Researcher: Feng Zhang

Feng Zhang Wins the 2017 Blavatnik National Award for Young Scientists

Anne Trafton |

The Blavatnik Family Foundation and the New York Academy of Sciences today announced the 2017 Laureates of the Blavatnik National Awards for Young Scientists. Starting with a pool of 308 nominees – the most promising scientific researchers aged 42 years and younger nominated by America’s top academic and research institutions – a distinguished jury first narrowed their selections to 30 Finalists, and then to three outstanding Laureates, one each from the disciplines of Life Sciences, Chemistry and Physical Sciences & Engineering. Each Laureate will receive $250,000 – the largest unrestricted award of its kind for early career scientists and engineers. This year’s Blavatnik National Laureates are:

Feng Zhang, PhD, Core Member, Broad Institute of MIT and Harvard; Associate Professor of Brain and Cognitive Sciences and Biomedical Engineering, MIT; Robertson Investigator, New York Stem Cell Foundation; James and Patricia Poitras ’63 Professor in Neuroscience, McGovern Institute for Brain Research at MIT. Dr. Zhang is being recognized for his role in developing the CRISPR-Cas9 gene-editing system and demonstrating pioneering uses in mammalian cells, and for his development of revolutionary technologies in neuroscience.

Melanie S. Sanford, PhD, Moses Gomberg Distinguished University Professor and Arthur F. Thurnau Professor of Chemistry, University of Michigan. Dr. Sanford is being celebrated for developing simpler chemical approaches – with less environmental impact – to the synthesis of molecules that have applications ranging from carbon dioxide recycling to drug discovery.

Yi Cui, PhD, Professor of Materials Science and Engineering, Photon Science and Chemistry, Stanford University and SLAC National Accelerator Laboratory. Dr. Cui is being honored for his technological innovations in the use of nanomaterials for environmental protection and the development of sustainable energy sources.

“The work of these three brilliant Laureates demonstrates the exceptional science being performed at America’s premiere research institutions and the discoveries that will make the lives of future generations immeasurably better,” said Len Blavatnik, Founder and Chairman of Access Industries, head of the Blavatnik Family Foundation, and an Academy Board Governor.

“Each of our 2017 National Laureates is shifting paradigms in areas that profoundly affect the way we tackle the health of our population and our planet — improved ways to store energy, “greener” drug and fuel production, and novel tools to correct disease-causing genetic mutations,” said Ellis Rubinstein, President and CEO of the Academy and Chair of the Awards’ Scientific Advisory Council. “Recognition programs like the Blavatnik Awards provide incentives and resources for rising stars, and help them to continue their important work. We look forward to learning where their innovations and future discoveries will take us in the years ahead.”

The annual Blavatnik Awards, established in 2007 by the Blavatnik Family Foundation and administered by the New York Academy of Sciences, recognize exceptional young researchers who will drive the next generation of innovation by answering today’s most complex and intriguing scientific questions.

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.”

Scientists unveil CRISPR-based diagnostic platform

Anne Trafton |

A team of scientists from the Broad Institute of MIT and Harvard, the McGovern Institute for Brain Research at MIT, the Institute for Medical Engineering and Science at MIT, and the Wyss Institute for Biologically Inspired Engineering at Harvard University has adapted a CRISPR protein that targets RNA (rather than DNA), for use as a rapid, inexpensive, highly sensitive diagnostic tool with the potential to transform research and global public health.

In a study published today in Science, Broad Institute members Feng Zhang, Jim Collins, Deb Hung, Aviv Regev, and Pardis Sabeti describe how this RNA-targeting CRISPR enzyme was harnessed as a highly sensitive detector — able to indicate the presence of as little as a single molecule of a target RNA or DNA. Co-first authors Omar Abudayyeh and Jonathan Gootenberg, graduate students at MIT and Harvard, respectively, dubbed the new tool SHERLOCK (Specific High-sensitivity Enzymatic Reporter unLOCKing); this technology could one day be used to respond to viral and bacterial outbreaks, monitor antibiotic resistance, and detect cancer.

The scientists demonstrate the method’s versatility on a range of applications, including:

• detecting the presence of Zika virus in patient blood or urine samples within hours;
• distinguishing between the genetic sequences of African and American strains of Zika virus;
• discriminating specific types of bacteria, such as E. coli;
• detecting antibiotic resistance genes;
• identifying cancerous mutations in simulated cell-free DNA fragments; and
• rapidly reading human genetic information, such as risk of heart disease, from a saliva sample.

Because the tool can be designed for use as a paper-based test that does not require refrigeration, the researchers say it is well-suited for fast deployment and widespread use inside and outside of traditional settings — such as at a field hospital during an outbreak, or a rural clinic with limited access to advanced equipment.

