Research Area: Biochemistry, Biophysics, and Structural Biology

From snapshots to movie: capturing the complete process of embryonic development

New research from the Weissman Lab provides a comprehensive view of a process that has long been studied in pieces: how a single fertilized egg gives rise to hundreds of different kinds of cells, arranged in the right places and at the right times to build an animal.

Shafaq Zia | Whitehead Institute
October 9, 2026

For decades, scientists have been able to look at individual moments in the development of an embryo: a snapshot of a developing brain, a picture of how the heart takes shape, or a glimpse of cells beginning to form the nervous system.

But what if instead of taking snapshots, they could watch the entire process unfold?

A new study out of the lab of Whitehead Institute Member Jonathan Weissman, also a professor of biology at the Massachusetts Institute of Technology (MIT) and a Howard Hughes Medical Institute (HHMI) Investigator, offers one of the most detailed views yet of how a mammal is built, cell by cell.

By following the family history of over a million cells as a mouse embryo develops, the researchers have created a kind of developmental blueprint, or movie, showing how cells divide and ultimately become the tissues and organs in the body.

This work, published Oct. 8 in the journal Cell,  in collaboration with Zachary Smith’s group at Yale University and the Max Planck Institute for Molecular Genetics, provides a comprehensive view of a process that has long been studied in pieces: how a single fertilized egg gives rise to hundreds of different kinds of cells, arranged in the right places and at the right times to build an animal.

“This is really a view of how the information in the genome plays out over space and time to go from linear DNA to a three-dimensional animal,” Weissman says.

The map could have broad implications for understanding birth defects and cancer. Many birth defects arise when cells change course as tissues and organs are being assembled. A detailed map of typical development could help researchers pinpoint where and when those processes go awry. In cancer, the same approach could help scientists trace when cells acquire traits such as the ability to spread or resist treatment.

The map could also inform stem cell research by revealing the sequence of cell states that leads to mature, functional cell types.

In the 1980s, scientists ventured into similar territory by painstakingly following the development of Caenorhabditis elegans, a tiny worm whose transparent body contains only about 1,000 cells. Using microscopy, they could trace how individual cells divided and where their descendants ended up.

But achieving something similar in a mammal was a challenge on a vastly different scale. Mammalian embryos contain far more cells, develop inside the uterus — out of sight — and do not follow a completely predetermined script.

The new study tackles this challenge using a technology developed in the Weissman Lab called PEtracer. The system acts somewhat like a flight recorder inside a cell. PEtracer makes small, heritable changes to DNA that are passed down as cells divide. By reading those changes later, scientists can work backward to reconstruct which cells came from which ancestors, essentially building a family tree for the cells in the developing embryo.

In this work, the researchers combined these family trees with information about what genes were turned on in each cell and where these cells were located in the embryo. They analyzed over a million cells from mouse embryos collected at multiple points during development, allowing them to follow not just where cells ended up, but when they began heading toward particular fates.

A new study from Jay Shendure’s group at the University of Washington, published concurrently in the journal Science, uses a related approach called DNA Typewriter to track cell divisions in developing mouse embryos and build a record of their cellular history.

Both studies provide a much more comprehensive look at mammalian development than existed previously. The Weissman team, however, studied embryos at closely spaced stages of development, looking at multiple embryos at each stage. This gave them a more detailed picture of how development unfolds and allowed them to ask how consistently cells follow the same paths from one embryo to another.

With this detailed timeline, the researchers could also determine when cells commit to particular fates, how many early cells go on to form a tissue, and how they ultimately contribute to the developing organ.

While earlier studies might focus on one cell population, this approach puts those individual stories into the context of the entire developing animal — a  perspective that is particularly useful for understanding disease.

Cancer, for example, is not a single event but a process in which cells acquire new characteristics over time, including the ability to spread or resist treatment. A lineage map could allow researchers to trace when those characteristics emerge and how cells change as they acquire them.

“Development and cancer both depend on decisions cells make about what they will  become,” says Luke Koblan, a postdoc in the Weissman Lab and co-first author of the paper. “By tracing how cells develop in mouse embryos, we hope to better understand how cancer cells change in ways that help them spread or resist treatment.”

The work could also provide a new guide for stem cell research. Scientists have spent decades trying to coax stem cells into becoming mature, functional versions of particular cell types for research or potential therapies. But reproducing the precise conditions in an embryo is difficult.

