1 00:00:00,160 --> 00:00:13,870 [Music] 2 00:00:18,980 --> 00:00:16,790 first I I want to introduce some people 3 00:00:21,849 --> 00:00:18,990 in my lab who did the work 4 00:00:27,380 --> 00:00:21,859 Nick HUD he's one of my best postdocs 5 00:00:31,009 --> 00:00:27,390 and Nick is my close collaborator and 6 00:00:32,900 --> 00:00:31,019 and a lot of what I'm doing is it has to 7 00:00:35,930 --> 00:00:32,910 do with our interaction but I'm gonna 8 00:00:36,590 --> 00:00:35,940 talk about work from Anton Petrov second 9 00:00:40,819 --> 00:00:36,600 right there 10 00:00:43,700 --> 00:00:40,829 Nick Kovacs Katherine Lanier Jessica 11 00:00:46,520 --> 00:00:43,710 Bowman and then my collaborators I have 12 00:00:49,250 --> 00:00:46,530 a some very nice collaborators at 13 00:00:52,580 --> 00:00:49,260 Georgia Tech Nick HUD Roger work tell 14 00:00:56,119 --> 00:00:52,590 and then George Fox who said Houston and 15 00:00:59,240 --> 00:00:56,129 I'd like to thank the organizers Irina 16 00:01:00,560 --> 00:00:59,250 wherever you are for inviting me here 17 00:01:02,779 --> 00:01:00,570 and running such a great meeting and 18 00:01:05,600 --> 00:01:02,789 keeping it so organized of course this 19 00:01:07,940 --> 00:01:05,610 is Japan so of course it's organized and 20 00:01:10,280 --> 00:01:07,950 I like to say hello to my friends in 21 00:01:10,850 --> 00:01:10,290 California at the end the I good 22 00:01:21,890 --> 00:01:10,860 afternoon 23 00:01:24,590 --> 00:01:21,900 so we're what we do is we try to 24 00:01:28,370 --> 00:01:24,600 understand the origin of life from 25 00:01:31,310 --> 00:01:28,380 extant biology and we look at the tree 26 00:01:33,080 --> 00:01:31,320 of life or the circle of life I guess if 27 00:01:35,600 --> 00:01:33,090 this thing and we look all around this 28 00:01:37,490 --> 00:01:35,610 thing and we try to use that to walk 29 00:01:41,060 --> 00:01:37,500 backwards in time and there's a lot of 30 00:01:44,870 --> 00:01:41,070 people who do this kind of thing but we 31 00:01:46,429 --> 00:01:44,880 I think probably go back further and one 32 00:01:48,889 --> 00:01:46,439 of the one of the ways we can do that is 33 00:01:50,030 --> 00:01:48,899 that we focus on structure on 34 00:01:53,450 --> 00:01:50,040 three-dimensional structure there is 35 00:01:55,130 --> 00:01:53,460 this axiom I guess you could say that 36 00:01:57,380 --> 00:01:55,140 structure is more conserved than 37 00:01:59,929 --> 00:01:57,390 sequence and if you want to look far far 38 00:02:02,389 --> 00:01:59,939 back in time you use structure instead 39 00:02:05,899 --> 00:02:02,399 of sequence so you can have especially 40 00:02:08,419 --> 00:02:05,909 with nucleic acids you can have you can 41 00:02:11,180 --> 00:02:08,429 have RNAs in which the the sequence is 42 00:02:13,320 --> 00:02:11,190 essentially scrambled between two RNAs 43 00:02:17,110 --> 00:02:13,330 and yet the structures are 44 00:02:18,790 --> 00:02:17,120 essentially it's in the experiment so so 45 00:02:20,410 --> 00:02:18,800 you can have variation in sequence but 46 00:02:22,839 --> 00:02:20,420 structure is conserved if you want to 47 00:02:28,020 --> 00:02:22,849 look far back in time you use structure 48 00:02:32,740 --> 00:02:30,790 okay so this is basically what we're 49 00:02:36,759 --> 00:02:32,750 after this is the Tree of Life we're 50 00:02:38,290 --> 00:02:36,769 interested in Luca and what was Luca 51 00:02:40,089 --> 00:02:38,300 we're sort of interested in that and 52 00:02:41,920 --> 00:02:40,099 then where did Luca come from basically 53 00:02:45,100 --> 00:02:41,930 this is the process and we're focused on 54 00:02:47,170 --> 00:02:45,110 the translation system and sort of for 55 00:02:49,360 --> 00:02:47,180 background you should know that the 56 00:02:52,660 --> 00:02:49,370 translation system was done at Luca so 57 00:02:54,430 --> 00:02:52,670 when you talk about the origin and 58 00:02:56,590 --> 00:02:54,440 evolution of the translation system 59 00:02:59,170 --> 00:02:56,600 you're really talking about things that 60 00:03:00,610 --> 00:02:59,180 happened before Luca so if we can if we 61 00:03:02,259 --> 00:03:00,620 can understand the origin of the 62 00:03:05,020 --> 00:03:02,269 translation system we are we are looking 63 00:03:06,580 --> 00:03:05,030 really far back in time you know 3.8 or 64 00:03:11,259 --> 00:03:06,590 4 billion years ago it depending on when 65 00:03:12,490 --> 00:03:11,269 life so of course this is what everybody 66 00:03:13,990 --> 00:03:12,500 does when they look at the origin of 67 00:03:17,970 --> 00:03:14,000 life and this is sort of various models 68 00:03:20,890 --> 00:03:17,980 people have there's RNA world clay world 69 00:03:22,990 --> 00:03:20,900 metabolism world vents and membranes 70 00:03:27,910 --> 00:03:23,000 which we've heard some about some of 71 00:03:29,289 --> 00:03:27,920 this at this meeting and I probably 72 00:03:31,300 --> 00:03:29,299 haven't really done justice to these 73 00:03:32,770 --> 00:03:31,310 cartoon representations but these are 74 00:03:33,940 --> 00:03:32,780 these are probably about all the models 75 00:03:38,229 --> 00:03:33,950 but this is kind of a survey of the 76 00:03:42,360 --> 00:03:38,239 model and then we have the data and this 77 00:03:45,160 --> 00:03:42,370 is the data that we focus on which is 78 00:03:47,770 --> 00:03:45,170 what I call the universal gene set 79 00:03:50,289 --> 00:03:47,780 things that everything alive has and 80 00:03:52,270 --> 00:03:50,299 it's actually there's several amazing 81 00:03:54,160 --> 00:03:52,280 characteristics of this universal gene 82 00:03:57,819 --> 00:03:54,170 set and this is this is a from 83 00:03:59,800 --> 00:03:57,829 Doolittle's paper in 2004 but pace has 84 00:04:02,140 --> 00:03:59,810 looked at this and Coonan and there is a 85 00:04:03,640 --> 00:04:02,150 nice consensus pretty much on what the 86 00:04:06,789 --> 00:04:03,650 universal gene set is and these are 87 00:04:09,099 --> 00:04:06,799 basically genes that you can find 88 00:04:11,470 --> 00:04:09,109 orthologues in everything alive so this 89 00:04:12,610 --> 00:04:11,480 is this is what you would say is 90 00:04:14,500 --> 00:04:12,620 universal biology 91 00:04:16,810 --> 00:04:14,510 everything has this and the first thing 92 00:04:18,580 --> 00:04:16,820 about it is it's a very small list it 93 00:04:20,379 --> 00:04:18,590 doesn't have very many genes on it 94 00:04:23,830 --> 00:04:20,389 depends on whose version you have but it 95 00:04:27,520 --> 00:04:23,840 has between 30 to 50 genes it's a small 96 00:04:29,110 --> 00:04:27,530 list and I've color-coded them here by 97 00:04:33,100 --> 00:04:29,120 what they what they're involved in and 98 00:04:34,990 --> 00:04:33,110 the the pink is translation and then we 99 00:04:37,210 --> 00:04:35,000 have replication transcription and 100 00:04:39,280 --> 00:04:37,220 replication and basically that the point 101 00:04:41,890 --> 00:04:39,290 of this thing is that this is dominated 102 00:04:44,500 --> 00:04:41,900 by translation so the universal gene set 103 00:04:46,600 --> 00:04:44,510 of biology is dominated by translation 104 00:04:49,510 --> 00:04:46,610 and this list actually does not have 105 00:04:51,730 --> 00:04:49,520 genes that encode RNAs so there are no 106 00:04:53,140 --> 00:04:51,740 genes four tRNAs on here and ribosomal 107 00:04:54,730 --> 00:04:53,150 RNAs and things like that if you 108 00:04:56,620 --> 00:04:54,740 actually included those on this list it 109 00:04:59,080 --> 00:04:56,630 would be a longer list and there would 110 00:05:04,510 --> 00:04:59,090 be more pink okay so the universal gene 111 00:05:07,750 --> 00:05:04,520 set of life is dominated by translation 112 00:05:11,110 --> 00:05:07,760 that's point of this and so you have 113 00:05:13,870 --> 00:05:11,120 this problem here that you have the data 114 00:05:15,730 --> 00:05:13,880 that sort of tells us about Luca and 115 00:05:18,130 --> 00:05:15,740 then you have these models and the 116 00:05:20,380 --> 00:05:18,140 models don't fit the data in the sense 117 00:05:22,590 --> 00:05:20,390 that the right let's say already world 118 00:05:25,240 --> 00:05:22,600 for example the RNA world predicts 119 00:05:26,920 --> 00:05:25,250 ribozymes that can replicate themselves 120 00:05:28,480 --> 00:05:26,930 and do metabolism and things like this 121 00:05:32,440 --> 00:05:28,490 and there are no there's nothing like 122 00:05:33,130 --> 00:05:32,450 that here there's no integral membrane 123 00:05:38,980 --> 00:05:33,140 proteins 124 00:05:41,140 --> 00:05:38,990 biosynthesis there's you know that these 125 00:05:46,390 --> 00:05:41,150 models are totally disconnected from 126 00:05:47,920 --> 00:05:46,400 this data and so what should you do if a 127 00:05:50,890 --> 00:05:47,930 model and you have data and they don't 128 00:05:54,520 --> 00:05:50,900 fit generally people would throw away 129 00:05:55,600 --> 00:05:54,530 the data that seems to be sort of what 130 00:05:57,700 --> 00:05:55,610 has happened in the origin of life 131 00:06:00,310 --> 00:05:57,710 people who study the origin of life 132 00:06:03,010 --> 00:06:00,320 basically ignore the universal gene set 133 00:06:07,090 --> 00:06:03,020 because it doesn't seem to relate to 134 00:06:11,320 --> 00:06:07,100 their models so when we look at this 135 00:06:13,510 --> 00:06:11,330 basically our idea is I just ignore all 136 00:06:16,000 --> 00:06:13,520 the models I just want to use the data 137 00:06:17,950 --> 00:06:16,010 and I want to walk the data