genomics
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
The Amazing Brain: Tracking Molecular Events with Calling Cards
Posted on by Dr. Francis Collins
In days mostly gone by, it was fashionable in some circles for people to hand out calling cards to mark their arrival at special social events. This genteel human tradition is now being adapted to the lab to allow certain benign viruses to issue their own high-tech calling cards and mark their arrival at precise locations in the genome. These special locations show where there’s activity involving transcription factors, specialized proteins that switch genes on and off and help determine cell fate.
The idea is that myriad, well-placed calling cards can track brain development over time in mice and detect changes in transcription factor activity associated with certain neuropsychiatric disorders. This colorful image, which won first place in this year’s Show Us Your BRAINs! Photo and Video contest, provides a striking display of these calling cards in action in living brain tissue.
The image comes from Allen Yen, a PhD candidate in the lab of Joseph Dougherty, collaborating with the nearby lab of Rob Mitra. Both labs are located in the Washington University School of Medicine, St. Louis.
Yen and colleagues zoomed in on this section of mouse brain tissue under a microscope to capture dozens of detailed images that they then stitched together to create this high-resolution overview. The image shows neural cells (red) and cell nuclei (blue). But focus in on the neural cells (green) concentrated in the brain’s outer cortex (top) and hippocampus (two lobes in the upper center). They’ve been labelled with calling cards that were dropped off by adeno-associated virus [1].
Once dropped off, a calling card doesn’t bear a pretentious name or title. Rather, the calling card, is a small mobile snippet of DNA called a transposon. It gets dropped off with the other essential component of the technology: a specialized enzyme called a transposase, which the researchers fuse to one of many specific transcription factors of interest.
Each time one of these transcription factors of interest binds DNA to help turn a gene on or off, the attached transposase “grabs” a transposon calling card and inserts it into the genome. As a result, it leaves behind a permanent record of the interaction.
What’s also nice is the calling cards are programmed to give away their general locations. That’s because they encode a fluorescent marker (in this image, it’s a green fluorescent protein). In fact, Yen and colleagues could look under a microscope and tell from all the green that their calling card technology was in place and working as intended.
The final step, though, was to find out precisely where in the genome those calling cards had been left. For this, the researchers used next-generation sequencing to produce a cumulative history and map of each and every calling card dropped off in the genome.
These comprehensive maps allow them to identify important DNA-protein binding events well after the fact. This innovative technology also enables scientists to attribute past molecular interactions with observable developmental outcomes in a way that isn’t otherwise possible.
While the Mitra and Dougherty labs continue to improve upon this technology, it’s already readily adaptable to answer many important questions about the brain and brain disorders. In fact, Yen is now applying the technology to study neurodevelopment in mouse models of neuropsychiatric disorders, specifically autism spectrum disorder (ASD) [2]. This calling card technology also is available for any lab to deploy for studying a transcription factor of interest.
This research is supported by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. One of the major goals of BRAIN Initiative is to accelerate the development and application of innovative technologies to gain new understanding of the brain. This award-winning image is certainly a prime example of striving to meet this goal. I’ll look forward to what these calling cards will tell us in the future about ASD and other important neurodevelopmental conditions affecting the brain.
References:
[1] A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues. Cammack AJ, Moudgil A, Chen J, Vasek MJ, Shabsovich M, McCullough K, Yen A, Lagunas T, Maloney SE, He J, Chen X, Hooda M, Wilkinson MN, Miller TM, Mitra RD, Dougherty JD. Proc Natl Acad Sci U S A. 2020 May 5;117(18):10003-10014.
[2] A MYT1L Syndrome mouse model recapitulates patient phenotypes and reveals altered brain development due to disrupted neuronal maturation. Jiayang Chen, Mary E. Lambo, Xia Ge, Joshua T. Dearborn, Yating Liu, Katherine B. McCullough, Raylynn G. Swift, Dora R. Tabachnick, Lucy Tian, Kevin Noguchi, Joel R. Garbow, John N. Constantino. bioRxiv. May 27, 2021.
Links:
Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Autism Spectrum Disorder (National Institute of Mental Health/NIH)
Dougherty Lab (Washington University School of Medicine, St. Louis)
Mitra Lab (Washington University School of Medicine)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Institute of General Medical Sciences
More Genetic Clues to COVID-19 Susceptibility and Severity
Posted on by Dr. Francis Collins
Many factors influence our risk of illness from SARS-CoV-2, the coronavirus responsible for COVID-19. That includes being careful to limit our possible exposures to the virus, as well as whether we have acquired immunity from a vaccine or an earlier infection. But once a person is infected, a host of other biological factors, including age and pre-existing medical conditions, will influence one’s risk of becoming severely ill.
While earlier studies have tied COVID-19 severity to genetic variations in a person’s antiviral defenses and blood type, we still have a lot to learn about how a person’s genetic makeup influences COVID-19 susceptibility and severity. So, I was pleased to see the recent findings of an impressive global effort to map the genetic underpinnings of SARS-CoV-2 infection and COVID-19 severity, which involved analyzing the genomes of many thousands of people with COVID-19 around the globe.
