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WEBVTT
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You
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You
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You
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You
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I
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Yes, sir. I'm back again. We got to finish this video
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And basketball is over one of the boys didn't want to play king of the court, so we're back a little early
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And that's okay. That's okay. I don't mind at all
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Welcome back to the show
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This is gigo and biological a high-resistance low-noise information brief brought to you by a biologist
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We've been trying to review free on protein biology and in so reviewing
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We have been listening to one Susan Linquist as well as one Stanley Prouzner as
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Well as some other people in the current COVID pandemic narrative like Stephanie Sinev
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Who have been speaking out rather vocally about the potential for the spike protein to
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generate pre-on like
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situations or neurodegenerative disorders and
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Amyloidogenesis as well has been tossed around as something that is possible so
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We've been listening to Susan Linquist
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Because she's very interesting from the perspective of her model of the disease her model of the disease is actually yeast
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Which has many of the same cellular components that we do
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But let's keep in mind that yeast is a single cellular organism and so there's a lot there that's not gonna be there as well and
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there are gonna be
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machinery and communicative devices and communicative mechanisms that aren't there and our cells are the analog or homolog rather will be
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will be different
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And so what she has identified are heat shock proteins which seem to be proteins which are activated
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By acute exposure to warmer temperatures of yeast and other
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bacteria and plants in culture and
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She has extrapolated this to the role of chaperones
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so proteins that prevent protein misfolding and protein aggregation and so she's
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Trying to use yeast as a model system for when chaperone proteins prevent
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the aggregation of
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Misfolded proteins and those could be amyloid proteins. They could be pre-on proteins
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They could be whatever protein that we decide to look at so here
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SUP 35 is is titled a self-assembling amyloid
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But we haven't actually defined what an amyloid is and if you go back to the previous
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Discussion where we started with the first 13 minutes. Oh, we're not defining what amyloid is
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We're not defining what pre-ion is except for the fact that there is an amyloid beta
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protein in the brain and there is a pre-on protein in the brain and
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But other than that, we're not talking about whether SUP 35 is also an amyloid
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Or whether we're just calling it that and it's unfortunate that we're not talking about it with more precision
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But here we go right where we left off. Thank you very much for coming back
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Not just a mess of aggregates
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They were very highly organized amyloid filaments and they were organized in a very interesting way because the central spine of that filament
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Was that region of the protein that previously been shown to be essential for the inheritance of the white trait?
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And the functional part of the protein that's normally functioning in translation is stuck out on the outside
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So when this protein gets get into assembled into this this amyloid fiber
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It can no longer get to the ribosome and there's no longer functioning
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So that's a lot of protein there that instead of being a sub component to a ribosome is now
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assembling into a a fiber which is which is an interesting positive and
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We were then able to actually monitor the assembly kinetics of this protein and we found that
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The protein initially assembles in a test tube very very inefficiently and very very slow
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We took hours and hours and hours with protein to assemble
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But now the question is is this pure protein?
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Is that the way that the protein exists in the cell?
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Probably not so this is again an in vitro preparation looking at pure protein and its behavior
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Might be different the key thing that I think explains the ability of this protein to serve as an element of genetic inheritance
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Is that lunch? Oh if you take a very small amount of this
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Preassembled protein and add it to the start of a new assembly reaction this one right here
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But you see is that boom the preassembled fibers have the capacity to completely very very rapidly convert all the other protein
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That same state and so this is where the idea comes from
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the idea comes from yeast and
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Whether or not pre on protein and other examples of this kind of phenomenon in protein folding exist in nature and underlie these
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Other disease states is completely
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Probably not not founded in experimental evidence, but found it in conjecture based on what is done in yeast so pay attention carefully
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so
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Now you can begin to see how this could explain the inheritance of this trait because if you have a soluble protein that's functional in the cells are
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Red and an insoluble protein that's not functional so that the cells are white you make those cells together and
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Then you sporeulate and segregate the genomes
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Well, the protein has served as a template to change the protein in the other cell type
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And so that when this cells spore late all of the progeny are going to be white is Brian Cox
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I'd shown and it doesn't segregate with the DNA doesn't matter with which which cells get which chromosome because the trait is not based upon the inheritance of a DNA change
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It's based upon the inheritance of a protein with an altered conformational state and how we just be one of four figures in this
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Is that but if the altered
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Confirmational state is requires the presence of the other
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Confirmational state and the other conformational state induces that conformational state and its aggregate
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It doesn't sound like a really nice kind of inheritance. You're not inheriting like a function or a are these proteins now serving as stop codons
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Or are they actually interrupting you see that's that's what's interesting. We're doing now
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We're we're using this as a model of genetic inheritance that doesn't use a nucleic acid, but we're not really
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using a
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Natural example of it. We're using an in vitro example. It happens in a laboratory and we're extrapolating to
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Natural systems and is it really possible that?
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Let's go on
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104 controls that amyloid state I told you that it saves cells from heat shock by now
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He just called it she just called it an amyloid state
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So I'm not sure that that has been substantiated as a term yet
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Aggregating proteins it also can disaggregate those amyloids. So in fact, it can cut them a little bits and pieces
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So here are fibers of that protein amyloid fibers very tough difficult to
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dissolve or
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Chemically you have to really go through incredible lengths to get them to dissolve
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But here's what H2O4 doesn't it chops them until tiny little pieces and that allows them to be inherited and to form the template
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That goes into the daughter cell and allows the daughter cells proteins to change
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So the whole thing putting that together then looks like this you have a reds. I don't understand the
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but the fibers don't exist, right, so
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When do they chop up? It's weird cells that are carrying a particular gene and when ribosomes do what they're supposed to do the translation
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Termination factors in a soluble state it tells the ribosomes to stop when the ribosomes see the stop codon
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But that protein can assemble into this self-repetuating amyloid and when it does
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There's not very much of the translation terminations we have to round
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And so quite a few of the ribosomes wind up reading through that stop codon ignoring it that changes the cells from having a red pigment
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They're having a white pigment and so that's the only stop codon that gets affected
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Aren't there other stop codons for other proteins that are made by the yeast
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Doesn't it have a lethal effect on other
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Proteins that don't stop where they're supposed to stop see that's the part about this model that doesn't make sense already to me
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If this is a stop codon, is it particular for one protein?
