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Whitehead Institute
February 9, 2021
Important moments of cancer — mutation, tumor formation, metastasis — are fleeting, easy-to-miss events. Even with modern medical technologies and methods, they often happen unobserved, and are only realized later when these cells spawn life-threatening conditions.
In recent years, however, new methods of tracking individual cells through time have allowed researchers to get closer to the origin of these events, and Whitehead Institute scientists are turning the power of these technologies to study cells involved in several different types of cancer. “With [these technologies], you can track down rare events in the past, identify all the offspring of an event, and see how they’ve changed their behavior,” said Whitehead Institute Member Jonathan Weissman. “You can ask, when a cell picks up an oncogene, how does it mutate, and further evolve, and proliferate and metastasize?”
Read on to learn how three Whitehead Institute Members are using specially engineered mice, CRISPR-based technologies, and other methods to track cells at different stages of cancer development, pushing the boundaries of what we understand about how the disease starts and proliferates. From the initial beginnings of a tumor, sometimes in the darkness of a still-forming embryo, to a tumor’s growth and eventual metastasis to other sites in the body, Whitehead Institute scientists Rudolf Jaenisch, Jonathan Weissman, and Robert Weinberg study the pivotal points in a cancer’s growth and spread.
The birth of a tumor
For around 800 children each year in the United States, the seeds are sown during fetal development for a rare and unpredictable childhood cancer called neuroblastoma. To understand how the disease develops, scientists need to study what happens to these cancerous “seeds” as the embryo matures. But they can hardly study a living human embryo, and fetal development is such a complex process that it is near impossible to simulate it in the lab.
To make matters more complex, the cancer grows and then may shrink unpredictably after the children are born and as they age. Sometimes the tumors disappear on their own; other times they grow uncontrollably.
In 2020, Institute Founding Member Rudolf Jaenisch’s lab introduced a new way of tracking the cells involved in the disease using his tried and true method for modeling such complex conditions: chimeric mice. A chimera is a conglomeration of two species — in this case, mostly mouse, with a few strategically placed human stem cells.
To create chimeras to study neuroblastoma, Jaenisch, who is also a Professor of Biology at Massachusetts Institute of Technology (MIT), along with collaborators at the Koch Institute for integrative Cancer Research at MIT and the Dana-Farber Cancer Institute, engineered human stem cells with glowing proteins to make them easy to see under the microscope. The cells contained a special genetic-switch that allowed the researchers to induce tumors by adding a certain chemical. These human stem cells were then induced to form a more specialized cell type – a neural crest stem cell.
Neural crest cells are a group of developing stem cells that go on to form the peripheral nervous system as well as other parts of the body such as the facial bones. It is neural crest cells that mutate into neuroblastoma tumors in humans, so the researchers hoped that by using these cells, they could create “human” tumors in mice. The researchers injected these human neural crest cells into mice so that they could readily incorporate with the host’s cells.
After the mice were born, the researchers were then able to take samples from the mice over the course of their development to see whether these implanted cells would form neural crest-derived tumors and, if so, what happened as they grew — something they would never have been able to do with neuroblastoma tumors in human infants and children.
The tumors in the chimeric mice pups developed in similar forms to human neuroblastomas — specifically, they formed characteristic rosette shapes — very similar to those seen in patient’s samples. With the help of Stefani Spranger, an assistant professor of biology at MIT and a Member of the Koch Institute for Integrative Cancer Research at MIT, they were able to track the cells’ interactions with the mice’s immune systems, and learn how the cancer “tricks” the immune cells into letting it stick around.
Now that they are able to model the formation of neuroblastoma tumors, the researchers hope to find a way to eliminate the tumors in the mice. “This is a model that will allow us to approach how to get rid of the tumors,” said Malkiel Cohen, a former postdoc in Jaenisch’s lab and first author of the paper, published in the journal Cell Stem Cell describing the work.
Cancer genealogy
A recent project from the lab of Whitehead Institute Member Jonathan Weissman focuses on another essential moment of cancer progression: metastasis. Metastasis happens when cancer spreads from a primary tumor to distant places in the body. Weissman, an expert in genome editing, created a CRISPR-based method to track the lineage of individual cancer cells in real time as they proliferate and metastasize.
Weissman and his collaborators, including graduate student Matthew Jones and then postdoctoral researcher Jeffrey Quinn, adapted the technology from a similar tool designed by Michelle Chan, a former postdoc in Weissman’s former lab at the University of California, San Francisco (UCSF) who is now an assistant professor at Princeton University. Chan designed a CRISPR mechanism to track the lineages of embryonic cells as they developed into specialized tissues.
