1 00:00:12,250 --> 00:00:06,150 you 2 00:00:17,140 --> 00:00:14,340 [Music] 3 00:00:19,570 --> 00:00:17,150 thank you for having me my name is 4 00:00:21,190 --> 00:00:19,580 Lawrence Tyler I'm a postdoc in match 5 00:00:25,179 --> 00:00:21,200 strikes lab at Michigan State University 6 00:00:29,710 --> 00:00:25,189 and I've been working on metabolomics as 7 00:00:31,540 --> 00:00:29,720 a means of mapping metabolic networks in 8 00:00:33,460 --> 00:00:31,550 microbial cultures and also an 9 00:00:35,200 --> 00:00:33,470 environmental sample since I started in 10 00:00:36,670 --> 00:00:35,210 this lab about a year and a half ago and 11 00:00:38,290 --> 00:00:36,680 so today I'm going to talk to you about 12 00:00:40,080 --> 00:00:38,300 a particular site that I've been working 13 00:00:43,210 --> 00:00:40,090 at the coast range ophiolite in 14 00:00:44,979 --> 00:00:43,220 California oh look it's the same slide 15 00:00:48,190 --> 00:00:44,989 that Katrina had it's almost like we 16 00:00:49,660 --> 00:00:48,200 worked in the same lab so you've already 17 00:00:51,400 --> 00:00:49,670 seen this you're already familiar with 18 00:00:53,200 --> 00:00:51,410 the reactions that are associated with 19 00:00:55,060 --> 00:00:53,210 repentance ation but what I really want 20 00:00:56,410 --> 00:00:55,070 to draw your attention to is the part of 21 00:00:58,299 --> 00:00:56,420 this reaction that interests me the most 22 00:01:00,490 --> 00:00:58,309 and that's this production of methane 23 00:01:02,260 --> 00:01:00,500 and these small organics and what's 24 00:01:05,950 --> 00:01:02,270 interesting about that to me is that 25 00:01:07,240 --> 00:01:05,960 while microbes can utilize methane and 26 00:01:08,800 --> 00:01:07,250 these small organics that are produced 27 00:01:10,240 --> 00:01:08,810 by this reaction they're also producing 28 00:01:11,529 --> 00:01:10,250 these things themselves 29 00:01:13,300 --> 00:01:11,539 we know that microbes can produce 30 00:01:15,370 --> 00:01:13,310 methane they produce these small 31 00:01:18,130 --> 00:01:15,380 organics and so it creates this really 32 00:01:21,010 --> 00:01:18,140 amazing and confounding grey area 33 00:01:22,840 --> 00:01:21,020 between geochemistry and biochemistry 34 00:01:25,030 --> 00:01:22,850 which i think is really at the crux of 35 00:01:27,039 --> 00:01:25,040 not only astrobiology but Originals life 36 00:01:29,289 --> 00:01:27,049 questions as well and it creates this 37 00:01:33,880 --> 00:01:29,299 beautiful loving relationship between 38 00:01:35,530 --> 00:01:33,890 microbes in rock and so as I mentioned 39 00:01:37,149 --> 00:01:35,540 I'm working specifically at the coast 40 00:01:40,300 --> 00:01:37,159 range ophiolite it's just one of many 41 00:01:44,319 --> 00:01:40,310 surprising environments that our lab is 42 00:01:46,240 --> 00:01:44,329 studying and this site is about three 43 00:01:48,490 --> 00:01:46,250 hours north of San Francisco or an hour 44 00:01:52,870 --> 00:01:48,500 north of Napa really nice drive up the 45 00:01:55,330 --> 00:01:52,880 coast and stop through wine country and 46 00:01:56,770 --> 00:01:55,340 there's two particular sites at the 47 00:01:58,630 --> 00:01:56,780 coast range ophiolite microbial 48 00:02:00,819 --> 00:01:58,640 Observatory which is shortened as chromo 49 00:02:02,920 --> 00:02:00,829 and that's Quarry Valley and the core 50 00:02:05,469 --> 00:02:02,930 shed well and each one of those sites 51 00:02:06,999 --> 00:02:05,479 has a cluster of well there's three at 52 00:02:09,639 --> 00:02:07,009 Quarry Valley and then there's another 53 00:02:12,930 --> 00:02:09,649 five plus an older well that was drilled 54 00:02:15,819 --> 00:02:12,940 before this project at korshack well and 55 00:02:18,090 --> 