3 Questions with new faculty member Yunha Hwang: Using computation to study the world’s best single-celled chemists

The assistant professor utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.

Lillian Eden | Department of Biology
December 15, 2025

Today, out of an estimated 1 trillion species on Earth, 99.999 percent are considered microbial — bacteria, archaea, viruses, and single-celled eukaryotes. For much of our planet’s history, microbes ruled the Earth, able to live and thrive in the most extreme of environments. Researchers have only just begun in the last few decades to contend with the diversity of microbes — it’s estimated that less than 1 percent of known genes have laboratory-validated functions. Computational approaches offer researchers the opportunity to strategically parse this truly astounding amount of information.

An environmental microbiologist and computer scientist by training, new MIT faculty member Yunha Hwang is interested in the novel biology revealed by the most diverse and prolific life form on Earth. In a shared faculty position as the Samuel A. Goldblith Career Development Professor in the Department of Biology, as well as an assistant professor at the Department of Electrical Engineering and Computer Science and the MIT Schwarzman College of Computing, Hwang is exploring the intersection of computation and biology.  

Q: What drew you to research microbes in extreme environments, and what are the challenges in studying them?

A: Extreme environments are great places to look for interesting biology. I wanted to be an astronaut growing up, and the closest thing to astrobiology is examining extreme environments on Earth. And the only thing that lives in those extreme environments are microbes. During a sampling expedition that I took part in off the coast of Mexico, we discovered a colorful microbial mat about 2 kilometers underwater that flourished because the bacteria breathed sulfur instead of oxygen — but none of the microbes I was hoping to study would grow in the lab.

The biggest challenge in studying microbes is that a majority of them cannot be cultivated, which means that the only way to study their biology is through a method called metagenomics. My latest work is genomic language modeling. We’re hoping to develop a computational system so we can probe the organism as much as possible “in silico,” just using sequence data. A genomic language model is technically a large language model, except the language is DNA as opposed to human language. It’s trained in a similar way, just in biological language as opposed to English or French. If our objective is to learn the language of biology, we should leverage the diversity of microbial genomes. Even though we have a lot of data, and even as more samples become available, we’ve just scratched the surface of microbial diversity.

Q: Given how diverse microbes are and how little we understand about them, how can studying microbes in silico, using genomic language modeling, advance our understanding of the microbial genome?

A: A genome is many millions of letters. A human cannot possibly look at that and make sense of it. We can program a machine, though, to segment data into pieces that are useful. That’s sort of how bioinformatics works with a single genome. But if you’re looking at a gram of soil, which can contain thousands of unique genomes, that’s just too much data to work with — a human and a computer together are necessary in order to grapple with that data.

During my PhD and master’s degree, we were only just discovering new genomes and new lineages that were so different from anything that had been characterized or grown in the lab. These were things that we just called “microbial dark matter.” When there are a lot of uncharacterized things, that’s where machine learning can be really useful, because we’re just looking for patterns — but that’s not the end goal. What we hope to do is to map these patterns to evolutionary relationships between each genome, each microbe, and each instance of life.

Previously, we’ve been thinking about proteins as a standalone entity — that gets us to a decent degree of information because proteins are related by homology, and therefore things that are evolutionarily related might have a similar function.

What is known about microbiology is that proteins are encoded into genomes, and the context in which that protein is bounded — what regions come before and after — is evolutionarily conserved, especially if there is a functional coupling. This makes total sense because when you have three proteins that need to be expressed together because they form a unit, then you might want them located right next to each other.

What I want to do is incorporate more of that genomic context in the way that we search for and annotate proteins and understand protein function, so that we can go beyond sequence or structural similarity to add contextual information to how we understand proteins and hypothesize about their functions.

Q: How can your research be applied to harnessing the functional potential of microbes?

A: Microbes are possibly the world’s best chemists. Leveraging microbial metabolism and biochemistry will lead to more sustainable and more efficient methods for producing new materials, new therapeutics, and new types of polymers.

But it’s not just about efficiency — microbes are doing chemistry we don’t even know how to think about. Understanding how microbes work, and being able to understand their genomic makeup and their functional capacity, will also be really important as we think about how our world and climate are changing. A majority of carbon sequestration and nutrient cycling is undertaken by microbes; if we don’t understand how a given microbe is able to fix nitrogen or carbon, then we will face difficulties in modeling the nutrient fluxes of the Earth.

On the more therapeutic side, infectious diseases are a real and growing threat. Understanding how microbes behave in diverse environments relative to the rest of our microbiome is really important as we think about the future and combating microbial pathogens.

Celebrating worm science

Time and again, an unassuming roundworm has illuminated aspects of biology with major consequences for human health.

Jennifer Michalowski | McGovern Institute
December 12, 2025

For decades, scientists with big questions about biology have found answers in a tiny worm. That worm–a millimeter-long creature called Caenorhabditis elegans–has helped researchers uncover fundamental features of how cells and organisms work. The impact of that work is enormous: Discoveries made using C. elegans have been recognized with four Nobel prizes and have led to the development of new treatments for human disease.

In a perspective piece published in the November 2025 issue of the journal PNAS, eleven biologists including Robert Horvitz, the David H. Koch (1962) Professor of Biology at MIT, celebrate Nobel Prize-winning advances made through research in C. elegans. The authors discuss how that work has led to advances for human health and highlight how a uniquely collaborative community among worm researchers has fueled the field.

MIT scientists are well represented in that community: The prominent worm biologists who coauthored the PNAS paper include former MIT graduate students Andy Fire and Paul Sternberg, now at Stanford University and the California Institute of Technology, and two past postdoctoral researchers in Horvitz’s lab, University of Massachusetts Medical School professor Victor Ambros and Massachusetts General Hospital investigator Gary Ruvkun. Ann Rougvie at the University of Minnesota is the paper’s corresponding author.

Early worm discoveries

“This tiny worm is beautiful—elegant both in its appearance and in its many contributions to our understanding of the biological universe in which we live,” says Horvitz, who in 2002 was awarded the Nobel Prize in Medicine along with colleagues Sydney Brenner and John Sulston for discoveries that helped explain how genes regulate programmed cell death and organ development. Horvitz is also a member of MIT’s McGovern Institute for Brain Research and Koch Institute for Integrative Cancer Research as well as an investigator at the Howard Hughes Medical Institute.

Those discoveries were among the early successes in C. elegans research, made by pioneering scientists who recognized the power of the microscopic roundworm. C. elegans offers many advantages for researchers: The worms are easy to grow and maintain in labs; their transparent bodies make cells and internal processes readily visible under a microscope; they are cellularly very simple (e.g., they have only 302 nerve cells, compared with about 100 billion in a human) and their genomes can be readily manipulated to study gene function.

Most importantly, many of the molecules and processes that operate in C. elegans have been retained throughout evolution, meaning discoveries made using the worm can have direct relevance to other organisms, including humans. “Many aspects of biology are ancient and evolutionarily conserved,” Horvitz explains. “Such shared mechanisms can be most readily revealed by analyzing organisms that are highly tractable in the laboratory.”

In the 1960s, Brenner, a molecular biologist who was curious about how animals’ nervous systems develop and function, recognized that C. elegans offered unique opportunities to study these processes. Once he began developing the worm into a model for laboratory studies, it did not take long for other biologists to join him to take advantage of the new system.

In the 1970s, the unique features of the worm allowed Sulston to track the transformation of a fertilized egg into an adult animal, tracing the origins of each of the adult worm’s 959 cells. His studies revealed that in every developing worm, cells divide and mature in predictable ways. He also learned that some of the cells created during development do not survive into adulthood and are instead eliminated by a process termed programmed cell death.

By seeking mutations that perturbed the process of programmed cell death, Horvitz and his colleagues identified key regulators of that process, which is sometimes referred to as apoptosis. These regulators, which both promote and oppose apoptosis, turned out to be vital for programmed cell death across the animal kingdom.

