A Google map of the brain

At the start of the twentieth century, Santiago Ramón y Cajal’s drawings of brain cells under the microscope revealed a remarkable diversity of cell types within the brain. Through sketch after sketch, Cajal showed that the brain was not, as many believed, a web of self-similar material, but rather that it is composed of billions of cells of many different sizes, shapes, and interconnections.

Yet more than a hundred years later, we still do not know how many cell types make up the human brain. Despite decades of study, the challenge remains daunting, as the brain’s complexity has overwhelmed attempts to describe it systematically or to catalog its parts.

Now, however, this appears about to change, thanks to an explosion of new technical advances in areas ranging from DNA sequencing to microfluidics to computing and microscopy. For the first time, a parts list for the human brain appears to be within reach.

Why is this important? “Until we know all the cell types, we won’t fully understand how they are connected together,” explains McGovern Investigator Guoping Feng. “We know that the brain’s wiring is incredibly complicated, and that the connections are key to understanding how it works, but we don’t yet have the full picture. That’s what we are aiming for. It’s like making a Google map of the brain.”

Identifying the cell types is also important for understanding disease. As genetic risk factors for different disorders are identified, researchers need to know where they act within the brain, and which cell types and connections are disrupted as a result. “Once we know that, we can start to think about new therapeutic approaches,” says Feng, who is also an institute member of the Broad Institute, where he leads the neurobiology program at the Stanley Center for Psychiatric Disorders Research.

Drop by drop

In 2012, computational biologist Naomi Habib arrived from the Hebrew University of Jerusalem to join the labs of McGovern Investigator Feng Zhang and his collaborator Aviv Regev at the Broad Institute. Habib’s plan was to learn new RNA methods as they were emerging. “I wanted to use these powerful tools to understand this fascinating system that is our brain,” she says.

Her rationale was simple, at least in theory. All cells of an organism carry the same DNA instructions, but the instructions are read out differently in each cell type. Stretches of DNA corresponding to individual genes are copied, sometimes thousands of times, into RNA molecules that in turn direct the synthesis of proteins. Differences in which sequences get copied are what give cells their identities: brain cells express RNAs that encode brain proteins, while blood cells express different RNAs, and so on. A given cell can express thousands of genes, providing a molecular “fingerprint” for each cell type.

Analyzing these RNAs can provide a great deal of information about the brain, including potentially the identities of its constituent cell types. But doing this is not easy, because the different cell types are mixed together like salt and pepper within the brain. For many years, studying brain RNA meant grinding up the tissue—an approach that has been compared to studying smoothies to learn about fruit salad.

As methods improved, it became possible to study the tiny quantities of RNA contained within single cells. This opened the door to studying the difference between individual cells, but this required painstaking manipulation of many samples, a slow and laborious process.

A breakthrough came in 2015, with the development of automated methods based on microfluidics. One of these, known as dropseq (droplet-based sequencing), was pioneered by Steve McCarroll at Harvard, in collaboration with Regev’s lab at Broad. In this method, individual cells are captured in tiny water droplets suspended in oil. Vast numbers of droplets are automatically pumped through tiny channels, where each undergoes its own separate sequencing reactions. By running multiple samples in parallel, the machines can process tens of thousands of cells and billions of sequences, within hours rather than weeks or months. The power of the method became clear when in an experiment on mouse retina, the researchers were able to identify almost every cell type that had ever been described in the retina, effectively recapitulating decades of work in a single experiment.

Dropseq works well for many tissues, but Habib wanted to apply it to the adult brain, which posed a unique challenge. Mature neurons often bear elaborate branches that become intertwined like tree roots in a forest, making it impossible to separate individual cells without damage.

Nuclear option

So Habib turned to another idea. RNA is made in the nucleus before moving to the cytoplasm, and because nuclei are compact and robust it is easy to recover them intact in large numbers, even from difficult tissues such as brain. The amount of RNA contained in a single nucleus is tiny, and Habib didn’t know if it would be enough to be informative, but Zhang and Regev encouraged her to keep going. “You have to be optimistic,” she says. “You have to try.”

