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Snapshots of Life

The Hidden Beauty of Intestinal Villi

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Credit: Amy Engevik, Medical University of South Carolina, Charleston.

The human small intestine, though modest in diameter and folded compactly to fit into the abdomen, is anything but small. It measures on average about 20 feet from end to end and plays a big role in the gastrointestinal tract, breaking down food and drink from the stomach to absorb the water and nutrients.

Also anything but small is the total surface area of the organ’s inner lining, where millions of U-shaped folds in the mucosal tissue triple the available space to absorb the water and nutrients that keep our bodies nourished. If these folds, packed with finger-like absorptive cells called villi, were flattened out, they would be the size of a tennis court!

That’s what makes this this microscopic image so interesting. It shows in cross section the symmetrical pattern of the villi (its cells outlined by yellow) that pack these folds. Each cell’s nucleus contains DNA (teal), and the villi themselves are fringed by thousands of tiny bristles, called microvilli (magenta), which are too small to see individually here. Collectively, microvilli make up an absorptive surface, called the brush border, where digested nutrients in the fluid passing through the intestine can enter cells via transport channels.

Amy Engevik, a researcher at the Medical University of South Carolina, Charleston, took this snapshot to show what a healthy intestinal cellular landscape looks like in a young mouse. The Engevik lab studies the dynamic movement of ions, water, and proteins in the intestine—a process that goes wrong in humans born with a rare disorder called microvillus inclusion disease (MVID).

MVID causes chronic gastrointestinal problems in newborn babies, due to defects in a protein that transports various cellular components. Because they cannot properly absorb nutrition from food, these tiny patients require intravenous feeding almost immediately, which carries a high risk for sepsis and intestinal injury.

Engevik and her team study this disease using a mouse model that replicates many of the characteristics of the disorder in humans [1]. Interestingly, when Engevik gets together with her family, she isn’t the only one talking about MVID and villi. Her two sisters, Mindy and Kristen, also study the basic science of gastrointestinal disorders! Instead of sibling rivalry, though, this close alliance has strengthened the quality of her research, says Amy, who is the middle child.

Beyond advancing science and nurturing sisterhood in science, Engevik’s work also captured the fancy of the judges for the Federation of American Societies for Experimental Biology’s annual BioArt Scientific Image and Video Competition. Her image was one of 10 winners announced in December 2020.

Because multiple models are useful for understanding fundamentals of diseases like MVID, Engevik has also developed a large-animal model (pig) that has many features of the human disease [2]. She hopes that her efforts will help to improve our understanding of MVID and other digestive diseases, as well as lead to new, potentially life-saving treatments for babies suffering from MVID.

References:

[1] Loss of MYO5B Leads to reductions in Na+ absorption with maintenance of CFTR-dependent Cl- secretion in enterocytes. Engevik AC, Kaji I, Engevik MA, Meyer AR, Weis VG, Goldstein A, Hess MW, Müller T, Koepsell H, Dudeja PK, Tyska M, Huber LA, Shub MD, Ameen N, Goldenring JR. Gastroenterology. 2018 Dec;155(6):1883-1897.e10.

[2] Editing myosin VB gene to create porcine model of microvillus inclusion disease, with microvillus-lined inclusions and alterations in sodium transporters. Engevik AC, Coutts AW, Kaji I, Rodriguez P, Ongaratto F, Saqui-Salces M, Medida RL, Meyer AR, Kolobova E, Engevik MA, Williams JA, Shub MD, Carlson DF, Melkamu T, Goldenring JR. Gastroenterology. 2020 Jun;158(8):2236-2249.e9.

Links:

Microvillus inclusion disease (Genetic and Rare Diseases Center/NIH)

Digestive Diseases (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Amy Engevik (Medical University of South Carolina, Charleston)

Podcast: A Tale of Three Sisters featuring Drs. Mindy, Amy, and Kristen Engevik (The Immunology Podcast, April 29, 2021)

BioArt Scientific Image and Video Competition (Federation of American Societies for Experimental Biology, Bethesda, MD)

NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases


Understanding Neuronal Diversity in the Spinal Cord

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Cross-section image of spinal cord showing glowing green and magenta neurons.
Credit: Salk Institute, La Jolla, CA

The spinal cord, as a key part of our body’s central nervous system, contains millions of neurons that actively convey sensory and motor (movement) information to and from the brain. Scientists have long sorted these spinal neurons into what they call “cardinal” classes, a classification system based primarily on the developmental origin of each nerve cell. Now, by taking advantage of the power of single-cell genetic analysis, they’re finding that spinal neurons are more diverse than once thought.