This comprehensive search led to the identification of 13 regions of the human genome that appear to play a role in COVID-19 infection or severity. Though more research is needed to sort out these leads, they represent potentially high-quality clues to the pathways that this virus uses to cause illness, and help to explain why some people are more likely to become infected with SARS-CoV-2 or to develop severe disease.
The international effort, known as The COVID-19 Host Genetics Initiative, is led by Andrea Ganna, Institute for Molecular Medicine Finland, Helsinki, and colleagues in the United States and around the world. Teasing out those important genetic influences is no easy task. It requires vast amounts of data, so Ganna reached out to the scientific community via Twitter to announce a new COVID-19 gene-hunting effort and ask for help. Thousands of researchers around the world answered his call. The new study, published in the journal Nature, includes data collected through the initiative as of January 2021, and represents nearly 50,000 COVID-19 patients and another 2 million uninfected controls [1].
In search of common gene variants that may influence who becomes infected with SARS-CoV-2 and how sick they will become, Ganna’s international team turned to genome-wide association studies (GWAS). As part of this, the team analyzed patient genome data for millions of so-called single-nucleotide polymorphisms, or SNPs. While these single “letter” nucleotide substitutions found all across the genome are generally of no health significance, they can point the way to the locations of gene variants that turn up more often in association with particular traits or conditions—in this case, COVID-19 susceptibility or severity. To find them, the researchers compared SNPs in people with COVID-19 to those in about 2 million healthy blood donors from the same population groups. They also looked for variants that turned up significantly more often in people who became severely ill.
Their analyses uncovered a number of gene variants associated with SARS-CoV-2 infection or severe COVID-19 in 13 regions of the human genome, six of which were new. Four of the 13 affect a person’s risk for becoming infected with SARS-CoV-2. The other nine influence a person’s risk for developing severe illness following the infection.
Interestingly, some of these gene variants already were known to have associations with other types of lung or autoimmune diseases. The new findings also help to confirm previous studies suggesting that the gene that determines a person’s blood type may influence a person’s susceptibility to SARS-CoV-2 infection, along with other genes that play a role in immunity. For example, the findings show overlap with variants within a gene called TYK2, which was earlier shown to protect against autoimmune-related diseases. Some of the variants also point to the need for further work to study previously unexplored biological processes that may play potentially important roles in COVID-19.
Two of the new variants associated with disease severity were discovered only by including individuals with East Asian ancestry, highlighting the value of diversity in such analyses to gain a more comprehensive understanding of the biology. One of these newfound variants is close to a gene known as FOXP4, which is especially intriguing because this gene is known to play a role in the airways of the lung.
The researchers continue to look for more underlying clues into the biology of COVID-19. In fact, their latest unpublished analysis has increased the number of COVID-19 patients from about 50,000 to 125,000, making it possible to add another 10 gene variants to the list.
Reference:
[1] Mapping the human genetic architecture of COVID-19. COVID-19 Host Genetics Initiative. Nature. 2021 Jul 8.
Links:
COVID-19 Research (NIH)
Understanding Neuronal Diversity in the Spinal Cord
Posted on by Dr. Francis Collins
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
Tracking the Evolution of a ‘Variant of Concern’ in Brazil
Posted on by Dr. Francis Collins
By last October, about three out of every four residents of Manaus, Brazil already had been infected with SARS-CoV-2, the virus that causes COVID-19 [1]. And yet, despite hopes of achieving “herd immunity” in this city of 2.2 million in the Amazon region, the virus came roaring back in late 2020 and early 2021 to cause a second wave of illness and death [2]. How is this possible?
The answer offers a lesson in viral evolution, especially when an infectious virus such as SARS-CoV-2 replicates and spreads through a population largely unchecked. In a recent study in the journal Science, researchers tied the city’s resurgence of SARS-CoV-2 to the emergence and rapid spread of a new SARS-CoV-2 “variant of concern” known as P.1 [3]. This variant carries a unique constellation of mutations that allow it not only to sneak past the human immune system and re-infect people, but also to be about twice as transmissible as earlier variants.
To understand how this is possible, consider that each time the coronavirus SARS-CoV-2 makes copies of itself in an infected person, there’s a chance a mistake will be made. Each mistake can produce a new variant that may go on to make more copies of itself. In most cases, those random errors are of little to no consequence. This is evolution in action.
But sometimes a spelling change can occur that benefits the virus. In the special case of patients with suppressed immune systems, the virus can have ample opportunity to accrue an unusually high number of mutations. Variants carrying beneficial mutations can make more copies of themselves than other variants, allowing them to build their numbers and spread to cause more infection.
At this advanced stage of the COVID-19 pandemic, such rapidly spreading new variants remain cause for serious concern. That includes variants such as B.1.351, which originated in South Africa; B.1.1.7 which emerged in the United Kingdom; and now P.1 from Manaus, Brazil.
