A multidimensional view of the coronavirus

 

What exactly happens when the corona virus SARS-CoV-2 infects a cell? In an article published in Nature, a team from the Technical University of Munich (TUM) and the Max Planck Institute of Biochemistry paints a comprehensive picture of the viral infection process. For the first time, the interaction between the coronavirus and a cell is documented at five distinct proteomics levels during viral infection. This knowledge will help to gain a better understanding of the virus and find potential starting points for therapies.

When a virus enters a cell, viral and cellular protein molecules begin to interact. Both the replication of the virus and the reaction of the cells are the result of complex protein signaling cascades. A team led by Andreas Pichlmair, Professor of Immunopathology of Viral Infections at the Institute of Virology at TUM, and Matthias Mann, Head of the Department of Proteomics and Signal Transduction at the Max Planck Institute of Biochemistry, has systematically recorded how human lung cells react to individual proteins of the covid-19 pathogen SARS-CoV-2 and the SARS coronavirus, the latter of which has been known for some time.

A detailed interaction map

To this end, more than 1200 samples were analyzed using the state-of-the-art mass spectrometry techniques and advanced bioinformatic methods. The result is a freely accessible dataset that provides information on which cellular proteins the viral proteins bind to and the effects of these interactions on the cell. In total, 1484 interactions between viral proteins and human cellular proteins were discovered. "Had we only looked at proteins, however, we would have missed out on important information," says Andreas Pichlmair. "A database that only includes the proteome would be like a map containing just the place names but no roads or rivers. If you knew about the connections between the points on that map, you could gain much more useful information."

According to Pichlmair, important counterparts to the network of traffic routes on a map are protein modifications called phosphorylation and ubiquitination. Both are processes in which other molecules are attached to proteins, thereby altering their functions. In a listing of proteins, these changes are not measured, so that there is no way of knowing whether proteins are active or inactive, for example. "Through our investigations, we systematically assign functions to the individual components of the pathogen, in addition to the cellular molecules that are switched off by the virus," explains Pichlmair. "There has been no comparable mapping for SARS-CoV-2 so far," adds Matthias Mann. "In a sense, we have taken a close look at five dimensions of the virus during an infection: its own active proteins and its effects on the host proteome, ubiquitinome, phosphoproteome and transcriptome."

Insights into how the virus works

Among other things, the database can also serve as a tool to find new drugs. By analyzing protein interactions and modifications, vulnerability hotspots of SARS-CoV-2 can be identified. These proteins bind to particularly important partners in cells and could serve as potential starting points for therapies. For example, the scientists concluded that certain compounds would inhibit the growth of SARS-CoV-2. Among them were some whose antiviral function is known, but also some compounds which have not yet been studied for efficacy against SARS-CoV-2. Further studies are needed to determine whether they show efficacy in clinical use against Covid-19.

"Currently, we are working on new anti Covid-19 drug candidates, that we have been able to identify through our analyses," says Andreas Pichlmair. "We are also developing a scoring system for automated identification of hotspots. I am convinced that detailed data sets and advanced analysis methods will enable us to develop effective drugs in a more targeted manner in the future and limit side effects in advance."

 

ournal Reference:

1. Alexey Stukalov, Virginie Girault, Vincent Grass, Ozge Karayel, Valter Bergant, Christian Urban, Darya A. Haas, Yiqi Huang, Lila Oubraham, Anqi Wang, M. Sabri Hamad, Antonio Piras, Fynn M. Hansen, Maria C. Tanzer, Igor Paron, Luca Zinzula, Thomas Enghleitner, Maria Reinecke, Teresa M. Lavacca, Rosina Ehmann, Roman Wölfel, Jörg Jores, Bernhard Kuster, Ulrike Protzer, Roland Rad, John Ziebuhr, Volker Thiel, Pietro Scaturro, Matthias Mann, Andreas Pichlmair. Multilevel proteomics reveals host perturbations by SARS-CoV-2 and SARS-CoV. Nature, 2021; DOI: 10.1038/s41586-021-03493-4 

Courtesy: ScienceDaily

Technical University of Munich (TUM). "A multidimensional view of the coronavirus: COVID-19: Analysis of protein interactions as a route to new drugs." ScienceDaily. ScienceDaily, 12 April 2021. <www.sciencedaily.com/releases/2021/04/210412142727.htm>.

 

How brain cells repair their DNA reveals 'hot spots' of aging and disease

Neurons lack the ability to replicate their DNA, so they're constantly working to repair damage to their genome. Now, a new study by Salk scientists finds that these repairs are not random, but instead focus on protecting certain genetic "hot spots" that appear to play a critical role in neural identity and function.

The findings, published in the April 2, 2021, issue of Science, give novel insights into the genetic structures involved in aging and neurodegeneration, and could point to the development of potential new therapies for diseases such Alzheimer's, Parkinson's and other age-related dementia disorders.

