1 00:00:00,500 --> 00:00:03,920 [SOUND EFFECTS] 2 00:00:16,680 --> 00:00:20,340 PROFESSOR: OK, I just want to just highlight your attention 3 00:00:20,340 --> 00:00:21,300 to things. 4 00:00:21,300 --> 00:00:23,460 Like every day, I get that MIT news feed. 5 00:00:23,460 --> 00:00:25,170 I get a couple of other news feeds. 6 00:00:25,170 --> 00:00:28,530 And I just thought this was really sort of a striking image 7 00:00:28,530 --> 00:00:33,060 and I think a great way to convey science and engineering 8 00:00:33,060 --> 00:00:37,300 is through sort of really eye catching imagery. 9 00:00:37,300 --> 00:00:41,190 This is a synapse, which is where nerves contact 10 00:00:41,190 --> 00:00:43,740 to other nerves or to the neuromuscular junction 11 00:00:43,740 --> 00:00:46,890 in order to trigger activity. 12 00:00:46,890 --> 00:00:52,050 And this is a piece of research out of the Cima-- whoops, 13 00:00:52,050 --> 00:00:55,440 go back one-- whoops, go back one more-- 14 00:00:55,440 --> 00:00:58,980 between the Cima and Langer labs, 15 00:00:58,980 --> 00:01:03,080 where they've designed little tiny microchip probes. 16 00:01:03,080 --> 00:01:05,670 They're about 10 microns big. 17 00:01:05,670 --> 00:01:09,420 They can be planted in the brain in different sites, 18 00:01:09,420 --> 00:01:12,160 hopefully non-invasively. 19 00:01:12,160 --> 00:01:14,850 And they can report on concentrations 20 00:01:14,850 --> 00:01:17,530 of this neurotransmitter, dopamine. 21 00:01:17,530 --> 00:01:19,860 And the reason you might want to be able to do that 22 00:01:19,860 --> 00:01:22,560 is that there is a dopamine deficit in a lot 23 00:01:22,560 --> 00:01:24,400 of neurologic disorders. 24 00:01:24,400 --> 00:01:27,540 So you would like to understand what the deficits are 25 00:01:27,540 --> 00:01:32,320 and pinpoint points of the brain where there may be issues. 26 00:01:32,320 --> 00:01:38,640 And in fact, they used it to track Parkinson's disease. 27 00:01:38,640 --> 00:01:40,890 Because Parkinson's disease, some 28 00:01:40,890 --> 00:01:45,690 of the therapeutic approaches involve deep brain stimulation. 29 00:01:45,690 --> 00:01:47,220 But you can't really tell if it's 30 00:01:47,220 --> 00:01:49,710 working unless you can measure something. 31 00:01:49,710 --> 00:01:51,240 And the thing that you could measure 32 00:01:51,240 --> 00:01:54,840 would be the absolute levels of this neurotransmitter, 33 00:01:54,840 --> 00:02:00,540 dopamine, which, by the way, is originated from the amino acid 34 00:02:00,540 --> 00:02:01,980 tyrosine. 35 00:02:01,980 --> 00:02:04,650 You could sort of spot some of the parts of that. 36 00:02:04,650 --> 00:02:07,410 That would be the carbon. 37 00:02:07,410 --> 00:02:11,790 Becomes a c-- there's a carboxylate and an amine. 38 00:02:11,790 --> 00:02:14,110 Oh, I've drawn the alcohol. 39 00:02:14,110 --> 00:02:15,560 This should be an NH2. 40 00:02:15,560 --> 00:02:17,640 Sorry, I just added this at last minute. 41 00:02:17,640 --> 00:02:21,690 So dopamine actually though originates from tyrosine. 42 00:02:21,690 --> 00:02:24,390 So I just thought you would be interested because when 43 00:02:24,390 --> 00:02:27,720 I talk about the highlighting things that are in the news, 44 00:02:27,720 --> 00:02:31,710 I mean things like this where we're all kind of interested. 45 00:02:31,710 --> 00:02:32,340 It's cool. 46 00:02:32,340 --> 00:02:34,620 It's relevant to what we do. 47 00:02:34,620 --> 00:02:37,980 And it really combines the efforts 48 00:02:37,980 --> 00:02:42,180 of scientists and engineers to make tools and methods 49 00:02:42,180 --> 00:02:45,000 and invent methods to make measurements 50 00:02:45,000 --> 00:02:47,310 that are quantitative enough to guide 51 00:02:47,310 --> 00:02:51,010 the analysis of a disorder. 52 00:02:51,010 --> 00:02:54,940 So I just want to wrap up a little bit on the aspects. 53 00:02:54,940 --> 00:02:58,440 I was showing you the energy diagrams in the last class 54 00:02:58,440 --> 00:03:03,720 and telling you how enzymes affect the course of a reaction 55 00:03:03,720 --> 00:03:06,480 by lowering the energy of activation, 56 00:03:06,480 --> 00:03:09,720 by stabilizing a transition state or a high energy 57 00:03:09,720 --> 00:03:11,370 intermediate state. 58 00:03:11,370 --> 00:03:13,280 So the energy of activation becomes 59 00:03:13,280 --> 00:03:15,670 smaller in the catalyzed reaction, 60 00:03:15,670 --> 00:03:18,930 therefore faster than any uncatalyzed reaction. 61 00:03:18,930 --> 00:03:21,450 And I did not give you this number last time. 62 00:03:21,450 --> 00:03:25,890 Enzymes catalyze reactions through about 10 63 00:03:25,890 --> 00:03:29,730 to the 6, a million 10 to the 10-fold. 64 00:03:29,730 --> 00:03:32,850 So these are dramatic increases in rates 65 00:03:32,850 --> 00:03:36,660 that are really physio-- we depend on physiologically. 66 00:03:36,660 --> 00:03:38,340 They ensure specificity. 67 00:03:38,340 --> 00:03:40,500 And they're essential in all systems. 68 00:03:40,500 --> 00:03:47,040 And the way we discuss energetic changes in reaction diagrams 69 00:03:47,040 --> 00:03:49,170 is by looking at what's known as the delta 70 00:03:49,170 --> 00:03:52,140 G. It's the change in free energy. 71 00:03:52,140 --> 00:03:56,370 What I show you here is an exergonic reaction, where 72 00:03:56,370 --> 00:04:00,120 it is a negative delta G. I didn't reinforce that point 73 00:04:00,120 --> 00:04:01,530 enough last time. 74 00:04:01,530 --> 00:04:04,980 The energy of the products is lower than the energy 75 00:04:04,980 --> 00:04:06,280 of the substrates. 76 00:04:06,280 --> 00:04:09,900 So energy is given out at the end of the transformation. 77 00:04:09,900 --> 00:04:13,350 That means the reaction is favorable with respect 78 00:04:13,350 --> 00:04:16,649 to an equilibrium, a thermodynamic parameter. 79 00:04:16,649 --> 00:04:18,750 And then it's the enzyme that takes 80 00:04:18,750 --> 00:04:23,800 care of the kinetic aspects of the reaction. 81 00:04:23,800 --> 00:04:26,630 So just to sort of show you the correlate, 82 00:04:26,630 --> 00:04:29,970 an endergonic reaction would look like this, 83 00:04:29,970 --> 00:04:32,250 where the delta G is positive. 84 00:04:32,250 --> 00:04:35,380 The products are less stable than the starting materials, 85 00:04:35,380 --> 00:04:38,190 which would mean the reaction is not favorable. 86 00:04:38,190 --> 00:04:41,130 But it will still proceed in the presence of a catalyst. 87 00:04:41,130 --> 00:04:42,690 And in this next small bit where we 88 00:04:42,690 --> 00:04:46,110 talk about pathways and different aspects 89 00:04:46,110 --> 00:04:48,630 of metabolism, I'm going to tell you 90 00:04:48,630 --> 00:04:51,640 how we get around the unfavorable equilibrium 91 00:04:51,640 --> 00:04:52,140 problem. 92 00:04:52,140 --> 00:04:55,860 Because that's obviously a big predicament in biochemistry. 93 00:04:55,860 --> 00:04:58,170 If reactions aren't favorable, why 94 00:04:58,170 --> 00:05:04,330 do they go far enough to be useful to us in metabolism? 95 00:05:04,330 --> 00:05:08,790 So that reaction would have a positive delta G. 96 00:05:08,790 --> 00:05:11,460 And then I also mentioned these two terms. 97 00:05:11,460 --> 00:05:15,590 Anabolic refers to the endergonic reactions. 98 00:05:15,590 --> 00:05:17,340 I don't know why you're doing this to me-- 99 00:05:17,340 --> 00:05:19,170 the endergonic reactions. 100 00:05:19,170 --> 00:05:23,730 And catabolic refers to the exergonic reactions. 101 00:05:23,730 --> 00:05:25,770 OK, then this last point-- 102 00:05:25,770 --> 00:05:28,020 I showed you this slide last time. 103 00:05:28,020 --> 00:05:30,360 But I think it was important to think about, 104 00:05:30,360 --> 00:05:32,460 why are enzymes so big? 105 00:05:32,460 --> 00:05:36,840 And I want to give one example of an additional genetic 106 00:05:36,840 --> 00:05:41,250 mutation that causes a human disorder, where I at least show 107 00:05:41,250 --> 00:05:44,160 you how the mutations are spread quite 108 00:05:44,160 --> 00:05:46,950 a distance from the reaction center 109 00:05:46,950 --> 00:05:50,610 to show you that all of that structure that you see 110 00:05:50,610 --> 00:05:55,020 in an enzyme as it interacts with a small substrate 111 00:05:55,020 --> 00:05:57,270 is critical for catalysis. 112 00:05:57,270 --> 00:06:00,640 So we see small substrates in each case. 113 00:06:00,640 --> 00:06:03,030 But we have this very large enzyme, 114 00:06:03,030 --> 00:06:07,890 which is many, many times its size, all engaged in catalysis. 115 00:06:07,890 --> 00:06:10,840 But what's the proof of that? 116 00:06:10,840 --> 00:06:12,330 So why are enzymes so big? 117 00:06:12,330 --> 00:06:15,780 So phenylketonuria is a human disorder. 