muscle
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
Capturing the Extracellular Matrix in 3D Color
Posted on by Dr. Francis Collins
For experienced and aspiring shutterbugs alike, sometimes the best photo in the bunch turns out to be a practice shot. That’s also occasionally true in the lab when imaging cells and tissues, and it’s the story behind this spectacular image showing the interface of skin and muscle during mammalian development.
Here you see an area of the mouse forelimb located near a bone called the humerus. This particular sample was labeled for laminin, a protein found in the extracellular matrix (ECM) that undergirds cells and tissues to give them mechanical and biochemical support. Computer algorithms were used to convert the original 2D confocal scan into a 3D image, and colorization was added to bring the different layers of tissue into sharper relief.
Skin tissue (bright red and yellow) is located near the top of the image; blood vessels (paler red, orange, and yellow) are in the middle and branching downward; and muscle (green, blue, and purple) makes up the bottom layer.
The image was created by Sarah Lipp, a graduate student in the NIH-supported tissue engineering lab of Sarah Calve. The team focuses on tissue interfaces to better understand the ECM and help devise strategies to engineer musculoskeletal tissues, such as tendon and cartilage.
In February 2020, Lipp was playing around with some new software tools for tissue imaging. Before zeroing in on her main target—the mouse’s myotendinous junction, where muscle transfers its force to tendon, Lipp snapped this practice shot of skin meeting muscle. After processing the practice shot with a color-projecting macro in an image processing tool called Fiji, she immediately liked what she saw.
So, Lipp tweaked the color a bit more and entered the image in the 2020 BioArt Scientific Image & Video Competition, sponsored by the Federation of American Societies for Experimental Biology, Bethesda, MD. Last December, the grad student received the good news that her practice shot had snagged one of the prestigious contest’s top awards.
But she’s not stopping there. Lipp is continuing to pursue her research interests at the University of Colorado, Boulder, where the Calve lab recently moved from Purdue University, West Lafayette, IN. Here’s wishing her a career filled with more great images—and great science!
Links:
Muscle and Bone Diseases (National Institute of Arthritis and Musculoskeletal and Skin Diseases/NIH)
Musculoskeletal Extracellular Matrix Laboratory (University of Colorado, Boulder)
BioArt Scientific Image & Video Competition (Federation of American Societies for Experimental Biology, Bethesda, MD)
NIH Support: National Institute of Arthritis and Musculoskeletal and Skin Diseases
A Race-Free Approach to Diagnosing Chronic Kidney Disease
Posted on by Dr. Francis Collins
Race has a long and tortured history in America. Though great strides have been made through the work of leaders like Dr. Martin Luther King, Jr. to build an equal and just society for all, we still have more work to do, as race continues to factor into American life where it shouldn’t. A medical case in point is a common diagnostic tool for chronic kidney disease (CKD), a condition that affects one in seven American adults and causes a gradual weakening of the kidneys that, for some, will lead to renal failure.
The diagnostic tool is a medical algorithm called estimated glomerular filtration rate (eGFR). It involves getting a blood test that measures how well the kidneys filter out a common waste product from the blood and adding in other personal factors to score how well a person’s kidneys are working. Among those factors is whether a person is Black. However, race is a complicated construct that incorporates components that go well beyond biological and genetic factors to social and cultural issues. The concern is that by lumping together Black people, the algorithm lacks diagnostic precision for individuals and could contribute to racial disparities in healthcare delivery—or even runs the risk of reifying race in a way that suggests more biological significance than it deserves.
That’s why I was pleased recently to see the results of two NIH-supported studies published in The New England Journal of Medicine that suggest a way to take race out of the kidney disease equation [1, 2]. The approach involves a new equation that swaps out one blood test for another and doesn’t ask about race.
For a variety of reasons, including socioeconomic issues and access to healthcare, CKD disproportionately affects the Black community. In fact, Blacks with the condition are also almost four times more likely than whites to develop kidney failure. That’s why Blacks with CKD must visit their doctors regularly to monitor their kidney function, and often that visit involves eGFR.
The blood test used in eGFR measures creatinine, a waste product produced from muscle. For about the past 20 years, a few points have been automatically added to the score of African Americans, based on data showing that adults who identify as Black, on average, have a higher baseline level of circulating creatinine. But adjusting the score upward toward normal function runs the risk of making the kidneys seem a bit healthier than they really are and delaying life-preserving dialysis or getting on a transplant list.
A team led by Chi-yuan Hsu, University of California, San Francisco, took a closer look at the current eGFR calculations. The researchers used long-term data from the Chronic Renal Insufficiency Cohort (CRIC) Study, an NIH-supported prospective, observational study of nearly 4,000 racially and ethnically diverse patients with CKD in the U.S. The study design specified that about 40 percent of its participants should identify as Black.
To look for race-free ways to measure kidney function, the researchers randomly selected more than 1,400 of the study’s participants to undergo a procedure that allows kidney function to be measured directly instead of being estimated based on blood tests. The goal was to develop an accurate approach to estimating GFR, the rate of fluid flow through the kidneys, from blood test results that didn’t rely on race.