back and say 138 00:06:20,080 --> 00:06:17,960 what does the data tell me about the 139 00:06:22,210 --> 00:06:20,090 origin of life I don't care about RNA 140 00:06:24,730 --> 00:06:22,220 world I don't care about metabolism 141 00:06:25,330 --> 00:06:24,740 world I just want to know what this 142 00:06:28,060 --> 00:06:25,340 means 143 00:06:31,300 --> 00:06:28,070 number one I want to know why is it so 144 00:06:36,339 --> 00:06:31,310 small why is it dominated by translation 145 00:06:38,110 --> 00:06:36,349 and can we use this to walk back and an 146 00:06:39,850 --> 00:06:38,120 important thing about this list is these 147 00:06:41,530 --> 00:06:39,860 are sequences right these are sequences 148 00:06:43,690 --> 00:06:41,540 that encode 149 00:06:45,610 --> 00:06:43,700 proteins but we know the structures of 150 00:06:47,050 --> 00:06:45,620 these proteins right crystallographers 151 00:06:49,150 --> 00:06:47,060 have determined drivers almost 152 00:06:51,340 --> 00:06:49,160 structures we know this is so so this 153 00:06:53,740 --> 00:06:51,350 isn't just a gene set of life this is 154 00:06:56,260 --> 00:06:53,750 really the sort of structure of life we 155 00:06:59,340 --> 00:06:56,270 know the universal three-dimensional 156 00:07:01,480 --> 00:06:59,350 structure of biology the conserved part 157 00:07:06,870 --> 00:07:01,490 another thing I'll point out about this 158 00:07:11,890 --> 00:07:09,460 you know people focus on things that are 159 00:07:13,990 --> 00:07:11,900 universal in biology but because there 160 00:07:16,150 --> 00:07:14,000 is this disconnect between the data and 161 00:07:18,520 --> 00:07:16,160 the models they tend to focus on small 162 00:07:20,880 --> 00:07:18,530 molecules so you'll hear people talk 163 00:07:23,020 --> 00:07:20,890 about metabolites and small molecules of 164 00:07:24,700 --> 00:07:23,030 biology that are highly conserved and 165 00:07:27,130 --> 00:07:24,710 they'll ascribe importance to these 166 00:07:29,560 --> 00:07:27,140 things but they never look at the 167 00:07:31,180 --> 00:07:29,570 macromolecules which are universal 168 00:07:33,130 --> 00:07:31,190 biology and the reason I think people 169 00:07:35,650 --> 00:07:33,140 don't do that is because this doesn't 170 00:07:38,940 --> 00:07:35,660 fit the models and it's very hard to 171 00:07:41,380 --> 00:07:38,950 take these universal macromolecules and 172 00:07:42,720 --> 00:07:41,390 fit them to these models they just 173 00:07:46,090 --> 00:07:42,730 they're just there's just no 174 00:07:49,360 --> 00:07:46,100 relationship between them okay so this 175 00:07:51,670 --> 00:07:49,370 is what we do we're looking at universal 176 00:07:53,140 --> 00:07:51,680 three-dimensional structures and we do 177 00:07:54,850 --> 00:07:53,150 that as I said because structures more 178 00:07:55,960 --> 00:07:54,860 conservative than sequence we want to 179 00:07:57,850 --> 00:07:55,970 look far back in time we use 180 00:07:59,410 --> 00:07:57,860 three-dimensional structures and we're 181 00:08:02,860 --> 00:07:59,420 asking you know what is the universal 182 00:08:04,300 --> 00:08:02,870 three-dimensional structure of life how 183 00:08:06,370 --> 00:08:04,310 conserved is it you know sequence is 184 00:08:08,380 --> 00:08:06,380 kind of digital essentially you could 185 00:08:09,400 --> 00:08:08,390 say this is a C this is a G but when 186 00:08:10,720 --> 00:08:09,410 you're talking about structure you know 187 00:08:13,600 --> 00:08:10,730 you're talking about something that is 188 00:08:15,400 --> 00:08:13,610 continuous you know you have RMS ease of 189 00:08:17,140 --> 00:08:15,410 atoms or something and it's and it's a 190 00:08:19,510 --> 00:08:17,150 little bit it's actually significantly 191 00:08:21,910 --> 00:08:19,520 more different difficult to sort of be 192 00:08:23,680 --> 00:08:21,920 analytical and quantitative about 193 00:08:26,110 --> 00:08:23,690 structural conservation than it is about 194 00:08:27,580 --> 00:08:26,120 sequence conservation so we have to sort 195 00:08:31,780 --> 00:08:27,590 of work and figure out how to deal with 196 00:08:33,670 --> 00:08:31,790 that we want to know how structure is 197 00:08:35,440 --> 00:08:33,680 elaborated like we have things that are 198 00:08:38,500 --> 00:08:35,450 conserved but then the part that varies 199 00:08:39,790 --> 00:08:38,510 what are the rules of that and then what 200 00:08:41,260 --> 00:08:39,800 are the origins of these conserved 201 00:08:45,100 --> 00:08:41,270 structures that's really that's really 202 00:08:47,560 --> 00:08:45,110 what we're after so what I what I'm sure 203 00:08:49,660 --> 00:08:47,570 you hear are secondary structures of 204 00:08:52,050 --> 00:08:49,670 ribosomal RNAs first thing these are 205 00:08:54,880 --> 00:08:52,060 very large molecules they're huge and 206 00:08:58,290 --> 00:08:54,890 this is e coli yeast 207 00:09:01,269 --> 00:08:58,300 I Inhumans and I want to first focus on 208 00:09:02,590 --> 00:09:01,279 let's just look at this little that 209 00:09:04,420 --> 00:09:02,600 little purple thing right there that 210 00:09:08,920 --> 00:09:04,430 little knob and what I want you to 211 00:09:12,460 --> 00:09:08,930 notice is B coli has it yeast has it 212 00:09:14,920 --> 00:09:12,470 fruit fly has it almost sapiens have it 213 00:09:17,949 --> 00:09:14,930 everything everything in biology has 214 00:09:20,410 --> 00:09:17,959 that okay and we have sequences of many 215 00:09:21,759 --> 00:09:20,420 ribosomal I mean the data is very rich 216 00:09:24,040 --> 00:09:21,769 here and we have three-dimensional 217 00:09:26,220 --> 00:09:24,050 structures and we can say that 218 00:09:31,269 --> 00:09:26,230 everything in biology has that little 219 00:09:32,470 --> 00:09:31,279 knob right there and but what really we 220 00:09:34,060 --> 00:09:32,480 want to look at is the three-dimensional 221 00:09:36,460 --> 00:09:34,070 structures so what I want to do is I 222 00:09:38,230 --> 00:09:36,470 want to show you kind of what what we 223 00:09:39,880 --> 00:09:38,240 mean when we say the universal structure 224 00:09:42,790 --> 00:09:39,890 of biology so I'm just going to take a 225 00:09:43,870 --> 00:09:42,800 part of this thing we have crystal 226 00:09:54,360 --> 00:09:43,880 structures of all these and show you 227 00:10:01,810 --> 00:09:58,650 okay I fixed it so this is this is a 228 00:10:03,880 --> 00:10:01,820 part of the ribosomal RNA from ecoli and 229 00:10:08,019 --> 00:10:03,890 I've stripped out all the bases it's 230 00:10:08,650 --> 00:10:08,029 just a trace of the backbone and it's 231 00:10:12,310 --> 00:10:08,660 beautiful 232 00:10:14,310 --> 00:10:12,320 okay if you look at and this is a global 233 00:10:16,689 --> 00:10:14,320 superimposition of ribosomes 234 00:10:18,280 --> 00:10:16,699 this is archaea okay so these are two 235 00:10:22,000 --> 00:10:18,290 separate branches of the phylogenetic 236 00:10:23,710 --> 00:10:22,010 tree and you can see that these look 237 00:10:25,689 --> 00:10:23,720 pretty similar now the interesting thing 238 00:10:27,819 --> 00:10:25,699 is the sequences are not necessarily the 239 00:10:30,939 --> 00:10:27,829 same right like this is a helix here and 240 00:10:33,460 --> 00:10:30,949 you helix can accommodate many sequences 241 00:10:36,069 --> 00:10:33,470 right so the sequences are not fully 242 00:10:37,480 --> 00:10:36,079 conserved but the structure is so these 243 00:10:39,910 --> 00:10:37,490 are two branches of the Tree of Life 244 00:10:43,600 --> 00:10:39,920 I can look at the other one here's yeast 245 00:10:45,850 --> 00:10:43,610 and basically this is it this is the 246 00:10:49,030 --> 00:10:45,860 diversity in all of biology that you're 247 00:10:51,430 --> 00:10:49,040 looking at this is this is how much this 248 00:10:53,710 --> 00:10:51,440 thing changes and I used to say this 249 00:10:55,810 --> 00:10:53,720 thing is how much it changes over four 250 00:11:00,699 --> 00:10:55,820 billion years of evolution but Greg 251 00:11:03,250 --> 00:11:00,709 Fournier pointed out that I need to 252 00:11:06,189 --> 00:11:03,260 double that because the distance from 253 00:11:08,139 --> 00:11:06,199 Luca to e.coli is four billion years the 254 00:11:10,569 --> 00:11:08,149 distance from Luca to 255 00:11:14,350 --> 00:11:10,579 hey lark EULA is 4 billion years so this 256 00:11:16,509 --> 00:11:14,360 is 8 billion years of evolution and this 257 00:11:20,379 --> 00:11:16,519 is showing you how much the structure 258 00:11:24,009 --> 00:11:20,389 changes and then just to kind of top it 259 00:11:26,170 --> 00:11:24,019 off you know evolution sort of is is on 260 00:11:28,059 --> 00:11:26,180 steroids in organelles and things are 261 00:11:30,809 --> 00:11:28,069 happening much faster in organelles in 262 00:11:34,179 --> 00:11:30,819 in in cytoplasm and so here is the 263 00:11:38,079 --> 00:11:34,189 mitochondrial ribosome from Homo sapiens 264 00:11:40,329 --> 00:11:38,089 and this you know basically this is just 265 00:11:41,619 --> 00:11:40,339 cemented this is okay there's some 266 00:11:45,309 --> 00:11:41,629 geologists here so I'm going to say 267 00:11:49,059 --> 00:11:45,319 something incorrect me this is the most 268 00:11:51,549 --> 00:11:49,069 permanent thing that is not cold in the 269 00:11:55,420 --> 00:11:51,559 universe I don't know if that's true but 270 00:11:58,900 --> 00:11:55,430 it sounds good you can it's but it 271 00:12:01,780 --> 00:11:58,910 really is very very constant okay so 272 00:12:04,509 --> 00:12:01,790 what we have done