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Blending machine learning and biology to predict cell fates and other changes
Greta Friar | Whitehead Institute
February 1, 2022

Imagine a ball thrown in the air: it curves up, then down, tracing an arc to a point on the ground some distance away. The path of the ball can be described with a simple mathematical equation, and if you know the equation, you can figure out where the ball is going to land. Biological systems tend to be harder to forecast, but Whitehead Institute Member Jonathan Weissman, postdoc in his lab Xiaojie Qiu, and collaborators at the University of Pittsburgh School of Medicine are working on making the path taken by cells as predictable as the arc of a ball. Rather than looking at how cells move through space, they are considering how cells change with time.

Weissman, Qiu, and collaborators Jianhua Xing, professor of computational and systems biology at the University of Pittsburgh School of Medicine, and Xing lab graduate student Yan Zhang have built a machine learning framework that can define the mathematical equations describing a cell’s trajectory from one state to another, such as its development from a stem cell into one of several different types of mature cell. The framework, called dynamo, can also be used to figure out the underlying mechanisms—the specific cocktail of gene activity—driving changes in the cell. Researchers could potentially use these insights to manipulate cells into taking one path instead of another, a common goal in biomedical research and regenerative medicine.  

The researchers describe dynamo in a paper published in the journal Cell on February 1. They explain the framework’s many analytical capabilities and use it to help understand mechanisms of human blood cell production, such as why one type of blood cell forms first (appears more rapidly than others).

“Our goal is to move towards a more quantitative version of single cell biology,” Qiu says. “We want to be able to map how a cell changes in relation to the interplay of regulatory genes as accurately as an astronomer can chart a planet’s movement in relation to gravity, and then we want to understand and be able to control those changes.”

How to map a cell’s future journey

 Dynamo uses data from many individual cells to come up with its equations. The main information that it requires is how the expression of different genes in a cell changes from moment to moment. The researchers estimate this by looking at changes in the amount of RNA over time, because RNA is a measurable product of gene expression. In the same way that knowing the starting position and velocity of a ball is necessary to understand the arc it will follow, researchers use the starting levels of RNAs and how those RNA levels are changing to predict the path of the cell. However, calculating changes in the amount of RNA from single cell sequencing data is challenging, because sequencing only measures RNA once. Researchers must then use clues like RNA-being-made at the time of sequencing and equations for RNA turnover to estimate how RNA levels were changing. Qiu and colleagues had to improve on previous methods in several ways in order to get clean enough measurements for dynamo to work. In particular, they used a recently developed experimental method that tags new RNA to distinguish it from old RNA, and combined this with sophisticated mathematical modeling, to overcome limitations of older estimation approaches.

The researchers’ next challenge was to move from observing cells at discrete points in time to a continuous picture of how cells change. The difference is like switching from a map showing only landmarks to a map that shows the uninterrupted landscape, making it possible to trace the paths between landmarks. Led by Qiu and Zhang, the group used machine learning to reveal continuous functions that define these spaces. 

“There have been tremendous advances in methods for broadly profiling transcriptomes and other ‘omic’ information with single-cell resolution. The analytical tools for exploring these data, however, to date have been descriptive instead of predictive. With a continuous function, you can start to do things that weren’t possible with just accurately sampled cells at different states. For example, you can ask: if I changed one transcription factor, how is it going to change the expression of the other genes?” says Weissman, who is also a professor of biology at the Massachusetts Institute of Technology (MIT), a member of the Koch Institute for Integrative Biology Research at MIT, and an investigator of the Howard Hughes Medical Institute.

Dynamo can visualize these functions by turning them into math-based maps. The terrain of each map is determined by factors like the relative expression of key genes. A cell’s starting place on the map is determined by its current gene expression dynamics. Once you know where the cell starts, you can trace the path from that spot to find out where the cell will end up.

The researchers confirmed dynamo’s cell fate predictions by testing it against cloned cells–cells that share the same genetics and ancestry. One of two nearly-identical clones would be sequenced while the other clone went on to differentiate. Dynamo’s predictions for what would have happened to each sequenced cell matched what happened to its clone.

