MSU researcher using synthetic biology and regenerative medicine to tackle fundamental questions

Nov 19, 2018

Assaf Gilad is the chief of the Division of Synthetic Biology and Regenerative Medicine in the Institute for Quantitative Health Science and Engineering at MSU. He was recruited from Johns Hopkins University. Dr. Gilad is a biologist by training and a professor of biomedical engineering and radiology.

The overarching theme of Dr. Gilad's research program harnesses the intersection of radiology and molecular biology to develop new in vivo imaging technologies that can be used to tackle fundamental biological questions. Specifically, the lab works to develop novel genetically encoded and nanoparticles biosensors for both MRI detection and neuromodulation.


The lab is interested in the interface between biology and electronics at the protein level. We are engineering new proteins that can improve medical diagnostics, disease treatment, tissue regeneration and biotechnological process.

White: Describe your research for us. What do you do?

Gilad: My research is in the field of synthetic biology. Synthetic biology is a relatively new field where scientists are looking at biological phenomena from the engineering point of view. Instead of looking at cells and organisms and proteins and trying to understand what they are good for or how they work, we look at them from the point of view that what can we do with them? How can we use them to build something new? How we can use it to build a new function? How we can use them to make, maybe, something that is like an electrical circuit where you have an on/off switch? Or, you can make some sort of cellular device that makes a process.

The idea is to take these biological or these engineering principles and use biological tools, and we call many of these proteins and genes bio-tools or bio-parts, and we try to see what we can do, how we can build with them things that will not exist in nature.

In that sense, we make synthetic proteins. When I started my research in that field, we made synthetic genes. Those genes encoded to proteins. What was special about these proteins is that you can visualize them with MRI, with magnetic resonance imaging.

It's pretty much the same instrument that physicians are using today to diagnose patients in the clinic. Except that we have smaller MRI systems that we can use for small animal models and image things in test tubes.

What was unique about it is that the gene was completely synthetic. We knew exactly what we want to have as we know genes are encoding to proteins. We knew what we are expecting from this protein. We knew what the protein, how the protein should look like, how it should be, how it should function. We reverse-engineered it into a synthetic gene, an artificial gene and made the gene that encodes this protein with this function. Indeed, we were able to distinguish this protein from other proteins in the cells with MRI.

That's one way of looking at synthetic biology. We keep working with it. We're trying to make it better. We're trying to make it more sensitive that we can detect lower concentrations of this protein. Now, we have different approaches to do it. One approach that we started to use is evolution-based, protein engineering. You can engineer proteins, and maybe we should go one step backward. Proteins and genes that encode to proteins is the essence of biology, it's the essence of nature. These are the building blocks of everything.

Today, we know of proteins that do everything from creating new life all the way to chew up used plastic. You can take proteins and make them into tiny tools that can do everything you want.

The question is how. That's not easy. That's not trivial, but we have a lot of smart people, and people came up with different ways. One of the best ways to do it is to use the tools that nature gave us, which is evolution. 
We want to take these proteins or genes and evolve them into proteins with different functions using the same principles of evolution that there is in nature which are mutations and selection for the fittest protein. What is important is to have a big population of mutated genes or mutated proteins and then a good screening way to find the one that is really good.

Then, once you find it, you can go for another generation. That's how mutations have been evolved. Much like people evolved wheat and corn to have these big grains with a lot of proteins and polysaccharides, and so on, we can evolve proteins. Proteins can evolve in evolution to do very unique things. This is how organisms evolve to live in volcanoes and very extreme temperatures.

We can use the same principles. We make libraries of mutated DNA, and then we screen them. We are looking for the ones that have specific or the most desired function, and then we keep evolving it. These genes can be synthetic genes like the one we used for the MRI, or these could be natural genes. We can take genes that were evolved by nature, and in general, if you can have someone else doing the work for you, it's easier.

Another example of the research in the lab is a gene that we cloned from a fish. It turns out that there are certain species of fish, certain types of fish that can navigate using the Earth’s magnetic field. They evolved a very specific protein that helps them with this navigation.

