The mosquito body hosts highly diverse microbes, which influence different physiological traits of both larvae and adults. The composition of adult mosquito microbiota is tightly linked to that of larvae, which are aquatic and feed on organic detritus, algae and prokaryotic microorganisms present in their breeding sites. Unraveling the ecological features of larval habitats that shape the structure of bacterial communities and their interactions with the mosquito host is still a poorly investigated topic in the Asian tiger mosquito Aedes albopictus, a highly invasive species that is vector of numerous arboviruses, including Dengue, Chikungunya, and Zika viruses. In this study, we investigated the composition of the bacterial community present in the water from a natural larval breeding site in which we separately reared wild-collected larvae and hatched eggs of the Foshan reference laboratory strain. Using sequence analysis of bacterial 16S rRNA gene amplicons, we comparatively analyzed the microbiota of the larvae and that of adult mosquitoes, deriving information about the relative impact of the breeding site water on shaping mosquito microbiota. We observed a higher bacterial diversity in breeding site water than in larvae or adults, irrespective of the origin of the sample. Moreover, larvae displayed a significantly different and most diversified microbial community than newly emerged adults, which appeared to be dominated by Proteobacteria. The microbiota of breeding site water significantly increased its diversity over time, suggesting the presence of a dynamic interaction among bacterial communities, breeding sites and mosquito hosts. The analysis of Wolbachia prevalence in adults from Foshan and five additional strains with different geographic origins confirmed the described pattern of dual wAlbA and wAlbB strain infection. However, differences in Wolbachia prevalence were detected, with one strain from La Reunion Island showing up to 18% uninfected individuals. These findings contribute in further understanding the dynamic interactions between the ecology of larval habitats and the structure of host microbiota, as well as providing additional information relative to the patterns of Wolbachia infection.

Background Several bioinformatics pipelines have been developed to detect sequences from viruses that integrate into the human genome because of the health relevance of these integrations, such as in the persistence of viral infection and/or in generating genotoxic effects, often progressing into cancer. Recent genomics and metagenomics analyses have shown that viruses also integrate into the genome of non-model organisms (i.e., arthropods, fish, plants, vertebrates). However, rarely studies of endogenous viral elements (EVEs) in non-model organisms have gone beyond their characterization from reference genome assemblies. In non-model organisms, we lack a thorough understanding of the widespread occurrence of EVEs and their biological relevance, apart from sporadic cases which nevertheless point to significant roles of EVEs in immunity and regulation of expression. The concomitance of repetitive DNA, duplications and/or assembly fragmentations in a genome sequence and intrasample variability in whole-genome sequencing (WGS) data could determine misalignments when mapping data to a genome assembly. This phenomenon hinders our ability to properly identify integration sites. Results To fill this gap, we developed ViR, a pipeline which solves the dispersion of reads due to intrasample variability in sequencing data from both single and pooled DNA samples thus ameliorating the detection of integration sites. We tested ViR to work with both in silico and real sequencing data from a non-model organism, the arboviral vector Aedes albopictus. Potential viral integrations predicted by ViR were molecularly validated supporting the accuracy of ViR results. Conclusion ViR will open new venues to explore the biology of EVEs, especially in non-model organisms. Importantly, while we generated ViR with the identification of EVEs in mind, its application can be extended to detect any lateral transfer event providing an ad-hoc sequence to interrogate.

Lateral gene transfer (LT) from viruses to eukaryotic cells is a well-recognized phenomenon. Somatic integrations of viruses have been linked to persistent viral infection and genotoxic effects, including various types of cancer. As a consequence, several bioinformatic tools have been developed to identify viral sequences integrated into the human genome. Viral sequences that integrate into germline cells can be transmitted vertically, be maintained in host genomes and be co-opted for host functions. Endogenous viral elements (EVEs) have long been known, but the extent of their widespread occurrence has only been recently appreciated. Modern genomic sequencing analyses showed that eukaryotic genomes may harbor hundreds of EVEs, which derive not only from DNA viruses and retroviruses, but also from nonretroviral RNA viruses and are mostly enriched in repetitive regions of the genome. Despite being increasingly recognized as important players in different biological processes such as regulation of expression and immunity, the study of EVEs in non-model organisms has rarely gone beyond their characterization from annotated reference genomes because of the lack of computational methods suited to solve signals for EVEs in repetitive DNA. To fill this gap, we developed ViR, a pipeline which ameliorates the detection of integration sites by solving the dispersion of reads in genome assemblies that are rich of repetitive DNA. Using paired-end whole genome sequencing (WGS) data and a user-built database of viral genomes, ViR selects the best candidate couples of reads supporting an integration site by solving the dispersion of reads resulting from intrasample variability. We benchmarked ViR to work with sequencing data from both single and pooled DNA samples and show its applicability using WGS data of a non-model organism, the arboviral vector Aedes albopictus. Viral integrations predicted by ViR were molecularly validated supporting the accuracy of ViR results. Additionally, ViR can be readily adopted to detect any LT event providing ad hoc non-host sequences to interrogate.