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[Music]

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[Applause]

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my name is Jack smelly and I'm at st.

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Louis University with the bomb lab and

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we have been working in collaboration

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with the Burke lab for some time on

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these fa be binding app tumors are f80

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binding RNA aptamers that increase

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potentially can increase the the redox

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potential of the bound flea oven so I

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guess for starters just give a little

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bit of background although not so much

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because I feel like a lot of people are

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adequate with this out what we're

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following here is RNA world hypothesis

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in that before president day cells with

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RNA DNA and proteins there was simpler

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system in which RNA could have

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contributed to being both the genetic

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material and also have catalytic

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function and also I also put the the

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peptides in that little protocell there

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just show that there might have been

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peptides around but not necessarily a

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formed from the RNA at that time some

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evidence of this is the ribonucleotide

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cofactors that we see today so all these

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cofactors fa d na d and then coenzyme a

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they all have p adenosine portion in it

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which is right with nucleotide co-factor

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is kind of like a prehistoric fossil if

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you will of the RNA world current cells

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and proteins use these cofactors in

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order to metabolize reactions so they

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essentially what they do is they have

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differential binding towards either the

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oxidized or reduced formed of these

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cofactors and in doing so they can vary

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the redox potential of that cofactor in

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order to carry out a wide variety of

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metabolic reactions and so and so the

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the idea behind this project is that if

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proteins can do it and really utilize

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the variability that comes with changing

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the redox potential can RNA also do the

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same thing because that would be

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extremely beneficial it's really kind of

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pushing forward with the RNA and and how

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it evolves from just you know simply

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finding things to it to actually

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catalyzing reactions

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such so the selections I'm just gonna go

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through really briefly because this was

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done well before I was even an undergrad

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but the Berk group identified a handful

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of RNA aptamers that preferentially

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binds to the oxidized fe D over the

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reduced fadh2 as you can see here so

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this is just an inline probing gel if

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you don't know what it is essentially if

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the band is dark here that indicates

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that the RNA took on a different

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structure in that conformation and

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whenever it was cleaved atom so in this

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Lane right here is the oxidized FA D and

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then here is reduced fadh2 and you can

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see that at similar concentrations we

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have different cleaving patterns which

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indicates different conformation the RNA

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that shows that the this RNA aptamer is

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preferentially binding to the oxidized

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fe D over at the reduced fadh2 and and

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just through inline probing they got

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rough dissociation constants of about 30

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micro molar for the oxidized FA D and

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greater than 500 micro molar for the

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reduced form now they're not you know

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super precise numbers but there's a

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there's a clear distinction that the

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these after MERS preferentially binds

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the oxidized form over the reduced form

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so now this is where I took over we

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decided to first look at UV vis of this

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so what I have appear structures of FA B

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and then 3 3 RNA aptamers that bind to

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FA D this X to be 2 right here was the

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one from the previous slide so this is

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the one that preferentially binds to the

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oxidized flavin over the reduced this F

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test one down here is a another one from

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the Burke lab they found that there was

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no difference between the oxidized and

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reduced binding and then this 27 F 81 up

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here the Burke lab originally it was

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proposed to be an Fe D Optima but they

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found that it actually is more than

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likely actually binding to the adenine a

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portion of FA D so we had three RNA

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aptamers that we want to look at and

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looking at ub vis we see that once you

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mix together the

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be in the RNA the ones that bind to this

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isoh locks Azim ring system here

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actually shift the uv-vis spectra of

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this and you know this is indicative of

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you know hydrogen bonding or ionic

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effects on different phases of fa D

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really some important parts is that this

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the X to be two Optima shifted the

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Maxima from 448 to 456 nanometers and

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then there's this presence of a shoulder

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at 482 nanometers so we had a good kind

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of baseline is to gauge whether or not

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binding is occurring so we decided to

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look at some kind of characteristics of

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binding with this app tumor so a couple

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of things we looked at is the time that

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it takes to bind and it's extremely fast

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probably within the order of seconds

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this is me just quickly pipetting RNA

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aptamer into a qubit and then pressing

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measure as quickly as I can

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and within 20 seconds we see this full

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peak shifts over to the fully bound form

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so really this this experiment was

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probably just diffusion limited as to

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how quickly it can actually diffuse to

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the solution but we know that it is

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extremely quick at binding and we know

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that this peak shift is indicative of

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binding because under denaturing

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conditions the peak will shift back

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towards that of PFA T so if we heat it

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up and it will shift its free Fe D let

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it cool down it will go back to the

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bound states and then also eight molar

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urea cetera et cetera so another thing

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we looked at was the divalent metal

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dependence so these selections were done

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with magnesium so we wanted to see how

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dependent they were on the divalent

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metals and we saw obviously with the

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increasing diving lit metals we get more

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and more binding with that at about 10

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millimolar kind of maxed out there was

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no change in binding there so interested

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in e i titled this the IV metal

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dependence instead of magnesium

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dependence because it also works with

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manganese calcium zinc and nickel so all

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of those diability metals induced

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binding it really didn't matter which

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one we use that they all caused the same

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amount of binding there and this was you

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know proven where we just add in an

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excess of EDTA to

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Tukey laid out the divalent metals and

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then that would shift it back towards

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that of free fe d another interesting

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point is that the binding remained

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unchanged between pH is 4 and 10 so

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there was no effect on the on the on the

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peak shifts there between that and

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really that's that's the range that I

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put because experiments at pH 3 and

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lower or pH 11 and higher just degraded

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the RNA immediately so really at the pH

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ranges where the RNA was happy it was

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fully binding home with the flavin and

