neurons
New Technology Opens Evolutionary Window into Brain Development
Posted on by Dr. Francis Collins
One of the great mysteries in biology is how we humans ended up with such large, complex brains. In search of clues, researchers have spent years studying the protein-coding genes activated during neurodevelopment. But some answers may also be hiding in non-coding regions of the human genome, where sequences called regulatory elements increase or decrease the activity of genes.
A fascinating example involves a type of regulatory element called a human accelerated region (HAR). Although “human” is part of this element’s name, it turns out that the genomes of all vertebrates—not just humans—contain the DNA segments now designated as HARs.
In most organisms, HARs show a relatively low rate of mutation, which means these regulatory elements have been highly conserved across species throughout evolutionary time [1]. The big exception is Homo sapiens, in which HARs have exhibited a much higher rate of mutations.
The accelerated rate of HARs mutations observed in humans suggest that, over the course of very long periods of time, these genomic changes might have provided our species with some sort of evolutionary advantage. What might that be? Many have speculated the advantage might involve the brain because HARs are often associated with genes involved in neurodevelopment. Now, in a paper published in the journal Neuron, an NIH-supported team confirms that’s indeed the case [2].
In the new work, researchers found that about half of the HARs in the human genome influence the activity, or expression, of protein-coding genes in neural cells and tissues during the brain’s development [3]. The researchers say their study—the most comprehensive to date of the 3,171 HARs in the human genome—firmly establishes that this type of regulatory element helps to drive patterns of neurodevelopmental gene activity specific to humans.
Yet to be determined is precisely how HARs affect the development of the human brain. The quest to uncover these details will no doubt shed new light on fundamental questions about the brain, its billions of neurons, and their trillions of interconnections. For example, why does human neural development span decades, longer than the life spans of most primates and other mammals? Answering such questions could also reveal new clues into a range of cognitive and behavioral disorders. In fact, early research has already made tentative links between HARs and neurodevelopmental conditions such as autism spectrum disorder and schizophrenia [3].
The latest work was led by Kelly Girskis, Andrew Stergachis, and Ellen DeGennaro, all of whom were in the lab of Christopher Walsh while working on the project. An NIH grantee, Walsh is director of the Allen Discovery Center for Brain Evolution at Boston Children’s Hospital and Harvard Medical School, which is supported by the Paul G. Allen Foundation Frontiers Group, and is an Investigator of the Howard Hughes Medical Institute.
Though HARs have been studied since 2006, one of the big challenges in systematically assessing them has been technological. The average length of a HAR is about 269 bases of DNA, but current technologies for assessing function can only easily analyze DNA molecules that span 150 bases or less.
Ryan Doan, who was then in the Walsh Lab, and his colleagues solved the problem by creating a new machine called CaptureMPRA. (MPRA is short for “massively parallel reporter assays.”) This technological advance cleverly barcodes HARs and, more importantly, makes it possible to analyze HARs up to about 500 bases in length.
Using CaptureMPRA technology in tandem with cell culture studies, researchers rolled up their sleeves and conducted comprehensive, full-sequence analyses of more than 3,000 HARs. In their initial studies, primarily in neural cells, they found nearly half of human HARs are active to drive gene expression in cell culture. Of those, 42 percent proved to have increased ability to enhance gene expression compared to their orthologues, or counterparts, in chimpanzees.
Next, the team integrated these data with an existing epigenetic dataset derived from developing human brain cells, as well as additional datasets generated from sorted brain cell types. They found that many HARs appeared to have the ability to increase the activity of protein-coding genes, while a smaller—but very significant—subset of the HARs appeared to be enhancing gene expression specifically in neural progenitor cells, which are responsible for making various neural cell types.
The data suggest that as the human HAR sequences mutated and diverged from other mammals, they increased their ability to enhance or sometimes suppress the activity of certain genes in neural cells. To illustrate this point, the researchers focused on two HARs that appear to interact specifically with a gene referred to as R17. This gene can have highly variable gene expression patterns not only in different human cell types, but also in cells from other vertebrates and non-vertebrates.
In the human cerebral cortex, the outermost part of the brain that’s responsible for complex behaviors, R17 is expressed only in neural progenitor cells and only at specific time points. The researchers found that R17 slows the progression of neural progenitor cells through the cell cycle. That might seem strange, given the billions of neurons that need to be made in the cortex. But it’s consistent with the biology. In the human, it takes more than 130 days for the cortex to complete development, compared to about seven days in the mouse.
