cc  >> Hello, thank you for watching  Wednesday Nite at the Lab  tonight.  Tonight our speaker is going to  be Scott Topper from the Genomic  Center of Wisconsin.  He's a fourth year genetics  PhD candidate working on the  signal transduction networks  and control the cellular  environmental stress response  of cells.  He's also an art and theater  critic for the Wisconsin State  Journal, a contributor to  the Wisconsin Public Radio's  To the Best of Our Knowledge,  and a poet with publications  in over 20 journals.  Tonight he's going to be doing  a speech on "Eavesdropping  on the Inner Life of Cells."  This talk will cover the basics  of genes and gene expression,  focusing on the current genomic  technologies and approaches to  understanding which genes are  active.  It will also touch on the kinds  of unique observations that are  available when approaching the  biology through this kind of  perspective.  So I'd like to present  Scott Topper.  [APPLAUSE]  >> Hello, thanks for coming.  Can everybody hear me?  Good.  So my name is Scott Topper,  I'm a fourth year graduate  student, as Cassie said. 

 And I'm very happy to be invited  to talk to you tonight.  I have, I came to graduate  school much later than most of  my colleagues did from a very  different field.  And what that's meant for me and  hopefully means for me still is  just that I can still remember  what it was like to have no idea  what everyone was talking about.  [LAUGHTER]  Which was a terrifying,  sort of fun and curious before  I got here, and then quickly  terrifying once I arrived.  So the talk that I'm going to  give tonight is going to start  out pretty basic.  And to try to address some of  those things that were real  stumbling blocks for me when I  began here and then we're going  to quickly move on to some of  the techniques and questions  that we try to answer in the lab  that I work in.  If you have any questions, feel  free to chime in.  Okay, so this is just a general  schematic that I'm sure you've  all seen before of the cell.  Eukaryotic cell, it has a  nucleus with the DNA inside,  chromosomes, whatever.  All of these words, DNA,  chromosomes, genes these are  concepts that are so fundamental  and familiar to most geneticists  that they fail to explain what  they actually mean. 

 Which was a big struggle for me  starting out.  So that's where I'm going to  begin.  If this is redundant for some of  you, apologies, but can't hurt.  But first let's take a little  detour.  The genome.  In the first half of the 18th  century, this very ambitious  project was undertaken in France  under the direction of a man  named Denis Diderot.  And he and his colleagues  endeavored to create an    encyclopedia that would be a  compendium of all of human  knowledge.  Everything that our species knew  how to do.  So an ambitious project.  Maybe less ambitious 250 years  ago but still pretty ambitious. 

 When it was complete, in its  first -- it stretched to 35  volumes and they contained  information on all branches of  knowledge from chemistry,  metallurgy, economics,  engineering, shipbuilding,  natural history, philosophy,  literature, music, politics,  everywhere and the great French  minds of that era were all  significant contributors to it.  This offers, I think, a pretty  good metaphor for what we're  going to talk about.  So when we say the genome, what  we really mean is all of the  genetic materials.  It's sort of like saying the  entire encyclopedia.  It's the sum total of everything  that the cell knows how to do.  When we say a chromosome, what  we mean is something like a  single volume of the  encyclopedia.  So this genome is too big to fit  in one book so it's divided up  into smaller sections.  So it's a part of the genome.  It contains some of the  information, some of the genetic  information in the genome and  it's like a single volume.  DNA is an interesting word. 

 It's very general.  It just refers to a material.  It's the physical stuff that the  genome is made of.  And when we say gene, what we  mean is a region of the genome,  a short section of DNA that has  meaning, and by meaning we mean  it contains the code for a  protein.  That's like flipping through the  genome, flipping through the  encyclopedia, pulling out a  volume, looking for a specific  page and finding a single thing  on that particular page.  So this is an illustration of  tools involved in making metal  buttons.  I don't really know what that  tool is but that's like a gene.  A description for how to make a  single tool that's involved  in a very specific process.  To abandon the beautiful  metaphor and move into the  biological reality, in humans,  the human genome is spread  across 23 pairs of chromosomes.  The DNA is made up of four  sub-units that are just strung  together in incredibly long  strings. 

 There's 3.2 billion individual  units in the entire genome,  3.2 billion individual units  of DNA strung together.  [INAUDIBLE]  Billion with a B, right.  And like I said, a gene is just  a short region that has meaning.  Humans have about 30,000 protein  coding genes.  And the average gene is about  3000 bases long.  So you can do the math.  There's a lot of space in the  genome that's not devoted to  making proteins.  There's a lot of other  interesting functions that may  be present in those other  regions that I'm not going to  talk about right now.  For our purposes, the way this  field has moved forward is to  start out with the understanding  that where things really  happen is protein and the gene  is the code for the protein.  So what genes are and aren't. 

 Genes are information.  Genes is DNA that codes for a  protein.  Genes are not themselves things.  They're kind of like ideas.  So it's sort of like the recipe  for a cake.  The recipe for cake is not a  cake.  It teaches you how to make a  cake should you decide to make  one, but you can't eat the  recipe.  So along those lines, the genes  that a cell has represents all  the things that a cell might be  able to do, should it find  itself doing those things.  The genes that a cell has  doesn't necessarily tell you  what the cell is doing.  So, for example, I know how to  ride a bike. 

 I'm not riding a bike right now.  That's not relevant to what I'm  doing.  So the fact that I have that  knowledge is more or less  irrelevant to what's going on  right now.  And the same thing is true for  cells.  So it's generally thought that  every cell in an individual's  body has the exact same DNA.  Which means every cell in the  human body has the exact same  genes.  Cells with the same DNA can wind  up being incredibly different.  So, for example, cells in your  eye encode for or are expressing  proteins that create these  beautiful little photoreceptors  and allow you to see.  There are cells in your stomach  that are involved in the  synthesis and excretion of  gastric acid.  The cells in your eye know how  to make the gastric acid. 