In the new study, Nuno Faria and Samir Bhatt, Imperial College London, U.K., and Ester Cerdeira Sabino, Universidade de Sao Paulo, Brazil, and their colleagues sequenced SARS-CoV-2 genomes from 184 patient samples collected in Manaus in November and December 2020. The research was conducted under the auspices of the Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology (CADDE), a project focused on viral genomics and epidemiology for public health.
Those genomic data revealed the P.1 variant had acquired 17 new mutations. Ten were in the spike protein, which is the segment of the virus that binds onto human cells and the target of current COVID-19 vaccines. In fact, the new work reveals that three of these spike protein mutations make it easier for the P.1 spike to bind the human ACE2 receptor, which is SARS-CoV-2’s preferred entry point.
The first P.1 variant case was detected by genomic surveillance on December 6, 2020, after which it spread rapidly. Through further evolutionary analysis, the team estimates that P.1 must have emerged, undetected for a brief time, in mid-November 2020.
To understand better how the P.1 variant led to such an explosion of new COVID-19 cases, the researchers developed a mathematical model that integrated the genomic data with mortality data. The model suggests that P.1 may be 1.7 to 2.4 times more transmissible than earlier variants. They also estimate that a person previously infected with a variant other than P.1 will have only 54 percent to 79 percent protection against a subsequent infection with P.1.
The researchers also observed an increase in mortality following the emergence of the P.1 variant. However, it’s not yet clear if that’s an indication P.1 is inherently more deadly than earlier variants. It’s possible the increased mortality is related primarily to the extra stress on the healthcare system in Manaus from treating so many people with COVID-19.
These findings are yet another reminder of the importance of genomic surveillance and international data sharing for detecting and characterizing emerging SARS-CoV-2 variants quickly. It’s worth noting that at about the same time this variant was detected in Brazil, it also was reported in four individuals who had traveled to Brazil from Japan. The P.1 variant continues to spread rapidly across Brazil. It has also been detected in more than 37 countries [4], including the United States, where it now accounts for more than 1 percent of new cases [5].
No doubt you are wondering what this means for vaccines, such as the Pfizer and Moderna mRNA vaccines, that have been used to immunize (at least one dose) over 140 million people in the United States. Here the news is encouraging. Serum from individuals who received the Pfizer vaccine had titers of neutralizing antibodies that were only slightly reduced for P.1 compared to the original SARS-CoV-2 virus [6]. Therefore, the vaccine is predicted to be highly protective. This is another example of a vaccine providing more protection than a natural infection.
The United States has made truly remarkable progress in combating COVID-19, but we must heed this lesson from Manaus: this terrible pandemic isn’t over just yet. While the P.1 variant remains at low levels here for now, the “U.K. variant” B.1.1.7 continues to spread rapidly and now is the most prevalent variant circulating in the U.S., accounting for 44 percent of new cases [6]. Fortunately, the mRNA vaccines also work well against B.1.1.7.
We must continue to do absolutely everything possible, individually and collectively, to prevent these new SARS-CoV-2 variants from slowing or even canceling the progress made over the last year. We need to remain vigilant for just a while longer, while encouraging our friends, neighbors, and loved ones to get vaccinated.
References:
[1] Three-quarters attack rate of SARS-CoV-2 in the Brazilian Amazon during a largely unmitigated epidemic. Buss, L. F., C. A. Prete, Jr., C. M. M. Abrahim, A. C. Dye, V. H. Nascimento, N. R. Faria and E. C. Sabino et al. (2021). Science 371(6526): 288-292.
[2] Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence. Sabino EC, Buss LF, Carvalho MPS, Prete Jr CCA, Crispim MAE, Fraiji NA, Pereira RHM, Paraga KV, Peixoto PS, Kraemer MUG, Oikawa MJ, Salomon T, Cucunuba ZM, Castro MC, Santos AAAS, Nascimento VH, Pereira HS, Ferguson NM, Pybus OG, Kucharski A, Busch MP, Dye C, Faria NR Lancet. 2021 Feb 6;397(10273):452-455.
[3] Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil. Faria NR, Mellan TA, Whittaker C, Claro IM, Fraiji NA, Carvalho MDPSS, Pybus OG, Flaxman S, Bhatt S, Sabino EC et al. Science. 2021 Apr 14:eabh2644.
[4] GRINCH Global Report Investigating novel coronavirus haplotypes. PANGO Lineages.
[5] COVID Data Tracker. Variant Proportions. Centers for Disease Control and Prevention.
[6] Antibody evasion by the P.1 strain of SARS-CoV-2. Dejnirattisai W, Zhou D, Supasa P, Liu C, Mongkolsapaya J, Ren J, Stuart DI, Screaton GR, et al. Cell. 2021 Mar 30:S0092-8674(21)00428-1.
Links:
COVID-19 Research (NIH)
Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology (CADDE)
Nuno Faria (Imperial College, London, U.K.)
Samir Bhatt (Imperial College)
Ester Cerdeira Sabino (Universidade de Sao Paulo, Brazil)
NIH Support: National Institute of Allergy and Infectious Diseases
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