“If we could have a step-by-step recipe for how to create every cell type in the body,” says graduate student and co-first author William Colgan, “that would be incredibly powerful for stem cell biology.”

Weissman compares the work to the Human Genome Project: knowing the sequence of the human genome gave scientists the ingredients — but not the instructions for how those ingredients are used — to build an organism.

“The genome is like the ingredient list for a four-course meal,” he says. “It tells you what the ingredients are, but it doesn’t tell you which ones you use when, how much you use, or where you put them. Without the recipe, it’s impossible to know how those ingredients can become the meal.”

This new map begins to fill in the details of that missing recipe. The result is a resource that researchers can use to explore mammalian development in a fundamentally new way. Rather than studying development as a collection of separate processes, scientists can now begin to see how those processes fit together into one unfolding story.

Avoiding a sticky situation: how cells stop messenger RNAs from clumping together

Although cells contain many thousands of mRNA molecules crowded into a tiny space, these molecules typically don't form the clumping aggregates often seen when they're removed from their native context for study. New research from the Jain Lab suggests that evolution has shaped mRNA sequences to reduce unwanted interactions.

Alice McCarthy | Whitehead Institute
September 14, 2026

Messenger RNA, or mRNA, is best known for carrying genetic instructions from DNA to the cellular machinery that makes proteins. But all RNA molecules have another, less appreciated property: they are naturally sticky.

When RNA is removed from cells and studied in the laboratory, the molecules readily interact with one another and can clump together, or aggregate. This creates a biological puzzle. Cells contain many thousands of mRNA molecules crowded into a tiny space, yet their mRNAs do not routinely form the large aggregates that their physical properties would seem to favor. This puzzling behavior is important for cell function: unwanted RNA interactions can prevent mRNAs from being accessible to make proteins, and large RNA aggregates can be toxic to cells.

Now, researchers at Whitehead Institute have uncovered one way cells may have evolved to avoid these sticky situations. Their findings suggest that evolution has shaped mRNA sequences to reduce unwanted interactions with other mRNAs. The work could potentially inform the development of RNA therapeutics, allowing drug designers to learn from evolution when selecting RNA sequences.

The study, led by Whitehead Institute Member Ankur Jain, also an associate professor of biology at MIT, and Marco Todisco, a postdoctoral researcher in his lab, reveals a previously unrecognized constraint on the evolution of genetic sequences: DNA must not only encode functional proteins, but also produce mRNAs with physical properties that help keep them soluble inside the cell.

The researchers’ findings were published in the Proceedings of the National Academy of Sciences on September 14.

Scientists studying purified RNA have known for decades that the molecules can readily aggregate. But if the chemistry of RNA makes these interactions so favorable outside cells, Todisco wondered, why shouldn’t the same thing happen inside them?

To investigate, Todisco and colleagues focused on Escherichia coli, or E. coli, a bacterium whose biology has been extensively studied. Researchers have detailed information about which mRNAs are present in an E. coli cell, how many copies of each are present, and what those molecules look like — making it possible to model the behavior of an entire collection of cellular mRNAs, known as the transcriptome.

Todisco developed computer simulations that tracked individual mRNA molecules and predicted how they would behave at concentrations similar to those found inside a cell. Based on the physical chemistry of RNA alone, the simulations indicated that the molecules should aggregate. Longer mRNAs were particularly prone to joining these clusters.

The team then tested that prediction experimentally. With help from Christalyn Ausler, a research technician in the Jain lab, they purified mRNA from E. coli cells. The authors found that without proteins and other components normally surrounding it in the cell, the purified mRNA readily aggregated. Using RNA sequencing, the researchers identified which mRNAs were enriched in the aggregates and found that their properties closely matched the simulations.

Those findings strengthened the original puzzle: If mRNA has such a strong physical tendency to associate with other RNA molecules, how have cells managed that problem?

The researchers found part of the answer written into the genetic sequences themselves.

DNA carries the instructions for building proteins using three-letter sequences called codons, each of which specifies an amino acid, one of the building blocks of proteins. But the genetic code contains redundancy: most amino acids can be encoded by more than one codon. That means an enormous number of different DNA and mRNA sequences can produce exactly the same protein. Evolution therefore has some freedom in which sequence it uses.

