Research Area: Biochemistry, Biophysics, and Structural Biology

MIT biologists discover a new type of control over RNA splicing

They identified proteins that influence splicing of about half of all human introns, allowing for more complex types of gene regulation.

Anne Trafton | MIT News
February 20, 2025

RNA splicing is a cellular process that is critical for gene expression. After genes are copied from DNA into messenger RNA, portions of the RNA that don’t code for proteins, called introns, are cut out and the coding portions are spliced back together.

This process is controlled by a large protein-RNA complex called the spliceosome. MIT biologists have now discovered a new layer of regulation that helps to determine which sites on the messenger RNA molecule the spliceosome will target.

The research team discovered that this type of regulation, which appears to influence the expression of about half of all human genes, is found throughout the animal kingdom, as well as in plants. The findings suggest that the control of RNA splicing, a process that is fundamental to gene expression, is more complex than previously known.

“Splicing in more complex organisms, like humans, is more complicated than it is in some model organisms like yeast, even though it’s a very conserved molecular process. There are bells and whistles on the human spliceosome that allow it to process specific introns more efficiently. One of the advantages of a system like this may be that it allows more complex types of gene regulation,” says Connor Kenny, an MIT graduate student and the lead author of the study.

Christopher Burge, the Uncas and Helen Whitaker Professor of Biology at MIT, is the senior author of the study, which appears today in Nature Communications.

Building proteins

RNA splicing, a process discovered in the late 1970s, allows cells to precisely control the content of the mRNA transcripts that carry the instructions for building proteins.

Each mRNA transcript contains coding regions, known as exons, and noncoding regions, known as introns. They also include sites that act as signals for where splicing should occur, allowing the cell to assemble the correct sequence for a desired protein. This process enables a single gene to produce multiple proteins; over evolutionary timescales, splicing can also change the size and content of genes and proteins, when different exons become included or excluded.

The spliceosome, which forms on introns, is composed of proteins and noncoding RNAs called small nuclear RNAs (snRNAs). In the first step of spliceosome assembly, an snRNA molecule known as U1 snRNA binds to the 5’ splice site at the beginning of the intron. Until now, it had been thought that the binding strength between the 5’ splice site and the U1 snRNA was the most important determinant of whether an intron would be spliced out of the mRNA transcript.

In the new study, the MIT team discovered that a family of proteins called LUC7 also helps to determine whether splicing will occur, but only for a subset of introns — in human cells, up to 50 percent.

Before this study, it was known that LUC7 proteins associate with U1 snRNA, but the exact function wasn’t clear. There are three different LUC7 proteins in human cells, and Kenny’s experiments revealed that two of these proteins interact specifically with one type of 5’ splice site, which the researchers called “right-handed.” A third human LUC7 protein interacts with a different type, which the researchers call “left-handed.”

The researchers found that about half of human introns contain a right- or left-handed site, while the other half do not appear to be controlled by interaction with LUC7 proteins. This type of control appears to add another layer of regulation that helps remove specific introns more efficiently, the researchers say.

“The paper shows that these two different 5’ splice site subclasses exist and can be regulated independently of one another,” Kenny says. “Some of these core splicing processes are actually more complex than we previously appreciated, which warrants more careful examination of what we believe to be true about these highly conserved molecular processes.”

“Complex splicing machinery”

Previous work has shown that mutation or deletion of one of the LUC7 proteins that bind to right-handed splice sites is linked to blood cancers, including about 10 percent of acute myeloid leukemias (AMLs). In this study, the researchers found that AMLs that lost a copy of the LUC7L2 gene have inefficient splicing of right-handed splice sites. These cancers also developed the same type of altered metabolism seen in earlier work.

“Understanding how the loss of this LUC7 protein in some AMLs alters splicing could help in the design of therapies that exploit these splicing differences to treat AML,” Burge says. “There are also small molecule drugs for other diseases such as spinal muscular atrophy that stabilize the interaction between U1 snRNA and specific 5’ splice sites. So the knowledge that particular LUC7 proteins influence these interactions at specific splice sites could aid in improving the specificity of this class of small molecules.”

Working with a lab led by Sascha Laubinger, a professor at Martin Luther University Halle-Wittenberg, the researchers found that introns in plants also have right- and left-handed 5’ splice sites that are regulated by Luc7 proteins.

The researchers’ analysis suggests that this type of splicing arose in a common ancestor of plants, animals, and fungi, but it was lost from fungi soon after they diverged from plants and animals.

“A lot what we know about how splicing works and what are the core components actually comes from relatively old yeast genetics work,” Kenny says. “What we see is that humans and plants tend to have more complex splicing machinery, with additional components that can regulate different introns independently.”

