Invasive Species Compendium

Detailed coverage of invasive species threatening livelihoods and the environment worldwide

Abstract

Viral networks and detection of potential zoonotic viruses in bats and rodents: a worldwide analysis.

Abstract

Bats and rodents are recognized to host a great diversity of viruses and several important viral zoonoses, but how this viral diversity is structured and how viruses are connected, shared and distributed among host networks is not well understood. To address this gap in knowledge, we compared the associative capacity of the host-virus networks in rodents and bats with the identification of those viruses with zoonotic potential. A virus database, detected by molecular methods, was constructed in the two taxonomic groups. We compiled 5,484 records: 825 in rodents and 4,659 in bats. We identified a total of 173 and 166 viruses, of which 53 and 40 are zoonotic viruses, in rodents and bats, respectively. Based on a network theory, a non-directed bipartite host-virus network was built for each group. Subsequently, the networks were collapsed to represent the connections among hosts and viruses. We identified both discrete and connected communities. We observed a greater degree of connectivity in bat viruses and more discrete communities in rodents. The Coronaviridae recorded in bats have the highest values of degree, betweenness and closeness centralities. In rodents, higher degree positions were distributed homogeneously between viruses and hosts. At least in our database, a higher proportion of rodent viruses were zoonotic. Rodents should thus not be underestimated as important reservoirs of zoonotic disease. We found that viruses were more frequently shared among bats than in rodents. Network theory can reveal some macroecological patterns and identify risks that were previously unrecognized. For example, we found that parvovirus in megabats and Gbagroube virus in rodents may represent a zoonotic risk due to the proximity to humans and other zoonotic viruses. We propose that epidemiological surveillance programmes should consider the connectivity of network actors as a measure of the risks of dispersion and transmission.