Category: Faculty Locations

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.”

Leading with rigor, kindness, and care

“We cannot be effective scientists if we are unhappy or unhealthy outside of the lab,” says “Committed to Caring” honoree Sara Prescott.

Leila Hudson | Office of Graduate Education
March 27, 2026

Professor Sara Prescott embodies the kind of mentorship every graduate student hopes to find: grounded in scientific rigor, guided by kindness, and defined by a deep commitment to well-being. Her approach reflects a simple but powerful belief that transformative mentorship is not only about advancing research, but about cultivating confidence, belonging, and resilience in the next generation of scholars.

A member of the 2025–27 Committed to Caring cohort, Prescott exemplifies the program’s spirit, which honors faculty who go above and beyond in nurturing both the intellectual and personal development of MIT’s graduate students.

Prescott is the Pfizer Inc. – Gerald D. Laubach Career Development Professor in the MIT departments of Biology and Brain and Cognitive Sciences, and an investigator at the Picower Institute for Learning and Memory. Her research addresses fundamental questions in body-brain communication, with a focus on lung biology, early-life adversity, women’s health, and the impacts of climate change on respiratory health.

A culture of compassion

Prescott’s mentoring philosophy begins with a focus on professional sustainability. “We cannot be effective scientists if we are unhappy or unhealthy outside of the lab,” she says.

She pushes back against what she sees as an unhelpful narrative in academia. “There’s this idea that you must choose between a successful PhD or having a personal life. This is a false dichotomy, and a problematic attitude.” Instead, she reminds her mentees that “graduate school is a marathon, not a sprint,” encouraging them to place importance not only on their research, but also on their mental and physical well-being.

This set of values shines through within her lab climate as a whole. Students describe support for flexible scheduling and mental health leave, a willingness to reimburse meals during late-night lab sessions, and encouragement during stretches of experimental failure. In addition to these more technical supports, nominators also shared stories of Prescott engaging in the smaller details: prioritizing connection for her students, celebrating their milestones, organizing lab retreats, and fostering a culture where people feel valued beyond their productivity.

Students recognize Prescott as a safe haven within the often complex and challenging world of research. Joining Prescott’s lab was a turning point for one student who was recovering from a damaging prior mentorship experience. They arrived uncertain, struggling to trust faculty and questioning whether they belonged in science at all. Prescott met them with empathy and professionalism, offering patience and trust not just in their work, but in them as a person. They describe steady support that, over time, helped them “fall back in love with science” and envision a future they had nearly abandoned.

Prescott draws inspiration from the mentorship she received early in her career. As a trainee, she had mentors who helped her believe that she could succeed. Now in a mentoring role herself, she does her best to pass this sense of confidence on to her advisees.

She is intentional about creating space where students can grow without fear. From their very first meetings, one nominator wrote, Prescott emphasized that “graduate school is a place for learning and curiosity.” They never felt judged for not knowing something; instead, they were encouraged to ask questions, share ideas, and take intellectual risks. That environment, the student explained, allowed them to grow into their scientific identity with confidence.

Prescott reinforces this message often. Success, she tells students, grows from effort, learning, and persistence, rather than from fixed traits. When working with students, she does her best to reframe failure as part of the process, emphasizing its importance within the scientific journey. Through these avenues, she cultivates a lab culture where nominators are challenged to think boldly while feeling genuinely supported, and where her students are seen not only as researchers, but as whole people.

Advocacy beyond the bench

Prescott’s commitment to caring extends well beyond day-to-day lab work. Her nominators relate that she actively supports her students’ professional development, encouraging them to pursue writing projects, certificates, internships, leadership roles, and community engagement.

Nominators also highlight Prescott’s focus on supporting underserved communities within the field as a whole. Students highlight her involvement with Graduate Women in Biology (GwiBio), where she volunteered as a speaker for the “Glass Shards” series. Her talk “Failure as the Path to Success,” in which she candidly shared pivots and setbacks in her own career, was described as one of the organization’s most impactful sessions.

Her dedication to inclusion is equally evident in her mentorship of scholars whose role in her lab is more temporary.  She welcomes international visiting scholars, temporary lab techs, and undergraduate interns in the MIT Summer Research Program. When one intern encountered barriers at their home institution, Prescott ensured they had a continued research home in her lab at MIT. These additional resources allowed them to complete their undergraduate thesis and graduate on time from their university.

Prescott says that she views mentorship as an evolving practice, regularly soliciting feedback from her students. Effective leadership, in her view, grows from mutual trust and open communication.

