WEBVTT 00:00:06.594 --> 00:00:07.550 ERIC LANDER: Good morning. 00:00:07.550 --> 00:00:08.800 Good morning. 00:00:11.870 --> 00:00:16.120 So we've been talking about recombinant DNA. 00:00:18.910 --> 00:00:22.520 And really what it does to our picture here-- 00:00:22.520 --> 00:00:25.080 function, gene, protein-- 00:00:25.080 --> 00:00:28.790 is for the first time take something that's a theoretical 00:00:28.790 --> 00:00:32.130 relationship and make it operational. 00:00:32.130 --> 00:00:42.160 Being able to go from a function like the ability to 00:00:42.160 --> 00:00:46.550 make your own arginine, to a specific gene, to a specific 00:00:46.550 --> 00:00:50.250 protein, and to be able to connect those up. 00:00:50.250 --> 00:00:53.340 In principle, by the time we're done with recombinant 00:00:53.340 --> 00:00:56.310 DNA, one should be able to go from any vertex of that 00:00:56.310 --> 00:00:59.190 triangle to any other vertex of that triangle. 00:00:59.190 --> 00:01:01.680 Given a function, find the genes. 00:01:01.680 --> 00:01:03.290 Given a gene, find the proteins. 00:01:03.290 --> 00:01:04.890 Given a protein, find the genes. 00:01:04.890 --> 00:01:07.700 Given a protein, find the function. 00:01:07.700 --> 00:01:11.630 That's really the goal of recombinant DNA is to be able 00:01:11.630 --> 00:01:14.750 to start at any vertex and reach any other 00:01:14.750 --> 00:01:16.670 vertex of that triangle. 00:01:16.670 --> 00:01:17.910 We're not there yet. 00:01:17.910 --> 00:01:20.590 But we will be in the next couple of days, to the point 00:01:20.590 --> 00:01:24.750 where we can move freely about this whole picture. 00:01:24.750 --> 00:01:29.450 So we've talked about DNA sequencing. 00:01:29.450 --> 00:01:31.840 And I want to pick up a little bit with DNA sequencing. 00:01:31.840 --> 00:01:35.570 And I'll probably end with DNA sequencing again, as I tell 00:01:35.570 --> 00:01:37.455 you where things stand today. 00:01:40.510 --> 00:01:43.860 How did we use DNA sequencing? 00:01:43.860 --> 00:01:45.780 Well, we found us a clone. 00:01:45.780 --> 00:01:49.620 Maybe our clone was a clone that conferred the ability to 00:01:49.620 --> 00:01:50.810 grow without arginine. 00:01:50.810 --> 00:01:53.420 That was cloning by complementation. 00:01:53.420 --> 00:01:57.160 Maybe it was a clone that encoded beta globin. 00:01:57.160 --> 00:02:01.200 There we found an antibody that recognized beta globin. 00:02:01.200 --> 00:02:05.170 We made a cDNA library with an appropriate promoter. 00:02:05.170 --> 00:02:08.440 And we asked E. coli to produce those human proteins 00:02:08.440 --> 00:02:10.259 from those cDNAs. 00:02:10.259 --> 00:02:13.560 And then we use our antibody to recognize which clone. 00:02:13.560 --> 00:02:16.430 One way or the other, we found ourselves a clone. 00:02:19.860 --> 00:02:21.870 The clone had this vector. 00:02:21.870 --> 00:02:23.520 It had this insert. 00:02:23.520 --> 00:02:25.750 The insert is now of interest to us. 00:02:25.750 --> 00:02:27.410 We wish to sequence it. 00:02:27.410 --> 00:02:32.460 And we talked before about taking that piece of DNA and 00:02:32.460 --> 00:02:33.710 subjecting it to sequencing. 00:02:36.820 --> 00:02:40.140 We started with a primer. 00:02:40.140 --> 00:02:41.765 From that primer, we extended. 00:02:45.200 --> 00:02:52.550 And we hit a point, let's say, opposite an A or maybe 00:02:52.550 --> 00:03:02.950 opposite the next A or opposite the A after that or 00:03:02.950 --> 00:03:05.300 opposite the A after that. 00:03:05.300 --> 00:03:10.450 And we had this clever trick, for which Fred Sanger actually 00:03:10.450 --> 00:03:15.830 won a Nobel Prize, of using a defective version of the 00:03:15.830 --> 00:03:20.930 nucleotide T that would stop at that point. 00:03:20.930 --> 00:03:24.980 But remember, we didn't use only defective T. We used a 00:03:24.980 --> 00:03:30.820 mixture of good T and defective T. Let's say 00:03:30.820 --> 00:03:33.370 defective T was 1% of the whole mixture, whenever we 00:03:33.370 --> 00:03:36.420 encountered a defective T and put it in, the chain would 00:03:36.420 --> 00:03:38.510 stop because it couldn't be extended. 00:03:38.510 --> 00:03:41.160 Whenever we put in a good T, it would keep going. 00:03:41.160 --> 00:03:42.840 And so since we're making-- 00:03:42.840 --> 00:03:46.050 Of course, we have millions and millions of copies of our 00:03:46.050 --> 00:03:48.000 template sitting there in the test tube. 00:03:48.000 --> 00:03:50.500 We're always working-- when I talk about "a" molecule, and I 00:03:50.500 --> 00:03:53.110 draw a picture of a molecule, we should always know that 00:03:53.110 --> 00:03:55.210 there's millions of copies of those things. 00:03:55.210 --> 00:03:56.370 Some of them are stopping here. 00:03:56.370 --> 00:03:57.410 Some of them are going here, et cetera, 00:03:57.410 --> 00:03:58.900 et cetera, et cetera. 00:03:58.900 --> 00:04:02.400 And we end up with a large collection. 00:04:02.400 --> 00:04:06.610 And if we separate it on a gel, we can detect the lengths 00:04:06.610 --> 00:04:07.860 of those fragments. 00:04:13.250 --> 00:04:17.360 If we attach a fluorescent dye, then those fragments are 00:04:17.360 --> 00:04:18.959 fluorescently labeled. 00:04:18.959 --> 00:04:24.660 We could all run them in the same lane 00:04:24.660 --> 00:04:25.910 with different colors. 00:04:28.530 --> 00:04:32.060 And we could put our little fluorescence detector and see 00:04:32.060 --> 00:04:32.990 what goes by. 00:04:32.990 --> 00:04:36.340 And the traces you would get, the actual pictures that 00:04:36.340 --> 00:04:41.356 emerge from this, look something like this. 00:04:55.920 --> 00:04:59.300 And you'd see colored traces like that emerging from that 00:04:59.300 --> 00:05:00.840 electrophoretic detector. 00:05:00.840 --> 00:05:03.770 And you could read off the sequence by the colors-- 00:05:03.770 --> 00:05:07.190 really very gorgeous, very simple, beautiful technology, 00:05:07.190 --> 00:05:09.890 all this taking place in a little capillary tube. 00:05:13.030 --> 00:05:15.840 You remember how we made a defective T, right? 00:05:15.840 --> 00:05:19.630 How did we make a defective T? 00:05:19.630 --> 00:05:20.270 Sorry? 00:05:20.270 --> 00:05:21.840 STUDENT: Dideoxy. 00:05:21.840 --> 00:05:22.930 ERIC LANDER: To dideoxy. 00:05:22.930 --> 00:05:25.520 Because remember, we need that 3-prime hydroxyl in 00:05:25.520 --> 00:05:26.870 order to extend it. 00:05:26.870 --> 00:05:29.590 No 3-prime hydroxyl, no extension. 00:05:29.590 --> 00:05:32.150 So if you make that deoxy at the 3-prime 00:05:32.150 --> 00:05:34.220 position, you can extend. 00:05:34.220 --> 00:05:36.780 And since it was originally 2-prime deoxy, it's now 00:05:36.780 --> 00:05:38.740 2-prime, 3-prime dideoxy. 00:05:38.740 --> 00:05:41.440 That's all it takes in order to block 00:05:41.440 --> 00:05:43.360 the extension reaction. 00:05:43.360 --> 00:05:46.380 And they sell the stuff, and you can use it. 00:05:46.380 --> 00:05:47.215 All right. 