Author: Julie Pryor

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

by Allessandra DiCorato | Broad Institute |

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.

Personal pursuits

by Jennifer Michalowski |

This story originally appeared in the Fall 2022 issue of BrainScan.

***

Many neuroscientists were drawn to their careers out of curiosity and wonder. Their deep desire to understand how the brain works drew them into the lab and keeps them coming back, digging deeper and exploring more each day. But for some, the work is more personal.

Several McGovern faculty say they entered their field because someone in their lives was dealing with a brain disorder that they wanted to better understand. They are committed to unraveling the basic biology of those conditions, knowing that knowledge is essential to guide the development of better treatments.

The distance from basic research to clinical progress is shortening, and many young neuroscientists hope not just to deepen scientific understanding of the brain, but to have direct impact on the lives of patients. Some want to know why people they love are suffering from neurological disorders or mental illness; others seek to understand the ways in which their own brains work differently than others. But above all, they want better treatments for people affected by such disorders.

Seeking answers

That’s true for Kian Caplan, a graduate student in MIT’s Department of Brain and Cognitive Sciences who was diagnosed with Tourette syndrome around age 13. At the time, learning that the repetitive, uncontrollable movements and vocal tics he had been making for most of his life were caused by a neurological disorder was something of a relief. But it didn’t take long for Caplan to realize his diagnosis came with few answers.

Graduate student Kian Caplan studies the brain circuits associated with Tourette syndrome and obsessive-compulsive disorder in Guoping Feng and Fan Wang’s labs at the McGovern Institute. Photo: Steph Stevens

Tourette syndrome has been estimated to occur in about six of every 1,000 children, but its neurobiology remains poorly understood.

“The doctors couldn’t really explain why I can’t control the movements and sounds I make,” he says. “They couldn’t really explain why my symptoms wax and wane, or why the tics I have aren’t always the same.”

That lack of understanding is not just frustrating for curious kids like Caplan. It means that researchers have been unable to develop treatments that target the root cause of Tourette syndrome. Drugs that dampen signaling in parts of the brain that control movement can help suppress tics, but not without significant side effects. Caplan has tried those drugs. For him, he says, “they’re not worth the suppression.”

Advised by Fan Wang and McGovern Associate Director Guoping Feng, Caplan is looking for answers. A mouse model of obsessive-compulsive disorder developed in Feng’s lab was recently found to exhibit repetitive movements similar to those of people with Tourette syndrome, and Caplan is working to characterize those tic-like movements. He will use the mouse model to examine the brain circuits underlying the two conditions, which often co-occur in people. Broadly, researchers think Tourette syndrome arises due to dysregulation of cortico-striatal-thalamo-cortical circuits, which connect distant parts of the brain to control movement. Caplan and Wang suspect that the brainstem — a structure found where the brain connects to the spinal cord, known for organizing motor movement into different modules — is probably involved, too.

Wang’s research group studies the brainstem’s role in movement, but she says that like most researchers, she hadn’t considered its role in Tourette syndrome until Caplan joined her lab. That’s one reason Caplan, who has long been a mentor and advocate for students with neurodevelopmental disorders, thinks neuroscience needs more neurodiversity.

“I think we need more representation in basic science research by the people who actually live with those conditions,” he says. Their experiences can lead to insights that may be inaccessible to others, he says, but significant barriers in academia often prevent this kind of representation. Caplan wants to see institutions make systemic changes to ensure that neurodiverse and otherwise minority individuals are able to thrive in academia. “I’m not an exception,” he says, “there should be more people like me here, but the present system makes that incredibly difficult.”

Overcoming adversity

Like Caplan, Lace Riggs faced significant challenges in her pursuit to study the brain. She grew up in Southern California’s Inland Empire, where issues of social disparity, chronic stress, drug addiction, and mental illness were a part of everyday life.

Postdoctoral fellow Lace Riggs studies the origins of neurodevelopmental conditions in Guoping Feng’s lab at the McGovern Institute. Photo: Lace Riggs

“Living in severe poverty and relying on government assistance without access to adequate education and resources led everyone I know and love to suffer tremendously, myself included,” says Riggs, a postdoctoral fellow in the Feng lab.

“There are not a lot of people like me who make it to this stage,” says Riggs, who has lost friends and family members to addiction, mental illness, and suicide. “There’s a reason for that,” she adds. “It’s really, really difficult to get through the educational system and to overcome socioeconomic barriers.”

Today, Riggs is investigating the origins of neurodevelopmental conditions, hoping to pave the way to better treatments for brain disorders by uncovering the molecular changes that alter the structure and function of neural circuits.

Riggs says that the adversities she faced early in life offered valuable insights in the pursuit of these goals. She first became interested in the brain because she wanted to understand how our experiences have a lasting impact on who we are — including in ways that leave people vulnerable to psychiatric problems.

“While the need for more effective treatments led me to become interested in psychiatry, my fascination with the brain’s unique ability to adapt is what led me to neuroscience,” says Riggs.

