Scientists discover how mutations in a language gene produce speech deficits

Mutations of a gene called Foxp2 have been linked to a type of speech disorder called apraxia that makes it difficult to produce sequences of sound. A new study from MIT and National Yang Ming Chiao Tung University sheds light on how this gene controls the ability to produce speech.

In a study of mice, the researchers found that mutations in Foxp2 disrupt the formation of dendrites and neuronal synapses in the brain’s striatum, which plays important roles in the control of movement. Mice with these mutations also showed impairments in their ability to produce the high-frequency sounds that they use to communicate with other mice.

Those malfunctions arise because Foxp2 mutations prevent the proper assembly of motor proteins, which move molecules within cells, the researchers found.

“These mice have abnormal vocalizations, and in the striatum there are many cellular abnormalities,” says Ann Graybiel, an MIT Institute Professor, a member of MIT’s McGovern Institute for Brain Research, and an author of the paper. “This was an exciting finding. Who would have thought that a speech problem might come from little motors inside cells?”

Fu-Chin Liu PhD ’91, a professor at National Yang Ming Chiao Tung University in Taiwan, is the senior author of the study, which appears today in the journal Brain. Liu and Graybiel also worked together on a 2016 study of the potential link between Foxp2 and autism spectrum disorder. The lead authors of the new Brain paper are Hsiao-Ying Kuo and Shih-Yun Chen of National Yang Ming Chiao Tung University.

Speech control

Children with Foxp2-associated apraxia tend to begin speaking later than other children, and their speech is often difficult to understand. The disorder is believed to arise from impairments in brain regions, such as the striatum, that control the movements of the lips, mouth, and tongue. Foxp2 is also expressed in the brains of songbirds such as zebra finches and is critical to those birds’ ability to learn songs.

Foxp2 encodes a transcription factor, meaning that it can control the expression of many other target genes. Many species express Foxp2, but humans have a special form of Foxp2. In a 2014 study, Graybiel and colleagues found evidence that the human form of Foxp2, when expressed in mice, allowed the mice to accelerate the switch from declarative to procedural types of learning.

In that study, the researchers showed that mice engineered to express the human version of Foxp2, which differs from the mouse version by only two DNA base pairs, were much better at learning mazes and performing other tasks that require turning repeated actions into behavioral routines. Mice with human-like Foxp2 also had longer dendrites — the slender extensions that help neurons form synapses — in the striatum, which is involved in habit formation as well as motor control.

In the new study, the researchers wanted to explore how the Foxp2 mutation that has been linked with apraxia affects speech production, using ultrasonic vocalizations in mice as a proxy for speech. Many rodents and other animals such as bats produce these vocalizations to communicate with each other.

While previous studies, including the work by Liu and Graybiel in 2016, had suggested that Foxp2 affects dendrite growth and synapse formation, the mechanism for how that occurs was not known. In the new study, led by Liu, the researchers investigated one proposed mechanism, which is that Foxp2 affects motor proteins.

One of these molecular motors is the dynein protein complex, a large cluster of proteins that is responsible for shuttling molecules along microtubule scaffolds within cells.

“All kinds of molecules get shunted around to different places in our cells, and that’s certainly true of neurons,” Graybiel says. “There’s an army of tiny molecules that move molecules around in the cytoplasm or put them into the membrane. In a neuron, they may send molecules from the cell body all the way down the axons.”

A delicate balance

The dynein complex is made up of several other proteins. The most important of these is a protein called dynactin1, which interacts with microtubules, enabling the dynein motor to move along microtubules. In the new study, the researchers found that dynactin1 is one of the major targets of the Foxp2 transcription factor.

The researchers focused on the striatum, one of the regions where Foxp2 is most often found, and showed that the mutated version of Foxp2 is unable to suppress dynactin1 production. Without that brake in place, cells generate too much dynactin1. This upsets the delicate balance of dynein-dynactin1, which prevents the dynein motor from moving along microtubules.

Those motors are needed to shuttle molecules that are necessary for dendrite growth and synapse formation on dendrites. With those molecules stranded in the cell body, neurons are unable to form synapses to generate the proper electrophysiological signals they need to make speech production possible.

Mice with the mutated version of Foxp2 had abnormal ultrasonic vocalizations, which typically have a frequency of around 22 to 50 kilohertz. The researchers showed that they could reverse these vocalization impairments and the deficits in the molecular motor activity, dendritic growth, and electrophysiological activity by turning down the gene that encodes dynactin1.

Mutations of Foxp2 can also contribute to autism spectrum disorders and Huntington’s disease, through mechanisms that Liu and Graybiel previously studied in their 2016 paper and that many other research groups are now exploring. Liu’s lab is also investigating the potential role of abnormal Foxp2 expression in the subthalamic nucleus of the brain as a possible factor in Parkinson’s disease.

The research was funded by the Ministry of Science and Technology of Taiwan, the Ministry of Education of Taiwan, the U.S. National Institute of Mental Health, the Saks Kavanaugh Foundation, the Kristin R. Pressman and Jessica J. Pourian ’13 Fund, and Stephen and Anne Kott.

Yang Dan named winner of the 2023 Scolnick Prize in Neuroscience

The McGovern Institute announced today that the 2023 Edward M. Scolnick Prize in Neuroscience will be awarded to neurobiologist Yang Dan. Dan holds the Nan Fung Life Sciences Chancellor’s Chair in Neuroscience at the University of California, Berkeley, and has been a Howard Hughes Investigator since 2008. The Scolnick Prize is awarded annually by the McGovern Institute for outstanding achievements in neuroscience.