is this is just part 273 00:12:06,189 --> 00:12:04,519 of the ribosome we have looked at the 274 00:12:08,230 --> 00:12:06,199 entire ribosome and we've defined what 275 00:12:11,650 --> 00:12:08,240 we call the common core so this is the 276 00:12:13,629 --> 00:12:11,660 bacterial this is e.coli ribosome this 277 00:12:16,299 --> 00:12:13,639 is large subunit RNA and small subunit 278 00:12:19,119 --> 00:12:16,309 and the blue parts are the part that are 279 00:12:22,809 --> 00:12:19,129 structurally conserved in everything 280 00:12:24,730 --> 00:12:22,819 alive okay and we've Chad Bernier is a 281 00:12:27,009 --> 00:12:24,740 graduate student who actually graduated 282 00:12:28,929 --> 00:12:27,019 but he spent years this this to work 283 00:12:30,400 --> 00:12:28,939 this out involved superimposition 284 00:12:33,699 --> 00:12:30,410 alignment it was a sort of iterative 285 00:12:36,340 --> 00:12:33,709 process of figuring out what's what and 286 00:12:37,869 --> 00:12:36,350 and so like for example this is this 287 00:12:39,759 --> 00:12:37,879 little blue bump I told you that 288 00:12:42,160 --> 00:12:39,769 everything has it's right there and 289 00:12:44,350 --> 00:12:42,170 right there but then like look at it 290 00:12:46,960 --> 00:12:44,360 let's focus on this little arm here see 291 00:12:49,749 --> 00:12:46,970 e.coli has an arm there and halo ocula 292 00:12:51,910 --> 00:12:49,759 doesn't so that's black so the things 293 00:12:53,439 --> 00:12:51,920 that are common are blue and and really 294 00:12:56,439 --> 00:12:53,449 the point of this slide is that to a 295 00:13:00,009 --> 00:12:56,449 first approximation the e.coli ribosome 296 00:13:03,100 --> 00:13:00,019 is the universal core everything in 297 00:13:06,400 --> 00:13:03,110 biology has something equivalent to the 298 00:13:08,019 --> 00:13:06,410 the bacterial ribosome okay and you can 299 00:13:10,030 --> 00:13:08,029 see it's not exactly true because the 300 00:13:11,610 --> 00:13:10,040 black parts are or where that breaks 301 00:13:15,480 --> 00:13:11,620 down but to a first approximation 302 00:13:21,290 --> 00:13:15,490 everything alive has a ecoli ribosome 303 00:13:28,790 --> 00:13:24,380 all around this tree that's that's 8 304 00:13:30,199 --> 00:13:28,800 billion years of evolution ok so but now 305 00:13:34,940 --> 00:13:30,209 I want to focus on the parts that are 306 00:13:36,620 --> 00:13:34,950 different because you can look here like 307 00:13:38,750 --> 00:13:36,630 look at the you the human ribosome has 308 00:13:41,540 --> 00:13:38,760 these devil horns right look at those 309 00:13:43,130 --> 00:13:41,550 those devil horns and of course bacteria 310 00:13:44,960 --> 00:13:43,140 don't have that and so there are places 311 00:13:47,110 --> 00:13:44,970 of the ribosome varies and what I want 312 00:13:49,250 --> 00:13:47,120 to focus on that for a minute because 313 00:13:51,949 --> 00:13:49,260 what I want to do is figure out how the 314 00:13:53,990 --> 00:13:51,959 ribosome changes over time and it turns 315 00:13:56,750 --> 00:13:54,000 out that the rules are very strict and 316 00:13:59,090 --> 00:13:56,760 there are very specific things that can 317 00:14:01,430 --> 00:13:59,100 happen to the ribosome you know like 318 00:14:02,690 --> 00:14:01,440 nothing can happen there that's just not 319 00:14:05,509 --> 00:14:02,700 allowed ok 320 00:14:06,769 --> 00:14:05,519 but this helix right here that's a lot 321 00:14:12,259 --> 00:14:06,779 of things are allowed there in fact they 322 00:14:13,880 --> 00:14:12,269 have well okay let me just really what 323 00:14:15,530 --> 00:14:13,890 what you have is you have something 324 00:14:17,840 --> 00:14:15,540 called the universal common core and 325 00:14:20,210 --> 00:14:17,850 that's the E coli ribosome basically and 326 00:14:23,509 --> 00:14:20,220 then you have a eukaryotic shell and 327 00:14:27,019 --> 00:14:23,519 those are these sorts of things and then 328 00:14:29,269 --> 00:14:27,029 in metazoans especially in mammals you 329 00:14:34,090 --> 00:14:29,279 have these tentacles that go out so 330 00:14:36,470 --> 00:14:34,100 really there are I'd say an extant 331 00:14:38,540 --> 00:14:36,480 ribosomes there are these sort of three 332 00:14:39,980 --> 00:14:38,550 phases there's the common core that 333 00:14:42,230 --> 00:14:39,990 everything happens then there's a 334 00:14:45,290 --> 00:14:42,240 eukaryotic shell the first shell and 335 00:14:47,210 --> 00:14:45,300 then there are these metazoan expansion 336 00:14:49,610 --> 00:14:47,220 segments so this is this is the large 337 00:14:51,740 --> 00:14:49,620 subunit we're looking at this sort of 338 00:14:54,019 --> 00:14:51,750 summarizes the evolution of the ribosome 339 00:14:56,240 --> 00:14:54,029 and we know this because we have 340 00:14:59,120 --> 00:14:56,250 examples all over the phylogenetic tree 341 00:15:03,199 --> 00:14:59,130 of these things okay now I want to focus 342 00:15:05,030 --> 00:15:03,209 on this helix this is called helix 25 an 343 00:15:07,400 --> 00:15:05,040 e.coli but it's called expansion segment 344 00:15:08,960 --> 00:15:07,410 seven and eukaryotes because it's no 345 00:15:11,269 --> 00:15:08,970 longer a helix once you get that you 346 00:15:13,490 --> 00:15:11,279 eukaryotes it gets really enormous in 347 00:15:16,100 --> 00:15:13,500 fact look at human it has these 348 00:15:19,730 --> 00:15:16,110 tentacles humans has has really long 349 00:15:21,560 --> 00:15:19,740 tentacles the ribosome it's kind of like 350 00:15:23,960 --> 00:15:21,570 kudzu if you actually cuz he was a 351 00:15:26,329 --> 00:15:23,970 Japanese vine that was imported in the 352 00:15:30,170 --> 00:15:26,339 United States and it grows like a foot a 353 00:15:32,949 --> 00:15:30,180 day and the eukaryotic ribosomes kind of 354 00:15:35,030 --> 00:15:32,959 reminds me of kudzu these arms are 355 00:15:36,560 --> 00:15:35,040 changing very rapidly over 356 00:15:40,250 --> 00:15:36,570 evolution and they seem to be getting 357 00:15:41,420 --> 00:15:40,260 longer and longer but what I want to do 358 00:15:42,860 --> 00:15:41,430 is I want to look at these in three 359 00:15:44,360 --> 00:15:42,870 dimensions we know how this grows 360 00:15:45,410 --> 00:15:44,370 everything I'm showing you here is in 361 00:15:47,420 --> 00:15:45,420 two dimensions but we know what this 362 00:15:49,880 --> 00:15:47,430 looks like in three dimensions and so 363 00:15:52,970 --> 00:15:49,890 this is what we call the vishnu basement 364 00:15:54,650 --> 00:15:52,980 this is helix 25 this is the bottom this 365 00:15:58,250 --> 00:15:54,660 is there everywhere it never goes away 366 00:16:00,530 --> 00:15:58,260 and and that's we know that what that is 367 00:16:02,450 --> 00:16:00,540 from bacterial ribosomes and we have 368 00:16:04,240 --> 00:16:02,460 ecoli and thermus thermophilus we have 369 00:16:06,710 --> 00:16:04,250 crystal structures of quite a few 370 00:16:10,010 --> 00:16:06,720 bacterial ribosomes and then when you 371 00:16:12,950 --> 00:16:10,020 look at archaea you can see helix 25 is 372 00:16:17,360 --> 00:16:12,960 still there and then something has grown 373 00:16:19,820 --> 00:16:17,370 out so this allows us to have an 374 00:16:21,800 --> 00:16:19,830 estimate of Luca right because we say 375 00:16:24,050 --> 00:16:21,810 what is common between archaea and 376 00:16:27,620 --> 00:16:24,060 bacteria is our best guess for Luca and 377 00:16:29,390 --> 00:16:27,630 so we say Luke I had helix 25 because 378 00:16:32,680 --> 00:16:29,400 that's what's common between archaea and 379 00:16:34,760 --> 00:16:32,690 bacteria that's sort of a standard way 380 00:16:36,680 --> 00:16:34,770 okay so but we can just keep walking 381 00:16:38,690 --> 00:16:36,690 here here's archaea 382 00:16:41,990 --> 00:16:38,700 here's yeast and what you can see is 383 00:16:43,520 --> 00:16:42,000 that the archaea element is essentially 384 00:16:44,660 --> 00:16:43,530 in yeast and then things have grown out 385 00:16:48,200 --> 00:16:44,670 of it 386 00:16:49,550 --> 00:16:48,210 here's fruit fly and fruit fly looks I 387 00:16:51,190 --> 00:16:49,560 mean really there's common ancestors 388 00:16:54,050 --> 00:16:51,200 here I don't want to give the idea that 389 00:16:56,090 --> 00:16:54,060 fruit fly ball from yeast but that but 390 00:16:58,640 --> 00:16:56,100 essentially the common ancestor looks 391 00:17:01,520 --> 00:16:58,650 like east and then things have grown out 392 00:17:02,960 --> 00:17:01,530 of it and then it's not nice you have a 393 00:17:04,640 --> 00:17:02,970 lot of crystal structures and cryo-em 394 00:17:06,710 --> 00:17:04,650 structures and then you can see the same 395 00:17:08,240 --> 00:17:06,720 thing so that so yes this is really 396 00:17:09,980 --> 00:17:08,250 important to us when we made this 397 00:17:11,870 --> 00:17:09,990 discovery that this is how the ribosome 398 00:17:13,970 --> 00:17:11,880 changes because this is a process called 399 00:17:15,800 --> 00:17:13,980 accretion it's just like geology 400 00:17:18,500 --> 00:17:15,810 it's just the way trees grow at the 401 00:17:21,650 --> 00:17:18,510 ribosome accretes and when of the creats 402 00:17:23,270 --> 00:17:21,660 like this helix 25 it's always there 403 00:17:25,280 --> 00:17:23,280 right when you add things onto the 404 00:17:26,660 --> 00:17:25,290 ribosome you don't mess with the 405 00:17:29,270 --> 00:17:26,670 underlying structure that's what 406 00:17:31,430 --> 00:17:29,280 evolution does and we have lots of 407 00:17:32,810 --> 