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The future of antibiotic synthesis

A chemical engineer explains why microbes make the best drug factories in the world — and why science is still playing catch-up.
Pills pour out of prescription medication bottle onto a countertop
Most of the antibiotics that we use come from bacteria and fungi living in the dirt. | iStock/DNY59

Chaitan Khosla is a chemical engineer who says that the world’s most advanced drug factories are not behemoths of the industrial age, but microscopic bacteria.

These tiny creatures have evolved enzymatic assembly lines that ingest raw materials and churn out valuable other molecules, like life-saving antibiotics. By engineering new microbes, we hope to create next-generation drugs, Khosla tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

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[00:00:00] Chaitan Khosla: While we have systematically characterized maybe a few hundred more known antibiotic assembly lines like the erythromycin and rapamycin assembly line, there have been literally 10,000 of these orphan assembly lines that have shown up in the database. And nobody knows what they did, but clear what they do. But clearly they evolve for a reason. And so if you are interested in where the next antibiotic is gonna come from, [00:00:30] you would be well served in trying to figure out what. This digital trash actually does in nature.

[00:00:43] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host, Russ Altman. If you enjoy The Future of Everything podcast, please follow or subscribe wherever you listen to your podcasts. This will guarantee that you never miss an episode and are never surprised by the future of anything.

Today, Chaitan Khosla will tell us how [00:01:00] bacteria create assembly lines to create complex molecules out of simple starting materials. They can do things that even the best chemists have trouble doing. It's the future of antibiotic synthesis.

Before we jump into this episode, A reminder that if you enjoy the podcast, please rate, review and follow it. It will help fellow listeners discover us and it'll make sure that you're never surprised by the future of anything.

Most of the antibiotics that [00:01:30] we use come from bacteria and fungi that are just living in the dirt. They are constantly waging a battle between one another and trying to kill each other, and they have developed these complex molecules that they use as part of this bacterial and fungal warfare. We take advantage of those compounds by using them to cure infections in humans. Now the chemical structure of many antibiotics is very complex, and it has required the bacteria to evolve very special ways to make these [00:02:00] molecules so special that even our best chemists who are human can't quite match the bacteria.

Well Chaitan Khosla is a professor of chemical engineering, chemistry and biochemistry at Stanford University. His lab studies the enzymes that form assembly lines in bacteria that make these complex molecules, including antibiotics and immunosuppressants. They take a series of very simple molecules and pass them from reaction to reaction ending ultimately with [00:02:30] these very complex antibiotics, for example, they're trying to understand not only how these systems work and were built and evolved, but how they can engineer them to create the next generation of antibiotics.

Chaitan, I'm looking at your work, two words come up a lot, enzyme and metabolism. So to start off with, why don't you tell us in technical terms, what does enzyme and metabolism mean for your work?

[00:02:56] Chaitan Khosla: Sure, thank you. Uh, enzymes are [00:03:00] nature's catalysts. A catalyst is a substance that makes chemistry happen faster than it would ordinarily happen without changing in the process. And that's what enzymes do for life. Uh, metabolism is the overall ensemble, the overall set of chemical processes that happen in [00:03:30] a living system. So in our bodies, when we talk about metabolism, it is essentially an aggregate of all of the chemistry that is happening in our bodies.

[00:03:42] Russ Altman: Very good. Okay. So, and I will add, I think that, um, enzymes, uh, in biological systems tend to be proteins that it's not exclusive, but when, when you think about enzymes, are you primarily thinking about biological proteins?

[00:03:56] Chaitan Khosla: Most of the systems I work with are [00:04:00] in fact proteins. In fact, all of the systems I'm currently working on are in, are proteins. But you're absolutely right, enzymes are not exclusively proteins. They can be nucleic acid molecules in life. In fact, the most important, the single most important chemistry that happens in our life, in our bodies, which is to make proteins happens off the back of an RNA catalyst.

[00:04:26] Russ Altman: Okay, so thank you for that, uh, for the preliminaries.

