Skip to main content

genomics

A New View of the 3D Genome

Posted on by

Caption: 3D model of a chromatin “forest.” Each sphere represents a tree-shaped domain of about 10 nucleosomes, the basic structural unit of DNA packaging. Larger domains are green; smaller ones are red. Credit: Northwestern University, Evanston, IL

 

This lush panoply of color might stir up daydreams of getting away to explore a tropical rain forest. But what you see here is a new model that’s enabling researchers to explore something equally amazing: how a string of DNA that measures 6 feet long can be packed into the microscopic nucleus of a human cell. Fitting that much DNA in a nucleus is like fitting a thread the length of the Empire State building underneath your fingernail!

Scientists have known for a while that that the answer lies in how DNA is folded onto spool-like complexes called chromatin, but many details of the process still remain to be worked out. Recently, an NIH-funded team, led by Vadim Backman and Igal Szleifer, Northwestern University, Evanston, IL, developed this new model of chromatin folding by pairing sophisticated mathematical modeling and optical imaging.In a study published in the journal Science Advances [1], the team found that chromatin is folded into a variety of tree-like domains along a chromatin backbone, which they liken to an aggregation of trees growing from the forest floor. The colorful spheres you see above represent trees of varying sizes.

Earlier models of chromatin folding had suggested that DNA folds into regular and orderly fibers. In the new study, the Northwestern researchers used their own specially designed Partial Wave Spectroscopic microscope. This high-powered system, coupled with electron imaging, allowed them to peer deep inside living cells to “sense” real-time alterations in chromatin packing. What makes their new view on chromatin so interesting is it suggests our DNA is packaged in a way that’s much more disorderly and unpredictable than initially thought.

Chromatin Forest
Caption: Schematic shows the interplay between transcription and chromatin packing. Inactive high DNA density (blue) regions and active low DNA density (red). The horizontal chromatin backbone includes RNA polymerase (green), activating factors (yellow), and repressing factors (purple). Credit: Huang et al., Sci. Adv. 2020

As Backman notes, it is reasonable to assume that a forest would be filled with trees of varying sizes and shapes. But you couldn’t predict the exact location of each tree or its particular size and configuration. The same appears to be true of these tree-like structures within chromatin. Their precise location and size vary, seemingly unpredictably, from cell to cell.

This apparently random DNA packing structure might seem surprising given chromatin’s importance in influencing the expression and function of our genes. But the researchers think such variability likely has its advantages.

Here’s the idea: If all of our cells responded to stressful conditions (such as heat or a toxic exposure) in exactly the same way and that way happened to be suboptimal, the whole tissue or organ might fail. But if differences in chromatin structure lead each cell to respond somewhat differently to the same stimulus, then some cells might be more likely to survive or even thrive under the stress. It’s a built-in way for cells to hedge their bets.

These new findings offer a fundamentally new three-dimensional view of the human genome. They might also inspire innovative strategies to understand and fight cancer, as well as other diseases. And, while most of us probably won’t be venturing off into the rain forest anytime soon, this work does give us all something to think about next time we’re enjoying the great outdoors in our own neck of the woods. 

Reference:

[1] Physical and data structure of 3D genome. Huang K, Li Y, Shim AR, Virk RKA, Agrawal V, Eshein A, Nap RJ, Almassalha LM, Backman V, Szleifer I. Sci Adv. 2020 Jan 10;6(2):eaay4055.

Links:

Deoxyribonucleic Acid (DNA) (National Human Genome Research Institute/NIH)

4D Nucleome (Common Fund/NIH)

Vadim Backman (Northwestern University, Evanston, IL)

Igal Szleifer (Northwestern University, Evanston, IL)

NIH Support: National Cancer Institute


Genome Data Help Track Community Spread of COVID-19

Posted on by

RNA Virus
Credit: iStock/vchal

Contact tracing, a term that’s been in the news lately, is a crucial tool for controlling the spread of SARS-CoV-2, the novel coronavirus that causes COVID-19. It depends on quick, efficient identification of an infected individual, followed by identification of all who’ve recently been in close contact with that person so the contacts can self-quarantine to break the chain of transmission.

Properly carried out, contact tracing can be extremely effective. It can also be extremely challenging when battling a stealth virus like SARS-CoV-2, especially when the virus is spreading rapidly.

