1
00:00:00,240 --> 00:00:10,869
[Music]

2
00:00:14,869 --> 00:00:13,249
where we get started I just wanted to

3
00:00:16,730 --> 00:00:14,879
say a quick thank you to everyone who

4
00:00:19,580 --> 00:00:16,740
showed up for the event last night to

5
00:00:21,500 --> 00:00:19,590
volunteer hang out eat pizza I think it

6
00:00:23,090 --> 00:00:21,510
was a really great turnout I had a lot

7
00:00:24,470 --> 00:00:23,100
of positive reviews from the public and

8
00:00:26,210 --> 00:00:24,480
everyone said they had a ton of fun so

9
00:00:27,290 --> 00:00:26,220
thank you you guys made the event and it

10
00:00:31,460 --> 00:00:27,300
really means a lot to me for your

11
00:00:32,959 --> 00:00:31,470
participation second I know this has

12
00:00:35,180 --> 00:00:32,969
been talked about a lot a lot already

13
00:00:36,799 --> 00:00:35,190
but I've literally been tweeting my

14
00:00:39,889 --> 00:00:36,809
thumbs off for this trying to capture a

15
00:00:41,389 --> 00:00:39,899
lot from the event going on so if you

16
00:00:43,189 --> 00:00:41,399
guys follow the account or follow the

17
00:00:47,299 --> 00:00:43,199
Instagram account I will tag you in

18
00:00:49,790 --> 00:00:47,309
anything that I know you're in so please

19
00:00:52,700 --> 00:00:49,800
follow this is the hashtag to have grad

20
00:00:54,559 --> 00:00:52,710
con for just like anything related to

21
00:00:56,840 --> 00:00:54,569
the conference and yesterday during our

22
00:00:59,809 --> 00:00:56,850
sicom panel I tagged everything with the

23
00:01:00,979 --> 00:00:59,819
AGC sicom so if you guys had any quotes

24
00:01:02,180 --> 00:01:00,989
or anything that you really love your

25
00:01:03,979 --> 00:01:02,190
thought was cool that you want to share

26
00:01:08,090 --> 00:01:03,989
I would appreciate it if you'd use these

27
00:01:10,280 --> 00:01:08,100
hashtags okay so as Julia already

28
00:01:12,170 --> 00:01:10,290
outlined we will have the first half of

29
00:01:13,370 --> 00:01:12,180
our talks up until about 10:05 and then

30
00:01:17,060 --> 00:01:13,380
we'll take a quick break and then we'll

31
00:01:18,740 --> 00:01:17,070
have the rest of our speakers so I'm

32
00:01:22,340 --> 00:01:18,750
going to start off today with the three

33
00:01:23,900 --> 00:01:22,350
domains of life so a very simple

34
00:01:25,880 --> 00:01:23,910
breakdown of the three domains which are

35
00:01:28,460 --> 00:01:25,890
bacteria archaea and eukaryotes

36
00:01:30,830 --> 00:01:28,470
that bacteria has no membrane bound

37
00:01:33,110 --> 00:01:30,840
organelles archaea are typically known

38
00:01:34,670 --> 00:01:33,120
for being extremely files and eukaryota

39
00:01:36,770 --> 00:01:34,680
house membrane bound organelles within

40
00:01:40,910 --> 00:01:36,780
their cells and here is my favorite

41
00:01:42,410 --> 00:01:40,920
eukaryote my cat so this is an example

42
00:01:44,330 --> 00:01:42,420
of the Tree of Life this is a

43
00:01:48,350 --> 00:01:44,340
phylogenetic tree which is based on

44
00:01:49,760 --> 00:01:48,360
sequencing of the 16s rRNA gene so again

45
00:01:53,090 --> 00:01:49,770
we have the three domains act Iria

46
00:01:54,560 --> 00:01:53,100
archaea and Eukarya and here's really

47
00:01:56,150 --> 00:01:54,570
quick the central dogma for those of you

48
00:01:59,270 --> 00:01:56,160
who might not be familiar with biology

49
00:02:01,630 --> 00:01:59,280
we have DNA which is the library DNA

50
00:02:06,620 --> 00:02:01,640
