1 00:00:00,260 --> 00:00:12,670 [Music] 2 00:00:16,970 --> 00:00:15,080 where's Michael Morrison I'm kind of 3 00:00:19,040 --> 00:00:16,980 gonna go back to it doctor to Lucas was 4 00:00:21,680 --> 00:00:19,050 kind of talking about at lunch with 5 00:00:24,770 --> 00:00:21,690 doing experiments that we kind of do on 6 00:00:27,500 --> 00:00:24,780 the ground but in a low orbit 7 00:00:29,210 --> 00:00:27,510 environment to kind of see how this 8 00:00:30,650 --> 00:00:29,220 microgravity environment affects what 9 00:00:32,540 --> 00:00:30,660 we're doing however instead of doing 10 00:00:35,330 --> 00:00:32,550 protein crystals I'm actually looking at 11 00:00:37,250 --> 00:00:35,340 how bacteria grow and adapt in this 12 00:00:40,430 --> 00:00:37,260 unique environment that can't be found 13 00:00:43,370 --> 00:00:40,440 on earth I'm instead of some background 14 00:00:45,200 --> 00:00:43,380 on how life adapts to space probably the 15 00:00:48,530 --> 00:00:45,210 best studied organism that we know of 16 00:00:50,000 --> 00:00:48,540 for her space are humans we've had a 17 00:00:52,819 --> 00:00:50,010 continuous presence in space for the 18 00:00:54,050 --> 00:00:52,829 last 70 and a half years and that's just 19 00:00:55,550 --> 00:00:54,060 if you consider the International Space 20 00:00:58,970 --> 00:00:55,560 Station before that there was a Space 21 00:01:00,470 --> 00:00:58,980 Station mer Skylab Apollo Vostok and so 22 00:01:02,780 --> 00:01:00,480 we've had about sixty years of studying 23 00:01:04,579 --> 00:01:02,790 how humans adapt to spaceflight and what 24 00:01:06,590 --> 00:01:04,589 we found as he pointed out was that 25 00:01:08,810 --> 00:01:06,600 astronauts lose bone density and muscle 26 00:01:10,910 --> 00:01:08,820 mass in space but they also experience 27 00:01:13,190 --> 00:01:10,920 this fluid redistribution because we've 28 00:01:15,710 --> 00:01:13,200 evolved with gravity constantly pulling 29 00:01:17,750 --> 00:01:15,720 down on our bodies so we have mechanisms 30 00:01:19,370 --> 00:01:17,760 mechanisms in our bodies to help push 31 00:01:21,830 --> 00:01:19,380 this fluid back up to kind of keep our 32 00:01:24,920 --> 00:01:21,840 blood circulating and everything kind of 33 00:01:27,920 --> 00:01:24,930 working in a nice harmonious manner and 34 00:01:29,180 --> 00:01:27,930 this dysregulation we are fluids when 35 00:01:30,380 --> 00:01:29,190 you get into space because gravity is no 36 00:01:32,750 --> 00:01:30,390 longer pointing down you can stress the 37 00:01:34,460 --> 00:01:32,760 body out which can cause this regulation 38 00:01:36,260 --> 00:01:34,470 of the immune system which has been seen 39 00:01:37,880 --> 00:01:36,270 in astronauts coming back from space as 40 00:01:41,179 --> 00:01:37,890 flare-ups of different dormant viruses 41 00:01:43,490 --> 00:01:41,189 such as epstein-barr and herpes and 42 00:01:45,980 --> 00:01:43,500 these astronauts we send up there are 43 00:01:48,560 --> 00:01:45,990 you know very active healthy individuals 44 00:01:54,800 --> 00:01:48,570 that we send up there for example right 45 00:01:57,649 --> 00:01:54,810 this photo right here is of this Oh what 46 00:02:00,410 --> 00:01:57,659 is it click okay well little the top 47 00:02:02,870 --> 00:02:00,420 button okay so this is a astronaut tim 48 00:02:05,539 --> 00:02:02,880 peake and this photo he was competing in 49 00:02:07,700 --> 00:02:05,549 the London Marathon where he actually 50 00:02:11,179 --> 00:02:07,710 set the record for the fastest off world 51 00:02:14,210 --> 00:02:11,189 marathon time at 3 at 3 hours and 35 52 00:02:16,100 --> 00:02:14,220 minutes and 12 seconds and so if we're 53 00:02:18,110 --> 00:02:16,110 you know seeing these effects and 54 00:02:21,020 --> 00:02:18,120 astronauts who are really physically fit 55 00:02:23,150 --> 00:02:21,030 what