"This research shows for the first time that there are sections of genome that neurons prioritize when it comes to repair," says Professor and Salk President Rusty Gage, the paper's co-corresponding author. "We're excited about the potential of these findings to change the way we view many age-related diseases of the nervous system and potentially explore DNA repair as a therapeutic approach."

Unlike other cells, neurons generally don't replace themselves over time, making them among the longest-living cells in the human body. Their longevity makes it even more important that they repair lesions in their DNA as they age, in order to maintain their function over the decades of a human life span. As they get older, neurons' ability to make these genetic repairs declines, which could explain why people develop age-related neurodegenerative diseases like Alzheimer's and Parkinson's.

To investigate how neurons maintain genome health, the study authors developed a new technique they term Repair-seq. The team produced neurons from stem cells and fed them synthetic nucleosides -- molecules that serve as building blocks for DNA. These artificial nucleosides could be found via DNA sequencing and imaged, showing where the neurons used them to make repairs to DNA that was damaged by normal cellular processes. While the scientists expected to see some prioritization, they were surprised by just how focused the neurons were on protecting certain sections of the genome.

"What we saw was incredibly sharp, well-defined regions of repair; very focused areas that were substantially higher than background levels," says co-first and co-corresponding author Dylan Reid, a former Salk postdoctoral scholar and now a fellow at Vertex Pharmaceutics. "The proteins that sit on these 'hot spots' are implicated in neurodegenerative disease, and the sites are also linked to aging."

The authors found approximately 65,000 hot spots that covered around 2 percent of the neuronal genome. They then used proteomics approaches to detect what proteins were found at these hot spots, implicating many splicing-related proteins. (These are involved in the eventual production of other proteins.) Many of these sites appeared to be quite stable when the cells were treated with DNA-damaging agents, and the most stable DNA repair hot spots were found to be strongly associated with sites where chemical tags attach ("methylation") that are best at predicting neuronal age.

Previous research has focused on identifying the sections of DNA that suffer genetic damage, but this is the first time researchers have looked for where the genome is being heavily repaired.

"We flipped the paradigm from looking for damage to looking for repair, and that's why we were able to find these hot spots," Reid says. "This is really new biology that might eventually change how we understand neurons in the nervous system, and the more we understand that, the more we can look to develop therapies addressing age-related diseases."

Gage, who holds the Vi and John Adler Chair for Research on Age-Related Neurodegenerative Disease, adds, "Understanding which areas within the genome are vulnerable to damage is a very exciting topic for our lab. We think Repair-seq will be a powerful tool for research, and we continue to explore additional new methods to study genome integrity, particularly in relation to aging and disease."

 Journal Reference:

1. Dylan A. Reid, Patrick J. Reed, Johannes C. M. Schlachetzki, Ioana I. Nitulescu, Grace Chou, Enoch C. Tsui, Jeffrey R. Jones, Sahaana Chandran, Ake T. Lu, Claire A. McClain, Jean H. Ooi, Tzu-Wen Wang, Addison J. Lana, Sara B. Linker, Anthony S. Ricciardulli, Shong Lau, Simon T. Schafer, Steve Horvath, Jesse R. Dixon, Nasun Hah, Christopher K. Glass, Fred H. Gage. Incorporation of a nucleoside analog maps genome repair sites in postmitotic human neurons. Science, 2021; 372 (6537): 91 DOI: 10.1126/science.abb9032 

Courtesy: ScienceDaily

Salk Institute. "How brain cells repair their DNA reveals 'hot spots' of aging and disease." ScienceDaily. ScienceDaily, 1 April 2021. <www.sciencedaily.com/releases/2021/04/210401151248.htm>.

 

 

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Novel coronavirus circulated undetected months before first COVID-19 cases in Wuhan, China

Using molecular dating tools and epidemiological simulations, researchers at University of California San Diego School of Medicine, with colleagues at the University of Arizona and Illumina, Inc., estimate that the SARS-CoV-2 virus was likely circulating undetected for at most two months before the first human cases of COVID-19 were described in Wuhan, China in late-December 2019.

Writing in the March 18, 2021 online issue of Science, they also note that their simulations suggest that the mutating virus dies out naturally more than three-quarters of the time without causing an epidemic.

"Our study was designed to answer the question of how long could SARS-CoV-2 have circulated in China before it was discovered," said senior author Joel O. Wertheim, PhD, associate professor in the Division of Infectious Diseases and Global Public Health at UC San Diego School of Medicine.

"To answer this question, we combined three important pieces of information: a detailed understanding of how SARS-CoV-2 spread in Wuhan before the lockdown, the genetic diversity of the virus in China and reports of the earliest cases of COVID-19 in China. By combining these disparate lines of evidence, we were able to put an upper limit of mid-October 2019 for when SARS-CoV-2 started circulating in Hubei province."

Cases of COVID-19 were first reported in late-December 2019 in Wuhan, located in the Hubei province of central China. The virus quickly spread beyond Hubei. Chinese authorities cordoned off the region and implemented mitigation measures nationwide. By April 2020, local transmission of the virus was under control but, by then, COVID-19 was pandemic with more than 100 countries reporting cases.

