Category: Faculty Locations

Enzymes that assemble into droplets can speed up cellular reactions

MIT biologists find highly concentrated droplets can help cells keep enzymes organized and control growth signals.

Anne Trafton | MIT News
June 1, 2026

Within the past decade, biologists have discovered that one strategy cells use to keep their contents organized is a phenomenon known as phase separation.

Similar to the way oil forms droplets that float in a vinegar solution, proteins inside cells can phase separate to form highly concentrated droplets that keep them organized within the cell. In a new study, MIT researchers have now shown that this droplet formation is critical for controlling the function of a class of enzymes called kinases.

The researchers found that condensing into droplets optimizes the biochemical conditions needed for kinases to catalyze reactions, allowing them to more rapidly activate cell signaling pathways. In some cases, droplet formation can even change which reactions the kinases perform.

“Many biological molecules have this propensity to spontaneously separate. We were really interested in asking, if we have these kinases forming droplets, what is the consequence of that in the context of signaling?” says Lindsay Case, an assistant professor of biology at MIT and the senior author of the study.

Learning more about how these droplets form could help researchers design drugs that target kinases, some of which can be overactive in cancer cells.

“Understanding the chemistry of these compartments, and what molecules go into them and what molecules don’t go into them, could help us design drugs that better localize to their target of interest,” Case says.

Nicholas Lea, an MIT graduate student, is the lead author of the paper, which appears today in Cell Reports.

Forming droplets

Since her days as a graduate student, Case has been studying how the physical organization of molecules inside cells affects their function. As a postdoc, she began studying how phase separation might affect a signaling pathway that allows cells to sense when they’re attached to their environment, so they can respond appropriately.

Some of the proteins in this pathway are kinases, which activate other proteins by adding phosphate groups to them. Kinases can also activate themselves through a process called autophosphorylation.

“Inside of the cell, you have these kinase molecules that are responsible for carrying a signal through the cell, and we know that the organization of these molecules changes. When the information is present, they’re organized in a different way than when the information is not present,” Case says. “We think that having the right molecules in the right place is incredibly important for the right biochemistry to occur.”

Phase separation is one of the methods that cells appear to use for this organization. The most familiar example of phase separation can be seen in a salad dressing, where oil forms droplets to minimize contact with water-based vinegar. Proteins can phase separate when they are highly concentrated, leading them to self-assemble into dense droplets floating in the cell’s cytoplasm.

Case hypothesized that this phase separation, which brings kinases together at a high density, might help cells to boost the enzymes’ activity because they are more likely to bump into and phosphorylate each other.

In this study, Case and Lea set out to test that hypothesis, focusing on an enzyme called focal adhesion kinase (FAK). This kinase, which becomes activated when cells attach to their surrounding environment, activates pro-growth and pro-survival signals. In cancer cells, this signaling pathway can go awry, allowing cells to proliferate even when they detach from their original locations.

Scientists already knew that when cells are properly attached to their environment, that adhesion signal causes FAK to accumulate at the cell membrane. In the new study, the MIT team mimicked that effect by overexpressing FAK in cells. These cells were floating freely in a solution, not attached to any surface. Even so, the high concentration of FAK caused the kinase to phase separate into droplets, which turned on the pro-growth signal.

“It was surprising that just by condensing this protein into a droplet, you can actually turn on a signaling pathway that should be turned off,” Case says. “If FAK concentration is too high, you’re always getting these droplets and you’re always signaling, regardless of what the receptors that are supposed to be controlling this are doing.”

The findings suggest that in cancer cells, overexpression of FAK may lead to phase separation, which then helps to drive cancer progression and metastasis.

“It may be that for some kinases, you’re not supposed to form these droplets in the cytoplasm because it leads to this always-on signal, and then the cells no longer listen to the information coming from the environment,” Case says.

Interfering with FAK’s ability to form droplets could offer a new strategy for cancer drug development, she says.

Controlling reactions

The researchers also studied two other kinases, Mst2 and Abl. They found that these enzymes could also phase separate at high concentrations, and that this increased their activity. While phase separation of FAK in the cytoplasm may occur only in cancerous cells, for Mst2, it appears to be a strategy that healthy cells use to control a signaling pathway called Hippo, which promotes cell growth and survival.

Additionally, for both Mst2 and Abl, the researchers discovered that phase separation can lead the enzymes to phosphorylate additional targets, which may lead them to activate different signaling pathways.

“It’s not just that you’re getting faster phosphorylation, but in those cases, the patterns of what is actually getting phosphorylated were very different inside of the droplet compared to what might be happening in a non-droplet context,” Case says. “The kinase is able to phosphorylate amino acid residues beyond the set of canonical sites that have been described before.”

The researchers also found that when these droplets form, they attract high concentrations of ATP, the molecule that kinases use as a source of phosphate. This occurs because kinases tend to contain floppy sections containing many positively charged amino acids, which attract negatively charged ATP.

Using a machine-learning model, the researchers predicted that about 45 percent of the 500 kinases found in human cells would have the ability to form droplets like those seen in this study. Those kinases were also more likely to be highly positively charged, which could help them to recruit ATP into the droplets.

In future work, Case hopes to explore the possibility of designing drugs that could mimic ATP’s ability to be attracted into droplets within a cell, which could help reduce negative side effects of the drugs.

“By localizing drugs to the compartment where your target localizes, that could reduce off-target effects by concentrating the drug with the target of interest and reducing interactions with other molecules,” Case says.

The research was funded by a Searle Scholars Program Award, the U.S. Air Force Office of Scientific Research, the National Institutes of Health, the Royal G. and Mae H. Westaway Family Memorial Fund, and a David H. Koch Graduate Fellowship.