In humans, apoptosis shapes developing organs, refines brain circuits, and optimizes other tissue structures. It also modulates our immune systems and eliminates cells that are in danger of becoming cancerous. The human version of CED-9, the anti-apoptotic regulator that Horvitz’s team discovered in worms, is BCL-2. Researchers have shown that activating apoptotic cell death by blocking BCL-2 is an effective treatment for certain blood cancers. Today, researchers are also exploring new ways of treating immune disorders and neurodegenerative disease by manipulating apoptosis pathways.

Collaborative worm community

Horvitz and his colleagues’ discoveries about apoptosis helped demonstrate that understanding C. elegans biology has direct relevance to human biology and disease. Since then, a vibrant and closely connected community of worm biologists—including many who trained in Horvitz’s lab—has continued to carry out impactful work. In their PNAS article, Horvitz and his coauthors highlight that early work, as well as the Nobel Prize-winning work of:

  • Andrew Fire and Craig Mello, whose discovery of an RNA-based system of gene silencing led to powerful new tools to manipulate gene activity. The innate process they discovered in worms, known as RNA interference, is now used as the basis of six FDA-approved therapeutics for genetic disorders, silencing faulty genes to stop their harmful effects.
  • Martin Chalfie, who used a fluorescent protein made by jellyfish to visualize and track specific cells in C. elegans, helping launch the development of a set of tools that transformed biologists’ ability to observe molecules and processes that are important for both health and disease.
  • Victor Ambros and Gary Ruvkun, who discovered a class of molecules called microRNAs that regulate gene activity not just in worms, but in all multicellular organisms. This prize-winning work was started when Ambros and Ruvkun were postdoctoral researchers in Horvitz’s lab. Humans rely on more than 1,000 microRNAs to ensure our genes are used at the right times and places. Disruptions to microRNAs have been linked to neurological disorders, cancer, cardiovascular disease, and autoimmune disease, and researchers are now exploring how these small molecules might be used for diagnosis or treatment.

Horvitz and his coauthors stress that while the worm itself made these discoveries possible, so too did a host of resources that facilitate collaboration within the worm community and enable its scientists to build upon the work of others. Scientists who study C. elegans have embraced this open, collaborative spirit since the field’s earliest days, Horvitz says, citing the Worm Breeder’s Gazette, an early newsletter where scientists shared their observations, methods, and ideas.

Today, scientists who study C. elegans—whether the organism is the centerpiece of their lab or they are looking to supplement studies of other systems—contribute to and rely on online resources like WormAtlas and WormBase, as well as the Caenorhabditis Genetics Center, to share data and genetic tools. Horvitz says these resources have been crucial to his own lab’s work; his team uses them every day.

Just as molecules and processes discovered in C. elegans have pointed researchers toward important pathways in human cells, the worm has also been a vital proving ground for developing methods and approaches later deployed to study more complex organisms. For example, C. elegans, with its 302 neurons, was the first animal for which neuroscientists successfully mapped all of the connections of the nervous system. The resulting wiring diagram, or connectome, has guided countless experiments exploring how neurons work together to process information and control behavior. Informed by both the power and limitations of the C. elegans’ connectome, scientists are now mapping more complex circuitry, such as the 139,000-neuron brain of the fruit fly, whose connectome was completed in 2024.

C. elegans remains a mainstay of biological research, including in neuroscience. Scientists worldwide are using the worm to explore new questions about neural circuits, neurodegeneration, development, and disease. Horvitz’s lab continues to turn to C. elegans to investigate the genes that control animal development and behavior. His team is now using the worm to explore how animals develop a sense of time and transmit that information to their offspring.

Also at MIT, Steven Flavell’s team in the Department of Brain and Cognitive Sciences and the Picower Institute for Learning and Memory is using the worm to investigate how neural connectivity, activity, and modulation integrate internal states, such as hunger, with sensory information, such as the smell of food, to produce sometimes long-lasting behaviors. Flavell is Horvitz’s academic grandson, as Flavell trained with one of Horvitz’s postdoctoral trainees. As new technologies accelerate the pace of scientific discovery, Horvitz and his colleagues are confident that the humble worm will bring more unexpected insights.

Paper: “From nematode to Nobel: How community-shared resources fueled the rise of Caenorhabditis elegans as a research organism”

RNA editing study finds many ways for neurons to diversify

When MIT neurobiologists including Troy Littleton tracked how more than 200 motor neurons in fruit flies each edited their RNA, they cataloged hundreds of target sites and widely varying editing rates. Scores of edits altered proteins involved in neural communication and function.

David Orenstein | The Picower Institute for Learning and Memory
November 20, 2025

All starting from the same DNA, neurons ultimately take on individual characteristics in the brain and body. Differences in which genes they transcribe into RNA help determine which type of neuron they become, and from there, a new MIT study shows, individual cells edit a selection of sites in those RNA transcripts, each at their own widely varying rates.

The new study surveyed the whole landscape of RNA editing in more than 200 individual cells commonly used as models of fundamental neural biology: tonic and phasic motor neurons of the fruit fly. One of the main findings is that most sites were edited at rates between the “all or nothing” extremes many scientists have assumed based on more limited studies in mammals, said senior author Troy Littleton, Menicon Professor in the Departments of Biology and Brain and Cognitive Sciences. The resulting dataset and analyses published in eLife set the table for discoveries about how RNA editing affects neural function and what enzymes implement those edits.

“We have this ‘alphabet’ now for RNA editing in these neurons,” Littleton said. “We know which genes are edited in these neurons so we can go in and begin to ask questions as to what is that editing doing to the neuron at the most interesting targets.”

Andres Crane, who earned his PhD in Littleton’s lab based on this work, is the study’s lead author.

From a genome of about 15,000 genes, Littleton and Crane’s team found, the neurons made hundreds of edits in transcripts from hundreds of genes. For example, the team documented “canonical” edits of 316 sites in 210 genes. Canonical means that the edits were made by the well-studied enzyme ADAR, which is also found in mammals including humans. Of the 316 edits, 175 occurred in regions that encode the contents of proteins. Analysis indeed suggested 60 are likely to significantly alter amino acids. But they also found 141 more editing sites in areas that don’t code for proteins but instead affect their production, which means they could affect protein levels, rather than their contents.

The team also found many “non-canonical” edits that ADAR didn’t make. That’s important, Littleton said, because that information could aid in discovering more enzymes involved in RNA editing, potentially across species. That, in turn, could expand the possibilities for future genetic therapies.

“In the future, if we can begin to understand in flies what the enzymes are that make these other non-canonical edits, it would give us broader coverage for thinking about doing things like repairing human genomes where a mutation has broken a protein of interest,” Littleton said.

Moreover, by looking specifically at fly larvae, the team found many edits that were specific to juveniles vs. adults, suggesting potential significance during development. And because they looked at full gene transcripts of individual neurons, the team was also able to find editing targets that had not been cataloged before.

Widely varying rates

Some of the most heavily edited RNAs were from genes that make critical contributions to neural circuit communication such as neurotransmitter release, and the channels that cells form to regulate the flow of chemical ions that vary their electrical properties. The study identified 27 sites in 18 genes that were edited more than 90 percent of the time.

Yet neurons sometimes varied quite widely in whether they would edit a site, which suggests that even neurons of the same type can still take on significant degrees of individuality.

“Some neurons displayed ~100 percent editing at certain sites, while others displayed no editing for the same target,” the team wrote in eLife. “Such dramatic differences in editing rate at specific target sites is likely to contribute to the heterogeneous features observed within the same neuronal population.”

On average, any given site was edited about two-thirds of the time, and most sites were edited within a range well between all or nothing extremes.

“The vast majority of editing events we found were somewhere between 20% and 70%,” Littleton said. “We were seeing mixed ratios of edited and unedited transcripts within a single cell.”

Also, the more a gene was expressed, the less editing it experienced, suggesting that ADAR could only keep up so much with its editing opportunities.

