News Brief: Lamason Lab uncovers seven novel effectors in Rickettsia parkeri infection

The enemy within: new research reveals insights into the arsenal Rickettsia parkeri uses against its host

Lillian Eden | Department of Biology
July 29, 2024

Identifying secreted proteins is critical to understanding how obligately intracellular pathogens hijack host machinery during infection, but identifying them is akin to finding a needle in a haystack.

For then-graduate student Allen Sanderlin, PhD ’24, the first indication that a risky, unlikely project might work was cyan, tic tac-shaped structures seen through a microscope — proof that his bacterial pathogen of interest was labeling its own proteins.  

Sanderlin, a member of the Lamason Lab in the Department of Biology at MIT, studies Rickettsia parkeri, a less virulent relative of the bacterial pathogen that causes Rocky Mountain Spotted Fever, a sometimes severe tickborne illness. No vaccine exists and definitive tests to diagnose an infection by Rickettsia are limited.

Rickettsia species are tricky to work with because they are obligately intracellular pathogens whose entire life cycles occur exclusively inside cells. Many approaches that have advanced our understanding of other bacterial infections and how those pathogens interact with their host aren’t applicable to Rickettsia because they can’t be grown on a plate in a lab setting. 

In a paper recently published in Nature Communications, the Lamason Lab outlines an approach for labeling and isolating R. parkeri proteins released during infection. This research reveals seven previously unknown secreted factors, known as effectors, more than doubling the number of known effectors in R. parkeri. 

Better-studied bacteria are known to hijack the host’s machinery via dozens or hundreds of secreted effectors, whose roles include manipulating the host cell to make it more susceptible to infection. However, finding those effectors in the soup of all other materials within the host cell is akin to looking for a needle in a haystack, with an added twist that researchers aren’t even sure what those needles look like for Rickettsia.  

Approaches that worked to identify the six previously known secreted effectors are limited in their scope. For example, some were found by comparing pathogenic Rickettsia to nonpathogenic strains of the bacteria, or by searching for proteins with domains that overlap with effectors from better-studied bacteria. Predictive modeling, however, relies on proteins being evolutionarily conserved. 

“Time and time again, we keep finding that Rickettsia are just weird — or, at least, weird compared to our understanding of other bacteria,” says Sanderlin, the paper’s first author. “This labeling tool allows us to answer some really exciting questions about rickettsial biology that weren’t possible before.”

The cyan tic tacs

To selectively label R. parkeri proteins, Sanderlin used a method called cell-selective bioorthogonal non-canonical amino acid tagging. BONCAT was first described in research from the Tirrell Lab at Caltech. The Lamason Lab, however, is the first group to use the tool successfully in an obligate intracellular bacterial pathogen; the thrilling moment when Sanderlin saw cyan tic-tac shapes indicated successfully labeling only the pathogen, not the host. 

Sanderlin next used an approach called selective lysis, carefully breaking open the host cell while leaving the pathogen, filled with labeled proteins, intact. This allowed him to extract proteins that R. parkeri had released into its host because the only labeled proteins amid other host cell material were effectors the pathogen had secreted. 

Sanderlin had successfully isolated and identified seven needles in the haystack, effectors never before identified in Rickettsia biology. The novel secreted rickettsial factors are dubbed SrfA, SrfB, SrfC, SrfD, SrfE, SrfF, and SrfG. 

“Every grad student wants to be able to name something,” Sanderlin says. “The most exciting — but frustrating — thing was that these proteins don’t look like anything we’ve seen before.”

Special delivery

Theoretically, Sanderlin says, once the effectors are secreted, they work independently from the bacteria — a driver delivering a pizza does not need to check back in with the store at every merge or turn.

Since SrfA-G didn’t resemble other known effectors or host proteins the pathogen could be mimicking during infection, Sanderlin then tried to answer some basic questions about their behavior. Where the effectors localize, meaning where in the cell they go, could hint at their purpose and what further experiments could be used to investigate it. 

To determine where the effectors were going, Sanderlin added the effectors he’d found to uninfected cells by introducing DNA that caused human cell lines to express those proteins. The experiment succeeded: he discovered that different Srfs went to different places throughout the host cells.  

SrfF and SrfG are found throughout the cytoplasm, whereas SrfB localizes to the mitochondria. That was especially intriguing because its structure is not predicted to interact with or find its way to the mitochondria, and the organelle appears unchanged despite the presence of the effector. 

Further, SrfC and SrfD found their way to the endoplasmic reticulum. The ER would be especially useful for a pathogen to appropriate, given that it is a dynamic organelle present throughout the cell and has many essential roles, including synthesizing proteins and metabolizing lipids. 

Aside from where effectors localize, knowing what they may interact with is critical. Sanderlin showed that SrfD interacts with Sec61, a protein complex that delivers proteins across the ER membrane. In keeping with the theme of the novelty of Sanderlin’s findings, SrfD does not resemble any proteins known to interact with the ER or Sec61. 

With this tool, Sanderlin identified novel proteins whose binding partners and role during infection can now be studied further. 

“These results are exciting but tantalizing,” Sanderlin says. “What Rickettsia secrete — the effectors, what they are, and what they do is, by and large, still a black box.” 

There are very likely other effectors in the proverbial cellular haystack. Sanderlin found that SrfA-G are not found in every species of Rickettsia, and his experiments were solely conducted with Rickettsia at late stages of infection — earlier windows of time may make use of different effectors. This research was also carried out in human cell lines, so there may be an entirely separate repertoire of effectors in ticks, which are responsible for spreading the pathogen.

Expanding Tool Development

Becky Lamason, the senior author of the Nature Communications paper, noted that this tool is one of a few avenues the lab is exploring to investigate R. parkeri, including a paper in the Journal of Bacteriology on conditional genetic manipulation. Characterizing how the pathogen behaves with or without a particular effector is leaps and bounds ahead of where the field was just a few years ago when Sanderlin was Lamason’s first graduate student to join the lab.

“What I always hoped for in the lab is to push the technology, but also get to the biology. These are two of what will hopefully be a suite of ways to attack this problem of understanding how these bacteria rewire and manipulate the host cell,” Lamason says. “We’re excited, but we’ve only scratched the surface.”

Gene silencing tool has a need for speed

Small changes in the molecular machines that carry out RNA interference can lead to big differences in the efficacy of gene silencing. These new findings from the Bartel Lab have implications for the design of gene-silencing therapeutics.

Greta Friar | Whitehead Institute
July 17, 2024

RNA interference (RNAi) is a process that many organisms, including humans, use to decrease the activity of target RNAs in cells by triggering their degradation or slicing them in half. If the target is a messenger RNA, the intermediary between gene and protein, then RNAi can decrease or completely silence expression of the gene. Researchers figured out how to tailor RNAi to target different RNAs, and since then it has been used as a research tool to silence genes of interest. RNAi is also used in a growing number of therapeutics to silence genes that contribute to disease.