“What Michelle Chan was able to do was uncover how tissues that look very similar to one another, actually come from disparate sources,” said Matthew Jones, a graduate student in Weissman’s lab and a co-first author on the paper describing the new method. “That has rapid implications about how tissues organize themselves, and we wanted to apply it to cancer.”
To create this system, the researchers engineered cancer cells with added genes: one for Cas9, the gene that codes for CRISPR’s “molecular scissors,” others for fluorescing proteins for microscopy, and a few sequences that would serve as targets for the CRISPR technology.
They then implanted thousands of these cells into the lungs of mice to simulate a tumor, using a model designed by Trever Bivona, a cancer biologist at UCSF. As the cells in the model tumors began to divide, the Cas9 protein began making small snips in the target sites in the cells’ DNA. When the cells fixed these snips, they patched in or deleted a few random nucleotides, leading to a unique “barcode” in each cell. Because these barcodes were added to each cell’s DNA, they were heritable and able to be passed on through generations of cells.
With the help of Nir Yosef, a computer scientist at the University of California, Berkeley, the researchers organized the data into “family trees” of cancer cells spanning multiple generations. By taking samples from different areas of the body, the researchers were able to resolve exactly when a cell jumped from where it started, in the lungs, to a distant tissue.
When they compared the trees, the researchers noticed that some cells were highly metastatic, jumping around multiple times over the course of the experiment, while others stayed put throughout. “We were excited to uncover some of these really rare, but consequential events that happened in the past that you would never be able to observe, and rarely be able to infer from a static snapshot,” Jones said.
By comparing highly metastatic and non-metastatic cells, they were able to identify metastasis-associated genes and answer questions about how the tumors were evolving and adapting. “It’s an entirely new way to look at the behavior and evolution of a tumor,” Weissman said. “We think it can be applied to many different problems in cancer biology.”
The next steps
A natural tumor begins with a single cell, mutated in a way that leads it to “go rogue,” so to speak. To mimic this in a model system, Dian Yang, another post-doc in the Weissman Lab, is collaborating with researchers in the lab of MIT Professor of Biology and Koch Institute Director Tyler Jacks’ to create a mouse model with the CRISPR lineage recording tool embedded in its DNA.
The model is based on a mouse model created by Jacks’ lab to study lung cancer. The lab has created genetically engineered mice that when left alone, live completely normal lives. But upon adding a trigger (an enzyme called “Cre”) — in Jacks’ and Yang’s case, they deliver the trigger to the lung using a virus — oncogenic signals are activated and lead to spontaneous tumors in the mice’s lungs.
Being able to “switch on” the mouse model in this way has a number of advantages. “Each tumor will start from one single transformed cell, which we can then watch in its native environment as it evolves,” Yang said. “Then, we can look back later at how the cells metastasize.”
Adding the CRISPR system to Jacks’ existing cancer model will also allow researchers to study cancerous cells on a broader time scale. “Usually, when we harvest samples from the mice, it is like a snapshot, just one sample at one stage,” Yang said. “You can see what it looks like, you can analyze gene expression at the time of sampling, you can even take a time series, but you don’t know what happened in the past.”
In a sense, the lineage recording technology embedded in the genome of the mice now makes it possible to look back in time. “When you have a million cells in a tumor, you can use the lineage network of these cells to find out how they’re related, and connect the current state with the past evolutionary lineage history,” he said. “I think this will provide a new dimension of biological information for us to understand biology that is not just limited to cancer biology.”The making of metastasis
Weissman’s lab’s method for tracking the lineage of cancer cells can illuminate the nature of the cells that leave the primary tumor and scatter throughout the body. But what actually happens to these cells to cause them to metastasize?
That’s where Whitehead Institute Founding Member Robert Weinberg’s research comes in. Weinberg has been studying cancer for decades. His early work helped to answer the question of how cells that form a primary tumor become cancerous. Weinberg identified the first human oncogene, a gene that causes otherwise-normal cells to form tumors. This finding, combined with others, demonstrated that cancer is a disease driven by damaged genes, at least in its origins. Weinberg has since turned his attention to the question of how cancer cells acquire the ability to spread.
Around 90 percent of cancer deaths are caused not by the primary tumor, but by its metastasis. Based on previous work, there is no single genetic switch that can be flipped to equip a cancer cell for metastasis. Instead, cells must go through a series of changes over time. Most cancer cells fail to acquire all of the necessary traits, and so may, for example, spread to new tissues but rarely form tumors there. Weinberg’s lab tracks cancer cells to help fill in the “road map” that cancer cells follow on the way to metastasis, in the hopes that their insights can be used to prevent or treat metastatic cancers.