After finishing high school, Riggs attended California State University in San Bernardino and became the only member of her family to attend university or attempt a four-year degree. Today, she spends her days working with mice that carry mutations linked to autism or ADHD in humans, studying the animals’ behavior and monitoring their neural activity. She expects that aberrant neural circuit activity in these conditions may also contribute to mood disorders, whose origins are harder to tease apart because they often arise when genetic and environmental factors intersect. Ultimately, Riggs says, she wants to understand how our genes dictate whether an experience will alter neural signaling and impact mental health in a long-lasting way.

Riggs uses patch clamp electrophysiology to record the strength of inhibitory and excitatory synaptic input onto individual neurons (white arrow) in an animal model of autism. Image: Lace Riggs

“If we understand how these long-lasting synaptic changes come about, then we might be able to leverage these mechanisms to develop new and more effective treatments.”

While the turmoil of her childhood is in the past, Riggs says it is not forgotten — in part, because of its lasting effects on her own mental health.  She talks openly about her ongoing struggle with social anxiety and complex post-traumatic stress disorder because she is passionate about dismantling the stigma surrounding these conditions. “It’s something I have to deal with every day,” Riggs says. That means coping with symptoms like difficulty concentrating, hypervigilance, and heightened sensitivity to stress. “It’s like a constant hum in the background of my life, it never stops,” she says.

“I urge all of us to strive, not only to make scientific discoveries to move the field forward,” says Riggs, “but to improve the accessibility of this career to those whose lived experiences are required to truly accomplish that goal.”

Making and breaking habits

by Shafaq Zia |

As part of our Ask the Brain series, science writer Shafaq Zia explores the question, “How are habits formed in the brain?”

____

Have you ever wondered why it is so hard to break free of bad habits like nail biting or obsessive social networking?

When we repeat an action over and over again, the behavioral pattern becomes automated in our brain, according to Jill R. Crittenden, molecular biologist and scientific advisor at McGovern Institute for Brain Research at MIT. For over a decade, Crittenden worked as a research scientist in the lab of Ann Graybiel, where one of the key questions scientists are working to answer is, how are habits formed?

Making habits

To understand how certain actions get wired in our neural pathways, this team of McGovern researchers experimented with rats, who were trained to run down a maze to receive a reward. If they turned left, they would get rich chocolate milk and for turning right, only sugar water. With this, the scientists wanted to see whether these animals could “learn to associate a cue with which direction they should turn in the maze in order to get the chocolate milk reward.”

Over time, the rats grew extremely habitual in their behavior; “they always turned the the correct direction and the places where their paws touched, in a fairly long maze, were exactly the same every time,” said Crittenden.

This isn’t a coincidence. When we’re first learning to do something, the frontal lobe and basal ganglia of the brain are highly active and doing a lot of calculations. These brain regions work together to associate behaviors with thoughts, emotions, and, most importantly, motor movements. But when we repeat an action over and over again, like the rats running down the maze, our brains become more efficient and fewer neurons are required to achieve the goal. This means, the more you do something, the easier it gets to carry it out because the behavior becomes literally etched in our brain as our motor movements.

But habits are complicated and they come in many different flavors, according to Crittenden. “I think we don’t have a great handle on how the differences [in our many habits] are separable neurobiologically, and so people argue a lot about how do you know that something’s a habit.”

The easiest way for scientists to test this in rodents is to see if the animal engages in the behavior even in the absence of reward. In this particular experiment, the researchers take away the reward, chocolate milk, to see whether the rats continue to run down the maze correctly. And to take it even a step further, they mix the chocolate milk with lithium chloride, which would upset the rat’s stomach. Despite all this, the rats continue to run down the maze and turn left towards the chocolate milk, as they had learnt to do over and over again.

Breaking habits

So does that mean once a habit is formed, it is impossible to shake it? Not quite. But it is tough. Rewards are a key building block to forming habits because our dopamine levels surge when we learn that an action is unexpectedly rewarded. For example, when the rats first learn to run down the maze, they’re motivated to receive the chocolate milk.

But things get complicated once the habit is formed. Researchers have found that this dopamine surge in response to reward ceases after a behavior becomes a habit. Instead the brain begins to release dopamine at the first cue or action that was previously learned to lead to the reward, so we are motivated to engage in the full behavioral sequence anyway, even if the reward isn’t there anymore.

This means we don’t have as much self-control as we think we do, which may also be the reason why it’s so hard to break the cycle of addiction. “People will report that they know this is bad for them. They don’t want it. And nevertheless, they select that action,” said Crittenden.

One common method to break the behavior, in this case, is called extinction. This is where psychologists try to weaken the association between the cue and the reward that led to habit formation in the first place. For example, if the rat no longer associates the cue to run down the maze with a reward, it will stop engaging in that behavior.

So the next time you beat yourself up over being unable to stick to a diet or sleep at a certain time, give yourself some grace and know that with consistency, a new, healthier habit can be born.