“It’s exciting that the Cas13a enzyme, which was originally identified in our collaboration with Eugene Koonin to study the basic biology of bacterial immunity, can be harnessed to achieve such extraordinary sensitivity, which will be powerful for both science and clinical medicine,” says Feng Zhang, core institute member of the Broad Institute, an investigator at the McGovern Institute, and the James and Patricia Poitras ’63 Professor in Neuroscience and associate professor in the departments of Brain and Cognitive Sciences and Biological Engineering at MIT.

In June 2016, Zhang and his colleagues first characterized the RNA-targeting CRISPR enzyme, now called Cas13a (previously known as C2c2), which can be programmed to cleave particular RNA sequences in bacterial cells. Unlike DNA-targeting CRISPR enzymes (such as Cas9 and Cpf1), Cas13a can remain active after cutting its intended RNA target and may continue to cut other nontargeted RNAs in a burst of activity that Zhang lab scientists referred to as “collateral cleavage.” In their paper and patent filing, the team described a wide range of biotechnological applications for the system, including harnessing RNA cleavage and collateral activity for basic research, diagnostics, and therapeutics.

In a paper in Nature in September 2016, Jennifer Doudna, Alexandra East-Seletsky, and their colleagues at the University of California at Berkeley employed the Cas13a collateral cleavage activity for RNA detection. That method required the presence of many millions of molecules, however, and therefore lacked the sensitivity required for many research and clinical applications.

The method reported today is a million-fold more sensitive. This increase was the result of a collaboration between Zhang and his team and Broad Institute member Jim Collins, who had been working on diagnostics for Zika virus.

Working together, the Zhang and Collins teams were able to use a different amplification process, relying on body heat, to boost the levels of DNA or RNA in their test samples. Once the level was increased, the team applied a second amplification step to convert the DNA to RNA, which enabled them to increase the sensitivity of the RNA-targeting CRISPR by a millionfold, all with a tool that can be used in nearly any setting.

“We can now effectively and readily make sensors for any nucleic acid, which is incredibly powerful when you think of diagnostics and research applications,” says Collins, the Termeer Professor of Medical Engineering and Science at MIT and core faculty member at the Wyss Institute. “This tool offers the sensitivity that could detect an extremely small amount of cancer DNA in a patient’s blood sample, for example, which would help researchers understand how cancer mutates over time. For public health, it could help researchers monitor the frequency of antibiotic-resistant bacteria in a population. The scientific possibilities get very exciting very quickly.”

One of the most urgent and obvious applications for this new diagnostic tool would be as a rapid, point-of-care diagnostic for infectious disease outbreaks in resource-poor areas.
“There is great excitement around this system,” says Deb Hung, co-author and co-director of the Broad’s Infectious Disease and Microbiome Program. “There is still much work to be done, but if SHERLOCK can be developed to its full potential it could fundamentally change the diagnosis of common and emerging infectious diseases.”

“One thing that’s especially powerful about SHERLOCK is its ability to start testing without a lot of complicated and time-consuming upstream experimental work,” says Pardis Sabeti, also a co-author in the paper. In the wake of the ongoing Zika outbreak, Sabeti and the members of her lab have been working to collect samples, rapidly sequence genomes, and share data in order to accelerate the outbreak response effort. “This ability to take raw samples and immediately start processing could transform the diagnosis of Zika and a boundless number of other infectious diseases,” she says. “This is just the beginning.”

Additional authors include Jeong Wook Lee, Patrick Essletzbichler, Aaron J. Dy, Julia Joung, Vanessa Verdine, Nina Donghia, Nichole M. Daringer, Catherine A. Freije, Cameron Myhrvold, Roby P. Bhattacharyya, Jonathan Livny, and Eugene V. Koonin.

Feng Zhang named James and Patricia Poitras Professor in Neuroscience

Anne Trafton |

The McGovern Institute for Brain Research at MIT has announced the appointment of Feng Zhang as the inaugural chairholder of the James and Patricia Poitras (1963) Professorship in Neuroscience. This new endowed professorship was made possible through a generous gift by Patricia and James Poitras ’63. The professorship is the second endowed chair Mr. and Mrs. Poitras have established at MIT, and extends their longtime support for mental health research.

“This newly created chair further enhances all that Jim and Pat have done for mental illness research at MIT,” said Robert Desimone, director of the McGovern Institute. “The Poitras Center for Affective Disorders Research has galvanized psychiatric research in multiple labs at MIT, and this new professorship will grant critical support to Professor Zhang’s genome engineering technologies, which continue to significantly advance mental illness research in labs worldwide.”

James and Patricia Poitras founded the Poitras Center for Affective Disorders Research at MIT in 2007. The Center has enabled dozens of advances in mental illness research, including the development of new disease models and novel technologies. Partnerships between the center and McLean Hospital have also resulted in improved methods for predicting and treating psychiatric disorders. In 2003, the Poitras Family established the James W. (1963) and Patricia T. Poitras Professor of Neuroscience in MIT’s Department of Brain and Cognitive Sciences, currently held by Guoping Feng.