Scientists map which genes are active in a developing seed to build hardier crops

Many of the basic biological processes that allow seeds of global food staples like wheat, rice, and corn, to grow, transport nutrients, and develop useful traits like withstanding heat and drought are not yet fully understood. A new gene expression map of seed development offers a framework to better understand, and even guide, seed development to improve crop productivity.

Shafaq Zia | Whitehead Institute
May 19, 2026

Seeds like wheat, rice, and corn are at the center of the global food supply and provide most of the daily calories consumed worldwide. But despite their importance, scientists still do not fully understand many of the basic biological processes that allow these seeds to grow, transport nutrients, and develop traits that determine crop resiliency.

With fluctuating environmental conditions and other stressors threatening agriculture, there is a need to develop hardier crops better able to withstand heat, drought, and changing soil conditions. Scientists are increasingly looking to understand the hidden biology of seed development that could one day help them achieve this.

Now, researchers in the lab of Mary Gehring have created a detailed gene expression “map” of seed development in Arabidopsis thaliana, a small flowering plant in the mustard family that is widely used to study plant biology and is closely related to major crops like canola.

This map, also known as a transcriptional atlas, shows which genes are turned on or off in different cell types as the seed develops. Active genes make messenger RNA (mRNA) that guides the production of proteins necessary for cellular processes. By tracking which genes are active where, researchers can better understand the role each cell type plays across different stages of seed development.

The work, published May 21 in Nature Plants, offers scientists new clues about how plants coordinate key biological processes tied to agriculturally significant traits, including seed size and nutrient storage.

“Seeds are fundamental to sustaining human life,” says Caroline (Carly) Martin, lead author of the paper and a graduate student in the Gehring Lab. “By building this atlas, we now have a framework researchers can use to start asking much more precise questions about how seeds develop and if those processes might eventually be improved in different crops.”

Unlike previous atlases of Arabidopsis, which do not distinguish many cell types due to technological limitations, the new atlas provides a more complete and higher resolution view of the developing seed. The researchers have captured seed development at three precisely timed stages after pollination when the plant embryo, the nutrient-rich tissue that feeds it (called the endosperm), and the surrounding tissues from the mother plant rapidly grow and reorganize. Using this dataset, they have identified where genes that regulate how seeds grow and store nutrients are active.

The researchers have found a small group of cells near the plant embryo that activate genes involved in producing brassinosteroids, plant hormones that regulate growth. Previous studies had shown that disrupting the production of this hormone can reduce seed size, but it was not known where within the developing seed the hormone is made.

The new data shows that these hormone-producing cells sit directly next to cells in the endosperm that might respond to the hormone. This close arrangement suggests the two cell types may work together to help fine-tune seed size.

The atlas has also revealed that the endosperm, which nourishes the embryo during development and later becomes the edible portion of many staple crops, contains far more specialized cell types than previously understood by researchers.

The team has identified a small “founder” population of cells that may help establish a key region of the endosperm located at the boundary where nutrients enter the seed from the mother plant.

Because the amount and timing of resources supplied by the mother plant determine how much energy the seed can store, this region of the endosperm helps shape the seed’s nutritional profile. These reserves — oils, starches, and proteins — are essential for both seed development and human nutrition.

These findings, taken together, could allow researchers to better understand — and even guide — seed development to improve crop productivity.

“We’re already seeing that seed filling in many crops is vulnerable to heat stress,” says Gehring, who is also a professor of biology at MIT and an investigator at the Howard Hughes Medical Institute (HHMI). “If we are to solve the humanitarian crises of food insecurity and malnutrition, we need to understand, at a fundamental level, how seeds of different crops form, store nutrients, and survive environmental stress.”

Caroline A. Martin, Kylee R. Cogdill, Alesandra L. Pusey, and Mary Gehring. “A transcriptional atlas of early Arabidopsis seed development suggests mechanisms for inter-tissue coordination.” Nature Plants, May 21, 2026. https://doi.org/10.1038/s41477-026-02295-8

How tissues tune immune responses to match the threat

Organs which interface with the outside world, like the lungs, skin, and intestines, must balance responding quickly to threats while also avoiding triggering unnecessary inflammation. A new study has found that immune sensitivity in the communities of epithelial cells that line the lungs is not evenly distributed, with cells deeper in the tissue more likely to sound the alarm in response to a threat such as viruses, microbes, allergens, and other particles.

Mackenzie White | Whitehead Institute
May 14, 2026

Barrier organs that form boundaries between the body and the outside environment, such as the lungs, skin, and intestines, face a difficult balancing act. They must respond quickly to threats such as infection, but they also need to avoid triggering unnecessary inflammation that can damage the tissue. A new study led by Whitehead Institute member Pulin Li and graduate student in her lab Diep Nguyen reveals one way the lung manages that tradeoff.

Published on May 15 in Cell Systems, the research found that immune sensitivity is not evenly distributed across the lung. Instead, it arranges in tiers: cells at the outer surface respond cautiously, while cells deeper in the tissue are more likely to sound the alarm when a threat breaks through.

“The central question was how tissues balance the benefits and harmful effects of immune activation when they face different degrees of danger or stress,” says Li, who is also a professor of biology at MIT. “Too little immune activation leaves the tissue unprotected, but too much can create inflammation and damage.”

The team focused on the lung, where epithelial cells line the airways and air sacs and form a physical barrier between the body and the outside world. These cells sit at the point of first contact with inhaled viruses, microbes, allergens, and other particles. For that reason, they are often thought of as front-line defenders.

But the new study suggests that the lung’s outermost defenders are deliberately cautious.

Using mouse models of influenza infection and imaging methods that allowed them to measure infection and immune responses in individual cells, the researchers found that epithelial cells were the least likely to respond to infection by producing interferons, signaling proteins that help alert the immune system. Cells deeper in the tissue, especially endothelial cells that line blood vessels, were much more likely to respond.