The researchers took advantage of that flexibility to computationally create alternative versions of E. coli mRNAs. They changed the RNA sequences while preserving the proteins they encoded — in effect creating alternative evolutionary paths in which an organism could make the same proteins from different mRNAs.

When the researchers compared these randomized sequences with naturally occurring E. coli mRNAs, they found that the natural sequences were less prone to interacting with one another. Native mRNAs tended to fold onto themselves and to avoid exposing sticky stretches, reducing opportunities to form stable and unwanted interactions with other mRNA molecules.

In other words, stickiness is unavoidable, but evolution appears to have favored not just DNA sequences that make the right proteins, but sequences that produce less sticky mRNAs along the way.

The researchers found evidence that the phenomenon extends beyond bacteria. When they performed sequence analyses on a set of abundant human mRNAs, they found similar signatures: naturally occurring human RNA sequences also showed a reduced potential for aggregation compared with alternative sequences.

The discovery adds another dimension to the familiar “central dogma” of molecular biology, in which information flows from DNA to RNA to protein. Scientists have traditionally thought about genetic sequences largely in terms of their ultimate product: the protein. The new findings suggest that evolution also has to contend with the physical behavior of the mRNA intermediate.

That may not be the whole solution. Although naturally occurring mRNA sequences are less prone to aggregation, purified mRNA still readily clumps together. The fact that widespread aggregation is not normally seen inside healthy cells suggests that proteins or other cellular components may provide an additional layer of protection by buffering inappropriate RNA-RNA interactions. These findings help build a broader picture of how cells may use multiple mechanisms to manage RNA interactions and prevent inappropriate aggregation.

The findings could also have implications for the growing field of mRNA therapeutics. When researchers design synthetic mRNAs for vaccines and other treatments, they can choose among different codons that ultimately produce the same protein. The new work suggests that how the resulting RNA folds and interacts with other RNAs may be another important consideration when selecting those sequences.

“What this gives us is a new lens for thinking about how genomes evolve,” Jain says. “Sequences aren’t evolving just to encode functional proteins; there is an additional constraint to produce mRNAs that are less likely to stick to one another. These findings could also provide guiding principles for designing the sequences used in mRNA vaccines and other RNA therapeutics.”

Notes:

Todisco, M., Ausler, C., and Jain, A. “Maintaining transcriptome solubility constrains mRNA sequence composition.” Proceedings of the National Academy of Sciences (2026). https://doi.org/10.1073/pnas.2622980123.

Funding:

This work is supported by grants from the NIH (R35GM151111), Chan Zuckerberg Initiative (DAF2022-250422), Richard and Susan Smith Family Foundation, and the David and Lucile Packard Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Lillian Eden | Department of Biology
August 27, 2026

A protein’s function is determined by its structure, and structure — the way a protein folds — is determined by its sequence of amino acids, the building blocks of proteins.

Many methods for designing novel proteins, including examples that could bind to a disease-causing molecule in our cells, involve a two-step process: The structure comes first, and then a machine-learning framework generates a repertoire of sequences that could potentially adopt that structure.

In nature, many different amino acid sequences can fold into the same structure. At the same time, one amino acid sequence can potentially adopt different structures depending on the protein’s flexibility or a functional trigger. Therefore, when researchers use artificial intelligence to design new proteins, the challenge is to guide AI to “see” that there are many potentially useful answers — that many sequences can adopt the same fold

“For years, the field has measured success by asking whether a model can reproduce the protein sequence that evolution happened to select — our work shows that this isn’t the best metric for protein design,” says Amy E. Keating, Department of Biology head, Jay A. Stein (1968) Professor of Biology, professor of biological engineering, and senior author of a paper recently published in PNAS.

PottsMPNN, a new machine-learning framework developed in the Department of Biology, incorporates the physical principles that govern protein structure and stability, improving sequence generation and the ability to predict how mutations will affect a protein’s stability. In other words, the model has a better understanding of the sequence-energy landscape, meaning the relationship between the identity of each amino acid and the stability of the protein.

Adding this framework to a protein design pipeline will allow researchers to design structurally feasible proteins with sequences that don’t resemble those of any native protein.

“If we’re thinking about a completely novel, designed structure, there would be no native sequence to compare it to,” says graduate student and lead author Foster Birnbaum. “What we actually care about is how likely the generated sequences are to fold into the desired structures, how well the model understands the sequence-energy landscape, and how well it can predict the effect of mutations on the stability of the protein.”

