Posted on by Dr. Francis Collins
You may have heard about the new variants of SARS-CoV-2—the coronavirus that causes COVID-19—that have appeared in other parts of the world and have now been detected in the United States. These variants, particularly one called B.1.351 that was first identified in South Africa, have raised growing concerns about the extent to which their mutations might help them evade current antibody treatments and highly effective vaccines.
While researchers take a closer look, it’s already possible in the laboratory to predict which mutations will help SARS-CoV-2 evade our therapies and vaccines, and even to prepare for the emergence of new mutations before they occur. In fact, an NIH-funded study, which originally appeared as a bioRxiv pre-print in November and was recently peer-reviewed and published in Science, has done exactly that. In the study, researchers mapped all possible mutations that would allow SARS-CoV-2 to resist treatment with three different monoclonal antibodies developed for treatment of COVID-19 .
The work, led by Jesse Bloom, Allison Greaney, and Tyler Starr, Fred Hutchinson Cancer Center, Seattle, focused on the receptor binding domain (RBD), a key region of the spike protein that studs SARS-CoV-2’s outer surface. The virus uses RBD to anchor itself to the ACE2 receptor of human cells before infecting them. That makes the RBD a prime target for the antibodies that our bodies generate to defend against the virus.
In the new study, researchers used a method called deep mutational scanning to find out which mutations positively or negatively influence the RBD from being able to bind to ACE2 and/or thwart antibodies from striking their target. Here’s how it works: Rather than waiting for new mutations to arise, the researchers created a library of RBD fragments, each of which contained a change in a single nucleotide “letter” that would alter the spike protein’s shape and/or function by swapping one amino acid for another. It turns out that there are more than 3,800 such possible mutations, and Bloom’s team managed to make all but a handful of those versions of the RBD fragment.
The team then used a standard laboratory approach to measure systematically how each of those single-letter typos altered RBD’s ability to bind ACE2 and infect human cells. They also measured how those changes affected three different therapeutic antibodies from recognizing and binding to the viral RBD. Those antibodies include two developed by Regeneron (REGN10933 and REGN10987), which have been granted emergency use authorization for treatment of COVID-19 together as a cocktail called REGN-COV2. They also looked at an antibody developed by Eli Lilly (LY-CoV016), which is now in phase 3 clinical trials for treating COVID-19.
Based on the data, the researchers created four mutational maps for SARS-CoV-2 to escape each of the three therapeutic antibodies, as well as for the REGN-COV2 cocktail. Their studies show most of the mutations that would allow SARS-CoV-2 to escape treatment differed between the two Regeneron antibodies. That’s encouraging because it indicates that the virus likely needs more than one mutation to become resistant to the REGN-COV2 cocktail. However, it appears there’s one spot where a single mutation could allow the virus to resist REGN-COV2 treatment.
The escape map for LY-CoV016 similarly showed a number of mutations that could allow the virus to escape. Importantly, while some of those changes might impair the virus’s ability to cause infection, most of them appeared to come at little to no cost to the virus to reproduce.
How do these laboratory data relate to the real world? To begin to explore this question, the researchers teamed up with Jonathan Li, Brigham and Women’s Hospital, Boston. They looked at an immunocompromised patient who’d had COVID-19 for an unusually long time and who was treated with the Regeneron cocktail for 145 days, giving the virus time to replicate and acquire new mutations.
Viral genome data from the infected patient showed that these maps can indeed be used to predict likely paths of viral evolution. Over the course of the antibody treatment, SARS-CoV-2 showed changes in the frequency of five mutations that would change the makeup of the spike protein and its RBD. Based on the newly drawn escape maps, three of those five are expected to reduce the efficacy of REGN10933. One of the others is expected to limit binding by the other antibody, REGN10987.
The researchers also looked to data from all known circulating SARS-CoV-2 variants as of Jan. 11, 2021, for evidence of escape mutations. They found that a substantial number of mutations with potential to allow escape from antibody treatment already are present, particularly in parts of Europe and South Africa.
However, it’s important to note that these maps reflect just three important antibody treatments. Bloom says they’ll continue to produce maps for other promising therapeutic antibodies. They’ll also continue to explore where changes in the virus could allow for escape from the more diverse set of antibodies produced by our immune system after a COVID-19 infection or vaccination.
While it’s possible some COVID-19 vaccines may offer less protection against some of these new variants—and recent results have suggested the AstraZeneca vaccine may not provide much protection against the South African variant, there’s still enough protection in most other current vaccines to prevent serious illness, hospitalization, and death. And the best way to keep SARS-CoV-2 from finding new ways to escape our ongoing efforts to end this terrible pandemic is to double down on whatever we can do to prevent the virus from multiplying and spreading in the first place.
