Research Area: Microbiology

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.”

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.

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.” 

Yunha Hwang

Education 

  • PhD, 2024, Evolutionary and Organismic Biology, Harvard University
  • MS, 2018, Earth Systems, Stanford University
  • B.Sc, 2018, Computer Science, Stanford University

Research Summary

Microbial genomes encode the largest molecular, biochemical, and functional diversity on Earth. We focus on developing machine learning models and experimental approaches to discover and design novel biological functions. We integrate computation with expertise in evolution, ecology, and biochemistry to characterize and harness the functional potential of microbes.

A sum of their parts

Researchers in the Department of Biology at MIT use an AI-driven approach to computationally predict short amino acid sequences that can bind to or inhibit a target, with a potential for great impact on fundamental biological research and therapeutic applications.

Lillian Eden | Department of Biology
February 6, 2025

All biological function is dependent on how different proteins interact with each other. Protein-protein interactions facilitate everything from transcribing DNA and controlling cell division to higher-level functions in complex organisms.

Much remains unclear about how these functions are orchestrated on the molecular level, however, and how proteins interact with each other — either with other proteins or with copies of themselves. 

Recent findings have revealed that small protein fragments have a lot of functional potential. Even though they are incomplete pieces, short stretches of amino acids can still bind to interfaces of a target protein, recapitulating native interactions. Through this process, they can alter that protein’s function or disrupt its interactions with other proteins. 

Protein fragments could therefore empower both basic research on protein interactions and cellular processes and could potentially have therapeutic applications. 

Recently published in Proceedings of the National Academy of Sciences, a new computational method developed in the Department of Biology at MIT builds on existing AI models to computationally predict protein fragments that can bind to and inhibit full-length proteins in E. coli. Theoretically, this tool could lead to genetically encodable inhibitors against any protein. 

The work was done in the lab of Associate Professor of Biology and HHMI Investigator Gene-Wei Li in collaboration with the lab of Jay A. Stein (1968) Professor of Biology, Professor of Biological Engineering and Department Head Amy Keating.

Leveraging Machine Learning

The program, called FragFold, leverages AlphaFold, an AI model that has led to phenomenal advancements in biology in recent years due to its ability to predict protein folding and protein interactions. 

The goal of the project was to predict fragment inhibitors, which is a novel application of AlphaFold. The researchers on this project confirmed experimentally that more than half of FragFold’s predictions for binding or inhibition were accurate, even when researchers had no previous structural data on the mechanisms of those interactions. 

“Our results suggest that this is a generalizable approach to find binding modes that are likely to inhibit protein function, including for novel protein targets, and you can use these predictions as a starting point for further experiments,” says co-first and corresponding author Andrew Savinov, a postdoc in the Li Lab. “We can really apply this to proteins without known functions, without known interactions, without even known structures, and we can put some credence in these models we’re developing.”

One example is FtsZ, a protein that is key for cell division. It is well-studied but contains a region that is intrinsically disordered and, therefore, especially challenging to study. Disordered proteins are dynamic, and their functional interactions are very likely fleeting — occurring so briefly that current structural biology tools can’t capture a single structure or interaction. 

The researchers leveraged FragFold to explore the activity of fragments of FtsZ, including fragments of the intrinsically disordered region, to identify several new binding interactions with various proteins. This leap in understanding confirms and expands upon previous experiments measuring FtsZ’s biological activity. 

This progress is significant in part because it was made without solving the disordered region’s structure, and because it exhibits the potential power of FragFold.

“This is one example of how AlphaFold is fundamentally changing how we can study molecular and cell biology,” Keating says. “Creative applications of AI methods, such as our work on FragFold, open up unexpected capabilities and new research directions.”

Inhibition, and beyond

The researchers accomplished these predictions by computationally fragmenting each protein and then modeling how those fragments would bind to interaction partners they thought were relevant.

They compared the maps of predicted binding across the entire sequence to the effects of those same fragments in living cells, determined using high-throughput experimental measurements in which millions of cells each produce one type of protein fragment. 

AlphaFold uses co-evolutionary information to predict folding, and typically evaluates the evolutionary history of proteins using something called multiple sequence alignments for every single prediction run. The MSAs are critical, but are a bottleneck for large-scale predictions — they can take a prohibitive amount of time and computational power. 

For FragFold, the researchers instead pre-calculated the MSA for a full-length protein once and used that result to guide the predictions for each fragment of that full-length protein. 

Savinov, together with Keating Lab alum Sebastian Swanson, PhD ‘23, predicted inhibitory fragments of a diverse set of proteins in addition to FtsZ. Among the interactions they explored was a complex between lipopolysaccharide transport proteins LptF and LptG. A protein fragment of LptG inhibited this interaction, presumably disrupting the delivery of lipopolysaccharide, which is a crucial component of the E. coli outer cell membrane essential for cellular fitness.