Potential impacts on function

One of the key questions the data enables scientists to ask is what impact RNA edits have on the function of the cells. In a 2023 study, Littleton’s lab began to tackle this question by looking at just two edits they found in the most heavily edited gene: Complexin. Complexin’s protein product restrains release of the neurotransmitter glutamate, making it a key regulator of neural circuit communication. They found that by mixing and matching edits, neurons produced up to eight different versions of the protein with significant effects on their glutamate release and synaptic electrical current. But in the new study, the team reports 13 more edits in Complexin that are yet to be studied.

Littleton said he’s intrigued by another key protein, called Arc1, that the study shows experienced a non-canonical edit. Arc is a vitally important gene in “synaptic plasticity,” which is the property neurons have of adjusting the strength or presence of their “synapse” circuit connections in response to nervous system activity. Such neural nimbleness is hypothesized to be the basis of how the brain can responsively encode new information in learning and memory. Notably, Arc1 editing fails to occur in fruit flies that model Alzheimer’s disease.

Littleton said the lab is now working hard to understand how the RNA edits they’ve documented affect function in the fly motor neurons.

In addition to Crane and Littleton, the study’s other authors are Michiko Inouye and Suresh Jetti.

The National Institutes of Health, The Freedom Together Foundation and The Picower Institute for Learning and Memory provided support for the study.

Research:

Andrés B CraneMichiko O InouyeSuresh K JettiJ Troy Littleton (2025) A stochastic RNA editing process targets a select number of sites in individual Drosophila glutamatergic motoneurons eLife 14:RP108282.
https://doi.org/10.7554/eLife.108282.2

Alternate proteins from the same gene contribute differently to health and rare disease

Whitehead Institute Member Iain Cheeseman, graduate student Jimmy Ly, and colleagues propose that researchers and clinicians may be able to get more information from patients’ genomes by looking at them in a different way.

Greta Friar | Whitehead Institute
November 7, 2025

In a paper published in Molecular Cell on November 7, Whitehead Institute Member Iain Cheeseman, graduate student Jimmy Ly, and colleagues propose that researchers and clinicians may be able to get more information from patients’ genomes by looking at them in a different way.

The common wisdom is that each gene codes for one protein. Someone studying whether a patient has a mutation or version of a gene that contributes to their disease will therefore look for mutations that affect the “known” protein product of that gene. However, Cheeseman and others are finding that the majority of genes code for more than one protein. That means that a mutation that may seem insignificant because it does not appear to affect the known protein could nonetheless alter a different protein made by the same gene. Now, Cheeseman and Ly have shown that mutations affecting one or multiple proteins from the same gene can contribute differently to disease.

In their paper, the researchers first share what they have learned about how cells make use of the ability to generate different versions of proteins from the same gene. Then, they examine how mutations that affect these proteins contribute to disease. Through a collaboration with co-author Mark Fleming, the pathologist-in-chief at Boston Children’s Hospital, they provide two case studies of patients with atypical presentations of a rare anemia linked to mutations that selectively affect only one of two proteins produced by the gene implicated in the disease.

“We hope this work demonstrates the importance of considering whether a gene of interest makes multiple versions of a protein, and what the role of each version is in health and disease,” Ly says. “This information could lead to better understanding of the biology of disease, better diagnostics, and perhaps one day to tailored therapies to treat these diseases.”

Rethinking how cells use genes

Cells have several ways to make different versions of a protein, but the variation that Cheeseman and Ly study happens during protein production from genetic code. Cellular machines build each protein according to the instructions within a genetic sequence that begins at a “start codon” and ends at a “stop codon.” However, some genetic sequences contain more than one start codon, many that are hiding in plain sight. If the cellular machinery skips the first start codon and detects a second one, it may build a shorter version of the protein. In other cases, the machinery may detect a section that closely resembles a start codon at a point earlier in the sequence than its typical starting place, and build a longer version of the protein.

These events may sound like mistakes: the cell’s machinery accidentally creating the wrong version of the correct protein. To the contrary, protein production from these alternate starting places is an important feature of cell biology that exists across species. When Ly traced when certain genes evolved to produce multiple proteins, he found that this is a common, robust process that has been preserved throughout evolutionary history for millions of years.

Ly shows that one function this serves is to send versions of a protein to different parts of the cell. Many proteins contain zip code-like sequences that tell the cell’s machinery where to deliver them so the proteins can do their jobs. Ly found many examples in which longer and shorter versions of the same protein contained different zip codes and ended up in different places within the cell.

In particular, Ly found many cases in which one version of a protein ended up in mitochondria, structures that provide energy to cells, while another version ended up elsewhere. Because of the mitochondria’s role in the essential process of energy production, mutations to mitochondrial genes are often implicated in disease.

Ly wondered what would happen when a disease-causing mutation eliminates one version of a protein but leaves the other intact, causing the protein to only reach one of its two intended destinations. He looked through a database containing genetic information from people with rare diseases to see if such cases existed, and found that they did. In fact, there may be tens of thousands of such cases. However, without access to the people, Ly had no way of knowing what the consequences of this were in terms of symptoms and severity of disease.

Meanwhile, Cheeseman had begun working with Boston Children’s Hospital to foster collaborations between Whitehead Institute and the hospital’s researchers and clinicians to accelerate the pathway from research discovery to clinical application. Through these efforts, Cheeseman and Ly met Fleming.

One group of Fleming’s patients have a type of anemia called SIFD—Sideroblastic Anemia with B-Cell Immunodeficiency, Periodic Fevers, and Developmental Delay—that is caused by mutations to the TRNT1 gene. TRNT1 is one of the genes Ly had identified as producing a mitochondrial version of its protein and another version that ends up elsewhere: in the nucleus.

Fleming shared anonymized patient data with Ly, and Ly found two cases of interest in the genetic data. Most of the patients had mutations that impaired both versions of the protein, but one patient had a mutation that eliminated only the mitochondrial version of the protein, while another patient had a mutation that eliminated only the nuclear version.

When Ly shared his results, Fleming revealed that both of those patients had very atypical presentations of SIFD, supporting Ly’s hypothesis that mutations affecting different versions of a protein would have different consequences. The patient who only had the mitochondrial version was anemic but developmentally normal. The patient missing the mitochondrial version of the protein did not have developmental delays or chronic anemia but did have other immune symptoms, and was not correctly diagnosed until his fifties. There are likely other factors contributing to each patient’s exact presentation of the disease, but Ly’s work begins to unravel the mystery of their atypical symptoms.

Cheeseman and Ly want to make more clinicians aware of the prevalence of genes coding for more than one protein, so they know to check for mutations affecting any of the protein versions that could contribute to disease. For example, several TRNT1 mutations that only eliminate the shorter version of the protein are not flagged as disease-causing by current assessment tools. Cheeseman lab researchers including Ly and graduate student Matteo Di Bernardo are now developing a new assessment tool for clinicians, called SwissIsoform, that will identify relevant mutations that affect specific protein versions, including mutations that would otherwise be missed.

“Jimmy and Iain’s work will globally support genetic disease variant interpretation and help with connecting genetic differences to variation in disease symptoms,” Fleming says. “In fact, we have recently identified two other patients with mutations affecting only the mitochondrial versions of two other proteins, who similarly have milder symptoms than patients with mutations that affect both versions.”

Long term, the researchers hope that their discoveries could aid in understanding the molecular basis of disease and in developing new gene therapies: once researchers understand what has gone wrong within a cell to cause disease, they are better equipped to devise a solution. More immediately, the researchers hope that their work will make a difference by providing better information to clinicians and people with rare diseases.

“As a basic researcher who doesn’t typically interact with patients, there’s something very satisfying about knowing that the work you are doing is helping specific people,” Cheeseman says. “As my lab transitions to this new focus, I’ve heard many stories from people trying to navigate a rare disease and just get answers, and that has been really motivating to us, as we work to provide new insights into the disease biology.”

