WEBVTT 00:00:33.000 --> 00:00:42.000 Good morning. Good morning. 00:00:42.000 --> 00:00:49.000 So, what I would like to do today is pick up on our basic theme of 00:00:49.000 --> 00:00:56.000 molecular biology. We've talked about DNA replication. 00:00:56.000 --> 00:01:03.000 The transcription of DNA into RNA, and the translation of RNA 00:01:03.000 --> 00:01:09.000 into protein. We discussed last time some of the variations between 00:01:09.000 --> 00:01:15.000 different types of organisms: viruses, prokaryotes, 00:01:15.000 --> 00:01:21.000 eukaryotes, with respect to the details of how they do that in 00:01:21.000 --> 00:01:27.000 general that bacteria have circular DNA chromosomes typically 00:01:27.000 --> 00:01:32.000 that eukaryotes have linear chromosomes, 00:01:32.000 --> 00:01:36.000 etc. What I'd like to talk about today is variation, 00:01:36.000 --> 00:01:41.000 but variation not between organisms but within an organism from time to 00:01:41.000 --> 00:01:46.000 time and place to place, namely, how it is that some genes or 00:01:46.000 --> 00:01:50.000 gene activities are turned on, on some occasions, and turned off on 00:01:50.000 --> 00:01:55.000 other occasions. This is, obviously, 00:01:55.000 --> 00:02:00.000 a very important problem to an organism, particularly 00:02:00.000 --> 00:02:03.000 to somebody like you who's a multi-cellular organism, 00:02:03.000 --> 00:02:06.000 and has the same DNA instruction set in all of your cells. 00:02:06.000 --> 00:02:09.000 It's obviously quite important to make sure that the same basic code 00:02:09.000 --> 00:02:13.000 is doing different things in different cells. 00:02:13.000 --> 00:02:16.000 It's important, also, to a bacterium to make sure that 00:02:16.000 --> 00:02:19.000 it's doing different things at different times, 00:02:19.000 --> 00:02:23.000 depending on its environment. So, I'm going to talk about a very 00:02:23.000 --> 00:02:26.000 particular system today as an illustration of how genes are 00:02:26.000 --> 00:02:30.000 regulated, but before we do that, let's 00:02:30.000 --> 00:02:35.000 Ask, where are the different places in this picture? 00:02:35.000 --> 00:02:40.000 DNA goes to DNA goes to RNA goes to protein, in which you might, 00:02:40.000 --> 00:02:45.000 in principle, regulate the activity of a gene. Could you regulate the 00:02:45.000 --> 00:02:50.000 activity of a gene by actually changing the DNA encoded in the 00:02:50.000 --> 00:02:55.000 genome? So, why not? Because what? It becomes a 00:02:55.000 --> 00:03:00.000 different gene. Yeah, that's just a definition. 00:03:00.000 --> 00:03:05.000 Why couldn't the cell just decide that I want this gene now to change 00:03:05.000 --> 00:03:10.000 in some way? Oh, I don't know, I'll alter the DNA 00:03:10.000 --> 00:03:16.000 sequence in some way. And, that'll make the gene work. 00:03:16.000 --> 00:03:21.000 Could that happen? Is that allowed? Yeah, it turns out to happen. 00:03:21.000 --> 00:03:27.000 It's not the most common thing, and it's not the thing they'll talk 00:03:27.000 --> 00:03:32.000 about in the textbooks a lot but you can actually do regulation. 00:03:32.000 --> 00:03:37.000 So, the levels of regulation are many, and one is actually at the 00:03:37.000 --> 00:03:42.000 level of DNA rearrangement. As we'll come to later in the 00:03:42.000 --> 00:03:47.000 course, for example, your immune system creates new, 00:03:47.000 --> 00:03:52.000 functional genes by rearranging locally some pieces of DNA, 00:03:52.000 --> 00:03:57.000 some bacteria, particularly infectious organisms control whether 00:03:57.000 --> 00:04:01.000 genes are turned on or off by actually going in there, 00:04:01.000 --> 00:04:04.000 and flipping around a piece of DNA in their chromosome. 00:04:04.000 --> 00:04:07.000 And, that's how they turn the gene on or off is they actually go in and 00:04:07.000 --> 00:04:10.000 change the genome. There's some protein that actually 00:04:10.000 --> 00:04:13.000 flips the orientation of a segment of DNA. Now, these are a little 00:04:13.000 --> 00:04:16.000 funky, and we're not going to talk a lot about them, 00:04:16.000 --> 00:04:19.000 but you should know, almost anything that can happen does 00:04:19.000 --> 00:04:22.000 happen and gets exploited in different ways by organisms. 00:04:22.000 --> 00:04:25.000 So, DNA rearrangement certainly happens. It's rare, 00:04:25.000 --> 00:04:29.000 but it's always cool when it happens. 00:04:29.000 --> 00:04:34.000 So, it's fun to look at. And, something like the immune 00:04:34.000 --> 00:04:40.000 system can't be dismissed as simply an oddity. That's an incredibly 00:04:40.000 --> 00:04:45.000 important thing. The most common form is at the 00:04:45.000 --> 00:04:51.000 level of transcriptional regulation, where whether or not a transcript 00:04:51.000 --> 00:04:57.000 gets made is how it's processed can be different. First off, 00:04:57.000 --> 00:05:02.000 the initiation of transcription that RNA polymerase should happen to 00:05:02.000 --> 00:05:06.000 sit down at this gene on this occasion and start transcribing it 00:05:06.000 --> 00:05:10.000 is a potentially regulatable (sic) step that maybe you're only going to 00:05:10.000 --> 00:05:14.000 turn on the gene for beta-globin and alpha-globin that together make the 00:05:14.000 --> 00:05:18.000 two components of hemoglobin, and you're only going to turn them 00:05:18.000 --> 00:05:22.000 on in red blood cells, or red blood cell precursors, 00:05:22.000 --> 00:05:26.000 and that could be done at the level of whether or not you make the 00:05:26.000 --> 00:05:30.000 message in the first place. That's one place it can be done. 00:05:30.000 --> 00:05:35.000 Another place is the splicing choices that you make. 00:05:35.000 --> 00:05:40.000 With respect to your message, you get this thing with a number of 00:05:40.000 --> 00:05:45.000 different potential exons, and you can regulate how this gene 00:05:45.000 --> 00:05:50.000 is used by deciding to splice it this way, and skip over that exon 00:05:50.000 --> 00:05:55.000 perhaps, or not skip over that exon. That alternative spicing is a 00:05:55.000 --> 00:06:00.000 powerful way to regulate. And then finally, you can also 00:06:00.000 --> 00:06:06.000 regulate at the level of mRNA stability. 00:06:06.000 --> 00:06:09.000 Stability means the persistence of the message, the degradation of the 00:06:09.000 --> 00:06:12.000 message. It could be that in certain cells, 00:06:12.000 --> 00:06:15.000 the message is protected so that it hangs around longer. 