“The big surprise was that we can predict binding with such high accuracy and, in fact, often predict binding that corresponds to inhibition,” Savinov says. “For every protein we’ve looked at, we’ve been able to find inhibitors.”

The researchers initially focused on protein fragments as inhibitors because whether a fragment could block an essential function in cells is a relatively simple outcome to measure systematically. Looking forward, Savinov is also interested in exploring fragment function outside inhibition, such as fragments that can stabilize the protein they bind to, enhance or alter its function, or trigger protein degradation. 

Design, in principle 

This research is a starting point for developing a systemic understanding of cellular design principles, and what elements deep-learning models may be drawing on to make accurate predictions. 

“There’s a broader, further-reaching goal that we’re building towards,” Savinov says. “Now that we can predict them, can we use the data we have from predictions and experiments to pull out the salient features to figure out what AlphaFold has actually learned about what makes a good inhibitor?” 

Savinov and collaborators also delved further into how protein fragments bind, exploring other protein interactions and mutating specific residues to see how those interactions change how the fragment interacts with its target. 

Experimentally examining the behavior of thousands of mutated fragments within cells, an approach known as deep mutational scanning, revealed key amino acids that are responsible for inhibition. In some cases, the mutated fragments were even more potent inhibitors than their natural, full-length sequences. 

“Unlike previous methods, we are not limited to identifying fragments in experimental structural data,” says Swanson. “The core strength of this work is the interplay between high-throughput experimental inhibition data and the predicted structural models: the experimental data guides us towards the fragments that are particularly interesting, while the structural models predicted by FragFold provide a specific, testable hypothesis for how the fragments function on a molecular level.”

Savinov is excited about the future of this approach and its myriad applications.

“By creating compact, genetically encodable binders, FragFold opens a wide range of possibilities to manipulate protein function,” Li agrees. “We can imagine delivering functionalized fragments that can modify native proteins, change their subcellular localization, and even reprogram them to create new tools for studying cell biology and treating diseases.” 

Kingdoms collide as bacteria and cells form captivating connections

Studying the pathogen R. parkeri, researchers discovered the first evidence of extensive and stable interkingdom contacts between a pathogen and a eukaryotic organelle.

Lillian Eden | Department of Biology
January 24, 2025

In biology textbooks, the endoplasmic reticulum is often portrayed as a distinct, compact organelle near the nucleus, and is commonly known to be responsible for protein trafficking and secretion. In reality, the ER is vast and dynamic, spread throughout the cell and able to establish contact and communication with and between other organelles. These membrane contacts regulate processes as diverse as fat metabolism, sugar metabolism, and immune responses.

Exploring how pathogens manipulate and hijack essential processes to promote their own life cycles can reveal much about fundamental cellular functions and provide insight into viable treatment options for understudied pathogens.

New research from the Lamason Lab in the Department of Biology at MIT recently published in the Journal of Cell Biology has shown that Rickettsia parkeri, a bacterial pathogen that lives freely in the cytosol, can interact in an extensive and stable way with the rough endoplasmic reticulum, forming previously unseen contacts with the organelle.

It’s the first known example of a direct interkingdom contact site between an intracellular bacterial pathogen and a eukaryotic membrane.

The Lamason Lab studies R. parkeri as a model for infection of the more virulent Rickettsia rickettsii. R. rickettsii, carried and transmitted by ticks, causes Rocky Mountain Spotted Fever. Left untreated, the infection can cause symptoms as severe as organ failure and death.

Rickettsia is difficult to study because it is an obligate pathogen, meaning it can only live and reproduce inside living cells, much like a virus. Researchers must get creative to parse out fundamental questions and molecular players in the R. parkeri life cycle, and much remains unclear about how R. parkeri spreads.

Detour to the junction

First author Yamilex Acevedo-Sánchez, a BSG-MSRP-Bio program alum and a graduate student at the time, stumbled across the ER and R. parkeri interactions while trying to observe Rickettsia reaching a cell junction.

The current model for Rickettsia infection involves R. parkeri spreading cell to cell by traveling to the specialized contact sites between cells and being engulfed by the neighboring cell in order to spread. Listeria monocytogenes, which the Lamason Lab also studies, uses actin tails to forcefully propel itself into a neighboring cell. By contrast, R. parkeri can form an actin tail, but loses it before reaching the cell junction. Somehow, R. parkeri is still able to spread to neighboring cells.

After an MIT seminar about the ER’s lesser-known functions, Acevedo-Sánchez developed a cell line to observe whether Rickettsia might be spreading to neighboring cells by hitching a ride on the ER to reach the cell junction.