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It's a stop terminator protein assembly protein for
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Ribosomes that's only for one protein or is it for all pro if it's for all proteins and all proteins will have an altered I
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Don't know I don't know
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Now
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Cells turn white and the next key the inheritance of this is that the self-templating amyloid protein is actually cut by HSP 104 to allow
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It's orderly segregation into daughter cells for inheritance and in fact with Helen Sable
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We overexpress this protein to a point where it made massive
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Assemblies amyloid assemblies in the cell and and use some very very sophisticated imaging techniques
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demography
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To suggest that just like polytene chromosomes larger assembly the polytene chromosomes give us our first view of
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The organization of DNA and in chromosomes
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We think these larger assemblies are giving us the first view of the way in which the an attribute
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I was sophisticated mitotic apparatus that breaks these fibers apart is working
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But in any case
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It's we want to force key to it, but it's not the only key to it
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There are multiple other proteins that are involved in helping these so those are only there during mitosis
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She said mitotic processes so during cell division
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those those which she calls amyloid fibers are broken up by
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HSP 104 but not in the normal state in the normal state
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They stay like that and there's no terminator and so they read through it's a very interesting model of what's going on without a whole
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Lot of explanation for why it would do this other than a color
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These amyloid fibers to be partitioned to be ourselves in a very orderly way sophisticated mitotic apparatus with Helen
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Sable hmm sophisticated mitotic apparatus sounds like voodoo guaranteeing the inheritance of the trait that's caused when this protein changes its conformational state
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So this provides a completely coherent biochemical explanation for this that is called
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insistence in science completely coherent mechanism. There's nothing wrong with my model
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My model has no holes in it. My model is seamless. Wow. What a weird statement. Is it really responsible?
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Is it the only thing that's going on?
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We did a lot of things we had mutations in the prion that didn't assemble very well
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And they could not inherit the trait and get ones that caused it to assemble more and they more like they didn't have the trade
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We did all sorts of things
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But let me just tell you about one line of evidence that that was particularly fun
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We figured that well if this really was responsible for that that new trait
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This this protein assembly process and we should be able to use that knowledge to create a new prion all of our own
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And so what we did was to take the sub 35 translation termination factor and in the genome
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We deleted the prion element from that strength is we didn't want it to interfere with our new prion
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We're going to be making and then we took glucocorticoid receptor
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Which is a steroid hormone receptor from rap and asked whether or not we could monitor its activity in a yeast cell and see it
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Change in its activity state when we fused it to that domain, which we now call the prion domain of this protein
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Which is responsible for this by stable state and sure enough
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We had a recorder in there that when the glucocorticoid receptor was working
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It would turn the cells blue when the glucocorticoid receptor was assembled into a self-repetuating aggregated template
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If the cells became white because it was no longer working and moreover
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They passed that white state onto their project in a very very stable way
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So they could either pass on the blue state or they could pass on the white state
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So the whitesmen led another wonderful experiment. They took the cell walls off of yeast cells and
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They did a protein-only transformation assembling the protein into those fibers that I told you that we need earlier
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They made them under a couple of different conditions
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And they used those fibers that stuck them into the yeast cells
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And they were able to show that the cells turn from red to white in a heritable way. So that protein only transformation
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Really was another nail establishing the coffin establishing that this another nail in the coffin
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She means that they're establishing the possibility that proteins as they fold differently can also be inherited and that
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Inherited folding difference can be passed on to generations whether or not it's causing other proteins to fold
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Differently is not always the center of their model and they go back and forth between that that is
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Sometimes required sometimes assumed but they are doing it in the context of highly manipulated in vitro models of
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yeast and yeast without cell walls and yeast with over expression of these proteins and yiddie yada yada
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So keep in mind everything here needs to take be taken with a teaspoon of salt
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Genetic trait was due to the inheritance of a protein with an altered transformation
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Now here we have this pre-owned protein as I mentioned, it's a translation termination factor
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Really important factor in this other determines when ribosomes will interpret stop codons properly
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Now the question is that that could be the n-terminal domain
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Of the pre-owned protein that that prisoner's studying. I'm not really sure she hasn't made that really clear to me yet
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If this is the whole protein and then that's the n-terminal domain
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Then what she did was she added
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the n-terminal domain to
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To the glucocorticoid
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receptor see
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the n-terminal domain is what they cut off of
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the pre-owned protein in
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In
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Stanley Prusner's lecture and then after they cut the n-terminal domain off it assembled into the rods
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Here
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She's saying that they assemble only when it has the n-terminal domain and then when the n-terminal domain actually determines whether or not
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They fold incorrectly, which is interesting
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I
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I'm not really following at this as parallel and and
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Confirmate like they're not confirming each other in a way
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Here we have this pre-owned protein as I mentioned it's a translation termination factor
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Really important factor in this other determines when so the c part is conserved in all eukaryotes in the n and m plus
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Minuses only in yeast I think is what she's saying
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Which is also very curious because again remember
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cutting off the n-terminal domain of the eukaryotic version of this in in
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Stanley Prusner's experiments is what made it form the rod like things that he called amyloids
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She's suggesting that actually it's this
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pre-owned forming conserved part over here that's not conserved in eukaryotes
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that causes and controls the pre-owned like inheritance of these protein folding schemes that's
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We better read we better make sure we're right, but i'm pretty sure we're right
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I think that we just did this today and yesterday so it's pretty hard for me to believe we're wrong
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Which is uh definitely not
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Jiving parallel here ribosomes will interpret stop codons properly
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And it's conserved in all eukaryotes and here we have this domain stuck onto the end of it
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Uh, and then also remind remember that in Stanley Prusner if indeed the pre-owned protein is a
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They
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Stop factor for ribosomes and not just this
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Unknown protein that sits in the membrane and and changes into a
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It's aberrant form inside of these clathrin coated
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um
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invaginations
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Think about this
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Where is all that story?
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Where is all the story about how pre-owned protein is expressed on the outside of the cell and then gets into clathrin
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Invaginations and theirs where it turns into the pre-owned they don't really understand it
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Yeah, but that's what we think
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Is that all gone now?