00:05:47.215 --> 00:05:49.712 I had another question for you guys. 00:05:49.712 --> 00:05:51.460 Where did the primer come from? 00:05:55.550 --> 00:05:57.520 Sorry? 00:05:57.520 --> 00:05:57.930 Sorry? 00:05:57.930 --> 00:05:58.340 STUDENT: We put it in. 00:05:58.340 --> 00:05:58.970 ERIC LANDER: We put it in. 00:05:58.970 --> 00:06:01.605 How did we know what to put in? 00:06:01.605 --> 00:06:03.000 STUDENT: [INAUDIBLE] catalog. 00:06:03.000 --> 00:06:04.950 ERIC LANDER: Well, the catalog's very smart, but it 00:06:04.950 --> 00:06:06.440 doesn't tell us what we need. 00:06:06.440 --> 00:06:08.352 How do we know what sequence it is? 00:06:12.510 --> 00:06:15.920 Actually, it turns out that so many different sequences might 00:06:15.920 --> 00:06:18.910 be needed for different purposes in molecular biology 00:06:18.910 --> 00:06:22.160 that they don't stock them all in the catalog because you 00:06:22.160 --> 00:06:23.950 might order any sequence. 00:06:23.950 --> 00:06:26.610 So it really turns out that if you want to order a specific 00:06:26.610 --> 00:06:31.320 20-letter sequence, you go on the web, type it in, and then 00:06:31.320 --> 00:06:33.080 the machine will make it for you, and you get it the next 00:06:33.080 --> 00:06:34.980 day, it turns out. 00:06:34.980 --> 00:06:36.790 But they don't actually put it in the catalog because it 00:06:36.790 --> 00:06:38.740 would be too big an inventory. 00:06:38.740 --> 00:06:41.440 Although ones that people use a lot they keep in the 00:06:41.440 --> 00:06:44.604 catalog, otherwise they just make it on the spot for you. 00:06:44.604 --> 00:06:46.030 But how do we know what sequence 00:06:46.030 --> 00:06:46.870 we're supposed to use? 00:06:46.870 --> 00:06:50.990 Here's my clone, let's say arginine, the ARG1 gene. 00:06:50.990 --> 00:06:53.200 How did I know what sequence to start with? 00:06:56.672 --> 00:06:59.120 You let me get away with just put a primer there. 00:06:59.120 --> 00:07:00.370 And what does it match? 00:07:07.216 --> 00:07:08.683 Yeah? 00:07:08.683 --> 00:07:12.110 STUDENT: Could you use the EcoR1 [INAUDIBLE]? 00:07:12.110 --> 00:07:13.360 ERIC LANDER: I did use EcoR1. 00:07:16.746 --> 00:07:18.730 STUDENT: [INAUDIBLE] 00:07:18.730 --> 00:07:23.778 ERIC LANDER: EcoR1 site here, GAATTC-- 00:07:23.778 --> 00:07:25.028 GAATTC-- 00:07:27.090 --> 00:07:31.090 I'm going to cut in this site. 00:07:31.090 --> 00:07:34.130 I'm sorry, I'm going to cut in this site 00:07:34.130 --> 00:07:35.715 like that, let's say. 00:07:35.715 --> 00:07:37.430 Yeah, like that. 00:07:37.430 --> 00:07:43.210 And this fragment here-- 00:07:43.210 --> 00:07:44.590 sorry, like that-- 00:07:44.590 --> 00:07:50.840 the fragment here that I'm going to start sequencing from 00:07:50.840 --> 00:07:53.470 it starts with a G, right? 00:07:53.470 --> 00:07:57.100 Because it's opposite that C. 00:07:57.100 --> 00:08:00.240 So because I cut with EcoR1, I'm pretty sure it starts with 00:08:00.240 --> 00:08:05.970 a G. It's not a very big primer to use, though. 00:08:05.970 --> 00:08:08.080 I could start with a C, but I don't think that's going to 00:08:08.080 --> 00:08:09.800 have enough binding energy to do it. 00:08:18.249 --> 00:08:23.230 STUDENT: Doesn't a bacteria already replicate that DNA? 00:08:23.230 --> 00:08:24.260 ERIC LANDER: It replicates that DNA just fine. 00:08:24.260 --> 00:08:26.232 STUDENT: So there's already a primer in there. 00:08:26.232 --> 00:08:27.220 Why do you [INAUDIBLE]? 00:08:27.220 --> 00:08:28.100 ERIC LANDER: Well, because I've now 00:08:28.100 --> 00:08:29.836 purified out my insert. 00:08:29.836 --> 00:08:31.410 And I'm going to subject it to sequencing. 00:08:31.410 --> 00:08:33.630 And I need to start with a primer. 00:08:33.630 --> 00:08:34.630 I've got that fragment. 00:08:34.630 --> 00:08:37.710 I need to know how that fragment starts. 00:08:37.710 --> 00:08:41.366 And I don't know how that fragment starts. 00:08:41.366 --> 00:08:43.843 STUDENT: Is there a place you could cut in a little bit 00:08:43.843 --> 00:08:44.159 after that? 00:08:44.159 --> 00:08:45.610 ERIC LANDER: Oh! 00:08:45.610 --> 00:08:51.640 What if I was really smart and put in a different restriction 00:08:51.640 --> 00:08:54.520 site back here? 00:08:54.520 --> 00:08:59.070 And I use that restriction enzyme, and I cut there? 00:08:59.070 --> 00:09:01.330 Then what would you be able to tell me? 00:09:01.330 --> 00:09:03.380 Well, then the fragment would start with a 00:09:03.380 --> 00:09:05.900 known vector sequence. 00:09:05.900 --> 00:09:07.250 Bingo. 00:09:07.250 --> 00:09:08.290 That'll work. 00:09:08.290 --> 00:09:08.660 Good. 00:09:08.660 --> 00:09:10.360 Good engineering. 00:09:10.360 --> 00:09:12.800 Since I don't know what the sequence is of the thing I'm 00:09:12.800 --> 00:09:17.180 reading, I'd better back up a little bit and use a known 00:09:17.180 --> 00:09:18.640 sequence from the vector. 00:09:18.640 --> 00:09:20.600 And then I keep going. 00:09:20.600 --> 00:09:22.850 This is all just to give you a sense of all the 00:09:22.850 --> 00:09:24.430 tricks you can do. 00:09:24.430 --> 00:09:25.530 So now it's easy. 00:09:25.530 --> 00:09:28.700 Now, in fact if that's the vector I use a lot, all the 00:09:28.700 --> 00:09:30.540 time, then bingo! 00:09:30.540 --> 00:09:31.740 I can go to the catalog because they 00:09:31.740 --> 00:09:33.330 will stock that one. 00:09:33.330 --> 00:09:34.400 And I'll use it. 00:09:34.400 --> 00:09:39.210 And I can use my green primer there to get going. 00:09:39.210 --> 00:09:39.970 All right. 00:09:39.970 --> 00:09:44.130 Now here's the problem. 00:09:44.130 --> 00:09:49.380 As I start sequencing, coming down this capillary tube are 00:09:49.380 --> 00:09:52.970 fragments of different lengths. 00:09:52.970 --> 00:09:58.860 The speed of migration depends on the logarithm of the length 00:09:58.860 --> 00:10:00.110 of the fragment. 00:10:02.250 --> 00:10:03.940 Big fragments goes slower. 00:10:03.940 --> 00:10:07.110 It's inversely proportional to the log of the 00:10:07.110 --> 00:10:08.140 length of the fragment. 00:10:08.140 --> 00:10:10.900 So big fragments go slower. 00:10:10.900 --> 00:10:12.590 And as they get bigger and bigger and bigger, they go 00:10:12.590 --> 00:10:13.720 slower and slower and slower. 00:10:13.720 --> 00:10:20.190 But the difference between log of 1,000 and log of 1,001 is 00:10:20.190 --> 00:10:22.220 pretty small. 00:10:22.220 --> 00:10:25.890 And then log of 1,001 and 1,002, very small. 00:10:25.890 --> 00:10:29.430 Actually, those peaks over there start bunching up, and I 00:10:29.430 --> 00:10:31.760 can't tell them apart. 00:10:31.760 --> 00:10:35.270 So I can actually only go with this electrophoretic process 00:10:35.270 --> 00:10:39.170 maybe 1,000 letters before the peaks get too bunched up 00:10:39.170 --> 00:10:42.630 because the different speeds are not so different anymore. 00:10:42.630 --> 00:10:51.940 So I can only read 1,000 bases, let's say. 00:10:51.940 --> 00:10:55.420 In practice, we would tend to read 700, 800 bases because it 00:10:55.420 --> 00:10:56.520 started getting scruffy. 