Instead, she saw an unexpectedly high percentage of R. parkeri surrounded and enveloped by the ER, at a distance of about 55 nanometers. This distance is significant because membrane contacts for interorganelle communication in eukaryotic cells form connections from 10-80 nanometers wide. The researchers ruled out that what they saw was not an immune response, and the sections of the ER interacting with the R. parkeri were still connected to the wider network of the ER.

“I’m of the mind that if you want to learn new biology, just look at cells,” Acevedo-Sánchez says. “Manipulating the organelle that establishes contact with other organelles could be a great way for a pathogen to gain control during infection.”

The stable connections were unexpected because the ER is constantly breaking and reforming connections, lasting seconds or minutes. It was surprising to see the ER stably associating around the bacteria. As a cytosolic pathogen that exists freely in the cytosol of the cells it infects, it was also unexpected to see R. parkeri surrounded by a membrane at all.

Small margins

Acevedo-Sánchez collaborated with the Center for Nanoscale Systems at Harvard University to view her initial observations at higher resolution using focused ion beam scanning electron microscopy. FIB-SEM involves taking a sample of cells and blasting them with a focused ion beam in order to shave off a section of the block of cells. With each layer, a high-resolution image is taken. The result of this process is a stack of images.

From there, Acevedo-Sánchez marked what different areas of the images were — such as the mitochondria, Rickettsia, or the ER — and a program called ORS Dragonfly, a machine learning program, sorted through the thousand or so images to identify those categories. That information was then used to create 3D models of the samples.

Acevedo-Sánchez noted that less than 5 percent of R. parkeri formed connections with the ER — but small quantities of certain characteristics are known to be critical for R. parkeri infection. R. parkeri can exist in two states: motile, with an actin tail, and nonmotile, without it. In mutants unable to form actin tails, R. parkeri are unable to progress to adjacent cells — but in nonmutants, the percentage of R. parkeri that have tails starts at about 2 percent in early infection and never exceeds 15 percent at the height of it.

The ER only interacts with nonmotile R. parkeri, and those interactions increased 25-fold in mutants that couldn’t form tails.

Creating connections

Co-authors Acevedo-Sánchez, Patrick Woida, and Caroline Anderson also investigated possible ways the connections with the ER are mediated. VAP proteins, which mediate ER interactions with other organelles, are known to be co-opted by other pathogens during infection.

During infection by R. parkeri, VAP proteins were recruited to the bacteria; when VAP proteins were knocked out, the frequency of interactions between R. parkeri and the ER decreased, indicating R. parkeri may be taking advantage of these cellular mechanisms for its own purposes during infection.

Although Acevedo-Sánchez now works as a senior scientist at AbbVie, the Lamason Lab is continuing the work of exploring the molecular players that may be involved, how these interactions are mediated, and whether the contacts affect the host or bacteria’s life cycle.

Senior author and associate professor of biology Rebecca Lamason noted that these potential interactions are particularly interesting because bacteria and mitochondria are thought to have evolved from a common ancestor. The Lamason Lab has been exploring whether R. parkeri could form the same membrane contacts that mitochondria do, although they haven’t proven that yet. So far, R. parkeri is the only cytosolic pathogen that has been observed behaving this way.

“It’s not just bacteria accidentally bumping into the ER. These interactions are extremely stable. The ER is clearly extensively wrapping around the bacterium, and is still connected to the ER network,” Lamason says. “It seems like it has a purpose — what that purpose is remains a mystery.”

An abundant phytoplankton feeds a global network of marine microbes

New findings illuminate how Prochlorococcus’ nightly “cross-feeding” plays a role in regulating the ocean’s capacity to cycle and store carbon.

Jennifer Chu | MIT News
January 3, 2025

One of the hardest-working organisms in the ocean is the tiny, emerald-tinged Prochlorococcus marinus. These single-celled “picoplankton,” which are smaller than a human red blood cell, can be found in staggering numbers throughout the ocean’s surface waters, making Prochlorococcus the most abundant photosynthesizing organism on the planet. (Collectively, Prochlorococcus fix as much carbon as all the crops on land.) Scientists continue to find new ways that the little green microbe is involved in the ocean’s cycling and storage of carbon.

Now, MIT scientists have discovered a new ocean-regulating ability in the small but mighty microbes: cross-feeding of DNA building blocks. In a study appearing today in Science Advances, the team reports that Prochlorococcus shed these extra compounds into their surroundings, where they are then “cross-fed,” or taken up by other ocean organisms, either as nutrients, energy, or for regulating metabolism. Prochlorococcus’ rejects, then, are other microbes’ resources.

What’s more, this cross-feeding occurs on a regular cycle: Prochlorococcus tend to shed their molecular baggage at night, when enterprising microbes quickly consume the cast-offs. For a microbe called SAR11, the most abundant bacteria in the ocean, the researchers found that the nighttime snack acts as a relaxant of sorts, forcing the bacteria to slow down their metabolism and effectively recharge for the next day.