118 00:06:15,780 --> 00:06:19,620 It's one of those disorders that neonates, 119 00:06:19,620 --> 00:06:22,070 brand newborns are tested for. 120 00:06:22,070 --> 00:06:25,410 They are checked for the genetic signal 121 00:06:25,410 --> 00:06:27,450 that shows that the protein will have 122 00:06:27,450 --> 00:06:29,640 mutations in its structure. 123 00:06:29,640 --> 00:06:34,080 And there are many mutations associated with a defect 124 00:06:34,080 --> 00:06:35,820 in this particular protein. 125 00:06:35,820 --> 00:06:37,950 And the protein that I'm talking about 126 00:06:37,950 --> 00:06:40,560 is phenylalanine hydroxylase. 127 00:06:40,560 --> 00:06:43,860 So the disorder is related to defects 128 00:06:43,860 --> 00:06:45,600 in phenylalanine hydroxylase. 129 00:06:45,600 --> 00:06:47,370 Now what does that enzyme do? 130 00:06:47,370 --> 00:06:51,510 It takes phenylalanine and installs a hydroxyl group 131 00:06:51,510 --> 00:06:54,300 opposite to where it's attached to the amino acid. 132 00:06:54,300 --> 00:06:57,540 So this is the hydrophobic amino acid phenylalanine. 133 00:06:57,540 --> 00:07:00,360 And this is another one of the hydrophobic amino acids 134 00:07:00,360 --> 00:07:02,940 in a similar family that's tyrosine. 135 00:07:02,940 --> 00:07:07,080 And in fact, it's the precursor to dopamine physiologically. 136 00:07:07,080 --> 00:07:09,420 Now it turns out there can always 137 00:07:09,420 --> 00:07:11,470 be too much of a good thing. 138 00:07:11,470 --> 00:07:13,920 So if you have too much phenylalanine, 139 00:07:13,920 --> 00:07:17,100 it has to be converted to a different amino acid. 140 00:07:17,100 --> 00:07:19,410 Because the build up of phenylalanine 141 00:07:19,410 --> 00:07:22,590 gets to a certain stage where it is converted itself 142 00:07:22,590 --> 00:07:25,260 to a toxic byproduct that actually 143 00:07:25,260 --> 00:07:29,260 causes severe mental disorders and seizures. 144 00:07:29,260 --> 00:07:33,870 So the body needs to monitor the levels of phenylalanine. 145 00:07:33,870 --> 00:07:36,900 And at a certain stage, phenylalanine hydroxylase 146 00:07:36,900 --> 00:07:38,760 will convert it to tyrosine. 147 00:07:38,760 --> 00:07:41,100 So even though phenylalanine is essential, 148 00:07:41,100 --> 00:07:43,900 too much phenylalanine is a bad thing. 149 00:07:43,900 --> 00:07:48,630 So that enzyme is the one that is associated with defects-- 150 00:07:48,630 --> 00:07:49,940 with mutations. 151 00:07:49,940 --> 00:07:53,690 The lower the activity of the phenylalanine hydroxylase 152 00:07:53,690 --> 00:07:58,170 and end you up accumulating phenylalanine too high. 153 00:07:58,170 --> 00:08:02,010 And so the PAH regulates the clearance 154 00:08:02,010 --> 00:08:04,470 from the body converting it to tyrosine. 155 00:08:04,470 --> 00:08:08,970 So why-- you know, I told you I would give you some insight 156 00:08:08,970 --> 00:08:14,850 into how entire enzymes are in fact critical for cat lysis. 157 00:08:14,850 --> 00:08:18,030 So what I'm showing you on this a little movie is 158 00:08:18,030 --> 00:08:22,200 that the sites shown in magenta all around this protein, 159 00:08:22,200 --> 00:08:24,570 the active site would be where this big ball is. 160 00:08:24,570 --> 00:08:27,480 It's actually cofactor iron. 161 00:08:27,480 --> 00:08:30,900 But the sites that are involved in the reduction of activity 162 00:08:30,900 --> 00:08:34,710 of phenylalanine hydroxylase are way out on the protein, 163 00:08:34,710 --> 00:08:36,120 out on its perimeters. 164 00:08:36,120 --> 00:08:40,590 So this protein is about 49 angstroms, 165 00:08:40,590 --> 00:08:43,450 4.9 nanometers across. 166 00:08:43,450 --> 00:08:46,380 But the sites that cause a reduction in activity 167 00:08:46,380 --> 00:08:49,910 are a long way away, 10 angstroms longer, 168 00:08:49,910 --> 00:08:52,050 15 angstroms, 16. 169 00:08:52,050 --> 00:08:54,570 So it turns out that enzymes as catalysts 170 00:08:54,570 --> 00:08:57,540 don't just use the local environment right near where 171 00:08:57,540 --> 00:08:58,830 chemistry happens. 172 00:08:58,830 --> 00:09:03,630 The entire protein collaborates to make the changes happen 173 00:09:03,630 --> 00:09:04,950 in catalysis. 174 00:09:04,950 --> 00:09:07,380 So enzymes are big, because you're not just 175 00:09:07,380 --> 00:09:10,080 using this inner shell of functional groups 176 00:09:10,080 --> 00:09:11,460 where the substrate binds. 177 00:09:11,460 --> 00:09:15,330 You're actually using a lot of the dynamics of the enzyme 178 00:09:15,330 --> 00:09:17,520 to promote catalysis. 179 00:09:17,520 --> 00:09:21,000 And just this sort of visual shows you 180 00:09:21,000 --> 00:09:23,520 how far away things can be where they 181 00:09:23,520 --> 00:09:25,950 suppress the activity of a protein 182 00:09:25,950 --> 00:09:27,690 and make it a poorer catalyst. 183 00:09:27,690 --> 00:09:29,460 OK. 184 00:09:29,460 --> 00:09:34,430 So as I said, this is one of the disorders, 185 00:09:34,430 --> 00:09:37,860 the genetic mutations that is tested for at birth. 186 00:09:37,860 --> 00:09:40,770 If you have one of these set of mutations, 187 00:09:40,770 --> 00:09:44,700 you immediately have to be put on a diet that's 188 00:09:44,700 --> 00:09:47,730 low in phenylalanine, so you don't bombard your body 189 00:09:47,730 --> 00:09:53,550 with too much phenylalanine, not allowing the phenylalanine 190 00:09:53,550 --> 00:09:54,900 to build up too much. 191 00:09:54,900 --> 00:09:57,480 But I don't know if any of you have lately 192 00:09:57,480 --> 00:09:59,520 grabbed a can of Coca-Cola that's 193 00:09:59,520 --> 00:10:02,070 got aspartame as a sweetener. 194 00:10:02,070 --> 00:10:05,580 It turns out that sweetener, NutraSweet rather, 195 00:10:05,580 --> 00:10:07,810 is a dipeptide. 196 00:10:07,810 --> 00:10:08,580 See? 197 00:10:08,580 --> 00:10:10,800 But it contains phenylalanine. 198 00:10:10,800 --> 00:10:15,600 So if you drink a ton of diet drinks that include NutraSweet, 199 00:10:15,600 --> 00:10:17,910 you are actually bombing yourself 200 00:10:17,910 --> 00:10:20,440 with high levels of phenylalanine 201 00:10:20,440 --> 00:10:21,960 that the body can't deal with. 202 00:10:21,960 --> 00:10:24,150 So people who have phenylketonuria, 203 00:10:24,150 --> 00:10:28,440 i.e. a defect in that enzyme, shouldn't be drinking or using 204 00:10:28,440 --> 00:10:30,360 NutraSweet type sweeteners. 205 00:10:30,360 --> 00:10:32,310 Because they actually give you too much 206 00:10:32,310 --> 00:10:36,390 phenylalanine at once, that you can mitigate the levels of. 207 00:10:36,390 --> 00:10:40,050 So I want to just tell you about these genetic disorders. 208 00:10:40,050 --> 00:10:43,980 There's a fairly decent set that are tested for at birth. 209 00:10:43,980 --> 00:10:46,080 But the ones that are tested are for ones 210 00:10:46,080 --> 00:10:49,140 that you can make dietary modifications or lifestyle 211 00:10:49,140 --> 00:10:53,110 modifications and mitigate the symptoms. 212 00:10:53,110 --> 00:10:56,190 And so that's a very important thing to know. 213 00:10:56,190 --> 00:10:59,760 You're not tested for things you don't know how to fix, 214 00:10:59,760 --> 00:11:02,430 because that wouldn't be appropriate. 215 00:11:02,430 --> 00:11:06,770 All right, any questions about that? 216 00:11:06,770 --> 00:11:07,441 Yeah. 217 00:11:07,441 --> 00:11:10,312 STUDENT: [INAUDIBLE] 218 00:11:10,312 --> 00:11:10,937 PROFESSOR: Yes. 219 00:11:10,937 --> 00:11:12,340 STUDENT: [INAUDIBLE] 220 00:11:12,340 --> 00:11:14,890 PROFESSOR: Oh, you know, that was me being clunky with-- 221 00:11:14,890 --> 00:11:16,694 of course you guys notice everything. 222 00:11:19,420 --> 00:11:21,133 This morning, I was making-- 223 00:11:21,133 --> 00:11:22,300 all right, let's go forward. 224 00:11:22,300 --> 00:11:25,600 One, two, and that and that. 225 00:11:25,600 --> 00:11:27,370 I know exactly what you're talking about. 226 00:11:27,370 --> 00:11:30,100 This little curb down, yeah that's 227 00:11:30,100 --> 00:11:33,520 me shaking when I'm doing the ChemDraw drawing. 228 00:11:33,520 --> 00:11:35,350 It should be flat. 229 00:11:35,350 --> 00:11:36,760 But thank you for noticing that. 230 00:11:36,760 --> 00:11:39,910 Just so that's not ambiguity, there should not be-- there 231 00:11:39,910 --> 00:11:42,280 could be, actually, a little dip when substrates bind 232 00:11:42,280 --> 00:11:42,850 to enzymes. 233 00:11:42,850 --> 00:11:44,630 But I didn't mean to imply it. 234 00:11:44,630 --> 00:11:45,730 OK, anything else? 235 00:11:49,590 --> 00:11:54,610 OK, so what I want to talk about now is the equilibrium problem. 