Beyond the noise 

In the same way that AI has recently powered some dramatic social changes, so too has machine learning impacted the pace and breadth of fundamental biological research. Only recently has it become possible to reliably use a computational model to generate a protein structure or sequence. Perhaps the most widely used model today, however, was released in 2022.

“For a field that’s moving as fast as machine learning in biology, that model has not been surpassed — we’ve been trying to understand why that is, and what it is about that model that makes it so useful,” Birnbaum says.

Birnbaum was first interested in strategic applications of something researchers call “noise,” or adding variations to a protein structure during training. Noise decreases the tendency of the model to overly mimic native sequences, increasing the diversity of structures for which it’s able to generate sequences.

PottsMPNN also uses a pairwise distribution to capture interactions between amino acids. The ability to account for the physical interactions between all 20 possible sequence options at a pair of positions in the protein is a key reason that PottsMPNN more accurately models the sequence-energy landscape than other methods.

Finally, Birnbaum says, they introduced sets of evolutionarily related sequences into training the PottsMPNN framework to teach the model how different sequences can adopt the same folded structure.

Birnbaum acknowledges that in trying to shift away from adhering to native sequences, incorporating evolutionary information is, in some ways, still a reliance on them. But PottsMPNN succeeded in demonstrating that as the model depends less and less on native sequences, structural compatibility and energy prediction, including for novel proteins, improve.

Protein design in the age of AI

“Once we can design any protein we want, that enables us to do a potentially scary amount of biological engineering,” Birnbaum says. “It’s a difficult task, but I’m really optimistic about this century’s progress in biology.”

Birnbaum hopes that the model could be further improved and fine-tuned for a specific task, which has in the past led to better predictions, for example, on the outcome or consequence of a particular mutation.

Ultimately, according to Keating, “Our methods move the field toward designing useful new-to-nature proteins for diverse applications while providing a stronger foundation for future advances.”

Cells use a little-known molecule to protect themselves from iron overload

Research from the Jain and Henry Labs in the Whitehead Institute and Koch Institute respectively have discovered that cells are protected from destructive levels of iron buildup by small molecules called polyamines, which act like storage lockers, safely holding the metal in a non-reactive state until cells need it.

Shafaq Zia | Whitehead Institute
August 14, 2026

Iron is essential. Our cells need it to produce energy, carry oxygen throughout the body, and power countless chemical reactions that sustain life. But this metal has a dark side. When too much of it is left free inside cells, it can trigger destructive reactions that break down DNA, proteins, and even cell membranes.

Now, Whitehead Institute Member Ankur Jain and Whitney Henry, an investigator in MIT’s Department of Biology and the Koch Institute for Integrative Cancer Research, together with graduate student Pushkal Sharma have discovered that cells rely on an unexpected protector against this threat: small molecules called polyamines.

The researchers’ detailed findings, published Aug. 14 in the journal Cell, reveal that polyamines act like storage lockers for iron, safely holding the metal in a non-reactive state until cells need it.

These findings solve a decades-old mystery about why cells maintain such extraordinarily high levels of polyamines and uncover a previously unknown defense mechanism that protects cells from toxic iron overload.

This work could also help scientists develop better cancer treatments, by allowing iron overload to trigger cancer cell death. It could also offer new clues about diseases like early-onset Parkinson’s disease, in which mutations affect polyamine levels within neurons.

The Jain Lab studies RNA, the intermediary between DNA and the tiny molecular machines called proteins that perform most of the essential tasks inside cells. The lab is particularly interested in how RNA folds, misfolds, and sometimes clumps inside cells.

Jain and Sharma first began studying polyamines because these molecules bind to RNA and help shape its structure. However, they suspected that polyamines must be playing other roles inside cells: they’re among the most abundant small molecules within cells, present at levels comparable to ATP, the molecule cells use as their energy currency.

“We’ve known that without polyamines, cells stop growing and dividing,” says Jain, who is also an associate professor of biology at the Massachusetts Institute of Technology (MIT). “But their best-known function only requires a small fraction of the polyamine levels cells actually have.”

To uncover polyamines’ hidden function inside cells, the researchers used a large-scale genetic approach that allows them to screen the entire genome at once, rather than testing genes one-by-one, in order to find out which cellular processes are impacted when polyamine levels are changed within cells.