00:10:56.520 --> 00:10:59.190 But let's make it round, and we'll say 1,000 bases. 00:10:59.190 --> 00:11:02.850 Now, suppose this fragment that I got that's the ARG1 00:11:02.850 --> 00:11:06.970 gene is 3,000 bases. 00:11:06.970 --> 00:11:09.830 Well, we've got our clever trick that you've introduced 00:11:09.830 --> 00:11:15.920 here of cutting back over here at some previous site, using 00:11:15.920 --> 00:11:18.090 our primer here and reading. 00:11:21.760 --> 00:11:25.290 But it kind of dies at about 1,000 bases. 00:11:25.290 --> 00:11:26.540 I can't read any further. 00:11:29.460 --> 00:11:30.710 What do I do? 00:11:33.260 --> 00:11:34.510 STUDENT: [INAUDIBLE] 00:11:47.470 --> 00:11:48.750 ERIC LANDER: What if there's not a perfect 00:11:48.750 --> 00:11:52.260 restriction site there? 00:11:52.260 --> 00:11:53.770 But you're on the right track. 00:11:53.770 --> 00:11:55.676 Keep going. 00:11:55.676 --> 00:12:01.190 Once I've sequenced the first 1,000 bases, what do I know? 00:12:01.190 --> 00:12:04.870 The sequence of the first 1,000 bases. 00:12:04.870 --> 00:12:07.364 What primer could I use then? 00:12:07.364 --> 00:12:08.360 STUDENT: [INAUDIBLE]. 00:12:08.360 --> 00:12:10.410 ERIC LANDER: I can just make a new primer based on those 00:12:10.410 --> 00:12:11.830 bases, right? 00:12:11.830 --> 00:12:13.730 So I don't even need my restriction site anymore. 00:12:13.730 --> 00:12:14.680 You've got it exactly right. 00:12:14.680 --> 00:12:15.920 I use my knowledge. 00:12:15.920 --> 00:12:18.910 And then I could use a new primer, and I 00:12:18.910 --> 00:12:23.130 could go more bases. 00:12:23.130 --> 00:12:31.360 Then I could use a new primer and go more bases. 00:12:31.360 --> 00:12:36.550 Then a new primer, and go more bases. 00:12:36.550 --> 00:12:38.060 And I can do what's called "primer 00:12:38.060 --> 00:12:41.400 walking" along the clone. 00:12:41.400 --> 00:12:43.170 Will that work? 00:12:43.170 --> 00:12:43.940 You bet. 00:12:43.940 --> 00:12:45.190 That works just fine. 00:12:47.820 --> 00:12:51.100 It's also very slow. 00:12:51.100 --> 00:12:56.050 Because I had to get my first bases, analyze them, order a 00:12:56.050 --> 00:12:58.760 new primer, and the next day set up my next reaction. 00:12:58.760 --> 00:13:01.130 Take a couple days, get my next reaction. 00:13:01.130 --> 00:13:03.110 Take a couple days, next reaction. 00:13:03.110 --> 00:13:06.550 Imagine sequencing the human genome like this. 00:13:06.550 --> 00:13:11.720 This could take a long time if I do it in serial. 00:13:11.720 --> 00:13:13.150 So what else could I do? 00:13:13.150 --> 00:13:13.930 This works, by the way. 00:13:13.930 --> 00:13:15.000 This totally works. 00:13:15.000 --> 00:13:16.110 It's a good procedure, and it's 00:13:16.110 --> 00:13:17.470 used for certain purposes. 00:13:17.470 --> 00:13:18.720 But what else could I do? 00:13:24.790 --> 00:13:26.320 Here's the cool thing. 00:13:26.320 --> 00:13:28.220 We've got biology. 00:13:28.220 --> 00:13:30.490 But you guys, being MIT students, you've also got 00:13:30.490 --> 00:13:33.260 computer science and other tricks available. 00:13:33.260 --> 00:13:34.510 Here's a cool trick. 00:13:37.160 --> 00:13:39.820 I have my clone, 3,000 bases. 00:13:39.820 --> 00:13:41.690 I like my clone. 00:13:41.690 --> 00:13:47.030 I'm going to take my clone, my fragment, of 3,000 bases, and 00:13:47.030 --> 00:13:51.180 maybe instead of sequencing it, I'm going to shred it up 00:13:51.180 --> 00:13:54.060 into a lot of smaller pieces. 00:13:54.060 --> 00:13:59.180 Suppose I shred this up into fragments of, 00:13:59.180 --> 00:14:01.600 say, size 800 bases. 00:14:01.600 --> 00:14:03.300 This was 3,000 bases. 00:14:03.300 --> 00:14:04.420 Now let me shred it up. 00:14:04.420 --> 00:14:06.750 I'll just take 800 as a number. 00:14:06.750 --> 00:14:09.740 Now remember, I had a lot of copies of this clone, right? 00:14:09.740 --> 00:14:12.795 So I'm going to get shreds like this and shreds like that 00:14:12.795 --> 00:14:14.060 and a shred like that. 00:14:14.060 --> 00:14:15.130 It's not just one copy. 00:14:15.130 --> 00:14:18.130 I've got a lot of copies of this piece of DNA there. 00:14:18.130 --> 00:14:19.300 I'm going to shred it up. 00:14:19.300 --> 00:14:21.600 And there are ways to shred it up by forcing it through a 00:14:21.600 --> 00:14:25.210 needle or treating it meanly, or things like that. 00:14:25.210 --> 00:14:27.550 I'm going to get lots of little fragments. 00:14:27.550 --> 00:14:33.540 And what I could do is I could clone all of those little 00:14:33.540 --> 00:14:35.990 subfragments. 00:14:35.990 --> 00:14:39.040 I take my big fragment, and what I'm going to do is I'm 00:14:39.040 --> 00:14:46.400 going to make a new library of subfragments. 00:14:46.400 --> 00:14:48.230 Got it? 00:14:48.230 --> 00:14:51.340 Now I have a whole lot of subfragments, each taken from 00:14:51.340 --> 00:14:52.580 my 3,000 bases. 00:14:52.580 --> 00:14:53.830 And they're all kind of smallish. 00:14:56.910 --> 00:14:58.720 What could I do to all of those little subfragments? 00:15:01.910 --> 00:15:04.520 They're all living in a vector. 00:15:04.520 --> 00:15:07.060 Each is in its own vector. 00:15:07.060 --> 00:15:07.570 I've spread them out. 00:15:07.570 --> 00:15:08.630 I've made a library. 00:15:08.630 --> 00:15:10.080 They're each in their own bacteria. 00:15:10.080 --> 00:15:11.370 They're each in a vector. 00:15:11.370 --> 00:15:13.240 That vector has a known sequence at its 00:15:13.240 --> 00:15:16.530 end, the green primer. 00:15:16.530 --> 00:15:22.430 Couldn't I just sequence a lot of different random subclones 00:15:22.430 --> 00:15:24.155 and paste them together? 00:15:24.155 --> 00:15:27.440 See, that's where it pays to have computer science as well. 00:15:27.440 --> 00:15:34.380 Because what I could do is by subcloning these into 00:15:34.380 --> 00:15:36.380 individual little random pieces-- 00:15:36.380 --> 00:15:38.210 I have no idea how they've been broken up. 00:15:38.210 --> 00:15:38.610 I don't care-- 00:15:38.610 --> 00:15:41.730 I just take the total DNA, shred it up into pieces, sub 00:15:41.730 --> 00:15:44.460 clone it into a vector. 00:15:44.460 --> 00:15:47.610 And now because it's in the vector, I could read this one 00:15:47.610 --> 00:15:49.760 and that one and this one and that one and this 00:15:49.760 --> 00:15:50.510 one and that one. 00:15:50.510 --> 00:15:53.980 Do I actually know which ones I'm reading? 00:15:53.980 --> 00:15:54.330 No. 00:15:54.330 --> 00:15:57.130 It's totally random. 00:15:57.130 --> 00:16:00.500 I take my 3,000 bases, shred it up into lots of smaller 00:16:00.500 --> 00:16:03.800 pieces, and I just read a lot of them. 00:16:03.800 --> 00:16:06.090 When I get a whole lot of these pieces, maybe 800 00:16:06.090 --> 00:16:09.410 letters each, what do I do? 00:16:09.410 --> 00:16:13.330 I write me a piece of code that looks for overlaps 00:16:13.330 --> 00:16:16.020 between them and start pasting it together. 00:16:18.540 --> 00:16:20.180 And that's called assembly. 