 So this is the rinderpest pathogen. 40:04.570 --> 40:07.370 It's a virus, and it attacks cattle, 40:07.373 --> 40:09.703 buffalo, eland, kudu, giraffe, 40:09.695 --> 40:12.655 bushbuck, warthogs and bush pigs; 40:12.659 --> 40:14.219 those are all ungulates. 40:14.219 --> 40:17.999 So it is attacking one clade on the mammalian tree; 40:18.000 --> 40:21.160 they're all things that have two hooves. 40:21.159 --> 40:24.539 And it evolved in Asia, and it came into Europe through 40:24.541 --> 40:26.421 human invasions, repeatedly. 40:26.420 --> 40:30.250 So things in Asia and Europe had evolutionary experience of 40:30.251 --> 40:33.481 rinderpest; they'd been exposed to this 40:33.480 --> 40:34.270 disease. 40:34.268 --> 40:38.138 However, things in Africa had not, and it got into Africa 40:38.144 --> 40:42.164 probably either when the Italians went into Somaliland, 40:42.159 --> 40:45.529 or when General Gordon brought in some Russian cattle when he 40:45.532 --> 40:49.692 went to relieve Khartoum; so in the 1880s rinderpest got 40:49.686 --> 40:54.786 into Africa, and it came in because Europeans were bringing 40:54.786 --> 40:56.806 cattle in with them. 40:56.809 --> 40:59.269 And by 1890, it had crossed the Sahara, 40:59.273 --> 41:01.483 and gotten into Southern Africa. 41:01.480 --> 41:04.590 So there were some direct consequences. 41:04.590 --> 41:07.800 It eliminated--in the 1890s it took out most of the domestic 41:07.797 --> 41:10.567 cattle and wild buffalo, and many related bovids. 41:10.570 --> 41:13.450 This caused enormous famine and disruption in the humans who 41:13.449 --> 41:16.279 were living in Africa and who either had domestic cattle or 41:16.282 --> 41:17.212 nomadic cattle. 41:17.210 --> 41:19.740 So, you know, the Masai really got hammered 41:19.737 --> 41:20.337 by this. 41:20.340 --> 41:22.930 Only one species went extinct--it was a species of 41:22.925 --> 41:25.775 antelope-- but the distributions of all of 41:25.782 --> 41:29.372 the other wild ungulates in Africa were altered, 41:29.369 --> 41:32.279 and they remain altered to this day. 41:32.280 --> 41:35.040 They're springing back in some areas, and there are now 41:35.041 --> 41:38.321 vaccines for rinderpest that are being used on domestic cattle in 41:38.315 --> 41:39.795 places like South Africa. 41:39.800 --> 41:43.560 So the distributions are altering, but you can still see 41:43.557 --> 41:45.537 the signature of the event. 41:45.539 --> 41:49.799 People lost food supplies, and there was an outbreak of 41:49.798 --> 41:53.268 endemic smallpox, while this was going on. 41:53.268 --> 41:57.798 So it started causing a cascade of effects, through the 41:57.802 --> 41:58.812 ecosystem. 41:58.809 --> 42:01.839 There were epizootics--an epizootic is like an epidemic, 42:01.844 --> 42:04.664 except it happens in populations of wild animals. 42:04.659 --> 42:08.389 So there were epizootics in 1917/18; 42:08.389 --> 42:11.299 so right at the time of the outbreak of the World Flu 42:11.297 --> 42:13.607 Epidemic, people in Africa were also 42:13.610 --> 42:17.210 getting hammered by another outbreak of rinderpest hitting 42:17.206 --> 42:18.276 their animals. 42:18.280 --> 42:21.540 1923; 1938 to '41. 42:21.539 --> 42:27.509 This is the kind of habitat in which rinderpest was spreading. 42:27.510 --> 42:29.610 There were some interesting indirect consequences. 42:29.610 --> 42:32.830 So over a lot of the infected area, 42:32.829 --> 42:36.739 tsetse flies disappeared, and the reason tsetse flies 42:36.735 --> 42:40.715 disappeared is that they make their living off of wild 42:40.717 --> 42:41.767 ungulates. 