Clearly, to learn more about how the human brain evolved, researchers will need to look for clues in many parts of the genome at once, including its non-coding regions. To help researchers navigate this challenging terrain, the Walsh team has created an online resource displaying their comprehensive HAR data. It will appear soon, under the name HAR Hub, on the University of California Santa Cruz Genome Browser.
References:
[1] An RNA gene expressed during cortical development evolved rapidly in humans. Pollard KS, Salama SR, Lambert N, Lambot MA, Coppens S, Pedersen JS, Katzman S, King B, Onodera C, Siepel A, Kern AD, Dehay C, Igel H, Ares M Jr, Vanderhaeghen P, Haussler D. Nature. 2006 Sep 14;443(7108):167-72.
[2] Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions. Girskis KM, Stergachis AB, DeGennaro EM, Doan RN, Qian X, Johnson MB, Wang PP, Sejourne GM, Nagy MA, Pollina EA, Sousa AMM, Shin T, Kenny CJ, Scotellaro JL, Debo BM, Gonzalez DM, Rento LM, Yeh RC, Song JHT, Beaudin M, Fan J, Kharchenko PV, Sestan N, Greenberg ME, Walsh CA. Neuron. 2021 Aug 25:S0896-6273(21)00580-8.
[3] Mutations in human accelerated regions disrupt cognition and social behavior. Doan RN, Bae BI, Cubelos B, Chang C, Hossain AA, Al-Saad S, Mukaddes NM, Oner O, Al-Saffar M, Balkhy S, Gascon GG; Homozygosity Mapping Consortium for Autism, Nieto M, Walsh CA. Cell. 2016 Oct 6;167(2):341-354.
Links:
Christopher Walsh Laboratory (Boston Children’s Hospital and Harvard Medical School)
The Paul G. Allen Foundation Frontiers Group (Seattle)
NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute of General Medical Sciences; National Cancer Institute
First Comprehensive Census of Cell Types in Brain Area Controlling Movement
Posted on by Dr. Francis Collins
The primary motor cortex is the part of the brain that enables most of our skilled movements, whether it’s walking, texting on our phones, strumming a guitar, or even spiking a volleyball. The region remains a major research focus, and that’s why NIH’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative – Cell Census Network (BICCN) has just unveiled two groundbreaking resources: a complete census of cell types present in the mammalian primary motor cortex, along with the first detailed atlas of the region, located along the back of the frontal lobe in humans (purple stripe above).
This remarkably comprehensive work, detailed in a flagship paper and more than a dozen associated articles published in the journal Nature, promises to vastly expand our understanding of the primary motor cortex and how it works to keep us moving [1]. The papers also represent the collaborative efforts of more than 250 BICCN scientists from around the world, teaming up over many years.
Started in 2013, the BRAIN Initiative is an ambitious project with a range of groundbreaking goals, including the creation of an open-access reference atlas that catalogues all of the brain’s many billions of cells. The primary motor cortex was one of the best places to get started on assembling an atlas because it is known to be well conserved across mammalian species, from mouse to human. There’s also a rich body of work to aid understanding of more precise cell-type information.
Taking advantage of recent technological advances in single-cell analysis, the researchers categorized into different types the millions of neurons and other cells in this brain region. They did so on the basis of morphology, or shape, of the cells, as well as their locations and connections to other cells. The researchers went even further to characterize and sort cells based on: their complex patterns of gene expression, the presence or absence of chemical (or epigenetic) marks on their DNA, the way their chromosomes are packaged into chromatin, and their electrical properties.
The new data and analyses offer compelling evidence that neural cells do indeed fall into distinct types, with a high degree of correspondence across their molecular genetic, anatomical, and physiological features. These findings support the notion that neural cells can be classified into molecularly defined types that are also highly conserved or shared across mammalian species.
So, how many cell types are there? While that’s an obvious question, it doesn’t have an easy answer. The number varies depending upon the method used for sorting them. The researchers report that they have identified about 25 classes of cells, including 16 different neuronal classes and nine non-neuronal classes, each composed of multiple subtypes of cells.
These 25 classes were determined by their genetic profiles, their locations, and other characteristics. They also showed up consistently across species and using different experimental approaches, suggesting that they have important roles in the neural circuitry and function of the motor cortex in mammals.