 They don't and we're all happy  about that.  It would hurt quite a lot if  they decided to do that.  So even though they have the  same genes, they have the scene  DNA, different things are going  on.  The way this happens is that  different genes get activated or  repressed in different cell  types.  So this is just a cartoon but if  you imagine they're these four  genes that all these cells have  in common.  Maybe in the eye gene, gene one  and gene three are being  activated, and in the stomach  cells gene three and gene four  are being activated.  So gene one is specific to the  eye cells.  Gene four is specifically  activated in the stomach cells.  Gene three is activated in both,  maybe it has something to do  with a general process that all  cells need.  But for us, the big question  isn't so much what genes the  cells have but what are they  doing with them. 

 Which genes are being expressed.  So just to touch base with the  metaphor, we have this DNA which  is sort of like an archive of  everything that the cell knows  how to do.  It's like this Diderot's awesome  encyclopedia.  Turns out, I found this out  today, the University of  Wisconsin actually has two  copies of this encyclopedia.  Which is amazing because I think   only about 4500 of them were  printed.  And you can go look at them but  they're in special collections.  They're precious and they need  to be protected.  And with the DNA it's sort of  the same thing.  The DNA is protected.  It's kept in the cell. 

 It's an archive of everything  that can happen.  If something happens to that, if  the directions the confused,  every time you refer to those  directions you're going to be  making mistakes.  The same way that DNA is stable  and protected in the archive of  the nucleus.  When the gene gets activated,  when a cell begins the process  of activating a gene, the first  thing it does is make an RNA  copy of a particular region,  just a short stretch of the  genome.  Just a particular gene.  RNA is chemically very much like  DNA.  It's less stable.  It's disposable.  The interesting thing is that  you can make lots and lots of  copies of it.  So you can have one archive make  a whole bunch of copies of the  particular bit that you're  interested in and then use those  copies for manufacturing. 

 So that's like going to a  particular page in your  encyclopedia and saying I'm kind  of interested in making shoes.  I'm going to make a whole bunch  of copies of this instruction  set and then move forward from  there.  That RNA is then used as the  working template for making the  actual functional proteins.  So you look at this, you figure  how to make a couple hammers.  You look at recipes, you figure  how to make a couple of cakes.  You look at this, you figure how  to make a couple of very  uncomfortable looking sandals.  Same thing.  RNA copies are used by other  mechanisms in the cell to go  ahead with the business of  making functional proteins.  Okay, so now I'm going to  introduce another word.  The genome, what we said is the  DNA of the cell. 

 It's everything a cell knows how  to do.  The genome is thought to be very  stable and unchanging.  There's a lot of systems present  in the cell to address and  correct mutations, should they  exist.  The transcriptome describes the  set of all of the RNA molecules  present in the cell at a  particular time.  So it's different.  The genome is all the genes that  are there.  The transcriptome is all the  genes that are being used at any  particular time.  It reflects the genes that are  active.  The genome is unchanging, the  transcriptome is dynamic and  responsive.  So about 2005, about 3 years ago  the genome was published and the  big news or the big not news was  that it was remarkably similar  to the human genome, by some  measures 98% similar. 

 98% identical, rather.  And that brought home the point  that maybe what makes us  different isn't that we have  radically different genes but  that those exact same genes are  regulated in different ways and  used in different ways.  So there's a chimpanzee; that's  one of my monkeys.  She has some remarkably simian  behaviors that she expresses  with great glee.  But she's not a monkey, she's  very different even though she  shares so much in common with  the chimpanzee.  Okay, so we start to move  towards the biology that we do  in our lab.  From our perspective, a cell is  alive, dynamic and constantly  changing.  And the questions that we once  asked in the lab that I work on  are to get to these dynamic  processes.  How do cells change over time?  How do they respond to  challenges in their environment?  The world is an unpredictable  place.  How do they protect themselves  from potential changes in the  environment?  And these cellular dynamics can  we track by monitoring the  changes in the RNA, the changes  in which genes are being  activated. 

 So if you can know which genes  are being activated, you can get  an idea of what the cell might  be trying to do to the extent  that it can try to anything.  So this is why I call this talk  eavesdropping on the inner life  of cells.  If we can understand sort of  from their perspective what  genes are important to activate  at any particular time, we do  get a better sense of really  what life is like for different  organisms or for different  cells.  So by looking at RNA levels, we  can ask which genes are being  expressed.  Importantly we can ask which  genes are being co-express.  So a single tool like that weird  little metal thing for making  buttons.  It's not used all by itself.  You need a whole host of tools  to be able to do something  meaningful.  So likewise, if you can see  which genes are activated  together, you can get a better  sense for how different  components in the cellular  machinery might be working  together to do something  meaningful.  So which genes are involved in  cellular processes?  How do genes respond to changes  in the environment?  Which is of particular interest  in our lab. 

 What happens when cells become  diseased?  All these things, all these  changes might manifest in  changes in which genes are being  expressed.  Alright, so our lab studies  yeast.  Saccharomyces -- is pretty much  the same yeast that's used in  making bread, making beer.  This causes no end of glee to  some of my friends.  For whom are unfamiliar with the  way scientific research actually  happens.  Does anyone know who this man  is?  That's William Butler Yeats.  When I explain to my poetry  friends what brought me here, I  often just tell them it was an  accident of dyslexia.  [LAUGHTER]  There's a poem that a guy  that I know wrote, Yeast.  I am Yeast, a great poet.  I live in Ireland. 

 Some say I am the greatest poet  ever.  My poetry makes bread grow all  over Ireland and the world.  In glens and valleys, bread  rising in huts, clover paths and  firewood.  There will always be critics who  deny yeast.  But you can see the effect of my  poetry through the potato fields  and the swell of the Liffey.  The amber coins and the foaming  black ale.  A beautiful confusion.  So why do we study yeast?  Yeast is one of the fundamental  model organisms for genetic  research.  The most important reason is  that yeast has the same basic  cellular structure as human  cells.  It's a single celled organism,  but it's not a bacteria. 