For now, emergence of these new variants should encourage all of us to take steps to slow the spread of SARS-CoV-2. That means following the three W’s: Wear a mask, Watch your distance, Wash your hands often. It also means rolling up our sleeves to get vaccinated as soon as the opportunity arises.
 Prospective mapping of viral mutations that escape antibodies used to treat COVID-19.
Starr TN, Greaney AJ, Addetia A, Hannon WW, Choudhary MC, Dingens AS, Li JZ, Bloom JD.
Science. 2021 Jan 25:eabf9302.
COVID-19 Research (NIH)
Bloom Lab (Fred Hutchinson Cancer Center, Seattle)
NIH Support: National Institute of Allergy and Infectious Diseases
Posted on by Dr. Francis Collins
There’s been tremendous excitement recently about the potential of CRISPR and related gene-editing technologies for treating or even curing sickle cell disease (SCD), muscular dystrophy, HIV, and a wide range of other devastating conditions. Now comes word of another remarkable advance—called “prime editing”—that may bring us even closer to reaching that goal.
As groundbreaking as CRISPR/Cas9 has been for editing specific genes, the system has its limitations. The initial version is best suited for making a double-stranded break in DNA, followed by error-prone repair. The outcome is generally to knock out the target. That’s great if eliminating the target is the desired goal. But what if the goal is to fix a mutation by editing it back to the normal sequence?
The new prime editing system, which was described recently by NIH-funded researchers in the journal Nature, is revolutionary because it offers much greater control for making a wide range of precisely targeted edits to the DNA code, which consists of the four “letters” (actually chemical bases) A, C, G, and T .
Already, in tests involving human cells grown in the lab, the researchers have used prime editing to correct genetic mutations that cause two inherited diseases: SCD, a painful, life-threatening blood disorder, and Tay-Sachs disease, a fatal neurological disorder. What’s more, they say the versatility of their new gene-editing system means it can, in principle, correct about 89 percent of the more than 75,000 known genetic variants associated with human diseases.
In standard CRISPR, a scissor-like enzyme called Cas9 is used to cut all the way through both strands of the DNA molecule’s double helix. That usually results in the cell’s DNA repair apparatus inserting or deleting DNA letters at the site. As a result, CRISPR is extremely useful for disrupting genes and inserting or removing large DNA segments. However, it is difficult to use this system to make more subtle corrections to DNA, such as swapping a letter T for an A.
To expand the gene-editing toolbox, a research team led by David R. Liu, Broad Institute of MIT and Harvard, Cambridge, MA, previously developed a class of editing agents called base editors [2,3]. Instead of cutting DNA, base editors directly convert one DNA letter to another. However, base editing has limitations, too. It works well for correcting four of the most common single letter mutations in DNA. But at least so far, base editors haven’t been able to make eight other single letter changes, or fix extra or missing DNA letters.
In contrast, the new prime editing system can precisely and efficiently swap any single letter of DNA for any other, and can make both deletions and insertions, at least up to a certain size. The system consists of a modified version of the Cas9 enzyme fused with another enzyme, called reverse transcriptase, and a specially engineered guide RNA, called pegRNA. The latter contains the desired gene edit and steers the needed editing apparatus to a specific site in a cell’s DNA.
Once at the site, the Cas9 nicks one strand of the double helix. Then, reverse transcriptase uses one DNA strand to “prime,” or initiate, the letter-by-letter transfer of new genetic information encoded in the pegRNA into the nicked spot, much like the search-and-replace function of word processing software. The process is then wrapped up when the prime editing system prompts the cell to remake the other DNA strand to match the new genetic information.
So far, in tests involving human cells grown in a lab dish, Liu and his colleagues have used prime editing to correct the most common mutation that causes SCD, converting a T to an A. They were also able to remove four DNA letters to correct the most common mutation underlying Tay-Sachs disease, a devastating condition that typically produces symptoms in children within the first year and leads to death by age four. The researchers also used their new system to insert new DNA segments up to 44 letters long and to remove segments at least 80 letters long.
Prime editing does have certain limitations. For example, 11 percent of known disease-causing variants result from changes in the number of gene copies, and it’s unclear if prime editing can insert or remove DNA that’s the size of full-length genes—which may contain up to 2.4 million letters.
It’s also worth noting that now-standard CRISPR editing and base editors have been tested far more thoroughly than prime editing in many different kinds of cells and animal models. These earlier editing technologies also may be more efficient for some purposes, so they will likely continue to play unique and useful roles in biomedicine.
As for prime editing, additional research is needed before we can consider launching human clinical trials. Among the areas that must be explored are this technology’s safety and efficacy in a wide range of cell types, and its potential for precisely and safely editing genes in targeted tissues within living animals and people.