would we see in it were humans 56 00:02:27,199 --> 00:02:23,160 myself who a marathon would probably 57 00:02:29,090 --> 00:02:27,209 kill so this is kind of astronauts kind 58 00:02:31,460 --> 00:02:29,100 of idea but you know these are macro you 59 00:02:33,710 --> 00:02:31,470 know big organisms my focus is more on 60 00:02:35,270 --> 00:02:33,720 the prokaryotes because we see keep 61 00:02:36,530 --> 00:02:35,280 sending humans to space but prokaryotes 62 00:02:38,150 --> 00:02:36,540 go with us everywhere we go they're 63 00:02:40,580 --> 00:02:38,160 central for our immune system our 64 00:02:42,410 --> 00:02:40,590 digestion and does it affect these 65 00:02:45,050 --> 00:02:42,420 prokaryotes and it actually does what 66 00:02:46,910 --> 00:02:45,060 we've observed is that prokaryotes have 67 00:02:48,620 --> 00:02:46,920 faster growth rates in space and it can 68 00:02:51,050 --> 00:02:48,630 reach fine cell density higher final 69 00:02:53,240 --> 00:02:51,060 cell densities they some experiments 70 00:02:55,100 --> 00:02:53,250 also suggest that antibiotic resistance 71 00:02:57,350 --> 00:02:55,110 increases in space as well as appearance 72 00:02:59,600 --> 00:02:57,360 and there's not things you want if the 73 00:03:01,850 --> 00:02:59,610 immune system becomes dysregulated big 74 00:03:04,009 --> 00:03:01,860 concern for NASA for sending astronauts 75 00:03:05,720 --> 00:03:04,019 past low-earth orbit because if you send 76 00:03:07,160 --> 00:03:05,730 them out there they're halfway to Mars 77 00:03:09,170 --> 00:03:07,170 they get sick you can't bring them back 78 00:03:11,570 --> 00:03:09,180 you said we have to figure this out kind 79 00:03:13,490 --> 00:03:11,580 of thing and last what they what kind of 80 00:03:16,250 --> 00:03:13,500 prokaryotes is this alteration and 81 00:03:18,559 --> 00:03:16,260 biofilm formation biofilms do have some 82 00:03:20,930 --> 00:03:18,569 role in chronic infections and 83 00:03:23,090 --> 00:03:20,940 antibiotic resistance but NASA's noticed 84 00:03:24,979 --> 00:03:23,100 that they affect the systems on the 85 00:03:26,870 --> 00:03:24,989 space station as well such as the space 86 00:03:28,759 --> 00:03:26,880 station mer it actually clogged the 87 00:03:29,990 --> 00:03:28,769 water reclaiming system with a biofilm 88 00:03:32,330 --> 00:03:30,000 and they had it completely read change 89 00:03:34,370 --> 00:03:32,340 out the entire system and also they find 90 00:03:36,830 --> 00:03:34,380 biofilms on the surface of this capsules 91 00:03:37,910 --> 00:03:36,840 which can actually corrode material and 92 00:03:39,740 --> 00:03:37,920 that's not something you want again 93 00:03:41,690 --> 00:03:39,750 pathway to space all sudden your machine 94 00:03:42,199 --> 00:03:41,700 you're starting to corrode what you can 95 00:03:44,449 --> 00:03:42,209 do about it 96 00:03:45,979 --> 00:03:44,459 so this is something that NASA is very 97 00:03:47,509 --> 00:03:45,989 interested in and that's kind of what my 98 00:03:49,520 --> 00:03:47,519 lab wants to look into kind of figuring 99 00:03:53,000 --> 00:03:49,530 out what's going on here and some kind 100 00:03:58,160 --> 00:03:53,010 of molecular like responses we can kind 101 00:03:59,539 --> 00:03:58,170 of predict and kind of treat so as the 102 00:04:01,430 --> 00:03:59,549 Lucas kind of point out spaceflight 103 00:04:03,440 --> 00:04:01,440 hardware is important so for us we use 104 00:04:05,569 --> 00:04:03,450 the biological research in canisters or 105 00:04:07,729 --> 00:04:05,579 brick space flight hardware they contain 106 00:04:10,370 --> 00:04:07,739 the petri dish that we air deposited 107 00:04:12,259 --> 00:04:10,380 vasila settler spores which are a soil 108 00:04:14,660 --> 00:04:12,269 bacteria that are non pathogenic know 109 00:04:16,670 --> 00:04:14,670 which astronauts whatsoever and