One important change that cancer cells undergo is called the epithelial to mesenchymal transition (EMT), a cellular process that causes the cancer cells to express different genes and go from being immobile to mobile and invasive. Cancer cells undergoing this transition to be able to spread are called “quasi-mesenchymal.” The ability to spread does not fully explain metastasis, however.
“There’s two aspects of the metastasis problem,” Weinberg said. “The first aspect is how cancer cells physically leave the primary tumor and get seeded into a distant tissue. In other words, the physical translocation of the cells. The second step represents the subsequent ability of the already seeded cells to figure out how to make a living in a distant tissue.”
In other words, how do those transplanted cells adapt to a new tissue environment, which might offer them only inhospitable conditions? “That represents the major unsolved problem of metastasis,” he said.
Weinberg hopes to study this more in the future; for now though, his lab has found that studying quasi-mesenchymal cells can serve another purpose. Anushka Dongre, a postdoc in Weinberg’s lab, found that these cells are resistant to a common type of cancer treatment, known as immune checkpoint therapy, and can even protect the other cancer cells around them from that therapy. If as little as ten percent of a tumor consists of quasi-mesenchymal cells, then the whole tumor may become resistant.
By using a tumor’s epithelial/mesenchymal profile, Dongre demonstrated that she could predict how likely a breast cancer tumor was to respond to a particular immune checkpoint therapy. This finding could help physicians match patients to the best treatment plan, by indicating ahead of time whether the treatment will work. She also identified a way to eliminate the quasi-mesenchymal cells’ protective effect by suppressing a certain enzyme that they employ to defend themselves.
Weinberg’s lab continues to study pivotal changes in the lives of cancer cells, such as the EMT, so that they can better understand metastasis and, they hope, help find effective treatments for patients with metastatic cancers.Tracking cells into the future
Scientists have been tracking cells for more than a century, and Whitehead Institute scientists will be tracking cancer cells for decades to come. In the coming years, Weinberg plans to continue to investigate the mysteries of metastasis. For Weissman’s part, he hopes to continue refining his CRISPR technique, with the end goal of eventually being able to predict the behavior of cancer cells. “We want to be able to measure where they are, where they’re going at any time, and then predict where they’re going to be in the future,” he said.
With new technologies and ever-expanding fields, there is limitless potential in these various methods. “That’s what is so exciting about the cell tracking field right now,” said Matt Jones. “It’s really pushing the boundaries on what we can capture from our measurements.”
The award recognizes Weinberg’s pioneering achievements in the field of cancer biology.
Eva Frederick | Whitehead Institute
February 10, 2021
The Japan Prize Foundation has named MIT Professor Robert Weinberg as one of the recipients of its 2021 awards in the category of Medical Science and Medicinal Science, citing Weinberg’s contributions to the development of a multi-step model of how cancer begins and progresses, and the application of that model to improve cancer treatments and outcomes.
Weinberg, along with co-recipient Bert Vogelstein of the Johns Hopkins University School of Medicine, will receive his award in April at a presentation ceremony attended by the emperor and empress of Japan. “Dr. Weinberg’s work has led to the identification of critical genes for cancer development that have subsequently been approved as therapeutic targets, resulting in thousands of lives being saved,” writes the Japan Prize Foundation in their news release.
“This award is a tribute to the brilliant scientists who have worked alongside me during my time at the Whitehead Institute,” says Weinberg, a Whitehead Institute founding member who is the Daniel K. Ludwig Professor for Cancer Research at MIT, as well as an extramural member of the David H. Koch Institute for Integrative Cancer Research at MIT.
In 1979, Weinberg and his lab discovered the first gene associated with tumor formation in humans, also known as an oncogene. In the decades since, he has devoted his career to studying not only the genetic basis of cancer, but also the ways in which cancerous cells spread and proliferate throughout the body. His work, along with Vogelstein’s, is credited with the development of new areas of cancer research, including the idea of targeted cancer therapies, and the broader field of precision medicine.
Weinberg joins a list of distinguished scientists from around the world who have received the prestigious Japan Prize, which is intended to express Japan’s gratitude to the international community. Each year, the Japan Prize Foundation selects two specialized fields of science and technology and solicits nominations from over a thousand scientists and engineers across Japan and abroad. This year, these scientists nominated 385 individuals, and three received a prize. In addition to Weinberg and Vogelstein, Martin A. Green, a professor at the University of New South Wales, was also honored this year, in the category of Resources, Energy, Environment, and Social Infrastructure.
“Weinberg’s work on oncogenes and tumor suppressor genes in cancer research has helped create the paradigm of cancer progression as we know it today, and has led the field of cancer biology in new and fruitful directions,” says Whitehead Institute director and MIT professor of biology Ruth Lehmann. “His research has laid the foundation for the development of new treatments that are improving the lives of cancer patients around the world.”