00:17:31,440 examples over this of this over the I 408 00:17:34,430 --> 00:17:32,820 don't want to take time here but you can 409 00:17:36,320 --> 00:17:34,440 just sort of see it it looks like a 410 00:17:39,410 --> 00:17:36,330 movie of things going okay so the 411 00:17:41,930 --> 00:17:39,420 ribosome the ribosomal RNA I need to be 412 00:17:44,810 --> 00:17:41,940 careful the ribosomal RNA grows by 413 00:17:48,650 --> 00:17:44,820 accretion okay and when it does that 414 00:17:49,070 --> 00:17:48,660 when it when it increases in size it 415 00:17:50,750 --> 00:17:49,080 leaves 416 00:17:52,850 --> 00:17:50,760 fingerprints it's very nice it's like a 417 00:17:54,740 --> 00:17:52,860 tree and when you have a branch going on 418 00:17:56,389 --> 00:17:54,750 a tree there's a knot and so even if you 419 00:17:57,590 --> 00:17:56,399 cut the branch off you can cut into the 420 00:17:59,810 --> 00:17:57,600 tree and you could say yes there was a 421 00:18:01,490 --> 00:17:59,820 branch here once and so this is 422 00:18:04,159 --> 00:18:01,500 something we've identified called an 423 00:18:07,549 --> 00:18:04,169 insertion fingerprint that it's a 424 00:18:11,029 --> 00:18:07,559 specific structural element that allows 425 00:18:12,950 --> 00:18:11,039 us to say this green thing grew out of 426 00:18:14,630 --> 00:18:12,960 that red thing and we can do that 427 00:18:16,730 --> 00:18:14,640 because we have these structures of I 428 00:18:19,700 --> 00:18:16,740 mean we know that's true because this is 429 00:18:21,909 --> 00:18:19,710 answer the the the blue is the 430 00:18:24,730 --> 00:18:21,919 prokaryotic ribosomes and this is the 431 00:18:27,169 --> 00:18:24,740 eukaryotic ribosomes and we know that 432 00:18:29,659 --> 00:18:27,179 that the red was essentially that the 433 00:18:31,789 --> 00:18:29,669 blue was the ancestor of the red and 434 00:18:33,710 --> 00:18:31,799 green so you know this is not modeling 435 00:18:35,450 --> 00:18:33,720 this is structures and and we really 436 00:18:37,070 --> 00:18:35,460 know how the ribosome changes over time 437 00:18:39,470 --> 00:18:37,080 so we have two things we have the 438 00:18:41,269 --> 00:18:39,480 ribosome grows by accretion and when 439 00:18:43,070 --> 00:18:41,279 there are growth steps we don't know 440 00:18:45,950 --> 00:18:43,080 that all of them but many of the growth 441 00:18:48,230 --> 00:18:45,960 steps leave fingerprints so that even if 442 00:18:49,549 --> 00:18:48,240 you only have the human ribosome you 443 00:18:51,620 --> 00:18:49,559 could look and say there was a growth 444 00:18:52,940 --> 00:18:51,630 event here but we don't have to do that 445 00:18:55,940 --> 00:18:52,950 because there have many many ribosomes 446 00:18:58,039 --> 00:18:55,950 of all different sizes and shapes okay 447 00:19:00,440 --> 00:18:58,049 so now I want to use this tree analogy 448 00:19:03,200 --> 00:19:00,450 because the ribosome is very similar to 449 00:19:05,509 --> 00:19:03,210 a tree in that a tree records its 450 00:19:07,039 --> 00:19:05,519 history and it does that because it 451 00:19:08,690 --> 00:19:07,049 grows by accretion if the tree died out 452 00:19:10,759 --> 00:19:08,700 every year and regrew then next year 453 00:19:13,009 --> 00:19:10,769 then it wouldn't record its history 454 00:19:16,370 --> 00:19:13,019 right the reason a tree records history 455 00:19:18,409 --> 00:19:16,380 is that something happens and then that 456 00:19:19,639 --> 00:19:18,419 doesn't change you you add layers and 457 00:19:21,440 --> 00:19:19,649 layers you had twigs and branches and 458 00:19:23,389 --> 00:19:21,450 you you don't perturb the underlying 459 00:19:26,269 --> 00:19:23,399 thing when you have growth processes and 460 00:19:28,129 --> 00:19:26,279 so maybe for from Arizona and you 461 00:19:31,039 --> 00:19:28,139 haven't seen a tree before this wouldn't 462 00:19:34,190 --> 00:19:31,049 make sense to you but for the rest of us 463 00:19:35,769 --> 00:19:34,200 we can look at this tree and we can you 464 00:19:38,240 --> 00:19:35,779 could at very high level of detail 465 00:19:40,430 --> 00:19:38,250 ascribe relative age to everything on 466 00:19:43,370 --> 00:19:40,440 this tree right you could say the oldest 467 00:19:45,620 --> 00:19:43,380 part of this tree is in the center of 468 00:19:48,310 --> 00:19:45,630 that trunk the leaves are the most 469 00:19:50,870 --> 00:19:48,320 recent that small tricked twigs are are 470 00:19:54,830 --> 00:19:50,880 younger than the big twigs etc right and 471 00:19:56,990 --> 00:19:54,840 you can look at this tree and and sort 472 00:19:59,120 --> 00:19:57,000 of wat work out its history and it turns 473 00:20:00,740 --> 00:19:59,130 out I'm going to explain it a little bit 474 00:20:02,870 --> 00:20:00,750 to you but the ribosome is the same 475 00:20:05,690 --> 00:20:02,880 thing okay because it grew by a 476 00:20:08,360 --> 00:20:05,700 and because it leaves telltale signs 477 00:20:09,920 --> 00:20:08,370 when it undergoes a growth event you can 478 00:20:12,110 --> 00:20:09,930 look at the ribosome and you can read 479 00:20:14,600 --> 00:20:12,120 out its history just the same way you 480 00:20:15,800 --> 00:20:14,610 can read out the history of this tree so 481 00:20:18,830 --> 00:20:15,810 what this really means is there is a 482 00:20:21,380 --> 00:20:18,840 history of biology before Luca because 483 00:20:23,630 --> 00:20:21,390 the ribosome was done at Luca and we 484 00:20:26,420 --> 00:20:23,640 have ways of reading out the history of 485 00:20:28,370 --> 00:20:26,430 that ribosome so this is just to be 486 00:20:30,950 --> 00:20:28,380 really clear these are observations the 487 00:20:32,870 --> 00:20:30,960 modern ribosome it grew and it is 488 00:20:34,550 --> 00:20:32,880 growing by accretion and we have we know 489 00:20:36,620 --> 00:20:34,560 that because we have crystal structures 490 00:20:38,270 --> 00:20:36,630 of so many ribosomes across the 491 00:20:43,700 --> 00:20:38,280 phylogenetic tree so that is what we 492 00:20:45,530 --> 00:20:43,710 call an observation we we know that when 493 00:20:46,610 --> 00:20:45,540 growth events occur some of them not all 494 00:20:48,710 --> 00:20:46,620 of them but some of them leave 495 00:20:51,560 --> 00:20:48,720 fingerprints okay so this is what we 496 00:20:54,160 --> 00:20:51,570 know and then these are in inferences so 497 00:20:56,900 --> 00:20:54,170 we are assuming that the common core 498 00:20:59,090 --> 00:20:56,910 also grew by accretion now we don't know 499 00:21:01,130 --> 00:20:59,100 that because we can't watch it the way 500 00:21:03,560 --> 00:21:01,140 we can watch eukaryotic ribosomes but 501 00:21:05,480 --> 00:21:03,570 we're just assuming the process is 502 00:21:07,880 --> 00:21:05,490 continuous and we're also assuming that 503 00:21:09,800 --> 00:21:07,890 in the common core that growth fence 504 00:21:11,810 --> 00:21:09,810 left fingerprints so we're just assuming 505 00:21:14,420 --> 00:21:11,820 a kind of continuity if our assumption 506 00:21:15,410 --> 00:21:14,430 is wrong then it's wrong but I just want 507 00:21:18,440 --> 00:21:15,420 to be clear about what our assumptions 508 00:21:20,390 --> 00:21:18,450 are so based on that we can look at the 509 00:21:23,030 --> 00:21:20,400 common core so this is the thing that 510 00:21:25,670 --> 00:21:23,040 everything in biology has and we can 511 00:21:28,550 --> 00:21:25,680 work out how it grew so just I'll just 512 00:21:30,290 --> 00:21:28,560 focus on right here every time the color 513 00:21:33,110 --> 00:21:30,300 changes there is an insertion 514 00:21:35,000 --> 00:21:33,120 fingerprint here okay so you can say 515 00:21:36,950 --> 00:21:35,010 something there was a growth event that 516 00:21:39,740 --> 00:21:36,960 green and the red got out of that green 517 00:21:41,360 --> 00:21:39,750 got outed etc so we can see these 518 00:21:44,210 --> 00:21:41,370 insertion fingerprints and we're 519 00:21:46,160 --> 00:21:44,220 assuming that it grew by accretion so we 520 00:21:49,310 --> 00:21:46,170 can work out in a very high level of 521 00:21:53,600 --> 00:21:49,320 detail the steps in the growth of the 522 00:21:55,400 --> 00:21:53,610 common core and so see this red thing 523 00:21:57,050 --> 00:21:55,410 right there that that's actually the 524 00:21:59,440 --> 00:21:57,060 secondary structure is misleading that's 525 00:22:02,180 --> 00:21:59,450 a continuous helix this is your mother 526 00:22:03,710 --> 00:22:02,190 okay that is the beginning of the 527 00:22:06,980 --> 00:22:03,720 ribosome that is the first thing that 528 00:22:08,930 --> 00:22:06,990 happened and then there's a series of 529 00:22:10,550 --> 00:22:08,940 growth events that ultimately leave this 530 00:22:13,340 --> 00:22:10,560 but we can work out in a very high level 531 00:22:15,610 --> 00:22:13,350 of detail how the ribosome Grill in fact 532 00:22:16,850 --> 00:22:15,620 it's so much detail that it was just 533 00:22:19,700 --> 00:22:16,860 mind-boggling 534 00:22:21,470 --> 00:22:19,710 and we just kind of left it for a while 535 00:22:23,690 --> 00:22:21,480 and then we said okay let's simplify it 536 00:22:25,130 --> 00:22:23,700 so we group these things into phases we 537 00:22:26,600 --> 00:22:25,140 just kind of did a coarse graining of 538 00:22:29,120 --> 00:22:26,610 this to cut down on the amount of 539 00:22:31,400 --> 00:22:29,130 information so really we have these 540 00:22:33,320 --> 00:22:31,410 steps one two three four five we just 541 00:22:35,840 --> 00:22:33,330 call