MIT scientists discover new antiviral defense system in bacteria

by Leah Eisenstadt | Broad Institute |

Bacteria use a variety of defense strategies to fight off viral infection, and some of these systems have led to groundbreaking technologies, such as CRISPR-based gene-editing. Scientists predict there are many more antiviral weapons yet to be found in the microbial world.

A team led by researchers at the Broad Institute of MIT and Harvard and the McGovern Institute for Brain Research at MIT has discovered and characterized one of these unexplored microbial defense systems. They found that certain proteins in bacteria and archaea (together known as prokaryotes) detect viruses in surprisingly direct ways, recognizing key parts of the viruses and causing the single-celled organisms to commit suicide to quell the infection within a microbial community. The study is the first time this mechanism has been seen in prokaryotes and shows that organisms across all three domains of life — bacteria, archaea, and eukaryotes (which includes plants and animals) — use pattern recognition of conserved viral proteins to defend against pathogens.

The study appears in Science.

“This work demonstrates a remarkable unity in how pattern recognition occurs across very different organisms,” said senior author Feng Zhang, who is a core institute member at the Broad, the James and Patricia Poitras Professor of Neuroscience at MIT, a professor of brain and cognitive sciences and biological engineering at MIT, and an investigator at MIT’s McGovern Institute and the Howard Hughes Medical Institute. “It’s been very exciting to integrate genetics, bioinformatics, biochemistry, and structural biology approaches in one study to understand this fascinating molecular system.”

Microbial armory

In an earlier study, the researchers scanned data on the DNA sequences of hundreds of thousands of bacteria and archaea, which revealed several thousand genes harboring signatures of microbial defense. In the new study, they homed in on a handful of these genes encoding enzymes that are members of the STAND ATPase family of proteins, which in eukaryotes are involved in the innate immune response.

In humans and plants, the STAND ATPase proteins fight infection by recognizing patterns in a pathogen itself or in the cell’s response to infection. In the new study, the researchers wanted to know if the proteins work the same way in prokaryotes to defend against infection. The team chose a few STAND ATPase genes from the earlier study, delivered them to bacterial cells, and challenged those cells with bacteriophage viruses. The cells underwent a dramatic defensive response and survived.

The scientists next wondered which part of the bacteriophage triggers that response, so they delivered viral genes to the bacteria one at a time. Two viral proteins elicited an immune response: the portal, a part of the virus’s capsid shell, which contains viral DNA; and the terminase, the molecular motor that helps assemble the virus by pushing the viral DNA into the capsid. Each of these viral proteins activated a different STAND ATPase to protect the cell.

The finding was striking and unprecedented. Most known bacterial defense systems work by sensing viral DNA or RNA, or cellular stress due to the infection. These bacterial proteins were instead directly sensing key parts of the virus.

The team next showed that bacterial STAND ATPase proteins could recognize diverse portal and terminase proteins from different phages. “It’s surprising that bacteria have these highly versatile sensors that can recognize all sorts of different phage threats that they might encounter,” said co-first author Linyi Gao, a junior fellow in the Harvard Society of Fellows and a former graduate student in the Zhang lab.

Structural analysis

For a detailed look at how the microbial STAND ATPases detect the viral proteins, the researchers used cryo-electron microscopy to examine their molecular structure when bound to the viral proteins. “By analyzing the structure, we were able to precisely answer a lot of the questions about how these things actually work,” said co-first author Max Wilkinson, a postdoctoral researcher in the Zhang lab.

The team saw that the portal or terminase protein from the virus fits within a pocket in the STAND ATPase protein, with each STAND ATPase protein grasping one viral protein. The STAND ATPase proteins then group together in sets of four known as tetramers, which brings together key parts of the bacterial proteins called effector domains. This activates the proteins’ endonuclease function, shredding cellular DNA and killing the cell.

The tetramers bound viral proteins from other bacteriophages just as tightly, demonstrating that the STAND ATPases sense the viral proteins’ three-dimensional shape, rather than their sequence. This helps explain how one STAND ATPase can recognize dozens of different viral proteins. “Regardless of sequence, they all fit like a hand in a glove,” said Wilkinson.

STAND ATPases in humans and plants also work by forming multi-unit complexes that activate specific functions in the cell. “That’s the most exciting part of this work,” said Strecker. “To see this across the domains of life is unprecedented.”

The research was funded in part by the National Institutes of Health, the Howard Hughes Medical Institute, Open Philanthropy, the Edward Mallinckrodt, Jr. Foundation, the Poitras Center for Psychiatric Disorders Research, the Hock E. Tan and K. Lisa Yang Center for Autism Research, the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience, the Phillips family, J. and P. Poitras, and the BT Charitable Foundation.

Why do we dream?

by Shafaq Zia |

As part of our Ask the Brain series, science writer Shafaq Zia answers the question, “Why do we dream?”

_____

One night, Albert Einstein dreamt that he was walking through a farm where he found a herd of cows against an electric fence. When the farmer switched on the fence, the cows suddenly jumped back, all at the same time. But to the farmer’s eyes, who was standing at the other end of the field, they seemed to have jumped one after another, in a wave formation. Einstein woke up and the Theory of Relativity was born.

