Category: Building 68

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.

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.”

Studying the genetic basis of disease to explore fundamental biological questions

Eliezer Calo’s studies of craniofacial malformations have yielded insight into protein synthesis and embryonic development.

Anne Trafton | MIT News
March 6, 2026

When Associate Professor Eliezer Calo PhD ’11 was applying for faculty positions, he was drawn to MIT not only because it’s his alma mater, but also because the Department of Biology places high value on exploring fundamental questions in biology.

In his own lab, Calo studies how craniofacial malformations arise. One motivation is to seek new treatments for those conditions, but another is to learn more about fundamental biological processes such as protein synthesis and embryonic development.

“We use genes that are mutated in disease to uncover fundamental biology,” Calo says. “Mutations that happen in disease are an experiment of nature, telling us that those are the important genes, and then we follow them up not only to understand the disease, but to fundamentally understand what the genes are doing.”

Calo’s work has led to new insights into how ribosomes form and how they control protein synthesis, as well as how the nucleolus, the birthplace of ribosomes in eukaryotic cells, has evolved over hundreds of millions of years.

In addition to earning his PhD at MIT, Calo is also an alumnus of MIT’s Summer Research Program (MSRP), which helps to prepare undergraduate students to pursue graduate education. Since starting his lab at MIT, Calo has made a point to serve as a research mentor for the program every summer.

“I feel that it’s important to pay back to the program that helped me realize what I wanted to do,” he says.

A nontraditional path

Growing up in a mountainous region of Puerto Rico, Calo was the first person from his family to finish high school. While attending the University of Puerto Rico at Rio Piedras, the largest university in Puerto Rico, he explored a few different majors before settling on chemistry.

One of Calo’s chemistry professors invited him to work in her lab, where he did a research project studying the pharmacokinetics of cell receptors found on the surface of astrocytes, a type of brain cell.

“It was a good mix of biology and chemistry,” he says. “I think that that was the catalyst to my pursuit of a career in the sciences.”

He learned about MSRP from Mandana Sassanfar, a senior lecturer in biology at MIT and director of outreach for several MIT departments, at an event hosted by the University of Puerto Rico for students interested in careers in science. He was accepted into the program, and during the summer after his junior year, he worked in the lab of Stephen Bell, an MIT professor of biology. That experience, he says, was transformative.

“Without that experience, I would have probably chosen another career,” Calo says. In Puerto Rico, “science was fun, but it was a struggle. We had to make everything from scratch, and then you spend more time making reagents than doing the experiments. When I came to MIT, I was always doing experiments.”

During that time, he realized he liked working in biology labs more than chemistry labs, so when he applied to graduate school, he decided to move into biology. He applied to five schools, including MIT. “Once MIT sent me the acceptance, I just had to say yes. There was no saying no.”

At MIT, Calo thought he might study biochemistry, but he ended up focusing on cancer biology instead, working with Jacqueline Lees, an MIT biology professor, to study the role of the tumor suppressor protein Rb.

After finishing his PhD, Calo felt burnt out and wasn’t sure if he wanted to continue along the academic track. His thesis committee advisors encouraged him to do a postdoc just to try it out, and he ended up going to Stanford University, where he fell in love with California and switched to a new research focus. Working with Joanna Wysocka, a professor of developmental biology at Stanford, he began investigating how development is affected by the regulation of proteins that make up cellular ribosomes — a topic his lab still studies today.

Returning to MIT

When searching for faculty jobs, Calo focused mainly on schools in California, but also sent an application to MIT. As he was deciding between offers from MIT and the University of California at Berkeley, a phone call from Angelika Amon, the late MIT professor of biology, convinced him to take the cross-country leap back to MIT.

“She had me on the phone for more than one hour telling me why I should come to MIT,” he recalls. “And that was so heartwarming that I could not say no.”

Since starting his lab in 2017, Calo has been studying how defects in the production of ribosomes give rise to diseases, in particular craniofacial malformations such as cleft palate.

Ribosomes, the organelles where protein synthesis occurs, consist of two subunits made of about 80 proteins. A longstanding question in biology has been why mutations that affect ribosome formation appear to primarily affect the development of the face, but not the rest of the body.