But there are some innovative ways to enhance contact tracing. In a new study, published in the journal Nature Medicine, researchers in Australia demonstrate one of them: assembling genomic data about the virus to assist contact tracing efforts. This so-called genomic surveillance builds on the idea that when the virus is passed from person to person over a few months, it can acquire random variations in the sequence of its genetic material. These unique variations serve as distinctive genomic “fingerprints.”

When COVID-19 starts circulating in a community, researchers can fingerprint the genomes of SARS-CoV-2 obtained from newly infected people. This timely information helps to tell whether that particular virus has been spreading locally for a while or has just arrived from another part of the world. It can also show where the viral subtype has been spreading through a community or, best of all, when it has stopped circulating.

The recent study was led by Vitali Sintchenko at the University of Sydney. His team worked in parallel with contact tracers at the Ministry of Health in New South Wales (NSW), Australia’s most populous state, to contain the initial SARS-CoV-2 outbreak from late January through March 2020.

The team performed genomic surveillance, using sequencing data obtained within about five days, to understand local transmission patterns. They also wanted to compare what they learned from genomic surveillance to predictions made by a sophisticated computer model of how the virus might spread amongst Australia’s approximately 24 million citizens.

Of the 1,617 known cases in Sydney over the three-month study period, researchers sequenced viral genomes from 209 (13 percent) of them. By comparing those sequences to others circulating overseas, they found a lot of sequence diversity, indicating that the novel coronavirus had been introduced to Sydney many times from many places all over the world.

They then used the sequencing data to better understand how the virus was spreading through the local community. Their analysis found that the 209 cases under study included 27 distinct genomic fingerprints. Based on the close similarity of their genomic fingerprints, a significant share of the COVID-19 cases appeared to have stemmed from the direct spread of the virus among people in specific places or facilities.

What was most striking was that the genomic evidence helped to provide information that contact tracers otherwise would have lacked. For instance, the genomic data allowed the researchers to identify previously unsuspected links between certain cases of COVID-19. It also helped to confirm other links that were otherwise unclear.

All told, researchers used the genomic evidence to cluster almost 40 percent of COVID-19 cases (81 of 209) for which the community-based data alone couldn’t identify a known contact source for the infection. That included 26 cases in which an individual who’d recently arrived in Australia from overseas spread the infection to others who hadn’t traveled. The genomic information also helped to identify likely sources in the community for another 15 locally acquired cases that weren’t known based on community data.

The researchers compared their genome surveillance data to SARS-CoV-2’s expected spread as modeled in a computer simulation based on travel to and from Australia over the time period in question. Because the study involved just 13 percent of all known COVID-19 cases in Sydney between late January through March, it’s not surprising that the genomic data presents an incomplete picture, detecting only a portion of the possible chains of transmission expected in the simulation model.

Nevertheless, the findings demonstrate the value of genomic data for tracking the virus and pinpointing exactly where in the community it is spreading. This can help to fill in important gaps in the community-based data that contact tracers often use. Even more exciting, by combining traditional contact tracing, genomic surveillance, and mathematical modeling with other emerging tools at our disposal, it may be possible to get a clearer picture of the movement of SARS-CoV-2 and put more targeted public health measures in place to slow and eventually stop its deadly spread.

Reference:

[1] Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling. Rockett RJ, Arnott A, Lam C, et al. Nat Med. 2020 July 9. [Published online ahead of print]

Links:

Coronavirus (COVID-19) (NIH)

Vitali Sintchenko (University of Sydney, Australia)


Genes, Blood Type Tied to Risk of Severe COVID-19

Posted on by

SARS-CoV-2 virus particles
Caption: Micrograph of SARS-CoV-2 virus particles isolated from a patient.
Credit: National Institute of Allergy and Infectious Diseases, NIH

Many people who contract COVID-19 have only a mild illness, or sometimes no symptoms at all. But others develop respiratory failure that requires oxygen support or even a ventilator to help them recover [1]. It’s clear that this happens more often in men than in women, as well as in people who are older or who have chronic health conditions. But why does respiratory failure also sometimes occur in people who are young and seemingly healthy?

A new study suggests that part of the answer to this question may be found in the genes that each one of us carries [2]. While more research is needed to pinpoint the precise underlying genes and mechanisms responsible, a recent genome-wide association (GWAS) study, just published in the New England Journal of Medicine, finds that gene variants in two regions of the human genome are associated with severe COVID-19 and correspondingly carry a greater risk of COVID-19-related death.