The screen revealed that when cells have reduced levels of polyamines, a protein called GPX4 becomes essential for survival. GPX4 is known to prevent harmful chemical reactions that damage the fatty molecules that make up cell membranes.

The team also found that cells with lower polyamine levels have higher amounts of another protein that acts as an iron sponge and keeps the metal in a mineralized form. Together, these findings led the researchers to hypothesize that polyamines might be helping keep iron in a safe, non-reactive state within cells.

To test this idea, they developed a new fluorescent sensor that would allow them to measure chemically reactive iron inside living cells. The new sensor causes living cells to glow based on the amount of chemically reactive iron they contain, allowing researchers to track any changes under a microscope in real time.

The team paired the new iron sensor with another sensor they had previously developed that measures polyamine levels within cells. By employing them simultaneously, they observed a striking pattern: as polyamine levels dropped within cells, the amount of chemically reactive iron went up, offering new evidence that polyamines play a key role in preventing toxic iron build up inside cells.

Beyond answering a fundamental biological question, these findings could have implications for cancer treatment. Cancer cells often rely on high polyamine levels to support their rapid growth and division. However, cancer drugs designed to lower polyamine levels to stop cell division have had limited success.

“We saw that when polyamine levels fall, cells rely on GPX4 to protect themselves from iron toxicity,” says Sharma, who is also the first author of the study. “This could mean that combining drugs that lower polyamine levels with those that block GPX4 might be more effective for killing cancer cells than targeting either pathway alone.”

The discovery may also have implications beyond cancer. Mutations in genes that help move polyamines around cells are linked to a rare form of early-onset Parkinson’s disease, and scientists have long observed unusually high levels of iron in the brains of Parkinson’s patients.

While it is still unclear whether excess iron directly contributes to neuron death in Parkinson’s, the discovery that polyamines help buffer reactive iron inside cells offers a possible explanation for this link and opens new directions for future investigation.

In addition, the researchers expect the new iron sensor to be a valuable tool for other scientists. By allowing them to track chemically reactive iron inside living cells, it could power new discoveries in aging, cancer, and neurodegeneration.

“There are a lot of promising future directions for this work,” Jain says. “It’s exciting to think about how these tools and findings could help answer further questions about disease pathways and potentially help design better therapies.”

Sharma, P., Keys, H. R., Mansell, R. P., Stark, J., Girard, L., Ausler, C., Anderson, R., Müller, S., Imada, S., Pires, I. S., Kunchok, T., Waite, M., Yuan, B., Deik, A., Ferro, L., Hammond, P. T., Rodriguez, R., Pandelia, M., Henry, W. S., & Jain, A. (2026). Polyamines buffer labile iron to suppress ferroptosis. Cell. https://doi.org/10.1016/j.cell.2026.07.040

Research reported in this press release was supported by the National Institutes of Health under grant number R35GM151111 awarded to A.J., which funded 25% of the project’s costs. Additional support was provided by the Bumpus Foundation and the Pew Charitable Trusts. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Why are some bacterial genes high in purines?

In certain species of bacteria, the answer lies in shielding RNA transcripts from a quality-control factor called Rho. Understanding the requirements for expressible sequences is critical for expression engineering of therapeutic agents.

Lillian Eden | Department of Biology
July 2, 2026

In the study of bacteria, a longstanding dogma held that two molecular machines — RNA polymerase, which leads the way in transcribing DNA into RNA, and ribosomes, which bring up the rear translating RNA into proteins — worked so closely in tandem that they were effectively attached.

This close coupling of transcription and translation in bacteria was thought to be fundamental to gene expression in part because the trailing ribosome could shield nascent gene products from an effective and omnipresent quality-control protein called Rho.

In bacteria that exhibit something called runaway transcription, however, the polymerase instead speeds ahead, unhitched from its protective ribosome. Inexplicably, however, in bacteria that exhibit this runaway transcription, such as Bacillus subtilis, Rho targeted primarily noncoding, useless RNA products.

New research from the Department of Biology reveals that the secret to Rho’s quality-control specificity lies in the sequence composition of nucleotide bases that make up coding strands of DNA.