236 00:11:54,610 --> 00:11:55,580 And what is that? 237 00:12:05,660 --> 00:12:16,560 So if we have reactions that are endergonic-- 238 00:12:16,560 --> 00:12:18,600 so we have one of these situations 239 00:12:18,600 --> 00:12:22,140 where we have a substrate going to a product that's 240 00:12:22,140 --> 00:12:22,845 higher energy. 241 00:12:25,360 --> 00:12:29,100 What that means is, at equilibrium between substrate 242 00:12:29,100 --> 00:12:32,820 and product, which is defined by the delta G, 243 00:12:32,820 --> 00:12:36,990 you have substrate going to product. 244 00:12:36,990 --> 00:12:40,120 But mostly, you've got a lot of substrate 245 00:12:40,120 --> 00:12:42,010 there, which is the amount of each 246 00:12:42,010 --> 00:12:44,890 of these is defined by this energy difference. 247 00:12:44,890 --> 00:12:45,700 OK. 248 00:12:45,700 --> 00:12:49,310 So how do we survive with these kinds of transformations 249 00:12:49,310 --> 00:12:52,780 when we really want the flux for an enzyme 250 00:12:52,780 --> 00:12:55,780 to be in the forward direction? 251 00:12:55,780 --> 00:12:59,450 Because if we need the product, we need to move things forward. 252 00:12:59,450 --> 00:13:02,680 So nature deals with this by coupling reactions 253 00:13:02,680 --> 00:13:04,220 to other reactions. 254 00:13:04,220 --> 00:13:07,510 So it finds ways around the equilibrium problem 255 00:13:07,510 --> 00:13:10,810 by, for example, putting a series of reactions. 256 00:13:10,810 --> 00:13:16,330 For example, let's go from A to B to C. 257 00:13:16,330 --> 00:13:21,940 So these are three intermediates catalyzed by enzyme 1, 258 00:13:21,940 --> 00:13:23,210 enzyme 2. 259 00:13:23,210 --> 00:13:24,250 OK. 260 00:13:24,250 --> 00:13:28,360 And let's just say this has an unfavorable delta G. 261 00:13:28,360 --> 00:13:35,910 So we don't make-- we have a lot of A. We have very little B. 262 00:13:35,910 --> 00:13:37,440 And then what happens? 263 00:13:37,440 --> 00:13:38,940 How are we going to-- and then let's 264 00:13:38,940 --> 00:13:43,710 just say, for example, this reaction is favorable. 265 00:13:43,710 --> 00:13:44,490 So let's see. 266 00:13:44,490 --> 00:13:47,950 The delta G here is positive. 267 00:13:47,950 --> 00:13:51,690 The delta G here is negative. 268 00:13:51,690 --> 00:13:55,030 So by plus VE, I mean positive and negative. 269 00:13:55,030 --> 00:13:59,500 So this is a favorable reaction, whereas this 270 00:13:59,500 --> 00:14:01,630 is an unfavorable reaction. 271 00:14:01,630 --> 00:14:04,990 How does putting two reactions adjacent 272 00:14:04,990 --> 00:14:07,900 to each other happening on the same substrate 273 00:14:07,900 --> 00:14:10,210 and moving through help that situation? 274 00:14:12,830 --> 00:14:13,910 Yeah. 275 00:14:13,910 --> 00:14:18,658 STUDENT: [INAUDIBLE] 276 00:14:18,658 --> 00:14:19,450 PROFESSOR: Perfect. 277 00:14:19,450 --> 00:14:24,490 So the answer here is that, as you take whatever B you have 278 00:14:24,490 --> 00:14:28,140 and turn it into C, A has to-- 279 00:14:28,140 --> 00:14:32,650 A1 has to make more B. So you solve the equilibrium problem 280 00:14:32,650 --> 00:14:35,650 in that way to a certain extent by just opening the tap 281 00:14:35,650 --> 00:14:37,430 at the other end of the series. 282 00:14:37,430 --> 00:14:40,750 And nature organizes a ton of reactions in sequential 283 00:14:40,750 --> 00:14:44,570 pathways to get around these kinds of problems. 284 00:14:44,570 --> 00:14:47,400 So this is done by coupling reactions. 285 00:14:53,700 --> 00:14:55,720 And so there are some reactions that 286 00:14:55,720 --> 00:14:59,380 are highly favorable, highly exothermic, 287 00:14:59,380 --> 00:15:02,260 where you can really sort of guarantee flux 288 00:15:02,260 --> 00:15:03,580 through that enzyme. 289 00:15:03,580 --> 00:15:07,800 A lot of these enzymes are ATP dependent. 290 00:15:10,890 --> 00:15:12,930 They use and burn ATP. 291 00:15:12,930 --> 00:15:14,850 So you get a lot of energy out. 292 00:15:14,850 --> 00:15:17,640 And they drive the flux through enzyme one, 293 00:15:17,640 --> 00:15:20,890 by enzyme to being an exergonic reaction, 294 00:15:20,890 --> 00:15:22,590 while the enzyme one is and endergonic. 295 00:15:22,590 --> 00:15:24,240 So flux is guaranteed. 296 00:15:24,240 --> 00:15:28,620 And a lot of pathways sort of set up to be in this way 297 00:15:28,620 --> 00:15:31,200 with this coupling of the chemistries. 298 00:15:33,900 --> 00:15:35,530 What else? 299 00:15:35,530 --> 00:15:43,590 So what we find is that enzymes, first of all, 300 00:15:43,590 --> 00:15:50,890 work in pathways where they are co-located in certain places. 301 00:15:50,890 --> 00:15:57,810 They may be, for example, co-localized 302 00:15:57,810 --> 00:16:00,030 to certain organelles in a human cell. 303 00:16:00,030 --> 00:16:03,090 They may be co-localized in the mitochondria 304 00:16:03,090 --> 00:16:07,390 or in some organelle. 305 00:16:07,390 --> 00:16:10,260 And we'll talk more about organelles and mitochondria 306 00:16:10,260 --> 00:16:11,390 later. 307 00:16:11,390 --> 00:16:14,435 They could be co-localized at a membrane. 308 00:16:17,870 --> 00:16:20,540 And so you ensure that the enzymes are together 309 00:16:20,540 --> 00:16:22,640 by putting them in the same place. 310 00:16:22,640 --> 00:16:25,520 And then nature also evolves ways 311 00:16:25,520 --> 00:16:28,760 where the enzymes physically interact with each other, 312 00:16:28,760 --> 00:16:31,670 either covalently or non-covalently. 313 00:16:31,670 --> 00:16:35,720 So they could be associated in the pathway 314 00:16:35,720 --> 00:16:39,320 by some kind of non-covalent interaction. 315 00:16:39,320 --> 00:16:48,390 Or you may actually link enzymes to make them single species. 316 00:16:48,390 --> 00:16:53,820 So if this is enzyme one and this is enzyme two, 317 00:16:53,820 --> 00:17:00,840 here you have an enzyme one, enzyme two single 318 00:17:00,840 --> 00:17:04,613 long polypeptide chain that has two domains. 319 00:17:04,613 --> 00:17:06,780 They can't get away from each other, because they're 320 00:17:06,780 --> 00:17:08,400 joined covalently. 321 00:17:08,400 --> 00:17:10,619 And they catalyze sequential reactions. 322 00:17:10,619 --> 00:17:13,410 This just doesn't happen with just three enzymes. 323 00:17:13,410 --> 00:17:15,869 It can happen with 10 enzymes or more. 324 00:17:15,869 --> 00:17:18,990 So there are very clever ways to ensure the flux 325 00:17:18,990 --> 00:17:21,990 occurs through pathways. 326 00:17:21,990 --> 00:17:22,490 OK. 327 00:17:26,609 --> 00:17:30,210 But don't forget, all along, that each of these enzymes 328 00:17:30,210 --> 00:17:32,730 is responsible for a single transformation. 329 00:17:32,730 --> 00:17:34,080 That's important. 330 00:17:34,080 --> 00:17:37,470 There's another phenomenon that having flux through pathways 331 00:17:37,470 --> 00:17:44,130 is very useful for, is to deal with toxic intermediates. 332 00:17:49,980 --> 00:17:52,390 Because that makes it very advantageous, 333 00:17:52,390 --> 00:17:54,920 again, to couple reactions. 334 00:17:54,920 --> 00:17:59,205 So let's say product B is toxic. 335 00:18:02,230 --> 00:18:04,100 We don't want it hanging around much. 336 00:18:04,100 --> 00:18:07,500 We don't want it released from an enzyme to go do damage 337 00:18:07,500 --> 00:18:09,160 somewhere in the cell. 338 00:18:09,160 --> 00:18:11,760 So having flux through a pathway basically 339 00:18:11,760 --> 00:18:14,160 ensures the B never gets out of the game. 340 00:18:14,160 --> 00:18:16,500 It just goes straight to enzyme two. 341 00:18:16,500 --> 00:18:20,250 So that's another physical advantage of those processes 342 00:18:20,250 --> 00:18:22,290 being linked together. 343 00:18:22,290 --> 00:18:28,050 And finally, the process also ensures a very nice opportunity 344 00:18:28,050 --> 00:18:29,760 to do regulation. 345 00:18:29,760 --> 00:18:32,490 So here we on this slide, I show you 346 00:18:32,490 --> 00:18:35,700 this sort of mega mess of metabolic pathways 347 00:18:35,700 --> 00:18:36,450 in physiology. 348 00:18:36,450 --> 00:18:39,090 That there would be the Krebs cycle. 349 00:18:39,090 --> 00:18:42,570 But all the metabolic pathways that are all interlinked. 350 00:18:42,570 --> 00:18:45,720 And many of these pathways will be co-locali-- 351 00:18:45,720 --> 00:18:49,800 steps in these pathways will be co-localized as clusters. 352 00:18:49,800 --> 00:18:55,050 And so that deal tells you how we can solve the equilibrium 353 00:18:55,050 --> 00:18:57,510 problem by linking enzymes-- 354 00:18:57,510 --> 00:18:59,400 the flux through pathways. 