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Alcantara, L. C. J.

Publications and source records attributed to Alcantara, L. C. J..

10 recordsLinked to original sources
bioRxiv2025

Short-Report: First whole-genome evidence of dengue virus in field-caught mosquitoes from southern Brazil

Dengue virus (DENV) is a major global health threat whose expansion into temperate regions has been facilitated by climate change and vector adaptation. Despite recurrent epidemics in Brazil, genomic surveillance in mosquitoes remains limited, particularly in the South. To address this gap, we implemented a novel urban mosquito-trapping strategy optimized for low-density and peri-domestic environments in Porto Alegre, Rio Grande do Sul. Between April and July 2023, were collected 4,768 Aedes aegypti samples across 16 neighborhoods, generating 2,022 pools. Among these, 41 pools tested positive for DENV, of which 33 pools exhibited RNA integrity suitable for sequencing. Whole-genome sequencing revealed 33 DENV-positive pools, including 29 DENV-1 (Genotype V) and 4 DENV-2 (Genotype II). Two pools contained both serotypes, highlighting the risk of sequential infections in humans. Phylogenetic analyses indicated sustained local transmission alongside multiple introductions, while recurrent mutations, particularly in NS1, NS2A, and NS5, suggested ongoing viral adaptation. These findings represent the first vector-based genomic data for dengue in southern Brazil and demonstrate the utility of mosquito genomics for early outbreak detection, serotype monitoring, and preparedness in emerging transmission zones. Author SummaryDengue virus (DENV) continues to expand into new regions, driven by climate change and mosquito adaptation. In Brazil, dengue epidemics are recurrent, but genomic surveillance of mosquitoes is still scarce, particularly in the southern states. To fill this gap, we implemented an urban mosquito-trapping strategy designed for low-density and peri-domestic environments in Porto Alegre, Rio Grande do Sul. From April to July 2023, we collected 4,768 Aedes aegypti samples across 16 neighborhoods, generating 2,022 pools. Among these, 41 pools were positive for DENV, of which 33 pools exhibited RNA integrity suitable for sequencing, mainly DENV-1 (Genotype V) and DENV-2 (Genotype II), with two pools showing co-circulation of both serotypes, raising concern for sequential infections in humans. Phylogenetic analysis revealed sustained local transmission combined with multiple virus introductions, and mutations in NS1, NS2A, and NS5 suggested ongoing viral adaptation. Our findings provide the first mosquito-based genomic data for dengue in southern Brazil and highlight how mosquito genomics can strengthen early outbreak detection, serotype monitoring, and epidemic preparedness.

molecular biology↗
bioRxiv2025

Unraveling Dengue Serotype 3 Transmission in Brazil: Evidence for Multiple Introductions of the 3III_B.3.2 Lineage

Dengue, caused by DENV 1-4, remains a global public health concern, with Brazil experiencing some of the largest epidemics. The reemergence of DENV-3 in Brazil between 2023 and 2024 has raised concerns about new outbreaks due to the absence of sustained circulation of this serotype in recent years. This study investigates the dynamics of DENV-3 in Brazil, focusing on the spread of the 3III_B.3.2 lineage within genotype 3III and its introduction routes. We analyzed 1,536 DENV-3 genomes, all classified as genotype 3III, the dominant DENV-3 genotype in Brazil since 2001. Phylogenetic analysis identified the 3III_B.3.2 lineage in all recent Brazilian cases, with detections also reported in Central America, the United States, and Europe. At least six independent introduction events of this lineage into Brazil were identified, with the Caribbean region and Costa Rica as the primary sources. The earliest introduction likely occurred in late 2022 in Roraima, followed by introductions in Sao Paulo, Minas Gerais, and Para. While one instance of interstate transmission was detected -- from Sao Paulo to Minas Gerais -- our findings indicate that external introductions, rather than domestic spread, were the primary drivers of DENV-3 circulation during this period. These results underscore the importance of continued genomic surveillance and coordinated public health strategies to monitor and mitigate future outbreaks.

bioinformatics↗
bioRxiv2021

Machine learning models exploring characteristic single-nucleotide signatures in Yellow Fever Virus