This arrangement suggests that the lung uses location as a clue to the seriousness of a threat. A stimulus that remains at the surface may not require a large immune response. But when infection breaches the epithelial barrier and reaches deeper tissue, the lung treats that as a more dangerous threat and activates a stronger defense.

“A less severe threat only requires a lower level of immune response,” says Nguyen. “As a threat goes deeper into the tissue, the inner cell types can encode that information and indicate that the threat has invaded further.”

The researchers traced these differences in sensitivity, in part, to immune-sensing proteins called pattern recognition receptors. These receptors detect molecular signs of infection or damage. One receptor, RIG-I, helps cells recognize viral RNA. Epithelial cells had relatively low levels of RIG-I and related sensors, while deeper stromal cells had higher levels.

That lower sensitivity appears to protect the lung from unnecessary damage. When the researchers increased RIG-I levels in lung epithelial cells in mice, the animals mounted a stronger immune response to a non-infectious inflammatory trigger. But the heightened response caused more tissue damage and interfered with repair.

The finding helps explain why the lung’s surface cells may be tuned not to overreact. The lung constantly encounters harmless or low-level irritants. If epithelial cells responded too readily, they could turn minor disturbances into damaging false alarms.

The researchers also found evidence that similar patterns may exist in other barrier organs, including the intestine and trachea. That raises the possibility that spatially tiered immune sensing is a broader strategy for protecting organs that face the outside world.

“One impact of this work is that it helps us look at an old question in a new way: how do tissues balance protection with tissue damage?” says Nguyen. “We can start to understand that when we look at the building blocks of the tissue and how they work together.”

Li says the work also reflects the value of studying tissues as communities of cells rather than collections of identical responders.

“To understand physiology, you have to take a multicellular approach,” she says. “Thinking about tissues as communities of cells can reveal new insights into how they function.”

Diep H. Nguyen, Jiakun Tian, Sean-Luc Shanahan, Connie Kangni Wang, Tyler Jacks, Xiao Wang, and Pulin Li. “A tissue-scale strategy for sensing threats in barrier organs.” Cell Systems, May 14, 2026. https://doi.org/10.1016/j.cels.2026.101611

Whitney Henry among MIT affiliates named 2026 Searle Scholars

Computational neuroscientist Sven Dorkenwald and cell biologist Whitney Henry, along with two MIT alumni, are recognized for their exceptional early-career research contributions.

Julie Pryor | Bendta Schroeder | McGovern Institute for Brain Research | Koch Institute
May 20, 2026

MIT scientists Sven Dorkenwald and Whitney Henry have been named 2026 Searle Scholars, an award given annually to 15 exceptional early-career researchers in the fields of biomedical sciences and chemistry. Dorkenwald is an assistant professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research. Henry is the Robert A. Swanson (1969) Career Development Professor of Life Sciences and an intramural faculty member at the Koch Institute for Integrative Cancer Research.

In addition, MIT alumni Irene Kaplow ’10 and Jared Mayers PhD ’15 were also honored.

Chosen by a scientific advisory board, Searle Scholars are considered among the most creative young researchers pursuing high-risk/high-reward research. The Searle Scholars Program is funded through the Searle Funds at The Chicago Community Trust and administered by Kinship Foundation. Each scholar will each receive $450,000 in flexible funding to support their work over the next three years.

Sven Dorkenwald

Sven Dorkenwald is a computational neuroscientist investigating the organizational principles of neuronal circuits. The synaptic connectivity of neurons, their connectome, is fundamental to how networks of neurons function. Dorkenwald develops computational and collaborative tools to map, analyze, and interpret synapse-resolution connectomes. His work has led to large connectomic reconstructions of the fruit fly brain and parts of mammalian brains. He uses these connectomes to investigate the architecture of neuronal circuits and how their structure supports complex computations.

“As I establish my new lab, the Searle Scholars Award will help us launch ambitious projects and set our long-term scientific direction,” says Dorkenwald. “I am deeply grateful for the support from the Kinship Foundation and look forward to interacting with this amazing cohort of Searle Scholars.”

Dorkenwald joined the faculty of MIT in 2026 as an assistant professor in the Department of Brain and Cognitive Sciences and an investigator at the McGovern Institute. He earned a BS in physics and an MS in computer engineering from the University of Heidelberg, followed by a PhD in computer science and neuroscience at Princeton University in 2023 under the mentorship of Sebastian Seung and Mala Murthy. Dorkenwald completed his postdoctoral training as a Shanahan Research Fellow at the Allen Institute and the University of Washington, while serving as a visiting faculty researcher at Google Research.

Whitney Henry

Whitney Henry investigates the potential of ferroptosis, an iron-dependent form of cell death, for developing novel therapies that target subpopulations of cancer cells that are highly metastatic, therapy-resistant, and therefore critical instigators of tumor relapse. Her research is focused on uncovering the molecular factors influencing ferroptosis susceptibility, investigating its effects on the tumor microenvironment, and developing innovative methods to manipulate ferroptosis resistance in living organisms, drawing from functional genomics, metabolomics, bioengineering, and a range of in vitro and in vivo models.

“I am incredibly grateful to the Kinship Foundation for supporting our research and giving us the freedom to ask bold, curiosity-driven scientific questions,” says Henry. “This support allows us to pursue ambitious ideas, take creative risks, and embark on new research directions.”

Henry joined the MIT faculty in 2024 as an assistant professor in the Department of Biology and a member of the Koch Institute, and is currently an HHMI Freeman Hrabowski Scholar. She received her bachelor’s degree in biology with a minor in chemistry from Grambling State University and her PhD from Harvard University. Following her doctoral studies, she worked in the lab of Robert Weinberg at the Whitehead Institute for Biomedical Research and was supported by fellowships from the Jane Coffin Childs Memorial Fund for Medical Research and the Ludwig Center at MIT.