Dreaming is one of the oldest biological phenomena; for as long as humans have slept, they’ve dreamt. But through most of our history, dreams have remained mystified, leaving scientists, philosophers, and artists alike searching for meaning.

In many aboriginal cultures, such as the Esa Eja community in Peruvian Amazon, dreaming is a sacred practice for gaining knowledge, or solving a problem, through the dream narrative. But in the last century or so, technological advancements have allowed neuroscientists to take up dreams as a matter of scientific inquiry in order to answer a much-pondered question — what is the purpose of dreaming?

Falling asleep

The human brain is a fascinating place. It is composed of approximately 80 billion neurons and it is their combined electrical chatter that generates oscillations known as brain waves. There are five types of brain waves —  alpha, beta, theta, delta, and gamma — that each indicate a different state between sleep and wakefulness.

Using EEG, a test that records electrical activity in the brain, scientists have identified that when we’re awake, our brain emits beta and gamma waves. These tend to have a stimulating effect and help us remain actively engaged in mental activities.

The differently named frequency bands of neural oscillations, or brainwaves: delta, theta, alpha, beta, and gamma.

But during the transition to sleep, the number of beta waves lowers significantly and the brain produces high levels of alpha waves. These waves regulate attention and help filter out distractions. A recent study led by McGovern Institute Director Robert Desimone, showed that people can actually enhance their attention by controlling their own alpha brain waves using neurofeedback training. It’s unknown how long these effects might last and whether this kind of control could be achieved with other types of brain waves, but the researchers are now planning additional studies to explore these questions.

Alpha waves are also produced when we daydream, meditate, or listen to the sound of rain. As our minds wander, many parts of the brain are engaged, including a specialized system called the “default mode network.” Disturbances in this network, explains Susan Whitfield-Gabrieli, a professor of psychology at Northeastern University and a McGovern Institute research affiliate, have been linked to various brain disorders including schizophrenia, depression and ADHD. By identifying the brain circuits associated with mind wandering, she says, we can begin to develop better treatment options for people suffering from these disorders.

Finally, as we enter a dreamlike state, the prefrontal cortex of the brain, responsible for keeping impulses in check, slowly grows less active. This is when there’s a spur in theta waves that leads to an unconstrained window of consciousness; there is little censorship from the mind, allowing for visceral dreams and creative thoughts.

The dreaming brain

“Every time you learn something, it happens so quickly,” said Dheeraj Roy, postdoctoral fellow in Guoping Feng’s lab at the McGovern Institute. “The brain is continuously recording information, but how do you take a break and then make sense of it all?”

This is where dreams come in, says Roy. During sleep, newly-formed memories are gradually stabilized into a more permanent form of long-term storage in the brain. Dreaming, he says, is influenced by the consolidation of these memories during sleep. Most dreams are made up of experiences, thoughts, emotion, places, and people we have already encountered in our lives. But, during dreaming, bits and pieces of these memories seem to be reorganized to create a particularly bizarre scenario: you’re talking to your sister when it suddenly begins to rain roses and you’re dancing at a New Year’s party.

This re-organization may not be so random; as the brain is processing memories, it pulls together the ones that are seemingly related to each other. Perhaps you dreamt of your sister because you were at a store recently where a candle smelt like her rose-scented perfume, which reminded you of the time you made a new year resolution to spend less money on flowers.

Some brain disorders, like Parkinson’s disease, have been associated with vivid, unpleasant dreams and erratic brain wave patterns. Researchers at the McGovern Institute hope that a better understanding of mechanics of the brain – including neural circuits and brain waves – will help people with Parkinson’s and other brain disorders.

So perhaps dreams aren’t instilled with meaning, symbolism, and wisdom in the way we’ve always imagined, and they simply reflect important biological processes taking place in our brain. But with all that science has uncovered about dreaming and the ways in which it links to creativity and memory, the magical essence of this universal human experience remains untainted.

_____

Do you have a question for The Brain? Ask it here.

McGovern Fellows recognized with life sciences innovation award

by Julie Pryor |

McGovern Institute Fellows Omar Abudayyeh and Jonathan Gootenberg have been named the inaugural recipients of the Termeer Scholars Awards, which recognize “emerging biomedical researchers that represent the future of the biotechnology industry.” The Termeer Foundation is a nonprofit organization focused on connecting life science innovators and catalyzing the creation of new medicines.

“The Termeer Foundation is committed to championing emerging biotechnology leaders and finding people who want to solve the biggest problems in human health,” said Belinda Termeer, president of the Termeer Foundation. “By supporting researchers like Omar and Jonathan, we plant the seeds for future success in individuals who are preparing to make significant contributions in academia and industry.”