42:41.768 --> 42:44.748 So if there aren't any wildebeest or giraffes around 42:44.750 --> 42:48.020 for the tsetse flies to eat, they will disappear from the 42:48.023 --> 42:48.553 area. 42:48.550 --> 42:52.730 Now they require trees and bushes as their habitat, 42:52.726 --> 42:55.396 and herbivores for their food. 42:55.400 --> 42:58.790 Now when the herbivores disappeared because of 42:58.786 --> 43:02.626 rinderpest, the tsetses lost their food, 43:02.630 --> 43:08.340 but their habitat sprang up, because there weren't ungulates 43:08.340 --> 43:13.170 eating the bushes that the tsetse flies would live in. 43:13.170 --> 43:15.980 When things like wildebeest disappeared, the lions got 43:15.981 --> 43:18.901 hungry, and there were outbreaks of man-eating lions. 43:18.900 --> 43:22.140 So in the 1920s, during a rinderpest epidemic, 43:22.135 --> 43:25.225 there was one lion that killed 84 people. 43:25.230 --> 43:27.240 When I first went to Queen Elizabeth National Park, 43:27.239 --> 43:31.759 in 1992, there were people living in the park, 43:31.760 --> 43:35.470 squatters living in the park, and they would try to get to 43:35.467 --> 43:38.397 the store at Park Headquarters, on a bicycle, 43:38.402 --> 43:41.862 and the lions had learned that it was possible to separate that 43:41.856 --> 43:44.526 blob on top of this funny two-wheeled thing, 43:44.530 --> 43:47.160 from what was moving so fast. 43:47.159 --> 43:49.879 And so like pussycats chasing balls of twine, 43:49.880 --> 43:52.450 they had gotten into knocking over bicycles and eating people, 43:52.449 --> 43:55.319 and there had been thirteen people who had been killed in 43:55.322 --> 43:57.172 the two months before we arrived, 43:57.170 --> 43:59.520 in Queen Elizabeth National Park. 43:59.518 --> 44:01.978 That kind of thing still goes on. 44:01.980 --> 44:06.910 So the lions contributed to the abandonment of big areas, 44:06.911 --> 44:09.731 and thickets of brush grew up. 44:09.730 --> 44:12.420 So the ungulates went down, and the people pulled back, 44:12.422 --> 44:13.522 and the bushes grew. 44:13.519 --> 44:18.139 44:18.139 --> 44:22.409 Now when the ungulates developed some immunity to 44:22.405 --> 44:25.175 rinderpest, and they moved back into the 44:25.179 --> 44:28.179 abandoned farming areas, they then became hosts for 44:28.179 --> 44:31.339 tsetse flies that could now live in the new bushes. 44:31.340 --> 44:31.640 Okay? 44:31.635 --> 44:35.245 So you see rinderpest goes in, and it changes a bunch of stuff 44:35.251 --> 44:37.861 ecologically, and it changes the geography of 44:37.858 --> 44:38.568 Africa. 44:38.570 --> 44:41.880 And the flies transmit sleeping sickness; 44:41.880 --> 44:43.920 so they do that, by the way, both in the 44:43.922 --> 44:47.122 ungulates and--sleeping sickness is a real problem in domestic 44:47.119 --> 44:48.849 cattle, as well as in people. 44:48.849 --> 44:51.829 And so the humans really pulled out of this area, 44:51.826 --> 44:55.606 and they remained absent even after the lions switched back to 44:55.608 --> 44:57.158 eating the ungulates. 44:57.159 --> 45:00.259 If you go into the Serengeti, just west of Seronera, 45:00.260 --> 45:03.240 there is a valley between Seronera and Lake Victoria, 45:03.239 --> 45:05.619 which is called The Valley of Death, 45:05.619 --> 45:07.909 and that's because of the sleeping sickness that's endemic 45:07.907 --> 45:10.857 in the valley; and that's an example of what 45:10.858 --> 45:12.848 happens in this process. 45:12.849 --> 45:18.429 And by the way, we call these areas now, 45:18.434 --> 45:25.884 to a certain extent, the National Parks of Africa. 