And now I want to [00:04:30] go to this extremely intriguing, um, analogy that you use in your work, which is enzymatic assembly lines. And so, um, I think now we get into the things that really, um, ignite your passions. So tell me about enzymatic assembly lines, cuz they sound fascinating.

[00:04:47] Chaitan Khosla: Okay. I think the best way I can give you a metaphor to explain my excitement about enzymatic assembly lines is pretend for a moment you are a martian [00:05:00] and you have developed technology to send out unmanned spacecrafts to earth to retrieve all the electrical, mechanical, chemical devices that are strewn around our planet. And so somebody brings back an engine, somebody brings back a camshaft, another um, uh, spacecraft, brings back a battery [00:05:30] uh, all the garbage that we put out is brought back in some kind of sampling manner to Mars, and you've gotten your army of martians to decode exactly what each of these devices does.

[00:05:45] Russ Altman: Okay.

[00:05:46] Chaitan Khosla: At that point, you've become a master of enzyme of understanding individual enzymes. Now imagine one day you come [00:06:00] yourself to Planet Earth and you happen to land in Detroit. And you happen to walk, the first object you encounter is the automotive assembly line that Henry Ford built to assemble cars.

[00:06:18] Russ Altman: Got it.

[00:06:19] Chaitan Khosla: You would probably recognize some of the individual widgets you saw over there, but you would have no clue how the [00:06:30] integrated system that you're seeing in front of you takes raw materials at one end and spits out fully functional automobiles on the other. That is what enzymatic assembly lines do in nature. There's a bunch of enzymes that not just operate as exquisite catalysts to do chemistry, but they come together in something that is very [00:07:00] analogous...

[00:07:00] Russ Altman: huh.

[00:07:00] Chaitan Khosla: what you think of as an automotive assembly line.

[00:07:05] Russ Altman: So when I think of an assembly line, I think that the output of step A turns into the input of step B. So do we have an analogous thing going on with the enzymes where one enzyme will produce an A and that'll actually turn into the input for the next enzyme?

[00:07:20] Chaitan Khosla: You're absolutely right. That is exactly one criterion you think of when you think about an assembly line.

The second criterion [00:07:30] that you did not talk about that I'm sure you think of when you think about assembly line is that the output of step A is effectively channeled into Step B without any choice.

[00:07:45] Russ Altman: Yes, yes.

[00:07:47] Chaitan Khosla: Which is very different from a cafeteria model for getting yourself fed over lunchtime. You can [00:08:00] go to any aisle. You have the flexibility to move around anywhere. Or a grocery store model for shopping. They, they're all, the grocery store is an extremely organized place, but there's nobody telling you in what order you go.

[00:08:16] Russ Altman: Right, right.

[00:08:17] Chaitan Khosla: But you happen to go in certain orders based on your personal preferences, that's how most enzymes in biology work. But these assembly line enzymes, [00:08:30] not only move things in a very defined order but they set up a process so that things have no choice.

[00:08:39] Russ Altman: Right.

[00:08:39] Chaitan Khosla: You're only going in one order, and it's all in a highly captive type of a mechanism, and it allows, obviously, nature to do chemistry, the likes of which would be virtually impossible to do. In with just a bunch of free-spirited [00:09:00] enzymes floating around in a cell soup.

[00:09:02] Russ Altman: So if I'm understanding you, in addition to this input output relationship, there are physical and other constraints about the proximity of these enzymes so that it's, if you will, the output of A is right in the face of B and B has no choice but to do its little thing to the output. And so there's an efficiency there that if you would want to take your analogy, if they were just wandering around looking for trouble, it might take forever for B to find its input from A, [00:09:30] whereas there's a physical organization in addition to the logical organization, okay.

[00:09:34] Chaitan Khosla: That's exactly.

[00:09:35] Russ Altman: That's so that's great. So now of course I've looked at some of your work. Tell me why, what types of molecules, uh, intrigue you and require this high level of organization that you've just described?