“Providing support for high-risk, high-reward projects that have the potential to significantly impact individuals living with mental illness has been immensely rewarding to us,” Mr. and Mrs. Poitras say. “We are most interested in bringing basic scientific research to bear on new treatment options for psychiatric diseases. The work of Feng Zhang and his team is immeasurably promising to us and to the field of brain disorders research.”

Zhang joined MIT in 2011 as an investigator in the McGovern Institute for Brain Research and an assistant professor in the departments of Brain and Cognitive Sciences and Biological Engineering. In 2013, he was named the W.M. Keck Career Development Professor in Biomedical Engineering, and in 2016 he was awarded tenure. In addition to his roles at MIT, Zhang is a core member of the Broad Institute of Harvard and MIT.

“I am deeply honored to be named the first James and Patricia Poitras Professor in Neuroscience,” says Zhang. “The Poitras Family and I share a passion for researching, treating, and eventually curing major mental illness. This chair is a terrific recognition of my group’s dedication to advancing genomic and molecular tools to research and one day solve psychiatric illness.”

Zhang earned his BA in chemistry and physics from Harvard College and his PhD in chemistry from Stanford University. Zhang has received numerous awards for his work in genome editing, especially the CRISPR gene editing system, and optogenetics. These include the Perl-UNC Neuroscience Prize, the National Science Foundation’s Alan T. Waterman Award, the Jacob Heskel Gabbay Award in Biotechnology and Medicine, the Society for Neuroscience’s Young Investigator Award, the Okazaki Award, the Canada Gairdner International Award, and the Tang Prize. Zhang is a founder of Editas Medicine, a genome editing company founded by world leaders in the fields of genome editing, protein engineering, and molecular and structural biology.

Reading the rules of gene regulation

Anne Trafton |

We have a reasonable understanding of the rules behind the genome’s protein-coding components. We can look at a DNA sequence and point with confidence to where a gene’s coding region begins, where it ends, and pieces of its geography.

For the remaining 98 percent of the genome — the part that dictates which genes a cell reads — it’s a different story. What knowledge we have of the rules governing this “dark matter” comes from from studying and manipulating individual bits of noncoding DNA one at a time. The rulebook that governs how the noncoding genome works, however, has remained out of reach.

“Ninety percent of the genetic variations that affect human disease are in the noncoding regions,” said Broad founding director Eric Lander. “But we haven’t had any way to tell, in a systematic way, which regulators affect which genes.”

In a pair of newly published Science papers, two research teams at the Broad show how methods leveraging CRISPR gene editing could help grasp those rules.

Using two complementary approaches, the teams — one from the Lander lab, the other from that of Broad Core Institute Member and McGovern Institute for Brain Research investigator Feng Zhang — used CRISPR as a tool to systematically probe thousands of noncoding DNA sequences simultaneously (much as Zhang and others did previously with coding DNA). In the process, both identified several interesting genetic regulators, including ones millions of bases away from the genes they control.

“We’d like to be able to catalog the noncoding elements that control every gene’s expression in every cell type,” said Jesse Engreitz, a postdoctoral fellow in the Lander lab and senior author on one of the papers. “This is a massive problem in biology, and it’s a rate-limiting step for connecting many genetic associations to their fundamental molecular mechanisms and to human disease.”
Variations on a theme

Both teams used pooled CRISPR screens (which scan and edit large swaths of the genome simultaneously using a molecular scalpel called the Cas9 enzyme and thousands of guide RNAs, which target Cas9 to specific sequences) to perturb noncoding DNA. But they did so in different ways.

Zhang, Neville Sanjana (a Zhang lab alum and now a core member of the New York Genome Center), and Jason Wright (another Zhang alum, now at Homology Medicines) used Cas9 to make precise edits to overlapping stretches of noncoding DNA — in their case, in regions surrounding three genes (NF1, NF2, and CUL3) whose functional loss has been linked to drug resistance in a form of melanoma.

“This approach lets us induce a wide diversity of mutations,” Sanjana explained. “We don’t have to speculate how a given sequence might best be disrupted.”

Engreitz, Lander, and graduate student Charles Fulco, on the other hand, employed a CRISPR interference system, using an inactive or “dead” form of Cas9 fused to a protein fragment called a KRAB domain to silence their target sequences (around MYC and GATA1, the genes for two important transcription factors).

“This system provides a good quantitative estimate of a given noncoding region’s regulatory influence,” Engreitz said. “It both shows you where the dials are that control a given gene, and tells you how much each dial matters.”

Each team then used a functional readout (increased drug resistance in melanoma cells for Sanjana, Wright, and Zhang; a drop in cell growth for Fulco, Lander, and Engreitz) and deep sequencing to see which of their guide RNAs impacted expression of their genes of interest and map the regulators those guide RNAs affected.

