Researcher: Ed Boyden

Microscopy technique could enable more informative biopsies

Anne Trafton |

MIT and Harvard Medical School researchers have devised a way to image biopsy samples with much higher resolution — an advance that could help doctors develop more accurate and inexpensive diagnostic tests.

For more than 100 years, conventional light microscopes have been vital tools for pathology. However, fine-scale details of cells cannot be seen with these scopes. The new technique relies on an approach known as expansion microscopy, developed originally in Edward Boyden’s lab at MIT, in which the researchers expand a tissue sample to 100 times its original volume before imaging it.

This expansion allows researchers to see features with a conventional light microscope that ordinarily could be seen only with an expensive, high-resolution electron microscope. It also reveals additional molecular information that the electron microscope cannot provide.

“It’s a technique that could have very broad application,” says Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT. He is also a member of MIT’s Media Lab and McGovern Institute for Brain Research, and an HHMI-Simons Faculty Scholar.

In a paper appearing in the 17 July issue of Nature Biotechnology, Boyden and his colleagues used this technique to distinguish early-stage breast lesions with high or low risk of progressing to cancer — a task that is challenging for human observers. This approach can also be applied to other diseases: In an analysis of kidney tissue, the researchers found that images of expanded samples revealed signs of kidney disease that can normally only be seen with an electron microscope.

“Using expansion microscopy, we are able to diagnose diseases that were previously impossible to diagnose with a conventional light microscope,” says Octavian Bucur, an instructor at Harvard Medical School, Beth Israel Deaconess Medical Center (BIDMC), and the Ludwig Center at Harvard, and one of the paper’s lead authors.

MIT postdoc Yongxin Zhao is the paper’s co-lead author. Boyden and Andrew Beck, a former associate professor at Harvard Medical School and BIDMC, are the paper’s senior authors.


“A few chemicals and a light microscope”

Boyden’s original expansion microscopy technique is based on embedding tissue samples in a dense, evenly generated polymer that swells when water is added. Before the swelling occurs, the researchers anchor to the polymer gel the molecules that they want to image, and they digest other proteins that normally hold tissue together.

This tissue enlargement allows researchers to obtain images with a resolution of around 70 nanometers, which was previously possible only with very specialized and expensive microscopes.

In the new study, the researchers set out to adapt the expansion process for biopsy tissue samples, which are usually embedded in paraffin wax, flash frozen, or stained with a chemical that makes cellular structures more visible.

The MIT/Harvard team devised a process to convert these samples into a state suitable for expansion. For example, they remove the chemical stain or paraffin by exposing the tissues to a chemical solvent called xylene. Then, they heat up the sample in another chemical called citrate. After that, the tissues go through an expansion process similar to the original version of the technique, but with stronger digestion steps to compensate for the strong chemical fixation of the samples.

During this procedure, the researchers can also add fluorescent labels for molecules of interest, including proteins that mark particular types of cells, or DNA or RNA with a specific sequence.

“The work of Zhao et al. describes a very clever way of extending the resolution of light microscopy to resolve detail beyond that seen with conventional methods,” says David Rimm, a professor of pathology at the Yale University School of Medicine, who was not involved in the research.

The researchers tested this approach on tissue samples from patients with early-stage breast lesions. One way to predict whether these lesions will become malignant is to evaluate the appearance of the cells’ nuclei. Benign lesions with atypical nuclei have about a fivefold higher probability of progressing to cancer than those with typical nuclei.

However, studies have revealed significant discrepancies between the assessments of nuclear atypia performed by different pathologists, which can potentially lead to an inaccurate diagnosis and unnecessary surgery. An improved system for differentiating benign lesions with atypical and typical nuclei could potentially prevent 400,000 misdiagnoses and hundreds of millions of dollars every year in the United States, according to the researchers.

After expanding the tissue samples, the MIT/Harvard team analyzed them with a machine learning algorithm that can rate the nuclei based on dozens of features, including orientation, diameter, and how much they deviate from true circularity. This algorithm was able to distinguish between lesions that were likely to become invasive and those that were not, with an accuracy of 93 percent on expanded samples compared to only 71 percent on the pre-expanded tissue.

“These two types of lesions look highly similar to the naked eye, but one has much less risk of cancer,” Zhao says.

