Scientists have developed a new tool designed to identify possible host species for filoviruses such as Ebola, which will aid in improving wildlife surveillance strategies.
Although bats are widely acknowledged as the primary carriers of filoviruses, including Ebola, pinpointing the specific species responsible for these viruses is still uncertain. A research team from the University of California, Davis, in collaboration with the Albert Einstein College of Medicine (Einstein), has created a tool to more accurately identify potential host species for filoviruses and set wildlife monitoring priorities. This research supports global efforts to prevent the transmission of viruses between animals and humans.
Published in the journal Cell Host & Microbe, this research uncovers the molecular mechanisms through which filoviruses recognize their receptors, which aids in finding previously unidentified host species for these viruses.
“A crucial question is, where might the next ebolavirus outbreak begin?” inquired Simon Anthony, co-leading author and associate professor at the UC Davis School of Veterinary Medicine. “Without identifying the wildlife host, it becomes impossible to predict how, where, or when it will happen.”
The most significant filovirus outbreak, caused by the Ebola virus, occurred in three West African countries from 2014 to 2016, leading to more than 11,000 deaths and 28,000 infections. Recently, a Marburg virus outbreak started in Rwanda last September, resulting in at least 15 deaths and 66 confirmed cases.
Understanding how viruses enter cells
This research represents the most comprehensive study on how filoviruses bind to receptors in bats conducted thus far. For an ebolavirus to infect a human cell, its glycoprotein must first attach to a specific cell receptor.
In 2011, co-leading author Kartik Chandran, a professor at Einstein specializing in microbiology and immunology, found that the cholesterol-transporting protein Niemann-Pick C1 (NPC1) is essential for Ebola virus entry.
“Importantly, every filovirus studied to date has been shown to depend on NPC1 for infection,” Chandran noted.
In this project, researchers carried out extensive binding tests to evaluate how well glycoproteins from various filoviruses interact with bat NPC1 proteins. They utilized machine learning to determine the genetic factors that affect receptor binding for these viruses.
The team focused on bat species whose NPC1 proteins exhibited strong interactions with the Ebola virus glycoprotein, especially in regions where previous Ebola outbreaks were documented. This strategy helps highlight bat species that are most likely to carry the virus.
“This study skillfully combines two seemingly disparate elements—geographic information and molecular data—to examine if these bats could serve as potential virus hosts,” remarked co-leading author Gorka Lasso, a research assistant professor at Einstein.
Shaping future research directions
The insights garnered from this research can guide future initiatives to locate the reservoir hosts of the Ebola virus and related viruses. As new ebolaviruses and their variants are discovered, scientists can leverage this method to assess their potential to infect humans.
“We hope this approach benefits not just filoviruses but also other viral agents,” Lasso added.
The research was partially influenced by a 2015 study led by Chandran, which suggested that African straw-colored fruit bats may be resistant to Ebola infection due to the poor binding efficiency of the Ebola virus to their NPC1 receptor.
“This finding was striking,” noted Anthony, who played a role in identifying the sixth known strain of ebolavirus, the Bombali virus. “It became obvious that certain species are unlikely hosts because they cannot be infected. Knowing which species are probable—and improbable—hosts is vital information we need.”
This study was supported by funding from the U.S. Agency for International Development, the National Institutes of Health, and the National Science Foundation’s Predictive Intelligence for Pandemic Prevention.