355 00:18:59,400 --> 00:19:03,240 And one of the best examples is in aerobic glycolysis, 356 00:19:03,240 --> 00:19:04,890 where in the early steps, they're 357 00:19:04,890 --> 00:19:07,110 not energetically favorable. 358 00:19:07,110 --> 00:19:11,220 You use ATP to start to break down glucose. 359 00:19:11,220 --> 00:19:13,110 Then you get to a certain intermediate 360 00:19:13,110 --> 00:19:16,530 where it's conversion to a smaller molecule 361 00:19:16,530 --> 00:19:19,780 generates ATP with very favorable reactions. 362 00:19:19,780 --> 00:19:24,360 So glycolysis is a really great example of this. 363 00:19:24,360 --> 00:19:27,210 Now the other thing that I just want to describe to you 364 00:19:27,210 --> 00:19:32,060 is the issue of feedback. 365 00:19:32,060 --> 00:19:36,920 And I've described this here on this slide. 366 00:19:36,920 --> 00:19:39,010 And so we'll talk about it on this slide. 367 00:19:39,010 --> 00:19:42,330 So if we are working with a pathway 368 00:19:42,330 --> 00:19:47,340 that goes through multiple steps to make an end product, five 369 00:19:47,340 --> 00:19:49,420 steps, three steps or whatever. 370 00:19:49,420 --> 00:19:50,990 And you've made too much of that. 371 00:19:50,990 --> 00:19:52,740 You've already made a lot of that product. 372 00:19:52,740 --> 00:19:54,690 And you don't need anymore. 373 00:19:54,690 --> 00:19:59,130 Nature also has in place a regulatory mechanism 374 00:19:59,130 --> 00:20:02,310 to feedback and stop flux through the pathway. 375 00:20:02,310 --> 00:20:04,350 You don't just stop all the enzymes. 376 00:20:04,350 --> 00:20:07,510 You find a way to stop the first enzyme. 377 00:20:07,510 --> 00:20:12,150 So this is a very important paradigm in biochemistry. 378 00:20:12,150 --> 00:20:14,400 And that's called negative feedback. 379 00:20:14,400 --> 00:20:17,910 So I'm showing you it here just in a very simple cartoon 380 00:20:17,910 --> 00:20:21,630 form in the isoleucine biosynthesis pathway. 381 00:20:21,630 --> 00:20:24,150 That's one of the hydrophobic amino acids. 382 00:20:24,150 --> 00:20:27,120 This is an intermediate that is on its way 383 00:20:27,120 --> 00:20:31,530 from this amino acid that is polar but not charged, 384 00:20:31,530 --> 00:20:32,400 threonine. 385 00:20:32,400 --> 00:20:35,280 So threonine gets converted to isoleucine. 386 00:20:35,280 --> 00:20:37,950 We need threonine to make isoleucine. 387 00:20:37,950 --> 00:20:40,280 But once we got a lot of isoleucine, 388 00:20:40,280 --> 00:20:45,510 it binds to the very first enzyme in the pathway and acts 389 00:20:45,510 --> 00:20:49,860 as an allosteric regulator that dampens activity. 390 00:20:49,860 --> 00:20:52,050 So in this case, I just want to point out 391 00:20:52,050 --> 00:20:56,490 to you that I'm showing a very common way we notate things. 392 00:20:56,490 --> 00:21:00,840 When we are talking about inhibiting a reaction, 393 00:21:00,840 --> 00:21:02,160 we draw it like this. 394 00:21:06,700 --> 00:21:10,060 We align and then align to the so the arrow, 395 00:21:10,060 --> 00:21:12,800 see which means you've stopped the activity. 396 00:21:12,800 --> 00:21:14,750 So you'll see this again and again. 397 00:21:14,750 --> 00:21:17,300 You're going to see it a lot in signaling pathways, 398 00:21:17,300 --> 00:21:19,190 because things often feedback. 399 00:21:19,190 --> 00:21:22,640 So another thing that nature ensures, in addition 400 00:21:22,640 --> 00:21:24,590 to not building up toxic products 401 00:21:24,590 --> 00:21:26,720 and dealing with equilibria, is that you 402 00:21:26,720 --> 00:21:29,360 don't want a ton of enzymes working to make something 403 00:21:29,360 --> 00:21:30,920 you don't need anymore. 404 00:21:30,920 --> 00:21:33,470 So you might as well take the end product 405 00:21:33,470 --> 00:21:35,870 and use it to stop the first enzyme. 406 00:21:35,870 --> 00:21:38,940 As that in product becomes scarce, 407 00:21:38,940 --> 00:21:40,910 it dissociates from the first enzyme. 408 00:21:40,910 --> 00:21:43,170 And it turns the pathway back on again. 409 00:21:43,170 --> 00:21:47,350 And I think that's a really neat way of making that happen. 410 00:21:47,350 --> 00:21:49,640 And also, in these cases, the enzymes 411 00:21:49,640 --> 00:21:51,200 have to be clustered as a group. 412 00:21:51,200 --> 00:21:54,080 Because you wouldn't get those local concentrations 413 00:21:54,080 --> 00:21:57,790 to be so advantageous if the enzymes weren't co-localized. 414 00:21:57,790 --> 00:21:59,600 So does that make sense? 415 00:21:59,600 --> 00:22:03,050 If they weren't in a really near location, the enzyme that 416 00:22:03,050 --> 00:22:06,230 present produces isoleucine, that isoleucine 417 00:22:06,230 --> 00:22:09,140 couldn't bind back to the first enzyme in the pathway 418 00:22:09,140 --> 00:22:12,290 if they were in different compartments of the cell. 419 00:22:12,290 --> 00:22:16,050 OK, everyone good with that? 420 00:22:16,050 --> 00:22:17,050 Good. 421 00:22:17,050 --> 00:22:19,080 All right. 422 00:22:19,080 --> 00:22:23,020 OK, so now we are moving on to carbohydrates. 423 00:22:41,340 --> 00:22:44,490 It's a pretty strange word, carbohydrate. 424 00:22:44,490 --> 00:22:47,360 But actually, it relates to early findings 425 00:22:47,360 --> 00:22:51,300 that glucose is a carbohydrate. 426 00:22:51,300 --> 00:22:53,820 And its molecular formula is C6H12O6. 427 00:22:56,850 --> 00:23:00,790 So they called it a hydrate of carbon 428 00:23:00,790 --> 00:23:04,060 before when they knew the elemental composition but they 429 00:23:04,060 --> 00:23:05,980 didn't know anything about the structure. 430 00:23:05,980 --> 00:23:09,610 There's a lot of carbohydrates that don't obey this rule. 431 00:23:09,610 --> 00:23:13,760 But that's where the name comes from, a hydrate of carbon. 432 00:23:13,760 --> 00:23:17,170 All right now carbohydrates account 433 00:23:17,170 --> 00:23:20,540 for-- what did I have here? 434 00:23:20,540 --> 00:23:25,970 25% of the mass of macromolecules, so 435 00:23:25,970 --> 00:23:27,470 a good amount. 436 00:23:27,470 --> 00:23:30,170 They are very, very important, carbohydrates 437 00:23:30,170 --> 00:23:31,700 in central metabolism. 438 00:23:31,700 --> 00:23:35,450 We use carbohydrates as a source of energy. 439 00:23:35,450 --> 00:23:37,880 But also, carbohydrates are a part 440 00:23:37,880 --> 00:23:42,320 of storage of energy in the form of polymeric structures, 441 00:23:42,320 --> 00:23:43,770 that I'll describe to you. 442 00:23:43,770 --> 00:23:47,210 There are different ones in plants and in humans. 443 00:23:47,210 --> 00:23:51,620 One is glycogen. One is cellulose. 444 00:23:51,620 --> 00:23:55,280 But carbohydrates have an increasingly important role 445 00:23:55,280 --> 00:23:58,580 in the extracellular matrix in these polymers that 446 00:23:58,580 --> 00:24:02,990 are wrapped around your cells and also as signaling entities 447 00:24:02,990 --> 00:24:05,460 both inside and outside the cell. 448 00:24:05,460 --> 00:24:07,370 So we used to think of carbohydrates 449 00:24:07,370 --> 00:24:10,190 and straight away connect this with metabolism. 450 00:24:10,190 --> 00:24:12,710 But the story is far greater than that. 451 00:24:12,710 --> 00:24:14,720 And I'll try to explain to you why. 452 00:24:14,720 --> 00:24:17,180 And it's because of the richness of functional groups 453 00:24:17,180 --> 00:24:18,830 in a carbohydrate. 454 00:24:18,830 --> 00:24:24,910 So the simplest carbohydrate, before I go up there, 455 00:24:24,910 --> 00:24:27,280 is a three carbon molecule. 456 00:24:30,810 --> 00:24:33,840 This would actually be called glyceraldehyde. 457 00:24:33,840 --> 00:24:36,220 But don't worry about that other name for it. 458 00:24:36,220 --> 00:24:39,730 It's a three carbon carbohydrate. 459 00:24:45,190 --> 00:24:50,120 And this molecule would be called a triose. 460 00:24:50,120 --> 00:24:53,345 So we've got a couple of new-- a new suffix. 461 00:24:56,680 --> 00:24:59,530 Because anything that is a carbohydrate 462 00:24:59,530 --> 00:25:02,140 ends with the suffix "ose," not to be 463 00:25:02,140 --> 00:25:05,840 confused with the suffix "ase," which is an enzyme. 464 00:25:05,840 --> 00:25:08,310 So look carefully whether it's an "a" or "o," because it's 465 00:25:08,310 --> 00:25:10,990 the difference between a big protein that catalyzes 466 00:25:10,990 --> 00:25:13,270 a reaction and a carbohydrate. 467 00:25:13,270 --> 00:25:16,090 So a triose would be a carbohydrate 468 00:25:16,090 --> 00:25:17,740 with three carbons. 469 00:25:17,740 --> 00:25:20,070 They have an aldehyde. 