Fortunately, the experiment worked. In a paper with Zhang and Regev, she was able to isolate nuclei from newly formed neurons in the adult mouse hippocampus (a brain structure involved in memory), and by analyzing their RNA profiles individually she could order them in a series according to their age, revealing their developmental history from birth to maturity.

Now, after much further experimentation, Habib and her colleagues have managed to apply the droplet method to nuclei, making it possible for the first time to analyze huge numbers of cells from adult brain—at least ten times more than with previous methods.

This opens up many new avenues, including the study of human postmortem tissue, given that RNA in nuclei can survive for years in frozen samples. Habib is already starting to examine tissue taken at autopsy from patients with Alzheimer’s and other neurodegenerative diseases. “The neurons are degenerating, but the other cells around them could also be contributing to the degenerative process,” she says. “Now we have these tools, we can look at what happens during the progression of the disease.”

Computing cells

Once the sequencing is completed, the results are analyzed using sophisticated computational methods. When the results emerge, data from individual cells are visualized as colored dots, clustered on a graph according to their statistical similarities. But because the cells were dissociated at the start of the experiment, information about their appearance and origin within the brain is lost.

To find out how these abstract displays correspond to the visible cells of the brain, Habib teamed up with Yinqing Li, a former graduate student with Zhang who is now a postdoc in the lab of Guoping Feng. Li began with existing maps from the Allen Institute, a public repository with thousands of images showing expression patterns for individual genes within mouse brain. By comparing these maps with the molecular fingerprints from Habib’s nuclear RNA sequencing experiments, Li was able to make a map of where in the brain each cell was likely to have come from.

It was a good first step, but still not perfect. “What we really need,” he says, “is a method that allows us to see every RNA in individual cells. If we are studying a brain disease, we want to know which neurons are involved in the disease process, where they are, what they are connected to, and which special genes might be involved so that we can start thinking about how to design a drug that could alter the disease.”

Expanding horizons

So Li partnered with Asmamaw (Oz) Wassie, a graduate student in the lab of McGovern Investigator Ed Boyden, to tackle the problem. Wassie had previously studied bioengineering as an MIT undergraduate, where he had helped build an electronic “artificial nose” for detecting trace chemicals in air. With support from a prestigious Hertz Fellowship, he joined Boyden’s lab, where he is now working on the development of a method known as expansion microscopy.

In this method, a sample of tissue is embedded with a polymer that swells when water is added. The entire sample expands in all directions, allowing scientists to see fine details such as connections between neurons, using an ordinary microscope. Wassie recently helped develop a way to anchor RNA molecules to the polymer matrix, allowing them to be physically secured during the expansion process. Now, within the expanded samples he can see the individual molecules using a method called fluorescent in situ hybridization (FISH), in which each RNA appears as a glowing dot under the microscope. Currently, he can label only a handful of RNA types at once, but by using special sets of probes, applied sequentially, he thinks it will soon be possible to distinguish thousands of different RNA sequences.

“That will help us to see what each cell looks like, how they are connected to each other, and what RNAs they contain,” says Wassie. By combining this information with the RNA expression data generated by Li and Habib, it will be possible to reveal the organization and fine structure of complex brain areas and perhaps to identify new cell types that have not yet been recognized.

Looking ahead

Li plans to apply these methods to a brain structure known as the thalamic reticular nucleus (TRN) – a sheet of tissue, about ten neurons thick in mice, that sits on top of the thalamus and close to the cortex. The TRN is not well understood, but it is important for controlling sleep, attention and sensory processing, and it has caught the interest of Feng and other neuroscientists because it expresses a disproportionate number of genes implicated in disorders such as autism, attention deficit hyperactivity disorder, and intelligence deficits. Together with Joshua Levin’s group at Broad, Li has already used nuclear RNA sequencing to identify the cell types in the TRN, and he has begun to examine them within intact brain using the expansion techniques. “When you map these precise cell types back to the tissue, you can integrate the gene expression information with everything else, like electrophysiology, connectivity, morphology,” says Li. “Then we can start to ask what’s going wrong in disease.”