However, researchers still do not understand some of the biochemistry underlying RNAi. Slight differences in the design of the RNAi machinery can lead to big differences in how effective it is at decreasing gene expression. Through trial and error, researchers have worked out guidelines for making the most effective RNAi tools without understanding exactly why they work. However, Whitehead Institute Member David Bartel and graduate student in his lab Peter Wang have now dug deeper to figure out the mechanics of the main cellular machine involved in RNAi. The researchers’ findings, shared in Molecular Cell on July 17, not only provide explanations for some of the known rules for RNAi tool design, but also provide new insights that could improve future designs.

Slicing speed is highly variable

The cellular machine that carries out RNAi has two main parts. One is a guide RNA, a tiny RNA typically only 22 bases or nucleotides long. RNA, like DNA, is made of four possible bases, although RNA has the base uracil (U) instead of the DNA base thymine (T). RNA bases bind to each other in certain pairings—guanines (G) pair to cytosines (C) and adenines (A) pair to U’s—and the sequence of bases in the guide RNA corresponds to a complementary sequence within the target RNA. When the guide RNA comes across a target, the corresponding bases pair up, binding the RNAs. Then the other part of the RNAi machine, an Argonaute protein bound to the guide RNA, can slice the target RNA in half or trigger the cell to break it down more gradually.

In humans, AGO2 is the Argonaute protein that is best at slicing. Only a couple dozen RNA targets actually get sliced, but these few targets play essential roles in processes such as neuron signal control and accurate body shape formation. Slicing is also important for RNAi tools and therapeutics.

In order for AGO2 to slice its target, the target must be in the exact right position. As the guide and target RNAs bind together, they go through a series of motions to ultimately form a double helix. Only in that configuration can AGO2 slice the target.

Researchers had assumed that AGO2 slices through different target RNAs at roughly the same rate, because most research into this process used the same few guide RNAs. These guide RNAs happen to have similar features, and so similar slicing kinetics—but they turn out not to be representative of most guide RNAs.

Wang paired AGO2 with a larger variety of guide RNAs and measured the rate at which each AGO2-guide RNA complex sliced its targets. He found big differences. Whereas the commonly used guide RNAs might differ in their slicing rate by 2-fold, the larger pool of guide RNAs differed by as much as 250-fold. The slicing rates were often much slower than the researchers expected. Previously, researchers thought that all targets could be sliced relatively quickly, so the rate wasn’t considered as a limiting factor – other parts of the process were thought to determine the overall pace – but Wang found that slicing can sometimes be the slowest step.

“The important consideration is whether the slicing rate is faster or slower than other processes in the cell,” Wang says. “We found that for many guide RNAs, the slicing rate was the limiting factor. As such, it impacted the efficacy.”

The slower AGO2 is to slice targets, the more messenger RNAs will remain intact to be made into protein, meaning that the corresponding gene will continue being expressed. The researchers observed this in action: the guide RNAs with slower slicing rates decreased target gene expression by less than the faster ones.

Small changes lead to big differences in slicing rate

Next, the researchers explored what could be causing such big differences in slicing rate between guide RNAs. They mutated guide RNAs to swap out single bases along the guide RNA’s sequence—say, switching the 10th base in the sequence from a C to an A—and measured how this changed the slicing rate.

“The important consideration is whether the slicing rate is faster or slower than other processes in the cell,” Wang says. “We found that for many guide RNAs, the slicing rate was the limiting factor. As such, it impacted the efficacy.”

The researchers found that slicing rate increased when the base at position 7 was an A or a U. The bases A and U pair more weakly than C and G. The researchers found that having a weak A-U pair at that position, or a fully mismatched pair at position 6 or 7, may allow a kink to form in the double helix shape that actually makes the target easier to slice. Wang also found that slicing rate increases with certain substitutions at the 10th and the 17th base positions, although the researchers could not yet determine possible underlying mechanisms.

These observations correspond to existing recommendations for RNAi design, such as not using a G at position 7. The new work demonstrates that the reason these recommendations work is because they affect the slicing rate, and, in the case of position 7, the new work further identifies the specific mechanism at play.

Interplay between regions matters

People designing synthetic guide RNAs thought that the bases at the tail end, past the 16th position, were not very important. This is because in the case of the most commonly used guide RNAs, the target will be rapidly cleaved even if all of the tail end positions are mismatches that cannot pair.

However, Wang and Bartel found that the identity of the tail end bases are only irrelevant in a specific scenario that happens to be true of the most commonly used guide RNAs: when the bases in the center of the guide RNA (positions 9-12) are strong-pairing Cs and Gs. When the center pairings are weak, then the tail end bases need to be perfect matches to the target RNA. The researchers found that guide RNAs could have up to a 600-fold difference in tolerance for tail end mismatches based on the strength of their central pairings.

The reason for this difference has to do with the final set of motions that the two RNAs must perform in order to assume their final double helix shape. A perfectly paired tail end makes it easier for the RNAs to complete these motions. However, a strong enough center can pull the RNAs into the double helix even if the tail ends are not ideally suited for doing so.

The observation that weak central pairing requires perfect or near perfect tail end matches could provide a useful new guideline for designing synthetic RNAs. Any guide RNA runs the risk of sometimes binding other messenger RNAs that are similar enough to the intended target RNA. In the case of a therapy, this off-target binding can lead to negative side effects. Bartel and Wang suggest that researchers could design guide RNAs with weak centers, which would require more perfect pairing in the tail end, so that the guide RNA will be less likely to bind non-target RNAs; only the perfect pairing of the target’s RNA sequence would suffice.

Altogether, Wang and Bartel’s findings explain how small differences between guide RNAs can make such large differences in the efficacy of RNAi, providing a rationale for the long-standing RNAi design guidelines. Some of the findings even suggest new guidelines that could help with future synthetic guide RNA designs.

“Discovering the interplay between the center and tail end of the guide RNA was unexpected and satisfying,” says Bartel, who is also a professor at the Massachusetts Institute of Technology and a Howard Hughes Medical Investigator. “It explains why, even though the guidelines suggested that tail-end sequence doesn’t matter, the target RNAs that are sliced in our cells do have pairing to the tail end. This observation could prove useful to reduce off-target effects in RNAi therapeutics.”

She’s fighting to stop the brain disease that killed her mother before it gets her

Jonathan Weissman is the senior author on a recent study on silencing a prion protein's expression. Prions cause devastating neurodegenerative disorders such as dementia, Huntington's, Parkinson's, and Lou Gehrig's disease. Silencing genes represents a step towards a therapeutic model for treating these diseases in humans.