“We started with a hypothesis that Rho was regulated by sequence, but the fact that the sequence alone was enough to protect any gene in the entire B. subtilis genome from Rho was really surprising,” says Julia Dierksheide PhD ’26, a graduate student in the Li Lab and first author of a paper recently published in Nature Microbiology. “That’s a really diverse range of sequences — what sequence feature is shared by every single gene in the genome?”

Barricading with bias

Rho serves as a termination factor, meaning that it is a crucial mechanism for preventing bacteria from wasting precious resources by making RNA transcripts that serve no purpose.

All the information a bacterial cell needs is encoded in its DNA, which is made up of two strands of nucleic acids. These strands twist together to form a double helix, with genetic information codified in pairs of bases: purines guanine and adenine are matched with pyrimidines cytosine and thymine, respectively. Any sequence that gives rise to RNA transcripts is stored in complement to a parallel, noncoding strand, meaning that a large portion of genetic material is transcriptionally useless.

Coding DNA strands in certain bacteria were known to be significantly higher in purines guanine and adenine compared to the rest of the bacterial genome. The researchers found that this purine bias alone shields productive mRNA transcripts from Rho-mediated termination.

“I love having a big, complicated dataset and trying to reduce that to biological meaning,” Dierksheide says. “It seems like Rho itself has been broadly shaping the evolution of the B. subtilis genome to create these sequence composition biases.”

Bacterial species that, over generations, have lost Rho no longer exhibit this strong purine bias.

Rho also serves as a regulatory factor in bacteria becoming motile, forming biofilms, or sporulating, all of which are critical for biology and survival. The purine bias could also provide a layer of protection against the insertion of foreign DNA, for example, when a viral bacteriophage infects bacteria.

“Bacteria exist as single cells, so everything that they do, they have to do through gene expression,” Dierksheide says. “Understanding the fundamental details about how gene expression works, how a cell encodes all the information it needs to survive in the nucleotide sequence of the genome, is really exciting.”

Future directions

Although the exact mechanism underlying Rho’s specificity remains unclear, these results crack an underlying code in the composition of bacterial genomes.

Dierksheide said she hoped to perform a similar screen to characterize Rho’s specificity in Escherichia coli, which diverged from B. subtilis on the evolutionary tree an estimated 2 billion years ago and still exhibits coupled transcription-translation, where the transcribing RNA polymerase is closely followed by a translating ribosome.

The high sequence specificity of B. subtilis Rho is crucial for the protection of its runaway RNA polymerase, in which that molecular machine speeds ahead of the ribosome. A systematic comparison to E. coli Rho could help reveal how this heightened stringency arose.

This information will be critical for engineering diverse bacterial species for applications including the production of therapeutic agents. Other bacterial species, such as B. subtilis, may be better models for this process because they have abundant secretion pathways, according to Dierksheide, making it much easier to produce and isolate proteins in large quantities.

“Our findings reveal an important criterion for successful sequence design that must be considered in expression engineering,” says associate department head, associate professor of biology, and Howard Hughes Medical Institute investigator Gene-Wei Li, the lead author of the study. “There are so many cryptic messages in the genome, like the purine bias, and we are just beginning to be able to decipher what they mean.”

Enzymes that assemble into droplets can speed up cellular reactions

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

Anne Trafton | MIT News
June 1, 2026

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

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

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

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

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

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

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

Forming droplets

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

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

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

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

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

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

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

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

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

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

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

Controlling reactions

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

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

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

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

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

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

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

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

Slice and dice

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

Lillian Eden | Department of Biology
April 9, 2026

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

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

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

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

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

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

Light it up

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

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

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

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

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

Problems at the periphery

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

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

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

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

There may also be other proteins or interactions involved.

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

Future directions

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

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

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

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

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

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

Mackenzie White | Whitehead Institute
March 17, 2026

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

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

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

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

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

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

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

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

The answer turned out to be surprisingly sophisticated.

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

The degradation machinery activates only when both signals are present.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Ekaterina Khalizeva | Department of Biology
March 20, 2026

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

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

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

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

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

A negative control that was not so negative

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

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

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

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

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

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

Discovering new biology in a saturated field

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

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

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

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

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

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

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

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

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

The future of cryoPRISM

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

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

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

Whitehead Institute Member Jonathan Weissman joins global Cancer Grand Challenges team

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

Mackenzie White | Whitehead Institute
March 4, 2026

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

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

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

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

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

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

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

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

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