For many nominators, Prescott’s impact extends beyond their careers. “She has taught me what positive and supportive mentoring relationships look like,” one student reflected. “When I think about the type of mentor I want to be, I hope I can emulate the ways in which she supports and guides nominators to develop their scientific independence and confidence.”

In lifting up the people behind the science as thoughtfully as the science itself, Sara Prescott demonstrates that the most enduring legacy of a mentor is not only the discoveries from their lab, but the composure and courage their advisees carry forward.

Study reveals “two-factor authentication” system that controls microRNA destruction

A new study led by researchers in the Bartel Lab and Germany’s Max Planck Institute of Biochemistry reveals how cells selectively eliminate certain microRNAs, which tune which genes are active and when, through an unexpectedly intricate molecular recognition system.

Mackenzie White | Whitehead Institute
March 17, 2026

Cells rely on tiny molecules called microRNAs to tune which genes are active and when. Cells must carefully control the lifespan of microRNAs to prevent widespread disruption to gene regulation.

A new study led by researchers at Whitehead Institute and Germany’s Max Planck Institute of Biochemistry reveals how cells selectively eliminate certain microRNAs through an unexpectedly intricate molecular recognition system. The work, published on March 18 in Nature, shows that the process requires two separate RNA signals, similar to how many digital systems require two forms of identity verification before granting access.

The findings explain how cells use this “two-factor authentication” system to ensure that only intended microRNAs are destroyed, leaving the rest of the gene regulation machinery in operation.

MicroRNAs are short strands of RNA that help control gene expression. Working together with a protein called Argonaute, they bind to specific messenger RNAs—the molecules that carry genetic instructions from DNA to the cell’s protein-making machinery—and trigger their destruction. In this way, microRNAs can reduce the production of specific proteins.

While scientists recognized that microRNAs could be destroyed through a pathway known as target-directed microRNA degradation, or TDMD, the details of how cells recognized which microRNAs to eliminate remained unclear.

“We knew there was a pathway that could target microRNAs for degradation, but the biochemical mechanism behind it wasn’t understood,” says David Bartel, Whitehead Institute Member and co-senior author of the study.

Earlier work from Bartel’s lab and others had identified a key player in this pathway: the ZSWIM8 E3 ubiquitin ligase. E3 ubiquitin ligases are involved in the cell’s recycling system and attach a small molecular tag called ubiquitin to other proteins, marking them for destruction.

The researchers first showed that the ZSWIM8 E3 ligase specifically binds and tags Argonaute, the protein that holds microRNAs and helps regulate genes. The researchers’ next challenge was to understand how this machinery recognized only Argonaute complexes carrying specific microRNAs that should be degraded.

The answer turned out to be surprisingly sophisticated.

Using a combination of biochemistry and cryo-electron microscopy—an imaging technique that reveals molecular structures at near-atomic resolution—the researchers discovered that the degradation system relies on a dual-RNA recognition process. First, Argonaute must carry a specific microRNA. Second, another RNA molecule called a “trigger RNA” must bind to that microRNA in a particular way.

The degradation machinery activates only when both signals are present.

This dual requirement ensures exquisite specificity. Each cell contains over a hundred thousand Argonaute–microRNA complexes regulating many genes, and destroying them indiscriminately would disrupt essential biological processes.

“The vast majority of Argonaute molecules in the cell are doing useful work regulating gene expression,” says Bartel, who is also a professor of biology at MIT and an HHMI Investigator. “You only want to degrade the ones carrying a particular microRNA and bound to the right trigger RNA. Without that specificity, the cell would lose its microRNAs and the essential regulation that they provide.”

The structural images revealed complex molecular interactions. The ZSWIM8 ligase detects multiple structural changes that occur when the two RNAs bind together within the Argonaute protein.

“When we saw the structure, everything clicked,” says Elena Slobodyanyuk, a graduate student in Bartel’s lab and co-first author of the study. “You could see how the pairing of the trigger RNA with the microRNA reshapes the Argonaute complex in a way that the ligase can recognize.”

Beyond explaining how TDMD works, the findings may impact how scientists think about the regulation of RNA molecules more broadly.

“A lot of E3 ligases recognize their targets through simpler signals,” says Jakob Farnung, co-first author and researcher in the Department of Molecular Machines and Signaling at the Max Planck Institute of Biochemistry. “It was like opening a treasure chest where every detail revealed something new and mesmerizing.”

MicroRNAs typically persist in cells for much longer time periods than most messenger RNAs, but some degrade far more quickly, and the TDMD pathway appears to account for many of these unusually short-lived microRNAs.