Karen Weintraub | USA TODAY
June 27, 2024

CAMBRIDGE, Mass. ‒ Sonia Vallabh watched helplessly as her 51-year-old mother rapidly descended into dementia and died. It didn’t take long for Vallabh to realize she was destined for the same rare genetic fate.

Vallabh and her husband did what anyone would want to do in their situation: They decided to fight.

Armed with little more than incredible intellect and determination they set out to conquer her destiny.

A dozen years later, they’ve taken a major step in that direction, finding a way to shut off enough genetic signals to hold off the disease.

And in the process of trying to rescue Vallabh, they may save many, many others as well.

In a paper published Thursday in the prestigious journal Science, Vallabh and her husband, Eric Minikel, and their co-authors offer a way to disrupt brain diseases like the one that killed her mother.

The same approach should also work against diseases such as Huntington’s, Parkinson’s, Lou Gehrig’s disease and even Alzheimer’s, which result from the accumulation of toxic proteins. If it works as well as they think, it could also be useful against a vast array of other diseases that can be treated by shutting off genes.

“It doesn’t have to be the brain. It could be the muscles. It could be the kidneys. It could be really anywhere in the body where we have not easily been able to do these things before,” said Dr. Kiran Musunuru, a cardiologist and geneticist at the University of Pennsylvania’s Perelman School of Medicine, who wasn’t involved in the research but wrote a perspective accompanying the paper.

So far, they’ve proven it only in mice.

“The data are good as far as they go,” Vallabh said this week from her office at the Broad Institute of Harvard and the Massachusetts Institute of Technology, where she has worked since getting a Ph.D. at Harvard. She had already gotten a law degree from the university, but she and Minikel, then a transportation planner, both pursued biology degrees after her mother’s death. Now, they work together at the Broad.

“We’re far from this being a drug,” Vallabh said. “There’s always, always reason for caution. Sadly, everything is always more likely to fail than succeed.

“But there is justifiable reason for optimism.”

A terrible disease

The disease that killed Vallabh’s mother was one of a group of conditions called prion diseases. These include mad cow disease, which affects mostly cattle, scrapie, which affects sheep, and Creutzfeldt-Jakob disease, which kills about 350 Americans a year ‒ most within months of their first symptom.

These diseases are triggered when the prion protein found in all normal brains starts misfolding for some reason, as yet unknown.

“Prion disease can strike anybody,” Vallabh said, noting the 1 in 6,000 risk to the general population.

Though prion diseases are, in some cases, contagious, a federal study earlier this year concluded that chronic wasting disease, found in deer, elk and moose, is very unlikely to pass to people who eat the meat of sick animals.

In Vallabh’s case, the cause is genetic. Vallabh discovered after her mother’s death that she carries the same variant of the same gene that caused her mother’s disease, meaning she will certainly develop it.

The only question is when.

“The age of onset is extremely unpredictable,” Vallabh said. “Your parent’s age of onset doesn’t actually predict anything.”

How the gene-editing tool works

Vallabh and Minikel approached colleagues at the Whitehead Institute a biomedical research institute next to the Broad. They asked to collaborate on a new gene-editing approach to turn off Vallabh’s disease gene. The technique developed by Whitehead scientists is called CHARM (for Coupled Histone tail Autoinhibition Release of Methyltransferase).

While previous gene-editing tools have been described as scissors or erasers, Musunuru described CHARM as volume control, allowing scientists to tune a gene up or down. It has three advantages over previous strategies, he said.

The device is tiny, so it fits easily inside the virus needed to deliver it. Other gene-editing tools, like CRISPR, are bigger, which means they need to be broken into pieces and much more of the virus is needed to deliver those pieces to the brain, risking a dangerous immune reaction.

CHARM, Musunuru said, is “easier to deliver to hard-to-deliver spaces like the brain.”

At least in the mouse, it also seems to have reached throughout the brain, making the desired genetic change without other, unwanted ones, Musunuru said.

And finally, the research team figured out a way to turn the gene editor off after its work was done. “If it’s sticking around, there’s the potential for genetic mischief,” Musunuru said.

One shot on goal

While researchers, including Vallabh, continue to work to perfect an approach, the clock for Vallabh and others is ticking.

Right now there’s no viable treatment and if it takes too long to develop one, Vallabh will miss her window. Once the disease process starts, like a runaway train, it’ll be much harder to stop than it would be to just shut the gene off in the first place.

The more prion protein in the brain, the more likely it is to misfold. And the more likely it is for the disease to spread, a process that co-opts the natural form of the protein and converts it to the toxic form.

That’s why getting rid of as much of it as possible makes sense, said Jonathan Weissman, the senior author of the study, who leads a Whitehead lab.

“The biology is really clear. The need (for a cure) is so compelling,” Weissman said.

Every cell in the brain has the gene for making the prion protein. By silencing even 50% of those genes, Weissman figures he can prevent the disease. In mice, CHARM silenced up to 80% to 90%.

“We’ve figured out what to deliver. Now we have to figure out how to deliver it,” he said.

Another of the paper’s co-authors, the Broad’s Ben Deverman, published a study late last year showing he could deliver a gene-therapy-carrying virus throughout the brain. Others are developing other viral delivery systems.

Vallabh and Minikel have hedged their bets, helping to develop a so-called antisense oligonucleotide, or ASO, which uses another path for stopping the gene from making the prion protein.

The ASO, which is in early trials in people by a company called Ionis Pharmaceuticals, requires regular treatment rather than the one-and-done of gene therapy. Recruitment for that trial had to be paused in April because the number of would-be volunteers outstripped the available slots.

Vallabh isn’t ready yet to start any treatment yet herself.

“She has one shot on goal,” Musunuru said. “At some point, she’ll have to decide what’s the best strategy.”

In the meantime, the clock Vallabh can’t see continues to tick toward the onset.

She and Minikel stay exceedingly busy with their research along with their daughter, almost 7, and 4-year-old son ‒ both born via IVF and preimplantation genetic testing to ensure they wouldn’t inherit her genetic curse. (They were super lucky, Vallabh notes, to be living in Massachusetts where IVF is at least “approachable” financially.)

“There is a mountain ahead of us,” Vallabh said of the path to a cure. “There’s still a lot of hurdles, there’s still a lot to figure out.”

CHARMed collaboration creates a potent therapy candidate for fatal prion diseases

A new gene-silencing tool shows promise as a future therapy against prion diseases and paves the way for new approaches to treating disease.

Greta Friar | Whitehead Institute
June 27, 2024

Drug development is typically slow: The pipeline from basic research discoveries that provide the basis for a new drug to clinical trials and then production of a widely available medicine can take decades. But decades can feel impossibly far off to someone who currently has a fatal disease. Broad Institute of MIT and Harvard Senior Group Leader Sonia Vallabh is acutely aware of that race against time, because the topic of her research is a neurodegenerative and ultimately fatal disease — fatal familial insomnia, a type of prion disease — that she will almost certainly develop as she ages.