00:16:20.180 --> 00:16:23.250 You assemble the sequence out of its little pieces. 00:16:23.250 --> 00:16:26.510 And so you can assemble things. 00:16:26.510 --> 00:16:31.301 And this gets referred to as shotgun sequencing. 00:16:31.301 --> 00:16:33.940 That's what it's really called, because it's like you 00:16:33.940 --> 00:16:35.630 shoot it out of the end of the shotgun or something. 00:16:35.630 --> 00:16:37.160 It's broken up into a lot of pieces. 00:16:37.160 --> 00:16:41.310 It's just a shotgun, random approach where I take 00:16:41.310 --> 00:16:43.920 individual random clones, and I assemble them. 00:16:43.920 --> 00:16:44.660 Any questions about that? 00:16:44.660 --> 00:16:46.440 It's really a way to do it. 00:16:46.440 --> 00:16:49.650 And the big difference there is you can do it in parallel. 00:16:49.650 --> 00:16:52.820 Rather than doing it one step at a time, which sounds so 00:16:52.820 --> 00:16:54.990 logical but takes so much time-- 00:16:54.990 --> 00:16:55.960 easier. 00:16:55.960 --> 00:17:01.220 Just shred it up, read lots of them all the same afternoon, 00:17:01.220 --> 00:17:03.810 and then assemble them by computer. 00:17:03.810 --> 00:17:06.099 So that's nice. 00:17:06.099 --> 00:17:06.849 So I do that. 00:17:06.849 --> 00:17:08.150 I get my clone. 00:17:08.150 --> 00:17:10.579 I'm going to now do my computer assembly of it. 00:17:10.579 --> 00:17:14.780 And I'm going to get my 3,000 bases. 00:17:14.780 --> 00:17:20.820 How do I analyze my clone, my clone sequence? 00:17:24.319 --> 00:17:29.818 Now I have 3,000 letters in order, nicely done. 00:17:29.818 --> 00:17:31.230 What do I do with it? 00:17:36.460 --> 00:17:39.680 That clone, let's say, is able to confer the ability to grow 00:17:39.680 --> 00:17:41.270 without arginine. 00:17:41.270 --> 00:17:45.120 It encodes some enzyme that lets you make arginine. 00:17:45.120 --> 00:17:46.260 I've got 3,000 letters. 00:17:46.260 --> 00:17:48.680 How do I tell what it's doing? 00:17:48.680 --> 00:17:50.040 What do I look for? 00:17:50.040 --> 00:17:50.757 Yep? 00:17:50.757 --> 00:17:52.705 STUDENT: Compare it with something that doesn't have 00:17:52.705 --> 00:17:54.660 [INAUDIBLE]? 00:17:54.660 --> 00:17:56.700 ERIC LANDER: Well, so tell me what I'm looking for? 00:17:56.700 --> 00:17:59.172 I'm looking for a gene? 00:17:59.172 --> 00:18:02.136 STUDENT: Yes, [INAUDIBLE]. 00:18:02.136 --> 00:18:02.630 ERIC LANDER: Yeah. 00:18:02.630 --> 00:18:05.320 So what about that gene? 00:18:05.320 --> 00:18:06.860 What's distinctive about genes? 00:18:06.860 --> 00:18:09.391 How do I recognize a gene? 00:18:09.391 --> 00:18:10.792 It's tricky. 00:18:10.792 --> 00:18:13.127 STUDENT: The sequence? 00:18:13.127 --> 00:18:13.594 ERIC LANDER: How can I just 00:18:13.594 --> 00:18:14.630 recognize it from the sequence? 00:18:14.630 --> 00:18:16.938 Can I tell that something is a gene? 00:18:16.938 --> 00:18:18.460 STUDENT: Start codon. 00:18:18.460 --> 00:18:20.660 ERIC LANDER: I could look for a start codon, ATG. 00:18:20.660 --> 00:18:24.970 Do you think that'll happen just by chance, though? 00:18:24.970 --> 00:18:28.390 There'll be a lot ATGs running around, because you've got two 00:18:28.390 --> 00:18:30.120 strands, three reading frames. 00:18:30.120 --> 00:18:32.390 It'll happen pretty often. 00:18:32.390 --> 00:18:33.570 But that's a start. 00:18:33.570 --> 00:18:35.362 What happens after the start codon. 00:18:35.362 --> 00:18:36.580 STUDENT: There's a stop codon. 00:18:36.580 --> 00:18:38.450 ERIC LANDER: There's a stop codon, at some point. 00:18:38.450 --> 00:18:39.660 And what's in between the start codon 00:18:39.660 --> 00:18:41.768 and the stop codon? 00:18:41.768 --> 00:18:44.000 STUDENT: [INAUDIBLE]. 00:18:44.000 --> 00:18:47.310 ERIC LANDER: Well, no stop codons. 00:18:47.310 --> 00:18:52.220 A gene should look like ATG and a whole lot of codons 00:18:52.220 --> 00:18:55.360 without any stops in the reading frame, until 00:18:55.360 --> 00:18:57.390 you get to a stop. 00:18:57.390 --> 00:19:01.320 That's called an open reading frame, a long stretch without 00:19:01.320 --> 00:19:02.780 stop codons. 00:19:02.780 --> 00:19:04.610 So I could look for an open reading frame. 00:19:18.560 --> 00:19:21.020 So by an open reading frame, I mean a long stretch that 00:19:21.020 --> 00:19:24.370 starts with an ATG and then goes on and on 00:19:24.370 --> 00:19:25.570 and on and on with-- 00:19:25.570 --> 00:19:26.630 How frequent are stops? 00:19:26.630 --> 00:19:28.500 There are three stops out of 64. 00:19:28.500 --> 00:19:31.340 One codon in 20 is a stop, on average. 00:19:31.340 --> 00:19:35.030 So if I go 20 codons, I might see a stop, on average. 00:19:35.030 --> 00:19:40.990 But suppose I run for 100 codons, and there's no stop--- 00:19:40.990 --> 00:19:43.460 without a stop codon. 00:19:43.460 --> 00:19:48.130 That's pretty impressive, isn't it, if I can read 100 00:19:48.130 --> 00:19:50.370 codons in a row, and I never see a stop, 00:19:50.370 --> 00:19:51.760 that's pretty unusual. 00:19:51.760 --> 00:19:53.110 So I say, that's an open reading frame. 00:19:56.370 --> 00:19:58.960 That's one way to recognize the gene in there. 00:19:58.960 --> 00:20:01.770 The problem is introns. 00:20:01.770 --> 00:20:04.760 What happens if there's an intron? 00:20:04.760 --> 00:20:05.900 Yikes. 00:20:05.900 --> 00:20:08.120 Then it'll be spliced there. 00:20:08.120 --> 00:20:10.490 That'll be spliced out, but I won't initially know that, 00:20:10.490 --> 00:20:11.350 reading the sequence. 00:20:11.350 --> 00:20:14.730 And there could be stop codons in the intron because it's not 00:20:14.730 --> 00:20:17.510 part of the final message. 00:20:17.510 --> 00:20:18.780 So I'm in trouble. 00:20:18.780 --> 00:20:22.050 So happily, in yeast, which has very small introns, not 00:20:22.050 --> 00:20:25.140 very many introns, I can actually almost get away by 00:20:25.140 --> 00:20:26.860 looking for open reading frames. 00:20:26.860 --> 00:20:31.332 In human DNA, this is kind of lousy. 00:20:31.332 --> 00:20:33.760 Well, it's really problematic because 00:20:33.760 --> 00:20:35.420 there'll be too many introns. 00:20:35.420 --> 00:20:38.070 There, other tricks that get used-- 00:20:38.070 --> 00:20:42.090 I could make cDNA and compare it to cDNAs, which have 00:20:42.090 --> 00:20:44.210 already spliced everything out, and look for the open 00:20:44.210 --> 00:20:45.390 reading frame. 00:20:45.390 --> 00:20:47.330 Other tricks that get used-- 00:20:47.330 --> 00:20:49.590 I can compare it to the database of everything 00:20:49.590 --> 00:20:52.830 everybody has ever sequenced before and start looking for 00:20:52.830 --> 00:20:54.010 similarities. 00:20:54.010 --> 00:20:56.480 And today there are massive databases. 00:20:56.480 --> 00:21:01.490 So many years ago, a postdoctoral fellow in my lab 00:21:01.490 --> 00:21:04.640 cloned a gene related to a human disease. 