 Bacteria are very different from  human cells.  But yeast are very much like  human cells in that they have  DNA that's encapsulated in a  nucleus, all the processes  involved in accessing the DNA,  transcribing it, exporting  RNA and dealing with it are  fundamentally conserved  throughout evolution.  So you can use yeast to study  these very basic processes.  That would be impossible to  study in higher organisms.  It even has many of the same  homologous genes.  It has a much smaller genome.  Whereas humans probably have  around 30,000 genes, yeast have  only 6000 so it's still a very  complex system to work on but  considerably less complex than  humans.  There's great genetic tools.  It's very easy to make genetic  manipulations in yeast.  It's also been studied for a  good long while. 

 So there's a great body of  knowledge.  Biology is very cumulative.  The more that's known, the  easier it is to fit a new  observation into a meaningful  body of knowledge.  They're fast to grow.  The double in about 90 minutes.  They're plentiful.  They're cheap.  They're immune to empathy.  I can kill millions of them in  an afternoon and feel not a  twinge of guilt.  So, like I said, our lab studies  environmental stresses and how  cells respond to environmental  stresses. 

 So life can be hard for yeast  especially when I get my hands  on them.  Like I said, they're single  cells.  They have a rigid cell wall that  makes them different from human  cells, but like other kinds of  cells they're kind of like  nasty, very small M&Ms.  They're soft and gooey in the  middle and they're kind of  crunchy on the outside.  The cell wall kind of protects  them from the environment but  they're very sensitive to subtle  changes.  So our research, and I should  say I'm a graduate student in  Audrey Gash's lab and most of  what I'm going to talk about  today is based on work that  she's done before she founded  our lab.  So our basic research questions  are in response to stress, which  genes are activated or  repressed?  Turned on or turned off.  What mechanisms activate the  stress?  How does the cell know that the  environment has changed?  How does it take that knowledge  and move it into the nucleus to  change the expression of these  different genes?  What are the signaling networks  involved?  For me, what I'm also very  interested in is what does this  mean for the cell?  What does this radical  alteration in the genes that are  being activated, what can that  tell us about what the  fundamentals of life are like  for this organism?  Possible applications for this  is improved stress tolerance for  industrial applications,  biofuels.  So right now what biofuels means  is making ethanol from corn,  that's going to change, but what  makes ethanol?  Yeast.  Right?  So yeast is currently the big  player that's going to change. 

 But also by understanding how  cells respond to stress, how  cells respond to disease,  disease is a kind of stress, it  might help us develop  understandings that can be used  to help cells survive medically  induced stress.  For example, chemotherapy is a  very stressful experience for  the individual cells.  What if it were possible to  understand better the ways cells  survive radical alterations in  their environment that might  have medical applications.  So here's the kind of  experiments that we do in our  lab.  We take yeast cells.  We do something that they don't  like to them and they don't like  a lot of things.  They don't like it when it gets  too hot.  They don't like it when it gets  too cold.  They don't like it when you take  away all their sugar.  They don't like it when you take  away all their nitrogen. 

 They don't like it when you dump  a whole bunch of salt in there  and change the -- of the media.  They're not thrilled about  hydrogen peroxide and other  oxidizing agents.  They complain mightily about  reducing agents, DTT.  They sure don't like DNA  damaging agents.  We've got a whole host of  unpleasant things that we can do  to them.  So we stress them out in any  number of ways, and we collect  their RNA which is possible to  do.  We take that RNA and we move it  with a couple of manipulations,  move it onto a micro array.  I'm going to spend a lot of time  telling you exactly what a micro  array is.  And that will help us learn  which genes are activated and  which genes are repressed.  We analyze this data. 

 We have very clever ideas.  Theoretically we publish them.  I'm moving in that direction.  So that's the kind of  experiments we do.  We look at how the RNA  component, the transcriptome of  the cells, change when we  confront the cells with  rationally introduced stresses.  So here's the basic principles  of eavesdropping.  To get a little closer into the  specific technology.  I'm sure you've seen strings of  letters like this.  Each gene can be represented as  a sequence of four letters: A,  G, T and C.  Which represent the different  fundamental four bases of DNA. 

 Genes are different.  They're some sequences that are  conserved and are very present  in multiple genes.  But for each gene you can always  find a sequence that's unique to  that gene.  The other property of DNA that  you need to know about is that  DNA, as I'm sure you do know, is  double stranded.  And there's complementarity  between the bases of DNA.  So A and T like to bind  together.  G and C like to bind together.  And that binding can be  capitalized on.  If you have a single strand of  DNA, that's like TAG-TAG, for  example.  Another piece of DNA that has a  complementary sequence to that  will bind to that. 

 So, for example, this one has  ATC-ATC the perfect complement  for this.  So this new sequence will  combine to this one.  This one doesn't have a  complementary sequence so it  won't bind.  So if you can make a little  sequence like this and attach it  to something, you can kind of  use that like a fishing pole to  pull out the exact sequence that  you want.  So you can imagine that there's  hundreds of thousands of  sequences maybe tens of  thousands of different  sequences, but if you have  somehow engineered a specific  short bit of DNA that has a  particular sequence, you can  just sort of sweep it over the  whole pool and pull out the ones  that you're interested in.  So micro arrays.  Micro arrays.  This is the technology that we  use to explore the genome.  What micro arrays essentially  are small chips that are spotted  with thousands of unique DNA  probes.  There's different platforms that  are primarily different in the  method of manufacturing, but  they all do more or less the  same thing. 