Vallabh and her husband, Eric Minikel, switched careers and became researchers after they learned that Vallabh carries a disease-causing version of the prion protein gene and that there is no effective therapy for fatal prion diseases. The two now run a lab at the Broad Institute, where they are working to develop drugs that can prevent and treat these diseases, and their deadline for success is not based on grant cycles or academic expectations but on the ticking time bomb in Vallabh’s genetic code.

That is why Vallabh was excited to discover, when she entered into a collaboration with Whitehead Institute for Biomedical Research member Jonathan Weissman, that Weissman’s group likes to work at full throttle. In less than two years, Weissman, Vallabh, and their collaborators have developed a set of molecular tools called CHARMs that can turn off disease-causing genes such as the prion protein gene — as well as, potentially, genes coding for many other proteins implicated in neurodegenerative and other diseases — and they are refining those tools to be good candidates for use in human patients. Although the tools still have many hurdles to pass before the researchers will know if they work as therapeutics, the team is encouraged by the speed with which they have developed the technology thus far.

“The spirit of the collaboration since the beginning has been that there was no waiting on formality,” Vallabh says. “As soon as we realized our mutual excitement to do this, everything was off to the races.”

Co-corresponding authors Weissman and Vallabh and co-first authors Edwin Neumann, a graduate student in Weissman’s lab, and Tessa Bertozzi, a postdoc in Weissman’s lab, describe CHARM — which stands for Coupled Histone tail for Autoinhibition Release of Methyltransferase — in a paper published today in the journal Science.

“With the Whitehead and Broad Institutes right next door to each other, I don’t think there’s any better place than this for a group of motivated people to move quickly and flexibly in the pursuit of academic science and medical technology,” says Weissman, who is also a professor of biology at MIT and a Howard Hughes Medical Institute Investigator. “CHARMs are an elegant solution to the problem of silencing disease genes, and they have the potential to have an important position in the future of genetic medicines.”

To treat a genetic disease, target the gene

Prion disease, which leads to swift neurodegeneration and death, is caused by the presence of misshapen versions of the prion protein. These cause a cascade effect in the brain: the faulty prion proteins deform other proteins, and together these proteins not only stop functioning properly but also form toxic aggregates that kill neurons. The most famous type of prion disease, known colloquially as mad cow disease, is infectious, but other forms of prion disease can occur spontaneously or be caused by faulty prion protein genes.

Most conventional drugs work by targeting a protein. CHARMs, however, work further upstream, turning off the gene that codes for the faulty protein so that the protein never gets made in the first place. CHARMs do this by epigenetic editing, in which a chemical tag gets added to DNA in order to turn off or silence a target gene. Unlike gene editing, epigenetic editing does not modify the underlying DNA — the gene itself remains intact. However, like gene editing, epigenetic editing is stable, meaning that a gene switched off by CHARM should remain off. This would mean patients would only have to take CHARM once, as opposed to protein-targeting medications that must be taken regularly as the cells’ protein levels replenish.

Research in animals suggests that the prion protein isn’t necessary in a healthy adult, and that in cases of disease, removing the protein improves or even eliminates disease symptoms. In a person who hasn’t yet developed symptoms, removing the protein should prevent disease altogether. In other words, epigenetic editing could be an effective approach for treating genetic diseases such as inherited prion diseases. The challenge is creating a new type of therapy.

Fortunately, the team had a good template for CHARM: a research tool called CRISPRoff that Weissman’s group previously developed for silencing genes. CRISPRoff uses building blocks from CRISPR gene editing technology, including the guide protein Cas9 that directs the tool to the target gene. CRISPRoff silences the targeted gene by adding methyl groups, chemical tags that prevent the gene from being transcribed, or read into RNA, and so from being expressed as protein. When the researchers tested CRISPRoff’s ability to silence the prion protein gene, they found that it was effective and stable.

Several of its properties, though, prevented CRISPRoff from being a good candidate for a therapy. The researchers’ goal was to create a tool based on CRISPRoff that was just as potent but also safe for use in humans, small enough to deliver to the brain, and designed to minimize the risk of silencing the wrong genes or causing side effects.

From research tool to drug candidate

Led by Neumann and Bertozzi, the researchers began engineering and applying their new epigenome editor. The first problem that they had to tackle was size, because the editor needs to be small enough to be packaged and delivered to specific cells in the body. Delivering genes into the human brain is challenging; many clinical trials have used adeno-associated viruses (AAVs) as gene-delivery vehicles, but these are small and can only contain a small amount of genetic code. CRISPRoff is way too big; the code for Cas9 alone takes up most of the available space.

The Weissman lab researchers decided to replace Cas9 with a much smaller zinc finger protein (ZFP). Like Cas9, ZFPs can serve as guide proteins to direct the tool to a target site in DNA. ZFPs are also common in human cells, meaning they are less likely to trigger an immune response against themselves than the bacterial Cas9.

Next, the researchers had to design the part of the tool that would silence the prion protein gene. At first, they used part of a methyltransferase, a molecule that adds methyl groups to DNA, called DNMT3A. However, in the particular configuration needed for the tool, the molecule was toxic to the cell. The researchers focused on a different solution: Instead of delivering outside DNMT3A as part of the therapy, the tool is able to recruit the cell’s own DNMT3A to the prion protein gene. This freed up precious space inside of the AAV vector and prevented toxicity.

The researchers also needed to activate DNMT3A. In the cell, DNMT3A is usually inactive until it interacts with certain partner molecules. This default inactivity prevents accidental methylation of genes that need to remain turned on. Neumann came up with an ingenious way around this by combining sections of DNMT3A’s partner molecules and connecting these to ZFPs that bring them to the prion protein gene. When the cell’s DNMT3A comes across this combination of parts, it activates, silencing the gene.

“From the perspectives of both toxicity and size, it made sense to recruit the machinery that the cell already has; it was a much simpler, more elegant solution,” Neumann says. “Cells are already using methyltransferases all of the time, and we’re essentially just tricking them into turning off a gene that they would normally leave turned on.”

Testing in mice showed that ZFP-guided CHARMs could eliminate more than 80 percent of the prion protein in the brain, while previous research has shown that as little as 21 percent elimination can improve symptoms.

Once the researchers knew that they had a potent gene silencer, they turned to the problem of off-target effects. The genetic code for a CHARM that gets delivered to a cell will keep producing copies of the CHARM indefinitely. However, after the prion protein gene is switched off, there is no benefit to this, only more time for side effects to develop, so they tweaked the tool so that after it turns off the prion protein gene, it then turns itself off.

