Pear Biotech Bench to Business: insights on the past, present, and future of synthetic biology with Dr. Jim Collins

Here at Pear, we specialize in backing companies at the pre-seed and seed stages, and we work closely with our founders to bring their breakthrough ideas, technologies, and businesses from 0 to 1. Because we are passionate about the journey from bench to business, we created this series to share stories from leaders in biotech and academia and to highlight the real-world impact of emerging life sciences research and technologies. This post was written by Pear Partner Eddie and Pear PhD Fellow Sarah Jones.

Today, we’re excited to share insights from our discussion with Dr. Jim Collins, Termeer Professor of Medical Engineering and Science at MIT. Jim is a member of the Harvard MIT Health Sciences Technology faculty, a founder of the Wyss Institute for Biologically Inspired Engineering at Harvard, and a member of the Broad Institute of MIT. His work has been recognized with numerous awards and honors over the course of his career, such as the MacArthur “Genius” Award and the Dickson Prize in Medicine.

Hailed as one of the key pioneers of synthetic biology, Dr. Collins has not only published numerous high-profile academic papers, but also has a track record of success as a founder and as an entrepreneur, co-founding companies such as Synlogic, Senti Biosciences, Sherlock Biosciences, Cellarity, and Phare Bio. If all that wasn’t enough, he’s even thrown the first pitch at a Boston Red Sox game. We were lucky to sit down and chat with Jim about his experiences and his perspective on the future of synthetic biology. 

If you prefer listening, here’s a link to the recording! 

Key takeaways:

1. At its conception, synthetic biology was simply a ‘bottom-up’ approach to molecular biology utilized by collaborative, interdisciplinary scientists. 

• In the late 90’s, Jim’s focus in biology began to shift: rather than continuing to explore biology at the whole organism or tissue level, he found himself more excited about molecular-scale biology. After speaking with some bioengineering faculty members at Boston University who were interested in his background in physics and engineering, Jim was quickly invited to join the department. From there, his interest in designing and engineering natural networks and biological processes flourished. 
• At that time, however, bioengineers weren’t yet able to reverse engineer biological systems and exert precise control at the molecular scale. He asked, 

Could we take a bottom-up approach to molecular biology? Could we build circuits from the ground up as ways to both test our physical and mathematical notions and also to create biotech capabilities?

• Though it didn’t start out as a quest to launch a new scientific field, Jim’s work contributed heavily to what would become the foundation of synthetic biology. He noted the value in bringing together scientists with diverse backgrounds to work on the same problems; for example, neuroscience had greatly benefitted from the introduction of mathematical models to describe complex neural systems. In a similar way, physicists, mathematicians, and molecular biologists began to find themselves interested in the same sorts of complex biological questions that could not be answered by any one discipline alone. 
• Jim also acknowledged that in the early days, the tools to engineer gene networks and molecular pathways did not exist, yet his team could envision a future in which gene networks could be described and designed using elegant mathematical models and a modular set of biological tools. This goal helped to propel synthetic biology into existence.

2. The ability to program genetic circuits marked the beginning of synthetic biology and allowed efforts within the field to quickly progress. 