The Abudayyeh-Gootenberg lab is developing a suite of new tools to enable next-generation cellular engineering, with uses in basic research, therapeutics and diagnostics. Building off the revolutionary biology of natural biological systems, including mobile genetic elements and CRISPR systems, the team develops new approaches for understanding and manipulating genomes, transcriptomes and cellular fate. The technologies have broad applications, including in oncology, aging and genetic disease.

These tools have been adopted by researchers over the world and formed the basis for four companies that Abudayyeh and Gootenberg have co-founded. They will receive a $50,000 grant to support professional development, knowledge advancement and/or stakeholder engagement and will become part of The Termeer Foundation’s signature Network of Termeer Fellows (first-time CEOs and entrepreneurs) and Mentors (experienced industry leaders).

“The Termeer Foundation is working to improve the long odds of biotechnology by identifying and supporting future biotech leaders; if we help them succeed as leaders, we can help their innovations reach patients,” said Alan Waltws, co-founder of the Termeer Foundation. “While our Termeer Fellows program has supported first time CEOs and entrepreneurs for the past five years, our new Termeer Scholars program will provide much needed support to the researchers whose innovative ideas represent the future of the biotechnology industry – researchers like Omar and Jonathan.”

Abudayyeh and Gootenberg were honored at the Termeer Foundation’s annual dinner in Boston on June 16, 2022.

Artificial neural networks model face processing in autism

by Matthew Hutson |

Many of us easily recognize emotions expressed in others’ faces. A smile may mean happiness, while a frown may indicate anger. Autistic people often have a more difficult time with this task. It’s unclear why. But new research, published today in The Journal of Neuroscience, sheds light on the inner workings of the brain to suggest an answer. And it does so using a tool that opens new pathways to modeling the computation in our heads: artificial intelligence.

Researchers have primarily suggested two brain areas where the differences might lie. A region on the side of the primate (including human) brain called the inferior temporal (IT) cortex contributes to facial recognition. Meanwhile, a deeper region called the amygdala receives input from the IT cortex and other sources and helps process emotions.

Kohitij Kar, a research scientist in the lab of MIT Professor James DiCarlo, hoped to zero in on the answer. (DiCarlo, the Peter de Florez Professor in the Department of Brain and Cognitive Sciences, is a member of the McGovern Institute for Brain Research and director of MIT’s Quest for Intelligence.)

Kar began by looking at data provided by two other researchers: Shuo Wang, at Washington University in St. Louis, and Ralph Adolphs, at the California Institute of Technology. In one experiment, they showed images of faces to autistic adults and to neurotypical controls. The images had been generated by software to vary on a spectrum from fearful to happy, and the participants judged, quickly, whether the faces depicted happiness. Compared with controls, autistic adults required higher levels of happiness in the faces to report them as happy.

Modeling the brain

Kar, who is also a member of the Center for Brains, Minds and Machines, trained an artificial neural network, a complex mathematical function inspired by the brain’s architecture, to perform the same task. The network contained layers of units that roughly resemble biological neurons that process visual information. These layers process information as it passes from an input image to a final judgment indicating the probability that the face is happy. Kar found that the network’s behavior more closely matched the neurotypical controls than it did the autistic adults.

The network also served two more interesting functions. First, Kar could dissect it. He stripped off layers and retested its performance, measuring the difference between how well it matched controls and how well it matched autistic adults. This difference was greatest when the output was based on the last network layer. Previous work has shown that this layer in some ways mimics the IT cortex, which sits near the end of the primate brain’s ventral visual processing pipeline. Kar’s results implicate the IT cortex in differentiating neurotypical controls from autistic adults.

The other function is that the network can be used to select images that might be more efficient in autism diagnoses. If the difference between how closely the network matches neurotypical controls versus autistic adults is greater when judging one set of images versus another set of images, the first set could be used in the clinic to detect autistic behavioral traits. “These are promising results,” Kar says. Better models of the brain will come along, “but oftentimes in the clinic, we don’t need to wait for the absolute best product.”

Next, Kar evaluated the role of the amygdala. Again, he used data from Wang and colleagues. They had used electrodes to record the activity of neurons in the amygdala of people undergoing surgery for epilepsy as they performed the face task. The team found that they could predict a person’s judgment based on these neurons’ activity. Kar re-analyzed the data, this time controlling for the ability of the IT-cortex-like network layer to predict whether a face truly was happy. Now, the amygdala provided very little information of its own. Kar concludes that the IT cortex is the driving force behind the amygdala’s role in judging facial emotion.

Noisy networks

Finally, Kar trained separate neural networks to match the judgments of neurotypical controls and autistic adults. He looked at the strengths or “weights” of the connections between the final layers and the decision nodes. The weights in the network matching autistic adults, both the positive or “excitatory” and negative or “inhibitory” weights, were weaker than in the network matching neurotypical controls. This suggests that sensory neural connections in autistic adults might be noisy or inefficient.

To further test the noise hypothesis, which is popular in the field, Kar added various levels of fluctuation to the activity of the final layer in the network modeling autistic adults. Within a certain range, added noise greatly increased the similarity between its performance and that of the autistic adults. Adding noise to the control network did much less to improve its similarity to the control participants. This further suggest that sensory perception in autistic people may be the result of a so-called “noisy” brain.