This is work that I started back when I was a professor at Johns Hopkins School of Medicine together with Professor Galit Pelled. We took one of these species of fish, and we made a DNA library out of it.

We cloned all the genes that this fish has, and we selected for the specific gene that is responsive to electromagnetic field. In fact, it's very interesting, because in order to screen for this protein, we used eggs from a frog. It was very neat. It sounds very easy, but it was very labor-intensive.

But, basically, we had this library of thousands of genes, and we divided into 10 libraries, and we injected each of them to a frog oocytes or eggs. Then, we selected for the single egg that responded. Then, we took the library of genes that was only, now it's a 10th of our original pool. We divided it to 10, and we injected it to 10 eggs and, again, selected for the one, and so on, until, we had a single gene that was responder.

Now, we have this gene, and the gene is very interesting by itself. We are working on characterizing the genes. It turns out that, and this is kind of an interesting story, so we published a paper.

When we published the paper, we were already at Michigan State University. One of the professors here, Jason Gallant, read the paper, and he's working on electrical fish, and he said, "Well, I have a lot of fish DNA. Let's see if we have something similar in my fish." Now, we are comparing different genes from different species of fishes. We get to see that there was some evolutionary development that makes this protein different.

Now, the question is, okay, so you have a protein that is responsive for magnetic field, for electromagnetic fields, now, what can you do with it? Galit Pelled, she is using it for many biomedical applications. From the point of view of synthetic biology, we are looking at it is as a switch.

Basically, we have a switch to turn on and off the cell, if we switch on and off electromagnetic field. An electromagnetic field, you can have it outside the body. You can have it outside your Petri dish, and you can still switch on and off activity.

One of the projects in the lab is to see if you can use it to build a circuit. If you have a switch, and you have these genes that you can detect with MRI, and we have similar genes that we can detect with microscopes, we can detect them with PET, with positron emission tomography. We have all these genes, these are our read out. We have basically the on/off switch, and then we have the light bulb. Now, all we need is to put the different parts in between and make a circuit.

That's one thing, and the circuit you can put something, a reporter gene, something that reports on activity inside the cell, or you can put a therapeutic gene. For example, you can put a gene that encodes to insulin. All right, so suddenly, you can make a circuit that when you switch on and off the switch, when you flip the switch, you have secretion of insulin. We are not there yet, but that's where we are going with our research. You can do it with insulin. You can do it with different proteins, TSH, the hormone that controls thyroid secretion, hormones that can control appetite and mood, and so on. That allows you to build an interface between electronic devices and biological systems.

Now you can have part of the system inside the body and part of the system that is external that could be some sort of a transmitter. The transmitter can be connected to your cell phone using blue tooth. The telephone could be connected through an app to your physician’s office, and you can do a reading, and you can actually initiate different actions.

With synthetic biology, there is much like in computer science, you have the read and the write. Much like what we are doing now, now we are recording. We are recording new information. Then, the person listening to the podcast is reading the information.

Can we do it with biological systems? Can we record information, and can we read it afterwards? This is something that I find very interesting, and it's not something that I'm currently doing in my lab. It's interesting, so I'm going to talk about it.

But, people in the field are trying to figure out a good way to record. For example, you can record on DNA. You can record information on DNA. That's how proteins are encoded. Its DNA has four bases, four nucleotides, and, depend on the order, you can record information.

In computer science, you record information as a series of ones and zeros. That's a binary code. But, you can use code of 123 or 1234. You can basically translate your information, these zeros and ones, into ABCD and record this information.

It turns out that you can record more information on DNA than on a silicon chip. In fact you can, if you just compare the weight, gram to gram, gram of silicon chips and gram of DNA, you can record 10,000 times more information on the DNA. I hope I get the number right, but that's about the measure.

How can you use the synthetic biology systems to record, and how can you use it to read? Because, it's easy to record, but then if it gets scrambled, and you can't read it, what's the point?

