Introduction to Synthetic Biology and Metabolic Engineering
Transcript of Part 1: Introduction to Synthetic Biology and Metabolic Engineering
00:00:06.09 My name is Kristala Prather, or Kris. I'm an associate professor 00:00:11.15 in the Department of Chemical Engineering at MIT 00:00:14.00 and today I'm going to talk to you about metabolic engineering and synthetic biology, 00:00:17.08 two fields in which I work and which have a very, very strong influence from biology. 00:00:22.01 If you think about biology in the world around you, 00:00:25.28 if you look around at nature, you'll see a lot of beauty and a lot of diversity. 00:00:30.17 You might see feathers on a peacock. 00:00:34.00 You can look at a nautilus shell 00:00:36.06 and see the structures, the symmetry, all of the details that are there. 00:00:40.08 You might look at the wing of a butterfly, for example, 00:00:42.28 and you see colors, and patterns, and lots of richness, 00:00:46.24 or even as you look at the leaf of a tree, you'll see lots of wonderful details and structures. 00:00:52.10 And all of that we see on a very large scale, 00:00:54.27 thinking about how nature gives us a lot of beauty, a lot of diversity, 00:00:59.01 a lot of function. If we actually look deeper, though, at that same leaf that came from the tree, 00:01:05.03 you'll notice that as you go closer and closer in scope, 00:01:08.02 or in scale, you'll see details that you couldn't see before. 00:01:11.20 You'll see that that leaf is actually composed of a series of individual cells, 00:01:15.15 and even within those cells, you see even smaller structures, structures we call organelles 00:01:20.25 that are all giving you this macroscopic property, or phenotype you see, 00:01:25.00 that you recognize as a leaf. And when we look at structures like this, 00:01:29.10 what we really realize is that it's really all about the DNA. 00:01:33.24 Everything that gives us what we see from nature, 00:01:37.00 that gives us the color, the structure, and the function, 00:01:40.11 the things that we think are beautiful, and the things that we think are useful, 00:01:44.08 really come back down to the DNA. 00:01:46.18 And it's really this focus on the DNA which is a hallmark of synthetic biology. 00:01:52.01 Synthetic biology has been defined in many different ways, 00:01:56.15 and it's actually interesting to think about some of the older definitions. 00:02:00.04 One of my favorite actually comes from 2000, 00:02:02.20 in a publication called Chemical and Engineering News. 00:02:05.21 And in that publication, synthetic biology was defined in the way that you can see on the screen now. 00:02:10.06 In particular, there's a focus on the use of non-natural, synthetic molecules. 00:02:15.24 That is, things that aren't really of biological origin, 00:02:19.05 and being able to use those molecules in order to give you function. 00:02:22.18 Ok, so the keys here are things being non-natural, 00:02:25.08 and the function that you would get in biological systems. 00:02:27.26 In the 10 to 15 years since this definition came out, 00:02:31.26 really synthetic biology has changed and the work that's going on in synthetic biology has become much broader. 00:02:38.13 And the definitions that are used more commonly than this first one that's given 00:02:42.17 are the following. One is that synthetic biology is the design and construction 00:02:47.15 of new biological parts, devices and systems. 00:02:52.01 And those parts, devices and systems are words that actually come from engineering. 00:02:57.07 So, one of the ways that we also think about synthetic biology, then, 00:03:00.22 is to re-design existing, natural biological systems for useful purposes, 00:03:06.06 which is really what engineering is all about. 00:03:08.12 Engineering is about design, it's about re-design, for useful purposes, 00:03:12.26 and that is, for specific applications. 00:03:14.25 So, you can see in just looking at how the definitions have changed, 00:03:18.07 from one in 2000, to the working definitions that are used more today, 00:03:22.15 we don't have to focus on unnatural pieces giving us natural or biological functions, 00:03:27.25 but rather, there's more of a focus on taking what nature has given us, 00:03:31.27 repurposing or re-using that for intentions that we as engineers 00:03:36.21 actually design. 00:03:38.02 So, for us, within what's called the Synthetic Biology Engineering Research Center, 00:03:43.24 this also a center in which I work, 00:03:45.17 we have what I describe as a practical definition of synthetic biology. 