Through this cross-feeding interaction, Prochlorococcus could be helping many microbial communities to grow sustainably, simply by giving away what it doesn’t need. And they’re doing so in a way that could set the daily rhythms of microbes around the world.

“The relationship between the two most abundant groups of microbes in ocean ecosystems has intrigued oceanographers for years,” says co-author and MIT Institute Professor Sallie “Penny” Chisholm, who played a role in the discovery of Prochlorococcus in 1986. “Now we have a glimpse of the finely tuned choreography that contributes to their growth and stability across vast regions of the oceans.”

Given that Prochlorococcus and SAR11 suffuse the surface oceans, the team suspects that the exchange of molecules from one to the other could amount to one of the major cross-feeding relationships in the ocean, making it an important regulator of the ocean carbon cycle.

“By looking at the details and diversity of cross-feeding processes, we can start to unearth important forces that are shaping the carbon cycle,” says the study’s lead author, Rogier Braakman, a research scientist in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS).

Other MIT co-authors include Brandon Satinsky, Tyler O’Keefe, Shane Hogle, Jamie Becker, Robert Li, Keven Dooley, and Aldo Arellano, along with Krista Longnecker, Melissa Soule, and Elizabeth Kujawinski of Woods Hole Oceanographic Institution (WHOI).

Spotting castaways

Cross-feeding occurs throughout the microbial world, though the process has mainly been studied in close-knit communities. In the human gut, for instance, microbes are in close proximity and can easily exchange and benefit from shared resources.

By comparison, Prochlorococcus are free-floating microbes that are regularly tossed and mixed through the ocean’s surface layers. While scientists assume that the plankton are involved in some amount of cross-feeding, exactly how this occurs, and who would benefit, have historically been challenging to probe; any stuff that Prochlorococcus cast away would have vanishingly low concentrations,and be exceedingly difficult to measure.

But in work published in 2023, Braakman teamed up with scientists at WHOI, who pioneered ways to measure small organic compounds in seawater. In the lab, they grew various strains of Prochlorococcus under different conditions and characterized what the microbes released. They found that among the major “exudants,” or released molecules, were purines and pyridines, which are molecular building blocks of DNA. The molecules also happen to be nitrogen-rich — a fact that puzzled the team. Prochlorococcus are mainly found in ocean regions that are low in nitrogen, so it was assumed they’d want to retain any and all nitrogen-containing compounds they can. Why, then, were they instead throwing such compounds away?

Global symphony

In their new study, the researchers took a deep dive into the details of Prochlorococcus’ cross-feeding and how it influences various types of ocean microbes.

They set out to study how Prochlorococcus use purine and pyridine in the first place, before expelling the compounds into their surroundings. They compared published genomes of the microbes, looking for genes that encode purine and pyridine metabolism. Tracing the genes forward through the genomes, the team found that once the compounds are produced, they are used to make DNA and replicate the microbes’ genome. Any leftover purine and pyridine is recycled and used again, though a fraction of the stuff is ultimately released into the environment. Prochlorococcus appear to make the most of the compounds, then cast off what they can’t.

The team also looked to gene expression data and found that genes involved in recycling purine and pyrimidine peak several hours after the recognized peak in genome replication that occurs at dusk. The question then was: What could be benefiting from this nightly shedding?

For this, the team looked at the genomes of more than 300 heterotrophic microbes — organisms that consume organic carbon rather than making it themselves through photosynthesis. They suspected that such carbon-feeders could be likely consumers of Prochlorococcus’ organic rejects. They found most of the heterotrophs contained genes that take up either purine or pyridine, or in some cases, both, suggesting microbes have evolved along different paths in terms of how they cross-feed.

The group zeroed in on one purine-preferring microbe, SAR11, as it is the most abundant heterotrophic microbe in the ocean. When they then compared the genes across different strains of SAR11, they found that various types use purines for different purposes, from simply taking them up and using them intact to breaking them down for their energy, carbon, or nitrogen. What could explain the diversity in how the microbes were using Prochlorococcus’ cast-offs?

It turns out the local environment plays a big role. Braakman and his collaborators performed a metagenome analysis in which they compared the collectively sequenced genomes of all microbes in over 600 seawater samples from around the world, focusing on SAR11 bacteria. Metagenome sequences were collected alongside measurements of various environmental conditions and geographic locations in which they are found. This analysis showed that the bacteria gobble up purine for its nitrogen when the nitrogen in seawater is low, and for its carbon or energy when nitrogen is in surplus — revealing the selective pressures shaping these communities in different ocean regimes.

“The work here suggests that microbes in the ocean have developed relationships that advance their growth potential in ways we don’t expect,” says co-author Kujawinski.