The two teams’ findings, confirmed with an array of additional techniques (e.g., chromatin profiling, 3D conformational capture, transcription factor profiling), point to the potential for tracing the noncoding genome’s regulatory wiring leveraging CRISPR tools. Fulco, Lander, and Engreitz found and ranked the relative importance of seven MYC and three GATA1 enhancers (short pieces of noncoding DNA that boost a gene’s chances of being read). Sanjana, Wright, and Zhang’s screen pinpointed numerous enhancers and transcription factor binding sites just for CUL3 alone.
Studying sequences in their natural habitat

While similar in principle to traditional reporter assays (where scientists couple interesting sequences to reporter genes in plasmids), these pooled CRISPR screens have a distinct difference: they probe the sequences directly, in their native habitat.

“The screens interrogate the sequences in their endogenous context,” Sanjana emphasized. “Reporter assays can be very helpful, but they lack the 3D conformation or local chromatin environment of the native genomic context. Here, the regulatory sequences undergo all of their normal interactions.”

“For example, we could see long-range loops between gene promoters and noncoding sites thousands of bases away,” he continued. “We would have missed these interesting 3D interactions entirely if we just looked at these regulatory elements in isolation.”

One limitation, Engreitz noted, is that neither CRISPR approach, in its current form, addresses the genome’s inherent redundancy. “Maybe it’s not enough to break one enhancer to really understand how a gene is controlled. Maybe you have to break more than one,” he said. “We can’t do that yet.”

But Engreitz, Sanjana, and Lander are all optimistic about the potential for using CRISPR-based approaches to reveal the noncoding genome’s underlying order.

“One interesting challenge with the noncoding genome is that while it is huge, the individual functional elements within it can be quite small,” Sanjana said. “In the future, it will be important to think about how we can develop new approaches that interrogate larger regions while maintaining high resolution.”

Engreitz agreed, adding, “There’s a potential that as we map more of these connections we’re going to learn the rules that let us predict them for the rest of the noncoding genome.”

“These approaches, using libraries of guide RNAs to bring CRISPR in to cut or bring in inhibitors, let you directly see the effects of large areas of noncoding DNA on different genes,” Lander said. “I think this is going to crack open systematic maps of gene regulation.”

Papers cited:

Fulco CP et al. Systematic mapping of functional enhancer-promoter connections with CRISPR interference. Science. September 29, 2016. DOI: 10.1126/science.aag2445

Sanjana NE et al. High-resolution interrogation of functional elements in the noncoding genome. Science. September 29, 2016. DOI: 10.1126/science.aaf7613

Finding a way in

by Elizabeth Dougherty |

Our perception of the world arises within the brain, based on sensory information that is sometimes ambiguous, allowing more than one interpretation. Familiar demonstrations of this point include the famous Necker cube and the “duck-rabbit” drawing (right) in which two different interpretations flip back and forth over time.

Another example is binocular rivalry, in which the two eyes are presented with different images that are perceived in alternation. Several years ago, this phenomenon caught the eye of Caroline Robertson, who is now a Harvard Fellow working in the lab of McGovern Investigator Nancy Kanwisher. Back when she was a graduate student at Cambridge University, Robertson realized that binocular rivalry might be used to probe the basis of autism, among the most mysterious of all brain disorders.

Robertson’s idea was based on the hypothesis that autism involves an imbalance between excitation and inhibition within the brain. Although widely supported by indirect evidence, this has been very difficult to test directly in human patients. Robertson realized that binocular rivalry might provide a way to perform such a test. The perceptual switches that occur during rivalry are thought to involve competition between different groups of neurons in the visual cortex, each group reinforcing its own interpretation via excitatory connections while suppressing the alternative interpretation through inhibitory connections. Thus, if the balance is altered in the brains of people with autism, the frequency of switching might also be different, providing a simple and easily measurable marker of the disease state.

To test this idea, Robertson recruited adults with and without autism, and presented them with two distinct and differently colored images in each eye. As expected, their perceptions switched back and forth between the two images, with short periods of mixed perception in between. This was true for both groups, but when she measured the timing of these switches, Robertson found that individuals with autism do indeed see the world in a measurably different way than people without the disorder. Individuals with autism cycle between the left and right images more slowly, with the intervening periods of mixed perception lasting longer than in people without autism. The more severe their autistic symptoms, as determined by a standard clinical behavioral evaluation, the greater the difference.

Robertson had found a marker for autism that is more objective than current methods that involve one person assessing the behavior of another. The measure is immediate and relies on brain activity that happens automatically, without people thinking about it. “Sensation is a very simple place to probe,” she says.