Whitehead Institute
January 27, 2021
Whitehead Institute director and Member Ruth Lehmann is the 2021 recipient of the Genetics Society of America’s (GSA) Thomas Hunt Morgan Medal for lifetime contributions to the field of genetics. The GSA is an international community of more than 5,000 scientists; and the Morgan Medal is one of the most prestigious awards for career achievement in the field of genetics.
The Morgan Medal was bestowed in recognition for Lehmann’s groundbreaking work revealing the unique biology of the specialized cells that give rise to egg and sperm. Known as germ cells, they are the only cells in the body with the power to build a new organism and transmit this potential to future generations. Lehmann’s research using the fruit fly Drosophila melanogaster has uncovered the molecular mechanisms by which germ cells are distinguished from the other cells of the body and how they migrate into position during development of the embryo. These and other highly influential discoveries from the Lehmann lab have spawned insights into many aspects of animal development, cell migration, cell signaling, RNA regulation, genome integrity, and mitochondrial inheritance.
This is the second consecutive year that a Whitehead Institute Member has received the Thomas Hunt Morgan Medal. It was awarded in 2020 to Whitehead Founding Member and former director Gerald R. Fink.
The Davis and Berger labs combined cryo-electron microscopy and machine learning to visualize molecules in 3D.
February 4, 2021
New technique reveals many possible conformations that a protein may take.
Anne Trafton | MIT News Office
February 4, 2021
Cryo-electron microscopy (cryo-EM) allows scientists to produce high-resolution, three-dimensional images of tiny molecules such as proteins. This technique works best for imaging proteins that exist in only one conformation, but MIT researchers have now developed a machine-learning algorithm that helps them identify multiple possible structures that a protein can take.
Unlike AI techniques that aim to predict protein structure from sequence data alone, protein structure can also be experimentally determined using cryo-EM, which produces hundreds of thousands, or even millions, of two-dimensional images of protein samples frozen in a thin layer of ice. Computer algorithms then piece together these images, taken from different angles, into a three-dimensional representation of the protein in a process termed reconstruction.
In a Nature Methods paper, the MIT researchers report a new AI-based software for reconstructing multiple structures and motions of the imaged protein — a major goal in the protein science community. Instead of using the traditional representation of protein structure as electron-scattering intensities on a 3D lattice, which is impractical for modeling multiple structures, the researchers introduced a new neural network architecture that can efficiently generate the full ensemble of structures in a single model.
“With the broad representation power of neural networks, we can extract structural information from noisy images and visualize detailed movements of macromolecular machines,” says Ellen Zhong, an MIT graduate student and the lead author of the paper.
With their software, they discovered protein motions from imaging datasets where only a single static 3D structure was originally identified. They also visualized large-scale flexible motions of the spliceosome — a protein complex that coordinates the splicing of the protein coding sequences of transcribed RNA.
“Our idea was to try to use machine-learning techniques to better capture the underlying structural heterogeneity, and to allow us to inspect the variety of structural states that are present in a sample,” says Joseph Davis, the Whitehead Career Development Assistant Professor in MIT’s Department of Biology.
Davis and Bonnie Berger, the Simons Professor of Mathematics at MIT and head of the Computation and Biology group at the Computer Science and Artificial Intelligence Laboratory, are the senior authors of the study, which appears today in Nature Methods. MIT postdoc Tristan Bepler is also an author of the paper.
Visualizing a multistep process
The researchers demonstrated the utility of their new approach by analyzing structures that form during the process of assembling ribosomes — the cell organelles responsible for reading messenger RNA and translating it into proteins. Davis began studying the structure of ribosomes while a postdoc at the Scripps Research Institute. Ribosomes have two major subunits, each of which contains many individual proteins that are assembled in a multistep process.
To study the steps of ribosome assembly in detail, Davis stalled the process at different points and then took electron microscope images of the resulting structures. At some points, blocking assembly resulted in accumulation of just a single structure, suggesting that there is only one way for that step to occur. However, blocking other points resulted in many different structures, suggesting that the assembly could occur in a variety of ways.
Because some of these experiments generated so many different protein structures, traditional cryo-EM reconstruction tools did not work well to determine what those structures were.
“In general, it’s an extremely challenging problem to try to figure out how many states you have when you have a mixture of particles,” Davis says.
After starting his lab at MIT in 2017, he teamed up with Berger to use machine learning to develop a model that can use the two-dimensional images produced by cryo-EM to generate all of the three-dimensional structures found in the original sample.
In the new Nature Methods study, the researchers demonstrated the power of the technique by using it to identify a new ribosomal state that hadn’t been seen before. Previous studies had suggested that as a ribosome is assembled, large structural elements, which are akin to the foundation for a building, form first. Only after this foundation is formed are the “active sites” of the ribosome, which read messenger RNA and synthesize proteins, added to the structure.