00:06:15.000 --> 00:06:18.000 And, in other cells, perhaps, it's unprotected and it's 00:06:18.000 --> 00:06:21.000 degraded very rapidly. If it's degraded very rapidly, 00:06:21.000 --> 00:06:24.000 it doesn't get a chance to make a protein or maybe it doesn't get to 00:06:24.000 --> 00:06:27.000 make too many copies of the protein. If it's persistent for a long time, 00:06:27.000 --> 00:06:30.000 it can make a lot of copies of protein. 00:06:30.000 --> 00:06:35.000 All of those things can and do occur. Then, of course, 00:06:35.000 --> 00:06:40.000 there is the regulation at the level of translation. 00:06:40.000 --> 00:06:46.000 Translation, if I give you an mRNA, is it automatically going to be 00:06:46.000 --> 00:06:51.000 translated? Maybe the cell has a way to sequester the RNA to ramp it 00:06:51.000 --> 00:06:57.000 up in some way so that it doesn't get to the ribosome under 00:06:57.000 --> 00:07:01.000 some conditions, and under other conditions it does 00:07:01.000 --> 00:07:05.000 get to the ribosome, or some ways to block in other 00:07:05.000 --> 00:07:08.000 manners than just sequestering it, but to physically block whether or 00:07:08.000 --> 00:07:12.000 not this message gets translated, what turns out that there's a 00:07:12.000 --> 00:07:15.000 tremendous amount of that. It's, again, not the most common, 00:07:15.000 --> 00:07:19.000 but we're learning, particularly over the last couple of years, 00:07:19.000 --> 00:07:22.000 that regulation of the translation of an mRNA is important. 00:07:22.000 --> 00:07:26.000 There are, although I won't talk about them at length, 00:07:26.000 --> 00:07:30.000 an exciting new set of genes called micro RNA's, 00:07:30.000 --> 00:07:34.000 teeny little RNAs that encode 21-22 base pair segments that are able to 00:07:34.000 --> 00:07:39.000 pair with a messenger RNA and interfere in some ways partially 00:07:39.000 --> 00:07:43.000 with its translatability. And so, by the number and the kinds 00:07:43.000 --> 00:07:48.000 of little micro RNAs that are there, organisms can tweak up or down how 00:07:48.000 --> 00:07:52.000 actively a particular message is being translated. 00:07:52.000 --> 00:07:57.000 So, the ability to regulate translation in a number of different 00:07:57.000 --> 00:08:01.000 ways is important. And then, of course, 00:08:01.000 --> 00:08:06.000 there's post-translational control. Once a protein is made, 00:08:06.000 --> 00:08:10.000 there's post-translational regulation that could happen. 00:08:10.000 --> 00:08:14.000 It could be that the protein is modified in some way. 00:08:14.000 --> 00:08:18.000 The proteins say completely inactive unless you put a phosphate 00:08:18.000 --> 00:08:22.000 group on it, and some enzyme comes along and puts a phosphate group on 00:08:22.000 --> 00:08:26.000 it. Or, it's inactive until you take off the phosphate group. 00:08:26.000 --> 00:08:30.000 All sorts of post-translational modifications can occur to proteins 00:08:30.000 --> 00:08:33.000 after the amino acid chain is made that can affect whether or not the 00:08:33.000 --> 00:08:37.000 protein is active. Every one of these is potentially a 00:08:37.000 --> 00:08:41.000 step by which an organism can regulate whether or not you have a 00:08:41.000 --> 00:08:45.000 certain biochemical activity present in a certain amount at a certain 00:08:45.000 --> 00:08:49.000 time. And, every one of these gets used. This is the thing about 00:08:49.000 --> 00:08:53.000 coming to a system that has been in the process of evolution for three 00:08:53.000 --> 00:08:57.000 and a half billion years is that even little differences can be 00:08:57.000 --> 00:09:01.000 fought over as competitive advantages, and can be fixed 00:09:01.000 --> 00:09:05.000 by an organism. So, if a tiny little thing began to 00:09:05.000 --> 00:09:10.000 help the organism slightly, it could reach fixation. And, 00:09:10.000 --> 00:09:15.000 you're coming along to this system, which has had about three and a half 00:09:15.000 --> 00:09:20.000 billion years of patches to the software code, 00:09:20.000 --> 00:09:25.000 and it's just got all sorts of layers and regulation piled on top 00:09:25.000 --> 00:09:30.000 of it. All of these things happen. But, what we think is the most 00:09:30.000 --> 00:09:35.000 important out of this whole collection is this guy. 00:09:35.000 --> 00:09:40.000 The fundamental place at which you're going to regulate whether or 00:09:40.000 --> 00:09:45.000 not you have the product of a gene is whether you bother to transcribe 00:09:45.000 --> 00:09:50.000 its RNA. But I do want to say because, yes? And, 00:09:50.000 --> 00:09:55.000 which exons you used and which aren't? Yeah, 00:09:55.000 --> 00:10:00.000 well, there are tissue-specific factors that are gene-specific 00:10:00.000 --> 00:10:03.000 that can influence that. And, surprisingly little is known 00:10:03.000 --> 00:10:06.000 about the details. There are a couple of cases where 00:10:06.000 --> 00:10:10.000 people know, but as you'd imagine, you actually need a regulatory 00:10:10.000 --> 00:10:13.000 system in that tissue to be able to decide to skip over that exon. 00:10:13.000 --> 00:10:17.000 And, the mechanics of that surprisingly are understood in very 00:10:17.000 --> 00:10:20.000 few cases. And, you might think that evolution 00:10:20.000 --> 00:10:23.000 wouldn't like to use that as the most common thing because you really 00:10:23.000 --> 00:10:27.000 do have to make a specialized thing to do that. So, that's what 00:10:27.000 --> 00:10:30.000 happens on these. That's one in particular where I 00:10:30.000 --> 00:10:33.000 think a tremendous amount of more work has to happen. 00:10:33.000 --> 00:10:36.000 mRNA stability, we understand some of it but not all the factors in 00:10:36.000 --> 00:10:39.000 this business. I was telling you about translation 00:10:39.000 --> 00:10:42.000 with these little micro-RNAs is stuff that's really only a few years 00:10:42.000 --> 00:10:45.000 old that people have come to understand. So, 00:10:45.000 --> 00:10:48.000 there's a lot to be understood about these things. I'm going to tell you 00:10:48.000 --> 00:10:51.000 about initiation of mRNAs, because it's the area where we know 00:10:51.000 --> 00:10:54.000 the most, and I think it'll give you a good idea of the general paradigm. 00:10:54.000 --> 00:10:57.000 But, any of you who want to go into this will find that there's a 00:10:57.000 --> 00:11:00.000 tremendous amount more to still be discovered about these things. 00:11:00.000 --> 00:11:05.000 So, the amount of protein that a cell might make varies wildly. 