Meanwhile, building on all these bold advances, efforts are already underway to accelerate the development of affordable, accessible gene-based cures for SCD and HIV on a global scale. Just last month, NIH and the Bill & Melinda Gates Foundation announced a collaboration that will invest at least $200 million over the next four years toward this goal. Last week, I had the chance to present this plan and discuss it with global health experts at the Grand Challenges meeting Addis Ababa, Ethiopia. The project is an unprecedented partnership designed to meet an unprecedented opportunity to address health conditions that once seemed out of reach but—as this new work helps to show—may now be within our grasp.
 Search-and-replace genome editing without double-strand breaks or donor DNA. Anzalone AV, Randolph PB, Davis JR, Sousa AA, Koblan LW, Levy JM, Chen PJ, Wilson C, Newby GA, Raguram A, Liu DR. Nature. Online 2019 October 21. [Epub ahead of print]
 Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Komor AC, Kim YB, Packer MS, Zuris JA, Liu DR. Nature. 2016 May 19;533(7603):420-424.
 Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Gaudelli NM, Komor AC, Rees HA, Packer MS, Badran AH, Bryson DI, Liu DR. Nature. 2017 Nov 23;551(7681):464-471.
Tay-Sachs Disease (Genetics Home Reference/National Library of Medicine/NIH)
Sickle Cell Disease (National Heart, Lung, and Blood Institute/NIH)
Cure Sickle Cell Initiative (NHLBI)
What are Genome Editing and CRISPR-Cas9? (National Library of Medicine/NIH)
Somatic Cell Genome Editing Program (Common Fund/NIH)
David R. Liu (Harvard, Cambridge, MA)
NIH Support: National Institute of Allergy and Infectious Diseases; National Human Genome Research Institute; National Institute for General Medical Sciences; National Institute of Biomedical Imaging and Bioengineering; National Center for Advancing Translational Sciences
Posted on by Dr. Francis Collins
You might recall learning in biology class that the cells constantly replicating and dividing in our bodies all carry the same DNA, inherited in equal parts from each parent. But it’s become increasingly clear in recent years that even seemingly healthy tissues contain neighborhoods of cells bearing their own acquired genetic mutations. The question is: What do all those altered cells mean for our health?
With support from a 2018 NIH Director’s New Innovator Award, Po-Ru Loh, Harvard Medical School, Boston, is on a quest to find out, though without the need for sequencing lots of DNA in his own lab. Loh will instead develop ultrasensitive computational tools to pick up on those often-subtle alterations within the vast troves of genomic data already stored in databases around the world.
How is that possible? The math behind it might be complex, but the underlying idea is surprisingly simple. His algorithms look for spots in the genome where a slight imbalance exists in the quantity of DNA inherited from mom versus dad.
Actually, Loh can’t tell from the data which parent provided any snippet of chromosomal DNA. But looking at DNA sequenced from a mixture of many cells, he can infer which stretches of DNA were most likely inherited together from a single parent.
Any slight skew in those quantities point the way to genomic territory where a tiny portion of chromosomal DNA either went missing or became duplicated in some cells. This common occurrence, especially in older adults, leads to a condition called genetic mosaicism, meaning that, contrary to most biology textbooks, all cells aren’t exactly the same.
By detecting those subtle imbalances in the data, Loh can pinpoint small DNA alterations, even when they occur in 1 in 1,000 cells collected from a person’s bloodstream, saliva, or tissues. That’s the kind of sensitivity that most scientists would not have thought possible.
Loh has already begun putting his new computational approach to work, as reported in Nature last year . In DNA data from blood samples of more than 150,000 participants in the United Kingdom Biobank, his method uncovered well over 8,000 mosaic chromosomal alterations.
The study showed that some of those alterations were associated with an increased risk of developing blood cancers. However, it’s important to note that most people with evidence of mosaicism won’t go on to develop cancer. The researchers also made the unexpected discovery that some individuals carried genetic variants that made them more prone than others to pick up new mutations in their blood cells.
What’s especially exciting is Loh’s computational tools now make it possible to search for signs of mosaicism within all the genetic data that’s ever been generated. Even more importantly, these tools will allow Loh and other researchers to ask and answer important questions about the consequences of mosaicism for a wide range of diseases.
 Insights into clonal haematopoiesis from 8,342 mosaic chromosomal alterations. Loh PR, Genovese G, Handsaker RE, Finucane HK, Reshef YA, Palamara PF, Birmann BM, Talkowski ME, Bakhoum SF, McCarroll SA, Price AL. Nature. 2018 Jul;559(7714):350-355.