00:03:49.00 And that is synthetic biology is the effort to make biology easier to engineer. 00:03:54.09 And it's this fusion of engineering principles with biology 00:03:58.01 that really gives synthetic biology its heart and its purpose. 00:04:02.04 And here are some of the engineering principles that we think about as engineers. 00:04:05.27 Things like design; by design, what we mean in that case is saying, 00:04:09.27 I want to build a certain machine that has this specific function, 00:04:14.16 and I know how to draw out or sketch out a way in which I get there. 00:04:18.17 If I think about modeling in an engineering sense, modeling is really about mathematics. 00:04:23.07 That means I can write an equation that actually will support my design, 00:04:27.25 and it represents as well the understanding I have of the underlying principles 00:04:32.24 that allow me to have that design. 00:04:34.17 And then we have these principles of characterization and abstraction, 00:04:37.23 and that really means the practice of going through your design, 00:04:42.02 what you have actually designed, to the point where you build that and then you test it, 00:04:45.22 and in the process of testing it, you characterize the system as a whole, 00:04:49.16 as well as the individual parts. 00:04:51.20 And finally, abstraction means actually being able to take, now, 00:04:55.09 a larger view and if go back to my definitions of parts and devices, 00:04:59.18 it means not always having to look at the very specific level of detail, 00:05:03.26 but knowing that if I want some bigger function, 00:05:06.18 I could encode that in a simpler way. 00:05:09.08 So, the key technology in synthetic biology for all of this 00:05:13.08 is DNA synthesis. 00:05:14.27 And DNA synthesis is really about having biology or biological function 00:05:20.07 but taking a step where you really remove biology from that process. 00:05:24.01 Here's actually an example of how that works; 00:05:27.28 so if we think about biology and think about DNA, 00:05:30.27 I've already told you that all of biology is really about the underlying DNA, 00:05:36.02 there's a sequence of A's and G's and C's and T's 00:05:39.03 in the natural system that is the DNA and how those strings of nucleotides, as they're called, 00:05:44.20 are strung together, actually gives us the function that we're interested in. 00:05:48.14 So, I may study the biological system, 00:05:51.05 and then figure out, what is that sequence that gives me the function that I actually want, 00:05:55.22 or the function that I'm looking to be able to now design, 00:05:58.21 into a new system, 00:06:00.03 I can then go now to a computer, store that information digitally 00:06:04.25 and go through the design process that I talked about 00:06:07.27 where I can specify now my own sequence of those A's and G's and C's and T's, 00:06:13.01 to give me the function that I want and then rather than having to go back into the biological host, 00:06:17.28 I can take advantage of DNA synthesis to make the DNA that I want, 00:06:21.20 without actually having to go back into a biological host to do this, 00:06:26.06 but by rather recognizing that those sequences of A's and G's and C's and T's 00:06:31.02 are just chemicals and those chemicals can be synthesized without biology, 00:06:34.28 and they can be strung together without biology. 00:06:37.05 I can though, once I've made those, put those, put them back into a biological host, 00:06:41.26 and that gives me then the function, as far as biology is concerned, that I'm interested in. 00:06:46.24 So, this is a nice representation of this type of process, 00:06:51.27 from Seed magazine, this was drawn by Drew Endy, 00:06:54.18 who's now at Stanford University, 00:06:56.15 and it's just a cartoon representation of exactly what I described, 00:07:00.01 where you start at the beginning, with actually defining what that sequence is, 00:07:03.17 of the A's, the G's, the T's and the C's, from now a natural host, 00:07:08.04 you can then reconstruct those now as synthetic DNA, 00:07:11.19 and then this abstraction is actually the line that I'm crossing here, 00:07:15.10 where we think about now that I have that DNA, if you will, 00:07:18.28 encoding a function that I'm interested in, 00:07:20.24 and that may result in taking a certain input, converting it to a different output, 00:07:25.16 or stringing together different devices here now, 00:07:28.27 one that may have one function, one that has another function, 00:07:31.21 and having now a composite device, 00:07:34.20 as we would call it, that would give us this feature that we're interested in. 00:07:38.05 And