Still, many precise features of the cells don’t fall neatly into these categories. In fact, by focusing on gene expression within single cells of the motor cortex, the researchers identified more potentially important cell subtypes, which fall into roughly 100 different clusters, or distinct groups. As scientists continue to examine this brain region and others using the latest new methods and approaches, it’s likely that the precise number of recognized cell types will continue to grow and evolve a bit.
This resource will now serve as a springboard for future research into the structure and function of the brain, both within and across species. The datasets already have been organized and made publicly available for scientists around the world.
The atlas also now provides a foundation for more in-depth study of cell types in other parts of the mammalian brain. The BICCN is already engaged in an effort to generate a brain-wide cell atlas in the mouse, and is working to expand coverage in the atlas for other parts of the human brain.
The cell census and atlas of the primary motor cortex are important scientific advances with major implications for medicine. Strokes commonly affect this region of the brain, leading to partial or complete paralysis of the opposite side of the body.
By considering how well cell census information aligns across species, scientists also can make more informed choices about the best models to use for deepening our understanding of brain disorders. Ultimately, these efforts and others underway will help to enable precise targeting of specific cell types and to treat a wide range of brain disorders that affect thinking, memory, mood, and movement.
Reference:
[1] A multimodal cell census and atlas of the mammalian primary motor cortex. BRAIN Initiative Cell Census Network (BICCN). Nature. Oct 6, 2021.
Links:
NIH Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
BRAIN Initiative – Cell Census Network (BICCN) (NIH)
NIH Support: National Institute of Mental Health; National Institute of Neurological Disorders and Stroke
The Amazing Brain: A Sharper Image of the Pyramidal Tract
Posted on by Dr. Francis Collins
Flip the image above upside down, and the shape may remind you of something. If you think it resembles a pyramid, then you and a lot of great neuroscientists are thinking alike. What you are viewing is a colorized, 3D reconstruction of a pyramidal tract, which are bundles of nerve fibers that originate from the brain’s cerebral cortex and relay signals to the brainstem or the spinal cord. These signals control many important activities, including the voluntary movement of our arms, legs, head, and face.
For a while now, it’s been possible to combine a specialized form of magnetic resonance imaging (MRI) with computer modeling tools to produce 3D reconstructions of complicated networks of nerve fibers, such as the pyramidal tract. Still, for technical reasons, the quality of these reconstructions has remained poor in parts of the brain where nerve fibers cross at angles of 40 degrees or less.
The video above demonstrates how adding a sophisticated algorithm, called Orientation Distribution Function (ODF)-Fingerprinting, to such modeling can help overcome this problem when reconstructing a pyramidal tract. It has potential to enhance the reliability of these 3D reconstructions as neurosurgeons begin to use them to plan out their surgeries to help ensure they are carried out with the utmost safety and precision.
In the first second of the video, you see gray, fuzzy images from a diffusion MRI of the pyramidal tract. But, very quickly, a more colorful, detailed 3D reconstruction begins to appear, swiftly filling in from the top down. Colors are used to indicate the primary orientations of the nerve fibers: left to right (red), back to front (green), and top to bottom (blue). The orange, magenta, and other colors represent combinations of these primary directional orientations.
About three seconds into the video, a rough draft of the 3D reconstruction is complete. The top of the pyramidal tract looks pretty good. However, looking lower down, you can see distortions in color and relatively poor resolution of the nerve fibers in the middle of the tract—exactly where the fibers cross each other at angles of less than 40 degrees. So, researchers tapped into the power of their new ODF-Fingerprinting software to improve the image—and, starting about nine seconds into the video, you can see an impressive final result.
The researchers who produced this amazing video are Patryk Filipiak and colleagues in the NIH-supported lab of Steven Baete, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York. The work paired diffusion MRI data from the NIH Human Connectome Project with the ODF-Fingerprinting algorithm, which was created by Baete to incorporate additional MRI imaging data on the shape of nerve fibers to infer their directionality [1].
This innovative approach to imaging recently earned Baete’s team second place in the 2021 “Show Us Your BRAINs” Photo and Video contest, sponsored by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. But researchers aren’t stopping there! They are continuing to refine ODF-Fingerprinting, with the aim of modeling the pyramidal tract in even higher resolution for use in devising new and better ways of helping people undergoing neurosurgery.
Reference:
[1] Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles. Baete SH, Cloos MA, Lin YC, Placantonakis DG, Shepherd T, Boada FE. Neuroimage. 2019 Sep;198:231-241.