Meanwhile, Feng is already looking beyond the TRN, and planning how to scale the approach to other structures and eventually to the entire brain. He returns to the metaphor of a Google map. “Microscopic images are like satellite photos,” he says. “Now with expansion microscopy we can add another layer of information, like property boundaries and individual buildings. And knowing which RNAs are in each cell will be like seeing who lives in those buildings. I think this will completely change how we view the brain.”

Tan-Yang Center for Autism Research: Feng Zhang

June 12, 2017
Tan-Yang Center for Autism Research: Launch Celebration
Feng Zhang, McGovern Institute for Brain Research
“Gene Therapy for the Brain”

Socioeconomic background linked to reading improvement

About 20 percent of children in the United States have difficulty learning to read, and educators have devised a variety of interventions to try to help them. Not every program helps every student, however, in part because the origins of their struggles are not identical.

MIT neuroscientist John Gabrieli is trying to identify factors that may help to predict individual children’s responses to different types of reading interventions. As part of that effort, he recently found that children from lower-income families responded much better to a summer reading program than children from a higher socioeconomic background.

Using magnetic resonance imaging (MRI), the research team also found anatomical changes in the brains of children whose reading abilities improved — in particular, a thickening of the cortex in parts of the brain known to be involved in reading.

“If you just left these children [with reading difficulties] alone on the developmental path they’re on, they would have terrible troubles reading in school. We’re taking them on a neuroanatomical detour that seems to go with real gains in reading ability,” says Gabrieli, the Grover M. Hermann Professor in Health Sciences and Technology, a professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

Rachel Romeo, a graduate student in the Harvard-MIT Program in Health Sciences and Technology, and Joanna Christodoulou, an assistant professor of communication sciences and disorders at the Massachusetts General Hospital Institute of Health Professions, are the lead authors of the paper, which appears in the June 7 issue of the journal Cerebral Cortex.

Predicting improvement

In hopes of identifying factors that influence children’s responses to reading interventions, the MIT team set up two summer schools based on a program known as Lindamood-Bell. The researchers recruited students from a wide income range, although socioeconomic status was not the original focus of their study.

The Lindamood-Bell program focuses on helping students develop the sensory and cognitive processing necessary for reading, such as thinking about words as units of sound, and translating printed letters into word meanings.

Children participating in the study, who ranged from 6 to 9 years old, spent four hours a day, five days a week in the program, for six weeks. Before and after the program, their brains were scanned with MRI and they were given some commonly used tests of reading proficiency.

In tests taken before the program started, children from higher and lower socioeconomic (SES) backgrounds fared equally poorly in most areas, with one exception. Children from higher SES backgrounds had higher vocabulary scores, which has also been seen in studies comparing nondyslexic readers from different SES backgrounds.

“There’s a strong trend in these studies that higher SES families tend to talk more with their kids and also use more complex and diverse language. That tends to be where the vocabulary correlation comes from,” Romeo says.

The researchers also found differences in brain anatomy before the reading program started. Children from higher socioeconomic backgrounds had thicker cortex in a part of the brain known as Broca’s area, which is necessary for language production and comprehension. The researchers also found that these differences could account for the differences in vocabulary levels between the two groups.

Based on a limited number of previous studies, the researchers hypothesized that the reading program would have more of an impact on the students from higher socioeconomic backgrounds. But in fact, they found the opposite. About half of the students improved their scores, while the other half worsened or stayed the same. When analyzing the data for possible explanations, family income level was the one factor that proved significant.