that we just sort of group them by 542 00:22:38,120 --> 00:22:35,850 color and it was a little you know we 543 00:22:39,980 --> 00:22:38,130 could have so we have we have five 544 00:22:41,600 --> 00:22:39,990 phases here we could have done four or 545 00:22:44,750 --> 00:22:41,610 we could have done six it was that's a 546 00:22:46,220 --> 00:22:44,760 bit art that's arbitrary but we just had 547 00:22:47,750 --> 00:22:46,230 to kind of cut down on the amount of 548 00:22:50,539 --> 00:22:47,760 detail because it was just more than we 549 00:22:52,789 --> 00:22:50,549 could deal with so but so this is sort 550 00:22:54,919 --> 00:22:52,799 of a more code so the blue is the first 551 00:22:59,390 --> 00:22:54,929 thing that happened dark blue light blue 552 00:23:01,310 --> 00:22:59,400 green then all those colors okay and we 553 00:23:03,680 --> 00:23:01,320 have large subunit small subunit and we 554 00:23:04,789 --> 00:23:03,690 have ways of correlating this is public 555 00:23:06,350 --> 00:23:04,799 so I don't to go into it but we have 556 00:23:08,620 --> 00:23:06,360 ways of correlating between the two 557 00:23:11,450 --> 00:23:08,630 subunits so we have a very very detailed 558 00:23:14,510 --> 00:23:11,460 model for the evolution of the ribosome 559 00:23:15,860 --> 00:23:14,520 and in our lab what we do is we make 560 00:23:18,500 --> 00:23:15,870 these things I mean we we have an 561 00:23:20,240 --> 00:23:18,510 experimental lab we we have predictions 562 00:23:22,070 --> 00:23:20,250 on what these molecules should do we can 563 00:23:24,350 --> 00:23:22,080 make any piece of RNA and we just make 564 00:23:25,909 --> 00:23:24,360 them and test the predictions and so 565 00:23:30,169 --> 00:23:25,919 that's really one of the main focuses of 566 00:23:32,150 --> 00:23:30,179 my lab and and this is the nice thing 567 00:23:34,220 --> 00:23:32,160 about RNA is that it tends to be modular 568 00:23:36,440 --> 00:23:34,230 and so because we have this structural 569 00:23:38,480 --> 00:23:36,450 map of what has happened we also have a 570 00:23:40,669 --> 00:23:38,490 functional map okay because the 571 00:23:42,590 --> 00:23:40,679 structure and the function are so easy 572 00:23:44,630 --> 00:23:42,600 to decipher so we have a very detailed 573 00:23:46,940 --> 00:23:44,640 map and all of these you know this is a 574 00:23:49,100 --> 00:23:46,950 hypothesis and we can make all of this 575 00:23:50,419 --> 00:23:49,110 easily we can we can make each one of 576 00:23:51,740 --> 00:23:50,429 these molecules we can test the 577 00:23:53,900 --> 00:23:51,750 predictions about what it should be 578 00:23:56,450 --> 00:23:53,910 doing so this is all experimental II 579 00:23:57,980 --> 00:23:56,460 grounded okay but I want to change 580 00:24:00,350 --> 00:23:57,990 subjects totally cuz so far I've talked 581 00:24:02,090 --> 00:24:00,360 to only about RNA and we've just talked 582 00:24:02,900 --> 00:24:02,100 about the changes of RNA how much time 583 00:24:07,970 --> 00:24:02,910 do I have Petula 584 00:24:11,419 --> 00:24:10,909 I'm fine okay cuz I have 47 more slides 585 00:24:18,020 --> 00:24:11,429 good 586 00:24:19,880 --> 00:24:18,030 she said I'm fine I don't really you 587 00:24:21,260 --> 00:24:19,890 guys so basically everything I've talked 588 00:24:22,789 --> 00:24:21,270 about so far is published but this is 589 00:24:25,010 --> 00:24:22,799 new and this is what I'm really 590 00:24:26,330 --> 00:24:25,020 interested in is the proteins I haven't 591 00:24:29,659 --> 00:24:26,340 talked about proteins yet we've only 592 00:24:31,159 --> 00:24:29,669 talked about RNA so what this is this is 593 00:24:33,140 --> 00:24:31,169 the three-dimensional structure of the 594 00:24:36,320 --> 00:24:33,150 bacterial ribosome and we have color 595 00:24:38,390 --> 00:24:36,330 coded the RNA by those phases so the 596 00:24:40,340 --> 00:24:38,400 oldest thing here is dark blue then 597 00:24:43,970 --> 00:24:40,350 light blue and green cetera okay so that 598 00:24:47,000 --> 00:24:43,980 the RNA is colored by its it's relative 599 00:24:51,530 --> 00:24:47,010 age and then the grey things here are 600 00:24:54,560 --> 00:24:51,540 the ribosomal proteins and what we have 601 00:24:56,240 --> 00:24:54,570 done is we have used the RNA to date the 602 00:25:00,770 --> 00:24:56,250 proteins and we just made kind of a 603 00:25:03,080 --> 00:25:00,780 simple assumption that that if a part of 604 00:25:07,070 --> 00:25:03,090 protein is surrounded by RNA then it's 605 00:25:11,930 --> 00:25:07,080 of the same age and and this is kind of 606 00:25:14,150 --> 00:25:11,940 a test of our model because I'll sort of 607 00:25:15,799 --> 00:25:14,160 show you why but if we can date the 608 00:25:17,570 --> 00:25:15,809 ribosomal RNA and we know what we're 609 00:25:24,360 --> 00:25:17,580 doing there then we should be able to 610 00:25:30,990 --> 00:25:29,370 okay all right okay so so what I have 611 00:25:33,240 --> 00:25:31,000 over here is I'm showing the ribosomal 612 00:25:34,830 --> 00:25:33,250 proteins and I've faded out the RNA and 613 00:25:38,250 --> 00:25:34,840 you can see the Rebels normal proteins 614 00:25:42,210 --> 00:25:38,260 are they're unique in in all of biology 615 00:25:45,840 --> 00:25:42,220 in they have these they're not random I 616 00:25:47,669 --> 00:25:45,850 mean they're they're not random coil 617 00:25:50,490 --> 00:25:47,679 because random coil is in an ensemble 618 00:25:53,730 --> 00:25:50,500 these are in specific States but they're 619 00:25:56,000 --> 00:25:53,740 non canonical so that's a it's a they're 620 00:25:58,440 --> 00:25:56,010 frozen they don't move but they're not 621 00:26:01,799 --> 00:25:58,450 folded in normal ways and you just don't 622 00:26:04,529 --> 00:26:01,809 see proteins doing this in biology and 623 00:26:06,720 --> 00:26:04,539 and what we've been able to do is we we 624 00:26:10,710 --> 00:26:06,730 take a given protein like this one and 625 00:26:13,590 --> 00:26:10,720 we cut it into segments and we cut it 626 00:26:15,899 --> 00:26:13,600 based on the age of the RNA around it so 627 00:26:18,269 --> 00:26:15,909 we can we basically say this part in 628 00:26:20,100 --> 00:26:18,279 fact this this color is one age that's 629 00:26:22,230 --> 00:26:20,110 another age that's at another age and we 630 00:26:24,630 --> 00:26:22,240 do that by the RNA that is surrounding 631 00:26:26,250 --> 00:26:24,640 it okay and that turns out to be pretty 632 00:26:27,840 --> 00:26:26,260 easy and clean there's some places where 633 00:26:32,700 --> 00:26:27,850 it's ambiguous you know but it's a 634 00:26:34,440 --> 00:26:32,710 pretty clean way so so we and there's a 635 00:26:36,060 --> 00:26:34,450 lot of proteins in the ribosome so this 636 00:26:38,010 --> 00:26:36,070 is a lot of data but this is kind of 637 00:26:40,980 --> 00:26:38,020 what it looks like is like so this is a 638 00:26:43,409 --> 00:26:40,990 ribosomal protein and this red part is 639 00:26:46,049 --> 00:26:43,419 the oldest and then this yellow part is 640 00:26:49,919 --> 00:26:46,059 younger and that is younger okay so we 641 00:26:52,740 --> 00:26:49,929 can segment these proteins by age and so 642 00:26:53,570 --> 00:26:52,750 these segments here are all of the same 643 00:26:58,820 --> 00:26:53,580 age 644 00:27:02,669 --> 00:26:58,830 time is moving in this direction right 645 00:27:05,310 --> 00:27:02,679 so and we didn't build this in we didn't 646 00:27:07,169 --> 00:27:05,320 sort of know it's going to be like this 647 00:27:09,990 --> 00:27:07,179 but this is basically a reaction 648 00:27:12,299 --> 00:27:10,000 coordinate of protein folding okay what 649 00:27:14,460 --> 00:27:12,309 we have here is frozen random coil I 650 00:27:15,750 --> 00:27:14,470 have another no okay we have tons of 651 00:27:17,970 --> 00:27:15,760 these proteins right there's a lot of 652 00:27:19,889 --> 00:27:17,980 them we have a lot of data here and I'm 653 00:27:21,779 --> 00:27:19,899 really in this what we call phase three 654 00:27:23,850 --> 00:27:21,789 that's the earliest phase where we see 655 00:27:26,269 --> 00:27:23,860 protein the actual core the ribosome 656 00:27:30,240 --> 00:27:26,279 itself has essentially no protein so 657 00:27:32,940 --> 00:27:30,250 when protein starts to show up in in 658 00:27:34,799 --> 00:27:32,950 phase 3 it's never folded there's no 659 00:27:37,020 --> 00:27:34,809 alpha helixes there's no beta sheet 660 00:27:38,250 --> 00:27:37,030 there's no hydrophobic cores there's 661 00:27:40,620 --> 00:27:38,260 nothing like that 662 00:27:42,990 --> 00:27:40,630 just looks like that and then the second 663 00:27:45,120 --> 00:27:43,000 thing we have is these isolated 664 00:27:47,580 --> 00:27:45,130 secondary structural elements and they 665 00:27:50,280 --> 00:27:47,590 tend to be data sheets not alpha helixes 666 00:27:54,420 --> 00:27:50,290 and then in the next phase we see 667 00:27:58,580 --> 00:27:54,430 collapse of these secondary elements to 668 00:28:01,020 --> 00:27:58,590 globular structures and then and then 669 00:28:02,430 --> 00:28:01,030 then those globular structures elaborate 670 00:28:04,890 --> 00:28:02,440 and the nice thing is I'm only showing 671 00:28:06,600 --> 00:28:04,900 you the prokaryotic ribosomes if we add 672 00:28:08,850 --> 00:28:06,610 the eukaryotic there's that shell and 673 00:28:10,890 --> 00:28:08,860 that shell came after one and a half 674 00:28:13,740 --> 00:28:10,900 billion years so we have another layer 675 00:28:15,300 --> 00:28:13,750 out