[00:09:47] Chaitan Khosla: So, 99% of metabolism, probably 99.9% of metabolism in biology happens of the back of free spirited enzymes that are just very [00:10:00] disciplined and know exactly what they're supposed to do, even though they have the freedom to do whatever they want. They have all of our constitutional amendments behind them. Uh, but there's this small set of enzymes in nature that are somehow have evolved. To make antibiotics.

[00:10:24] Russ Altman: Antibiotics, so that's a big thing, that's the used to fight infection.

[00:10:28] Chaitan Khosla: That's why I get [00:10:30] paid to be able to pursue these crazy systems.

[00:10:33] Russ Altman: Okay.

[00:10:34] Chaitan Khosla: Because to be able to study them, because people care about what these systems make. They make very important antibiotics, life-saving medicines and the more you can explain about how nature does something that humans would never be able to do with even 1% comparable efficiency, the more likely you are to improve on it.

[00:10:56] Russ Altman: Okay. So, um, are antibiotics particularly [00:11:00] challenging to make?

[00:11:01] Chaitan Khosla: Very, I mean, a good example is I've spent the past 30 years studying the assembly line. That makes a well known antibiotic that probably all your audience have it consumed. It's called erythromycin. You may have heard of it.

[00:11:16] Russ Altman: I've prescribed it many times.

[00:11:18] Chaitan Khosla: Yeah. So in nature makes one erythromycin molecule on an antibiotic assembly line on an enzymatic assembly line once about every few [00:11:30] seconds it spits out one. And so this assembly line is basically spitting out erythromycins one after another every few seconds.

[00:11:37] Russ Altman: Are we talking five enzymes, 50? What's the scale of this assembly line?

[00:11:42] Chaitan Khosla: On the order of 50 50, on the order of 50 enzymes and humans, the best chemist to ever walk this planet has done the same chemistry with an army of about 20 postdocs. Highly [00:12:00] trained postdocs over a period of several years within an overall efficiency, that's on the order of 1%.

[00:12:08] Russ Altman: Huh. Okay. So the bacteria

[00:12:10] Chaitan Khosla: we have a lot to learn

[00:12:11] Russ Altman: are these occurring in, I say bacteria, but that was an assumption. Are these mostly bacteria or are they fungi or, uh, what organisms?

[00:12:18] Chaitan Khosla: They're mostly bacteria, but they exist in everything. I mean, the amazing thing is people have found these assembly lines in protozones in the [00:12:30] ocean. And they do amazing stuff too. We just don't know what they do.

[00:12:34] Russ Altman: Okay, great. So now we have a really good sense of what we're talking about.

Antibiotics extremely important for fighting bacterial infections and other infections. Uh, they're part of the arms race between these organisms, which are constantly trying to get a leg up on each other. And we take advantage of that by using those same, uh, arms, if you will, to, uh, fight infections.

So where does your lab come in and what are, what's at the frontier? What are the frontier questions [00:13:00] now about these assembly lines and about our ability to, uh, harness them for good use?

[00:13:06] Chaitan Khosla: Right, right. The reason why we can rejigger an automobile assembly line. At the drop of a hat, every time a new marketing genius comes up with a new plan for how to sell a lot of new Ford Bronco sports, you can send that message to the engineer on the assembly line [00:13:30] plant, and they will reconfigure the plant to make it with very little loss.

The reason we can do that is humans built these assembly lines. They know the blueprint like the back of their hands and they can do it. We didn't build these enzymatic assembly lines that make antibiotics.

[00:13:50] Russ Altman: Right.

[00:13:51] Chaitan Khosla: So I am like that proverbial martian who has a pretty good understanding of how the [00:14:00] individual enzymes do the chemistry that they do. It's not perfect, but it's pretty good by now. But now I'm seeing how they integrate into this amazing system that does the overall integrated chemistry. And my job is to figure out what is the code, if you will, that allows individual pieces to fit together [00:14:30] and work seamlessly so that this assembly line can just keep spitting out erythromycins every few seconds.

