Synthetic Biology and the Pursuit of Living Diagnostics

Thought LeadersJames J. CollinsTermeer Professor of Medical Engineering and ScienceMassachusetts Institute of Technology

In this interview, Professor James J. Collins, co-founder of the field of Synthetic Biology, discusses his journey to founding the field of synthetic biology and the potential of next-generation diagnostics and living therapeutics.

How did your early interest in science develop?

I come from a technical family. My mom studied and taught mathematics, and my dad is an electrical engineer who worked in the aerospace industry. Notably, his team helped develop an optical system for the Apollo 11 lunar module.

I was four years old and remember watching the Apollo 11 astronauts land on the moon—it was a very proud and happy day in our household. My dad was great at bringing home technology that he and his colleagues were developing, and he set up an electronics lab in our basement. My brother, sisters, and I were exposed to many different sciences.

When I was seven years old, my dad’s father—my grandfather—lost his vision. Several years later, my mom’s father had a series of strokes and became hemiplegic, losing sensation and significant control of half of his body. While I saw my dad and his colleagues creating amazing technology to send things into space and bring them back, I saw little being done to help the two people I cared for deeply to regain the function they had lost due to illness and injury.

That motivated me to consider how I could develop technology to enhance human health and specifically restore function to those who had lost it due to injury, disease, or aging.

How did your academic journey progress after high school, and what was your college experience like?

I came out of high school in 1983, just as biomedical engineering was beginning to form as an undergraduate major, but few programs were available. I then went on to study Physics at Holy Cross, where I also received a broad liberal arts education in biology, chemistry, mathematics, psychology, and arts and humanities.

Having such a broad view of different disciplines and the ability to communicate across them was transformative for me. From there, I did a doctorate in medical engineering at the University of Oxford and began working on biomechanics and neural control, studying how people walk, run, jump, lift, and maintain balance. That became the primary focus of my work as a professor for the first 10 years of my professorial career throughout the 1990s.

Your broad scientific training seems to have positioned you well for the eventual foundation of synthetic biology, which began with a 2000 paper. Can you tell me about that paper and its significance?

My liberal arts education at Holy Cross, a marvelous Jesuit school, prepared me well for two big aspects of my career. One was dealing with the emergence of interdisciplinary scientific work in the American academy. When I came out of graduate work, interdisciplinary work was viewed as being less rigorous than the more traditional disciplines.

But interdisciplinary efforts at Boston University, where I started my academic career as a professor, were beginning to emerge, and quite interesting problems and questions were arising at the interface of disciplines—physics and biology, chemistry and biology, etc.—and my broad liberal arts education set me up well. Second is that I have changed fields multiple times, and I think the training I received at Holy Cross, both in critical thinking and communication, set me up well to make those transitions where I could learn a new scientific language and be able to communicate with the folks in those disciplines.

Our effort that helped launch synthetic biology was interesting. This was done with Tim Gardner, my first graduate student in what became synthetic biology. Tim and I were intrigued—what could we do in molecular biology as engineers and physicists? There was an emerging interest in studying systems biology at the time. Specifically, could you reverse engineer natural biomolecular networks on the heels of the amazing output coming from the Human Genome Project, as different groups were beginning to identify the components of our genome and cells on a large scale in a high-throughput manner? The excitement then became: could you combine those components in networks and pathways?

Tim and I initially considered that problem, but the needed data were unavailable. Microarray technology—an older technology no longer used—had just appeared, allowing us to simultaneously measure the output of multiple genes inside a living cell. But they were not yet available at a public level where a group like ours, which did not have a wet lab or any money in this space, could reasonably begin to reverse engineer natural biomolecular networks.

We got excited instead with the notion of forward engineering synthetic biological circuits—namely, could we put molecular components together into circuits and program them to exhibit desired functions? We came up with modeling and designing a genetic toggle switch. This was a simple system of two genes that were arranged in a mutually inhibitory network that could exist in one of two stable states: gene one is on and gene two is off, or gene two is on and gene one is off. You could flip it between those states by applying a chemical pulse.

Tim and I did not have any grant money to work on this project. We did not even have a wet lab. So, we started with mathematical modeling. Looking back, this was in the late ’90s, and we were motivated to build the genetic toggle switch primarily to validate our mathematical model. I had come out of the math biology community as a graduate student and early faculty member. It was a fantastically supportive, engaging community that developed in the 1960s and continued through the ’70s, ’80s, and ’90s.