holds all of the genetic information

51
00:02:10,100 --> 00:02:06,630
then DNA transcribed into RNA which kind

52
00:02:11,210 --> 00:02:10,110
of relays the message and then RNA makes

53
00:02:12,560 --> 00:02:11,220
you know acids and proteins and

54
00:02:14,750 --> 00:02:12,570
everything which does kind of a lot of

55
00:02:17,300 --> 00:02:14,760
the heavy lifting in our bodies so as I

56
00:02:20,960 --> 00:02:17,310
said the phylogenetic tree is based on

57
00:02:23,480 --> 00:02:20,970
the sequencing of the 16s rRNA gene it's

58
00:02:26,180 --> 00:02:23,490
rooted with Luca which stands for the

59
00:02:27,830 --> 00:02:26,190
last Universal common ancestor something

60
00:02:30,470 --> 00:02:27,840
important to keep in mind about Luca is

61
00:02:34,070 --> 00:02:30,480
that it is not necessarily the first

62
00:02:35,900 --> 00:02:34,080
organism on earth but the organism that

63
00:02:37,820 --> 00:02:35,910
persisted and didn't become extinct so

64
00:02:43,150 --> 00:02:37,830
it's the idea that every living organism

65
00:02:46,550 --> 00:02:43,160
can tie back to a single living thing so

66
00:02:49,610 --> 00:02:46,560
16s rRNA sequencing is this sequencing

67
00:02:52,280 --> 00:02:49,620
of the 16s ribosomal RNA RNA gene and

68
00:02:56,410 --> 00:02:52,290
this is also known as deep sequencing so

69
00:02:59,449 --> 00:02:56,420
it kind of gives us a very accurate

70
00:03:01,910 --> 00:02:59,459
profile it's almost like the passport or

71
00:03:04,340 --> 00:03:01,920
the license of the microbes living there

72
00:03:07,550 --> 00:03:04,350
it tells us okay this guy's here this is

73
00:03:11,330 --> 00:03:07,560
here this is here and it can tell us who

74
00:03:13,010 --> 00:03:11,340
is in an environment so this is the same

75
00:03:15,170 --> 00:03:13,020
tree that was shown earlier but as you

76
00:03:17,060 --> 00:03:15,180
can see with the colors this might not

77
00:03:20,870 --> 00:03:17,070
be clear but this shows the maximum

78
00:03:23,570 --> 00:03:20,880
growth temperature so Green is up to 60

79
00:03:26,210 --> 00:03:23,580
degrees Celsius yellow is up to 75

80
00:03:28,940 --> 00:03:26,220
orange is up to 90 and anything that's

81
00:03:30,770 --> 00:03:28,950
red is 90 degrees Celsius and above so

82
00:03:32,720 --> 00:03:30,780
as you can see within the Eukarya domain

83
00:03:34,820 --> 00:03:32,730
it's mostly green there's a little bit

84
00:03:36,440 --> 00:03:34,830
of color but for the most part you carry

85
00:03:39,729 --> 00:03:36,450
our Musa files which means that they

86
00:03:42,170 --> 00:03:39,739
prefer more mild growing temperatures

87
00:03:43,850 --> 00:03:42,180
over here in bacteria we have a little

88
00:03:45,830 --> 00:03:43,860
bit more color diversity so there are a

89
00:03:47,300 --> 00:03:45,840
little more thermo tolerance and over

90
00:03:49,190 --> 00:03:47,310
here as I mentioned archaea are

91
00:03:51,320 --> 00:03:49,200
typically extremophiles and as you can

92
00:03:55,100 --> 00:03:51,330
see there are a lot of bugs in here that

93
00:03:57,620 --> 00:03:55,110
like hot temperatures so as I was saying

94
00:03:59,210 --> 00:03:57,630
thermo files have our organisms with a

95
00:04:02,330 --> 00:03:59,220
preference of high temperatures ranging

96
00:04:04,850 --> 00:04:02,340
from 41 degrees to 122 degrees Celsius

97
00:04:07,100 --> 00:04:04,860
and acidophiles are organisms that

98
00:04:09,140 --> 00:04:07,110
prefer highly acidic environments so