Moving from math to biological insight and non-trivial predictions

With a continuous function for a cell’s path over time determined, dynamo can then gain insights into the underlying biological mechanisms. Calculating derivatives of the function provides a wealth of information, for example by allowing researchers to determine the functional relationships between genes—whether and how they regulate each other. Calculating acceleration can show that a gene’s expression is growing or shrinking quickly even when its current level is low, and can be used to reveal which genes play key roles in determining a cell’s fate very early in the cell’s trajectory. The researchers tested their tools on blood cells, which have a large and branching differentiation tree. Together with blood cell expert Vijay Sankaran of Boston Children’s Hospital, the Dana-Farber Cancer Institute, Harvard Medical School, and Broad Institute of MIT and Harvard, and Eric Lander of Broad Institute, they found that dynamo accurately mapped blood cell differentiation and confirmed a recent finding that one type of blood cell, megakaryocytes, forms earlier than others. Dynamo also discovered the mechanism behind this early differentiation: the gene that drives megakaryocyte differentiation, FLI1, can self-activate, and because of this is present at relatively high levels early on in progenitor cells. This predisposes the progenitors to differentiate into megakaryocytes first.

The researchers hope that dynamo could not only help them understand how cells transition from one state to another, but also guide researchers in controlling this. To this end, dynamo includes tools to simulate how cells will change based on different manipulations, and a method to find the most efficient path from one cell state to another. These tools provide a powerful framework for researchers to predict how to optimally reprogram any cell type to another, a fundamental challenge in stem cell biology and regenerative medicine, as well as to generate hypotheses of how other genetic changes will alter cells’ fate. There are a variety of possible applications.

“If we devise a set of equations that can describe how genes within a cell regulate each other, we can computationally describe how to transform terminally differentiated cells into stem cells, or predict how a cancer cell may respond to various combinations of drugs that would be impractical to test experimentally,” Xing says.

Dynamo’s computational modeling can be used to predict the most likely path that a cell will follow when reprogramming one cell type to another, as well as the path that a cell will take after specific genetic manipulations. 

Dynamo moves beyond merely descriptive and statistical analyses of single cell sequencing data to derive a predictive theory of cell fate transitions. The dynamo toolset can provide deep insights into how cells change over time, hopefully making cells’ trajectories as predictable for researchers as the arc of a ball, and therefore also as easy to change as switching up a pitch.

School of Science announces 2022 Infinite Expansion Awards

Eight postdocs and research scientists within the School of Science honored for contributions to the Institute.

School of Science
January 28, 2022

The MIT School of Science has announced eight postdocs and research scientists as recipients of the 2022 Infinite Expansion Award.

The award, formerly known as the Infinite Kilometer Award, was created in 2012 to highlight extraordinary members of the MIT science community. The awardees are nominated not only for their research, but for going above and beyond in mentoring junior colleagues, participating in educational programs, and contributing to their departments, labs, and research centers, the school, and the Institute.

The 2022 School of Science Infinite Expansion winners are:

  • Héctor de Jesús-Cortés, a postdoc in the Picower Institute for Learning and Memory, nominated by professor and Department of Brain and Cognitive Sciences (BCS) head Michale Fee, professor and McGovern Institute for Brain Research Director Robert Desimone, professor and Picower Institute Director Li-Huei Tsai, professor and associate BCS head Laura Schulz, associate professor and associate BCS head Joshua McDermott, and professor and BCS Postdoc Officer Mark Bear for his “awe-inspiring commitment of time and energy to research, outreach, education, mentorship, and community;”
  • Harold Erbin, a postdoc in the Laboratory for Nuclear Science’s Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), nominated by professor and IAIFI Director Jesse Thaler, associate professor and IAIFI Deputy Director Mike Williams, and associate professor and IAIFI Early Career and Equity Committee Chair Tracy Slatyer for “provid[ing] exemplary service on the IAIFI Early Career and Equity Committee” and being “actively involved in many other IAIFI community building efforts;”
  • Megan Hill, a postdoc in the Department of Chemistry, nominated by Professor Jeremiah Johnson for being an “outstanding scientist” who has “also made exceptional contributions to our community through her mentorship activities and participation in Women in Chemistry;”
  • Kevin Kuns, a postdoc in the Kavli Institute for Astrophysics and Space Research, nominated by Associate Professor Matthew Evans for “consistently go[ing] beyond expectations;”
  • Xingcheng Lin, a postdoc in the Department of Chemistry, nominated by Associate Professor Bin Zhang for being “very talented, extremely hardworking, and genuinely enthusiastic about science;”
  • Alexandra Pike, a postdoc in the Department of Biology, nominated by Professor Stephen Bell for “not only excel[ing] in the laboratory” but also being “an exemplary citizen in the biology department, contributing to teaching, community, and to improving diversity, equity, and inclusion in the department;”
  • Nora Shipp, a postdoc with the Kavli Institute for Astrophysics and Space Research, nominated by Assistant Professor Lina Necib for being “independent, efficient, with great leadership qualities” with “impeccable” research; and
  • Jakob Voigts, a research scientist in the McGovern Institute for Brain Research, nominated by Associate Professor Mark Harnett and his laboratory for “contribut[ing] to the growth and development of the lab and its members in numerous and irreplaceable ways.”

Winners are honored with a monetary award and will be celebrated with family, friends, and nominators at a later date, along with recipients of the Infinite Mile Award.

Life Sciences at MIT is unmatched

Paul Schimmel and family’s recent donation can match up to $25 million in additional funds to support life sciences at MIT

Julia Keller | MIT School of Science
January 18, 2022

This past August, the Department of Biology and the School of Science announced the creation of the Schimmel Family Program for Life Sciences at MIT as a result of the $50 million dollar donation from Professor Emeritus Paul Schimmel PhD ’66 and his family. Half of this support is designated to be matched with donations from other supporters of the department and the life sciences research enterprise. Now, with a recent donation from Institute Professor Phillip Sharp — a friend of the Schimmels and another lifelong supporter of biology — the matching funds, and opportunities for life sciences research at MIT, continue to be unlocked.

“The life sciences educational enterprise spreads across a dozen departments at MIT,” says Schimmel of the impact of this giving. “What makes the Biology Department and the life sciences at MIT so extraordinary is the singular ability to transfer knowledge and inventions to society for its benefit.”

Schimmel and Sharp, well-matched

In August 2021, the Schimmel family committed $50 million to support the life sciences at MIT. The family’s initial gift of $25 million established the Schimmel Family Program for Life Sciences and was matched with $25 million secured from other sources in support of the Department of Biology. The remaining $25 million from the Schimmel family now serves as matching funds for future gifts supporting the life sciences. To date, $7 million in new gifts from other donors have been committed toward this effort, eliciting an additional $7 million in matching funds from the Schimmel family.

Professor Sharp is among those supporters who have joined his former colleague and friend, Paul Schimmel.

“Paul and I taught together, shared an interest in RNA biology, and have remained close friends since his move to Scripps Institute,” says Sharp of his career-long friendship with Schimmel, who is the Ernst and Jean Hahn Professor at the Skaggs Institute for Chemical Biology at the Scripps Research Institute.

Though Schimmel formally left MIT for the Scripps Institute in 1997, he remained actively involved in supporting MIT’s research enterprise, with a particular focus on MIT graduate students, through his role on the Biology Visiting Committee.

Sharp and Schimmel agree that the success of graduate students remains key to the long-term sustainability of the life sciences at MIT. “We share a passion for supporting and engaging with the next generation of outstanding biologists, scientists, and leaders — well represented among MIT graduate students,” Sharp adds.

Sharp’s donation — matched by the Schimmel family gift — provides funds to establish fellowships for biology graduate students. “I hope others will join me in supporting the biology department and life sciences here at the Institute through the Schimmel family matching opportunity, as their investment will impact students and research for generations to come.”