The researchers are now investigating whether other RNAs can trigger similar degradation pathways and whether additional microRNAs are regulated through variations of the mechanism shown in this study.

“This opens up a whole new way of thinking about how RNA molecules can control protein degradation,” says Brenda Schulman, study co-senior author and Director of the Department of Molecular Machines and Signaling at the Max Planck Institute of Biochemistry. “Here, the recognition was far more elaborate than expected. There’s likely much more left to discover.”

Uncovering the details of this intricate regulatory system required interdisciplinary collaboration, combining expertise in RNA biochemistry, structural biology, and ubiquitin enzymology to solve this long-standing molecular puzzle.

“This was a project that required the strengths of two labs working at the forefront of their fields,” says Schulman, who is also an alum of Whitehead Institute. “It was an incredible team effort.”

Paper: Jakob Farnung, Elena Slobodyanyuk, Peter Y. Wang, Lianne W. Blodgett, Daniel H. Lin, Susanne von Gronau, Brenda A. Schulman & David P. Bartel. “The E3 ubiquitin ligase mechanism specifying targeted microRNA degradation.” Nature (2026). https://doi.org/10.1038/s41586-026-10232-0

CryoPRISM: A new tool for observing cellular machinery in a more natural environment

The method allows researchers to observe biomolecular complexes in a quick, accurate, and budget-friendly way, providing new insights into bacterial protein synthesis.

Ekaterina Khalizeva | Department of Biology
March 20, 2026

The blobfish, once considered the ugliest animal in the world, has since had quite the redemption arc. Years after it was first discovered, scientists realized that the deep-sea creature appeared so unnervingly blobby only because it went through an extreme change in pressure when it was brought up to the surface. In its natural environment, 4,000 feet underwater, the fish looks perfectly handsome.

Structural biologists, whose goal is to deduce a molecule’s structure and function within a cell, face the risk of making a similar mistake. If biomolecular complexes are extracted from the cell, better-quality images can be obtained, but the molecules may not look natural. On the other hand, studying molecules without disrupting their environment at all is technically challenging, like filming deep underwater.

A new method, called purification-free ribosome imaging from subcellular mixtures (cryoPRISM), offers an appealing compromise. Developed by graduate students Mira May and Gabriela López-Pérez in the Davis lab in the MIT Department of Biology and recently published in PNAS, the technique allows biologists to visualize molecular complexes without taking them too far out of their natural context.

CryoPRISM captures molecular structures in cells that have just been broken open. This comes as close to preserving the natural interactions between molecules as possible, short of the extremely resource-intensive in-cell structural imaging, according to associate professor of biology Joey Davis, the faculty lead of the study.

“We think that the cryoPRISM method is a sweet spot where we preserve much of the native cellular contacts, but still have the resolution that lets us actually see molecular details,” Davis says. “Even in the extremely well-trodden system of translation in E. coli, which people have worked on for over 50 years, we are still finding new states that had just escaped people’s attention.”

A negative control that was not so negative

The development of cryoPRISM, as many discoveries in science, resulted from an unexpected observation that Mira May, the co-first author of the study, made while working on a different project.

Like all living organisms, bacteria rely on a process called translation to manufacture the proteins that carry out essential functions within the cell, from copying DNA to digesting nutrients. A key machine involved in translation is the ribosome — a biomolecular complex that assembles proteins based on instructions encoded by another molecule called mRNA. To regulate its activity, cells employ additional proteins that can change the shape of the ribosome, thus guiding its function.

May sought to identify new players in ribosomal regulation using cryoEM, by rapidly freezing lots of purified molecules and collecting thousands of 2D images to reconstruct their 3D structures. May was trying to pull ribosomes out of cells to visualize them together with their regulators. For her experiments, she designed a negative control containing unpurified bacterial lysate — a mixture of everything spilled from burst cells.

May expected to get noisy, low-quality images from this sample. To her surprise, instead, she saw intact ribosomes together with their natural interacting partners.

In just a few days, this technique experimentally validated data that would have taken months to acquire using other approaches.

“As I found more and more ribosomal states, this project became a method, not just a one-off finding,” May recalls.

Discovering new biology in a saturated field

Once May and her colleagues were confident that cryoPRISM could detect known ribosomal states, they began searching for ones that had previously escaped detection.

“It’s not just that we can recapitulate things that have been previously observed, but we can actually also discover novel ribosomal biology,” May says.

One of the novel states May identified has important implications for our understanding of the evolution of translation regulation.

During active translation, bacterial ribosomes are accompanied by a group of helper proteins called elongation factors. These factors bring in the materials for protein synthesis, like tRNAs and amino acids.

