Research Area: Neurotechnology

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Next-generation optogenetic molecules control single neurons

Anne Trafton |

Researchers at MIT and Paris Descartes University have developed a new optogenetic technique that sculpts light to target individual cells bearing engineered light-sensitive molecules, so that individual neurons can be precisely stimulated.

Until now, it has been challenging to use optogenetics to target single cells with such precise control over both the timing and location of the activation. This new advance paves the way for studies of how individual cells, and connections among those cells, generate specific behaviors such as initiating a movement or learning a new skill.

“Ideally what you would like to do is play the brain like a piano. You would want to control neurons independently, rather than having them all march in lockstep the way traditional optogenetics works, but which normally the brain doesn’t do,” says Ed Boyden, an associate professor of brain and cognitive sciences and biological engineering at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research.

The new technique relies on a new type of light-sensitive protein that can be embedded in neuron cell bodies, combined with holographic light-shaping that can focus light on a single cell.

Boyden and Valentina Emiliani, a research director at France’s National Center for Scientific Research (CNRS) and director of the Neurophotonics Laboratory at Paris Descartes University, are the senior authors of the study, which appears in the Nov. 13 issue of Nature Neuroscience. The lead authors are MIT postdoc Or Shemesh and CNRS postdocs Dimitrii Tanese and Valeria Zampini.

Precise control

More than 10 years ago, Boyden and his collaborators first pioneered the use of light-sensitive proteins known as microbial opsins to manipulate neuron electrical activity. These opsins can be embedded into the membranes of neurons, and when they are exposed to certain wavelengths of light, they silence or stimulate the cells.

Over the past decade, scientists have used this technique to study how populations of neurons behave during brain tasks such as memory recall or habit formation. Traditionally, many cells are targeted simultaneously because the light shining into the brain strikes a relatively large area. However, as Boyden points out, neurons may have different functions even when they are near each other.

“Two adjacent cells can have completely different neural codes. They can do completely different things, respond to different stimuli, and play different activity patterns during different tasks,” he says.

To achieve independent control of single cells, the researchers combined two new advances: a localized, more powerful opsin and an optimized holographic light-shaping microscope.

For the opsin, the researchers used a protein called CoChR, which the Boyden lab discovered in 2014. They chose this molecule because it generates a very strong electric current in response to light (about 10 times stronger than that produced by channelrhodopsin-2, the first protein used for optogenetics).

They fused CoChR to a small protein that directs the opsin into the cell bodies of neurons and away from axons and dendrites, which extend from the neuron body. This helps to prevent crosstalk between neurons, since light that activates one neuron can also strike axons and dendrites of other neurons that intertwine with the target neuron.

Boyden then worked with Emiliani to combine this approach with a light-stimulation technique that she had previously developed, known as two-photon computer-generated holography (CGH). This can be used to create three-dimensional sculptures of light that envelop a target cell.

Traditional holography is based on reproducing, with light, the shape of a specific object, in the absence of that original object. This is achieved by creating an “interferogram” that contains the information needed to reconstruct an object that was previously illuminated by a reference beam. In computer generated holography, the interferogram is calculated by a computer without the need of any original object. Years ago, Emiliani’s research group demonstrated that combined with two-photon excitation, CGH can be used to refocus laser light to precisely illuminate a cell or a defined group of cells in the brain.

In the new study, by combining this approach with new opsins that cluster in the cell body, the researchers showed they could stimulate individual neurons with not only precise spatial control but also great control over the timing of the stimulation. When they target a specific neuron, it responds consistently every time, with variability that is less than one millisecond, even when the cell is stimulated many times in a row.

“For the first time ever, we can bring the precision of single-cell control toward the natural timescales of neural computation,” Boyden says.

Mapping connections

Using this technique, the researchers were able to stimulate single neurons in brain slices and then measure the responses from cells that are connected to that cell. This paves the way for possible diagramming of the connections of the brain, and analyzing how those connections change in real time as the brain performs a task or learns a new skill.

One possible experiment, Boyden says, would be to stimulate neurons connected to each other to try to figure out if one is controlling the others or if they are all receiving input from a far-off controller.

“It’s an open question,” he says. “Is a given function being driven from afar, or is there a local circuit that governs the dynamics and spells out the exact chain of command within a circuit? If you can catch that chain of command in action and then use this technology to prove that that’s actually a causal link of events, that could help you explain how a sensation, or movement, or decision occurs.”

