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Arboviruses cause diseases of significant global health concerns. Interactions between mosquitoes and their microbiota as well as the important role of this interaction in the mosquito's capacity to harbor and transmit pathogens have emerged as important fields of research. Aedes aegypti is one of the most abundant mosquitoes in many geographic locations, a vector capable of transmitting a number of arboviruses such as dengue and Zika. Currently, there are few studies on the metavirome of this mosquito particularly in the Americas. This study analyzes the metavirome of A. aegypti from Grenada, a Caribbean nation with tropical weather, abundant A. aegypti, and both endemic and arboviral pathogens transmitted by this mosquito. Between January and December 2018, 1152 mosquitoes were collected from six semi-rural locations near houses in St. George Parish, Grenada, by weekly trapping using BG-Sentinel traps. From these, 300 A. aegypti were selected for analysis. The metavirome was analyzed using the Illumina HiSeq 1500 for deep sequencing. The generation sequencing library construction protocol used was NuGEN Universal RNA with an average read length of 125 bp. Reads were mapped to the A. aegypti assembly. Non-mosquito reads were analyzed using the tools FastViromeExplorer. The NCBI total virus, RNA virus, and eukaryotic virus databases were used as references. The metagenomic comparison analysis showed that the most abundant virus-related reads among all databases and assemblies was Phasi Charoen-like virus. The Phasi Charoen-like virus results are in agreement to other studies in America, Asia and Australia. Further studies using wild-caught mosquitoes is needed to assess the impact of this insect-specific virus on the A. aegypti lifecycle and vector capacity., Competing Interests: The authors have declared that no competing interests exist.

Background: One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited., Results: In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages., Conclusions: This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

The Extreme Microbiome Project (XMP) is a project launched by the Association of Biomolecular Resource Facilities Metagenomics Research Group (ABRF MGRG) that focuses on whole genome shotgun sequencing of extreme and unique environments using a wide variety of biomolecular techniques. The goals are multifaceted, including development and refinement of new techniques for the following: 1) the detection and characterization of novel microbes, 2) the evaluation of nucleic acid techniques for extremophilic samples, and 3) the identification and implementation of the appropriate bioinformatics pipelines. Here, we highlight the different ongoing projects that we have been working on, as well as details on the various methods we use to characterize the microbiome and metagenome of these complex samples. In particular, we present data of a novel multienzyme extraction protocol that we developed, called Polyzyme or MetaPolyZyme. Presently, the XMP is characterizing sample sites around the world with the intent of discovering new species, genes, and gene clusters. Once a project site is complete, the resulting data will be publically available. Sites include Lake Hillier in Western Australia, the "Door to Hell" crater in Turkmenistan, deep ocean brine lakes of the Gulf of Mexico, deep ocean sediments from Greenland, permafrost tunnels in Alaska, ancient microbial biofilms from Antarctica, Blue Lagoon Iceland, Ethiopian toxic hot springs, and the acidic hypersaline ponds in Western Australia.