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COVID-19 targets cells; bats, coronavirus co-evolved; fighting cancer with math

This is a recurring column on early-stage research in animals or other laboratory models that has not yet entered the clinic but could have implications for future research and development of human medicines.

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Learning the ways the coronavirus infects cells can help researchers discover vaccines and treatments.

Source: U.S. NIAID

The scientific community is scrambling to learn more about the novel coronavirus causing the COVID-19 pandemic, and preclinical trials have quickly revealed some of the virus's unique characteristics, potentially leading to treatments and vaccines.

Scientists at the Ragon Institute and the Broad Institute — collectively run by the Massachusetts General Hospital, the Massachusetts Institute of Technology and Harvard University — have found that the virus targets particular cells in the body.

Investigating proteins coded by genetic material, the Boston-area researchers discovered that the virus can enter cells in the lungs, nasal passages and intestines. These cells express two proteins that are susceptible to the virus's own genetic makeup. The findings were published in the journal Cell.

The researchers used RNA sequencing of mouse, primate and human cells to decipher what causes a particular cell type to act the way it does and compared the genes to the coronavirus infection mechanism.

Specifically, cells that produce mucus and those that line the air sacs in the lung expressed the susceptible genes. In the intestine, the cells responsible for absorbing nutrients gave a similar signal.

The study suggested that the virus evolved to take advantage of the cells' natural defenses. The researchers found that it is possible to use signaling proteins called interferons to heighten an anti-viral defense, but they urged caution until human trials can begin.

"This may not be the full story, but it definitely paints a much more precise picture than where the field stood before," said study co-author Jose Ordovas-Montanes, who now runs a lab at Boston Children's Hospital. "Now we can say with some level of confidence that these receptors are expressed on these specific cells in these tissues."

Learning from bats' coronavirus evolution

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Bats have evolved with coronaviruses for millions of years, scientists say.

Source: Anton 17

Bats have gotten a bad rap during the pandemic as the likely progenitor of the virus causing it all. But researchers have found that the flying mammals and coronaviruses have evolved together for millions of years.

Biologists from Chicago's Field Museum and the Université de La Réunion found that in 36 bat species from the western Indian Ocean and nearby Africa, each specific type carried unique strains of coronavirus, suggesting they have coevolved.

"We found that there's a deep evolutionary history between bats and coronaviruses," according to the Field Museum's Steve Goodman, an author of the paper in Scientific Reports. "Developing a better understanding of how coronaviruses evolved can help us build public health programs in the future."

Understanding the different strains of coronavirus present in bats also could help prevent future human outbreaks, Goodman said.

"Before you can actually figure out programs for public health and try to deal with the possible shift of certain diseases to humans, or from humans to animals, you have to know what's out there," Goodman said. "This is the kind of blueprint."

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Fighting cancer with math

Besides the worldwide effort to quell the coronavirus pandemic, cancer remains the focus of many preclinical studies, and an unlikely group of researchers has joined the fray: mathematicians.

Researchers specializing in game theory at Cornell University have likened the way cancer cells attack the body to a game of rock, paper, scissors. Cancer cells of different types, depending on their need for oxygen, compete with one another inside a tumor, adapting their strategies to survive.

The findings could help determine the right way to treat a patient so that a drug regimen accounts for these adapting cancer cells.

"Our main contribution is in computing how to optimally time these periods of drug treatment adaptively," said senior study author Alex Vladimirsky, director of the Center for Applied Mathematics at Cornell. "We basically developed a map that shows when to administer drugs based on the current ratio of different subtypes of cancer."

Applying the mathematical model to patients could allow for a reduced amount of cancer drugs that often come with severe side effects. But Vladimirsky cautioned that mathematical models and biological systems are not always a perfect match.

"In principle, the same ideas should also be applicable to much more detailed, and even patient-specific, models, but we are still a long way from there," Vladimirsky said.