99
00:04:11,840 --> 00:04:09,150
this is an example of the Yellowstone

100
00:04:14,600 --> 00:04:11,850
National Park hot spring which is both

101
00:04:16,520 --> 00:04:14,610
very hot and very acidic and really

102
00:04:20,360 --> 00:04:16,530
quick this is the pH scale which ranges

103
00:04:23,580 --> 00:04:20,370
from 0 to 6 for acidic 7 is neutral and

104
00:04:25,320 --> 00:04:23,590
then 8 to 14 is alkaline and

105
00:04:28,620 --> 00:04:25,330
settle files are over in this region

106
00:04:30,840 --> 00:04:28,630
preferring high acidity psycrow files

107
00:04:32,760 --> 00:04:30,850
are organisms with a preference of very

108
00:04:35,129 --> 00:04:32,770
low temperatures ranging from negative

109
00:04:37,469 --> 00:04:35,139
20 to positive 10 degrees Celsius this

110
00:04:39,600 --> 00:04:37,479
can be found in like polar icecaps the

111
00:04:41,280 --> 00:04:39,610
frozen tundra the bottom of the ocean

112
00:04:44,280 --> 00:04:41,290
where there are cold seeps anyway that's

113
00:04:46,020 --> 00:04:44,290
just really cold pale files are

114
00:04:48,420 --> 00:04:46,030
organisms with a preference of high

115
00:04:50,040 --> 00:04:48,430
salinity conditions and within the Halo

116
00:04:52,080 --> 00:04:50,050
file designation there are slight

117
00:04:53,400 --> 00:04:52,090
moderate and extreme preferences and

118
00:04:55,980 --> 00:04:53,410
this just depends on the salt

119
00:04:57,870 --> 00:04:55,990
concentration a local example is the

120
00:05:00,360 --> 00:04:57,880
Great Salt Lake which is five times

121
00:05:02,340 --> 00:05:00,370
saltier than the ocean and this pink

122
00:05:08,640 --> 00:05:02,350
color is actually a bunch of halophiles

123
00:05:10,170 --> 00:05:08,650
and the Archaean domain another example

124
00:05:12,030 --> 00:05:10,180
of an external file are alkyl files

125
00:05:14,550 --> 00:05:12,040
which are organisms that prefer alkaline

126
00:05:16,620 --> 00:05:14,560
environments this is an image from the

127
00:05:19,950 --> 00:05:16,630
lost city cruise that the browses in lab

128
00:05:21,330 --> 00:05:19,960
and a few others went on last fall if

129
00:05:22,950 --> 00:05:21,340
you were here for the opening ceremonies

130
00:05:25,710 --> 00:05:22,960
dr. Brazelton showed some videos and

131
00:05:28,050 --> 00:05:25,720
pictures of this place so they're on the

132
00:05:29,850 --> 00:05:28,060
opposite end of the pH scale from the

133
00:05:34,290 --> 00:05:29,860
acidophiles and they're over here in an

134
00:05:36,719 --> 00:05:34,300
environment from nine to eleven so there

135
00:05:39,629 --> 00:05:36,729
are different kinds of extremophiles

136
00:05:41,250 --> 00:05:39,639
there are organisms that don't love

137
00:05:44,610 --> 00:05:41,260
oxygen so they're found in anoxic

138
00:05:48,029 --> 00:05:44,620
conditions there are organisms that live

139
00:05:49,350 --> 00:05:48,039
in low nutrient environments and one

140
00:05:51,960 --> 00:05:49,360
thing that's important to remember is

141
00:05:55,379 --> 00:05:51,970
while these environments are extreme to

142
00:05:56,670 --> 00:05:55,389
us these guys are completely happy here

143
00:05:58,680 --> 00:05:56,680
like this is their happy place they're

144
00:06:01,290 --> 00:05:58,690
on vacation this is what they were made

145
00:06:03,779 --> 00:06:01,300
for so while these appear and then

146
00:06:05,700 --> 00:06:03,789
habitable or uncomfortable to us they

147
00:06:09,600 --> 00:06:05,710