Jimmy Ly, Matteo Di Bernardo, Yi Fei Tao, Ekaterina Khalizeva, Christopher J. Giuliano, Sebastian Lourido, Mark D. Fleming, Iain M. Cheeseman. “Alternative start codon selection shapes mitochondrial function and rare human diseases.” Molecular Cell, November 7, 2025. DOI: https://10.0.3.248/j.molcel.2025.10.013

Q&A: Picower researchers including MIT Biology faculty Sara Prescott join effort to investigate the ‘Biology of Adversity’

Assistant Professor Sara Prescott and Research Affiliate Ravikiran Raju are key collaborators in a new Broad Institute research project to better understand physiological and medical effects of acute and chronic life stressors.

David Orenstein | The Picower Institute for Learning and Memory
November 3, 2025

Adverse experiences such as abuse and violence or poverty and deprivation have always been understood to be harmful, but the tools to understand how they may cause specific medical conditions and outcomes have only emerged recently. Technologies such as RNA or chromatin sequencing, for instance, can help scientists observe how stressors change gene expression, which can help establish mechanistic biological explanations for why people who’ve suffered adversity also experience higher risks of conditions such as stroke or Alzheimer’s disease.

Advancing scientific understanding of the physiological connections between adversity and disease can help pharmaceutical developers, physicians and public officials to develop meaningful interventions. Led by researcher Jason Buenrostro, the Broad Institute has launched a new research program, the “Biology of Adversity” project.. As leading collaborators in the effort, Picower Institute investigator Sara Prescott, assistant professor of biology, and Tsai Lab research affiliate Ravikiran Raju, a pediatrician at Boston Children’s Hospital, plan research projects in their Picower Institute labs to better elucidate how life stress leads to medical distress.

How can biology and neuroscience studies help people who’ve experienced adversity?

Prescott: Adversity comes in many flavors. But across different types of adversity, there is a common theme that it leads to psychological and emotional distress. If you were to ask a random person on the street, they’d probably tell you that distress is simply a feeling that exists only in the mind, rather than a biological process. But this is not true. We now appreciate that stress has predictable effects on the body, and there are severe long-term health consequences of experiencing chronic stress. Unfortunately, it’s been difficult to argue based on epidemiological data that stress itself (rather than other lifestyle factors like diet, smoking or access to health care services) is causally linked to poor health outcomes. This is confounded by the fact that we haven’t had good ways to empirically measure people’s levels of adversity and stress. This is part of what we want to address at the Biology of Adversity Project.

From a scientific perspective, there is still much to be understood about stress and the biological processes that lead to stress-associated diseases. And so that’s hopefully where efforts like the Biology of Adversity Project are going to come in. We can use scientific practices to come up with better guidelines for ways to track levels of stress, develop diagnostics, and then, hopefully, one day this will turn into actionable interventions. It’s not a random process of things going awry. There are going to be biological programs that are engaged in predictable ways. And we’re trying to understand, what exactly are these neural or biological programs? How many different types of programs are there? And how do each of those programs actually work down to the cellular and molecular level?

Raju: Efforts to combat adversity and stress have largely remained in the social space to date. But what we know from a growing body of epidemiological literature is that social stressors can have profound biological impact. They cause increases in mental health disorders, physical disorders like cancer, stroke, and heart disease. Individuals who experience chronic and high levels of stress are dying sooner. I think there is an imperative to understand what these forces are doing to our biology and how they’re dysregulating our physiology. Armed with that information, we can start to be more mechanistic and evidence-based in our promotion of resilience. What are the pathways that are made vulnerable when individuals are stressed? How do we rescue those deficiencies, whether it be through existing practices or novel interventions? A lot of the research we’re doing here at Picower is focusing on pathways that could be targeted and leveraged using specific micronutrients or specific small molecules that help promote resilience and prevent the onset of premature illness in individuals who are stress exposed.

What is the Biology of Adversity Project and how are each of you involved?

Prescott: My lab studies the autonomic nervous system, and we’re involved in the project’s animal studies. We think of stress as an adaptive response to prepare the body for an impending threat. When people experience stress, what happens? You engage a fight or flight response—you sweat, start to breathe harder, your heart rate goes up, your pupils dilate. This is protective in acute settings, but can become very maladaptive when these systems are activated for too long or in inappropriate settings, like when someone is having a panic attack. We predict that a lot of the long-term health consequences associated with adversity could relate to dysregulated autonomic stress responses.

And so that’s where our lab’s tools come in. We have good ways in animals to measure their heart rate and breathing in response to stress. We also have a wide range of genetic tools to specifically target different neural pathways in the periphery, possibly blocking stress pathways at the source. With these tools, we can explore what role those circuits have in long-term changes in these animals with greater precision than what was possible in the past.

Raju: My involvement came through my work on the Environmental and Social Determinants of Child Mental Health Conference in 2023, which I co-hosted with Li-Huei Tsai. I think this conference made the scientific community in Boston more aware that this was something of deep interest to researchers at Picower and MIT. In the creation of the Biology of Adversity Project, the center director, Jason Buenrostro, was doing a survey of the landscape of folks who were studying stress and adversity, and who were passionate about it and connected with us because of that symposium. Since then, I’ve been engaged in really exciting conversations with him and a exciting group of collaborators, including Sara Prescott. And so I’m really excited that a few of our projects are being showcased as flagship projects. We are currently using animal models of early life stress to try and build preclinical models to deepen our understanding of how stress dysregulates physiology. We’re developing pipelines for trying to think about promoting resilience through targeted interventions, using those preclinical models.

What research questions do you each plan to tackle?

Prescott: Broadly, we’re interested in the body-brain connection and how this relates to stress. How do different cues from within the body—like diet, or taking a deep breath–promote or regulate stress levels? These are interesting questions about how sensory inputs from the body feed into stress circuits in the brain. We’re also interested in the other direction—understanding how stress causes changes to peripheral organs, for example, by engaging the sympathetic nervous system. It’s well understood that sympathetic neurons are responsible for making you sweat and your heart race, but do they do other things as well? For example, the field is starting to appreciate that these same neurons regulate the immune system, and can signal to stem cells to promote or suppress tissue repair. These are important pathways to understand, as they could explain some of the links between chronic stress (where sympathetic neurons are over-activated) and increased rates of diseases like cancer. It also may have therapeutic applications down the road. I’m incredibly excited for the opportunity to work with people like Ravi, and others in the project, to apply our expertise in physiology and autonomic signaling towards this immensely important problem. I’m hoping that through this work we can move to an era where we can, from a societal perspective, understand how much our stress levels are damaging our body, be able to track that, and then find better ways to prevent the damage that’s happening.

Raju:  We are leveraging three key mouse models of environmental perturbations in this work: environmental enrichment, social isolation and resource deprivation. In studying enrichment, we are trying to better study the factors that promote resilience to stress. In our previous work on resilience, for example, we identified a transcription factor that’s specifically recruited to help ensure that neurons are resilient to the onset of Alzheimer’s pathology. So we’ve leveraged these enrichment models to study that mechanism and are able to then think of how that pathway might be leveraged in stress-exposed individuals. We are also using models of stress, specifically social isolation and resource deprivation. The idea here is that because mice are social mammals and rely on resources and social interactions and social networks in order to thrive, we can modulate these in a species-relevant way, and then study the pathways that are dysregulated. This will allow us to define vulnerable pathways in these preclinical models, and then assess if those same pathways are dysregulated in humans that are experiencing analagous environmental conditions. Armed with the right model, we can then determine how to reverse the physiological derangements induced by environmental stressors.

A new way to understand and predict gene splicing

The KATMAP model, developed by researchers in the Department of Biology, can predict alternative cell splicing, which allows cells to create endless diversity from the same sets of genetic blueprints.

Lillian Eden | Department of Biology
November 4, 2025

Although heart cells and skin cells contain identical instructions for creating proteins encoded in their DNA, they’re able to fill such disparate niches because molecular machinery can cut out and stitch together different segments of those instructions to create endlessly unique combinations.

The ingenuity of using the same genes in different ways is made possible by a process called splicing and is controlled by splicing factors; which splicing factors a cell employs determines what sets of instructions that cell produces, which, in turn, gives rise to proteins that allow cells to fulfill different functions.