Most of the efforts in the math biology community at that time focused on the developed models, and few, if any, experiments were being done. But in the early ’90s, several groups in the neurosciences began looking at very small systems of interacting neurons in the stomatogastric ganglion and lamprey spinal cord—efforts done by my colleague at BU, Nancy Kopell, Eve Marder at Brandeis, Avis Cohen at Cornell, and Bard Ermentrout at the University of Pittsburgh. It was fascinating to see the interplay between modeling and experiment.

Tim and I thought we could do this in molecular biology. We teamed up with Charles Cantor, who had a wet lab at BU, and we began building genetic toggle switches in bacteria. In just a few months, Tim successfully built a bistable toggle switch.

What was interesting historically—and kind of what was in the air at the time—was that unbeknownst to us, at Princeton University, Michael Elowitz, a Ph.D. student with Stan Leibler, who were both physicists also working in the molecular biology department, had very similar ideas to ours. They wanted to tinker as physicists in molecular biology and put together biological circuits inside cells.

Our teams both ended up working on E. coli and dynamical systems modeling. We both used the same biomolecular components. We assembled a two-gene circuit where gene A would inhibit gene B and gene B would inhibit gene A. Elowitz and Leibler put together a three-gene circuit where gene A inhibited gene B, gene B inhibited gene C, and gene C inhibited gen A to create a ring oscillator—also motivated by electronics, as was our toggle switch. Theirs oscillated, whereas ours could stably be flipped between two stable states.

We were completely unaware of their work or motivation. Our pieces were published together back-to-back in a January 2000 issue of Nature. It was a flashpoint for physicists, engineers, and mathematicians wanting to move into molecular biology—giving them an invitation to come in along with a toolset and entry points. These papers ended up unintentionally launching the field of synthetic biology. We intended to do interesting, cool work that we could build upon, but it had a much bigger impact than anticipated or planned.

How do you reflect on the progress and evolution of the field of synthetic biology over the past 25 years?

In my talk at Pittcon, I mentioned that the field has moved from being an emerging field to a maturing field. Twenty-five years on, I am proud of what the field has done in academia and increasingly excited about what can be translated out of academia into different aspects of society.

It is still a young field with several hundred labs worldwide. Many major universities have research centers, programs, and institutes, and hundreds of companies have launched.

One of the more exciting areas is the emergence of artificial intelligence combined with synthetic biology to create what is being called generative biology. It is viewed as synthetic biology 2.0.

Young people are intrigued by how biology can be harnessed as technology to address some of the world's biggest problems. When we look back on this century, two of the dominant areas will likely be artificial intelligence and synthetic biology.

Synthetic biology has played a role in diagnostics in infectious diseases. Can you explain the paper-based diagnostics you have worked on?

This is an effort that we pioneered a little over a decade ago, and it was based on the work of my then-postdoc Keith Pardee, now a professor at the University of Toronto. Keith discovered we could freeze-dry cell-free extracts and synthetic biology components, including biosensors, onto paper and rehydrate them later.

What had been freeze-dried on paper now behaved as if it was in a Petri dish, a test tube, or even inside a living cell. We used this to create paper-based diagnostics using simple RNA sensors—RNA switches that could detect RNA output from pathogens of interest.

We initially focused on using these paper-based diagnostics to detect antibiotic resistance in patient samples in an emergency room. Keith developed several sensors to detect key markers of antibiotic resistance and give a readout in, for example, 30 to 60 minutes, so within that golden window of an hour for an infectious disease doctor.

As we were advancing that technology, we had the Ebola outbreak. During our submission to the journal Cell, Keith and Alex Green, another postdoc in our lab at the time and now a professor of biomedical engineering at Boston University, teamed up and were able to design two dozen different sensors for Ebola. This was not used as part of the outbreak because they were no longer needed by the time we published the work.

About a year and a half later, we were rallied by MIT leadership to consider whether we could use the platform to respond to the Zika outbreak.

With Keith, Alex, and several young people in our lab, we developed paper-based sensors based on our RNA switches and CRISPR-based components. We also developed a paper-based system deployed in six different countries as part of the outbreak, both as a surveillance tool and a research tool, including by the Red Cross.