“Yang Dan’s systems-level experimentation to identify the cell types and circuits that control sleep cycles represents the highest level of neuroscience research,” says Robert Desimone, McGovern Institute director and chair of the selection committee. “Her work has defined precise mechanisms for how motor behaviors are suppressed during sleep and activated during arousal, with potential implications for the design of more targeted sedatives and the treatment of sleep disorders.”

Significance of sleep

Dan received a BS in Physics in 1988 from Peking University in China. She then moved to the US to obtain her PhD in neurobiology from Columbia University, in 1994, under the mentorship of Professor Mu-Ming Poo. Her doctoral research focused on mechanisms of plasticity at the neuromuscular synapse and was published in Science, Nature, and Neuron. During this time, she showed that the quantal release of neurotransmitters is not unique to neuronal cell types and, as one example, that retrograde signaling from muscle cells regulates the synaptic strength of the neuromuscular junction. For her postdoctoral training, Dan joined Clay Reid’s lab at The Rockefeller University and then accompanied Reid’s move to Harvard Medical School a short time later. Within just over two years, Yang had collected and analyzed neuronal recording data to support and develop key computational models of visual information coding – her two papers describing this work have been cited, together, over 900 times.

Yang Dan started her own laboratory in January 1997 when she joined the faculty of UC Berkeley’s Department of Molecular and Cell Biology as an assistant professor; she became a full professor in 2005. Dan’s lab became known for discoveries of how sensory inputs, especially visual inputs, are processed by the brain to influence behavior. Using electrophysiological recordings in model animals and computational analyses, her group worked out rules for how synaptic plasticity and neural connectivity, at the microcircuit and brain-wide level, contribute to learning and goal-directed behaviors.

Sleep recordings in various animal models and humans, shown in a research review by Yang Dan (2019 Annual Review of Neuroscience). (a) In nonmammalian animals such as jellyfish, Caenorhabditis elegans, Drosophila, and zebrafish, locomotor assay is used to measure sleep. (b) Examples of mouse EEG and EMG recordings during wakefulness and NREM and REM sleep. (c) Example polysomnography recordings from a healthy human subject during wakefulness and NREM (stage 3) and phasic REM sleep.

The Dan lab carved out a new research direction upon their discovery of mechanisms controlling rapid eye movement (REM) sleep, a state in which the brain is active and neuroplastic despite minimal sensory input. In their 2015 Nature paper, Dan’s group showed that, in mice, optogenetic activation of inhibitory neurons that project forward from the brainstem to the middle of the brain can instantaneously induce REM sleep. Since then, the Dan lab has published nearly a dozen primary research papers on the sleep-wake cycle that capitalize on the latest neural engineering techniques to record and control specific cell types and circuits in the brain. Most recently, she reported the discovery of neurons in the midbrain that receive wide-ranging inputs to coordinate active suppression of movement during REM and non-REM sleep with the release of movement during arousal. This circuit is key to the ability, known to exist in most animals, to experience sleep and even vivid dreaming without acting out. Dan’s discoveries are paving the way to a holistic understanding, from the molecular to macrocircuit levels, of how our bodies regulate sleep, an evolutionarily conserved behavior that is essential for survival.

Awards and honors

Dan was appointed as a Howard Hughes Medical Institute Investigator in 2008 and elected to the US National Academy of Sciences in 2018. She was awarded the Li Ka Shing Women in Science Award in 2007 and a Research Award for Innovation in Neuroscience from the Society for Neuroscience in 2009. She teaches summer courses at institutes around the world and has mentored 16 graduate students and 27 postdoctoral researchers, 25 of whom now run their own independent laboratories. Currently, Dan serves as an editorial board member on top-ranked science journals including Cell, Neuron, PNAS, and Current Opinion in Neurobiology.

Yang Dan will be awarded the Scolnick Prize on Wednesday, June 7, 2023. At 4:00 pm on that day, she will deliver a lecture titled “The how and why of sleep,” to be followed by a reception at the McGovern Institute, 43 Vassar Street (building 46, room 3002) in Cambridge. The event is free and open to the public.

 

 

Partnership with MIT Museum explores relationship between neuroscience and society

What does a healthy relationship between neuroscience and society look like? How do we set the conditions for that relationship to flourish? Researchers and staff at the McGovern Institute and the MIT Museum have been exploring these questions with a five-month planning grant from the Dana Foundation.

Between October 2022 and March 2023, the team tested the potential for an MIT Center for Neuroscience and Society through a series of MIT-sponsored events that were attended by students and faculty of nearby Cambridge Public Schools. The goal of the project was to learn more about what happens when the distinct fields of neuroscience, ethics, and public engagement are brought together to work side-by-side.

Researchers assist volunteer in mock MRI scanner
Gabrieli lab members Sadie Zacharek (left) and Shruti Nishith (right) demonstrate how the MRI mock scanner works with a student volunteer from the Cambridge Public Schools. Photo: Emma Skakel, MIT Museum

Middle schoolers visit McGovern

Over four days in February, more than 90 sixth graders from Rindge Avenue Upper Campus (RAUC) in Cambridge, Massachusetts, visited the McGovern Institute and participated in hands-on experiments and discussions about the ethical, legal, and social implications of neuroscience research. RAUC is one of four middle schools in the city of Cambridge with an economically, racially, and culturally diverse student population. The middle schoolers interacted with an MIT team led by McGovern Scientific Advisor Jill R. Crittenden, including seventeen McGovern neuroscientists, three MIT Museum outreach coordinators, and neuroethicist Stephanie Bird, a member of the Dana Foundation planning grant team.