In an open-access paper published today in Nature Biotechnology, researchers in the MIT Department of Biology outlined a framework for parsing the complex relationship between sequences and splicing regulation to investigate the regulatory activities of splicing factors, creating models that can be applied to interpret and predict splicing regulation across different cell types, and even different species. Called Knockdown Activity and Target Models from Additive regression Predictions, KATMAP draws on experimental data from disrupting the expression of a splicing factor and information on which sequences the splicing factor interacts with to predict its likely targets.

Aside from the benefits of a better understanding of gene regulation, splicing mutations — either in the gene that is spliced or in the splicing factor itself — can give rise to diseases such as cancer by altering how genes are expressed, leading to the creation or accumulation of faulty or mutated proteins. This information is critical for developing therapeutic treatments for those diseases. The researchers also demonstrated that KATMAP can potentially be used to predict whether synthetic nucleic acids, a promising treatment option for disorders including a subset of muscular atrophy and epilepsy disorders, affect splicing.

Perturbing splicing 

In eukaryotic cells, including our own, splicing occurs after DNA is transcribed to produce an RNA copy of a gene, which contains both coding and non-coding regions of RNA. The noncoding intron regions are removed, and the coding exon segments are spliced back together to make a near-final blueprint, which can then be translated into a protein.

According to first author Michael P. McGurk, a postdoc in the lab of MIT Professor Christopher Burge, previous approaches could provide an average picture of regulation, but could not necessarily predict the regulation of splicing factors at particular exons in particular genes.

KATMAP draws on RNA sequencing data generated from perturbation experiments, which alter the expression level of a regulatory factor by either overexpressing it or knocking down its levels. The consequences of overexpression or knockdown are that the genes regulated by the splicing factor should exhibit different levels of splicing after perturbation, which helps the model identify the splicing factor’s targets.

Cells, however, are complex, interconnected systems, where one small change can cause a cascade of effects. KATMAP is also able to distinguish between direct targets from indirect, downstream impacts by incorporating known information about the sequence the splicing factor is likely to interact with, referred to as a binding site or binding motif.

“In our analyses, we identify predicted targets as exons that have binding sites for this particular factor in the regions where this model thinks they need to be to impact regulation,” McGurk says, while non-targets may be affected by perturbation but don’t have the likely appropriate binding sites nearby.

This is especially helpful for splicing factors that aren’t as well-studied.

“One of our goals with KATMAP was to try to make the model general enough that it can learn what it needs to assume for particular factors, like how similar the binding site has to be to the known motif or how regulatory activity changes with the distance of the binding sites from the splice sites,” McGurk says.

Starting simple

Although predictive models can be very powerful at presenting possible hypotheses, many are considered “black boxes,” meaning the rationale that gives rise to their conclusions is unclear. KATMAP, on the other hand, is an interpretable model that enables researchers to quickly generate hypotheses and interpret splicing patterns in terms of regulatory factors while also understanding how the predictions were made.

“I don’t just want to predict things, I want to explain and understand,” McGurk says. “We set up the model to learn from existing information about splicing and binding, which gives us biologically interpretable parameters.”

The researchers did have to make some simplifying assumptions in order to develop the model. KATMAP considers only one splicing factor at a time, although it is possible for splicing factors to work in concert with one another. The RNA target sequence could also be folded in such a way that the factor wouldn’t be able to access a predicted binding site, so the site is present but not utilized.

“When you try to build up complete pictures of complex phenomena, it’s usually best to start simple,” McGurk says. “A model that only considers one splicing factor at a time is a good starting point.”

David McWaters, another postdoc in the Burge Lab and a co-author on the paper, conducted key experiments to test and validate that aspect of the KATMAP model.

Future directions

The Burge lab is collaborating with researchers at Dana-Farber Cancer Institute to apply KATMAP to the question of how splicing factors are altered in disease contexts, as well as with other researchers at MIT as part of an MIT HEALS grant to model splicing factor changes in stress responses. McGurk also hopes to extend the model to incorporate cooperative regulation for splicing factors that work together.

“We’re still in a very exploratory phase, but I would like to be able to apply these models to try to understand splicing regulation in disease or development. In terms of variation of splicing factors, they are related, and we need to understand both,” McGurk says.

Burge, the Uncas (1923) and Helen Whitaker Professor and senior author of the paper, will continue to work on generalizing this approach to build interpretable models for other aspects of gene regulation.

“We now have a tool that can learn the pattern of activity of a splicing factor from types of data that can be readily generated for any factor of interest,” says Burge, who is also an extra-mural member of the Koch Institute for Integrative Cancer Research and an associate member of the Broad Institute of MIT and Harvard. “As we build up more of these models, we’ll be better able to infer which splicing factors have altered activity in a disease state from transcriptomic data, to help understand which splicing factors are driving pathology.”

The joy of life (sciences)

Mary Gallagher’s deeply rooted MIT experience and love of all life supports growth at the MIT Department of Biology.

Samantha Edelen | Department of Biology
November 28, 2025

For almost 30 years, Mary Gallagher has supported award-winning faculty members and their labs in the same way she tends the soil beneath her garden. In both, she pairs diligence and experience with a delight in the way that interconnected ecosystems contribute to the growth of a plant, or an idea, seeded in the right place.

Gallagher, a senior administrative assistant in the Department of Biology, has spent much of her career at MIT. Her mastery in navigating the myriad tasks required by administrators, and her ability to build connections, have supported and elevated everyone she interacts with, at the Institute and beyond.

Oh, the people you’ll know

Gallagher didn’t start her career at MIT. Her first role following graduation from the University of Vermont in the early 1980s was at a nearby community arts center, where she worked alongside a man who would become a household name in American politics.

“This guy had just been elected mayor, shockingly, of Burlington, Vermont, by under 100 votes, unseating the incumbent. He went in and created this arts council and youth office,” Gallagher recalls.

That political newcomer was none other than a young Bernie Sanders, now the longest-serving independent senator in U.S. congressional history.

Gallagher arrived at MIT in 1996, becoming an administrative assistant (aka “lab admin”) in what was then called the MIT Energy Laboratory. Shortly after her arrival, Cecil and Ida Green Professor of Physics and Engineering Systems Ernest Moniz transformed the laboratory into the MIT Energy Initiative (MITEI).

Gallagher quickly learned how versatile the work of an administrator can be. As MITEI rapidly grew, she interacted with people across campus and its vast array of disciplines at the Institute, including mechanical engineering, political science, and economics.

“Admin jobs at MIT are really crazy because of the depth of work that we’re willing to do to support the institution. I was hired to do secretarial work, and next thing I know, I was traveling all the time, and planning a five-day, 5,000-person event down in D.C.,” Gallagher says. “I developed crazy computer and event-planner skills.”

Although such tasks may seem daunting to some, Gallagher has been thrilled with the opportunities she’s had to meet so many people and develop so many new skills. As a lab admin in MITEI for 18 years, she mastered navigating MIT administration, lab finances, and technical support. When Moniz left MITEI to lead the U.S. Department of Energy under President Obama, she moved to the Department of Biology at MIT.

Mutual thriving

Over the years, Gallagher has fostered the growth of students and colleagues at MIT, and vice versa.

Friend and former colleague Samantha Farrell recalls her first days at MITEI as a rather nervous and very “green” temp, when Gallagher offered an excellent cappuccino from Gallagher’s new Nespresso coffee machine.

“I treasure her friendship and knowledge,” Farrell says. “She taught me everything I needed to know about being an admin and working in research.”

Gallagher’s experience has also set faculty across the Institute up for success.

According to one principal investigator she currently supports, Novartis Professor of Biology Leonard Guarente, Gallagher is “extremely impactful and, in short, an ideal administrative assistant.”

Similarly, professor of biology Daniel Lew is grateful that her extensive MIT experience was available as he moved his lab to the Institute in recent years. “Mary was invaluable in setting up and running the lab, teaching at MIT, and organizing meetings and workshops,” Lew says. “She is a font of knowledge about MIT.”