• One notable 1995 publication in Science authored by Lucy Shapiro and Harley McAdams that was titled ‘Circuit simulation of genetic networks’ helped to shape Jim’s efforts in programming genetic circuits. The paper explored parallels between electrical circuits and genetic circuits and used mathematical modeling to accurately describe the bacteriophage lambda lysis-lysogeny decision circuit. In this circuit, bacteriophages that have infected bacteria cells must decide whether they are going to kill the cell or remain dormant, sparing the cell’s life.
• Such work helped to bridge the gap between bioengineering and molecular biology at a time when many bioengineers felt largely excluded from the world of molecular biology.
• To prove that genetic engineering was possible, the Collins lab worked to develop a genetic toggle switch in the form of a synthetic, bi-stable regulatory genetic network that could be switched ‘on’ or ‘off’ by applying heat or a particular chemical stimuli. This is significant because researchers could now add well-defined genetic networks to cells in order to precisely control their behavior or output.
• This work by Gardner et al. was published in 2000 in the prestigious scientific journal, Nature and was titled “Construction of a genetic toggle switch in Escherichia coli.” Interestingly, in the same issue of Nature, work by Mike Elowitz’s lab at Caltech also outlined the development of a synthetic gene circuit in E. coli. Their system, dubbed the ‘Repressilator,’ was also a regulatory network in which three feedback loops could oscillate over time and change the status of the cells. Basically, it was three genes in a ring where gene A could inhibit gene B, which could inhibit gene C, which could then inhibit gene A, creating an oscillatory network. 
• This critical body of work and scientific discovery both demonstrated that genetic engineering was possible and highlighted tools and methods that could be used to modulate molecular systems. 

3. To expand the repertoire of synthetic biology, Jim has co-founded two companies, Synlogic and Senti Biosciences, that are aimed at targeting the gut microbiome and engineering the mammalian system.

• While initial excitement for synthetic biology applications centered on biofuel generation, the small scale bioreactors were never a match for fossil fuel companies. The paradigm in synthetic biology started shifting away from biofuel generation in the early 2000s to focus on the microbiome and its role in human disease. 
• As local venture capitalists approached Jim and asked about what could actually be done with synthetic biology, it became clear to Jim that there were two main directions he could pursue. 

One was…an opportunity to create a picks and shovels company in synthetic biology. So, coming to create additional components or capacity to address a broad range of indications and applications, be it biofuels, industrial applications, therapeutics. The second was that you could engineer microbes to be living therapeutics, and in some cases, living diagnostics.

• Jim partnered with Tim Lu, his former student and eventual coworker at MIT, to start Synlogic. One early direction of Synlogic was tackling a rare genetic metabolic disorder, phenylketonuria (PKU), that causes the amino acid phenylalanine to build up in the body. The idea was that they could engineer a microbe that could break down this byproduct and thereby eliminate the negative effects of the disease. This approach relied on the ability of the synthetic biologist to directly harness and control cell behavior via genetic engineering. 
• Synlogic is also working on enzymes that produce therapeutic molecules instead of degrading toxic ones. The company now has efforts in inflammatory bowel disease and Lyme disease and has partnered with Roche to advance its pipeline. 
• By around 2015, synthetic biology had continued to grow as an academic discipline and had moved beyond microbes to mammalian cells. Jim had since moved his lab from Boston University to MIT, and it wasn’t long before he was once again collaborating with Tim Lu, this time to apply synthetic biology in a mammalian system. This marked the start of Senti Biosciences, a company aimed at creating ‘smart medicines’ using genetic circuits.

We began to consider the possibility that we could do a mammalian version of Synlogic. Could we begin to really advance the development of human cell therapy and gene therapy using synthetic genes and gene circuits to create smart medicines? Having therapeutics that could sense their environment, sense the disease state or sense the disease target and produce therapeutics in a meaningful, decision-making way… was an exciting notion.

4. Historically, a lack of support from the venture community and insufficient infrastructure have been challenges for the diagnostics space.

• Another company Jim helped start, Sherlock Biosciences, also leverages synthetic biology but operates in the diagnostic space. Although the diagnostic space is a notoriously challenging one, Sherlock was founded with the goal of combining approaches from synthetic biology and CRISPR technology to develop next-generation molecular diagnostics for at-home tests.
• While many of the companies started right before the COVID-19 pandemic ultimately didn’t make it long-term, the team at Sherlock was able to quickly pivot and develop a CRISPR-based COVID-19 diagnostic that gained FDA-approval in May 2020. Notably, this test was the very first FDA-approved CRISPR product. 
• Jim explained that the difficulties facing a company trying to operate in the diagnostics space are twofold:
  • (1) there is a lack of infrastructure for things like at-home testing, point-of-care testing, or nucleic acid tests
  • (2) there is a general lack of support for diagnostic companies in the venture community
• Diagnostics companies are essentially valued as a multiple of revenue. In contrast, therapeutic companies can be valued based on projections 10-20 years in the future without the requirement of existing revenue. Combine this with the fact that wins tend to be much larger in the therapeutics space, diagnostic discovery and development have largely been set to the side. 
• While COVID-19 did help to bring interest to the sector, funding and infrastructure continue to limit breakthroughs in diagnostics. 