A top-down approach

When she arrived in Kanwisher’s lab, Robertson wanted to use brain imaging to probe the basis for the perceptual phenomenon that she had discovered. With Kanwisher’s encouragement, she began by repeating the behavioral experiment with a new group of subjects, to check that her previous results were not a fluke. Having confirmed that the finding was real, she then scanned the subjects using an imaging method called Magnetic Resonance Spectroscopy (MRS), in which an MRI scanner is reprogrammed to measure concentrations of neurotransmitters and other chemicals in the brain. Kanwisher had never used MRS before, but when Robertson proposed the experiment, she was happy to try it. “Nancy’s the kind of mentor who could support the idea of using a new technique and guide me to approach it rigorously,” says Robertson.

For each of her subjects, Robertson scanned their brains to measure the amounts of two key neurotransmitters, glutamate, which is the main excitatory transmitter in the brain, and GABA, which is the main source of inhibition. When she compared the brain chemistry to the behavioral results in the binocular rivalry task, she saw something intriguing and unexpected. In people without autism, the amount of GABA in the visual cortex was correlated with the strength of the suppression, consistent with the idea that GABA enables signals from one eye to inhibit those from the other eye. But surprisingly, there was no such correlation in the autistic individuals—suggesting that GABA was somehow unable to exert its normal suppressive effect. It isn’t yet clear exactly what is going wrong in the brains of these subjects, but it’s an early flag, says Robertson. “The next step is figuring out which part of the pathway is disrupted.”

A bottom-up approach

Robertson’s approach starts from the top-down, working backward from a measurable behavior to look for brain differences, but it isn’t the only way in. Another approach is to start with genes that are linked to autism in humans, and to understand how they affect neurons and brain circuits. This is the bottom-up approach of McGovern Investigator Guoping Feng, who studies a gene called Shank3 that codes for a protein that helps build synapses, the connections through which neurons send signals to each other. Several years ago Feng knocked out Shank3 in mice, and found that the mice exhibited behaviors reminiscent of human autism, including repetitive grooming, anxiety, and impaired social interaction and motor control.

These earlier studies involved a variety of different mutations that disabled the Shank3 gene. But when postdoc Yang Zhou joined Feng’s lab, he brought a new perspective. Zhou had come from a medical background and wanted to do an experiment more directly connected to human disease. So he suggested making a mouse version of a Shank3 mutation seen in human patients, and testing its effects.

Zhou’s experiment would require precise editing of the mouse Shank3 gene, previously a difficult and time-consuming task. But help was at hand, in the form of a collaboration with McGovern Investigator Feng Zhang, a pioneer in the development of genome-editing methods.

Using Zhang’s techniques, Zhou was able to generate mice with two different mutations: one that had been linked to human autism, and another that had been discovered in a few patients with schizophrenia.

The researchers found that mice with the autism-related mutation exhibited behavioral changes at a young age that paralleled behaviors seen in children with autism. They also found early changes in synapses within a brain region called the striatum. In contrast, mice with the schizophrenia-related gene appeared normal until adolescence, and then began to exhibit changes in behavior and also changes in the prefrontal cortex, a brain region that is implicated in human schizophrenia. “The consequences of the two different Shank3 mutations were quite different in certain aspects, which was very surprising to us,” says Zhou.

The fact that different mutations in just one gene can produce such different results illustrates exactly how complex these neuropsychiatric disorders can be. “Not only do we need to study different genes, but we also have to understand different mutations and which brain regions have what defects,” says Feng, who received funding from the Poitras Center for Affective Disorders research and the Simons Center for the Social Brain. Robertson and Kanwisher were also supported by the Simons Center.

Surprising plasticity

The brain alterations that lead to autism are thought to arise early in development, long before the condition is diagnosed, raising concerns that it may be difficult to reverse the effects once the damage is done. With the Shank3 knockout mice, Feng and his team were able to approach this question in a new way, asking what would happen if the missing gene were to be restored in adulthood.

To find the answer, lab members Yuan Mei and Patricia Monteiro, along with Zhou, studied another strain of mice, in which the Shank3 gene was switched off but could be reactivated at any time by adding a drug to their diet. When adult mice were tested six weeks after the gene was switched back on, they no longer showed repetitive grooming behaviors, and they also showed normal levels of social interaction with other mice, despite having grown up without a functioning Shank3 gene. Examination of their brains confirmed that many of the synaptic alterations were also rescued when the gene was restored.

Not every symptom was reversed by this treatment; even after six weeks or more of restored Shank3 expression, the mice continued to show heightened anxiety and impaired motor control. But even these deficits could be prevented if the Shank3 gene was restored earlier in life, soon after birth.

The results are encouraging because they indicate a surprising degree of brain plasticity, persisting into adulthood. If the results can be extrapolated to human patients, they suggest that even in adulthood, autism may be at least partially reversible if the right treatment can be found. “This shows us the possibility,” says Zhou. “If we could somehow put back the gene in patients who are missing it, it could help improve their life quality.”