The researchers now plan to further analyze the structures formed by the interactions of Luc7 proteins with mRNA and the rest of the spliceosome, which could help them figure out in more detail how different forms of Luc7 bind to different 5’ splice sites.

The research was funded by the U.S. National Institutes of Health and the German Research Foundation.

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.”

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.”

PNAS Profile: Catherine Drennan

Structural intuitions lead to structural insights

Jennifer Viegas | PNAS
November 8, 2024

HHMI Investigator and Professor of Biology and Chemistry Catherine Drennan has spent a distinguished career addressing challenging and wide-ranging structural biology problems.

Catherine Drennan, a Howard Hughes Medical Institute investigator and professor and a professor of biology and chemistry at the Massachusetts Institute of Technology (MIT), has spent a distinguished career addressing challenging and wide-ranging structural biology problems. These include her discovery, while she was a graduate student, of the structure of vitamin B12 bound to protein and her recent determination at atomic resolution of the structure of an active ribonucleotide reductase (RNR) with water molecules, findings reported in her Inaugural Article (IA) (1).

Drennan, who was elected to the National Academy of Sciences in 2023, has uncovered the form and function of metalloenzymes that use metal cofactors to catalyze chemical reactions involving free radicals. Metalloenzymes are of broad human health and environmental interest; some are promising antibiotic and cancer drug targets, whereas others hold the potential for bioremediation efforts, such as converting carbon dioxide into biofuels.

Family of Accomplished Scientists

Drennan was raised in New York City by her father, an obstetrician–gynecologist, and her mother, an anthropologist. Her father was born in Germany and attended medical school at the University of Hamburg. Harboring antifascist leanings, he fled Germany in 1933. He completed medical training in Geneva, Switzerland, before obtaining political asylum in 1940 in the United States, where he became one of the first doctors to practice the Lamaze Method of natural childbirth.
Drennan’s mother attended Antioch College, where she was a student of civil engineer Arthur Ernest Morgan, who was appointed in 1948 to India’s first University Education Commission. She accompanied Morgan to India and served as his administrative assistant before earning her doctorate in anthropology at Cornell University.

“Both my parents were endlessly curious,” says Drennan. “My father was fascinated by the molecular basis of medicine, and my mother was fascinated by people and instilled in me her love for storytelling, teaching, and mentoring.”

Diagnosed with Dyslexia

Although she was an attentive student, Drennan did not learn to read until her second time through sixth grade. “When I finally learned how to read, it was by memorizing the shapes of words,” says Drennan, who was diagnosed with dyslexia when she was in first grade. “Over time I became very good at shape recognition. I am not disabled; I am differently abled. The skill set that I developed to compensate for my dyslexia has made me a world-class structural biologist. We all have strengths and weaknesses, and my ‘weakness’ is also my superpower.”
She was accepted to Vassar College, where she earned a bachelor’s degree in chemistry in 1985. “Miriam Rossi was my undergraduate chemistry research advisor, and she believed in me before I believed in me,” Drennan says. Upon Rossi’s advice, Drennan pursued a doctorate, but not before teaching high-school science and drama at Scattergood Friends School in Iowa.
Following three years of high-school teaching, Drennan pursued graduate studies at the University of Michigan, Ann Arbor, where she earned a PhD in 1995, served as a research fellow from 1995 to 1996, and was mentored by biochemists Martha Ludwig and Rowena Matthews. “They treated me as a colleague, allowing me to see myself as a scientist of value,” Drennan says. “I learned so much from these two incredible scientists. They are, and always will be, my heroes.”

Structure of Vitamin B12 Bound to Protein

With Ludwig et al., Drennan determined the structure of cobalamin (vitamin B12) bound to protein (2). This crystal structure revealed how the protein modulates the reactivity of the B12 cofactor to enable its critical roles in metabolism.
From 1996 to 1999, Drennan did a postdoctoral stint at the California Institute of Technology, under the mentorship of structural biologist Douglas Rees. “Doug taught by example that one does not have to be cutthroat to succeed in the competitive area of structural biology,” she says. “He has continued to mentor me throughout my career, helping me through challenging times.”
Another important mentor was chemist JoAnne Stubbe, a leader in the study of RNRs who recruited Drennan to MIT in 1999 as an assistant professor of chemistry and has been her collaborator for the past 25 years. Drennan says, “Her passion for scientific discovery is unmatched and has inspired me to keep digging to try to understand, at the most fundamental level, how ribonucleotide reductase works.” Drennan advanced to an associate professorship at MIT in 2004 and a full professorship in 2006.