In a 2018 study, Calo discovered that this is because the mutations that affect ribosomes can have secondary effects that influence craniofacial development. In embryonic cells that form the face, a mutation in a gene called TCOF1 activates p53 at a higher level than in other embryonic cells. High levels of p53 cause some of those cells to undergo programmed cell death, leading to Treacher-Collins Syndrome, a disorder that produces underdeveloped bones in the jaw and cheek.

His lab has shown that p53 overactivation is also responsible for craniofacial disorders caused by mutations in RNA splicing factors.

Calo’s work on ribosome formation also led him to explore another cell organelle known as the nucleolus, whose role is to help build ribosomes. In 2023, he found that a gene called TCOF1, which can lead to craniofacial malformations when mutated, is critical for forming the three compartments that make up the nucleolus.

That finding, he says, could help to explain a major evolutionary shift that occurred around 300 million years ago, when the nucleolus transitioned from two to three compartments. This “tripartite” nucleolus is found in all reptiles, birds, and mammals.

“That was quite surprising,” Calo says. “Studying disease-related genes allowed us to understand a very fundamental biological process of how the nucleolus evolved, which has been a question in the field that nobody could figure out the answer for.”

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.

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.”

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.

Little picture, large revelations

A summer intensive using microscopy to study a unique type of yeast was a dream come true for BSG-MSRP-Bio student Adryanne Gonzalez.

Lillian Eden | Department of Biology
September 11, 2025

For Adryanne Gonzalez, studying yeast using microscopy at MIT this summer has been a dream come true. 

“Whatever world we’re living in, there’s an even smaller one,” Gonzalez says. “Knowing and understanding the smaller one can help us learn about the bigger stuff, and I think that’s so fascinating.” 

Gonzalez was part of the Bernard S. and Sophie G. Gould MIT Summer Research Program in Biology, working in the Lew Lab this summer. The program offers talented undergraduates from institutions with limited research opportunities at their home institutions the chance to spend 10 weeks at MIT, where they gain experience, hone skills, and create the types of connections with potential collaborators and future colleagues that are critical for success in academia. 

Gonzalez was so excited about the opportunity that she didn’t apply for any other summer programs.  

“I really wanted to work on becoming more independent in the lab, and this program was research-intensive, and you get to lead your own project,” she says. “It was this or nothing.”

two people standing at a bench in front of a computer
Adryanne Gonzalez, right, with her mentor, Lew Lab graduate student Clara Fikry, left. Gonzalez spent the summer studying Aureobasidium pullulans, a type of yeast that produces large, root-like networks. Photo credit: Mandana Sassanfar/MIT Department of Biology

The fun of science & the rigors of mentoring

The Lew Lab works with two different specimens: a model baker’s yeast that multiplies by producing a round growth called a bud that eventually separates into a separate, daughter cell; and Aureobasidium pullulans, which is unusual because it can create multiple buds at the same time, and can also spread in large networks of branching, rootlike growths called hyphae. A. pullulans is an emerging model system, meaning that researchers are still defining what normal growth and behavior is for the fungus, like how it senses and responds to obstacles, and how resources and molecular machinery are allocated to its branching structures.  

“I’m really interested in all the diversity of biology that we don’t get to study if we’re only focused on the model species,” says Clara Fikry, a graduate student in the Lew Lab and Gonzalez’s mentor for the summer. 

On the mentoring side, Fikry learned how to balance providing a rigorous workload while not overwhelming her mentee with information. 

“Science should be fun,” Fikry says. “The goal of this isn’t to produce as much data as possible; it’s to learn what the process of science is like.”

Although her day-to-day work was with Fikry, Gonzalez also received guidance from Daniel Lew himself. For example, his advice was invaluable for honing a draft of her research statement for potential graduate school applications, which she’d previously written as part of a class assignment.

“It was an assignment where I needed to hit a page count, and he pointed out that I kind of wrote the same thing three times in the first paragraph,” she shares with a laugh. He helped her understand that “when you’re writing something professionally, you want your writing to be concise and understandable to a broad spectrum of readers.” 