“Socioeconomic status just showed up as the piece that was most predictive of treatment response,” Romeo says.

The same children whose reading scores improved also displayed changes in their brain anatomy. Specifically, the researchers found that they had a thickening of the cortex in a part of the brain known as the temporal occipital region, which comprises a large network of structures involved in reading.

“Mix of causes”

The researchers believe that their results may have been different than previous studies of reading intervention in low SES students because their program was run during the summer, rather than during the school year.

“Summer is when socioeconomic status takes its biggest toll. Low SES kids typically have less academic content in their summer activities compared to high SES, and that results in a slump in their skills,” Romeo says. “This may have been particularly beneficial for them because it may have been out of the realm of their typical summer.”

The researchers also hypothesize that reading difficulties may arise in slightly different ways among children of different SES backgrounds.

“There could be a different mix of causes,” Gabrieli says. “Reading is a complicated skill, so there could be a number of different factors that would make you do better or do worse. It could be that those factors are a little bit different in children with more enriched or less enriched environments.”

The researchers are hoping to identify more precisely the factors related to socioeconomic status, other environmental factors, or genetic components that could predict which types of reading interventions will be successful for individual students.

“In medicine, people call it personalized medicine: this idea that some people will really benefit from one intervention and not so much from another,” Gabrieli says. “We’re interested in understanding the match between the student and the kind of educational support that would be helpful for that particular student.”

The research was funded by the Ellison Medical Foundation, the Halis Family Foundation, Lindamood-Bell Learning Processes, and the National Institutes of Health.

McGovern Institute 2017 Retreat

On June 5-6, McGovern researchers and staff gathered in Newport, Rhode Island for the annual McGovern Institute retreat. The overnight retreat featured talks, a poster session, a Newport Harbor cruise (for those willing to brave the cool, wet weather) and a dance party. Click the thumbnails below to see other images from the McGovern Institute Retreat.

A noninvasive method for deep brain stimulation

Delivering an electrical current to a part of the brain involved in movement control has proven successful in treating many Parkinson’s disease patients. This approach, known as deep brain stimulation, requires implanting electrodes in the brain — a complex procedure that carries some risk to the patient.

Now, MIT researchers, collaborating with investigators at Beth Israel Deaconess Medical Center (BIDMC) and the IT’IS Foundation, have come up with a way to stimulate regions deep within the brain using electrodes placed on the scalp. This approach could make deep brain stimulation noninvasive, less risky, less expensive, and more accessible to patients.

“Traditional deep brain stimulation requires opening the skull and implanting an electrode, which can have complications. Secondly, only a small number of people can do this kind of neurosurgery,” says Ed Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT, and the senior author of the study, which appears in the June 1 issue of Cell.

Doctors also use deep brain stimulation to treat some patients with obsessive compulsive disorder, epilepsy, and depression, and are exploring the possibility of using it to treat other conditions such as autism. The new, noninvasive approach could make it easier to adapt deep brain stimulation to treat additional disorders, the researchers say.

“With the ability to stimulate brain structures noninvasively, we hope that we may help discover new targets for treating brain disorders,” says the paper’s lead author, Nir Grossman, a former Wellcome Trust-MIT postdoc working at MIT and BIDMC, who is now a research fellow at Imperial College London.

Deep locations

Electrodes for treating Parkinson’s disease are usually placed in the subthalamic nucleus, a lens-shaped structure located below the thalamus, deep within the brain. For many Parkinson’s patients, delivering electrical impulses in this brain region can improve symptoms, but the surgery to implant the electrodes carries risks, including brain hemorrhage and infection.

Other researchers have tried to noninvasively stimulate the brain using techniques such as transcranial magnetic stimulation (TMS), which is FDA-approved for treating depression. Since TMS is noninvasive, it has also been used in normal human subjects to study the basic science of cognition, emotion, sensation, and movement. However, using TMS to stimulate deep brain structures can also result in surface regions being strongly stimulated, resulting in modulation of multiple brain networks.