“It is probably the only time in my life I will see a real human brain.” – RAUC student

The students participated in nine activities each day, including trials of brain-machine interfaces, close-up examinations of preserved human brains, a tour of McGovern’s imaging center in which students watched as their teacher’s brain was scanned, and a visit to the MIT Museum’s interactive Artificial Intelligence Gallery.

Imagine-IT, a brain-machine interface designed by a team of middle school students during a visit to the McGovern Institute.

To close out their visit, students worked in groups alongside experts to invent brain-computer interfaces designed to improve or enhance human abilities. At each step, students were introduced to ethical considerations through consent forms, questions regarding the use of animal and human brains, and the possible impacts of their own designs on individuals and society.

“I admit that prior to these four days, I would’ve been indifferent to the inclusion of children’s voices in a discussion about technically complex ethical questions, simply because they have not yet had any opportunity to really understand how these technologies work,” says one researcher involved in the visit. “But hearing the students’ questions and ideas has changed my perspective. I now believe it is critically important that all age groups be given a voice when discussing socially relevant issues, such as the ethics of brain computer interfaces or artificial intelligence.”

 

For more information on the proposed MIT Center for Neuroscience and Society, visit the MIT Museum website.

How Huntington’s disease affects different neurons

In patients with Huntington’s disease, neurons in a part of the brain called the striatum are among the hardest-hit. Degeneration of these neurons contributes to patients’ loss of motor control, which is one of the major hallmarks of the disease.

Neuroscientists at MIT have now shown that two distinct cell populations in the striatum are affected differently by Huntington’s disease. They believe that neurodegeneration of one of these populations leads to motor impairments, while damage to the other population, located in structures called striosomes, may account for the mood disorders that are often see in the early stages of the disease.

“As many as 10 years ahead of the motor diagnosis, Huntington’s patients can experience mood disorders, and one possibility is that the striosomes might be involved in these,” says Ann Graybiel, an MIT Institute Professor, a member of MIT’s McGovern Institute for Brain Research, and one of the senior authors of the study.

Using single-cell RNA sequencing to analyze the genes expressed in mouse models of Huntington’s disease and postmortem brain samples from Huntington’s patients, the researchers found that cells of the striosomes and another structure, the matrix, begin to lose their distinguishing features as the disease progresses. The researchers hope that their mapping of the striatum and how it is affected by Huntington’s could help lead to new treatments that target specific cells within the brain.

This kind of analysis could also shed light on other brain disorders that affect the striatum, such as Parkinson’s disease and autism spectrum disorder, the researchers say.

Myriam Heiman, an associate professor in MIT’s Department of Brain and Cognitive Sciences and a member of the Picower Institute for Learning and Memory, and Manolis Kellis, a professor of computer science in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and a member of the Broad Institute of MIT and Harvard, are also senior authors of the study. Ayano Matsushima, a McGovern Institute research scientist, and Sergio Sebastian Pineda, an MIT graduate student, are the lead authors of the paper, which appears in Nature Communications.

Neuron vulnerability

Huntington’s disease leads to degeneration of brain structures called the basal ganglia, which are responsible for control of movement and also play roles in other behaviors, as well as emotions. For many years, Graybiel has been studying the striatum, a part of the basal ganglia that is involved in making decisions that require evaluating the outcomes of a particular action.

Many years ago, Graybiel discovered that the striatum is divided into striosomes, which are clusters of neurons, and the matrix, which surrounds the striosomes. She has also shown that striosomes are necessary for making decisions that require an anxiety-provoking cost-benefit analysis.

In a 2007 study, Richard Faull of the University of Auckland discovered that in postmortem brain tissue from Huntington’s patients, the striosomes showed a great deal of degeneration. Faull also found that while those patients were alive, many of them had shown signs of mood disorders such as depression before their motor symptoms developed.

To further explore the connections between the striatum and the mood and motor effects of Huntington’s, Graybiel teamed up with Kellis and Heiman to study the gene expression patterns of striosomal and matrix cells. To do that, the researchers used single-cell RNA sequencing to analyze human brain samples and brain tissue from two mouse models of Huntington’s disease.

Within the striatum, neurons can be classified as either D1 or D2 neurons. D1 neurons are involved in the “go” pathway, which initiates an action, and D2 neurons are part of the “no-go” pathway, which suppresses an action. D1 and D2 neurons can both be found within either the striosomes and the matrix.

The analysis of RNA expression in each of these types of cells revealed that striosomal neurons are harder hit by Huntington’s than matrix neurons. Furthermore, within the striosomes, D2 neurons are more vulnerable than D1.

The researchers also found that these four major cell types begin to lose their identifying molecular identities and become more difficult to distinguish from one another in Huntington’s disease. “Overall, the distinction between striosomes and matrix becomes really blurry,” Graybiel says.

Striosomal disorders

The findings suggest that damage to the striosomes, which are known to be involved in regulating mood, may be responsible for the mood disorders that strike Huntington’s patients in the early stages of the disease. Later on, degeneration of the matrix neurons likely contributes to the decline of motor function, the researchers say.