The two stretches of DNA implicated as harboring risks for severe COVID-19 are known to carry some intriguing genes, including one that determines blood type and others that play various roles in the immune system. In fact, the findings suggest that people with blood type A face a 50 percent greater risk of needing oxygen support or a ventilator should they become infected with the novel coronavirus. In contrast, people with blood type O appear to have about a 50 percent reduced risk of severe COVID-19.

These new findings—the first to identify statistically significant susceptibility genes for the severity of COVID-19—come from a large research effort led by Andre Franke, a scientist at Christian-Albrecht-University, Kiel, Germany, along with Tom Karlsen, Oslo University Hospital Rikshospitalet, Norway. Their study included 1,980 people undergoing treatment for severe COVID-19 and respiratory failure at seven medical centers in Italy and Spain.

In search of gene variants that might play a role in the severe illness, the team analyzed patient genome data for more than 8.5 million so-called single-nucleotide polymorphisms, or SNPs. The vast majority of these single “letter” nucleotide substitutions found all across the genome are of no health significance, but they can help to pinpoint the locations of gene variants that turn up more often in association with particular traits or conditions—in this case, COVID-19-related respiratory failure. To find them, the researchers compared SNPs in people with severe COVID-19 to those in more than 1,200 healthy blood donors from the same population groups.

The analysis identified two places that turned up significantly more often in the individuals with severe COVID-19 than in the healthy folks. One of them is found on chromosome 3 and covers a cluster of six genes with potentially relevant functions. For instance, this portion of the genome encodes a transporter protein known to interact with angiotensin converting enzyme 2 (ACE2), the surface receptor that allows the novel coronavirus that causes COVID-19, SARS-CoV-2, to bind to and infect human cells. It also encodes a collection of chemokine receptors, which play a role in the immune response in the airways of our lungs.

The other association signal popped up on chromosome 9, right over the area of the genome that determines blood type. Whether you are classified as an A, B, AB, or O blood type, depends on how your genes instruct your blood cells to produce (or not produce) a certain set of proteins. The researchers did find evidence suggesting a relationship between blood type and COVID-19 risk. They noted that this area also includes a genetic variant associated with increased levels of interleukin-6, which plays a role in inflammation and may have implications for COVID-19 as well.

These findings, completed in two months under very difficult clinical conditions, clearly warrant further study to understand the implications more fully. Indeed, Franke, Karlsen, and many of their colleagues are part of the COVID-19 Host Genetics Initiative, an ongoing international collaborative effort to learn the genetic determinants of COVID-19 susceptibility, severity, and outcomes. Some NIH research groups are taking part in the initiative, and they recently launched a study to look for informative gene variants in 5,000 COVID-19 patients in the United States and Canada.

The hope is that these and other findings yet to come will point the way to a more thorough understanding of the biology of COVID-19. They also suggest that a genetic test and a person’s blood type might provide useful tools for identifying those who may be at greater risk of serious illness.

References:

[1] Characteristics of and important lessons from the Coronavirus Disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. Wu Z, McGoogan JM, et. al. 2020 Feb 24. [published online ahead of print]

[2] Genomewide association study of severe Covid-19 with respiratory failure. Ellinghaus D, Degenhardt F, et. a. NEJM. June 17, 2020.

Links:

The COVID-19 Host Genetics Initiative

Andre Franke (Christian-Albrechts-University of Kiel, Germany)

Tom Karlsen (Oslo University Hospital Rikshospitalet, Norway)


The Prime Cellular Targets for the Novel Coronavirus

Posted on by

Credit: NIH

There’s still a lot to learn about SARS-CoV-2, the novel coronavirus that causes COVID-19. But it has been remarkable and gratifying to watch researchers from around the world pull together and share their time, expertise, and hard-earned data in the urgent quest to control this devastating virus.

That collaborative spirit was on full display in a recent study that characterized the specific human cells that SARS-CoV-2 likely singles out for infection [1]. This information can now be used to study precisely how each cell type interacts with the virus. It might ultimately help to explain why some people are more susceptible to SARS-CoV-2 than others, and how exactly to target the virus with drugs, immunotherapies, and vaccines to prevent or treat infections.