are just having the time of their life

148
00:06:11,339 --> 00:06:09,610
wherever they are so there are some

149
00:06:12,900 --> 00:06:11,349
heavy words within the microbiology

150
00:06:15,060 --> 00:06:12,910
field when it comes to the organisms

151
00:06:17,040 --> 00:06:15,070
like this word keema with no heterotroph

152
00:06:19,379 --> 00:06:17,050
sounds like a mouthful but it can give

153
00:06:21,800 --> 00:06:19,389
you a lot of information about the

154
00:06:24,120 --> 00:06:21,810
organism where it lives and what it does

155
00:06:27,450 --> 00:06:24,130
so a quick breakdown of some of the

156
00:06:30,000 --> 00:06:27,460
terms troph it means nourish litho

157
00:06:31,860 --> 00:06:30,010
literally means eater of rock Auto means

158
00:06:33,779 --> 00:06:31,870
self or self producing and in this

159
00:06:34,999 --> 00:06:33,789
context it's an organism that can

160
00:06:37,790 --> 00:06:35,009
produce their own organ

161
00:06:40,279 --> 00:06:37,800
compounds hetero cannot produce its own

162
00:06:42,649 --> 00:06:40,289
food chemos oxidation of chemical

163
00:06:44,989 --> 00:06:42,659
whether organic or inorganic compounds

164
00:06:46,760 --> 00:06:44,999
an oligo means few so earlier I

165
00:06:49,549 --> 00:06:46,770
mentioned that there are organisms that

166
00:06:52,089 --> 00:06:49,559
can live in low nutrient vironment so

167
00:06:54,260 --> 00:06:52,099
they would be classified as oligo trove

168
00:06:56,689 --> 00:06:54,270
back to that word chemo little

169
00:06:59,480 --> 00:06:56,699
heterotroph chemo oxidation of chemicals

170
00:07:01,399 --> 00:06:59,490
litho eaters of rock hetero cannot make

171
00:07:03,230 --> 00:07:01,409
its own food troph nourish so

172
00:07:04,730 --> 00:07:03,240
chemoautotrophs are organisms that

173
00:07:07,629 --> 00:07:04,740
derive their energy from inorganic

174
00:07:10,040 --> 00:07:07,639
minerals or other geological processes

175
00:07:12,589 --> 00:07:10,050
so here is kind of another little

176
00:07:15,049 --> 00:07:12,599
breakdown of that flowchart so if you

177
00:07:17,600 --> 00:07:15,059
know the energy source and the carbon

178
00:07:20,149 --> 00:07:17,610
source then you can almost designate

179
00:07:22,249 --> 00:07:20,159
where if that organism would be and the

180
00:07:24,499 --> 00:07:22,259
kind of environment that it lives in so

181
00:07:26,809 --> 00:07:24,509
autotrophs make food from carbon dioxide

182
00:07:30,619 --> 00:07:26,819
and heterotrophs cannot make their own

183
00:07:33,170 --> 00:07:30,629
food so earlier I mentioned sequencing

184
00:07:34,820 --> 00:07:33,180
of the 16s rRNA gene another type of

185
00:07:37,459 --> 00:07:34,830
sequencing that's very common for

186
00:07:39,529 --> 00:07:37,469
environmental microbiologist is called

187
00:07:41,299 --> 00:07:39,539
metagenomics it's the study of genetic

188
00:07:43,790 --> 00:07:41,309
material directly from environmental

189
00:07:45,709 --> 00:07:43,800
samples so when it comes to metagenomics

190
00:07:47,600 --> 00:07:45,719
you're taking an environmental sample

191
00:07:50,809 --> 00:07:47,610
and you extract the DNA and you're

192
00:07:52,999 --> 00:07:50,819
sequencing everything so this gives you

193
00:07:54,739 --> 00:07:53,009
kind of a big picture idea of everything

194
00:07:57,619 --> 00:07:54,749
that can possibly go on in this

195
00:08:00,379 --> 00:07:57,629
environment it's an analogy that our lab

196
00:08:01,759 --> 00:08:00,389