In future work, the researchers hope to explore how degeneration or abnormal gene expression in the striosomes may contribute to other brain disorders.

Previous research has shown that overactivity of striosomes can lead to the development of repetitive behaviors such as those seen in autism, obsessive compulsive disorder, and Tourette’s syndrome. In this study, at least one of the genes that the researchers discovered was overexpressed in the striosomes of Huntington’s brains is also linked to autism.

Additionally, many striosome neurons project to the part of the brain that is most affected by Parkinson’s disease (the substantia nigra, which produces most of the brain’s dopamine).

“There are many, many disorders that probably involve the striatum, and now, partly through transcriptomics, we’re working to understand how all of this could fit together,” Graybiel says.

The research was funded by the Saks Kavanaugh Foundation, the CHDI Foundation, the National Institutes of Health, the Nancy Lurie Marks Family Foundation, the Simons Foundation, the JPB Foundation, the Kristin R. Pressman and Jessica J. Pourian ’13 Fund, and Robert Buxton.

Self-assembling proteins can store cellular “memories”

As cells perform their everyday functions, they turn on a variety of genes and cellular pathways. MIT engineers have now coaxed cells to inscribe the history of these events in a long protein chain that can be imaged using a light microscope.

Cells programmed to produce these chains continuously add building blocks that encode particular cellular events. Later, the ordered protein chains can be labeled with fluorescent molecules and read under a microscope, allowing researchers to reconstruct the timing of the events.

This technique could help shed light on the steps that underlie processes such as memory formation, response to drug treatment, and gene expression.

“There are a lot of changes that happen at organ or body scale, over hours to weeks, which cannot be tracked over time,” says Edward Boyden, the Y. Eva Tan Professor in Neurotechnology, a professor of biological engineering and brain and cognitive sciences at MIT, a Howard Hughes Medical Institute investigator, and a member of MIT’s McGovern Institute for Brain Research and Koch Institute for Integrative Cancer Research.

If the technique could be extended to work over longer time periods, it could also be used to study processes such as aging and disease progression, the researchers say.

Boyden is the senior author of the study, which appears today in Nature Biotechnology. Changyang Linghu, a former J. Douglas Tan Postdoctoral Fellow at the McGovern Institute, who is now an assistant professor at the University of Michigan, is the lead author of the paper.

Cellular history

Biological systems such as organs contain many different kinds of cells, all of which have distinctive functions. One way to study these functions is to image proteins, RNA, or other molecules inside the cells, which provide hints to what the cells are doing. However, most methods for doing this offer only a glimpse of a single moment in time, or don’t work well with very large populations of cells.

“Biological systems are often composed of a large number of different types of cells. For example, the human brain has 86 billion cells,” Linghu says. “To understand those kinds of biological systems, we need to observe physiological events over time in these large cell populations.”

To achieve that, the research team came up with the idea of recording cellular events as a series of protein subunits that are continuously added to a chain. To create their chains, the researchers used engineered protein subunits, not normally found in living cells, that can self-assemble into long filaments.

The researchers designed a genetically encoded system in which one of these subunits is continuously produced inside cells, while the other is generated only when a specific event occurs. Each subunit also contains a very short peptide called an epitope tag — in this case, the researchers chose tags called HA and V5. Each of these tags can bind to a different fluorescent antibody, making it easy to visualize the tags later on and determine the sequence of the protein subunits.

For this study, the researchers made production of the V5-containing subunit contingent on the activation of a gene called c-fos, which is involved in encoding new memories. HA-tagged subunits make up most of the chain, but whenever the V5 tag shows up in the chain, that means that c-fos was activated during that time.

“We’re hoping to use this kind of protein self-assembly to record activity in every single cell,” Linghu says. “It’s not only a snapshot in time, but also records past history, just like how tree rings can permanently store information over time as the wood grows.”

Recording events

In this study, the researchers first used their system to record activation of c-fos in neurons growing in a lab dish. The c-fos gene was activated by chemically induced activation of the neurons, which caused the V5 subunit to be added to the protein chain.

To explore whether this approach could work in the brains of animals, the researchers programmed brain cells of mice to generate protein chains that would reveal when the animals were exposed to a particular drug. Later, the researchers were able to detect that exposure by preserving the tissue and analyzing it with a light microscope.

The researchers designed their system to be modular, so that different epitope tags can be swapped in, or different types of cellular events can be detected, including, in principle, cell division or activation of enzymes called protein kinases, which help control many cellular pathways.

The researchers also hope to extend the recording period that they can achieve. In this study, they recorded events for several days before imaging the tissue. There is a tradeoff between the amount of time that can be recorded and the time resolution, or frequency of event recording, because the length of the protein chain is limited by the size of the cell.

“The total amount of information it could store is fixed, but we could in principle slow down or increase the speed of the growth of the chain,” Linghu says. “If we want to record for a longer time, we could slow down the synthesis so that it will reach the size of the cell within, let’s say two weeks. In that way we could record longer, but with less time resolution.”

The researchers are also working on engineering the system so that it can record multiple types of events in the same chain, by increasing the number of different subunits that can be incorporated.

The research was funded by the Hock E. Tan and K. Lisa Yang Center for Autism Research, John Doerr, the National Institutes of Health, the National Science Foundation, the U.S. Army Research Office, and the Howard Hughes Medical Institute.