I might be able to string these together in many different ways, 00:07:41.02 in order to get different kinds of functions now, 00:07:43.07 putting two devices together, or maybe multiple devices together that may give me a certain structure, 00:07:48.14 or feature, that has the function that I'm interested in. 00:07:50.29 So, if we now think about some examples of how we could make this work, 00:07:56.08 that is designing different pieces of DNA such that we put them together and get different functions, 00:08:01.11 you can see a movie that's playing on the screen now 00:08:04.23 where there are individual cells that are growing, they're dividing, 00:08:07.14 and you can see that they're actually blinking. 00:08:09.20 They're sometimes having light turned on and sometimes having light turned off. 00:08:13.22 This is actually an example of something that's called an oscillator, 00:08:16.27 that process of turning on and off means that the expression, in this case of this protein, 00:08:21.27 is oscillating. And that feature of being able to have a system now that blinks, if you will, 00:08:26.25 is something that can be encoded in the DNA, 00:08:29.03 by taking advantage of different parts, 00:08:31.08 for example, what's shown here is a Tet repressor, 00:08:34.05 a Lac repressor and a lambda repressor, 00:08:36.12 that all work together in a way that you have now a system that gives you sometimes the gene expression being on, 00:08:43.13 that is the light is on, 00:08:44.26 and sometimes the light being off. 00:08:46.15 So, this is an example of how a specific function, that is, oscillation, or blinking, 00:08:51.24 could be designed, there were models that were built in this system, 00:08:54.28 that is mathematical equations to describe how that had to happen, 00:08:58.16 and then you could actually build in those pieces with DNA, 00:09:01.10 these circles here are plasmid DNA, and the output, finally, is GFP. 00:09:05.22 And that's actually the protein that gives you the lightness or the darkness, 00:09:08.22 that is the blinking pattern. 00:09:11.21 Here's a different example of being able to string those pieces of DNA together 00:09:15.25 in order to get a particular type of function that we want, 00:09:18.24 and in this case, the goal was to have effectively a bacterial photography system. 00:09:23.11 And in this case, there was DNA taken from many different pieces, 00:09:26.15 there was something called phytochromes, or light sensors, from an organism called Synechocystis. 00:09:31.23 There was something called an osmoregulation system, 00:09:34.23 and this is really just a way to make proteins from E. coli 00:09:38.15 and then a protein called LacZ, which has really been around for quite a long time, 00:09:43.18 in biological standards, since the late 1970's, 00:09:46.06 which allows you to either have color or not have color. 00:09:49.14 And you can see now in the pictorial diagram here the way this is supposed to work 00:09:53.14 is that when light is present, you're going to have now activation of this osmoregulation system, 00:09:58.27 that gives you an output which in this case is going to be black. 00:10:02.11 If there's no light that's present, then you'll have an output that's going to be light. 00:10:06.07 So, we can have a table that's written here, that would be our design table that says, 00:10:10.14 the first condition that we want is a light condition, 00:10:13.07 and in that case the LacZ is going to be low, 00:10:16.07 and the result is a light color. 00:10:17.15 The second condition now would be a condition that's dark. 00:10:20.08 In that case, the LacZ output is going to be high, and that's actually going to give us a dark color. 00:10:25.00 How does this actually work? 00:10:27.21 Well, what you can do now is to create a mask where if you look on the left-hand side here, 00:10:33.16 what's shown is 'Hello World,' where everything now that's white would be white, 00:10:37.24 and you would actually be able to shine light through the words hello and world 00:10:41.29 and you can see next to that then the result of what happens. 00:10:45.02 When the light output was low, 00:10:47.10 you have no color, when it's high, you have a dark color, 00:10:50.15 and that actually gives you now, in bacteria, bacteria that are dark that say hello, 00:10:55.07 bacteria that are dark that say world, and will actually recapitulate, or give you that image, 00:11:00.05 much like a camera would. 00:11:01.26 Here's an example of this same system now, taking it a little bit further, 00:11:07.01 with images that are even more complex. 