A willingness to share knowledge, resources, and sometimes a cappuccino, is just as critical as a willingness to learn, especially at a teaching institution like MIT. So it goes without saying that the students at MIT have left their mark on Gallagher in turn — including teaching her how to format a digital table of contents on her very first day at MIT.

“Working with undergrads and grad students is my favorite part of MIT. Their generosity leaves me breathless,” says Gallagher. “No matter how busy they are, they’re always willing to help another person.”

Campus community

Gallagher cites the decline in community following the Covid-19 pandemic shutdown as one of her most significant challenges.

Prior to Covid, Gallagher says, “MIT had this great sense of community. Everyone had projects, volunteered, and engaged. The campus was buzzing, it was a hoot!”

She nurtured that community, from active participation in the MIT Women’s League to organizing an award-winning relaunch of Artist Behind the Desk. This subgroup of the MIT Working Group for Support Staff Issues hosted lunchtime recitals and visual art shows to bring together staff artists around campus, for which the group received a 2005 MIT Excellence Award for Creating Connections.

Moreover, Gallagher is an integral part of the smaller communities within the labs she supports.

Professor of biology and American Cancer Society Professor Graham Walker, yet another Department of Biology faculty member Gallagher supports, says, “Mary’s personal warmth and constant smile has lit up my lab for many years, and we are all grateful to have her as such a good colleague and friend.”

She strives to restore the sense of community that the campus used to have, but recognizes that striving for bygone days is futile.

“You can never go back in time and make the future what it was in the past,” she says. “You have to reimagine how we can make ourselves special in a new way.”

Spreading her roots

Gallagher’s life has been inextricably shaped by the Institute, and MIT, in turn, would not be what it is if not for Gallagher’s willingness to share her wisdom on the complexities of administration alongside the “joie de vivre” of her garden’s butterflies.

She recently bought a home in rural New Hampshire, trading the buzzing crowds of campus for the buzzing of local honeybees. Her work ethic is reflected in her ongoing commitment to curiosity, through reading about native plant life and documenting pollinating insects as they wander about her flowers.

Just as she can admire each bug and flower for the role it plays in the larger system, Gallagher has participated in and contributed to a culture of appreciating the role of every individual within the whole.

“At MIT’s core, they believe that everybody brings something to the table,” she says. “I wouldn’t be who I am if I didn’t work at MIT and meet all these people.”

Research Threads: One lab’s detective work reveals secrets of immortal cells

Most cells in our body live and die. But the germline, the cells that produce eggs and sperm, must carry on forever. How the germline successfully produces the next generation is a long-studied question. Through a string of discoveries made over years, the Yamashita lab is teasing apart how the germline remains immortal.

Madeleine Turner | Whitehead Institute
October 7, 2025

Most cells in our body live and die. But the germline, the cells that produce eggs and sperm, must carry on forever. How the germline successfully produces the next generation is a long-studied question. Research Threads examines how answering one question uncovers more questions to be solved. In our first installment of Research Threads, we follow the research of Whitehead Institute Member Yukiko Yamashita. Through a string of discoveries made over years, the Yamashita lab is teasing apart how the germline remains immortal.

“The germline is the only cell type responsible for transmitting the genome from generation to generation,” Whitehead Institute Member Yukiko Yamashita says. “We’ve done that for 1.5 billion years.”

The germline is the population of cells in an organism that give rise to gametes, either egg or sperm cells. These gametes contain genetic information, encoded in DNA, needed to produce the next generation. The act of transmitting this information — the instructions that a new individual needs to develop and function — is like a relay race that never ends. While a skin or gut cell may be prone to genetic errors and is generally replaceable, germline stem cells (GSCs) must maintain their genomes with precision. Otherwise, any mistakes or imbalances would be inherited by offspring and accumulated over generations, potentially driving a species to extinction. In other words, to keep passing the baton in this relay, the germline must be faithfully preserved.

Although germline preservation is paramount to the existence and survival of a species, some fundamental parts of its biology have remained a mystery. Yamashita, who is also a professor of biology at the Massachusetts Institute of Technology and a Howard Hughes Medical Institute Investigator, has focused her research on unraveling the secrets of the germline. To study these cells’ immortality, her lab utilizes the model organism Drosophila melanogaster, or the fruit fly. Along the way, research in the Yamashita lab has highlighted how the process of scientific discovery can be circuitous, often pulling scientists in surprising directions, revealing new questions and avenues to explore.

For decades, scientists had observed an aspect of germline behavior that was hard to explain. Most cells in the body divide to produce two identical copies, or daughter cells. GSCs in male fruit flies, however, divide “asymmetrically,” meaning they yield two daughter cells that are not identical. Instead, one daughter cell becomes a new GSC, while the other goes on to become a gamete, in this case a sperm cell. It might be easy to assume that asymmetric cell division is about producing gametes while maintaining a pool of stem cells. But an additional detail complicates this theory: when a daughter cell is on the path to becoming sperm, it can loop back around to become another stem cell, instead of continuing differentiation to become a sperm cell.

“If it can do that, why divide asymmetrically in the first place?” Yamashita says.

To shed light on why GSCs divide asymmetrically, researchers wanted to know how genetic information was actually divvied up between daughter cells. “After I started my own lab, there was this question hanging in the field,” Yamashita says. It made sense to find some difference in inheritance, DNA-based or otherwise: something to distinguish between the daughter fated to become a gamete, and the other that would remain in the GSC pool.

Preparing for division, a cell duplicates its DNA. Chromosomes happen to be shaped like the letter “X” as a result of this duplication: the left and right sides of the “X” are called matching sister chromatids, each a copy of the other. Later in cell division, these two sister chromatids part ways, winding up in separate daughter cells.

In 2013, Yamashita and her former graduate student, Swathi Yadlapalli, made a strange but important discovery. In fruit flies, for the X and Y chromosomes (the sex chromosomes), sister chromatids were not being sorted randomly. Instead, one was more likely to go to the daughter cell that would become a gamete; the other to the daughter on the GSC track. There had to be a reason for this preference, but no one had an explanation.

Initial experiments did not reveal obvious differences between these sister chromatid pairs. “Everyone would say, ‘oh, there’s probably some sort of epigenetic information in there,” Yamashita says, referring to heritable changes not carried in DNA. With few promising leads, the lab decided to take a systematic approach. George Watase, then a postdoc in the lab, began the painstaking work of removing different a parts of flies’ X chromosomes, seeing if the absence of any particular element would disrupt the pattern of preferential segregation.

“We thought it was going to be satellite DNA,” Yamashita says, referring to large swathes of DNA in the genome that are highly repetitive but don’t code for any genes. (While this initial guess was wrong, it kickstarted a separate project in the lab — one which led to discovering the unexpected role that satellite DNA plays when one species forks into two.)

Eventually the team narrowed in on the true culprit: ribosomal DNA (rDNA). The primary role of rDNA is to produce the components that make up ribosomes. Ribosomes, in turn, perform the crucial task of synthesizing proteins.

“We didn’t like this finding in the beginning. I always say that ribosomal DNA is ‘too important to be interesting.’ You don’t get excited about something you really need, like toilet paper,” Yamashita says. “In the case of ribosomal DNA, bacteria needs it, humans need it, everybody needs it.”

But what did rDNA have to do with asymmetric cell division in the germline?

“Around that time, we started reading lots of papers,” Yamashita says. “Then we discovered a phenomenon called rDNA magnification. These were studies from the 1960s and ’80s — most of the people in my lab were not even born yet.”

These studies from decades ago described mutant flies that lacked a sufficient amount of rDNA and, as a result, had a “bobbed” phenotype, or appearance. Since these flies possessed fewer ribosomes to produce proteins, the bristles on their back were shorter; the protective cuticle covering their bodies weakened. But when they reproduced, many of their offspring possessed a normal amount of rDNA. These observations pointed towards a mechanism that allowed flies to replenish their supply of rDNA.

At the time rDNA magnification was first observed, the phenomenon was regarded as an oddity, something that only happened in mutant flies and did not have physiological relevance. But Yamashita realized there was a connection between rDNA magnification and asymmetric division in the germline.