Converging paths

Robertson and Feng are approaching the challenge of autism from different starting points, but already there are signs of convergence. Feng is finding early signs that his Shank3 mutant mice may have an altered balance of inhibitory and excitatory circuits, consistent with what Robertson and Kanwisher have found in humans.

Feng is continuing to study these mice, and he also hopes to study the effects of a similar mutation in non-human primates, whose brains and behaviors are more similar to those of humans than rodents. Robertson, meanwhile, is planning to establish a version of the binocular rivalry test in animal models, where it is possible to alter the balance between inhibition and excitation experimentally (for example, via a genetic mutation or a drug treatment). If this leads to changes in binocular rivalry, it would strongly support the link to the perceptual changes seen in humans.

One challenge, says Robertson, will be to develop new methods to measure the perceptions of mice and other animals. “The mice can’t tell us what they are seeing,” she says. “But it would also be useful in humans, because it would allow us to study young children and patients who are non-verbal.”

A multi-pronged approach

The imbalance hypothesis is a promising lead, but no single explanation is likely to encompass all of autism, according to McGovern director Bob Desimone. “Autism is a notoriously heterogeneous condition,” he explains. “We need to try multiple approaches in order to maximize the chance of success.”

McGovern researchers are doing exactly that, with projects underway that range from scanning children to developing new molecular and microscopic methods for examining brain changes in animal disease models. Although genetic studies provide some of the strongest clues, Desimone notes that there is also evidence for environmental contributions to autism and other brain disorders. “One that’s especially interesting to us is a maternal infection and inflammation, which in mice at least can affect brain development in ways we’re only beginning to understand.”

The ultimate goal, says Desimone, is to connect the dots and to understand how these diverse human risk factors affect brain function. “Ultimately, we want to know what these different pathways have in common,” he says. “Then we can come up with rational strategies for the development of new treatments.”

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.

Feng Zhang named 2016 Tang Prize Laureate

Anne Trafton |

Feng Zhang, a core institute member of the Broad Institute, an investigator at the McGovern Institute for Brain Research at MIT, and W. M. Keck Career Development Associate Professor in MIT’s Department of Brain and Cognitive Sciences with a joint appointment in Biological Engineering, has been named a 2016 Tang Prize Laureate in Biopharmaceutical Science for his role in developing the CRISPR-Cas9 gene-editing system and demonstrating pioneering uses in eukaryotic cells.

The Tang Prize is a biennial international award granted by judges convened by Academia Sinica, Taiwan’s top academic research institution.

In January 2013 Zhang and his team were first to report CRISPR-based genome editing in mammalian cells, in what has become the most-cited paper in the CRISPR field. Zhang shares the award with Emmanuelle Charpentier of the Max Planck Institute and Jennifer A. Doudna of the University of California at Berkeley.

“To be recognized with the Tang Prize is an incredible honor for our team and it demonstrates the impact of the entire CRISPR field, which began with microbiologists and will continue for years to come as we advance techniques for genome editing,” Zhang said. “Thanks to the scientific community’s commitment to collaboration and an emphasis on sharing across institutions and borders, the last few years have seen a revolution in our ability to understand cancer, autoimmune disease, mental health and infectious disease. We are entering a remarkable period in our understanding of human health.”

Although Zhang is well-known for his work with CRISPR, the 34-year-old scientist has a long track record of innovation. As a graduate student at Stanford University, Zhang worked with Karl Deisseroth and Edward Boyden, who is now also a professor at MIT, to develop optogenetics, in which neuronal activity can be controlled with light. The three shared the Perl-UNC Prize in Neuroscience in 2012 as recognition of these efforts. Zhang has also received the National Science Foundation’s Alan T. Waterman Award (2014), the Jacob Heskel Gabbay Award in Biotechnology and Medicine (2014, shared with Charpentier and Doudna), the Tsuneko & Reiji Okazaki Award (2015), the Human Genome Organization (HUGO) Chen New Investigator Award (2016), and the Canada Gairdner International Award (2016, shared with Charpentier and Doudna, as well as Rodolphe Barrangou from North Carolina State University and Philippe Horvath from DuPont Nutrition & Health).

One of Zhang’s long-term goals is to use genome-editing technologies to better understand the nervous system and develop new approaches to the treatment of neurological and psychiatric diseases. The Zhang lab has shared CRISPR-Cas9 components in response to more than 30,000 requests from academic laboratories around the world and has trained thousands of researchers in the use of CRISPR-Cas9 genome-editing technology through in-person events and online opportunities. In his current research, he and his students and postdoctoral fellows continue to improve and expand the gene-editing toolbox.

“Professor Zhang’s lab has become a global hub for CRISPR research,” said MIT Provost Martin Schmidt. “His group has shared CRISPR-Cas9 components with tens of thousands of scientists, and has trained many more in the use of CRISPR-Cas9 technology. The Tang Prize is a fitting recognition of all that Professor Zhang has done, and continues to do, to advance this field.”