Season’s Greetings from the McGovern Institute

This year’s holiday video (shown above) was inspired by Ev Fedorenko’s July 2022 Nature Neuroscience paper, which found similar patterns of brain activation and language selectivity across speakers of 45 different languages.

Universal language network

Ev Fedorenko uses the widely translated book “Alice in Wonderland” to test brain responses to different languages. Photo: Caitlin Cunningham

Over several decades, neuroscientists have created a well-defined map of the brain’s “language network,” or the regions of the brain that are specialized for processing language. Found primarily in the left hemisphere, this network includes regions within Broca’s area, as well as in other parts of the frontal and temporal lobes. Although roughly 7,000 languages are currently spoken and signed across the globe, the vast majority of those mapping studies have been done in English speakers as they listened to or read English texts.

To truly understand the cognitive and neural mechanisms that allow us to learn and process such diverse languages, Fedorenko and her team scanned the brains of speakers of 45 different languages while they listened to Alice in Wonderland in their native language. The results show that the speakers’ language networks appear to be essentially the same as those of native English speakers — which suggests that the location and key properties of the language network appear to be universal.

The many languages of McGovern

English may be the primary language used by McGovern researchers, but more than 35 other languages are spoken by scientists and engineers at the McGovern Institute. Our holiday video features 30 of these researchers saying Happy New Year in their native (or learned) language. Below is the complete list of languages included in our video. Expand each accordion to learn more about the speaker of that particular language and the meaning behind their new year’s greeting.

Silent synapses are abundant in the adult brain

MIT neuroscientists have discovered that the adult brain contains millions of “silent synapses” — immature connections between neurons that remain inactive until they’re recruited to help form new memories.

Until now, it was believed that silent synapses were present only during early development, when they help the brain learn the new information that it’s exposed to early in life. However, the new MIT study revealed that in adult mice, about 30 percent of all synapses in the brain’s cortex are silent.

The existence of these silent synapses may help to explain how the adult brain is able to continually form new memories and learn new things without having to modify existing conventional synapses, the researchers say.

“These silent synapses are looking for new connections, and when important new information is presented, connections between the relevant neurons are strengthened. This lets the brain create new memories without overwriting the important memories stored in mature synapses, which are harder to change,” says Dimitra Vardalaki, an MIT graduate student and the lead author of the new study.

Mark Harnett, an associate professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research, is the senior author of the paper, which appears today in Nature. Kwanghun Chung, an associate professor of chemical engineering at MIT, is also an author.

A surprising discovery

When scientists first discovered silent synapses decades ago, they were seen primarily in the brains of young mice and other animals. During early development, these synapses are believed to help the brain acquire the massive amounts of information that babies need to learn about their environment and how to interact with it. In mice, these synapses were believed to disappear by about 12 days of age (equivalent to the first months of human life).

However, some neuroscientists have proposed that silent synapses may persist into adulthood and help with the formation of new memories. Evidence for this has been seen in animal models of addiction, which is thought to be largely a disorder of aberrant learning.

Theoretical work in the field from Stefano Fusi and Larry Abbott of Columbia University has also proposed that neurons must display a wide range of different plasticity mechanisms to explain how brains can both efficiently learn new things and retain them in long-term memory. In this scenario, some synapses must be established or modified easily, to form the new memories, while others must remain much more stable, to preserve long-term memories.

In the new study, the MIT team did not set out specifically to look for silent synapses. Instead, they were following up on an intriguing finding from a previous study in Harnett’s lab. In that paper, the researchers showed that within a single neuron, dendrites — antenna-like extensions that protrude from neurons — can process synaptic input in different ways, depending on their location.

As part of that study, the researchers tried to measure neurotransmitter receptors in different dendritic branches, to see if that would help to account for the differences in their behavior. To do that, they used a technique called eMAP (epitope-preserving Magnified Analysis of the Proteome), developed by Chung. Using this technique, researchers can physically expand a tissue sample and then label specific proteins in the sample, making it possible to obtain super-high-resolution images.

The first thing we saw, which was super bizarre and we didn’t expect, was that there were filopodia everywhere.

While they were doing that imaging, they made a surprising discovery. “The first thing we saw, which was super bizarre and we didn’t expect, was that there were filopodia everywhere,” Harnett says.

Filopodia, thin membrane protrusions that extend from dendrites, have been seen before, but neuroscientists didn’t know exactly what they do. That’s partly because filopodia are so tiny that they are difficult to see using traditional imaging techniques.

After making this observation, the MIT team set out to try to find filopodia in other parts of the adult brain, using the eMAP technique. To their surprise, they found filopodia in the mouse visual cortex and other parts of the brain, at a level 10 times higher than previously seen. They also found that filopodia had neurotransmitter receptors called NMDA receptors, but no AMPA receptors.

A typical active synapse has both of these types of receptors, which bind the neurotransmitter glutamate. NMDA receptors normally require cooperation with AMPA receptors to pass signals because NMDA receptors are blocked by magnesium ions at the normal resting potential of neurons. Thus, when AMPA receptors are not present, synapses that have only NMDA receptors cannot pass along an electric current and are referred to as “silent.”

Unsilencing synapses

To investigate whether these filopodia might be silent synapses, the researchers used a modified version of an experimental technique known as patch clamping. This allowed them to monitor the electrical activity generated at individual filopodia as they tried to stimulate them by mimicking the release of the neurotransmitter glutamate from a neighboring neuron.