00:02:15,829 this is what the wells look like not 56 00:02:21,280 --> 00:02:18,100 very exciting to look at on the surface 57 00:02:23,990 --> 00:02:21,290 and I took these samples in May in June 58 00:02:25,760 --> 00:02:24,000 of last year 59 00:02:28,340 --> 00:02:25,770 and this is some work that Katrina did 60 00:02:32,960 --> 00:02:28,350 while she was still a PhD student in 61 00:02:34,970 --> 00:02:32,970 Matt's lab looking at 16s diversity in 62 00:02:38,120 --> 00:02:34,980 some of these wells and what I want to 63 00:02:40,400 --> 00:02:38,130 point out this is a figure from her 64 00:02:44,840 --> 00:02:40,410 latest paper what I want to point out 65 00:02:46,460 --> 00:02:44,850 here is the incredible decrease in alpha 66 00:02:51,530 --> 00:02:46,470 diversity that occurs as you go from 67 00:02:54,260 --> 00:02:51,540 these lower pH wells like CS w14 down to 68 00:02:57,500 --> 00:02:54,270 these very high alkaline walls like QV 1 69 00:02:59,510 --> 00:02:57,510 1 and c SW 1 1 so as you get into these 70 00:03:02,510 --> 00:02:59,520 higher alkaline well these deeper wells 71 00:03:03,949 --> 00:03:02,520 we really see a decrease in the amount 72 00:03:05,780 --> 00:03:03,959 of diversity that we see in these 73 00:03:07,910 --> 00:03:05,790 communities become very very simple and 74 00:03:09,949 --> 00:03:07,920 that's why I decided to focus on these 75 00:03:12,140 --> 00:03:09,959 1:1 wells because they are hyper alkalyn 76 00:03:13,940 --> 00:03:12,150 and they are very simple communities and 77 00:03:16,370 --> 00:03:13,950 I thought that they best reflected this 78 00:03:20,240 --> 00:03:16,380 relationship between microbes and mr. 79 00:03:21,770 --> 00:03:20,250 Penton izing system and so if we just 80 00:03:24,710 --> 00:03:21,780 want to look at the 1:1 wells at a 81 00:03:26,840 --> 00:03:24,720 glance these are the deepest wells at 82 00:03:29,540 --> 00:03:26,850 these sites with the exception of csw 83 00:03:30,949 --> 00:03:29,550 old and they are the highest pH as I 84 00:03:31,820 --> 00:03:30,959 mentioned they're the least diverse and 85 00:03:34,250 --> 00:03:31,830 so there you have the simplest 86 00:03:35,660 --> 00:03:34,260 communities they're also uncased which 87 00:03:37,850 --> 00:03:35,670 means that they can be influenced by 88 00:03:39,259 --> 00:03:37,860 water coming from the surface rain water 89 00:03:42,080 --> 00:03:39,269 which there isn't much of in this area 90 00:03:44,120 --> 00:03:42,090 but it is a concern and so we can have 91 00:03:45,979 --> 00:03:44,130 this percolation of organic material 92 00:03:49,160 --> 00:03:45,989 from the surface down into the swell 93 00:03:50,780 --> 00:03:49,170 water and if we just look really quickly 94 00:03:52,310 --> 00:03:50,790 at some of the chemical parameters of 95 00:03:56,600 --> 00:03:52,320 these wells they're about the same depth 96 00:03:58,610 --> 00:03:56,610 the pH ranges from 11.5 to 12.5 the 97 00:04:02,420 --> 00:03:58,620 highly reducing very low dissolved 98 00:04:04,280 --> 00:04:02,430 oxygen and relatively low biomass 99 00:04:07,449 --> 00:04:04,290 compared to something like seawater for 100 00:04:09,860 --> 00:04:07,459 example or surface strains in the area 101 00:04:15,020 --> 00:04:09,870 but again I want to draw your attention 102 00:04:17,240 --> 00:04:15,030 to the concentration of methane in these 103 00:04:20,180 --> 00:04:17,250 wells and some of these simple organic 104 00:04:22,009 --> 00:04:20,190 acids like acetate in forming in the QV 105 00:04:23,810 --> 00:04:22,019 wells in particular these organic acids 106 00:04:24,920 --> 00:04:23,820 are sometimes below detection limits but 107 00:04:26,510 --> 00:04:24,930 that doesn't necessarily mean that 108 00:04:31,250 --> 00:04:26,520 