People are doing really exciting stuff. I read a paper a while ago that people recorded a movie on a DNA of bacteria. You have a bacteria, and the bacteria has a whole, short movie, but it's a movie. The most fascinating thing about it is that they were actually able to watch the movie afterward.

There's a lot of potential of using these organisms. If you can record a movie on a single bacteria instead of, well, we don't go to Blockbuster anymore, but instead of even downloading them from Netflix, you can just sneeze, and you can share your movie. But, this is, the amount of information you can use it.

Again, people have been using nature and biological material for many years. For the most of it, we use dead biological material. We first have to wait for it to be dead. I'm not just talking about eating and consumption. But, if you build a house of wood, you have to basically wait for the wood to dry up. We use it to dress ourselves. We use it for cotton. We use it for wool. We use it for, obviously, for eating.

But, people developed also live organisms for other things. For example, yeast being used for baking bread and making beer, and these are live organisms that we learned how to use. Now, can we take those organisms and others, and can we use live organisms to be the core of our next computer?

There is so much we can learn from nature. That's in a nutshell, or a little bit more than a nutshell, of what we are doing in the lab, and where the synthetic biology field is going.

White: Assaf, let me ask you if, and you've given some examples already, but if your research progresses well, what are some of the benefits to people or society that might come out of this, and when might we see some of those? It sounds like we are all already.

Gilad: The biomedical applications are very, very important. But, some of them are long-term. Much like with the space program in the late '60s and '70s, we had people going out to space. People thought that conquering space is going to be a big thing. In fact, I was talking to my daughter, and we were talking about space. I told her, "Now with programs like SpaceX, you're probably going to buy a ticket and fly to space the way that you fly to California."

But, then I thought, well, when I was a kid in the '70s, that's what my parents told me, "When you're going to be in your 40s, you're going to go to space every day." But, the fact is that very few people are going to space, so what was the point?

But, I think people now are appreciating more and more that there were a lot of benefits from the space program in terms of technology, and I know in terms of material science. We have all these very cool materials that are derivative of this space program.

An analogy for the synthetic biology is that even if you don't have goals that we're going to see, because people will say, "Well, how will you get this DNA? How will you get it to the people?" There are ways to do genome engineering, and people are being more serious about it, and there are hundreds of clinical trials. 20 years ago, people said, "Well, it's no problem. We can use viruses." Now, people don't really like to use viruses. It's still a pretty good way to do it, and the safety of the viruses has improved dramatically.

But, then people started to think, "Well, we can use stem cells." Stem cells is a good way to deliver, because you can take stem cells from the patient itself, and, now, you can take skin cells or fat cells, and you can either isolate or generate cells from stem cells from these fat or skin tissues, and you can engineer them to express your gene of interest, and then you can transplant them to the same patient.

There is no immune rejection, and so on. This could be a good way to treat many devastating diseases. That was probably in the 2000s. That was the decade of the stem cells.

Now, many labs can produce stem cells. It's not complicated. But, lately, people started to think about immune cells. Viruses might be dangerous. While at the beginning, there was the ethical question. I think some people don't like stem cells that much.

But, now people are talking about immune cells. You can take your immune cells, your T cells or other immune cells, and you can take them out of the body, you can engineer them, and you can train them to recognize tumors. You can use those cells to track down tumors and to attack them and to kill them, actually, identify them in places that other cells or other drugs cannot approach.

One of the projects that we are involved with, and this is a collaboration with a center with Johns Hopkins is that can we take those immune cells and we can engineer them with our specific proteins, and can we image them with MRI? Can we see where those cells are exactly going in the body?

The problem with all these kinds of treatments is then when you inject those cells, you usually can assume where they're going to go. You know they're going to the lymph nodes. You know they might go to the tumor. But, can you actually label them and visualize them and see them with MRI? These are some of the clinical applications.

Again, much like with the space program, this is what we can envision now. But, as science and communication evolves at the rate that it evolves now, you can use it for other things. You can use it to generate new materials. You can use it to generate new ways to solve problems. Obviously, you can use it in agriculture.

Yeah, there are a lot of ways that I can see and imagine how this technology or these technologies can be beneficial, and there are more that even I cannot envision.