Their studies showed that simply omitting race from the equation would underestimate GFR in Black study participants. The best solution, they found, was to calculate eGFR based on cystatin C, a small protein that the kidneys filter from the blood, in place of the standard creatinine. Estimation of GFR using cystatin C generated similarly accurate results but without the need to factor in race.
The second NIH-supported study led by Lesley Inker, Tufts Medical Center, Boston, MA, came to similar conclusions. They set out to develop new equations without race using data from several prior studies. They then compared the accuracy of their new eGFR equations to measured GFR in a validation set of 12 other studies, including about 4,000 participants.
Their findings show that currently used equations that include race, sex, and age overestimated measured GFR in Black Americans. However, taking race out of the equation without other adjustments underestimated measured GFR in Black people. Equations including both creatinine and cystatin C, but omitting race, were more accurate. The new equations also led to smaller estimated differences between Black and non-Black study participants.
The hope is that these findings will build momentum toward widespread adoption of cystatin C for estimating GFR. Already, a national task force has recommended immediate implementation of a new diagnostic equation that eliminates race and called for national efforts to increase the routine and timely measurement of cystatin C [3]. This will require a sea change in the standard measurements of blood chemistries in clinical and hospital labs—where creatinine is routinely measured, but cystatin C is not. As these findings are implemented into routine clinical care, let’s hope they’ll reduce health disparities by leading to more accurate and timely diagnosis, supporting the goals of precision health and encouraging treatment of CKD for all people, regardless of their race.
References:
[1] Race, genetic ancestry, and estimating kidney function in CKD. Hsu CY, Yang W, Parikh RV, Anderson AH, Chen TK, Cohen DL, He J, Mohanty MJ, Lash JP, Mills KT, Muiru AN, Parsa A, Saunders MR, Shafi T, Townsend RR, Waikar SS, Wang J, Wolf M, Tan TC, Feldman HI, Go AS; CRIC Study Investigators. N Engl J Med. 2021 Sep 23.
[2] New creatinine- and cystatin C-based equations to estimate GFR without race. Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, Crews DC, Doria A, Estrella MM, Froissart M, Grams ME, Greene T, Grubb A, Gudnason V, Gutiérrez OM, Kalil R, Karger AB, Mauer M, Navis G, Nelson RG, Poggio ED, Rodby R, Rossing P, Rule AD, Selvin E, Seegmiller JC, Shlipak MG, Torres VE, Yang W, Ballew SH,Couture SJ, Powe NR, Levey AS; Chronic Kidney Disease Epidemiology Collaboration. N Engl J Med. 2021 Sep 23.
[3] A unifying approach for GFR estimation: recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease. Delgado C, Baweja M, Crews DC, Eneanya ND, Gadegbeku CA, Inker LA, Mendu ML, Miller WG, Moxey-Mims MM, Roberts GV, St Peter WL, Warfield C, Powe NR. Am J Kidney Dis. 2021 Sep 22:S0272-6386(21)00828-3.
Links:
Chronic Kidney Disease (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)
Explaining Your Kidney Test Results: A Tool for Clinical Use (NIDDK)
Chronic Renal Insufficiency Cohort Study
Chi-yuan Hsu (University of California, San Francisco)
Lesley Inker (Tufts Medical Center, Boston)
NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases
Engineering a Better Way to Deliver Therapeutic Genes to Muscles
Posted on by Dr. Francis Collins
Amid all the progress toward ending the COVID-19 pandemic, it’s worth remembering that researchers here and around the world continue to make important advances in tackling many other serious health conditions. As an inspiring NIH-supported example, I’d like to share an advance on the use of gene therapy for treating genetic diseases that progressively degenerate muscle, such as Duchenne muscular dystrophy (DMD).
As published recently in the journal Cell, researchers have developed a promising approach to deliver therapeutic genes and gene editing tools to muscle more efficiently, thus requiring lower doses [1]. In animal studies, the new approach has targeted muscle far more effectively than existing strategies. It offers an exciting way forward to reduce unwanted side effects from off-target delivery, which has hampered the development of gene therapy for many conditions.
In boys born with DMD (it’s an X-linked disease and therefore affects males), skeletal and heart muscles progressively weaken due to mutations in a gene encoding a critical muscle protein called dystrophin. By age 10, most boys require a wheelchair. Sadly, their life expectancy remains less than 30 years.
The hope is gene therapies will one day treat or even cure DMD and allow people with the disease to live longer, high-quality lives. Unfortunately, the benign adeno-associated viruses (AAVs) traditionally used to deliver the healthy intact dystrophin gene into cells mostly end up in the liver—not in muscles. It’s also the case for gene therapy of many other muscle-wasting genetic diseases.
The heavy dose of viral vector to the liver is not without concern. Recently and tragically, there have been deaths in a high-dose AAV gene therapy trial for X-linked myotubular myopathy (XLMTM), a different disorder of skeletal muscle in which there may already be underlying liver disease, potentially increasing susceptibility to toxicity.