Yellow fever virus (YFV) is the agent of the most severe mosquito-borne disease in the tropics. Recently, Brazil suffered major YFV outbreaks with a high fatality rate affecting areas where the virus has not been reported for decades, consisting of urban areas where a large number of unvaccinated people live. We developed a machine learning framework combining three different algorithms (XGBoost, random forest and regularized logistic regression). This method was applied to 56 YFV sequences from human infections and 27 from non-human primate (NHPs) infections to investigate the presence of genetic signatures possibly related to disease severity (in human related sequences) and differences in the PCR cycle threshold (Ct) values (in NHP related sequences). Our analyses reveal four non-synonymous single nucleotide variations (SNVs) on sequences from human infections, in proteins NS3 (E614D), NS4a (I69V), NS5 (R727G, V643A) and six non-synonymous SNVs on NHP sequences, in proteins E (L385F), NS1 (A171V), NS3 (I184V) and NS5 (N11S, I374V, E641D). We performed comparative protein structural analysis on these SNVs, describing possible impacts on protein function. Despite the fact that the dataset is limited in size and that this study does not consider virus-host interactions, our work highlights the use of machine learning as a versatile and fast initial approach to genomic data exploration. ImportanceYellow fever is responsible for 29-60 thousand deaths annually in South America and Africa and is the most severe mosquito-borne disease in the tropics. Given the range of clinical outcomes and the availability of YFV genomic data, the use of machine learning analysis promises to be a powerful tool in the investigation of genetic signatures that could impact disease severity and its potential of being reintroduced in an urban transmission cycle. This can assist in the search for biomarkers of severity as well as help elucidating variations in hosts Ct value. This work aims to propose a relatively fast and inexpensive computational analysis framework, which can be used as a real-time, innitial strategy associated with genomic surveillance to identify a set of single nucleotide variants putatively related to biological and clinical characteristics being observed.

microbiology↗
bioRxiv2021

Chikungunya virus ECSA lineage reintroduction in the northeasternmost region of Brazil

The Northeast region of Brazil registered the second highest incidence proportion of chikungunya fever in 2019. In that year an outbreak consisting of patients presented with febrile disease associated with joint pain were reported by the public primary health care service in the city of Natal, Rio Grande do Norte state, in March 2019. At first, the aetiological agent of the disease was undetermined. Since much is still unknown about chikungunya virus (CHIKV) genomic diversity and evolutionary history in this northeasternmost state, we used a combination of portable whole genome sequencing, molecular clock, and epidemiological analyses that revealed the re-introduction of the CHIKV East-Central-South-African (ECSA) lineage into Rio Grande do Norte. We estimated CHIKV ECSA lineage was first introduced into Rio Grande do Norte in early June 2014, while the 2019 outbreak clade diverged around April 2018 during a period of increased chikungunya incidence in the Southeast region, which might have acted as a source of virus dispersion towards the Northeast region. Together, these results confirm the ECSA lineage continues to spread across the country through interregional importation events likely mediated by human mobility. HIGHLIGHTSCHIKV ECSA lineage introduction into Rio Grande do Norte state, Northeast Brazil, was estimated to early June 2014 At least two CHIKV importation events occurred in Rio Grande do Norte state, Brazil The 2019 chikungunya outbreak in Rio Grande do Norte was likely caused by a second event of CHIKV introduction imported from Rio de Janeiro state.

genomics↗
bioRxiv2021

West Nile virus detection in horses in three Brazilian states.

We report genetic evidence of WNV circulation from southern and northeastern Brazilian states isolated from equine red blood cells. In the northeastern state the tenth human case was also detected, presenting neuroinvasive disease compatible with WNV infection. Our analyses demonstrate that much is still unknown on the virus local epidemiology. We advocate for a shift to active surveillance, to ensure adequate control for future epidemics with spill-over potential to humans.

genomics↗
bioRxiv2020

Whole Genome Sequencing of SARS-CoV-2: Adapting Illumina Protocols for Quick and Accurate Outbreak Investigation During a Pandemic

The COVID-19 pandemic spread very fast around the world. A few days after the first detected case in South Africa, an infection started a large hospital outbreak in Durban, KwaZulu-Natal. Phylogenetic analysis of SARS-CoV-2 genomes can be used to trace the path of transmission within a hospital. It can also identify the source of the outbreak and provide lessons to improve infection prevention and control strategies. In this manuscript, we outline the obstacles we encountered in order to genotype SARS-CoV-2 in real-time during an urgent outbreak investigation. In this process, we encountered problems with the length of the original genotyping protocol, reagent stockout and sample degradation and storage. However, we managed to set up three different library preparation methods for sequencing in Illumina. We also managed to decrease the hands on library preparation time from twelve to three hours, which allowed us to complete the outbreak investigation in just a few weeks. We also fine-tuned a simple bioinformatics workflow for the assembly of high-quality genomes in real-time. In order to allow other laboratories to learn from our experience, we released all of the library preparation and bioinformatics protocols publicly and distributed them to other laboratories of the South African Network for Genomics Surveillance (SANGS) consortium.

genomics↗
bioRxiv2020

Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes

SummaryGenome Detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present The Genome Detective Coronavirus Typing Tool that can accurately identify novel coronavirus (2019-nCoV) sequences isolated in China and around the world. The tool can accept up to 2,000 sequences per submission and the analysis of a new whole genome sequence will take approximately one minute. The tool has been tested and validated with hundreds of whole genomes from ten coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for 2019-nCoV. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines. AvailabilityAvailable online: https://www.genomedetective.com/app/typingtool/cov * Contactkoen@emweb.be and deoliveira@ukzn.ac.za Supplementary informationSupplementary data is available online.