This work was driven by the mostly shuttered labs of Alex K. Shalek, Massachusetts Institute of Technology, Ragon Institute of MGH, MIT, and Harvard, and Broad Institute of MIT and Harvard, Cambridge; and Jose Ordovas-Montanes at Boston Children’s Hospital. In the end, it brought together (if only remotely) dozens of their colleagues in the Human Cell Atlas Lung Biological Network and others across the U.S., Europe, and South Africa.

The project began when Shalek, Ordovas-Montanes, and others read that before infecting human cells, SARS-CoV-2 docks on a protein receptor called angiotensin-converting enzyme 2 (ACE2). This enzyme plays a role in helping the body maintain blood pressure and fluid balance.

The group was intrigued, especially when they also learned about a second enzyme that the virus uses to enter cells. This enzyme goes by the long acronym TMPRSS2, and it gets “tricked” into priming the spike proteins that cover SARS-CoV-2 to attack the cell. It’s the combination of these two proteins that provide a welcome mat for the virus.

Shalek, Ordovas-Montanes, and an international team including graduate students, post-docs, staff scientists, and principal investigators decided to dig a little deeper to find out precisely where in the body one finds cells that express this gene combination. Their curiosity took them to the wealth of data they and others had generated from model organisms and humans, the latter as part of the Human Cell Atlas. This collaborative international project is producing a comprehensive reference map of all human cells. For its first draft, the Human Cell Atlas aims to gather information on at least 10 billion cells.

To gather this information, the project relies, in part, on relatively new capabilities in sequencing the RNA of individual cells. Keep in mind that every cell in the body has essentially the same DNA genome. But different cells use different programs to decide which genes to turn on—expressing those as RNA molecules that can be translated into protein. The single-cell analysis of RNA allows them to characterize the gene expression and activities within each and every unique cell type. Based on what was known about the virus and the symptoms of COVID-19, the team focused their attention on the hundreds of cell types they identified in the lungs, nasal passages, and intestines.

As reported in Cell, by filtering through the data to identify cells that express ACE2 and TMPRSS2, the researchers narrowed the list of cell types in the nasal passages down to the mucus-producing goblet secretory cells. In the lung, evidence for activity of these two genes turned up in cells called type II pneumocytes, which line small air sacs known as alveoli and help to keep them open. In the intestine, it was the absorptive enterocytes, which play an important role in the body’s ability to take in nutrients.

The data also turned up another unexpected and potentially important connection. In these cells of interest, all of which are found in epithelial tissues that cover or line body surfaces, the ACE2 gene appeared to ramp up its activity in concert with other genes known to respond to interferon, a protein that the body makes in response to viral infections.

To dig further in the lab, the researchers treated cultured cells that line airways in the lungs with interferon. And indeed, the treatment increased ACE2 expression.

Earlier studies have suggested that ACE2 helps the lungs to tolerate damage. Completely missed was its connection to the interferon response. The researchers now suspect that’s because it hadn’t been studied in these specific human epithelial cells before.

The discovery suggests that SARS-CoV-2 and potentially other coronaviruses that rely on ACE2 may take advantage of the immune system’s natural defenses. When the body responds to the infection by producing more interferon, that in turn results in production of more ACE2, enhancing the ability of the virus to attach more readily to lung cells. While much more work is needed, the finding indicates that any potential use of interferon as a treatment to fight COVID-19 will require careful monitoring to determine if and when it might help patients.

It’s clear that these new findings, from data that weren’t originally generated with COVID-19 in mind, contained several potentially important new leads. This is another demonstration of the value of basic science. We can also rest assured that, with the outpouring of effort from members of the scientific community around the globe to meet this new challenge, progress along these and many other fronts will continue at a remarkable pace.

Reference:

[1] SARS-CoV-2 receptor ACE2 is an interferon-stimulated gene in human airway epithelial cells and is detected in specific cell subsets across tissues. Ziegler, CGK et al. Cell. April 20, 2020.

Links:

Coronaviruses (National Institute of Allergy and Infectious Diseases/NIH)

Human Cell Atlas (Broad Institute, Cambridge, MA)

Shalek Lab (Harvard Medical School and Massachusetts Institute of Technology, Cambridge)

Ordovas-Montanes Lab (Boston Children’s Hospital, MA)

NIH Support: National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute


Genomic Study Points to Natural Origin of COVID-19

Posted on by

COVID-19 Update

No matter where you go online these days, there’s bound to be discussion of coronavirus disease 2019 (COVID-19). Some folks are even making outrageous claims that the new coronavirus causing the pandemic was engineered in a lab and deliberately released to make people sick. A new study debunks such claims by providing scientific evidence that this novel coronavirus arose naturally.