Match point

“I am extremely grateful to Paul, his family, and Professor Phillip Sharp and Ann Sharp for their generosity and helping to inspire others to follow their lead,” says Biology Department Head and Praecis Professor of Biology Alan Grossman.

Grossman has worked with Sharp and the Schimmels for many years and is keenly aware of the important role these gifts play in a time of dwindling government investment in the sciences.

“As federal support for graduate training continues to wane over time, support from individuals like Paul, Phil, and others becomes crucial to the future of the life sciences,” Grossman says. “As COVID-19 has laid bare, there has never been a more critical need or better time to invest in basic science than right now.”

With $18 million remaining in available matching funds, Grossman says that he and partners throughout MIT continue to seek out others who wish to contribute to and participate in the Schimmel Family Program for Life Sciences. “Providing students with the resources they need to be successful in their education, research, and careers remains at the core of our mission,” says Grossman.

“Paul and the Schimmel family have provided other donors with an extraordinary opportunity to amplify the impact of their giving by leveraging their vision for the betterment of life sciences at the Institute,” says Biology Director of Development Daniel Griffin. “This initiative is resonating with people in and outside of the MIT community and we are all excited to see where it leads.”

Ensuring a bright future for Seattle
Ari Daniel | MIT Technology Review
January 10, 2022
In 1982, when Lynn Best ’69 joined the public utility Seattle City Light, her team faced an immediate challenge: evaluating the environmental, cultural, and financial impacts of its three dams generating electricity on the Skagit River in northwest Washington State. As acting director, she was able to persuade City Light to allow the environmental team to lead negotiations.

“Of course,” Best says, “the biggest issue was protecting the salmon on the river.” Four species of salmonids were known to spawn at different times and depths. The team relied upon science to determine optimal flow and ramping rates, placing the health of these species first, above power demand. Because the work was done in collaboration with state and federal agencies as well as local tribal communities, these partner groups signed on to the approach, which was the first time this had ever happened on a large hydro project. The fish responded immediately. The chum and pink salmon returned to historic abundances.

City Light’s efforts didn’t go unnoticed. In 1992, a senior member of the Federal Energy Regulatory Commission said that the utility’s Skagit River effort was the most comprehensive piece of work for the public good that he had ever seen. According to Best, if you dig hard enough, multiple science-based solutions to a problem emerge. And in her experience, at least one of these answers can benefit all the stakeholders. It’s a lesson she learned during her time as a biology major at MIT.

Of course, mistakes happen. Roughly a decade ago, the dam gates failed to open properly, draining water away from a number of salmon nests. This time, as environmental affairs director of Seattle City Light, Best and her now much larger team reported the violation to their partners. The tribal communities “didn’t advocate for any penalties, which is pretty unheard-of in those circumstances,” she says. It was a testament to how effective her cooperative approach had been.

In 2005, under Best’s leadership, Seattle City Light became the first utility in the nation to go carbon neutral. And more recently, during her time as the organization’s chief environmental officer, she championed an environmental justice program to protect and support diverse and economically disadvantaged communities.

Best retired from Seattle City Light in early 2020. She is now a commissioner on the Skagit Environmental Endowment Commission, dedicated to protecting the Upper Skagit environment on both sides of the border. She also spends time birdwatching and hiking. Her legacy of relationship building and environmental stewardship endures.

“Geeking Out” About Lab Equipment
Julie Fox | MIT Alumni Association
January 14, 2022

“Globally, there is a huge disparity in access to scientific resources,” says Melissa Wu ’05, CEO of Seeding Labs. “About 80 percent of the world’s population lives in low- and middle-income countries, but 80 percent of research funding is directed to just 10 countries in the world.”

And that disparity, she explains, biases what gets studied, what societal challenges are addressed, and who is a part of the scientific workforce. Seeding Labs is an NGO focused on shifting that balance of resources. It empowers scientists to transform the world by providing the resources needed to fight global diseases, feed a growing population, and protect our planet.