00:11:05.000 --> 00:11:10.000 Your red blood cells, 80% of your red blood cells, 00:11:10.000 --> 00:11:15.000 protein, is alpha or beta-globin. It's a huge amount. That's not 00:11:15.000 --> 00:11:21.000 true in any other cell in your body. So, we were talking about pretty 00:11:21.000 --> 00:11:26.000 significant ranges of difference as to how much protein is made. 00:11:26.000 --> 00:11:31.000 How do things like that happen? Well, I'm going to describe the 00:11:31.000 --> 00:11:37.000 simplest and classic case of gene regulation and bacteria, 00:11:37.000 --> 00:11:43.000 and in particular, the famous lack operon of E coli. 00:11:43.000 --> 00:11:49.000 So, this was the first case in which regulation was ever really 00:11:49.000 --> 00:11:55.000 worked out, and it stands today as a very good paradigm of how 00:11:55.000 --> 00:12:00.000 regulation works. E coli, in order to grow, 00:12:00.000 --> 00:12:05.000 needs a carbon source. In particular, E coli is fond of sugar. 00:12:05.000 --> 00:12:10.000 It would like to have a sugar to grow on. Given a choice, 00:12:10.000 --> 00:12:15.000 what's E coli's favorite sugar? It's glucose, right, because we 00:12:15.000 --> 00:12:20.000 have the whole cycle of glucose. The whole pathway of glucose goes 00:12:20.000 --> 00:12:25.000 to pyruvate, which we've talked about, and glucose is the preferred 00:12:25.000 --> 00:12:30.000 sugar to go into that pathway, OK, of glycolysis. 00:12:30.000 --> 00:12:36.000 Glycolysis: the breakdown of glucose. But, suppose there's no glucose 00:12:36.000 --> 00:12:42.000 available. Is E coli willing to have a different sugar? 00:12:42.000 --> 00:12:48.000 Sure, because E coli's not stupid. If it were to refuse another sugar, 00:12:48.000 --> 00:12:54.000 it wouldn't be able to grow. So, it has a variety of pathways that will 00:12:54.000 --> 00:13:00.000 shunt other sugars to glucose, which will then allow you to go 00:13:00.000 --> 00:13:08.000 through glycolysis, etc. Now, given a choice, 00:13:08.000 --> 00:13:16.000 it would prefer to use the glucose. But if not, suppose you gave it 00:13:16.000 --> 00:13:24.000 lactose. Lactose is a disaccharide. It's milk sugar, and I'll just 00:13:24.000 --> 00:13:32.000 briefly sketch, so lactose is a disaccharide where 00:13:32.000 --> 00:13:40.000 you've got a glucose and a galactose. 00:13:40.000 --> 00:13:50.000 Glucose plus galactose equals lactose. So, if E coli is given 00:13:50.000 --> 00:14:00.000 galactose, it is able to break it down into glucose plus galactose. 00:14:00.000 --> 00:14:08.000 And it does that by a particular enzyme called beta galactosidase, 00:14:08.000 --> 00:14:17.000 which breaks down glactosides. And, it'll give you galactose plus 00:14:17.000 --> 00:14:25.000 glucose. How much beta-galactosidase does an E coli 00:14:25.000 --> 00:14:32.000 cell have around? Sorry? None? But how does it do this? 00:14:32.000 --> 00:14:38.000 When it needs it, it'll synthesize it. When it needs it, 00:14:38.000 --> 00:14:43.000 like, there's no glucose and there's a lot of galactose around, 00:14:43.000 --> 00:14:49.000 how much of it will there be? A lot. It turns out that in 00:14:49.000 --> 00:14:54.000 circumstances where E coli is dependent on galactose as its fuel, 00:14:54.000 --> 00:15:00.000 something like 10% of total protein 00:15:00.000 --> 00:15:06.000 can be beta-gal under the circumstances when you have 00:15:06.000 --> 00:15:13.000 galactose but no glucose. Sorry? Sorry, when you have 00:15:13.000 --> 00:15:19.000 lactose but no glucose. Thank you. So, when you have 00:15:19.000 --> 00:15:26.000 lactose but no glucose, E coli has 10% of its protein weight 00:15:26.000 --> 00:15:33.000 as beta-galactosidase. Wow. But when you have glucose 00:15:33.000 --> 00:15:39.000 around or you don't have lactose around, you have very little. 00:15:39.000 --> 00:15:45.000 It could be almost none, trace amounts. So, why do this? 00:15:45.000 --> 00:15:51.000 Why not, for example, just have a far more reasonable some compromise? 00:15:51.000 --> 00:15:57.000 Like, let's always just have 1% of beta-galactosidase. 00:15:57.000 --> 00:16:04.000 Why do we need the 0-10%? 10%'s actually extremely high. 00:16:04.000 --> 00:16:09.000 So what. It's a good insurance policy. So, if I only have 00:16:09.000 --> 00:16:15.000 galactose, I need more. Well, I mean, 1% will still digest 00:16:15.000 --> 00:16:21.000 it. I'll still do it. What's the problem? Sorry? 00:16:21.000 --> 00:16:27.000 So what, I do it at a slower rate. Life's long. Why not? Ah, it has 00:16:27.000 --> 00:16:31.000 to compete. So, if the cell to the left had a 00:16:31.000 --> 00:16:35.000 mutation that got it to produce four times as much, 00:16:35.000 --> 00:16:38.000 then it would soak up the lactose in the environment, 00:16:38.000 --> 00:16:42.000 grow faster, etc. etc., and we could have competed. 00:16:42.000 --> 00:16:45.000 So, these little tuning mutations have a huge effect amongst this 00:16:45.000 --> 00:16:49.000 competing population of bacteria. And so, if E coli currently thinks 00:16:49.000 --> 00:16:53.000 that it's really good to have almost non at sometimes and 10% at other 00:16:53.000 --> 00:16:56.000 times, you can bet that it's worked that out through the product of 00:16:56.000 --> 00:17:00.000 pretty rigorous competition, that it doesn't want to waste the 00:17:00.000 --> 00:17:03.000 energy making this when you don't need it, and that when you do need 00:17:03.000 --> 00:17:07.000 it, you really have to compete hard by growing as fast as you can when 00:17:07.000 --> 00:17:11.000 you have that lactose around. OK. So, how does it actually get 00:17:11.000 --> 00:17:16.000 the lactose, sorry, keep me honest on lactose versus 00:17:16.000 --> 00:17:22.000 galactose, into the cell? It turns out that it also has 00:17:22.000 --> 00:17:27.000 another gene product, another protein, which is a lactose 00:17:27.000 --> 00:17:32.000 permease. And, any guesses as to what a 00:17:32.000 --> 00:17:38.000 lactose permease does? It makes the cell permeable to 00:17:38.000 --> 00:17:43.000 lactose, right, good. So, the lactose can get into 00:17:43.000 --> 00:17:49.000 the cell, and then beta-gal can break it down into galactose plus 00:17:49.000 --> 00:17:54.000 glucose. These two things, in fact, both get regulated, 00:17:54.000 --> 00:18:00.000 beta-gal and this lactose permease. So, how does it work? 00:18:00.000 --> 00:18:07.000 Let's take a look now at the structure of the lack operon. 