Revealing Metalloenzyme Form and Function

Drennan’s group continues to study B12 and has provided numerous snapshots of cobalamin-dependent proteins and protein complexes. The findings have changed what is known about B12 functions and mechanisms. Using X-ray crystallography, the researchers unveiled a protein complex capable of methyl transfer from folate to B12 (3). They obtained snapshots of the biological process involved in loading B12 into an enzyme (4) and provided structural data on how B12 can be repurposed from enzyme cofactor to light sensor (5).
Drennan has also worked on uncovering the structures of enzymes containing radical S-adenosylmethionine (SAM) cofactors. Drennan and colleagues revealed an X-ray structure of a radical SAM enzyme (6), helping to establish the “core” fold for an enzyme superfamily that has over 100,000 members. Her group further elucidated structures of SAM family members with functions including posttranslational modification (7), antibiotic and antiviral compound biosynthesis (8, 9), and vitamin biosynthesis (6, 10).
Mononuclear nonheme iron enzymes are also of interest to Drennan. The cofactor is simple, but the reactions catalyzed are complex. Her group reported the structure of a nonheme iron halogenase, showing that the halogen binds directly to the catalytic iron (11). Drennan says, “This was a complete surprise that required new mechanistic proposals to be written.”

“Oceanic Methane Paradox”

Early in her independent career, Drennan determined one of the first structures of a nickel-iron-sulfur-dependent carbon monoxide dehydrogenase (CODH), which plays an important role in the global carbon cycle (12). The structure, along with that of an associated enzyme complex (13), provided a series of snapshots of the multiple metal ion centers underlying the ability of certain microbes to live off hydrogen gas and carbon dioxide in a process known as acetogenesis. More recently, they investigated the molecular basis by which the activity of CODH enzymes can be restored after oxygen exposure (14), a discovery with implications for the industrial use of CODHs.
Drennan and her team have also studied the organic compound methylphosphonate that was proposed as a source of methane from the aerobic upper ocean; the biological source was long a mystery. When a methylphosphonate synthase was discovered by chemical biologist Wilfred van der Donk and coworkers, part of the mystery was solved but the gene for this enzyme did not appear to be widespread. When Drennan and colleagues solved the structure of a methylphosphonate synthase; however, they discovered a sequence motif showing that the gene was, in fact, abundant in microbes that inhabit the upper ocean (15). This seminal finding is credited with resolving the oceanic methane paradox.

Radical-Based Chemistry in Ribonucleotide Reductases

Human RNR is an established chemotherapeutic target, and bacterial RNRs hold promise as antibiotic targets. So Drennan and her team have a longstanding interest in uncovering the mechanisms of RNRs. In 2002, her lab determined the structure of a B12-dependent RNR, which showed how cobalamin could be used to initiate radical chemistry (16). Nearly a decade later, Drennan’s team revealed how high levels of the nucleotide deoxyadenosine triphosphate (dATP) down-regulate RNR activity (17, 18). They subsequently provided structures showing the molecular basis of allosteric specificity, which maintains the proper ratios of RNA to DNA building blocks (19), and demonstrated the importance of RNR activity regulation (20).
An atomic-resolution structure of any RNR in an active state had been elusive for many years. Drennan and her team achieved the feat in 2020 when they trapped the active state of Escherichia coli RNR and determined its structure by cryoelectron microscopy (21). However, the resolution of the structure was too low for the visualization of water molecules believed to be critical in the radical transfer pathway.
In her IA, Drennan (1) describes how her team resolved the problem, presenting the structure of an active RNR at atomic resolution allowing for the visualization of water molecules. She explains, “This time, instead of using unnatural amino acids to trap the structure, we used a mechanism-based inhibitor. It was a very long road to get to these data, but it was worth the wait.”

“Superheroes of the Cell”

For her achievements, Drennan has received MIT’s Everett Moore Baker Memorial Award for Excellence in Undergraduate Teaching (2005, 2024), the Dorothy Crowfoot Hodgkin Award from The Protein Society (2020), and the William C. Rose Award from the American Society for Biochemistry and Molecular Biology (2023), among other honors. She has mentored nearly 100 undergraduates and dozens of graduate students and postdoctoral associates, many of whom are from underrepresented minority groups or disadvantaged backgrounds. She considers her students extended family members and takes pride in their accomplishments.
She and her team continue to work on RNR using the tools of structural biology. She says, “We want to obtain a deeper level of understanding of the human RNR, which is a cancer drug target. We also want to identify differences between the human enzyme and bacterial RNRs, differences that could be exploited in the development of new antibiotics.”
Beyond these efforts, Drennan’s overall goal is to understand how enzymes control radical species to enable challenging chemical reactions without damaging themselves or their cellular environment. “Radical enzymes are like the Avengers, powerful but with a high potential for collateral damage,” she explains. “I am fascinated by how nature catalyzes the most challenging of chemical reactions. The enzymes that do this work are the superheroes of the cell and I want to know their secrets.”
1.
D. E. Westmoreland et al., 2.6-Å resolution cryo-EM structure of a class Ia ribonucleotide reductase trapped with mechanism-based inhibitor N3CDP. Proc. Natl. Acad. Sci. U.S.A. 121, e2417157121 (2024). Crossref. PubMed.
2.
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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.”