As a step toward that type of study, the researchers now plan to extend this approach into living animals. They are also working on improving their targeting molecules and developing high-current opsins that can silence neuron activity.

Kirill Volynski, a professor at the Institute of Neurology at University College London, who was not involved in the research, plans to use the new technology in his studies of diseases caused by mutations of proteins involved in synaptic communication between neurons.

“This gives us a very nice tool to study those mutations and those disorders,” Volynski says. “We expect this to enable a major improvement in the specificity of stimulating neurons that have mutated synaptic proteins.”

The research was funded by the National Institutes of Health, France’s National Research Agency, the Simons Foundation for the Social Brain, the Human Frontiers Science Program, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the Defense Advanced Research Projects Agency.

Ten researchers from MIT and Broad receive NIH Director’s Awards

Anne Trafton |

The High-Risk, High-Reward Research (HRHR) program, supported by the National Institutes of Health (NIH) Common Fund, has awarded 86 grants to scientists with unconventional approaches to major challenges in biomedical and behavioral research. Ten of the awardees are affiliated with MIT and the Broad Institute of MIT and Harvard.

The NIH typically supports research projects, not individual scientists, but the HRHR program identifies specific researchers with innovative ideas to address gaps in biomedical research. The program issues four types of awards annually — the Pioneer Award, the New Innovator Award, the Transformative Research Award and the Early Independence Award — to “high-caliber investigators whose ideas stretch the boundaries of our scientific knowledge.”

Four researchers who are affiliated with either MIT or the Broad Institute received this year’s New Innovator Awards, which support “unusually innovative research” from early career investigators. They are:

  • Paul Blainey, an MIT assistant professor of biological engineering and a core member of the Broad Institute, is an expert in microanalysis systems for studies of individual molecules and cells. The award will fund the establishment a new technology that enables advanced readout from living cells.
  • Kevin Esvelt, an associate professor of media arts and sciences at MIT’s Media Lab, invents new ways to study and influence the evolution of ecosystems. Esvelt plans to use the NIH grant to develop powerful “daisy drive” systems for more precise genetic alterations of wild organisms. Such an intervention has the potential to serve as a powerful weapon against malaria, Zika, Lyme disease, and many other infectious diseases.
  • Evan Macosko is an associate member of the Broad Institute who develops molecular techniques to more deeply understand the function of cellular specialization in the nervous system. Macosko’s award will fund a novel technology, Slide-seq, which enables genome-wide expression analysis of brain tissue sections at single-cell resolution.
  • Gabriela Schlau-Cohen, an MIT assistant professor of chemistry, combines tools from chemistry, optics, biology, and microscopy to develop new approaches to study the dynamics of biological systems. Her award will be used to fund the development of a new nanometer-distance assay that directly accesses protein motion with unprecedented spatiotemporal resolution under physiological conditions.

Recipients of the Early Independence Award include three Broad Institute Fellows. The award recognizes “exceptional junior scientists” with an opportunity to skip traditional postdoctoral training and move immediately into independent research positions.

  • Ahmed Badran is a Broad Institute Fellow who studies the function of ribosomes and the control of protein synthesis. Ribosomes are important targets for antibiotics, and the NIH award will support the development of a new technology platform for probing ribosome function within living cells.
  • Fei Chen, a Broad Institute Fellow who is also a research affiliate at MIT’s McGovern Institute for Brain Research, has pioneered novel molecular and microscopy tools to illuminate biological pathways and function. He will use one of these tools, expansion microscopy, to explore the molecular basis of glioblastomas, an aggressive form of brain cancer.
  • Hilary Finucane, a Broad Institute Fellow who recently received her PhD from MIT’s Department of Mathematics, develops computational methods for analyzing biological data. She plans to develop methods to analyze large-scale genomic data to identify disease-relevant cell types and tissues, a necessary first step for understanding molecular mechanisms of disease.