Alumni also honored

Irene Kaplow ’10, a graduate of the MIT Department of Mathematics, is an assistant professor in the Department of Biology and the Ray and Stephanie Lane Computational Biology Department at Carnegie Mellon University. Her selection as a Searle Scholar is for “deciphering transcriptional regulatory mechanisms underlying mammalian dietary phenotype evolution and their relationships to transcriptional regulatory responses to changes in diet.”

Jared Mayers PhD ’15, who earned his doctorate from the MIT Department of Biology, is an assistant professor at the Fred Hutchinson Cancer Center at the University of Washington. His selection as a Searle Scholar is for “a reverse-translational framework to decipher metabolic vulnerabilities of bacterial pathogens.”

Biologist Joey Davis explores how cells build complex structures

His studies have shed light on the assembly instructions that govern ribosomes, the critical protein-building machines of the cell.

Anne Trafton | MIT News
May 5, 2026

Ribosomes, the cellular machines that assemble proteins, are made from dozens of proteins and RNA molecules. Putting all of those pieces together is a complex puzzle — one that MIT Associate Professor Joey Davis PhD ’10 revels in trying to solve.

Understanding how these structures form and later break down could help researchers learn more about how disruptions of these fundamental processes can lead to disease. But, as Davis points out, it’s also an interesting biological question.

“Our long-term goal is to really understand how the natural world assembles these huge complexes rapidly and efficiently. It’s a fundamentally interesting question to think about how these things get put together,” he says.

His work has helped reveal that unlike building a house, which happens in a prescribed sequence of steps — pouring the foundation, building the frame, putting on the roof, then doing electrical and plumbing work — ribosomes can be assembled in a more flexible way. Cells can even skip an assembly step and then come back to it later.

“In these natural systems, it seems like the assembly pathways are much more dynamic and flexible,” he says. “It appears that evolution has selected pathways that aren’t strictly ordered in the way we would think about an assembly line, where you always put in one component, then the next, and then the next. We’re excited to understand the selective advantages of such approaches.”

A love of discovery

Davis’ interest in how things are put together developed early in life, inspired by his father, a carpenter who framed houses. During the mid-1980s, the family moved from Colorado to Southern California, where his father worked in construction during a housing boom there.

“I was always interested in building things, which I think probably came from being around my dad and other builders,” Davis says.

As an undergraduate at the University of California at Berkeley, where he majored in computer science and biological engineering, Davis’ interests turned toward smaller scales, in the realm of cells and molecules. During his junior year, he started working in the lab of chemistry professor Michael Marletta, who studies molecular-level biological interactions.

In the lab, Davis investigated how enzymes that contain heme are able to preferentially bind to either oxygen or nitric oxide, two gases that are very similar in structure. That work kindled a love of studying the natural world and pursuing discoveries in fundamental science.

“Being in the Marletta lab and seeing students and postdocs that were really passionate about these problems had a big impact on me,” Davis says. “The goal was to understand the fundamentals of how molecular discrimination works, and the idea of discovery for the sake of discovery was thrilling.”

After graduating from Berkeley, Davis spent another year working in Marletta’s lab, and then a year working odd jobs, before heading to MIT to pursue a PhD in biology. There, he worked with Professor Bob Sauer, now emeritus, who studied the relationship between protein structure and function, with a particular focus on the molecular machines that degrade or remodel proteins.

Davis’ thesis research centered on enzymes called AAA proteases, which remove damaged proteins from cellular membranes and send them to cell organelles that break them down. In addition to studying the structure and function of the proteases, Davis worked on ways to engineer them to tag specific proteins for destruction.

That work led him into synthetic biology, which he used to develop genetic parts that drive production of proteins of interest. Some of those parts ended up being used by the biotech startup Ginkgo Bioworks, where Davis took a job as a senior scientist after graduating.

Working at Ginkgo Bioworks allowed Davis to stay in Boston while his partner finished her PhD. The couple then moved back to California, where Davis worked as a postdoc at Scripps Research, which was home to one of the first direct electron detection cameras for cryo-electron microscopy (cryo-EM). These detectors allow researchers to generate structures with near atomic resolution. At Scripps, Davis began using them to study ribosomes as they were being assembled.

Peering into the ribosome

After joining the MIT faculty in 2017, Davis continued his work on ribosomes and assembled a lab group that includes students from a variety of backgrounds who work together to develop new ways to explore biological phenomena.

“I have a mix of method developers and biologists in the group, and the work from each of them informs each other,” Davis says. “My lab goes back and forth between building sets of tools to answer biological questions, and then as we’re answering those questions, it motivates the next generation of tool development.”

During ribosome assembly, RNA molecules fold themselves into the correct shapes, creating docking sites for proteins to attach. Then, more RNA molecules come in and fold themselves into the structure.

“It’s a beautifully coupled process by which the cell folds hundreds of RNA helices and binds on the order of 50 proteins, and it does it in two minutes from start to finish. E. coli does this 100,000 times per hour, and it’s amazing how rapid and efficient the process is,” Davis says.

Cryo-EM allows scientists to capture this process in minute detail. It can be used to take hundreds of thousands of two-dimensional images of ribosome samples frozen in a thin layer of ice, from different angles. Computer algorithms then piece together these images into a three-dimensional representation of the ribosome.

To gain insight into how ribosomes are assembled, researchers can stall the process at different points and then analyze the resulting structures. In 2021, Davis’s lab developed a new method called CryoDRGN, which uses neural networks to analyze cryo-EM data and generate the full ensemble of structures that were present in the sample.

This work has shown that when certain steps of ribosome assembly are blocked, many different structures result, suggesting that the assembly can occur in a variety of ways.

In future work, Davis aims to dramatically increase the throughput of cryo-EM to generate datasets of protein structures that could help improve the AI-based models that are now used to predict protein structures.