Computational power

Looking forward, Kar sees several uses for computational models of visual processing. They can be further prodded, providing hypotheses that researchers might test in animal models. “I think facial emotion recognition is just the tip of the iceberg,” Kar says. They can also be used to select or even generate diagnostic content. Artificial intelligence could be used to generate content like movies and educational materials that optimally engages autistic children and adults. One might even tweak facial and other relevant pixels in what autistic people see in augmented reality goggles, work that Kar plans to pursue in the future.

Ultimately, Kar says, the work helps to validate the usefulness of computational models, especially image-processing neural networks. They formalize hypotheses and make them testable. Does one model or another better match behavioral data? “Even if these models are very far off from brains, they are falsifiable, rather than people just making up stories,” he says. “To me, that’s a more powerful version of science.”

Convenience-sized RNA editing

by Sarah CP Williams |

Last year, researchers at MIT’s McGovern Institute discovered and characterized Cas7-11, the first CRISPR enzyme capable of making precise, guided cuts to strands of RNA without harming cells in the process. Now, working with collaborators at the University of Tokyo, the same team has revealed that Cas7-11 can be shrunk to a more compact version, making it an even more viable option for editing the RNA inside living cells. The new, compact Cas7-11 was described today in the journal Cell along with a detailed structural analysis of the original enzyme.

“When we looked at the structure, it was clear there were some pieces that weren’t needed which we could actually remove,” says McGovern Fellow Omar Abudayyeh, who led the new work with McGovern Fellow Jonathan Gootenberg and collaborator Hiroshi Nishimasu from the University of Tokyo. “This makes the enzyme small enough that it fits into a single viral vector for therapeutic applications.”

The authors, who also include postdoctoral researcher Nathan Zhou from the McGovern Institute and Kazuki Kato from the University Tokyo, see the new three-dimensional structure of Cas7-11 as a rich resource toanswer questions about the basic biology of the enzymes and reveal other ways to tweak its function in the future.

Targeting RNA

McGovern Fellows Jonathan Gootenberg and Omar Abudayyeh in their lab. Photo: Caitlin Cunningham

Over the past decade, the CRISPR-Cas9 genome editing technology has given researchers the ability to modify the genes inside human cells—a boon for both basic research and the development of therapeutics to reverse disease-causing genetic mutations. But CRISPR-Cas9 only works to alter DNA, and for some research and clinical purposes, editing RNA is more effective or useful.

A cell retains its DNA for life, and passes an identical copy to daughter cells as it duplicates, so any changes to DNA are relatively permanent. However, RNA is a more transient molecule, transcribed from DNA and degraded not long after.

“There are lots of positives about being able to permanently change DNA, especially when it comes to treating an inherited genetic disease,” Gootenberg says. “But for an infection, an injury or some other temporary disease, being able to temporarily modify a gene through RNA targeting makes more sense.”

Until Abudayyeh, Gootenberg and their colleagues discovered and characterized Cas7-11, the only enzyme that could target RNA had a messy side effect; when it recognized a particular gene, the enzyme—Cas13—began cutting up all the RNA around it. This property makes Cas13 effective for diagnostic tests, where it is used to detect the presence of a piece of RNA, but not very useful for therapeutics, where targeted cuts are required.

The discovery of Cas7-11 opened the doors to a more precise form of RNA editing, analogous to the Cas9 enzyme for DNA. However, the massive Cas7-11 protein was too big to fit inside a single viral vector—the empty shell of a virus that researchers typically use to deliver gene editing machinery into patient’s cells.

Structural insight

To determine the overall structure of Cas7-11, Abudayyeh, Gootenberg and Nishimasu used cryo-electron microscopy, which shines beams of electrons on frozen protein samples and measures how the beams are transmitted. The researchers knew that Cas7-11 was like an amalgamation of five separate Cas enzymes, fused into one single gene, but were not sure exactly how those parts folded and fit together.

“The really fascinating thing about Cas7-11, from a fundamental biology perspective, is that it should be all these separate pieces that come together, but instead you have a fusion into one gene,” Gootenberg says. “We really didn’t know what that would look like.”

The structure of Cas7-11, caught in the act of binding both its target tRNA strand and the guide RNA, which directs that binding, revealed how the pieces assembled and which parts of the protein were critical to recognizing and cutting RNA. This kind of structural insight is critical to figuring out how to make Cas7-11 carry out targeted jobs inside human cells.

The structure also illuminated a section of the protein that wasn’t serving any apparent functional role. This finding suggested the researchers could remove it, re-engineering Cas7-11 to make it smaller without taking away its ability to target RNA. Abudayyeh and Gootenberg tested the impact of removing different bits of this section, resulting in a new compact version of the protein, dubbed Cas7-11S. With Cas7-11S in hand, they packaged the system inside a single viral vector, delivered it into mammalian cells and efficiently targeted RNA.