00:21:04.640 --> 00:21:07.000 And she didn't know what the gene did. 00:21:07.000 --> 00:21:09.630 And she found it. 00:21:09.630 --> 00:21:11.935 And it had exons, but she didn't know 00:21:11.935 --> 00:21:14.250 where they were yet. 00:21:14.250 --> 00:21:17.610 But she just took the whole sequence and said, this 00:21:17.610 --> 00:21:21.430 sequence here, is it similar to anything that's ever been 00:21:21.430 --> 00:21:22.820 seen before? 00:21:22.820 --> 00:21:25.580 This was a gene that was in people who had a really severe 00:21:25.580 --> 00:21:28.820 form of dwarfism with twisted bones and things, called 00:21:28.820 --> 00:21:30.370 diastrophic dysplasia. 00:21:30.370 --> 00:21:33.060 And she put it against the computer database. 00:21:33.060 --> 00:21:36.910 And the computer came back and said, the sequence you just 00:21:36.910 --> 00:21:42.120 gave me has a whole lot of patches that looks just like 00:21:42.120 --> 00:21:46.680 sulfate transporters in a fungus. 00:21:46.680 --> 00:21:51.030 She instantly knew what her gene did. 00:21:51.030 --> 00:21:53.830 Because it turns out that bones have a lot of sulfated 00:21:53.830 --> 00:21:56.780 proteoglycans, et cetera, et cetera, whatever those are. 00:21:56.780 --> 00:21:59.370 And she instantly knew, because my sequence was 00:21:59.370 --> 00:22:01.190 similar to something-- it's a human sequence similar to 00:22:01.190 --> 00:22:04.430 something in a fungus that does sulfate transport, I've 00:22:04.430 --> 00:22:05.800 probably got a sulfate transporter. 00:22:05.800 --> 00:22:07.700 That's probably the basis of my disease. 00:22:07.700 --> 00:22:10.900 She took her cells from her patients, added sulfate, found 00:22:10.900 --> 00:22:14.060 that the cells couldn't take up sulfate very well, and 00:22:14.060 --> 00:22:16.490 bingo-- had found the cause of her disease. 00:22:16.490 --> 00:22:18.670 One of the most powerful ways-- 00:22:18.670 --> 00:22:21.120 it's sort of Google, of course, right?-- 00:22:21.120 --> 00:22:22.480 it's Google before Google. 00:22:22.480 --> 00:22:24.700 You take your sequence and you Google it against all other 00:22:24.700 --> 00:22:27.440 sequences and see what it's like. 00:22:27.440 --> 00:22:30.540 And by googling all of life's sequences against each other, 00:22:30.540 --> 00:22:33.740 if somebody else has already solved your problem for you, 00:22:33.740 --> 00:22:36.350 you can find out about your problem. 00:22:36.350 --> 00:22:39.340 And it's just this wonderful network effect that is so 00:22:39.340 --> 00:22:41.940 characteristic of information technologies. 00:22:41.940 --> 00:22:47.320 So anyway, you can do that by searching databases. 00:22:47.320 --> 00:22:48.815 And we will not, in this class. 00:22:51.650 --> 00:22:53.830 So you can write code for looking for open reading 00:22:53.830 --> 00:22:57.150 frames, you can search databases for similarities 00:22:57.150 --> 00:23:00.610 across organisms or within organisms, 00:23:00.610 --> 00:23:01.750 or things like that. 00:23:01.750 --> 00:23:04.850 We won't here, but there are at MIT some great courses on 00:23:04.850 --> 00:23:08.550 computational biology that, for example, you can write 00:23:08.550 --> 00:23:10.620 algorithms for detecting these sorts of things. 00:23:10.620 --> 00:23:11.490 It's an interesting question. 00:23:11.490 --> 00:23:14.340 How do you write an algorithm for comparing two strings 00:23:14.340 --> 00:23:17.200 which might have insertions and deletions and changes and 00:23:17.200 --> 00:23:17.780 things like that? 00:23:17.780 --> 00:23:20.820 There's a whole rich field of computational mathematics 00:23:20.820 --> 00:23:23.060 associated with genome comparisons. 00:23:23.060 --> 00:23:23.910 All right. 00:23:23.910 --> 00:23:26.240 So we've got it. 00:23:26.240 --> 00:23:27.348 Bingo! 00:23:27.348 --> 00:23:30.910 Now, here's our next problem. 00:23:30.910 --> 00:23:38.010 Our next problem, we cloned the gene for 00:23:38.010 --> 00:23:41.730 beta globin from you. 00:23:41.730 --> 00:23:42.770 You were kind enough. 00:23:42.770 --> 00:23:46.020 You signed an informed consent allowing us to take some DNA, 00:23:46.020 --> 00:23:47.370 prepare a library. 00:23:47.370 --> 00:23:49.220 We made our antibody, we found your beta 00:23:49.220 --> 00:23:51.360 globin gene, et cetera. 00:23:51.360 --> 00:23:55.310 Now we're going to conduct a study of beta globin in a 00:23:55.310 --> 00:23:58.010 larger population. 00:23:58.010 --> 00:24:01.740 Maybe we're going to ask multiple people in the class, 00:24:01.740 --> 00:24:04.420 would they be willing to sign an informed consent to have 00:24:04.420 --> 00:24:06.740 their beta globin gene sequenced? 00:24:06.740 --> 00:24:07.740 It's an interesting gene. 00:24:07.740 --> 00:24:10.320 There are variants in it that confer risk of sickle cell. 00:24:10.320 --> 00:24:13.040 There are variants in it that confer risks of other things. 00:24:13.040 --> 00:24:14.790 There are fascinating things about that gene. 00:24:14.790 --> 00:24:17.110 Maybe we'd like to see the beta globin 00:24:17.110 --> 00:24:18.130 sequence of many people. 00:24:18.130 --> 00:24:20.380 How do we get the beta globin sequence of a second person? 00:24:24.430 --> 00:24:25.690 Well, how'd we get the beta globin sequence 00:24:25.690 --> 00:24:27.890 from the first person? 00:24:27.890 --> 00:24:34.520 Took DNA, cut it up, cloned it in our vector, spread it out 00:24:34.520 --> 00:24:37.230 on the plate, washed over the antibody-- 00:24:37.230 --> 00:24:39.200 actually, we took cDNA-- 00:24:39.200 --> 00:24:42.400 washed it over, et cetera, et cetera, et cetera. 00:24:42.400 --> 00:24:43.890 It's a lot of work. 00:24:43.890 --> 00:24:46.410 If we wanted to do 100 people in this class, do we have to 00:24:46.410 --> 00:24:50.820 get DNA from each of you, prepare a library, maybe a 00:24:50.820 --> 00:24:54.880 cDNA library even, and do the same exact process to discover 00:24:54.880 --> 00:24:57.200 your beta globe gene? 00:24:57.200 --> 00:25:00.000 Or is there any way where after we've done your beta 00:25:00.000 --> 00:25:03.740 globin gene, we could now do everybody's beta globin gene a 00:25:03.740 --> 00:25:04.990 lot easier? 00:25:07.440 --> 00:25:09.440 STUDENT: [INAUDIBLE] 00:25:09.440 --> 00:25:11.040 ERIC LANDER: Actually, I do know the sequence. 00:25:11.040 --> 00:25:12.930 That's the thing that's different is having found it 00:25:12.930 --> 00:25:15.970 once, I know the whole sequence. 00:25:15.970 --> 00:25:19.640 The question is, can I use the sequence to save me the 00:25:19.640 --> 00:25:24.060 trouble of making an entire library of everything? 00:25:24.060 --> 00:25:27.130 How can I use the knowledge I've just gained to make it so 00:25:27.130 --> 00:25:28.560 much easier? 00:25:28.560 --> 00:25:32.510 Well, the answer occurred to a chemist working at Cetus 00:25:32.510 --> 00:25:35.590 corporation in the mid 1980s. 00:25:35.590 --> 00:25:38.580 He was driving along, and he was thinking about this very 00:25:38.580 --> 00:25:42.410 problem and thinking about sequencing and how they do it. 00:25:42.410 --> 00:25:45.650 And he had the following thought. 00:25:45.650 --> 00:25:49.630 His following thought was, suppose we've got the whole 00:25:49.630 --> 00:25:51.250 human genome. 