Links:
Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Human Connectome Project (University of Southern California, Los Angeles)
Steven Baete (Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Cancer Institute
The Amazing Brain: Visualizing Data to Understand Brain Networks
Posted on by Dr. Francis Collins
The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative continues to teach us about the world’s most sophisticated computer: the human brain. This striking image offers a spectacular case in point, thanks to a new tool called Visual Neuronal Dynamics (VND).
VND is not a camera. It is a powerful software program that can display, animate, and analyze models of neurons and their connections, or networks, using 3D graphics. What you’re seeing in this colorful image is a strip of mouse primary visual cortex, the area in the brain where incoming sensory information gets processed into vision.
This strip contains more than 230,000 neurons of 17 different cell types. Long and spindly excitatory neurons that point upward (purple, blue, red, orange) are intermingled with short and stubby inhibitory neurons (green, cyan, magenta). Slicing through the neuronal landscape is a neuropixels probe (silver): a tiny flexible silicon detector that can record brain activity in awake animals [1].
Developed by Emad Tajkhorshid and his team at University of Illinois at Urbana-Champaign, along with Anton Arkhipov of the Allen Institute, Seattle, VND represents a scientific milestone for neuroscience: using an adept software tool to see and analyze massive neuronal datasets on a computer. What’s also nice is the computer doesn’t have to be a fancy one, and VND’s instructions, or code, are publicly available for anyone to use.
VND is the neuroscience-adapted cousin of Visual Molecular Dynamics (VMD), a popular molecular biology visualization tool to see life up close in 3D, also developed by Tajkhorshid’s group [2]. By modeling and visualizing neurons and their connections, VND helps neuroscientists understand at their desktops how neural networks are organized and what happens when they are manipulated. Those visualizations then lay the groundwork for follow-up lab studies to validate the data and build upon them.
Through the Allen Institute, the NIH BRAIN Initiative is compiling a comprehensive whole-brain atlas of cell types in the mouse, and Arkhipov’s work integrates these data into computer models. In May 2020, his group published comprehensive models of the mouse primary visual cortex [3].
Arkhipov and team are now working to understand how the primary visual cortex’s physical structure (the cell shapes and connections within its complicated circuits) determines its outputs. For example, how do specific connections determine network activity? Or, how fast do cells fire under different conditions?
Ultimately, such computational research may help us understand how brain injuries or disease affect the structure and function of these neural networks. VND should also propel understanding of many other areas of the brain, for which the data are accumulating rapidly, to answer similar questions that still remain mysterious to scientists.
In the meantime, VND is also creating some award-winning art. The image above was the second-place photo in the 2021 “Show us Your BRAINs!” Photo and Video Contest sponsored by the NIH BRAIN Initiative.
References:
[1] Fully integrated silicon probes for high-density recording of neural activity. Jun JJ, Steinmetz NA, Siegle JH, Denman DJ, Bauza M, Barbarits B, Lee AK, Anastassiou CA, Andrei A, Aydın Ç, Barbic M, Blanche TJ, Bonin V, Couto J, Dutta B, Gratiy SL, Gutnisky DA, Häusser M, Karsh B, Ledochowitsch P, Lopez CM, Mitelut C, Musa S, Okun M, Pachitariu M, Putzeys J, Rich PD, Rossant C, Sun WL, Svoboda K, Carandini M, Harris KD, Koch C, O’Keefe J, Harris TD. Nature. 2017 Nov 8;551(7679):232-236.
[2] VMD: visual molecular dynamics. Humphrey W, Dalke A, Schulten K. J Mol Graph. 1996 Feb;14(1):33-8, 27-8.
[3] Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex. Billeh YN, Cai B, Gratiy SL, Dai K, Iyer R, Gouwens NW, Abbasi-Asl R, Jia X, Siegle JH, Olsen SR, Koch C, Mihalas S, Arkhipov A. Neuron. 2020 May 6;106(3):388-403.e18
Links:
The Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Models of the Mouse Primary Visual Cortex (Allen Institute, Seattle)
Visual Neuronal Dynamics (NIH Center for Macromolecular Modeling and Bioinformatics, University of Illinois at Urbana-Champaign)
Tajkhorshid Lab (University of Illinois at Urbana-Champaign)
Arkhipov Lab (Allen Institute)
Show Us Your BRAINs! Photo & Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke
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