they're not being produced they may just 109 00:04:33,290 --> 00:04:31,260 be cycled very very rapidly so we're not 110 00:04:34,460 --> 00:04:33,300 really sure if the microbes are 111 00:04:35,570 --> 00:04:34,470 producing methane or if they're 112 00:04:37,450 --> 00:04:35,580 consuming methane or if they're 113 00:04:40,400 --> 00:04:37,460 producing something else entirely 114 00:04:42,530 --> 00:04:40,410 if we look at the meta genomic data 115 00:04:44,030 --> 00:04:42,540 which is provided by Billy Brazelton 116 00:04:47,570 --> 00:04:44,040 who's now professor at University of 117 00:04:49,120 --> 00:04:47,580 Utah we see a lot of pathways for things 118 00:04:51,740 --> 00:04:49,130 that we would expect and well that's 119 00:04:54,470 --> 00:04:51,750 influenced by groundwater percolating 120 00:04:56,810 --> 00:04:54,480 down into the wall so genes associated 121 00:04:58,970 --> 00:04:56,820 with the hydrolysis of cellulose from 122 00:05:01,190 --> 00:04:58,980 plants for example or the degradation of 123 00:05:03,590 --> 00:05:01,200 poly aromatic hydrocarbons fatty acid 124 00:05:05,540 --> 00:05:03,600 catabolism we also see a ton of gene 125 00:05:06,950 --> 00:05:05,550 pathways associated with fermentation 126 00:05:09,350 --> 00:05:06,960 which makes sense because it's a very 127 00:05:10,550 --> 00:05:09,360 low oxygen environment so the production 128 00:05:13,010 --> 00:05:10,560 of acetone 129 00:05:17,420 --> 00:05:13,020 for example which permit ativ cells used 130 00:05:18,950 --> 00:05:17,430 to store excess acetate and this makes 131 00:05:20,630 --> 00:05:18,960 sense when we look again at the chemical 132 00:05:22,160 --> 00:05:20,640 parameters of the wells you can see this 133 00:05:23,900 --> 00:05:22,170 production of formate and acetate 134 00:05:25,910 --> 00:05:23,910 through all of these fermentated 135 00:05:28,820 --> 00:05:25,920 processes so that's interesting but what 136 00:05:31,070 --> 00:05:28,830 about the methane well if we start 137 00:05:33,020 --> 00:05:31,080 looking at the genes associated with 138 00:05:34,460 --> 00:05:33,030 methane production and consumption we 139 00:05:39,530 --> 00:05:34,470 start to get a really interesting story 140 00:05:41,540 --> 00:05:39,540 here so the reductive acetyl co a 141 00:05:43,100 --> 00:05:41,550 pathway or the wood long draw pathway 142 00:05:46,580 --> 00:05:43,110 isn't really prevalent in these wells 143 00:05:48,530 --> 00:05:46,590 and neither are the genes for Masana 144 00:05:50,090 --> 00:05:48,540 genesis which makes sense because we 145 00:05:53,270 --> 00:05:50,100 weren't really able to find any evidence 146 00:05:56,210 --> 00:05:53,280 of mismanage ends in the 16s data either 147 00:05:57,620 --> 00:05:56,220 that comes from these meta-genome so it 148 00:06:01,960 --> 00:05:57,630 doesn't really look like methanogenesis 149 00:06:04,670 --> 00:06:01,970 is happening in these well there is 150 00:06:07,250 --> 00:06:04,680 Mehsana Genesis from acetate here in a 151 00:06:09,140 --> 00:06:07,260 small amount but if we can't find the 152 00:06:12,080 --> 00:06:09,150 misc antigens and that could be there 153 00:06:14,570 --> 00:06:12,090 because of a horizontal gene transfer or 154 00:06:17,930 --> 00:06:14,580 maybe it's been mislabeled any number of 155 00:06:20,470 --> 00:06:17,940 things we do find them quite a bit of 156 00:06:24,530 --> 00:06:20,480 acetate formation from acetyl co a and 157 00:06:26,330 --> 00:06:24,540 then all of these available genes and 158 00:06:30,890 --> 00:06:26,340 gene pathways for the consumption of 159 00:06:33,920 --> 00:06:30,900 methane from methyl a trophy and not 160 00:06:36,320 --> 00:06:33,930 quite as much methane oxidation to co2 161 00:06:38,120 --> 00:06:36,330 