“There are still huge swaths of sequence space that these models are very poor at predicting, but if we could collect data on those sequences en masse, that could potentially serve as key training data for a next-generation protein structure prediction method that could fill out that space,” he says.

Q&A: Why feeling sick may be important for surviving infection

Zuri Sullivan studies sickness behavior to understand how the immune system communicates with the brain to produce changes during illness, hoping to learn more about how the brain interprets immune signals, how these responses may help organisms fight infection, and what they could reveal about disease and immunity.

Shafaq Zia | Whitehead Institute
April 30, 2026

Now, in a new perspective published in Trends in Immunology on April 30, Whitehead Institute Member Zuri Sullivan and colleagues propose a different way of thinking: what if these behaviors are part of an integrated immune strategy that operates across scales — from individual cells to tissues and organs, to the whole organism — and helps promote survival?

Sullivan studies “sickness behavior” to understand how the immune system communicates with the brain to produce these changes during illness — and what they can reveal about how the body coordinates its defense. This work points to a broader biological question: how living systems, from single cells to whole organisms, detect and respond to threats.

We sat down with Sullivan to learn more about how the brain interprets immune signals, how these responses may help organisms fight infection, and what they could reveal about disease and immunity. This interview has been edited for length and clarity.

Whitehead Institute: What led you to start thinking about sickness behavior as a form of whole-organism immunity?

Zuri Sullivan: In graduate school, I found that immune cells in the intestine do more than defend against pathogens — they also help regulate how the body responds to food by changing how intestinal tissue functions depending on the diet.

That work shifted how I thought about immunity, from a local defense system to something broader: a whole-body program that helps shape how we interact with the environment in ways that support survival, including avoiding foods that are harmful or allergenic.

That idea stayed with me in my postdoctoral work in neuroscience, where I studied sickness behavior — things like reduced appetite and social withdrawal during infection. I was interested in how inflammation affects behavior, especially through the hypothalamus, a brain region that controls many of the body’s responses during illness.

Putting those two lines of work together — immunology and neuroscience — led me to an integrated view in which immunity operates across scales, shaping both bodily function and behavior as part of a coordinated system.

WI: We often think of the brain and immune system as separate systems. How are they connected, and why does this connection matter?

ZS: For a long time, the brain was thought to be mostly separate from the immune system, protected by what’s called the blood–brain barrier, which tightly controls what can enter the brain from the bloodstream. That barrier is still very important, but we now know the brain isn’t isolated. The brain and immune system communicate with each other, and that communication can influence both brain activity and behavior. This connection is called the brain–immune axis.

The brain–immune axis is one of the ways the body senses and responds to what’s happening in the outside world. The nervous system does this through our senses, while the immune system uses molecular sensors to detect pathogens and other signs of danger.

The two-way communication between these systems helps coordinate how the body responds to threats. We see this most clearly during infection, in what’s called sickness behavior — things like loss of appetite, fatigue, or social withdrawal. But this connection also matters beyond infection, including in conditions like long COVID and the effects of chronic inflammation on the brain.

In our work, we try to construct  a bigger picture of how the body protects itself. Individual cells can defend themselves, tissues like the gut can mount local immune responses, and the brain–immune axis represents the highest level of this system, where the immune system and the brain coordinate to affect both physiology and behavior across the whole body as part of a unified defense response.

WI: Is the brain–immune axis disrupted in chronic diseases like long COVID or other neuropsychiatric disorders?

ZS: In some conditions, the immune response that is normally helpful can become dysregulated. This can happen after infections or due to genetic and environmental factors. When that happens, it can lead to chronic inflammation that starts to damage tissues—for example, scarring in the lungs after infection, or conditions in the gut like inflammatory bowel disease (IBD) or irritable bowel syndrome (IBS).

There are still two main possibilities being studied for long COVID. One is that a small amount of virus remains in the body and keeps the immune system activated. The other is that the virus is gone, but the brain–immune axis becomes dysregulated and keeps the immune system in an activated state. Researchers are still working to distinguish between these two.

What’s also striking is that there are strong associations between inflammation and both neurodevelopmental and neuropsychiatric disorders. For example, people with autism have higher rates of inflammatory gut conditions like IBD and IBS, and many also experience gastrointestinal symptoms. People with IBD and IBS are associated with being at a higher risk of developing anxiety and depression, especially during a flare-up.

What this suggests is that brain–immune communication can influence both brain function and body function in both directions. The challenge now is figuring out causality — whether inflammation drives changes in the brain, the brain drives inflammation, or if it’s a feedback loop between the two.

WI: How can your proposed framework inform how we think about treating infections in the clinic?

ZS: I think it can inform treatment in a few ways. Right now, when people get sick, we often focus on treating symptoms: reducing fever with medications like Tylenol, overriding behaviors like reduced appetite by providing nutrition through feeding tubes in critically-ill patients. But if sickness behavior is part of an organized response, then it becomes important to understand what these behaviors are actually doing before deciding when to suppress them and when to support them.

A useful example comes from a 2016 mouse study. Researchers found that force-feeding sick mice using feeding tubes had a different outcome based on the type of infection they had. Mice with a bacterial infection became more likely to die, but mice with a viral infection had improved survival. What this tells us is that behavioral changes like reduced appetite may actually be tuned to the type of immune challenge the body is facing. So, if we could understand how these behavioral changes affect the course of infection, it could help clarify which interventions are helpful and which might interfere with recovery.

There are also implications beyond acute infection, especially for conditions like long COVID and other neuropsychiatric or post-inflammatory disorders. One key possibility is that the immune system is playing a causal role in either triggering or maintaining some of these conditions. If that’s the case, it becomes especially relevant that the immune system is highly “druggable”— there are already many therapies that target immune pathways. So, understanding how immune signals influence the brain could open up new ways to intervene in conditions where current treatments aren’t working for patients.