SARS-CoV-2 is a zoonotic coronavirus, believed to have jumped from an unknown animal host to humans. Numerous efforts have been made to identify when the virus first began spreading among humans, based on investigations of early-diagnosed cases of COVID-19. The first cluster of cases -- and the earliest sequenced SARS-CoV-2 genomes -- were associated with the Huanan Seafood Wholesale Market, but study authors say the market cluster is unlikely to have marked the beginning of the pandemic because the earliest documented COVID-19 cases had no connection to the market.

Regional newspaper reports suggest COVID-19 diagnoses in Hubei date back to at least November 17, 2019, suggesting the virus was already actively circulating when Chinese authorities enacted public health measures.

In the new study, researchers used molecular clock evolutionary analyses to try to home in on when the first, or index, case of SARS-CoV-2 occurred. "Molecular clock" is a term for a technique that uses the mutation rate of genes to deduce when two or more life forms diverged -- in this case, when the common ancestor of all variants of SARS-CoV-2 existed, estimated in this study to as early as mid-November 2019.

Molecular dating of the most recent common ancestor is often taken to be synonymous with the index case of an emerging disease. However, said co-author Michael Worobey, PhD, professor of ecology and evolutionary biology at University of Arizona: "The index case can conceivably predate the common ancestor -- the actual first case of this outbreak may have occurred days, weeks or even many months before the estimated common ancestor. Determining the length of that 'phylogenetic fuse' was at the heart of our investigation."

Based on this work, the researchers estimate that the median number of persons infected with SARS-CoV-2 in China was less than one until November 4, 2019. Thirteen days later, it was four individuals, and just nine on December 1, 2019. The first hospitalizations in Wuhan with a condition later identified as COVID-19 occurred in mid-December.

Study authors used a variety of analytical tools to model how the SARS-CoV-2 virus may have behaved during the initial outbreak and early days of the pandemic when it was largely an unknown entity and the scope of the public health threat not yet fully realized.

These tools included epidemic simulations based on the virus's known biology, such as its transmissibility and other factors. In just 29.7 percent of these simulations was the virus able to create self-sustaining epidemics. In the other 70.3 percent, the virus infected relatively few persons before dying out. The average failed epidemic ended just eight days after the index case.

"Typically, scientists use the viral genetic diversity to get the timing of when a virus started to spread," said Wertheim. "Our study added a crucial layer on top of this approach by modeling how long the virus could have circulated before giving rise to the observed genetic diversity.

"Our approach yielded some surprising results. We saw that over two-thirds of the epidemics we attempted to simulate went extinct. That means that if we could go back in time and repeat 2019 one hundred times, two out of three times, COVID-19 would have fizzled out on its own without igniting a pandemic. This finding supports the notion that humans are constantly being bombarded with zoonotic pathogens."

Wertheim noted that even as SARS-CoV-2 was circulating in China in the fall of 2019, the researchers' model suggests it was doing so at low levels until at least December of that year.

"Given that, it's hard to reconcile these low levels of virus in China with claims of infections in Europe and the U.S. at the same time," Wertheim said. "I am quite skeptical of claims of COVID-19 outside China at that time."

The original strain of SARS-CoV-2 became epidemic, the authors write, because it was widely dispersed, which favors persistence, and because it thrived in urban areas where transmission was easier. In simulated epidemics involving less dense rural communities, epidemics went extinct 94.5 to 99.6 percent of the time.

The virus has since mutated multiple times, with a number of variants becoming more transmissible.

"Pandemic surveillance wasn't prepared for a virus like SARS-CoV-2," Wertheim said. "We were looking for the next SARS or MERS, something that killed people at a high rate, but in hindsight, we see how a highly transmissible virus with a modest mortality rate can also lay the world low."

Co-authors include: Jonathan Pekar and Niema Moshiri, UC San Diego; and Konrad Scheffler, Illumina, Inc.

Funding for this research came, in part, from the National Institutes of Health (grants AI135992, AI136056, T15LM011271), the Google Cloud COVID-19 Research Credits Program, the David and Lucile Packard Foundation, the University of Arizona and the National Science Foundation (grant 2028040).

Journal Reference:

1. Jonathan Pekar, Michael Worobey, Niema Moshiri, Konrad Scheffler, Joel O. Wertheim. Timing the SARS-CoV-2 index case in Hubei province. Science, 2021; eabf8003 DOI: 10.1126/science.abf8003 

Courtesy: ScienceDaily

University of California - San Diego. "Novel coronavirus circulated undetected months before first COVID-19 cases in Wuhan, China: Study dates emergence to as early as October 2019; Simulations suggest in most cases zoonotic viruses die out naturally before causing a pandemic." ScienceDaily. ScienceDaily, 18 March 2021. <www.sciencedaily.com/releases/2021/03/210318185328.htm>.