1 00:00:00,790 --> 00:00:07,320 [Music] 2 00:00:12,160 --> 00:00:09,030 [Applause] 3 00:00:15,609 --> 00:00:12,170 I'm really excited to present on what is 4 00:00:17,679 --> 00:00:15,619 a very new project for me as well I want 5 00:00:19,929 --> 00:00:17,689 to begin by thanking my callers 6 00:00:22,569 --> 00:00:19,939 particularly Alex funfact the PI on this 7 00:00:24,159 --> 00:00:22,579 project and Chris Carr and then Hannity 8 00:00:26,049 --> 00:00:24,169 and Krishna is a former undergrad of 9 00:00:29,880 --> 00:00:26,059 mine who has done most of this work in 10 00:00:32,290 --> 00:00:29,890 the lab so very grateful to her as well 11 00:00:42,489 --> 00:00:32,300 and then our funding sources this is a 12 00:00:44,919 --> 00:00:42,499 recent Nessa exobiology funded okay okay 13 00:00:47,729 --> 00:00:44,929 so it shouldn't be surprising to any of 14 00:00:49,930 --> 00:00:47,739 us that salt is a good preservative 15 00:00:51,819 --> 00:00:49,940 right so humans have been preserving 16 00:00:54,189 --> 00:00:51,829 things in salt for a very long time and 17 00:00:57,009 --> 00:00:54,199 so there's an intuition here that this 18 00:00:58,660 --> 00:00:57,019 might work but understanding how this 19 00:01:01,180 --> 00:00:58,670 process works is really important for 20 00:01:02,889 --> 00:01:01,190 astrobiology because it's going to 21 00:01:04,420 --> 00:01:02,899 affect the bio signatures that we see we 22 00:01:07,030 --> 00:01:04,430 saw some really beautiful work from Lou 23 00:01:09,070 --> 00:01:07,040 yesterday showing these relict bio 24 00:01:12,370 --> 00:01:09,080 signatures and just like you know poor 25 00:01:13,870 --> 00:01:12,380 little eukaryotic shells hanging out but 26 00:01:15,460 --> 00:01:13,880 they still have lipids they still have 27 00:01:18,400 --> 00:01:15,470 bio signatures so we need to think about 28 00:01:19,600 --> 00:01:18,410 how these processes work and so key 29 00:01:21,550 --> 00:01:19,610 questions that we're asking on this 30 00:01:23,290 --> 00:01:21,560 project are do different salts preserve 31 00:01:27,070 --> 00:01:23,300 things differently we're working in 32 00:01:28,780 --> 00:01:27,080 magnesium sulfate brines and do 33 00:01:30,910 --> 00:01:28,790 different organic compounds preserve 34 00:01:32,800 --> 00:01:30,920 differently so our lipids different than 35 00:01:35,500 --> 00:01:32,810 DNA are different from RNA and so on 36 00:01:37,780 --> 00:01:35,510 alex is going to tell you all about why 37 00:01:38,170 --> 00:01:37,790 those things should be true and how that 38 00:01:40,180 --> 00:01:38,180 works 39 00:01:42,310 --> 00:01:40,190 I know very little about that and so the 40 00:01:43,870 --> 00:01:42,320 question I'll be asking is how is 41 00:01:46,150 --> 00:01:43,880 organic matter incorporated into 42 00:01:50,200 --> 00:01:46,160 sediments and salts in this kind of 43 00:01:53,500 --> 00:01:50,210 hyper saline basin okay so the sites we 44 00:01:57,010 --> 00:01:53,510 are headed to over here in the middle of 45 00:01:58,840 --> 00:01:57,020 fabulous nowhere British Columbia really 46 00:02:01,030 --> 00:01:58,850 the middle of nowhere guys it's great 47 00:02:06,850 --> 00:02:01,040 and so zooming into these lake sites 48 00:02:08,770 --> 00:02:06,860 there are three of them and so the 49 00:02:10,719 --> 00:02:08,780 farthest self is bath quake number two 50 00:02:12,190 --> 00:02:10,729 this is a site that has a variety of 51 00:02:13,660 --> 00:02:12,200 previous work on it just a little bit 52 00:02:15,850 --> 00:02:13,670 and you can see they're really beautiful 53 00:02:18,610 --> 00:02:15,860 so this is a little light in this view 54 00:02:20,620 --> 00:02:18,620 but you can see the spotted character of 55 00:02:22,090 --> 00:02:20,630 these Lakes so it's a basin that have 56 00:02:23,740 --> 00:02:22,100 sub brine pools that make 57 00:02:25,780 --> 00:02:23,750 I'm really interesting to look at and 58 00:02:27,910 --> 00:02:25,790 means you can run around on this and 59 00:02:29,500 --> 00:02:27,920 sample a bunch of different compositions 60 00:02:32,310 --> 00:02:29,510 all at the same time so that's pretty 61 00:02:35,020 --> 00:02:32,320 neat so that's one site and then we have 62 00:02:37,000 --> 00:02:35,030 Clinton lake or Salt Lake in the 63 00:02:38,110 --> 00:02:37,010 thriving metropolis of Clinton British 64 00:02:40,870 --> 00:02:38,120 Columbia 65 00:02:42,430 --> 00:02:40,880 it is sometimes a salt pan and sometimes 66 00:02:44,980 --> 00:02:42,440 more of a lake so you can see it there 67 00:02:47,890 --> 00:02:44,990 and then the optimistically Lane named 68 00:02:50,290 --> 00:02:47,900 last chance lake which is up here on the 69 00:02:52,270 --> 00:02:50,300 far north this one is interesting 70 00:02:54,340 --> 00:02:52,280 because it's a chemical comparison and 71 00:02:57,550 --> 00:02:54,350 so this one has some bicarbonate and 72 00:02:59,590 --> 00:02:57,560 some sodium in addition to the magnesium 73 00:03:00,970 --> 00:02:59,600 and sulfate which Alex will tell you all 74 00:03:04,750 --> 00:03:00,980 about whereas these ones are much more 75 00:03:06,940 --> 00:03:04,760 strict magnesium sulfate brines okay so 76 00:03:09,100 --> 00:03:06,950 what are we doing so the goal here is to 77 00:03:10,300 --> 00:03:09,110 figure out what's being produced in 78 00:03:11,860 --> 00:03:10,310 these systems and how that's being 79 00:03:14,500 --> 00:03:11,870 translated into various sedimentary 80 00:03:16,570 --> 00:03:14,510 archives and so you go to a lake collect 81 00:03:18,520 --> 00:03:16,580 some water in my case filter that water 82 00:03:20,620 --> 00:03:18,530 down onto glass fiber filters to collect 83 00:03:23,440 --> 00:03:20,630 organic matter that is being produced in 84 00:03:26,080 --> 00:03:23,450 situ then also go into the more solid 85 00:03:28,210 --> 00:03:26,090 reservoir so this is some green salt for 86 00:03:30,670 --> 00:03:28,220 you so these are organic compounds being 87 00:03:34,180 --> 00:03:30,680 incorporated into salts then also the 88 00:03:37,090 --> 00:03:34,190 sediments then collecting modern biomass 89 00:03:40,180 --> 00:03:37,100 so this is a beaker of slime collected 90 00:03:42,820 --> 00:03:40,190 by Chris Carr so this is a big microbial 91 00:03:44,140 --> 00:03:42,830 mat and then also things like macro 92 00:03:46,390 --> 00:03:44,150 biology so these little wee beasties 93 00:03:48,400 --> 00:03:46,400 swimming around because we need to know 94 00:03:49,600 --> 00:03:48,410 what sorts of organics are being 95 00:03:51,730 --> 00:03:49,610 produced in these systems and how 96 00:03:53,470 --> 00:03:51,740 they're getting incorporated so then 97 00:03:55,840 --> 00:03:53,480 this was the summer and I went along on 98 00:03:57,940 --> 00:03:55,850 this trip and is fabulous then we went 99 00:03:59,710 --> 00:03:57,950 in the winter and by we I mean I sent my 100 00:04:01,240 --> 00:03:59,720 for undergrad to go sample when the 101 00:04:05,140 --> 00:04:01,250 lakes looked a little bit more like this 102 00:04:08,140 --> 00:04:05,150 I had to teach and also I'm weak and so 103 00:04:10,990 --> 00:04:08,150 in this case you got a drill down 104 00:04:13,510 --> 00:04:11,000 through that ice to then tap into both 105 00:04:16,300 --> 00:04:13,520 the ice itself which we saw some posters 106 00:04:18,070 --> 