An elegant switch regulates production of protein variants during cell division

Cells make variants of thousands of proteins. These variants are not produced indiscriminately, but rather through precise regulatory mechanisms that can meet rapidly changing needs of the cell according to new research from the Cheeseman Lab.

Greta Friar | Whitehead Institute
October 18, 2024

Our cells contain thousands of proteins that have gone largely undetected and unstudied until recent years: these are variants of known proteins, which cells can make when their protein-building machinery interacts differently with the same stretch of genetic code. These protein variants have typically been overlooked as occasional accidents of gene expression, but researchers including Whitehead Institute Member Iain Cheeseman are discovering that they are actually abundant and can play important roles in cell functions. Researchers in Cheeseman’s lab are studying individual protein variants to learn more about them and their roles in health and disease, but they also wanted to understand broader patterns of protein variant production: how do cells control when to make one variant of a protein versus another, and what are the consequences of such switches?

Cheeseman, who is also a professor of biology at the Massachusetts Institute of Technology, and graduate student in his lab Jimmy Ly have now identified how cells switch to a different pattern of protein variant production during mitosis, or cell division. In research published in the journal Nature on October 23, they show that this broad regulatory switch helps cells survive paused cell divisions that can sometimes occur in healthy humans or be triggered by certain chemotherapy treatments. The work confirms that cells make variants of thousands of proteins, and also demonstrates that cells do not do so indiscriminately. Rather, cells use precise regulatory mechanisms to switch between different patterns of protein variant production, in order to rapidly tailor the proteins available to fit the changing needs of the cell.

A plethora of hidden proteins

Hw can our cells contain unknown proteins? In high school biology classes, students learn the rule that each gene codes for exactly one protein, such that if you know an organism’s genetic code, you should know every protein it can make. In fact, there are instead many genes that code for multiple proteins. For a protein to be made, first the genetic code for it is copied from DNA into a messenger RNA (mRNA). Then, a ribosome, the cellular machine that follows the instructions in genetic code to build a protein, locates the coding sequence within the mRNA by scanning for the start codon, a sequence of the three bases A, U, and G – bases are the chemical building blocks of RNA, abbreviated as A, U, C, and G. The ribosome recognizes the AUG start codon as the place to begin following instructions, and builds a protein based on the genetic sequence from there through to another trio of bases called a stop codon. However, one way that different versions of a protein can be produced is that a ribosome may begin reading the instructions from multiple different starting points.

Sometimes, a ribosome may miss the first AUG start codon and skip ahead to another AUG somewhere in the middle of the gene’s code, creating a truncated version of the protein. Sometimes, a ribosome may treat a similar trio of bases, such as CUG or GUG, as a start codon. This can cause it to begin earlier, creating a protein based on an extended genetic sequence. These possibilities mean that cells contain thousands more different proteins, or variants of proteins, than are represented by the dogma of one gene, one protein.

In order to understand protein variant production, the researchers—in collaboration with researchers from Whitehead Institute Member David Bartel’s lab–used a method that let them carefully track ribosomes to compare which start sites ribosomes tended to use. They looked at start site selection during mitosis versus during the rest of the cell cycle and found that a dramatic shift in use occurred for thousands of start sites. Specifically, the researchers found that during mitosis, ribosome scanning becomes more stringent. The ribosome will only begin making proteins at AUG sequences, and even then, only at AUGs that have preferable sequences of bases surrounding them—known as a strong Kozak context. This increased selectivity does not always lead to the familiar version of the protein being made during mitosis; sometimes the first AUG start codon has a weak Kozak context, so a truncated protein gets made from an AUG start codon with a stronger Kozak context that lies within the gene.

“Coming into this project, we knew very little about protein production during mitosis—for a long time, people didn’t think much protein production happened in mitosis at all,” Ly says. “It was satisfying to show not only that it is occurring, but that there’s a shift in which proteins are being made—and that this shift is important for cellular viability.”

How cells switch between protein variant programs

The researchers next identified how the switch to increased stringency is initiated during mitosis. They discovered that the key player is a protein called eIF1, which is one of many partners that can pair with ribosomes to help them select their start site. In particular, increased eIF1 pairing with ribosomes causes the ribosomes to be more stringent in their start codon selection, inhibiting the usage of non-AUG initiation sites or sites with weak Kozak contexts.