Among the recipients of the NIH’s Pioneer Awards are Kay Tye, an assistant professor of brain and cognitive sciences at MIT and a member of MIT’s Picower Institute for Learning and Memory, and Feng Zhang, the James and Patricia Poitras ’63 Professor in Neuroscience, an associate professor of brain and cognitive sciences and biological engineering at MIT, a core member of the Broad Institute, and an investigator at MIT’s McGovern Institute for Brain Research. Recipients of this award are challenged to pursue “groundbreaking, high-impact approaches to a broad area of biomedical or behavioral science. Tye, who studies the brain mechanisms underlying emotion and behavior, will use her award to look at the neural representation of social homeostasis and social rank. Zhang, who pioneered the gene-editing technology known as CRISPR, plans to develop a suite of tools designed to achieve precise genome surgery for repairing disease-causing changes in DNA.

Ed Boyden, an associate professor of brain and cognitive sciences and biological engineering at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research, is a recipient of the Transformative Research Award. This award promotes “cross-cutting, interdisciplinary approaches that could potentially create or challenge existing paradigms.” Boyden, who develops new strategies for understanding and engineering brain circuits, will use the grant to develop high-speed 3-D imaging of neural activity.

This year, the NIH issued a total of 12 Pioneer Awards, 55 New Innovator Awards, 8 Transformative Research Awards, and 11 Early Independence Awards. The awards total $263 million and represent contributions from the NIH Common Fund; National Institute of General Medical Sciences; National Institute of Mental Health; National Center for Complementary and Integrative Health; and National Institute of Dental and Craniofacial Research.

“I continually point to this program as an example of the creative and revolutionary research NIH supports,” said NIH Director Francis S. Collins. “The quality of the investigators and the impact their research has on the biomedical field is extraordinary.”

Gene-editing technology developer Feng Zhang awarded $500,000 Lemelson-MIT Prize

Anne Trafton |

Feng Zhang, a pioneer of the revolutionary CRISPR gene-editing technology, TAL effector proteins, and optogenetics, is the recipient of the 2017 $500,000 Lemelson-MIT Prize, the largest cash prize for invention in the United States. Zhang is a core member of the Broad Institute of MIT and Harvard, an investigator at the McGovern Institute for Brain Research, the James and Patricia Poitras Professor in Neuroscience at MIT, and associate professor in the departments of Brain and Cognitive Sciences and Biological Engineering at MIT.

Zhang and his team were first to develop and demonstrate successful methods for using an engineered CRISPR-Cas9 system to edit genomes in living mouse and human cells and have turned CRISPR technology into a practical and shareable collection of tools for robust gene editing and epigenomic manipulation. CRISPR, short for Clustered Regularly Interspaced Short Palindromic Repeats, has been harnessed by Zhang and his team as a groundbreaking gene-editing tool that is simple and versatile to use. A key tenet of Zhang’s is to encourage further development and research through open sharing of tools and scientific collaboration. Zhang believes that wide use of CRISPR-based tools will further our understanding of biology, allowing scientists to identify genetic differences that contribute to diseases and, eventually, provide the basis for new therapeutic techniques.

Zhang’s lab has trained thousands of researchers to use CRISPR technology, and since 2013 he has shared over 40,000 plasmid samples with labs around the world both directly and through the nonprofit Addgene, enabling wide use of his CRISPR tools in their research.

Zhang began working in a gene therapy laboratory at the age of 16 and has played key roles in the development of multiple technologies. Prior to harnessing CRISPR-Cas9, Zhang engineered microbial TAL effectors (TALEs) for use in mammalian cells, working with colleagues at Harvard University, authoring multiple publications on the subject and becoming a co-inventor on several patents on TALE-based technologies. Zhang was also a key member of the team at Stanford University that harnessed microbial opsins for developing optogenetics, which uses light signals and light-sensitive proteins to monitor and control activity in brain cells. This technology can help scientists understand how cells in the brain affect mental and neurological illnesses. Zhang has co-authored multiple publications on optogenetics and is a co-inventor on several patents related to this technology.

Zhang’s numerous scientific discoveries and inventions, as well as his commitment to mentorship and collaboration, earned him the Lemelson-MIT Prize, which honors outstanding mid-career inventors who improve the world through technological invention and demonstrate a commitment to mentorship in science, technology, engineering and mathematics (STEM).

“Feng’s creativity and dedication to problem-solving impressed us,” says Stephanie Couch, executive director of the Lemelson-MIT Program. “Beyond the breadth of his own accomplishments, Feng and his lab have also helped thousands of scientists across the world access the new technology to advance their own scientific discoveries.”