here where we can say what happened 676 00:28:17,670 --> 00:28:15,310 and you can really see that protein 677 00:28:19,320 --> 00:28:17,680 folding so this is a reaction at 678 00:28:22,050 --> 00:28:19,330 coordinate for protein folding maybe 679 00:28:23,160 --> 00:28:22,060 I'll just okay jump to this I'm just 680 00:28:24,690 --> 00:28:23,170 gonna jump ahead we have a bunch of 681 00:28:26,460 --> 00:28:24,700 statistics so I'm just gonna ignore all 682 00:28:28,440 --> 00:28:26,470 that but this is what it this is what it 683 00:28:31,530 --> 00:28:28,450 looks like this is the ribosomal RNA 684 00:28:32,970 --> 00:28:31,540 colored by phase right so the I've 685 00:28:34,920 --> 00:28:32,980 changed the coloring scheme I know it 686 00:28:36,990 --> 00:28:34,930 yeah so this is young and this is old 687 00:28:38,670 --> 00:28:37,000 and this is ribosomal protein and what 688 00:28:40,410 --> 00:28:38,680 we get is a reaction coordinate and we 689 00:28:44,280 --> 00:28:40,420 think this is the reaction coordinate 690 00:28:46,920 --> 00:28:44,290 for the evolution of protein folding and 691 00:28:48,930 --> 00:28:46,930 what what we can see in this this result 692 00:28:53,570 --> 00:28:48,940 I just going to jump to them getting cut 693 00:28:58,050 --> 00:28:53,580 off here is that protein folding 694 00:28:59,760 --> 00:28:58,060 occurred in a sea of RNA those secondary 695 00:29:02,970 --> 00:28:59,770 structural elements I talked to you 696 00:29:05,190 --> 00:29:02,980 about I showed you are enveloped in RNA 697 00:29:07,860 --> 00:29:05,200 and we think RNA basically chaperoned 698 00:29:09,990 --> 00:29:07,870 protein folding and that protein folding 699 00:29:13,740 --> 00:29:10,000 is an emergent property of interactions 700 00:29:14,760 --> 00:29:13,750 with RNA and I didn't really show you 701 00:29:17,570 --> 00:29:14,770 this but 702 00:29:20,790 --> 00:29:17,580 but the RNA folding changes around the 703 00:29:24,090 --> 00:29:20,800 are basically these two polymers are 704 00:29:27,030 --> 00:29:24,100 changing together the RNA is changing as 705 00:29:29,850 --> 00:29:27,040 protein folds and as protein folds RNA 706 00:29:31,860 --> 00:29:29,860 is it's folding is changing also not as 707 00:29:35,630 --> 00:29:31,870 dramatically but they're definitely more 708 00:29:37,440 --> 00:29:35,640 sophisticated RNA folds around 709 00:29:40,680 --> 00:29:37,450 sophisticated protein folds so that 710 00:29:43,260 --> 00:29:40,690 leads us to our sort of what we believe 711 00:29:46,950 --> 00:29:43,270 is happening is that RNA and protein are 712 00:29:49,860 --> 00:29:46,960 what we call molecular symbols and that 713 00:29:51,510 --> 00:29:49,870 the evolution of protein folding was 714 00:29:53,880 --> 00:29:51,520 chaperoned by RNA and the 715 00:29:55,890 --> 00:29:53,890 the evolution of RNA I'm not saying 716 00:29:58,020 --> 00:29:55,900 folding because you had stem loops and 717 00:30:01,440 --> 00:29:58,030 things but complex RNA assembly was 718 00:30:02,850 --> 00:30:01,450 chaperoned by protein so that kind of 719 00:30:05,550 --> 00:30:02,860 leads us to how I've started to think 720 00:30:08,730 --> 00:30:05,560 about biology in general this is because 721 00:30:10,980 --> 00:30:08,740 my friend Nick HUD grows figs and he 722 00:30:13,320 --> 00:30:10,990 gives me fig jam sometime and so I 723 00:30:15,360 --> 00:30:13,330 started thinking about fig trees and you 724 00:30:17,820 --> 00:30:15,370 know fig there's a symbiotic 725 00:30:20,780 --> 00:30:17,830 relationship between wasps and figs the 726 00:30:23,820 --> 00:30:20,790 wasps pollinate the figs and the figs 727 00:30:25,740 --> 00:30:23,830 feed the wasp embryos and there's this 728 00:30:28,260 --> 00:30:25,750 beautiful what's called a mutualism 729 00:30:30,090 --> 00:30:28,270 relationship and this is all over 730 00:30:31,620 --> 00:30:30,100 biology of course in fact you are 731 00:30:34,740 --> 00:30:31,630 involved in relationships like this with 732 00:30:36,810 --> 00:30:34,750 microbes in your gut and and there is 733 00:30:40,170 --> 00:30:36,820 something about mutualism relationships 734 00:30:42,150 --> 00:30:40,180 in biology that confers advantage and we 735 00:30:44,610 --> 00:30:42,160 basically say that goes down to the 736 00:30:48,780 --> 00:30:44,620 molecular level and that RNA and protein 737 00:30:51,390 --> 00:30:48,790 are molecular symbols all RNA is made by 738 00:30:52,770 --> 00:30:51,400 protein all protein is made by RNA and 739 00:30:54,600 --> 00:30:52,780 you could we could throw in membranes 740 00:30:57,870 --> 00:30:54,610 and other elements to this too but that 741 00:31:00,210 --> 00:30:57,880 basically we define life as a molecular 742 00:31:01,890 --> 00:31:00,220 symbiosis and that definition sort of 743 00:31:05,520 --> 00:31:01,900 comes from what we have learned from the 744 00:31:12,420 --> 00:31:05,530 ribosome so that i think i'm terminated 745 00:31:25,740 --> 00:31:22,590 okay thanks Lauren that was great um I 746 00:31:27,750 --> 00:31:25,750 find myself wondering as you described 747 00:31:29,730 --> 00:31:27,760 the secretion through time do we know 748 00:31:32,390 --> 00:31:29,740 much about the functional consequences 749 00:31:34,200 --> 00:31:32,400 of those modifications of the ribosome 750 00:31:37,590 --> 00:31:34,210 in your carry ox 751 00:31:39,360 --> 00:31:37,600 actually that's some of it has to do 752 00:31:41,400 --> 00:31:39,370 actually charlie was just asking with 753 00:31:43,770 --> 00:31:41,410 ribosome biogenesis I mean if you people 754 00:31:46,620 --> 00:31:43,780 have cut these things off and say what 755 00:31:48,390 --> 00:31:46,630 happens and ribosome biogenesis stalls 756 00:31:50,730 --> 00:31:48,400 out but actually in our lab we've taken 757 00:31:52,320 --> 00:31:50,740 those human expansion segments and we've 758 00:31:54,360 --> 00:31:52,330 done pulldown assays and say what 759 00:31:55,830 --> 00:31:54,370 proteins bind to them and it's really 760 00:31:58,650 --> 00:31:55,840 interesting I mean it's like the 761 00:32:00,600 --> 00:31:58,660 proteasome is associated with the 762 00:32:02,070 --> 00:32:00,610 ribosome it binds to that and so we just 763 00:32:05,190 --> 00:32:02,080 we think they're kind of especially 764 00:32:07,110 --> 00:32:05,200 those tentacles are and those those are 765 00:32:09,600 --> 00:32:07,120 kind of docking sites we think for 766 00:32:11,940 --> 00:32:09,610 things auxilary to translation you know 767 00:32:16,680 --> 00:32:11,950 some protein quality control things like 768 00:32:18,660 --> 00:32:16,690 that darn yeah nice to talk I'm 769 00:32:19,560 --> 00:32:18,670 concerned about one thing and maybe you 770 00:32:21,690 --> 00:32:19,570 can help me out with this 771 00:32:24,810 --> 00:32:21,700 when phylogenetic people are making 772 00:32:26,640 --> 00:32:24,820 sequences some there are short branches 773 00:32:28,290 --> 00:32:26,650 and some of their long branches but 774 00:32:30,930 --> 00:32:28,300 there is no such thing as a branch that 775 00:32:33,690 --> 00:32:30,940 has zero length and it seems to me that 776 00:32:36,860 --> 00:32:33,700 if you're married to this accretion only 777 00:32:40,380 --> 00:32:36,870 model what you've done is put the e coli 778 00:32:42,990 --> 00:32:40,390 ribosome which as some at the bottom 779 00:32:46,620 --> 00:32:43,000 with zero length and then accreted only 780 00:32:47,880 --> 00:32:46,630 but it seems to me that it's I mean when 781 00:32:49,470 --> 00:32:47,890 you're doing phylogenetic analysis you 782 00:32:50,790 --> 00:32:49,480 have deletions and insertions and I 783 00:32:54,300 --> 00:32:50,800 think they weight them pretty much 784 00:32:56,220 --> 00:32:54,310 equally you have waited only insertions 785 00:33:00,750 --> 00:32:56,230 and said there are no deletions is that 786 00:33:05,670 --> 00:33:00,760 right no actually I and you know I used 787 00:33:07,650 --> 00:33:05,680 that es7 and I and I could and really I 788 00:33:10,380 --> 00:33:07,660 should say this clearly that that that 789 00:33:12,630 --> 00:33:10,390 the the best estimate for the universal 790 00:33:15,690 --> 00:33:12,640 common core is the prokaryotic ribosomes 791 00:33:18,600 --> 00:33:15,700 and in some places you have things that 792 00:33:21,120 --> 00:33:18,610 are added on in in bacteria and in other 793 00:33:23,070 --> 00:33:21,130 places in archaea and that and there are 794 00:33:24,990 --> 00:33:23,080 we can see that places there are 795 00:33:25,840 --> 00:33:25,000 deletions I kind of didn't point it out 796 00:33:27,510 --> 00:33:25,850 because I was 797 00:33:29,980 --> 00:33:27,520 well for example you showed the 798 00:33:32,230 --> 00:33:29,990 comparison between ecoli and the Archaea 799 00:33:35,020 --> 00:33:32,240 and I'm thinking why do you assume that 800 00:33:37,390 --> 00:33:35,030 the e.coli is more basic and then 801 00:33:38,890 --> 00:33:37,400 something to the Archaea maybe the 802 00:33:40,960 --> 00:33:38,900 e.coli lost something in the last four 803 00:33:45,400 --> 00:33:40,970 okay here's a here's an example of 804 00:33:47,740 --> 00:33:45,410 exactly that so this is in the small 805 00:33:50,530 --> 00:33:47,750 subunit but you see this blue ecoli has 806 00:33:53,230 --> 00:33:50,540 this and sorry this is thermus 807 00:33:54,700 --> 00:33:53,240 thermophilus and sorry anyway yeah these 808 00:33:56,530 --> 00:33:54,710 are both bacteria so I can't really show 809 00:33:58,930 --> 00:33:56,540 that here but yes we have places where 