00:04:16,310 on and you can melt that ice filter down 107 00:04:19,660 --> 00:04:18,080 onto the filter you can get the sub ice 108 00:04:22,420 --> 00:04:19,670 brine which I'll be referring to as 109 00:04:25,450 --> 00:04:22,430 brine as opposed to water filter those 110 00:04:28,480 --> 00:04:25,460 down and then also get down deep with a 111 00:04:31,870 --> 00:04:28,490 ladle and get some sediment out from 112 00:04:32,830 --> 00:04:31,880 beneath in addition to the salts okay so 113 00:04:34,540 --> 00:04:32,840 then what are we gonna do 114 00:04:35,280 --> 00:04:34,550 so everything in our little organic jars 115 00:04:36,540 --> 00:04:35,290 is the same 116 00:04:38,730 --> 00:04:36,550 and so we're gonna first freeze-drying 117 00:04:40,890 --> 00:04:38,740 homogenize that sample and then analyze 118 00:04:43,140 --> 00:04:40,900 a variety of bulk parameters and so I'm 119 00:04:44,550 --> 00:04:43,150 interested in carbon and carbon isotopes 120 00:04:46,470 --> 00:04:44,560 and organics and so you need to first 121 00:04:48,270 --> 00:04:46,480 characterize the inorganic baseline of 122 00:04:49,080 --> 00:04:48,280 those samples and so we're looking at 123 00:04:51,420 --> 00:04:49,090 things like dissolved inorganic 124 00:04:54,060 --> 00:04:51,430 concentrations and isotopes and isotopes 125 00:04:55,350 --> 00:04:54,070 of carbonate then D carbonate and focus 126 00:04:57,180 --> 00:04:55,360 on that organic matter so how much 127 00:04:58,950 --> 00:04:57,190 organic carbon is in there total organic 128 00:05:00,900 --> 00:04:58,960 carbon and total organic nitrogen and 129 00:05:03,600 --> 00:05:00,910 then what does the isotopic composition 130 00:05:05,670 --> 00:05:03,610 of those phases look like and then the 131 00:05:07,860 --> 00:05:05,680 real lab work fun begins and again bring 132 00:05:09,300 --> 00:05:07,870 in the undergrads and so this is where 133 00:05:11,250 --> 00:05:09,310 we spend a lot of time doing lipid 134 00:05:14,250 --> 00:05:11,260 extractions via super time intensive 135 00:05:15,930 --> 00:05:14,260 blyer approach which preserves intact 136 00:05:17,550 --> 00:05:15,940 polar lipids and so that allows us to 137 00:05:19,680 --> 00:05:17,560 look at those complete lipids together 138 00:05:21,680 --> 00:05:19,690 and then also you can hydrolyze these 139 00:05:24,210 --> 00:05:21,690 things separate them clean them up and 140 00:05:25,680 --> 00:05:24,220 identify compound specific biomarker 141 00:05:28,230 --> 00:05:25,690 abundances and hopefully eventually 142 00:05:32,010 --> 00:05:28,240 isotopes okay 143 00:05:33,150 --> 00:05:32,020 so first step look at the waters and so 144 00:05:34,500 --> 00:05:33,160 if we look at these things under the 145 00:05:36,300 --> 00:05:34,510 microscope with just a little bit of 146 00:05:38,850 --> 00:05:36,310 crystal violet stain you can see 147 00:05:40,620 --> 00:05:38,860 beautiful beautiful cells this is a 10 148 00:05:42,120 --> 00:05:40,630 micron scale bar and so these are 149 00:05:44,430 --> 00:05:42,130 actually algae so that's what's making 150 00:05:46,440 --> 00:05:44,440 these bright yellow but you can see 151 00:05:48,330 --> 00:05:46,450 abundant cells we don't have cell counts 152 00:05:51,330 --> 00:05:48,340 yet but these are all the same amount of 153 00:05:53,910 --> 00:05:51,340 fluid just in a little reservoir if we 154 00:05:55,950 --> 00:05:53,920 look at the sub ice rinds they look 155 00:05:57,390 --> 00:05:55,960 almost exactly the same and so I was 156 00:05:59,430 --> 00:05:57,400 surprised going in you still have those 157 00:06:03,540 --> 00:05:59,440 algal morphologies you still have nice 158 00:06:05,820 --> 00:06:03,550 REM cells all over the place so how much 159 00:06:07,860 --> 00:06:05,830 organic matter is there and so if we 160 00:06:09,300 --> 00:06:07,870 look at the total organic carbon you 161 00:06:11,250 --> 00:06:09,310 should maybe not be surprised that 162 00:06:12,330 --> 00:06:11,260 microbial mats are full of organic 163 00:06:13,890 --> 00:06:12,340 carbon 164 00:06:17,130 --> 00:06:13,900 but these sediments are also quite rich 165 00:06:18,900 --> 00:06:17,140 in organic carbon if we look at the 166 00:06:20,010 --> 00:06:18,910 total organic nitrogen you can see that 167 00:06:23,010 --> 00:06:20,020 that's mirroring the organic carbon 168 00:06:26,880 --> 00:06:23,020 really well it has like a r-squared of 169 00:06:29,040 --> 00:06:26,890 0.9 7 and slope of 10 to 1 so well 170 00:06:30,390 --> 00:06:29,050 correlated and so what did the isotopes 171 00:06:31,560 --> 00:06:30,400 of those look like so this is a little 172 00:06:33,900 --> 00:06:31,570 bit more interesting and here I've 173 00:06:36,360 --> 00:06:33,910 plotted these by Lake so the Basques 174 00:06:38,600 --> 00:06:36,370 Lakes last chance Lake and Salt Lake and 175 00:06:42,000 --> 00:06:38,610 then they're colored by what type of 176 00:06:43,680 --> 00:06:42,010 sample that was and so you can see some 177 00:06:46,170 --> 00:06:43,690 differences between the Basques Lakes 178 00:06:48,810 --> 00:06:46,180 they're relatively enriched compared to 179 00:06:50,370 --> 00:06:48,820 the last chance lake or salt lake you 180 00:06:52,350 --> 00:06:50,380 and also if you look at the colors of 181 00:06:54,240 --> 00:06:52,360 these can you can see that these salts 182 00:06:55,980 --> 00:06:54,250 are enriched relative to the sediments 183 00:06:59,490 --> 00:06:55,990 are enriched relative to the sub ice 184 00:07:01,140 --> 00:06:59,500 brines really clearly there so that's an 185 00:07:03,300 --> 00:07:01,150 interesting trend so we need to look at 186 00:07:04,830 --> 00:07:03,310 our inorganic phases to see how these 187 00:07:07,680 --> 00:07:04,840 compare because that's setting your 188 00:07:10,860 --> 00:07:07,690 baseline and so if we look at the 189 00:07:12,390 --> 00:07:10,870 isotopes of di C and of carbonate you 190 00:07:14,640 --> 00:07:12,400 can see that this does explain a little 191 00:07:16,170 --> 00:07:14,650 bit of these trends so in our di C for 192 00:07:18,180 --> 00:07:16,180 instance this one is quite enriched 193 00:07:19,530 --> 00:07:18,190 whereas this one is quite depleted so 194 00:07:22,740 --> 00:07:19,540 you've got about a five per mil spread 195 00:07:24,660 --> 00:07:22,750 there but this one isn't so this is not 196 00:07:26,100 --> 00:07:24,670 explaining all of our data which 197 00:07:27,800 --> 00:07:26,110 suggests that you might have some 198 00:07:30,810 --> 00:07:27,810 distinct biological fraction nations 199 00:07:33,150 --> 00:07:30,820 changing the organic isotopes within 200 00:07:34,980 --> 00:07:33,160 that system if we look at the nitrogen 201 00:07:37,050 --> 00:07:34,990 isotopes there are also some kind of 202 00:07:39,150 --> 00:07:37,060 interesting trends for those of you that 203 00:07:41,040 --> 00:07:39,160 work in the system so zero to fifteen 204 00:07:42,870 --> 00:07:41,050 that's a really enriched nitrogen 205 00:07:46,380 --> 00:07:42,880 isotopic value we're sitting here kind 206 00:07:48,210 --> 00:07:46,390 of around ten quite enriched just fixing 207 00:07:50,460 --> 00:07:48,220 in two out of the air you get zero or 208 00:07:52,290 --> 00:07:50,470 two and so these are super enriched 209 00:07:54,000 --> 00:07:52,300 suggesting processing of these of 210 00:07:55,530 --> 00:07:54,010 nitrogen in the system usually 211 00:07:59,240 --> 00:07:55,540 denitrification gets blamed on 212 00:08:01,410 --> 00:07:59,250 enrichments like this also though in 213 00:08:03,750 --> 00:08:01,420 alkaline lakes you have a scenario where 214 00:08:05,610 --> 00:08:03,760 pH matters because you can actually get 215 00:08:07,950 --> 00:08:05,620 enrichment of the nitrogen pool through 216 00:08:14,930 --> 00:08:07,960 the volatile loss of ammonia and so some 217 00:08:17,730 --> 00:08:14,940 of these points up here are in go back 218 00:08:19,440 --> 00:08:17,740 so last chance leak is actually much 219 00:08:20,970 --> 00:08:19,450 higher pH than the other ones and we see 220 00:08:24,660 --> 00:08:20,980 these enrichments most strongly within 221 00:08:26,190 --> 00:08:24,670 that system okay so total lipids how 222 00:08:28,140 --> 00:08:26,200 much lipid is in these phases and so 223 00:08:30,330 --> 00:08:28,150 these I'm showing you in terms of 224 00:08:35,130 --> 00:08:30,340 milligrams per liter filtered for the 225 00:08:37,320 --> 00:08:35,140 fluid phases or per gram solid with in 226 00:08:38,010 --> 00:08:37,330 things like them sediments and the salts 227 00:08:41,010 --> 00:08:38,020 and whatnot 228 00:08:43,589 --> 00:08:41,020 and so if we look at this you can see a 229 00:08:46,560 --> 00:08:43,599 decrease in abundance when you go from 230 00:08:49,890 --> 00:08:46,570 the water to the brine to the ice within 231 00:08:52,590 --> 00:08:49,900 our lipids per liter and so if the brine 232 00:08:54,390 --> 00:08:52,600 was just concentrating cells we would 233 00:08:56,250 --> 00:08:54,400 expect the opposite trend right because 234 00:08:57,750 --> 00:08:56,260 it's gonna sort of push the cells into 235 00:09:00,090 --> 00:08:57,760 the brine and then there's gonna be less 236 00:09:03,389 --> 00:09:00,100 in the ice more in the brine and so on 237 00:09:05,819 --> 00:09:03,399 and so you do see some degradation 238 00:09:07,230 --> 00:09:05,829 and then if we look at the sediment 239 00:09:11,069 --> 00:09:07,240 phrases so I keep getting the laser 240 00:09:13,230 --> 00:09:11,079 they're both green if we look at the 241 00:09:15,210 --> 00:09:13,240 sediments you can see that the sediments 242 00:09:16,829 --> 00:09:15,220 have essentially the same amount of 243 00:09:18,420 --> 00:09:16,839 organic matter as things like the 244 00:09:20,280 --> 00:09:18,430 microbial math and they're they're 245 00:09:23,460 --> 00:09:20,290 nearing brine shrimp and so these 246 00:09:25,319 --> 00:09:23,470 sediments are really organic rich and 247 00:09:27,120 --> 00:09:25,329 they have a lot of extractable lipid in 248 00:09:29,069 --> 00:09:27,130 there which is suggesting to me that 249 00:09:30,420 --> 00:09:29,079 we've got some really preferential 250 00:09:32,610 --> 00:09:30,430 preservation going on within these 251 00:09:36,030 --> 00:09:32,620 sediments I'm consistent with it being a 252 00:09:37,800 --> 00:09:36,040 salty you know environment you can also 253 00:09:39,600 --> 00:09:37,810 note that the abundance varies a little 254 00:09:40,769 --> 00:09:39,610 bit by lake so you see the blue one the 255 00:09:42,629 --> 00:09:40,779 light blue ones are down here in 256 00:09:45,980 --> 00:09:42,639 last-chance lake whereas those bass 257 00:09:48,030 --> 00:09:45,990 clicks seem to be preserving more 258 00:09:49,500 --> 00:09:48,040 extractable lipid and so we're 259 00:09:51,360 --> 00:09:49,510 interested in sort of delving into those 260 00:09:53,819 --> 00:09:51,370 trends see how they compare to chemistry 261 00:09:57,150 --> 00:09:53,829 and sort of flush out some of these 262 