45:25.880 --> 45:29.040 So if you wonder why those parks are where they are, 45:29.041 --> 45:32.451 in part it's due to the history that I just told you. 45:32.449 --> 45:35.879 So rinderpest changed the ecological structure of at least 45:35.880 --> 45:38.290 half a continent, for about a century. 45:38.289 --> 45:41.949 The consequences were pretty bad, and they were only kind of 45:41.945 --> 45:43.675 predictable in retrospect. 45:43.679 --> 45:47.329 Nobody had the knowledge, when General Gordon relieved 45:47.331 --> 45:49.541 Khartoum, with a few Russian cattle in 45:49.536 --> 45:52.476 his supply train, that they were carrying a virus 45:52.480 --> 45:55.140 that would do this to a whole continent. 45:55.139 --> 45:56.139 Okay? 45:56.139 --> 46:00.019 I think that this is one of those places where we have to be 46:00.016 --> 46:04.086 extremely modest about how much we understand about ecology and 46:04.090 --> 46:05.010 evolution. 46:05.010 --> 46:08.950 Bad shit can happen. 46:08.949 --> 46:16.789 So the same thing happened in the New World when Europeans, 46:16.789 --> 46:19.489 who were relatively resistant to smallpox and measles and 46:19.494 --> 46:21.914 things like that, brought with them their 46:21.911 --> 46:25.831 diseases, and that is why they were able to overthrow the Aztec 46:25.829 --> 46:26.839 civilization. 46:26.840 --> 46:29.380 If you ever ask yourself, how the heck did a couple of 46:29.376 --> 46:32.246 hundred Conquistadores wipe out an Aztec army of 100,000, 46:32.250 --> 46:35.170 the answer is the Aztecs were all sick and dying, 46:35.170 --> 46:37.940 and by the time the Conquistadores got to Mexico 46:37.938 --> 46:39.438 City, from Vera Cruz, 46:39.436 --> 46:42.106 the epidemic had spread ahead of them; 46:42.110 --> 46:45.300 and that happened all over the New World and all over 46:45.302 --> 46:46.042 Polynesia. 46:46.039 --> 46:50.819 So the point of this basically is we want to compare what 46:50.815 --> 46:56.355 happened in Africa with what did not happen in Asia and Europe. 46:56.360 --> 46:59.960 The Eurasian ungulates have a long evolutionary history with 46:59.958 --> 47:03.798 rinderpest, and the ones that we see there are the ones that are 47:03.802 --> 47:05.642 not extinct; they made it. 47:05.639 --> 47:07.349 Okay? 47:07.349 --> 47:11.579 And if we summarize coevolution as a whole, there are lots of 47:11.577 --> 47:13.197 things that coevolve. 47:13.199 --> 47:16.159 It's not just species that are coevolving with each other; 47:16.159 --> 47:18.349 it happens at many scales. 47:18.349 --> 47:22.329 And that means that other living things are among the most 47:22.333 --> 47:25.763 important elements of the selected environment. 47:25.760 --> 47:30.740 So you shouldn't think of organisms as being faced only by 47:30.744 --> 47:36.084 challenges of temperature and rainfall and stuff like that. 47:36.079 --> 47:40.139 Really, once life got going, the different species on the 47:40.143 --> 47:44.863 planet became each other's most important interaction partners. 47:44.860 --> 47:48.290 Part of this is running just as fast as you can to stay in one 47:48.289 --> 47:50.469 place; and this Red Queen concept is 47:50.467 --> 47:53.447 probably particularly appropriate for the virulence 47:53.449 --> 47:57.059 resistance paradigm, and for the evolution of sex as 47:57.063 --> 47:59.393 an adaptation against parasites. 47:59.389 --> 48:02.159 And as the rinderpest example shows us, 48:02.159 --> 48:06.769 the extent of coevolution is particularly strikingly revealed 48:06.773 --> 48:11.543 when you see a foreign species invade another continent after a 48:11.539 --> 48:13.769 long period of isolation. 48:13.769 --> 48:14.809 Okay. 48:14.809 --> 48:19.999