“It is a tremendous honor to receive the Lemelson-MIT Prize and to join the company of so many incredibly impactful inventors who have won this prize in years past,” says Zhang. “Invention has always been a part of my life; I think about new problems every day and work to solve them creatively. This prize is a testament to the passionate work of my team and the support of my family, teachers, colleagues and counterparts around the world.”

The $500,000 prize, which bears no restrictions in how it can be used, is made possible through the support of The Lemelson Foundation, the world’s leading funder of invention in service of social and economic change.

“We are thrilled to honor Dr. Zhang, who we commend for his advancements in genetics, and more importantly, his willingness to share his discoveries to advance the work of others around the world,” says Dorothy Lemelson, chair of The Lemelson Foundation. “Zhang’s work is inspiring a new generation of inventors to tackle the biggest problems of our time.”

Zhang will speak at EmTech MIT, the annual conference on emerging technologies hosted by MIT Technology Review at the MIT Media Lab on Tuesday, Nov. 7.

The Lemelson-MIT Program is now seeking nominations for the 2018 $500,000 Lemelson-MIT Prize. Please contact the Lemelson-MIT Program at awards-lemelson@mit.edu for more information or visit the MIT-Lemelson Prize website.

Robotic system monitors specific neurons

Anne Trafton |

Recording electrical signals from inside a neuron in the living brain can reveal a great deal of information about that neuron’s function and how it coordinates with other cells in the brain. However, performing this kind of recording is extremely difficult, so only a handful of neuroscience labs around the world do it.

To make this technique more widely available, MIT engineers have now devised a way to automate the process, using a computer algorithm that analyzes microscope images and guides a robotic arm to the target cell.

This technology could allow more scientists to study single neurons and learn how they interact with other cells to enable cognition, sensory perception, and other brain functions. Researchers could also use it to learn more about how neural circuits are affected by brain disorders.

“Knowing how neurons communicate is fundamental to basic and clinical neuroscience. Our hope is this technology will allow you to look at what’s happening inside a cell, in terms of neural computation, or in a disease state,” says Ed Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research.

Boyden is the senior author of the paper, which appears in the Aug. 30 issue of Neuron. The paper’s lead author is MIT graduate student Ho-Jun Suk.

Precision guidance

For more than 30 years, neuroscientists have been using a technique known as patch clamping to record the electrical activity of cells. This method, which involves bringing a tiny, hollow glass pipette in contact with the cell membrane of a neuron, then opening up a small pore in the membrane, usually takes a graduate student or postdoc several months to learn. Learning to perform this on neurons in the living mammalian brain is even more difficult.

There are two types of patch clamping: a “blind” (not image-guided) method, which is limited because researchers cannot see where the cells are and can only record from whatever cell the pipette encounters first, and an image-guided version that allows a specific cell to be targeted.

Five years ago, Boyden and colleagues at MIT and Georgia Tech, including co-author Craig Forest, devised a way to automate the blind version of patch clamping. They created a computer algorithm that could guide the pipette to a cell based on measurements of a property called electrical impedance — which reflects how difficult it is for electricity to flow out of the pipette. If there are no cells around, electricity flows and impedance is low. When the tip hits a cell, electricity can’t flow as well and impedance goes up.

Once the pipette detects a cell, it can stop moving instantly, preventing it from poking through the membrane. A vacuum pump then applies suction to form a seal with the cell’s membrane. Then, the electrode can break through the membrane to record the cell’s internal electrical activity.

The researchers achieved very high accuracy using this technique, but it still could not be used to target a specific cell. For most studies, neuroscientists have a particular cell type they would like to learn about, Boyden says.

“It might be a cell that is compromised in autism, or is altered in schizophrenia, or a cell that is active when a memory is stored. That’s the cell that you want to know about,” he says. “You don’t want to patch a thousand cells until you find the one that is interesting.”

To enable this kind of precise targeting, the researchers set out to automate image-guided patch clamping. This technique is difficult to perform manually because, although the scientist can see the target neuron and the pipette through a microscope, he or she must compensate for the fact that nearby cells will move as the pipette enters the brain.

“It’s almost like trying to hit a moving target inside the brain, which is a delicate tissue,” Suk says. “For machines it’s easier because they can keep track of where the cell is, they can automatically move the focus of the microscope, and they can automatically move the pipette.”

By combining several imaging processing techniques, the researchers came up with an algorithm that guides the pipette to within about 25 microns of the target cell. At that point, the system begins to rely on a combination of imagery and impedance, which is more accurate at detecting contact between the pipette and the target cell than either signal alone.