Life in the cohort

The BSG-MSRP-Bio program gives undergraduate students a taste of what the day-to-day life of graduate school might feel like, from balancing one’s workload and reading research papers to learning new techniques and troubleshooting when experiments don’t go as planned. Gonzalez recalls that the application process felt very “adult” and “professional” because she was responsible for reaching out to the faculty member of the lab she was interested in on her own behalf, rather than going through a program intermediary. 

Gonzalez is one of just three students from Massachusetts participating in the program this year—the program draws students from across the globe to study at MIT. 

Every student also arrives with different levels of experience, from Gonzalez, who can only work in a lab during the school year about once a week, to Calo Lab student Adriana Camacho-Badillo, who is in her third consecutive summer in the program, and continuing work on a project she began last year.

“We’re all different levels of novice, and we’re coming together, and we’re all really excited about research,” Gonzalez says.

Gonzalez is a Gould Fellow, supported at MIT through the generous donations of Mike Gould and Sara Moss. The program funding was initiated in 2015 to honor the memory of Gould’s parents, Bernard S. and Sophie G. Gould. Gould and Moss take the time to come to campus and meet the students they’re supporting every year. 

“You don’t often get to meet the person that’s helping you,” Gonzalez said. “They were so warm and welcoming, and at the end, when they were giving everyone a nice, firm handshake, Mike Gould said, ‘Make sure you keep going. Don’t give up,’ which was so sweet.” 

Gonzalez is also supported by Cedar Tree, a Boston-based family foundation that primarily funds local environmental initiatives. In the interest of building a pipeline for future scientists with potential interest in the environmental sciences and beyond, Cedar Tree recently established a grant program for local high school and undergraduate students pursuing STEM research and training opportunities. 

Gonzalez discusses her summer research with attendees of the poster session that serves as the culmination of the 10-week summer research intensive for talented non-MIT undergraduate students from around the world. Photo credit: Lillian Eden/MIT Department of Biology.

Preparing for the future

The BSG-MSRP-Bio program culminates with a lively poster session where students present their summer projects to the MIT community—the first time some students are presenting their data to the public in that format.

Although the program is aimed at students who foresee a career in academia, the majority of students who participate are uncertain about the specific field, organism, or process they’ll eventually want to study during a PhD program. For Gonzalez, the program has helped her feel more prepared for the potential rigors of academic research.

“I think the hardest thing about this program is convincing yourself to apply,” she says. “Don’t let that hinder you from exploring opportunities that may seem out of reach.” 

3 Questions: Mariely Morales Burgos on the BSG-MSRP-Bio program

Undergraduate student and Gould Fellow discusses choosing a summer research lab, living in the Greater Boston Area, and managing imposter syndrome.

Lillian Eden | Department of Biology
August 28, 2025

Mariely Morales Burgos first fell in love with MIT while participating in the Quantitative Methods Workshop, a weeklong intensive offered in January to prepare students to analyze data in biology and neuroscience. Those skills have come in handy this summer while participating in the Bernard S. and Sophie G. Gould MIT Summer Research Program in Biology (BSG-MSRP-Bio), a ten-week training program for non-MIT undergraduate students interested in pursuing an academic career.

A Gould Fellow and McNair Scholar, Morales Burgos spent the summer mentored by Associate Professor of Biology Eliezer Calo, for whom the program served as a critical stepping stone in his own career. Calo is the first BSG-MSRP-Bio program alum to receive tenure at MIT. 

A rising senior at the University of Puerto Rico at Aguadilla, Morales Burgos spent the summer using zebrafish to study the molecular machinery responsible for making proteins. 

Three people standing in an interior lab space smiling at the camera
(from right to left) Mariely Morales Burgos, mentor and Associate Professor of Biology Eliezer Calo, and Adriana Camacho-Badillo in the lab at MIT. Camacho-Badillo, a returning BSG-MSRP-Bio student, encouraged Morales Burgos to apply for the program. Photo Credit: Mandana Sassanfar/MIT Department of Biology.

Q: How did you select your lab, and what have you been working on?