After leaving MIT, where she was active in service to her community and discovered a passion for research, Wu intended to pursue a career as a research professor. While earning a PhD in cell and developmental biology at Harvard and getting involved in a student group that advocated for global research, she began to realize that she craved more immediate impact from her work.

“As students, we convened a panel to talk about the barriers that are unique to researchers in lower- and middle-income countries,” she says. “We saw an immediate solution to one of those challenges: access to laboratory equipment, which can be prohibitively expensive. I worked with other students to collect and ship surplus equipment to researchers in developing countries. Within a few months after receiving equipment, we heard back the impacts of our efforts―successful grant apps, staff hired, and graduate students recruited to their labs.”

“After a few years of doing this work as students, we realized that we’d found a solution to a challenge that nobody else seemed able to address,” Wu explained. She supported a Harvard classmate, Nina Dudnik, in forming Seeding Labs, a nonprofit that could grow and sustain their efforts. Wu joined the Boston-based company as a full-time staff member in 2014 after completing her PhD, holding several positions before becoming CEO in 2019.

Seeding Labs aims to unleash the power of the most talented scientists around the globe to do what they do best: research, innovate, and discover. Through its flagship program, Instrumental Access, the company provides high-quality laboratory equipment at huge discounts to universities and research institutes in developing countries. “Since 2003, we’ve supported nearly 100 universities in 36 countries around the world with equipment that would’ve cost an estimated $40 million to obtain otherwise.”

Wu says that the stories of success, and the gratitude, from the universities and research institutions are continually inspiring. “One of the researchers told us that it was his dream to start a lab. There is no better reward than to be told that you’re fulfilling someone’s dream.” And in the current pandemic, these established labs are helping to save lives. In southeastern Africa, the Malawi University of Science and Technology has been able to analyze thousands of Covid-19 test kits in its lab because of the specialized equipment received through a 2017 Instrumental Access award.

The impact of the new equipment has a ripple effect beyond the labs and their research projects. Seeding Labs recently supported the top school in Tanzania, the Dar es Salaam University College of Education, with a shipment of lab equipment to help train the next generation of chemistry teachers. The university reported that the student dropout rate fell by 50 percent after receipt of the lab equipment, Wu says.

Her commitment to service doesn’t stop at helping to fund the global science community through lab equipment—Wu has also devoted her time to mentoring, with a special interest in helping to foster more diversity and equity in the sciences. “You know the phrase when you ‘geek out’ about something? It’s like you have this overwhelming desire to share something that you’re really passionate about because it makes you happy and you want others to experience that too. That’s what my love of scientific research is like. Who wouldn’t be excited about the opportunity to understand and then literally transform the world we live in? I want to share that with others and hope that I can inspire them to chase their dreams.”

Uncovering the mysteries of methylation in plants
Eva Frederick | Whitehead Institute
January 11, 2022

Growing up is a complex process for multi-celled organisms — plants included. In the days or weeks it takes to go from a seed to a sprout to a full plant, plants express hundreds of genes in different places at different times.

In order to conduct this symphony of genes, plants rely in part on an elegant regulatory method called DNA methylation. By adding or removing small molecules called methyl groups to the DNA strand, the plant can silence or activate different regions of its genetic code without changing the underlying sequence.

In a new paper from the lab of Whitehead Institute Member Mary Gehring, researchers led by former Gehring lab postdoc Ben Williams (now an assistant professor at the University of California, Berkeley) tease apart the role of proteins governing this system of genetic control, and reveal how enzymes that regulate methylation can affect essential decisions for plants such as when to produce flowers. “We’re starting to see that there is actually a broader role for  demethylation [in plant development] than we thought,” Gehring said.

In the model plant Arabidopsis thaliana, methylation is regulated in part by enzymes encoded by  a family of four genes called the DEMETER genes. The protein products of these genes are in charge of demethylating, or removing those methyl groups from the DNA, allowing different parts of the strand to be expressed. “You have these enzymes that can come in and completely change the way the DNA is read in different cells, which I find super interesting,” Williams said.