Finally, the team carried out a simple experiment in the lab, to see if they could directly observe a mechanism by which purine acts on SAR11. They grew the bacteria in cultures, exposed them to various concentrations of purine, and unexpectedly found it causes them to slow down their normal metabolic activities and even growth. However, when the researchers put these same cells under environmentally stressful conditions, they continued growing strong and healthy cells, as if the metabolic pausing by purines helped prime them for growth, thereby avoiding the effects of the stress.

“When you think about the ocean, where you see this daily pulse of purines being released by Prochlorococcus, this provides a daily inhibition signal that could be causing a pause in SAR11 metabolism, so that the next day when the sun comes out, they are primed and ready,” Braakman says. “So we think Prochlorococcus is acting as a conductor in the daily symphony of ocean metabolism, and cross-feeding is creating a global synchronization among all these microbial cells.”

This work was supported, in part, by the Simons Foundation and the National Science Foundation.

Imperiali Lab News Brief: combining bioinformatics and biochemistry

Parsing endless possibilities

Lillian Eden | Department of Biology
December 11, 2024

New research from the Imperiali Lab in the Department of Biology at MIT combines bioinformatics and biochemistry to reveal critical players in assembling glycans, the large sugar molecules on bacterial cell surfaces responsible for behaviors such as evading immune responses and causing infections.

In most cases, single-celled organisms such as bacteria interact with their environment through complex chains of sugars known as glycans bound to lipids on their outer membranes. Glycans orchestrate biological responses and interactions, such as evading immune responses and causing infections. 

The first step in assembling most bacterial glycans is the addition of a sugar-phosphate group onto a lipid, which is catalyzed by phosphoglycosyl transferases (PGTs) on the inner membrane. This first sugar is then further built upon by other enzymes in subsequent steps in an assembly-line-like pathway. These critical biochemical processes are challenging to explore because the proteins involved in these processes are embedded in membranes, which makes them difficult to isolate and study. 

Although glycans are found in all living organisms, the sugar molecules that compose glycans are especially diverse in bacteria. There are over 30,000 known bacterial PGTs, and hundreds of sugars for them to act upon. 

Research recently published in PNAS from the Imperiali Lab in the Department of Biology at MIT uses a combination of bioinformatics and biochemistry to predict clusters of “like-minded” PGTs and verify which sugars they will use in the first step of glycan assembly. 

Defining the biochemical machinery for these assembly pathways could reveal new strategies for tackling antibiotic-resistant strains of bacteria. This comprehensive approach could also be used to develop and test inhibitors, halting the assembly pathway at this critical first step. 

Exploring Sequence Similarity

First author Theo Durand, an undergraduate student from Imperial College London who studied at MIT for a year, worked in the Imperiali Lab as part of a research placement. Durand was first tasked with determining which sugars some PGTs would use in the first step of glycan assembly, known as the sugar substrates of the PGTs. When initially those substrate-testing experiments didn’t work, Durand turned to the power of bioinformatics to develop predictive tools. 

Strategically exploring the sugar substrates for PGTs is challenging due to the sheer number of PGTs and the diversity of bacteria, each with its own assorted set of glycans and glycoconjugates. To tackle this problem, Durand deployed a tool called a Sequence Similarity Network (SSN), part of a computational toolkit developed by the Enzyme Function Initiative. 

According to senior author Barbara Imperiali, Class of 1922 Professor of Biology and Chemistry, an SSN provides a powerful way to analyze protein sequences through comparisons of the sequences of tens of thousands of proteins. In an optimized SSN, similar proteins cluster together, and, in the case of PGTs, proteins in the same cluster are likely to share the same sugar substrate. 

For example, a previously uncharacterized PGT that appears in a cluster of PGTs whose first sugar substrate is FucNAc4N would also be predicted to use FucNAc4N. The researchers could then test that prediction to verify the accuracy of the SSN. 

FucNAc4N is the sugar substrate for the PGT of Fusobacterium nucleatum (F. nucleatum), a bacterium that is normally only present in the oral cavity but is correlated with certain cancers and endometriosis, and Streptococcus pneumoniae, a bacterium that causes pneumonia. 

Adjusting the assay

The critical biochemical process of assembling glycans has historically been challenging to define, mainly because assembly is anchored to the interior side of the inner membrane of the bacterium. The purification process itself can be difficult, and the purified proteins don’t necessarily behave in the same manner once outside their native membrane environment.

To address this, the researchers modified a commercially available test to work with proteins still embedded in the membrane of the bacterium, thus saving them weeks of work to purify the proteins. They could then determine the substrate for the PGT by measuring whether there was activity. This first step in glycan assembly is chemically unique, and the test measures one of the reaction products. 