00:18:07.000 --> 00:18:14.000 So, I mentioned briefly last time, what's an operon? Remember we said 00:18:14.000 --> 00:18:21.000 that in bacteria, you often made a transcript that had 00:18:21.000 --> 00:18:29.000 multiple proteins that were encoded on it. 00:18:29.000 --> 00:18:33.000 A single mRNA could get made, and multiple starts for translation 00:18:33.000 --> 00:18:37.000 could occur, and you could make multiple proteins. 00:18:37.000 --> 00:18:41.000 And, this would be a good thing if you wanted to make a bunch of 00:18:41.000 --> 00:18:45.000 proteins that were a part of the same biochemical pathway. 00:18:45.000 --> 00:18:49.000 Such an object, a regulated piece of DNA that makes a transcript 00:18:49.000 --> 00:18:53.000 encoding multiple polypeptides is called an operon because they're 00:18:53.000 --> 00:18:57.000 operated together. So, let's take a look here at the 00:18:57.000 --> 00:19:03.000 lack operon. I said there was a promoter. 00:19:03.000 --> 00:19:09.000 Here is a promoter for the operon, and we'll call it P lack, promoter 00:19:09.000 --> 00:19:16.000 for the lack operon. Here is the first gene that is 00:19:16.000 --> 00:19:23.000 encoded. So, the message will start here, actually about here, 00:19:23.000 --> 00:19:30.000 and start going off. And, the first gene is given the name lack Z. 00:19:30.000 --> 00:19:34.000 It happens to encode beta-galactosidase enzyme. 00:19:34.000 --> 00:19:38.000 Remember, they did a mutant hunt, and when they did the mutant hunt, 00:19:38.000 --> 00:19:42.000 they didn't know what each gene was as they isolated mutants. 00:19:42.000 --> 00:19:46.000 So, they just gave them names of letters. And so, 00:19:46.000 --> 00:19:50.000 it's called lack Z. And, everybody in molecular biology 00:19:50.000 --> 00:19:54.000 knows this is the lack Z gene, although Z has nothing to do with 00:19:54.000 --> 00:19:58.000 beta-galactosidase. It was just the letter given to it. 00:19:58.000 --> 00:20:02.000 But, it's stuck. Next is lack Y. 00:20:02.000 --> 00:20:07.000 And, that encodes the permease. And, there is also lack A, which 00:20:07.000 --> 00:20:12.000 encodes a transacetylase, and as far as I'm concerned you can 00:20:12.000 --> 00:20:17.000 forget about it. OK, but I just mentioned that it is 00:20:17.000 --> 00:20:22.000 there, and it actually does make three polypeptides. 00:20:22.000 --> 00:20:27.000 We won't worry about it, OK, but it does make a 00:20:27.000 --> 00:20:32.000 transacetylase, OK? But it won't figure in what we're 00:20:32.000 --> 00:20:36.000 going to talk about, and actually remarkably little is 00:20:36.000 --> 00:20:41.000 known about the transacetylase. There's also one other gene I need 00:20:41.000 --> 00:20:46.000 to talk about, and that's over here, 00:20:46.000 --> 00:20:50.000 and that's called lack I. And, it too has a promoter, 00:20:50.000 --> 00:20:55.000 which we can call PI, for the promoter for lack I. 00:20:55.000 --> 00:21:00.000 And, this encodes a very interesting protein. 00:21:00.000 --> 00:21:05.000 So, we get here one message encoding one polypeptide here. 00:21:05.000 --> 00:21:11.000 This mRNA encodes one polypeptide. It is monocystronic. This guy here 00:21:11.000 --> 00:21:17.000 is a polycystronic message. It has multiple cystrons, which is 00:21:17.000 --> 00:21:23.000 the dusty old name for these regions that were translated into distinct 00:21:23.000 --> 00:21:29.000 proteins. And so, that's that mRNA. 00:21:29.000 --> 00:21:40.000 So, lack I, this encodes a very interesting protein, 00:21:40.000 --> 00:21:52.000 which is called the lack repressor. The lack repressor, actually I'll 00:21:52.000 --> 00:22:04.000 bring this down a moment, is not an enzyme. 00:22:04.000 --> 00:22:10.000 It's not a self-surface channel for putting in galactose. 00:22:10.000 --> 00:22:17.000 It is a DNA binding protein. It binds to DNA. But, it's not a 00:22:17.000 --> 00:22:23.000 nonspecific DNA binding protein that binds to any old DNA. 00:22:23.000 --> 00:22:30.000 It has a sequence-specific preference. 00:22:30.000 --> 00:22:35.000 It's a protein that has a particular confirmation, a particular shape, 00:22:35.000 --> 00:22:40.000 a particular set of amino acids sticking out, that it combined into 00:22:40.000 --> 00:22:46.000 the major groove of DNA in a sequence-specific fashion such that 00:22:46.000 --> 00:22:51.000 it particularly likes to recognize a certain sequence of nucleotides and 00:22:51.000 --> 00:22:57.000 binds there. Where is the specific sequence of nucleotides where this 00:22:57.000 --> 00:23:03.000 guy likes to bind? It so happens that it's there. 00:23:03.000 --> 00:23:11.000 And this is called the operator sequence or the operator site. 00:23:11.000 --> 00:23:18.000 So, this protein likes to go and bind there. Now, 00:23:18.000 --> 00:23:26.000 I've drawn this, by the way, so that this operator site is 00:23:26.000 --> 00:23:34.000 actually right overlapping the promoter site. 00:23:34.000 --> 00:23:40.000 Who likes to bind at the promoter site? RNA polymerase. 00:23:40.000 --> 00:23:46.000 What's going to happen if the lack repressor protein is sitting there? 00:23:46.000 --> 00:23:52.000 RNA polymerase can't bind. It's just physically, 00:23:52.000 --> 00:23:58.000 blocked from binding. So, let's examine some cases here. 00:23:58.000 --> 00:24:06.000 Let's suppose that we look at here 00:24:06.000 --> 00:24:14.000 at our gene. We've got our promoter, P lack. We've got the operator site 00:24:14.000 --> 00:24:22.000 here. We've got the lack Z gene here, and we've got the lack 00:24:22.000 --> 00:24:31.000 repressor, lack I, the repressor sitting there. 00:24:31.000 --> 00:24:38.000 Polymerase tries to come along to this, and it's blocked. 00:24:38.000 --> 00:24:45.000 So, what will happen in terms of the transcription of the lack 00:24:45.000 --> 00:24:52.000 operon: no mRNA. So, that's great. 00:24:52.000 --> 00:24:59.000 So, we've solved one problem right off the bat. 00:24:59.000 --> 00:25:03.000 We want to be sure that sometimes there's going to be no mRNA made. 00:25:03.000 --> 00:25:07.000 This way, we're not going to waste any metabolic energy, 00:25:07.000 --> 00:25:11.000 making beta-galactosidase. Are we done? No? Why not. 00:25:11.000 --> 00:25:16.000 We've got to sometimes make beta-galactosidase. 00:25:16.000 --> 00:25:20.000 So, we've got to get that repressor off there. Well, 00:25:20.000 --> 00:25:24.000 how is the repressor going to come off there? When do we want the 00:25:24.000 --> 00:25:29.000 repressor off there: when there's lactose present. 