The MIT team devised a way to deliver electrical stimulation deep within the brain, via electrodes placed on the scalp, by taking advantage of a phenomenon known as temporal interference.

This strategy requires generating two high-frequency electrical currents using electrodes placed outside the brain. These fields are too fast to drive neurons. However, these currents interfere with one another in such a way that where they intersect, deep in the brain, a small region of low-frequency current is generated inside neurons. This low-frequency current can be used to drive neurons’ electrical activity, while the high-frequency current passes through surrounding tissue with no effect.

By tuning the frequency of these currents and changing the number and location of the electrodes, the researchers can control the size and location of the brain tissue that receives the low-frequency stimulation. They can target locations deep within the brain without affecting any of the surrounding brain structures. They can also steer the location of stimulation, without moving the electrodes, by altering the currents. In this way, deep targets could be stimulated, both for therapeutic use and basic science investigations.

“You can go for deep targets and spare the overlying neurons, although the spatial resolution is not yet as good as that of deep brain stimulation,” says Boyden, who is a member of MIT’s Media Lab and McGovern Institute for Brain Research.

Targeted stimulation

Li-Huei Tsai, director of MIT’s Picower Institute for Learning and Memory, and researchers in her lab tested this technique in mice and found that they could stimulate small regions deep within the brain, including the hippocampus. They were also able to shift the site of stimulation, allowing them to activate different parts of the motor cortex and prompt the mice to move their limbs, ears, or whiskers.

“We showed that we can very precisely target a brain region to elicit not just neuronal activation but behavioral responses,” says Tsai, who is an author of the paper. “I think it’s very exciting because Parkinson’s disease and other movement disorders seem to originate from a very particular region of the brain, and if you can target that, you have the potential to reverse it.”

Significantly, in the hippocampus experiments, the technique did not activate the neurons in the cortex, the region lying between the electrodes on the skull and the target deep inside the brain. The researchers also found no harmful effects in any part of the brain.

Last year, Tsai showed that using light to visually induce brain waves of a particular frequency could substantially reduce the beta amyloid plaques seen in Alzheimer’s disease, in the brains of mice. She now plans to explore whether this type of electrical stimulation could offer a new way to generate the same type of beneficial brain waves.

Other authors of the paper are MIT research scientist David Bono; former MIT postdocs Suhasa Kodandaramaiah and Andrii Rudenko; MIT postdoc Nina Dedic; MIT grad student Ho-Jun Suk; Beth Israel Deaconess Medical Center and Harvard Medical School Professor Alvaro Pascual-Leone; and IT’IS Foundation researchers Antonino Cassara, Esra Neufeld, and Niels Kuster.

The research was funded in part by the Wellcome Trust, a National Institutes of Health Director’s Pioneer Award, an NIH Director’s Transformative Research Award, the New York Stem Cell Foundation Robertson Investigator Award, the MIT Center for Brains, Minds, and Machines, Jeremy and Joyce Wertheimer, Google, a National Science Foundation Career Award, the MIT Synthetic Intelligence Project, and Harvard Catalyst: The Harvard Clinical and Translational Science Center.

Making brain implants smaller could prolong their lifespan

Many diseases, including Parkinson’s disease, can be treated with electrical stimulation from an electrode implanted in the brain. However, the electrodes can produce scarring, which diminishes their effectiveness and can necessitate additional surgeries to replace them.

MIT researchers have now demonstrated that making these electrodes much smaller can essentially eliminate this scarring, potentially allowing the devices to remain in the brain for much longer.

“What we’re doing is changing the scale and making the procedure less invasive,” says Michael Cima, the David H. Koch Professor of Engineering in the Department of Materials Science and Engineering, a member of MIT’s Koch Institute for Integrative Cancer Research, and the senior author of the study, which appears in the May 16 issue of Scientific Reports.