the 110 00:04:18,920 --> 00:04:16,680 spores are dormant and so when we send 111 00:04:20,930 --> 00:04:18,930 them up we can inject media into them 112 00:04:22,640 --> 00:04:20,940 they become you know viable growing 113 00:04:24,350 --> 00:04:22,650 cells and so we can affect of what they 114 00:04:26,450 --> 00:04:24,360 do just in space without having to worry 115 00:04:27,800 --> 00:04:26,460 about the launch and the return and down 116 00:04:29,510 --> 00:04:27,810 here there's an actual chamber for the 117 00:04:31,940 --> 00:04:29,520 media that can be stored in until we're 118 00:04:34,759 --> 00:04:31,950 ready to inoculate the petri dish and we 119 00:04:37,939 --> 00:04:34,769 used a rich media TS 120 00:04:39,949 --> 00:04:37,949 that has protein and glucose as carbon 121 00:04:41,029 --> 00:04:39,959 sources as well as about twenty ten 122 00:04:42,889 --> 00:04:41,039 percent glycerol so we could actually 123 00:04:44,749 --> 00:04:42,899 freeze our samples and bring them back 124 00:04:47,359 --> 00:04:44,759 to earth and they would still be in this 125 00:04:48,739 --> 00:04:47,369 kind of state of hey we're still in 126 00:04:51,769 --> 00:04:48,749 space even though they're on the ground 127 00:04:53,509 --> 00:04:51,779 white when we follow them and so the 128 00:04:55,219 --> 00:04:53,519 actual timeline for our mission which 129 00:04:59,209 --> 00:04:55,229 became known as Brook 21 because it was 130 00:05:02,479 --> 00:04:59,219 the 21st brick mission launched in April 131 00:05:04,429 --> 00:05:02,489 2015 dr. the National Space Station they 132 00:05:08,119 --> 00:05:04,439 inoculated the samples in space right 133 00:05:09,499 --> 00:05:08,129 here and they roiled to grow at ambient 134 00:05:12,229 --> 00:05:09,509 space station temperature approximately 135 00:05:13,819 --> 00:05:12,239 23 degrees Celsius for about 25 hours 136 00:05:16,609 --> 00:05:13,829 after which they were frozen in minus 80 137 00:05:18,529 --> 00:05:16,619 degrees and shipped back to earth where 138 00:05:19,579 --> 00:05:18,539 you know me and my lab were able to get 139 00:05:22,549 --> 00:05:19,589 our hands on and I saw actually 140 00:05:24,169 --> 00:05:22,559 processing the samples and because space 141 00:05:24,469 --> 00:05:24,179 is limited we wanted to do a lot with a 142 00:05:26,989 --> 00:05:24,479 little 143 00:05:28,819 --> 00:05:26,999 and so this is kind of everything we 144 00:05:29,749 --> 00:05:28,829 wanted to do with them and you can kind 145 00:05:31,399 --> 00:05:29,759 of see we've kind of looked at the 146 00:05:32,600 --> 00:05:31,409 antibiotic profiles and the mutation 147 00:05:34,549 --> 00:05:32,610 rates and everything I'm going to focus 148 00:05:37,129 --> 00:05:34,559 mostly on the transcriptome how they're 149 00:05:39,499 --> 00:05:37,139 actually adapting today but I guess it's 150 00:05:40,909 --> 00:05:39,509 a little late but Josh Lee had a student 151 00:05:41,689 --> 00:05:40,919 in our lab was actually giving a poster 152 00:05:43,339 --> 00:05:41,699 on this yesterday 153 00:05:45,139 --> 00:05:43,349 pretty sure if you still are interested 154 00:05:46,819 --> 00:05:45,149 in that Josh Ling Han would be happy to 155 00:05:47,929 --> 00:05:46,829 talk to you about mutation frequencies 156 00:05:50,119 --> 00:05:47,939 in space so they're my little plug for 157 00:05:52,189 --> 00:05:50,129 him but from here on I'm mostly talking 158 00:05:56,839 --> 00:05:52,199 about the transcriptome and how the gene 159 00:05:59,719 --> 00:05:56,849 expression is affected by space so how 160 00:06:01,819 --> 00:05:59,729 do we do transcriptomics we get the 161 00:06:03,559 --> 00:06:01,829 samples back they're frozen we thaw them 162 00:06:05,569 --> 00:06:03,569 in the lab and we immediately extract 163 00:06:09,679 --> 00:06:05,579 the RNA so we have all the RNA that was 