810 00:34:01,420 --> 00:33:58,940 things get added on and taken off I mean 811 00:34:06,550 --> 00:34:01,430 here you can see a place where thermos 812 00:34:08,860 --> 00:34:06,560 has thermos has loss or the common 813 00:34:10,300 --> 00:34:08,870 ancestor something got added onto e.coli 814 00:34:12,910 --> 00:34:10,310 but not thermos and then something got 815 00:34:14,560 --> 00:34:12,920 add onto thermos but not e.coli so you 816 00:34:19,000 --> 00:34:14,570 know things are getting added on and 817 00:34:20,980 --> 00:34:19,010 taken off and we have yeah you're right 818 00:34:23,560 --> 00:34:20,990 so e.coli is not at the bottom no new 819 00:34:25,600 --> 00:34:23,570 Kiko lies not the bottom it yeah I said 820 00:34:27,310 --> 00:34:25,610 I was just sort of speaking shorthand 821 00:34:29,020 --> 00:34:27,320 it's our approximate I was using it as 822 00:34:31,030 --> 00:34:29,030 an approximation for the bottom but I 823 00:34:36,550 --> 00:34:31,040 could have used hello I could have used 824 00:34:39,880 --> 00:34:36,560 archaea for that actually yeah very 825 00:34:42,910 --> 00:34:39,890 interesting do you think you can deduce 826 00:34:47,620 --> 00:34:42,920 which ii was the lifestyle of luke if 827 00:34:51,250 --> 00:34:47,630 thermophiles meso file secret file no I 828 00:34:54,970 --> 00:34:51,260 don't think so I mean it might be 829 00:34:58,170 --> 00:34:54,980 possible once we know more but you know 830 00:35:00,430 --> 00:34:58,180 I mean what we know about Luca really is 831 00:35:04,930 --> 00:35:00,440 really what we know is the translation 832 00:35:06,430 --> 00:35:04,940 system and and and you know people who 833 00:35:08,980 --> 00:35:06,440 are trying to do you know does it live 834 00:35:11,670 --> 00:35:08,990 in a vent or whatever like actually Sean 835 00:35:15,910 --> 00:35:11,680 talked about that paper I mean people 836 00:35:17,770 --> 00:35:15,920 are sometimes willing to kind of make 837 00:35:20,230 --> 00:35:17,780 assumptions about what Lucas is but when 838 00:35:22,120 --> 00:35:20,240 I see that happening it really seems to 839 00:35:24,010 --> 00:35:22,130 be model dependent like you know if 840 00:35:26,200 --> 00:35:24,020 somebody is a vent person they're gonna 841 00:35:28,600 --> 00:35:26,210 say Luke I lived in a vent I promise you 842 00:35:32,290 --> 00:35:28,610 this and if they're you know I mean that 843 00:35:33,520 --> 00:35:32,300 is just what is going to happen and you 844 00:35:35,650 --> 00:35:33,530 know I just think you got to be very 845 00:35:37,300 --> 00:35:35,660 careful and so that's why we use the 846 00:35:39,490 --> 00:35:37,310 universal gene set I mean that's data 847 00:35:41,110 --> 00:35:39,500 that's there's no we're 848 00:35:42,910 --> 00:35:41,120 trying to make any assumptions about 849 00:35:44,560 --> 00:35:42,920 what was there we're just saying these 850 00:35:47,380 --> 00:35:44,570 are the things if you take ribosomal 851 00:35:50,890 --> 00:35:47,390 protein l-3 from bacteria and you've 852 00:35:52,840 --> 00:35:50,900 searched in yet strangest archaea you 853 00:35:55,240 --> 00:35:52,850 can find you will find it right I mean 854 00:35:57,790 --> 00:35:55,250 this is just that's but people are very 855 00:36:00,670 --> 00:35:57,800 you know commonly trying to infer things 856 00:36:02,410 --> 00:36:00,680 about Luca and I when I look at the 857 00:36:04,720 --> 00:36:02,420 literature it just seems like it they 858 00:36:10,240 --> 00:36:04,730 always get the answer they want so I'm 859 00:36:12,340 --> 00:36:10,250 very suspicious of those things science 860 00:36:15,940 --> 00:36:12,350 a great luck for molecular symbiosis and 861 00:36:19,120 --> 00:36:15,950 I have a question for ability nope short 862 00:36:21,130 --> 00:36:19,130 peptide of ribosomal proteins okay so 863 00:36:24,070 --> 00:36:21,140 before interaction in what are they have 864 00:36:26,230 --> 00:36:24,080 to be distributed in severe form so have 865 00:36:27,970 --> 00:36:26,240 you checked that sort of peptide or so 866 00:36:33,490 --> 00:36:27,980 the peptide process with two beta 867 00:36:35,650 --> 00:36:33,500 strands okay 868 00:36:37,780 --> 00:36:35,660 we actually we've made these peptides 869 00:36:40,660 --> 00:36:37,790 and they're soluble so we actually are 870 00:36:42,700 --> 00:36:40,670 studying the chaperoning of the peptide 871 00:36:46,270 --> 00:36:42,710 folding by RNA they're the peptides are 872 00:36:52,240 --> 00:36:46,280 soluble oh if you can such the secrets 873 00:36:54,370 --> 00:36:52,250 you can estimate the solubility these 874 00:36:56,110 --> 00:36:54,380 are soluble peptides because remember 875 00:36:58,420 --> 00:36:56,120 they're living in a sea of RNA and 876 00:37:01,030 --> 00:36:58,430 they're very highly charged they have a 877 00:37:02,920 --> 00:37:01,040 lottery but in the case of a peptide or 878 00:37:04,960 --> 00:37:02,930 in general peptide yeah okay so our 879 00:37:08,320 --> 00:37:04,970 model for the ribosome is the ribosome 880 00:37:10,570 --> 00:37:08,330 early on was doing nonspecific it was 881 00:37:13,300 --> 00:37:10,580 making and I don't I mean really 882 00:37:14,950 --> 00:37:13,310 nonspecific I mean esters you can make 883 00:37:16,600 --> 00:37:14,960 polyester with the ribosome it doesn't 884 00:37:21,100 --> 00:37:16,610 character so I think that the ribosome 885 00:37:23,980 --> 00:37:21,110 was making rasa mates of ester peptide 886 00:37:25,540 --> 00:37:23,990 it was and some small fraction of what 887 00:37:27,940 --> 00:37:25,550 it was making and it could have been a 888 00:37:29,380 --> 00:37:27,950 very small fraction because there wasn't 889 00:37:31,810 --> 00:37:29,390 a lot of competition in those days right 890 00:37:34,330 --> 00:37:31,820 we're talking about some small fraction 891 00:37:36,550 --> 00:37:34,340 stuck and conferred advantage right if 892 00:37:39,070 --> 00:37:36,560 most of it was insoluble or did nothing 893 00:37:40,780 --> 00:37:39,080 really didn't matter it's a if some 894 00:37:42,610 --> 00:37:40,790 small fraction stuck and conferred 895 00:37:44,290 --> 00:37:42,620 advantage and allowed the ribosome to 896 00:37:46,030 --> 00:37:44,300 fold better and function better and be 897 00:37:48,160 --> 00:37:46,040 more stable or whatever the Selective 898 00:37:51,850 --> 00:37:48,170 pressure was we don't really know but 899 00:37:53,410 --> 00:37:51,860 then then that would lock it in and and 900 00:37:55,150 --> 00:37:53,420 actually we believe 901 00:37:57,069 --> 00:37:55,160 that peptides got longer and the 902 00:37:58,660 --> 00:37:57,079 ribosomal RNA got bigger and that this 903 00:38:01,420 --> 00:37:58,670 was a kind of a bootstrapping process 904 00:38:02,980 --> 00:38:01,430 that cycled in on each other I didn't 905 00:38:05,140 --> 00:38:02,990 talk about the tunnel but we can really 906 00:38:06,520 --> 00:38:05,150 see we can infer sort of what was 907 00:38:08,319 --> 00:38:06,530 happening with the peptides by the 908 00:38:10,930 --> 00:38:08,329 length of the tunnel and it's it's 909 00:38:13,720 --> 00:38:10,940 pretty clear that there was a sort of a 910 00:38:17,410 --> 00:38:13,730 cyclic process peptides got bigger the 911 00:38:23,890 --> 00:38:17,420 ribosome got bigger okay I'm sorry but 912 00:38:27,819 --> 00:38:23,900 I'm I'm too long-winded to two questions 913 00:38:29,380 --> 00:38:27,829 learned one is is there any possibility 914 00:38:32,680 --> 00:38:29,390 of you play with the idea that instead 915 00:38:34,750 --> 00:38:32,690 of the the helix 25 being the ancestral 916 00:38:37,510 --> 00:38:34,760 state that since bacteria reduced in 917 00:38:40,630 --> 00:38:37,520 many ways that that entire arc eel bit 918 00:38:43,329 --> 00:38:40,640 is the primitive local legal for want of 919 00:38:46,030 --> 00:38:43,339 a better word state and that there was a 920 00:38:48,490 --> 00:38:46,040 loss of that upper part and the other 921 00:38:50,799 --> 00:38:48,500 question is have you thought at all 922 00:38:52,359 --> 00:38:50,809 about whether non ribosomal protein 923 00:38:56,680 --> 00:38:52,369 synthesis could have been earlier or 924 00:38:58,240 --> 00:38:56,690 later okay first about yeah I mean we we 925 00:39:01,359 --> 00:38:58,250 sort of are using the assumption that 926 00:39:03,730 --> 00:39:01,369 things that are common are that our best 927 00:39:05,109 --> 00:39:03,740 representation of the ancestor but it's 928 00:39:08,319 --> 00:39:05,119 not necessarily true 929 00:39:10,750 --> 00:39:08,329 so yeah yes you know we really can't 930 00:39:14,440 --> 00:39:10,760 exclude that that longer helix was 931 00:39:17,250 --> 00:39:14,450 ancestral we can't okay now the next 932 00:39:20,530 --> 00:39:17,260 what was the next question 933 00:39:22,750 --> 00:39:20,540 non ribosomal protein synthesis preceded 934 00:39:24,309 --> 00:39:22,760 the ribosome so that you could have well 935 00:39:26,440 --> 00:39:24,319 I guess I guess it depends on what you 936 00:39:28,270 --> 00:39:26,450 mean by non-ribosomal I do believe that 937 00:39:30,010 --> 00:39:28,280 peptides were being synthesized abiotic 938 00:39:32,170 --> 00:39:30,020 ly before the ribosome in fact I think 939 00:39:34,660 --> 00:39:32,180 all the ribosome did was help what was 940 00:39:36,069 --> 00:39:34,670 going on there and I think that possibly 941 00:39:38,200 --> 00:39:36,079 the original function of the ribosome 942 00:39:40,660 --> 00:39:38,210 was just to keep the two ends apart 943 00:39:42,970 --> 00:39:40,670 because and stop