The researchers imaged the cells with two-photon microscopy, a commonly used technique that uses a pulsed laser to send infrared light into the brain, lighting up cells that have been engineered to express a fluorescent protein.

Using this automated approach, the researchers were able to successfully target and record from two types of cells — a class of interneurons, which relay messages between other neurons, and a set of excitatory neurons known as pyramidal cells. They achieved a success rate of about 20 percent, which is comparable to the performance of highly trained scientists performing the process manually.

Unraveling circuits

This technology paves the way for in-depth studies of the behavior of specific neurons, which could shed light on both their normal functions and how they go awry in diseases such as Alzheimer’s or schizophrenia. For example, the interneurons that the researchers studied in this paper have been previously linked with Alzheimer’s. In a recent study of mice, led by Li-Huei Tsai, director of MIT’s Picower Institute for Learning and Memory, and conducted in collaboration with Boyden, it was reported that inducing a specific frequency of brain wave oscillation in interneurons in the hippocampus could help to clear amyloid plaques similar to those found in Alzheimer’s patients.

“You really would love to know what’s happening in those cells,” Boyden says. “Are they signaling to specific downstream cells, which then contribute to the therapeutic result? The brain is a circuit, and to understand how a circuit works, you have to be able to monitor the components of the circuit while they are in action.”

This technique could also enable studies of fundamental questions in neuroscience, such as how individual neurons interact with each other as the brain makes a decision or recalls a memory.

Bernardo Sabatini, a professor of neurobiology at Harvard Medical School, says he is interested in adapting this technique to use in his lab, where students spend a great deal of time recording electrical activity from neurons growing in a lab dish.

“It’s silly to have amazingly intelligent students doing tedious tasks that could be done by robots,” says Sabatini, who was not involved in this study. “I would be happy to have robots do more of the experimentation so we can focus on the design and interpretation of the experiments.”

To help other labs adopt the new technology, the researchers plan to put the details of their approach on their web site, autopatcher.org.

Other co-authors include Ingrid van Welie, Suhasa Kodandaramaiah, and Brian Allen. The research was funded by Jeremy and Joyce Wertheimer, the National Institutes of Health (including the NIH Single Cell Initiative and the NIH Director’s Pioneer Award), the HHMI-Simons Faculty Scholars Program, and the New York Stem Cell Foundation-Robertson Award.

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.

A radiation-free approach to imaging molecules in the brain

Anne Trafton |

Scientists hoping to get a glimpse of molecules that control brain activity have devised a new probe that allows them to image these molecules without using any chemical or radioactive labels.

Currently the gold standard approach to imaging molecules in the brain is to tag them with radioactive probes. However, these probes offer low resolution and they can’t easily be used to watch dynamic events, says Alan Jasanoff, an MIT professor of biological engineering.

Jasanoff and his colleagues have developed new sensors consisting of proteins designed to detect a particular target, which causes them to dilate blood vessels in the immediate area. This produces a change in blood flow that can be imaged with magnetic resonance imaging (MRI) or other imaging techniques.

“This is an idea that enables us to detect molecules that are in the brain at biologically low levels, and to do that with these imaging agents or contrast agents that can ultimately be used in humans,” Jasanoff says. “We can also turn them on and off, and that’s really key to trying to detect dynamic processes in the brain.”

In a paper appearing in the Dec. 2 issue of Nature Communications, Jasanoff and his colleagues used these probes to detect enzymes called proteases, but their ultimate goal is to use them to monitor the activity of neurotransmitters, which act as chemical messengers between brain cells.

The paper’s lead authors are postdoc Mitul Desai and former MIT graduate student Adrian Slusarczyk. Recent MIT graduate Ashley Chapin and postdoc Mariya Barch are also authors of the paper.

Indirect imaging

To make their probes, the researchers modified a naturally occurring peptide called calcitonin gene-related peptide (CGRP), which is active primarily during migraines or inflammation. The researchers engineered the peptides so that they are trapped within a protein cage that keeps them from interacting with blood vessels. When the peptides encounter proteases in the brain, the proteases cut the cages open and the CGRP causes nearby blood vessels to dilate. Imaging this dilation with MRI allows the researchers to determine where the proteases were detected.