This image helps to visualize the story. Each dot represents the nucleus of a spinal neuron in a mouse; humans have a very similar arrangement. Most of these neurons are involved in the regulation of motor control, but they also differ in important ways. Some are involved in local connections (green), such as those that signal outward to a limb and prompt us to pull away reflexively when we touch painful stimuli, such as a hot frying pan. Others are involved in long-range connections (magenta), relaying commands across spinal segments and even upward to the brain. These enable us, for example, to swing our arms while running to help maintain balance.

It turns out that these two types of spinal neurons also have distinctive genetic signatures. That’s why researchers could label them here in different colors and tell them apart. Being able to distinguish more precisely among spinal neurons will prove useful in identifying precisely which ones are affected by a spinal cord injury or neurodegenerative disease, key information in learning to engineer new tissue to heal the damage.

This image comes from a study, published recently in the journal Science, conducted by an NIH-supported team led by Samuel Pfaff, Salk Institute for Biological Studies, La Jolla, CA. Pfaff and his colleagues, including Peter Osseward and Marito Hayashi, realized that the various classes and subtypes of neurons in our spines arose over the course of evolutionary time. They reasoned that the most-primitive original neurons would have gradually evolved subtypes with more specialized and diverse capabilities. They thought they could infer this evolutionary history by looking for conserved and then distinct, specialized gene-expression signatures in the different neural subtypes.

The researchers turned to single-cell RNA sequencing technologies to look for important similarities and differences in the genes expressed in nearly 7,000 mouse spinal neurons. They then used this vast collection of genomic data to group the neurons into closely related clusters, in much the same way that scientists might group related organisms into an evolutionary family tree based on careful study of their DNA.

The first major gene expression pattern they saw divided the spinal neurons into two types: sensory-related and motor-related. This suggested to them that one of the first steps in spinal cord evolution may have been a division of labor of spinal neurons into those two fundamentally important roles.

Further analyses divided the sensory-related neurons into excitatory neurons, which make neurons more likely to fire; and inhibitory neurons, which dampen neural firing. Then, the researchers zoomed in on motor-related neurons and found something unexpected. They discovered the cells fell into two distinct molecular groups based on whether they had long-range or short-range connections in the body. Researches were even more surprised when further study showed that those distinct connectivity signatures were shared across cardinal classes.

All of this means that, while previously scientists had to use many different genetic tags to narrow in on a particular type of neuron, they can now do it with just two: a previously known tag for cardinal class and the newly discovered genetic tag for long-range vs. short-range connections.

Not only is this newfound ability a great boon to basic neuroscientists, it also could prove useful for translational and clinical researchers trying to determine which specific neurons are affected by a spinal injury or disease. Eventually, it may even point the way to strategies for regrowing just the right set of neurons to repair serious neurologic problems. It’s a vivid reminder that fundamental discoveries, such as this one, often can lead to unexpected and important breakthroughs with potential to make a real difference in people’s lives.

Reference:

[1] Conserved genetic signatures parcellate cardinal spinal neuron classes into local and projection subsets. Osseward PJ 2nd, Amin ND, Moore JD, Temple BA, Barriga BK, Bachmann LC, Beltran F Jr, Gullo M, Clark RC, Driscoll SP, Pfaff SL, Hayashi M. Science. 2021 Apr 23;372(6540):385-393.