 They've all got a whole bunch of  those little fishing hooks  attached to the same surface.  So if you look closely at a  micro array, and this is the  kind we use in our lab, it's  really just a microscope slide.  With lots and lots of very small  spots on it.  So to look closely here, you'll  see a grid of little spots.  If you look very closely at any  one of those spots, each spot  will correspond to a single gene  and inside each one of those  spots you'll see tens of  thousands of identical pieces of  single stranded DNA.  The sequence of those strands is  going to correspond to a single  gene.  So in this example this spot  corresponds to a gene called  PKC1.  All of these oligonucleotides,  they're called, contain a  sequence that only the gene PKC1  has.  Maybe this guy over here  corresponds to a different gene  called HOG1.  The oligonucleotides in that  spot will only correspond to  that particular gene. 

 So, like I said, RNA or a  different kind, or complementary  strand of CDNA from a single  gene will hybridize to a  specific spot.  What we can do is take the RNA  from the cell, make DNA copies,  and we do that just because,  like I said, RNA is very  unstable.  DNA is much more stable.  And when we do that, we can  attach little fluorescent probes  to the actual DNA.  So now we have DNA that has the  exact sequence from the gene  that it came with and it's  green.  Or it's red.  And if I take that red DNA and I  pour it all over the micro  array, all the little red bits  from the gene and I care about,  the PKC1 they'll find the spot  that they're meant to find.  And that spot will light up red.  So with micro arrays we can  interrogate the entire genome  all at once to learn the  identities of all the genes that  are expressed.  So, for example, if this gene  right here corresponds to PKC1  and I do a micro array, I look  at that spot, it's bright red, I  know wow, the sample that this  RNA came from was really  activating that gene. 

 And I'll talk a little more  about what these different  colors mean.  So what do you need to make a  micro array yourself?  First of all, you need a  sequence genome.  As all this depends on knowing  the sequence of every single  gene.  We're awash in sequence genomes  these days and the technology is  just getting faster and more  fantastic.  And that's going to continue.  There's Yeats again.  You need bioinformatic  techniques to know where  the gene is in this genome.  So when you have a sequence of  genomes, you have 3.2 billion  letters in a row.  You need to figure out which  bits of those are actually  genes.  You need chemically synthesized  oligonucleotides. 

 So you need the short fishing  hooks that I talked about.  So I worked right next to the  Genome Center which is run by a  woman named Sandra -- and she  brought her daughter to work one  day, and her daughter said, Mom,  what are you doing?  And I heard her say, Oh, I'm  chemically synthesizing  oligonucleotides.  Which remarkably turned out to  be a pretty sufficient answer  because that was the end of the  conversation.  But that just means you need to  be able to make whatever  sequence you want.  And that technology exists and  is fast and cheap.  And then you need money.  You need a lot of money.  This is an expensive technique.  It's getting a little cheaper  but it's still pretty expensive.  A single array with a commercial  technology can run about $300. 

 A single experiment isn't worth  much.  So these kinds of experiments  get expensive fast.  So to talk in more detail about  the kinds of experiments that  are routinely done.  What are often done is to try to  simplify and simplify the  question of what's going on by  comparing two similar but  slightly different samples.  So, for example, if you can  compare the same kind of cell,  the human cell line that one of  the human cell lines is healthy  and one of the human cells lines  is cancerous, then you can just  look at which genes are  activated differently in those  two samples and begin to get  some understanding of what the  consequences for the cell are.  Or maybe how the cell is trying  to adapt to the new regime.  For our lab, we look at  unstressed verses stressed  cells.  And just look at which genes are  doing something different.  If the genes are doing the same  thing in a stressed cell and an  unstressed cell, it's not  interesting to us.  They're not the genes that are  relevant to the question of how  a cell deals with stress. 

 So what we do is we have these  two samples, we collect the  cells, we isolate the RNA, we  make labeled CDNA, we a DNA copy  and color them with our label  probes.  We apply them to the micro  array.  We scan them.  We analyze them.  I'll talk more about what this  detail means.  So what we'll do is we'll take  the unstressed sample, collect  the RNA, make CDNA from it and  label that green.  We'll take the RNA from the  stressed sample, make CDNA and  label it red.  And we'll put both of those at  the same time onto the same  micro array.  So if a single spot ends up  looking red, then that means  that that gene was more highly  expressed in the red sample, in  healthy cell or the stressed  cell.  Whichever one it is. 

 If the spot turns out to be  green, then that means that gene  was very active in the sample  that we labeled green and not  very active in the sample that  was labeled red.  When spots turn out to be  yellow, it means they were the  green and red were equal in  about the same amount.  When a spot is black or absent,  it means that neither of these  cell types were using that  particular gene.  Analyzing the data is a  challenge.  Biology is this sort of  interesting tug-of-war between  trying to get as much data as  you can and then trying to be  savvy about ignoring as much of  it as possible to pick out the  relevant bits.  But what we do is we do many,  many experiments.  And we try to look for groups of  genes whose expression patterns  match across many different  kinds of experiments.  And that could be an indication  that those genes are  co-regulated.  So if a gene, if a cell always  activates these 15 genes at the  same time, and in response to  different experiences, that's an  indication that those 15 genes  have something to do with each  other for the cell.  If we know what six of those  genes do, and there's nine more  that are along for the ride,  it's a pretty good starting  place to say maybe these genes  have something to do with the  other genes that we know about. 

 So I'll talk specifically about  the observations that Audrey  Gash made that started this lab.  So what she did, she took yeast  cells and she did a whole host  of very unpleasant things to  them.  She looked at which genes were  induced and which genes were  repressed.  So when we visualize data it  ends up looking like this.  And I'll explain what this  means.  Maybe I'll turn the lights down.  There we go.  So like I said, yeast have 6,000  genes.  This is what micro array data  looks like when we start to work  with it.  Each row here represents a  single gene. 