uses commonly is that it's like taking a

197
00:08:03,409 --> 00:08:01,769
bunch of puzzle pieces together from

198
00:08:05,959 --> 00:08:03,419
different puzzles throwing them in a

199
00:08:07,820 --> 00:08:05,969
pile throwing the boxes away so you

200
00:08:08,959 --> 00:08:07,830
don't know if the puzzle is complete you

201
00:08:10,489 --> 00:08:08,969
don't know what it looks like and you

202
00:08:11,809 --> 00:08:10,499
don't know how many puzzles or pieces

203
00:08:12,679 --> 00:08:11,819
there are and then trying to piece

204
00:08:16,309 --> 00:08:12,689
everything together

205
00:08:18,469 --> 00:08:16,319
so while 16s is deep meta genomic

206
00:08:20,029 --> 00:08:18,479
sequencing is wide and like I said this

207
00:08:21,980 --> 00:08:20,039
gives you at a Baalak potential of

208
00:08:25,549 --> 00:08:21,990
everything that could be going on an

209
00:08:27,259 --> 00:08:25,559
environment meta transcriptomics on the

210
00:08:31,579 --> 00:08:27,269
other hand is a study of gene expression

211
00:08:33,620 --> 00:08:31,589
which is RNA based and this can tell you

212
00:08:35,689 --> 00:08:33,630
exactly what's going on so right now

213
00:08:37,939 --> 00:08:35,699
we're all alive we're all breathing we

214
00:08:39,889 --> 00:08:37,949
could be skydiving we could be reading a

215
00:08:42,170 --> 00:08:39,899
book we could be taking a nap you could

216
00:08:43,850 --> 00:08:42,180
be getting a root canal or you could be

217
00:08:45,319 --> 00:08:43,860
listening to this talk which I'm hoping

218
00:08:46,890 --> 00:08:45,329
is a little less painful than a root

219
00:08:50,140 --> 00:08:46,900
canal

220
00:08:52,690 --> 00:08:50,150
so again the overview is 16's tells us

221
00:08:54,730 --> 00:08:52,700
who is their metagenomics tells us what

222
00:08:57,070 --> 00:08:54,740
they can do and that a transcriptomics

223
00:08:59,940 --> 00:08:57,080
tells us what they are doing and how

224
00:09:03,610 --> 00:08:59,950
they are doing it right in the moment so

225
00:09:05,200 --> 00:09:03,620
o RP or oxidation reduction potential is

226
00:09:06,910 --> 00:09:05,210
a measurement within an environment so

227
00:09:08,800 --> 00:09:06,920
earlier I mentioned the pH scale which

228
00:09:11,890 --> 00:09:08,810
is a measurement of the hydrogen ions

229
00:09:13,840 --> 00:09:11,900
present in the environment or P is kind

230
00:09:16,360 --> 00:09:13,850
of similar as it's a measurement of

231
00:09:18,640 --> 00:09:16,370
what's going on but instead of what's

232
00:09:20,470 --> 00:09:18,650
going on in the environment it's telling

233
00:09:23,440 --> 00:09:20,480
you how easily electrons are transferred

234
00:09:25,600 --> 00:09:23,450
from one species to another so in case

235
00:09:27,010 --> 00:09:25,610
any you guys remember oil rig oxidation

236
00:09:30,400 --> 00:09:27,020
is lost reduction is gain

237
00:09:32,230 --> 00:09:30,410
we have electron donors which donate to

238
00:09:34,090 --> 00:09:32,240
the electron acceptor and that means

239
00:09:36,640 --> 00:09:34,100
that they become oxidized they're losing

240
00:09:40,060 --> 00:09:36,650
that electron on the other hand electron

241
00:09:42,010 --> 00:09:40,070
acceptors who accept the electron become

242
00:09:46,900 --> 00:09:42,020
reduced when they gain that electron

243
00:09:49,150 --> 00:09:46,910
from the donor so this is really where

244
00:09:52,060 --> 00:09:49,160
di realize that but all I wanted to take