During mitosis, ribosome pairing with eIF1 increases sharply, leading to the shift in stringency. This change in pairing rate during mitosis puzzled the researchers: ribosomes and their partners, including eIF1, all typically reside together in the main body of the cell—where ribosomes make proteins—so they should be able to pair freely at any time. The researchers looked for other molecules in the same location that could be altering how ribosomes and eIF1 interact during different parts of the cell cycle, but they couldn’t find anything. Eventually, the researchers realized that the answer to the puzzle lay in a separate location: the nucleus.

They found that cells maintain a large pool of eIF1 inside of the nucleus, locked away from the ribosomes. Then, during cell division, the wall of the nucleus dissolves, mixing its contents with the rest of the cell. This is necessary for the dividing cell to divvy up its DNA, but it also releases the pool of eIF1 to pair with ribosomes, increasing stringency. At the end of mitosis, the nucleus reforms and eIF1 is re-incorporated into the nucleus of each of the two daughter cells, and the cells return to a less stringent program.

“The explanation for increased interaction between eIF1 and ribosomes during mitosis had really stumped us, and so when I saw eIF1 localizing to the nucleus, that was a really exciting ‘aha’ moment,” Ly says. “Discovering this mechanism of nuclear release during mitosis was unexpected, and it’s interesting to think about how else cells might be using it.”

Consequences of increased stringency for the cell

Once the researchers understood the how, they then wanted to understand the why? What they discovered is that when cells have no nuclear pool of eIF1, and so no change in stringency during mitosis, they are more likely to die during mitosis. In particular, these cells fare poorly during mitotic arrest, a state in which cells get stuck in mitosis for hours or even days–much longer than typical mitosis. Arrest occurs when cells detect a possible cell division error and so halt their division until the error is corrected or the cell dies.

One effect of increased stringency during mitosis is related to mitochondria, which are required for energy production in many cell types and are therefore required for maintaining viability. Cells stuck in mitotic arrest need energy to keep them going through this unexpected delay. The researchers found that increased stringency during mitosis led to an increase in the production of important mitochondrial proteins, boosting the cells’ energy supply to get them through arrest.

Increased stringency also gives cells the tools they need to escape arrest, even if they haven’t fixed the error that caused them to pause division. In a Nature paper in 2023, Cheeseman and then-postdoc in his lab Mary-Jane Tsang showed that when cells build up enough of the truncated version of a protein called CDC20, they can escape arrest. Ly’s work adds to this story by showing that the nuclear release of eIF1 increases stringency, leading to more production of truncated CDC20 during mitosis, which explains how cells build up enough of this protein variant during mitosis to trigger their escape. These findings may have important potential implications for some cancer chemotherapy strategies.

Some chemotherapies work by trapping cancer cells in mitotic arrest until they die. Cheeseman, Tsang, and Ly’s work collectively shows that when cancer cells lack sufficient truncated CDC20—as can occur in the absence of nuclear eIF1—the cells cannot escape arrest and so are killed off by these chemotherapies at higher rates. These results could be used to improve the efficacy of antimitotic chemotherapy drugs.

The switch in protein variant production that the researchers found affects thousands of proteins. These newly identified protein variants serve as a foundation for many future projects in the lab.

As the researchers continue to examine the consequences of this switch to stringency during mitosis, they are also searching for other cases in which cells regulate protein variant production outside of mitosis. For example, the researchers are interested in how this switch in stringency affects fertility; immature egg cells spend a long time in a form of arrested cell division without an intact nucleus, and Ly observed eIF1 in the nucleus of the immature female eggs.

“Cells have axes of control that they use to quickly make broad changes in gene expression,” Cheeseman says. “Several of these are central to controlling cell division—for example, the role of phosphorylation as a regulatory switch in mitosis has been well studied. Our work identifies another axis of control, and we’re excited to discover more about when and how cells make use of it.”

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.” 

Research Reflections: Alison Biester (PhD ’24), Drennan Lab

New snapshots of ancient life

Alison Biester | Department of Chemistry
October 3, 2024

The resolution revolution, beating “blobology”, and shedding light on how ancient microbes thrived in a primordial soup.

The earliest life on earth created biological molecules despite the limited materials available in the primordial soup such as CO2, hydrogen gas, and minerals containing iron, nickel, and sulfur.

As ancient microbes evolved, they developed proteins that sped up chemical reactions, called enzymes. Enzymes were evolutionarily advantageous because they created local environments called active sites optimized for reaction performance.