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and again that's divalent metal

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dependent at all those PHS so the next

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step we took was to do some mutations to

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kind of gauge where the which

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nucleotides were important for binding

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so this is the predicted secondary

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structure and essentially what we did is

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we just did some point mutations along

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these loop regions here and then some

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base swaps in the base pairing regions

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either constructive or destructive

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towards the secondary structure and in

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short this is what we saw so red means

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that that mutation effectively killed

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the binding there was no longer any peak

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shift whenever we introduced it blue

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indicates partial binding so there was a

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small peak shift but not significant to

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that of the parent Optima and then green

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indicates that there was full binding

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retain so there was still the full peak

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shift that was there and these aren't

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very interesting because the proposed

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binding site is up here in these loop

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regions so down here that's you know it

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doesn't really affect the secondary

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structure too much what was really

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interesting though was these two kind of

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outliers just kind of randomly placed in

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there and when looking at the uv-vis of

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each of these mutations we can see that

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the L 14 Cu mutation actually shifted

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the peak a little bit more and the

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shoulders a little bit more pronounced

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and then the L 24 you a mutation the

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Maxima is about the same but the

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shoulder here is not as prevalent as

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that in the mutation so now I'll quickly

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go into how we determine the redox

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potential Devon flavin

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so what we use was xanthine xanthine

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oxidase redox si

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it's uv-vis based assay but in short

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xanthine oxidase will catalyze this

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reaction here

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if you remove oxygen from the system and

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place in a high redox potential dye like

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methyl violet in here it can use the

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methyl violet in catalyzed reaction and

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then you have this reduced methyl violet

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in a species that's in solution if you

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have your flavin and then a redox active

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dye that you can monitor the methyl

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violet gene will then go and then react

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that the redox potential dye is known

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whereas the flavin is unknown we can do

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is then compared the two nurse equations

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with the dye and the flavin to each

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other whenever you plot these log terms

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against each other the y-intercept is

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getting equal the difference in redox

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potential between the dye and the and

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the flavin so so a couple things one

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this has been used on flavor proteins

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before but not on apt tumors it's

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important to pick a redox dye that's

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close in redox potential to that of your

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flavin otherwise then the dye can react

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with the flavin or vice versa and then

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essentially so the absorbance change is

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how we're good to see that ratio of

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oxidized to reduced so here's what a

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spectra just kind of looks like as time

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progresses the absorbance goes down so

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this is f ad with a redox dye

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anthraquinone - so folic acid which is

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essentially once it gets reduced it this

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starts to come up right here and and

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basically what we do is we pick the I

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suspect this points for each the redox

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dye and the F ad and measure the other

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one at that point so essentially an I

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suspect this point is 4f ad no matter

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what the ratio of oxidized to reduced is

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it's the absorbance is get a remain

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exactly the same so we measured the dye

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at that location so that's just a

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spectra for that one and then this is

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for the optimal with F ad I guess just

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one thing to note is that we still see

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the characteristic binding peak shifts

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there even though throughout the

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entirety of the of the reaction going on

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so we know that it's still binding with

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though this is just a comparison of pots

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just to see kind of how the data is

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spread and to see how much of a

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difference there actually was between

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free f ad here and then the app de Mer

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with F ad and then this is just the

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results with the Optima and then the

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mutations here so what we can see is

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this F test one which was the Optima

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that didn't had no preference between

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the oxidized and reduced Flavin's we can

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see that there was little to no change

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in the redox potential that was measured

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of F ad the X to be to mutant cause

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negative 12 millivolt shift in redox

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potential and then the the l14 CU mutant

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which was this one right here actually

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doubled that redox shift so there was an

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minus 24 millivolt shift in potential

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interestingly those this 24 you a

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mutation actually killed the redox shift

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so this one while it still was binding

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to F ad this mutation essentially lost

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that that distinction between the

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oxidized and reduced forms of F ad and

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so like just really to kind of point out

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that the the Optima here and then this

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mutation caused us enhance electron

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transfer of this so we essentially you

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know it just shows that the binding of

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this AB temir changed redox potential of

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the other bound flavin compared to you

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know that in solution and and that you

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know this can kind of really just be

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there this is more just beginning

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experiments and whatnot but you can

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imagine if this is like a components on

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a ribozyme that can bring in this F ad

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with with a different redox potential in

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order to catalyze some kind of reactions

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all right and then just to finish off

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thank st. Louis University bomb lab

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Burke lab University of

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missouri-columbia and then on NASA as

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well for the funding and with that I

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Thank You jack we have time for maybe

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so the rate and the rate of electrons

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like how how long that yeah exactly so

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actually so right so the in you're

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talking about like the assay essentially

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in that that I was showing so the assay

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the actually idea in order to get good

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results is actually to keep that as slow

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as possible and if there is a difference

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it will show up and the reason why is

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because we want the flavin and the dye

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to be kind of reducing at the same rate

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what's gonna happen though is but

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they're not an equilibrium right at the

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beginning that's when one is going to

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I mean I'm not entirely sure like if if

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I were just to like I mean it should be

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pretty quickly if I were just to put

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like a highly reduced species in there

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right so actually you can actually kind

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of gauge that as to how quickly each

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species is being reduced by in those

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plots whenever you plot them if it's a

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slope of one that means everything is

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reducing at the same rate which means

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that if there's not a slope of one that

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means something is reducing quicker than

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the other thing and it's not a very good

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test and it's not really showing what's

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actually happening and all these that we

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did all the mutants and everything they

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also a slope of one on that indicating

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that everything is is reducing at the

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same rate throughout the reaction so