as I would have expected so there's all 162 00:06:42,110 --> 00:06:38,130 of these potential pathways for 163 00:06:44,750 --> 00:06:42,120 consuming methane and using it up but 164 00:06:47,030 --> 00:06:44,760 not necessarily pushing it to co2 and 165 00:06:48,770 --> 00:06:47,040 perhaps that's because co2 precipitates 166 00:06:50,119 --> 00:06:48,780 out so readily in these systems I'm not 167 00:06:54,659 --> 00:06:50,129 really sure 168 00:06:56,129 --> 00:06:54,669 so we have this very complex metabolic 169 00:06:58,469 --> 00:06:56,139 network here that we're trying to tease 170 00:07:00,330 --> 00:06:58,479 apart and while we have all this 171 00:07:02,010 --> 00:07:00,340 metagenomic data all that's really 172 00:07:03,719 --> 00:07:02,020 telling us is that these cells have the 173 00:07:05,429 --> 00:07:03,729 potential or they have the knowledge for 174 00:07:07,050 --> 00:07:05,439 these processes not necessarily that 175 00:07:09,659 --> 00:07:07,060 these processes are actively occurring 176 00:07:11,249 --> 00:07:09,669 and that's where metabolomics comes into 177 00:07:14,129 --> 00:07:11,259 play so for those of you in the audience 178 00:07:16,140 --> 00:07:14,139 who are not biochemist or not microbial 179 00:07:18,600 --> 00:07:16,150 ecologists like me a metabolite is a 180 00:07:20,580 --> 00:07:18,610 small organic molecule it's a product or 181 00:07:23,700 --> 00:07:20,590 an intermediate of a metabolic process 182 00:07:25,499 --> 00:07:23,710 and the metabolomic election of all the 183 00:07:29,730 --> 00:07:25,509 metabolites produced by an organism a 184 00:07:31,950 --> 00:07:29,740 population or a community so metabolomic 185 00:07:34,110 --> 00:07:31,960 this is really a snapshot of metabolism 186 00:07:35,279 --> 00:07:34,120 as it's occurring we have genomics which 187 00:07:37,320 --> 00:07:35,289 will tell us that a cell has the 188 00:07:38,640 --> 00:07:37,330 knowledge of a process proteomics will 189 00:07:40,680 --> 00:07:38,650 tell us that the cells producing the 190 00:07:42,659 --> 00:07:40,690 tools to perform that process but 191 00:07:44,610 --> 00:07:42,669 metabolomics is evidence of the process 192 00:07:46,890 --> 00:07:44,620 in action of course there are some 193 00:07:48,390 --> 00:07:46,900 limitations and as I mentioned before 194 00:07:50,580 --> 00:07:48,400 there's not a lot of biomass in these 195 00:07:52,260 --> 00:07:50,590 wells so in order to really get at some 196 00:07:54,390 --> 00:07:52,270 of the rarer metabolites that are like 197 00:07:56,339 --> 00:07:54,400 the smoking gun of metabolism we need 198 00:07:59,850 --> 00:07:56,349 quite a bit of carbon on these on these 199 00:08:01,800 --> 00:07:59,860 filters if we assume that each cell 200 00:08:03,749 --> 00:08:01,810 contains about 30 50 grams of carbon 201 00:08:06,540 --> 00:08:03,759 that means I would need to filter about 202 00:08:08,969 --> 00:08:06,550 50 litres of water that's a huge amount 203 00:08:10,709 --> 00:08:08,979 and while the one on wells have a pretty 204 00:08:12,689 --> 00:08:10,719 high fluid output that's not true for 205 00:08:14,189 --> 00:08:12,699 all of the wells at this site and 206 00:08:16,439 --> 00:08:14,199 there's also limitations just to 207 00:08:18,240 --> 00:08:16,449 filtration the filters can clog because 208 00:08:20,339 --> 00:08:18,250 as this highly alkaline water comes in 209 00:08:22,079 --> 00:08:20,349 contact with the atmosphere carbonates 210 00:08:24,269 --> 00:08:22,089 precipitate out clog the filter it's 211 00:08:25,980 --> 00:08:24,279 difficult to keep this water cold to 212 00:08:27,659 --> 00:08:25,990 prevent all kinds of metabolic 213 00:08:29,850 --> 00:08:27,669 interactions from occurring as you're 214 00:08:33,180 --> 