Although we know that carbon is the building block of life on earth–we wouldn’t exist without carbon-based molecules such as proteins and DNA–much remains unclear about how more complex carbon-based molecules were originally generated from CO2. Proteins and DNA are huge molecules with thousands of carbon atoms, so creating life from CO2 would be no small undertaking.

Catherine Drennan, Professor of Biology and Chemistry and HHMI Investigator and Professor, has long studied the enzymes that perform these crucial reactions wherein CO2 is converted into a form of carbon that cells can use, which requires iron, nickel, and sulfur.

In particular, she uses structural biology to study carbon monoxide dehydrogenase (CODH), which reacts with CO2 to produce CO, and acetyl-CoA synthase (ACS), which uses CO with another single unit of carbon to create a carbon-carbon bond. Crystallographic work by Drennan and others has provided structural snapshots of bacterial CODH and ACS, but its structure in other contexts remains elusive. During my PhD, I worked with Drennan on the structural characterization of CODH and ACS, culminating in a publication in PNAS, published October 3, 2024.

Throughout Drennan’s career, the lab has used a method known as X-ray crystallography to determine enzyme structures at atomic resolution. In recent years, however, cryogenic electron microscopy (cryo-EM) has risen in popularity as a structural biology technique.

Cryo-EM offers some key advantages over X-ray crystallography, such as its ability to capture structures of large and dynamic complexes. However, cryo-EM is limited in its ability to elucidate structures of small proteins, an area where X-ray crystallography continues to excel.

To perform a cryo-EM experiment, proteins are rapidly frozen in a thin layer of ice and imaged on an electron microscope. By capturing images of the protein in various orientations, researchers can generate a 3D model of their protein of interest.

Around 2015, cryo-EM reached a tipping point known as the “resolution revolution.” Due to improvements in both the hardware for collecting cryo-EM data and the software used for data processing, the technique could, for the first time, be used to determine protein structures at near-atomic resolution.

Seeing the potential for this new technique, MIT opened its very own cryo-EM facility with two electron microscopes in 2018. Just a year later, I joined the Drennan lab. When I began my thesis work, Cathy asked “Would you like to do crystallography or cryo-EM?”

Eager to try something that was both novel for researchers and new to me, I chose cryo-EM.

Ancient microbes

An ancient type of microbe, archaea, also uses CODH and ACS. Without information on how these protein chains interact, we cannot understand how these proteins work together within this complex–but it’s a difficult question to answer. In total, the complex contains forty protein chains that interact with one another and adopt various conformations to perform their chemistry.

We don’t know for sure which ACS enzyme came first, the bacterial or archaeal one, but we know they are both very ancient.

Archaeal CODH has been visualized via X-ray crystallography, but that CODH was isolated from the enormous megadalton enzyme complex present in the native archaea.

A CO2 molecule, which reacts with CODH, is 44 daltons; the enzyme complex at 2.2 megadaltons is 50,000 times the size of CO2. The complex consists of several copies of CODH, ACS, and a cobalt-containing enzyme that donates the second one-carbon unit used by ACS. Due to the large and dynamic nature of the complex, it was a great candidate for visualizing with cryo-EM.

Before I joined the lab, a collaboration had been initiated between the Drennan Lab and Dr. David Grahame of the Uniformed Services University of the Health Sciences, an expert in archaeal CODH and ACS.

Just before his retirement, Grahame grew hundreds of liters of archaea and isolated approximately one gram of the enzyme complex that he provided to the Drennan Lab for structural characterization. Each cryo-EM experiment can use as little as a microgram of protein. For a structural biologist, having one gram of protein–in theory, enough for one million experiments–to work with is a dream.

Blobology

With an abundance of protein, I embarked on this project with this exciting new technique on a promising target. I prepared my cryo-EM sample and collected data at the new MIT cryo-EM facility. As I was collecting data, I could see in the images large protein complexes that appeared to be my complex of interest. I could also see some smaller proteins that were consistent with the shape of isolated CODH. When I went on to process my data, I focused on the larger protein complexes, since the structure of isolated CODH was already known.

However, when I finished processing my first dataset, I was a bit disappointed. My resolution was very low–instead of atoms, I was seeing amorphous blobs, and I had no idea which blob matched with which protein, or how the proteins fit together. Rather than post-revolution cryo-EM, I felt like I was performing the “blobology” of the past.

Our cryo-EM data contains detailed structural information that becomes evident after significant data processing. On the left is the initial structure of our proteins of interest, carbon monoxide dehydrogenase (CODH) and acetyl-CoA synthase (ACS), and on the right is our final, detailed one. Photo courtesy of Alison Biester.

But the project was young, and a few failed experiments are par for the course of a PhD.

The next step was sample optimization, and luckily I had plenty of sample to work with. I tried preparing the protein in a different way, changed the protein concentration, used different additives, and scaled up my data collection.

