Zika virus (ZIKV) is a flavivirus that has recently been associated with an increased incidence of neonatal microcephaly and other neurological disorders. The virus is primarily transmitted by mosquito bite, although other routes of infection have been implicated in some cases. The Aedes aegypti mosquito is considered to be the main vector to humans worldwide; however, there is evidence that other mosquito species, including Culex quinquefasciatus, transmit the virus. To test the potential of Cx. quinquefasciatus to transmit ZIKV, we experimentally compared the vector competence of laboratory-reared Ae. aegypti and Cx. quinquefasciatus. Interestingly, we were able to detect the presence of ZIKV in the midgut, salivary glands and saliva of artificially fed Cx. quinquefasciatus. In addition, we collected ZIKV-infected Cx. quinquefasciatus from urban areas with high microcephaly incidence in Recife, Brazil. Corroborating our experimental data from artificially fed mosquitoes, ZIKV was isolated from field-caught Cx. quinquefasciatus, and its genome was partially sequenced. Collectively, these findings indicate that there may be a wider range of ZIKV vectors than anticipated.

The rapid spread of Zika virus (ZIKV) represents a global public health problem, especially in areas that harbor several mosquito species responsible for virus transmission, such as Brazil. In these areas, improvement in mosquito control needs to be a top priority, but mosquito viral surveillance occurs inefficiently in ZIKV-endemic countries. Quantitative reverse transcription PCR (qRT-PCR) is the gold standard for molecular diagnostic of ZIKV in both human and mosquito samples. However, the technique presents high cost and limitations for Point-of-care (POC) diagnostics, which hampers its application for a large number of samples in entomological surveillance programs. Here, we developed and validated a one-step reverse transcription LAMP (RT-LAMP) platform for detection of ZIKV in mosquito samples. The RT-LAMP assay was highly specific for ZIKV and up to 10,000 times more sensitive than qRT-PCR. Assay validation was performed using 60 samples from Aedes aegypti and Culex quinquefasciatus mosquitoes collected in Pernambuco State, Brazil, which is at the epicenter of the Zika epidemic. The RT-LAMP had a sensitivity of 100%, specificity of 91.18%, and overall accuracy of 95.24%. Thus, our POC diagnostics is a powerful and inexpensive tool to monitor ZIKV in mosquito populations and will allow developing countries to establish better control strategies for this devastating pathogen.

These authors contributed equally to this work. Abstract:Zika virus (ZIKV) is a flavivirus that has recently been associated with increased incidence of neonatal microcephaly and other neurological disorders. The virus is primarily transmitted by mosquito bite, although other routes of infection have been implicated in some cases. The Aedes aegypti mosquito is considered to be the main vector to humans worldwide, but there is evidence of other mosquito species, including Culex quinquefasciatus, playing a role in the Brazilian outbreak. To test this hypothesis, we experimentally compared the vectorial competence of laboratory-reared A. aegypti and C. quinquefasciatus. We found ZIKV in the not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/073197 doi: bioRxiv preprint first posted online Sep. 2, 2016; 2 midgut, salivary glands, and saliva of artificially fed C. quinquefasciatus. Additionally, we collected ZIKV-infected C. quinquefasciatus from urban areas of high microcephaly incidence in Recife, Brazil. Take into account; these findings indicate that there may be a wider range of vectors for ZIKV than anticipated.Keywords: Zika, microcephaly, Culex, Aedes, vectorial competence, vector control.Zika is classically considered a mild disease whose symptoms include fever, joint pain, rash and, in some cases, conjunctivitis (1). However, the Zika outbreak in Brazil has been associated with an increased incidence of neonatal microcephaly and neurological disorders (2, 3). Zika virus (ZIKV) is a poorly known, small, enveloped RNA virus with ssRNA (+) belonging to the Family Flaviviridae. It was first isolated in April 1947 from a rhesus monkey and in January 1948 from the mosquito species Aedes africanus (4). Since then, several ZIKV strains have been isolated from many samples, mostly mosquitoes, including species from the genera Aedes, Mansonia, Anopheles and Culex (5).The first known Zika epidemic in an urban environment occurred in Micronesia in 2007, with approximately 73% of the human population on Yap island becoming infected (6).Intriguingly, although many Aedes mosquitoes were collected in the field and evaluated for virus detection, no samples were found to be positive for ZIKV (6). Additionally, it is important to highlight that Aedes aegypti (A. aegypti) is absent from most islands in the Micronesia archipelago and is very rare on the islands where it is present (6, 7).There is a global consensus among scientists and health agencies that Aedes spp. are the main ZIKV vector in urban areas (WHO, 2016). This is in part because vector competence experiments for ZIKV have been conducted exclusively for species of this genus, mainly A.aegypti (8, 9). Previous laboratory studies (8, 10) suggested that A. aegypti is a ZIKV vector. not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was . http://dx.doi...

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.

In low-resource settings, resilience to infectious disease outbreaks can be hindered by limited access to diagnostic tests. Here we report the results of double-blinded studies of the performance of paper-based diagnostic tests for the Zika and chikungunya viruses in a field setting in Latin America. The tests involved a cell-free expression system relying on isothermal amplification and toehold-switch reactions, a purpose-built portable reader and onboard software for computer vision-enabled image analysis. In patients suspected of infection, the accuracies and sensitivities of the tests for the Zika and chikungunya viruses were, respectively, 98.5% (95% confidence interval, 96.2–99.6%, 268 serum samples) and 98.5% (95% confidence interval, 91.7–100%, 65 serum samples) and approximately 2 aM and 5 fM (both concentrations are within clinically relevant ranges). The analytical specificities and sensitivities of the tests for cultured samples of the viruses were equivalent to those of the real-time quantitative PCR. Cell-free synthetic biology tools and companion hardware can provide de-centralized, high-capacity and low-cost diagnostics for use in low-resource settings.