In the new study, however, the researchers found that in a very small subset of ribosomes, about 1 percent, a structure that is normally added at the end actually appears before assembly of the foundation. To account for that, Davis hypothesizes that it might be too energetically expensive for cells to ensure that every single ribosome is assembled in the correct order.
“The cells are likely evolved to find a balance between what they can tolerate, which is maybe a small percentage of these types of potentially deleterious structures, and what it would cost to completely remove them from the assembly pathway,” he says.
Viral proteins
The researchers are now using this technique to study the coronavirus spike protein, which is the viral protein that binds to receptors on human cells and allows them to enter cells. The receptor binding domain (RBD) of the spike protein has three subunits, each of which can point either up or down.
“For me, watching the pandemic unfold over the past year has emphasized how important front-line antiviral drugs will be in battling similar viruses, which are likely to emerge in the future. As we start to think about how one might develop small molecule compounds to force all of the RBDs into the ‘down’ state so that they can’t interact with human cells, understanding exactly what the ‘up’ state looks like and how much conformational flexibility there is will be informative for drug design. We hope our new technique can reveal these sorts of structural details,” Davis says.
The research was funded by the National Science Foundation Graduate Research Fellowship Program, the National Institutes of Health, and the MIT Jameel Clinic for Machine Learning and Health. This work was supported by MIT Satori computation cluster hosted at the MGHPCC.
Thirteen postdocs and research scientists honored for contributions to the Institute with awards formerly known as Infinite Kilometer.
School of Science
February 3, 2021
This year, the MIT School of Science has recognized 13 postdocs and research scientists who are the recipients of the 2021 Infinite Expansion Award.
The award, formerly called the “Infinite Kilometer Award,” was created in 2012 to highlight the contributions of important members of the MIT science community. The awardees are nominated for their contributions to their research labs, participation in educational programs, exceptional talent, generous character, service to the community, teamwork, and in general, going above and beyond in their roles at the Institute, especially during the coronavirus pandemic.
The following are the 2021 School of Science Infinite Expansion winners:
- Xinqiang Ding, a postdoc in the Department of Chemistry, nominated by Assistant Professor Bin Zhang for “being one of the most promising, talented, and hard-working scientists that [he has] worked with in [his] entire career”;
- Quentin Ferry, a postdoc in the Picower Institute for Learning and Memory, nominated by Professor Susumu Tonegawa for “remarkable raw talent, versatility … a highly motivated attitude, deep critical thinking, and an extremely creative personality”;
- Hamed Owladeghaffari, a postdoc in the Department of Earth, Atmospheric and Planetary Sciences, nominated by Assistant Professor Matěj Peč for “consistently gone above and beyond his duty”;
- Andrew Grassetti, a postdoc in the Department of Biology, nominated by Assistant Professor Joseph Davis for “[going] well beyond any reasonable expectations to ensure that my entire group has the support — scientific, professional, and emotional — that they needed to succeed”;
- Sarah Heine, a research scientist in the MIT Kavli Institute for Astrophysics and Space Research (MKI), nominated by Principal Research Scientist Herman Marshall for “[being] a major contributor”;
- Samantha Kristufek, a postdoc in the Department of Chemistry, nominated by Professor Jeremiah Johnson for “cultivating an inclusive, supportive group culture”;
- Nathan Lourie, a research scientist in the MIT Kavli Institute for Astrophysics and Space Research, nominated by Professor and MKI Director Rob Simcoe for “demonstrat[ing] both a high degree of personal grit, a capacity to build and lead a team, and a high degree of community engagement”;
- Hiruy Meharena, a postdoc in the Picower Institute for Learning and Memory, nominated by Professor and Picower Institute Director Li-Huei Tsai for “being a community builder and exemplary scientific colleague”;
- Alexander Schuppe, a postdoc in the Department of Chemistry, nominated by Professor Stephen Buchwald for “consistent and significant positive impact on the research efforts of others”;
- Jitendra Sharma, a research scientist in the Picower Institute for Learning and Memory, nominated by administrative manager Eleanor MacPhail, postdoc Grayson Sipe, and Professor Mriganka Sur for “willingness to help everyone,” “serves as a beacon of optimism and collegiality,” and “approach[ing] each day with the goal of making a difference that will help advance the MIT mission”;
- Yong Wang, a postdoc in the Department of Chemistry, nominated by Assistant Professor Alison Wendlandt for “[being] an exceptionally talented scientist, a committed mentor, and a model coworker”;
- Jun Yang, a postdoc in the Department of Physics and MIT Kavli Institute for Astrophysics and Space Research, nominated by Professor Or Hen, professor and physics head Peter Fisher, and Research Scientist Norbert Shulz for “community building,” “mak[ing] a difference,” and “[making] great efforts to organize events for the physics postdoc association during a time of isolation”; and
- Hannah Yevick, a research scientist in the Department of Biology, nominated by Associate Professor Adam Martin for “devotion to mentoring.”