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And now we have this yeast model
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Or by the way for 800 million years of evolution and its regulation base just be 104 has been conserved for hsp for 800 million years of evolution
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Uh, and so the question becomes why why in heaven's name would cells allow this
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Translation termination factor to suddenly be sucked out of solution so that ribosomes aren't performing properly
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And it occurred to us that this had to have some meaning
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Uh, because otherwise yeast can very very rapidly evolve and they could have acquired mutations in it that pre-owned domain that would have still allowed the protein to have its translation termination function
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But not allowed it to be sucked up into these aggregates
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So one thing that occurred to us was that the read-through of ribosomes might be occurring not just on those
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That one messenger RNA that that Brian Cox had first discovered
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But actually it might be happening on messenger RNAs that were coming from all over the genome
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And in that case we might expect to see some really new and interesting traits
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We started growing strains in different conditions not on rich media in the laboratory
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So here's an example of a really wonderful trait, uh, that's caused by the appearance of this same prion
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And uh, you can see that the colony morphology of these cells has changed completely
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Uh, the cells that normally look like this will create colonies like this
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Uh, created very very different types of colonies that adhere to each other cells adhere to each other. They stick to each other. They have different abilities to grow in different environments
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And here's an example of the fact that these prions actually spontaneously appear every once in a while
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And we tried brewing cells under all sorts of different conditions kind of like the story I told you about it just being 90 them a while ago
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Uh, and we found that in different strains we got completely different traits
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And that makes sense when you realize that the reasons that are downstream of stop codons
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And not normally under much selective pressure. They're free to vary quite a bit
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And so changes in those downstream sequences might be expected to accumulate over the course of evolution
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And then when the cell switches into the prion state by perhaps sure happenstance
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Um, that will cause the creation of many new phenotypes
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So, um, get lots of different traits and lots of different strains and each the traits and different strains were completely dependent upon the genotype of that strain
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So what we think is that this prion allows cells to sample genetic variation. I don't know. Don't get too excited about this, right?
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This is something that could could be one or two proteins slightly different or
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One or two assemblies slightly different or an enzyme functioning or not functioning
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And so the morphology of the colony changing this must shouldn't be over interpreted as much
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wide scale
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Uh, it's not a change
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It is a change don't get me wrong, but don't think of it as like, wow, they must have changed every single protein
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I mean, that's not very likely
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Um, I don't think that all stop codons are now missed as a result of this
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And so it's very tricky for me to interpret exactly how much she knows about the change that occurs when it
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Goes into the prion state that the yeast does
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Plicated traits that would be very hard for them to acquire by individual mutations
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For example on a stop codon that would cause one individual messenger RNA to be read through rather
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Multiple messages being read through at the same time could create quite complicated complicated traits
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The other thing could be that reading through in yeast is not the same as reading through in our cells and reading through in our cells
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Could be regulated by other means or more specific and and varied means and so again
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What we're really looking at here remember is not the discovery of an infectious disease
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What we're discovering is an added layer of complexity to the irreducible complexity of our own biology
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Represented in a very simple eukaryotic model the yeast
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And as long as you see it that way, then I think susan's presentation is really cool
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But if you see it as okay, so what are these people talking about with regard to prions in the spike protein
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You can clearly see that whatever susan is talking about makes them liars basically
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And in some weird
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Need to have a worst-case scenario. They can't be genuine in their belief that there is
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Some sequence in the spike protein that they don't have to be very specific about that they can call a pre anogenic epitope
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And imply that this thing has the propensity to do
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What she's explaining these particular proteins and these particular combinations of proteins in yeast
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seem to do
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So if this mechanism has really existed this prion has existed in order to create evolutionary novelty
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And the ability to sell to sometimes people who exploit new environments then evolutionary biologists
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And we ourselves realize that if this was how but this purpose this prion was serving such a purpose in evolution
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Then switching should increase with stress that as it should be tuned such that
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Under stressful environments the cells would be more likely to switch into the prion state because they would be more likely than need
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Novel new phenotypes under stress. And so we asked whether or not it does and the answer to that was yes
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And then the question of course becomes how but for us that it's a pretty simple logical explanation for that
22:25.520 --> 22:30.480
And that is because of how stress influences the protein folding and protein homeostasis pathways of the cell
22:31.120 --> 22:33.920
So stress increases the likelihood that proteins will misfold
22:34.240 --> 22:38.800
Making it more likely that those prion domains will now suddenly acquire that that aggregated amyloid state
22:39.200 --> 22:41.040
See so are they
22:41.040 --> 22:45.360
Misfolding or is it an evolutionary thing that is genetic inheritance?
22:45.360 --> 22:47.520
You see they're flip flopping between
22:47.520 --> 22:50.800
Is it a good thing or a bad thing? Do we understand or do we don't?
22:50.800 --> 22:53.680
Is it really just a disease or is it aberrant or what?
22:54.160 --> 22:56.160
And so it it is because
22:56.720 --> 23:00.320
Their model of what's going on does not really work
23:00.320 --> 23:02.320
I
23:02.320 --> 23:06.560
Want you to believe it's really simple and that what did she say? Why did she say back there?