The team is now planning future studies on other proteins that interact with Cas7-11 in the bacteria that it originates from, and also hopes to continue working towards the use of Cas7-11 for therapeutic applications.

“Imagine you could have an RNA gene therapy, and when you take it, it modifies your RNA, but when you stop taking it, that modification stops,” Abudayyeh says. “This is really just the beginning of enabling that tool set.”

This research was funded, in part, by the McGovern Institute Neurotechnology Program, K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience, G. Harold & Leila Y. Mathers Charitable Foundation, MIT John W. Jarve (1978) Seed Fund for Science Innovation, FastGrants, Basis for Supporting Innovative Drug Discovery and Life Science Research Program, JSPS KAKENHI, Takeda Medical Research Foundation, and Inamori Research Institute for Science.

A voice for change — in Spanish

by Jennifer Michalowski |

Jessica Chomik-Morales had a bicultural childhood. She was born in Boca Raton, Florida, where her parents had come seeking a better education for their daughter than she would have access to in Paraguay. But when she wasn’t in school, Chomik-Morales was back in that small, South American country with her family. One of the consequences of growing up in two cultures was an early interest in human behavior. “I was always in observer mode,” Chomik-Morales says, recalling how she would tune in to the nuances of social interactions in order to adapt and fit in.

Today, that fascination with human behavior is driving Chomik-Morales as she works with MIT professor of cognitive science Laura Schulz and Walter A. Rosenblith Professor of Cognitive Neuroscience and McGovern Institute for Brain Research investigator Nancy Kanwisher as a post-baccalaureate research scholar, using functional brain imaging to investigate how the brain recognizes and understands causal relationships. Since arriving at MIT last fall, she’s worked with study volunteers to collect functional MRI (fMRI) scans and used computational approaches to interpret the images. She’s also refined her own goals for the future.

Jessica Chomik-Morales (right) with postdoctoral associate Héctor De Jesús-Cortés. Photo: Steph Stevens

She plans to pursue a career in clinical neuropsychology, which will merge her curiosity about the biological basis of behavior with a strong desire to work directly with people. “I’d love to see what kind of questions I could answer about the neural mechanisms driving outlier behavior using fMRI coupled with cognitive assessment,” she says. And she’s confident that her experience in MIT’s two-year post-baccalaureate program will help her get there. “It’s given me the tools I need, and the techniques and methods and good scientific practice,” she says. “I’m learning that all here. And I think it’s going to make me a more successful scientist in grad school.”

The road to MIT

Chomik-Morales’s path to MIT was not a straightforward trajectory through the U.S. school system. When her mom, and later her dad, were unable to return to the U.S., she started eight grade in the capital city of Asunción. It did not go well. She spent nearly every afternoon in the principal’s office, and soon her father was encouraging her to return to the United States. “You are an American,” he told her. “You have a right to the educational system there.”

Back in Florida, Chomik-Morales became a dedicated student, even while she worked assorted jobs and shuffled between the homes of families who were willing to host her. “I had to grow up,” she says. “My parents are sacrificing everything just so I can have a chance to be somebody. People don’t get out of Paraguay often, because there aren’t opportunities and it’s a very poor country. I was given an opportunity, and if I waste that, then that is disrespect not only to my parents, but to my lineage, to my country.”

As she graduated from high school and went on to earn a degree in cognitive neuroscience at Florida Atlantic University, Chomik-Morales found herself experiencing things that were completely foreign to her family. Though she spoke daily with her mom via WhatsApp, it was hard to share what she was learning in school or what she was doing in the lab. And while they celebrated her academic achievements, Chomik-Morales knew they didn’t really understand them. “Neither of my parents went to college,” she says. “My mom told me that she never thought twice about learning about neuroscience. She had this misconception that it was something that she would never be able to digest.”

Chomik-Morales believes that the wonders of neuroscience are for everybody. But she also knows that Spanish speakers like her mom have few opportunities to hear the kinds of accessible, engaging stories that might draw them in. So she’s working to change that. With support from the McGovern Institute, the National Science Foundation funded Science and Technology Center for Brains, Minds, and Machines, Chomik-Morales is hosting and producing a weekly podcast called “Mi Última Neurona” (“My Last Neuron”), which brings conversations with neuroscientists to Spanish speakers around the world.

Listeners hear how researchers at MIT and other institutions are exploring big concepts like consciousness and neurodegeneration, and learn about the approaches they use to study the brain in humans, animals, and computational models. Chomik-Morales wants listeners to get to know neuroscientists on a personal level too, so she talks with her guests about their career paths, their lives outside the lab, and often, their experiences as immigrants in the United States.

After recording an interview with Chomik-Morales that delved into science, art, and the educational system in his home country of Peru, postdoc Arturo Deza thinks “Mi Última Neurona” has the potential to inspire Spanish speakers in Latin America, as well immigrants in other countries. “Even if you’re not a scientist, it’s really going to captivate you and you’re going to get something out of it,” he says. To that point, Chomik-Morales’s mother has quickly become an enthusiastic listener, and even begun seeking out resources to learn more about the brain on her own.