Links:

What Are the Parts of the Nervous System? (Eunice Kennedy Shriver National Institute of Child Health and Human Development/NIH)

Spinal Cord Injury (National Institute of Neurological Disorders and Stroke/NIH)

Samuel Pfaff (Salk Institute, La Jolla, CA)

NIH Support: National Institute of Mental Health; National Institute of Neurological Disorders and Stroke; Eunice Kennedy Shriver National Institute of Child Health and Human Development


Finding Better Ways to Image the Retina

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Two light microscopy fields of the retina showing small blue dots (rods) surrounding larger yellow dots (cones)
Credit: Johnny Tam, National Eye Institute, NIH

Every day, all around the world, eye care professionals are busy performing dilated eye exams. By looking through a patient’s widened pupil, they can view the retina—the postage stamp-sized tissue lining the back of the inner eye—and look for irregularities that may signal the development of vision loss.

The great news is that, thanks to research, retinal imaging just keeps getting better and better. The images above, which show the same cells viewed with two different microscopic techniques, provide good examples of how tweaking existing approaches can significantly improve our ability to visualize the retina’s two types of light-sensitive neurons: rod and cone cells.

Specifically, these images show an area of the outer retina, which is the part of the tissue that’s observed during a dilated eye exam. Thanks to colorization and other techniques, a viewer can readily distinguish between the light-sensing, color-detecting cone cells (orange) and the much smaller, lowlight-sensing rod cells (blue).

These high-res images come from Johnny Tam, a researcher with NIH’s National Eye Institute. Working with Alfredo Dubra, Stanford University, Palo Alto, CA, Tam and his team figured out how to limit light distortion of the rod cells. The key was illuminating the eye using less light, provided as a halo instead of the usual solid, circular beam.

But the researchers’ solution hit a temporary snag when the halo reflected from the rods and cones created another undesirable ring of light. To block it out, Tam’s team introduced a tiny pinhole, called a sub-Airy disk. Along with use of adaptive optics technology [1] to correct for other distortions of light, the scientists were excited to see such a clear view of individual rods and cones. They published their findings recently in the journal Optica [2]

The resolution produced using these techniques is so much improved (33 percent better than with current methods) that it’s even possible to visualize the tiny inner segments of both rods and cones. In the cones, for example, these inner segments help direct light coming into the eye to other, photosensitive parts that absorb single photons of light. The light is then converted into electrical signals that stream to the brain’s visual centers in the occipital cortex, which makes it possible for us to experience vision.

Tam and team are currently working with physician-scientists in the NIH Clinical Center to image the retinas of people with a variety of retinal diseases, including age-related macular degeneration (AMD), a leading cause of vision loss in older adults. These research studies are ongoing, but offer hopeful possibilities for safe and non-intrusive monitoring of individual rods and cones over time, as well as across disease types. That’s obviously good news for patients. Plus it will help scientists understand how a rod or cone cell stops working, as well as more precisely test the effects of gene therapy and other experimental treatments aimed at restoring vision.

References:

[1] Noninvasive imaging of the human rod photoreceptor mosaic using a confocal adaptive optics scanning ophthalmoscope. Dubra A, Sulai Y, Norris JL, Cooper RF, Dubis AM, Williams DR, Carroll J. Biomed Opt Express. 2011 Jul 1;2(7):1864-76.

[1] In-vivo sub-diffraction adaptive optics imaging of photoreceptors in the human eye with annular pupil illumination and sub-Airy detection. Rongwen L, Aguilera N, Liu T, Liu J, Giannini JP, Li J, Bower AJ, Dubra A, Tam J. Optica 2021 8, 333-343. https://doi.org/10.1364/OPTICA.414206

Links:

Get a Dilated Eye Exam (National Eye Institute/NIH)

How the Eyes Work (NEI)

Eye Health Data and Statistics (NEI)

Tam Lab (NEI)

Dubra Lab (Stanford University, Palo Alto, CA)

NIH Support: National Eye Institute


The Synchronicity of Memory

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Credit: Zhou Y, FASEB J, 2020

You may think that you’re looking at a telescopic heat-map of a distant planet, with clickable thumbnail images to the right featuring its unique topography. In fact, what you’re looking at is a small region of the brain that’s measured in micrometers and stands out as a fascinating frontier of discovery into the very origins of thought and cognition.

It’s a section of a mouse hippocampus, a multi-tasking region of the brain that’s central to memory formation. What makes the image on the left so interesting is it shows four individual neurons (numbered circles) helping to form a memory.

The table of images on the right shows in greater detail how the memory is formed. You see those same four neurons, their activity logged individually. Cooler colors—indigo to turquoise—indicate background or low neuronal activity; warmer colors—yellow to red—indicate high neuronal activity.

Now, take a closer look at the rows of the table that are labeled “Initial.” The four neurons have responded to an initial two-part training session: the sounding of a tone (gray-shaded columns) followed by a stimulus (red-shaded columns) less than a minute later. The neurons, while active (multi-colored pattern), don’t fire in unison or at the same activity levels. A memory has not yet been formed.

That’s not the case just below in the rows labeled “Trained.” After several rounds of reinforcing the one-two sequence, neurons fire together at comparable activity levels in response to the tone (gray) followed by the now-predictable stimulus (red). This process of firing in unison, called neuronal synchronization, encodes the memory. In fact, the four neurons even deactivate in unison after each prompt (unshaded columns).

These fascinating images are the first to show an association between neuronal burst synchronization and hippocampus-dependent memory formation. This discovery has broad implications, from improving memory to reconditioning the mental associations that underlie post-traumatic stress disorder (PTSD).

This research comes from a team led by the NIH-supported investigator Xuanmao Chen, University of New Hampshire, Durham. In the study, published in the FASEB Journal, Chen and colleagues used deep-brain imaging technology to shed new light on some old-fashioned classical conditioning: Pavlovian training [1].

Over a century ago, Ivan Pavlov conducted experiments that conditioned dogs to salivate at the sound of a bell that signaled their feeding time. This concept of “classical conditioning” is central to our understanding of how we humans form certain types of memories. A baby smiles at the sound of her mother’s voice. Stores play holiday music at the end of the year, hoping the positive childhood association puts shoppers in the mood to buy more gifts. Our phone plays a distinctive tone, and we immediately check our text messages. In each example, the association with an otherwise neutral stimulus is learned—and stored in the brain as a “declarative,” or explicit, memory.

The researchers wanted to see what happened in neural cells when mice learned a new association. They applied Pavlov’s learning paradigm, training mice over repeated sessions by pairing an audible tone and, about 30 seconds later, a brief, mild foot stimulus. Mice instinctively halt their activities, or freeze, in response to the foot stimulus. After a few tone-stimulus training sessions, the mice also began freezing after the tone was sounded. They had formed a conditioned response.

During these training sessions, Chen and his colleagues were able to take high-resolution, real-time images of the hippocampus. This allowed them to track the same four neurons over the course of the day—and watch as memory creation, in the form of neuronal synchronization, took place. Later, during recall experiments, the tone itself elicited both the behavioral change and the coordinated neuronal response—if with a bit less regularity. It’s something we humans experience whenever we forget a computer password!

The researchers went on to capture even more evidence. They showed that these neurons, which became part of the stored “engram,” or physical location of the memory, were already active even before they were synchronized. This finding contributes to recent work challenging the long-held paradigm that memory-eligible neurons “switch on” from a silent state to form a memory [2]. The researchers offered a new name for these active neurons: “primed,” as opposed to “silent.”

Chen and his colleagues continue studying the priming process and working out more of the underlying molecular details. They’re attempting to determine how the process is regulated and primed neurons become synchronized. And, of course, the big question: how does this translate into an actual memory in other living creatures? The next round of results should be memorable!

References:

[1] Induction of activity synchronization among primed hippocampal neurons out of random dynamics is key for trace memory formation and retrieval. Zhou Y, Qiu L, Wang H, Chen X. FASEB J. 2020 Mar;34(3):3658–3676.

[2] Memory engrams: Recalling the past and imagining the future. Josselyn S, Tonegawa S. Science 2020 Jan 3;367(6473):eaaw4325.