Keith Pardee, during the COVID pandemic, conducted a field-based clinical trial in Colombia, Ecuador, and Brazil using paper-based sensors to detect Zika and Chikungunya and showed that these incredibly inexpensive, portable, easy-to-use systems could have sensitivities and specificities in the high 90 percent range.

Although not as high as PCR, which has sensitivites and specificities near or at 100 percent, this approach is quite close. Moreover, our platform does not require expensive equipment or even a laboratory. It can be done in a remote setting. I am very excited about where that effort went and where it continues to go. It has huge potential for impacting global health and leading to next-generation at-home diagnostics.

The COVID-19 pandemic was also a target of your work. Can you explain your contributions to the diagnosis of this infectious disease?

Based on our Zika effort, which included both a synthetic biology component and a CRISPR component, Feng Zhang, my colleague at MIT and the Broad Institute, reached out to us and asked if we wanted to collaborate on a new CRISPR platform that he and his team were developing based on Cas13, an enzyme related to Cas9.

We did, and we created a platform called SHERLOCK that could detect RNA using CRISPR at a very high sensitivity level. Feng and I launched a company called Sherlock Biosciences along with David Walt. SHERLOCK’s mission was to advance our CRISPR and synthetic biology diagnostics toward applications in infectious diseases and other clinical challenges, including clinical study designs.

Very early in the pandemic, SHERLOCK teamed up with my group at the Wyss Institute of Harvard to create a CLIA lab-based system based on CRISPR to detect COVID, which became the first FDA-authorized CRISPR product in May 2020.

At SHERLOCK, where I was on the board and in the SAB, we did not think anybody should profit from the pandemic. So, we set up a foundation called the 221b Foundation, named after Sherlock Holmes' fictional address on Baker Street in London. We made our IP and our tech available to anyone who wanted to use it to develop a COVID-based test. All profits from our efforts and those that licensed the tech were returned to the foundation and used to support STEM efforts for underrepresented minorities in the United States.

Notably, five global diagnostics companies picked up our IP and used it worldwide during the pandemic. At its peak, these companies ran about 10 million tests per year, and Nepal adopted our test as its national test.

That was early in the pandemic. In an effort led by Peter Nguyen, a senior postdoc of mine at the time at the Wyss Institute, we realized we could embed our freeze-dried, cell-free synthetic biology technology into clothing to create wearable diagnostics for healthcare professionals, first responders, and military personnel.

Before the pandemic, we were advancing the notion of the next-generation lab coat. The idea was that healthcare personnel could wear this as they made rounds around a hospital and use these wearable sensors to determine whether they had been exposed to a pathogen or an outbreak in the hospital.

When we submitted our paper based on this technology to Nature Biotechnology, the editors were quite excited about the platform but challenged us to develop a killer app—pun intended. Before the pandemic, we focused on using technology to create a wearable Ebola diagnostic. We were making advances along these lines when the pandemic hit.

Peter Nguyen, Luis Soenksen, a grad student then postdoc in our lab, and Nina Donghia, a research scientist in our group, thought we could use the platform to create a wearable diagnostic. In this case, the wearable would be in the form of a face mask. The team had the idea of creating a small insert that could be added to any face mask. The notion was that through the normal act of talking, breathing, coughing, or sneezing, if you are infected, you are giving off water vapor, which contained viral particles.

Our team developed a highly sensitive, highly specific sensor that could be incorporated into these diagnostic face masks and detect down to 500 viral particles. We showed that we could multiplex the system so we can use it for SARS-CoV-2, RSV, and seasonal flu.

We are very excited about where this technology could go as we prepare for the next outbreak, which, unfortunately, is coming. We do not know when or where, but it is coming. This technology, along with many others, will be quite useful as surveillance and research tools.

How has Sherlock Biosciences advanced its technology for at-home diagnostics?

Sherlock Biosciences has advanced the technology for low-power and even no-power at-home tests. They are just finishing a clinical trial using it to detect sexually transmitted infections (STIs), specifically chlamydia and gonorrhea. SHERLOCK was recently acquired by OraSure, a major diagnostics firm, and OraSure is excited about leveraging our technology. They are completing the trial to expand into the at-home market for STIs.