the siccolas ation that 944 00:39:44,920 --> 00:39:42,980 kills your polymerization so really all 945 00:39:47,559 --> 00:39:44,930 the ribosome it looks like in the very 946 00:39:50,140 --> 00:39:47,569 early part of the ribosome it was just a 947 00:39:52,299 --> 00:39:50,150 device where two amino acids could bind 948 00:39:54,640 --> 00:39:52,309 and they could cycle eyes and that ends 949 00:39:56,620 --> 00:39:54,650 were not allowed to come together so in 950 00:39:58,329 --> 00:39:56,630 that sense yes there was peptide 951 00:40:02,020 --> 00:39:58,339 synthesis going on before the ribosomes 952 00:40:03,700 --> 00:40:02,030 but you mean biological you know like or 953 00:40:05,410 --> 00:40:03,710 that still occurs I would have a hard 954 00:40:07,220 --> 00:40:05,420 time with that because that requires 955 00:40:08,870 --> 00:40:07,230 complex coded proteins 956 00:40:12,859 --> 00:40:08,880 and I can't imagine where they came from 957 00:40:15,109 --> 00:40:12,869 so yeah I'm not big on that model that 958 00:40:17,000 --> 00:40:15,119 there was that there were intact 959 00:40:20,599 --> 00:40:17,010 functional proteins before the ribosome 960 00:40:25,910 --> 00:40:20,609 I I don't know I I think that's a 961 00:40:27,470 --> 00:40:25,920 difficult model hey Lauren thanks to the 962 00:40:29,690 --> 00:40:27,480 nice talk 963 00:40:32,030 --> 00:40:29,700 I was wondering just how you 964 00:40:34,670 --> 00:40:32,040 conceptualize the gradual buildup of the 965 00:40:36,200 --> 00:40:34,680 ribosome in general there's these 966 00:40:38,180 --> 00:40:36,210 different kind of hierarchical levels 967 00:40:40,640 --> 00:40:38,190 that it seems like this progressive 968 00:40:45,430 --> 00:40:40,650 addition of subunits has occurred so you 969 00:40:47,480 --> 00:40:45,440 showed the cool squiggly green peptides 970 00:40:49,280 --> 00:40:47,490 gradually accumulating secondary 971 00:40:51,560 --> 00:40:49,290 structure and then looks like there's 972 00:40:54,109 --> 00:40:51,570 some tertiary structure coming in and so 973 00:40:55,700 --> 00:40:54,119 I don't there's not any ribosomes today 974 00:40:57,740 --> 00:40:55,710 that only have the green bit is that 975 00:41:00,380 --> 00:40:57,750 right that's correct okay right and so 976 00:41:01,970 --> 00:41:00,390 as that happens and in addition to that 977 00:41:03,620 --> 00:41:01,980 at the same time presumably there's all 978 00:41:05,810 --> 00:41:03,630 these different ribosomal subunits that 979 00:41:07,400 --> 00:41:05,820 are being tacked onto the side and and 980 00:41:10,070 --> 00:41:07,410 so we see all these different subunits 981 00:41:12,440 --> 00:41:10,080 in archaea versus bacteria versus 982 00:41:13,609 --> 00:41:12,450 eukaryotes so would it what's driving 983 00:41:15,890 --> 00:41:13,619 that and what is the functional 984 00:41:19,250 --> 00:41:15,900 consequence of that do you think okay 985 00:41:21,170 --> 00:41:19,260 well what we think is happening is that 986 00:41:23,810 --> 00:41:21,180 you have this core and small things were 987 00:41:25,700 --> 00:41:23,820 added on you know and and it kind of 988 00:41:28,220 --> 00:41:25,710 grew by the addition of small elements 989 00:41:31,550 --> 00:41:28,230 and small peptides small pieces of RNA 990 00:41:33,470 --> 00:41:31,560 and that grew in that way and we think 991 00:41:36,140 --> 00:41:33,480 there was a diverse population in fact 992 00:41:38,930 --> 00:41:36,150 that and we're maybe not talking about 993 00:41:40,700 --> 00:41:38,940 this the the origins of the ribosome we 994 00:41:42,410 --> 00:41:40,710 believe could have been before RNA the 995 00:41:44,300 --> 00:41:42,420 ancestor of the ribosome was not 996 00:41:48,200 --> 00:41:44,310 necessarily made of RNA it could have 997 00:41:50,240 --> 00:41:48,210 been an ancestral molecule in the and 998 00:41:52,099 --> 00:41:50,250 that product of the ribosome was not 999 00:41:54,620 --> 00:41:52,109 necessarily protein in fact we're pretty 1000 00:41:57,170 --> 00:41:54,630 sure it was not broken it was it was 1001 00:42:00,710 --> 00:41:57,180 peptide I mean it was esters and things 1002 00:42:02,359 --> 00:42:00,720 like that and I'm not answering your 1003 00:42:04,130 --> 00:42:02,369 question though so what tell me your 1004 00:42:06,349 --> 00:42:04,140 question again it's just something that 1005 00:42:08,450 --> 00:42:06,359 I wonder about when I look at all these 1006 00:42:10,190 --> 00:42:08,460 different ribosomal subunits you can 1007 00:42:11,390 --> 00:42:10,200 draw a Venn diagram and find that 1008 00:42:14,210 --> 00:42:11,400 there's all these different ones in 1009 00:42:16,280 --> 00:42:14,220 archaea and bacteria okay ribosomal 1010 00:42:17,599 --> 00:42:16,290 subunits in but too bright but this is a 1011 00:42:19,440 --> 00:42:17,609 different hierarchical level but it's 1012 00:42:21,090 --> 00:42:19,450 really in parallel to 1013 00:42:23,160 --> 00:42:21,100 you presented in that way and that table 1014 00:42:25,260 --> 00:42:23,170 of the green yellow and okay but the 1015 00:42:26,790 --> 00:42:25,270 ribosomal subunits are the same in 1016 00:42:28,860 --> 00:42:26,800 bacteria and archaea that's what I'm 1017 00:42:30,510 --> 00:42:28,870 getting confused by your crab but some 1018 00:42:32,520 --> 00:42:30,520 of them are different like bacteria have 1019 00:42:37,640 --> 00:42:32,530 different ones than archaea ones 1020 00:42:41,760 --> 00:42:37,650 different from eukaryote right no again 1021 00:42:43,140 --> 00:42:41,770 the ribosome has accreted yeah I'm not 1022 00:42:45,480 --> 00:42:43,150 I'm not understanding your question 1023 00:42:48,600 --> 00:42:45,490 there's no there's no different subunits 1024 00:42:51,360 --> 00:42:48,610 in archaea and vs. bacteria on the 1025 00:42:53,310 --> 00:42:51,370 periphery there is okay yes there's not 1026 00:42:54,570 --> 00:42:53,320 like how many ribosomal yeah okay 1027 00:42:56,040 --> 00:42:54,580 there's things added oh yeah we don't 1028 00:42:56,820 --> 00:42:56,050 call those subunits so some confused 1029 00:42:59,070 --> 00:42:56,830 yeah okay 1030 00:43:00,270 --> 00:42:59,080 there's expansion segments that's what 1031 00:43:01,890 --> 00:43:00,280 that's what you're talking about that 1032 00:43:03,450 --> 00:43:01,900 that are added onto the surface of the 1033 00:43:05,550 --> 00:43:03,460 ribosome we'll have to draw this out 1034 00:43:08,580 --> 00:43:05,560 later but if there's time I'll squeaking 1035 00:43:14,280 --> 00:43:08,590 another question okay so if I take that 1036 00:43:16,440 --> 00:43:14,290 common gene set and I and I throw that 1037 00:43:19,290 --> 00:43:16,450 in a tube what does it do and what can 1038 00:43:21,360 --> 00:43:19,300 that tell us about there Oh first life 1039 00:43:23,820 --> 00:43:21,370 if you take that common genes out you 1040 00:43:26,900 --> 00:43:23,830 can probably and a little bit other 1041 00:43:30,540 --> 00:43:26,910 stuff you could do in vitro translation 1042 00:43:34,430 --> 00:43:30,550 so that tells you I don't know you can 1043 00:43:37,800 --> 00:43:34,440 interpret that how you want but the way 1044 00:43:39,450 --> 00:43:37,810 but I think you can't ignore it right if 1045 00:43:43,050 --> 00:43:39,460 you have a model of the origin of life 1046 00:43:45,570 --> 00:43:43,060 that does not account for the extreme 1047 00:43:48,750 --> 00:43:45,580 conservation of the translation system 1048 00:43:51,060 --> 00:43:48,760 and the fact that that Luca had a 1049 00:43:53,460 --> 00:43:51,070 translation system that is untouchable 1050 00:43:54,930 --> 00:43:53,470 essentially by evolution and if you want 1051 00:43:56,580 --> 00:43:54,940 to take your next step back and say 1052 00:43:58,350 --> 00:43:56,590 there was no translation system and 1053 00:44:00,000 --> 00:43:58,360 there was a different biology then 1054 00:44:02,850 --> 00:44:00,010 that's what I find very difficult 1055 00:44:05,460 --> 00:44:02,860 because post luca the translation system 1056 00:44:07,800 --> 00:44:05,470 is the most permanent system in the 1057 00:44:10,350 --> 00:44:07,810 known universe and if you you know if 1058 00:44:12,390 --> 00:44:10,360 your evolutionary model goes a half a 1059 00:44:15,660 --> 00:44:12,400 step backwards and abolish as it totally 1060 00:44:18,510 --> 00:44:15,670 i have a problem with that as in the RNA 1061 00:44:20,250 --> 00:44:18,520 world for example right so the RNA world 1062 00:44:23,820 --> 00:44:20,260 says there was no translation system 1063 00:44:26,580 --> 00:44:23,830 biology matured and then a translation 1064 00:44:28,380 --> 00:44:26,590 system was invented that suddenly became 1065 00:44:31,560 --> 00:44:28,390 so important it could not it's 1066 00:44:32,650 --> 00:44:31,570 untouchable and that just seems kind of 1067 00:44:34,900 --> 00:44:32,660 incredible to me 1068 00:44:36,579 --> 00:44:34,910 I think this this this permanence and 1069 00:44:38,529 --> 00:44:36,589 the resilience and the robustness of the 1070 00:44:40,630 --> 00:44:38,539 translation system you've got to take it 1071 00:44:43,720 --> 00:44:40,640 back to the beginning you've got to say 1072 00:44:46,960 --> 00:44:43,730 that was built in but that's sort of to 1073 00:44:48,250 --> 00:44:46,970 me that's the simplest model well I 1074 00:44:50,289 --> 00:44:48,260 think you'll agree that this was a 1075 00:44:51,430 --> 00:44:50,299 fascinating talk so let's thank Laurie 1076 00:44:53,800 --> 00:44:51,440 thank you guys again 1077 00:45:06,480 --> 00:44:53,810 [Applause]