The researchers also analyzed kidney tissue samples from patients with nephrotic syndrome, which impairs the kidneys’ ability to filter blood. In these patients, tiny finger-like projections that filter the blood are lost or damaged. These structures are spaced about 200 nanometers apart and therefore can usually be seen only with an electron microscope or expensive super resolution microscopes.

When the researchers showed the images of the expanded tissue samples to a group of scientists that included pathologists and nonpathologists, the group was able to identify the diseased tissue with 90 percent accuracy overall, compared to only 65 percent accuracy with unexpanded tissue samples.

“Now you can diagnose nephrotic kidney disease without needing an electron microscope, a very expensive machine,” Boyden says. “You can do it with a few chemicals and a light microscope.”

Uncovering patterns

Using this approach, the researchers anticipate that scientists could develop more precise diagnostics for many other diseases. To do that, scientists and doctors will need to analyze many more patient samples, allowing them to discover patterns that would be impossible to see otherwise.

“If you can expand a tissue by one-hundredfold in volume, all other things being equal, you’re getting 100 times the information,” Boyden says.

For example, researchers could distinguish cancer cells based on how many copies of a particular gene they have. Extra copies of genes such as HER2, which the researchers imaged in one part of this study, indicate a subtype of breast cancer that is eligible for specific treatments.

Scientists could also look at the architecture of the genome, or at how cell shapes change as they become cancerous and interact with other cells of the body. Another possible application is identifying proteins that are expressed specifically on the surface of cancer cells, allowing researchers to design immunotherapies that mark those cells for destruction by the patient’s immune system.

Boyden and his colleagues run training courses several times a month at MIT, where visitors can come and watch expansion microscopy techniques, and they have made their protocols available on their website. They hope that many more people will begin using this approach to study a variety of diseases.

“Cancer biopsies are just the beginning,” Boyden says. “We have a new pipeline for taking clinical samples and expanding them, and we are finding that we can apply expansion to many different diseases. Expansion will enable computational pathology to take advantage of more information in a specimen than previously possible.”

Humayun Irshad, a research fellow at Harvard/BIDMC and an author of the study, agrees: “Expanded images result in more informative features, which in turn result in higher-performing classification models.”

Other authors include Harvard pathologist Astrid Weins, who helped oversee the kidney study. Other authors from MIT (Fei Chen) and BIDMC/Harvard (Andreea Stancu, Eun-Young Oh, Marcello DiStasio, Vanda Torous, Benjamin Glass, Isaac E. Stillman, and Stuart J. Schnitt) also contributed to this study.

The research was funded, in part, by the New York Stem Cell Foundation Robertson Investigator Award, the National Institutes of Health Director’s Pioneer Award, the Department of Defense Multidisciplinary University Research Initiative, the Open Philanthropy Project, the Ludwig Center at Harvard, and Harvard Catalyst.

A Google map of the brain

by Elizabeth Dougherty |

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.”

A noninvasive method for deep brain stimulation

Anne Trafton |

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.

High-resolution imaging with conventional microscopes

Anne Trafton |

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.

Sensor traces dopamine released by single cells

Anne Trafton |

MIT chemical engineers have developed an extremely sensitive detector that can track single cells’ secretion of dopamine, a brain chemical responsible for carrying messages involved in reward-motivated behavior, learning, and memory.

Using arrays of up to 20,000 tiny sensors, the researchers can monitor dopamine secretion of single neurons, allowing them to explore critical questions about dopamine dynamics. Until now, that has been very difficult to do.

“Now, in real-time, and with good spatial resolution, we can see exactly where dopamine is being released,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering and the senior author of a paper describing the research, which appears in the Proceedings of the National Academy of Sciences the week of Feb. 6.

Strano and his colleagues have already demonstrated that dopamine release occurs differently than scientists expected in a type of neural progenitor cell, helping to shed light on how dopamine may exert its effects in the brain.

The paper’s lead author is Sebastian Kruss, a former MIT postdoc who is now at Göttingen University, in Germany. Other authors are Daniel Salem and Barbara Lima, both MIT graduate students; Edward Boyden, an associate professor of biological engineering and brain and cognitive sciences, as well as a member of the MIT Media Lab and the McGovern Institute for Brain Research; Lela Vukovic, an assistant professor of chemistry at the University of Texas at El Paso; and Emma Vander Ende, a graduate student at Northwestern University.

“A global effect”

Dopamine is a neurotransmitter that plays important roles in learning, memory, and feelings of reward, which reinforce positive experiences.

