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Multiplex Rainbow Technology Offers New View of the Brain

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Proteins imaged with this new approach
Caption: Confocal LNA-PRISM imaging of neuronal synapses. Conventional images of cell nuclei and two proteins (top row, three images on the left), along with 11 PRISM images of proteins and one composite, multiplexed image (bottom row, right). Credit: Adapted from Guo SM, Nature Communications, 2019

The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is revolutionizing our understanding of how the brain works through its creation of new imaging tools. One of the latest advances—used to produce this rainbow of images—makes it possible to view dozens of proteins in rapid succession in a single tissue sample containing thousands of neural connections, or synapses.

Apart from their colors, most of these images look nearly identical at first glance. But, upon closer inspection, you’ll see some subtle differences among them in both intensity and pattern. That’s because the images capture different proteins within the complex network of synapses—and those proteins may be present in that network in different amounts and locations. Such findings may shed light on key differences among synapses, as well as provide new clues into the roles that synaptic proteins may play in schizophrenia and various other neurological disorders.

Synapses contain hundreds of proteins that regulate the release of chemicals called neurotransmitters, which allow neurons to communicate. Each synaptic protein has its own specific job in the process. But there have been longstanding technical difficulties in observing synaptic proteins at work. Conventional fluorescence microscopy can visualize at most four proteins in a synapse.

As described in Nature Communications [1], researchers led by Mark Bathe, Massachusetts Institute of Technology (MIT), Cambridge, and Jeffrey Cottrell, Broad Institute of MIT and Harvard, Cambridge, have just upped this number considerably while delivering high quality images. They did it by adapting an existing imaging method called DNA PAINT [2]. The researchers call their adapted method PRISM. It is short for: Probe-based Imaging for Sequential Multiplexing.

Here’s how it works: First, researchers label proteins or other molecules of interest using antibodies that recognize those proteins. Those antibodies include a unique DNA probe that helps with the next important step: making the proteins visible under a microscope.

To do it, they deliver short snippets of complementary fluorescent DNA, which bind the DNA-antibody probes. While each protein of interest is imaged separately, researchers can easily wash the probes from a sample to allow a series of images to be generated, each capturing a different protein of interest.

In the original DNA PAINT, the DNA strands bind and unbind periodically to create a blinking fluorescence that can be captured using super-resolution microscopy. But that makes the process slow, requiring about half an hour for each protein.

To speed things up with PRISM, Bathe and his colleagues altered the fluorescent DNA probes. They used synthetic DNA that’s specially designed to bind more tightly or “lock” to the DNA-antibody. This gives a much brighter signal without the blinking effect. As a result, the imaging can be done faster, though at slightly lower resolution.

Though the team now captures images of 12 proteins within a sample in about an hour, this is just a start. As more DNA-antibody probes are developed for synaptic proteins, the team can readily ramp up this number to 30 protein targets.

Thanks to the BRAIN Initiative, researchers now possess a powerful new tool to study neurons. PRISM will help them learn more mechanistically about the inner workings of synapses and how they contribute to a range of neurological conditions.

References:

[1] Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes. Guo SM, Veneziano R, Gordonov S, Li L, Danielson E, Perez de Arce K, Park D, Kulesa AB, Wamhoff EC, Blainey PC, Boyden ES, Cottrell JR, Bathe M. Nat Commun. 2019 Sep 26;10(1):4377.

[2] Super-resolution microscopy with DNA-PAINT. Schnitzbauer J, Strauss MT, Schlichthaerle T, Schueder F, Jungmann R. Nat Protoc. 2017 Jun;12(6):1198-1228.

Links:

Schizophrenia (National Institute of Mental Health)

Mark Bathe (Massachusetts Institute of Technology, Cambridge)

Jeffrey Cottrell (Broad Institute of MIT and Harvard, Cambridge)

Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

NIH Support: National Institute of Mental Health; National Human Genome Research Institute; National Institute of Neurological Disorders and Stroke; National Institute of Environmental Health Sciences


People Read Facial Expressions Differently

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Credit: Lydia Polimeni, NIH

What do you see in the faces above? We constantly make assumptions about what others are feeling based on their facial expressions, such as smiling or frowning. Many have even suggested that human facial expressions represent a universal language. But an NIH-funded research team recently uncovered evidence that different people may read common facial expressions in surprisingly different ways.