00:11:09.05 And you see in this case, now, from a paper published in Nature from the same group, 00:11:13.08 that you can actually end up with a picture of a bacteriophage 00:11:16.14 based on this same principle of having a mask and exposing light, 00:11:20.27 and in the places where the light is there, you have a dark color, 00:11:23.21 when it's not, you have a lighter color. 00:11:25.25 And you can even go even further and make a picture of Andy Ellington, 00:11:29.02 who is the professor in whose lab this was developed. 00:11:32.08 These are examples, now, of being able to put biology, or biological pieces together 00:11:38.19 for functions, but as engineers, we often want to think about how do we actually solve problems, 00:11:43.26 whether they be problems in healthcare, in energy or the environment. 00:11:47.29 And so I'd like give you a few examples of applications 00:11:51.12 that are emerging from synthetic biology 00:11:53.23 where researchers are actively working to build these biological systems 00:11:57.17 to address some of these global problems. 00:11:59.26 And the first example I'm going to give you is from the lab of professor Ron Weiss 00:12:03.18 who's in biological engineering at MIT, 00:12:05.16 and he's been looking at the issue of diabetes. 00:12:08.19 There are two types of diabetes: type I and type II. 00:12:11.18 In type I diabetes, what actually happens is that your body destroys 00:12:16.08 the cells that make the insulin that you need 00:12:18.17 to control your glucose levels in the blood. 00:12:21.24 And so, you may have seen an image like this before, 00:12:25.02 where patients who have diabetes have to check their blood glucose levels, 00:12:29.07 they actually have to prick themselves to extract blood, 00:12:32.19 expose that to a glucose meter, and then based on their glucose levels, 00:12:36.01 decide to dose themselves with insulin or not. 00:12:39.05 Well, if we say the problem is in the pancreas, 00:12:41.26 the question is, can you actually engineer an artificial pancreas 00:12:46.11 or engineer cells that will perform the function of the pancreas 00:12:49.21 so that you now no longer need to have this process of measuring blood glucose levels, 00:12:55.00 and then actually dosing yourself with insulin. 00:12:57.09 So, what Professor Weiss is doing is looking at engineering stem cells 00:13:01.01 to be able to stay in an undifferentiated state 00:13:03.19 to then sense when the presence of these insulin producing cells has gone very low, 00:13:09.00 and then to differentiate and produce new cells, only up to a point, 00:13:12.18 and then to stay quiet again, or quiescent, 00:13:14.29 such that you maintain this population of cells 00:13:17.18 that can spontaneously produce new insulin producing cells whenever your body needs them. 00:13:22.19 That's an application in health. 00:13:25.23 There are other applications, for example, in the environment, 00:13:29.05 and this is actually a significant problem in agriculture, 00:13:32.02 which is that you have to provide a lot of nitrogen 00:13:35.09 to plants in order to get them to grow. 00:13:37.18 Proteins, for example, have a lot of nitrogen in them, and so it's necessary to provide that 00:13:42.03 because it can be difficult to actually extract it in a way that's usable. 00:13:46.04 But it turns out that there are certain organisms that will actually live on the roots of plants 00:13:51.02 that have the ability to fix nitrogen, that means they can take nitrogen from the atmosphere, 00:13:56.00 and convert it into the kind of nitrogen which is useful for plants. 00:14:00.01 And so Professor Chris Voigt, who's in biological engineering at MIT 00:14:03.28 has been looking at whether or not you could take that ability to fix nitrogen, as we call it, 00:14:08.21 that is to take nitrogen out of the atmosphere and put it into a usable form for plants, 00:14:13.25 can you actually take that capacity from these microorganisms and put it directly into the plants 00:14:20.10 so that you actually have a need for much less fertilizer in the environment. 00:14:25.13 Here's a third example of a way that now a group of students 00:14:30.23 were looking at using synthetic biology to be able to really address a critical problem in both health and the environment. 00:14:37.14 And this is actually part of the iGEM program, you can see the URL for that at the bottom of the screen, 00:14:41.28 where iGEM stands for international genetically engineered machines 00:14:46.01 and the iGEM competition is an opportunity for students from all over the world to come together 00:14:51.15 and decide for themselves, here's a problem that we want biology to try to solve 00:14:55.21 and then to go through this process of designing, modeling, characterizing and building these systems 00:15:00.29 to see if they can address those problems. 