After the Zika virus (ZIKV) epidemic in the Americas in 2016, both Zika and dengue incidence declined to record lows in many countries in 2017–2018, but in 2019 dengue resurged in Brazil, causing ~2.1 million cases. In this study we use epidemiological, climatological and genomic data to investigate dengue dynamics in recent years in Brazil. First, we estimate dengue virus force of infection (FOI) and model mosquito-borne transmission suitability since the early 2000s. Our estimates reveal that DENV transmission was low in 2017–2018, despite conditions being suitable for viral spread. Our study also shows a marked decline in dengue susceptibility between 2002 and 2019, which could explain the synchronous decline of dengue in the country, partially as a result of protective immunity from prior ZIKV and/or DENV infections. Furthermore, we performed phylogeographic analyses using 69 newly sequenced genomes of dengue virus serotype 1 and 2 from Brazil, and found that the outbreaks in 2018–2019 were caused by local DENV lineages that persisted for 5–10 years, circulating cryptically before and after the Zika epidemic. We hypothesize that DENV lineages may circulate at low transmission levels for many years, until local conditions are suitable for higher transmission, when they cause major outbreaks.

Wolbachia is an endosymbiotic bacterium that naturally infects several arthropods and nematode species. Wolbachia gained particular attention due to its impact on their host fitness and the capacity of specific Wolbachia strains in reducing pathogen vector and agricultural pest populations and pathogens transmission. Despite the success of mosquito/pathogen control programs using Wolbachia-infected mosquito release, little is known about the abundance and distribution of Wolbachia in most mosquito species, a crucial knowledge for planning and deployment of mosquito control programs and that can further improve our basic biology understanding of Wolbachia and host relationships. In this systematic review, Wolbachia was detected in only 30% of the mosquito species investigated. Fourteen percent of the species were considered positive by some studies and negative by others in different geographical regions, suggesting a variable infection rate and/or limitations of the Wolbachia detection methods employed. Eighty-three percent of the studies screened Wolbachia with only one technique. Our findings highlight that the assessment of Wolbachia using a single approach limited the inference of true Wolbachia infection in most of the studied species and that researchers should carefully choose complementary methodologies and consider different Wolbachia-mosquito population dynamics that may be a source of bias to ascertain the correct infectious status of the host species.

The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis.

Multiple epicenters of the SARS-CoV-2 pandemic have emerged since the first pneumonia cases in Wuhan, China, such as Italy, USA, and Brazil. Brazil is the third-most affected country worldwide, but genomic sequences of SARS-CoV-2 strains are mostly restricted to states from the Southeast region. Pernambuco state, located in the Northeast region, is the sixth most affected Brazilian state, but very few genomic sequences from the strains circulating in this region are available. We sequenced 101 strains of SARS-CoV-2 from patients presenting Covid-19 symptoms that reside in Pernambuco. Phylogenetic reconstructions revealed that all genomes belong to the B lineage and most of the samples (88%) were classified as lineage B.1.1. We detected multiple viral introductions from abroad (likely from Europe) as well as six local B.1.1 clades composed by Pernambuco only strains. Local clades comprise sequences from the capital city (Recife) and other country-side cities, corroborating the community spread between different municipalities of the state. These findings demonstrate that different from Southeastern Brazilian states where the epidemics were majorly driven by one dominant lineage (B.1.1.28 or B.1.1.33), the early epidemic phase at the Pernambuco state was driven by multiple B.1.1 lineages seeded through both national and international traveling.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has infected almost 200 million people worldwide by July 2021 and the pandemic has been characterized by infection waves of viral lineages showing distinct fitness profiles. The simultaneous infection of a single individual by two distinct SARS-CoV-2 lineages may impact COVID-19 disease progression and provides a window of opportunity for viral recombination and the emergence of new lineages with differential phenotype. Several hundred SARS-CoV-2 lineages are currently well phylogenetically defined, but two main factors have precluded major coinfection/codetection and recombination analysis thus far: (i) the low diversity of SARS-CoV-2 lineages during the first year of the pandemic, which limited the identification of lineage defining mutations necessary to distinguish coinfecting/recombining viral lineages; and the (ii) limited availability of raw sequencing data where abundance and distribution of intrasample/intrahost variability can be accessed. Here, we assembled a large sequencing dataset from Brazilian samples covering a period of 18 May 2020 to 30 April 2021 and probed it for unexpected patterns of high intrasample/intrahost variability. This approach enabled us to detect nine cases of SARS-CoV-2 coinfection with well characterized lineage-defining mutations, representing 0.61 % of all samples investigated. In addition, we matched these SARS-CoV-2 coinfections with spatio-temporal epidemiological data confirming its plausibility with the cocirculating lineages at the timeframe investigated. Our data suggests that coinfection with distinct SARS-CoV-2 lineages is a rare phenomenon, although it is certainly a lower bound estimate considering the difficulty to detect coinfections with very similar SARS-CoV-2 lineages and the low number of samples sequenced from the total number of infections.

Horizontal Transfer (HT) of genetic material between species is a common phenomenon among Bacteria and Archaea species and several databases are available for information retrieval and data mining. However, little attention has been given to this phenomenon among eukaryotic species mainly due to the lower proportion of these events. In the last years, a vertiginous amount of new HT events involving eukaryotic species was reported in the literature, highlighting the need of a common repository to keep the scientific community up to date and describe overall trends. Recently, we published the first HT database focused on HT of transposable elements among eukaryotes: the Horizontal Transposon Transfer DataBase: Database URL: (http://lpa.saogabriel.unipampa.edu.br: 8080/httdatabase/). Here, we present new features and updates of this unique database: (i) its expansion to include virus-host exchange of genetic material, which we called Horizontal Virus Transfer (HVT) and (ii) the availability of a web server for HT detection, where we implemented the online version of vertical and horizontal inheritance consistence analysis (VHICA), an R package developed for HT detection. These improvements will help researchers to navigate through known HVT cases, take data-informed decision and export figures based on keywords searches. Moreover, the availability of the VHICA as an online tool will make this software easily reachable even for researchers with no or little computation knowledge as well as foster our capability to detect new HT events in a wide variety of taxa. Database URL: http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase/