Past Stories
Millions of Single-Cell Analyses Yield Most Comprehensive Human Cell Atlas Yet
Posted on by Lawrence Tabak, D.D.S., Ph.D.
There are 37 trillion or so cells in our bodies that work together to give us life. But it may surprise you that we still haven’t put a good number on how many distinct cell types there are within those trillions of cells.
That’s why in 2016, a team of researchers from around the globe launched a historic project called the Human Cell Atlas (HCA) consortium to identify and define the hundreds of presumed distinct cell types in our bodies. Knowing where each cell type resides in the body, and which genes each one turns on or off to create its own unique molecular identity, will revolutionize our studies of human biology and medicine across the board.
Since its launch, the HCA has progressed rapidly. In fact, it has already reached an important milestone with the recent publication in the journal Science of four studies that, together, comprise the first multi-tissue drafts of the human cell atlas. This draft, based on analyses of millions of cells, defines more than 500 different cell types in more than 30 human tissues. A second draft, with even finer definition, is already in the works.
Making the HCA possible are recent technological advances in RNA sequencing. RNA sequencing is a topic that’s been mentioned frequently on this blog in a range of research areas, from neuroscience to skin rashes. Researchers use it to detect and analyze all the messenger RNA (mRNA) molecules in a biological sample, in this case individual human cells from a wide range of tissues, organs, and individuals who voluntarily donated their tissues.
By quantifying these RNA messages, researchers can capture the thousands of genes that any given cell actively expresses at any one time. These precise gene expression profiles can be used to catalogue cells from throughout the body and understand the important similarities and differences among them.
In one of the published studies, funded in part by the NIH, a team co-led by Aviv Regev, a founding co-chair of the consortium at the Broad Institute of MIT and Harvard, Cambridge, MA, established a framework for multi-tissue human cell atlases [1]. (Regev is now on leave from the Broad Institute and MIT and has recently moved to Genentech Research and Early Development, South San Francisco, CA.)
Among its many advances, Regev’s team optimized single-cell RNA sequencing for use on cell nuclei isolated from frozen tissue. This technological advance paved the way for single-cell analyses of the vast numbers of samples that are stored in research collections and freezers all around the world.
Using their new pipeline, Regev and team built an atlas including more than 200,000 single-cell RNA sequence profiles from eight tissue types collected from 16 individuals. These samples were archived earlier by NIH’s Genotype-Tissue Expression (GTEx) project. The team’s data revealed unexpected differences among cell types but surprising similarities, too.
For example, they found that genetic profiles seen in muscle cells were also present in connective tissue cells in the lungs. Using novel machine learning approaches to help make sense of their data, they’ve linked the cells in their atlases with thousands of genetic diseases and traits to identify cell types and genetic profiles that may contribute to a wide range of human conditions.
By cross-referencing 6,000 genes previously implicated in causing specific genetic disorders with their single-cell genetic profiles, they identified new cell types that may play unexpected roles. For instance, they found some non-muscle cells that may play a role in muscular dystrophy, a group of conditions in which muscles progressively weaken. More research will be needed to make sense of these fascinating, but vital, discoveries.
The team also compared genes that are more active in specific cell types to genes with previously identified links to more complex conditions. Again, their data surprised them. They identified new cell types that may play a role in conditions such as heart disease and inflammatory bowel disease.
Two of the other papers, one of which was funded in part by NIH, explored the immune system, especially the similarities and differences among immune cells that reside in specific tissues, such as scavenging macrophages [2,3] This is a critical area of study. Most of our understanding of the immune system comes from immune cells that circulate in the bloodstream, not these resident macrophages and other immune cells.
These immune cell atlases, which are still first drafts, already provide an invaluable resource toward designing new treatments to bolster immune responses, such as vaccines and anti-cancer treatments. They also may have implications for understanding what goes wrong in various autoimmune conditions.
Scientists have been working for more than 150 years to characterize the trillions of cells in our bodies. Thanks to this timely effort and its advances in describing and cataloguing cell types, we now have a much better foundation for understanding these fundamental units of the human body.
But the latest data are just the tip of the iceberg, with vast flows of biological information from throughout the human body surely to be released in the years ahead. And while consortium members continue making history, their hard work to date is freely available to the scientific community to explore critical biological questions with far-reaching implications for human health and disease.
References:
[1] Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. Eraslan G, Drokhlyansky E, Anand S, Fiskin E, Subramanian A, Segrè AV, Aguet F, Rozenblatt-Rosen O, Ardlie KG, Regev A, et al. Science. 2022 May 13;376(6594):eabl4290.
[2] Cross-tissue immune cell analysis reveals tissue-specific features in humans. Domínguez Conde C, Xu C, Jarvis LB, Rainbow DB, Farber DL, Saeb-Parsy K, Jones JL,Teichmann SA, et al. Science. 2022 May 13;376(6594):eabl5197.
[3] Mapping the developing human immune system across organs. Suo C, Dann E, Goh I, Jardine L, Marioni JC, Clatworthy MR, Haniffa M, Teichmann SA, et al. Science. 2022 May 12:eabo0510.
Links:
Ribonucleic acid (RNA) (National Human Genome Research Institute/NIH)
Studying Cells (National Institute of General Medical Sciences/NIH)
Regev Lab (Broad Institute of MIT and Harvard, Cambridge, MA)
NIH Support: Common Fund; National Cancer Institute; National Human Genome Research Institute; National Heart, Lung, and Blood Institute; National Institute on Drug Abuse; National Institute of Mental Health; National Institute on Aging; National Institute of Allergy and Infectious Diseases; National Institute of Neurological Disorders and Stroke; National Eye Institute
Rice-Sized Device Tests Brain Tumor’s Drug Responses During Surgery
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Scientists have made remarkable progress in understanding the underlying changes that make cancer grow and have applied this knowledge to develop and guide targeted treatment approaches to vastly improve outcomes for people with many cancer types. And yet treatment progress for people with brain tumors known as gliomas—including the most aggressive glioblastomas—has remained slow. One reason is that doctors lack tests that reliably predict which among many therapeutic options will work best for a given tumor.
Now an NIH-funded team has developed a miniature device with the potential to change this for the approximately 25,000 people diagnosed with brain cancers in the U.S. each year [1]. When implanted into cancerous brain tissue during surgery, the rice-sized drug-releasing device can simultaneously conduct experiments to measure a tumor’s response to more than a dozen drugs or drug combinations. What’s more, a small clinical trial reported in Science Translational Medicine offers the first evidence in people with gliomas that these devices can safely offer unprecedented insight into tumor-specific drug responses [2].
These latest findings come from a Brigham and Women’s Hospital, Boston, team led by Pierpaolo Peruzzi and Oliver Jonas. They recognized that drug-screening studies conducted in cells or tissue samples in the lab too often failed to match what happens in people with gliomas undergoing cancer treatment. Wide variation within individual brain tumors also makes it hard to predict a tumor’s likely response to various treatment options.
It led them to an intriguing idea: Why not test various therapeutic options in each patient’s tumor? To do it, they developed a device, about six millimeters long, that can be inserted into a brain tumor during surgery to deliver tiny doses of up to 20 drugs. Doctors can then remove and examine the drug-exposed cancerous tissue in the laboratory to determine each treatment’s effects. The data can then be used to guide subsequent treatment decisions, according to the researchers.
In the current study, the researchers tested their device on six study volunteers undergoing brain surgery to remove a glioma tumor. For each volunteer, the device was implanted into the tumor and remained in place for about two to three hours while surgeons worked to remove most of the tumor. Next, the device was taken out along with the last piece of a tumor at the end of the surgery for further study of drug responses.
Importantly, none of the study participants experienced any adverse effects from the device. Using the devices, the researchers collected valuable data, including how a tumor’s response changed with varying drug concentrations or how each treatment led to molecular changes in the cancerous cells.
More research is needed to better understand how use of such a device might change treatment and patient outcomes in the longer term. The researchers note that it would take more than a couple of hours to determine how treatments produce less immediate changes, such as immune responses. As such, they’re now conducting a follow-up trial to test a possible two-stage procedure, in which their device is inserted first using minimally invasive surgery 72 hours prior to a planned surgery, allowing longer exposure of tumor tissue to drugs prior to a tumor’s surgical removal.
Many questions remain as they continue to optimize this approach. However, it’s clear that such a device gives new meaning to personalized cancer treatment, with great potential to improve outcomes for people living with hard-to-treat gliomas.
References:
[1] National Cancer Institute Surveillance, Epidemiology, and End Results Program. Cancer Stat Facts: Brain and Other Nervous System Cancer.
[2] Peruzzi P et al. Intratumoral drug-releasing microdevices allow in situ high-throughput pharmaco phenotyping in patients with gliomas. Science Translational Medicine DOI: 10.1126/scitranslmed.adi0069 (2023).
Links:
Brain Tumors – Patient Version (National Cancer Institute/NIH)
Pierpaolo Peruzzi (Brigham and Women’s Hospital, Boston, MA)
Jonas Lab (Brigham and Women’s Hospital, Boston, MA)
NIH Support: National Cancer Institute, National Institute of Biomedical Imaging and Bioengineering, National Institute of Neurological Disorders and Stroke
New Approach to ‘Liquid Biopsy’ Relies on Repetitive RNA in the Bloodstream
Posted on by Lawrence Tabak, D.D.S., Ph.D.
It’s always best to diagnose cancer at an early stage when treatment is most likely to succeed. Unfortunately, far too many cancers are still detected only after cancer cells have escaped from a primary tumor and spread to distant parts of the body. This explains why there’s been so much effort in recent years to develop liquid biopsies, which are tests that can pick up on circulating cancer cells or molecular signs of cancer in blood or other bodily fluids and reliably trace them back to the organ in which a potentially life-threatening tumor is growing.
Earlier methods to develop liquid biopsies for detecting cancers often have relied on the presence of cancer-related proteins and/or DNA in the bloodstream. Now, an NIH-supported research team has encouraging evidence to suggest that this general approach to detecting cancers—including aggressive pancreatic cancers—may work even better by taking advantage of signals from a lesser-known form of genetic material called noncoding RNA.
The findings reported in Nature Biomedical Engineering suggest that the new liquid biopsy approach may aid in the diagnosis of many forms of cancer [1]. The studies show that the sensitivity of the tests varies—a highly sensitive test is one that rarely misses cases of disease. However, they already have evidence that millions of circulating RNA molecules may hold promise for detecting cancers of the liver, esophagus, colon, stomach, and lung.
How does it work? The human genome contains about 3 billion paired DNA letters. Most of those letters are transcribed, or copied, into single-stranded RNA molecules. While RNA is best known for encoding proteins that do the work of the cell, most RNA never gets translated into proteins at all. This noncoding RNA includes repetitive RNA that can be transcribed from millions of repeat elements—patterns of the same few DNA letters occurring multiple times in the genome.
Common approaches to studying RNA don’t analyze repetitive RNA, so its usefulness as a diagnostic tool has been unclear—until recently. Last year, the lab of Daniel Kim at the University of California, Santa Cruz reported [2] that a key genetic mutation that occurs early on in some cancers causes repetitive RNA molecules to be secreted in large quantities from cancer cells, even at the earliest stages of cancer. Non-cancerous cells, by comparison, release much less repetitive RNA.
The findings suggested that liquid biopsy tests that look for this repetitive, noncoding RNA might offer a powerful new way to detect cancers sooner, according to the authors. But first they needed a method capable of measuring it. Due to its oftentimes uncertain functions, the researchers have referred to repetitive, noncoding RNA as “dark matter.”
Using a liquid biopsy platform they developed called COMPLETE-seq, Kim’s team trained computers to detect cancers by looking for patterns in RNA data. The platform enables sequencing and analysis of all protein coding and noncoding RNAs—including any RNA from more than 5 million repeat elements—present in a blood sample. They found that their classifiers worked better when repetitive RNAs were included. The findings lend support to the idea that repetitive, noncoding RNA in the bloodstream is a rich source of information for detecting cancers, which has previously been overlooked.
In a study comparing blood samples from healthy people to those with pancreatic cancer, the COMPLETE-seq technology showed that nearly all people in the study with pancreatic cancer had more repetitive, noncoding RNA in their blood samples compared to healthy people, according to the researchers. They used the COMPLETE-seq test on blood samples from people with other types of cancer as well. For example, their test accurately detected 91% of colorectal cancer samples and 93% of lung cancer samples.
They now plan to look at many more cancer types with samples from additional patients representing a broad range of cancer stages. The goal is to develop a single RNA liquid biopsy test that could detect multiple forms of cancer with a high degree of accuracy and specificity. They note that such a test might also be used to guide treatment decisions and more readily detect a cancer’s recurrence. The hope is that one day a comprehensive liquid biopsy test including coding and noncoding RNA will catch many more cancers sooner, when treatment can be most successful.
References:
[1] RE Reggiardo et al. Profiling of repetitive RNA sequences in the blood plasma of patients with cancer. Nature Biomedical Engineering DOI: 10.1038/s41551-023-01081-7 (2023).
[2] RE Reggiardo et al. Mutant KRAS regulates transposable element RNA and innate immunity via KRAB zinc-finger genes. Cell Reports DOI: 10.1016/j.celrep.2022.111104 (2022).
Links:
Daniel Kim Lab (UC Santa Cruz)
Cancer Screening Overview (National Cancer Institute/NIH)
Early Detection (National Cancer Institute/NIH)
NIH Support: National Cancer Institute, National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases
NIH Welcomes Tribal Leaders for Annual Tribal Advisory Committee Meeting
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Credit: Chiachi Chang, NIH
How to Feed a Macrophage
Posted on by Lawrence Tabak, D.D.S., Ph.D.
For Annalise Bond, a graduate student in the lab of Meghan Morrissey, University of California, Santa Barbara (UCSB), macrophages are “the professional eaters of our immune system.” Every minute of every day, macrophages somewhere in the body are gorging themselves to remove the cellular debris that builds up in our tissues and organs.
In this image, Bond caught several macrophages (green) doing what they do best: shoveling it in—in this case, during a lab experiment. The macrophages are consuming silica beads (purple) prepared with biochemicals that whet their appetites. Each bead measures about five microns in diameter. That’s roughly the size of a bacterium or a spent red blood cell—debris that a macrophage routinely consumes.
When Bond snapped this image, she noticed a pattern that reminded her of a childhood tabletop game called Hungry Hungry Hippos. Kids press a lever attached to the mouth of a plastic hippo, its lower jaw flaps open, and the challenge is to fill the mouth with as many marbles as possible . . . just like the macrophages eating beads.
Bond adjusted the colors in the photo to make them pop. She then entered it into UCSB’s 2023 Art of Science contest with the caption of Hungry Hungry Macrophages, winning high marks for drawing the association.
Though the caption was written in fun, Bond studies in earnest a fascinating biological question: How do macrophages know what to eat in the body and what to leave untouched?
In her studies, Bond coats the silica beads shown above with a lipid bilayer to mimic a cell membrane. To that coating, she adds various small molecules and proteins as “eat-me” signals often found on the surface of dying cells. Some of the signals are well characterized; but many aren’t, meaning there’s still a lot to learn about what makes a macrophage “particularly hungry” and what makes a particular target cell “extra tasty.”