00:15:02.29 The University of Edinburgh iGEM team in 2006 00:15:07.15 decided to try to tackle the problem of groundwater contaminated by arsenic in Bangladesh. 00:15:13.03 They studied the problem, found that it really is significant, 00:15:15.29 in terms of a lot of the groundwater being contaminated 00:15:18.15 and there not being really any easy systems for villagers to know whether or not a source of water 00:15:24.14 was safe to drink or not. 00:15:26.03 So, they decided to take pieces from biology that naturally responded to arsenic 00:15:31.07 and to build a sensor that would tell them whether or not there was arsenic in the water or not. 00:15:35.29 And it was actually designed after something you may have seen, 00:15:38.29 which is just a sensor that tells you, for example, the chlorine level and the pH level in a pool. 00:15:43.14 The idea being that you could take a sample of water, you could add now this sample of bacteria, 00:15:48.19 E. coli in this case, that could detect the arsenic. 00:15:51.19 If the arsenic was present at a certain level, the colors would become very bright, 00:15:55.13 and you would know that that water was not safe to drink. 00:15:58.02 Now, I want to actually switch gears a little bit and talk about metabolic engineering, 00:16:04.07 which is an area that's been around for awhile, 00:16:06.10 but we're increasingly seeing a merger between principles of metabolic engineering and those of synthetic biology. 00:16:12.16 And metabolic engineering is really about the fact 00:16:15.17 that biology is very good at doing chemistry; 00:16:18.09 that is, from biological systems, you can get a wide range of chemical molecules 00:16:23.10 that have useful functions. And I've shown two of them here. 00:16:26.02 The first one is called caspofungin, and then there's another one that's shown here that's called lovastatin. 00:16:31.15 Caspofungin is actually an antifungal organism, that is, it's used to treat fungal infections, 00:16:37.00 and lovastatin is one of the first cholesterol lowering drugs. 00:16:40.11 So, you've heard about statins, perhaps, and there are lots of them now, 00:16:43.14 but lovastatin was one of the first that was discovered. 00:16:45.29 Both of these are naturally produced by biological systems 00:16:49.20 and they've been very useful as natural products, we would call them in this case, 00:16:53.21 to have therapeutic functions. And traditionally, when we think about biology being used for chemistry, 00:16:59.06 it's usually for molecules like this. 00:17:01.06 If you look at caspofungin, for example, you can see that it has complexity 00:17:04.20 both in terms of just the number of atoms that it has, it's a pretty big molecule, 00:17:09.17 and then you'll also see a lot of these hydroxyl groups, you'll also see chiral centers, 00:17:13.16 which are shown now by the bold, or the arrows that go back and forth. 00:17:18.14 And so traditionally, if you think about how synthetic chemistry works 00:17:22.18 it's not that chemistry can't make a molecule like that, 00:17:25.09 but the yields would be very low, it would take a large number of steps 00:17:29.03 to get to that compound, whereas you have a biological organism 00:17:32.19 that can make these molecules very easily. 00:17:35.01 And so it's molecules like this that traditionally have been made by biology. 00:17:39.28 Now, I want to introduce as well a couple of other molecules, one being an amino acid, glutamic acid, 00:17:45.12 and the other being an organic acid, malic acid. 00:17:48.12 And these are also molecules that biology can make efficiently 00:17:52.09 using biological means as opposed to chemistry. 00:17:55.14 And what I mean by that is they can be produced commercially through fermentation. 00:17:59.16 So, you have an organism that's capable of making these compounds, 00:18:03.12 you can grow them up in very large quantities, 00:18:05.12 and now you have a product that you can bring to market. 00:18:08.02 What's true about all of these molecules is that they are produced by organisms 00:18:13.11 that naturally make them and the goal when metabolic engineering first arose 00:18:17.25 was to figure out how do you actually get these organisms 00:18:20.28 to do what they do better. 00:18:23.11 And better, in an engineering extent means to make more of the molecule, to make it faster, 00:18:28.13 and to make it more efficiently and the efficiency part, it's typically considered as yield. 