Meanwhile, a complementary project from Broad Institute scientist and collaborator Benjamin Deverman’s lab, focused on brain-wide gene delivery and published in Science on May 17, has brought the CHARM technology one step closer to being ready for clinical trials. Although naturally occurring types of AAV have been used for gene therapy in humans before, they do not enter the adult brain efficiently, making it impossible to treat a whole-brain disease like prion disease. Tackling the delivery problem, Deverman’s group has designed an AAV vector that can get into the brain more efficiently by leveraging a pathway that naturally shuttles iron into the brain. Engineered vectors like this one make a therapy like CHARM one step closer to reality.

Thanks to these creative solutions, the researchers now have a highly effective epigenetic editor that is small enough to deliver to the brain, and that appears in cell culture and animal testing to have low toxicity and limited off-target effects.

“It’s been a privilege to be part of this; it’s pretty rare to go from basic research to therapeutic application in such a short amount of time,” Bertozzi says. “I think the key was forming a collaboration that took advantage of the Weissman lab’s tool-building experience, the Vallabh and Minikel lab’s deep knowledge of the disease, and the Deverman lab’s expertise in gene delivery.”

Looking ahead

With the major elements of the CHARM technology solved, the team is now fine-tuning their tool to make it more effective, safer, and easier to produce at scale, as will be necessary for clinical trials. They have already made the tool modular, so that its various pieces can be swapped out and future CHARMs won’t have to be programmed from scratch. CHARMs are also currently being tested as therapeutics in mice.

The path from basic research to clinical trials is a long and winding one, and the researchers know that CHARMs still have a way to go before they might become a viable medical option for people with prion diseases, including Vallabh, or other diseases with similar genetic components. However, with a strong therapy design and promising laboratory results in hand, the researchers have good reason to be hopeful. They continue to work at full throttle, intent on developing their technology so that it can save patients’ lives not someday, but as soon as possible.

New technique reveals how gene transcription is coordinated in cells

By capturing short-lived RNA molecules, scientists can map relationships between genes and the regulatory elements that control them.

Anne Trafton | MIT News
June 5, 2024

The human genome contains about 23,000 genes, but only a fraction of those genes are turned on inside a cell at any given time. The complex network of regulatory elements that controls gene expression includes regions of the genome called enhancers, which are often located far from the genes that they regulate.

This distance can make it difficult to map the complex interactions between genes and enhancers. To overcome that, MIT researchers have invented a new technique that allows them to observe the timing of gene and enhancer activation in a cell. When a gene is turned on around the same time as a particular enhancer, it strongly suggests the enhancer is controlling that gene.

Learning more about which enhancers control which genes, in different types of cells, could help researchers identify potential drug targets for genetic disorders. Genomic studies have identified mutations in many non-protein-coding regions that are linked to a variety of diseases. Could these be unknown enhancers?

“When people start using genetic technology to identify regions of chromosomes that have disease information, most of those sites don’t correspond to genes. We suspect they correspond to these enhancers, which can be quite distant from a promoter, so it’s very important to be able to identify these enhancers,” says Phillip Sharp, an MIT Institute Professor Emeritus and member of MIT’s Koch Institute for Integrative Cancer Research.

Sharp is the senior author of the new study, which appears today in Nature. MIT Research Assistant D.B. Jay Mahat is the lead author of the paper.

Hunting for eRNA

Less than 2 percent of the human genome consists of protein-coding genes. The rest of the genome includes many elements that control when and how those genes are expressed. Enhancers, which are thought to turn genes on by coming into physical contact with gene promoter regions through transiently forming a complex, were discovered about 45 years ago.

More recently, in 2010, researchers discovered that these enhancers are transcribed into RNA molecules, known as enhancer RNA or eRNA. Scientists suspect that this transcription occurs when the enhancers are actively interacting with their target genes. This raised the possibility that measuring eRNA transcription levels could help researchers determine when an enhancer is active, as well as which genes it’s targeting.

“That information is extraordinarily important in understanding how development occurs, and in understanding how cancers change their regulatory programs and activate processes that lead to de-differentiation and metastatic growth,” Mahat says.

However, this kind of mapping has proven difficult to perform because eRNA is produced in very small quantities and does not last long in the cell. Additionally, eRNA lacks a modification known as a poly-A tail, which is the “hook” that most techniques use to pull RNA out of a cell.

One way to capture eRNA is to add a nucleotide to cells that halts transcription when incorporated into RNA. These nucleotides also contain a tag called biotin that can be used to fish the RNA out of a cell. However, this current technique only works on large pools of cells and doesn’t give information about individual cells.

While brainstorming ideas for new ways to capture eRNA, Mahat and Sharp considered using click chemistry, a technique that can be used to join two molecules together if they are each tagged with “click handles” that can react together.

The researchers designed nucleotides labeled with one click handle, and once these nucleotides are incorporated into growing eRNA strands, the strands can be fished out with a tag containing the complementary handle. This allowed the researchers to capture eRNA and then purify, amplify, and sequence it. Some RNA is lost at each step, but Mahat estimates that they can successfully pull out about 10 percent of the eRNA from a given cell.

Using this technique, the researchers obtained a snapshot of the enhancers and genes that are being actively transcribed at a given time in a cell.

“You want to be able to determine, in every cell, the activation of transcription from regulatory elements and from their corresponding gene. And this has to be done in a single cell because that’s where you can detect synchrony or asynchrony between regulatory elements and genes,” Mahat says.

Timing of gene expression

Demonstrating their technique in mouse embryonic stem cells, the researchers found that they could calculate approximately when a particular region starts to be transcribed, based on the length of the RNA strand and the speed of the polymerase (the enzyme responsible for transcription) — that is, how far the polymerase transcribes per second. This allowed them to determine which genes and enhancers were being transcribed around the same time.

The researchers used this approach to determine the timing of the expression of cell cycle genes in more detail than has previously been possible. They were also able to confirm several sets of known gene-enhancer pairs and generated a list of about 50,000 possible enhancer-gene pairs that they can now try to verify.

Learning which enhancers control which genes would prove valuable in developing new treatments for diseases with a genetic basis. Last year, the U.S. Food and Drug Administration approved the first gene therapy treatment for sickle cell anemia, which works by interfering with an enhancer that results in activation of a fetal globin gene, reducing the production of sickled blood cells.

The MIT team is now applying this approach to other types of cells, with a focus on autoimmune diseases. Working with researchers at Boston Children’s Hospital, they are exploring immune cell mutations that have been linked to lupus, many of which are found in non-coding regions of the genome.

“It’s not clear which genes are affected by these mutations, so we are beginning to tease apart the genes these putative enhancers might be regulating, and in what cell types these enhancers are active,” Mahat says. “This is a tool for creating gene-to-enhancer maps, which are fundamental in understanding the biology, and also a foundation for understanding disease.”

