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[Music]

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[Applause]

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my name is a nice gentleman I'm a first

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year masters student at the University

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of Alaska Fairbanks and today I'm

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presenting my preliminary results and my

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future methods as this is the first year

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of my master's in my research titled

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predicting optimal growth rates of

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marine bacteria using genetic signatures

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of cold adaptation so to give kind of a

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little bit of background before I kind

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of dive into my methods and results I

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wanted to give a kind of a broad

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definition of the term of sacrifice as

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organisms that grow at cold temperatures

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ranging from about negative 20 degrees

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Celsius to positive 20 degrees Celsius

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and the research into these organisms is

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really broad and really interesting and

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for many different reasons particularly

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because ninety percent 90 percent of our

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Earth's ocean volume is less than five

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degrees Celsius including the Arctic

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Ocean which is at risk right now with

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increasing atmospheric temperatures but

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the primary results and the reason why

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we're all here at this conference in

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terms of astrobiology is that most of

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the water that we find that we will find

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we have found in our solar system is

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solid ice but an ocean such as on

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locations such as Europa are really

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likely to be cold so looking at how

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these organisms thrive in these really

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extreme environments is kind of key so I

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wanted to make a quick note before I get

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started I wanted to say that most of the

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organisms that thrive at sub-zero

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temperatures also live and grow at warm

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temperatures and these are known as

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psycrow tolerance and psycrow trophic

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s-- as you can see with these figure

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these this figure sorry we have a kind

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of a broad range of strains that grow a

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lot of different temperatures in

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different locations and different

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environments and the blue of kind of

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square represents minimum temperature

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the green circle is the optimal

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temperature and the red

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is the maximum temperature however when

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we kind of reduce this figure down a

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little bit we see that the true

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sacrifice are those organisms that

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thrive in that set range of temperatures

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underneath positive 20 degrees Celsius

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lie in saline systems and like sea water

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and sea ice and marine sediment and this

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makes it so that Arctic marine bacteria

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are really excellent isolates and

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proxies to study these kind of cold

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adaptive signatures and probably bio

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signatures that we could use and

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identify later on however I wanted to

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also note that a lot of these strains as

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you saw in the previous figure are there

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we have very few of them currently and

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so in order to address that issue we

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have isolated over 600 strains actually

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in marine bacteria and sequence 50 of

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them so this is a figure by du close ode

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that has been unpublished currently but

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it kind of shows the broad range of

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marine bacteria that we can find in sea

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unfortunately psycho Philly is not a

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phenotype that is really easily

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identifiable which would make my job a

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lot easier

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but as found in a previous study using

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machine learning by Phillip Bauer at L

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in 2015 he found that actually that

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psycho Philly which is kind of the

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orange triangle right there has the

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lowest predictability out of all of the

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okay so why do we do this and what is

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the purpose of this is that if this is

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possible if we can use and predict

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psycho Philly and use it to predict

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growth rates in Arctic marine bacteria

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we could use it to make predictions in

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other uncultured taxa known only from

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meta-genome assembled genomes or max

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these two figures are one that are kind

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of examples that's know these two

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figures are examples of mag's actually

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so this is right here

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this is known as a mag of a psycho

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vector so all of these this broad figure

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actually is when you compare a lot of

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different strains and compare them to

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each other

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specifically their context and they're

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really closely bunched up together it

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can be isolated into one strain this is

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another figure of a set of the same

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psycho factor so the little one in blue

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up there of a mag met at a different

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Assembly graph so I got started in

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formulating my methods by looking at the

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mechanisms of cold adaptation had that

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had already been determined and these

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include Osmo protection through

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accumulation of compatible solutes and

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osmolytes lipid profile changes for

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increased membrane fluidity increased

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increased production of EPS or

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extracellular polymer a substance called

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identification of cold shock proteins

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and the identification of cold active

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enzymes all of these except for the cold

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active enzymes are likely evolutionary

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mechanisms that are looked at either

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vertically or through horizontal gene

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transfer the cold active enzyme has a

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vertically inherit change in amino acid

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usage which I'll get to a little later

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but with how identified all of these

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mechanisms led me to kind of the

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creation of my goal and these so what

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why am I doing this and the goal the end

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product of this study if everything goes

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well would be to create a phylogenetic

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informed predictive model to estimate

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growth temperature ranges and optimal

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growth rates using only gene content and

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amino acid usage and so if this works

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and this could help to lay some

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groundwork for changes in a microbial

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community on structure and function and

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a really rapidly warming Arctic okay and

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I want also wanted to make a quick thing

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clear you'll see in my methods that I

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sequenced multiple strains of the same

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species and the reason why I did that

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and the reason why a lot of people do

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that is to look at the difference

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between the pan genome and the core

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genome most

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bacterial species every new strain is

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going to have genes that have not been

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observed before and the set of all of

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those genes is known as the pan genome

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so the more strains of the same species

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you sequence the more likely you are

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going to have to have that increase I'm

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sorry that increase in genes right there

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well if you just look at one strain if

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you just sequence one strain of the

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species you're only going to get a

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little bit of those genes and just the

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core genome so it's really beneficial to

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strain to sequence multiple strains so

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no good research is complete without a

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prediction and so I predicted so that

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the requirement for increased protein

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flexibility or the requirement to

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predict how psycho philic these bacteria

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are would be by looking at amino acid

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indices or ratios which are publicly

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available through a lot of different

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publications currently and so I am

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currently using these five amino acid

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indices because they were the one that

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was most currently on hand at the moment

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and the easiest to find but all of these

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are really pretty straightforward

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and they'll they'll portray kind of a

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conventional statistic methods but

