The risk to human health from mosquito-borne viruses such as dengue, chikungunya and yellow fever is increasing due to increased human expansion, deforestation and climate change. To anticipate and predict the spread and transmission of mosquito-borne viruses, a better understanding of the transmission cycle in mosquito populations is needed. We present a pathogen-agnostic combined sequencing protocol for identifying vectors, viral pathogens and their hosts or reservoirs using portable Oxford Nanopore sequencing. Using mosquitoes collected in São Paulo, Brazil, we extracted RNA for virus identification and DNA for blood meal and mosquito identification. Mosquitoes and blood meals were identified by comparing cytochrome c oxidase I (COI) sequences against a curated Barcode of Life Data System (BOLD). Viruses were identified using the SMART-9N protocol, which allows amplified DNA to be prepared with native barcoding for nanopore sequencing. Kraken 2 was employed to detect viral pathogens and Minimap2 and BOLD identified the contents of the blood meal. Due to the high similarity of some species, mosquito identification was conducted using blast after generation of consensus COI sequences using RACON polishing. This protocol can simultaneously uncover viral diversity, mosquito species and mosquito feeding habits. It also has the potential to increase understanding of mosquito genetic diversity and transmission dynamics of zoonotic mosquito-borne viruses.

Metagenomic studies of mosquito viromes demonstrated a more diverse composition than just an exclusive composition of pathogenic arboviruses transmitted to humans. In our study, the virome of 866 female mosquitoes collected throughout 2020 at the São Paulo Zoo, located in the city of São Paulo/SP—Brazil, was obtained. Specifically, in this paper, we describe a new virus found by viral RNA extraction and next-generation MiSeq sequencing of a group of 23 specimens of Anopheles (Nys.) strodei. The complete genome with a length of 9709 nucleotides was characterized by a positive orientation and a single strand, with a single large ORF, which encodes a polyprotein of 2987 amino acids. The phylogenetic analysis showed an association with the viral family Iflaviridae and the Riboviria realm. We carried out comparisons with translated sequences of the capsid regions of other iflavirus, and the identities in relation to our sequence were below the minimum limit of 90%, indicating that possibly it is a new species of iflavirus. Our findings contribute to expanding knowledge of virome composition among mosquito species in Brazil and globally. Moreover, we provide a viral genome reference specific to this geographic region and Culicidae family of mosquitoes. This resource facilitates future in silico recognition and assembly of viral genomes within metagenomic datasets.

The identification of mosquito species is necessary for determining the entomological components of disease transmission. However, identification can be difficult in species that are morphologically similar. The cytochrome c oxidase subunit I (COI) DNA barcode region is considered a valuable and reliable diagnostic tool for mosquito species recognition, including those that belong to species complexes. Mansonia mosquitoes are found in forests near swampy areas. They are nocturnal and are highly attracted to light. Hematophagous adult females exhibit aggressive biting behavior and can become infected with and transmit pathogens during their feeding, including some epizootic viruses and avian malaria. In Brazil, twelve Mansonia species have been reported. In a recent study from the São Paulo Zoo in Brazil, three morphologically distinct species were collected and identified, namely: Mansonia (Mansonia) indubitans, Ma. (Man.) pseudotitillans and Ma. (Man.) titillans. However, confirmation of these species by molecular identification was unsuccessful due to a lack of COI sequences in the GenBank database. Thus, this research aimed to describe the COI DNA barcode sequences of some morphologically characterized Mansonia (Man.) species from Brazil and to determine their utility in delimiting species collected from the Atlantic Forest and Brazilian Savanna. Accordingly, we provide tools for the genetic identification of species that play a significant role in pathogen transmission in wildlife and potentially humans. We show that the delimitation of Mansonia species via five different approaches based on COI DNA sequences (BI, NJ, ASAP, bPTP and GMYC) yield basically the same groups identified by traditional taxonomy, and we provide the identification of specimens that were previously identified only up to the subgenus level. We also provide COI sequences from two Mansonia species that were not previously available in sequence databases, Ma. wilsoni and Ma. pseudotitillans, and thus contribute to the ongoing global effort to standardize DNA barcoding as a molecular means of species identification.

Several viruses belonging to the order Mononegavirales are recognized as highly pathogenic in humans and are often associated with lethal disease outcomes. Prominent examples include human respiratory syncytial virus (HRSV), Ebola virus (EBOV), rabies virus (RABV), and Marburg virus (MARV). In addition to their clinical severity, these viruses are considered potential biological threats due to their high transmissibility and virulence. In this study, we performed a metatranscriptomic analysis of Culex and Anopheles mosquitoes collected at the DBB (Diretoria de Biodiversidade e Biotecnologia), São Paulo, Brazil. Our analysis revealed viral sequences associated with two families within Mononegavirales : Lispiviridae and Rhabdoviridae . Phylogenetic analysis of the Lispiviridae sequences identified six variants, designated CxLispV-SP_03 , CxLispV-SP_09 , CxLispV-SP_12 , CxLispV-SP_13 , CxLispV-SP_14 , and CxLispV-SP_15 , that formed a strongly supported monophyletic clade with Canya virus, suggesting the discovery of a putative novel viral lineage. Examination of RNA‐dependent RNA polymerase (RdRp) domains in these sequences confirmed the presence of essential catalytic motifs. In contrast, the detected rhabdoviruses exhibited greater genomic structural heterogeneity, including the presence of accessory protein domains. Pairwise comparisons based on RdRp amino acid identity delineated four distinct groups among these sequences, pointing to substantial evolutionary divergence within the sampled rhabdovirus diversity. Together, these findings contribute to the growing characterization of mosquito‐associated mononegaviruses and provide a genomic foundation to support future surveillance efforts and public health risk assessments related to vector‐borne viruses.

This study investigated the RNA virome associated with the phlebotomine sand fly Pintomyia fischeri using a metatranscriptomic approach applied to the Meta29 library, composed of 21 specimens collected at the São Paulo Zoo, Brazil. Read-based taxonomic analysis revealed a diverse viral community composed of viruses associated with the families Iflaviridae, Narnaviridae, Partitiviridae, Reoviridae, Solemoviridae, Tombusviridae, Totiviridae, and Tymoviridae, in addition to highly abundant unclassified RNA viruses related to the ShiM 2016 group. Assembly and annotation analyses enabled the characterization of four viral RNA genomes associated with the families Partitiviridae (PfPartitiV-1a-SP, PfPartitiV-1b-SP, and PfPartitiV-2-SP) and Narnaviridae (PfNarnaV-1-SP). Sequence comparisons revealed low amino acid identity relative to currently available reference viral sequences, supporting the classification of these sequences as highly divergent and potentially novel viral lineages. Structural modeling of the RNA-dependent RNA polymerase (RdRp) proteins identified the viral polymerase-specific catalytic motifs A, B, and C. Phylogenetic analyses further supported the evolutionary divergence of the identified viruses relative to currently described taxa. Overall, these findings expand current knowledge of viral RNA diversity associated with Neotropical sand flies and highlight the value of metatranscriptomic approaches for the detection and characterization of previously undescribed viruses associated with medically important insect vectors.