[00:14:39] Russ Altman: Yes.

[00:14:40] Chaitan Khosla: And that is, I don't have any precedent to be able to think about that problem because the textbooks of biochemistry teach me about metabolism as something that happens of the back of [00:15:00] free spirited yet quite self disciplined enzymes. And now I'm learning that these enzymes need to work together in order to do so.

The big questions that I need to understand is not just what's the code that holds the assembly line that makes erythromycin together, but then there's other antibiotics. You may have heard of an antibiotic called rapamycin.

[00:15:27] Russ Altman: Yes.

[00:15:28] Chaitan Khosla: Used as an [00:15:30] a frontline immunosuppressive when you do organ transplants. Uh, that assembly line is very similar to Erythromycins assembly line, except it's spewing out a very different product.

Evolutionarily, these two systems are very close to each other. So somehow nature evolved a system that is not just exquisite at [00:16:00] making erythromycin, but at the drop of a hat, so to speak, evolution could change it. To make rapamycin, and that is of course, an engineer's dream, right? That's what engineers salivate about. Where on one hand you can have exquisite selectivity on the other hand, every time your boss says, no, I want something different, you just go in there, do some rejiggering and you've got something that can do it.

[00:16:25] Russ Altman: So you, I'm really glad you brought up this engineering aspect because what, there's two [00:16:30] aspects to what I'm hearing you describe the.

First is understanding the, how the system works and how it's organized and that's very much a scientific question, the knowledge of the system. But I know that you're an engineer by training and I know that you're also not. Yes. And I know that you're also interested not just in understanding. So paint a picture for me, perhaps of the kinds of things we might be able to engineer and do with that full understanding that you're seeking.

[00:16:55] Chaitan Khosla: Not just might be able to, but we have done. Let me [00:17:00] backtrack to, so the first antibiotic assembly line was discovered right at the time when I was finishing up my postdoc and starting my lab at Stanford and I made a commitment to myself, I'll work on these enzymes until I understand them enough to be able to be a good engineer with them and or at least die trying.

Uh, [00:17:30] my, when I started my lab, thankfully my students, my early students, they didn't care what I thought and what degrees of difficulty I thought. They just thought, wow, this is a really cool enzymatic system to be studying. Let's just see what happens if we tinker with this and change it to do something else.

And sure enough, when they did that at [00:18:00] some pretty good frequency, good enough for them to write papers and write, get PhDs. They started seeing that they could manipulate genetically the assembly line that makes erythromycin and make modified erythromycins. And in fact, my first student, Bob McDaniel, he made an entire library of erythromycins, which allowed us to start a company and take it public on Nasdaq and do all of the things that Stanford [00:18:30] faculty need to do in order to earn tenure, uh, other than write papers. And so we did all of that. But fast forward to year 2000 when I had become a full professor and my students had become rich and famous, or at least famous and rich perhaps also, but, and we had made all kinds of modified antibiotics with these kinds of sort of, Uh, [00:19:00] flying by the seat of our pants, so to speak. But we still weren't any wiser in how nature built these amazing machines. It was essentially tinkering with these machines in a very empirical sense.

[00:19:17] Russ Altman: Yeah.

[00:19:17] Chaitan Khosla: And you can do that for a while, but it gets unsatisfying. It's very dissatisfactory to be able to do that. And so around [00:19:30] 2000, I made a conscious decision, this is not the way I wanna spend the next 20 years of my career. And we basically, RE-essentially said, that's great. Let other people do all the engineering that can be done using the know-how we had at that time. We're gonna focus on trying to understand these systems and so at this point in time, we're at a point where our [00:20:00] understanding of these systems, I would say it's getting to be fairly decent. By no means sophisticated, but it's getting to be fairly decent.

[00:20:12] Russ Altman: This is The Future of Everything with Russ Altman. More with Chaitan Khosla next.