Nothing helped. No matter what I tried, I could not move out of blobology territory. So, as one does when a project is failing, I stepped away. I worked on other projects and stopped thinking about the archaeal CODH and ACS.

A few months later, the cryo-EM facility was seeking users to try a new sample preparation instrument called the chameleon. Chameleon automates the sample preparation process and is intended to improve sample quality. With plenty of sample still to spare, I volunteered to try the instrument.

Just prior to my data collection, the facility had also installed a new software that allows data processing as it is being collected. The software uses automated processes to select proteins within your data; previously, I had only selected large protein complexes consistent with my complex of interest after the fact.

The new software is not very discriminating–but I was surprised when I looked at the results of the live processing. The processing showed that I had a protein complex in my sample that I did not expect – a complex of CODH and ACS!

This complex had just one copy of CODH and one copy of ACS, unlike the full complex that has multiple copies of each. My excitement for the project was reinvigorated. With this new target, could I leave blobology behind and finally join the resolution revolution?

After running more experiments and collecting more data and a few months of data processing, I realized that the sample contained three different states: isolated CODH, CODH with one copy of ACS, and CODH with two copies of ACS. I was able to use the Model-based Analysis of Volume Ensembles (MAVEn) tool developed by the Davis Lab at MIT to sort out these three states. When I finished the data processing, I achieved near-atomic resolution of all three states.

Through this work, for the first time, we can see what the archaeal ACS looks like. The archaeal ACS is fundamentally different from the bacterial one: a huge portion of the enzyme is missing, including part of the enzyme that makes up the active site in bacteria, leaving open the question of what the ACS active site looks like in archaea.

In our structure of archaeal ACS in complex with CODH, we were surprised to see that the active site looks almost identical to the bacterial one. This similarity is enabled by the archaeal CODH, which compensates for the missing part of ACS.

Given how similar the ACS active site environment in bacterial and archaea, we are likely getting a look at an active site that has remained conserved over billions of years of evolution.

Although the project didn’t fulfill its original promise of solving the structure of the large, dynamic protein complex, I did find intriguing insights. The tools available in 2015 would not have enabled me to achieve these results; it is clear to me that the resolution revolution is far from over, and the evolution of structural biology has been fascinating to experience. Cryo-EM has and will continue to evolve, as amazing new tools are still being developed.

Since graduating from MIT, I’ve been working at the Protein Data Bank, the data center that houses all available protein structure information. Working here gives me a front-row view of new discoveries in structural biology. I’m so excited to see where this field will go in the future.

Cancer biologists discover a new mechanism for an old drug

Study reveals the drug, 5-fluorouracil, acts differently in different types of cancer — a finding that could help researchers design better drug combinations.

Anne Trafton | MIT News
October 7, 2024

Since the 1950s, a chemotherapy drug known as 5-fluorouracil has been used to treat many types of cancer, including blood cancers and cancers of the digestive tract.

Doctors have long believed that this drug works by damaging the building blocks of DNA. However, a new study from MIT has found that in cancers of the colon and other gastrointestinal cancers, it actually kills cells by interfering with RNA synthesis.

The findings could have a significant effect on how doctors treat many cancer patients. Usually, 5-fluorouracil is given in combination with chemotherapy drugs that damage DNA, but the new study found that for colon cancer, this combination does not achieve the synergistic effects that were hoped for. Instead, combining 5-FU with drugs that affect RNA synthesis could make it more effective in patients with GI cancers, the researchers say.

“Our work is the most definitive study to date showing that RNA incorporation of the drug, leading to an RNA damage response, is responsible for how the drug works in GI cancers,” says Michael Yaffe, a David H. Koch Professor of Science at MIT, the director of the MIT Center for Precision Cancer Medicine, and a member of MIT’s Koch Institute for Integrative Cancer Research. “Textbooks implicate the DNA effects of the drug as the mechanism in all cancer types, but our data shows that RNA damage is what’s really important for the types of tumors, like GI cancers, where the drug is used clinically.”

Yaffe, the senior author of the new study, hopes to plan clinical trials of 5-fluorouracil with drugs that would enhance its RNA-damaging effects and kill cancer cells more effectively.

Jung-Kuei Chen, a Koch Institute research scientist, and Karl Merrick, a former MIT postdoc, are the lead authors of the paper, which appears today in Cell Reports Medicine.

An unexpected mechanism

Clinicians use 5-fluorouracil (5-FU) as a first-line drug for colon, rectal, and pancreatic cancers. It’s usually given in combination with oxaliplatin or irinotecan, which damage DNA in cancer cells. The combination was thought to be effective because 5-FU can disrupt the synthesis of DNA nucleotides. Without those building blocks, cells with damaged DNA wouldn’t be able to efficiently repair the damage and would undergo cell death.