470 00:25:20,070 --> 00:25:23,020 Or let's just say they have a carbonyl functionality. 471 00:25:25,720 --> 00:25:31,570 So remember, there would be lone pair electrons on those OHs, 472 00:25:31,570 --> 00:25:33,490 similarly on these. 473 00:25:33,490 --> 00:25:36,700 And remember, that each of these vertices 474 00:25:36,700 --> 00:25:39,660 corresponds to a carbon. 475 00:25:39,660 --> 00:25:44,620 It's some-- the way you recognize carbohydrates is most 476 00:25:44,620 --> 00:25:45,910 commonly-- 477 00:25:45,910 --> 00:25:53,020 is that they are rich in carbon dash OH 478 00:25:53,020 --> 00:25:54,818 bonds, which are hydroxyls. 479 00:25:57,746 --> 00:26:00,610 Which makes them polar molecules, 480 00:26:00,610 --> 00:26:04,630 likely to be highly solvated in water and very different 481 00:26:04,630 --> 00:26:08,320 for from the compounds that are rich in just CH bonds that 482 00:26:08,320 --> 00:26:10,460 don't have such opportunities. 483 00:26:10,460 --> 00:26:13,660 So if you see a molecule and it's got a bunch of CHs 484 00:26:13,660 --> 00:26:16,440 but not a bunch of OHs, it's probably a lipid. 485 00:26:16,440 --> 00:26:19,810 If you see a compound that's rich in OHs, 486 00:26:19,810 --> 00:26:22,420 it's likely to be a carbohydrate. 487 00:26:22,420 --> 00:26:24,790 The story gets a little bit more interesting 488 00:26:24,790 --> 00:26:28,060 as we move up to some of the different carbohydrates, which 489 00:26:28,060 --> 00:26:29,560 I've shown you there on that screen. 490 00:26:29,560 --> 00:26:32,110 And I'm going to go forward to talk about those. 491 00:26:32,110 --> 00:26:37,240 Because this triose is important in primary metabolism. 492 00:26:37,240 --> 00:26:40,030 We break down carbon carbohydrates 493 00:26:40,030 --> 00:26:44,740 that have six sugars to small carbohydrates that have three-- 494 00:26:44,740 --> 00:26:46,600 excuse me, carbohydrates that have 495 00:26:46,600 --> 00:26:49,850 six carbons to carbohydrates that have three carbons. 496 00:26:49,850 --> 00:26:52,990 And that's where these three carbon entities crop up. 497 00:26:52,990 --> 00:26:58,810 But I want to focus you in on two sets of carbohydrates, 498 00:26:58,810 --> 00:27:00,860 the hexoses and the pentoses. 499 00:27:04,750 --> 00:27:09,010 So we immediately know they're carbohydrates, right? 500 00:27:09,010 --> 00:27:10,600 "Ose." 501 00:27:10,600 --> 00:27:15,110 The hexoses obviously have six carbons. 502 00:27:15,110 --> 00:27:18,170 And the pentoses have five carbons. 503 00:27:18,170 --> 00:27:21,050 And these are the most important of the carbohydrates. 504 00:27:21,050 --> 00:27:23,810 Yes, there are carbohydrates with four carbons. 505 00:27:23,810 --> 00:27:27,230 And then there were ones with seven, eight, nine carbons. 506 00:27:27,230 --> 00:27:28,730 But these are the ones will totally 507 00:27:28,730 --> 00:27:31,550 focus on in 7016, because these are 508 00:27:31,550 --> 00:27:34,550 very important in different biopolymers. 509 00:27:34,550 --> 00:27:39,220 And the hexoses are important components, for example, 510 00:27:39,220 --> 00:27:50,570 of cellulose and glycogen. But where are the pentose carbons? 511 00:27:50,570 --> 00:27:53,320 And why are they so important? 512 00:27:53,320 --> 00:27:55,962 Actually, I need to draw this is its straight chain version. 513 00:27:55,962 --> 00:27:57,170 Because I'll drive you crazy. 514 00:28:07,580 --> 00:28:11,420 So this sugar here is a pentose, one, two, three, four, 515 00:28:11,420 --> 00:28:15,890 five carbons, a bunch of OHs, aldehyde at one end. 516 00:28:15,890 --> 00:28:20,002 Commonly, carbohydrates will fold up into a cyclic structure 517 00:28:20,002 --> 00:28:20,960 through an equilibrium. 518 00:28:20,960 --> 00:28:23,660 I won't worry you too much with the chemistry. 519 00:28:23,660 --> 00:28:28,240 But I'm just going to show you that structure. 520 00:28:28,240 --> 00:28:30,600 It looks like this, a five-membered ring. 521 00:28:33,370 --> 00:28:37,260 The interconversion of these two is an equilibrium process. 522 00:28:37,260 --> 00:28:41,860 And those carbohydrates are incredibly important where? 523 00:28:41,860 --> 00:28:44,930 Yeah, nucleic acids. 524 00:28:44,930 --> 00:28:48,880 So your phosphodiester backbone is 525 00:28:48,880 --> 00:28:54,820 attached to sugars that are attached a bit to purines 526 00:28:54,820 --> 00:28:55,510 and pyrimidines. 527 00:28:55,510 --> 00:28:57,520 And we'll see those structures later. 528 00:28:57,520 --> 00:29:02,050 But an absolutely essential feature of that polymer 529 00:29:02,050 --> 00:29:04,960 is the five-membered ring carbohydrates 530 00:29:04,960 --> 00:29:11,770 that are known as ribose, which is what that guy is, 531 00:29:11,770 --> 00:29:21,160 and two deoxyribose, where one of the hydroxyls 532 00:29:21,160 --> 00:29:23,840 is actually a hydrogen. It's not a hydroxyl. 533 00:29:23,840 --> 00:29:27,070 And it's this one. 534 00:29:27,070 --> 00:29:31,140 So instead of being an OH, it's an H. 535 00:29:31,140 --> 00:29:32,700 And we number carbohydrates. 536 00:29:32,700 --> 00:29:34,860 And I'll reinforce this much more 537 00:29:34,860 --> 00:29:38,370 when we talk about carbohydrate, about nucleic acids. 538 00:29:38,370 --> 00:29:39,890 There's a numbering system. 539 00:29:39,890 --> 00:29:43,230 So two deoxyribose is in your DNA. 540 00:29:46,920 --> 00:29:51,980 And ribose itself is in your RNA. 541 00:29:51,980 --> 00:29:54,835 OK, so obviously, we need to worry about carbohydrates 542 00:29:54,835 --> 00:29:56,210 and learn a little bit about them 543 00:29:56,210 --> 00:29:58,260 based on that key criterion. 544 00:29:58,260 --> 00:30:02,330 OK, let's move now to the hexoses. 545 00:30:02,330 --> 00:30:05,660 I'm not going to make you keep drawing hexoses and things. 546 00:30:05,660 --> 00:30:08,090 I'm going to just tell you a little bit about them 547 00:30:08,090 --> 00:30:10,220 with respect to their structures. 548 00:30:10,220 --> 00:30:16,070 So I've shown you on the board the cyclic form of a pentose. 549 00:30:16,070 --> 00:30:18,352 This is the linear form and the cyclic form. 550 00:30:18,352 --> 00:30:19,310 Let me write that down. 551 00:30:25,060 --> 00:30:28,450 And by the way, in your DNA, it's always in the cyclic form. 552 00:30:28,450 --> 00:30:30,310 It's not in the linear form. 553 00:30:30,310 --> 00:30:34,720 And the hexoses also have a linear and a cyclic form. 554 00:30:34,720 --> 00:30:38,320 And I show you that equilibrium for glucose. 555 00:30:38,320 --> 00:30:40,210 You see six carbons. 556 00:30:40,210 --> 00:30:41,530 I've got them numbered. 557 00:30:41,530 --> 00:30:45,220 And they form favorably into the six-membered ring. 558 00:30:45,220 --> 00:30:47,470 This is the cyclic form of glucose. 559 00:30:47,470 --> 00:30:49,870 This is the linear form of glucose. 560 00:30:49,870 --> 00:30:53,080 When glucose associates into polymers, 561 00:30:53,080 --> 00:30:56,890 it becomes these things like cellulose or glycogen. 562 00:30:56,890 --> 00:30:59,920 And it depends a lot on the linkages in those polymers 563 00:30:59,920 --> 00:31:02,000 to define which one it is. 564 00:31:02,000 --> 00:31:07,120 Now, as I mentioned, carbohydrates aren't always 565 00:31:07,120 --> 00:31:09,430 just a series of OH groups. 566 00:31:09,430 --> 00:31:12,518 There's sometimes other functionality. 567 00:31:12,518 --> 00:31:14,185 So I'm just going to quickly draw those. 568 00:31:17,030 --> 00:31:22,310 And if you've got them on your handouts, 569 00:31:22,310 --> 00:31:24,640 you can play along with me here. 570 00:31:29,230 --> 00:31:36,010 So sometimes, there's an NH2 there. 571 00:31:36,010 --> 00:31:39,850 That's called glucose amine, very creatively. 572 00:31:39,850 --> 00:31:46,840 Sometimes that NH2 is converted to an amide, 573 00:31:46,840 --> 00:31:48,430 like that bond in a peptide. 574 00:31:48,430 --> 00:31:51,310 So it's glucose amide. 575 00:31:51,310 --> 00:31:54,640 And sometimes-- so you can draw these on your handout, 576 00:31:54,640 --> 00:31:57,070 because the six-membered rings are there. 577 00:31:57,070 --> 00:31:59,790 This stays as an OH. 578 00:31:59,790 --> 00:32:04,600 But this OH here is at a different oxidation state. 579 00:32:04,600 --> 00:32:06,310 Don't worry about that terminology. 580 00:32:06,310 --> 00:32:09,920 But what's important, it's glucuronic acid. 581 00:32:09,920 --> 00:32:13,690 So it can be negatively charged, positively charged, neutral. 582 00:32:13,690 --> 00:32:17,380 So there are variations on a lot of our hexoses, 583 00:32:17,380 --> 00:32:20,380 basically meaning this carbohydrate molecular formula 584 00:32:20,380 --> 00:32:21,340 doesn't work anymore. 