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Defining Neurons in Technicolor

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Brain Architecture
Credit: Allen Institute for Brain Science, Seattle

Can you identify a familiar pattern in this image’s square grid? Yes, it’s the outline of the periodic table! But instead of organizing chemical elements, this periodic table sorts 46 different types of neurons present in the visual cortex of a mouse brain.

Scientists, led by Hongkui Zeng at the Allen Institute for Brain Science, Seattle, constructed this periodic table by assigning colors to their neuronal discoveries based upon their main cell functions [1]. Cells in pinks, violets, reds, and oranges have inhibitory electrical activity, while those in greens and blues have excitatory electrical activity.

For any given cell, the darker colors indicate dendrites, which receive signals from other neurons. The lighter colors indicate axons, which transmit signals. Examples of electrical properties—the number and intensity of their “spikes”—appear along the edges of the table near the bottom.

To create this visually arresting image, Zeng’s NIH-supported team injected dye-containing probes into neurons. The probes are engineered to carry genes that make certain types of neurons glow bright colors under the microscope.

This allowed the researchers to examine a tiny slice of brain tissue and view each colored neuron’s shape, as well as measure its electrical response. They followed up with computational tools to combine these two characteristics and classify cell types based on their shape and electrical activity. Zeng’s team could then sort the cells into clusters using a computer algorithm to avoid potential human bias from visually interpreting the data.

Why compile such a detailed atlas of neuronal subtypes? Although scientists have been surveying cells since the invention of the microscope centuries ago, there is still no consensus on what a “cell type” is. Large, rich datasets like this atlas contain massive amounts of information to characterize individual cells well beyond their appearance under a microscope, helping to explain factors that make cells similar or dissimilar. Those differences may not be apparent to the naked eye.

Just last year, Allen Institute researchers conducted similar work by categorizing nearly 24,000 cells from the brain’s visual and motor cortex into different types based upon their gene activity [2]. The latest research lines up well with the cell subclasses and types categorized in the previous gene-activity work. As a result, the scientists have more evidence that each of the 46 cell types is actually distinct from the others and likely drives a particular function within the visual cortex.

Publicly available resources, like this database of cell types, fuel much more discovery. Scientists all over the world can look at this table (and soon, more atlases from other parts of the brain) to see where a cell type fits into a region of interest and how it might behave in a range of brain conditions.

References:

[1] Classification of electrophysiological and morphological neuron types in the mouse visual cortex. N Gouwens NW, et al. Neurosci. 2019 Jul;22(7):1182-1195.

[2] Shared and distinct transcriptomic cell types across neocortical areas. Tasic B, et al. Nature. 2018 Nov;563(7729):72-78.

Links:

Brain Basics: The Life and Death of a Neuron (National Institute of Neurological Disorders and Stroke/NIH)

Cell Types: Overview of the Data (Allen Brain Atlas/Allen Institute for Brain Science, Seattle)

Hongkui Zeng (Allen Institute)

NIH Support: National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health & Human Development


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!


Cool Videos: Making Multicolored Waves in Cell Biology

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Bacteria are single-cell organisms that reproduce by dividing in half. Proteins within these cells organize themselves in a number of fascinating ways during this process, including a recently discovered mechanism that makes the mesmerizing pattern of waves, or oscillations, you see in this video. Produced when the protein MinE chases the protein MinD from one end of the cell to the other, such oscillations are thought to center the cell’s division machinery so that its two new “daughter cells” will be the same size.

To study these dynamic patterns in greater detail, Anthony Vecchiarelli purified MinD and MinE proteins from the bacterium Escherichia coli. Vecchiarelli, who at the time was a postdoc in Kiyoshi Mizuuchi’s intramural lab at NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), labeled the proteins with fluorescent markers and placed them on a synthetic membrane, where their movements were then visualized by total internal reflection fluorescence microscopy. The proteins self-organized and generated dynamic spirals of waves: MinD (blue, left); MinE (red, right); and both MinD and MinE (purple, center) [1].


Snapshots of Life: A Flare for the Dramatic

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lipid-covered water drop

Credit: Valentin Romanov, University of Utah, Salt Lake City

Oil and water may not mix, but under the right conditions—like those in the photo above—it can sure produce some interesting science that resembles art. You’re looking at a water droplet suspended in an emulsion of olive oil (black and purple) and lipids, molecules that serve as the building blocks of cell membranes. Each lipid has been tagged with a red fluorescent marker, and what look like red and yellow flames are the markers reacting to a beam of UV light. Their glow shows the lipids sticking to the surface of the water droplet, which will soon engulf the droplet to form a single lipid bilayer, which can later be transformed into a lipid bilayer that closely resembles a cell membrane. Scientists use these bubbles, called liposomes, as artificial cells for a variety of research purposes.

In this case, the purpose is structural biology studies. Valentin Romanov, the graduate student at the University of Utah, Salt Lake City, who snapped the image, creates liposomes to study proteins that help cells multiply. By encapsulating and letting the proteins interact with lipids in the artificial cell membrane, Romanov and his colleagues in the NIH-supported labs of Bruce Gale at the University of Utah and Adam Frost at the University of California, San Francisco, can freeze and capture their changing 3D structures at various points in the cell division process with high-resolution imaging techniques. These snapshots will help the researchers to understand in finer detail how the proteins work and perhaps to design drugs to manipulate their functions.


Snapshots of Life: Fish Awash in Color

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Skin cells from a genetically engineered zebrafish

Credit: Chen-Hui Chen, Duke University

If this image makes you think of a modern art, you’re not alone. But what you’re actually seeing are hundreds of live cells from a tiny bit (0.0003348 square inches) of skin on the tail fin of a genetically engineered adult zebrafish. Zebrafish are normally found in tropical freshwater and are a favorite research model to study vertebrate development and tissue regeneration. The cells have been labeled with a cool, new fluorescent imaging tool called Skinbow. It uniquely color codes cells by getting them to express genes encoding red, green, and blue fluorescent proteins at levels that are randomly determined. The different ratios of these colorful proteins mix to give each cell a distinctive hue when imaged under a microscope. Here, you can see more than 70 detectable Skinbow colors that make individual cells as visually distinct from one another as jellybeans in a jar.

Skinbow is the creation of NIH-supported scientists Chen-Hui Chen and Kenneth Poss at Duke University, Durham, NC, with imaging computational help from collaborators Stefano Di Talia and Alberto Puliafito. As reported recently in the journal Developmental Cell [1], Skinbow’s distinctive spectrum of color occurs primarily in the outermost part of the skin in a layer of non-dividing epithelial cells. Using Skinbow, Poss and colleagues tracked these epithelial cells, individually and as a group, over their entire 2 to 3 week lifespans in the zebrafish. This gave them an unprecedented opportunity to track the cellular dynamics of wound healing or the regeneration of lost tissue over time. While Skinbow only works in zebrafish for now, in theory, it could be adapted to mice and maybe even humans to study skin and possibly other organs.


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