Yaffe’s lab, which studies cell signaling pathways, wanted to further explore the underlying mechanisms of how these drug combinations preferentially kill cancer cells.

The researchers began by testing 5-FU in combination with oxaliplatin or irinotecan in colon cancer cells grown in the lab. To their surprise, they found that not only were the drugs not synergistic, in many cases they were less effective at killing cancer cells than what one would expect by simply adding together the effects of 5-FU or the DNA-damaging drug given alone.

“One would have expected that these combinations to cause synergistic cancer cell death because you are targeting two different aspects of a shared process: breaking DNA, and making nucleotides,” Yaffe says. “Karl looked at a dozen colon cancer cell lines, and not only were the drugs not synergistic, in most cases they were antagonistic. One drug seemed to be undoing what the other drug was doing.”

Yaffe’s lab then teamed up with Adam Palmer, an assistant professor of pharmacology at the University of North Carolina School of Medicine, who specializes in analyzing data from clinical trials. Palmer’s research group examined data from colon cancer patients who had been on one or more of these drugs and showed that the drugs did not show synergistic effects on survival in most patients.

“This confirmed that when you give these combinations to people, it’s not generally true that the drugs are actually working together in a beneficial way within an individual patient,” Yaffe says. “Instead, it appears that one drug in the combination works well for some patients while another drug in the combination works well in other patients. We just cannot yet predict which drug by itself is best for which patient, so everyone gets the combination.”

These results led the researchers to wonder just how 5-FU was working, if not by disrupting DNA repair. Studies in yeast and mammalian cells had shown that the drug also gets incorporated into RNA nucleotides, but there has been dispute over how much this RNA damage contributes to the drug’s toxic effects on cancer cells.

Inside cells, 5-FU is broken down into two different metabolites. One of these gets incorporated into DNA nucleotides, and other into RNA nucleotides. In studies of colon cancer cells, the researchers found that the metabolite that interferes with RNA was much more effective at killing colon cancer cells than the one that disrupts DNA.

That RNA damage appears to primarily affect ribosomal RNA, a molecule that forms part of the ribosome — a cell organelle responsible for assembling new proteins. If cells can’t form new ribosomes, they can’t produce enough proteins to function. Additionally, the lack of undamaged ribosomal RNA causes cells to destroy a large set of proteins that normally bind up the RNA to make new functional ribosomes.

The researchers are now exploring how this ribosomal RNA damage leads cells to under programmed cell death, or apoptosis. They hypothesize that sensing of the damaged RNAs within cell structures called lysosomes somehow triggers an apoptotic signal.

“My lab is very interested in trying to understand the signaling events during disruption of ribosome biogenesis, particularly in GI cancers and even some ovarian cancers, that cause the cells to die. Somehow, they must be monitoring the quality control of new ribosome synthesis, which somehow is connected to the death pathway machinery,” Yaffe says.

New combinations

The findings suggest that drugs that stimulate ribosome production could work together with 5-FU to make a highly synergistic combination. In their study, the researchers showed that a molecule that inhibits KDM2A, a suppressor of ribosome production, helped to boost the rate of cell death in colon cancer cells treated with 5-FU.

The findings also suggest a possible explanation for why combining 5-FU with a DNA-damaging drug often makes both drugs less effective. Some DNA damaging drugs send a signal to the cell to stop making new ribosomes, which would negate 5-FU’s effect on RNA. A better approach may be to give each drug a few days apart, which would give patients the potential benefits of each drug, without having them cancel each other out.

“Importantly, our data doesn’t say that these combination therapies are wrong. We know they’re effective clinically. It just says that if you adjust how you give these drugs, you could potentially make those therapies even better, with relatively minor changes in the timing of when the drugs are given,” Yaffe says.

He is now hoping to work with collaborators at other institutions to run a phase 2 or 3 clinical trial in which patients receive the drugs on an altered schedule.

“A trial is clearly needed to look for efficacy, but it should be straightforward to initiate because these are already clinically accepted drugs that form the standard of care for GI cancers. All we’re doing is changing the timing with which we give them,” he says.

The researchers also hope that their work could lead to the identification of biomarkers that predict which patients’ tumors will be more susceptible to drug combinations that include 5-FU. One such biomarker could be RNA polymerase I, which is active when cells are producing a lot of ribosomal RNA.

The research was funded by the Damon Runyon Cancer Research Fund, a Ludwig Center at MIT Fellowship, the National Institutes of Health, the Ovarian Cancer Research Fund, the Holloway Foundation, and the STARR Cancer Consortium.