When cells encounter unfavorable conditions, such as colder temperatures, they reduce translation, which means that many ribosomes are out of work. These idle, hibernating ribosomes stop decoding mRNA, and the interface where they usually interact with helper molecules gets blocked by a hibernation factor called RaiA. This protein helps idle ribosomes avoid reactivation, like a sleeping mask that prevents a person from being woken up by light.

May observed the idle ribosomal state in her data, which on its own did not surprise her – this state had been described before. What surprised her was that some inactive ribosomes were interacting not only with RaiA, but also with an elongation factor called EF-G, which in bacteria was previously believed to only interact with active ribosomes.

A similar phenomenon has been seen before in more complex organisms, but observing it in a microbe suggests that its evolutionary origin may be older than previously thought.

“It fits an emerging model in the field, that elongation factors might bind to hibernating ribosomes to protect both the ribosome and themselves from degradation during periods of stress,” May explains. “Think of it like short-term storage.”

An unstressed cell might quickly eliminate unneeded inactive ribosomes, but because any stressor that puts ribosomes to sleep could be temporary, the cell may prefer to hold off on destroying them. That way, the ribosomes can be quickly reactivated if conditions improve.

The future of cryoPRISM

May has already teamed up with other MIT researchers to use cryoPRISM to visualize ribosomes in cells that are notoriously difficult to work with, including pathogenic organisms, which can be challenging to culture at the scale required for particle purification, and red blood cells isolated from patients, which cannot be cultured at all.

Besides its immediate application for translation research, cryoPRISM is a stepping stone toward the broader goal of structural biology: studying biomolecules in their natural environment.

To truly learn about deep-sea fish, scientists need to look at them in the deep sea; and to learn about cellular machines, scientists need to look at them in cells. According to Davis, cryoPRISM perfectly fits into the “theme of structural biology moving closer and closer to cellular context.”

Whitehead Institute Member Jonathan Weissman joins global Cancer Grand Challenges team

Whitehead Institute Member Jonathan Weissman has been named to a newly funded Cancer Grand Challenges team that will tackle one of the most elusive frontiers in cancer biology: the “dark proteome.”

Mackenzie White | Whitehead Institute
March 4, 2026

Whitehead Institute Member Jonathan Weissman has been named to a newly funded Cancer Grand Challenges team that will tackle one of the most elusive frontiers in cancer biology: the “dark proteome.”

The interdisciplinary team, ILLUMINE, will receive up to $25 million over approximately five years through Cancer Grand Challenges to investigate proteins expressed by cancer cells that don’t correspond exactly to known genes. These include proteins produced from previously unrecognized regions of the genome, proteins created from offset start sites of known genes, and proteins with altered amino acid sequences that cannot be explained by known DNA mutations. The origins and functions of this dark proteome remain largely unknown.

Cancer Grand Challenges is a global research initiative co-founded in 2020 by Cancer Research UK and the National Cancer Institute (part of the National Institutes of Health) in the United States. The initiative supports a global community of diverse, world-class research teams to come together, think differently, and take on some of cancer’s toughest challenges.

The ILLUMINE team is led by Reuven Agami of the Netherlands Cancer Institute and brings together clinicians, advocates, and scientists across eight institutions in four countries. The team is funded by Cancer Research UK, the National Cancer Institute, the Cancer Research Institute, and KiKa (Children Cancer Free Foundation) through Cancer Grand Challenges. It is one of five new teams announced this year, representing a total investment of $125 million.

Weissman, also a professor of biology at MIT and an investigator of the Howard Hughes Medical Institute, studies how proteins are produced and folded inside cells, and how disruptions in these processes contribute to disease. His laboratory developed ribosome profiling, a technique that reveals which parts of the genome are actively being translated into proteins inside cells.

This method is directly relevant to the dark proteome challenge. If cancer cells generate proteins from unexpected regions of the genome, understanding when and how those proteins are made is critical. Weissman’s lab continues to refine tools that measure protein production at scale, helping to illuminate these hidden products and their potential role in cancer.

By comprehensively identifying and characterizing the dark proteome, the ILLUMINE team aims to uncover novel, potentially universal tumor antigens — cancer cell molecules that are recognizable by the immune system — and develop innovative immunotherapies for hard-to-treat cancers.

Collectively, the newly funded teams unite researchers from nine countries and 34 institutions, bringing together more than 40 investigators to address long-standing barriers in cancer research.

Dr. David Scott, Director of Cancer Grand Challenges, said of the initiative: “Together, we’re creating opportunities for bold team science that could redefine what’s possible for people affected by cancer.”