Neurotransmitters allow neurons to relay messages to nearby neurons through connections known as synapses. However, unlike most other neurotransmitters, dopamine can exert its effects beyond the synapse: Not all dopamine released into a synapse is taken up by the target cell, allowing some of the chemical to diffuse away and affect other nearby cells.

“It has a local effect, which controls the signaling through the neurons, but also it has a global effect,” Strano says. “If dopamine is in the region, it influences all the neurons nearby.”

Tracking this dopamine diffusion in the brain has proven difficult. Neuroscientists have tried using electrodes that are specialized to detect dopamine, but even using the smallest electrodes available, they can place only about 20 near any given cell.

“We’re at the infancy of really understanding how these packets of chemicals move and their directionality,” says Strano, who decided to take a different approach.

Strano’s lab has previously developed sensors made from arrays of carbon nanotubes — hollow, nanometer-thick cylinders made of carbon, which naturally fluoresce when exposed to laser light. By wrapping these tubes in different proteins or DNA strands, scientists can customize them to bind to different types of molecules.

The carbon nanotube sensors used in this study are coated with a DNA sequence that makes the sensors interact with dopamine. When dopamine binds to the carbon nanotubes, they fluoresce more brightly, allowing the researchers to see exactly where the dopamine was released. The researchers deposited more than 20,000 of these nanotubes on a glass slide, creating an array that detects any dopamine secreted by a cell placed on the slide.

Dopamine diffusion

In the new PNAS study, the researchers used these dopamine sensors to explore a longstanding question about dopamine release in the brain: From which part of the cell is dopamine secreted?

To help answer that question, the researchers placed individual neural progenitor cells known as PC-12 cells onto the sensor arrays. PC-12 cells, which develop into neuron-like cells under the right conditions, have a starfish-like shape with several protrusions that resemble axons, which form synapses with other cells.

After stimulating the cells to release dopamine, the researchers found that certain dopamine sensors near the cells lit up immediately, while those farther away turned on later as the dopamine diffused away. Tracking those patterns over many seconds allowed the researchers to trace how dopamine spreads away from the cells.

Strano says one might expect to see that most of the dopamine would be released from the tips of the arms extending out from the cells. However, the researchers found that in fact more dopamine came from the sides of the arms.

“We have falsified the notion that dopamine should only be released at these regions that will eventually become the synapses,” Strano says. “This observation is counterintuitive, and it’s a new piece of information you can only obtain with a nanosensor array like this one.”

The team also showed that most of the dopamine traveled away from the cell, through protrusions extending in opposite directions. “Even though dopamine is not necessarily being released only at the tip of these protrusions, the direction of release is associated with them,” Salem says.

Other questions that could be explored using these sensors include how dopamine release is affected by the direction of input to the cell, and how the presence of nearby cells influences each cell’s dopamine release.

The research was funded by the National Science Foundation, the National Institutes of Health, a University of Illinois Center for the Physics of Living Cells Postdoctoral Fellowship, the German Research Foundation, and a Liebig Fellowship.

Researchers create synthetic cells to isolate genetic circuits

Anne Trafton |

Synthetic biology allows scientists to design genetic circuits that can be placed in cells, giving them new functions such as producing drugs or other useful molecules. However, as these circuits become more complex, the genetic components can interfere with each other, making it difficult to achieve more complicated functions.

MIT researchers have now demonstrated that these circuits can be isolated within individual synthetic “cells,” preventing them from disrupting each other. The researchers can also control communication between these cells, allowing for circuits or their products to be combined at specific times.

“It’s a way of having the power of multicomponent genetic cascades, along with the ability to build walls between them so they won’t have cross-talk. They won’t interfere with each other in the way they would if they were all put into a single cell or into a beaker,” says Edward Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT. Boyden is also a member of MIT’s Media Lab and McGovern Institute for Brain Research, and an HHMI-Simons Faculty Scholar.

This approach could allow researchers to design circuits that manufacture complex products or act as sensors that respond to changes in their environment, among other applications.

Boyden is the senior author of a paper describing this technique in the Nov. 14 issue of Nature Chemistry. The paper’s lead authors are former MIT postdoc Kate Adamala, who is now an assistant professor at the University of Minnesota, and former MIT grad student Daniel Martin-Alarcon. Katriona Guthrie-Honea, a former MIT research assistant, is also an author of the paper.

Circuit control

The MIT team encapsulated their genetic circuits in droplets known as liposomes, which have a fatty membrane similar to cell membranes. These synthetic cells are not alive but are equipped with much of the cellular machinery necessary to read DNA and manufacture proteins.

By segregating circuits within their own liposomes, the researchers are able to create separate circuit subroutines that could not run in the same container at the same time, but can run in parallel to each other, communicating in controlled ways. This approach also allows scientists to repurpose the same genetic tools, including genes and transcription factors (proteins that turn genes on or off), to do different tasks within a network.

“If you separate circuits into two different liposomes, you could have one tool doing one job in one liposome, and the same tool doing a different job in the other liposome,” Martin-Alarcon says. “It expands the number of things that you can do with the same building blocks.”

This approach also enables communication between circuits from different types of organisms, such as bacteria and mammals.

As a demonstration, the researchers created a circuit that uses bacterial genetic parts to respond to a molecule known as theophylline, a drug similar to caffeine. When this molecule is present, it triggers another molecule known as doxycycline to leave the liposome and enter another set of liposomes containing a mammalian genetic circuit. In those liposomes, doxycycline activates a genetic cascade that produces luciferase, a protein that generates light.

Using a modified version of this approach, scientists could create circuits that work together to produce biological therapeutics such as antibodies, after sensing a particular molecule emitted by a brain cell or other cell.

“If you think of the bacterial circuit as encoding a computer program, and the mammalian circuit is encoding the factory, you could combine the computer code of the bacterial circuit and the factory of the mammalian circuit into a unique hybrid system,” Boyden says.

The researchers also designed liposomes that can fuse with each other in a controlled way. To do that, they programmed the cells with proteins called SNAREs, which insert themselves into the cell membrane. There, they bind to corresponding SNAREs found on surfaces of other liposomes, causing the synthetic cells to fuse. The timing of this fusion can be controlled to bring together liposomes that produce different molecules. When the cells fuse, these molecules are combined to generate a final product.

More modularity

The researchers believe this approach could be used for nearly any application that synthetic biologists are already working on. It could also allow scientists to pursue potentially useful applications that have been tried before but abandoned because the genetic circuits interfered with each other too much.

“The way that we wrote this paper was not oriented toward just one application,” Boyden says. “The basic question is: Can you make these circuits more modular? If you have everything mishmashed together in the cell, but you find out that the circuits are incompatible or toxic, then putting walls between those reactions and giving them the ability to communicate with each other could be very useful.”

Vincent Noireaux, an associate professor of physics at the University of Minnesota, described the MIT approach as “a rather novel method to learn how biological systems work.”

“Using cell-free expression has several advantages: Technically the work is reduced to cloning (nowadays fast and easy), we can link information processing to biological function like living cells do, and we work in isolation with no other gene expression occurring in the background,” says Noireaux, who was not involved in the research.

Another possible application for this approach is to help scientists explore how the earliest cells may have evolved billions of years ago. By engineering simple circuits into liposomes, researchers could study how cells might have evolved the ability to sense their environment, respond to stimuli, and reproduce.

“This system can be used to model the behavior and properties of the earliest organisms on Earth, as well as help establish the physical boundaries of Earth-type life for the search of life elsewhere in the solar system and beyond,” Adamala says.

Newly discovered neural connections may be linked to emotional decision-making

Anne Trafton |

MIT neuroscientists have discovered connections deep within the brain that appear to form a communication pathway between areas that control emotion, decision-making, and movement. The researchers suspect that these connections, which they call striosome-dendron bouquets, may be involved in controlling how the brain makes decisions that are influenced by emotion or anxiety.

This circuit may also be one of the targets of the neural degeneration seen in Parkinson’s disease, says Ann Graybiel, an Institute Professor at MIT, member of the McGovern Institute for Brain Research, and the senior author of the study.

Graybiel and her colleagues were able to find these connections using a technique developed at MIT known as expansion microscopy, which enables scientists to expand brain tissue before imaging it. This produces much higher-resolution images than would otherwise be possible with conventional microscopes.

That technique was developed in the lab of Edward Boyden, an associate professor of biological engineering and brain and cognitive sciences at the MIT Media Lab, who is also an author of this study. Jill Crittenden, a research scientist at the McGovern Institute, is the lead author of the paper, which appears in the Proceedings of the National Academy of Sciences the week of Sept. 19.