Cima and his colleagues are now designing brain implants that can not only deliver electrical stimulation but also record brain activity or deliver drugs to very targeted locations.

The paper’s lead author is former MIT graduate student Kevin Spencer. Other authors are former postdoc Jay Sy, graduate student Khalil Ramadi, Institute Professor Ann Graybiel, and David H. Koch Institute Professor Robert Langer.

Effects of size

Many Parkinson’s patients have benefited from treatment with low-frequency electrical current delivered to a part of the brain involved in movement control. The electrodes used for this deep brain stimulation are a few millimeters in diameter. After being implanted, they gradually generate scar tissue through the constant rubbing of the electrode against the surrounding brain tissue. This process, known as gliosis, contributes to the high failure rate of such devices: About half stop working within the first six months.

Previous studies have suggested that making the implants smaller or softer could reduce the amount of scarring, so the MIT team set out to measure the effects of both reducing the size of the implants and coating them with a soft polyethylene glycol (PEG) hydrogel.

The hydrogel coating was designed to have an elasticity very similar to that of the brain. The researchers could also control the thickness of the coating. They found that when coated electrodes were pushed into the brain, the soft coating would fall off, so they devised a way to apply the hydrogel and then dry it, so that it becomes a hard, thin film. After the electrode is inserted, the film soaks up water and becomes soft again.

In mice, the researchers tested both coated and uncoated glass fibers with varying diameters and found that there is a tradeoff between size and softness. Coated fibers produced much less scarring than uncoated fibers of the same diameter. However, as the electrode fibers became smaller, down to about 30 microns (0.03 millimeters) in diameter, the uncoated versions produced less scarring, because the coatings increase the diameter.

This suggests that a 30-micron, uncoated fiber is the optimal design for implantable devices in the brain.

“Before this paper, no one really knew the effects of size,” Cima says. “Softer is better, but not if it makes the electrode larger.”

New devices

The question now is whether fibers that are only 30 microns in diameter can be adapted for electrical stimulation, drug delivery, and recording electrical activity in the brain. Cima and his colleagues have had some initial success developing such devices.

“It’s one of those things that at first glance seems impossible. If you have 30-micron glass fibers, that’s slightly thicker than a piece of hair. But it is possible to do,” Cima says.
Such devices could be potentially useful for treating Parkinson’s disease or other neurological disorders. They could also be used to remove fluid from the brain to monitor whether treatments are having the intended effect, or to measure brain activity that might indicate when an epileptic seizure is about to occur.

The research was funded by the National Institutes of Health and MIT’s Institute for Soldier Nanotechnologies.

High-resolution imaging with conventional microscopes

MIT researchers have developed a way to make extremely high-resolution images of tissue samples, at a fraction of the cost of other techniques that offer similar resolution.

The new technique relies on expanding tissue before imaging it with a conventional light microscope. Two years ago, the MIT team showed that it was possible to expand tissue volumes 100-fold, resulting in an image resolution of about 60 nanometers. Now, the researchers have shown that expanding the tissue a second time before imaging can boost the resolution to about 25 nanometers.

This level of resolution allows scientists to see, for example, the proteins that cluster together in complex patterns at brain synapses, helping neurons to communicate with each other. It could also help researchers to map neural circuits, says Ed Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT.

“We want to be able to trace the wiring of complete brain circuits,” says Boyden, the study’s senior author. “If you could reconstruct a complete brain circuit, maybe you could make a computational model of how it generates complex phenomena like decisions and emotions. Since you can map out the biomolecules that generate electrical pulses within cells and that exchange chemicals between cells, you could potentially model the dynamics of the brain.”

This approach could also be used to image other phenomena such as the interactions between cancer cells and immune cells, to detect pathogens without expensive equipment, and to map the cell types of the body.

Former MIT postdoc Jae-Byum Chang is the first author of the paper, which appears in the April 17 issue of Nature Methods.