Chomik-Morales hopes the stories her guests share on “Mi Última Neurona” will inspire a future generation of Hispanic neuroscientists. She also wants listeners to know that a career in science doesn’t have to mean leaving their country behind. “Gain whatever you need to gain from outside, and then, if it’s what you desire, you’re able to go back and help your own community,” she says. With “Mi Última Neurona,” she adds, she feels she is giving back to her roots.

How do illusions trick the brain?

by Dana Boebinger | Jarrod Hicks |

As part of our Ask the Brain series, Jarrod Hicks, a graduate student in Josh McDermott‘s lab and Dana Boebinger, a postdoctoral researcher at the University of Rochester (and former graduate student in Josh McDermott’s lab), answer the question, “How do illusions trick the brain?”

_____

Graduate student Jarrod Hicks studies how the brain processes sound. Photo: M.E. Megan Hicks

Imagine you’re a detective. Your job is to visit a crime scene, observe some evidence, and figure out what happened. However, there are often multiple stories that could have produced the evidence you observe. Thus, to solve the crime, you can’t just rely on the evidence in front of you – you have to use your knowledge about the world to make your best guess about the most likely sequence of events. For example, if you discover cat hair at the crime scene, your prior knowledge about the world tells you it’s unlikely that a cat is the culprit. Instead, a more likely explanation is that the culprit might have a pet cat.

Although it might not seem like it, this kind of detective work is what your brain is doing all the time. As your senses send information to your brain about the world around you, your brain plays the role of detective, piecing together each bit of information to figure out what is happening in the world. The information from your senses usually paints a pretty good picture of things, but sometimes when this information is incomplete or unclear, your brain is left to fill in the missing pieces with its best guess of what should be there. This means that what you experience isn’t actually what’s out there in the world, but rather what your brain thinks is out there. The consequence of this is that your perception of the world can depend on your experience and assumptions.

Optical illusions

Optical illusions are a great way of showing how our expectations and assumptions affect what we perceive. For example, look at the squares labeled “A” and “B” in the image below.

Checkershadow illusion. Image: Edward H. Adelson

Is one of them lighter than the other? Although most people would agree that the square labeled “B” is much lighter than the one labeled “A,” the two squares are actually the exact same color. You perceive the squares differently because your brain knows, from experience, that shadows tend to make things appear darker than what they actually are. So, despite the squares being physically identical, your brain thinks “B” should be lighter.

Auditory illusions

Tricks of perception are not limited to optical illusions. There are also several dramatic examples of how our expectations influence what we hear. For example, listen to the mystery sound below. What do you hear?

Mystery sound

Because you’ve probably never heard a sound quite like this before, your brain has very little idea about what to expect. So, although you clearly hear something, it might be very difficult to make out exactly what that something is. This mystery sound is something called sine-wave speech, and what you’re hearing is essentially a very degraded sound of someone speaking.

Now listen to a “clean” version of this speech in the audio clip below:

Clean speech

You probably hear a person saying, “the floor was quite slippery.” Now listen to the mystery sound above again. After listening to the original audio, your brain has a strong expectation about what you should hear when you listen to the mystery sound again. Even though you’re hearing the exact same mystery sound as before, you experience it completely differently. (Audio clips courtesy of University of Sussex).

 

Dana Boebinger describes the science of illusions in this McGovern Minute.

Subjective perceptions

These illusions have been specifically designed by scientists to fool your brain and reveal principles of perception. However, there are plenty of real-life situations in which your perceptions strongly depend on expectations and assumptions. For example, imagine you’re watching TV when someone begins to speak to you from another room. Because the noise from the TV makes it difficult to hear the person speaking, your brain might have to fill in the gaps to understand what’s being said. In this case, different expectations about what is being said could cause you to hear completely different things.

Which phrase do you hear?

Listen to the clip below to hear a repeating loop of speech. As the sound plays, try to listen for one of the phrases listed in teal below.

Because the audio is somewhat ambiguous, the phrase you perceive depends on which phrase you listen for. So even though it’s the exact same audio each time, you can perceive something totally different! (Note: the original audio recording is from a football game in which the fans were chanting, “that is embarrassing!”)

Illusions like the ones above are great reminders of how subjective our perceptions can be. In order to make sense of the messy information coming in from our senses, our brains are constantly trying to fill in the blanks and with its best guess of what’s out there. Because of this guesswork, our perceptions depend on our experiences, leading each of us to perceive and interact with the world in a way that’s uniquely ours.

Jarrod Hicks is a PhD candidate in the Department of Brain and Cognitive Sciences at MIT working with Josh McDermott in the Laboratory for Computational Audition. He studies sound segregation, a key aspect of real-world hearing in which a sound source of interest is estimated amid a mixture of competing sources. He is broadly interested in teaching/outreach, psychophysics, computational approaches to represent stimulus spaces, and neural coding of high-level sensory representations.

_____

Do you have a question for The Brain? Ask it here.