 The activity of a single gene.  Each column represents a single  experiment.  So what these are, are time  course experiments.  So when Dr. Gash did was exposed  cells to high temperatures and  then collected samples at  multiple times, did micro arrays  and saw which genes are  changing.  So red means a gene got induced.  Turned on by the stimulus.  Green means the gene got  repressed or turned off by  stimulus.  You can look, here's a big group  of genes that started out doing  nothing or started out at a  certain level and then got  brighter green which means they  got turned off.  Here's a group of genes that  started out at a certain level  and then all got turned on.  Here's a group of genes that  didn't really care about heat  shock at all. 

 She did this again for some  oxidizing agent.  Same thing, so lots of genes  turning on and lots of genes  turning off.  Did again for a reducing agent.  Lots of genes on and off.  We're beginning to drown in the  data.  Other reducing agents.  She gave them high osmolarity.  She starved them.  She took away their nitrogen.  And what happened in each  experiment is different. 

 When she starves them for  nitrogen, here's a group of  genes that were repressed that  weren't repressed before.  Here's a group genes that are  highly induces when they're  starved but not under any other  condition.  But even though there's  differences, what she noticed  was that there's this core group  of genes that seems to be doing  more or less the same thing  regardless of what the stress  is.  So however you upset them, this  group of genes gets turned off.  However you upset them, these  groups of genes get turned on.  They seem to be general stress  response genes.  How the cells are just dealing  with change.  Among these repressed genes are  genes involved in RNA  metabolism.  So making the copies of the new  genes.  Genes involved in the ribosomal  proteins. 

 Ribosomes are the things that  make proteins from RNA.  To the things that get turned  off when a cell gets stressed  seem to be the things at that  are involved in making more of  whatever you've got.  It's like the cells have taken a  step back from the very active  life.  The things that get turned on  across all stresses are a host  of different things that may or  may not have much to do with the  particular stress but seem like  they're defensive things.  So cell wall genes get turned  on.  Maybe the cell wall gets beefed  up a little bit.  Carbohydrate metabolism gets  turned on, maybe the cells are  starting to make a little more  energy.  Genes involved in detoxifying  reactive oxygen species get  turned on.  But what's interesting is those  get turned on even when there's  not reactive oxygen species.  Not reactive oxygen around. 

 They get turned on by salt.  They get turned on by heat  shock.  So the cell senses that  something is going on and mounts  this kind of general response.  I'll take a little detour, so  this diagram which I think is  actually quite beautiful and  this experiment is the big  reason why I decided to join  this lab.  So for me this kind of science  is unique and really  fascinating.  Generally what geneticists due  to understand what a gene does  is we're like big, brutal kids.  We break the gene and we see  what's different about  something.  Oh, you've got this gene.  Break the gene.  Now the limb isn't growing  right. 

 Okay that gene has something to  do with limb development.  Or oh, I don't know what this  gene is.  Well, break it and we'll say now  this yeast cell can grow on this  particular sugar source.  I guess that gene has something  to do with that particular sugar  source.  But we're always sort of working  with damaged organisms.  We're always working with things  that we've manipulated in some  way because it's a very  effective way of gaining  understanding.  But this is different.  So these are healthy cells.  These are healthy cells  responding to changes in their  environment that are not lethal.  So these doses have been  specifically calibrated so they  can survive them and they're  just responding to them. 

 So from my perspective, this is  really what health looks like  from a genetics standpoint.  Usually as scientists and even  the medical institution is very  focused on addressing disease,  what looks like when things go  wrong.  And that's really what we  understand.  But this offers, this kind of  work offers a different sort of  approach, a different kind of  picture.  What do things look like when  everything's going right?  When healthy cells responding to  changes in the environment.  Life changes a lot.  And if you can't change, that's  essentially the description that  we have of dead.  Right?  Living things move and change,  dead things don't.  So, I'll turn the lights back  on.  So there's fascinating questions  that are available to answer  with this kind of data. 

 So what?  So we found that you stress  yeast cells out in any number of  ways and lots of genes change.  In fact, about 900 genes  reliably change.  What's the cell doing?  A paper that was published from  our lab just a couple of weeks  ago did some very interesting  experiments by a fellow graduate  student named David Barry.  And what he found is you can  make genetic manipulations to an  organism, to a yeast organism  such that it can't do that  anymore.  It can't activate all of these  genes.  And it can't repress them.  And it turns out that when you  do that, the cells respond, the  cells survive those particular  stresses just fine.  So in response to a lot of  salts, the yeast cells change  their expression of 900 genes.  If they don't do that, they can  still survive this salt stress.  So that's a little weird right,  it's a lot of work to  essentially do nothing. 

 But what he found was that it's  all of those, what the cells  can't do, sorry I'll take a step  back.  There's an interesting  phenomenon called acquired  stress resistance.  So when you stress out a cell in  a particular way, give it a  little bit of a salt stress, it  kind of gets a little tougher  and it's able to survive a  secondary stress that would  otherwise be lethal.  So, for example, if you know  that a particular dose of  hydrogen peroxide will kill  yeast cells, if you give them a  little dose of salt first, they  get tougher and then they can  survive that one in the future.  If they can't do this, if they  can't turn on and turn off those  900 genes, they've lost that  capacity.  So what we think now is that  this massive response is kind of  a guess of what's going to  happen next.  Things get bad, they're likely  to get worse.  Or, you know, it can't hurt to  defend yourself.  If you defend yourself too  strongly you're going to fail to  take advantage of the resources  that are there.  You're going to get out-competed  by other organisms. 

 But if things start to go south,  it's a good indication that you  should get ready for what's  coming next.  So what we think now is that  this, we don't really know yet  how that robustness happens.  We know that a lot of genes get  turned on, a lot of genes get  turned off.  We know that end up more robust.  But we don't really know the  mechanism of it.  And we're working on that.  >> What is the time period  between the first stress and the  small stress?  >> Repeat the question.  >> Oh, I'm sorry.  He asked what the time period is  that it takes to acquire this  stress resistance.  It can be as short as 30 minutes  or an hour. 