To correct this concerning routing error, researchers led by Mohammadsharif Tabebordbar in the lab of Pardis Sabeti, Broad Institute of MIT and Harvard and Harvard University, Cambridge, MA, have now assembled an optimized collection of AAVs. They have been refined to be about 10 times better at reaching muscle fibers than those now used in laboratory studies and clinical trials. In fact, researchers call them myotube AAVs, or MyoAAVs.
MyoAAVs can deliver therapeutic genes to muscle at much lower doses—up to 250 times lower than what’s needed with traditional AAVs. While this approach hasn’t yet been tried in people, animal studies show that MyoAAVs also largely avoid the liver, raising the prospect for more effective gene therapies without the risk of liver damage and other serious side effects.
In the Cell paper, the researchers demonstrate how they generated MyoAAVs, starting out with the commonly used AAV9. Their goal was to modify the outer protein shell, or capsid, to create an AAV that would be much better at specifically targeting muscle. To do so, they turned to their capsid engineering platform known as, appropriately enough, DELIVER. It’s short for Directed Evolution of AAV capsids Leveraging In Vivo Expression of transgene RNA.
Here’s how DELIVER works. The researchers generate millions of different AAV capsids by adding random strings of amino acids to the portion of the AAV9 capsid that binds to cells. They inject those modified AAVs into mice and then sequence the RNA from cells in muscle tissue throughout the body. The researchers want to identify AAVs that not only enter muscle cells but that also successfully deliver therapeutic genes into the nucleus to compensate for the damaged version of the gene.
This search delivered not just one AAV—it produced several related ones, all bearing a unique surface structure that enabled them specifically to target muscle cells. Then, in collaboration with Amy Wagers, Harvard University, Cambridge, MA, the team tested their MyoAAV toolset in animal studies.
The first cargo, however, wasn’t a gene. It was the gene-editing system CRISPR-Cas9. The team found the MyoAAVs correctly delivered the gene-editing system to muscle cells and also repaired dysfunctional copies of the dystrophin gene better than the CRISPR cargo carried by conventional AAVs. Importantly, the muscles of MyoAAV-treated animals also showed greater strength and function.
Next, the researchers teamed up with Alan Beggs, Boston Children’s Hospital, and found that MyoAAV was effective in treating mouse models of XLMTM. This is the very condition mentioned above, in which very high dose gene therapy with a current AAV vector has led to tragic outcomes. XLMTM mice normally die in 10 weeks. But, after receiving MyoAAV carrying a corrective gene, all six mice had a normal lifespan. By comparison, mice treated in the same way with traditional AAV lived only up to 21 weeks of age. What’s more, the researchers used MyoAAV at a dose 100 times lower than that currently used in clinical trials.
While further study is needed before this approach can be tested in people, MyoAAV was also used to successfully introduce therapeutic genes into human cells in the lab. This suggests that the early success in animals might hold up in people. The approach also has promise for developing AAVs with potential for targeting other organs, thereby possibly providing treatment for a wide range of genetic conditions.
The new findings are the result of a decade of work from Tabebordbar, the study’s first author. His tireless work is also personal. His father has a rare genetic muscle disease that has put him in a wheelchair. With this latest advance, the hope is that the next generation of promising gene therapies might soon make its way to the clinic to help Tabebordbar’s father and so many other people.
Reference:
[1] Directed evolution of a family of AAV capsid variants enabling potent muscle-directed gene delivery across species. Tabebordbar M, Lagerborg KA, Stanton A, King EM, Ye S, Tellez L, Krunnfusz A, Tavakoli S, Widrick JJ, Messemer KA, Troiano EC, Moghadaszadeh B, Peacker BL, Leacock KA, Horwitz N, Beggs AH, Wagers AJ, Sabeti PC. Cell. 2021 Sep 4:S0092-8674(21)01002-3.
Links:
Muscular Dystrophy Information Page (National Institute of Neurological Disorders and Stroke/NIH)
X-linked myotubular myopathy (Genetic and Rare Diseases Information Center/National Center for Advancing Translational Sciences/NIH)
Somatic Cell Genome Editing (Common Fund/NIH)
Mohammadsharif Tabebordbar (Broad Institute of MIT and Harvard and Harvard University, Cambridge, MA)
Sabeti Lab (Broad Institute of MIT and Harvard and Harvard University)
NIH Support: Eunice Kennedy Shriver National Institute of Child Health and Human Development; Common Fund
Boldly Going Where No Science Has Gone Before
Posted on by Dr. Francis Collins
It was an amazing experience to touch base once again with Kate Rubins, a NASA astronaut aboard the International Space Station. Connecting via live downlink on March 26, 2021, we discussed how space-based research can enable valuable biomedical advances on our planet. For example, over the past five years, NIH’s National Center for Advancing Translational Sciences has funded a series of tissue chip payloads that have launched to the orbiting laboratory. Rubins, who is a biologist and infectious disease expert, has facilitated three of these projects: Cardinal Heart from Stanford University, Electrical Stimulation of Human Myocytes in Microgravity from the University of Florida, and Cartilage-Bone-Synovium from the Massachusetts Institute of Technology.
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