In a study published in Nature Human Behaviour, the researchers found that each individual’s past experience, beliefs, and conceptual knowledge of emotions will color how he or she interprets facial expressions [1]. These findings are not only fascinating, they might lead to new ways to help people who sometimes struggle with reading social cues, including those with anxiety, depression, bipolar disorder, schizophrenia, or autism spectrum disorder.


Study Shows Genes Unique to Humans Tied to Bigger Brains

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cortical organoid

Caption: Cortical organoid, showing radial glial stem cells (green) and cortical neurons (red).
Credit: Sofie Salama, University of California, Santa Cruz

In seeking the biological answer to the question of what it means to be human, the brain’s cerebral cortex is a good place to start. This densely folded, outer layer of grey matter, which is vastly larger in Homo sapiens than in other primates, plays an essential role in human consciousness, language, and reasoning.

Now, an NIH-funded team has pinpointed a key set of genes—found only in humans—that may help explain why our species possesses such a large cerebral cortex. Experimental evidence shows these genes prolong the development of stem cells that generate neurons in the cerebral cortex, which in turn enables the human brain to produce more mature cortical neurons and, thus, build a bigger cerebral cortex than our fellow primates.

That sounds like a great advantage for humans! But there’s a downside. Researchers found the same genomic changes that facilitated the expansion of the human cortex may also render our species more susceptible to certain rare neurodevelopmental disorders.


Teaching Computers to “See” the Invisible in Living Cells

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Brain Cell Analysis

Caption: While analyzing brain cells, a computer program “thinks” about which cellular structure to identify.
Credit: Steven Finkbeiner, University of California, San Francisco and the Gladstone Institutes

For centuries, scientists have trained themselves to look through microscopes and carefully study their structural and molecular features. But those long hours bent over a microscope poring over microscopic images could be less necessary in the years ahead. The job of analyzing cellular features could one day belong to specially trained computers.

In a new study published in the journal Cell, researchers trained computers by feeding them paired sets of fluorescently labeled and unlabeled images of brain tissue millions of times in a row [1]. This allowed the computers to discern patterns in the images, form rules, and apply them to viewing future images. Using this so-called deep learning approach, the researchers demonstrated that the computers not only learned to recognize individual cells, they also developed an almost superhuman ability to identify the cell type and whether a cell was alive or dead. Even more remarkable, the trained computers made all those calls without any need for harsh chemical labels, including fluorescent dyes or stains, which researchers normally require to study cells. In other words, the computers learned to “see” the invisible!


Creative Minds: Mapping the Biocircuitry of Schizophrenia and Bipolar Disorder

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Bruce Yankner

Bruce Yankner

As a graduate student in the 1980s, Bruce Yankner wondered what if cancer-causing genes switched on in non-dividing neurons of the brain. Rather than form a tumor, would those genes cause neurons to degenerate? To explore such what-ifs, Yankner spent his days tinkering with neural cells, using viruses to insert various mutant genes and study their effects. In a stroke of luck, one of Yankner’s insertions encoded a precursor to a protein called amyloid. Those experiments and later ones from Yankner’s own lab showed definitively that high concentrations of amyloid, as found in the brains of people with Alzheimer’s disease, are toxic to neural cells [1].

The discovery set Yankner on a career path to study normal changes in the aging human brain and their connection to neurodegenerative diseases. At Harvard Medical School, Boston, Yankner and his colleague George Church are now recipients of an NIH Director’s 2016 Transformative Research Award to apply what they’ve learned about the aging brain to study changes in the brains of younger people with schizophrenia and bipolar disorder, two poorly understood psychiatric disorders.


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