The honor includes a monetary award and will be commemorated in person at a later date with family, friends, and nominators, as well as the winners of the 2021 Infinite Mile Award.
Case’s new lab investigates why cancer arises when disruptions in cellular organization change how cells sense mechanical forces.
Saima Sidik | Department of Biology
February 2, 2021
Assistant professor of biology Lindsay Case wants to understand the protein complexes called focal adhesions that let cells move and sense the world around them. She also aims to determine how cancer arises when focal adhesions malfunction. During her postdoc work at the University of Texas Southwestern Medical Center, she discovered that some of the proteins in focal adhesions work together because of phase separation — a clumping behavior that researchers are just beginning to understand. She sat down to discuss what her work means for cancer research, and her future plans for her new lab in the Department of Biology.
Q: What is phase separation, and how does it affect the way cells function?
A: I always compare phase separation to the separation of oil and vinegar. Something similar can happen with almost any kind of molecule, including proteins. When the interactions between proteins are stronger than their interactions with their surroundings, they can segregate into something called a liquid phase, similar to oil droplets floating in vinegar.
Phase separation matters because organization is a major challenge for our cells, which contain tons of different types of molecules. Sometimes cells organize these molecules using membranes, which is like using fences to keep them in place. But many subcellular structures aren’t surrounded by membranes, and how these compartments keep their components together has been a big mystery since scientists first observed them under microscopes in the 1800s. It’s really only in the last 10 years that people have realized that phase separation is part of the answer.
When cells lose the ability to stay organized, it can have devastating consequences. Changes in how proteins phase separate might underlie serious diseases, like Alzheimer’s and ALS [amyotrophic lateral sclerosis]. I’m really interested in how phase separation organizes protein complexes called focal adhesions, which link cells to their external environment. One function of focal adhesion is to let cells sense mechanical forces from the outside world, and when cells lose this ability it can contribute to cancer progression.
Q: How did phase separation initially pique your interest, and how has your research career prepared you for the work you’ll do at MIT?
A: During my PhD, I was studying how molecules within focal adhesions are organized. I saw a talk by Michael Rosen from the University of Texas Southwestern Medical Center, who would later become my postdoc advisor. Phase separation of proteins was a new idea at the time, but Mike thought it was a powerful force underlying protein organization that we needed to understand more thoroughly. I was intrigued because, at the time, I was unsure what drove focal adhesions to assemble on the plasma membrane, and I wondered if that arrangement might be due to phase separation.
I ended up joining Mike’s lab for my postdoc so that I could apply his ideas about phase separation to my interest in cell signaling and focal adhesions. As a result, I ended up working in a field as it was being born. The first year of my postdoc there were only a few papers investigating phase separation in cellular organization, and now there are over 1,000. Seeing this rapid progress firsthand has been exciting. One of the highlights of my postdoc was showing that phase separation can actually affect the functions of signaling proteins organized on membranes, and I think this discovery went a long way towards showing that phase separation isn’t just a thing that cells can do — it’s something they need to do to survive.
MIT will be an awesome place to continue studying how phase separation lets cells sense the world around them. It’s one of the institutes where the idea of phase separation in biology took off, and the MIT scientists who work on phase separation come from so many different research backgrounds. Understanding phase separation is going to require an interdisciplinary approach, which MIT values. Plus, the students are amazing!
Q: What makes your approach to studying cancer unique?
A: A lot of cancer researchers focus on large-scale or small-scale aspects of these diseases. They either look at how cancer cells behave as a whole, or study the behavior of just one protein. But there’s a level in between where I want to focus my work. I can figure out how large, multi-protein complexes like focal adhesions — some of which form because of phase separation — affect disease progression. During my postdoc, I developed a way to recreate simplified focal adhesions outside of cells. I want to use this system to learn more about how phase separation lets these complexes sense mechanical forces, and how this changes in cancer cells.
Some of the proteins found in focal adhesions are tethered to the plasma membrane, and not many people have studied how protein phase separation changes when you throw a membrane into the mix. I’m excited to keep building up my simplified focal adhesion system in my new lab, and eventually recreate the rest of the complex.
As my lab becomes more established, I’d also like to study how phase separation affects interactions between different protein complexes and signaling pathways. Phase separation is such a rapidly evolving field that it’s hard to know where my research will lead, but that’s part of the fun — not knowing where my work will take me.