Using this technique, the researchers found that glutamate would not generate any electrical signal in the filopodium receiving the input, unless the NMDA receptors were experimentally unblocked. This offers strong support for the theory the filopodia represent silent synapses within the brain, the researchers say.

The researchers also showed that they could “unsilence” these synapses by combining glutamate release with an electrical current coming from the body of the neuron. This combined stimulation leads to accumulation of AMPA receptors in the silent synapse, allowing it to form a strong connection with the nearby axon that is releasing glutamate.

The researchers found that converting silent synapses into active synapses was much easier than altering mature synapses.

“If you start with an already functional synapse, that plasticity protocol doesn’t work,” Harnett says. “The synapses in the adult brain have a much higher threshold, presumably because you want those memories to be pretty resilient. You don’t want them constantly being overwritten. Filopodia, on the other hand, can be captured to form new memories.”

“Flexible and robust”

The findings offer support for the theory proposed by Abbott and Fusi that the adult brain includes highly plastic synapses that can be recruited to form new memories, the researchers say.

“This paper is, as far as I know, the first real evidence that this is how it actually works in a mammalian brain,” Harnett says. “Filopodia allow a memory system to be both flexible and robust. You need flexibility to acquire new information, but you also need stability to retain the important information.”

The researchers are now looking for evidence of these silent synapses in human brain tissue. They also hope to study whether the number or function of these synapses is affected by factors such as aging or neurodegenerative disease.

“It’s entirely possible that by changing the amount of flexibility you’ve got in a memory system, it could become much harder to change your behaviors and habits or incorporate new information,” Harnett says. “You could also imagine finding some of the molecular players that are involved in filopodia and trying to manipulate some of those things to try to restore flexible memory as we age.”

The research was funded by the Boehringer Ingelheim Fonds, the National Institutes of Health, the James W. and Patricia T. Poitras Fund at MIT, a Klingenstein-Simons Fellowship, and Vallee Foundation Scholarship, and a McKnight Scholarship.

How touch dampens the brain’s response to painful stimuli

McGovern Investigator Fan Wang. Photo: Caitliin Cunningham

When we press our temples to soothe an aching head or rub an elbow after an unexpected blow, it often brings some relief. It is believed that pain-responsive cells in the brain quiet down when these neurons also receive touch inputs, say scientists at MIT’s McGovern Institute, who for the first time have watched this phenomenon play out in the brains of mice.

The team’s discovery, reported November 16, 2022, in the journal Science Advances, offers researchers a deeper understanding of the complicated relationship between pain and touch and could offer some insights into chronic pain in humans. “We’re interested in this because it’s a common human experience,” says McGovern Investigator Fan Wang. “When some part of your body hurts, you rub it, right? We know touch can alleviate pain in this way.” But, she says, the phenomenon has been very difficult for neuroscientists to study.

Modeling pain relief

Touch-mediated pain relief may begin in the spinal cord, where prior studies have found pain-responsive neurons whose signals are dampened in response to touch. But there have been hints that the brain was involved too. Wang says this aspect of the response has been largely unexplored, because it can be hard to monitor the brain’s response to painful stimuli amidst all the other neural activity happening there—particularly when an animal moves.

So while her team knew that mice respond to a potentially painful stimulus on the cheek by wiping their faces with their paws, they couldn’t follow the specific pain response in the animals’ brains to see if that rubbing helped settle it down. “If you look at the brain when an animal is rubbing the face, movement and touch signals completely overwhelm any possible pain signal,” Wang explains.

She and her colleagues have found a way around this obstacle. Instead of studying the effects of face-rubbing, they have focused their attention on a subtler form of touch: the gentle vibrations produced by the movement of the animals’ whiskers. Mice use their whiskers to explore, moving them back and forth in a rhythmic motion known as whisking to feel out their environment. This motion activates touch receptors in the face and sends information to the brain in the form of vibrotactile signals. The human brain receives the same kind of touch signals when a person shakes their hand as they pull it back from a painfully hot pan—another way we seek touch-mediate pain relief.

If you look at the brain when an animal is rubbing the face, movement and touch signals completely overwhelm any possible pain signal, says Wang.

Wang and her colleagues found that this whisker movement alters the way mice respond to bothersome heat or a poke on the face—both of which usually lead to face rubbing. “When the unpleasant stimuli were applied in the presence of their self-generated vibrotactile whisking…they respond much less,” she says. Sometimes, she says, whisking animals entirely ignore these painful stimuli.

In the brain’s somatosensory cortex, where touch and pain signals are processed, the team found signaling changes that seem to underlie this effect. “The cells that preferentially respond to heat and poking are less frequently activated when the mice are whisking,” Wang says. “They’re less likely to show responses to painful stimuli.” Even when whisking animals did rub their faces in response to painful stimuli, the team found that neurons in the brain took more time to adopt the firing patterns associated with that rubbing movement. “When there is a pain stimulation, usually the trajectory the population dynamics quickly moved to wiping. But if you already have whisking, that takes much longer,” Wang says.

Wang notes that even in the fraction of a second before provoked mice begin rubbing their faces, when the animals are relatively still, it can be difficult to sort out which brain signals are related to perceiving heat and poking and which are involved in whisker movement. Her team developed computational tools to disentangle these, and are hoping other neuroscientists will use the new algorithms to make sense of their own data.