Double expansion

To expand tissue samples, the researchers embed them in a dense, evenly generated gel made of polyacrylate, a very absorbent material that’s also used in diapers. Before the gel is formed, the researchers label the cell proteins they want to image, using antibodies that bind to specific targets. These antibodies bear “barcodes” made of DNA, which in turn are attached to cross-linking molecules that bind to the polymers that make up the expandable gel. The researchers then break down the proteins that normally hold the tissue together, allowing the DNA barcodes to expand away from each other as the gel swells.

These enlarged samples can then be labeled with fluorescent probes that bind the DNA barcodes, and imaged with commercially available confocal microscopes, whose resolution is usually limited to hundreds of nanometers.

Using that approach, the researchers were previously able to achieve a resolution of about 60 nanometers. However, “individual biomolecules are much smaller than that, say 5 nanometers or even smaller,” Boyden says. “The original versions of expansion microscopy were useful for many scientific questions but couldn’t equal the performance of the highest-resolution imaging methods such as electron microscopy.”

In their original expansion microscopy study, the researchers found that they could expand the tissue more than 100-fold in volume by reducing the number of cross-linking molecules that hold the polymer in an orderly pattern. However, this made the tissue unstable.

“If you reduce the cross-linker density, the polymers no longer retain their organization during the expansion process,” says Boyden, who is a member of MIT’s Media Lab and McGovern Institute for Brain Research. “You lose the information.”

Instead, in their latest study, the researchers modified their technique so that after the first tissue expansion, they can create a new gel that swells the tissue a second time — an approach they call “iterative expansion.”

Mapping circuits

Using iterative expansion, the researchers were able to image tissues with a resolution of about 25 nanometers, which is similar to that achieved by high-resolution techniques such as stochastic optical reconstruction microscopy (STORM). However, expansion microscopy is much cheaper and simpler to perform because no specialized equipment or chemicals are required, Boyden says. The method is also much faster and thus compatible with large-scale, 3-D imaging.

The resolution of expansion microscopy does not yet match that of scanning electron microscopy (about 5 nanometers) or transmission electron microscopy (about 1 nanometer). However, electron microscopes are very expensive and not widely available, and with those microscopes, it is difficult for researchers to label specific proteins.

In the Nature Methods paper, the MIT team used iterative expansion to image synapses — the connections between neurons that allow them to communicate with each other. In their original expansion microscopy study, the researchers were able to image scaffolding proteins, which help to organize the hundreds of other proteins found in synapses. With the new, enhanced resolution, the researchers were also able to see finer-scale structures, such as the location of neurotransmitter receptors located on the surfaces of the “postsynaptic” cells on the receiving side of the synapse.

“My hope is that we can, in the coming years, really start to map out the organization of these scaffolding and signaling proteins at the synapse,” Boyden says.

Combining expansion microscopy with a new tool called temporal multiplexing should help to achieve that, he believes. Currently, only a limited number of colored probes can be used to image different molecules in a tissue sample. With temporal multiplexing, researchers can label one molecule with a fluorescent probe, take an image, and then wash the probe away. This can then be repeated many times, each time using the same colors to label different molecules.

“By combining iterative expansion with temporal multiplexing, we could in principle have essentially infinite-color, nanoscale-resolution imaging over large 3-D volumes,” Boyden says. “Things are getting really exciting now that these different technologies may soon connect with each other.”

The researchers also hope to achieve a third round of expansion, which they believe could, in principle, enable resolution of about 5 nanometers. However, right now the resolution is limited by the size of the antibodies used to label molecules in the cell. These antibodies are about 10 to 20 nanometers long, so to get resolution below that, researchers would need to create smaller tags or expand the proteins away from each other first and then deliver the antibodies after expansion.

This study was funded by the National Institutes of Health Director’s Pioneer Award, the New York Stem Cell Foundation Robertson Award, the HHMI-Simons Faculty Scholars Award, and the Open Philanthropy Project.