23:06.640 --> 23:14.560
It's a it's a definitive model of of something something where we're going to find that it is a completely coherent mechanism
23:15.760 --> 23:19.120
Completely coherent mechanism
23:20.720 --> 23:24.640
It's very insistent. That's for sure perpetuate that state to the daughter self
23:25.360 --> 23:27.200
Stress also
23:27.200 --> 23:29.040
increases the
23:29.040 --> 23:31.440
rate at which cells lose prions because
23:32.800 --> 23:39.200
the stresses cause induction of chaperone proteins and induction of first-integration mechanisms and all sorts of other things that influence protein homeostasis so
23:39.760 --> 23:43.200
These prions which normally appear only relatively rarely
23:43.680 --> 23:47.840
Would just because of the very nature of protein homeostasis and the way in which stress influences protein homeostasis
23:48.000 --> 23:51.280
Be more likely to appear and disappear under conditions when the cells might need new phenotypes
23:51.840 --> 23:53.920
So here's the way we think it's working cells
23:54.480 --> 23:56.880
Switching to the prion state just every once in a while and in fact
23:57.280 --> 24:01.600
With scythe pre and I've just been talking to you about the translation termination effect that happens about one in a million cells
24:02.080 --> 24:05.440
And generally one would expect that when the translation termination activities and working on ribosomes are
24:06.000 --> 24:10.480
See she called it scy there. So it's not the prion protein that we have in our brain
24:10.480 --> 24:14.640
She's just calling it a prion because it frills folds in two different ways
24:15.520 --> 24:23.280
And that it appears that that folding can be passed on from from protein to protein and that the aggregation occurs
24:24.080 --> 24:31.200
So there is some mechanism here some molecular mechanism that they believe they're they're looking at in yeast that has a
24:32.720 --> 24:42.240
A homologue in in these various neurodegenerative disorders and maybe even in our own bodies, but remember she's talking about yeast
24:46.240 --> 24:48.880
Everything through stock bonuses generally not necessarily create a good trade
24:48.880 --> 24:52.320
So that one in a million cells might die not a big loss to the to the population
24:52.800 --> 24:58.640
But when you can imagine that reading through stop codons might be okay in yeast and might be really bad at a mammal
25:00.480 --> 25:02.720
And so I just don't see it
25:02.720 --> 25:09.200
I don't see this as being related to the other and the implication that they are or that we're understanding
25:09.760 --> 25:15.040
How some things work by understanding this I think is a very very misleading
25:15.600 --> 25:19.040
Assumption if the environment changes and that's what we found that in different environments
25:19.760 --> 25:23.680
Prions could sometimes give cells an ability to survive conditions that otherwise could not possibly survive
25:24.240 --> 25:25.680
um
25:25.680 --> 25:26.560
then
25:26.560 --> 25:28.560
The cells would
25:28.560 --> 25:31.120
Now be able to live in an environment where they would not otherwise be able to live
25:31.200 --> 25:33.360
They would proliferate the non prion cells might disappear
25:33.360 --> 25:34.640
And this allows this genome
25:34.640 --> 25:38.480
This the prion allowed this genome to survive under conditions when those cells would otherwise not be able to survive
25:38.560 --> 25:43.120
Because the formation that prion has allowed all kinds of new genetic variation to be exploited some of which is beneficial
25:43.760 --> 25:47.280
Uh, now the cool thing is that because this is all tied to protein homeostasis in the cell
25:47.440 --> 25:52.000
Under conditions when the environments have changed and where cells are not doing so well and protein homeostasis is not going so well
25:52.320 --> 25:54.320
They are more likely to switch
25:54.880 --> 25:58.320
And of course the return is also uh going to be influenced by stress
25:58.800 --> 26:02.480
Uh, the protein homeostasis if cells change free on may be really great here
26:02.480 --> 26:05.920
But if the environment changes under these new circumstances the prion might not be so good
26:06.000 --> 26:08.160
But under those stressful conditions would be more likely to try out
26:09.120 --> 26:17.760
And so this cartoon is laughably simple environment too obviously needs whatever adaptations are at these skipped stop codon part of the
26:18.560 --> 26:20.000
Of the genes
26:20.000 --> 26:24.000
And so this assumption is just insane like okay. There's an environment
26:24.000 --> 26:25.360
There's some stress
26:25.360 --> 26:30.080
Let's turn off all the stop codons and see if any of the proteins that we make are useful
26:30.480 --> 26:33.440
And lo and behold they are until the stress goes away
26:33.760 --> 26:36.320
Or we get back into uh environment one and then
26:36.720 --> 26:39.360
I guess it goes back to normal because there are more
26:40.080 --> 26:43.440
Uh heat shock proteins produced in environment two
26:47.360 --> 26:54.160
This is how academic biology was ruined ladies and gentlemen by p values and in vitro extrapolation on
26:54.800 --> 26:59.600
Environment and experimental models that don't mean what they say they mean
27:00.240 --> 27:04.080
Loss of the prion because shepherds have been up regulated and maybe stabilized the whole system
27:04.480 --> 27:06.640
Maybe maybe so um
27:08.640 --> 27:12.320
So we decided to look for new prions. How many new prions might there be?
27:12.800 --> 27:20.880
We serve as her definition is a prion is an a protein which can fold in two different configurations and be inherited that way
27:22.560 --> 27:27.040
In cells that divide their cytoplasm, you know kind of like how mitochondria are inherited
27:27.680 --> 27:30.800
Interesting survey the yeast genome and we found that there were about a hundred
27:31.200 --> 27:34.160
uh proteins that had domains on them. What an interesting edit
27:34.720 --> 27:40.000
We found that there were about a hundred uh proteins that had domains on them that looked a lot like a sub 35 domain
27:40.400 --> 27:43.440
So the sub 35 domain is a prion domain
27:43.520 --> 27:46.880
So if there is a domain that looks a lot like that in the spike protein
27:46.880 --> 27:52.080
Then these people could make the statement that wow it's got a prion like domain in it. You see
27:53.200 --> 27:55.360
You see how this works?