To make enough protein, a cell must produce ample ribosomes. To do that, the fruit fly genome contains hundreds of copies of rDNA in a row. But the DNA replication process can struggle to handle so many rDNA copies strung together, and can sometimes experience a hiccup, resulting in the loss of rDNA copies with each new division. It’s an outcome that might be okay on occasion, but would wreak havoc over many generations.

“All of a sudden, [rDNA magnification] was not about a mutant chromosome,” Yamashita says. “We were like, holy moly. This is about germline immortality.”

Soon many different pieces became part of a cohesive story: asymmetric cell division is not about producing a balance of gametes and stem cells; it’s about maintaining rDNA in the germline. Sister chromatids are almost identical — but one contains more copies of rDNA than the other, and that copy is fated to stay in the GSC pool. Through this asymmetry, the germline is replenished of rDNA; it can pass the baton to the next generation.

“For quite some time, for so many observations that everyone knew in the field, we felt we had an explanation. But from that ‘aha!’ moment, we took multiple years to test everything,” Yamashita says.

In subsequent years, the Yamashita lab pinned down additional details about how rDNA is diverted back to the germline. First, in 2022, the team identified a specific protein, which they named Indra, which binds to rDNA. The presence of Indra helps assign the sister chromatid containing more rDNA copies to the GSC daughter cell.

Their next discovery was another plot twist. If one sister chromatid contained more rDNA than the other, and those rDNA copies weren’t appearing out of thin air, it meant that one chromatid needed to be stealing rDNA from its sister. The lab discovered a genetic element that facilitated this transfer: a retrotransposon.

Retrotransposons are usually considered “genetic parasites,” copying and pasting themselves into the genome. In an attempt to reinsert itself, this particular retrotransposon, called R2, slices open sections containing rDNA on both chromatids. As the cell repairs these breaks, it may inadvertently stitch copies of rDNA from one chromosome to the other, creating an unequal number of copies between the two.

“Not many people thought retrotransposons could be beneficial to the host. They’re seen as parasites,” Yamashita says. “But it turns out that they are essential for germline immortality.”

Sometimes, one research project is a spin off of a spin off. That was true for Xuefeng Meng, a graduate student in the lab who was working on satellite DNA, the genetic element that turned out to be unrelated to asymmetric cell division, but was interesting in its own right.

While studying satellite DNA, Meng noticed that a particular stock of flies had a problem producing normal sperm, that their cells’ nuclei were abnormally packaged. The problem had to do with a gene called Stellate on the flies’ X chromosome. While most flies have few copies of Stellate, these flies had a higher number of copies.

Stellate was already known in the field as a meiotic driver, or “selfish-gene”: a genetic element that has evolved ways to preferentially transmit itself to the next generation. Some meiotic drivers, including Stellate, are on the sex chromosomes and, when not suppressed, cause an excess of either male or female progeny. In this case, Stellate produces a protein, Ste, which is found to concentrate in Y-carrying cells during meiosis, the specialized type of cell division that produces gametes (meiosis follows the earlier round of asymmetric cell division described above). High concentrations of Ste impede the proper packaging of nuclei in cells, leading to their eventual death. When Stellate is widely expressed, fewer male flies emerge in the next generation.

But here lies an inherent tension: if a selfish gene is too good at propagating itself, and produces only males or females, its host species would go extinct — and so would the gene. Meng and Yamashita were interested in this paradox. Through this work, they identified a novel mechanism that keeps Stellate in check. To balance selfish propagation with the host species’ survival, Stellate has a built-in system for pumping the brakes. After Ste concentrates in Y-carrying cells during the first meiotic division, the protein is unevenly distributed a second time. This second step spares a portion of Y-carrying cells that go on to create males.

How the germline is able to counter disruptive forces, thereby renewing itself, continues to be a ripe research area. Researchers still don’t know all the secrets to how a line of cells can achieve perpetuity — but the Yamashita lab continues to investigate the question.

“What I really like about people in my lab is that they don’t jump to the easiest conclusion,” Yamashita says. “If you start embracing surprise, then good things happen. Because you are surprised, you start testing your finding in multiple ways. Then you can build confidence about the result.”

Notes

Xuefeng Meng and Yukiko Yamashita (2025). “Intrinsically weak sex chromosome drive through sequential asymmetric meiosis.” Science Advanceshttps://doi.org/10.1126/sciadv.adv7089

Jonathan O. Nelson, Tomohiro Kumon, Yukiko M. Yamashita. (2023) “rDNA magnification is a unique feature of germline stem cells.” PNAShttps://doi.org/10.1073/pnas.2314440120

Jonathan O. Nelson, Alyssa Slicko, Yukiko M. Yamashita. (2023) “The retrotransposon R2 maintains Drosophila ribosomal DNA repeats.” PNAShttps://doi.org/10.1073/pnas.2221613120

George J. Watase, Jonathan O. Nelson, Yukiko M. Yamashita. (2022) “Nonrandom sister chromatid segregation mediates rDNA copy number maintenance in Drosophila.” Science Advanceshttps://www.science.org/doi/10.1126/sciadv.abo4443

Madhav Jagannathan and Yukiko Yamashita. (2021) “Defective satellite DNA clustering into chromocenters underlies hybrid incompatibility in Drosophila.” Molecular Biology and Evolutionhttps://doi.org/10.1093/molbev/msab221

Swathi Yadlapalli and Yukiko Yamashita (2013) “Chromosome-specific nonrandom sister chromatid segregation during stem-cell division.” Nature10.1038/nature12106

Facundo Batista among MIT affiliates elected to National Academy of Medicine for 2025

Professors Facundo Batista and Dina Katabi, along with three additional MIT alumni, are honored for their outstanding professional achievement and commitment to service.

Lillian Eden | Jane Halpern | Department of Biology | Department of Electrical Engineering and Computer Science
October 22, 2025

On Oct. 20 during its annual meeting, the National Academy of Medicine announced the election of 100 new members, including MIT faculty members Dina Katabi and Facundo Batista, along with three additional MIT alumni.

Election to the National Academy of Medicine (NAM) is considered one of the highest honors in the fields of health and medicine, recognizing individuals who have demonstrated outstanding professional achievement and commitment to service.

Facundo Batista is the associate director and scientific director of the Ragon Institute of MGH, MIT and Harvard, as well as the first Phillip T. and Susan M. Ragon Professor in the MIT Department of Biology. The National Academy of Medicine recognized Batista for “his work unraveling the biology of antibody-producing B cells to better understand how our body’s immune systems responds to infectious disease.” More recently, Facundo’s research has advanced preclinical vaccine and therapeutic development for globally important diseases including HIV, malaria, and influenza.

Batista earned a PhD from the International School of Advanced Studies and established his lab in 2002 as a member of the Francis Crick Institute (formerly the London Research Institute), simultaneously holding a professorship at Imperial College London. In 2016, he joined the Ragon Institute to pursue a new research program applying his expertise in B cells and antibody responses to vaccine development, and preclinical vaccinology for diseases including SARS-CoV-2 and HIV. Batista is an elected fellow or member of the U.K. Academy of Medical Sciences, the American Academy of Microbiology, the Academia de Ciencias de América Latina, and the European Molecular Biology Organization, and he is chief editor of The EMBO Journal.

Dina Katabi SM ’99, PhD ’03 is the Thuan (1990) and Nicole Pham Professor in the Department of Electrical Engineering and Computer Science at MIT. Her research spans digital health, wireless sensing, mobile computing, machine learning, and computer vision. Katabi’s contributions include efficient communication protocols for the internet, advanced contactless biosensors, and novel AI models that interpret physiological signals. The NAM recognized Katabi for “pioneering digital health technology that enables non-invasive, off-body remote health monitoring via AI and wireless signals, and for developing digital biomarkers for Parkinson’s progression and detection. She has translated this technology to advance objective, sensitive measures of disease trajectory and treatment response in clinical trials.”