For PGTs whose substrate was unknown, Durand did a deep dive into the literature to find new substrates to test. FucNAc4N, the first sugar substrate for F. nucleatum, was, in fact, Durand’s favorite sugar – he found it in the literature and reached out to a former Imperiali Lab postdoc for the instructions and materials to make it. 

“I ended up down a rabbit hole where I was excited every time I found a new, weird sugar,” Durand recalls with a laugh. “These bacteria are doing a bunch of really complicated things and any tools to help us understand what is actually happening is useful.” 

Exploring inhibitors

Imperiali noted that this research both represents a huge step forward in our understanding of bacterial PGTs and their substrates and presents a pipeline for further exploration. She’s hoping to create a searchable database where other researchers can seed their own sequences into the SSN for their organisms of interest. 

This pipeline could also reveal antibiotic targets in bacteria. For example, she says, the team is using this approach to explore inhibitor development. 

The Imperiali lab worked with Karen Allen, a professor of Chemistry at Boston University, and graduate student Roxanne Siuda to test inhibitors, including ones for F. nucleatum, the bacterium correlated with certain cancers and endometriosis whose first sugar substrate is FucNAc4N. They are also hoping to obtain structures of inhibitors bound to the PGT to enable structure-guided optimization.

“We were able to, using the network, discover the substrate for a PGT, verify the substrate, use it in a screen, and test an inhibitor,” Imperiali says. “This is bioinformatics, biochemistry, and probe development all bundled together, and represents the best of functional genomics.”

Sauer & Davis Lab News Brief: structures of molecular woodchippers reveal mechanism for versatility

Rest in pieces: deconstructing polypeptide degradation machinery

Lillian Eden | Department of Biology
November 12, 2024

Research from the Sauer and Davis Labs in the Department of Biology at MIT shows that conformational changes contribute to the specificity of “molecular woodchippers” 

Degradation is a crucial process for maintaining protein homeostasis by culling excess or damaged proteins whose components can then be recycled. It is also a highly regulated process—for good reason. A cell could potentially waste many resources if the degradation machinery destroys proteins it shouldn’t. 

One of the major pathways for protein degradation in bacteria and eukaryotic mitochondria involves a molecular machine called ClpXP. ClpXP is made up of two components: a star-shaped structure made up of six subunits called ClpX that engages and unfolds proteins tagged for degradation, and an associated barrel-shaped enzyme, called ClpP, that chemically breaks up proteins into small pieces called peptides. 

ClpXP is incredibly adaptable and is often compared to a woodchipper — able to take in materials and spit out their broken-down components. Thanks to biochemical experiments, this molecular degradation machine is known to be able to break down hundreds of different proteins in the cell regardless of physical or chemical properties such as size, shape, or charge. ClpX uses energy from ATP hydrolysis to unfold proteins before they are threaded through its central channel, referred to as the axial channel, and into the degradation chamber of ClpP.

In three papers, one in PNAS and two in Nature Communications, researchers from the Department of Biology at MIT have expanded our understanding of how this molecular machinery engages with, unfolds, and degrades proteins — and how that machinery refrains, by design, from unfolding proteins not tagged for degradation. 

Alireza Ghanbarpour, until recently a postdoc in the Sauer Lab and Davis Lab and first author on all three papers, began with a simple question: given the vast repertoire of potential substrates — that is, proteins to be degraded — how is ClpXP so specific?

Ghanbarpour — now an assistant professor in the Department of Biochemistry and Molecular Biology at Washington University School of Medicine in St. Louis — found that the answer to this question lies in conformational changes in the molecular machine as it engages with an ill-fated protein. 

Reverse Engineering using Structural Insights

Ghanbarpour approached the question of ClpXP’s versatility by characterizing conformational changes of the molecular machine using a technique called cryogenic electron microscopy. In cryo-EM, sample particles are frozen in solution, and images are collected; algorithms then create 3D renderings from the 2D images.

“It’s really useful to generate different structures in different conditions and then put them together until you know how a machine works,” he says. “I love structural biology, and these molecular machines make fascinating targets for structural work and biochemistry. Their structural plasticity and precise functions offer exciting opportunities to understand how nature leverages enzyme conformations to generate novel functions and tightly regulate protein degradation within the cell.”

Inside the cell, these proteases do not work alone but instead work together with “adaptor” proteins, which can promote — or inhibit — degradation by ClpXP. One of the adaptor proteins that promotes degradation by ClpXP is SspB. 

In E. coli and most other bacteria, ClpXP and SspB interact with a tag called ssrA that is added to incomplete proteins when their biosynthesis on ribosomes stalls. 

The tagging process frees up the ribosome to make more proteins, but creates a problem: incomplete proteins are prone to aggregation, which could be detrimental to cellular health and can lead to disease. By interacting with the degradation tag, ClpXP and SspB help to ensure the degradation of these incomplete proteins. Understanding this process and how it may go awry may open therapeutic avenues in the future.