“CRISPR is a powerful new tool that is transforming biological science while promising revolutionary advances in health care,” said Michael Sipser, dean of the School of Science and Donner Professor of Mathematics at MIT. “We are delighted that Feng Zhang, together with Jennifer Doudna and Emmanuelle Charpentier, have been recognized with the Tang Prize.”

“It is wonderful that the Academia Sinica has chosen to recognize the CRISPR field with this year’s Tang Prize,” said Eric Lander, founding director of the Broad Institute. “On behalf of my colleagues at the Broad and MIT, I wish to congratulate Feng, as well as Emmanuelle Charpentier and Jennifer Doudna, along with the many teams of scientists and all others who have contributed to these transformational discoveries.”

Founded in 2012 by Samuel Yin, the Tang Prize is a non-governmental, non-profit educational foundation that awards outstanding contributions in four fields: sustainable development, biopharmaceutical science, sinology, and rule of law. Nomination and selection of laureates is conducted by the Academia Sinica. Each award cycle, the academy convenes four autonomous selection committees, each consisting of an assembly of international experts, until a consensus on the recipients is reached. Recipients are chosen on the basis of the originality of their work along with their contributions to society, irrespective of nationality, ethnicity, gender, and political affiliation.

This year marks the second awarding of the prize. This year’s awardees will receive the medal, diploma, and cash prize at an award ceremony on September 25 in Taipei. Recipients in each Tang Prize category receive a total of approximately $1.24 million (USD) and a grant of approximately $311,000 (USD). The cash prize and grants are divided equally among joint recipients in each category.

 

New CRISPR system for targeting RNA

Anne Trafton |

Researchers from MIT and the Broad Institute of MIT and Harvard, as well as the National Institutes of Health, Rutgers University at New Brunswick, and the Skolkovo Institute of Science and Technology, have characterized a new CRISPR system that targets RNA, rather than DNA.

The new approach has the potential to open a powerful avenue in cellular manipulation. Whereas DNA editing makes permanent changes to the genome of a cell, the CRISPR-based RNA-targeting approach may allow researchers to make temporary changes that can be adjusted up or down, and with greater specificity and functionality than existing methods for RNA interference.

In a study published today in Science, Feng Zhang and colleagues at the Broad Institute and the McGovern Institute for Brain Research at MIT, along with co-authors Eugene Koonin and his colleagues at the NIH, and Konstantin Severinov of Rutgers University at New Brunswick and Skoltech, report the identification and functional characterization of C2c2, an RNA-guided enzyme capable of targeting and degrading RNA.

The findings reveal that C2c2 — which is the first naturally occurring CRISPR system known to target only RNA, and was discovered by this collaborative group in October 2015 — helps protect bacteria against viral infection. The researchers demonstrate that C2c2 can be programmed to cleave particular RNA sequences in bacterial cells, which would make it an important addition to the molecular biology toolbox.

The RNA-focused action of C2c2 complements the CRISPR-Cas9 system, which targets DNA, the genomic blueprint for cellular identity and function. The ability to target only RNA, which helps carry out the genomic instructions, offers the ability to specifically manipulate RNA in a high-throughput manner — and to manipulate gene function more broadly. This has the potential to accelerate progress to understand, treat, and prevent disease.

“C2c2 opens the door to an entirely new frontier of powerful CRISPR tools,” said senior author Feng Zhang, who is a core institute member of the Broad Institute, an investigator at the McGovern Institute for Brain Research at MIT, and the W. M. Keck Career Development Associate Professor in MIT’s Department of Brain and Cognitive Sciences.
“There are an immense number of possibilities for C2c2, and we are excited to develop it into a platform for life science research and medicine.”

“The study of C2c2 uncovers a fundamentally novel biological mechanism that bacteria seem to use in their defense against viruses,” said Eugene Koonin, senior author and leader of the Evolutionary Genomics Group at the NIH. “Applications of this strategy could be quite striking.”

Currently, the most common technique for performing gene knockdown is small interfering RNA (siRNA). According to the researchers, C2c2 RNA-editing methods suggest greater specificity and hold the potential for a wider range of applications, such as:

  • Adding modules to specific RNA sequences to alter their function — how they are translated into proteins — which would make them valuable tools for large-scale screens and constructing synthetic regulatory networks; and
  • Harnessing C2c2 to fluorescently tag RNAs as a means to study their trafficking and subcellular localization.

In this work, the team was able to precisely target and remove specific RNA sequences using C2c2, lowering the expression level of the corresponding protein. This suggests C2c2 could represent an alternate approach to siRNA, complementing the specificity and simplicity of CRISPR-based DNA editing and offering researchers adjustable gene “knockdown” capability using RNA.