White: What are some of the next steps then as you keep working, Assaf?

Gilad: We are working a lot on evolution of those proteins both for imaging and the biological circuits. We are trying to look into different organisms that have different genes. We are testing different kinds of ways to change these proteins.

For example, when we think about evolution, many of us think about mutations. But, we started to think about recombinations. Recombination is where you take two different genes or similar genes or alleles or pieces of DNA and you basically mix them together and see what you get.

Now, intuitively, you think, well, this is not how things are working. But, in real life, this is how most of the biology evolved. This is what happens when you have kids. You take DNA from one parent and from the other, and you mix them together, and you see, well, you get something.

It's usually a good thing that you get. Originally, from recombination, you get good things. From mutations, I don't know. We try to look at different ways to evolve these proteins. We try to look at different organisms that have different features or different genes that we're using.

White: Assaf, talk to me some more too about this collaborative ethos, if you will, at IQ that Chris Contag is developing, and how your work even maybe benefits from this interface of engineering and medicine. I'm guessing that collaboration is what attracted you to MSU.

Gilad: Yes. To being part of the IQ, it's a very unique experience. What Chris did, he did a great thing. He brought people from all over the country, and each of them have different sets of skills. He put them together with a lot of emphasis on collaboration.

Of course, there was a lot of support from the university. We have state-of-the-art equipment, and we have one of the biggest imaging centers. It's pretty impressive. But, I think it's all about the manpower and the human factor.

The IQ is built in a way that people have a lot of access to one another. We have this shared space. The IQ is divided into eight divisions. Each division is like a neighborhood. We have four or five labs, four or five professors with their students who basically live in a block or neighborhood. We share one big lab.

We get to talk with one another. What I like about it, and, honestly, I didn't like it at the beginning, but the way it's built is that the students are sitting next to the windows, so they have their cubicles, then there are the professors' offices. All the professors have offices not next to the window, which I didn't like, because I wanted the window.

It turns out that in Michigan, it's not a big advantage anyways, but, especially that we are facing north. Then, the lab is on the other side of my office. We have glass windows.

What it creates is that I can see what's going on in the lab. I can see the students, what they are doing. They can see me, so if they have good results, they just knock on my window, and I can rush to the lab and see what they are doing. I get to see the results in real time.

But, then, I can always see them in the cubicles, and they can talk to me. We don't have good sound insulation, also, so we can just talk through the wall. I like the fact that we have this glass wall, and we just write things on the wall. Then, if I have some sort of idea, I just write it on this glass wall, and the students can comment on it. They can mark on the wall whatever they think, and we have these discussions.

What's even nicer about it is that if one of my colleagues, one of my neighbors, is walking through, and they see my drawings on the wall that starts a conversation. They say, "Well, you know what? I see you have a problem. I have an instrument in my lab that you can use to solve this problem." We have all these collaborations.

For example, in my division which is synthetic biology, we have one guy that is expert in super resolution microscopy. His name is Jens Schmidt, and he's a brilliant scientist and is working on super resolution microscopy.

Suddenly, we can take our proteins, and we can see a single protein, which we couldn't do anywhere else, just because we were chatting, because I was scrambling something on the wall, and he saw it. We started to chat, and he said, "Well, we have a way to test it." Now, we can. We have these really cool movies of single proteins moving in the membranes. We can expand it.

We have another guy that just started, a new professor, Taeho Kim, and he's making nanoparticles. Suddenly, we have these inorganic chemistry capabilities that we didn't have before. I'm working with Galit Pelled who is working on the other side of the floor at neuroengineering. The way it's built, and the people that we have there are a very unique environment.

White: Well, Assaf, thank you so much for telling me about your research today.

Gilad: Well, thank you for giving me the opportunity.

White: That's Assaf Gilad. He's a professor of biomedical engineering and radiology at Michigan State University. He's part of the IQ Team at MSU as well. IQ is the Institute for Quantitative Health Science and Engineering. There's more online at iq.msu.edu.

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