00:25:51.250 --> 00:25:53.160 There's a whole human genome. 00:25:53.160 --> 00:25:56.380 And I'm just going to melt it for you, for a second, into 00:25:56.380 --> 00:25:58.016 two strands. 00:25:58.016 --> 00:25:59.670 And suppose we've already discovered 00:25:59.670 --> 00:26:01.780 the beta globin gene. 00:26:01.780 --> 00:26:05.590 The beta globin gene is right over here, it turns out. 00:26:05.590 --> 00:26:06.840 That's beta globin. 00:26:10.540 --> 00:26:11.790 Well, we know this whole sequence. 00:26:16.950 --> 00:26:18.100 This is total DNA. 00:26:18.100 --> 00:26:19.640 I haven't done anything right now. 00:26:19.640 --> 00:26:21.140 This is the whole human genome that runs 00:26:21.140 --> 00:26:22.960 over 3 billion bases. 00:26:22.960 --> 00:26:24.413 But it's the whole genome. 00:26:24.413 --> 00:26:28.010 I know the sequence, right? 00:26:28.010 --> 00:26:32.500 I could make a primer to that part of the sequence. 00:26:32.500 --> 00:26:34.590 And suppose I just make a primer to that part of the 00:26:34.590 --> 00:26:37.990 sequence, throw it into your total DNA, and I add 00:26:37.990 --> 00:26:40.410 polymerase and nucleotides. 00:26:40.410 --> 00:26:47.850 Maybe it'll start copying. 00:26:47.850 --> 00:26:48.970 At some point, it'll fall off. 00:26:48.970 --> 00:26:57.630 But notice, I've made an extra copy of beta globin-- 00:26:57.630 --> 00:27:01.210 of course, mixed into the whole, total human genome. 00:27:01.210 --> 00:27:04.130 But there's a little bit extra beta globin now. 00:27:04.130 --> 00:27:06.600 Suppose I also made a primer over here. 00:27:13.070 --> 00:27:14.320 I'd get that. 00:27:16.320 --> 00:27:18.810 I'd now have two double strands of beta globin, 00:27:18.810 --> 00:27:20.080 whereas before, I only had one. 00:27:23.930 --> 00:27:25.180 Let's call this step 1. 00:27:28.190 --> 00:27:31.030 What do you think step 1 should be followed by? 00:27:31.030 --> 00:27:32.030 STUDENT: Step 2. 00:27:32.030 --> 00:27:33.010 ERIC LANDER: Step 2. 00:27:33.010 --> 00:27:34.490 Very good. 00:27:34.490 --> 00:27:35.140 Excellent. 00:27:35.140 --> 00:27:38.190 You guys have learned induction. 00:27:38.190 --> 00:27:59.230 So let me melt the DNA and now throw back my primer. 00:28:03.240 --> 00:28:07.440 Actually, if you'll allow me, I'm going to make the two 00:28:07.440 --> 00:28:10.230 primers different colors. 00:28:10.230 --> 00:28:13.470 Let's make that one a different color. 00:28:13.470 --> 00:28:14.720 There we go. 00:28:20.270 --> 00:28:27.240 So now what will happen is this primer goes here. 00:28:27.240 --> 00:28:30.280 This green primer goes here. 00:28:34.220 --> 00:28:37.420 This guy sits down here. 00:28:42.060 --> 00:28:44.306 And this guy goes like that. 00:28:44.306 --> 00:28:45.950 Well, that didn't come out very good. 00:28:45.950 --> 00:28:47.945 I'll just draw it a little more clearly here. 00:28:50.560 --> 00:28:58.160 What happens is this guy will start copying this way. 00:28:58.160 --> 00:29:02.600 This guy starts copying this way. 00:29:02.600 --> 00:29:06.470 This guy starts copying this way. 00:29:06.470 --> 00:29:11.860 This guy starts copying this way. 00:29:11.860 --> 00:29:16.910 Now, after step 2, how many copies of 00:29:16.910 --> 00:29:19.670 beta globin do I have? 00:29:19.670 --> 00:29:20.920 Four copies. 00:29:24.500 --> 00:29:26.424 What's the next step? 00:29:26.424 --> 00:29:27.300 STUDENT: Step 3. 00:29:27.300 --> 00:29:28.190 ERIC LANDER: Step 3. 00:29:28.190 --> 00:29:28.940 Very good. 00:29:28.940 --> 00:29:30.810 No putting anything over on you. 00:29:30.810 --> 00:29:33.900 And after we melt the DNA and we add back the primers, how 00:29:33.900 --> 00:29:36.031 many copies of beta globin will we now have? 00:29:38.917 --> 00:29:39.400 STUDENT: Eight. 00:29:39.400 --> 00:29:41.700 ERIC LANDER: Eight, because it's doubling every time. 00:29:41.700 --> 00:29:44.240 Step 4? 00:29:44.240 --> 00:29:46.050 Step 10? 00:29:46.050 --> 00:29:47.910 2 the 10th. 00:29:47.910 --> 00:29:48.860 2 to the 10th, because we're doubling. 00:29:48.860 --> 00:29:50.270 2 to the 10th. 00:29:50.270 --> 00:29:51.520 Step 20? 00:29:53.990 --> 00:29:58.790 2 to the 20th, which is about a million. 00:29:58.790 --> 00:30:01.800 Step 30? 00:30:01.800 --> 00:30:04.030 2 to the 30th is about a billion. 00:30:07.410 --> 00:30:08.660 Oh. 00:30:11.810 --> 00:30:20.480 After 30 steps, I have 2 to the 30th copies, which is 00:30:20.480 --> 00:30:24.080 about a billion copies. 00:30:24.080 --> 00:30:26.970 And at that point, the majority of the DNA in my tube 00:30:26.970 --> 00:30:28.470 is beta globin. 00:30:28.470 --> 00:30:30.855 The rest of the human genome is still there, but beta 00:30:30.855 --> 00:30:33.635 globin started out being one 00:30:33.635 --> 00:30:37.190 one-hundred-millionth of the genome. 00:30:37.190 --> 00:30:40.590 And I've just amplified it a billionfold. 00:30:40.590 --> 00:30:45.080 So it's now 90% of what's in the tube. 00:30:45.080 --> 00:30:47.070 Pretty cool. 00:30:47.070 --> 00:30:48.400 This is like a chain reaction. 00:30:48.400 --> 00:30:49.890 You do it once, you do it again, you do it 00:30:49.890 --> 00:30:50.770 again, you do it again. 00:30:50.770 --> 00:30:54.280 You just throw in polymerase, and you run a chain reaction. 00:30:54.280 --> 00:31:10.610 This therefore is called the polymerase chain reaction, or 00:31:10.610 --> 00:31:12.862 as it is universally known, PCR. 00:31:16.040 --> 00:31:17.670 That's PCR. 00:31:17.670 --> 00:31:21.020 That's the polymerase chain reaction. 00:31:21.020 --> 00:31:23.830 Kary Mullis, who invented this thing, won a Nobel Prize in 00:31:23.830 --> 00:31:24.890 chemistry for it. 00:31:24.890 --> 00:31:26.930 Because notice what he's just done. 00:31:26.930 --> 00:31:31.400 He's cloned your beta globin gene without cloning. 00:31:31.400 --> 00:31:33.050 It's cloning without cloning. 00:31:33.050 --> 00:31:34.900 I didn't need any vectors, I didn't need any bacteria, I 00:31:34.900 --> 00:31:35.730 didn't need no nothing. 00:31:35.730 --> 00:31:39.960 All I needed was the sequence that I got once by cloning, 00:31:39.960 --> 00:31:41.890 and then I'm off to the races. 00:31:41.890 --> 00:31:43.603 I throw in two primers-- 00:31:43.603 --> 00:31:46.370 choop-choop-choop-choop-choop-- 00:31:46.370 --> 00:31:47.750 bingo! 00:31:47.750 --> 00:31:49.880 Where do my primers come from? 00:31:49.880 --> 00:31:51.020 They're not in the catalogs. 00:31:51.020 --> 00:31:52.140 We don't keep all that inventory. 00:31:52.140 --> 00:31:54.440 You just type them in, and they come to you the next day 00:31:54.440 --> 00:31:56.640 by an automatic synthesis machine. 00:31:56.640 --> 00:31:59.370 So anyplace in the human genome or the yeast genome or 00:31:59.370 --> 00:32:02.930 any other thing that you want to PCR, just give me the two 00:32:02.930 --> 00:32:04.620 primers and piece it out. 00:32:04.620 --> 00:32:05.360 How do we do this? 00:32:05.360 --> 00:32:07.750 There are a couple of the details that I have to worry 00:32:07.750 --> 00:32:09.000 about here. 00:32:11.290 --> 00:32:14.990 Cooking details here for the recipe. 