00:08:29,860 filtering so the data shown here is for 215 00:08:35,100 --> 00:08:33,190 about 12 liters of water so it's really 216 00:08:37,469 --> 00:08:35,110 a two-step process first a filter the 217 00:08:39,719 --> 00:08:37,479 water through a vacuum filtration and a 218 00:08:42,449 --> 00:08:39,729 glass stand like this through a PTFE 219 00:08:44,910 --> 00:08:42,459 filter and then yes that's the front 220 00:08:46,290 --> 00:08:44,920 seat of a car this is the best picture I 221 00:08:50,220 --> 00:08:46,300 had of me actually doing this in the 222 00:08:52,620 --> 00:08:50,230 field so and then that filtered water is 223 00:08:53,689 --> 00:08:52,630 run again through an SP II cartridge 224 00:08:55,949 --> 00:08:53,699 which stands for solid phase extraction 225 00:08:58,590 --> 00:08:55,959 which captures all of the dissolved 226 00:09:01,800 --> 00:08:58,600 carbon in the sample so that can be run 227 00:09:03,929 --> 00:09:01,810 separately so we're looking at two pools 228 00:09:06,179 --> 00:09:03,939 metabolites here whatever trapped on the 229 00:09:07,679 --> 00:09:06,189 filter which represents intracellular 230 00:09:09,239 --> 00:09:07,689 metabolites and then all of the 231 00:09:12,150 --> 00:09:09,249 dissolved organic matter that's present 232 00:09:14,970 --> 00:09:12,160 in the well water and if we look at that 233 00:09:17,850 --> 00:09:14,980 and compare those samples on a PCA plot 234 00:09:20,189 --> 00:09:17,860 we see that the fluid samples are sort 235 00:09:25,799 --> 00:09:20,199 of similar to each other but drastically 236 00:09:34,110 --> 00:09:25,809 different from everything else what's 237 00:09:35,100 --> 00:09:34,120 happening it's not going over there goes 238 00:09:37,619 --> 00:09:35,110 sorry 239 00:09:39,480 --> 00:09:37,629 and then the biomass samples are very 240 00:09:43,530 --> 00:09:39,490 very similar to each other and there's 241 00:09:45,569 --> 00:09:43,540 our blank and our biomass like so if we 242 00:09:47,040 --> 00:09:45,579 look at all of the different compounds 243 00:09:49,590 --> 00:09:47,050 that we've observed which are analyzed 244 00:09:52,559 --> 00:09:49,600 on a tandem liquid chromatography mass 245 00:09:54,480 --> 00:09:52,569 spec we had a total of about 6,800 246 00:09:55,799 --> 00:09:54,490 compounds when we subtracted out 247 00:09:59,610 --> 00:09:55,809 whatever ones were also found in the 248 00:10:01,650 --> 00:09:59,620 blanks that was about 4500 and only 79 249 00:10:04,110 --> 00:10:01,660 of those samples or those compounds were 250 00:10:05,850 --> 00:10:04,120 found across all the samples so there 251 00:10:08,490 --> 00:10:05,860 were a lot of compounds that were very 252 00:10:10,769 --> 00:10:08,500 unique to the extracellular fluid and 253 00:10:14,100 --> 00:10:10,779 only a few that were unique to the 254 00:10:15,900 --> 00:10:14,110 biomass and the CSW well had a lot more 255 00:10:18,689 --> 00:10:15,910 unique compounds from the QV well for 256 00:10:20,670 --> 00:10:18,699 whatever reason there's also a ton of 257 00:10:22,559 --> 00:10:20,680 possible identifications for all of 258 00:10:25,549 --> 00:10:22,569 these compounds we searched database and 259 00:10:28,019 --> 00:10:25,559 compared with the mass-to-charge ratio 260 00:10:29,400 --> 00:10:28,029 retention time fragmentation and try to 261 00:10:32,340 --> 00:10:29,410 figure out what all of these compounds 262 00:10:34,499 --> 00:10:32,350 are and there are 50,000 possible IDs in 263 00:10:36,540 --> 00:10:34,509 a human metabolomic data base which we 264 00:10:39,990 --> 00:10:36,550 were able to narrow down to about 3600 265 00:10:41,579 --> 00:10:40,000 in the CAG database so some of the 266 00:10:43,439 --> 00:10:41,589 common compounds that we found here