Tracing a circuit

In this study, the researchers focused on a small region of the brain known as the striatum, which is part of the basal ganglia — a cluster of brain centers associated with habit formation, control of voluntary movement, emotion, and addiction. Malfunctions of the basal ganglia have been associated with Parkinson’s and Huntington’s diseases, as well as autism, obsessive-compulsive disorder, and Tourette’s syndrome.

Much of the striatum is uncharted territory, but Graybiel’s lab has previously identified clusters of cells there known as striosomes. She also found that these clusters receive very specific input from parts of the brain’s prefrontal cortex involved in processing emotions, and showed that this communication pathway is necessary for making decisions that require an anxiety-provoking cost-benefit analysis, such as choosing whether to take a job that pays more but forces a move away from family and friends.

Her studies also suggested that striosomes relay information to cells within a region called the substantia nigra, one of the brain’s main dopamine-producing centers. Dopamine has many functions in the brain, including roles in initiating movement and regulating mood.

To figure out how these regions might be communicating, Graybiel, Crittenden, and their colleagues used expansion microscopy to image the striosomes and discovered extensive connections between those clusters of cells and dopamine-producing cells of the substantia nigra. The dopamine-producing cells send down many tiny extensions known as dendrites that become entwined with axons that come up to meet them from the striosomes, forming a bouquet-like structure.

“With expansion microscopy, we could finally see direct connections between these cells by unraveling their unusual rope-like bundles of axons and dendrites,” Crittenden says. “What’s really exciting to us is we can see that it’s small discrete clusters of dopamine cells with bundles that are being targeted.”

Hard decisions

This finding expands the known decision-making circuit so that it encompasses the prefrontal cortex, striosomes, and a subset of dopamine-producing cells. Together, the striosomes may be acting as a gatekeeper that absorbs sensory and emotional information coming from the cortex and integrates it to produce a decision on how to react, which is initiated by the dopamine-producing cells, the researchers say.

To explore that possibility, the researchers plan to study mice in which they can selectively activate or shut down the striosome-dendron bouquet as the mice are prompted to make decisions requiring a cost-benefit analysis.

The researchers also plan to investigate whether these connections are disrupted in mouse models of Parkinson’s disease. MRI studies and postmortem analysis of brains of Parkinson’s patients have shown that death of dopamine cells in the substantia nigra is strongly correlated with the disease, but more work is needed to determine if this subset overlaps with the dopamine cells that form the striosome-dendron bouquets.

Seeing RNA at the nanoscale

Anne Trafton |

Cells contain thousands of messenger RNA molecules, which carry copies of DNA’s genetic instructions to the rest of the cell. MIT engineers have now developed a way to visualize these molecules in higher resolution than previously possible in intact tissues, allowing researchers to precisely map the location of RNA throughout cells.

Key to the new technique is expanding the tissue before imaging it. By making the sample physically larger, it can be imaged with very high resolution using ordinary microscopes commonly found in research labs.

“Now we can image RNA with great spatial precision, thanks to the expansion process, and we also can do it more easily in large intact tissues,” says Ed Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT, a member of MIT’s Media Lab and McGovern Institute for Brain Research, and the senior author of a paper describing the technique in the July 4 issue of Nature Methods.

Studying the distribution of RNA inside cells could help scientists learn more about how cells control their gene expression and could also allow them to investigate diseases thought to be caused by failure of RNA to move to the correct location.

Boyden and colleagues first described the underlying technique, known as expansion microscopy (ExM), last year, when they used it to image proteins inside large samples of brain tissue. In a paper appearing in Nature Biotechnology on July 4, the MIT team has now presented a new version of the technology that employs off-the-shelf chemicals, making it easier for researchers to use.

MIT graduate students Fei Chen and Asmamaw Wassie are the lead authors of the Nature Methods paper, and Chen and graduate student Paul Tillberg are the lead authors of the Nature Biotechnology paper.

A simpler process

The original expansion microscopy technique is based on embedding tissue samples in a polymer that swells when water is added. This tissue enlargement allows researchers to obtain images with a resolution of around 70 nanometers, which was previously possible only with very specialized and expensive microscopes.

However, that method posed some challenges because it requires generating a complicated chemical tag consisting of an antibody that targets a specific protein, linked to both a fluorescent dye and a chemical anchor that attaches the whole complex to a highly absorbent polymer known as polyacrylate. Once the targets are labeled, the researchers break down the proteins that hold the tissue sample together, allowing it to expand uniformly as the polyacrylate gel swells.