“These are molecules that aren’t visualized directly, but instead produce changes in the body that can then be visualized very effectively by imaging,” Jasanoff says.

Proteases are sometimes used as biomarkers to diagnose diseases such as cancer and Alzheimer’s disease. However, Jasanoff’s lab used them in this study mainly to demonstrate the validity their approach. Now, they are working on adapting these imaging agents to monitor neurotransmitters, such as dopamine and serotonin, that are critical to cognition and processing emotions.

To do that, the researchers plan to modify the cages surrounding the CGRP so that they can be removed by interaction with a particular neurotransmitter.

“What we want to be able to do is detect levels of neurotransmitter that are 100-fold lower than what we’ve seen so far. We also want to be able to use far less of these molecular imaging agents in organisms. That’s one of the key hurdles to trying to bring this approach into people,” Jasanoff says.

Jeff Bulte, a professor of radiology and radiological science at the Johns Hopkins School of Medicine, described the technique as “original and innovative,” while adding that its safety and long-term physiological effects will require more study.

“It’s interesting that they have designed a reporter without using any kind of metal probe or contrast agent,” says Bulte, who was not involved in the research. “An MRI reporter that works really well is the holy grail in the field of molecular and cellular imaging.”

Tracking genes

Another possible application for this type of imaging is to engineer cells so that the gene for CGRP is turned on at the same time that a gene of interest is turned on. That way, scientists could use the CGRP-induced changes in blood flow to track which cells are expressing the target gene, which could help them determine the roles of those cells and genes in different behaviors. Jasanoff’s team demonstrated the feasibility of this approach by showing that implanted cells expressing CGRP could be recognized by imaging.

“Many behaviors involve turning on genes, and you could use this kind of approach to measure where and when the genes are turned on in different parts of the brain,” Jasanoff says.

His lab is also working on ways to deliver the peptides without injecting them, which would require finding a way to get them to pass through the blood-brain barrier. This barrier separates the brain from circulating blood and prevents large molecules from entering the brain.

The research was funded by the National Institutes of Health BRAIN Initiative, the MIT Simons Center for the Social Brain, and fellowships from the Boehringer Ingelheim Fonds and the Friends of the McGovern Institute.

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.

Divide and conquer

Anne Trafton |

Cell populations are remarkably diverse—even within the same tissue or cell type. Each cell, no matter how similar it appears to its neighbor, behaves and responds to its environment in its own way depending on which of its genes are expressed and to what degree. How genes are expressed in each cell—how RNA is “read” and turned into proteins—determines what jobs the cell performs in the body.

Traditionally, researchers have taken an en masse approach to studying gene expression, extracting an averaged measurement derived from an entire cell population. But over the past few years, single cell sequencing has emerged as a transformative tool, enabling scientists to look at gene expression within cells at an unprecedented resolution. With single-cell technologies, researchers have been able to examine the heterogeneity within cell populations; identify rare cells; observe interactions between diverse cell types; and better understand how these interactions influence health and disease.

This week in Science, researchers from the labs of Broad core institute members Aviv Regev and Feng Zhang, of MIT and MIT’s McGovern Institute respectively, report on their newest contribution to this field: Div-Seq, a method that enables the study of previously intractable and rare cell types in the brain. The study’s first authors, Naomi Habib, a postdoctoral fellow in the Regev and Zhang labs, and Yinqing Li, also a postdoc in the Zhang lab, sat down to answer questions about this groundbreaking approach.

Why is it so important to study neurons at the single cell level?

Li: Neuropsychiatric diseases are often too complex to find an effective treatment, partly because the neurons, that underly the disease are heterogeneous. Only when we have a full atlas of every neuron type at single-cell resolution—and figure out which ones are the cause of the pathology—can we develop a targeted and effective therapy. With this goal in mind, we developed sNuc-Seq and Div-Seq to make it technologically possible to profile neurons from the adult brain at significantly improved resolution, fidelity, and sensitivity.

Scientifically, what was the need that you were trying to address when you started this study?

Habib: Going into this study we were specifically interested in studying so-called “newborn” neurons, which are rare and hard to find. We think of our brain as being non-regenerative, but in fact there are rare, neuronal stem cells in specific areas of the brain that divide and create new neurons throughout our lives. We wanted to understand how gene expression changed as these cells developed. Typically when people studied gene expression in the brain they just mashed up tissue and took average measurements from that mixture. Such “bulk” measurements are hard to interpret and we lose the gene expression signals that come from individual cell types.