00:25:29.000 --> 00:25:34.000 So, somehow we need to build some kind of an elaborate sensory 00:25:34.000 --> 00:25:39.000 mechanism that is able to tell when lactose is present, 00:25:39.000 --> 00:25:44.000 and send a signal to the repressor protein saying, 00:25:44.000 --> 00:25:49.000 hey, lactose is around. The signal gets transmitted all the 00:25:49.000 --> 00:25:55.000 way to the repressor protein, and the repressor protein comes off. 00:25:55.000 --> 00:26:00.000 What kind of an elaborate sensory mechanism might be built? 00:26:00.000 --> 00:26:05.000 Use lactose as what? So, this is actually pretty simple. 00:26:05.000 --> 00:26:11.000 You're saying just take lactose, and you want lactose to be its own 00:26:11.000 --> 00:26:16.000 signal? So, if lactose were to just bind to the repressor, 00:26:16.000 --> 00:26:21.000 the repressor might then know that there was lactose around. 00:26:21.000 --> 00:26:27.000 Well, what would it do if lactose bound to it? Sorry? Why 00:26:27.000 --> 00:26:33.000 would it fall off? Yep. More interested in the lactose. 00:26:33.000 --> 00:26:39.000 So, if you're suggestion, this is good. I like the design 00:26:39.000 --> 00:26:45.000 work going on here. The suggestion is that if lactose 00:26:45.000 --> 00:26:51.000 binds to this here, binds to our repressor, 00:26:51.000 --> 00:26:57.000 it's going to fall off because it's more interested in lactose 00:26:57.000 --> 00:27:03.000 than in the DNA. Now, how is the interest actually 00:27:03.000 --> 00:27:07.000 conveyed into something material? Because the actual level of 00:27:07.000 --> 00:27:11.000 cognitive like or dislike for DNA on the part of this polypeptide is 00:27:11.000 --> 00:27:15.000 unclear, you may be anthropomorphizing slightly with 00:27:15.000 --> 00:27:19.000 regard to this polypeptide chain. So, mechanistically, what's going 00:27:19.000 --> 00:27:23.000 to happen? Shape. Yes, shape? Change confirmation, 00:27:23.000 --> 00:27:27.000 the binding act, the act of binding lactose creates some energy, 00:27:27.000 --> 00:27:31.000 may change the shape of the protein, 00:27:31.000 --> 00:27:35.000 and that shape of the protein may, in the process of wiggling around to 00:27:35.000 --> 00:27:40.000 bind lactose may de-wiggle some other part of it that now no longer 00:27:40.000 --> 00:27:44.000 binds so well to DNA. That is exactly what happens. 00:27:44.000 --> 00:27:49.000 Good job. So, you guys have designed, in fact, 00:27:49.000 --> 00:27:54.000 what really happens. What happens is what's called an 00:27:54.000 --> 00:27:58.000 allosteric change. It just means other shape. 00:27:58.000 --> 00:28:03.000 So, it just changes its shape, that it changes shape on binding of 00:28:03.000 --> 00:28:10.000 lactose. And it falls off because it's less 00:28:10.000 --> 00:28:18.000 suitable for binding this particular DNA sequence when it's bound to 00:28:18.000 --> 00:28:26.000 lactose there. So, in this case, 00:28:26.000 --> 00:28:34.000 in the presence of lactose, lack I does not bind. 00:28:34.000 --> 00:28:44.000 And, the lack operon is transcribed. Yes? Uh-oh. OK, all right 00:28:44.000 --> 00:28:54.000 designers, here we've got a problem. You have such a cool system, 00:28:54.000 --> 00:29:03.000 right? You were going to sense lactose. 00:29:03.000 --> 00:29:10.000 Lactose was going to bind to the lack repressor, 00:29:10.000 --> 00:29:17.000 change its confirmation falloff: uh-oh. But, as you point out, 00:29:17.000 --> 00:29:25.000 how's it going to get any lactose, because there's not a lactose 00:29:25.000 --> 00:29:32.000 permease because the lactose permease is made by 00:29:32.000 --> 00:29:37.000 the same operon. So, what if, in fact, 00:29:37.000 --> 00:29:40.000 instead of getting one of these DOD mill speck kind of things of some 00:29:40.000 --> 00:29:43.000 repressor that is absolutely so tight that it never falls off under 00:29:43.000 --> 00:29:47.000 any circumstances, what if we build a slightly sloppy 00:29:47.000 --> 00:29:50.000 repressor that occasionally falls off, and occasionally allows 00:29:50.000 --> 00:29:53.000 transcription of the lack operon? Then, we'll have some trace 00:29:53.000 --> 00:29:56.000 quantities of permease around. With a little bit of permease 00:29:56.000 --> 00:30:00.000 around, a little lactose will get in. 00:30:00.000 --> 00:30:04.000 And, as long as even a little lactose gets in, 00:30:04.000 --> 00:30:08.000 it'll now shift the equilibrium so that the repressor is off more, 00:30:08.000 --> 00:30:12.000 and of course that will make more permease, and shift, 00:30:12.000 --> 00:30:16.000 and shift, and shift, and shift. So, as long as it's not 00:30:16.000 --> 00:30:21.000 so perfectly engineered as to have nothing being transcribed, 00:30:21.000 --> 00:30:25.000 so no mRNA is really very little mRNA. See, this is what's so good, 00:30:25.000 --> 00:30:29.000 I think, about having MIT students learn this stuff because there are 00:30:29.000 --> 00:30:33.000 all sorts of wonderful design principles here about how 00:30:33.000 --> 00:30:38.000 you build systems. And, I think this is just a very 00:30:38.000 --> 00:30:43.000 good example of how you build a system like this. 00:30:43.000 --> 00:30:48.000 Now, all right, so we now have the ability to have lack on and lack off, 00:30:48.000 --> 00:30:52.000 and that is lack off, mostly off because of your permease 00:30:52.000 --> 00:30:57.000 problem: very good. Now, let's take a little digression 00:30:57.000 --> 00:31:02.000 about, how do we know this? This kind of reasoning, 00:31:02.000 --> 00:31:06.000 I've now told you the answer. But let's actually take a look at 00:31:06.000 --> 00:31:10.000 understanding the evidence that lets you conclude this. 00:31:10.000 --> 00:31:14.000 So, in order to do this, and this is the famous work in 00:31:14.000 --> 00:31:18.000 molecular biology of Jacobin Manoux in the late '50s for which they won 00:31:18.000 --> 00:31:22.000 a Nobel Prize, they wanted to collect some mutants. 00:31:22.000 --> 00:31:26.000 Remember, this is before the time of DNA sequence or anything like 00:31:26.000 --> 00:31:30.000 that, and wanted to collect mutants that affected this process. 00:31:30.000 --> 00:31:37.000 So, in order to collect mutants that screwed up the regulation, 00:31:37.000 --> 00:31:45.000 they knew that beta-galactosidase was produced in much higher quantity 00:31:45.000 --> 00:31:53.000 if lactose was around. The difficulty with that was that 00:31:53.000 --> 00:32:01.000 wild type E coli, when you had no lactose would 00:32:01.000 --> 00:32:07.000 produce very little beta-gal, one unit of beta-gal, 00:32:07.000 --> 00:32:11.000 and in the presence of lactose, would produce a lot, let's call it 1, 00:32:11.000 --> 00:32:16.000 00 units of beta-gal. But, the problem with playing 00:32:16.000 --> 00:32:20.000 around with this is lactose is serving two different roles. 