Welcome back to The Future of Everything. This is Russ Altman and I'm talking with Chaitan Khosla from Stanford University. [00:20:30]

In the last segment Chaitan told us about these amazing assembly lines of enzymes that make complex molecules and bacteria. You know, most antibiotics that we use come from dirt and Chaitan hopes that by looking at more dirt, we're gonna be able to find more antibiotics.

In this segment, he'll tell us that there are databases filled with what he calls digital trash that actually may contain the keys to a next generation of powerful antibiotics.

Chaitan, I know that one of the things you're very excited about is [00:21:00] a field that I've heard you call digital trash. So let's start out what is digital trash and why should I be excited about it?

[00:21:07] Chaitan Khosla: Okay. I can't tell you about digital trash in its entirety, but I'll tell you about digital crash in my field. So over the past, 25- 30 years as my students and I have been studying a handful of these antibiotic assembly lines that make molecules antibiotics like erythromycin and rapamycin, [00:21:30] uh, one of the biggest things that's happened in the world beyond what we do is the human genome got sequenced around year 2000, and that was a herculean effort. I'm sure your audience knows about what went into that, but what happened in that process is the ability to sequence DNA at a high pace became a lot easier. And as these machines [00:22:00] successfully concluded the Human Genome Project, they started looking for stuff to do. And what they immediately realized was these machines that took a year or several years to sequence the human genome could essentially sequence the genomes of bacteria in their lunch break because bacterial genomes are much smaller.

And so the next thing you [00:22:30] knew, everybody who had a bacterium in their collection brought it to one of these sequencing facilities and they sequenced it for them in their lunch break. And then they started depositing those sequences in public databases. And obviously when you sequence several mega based pairs of DNA and you put it there, You don't spend your entire, you don't spend adequate bandwidth on [00:23:00] analyzing all of the DNA.

[00:23:01] Russ Altman: Right. You might have some specific question that gets answered and then you put the rest of the data in the database.

[00:23:06] Chaitan Khosla: So by now we have, fast forward to today, we have literally tens of thousands, maybe even millions of bacteria whose genomes have been sequenced and deposited in public databases. And one of the amazing things my students and I started appreciating around 2010, maybe a little bit earlier, is [00:23:30] there was an explosive growth of sequences of enzymatic assembly lines.

[00:23:37] Russ Altman: Ah.

[00:23:37] Chaitan Khosla: That looked like our antibiotic assembly lines, but nobody knew what they did. Uh, they were just like leftover digital trash from these bacterial sequencing projects. By now, you've probably heard of the field of people sequencing poop to describe microbiomes. So a [00:24:00] typical micro microbiome sequence from somebody's stool sample could give you hundreds of bacteria worth of genome sequence. So genome sequences are just exploding out there, including bacteria, and it turns out that the soil bacteria are unbelievably rich in these antibiotic assembly lines.

Ah, so the average bacterium could have within its genome, up to 10 assembly lines. So [00:24:30] over the past 30 years, and especially over the past 20 years, since 2000. While we have systematically characterized maybe a few hundred more known antibiotic assembly lines like the erythromycin and rapamycin assembly line, there have been literally 10,000 of these orphan assembly lines that have shown up in the database. And nobody knows what they did, but clear what they do. But clearly they evolve for [00:25:00] a reason.

[00:25:00] Russ Altman: Right.

[00:25:01] Chaitan Khosla: And so if you are interested in where the next antibiotic is gonna come from, You would be well served in trying to figure out what this digital trash actually does in nature.

[00:25:14] Russ Altman: Great. So how are we doing this? This is very exciting because as you said, this could be untold either antibiotics that are ready to go or the capabilities for building things that might be new antibiotics that are entirely human [00:25:30] designed. So what's our status there?

[00:25:32] Chaitan Khosla: So I'll give you the good news first, then I'll give you the bad news.