00:18:33.19 That is, how much of the starting material that goes into the system 00:18:37.06 ends up in the product that you're interested in. 00:18:39.00 So, I have a graduate student who once came up with this analogy, or this cartoon, 00:18:44.09 to describe how metabolic engineering actually works in terms of improving these natural producers. 00:18:49.14 And what you see here is a maze, where you have this poor mouse, Wemberly, 00:18:53.28 that's lost its pet rabbit Petal, and Wemberly has to figure out how to get to Petal. 00:18:58.20 And you can see, as with any maze, there are a number of different starting points 00:19:02.12 that the mouse could use in order to get to the end point. 00:19:05.00 However, we know not all of those are going to be productive. 00:19:07.22 So, with metabolic engineering, what you want to do is to remove those routes 00:19:12.05 that are going to be non-productive. 00:19:13.11 That means to actually knock out, or delete, competing pathways. 00:19:17.07 Pathways that would actually take your substrate, your intermediate or your carbon 00:19:21.29 a place that you don't want it to go. 00:19:23.23 The other thing that you might want to have in order to have this faster objective met 00:19:28.13 is a little bit of a stimulation or motivation 00:19:31.17 for the enzymes to be overexpressed. 00:19:33.13 And overexpressing those enzymes, you can increase the amount of a limiting enzyme 00:19:40.01 in order to get more of that through the system. 00:19:42.26 And now again, in our cartoon fashion, what that means is encouraging the mouse to run a little bit faster 00:19:47.10 and to get through the maze quicker than it otherwise would. 00:19:50.12 So, I finally want to introduce just as background two other molecules that are interesting 00:19:57.06 both from a metabolic engineering and a synthetic biology standpoint. 00:20:00.23 And these are 1,3-propanediol and artemisinic acid 00:20:04.03 and you can see on the slide the uses for them. 00:20:06.20 1,3-propanediol, or PDO, as it's called, is an industrial chemical that's also used for materials production, 00:20:12.09 and artemesinic acid is a precursor to an anti-malarial drug. 00:20:16.19 Now, these are also compounds that are produced by biology, 00:20:20.00 meaning that we can make them through fermentation, 00:20:22.07 that is growing up a large number of microorganims to produce the compound that we're interested in. 00:20:27.14 They're also natural products, meaning that they're naturally produced by organisms. 00:20:32.01 But the difference between these two molecules and the first four examples that I gave 00:20:36.05 is that those molecules are produced naturally by one particular host, 00:20:41.17 but it's actually a different host that's been able to be used to have them produced economically. 00:20:46.28 And this allows us now to think about that DNA that we talked about, in terms of moving that around, 00:20:52.19 to be able to move it to reconstitute natural pathways in heterologous hosts, 00:20:57.19 or in hosts that don't normally contain that pathway. 00:21:01.10 Here's actually an example of doing just this thing. 00:21:05.14 So, the artemisinic acid that I told you about is a precursor to the drug that's shown here, 00:21:09.17 which is called artemesinin. It's naturally produced in a plant that's called Artemisia annua 00:21:14.17 and the goal is to be able to have, rather than that plant, a yeast cell 00:21:19.10 make this same compound. The reason for that is that you can put yeast cells into a factory 00:21:24.11 that looks much like factories that you may have seen before, 00:21:27.00 or, if you think about yeast and fermentation, this might actually be a brewery, 00:21:31.13 or a beer manufacturing unit. 00:21:33.00 And you can't take plants and actually scale them up in that same way. 00:21:37.02 Instead, you have to plant plants in the ground, 00:21:39.13 and wait for the proper amount of sunlight and nutrition in order for them to grow. 00:21:43.11 So, if my goal is to actually have a compound that's produced in Artemisia annua, 00:21:48.27 to have that be produced in a yeast, so that I can put it into a factory, 00:21:53.06 what that really means is identifying the DNA that encodes for those enzymes 00:21:57.25 that gives me the chemical that I'm interested in. I now can go through this process that I talked about before, 00:22:03.01 of sequencing that DNA and then synthesizing the DNA to get just those pieces that I need, 00:22:08.16 and then I can move that DNA now into my unnatural, or my heterologous host, 00:22:13.25 and that host, once it's properly engineered, is able to make the compound that I'm interested in, 00:22:18.22 and I can actually grow it up now in a large factory. 