 And what's interesting is we've  done some experiments to see how  long it lasts and it can last  many generations for the yeast  cell.  A generation is only about 90  minutes or two hours or so.  But the memory of this rough  experience gets passed on to the  offspring that retain a little  robustness for a while.  So there's a number of different  ways to think about this in the  life of the yeast.  What might be happening is the  yeast might be working to  protect essential core  functions.  So there's, the cell works to  maintain an internal homeostasis  against the changing  environment.  A set of environmental  conditions that allow the  necessary biochemical reactions  to take place.  So what it could be doing is  just protecting those core  functions.  Why is it, though, that these  multiple different stresses  induce changes that protect  against unrelated stresses?  One explanation is that it's  just sort of an artifact of  working with an organism in the  lab.  Right?  Like I can squirt DNA damaging  agents on a yeast cell and  nothing else. 

 I can squirt salt on the yeast  cell and nothing else.  Maybe when a yeast cell  experiences these things in the  environment, what we've  separated out as different  experiences for the yeast cell  actually always show up at the  same time.  So it doesn't make any sense  that it would just encounter  salt.  Maybe where the yeast grow, they  would always encounter salts and  hydrogen peroxide or some kind  of oxidizing agent at the same  time.  So there's always a caveat of  interpreting data that's  gathered in the lab is how does  it apply to an organism that has  not necessarily evolved for my  experimenting.  Another hypothetical explanation  is to think about genetic  networks.  So we've got many, many genes  working together.  Maybe there's certain conditions  where it's very important that  genes are tightly co-regulated.  So important that the network  connecting them is pretty rigid.  It could be that one of those  genes is essential for another  process dealing with a  particular stress. 

 And when that one gets pulled to  deal with this particular  stress, all the other ones get  pulled along with it that are  connected for a completely  unrelated reason.  So genetics versus genomics.  Like I said, where genetics has  come from is trying to  understand what single genes do.  And where our lab and other  genomics labs are going is to  understand all the genes at  once.  So I'm a geneticist, I love  genes.  Genes are not life.  Right?  A single gene can't do much for  you.  But 6,000 genes altogether can  begin to work to create some  sort of biological meaning.  For me, that's the interesting  question.  Is where in this complexity does  life emerge and how can you  begin to understand the logic of  this interconnectedness through  these kinds of experiments?  So how do groups of genes work  together to create living,  changing cell?  How you take the particulars and  take a step back to a bit of a  larger picture?  So to summarize, life is dynamic  and the science that we're  trying to pursue is trying to  begin to capture that kind of    dynamism. 

 Cells begin to activate genes by  making RNA copies of their DNA.  So we can learn about what a  cell is doing over time by  monitoring that RNA level using  micro arrays.  And this can help us understand  the differences between cells.  It can help us understand the  details of cellular networks.  It can suggest therapies or  functional mutations for dealing  with particular experiences.  So with that, I'll stop and I'm  happy to take any questions.  Yes?  >> In these adaptations that the  cells are undergoing does stress  take place if you put in an  inhibitor of cell division so  the cells can't replicate?  >> Good question.  So the question is can this  adaptation take place if you add  some sort of inhibitor of cell  division?  So if you prevent the cells from  the dividing.  And with yeast that's very,  there's a couple of easy pretty  non-invasive methods for getting  them to stop.  The answer is sort of. 

 You can, weirdly you can inhibit  protein synthesis and still get  some resistance.  But those experiments are not  really complete.  So maybe I shouldn't be  speculating.  What was the idea that caused  you to ask that?  >> I just wondered whether the  cells had to be actually  changing perhaps in their  response to the negative  stimulus.  >> When you do stress them out,  they slow down a lot.  So on their own they've sort of  taken a step back from the rapid  process of division to kind of  regroup and figure out what  comes next.  So it's definitely not tied to  active cell division because the  cells on their own have decided  to stop that.  Yes?  >> You demonstrated that you can  make a cell more robust by  stressing them a little and then  the rally their resources and  can then withstand a more lethal  stress.  >> Exactly.  >> Now has anybody helped cells  become more robust, resistant to  stress or able to handle stress  by giving them the goodies of  life?  >> So the question is, we can  make cells more robust by doing  something that they don't like,  what if we do something that  they really, really like?  Will that also make them more  robust?  I don't think we've done that  experiment. 

 It's interesting.  We've done experiments to look  at the changes in gene  expression when you reintroduce  them to a very rich environment.  And they pretty much do the  exact opposite.  The genes that went off, go back  on.  The genes the went on, go back  off.  I don't know, I do know that  they lose the acquired stress  resistance after they've been in  that fresh media for a while.  So like I mentioned before,  we've done experiments where we  look to see how long that  acquired stress lasts.  And we do those experiments by  stressing them out, introducing  them to another stress or  putting them back in fresh media  for a while.  And then stressing them out  later on.  So they definitely, I think that  would be the equivalent  experience of giving them  something good and I don't think  giving them something good makes  them more robust. 

 But this is another question  that points out the difference  between working in the lab and  imagining an organism in nature.  So we can be pretty cruel to  them but we also know what they  like.  And when we're growing them in  the fast growth media, we've  given them everything that they  need.  And we found exactly the right  temperature that they grow at  the best.  We're probably starting them out  in an embarrassment of riches  that they never see in the real  world.  So we've moved them from the  best life possible for yeast to  something else.  Where they're really existing in  nature is probably somewhere in  the middle.  So maybe this stress response is  always on and the interesting  way to interpret it is how fast  can it turn off.  When the environment is not  good, they're growing more  slowly.  But if the environment can  suddenly get good, then  whoo hoo, it's party time. 