“Organs-on-a-chip” system sheds light on how bacteria in the human digestive tract may influence neurological diseases.
Anne Trafton | MIT News Office
January 29, 2021
In many ways, our brain and our digestive tract are deeply connected. Feeling nervous may lead to physical pain in the stomach, while hunger signals from the gut make us feel irritable. Recent studies have even suggested that the bacteria living in our gut can influence some neurological diseases.
Modeling these complex interactions in animals such as mice is difficult to do, because their physiology is very different from humans’. To help researchers better understa nd the gut-brain axis, MIT researchers have developed an “organs-on-a-chip” system that replicates interactions between the brain, liver, and colon.
Using that system, the researchers were able to model the influence that microbes living in the gut have on both healthy brain tissue and tissue samples derived from patients with Parkinson’s disease. They found that short-chain fatty acids, which are produced by microbes in the gut and are transported to the brain, can have very different effects on healthy and diseased brain cells.
“While short-chain fatty acids are largely beneficial to human health, we observed that under certain conditions they can further exacerbate certain brain pathologies, such as protein misfolding and neuronal death, related to Parkinson’s disease,” says Martin Trapecar, an MIT postdoc and the lead author of the study.
Linda Griffith, the School of Engineering Professor of Teaching Innovation and a professor of biological engineering and mechanical engineering, and Rudolf Jaenisch, an MIT professor of biology and a member of MIT’s Whitehead Institute for Medical Research, are the senior authors of the paper, which appears today in Science Advances.
The gut-brain connection
For several years, Griffith’s lab has been developing microphysiological systems — small devices that can be used to grow engineered tissue models of different organs, connected by microfluidic channels. In some cases, these models can offer more accurate information on human disease than animal models can, Griffith says.
In a paper published last year, Griffith and Trapecar used a microphysiological system to model interactions between the liver and the colon. In that study, they found that short-chain fatty acids (SCFAs), molecules produced by microbes in the gut, can worsen autoimmune inflammation associated with ulcerative colitis under certain conditions. SCFAs, which include butyrate, propionate, and acetate, can also have beneficial effects on tissues, including increased immune tolerance, and they account for about 10 percent of the energy that we get from food.
In the new study, the MIT team decided to add the brain and circulating immune cells to their multiorgan system. The brain has many interactions with the digestive tract, which can occur via the enteric nervous system or through the circulation of immune cells, nutrients, and hormones between organs.
Several years ago, Sarkis Mazmanian, a professor of microbiology at Caltech, discovered a connection between SCFAs and Parkinson’s disease in mice. He showed that SCFAs, which are produced by bacteria as they consume undigested fiber in the gut, sped up the progression of the disease, while mice raised in a germ-free environment were slower to develop the disease.
Griffith and Trapecar decided to further explore Mazmanian’s findings, using their microphysiological model. To do that, they teamed up with Jaenisch’s lab at the Whitehead Institute. Jaenisch had previously developed a way to transform fibroblast cells from Parkinson’s patients into pluripotent stem cells, which can then be induced to differentiate into different types of brain cells — neurons, astrocytes, and microglia.
More than 80 percent of Parkinson’s cases cannot be linked to a specific gene mutation, but the rest do have a genetic cause. The cells that the MIT researchers used for their Parkinson’s model carry a mutation that causes accumulation of a protein called alpha synuclein, which damages neurons and causes inflammation in brain cells. Jaenisch’s lab has also generated brain cells that have this mutation corrected but are otherwise genetically identical and from the same patient as the diseased cells.
Griffith and Trapecar first studied these two sets of brain cells in microphysiological systems that were not connected to any other tissues, and found that the Parkinson’s cells showed more inflammation than the healthy, corrected cells. The Parkinson’s cells also had impairments in their ability to metabolize lipids and cholesterol.
Opposite effects
The researchers then connected the brain cells to tissue models of the colon and liver, using channels that allow immune cells and nutrients, including SCFAs, to flow between them. They found that for healthy brain cells, being exposed to SCFAs is beneficial, and helps them to mature. However, when brain cells derived from Parkinson’s patients were exposed to SCFAs, the beneficial effects disappeared. Instead, the cells experienced higher levels of protein misfolding and cell death.
These effects were seen even when immune cells were removed from the system, leading the researchers to hypothesize that the effects are mediated by changes to lipid metabolism.
“It seems that short-chain fatty acids can be linked to neurodegenerative diseases by affecting lipid metabolism rather than directly affecting a certain immune cell population,” Trapecar says. “Now the goal for us is to try to understand this.”