Capturing fluorescent images of macrophages under the microscope, Bond counts up how many beads are eaten. Beads bearing no signal to stimulate their appetite might get eaten occasionally. But when an especially enticing signal is added, macrophages will gorge themselves until they can’t eat anymore.
In the experiment pictured above, the beads contain the antibody immunoglobulin G (IgG), which tags foreign pathogens for macrophage removal. Interestingly, IgG antibody responses also play an important role in cancer immunotherapies, in which the immune system is unleashed to fight cancer.
Among its many areas of study, the NIH-supported Morrissey lab’s wants to understand better how macrophages interact with cancer cells. They want to learn how to make cancer cells even tastier to macrophages and program their elimination from the body. Sorting out the signals will be challenging, but we know that macrophages will take a bite at the right ones. They are, after all, professional eaters.
Links:
Cancer Immunotherapy (NIH)
Annalise Bond (University of California, Santa Barbara)
Morrissey Lab (University of California, Santa Barbara)
Art of Science (University of California, Santa Barbara)
NIH Support: National Institute of General Medical Sciences
Science, Serendipity, and Art
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Fractals are complex geometric patterns repeated at progressively smaller scales. You’ll find them throughout nature. That includes in the 3D structures and shapes of tissues throughout our bodies, from the bones in our skulls down to the blood vessels in our feet. But the fractal pattern above isn’t from a precisely patterned human tissue. It comes from some unexpected biochemistry that formed the stunning pattern on its own.
In fact, the exact source for this fractal pattern reminiscent of peacock feathers isn’t known. It turned up out of the blue (and green) in a sample that had been sitting around on the shelf for some time. The original image appeared in black and white, but the colors added post-collection help to highlight the fractal pattern of a sample including an essential hormone produced in the pancreas. The hormone is called islet amyloid polypeptide (IAPP).
Also known as amylin, IAPP plays many important roles in our bodies, including the feeling of fullness after a meal. But the amino acid chains that make up IAPP also are prone to forming abnormal clumps of misfolded polypeptides (a long name for proteins) known as amyloids. Much like the amyloid plaques in the brains of people with Alzheimer’s disease, misfolded IAPP amyloids in people with type 2 diabetes also can damage insulin-producing beta cells in the pancreas and make controlling their blood sugar levels even more difficult.
This unusual image comes from graduate students Bryan Bogin and Matthew Steinsaltz. They study the biophysics and biochemistry of protein folding and misfolding in the lab of Zachary Levine, Yale School of Medicine, New Haven, CT. The Levine lab recently moved to the Altos Labs San Diego Institute. However, Bogin and Steinsaltz continue to conduct their studies at Yale.
The two conduct in-solution experiments and molecular simulations to elucidate the precise conditions and triggers that can lead otherwise normal polypeptide chains to fold up incorrectly and wreak havoc as they do in diabetes and other diseases. When Steinsaltz was learning how to use transmission electron microscopy (TEM), a technique in which an electron beam captures images including detailed molecular-level structures, Bogin handed over an assortment of IAPP samples in different solution conditions from some of his past experiments for a look.
In those microscopy images, they expected to see long, linear fibrils consisting of IAPP polypeptides. While that’s indeed what they saw in most of the samples, this one was the exception. It was such a remarkable image that they submitted it in the Biophysical Society’s 2022 Art of Science Image Contest, where it took the top prize.
Bogin and Steinsaltz say they still can’t explain the source or meaning behind these unusual fractal patterns. But they do continue to conduct experiments to understand how various polypeptides implicated in health and disease misfold to form destructive aggregates. This striking image may not hold the answers they seek, but it is an inspiring reminder that the path to making groundbreaking biomedical discoveries will have many beautiful surprises along the way.
Links:
Type 2 Diabetes (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)
Zachary Levine Lab (Yale School of Medicine, New Haven, CT)
Art of Science Image Contest (Biophysical Society, Rockville, MD)
NIH Support: National Institute on Aging
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