In their new studies, to eliminate the need for custom-designed labels, the researchers used a different molecule to anchor the targets to the gel before digestion. This molecule, which the researchers dubbed AcX, is commercially available and therefore makes the process much simpler.

AcX can be modified to anchor either proteins or RNA to the gel. In the Nature Biotechnology study, the researchers used it to anchor proteins, and they also showed that the technique works on tissue that has been previously labeled with either fluorescent antibodies or proteins such as green fluorescent protein (GFP).

“This lets you use completely off-the-shelf parts, which means that it can integrate very easily into existing workflows,” Tillberg says. “We think that it’s going to lower the barrier significantly for people to use the technique compared to the original ExM.”

Using this approach, it takes about an hour to scan a piece of tissue 500 by 500 by 200 microns, using a light sheet fluorescence microscope. The researchers showed that this technique works for many types of tissues, including brain, pancreas, lung, and spleen.

Imaging RNA

In the Nature Methods paper, the researchers used the same kind of anchoring molecule but modified it to target RNA instead. All of the RNAs in the sample are anchored to the gel, so they stay in their original locations throughout the digestion and expansion process.

After the tissue is expanded, the researchers label specific RNA molecules using a process known as fluorescence in situ hybridization (FISH), which was originally developed in the early 1980s and is widely used. This allows researchers to visualize the location of specific RNA molecules at high resolution, in three dimensions, in large tissue samples.

This enhanced spatial precision could allow scientists to explore many questions about how RNA contributes to cellular function. For example, a longstanding question in neuroscience is how neurons rapidly change the strength of their connections to store new memories or skills. One hypothesis is that RNA molecules encoding proteins necessary for plasticity are stored in cell compartments close to the synapses, poised to be translated into proteins when needed.

With the new system, it should be possible to determine exactly which RNA molecules are located near the synapses, waiting to be translated.
“People have found hundreds of these locally translated RNAs, but it’s hard to know where exactly they are and what they’re doing,” Chen says. “This technique would be useful to study that.”

Boyden’s lab is also interested in using this technology to trace the connections between neurons and to classify different subtypes of neurons based on which genes they are expressing.

The research was funded by the Open Philanthropy Project, the New York Stem Cell Foundation Robertson Award, the National Institutes of Health, the National Science Foundation, and Jeremy and Joyce Wertheimer.

Controlling RNA in living cells

Anne Trafton |

MIT researchers have devised a new set of proteins that can be customized to bind arbitrary RNA sequences, making it possible to image RNA inside living cells, monitor what a particular RNA strand is doing, and even control RNA activity.

The new strategy is based on human RNA-binding proteins that normally help guide embryonic development. The research team adapted the proteins so that they can be easily targeted to desired RNA sequences.

“You could use these proteins to do measurements of RNA generation, for example, or of the translation of RNA to proteins,” says Edward Boyden, an associate professor of biological engineering and brain and cognitive sciences at the MIT Media Lab. “This could have broad utility throughout biology and bioengineering.”

Unlike previous efforts to control RNA with proteins, the new MIT system consists of modular components, which the researchers believe will make it easier to perform a wide variety of RNA manipulations.

“Modularity is one of the core design principles of engineering. If you can make things out of repeatable parts, you don’t have to agonize over the design. You simply build things out of predictable, linkable units,” says Boyden, who is also a member of MIT’s McGovern Institute for Brain Research.

Boyden is the senior author of a paper describing the new system in the Proceedings of the National Academy of Sciences. The paper’s lead authors are postdoc Katarzyna Adamala and grad student Daniel Martin-Alarcon.

Modular code

Living cells contain many types of RNA that perform different roles. One of the best known varieties is messenger RNA (mRNA), which is copied from DNA and carries protein-coding information to cell structures called ribosomes, where mRNA directs protein assembly in a process called translation. Monitoring mRNA could tell scientists a great deal about which genes are being expressed in a cell, and tweaking the translation of mRNA would allow them to alter gene expression without having to modify the cell’s DNA.

To achieve this, the MIT team set out to adapt naturally occurring proteins called Pumilio homology domains. These RNA-binding proteins include sequences of amino acids that bind to one of the ribonucleotide bases or “letters” that make up RNA sequences — adenine (A), thymine (T), uracil (U), and guanine (G).

In recent years, scientists have been working on developing these proteins for experimental use, but until now it was more of a trial-and-error process to create proteins that would bind to a particular RNA sequence.