Whisking’s effects on pain signaling seem to depend on dedicated touch-processing circuitry that sends tactile information to the somatosensory cortex from a brain region called the ventral posterior thalamus. When the researchers blocked that pathway, whisking no longer dampened the animals’ response to painful stimuli. Now, Wang says, she and her team are eager to learn how this circuitry works with other parts of the brain to modulate the perception and response to painful stimuli.

Wang says the new findings might shed light on a condition called thalamic pain syndrome, a chronic pain disorder that can develop in patients after a stroke that affects the brain’s thalamus. “Such strokes may impair the functions of thalamic circuits that normally relay pure touch signals and dampen painful signals to the cortex,” she says.

RNA-sensing system controls protein expression in cells based on specific cell states

Researchers at the Broad Institute of MIT and Harvard and the McGovern Institute for Brain Research at MIT have developed a system that can detect a particular RNA sequence in live cells and produce a protein of interest in response. Using the technology, the team showed how they could identify specific cell types, detect and measure changes in the expression of individual genes, track transcriptional states, and control the production of proteins encoded by synthetic mRNA.

The platform, called Reprogrammable ADAR Sensors, or RADARS, even allowed the team to target and kill a specific cell type. The team said RADARS could one day help researchers detect and selectively kill tumor cells, or edit the genome in specific cells. The study appears today in Nature Biotechnology and was led by co-first authors Kaiyi Jiang (MIT), Jeremy Koob (Broad), Xi Chen (Broad), Rohan Krajeski (MIT), and Yifan Zhang (Broad).

“One of the revolutions in genomics has been the ability to sequence the transcriptomes of cells,” said Fei Chen, a core institute member at the Broad, Merkin Fellow, assistant professor at Harvard University, and co-corresponding author on the study. “That has really allowed us to learn about cell types and states. But, often, we haven’t been able to manipulate those cells specifically. RADARS is a big step in that direction.”

“Right now, the tools that we have to leverage cell markers are hard to develop and engineer,” added Omar Abudayyeh, a McGovern Institute Fellow and co-corresponding author on the study. “We really wanted to make a programmable way of sensing and responding to a cell state.”

Jonathan Gootenberg, who is also a McGovern Institute Fellow and co-corresponding author, says that their team was eager to build a tool to take advantage of all the data provided by single-cell RNA sequencing, which has revealed a vast array of cell types and cell states in the body.

“We wanted to ask how we could manipulate cellular identities in a way that was as easy as editing the genome with CRISPR,” he said. “And we’re excited to see what the field does with it.” 

Omar Abudayyeh, Jonathan Gootenberg and Fei Chen at the Broad Institute
Study authors (from left to right) Omar Abudayyeh, Jonathan Gootenberg, and Fei Chen. Photo: Namrita Sengupta

Repurposing RNA editing

The RADARS platform generates a desired protein when it detects a specific RNA by taking advantage of RNA editing that occurs naturally in cells.

The system consists of an RNA containing two components: a guide region, which binds to the target RNA sequence that scientists want to sense in cells, and a payload region, which encodes the protein of interest, such as a fluorescent signal or a cell-killing enzyme. When the guide RNA binds to the target RNA, this generates a short double-stranded RNA sequence containing a mismatch between two bases in the sequence — adenosine (A) and cytosine (C). This mismatch attracts a naturally occurring family of RNA-editing proteins called adenosine deaminases acting on RNA (ADARs).

In RADARS, the A-C mismatch appears within a “stop signal” in the guide RNA, which prevents the production of the desired payload protein. The ADARs edit and inactivate the stop signal, allowing for the translation of that protein. The order of these molecular events is key to RADARS’s function as a sensor; the protein of interest is produced only after the guide RNA binds to the target RNA and the ADARs disable the stop signal.

The team tested RADARS in different cell types and with different target sequences and protein products. They found that RADARS distinguished between kidney, uterine, and liver cells, and could produce different fluorescent signals as well as a caspase, an enzyme that kills cells. RADARS also measured gene expression over a large dynamic range, demonstrating their utility as sensors.

Most systems successfully detected target sequences using the cell’s native ADAR proteins, but the team found that supplementing the cells with additional ADAR proteins increased the strength of the signal. Abudayyeh says both of these cases are potentially useful; taking advantage of the cell’s native editing proteins would minimize the chance of off-target editing in therapeutic applications, but supplementing them could help produce stronger effects when RADARS are used as a research tool in the lab.

On the radar

Abudayyeh, Chen, and Gootenberg say that because both the guide RNA and payload RNA are modifiable, others can easily redesign RADARS to target different cell types and produce different signals or payloads. They also engineered more complex RADARS, in which cells produced a protein if they sensed two RNA sequences and another if they sensed either one RNA or another. The team adds that similar RADARS could help scientists detect more than one cell type at the same time, as well as complex cell states that can’t be defined by a single RNA transcript.

Ultimately, the researchers hope to develop a set of design rules so that others can more easily develop RADARS for their own experiments. They suggest other scientists could use RADARS to manipulate immune cell states, track neuronal activity in response to stimuli, or deliver therapeutic mRNA to specific tissues.

“We think this is a really interesting paradigm for controlling gene expression,” said Chen. “We can’t even anticipate what the best applications will be. That really comes from the combination of people with interesting biology and the tools you develop.”

This work was supported by the The McGovern Institute Neurotechnology (MINT) program, the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience, the G. Harold & Leila Y. Mathers Charitable Foundation, Massachusetts Institute of Technology, Impetus Grants, the Cystic Fibrosis Foundation, Google Ventures, FastGrants, the McGovern Institute, National Institutes of Health, the Burroughs Wellcome Fund, the Searle Scholars Foundation, the Harvard Stem Cell Institute, and the Merkin Institute.