When I joined the Zhang and Regev labs, some of the first single cell papers were coming out, and it seemed like the perfect approach for advancing the way we do neuroscience research; we could measure RNA at the single cell level and really understand what different cell types were there, including rare cells, and what they contribute to different brain functions. But there was a problem. Neurons do not look like regular cells: they are intricately connected. In the process of separating them, the cells do not stay intact and their RNA gets damaged, and this problem increases with age.

So what was your solution?

Habib: Isolating single neurons is problematic, but the nucleus is nice and round and relatively easy to isolate. That led us to ask, “Why not try single nucleus RNA sequencing instead of single cell sequencing?” We called it “sNuc-Seq.”

It worked well. We get a lot of information from the RNA in the nucleus; we can learn what cell type we’re looking at, what state of development it’s in, and what kind of processes are going on in the cell—all of the key information we would want to get from RNA sequencing.

Then, to make it possible to find the rare newborn neurons, we developed Div-Seq. It’s based on sNuc-Seq, but we introduce a compound that incorporates into DNA and labels the DNA while it’s replicating, so it’s specific for newly divided cells. Because we already isolated the nuclei, it’s fairly simple from there to fluorescently tag the labeled cells, sort them, and get RNA for sequencing.

You tested this method while preparing your paper. What did you find?

Habib: We studied “newborn” neurons from the brain across multiple time-points. We could see the changes in gene expression that occur throughout adult neurogenesis; the cells transition from state-to-state—from stem cells to mature neurons—and during these transitions, we found a coordinated change in the expression of hundreds of genes. It was beautiful to see these signatures, and they enabled us to pinpoint regulatory genes expressed during specific points of the cell differentiation process.

We were also able to look at where regeneration occurs. We decided to look in the spinal cord because there is a lot of interest in understanding the potential of regeneration to help with spinal cord injury. Div-Seq enabled us to scan millions of neurons and isolate the small percentage that were dividing and characterize each by its RNA signature. We found that within the spinal cord there is ongoing regeneration of a specific type of neuron—GABAergic neurons. That was an exciting finding that also showed the utility of our method.

Are the data you get from this method compatible with data from previous single-cell techniques?

Li: Because this method is specifically designed to address the particular challenges of profiling neurons, the data from this method is distinct from that obtained from previous single-cell techniques. Since the data was new to this approach, a novel computational tool was developed in this project in order to fully reveal the rich information, which is now available to the scientific community.

Are there other benefits of using this method?

Habib: Single nucleus RNA-seq enables the study of the adult and aging brain at the single cell level, which is now being applied to study cellular diversity across the brain during health and disease. Our approach also makes it easier to explore any complex tissue where single cells are hard to obtain for technical reasons. One important aspect is that it works on frozen and fixed tissue, which opens up opportunities to study human samples, such as biopsies, that may be collected overseas or frozen for days or even years.

Additionally, Div-Seq opens new ways to look at the rare process of adult neurogenesis and other regenerative processes that might have been challenging before. Because Div- Seq specifically labels dividing cells, it is a great tool to use to see what cells are dividing in a given tissue and to track gene expression changes over time.

What is the endgame of studying these processes? Can you put this work in context of human health and disease?

Li: We hope that the methods in this study will provide a starting point and method for future work on neuropsychiatric diseases. As we expand our understanding of cell types and their signatures, we can start to ask questions like: Which cells express disease associated genes? Where are these cells located in the brain? What other genes are expressed in these cells, and which might serve as potential drug targets? This approach could help bridge human genetic association studies and molecular neurobiology and open new windows into disease pathology and potential treatments.

Habib: These two methods together enable many applications, which were either very hard or impossible to do before. For example, we characterized the cellular diversity of a region of the brain important for learning and memory—the first region affected in Alzheimer’s disease. Having that understanding—knowing what the normal state of cells is at the molecular level and what went wrong in each individual cell type—can advance our understanding of the disease and perhaps aid in the search for a treatment. We are also excited by the prospect of finding naturally-occurring regeneration in the brain and spine, which could have implications for the field of regenerative medicine in treating, for example, neuronal degeneration or spinal injury.

Paper cited:

Habib N, Li Y, et al. Div-Seq: Single nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. Science. Online July 28, 2016.

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.