00:32:14.990 --> 00:32:18.415 What I have to do is I have to take my test tube, and I have 00:32:18.415 --> 00:32:24.290 to heat it up so high that the double helix melts and comes 00:32:24.290 --> 00:32:26.960 apart, so that the primers can get in there. 00:32:26.960 --> 00:32:32.120 So I have to heat to 97 degrees. 00:32:35.230 --> 00:32:38.360 Then it comes apart. 00:32:38.360 --> 00:32:42.410 I cool it down, I add my polymerase. 00:32:42.410 --> 00:32:45.990 I cool it, I add polymerase and nucleotides. 00:32:54.690 --> 00:32:56.270 And then it does its extension. 00:32:56.270 --> 00:32:58.630 Then I heat it up to 97. 00:32:58.630 --> 00:33:00.320 Now the problem is when I heat it up to 97, you know what 00:33:00.320 --> 00:33:02.256 happens to my polymerase? 00:33:02.256 --> 00:33:02.700 STUDENT: Denatured. 00:33:02.700 --> 00:33:03.490 ERIC LANDER: It gets denatured, 00:33:03.490 --> 00:33:04.660 and it doesn't come. 00:33:04.660 --> 00:33:05.820 It's ruined. 00:33:05.820 --> 00:33:08.250 So what I have to do is I have to pop open my two-- 00:33:08.250 --> 00:33:09.690 Sorry, you had a question? 00:33:09.690 --> 00:33:10.940 STUDENT: [INAUDIBLE] 00:33:13.110 --> 00:33:14.120 ERIC LANDER: Why do I heat it up? 00:33:14.120 --> 00:33:16.320 There are ways you might be able to avoid it. 00:33:16.320 --> 00:33:18.530 But the traditional technique is you heat it up. 00:33:18.530 --> 00:33:20.230 But you're right, there might be other solution. 00:33:20.230 --> 00:33:22.110 But now I'm going heat it up. 00:33:22.110 --> 00:33:24.280 And my polymerase gets denatured. 00:33:24.280 --> 00:33:26.880 So I have to pop open the test tube, throw in some more 00:33:26.880 --> 00:33:30.750 polymerase, let it do its work, heat it up again, pop 00:33:30.750 --> 00:33:32.750 open the test tube, put some more polymerase in. 00:33:32.750 --> 00:33:33.780 And it gets really boring. 00:33:33.780 --> 00:33:35.820 Every one of these 30 steps, I have to keep adding 00:33:35.820 --> 00:33:37.070 polymerase. 00:33:41.780 --> 00:33:44.180 So the engineers in you will say, why don't we just design 00:33:44.180 --> 00:33:47.430 a polymerase that doesn't denature at 97 degrees? 00:33:47.430 --> 00:33:49.800 So we should go to an expert and say, please make us a 00:33:49.800 --> 00:33:52.980 polymerase that doesn't denature at 97 degrees, even 00:33:52.980 --> 00:33:55.630 that doesn't mind being boiled. 00:33:55.630 --> 00:33:59.220 So what expert do we go to? 00:33:59.220 --> 00:33:59.980 STUDENT: Bacteria. 00:33:59.980 --> 00:34:00.960 ERIC LANDER: Bacteria. 00:34:00.960 --> 00:34:03.650 What bacteria do you think has a DNA polymerase that doesn't 00:34:03.650 --> 00:34:05.058 mind being boiled? 00:34:05.058 --> 00:34:06.730 STUDENT: [INAUDIBLE]. 00:34:06.730 --> 00:34:08.350 ERIC LANDER: Bacteria that live in, say, 00:34:08.350 --> 00:34:10.070 geysers, hot springs. 00:34:10.070 --> 00:34:11.340 So you go to a hot spring. 00:34:11.340 --> 00:34:14.370 You go to geyser, you go to Yosemite, and you fish out 00:34:14.370 --> 00:34:16.920 some water, and you see what's growing there, and you find 00:34:16.920 --> 00:34:19.719 the bacteria growing there that has the 00:34:19.719 --> 00:34:25.380 name Thermus aquaticus. 00:34:31.070 --> 00:34:34.300 And you purify DNA from Thermus aquaticus. 00:34:34.300 --> 00:34:38.900 Thermus aquaticus just goes by name TAQ, T-A-Q. You purify 00:34:38.900 --> 00:34:40.929 TAQ polymerase. 00:34:40.929 --> 00:34:44.060 And now, no problem. 00:34:44.060 --> 00:34:46.610 You just use TAQ polymerase, throw it in your test tube. 00:34:46.610 --> 00:34:48.290 And you go heat, cool, heat, cool, heat,cool, heat, cool, 00:34:48.290 --> 00:34:51.000 heat, cool, and you're all done. 00:34:51.000 --> 00:34:52.690 You just put it on a little heating block. 00:34:52.690 --> 00:34:54.650 And the heating block automatically goes hot, cold, 00:34:54.650 --> 00:34:56.969 hot, cold, hot, cold, hot, cold. 00:34:56.969 --> 00:34:58.840 And that's called the thermocycler. 00:34:58.840 --> 00:35:00.490 The thermocycler does it. 00:35:00.490 --> 00:35:02.670 And of course, nowadays, do you have to yourself 00:35:02.670 --> 00:35:05.740 personally go to the hot spring and risk your life 00:35:05.740 --> 00:35:07.740 fishing out the bacteria? 00:35:07.740 --> 00:35:08.640 No. 00:35:08.640 --> 00:35:09.950 Because it's in--? 00:35:09.950 --> 00:35:10.380 STUDENT: The catalog. 00:35:10.380 --> 00:35:11.350 ERIC LANDER: The catalog. 00:35:11.350 --> 00:35:12.620 Exactly. 00:35:12.620 --> 00:35:13.240 Very good. 00:35:13.240 --> 00:35:16.740 TAQ polymerase is in the catalog. 00:35:16.740 --> 00:35:18.470 All right. 00:35:18.470 --> 00:35:19.310 I'll tell you a story. 00:35:19.310 --> 00:35:22.330 The statute of limitations has already expired, so it's OK. 00:35:22.330 --> 00:35:25.060 TAQ polymerase used to be very expensive. 00:35:25.060 --> 00:35:29.000 So we needed a lot of it in our lab. 00:35:29.000 --> 00:35:33.100 And we couldn't afford all of it. 00:35:33.100 --> 00:35:39.360 So what we did was we just looked up the sequence of the 00:35:39.360 --> 00:35:44.100 TAQ polymerase in Thermus aquaticus, got primers, used 00:35:44.100 --> 00:35:49.640 PCR to get the gene for TAQ polymerase, and then expressed 00:35:49.640 --> 00:35:51.940 it to make a lot of TAQ polymerase. 00:35:51.940 --> 00:35:54.500 So it's kind of cool. 00:35:54.500 --> 00:35:57.040 Anyway, that was about 15 years ago. 00:35:57.040 --> 00:35:59.830 We produced in a few days what was then worth about $4 00:35:59.830 --> 00:36:01.610 million worth of TAQ polymerase. 00:36:01.610 --> 00:36:02.402 [LAUGHTER] 00:36:02.402 --> 00:36:05.030 That was why we went to the trouble of doing it. 00:36:07.810 --> 00:36:09.900 We didn't end up getting in any real trouble about it. 00:36:09.900 --> 00:36:10.250 OK. 00:36:10.250 --> 00:36:13.770 So now, why is this stuff cool? 00:36:13.770 --> 00:36:19.290 This stuff is cool because you're able to amplify tiny 00:36:19.290 --> 00:36:20.240 amounts of DNA. 00:36:20.240 --> 00:36:22.720 So if I want to purify any human gene now, and I know its 00:36:22.720 --> 00:36:25.480 sequence initially, PCR it out. 00:36:25.480 --> 00:36:27.730 No problem. 00:36:27.730 --> 00:36:32.300 Suppose a patient presents with a bacterial infection. 00:36:32.300 --> 00:36:34.730 And you're a physician. 00:36:34.730 --> 00:36:37.530 And you suspect that there might be a specific bacterial 00:36:37.530 --> 00:36:40.960 infection or maybe a specific viral infection. 00:36:40.960 --> 00:36:43.115 So applications of PCR. 00:36:50.260 --> 00:36:52.180 Application of PCR? 00:36:52.180 --> 00:36:55.780 Well, resequencing a known gene, yes. 00:36:55.780 --> 00:36:58.160 Resequencing beta globin. 00:36:58.160 --> 00:37:00.325 But infectious disease. 00:37:08.340 --> 00:37:09.910 I have a patient. 00:37:09.910 --> 00:37:11.450 I think there might be a bacteria, there might be a 00:37:11.450 --> 00:37:13.230 virus in the blood. 