245
00:09:55,420 --> 00:09:52,070
away from this is that the more positive

246
00:09:57,100 --> 00:09:55,430
value the stronger oxidizing agent and

247
00:09:59,380 --> 00:09:57,110
at the same time the weaker reducing

248
00:10:01,660 --> 00:09:59,390
agent and on the other end where there's

249
00:10:03,910 --> 00:10:01,670
a higher negative value it's a stronger

250
00:10:08,310 --> 00:10:03,920
reducing agent and a weaker oxidizing

251
00:10:12,100 --> 00:10:08,320
agent so this is the electron power and

252
00:10:14,230 --> 00:10:12,110
this is kind of the same idea where the

253
00:10:17,080 --> 00:10:14,240
better reductants electron donors are up

254
00:10:19,510 --> 00:10:17,090
here and the better oxidizers better

255
00:10:20,950 --> 00:10:19,520
electron acceptors are down here and all

256
00:10:23,740 --> 00:10:20,960
we really need to get from this is that

257
00:10:27,400 --> 00:10:23,750
the longer the arrow the more energy is

258
00:10:29,410 --> 00:10:27,410
obtained so glucose to oxygen that's

259
00:10:31,210 --> 00:10:29,420
from the top to the bottom so there's a

260
00:10:33,730 --> 00:10:31,220
ton of art of energy to be gained there

261
00:10:35,770 --> 00:10:33,740
whereas with hydrogen gas to carbon

262
00:10:37,930 --> 00:10:35,780
dioxide there's not much going on there

263
00:10:42,030 --> 00:10:37,940
is energy available and present but it's

264
00:10:48,340 --> 00:10:45,580
relating also relating to ORP our oxygen

265
00:10:50,140 --> 00:10:48,350
levels so there are different ranges of

266
00:10:54,040 --> 00:10:50,150
oxygen concentration or dissolved oxygen

267
00:10:56,560 --> 00:10:54,050
within water so there's oxic hypoxic and

268
00:10:58,910 --> 00:10:56,570
a toxic toxic is classified as like a

269
00:11:00,949 --> 00:10:58,920
healthy dissolved oxygen content

270
00:11:03,160 --> 00:11:00,959
means macro organisms can live there

271
00:11:05,420 --> 00:11:03,170
like fish and other aquatic animals

272
00:11:07,550 --> 00:11:05,430
hypoxic is kind of on the range of like

273
00:11:09,829 --> 00:11:07,560
well something could be living here but

274
00:11:12,769 --> 00:11:09,839
probably nothing big would be mostly

275
00:11:15,530 --> 00:11:12,779
bacteria or other organisms and then

276
00:11:18,620 --> 00:11:15,540
anoxic is pretty much nothing going on

277
00:11:21,670 --> 00:11:18,630
there's if there's anything living there

278
00:11:24,319 --> 00:11:21,680
it's definitely going to be microbial

279
00:11:27,470 --> 00:11:24,329
ORP has a positive correlation with

280
00:11:29,329 --> 00:11:27,480
oxygen levels so the higher the oxygen

281
00:11:31,970 --> 00:11:29,339
levels the more positive the ORP value

282
00:11:34,100 --> 00:11:31,980
and then down here it's the same the

283
00:11:36,590 --> 00:11:34,110
lower the oxygen levels the more

284
00:11:38,900 --> 00:11:36,600
negative ORP values and down here are

285
00:11:43,220 --> 00:11:38,910
going to be like a lot of heavy metals

286
00:11:44,660 --> 00:11:43,230
and kind of the more extremophiles and

287
00:11:46,310 --> 00:11:44,670
with that that's all I have for you

288
00:11:48,319 --> 00:11:46,320
today thank you so much so our next

289
00:11:50,660 --> 00:11:48,329
speaker will be Nicole Wagner talking

290
00:11:52,960 --> 00:11:50,670
about meta genomic profiling of the

291
00:11:55,759 --> 00:11:52,970
methane-rich anoxic basin of Lake

292
00:11:57,290 --> 00:11:55,769
Untersee and of ocean world thank you so