are 267 00:10:44,850 --> 00:10:43,449 some compounds of interest lots of 268 00:10:46,860 --> 00:10:44,860 different vitamins including a lot of B 269 00:10:49,910 --> 00:10:46,870 vitamins and the metabolites of those 270 00:10:52,049 --> 00:10:49,920 vitamins quinolones which are used in 271 00:10:58,079 --> 00:10:52,059 respiration and for different metabolic 272 00:10:59,910 --> 00:10:58,089 processes aromatic hydrocarbons acetone 273 00:11:02,519 --> 00:10:59,920 acetate which I mentioned is linked to 274 00:11:04,230 --> 00:11:02,529 fermentated processes and antibiotics 275 00:11:05,879 --> 00:11:04,240 and the products of the degradation of 276 00:11:07,590 --> 00:11:05,889 antibiotics all very interesting but 277 00:11:10,139 --> 00:11:07,600 what was most interesting to me is that 278 00:11:13,549 --> 00:11:10,149 I found all of the compounds that are 279 00:11:15,180 --> 00:11:13,559 associated with this are ump 280 00:11:16,950 --> 00:11:15,190 formaldehyde fixation 281 00:11:20,220 --> 00:11:16,960 halfway associated with methyl a trophy 282 00:11:21,870 --> 00:11:20,230 all of the compounds associated with the 283 00:11:24,000 --> 00:11:21,880 cesarean pathway for formaldehyde 284 00:11:26,460 --> 00:11:24,010 fixation some of the ones associated 285 00:11:28,130 --> 00:11:26,470 with tetrahydrofolate pathway and some 286 00:11:30,750 --> 00:11:28,140 of the ones that were associated with a 287 00:11:32,340 --> 00:11:30,760 glutathione pathway as well so there's 288 00:11:34,170 --> 00:11:32,350 plenty of evidence here from methyl a 289 00:11:36,000 --> 00:11:34,180 trophy occurring in these wells not only 290 00:11:39,120 --> 00:11:36,010 in the meta genome but also in the 291 00:11:42,030 --> 00:11:39,130 metabolome and very little evidence I 292 00:11:46,620 --> 00:11:42,040 believe for Mehsana Genesis at least in 293 00:11:48,300 --> 00:11:46,630 this particular site we still need to 294 00:11:49,260 --> 00:11:48,310 use some more sensitive methods to 295 00:11:50,040 --> 00:11:49,270 measure some of these small 296 00:11:52,050 --> 00:11:50,050 intermediates 297 00:11:53,700 --> 00:11:52,060 because lc/ms doesn't really pick up the 298 00:11:56,130 --> 00:11:53,710 very small metabolites especially 299 00:11:58,230 --> 00:11:56,140 uncharged ones and we have a ton of an 300 00:12:00,120 --> 00:11:58,240 unidentified compounds that may also be 301 00:12:01,940 --> 00:12:00,130 used as possible biomarkers for for 302 00:12:04,620 --> 00:12:01,950 looking for microbes associated with 303 00:12:06,480 --> 00:12:04,630 serpentine izing environment potentially 304 00:12:09,480 --> 00:12:06,490 on other worlds and they may be very 305 00:12:13,800 --> 00:12:09,490 very useful for for those kinds of 306 00:12:15,300 --> 00:12:13,810 studies so I'm running out of time but 307 00:12:16,890 --> 00:12:15,310 the next steps that we're going to do in 308 00:12:19,170 --> 00:12:16,900 this project is we're going to construct 309 00:12:22,500 --> 00:12:19,180 metabolic networks in our using the 310 00:12:23,940 --> 00:12:22,510 metabolome and the meta-genome i'm going 311 00:12:26,100 --> 00:12:23,950 to do some further work in chromo and 312 00:12:27,810 --> 00:12:26,110 including some work at c SW old because 313 00:12:29,610 --> 00:12:27,820 it is such a deep well and it is so 314 00:12:31,670 --> 00:12:29,620 interesting it's got very low amount of 315 00:12:34,170 --> 00:12:31,680 biomass there's a lot of potential there 316 00:12:36,270 --> 00:12:34,180 I've also been using these same 317 00:12:38,460 --> 00:12:36,280 techniques in the Oman drilling project 318 00:12:41,330 --> 00:12:38,470 and the picture from the front seat of a 319 00:12:44,780 --> 00:12:41,340 car was some problems from that project 320 