Genetic characterization of a novel picorna-like virus in Culex spp. mosquitoes from Mozambique

Background: Mosquitoes are the potential vectors for a variety of viruses that can cause diseases in the human and animal populations. Viruses in the order Picornavirales infect a broad range of hosts, including mosquitoes. In this study, we aimed to characterize a novel picorna-like virus from the Culex spp. of mosquitoes from the Zambezi Valley of Mozambique.

Methods: The extracted RNA from mosquito pools was pre-amplified with the sequence independent single primer amplification (SISPA) method and subjected to high-throughput sequencing using the Ion Torrent platform. Reads that are classified as Iflaviridae, Picornaviridae and Dicistroviridae were assembled by CodonCode Aligner and SPAdes. Gaps between the viral contigs were sequenced by PCR. The genomic ends were analyzed by 5' and 3' RACE PCRs. The ORF was predicted with the NCBI ORF finder. The conserved domains were identified with ClustalW multiple sequence alignment, and a phylogenetic tree was built with MEGA. The presence of the virus in individual mosquito pools was detected by RT-PCR assay.

Results: A near full-length viral genome (9740 nt) was obtained in Culex mosquitoes that encoded a complete ORF (3112 aa), named Culex picorna-like virus (CuPV-1). The predicted ORF had 38% similarity to the Hubei picorna-like virus 35. The sequence of the conserved domains, Helicase-Protease-RNA-dependent RNA polymerase, were identified by multiple sequence alignment and found to be at the 3' end, similar to iflaviruses. Phylogenetic analysis of the putative RdRP amino acid sequences indicated that the virus clustered with members of the Iflaviridae family. CuPV-1 was detected in both Culex and Mansonia individual pools with low infection rates.

Conclusions: The study reported a highly divergent, near full-length picorna-like virus genome from Culex spp. mosquitoes from Mozambique. The discovery and characterization of novel viruses in mosquitoes is an initial step, which will provide insights into mosquito-virus interaction mechanisms, genetic diversity and evolution.