Rhinolophus rouxi, which inhabits parts of South Asia, was identified as a likely but undetected betacoronavirus host by the study authors.
CREDIT: Brock and Sherri Fenton
An international research team led by scientists at Georgetown University have demonstrated the power of artificial intelligence to predict which viruses could infect humans — like SARS-CoV-2, the virus that led to the COVID-19 pandemic — which animals host them, and where they could emerge.
Their ensemble of predictive models of likely reservoir hosts, published January 10 in Lancet Microbe (“Optimizing predictive models to prioritize viral discovery in zoonotic reservoirs”), was validated in an 18-month project to identify specific bat species likely to carry betacoronaviruses, the group that includes SARS-like viruses.
“If you want to find these viruses, you have to start by profiling their hosts — their ecology, their evolution, even the shape of their wings,” explains the study’s senior author, Colin Carlson, PhD, an assistant research professor in the Department of Microbiology & Immunology and a member of Georgetown’s Center for Global Health Science and Security at Georgetown University Medical Center. “Artificial intelligence lets us take data on bats and turn it into concrete predictions: where should we be looking for the next SARS?”
Despite global investments in disease surveillance, it remains difficult to identify and monitor wildlife reservoirs of viruses that could someday infect humans. Statistical models are increasingly being used to prioritize which wildlife species to sample in the field, but the predictions being generated from any one model can be highly uncertain. Scientists also rarely track the success or failure of their predictions after they make them, making it hard to learn and make better models in the future. Together, these limitations mean that there is high uncertainty in which models may be best suited to the task.
This new study suggests that the search for closely-related viruses could be non-trivial, with over 400 bat species around the world predicted to host betacoronaviruses, a large group of viruses that includes those responsible for SARS-CoV (the virus that caused the 2002-2004 outbreak of SARS) and SARS-CoV-2 (the virus that causes COVID-19). Although the origin of SARS-CoV-2 remains uncertain, the spillover of other viruses from bats is a growing problem due to factors like agricultural expansion and climate change.
Greg Albery, PhD, a postdoctoral fellow in Georgetown’s Biology Department, says COVID-19 provided the impetus to expedite their research. “This is a really rare opportunity,” explains Albery. “Outside of a pandemic, we’d never learn this much about these viruses in this small a timeframe. A decade of research has been collapsed into about a year of publications, and it means we can actually show that these tools work.”
In the first quarter of 2020, the researcher team trained eight different statistical models that predicted which kinds of animals could host betacoronaviruses. Over more than a year, the team then tracked discovery of 40 new bat hosts of betacoronaviruses to validate initial predictions and dynamically update their models. The researchers found that models harnessing data on bat ecology and evolution performed extremely well at predicting new hosts. In contrast, cutting-edge models from network science that used high-level mathematics – but less biological data – performed roughly as well or worse than expected at random.
“One of the most important things our study gives us is a data-driven shortlist of which bat species should be studied further,” says Daniel Becker, PhD, assistant professor of biology at the University of Oklahoma. “After identifying these likely hosts, the next step is then to invest in monitoring to understand where and when betacoronaviruses are likely to spill over.”
Carlson says that the team is now working with other scientists around the world to test bat samples for coronaviruses based on their predictions.
“If we spend less money, resources, and time looking for these viruses, we can put all of those resources into the things that actually save lives down the road. We can invest in building universal vaccines to target those viruses, or monitoring for spillover in people that live near bats,” says Carlson. “It’s a win-win for science and public health.”
More from: Georgetown University Medical Center | University of Idaho | Louisiana State University | University of California Berkeley | Colorado State University | Pacific Lutheran University | Icahn School of Medicine at Mount Sinai | University of Glasgow | Université de Montréal | University of Toronto | Ghent University | University College Dublin | Cary Institute of Ecosystem Studies | American Museum of Natural History
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
- Lunar New Year festival kicks off at Disney California Adventure
Disney’s Lunar New Year event kicked off on Friday, Jan. 21 and runs through Feb. 13 at Disney California Adventure in celebration of Chinese, Korean and Vietnamese cultures and traditions.
- Vietnam Fertilizer Market Scope and Overview with details Analysis, Competitive Landscapes, Forecast to 2020-2027
According to the report published by Allied Market Research, the Vietnam fertilizer market generated $4.5 billion in 2019, and is estimated to ...
- Gary Russell Jr. vs. Mark Magsayo odds, picks and prediction: featherweight championship
Breaking down Saturday’s Brandon Figueroa vs. Stephen Fulton jr. featherweight fight, with boxing odds, picks and predictions.
- Ohio’s pandemic politics cast long shadow over omicron surge
After a severe bout of COVID-19 put him in the ICU and left him with significant respiratory systems, Dr. Emily Amin’s patient had questions about getting vaccinated.
- UW researchers predict end to the pandemic
Thursday marked two years since the pandemic began, but a leading group of researchers in Washington say we are close to the end of the pandemic as well as a shift in how we deal with the virus.
Go deeper with Google Headlines on:
Go deeper with Bing News on:
Artificial intelligence can predict which viruses could infect humans
- 'Game-changing' AI technology can detect Covid-19 in minutes
A group of scientists in Scotland has found a way to detect the presence of Covid-19 infection in a person using AI-based X-rays within minutes ...
- Artificial Intelligence Used To Search for the Next SARS-COV-2
Daniel Becker, an assistant professor of biology in the University of Oklahoma’s Dodge Family College of Arts and Sciences, has been leading a proactive modeling study over the last year and a half to ...
- Shall We Play a Game? Researchers Use AI To Search for the Next COVID/SARS-Like Virus
An international research team led by scientists at Georgetown University have demonstrated the power of artificial intelligence to predict which viruses could infect humans — like SARS-CoV-2, the ...
- OU-led research team uses AI to predict coronavirus strains in bats
The origins of COVID-19 aren't fully understood, but bats are a main suspect. An OU professor is leading a team using artificial intelligence to better understand bat populations and predict virus ...
- Researchers use artificial intelligence to search for next SARS-like virus
An international research team of scientists has demonstrated the power of Artificial Intelligence (AI) to predict which viruses could infect humans ... these viruses, we can put all of those ...