00:32:20.000 --> 00:32:25.000 Lactose is both the inducer of the expression of the gene by virtue of 00:32:25.000 --> 00:32:30.000 binding to the repressor, etc., etc. 00:32:30.000 --> 00:32:34.000 But, it's also the substrate for the enzyme because as beta-galactosidase 00:32:34.000 --> 00:32:38.000 gets made, it breaks down the lactose. So, there's less lactose 00:32:38.000 --> 00:32:43.000 in binding, and if you wanted to really study the regulatory controls, 00:32:43.000 --> 00:32:47.000 you have the problem that the thing that's inducing the gene by binding 00:32:47.000 --> 00:32:52.000 to the repressor is the thing that's getting destroyed by the product of 00:32:52.000 --> 00:32:56.000 the gene. So, it's going to make the kinetics of 00:32:56.000 --> 00:33:01.000 studying such a process really messy. It would be very nice if you could 00:33:01.000 --> 00:33:05.000 make a form of lactose that could induce beta-galactosidase by binding 00:33:05.000 --> 00:33:10.000 to the repressor, but wasn't itself digested. 00:33:10.000 --> 00:33:17.000 Chemically, in fact, you can do that. Chemically, 00:33:17.000 --> 00:33:24.000 it's possible to make a molecule called IPTG, which is a 00:33:24.000 --> 00:33:32.000 galactoside analog. And, what it does is this molecule 00:33:32.000 --> 00:33:41.000 here which I'll just sketch very quickly here, it's a sulfur there, 00:33:41.000 --> 00:33:50.000 and you can see vaguely similar, this is able to be an inducer. 00:33:50.000 --> 00:33:59.000 It'll induce beta-gal, but not a substrate. It won't get digested. 00:33:59.000 --> 00:34:04.000 So, it'll stick around as long as you want. It's also very convenient 00:34:04.000 --> 00:34:09.000 to use a molecule that was developed called ex-gal. 00:34:09.000 --> 00:34:15.000 Ex-gal again has a sugar moiety, and then it also has this kind of a 00:34:15.000 --> 00:34:20.000 funny double ring here, which is a chlorine, and a bromine, 00:34:20.000 --> 00:34:25.000 and etc. And, this guy here is not an inducer. It's not capable of 00:34:25.000 --> 00:34:31.000 being induced, of inducing beta-galactosidase 00:34:31.000 --> 00:34:37.000 expression. But, it is a substrate. 00:34:37.000 --> 00:34:43.000 It will be broken down by the enzyme, and rather neatly when it's 00:34:43.000 --> 00:34:49.000 broken down it turns blue. These two chemicals turned out to 00:34:49.000 --> 00:34:55.000 be very handy in trying to work out the regulation of the 00:34:55.000 --> 00:35:00.000 lack operon. So, if I, instead of adding lactose, 00:35:00.000 --> 00:35:06.000 if I think about adding IPTG, my inducer, when I add IPTG I'm going 00:35:06.000 --> 00:35:12.000 to get beta-gal produced. When I don't have IPTG, I won't 00:35:12.000 --> 00:35:18.000 produce beta-gal. But then I don't have a problem of 00:35:18.000 --> 00:35:24.000 this getting used up. So now, what kind of a mutant might 00:35:24.000 --> 00:35:29.000 I look for? I might look for a mutant that even 00:35:29.000 --> 00:35:34.000 in the absence of the inducer, IPTG, still produces a lot of 00:35:34.000 --> 00:35:39.000 beta-gal. Now, I can also look for mutants that no 00:35:39.000 --> 00:35:44.000 matter what never produce beta-gal, right? But, what would they likely 00:35:44.000 --> 00:35:50.000 be? They'd likely be structural mutations affecting the coding 00:35:50.000 --> 00:35:55.000 sequence of beta-gal, right? Those will happen. 00:35:55.000 --> 00:36:00.000 I can collect mutations that cause the E coli never to 00:36:00.000 --> 00:36:05.000 produce beta-gal. But that's not as interesting as 00:36:05.000 --> 00:36:11.000 collecting mutations that block the repression that cause beta-gal to be 00:36:11.000 --> 00:36:16.000 produced all of the time. So, how would I find such a mutant? 00:36:16.000 --> 00:36:22.000 I want to find a mutant that's producing a lot of beta-gal even 00:36:22.000 --> 00:36:27.000 when there's no IPTG. So, let's place some E coli on a 00:36:27.000 --> 00:36:33.000 plate. Should we put IPTG on a plate? No, so no IPTG. 00:36:33.000 --> 00:36:37.000 What do I look for? How do I tell whether or not any of 00:36:37.000 --> 00:36:42.000 these guys here is producing a lot of beta-gal? Yep? 00:36:42.000 --> 00:36:46.000 So, no IPTG, but put on ex-gal, and if anybody's producing a lot of 00:36:46.000 --> 00:36:51.000 beta-gal, what happens? They turn blue: very easy to go 00:36:51.000 --> 00:36:55.000 through lots of E coli like that looking for something blue. 00:36:55.000 --> 00:37:00.000 And so, lots of mutants were collected that were blue. 00:37:00.000 --> 00:37:05.000 And, these chemicals are still used today. They're routinely used in 00:37:05.000 --> 00:37:10.000 labs, ex-gal and stuff like that, making bugs turn blue because this 00:37:10.000 --> 00:37:15.000 has turned out to be such a well-studied system that we use it 00:37:15.000 --> 00:37:20.000 for a lot of things. So, mutants were found that were 00:37:20.000 --> 00:37:25.000 constituative. So, mutants were found that were 00:37:25.000 --> 00:37:30.000 constituative mutants. Constituative mutants: meaning 00:37:30.000 --> 00:37:35.000 expressing all the time, no longer regulated, so, 00:37:35.000 --> 00:37:40.000 characterizing these constituative mutants. 00:37:40.000 --> 00:37:44.000 It turns out that they fell into two different classes of constituative 00:37:44.000 --> 00:37:48.000 mutants. If we had enough time, and you could read the papers and 00:37:48.000 --> 00:37:52.000 all, what I would do is give you the descriptions that Jacobin Maneaux 00:37:52.000 --> 00:37:56.000 had of these funny mutants which they'd isolated and were trying to 00:37:56.000 --> 00:38:00.000 characterize, and how to puzzle out what was going on. 00:38:00.000 --> 00:38:04.000 But, it's complicated and hard, and makes your head hurt if you 00:38:04.000 --> 00:38:08.000 don't know what the answer is. So, I'm going to first tell you the 00:38:08.000 --> 00:38:12.000 answer of what's going on, and then sort of see how you would 00:38:12.000 --> 00:38:17.000 know that this was the case. But, imagine that you didn't know 00:38:17.000 --> 00:38:21.000 this answer, and had to puzzle this out from the data. 00:38:21.000 --> 00:38:25.000 So, suppose we had, so if there were going to be two 00:38:25.000 --> 00:38:30.000 kinds of mutants: mutant number one are operator constituents. 00:38:30.000 --> 00:38:38.000 They have a defective operator sequence. Mutations have occurred 00:38:38.000 --> 00:38:46.000 at the operator site. Mutant number two have a defective 00:38:46.000 --> 00:38:54.000 repressor protein, the gene for the repressor protein. 