“It was not a truly modular code,” Boyden says, referring to the protein’s amino acid sequences. “You still had to tweak it on a case-by-case basis. Whereas now, given an RNA sequence, you can specify on paper a protein to target it.”

To create their code, the researchers tested out many amino acid combinations and found a particular set of amino acids that will bind each of the four bases at any position in the target sequence. Using this system, which they call Pumby (for Pumilio-based assembly), the researchers effectively targeted RNA sequences varying in length from six to 18 bases.

“I think it’s a breakthrough technology that they’ve developed here,” says Robert Singer, a professor of anatomy and structural biology, cell biology, and neuroscience at Albert Einstein College of Medicine, who was not involved in the research. “Everything that’s been done to target RNA so far requires modifying the RNA you want to target by attaching a sequence that binds to a specific protein. With this technique you just design the protein alone, so there’s no need to modify the RNA, which means you could target any RNA in any cell.”

RNA manipulation

In experiments in human cells grown in a lab dish, the researchers showed that they could accurately label mRNA molecules and determine how frequently they are being translated. First, they designed two Pumby proteins that would bind to adjacent RNA sequences. Each protein is also attached to half of a green fluorescent protein (GFP) molecule. When both proteins find their target sequence, the GFP molecules join and become fluorescent — a signal to the researchers that the target RNA is present.

Furthermore, the team discovered that each time an mRNA molecule is translated, the GFP gets knocked off, and when translation is finished, another GFP binds to it, enhancing the overall fluorescent signal. This allows the researchers to calculate how often the mRNA is being read.

This system can also be used to stimulate translation of a target mRNA. To achieve that, the researchers attached a protein called a translation initiator to the Pumby protein. This allowed them to dramatically increase translation of an mRNA molecule that normally wouldn’t be read frequently.

“We can turn up the translation of arbitrary genes in the cell without having to modify the genome at all,” Martin-Alarcon says.

The researchers are now working toward using this system to label different mRNA molecules inside neurons, allowing them to test the idea that mRNAs for different genes are stored in different parts of the neuron, helping the cell to remain poised to perform functions such as storing new memories. “Until now it’s been very difficult to watch what’s happening with those mRNAs, or to control them,” Boyden says.

These RNA-binding proteins could also be used to build molecular assembly lines that would bring together enzymes needed to perform a series of reactions that produce a drug or another molecule of interest.

Edward Boyden wins BBVA Foundation Frontiers of Knowledge Award

Anne Trafton |

Edward S. Boyden, a professor of media arts and sciences, biological engineering, and brain and cognitive sciences at MIT, has won the BBVA Foundation Frontiers of Knowledge Award in Biomedicine for his role in the development of optogenetics, a technique for controlling brain activity with light. Gero Miesenböck of the University of Oxford and Karl Deisseroth of Stanford University were also honored with the prize for their role in developing and refining the technique.

The BBVA Foundation Frontiers of Knowledge Awards are given annually for “outstanding contributions and radical advances in a broad range of scientific, technological and artistic areas.” The €400.000 prize in the category of biomedicine will be shared among the three neuroscientists.

“If we imagine the brain as a computer, optogenetics is a keyboard that allows us to send extremely precise commands,” says Boyden, a a faculty member at the MIT Media Lab with a joint appointment at MIT’s McGovern Institute for Brain Research. “It is a tool whereby we can control the brain with exquisite precision.”

Boyden joins an illustrious list of prize laureates including physicist Stephen Hawking and artificial intelligence pioneer Marvin Minsky of MIT, who died on January 24.

The BBVA Foundation will host the winners at an awards ceremony on June 21, 2016 at the foundation’s headquarters in Madrid, Spain.

About the BBVA Foundation Frontiers of Knowledge Awards

The BBVA Foundation promotes, funds and disseminates world-class scientific research and artistic creation, in the conviction that science, culture and knowledge hold the key to better opportunities for all world citizens. The Foundation designs and implements its programs in partnership with some of the leading scientific and cultural organizations in Spain and abroad, striving to identify and prioritize those projects with the power to significantly advance the frontiers of the known world.

The juries in each of eight categories are made up of leading international experts in their respective fields, who arrive at their decisions in a wholly independent manner, applying internationally recognized metrics of excellence. The BBVA Foundation is aided in the organization of the awards by the Spanish National Research Council (CSIC).