27:55.360 --> 27:57.360
a yeast gene
27:58.320 --> 28:02.800
And so we decided because we know so much about sub 35 and but how it behaves and looks when it changes into prions
28:02.800 --> 28:04.800
They we borrowed that prion domain of sub 35
28:05.120 --> 28:06.400
Uh, it took it away
28:06.400 --> 28:10.240
And we added the prion domain of these other potential blue prions
28:10.720 --> 28:12.800
And sure enough when we tested them out
28:13.200 --> 28:17.600
Many many different protein domains had the ability to switch cells from red to white in a in a very terrible way
28:17.920 --> 28:20.080
Once the cells switched from red to white they could be
28:20.640 --> 28:26.240
Struck out and they maintain that characteristic for uh generation after generation and in every case that depended upon the formation
28:26.480 --> 28:32.240
Of prion amyloids and in fact, it depends on if you want to for see she calls them prion amyloids
28:32.560 --> 28:34.560
it's a pretty
28:34.640 --> 28:39.840
I would go so far as to say that this is a pretty disingenuous use of those words on purpose
28:41.040 --> 28:44.000
Prion amyloids dang that's impressive
28:45.760 --> 28:47.600
Prion amyloids she called them
28:49.200 --> 28:55.440
25 new 25 new prion amyloid domains that's interesting because
28:56.240 --> 28:58.880
Family prisoner wasn't calling them prion amyloids
28:59.360 --> 29:01.600
Not just to the prion domain that we were testing
29:01.600 --> 29:04.880
But we went back to the endogenous protein and that's where those proteins could switch states
29:05.040 --> 29:07.600
We couldn't handle all of them, but we looked at several of them
29:07.600 --> 29:13.360
And they created some really interesting beneficial in the traits and intriguingly many of those proteins are RNA binding proteins or DNA binding proteins
29:13.360 --> 29:19.040
So they sit in the middle of regulatory networks in such a way that they're really primed to change the way information is being decoded
29:19.040 --> 29:23.440
It really creates some reason so what she's talking about is if they're regulating DNA and RNA
29:23.440 --> 29:27.840
Then there are proteins that can regulate different things depending on the confirmation they're in
29:28.320 --> 29:32.080
Sounds like enzymes that change confirmation when they work
29:33.200 --> 29:37.680
It sounds like ion channels that change confirmation from the open to the closed state
29:38.880 --> 29:44.720
It's not so special ladies and gentlemen. It's not so special ladies and gentlemen
29:46.560 --> 29:50.880
And the induction of the change from one to the other
29:51.520 --> 29:53.920
Has not really been as
29:56.880 --> 30:02.000
I don't know. I don't know if I'm convinced by this data as they are convinced by this data that
30:02.720 --> 30:06.800
Somehow this this just kind of works remember there's there's substituting
30:07.840 --> 30:12.320
But complex novelin traits. This is one example. So this is uh, the prion known as mat three
30:12.880 --> 30:15.600
And that's the prion minus cell and that's the prion plus cells
30:16.080 --> 30:18.720
Growing in rich media. There's a variety of different cells that have a prion
30:19.040 --> 30:24.320
And now we've washed away that media that sorry the cells from that that media and we look to see
30:24.960 --> 30:31.200
If they need the cells remain and in fact the prion in this case has allowed many of these cell types to acquire a new
30:31.520 --> 30:33.360
Invasive growth phenotype
30:33.360 --> 30:39.520
It also has created the capacity in some of the strains to flacculate that is to group together which really changes their growth properties
30:39.520 --> 30:42.800
It really makes them in many ways function as a community of these rather than as individuals
30:43.280 --> 30:48.160
And you can see that in different strains we're getting different phenotypes of the again a variety of different phenotypes
30:48.320 --> 30:50.320
And mat three by the way, this is a transcription
30:50.640 --> 30:53.840
Repressor so when it goes into the prion state, it can alter the expression of lots of different
30:53.840 --> 30:55.840
So are you surprised that when you
30:56.400 --> 31:01.680
Induce a transcription factor or knock it out that things change? I mean, uh darn it
31:03.040 --> 31:05.680
So this had us excited. We were very very interested in it
31:06.080 --> 31:08.080
And a lot of people other people thought it was very interesting too
31:08.560 --> 31:12.720
But there were also a lot of skeptics and that's good reason because after all second my C server visa
31:12.800 --> 31:14.960
Is the best understood organism on the planet?
31:15.040 --> 31:16.560
So the question arises well
31:16.560 --> 31:21.680
If there's so many of these things why weren't they discovered before and um, I have the answer and the answer to one aspect of that
31:22.320 --> 31:24.960
Question because I picked the Colesman Harbour yeast course many years ago
31:25.040 --> 31:28.800
It was a wonderful wonderful course and I learned so much and empowered my research in so many ways
31:28.880 --> 31:30.800
But there was one thing that was very interesting about that course
31:31.200 --> 31:33.520
They told us that whenever we found a new phenotype new
31:34.160 --> 31:38.960
Trait in a yeast cell should cross it back to the original and then look for it to segregate two to two
31:38.960 --> 31:42.480
So that you had some clean system in which to investigate and things that didn't segregate to it too
31:42.560 --> 31:45.680
Were complex and would be too difficult to deconstruct and you shouldn't shouldn't look at them
31:46.320 --> 31:47.920
Since we've been talking about these these prions
31:47.920 --> 31:49.520
I've actually had an awful lot of people come up to me and say
31:49.520 --> 31:53.120
I had these weird traits in case that we're segregating that way too and my advisor made me give it up
31:53.360 --> 31:59.600
So I think this is kind of a wonderful story where um, we really get into habits of of doing science in particular types of ways
31:59.600 --> 32:02.080
And we really need to remember that it's sometimes time to break away from those
32:02.960 --> 32:07.520
Anyway, um, the other criticism was so far these things that only been found in in laboratory strains
32:07.520 --> 32:08.960
And maybe it was just an artifact of laboratory strains
32:08.960 --> 32:12.800
So we went to the same broad group of strains that we'd worked with with our hsp 90
32:13.280 --> 32:18.720
Investigations strains collected from all over the world with all sorts of different properties and lots of different ecological niches
32:19.680 --> 32:24.800
And we asked whether or not any of them had had prions and we found that a lot of them did
32:25.680 --> 32:29.440
So here's an example of a prion that exists in a wild a strain of yeast
32:29.440 --> 32:32.320
It's a wine stream and this is the cells growing in great must media
32:32.400 --> 32:36.560
And it turned out that we were able to create isogenic cells in which we caused the cells to lose the prion
32:36.880 --> 32:40.480
Didn't make any difference really to their growth on normal media rich media that they're using the laboratory
32:40.560 --> 32:42.800
But when you look at their ability to grow in great media great must media
32:43.360 --> 32:49.280
That growth was really dependent upon the prion so the prion was creating in this case a very valuable trait for that for that that strain
32:50.480 --> 32:53.600
And we have found in fact that prions very frequently create
32:54.480 --> 32:59.840
So when she identifies one of these proteins as such she calls it a prion and they do things
32:59.920 --> 33:07.520
But it's hard to differentiate these from enzymes or any other protein that changes confirmation in that confirmation has a different effect
33:08.880 --> 33:16.960
So I really feel like there's a lot of disingenuousness here in terms of how they're selling this and then also how it's related to prions as as pathogen
33:17.520 --> 33:20.560
Pathogenic mechanisms. It's really frustrating. This is
33:20.560 --> 33:25.600
That can be beneficial. In fact in the strains that we've looked at so far about 25 percent of these traits a lot of the cells
33:25.600 --> 33:30.080
You're growing their conditions where the otherwise just simply could not grow so again because they normally appear quite rarely
33:30.480 --> 33:39.680
And you only lose a small percentage of the cells and their implication is is that they're reading through a stopcode on and adding to an endogenous protein in one state with an extra
33:40.560 --> 33:42.480
Part of amino acids at the end
33:43.120 --> 33:45.680
That's the implication, right? That's how she explained it
33:46.080 --> 33:49.920
And so by reading through the stopcode ons you get new phenotypes in
33:50.480 --> 33:52.480
proteins by adding on to their
33:53.680 --> 33:59.600
End terminal, I guess I don't get it. It's weird. It's the the model is so simple
34:00.080 --> 34:05.360
And it makes so many predictions. Can we go and look at these proteins and see that they've all become longer
34:06.480 --> 34:09.520
Can you look with like antibodies and show us like
34:10.240 --> 34:17.840
Some standard proteins in one state and then the other state and show us that they've all elongated because they've read through a stopcode on
34:18.800 --> 34:20.800
How come we didn't do any of those things
34:24.960 --> 34:31.600
And again, that's where you really need to have you know, it gets frustrating when somebody says, can you just send me a few papers?