The findings of this study also offer evidence for a theory that Sharp has recently developed, along with MIT professors Richard Young and Arup Chakraborty, that gene transcription is controlled by membraneless droplets known as condensates. These condensates are made of large clusters of enzymes and RNA, which Sharp suggests may include eRNA produced at enhancer sites.

“We picture that the communication between an enhancer and a promoter is a condensate-type, transient structure, and RNA is part of that. This is an important piece of work in building the understanding of how RNAs from enhancers could be active,” he says.

The research was funded by the National Cancer Institute, the National Institutes of Health, and the Emerald Foundation Postdoctoral Transition Award.

“Rosetta Stone” of cell signaling could expedite precision cancer medicine

An atlas of human protein kinases enables scientists to map cell signaling pathways with unprecedented speed and detail. Michael Yaffe, the David H. Koch Professor of Science at MIT, the director of the MIT Center for Precision Cancer Medicine, a member of MIT’s Koch Institute for Integrative Cancer Research, and a senior author of the new study published in Nature, is hoping to apply the comprehensive atlas of enzymes that regulate a wide variety of cellular activities to individual patients’ tumors to learn more about how the signaling states differ in cancer cancer, which could reveal new

Megan Scudellari | Koch Institute
June 3, 2024

A newly complete database of human protein kinases and their preferred binding sites provides a powerful new platform to investigate cell signaling pathways.

Culminating 25 years of research, MIT, Harvard University, and Yale University scientists and collaborators have unveiled a comprehensive atlas of human tyrosine kinases — enzymes that regulate a wide variety of cellular activities — and their binding sites.

The addition of tyrosine kinases to a previously published dataset from the same group now completes a free, publicly available atlas of all human kinases and their specific binding sites on proteins, which together orchestrate fundamental cell processes such as growth, cell division, and metabolism.

Now, researchers can use data from mass spectrometry, a common laboratory technique, to identify the kinases involved in normal and dysregulated cell signaling in human tissue, such as during inflammation or cancer progression.

“I am most excited about being able to apply this to individual patients’ tumors and learn about the signaling states of cancer and heterogeneity of that signaling,” says Michael Yaffe, who is the David H. Koch Professor of Science at MIT, the director of the MIT Center for Precision Cancer Medicine, a member of MIT’s Koch Institute for Integrative Cancer Research, and a senior author of the new study. “This could reveal new druggable targets or novel combination therapies.”

The study, published in Nature, is the product of a long-standing collaboration with senior authors Lewis Cantley at Harvard Medical School and Dana-Farber Cancer Institute, Benjamin Turk at Yale School of Medicine, and Jared Johnson at Weill Cornell Medical College.

The paper’s lead authors are Tomer Yaron-Barir at Columbia University Irving Medical Center, and MIT’s Brian Joughin, with contributions from Kontstantin Krismer, Mina Takegami, and Pau Creixell.

Kinase kingdom

Human cells are governed by a network of diverse protein kinases that alter the properties of other proteins by adding or removing chemical compounds called phosphate groups. Phosphate groups are small but powerful: When attached to proteins, they can turn proteins on or off, or even dramatically change their function. Identifying which of the almost 400 human kinases phosphorylate a specific protein at a particular site on the protein was traditionally a lengthy, laborious process.

Beginning in the mid 1990s, the Cantley laboratory developed a method using a library of small peptides to identify the optimal amino acid sequence — called a motif, similar to a scannable barcode — that a kinase targets on its substrate proteins for the addition of a phosphate group. Over the ensuing years, Yaffe, Turk, and Johnson, all of whom spent time as postdocs in the Cantley lab, made seminal advancements in the technique, increasing its throughput, accuracy, and utility.

Johnson led a massive experimental effort exposing batches of kinases to these peptide libraries and observed which kinases phosphorylated which subsets of peptides. In a corresponding Nature paper published in January 2023, the team mapped more than 300 serine/threonine kinases, the other main type of protein kinase, to their motifs. In the current paper, they complete the human “kinome” by successfully mapping 93 tyrosine kinases to their corresponding motifs.

Next, by creating and using advanced computational tools, Yaron-Barir, Krismer, Joughin, Takegami, and Yaffe tested whether the results were predictive of real proteins, and whether the results might reveal unknown signaling events in normal and cancer cells. By analyzing phosphoproteomic data from mass spectrometry to reveal phosphorylation patterns in cells, their atlas accurately predicted tyrosine kinase activity in previously studied cell signaling pathways.

For example, using recently published phosphoproteomic data of human lung cancer cells treated with two targeted drugs, the atlas identified that treatment with erlotinib, a known inhibitor of the protein EGFR, downregulated sites matching a motif for EGFR. Treatment with afatinib, a known HER2 inhibitor, downregulated sites matching the HER2 motif. Unexpectedly, afatinib treatment also upregulated the motif for the tyrosine kinase MET, a finding that helps explain patient data linking MET activity to afatinib drug resistance.

Actionable results

There are two key ways researchers can use the new atlas. First, for a protein of interest that is being phosphorylated, the atlas can be used to narrow down hundreds of kinases to a short list of candidates likely to be involved. “The predictions that come from using this will still need to be validated experimentally, but it’s a huge step forward in making clear predictions that can be tested,” says Yaffe.

Second, the atlas makes phosphoproteomic data more useful and actionable. In the past, researchers might gather phosphoproteomic data from a tissue sample, but it was difficult to know what that data was saying or how to best use it to guide next steps in research. Now, that data can be used to predict which kinases are upregulated or downregulated and therefore which cellular signaling pathways are active or not.

“We now have a new tool now to interpret those large datasets, a Rosetta Stone for phosphoproteomics,” says Yaffe. “It is going to be particularly helpful for turning this type of disease data into actionable items.”

In the context of cancer, phosophoproteomic data from a patient’s tumor biopsy could be used to help doctors quickly identify which kinases and cell signaling pathways are involved in cancer expansion or drug resistance, then use that knowledge to target those pathways with appropriate drug therapy or combination therapy.

Yaffe’s lab and their colleagues at the National Institutes of Health are now using the atlas to seek out new insights into difficult cancers, including appendiceal cancer and neuroendocrine tumors. While many cancers have been shown to have a strong genetic component, such as the genes BRCA1 and BRCA2 in breast cancer, other cancers are not associated with any known genetic cause. “We’re using this atlas to interrogate these tumors that don’t seem to have a clear genetic driver to see if we can identify kinases that are driving cancer progression,” he says.

Biological insights

In addition to completing the human kinase atlas, the team made two biological discoveries in their recent study. First, they identified three main classes of phosphorylation motifs, or barcodes, for tyrosine kinases. The first class is motifs that map to multiple kinases, suggesting that numerous signaling pathways converge to phosphorylate a protein boasting that motif. The second class is motifs with a one-to-one match between motif and kinase, in which only a specific kinase will activate a protein with that motif. This came as a partial surprise, as tyrosine kinases have been thought to have minimal specificity by some in the field.