00:38:54.000 --> 00:39:00.000 How can I tell the difference? 00:39:00.000 --> 00:39:04.000 So, I could have a problem in my operator site. 00:39:04.000 --> 00:39:08.000 What would be the problem with the operator site? 00:39:08.000 --> 00:39:12.000 Some mutation to the sequence causes the repressor not to bind 00:39:12.000 --> 00:39:16.000 there anymore, OK? So, a defective operator site 00:39:16.000 --> 00:39:20.000 doesn't bind repressors. Defective repressor, the operator 00:39:20.000 --> 00:39:24.000 site is just fine, but I don't have a repressor to bind 00:39:24.000 --> 00:39:28.000 at it. So how do I tell the difference? One way to tell the 00:39:28.000 --> 00:39:32.000 difference is to begin crossing the mutants together to wild type, 00:39:32.000 --> 00:39:36.000 and asking, are they dominant or recessive, or things like that? 00:39:36.000 --> 00:39:39.000 Now, here's a little problem. E Coli is not a diploid, so you 00:39:39.000 --> 00:39:43.000 can't cross together two E colis and make a diploid E coli, 00:39:43.000 --> 00:39:46.000 right? It's a prokaryote. It only has one genome. But, 00:39:46.000 --> 00:39:50.000 it turns out that you can make temporary diploids, 00:39:50.000 --> 00:39:53.000 partial diploids out of E coli because it turns out you can mate 00:39:53.000 --> 00:39:57.000 bacteria. Bacteria, which have a bacterial chromosome 00:39:57.000 --> 00:40:01.000 here also engage in sex and in the course of bacterial sex, 00:40:01.000 --> 00:40:05.000 plasmids can be transferred called, for example, an F factor, is able to 00:40:05.000 --> 00:40:10.000 be transferred from another bacteria. And, through the wonders of partial 00:40:10.000 --> 00:40:15.000 merodiploid, you can temporarily get E colis, or you can permanently get 00:40:15.000 --> 00:40:20.000 E colis, that are partially diploid. So, you can do what I'm about to 00:40:20.000 --> 00:40:25.000 say. But, in case you were worried about my writing diploid genotypes 00:40:25.000 --> 00:40:30.000 for E coli, you can actually do this. 00:40:30.000 --> 00:40:36.000 You can make partial diploids. So, let's try out a genotype here. 00:40:36.000 --> 00:40:43.000 Suppose the repressor is a wild type, the operator is wild type, 00:40:43.000 --> 00:40:49.000 and the lack Z gene is wild type. And, suppose I have no IPTG, I'm 00:40:49.000 --> 00:40:56.000 un-induced. I have one unit of beta-gal. When I add my inducer, 00:40:56.000 --> 00:41:03.000 what happens? I get 1,000 units of beta-gal. 00:41:03.000 --> 00:41:07.000 Now, suppose I would have an operator constituative mutation. 00:41:07.000 --> 00:41:12.000 Then, the operator site is defective. It doesn't bind the 00:41:12.000 --> 00:41:17.000 repressor. Beta-gal is going to be expressed all the time, 00:41:17.000 --> 00:41:22.000 even in the absence. All right, well that was, of course, what we 00:41:22.000 --> 00:41:27.000 selected for. Now, suppose I made the following diploid. 00:41:27.000 --> 00:41:32.000 I plus, O plus, Z plus, over I plus, 00:41:32.000 --> 00:41:38.000 O constituative, Z plus. So, here's my diploid. What would 00:41:38.000 --> 00:41:44.000 be the phenotype? So, in other words, 00:41:44.000 --> 00:41:50.000 one of the chromosomes has an operator problem. 00:41:50.000 --> 00:41:56.000 Well, that means that this chromosome here is always going to 00:41:56.000 --> 00:42:02.000 be constituatively expressing beta-gal. 00:42:02.000 --> 00:42:06.000 But, what about this chromosome here? It won't. So, 00:42:06.000 --> 00:42:10.000 this would be about 1, 01, give or take, because it's got 00:42:10.000 --> 00:42:14.000 one chromosome doing that and one chromosome doing this, 00:42:14.000 --> 00:42:18.000 and this one would be about 2, 00. Now, that quantitative 00:42:18.000 --> 00:42:22.000 difference doesn't matter a lot. What you really saw when you did 00:42:22.000 --> 00:42:26.000 the molecular biology was that when you had one copy of the operator 00:42:26.000 --> 00:42:30.000 constituative mutation, you still got a lot of beta-gal here 00:42:30.000 --> 00:42:36.000 even in the absence of IPTG. So, that operator constituative site 00:42:36.000 --> 00:42:44.000 looked like it was dominant to this plus site here. 00:42:44.000 --> 00:42:52.000 But now, let's try this one here. I plus, O plus, Z plus, over I plus, 00:42:52.000 --> 00:43:00.000 operator constituative, Z minus. What happens then? 00:43:00.000 --> 00:43:05.000 This operator constituative site allows constant transcription of 00:43:05.000 --> 00:43:10.000 this particular copy. But, can this particular copy make 00:43:10.000 --> 00:43:15.000 a working, functional beta-gal? No. So, this looks, when you do 00:43:15.000 --> 00:43:20.000 your genetic crosses, you find that the operator 00:43:20.000 --> 00:43:25.000 constituative, now, if I reverse these here, 00:43:25.000 --> 00:43:30.000 suppose I reverse these, I plus, O plus, Z minus, I plus, O 00:43:30.000 --> 00:43:35.000 constituative, Z plus, same genotypes, 00:43:35.000 --> 00:43:40.000 right, except that I flipped which chromosome these are on. 00:43:40.000 --> 00:43:46.000 Now, what happens? This chromosome here: always making beta-gal and it 00:43:46.000 --> 00:43:51.000 works. This chromosome here: not making beta-gal. 00:43:51.000 --> 00:43:56.000 Even though it's regulated, it's a mutant. So, in other words, 00:43:56.000 --> 00:44:01.000 from this very experiment, you can tell that the operator site is only 00:44:01.000 --> 00:44:07.000 affecting the chromosome that it's physically on, 00:44:07.000 --> 00:44:13.000 that it doesn't make a protein that floats around. 00:44:13.000 --> 00:44:19.000 What it does is it's said to work in cys. In cys means on the same 00:44:19.000 --> 00:44:26.000 chromosome. It physically works on the same chromosome. 00:44:26.000 --> 00:44:32.000 Now, let's take a look, by contrast, of the properties of 00:44:32.000 --> 00:44:38.000 the lack repressor mutants. If I give you a lack repressor 00:44:38.000 --> 00:44:43.000 mutant, I plus, O plus, Z plus is the wild type. 00:44:43.000 --> 00:44:49.000 I constituative, O plus, Z plus: what happens here? 00:44:49.000 --> 00:44:54.000 This wild type is one in 1, 00. This guy here: 1,000 and 1, 00:44:54.000 --> 00:45:00.000 00, and then here let's look at a diploid: 00:45:00.000 --> 00:45:05.000 I plus, O plus, Z plus, I constituative, 00:45:05.000 --> 00:45:10.000 O plus, Z plus. What's the effect? The I constituative doesn't make a 00:45:10.000 --> 00:45:15.000 functioning repressor. But, I plus makes a functioning 00:45:15.000 --> 00:45:21.000 repressor. So, will this show regulation? 