00:22:21.20 And this is work that's been done by Professor Jay Keasling, in chemical engineering at UC-Berkeley. 00:22:26.20 So, the work that's done in my lab is really focused on expanding this capacity of biology 00:22:33.04 to do chemistry. And we're motivated by the diagram that's shown here, 00:22:37.01 where if we think about the materials that we get in our world today, 00:22:40.16 where they come from and what they're used for, most of it comes from crude oil as the input, 00:22:45.15 and the outputs are things that you're familiar with, which include fuels, 00:22:49.05 which I think is mostly what we think about in terms of oil being used for, 00:22:52.27 but also quite a large bit of petrol chemicals. 00:22:55.22 And these are actually the molecules, olefins and aromatics are highlighted here as examples, 00:22:59.24 that are used for polymers, for resins, for adhesives, et cetera. 00:23:03.28 That is, those are molecules where the chemicals that are being produced 00:23:08.05 are being used for their mass properties, or their properties as chemicals 00:23:11.14 and not for their energetic properties, which is what we use them for for fuels. 00:23:15.18 And we've talked a lot in this country and across the world 00:23:18.19 about replacing crude oil as the input for this process, 00:23:21.29 and instead we can think about creating what we might describe as a bio refinery, 00:23:26.05 where the input in that case, rather than being oil, is glucose or other sugars, 00:23:31.07 that might come from biomass, in the same way that we now want to be able to make biofuels, 00:23:36.01 we want to be able to make more chemicals, 00:23:38.21 that is, the same chemicals that give us the function that we're used to from petrochemicals, 00:23:42.23 we want to be able to access those from biomass as well. 00:23:46.17 In the second part of my talk, I'm actually going to give you examples from my lab, 00:23:50.14 where we focus on exactly this, that is, building new kinds of chemical molecules 00:23:55.02 from biology in different ways that really take advantage of the key principles of synthetic biology, 00:24:00.25 but also are very firmly rooted within metabolic engineering as well. 00:24:05.23 So, this is actually our vision of how that happens, this is a cartoon representation from an artist at MIT, 00:24:13.16 where really what we're looking at doing in expanding the capacity of biology to do chemistry, 00:24:18.03 is to think about these microbes as they were, this is an E. coli representation, 00:24:22.21 as little chemical factories, where we can now, inside the cell, engineer different pathways 00:24:28.12 to make different products and that same image that I showed you before 00:24:31.28 of a large factory, we can think about that on a greatly, greatly magnified scale 00:24:36.23 or a greatly miniaturized scale, I should say, in terms of having now small microbes give us this same capacity. 00:24:43.00 So, let me give you my final thoughts about the field of synthetic biology 00:24:47.10 and a little bit about metabolic engineering. Synthetic biology is a very diverse field 00:24:51.21 and it's actually composed of very diverse individuals as well, 00:24:55.06 and so people like myself, who work in metabolic engineering are in that field, 00:24:58.13 those who are trained as electrical engineers, as computer scientists, as biological engineers, 00:25:03.11 as physicists, they are a lot of different people in this area who are looking at how do you actually use DNA 00:25:08.21 in order to get important functions of interest to solve the problems that we have to solve in the world. 00:25:13.25 The problems that are being worked on are very diverse problems; 00:25:16.25 I gave you examples that come from health, from the environment, from energy, 00:25:21.02 and again, this diverse set of people are working on this diverse set of problems 00:25:24.21 and are also taking diversity of approaches towards solving those problems. 00:25:28.27 And I would say that the goal for all of us as we go through this 00:25:32.10 is to actually make biology easier to engineer, 00:25:35.02 so that we really can bring solutions to some of our most pressing global problems. 00:25:39.22 In the second half of my talk, I'll talk much more about examples from my lab, 00:25:43.10 but this is my overview for metabolic engineering and for synthetic biology.