The researchers also plan to model other types of neurological diseases that may be influenced by the gut microbiome. The findings offer support for the idea that human tissue models could yield information that animal models cannot, Griffith says. She is now working on a new version of the model that will include micro blood vessels connecting different tissue types, allowing researchers to study how blood flow between tissues influences them.
“We should be really pushing development of these, because it is important to start bringing more human features into our models,” Griffith says. “We have been able to start getting insights into the human condition that are hard to get from mice.”
The research was funded by DARPA, the National Institutes of Health, the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Environmental Health Sciences, the Koch Institute Support (core) Grant from the National Cancer Institute, and the Army Research Office Institute for Collaborative Biotechnologies.
Generous gift from Michael Gould and Sara Moss provides endowed support for MIT’s Summer Research Program in Biology.
Department of Biology
January 27, 2021
Last month, the Department of Biology received a generous gift from Michael Gould and Sara Moss to support students participating in MIT’s Summer Research Program in Biology (MSRP-Bio). Gould is a philanthropist and the retired chair and CEO of Bloomingdales, and Moss is the vice chair of Estée Lauder Companies. Their gift will supplement the existing Bernard S. and Sophie G. Gould Fund, which the couple initiated in 2015 to honor Gould’s parents. Together, these donations will enable many undergraduate students from outside MIT who are interested in a career in life science to participate in MSRP-Bio each summer. To honor the Gould family’s generosity, MSRP-Bio will be renamed the Bernard S. and Sophie G. Gould MIT Summer Research Program in Biology, or BSG-MSRP-Bio.
“We are deeply grateful to Mike and Sara for their commitment to and support for our community,” says department head and Praecis Professor Alan Grossman. “Their willingness to enable opportunities for students will allow many talented individuals to benefit from research experiences here at MIT, and foster the next generation of scientists.”
“Mike Gould and Sara Moss are amazing people,” says Mandana Sassanfar, the Department of Biology’s director of outreach. “They’ve made a generous gift that has enabled MRSP-Bio to give many deserving undergraduates a life-changing summer research experience.”
MSRP-Bio is a 10-week summer program offered to non-MIT undergraduates, which provides access to cutting-edge facilities and supervised research in a fast-paced environment. The program encourages students from groups that are historically underrepresented in science, first-generation college students, students from economically disadvantaged backgrounds, and students with disabilities to attend graduate school and pursue careers in basic research.
Every year, roughly 20 participants are placed in laboratories affiliated with the Department of Biology. In total, nearly 400 students have participated in MSRP-Bio since its establishment in 2003. Nearly 300 have already gone to PhD or MD/PhD programs, and of these, 63 have enrolled at MIT for graduate school and 45 have joined the Department of Biology specifically.
Gould and Moss were inspired to create a fund supporting MSRP-Bio because both of Gould’s parents were MIT alumni devoted to mentorship. Bernard “Bernie” Gould ’32 was a beloved biochemistry professor in the Department of Biology and counseled many biology and pre-med students for 50 years. His wife, Sophia Gould CMP ’48, earned a master’s degree in public health at a time when there were few female graduate students at the Institute, and shared this passion for training students.
“I’ve been inspired by my father, who was a first-generation American, cared enormously about his students, and nurtured their intellectual curiosity and drive,” Michael Gould says. “MSRP-Bio does the same by giving each student the opportunity of a lifetime. My dream is for every department at MIT to create a similar program. It would enrich the Institute immeasurably.”
“This gift will have a tremendous impact on the MSRP-Bio program in the biology department, and comes at a crucial time as issues surrounding diversity, equity, and inclusion remain key priorities for the School of Science and Institute,” says Nergis Mavalvala, dean of MIT’s School of Science.
Since its inauguration in 2015, the Bernard S. and Sophie G. Gould Fund has offered scholarships to 30 MSRP-Bio students — six each year. Every summer, Gould and Moss travel to campus to get to know the current Gould fellows. The duo has been continually impressed by the caliber of students, and decided to provide more support to fund additional fellows and ensure the program’s longevity.
“Mike and Sara have a sustained interest in the well-being and success of the Gould fellows, and take pride in these students’ accomplishments,” Sassanfar says. “The Gould Fellowship stands out because of the open relationship between the Mike and Sara and the fellows, which forges meaningful connections that will last for many years.”
Participating in MSRP-Bio was a “life-changing” experience, says former Gould Fellow Meucci Ilunga. “I genuinely mean that — I can only imagine how different my life would be if I had not had that opportunity.”
Former Gould Fellow Asmita Panthi adds that MSRP-Bio showed her what she was capable of accomplishing, and gave her the confidence to apply to graduate school. “I’m so thankful for this impactful fellowship, which gives students like me — who come from small undergraduate institutions or humble backgrounds — the chance to participate in a rigorous research program.”