What we need is a better map of how different infections affect the brain over time—what we might call “neural signatures” of infection. In animal studies, where we can track both immune responses and brain activity over time, we can start to build that kind of map: how you go from a healthy state and through infection to changes in brain function and behavior.

The hope is that this kind of framework would eventually help us interpret complex symptoms during and post-infection in humans and have more targeted ways to treat them.

How stem cell descendants preserve flexibility while maintaining distinct identities

In many tissues, some early descendants of stem cells, the body's ultimate shape-shifters, can revert back to a stem cell state through a process known as dedifferentiation. Researchers in the Yamashita Lab have identified two complementary mechanisms that allow cells to preserve stem cell potential while adopting distinct identities.

Mackenzie White | Whitehead Institute
April 6, 2026

Stem cells are the body’s ultimate shape-shifters, sustaining tissues by balancing two competing demands: maintaining their own population and generating specialized descendants. In many tissues, some early descendants can revert to a stem cell state through a process known as dedifferentiation. This ability can help replenish the stem cell pool when stem cells are lost.

In a new study published on April 6 in PNAS, researchers at Whitehead Institute identify two complementary mechanisms that allow cells to preserve stem cell potential while adopting distinct identities.

Led by Whitehead Institute Member Yukiko Yamashita and Yamashita Lab postdoc Amelie Raz, the study focuses on the male fruit fly germline stem cells, which give rise to sperm. These cells sit at the foundation of a lineage that continues across generations.

To understand what distinguishes these stem cells, the researchers analyzed RNA, the intermediary molecules that link genes in DNA to the proteins they encode. RNA quantities typically reflect which genes a cell is using—which in turn reflects a cell’s identity. The researchers expected to find a set of RNAs unique to stem cells. Instead, they discovered that stem cells and their immediate descendants share seemingly identical RNA profiles.

“We didn’t have anything that was specific to stem cells,” Raz says. “It turned out that that was actually the key to understanding how you make them.”

The difference between these cell types lies not only in which RNAs are present, but in whether the cells are still making them. Stem cells continue producing these RNAs, while their descendants inherit many of the same molecules but stop making new copies of RNA.

This means RNA alone does not fully define a cell’s state. In these descendant cells, the shared RNAs reflect an earlier state, not the same productive gene program seen in stem cells.

“On the level of RNA, they’re the same,” Raz says. “But they’re different in what’s actually happening in the nucleus—whether that RNA is being actively produced.”

The study also clarifies how signals from the surrounding environment help determine what path a cell follows. Stem cells reside in a specialized microenvironment known as a niche, which sends molecular cues that influence cell behavior. Two well-studied signaling pathways—Bmp and Jak-Stat—have long been known to regulate germline stem cells.

Previous models assumed these pathways worked together or redundantly. However, the new findings show that they instead act independently, each controlling a different subset of genes.

“What we found was that they’re acting on completely separate parts of this gene activity program,” Raz says.

Because the pathways operate independently, their combined activity defines distinct cellular states. When both signals are active, cells maintain stem cell identity. When neither is active, cells continue along a differentiation pathway. When only one pathway is active, cells can revert toward a stem cell state through dedifferentiation. This modular arrangement allows cells with the same underlying potential to follow different paths depending on the signals they receive.

The findings help explain why many stem cell populations rely on multiple signaling pathways. Rather than serving as backups for one another, these pathways can regulate different parts of cell behavior and work together to shape a cell’s trajectory.

“In many stem cell populations, multiple signals have been thought to be redundant,” says Yamashita, who is also a professor of biology at MIT and an HHMI Investigator. “Here, we show that they can have distinct roles to determine whether a cell self-renews, differentiates, or reverts in combination.”

More broadly, the work shows that knowing which molecules are present in a cell does not always reveal how that cell is functioning. Two cells can appear identical by standard molecular measures even when they are operating in different regulatory states.

The study also lays the groundwork for future research. Raz and colleagues have identified a set of genes linked to this early germline state in fruit flies and are now investigating what those genes do and how they help govern stem cell behavior.

“Now that we know what’s there, the next step is understanding what those RNA molecules are doing,” Raz says.

Additionally, the work suggests that long-standing models of stem cell regulation may be incomplete, even in systems that have been studied for decades.

“What we are showing is that these pathways aren’t necessarily working in the way people had assumed,” Raz says. “There’s almost certainly more to it.”

A. Raz, H. Hassan, & Y.M. Yamashita, Niche-dependent modular regulation of the stem cell transcriptome separates cell identity and potential, Proc. Natl. Acad. Sci. U.S.A. 123 (15) e2533973123, https://doi.org/10.1073/pnas.2533973123 (2026).

Professor Michael Laub named 2025 AAAS Fellow

The American Association for the Advancement of Science recognized Laub and 21 alumni for their efforts to advance science and related fields.

School of Science
April 17, 2026

MIT Professor Michael T. Laub as well as 21 MIT alumni have been elected as fellows of the American Association for the Advancement of Science (AAAS).

The 2025 class of AAAS Fellows includes 449 scientists, engineers, and innovators, spanning all 24 of AAAS disciplinary sections, who are recognized for their scientific achievements.

Laub, the Salvador E. Luria Professor in the MIT Department of Biology and an HHMI Investigator, studies the biological mechanisms and evolution of how cells process information to regulate their own growth and proliferation, using bacteria as a model organism to develop a deeper, fundamental understanding of how bacteria function and evolve. Laub was honored as a AAAS Fellow for distinguished contributions to the field of bacterial information processing, particularly to the understanding of coevolution of host-pathogen response and immunity.

“This year’s AAAS Fellows have demonstrated research excellence, made notable contributions to advance science, and delivered important services to their communities,” said Sudip S. Parikh, AAAS chief executive officer and executive publisher of the Science family of journals. “These fellows and their accomplishments validate the importance of investing in science and technology for the benefit of all.”