“It wasn’t clear how certain adapters were interacting with the substrate and the molecular machines during substrate delivery,” Ghanbarpour notes. “My recent structure reveals that the adapter engages with the enzyme, reaching deep into the axial channel to deliver the substrate.” 

Ghanbarpour and colleagues showed that ClpX engages with both the SspB adaptor and the ssrA degradation tag of an ill-fated protein at the same time. Surprisingly, they also found that this interaction occurs while the upper part of the axial channel through ClpX is closed — in fact, the closed channel allows ClpX to contact both the tag and the adaptor simultaneously.

This result was surprising, according to senior author and Salvador E. Luria Professor of Biology Robert Sauer, whose lab has been working on understanding this molecular machine for more than two decades: it was unclear whether the channel through ClpX closes in response to a substrate interaction, or if the channel is always closed until it opens to pass an unfolded protein down to ClpP to be degraded.

Preventing Rogue Degradation

Throughout this project, Ghanbarpour was co-advised by structural biologist and Associate Professor of Biology Joey Davis and collaborated with members of the Davis Lab to better understand the conformational changes that allow these molecular machines to function. Using a cryo-EM analysis approach developed in the Davis lab called CryoDRGN, the researchers showed that there is an equilibrium between ClpXP in the open and closed states: it’s usually closed but is open in about 10% of the particles in their samples. 

The closed state is almost identical to the conformation ClpXP assumes when it is engaged with an ssrA-tagged substrate and the SspB adaptor. 

To better understand the biological significance of this equilibrium, Ghanbarpour created a mutant of ClpXP that is always in the open position. Compared to normal ClpXP, the mutant degraded some proteins lacking obvious degradation tags faster but degraded ssrA-tagged proteins more slowly. 

According to Ghanbarpour, these results indicate that the closed channel improves ClpXP’s ability to efficiently engage tagged proteins meant to be degraded, whereas the open channel allows more “promiscuous” degradation. 

Pausing the Process

The next question Ghanbarpour wanted to answer was what this molecular machine looks like while engaged with a protein it is attempting to unfold. To do that, he created a substrate with a highly stable protein attached to the degradation tag that is initially pulled into ClpX, but then dramatically slows protein unfolding and degradation.

In the structures where the degradation process stalls, Ghanbarpour found that the degradation tag was pulled far into the molecular machine—through ClpX and into ClpP—and the folded protein part of the substrate was pulled tightly against the axial channel of ClpX. 

The opening of the axial channel, called the axial pore, is made up of looping protein structures called RKH loops. These flexible loops were found to play roles both in recognizing the ssrA degradation tag and in how substrates or the SspB adaptor interact with or are pulled against the channel during degradation. 

The flexibility of these RKH loops allows ClpX to interact with a large number of different proteins and adapters, and these results clarify some previous biochemical and mutational studies of interactions between the substrate and ClpXP. 

Although Ghanbarpour’s recent work focused on just one adaptor and degradation tag, he noted there are many more targets — ClpXP is something akin to a Swiss army knife for breaking down polypeptide chains. 

The way those other substrates interact with ClpXP could differ from the structures solved with the SspB adaptor and ssrA tag. It also stands to reason that the way ClpXP reacts to each substrate may be unique. For example, given that ClpX is occasionally in an open state, some substrates may engage with ClpXP only while it’s in an open conformation. 

In his new position at Washington University, Ghanbarpour intends to continue exploring how ClpXP and other molecular machines locate their target substrates and interact with adaptors, shedding light on how cells regulate protein degradation and maintain protein homeostasis.

The structures Ghanbarpour solved involved free-floating protein degradation machinery, but membrane-bound degradation machinery also exists. The membrane-bound version’s structure and conformational adaptions potentially differ from the structures Ghanbarpour found in his previous three papers. Indeed, in a recent preprint, Ghanbarpour worked on the cryo-EM structure of a nautilus shell-shaped protein assembly that seems to control membrane-bound degradation machinery. This assembly plays a critical role in regulating protein degradation within the bacterial inner membrane.

“The function of these proteases goes beyond simply degrading damaged proteins. They also target transcription factors, regulatory proteins, and proteins that don’t exist in normal conditions,” he says. “My new lab is particularly interested in understanding how cells use these proteases and their accessory adaptors, both under normal and stress conditions, to reshape the proteome and support recovery from cellular distress.”

Laub Lab News Brief: anti-viral defense system in bacteria modifies mRNA

Killing the messenger

Lillian Eden | Department of Biology
October 23, 2024

Newly characterized anti-viral defense system in bacteria aborts infection through novel mechanism by chemically modifying mRNA.