bioinformatics↗
bioRxiv2019

Early identification of dengue virus lineage replacement in Brazil using portable genomic surveillance

Over 400 million people are estimated to be at risk of acquiring dengue virus (DENV). Despite efforts to mitigate the impact of DENV epidemics, the virus remains a public health problem in the Americas: more than one million DENV cases were reported in the continent between January and July 2019 DENV was first detected in Brazil in 1982, and Brazil has reported 88% (1,127,244 cases) of all DENV cases in the Americas during 2019 to date. Sao Paulo state in the southeast of Brazil has reported nearly half of all DENV infections in the country. Here we characterised the genetic diversity of DENV strains circulating in Sao Paulo state in 2019, at the epicentre of the ongoing DENV epidemic. Using portable nanopore sequencing we generated 20 new DENV genome sequences from viremic patients with suspected dengue infection residing in two of the most-affected municipalities, Araraquara and Sao Jose do Rio Preto. We conducted a comprehensive phylogenetic analysis with 1,630 global DENV strains to better understand the evolutionary history of the DENV lineages that currently circulate in the region. The new outbreak strains were classified as DENV2 genotype III (American/Asian genotype). Notably, phylogenetic analysis indicated that the 2019 outbreak is the result of a novel DENV lineage that was recently introduced to Brazil from the Caribbean region. Our genetic analysis further indicates that the introduction and onwards spread of the outbreak lineage (named here DENV2-III BR-4) indicates a new DENV2 lineage replacement in Brazil. Dating phylogeographic analysis suggests that DENV2-III BR-4 was introduced to Brazil in or around early 2014, possibly from the Caribbean region. Our study describes the early detection of a newly introduced and rapidly-expanding DENV2 virus lineage in Brazil.\n\nAuthor SummaryDengue is the most important mosquito-borne viral disease of humans. The disease is caused by the dengue virus (DENV) that is classified within genus Flavivirus. DENV infections are caused by 4 serotypes (DENV 1-4) that are genetically related but antigenically distinct. Dengue infection results in a variety of symptoms that range from mild fever to dengue hemorrhagic fever and/or dengue shock syndrome (DHF/DSS). Clinical outcomes are associated with different types of infection, viral serotypes, genotypes, lineages, and host genetic factors. As a re-emerging infectious disease, DENV has become a serious threat to public health in the Americas, and particularly in Brazil, where it was introduced in the 1980s and became well established due to the country-wide re-infestation of the Aedes aegypti mosquito vector species. During the first six months of 2019, 1,282,183 DENV cases were reported in the Americas, with Brazil reporting a staggering 1,127,244 (88%) of all dengue cases in the continent. To date, no information exists on the genetic composition of the DENV lineage or lineages causing the current epidemic. Here we use portable sequencing to rapidly generate virus genome data from cases occurring in two different are severely-affected municipalities in Sao Paulo state, Brazil. We find that the 2019 dengue outbreak in Brazil is caused by a newly introduced DENV serotype 2 genotype III (Asian/American) that seems to be replacing previously-circulating DENV2 lineages. We discuss the potential implications of our results regarding the current outbreak in the context of previous outbreaks in the same region.

genomics↗
bioRxiv2019

Yellow fever virus spread in Rio de Janeiro and Espirito Santo, 2016-2019: Phylodynamic assessment to improve intervention strategies

The recent re-emergence of yellow fever virus (YFV) in Brazil has raised serious concerns due to the virus rapid dissemination in the southeastern region. To better understand YFV genetic diversity and dynamics during the recent outbreak in southeastern Brazil we generated 18 complete and near-complete genomes from the peak of the epidemic curve from non-human primates (NHPs) and human infected cases across Espirito Santo and Rio de Janeiro states. Genomic sequencing of 18 YFV genomes revealed the timing, source and likely routes of yellow fever virus transmission and dispersion during the one of the largest outbreaks ever registered in Brazil. We showed that the recent YFV epidemic spillover southwards several times from Minas Gerais to Espirito Santo and Rio de Janeiro states in 2016 to 2019. The quick production and analysis of data from portable sequencing could identify the corridor of spread of YFV. These findings reinforce that real-time and continued genomic surveillance strategies can assist in the monitoring and public health responses of arbovirus epidemics.\n\nIMPORTANCEArbovirus infections in Brazil including Yellow Fever, Dengue, Zika and Chikungunya result in considerable morbidity and mortality and are pressing public health concerns. However, our understanding of these outbreaks is hampered by limited availability of real time genomic data. In this study, we investigated the genetic diversity and spatial distribution of YFV during the current outbreak in southeastern Brazil. To gain insights into the routes of YFV introduction and dispersion, we tracked the virus by sequencing YFV genomes sampled from non-human primates and infected patients from the southeastern region. Our study provides an understanding of how YFV initiates transmission in new Brazilian regions and illustrates that near-real time genomics in the field can augment traditional approaches to infectious disease surveillance and control.

microbiology↗