Links:

Brain Basics: Know Your Brain (National Institute of Neurological Disorders and Stroke/NIH)

Neuroanatomy, Hippocampus Fogwe LA, Reddy V, Mesfin FB. StatPearls Publishing (National Library of Medicine/NIH)

Xuanmao Chen (University of New Hampshire, Durham)

NIH Support: National Institute of Mental Health; National Institute on Aging; National Institute of General Medical Sciences


On-the-Spot Gene Readouts Offer Clues to How Cells Work

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Credit: MIT and Harvard Medical School, Cambridge, MA

Just as two companies can merge to expand their capabilities, two technologies can become more powerful when integrated into one. That’s why researchers recently merged two breakthrough technologies into one super powerful new method called ExSeq. The two-in-one technology enables researchers for the first time to study an intact tissue sample and track genetic activity on the spot within a cell’s tiniest recesses, or microenvironments—areas that have been largely out of reach until now.

ExSeq, which is described in a paper in the journal Science [1], will unleash many new experimental applications. Beyond enabling more precise analysis of the basic building blocks of life, these applications include analyzing tumor biopsies more comprehensively and even unlocking mysteries of how the brain works. The latter use is on display in this colorful cross-section of a mouse’s hippocampus, a region of the brain involved in the memory of facts and events.

Here you can see in precise and unprecedented detail the areas where genes are activated (magenta) in the brain’s neurons (green). In this particular example, the genes are working within subregions of the hippocampus called the CA1 and dentate gyrus regions (white, bottom and top left).

ExSeq is a joint effort from NIH grantees Ed Boyden, Massachusetts Institute of Technology (MIT), Cambridge, and George Church, Harvard Medical School, Boston. The new method combines a technology called tissue expansion with an in situ sequencing approach.

Tissue expansion swells the contents of tissue sections up to 100 times their normal size but retains their same physical structure [2]. It’s sort of like increasing the font size and line spacing on a hard-to-read document. It makes cellular details that were outside the resolution range of the light microscope suddenly accessible.

With the information inside cells now easier to see, the next step involves a technique called FISSEQ (fluorescent in situ sequencing), which generates readouts of thousands of mRNA molecules in cells [3]. FISSEQ works by detecting individual RNA molecules where they are inside cells and amplifying them into “nanoballs,” or rolled-up copies of themselves. Each nanoball can be read using standard sequencing methods and a fluorescence microscope.

Using the combined ExSeq approach, the team can analyze precisely where gene activity changes within tiny cellular microenvironments. Or, it can compile a more-comprehensive readout of gene activity within cells by analyzing as many gene readouts as detectable. When used in the hippocampus, this untargeted, “agnostic” approach led to some surprises—revealing unusual forms of RNA and, by association, genes for proteins not previously linked with communication between neurons.

Like many technology developments, the scientists envision that ExSeq can be used in many ways, including for more precise analysis of tumor biopsies. To illustrate this point, the researchers analyzed breast cancer metastases, which are cells from breast tumors that have spread to other areas in the body. Metastases contain many different cell types, including cancer cells and immune cells.

Using ExSeq, Boyden and Church learned that these distinct cell types can behave differently depending on where they are inside a tumor. They discovered, for example, that immune B cells near tumor cells expressed certain inflammatory genes at a higher level than immune B cells that were further away. Precise information about a tumor’s composition and activity may lead to development of more targeted approaches to attack it.

Many discoveries come on the heels of transformative new technologies. ExSeq shines a much brighter light on the world of the very small. And that should help us better understand how different parts of cells work together, as well as how cells work with each other in the brain, in cancer, and throughout the body.

References:

[1] Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems. Alon S, Goodwin DR, Sinha A, Wassie AT, et al. Science. 2021 Jan 29;37:eaax2656.

[2] Expansion microscopy. Chen F, Tillberg PW, Boyden ES. Science. 2015;347:543-548.

[3]. Highly multiplexed subcellular RNA sequencing in situ. Lee JH, Daugharthy ER, Scheiman J, Kalhor R, et al. Science. 2014;343:1360-1363.

Links:

Ribonucleic Acid (RNA) (National Human Genome Research Institute/NIH)

Synthetic Neurobiology Group (Massachusetts Institute of Technology, Cambridge)

George Church (Harvard Medical School, Boston)

NIH Support: National Human Genome Research Institute; National Cancer Institute; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute of Neurological Disorders and Stroke


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