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unfortunately science is not that easy

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and I will also have to take into

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account what evolution provides and in

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the sense of you're not going to have

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just straightforward this is how the

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amino indices um index kind of brought

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around it's going to come this way and

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then it's gonna come that way to start

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my methods and so to create this model I

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had to identify kind of a core or a

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proxy genus to predict the to create the

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model and so I chose the genus of Co

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alia because this is a bacterial genus

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that is found in cold waters around the

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world especially in the Arctic but it is

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its members are mostly sacra philic and

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hallow philic but primarily its genetic

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code actually reflects the geological

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evolution of polar regions so this would

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help take care of my previous problem

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looking at the evolution of the

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amino acids and so this is kind of step

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by sub go through of my methods you

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start off with your observations of

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course currently we have field

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collections from you javac in Barrow 17

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out of 17 from March 2012 have been

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sequenced 1 out of 25 from April 2015

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have been sequence that's currently in

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progress determining their phenotypic

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traits and determining how well they

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grow at various temperatures is also in

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progress so right now I have about 19

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different strange sitting in my fridges

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and freezers and I'm looking at the

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temperature and how well they're growing

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I'm further doing the sequencing of all

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of these strains using DNA extraction

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library construction and annotation

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using the Patric portal in addition to

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doing primarily lab laboratory work I'm

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also using 44 additional Co alia genomes

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that are downloaded from a public

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database and with those and with my

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laboratory work I was able to create a

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phylogenetic tree comparing all of those

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I was also able to synthesize cold

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adaptation indices all from all of these

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genes and put them together and compare

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each and these are figures that I will

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be showing momentarily so once I have

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all of this data the growth rates and

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the cold adaptive indices of amino acids

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I'm going to take all that data and put

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it together into a phylogenetic

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generalized least squares regression of

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cold adaptation indices to create that

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model so that you just give me the

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genomes I can tell you what temperature

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it'll grow best at and how quickly it'll

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grow so this is a heat map of the

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preliminary results so at the very top

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right here these are the koalas that I'm

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currently studying this is a heat map of

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all of the strains from a collaborator

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of called charles suite which isolated

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several hundred strains of bacteria from

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Ikea and Chesapeake Bay and right now we

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we have sequence only 60 of them and

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this is what we are presenting right

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here is a phylogenetic tree comparing

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all of these sequences and the red

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represents how closely related they are

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if and the yellow represents if there

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was a fluke or if even if they weren't

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closely related at all actually this is

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the big preliminary results at the end

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of my first year of my Master's so these

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this is a histogram of this of all of

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the amino acid indices that are labeled

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down here I apologize it you cannot read

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them right here these are all the Koala

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strains these top ones the BRX are the

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ones that I'm currently growing while

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the rest of these are from public date

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available databases but you can see that

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these kind of histograms and curves are

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really closely related and so the minor

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differences of the distribution of these

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amino acids were sequence the only real

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one is this one right here which is kind

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of new and I haven't quite defined why

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that is so that's yet to come but this

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really suggests that phylogeny in

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general so large phylogeny plays a more

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important role in determining these

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amino acid compositions then the then

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does the adaptation to local conditions

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because these oh my god I'm sorry yeah

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these are taken from Chesapeake Bay but

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these are from public available

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databases so these are taken from really

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a wide variety of environments and

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locations and they still managed to have

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kind of the same structure which is kind

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of incredible in my opinion so the next

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step since this study is really in its

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infancy is to complete the growth rates

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measurements of all the ones that I have

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sitting in my fridges and freezers and

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sequence all of those strains to catalog

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all these cold adaptation related genes

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within each of the genomes test for

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differences in adaption indices of

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individual gene families examine other

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genre that have more phenotypic or

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genotypic diversity Prem

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all of these are so similar to each

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other it's going to become beneficial to

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use a different and apply different

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genus and right now the one that I have

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on hand is most likely to be used is

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psycho vector and finally incorporate

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all of this data into a predictive model

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and with that I'd like to acknowledge my

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committee my advisor dr. Eric Collins

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dr. Charles sweets and Lee's Duclos oh

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and Jody Deming and Shelley carpenter

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for sample collection and helping me and

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as well as my funding sources and with

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that I'll take questions thanks to

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having any questions for a nice if you

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could come up to the microphone in the

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center and say where you're from and

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your name the stage one oh yeah yeah

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that would be why thank you yes so it's

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an interesting observation so it is know

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we've done this data analysis multiple

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times that things that reside or

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bacteria that resides in cold

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temperatures or hot temperatures tend to

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share amino acid composition across the

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genes that are relevant for activity in

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these types of environments the fact

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that their evolutionary similar bacteria

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tend to not have the same composition

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across everything great it's actually

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expected so there is a lot of horizontal

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gene transfer and implementation which

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is also driven by so I'm kind of curious

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what is the big

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ooomph right of these genes that are

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looking not like their genome but

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similar across even though the genomes

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are similar you know I'm not quite

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understanding your question so yes we

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know about the adaptation so what is the

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the big deal about them being different

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from the genome similarities so how

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important is it that the genes that are

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useful for adaptations or particular

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environment are different from the

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genomes that they come it's important in

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the sense that they they use different

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factions I'm also admittedly new to the

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field so these is probably something

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I'll take a closer look at and identify

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later on in my research oh I'm sorry

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yes so it'll be something that I take a

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closer look like I'd love to chat with

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you actually later on if you have a

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moment to talk about that yeah

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absolutely yeah so so the big deal kind

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of looking forward to if you identify

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the genes that are similar you can

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identify new yes so I think that that

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would be really cool so I think that's

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all the time we have for questions