The following alumni were also named fellows of the AAAS:

  • Debra Auguste ’99
  • Julie Claycomb PhD ’04
  • Chris Clifton ’85, SM ’86
  • Kevin Crowston PhD ’91
  • Maitreya Dunham ’99
  • David Fike PhD ’07
  • Jianping Fu PhD ’07
  • Peter A. Gilman SM ’64, PhD ’66
  • Diane M. Harper ’80, SM ’82
  • Cherie R. Kagan PhD ’96
  • Elizabeth A. Kensinger PhD ’03
  • Kenro Kusumi PhD ’97
  • Charla Lambert ’96
  • Bennett A. Landman ’01, MNG ’02
  • Michael E. Matheny SM ’06
  • Paul David Ronney ScD ’83
  • Steven Semken ’80, PhD ’89
  • Sudipta Sengupta SM ’99, PhD ’06
  • Lawrence R. Sita PhD ’86
  • Jan M. Skotheim ’99
  • Beverly Park Woolf ’66
Slice and dice

SNIPE, a newly characterized defense system, directly protects bacteria by chopping up invading viral DNA.

Lillian Eden | Department of Biology
April 9, 2026

What if the Trojan horse had been pulled to pieces, revealing the ruse and fending off the invasion, just as it entered the gates of Troy?

That’s an apt description of a newly characterized bacterial defense system that chops up foreign DNA.

Bacteria and the viruses that infect them, bacteriophages — phages for short — are ceaselessly at odds, with bacteria developing methods to protect themselves against phages that are constantly striving to overcome those safeguards.

New research from the Department of Biology at MIT, recently published in Nature, describes a defense system that is integrated into the protective membrane that encapsulates bacteria. SNIPE, which stands for surface-associated nuclease inhibiting phage entry, contains a nuclease domain that cleaves genetic material, chopping the invading phage genome into harmless fragments before it can appropriate the host’s molecular machinery to make more phages.

Daniel Saxton, a postdoc in the Laub Lab and the paper’s first author, was initially drawn to studying this bacterial defense system in E. coli, in part because it is highly unusual to have a nuclease that localizes to the membrane, as most nucleases are free-floating in the cytoplasm, the gelatinous fluid that fills the space inside cells.

“The other thing that caught my attention is that this is something we call a direct defense system, meaning that when a phage infects a cell, that cell will actually survive the attack,” Saxton says. “It’s hard to fend off a phage directly in a cell and survive — but this defense system can do it.”

Light it up

For Saxton, the project came into focus during a fluorescence-based experiment in which viral genetic material would light up if it successfully penetrated the bacteria.

“SNIPE was obliterating the phage DNA so fast that we couldn’t even see a fluorescent spot,” Saxton recalls. “I don’t think I’ve ever seen such an effective defense system before — you can barrage the bacteria with hundreds of phage per cell, but SNIPE is like god-tier protection.”

When the nuclease domain of SNIPE was mutated so it couldn’t chop up DNA, fluorescent spots appeared as usual, and the bacteria succumbed to the phage infection.

Bacteria maintain tight control over all their defense systems, lest they be turned against their host. Some systems remain dormant until they flare up, for example, to halt all translation of all proteins in the cell, while others can distinguish between bacterial DNA and foreign, invading phage DNA. There were only two previously characterized mechanisms in the latter category before researchers uncovered SNIPE.

“Right now, the phage field is at a really interesting spot where people are discovering phage defense systems at a breakneck pace,” Saxton says.

Problems at the periphery

Saxton says they had to approach the work in a somewhat roundabout way because there are currently no published structures depicting all the steps of phage genome injection. Studying processes at the membrane is challenging: Membranes are dense and chaotic, and phage genome injection is a highly transient process, lasting only a few minutes.

SNIPE seems to discern viral DNA by interacting with proteins the phage uses to tunnel through the bacteria’s protective membrane. This “subcellular localization,” according to Saxton, may also prevent SNIPE from inadvertently chopping up the bacteria’s own genetic material.

The model outlined in the paper is that one region of SNIPE binds to a bacterial membrane protein called ManYZ, while another region likely binds to the tape measure protein from the phage.

The tape measure protein got its name because it determines the length of the phage tail — the part of the phage between the small, leglike protrusions and the bulbous head, which contains the phage’s genetic material. The researchers revealed that the phage’s tape measure protein enters the cytoplasm during injection, a phenomenon that had not been physically demonstrated before.

There may also be other proteins or interactions involved.

“If you shunt the phage genome injection through an alternate pathway that isn’t ManYZ, suddenly SNIPE doesn’t defend against the phage nearly as well,” Saxton says. “It’s unclear exactly how these proteins interact, but we do know that these two proteins are involved in this genome injection process.”

Future directions

Saxton hopes that future work will expand our understanding of what occurs during phage genome injection and uncover the structures of the proteins involved, especially the tunnel complex in the membrane through which phages insert their genome.

Members of the Laub Lab are already collaborating with another lab to determine the structure of SNIPE. In the meantime, Saxton has been working on a new defense system in which molecular mimicry — bacterial proteins imitating phage proteins — may play a role.

Michael T. Laub, the Salvador E. Luria Professor of Biology and a Howard Hughes Medical Institute investigator, notes that one of the breakthrough experiments for demonstrating how SNIPE works came from a brainstorming session at a lab retreat.

“Daniel and I were kind of stuck with how to directly measure the effect of SNIPE during infection, but another postdoc in the lab, Ian Roney, who is a co-author on the paper, came up with a very clever idea that ultimately worked perfectly,” Laub recalls. “It’s a great example of how powerful internal collaborations can be in pushing our science forward.”

Building the blocks of life

Computational biologist Sergei Kotelnikov is working to develop new methods in protein modeling as part of the School of Science Dean’s Postdoctoral Fellowship.