585 00:32:21,340 --> 00:32:23,290 But the term has stuck. 586 00:32:23,290 --> 00:32:26,920 So there's quite a variety of different carbohydrates 587 00:32:26,920 --> 00:32:28,510 with slight differences. 588 00:32:28,510 --> 00:32:31,840 And the intriguing thing is that the carbohydrates 589 00:32:31,840 --> 00:32:35,710 that you and I use in all of our physiologic processes 590 00:32:35,710 --> 00:32:37,780 are much simpler than the carbohydrates 591 00:32:37,780 --> 00:32:39,450 that bacteria use. 592 00:32:39,450 --> 00:32:42,250 There is an expansion of like 10 to the 2 or 10 593 00:32:42,250 --> 00:32:46,690 to the 3 in the variety of sugars that bacteria use. 594 00:32:46,690 --> 00:32:49,280 And that's definitely a story for another day. 595 00:32:49,280 --> 00:32:53,170 So let me now move on to thinking about carbohydrates 596 00:32:53,170 --> 00:32:56,770 not as the monomers that you metabolize, 597 00:32:56,770 --> 00:32:58,720 but rather as the polymers that are 598 00:32:58,720 --> 00:33:01,930 involved in many other different types of processes. 599 00:33:01,930 --> 00:33:03,760 And when we think about the polymers, 600 00:33:03,760 --> 00:33:06,850 we want to think about how their polymers differ 601 00:33:06,850 --> 00:33:11,290 from the polymers of nucleic acids or proteins. 602 00:33:11,290 --> 00:33:14,260 Because this will tell you why carbohydrates 603 00:33:14,260 --> 00:33:16,630 are so complicated. 604 00:33:16,630 --> 00:33:21,190 When you take a bunch of amino acids and make a polymer, 605 00:33:21,190 --> 00:33:23,630 it's a linear polymer. 606 00:33:23,630 --> 00:33:25,940 Every unit is joined to the next by a name. 607 00:33:25,940 --> 00:33:27,330 There's no branching there. 608 00:33:27,330 --> 00:33:28,990 It's just a linear polymer. 609 00:33:28,990 --> 00:33:31,960 So the diversity is not enormous. 610 00:33:31,960 --> 00:33:33,190 Or-- it's pretty enormous. 611 00:33:33,190 --> 00:33:34,960 But it's not as big as it could be 612 00:33:34,960 --> 00:33:38,380 if it were a branch polymer with different types of side chains. 613 00:33:38,380 --> 00:33:42,740 We will see next week that the polymers of the nucleic acids-- 614 00:33:42,740 --> 00:33:44,130 here's the basic structure. 615 00:33:44,130 --> 00:33:45,910 There's the ribose, by the way. 616 00:33:45,910 --> 00:33:49,770 The R could be an OH or an H attached to a base of purine 617 00:33:49,770 --> 00:33:52,070 or pyrimidine-- you don't need to know that yet; 618 00:33:52,070 --> 00:33:53,260 you'll know it next week-- 619 00:33:53,260 --> 00:33:54,730 and then to a phosphate. 620 00:33:54,730 --> 00:33:58,398 But those again, are linear polymers. 621 00:33:58,398 --> 00:33:59,440 You don't have branching. 622 00:33:59,440 --> 00:34:02,020 You just have a single continuous chain. 623 00:34:02,020 --> 00:34:04,330 The crazy thing about sugars is they can 624 00:34:04,330 --> 00:34:06,680 branch from any of those OHs. 625 00:34:06,680 --> 00:34:11,500 So there's much more diversity of structure and function 626 00:34:11,500 --> 00:34:13,750 wrapped in the carbohydrates, which makes 627 00:34:13,750 --> 00:34:16,070 them real trouble to study. 628 00:34:16,070 --> 00:34:20,270 OK, I want to now introduce you to another feature. 629 00:34:20,270 --> 00:34:22,659 The other thing is, when we join amino acids 630 00:34:22,659 --> 00:34:27,190 or we join nucleic acid building blocks, nucleosides, 631 00:34:27,190 --> 00:34:30,130 there's no difference in the shapes that we can form. 632 00:34:30,130 --> 00:34:31,870 We don't have variety there. 633 00:34:31,870 --> 00:34:35,679 But in sugars, we can make different kinds of linkages 634 00:34:35,679 --> 00:34:39,909 depending on how two OH groups in a sugar are joined. 635 00:34:39,909 --> 00:34:43,520 So for example, if you join two glucoses, 636 00:34:43,520 --> 00:34:46,790 in this kind of linkage, that would give you maltose. 637 00:34:46,790 --> 00:34:50,837 But if you join two glucoses in that kind of linkage, 638 00:34:50,837 --> 00:34:51,920 it would give you lactose. 639 00:34:51,920 --> 00:34:54,139 And those are different compounds. 640 00:34:54,139 --> 00:34:58,060 They serve different types of physiologic roles. 641 00:34:58,060 --> 00:35:02,750 And there are enzymes that will make these bonds and then 642 00:35:02,750 --> 00:35:05,850 enzymes that will break these bonds. 643 00:35:05,850 --> 00:35:11,040 There is a common disorder that people have as they grow older. 644 00:35:11,040 --> 00:35:16,190 The enzyme that breaks the lactose bond the gets 645 00:35:16,190 --> 00:35:16,790 turned off. 646 00:35:16,790 --> 00:35:18,210 It doesn't work anymore. 647 00:35:18,210 --> 00:35:20,510 And that's the enzyme, lactose. 648 00:35:20,510 --> 00:35:24,710 So when people are intolerant to sugars-- 649 00:35:24,710 --> 00:35:27,170 lactose is the sugar in milk. 650 00:35:27,170 --> 00:35:29,150 And they can't digest dairy products. 651 00:35:29,150 --> 00:35:31,460 Because lactase doesn't work anymore. 652 00:35:31,460 --> 00:35:32,690 Or you can take supplements. 653 00:35:32,690 --> 00:35:36,230 So that's how that relates to physiology. 654 00:35:36,230 --> 00:35:38,990 The reaction between two glucoses 655 00:35:38,990 --> 00:35:42,590 to make the disaccharide is actually a condensation. 656 00:35:42,590 --> 00:35:45,470 Because when you join that bond, you kick out 657 00:35:45,470 --> 00:35:47,750 water as a side product. 658 00:35:47,750 --> 00:35:51,360 Or when you break that bond, you release water. 659 00:35:51,360 --> 00:35:54,500 So this is another one of the condensation reactions. 660 00:35:54,500 --> 00:35:56,690 So underline that on the slide. 661 00:35:56,690 --> 00:35:58,940 Because condensation means a reaction 662 00:35:58,940 --> 00:36:02,150 that precedes and produces you a molecule of water. 663 00:36:08,030 --> 00:36:10,610 And this just sums up the lactase problem, 664 00:36:10,610 --> 00:36:13,790 where you can digest lactose, the milk sugar. 665 00:36:13,790 --> 00:36:15,980 OK, so those are monomers. 666 00:36:15,980 --> 00:36:19,550 Now let's think about polymers and complex structures 667 00:36:19,550 --> 00:36:20,870 of sugars. 668 00:36:20,870 --> 00:36:22,580 And I put these all on the slides, 669 00:36:22,580 --> 00:36:25,800 because it's just impossible for you to keep drawing them. 670 00:36:25,800 --> 00:36:28,535 And I'm just going to give you sort of one of my pet peeves. 671 00:36:31,070 --> 00:36:34,670 I draw sugars like this. 672 00:36:34,670 --> 00:36:39,020 A lot of other people draw sugars like that. 673 00:36:41,700 --> 00:36:42,660 And I don't like that. 674 00:36:42,660 --> 00:36:44,350 Because this is what they look like. 675 00:36:44,350 --> 00:36:46,530 So if you see this and you go, I haven't 676 00:36:46,530 --> 00:36:49,740 seen sugars looking like that before, it's 677 00:36:49,740 --> 00:36:55,830 because this is the way to draw them that actually represents 678 00:36:55,830 --> 00:36:56,580 their shape. 679 00:36:56,580 --> 00:36:59,100 So if it's unusual format to you, 680 00:36:59,100 --> 00:37:02,050 I'm not going to ask you to construct these. 681 00:37:02,050 --> 00:37:05,310 I just want you to be familiar with looking at them like this 682 00:37:05,310 --> 00:37:06,750 rather than like this. 683 00:37:06,750 --> 00:37:11,210 Because, to me, that's the best way to render them. 684 00:37:11,210 --> 00:37:12,960 OK, so polymers of sugar. 685 00:37:12,960 --> 00:37:14,790 I just mentioned to you, there are 686 00:37:14,790 --> 00:37:18,300 polymers of sugars that are important to storage. 687 00:37:18,300 --> 00:37:21,270 So when we have excess glucose, we 688 00:37:21,270 --> 00:37:26,520 store glucose as glycogen. It's often stored in the liver. 689 00:37:26,520 --> 00:37:28,140 And later on in the semester, we'll 690 00:37:28,140 --> 00:37:31,410 see how a bolt of adrenaline sets 691 00:37:31,410 --> 00:37:34,560 all the processes in motion to chew up glycogen, 692 00:37:34,560 --> 00:37:37,860 to release more glucose so you can have a lot of energy 693 00:37:37,860 --> 00:37:39,600 quickly. 694 00:37:39,600 --> 00:37:44,280 So in that polymer, the sugars are linked in a different way. 695 00:37:44,280 --> 00:37:48,060 The common polymer in plants and, in fact, 696 00:37:48,060 --> 00:37:51,360 accounts for a massive proportion of the biomass, 697 00:37:51,360 --> 00:37:53,670 is a different polymer of glucose 698 00:37:53,670 --> 00:37:56,640 where the linkages are beta-- 699 00:37:56,640 --> 00:37:58,240 we would call this a beta linkage. 700 00:37:58,240 --> 00:37:59,520 But that's the way it looks. 