164 00:06:11,419 --> 00:06:09,689 up in space before it's degraded as well 165 00:06:13,309 --> 00:06:11,429 as the ground samples that we flew are 166 00:06:14,719 --> 00:06:13,319 that we didn't fly that we're sitting at 167 00:06:17,509 --> 00:06:14,729 NASA while the ground all the 168 00:06:19,609 --> 00:06:17,519 spaceflight samples were flying and we 169 00:06:21,229 --> 00:06:19,619 then sequenced that RNA to get it you 170 00:06:22,939 --> 00:06:21,239 know figure out what the actual code is 171 00:06:26,089 --> 00:06:22,949 and then we can do differential 172 00:06:28,159 --> 00:06:26,099 expression analysis on those sequences 173 00:06:30,679 --> 00:06:28,169 so differential expression analysis I 174 00:06:31,999 --> 00:06:30,689 take the reads and I filter them for 175 00:06:33,499 --> 00:06:32,009 quality making sure that you know we 176 00:06:35,569 --> 00:06:33,509 actually have good reads or reads aren't 177 00:06:36,919 --> 00:06:35,579 you know messed up or anything and then 178 00:06:38,899 --> 00:06:36,929 I line them to the genome and every 179 00:06:41,389 --> 00:06:38,909 single sample we had had about 50 180 00:06:43,909 --> 00:06:41,399 million reads per sample and we had in 181 00:06:46,670 --> 00:06:43,919 equals 3 for Brick 21 so that's total of 182 00:06:47,790 --> 00:06:46,680 6 samples 3 per condition and we use a 183 00:06:49,170 --> 00:06:47,800 machine to do this because I 184 00:06:51,809 --> 00:06:49,180 you want to graduate eventually and not 185 00:06:54,149 --> 00:06:51,819 have film and then once we align them to 186 00:06:55,860 --> 00:06:54,159 the genome we count how many sequences 187 00:06:57,839 --> 00:06:55,870 are there for every single gene so we 188 00:06:59,640 --> 00:06:57,849 can get kind of a quantitative number of 189 00:07:01,379 --> 00:06:59,650 how much was this gene being expressed 190 00:07:03,570 --> 00:07:01,389 in space compare and you know compared 191 00:07:05,580 --> 00:07:03,580 to on the ground and then we statistics 192 00:07:09,809 --> 00:07:05,590 we use actually two packages Lima into 193 00:07:12,300 --> 00:07:09,819 ec2 to determine if it's you know higher 194 00:07:13,260 --> 00:07:12,310 or lower in space compared to ground in 195 00:07:14,820 --> 00:07:13,270 order for a gene to be consider 196 00:07:16,439 --> 00:07:14,830 differentially expressed it had to have 197 00:07:17,909 --> 00:07:16,449 at least a two-fold change in the number 198 00:07:20,580 --> 00:07:17,919 of counts and between flight and ground 199 00:07:21,719 --> 00:07:20,590 with a p-value of point zero one and 200 00:07:24,180 --> 00:07:21,729 since we were looking about four 201 00:07:25,709 --> 00:07:24,190 thousand four hundred transcripts we did 202 00:07:27,300 --> 00:07:25,719 correct from local testing bias using 203 00:07:29,670 --> 00:07:27,310 Benjamin Hochberg and all that stuff and 204 00:07:31,050 --> 00:07:29,680 so we're pretty confident with our you 205 00:07:32,399 --> 00:07:31,060 know genes we get and then we do 206 00:07:33,749 --> 00:07:32,409 functional analysis to kind of figure 207 00:07:35,640 --> 00:07:33,759 out what are those genes actually doing 208 00:07:37,770 --> 00:07:35,650 and do they kind of group into different 209 00:07:41,339 --> 00:07:37,780 pathways so we can kind of try to target 210 00:07:44,490 --> 00:07:41,349 pathways not just individual genes so we 211 00:07:45,540 --> 00:07:44,500 did this on Brick 21 and we found 293 212 00:07:47,640 --> 00:07:45,550 genes that were differentially expressed 213 00:07:49,920 --> 00:07:47,650 between flight and ground so there's 214 00:07:52,379 --> 00:07:49,930 about 177 that were higher in space 215 00:07:55,019 --> 00:07:52,389 flight and about 116 that were higher in 216 00:07:56,339 --> 00:07:55,029 the ground samples and from this we did 217 00:07:57,959 --> 00:07:56,349 you know