Looking ahead, we will likely use nucleic acid-based at-home diagnostic tests for the next outbreak or pandemic rather than the antigen tests most of us used during COVID. The nucleic acid tests will be easier, faster to develop, and more sensitive and accurate.

You also work within the field of living diagnostics and therapeutics. Could you explain these fields and the work you have done in them?

Over a decade ago, we became intrigued by engineering microbes to serve as living diagnostics and living therapeutics. Specifically, the Gates Foundation challenged us to engineer microbes that could detect and treat cholera.

In an effort led by Ning Mao, Ewen Cameron, and Andres Cubillos in our lab, the team engineered Lactococcus lactis by repurposing quorum sensing systems out of cholera to create a living diagnostic. This engineered L. lactis could detect quorum-sensing molecules produced by cholera and trigger a synthetic biology circuit inside the microbe.

The engineered bacteria produced an enzyme that changed the color of your stool, signaling an infection. If your stool turned purple, you would know that you had been exposed to cholera and possibly had an early or more mature infection.

This work also built on earlier research with Pam Silver, where we engineered E. coli using a toggle switch to report on the presence of certain drugs in the gut. The concept of living diagnostics could be extended to other infections as well. We have been very excited about moving toward living therapeutics, and notably showed that our engneered L. lactis strain could also prevent and treat cholera infections by producing lactic acid.

We have also focused on how we can manage antibiotic-induced gut dysbiosis. In a follow-up effort, Andres Cubillos was able to engineer L. lactis with split beta-lactamases integrated into its genome. When expressed, these enzymes combine outside the cell to break down beta-lactam antibiotics in the gut, but only when the antibiotics are not needed. This is especially important since only 10% of infections are in the gut, and the remaining 90% of the time, you do not want antibiotics messing with your gut microbiome.

Andres and Raphaël Gayet, another lab postdoc in our lab, just launched Florey Biosciences. This company aims to use engineered probiotics as a medicinal food to help manage gut dysbiosis and potentially improve outcomes for clinical patients, especially cancer patients undergoing cell therapies.

You mentioned AI earlier. Is that what you think the future of synthetic biology looks like?

AI will play a crucial role in the future of synthetic biology. If I think back to those early efforts with Tim Gardner and compare them to the work Michael Elowitz and Stan Leibler did, modeling was at the core.

Early on, modeling often meant ordinary differential equations—simple equations that you could simulate or sometimes solve analytically. These approaches worked well for smaller, simpler biological systems that could be represented mathematically.

But as we move toward more complex biological systems, we will need more advanced modeling. And AI, particularly deep learning, will be key in helping us tackle that complexity. Beyond modeling, AI can also help us infer design principles that have evolved in biological systems over millions, if not billions, of years.

To make this happen, though, we need the right data sets. Currently, much of the focus in the DNA and RNA space is on sequence and classification, but to truly unlock predictive models and generative biology, we need more data that connect function to sequence and structure. Only then will we be able to design predictable systems based on sequence, structure and function.

What is next immediately for you and your lab?

We are working on many exciting projects. Notably, we are focusing on using AI in biological design at the RNA level and for synthetic circuits.

We are particularly excited about living therapeutics, especially looking into gut-related conditions like inflammatory bowel disease and exploring ways to expand synthetic biology for treating infectious diseases. Another big area we are diving into is RNA. Our goal is to leverage synthetic biology alongside AI to develop next-generation RNA control elements for RNA therapeutics and broader biotech applications.

About James J. Collins

Dr. James J. Collins is the Termeer Professor of Medical Engineering & Science and Professor of Biological Engineering at the Massachusetts Institute of Technology (MIT). He is a pioneering figure in synthetic biology, renowned for engineering genetic circuits that reprogram cells to perform novel functions. His innovative work has led to advancements in diagnostics, therapeutics, and the application of artificial intelligence in antibiotic discovery.

Dr. Collins holds a B.A. in Physics from the College of the Holy Cross and a D.Phil. in Medical Engineering from the University of Oxford, where he was a Rhodes Scholar. He has been honored with numerous awards, including a MacArthur Fellowship, the Dickson Prize in Medicine, and election to the National Academies of Sciences, Engineering, and Medicine. His research group at MIT focuses on synthetic and systems biology, particularly in combating antibiotic resistance and developing innovative diagnostic tools and therapeutics.

About Pittcon

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