34:32.160 --> 34:34.320
You need a lot of experience and a lot of
34:35.120 --> 34:36.480
general
34:36.480 --> 34:41.680
Knowledge in order to listen to this woman and then ask her that question like hey, did you look
34:42.560 --> 34:49.040
at a few control proteins from your yeast line before and after the pre-on state
34:49.600 --> 34:55.680
And show that all of those control proteins are now reading through a stopcode on has part of your
34:56.480 --> 34:57.680
sort of
34:57.680 --> 35:03.120
Experimental exploration of the model and what it what predictions it makes the answer is no
35:06.080 --> 35:11.120
They're not beneficial, but when they do appear they allow cells to grow into conditions where they couldn't otherwise we think this is a really plausible
35:11.200 --> 35:14.640
That hedging strategy for the acquisition of a genetic
35:15.440 --> 35:17.440
Diversity in the organism
35:17.440 --> 35:22.080
Creating lots of new phenotypes which allows it to exploit fluctuating environments and grow in a variety of different situations
35:22.480 --> 35:26.560
And that just showed you one phenotype from psi. We've seen many phenotypes from many other prions as well
35:27.200 --> 35:34.240
And in fact, although we haven't identified many of the prions that exist in those strains the genetic behavior tells us that about 236 out of a 700 wild
35:34.240 --> 35:38.400
These strains we looked at do carry prions. So the final part of the story that i'm going to tell you about is
35:39.280 --> 35:40.560
concerns
35:40.560 --> 35:47.040
The ways in which a pre-on can influence the dynamics of the growth of these microbes in communities now of course
35:47.920 --> 35:52.160
Almost all experimental investigations in the laboratory work with organisms in pure culture
35:52.560 --> 35:58.880
So yeast growing or bacteria growing and that's natural that we started out doing experiments that way because otherwise we have everything all mixed up
35:58.880 --> 36:04.960
It's just impossible to do to do the kinds of experimental investigation that we needed to do over the last century to understand biological systems
36:05.600 --> 36:11.760
But organisms never virtually never grow into those circumstances in the wild in the wild they grow in mixed communities
36:12.480 --> 36:13.680
so
36:13.680 --> 36:19.200
But i'm going to tell you about is just the first case i think of a of a pre-on influencing the dynamics of of community
36:19.520 --> 36:23.840
Organization and organismal communication to create more diverse and more robust communities
36:24.640 --> 36:28.080
Uh, so the only one we've really looked at so far, my guess is that that's just again the tip of the iceberg
36:28.720 --> 36:30.720
so
36:30.720 --> 36:33.920
E cells have a very particular type of mass dev metabolism
36:33.920 --> 36:38.480
They're very fastidious and that's the reason why we love them when we give them glucose sugars like from grapes
36:38.720 --> 36:41.520
They take those sugars and they convert them into ethanol extremely efficiently
36:41.680 --> 36:44.400
They don't use the ethanol they only make the sugar into ethanol
36:44.400 --> 36:47.200
It's only when all the sugars exhausted that they start turning around in using the ethanol
36:48.000 --> 36:51.120
So, um, they will not grow um another carbon source
36:51.520 --> 36:54.480
Uh, if there's any glucose present very very fastidious
36:55.440 --> 37:00.240
But we found a pre-on that uh, it can cells can acquire that allows them to bypass the system
37:00.720 --> 37:03.840
They don't grow quite as well in pure glucose when they have that pre-on
37:03.840 --> 37:06.480
And that's probably why this was not really found and looked at before
37:06.880 --> 37:11.360
Uh, but in mixed carbon sources where there's other carbon sources around and a little bit of glucose too
37:11.600 --> 37:13.760
Those cells can now grow and the otherwise you'd not be able to
37:15.200 --> 37:17.200
So how do we investigate this story?