A “golden era” to study the brain

As an undergraduate, Mitch Murdock was a rare science-humanities double major, specializing in both English and molecular, cellular, and developmental biology at Yale University. Today, as a doctoral student in the MIT Department of Brain and Cognitive Sciences, he sees obvious ways that his English education expanded his horizons as a neuroscientist.

“One of my favorite parts of English was trying to explore interiority, and how people have really complicated experiences inside their heads,” Murdock explains. “I was excited about trying to bridge that gap between internal experiences of the world and that actual biological substrate of the brain.”

Though he can see those connections now, it wasn’t until after Yale that Murdock became interested in brain sciences. As an undergraduate, he was in a traditional molecular biology lab. He even planned to stay there after graduation as a research technician; fortunately, though, he says his advisor Ron Breaker encouraged him to explore the field. That’s how Murdock ended up in a new lab run by Conor Liston, an associate professor at Weill Cornell Medicine, who studies how factors such as stress and sleep regulate the modeling of brain circuits.

It was in Liston’s lab that Murdock was first exposed to neuroscience and began to see the brain as the biological basis of the philosophical questions about experience and emotion that interested him. “It was really in his lab where I thought, ‘Wow, this is so cool. I have to do a PhD studying neuroscience,’” Murdock laughs.

During his time as a research technician, Murdock examined the impact of chronic stress on brain activity in mice. Specifically, he was interested in ketamine, a fast-acting antidepressant prone to being abused, with the hope that better understanding how ketamine works will help scientists find safer alternatives. He focused on dendritic spines, small organelles attached to neurons that help transmit electrical signals between neurons and provide the physical substrate for memory storage. His findings, Murdock explains, suggested that ketamine works by recovering dendritic spines that can be lost after periods of chronic stress.

After three years at Weill Cornell, Murdock decided to pursue doctoral studies in neuroscience, hoping to continue some of the work he started with Liston. He chose MIT because of the research being done on dendritic spines in the lab of Elly Nedivi, the William R. (1964) and Linda R. Young Professor of Neuroscience in The Picower Institute for Learning and Memory.

Once again, though, the opportunity to explore a wider set of interests fortuitously led Murdock to a new passion. During lab rotations at the beginning of his PhD program, Murdock spent time shadowing a physician at Massachusetts General Hospital who was working with Alzheimer’s disease patients.

“Everyone knows that Alzheimer’s doesn’t have a cure. But I realized that, really, if you have Alzheimer’s disease, there’s very little that can be done,” he says. “That was a big wake-up call for me.”

After that experience, Murdock strategically planned his remaining lab rotations, eventually settling into the lab of Li-Huei Tsai, the Picower Professor of Neuroscience and the director of the Picower Institute. For the past five years, Murdock has worked with Tsai on various strands of Alzheimer’s research.

In one project, for example, members of the Tsai lab have shown how certain kinds of non-invasive light and sound stimulation induce brain activity that can improve memory loss in mouse models of Alzheimer’s. Scientists think that, during sleep, small movements in blood vessels drive spinal fluid into the brain, which, in turn, flushes out toxic metabolic waste. Murdock’s research suggests that certain kinds of stimulation might drive a similar process, flushing out waste that can exacerbate memory loss.

Much of his work is focused on the activity of single cells in the brain. Are certain neurons or types of neurons genetically predisposed to degenerate, or do they break down randomly? Why do certain subtypes of cells appear to be dysfunctional earlier on in the course of Alzheimer’s disease? How do changes in blood flow in vascular cells affect degeneration? All of these questions, Murdock believes, will help scientists better understand the causes of Alzheimer’s, which will translate eventually into developing cures and therapies.

To answer these questions, Murdock relies on new single-cell sequencing techniques that he says have changed the way we think about the brain. “This has been a big advance for the field, because we know there are a lot of different cell types in the brain, and we think that they might contribute differentially to Alzheimer’s disease risk,” says Murdock. “We can’t think of the brain as only about neurons.”

Murdock says that that kind of “big-picture” approach — thinking about the brain as a compilation of many different cell types that are all interacting — is the central tenet of his research. To look at the brain in the kind of detail that approach requires, Murdock works with Ed Boyden, the Y. Eva Tan Professor in Neurotechnology, a professor of biological engineering and brain and cognitive sciences at MIT, a Howard Hughes Medical Institute investigator, and a member of MIT’s McGovern Institute for Brain Research and Koch Institute for Integrative Cancer Research. Working with Boyden has allowed Murdock to use new technologies such as expansion microscopy and genetically encoded sensors to aid his research.

That kind of new technology, he adds, has helped blow the field wide open. “This is such a cool time to be a neuroscientist because the tools available now make this a golden era to study the brain.” That rapid intellectual expansion applies to the study of Alzheimer’s as well, including newly understood connections between the immune system and Alzheimer’s — an area in which Murdock says he hopes to continue after graduation.

Right now, though, Murdock is focused on a review paper synthesizing some of the latest research. Given the mountains of new Alzheimer’s work coming out each year, he admits that synthesizing all the data is a bit “crazy,” but he couldn’t be happier to be in the middle of it. “There’s just so much that we are learning about the brain from these new techniques, and it’s just so exciting.”