Loh Lab (Harvard Medical School, Boston)
Loh Project Information (NIH RePORTER)
NIH Director’s New Innovator Award (Common Fund)
NIH Support: Common Fund; National Institute of Environmental Health Sciences
Posted on by Dr. Francis Collins
The standard view of biology is that every normal cell copies its DNA instruction book with complete accuracy every time it divides. And thus, with a few exceptions like the immune system, cells in normal, healthy tissue continue to contain exactly the same genome sequence as was present in the initial single-cell embryo that gave rise to that individual. But new evidence suggests it may be time to revise that view.
By analyzing genetic information collected throughout the bodies of nearly 500 different individuals, researchers discovered that almost all had some seemingly healthy tissue that contained pockets of cells bearing particular genetic mutations. Some even harbored mutations in genes linked to cancer. The findings suggest that nearly all of us are walking around with genetic mutations within various parts of our bodies that, under certain circumstances, may have the potential to give rise to cancer or other health conditions.
Efforts such as NIH’s The Cancer Genome Atlas (TCGA) have extensively characterized the many molecular and genomic alterations underlying various types of cancer. But it has remained difficult to pinpoint the precise sequence of events that lead to cancer, and there are hints that so-called normal tissues, including blood and skin, might contain a surprising number of mutations —perhaps starting down a path that would eventually lead to trouble.
In the study published in Science, a team from the Broad Institute at MIT and Harvard, led by Gad Getz and postdoctoral fellow Keren Yizhak, along with colleagues from Massachusetts General Hospital, decided to take a closer look. They turned their attention to the NIH’s Genotype-Tissue Expression (GTEx) project.
The GTEx is a comprehensive public resource that shows how genes are expressed and controlled differently in various tissues throughout the body. To capture those important differences, GTEx researchers analyzed messenger RNA sequences within thousands of healthy tissue samples collected from people who died of causes other than cancer.
Getz, Yizhak, and colleagues wanted to use that extensive RNA data in another way: to detect mutations that had arisen in the DNA genomes of cells within those tissues. To do it, they devised a method for comparing those tissue-derived RNA samples to the matched normal DNA. They call the new method RNA-MuTect.
All told, the researchers analyzed RNA sequences from 29 tissues, including heart, stomach, pancreas, and fat, and matched DNA from 488 individuals in the GTEx database. Those analyses showed that the vast majority of people—a whopping 95 percent—had one or more tissues with pockets of cells carrying new genetic mutations.
While many of those genetic mutations are most likely harmless, some have known links to cancer. The data show that genetic mutations arise most often in the skin, esophagus, and lung tissues. This suggests that exposure to environmental elements—such as air pollution in the lung, carcinogenic dietary substances in the esophagus, or the ultraviolet radiation in sunlight that hits the skin—may play important roles in causing genetic mutations in different parts of the body.
The findings clearly show that, even within normal tissues, the DNA in the cells of our bodies isn’t perfectly identical. Rather, mutations constantly arise, and that makes our cells more of a mosaic of different mutational events. Sometimes those altered cells may have a subtle growth advantage, and thus continue dividing to form larger groups of cells with slightly changed genomic profiles. In other cases, those altered cells may remain in small numbers or perhaps even disappear.
It’s not yet clear to what extent such pockets of altered cells may put people at greater risk for developing cancer down the road. But the presence of these genetic mutations does have potentially important implications for early cancer detection. For instance, it may be difficult to distinguish mutations that are truly red flags for cancer from those that are harmless and part of a new idea of what’s “normal.”
To further explore such questions, it will be useful to study the evolution of normal mutations in healthy human tissues over time. It’s worth noting that so far, the researchers have only detected these mutations in large populations of cells. As the technology advances, it will be interesting to explore such questions at the higher resolution of single cells.
Getz’s team will continue to pursue such questions, in part via participation in the recently launched NIH Pre-Cancer Atlas. It is designed to explore and characterize pre-malignant human tumors comprehensively. While considerable progress has been made in studying cancer and other chronic diseases, it’s clear we still have much to learn about the origins and development of illness to build better tools for early detection and control.
 RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues. Yizhak K, Aguet F, Kim J, Hess JM, Kübler K, Grimsby J, Frazer R, Zhang H, Haradhvala NJ, Rosebrock D, Livitz D, Li X, Arich-Landkof E, Shoresh N, Stewart C, Segrè AV, Branton PA, Polak P, Ardlie KG, Getz G. Science. 2019 Jun 7;364(6444).
The Cancer Genome Atlas (National Cancer Institute/NIH)
Pre-Cancer Atlas (National Cancer Institute/NIH)
Getz Lab (Broad Institute, Cambridge, MA)
NIH Support: Common Fund; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; National Institute of Mental Health; National Cancer Institute; National Library of Medicine; National Institute on Drug Abuse; National Institute of Neurological Diseases and Stroke