our functional annotation try 218 00:07:59,700 --> 00:07:57,969 figure out what was going on and we 219 00:08:01,890 --> 00:07:59,710 found about 10 enriched KEGG pathways 220 00:08:03,689 --> 00:08:01,900 KEGG pathways are just kind of submitted 221 00:08:05,600 --> 00:08:03,699 but pathways such as biotin metabolism 222 00:08:07,890 --> 00:08:05,610 arginine we actually had a couple of 223 00:08:09,899 --> 00:08:07,900 non-ribosomal peptide biosynthesis 224 00:08:11,610 --> 00:08:09,909 pathways going on and it's an actually 225 00:08:14,670 --> 00:08:11,620 metabolism just to kinda name a few but 226 00:08:16,980 --> 00:08:14,680 while we were analyzing this data nasa 227 00:08:18,689 --> 00:08:16,990 was generous enough to let our lab kind 228 00:08:20,339 --> 00:08:18,699 of participate on a second space flight 229 00:08:22,499 --> 00:08:20,349 experiment which became those brook 23 230 00:08:24,540 --> 00:08:22,509 where we flew the exact same hardware 231 00:08:26,730 --> 00:08:24,550 exact same strain exact same media and 232 00:08:29,730 --> 00:08:26,740 this was very important because to this 233 00:08:32,430 --> 00:08:29,740 point no transcriptome for bacteria has 234 00:08:33,750 --> 00:08:32,440 ever been duplicated in space so this 235 00:08:35,639 --> 00:08:33,760 was kind of a nice idea to say can we 236 00:08:36,990 --> 00:08:35,649 see the same results if we duplicate the 237 00:08:41,389 --> 00:08:37,000 sensation of the gold standard of 238 00:08:44,130 --> 00:08:41,399 science and however adhering the kind of 239 00:08:46,500 --> 00:08:44,140 development and planning stage instead 240 00:08:48,240 --> 00:08:46,510 of rowing it for 20-25 hours we they 241 00:08:49,350 --> 00:08:48,250 grew these for 26 hours that's the only 242 00:08:52,410 --> 00:08:49,360 difference between these two we actually 243 00:08:53,579 --> 00:08:52,420 wanted to look at stationary phase which 244 00:08:55,500 --> 00:08:53,589 the first one for an exponential phase 245 00:08:57,329 --> 00:08:55,510 to kind of see like differences in fit 246 00:09:00,180 --> 00:08:57,339 growth phases but if there's an effect 247 00:09:01,540 --> 00:09:00,190 by spaceflight we should still see genes 248 00:09:03,550 --> 00:09:01,550 up regardless of what 249 00:09:05,769 --> 00:09:03,560 Faye's it's in so can we kind of use 250 00:09:07,509 --> 00:09:05,779 these two different phases to pull out 251 00:09:11,800 --> 00:09:07,519 genes that spaceflight effects 252 00:09:15,040 --> 00:09:11,810 continuously and so these flew about a 253 00:09:16,720 --> 00:09:15,050 year after the first ones and then so we 254 00:09:18,370 --> 00:09:16,730 did you know transcriptome profiling the 255 00:09:19,900 --> 00:09:18,380 same way as the first one and I love 256 00:09:22,360 --> 00:09:19,910 this photo because these are actually 257 00:09:27,100 --> 00:09:22,370 our samples in space and they're 258 00:09:30,400 --> 00:09:27,110 floating I love looking at there's no 259 00:09:33,130 --> 00:09:30,410 strings attached and so we found about 260 00:09:35,590 --> 00:09:33,140 255 genes in the 23 samples that were 261 00:09:37,030 --> 00:09:35,600 differentially expressed so feel a few 262 00:09:38,680 --> 00:09:37,040 less than brick 20 where I'm about the 263 00:09:40,480 --> 00:09:38,690 same number and we found about seven and 264 00:09:44,980 --> 00:09:40,490 rich pathways 265 00:09:46,449 --> 00:09:44,990 among these 255 genes this is all great 266 00:09:47,829 --> 00:09:46,459 and everything but you know how do they 267 00:09:49,150 --> 00:09:47,839 compare to one another that was the you 268 00:09:50,259 --> 00:09:49,160 know the big question and so I want to 269 00:09:52,389 --> 00:09:50,269 know what the variation between the 270 00:09:53,860 --> 00:09:52,399 different samples were you know do are 271 00:09:55,720 --> 00:09:53,870 their