701 00:37:59,520 --> 00:38:01,200 And that would be cellulose. 702 00:38:01,200 --> 00:38:02,910 And it's a linear polymer. 703 00:38:02,910 --> 00:38:07,290 Coming down here, glycogen is often a branched polymer 704 00:38:07,290 --> 00:38:10,760 with different kinds of linkages with different aspects 705 00:38:10,760 --> 00:38:12,220 or different shapes. 706 00:38:12,220 --> 00:38:16,110 So the glycogen that we store and can break down 707 00:38:16,110 --> 00:38:20,790 in order to produce glucose to make energy is glycogen. 708 00:38:20,790 --> 00:38:23,940 We cannot break down cellulose. 709 00:38:23,940 --> 00:38:26,610 We don't digest plant cellulose, because we 710 00:38:26,610 --> 00:38:28,560 don't have those enzymes, which is 711 00:38:28,560 --> 00:38:30,750 why we don't get nutritional value out 712 00:38:30,750 --> 00:38:35,190 of the cellulose the same way we can put forces in action 713 00:38:35,190 --> 00:38:36,970 to break down glucose. 714 00:38:36,970 --> 00:38:42,180 So the way those bonds look is absolutely critical for how 715 00:38:42,180 --> 00:38:45,750 you can use the energy that's within them by using enzymes 716 00:38:45,750 --> 00:38:46,890 to break those bonds. 717 00:38:49,830 --> 00:38:52,700 OK, so in general-- 718 00:38:52,700 --> 00:38:53,940 I've just said that. 719 00:38:53,940 --> 00:38:59,100 Glucose can be stored a cellulose or as glycogen. 720 00:38:59,100 --> 00:39:04,500 The process of photosynthesis converts energy and sunlight 721 00:39:04,500 --> 00:39:08,190 into glucose. 722 00:39:08,190 --> 00:39:11,160 And then you can make the polymers of glucose. 723 00:39:11,160 --> 00:39:13,410 And what I'm showing you here in these polymers 724 00:39:13,410 --> 00:39:15,720 is a simplified view. 725 00:39:15,720 --> 00:39:18,900 I want to introduce to you one other term. 726 00:39:18,900 --> 00:39:20,250 And that term is glycan. 727 00:39:23,960 --> 00:39:26,640 And that basically refers to something 728 00:39:26,640 --> 00:39:29,580 that is more than one sugar, one carbohydrate. 729 00:39:35,398 --> 00:39:37,190 I was looking at the videos of my lectures. 730 00:39:37,190 --> 00:39:39,120 I realized my handwriting is horrible. 731 00:39:39,120 --> 00:39:41,450 So I'm really trying very hard to make it a little bit 732 00:39:41,450 --> 00:39:42,740 neater today. 733 00:39:42,740 --> 00:39:46,070 So glycan is just the name for a polymer of sugars. 734 00:39:46,070 --> 00:39:50,880 But they can also be called polysaccharides. 735 00:39:56,550 --> 00:39:59,340 But glycan now is the commonly accepted term 736 00:39:59,340 --> 00:40:00,610 for a lot of sugars. 737 00:40:00,610 --> 00:40:03,180 Now, I told you about energy storage. 738 00:40:03,180 --> 00:40:05,370 I've told you about simple disaccharides 739 00:40:05,370 --> 00:40:07,680 and monosaccharides and metabolism. 740 00:40:07,680 --> 00:40:09,570 But what I want to do now is give you 741 00:40:09,570 --> 00:40:13,380 a little overview of all the different places where 742 00:40:13,380 --> 00:40:15,138 sugars feature in a cell. 743 00:40:15,138 --> 00:40:16,680 Because I think it's really important 744 00:40:16,680 --> 00:40:20,670 to realize that sugars form a great sort of set 745 00:40:20,670 --> 00:40:23,640 of molecules for communication. 746 00:40:23,640 --> 00:40:25,200 So I'm going to go around this sort 747 00:40:25,200 --> 00:40:27,860 of funny looking square cell. 748 00:40:27,860 --> 00:40:29,670 And this would be a eukaryotic cell, 749 00:40:29,670 --> 00:40:31,230 because it's got a nucleus. 750 00:40:31,230 --> 00:40:33,150 And there are different compartments. 751 00:40:33,150 --> 00:40:36,510 So within the cell, the cell sits 752 00:40:36,510 --> 00:40:39,300 in what's known as an extracellular matrix. 753 00:40:39,300 --> 00:40:42,930 It's a mesh work of sugar polymers 754 00:40:42,930 --> 00:40:44,980 that actually is important for the cells 755 00:40:44,980 --> 00:40:48,180 and important for trapping signals that come from cells 756 00:40:48,180 --> 00:40:49,720 and go to other cells. 757 00:40:49,720 --> 00:40:53,940 So those are all predominantly made up of carbohydrate. 758 00:40:53,940 --> 00:40:55,740 The next thing to look at is that there 759 00:40:55,740 --> 00:40:58,880 are proteins within the cell. 760 00:40:58,880 --> 00:41:03,120 They can become modified with a sugar and go to the nucleus 761 00:41:03,120 --> 00:41:04,420 or leave the nucleus. 762 00:41:04,420 --> 00:41:08,340 So there is a type of signaling that is based on adding a sugar 763 00:41:08,340 --> 00:41:10,500 or taking it off a protein. 764 00:41:10,500 --> 00:41:13,950 We'll see later in the semester how also phosphorylation 765 00:41:13,950 --> 00:41:17,070 does a lot of functions that look like that. 766 00:41:17,070 --> 00:41:20,340 There are sugars that are displayed on the cell surface 767 00:41:20,340 --> 00:41:21,450 polymers. 768 00:41:21,450 --> 00:41:23,610 And that's where signaling becomes important. 769 00:41:23,610 --> 00:41:26,490 Because sugars may be attached to lipids. 770 00:41:26,490 --> 00:41:28,980 You remember, we've talked about phospholipids 771 00:41:28,980 --> 00:41:30,630 being part of the membrane. 772 00:41:30,630 --> 00:41:33,810 Sugars can be attached to lipids that sit in the membrane 773 00:41:33,810 --> 00:41:34,650 and face out. 774 00:41:34,650 --> 00:41:37,650 And it's how cell-cell communication 775 00:41:37,650 --> 00:41:39,930 occurs in some instances. 776 00:41:39,930 --> 00:41:42,960 Or they may be attached to proteins 777 00:41:42,960 --> 00:41:45,940 that are also displayed on the surface of the cell. 778 00:41:45,940 --> 00:41:48,390 So this tells you a little bit about where 779 00:41:48,390 --> 00:41:52,110 we put these sugars is what's responsible for communication. 780 00:41:52,110 --> 00:41:55,560 Because they're on the surface of the cell with their sides 781 00:41:55,560 --> 00:41:58,360 out. 782 00:41:58,360 --> 00:42:00,490 And then the final thing I want to talk about 783 00:42:00,490 --> 00:42:02,270 is the blood group system. 784 00:42:02,270 --> 00:42:05,770 So a lot of you may be aware of blood groups. 785 00:42:05,770 --> 00:42:08,860 There are four principal blood groups. 786 00:42:08,860 --> 00:42:12,850 The differences between the blood in a A, B, AB and O blood 787 00:42:12,850 --> 00:42:16,720 groups are differences in just the sugars that are attached 788 00:42:16,720 --> 00:42:18,440 to the surface of the cell. 789 00:42:18,440 --> 00:42:19,960 So let me describe those. 790 00:42:19,960 --> 00:42:22,360 And then we'll talk about blood groups and things that 791 00:42:22,360 --> 00:42:27,250 are being done to enhance the supplies of red blood cells 792 00:42:27,250 --> 00:42:28,590 in cases of emergency. 793 00:42:28,590 --> 00:42:31,420 I have a nice little video I'm hoping to get to. 794 00:42:31,420 --> 00:42:33,310 So on the surface of the cell, you 795 00:42:33,310 --> 00:42:35,150 might have different sugars. 796 00:42:35,150 --> 00:42:37,930 This is a trisaccharide. 797 00:42:37,930 --> 00:42:40,680 All right, you can see one, two, three sugars. 798 00:42:40,680 --> 00:42:41,940 They have different linkages. 799 00:42:41,940 --> 00:42:43,710 But you can pick out the sugars. 800 00:42:43,710 --> 00:42:53,250 And they are joined by a bond called a glycoside bond 801 00:42:53,250 --> 00:42:54,405 and those join sugars. 802 00:42:59,700 --> 00:43:02,370 So what do you think the enzyme that cleaves the glycoside is? 803 00:43:06,362 --> 00:43:08,360 STUDENT: Glycosidase. 804 00:43:08,360 --> 00:43:10,040 PROFESSOR: Glycosidase. 805 00:43:10,040 --> 00:43:11,300 You would say glycosidase. 806 00:43:11,300 --> 00:43:12,530 I would say glycosidase. 807 00:43:12,530 --> 00:43:13,940 But if they are the same thing. 808 00:43:16,890 --> 00:43:19,310 And that's going to be pertinent in a minute. 809 00:43:22,750 --> 00:43:25,970 So remember, if in doubt, guess and stick "ase" 810 00:43:25,970 --> 00:43:27,970 at the end if I ask you the name of an enzyme, 811 00:43:27,970 --> 00:43:29,570 because that works pretty well. 812 00:43:29,570 --> 00:43:31,870 So if you have O blood group, you 813 00:43:31,870 --> 00:43:36,820 would have exclusively this trisaccharide on your red blood 814 00:43:36,820 --> 00:43:37,790 cells. 815 00:43:37,790 --> 00:43:40,060 If you have the A blood group, you 816 00:43:40,060 --> 00:43:42,550 have an extra sugar attached to that trisaccharide. 817 00:43:42,550 --> 00:43:47,470 And it's a glucosamide sugar. 818 00:43:47,470 --> 00:43:53,380 There's an extra carbonyl group on an amide. 819 00:43:53,380 --> 00:43:56,990 And if you have B blood group, it's gluco-- 820 00:43:56,990 --> 00:43:57,770 it's a sugar. 