But teasing apart the role of each DEMETER gene has proved difficult in the past, because one member of this gene family in particular, called DME, is essential for seed development. Knock out DME, and the seed is aborted. “We had to design a synthetic gene to get around that,” Williams said. “We had to create plants that would rescue the reproductive failure, but then still be mutated throughout the rest of the life cycle.”

The researchers accomplished this by putting the DME gene under the control of a genetic element called a promoter that allowed it to be expressed in a cell that only existed in the plant during seed development. Once the plant was past the critical point where DME was needed for development, the gene would no longer be expressed, allowing the plant to grow up as a dme knockout. “It was an exciting thing, finally being able to create this knockout,” Gehring said.

Now, for the first time, the researchers could create plants with any combination of the DEMETER family genes knocked out, and then compare them to try and understand what the enzymes produced by each of the four genes was doing.

As expected, plants missing any of the DEMETER demethylases ended up with areas of their genomes with too many methyl groups (this is called hypermethylation). These areas were often overlapping, suggesting that the four DEMETER genes shared responsibility for demethylating certain areas of the genome.

“When one of these enzymes is gone, the others are surprisingly good at knowing that they need to step forward and do the job instead,” Williams said. “So the system has flexibility built in, which makes sense if it’s going to be involved in making important decisions like when to make flowers. You’d want there to be multiple layers of responsibility, right? It’s like in an organization, you don’t want to load all responsibility on one person — you’d want a few people who can take on that responsibility.”

Williams hypothesizes that while the DEMETER enzymes could step in for each other when needed, each specialized in demethylating DNA in particular types of plant tissue. “If you look at the protein sequences,they are actually really similar,” he said. “What’s different about them is they’re expressed in different cell types.”

A crucial finding of the study came about when the researchers knocked out all four genes in the DEMETER family at the same time. “All flowering plants have this really important decision of when to make flowers,” Williams said. “For plants out in the wild, that decision is usually dependent on temperature and pollinators. What we found really strange is that these mutants just flowered straight away. It’s almost like they weren’t even putting any effort into the decision. They made a few leaves, then boom, flower.”

When the researchers dove deeper, they saw that one area of the genome in particular that controls flowering time is under very careful and continuous regulation by methylating and demethylating enzymes. “We don’t really know why they’re doing that,” he said. “But when you knock out the demethylases, that gene just becomes methylated, and it’s then switched off. And that just sends plants into an automatic flowering state.”

In the future, the researchers plan to investigate other outcomes associated with their quadruple knockout of the DEMETER genes. “When we knocked out all four of the enzymes, it led to a lot of interesting phenotypes and tons of stuff to study,” Williams said. “We’ve learned through doing this that with DEMETER, like many gene families, we had to knock out all the players to find out the importance of what they are doing.”

Gehring will continue the research at Whitehead Institute. Williams recently started his own lab at the University of California, Berkeley. “I feel very lucky because this project has given me two or three different avenues that I can pursue in my new lab,” Williams said. “It has opened a lot of doors, which is very rewarding.”

3 Questions: Kristin Knouse on the liver’s regenerative capabilities

The clinically-trained cell biologist exploits the liver’s unique capacities in search of new medical applications.

Grace van Deelen | Department of Biology
December 15, 2021

Why is the liver the only human organ that can regenerate? How does it know when it’s been injured? What can our understanding of the liver contribute to regenerative medicine? These are just some of the questions that new assistant professor of biology Kristin Knouse and her lab members are asking in their research at the Koch Institute for Integrative Cancer Research. Knouse sat down to discuss why the liver is so unique, what lessons we might learn from the organ, and what its regeneration might teach us about cancer.

Q: Your lab is interested in questions about how body tissues sense and respond to damage. What is it about the liver that makes it a good tool to model those questions?