C2c2 has advantages that make it suitable for tool development:

  • C2c2 is a two-component system, requiring only a single guide RNA to function; and
  • C2c2 is genetically encodable — meaning the necessary components can be synthesized as DNA for delivery into tissue and cells.

“C2c2’s greatest impact may be made on our understanding of the role of RNA in disease and cellular function,” said co-first author Omar Abudayyeh, a graduate student in the Zhang Lab.

Feng Zhang receives 2016 Canada Gairdner International Award

Anne Trafton |

Feng Zhang, a core institute member of the Broad Institute, an investigator at the McGovern Institute for Brain Research at MIT, and W. M. Keck Career Development Associate Professor in MIT’s Department of Brain and Cognitive Sciences, has been named a recipient of the 2016 Canada Gairdner International Award — Canada’s most prestigious scientific prize — for his role in developing the CRISPR-Cas9 gene-editing system.

In January 2013 Zhang and his team were first to report CRISPR-based genome editing in mammalian cells, in what has become the most-cited paper in the CRISPR field. He is one of five scientists the Gairdner Foundation is honoring for work with CRISPR. Zhang shares the award with Rodolphe Barrangou from North Carolina State University; Emmanuelle Charpentier of the Max Planck Institute; Jennifer Doudna of the University of California at Berkeley and Phillipe Horvath from DuPont Nutrition and Health.

“The Gairdner Award is a tremendous recognition for my entire team, and it is a great honor to share this recognition with other pioneers in the CRISPR field,” Zhang says. “In the next decade, the understanding and the discoveries that scientists are going to be able to make using the CRISPR-Cas9 system will lead to new innovations that will translate into new therapeutics and new products that can benefit our lives.”

Although Zhang is well-known for his work with CRISPR, the 34-year-old scientist has a long track record of innovation. As a graduate student at Stanford University, Zhang worked with Karl Deisseroth and Edward Boyden, who is now also a professor at MIT, to develop optogenetics, in which neuronal activity can be controlled with light. The three shared the Perl-UNC Prize in Neuroscience in 2012 as recognition of these efforts. Zhang has also received the National Science Foundation’s Alan T. Waterman Award (2014), the Jacob Heskel Gabbay Award in Biotechnology and Medicine (2014, shared with Charpentier and Doudna), the Tsuneko & Reiji Okazaki Award (2015), and the Human Genome Organization (HUGO) Chen New Investigator Award (2016).

One of Zhang’s long-term goals is to use genome-editing technologies to better understand the nervous system and develop new approaches to the treatment of psychiatric disease. The Zhang lab has shared CRISPR-Cas9 components in response to nearly 30,000 requests from academic laboratories around the world and has trained thousands of researchers in the use of CRISPR-Cas9 genome-editing technology through in-person events and online opportunities. In his current research, he continues to improve and expand the gene-editing toolbox. “I feel incredibly fortunate and excited to work with an incredible team of students and postdocs to continue advancing our ability to edit and understand the genome,” Zhang says.

“CRISPR is a revolutionary breakthrough that will advance the frontiers of science and enable us to meet the health challenges of the 21st century in ways we are only beginning to imagine,” says Michael Sipser, dean of MIT’s School of Science and the Barton L. Weller Professor of Mathematics. “I am exceedingly proud of the contributions Feng has made to MIT and the greater community of scientists, and extend my heartfelt congratulations to him and his colleagues.”

“CRISPR is a great example of how the scientific community can come together and make stunning progress in a short period of time,” says Eric Lander, founding director of the Broad Institute. “On behalf of my colleagues at the Broad and MIT, I wish to congratulate Feng and all the winners of this prestigious award, as well as the teams of scientists and all others who have contributed to these transformational discoveries.”

The Canada Gairdner International Awards, created in 1959, are given annually to recognize and reward the achievements of medical researchers whose work contributes significantly to the understanding of human biology and disease. The awards provide a $100,000 (CDN) prize to each scientist for their work. Each year, the five honorees of the International Awards are selected after a rigorous two-part review, with the winners voted by secret ballot by a medical advisory board composed of 33 eminent scientists from around the world.

The Broad Institute of MIT and Harvard was launched in 2004 to empower this generation of creative scientists to transform medicine. The Broad Institute seeks to describe all the molecular components of life and their connections; discover the molecular basis of major human diseases; develop effective new approaches to diagnostics and therapeutics; and disseminate discoveries, tools, methods, and data openly to the entire scientific community.

Founded by MIT, Harvard, Harvard-affiliated hospitals, and the visionary Los Angeles philanthropists Eli and Edythe L. Broad, the Broad Institute includes faculty, professional staff, and students from throughout the MIT and Harvard biomedical research communities and beyond, with collaborations spanning over a hundred private and public institutions in more than 40 countries worldwide. For further information about the Broad Institute, visit: http://www.broadinstitute.org.