Like humans and other complex multicellular organisms, single-celled bacteria can fall ill and fight off viral infections. A bacterial virus is known as a bacteriophage, or, more simply, a phage, which is one of the most ubiquitous life forms on Earth. Phages and bacteria are engaged in a constant battle, the virus attempting to circumvent the bacteria’s defenses, and the bacteria racing to find new ways to protect itself.

These anti-phage defense systems are carefully controlled and prudently managed — dormant but always poised to strike. 

New research recently published in Nature from the Laub Lab in the Department of Biology at MIT has characterized an anti-phage defense system in bacteria known as CmdTAC. CmdTAC prevents viral infection by altering mRNA, the single-stranded genetic code used to produce proteins, of both the host and the virus.  

This defense system detects phage infection at a stage when the viral phage has already commandeered the host’s machinery for its own purposes. In the face of annihilation, the ill-fated bacterium activates a defense system that will halt translation, preventing the creation of new proteins and aborting the infection — but dooming itself in the process. 

“When bacteria are in a group, they’re kind of like a multicellular organism that is not connected to one another. It’s an evolutionarily beneficial strategy for one cell to kill itself to save another identical cell,” says Christopher Vassallo, a postdoc and co-author of the study. “You could say it’s like self-sacrifice: one cell dies to protect the other cells.” 

The enzyme responsible for altering the mRNA is called an ADP-ribosyltransferase.  Researchers have characterized hundreds of these enzymes — although only a few are known to target DNA or other types of RNA, all but a handful target proteins. This is the first time these enzymes have been characterized targeting mRNA within cells.

Expanding understanding of anti-phage defense

Co-first author and graduate student Chris Doering noted that it is only within the last decade or so that researchers have begun to appreciate the breadth of diversity and complexity of anti-phage defense systems. For example, CRISPR gene editing, a technique used in everything from medicine to agriculture, is rooted in research on the bacterial CRISPR-Cas9 anti-phage defense system. 

CmdTAC is a subset of a widespread anti-phage defense mechanism called a toxin-antitoxin system. A TA system is just that: a toxin capable of killing or altering the cell’s processes rendered inert by an associated antitoxin. 

Although these TA systems can be identified — if the toxin is expressed by itself, it kills or inhibits the growth of the cell; if the toxin and antitoxin are expressed together, the toxin is neutralized — characterizing the cascade of circumstances that activates these systems requires extensive effort. In recent years, however, many TA systems have been shown to serve as anti-phage defenses. 

Two general questions need to be answered to understand a viral defense system: how do bacteria detect an infection, and how do they respond?

Detecting infection

CmdTAC is a TA system with an additional element, and the three components generally exist in a stable complex: the toxin CmdT, the antitoxin CmdA, and an additional component that mediates the system, the chaperone CmdC. 

If the phage’s protective capsid protein is present, CmdC disassociates from CmdT and CmdA and interacts with the phage capsid protein instead. In the model outlined in the paper, the chaperone CmdC is, therefore, the sensor of the system, responsible for recognizing when an infection is occurring. Structural proteins, such as the capsid that protects the phage genome, are a common trigger because they’re abundant and essential to the phage.

The uncoupling of CmdC leads to the degradation of the neutralizing antitoxin CmdA, which releases the toxin CmdT to do its lethal work.

Toxicity on the loose

Guided by computational tools, the researchers knew that CmdT was likely an ADP-ribosyltransferase due to its similarities to other such enzymes. As the name suggests, the enzyme transfers an ADP ribose onto its target.

To determine how CmdT was altering mRNA, the researchers tested a mix of short sequences of single-stranded RNA to see if the enzyme was drawn to any sequences or positions in particular. RNA has four bases: A, U, G, and C, and the evidence points to the enzyme recognizing GA sequences. 

The CmdT modification of GA sequences in mRNA blocks its translation. The cessation of creating new proteins aborts the infection, preventing the phage from spreading beyond the host to infect other bacteria. 

“Not only is it a new type of bacterial immune system, but the enzyme involved does something that’s never been seen before: the ADP-ribsolyation of mRNA,” Vassallo says. 

Although the paper outlines the broad strokes of the anti-phage defense system, there’s more to learn: it’s unclear how CmdC interacts with the capsid protein, and how the chemical modification of GA sequences prevents translation. 

Beyond Bacteria

While exploring anti-phage defense aligns with the Laub Lab’s overall goal of understanding how bacteria function and evolve, these results may have broader implications beyond bacteria.

Senior author Michael Laub, Salvador E. Luria Professor and HHMI Investigator, says the ADP-ribosyltransferase has homologs in eukaryotes, including human cells. They are not well studied, and not currently among the Laub Lab’s research topics, but they are known to be up-regulated in response to viral infection. 

“There are so many different — and cool — mechanisms by which organisms defend themselves against viral infection,” Laub says. “The notion that there may be some commonality between how bacteria defend themselves and how humans defend themselves is a tantalizing possibility.”