5. Desperate for new antibiotics: a combination of synthetic biology, Machine Learning (ML) and in silico modeling has so far been fruitful.

• With a challenging funding landscape, antibiotics have also been long-neglected by VC and industry. Despite this, Jim’s team was able to secure funding through The Audacious Project, a philanthropic effort put together by TED to support their work in antibiotic discovery. The funded project involved developing deep learning based models that could both discover and design novel antibiotics against some of the world’s nastiest pathogens. In fact, the team found success when they discovered a very powerful antibiotic called halicin. 
• Recently published in Nature, an article by the Collins lab highlights their continued efforts in the “Discovery of a structural class of antibiotics using explainable deep learning.” 
• Jim stressed the urgency for new antibiotic development: the pipeline has been drying up, but the demand has only increased. Acquired antibiotic resistance is also a significant problem that hasn’t yet been resolved.
• As new, powerful antibiotics are developed, they become the last-line of defense against the worst, most deadly pathogens. However, drugs used as a last-line of defense don’t make it off the shelves very often: this means that there is less financial motivation to develop particularly potent antibiotics. To address this, Jim noted that we are going to need a new financial model to sufficiently support research in this space.

6. Past the hype cycle: the synthetic biology of tomorrow.

• The field has experienced its fair share of ups and downs. In speaking with Jim, it’s clear that the roller coaster of high expectations and disappointing failures has not diminished his excitement about the future of synthetic biology. 
• In 2004, the initial hype cycle was centered on biofuels and their potential to replace fossil fuels. Unrealistic expectations combined with the high cost of biofuel production led to disappointment; people began to question whether or not synthetic biology could deliver. 
• In the second hype cycle, bold claims and an attitude that synbio could solve every problem in the world led to yet another massive let-down and shift in attitude towards the field. 

I think the markets haven’t kept pace with the public statements that are being made by some of the high priests in the field. And that’s a shame. I do think synthetic biology will emerge as one of the dominant technologies of this century. Our ability to engineer biology gives us capabilities that can address many of the big challenges that we have. But it’s still going to take a lot of time, it’s still very hard to engineer biology, and biology is not yet an engineering discipline.

• Successes in areas where biology still outcompetes chemistry have helped to put some points back on the board for synthetic biology. Increasing utilization in therapeutic development has leveraged the efficiency of biological systems and will help to pave the way for the next way of discoveries in the field. 
• Technologies like cell-free systems also have Jim excited about the future of synthetic biology. 

Get to know Jim Collins: 

Early career and developing a passion for science: 

• Jim comes from a family of engineers and mathematicians and has always found himself wanting to do science. Jim explained that when he was four years old, his dad was a part of a team that designed an altimeter for Apollo 11. 
• Another seminal event that influenced Jim’s decision to become a scientist was the decline of his grandfather’s health after a series of strokes left him hemiplegic. After watching someone he loved not receive the care or have treatment options that could restore function, Jim was inspired to pursue biomedical engineering. 
• Once he realized that he could interface with clinicians, entrepreneurs, and policy-makers as a professor, he realized that was the path for him.

Advice for early-stage founders:

• Find a strong business team early on to help find market fit and to guide the development of your final product. Young scientists are not trained to be good CEO’s, and it’s often challenging to navigate these decisions if you don’t have the experience.
• Make sure your strategy has a real market pull and is differentiated from other approaches.