00:12:47,100 --> 00:12:44,790 that's an entirely separate funny story 321 00:12:48,540 --> 00:12:47,110 I'm also using these techniques on 322 00:12:50,430 --> 00:12:48,550 microcosms and enrichments in the 323 00:12:52,080 --> 00:12:50,440 laboratory we're talking about 324 00:12:54,720 --> 00:12:52,090 potentially using them on micro cosmos 325 00:12:56,220 --> 00:12:54,730 from lost city and definitely if you're 326 00:12:57,480 --> 00:12:56,230 interested in this work and particularly 327 00:12:58,890 --> 00:12:57,490 the work that we're doing at chromo you 328 00:13:00,780 --> 00:12:58,900 should check out Marisa Buddha's and 329 00:13:04,050 --> 00:13:00,790 Lindsey Williams's talk this afternoon 330 00:13:06,270 --> 00:13:04,060 in this room and hopefully we'll be able 331 00:13:09,390 --> 00:13:06,280 to use some of this work to eventually 332 00:13:10,890 --> 00:13:09,400 find a microbe in space and so with that 333 00:13:12,360 --> 00:13:10,900 I'd like to thank you for your attention 334 00:13:18,740 --> 00:13:12,370 and I welcome your questions if there's 335 00:13:26,940 --> 00:13:21,120 we have time for a question or two for 336 00:13:28,260 --> 00:13:26,950 Lord oh yeah in the back if you could 337 00:13:49,889 --> 00:13:28,270 either speak loudly or come up to a 338 00:13:52,650 --> 00:13:49,899 microphone so I'm still working very 339 00:13:54,540 --> 00:13:52,660 preliminary on some of these enrichment 340 00:13:56,460 --> 00:13:54,550 experiments and microcosms but if you're 341 00:13:58,350 --> 00:13:56,470 interested in enrichment experiments 342 00:14:00,090 --> 00:13:58,360 from from this site in particular 343 00:14:03,180 --> 00:14:00,100 definitely check out Mary's talk this 344 00:14:07,050 --> 00:14:03,190 afternoon but we've been basically 345 00:14:09,690 --> 00:14:07,060 providing a reductant to to these 346 00:14:11,400 --> 00:14:09,700 microcosms and seeing if we can observe 347 00:14:16,199 --> 00:14:11,410 methyl a trophy in the production of co2 348 00:14:17,940 --> 00:14:16,209 in our lab hi hi Jamie Foster University 349 00:14:19,710 --> 00:14:17,950 of Florida I'm really curious about the 350 00:14:21,720 --> 00:14:19,720 metabolomic so did you see any cycling 351 00:14:24,380 --> 00:14:21,730 any Dial cycling within your community 352 00:14:26,699 --> 00:14:24,390 or you is this just a single time point 353 00:14:28,980 --> 00:14:26,709 what's the reproducibility of your 354 00:14:31,800 --> 00:14:28,990 signatures in your community 355 00:14:34,230 --> 00:14:31,810 so this is a single time point I 356 00:14:36,030 --> 00:14:34,240 initially took triplicates samples but 357 00:14:37,620 --> 00:14:36,040 the signal was so low that I had to pull 358 00:14:39,180 --> 00:14:37,630 all of them and that's why I was a 12 359 00:14:42,540 --> 00:14:39,190 leader sample because originally it was 360 00:14:44,880 --> 00:14:42,550 four in samples that I've done in 361 00:14:47,579 --> 00:14:44,890 culturing these results are very 362 00:14:49,860 --> 00:14:47,589 reproducible and triplicate samples look 363 00:14:51,690 --> 00:14:49,870 very very alike as far as 364 00:14:53,760 --> 00:14:51,700 reproducibility at this particular site 365 00:14:55,019 --> 00:14:53,770 this is still very preliminary and we're 366 00:14:57,870 --> 00:14:55,029 still working through the methodology 367 00:15:00,840 --> 00:14:57,880 and so I was only able to take one 368 00:15:02,760 --> 00:15:00,850 sample from each well but we'll be going 369 00:15:04,980 --> 00:15:02,770 back and hopefully doing this at a 370 00:15:06,780 --> 00:15:04,990 larger scale in order to show that 371 00:15:09,449 --> 00:15:06,790 reproducibility and maybe see some 372 00:15:14,790 --> 00:15:09,459 differences seasonally or with other