37:17.360 --> 37:19.760
Well, we took advantage of a glucose in the medic
37:19.760 --> 37:21.760
It's a compound called glucosamine
37:21.760 --> 37:25.040
That looks just like glucose probably the most of you and it does to the e cells
37:25.120 --> 37:26.480
It has this little amino group here
37:26.480 --> 37:28.800
But what it does is that e cells take this glucosamine up
37:28.800 --> 37:32.640
They think they're in glucose and they shut off the pathways for utilization of all other carbon sources
37:33.760 --> 37:36.320
So here you see an example of this we've got cells that are growing
37:36.720 --> 37:38.400
Without the pre-on
37:38.400 --> 37:40.400
Growing in pure glycerol and they're just fine
37:40.400 --> 37:43.600
But if you try to get them to grow in glycerol just a little bit of this glucosamine in there
37:43.680 --> 37:45.680
They think oh, no, I do not want to use any other carbon source
37:45.680 --> 37:48.800
I only want to use glucose and won't use that other carbon source until all the glucose is going
37:48.880 --> 37:50.880
They can't metabolize it so they're just stuck
37:51.520 --> 37:55.920
This allowed us to search for strains that might bypass that uh, metabolic
37:56.880 --> 38:02.080
Metabolic problem and allow the cells to grow in the presence of other carbon sources when there was a little bit glucose present
38:02.240 --> 38:04.640
As you can see we've got strains here that do that very very well
38:05.040 --> 38:08.720
This strain is genetically identical to the strain and we tested that in many many ways
38:09.120 --> 38:15.840
Or over these cells once they acquire that ability to grow on that other carbon source can be processed and passage for hundreds of generations
38:16.240 --> 38:20.640
Back on pure glucose, but they remember they retain that trait as a biological memory
38:20.640 --> 38:22.720
And they retain that trait for many many generations
38:23.440 --> 38:28.240
Uh, that allows them the next time they're put on that diverse carbon source to be able to grow on them
38:28.720 --> 38:32.160
So really changes their metabolic potential and really quite strong way
38:33.120 --> 38:34.160
Now
38:34.160 --> 38:39.760
The cool thing about this in terms of functioning in the community when you think about it carbon source utilization strategies might change quite a bit
38:39.920 --> 38:42.560
Depending upon whether you have other neighbors that are competing with you for those carbon sources
38:43.360 --> 38:45.520
And this is something we found actually by accident
38:45.920 --> 38:50.320
Jessica Brown was working on strains looking at what causes prion switching and she said we found a
38:50.960 --> 38:55.440
Colony around which there are all kinds of strains that had switched into the prion state and that colony that was in the middle was a bacteria
38:56.080 --> 39:01.520
So this experiment we tested that more rigorously do bacteria have a capacity to secrete a factor that will cause the yeast cells
39:01.680 --> 39:04.240
To switch their metabolism the heritable way by the induction of this prion
39:04.560 --> 39:10.320
So in this experiment what we've done is we've uh, plated not left these how are they secreting that do you think they're doing that by phage
39:10.960 --> 39:15.120
Wow, this is she doesn't use the word phage very soon. I'm going to be upset
39:15.360 --> 39:21.120
Well, it's empty and we've plated the gar minus he sells here the gar plus he sells gar is for glucose associated repression
39:21.120 --> 39:22.880
I should have said that's the name of that prion
39:22.880 --> 39:32.880
Uh, and then uh, we've planted gar of minus cells here. So these cells see so glucose associated repression is a gene that is considered a prion because it has
39:33.440 --> 39:35.440
apparently in her
39:35.440 --> 39:41.760
Estimation two states of functionality based on its folding that's not strange for a protein
39:42.560 --> 39:43.760
and
39:43.760 --> 39:45.200
enzymes change
39:45.200 --> 39:52.240
Confirmation ion channels change confirmation the actin in your muscles changes confirmation like
39:52.960 --> 39:56.720
The are the actin and mycin change confirmation like this is annoying
39:57.600 --> 39:59.600
Because we're implying
39:59.600 --> 40:06.400
Essentially, I feel like we're muddying the water about what prions are and how they work by talking about these
40:07.040 --> 40:11.280
As prions and then it's establishing this biological principle
40:11.760 --> 40:17.920
That there could be a prion in you that's very very bad and then only one needed and then it can go from cell to cell to cell
40:19.440 --> 40:24.880
And so if we can establish some kind of I think prions are beautiful in yeast kind of story
40:25.360 --> 40:32.080
Then we can also establish a prions can also be dangerous because look and they obviously exist because look at yeast
40:33.760 --> 40:35.120
That's what this is
40:35.120 --> 40:42.000
Remember our genetically identical the only difference between them is that these cells have switched into a prion state that is inherited in the non-mondylian fashion
40:42.960 --> 40:46.320
Because it's a it is a single-celled organism
40:47.040 --> 40:48.800
I'm protein-based inheritance
40:48.800 --> 40:52.240
And the cells are being played on glycerol with again just a little bit of glucosamine
40:52.560 --> 40:56.240
And you can see by the way that the cells do switch spontaneously every once in a while into this prion state
40:56.240 --> 40:59.200
Which allows them to grow but they really only switch that way every once in a while
40:59.280 --> 41:01.680
This is a dilution of strains across this plate
41:02.640 --> 41:05.920
Now the next experiment is done exactly the same way except we're going to plate bacteria
41:06.320 --> 41:08.400
That seem to have the capacity to induce this prion here
41:08.800 --> 41:11.840
And what you can see is that the presence of the bacteria on that plate
41:12.240 --> 41:19.920
A substance has diffused down the plate and influenced these yeast cells here to now switch their metabolic state and be able to grow into their condition when they otherwise wouldn't
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But it's a diffusible compound and it doesn't get far enough to get all the way down to this row here
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We established by lots of experiments that I won't take the time to show you
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But we could just condition media with no bacteria that bacteria had grown in and get rid of bacteria
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And we could use the condition media to induce this this new inheritable trait
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So what happens that cells usually are using glucose and they make lots of ethanol and only some ATP
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But when they're in the presence of glucose and other carbon sources this prion now allows them to
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Make less ethanol but lots of ATP
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And what does that do? It causes both organisms to flourish
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So it turns out that when the when the yeast cells switch as I mentioned
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It allows them to grow in different kinds of carbon sources even when glucose is present
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It also reasons we don't quite understand creates increased longevity in those cells
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They can they can live in in culture for much longer periods of time
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And the bacteria get a big advantage out of it because the yeast cells are making less ethanol and that means that the
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The bacteria can grow up to much higher concentrations because the bacteria don't like ethanol it poisons them
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now
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Turns out this is a very highly conserved property of yeast and bacterial strains from all over the world
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That's because yeast and bacterial strains are often found in the same places in the same environments
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And so they often have interaction
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That doesn't mean that these interactions have a homolog in our own bodies and in our own physiology
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But that's what they want you to believe
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They want you to believe it. They want you to think that there's
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This means that prions in the the human brain work exactly the same way and they may
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be
42:47.680 --> 42:53.200
Lots and lots of streams are capable of yeast strains are capable of this kind of a switch and many many different bacteria are capable of inducing it
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Does it matter in the real world?