The reassuring findings are the result of genomic analyses conducted by an international research team, partly supported by NIH. In their study in the journal Nature Medicine, Kristian Andersen, Scripps Research Institute, La Jolla, CA; Robert Garry, Tulane University School of Medicine, New Orleans; and their colleagues used sophisticated bioinformatic tools to compare publicly available genomic data from several coronaviruses, including the new one that causes COVID-19.

The researchers began by homing in on the parts of the coronavirus genomes that encode the spike proteins that give this family of viruses their distinctive crown-like appearance. (By the way, “corona” is Latin for “crown.”) All coronaviruses rely on spike proteins to infect other cells. But, over time, each coronavirus has fashioned these proteins a little differently, and the evolutionary clues about these modifications are spelled out in their genomes.

The genomic data of the new coronavirus responsible for COVID-19 show that its spike protein contains some unique adaptations. One of these adaptations provides special ability of this coronavirus to bind to a specific protein on human cells called angiotensin converting enzyme (ACE2). A related coronavirus that causes severe acute respiratory syndrome (SARS) in humans also seeks out ACE2.

Existing computer models predicted that the new coronavirus would not bind to ACE2 as well as the SARS virus. However, to their surprise, the researchers found that the spike protein of the new coronavirus actually bound far better than computer predictions, likely because of natural selection on ACE2 that enabled the virus to take advantage of a previously unidentified alternate binding site. Researchers said this provides strong evidence that that new virus was not the product of purposeful manipulation in a lab. In fact, any bioengineer trying to design a coronavirus that threatened human health probably would never have chosen this particular conformation for a spike protein.

The researchers went on to analyze genomic data related to the overall molecular structure, or backbone, of the new coronavirus. Their analysis showed that the backbone of the new coronavirus’s genome most closely resembles that of a bat coronavirus discovered after the COVID-19 pandemic began. However, the region that binds ACE2 resembles a novel virus found in pangolins, a strange-looking animal sometimes called a scaly anteater. This provides additional evidence that the coronavirus that causes COVID-19 almost certainly originated in nature. If the new coronavirus had been manufactured in a lab, scientists most likely would have used the backbones of coronaviruses already known to cause serious diseases in humans.

So, what is the natural origin of the novel coronavirus responsible for the COVID-19 pandemic? The researchers don’t yet have a precise answer. But they do offer two possible scenarios.

In the first scenario, as the new coronavirus evolved in its natural hosts, possibly bats or pangolins, its spike proteins mutated to bind to molecules similar in structure to the human ACE2 protein, thereby enabling it to infect human cells. This scenario seems to fit other recent outbreaks of coronavirus-caused disease in humans, such as SARS, which arose from cat-like civets; and Middle East respiratory syndrome (MERS), which arose from camels.

The second scenario is that the new coronavirus crossed from animals into humans before it became capable of causing human disease. Then, as a result of gradual evolutionary changes over years or perhaps decades, the virus eventually gained the ability to spread from human-to-human and cause serious, often life-threatening disease.

Either way, this study leaves little room to refute a natural origin for COVID-19. And that’s a good thing because it helps us keep focused on what really matters: observing good hygiene, practicing social distancing, and supporting the efforts of all the dedicated health-care professionals and researchers who are working so hard to address this major public health challenge.

Finally, next time you come across something about COVID-19 online that disturbs or puzzles you, I suggest going to FEMA’s new Coronavirus Rumor Control web site. It may not have all the answers to your questions, but it’s definitely a step in the right direction in helping to distinguish rumors from facts.

Reference:
[1] The proximal origin of SARS-CoV-2. Andersen KG, Rambaut A, Lipkin WI, Holmes EC, Garry RF. Nat Med, 17 March 2020. [Epub ahead of publication]

Links:

Coronavirus (COVID-19) (NIH)

COVID-19, MERS & SARS (National Institute of Allergy and Infectious Diseases/NIH)

Andersen Lab (Scripps Research Institute, La Jolla, CA)

Robert Garry (Tulane University School of Medicine, New Orleans)

Coronavirus Rumor Control (FEMA)

NIH Support: National Institute of Allergy and Infectious Diseases; National Human Genome Research Institute


Previous Page Next Page