Katabi is director of the MIT Center for Wireless Networks and Mobile Computing. She is also a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), where she leads the Networks at MIT Research Group. Katabi received a bachelor’s degree from the University of Damascus and MS and PhD degrees in computer science from MIT. She is a MacArthur Fellow; a member of the American Academy of Arts and Sciences, National Academy of Sciences, and National Academy of Engineering; and a recipient of the ACM Computing Prize.

Additional MIT alumni who were elected to the NAM for 2025 are:

  • Christopher S. Chen SM ’93, PhD ’97, an alumnus of the Department of Mechanical Engineering and the Harvard-MIT Program in Health Sciences and Technology;
  • Michael E. Matheny SM ’06, an alumnus of the Harvard-MIT Program in Health Sciences and Technology; and
  • Rebecca R. Richards-Kortum SM ’87, PhD ’90, and alumna of the Department of Physics and the Harvard-MIT Program in Health Sciences and Technology.

Established originally as the Institute of Medicine in 1970 by the National Academy of Sciences, the National Academy of Medicine addresses critical issues in health, science, medicine, and related policy, and inspires positive actions across sectors.

“I am deeply honored to welcome these extraordinary health and medicine leaders and researchers into the National Academy of Medicine,” says NAM President Victor J. Dzau. “Their demonstrated excellence in tackling public health challenges, leading major discoveries, improving health care, advancing health policy, and addressing health equity will critically strengthen our collective ability to tackle the most pressing health challenges of our time.”

Department of Biology welcomes new faculty Yunha Hwang in shared position with EECS, Schwarzman College of Computing

Hwang is one of 11 new faculty members that occupy core computing and shared positions, bringing varied backgrounds and expertise to the MIT community.

Amanda Diehl | MIT Schwarzman College of Computing
October 17, 2025

The MIT Schwarzman College of Computing welcomes 11 new faculty members in core computing and shared positions to the MIT community. They bring varied backgrounds and expertise spanning sustainable design, satellite remote sensing, decision theory, and the development of new algorithms for declarative artificial intelligence programming, among others.

“I warmly welcome this talented group of new faculty members. Their work lies at the forefront of computing and its broader impact in the world,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science.

College faculty include those with appointments in the Department of Electrical Engineering and Computer Science (EECS) or in the Institute for Data, Systems, and Society (IDSS), which report into both the MIT Schwarzman College of Computing and the School of Engineering. There are also several new faculty members in shared positions between the college and other MIT departments and sections, including Political Science, Linguistics and Philosophy, History, and Architecture.

“Thanks to another successful year of collaborative searches, we have hired six additional faculty in shared positions, bringing the total to 20,” says Huttenlocher.

The new shared faculty include:

Bailey Flanigan is an assistant professor in the Department of Political Science, holding an MIT Schwarzman College of Computing shared position with EECS. Her research combines tools from social choice theory, game theory, algorithms, statistics, and survey methods to advance political methodology and strengthen democratic participation. She is interested in sampling algorithms, opinion measurement, and the design of democratic innovations like deliberative minipublics and participatory budgeting. Flanigan was a postdoc at Harvard University’s Data Science Initiative, and she earned her PhD in computer science from Carnegie Mellon University.

Brian Hedden PhD ’12 is a professor in the Department of Linguistics and Philosophy, holding an MIT Schwarzman College of Computing shared position with EECS. His research focuses on how we ought to form beliefs and make decisions. His works span epistemology, decision theory, and ethics, including ethics of AI. He is the author of “Reasons without Persons: Rationality, Identity, and Time” (Oxford University Press, 2015) and articles on topics such as collective action problems, legal standards of proof, algorithmic fairness, and political polarization. Prior to joining MIT, he was a faculty member at the Australian National University and the University of Sydney, and a junior research fellow at Oxford University. He received his BA from Princeton University and his PhD from MIT, both in philosophy.

Yunha Hwang is an assistant professor in the Department of Biology, holding an MIT Schwarzman College of Computing shared position with EECS. She is also a member of the Laboratory for Information and Decision Systems. Her research interests span machine learning for sustainable biomanufacturing, microbial evolution, and open science. She serves as the co-founder and chief scientist at Tatta Bio, a scientific nonprofit dedicated to advancing genomic AI for biological discovery. She holds a BS in computer science from Stanford University and a PhD in biology from Harvard University.

Ben Lindquist is an assistant professor in the History Section, holding an MIT Schwarzman College of Computing shared position with EECS. Through a historical lens, his work observes the ways that computing has circulated with ideas of religion, emotion, and divergent thinking. His book, “The Feeling Machine” (University of Chicago Press, forthcoming), follows the history of synthetic speech to examine how emotion became a subject of computer science. He was a postdoc in the Science in Human Culture Program at Northwestern University and earned his PhD in history from Princeton University.

Mariana Popescu is an assistant professor in the Department of Architecture, holding an MIT Schwarzman College of Computing shared position with EECS. She is also a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). A computational architect and structural designer, Popescu has a strong interest and experience in innovative ways of approaching the fabrication process and use of materials in construction. Her area of expertise is computational and parametric design, with a focus on digital fabrication and sustainable design. Popescu earned her doctorate at ETH Zurich.

Paris Smaragdis SM ’97, PhD ’01 is a professor in the Music and Theater Arts Section, holding an MIT Schwarzman College of Computing shared position with EECS. His research focus lies at the intersection of signal processing and machine learning, especially as it relates to sound and music. Prior to coming to MIT, he worked as a research scientist at Mitsubishi Electric Research Labs, a senior research scientist at Adobe Research, and an Amazon Scholar with Amazon’s AWS. He spent 15 years as a professor at the University of Illinois Urbana Champaign in the Computer Science Department, where he spearheaded the design of the CS+Music program, and served as an associate director of the School of Computer and Data Science. He holds a BMus from Berklee College of Music and earned his PhD in perceptual computing from MIT.

Daniel Varon is an assistant professor in the Department of Aeronautics and Astronautics, holding an MIT Schwarzman College of Computing shared position with IDSS. His work focuses on using satellite observations of atmospheric composition to better understand human impacts on the environment and identify opportunities to reduce them. An atmospheric scientist, Varon is particularly interested in greenhouse gasses, air pollution, and satellite remote sensing. He holds an MS in applied mathematics and a PhD in atmospheric chemistry, both from Harvard University.

In addition, the School of Engineering has adopted the shared faculty search model to hire its first shared faculty member:

Mark Rau is an assistant professor in the Music and Theater Arts Section, holding a School of Engineering shared position with EECS. He is involved in developing graduate programming focused on music technology. He has an interest in musical acoustics, vibration and acoustic measurement, audio signal processing, and physical modeling synthesis. His work focuses on musical instruments and creative audio effects. He holds an MA in music, science, and technology from Stanford, as well as a BS in physics and BMus in jazz from McGill University. He earned his PhD at Stanford’s Center for Computer Research in Music and Acoustics.

The new core faculty are:

Mitchell Gordon is an assistant professor in EECS. He is also a member of CSAIL. In his research, Gordon designs interactive systems and evaluation approaches that bridge principles of human-computer interaction with the realities of machine learning. His work has won awards at conferences in human-computer interaction and artificial intelligence, including a best paper award at CHI and an Oral at NeurIPS. Gordon received a BS from the University of Rochester, and MS and PhD from Stanford University, all in computer science.

Omar Khattab is an assistant professor in EECS. He is also a member of CSAIL. His work focuses on natural language processing, information retrieval, and AI systems. His research includes developing new algorithms and abstractions for declarative AI programming and for composing retrieval and reasoning. He received his BS from Carnegie Mellon University and his PhD from Stanford University, both in computer science.

Rachit Nigam will join EECS as an assistant professor in January 2026. He will also be a member of CSAIL and the Microsystems Technology Laboratories. He works on programming languages and computer architecture to address the design, verification, and usability challenges of specialized hardware. He was previously a visiting scholar at MIT. Nigam earned an MS and PhD in computer science from Cornell University.