samples clustered together are 272 00:09:57,370 --> 00:09:55,730 they completely over the map and so I 273 00:09:59,110 --> 00:09:57,380 ran a principal component analysis and 274 00:10:01,060 --> 00:09:59,120 what you can kind of see is if you look 275 00:10:02,230 --> 00:10:01,070 at the first principal component you see 276 00:10:05,860 --> 00:10:02,240 that the sample is kind of clustered 277 00:10:07,630 --> 00:10:05,870 between brick 21 and brick 23 and have 278 00:10:10,329 --> 00:10:07,640 about 51 percent of variation between 279 00:10:12,460 --> 00:10:10,339 all the samples and because we grew them 280 00:10:13,810 --> 00:10:12,470 at different state growth phases this 281 00:10:16,120 --> 00:10:13,820 isn't uncommon because they should have 282 00:10:17,440 --> 00:10:16,130 completely different gene expressions 283 00:10:18,880 --> 00:10:17,450 when they're you know rapidly growing an 284 00:10:20,740 --> 00:10:18,890 exponential phase that's when they're 285 00:10:22,660 --> 00:10:20,750 dormant in stationary phase but if you 286 00:10:24,579 --> 00:10:22,670 look over at the second principal 287 00:10:26,590 --> 00:10:24,589 component you see that about 21 percent 288 00:10:28,449 --> 00:10:26,600 of the variants between all the genes 289 00:10:30,340 --> 00:10:28,459 can be explained by grouping the ground 290 00:10:33,910 --> 00:10:30,350 samples together and the flight samples 291 00:10:37,240 --> 00:10:33,920 together so we do see this effect of 292 00:10:38,470 --> 00:10:37,250 spaceflight even though our examples 293 00:10:39,910 --> 00:10:38,480 were going to this different face so we 294 00:10:41,590 --> 00:10:39,920 can actually pull out maybe some 295 00:10:44,710 --> 00:10:41,600 effective spaceflight even though it's 296 00:10:47,889 --> 00:10:44,720 it's not the dominant source of our 297 00:10:49,540 --> 00:10:47,899 variants and so we then want to see can 298 00:10:50,769 --> 00:10:49,550 we actually see this at the actual gene 299 00:10:52,800 --> 00:10:50,779 level do we have new genes that are 300 00:10:55,449 --> 00:10:52,810 differentially expressed in both 301 00:10:56,500 --> 00:10:55,459 experiments and we found 91 genes that 302 00:11:00,610 --> 00:10:56,510 were differentially expressed in both 303 00:11:02,110 --> 00:11:00,620 experiments so yeah about put and so 55 304 00:11:04,480 --> 00:11:02,120 of these genes were upregulated in 305 00:11:06,759 --> 00:11:04,490 spaceflight which include our biotin 306 00:11:09,430 --> 00:11:06,769 metabolism biotin uptake genes as well 307 00:11:10,569 --> 00:11:09,440 as our biofilm biosynthesis genes as I 308 00:11:11,980 --> 00:11:10,579 mentioned before you know NASA is very 309 00:11:15,250 --> 00:11:11,990 interested in these biofilm by since the 310 00:11:17,260 --> 00:11:15,260 scheme and then we found 36 that 311 00:11:19,030 --> 00:11:17,270 regulating the ground control and these 312 00:11:21,550 --> 00:11:19,040 are national metabolism into component 313 00:11:23,590 --> 00:11:21,560 systems an actually metabolism is a bit 314 00:11:25,960 --> 00:11:23,600 of a misleading because it was really 315 00:11:27,610 --> 00:11:25,970 just the nitrate reductase genes which 316 00:11:29,920 --> 00:11:27,620 are expressed in low oxygen conditions 317 00:11:31,450 --> 00:11:29,930 and this is we also saw some other 318 00:11:33,700 --> 00:11:31,460 fermentation genes that are also 319 00:11:35,410 --> 00:11:33,710 expressed in low oxygen conditions so we 320 00:11:37,330 --> 00:11:35,420 think most of the genes it looks like 321 00:11:39,610 --> 00:11:37,340 most the genes that are down regulated 322 00:11:43,060 --> 00:11:39,620 were due to maybe a difference in oxygen 323 00:11:44,680 --> 00:11:43,070 between the flight and ground sample but 324 00:11:46,360 --> 00:11:44,690 the flight samples going back to those 325 00:11:47,920 --> 00:11:46,370 you know we didn't see this biofilm 326 00:11:49,420 --> 00:11:47,930 bison for this gene which we're kind of 327 00:11:51,580 --> 00:11:49,430 like wanting to dive in a bit more into 328 00:11:53,410 --> 00:11:51,590 like okay we see them up masses kind of 329 00:11:55,780 --> 00:11:53,420 interest in these you know what do we 330 00:11:56,980 --> 00:11:55,790 actually see with our gene counts and I 331 00:11:58,210 --> 00:11:56,990 know probably most of you do not 332 00:12:00,490 --> 00:11:58,220 understand what these four little 333 00:12:02,920 --> 00:12:00,500 radiations are so I will be I will kind 334 00:12:05,800 --> 00:12:02,930 of dive into that all these genes are 335 00:12:07,360 --> 00:12:05,810 the genes required to make biofilms in 336 00:12:09,670 --> 00:12:07,370 bacillus unless the organism that we're 337 00:12:12,340 --> 00:12:09,680 using so any available that aren't 338 00:12:14,350 --> 00:12:12,350 familiar with biofilms the most simple 339 00:12:16,390 --> 00:12:14,360 and probably when you associate with the 340 00:12:18,520 --> 00:12:16,400 most is plaque on your teeth it's a 341 00:12:21,820 --> 00:12:18,530 community of cells that kind of grouped 342 00:12:23,290 --> 00:12:21,830 together in a protein sugar matrix that 343 00:12:25,570 --> 00:12:23,300 kind of shared nutrients kind of help 344 00:12:27,760 --> 00:12:25,580 each other out and this protects them 345 00:12:29,200 --> 00:12:27,770 from invaders antibiotics and a bunch of 346 00:12:30,970 --> 00:12:29,210 other environmental stresses so you know 347 00:12:33,550 --> 00:12:30,980 bacteria love to grow in these biofilms 348 00:12:39,490 --> 00:12:33,560 and they're made up of like I said EXO 349 00:12:41,260 --> 00:12:39,500 polysaccharide or EPS sugars there's a 350 00:12:43,240 --> 00:12:41,270 biofilm surface layer protein and then 351 00:12:44,770 --> 00:12:43,250 you also have a protein scaffold that 352 00:12:47,470 --> 00:12:44,780 kind of holds them together as well 353 00:12:50,200 --> 00:12:47,480 within the sugar matrix so we have all 354 00:12:52,480 --> 00:12:50,210 of our genes here and if you look at you 355 00:12:54,010 --> 00:12:52,490 know this cut off of it this is a log to 356 00:12:56,380 --> 00:12:54,020 scale so this is a two-fold change 357 00:12:58,420 --> 00:12:56,390 there's only two genes that don't have a 358 00:13:01,150 --> 00:12:58,430 two-fold change between fly and grounds 359 00:13:03,670 --> 00:13:01,160 so almost all of our biofilm 360 00:13:05,290 --> 00:13:03,680 biosynthesis genes are upregulated in 361 00:13:07,620 --> 00:13:05,300 spaceflight and so this is the first 362 00:13:10,390 --> 00:13:07,630 molecular evidence that we have that 363 00:13:13,150 --> 00:13:10,400 points towards spaceflight you know 364 00:13:14,680 --> 00:13:13,160 promoting biofilm biosynthesis now we 365 00:13:16,750 --> 00:13:14,690 don't have a you know reason why this is 366 00:13:18,190 --> 00:13:16,760 right now but you know something that 367 00:13:21,730 --> 00:13:18,200 we're hoping to look into in the future 368 00:13:25,780 --> 00:13:21,740 with more spaceflight missions you know 369 00:13:27,910 --> 00:13:25,790 and more regular tests on regulations so 370 00:13:28,720 --> 00:13:27,920 it's kind of with that in the conclusion 371 00:13:30,460 --> 00:13:28,730 we 372 00:13:31,900 --> 00:13:30,470 fine about 91 genes that are 373 00:13:32,980 --> 00:13:31,910 differentially expressed and these 91 374 00:13:35,230 --> 00:13:32,990 genes we're gonna look further into 375 00:13:38,319 --> 00:13:35,240 because these could be good candidates 376 00:13:40,120 --> 00:13:38,329 for how space is affecting bacteria like 377 00:13:42,819 --> 00:13:40,130 what are these you know we'd knock out 378 00:13:44,170 --> 00:13:42,829 these 91 genes one of them how does it 379 00:13:46,620 --> 