 Stop wasting energy on your  defenses and take advantage of  the resources that are there and  speed up cell division and go  forth and multiply.  For the yeast.  Not nearly that fun for them.  Yes?  >> Your comments on these things  passing down a few generations  reminds me of part of a book  actually talking about a study  in Sweden that looked at people  who were born in famine and then  had children and then their  progeny developed something due  to methylation of genes and they  were having a problem with  responding to normal conditions  again.  >> Two generations later?  >> Yes.  >> And the question is?  >> Is that the same thing?  >> It could be.  So one of, there's a number of  different models that we have.  I'm sorry, the question is, in  humans there is an observation  that when people experience  famine, there are some changes  that can last for at least two  generations that make the  grandchildren respond  differently to different  environments.  And in that case, I guess this  done by methylation of the  genome.  So there's different mechanisms  for changing which genes will be  activated and responded. 

 Some of them are permanent like  a mutation.  If you just actually physically  remove the gene, it can't make  that any more.  But you can also pack up a  region of the genome very  tightly and make it inaccessible  to everything else.  So there's alterations to the  DNA that don't change the  sequence but change the  properties of it.  Methylation is one of those and  that's a field called  epigenetics.  So one theory of how this memory  gets passed on, we call it  memory just kind of to be cute,  I don't think they actually  remember stuff because they have  no brains.  So one theory is that there's  epigenetics.  There's physical modifications  to the genome that change it.  Another theory is that in that  initial burst, proteins get  synthesized at a certain level  and that those proteins get  physically passed on to the  daughter cells.  So, could be. 

 We're working on understanding  the mechanism but epigenetic  modifications is a prime  candidate.  So one thing that I meant to  mention and actually forgot is I  said before that really the real  action of things is in the  proteins of the cells.  That's what the cell is using to  do stuff.  There is active RNAs but we  still think that the useful end  product of a gene is a protein.  So why don't we just measure  proteins?  Why are we messing around with  this RNA business?  And the reason is it's just  really hard still and the  technology's just not quite  there.  You can measure single proteins  and there is a mass spectrometry  system being developed to you to  assay proteins on a genomic  level but they're still being  developed.  We actually have just started an  awesome collaboration with a  fantastic chemist on campus  who's one of the people involved  in developing more high  throughput mass spectrometry.  So we're going to begin to look  at which proteins because really  because an RNA transcript goes  up doesn't necessarily mean that  transcript is being used to make  a protein.  There's a whole other step that  can theoretically be regulated.  So we kind of make the glib  assumption that increased  transcript of an RNA means more  protein. 

 But it's not necessarily true.  It means that the cell has  increased its capacity to make a  protein, should it then decide  to do so.  Yes?  >> Each array contains 6,000  spots each of which corresponds  to a specific gene?  >> Yes.  >> That sounds like a technical  nightmare.  How can that be only $300?  >> Only $300.  Sorry, the question is so each  array contains 6,000 spots.  Each one corresponding to a  single gene.  Very hard to get those teeny  little spots on there.  How can it cost only $300?  So the ones in our lab actually  cost only about $10.  So we make them ourselves. 

 We've got a robot that has these  fantastically precise little  pins.  It dips into these plates that  contain different  oligonucleotides and it pokes  them right there on the slide.  These are very crude micro  arrays.  There's far more sophisticated  systems for developing them.  The chemistry for creating  oligonucleotides is very  understood and very inexpensive.  So even for someone like me in a  lab, if I want a particular  sequence of DNA, I go to a web  site, type in what I want, press  go, give them eight bucks and  they send it to me.  And that's a very profitable  business.  The chemistry for synthesizing  oligonucleotides onto DNA  surfaces is different and a lot  more sophisticated, but it's  highly multiplexed and it's also  a very profitable business at  $300.  >> How do you know you're  getting all 6,000 genes  expressed on this micro array?  >> So are you asking what kind  of controls do we do to verify  the data?  >> It seems to me by choosing  various oligonucleotides you're  not going to get all 6,000  genes.  There could be redundancy, etc. 

 >> Right.  Sorry, the question is, in the  synthesis of the genes, I'm  sorry in the synthesis of the  DNA micro arrays, how can you  trust that a single spot is  actually working as a probe for  the particular gene that you're  interested in.  Across all them.  Is that a pretty good summary?  Anyone from Nimblegen here?  No.  Affymetrix?  No.  I'm actually not sure about the  controls that go into the  synthesis.  But it's a very good question.  But one of the companies that  makes these is local.  In Madison, Nimblegen.  So you can call them up. 

 Yes?  I'm sorry, let me just say one  more thing and then I'll get  right back to you.  There are other methods for  measuring the level of a  particular RNA.  There's something called QPCR or  RTPCR that for a single gene  allows you to measure a  particular gene.  It's not a system that's easily  multiplexed to the whole system.  So for a particular, and that's  often something that we do after  we do a micro array we'll take a  few candidate genes and measure  the RNA with a different method  and make sure that the two  methods are correlating and  giving us more or less the same  answer.  There's also sequencing methods  coming down the pipe where  instead of hybridizing to a  particular spot, you'll just  take the whole pool of RNA,  sequence everything in that bag  and then figure out after the  fact what you have.  Those are being used but  fantastically expensive.  But will come down.  Yes?  >> What is the average life of  the yeast cell in a benign  environment.  >> What's the average life of a  yeast cell?  You mean how long they live?  >> Yes. 

 >> What's the average life of a  yeast cell in a benign  environment?  In the lab, like I said, they  grow in happy town, happy yeast  town.  And their doubling time is 90  minutes.  So that means every 90 minutes  they bud off a new cell.  So there's a couple, we think  about longevity in yeast in a  couple different ways.  We think about their replicative  life span.  How long they can continue  budding off new cells.  And then their chronological  life span, how long can they  continue being a viable  organism.  And so just like human beings we  can reproduce for some time and  then we can live for long beyond  that.  What's kind of cool is if you  look at these yeast cells over  here, so they've got this  awesome crown and when a new  yeast cell buds off it leaves  that scar.  So each one of those little  things is a physical scar that's  a memory of a cell division  event. 