The good news is we've developed some pretty powerful tools to deorphanize these antibiotics. So I'll give you an example. About five years ago I had some, uh, a postdoc in my lab who got interested in a class of orphan assembly lines that seemed to be occurring again and again in a species [00:26:00] of bacteria called nocardia.

[00:26:02] Russ Altman: Now you call them orphan because they're clearly an assembly line, but you don't know what comes out at the end.

[00:26:07] Chaitan Khosla: That's exactly right.

[00:26:08] Russ Altman: Okay, nocardia, that's an infection.

[00:26:10] Chaitan Khosla: You got it. So these were nocardia that infectious disease docs were isolating from patients who had succumbed to no cardiologists and sending to a sequencing lab because that's what you do if you are a modern infectious disease doc. And depositing that sequence as [00:26:30] digital trash. And what we started noticing was the same assembly line was occurring again and again, but only in sequences deposited by ID labs from patients who had died of no cardios. And so we got interested in figuring out. Now this assembly line is a beast. If you think the erythromycin assembly line, to give you a sense of scale, the erythromycin assembly line is an enzyme system that has a molecular mass of 2 million [00:27:00] Daltons.

[00:27:00] Russ Altman: Okay.

[00:27:00] Chaitan Khosla: If you don't know what 2 million Daltons is, you probably know what a ribosome is and a ribosome has a mass of 2 million Daltons. So the erythromycin synthase is a giant thing. This guy is about twice the size of the erythromycin synthase.

[00:27:17] Russ Altman: Okay.

[00:27:17] Chaitan Khosla: And we had no idea what it makes. Fast forward to today, we know he exactly what it means. Right.?

So we've deorthanized it, hooray. We get to publish good papers and all of that.

[00:27:29] Russ Altman: And [00:27:30] presumably it makes something that might be bad because you said this was found in patients who died.

[00:27:35] Chaitan Khosla: So that's our hypothesis. And now that's gonna be the next chapter of that story. Now that we know what it makes, we gotta figure out how does that bacterium use it

[00:27:45] Russ Altman: Right.

[00:27:46] Chaitan Khosla: To be able to immuno, to be able to take over immunocompromised humans.

[00:27:51] Russ Altman: Okay.

[00:27:52] Chaitan Khosla: Okay, but that's a different story when it comes to mining digital trash for new gold. [00:28:00] The problem is the time and effort it's taken us to de orphanize this nocardia associated antibiotic or nocardia associated metabolite. In that time, the world of orphan assembly lines has grown from 3000 to 10,000.

[00:28:21] Russ Altman: So you have a lot of work to do.

[00:28:23] Chaitan Khosla: Yeah, I'm clearly not keeping pace. So our tools to de orphanize have to get [00:28:30] better and our strategies to pick the ones we are going to make an effort to de orphan eyes have to get smarter.

[00:28:38] Russ Altman: Yes. So, uh, that this sounds like a technology development challenge and I know that this is another one of your passions. Uh, in the last minute, can you tell us what are the technologies that look most promising for de orphanizing, as many of these magical assembly lines as possible?

[00:28:54] Chaitan Khosla: The one that I am betting on because I care about where future [00:29:00] antibiotics are gonna come from is within these enzyme systems, there's usually a hint of what these products might be doing. It doesn't tell us what the product is, but it tells us why nature might have evolved this product. If we can decode the molecular logic. Starting from that hint quickly, resource efficiently. [00:29:30] We can now get to the punchline and ask ourselves of these 10,000...

[00:29:36] Russ Altman: Ahh.

[00:29:37] Chaitan Khosla: ...which hundred do we want to spend one PhD student's thesis worth of effort on?

[00:29:43] Russ Altman: So it's a prioritization effort based on clues about how it might be using the output of the assembly line to either infect people or fight a battle with another bacteria. But that allows you then to figure out, this is the one we should go for next.

[00:29:58] Chaitan Khosla: That's exactly right. [00:30:00]

[00:30:00] Russ Altman: Thanks to Chaitan Khosla, that was The Future of Antibiotic Synthesis.

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