A: I’ve always felt that we, as scientists, have so much to gain from treasuring nature’s exceptions, because those exceptions can shine light onto a completely unknown area of biology and provide building blocks to confer such novelty to other systems. When it comes to organ regeneration in mammals, the liver is that exception. It is the only solid organ that can completely regenerate itself. You can damage or remove over 75 percent of the liver and the organ will completely regenerate in a matter of weeks. The liver therefore contains the instructions for how to regenerate a solid organ; however, we have yet to access and interpret those instructions. If we could fully understand how the liver is able to regenerate itself, perhaps one day we could coax other solid organs to do the same.

There are some things we already know about liver regeneration, such as when it begins, what genes are expressed, and how long it takes. However, we still don’t understand why the liver can regenerate but other organs cannot. Why is it that these fully differentiated liver cells — cells that have already assumed specialized roles in the liver — can re-enter the cell cycle and regenerate the organ? We don’t have a molecular explanation for this. Our lab is working to answer this fundamental question of cell and organ biology and apply our discoveries to unlock new approaches for regenerative medicine. In this regard, I don’t necessarily consider myself exclusively a liver biologist, but rather someone who is leveraging the liver to address this much broader biological problem.

Q: As an MD/PhD student, you conducted your graduate research in the lab of the late Professor Angelika Amon here at MIT. How did your work in her lab lead to an interest in studying the liver’s regenerative capacities?

A: What was incredible about being in Angelika’s lab was that she had an interest in almost everything and gave me tremendous independence in what I pursued. I began my graduate research in her lab with an interest in cell division, and I was doing experiments to observe how cells from different mammalian tissues divide. I was isolating cells from different mouse tissues and then studying them in culture. In doing that, I found that when the cells were isolated and grown in a dish they could not segregate their chromosomes properly, suggesting that the tissue environment was essential for accurate cell division. In order to further study and compare these two different contexts — cells in a tissue versus cells in culture — I was keen to study a tissue in which I could observe a lot of cells undergoing cell division at the same time.

So I thought back to my time in medical school, and I remembered that the liver has the ability to completely regenerate itself. With a single surgery to remove part of the liver, I could stimulate millions of cells to divide. I therefore began exploiting liver regeneration as a means of studying chromosome segregation in tissue. But as I continued to perform surgeries on mice and watch the liver rapidly regenerate itself, I couldn’t help but become absolutely fascinated by this exceptional biological process. It was that fascination with this incredibly unique but poorly understood phenomenon — alongside the realization that there was a huge, unmet medical need in the area of regeneration — that convinced me to dedicate my career to studying this.

Q: What kinds of clinical applications might a better understanding of organ regeneration lead to, and what role do you see your lab playing in that research?

A: The most proximal medical application for our work is to confer regenerative capacity to organs that are currently non-regenerative. As we begin to achieve a molecular understanding of how and why the liver can regenerate, we put ourselves in a powerful position to identify and surmount the barriers to regeneration in non-regenerative tissues, such as the heart and nervous system. By answering these complementary questions, we bring ourselves closer to the possibility that, one day, if someone has a heart attack or a spinal cord injury, we could deliver a therapy that stimulates the tissue to regenerate itself. I realize that may sound like a moonshot now, but I don’t think any problem is insurmountable so long as it can be broken down into a series of tractable questions.

Beyond regenerative medicine, I believe our work studying liver regeneration also has implications for cancer. At first glance this may seem counterintuitive, as rapid regrowth is the exact opposite of what we want cancer cells to do. However, the reality is that the majority of cancer-related deaths are attributable not to the rapidly proliferating cells that constitute primary tumors, but rather to the cells that disperse from the primary tumor and lie dormant for years before manifesting as metastatic disease and creating another tumor. These dormant cells evade most of the cancer therapies designed to target rapidly proliferating cells. If you think about it, these dormant cells are not unlike the liver: they are quiet for months, maybe years, and then suddenly awaken. I hope that as we start to understand more about the liver, we might learn how to target these dormant cancer cells, prevent metastatic disease, and thereby offer lasting cancer cures.