 And what's thought is that the  replicative life span of the  yeast cell is pretty much  determined by how much space  there is on the surface of the  cell for those little scars.  I don't know offhand exactly how  many it is.  Yes?  >> You may have answered this  but along the lines of the  observation that the response to  stress sustains itself after  several generations.  I guess I could imagine several  mechanisms, one would be that  the proteins would be diluted  and gradually be diluted out.  And another would be that  certain proteins like the  repressors would be diluted out.  And I thought I heard you say  that you were looking at that  and hadn't really got the answer  yet.  >> So the question is about  different mechanisms for  maintaining this robustness over  time.  One possibility is that when the  cells get stressed, they produce  a whole bunch of proteins but  then they divide and now there's  two cells and only one batch of  proteins.  And so over time, the protein  just gets diluted out.  And the memory lasts longer than  you'd expect if that were the  case. 

 So we can sort of, I'm not going  to describe the experiment.  But we know it's more  complicated than that than just  a pool of protein getting  diluted out over time.  The other possibility is that  there's some proteins that get  created that are in turn  involved in activating other  genes.  So like a repressor or an  activator.  So maybe that protein is what's  getting diluted out and then the  consequences of that protein  being there are sort of creating  more protein or creating more of  that same protein and we just  don't know if that's the case  yet.  So we're working on looking at  candidate proteins and, like I  said, we're also working with  this mass spec lab to get a  sense of which proteins are  there and for how long and how  that changes.  But we're very curious in  knowing how this happens.  Yes?  >> It sounded like you had some  research that you saw potential  for publishing in the future?  >> Me?  >> Yes.  So what is that specifically if  you could explain it to us?  >> Okay, so I work on a couple  different projects.  One of them is just trying to  understand the role of a  particular gene in regulating a  particular response. 

 So what I'm really interested in  is, what I'm interested in as a  researcher is understanding this  signaling network that  recognizes that something has  changed in the environment and  sends the signal into the  nucleus.  And understanding is, once it  gets to the nucleus is it the  same signal responding to  different stresses or is it  different signals that all are  doing the same, happen to be  doing the same thing or are  there certain networks that  address the regulation of  certain subsets of genes and  other and networks that are  addressing the regulation of  different subsets of genes?  So what I'm working on right now  is a genetic screen to try to  identify all of the yeast genes  that are required for a  completely robust genetic  response to all of these  different stresses.  And I have great faith and  optimism that's sometimes  difficult to maintain.  Right now I feel pretty good  about it.  So it was a good time to ask the  question.  Last week, not so good.  Yes?  Go ahead.  >> Going back to the  applications for like human  cells and stuff how would you  apply, like after you analyze  all the micro arrays and stuff  how do apply your analysis to  the human cells?  Like for chemotherapy, for  example?  >> Right.  So just the phenomenon of  acquired stress resistance is  known and is already at times  used in human therapy.  So apparently one of the real  risks of open heart surgery, for  example, isn't so much the  surgery but after it's over when  the blood supply is  reintroduced, there's a massive  influx of oxygen. 

 And that massive influx of  oxygen is very stressful to the  cell.  Even though they need it, it's a  big change in their environment  and a lot of damage can be  caused if the blood supply is  reestablished very quickly.  And what's already done is  different methods of this  essentially stressing out the  heart cells immediately before  the reintroduction of the blood.  So that's sort of an application  of the general principle of  acquired stress resistance which  has been observed in a lot of  different organisms.  What we're focused on right now  a lot of the time is this  biofuels initiative.  So, as you probably know, just  last year the University of  Wisconsin got awarded  a $150 million grant from the  Department of Energy to begin  establishing the Great Lakes  Biofuels Research C--  I can't remember what the C  stands for.  Center, let's go with.  So yeast, for example ferments  sugar into alcohol, but they  stop after a certain point.  Like ethanol is also toxic to  the yeast.  Even though they are making it,  after a certain while they stop  and they do something else with  it. 

 If you could somehow make the  cells more robust against  ethanol, and ethanol is one of  the stresses that we look at, if  you could essentially understand  what ethanol is doing to them,  how they are mounting a response  and then make genetic  manipulations to help them make  that response more effectively,  maybe you could end up with an  industrial yeast strain that  could produce ethanol at greater  concentrations.  So that's one thing that's being  looked at pretty closely in our  lab and many others is  understanding how yeast respond  to ethanol and how we can  improve their tolerance to it.  Or improve their capacity for  synthesizing it.  Yes?  >> Is the following known, the  organism that has the fewest  genes.  Yeast has 6,000.  >> Yeast has 6,000.  >> The human has about 30,000.  >> 30,000.  So you're asking for the bottom  number?  So the question is, what's  the fewest number of genes you  can have?  I don't remember the exact  number, but it's a symbiotic  organism.  Somebody help me out here. 

 Someone knows.  Anyway it's some symbiotic  bacteria.  It's smaller than you'd think.  I thought it was 600 or 900.  But I'm not sure.  But like I said, it's a  symbiotic or a parasitic  organism that lives in a  well-defined environment of  another animal.  And maybe needs fewer genes  because it's reliably receiving  product.  >> And the bottom number when  you can live independently from  another?  >> I don't know offhand.  >> Okay.  >> It's a good question. 

 So Fred Blattner is a professor  in the Department of Genetics,  and he was the guy to first  sequence the E. coli genome.  He's done some very interesting  work on creating a minimal E.  coli genome so deleting as many  genes as he possibly can and  making this sort of streamlined  workhorse organism.  I think we might be running out  of time.  Not exactly sure when this is  supposed end.  But it looks like that's it.  So thank you, very much.  Great questions.  [APPLAUSE]