The final class includes motifs for which there is no clear match to one of the 78 classical tyrosine kinases. This class includes motifs that match to 15 atypical tyrosine kinases known to also phosphorylate serine or threonine residues. “This means that there’s a subset of kinases that we didn’t recognize that are actually playing an important role,” says Yaffe. It also indicates there may be other mechanisms besides motifs alone that affect how a kinase interacts with a protein.

The team also discovered that tyrosine kinase motifs are tightly conserved between humans and the worm species C. elegans, despite the species being separated by more than 600 million years of evolution. In other words, a worm kinase and its human homologue are phosphorylating essentially the same motif. That sequence preservation suggests that tyrosine kinases are highly critical to signaling pathways in all multicellular organisms, and any small change would be harmful to an organism.

The research was funded by the Charles and Marjorie Holloway Foundation, the MIT Center for Precision Cancer Medicine, the Koch Institute Frontier Research Program via L. Scott Ritterbush, the Leukemia and Lymphoma Society, the National Institutes of Health, Cancer Research UK, the Brain Tumour Charity, and the Koch Institute Support (core) grant from the National Cancer Institute.

Taking RNAi from interesting science to impactful new treatments

Alnylam Pharmaceuticals is translating the promise of RNA interference (RNAi) research into a new class of powerful, gene-based therapies. These days Alnylam is not the only company developing RNAi-based medicines, but it is still a pioneer in the field. The company’s founders — MIT Institute Professor Phil Sharp, Professor David Bartel, Professor Emeritus Paul Schimmel, and former MIT postdocs Thomas Tuschl and Phillip Zamore — see Alnylam as a champion for the field more broadly.

Zach Winn | MIT News
May 13, 2024

There are many hurdles to clear before a research discovery becomes a life-changing treatment for patients. That’s especially true when the treatments being developed represent an entirely new class of medicines. But overcoming those obstacles can revolutionize our ability to treat diseases.

Few companies exemplify that process better than Alnylam Pharmaceuticals. Alnylam was founded by a group of MIT-affiliated researchers who believed in the promise of a technology — RNA interference, or RNAi.

The researchers had done foundational work to understand how RNAi, which is a naturally occurring process, works to silence genes through the degradation of messenger RNA. But it was their decision to found Alnylam in 2002 that attracted the funding and expertise necessary to turn their discoveries into a new class of medicines. Since that decision, Alnylam has made remarkable progress taking RNAi from an interesting scientific discovery to an impactful new treatment pathway.

Today Alnylam has five medicines approved by the U.S. Food and Drug Administration (one Alnylam-discovered RNAi therapeutic is licensed to Novartis) and a rapidly expanding clinical pipeline. The company’s approved medicines are for debilitating, sometimes fatal conditions that many patients have grappled with for decades with few other options.

The company estimates its treatments helped more than 5,000 patients in 2023 alone. Behind that number are patient stories that illustrate how Alnylam has changed lives. A mother of three says Alnylam’s treatments helped her take back control of her life after being bed-ridden with attacks associated with the rare genetic disease acute intermittent porphyria (AIP). Another patient reported that one of the company’s treatments helped her attend her daughter’s wedding. A third patient, who had left college due to frequent AIP attacks, was able to return to school.

These days Alnylam is not the only company developing RNAi-based medicines. But it is still a pioneer in the field, and the company’s founders — MIT Institute Professor Phil Sharp, Professor David Bartel, Professor Emeritus Paul Schimmel, and former MIT postdocs Thomas Tuschl and Phillip Zamore — see Alnylam as a champion for the field more broadly.

“Alnylam has published more than 250 scientific papers over 20 years,” says Sharp, who currently serves as chair of Alnylam’s scientific advisory board. “Not only did we do the science, not only did we translate it to benefit patients, but we also described every step. We established this as a modality to treat patients, and I’m very proud of that record.”

Pioneering RNAi development

MIT’s involvement in RNAi dates back to its discovery. Before Andrew Fire PhD ’83 shared a Nobel Prize for the discovery of RNAi in 1998, he worked on understanding how DNA was transcribed into RNA, as a graduate student in Sharp’s lab.

After leaving MIT, Fire and collaborators showed that double-stranded RNA could be used to silence specific genes in worms. But the biochemical mechanisms that allowed double-stranded RNA to work were unknown until MIT professors Sharp, Bartel, and Ruth Lehmann, along with Zamore and Tuschl, published foundational papers explaining the process. The researchers developed a system for studying RNAi and showed how RNAi can be controlled using different genetic sequences. Soon after Tuschl left MIT, he showed that a similar process could also be used to silence specific genes in human cells, opening up a new frontier in studying genes and ultimately treating diseases.

“Tom showed you could synthesize these small RNAs, transfect them into cells, and get a very specific knockdown of the gene that corresponded to that the small RNAs,” Bartel explains. “That discovery transformed biological research. The ability to specifically knockdown a mammalian gene was huge. You could suddenly study the function of any gene you were interested in by knocking it down and seeing what happens. … The research community immediately started using that approach to study the function of their favorite genes in mammalian cells.”

Beyond illuminating gene function, another application came to mind.

“Because almost all diseases are related to genes, could we take these small RNAs and silence genes to treat patients?” Sharp remembers wondering.

To answer the question, the researchers founded Alnylam in 2002. (They recruited Schimmel, a biotech veteran, around the same time.) But there was a lot of work to be done before the technology could be tried in patients. The main challenge was getting RNAi into the cytoplasm of the patients’ cells.

“Through work in Dave Bartel and Phil Sharp’s lab, among others, it became evident that to make RNAi into therapies, there were three problems to solve: delivery, delivery, and delivery,” says Alnylam Chief Scientific Officer Kevin Fitzgerald, who has been with the company since 2005.

Early on, Alnylam collaborated with MIT drug delivery expert and Institute Professor Bob Langer. Eventually, Alnylam developed the first lipid nanoparticles (LNPs) that could be used to encase RNA and deliver it into patient cells. LNPs were later used in the mRNA vaccines for Covid-19.

“Alnylam has invested over 20 years and more than $4 billion in RNAi to develop these new therapeutics,” Sharp says. “That is the means by which innovations can be translated to the benefit of society.”

From scientific breakthrough to patient bedside

Alnylam received its first FDA approval in 2018 for treatment of the polyneuropathy of hereditary transthyretin-mediated amyloidosis, a rare and fatal disease. It doubled as the first RNAi therapeutic to reach the market and the first drug approved to treat that condition in the United States.

“What I keep in mind is, at the end of the day for certain patients, two months is everything,” Fitzgerald says. “The diseases that we’re trying to treat progress month by month, day by day, and patients can get to a point where nothing is helping them. If you can move their disease by a stage, that’s huge.”