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Well, I can tell you one way in which it clearly matters in the real world and that is it spoils wine fermentations
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so
43:00.800 --> 43:04.560
The yeast are making less ethanol and making other kinds of metabolic byproducts and it really makes lively wine
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In effect, it turns out that the bacteria that contaminates spoiled wine preparations
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That um, monologists have been studying for a long period of time
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Turn out to be super-inducirous and make lots of this compound that switches the yeast cells into this new prion state
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So I don't think I don't think calling it a prion state is
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Is is intellectually genuine? It's not it's not
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It isn't I think that that is a misnomer on purpose. They're doing it on purpose to
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to muddy this water to
43:34.000 --> 43:40.000
To make the idea of infectious prions a more plausible idea and create
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The intellectual idea space where they could exist where otherwise
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Stanley Prouzner doesn't have doesn't have squat
43:49.760 --> 43:52.560
A tremendous advantage is out of it. The bacteria get tremendous advantages out of it
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It's to the detriment of man but to the benefit of both those organisms
43:55.520 --> 44:00.240
And again in terms of the conservation of this um across uh tens of millions of years of of yeast evolution
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Uh, these strains have really exactly what seems to be exactly the same mechanism
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Uxilensis which has uh diverged from sachromisies
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Uh, these strains don't have it. They have a different kind of metabolic profile
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Vercellensis is another yeast that has that same kind of fastidious lifestyle in terms of carbon socialization
44:13.920 --> 44:17.680
That sachromisies has and it also has that car prion state even pombe
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Which is diverged hundreds of millions of years ago
44:20.160 --> 44:25.440
Um, although the mechanism isn't quite the same has this capacity to switch into an epigenetic state that changes its metabolism heritably
44:25.600 --> 44:29.920
So vast amounts of evolutionary distances these um, these these these ability to switch carbon source
44:29.920 --> 44:35.920
Inheritable way induced by environmental factors has been concerned. So here we have really uh, what I consider the ultimate example of a marking evolution
44:36.160 --> 44:41.520
We have chemical communication between a prokeria and eukaryum that transforms metabolism in the heritable way
44:42.080 --> 44:45.200
And the simple exposure of the yeast cells to that chemical compound
44:45.840 --> 44:53.120
Causes them to change their biology chemical compound or phage carried by a chemical chemical compound carried by a phage
44:53.200 --> 44:55.200
I'm not sure we probably have to look into it
44:55.680 --> 44:57.200
I don't know
44:57.200 --> 45:00.720
what other ways that bacteria shed things other than phages, but
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Anyway, it's interesting that she hasn't mentioned phage and
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Prouzner never mentions phage and nobody mentions phage in the way that's heritable for hundreds of generations
45:12.720 --> 45:14.720
So again when a considering
45:15.040 --> 45:18.000
Jamba of tisth Lamarck, I think it's time to give them back his dignity
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There are mechanisms by which changes in the environment can produce new traits
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If you accept what she has presented to you in yeast as evidence of inheritance
45:26.880 --> 45:31.200
I mean that can be passed on to progeny. Okay, so once again, I want to end my lecture
45:31.840 --> 45:34.560
Amazing and wonderful people in my laboratory. He's done this work over the years
45:34.880 --> 45:39.760
Um, I've spoken about each things that each of them have have done and I if you're interested in this work
45:39.760 --> 45:43.600
I would really urge you to take a look at some of the papers. I think they're pretty cool. Thank you
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Okay, well, that wasn't so bad. I'm glad we finished it. Um, I don't think I'm very impressed with the state of
45:51.520 --> 45:55.440
Prion uh stuff nowadays. Uh, I'm really not
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Um ladies and gentlemen, uh, this has been a presentation of gigo and biological dead lady from mit and prions in 2016
46:05.120 --> 46:09.360
And uh, the goal is to really make sure that we cover all of our bases
46:09.360 --> 46:12.320
We've listened to stanley prouzner explained it in 2002
46:12.880 --> 46:18.960
We've listened to four lectures from this lady already and she's given us a pretty good idea of what's been done in yeast
46:19.600 --> 46:21.600
and we've listened, um
46:22.880 --> 46:30.080
To stephanie sineph explain, um, some of the details of how the spike protein may or may not
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Either have antibodies produced to it which overlap with specificity to the protein
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um some other kind of
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Of way that the prion protein is being attacked by the immune system
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She didn't mention prionogenic
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sequences, but
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I've heard other people mentioned prionogenic epitopes
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Um, and so before we really tackle the spike protein story and what I think is part of the worst case scenario illusion
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That was laid down in 2020 to make sure that all we knew
47:04.960 --> 47:09.280
Was that we had to argue about whether it was a lab leak or a natural virus
47:09.360 --> 47:16.160
So you can find me at giggleandbiological.com if you can please share this work wherever you social media
47:16.800 --> 47:18.800
And wherever you and whoever you email
47:19.440 --> 47:23.360
And if you really can, um, please choose to subscribe
47:24.000 --> 47:25.840
Choose to support the stream
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My family really depends on it. Um, this is this is what we're gonna
47:30.480 --> 47:32.880
We're gonna contribute, um at this time
47:32.880 --> 47:37.520
And so my whole family is working very hard to make sure that I have the time and the energy to do this
47:38.080 --> 47:41.920
And, uh, I am trying to make sure that I'm here every day and as we move forward
47:42.560 --> 47:44.560
Um, we're gonna be putting out some more material
47:44.560 --> 47:48.560
We haven't gone to sub stack in a while and of course that's gonna kick up again too. So
47:49.440 --> 47:57.680
Um, thank you guys everything in terms of patience. Um, and uh, yeah, it's it's a long summer and there's lots of stuff to come
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Um, so thanks very much for joining me. I'll play this out. Thank you
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So
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So
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So
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So