00:13:44,180 affect space why does it have a effect 380 00:13:49,150 --> 00:13:46,630 at all you know kind of dive in further 381 00:13:51,250 --> 00:13:49,160 also look further into biofilm 382 00:13:53,079 --> 00:13:51,260 biosynthesis we do see the first 383 00:13:56,350 --> 00:13:53,089 molecular kind of evidence for this 384 00:13:58,629 --> 00:13:56,360 increased production in space and it 385 00:14:00,430 --> 00:13:58,639 appears that at least for the hardware 386 00:14:02,920 --> 00:14:00,440 we're using the available of nitrogen 387 00:14:04,090 --> 00:14:02,930 oxygen is different between flight and 388 00:14:06,400 --> 00:14:04,100 ground and that's something that we are 389 00:14:10,389 --> 00:14:06,410 discussing with NASA on kind of making 390 00:14:12,280 --> 00:14:10,399 adjustments to the hardware for that but 391 00:14:13,920 --> 00:14:12,290 you know science is in a one-man show so 392 00:14:17,019 --> 00:14:13,930 I have a lot of people I want to thank 393 00:14:18,430 --> 00:14:17,029 primarily my boss and Patricia Fajardo 394 00:14:20,079 --> 00:14:18,440 who actually helped with a lot of 395 00:14:21,220 --> 00:14:20,089 processing and integration the 396 00:14:23,650 --> 00:14:21,230 integration of the spaceflight 397 00:14:25,960 --> 00:14:23,660 experiments the BRIC 21 BRIC 23 teams 398 00:14:27,400 --> 00:14:25,970 who you know helped integration with the 399 00:14:29,350 --> 00:14:27,410 preparing of the samples and everything 400 00:14:31,810 --> 00:14:29,360 and the astronauts who actually ran my 401 00:14:35,650 --> 00:14:31,820 experiments in space that you know they 402 00:14:39,100 --> 00:14:35,660 wouldn't let me do and so with that 403 00:14:43,060 --> 00:14:39,110 oh and NASA for funding me and and with 404 00:14:47,620 --> 00:14:46,139 [Applause] 405 00:14:57,340 --> 00:14:47,630 thank you Michael 406 00:15:04,549 --> 00:15:02,569 do you have ideas about why biotin is 407 00:15:05,749 --> 00:15:04,559 upregulated is it a general stress 408 00:15:07,939 --> 00:15:05,759 response do you think there's a certain 409 00:15:10,609 --> 00:15:07,949 protein that is a cofactor that's 410 00:15:12,169 --> 00:15:10,619 hindered in some way like so yeah we're 411 00:15:14,389 --> 00:15:12,179 working fused about that little bit we 412 00:15:16,609 --> 00:15:14,399 don't know for sure because it's you 413 00:15:19,850 --> 00:15:16,619 it's a B vitamin it's used in the 414 00:15:22,100 --> 00:15:19,860 biosynthesis of some fatty acids and 415 00:15:24,169 --> 00:15:22,110 branched chain amino acids and buccaneer 416 00:15:25,729 --> 00:15:24,179 genesis but we looked at all the genes 417 00:15:27,710 --> 00:15:25,739 involved in those pathways and none of 418 00:15:35,780 --> 00:15:27,720 more differentially expressed so we have 419 00:15:38,660 --> 00:15:35,790 no clue why they're up regarding the 420 00:15:40,609 --> 00:15:38,670 about film production do you think that 421 00:15:43,160 --> 00:15:40,619 a my absolutely to do with form sensing 422 00:15:45,859 --> 00:15:43,170 signal regulation with volatility in the 423 00:15:48,259 --> 00:15:45,869 og so there is some thought about 424 00:15:50,509 --> 00:15:48,269 motility in space we didn't see any 425 00:15:52,639 --> 00:15:50,519 motility genes upregulated but we did 426 00:15:55,160 --> 00:15:52,649 see a quorum sensing gene surfactant 427 00:15:57,499 --> 00:15:55,170 that was up regulated in space so that 428 00:15:59,030 --> 00:15:57,509 probably one reason why we're seeing the 429 00:16:02,539 --> 00:15:59,040 increase in point of information but we 430 00:16:04,069 --> 00:16:02,549 don't necessarily know you know why that 431 00:16:06,309 --> 00:16:04,079 coursing gene would be higher in space 432 00:16:09,019 --> 00:16:06,319 but we did see one Qantas engine 433 00:16:11,970 --> 00:16:09,029 okay let's thank Michael again I don't