00:45:21.000 --> 00:45:26.000 Yeah, this will be regulated just fine. This works out just fine, 00:45:26.000 --> 00:45:32.000 and in fact it'll make 2,000, and it'll make two copies there. 00:45:32.000 --> 00:45:37.000 But again, the units don't matter too much. And, 00:45:37.000 --> 00:45:42.000 by contrast, if I give you I plus, O plus, Z minus, and I constituative, 00:45:42.000 --> 00:45:47.000 O plus, Z plus, what will happen? 00:45:47.000 --> 00:45:53.000 Here, I have my mutation on this chromosome. But, 00:45:53.000 --> 00:45:58.000 it doesn't matter because I've got my mutation on this chromosome in 00:45:58.000 --> 00:46:03.000 the repressor. I've got a mutation on lack Z here, 00:46:03.000 --> 00:46:09.000 but as long as I have a functional copy, one functional copy of the 00:46:09.000 --> 00:46:15.000 lack repressor, it works on both chromosomes. 00:46:15.000 --> 00:46:20.000 It will work on both chromosomes, and so in other words this lack 00:46:20.000 --> 00:46:26.000 repressor, one copy works on both chromosomes. In other words, 00:46:26.000 --> 00:46:32.000 it makes a product that diffuses around, and can work on either 00:46:32.000 --> 00:46:38.000 chromosome, and it's said to work in trans, that is, across. 00:46:38.000 --> 00:46:41.000 So, the operator is working in cys. It's operating on its own 00:46:41.000 --> 00:46:45.000 chromosome only. A mutation in the operator only 00:46:45.000 --> 00:46:48.000 affects the chromosome it lives on, whereas a functional copy of the 00:46:48.000 --> 00:46:52.000 lack repressor will float around because it's a protein, 00:46:52.000 --> 00:46:55.000 and that's how Jacobin Maneaux knew the difference. 00:46:55.000 --> 00:46:59.000 They proved their model by showing that these two kinds of mutations 00:46:59.000 --> 00:47:03.000 had very different properties. Operator mutations affected only the 00:47:03.000 --> 00:47:07.000 physical chromosome on which they occurred, which of course they had 00:47:07.000 --> 00:47:11.000 to infer from the genetics they did, whereas repressor, a functional copy 00:47:11.000 --> 00:47:15.000 repressor, could act on any chromosome in the cell. 00:47:15.000 --> 00:47:20.000 So, OK, we've got that. Now, last point, what about glucose? 00:47:20.000 --> 00:47:24.000 I haven't said a word about glucose. See, this was a big deal to people. 00:47:24.000 --> 00:47:28.000 This model, the repressor model, we have this repressor. What 00:47:28.000 --> 00:47:36.000 about glucose? What's glucose doing in this picture? 00:47:36.000 --> 00:47:47.000 So, glucose control: so here's my gene. Here's my promoter, 00:47:47.000 --> 00:47:58.000 P lack. Here's my operator, beta-gal. 00:47:58.000 --> 00:48:03.000 It's encoded by lack Z. You've got all that. When this guy 00:48:03.000 --> 00:48:08.000 is present, sorry, when lactose is present, 00:48:08.000 --> 00:48:13.000 the repressor comes off. Polymerase sits down. Wait a second, 00:48:13.000 --> 00:48:18.000 polymerase isn't supposed to sit down unless there's no glucose. 00:48:18.000 --> 00:48:23.000 We need another sensor to tell if there's glucose, 00:48:23.000 --> 00:48:28.000 or if there's low glucose. So, we're going to need us a sensor 00:48:28.000 --> 00:48:34.000 that tells that. Any ideas? Yep? 00:48:34.000 --> 00:48:40.000 Yeah, if you work that one through, I don't think it quite works. But, 00:48:40.000 --> 00:48:46.000 you've got the basic idea. You're going to want another 00:48:46.000 --> 00:48:52.000 something, and it turns out there's another site over here, 00:48:52.000 --> 00:48:58.000 OK? There's a second site on which a completely different 00:48:58.000 --> 00:49:05.000 protein binds. And, this protein is the cyclic AMP 00:49:05.000 --> 00:49:13.000 regulatory protein, and it so happens that in the cell, 00:49:13.000 --> 00:49:20.000 when there's low amounts of glucose, let me make sure I've got this right, 00:49:20.000 --> 00:49:28.000 when there's low amounts of glucose, what we have is high amounts of 00:49:28.000 --> 00:49:34.000 cyclic AMP. Cyclic AMP turns out, 00:49:34.000 --> 00:49:38.000 whereas lactose is used directly as the signal, cyclic AMP is used as 00:49:38.000 --> 00:49:42.000 the signal here. When the cell has low amounts of 00:49:42.000 --> 00:49:46.000 glucose, it has high amounts of cyclic AMP. Now, 00:49:46.000 --> 00:49:50.000 what do you want your cyclic AMP to do? How are we going to design this? 00:49:50.000 --> 00:49:54.000 It's going to bind to a protein, cyclic AMP regulatory protein, it's 00:49:54.000 --> 00:49:58.000 going to sit down, and now what's it going to do? 00:49:58.000 --> 00:50:02.000 Is it going to block RNA polymerase? 00:50:02.000 --> 00:50:06.000 What do we want to do? If there's low glucose, 00:50:06.000 --> 00:50:10.000 high cyclic AMP, we sit down at the site, we want to turn on 00:50:10.000 --> 00:50:15.000 transcription now, right? So, what it's got to do is 00:50:15.000 --> 00:50:19.000 not block RNA polymerase, but help RNA polymerase. So, 00:50:19.000 --> 00:50:24.000 what it actually does is instead of being a repressor, 00:50:24.000 --> 00:50:28.000 it's an activator. And what it does is it makes it more attractive for 00:50:28.000 --> 00:50:32.000 RNA polymerase to bind, and it actually does that by, 00:50:32.000 --> 00:50:36.000 actually it does it slightly by bending the DNA. 00:50:36.000 --> 00:50:40.000 But, what it does is it makes it easier for RNA polymerase to bind. 00:50:40.000 --> 00:50:44.000 It turns out that the promoter is kind of a crummy promoter. 00:50:44.000 --> 00:50:48.000 It's actually just like, remember the repressor wasn't perfect; the 00:50:48.000 --> 00:50:52.000 promoter's not perfect either. The promoter's kind of crummy. 00:50:52.000 --> 00:50:56.000 And, unless RNA polymerase gets a little help from this other 00:50:56.000 --> 00:51:00.000 regulatory protein, it doesn't work. 00:51:00.000 --> 00:51:04.000 We have two controls: a negative regulator responding to an 00:51:04.000 --> 00:51:09.000 environmental cue, a positive activator responding to 00:51:09.000 --> 00:51:13.000 an environmental cue, helping polymerase decide whether to 00:51:13.000 --> 00:51:18.000 transcribe or not, and basically that's how a human egg 00:51:18.000 --> 00:51:22.000 goes to a complete adult and lives its entire life, 00:51:22.000 --> 00:51:27.000 minus a few other details. There are some details left out, 00:51:27.000 --> 00:51:32.000 but that's a sketch of how you turn genes on and off.