00:09:58,530 --> 00:09:57,160 hypotheses we went in with so though how 263 00:10:00,900 --> 00:09:58,540 much time do I have three minutes great 264 00:10:03,150 --> 00:10:00,910 um so this is hot off the presses data 265 00:10:05,160 --> 00:10:03,160 which is why it's in Excel and not 266 00:10:07,980 --> 00:10:05,170 something prettier so this is showing 267 00:10:11,250 --> 00:10:07,990 you those hydrolyzed lipids just a 268 00:10:15,720 --> 00:10:11,260 subset that have been quantified for 269 00:10:18,329 --> 00:10:15,730 their fatty acid characterization okay 270 00:10:20,009 --> 00:10:18,339 so if we look at these in a little bit 271 00:10:21,750 --> 00:10:20,019 more detail we see that the waters are a 272 00:10:23,430 --> 00:10:21,760 little bit different from the ices a 273 00:10:25,410 --> 00:10:23,440 little bit different from the sediments 274 00:10:26,850 --> 00:10:25,420 and mats in particular I think it's 275 00:10:28,829 --> 00:10:26,860 interesting these sediments seem to be 276 00:10:31,560 --> 00:10:28,839 incorporating some long-chain fatty 277 00:10:32,970 --> 00:10:31,570 acids or sort of mid chain that are more 278 00:10:34,439 --> 00:10:32,980 characteristic of algal primary 279 00:10:36,810 --> 00:10:34,449 productivity when you get into the Paleo 280 00:10:39,150 --> 00:10:36,820 climate literature but you do see sort 281 00:10:41,009 --> 00:10:39,160 of strange Peaks so this is a branched 282 00:10:43,259 --> 00:10:41,019 fatty acid showing up in the ice that's 283 00:10:44,550 --> 00:10:43,269 not really in anything else um so we 284 00:10:46,139 --> 00:10:44,560 definitely see some differences and this 285 00:10:49,620 --> 00:10:46,149 is just a subset so we'll delve into 286 00:10:51,420 --> 00:10:49,630 that in the future and so then the next 287 00:10:53,880 --> 00:10:51,430 steps this is my incoming graduate 288 00:10:55,650 --> 00:10:53,890 student Floyd and so he's going to take 289 00:10:58,139 --> 00:10:55,660 this project over from departing 290 00:10:59,460 --> 00:10:58,149 undergrad and we're gonna do we're gonna 291 00:11:01,500 --> 00:10:59,470 actually look at those intact polar 292 00:11:03,030 --> 00:11:01,510 lipids so this is what I showed you 293 00:11:04,920 --> 00:11:03,040 before this is just the fatty acid 294 00:11:06,600 --> 00:11:04,930 skeleton but lipids actually come in in 295 00:11:08,759 --> 00:11:06,610 big boy molecules like this and there's 296 00:11:11,220 --> 00:11:08,769 a lot of structural variability that is 297 00:11:12,960 --> 00:11:11,230 interesting and you can learn a lot more 298 00:11:15,929 --> 00:11:12,970 about who's making what based on the in 299 00:11:18,149 --> 00:11:15,939 tech polar lipids so yeah and so life 300 00:11:20,339 --> 00:11:18,159 usually they're they're thought to 301 00:11:21,899 --> 00:11:20,349 degrade very rapidly but we don't know 302 00:11:23,669 --> 00:11:21,909 how that works in salt so we're going to 303 00:11:25,409 --> 00:11:23,679 figure it out so we're going to do the 304 00:11:26,789 --> 00:11:25,419 modern sample set and then see how that 305 00:11:28,529 --> 00:11:26,799 extends in time both through some 306 00:11:30,329 --> 00:11:28,539 controlled experiments and then through 307 00:11:31,859 --> 00:11:30,339 an extension into the sedimentary 308 00:11:33,809 --> 00:11:31,869 archives which Alex will tell you a 309 00:11:35,639 --> 00:11:33,819 little bit more about on the bottom of 310 00:11:37,439 --> 00:11:35,649 these course cores are actually quite 311 00:11:40,649 --> 00:11:37,449 old and so we'll be able to track these 312 00:11:42,179 --> 00:11:40,659 bio signatures as they go or as they are 313 00:11:44,029 --> 