A: I knew I wanted to work in Eliezer’s lab after meeting him during a QMW faculty lunch. I felt like we really connected because of his genuine passion for science, commitment to his trainees, and the way he spoke about his lab and the care he puts into mentoring. 

My research focuses on ribosomes, which are the protein factories of the cell, and they’re essential to make what the cell needs to go through different developmental stages and through its most crucial processes. In early development, zebrafish and numerous other organisms depend on maternally deposited ribosomes and associated molecular components inherited directly from the oocyte. As time goes on, their own genomes activate, and they start being able to make their own ribosomes. What I’m studying is this transition from maternal to zygotic ribosomes during early development. We know this transition happens, but we don’t know how this transition is regulated, whether it happens passively, through dilution, or actively, through targeted cellular mechanisms.  

One skill that I’ve been able to learn here, other than just learning and applying techniques, is how to develop a whole project independently, how to think critically about the next step of my project, and what other questions I can ask.

Being able to work with a live animal organism and see the developmental stages in real-time, I thought that was really cool. And it really makes me appreciate the beauty of developmental biology, and just life in general.

Q: How did you prepare for the program, and what has it been like living and working in Boston and Cambridge? As a Gould Fellow, you also met with program supporters Mike Gould and Sara Moss, who established the Bernard S. and Sophie G. Gould fund to honor the memory of Mike’s parents. What was it like to meet and talk to Mike and Sara? 

A: Once we get accepted, we’re encouraged to start communication with our faculty. I had a few meetings with Eliezer to discuss some papers, and based on our discussion and the expectations for the project, I was able to read more and start preparing before I arrived.

Every few weeks beforehand, we had a meeting with Mandana and the rest of the cohort on Zoom, and we were talking on an app called GroupMe, and we exchanged socials, so when we came here, we weren’t complete, total strangers. 

When I’m not in the lab, I spend a lot of time with my roommates, and we like walking around Boston. It’s a very walkable city and has a lot of unique architecture, but Boston weather is very unpredictable. I’m from a tropical island, so I wish someone had told me to prepare for the rain and cold, but the July weather has been so nice. 

In Puerto Rico, you don’t have public transportation, so I’ve really enjoyed commuting. Our dorms are at Northeastern, so I take the bus, and it goes over the Charles, and it’s so beautiful. 

I’m a person who feels a lot of emotions, so I was the only one who cried when we met the Goulds. It was a bit embarrassing, but that’s okay. They told me to never lose the empathy that I have, no matter how hard my journey is, to keep on holding on to my sentimental side and keep working hard, and they’re so excited to see where we end up and what we end up doing.

Mariely Morales Burgos standing in front of a paper poster, indicating a certain point of data to three people
The summer research intensive culminated in a lively poster session. Photo Credit: Lillian Eden/MIT Department of Biology

Q: This program’s aim is to make research available for students who don’t have access to hands-on experience at their home institutions, so many students, including you, are embarking on independent research projects for the first time, which could trigger “imposter syndrome.” What was that experience like for you, and what advice would you give to future BSG-MSRP-Bio program participants? 

A: I was a little bit intimidated by the program, and didn’t apply the first time I had the opportunity. Then I did the Quantitative Methods Workshop, and those eight days were beautiful. I got to see how everybody loves collaborating and that the community here is very supportive. I met many wonderful faculty who were passionate about their research, and that exposure made me realize I would love to be part of a place like this. 

Imposter syndrome is something that I feel like most everybody deals with, but MSRP is a place that, if you’re willing to put in the work, everyone is willing to help you reach the places that you dream of being. It might feel intimidating to ask questions, and you could be scared of feeling like you don’t deserve to be in these spaces. But somebody who wants you to grow will answer your questions. I wanted to be able to work independently as soon as possible, because that really showcases your abilities, but no matter what, Eliezer, who’s mentoring me, his door is always open. 

What I advise is to really dive into your project and take advantage of everything this program offers. Working hard on your project, you get to fall in love with the process and the questions you’re trying to answer and science as a whole, and there’s nothing better than to spend the summer on a project that you love.