821 00:43:57,770 --> 00:43:59,410 It's actually called galactose. 822 00:43:59,410 --> 00:44:02,200 That has all OH groups. 823 00:44:02,200 --> 00:44:05,110 So the differences between if you're O group, 824 00:44:05,110 --> 00:44:07,590 if you're A group, or if you're B group, 825 00:44:07,590 --> 00:44:10,270 adjust those differences in sugars. 826 00:44:10,270 --> 00:44:13,960 And then people who have AB blood group have a composite. 827 00:44:13,960 --> 00:44:17,890 They have a mixture of the A and the B blood group. 828 00:44:17,890 --> 00:44:20,824 So do you-- yeah, question. 829 00:44:20,824 --> 00:44:22,600 STUDENT: [INAUDIBLE] 830 00:44:22,600 --> 00:44:26,650 PROFESSOR: That's a second marker, 831 00:44:26,650 --> 00:44:28,450 which we won't talk about. 832 00:44:28,450 --> 00:44:32,110 So it's A plus another marker that's either 833 00:44:32,110 --> 00:44:34,060 one type or another type. 834 00:44:34,060 --> 00:44:36,430 But the AB and O are defined by the sugars. 835 00:44:36,430 --> 00:44:38,560 Yeah, good question. 836 00:44:38,560 --> 00:44:42,810 OK, so do people know their blood group? 837 00:44:42,810 --> 00:44:44,340 It's good to know, frankly. 838 00:44:44,340 --> 00:44:46,792 Because someone-- you know, you may you cut yourself. 839 00:44:46,792 --> 00:44:48,750 And someone says, do you know your blood group? 840 00:44:48,750 --> 00:44:49,542 And you'll go, yes. 841 00:44:49,542 --> 00:44:51,745 And they'll give you an on-site transfusion. 842 00:44:51,745 --> 00:44:53,370 I've been watching too much Jack Bauer. 843 00:44:53,370 --> 00:44:58,950 But, you know, that's a story for another day as well. 844 00:44:58,950 --> 00:45:01,200 So it turns out that depending on blood groups, 845 00:45:01,200 --> 00:45:05,500 you can either be a universal donor or a universal acceptor. 846 00:45:05,500 --> 00:45:07,860 So the people with the O blood group 847 00:45:07,860 --> 00:45:10,560 can give anyone their blood. 848 00:45:10,560 --> 00:45:13,380 People with O, A, B, and AB. 849 00:45:13,380 --> 00:45:17,360 But unfortunately for the poor people with O blood group is 850 00:45:17,360 --> 00:45:22,080 that they cannot receive blood from blood group A, B, or AB. 851 00:45:22,080 --> 00:45:23,760 And I wanted to show this. 852 00:45:23,760 --> 00:45:25,650 And I hope I can get it working. 853 00:45:25,650 --> 00:45:27,670 Because we have just the right amount of time, 854 00:45:27,670 --> 00:45:29,820 which makes me really happy. 855 00:45:29,820 --> 00:45:33,030 Because I don't really program things that well sometimes. 856 00:45:33,030 --> 00:45:36,340 There was a pay-- there was-- 857 00:45:36,340 --> 00:45:38,130 the latest American chemist-- 858 00:45:38,130 --> 00:45:39,380 NARRATOR: --or other disaster. 859 00:45:39,380 --> 00:45:41,300 Those who are affected by crisis usually 860 00:45:41,300 --> 00:45:45,740 need four vital things, food, shelter, water and blood. 861 00:45:45,740 --> 00:45:48,590 In particular, O-type blood, because it can be safely given 862 00:45:48,590 --> 00:45:49,790 to any patient. 863 00:45:49,790 --> 00:45:52,250 Now, scientists say they have identified enzymes 864 00:45:52,250 --> 00:45:55,610 from the human gut that can turn type A and B blood into type 865 00:45:55,610 --> 00:45:58,310 O up to 30 times more efficiently than previously 866 00:45:58,310 --> 00:45:59,720 studied enzymes. 867 00:45:59,720 --> 00:46:01,823 Type A or B blood has specific sugars 868 00:46:01,823 --> 00:46:02,990 on the outside of its cells. 869 00:46:02,990 --> 00:46:03,650 PROFESSOR: I just described-- 870 00:46:03,650 --> 00:46:04,880 NARRATOR: These sugars are recognized 871 00:46:04,880 --> 00:46:05,932 by the immune system. 872 00:46:05,932 --> 00:46:07,640 And if they don't match the type of blood 873 00:46:07,640 --> 00:46:10,880 that's already in an individual, those cells are destroyed. 874 00:46:10,880 --> 00:46:12,590 Because these sugars are recognized 875 00:46:12,590 --> 00:46:15,020 by the immune system, they're called antigens. 876 00:46:15,020 --> 00:46:17,360 Type AB blood has both antigens. 877 00:46:17,360 --> 00:46:19,100 And type O blood has none. 878 00:46:19,100 --> 00:46:20,900 The researchers presented these findings 879 00:46:20,900 --> 00:46:22,790 at the recent American Chemical Society 880 00:46:22,790 --> 00:46:24,620 National Meeting in Boston. 881 00:46:24,620 --> 00:46:27,590 Stephen Withers from the University of British Columbia 882 00:46:27,590 --> 00:46:30,080 has been studying enzymes that remove A or B 883 00:46:30,080 --> 00:46:32,190 antigens from red blood cells. 884 00:46:32,190 --> 00:46:33,950 If those antigens can be removed, 885 00:46:33,950 --> 00:46:37,190 then type A or B can be converted to type O blood. 886 00:46:37,190 --> 00:46:38,900 To find the enzymes more quickly, 887 00:46:38,900 --> 00:46:41,690 Withers and a colleague at his institution used a technique 888 00:46:41,690 --> 00:46:44,330 called metagenomics, which allows scientists 889 00:46:44,330 --> 00:46:46,880 to sample the genes of millions of microorganisms 890 00:46:46,880 --> 00:46:49,070 without the need for individual c-- 891 00:46:49,070 --> 00:46:50,720 PROFESSOR: So that tells you something 892 00:46:50,720 --> 00:46:55,100 about technology and engineering and understanding structures. 893 00:46:55,100 --> 00:46:57,810 So it would be really advantageous. 894 00:46:57,810 --> 00:47:00,590 The stage at which you really need blood supplies 895 00:47:00,590 --> 00:47:02,600 is to take all the blood in the blood banks 896 00:47:02,600 --> 00:47:05,720 and turn everything into a universal donor. 897 00:47:05,720 --> 00:47:08,810 But the blood banks keep these differentiated supplies 898 00:47:08,810 --> 00:47:09,620 of blood. 899 00:47:09,620 --> 00:47:13,160 But what if you need something that you can give everyone 900 00:47:13,160 --> 00:47:14,300 safely? 901 00:47:14,300 --> 00:47:17,000 And so there are enzymes in the gut. 902 00:47:17,000 --> 00:47:20,810 There are bacteria in the gut that actually live off 903 00:47:20,810 --> 00:47:22,790 of sugars that they chop off cells 904 00:47:22,790 --> 00:47:30,690 in the matrix in the GI system. 905 00:47:30,690 --> 00:47:32,600 And so what the Withers group did 906 00:47:32,600 --> 00:47:35,870 was to screen a lot of different enzymes 907 00:47:35,870 --> 00:47:39,410 from bacteria in the gut and find 908 00:47:39,410 --> 00:47:42,530 ones that had a really good specificity for removing 909 00:47:42,530 --> 00:47:43,820 those sugars. 910 00:47:43,820 --> 00:47:45,740 Then they did protein engineering 911 00:47:45,740 --> 00:47:48,410 work to make them more efficient, 912 00:47:48,410 --> 00:47:50,450 thus creating something that was proposed 913 00:47:50,450 --> 00:47:53,690 a long time ago as could be useful, but now really 914 00:47:53,690 --> 00:47:54,860 making it useful. 915 00:47:54,860 --> 00:47:57,380 Because those enzymes are much more efficient. 916 00:47:57,380 --> 00:48:00,050 They really catalyze reactions at great speed. 917 00:48:00,050 --> 00:48:03,080 So they're much more efficient engineering enzymes 918 00:48:03,080 --> 00:48:04,760 to treat your blood cells, to make 919 00:48:04,760 --> 00:48:08,390 sure you get rid of all the features 920 00:48:08,390 --> 00:48:12,300 that are characteristic of the A, the B, and the AB antigens. 921 00:48:12,300 --> 00:48:14,750 Because if you don't do a good job of it, 922 00:48:14,750 --> 00:48:16,640 then the human immune system will 923 00:48:16,640 --> 00:48:19,220 recognize the little bits that sneak in 924 00:48:19,220 --> 00:48:21,780 and start triggering an immune response. 925 00:48:21,780 --> 00:48:24,770 So the efficiency of the enzymes that cleave those sugars off 926 00:48:24,770 --> 00:48:26,730 is absolutely paramount. 927 00:48:26,730 --> 00:48:29,670 And that's what I have for you today. 928 00:48:29,670 --> 00:48:31,340 I will see you Monday, so don't forget. 929 00:48:31,340 --> 00:48:34,310 The Pset's due at 3:00. 930 00:48:34,310 --> 00:48:39,620 Monday, I would like for you to have a preview of the-- 931 00:48:39,620 --> 00:48:44,822 whoops, come on-- of the DNA reading material. 932 00:48:44,822 --> 00:48:46,280 I don't know if any of you do this. 933 00:48:46,280 --> 00:48:48,020 But I think it's really handy. 934 00:48:48,020 --> 00:48:50,110 So there's just some very little sections 935 00:48:50,110 --> 00:48:53,600 that will give you a bit of exposure to nucleic acids. 936 00:48:53,600 --> 00:48:55,730 It'll just make the lecture a little bit more 937 00:48:55,730 --> 00:48:56,610 kind of familiar. 938 00:48:56,610 --> 00:48:59,350 But that's what we're up for Monday.