00:11:42,189 accreted through time to really 314 00:11:46,769 --> 00:11:44,039 understand what degradation looks like 315 00:11:48,689 --> 00:11:46,779 and with that I will thank you for your 316 00:11:52,290 --> 00:11:48,699 attention now so for money and all the 317 00:11:59,599 --> 00:11:52,740 [Music] 318 00:12:11,290 --> 00:12:01,979 all right we have time for a couple of 319 00:12:18,940 --> 00:12:16,540 it's a race hey so can you talk a little 320 00:12:20,830 --> 00:12:18,950 bit more about the specific fatty acid 321 00:12:22,450 --> 00:12:20,840 that you saw in the ice and like why 322 00:12:24,790 --> 00:12:22,460 that might be there or what exactly that 323 00:12:27,220 --> 00:12:24,800 that is I have no idea so literally and 324 00:12:29,080 --> 00:12:27,230 I send me that data like three days ago 325 00:12:30,610 --> 00:12:29,090 and so I plotted up so branch fatty 326 00:12:32,470 --> 00:12:30,620 acids tend to be really characteristic 327 00:12:34,600 --> 00:12:32,480 so they're only made by bacteria you 328 00:12:36,180 --> 00:12:34,610 don't get eukaryotes making those so 329 00:12:38,500 --> 00:12:36,190 that's definitely not an algal marker 330 00:12:41,350 --> 00:12:38,510 why it's in the ice and not in the 331 00:12:43,060 --> 00:12:41,360 fluids I don't know but that was not all 332 00:12:45,550 --> 00:12:43,070 of the fluids and so what I haven't done 333 00:12:47,980 --> 00:12:45,560 is compared like that ice to its paired 334 00:12:50,200 --> 00:12:47,990 fluid to its bride to see you know if 335 00:12:51,670 --> 00:12:50,210 it's like one of those brine pools and 336 00:12:53,740 --> 00:12:51,680 Bass Lake is making some weird branch 337 00:12:57,070 --> 00:12:53,750 fatty acids or if it's something else 338 00:12:59,380 --> 00:12:57,080 so it's a it's a rich data set that's 339 00:13:01,480 --> 00:12:59,390 only gonna get richer as we get all of 340 00:13:03,190 --> 00:13:01,490 the samples unfortunately if for any 341 00:13:05,650 --> 00:13:03,200 GCMs people out there these samples are 342 00:13:07,960 --> 00:13:05,660 really hard on GC columns if they're 343 00:13:09,400 --> 00:13:07,970 just destroying the column so I'm trying 344 00:13:11,230 --> 00:13:09,410 to figure out what is in there that's 345 00:13:13,750 --> 00:13:11,240 doing that I think it's organic sulfur 346 00:13:17,650 --> 00:13:13,760 molecules in addition to maybe some 347 00:13:18,970 --> 00:13:17,660 other stuff so you know suggestions so 348 00:13:24,870 --> 00:13:18,980 it's a difficult data set now to 349 00:13:29,680 --> 00:13:27,850 they're really cool systems my question 350 00:13:31,530 --> 00:13:29,690 is kind of related you showed some 351 00:13:33,820 --> 00:13:31,540 decrease in concentration is there any 352 00:13:38,200 --> 00:13:33,830 extraction efficiency challenges with 353 00:13:40,870 --> 00:13:38,210 some of these salts um it's a good 354 00:13:44,020 --> 00:13:40,880 question and I don't know the answer 355 00:13:47,950 --> 00:13:44,030 the extraction buffers themselves are 356 00:13:50,440 --> 00:13:47,960 pretty salty and so I wouldn't predict 357 00:13:53,350 --> 00:13:50,450 so so the blight ire process we do via a 358 00:13:55,090 --> 00:13:53,360 pretty intense sonication in a in a 359 00:13:57,160 --> 00:13:55,100 single phase liquid that then separates 360 00:13:59,830 --> 00:13:57,170 into a two phase organic extraction and 361 00:14:02,170 --> 00:13:59,840 so I think I mean so these each got 362 00:14:03,850 --> 00:14:02,180 sonicated it's like five rounds 363 00:14:06,130 --> 00:14:03,860 sonicated for ten minutes which should 364 00:14:08,370 --> 00:14:06,140 be pretty disruptive to lipid membranes