Lyn Nanticha Ocharoenchai | School of Science
March 31, 2026

Billions of years ago, simple organic molecules drifted across Earth’s primordial landscape — nothing more than basic chemical compounds. But as natural forces shaped the planet over hundreds of millions of years, these molecules began to interact and bond in increasingly complex ways. Along the way, something spectacular emerged: life.

“Life is, to some degree, magical,” says computational biologist Sergei Kotelnikov. Simple organic compounds congregate into polymers, which assemble into living cells and ultimately organisms — the whole being greater than the sum of its parts.

“You can write formulas on how a molecule behaves,” he says, referring to the world of quantum mechanics. “But yet somehow, a few orders of magnitude above, on a bigger scale, it gives rise to such a mystery.”

Kotelnikov builds models to analyze and predict the structure of these biomolecules, particularly proteins, the fundamental building blocks of every organism. This year, he joined MIT as part of the School of Science Dean’s Postdoctoral Fellowship to work with the Keating Lab, where researchers focus on protein structure, function, and interaction. Using machine learning, his goal is to develop new methods in protein modeling with potential applications that span from medicine to agriculture.

A hunger for problems to solve

Kotelnikov grew up in Abakan, Russia, a small city sitting right in the center of Eurasia. As a child, one of his favorite pastimes was playing with Lego bricks.

“It encouraged me to build new things, rather than just following instructions,” he says. “You can do anything.”

Kotelnikov’s father, whose background lies in engineering and economics, would often challenge him with math problems.

“Your brain — you can feel some kind of expansion of understanding how things work, and that’s a very satisfactory feeling,” Kotelnikov says.

This itch to solve problems led him to join science Olympiad competitions, and later, a science-focused public boarding school located near the Russian Academy of Sciences, from which he often encountered scientists.

“It was like a candy shop,” he recalls, describing the period as a life-changing experience.

In 2012, Kotelnikov began his bachelor of science in physics and applied mathematics at the Moscow Institute of Physics and Technology — considered one of the leading STEM universities in Russia, and globally — and continued there for his master’s degree. It was there that biology came into the picture.

During a course on statistical physics, Kotelnikov was first introduced to the idea of the “emergence of complexity.” He became fascinated by this “mysterious and attractive manifestation of biology … this evolution that sharpens the physical phenomenon” to create, drive, and shape life as we know it today. By the time he completed his master’s degree, he realized he had only scratched surface of the field of computational biology.

In 2018, he began his PhD at Stony Brook University in New York and began working with Dima Kozakov, who is recognized as one of the world’s leaders in predicting protein interactions and complex structures.

Studying the architecture of life  

Proteins act like the bricks that construct an organism, underpinning almost every cellular process from tissue repair to hormone production. Like pieces of a Lego tower, their structures and interactions determine the functions that they carry out in a body.

However, diseases arise when they’re folded, curled, twisted, or connected in unusual ways. To develop medical interventions, scientists break down the tower and examine each individual piece to find the culprit and correct their shape and pairing. With limited experimental data on protein structures and interactions currently available, simulations developed by computational biologists like Kotelnikov provide crucial insight that inform fundamental understanding and applications like drug discovery.

With the guidance of Kozakov at Stony Brook’s Laufer Center for Physical and Quantitative Biology, Kotelnikov carried over his understanding of physics to create modeling methods that are more effective, efficient, reliable, and generalizable. Among them, he developed a new way of predicting the protein complex structures mediated by proteolysis-targeting chimeras, or PROTACs, a new class of molecules that can trigger the breakdown of specific proteins previously considered undruggable, such as those found in cancer.

PROTACs have been challenging to model, in part because they are composed of proteins that don’t naturally interact with each other, and because the linker that connects them is flexible. Imagine trying to guess the overall shape of a bendy Lego piece attached to two other pieces of different irregular, unmatched shapes. To efficiently find all possible configurations, Kotelnikov’s method conceptually cuts the linker into two halves and models each separately, then reformulates the problem and calculates it using a powerful algorithm called Fast Fourier Transform.

“It’s kind of like applied math judo that you sometimes need to do in order to make certain intractable computations tractable,” he says.

Kotelnikov’s state-of-the-art methods have been instrumental to his team’s top performance in numerous international challenges including the Critical Assessment of protein Structure Prediction (CASP) competition — the same contest in which the Nobel Prize-winning AlphaFold system for protein 3D structure prediction was presented.

Physics and machine learning

At MIT, Kotelnikov is working with Amy Keating, the Jay A. Stein (1968) Professor of Biology, biology department head, and professor of biological engineering, to study protein structure, function, and interactions.

A recognized leader in the field, Keating employs both computational and experimental methods to study proteins, their interactions, as well as how this can impact disease. By infusing physics with machine learning, Kotelnikov’s goal is to advance modeling methods that can vastly inform applications such as cancer immunology and crop protection.

“Kotelnikov stands to gain a lot from working closely with wet lab researchers who are doing the experiments that will complement and test his predictions, and my lab will benefit from his experience developing and applying advanced computational analyses,” says Keating.

Kotelnikov is also planning to work with professors Tommi Jaakkola and Tess Smidt in MIT’s Department of Electrical Engineering and Computer Science to explore a field called geometric deep learning. In particular, he aims to integrate physical and geometric knowledge about biomolecules into neural network architectures and learning procedures. This approach can significantly reduce the amount of data needed for learning, and improve the generalizability of resulting models.

Beyond the two departments, Kotelnikov is also excited to see how the diversity and interdisciplinary mix of MIT’s community will help him come up with ideas.

“When you’re building a model, you’re entering this imaginary world of assumptions and simplifications and it might feel challenging because of this disconnect with reality,” Kotelnikov says. “Being able to efficiently communicate with experimentalists is of high value.”