Since that first treatment, Alnylam has updated its RNAi delivery system — including by conjugating small interfering RNAs to molecules that help them gain entry to cells — and earned approvals to treat other rare genetic diseases along with high cholesterol (the treatment licensed to Novartis). All of those treatments primarily work by silencing genes that encode for the production of proteins in the liver, which has proven to be the easiest place to deliver RNAi molecules. But Alnylam’s team is confident they can deliver RNAi to other areas of the body, which would unlock a new world of treatment possibilities. The company has reported promising early results in the central nervous system and says a phase one study last year was the first RNAi therapeutic to demonstrate gene silencing in the human brain.

“There’s a lot of work being done at Alnylam and other companies to deliver these RNAis to other tissues: muscles, immune cells, lung cells, etc.,” Sharp says. “But to me the most interesting application is delivery to the brain. We think we have a therapeutic modality that can very specifically control the activity of certain genes in the nervous system. I think that’s extraordinarily important, for diseases from Alzheimer’s to schizophrenia and depression.”

The central nervous system work is particularly significant for Fitzgerald, who watched his father struggle with Parkinson’s.

“Our goal is to be in every organ in the human body, and then combinations of organs, and then combinations of targets within individual organs, and then combinations of targets within multi-organs,” Fitzgerald says. “We’re really at the very beginning of what this technology is going do for human health.”

It’s an exciting time for the RNAi scientific community, including many who continue to study it at MIT. Still, Alnylam will need to continue executing in its drug development efforts to deliver on that promise and help an expanding pool of patients.

“I think this is a real frontier,” Sharp says. “There’s major therapeutic need, and I think this technology could have a huge impact. But we have to prove it. That’s why Alnylam exists: to pursue new science that unlocks new possibilities and discover if they can be made to work. That, of course, also why MIT is here: to improve lives.”

De-tail-ing RNA regulation in eggs and early embryos

For a brief period during embryonic development, cells must rely on messenger RNAs provided by the maternal genome. In Developmental Cell, Bartel Lab members detail how cells regulate this limited supply of genetic material.

Greta Friar | Whitehead Institute
March 6, 2024
News brief: Davis Lab

Exploring the cellular neighborhood

Alison Biester | Department of Biology
March 12, 2024

New software allows scientists to model shapeshifting proteins in native cellular environments

Cells rely on complex molecular machines composed of protein assemblies to perform essential functions such as energy production, gene expression, and protein synthesis. To better understand how these machines work, scientists capture snapshots of them by isolating proteins from cells and using various methods to determine their structures. However, isolating proteins from cells also removes them from the context of their native environment, including protein interaction partners and cellular location.

Recently, cryogenic electron tomography (cryo-ET) has emerged as a way to observe proteins in their native environment by imaging frozen cells at different angles to obtain three-dimensional structural information. This approach is exciting because it allows researchers to directly observe how and where proteins associate with each other, revealing the cellular neighborhood of those interactions within the cell.

With the technology available to image proteins in their native environment, graduate student Barrett Powell wondered if he could take it one step further: what if molecular machines could be observed in action? In a paper published today in Nature Methods, Powell describes the method he developed, called tomoDRGN, for modeling structural differences of proteins in cryo-ET data that arise from protein motions or proteins binding to different interaction partners. These variations are known as structural heterogeneity. 

Although Powell had joined the Davis Lab as an experimental scientist, he recognized the potential impact of computational approaches in understanding structural heterogeneity within a cell. Previously, the Davis Lab developed a related methodology named cryoDRGN to understand structural heterogeneity in purified samples. As Powell and Associate Professor of Biology Joey Davis saw cryo-ET rising in prominence in the field, Powell took on the challenge of reimagining this framework to work in cells. 

When solving structures with purified samples, each particle is imaged only once. By contrast, cryo-ET data is collected by imaging each particle more than 40 times from different angles. That meant tomoDRGN needed to be able to merge the information from more than 40 images, which was where the project hit a roadblock: the amount of data led to an information overload.

To address the information overload, Powell successfully rebuilt the cryoDRGN model to prioritize only the highest-quality data. When imaging the same particle multiple times, radiation damage occurs. The images acquired earlier, therefore, tend to be of higher quality because the particles are less damaged.

“By excluding some of the lower quality data, the results were actually better than using all of the data–and the computational performance was substantially faster,” Powell says.

Just as Powell was beginning work on testing his model, he had a stroke of luck: the authors of a groundbreaking new study that visualized, for the first time, ribosomes inside cells at near-atomic resolution, shared their raw data on the Electric Microscopy Public Image Archive (EMPIAR). This dataset was an exemplary test case for Powell, through which he demonstrated that tomoDRGN could uncover structural heterogeneity within cryo-ET data. 

According to Powell, one exciting result is what tomoDRGN found surrounding a subset of ribosomes in the EMPIAR dataset. Some of the ribosomal particles were associated with a bacterial cell membrane and engaged in a process called cotranslational translocation. This occurs when a protein is being simultaneously synthesized and transported across a membrane. Researchers can use this result to make new hypotheses about how the ribosome functions with other protein machinery integral to transporting proteins outside of the cell, now guided by a structure of the complex in its native environment. 

After seeing that tomoDRGN could resolve structural heterogeneity from a structurally diverse dataset, Powell was curious: how small of a population could tomoDRGN identify? For that test, he chose a protein named apoferritin which is a commonly used benchmark for cryo-ET and is often treated as structurally homogeneous. Ferritin is a protein used for iron storage and is referred to as apoferritin when it lacks iron.

Surprisingly, in addition to the expected particles, tomoDRGN revealed a minor population of ferritin particles–with iron bound–making up just 2% of the dataset that was not previously reported. This result further demonstrated tomoDRGN’s ability to identify structural states that occur so infrequently that they would be averaged out with traditional analysis tools. 

Powell and other members of the Davis Lab are excited to see how tomoDRGN can be applied to further ribosomal studies and to other systems. Davis works on understanding how cells assemble, regulate, and degrade molecular machines, so the next steps include exploring ribosome biogenesis within cells in greater detail using this new tool.

“What are the possible states that we may be losing during purification?” Davis says. “Perhaps more excitingly, we can look at how they localize within the cell and what partners and protein complexes they may be interacting with.” 

How signaling proteins get to the mitochondrial surface

Whitehead Institute Member Jonathan Weissman and colleagues used large-scale systematic genetic screens to identify the molecules and pathways that populate the mitochondrial surface with important and diverse signaling proteins. They deciphered the logic by which the cell ensures the proper delivery of these proteins. These findings may have important implications for understanding the impact on health and disease when these processes go awry.

Greta Friar | Whitehead Institute
February 26, 2024