Two Novel Iflaviruses Discovered in Bat Samples in Washington State

Abstract

Arthropods are integral to ecosystem equilibrium, serving as both a food source for insectivores and supporting plant reproduction. Members of the Iflaviridae family in the order Picornavirales are frequently found in RNA sequenced from arthropods, who serve as their hosts. Here we implement a metagenomic deep sequencing approach followed by rapid amplification of cDNA ends (RACE) on viral RNA isolated from wild and captured bat guano in Washington State at two separate time points. From these samples we report the complete genomes of two novel viruses in the family Iflaviridae. The first virus, which we call King virus, is 46% identical by nucleotide to the lethal honeybee virus, deformed wing virus, while the second virus which we call Rolda virus, shares 39% nucleotide identity to deformed wing virus. King and Rolda virus genomes are 10,183 and 8934 nucleotides in length, respectively. Given these iflaviruses were detected in guano from captive bats whose sole food source was the Tenebrio spp. mealworm, we anticipate this invertebrate may be a likely host. Using the NCBI Sequence Read Archive, we found that these two viruses are located in six continents and have been isolated from a variety of arthropod and mammalian specimens.

Unlocking the Viral Universe: Metagenomic Analysis of Bat Samples Using Next-Generation Sequencing

“…A prime example is the numerous reads from the family Densovirinae, accounting for up to 30% of all sequencing reads in some samples, most of which probably belong to insect viruses. Other examples of viruses capable of infecting insects that we found in bat feces include the following: King and Rold viruses [41], Cricket Iridovirus, Pidgeon bunyavirus, Icha Creek insect virus, Mothra virus, and Lampyris noctiluca tymovirus-like virus 1. The mammalian viruses detected included adenoviruses, papillomaviruses, astroviruses, bastroviruses, rotaviruses, and herpesviruses.…”

Characterization of Iflavirus in the Red Flour Beetle, Tribolium castaneum (Coleoptera; Tenebrionidae)

“…Iflaviruses are arthropod-specific viruses that infect insects from the insect orders Lepidoptera, Hymenoptera, Hemiptera, Diptera, Coleoptera, and Orthoptera [ 10 ]. Recently, Juergens et al, 2022 [ 27 ], identified two novel iflaviruses named the King virus and Rolda virus from bat guano in Washington state. Since these bats were captive and fed solely on Tenebrio spp., the insect diet of the bat might have been the source of the virus in them.…”

“…Even though there are some reports of lethal infections by iflaviruses in insects, such as pupation failure in honeybee larvae infected with sacbrood virus [ 38 ] and premature death in honeybees carrying deformed wing virus [ 17 ], such infections commonly appear to be covert and symptomless [ 10 , 14 , 39 , 40 , 41 ]. Iflaviruses often show no signs of overt infection in a number of insect species [ 39 , 40 , 41 , 42 ] and are usually detected through next-generation sequencing [ 27 , 43 ]. Often, they are found to cause sublethal effects on their hosts.…”

“…The SRX samples with hits were further analyzed using the analysis tab for the presence of the TcIV, and the transcript per million value (TPM) was calculated by dividing the number of BLASTN hits by the number of total spots for each of the SRX data. Those without hits were excluded from further analysis [ 27 ].…”

CZ ID: a cloud-based, no-code platform enabling advanced long read metagenomic analysis

“…Metagenomics has emerged as an effective lens for studying infectious diseases, enabling the unbiased, direct detection and identification of pathogens from clinical (e.g., Chiu and Miller, 2019;Li et al, 2021;Bohl et al, 2022), non-human host (e.g., Batson et al, 2021;Ergunay et al, 2022;Juergens et al, 2022), and environmental samples (e.g., Datta et al, 2020;Farrell et al, 2022;Ramuta et al, 2023;Urban et al, 2023). Unlike traditional culture-independent methods that rely on targeted assays to identify microbes, metagenomics can potentially detect all microbes present in a sample, regardless of whether they have been previously characterized.…”