00:37:13.230 --> 00:37:14.480 What do I do? 00:37:16.650 --> 00:37:19.700 Make primers, do PCR. 00:37:19.700 --> 00:37:21.570 I have a detection technique. 00:37:21.570 --> 00:37:25.530 I can detect the presence of a viral infection 00:37:25.530 --> 00:37:27.320 or a bacterial infection. 00:37:27.320 --> 00:37:31.540 For example, HIV testing can be done by PCR. 00:37:31.540 --> 00:37:33.170 Because it doesn't take very much there in 00:37:33.170 --> 00:37:35.900 order to detect it. 00:37:35.900 --> 00:37:37.620 Water contamination. 00:37:37.620 --> 00:37:40.930 You can test for bugs that shouldn't be in the water, by 00:37:40.930 --> 00:37:43.070 PCR because you don't need much. 00:37:43.070 --> 00:37:45.160 How little do you need? 00:37:45.160 --> 00:37:49.540 Suppose I take a tube of DNA, and I start diluting it and 00:37:49.540 --> 00:37:52.330 diluting it and diluting it. 00:37:52.330 --> 00:37:55.660 How far down do you think I can go and still PCR back up, 00:37:55.660 --> 00:37:58.670 say, beta globin? 00:37:58.670 --> 00:38:01.360 Suppose I dilute it so that there's only like 1,000 copies 00:38:01.360 --> 00:38:04.040 of beta globin left, on average. 00:38:04.040 --> 00:38:06.590 Can I still PCR it? 00:38:06.590 --> 00:38:09.100 100 copies? 00:38:09.100 --> 00:38:11.260 10 copies? 00:38:11.260 --> 00:38:13.920 Suppose I dilute it so on average there's only one copy 00:38:13.920 --> 00:38:16.280 of the beta globin molecule there. 00:38:16.280 --> 00:38:19.810 Can I PCR it? 00:38:19.810 --> 00:38:22.410 How can I prove that? 00:38:22.410 --> 00:38:23.590 An easy way to prove that-- 00:38:23.590 --> 00:38:25.930 I could do it statistically by just diluting it so that on 00:38:25.930 --> 00:38:27.380 average there's only one beta globin. 00:38:27.380 --> 00:38:29.950 But how can I get one copy of beta globin 00:38:29.950 --> 00:38:31.260 packaged up very nicely? 00:38:34.410 --> 00:38:35.310 STUDENT: Order it. 00:38:35.310 --> 00:38:36.146 ERIC LANDER: Sorry? 00:38:36.146 --> 00:38:37.394 STUDENT: Order it. 00:38:37.394 --> 00:38:39.550 ERIC LANDER: No. 00:38:39.550 --> 00:38:40.800 Can't order that. 00:38:45.040 --> 00:38:47.660 Where do you know that there's just exactly one copy of the 00:38:47.660 --> 00:38:49.950 beta globin gene? 00:38:49.950 --> 00:38:53.510 One human sperm. 00:38:53.510 --> 00:38:55.570 Suppose with a micromanipulator, I purify a 00:38:55.570 --> 00:38:58.450 single human sperm, one sperm. 00:39:03.420 --> 00:39:03.895 It's haploid. 00:39:03.895 --> 00:39:05.940 It's got exactly one beta globin. 00:39:05.940 --> 00:39:10.020 Throw it in a test tube, crack it open, do PCR, it works. 00:39:10.020 --> 00:39:13.230 That's how I demonstrate that a single copy is enough. 00:39:13.230 --> 00:39:14.240 I can make that work. 00:39:14.240 --> 00:39:15.550 Pretty impressive. 00:39:15.550 --> 00:39:18.130 Not only that, that I can do it from a 00:39:18.130 --> 00:39:19.380 single copy in a sperm. 00:39:25.390 --> 00:39:27.576 If someone is doing in vitro fertilization-- 00:39:32.350 --> 00:39:34.070 remember, in vitro fertilization won the Nobel 00:39:34.070 --> 00:39:37.396 Prize this semester-- 00:39:37.396 --> 00:39:38.810 in vitro. 00:39:38.810 --> 00:39:42.960 Suppose a couple has a 1 in 4 chance of having a baby with 00:39:42.960 --> 00:39:45.520 some terrible lethal disorder. 00:39:45.520 --> 00:39:49.150 The couple might use in vitro fertilization to make multiple 00:39:49.150 --> 00:39:52.300 independent embryos. 00:39:52.300 --> 00:39:56.540 The doctor, then, is deciding which embryo should we implant 00:39:56.540 --> 00:39:58.750 back in mom? 00:39:58.750 --> 00:40:03.660 Well, how could they tell at this eight-cell stage which 00:40:03.660 --> 00:40:07.030 embryo carries the genetic disease? 00:40:07.030 --> 00:40:08.930 Suppose this genetic disease they already knew the 00:40:08.930 --> 00:40:10.702 molecular mutation causing it. 00:40:13.600 --> 00:40:14.850 Pull off a cell. 00:40:19.400 --> 00:40:25.200 Pull off one cell, pull off one cell, pull off one cell. 00:40:25.200 --> 00:40:27.760 This is at the eight-cell stage, let's say. 00:40:27.760 --> 00:40:30.620 If I pull off one of those cells at the eight-cell stage, 00:40:30.620 --> 00:40:33.180 does that mean the baby doesn't have an ear or an arm 00:40:33.180 --> 00:40:34.860 or something? 00:40:34.860 --> 00:40:35.640 No, it doesn't. 00:40:35.640 --> 00:40:37.350 Because at that stage, none of the cells have 00:40:37.350 --> 00:40:39.030 taken up any identity. 00:40:39.030 --> 00:40:39.830 It regulates. 00:40:39.830 --> 00:40:40.630 There's no problem. 00:40:40.630 --> 00:40:43.550 It turns out you can pull off an individual cell, and it has 00:40:43.550 --> 00:40:45.960 no impact on the embryo. 00:40:45.960 --> 00:40:47.210 And I do PCR. 00:40:49.710 --> 00:40:53.330 And I can figure out that that one carries the severe genetic 00:40:53.330 --> 00:40:55.090 disease that's going to cause the baby 00:40:55.090 --> 00:40:56.630 to die at five months. 00:40:56.630 --> 00:40:59.120 And the couple says, we're not going to implant that one. 00:40:59.120 --> 00:41:00.580 We'll implant the other ones. 00:41:00.580 --> 00:41:02.580 That's called preimplantation diagnostics. 00:41:13.830 --> 00:41:17.310 Or suppose somebody's being treated for cancer. 00:41:17.310 --> 00:41:22.840 And the cancer cells that had previously been there are no 00:41:22.840 --> 00:41:25.070 longer detectable. 00:41:25.070 --> 00:41:27.820 The drug therapy has apparently killed this blood 00:41:27.820 --> 00:41:29.130 cancer that somebody has. 00:41:29.130 --> 00:41:31.620 Maybe they have a cancer of the blood. 00:41:31.620 --> 00:41:34.670 Now what I'm going to do is monitor that patient every 00:41:34.670 --> 00:41:38.250 several months by getting a blood sample and seeing if the 00:41:38.250 --> 00:41:40.110 distinct mutations that were present in 00:41:40.110 --> 00:41:41.830 the cancer were there. 00:41:41.830 --> 00:41:44.750 And I can begin to see if that's coming back, if those 00:41:44.750 --> 00:41:46.840 cells are now recurring. 00:41:46.840 --> 00:41:49.020 It's an incredibly sensitive technique. 00:41:49.020 --> 00:41:51.420 And then of course, where does this stuff get used that you 00:41:51.420 --> 00:41:55.280 guys all surely we know about? 00:41:55.280 --> 00:41:57.040 Forensics. 00:41:57.040 --> 00:41:59.120 CSI and all that kind of stuff. 00:42:02.660 --> 00:42:04.900 If I lick an envelope-- 00:42:04.900 --> 00:42:08.100 I used to say, licking a stamp, but stamps just peel 00:42:08.100 --> 00:42:08.700 off these days. 00:42:08.700 --> 00:42:10.610 But people still do lick an envelope sometimes. 00:42:10.610 --> 00:42:14.590 If you lick an envelope, more than enough DNA comes off when 00:42:14.590 --> 00:42:18.720 you lick the envelope that you can use PCR to determine who 00:42:18.720 --> 00:42:21.680 do the licking. 00:42:21.680 --> 00:42:22.930 ERIC LANDER: You can. 00:42:22.930 --> 00:42:24.590 It works. 00:42:24.590 --> 00:42:25.270 All right. 00:42:25.270 --> 00:42:26.520 So that's PCR.